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Investigation of Expansive Soil for Design of
Light Residential Footings in Melbourne
Aruna Nishantha Karunarathne
Submitted for the Degree of Doctor of Philosophy, Ph.D.
Faculty of Engineering and Industrial Sciences
Swinburne University of Technology
2016
Abstract
Expansive soils are found in most Australian states. In fact, it is estimated that 20% of
surface soils in Australia are categorized as moderate to highly expansive clays.
Quaternary basalt clays generally exhibit expansive characteristics and are commonly
found in the Western part of Victoria. These expansive soils undergo heave and
settlement due to moisture changes. Such ground movements are capable of creating
differential movement in footings which results in cracks and damage to light structures.
Recently, it has been reported that more than 5000 houses experienced damage in
Victoria due to changes in soil moisture caused by extreme climate events. Since the
climate condition is the natural cause of soil moisture changes, it must be considered in
the design stage of relevant structures.
This study is part of a comprehensive research programme aimed at enhancing
knowledge about expansive soil behaviour and mitigating damages to residential
structures due to ground movement caused by climate influences. This particular
dissertation focused on estimating soil moisture changes in response to climate
conditions and its consequences. The Australian standard (AS2870) considers the effect
of climate on footing design in terms of Thornthwaite Moisture Index (TMI). It was
found in this study that there are several methods to calculate TMI, which produce
different values for a particular climate condition and hence result in different footing
designs. Furthermore, TMI depends mostly on rainfall and may not be adequate to
consider the variations in soil moisture condition particularly when the TMI values are
based on averaging of long periods.
Soil moisture changes and subsequent ground movement were monitored in a field site
established in Braybrook in Melbourne, which has typical basalt clay soils. The
collected data shows that soil moisture contents follow the rainfall pattern and a
subsequent ground movement, with seasonal variation. Field monitoring over a two year
period revealed that the changes in soil moisture were recorded mainly in top soils
which contributed to the ground movement.
A comprehensive laboratory investigation was performed to characterise the basic
properties of Braybrook soils. These properties suggested that the site has a consistent
profile of highly expansive clay. Further investigations were performed to obtain
specific expansive properties such as mineral composition, soil suction changes and
hydraulic conductivity. These results confirmed the presence of expansive clay soils in
Braybrook. Moreover, a series of shrink swell tests were performed using undisturbed
soils at various in situ moisture contents. These test results indicated the dependency of
shrink swell index on in situ moisture content, which is in contrast to the specifications
outlined in the Australian standard AS1289. The outcome of the laboratory
investigation led to publication of a comprehensive data set that benefits both
practitioners and researchers.
The soil properties collected from the Braybrook site were then used to develop a finite
element model to predict the soil moisture changes in response to climate conditions.
The climate data were obtained from a nearby weather station and the model was
validated against the monitoring data over a two-year period. The validated model was
used to investigate the soil moisture changes due to long-term climate conditions,
including extreme events such as the millennium drought and the subsequent above
average rainfall period in Melbourne. In addition, the soil moisture predictions taken
from this model were fed into another model, developed as part of this comprehensive
research programme, to obtain the ground movement. The results of ground movements
obtained from these models were then compared with the outcomes from the current
Australian standard (AS2870). The results from the model suggest that considerable
additional ground movement has occurred due to the millennium drought, which was
not captured by the AS2870. Furthermore, the model predictions were used to consider
the mound shapes underneath flexible cover slabs placed at different times of the recent
years. Finally, available climate predictions were used to examine the possible future
changes in soil moisture and ground movement.
This research provides a versatile prediction tool for soil moisture changes due to
climate conditions and, therefore, will greatly assist the footing design procedure given
in AS2870. The model can be used to observe future changes of soil moisture within the
design life of a structure using various climate prediction scenarios. Hence, it is an
invaluable tool for designing residential structures that can withstand different severities
of climate conditions as well as uphold the homeowner’s expectations.
Acknowledgement
I am deeply indebted to my principal supervisor, Professor Emad Gad for his endless
guidance, support and constructive criticisms. Working with Professor Emad is the most
pleasurable experience I had in my life. In addition to his assistance in my research
study, the discussions with Professor Emad enhanced my attitude towards success and
personal knowledge.
I also thankful to my second supervisor, Professor John Wilson, for his guidance and
support. I was very lucky to have the luxury of five supervisors including three co-
supervisors from various backgrounds. I wish to express heartfelt appreciation to co-
supervisors Dr. Mahdi Miri Disfani, Dr. Siva Sivanerupan and Dr. Pathmanathan
Rajeev. The guidance in laboratory work from Dr. Mahdi was really important. If I had
not received the invaluable assistance from Dr. Siva, I would not have been able to
initiate field monitoring in the very early stage of this research study. Dr. Rajeevs’s
assistance in finite element model development has been significant. I wish to express
sincere appreciation to all three co-supervisors for their enormous support.
I would like to acknowledge the guidance I had from Mr. Dominic Lopes. He has been
a mentor for our research group. The assistance through his vast knowledge in
expansive soil area has laid the sound foundation for my research study. I also thank Dr.
Robert Evans for giving me the opportunity to undertake tutoring in Geotechnical
Engineering subject, which enhanced my knowledge about footing design.
My warm thanks are due to the administrative and technical staff at the Department of
Civil and Construction Engineering of Swinburne University of Technology. Special
appreciation must be given to Senior Technical Officer, Alec Papanicolaou, in the
workshop for his help in modifications of testing devices and organising various
experimental setups. In addition, PC Support Officer Andrew Zammit in Information
Technology Services kindly provided assistance in various occasions.
I would like to acknowledge Australia Research Council (ARC), the main contributor of
this research project from the ARC Linkage Grant (LP100200306). I gratefully
acknowledge the financial and technical support provided by the collaborating
organizations, namely; Victorian Building Authority (VBA), Victorian Office of
Housing (OoH), Foundation and Footings Society of Victoria (FFSV), Association of
Consulting Structural Engineers Victoria (ACSEV) and Housing Engineering Design
and Research Association (HEDRA). I would like to recognise the invaluable feedback
from adversary panel members who represented the above-mentioned organizations. I
wish to express my deep and sincere gratitude to my colleagues of the research group;
Jenny Boyer and Deepti Wagle for their support during the study.
Finally, I owe my loving thanks to everyone in my family. Special thanks should be
given to my brother who has been looking after my parents while I was far from them.
This thesis would not have been possible without their love, encouragement and
understanding.
Declaration
I hereby declare that this thesis contains no material which has been accepted for the
award of any other degree or diploma in any university or institution. To the best of my
knowledge and belief, this thesis contains no material previously published or written
by another person, except when due reference is made in the text of the thesis.
Aruna Nishantha Karunarathne
August 2016
Preface
This dissertation is produced as part of a comprehensive research study aimed to assist
in mitigating damage to residential structures due to ground movement. The study
involved three PhD students and several resource persons directing at a number of
engagements of the research problem. The author of this dissertation has been
responsible for the geotechnical section of the study which indeed focused on
estimation of soil moisture and ground movement induced by climate conditions. This
dissertation is original, unpublished and independent work by the author, Aruna
Nishantha Karunarathne.
Following peer reviewed publications were produced from various outcomes of the
research and they are based on certain sections of thesis chapters.
Journal papers
KARUNARATHNE, A. M. A. N., SIVANERUPAN, S., GAD, E. F., DISFANI,
M. M., RAJEEV, P., WILSON, J. L. & LI, J. 2014. Field and laboratory
investigation of an expansive soil site in Melbourne. Australian Geomechanics,
49, 85-93.
KARUNARATHNE, A. M. A. N., GAD, E. F., DISFANI, M. M.,
SIVANERUPAN, S. & WILSON, J. L. 2016. Review of Calculation Procedures
of Thornthwaite Moisture Index and its Impact on Footing Design. Australian
Geomechanics, 51, 85-95.
FARDIPOUR, M., GAD, E., SIVAGNANASUNDRAM, S., RAJEEV, P.,
KARUNARATHNE, A. & WILSON, J. 2016. Interaction analysis of waffle
slabs supporting houses on expansive soil. Innovative Infrastructure Solutions,
1, 1-10.
Conference papers
KARUNARATHNE, A. M. A. N., GAD, E. F., SIVANERUPAN, S. &
WILSON, J. L. Review of Residential Footing Design on Expansive Soil in
Australia. In: SAMALI, B., ATTARD, M. M. & SONG, C., eds. 22nd
Australasian Conference on the Mechanics of Structures and Materials, 11-14
December 2012 Sydney, NSW. Taylor & Francis Group, 575-579
KARUNARATHNE, A. M. A. N., SIVANERUPAN, S., GAD, E. F., DISFANI,
M. M., WILSON, J. L. & LI, J. Field monitoring of seasonal ground movements
in expansive soils in Melbourne. In: KHALILI, N., RUSSELL, A. &
KHOSHGHALB, A., eds. 'UNSAT 2014', Unsaturated Soils: Research and
Applications - the 6th International Conference on Unsaturated Soils, 2-4July
2014 Sydney, NSW. Taylor & Francis Group, 1359-1365.
i
Table of contents
1. Introduction ............................................................................................................... 1
1.1 Background ........................................................................................................ 1
1.2 Research objectives ............................................................................................ 8
1.3 Overview of the research methodology .............................................................. 9
1.4 Perceived specific contributions of the research .............................................. 10
1.5 Outline of the thesis .......................................................................................... 11
2. Literature review ..................................................................................................... 13
2.1 Introduction ...................................................................................................... 13
2.2 Expansive behaviour of soil ............................................................................. 13
2.2.1 Overview ................................................................................................... 13
2.2.2 Mineral composition of expansive clay .................................................... 14
2.2.3 Identification of shrink - swell potential based on soil properties ............ 17
2.2.4 Effects of moisture changes on soil properties ......................................... 20
2.2.5 Reasons for soil moisture change .............................................................. 27
2.3 Investigations on expansive soil problems ....................................................... 29
2.3.1 Expansive soils - a global issue ................................................................. 29
2.3.2 Field monitoring systems in expansive soil research ................................ 30
2.3.3 Previous expansive soil research investigations in Australia .................... 35
2.3.4 Forensic investigations .............................................................................. 42
2.4 AS2870 footing design procedure .................................................................... 44
2.4.1 Characteristic ground movement of expansive soil .................................. 46
2.4.2 Factors affecting ys calculation ................................................................. 49
2.5 Limitations of soil moisture predictions ........................................................... 57
2.5.1 Effectiveness of AS2870 design procedure with changes in TMI ............ 57
2.5.2 Standard design outcome and home owner’s expectations ....................... 58
ii
2.6 importance of a robust method of estimating soil moisture changes ............... 59
2.7 Summary .......................................................................................................... 59
3. Effects of climate on footing design ....................................................................... 61
3.1 Influence of climate conditions on soil moisture content ................................. 61
3.2 Climate consideration in AS2870 ..................................................................... 65
3.3 Thornthwaite Moisture Index (TMI) ................................................................ 66
3.3.1 Calculation of TMI .................................................................................... 67
3.3.2 Definitions and Assumptions .................................................................... 67
3.3.3 Different methods of TMI calculation ...................................................... 71
3.3.4 Comparison of TMI results from different methods ................................. 76
3.3.5 Sensitivity of climate parameters of TMI calculation ............................... 77
3.4 Correlation of TMI and expansive soil behaviour ............................................ 81
3.5 Issues of TMI being used in AS2870 ............................................................... 84
3.6 Effect of soil moisture condition on AS2870 design parameters ..................... 93
3.6.1 Variation of Iss with moisture content ....................................................... 93
3.6.2 Effect of Iss changes on site classification ................................................. 97
3.7 Summary .......................................................................................................... 98
4. Field and laboratory investigations of expansive soil behaviour .......................... 101
4.1 Introduction .................................................................................................... 101
4.2 Site selection criteria ...................................................................................... 101
4.3 Soil classification ........................................................................................... 105
4.3.1 Soil profile ............................................................................................... 106
4.3.2 Atterberg limits and linear shrinkage ...................................................... 107
4.3.3 Particle size distribution and density tests .............................................. 110
4.3.4 Mineral composition of the soil .............................................................. 111
4.4 Site classification according to AS2870 ......................................................... 112
4.4.1 Shrink-swell characteristics of Braybrook soil ....................................... 112
iii
4.4.2 Site classification .................................................................................... 113
4.5 Development of main expansive soil parameters ........................................... 113
4.5.1 Soil Water Characteristic Curve (SWCC)............................................... 114
4.5.2 Hydraulic conductivity function ............................................................. 134
4.6 Summary ........................................................................................................ 142
5. Field instrumentation and data analysis ................................................................ 144
5.1 Introduction .................................................................................................... 144
5.2 Field monitoring system ................................................................................. 144
5.2.1 Overview ................................................................................................. 144
5.2.2 Soil moisture monitoring ........................................................................ 144
5.2.3 Ground movement monitoring ................................................................ 149
5.3 Site layout ....................................................................................................... 152
5.4 Investigation of field monitoring data ............................................................ 153
5.4.1 Soil moisture profiles with time .............................................................. 153
5.4.2 Ground movement monitoring ................................................................ 160
5.5 Summary ........................................................................................................ 167
6. Modelling of moisture changes in expansive soil ................................................. 169
6.1 Introduction .................................................................................................... 169
6.2 Finite element modelling tool selection ......................................................... 169
6.3 Modelling of soil moisture movement using Vadose/w ................................. 172
6.4 Soil parameters ............................................................................................... 176
6.4.1 Soil Water Characteristic Curve (SWCC)............................................... 176
6.4.2 Hydraulic conductivity function ............................................................. 177
6.4.3 Thermal properties of soil ....................................................................... 177
6.5 Climate data .................................................................................................... 180
6.6 Vegetation influence ....................................................................................... 182
6.7 Development of one dimensional soil column ............................................... 185
iv
6.7.1 Selection of soil layers ............................................................................ 185
6.8 Calibration of 1D soil model against measured data ...................................... 187
6.9 Development of two dimensional soil model ................................................. 195
6.9.1 Selection of model parameters ................................................................ 195
6.9.2 2D model predictions .............................................................................. 201
6.10 Model generalization .................................................................................. 201
6.10.1 Sensitivity of the material model ............................................................ 201
6.10.2 Sensitivity of climate parameters ............................................................ 205
6.11 Summary ..................................................................................................... 211
7. Model applications ................................................................................................ 214
7.1 Overview on model predictions of soil moistures .......................................... 214
7.1.1 Prediction of soil moistures ..................................................................... 215
7.1.2 Prediction of ground movement .............................................................. 219
7.2 Model predictions due to Long term climate conditions ................................ 221
7.2.1 Variation of suction profiles.................................................................... 222
7.2.2 Variation of soil moisture contents ......................................................... 224
7.2.3 Variation of ground movement ............................................................... 225
7.2.4 Comparison of ground movement estimations ....................................... 227
7.2.5 Effects of the depth of bedrock on ground movement ............................ 232
7.2.6 Effects of site drainage condition on ground movement ........................ 235
7.3 Short term climate variations ......................................................................... 237
7.4 Long term climate predictions ........................................................................ 240
7.5 Soil moisture changes beneath cover slabs .................................................... 242
7.6 Changes of the mound profiles ....................................................................... 246
7.6.1 Slab subjected to heave condition (1983 to 1992) .................................. 248
7.6.2 Slab subjected to settlement condition (1992 to 2010) ........................... 251
7.6.3 Comparison of mound shape predictions ................................................ 255
v
7.7 Effect of abnormal moisture conditions ......................................................... 255
7.7.1 Soil slope towards the cover slab ............................................................ 256
7.8 Summary ........................................................................................................ 257
8. Conclusions and future work ................................................................................ 262
8.1 Overview of the study .................................................................................... 262
8.2 Summary of conclusions ................................................................................ 263
8.2.1 Ground movement, climate changes and TMI ........................................ 263
8.2.2 Characterization of typical basaltic clay in Western Melbourne ............ 265
8.2.3 Field monitoring of expansive soil behaviour ......................................... 266
8.2.4 Finite element modelling approach of expansive soil and climate
interaction .............................................................................................................. 267
8.2.5 Prediction of ground movement due to several site conditions and climate
scenarios ................................................................................................................ 268
8.3 Recommendations for future work ................................................................. 271
9. References ............................................................................................................. 274
10. Appendices
A: Hyprop measurements of Braybrook soil
B: WP4C measurements of Braybrook soil
C: Filter paper suction measurements of Braybrook soil
D: Saturated hydraulic conductivity measurements of Braybrook soil
E: Model calibration data
vi
List of figures
Figure 1-1: a) Expansive soil distribution in Australia (Richards et al., 1983); b)
Geographic distribution of population (Statistics, 2012) .................................................. 2
Figure 1-2: Areas of reported damaged houses................................................................. 4
Figure 1-3: Crack in an interior plasterboard lined wall (ACA, 2012) ............................. 4
Figure 1-4: Another example of a crack in an interior plasterboard lined wall (ACA,
2012) ................................................................................................................................. 5
Figure 1-5: Large crack in a plasterboard lined wall (THE-AGE, 2011) ......................... 5
Figure 1-6: A crack in a wall caused by edge lift of footing (Photo taken by the author) 6
Figure 1-7: Crack appeared in a wall caused by edge lift of footing (Photo taken by the
author) ............................................................................................................................... 6
Figure 1-8: Separation of up to 50mm in a wall and the window frame caused by
footing movement (Photo taken by the author) ................................................................ 7
Figure 1-9: An internal wall has been lifted by roof truss due to edge heave of footing
(Photo taken by the author) ............................................................................................... 7
Figure 2-1: Schematic diagrams of the mineral structure of Kaolinite, Illite and
Montmorillonite (Nelson et al., 2015) ............................................................................ 15
Figure 2-2: Conceptual model of sequential crystalline swelling of smectite (Likos,
2004) ............................................................................................................................... 16
Figure 2-3: : Index test correlation – Volume change vs Liquid Limit (Kay, 1990) ...... 19
Figure 2-4: Matric suction variation of a soil column(Nelson et al., 2003) .................... 21
Figure 2-5: Osmotic pressure across the semipermeable membrane (Nelson et al., 2003)
......................................................................................................................................... 22
Figure 2-6: Measured total, matric, and osmotic suctions for Glacial Till from Chao
(2007) after Krahn and Fredlund (1972) ......................................................................... 23
Figure 2-7: Measured soil moisture change with suction for some Adelaide soils
(Mitchell, 1984b)............................................................................................................. 24
Figure 2-8: Typical shape of a SWCC (Fredlund, 2000) ................................................ 25
Figure 2-9: Global distribution of reported expansive soil sites (Nelson et al., 2015) ... 29
Figure 2-10: Schematic depiction of neutron probe deployment(Ward and Wittman,
2009) ............................................................................................................................... 32
Figure 2-11: Spider magnet of the extensometer ............................................................ 34
vii
Figure 2-12: Magnetic extensometer arrangement ......................................................... 35
Figure 2-13: Ground Movement Stations (GMS) used in Swinburne's study in the 1970s'
(Washusen, 1977) ............................................................................................................ 36
Figure 2-14: Hygrometers used in Swinburne's study in the 1970s' (Washusen, 1977) . 37
Figure 2-15: Model 4000 Borehole Rod Extensometers (HMA, 2014).......................... 41
Figure 2-16: Measured and predicted soil moistures at 300 mm depth in Altona North
(Chan, 2014) .................................................................................................................... 41
Figure 2-17: Propagated cracks on wall even after remedial actions were taken (A house
in Taylors Hill) ................................................................................................................ 43
Figure 2-18: Contours showing deviations from assumed planar initial condition (in
mm) of a damaged house in Wyndham Vale measured over a year ............................... 43
Figure 2-19: Typical wet and dry suction profiles in different Australian regions (Walsh
and Cameron, 1997) ........................................................................................................ 45
Figure 2-20: Comparison between measured and predicted free surface movement in
O'Halloran Hill, Adelaide (Mitchell and Avalle, 1984) .................................................. 49
Figure 2-21: Idealized water content profile (Nelson et al., 2001) ................................. 50
Figure 2-22: Theoretical suction profiles given in (Mitchell, 1979) ............................... 51
Figure 2-23: Simplified suction profile and the effect of bedrock and water table on ΔU
and Hs(AS2870, 2011) .................................................................................................... 52
Figure 2-24: Sample calculation of Ipt from different Iss values for cracked soil ........... 56
Figure 3-1: The hydrologic cycle (NWS, 2010) ............................................................. 61
Figure 3-2: Redistribution of the soil moisture (Dingman, 2002) .................................. 63
Figure 3-3: Variation of monthly rainfall and evapotranspiration with soil moisture
conditions in various sites (Russam and Coleman, 1961)............................................... 64
Figure 3-4: Flow chart of the TMI calculation................................................................ 67
Figure 3-5: TMI variation in Melbourne CBD for the last 50 years ............................... 76
Figure 3-6: TMI and annual rainfall variation in Melbourne CBD for last 50 years ...... 77
Figure 3-7: Relationship between TMI and annual rainfall (Melbourne) ....................... 78
Figure 3-8: TMI and annual average temperature variation in Melbourne CBD for the
last 50 years ..................................................................................................................... 79
Figure 3-9: Relationship between TMI and annual average temperature (Melbourne) .. 79
Figure 3-10: Sensitivity of averaging period on TMI ..................................................... 80
viii
Figure 3-11: Variation of soil suction of road subgrade with TMI (Russam and
Coleman, 1961) ............................................................................................................... 81
Figure 3-12: Edge moisture variation distance determination in Post Tensioning
Institute (PTI, 2004) ........................................................................................................ 82
Figure 3-13: Correlations of equilibrium soil suction and TMI (Mitchell, 2008) .......... 82
Figure 3-14: Correlation of ΔU and TMI (Mitchell, 2008) ........................................... 83
Figure 3-15: Correlation of Hs and TMI (Mitchell, 2008) ............................................. 84
Figure 3-16: (a) Average Annual Rainfall in mm for 2100 predicted climate; (b) TMI
map for 2100 predicted climate(Austroads, 2004) .......................................................... 85
Figure 3-17: Victorian mean annual rainfall map (BoM, 2015a) ................................... 85
Figure 3-18: TMI map for Victoria for 1913 to 1932 (Leao and Osman, 2013) ............ 86
Figure 3-19: TMI map of Victoria given in AS2870 (1996) .......................................... 87
Figure 3-20: TMI map of Victoria given in AS2870 (2011) .......................................... 89
Figure 3-21: TMI calculation for Victorian cities ........................................................... 90
Figure 3-22: TMI of Victorian cities in different climate zones specified in AS2870
(1996) .............................................................................................................................. 91
Figure 3-23: TMI of Victorian cities in different climate zones specified in AS2870
(2011) .............................................................................................................................. 91
Figure 3-24: Vertical strain and suction relationship (Braybrook soil) .......................... 94
Figure 3-25: Iss variation with starting moisture content for soils at 0.5-1.0 m depth in
Braybrook ........................................................................................................................ 96
Figure 4-1: Geology of Melbourne and the location of Braybrook site - extracted from
1:31680 map of Melbourne (Maps, 2015) .................................................................... 102
Figure 4-2: Distribution of expansive soils in Victoria (after Mann (2003)) ................ 103
Figure 4-3: Google map view of the Braybrook site and samples collected locations
(Google image was taken in 2010)................................................................................ 104
Figure 4-4: Three adjacent blocks of Braybrook Site ................................................... 105
Figure 4-5: Cross section of an undisturbed sample extruded from a tube (2.5 -3.0 m)
....................................................................................................................................... 106
Figure 4-6: Cross section of the soil profile of Braybrook site exposed through an
excavation ..................................................................................................................... 107
Figure 4-7: Atterberg limits and linear shrinkage variation with depth ........................ 109
Figure 4-8: Location of Braybrook clay in plasticity chart (ASTM-D2487, 2011) ...... 109
ix
Figure 4-9: a) Hydrometer test, b) Specific gravity test................................................ 110
Figure 4-10: Specific gravity and fine particle percentages variation with depth in
Braybrook Soil .............................................................................................................. 111
Figure 4-11: Hyprop sample in the ring ........................................................................ 117
Figure 4-12: Excavation of a pit in Braybrook site to collect Hyprop samples ............ 117
Figure 4-13: Excavation of undisturbed samples using Hyprop sampling device ........ 118
Figure 4-14: Hyprop samples saturation under a surcharge.......................................... 119
Figure 4-15: Refilling of de-gassed water; a) into tensiometer, b) into Hyprop sensor
unit ................................................................................................................................ 120
Figure 4-16: Suction measuring unit of Hyprop device(UMS, 2013) .......................... 121
Figure 4-17: The auger adapter and the sample with two holes drilled in the bottom
surface ........................................................................................................................... 122
Figure 4-18: The soil sample attached to the Hyprop sensor unit ................................. 122
Figure 4-19: The Hyprop test is running inside the environmental chamber ............... 123
Figure 4-20: The soil sample at the end of the Hyprop test .......................................... 124
Figure 4-21: Relationship between volumetric and gravimetric moisture consents in
Braybrook soil ............................................................................................................... 125
Figure 4-22: A portion of typical SWCC developed using Hyprop ............................. 125
Figure 4-23: Schematic of chilled-mirror dew-point device (after Leong et al. (2003) )
....................................................................................................................................... 126
Figure 4-24: Standard liquids used to calibrate the WP4C ........................................... 128
Figure 4-25: Soil sampling devises used to prepare WP4C samples ............................ 128
Figure 4-26: The sample is ready to measure suction using WP4C ............................. 129
Figure 4-27: A portion of typical SWCC developed using WP4C ............................... 130
Figure 4-28: Filter paper suction measurements of Braybrook soil .............................. 131
Figure 4-29: Calibration Suction-Water Content Curves for Wetting of Filter Paper
(ASTM-D5298, 2003) ................................................................................................... 132
Figure 4-30: SWCCs of soil from Braybrook site at different depths .......................... 134
Figure 4-31: Saturated hydraulic conductivity test for Braybrook soil using tri-axial
machine ......................................................................................................................... 135
Figure 4-32: Variation of Ksat with time of measurement - top two layers ................... 137
Figure 4-33: Variation of Ksat with time of measurement - bottom two layers ............ 137
x
Figure 4-34: Predicted hydraulic conductivity functions for Braybrook soil at 0-0.4 m
....................................................................................................................................... 141
Figure 4-35: Hydraulic conductivity functions (based on Fredlund’s model) of
Braybrook soil at different depths ................................................................................. 141
Figure 5-1: Neutron probe access tube pushing into the borehole ................................ 145
Figure 5-2: CPN 503DR neutron probe used in the Braybrook site ............................. 146
Figure 5-3: Calibration curve of the neutron Probe ...................................................... 147
Figure 5-4: Schematic of neutron probe measuring arrangement ................................. 148
Figure 5-5: Releasing mechanism of the spider magnet in extensometer ..................... 150
Figure 5-6: Magnetic extensometer installation at the Braybrook site ......................... 151
Figure 5-7: Ground surface movement measurements using extensometer ................. 151
Figure 5-8: Monitoring Plan of the Braybrook Site ...................................................... 152
Figure 5-9: Volumetric moisture content profiles at CN1 location .............................. 154
Figure 5-10: Volumetric moisture content profiles at the CN2 location ...................... 154
Figure 5-11: Volumetric moisture content profiles at the TN6 location ....................... 155
Figure 5-12: Crack measurements using a steel cable .................................................. 156
Figure 5-13: Comparison of moisture contents obtained from the neutron probe and the
samples .......................................................................................................................... 158
Figure 5-14: Volumetric moisture content (VMC) change comparison with monthly
rainfall (Location – CN1) .............................................................................................. 159
Figure 5-15: Volumetric moisture content (VMC) change comparison with daily rainfall
(Location – CN1) .......................................................................................................... 160
Figure 5-16: Surface movements measured at 3 locations and monthly rainfall .......... 163
Figure 5-17: Soil movements in response to monthly rainfall - E1 extensometer ........ 164
Figure 5-18: Soil movements in response to monthly rainfall - E2 extensometer ........ 164
Figure 5-19: Soil movements in response to monthly rainfall - E3 extensometer ........ 165
Figure 5-20: Incremental paver movements with monthly rainfall .............................. 167
Figure 6-1: Thermal conductivity functions used in this study..................................... 178
Figure 6-2: Specific heat capacity functions used in this study .................................... 179
Figure 6-3: Initial soil temperature function used in this study .................................... 180
Figure 6-4: Hourly rainfall distribution used in vadose software (for data set given in
Table 6-1) ...................................................................................................................... 181
Figure 6-5: Grass cover in Braybrook site .................................................................... 183
xi
Figure 6-6: Estimated leaf area index function for Braybrook site ............................... 184
Figure 6-7: Typical PML function used in the study (Vadose, 2013) .......................... 184
Figure 6-8: Root depth function for Braybrook site...................................................... 185
Figure 6-9: Summary of one-dimensional Vadose/w model ........................................ 187
Figure 6-10: Initial moisture content measured at various depths; (b) corresponding
suction at various depths ............................................................................................... 188
Figure 6-11: Measured soil moisture contents at 0.35 m and model predictions with
rainfall variation ............................................................................................................ 190
Figure 6-12: Measured soil moisture contents at 0.60 m and model predictions with
rainfall variation ............................................................................................................ 190
Figure 6-13: Measured soil moisture contents at 0.85 m and model predictions with
rainfall variation ............................................................................................................ 191
Figure 6-14: Measured soil moisture contents at 1.60 m and model predictions with
rainfall variation ............................................................................................................ 191
Figure 6-15: Measured average soil moisture contents at 0.35 m and model predictions
with rainfall variation .................................................................................................... 192
Figure 6-16: Measured average soil moisture contents at 0.60 m and model predictions
with rainfall variation .................................................................................................... 192
Figure 6-17: Measured average soil moisture contents at 0.85 m and model predictions
with rainfall variation .................................................................................................... 193
Figure 6-18: Measured average soil moisture contents at 1.60 m and model predictions
with rainfall variation .................................................................................................... 193
Figure 6-19: Actual measurements and model predictions for two extreme measurement
dates; a) recorded wettest, b) recorded driest ........................................................... 194
Figure 6-20: Model predictions against neutron probe measured data ......................... 194
Figure 6-21: A large soil chunk from Braybrook ......................................................... 196
Figure 6-22: Two-dimensional Vadose/w model .......................................................... 199
Figure 6-23: Characteristic wettest and driest suctions at 300 mm depth taken from the
2D model with different sizes ....................................................................................... 199
Figure 6-24: Soil moisture profiles obtained from models with different mesh sizes .. 200
Figure 6-25: 20% changes applied to SWCC of surface layer in sensitivity analysis .. 202
Figure 6-26: 20% changes applied to hydraulic conductivity of surface layer in
sensitivity analysis ........................................................................................................ 203
xii
Figure 6-27: 20% changes applied to thermal conductivity of surface layer in sensitivity
analysis .......................................................................................................................... 203
Figure 6-28: 20% changes applied to specific heat capacity of surface layer in
sensitivity analysis ........................................................................................................ 204
Figure 6-29: Sensitivity of soil parameters ................................................................... 204
Figure 6-30: Daily rainfall variation of 3 locations around Braybrook (April 2013) ... 206
Figure 6-31: Variation of evaporation in Fawkner ....................................................... 207
Figure 6-32: Comparison of pan evaporation and Penman potential evaporation in
Fawkner ......................................................................................................................... 207
Figure 6-33: Sensitivity of climate parameters ............................................................. 209
Figure 6-34: Effect of vegetation layer on soil moisture at Braybrook site .................. 210
Figure 6-35: Effect of ponding condition on soil moisture at Braybrook site .............. 211
Figure 7-1: Annual rainfall recorded in Essendon airport weather station ................... 216
Figure 7-2: Flow chart of AS2870 method ................................................................... 219
Figure 7-3: Flow chart of Vadose/w + AS2870 method ............................................... 220
Figure 7-4: Soil stiffness versus moisture content relationship for Braybrook soil ...... 221
Figure 7-5: Flow chart of Vadose/w + FLAC model .................................................... 221
Figure 7-6: Predicted characteristic suction profiles; a) Braybrook-VB1 model and b)
Fawkner-VF1 model ..................................................................................................... 223
Figure 7-7: Variation of volumetric moisture content near surface and at Hs– Braybrook
(VB1 model) ................................................................................................................. 224
Figure 7-8: Variation of volumetric moisture content near surface and at Hs – Fawkner
(VF1model) ................................................................................................................... 225
Figure 7-9: Braybrook ground movement prediction from VB1 and FLAC model ..... 226
Figure 7-10: Fawkner ground movement prediction from VF1 and FLAC model....... 227
Figure 7-11: Idealized characteristic suction profiles in Braybrook site (VB1 model) 228
Figure 7-12: Changes in characteristic suction profiles within 25 year periods; a)
Braybrook -VB1 model and b) Fawkner-VF1 model ................................................... 231
Figure 7-13: Changes in characteristic suction profiles -VB2 model; a) Extreme profiles
in three periods b) Idealized triangles for AS2870 calculations ................................... 233
Figure 7-14: Ground movement prediction from VB2 and FLAC model .................... 234
Figure 7-15: Soil moisture predictions without any runoff correction ......................... 236
Figure 7-16: Ground movement predictions with different runoff conditions ............. 237
xiii
Figure 7-17: 12 month moving average ground movement – Braybrook ..................... 239
Figure 7-18: 12 month moving average ground movement –Fawkner ......................... 239
Figure 7-19: Effect of long-term climate predictions on ground movement – Braybrook
....................................................................................................................................... 241
Figure 7-20: Effect of long-term climate predictions on ground movement – Fawkner
....................................................................................................................................... 241
Figure 7-21: Predicted moisture variation with the distance at 300 mm depth in
Braybrook soil ............................................................................................................... 243
Figure 7-22: Predicted edge moisture variation (e) at 300 mm depth in Braybrook soil
....................................................................................................................................... 244
Figure 7-23: Discrete points along the distance where soil moisture variations
considered to obtain ground movement ........................................................................ 247
Figure 7-24: Suction profiles during 1983-1992 at distances 3 m and 4 m from axis of
symmetry ....................................................................................................................... 249
Figure 7-25: Suction profiles during 1983-1992 at distances 5 m and 6 m from axis of
symmetry ....................................................................................................................... 249
Figure 7-26: Suction profiles during 1983-1992 at distances 7 m and 8 m from axis of
symmetry ....................................................................................................................... 250
Figure 7-27: Maximum edge heave profile during 1983-1992 ..................................... 251
Figure 7-28: Suction profiles during 1992-2010 at distances 3 m and 4 m from axis of
symmetry ....................................................................................................................... 252
Figure 7-29: Suction profiles during 1992-2010 at distances 5 m and 6 m from axis of
symmetry ....................................................................................................................... 253
Figure 7-30: Suction profiles during 1992-2010 at distances 7 m and 8 m from axis of
symmetry ....................................................................................................................... 253
Figure 7-31: Maximum centre heave profile during 1992-2010 ................................... 254
Figure 7-32: Comparison of lateral moisture movement at 300 mm depth in with and
without slope condition ................................................................................................. 256
xiv
List of tables
Table 2-1: Typical Atterberg limit ranges of pure clays (Fratta et al., 2007) ................. 17
Table 2-2: Identification of shrink-swell potential using shrinkage limit and linear
shrinkage (Altmeyer, 1955) .......................................................................................... 18
Table 2-3: Identification of shrink-swell potential using Plasticity index (Holtz and
Gibbs, 1956) .................................................................................................................... 18
Table 2-4: Site classification by characteristic surface movement (AS2870, 2011) ...... 45
Table 3-1: Climate types together with their TMI limits (Thornthwaite, 1948) ............. 66
Table 3-2: TMI calculation steps in Method 1 ................................................................ 72
Table 3-3: TMI calculation steps in Method 2 ................................................................ 73
Table 3-4: TMI calculation steps in Method 3 ................................................................ 74
Table 3-5: TMI calculation steps in Method 4 ................................................................ 75
Table 3-6: Climate zones and corresponding Hs inferred from AS2870 (1996) ............. 88
Table 3-7: Relationship between TMI and Hs(AS2870, 2011) ...................................... 90
Table 3-8: Hs and ΔU values specified in AS2870 ......................................................... 92
Table 3-9: Iss test results from different samples collected at similar locations from
Braybrook ........................................................................................................................ 96
Table 3-10: Iss results of Burnside samples ..................................................................... 97
Table 3-11: Calculation of ys using different Iss values .................................................. 98
Table 4-1: Soil profile at Braybrook ............................................................................. 106
Table 4-2: Basic soil test result - Location 1................................................................. 108
Table 4-3: Basic soil test result - Location 2................................................................. 108
Table 4-4: Basic soil test result - Location 3................................................................. 108
Table 4-5: Mineral composition of Braybrook clay ...................................................... 112
Table 4-6: Iss values of Braybrook soil at different depths ........................................... 113
Table 4-7: ys calculation ................................................................................................ 113
Table 4-8: Approximate measurement ranges and times for equilibration in
measurement and control of soil suction (Murray and Sivakumar, 2010) .................... 115
Table 4-9: Filter paper readings of Braybrook soil ....................................................... 132
Table 4-10: Saturated hydraulic conductivity data sheet .............................................. 136
Table 4-11: Saturated hydraulic conductivities of Braybrook soil ............................... 138
Table 5-1: Results from neutron probe measurements ................................................. 149
xv
Table 5-2: Description of crack depth measurements at CN1, CN2 and TN6 locations
....................................................................................................................................... 157
Table 5-3: Soil layer movements from E1 extensometer .............................................. 161
Table 5-4: Soil layer movements from E2 extensometer .............................................. 161
Table 5-5: Soil layer movements from E3 extensometer .............................................. 162
Table 5-6: Movements of paving blocks ....................................................................... 166
Table 6-1: Hourly rainfall distribution (sinusoidal) of daily rainfall – assumed data set
....................................................................................................................................... 181
Table 6-2: Typical set of data used in climate boundary in Vadose/w software .......... 182
Table 7-1: Soil profile at Fawkner site (Rajeev et al., 2012) ........................................ 217
Table 7-2: Geotechnical properties of Fawkner soil (Rajeev et al., 2012) ................... 217
Table 7-3: Estimation of ys for Braybrook site ............................................................. 229
Table 7-4: 25 year periods and corresponding TMI...................................................... 230
Table 7-5: Estimation of ys based on AS2870 (2011) for Braybrook ........................... 230
Table 7-6: Estimation of ys for 25 year periods – Braybrook site ................................ 232
Table 7-7: Estimation of ys for 25 year periods – Fawkner site .................................... 232
Table 7-8: Estimation of ys for Braybrook site with bedrock at 3m depth (from VB2
model) ........................................................................................................................... 235
Table 7-9: relationship of ym and ys (AS2870, 2011) ................................................... 245
Table 7-10: Comparison of changes in 'e' distances ..................................................... 245
Table 7-11: Ground movement estimation during 1983-1992 ...................................... 251
Table 7-12: Ground movement estimation during 1992-2010 ...................................... 254
Table 7-13: Mound shape parameters obtained from models ....................................... 255
1
1. INTRODUCTION
This thesis is a documentation of PhD research undertaken at Swinburne University of
Technology, Australia from 2012 to 2015. This doctoral programme was part of a larger
research project carried out in association with five industry organizations namely,
Victorian Building Authority (VBA), Victorian Office of Housing (OoH), Foundation
and Footing Society of Victoria (FFSV), Association of Consulting Structural Engineers
Victoria (ACSEV) and Housing Engineering Design and Research Association
(HEDRA). The overall objective of the programme was to assist in the mitigation of
damages to residential structures due to ground movement. The following section
describes the background of the problem and the specific objective of this doctoral
research.
1.1 BACKGROUND
Expansive soil has been a great concern in design and construction of lightly loaded
structures in Australia. Approximately 20% of the surface soils in Australia can be
categorized as moderate to highly expansive soils (Richards et al., 1983) and these
expansive soils are frequently found in populated areas, as shown in Figure 1-1.
Expansive soils undergo changes in volume mainly due to moisture variations. This
volume change behavior causes heave and settlements of the ground surface which can
result in substantial differential footing movements resulting in damage to houses and
other lightly loaded structures.
The moisture changes of the soil beneath house footings can result from various factors
including climate conditions, gardening around the house and pipe failures.
Unfortunately, it is not possible to completely eliminate these causes. While the
maintenance issues can be minimized, the environmental effects have to be accepted.
However, the detrimental consequences of the soil moisture changes under footings can
be minimized by taking suitable procedures in the design. For instance, the majority of
damage can be minimized by designing footings to sustain the expected ground
movement. Consequently, the construction and maintenance procedures can also be
adjusted based on the footing design.
2
Figure 1-1: a) Expansive soil distribution in Australia (Richards et al., 1983); b) Geographic distribution of population (Statistics, 2012)
Soil moisture is also dependent on the climate. Indeed, weather patterns and extreme
climate events are reflected in soil moisture contents. Drought conditions, for example,
can decrease the moisture of the soil underneath the footing around the house. Hence,
edge settlements of footings can be expected during droughts. In contrast, moisture
content increases during wet periods which result in edge heave of the houses. Apart
from climate effects, soil moistures are also influenced by the type of soil. Therefore,
the climate condition and the soil type of the area are key design parameters of
residential footings. Since both of these parameters vary from place to place it is
difficult to develop a generalized approach for the design and, therefore, many
assumptions must be implemented in ground movement estimations (Cameron and
Walsh, 1984, Mitchell, 1984a, Walsh, 1975).
There has been some research on designing footings on expansive soils (Cameron,
1977, Lytton, 1970b, Lytton, 1970a, Lytton and Woodburn, 1985, Mitchell, 1984b,
Nelson et al., 2003, Walsh, 1975, Wray, 1978, Pitt, 1982, Washusen, 1977). These
researchers mainly concentrated on strengthening the footings to withstand the ground
movement. The estimation of expected ground movement has also been considered and
a) b)
3
various methods have been developed. All these methods are based on moisture
variation, which is the primary cause of volume change behaviour of expansive soils.
Research on the design of footings on expansive soils has resulted in the development
of an Australian standard which offers guidelines for the design of reliable and
economical footings (AS2870, 1986). This standard was updated twice, in 1996 and
2011, but remains largely unchanged in relation to the design philosophy and approach.
The standard provides a simplified method to classify the sites by calculating the
characteristic ground movement (ys). Additionally, deem-to-comply footing designs are
provided for each site classification and construction type, which are expected to
tolerate the calculated surface movement. In addition, the standard allows engineers to
design footings from first principles and provides simple design assumptions to follow.
However, in recent years, there have been many reports in the media (ACA, 2012, THE-
AGE, 2011, THE-AGE, 2014a, THE-AGE, 2014b) as well as anecdotal evidence
regarding footing movements and house cracks. The Housing Industry Association
(HIA) has estimated that more than 1000 houses in Melbourne’s west have been
damaged due to slab heave (THE-AGE, 2011) while other reports claim that up to 4300
houses could be suffering from this problem (THE-AGE, 2014a). Victoria experienced
a severe drought from 1996 to early 2009 which was broken in 2010 followed by above
average rainfall for two years (BoM, 2012). According to HIA, the damage to the
houses arose due to abnormal moisture conditions in the soil that was created by the
drought-breaking rains. During the drought period, older houses experienced damage
due to edge settlement. But after the breaking of the drought, it was newer houses,
which were built during the drought, which were reported to experience the most
damage (THE-AGE, 2011).
The damaged houses were recorded in most of the Western suburbs (Figure 1-2)
including Melton, Werribee, Hoppers Crossing, Tarneit, Truganina, Deer Park, Point
Cook, and Caroline Springs (THE-AGE, 2011). Cracks in plasterboards and brick wall
ranged from the size of a hairline to more than 20 mm. In addition, interior walls were
lifted off the floor, windows and doors shifted from their frames and the floors moved
causing objects to roll off the floor and tabletops. Figures 1-3 to 1-5 show typical
damage as reported in the media.
4
Figure 1-2: Areas of reported damaged houses
Figure 1-3: Crack in an interior plasterboard lined wall (ACA, 2012)
MeltonCaroline Springs
Hoppers CrossingWerribee
Point Cook
Deer ParkTruganina
TarneitMelbourne CBD
5
Figure 1-4: Another example of a crack in an interior plasterboard lined wall (ACA, 2012)
Figure 1-5: Large crack in a plasterboard lined wall (THE-AGE, 2011)
Further to the media reports, the author of this thesis has been involved in a number of
damaged houses investigations in association with advisory panel members of this
research programme. Figures 1-6 to 1-9 illustrate examples of damage to houses in the
Wyndham Vale and Taylors Hill areas in West Melbourne.
6
Figure 1-6: A crack in a wall caused by edge lift of footing (Photo taken by the author)
Figure 1-7: Crack appeared in a wall caused by edge lift of footing (Photo taken by the author)
7
Figure 1-8: Separation of up to 50mm in a wall and the window frame caused by footing movement
(Photo taken by the author)
Figure 1-9: An internal wall has been lifted by roof truss due to edge heave of footing (Photo taken
by the author)
8
It appears that changes in the climate conditions, caused by back-to-back extreme
events, have contributed substantially to the damage observed in these houses.
Importantly, the above-mentioned problems have occurred despite these houses being
designed according to the Australian standard. This has raised question whether the
current standard is capable of capturing ground movements due to recent climate
changes. Moreover, as these damages are observed in the western part of Melbourne
which has moderate to highly expansive basaltic clay soils, the moisture changes and
subsequent ground movement of such clay soils is needed to be thoroughly examined.
The inappropriate procedures for design, construction and maintenance of houses on
expansive soils could lead to damage and hence require identification and vigilant
attention.
The houses built during the drought were designed based on the 1996 edition of the
standard. This edition used climate data from 1940-1960 to define the parameters of ys
calculation. While certain changes were made in the latest edition in 2011, the climate
consideration in ys calculation is still not clearly explained and has been questioned by
many researchers (Leao and Osman, 2013, Karunarathne et al., 2012, Lopes and Osman,
2010). However, it must be noted that Australian climate conditions have changed and
more extreme weather conditions can be expected (Austroads, 2004). As a result,
designing footings for soil moisture changes based on past climate conditions may not
be appropriate and more frequent modifications may have to be included for the
standard.
The aim of this doctoral research is to provide further understanding of the behaviour of
expansive soils in Western Melbourne and investigate the expected surface movement
due to seasonal climate changes. The following section describes the specific objectives
of this research.
1.2 RESEARCH OBJECTIVES
I. Review key characteristics of expansive soils and associated recent findings
from field and laboratory studies in Australia.
II. Review the effects of climate on expansive soils and establish likely effects on
soils from changes of climate conditions.
9
III. Undertake a comprehensive study of typical expansive basaltic clay found in
West Melbourne through field sampling and laboratory investigation.
IV. Establish typical behaviour of expansive soil in the field over multiple seasons
through ongoing monitoring of a field site. The results from this work will
establish data for calibration and validation of analytical models
V. Develop an analytical model to predict the moisture and suction variation of
expansive soils under varying climate conditions. Further, use the model output
to predict the ground movement using other tools.
VI. Use the validated model to predict the ground movement for different climate
conditions and site conditions.
1.3 OVERVIEW OF THE RESEARCH METHODOLOGY
A literature review was undertaken to acquire a thorough understanding of the
behaviour of expansive soils under moisture changes and the available estimating
methods, particularly emphasising the procedure given in Australian Standard. The
reports on research and forensic investigations of soil moisture changes and ground
movement were studied to determine the causes and the consequences. Moreover, the
climate consideration approach used in the current Australian footing design standard
was critically investigated. The recent changes of climate conditions in Victoria and its
effects on soil moisture were also examined. Subsequently, the changes of expansive
soil properties in response to moisture changes were studied using various laboratory
experiments. These studies were required to select the most appropriate approach to
develop a prediction method.
A field site was established in one of the Western suburbs in Melbourne where
expansive soils are widely spread. The site has a consistent profile of typical basaltic
clay. The moisture content at various depths, and the subsequent soil movements were
regularly monitored using the most sophisticated equipment available at the time of the
study. Soil samples were collected at different depths. A laboratory investigation was
conducted to develop a comprehensive database for that site, including the basic
properties and more specific properties such as the soil water characteristic curve,
hydraulic conductivity and mineral composition. Soil moisture changes at different
10
depths and the corresponding ground movements were monitored regularly. The climate
data during the monitored period was collected from a nearby weather station.
A finite element approach was implemented to model the soil moisture changes due to
climate conditions. The Vadose/w package, available in GeoSlope software, was used to
develop the model. The material model was developed using extracted soil properties
from the Braybrook site and climate data was used as an input parameter. This model
was validated against the monitored soil moistures from a Neutron probe. The validated
model results were then used in a different software to investigate the ensuing ground
movement. The development of a ground movement prediction model was a part of this
major research programme but not form part of this thesis. However, the results are
reported herein. The results of the model using the Vadose/w are compared with
AS2870 standard estimations in this thesis. The validated Vadose/w model was then
used to investigate the soil moistures due to different climate scenarios including
drought and wet periods. The subsequent ground movements were also compared. The
model was extended to investigate the soil moisture changes beneath footings due to
different situations on adjacent open ground. Climate effects and various manmade
causes were investigated to predict the abnormal soil moisture changes beneath
footings.
1.4 PERCEIVED SPECIFIC CONTRIBUTIONS OF THE RESEARCH
Using up-to-date technology and equipment, a complete test series related to expansive
soil was performed within a reasonably short time period. The behaviour of expansive
soil in typical basaltic clay soil area was thoroughly investigated in this study. As a
result, a comprehensive data set was developed and published which is beneficial for
both practitioners and researchers. More specifically, a series of shrink swell tests were
performed using undisturbed soils at various in situ moisture contents. These test results
indicated the dependency of shrink swell index on in situ moisture content. This
contradicts the Australian standard-AS1289 which states the shrink swell index as a
constant for a given soil type.
The validated analytical model is capable of predicting soil moisture changes due to
climate variations. The model can be used to estimate the expected soil moisture and
suction profiles within a lifespan of a structure. The model was used to investigate the
11
soil moisture changes due to long-term climate conditions including various extreme
events. The model was also used to study the moisture changes of sites with different
soil types. Furthermore, the model was used to investigate the moisture changes caused
by different site situations such as sloping ground.
The soil moisture predictions from this model were also used to investigate the ground
movement in another part of the research programme. In this thesis, ground movement
predictions from the model were compared with the ys calculations based on the lab
testing and the Australian standard. Hence, the outcome of this doctoral research is
valuable in assessing the footing design procedure given in the current Australian
standard and for its further modifications.
1.5 OUTLINE OF THE THESIS
Following the introduction of this PhD research given here, the next chapter provides a
comprehensive literature review associated with the characteristics of expansive soils.
The reasons for volume changes in expansive soils are discussed in Chapter 2 together
with the influences of ground movement on the design of footings on expansive soils.
The recent findings of research investigations in the expansive soils field are also
discussed in the next chapter.
Chapter 3 provides a critical description of the standard procedure of considering the
effects of climate conditions on footing design given in AS2870. The issues related to
employing Thornthwaite Moisture Index to evaluate the soil moisture condition in
response to climate conditions are discussed with example calculations. Furthermore,
certain issues of calculation of ground movement given in AS2870 are presented in
Chapter 3.
Chapter 4 describes the field and laboratory investigation performed in this study. The
selection criterion of the field site to monitor the expansive soil behavior is explained.
Moreover, the soil characterisation and the development of specific properties of
expansive soils are presented in this chapter.
Chapter 5 presents the field instrumentation used for regular monitoring of soil moisture
changes and subsequent ground movement. The analysis of collected data over a two-
year period is also discussed.
12
Chapter 6 explains the development of the finite element model to predict soil moisture
changes in response to climate conditions. The 1D model was validated using data
collected from the site monitoring. Hence, a comparison of field measurement and the
model outcomes is presented in this chapter. The one-dimensional model was also
extended to a two-dimensional model to observe the soil moisture movement in the
lateral direction. Therefore, the details of two-dimensional model development are also
provided in this chapter.
Chapter 7 discusses the applications of the developed finite element models. The one-
dimensional model was used to observe soil moisture changes in long-term climate
conditions. The effects of recent extreme climate events on soil moisture conditions
were studied using finite element models. The model results were used to identify the
changes in parameters required to calculate the ground movement based on AS2870.
The model results were also used to obtain ground movements using another model
developed as a part of this comprehensive research programme. The ground movement
predictions from the AS2870 procedure and from developed models are compared in
Chapter 7. Furthermore, the two-dimensional model was used to simulate the changes in
edge moisture variation in response to different climate conditions, and those changes
are compared with the guidance from AS2870.
Chapter 8 provides a summary of the conclusions of the many aspects of this research
study and presents the recommendations for future research.
13
2. LITERATURE REVIEW
2.1 INTRODUCTION
The investigation of climate induced soil moisture changes in expansive soils requires a
thorough understanding of the fundamentals of expansive soil behaviour. Certain soil
properties are sensitive to the moisture changes and hence they can be used to describe
the expansive characteristics of the soil. The mechanism of the moisture changes and
the subsequent volume changes provides the background to predicting the expected soil
moisture changes. The first part of the literature review focused on studying the
expansive soil behaviour, soil properties and their responses to moisture variations.
Next, the details of recent research and forensic investigations were examined to
determine moisture changes and their consequences on residential structures. Finally,
the standard approach to Australian residential footing design on expansive soil is also
reviewed and explained in this chapter, with an emphasis on the estimation of soil
moisture variation. The following section describes the behaviour of expansive soils due
to moisture changes.
2.2 EXPANSIVE BEHAVIOUR OF SOIL
2.2.1 Overview
Expansive soil is susceptible to volume changes in response to variations in moisture
content. Expansive soils swell on wetting and shrink on drying by significant amounts
(Walsh and Cameron, 1997) and are often termed “reactive soil”. The clay consists of
fine grained material with particles smaller than 0.002 mm (ASTM-D422, 2007). As
such, clay content of the expansive soils governs the reactivity (Gray and Allbrook,
2002). Clay is a general term including many combinations of one or more minerals
with traces of metal oxides and organic matter (Guggenheim and Martin, 1995).
Geologic clay deposits are mostly composed of sheet silicate minerals with water
trapped in between the mineral structure (Nelson and Miller, 1992). These smaller
particles combined with the layered crystalline composition produce properties of
plasticity during wet conditions and significant strength during dry conditions (Nelson
and Miller, 1992).
14
Effect of the expansive clay content on soil reactivity has been measured with respect to
the Coefficient of Linear Extensibility (COLE) by Gray and Allbrook (2002). They
carried out experiments on various soils in New Zealand and noted that COLE linearly
increases with the clay content. Specifically, it was observed that shrink–swell potential
is governed by the amount of water absorbed and desorbed from soil surfaces (Gray and
Allbrook, 2002). Clay particles can adsorb water due to their surface charge and the
layered arrangement. Therefore, the higher the clay contents the higher the reactivity in
soil. This behaviour can be explained by considering the micro scale factors and is
discussed further in the next section together with the mineralogy of expansive clay.
2.2.2 Mineral composition of expansive clay
Micro scale factors of expansive soils are sensitive to the moisture movements and their
responses can be investigated from the macro scale factors. Mineralogy, pore fluid
chemistry and soil structure are the main micro scale factors of soil (Nelson et al.,
2015). The expansive behaviour of clay soil can be explained using the mineralogy and
its reactions with soil moisture.
Clay minerals primarily consist of microscopic platelets made of silicates of aluminium,
iron and magnesium and they stack to form a layered type structure. A typical
microscopic platelet has negative electrical charges on its surfaces and positive
electrical charges on its edges. The atoms of oxygen, aluminium and/or magnesium
attract cations to equilibrate the imbalances. The various arrangements of those atoms
are the result of different crystalline structures and represent the different clay minerals.
The sheets of these minerals stack on each other and form a sequence to crate the clay
structure. The bond between stacked sheets depends on the arrangement of the charges.
The minerals are grouped according to the stack sequence as shown in Figure 2-1. There
are several clay mineral types, but common soils are mainly composed of Kaolinite,
Illite and Smectite (Galleries, 2014). The Kaolinite group includes Kaolinite, Dickite
and Nacrite whereas the Illite group mainly consists of a rock forming mineral; Illite.
The Smectite group, also called Montmorillonite, includes mainly Montmorillonite,
Sauconite, Saponite and Nontronite (Galleries, 2014). All these minerals contain strong
bonds between the elements of the platelet. The bonds between staked sheets are
different as shown in Figure 2-1. Illite has the strongest bond between its platelets
whereas Montmorillonite has the weakest bond.
15
Figure 2-1: Schematic diagrams of the mineral structure of Kaolinite, Illite and Montmorillonite (Nelson et al., 2015)
The Smectite category is the main type of clay mineral which is sensitive to soil
moisture, and hence governs the reactivity of clay soil (Chen, 1988). Montmorillonite is
the main component in Smectite. In Montmorillonite, the bond between the bases of the
two sheets is formed by weaker Van der Waals forces and thus the sheets will easily
separate at the weak bond. (Nelson and Miller, 1992). Therefore, the inter layer cations
can adsorb moisture. Figure 2-2 shows the swelling process of smectite illustrated by
Likos (2004). This figure shows four consecutive stages of hydration for a smectite
particle that contains two unit layers. Initially, the particles are in dry state such that the
negative charges concentrated on the surfaces and the positive charges are in between
the inter layers. As the water is absorbed by the inter layer cations, smectite layers move
apart which allows for transition from one stable hydration state to the next. Hence, the
gaps between platelets are expanded and the soil volume increases.
The reasons for the above phenomenon can be categorized into three micro scale
mechanisms of water absorption, namely; hydration, capillarity, and osmosis (Wayllace,
2008). Hydration is the attraction of water molecules into the soil. Capillarity originates
due to the pressure difference between two sides of air-water interfaces within the
porous soil fabric. Unsaturated soil pores have built up negative pressure and hence tend
to adsorb moisture. Radius of pore water menisci is inversely proportional to the
magnitude of pore pressure. This is the soil suction phenomenon and it is discussed
further in the succeeding sections. The osmotic water absorption occurs due to
concentration difference of dissolved ions between inter layer pore water and free water
(Wayllace, 2008).
Strong bond
Very weak bond
Strong bondWeak bond
Kaolinite Illite Montmorillonite
16
On the other hand, the water absorption and expulsion in clay minerals is also affected
by the changes of the density due to surcharge forces or compaction (Nelson and Miller,
1992). Collectively, this phenomenon of interaction between water and clay particles
causes the shrink-swell behaviour of expansive soils.
Figure 2-2: Conceptual model of sequential crystalline swelling of smectite (Likos, 2004)
The soil moisture influences in micro scale factors are reflected as shrink-swell
movements in expansive soils and can be qualitatively assessed using properties of soil
(Covar and Lytton, 2001). Plasticity, density and moisture content are the main macro
scale factors, which are used to describe the engineering behaviour of soil. Those
responses are discussed in the next section.
Crystal layer Negative charges on surfaces Interlayer cations
9.7 x 10-10 m
1.2 x 10-9 m
1.55 x 10-9 m
1.83 x 10-9 m
Zero-layer hydrate state
1-layer hydrate state
2-layer hydrate state
3-layer hydrate state
(a)
(b)
(d)
(c)
Molecular layer of H2O
17
2.2.3 Identification of shrink - swell potential based on soil properties
The basic soil properties vary based on the presence of the above-mentioned clay
minerals in soils. Typically, the high amount of Montmorillonite present in soils can
result in very high Atterberg limits as shown in Table 2-1.
Table 2-1: Typical Atterberg limit ranges of pure clays (Fratta et al., 2007)
Clay mineral Liquid limit % Plastic limit %
Kaolinite 35 - 100 25 - 35 Illite 50 - 100 30 - 60
Montmorillonite 100 - 800 50 - 100
Many researchers have investigated the links between basic soil properties and the
shrink-swell potential. As a result, a number of correlations have been proposed
(Altmeyer, 1955, Bandyopadhyay, 1981, Hazelton and Murphy, 2007, Holtz, 1959,
Holtz and Gibbs, 1956, Ranganatham and Satyanarayana, 1965) and most of these
correlations are associated with Atterberg limits (AS1289.3.1.1, 2009, AS1289.3.2.1,
2009), linear shrinkage (AS1289.3.4.1, 2008) and shrinkage limits (ASTM-D4943,
2008).
Table 2-2 shows relations given by Altmeyer (1955) using linear shrinkage and
shrinkage limits. Shrink-swell potential is less sensitive to the extreme ends of the
moisture content (Fityus et al., 2005). When moisture content is decreased starting from
wet condition, a significant volume reduction can be observed until the shrinkage limit
is reached (ASTM-D4943, 2008). There is no significant shrinkage if soil moisture is
further decreased. The opposite behaviour can be observed when the moisture content is
increased starting from dry state. No swelling occurs until the moisture content passes
the shrinkage limit but, beyond that, significant swelling can be observed. Therefore,
the soils with lower shrinkage limit may have a wider range for the shrink-swell
movement and hence can be identified as highly expansive. The linear shrinkage test
starts from the liquid limit of the soil which is the highest moisture that the soil would
behave in the plastic state. Therefore, highly expansive soils, which have higher liquid
limits, generally produce a greater amount of shrinkage movement during the drying
process of the linear shrinkage test. Hence, the higher the linear shrinkage amount, the
higher the reactivity of the soil. In conclusion, as shown in Table 2-2, soils with lower
18
shrinkage limit and higher linear shrinkage has high potential for shrink-swell
behaviour.
Table 2-2: Identification of shrink-swell potential using shrinkage limit and linear shrinkage (Altmeyer, 1955)
Shrinkage Limit % Linear Shrinkage % Probable swell % Degree of expansion
< 10 > 8 > 1.5 Critical 10 - 12 5 - 8 0.5 - 1.5 Marginal
> 12 < 5 < 0.5 Non-critical
Holtz and Gibbs (1956) suggested that the plasticity index alone can be used to indicate
the swelling potential of moist clay because both liquid limit and swell potential depend
on the soil’s water absorbability within the plastic state (Nelson and Miller, 1992).
Table 2-3 gives a qualitative assessment on swell potential based on plasticity index
(Holtz and Gibbs, 1956). The soils with a higher plastic index have a wider moisture
content range to behave plastically and, consequently, have a greater potential for
volume change.
Table 2-3: Identification of shrink-swell potential using Plasticity index (Holtz and Gibbs, 1956)
Plasticity Index % Swelling potential
0 - 15 Low 10 – 35 Medium 20 - 55 High
35 and above Very high
In addition to the qualitative measures of shrink-swell potential of soil, various
researchers have developed methods to quantify the shrink-swell movements using
basic soil properties (Seed et al., 1962, Skempton, 1953, Al-Rawas and Goosen, 2006).
Most of the relationships have been developed for compacted expansive soil however,
Chen (1988) proposed an empirical correlation to determine the swell percentage (S) of
undisturbed soils using plasticity index (PI) as shown in Equation 2-1. This relationship
was developed using swell results under surcharge of 6.9 kPa for soils with dry density
between 16 - 17.6 kN/m3 and limited moisture variation. For that particular range of
soils, A and B constants are equal to 0.0838 and 0.2558, respectively.
19
𝑆 = 𝐵𝑒𝐴(𝑃𝐼) ……………………………………………………….…… Equation 2-1
In conclusion, it is difficult to obtain a reliable estimation of shrink-swell movements
for a wide range of soils using basic soil properties. This is observed in the liquid limit
and volume change data plotted in Figure 2-3 (Kay (1990). The measured results are
highly scattered regardless of the qualitative assessment. Delaney et al. (2005)
attempted to find a correlation between the shrink-swell test and other basic soil tests
including linear shrinkage, plastic index and liquid limit but they concluded that a
considerable scatter exists in relationships of soil reactivity and basic properties. A
number of rigorous procedures, specific test methods and instruments have therefore
been developed to quantitatively measure the volume change of soil (Fityus et al., 2005,
Golait and Wakhare, 1999, Jennings et al., 1973, Jennings and Knight, 1957, Mitchell,
1979, Sridharan, 1999). However, the quantitative measurement of volume change
using laboratory test methods is out of the scope of this thesis.
Figure 2-3: : Index test correlation – Volume change vs Liquid Limit (Kay, 1990)
The above-mentioned properties are constants for a particular soil type. However,
certain soil properties vary with the soil moisture and therefore they can be used to
0 20 40 60 80 100 1200
10
20
30
40
50
60
70
Extremely expansive
Highly expansive
Vol
ume
chan
ge (%
)
Liquid limit (%)
Salinity > 10000 ppm Salinity < 10000 ppm
Moderately expansive
20
explain the expansive behaviour against moisture variation of the soil. The Atterberg
limits and linear shrinkage, which are correlated with shrink-swell potential as described
in the previous section, are obtained from disturbed and sieved soil samples. Hence,
they do not reflect the effect of soil structure. Some properties of undisturbed soils are
associated with the arrangement of particles and the pore structure. Pore structure of soil
is affected by hydration process as described in section 2.2.2. Therefore, undisturbed
soil properties vary with the moisture content changes. The following section describes
the soil properties affected by the moisture content.
2.2.4 Effects of moisture changes on soil properties
2.2.4.1 Soil suction
The main soil parameters used to describe expansive behaviour resulting from moisture
variation are suction and permeability. Both of these properties depend on the
arrangement of the pore structure. Among the various properties of soil, suction is
widely used to describe the expansive behaviour. It is one of the main stress state
parameters of the constitutive models developed to quantify volume changes (Alonso et
al., 1990, Alonso et al., 1999, Fredlund and Rahardjo, 1993, Fredlund and Vu, 2003,
Jones et al., 2009). The suction is defined as the potential of soil water in a soil
undergoing changes (Mitchell, 1984b). This potential arises due to two main
components usually referred to as “matric suction” and “osmotic suction” and the
summation of these two components is called “total suction”.
The matric suction depends on the pore structure which governs the capillary tension
(Mitchell, 1984b). A porous medium has an ability to absorb and hold a certain amount
of water due to its capillarity, texture and surface adsorptive forces. The openings
between soil particles are termed “necked” capillaries, which can absorb and hold water
until the maximum possible quantity under gravity is reached (Shroff, 2003). The water
held within the capillaries is in the state of negative pressure, which is identified as the
matric suction of the soil corresponding to particular moisture content. When the
moisture content of the soil is increased, the negative pressure in the held water is
reduced. Therefore, the matric suction reduces with increasing soil moisture content.
At saturation, all the pore spaces are completely filled with moisture that results in zero
matric suction. Therefore, the matric suction at the water table is zero. The suction
21
variation along the soil depth above the water table is called suction profile. Suction
profile can be identified using a saturated soil column as shown in Figure 2-4, which
shows the matric suction variation of soil column placed on a water container. The soil
column (Figure 2-4_b) is initially saturated and then allowed to drain from the bottom
under gravitation forces. The water level of the container is similar to the water table of
a soil profile. A certain height of the soil above the water level remains saturated with a
non-zero suction (Figure 2-4_a) due to capillary tension of soil pores. Once the
capillary tension passes a certain limit, the air starts to enter into soil pores. The air-
water interfaces of the pore water are curved towards water phase (Figure 2-4_c) which
indicates lower pressure in the water than in the air phase, which in turn indicates that
the pore water is in negative pressure state. This negative pore water pressure is the
matric suction, which generally measures in kPa units. The conventional unit of suction
is pF which is the logarithmic value of equivalent pressure of a water column in
centimetres (Schofield, 1935).
Figure 2-4: Matric suction variation of a soil column(Nelson et al., 2003)
The osmotic suction component, also known as solute suction, is the negative pore
water pressure created by the dissolved ions in soil moisture (Nelson et al., 2003). For
example, this is equal to the pressure difference of a pool of water which is divided by a
hd
MAT
RIC
SU
CTI
ON
, h c
DEGREE OF SATURATION100%
(a) (b)
WATER
SOLIDS
AIR
Uw = WATER PRESSURE
Ua = AIR PRESSURE
R
(c)
22
semipermeable (i.e. permeable to water molecules only) membrane such that one side
contains a solution identical in composition with the soil moisture while the other side
contains pure water (Aitchison, 1965). This is illustrated in Figure 2-5. The
semipermeable membrane shown in Figure 2-5 allows water molecules to pass through
but prevent salt molecules passing through. Then, a pressure will build up at the side of
salt solution, which is reflected in the height difference of the salt and pure water
columns in Figure 2-5. This pressure is the osmotic suction. Based on that illustration,
the osmotic suction varies due to dissolved salt in soil water. The presence of dissolved
ions in water reduce the energy state of the soil by reducing soil vapour pressures and
relative humidity, which ultimately increases the total suction (Nelson et al., 2003). The
higher the salt concentration in soil moisture the higher the osmotic suction in soil.
Figure 2-5: Osmotic pressure across the semipermeable membrane (Nelson et al., 2003)
Osmotic suctions of salt solutions are generally used to calibrate the suction
measurement equipment such as filter papers and psychrometers (ASTM-D5298, 2003,
ASTM-D6836, 2008). Osmotic suctions can be calculated using available relationships
(Lang, 1967, Bulut, 2001) and the standard salt solutions are readily available in the
literature (Goldberg and Nuttall, 1978, Hamer and Wu, 1972, Goldberg, 1981, ASTM-
D5298, 2003).
ho
SEMIPERMEABLE MEMBRANE
PURE WATER
SALT SOLUTION
23
In conclusion, total suction is influenced by the amount of moisture in soil pores and the
concentration of salts in soil moisture. However, for some soils, osmotic suction, which
is driven by salt concentration, can be constant over a certain moisture range as shown
in Figure 2-6. Soil suction is preferred over the moisture content in expansive soil
research sector as it represents the stress state of the soil (Fredlund and Rahardjo, 1993).
Therefore, the variation of suction with moisture content is the most important function
in describing expansive soil behavior. The following section describes the importance
of that relationship.
Figure 2-6: Measured total, matric, and osmotic suctions for Glacial Till from Chao (2007) after Krahn and Fredlund (1972)
2.2.4.2 The moisture characteristic
The same value of suction leads to different moisture contents of soils with different
textures (Mitchell, 1984b). The stress state of the soil depends not only on the moisture
content but also on the pore arrangement. Figure 2-7 shows the suction versus moisture
content variation for different soils in Adelaide, South Australia, as measured by
Mitchell (1984b). According to the curves in that figure, the higher the plasticity index
(PI) the higher the suction at a given moisture content. Table 2-3 concludes that the
higher the PI, the higher the expansiveness of soil. Therefore, observation of Figure 2-7
8 10 12 14 16 180
500
1000
1500
2000
2500
3000
Suc
tion
(kP
a)
Moisture content (%)
Total suction Matric suction Osmotic suction Osmotic + Matric suction
24
indicates that the highly expansive soils have higher suction values at given moisture
contents compared to less expansive clays. That is, at a particular suction (or stress
state) highly expansive soils can hold more moisture than less expansive clays. This
moisture holding capacity depends on the clay content and the clay type of the soil
(Mitchell, 1984b). The higher the clay content, the higher the value of moisture content
at a given suction (Morris and Gray, 1976). Therefore, highly expansive soils have
lesser slope in the suction and moisture relationship, as shown in Figure 2-7. The
relationship between soil suction and moisture content is called Soil Water
Characteristic Curve (SWCC) and the slope of the SWCC is called soil moisture
characteristic.
Figure 2-7: Measured soil moisture change with suction for some Adelaide soils (Mitchell, 1984b)
Figure 2-7 shows the variation of suction against moisture. However, in most expansive
soil studies, suction has been used as the independent variable and volumetric moisture
content is plotted against it (Chao, 2007, Fredlund, 2000, Fredlund and Rahardjo, 1993,
Hung, 2002, Likos, 2000). This is because the suction represents the stress level and one
of the main constitutive parameters of expansive soils.
Figure 2-8 shows typical features of a SWCC explained in Fredlund (2000). SWCC can
be developed in two different ways. The moisture content of initially dry soil can be
increased incrementally and the suction measured, to develop the wetting curve. The
Moisture Content %
Tota
l Suc
tion
(pF)
10 20 30 40 50
7
6
5
4
3PI=4 PI=22 PI=31
PI=45
PI=76
PI=101
25
drying curve can be developed by decreasing moisture from initially wet soil. Typically
these methods produce two different curves for SWCC. The non-uniform pore
arrangement is the main reason for this hysteresis of SWCCs from drying and wetting
methods (Fredlund and Rahardjo, 1993).
Figure 2-8: Typical shape of a SWCC (Fredlund, 2000)
Three phases can be identified in a typical soil moisture characteristic curve including
the boundary effect stage, transient stage and residual stage (see Figure 2-8). Two major
points can be identified in SWCC which divide the three stages; the air entry value and
the residual water content. The air entry value is the suction corresponding to the point
at which air begins entering into the saturated soil pores (Chao, 2007). Beyond the
residual water content, a very large suction should be provided for further removal of
moisture from the soil (Fredlund and Xing, 1994). Therefore, SWCC has mild slopes
during boundary effect stage and residual stage. It has a steeper slope in the transient
stage and this slope is the soil moisture characteristic, which is actually shown in Figure
2-7. Most of the volume changes in expansive soil occur during the transient stage. The
slopes of these three stages depend on the soil type (Fredlund, 2000, Fredlund and Xing,
1994). SWCC starts at saturated state that corresponds to very low suction. Suction
26
becomes substantially higher in low moisture contents. In general, the suction value at
zero moisture content is approximated to 106kPa (7 pF) in Fredlund and Xing (1994).
Some experimental data (Croney and Coleman, 1961, Richards, 1965, Mitchell, 1984b)
also confirms that it would be less than 106 kPa. A more detailed description on
developing SWCC is given in Chapter 4.
In addition to suction, the moisture flow rate is also affected by the pore structure and
moisture content. These changes can be identified from the permeability of soil at
different suction levels, which is described in next section.
2.1.2.3 Permeability
The permeability of soil describes the rate of moisture flow through the porous structure
of soil. The pore structure determines the path, length and the available cross sectional
area for moisture flow (Fredlund and Rahardjo, 1993). The clay soils have lower
permeability than sandy soils due to their closely arranged pore structure with finer
particles. Changes of conductive area can result in changes in permeability. Since the
pore structure is influenced by the volume change behaviour, the permeability of
expansive soils varies with the moisture content. In addition to the changes of pore
arrangement, fissures and layered soils also significantly contribute to the permeability.
Unsaturated soil pores are filled with both air and water. Therefore, when the
permeability of fluid through unsaturated soil pores is considered, both air and water
phases need to be taken into account. Therefore, it is difficult to measure the
permeability of unsaturated soils. Moreover, the compressibility of air in soil pores
creates uncertainties in these estimations. (Ng and Menzies, 2007).
When the permeability of moisture is considered, the driving potential of moisture flow
is important. The moisture flow can occur due to pressure difference or moisture content
difference at two points. However, the most suitable driving potential to be considered
is the energy difference of the points. The energy state of a point depends on the
hydraulic pressure, elevation and the velocity (Fredlund and Rahardjo, 1993). The
moisture flow through unsaturated porous mediums at different moisture contents is
commonly described using Darcy’s flow equation (Fredlund and Rahardjo, 1993).
Darcy (1856) developed an equation to calculate the rate of water flow through soil
using the energy state of the soil (Equation 2-2).
27
𝑣𝑤 = −𝑘𝑤
𝜕ℎ𝑤
𝜕𝑦 .……………………………………………………… Equation 2-2
where, vw is the flow rate of water, kw is the coefficient of permeability of the soil and
𝜕hw/𝜕y is the hydraulic head gradient in the y direction. According to Darcy, the flow
rate of water is proportional to the hydraulic head gradient. The coefficient of
proportionality is the permeability of the water phase and is also known as hydraulic
conductivity. Hydraulic conductivity is positively associated with moisture flow such
that the higher the hydraulic conductivity of the soil, the higher the capability of
moisture to flow through the soil. The hydraulic conductivity is constant for saturated
soils whereas it is a function of matric suction for unsaturated soils (Fredlund and
Rahardjo, 1993). This function is called hydraulic conductivity function which
describes the rate of moisture flow at different suction levels of the soil. A further
description on developing a hydraulic conductivity function is given in Chapter 4.
Since the expansive soil properties described in the sections above are dependent on
moisture changes, it is important to identify the reasons behind the soil moisture
changes. There are various causes of soil moisture changes and identifying them is
highly useful in the prevention of structural damage and to decide suitable remedies.
The following section describes possible causes for soil moisture changes.
2.2.5 Reasons for soil moisture change
Soil moisture changes occur as a result of various causes. The natural causes arise from
the environment that makes soil to absorb or desorb moisture. The main natural cause is
the climate condition. Several components of climate condition affect the soil moisture
in different ways. Precipitation is the main component, which increases the soil
moisture. Evaporation is the next important component and it causes loss of moisture
from surface soils. Relative humidity affects the moisture transfer between atmosphere
and soil and mainly governs the rate of evaporation from the surface. The climate
condition can be categorized as normal or extreme, depending on the amount of
influence from each component. Extreme conditions include floods and droughts, which
can cause substantial changes in soil moistures. The climate influences are generally
considered in design of footings for structures. However, the extreme conditions are not
28
predictable and therefore cannot be fully accounted for in the design. More details on
climate effects on soil moisture are given in Chapter 3.
The next important cause of soil moisture change is the influence of vegetation.
Vegetation, including trees, shrubs and grass covers, can deplete moisture from soil and
discharge to the atmosphere through a transpiration process. The effect of vegetation on
soil moisture depends on many factors including type of vegetation, root depth and root
sizes (Biddle, 1998). In general, the effects of trees are included when designing
residential footings however, a more specific approach would be effective which
considers the effects of different tree species, gardening, and grass covers. The
consideration of tree influence on soil moisture is a part of this group research
programme but it is not within the scope of this doctoral thesis.
In addition to those natural causes, there are various man-made causes that change the
moisture contents of soil beneath structures. These causes are mainly maintenance
issues such as water pipe failures, leaks and inappropriate gardening around houses.
Maintenance issues such as these can produce abnormal changes in soil moistures
which can outburst as differential movements in soil and footings. Importantly, these
issues can be minimized with proper maintenance and preventive measures. Since the
magnitude of these types of influences is not predictable, allowances are generally not
included in footing designs.
Based on the anecdotal evidence, in most situations, expansive soil problems arise not
only due to a single reason, but also due to a combination of several reasons. Therefore,
it is very complex to determine and fix the causative problems before taking remedial
actions. In contrast, a number of research investigations are performed to quantify
expansive soil behavior due to moisture changes. Moreover, forensic investigations
have been performed to ascertain the specific reasons behind residential property
damages due to expansive soil problems. The following section describes the
investigations of expansive soil problems, which are important in predicting moisture
movement and consequences.
29
2.3 INVESTIGATIONS ON EXPANSIVE SOIL PROBLEMS
2.3.1 Expansive soils - a global issue
Expansive soils are widely found in many countries in the world. Reported expansive
soil sites shown in Figure 2-9 indicate that in addition to Australia, expansive soils can
be commonly found in USA, Canada, South Africa, India, China, Israel, etc. The
expansive soils in these countries affect light structures and road pavements, and
researchers from across the globe undertake relevant research to reduce their adverse
effects.
Figure 2-9: Global distribution of reported expansive soil sites (Nelson et al., 2015)
Expansive soils can frequently be found in humid tropics and semi-arid zones in
England with most of these soils having more than 50% clay content with a significant
amount of mica-smectite (Driscoll, 1984). For such locations, seasonal soil moisture
variation under typical climatic conditions is small, and therefore ground movement is
not a major issue. However, the condition of tree drying which causes settlement has
been given most attention in designing light structures (Clarke and Smethurst, 2010).
Many research studies were focused on performance of deep narrow strip footings under
the influence of trees (Cutler and Richardson, 1981, Samuels and Cheney, 1975, Biddle,
2001, Biddle, 1983)
30
Regina, Saskatchewan in Canada is known to have preglacial, lacustrine clay sediments
which exhibit high plasticity characteristics (Nelson et al., 2015). Regina clay soils
have about 50% clay content with a liquid limit of about 80% and plasticity index of
about 50% (Yoshida et al., 1983, D.G.Fredlund, 1975). Lightweight structures built on
these soils may experience about 50-150 mm movement. (Fredlund et al., 2012). There
has been extensive research performed about these soils particularly which focused on
developing equations for SWCC (Fredlund and Xing, 1994).
Highly expansive soils can also be found in some areas of USA. In Colorado, clay soils
found which have liquid limits and plasticity index vary from 35-75% and 15-50%
respectively (Nelson et al., 2015). Those soils have significant influence on lightweight
structures resulting in structural deformations (Chao, 2007). Some buildings have
basements built removing most of the expansive soil within the active zone, but these
structures are subjected to influences of pore pressure rises particularly in initially dry
soils (Nelson et al., 2015). Highly expansive soils have been found in Texas, which can
cause damage to residential structures. Research on these soils led to developing a
standard practice to design suitable footings for those structures (Lytton et al., 2004).
The research studies on moisture-induced ground movement in expansive soils
performed in various parts of the world were mostly associated with field monitoring to
study the various factors affect soil moisture changes. The following section describes
the techniques used in such filed monitoring systems.
2.3.2 Field monitoring systems in expansive soil research
The monitoring of soil moisture content and the subsequent movement has been a
challenging task. Several approaches can be found in the literature. Field investigations
have been performed for many different purposes and a variety of equipment has been
used.
2.3.2.1 Neutron moisture measuring technique
The moisture content can be monitored by occasionally collecting samples at different
depths. However, depending on the available space and the variation of soil properties,
this procedure can be ineffective in the long-term. A non-destructive and repetitive
method is necessary to perform long-term monitoring of soil moisture. The neutron
probe moisture measuring technique is the most suitable method and is an indirect
31
method of moisture measurement. The neutron moisture measuring technique was
developed more than 60 years ago (Belcher et al., 1950) and since then has been widely
used in many different applications including in agriculture, water management and
building design (Chanasyk and Naeth, 1996, Evett et al., 1993, Hupet and Vanclooster,
2002, Nixon and Lawless, 1960, Ren and Li, 2010).
CPN 503DR neutron probe (Ward and Wittman, 2009) was successfully used in most
recent studies (Chan, 2014). Sources of neutrons in CPN 503 DR probes are Americium
and Beryllium. The probe, connected through a cable into the control unit, is inserted
into the access tube and clenched at the required position. The probe emits neutrons
during the measurement as a result of reaction involving Americium and Beryllium.
Americium ( 𝐴𝑚95241 ) is an unstable isotope with an excess of protons. It decays to
Neptunium ( 𝑁𝑝93237 ) by releasing an alpha (α) particle with energy (E) according to
Equation 2-3 (Ward and Wittman, 2009).
𝐴𝑚 → 𝑁𝑝 + 𝛼24
93237
95241 + 𝐸 .…………….....……………………...…… Equation 2-3
Beryllium ( 𝐵𝑒49 ) reacts with the emitted‘α’ particles and is converted into Carbon 𝐶6
13
which then decays to 𝐶612 , releasing ‘‘fast neutrons (n)’’ in the process, as described in
Equation 2-4 (Ward and Wittman, 2009).
𝐵𝑒 + 𝛼24 → 𝐶 → 𝐶6
12 + 𝑛01
613
49 + 𝐸 .…………….………………...…… Equation 2-4
These fast neutrons interact with the soil particles and soil moisture that surround the
probe. The sizes of the neutron and the hydrogen atoms are similar and therefore, in a
collision, much of the energy of the fast neutron can be imported to the hydrogen,
causing the neutron to become slowed, or thermalised (Ward and Wittman, 2009). Some
of these thermalised neutrons are back-scattered back to the detector in the probe. The
concentration of back-scattered neutrons detected is proportional to the concentration of
hydrogen in the soil. Finally, the corresponding moisture content can be obtained
through a calibration curve.
The radius (R) of the neutron scattering (in cm units) shown in Figure 2-10 depends on
the volumetric soil moisture content percentage (θ), as illustrated in Equation 2-5.
32
Hence, the drier the soil, the larger the radius of the neutron scattering sphere and the
smaller the rate of back-scattered neutrons detected.
Figure 2-10: Schematic depiction of neutron probe deployment(Ward and Wittman, 2009)
𝑅 =100
1.4 + 0.1 × 𝜃 ………...…………….....……………………...…… Equation 2-5
The main advantages of using the neutron probe technique is that it is a non-destructive
method which gives reliable, repetitive readings (Chanasyk and Naeth, 1996). This
method overcomes the sample collection procedure and hence it can be used
irrespective to the condition of the sample. This method also facilitates the measurement
of rapid changes of moisture content of soil (Chanasyk and Naeth, 1996). Since the
measurements consider a certain spherical volume of soil to obtain the moisture content,
it could be more reliable than using a fairly small sample to measure the gravimetric
moisture content (Nixon and Lawless, 1960).
However, there are some disadvantages to this technique. First, it uses radioactive
material and therefore requires special protection measures, training and an
authorization is required to use it. In addition, the readings may not represent the
measured depth due to consideration of the spherical volume of soil. However, this is
largely affected only for the layered soils (Nixon and Lawless, 1960). The other main
R
33
drawback of this technique is the difficulty in taking the near surface measurements. It
considers a spherical volume of soil which radioactive material is scattered and
therefore it is ineffective in measuring the soils shallower than the radius of the
influential sphere. The top soil layer is largely affected by the climate variations and
therefore the soil moisture fluctuates more frequently. But it is unlikely to reliably
capture the near surface moisture changes using the neutron probe technique. More
details on neutron probe technique are given in Chapter 5 of this thesis.
2.3.2.2 Monitoring of moisture ground movement
The volume changes of the soil with respect to the moisture variation have also
previously been performed in many places. The primary purpose of these types of
monitoring is related to residential building design applications (Fityus et al., 2004,
Sattler and Fredlund, 1991, Yoshida et al., 1983).
The main challenge of ground movement monitoring is to locate a permanent datum
point. In the late 1950’s, ground movement was measured using precise surveying
equipment and deep bench-marks (Sattler and Fredlund, 1991). In the 1960’s, Yoshida
et al. (1983) used deep bench-marks and vertical movement gauges to monitor soil
movement under a slab. They installed 3 gauges to measure movements at different
depths. Another gauge, inserted beyond 14 m, was considered as the datum. Later,
Fityus et al. (2004) used surface movement probes made constructed with galvanized
steel rods. This technique is similar to the technique used by Yoshida et al. (1983).
Fityus et al. (2004) used 25 mm diameter galvanized steel rods of different depths and
grouted to the bases of 100 mm diameter augured holes. The datum probes were
embedded to 5 m from the surface. One probe gives the movement at one particular
depth therefore they used a number of probes embedded from 0.5 to 3 m depths to cover
the soil layer movements of that site.
In most field studies, magnetic extensometers have been successfully used to monitor
movements of clay barriers, embankments, tunnels, earth dams, etc (Gikas and
Sakellariou, 2008, Liu et al., 2005, Wijeyesekera et al., 2001). The magnetic
extensometers were incorporated with a datum mechanism that was positioned below a
certain depth from the ground surface. According to the reactivity of the soil and the
given Hs, the depth of the datum can be determined by assuming the soil at that depth is
34
stable. The extensometers contain spider magnets placed at certain distances. The
distance of the magnets can be decided according to the number of measurements
expected within the total depth. Figure 2-11 and 2-12 show the spider magnet and the
arrangement of the extensometer. The spider magnets are attached to a collapsible pipe
around a PVC conduit, as shown in Figure 2-12. The legs of the spider magnets
penetrate the surrounding soil after installation and then move up and down along the
PVC conduit with respect to the movements of surrounding soil. The datum magnet is
attached to the bottom of the conduit. A measuring tape with a probe is used to identify
the location of the magnets and therefore can measure the distances between the spider
magnet positions. This tape can measure layer movements with ±2 mm error margin.
Figure 2-11: Spider magnet of the extensometer
35
Figure 2-12: Magnetic extensometer arrangement
The specific details of studies provide more information regarding installation and data
collection. The following sections describe some of the major investigations performed
in Australia over the last few decades. The details of these studies assist in the
development of the most convenient approach to this research programme.
2.3.3 Previous expansive soil research investigations in Australia
2.3.3.1 Swinburne research study in 1970’s
At Swinburne University of Technology, a major research programme was undertaken
in the 1970’s to investigate the Melbourne expansive soil issues on footings. Many
researchers were involved in this programme. Therefore the details of the study can be
found in many theses (Cameron, 1977, Crichton, 1974, Pitt, 1982, Washusen, 1977).
Various conclusions of this study can be also found in other publications (Holland and
Lawrance, 1980, Holland et al., 1980, Holland., 1978, Holland. et al., 1975).
The main purpose of the investigation was to develop a rational and economical method
for residential footing design on expansive soil. There were several field sites
established to monitor slabs in expansive soil areas in Melbourne including in Sunshine,
36
Waverley, Frankston, Keilor and Werribee. Several Ground Movement Stations (GMS)
were installed at each site to observe the soil and slab movements. GMSs consist of a
steel probe and a surface plate, as shown in Figure 2-13. The bottom end of the probe
was placed at a stable depth and anchored to the base of the borehole. A protective
casing was used around the probe and the hole and casing filled with a Cardium
compound to prevent moisture penetration into the borehole. The purpose of the casing
was to prevent the obstructions against the side of the hole. This probe acts as a datum
for the measurements. A surface pate was placed next to the GMS and changes of its
level were measured using an automatic level. An accuracy of ±0.1 mm was achieved
for ground movements. In this method, the top soil movement is measured in reference
to the bottom level of GMS. Hence, GMSs with various probe lengths were used to
measure soil movements within different depths.
Figure 2-13: Ground Movement Stations (GMS) used in Swinburne's study in the 1970s' (Washusen, 1977)
In addition to the ground and slab movements, soil moisture changes were also
measured using hygrometers. The hygrometers consisted of WESCOR thermocouple
probes to measure suction which were placed at 500 mm intervals in a borehole with
compacted clay fill, as shown in Figure 2-14. These probes were installed in open areas
Precise levelling cap Surface plate
Ground movement probe
100mm diameter hole filled with cardium compound to prevent moisture penitration
Protective casing
37
and beneath the slabs. Soil pressure transducers were also installed to determine the
tendency of slabs to lift off due to soil swelling. In this case, before casting the slab, the
soil beneath the slab was levelled, and the transducers were attached to the polythene
moisture barrier between slab and supporting soil. The transducers measure the changes
of bearing pressure when the soil is moving, and the slab is lifting off.
Figure 2-14: Hygrometers used in Swinburne's study in the 1970s' (Washusen, 1977)
Reports of this study identified certain differences in hygrometer results and laboratory
measurements. These differences may be attributed to a number of reasons including
smaller samples used in laboratory measurements, high sensitivity of hygrometer
probes, damages during installations and dissimilarities in compacted soils in borehole
and laboratory samples.
The slab movements were monitored regularly at different sites and the deflected slab
contours were presented. The rainfall and evaporation data were obtained from nearby
Probe leads Metal cover
100mm diameter borehole
Bentonite clay plug moisture barrier (approximately 50-75 mm thick)
Compacted clay soil
Hygrometer (psychrometer) thermocouple at 0.5 m intervals
38
weather stations. These field results of slab and soil movements were presented together
with soil moisture, rainfall and evaporation data (Washusen, 1977). For example, in the
Sunshine site, approximately 20% of the surface moisture change and subsequent
ground movements in the range of 50-60 mm were observed between 1974 and 1975.
Overall, this research has provided a comprehensive data set of expansive behavior of
Melbourne soils. The observed mound shapes of the soil beneath slabs were used to
develop a reliable and economical footing design. Indeed, the outcome of this research
has been helpful in developing a standardized procedure of slab design which is
described in the next sections. However, the prediction of soil moisture movements was
not a part of the study in the 1970s and hence hydraulic properties (e.g., soil water
characteristic function, permeability) of those soils, which are essential to investigate
the soil moisture changes, cannot be found in the relevant literature.
2.3.3.2 Expansive soil site monitoring at Newcastle
In the 1990s, a long term research investigation on expansive soil behaviour was
undertaken in Newcastle (Fityus et al., 2004). In this research programme, moisture
changes and subsequent soil movements were monitored in 20 different sites in the
Hunter area, NSW. This extensive research was aimed at assessing the design procedure
used in New South Wales. There are several publications from this research study
which provide the details of monitoring aspects and also the conclusions of the research
(Delaney et al., 1996, Delaney et al., 2005, Fityus et al., 2004, Fityus et al., 1998, Li et
al., 2003b).
During this research study, laboratory investigations were performed to obtain soil
properties of the monitored sites. Atterberg limits, linear shrinkages, particle size
distributions and cation exchange capacities were investigated (Delaney et al., 2005). In
addition to those soil properties, shrink-well index (Iss) values were obtained in order to
compare the monitoring results with AS2870 standard calculations.
In the field monitoring, soil moisture variations were monitored using neutron probe
technique. Therefore, access tubes were installed at the required depth to collect neutron
probe measurements. The ground movements were monitored using probes similar to
GMS, as explained in the previous section. Surface and sub-surface movement
39
measuring probes were installed at different depths. The site monitoring continued from
2 to 7 years.
Characteristic ground movements were estimated based on AS2870 (1996) guidelines
using Iss values. Delaney et al. (2005) concluded that AS2870 predictions are slightly
lower than the probe measurements but do not considerably under predict the ground
movements. However, some sites showed more than 30 mm surface movement
difference over the predictions. The movement probes at intermediate depths provided
important conclusions. On average, each of the soil layers of depth of 0-0.5 m, and 0.5-
1.0 m contributed 30% to the total movement. Soils at 1.0-1.5m and 1.5m to below
layers contributed 20% each. However, this is dependent on soil type and moisture
changes. The depth of variation of soil moisture was specified in 1996 edition of the
standard as 1.5 m for the Newcastle area. According to Delaney et al. (2005), this limit
causes an under estimation of ground movement due to avoiding about 20% of
contribution from soils below 1.5 m. The profiles indicate that the moisture change
occurred down to about 2.5 m within the monitored period. However, this depends on
the climate conditions of those sites during the monitoring. Therefore, these
observations may not represent the behavior during a life span of a structure and,
consequently, the characteristic ground movement calculations may differ from the
measurements.
This research study provides valuable information on soil moisture and ground
movement monitoring. The details of experimental and analytical investigations given
about neutron probe technique have been presented (Li et al., 2003a, Li et al., 2003b).
However, similar to Swinburne’s research programme, described in the previous
section, the modelling of soil moisture changes was not the primary objective of the
Newcastle study and therefore, some of the required soil properties are not available.
2.3.3.3 Investigation of buried pipes in expansive soil
Recently, an extensive research programme on the expansive behaviour of Melbourne
soils was undertaken in Monash University. The specific aim of the study was to
investigate the effects of climate and soil interaction on buried pipes in expansive soils.
Laboratory and field investigations, together with finite element modelling, were
performed in this research and the details have been previously described (Chan et al.,
40
2007, Chan et al., 2010, Chan, 2014, Kodikara et al., 2013, Rajeev et al., 2012, Rajeev
and Kodikara, 2011).
Two major sites were monitored during this study in Altona North and Fawkner. These
sites were nature strips where service pipes were installed beside the roads beneath the
nature strip. The soils of those sites were mainly typical basaltic clays that continued to
bedrock at about 2 m depth. Basic properties of the soils were investigated at different
depths. In addition, this comprehensive data set includes specific properties. For
example, soil water characteristic curves and hydraulic conductivity functions were
developed for the soils at various depths. Thermal properties required to develop finite
element models to study the soils effect on service pipes were also determined. This
includes thermal conductivity and specific heat capacity functions at different depths.
The field monitoring includes soil moisture, ground movement and temperature
monitoring together with pipe pressure and strains. The soil moistures were monitored
using neutron probe technique similar to the Newcastle study. Custom-built model 4000
rod extensometers, shown in Figure 2-15, were used to monitor soil movement. This
system is commonly used in measuring deformations in tunnelling, underground mining
and dam construction. These rod anchors can measure movements with ±0.1 mm
accuracy (HMA, 2014) and were installed at different depths starting at 400 mm from
surface. Moreover, weather stations were built on each site to collect critical climate
parameters including rainfall, evaporation, humidity, solar radiation, wind speed etc.
Importantly, the surface movements were not measured. The rod anchors used in this
study are very sensitive and can be damaged due to higher movements in expansive
soils. In fact, in this study, the rod extensometer installed in Fawkner site had some
problems and the movements were not able to be captured.
41
Figure 2-15: Model 4000 Borehole Rod Extensometers (HMA, 2014)
The soil moisture and temperature variations were modelled using Vadose/w software
(Vadose, 2013). Figure 2-16 shows the measured and predicted soil moisture in Altona
North during the period of monitoring. This suggests that the model can predict trends
of soil moisture changes against variations of climate conditions.
Figure 2-16: Measured and predicted soil moistures at 300 mm depth in Altona North (Chan, 2014)
42
Most of the conclusions of this buried pipe study were published after 2012 and hence
they were useful at the middle stage of this doctoral research. Even though this study
provides a comprehensive approach for predicting moisture changes in expansive soils,
the variations of soil moisture or suction profiles with respect to long-term climate
conditions have not been considered. However, the collected data, implemented
procedures and the results of this study is further used to investigate the soil moisture
profile variation and subsequent ground movement predictions described in Chapter 7
of this thesis.
2.3.4 Forensic investigations
In addition to the research investigations related to expansive soil behaviour described
in above sections, there have been a number of forensic investigations performed on
damaged houses. According to the media, more than 4300 houses recorded damage after
the drought-breaking rainfall in Melbourne (THE-AGE, 2014a). Most owners of those
damaged homes have relied on expertise in geotechnical and/or structural investigations
to determine the cause of the damages before taking further legal actions.
The forensic investigations were undertaken with a senior geotechnical investigator,
Dominic Lopes, who is also a member of the adversary panel of this research
programme. The author accompanied Dominic Lopes to observe investigations of some
damaged houses. According to the personal communication with him, most of the
damages have occurred due to more than one cause of abnormal moisture changes in
soil beneath footings.
A typical forensic investigation consists of inspecting soil moistures near the damaged
area using samples collected by manual drilling (e.g., beneath the footing at heaved or
settled external walls), taking level measurements of deflected floor slab to develop
contour plots, investigating pipe failures, investigating the possible effects from nearby
trees (existing and already removed trees), the gardening around the houses and
inspecting the design reports of the house. Even if an expert uses these several aspects
in an investigation, it is difficult to ascertain all combinations of reasons for the
abnormal moisture changes. Figure 2-17 shows an example of this difficulty. The
damaged house shown in this figure was less than 5 years old when cracks appeared.
After an extensive investigation, the footing under the damaged wall was under-pinned
43
after addressing the cause of moisture change in 2012. However, the cracks further
propagated over the next two years. In a similar case, Figure 2-18 shows the floor
contours have changed due to the progression of differential movements within a period
of one year, after taking remedial action. These incidents emphasize the importance of
preventing possible causes of abnormal moisture conditions and considering certain
allowances for them at the design stage.
Figure 2-17: Propagated cracks on wall even after remedial actions were taken (A house in Taylors Hill)
Figure 2-18: Contours showing deviations from assumed planar initial condition (in mm) of a damaged house in Wyndham Vale measured over a year
44
The outcomes of these forensic investigations are very useful in identifying weaknesses
in construction, design and maintenance of houses which excessive damages.
2.4 AS2870 FOOTING DESIGN PROCEDURE
Research studies on expansive soils commenced in the early 1950’s in Australia.
Aitchison and Holmes (1953) investigated soil suctions and ground movements and
examined the compatibility of the relationship between soil moisture and movement in
clay soils. Swinburne’s major research study described in section 2.3.3 was followed by
further investigations on designing of footings on clay soils by Walsh (1978) and
Mitchell (Mitchell, 1979, Mitchell, 1980, Mitchell, 1984b). These research efforts led
to the establishment of a standard design for residential footings in Australia called
AS2870, which was first published in 1986. Later, two revised editions were published
in 1996 and 2011.
The standard provides a simplified approach to calculate characteristic surface
movement (ys) . AS2870 classifies the expansive soil potential of a site based on the
magnitude of ys. The ys indicates the probable ground settlement or heave within the
design life, which is considered as 50 years for residential structures. AS2870 describes
ys as a function of instability index (Ipt), soil suction at ground surface (∆U) and the
design depth of suction change (Hs), as shown in Equation 2-6. In general, a suction
profile has a champagne flute shape as shown in Figure 2-19. In the Standard, a suction
profile is considered to be triangular and it is defined using ∆U and Hs. The ∆U and Hs
values depend on soil type and climate conditions, as shown in Figure 2-19. The
Standard also provides some typical values of Hs for certain locations in Australia. The
expected vertical movement of a soil layer of thickness ‘h’ is calculated and then the
total surface movement is obtained as the summation of each layer movement up to Hs.
Ipt, used in Equation 2-6, is considered a constant for a particular soil type (layer) which
accounts for vertical strain per unit suction. The ∆U is in units of suction (pF) and the
‘h’ is given in millimetres, hence ys is in millimetres.
ys = ∑(Ipt × ∆U × h)
Hs
0
…..…………………………………………… Equation 2-6
45
Figure 2-19: Typical wet and dry suction profiles in different Australian regions (Walsh and Cameron, 1997)
The footing design procedure described in AS2870 is based on site classification.
AS2870 (1996) classifies the sites from slightly reactive to extremely reactive using ys.
Highly reactive sites are further divided into H1 and H2 in AS2870 (2011). Table 2-4
shows the site classification given in AS2870 (2011).
Table 2-4: Site classification by characteristic surface movement (AS2870, 2011)
Characteristic Surface Movement, ys (mm)
Site Classification
0 < ys≤ 20 S
20 < ys≤ 40 M
40 < ys≤ 60 H1
60 < ys≤ 75 H2
ys> 75 E
Areas with more than 3 m suction change depths are categorized as deep seated
moisture variation sites and further classified as S-D, M-D, H-D and E-D.
46
Walsh (1978) developed a method to design footings on expansive soil using idealized
mound shapes. The mound shapes are defined by edge moisture variation distance (e)
and differential mound movement (ym). There are two different mound shapes identified
as centre heave and edge heave. Walsh (1978) suggested that ym can be taken as 0.7ys in
centre heave condition whereas 0.5ys in edge heave condition. The requirements of
moment, shear and stiffness are calculated using these ym and e values.
Mitchell (1979) also developed another method to design footings on expansive soils
using a similar approach. He also suggested idealized mound shapes. However, in
Mitchell’s (1979) method ym is taken as 0.7ys for both centre heave and edge heave
conditions. He suggested equations for e distance and depth of embedment of edge
beams using Hs and ym. These values are then used to obtain moment capacity
requirements of the footing.
AS2870 (1996 and 2011) design procedure was derived from both Walsh (1978) and
Mitchell (1979) methods and provides suitable footing types according to the site
classification in the deemed-to-comply provisions. However, it also guides design of
footings for any site classification using engineering principles.
According to the approach described above, the site classification based on ys
calculation is the most significant aspect in designing footings for houses. Therefore,
the calculation procedure of ys needs to be carefully investigated together with the
sensitivity of the associated assumptions. The following section provides the
background of ground movement calculation used in AS2870.
2.4.1 Characteristic ground movement of expansive soil
The quantitative estimation of movement in expansive soil is important in the design of
footings. Since the stress state of the soil is considered in estimating volume changes,
suction has been the commonly accepted soil parameter to obtain the quantitative
measures (Fratta et al., 2007, Mitchell, 1979, Mitchell and Avalle, 1984, PTI, 2004,
Matyas and Radhakrishna, 1968). Soil suction is defined as the potential of undergoing
a change in moisture content (Mitchell, 1984). It is measured as a negative pressure and
expressed in kPa but the conventional units of expressing suctions measurements is pF
(Schofield, 1935). More details on soil suction are given in the next sections of this
chapter.
47
The gradient of SWCC, which is the moisture characteristic (c), is shown in Equation
2-7 where Δw is the change in moisture content and Δu is the change in suction
(Mitchell, 1984b).
𝑐 =Δw
Δu ………………..…..…………………………………………… Equation 2-7
The moisture characteristic depends on the composition of the soil. The higher the clay
content of the soil, the higher its moisture characteristic (Mitchell, 1979). The “c”
values can be used to replace the change in water content in soil in terms of suction.
Mitchell and Avalle (1984) provide a comprehensive description on estimating the free
surface movement of expansive soils in terms of the fundamental concepts associates
with soil suction. They used the saturated soil theory to develop an explanation. The
volumetric strain of the soil can be calculated (Equation 2-8) in terms of void ratio (e),
specific gravity (Gs) and Δw. “V” is the volume of soil and “ΔV” is the change of the
volume. The compressibility factor “f” is to account for the ratio of volume change to
moisture content change (Mitchell, 1984b).
ΔV
𝑉= 𝑓
Δe
1 + 𝑒= 𝑓
𝐺𝑠 × Δw
1 + 𝑒 …………………………………………… Equation 2-8
By introducing a lateral restraint factor (g) to account for the effects from surrounding
soil and the shrinkage cracks during the dry period, the volumetric strain can be
converted into vertical strain as given in Equation 2-9.
𝑔ΔV
𝑉= 𝜀𝑣𝑒𝑟𝑡 = 𝑔𝑓
𝐺𝑠 × Δw
1 + 𝑒 ………………………………………… Equation 2-9
The change in soil moisture given in Equation 2-9 can be replaced by suction using
Equation 2-7 and the moisture characteristic. It is shown in Equation 2-10.
𝜀𝑣𝑒𝑟𝑡 = [𝑔𝑓𝐺𝑠 × 𝑐
1 + 𝑒 ]ΔU …………………………………………… Equation 2-10
48
Rahardjo and Leong (2006) experimentally showed that for a particular soil type (with
constant void ratio and specific gravity) the strain of the soil is proportional to the
suction change and a constant called “Instability index” has been introduced to represent
the linear relationship. It is similar to the constant shown within the brackets in
Equation 2-10. The instability index is denoted by “Ipt”. A further description of this
constant is given in section 2.4.2.3. The Equation 2-10 can be used to obtain the vertical
movement of a certain soil layer of Δl thickness and therefore the free surface
movement (y) can be calculated from the summation of each layer movements down to
the depth of suction change (Equation 2-11).
y = Σ [ 𝐼𝑝𝑡 × ΔU × Δl ] ……………………………………… Equation 2-11
This equation is similar to the Equation 2-6 which is used in AS2870 to calculate
characteristic ground movement.
Mitchell and Avalle (1984) provide clear evidence that Equation 2-11 predicts the free
surface moment with good agreement. They have measured the Ipt by using core
shrinkage and suction tests. The free surface has been measured together with field
suctions. The depth of changing suctions has been decided by the suction profiles
between the considered time intervals and then the free surface movement has been
calculated using Equation 2-11. Figure 2-20 shows the comparison between
measurements from O'Halloran Hill area in Adelaide and the predicted free surface
movements.
49
Figure 2-20: Comparison between measured and predicted free surface movement in O'Halloran Hill, Adelaide (Mitchell and Avalle, 1984)
This procedure has been widely accepted and experimentally supported by different
researchers (Rahardjo and Leong, 2006, Fratta et al., 2007, Mitchell, 1979, Cameron
and Walsh, 1984, Cameron, 1989, Walsh and Cameron, 1997). AS2870 implemented
the procedure explained in Mitchell and Avalle (1984) to calculate the characteristic
surface movement (ys), which is given in Equation 2-6. It is important to investigate the
influences of factors used to calculate ys which are described in the next sections.
2.4.2 Factors affecting ys calculation
2.4.2.1 Design Depth of Suction Change (Hs)
Moisture content of the soil varies with the depth and reaches an equilibrium value at a
certain depth (Fityus et al., 2004). Since the suction is related to the soil moisture
content, the suction throughout the depth can also be identified as a gradual variation
that follows a similar trend.
Figure 2-21 shows typical moisture variations for open ground and under a covered slab
given in Nelson et al. (2001). The profile ‘A’ shows the moisture content variation of
uniform soil for open ground in a dry climate. The moisture content varies from ground
surface up to the depth ‘Zs’ and after that, the equilibrium moisture content value
continues. Above the depth of ‘Zs’ the moisture content varies with the depth and the
time. The changes of suction in soil above the depth ‘Zs’ is affected by various
50
environmental factors including precipitation, evaporation, transpiration and the
location of water table depth (Lu and Griffiths, 2004).
When a slab is placed on expansive soil, the slab becomes a moisture barrier and the
suction profile differs from the typical suction profile of an open ground, which is
shown in profile “B” in Figure 2-21. The soil beneath the slab edge is affected by the
environmental influences at the open ground, and the moisture changes are gradually
reduced towards the slab centre where it is normally assumed that the soil moisture is
more stable. During the dry season, top soil is desiccated and the top soil layers can
have moisture contents lower than the equilibrium value. During the wet season the top
layers are influenced by wetting due to precipitation and can have higher moisture
contents than the equilibrium value. Therefore, during the summer and winter season,
the profile varies around ‘B’ and the profiles ‘C’ and ‘D’ represent the corresponding
variations at two extremes. The slab prevents the moisture loss due to environmental
factors and hence the moisture content reaches an equilibrium value at a depth lower
that Zs.
Figure 2-21: Idealized water content profile (Nelson et al., 2001)
51
The wet and dry suction values usually change rapidly with depth (Fityus et al., 2004,
Fityus et al., 1998). Mitchell (1979) assumed a “trumpet” shaped suction profile (Figure
2-22) to derive the concept of swelling of expansive soil. However, the wet and dry
suction variation is approximated to a triangular shape in AS2870, as shown in Figure
2-23.
Figure 2-22: Theoretical suction profiles given in (Mitchell, 1979)
This triangular shape is defined using surface suction change and the depth of suction
change. The depth of suction change is influenced by many factors including climate,
depth to the groundwater table, type and amount of clay minerals, soil profile, and
vegetation. Different researchers defined the depth of suction/moisture variation of soil
using different terminologies (Hamilton, 1969, Nelson and Miller, 1992). Nelson et al.
(2001) summarized these terminologies such as depth of potential heave, depth of
seasonal moisture variation, depth of wetting, active zone, and depth of suction change,
as illustrated below.
The depth of potential heave defines as the depth at which the overburden vertical stress
equals or exceeds the swelling pressure of the soil (Nelson et al., 2001).
The depth of seasonal moisture fluctuation is defined as the depth of soil in which the
soil moisture content of an open area varies seasonally due to climate conditions at the
ground surface (Nelson et al., 2001).
52
The depth of wetting is defined in Nelson et al. (2001) as the depth in which the soil
moisture increases due to introduction of water from external source due to capillary
action of soil neglecting the evapotranspiration. In a case of cracking clay soils, this
depth can be abruptly increased by the presence of cracks during dry period where rain
water can easily flow in.
Since the shrink-swell behavior of the expansive soil depends on the suction variation as
well as the overburden pressure; the depth of suction variation related to residential
footing design is slightly different from the definitions based purely on moisture
fluctuations. A more sensible definition is given in Nelson et al. (2001), termed “Active
Zone” which is the depth of soil beneath a structure that contributes to the actual heave.
The actual heave may occur due to various climate conditions including extreme events.
The depth of active zone observed in normal seasonal climate conditions is called
‘Design depth of suction change (Hs)’ in AS2870.
The Hs is also affected by the location of bedrock and the ground water table (AS2870,
2011). Based on the location of bedrock and ground water table, the typical values
appropriate to the particular area need to be adjusted, as shown in Figure 2-23. Since,
the suction below ground water table is constant at saturated value; the suction profile
must be modified if the water table is encountered within the defined Hs of the area
(Figure 2-23). If the bedrock is encountered within the specified Hs, the suction profile
will remain same. However the calculation of free surface movement is only considered
up to the depth of bedrock, because Ipt of bedrock is insignificant.
Figure 2-23: Simplified suction profile and the effect of bedrock and water table on ΔU and Hs(AS2870, 2011)
53
2.4.2.2 Suction Change at Surface (∆U)
The difference between wet and dry suctions at the surface is defined as surface suction
change (∆U) (Walsh and Cameron, 1997). AS2870 (2011) provides a single value of 1.2
pF for all specified locations in Australia. However, higher ∆U values have been
recorded in some field monitoring (Fityus et al., 1998, Fityus et al., 2004). The
approximation of the suction profile into a triangular distribution in AS2870 slightly
underestimates the ∆U (Walsh and Cameron, 1997).
2.4.2.3 Instability Index (Ipt)
The amount of volume change of expansive soil in response to change in suction is
represented by the Instability Index, Ipt. Mitchell (1979) suggested a simple method to
obtain the Ipt using the soil strain measured over a certain range of moisture content and
the moisture characteristic. The method is shown in Equation 2-12.
Ipt =
ΔL
L
Δw×
Δw
ΔU ………..…………………………………………… Equation 2-12
The Ipt depends on the vertical strain of soil per unit change in suction which is defined
by volume change indices. There are number of ways to obtain these indices of soil, as
explained in Cameron (1989).
The core shrinkage test (ASTM-D5084, 2003) can be used to obtain the core shrinkage
index (Ics) by using unloaded shrinkage test. The test uses 38 to 65 mm diameter
undisturbed soil samples which has a length of 1.5 to 2.0 times of its diameter. The test
starts from the in situ moisture content and the initial moisture content is measured from
the sample trimmings. The soil samples are then allowed to air dry for a few days before
being placed in an oven to determine the final moisture content. The strain and the
weight is monitored regularly from the beginning to obtain the stain-moisture curve.
The Ics is calculated for the linear part of the curve using shrinkage strain and the
moisture content difference as given in Equation 2-13.
Ics = ε × c
Δw ………..……………………………………………...…… Equation 2-13
54
“ε” is the shrinkage strain and “c” is the moisture characteristic. The moisture
characteristic can be calculated by measuring suctions during the test or assuming
appropriate values. However, this method does not include the surcharge to
accommodate the effects of load coming from footings.
Another method of obtaining Ipt is using a loaded shrinkage test that considers the
surcharge upon shrinkage. A surcharge of 25 kPa, to account the footing load, is applied
during this test and measures the shrinkage stain and the moisture contents. The loaded
shrinkage index (Ils) is obtained using an equation similar to Equation 2-13.
These two methods require measuring the moisture content and the soil moisture
characteristic by measuring the suctions. However, the shrink-swell test (AS1289.7.1.1,
2003) has bypassed the suction measurements and produced reliable results (Fityus et
al., 2005). Walsh and Cameron (1997) also describe the core shrinkage test and loaded
shrinkage test but recommended the shrink-swell test to obtain the instability index.
The shrinkage strain and the swell strain started at the in situ moisture content of
undisturbed soil sample are measured separately during the shrink-swell test
(AS1289.7.1.1, 2003). The shrinkage strain (εsh) is measured from a shrinkage test that
is similar to the core shrinkage test (ASTM-D5084, 2003) but the moisture contents are
not measured. The swell strain (εsw) is taken from a one-dimensional swell test. This test
is performed using a consolidation cell so that only the vertical strain occurs. A
surcharge of 25 kPa is applied during the swelling process to account for the effect of
the footing. Then, the total strain is calculated from εsh and εsw. The free shrinkage test
accounts for the three-dimensional strain with εsh while εsw is a one-dimensional strain
due to lateral restraint applied from the ring. Those two strain values cannot be added
together without correcting the dimensional inequality. Cameron and Walsh (1984)
concluded that the unrestrained three-dimensional strain of the soil is commonly in 0.3
to 0.6 of vertical strain of the laterally restrained soil. This effect must be
accommodated in the context of the results of the one-dimensional consolidation taken
from the laboratory tests. Therefore, the swell strain is divided by a factor of 2
(Equation 2-14) to convert it to the free swell strain before adding to the shrinkage
strain (AS1289.7.1.1, 2003). This factor has been investigated in many studies
(Cameron, 1989, Leong et al., 2002) and was subsequently accepted for use in AS1289
55
(Fityus et al., 2005). Equation 2-14 shows the estimation of shrink-swell index from εsh
and εsw.
Iss =
εsw
2+ εsh
1.8 ..……………………………………………...…… Equation 2-14
Since the instability index accounts for the strain per unit suction, the suction change
during the test must be obtained. However, an advantage of using the shrink-swell index
to obtain Ipt is to bypass the measurement of suction. Since this test considers the total
stain of the soil sample from saturated condition to the oven dry condition, an
approximated value can be used to obtain the suction change during the volume change
process. The researchers in this area suggest the use of the suctions corresponding to the
wilting point and saturation point of the soil (Fityus et al., 2005). This idea is based on
the notion that significant volume change will not occur beyond the limits of the wilting
point and the saturation point of soil. Observations suggest that the wilting point suction
varies around 4.2 pF for clay soil (Cameron, 2001, Wray, 1998). Fredlund and Rahardjo
(1993) argued that the total suction of saturated soil is about 2.2-2.5 pF. Therefore, the
suction change during the total strain of the shrink-swell test has been assumed to be 1.8
pF for all soils (Equation 2-14). In the hand book of AS2870, Walsh and Cameron
(1997) specified that the shrink-swell test is the most appropriate soil reactivity index to
obtain Ipt because it generates a significantly lower coefficient of variation compared to
other tests. It is assumed that the Iss is a constant irrespective of the starting moisture
content of the undisturbed soil sample (AS2870, 2011). However, there is anecdotal
evidence from forensic investigations demonstrating that Iss values can be obtained that
are different to the designed values due to changes to the in situ moistures. The changes
of Iss affect the estimation of ground movement. Therefore, this issue has been further
investigated using experimental results by the author and it is described in Chapter 3.
Both accurate research techniques and practical engineering procedures need to be
considered to derive the instability index from the soil reactivity indices. The soil
beneath the surface cannot swell freely because of lateral restraint by the surrounding
soil and the surcharge due to the weight of the above soil layers. During the shrinking of
clay soil, the lateral restraint is not affected and the cracks will propagate to a certain
56
depth. The probable crack depth depends on many factors including the soil type,
shrinkage amount, moisture content and depth of soil layers. During the swelling
process, the soil can freely swell until the cracks close and then the three-dimensional
swell ceases as the lateral restraint is initiated by the adjacent soils. Then, the swell
would occur more over the vertical direction and will be controlled by the surcharge
pressure.
Ipt is derived from reactivity indices by modification by a specific restraint factor (α)
depending on the site condition (AS2870, 2011). The restraint factor accounts for the
effect of cracks and the surcharge by assuming that, below 10 m depth, no soil
movement occurs. Hence, ‘α’ at depth ‘Z’ from the ground surface is defined by
Equation 2-15 for the uncracked zone (AS2870, 2011). The factor, α is taken as 1 for
the cracked zone to represent zero restraint.
α = 2.0 −Z
5 ……...……………………………………………...…… Equation 2-15
Figure 2-24 illustrates the use of Equation 2-15 to obtain Ipt from the various Iss values
at different soil depths. Since the soil in the uncracked zone is highly affected by the
lateral restrain from the surrounding soil, the instability index has been increased by the
“α” factor.
Figure 2-24: Sample calculation of Ipt from different Iss values for cracked soil
Even though AS2870 considers these factors of soil moisture changes and reactivity to
estimate the ground movement, the outcome of the standard procedure has certain
Iss = 3%
Iss = 4%
Iss = 4.5%
Iss = 6%
1 m
1 m
1 m
2 m
α = 1
α = 1
α = 1.5
α = 1.2
Ipt = 3%
Ipt = 4%
Ipt = 6%
Ipt = 7.2%
Crack
depth
= 2 m
57
limitations. Therefore, homeowners have been constrained to a particular way of usage
and maintenance requirements to prevent abnormal moisture changes beneath footings.
Those limitations are described in next section.
2.5 LIMITATIONS OF SOIL MOISTURE PREDICTIONS
2.5.1 Effectiveness of AS2870 design procedure with changes in TMI
The estimation of soil moisture change and ground movement specified in AS2870 is
principally based on parameters of suction profile; ∆U and Hs. The standard procedure
defines them based on the climate condition of the area. Climate condition is classified
by Thornthwaite Moisture Index (TMI) and is correlated with Hs. In addition to this
correlation, the standard includes a climate zone map of Victoria, which enables the
Victorian designers to pick the TMI of the location and then the corresponding Hs. The
climate zone map given in the 1996 edition of the standard was a part of Australian
climate map developed by Aitchison and Richards (1965) based on climate data from
1940-1960. The climate data suggest that there has been a significant change in climate
condition in Australia in the last few decades and hence past climate data may no longer
represent the current or future conditions (Hughes, 2003, Murphy and Timbal, 2008,
Smith et al., 2009). AS2870 was refined in 2011 and has incorporated some changes to
the TMI ranges. In contrast, the climate zone map of Victoria has remained identical to
the previous version. Since the climate continues to change, further modifications to
AS2870 will be required and this will create complications in designs. On the other
hand, several changes to the normal weather pattern was observed recently and more
frequent extreme climate events are expected (BoM, 2012). Therefore, the dependence
on past climate data in designing footings for 50 years of lifespan appears to be
deficient.
Moreover, the effectiveness of TMI to correlate the soil moisture changes has been a
concern because it relies on many assumptions and different definitions (Karunarathne
et al., 2012). Indeed, there exists various ways to calculate TMI due to different
definitions of the associated parameters. Furthermore, researchers have used different
numbers of years to calculate the average TMI from yearly calculations and hence their
conclusions on TMI and soil moisture correlations cannot be compared (Chan and
58
Mostyn, 2008, Fityus et al., 1998, Fox, 2000). This issue was critically investigated in
this study, and will be described in the next chapter of this thesis.
In summary, the AS2870 procedure of estimating soil moisture changes, and hence
ground movement, requires review in response to uncertainties in the normal climate
condition. Moreover, foundations in accordance with AS2870 require tight maintenance
to maintain “normal” soil moisture condition and prevent damage to the super structure
as described in next section.
2.5.2 Standard design outcome and home owner’s expectations
Design is based on past climate conditions and therefore soil moistures must be
maintained within the limits of the corresponding normal condition. However, many
influences can create abnormal moistures beneath footings. For example, trees can
absorb moisture from the soils within the root zone and create unexpected dry
conditions. Hence, differential settlements can be observed due to existing trees within
their influential zone. Gardening around the house can also lead to increase moisture
due to watering. Similarly, sloping ground towards the footing leads to increase in the
water available for infiltration. Pipe breaks or leaks can also increase soil moisture.
AS2870 is deemed to provide a reliable and economical footing design. The footings
should therefore be able to tolerate the ground movements to transfer an acceptable
effect into the superstructure. However, AS2870 (2011) provides information about
expectable cracks in walls and floors of houses even if they are correctly designed based
on the AS2870. It stated that cracks less than 1 mm in width do not need to be repaired
whereas less than 5 mm wide cracks can be easily filled. The author inspected some
damaged houses with cracks up to 30 mm in width. Some home owners do not tolerate
that a properly designed and constructed house can have the tolerable cracks stated in
AS2870. Since these cracks are mostly caused by differential movements, a better
system to predict soil moisture changes and estimate ground movement is vital to
provide homeowners with different performance options depending on their
expectations and financial investment.
59
2.6 IMPORTANCE OF A ROBUST METHOD OF ESTIMATING SOIL MOISTURE
CHANGES
Since climate is a parameter varying within periods shorter than lifespans of houses, the
footing design must be based on expected climate conditions. Future climate condition
can be predicted based on various scenarios and hence an effective footing design can
be achieved by using the following options.
I. A design based on predicted future climate condition within the lifespan
II. A design based on probability of severity of extreme climate events
Both approaches require a reliable method of estimating future soil moisture changes
due to climate conditions. Such a method will overcome the limitations of the standard
described in previous section, which is based only on historical data.
A reliable prediction method of soil moisture changes will enable the consideration of
soil moistures and related ground movements due to various climate scenarios including
different frequencies of extreme events. Hence, several footing designs can be
introduced to withstand different severities of climate. This also allows the study of
damage on superstructure due to different climate scenarios. Moreover, a robust
prediction system of soil moisture will facilitate the study of the various causes of
abnormal moistures. This PhD research has focused on developing a better prediction of
soil moisture changes due to climate conditions.
2.7 SUMMARY
This chapter describes the features of expansive soils and the investigations of
expansive soil behaviour in Australia. Expansive soils consist of layered structures that
are formed by platelets of clay minerals. The distribution of charges in these platelets
attracts water, which increases the gap between layers. This phenomenon causes the
volume change in expansive soils. Therefore, moisture changes represent the primary
cause of volume changes in clay soils. Such expansive behaviour can be characterized
quantitatively and qualitatively using several soil index tests.
Since these volume changes can lead to ground movement that can damage lightly-
loaded structures that are built on such soils, much research has been carried out to
investigate moisture-induced ground movements. Most of these studies aimed to
60
develop reliable footing designs that could withstand expected ground movements.
These investigations led to the development of the standard for residential footing
design in Australia, termed AS2870, which was first published in 1986. This Standard
was updated twice, in 1996 and 2011, but remains largely unchanged in relation to the
design philosophy and approach. Specifically, there are certain issues in considering
climate effects on footing design in the AS2870 including the use of historical climate
data. Moreover, there has been some severe climate condition in Victoria, Australia
which led to significant damage to some houses. It is therefore imperative that we
review the Standard procedure of estimating soil moisture changes and ground
movement.
A number of studies have informed the management of impacts of expansive soil
behaviour on structures. In the 1970s, a comprehensive study was undertaken at
Swinburne University that focused on the performance of residential footings built on
expansive soils at various places around Melbourne. The hygrometer mechanism was
used to monitor soil moisture changes whereas ground movement stations were used to
measure surface movements. Another field investigation was undertaken at the
University of Newcastle, to investigate the moisture and ground movements in an open
ground and under a flexible cover. The neutron probe technique was used to monitor
soil moisture changes while surface and sub-surface movement were monitored using
probes. This research revealed the rainfall variation, seasonal ground movements and
the corresponding variation of mound shape beneath the flexible cover. Other, more
recent, research was undertaken at Monash University to determine the performance of
buried pipes in expansive soils. The neutron probe technique and rod extensometers
were used to monitor moisture and ground movement, respectively. Soil moisture
changes in response to climate conditions were modelled in this research using field
measurements taken from two expansive soil sites in Melbourne.
Even though the above studies were not focused on estimating soil moisture changes in
expansive soils, they provide details of applicable mechanisms in monitoring and
modelling the expansive soil behaviour. Furthermore, they emphasize the effect of
climate conditions for the design of footings for light-weight structures. The next
chapter describes the results of an extensive investigation on climate effects on footing
design together with a critical examination of the current procedure adapted in AS2870.
61
3. EFFECTS OF CLIMATE ON FOOTING DESIGN
3.1 INFLUENCE OF CLIMATE CONDITIONS ON SOIL MOISTURE CONTENT
Soil and climate interaction is the natural mechanism by which moisture enters and
leaves the soil. Figure 3-1 shows the hydrologic cycle which explains how the moisture
content of the soil is influenced by the climate. Soil receives water mainly from
precipitation. Certain amounts of the received water infiltrate the soil while the
remainder runs off along the surface and adds to water bodies. Water then evaporates
directly from the surface. The infiltrated water also returns to atmosphere through
upward diffusion and transpiration. These processes depend on climate conditions,
including humidity, temperature and the wind. In addition to these climate parameters,
soil moisture changes also depend on other factors, including vegetation, permeability
of the soil, ground slope and human interactions.
Figure 3-1: The hydrologic cycle (NWS, 2010)
Rainfall, snowfall and dewfall are the main components of precipitation which provide
moisture into the soil. However, rainfall is the prominent component. It has different
patterns throughout the year. The moisture content of exposed surface soil follows a
62
similar pattern while the moisture content of subsequent layers depends mainly on the
permeability of the soil. If the precipitation rate exceeds the hydraulic conductivity of
the soil, then the surface layers become saturated and the excess water ponds on the
ground or runs off towards the downslope. However, the presence of cracks can
increase the amount of water infiltration and recharge the deeper soil layers.
Furthermore, runoff is also reduced by soil cracks.
It is estimated that more than 75% of the precipitation on land infiltrates and affects the
soil moisture content (Maps, 2015). Once the water infiltrates into the soil, it can
redistribute within the subsequent soil layers. The depth of the soil to which the
moisture content is prone to change significantly is called the “active zone” (McKeen
and Johnson, 1990). The redistribution of moisture within the active zone is influenced
by many different processes. The main process is exfiltration, which withdraws soil
moisture. Exfiltration includes evaporation from near surface soil and transpiration from
vegetation. These two processes are collectively called “evapotranspiration” (Dingman,
2002) The soil moisture transforms from a liquid state to a gas state during these two
scenarios. Evapotranspiration depends on the types of vegetation and their distribution.
For example, trees have different canopy types and root systems which govern the
amount of water they suck from the soil and transfer to the environment. If water is
deficient, vegetation is sparse and if more water is available, then trees grow closer
together (Thornthwaite, 1948).
Other redistribution processes include capillary rise, recharge and interflow (Figure
3-2). Capillary rise is the movement of moisture from a saturated zone to an unsaturated
zone due to capillary action of the pore spaces. Recharge is the movement of moisture
from an unsaturated zone into the ground water storage. Interflow is the flowing of
water through the soil layers which can only occur in downslopes (Dingman, 2002).
63
Figure 3-2: Redistribution of the soil moisture (Dingman, 2002)
Russam and Coleman (1961) investigated the interaction between climate and soil
moisture and provided a comprehensive data set. They considered the effect of climate
cycles on soil moisture condition under airfields in different countries including
Australia, England, Singapore, Sudan, Egypt, and Rhodesia. The climate effects on soil
moisture were considered in terms of moisture surplus and deficit, as defined by the
Thornthwaite Moisture Index (TMI). A more detailed description of the TMI is given in
the next sections of this chapter. Russam and Coleman (1961) divided the areas they
investigated into three categories, based on surplus and deficit, namely Wet, Dry and
Intermediate. The wet areas were defined as having zero deficits throughout the year
while the areas with zero surpluses throughout the year were defined as dry areas. Areas
with zero surpluses for certain months and zero deficits for other months were termed
intermediate areas. Figure 3-3 shows the monthly variation of surplus and deficit in
different sites examined by Russam and Coleman (1961). The figure also shows how
the soil moistures vary and the related processes due to the variation of the balance
between precipitation and evapotranspiration.
The authors found that areas in the wet category experience little seasonal change in
volume and moisture condition. Hence, moisture conditions under the pavements would
be expected to differ little from those in exposed soil. Areas in the dry category consist
of deserts and semi deserts where seasonal changes in soil moisture content are likely to
64
be very small. It was concluded that if the water table is maintained within 25 feet of the
ground surface, it will dominate the moisture regime of the subgrade in dry areas.
Otherwise, climate conditions govern the soil moistures.
Figure 3-3: Variation of monthly rainfall and evapotranspiration with soil moisture conditions in various sites (Russam and Coleman, 1961)
65
In the intermediate areas, soil moisture recharge occurs in certain rainy periods and a
surplus can be observed if more precipitation is received after the soil reached the field
capacity. The volume increase of expansive soil can be observed in this situation.
However, if the precipitation rate becomes less than the evapotranspiration rate, then the
recharged moisture is utilized to balance the additional requirement and the expansive
soils undergo volume reduction. Further, reduction in precipitation would lead to water
deficiency in the soil.
This reflects the influence of characteristics of the climate cycles on moisture and the
volume change of soil. Hence, the impact of climate must be a vital parameter in
designing lightweight structures built on expansive soils.
3.2 CLIMATE CONSIDERATION IN AS2870
Climate condition drastically affects the soil moisture change, as described in the
previous section. Expansive soils undergo heave and settlement due to increment and
decrement of the soil moisture, respectively. These soil movements can create
differential movements under footings and they are large enough to cause distress in
lightly loaded structures such as houses and pavements (ACA, 2012, THE-AGE, 2011).
Since about 20% of the surface soils in Australia have been classified as expansive soil
(Richards et al., 1983), climate conditions have a huge impact on residential footing
design in Australia.
The site classification procedure given in AS2870 (2011) takes into consideration the
climate conditions of the area. The standard allows for use of the Thornthwaite
Moisture Index –TMI (Thornthwaite, 1948) to estimate the depth of moisture change.
TMI is a commonly used climate classification index that characterises different climate
conditions from arid to humid.
Since the depth of seasonal moisture variation depends on climate conditions, AS2870
(2011) has categorized Hs values in relation to the TMI of the area. The standard has
given Hs for certain Australian cities, whereas for other areas it may be obtained from
the relationship of Hs versus TMI provided. This relationship is shown in Tables 3-6
and 3-7, and further discussed in section 3.5. The climate zones have been specified
66
based on the TMI ranges. The standard has provided a TMI map of Victoria to facilitate
the identification of the climate zone without using the TMI calculation.
Since the climate effects on footings are considered through TMI, it is important to
review the calculation procedure of the TMI. This calculation is associated with many
uncertainties, which are described in the next sections.
3.3 THORNTHWAITE MOISTURE INDEX (TMI)
The Thornthwaite Moisture Index was introduced by C.W. Thornthwaite (Thornthwaite,
1948) to classify climate conditions. It is a dimensionless index varying from +100 to -
100, which represent the climate conditions given in Table 3-1. TMI is calculated using
two indices called aridity index (Ia), and humidity index (Ih). These indices are defined
by water deficit (D) and run-off or surplus (R) based on a water balance calculation. The
water balance calculation can be performed in various ways, which result in different
values for TMI. Indeed, recent researchers have used different methods to calculate TMI
(Austroads, 2004, Fityus et al., 1998, Jewell and Mitchell, 2009, Lopes and Osman,
2010, Mather, 1978) and this has curtailed the ability to compare their results.
While the primary objective of the TMI was to classify the climate, it has been widely
applied in different areas such as agriculture, hydrology, pavement design and footing
design (AS2870, 2011, Austroads, 2004, Keim, 2010, Philp and Taylor, 2012).
Moreover, recent concerns about climate change and its effects on footing design have
also been discussed in terms of the TMI (Austroads, 2004, Leao and Osman, 2013).
Table 3-1: Climate types together with their TMI limits (Thornthwaite, 1948)
Climate type TMI
A Perhumid 100 and above B4 Humid 80 to 100 B3 Humid 60 to 80 B2 Humid 40 to 60 B1 Humid 20 to 40 C2 Moist subhumid 0 to 20 C1 Dry subhumid -20 to 0 D Semiarid -40 to -20 E Arid -60 to -40
67
3.3.1 Calculation of TMI
Thornthwaite (1948) introduced the TMI in 1948 and later published a number of
papers (Thornthwaite, 1952, Thornthwaite and Mather, 1955, Thornthwaite and Mather,
1957) to provide a clearer understanding of the calculation. According to these
publications, the TMI calculation procedure can be expressed in the flow chart shown in
Figure 3-4. Precipitation and temperature are the main input parameters of the TMI.
Water balance is calculated using those inputs and this provides the surplus and deficit.
The surplus and deficit are then used to obtain Ih and Ia to calculate the TMI.
Figure 3-4: Flow chart of the TMI calculation
3.3.2 Definitions and Assumptions
TMI calculation is associated with various terms that have been defined and modified at
different times. However, certain terms are defined in alternative ways, which has
caused alterations in the calculation.
Precipitation (P), also known as rainfall, is the main soil moisture input.
Evapotranspiration causes soil moisture loss which transfers the water from soil to air
by evaporation and transpiration. Potential Evapotranspiration (PE) is defined as the
amount of water that would be evapotranspired under certain climate conditions given
an unlimited supply of water. However, the amount of water lost from soil in a
particular climate condition is always restrained by the water availability and is defined
as Actual Evapotranspiration (AE).
Precipitation (P)
Mean Maximum
Temperature
Mean Minimum
Temperature
Average
Temperature
Potential Evapotranspiration
(PE)
Water Balance
Surplus (R) and Deficit (D)TMI Aridity index (Ia) and Humidity index (Ih)
Field capacity and initial storage
Latitude of location
68
The TMI calculation generally considers the soil body as a tank, hence the soil moisture
storage (S) is defined as the amount of water held in the soil at any particular time. The
maximum amount of water the soil can hold is called the field capacity (Smax). Based on
the monthly values of P and AE, soil moisture storage changes when monthly P is not
equal to AE and this change in storage is denoted as ∆S.
A number of definitions exist for moisture surplus (R) or runoff. Thornthwaite (1948)
states that water surplus refers to seasonal additions to subsoil moisture and ground
water. Thornthwaite and Mather (1955) defined the moisture surplus as the precipitation
in excess of potential evapotranspiration which occurs when soil is at the field capacity.
Later, Mather (1978) gave a more descriptive explanation that “surplus is the excess
water available to percolate through the soil both as recharge to the ground water table
or as through flow. This amount is P-PE in the months of soil moisture is at the field
capacity. When the soil storage is not at its capacity, no surplus can exist.” These
definitions contain slight differences, which can cause inconsistencies in the water
balance calculation.
Moisture deficit (D) is defined as the additional water that would be necessary to
achieve potential evapotranspiration when the precipitation is not sufficient. Mather
(1978) stated that the deficit is the difference between the water demand in a particular
climate condition and the actual evapotranspiration losses which can be calculated as
PE-AE.
In addition to contrasting definitions, the TMI calculation also includes some
assumptions. To account for the difficulty of water extraction from its adsorbed state in
a soil, Thornthwaite (1948) assumed a surplus of 60% in one season will counteract a
deficiency of 100% in another. The TMI calculation assumes the excess precipitation
(P-PE) that comes after a deficiency period will entirely infiltrate into the soil and
recharge the soil moisture storage until it reaches the field capacity. The excessive P
received when the soil is at the field capacity is becomes a runoff. Therefore, surface
runoff which may occur when the soil is being recharged is not considered, which
frequently happen when the rain falls in high intensity. The Australian TMI map has
also been developed employing the same assumption (Aitchison and Richards, 1965).
69
The next important assumption is the value of field capacity. Chan and Mostyn (2008)
suggested that the Smax depends on the climate and proposed the use of 0 mm for dry, 50
mm for temperate and 100 mm for wet conditions. Even though Thornthwaite and Mather
(1957) specified different values for field capacities based on soil types, most
researchers (Aitchison and Richards, 1965, Jewell and Mitchell, 2009, Russam and
Coleman, 1961) have assumed a constant value over a number of different soil types
and 100 mm has been used commonly. Indeed, Aitchison and Richards (1965) assumed
Smax of 100 mm to obtain the TMI for more than 600 locations to develop the Australian
TMI map.
Another assumption of the TMI calculation relates to the behaviour of soil moisture
storage. Thornthwaite and Mather (Mather, 1978, Thornthwaite and Mather, 1955)
assumed that, when soil becomes dryer, the removal of water from the soil becomes
increasingly difficult and soil cannot extract the same amount of moisture from the
storage. Therefore, the soil moisture storage never becomes zero. In contrast, most of
the recent research (Barnett and Kingsland, 1999, Chan and Mostyn, 2008, Fityus et al.,
1998, Fox, 2000, Jewell and Mitchell, 2009, Lopes and Osman, 2010, McManus et al.,
2004, Mitchell, 2008) has assumed that the soil can provide the required additional
amount of moisture until the storage level becomes zero.
The initial storage (S0) needs to be assumed to perform the water balance in the TMI
calculation. This is the water storage available at the first month of the first year of TMI
calculation. When the calculation is performed over a longer period, the impact of this
assumed value becomes insignificant.
Based on the above definitions and the stated assumptions, TMI has been defined by an
aridity index (Ia) and humidity index (Ih). Ia is a relationship between moisture deficit
and water necessity (Equation 3-1) whereas Ih is a relationship between moisture
surplus and water necessity (Equation 3-2).
Ia = 100 ×D
PE ……...…………………………………………...…… Equation 3-1
70
Ih = 100 ×R
PE ……...…………………………………………...…… Equation 3-2
Thornthwaite (1948) suggests that, PE be calculated using Equation 3-3 for each month
and then the monthly summation is taken as annual PE. The unit of D, R and PE is
centimetres.
PE = 1.6 × (10 × t
I)
a
.………...…………………………………...…… Equation 3-3
‘t’ is the average temperature in a particular month and ‘I’ is annual heat index in a
particular year which is taken as the summation of monthly heat index values (i)
calculated using Equation 3-4. Parameter ‘a’ is calculated using Equation 3-5.
i = (0.2 × t)1.514 .……...……...…………………………………...…… Equation 3-4
a = 6.75 × 10−7 × I3 − 7.771 × 10−5 × I2 + 0.01792 × I + 0.49239 ... Equation 3-5
In Equation 3-3, PE is assumed as a 30-day month for a location with a 12 hour daylight
period. Therefore, it must be multiplied by two factors which account for daylight hours
for the location for a given month (f1) and number of days per month (f2),
f1 =d
12 …………..…...…………………………………………...…… Equation 3-6
f2 =N
30 …………….....…………………………………………...…… Equation 3-7
where ‘d’ is number of hours in a day between sunrise and sunset in a month and ‘N’ is
number of days for the particular month. The value of ‘d’ depends on the location which
can be related to the latitude. Thornthwaite (1948) provided a table to find out “d” at
each latitude for each month of the year.
71
PE is calculated on a monthly basis to perform the water balance and then the
summations of monthly results are used to calculate Ia and Ih annually. The TMI
equation using Ia and Ih is shown in Equation 3-8 (Thornthwaite, 1948).
TMI = Ih – 0.6 × Ia ……………………………………………...…… Equation 3-8
Even though the equations given for PE calculation are widely accepted by most of the
investigations (Austroads, 2004, Barnett and Kingsland, 1999, Chan and Mostyn, 2008,
Fityus et al., 1998, Fox, 2000, Jewell and Mitchell, 2009, Mather, 1974, Mather, 1978,
Mitchell, 2008, Thornthwaite, 1948, Thornthwaite and Mather, 1957), the water balance
calculation has been performed in different ways. Hence, three different methods of
calculation were identified during the critical literature review of this study. The
uncertainties in calculation have resulted in the simplification of the TMI equation to
bypass the calculation of water balance. However, the simplified method also gives
different results. Therefore, based on the definitions and assumptions, four different
approaches have been identified and they are discussed in the next section.
3.3.3 Different methods of TMI calculation
3.3.3.1 Method 1
In 1957, Thornthwaite and Mather published an explanation of the procedures used to
calculate TMI which is denoted as Method 1 in this study (Thornthwaite and Mather,
1957). They developed tables for the water retention calculation based on the
phenomenon of increasing difficulty of water removal from the soil when it becomes
dry. According to their tables, soil moisture storage cannot be empty at any time.
Mather (1978) used these tables to calculate soil moisture storage depending on the field
capacity. Thornthwaite and Mather (1957) proposed Equation 3-9 to calculate change in
soil moisture (∆S) in successive months.
∆S = 𝑆𝑖 – 𝑆𝑖−1 .……...……...…………………………………...…… Equation 3-9
Si and Si-1 are soil moisture storages in the current month and the previous month
respectively as obtained from the water retention tables.
72
Based on the change in soil moisture storage of the current month, actual
evapotranspiration (AE) is calculated using Equation 3-10. The difference between PE
and AE was also explained in Tucker (1955) using a similar equation to that provided
by Thornthwaite and Mather (1957).
AE = PE; when P ≥ PE .…………….………………………...…… Equation 3-10
= P + ∆S; when P < PE
Soil moisture deficit (D) is taken as the difference between PE and AE (Equation 3-11),
while surplus is calculated using P, PE and S, as shown in Equation 3-12.
D = PE − AE .………………...……….………………………...…… Equation 3-11
R = Si−1 + (P − PE)i − Smax ; Only when Si = Smax ...……………… Equation 3-12
These D and R values are then used to calculate TMI from Equations 3-1, 3-2 and 3-8.
Table 3-2 shows the calculation steps for Method 1 assuming 10 cm of field capacity
and 8 cm of initial storage.
Table 3-2: TMI calculation steps in Method 1
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1
PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0
P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8
∆S -2.0 -2.1 -0.9 -0.3 4.5 2.7 0.0 0.0 -0.8 -2.8 -2.6 -2.1
S 6.0 3.9 3.1 2.8 7.3 10.0 10.0 10.0 9.2 6.4 3.8 1.7
AE 4.9 8.1 6.8 5.4 3.8 2.6 2.7 3.1 4.7 5.7 6.3 5.1
R 0.0 0.0 0.0 0.0 0.0 1.9 3.2 2.2 0.0 0.0 0.0 0.0 7.3
D 7.7 2.1 1.6 0.6 0.0 0.0 0.0 0.0 0.0 0.7 2.4 5.9 20.9
TMI -7
73
3.3.3.2 Method 2
Recently, researchers (Austroads, 2004, Barnett and Kingsland, 1999, Chan and
Mostyn, 2008, Fityus et al., 1998, Fox, 2000, Mitchell, 2008) have avoided employing
the water retention tables given by Thornthwaite and Mather (1957) in order to simplify
the calculation and make it more accessible. Instead, they adapted a different definition
to calculate the soil moisture storage which shown in Equation 3-13.
Si = Si−1 + (P − PE)i and 0 ≤ Si ≤ Smax ......………….………...…… Equation 3-13
In these studies, except Austroads (2004), the ΔS and AE calculation have been
skipped. This produces different values for the TMI and it is denoted as Method 2 in
this study.
In this method, moisture surplus is calculated using the same equation used in Method 1
(Equation 3-12) but Equation 3-14 is used for the moisture deficit.
D = Si−1 + (P − PE)i ; Only when Si = 0 …….…….………...…… Equation 3-14
These D and R values are then used to calculate the TMI from Equation 3-8. Table 3-3
shows the calculation steps for Method 2 assuming 10 cm of field capacity and 8 cm of
initial storage.
Table 3-3: TMI calculation steps in Method 2
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1
PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0
P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8
∆S ∆S is not used in this method
S 0.0 0.0 0.0 0.0 4.5 9.1 10.0 10.0 9.2 5.7 0.7 0.0
AE AE is not used in this method
R 0.0 0.0 0.0 0.0 0.0 0.0 2.3 2.2 0.0 0.0 0.0 0.0 4.5
D 0.0 4.2 2.4 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3 14.7
TMI -5
74
3.3.3.3 Method 3
Austroads (2004) used a different definition for ΔS (Equation 3-15) and AE (Equation
3-16) to calculate the moisture deficit, which is denoted here as Method 3.
ΔS = Si−1 − Si .………………...……….………………………...…… Equation 3-15
AE = PE ; when P + ∆S ≥ PE .……...….………………………...…… Equation 3-16
= P + ∆S ; when P + ∆S < PE
Similar to Method 1, this method uses Equation 3-11 to calculate the deficit however
moisture surplus is calculated in a different way, as shown in Equation 3-17.
R = P − AE ; Only when P > AE .………………….…………...…… Equation 3-17
This equation produces values for surplus when the soil moisture storage begins
recharging from an additional amount of water provided by the difference between P
and PE. In Methods 1 and 2, the storage recharge is not considered as a surplus and it is
calculated only when the storage is at its maximum. Hence, Method 3 calculates a
surplus higher than those obtained from Methods 1 and 2. This consequently shifts TMI
towards a more humid condition. Table 3-4 shows the calculation steps for Method 3
assuming 10 cm of field capacity and 8 cm of initial storage.
Table 3-4: TMI calculation steps in Method 3
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1
PE(cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0
P-PE -9.7 -4.2 -2.4 -0.8 4.5 4.6 3.2 2.2 -0.8 -3.5 -5 -8
∆S 8.0 0.0 0.0 0.0 -4.5 -4.6 -0.9 0.0 0.8 3.5 5.0 0.7
S 0 0 0 0 4.5 9.1 10 10 9.2 5.7 0.7 0
AE 10.9 6.0 5.9 5.1 3.8 2.6 2.7 3.1 4.7 6.4 8.7 3.7
R 0.0 0.0 0.0 0.0 4.5 4.6 3.2 2.2 0.0 0.0 0.0 0.0 14.5
D 1.7 4.2 2.4 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.3 16.4
TMI 6
75
3.3.3.4 Method 4
Uncertainties in water balance calculations have encouraged researchers to modify the
TMI equation. Mather (1974) presented a simplified version to obtain the TMI
(Equation 3-18), which omits the 0.6 factor from Equation 3-8. Moreover, this
simplification assumes that there is no net change in the storage in long-term and hence
on an annual basis R and D can be obtained from Equation 3-19 and 3-20. By
substituting them into Equation 3-18, the simplified version given in Equation 3-21 can
be obtained and it does not require water balance calculation.
TMI = 𝐼ℎ − 𝐼𝑎
.………….…….………………………...…… Equation 3-18
R = P − AE
.………….…….………………………...…… Equation 3-19
D = PE − AE
.………….…….………………………...…… Equation 3-20
TMI = 100 × (P
PE− 1) .………….…….………………………...…… Equation 3-21
This method also gives different values for the TMI. Table 3-5 illustrates the calculation
steps for Method 4.
Table 3-5: TMI calculation steps in Method 4
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
P (cm) 2.9 6.0 5.9 5.1 8.3 7.2 5.9 5.3 3.9 2.9 3.7 3.0 60.1
PE (cm) 12.6 10.2 8.3 5.9 3.8 2.6 2.7 3.1 4.7 6.4 8.7 11.0 80.0
P-PE
These factors are not used in Method 4
∆S
S
AE
R
D
TMI -25
76
3.3.4 Comparison of TMI results from different methods
The variation in TMI results obtained using the four different methods is compared in
this section. Climate data collected from Melbourne regional office weather station has
been used in this comparison. Melbourne regional office is one of the main weather
stations in Melbourne Central Business District (CBD) where climate data is available
since 1850’s. Figure 3-5 shows calculated TMI using each of the four methods for the
last 50 years.
Figure 3-5 suggests that, even though different equations are used to calculate soil
moisture storage and deficit, Methods 1 and 2 appear to produce similar results.
Thornthwaite and Mather (1957)water retention tables and the Equation 3-13 used in
Method 2 give similar storage values for certain months in a year depending on P and
PE. While the two methods produce slightly different deficit values, the 0.6 factor used
in TMI equation (Equation 3-8) minimises the difference.
Figure 3-5: TMI variation in Melbourne CBD for the last 50 years
Method 3 uses a different definition for moisture surplus and it produced higher R
values than Methods 1 and 2. Therefore, TMI values have become more positive,
expressing a more humid climate condition compared to Methods 1 and 2.
Method 4, which uses completely different equation for TMI (Equation 3-21), has
simplified the calculation but the results tend towards more negative values expressing a
more arid climate condition. The PE calculation proposed in Thornthwaite (1948) has
1965 1970 1975 1980 1985 1990 1995 2000 2005 2010-60
-40
-20
0
20
40
TMI
Year
Method 1 Method 2 Method 3 Method 4
77
shown that the lesser the P, the higher the PE. Since, Method 4 uses the ratio of P and
PE it reflects higher peaks in extreme dry weather conditions. In wet extremes, peaks
shown in Method 4 are within the range of the other methods.
When the four different methods produce different TMI results, it is questionable which
method should be implemented in the footing design. Since AS2870 provides a climate
zone map of Victoria, which is extracted from Australian TMI map produced in 1965, it
appears that the Method 1 is considered in the Standard. All the methods show the same
trend of long-term climate variation. However, the yearly TMI values differ and hence
different average values will lead to classifying a particular area into different zones. In
addition, the capability of TMI to capture the effects of climate conditions on soil is
debatable. The TMI calculation requires only the rainfall and temperature as climate
parameters. Sensitivities of those parameters are discussed in the next section.
3.3.5 Sensitivity of climate parameters of TMI calculation
Since all four methods express the same trend on climate condition variation with time
and both Methods 1 and 2 produce similar values, Method 1 is used to investigate the
impact of the climate parameters on TMI.
3.3.5.1 Rainfall (Precipitation)
Monthly rainfall values are used in the TMI calculation to perform the monthly water
balance that is then used to obtain annual TMI. Therefore, annual TMI is compared with
annual rainfall. Figure 3-6 shows TMI and annual rainfall variation for the last 50 years
in Melbourne.
Figure 3-6: TMI and annual rainfall variation in Melbourne CBD for last 50 years
1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008-40
-30
-20
-10
0
10
20
30
40 TMI (Method 1) Annual Rainfall (mm)
Year
TM
I
200
300
400
500
600
700
800
900
1000
1100
Ann
ual R
ainf
all (
mm
)
78
Figure 3-6 provides evidence that TMI is almost entirely dependent on rainfall. Indeed,
the annual TMI has the same variation as annual rainfall. The annual rainfall and the
corresponding TMI are plotted in Figure 3-7 and it demonstrates a linear relationship
with a coefficient of determination of 0.89. It is therefore proposed that such an
extended calculation associated with many uncertainties can be summarized to a liner
relationship of annual rainfall with an acceptable reliability. Li and Sun (2015) observed
the similar behavior in the TMI and rainfall in Victorian cities. Consequently, the
annual rainfall can certainly replace the TMI without the hysteresis of calculation.
Figure 3-7: Relationship between TMI and annual rainfall (Melbourne)
3.3.5.2 Temperature
The other climate parameter used in TMI is the average temperature. It is obtained by
averaging the mean minimum and maximum temperatures. The average temperature is
then used to calculate PE. Figure 3-8 shows the variation of TMI and annual average
temperature in Melbourne. PE is the denominator of Ia and Ih equations used to
calculated TMI (Equation 3-1 and 3-2) therefore, an inverse variation is observed
between TMI and average temperature. The TMI values are plotted against the
corresponding average temperatures as shown in Figure 3-9. It suggests that the TMI
only has a weaker correlation with the temperature.
300 400 500 600 700 800 900 1000-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
TMI (
Met
hod
1)
Annual Rainfall (mm)
R-Square = 0.8982
79
Figure 3-8: TMI and annual average temperature variation in Melbourne CBD for the last 50 years
Figure 3-9: Relationship between TMI and annual average temperature (Melbourne)
3.3.5.3 Sensitivity of averaging period on TMI
Since the yearly TMIs fluctuate within a short period, AS2870 (2011) recommends the
use of average TMI for at least 25 years for designing residential structures. Average
TMI is obtained by averaging the annual TMIs calculated for particular number of
1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008-60
-50
-40
-30
-20
-10
0
10
20
30
40 TMI (Method 1) Average Temperature (0C)
Year
TMI
14
15
16
17
18
Ave
rage
Tem
pera
ture
(0 C)
13.0 13.5 14.0 14.5 15.0 15.5 16.0 16.5 17.0 17.5 18.0-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
TMI (
Met
hod
1)
Average Temperature (0C)
80
years. Figure 3-10 shows the impact of changing the averaging period from 3 years to 5,
10, 20 and 25 years on the TMI for Melbourne. Lowering the number of average years
results in an increase in the sensitivity of TMI to extreme climate events. A 20 or 25
year average TMI neutralizes most of the extreme events and shows the long-term
drying trend over the years. In contrast, 3, 5 and 10 year TMIs have more fluctuations
with peaks smaller than the annual TMI variation and reflect the short-term trends.
Average TMI values are less sensitive for consecutive extreme climate events. For
example, a severe drought followed by a few wet years will make a significant impact
on soil moisture and hence the ground movement in expansive soil. However, average
TMI is unable to reflect such changes. Indeed, consecutive extreme climates have
occurred in Melbourne in the recent years. Severe drought from the late 1990’s to early
2000s followed by a few years of above average rainfall was recorded for Melbourne.
This phenomenon is clearly shown in the yearly TMI line in Figure 3-10. TMI values
calculated for averaging periods of 5 and 10 years are less sensitive to these consecutive
events. In fact, the 20 and 25 years averaged TMIs do not reflect this extreme event at
all.
Figure 3-10: Sensitivity of averaging period on TMI
While Figure 3-10 shows the impact of averaging period on TMI results, determining
the most appropriate averaging period also depends on the type of soil. The climate
1938 1944 1950 1956 1962 1968 1974 1980 1986 1992 1998 2004 2010-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
TMI
Year
Yearly TMI 3 years 5 years 10 years 20 years 25 years
81
impact on soil moisture is largely a site dependent phenomenon because of the soil
properties and the local effects. Therefore, the average years need to be considered in
association with many factors including permeability of the soil and vegetation cover.
3.4 CORRELATION OF TMI AND EXPANSIVE SOIL BEHAVIOUR
TMI has become the most popular climate index to be correlated with the soil moisture
or suction (PTI, 2004, Russam and Coleman, 1961, Aitchison and Richards, 1965).
Since the moisture content of the surface layer fluctuates more frequently, the long-term
average TMI has been used to correlate the equilibrium suction (constant suction below
depth of seasonal moisture change) by Russam and Coleman (1961). Figure 3-11 shows
the variation of equilibrium suction with TMI. The suction values obtained from this
correlation were used in designing road subgrades. In the Post Tensioning Institute
method of footing design, TMI is correlated with the edge moisture change distance of a
cover slab (Figure 3-12) in centre lift and edge lift situations (PTI, 2004). Figures 3-10
and 3-11 are also referred to in the hand book of AS2870 (Walsh and Cameron, 1997).
However, none of the above publications mentioned that the TMI calculation procedure
or period of averaging years must be considered.
Figure 3-11: Variation of soil suction of road subgrade with TMI (Russam and Coleman, 1961)
82
Figure 3-12: Edge moisture variation distance determination in Post Tensioning Institute (PTI, 2004)
Mitchell (2008) summarised the conclusions of a number of research outcomes about
TMI and the equilibrium suctions in Australia, shown in Figure 3-13. Figure 3-13 shows
the reduction in equilibrium suction towards a humid climate condition, which is similar
to Figure 3-11.
Figure 3-13: Correlations of equilibrium soil suction and TMI (Mitchell, 2008)
83
The AS2870 design procedure is based on the shape of the suction profiles rather than
the equilibrium suction. The extreme suction profiles in dry and wet conditions shows
the possible range of suction variation at different times. Walsh and Cameron (1997)
argued that the overall variation has the shape of a champagne flute. The ground
movement calculation given in AS2870 depends on the area within the extreme suction
profiles. Since it is difficult to calculate the area of the champagne flute shape, it has
been simplified to a triangular shape defined by ΔU and Hs. The AS2870 standard has
defined climate zones based on TMI and provided ∆U and Hs for each zone.
Figure 3-14 shows the corrections of ΔU and TMI suggested by various researchers. All
the references except AS2870 (2011) and Fox (2000) suggested that ΔU increases with
increasing the aridity of the climate. However, irrespective of the different climate
conditions and soil types in Australia, AS2870 (2011) has specified a single value (1.2
pF) for all the cities.
Figure 3-14: Correlation of ΔU and TMI (Mitchell, 2008)
Figure 3-15 shows the suggestions from the same researchers for TMI verses Hs
relationship. It clearly shows that the higher the aridity in the climate the higher the Hs
value. AS2870 shows a discrete variation in the climate zones and the corresponding Hs
depths.
84
Figure 3-15: Correlation of Hs and TMI (Mitchell, 2008)
3.5 ISSUES OF TMI BEING USED IN AS2870
The main issue of TMI being used in footing design is its ability to represent the soil
moisture condition. The TMI is largely based on rainfall and temperature with a
negligible contribution from soil parameters. As described in the section 3.3.5.2,
temperature has minimal impact on TMI however, the influence of rainfall on TMI is
clearly observed by considering the contour maps. Figure 3-16 shows predicted rainfall
and TMI maps in year 2100 for Australia (Austroads, 2004). The contours of rainfall
and TMI are almost similar which strengthens the linear correlation shown in Figure
3-7. Figure 3-17 shows Victorian mean annual rainfall map (BoM, 2015a). These
annual rainfall contours are almost identical to the TMI contours shown in Figure 3-18.
85
Figure 3-16: (a) Average Annual Rainfall in mm for 2100 predicted climate; (b) TMI map for 2100 predicted climate(Austroads, 2004)
Figure 3-17: Victorian mean annual rainfall map (BoM, 2015a)
(a) (b)
86
Figure 3-18: TMI map for Victoria for 1913 to 1932 (Leao and Osman, 2013)
Another issue of TMI is the use of average TMI. Various researchers, who studied TMI
and Hs, have used different average periods. The number of years used to calculate the
average has varied within a broader range (from 5 to 144 years) and some researchers
used the average TMIs based on the entire years of available data (Chan and Mostyn,
2008, Fityus et al., 1998). This may be due to the recommendation of AS2870 to
consider the average TMI of at least 25 years. Figure 3-10 shows that the higher the
averaging years, the lesser the sensitivity to extreme weather events such as droughts.
The long-term average TMI clearly displays the long-term trends. However, for the
residential footing design, this averaging period needs to be considered together with
more soil specific parameters.
During a drought period, the surface soils can become dry depending on the severity of
the moisture deficit. If the rain comes immediately after, a certain amount of water will
infiltrate through the surface soil while some rain will move in to the cracks. However,
there is a runoff on the surface depending on the surface condition. Since the TMI
calculation is associated with monthly rainfall to obtain the water balance, it assumes
that all the rainwater after a deficit period infiltrates the soil moisture storage until it
reaches the field capacity. Any possible runoff while soil is being recharged is not
considered. Hence, TMI results indicate a more humid condition than the actual
87
situation. This highlights the lack of ability of TMI to capture effects of rainfall spread
given the overall rainfall kept constant.
The next issue of using TMI in AS2870 is the uncertainty surrounding the time of
climate data to be used in the calculation. Many researchers concluded that climate
change has been ongoing in Australia since the 1950s’ (Karunarathne et al., 2013,
Lopes and Osman, 2010, McManus et al., 2004, Mitchell, 2008, Hughes, 2003, Murphy
and Timbal, 2008, Smith et al., 2009). However, the climate classification given in
AS2870 is based on the climate data collected from 1940 to 1960 and therefore is likely
to be out-dated (Lopes et al., 2003).
Aitchison and Richards (1965) developed the Australian TMI map using 1940-1960
climate data. The Victorian TMI map shown in Figure 3-19 was extracted from the
Australian TMI map produced in 1965 (Aitchison and Richards, 1965). This map shows
the TMI contours and the climate zones based on the TMI ranges given in Table 3-6.
According to the map shown in Figure 3-19, Melbourne city and the Western suburbs
fall in to climate zones 2 and 3 which have TMI variations from -5 to +40. In these
climate zones, Hs varies from 1.8 m to 2.3 m.
Figure 3-19: TMI map of Victoria given in AS2870 (1996)
88
Table 3-6: Climate zones and corresponding Hs inferred from AS2870 (1996)
TMI Range
Hs (m)
Climate Zone
TMI > 40 1.5 1
40 > TMI >= 10 1.8 2
10 > TMI >= -5 2.3 3
-5 > TMI >= -25 3.0 4
-25 > TMI 4.0 5
The effect of climate variation on Hs has been considered in several studies in different
Australian states (Barnett and Kingsland, 1999, Chan and Mostyn, 2008, Fityus et al.,
1998, Fox, 2000, Lopes and Osman, 2010, McManus et al., 2004, Smith, 1993). Fityus
et al. (1998) calculated the TMI for 38 locations and proposed a detailed TMI map for
the Hunter Valley area. Moreover, McManus et al. (2004) produced TMI maps for
Queensland, South Australia, Western Australia, New South Wales and Victoria to
describe the climate change. They developed TMI maps for two different periods; 1940-
1960 and 1960-1991. Their results highlighted that those areas have shown a trend of
drying since the 1960’s.
Lopes and Osman (2010) calculated the TMI for certain Victorian towns for three
different time periods; 1948-1967, 1968-1987 and 1988-2007. Based on the results, they
have concluded that TMI values of those towns have changed and Aitchison and
Richards (1965) TMI map is not valid for the climate condition for the period of 1988-
2007. Furthermore, Lopes and Osman (2010) proposed updated Hs values
corresponding to the TMI results for 1988-2007 period.
The 2011 edition of AS2870 provided an updated relationship for TMI and Hs shown in
Table 3-7. The TMI ranges of each climate zone have been shifted towards more
negative values to accommodate the drying trend. Consequently, a new climate zone has
been introduced as “Zone 6” which represents the main difference between Tables 3-6
and 3-7.
89
Even after the modifications given in AS2870 (2011), some problems remain uncertain
in the new climate map and the corresponding Hs relationship (Lopes and Osman
(2010). The updated Victorian climate map is shown in Figure 3-20. The TMI contour
maps given in the 1996 and 2011 editions are identical, as shown in Figure 3-19 and
Figure 3-20. The only difference is that the TMI values shown in 1996 map were
deleted in the 2011 map. The TMI contours and the zone numbers are the same in both
maps. Therefore, even if the calculations indicated decrease in the TMI, the map
suggests that zone 6 areas are not identified in Victoria.
Recently calculated TMI values show a considerable change in climate conditions
(Karunarathne et al., 2012). During this study, TMI was calculated in two different
periods for more than fifty locations in Victoria. Ten cities from each climate zone were
considered. Figure 3-21 shows the results and indicates that all the locations have lower
TMI values for the period 1991 to 2011 compared to 1940-1960. Most of the
differences are 10-15 units. This indicates the drying trend of the climate. The updated
TMI ranges in AS2870 (2011) were able to encompass the changes to certain extent and
the TMI limits in each climate zones were reduced by 10 to 15 units in 2011 edition.
However, these changes were not implemented in terms of Hs.
Figure 3-20: TMI map of Victoria given in AS2870 (2011)
90
Table 3-7: Relationship between TMI and Hs(AS2870, 2011)
TMI Range Hs (m) Climate Zone
TMI > 10 1.5 1
10 > TMI >= -5 1.8 2
-5 > TMI >= -15 2.3 3
-15 > TMI >= -25 3.0 4
-25 > TMI >= -40 4.0 5
-40 > TMI > 4.0 6
Figure 3-21: TMI calculation for Victorian cities
Figures 3-22 and 3-23 show the positions in the TMI bands for each climate zone
specified by the 1996 and 2011 edition of the standard, respectively. The highlighted
areas are the TMI bands of each climate zone in the particular edition of the standard.
The TMI values are calculated using Method 1. In general, in Figures 3-22 and 3-23,
most of the cities were captured by the specified TMI bands in both editions of the
standard. However, in zone 3 of Figure 3-22 and zone 4 of Figure 3-23, most of the
cities fell outside the bands.
Ap
ollo
Bay
Ararat
Ballan
B
allarat B
eaufo
rt C
ashim
ore A
irpo
rt C
olac
Daylesfo
rd
Dim
bo
ola
Do
nald
East Sale Ech
uca
Elmo
re Essen
do
n
Gisb
orn
e H
amilto
n
Heyw
oo
d
Ho
rsham
K
aniva
Keran
g K
ew
Kyab
ram
Laverton
Leo
ngath
a Lism
ore
Lon
gerno
ng
Man
galore
Marib
yrno
ng
Melb
ou
rne
Mered
ith
Mild
ura
Mo
e M
orn
ingto
n
Mu
rrayville N
hill
Ou
yen
Po
rtland
Q
ueen
scliff R
ainb
ow
R
ob
invale
Ro
chester
Sea Lake Seym
ou
r Skip
ton
Sp
eed
St. Arn
aud
Tatu
ra Taw
on
ga W
arracknab
eal W
atson
ia W
erribee
Wo
nth
aggi W
ychep
roo
f
-50-40-30-20-10
01020304050607080
TMI
Method 1 (1940-1960) Method 1 (1991-2011)
91
Figure 3-22: TMI of Victorian cities in different climate zones specified in AS2870 (1996)
Figure 3-23: TMI of Victorian cities in different climate zones specified in AS2870 (2011)
-50-45-40-35-30-25-20-15-10
-505
10152025303540455055606570
1.00 2.00 3.00 4.00 5.00 6.00
TMI
Mather
Zone 1 Zone 2 Zone 3 Zone 4 Zone 5
Method 1 (1940-1960)
-50
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
50
1.00 2.00 3.00 4.00 5.00 6.00 7.00
TMI
Mather
Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 6
Method 1 (1991-2011)
92
Overall, the modifications adopted in the 2011 edition of the standard are able to predict
most of the recent climate changes. However, the corresponding Hs values have not
been updated for zone 2 and 3 which cover Melbourne’s Western suburbs. This leads to
some confusion in the use of the TMI map and the TMI verses Hs relationship given in
Table 3-7. Subsequently, the ys calculation for Western suburbs based on both editions
of the standard would produce same values.
Some of the specified Hs values for Australian cities have been updated in 2011 edition
of the standards, as shown in Table 3-8. In most cases, Hs was increased to
accommodate the effects from the drying trend of the climate. In contrast, the ΔU values
were reduced from 1.5 pF to 1.2 pF for some regions making all parts of Australia
having ΔU value of 1.2 pF (Table 3-8). However, even after the 1996 edition of the
standard was published, some researchers have found ΔU value to be greater than 1.5
pF for some areas (Barnett and Kingsland, 1999, Fityus et al., 2004).
Table 3-8: Hs and ΔU values specified in AS2870
Location Hs (m) ∆U(pF)
AS2870 (1996)
AS2870 (2011)
AS2870 (1996)
AS2870 (2011)
Adelaide 4 4 1.2 1.2 Albury/ Wodonga 3 3 1.2 1.2 Brisbane/ Ipswich 1.5 – 2.3 1.5 – 2.3 1.2 1.2 Gosford Not given 1.5 – 1.8 Not given 1.2 Hobart 2 2.3 – 3.0 1.5 1.2 Hunter Valley 2 1.8 – 3.0 1.5 1.2 Launceston 2 2.3 – 3.0 1.2 1.2 Melbourne 1.5 – 2.3 1.8 – 2.3 1.2 1.2 Newcastle 1.5 1.5 – 1.8 1.5 1.2 Perth 3 1.8 1.2 1.2 Sydney 1.5 1.5 – 1.8 1.5 1.2 Toowoomba 1.8 – 2.3 1.8 – 2.3 1.2 1.2
Austroads (2004) predicted the expected changes in Australian climate to the year 2100.
This report concluded that most of Australian cities will have a dryer climatic condition
in 2100 than they had in 2000. According to the prediction, current TMI values in most
of the Victorian cities will be reduced by 15 in 100 years. Indeed, based on the results
presented in Figure 3-21, some locations have seen a reduction of 20 in the TMI value
93
over the last 50 years. Therefore, given that TMI, and consequently Hs, values are based
on historical data, an allowance should be made for potential changes during the design
life of the structure. It is therefore proposed to adopt a Hs value for design that is based
on a probabilistic design event based on more recent climate data and future forecasts
which suggest potentially greater drying.
In addition to the dependency of Hs on climate condition, other soil parameters vary
with the moisture content, which can affect the ground movement as described the next
section
3.6 EFFECT OF SOIL MOISTURE CONDITION ON AS2870 DESIGN PARAMETERS
3.6.1 Variation of Iss with moisture content
According to the site classification procedure given in AS2870 and described in the
previous chapter, ΔU, Hs, shrinkage index and assumed cracking depth are the
parameters that represent the site condition. ΔU and Hs depend on the long-term climate
condition, as described in the previous section. AS2870 considers that shrinkage indices
are constant for a given soil type. The shrink swell test considers total strain of
undisturbed soil from both shrinkage and swell movements irrespective to the initial
moisture content. Therefore, the hand book of AS2870 recommends Iss is the most
reliable index among others such as core shrinkage index and loaded shrinkage index
(Walsh and Cameron, 1997).
Shrinkage indices represent the volume change of expansive soils per unit suction
change. Iss includes strains from both shrinkage and swell movements. Vertical
movement is most critical, because lateral movement is restrained by the surrounding
soils. Therefore, Iss considers only the vertical strain per unit suction. The Iss test starts
at the in situ moisture content and proceeds to swell and shrinkage movements. Swell
strain is measured from the one-dimensional swell test whereas shrinkage strain is
measured from the core shrinkage test.
As shown in Figure 3-24, variation of soil strain with suction is a curvilinear function.
This figure is developed using the core shrinkage test starting from a very wet
condition. The weight and the length of the sample are measured until the sample
reaches an oven dry condition. Then, the moisture contents are calculated and the
94
corresponding suction values are obtained from the soil water characteristic curve (more
details on soil water characteristic curve are provided in Chapter 4). Iss is the gradient of
the strain versus suction curve. According to Figure 3-24, the relationship has an “S”
shape with three different stages. The main stage is the darkened area of Figure 3-24,
which has a linear variation with steep slope. Therefore, soils in this section experience
significant strain per given suction change. Very wet soils and very dry soils represent
either side of that area, as illustrated in the figure. These two sections of the curve have
mild and changing slopes implying that less strain will be observed for a given suction
change.
Figure 3-24: Vertical strain and suction relationship (Braybrook soil)
According to AS1289.7.1.1 (2003), the Iss test starts from the in situ moisture content
which can be at any suction value shown in Figure 3-24. AS1289.7.1.1 (2003) specifies
to stop the swell test when the movement between the last reading and a reading at least
3 hours previously is less than 5% of the total swelling of the specimen. Most of the
soils will reach this limit close to the end of the linear section of the relationship. The
author has experienced this incident for the clays collected from different areas
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.50
3
6
9
12
15
18
21 Strain (%) Polynomial fit
Stra
in (%
)
Suction (pF)
Very wet soil Very dry soil
95
including Braybrook, Burnside, Taylors Hill, Point Cook, Melton and Plumpton in
Victoria, Australia. Those soils have shown a considerable swelling after this specific
limit and continued swelling for more than 5 days. Most of those soils are moderate to
highly expansive clays. Even though the standard neglects strain after this 5% limit, it
can represent a significant amount compared to the total strain. However, the shrinkage
test has no restricted stopping point and continues to the oven dry state. The total
vertical strain is then divided by suction change to obtain the gradient.
The Iss test is purposely developed to bypass the difficulties of measuring soil suction.
Therefore, it assumes that the suction varies by 1.8 pF over most of the significant strain
change in soil. This suction change is commonly accepted by many researchers (Fityus
et al., 2005). However, since the relationship of suction and strain has “S” shape (Figure
3-24), its gradient varies at suctions close to the extreme ends. Thus, Iss can have
different values at different operating suctions. Moreover, based on the Iss equation
explained in Chapter 2 (Equation 2-14), tests started at high moisture contents have
lower swell movements and higher shrinkages, which result in higher total strains.
Consequently, tests started at different in situ moistures produce different Iss results.
This phenomenon was experimentally observed in this study. Undisturbed samples were
collected around a specific location at the field site of Braybrook (see Chapter 4) at
different times of the study. Hence, the samples were assumed to be identical and they
were at different in situ moisture levels. Results of Iss tests performed on those soils are
presented in Table 3-9.
Within the period of sample collection, March 2013 was recorded as driest month
whereas August 2013 was the wettest. Moisture contents of the top soil varied by more
than 15% between these two conditions. However, the soil moistures below 1.5 m were
stable. Table 3-9 shows the different Iss results obtained corresponding to different
moisture contents particularly for soils up to 2.0 m. This difference is higher in top
soils, as shown in Figure 3-25. Shrinkage strain becomes increasingly higher when in
situ moisture content is increased. Swell strain showed the opposite variation against in
situ moisture. However, according to the calculation based on those two strain values,
Iss increased with in situ moisture content. Interestingly, Iss changed by 2.5% for a
change of soil moisture of 15%.
96
Table 3-9: Iss test results from different samples collected at similar locations from Braybrook
Sample date Depth (m) In situ mc % Shrinkage
(%) Swell (%) Iss (%)
02/08/2012
0.5-1.0 28.53 8.75 2.35 5.51 1.5-2.0 26.78 8.83 2.70 5.65 2.5-3.0 26.06 8.86 1.45 5.33
26/03/2013
0.5-1.0 21.86 3.95 7.20 4.19 1.5-2.0 26.01 7.92 3.25 5.30 2.5-3.0 24.26 8.53 3.10 5.60
20/06/2013 0.5-1.0 32.15 9.89 0.25 5.56 1.5-2.0 25.02 7.93 5.10 5.82
08/08/2013
0.5-1.0 37.12 11.54 0.16 6.46 1.5-2.0 30.83 9.14 5.91 6.72 2.5-3.0 25.42 8.70 3.78 5.88
21/10/2013
0.5-1.0 34.42 10.29 1.45 6.12 1.5-2.0 25.86 7.90 3.51 5.37 2.5-3.0 25.30 7.99 2.66 5.17
Figure 3-25: Iss variation with starting moisture content for soils at 0.5-1.0 m depth in Braybrook
20 22 24 26 28 30 32 34 36 38 400
1
2
3
4
5
6
7
8
9
10
11
12 Shrinkage strain (%) Swell strain (%) Iss (%)
Stra
in a
nd I ss
(%)
Gravimetric moisture content (%)
97
Another set of samples was taken from a different site which was tested for Iss during
this study. The site is located in Burnside area, which is one of the western suburbs of
Melbourne. Red-brown clay soil was found within the top layer of this site. The site had
a house which was damaged due to abnormal moisture condition. The collected samples
had different in situ moisture content even if the boreholes were closely located (within
2 m radius). Four samples were tested, and Table 3-10 shows the Iss results for those
samples. There is a considerable increase in Iss with the increase in moisture content.
Hence, these results suggest that Iss can be dependent on in situ moisture content. The
effect of such changes of Iss on site classification is described in the next section.
Table 3-10: Iss results of Burnside samples
In situ moisture content
(%)
Shrinkage %
Swell % Iss
27 8.9 3.9 6.1 41 13.2 0 7.4 46 15.9 0.1 8.9 49 17 0 9.4
3.6.2 Effect of Iss changes on site classification
According to the calculation of ys for classifying the site, the instability index is
calculated using Iss and crack depth, as described in the previous chapter. The instability
index increases the effect of Iss below the crack depth by means of lateral restraint factor
(α). Therefore, even deeper depths show a slight variation in moisture and hence Iss,
which can significantly affect the ys calculation.
The ys was calculated using different Iss values given in Table 3-9 and the specified
parameters in AS2870 (2011). The standard specified that a suitable Hs of 2.3m and a
crack depth of 0.75Hs for the Melbourne area. ΔU is specified as 1.2 pF. The ys was
calculated from Iss obtained at three different periods representing wet, dry and
moderate soil moisture content, as shown in Table 3-11.
98
Table 3-11: Calculation of ys using different Iss values
Depth (m) ΔZ (mm)
Average ΔU (pF) for layer
α
Iss (%) at different soil moisture condition ys (mm)
Wet
08
/08/
2013
Mod
erat
e 02
/08/
2012
Dry
26
/03/
2013
Wet
Mod
erat
e
Dry
0-1.0 1000 1.026 1 6.46 5.51 4.19 66.3 56.5 43.0 1.0-1.5 500 0.591 1 6.46 5.51 4.19 19.1 16.3 12.4
1.5-1.725 225 0.378 1 6.72 5.65 5.3 5.7 4.8 4.5 1.725-2.3 575 0.2 1.62 6.72 5.65 5.3 12.5 10.5 9.9
Total ys 103.6 88.1 69.7
This site was then classified based on ys values and the site classification given in
AS2870 (2011). According to the standard, the highly reactive class (H2) includes ys
values from 60 to 75 mm. Sites with ys higher than 75 mm are classified as extremely
reactive (class E). Based on the different ys values obtained at different periods, this site
can be classified as class E in wet and moderate soil moisture conditions whereas it is
classified as H2 in dry conditions. Hence, a footing design performed for the same soils
collected at different times of the year would result in different designs.
3.7 SUMMARY
This chapter describes the impact of climate on the footing design procedure given in
AS2870. Soil and climate interaction is the natural mechanism by which changes occur
in soil moisture. The climate condition governs the amount of water available for
infiltration and, therefore, it influences the changes in moisture contents at the surface
as well as the depth of moisture change. The Australian Standard uses TMI to classify
the climate condition and then correlates the parameters in soil moisture profile with the
climate categories. Six climate zones are given in the current Standard, based on TMI
values and the corresponding depth of suction change (Hs) values. The suction change at
the surface (ΔU) is also dependent on the climate condition; however, the current
Standard provides a single value (1.2pF) for all regions in Australia. Hs and ΔU are the
key parameters in estimating surface movement and hence govern the footing design.
99
There are certain issues in using TMI to consider the impacts of climate on footing
design. The first issues relates to its ability to correlate the soil moisture condition. The
TMI largely depends on rainfall and consequently, linear correlations were observed
between annual rainfall and TMI variations in most of the cities in Victoria. Therefore,
the influence of the other climate components such as evaporation, relative humidity
and wind are not considered in in determining soil moisture changes.
Second, several methods exist to calculate the TMI and each method produces different
values. Irrespective of the calculation method, it appears that there is an ongoing drying
in the Victorian climate. The calculation method used in AS2870 is not clearly
identified. Since the Standard provides the TMI map developed in 1960s and Method 1
is based on the procedure given by Thornthwaite in 1957, it appears that Method 1
produces the closest results to the values provided by the Standard.
Since each TMI calculation method produces different values, the correlation between
TMI and Hs results in different values for the same climate condition. This can result in
different footing designs. In addition, the use of the average TMI also produces different
values. Specifically, the more years used in the average calculation, the lesser the
sensitivity to extreme weather events, such as droughts. The long-term average TMI is
appropriate to reflect long-term trends. However, for the residential footing design, this
averaging period needs to be considered together with more soil specific parameters.
Apart from these issues in using the TMI to correlate with soil moisture changes, the
correlations given in AS2870 are based on climate data in 1960s. The modifications to
AS2870 in the 2011 edition captured the changes of TMI due to the drought effect
experienced in the last 25 years. However, this may not be enough to capture ongoing
changes. Furthermore, the values of Hs and ΔU have not been updated to reflect the
recent changes and possible changes in the future.
In addition to Hs and ΔU, Iss is the next important parameter in estimating surface
movement which also appear to be dependent on in situ moisture content. The
Australian standard AS1289 specifies Iss as a constant for a given soil type. In this
research, soils collected from a field site at different times of the year were tested and a
number of Iss values were obtained for the same soil. The results indicated that the Iss
increases with increasing in situ moisture. This shows the dependency of Iss on in situ
100
moisture, which is in contrast to the specifications outlined in the Australian standard
AS1289. It can result in different footing designs for a particular site, when the soils are
tested at different times of the year. These issues highlight the importance of a
comprehensive understanding of the impacts of climate conditions on soil moisture
changes and the subsequent ground movements. The climate-induced soil moisture
changes governed by site and soil characteristics are described in the next chapter.
101
4. FIELD AND LABORATORY INVESTIGATIONS OF EXPANSIVE
SOIL BEHAVIOUR
4.1 INTRODUCTION
For this research, a suitable field site was necessary to collect soil moisture and ground
movement data. The site required to have typical expansive soils (Basaltic clays) which
would be found in Western Melbourne. Lab testing on soils was undertaken to establish
the suitability of the various sites for the study. The lab tests included Atterberg limits,
linear shrinkage, shrink swell index test, particle size distribution and mineral
composition. This chapter describes the site selection and the lab test results of the
selected site.
4.2 SITE SELECTION CRITERIA
The main purpose of site selection was to identify a vacant block of land with
reasonably reactive soils. Therefore, the available geology maps were examined to find
an appropriate area.
Most of the Melbourne suburbs have been established on blankets of lava flows rest on
an erosion surface of Tertiary and Quaternary sediments such as Brighton group
sediments (Thomas, 1967). These extensive lava flows belong to newer volcanos
(Werribee plane phase) which is comparatively young in terms of geological time
(Thomas, 1967). The thickness of basalt flows varies from place to place. Deep surface
weathering occurred over millions of years resulted in deposits of residual clay. These
newer volcanic soils extent most parts of western Victoria towards the corner of South
Australia (Dahlhaus and O'Rouke, 1992). These quaternary volcanic soils are mostly in
dark to light grey, and associated with inter-bedded silty sands and backed soils
(Thomas, 1967). The distribution of Quaternary Basalts soil is shown as pink colour in
Figure 4-1 (Maps, 2015). Mann (2003) provided an expansive soil map of Victoria, as
shown in Figure 4-2, which suggests that most of the basalt soils shown in Figure 4-1
are expansive. The dark red and orange areas in Figure 4-2 have highly reactive
cracking clay soils whereas the yellowish areas have calcareous clay soils. According to
this map, most of the soils in west part of Melbourne are moderate to highly reactive.
102
Therefore, the investigations were aimed at the Western suburbs to find a suitable site to
be monitored.
Figure 4-1: Geology of Melbourne and the location of Braybrook site - extracted from 1:31680 map of Melbourne (Maps, 2015)
More than ten typical residential blocks of land were initially investigated in the
Western part of Victoria, which were likely to have reactive soils. Most of these sites
are owned by the Victorian Office of Housing who is one of the supporting partners of
this research project. The soils collected from Heidelberg, Rosebrook, Horsham,
Taylors Hill, Williams landing, Point Cook and Braybrook were tested for an indication
of reactivity. A primary consideration was to find a vacant land with reactive soils that
could be categorized as class H to E based on AS2870. A tree on the site was also a
desirable feature. Most of the sites previously contained dwellings but these dwellings
had been demolished for redevelopments. The monitoring plan was to use the intact area
of the lands that corresponded to the old back yards of the dwellings.
Alluvial flats, mud flats, beach & estuarine depositsAlluvial terraces
Basalts
Basalts
Non-marine silts & clays (pre-Tertiary basalt)
Mudstones, siltstones & sandstones
Marine & non-marine sands, cays, ferruginous sand& gravels
Quaternary
Tertiary
Silurian
Melbourne CBD
N
Braybrook
103
Figure 4-2: Distribution of expansive soils in Victoria (after Mann (2003))
Figure 4-1 shows the location of the Braybrook site in the west part of the Melbourne.
Braybrook was an industrial suburb, however, residential areas have begun to appear in
this area due to the expansion of the Western suburbs. Therefore, many redevelopments
have been ongoing since last decade. The selected site consists of three adjacent blocks
of about 1000 m2 each, which previously held three single storey houses. Figure 4-3
shows the aerial view of the Braybrook site that was taken before the demolition of the
houses. Those houses were demolished in 2010 for redevelopments and the land
currently belongs to the Victorian Office of Housing. Each of the blocks had relatively
large back yards as shown in Figure 4-3, making them ideal for field monitoring. Some
trees are visible in Figure 4-3 and most of them were also pulled down during the
demolition work. However, there are plenty of intact areas to perform a field
investigation on expansive soil behaviour.
N
Highly calcareous loamy earth soils (Alluvial)
Sandy soils with clayey subsoils (Alluvial)
Hard setting loamy soils with clayey subsoils Clay soils (Alluvial)
Hard setting loamy soils with clayey subsoils Clay soil (Basaltic)
Cracking Clay soil (Alluvial)
Cracking Clay soil (Basaltic)
Friable loamy soils (Basaltic)
Peats
Lakes
Braybrook
104
Figure 4-3: Google map view of the Braybrook site and samples collected locations (Google image was taken in 2010)
The identified site in Braybrook is virtually a flat site. One of the blocks has a mature
and isolated Paper Bark tree, which is an optimal condition for the purpose of
monitoring. Figure 4-4 shows the current view of the three blocks in Braybrook site.
N
Location 1
Location 2
Location 3
105
Figure 4-4: Three adjacent blocks of Braybrook Site
Based on the Atterberg limits and linear shrinkage results at different depths, Braybrook
soils appeared to be highly reactive. The descriptive explanation of the basic soil test
results is provided in the next sections.
Since the Braybrook site can be categorized as a highly reactive site that has space and
fulfils the other requirements of the study, this site was selected for long-term field
monitoring.
4.3 SOIL CLASSIFICATION
In Braybrook, clay soils with a slight colour variation along the depth were found
during the soil sampling. Disturbed and undisturbed soil samples were collected from
depths down to 3.5 m in various locations. Tubes of 50 mm diameter were used to
obtain the undisturbed soil samples. The length of a tube sample is 0.5 m and samples
were capped as soon as they were taken out of the ground to prevent moisture loss.
Tubes were labelled on site with the date, location and depth. Normally three
undisturbed soil samples were collected from each borehole at various depths.
Disturbed soil samples were collected in between the depths of tube samples and
continued up to 3.5 m. Disturbed soils were collected into polythene bags, tied to
prevent moisture loss and labelled.
106
Tube samples were extruded using a hydraulic extruder and used to determine shrink-
swell index, suction and mineral composition measurements. Figure 4-5 shows the cross
section of an extruded undisturbed sample at 2.5-3.0 m depth. The appearance of the
soil below 2.0 m depth seems to be consistent as shown in Figure 4-5. Both disturbed
and undisturbed samples were used to obtain the Atterberg limits, linear shrinkage and
particle size distribution.
Figure 4-5: Cross section of an undisturbed sample extruded from a tube (2.5 -3.0 m)
4.3.1 Soil profile
The soil profile of the Braybrook site appears to be consistent and the soil colour
changes gradually towards the bottom. The top soil layer contains a certain amount of
grass roots and the soil between 1.0 to 1.5 m is slightly calcareous. The soils at the
bottom tend to be stiffer, as shown in Table 4-1.
Table 4-1: Soil profile at Braybrook
Depth (m) Soil description
0.0-0.3 Clay (CH), Dark Brown, Soft, Root fibres present
0.3-0.5 Clay (CH), Dark Brown, Stiff,Root fibres present
0.5-1.0 Clay (CH), Brown, Stiff, Slightly calcareous
1.0-1.5 Clay (CH), Brown to dark gray, Stiff, Slightly calcareous
1.5-2.0 Clay (CH), Dark gray to light gray, Very stiff, Slightly calcareous
2.0-2.5 Clay (CH), Light gray, Very stiff, Slightly calcareous
2.5-3.0 Clay (CH), Light gray, Very stiff
3.0-5.0 Clay (CH), Light gray, Very stiff
107
Figure 4-6 shows a cross section of the soil profile. This pit was excavated to collect
undisturbed samples for further testings. The isolated calcrete layer about 1.5 - 2.0 m
depth can be clearly seen in Figure 4-6. The gradual change of the colour is also visible.
The site has a deep clay profile and the bedrock was not hit even after excavating to 4.5
m depth.
Figure 4-6: Cross section of the soil profile of Braybrook site exposed through an excavation
4.3.2 Atterberg limits and linear shrinkage
Atterberg limits tests (AS1289.3.1.1, 2009) were performed at different depths to
identify the variation of the properties. The tests were conducted from soils collected at
three different locations (shown in Figure 4-3). Tables 4-2 to 4-4 show the results of
Atterberg limits and linear shrinkage tests. All three locations show similar variation of
soil properties, and the variation of average results are shown in Figure 4-7. The plastic
limit varied from 20 to 25% and the liquid limit varied from 70 to 80% throughout the
depth. Linear shrinkage test (AS1289.3.4.1, 2008) results were within 17 to 19%.
According to the values of plasticity index (PI) and linear shrinkage, the Braybrook soil
was recognized as highly reactive (Hazelton and Murphy, 2007).
Ground level
~0.5 m
~1.0 m
~1.5 m
~2.0 m
~2.5 m
Isolated layer of calcrete
108
Table 4-2: Basic soil test result - Location 1
Depth Range(m)
LL PL PI LS (%)
0-0.5 77.0 30.1 46.9 16.5
0.5-1.0 74.1 23.0 51.1 18.9
1.0-1.5 74.2 24.0 50.2 18.1
1.5-2.0 58.7 24.8 33.9 17.8
2.0-2.5 82.6 24.7 57.9 19.5
2.5-3.0 66.1 19.3 46.8 18.3
3.0-3.5 72.8 20.9 51.8 18.1
3.5-4 77.0 23.8 53.2 17.3
Table 4-3: Basic soil test result - Location 2
Depth Range(m)
LL PL PI LS (%)
0-0.5 75.3 25.4 50.0 17.5
0.5-1.0 73.3 26.3 47.0 18.1
1.0-1.5 64.8 22.3 42.4 18.6
1.5-2.0 72.0 22.5 49.5 16.4
2.0-2.5 66.6 17.8 48.8 17.3
2.5-3.0 68.3 23.2 45.1 16.7
3.0-3.5 73.0 21.0 52.0 19.0
3.5-4 81.0 24.4 56.6 16.9
Table 4-4: Basic soil test result - Location 3
Depth Range(m)
LL PL PI LS (%)
0-0.5 70.6 27.7 42.9 21.5
0.5-1.0 81.8 18.6 63.2 19.7
1.0-1.5 82.5 23.1 59.4 19.4
1.5-2.0 82.6 18.3 64.3 20.4
2.0-2.5 81.7 21.1 60.6 18.1
2.5-3.0 95.4 26.4 69.0 16.3
3.0-3.5 88.1 23.4 64.7 17.2
3.5-4 68.9 16.4 52.5 20.7
109
Figure 4-7: Atterberg limits and linear shrinkage variation with depth
Based on the Liquid Limits and Plasticity Index values given in Figure 4-7, the fine-
grained soil up to 3.5 m depth can be located above the “A” line in Figure 4-8.
Therefore, this soil can be classified as Fat clay (CH) according to the Unified soil
classification (ASTM-D2487, 2011).
Figure 4-8: Location of Braybrook clay in plasticity chart (ASTM-D2487, 2011)
Braybrook clay
110
4.3.3 Particle size distribution and density tests
The fine particle percentages of the soils at different depths were analysed using
Hydrometer test (ASTM-D422, 2007). A solution of sodium hexametaphosphate was
used as dispersing agent as the Braybrook soil is slightly calcareous and may tend to
remain aggregated. The specific gravity of the soils, which is a required parameter to
analyse the Hydrometer test results, was obtained using a water pycnometer (ASTM-
D854, 2010) as shown in Figure 4-9.
Figure 4-9: a) Hydrometer test, b) Specific gravity test
Figure 4-10 shows the variation in particle size with depth. According to the results, the
clay content of the soil below 0.5 m depth is about 45% and is consistent up to 3.5 m.
The top soil layer was contaminated with grass roots and some organic material.
Specific gravity and clay content values are lower at the top layer which reflects the
presence of organic material.
111
Figure 4-10: Specific gravity and fine particle percentages variation with depth in Braybrook Soil
4.3.4 Mineral composition of the soil
A clay mineralogy analysis was performed using X Ray Diffraction (XRD; (Burnett,
1995) to determine the mineral composition of the Braybrook soil. Results from the
quantitative XRD analysis are shown in Table 4-5. The mineral compositions of the soil
at two different depths are almost identical, which confirms the consistency of the basic
soil properties.
The high content of Quartz is related to Silica in the soil that comes from different sizes
of minerals. They can be originated from sandstone, fine argillaceous sediments,
mudstone, claystone or siltstone. However, Braybrook soils have less than 10% of sand,
and therefore, this Quartz may represent the clay size and silt size minerals. The higher
content of Montmorillonite provides evidence of the expansive properties. Similar
expansive properties were reported in Tadanier and Nguyen (1984) for soils with
similar clay mineralogy.
112
Table 4-5: Mineral composition of Braybrook clay
Mineral Depth
0.5-1.0 m 1.0-1.5 m
Quartz (%) 53 59
Montmorillonite (%) 32.5 31
Mica/ Illite (%) 5.5 2
Kaolinite (%) 4 4
Albite (%) 2.5 2
Orthoclase (%) 2 2
Anatase (%) <1 <1
4.4 SITE CLASSIFICATION ACCORDING TO AS2870
The next purpose of soil tests was to classify the site that states the effect of the
reactivity of the site on residential structures. The site classification procedure explained
in AS2870 is based on the shrink-swell characteristics of the soil. This behaviour of the
clay soil can be obtained using the shrink-swell test (AS1289.7.1.1, 2003).
4.4.1 Shrink-swell characteristics of Braybrook soil
A one-dimensional consolidometer was used to measure the swell percentage of the soil
under a 25 kPa surcharge load. The core shrinkage test (Mitchell and Avalle, 1984) was
performed to obtain the shrinkage percentage. The two tests were started at in situ
moisture condition for the undisturbed samples collected at three different depths. Then
the shrink-swell index (Iss) values were calculated in accordance with AS1289.7.1.1
(2003) and their variation with depth is shown in Table 4-6. Iss test was performed many
times during this study to investigate its dependency on in situ moisture content as
described in section 3.6.1. However, the values shown in Table 4-6, which were
considered in site classification, are the results at one location tested during the initial
stage of site selection.
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Table 4-6: Iss values of Braybrook soil at different depths
Depth from
surface (m)
Iss
(%)
0.5 – 1.0 5.69
1.5 – 2.0 5.62
2.5 – 3.0 5.88
4.4.2 Site classification
The site classification requires the Hs, ΔU and the depth of the soil cracks in that
particular area. According to AS2870 (2011), Hs is 2.3 m for Melbourne and ΔU is 1.2
pF. The crack depth is defined as 0.75 of Hs for Melbourne. Based on those values and
the Iss values given in Table 4-6, the layer movements have been calculated and the ys is
obtained as shown in Table 4-7.
Table 4-7: ys calculation
Layer depth - Z(m)
∆Z (m) ∆U
Iss (%)
α Ipt
(%) ys
(mm) 0.0 – 1.0 0.5 0.963 5.69 1 5.69 54.8 1.0 - 1.725 0.725 0.514 5.62 1 5.62 20.9 1.725 – 2.0 0.275 0.236 5.62 1.63 9.16 5.9
2.0 - 2.3 0.3 0.104 5.88 1.58 9.29 2.9 Total ys 84.5
The calculated ys is higher than 75 mm which is the lower limit of class E (Table 2-4)
and hence the site was classified in the Extremely reactive category.
4.5 DEVELOPMENT OF MAIN EXPANSIVE SOIL PARAMETERS
Models developed to describe the volume change behaviour of expansive soil due to
moisture changes commonly use suction as a main soil characteristic (Fredlund and
Rahardjo, 1993, Fredlund and Vu, 2003, Mitchell and Avalle, 1984). This is because
suction represents the stress state of the soil (Fredlund and Rahardjo, 1993). The
relationship between suction and moisture content is one of the two main constitutive
114
parameters (Likos, 2000). The amount of water that can be held by the soil pores at
certain suctions varies with the soil type (Likos, 2000). Water can be trapped in soil
pores and this amount can also change with the compaction of the soil (Dingman,
2002). Hence, the relationship of suction and water content (SWCC) is an important
parameter, which is essential to study expansive soil behaviour.
The moisture content of soil varies with time due to changes in climate conditions. This
phenomenon associates with the permeability of the soil at different moisture contents.
The hydraulic conductivity allows water to flow easily through the porous media and
therefore depends on many soil parameters including pore size, soil grain size and the
amount of water held in the pores (Fratta et al., 2007). It can therefore also be correlated
to the soil suction. This relationship is called the hydraulic conductivity function.
The following sections describe the details of the development of SWCC and the
hydraulic conductivity function of Braybrook soil.
4.5.1 Soil Water Characteristic Curve (SWCC)
The negative pore water pressure created due to water content in soil pores is called
matric suction (Fredlund and Rahardjo, 1993). The variation of matric suction with
water content is expressed by SWCC. Therefore, matric suction and the corresponding
moisture content should be measured to obtain the coordinates of SWCC. The moisture
measurements are straight forward and can be performed simultaneously with the
suction measurements. The moisture content of the soil can be expressed in various
forms. Therefore, SWCC function can be plotted using volumetric water content,
gravimetric water content or degree of saturation. However, the constitutive model
explanations of volume change in expansive soil are associated with volumetric basis
(Fredlund and Rahardjo, 1993, Fredlund and Vu, 2003, Mitchell and Avalle, 1984) and
therefore Braybrook SWCCs have been developed based on both the matric suction and
the volumetric water content.
4.5.1.1 Soil suction
A variety of equipment and different techniques can be used to measure soil suction.
Each of the techniques has its own measuring range and different equilibration time to
produce readings. Table 4-8 shows approximate equilibration time and the measuring
rage of different instruments and techniques. None of the available equipment can
115
measure the full range of suction in SWCC function and therefore the development of
SWCC must be performed in different stages with different equipment.
Table 4-8: Approximate measurement ranges and times for equilibration in measurement and control of soil suction (Murray and Sivakumar, 2010)
Instrument Suction component measured
Typical measurement range (kPa)
Equilibration time
Pressure plate Matric 0-1,500 Several hours to days Tensiometers and suction probes Matric 0-1,500 Several minutes Thermal conductivity sensors Matric 1-1,500 Several hours to days
Electrical conductivity sensors Matric 50-1,500 Several hours to weeks
Filter paper contact Matric 0-10,000 or greater 2-57 days
Thermocouple psychrometers Total 100-8,000 Several minutes to several hours
Transistor psychrometers Total 100-70,000 About 1 hour Chilled mirror psychrometer Total 1-60,000 3-10 minutes
Filter paper non-contact Total 1,000-10,000 or
2-14 days greater
Electrical conductivity of pore water extracted using pore fluid squeezer
Osmotic entire range —
Suction control
Negative (or Hanging) water column technique Matric
0-30 or greater with multiple columns or vacuum control
Several hours to days
Axis translation technique Matric 0-1,500 Several hours to days Osmotic technique Matric 0-10,000 up to 2 months Vapour equilibrium technique Total 4,000-600,000 1-2 months
During the development of Braybrook SWCCs, the high suctions (dry soils) were
measured using WP4C (Decagon, 2012). WP4C uses the chilled mirror psychometric
technique and hence it measures the total suction of the soil. The low suctions (wet
soils) were measured from Hyprop (UMS, 2013). The Hyprop uses the tensiometer
technique which measures the matric suction. However, there is a gap between the
measurable suction ranges of these equipment and that gap was filled using
conventional filter paper measurements. Both total suction and the matric suction can be
measured using the filter paper test and, as a result, the osmotic suction can be
116
calculated. The osmotic suction, which is created by salt concentration of the soil,
appears almost as a constant with the moisture content (Fredlund and Rahardjo, 1993).
The filter paper test was therefore used in this study to obtain the osmotic suction and
then to convert the WP4C readings into matric suction.
4.5.1.2 Hyprop measurements
Hyprop (UMS, 2013) is an instrument specifically developed to produce SWCC of soil
in wet conditions. This instrument uses the tensiometer technique to measure the suction
of soil. The tensiometers consist of a high air entry ceramic tip connected to one end of
a hollow shaft carrying de-gassed water and the other end of the shaft is connected to a
pressure transducer. When the porous tip is inserted into the soil sample, the water is
drawn from the tensiometer due to the suction difference until the stress of the water
inside the tensiometer is equal to the suction of the soil (Murray and Sivakumar, 2010).
The soluble salts that create the osmotic suction can transfer freely through the porous
tip (Murray and Sivakumar, 2010). Therefore, pressure transducer records only the
matric suction. The Hyprop arrangement can take continuous weight measurements of
the soil and can measure the suction in addition to the corresponding moisture content,
which are essentially the coordinates of SWCC.
The initialization of the instrument takes few hours and some experience to set it up
properly. The measurements begin from the saturated stage and continue until the
sample is dried out. The moisture evaporates from the top surface of the sample during
the test. The clay soils take a longer time than sandy soils to reach the dry stage so the
total measurement time can vary from a few hours to few weeks depending on the soil
type.
The Hyprop device uses undisturbed soil samples of 80 mm diameter and 50 mm
height, as shown in Figure 4-11. The samples cannot be taken out of normal tube
sampling, which has a 50 mm diameter. Indeed, 80 mm is an uncommon tube size and it
is difficult to push this size of a ring into soil using a vehicle mounted rig to collect
undisturbed soil at deeper depths. Therefore, the Hyprop samples were collected from a
pre-excavated pit in the Braybrook site shown in Figure 4-12. An eight tonne excavator
was used to dig a 3 m deep pit in a 2x3 m area. The pit was excavated as steps of 0.5 m,
117
as shown in Figure 4-12, to allow access at roughly 0.5 m depths for sample collection.
This pit also helped to visually examine the soil profile in Braybrook site (Figure 4-6).
Figure 4-11: Hyprop sample in the ring
Figure 4-12: Excavation of a pit in Braybrook site to collect Hyprop samples
118
Undisturbed soils were collected into sampling rings using the apparatus that is
provided with the Hyprop devices, as shown in Figure 4-13. The sampling rings were
pushed into soils by hammering and removed by clearing the surrounding soil. The
samples were trimmed at the site, as shown in Figure 4-11, and labelled with the depths
before being taken to the laboratory.
Figure 4-13: Excavation of undisturbed samples using Hyprop sampling device
The samples were saturated under a surcharge pressure corresponding to their depth.
The soil bulk density was about 2 gcm3. For example, soil samples at 0.5 m depth were
saturated under 10 kPa pressure and two porous plates were placed at the top and
bottom to prevent the samples dispersing in water. Next, the samples were submerged in
distilled water (Figure 4-14) and the swelling of the soil was also monitored during
saturation. The samples were left submerged for at least two weeks to confirm that full
saturation was achieved.
119
Figure 4-14: Hyprop samples saturation under a surcharge
Once the saturation process was completed, the Hyprop apparatus was initialized to start
the test. This process involves refilling the tensiometers and the Hyprop sensor unit. The
refilling kit provided with the Hyprop device was used. Figure 4-15 shows the initial
steps of the refilling process. Distilled and de-gassed water must be used for refilling.
De-gassing can be performed using syringes with spacer snaps and once the water is de-
gassed, the tensiometers should be filled without trapping air bubbles. The tensiometers
must be kept in an upright position as shown in Figure 4-15(a). The bottom syringe is
filled with de-gassed water and all the air bubbles must be removed before connecting
to the ceramic tip of the tensiometer. The top syringe is half filled with de-gassed water
and suction is applied by locking the spacer snaps, as shown in Figure 4-15(a). The de-
gassed water from the bottom syringe is forced to travel to the top syringe through the
ceramic tip and the shaft of the tensiometer. This process removes all the air entrapped
in the tensiometers and at least 2 hours is required for this process. The Hyprop consists
of two tensiometers and both of them can be refilled at the same time using four
syringes. The Hyprop sensor unit must also be filled with de-gassed water using the
acrylic attachment and a syringe as shown in Figure 4-15(b).
120
Figure 4-15: Refilling of de-gassed water; a) into tensiometer, b) into Hyprop sensor unit
The refilled tensiometers are then attached to the sensor unit while monitoring the
pressure developed at the pressure sensors. The “tensioVIEW” software, which comes
with the Hyprop equipment, was used to monitor the pressure during the initialization
process. The Hyprop sensor unit needs to be connected to a computer before the
tensiometers attach to the provided slots in the sensor unit. The pressure reading of the
sensor must be carefully monitored and, as described in the manual, should not be
allowed to exceed 100 kPa during the tensiometer attaching process (UMS, 2013). O-
rings are pushed over each of the tensiometer shafts to prevent the entering of dirt
during the test and a silicon gasket is also placed through tensiometers to avoid contact
between the sensor base and the sample as shown in Figure 4-16.
The Hyprop device comes with a balance that can be connected to a computer. The
weight measurements can be recorded using “tensioVIEW” software. Therefore, the
Hyprop sensor unit and the balance were connected to a laptop computer to record the
suction and weight during the test period.
a) b)
121
The saturated soil sample is then prepared to insert two tensiometers. The tensiometers
are in two different heights, as shown in Figure 4-16. This is to measure the suction at
top and bottom of the sample. The top tensiometer is 50 mm long and penetrates about
37.5 mm into the soil samples. The tip of the top tensiometer is located approximately
12 mm below the top surface of the soil. The bottom tensiometer is 25 mm long and
penetrates about 12.5 mm into the soil. An augur with an adapter is provided with the
Hyprop device to make two holes in the soil sample similar to the heights of the two
tensiometers to be penetrated into the soil.
Figure 4-16: Suction measuring unit of Hyprop device(UMS, 2013)
Figure 4-17 shows the sample, with two holes drilled at the bottom surface, ready to
insert the tensiometers. The holes must be filled with de-gassed distilled water before
inserting the tensiometers. The sensor unit with tensiometers is attached to the soil
sample using two fastener clips at either side (Figure 4-18). The sensor is then
connected to the laptop computer and the arrangement is placed on top of the balance
(Figure 4-19). The readings can be recorded in pre-specified time period. The readings
have been recorded in 1 minute intervals during the first few hours of the test and
extended to 10 minutes later.
122
Figure 4-17: The auger adapter and the sample with two holes drilled in the bottom surface
Figure 4-18: The soil sample attached to the Hyprop sensor unit
The moisture evaporates during the test period from the surface of the sample, which
leads to changes in suction and the weight of the soil. The test was conducted inside an
environmental chamber to smoothen the evaporation process and to avoid the unwanted
interruptions such as turbulent wind over the samples surface, disturbance to the
balance, etc. The humidity and the temperature were set to 60% and 20 0C inside the
chamber.
123
Figure 4-19: The Hyprop test is running inside the environmental chamber
The measurements continued for 5 to 7 days. The moisture evaporation from the top
surface crated cracks, as shown in Figure 4-20, which propagated towards the bottom.
Once a developed crack reaches the tensiometer, the porous tip is exposed to the air. At
this point, the tensiometer fails and starts reading an untrue value for the soil suction.
The Hyprop test can be stopped at this point. The dried out sample is shown in Figure
4-20. During the drying process of the Hyprop test, the clay samples tend to stick to the
tensiometer shaft and therefore, it is difficult to remove the samples immediately after
the test. This can be overcome by placing the sample in a water bath after the test
without letting water get into the cable outlet of the sensor unit. Leaving the sample in a
water bath for a few hours will moisturize the samples and facilitate removal from the
sensor unit. The entire soil sample needs to be collected including soils attached to
124
sample ring and the tensiometer shafts. Then, the sample is placed in an oven at 105 0C
to determine the oven dry weight.
Figure 4-20: The soil sample at the end of the Hyprop test
UMS (2013) has provided another software called “HYPROP” to analyse the data
collected from tensioVIEW to develop the SWCC. This software requires the data file
from tensioVIEW and the oven dry weight of the soil sample. The “HYPROP” software
uses the top and bottom tensiometer readings and calculates the representative matric
suction of the soil at a particular time. It uses the initial volume of the soil (the volume
of the sampling ring) and the provided oven dry soil weight to calculate the volumetric
moisture content of the soil. However, for expansive soil, the calculation procedure of
volumetric moisture content of the soil is incorrect in the drying stage. This is because
the expansive soils undergo a significant volume change and cracking during the drying
process hence, the volume of the soil at a particular time cannot be considered as the
volume of the sampling ring. This problem has been overcome using the relationship
between volumetric moisture content and the gravimetric moisture content for the
Braybrook soil. The instant weight of the soil at each record has been extracted from
“HYPROP” software and then the gravimetric moisture contents were calculated using
the oven dry soil weight. Next, they were converted into volumetric moisture contents
using the relationship shown in Figure 4-21. This relationship has been developed using
125
undisturbed samples collected from Braybrook site at different depths. The first point
has been assumed such that, at the zero percent volumetric moisture content,
gravimetric moisture content is also zero. The relationship has an R2 value of 0.99.
Figure 4-21: Relationship between volumetric and gravimetric moisture consents in Braybrook soil
Figure 4-22 shows a portion of SWCC obtained using Hyprop devices as described
above. Appendix-A provides the necessary calculations related to the Hyprop test.
Figure 4-22: A portion of typical SWCC developed using Hyprop
0 5 10 15 20 25 30 35 400
10
20
30
40
50
60V
olum
etric
Moi
stur
e C
onte
nt (%
)
Gravimetric Moisture Content (%)
y = -0.014x2 + 1.9168xR2= 0.99
1 10 1000.35
0.40
0.45
0.50
0.55
Volu
met
ric M
oist
ure
Con
tent
Matric Suction (kPa)
Hyprop measurements
126
4.5.1.3 WP4C measurements
WP4C (Decagon, 2012) measures the total suction of the soil using the chilled-mirror
psychometric technique. The suction readings can be observed in “MPa” units and the
conventional “pF” units. As shown in Figure 4-23, the WP4C consists of a temperature
controller, temperature sensor, mirror and a photo detector cell. The sample must be
placed in a standard ring of 37.5 mm diameter and about 8 mm in height. The sample
ring is made out of plastic or metal. The sample is placed on the drawer and pushed into
the chamber. When the switch is turned to the “READ” position, the sample is raised
and the chamber is sealed to begin the measurement process. Therefore, the sampling
cup must not entirely fill with the samples to prevent the contamination of the sensor
while sealing the chamber.
Figure 4-23: Schematic of chilled-mirror dew-point device (after Leong et al. (2003) )
When the switch is turned to the “READ” position, the equilibration process begins
which makes the relative humidity of the air above the soil equal to the relative
humidity of the air in the soil pore spaces (Murray and Sivakumar, 2010). This takes a
certain amount of time depending on the soil type and the moisture content of the soil.
Once the equilibrium is achieved, the mirror is cooled by carefully controlling the
temperature using a Peltier current (Murray and Sivakumar, 2010). When the
temperature of the mirror reduces, the vapour starts to condensate on the mirror at a
certain point, called the dew point, and it can be recognized by the photo detector cell
because of the difference of the reflection from the mirror (Leong et al., 2003). By using
dew point temperature and the controlling temperature, the relative humidity is
127
calculated and then it can be correlated to the total suction using Equation 4-1 (Bulut et
al., 2001, Leong et al., 2003, Likos, 2000).
𝛹 = −𝑅 × 𝑇
𝜐 × 𝜔ln (𝑅𝐻) .……………...……………………………...…… Equation 4-1
where, Ψ is the total suction in kPa, R is the universal gas constant (8.31432 J/mol.K), T
is the absolute temperature in K, υ is the specific volume of water and ω is the
molecular mass of water vapour in kg/kmol. RH is the relative humidity.
According to Equation 4-1, the total suction is zero when RH is 1 (100% relative
humidity) and it increases with decreasing RH. The chilled-mirror dew point device can
measure the relative humidity up to an accuracy of ±0.01% (Leong et al., 2003). If pure
water is placed in the sample cup, it would record 100% relative humidity, because the
partial pressure of pure water at the equilibrium stage is similar to the saturated vapour
pressure at a particular temperature. This means that the suction of the pure water,
which is essentially the matric component, is zero. However, the partial pressure of the
unsaturated soil pores is less than the saturated vapour pressure of the pure water due to
the pore structure and the free ions of salts in pore water (Bulut et al., 2001). Therefore,
it will result in a relative humidity less than 100% and hence a higher total suction.
The above-mentioned phenomenon is also used to calibrate the chilled-mirror
psychometric devices. The slope of the linear correlation of suction and relative
humidity shown in Equation 4-1 is fixed during the factory calibration and hence only
the zero offset needs to be occasionally fixed (Decagon, 2010). Therefore, the
calibration process needs only one measurement of known suction. Any salt solution
with known osmotic suction can be used to calibrate WP4C. Osmotic suctions of
different salt solutions can be found in the literature (ASTM-D5298, 2003, Decagon,
2010, Bulut et al., 2001). The calibration was achieved by measuring the suction of 0.5
molar KCl and adjusting the value to 2.2 MPa, its suction at 20 0C. However, in this
study, two more standard liquids were used to confirm the measurements from WP4C,
as shown in Figure 4-24. The WP4C manual recommends checking the calibration at
least once in every 50 sample measurements (Decagon, 2010).
128
The WP4C is capable of reliably measuring higher suctions, up to 300 MPa.
Measurements less than 5 MPa can have ±0.05 MPa error whereas the suctions above 5
MPa only have a ± 1% error (Decagon, 2010).
Figure 4-24: Standard liquids used to calibrate the WP4C
For the suction measurements in Braybrook soil, undisturbed samples were used. The
extruded tube samples were prepared to place into WP4C sampling cups using a special
cutting ring and a piston arrangement shown in Figure 4-25. This cutting ring and the
piston arrangement used to prepare the samples without touching the soil. This is
required to measure in situ suctions without losing moisture. However, for the purpose
of measuring suctions to obtain SWCC, the moisture contents of the samples have been
changed in the laboratory. Those samples were prepared in the WP4C sample cups and
then different amounts of water drops were added to change the moisture content. The
sample cups were then sealed and left for few days to achieve the equilibrium before
measuring the suction.
Figure 4-25: Soil sampling devises used to prepare WP4C samples
129
Figure 4-26 illustrates measuring the suction using WP4C. The samples were placed in
the oven in order to achieve the correct moisture content after the suction
measurements. The gravimetric moisture contents were measured and then converted
into volumetric moisture contents using the same relationship used in Hyprop
measurements shown in Figure 4-21.
Figure 4-26: The sample is ready to measure suction using WP4C
Figure 4-27 shows a typical set of suctions obtained from WP4C to develop the later
part of the SWCC. The WP4C measurement data related to Braybrook soil can be found
in Appendix-B. The matric suctions have been used to plot graphs which were obtained
using the osmotic suctions. A filter paper test was employed to obtain osmotic suction
which is described in the next section.
130
Figure 4-27: A portion of typical SWCC developed using WP4C
4.5.1.4 Filter paper measurements
The filter paper method is one of the conventional methods of suction measurements.
By allowing filter papers to attain equilibrium with the soil through vapour or liquid
transfer, the suction can be estimated. If a filter paper equilibrates to the soil’s vapour,
without contacting the specimen, it measures the total suction of the soil. At the same
time, if another filter paper makes contact with the soil and equilibrates with the soil
moisture, it measures the matric suction component (Bulut et al., 2001). The
equilibrium time can vary from days to weeks depending on the soil type and the
moisture content of the soil (Murray and Sivakumar, 2010). Once the equilibrium state
is achieved, the moisture content of the filter papers can be measured and the suction
can be obtained using calibration curves. The contacted filter papers can measure
suctions in a broader range (0-10,000 kPa) compared to non-contacted filter papers
which can only measure suctions within 1000-10000 kPa (Murray and Sivakumar,
2010, Rahardjo and Leong, 2006). A further description of the filter paper suction
procedure can be found elsewhere (ASTM-D5298, 2003, Bulut et al., 2001, Leong et
al., 2002, Fredlund and Rahardjo, 1993).
1000 10000 1000000.10
0.15
0.20
0.25
0.30
0.35
0.40
Vol
umet
ric M
oist
ure
Con
tent
Matric Suction (kPa)
WP4C measurements
131
The undisturbed soil samples collected at different depths were used to measure filter
paper suctions in Braybrook soil. Whatman No. 42 filter papers were used and 47 mm
diameter filter papers were used to measure the total suction whereas matric suction
measurements were taken using 42.5 mm diameter papers. Soil samples of 50 mm
diameter and 100 mm height were used as shown in Figure 4-28. The samples were kept
at least 14 days to reach the equilibrium before measuring the weights of the filter
papers. The standard calibration equations (Figure 4-29) provided in ASTM-D5298
(2003) have been used to obtain the total and matric suctions from filter paper moisture
contents.
Figure 4-28: Filter paper suction measurements of Braybrook soil
Table 4-9 shows the filter paper suction measurements of Braybrook soil. The
calculated osmotic suctions have also been presented in Table 4-9. The Braybrook soil
is slightly calcareous from 0.5 m to 2.5 m and an isolated calcrete layer was observed
about 1.5 to 2.0 m in some places (Figure 4-6). The effect of calcrete can be clearly
observed in terms of osmotic suctions. The soils containing CaCO3 have higher osmotic
suctions than the rest of the soils. All the filter paper suction measurement data related
to Braybrook soil can be found in Appendix-C.
132
Figure 4-29: Calibration Suction-Water Content Curves for Wetting of Filter Paper (ASTM-D5298, 2003)
Table 4-9: Filter paper readings of Braybrook soil
Depth (m)
Gravimetric moisture
content of sample (%)
Total suction (kPa)
Matric suction (kPa)
Osmotic suction (kPa)
0.3-0.8 23.01 2346 1630 716 36.84 779 47 732 29.05 858 238 620
0.5-1.0 24.41 1580 488 1091
1.5-2.0 21.11 4682 2379 2303 23.15 3990 1322 2669 23.45 3958 1355 2604
2.5-3.0 22.18 2243 1586 657
Even though some soils as depicted in Figure 2-6 show almost constant osmotic suction
values irrespective of the moisture contents (Fredlund and Rahardjo, 1993), the
Braybrook results in Table 4-9 show a considerable variation. However, if the soils that
0 10 20 30 40 50 60 70 80 90 1000
1
2
3
4
5
6
Log(kPa) = 2.412 - 0.0135w
Suc
tion,
Log
(kP
a)
Filter paper water content (%)
Log(kPa) = 5.327 - 0.0779w
133
are not contaminated with calcrete are considered, the osmotic suction has changed
within a small range (from 620 kPa to 732 kPa) which appears to be acceptable with the
errors of measurements.
4.5.1.5 Braybrook SWCC
SWCC functions were developed for soils taken at different depths from the Braybrook
site. Matric suction and the corresponding volumetric moisture contents were obtained
as described in the previous sections. The osmotic suction of a particular soil is fairly
constant with the moisture content (Fredlund and Rahardjo, 1993). Apart from the
isolated calcrete layer, the Braybrook soil appears to be consistent. Table 4-9 suggests
that the soils with no calcrete contamination have approximately constant osmotic
suction over a wide moisture range. Since WP4C provides total suction, the osmotic
suctions calculated from the filter paper test were used to convert them into matric
suctions. However, when converting the total suction into matric suction, the very high
suction measurements taken from WP4C have a minimal influence from the osmotic
component.
VADOSE/W package in Geo-Slope (2013) software was used to draw appropriate
curves of SWCCs using measured points. Since there were enough measurements of
suction and corresponding moisture content, SWCCs were drawn using a smooth line
along the measured point and therefore, available estimating models in GeoSlope were
not used. Figure 4-30 shows the developed SWCCs for different depths in Braybrook.
Different markers used in Figure 4-30 to indicate the measurements made using
Hyprop, Filter paper method and WP4C. These SWCCs were used to develop the finite
element model of expansive soil described in the following chapters. SWCCs of soils at
different depths have almost identical functions and this reflects the consistency of the
soil properties discussed in the previous sections.
134
Figure 4-30: SWCCs of soil from Braybrook site at different depths
4.5.2 Hydraulic conductivity function
The moisture movement in soils can be explained by the hydraulic conductivity
(permeability) of soil and is dependent on the void ratio and the moisture content
(Fredlund and Rahardjo, 1993). The saturated hydraulic conductivity (Ksat) depends on
the void ratio of the soil, however, it is usually considered as a constant in transient flow
analysis (Fredlund and Rahardjo, 1993). The ability of moisture movement in
unsaturated soils can be observed using hydraulic conductivity verses matric suction
relationship, which is called hydraulic conductivity function.
Ksat can be measured using conventional methods such as the falling head and constant
head permeability test. However, measuring unsaturated hydraulic conductivity is
difficult as it changes considerably in the transient process (Fredlund and Rahardjo,
1993). Therefore, certain empirical correlations can be used to develop the hydraulic
conductivity function. The following section describes the Ksat measurement and the
development of hydraulic conductivity function for Braybrook soil.
1 10 100 1000 10000 1000000.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
Vol
umet
ric M
oist
ure
Con
tent
Matric Suction (kPa)
0-0.3 m 0.3-0.8 m 0.8-1.3 m 1.3-1.8 m 1.8-2.5 m
Markers for different measurements; Squares:- Hyprop, Circles:- Filter paper, Triangles:- WP4C
135
4.5.2.1 Saturated hydraulic conductivity
The saturated hydraulic conductivities of Braybrook soils were obtained using the
constant head method. The tri-axial apparatus was used to apply the head differences.
The undisturbed soil samples collected at different depths were used to perform the
tests. The specimen diameters were approximately 50 mm and the lengths
approximately 100 mm. The specimens were covered with a flexible membrane and
then placed in a tri-axial machine as shown in Figure 4-31. An appropriate surcharge
pressure was applied based on the depth of the sample and then the sample was allowed
to become saturated before proceeding to the consolidation stage, as explained in
ASTM-D5084 (2003). When the sample is consolidated, a pressure difference was
applied between the top and the bottom flows while maintaining a constant sample
pressure. The pressure difference was kept at 2-3 kPa as explained in the standard. The
flow rates were recorded in 60 minute intervals. Table 4-10 shows a typical data sheet
of the Ksat test. All the Ksat measurement data related to the Braybrook soil can be found
in Appendix-D.
Figure 4-31: Saturated hydraulic conductivity test for Braybrook soil using tri-axial machine
136
Table 4-10: Saturated hydraulic conductivity data sheet
Material Specification
Saturation Duration
Reading Duration
Sample Diameter (cm)
Sample Area (cm2)
Sample height, L
(cm)
24 hours
48 hours
0.50 19.634375 10.6
Curing Duration
Water Temperature (°C)
Cell pressure
(kPa) Flow
direction Cell
Diameter (cm)
Water density at test temperature
(gr/cm3)
24 hours 20 410.4 Downward 0.75 0.998207
Readings
Reading No
Reading (cm3)
Q (cm3)
Time (sec)
q (cm3/sec)
Top Pressure (kPa)
Bottom pressure (kPa)
Δ h (cm)
i=Δh/L k (m/sec)
1 127.936 13.5 3600 0.00377 410.4 407.9 24.48 2.31 8.32E-07
2 141.521 12.4 3600 0.00345 410.4 407.9 24.48 2.31 7.62E-07
3 153.959 12.5 3600 0.00349 410.4 407.9 24.48 2.31 7.71E-07
4 166.538 12.3 3600 0.00342 410.4 407.9 24.48 2.31 7.56E-07
5 178.883 12.1 3600 0.00337 410.4 407.9 24.48 2.31 7.44E-07
6 191.032
3600
410.4 407.9 24.48 2.31
Average value 7.73E-07
Q: - flow amount, q:- flow rate, Δ h:- pressure head difference, L:- sample thickness, i:- hydraulic gradient, k:- hydraulic conductivity
Figures 4-32 and 4-33 show the variation of Ksat with the time of measurement. The
tests were continued til at least five consecutive readings appear fairly constant and
then the average of those readings was taken as the Ksat of the particular layer as shown
in Table 4-11. The Ksat of the surface layer is higher than that of the bottom layers
indicating that the top layer is different from the other layers as shown in basic soil
properties variation (Figures 4-7 and 4-10). The values of other layers are in the range
of dense clay soils (Das, 1998).
137
Figure 4-32: Variation of Ksat with time of measurement - top two layers
Figure 4-33: Variation of Ksat with time of measurement - bottom two layers
0 30000 60000 90000 120000 150000 180000 210000-1
0
1
2
3
4
5
6
7
8
9
10
Sat
urat
ed h
ydra
ulic
con
duct
ivity
(m/s
) x 1
0-7
Time after starting test (sec)
0-0.4 m 0.5-1.0 m
0 20000 40000 60000 80000 100000 1200000.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Sat
urat
ed h
ydra
ulic
con
duct
ivity
(m/s
) x 1
0-9
Time after starting test (sec)
1.0-1.4 m 1.5-1.8 m
138
Table 4-11: Saturated hydraulic conductivities of Braybrook soil
Sample depth (m)
Saturated Hydraulic
conductivity (m/s)
0.0 - 0.4 7.73 x 10-07 0.5 - 1.0 1.57 x 10-07
1.0 - 1.4 3.43 x 10-09
1.5 - 1.8 1.99 x 10-09
4.5.2.2 Prediction of hydraulic conductivity function
Hydraulic conductivity of unsaturated soils is less than Ksat of the soil because of the
reduction of area available to moisture flow (Briaud, 2013). It is difficult to measure the
hydraulic conductivity in the unsaturated state of the soil therefore empirical
correlations were used to develop the hydraulic conductivity function. GeoSlope
software has incorporated models to predict the hydraulic conductivity function using
SWCC. There are two models available in the software which were developed by
Fredlund et al. (1994) and Van Genuchten (1980). The software requires defining the
SWCC and Ksat of the particular soil to develop the hydraulic conductivity function.
However, a number of different equations are employed in these models, and they are
presented here.
Equations 4-2 to 4-4 show the equations used by Fredlund et al. (1994) to predict the
hydraulic conductivity function using the SWCC
𝑘𝑤 = 𝑘𝑠
∑𝜃𝑒𝑦−𝜃𝛹
𝑒𝑦𝑖𝜃′𝑒𝑦𝑖𝑁
𝑖=𝑗
∑𝜃𝑒𝑦−𝜃𝑠𝛹
𝑒𝑦𝑖𝜃′𝑒𝑦𝑖𝑁
𝑖=𝑗
.……...…….……………………...…… Equation 4-2
kw = the conductivity for a specified negative pore-water pressure (m/s),
ks = the measured saturated hydraulic conductivity (m/s),
θs = the volumetric water content,
e = the natural number 2.71828,
139
y = a dummy variable of integration representing the logarithm of negative pore-water
pressure,
i = the interval between the range of j to N,
j = the least negative pore-water pressure to be described by the final function,
N = the maximum negative pore-water pressure to be described by the final function,
Ψ = the suction corresponding to the jth interval
θ’ = the first derivative of the Equation 4-3
𝜃 = 𝐶(𝛹)𝜃𝑠
[ln [𝑒 + (𝛹
𝑎)
𝑛
]]𝑚 ………...…….……………………...…… Equation 4-3
a = approximately the air-entry value of the soil,
n = a parameter that controls the slope at the inflection point in the volumetric water
content function,
m = a parameter that is related to the residual water content,
C(Ψ) = a correcting function defined in Equation 4-4,
𝐶(𝛹) = 1 −ln (1 +
𝛹
𝐶𝑟)
ln (1+1,000,000
𝐶𝑟) ……..…….……………………...…… Equation 4-4
where, Cr is a constant related to the matric suction corresponding to the residual water
content and the typical value is 1500 kPa.
More details about the correlation can be found in Fredlund et al. (1994) and Vadose
(2013). For certain soils, Fredlund et al. (1994) predicts low conductivity in high
suction ranges. For example, the given correlation for the Yolo light clay given in
Fredlund et al. (1994) has a close match only up to 4 kPa. Therefore, the other available
correlations have also been considered in this study.
Van Genuchten (1980) also provided a correlation to predict the hydraulic conductivity
function using SWCC and saturated conductivity. Equation 4-5 shows the relationship
given by Van Genuchten (1980).
140
𝑘𝑤 = k𝑠
[1 − (𝑎𝛹(𝑛−1))(1 + (𝑎𝛹𝑛)−𝑚)]2
[(1 + 𝑎𝛹)𝑛]𝑚
2
….………......……...…… Equation 4-5
ks= saturated hydraulic conductivity,
a,n,m = curve fitting parameters,
n = 1/(1-m)
Ψ = required suction range.
Van Genuchten (1980) noted that the curve fitting parameters can be properly estimated
at the halfway point between saturated water content and the residual water content of
the SWCC of the soil. Therefore, those points must be specified to estimate the
hydraulic conductivity function. More details on the estimation procedure can be found
in Van Genuchten (1980) and Vadose (2013).
Figure 4-34 shows the predicted hydraulic conductivity functions for the surface layer
in the Braybrook site using Fredlund et al. (1994) and Van Genuchten (1980) models.
The predictions of the Fredlund et al. (1994) model are slightly higher at low suctions
whereas the Van Genuchten (1980) model predictions are considerably higher than the
Fredlund et al. (1994) model predictions at in the high suction range. The hydraulic
conductivity functions obtained from both models were used in a finite element model
analysis of Braybrook soil behaviour, which is described in the next chapters. However,
it appears that the conductivity functions obtained from the Fredlund et al. (1994) model
produces a closer match with field measured soil moisture contents. Figure 4-35 shows
hydraulic conductivity functions developed for the Braybrook site using the Fredlund et
al. (1994) model. The functions were obtained using SWCCs shown in Figure 4-30 and
the saturated hydraulic conductivities given in Table 4-11.
141
Figure 4-34: Predicted hydraulic conductivity functions for Braybrook soil at 0-0.4 m
Figure 4-35: Hydraulic conductivity functions (based on Fredlund’s model) of Braybrook soil at different depths
0.1 1 10 100 1000 10000 1000001E-16
1E-15
1E-14
1E-13
1E-12
1E-11
1E-10
1E-9
1E-8
1E-7
1E-6
1E-5
Hyd
raul
ic c
ondu
ctiv
ity (m
/s)
Matric Suction (kPa)
Van Genuchten (1980) model Fredlund et al (1994) model
0.1 1 10 100 1000 10000 1000001E-16
1E-15
1E-14
1E-13
1E-12
1E-11
1E-10
1E-9
1E-8
1E-7
1E-6
1E-5
Hyd
raul
ic c
ondu
ctiv
ity (m
/s)
Matric Suction (kPa)
0 - 0.4 m 0.5 - 1.0 m 1.0 - 1.4 m 1.5 - 1.8 m
142
4.6 SUMMARY
This chapter describes the selection of Braybrook site and the characterization of the
Braybrook soil. Since Western suburbs of Melbourne are well known for expansive
soils, more than 10 sites in West Melbourne were considered to select an appropriate
field site. The Braybrook site contains three large vacant blocks of lands and is
primarily a flat site. There is a deep profile of clay soils in Braybrook site. The top soil
layer of about 0.5 m consists of silty clay and some organic matter. Below the top soils,
plasticity indices are higher than 50% whereas linear shrinkages are about 18%
throughout the profile. These basic soil tests indicated that the soils are highly
expansive and consistent with depth. Taken together, these factors resulted in the
selection of the Braybrook for long-term field monitoring.
In addition to the basic soil tests, more specific properties were examined during the
laboratory investigation. A shrink well test was performed for soils collected at different
depths to determine the Iss. Then, the site was classified based on the AS2870 and was
classified in the extremely reactive category. However, X-Ray Diffraction tests revealed
that there is more than 50% of Quartz, which can be originated from sandstone, fine
argillaceous sediments, mudstone, claystone or siltstone. Since Braybrook soils have
less than 10% of sand, the Quartz content may represent the clay size and silt size
minerals. However, there is more than 30% of Montmorillonite in the mineral
composition in Braybrook clay that is a primary cause of the expansiveness. Similar
expansive characteristics were recorded in different Australian soils with a similar
Montmorillonite composition to the Braybrook clay.
More measurements were taken to determine the expansive soil characteristics. During
the development of SWCC, various equipment including Hyprop, WP4C and filter
papers were used to measure suctions at different moisture levels. SWCCs were
developed for soils collected at different depths. The soils below the top 0.5 m showed
similar SWCCs. Furthermore, saturated hydraulic conductivities were obtained using tri
axial apparatus. The top soils had higher Ksat value compared to the dense clay at the
bottom layers due to the presence of silty clay and organic matters. The ksat of bottom
layers were in the range of 10-9 ms-1. The hydraulic conductivities of unsaturated soils
143
were determined from available correlations with SWCC. These hydraulic conductivity
functions were developed for soils collected at different depths in the Braybrook site.
This comprehensive data set is beneficial for both practitioners and researchers. It
provides characteristics of typical basaltic clay found in West Melbourne which are
useful in site classification and modelling. Indeed, Braybrook soil properties were used
in prediction models developed in this study. The models require field monitoring data
and the next chapter describes the field monitoring and data analysis.
144
5. FIELD INSTRUMENTATION AND DATA ANALYSIS
5.1 INTRODUCTION
The selection and the soil properties of the Braybrook test site are described in the
previous chapter. The aim of the field instrumentation was to install devices required to
monitor the seasonal variation of soil moisture content and the subsequent ground
movement. The soil moisture variation was recorded using the neutron probe technique
and magnetic extensometers were used to measure the movement of the soil layers at
different depths. The movement of ground surface was monitored using small paving
blocks laid next to the magnetic extensometers. Details of those devices, the installation
procedure, calibration, data collection and the interpretation are described in this
chapter.
5.2 FIELD MONITORING SYSTEM
5.2.1 Overview
As described in the literature review chapter, the monitoring of soil moisture content
and the subsequent movement is a challenging task. A non-destructive and repeatable
technique is essential in the regular monitoring of soil moisture in a particular location
over long periods. In the current research, this task was achieved by using neutron probe
moisture measuring technique in this study.
Most previous investigations used ground movement probes to monitor soil movements.
However, in this technique, soil movement at different depths cannot be measured using
a single probe and hence many probes have to be used at different depths. This issue has
been overcome by using magnetic extensometers (HMA, 2013) in this study. The
magnetic extensometers consist of a datum magnet at the bottom, which can be placed
at a stable depth. The extensometer can be used to measure the soil movements at
different depths. More details on the magnetic extensometer are provided in the next
sections of this chapter.
5.2.2 Soil moisture monitoring
The neutron moisture measuring procedure followed in this study requires a neutron
probe and access tubes inserted to the deepest measurement depth. The following
145
section describes the installation, calibration and data collection of the neutron probe
technique.
5.2.2.1 Installation of access tubes
According to AS2870, Hs is specified as 1.8 – 2.3 m for Melbourne, which is the
possible depth of suction variation. It was decided to investigate moisture and soil
movements up to 3 m depth from the ground surface to cover the specified Hs with an
allowance for possible changes. At the Braybrook site, aluminium access tubes with a
diameter of 50 mm were installed up to 3 m depth. A gap between the soil and the
access tube can cause erroneous reading in neutron counts (Li et al., 2003b) and allow
unwanted ingress of surface water, therefore, the boreholes for the access tubes drilled
to the same diameter as the tubes and then the tubes were pushed into the holes (see
Figure 5-1) to achieve a neat fit. The first 200-300 mm of soils was very dry and hence
created certain gaps around the pipe. However, these gaps were closed after the
installation using the surrounding soil. Hence the rain water was not able to infiltrate
along the surface of the tube. Upon insertion of the access tubes into the ground about
100 mm of each tube was maintained above ground for the placement of the neutron
probe control unit, as shown in Figure 5-2. Access tubes were capped at the top to
prevent water intrusion while not in use.
Figure 5-1: Neutron probe access tube pushing into the borehole
146
Figure 5-2: CPN 503DR neutron probe used in the Braybrook site
5.2.2.2 Calibration of Neutron probe
The neutron probe provides the count of thermalised neutrons through interaction with
soil moisture. Therefore, a calibration curve is needed to convert the neutron count into
the volumetric moisture contents. The relationship between neutron counts and
volumetric moisture content is an exponential curve through the zero intercept (Ward
and Wittman, 2009). Undisturbed samples were collected from the bore holes cored to
insert the access tubes, and used to measure the volumetric moisture content. These
moisture contents and the probe readings collected on the installation date were used to
develop the calibration curve.
Volumetric moisture content (θ) and neutron counts (N) follow the relationship given in
Equation 5-1 where ‘A’ and ‘B’ are constants.
𝜃 = 𝑒𝐴 × 𝑁𝐵 ……………..…………….....……………………...…… Equation 5-1
Equation 5-1can be converted into a linear relationship to determine the A and B
constants as shown in Equation 5-2. The calibration curve of the neutron probe is shown
in Figure 5-3. The linear fit has an R2 of 0.86 (standard error = 0.028).
147
Equation 5-3 shows the calibration line with the obtained constants for the Braybrook
soil. This calibration was further checked and confirmed with more measurements
(neutron probe and collected soil samples) made during different days of the study.
These measurements are given in section 5.4.1.
ln(𝜃) = 𝐴 + 𝐵 × ln (𝑁) …..…………….....……………………...…… Equation 5-2
ln(θ )= -2.9406+0.7005 × ln(N) ….……….………………........…… Equation 5-3
Figure 5-3: Calibration curve of the neutron Probe
5.2.2.3 Neutron probe measurement procedure
The neutron probe is connected to its control unit via a cable and the length of this cable
is decided based on the required maxim depth of measurements. A 5 m cable was used
in the present study. The stoppings are attached to the cable (see Figure 5-2) to hold the
probe while collecting measurements.
9.15 9.20 9.25 9.30 9.35 9.40 9.453.45
3.50
3.55
3.60
3.65
3.70
Ln(V
olum
etric
mc
%)
Ln(Neutron counts)
Measured data Linear Fit Upper 95% Confidence Limit Lower 95% Confidence Limit
148
In this study, the stoppings were attached to the cable to collect readings at every 250
mm distance from the topmost measurement. Therefore, 11 stoppings were connected to
the cable, as shown in the schematic in Figure 5-4. When the probe is lowered into the
access tube via cable, the stopping can be clamped into the control to hang the probe at
the required depth. The lengths of the probe and the control unit are 300 m and 350 mm
respectively. A 100 m height portion of access tube protrudes from the ground to hold
the control unit, as demonstrated in Figure 5-4. The locations of stoppings of the cable
were arranged by considering those distances.
Figure 5-4: Schematic of neutron probe measuring arrangement
Once the probe is clamped at a certain depth, the measurements can begin. The time
allowance for emissions and the detection of neutrons can be selected as 16, 32 or more
seconds. An initial test was performed to observe the sensitivity of the time allowance
on the accuracy of the repetitive readings. It was found that 16 seconds produces
reliable, repetitive neutron counts. It was also useful to finish the measurements of all
149
the access tubes installed in the Braybrook site within a day. Measurements were taken
two times at each depth to calculate the average neutron count represent the moisture
level at particular depth. The distances of the stopping locations were converted to depth
from the ground surface and then the results expressed as shown in Table 5-1.
Table 5-1: Results from neutron probe measurements
Stop No
Depth from
Ground (mm)
NP Reading Trial 1
NP Reading Trial 2
Average NP
counts
Volumetric MC (%)
11 350 10613 10689 10651 35.00 10 600 11211 11234 11223 36.31 9 850 10897 10933 10915 35.61 8 1100 10913 10919 10916 35.61 7 1350 11527 11392 11460 36.84 6 1600 11795 11801 11798 37.60 5 1850 11826 11700 11763 37.52 4 2100 12119 11939 12029 38.12 3 2350 12185 12183 12184 38.46 2 2600 12225 12425 12325 38.77 1 2850 12538 12387 12463 39.07
Since, the radioactive material can be harmful for the health, the amount of neutron
absorbed to the persons involved in the measuring was carefully monitored. An
authorization certificate and training were required to use the neutron probe and users
wore a monitoring badge at all times. The badge was independently checked every three
months for neutron absorption.
5.2.3 Ground movement monitoring
5.2.3.1 Installation of magnetic extensometers
The installation procedure of the extensometer is a challenging task. After the spider
magnets are attached to the collapsible pipe at the desired spacing, the magnet legs are
folded and held together with temporary ties, as shown in Figure 5-5. Magnetic
extensometers are installed into pre-drilled boreholes. The diameters of the bore holes
are limited by the size of the folded legs of the magnets and the capability of them to
penetrate to the soil. If the borehole diameter is too large then the magnet legs cannot
penetrate the surrounding soil. The spider magnets used in this study were capable of
150
penetrating soil in a borehole up to 150 mm diameter. However, the compressed legs of
the magnets were able to push into 100 mm diameter borehole safely. The temporary
ties must be removed after installation, which will release the legs and allow them to
penetrate the soil. All the temporary ties are held by a steel code which is parallel to a
collapsible pipe and attached to the bottom using a glue tape. The steel cord is removed
after the installation and the magnet legs are allowed to unfold. They enter the soil with
the sudden releasing of the ties. Figure 5-6 shows the installation of one of the magnetic
extensometers in the Braybrook site. The prearranged spacing between the spider
magnets could change during the installation due to the flexibility of the collapsible pipe
and the pressure applied to insert into the borehole.
Figure 5-5: Releasing mechanism of the spider magnet in extensometer
151
Figure 5-6: Magnetic extensometer installation at the Braybrook site
The extensometers were covered using plastic caps as shown in Figure 5-7. Since the
measuring probe reads the distance between the spider magnets, a reference point at the
surface is required to convert the readings into layer depths. A concrete paver was
placed and kept undisturbed next to the extensometer (see Figure 5-7). The depths of
spider magnets were measured with respect to the level of this paver and its level was
considered as the ground level at that location. As demonstrated in Figure 5-7, a spirit
level was used to transfer the top level of the paver to the top of the extensometer
conduit pipe to obtain the measurements.
Figure 5-7: Ground surface movement measurements using extensometer
152
5.3 SITE LAYOUT
Figure 5-8 shows the monitoring locations in the Braybrook site. Three extensometers
are located on the site marked as E1, E2 and E3. All the extensometers were located in
the intact area of the blocks and away from the trees. The datum of the E1 extensometer
was placed 5 m below the ground surface while E2 and E3 had datum magnets at 4 m
depth. The access tubes for neutron probes were located next to each extensometer to
monitor the moisture variations along with the soil layer movements. Concrete paving
blocks of measuring 300x300 mm in plain area and 50 mm thick were placed on the
ground surface at locations marked as TP and CP. The purpose of the paving blocks was
to measure the movement of the ground surface which was done using a surveying
level. Moisture changes have been monitored close to each TP paver to monitor the
effect of trees on soil moisture. However, the measurements related to the tree are not in
the scope of this thesis. The E1 extensometer was located in the first block where the
tree is situated, while E2 and E3 extensometers were located in third block away from
the tree. CP paving blocks around E2 and E3 extensometers were placed in a grid of 2
m x 5 m. The purpose of those paving blocks was to check the deviation of ground
surface movement around extensometers.
Figure 5-8: Monitoring Plan of the Braybrook Site
TP 1 to 14 : Paving blocks around the treeCP 1 to 10 : Paving blocks away from the tree siteE 1 to 3 : Magnetic extensometersTN 6 : Neutron probe access tube close to E1CN 1 : Neutron probe access tube close to E2CN 2 : Neutron probe access tube close to E3
Location marks are not to scale
TN6
CN1
CN2
153
5.4 INVESTIGATION OF FIELD MONITORING DATA
The extensometers and the neutron probe access tubes were installed at two different
times. The extensometer E1 was installed in October 2012 and the other two were
installed in March 2013. The neutron probe access tubes which were inserted next to
extensometers are considered in this analysis. Neutron probe access tube denoted as
“TN6” was located next to the E1 extensometer. The neutron probe access tubes, CN1
and CN2 were located next to E2 and E3 extensometers, respectively. The data
collected from those locations are described in the following section.
5.4.1 Soil moisture profiles with time
The CN1 and CN2 were located close to each other and hence a similar moisture
variation was expected. However, slight differences in the clay content of surface soils
at two locations were observed. The CN2 location has a sandy top layer about 200 mm
and then gradually changed to silty clay and clay soil. Apart from the CN2 location,
such a different soil profile was not observed in other areas of the Braybrook site.
Hence, it could be a site disturbance from its previous usage. However, the area used to
perform the ongoing monitoring had been part of the back yard as shown in Google map
photo taken in 2010 (Figure 4-3). Some potholes surrounded by clay soil chunks were
observed near the CN1 location. There was also a slope difference on the ground.
Figures 5-9 and 5-10 show the moisture variation at CN1 and CN2 locations.
154
Figure 5-9: Volumetric moisture content profiles at CN1 location
Figure 5-10: Volumetric moisture content profiles at the CN2 location
The neutron probe calibration equation gives the volumetric moisture content and it also
has been used in the finite element modelling. Therefore, volumetric moisture content
has received more interest than gravimetric moisture content. The volumetric moisture
20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dep
th (m
)
Volumetric moisture content (%)
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20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 500.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dep
th (m
)
Volumetric moisture content (%)
10/04/2013 20/06/2013 21/08/2013 21/10/2013 11/12/2013 29/01/2014 26/02/2014 01/04/2014 01/05/2014 05/06/2014 08/07/2014 12/11/2014 25/03/2015
155
content profiles at different times are considered in both figures. Since the top soils in
the CN1 and CN2 locations differ, a considerable offset can be observed in the moisture
results of the surface layer. The first measurements were taken at 0.35 m. Apart from
the top most measurements; the rest of the soil showed a similar moisture variation in
CN1 and CN2. There is not a significant moisture change below 1.25 m depth within
this 18-month period.
Figure 5-11 illustrates the volumetric moisture contents obtained from the TN6 location.
While the moisture variation is slightly different to the CN1 and CN2 locations, the
depth of moisture variation can be observed up to 1.25 m depth which is similar to the
other two locations. Interestingly, there was not a significant moisture variation
recorded at this location from May to November in 2014. Indeed, the moisture readings
at 0.41 m and 0.66 m depths appear to be constant during that period. This may be due
to a certain problem in that location or the access tube. These erroneous readings are
further discussed in the next section by comparing these readings to the extensometer
data from that location.
Figure 5-11: Volumetric moisture content profiles at the TN6 location
22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 520.0
0.5
1.0
1.5
2.0
2.5
Dep
th (m
)
Volumetric moisture content (%)
10/04/2013 20/06/2013 21/08/2013 21/10/2013 11/12/2013 29/01/2014 26/02/2014 01/04/2014 01/05/2014 05/06/2014 08/07/2014 12/11/2014 25/03/2015
156
There can be a considerable influence from the cracks on the moisture content of deep
soil. Cracks were observed at the Braybrook site during the summer months and the
depths of these cracks were recorded using a thin steel cable, as shown in Figure 5-12.
Table 5-2 lists the crack depths around the access tubes that were observed in different
site visits. Some cracks of more than 0.75 m depth were also observed in the Braybrook
site. The observations given in Table 5-2 show the depth that steel cable can penetrate,
however, the actual crack depths could be greater than that. The runoff water from
rainfall can easily penetrate those cracks and can cause sudden moisture increments at
deeper depths. When the rainwater penetrated the cracks along the surface of the access
tube, it will result a high moisture reading from the neutron probe. This is an
unavoidable shortcoming of using the neutron probe technique in cracking soils. The
penetrated moisture becomes entrapped in the cracks when they close in the winter and
this can cause changes in the bottom soil. Therefore, even in a relatively small area of a
site, there can be locations with considerable differences in moisture contents. This
scenario can be observed in Figures 5-9 and 5-10.
Figure 5-12: Crack measurements using a steel cable
157
Table 5-2: Description of crack depth measurements at CN1, CN2 and TN6 locations
Date Crack description
CN1 CN2 TN6
26/02/2014
Few cracks around the
tube. Maximum depth was ~400 mm
Few cracks
around the tube.
Maximum depth was ~150 mm
Few cracks around
the tube. Maximum depth was ~100 mm
1/04/2014
Few cracks around the
tube. Maximum depth was ~650 mm
Two cracks
around the tube.
Maximum depth was ~300 mm
Few cracks around
the tube. Maximum depth was ~300 mm
1/05/2014 No cracks No cracks No cracks 5/06/2014 No cracks No cracks No cracks 8/07/2014 No cracks No cracks No cracks
12/11/2014
Few cracks around the tube with 300-500
mm deep. A gap of 350 mm deep
was observed beside the
tube
Few cracks
around the tube with 100 mm deep. A
small gap of 30 mm deep was observed beside the
tube
No cracks around the tube
but a small gap of 50 mm deep was observed beside the
tube
Gravimetric moisture contents were occasionally measured to observe the differences of
the neutron probe results. The samples were collected at different depths around the
TN6 location and the gravimetric moisture contents were measured from the collected
disturbed samples. The volumetric moisture contents obtained from the neutron probe
(NP) were converted into gravimetric moisture contents using the relationship shown in
Figure 4-21. Figure 5-13 shows a comparison highlighting that the direct measured
moisture contents are slightly different from the NP measurements. There is a difference
158
of approximately 3% between the direct measurements and NP measurements in deeper
depths. However, this difference was observed even within the measured values at
depths greater than 1.5 m, where it is unlikely to have such a moisture change. It should
be noted that gravimetric moistures corresponding to neutron probe readings shown in
Figure 5-13 were obtained using two conversions. The neutron counts were converted to
volumetric moistures using the calibration equation (Equation 5-3) and then were
converted to gravimetric moisture contents using the relationship shown in Figure 4-21.
The errors associated with those conversions could be a reason for the differences of
neutron probe and actual measurements shown in Figure 5-13. The surface soils have a
huge variation due to local effects. However, the NP measurements successfully
captured the trend of moisture variation.
Figure 5-13: Comparison of moisture contents obtained from the neutron probe and the samples
All three locations shown in Figures 5-9 to 5-11 have similar moisture variation at
deeper depths. The moisture contents have fluctuated severely within the surface layer.
The changes below 1.25 m are negligible and within the standard error of the NP
calibration. Figure 5-14 shows the soil moisture variation at CN1 with the monthly
rainfall. The rainfall data were obtained from nearby weather station from the Bureau of
15 20 25 30 35 40 45 50
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Dep
th (m
)
Gravimetric moisture content (%)
20-Jun-13 NP 21-Aug-13 NP 21-Oct-13 NP 11-Dec-13 NP 20-Jun-13 Measured 21-Aug-13 Measured 21-Oct-13 Measured 11-Dec-13 Measured
159
Meteorology. According to Figure 5-14, the moisture content of the top soil changed in
response to the monthly rainfall. The moisture contents of upper layers reflect the
rainfall pattern with a certain time lag, which is due to the permeability of the soil. This
pattern can also be interrupted by the cracks on the surface in dry season. The
fluctuations of the moisture contents are gradually decreasing with the depth. The
moisture content variation at 1.6 m depth provides evidence of this lower sensitivity to
monthly rainfalls within those 18 months.
Figure 5-14: Volumetric moisture content (VMC) change comparison with monthly rainfall (Location – CN1)
Interestingly, when the moisture variation is plotted with the daily rainfall, as shown in
Figure 5-15, it highlights that the surface moisture variation is more sensitive to the
daily rainfall variation rather than the monthly rainfall. This behaviour is prominent in
the summer and hence indicates the effect of the cracks on the moisture content of the
surface layer.
Jan-13 Apr-13 Jun-13 Sep-13 Dec-13 Mar-14 Jun-14 Sep-140
10
20
30
40
50
60
70
80
90
100 Monthly Rainfall (mm) VMC at 0.35 m VMC at 0.60 m VMC at 0.85 m VMC at 1.10 m VMC at 1.35 m VMC at 1.60 m
Month
Mon
thly
Rai
nfal
l (m
m)
20
25
30
35
40
45
50
Vol
umet
ric m
oist
ure
cont
ent (
%)
160
Figure 5-15: Volumetric moisture content (VMC) change comparison with daily rainfall (Location – CN1)
5.4.2 Ground movement monitoring
The extensometer readings were also taken on the same dates as the NP measurements.
Tables 5-3 to 5-5 show the soil movements observed from E1, E2 and E3
extensometers, respectively. Distances between the spider magnets measured on the
installed date are considered as the initial thickness of the layers. The distance between
the ground surface paving block and the first spider magnet is considered as the top
layer. The results of the regular measurements are shown as the differences of the layer
thicknesses with respect to the immediate previous measurements. Hence, the positive
values represent swell movement and the negative values indicate shrink movement.
1/01/2013 31/05/2013 28/10/2013 27/03/2014 24/08/20140
5
10
15
20
25
30
35
40 Daily Rainfall (mm) VMC at 0.35 m VMC at 0.60 m VMC at 0.85 m
Date
Dai
ly R
ainf
all (
mm
)
20
25
30
35
40
45
50
Vol
umet
ric m
oist
ure
cont
ent (
%)
161
Table 5-3: Soil layer movements from E1 extensometer
Initial layer
thickness (m)
Change of the layer thickness with
respect to previous visit reading (mm)
05/1
0/20
12
07/0
2/20
13
26/0
3/20
13
20/0
6/20
13
21/0
8/20
13
21/1
0/20
13
11/1
2/20
13
29/0
1/20
14
26/0
2/20
14
01/0
4/20
14
01/0
5/20
14
05/0
6/20
14
08/0
7/20
14
03/0
9/20
14
12/1
1/20
14
25/0
3/20
15
Top layer 0.983 -9 -3 30 13 1 3 -24 -11 -3 15 4 3 3 -18 -13 2nd layer 0.748 -3 1 -3 4 2 2 1 0 -1 -1 0 1 -1 2 2 3rd layer 1.062 2 -1 3 -2 0 1 0 1 -1 0 0 0 0 0 0 4th layer 0.450 3 0 2 -2 0 0 0 0 1 0 0 0 0 0 0 Bottom layer 1.727 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 4.970 -7 -3 32 13 3 6 -23 -10 -4 14 4 4 2 -16 -11 Incremental change (0 mm at start)
0 -7 -10 22 35 38 44 21 11 7 21 25 29 31 15 0
Table 5-4: Soil layer movements from E2 extensometer
Initial layer
thickness (m)
Change of the layer thickness with respect to previous visit reading
(mm)
04/0
3/20
123
26/0
3/20
13
20/0
6/20
13
21/0
8/20
13
21/1
0/20
13
11/1
2/20
13
29/0
1/20
14
26/0
2/20
14
01/0
4/20
14
01/0
5/20
14
05/0
6/20
14
08/0
7/20
14
03/0
9/20
14
12/1
1/20
14
25/0
3/20
15
Top layer 0.750 -1 14 2 0 -4 -16 -2 0 8 4 -5 2 -5 6 2nd layer 0.976 0 12 -4 1 4 -3 -4 -3 -3 -2 0 2 0 -2 3rd layer 1.044 0 0 0 0 0 0 0 0 -1 1 0 -1 1 1 Bottom layer 1.078 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 Total 3.848 -1 26 -2 1 0 -19 -6 -3 4 3 -5 3 -5 5 Incremental change (0 mm at start)
0 -1 25 23 24 24 5 -1 -4 0 3 -2 1 -4 0
162
Table 5-5: Soil layer movements from E3 extensometer
Initial layer
thickness (m)
Change of the layer thickness with respect to previous visit reading
(mm)
04/0
3/20
123
26/0
3/20
13
20/0
6/20
13
21/0
8/20
13
21/1
0/20
13
11/1
2/20
13
29/0
1/20
14
26/0
2/20
14
01/0
4/20
14
01/0
5/20
14
05/0
6/20
14
08/0
7/20
14
03/0
9/20
14
12/1
1/20
14
25/0
3/20
15
Top layer 0.803 1 23 9 0 -4 -29 -2 0 9 3 5 2 -13 7 2nd layer 1.092 -1 0 6 3 1 1 -5 -3 -2 -1 0 0 0 0 3rd layer 1.059 0 4 -4 1 0 -1 1 0 0 0 0 0 -1 1 Bottom layer 1.036 0 0 0 -1 0 1 0 0 0 0 -1 0 1 -1 Total 3.990 0 27 11 3 -3 -28 -6 -3 7 2 4 2 -13 7 Incremental change (0 mm at start)
0 0 27 38 41 38 10 4 1 8 10 14 16 3 0
All three extensometers reveal that there are significant movements occurred in the top
layer and less movement in the second layer. The spider magnets of the magnetic
extensometers are roughly 1 m apart. A change of level between adjacent magnets,
which are embedded in the surrounding body of soil, is considered to be a movement of
the soil layer contained between the two magnets. The top layer shows more than 80%
movements of the total movement in all three locations. The lower layers moved a little
and in fact, they moved by less than the error margin of the extensometer (±2mm).
Therefore, the remaining 20% of movement is likely to be within the second layer of
soil. However, moisture changes plotted in Figures 5-9 to 5-11 show that no significant
moisture changes occurred below 1.25 m, and hence it is suggested that no significant
soil movement occurred beyond that depth. This is mainly because the observations are
limited to a short period of monitoring (approx. 2 years).
Figure 5-16 shows incremental ground surface movements measured at three locations.
Extensometer E1 recorded a total seasonal movement of 54 mm within the two-year
period, whereas E2 and E3 recorded 29 mm and 41 mm seasonal movement,
respectively, in the 18-month period. The higher movement recorded in E1 suggests that
there is a variation of soil properties and other local effects within the site. The unusual
163
changes in moisture content in CN2 location as described in Section 5.4.1 could be the
reason for lesser ground movement observed in E2 location.
Figure 5-16: Surface movements measured at 3 locations and monthly rainfall
Figures 5-17 to 5-19 shows the variation of soil movements from the extensometer with
rainfall. The three locations showed similar variations in soil movement patterns. These
figures illustrate the swell movements in winter and settlements in the summer. Surface
movements follow the monthly rainfall pattern, i.e., the higher the depth of soil, the
lesser the sensitivity of soil to the rainfall pattern.
0
20
40
60
80
100
120
Mon
thly
rain
fall
(mm
)
29 mm
1/10/2012 1/04/2013 1/10/2013 1/04/2014 1/10/2014-15
-10
-5
0
5
10
15
20
25
30
35
40
45 Monthly rainfall (mm) E1 - Surface movement E2 - Surface movement E3 - Surface movement
Date
Incr
emen
tal s
oil m
ovem
ent (
mm
)
54 mm
41 mm
164
Figure 5-17: Soil movements in response to monthly rainfall - E1 extensometer
Figure 5-18: Soil movements in response to monthly rainfall - E2 extensometer
0
20
40
60
80
100
120
140
Mon
thly
rain
fall
(mm
)
25/10/2012 25/04/2013 25/10/2013 25/04/2014 25/10/2014-15
-10
-5
0
5
10
15
20
25
30
35
40
45
50 Monthly rainfall (mm) Surface movement Movement at 0.983 m Movement at 1.731 m Movement at 2.793 m Movement at 3.243 m
Date
Incr
emen
tal s
oil m
ovem
ent (
mm
)
0
20
40
60
80
100
120
Mon
thly
rain
fall
(mm
)
1/03/2013 1/09/2013 1/03/2014 1/09/2014-15
-10
-5
0
5
10
15
20
25
30 Monthly rainfall (mm) Surface movement Movement at 0.750 m Movement at 1.726 m Movement at 2.770 m
Date
Incr
emen
tal s
oil m
ovem
ent (
mm
)
165
Figure 5-19: Soil movements in response to monthly rainfall - E3 extensometer
This behaviour of the soil movements is comparable with the moisture variation
described in the previous section. The severe moisture changes in the top layer caused
the subsequent volume changes. Even though soil movements recorded in the E1
extensometer were relatively similar to the E3 during May to November 2014, the TN6
access tube, which is next to E1, showed no change in moisture contents during that
particular period. This provides strong evidence that there was something went wrong at
TN6 location during that period. Therefore, TN6 readings were ignored and CN1 and
CN2 locations were considered in modelling the moisture changes of the Braybrook soil
using a finite element model.
The level changes of paving blocks placed around E2 and E3 extensometers provide
evidence for differential ground movement in a relatively small area. Table 5-6 shows
the movement paving blocks CP1 to CP10 in the site layout shown in Figure 5-8. The
datum of E3 extensometer was considered in measuring these levels. The pavers also
indicate a similar settlement and heave movement trend to the extensometers. They
follow similar pattern in heave and settlements with the monthly rainfall variation as
shown in Figure 5-20. However, there are some level differences among these blocks,
which highlight the influence of local effects such as surface slope differences, potholes
and cracks which created differential moisture changes and hence ground movement
0
20
40
60
80
100
120
Mon
thly
rain
fall
(mm
)
1/03/2013 1/09/2013 1/03/2014 1/09/2014-15
-10
-5
0
5
10
15
20
25
30
35
40
45 Monthly rainfall (mm) Surface movement Movement at 0.803 m Movement at 1.895 m Movement at 2.954 m
Date
Incr
emen
tal s
oil m
ovem
ent (
mm
)
166
within 10 m2 area. Cracks were observed around the pavers during the summer months.
However, soils were certainly wet underneath the pavers due to prevention of
evaporation from the paver.
Table 5-6: Movements of paving blocks
Paver No
Height (m) above the datum
on 26/03/2013
Change of the height above datum with respect to previous visit reading (mm)
20/0
6/20
13
21/0
8/20
13
21/1
0/20
13
11/1
2/20
13
29/0
1/20
14
26/0
2/20
14
1/04
/201
4
1/05
/201
4
5/06
/201
4
8/07
/201
4
3/09
/201
4
12/1
1/20
14
CP1 4.008 31 12 2 -3 -36 -6 7 5 2 4 2 -22 CP2 3.981 30 15 5 0 -44 -6 8 5 0 4 3 -17 CP3 3.985 32 11 2 -4 -28 -5 4 3 -1 4 4 -4 CP4 3.976 30 8 2 -4 -28 -6 8 2 0 4 4 -5 CP5 3.985 25 3 0 -4 -11 -1 7 -5 0 3 0 0 CP6 3.951 27 7 -1 -2 -24 -1 8 0 1 3 1 2 CP7 3.970 30 10 0 -3 -28 -4 7 1 1 3 2 -14 CP8 3.959 31 13 1 -4 -35 -5 7 9 0 4 3 -12 CP9 3.977 32 17 1 -2 -32 -5 6 0 2 4 3 -7 CP10 3.981 26 8 3 -2 -22 -5 7 -1 1 3 1 -4 Average 29 11 1 -3 -29 -5 6 3 1 4 2 -9 Stdv 3 4 2 1 8 2 3 4 1 1 1 8 Min 25 3 -1 -4 -44 -6 -3 -5 -1 3 0 -22
Max 32 17 5 0 -11 -1 8 10 2 4 4 2
167
Figure 5-20: Incremental paver movements with monthly rainfall
5.5 SUMMARY
This chapter explains the installation of field monitoring instruments in Braybrook site
and the details of the monitored data over a two year period. Monitoring soil moisture
changes and consequent ground movements were the focus of the field monitoring. The
neutron probe technique was used to monitor soil moisture changes. Hence, neutron
probe access tubes were installed at a number of locations in the Braybrook site. The
neutron probe reads the number of neutrons that interact with soil moisture. Therefore, a
calibration equation was developed between neutron counts and volumetric moisture
content. Field samples were collected at different times to cross check the results
obtained from the neutron probe readings. Another correlation was developed between
volumetric and gravimetric moisture contents to help in comparing readings obtained
from neutron probe and the field samples in Braybrook site. The comparison showed
that neutron probe readings gave similar moistures as field sample measurements but
include about 3% difference, possibly due to errors in measurement and calibration.
Magnetic extensometers were installed in Braybrook at three locations next to the
neutron probe access tubes. They were used to measure surface and sub-surface soil
0
20
40
60
80
100
120
Mon
thly
rain
fall
(mm
)
1/09/2012 1/03/2013 1/09/2013 1/03/2014 1/09/2014-10
-5
0
5
10
15
20
25
30
35
40
45
50
55 Monthly rainfall (mm) CP1 CP2 CP3 CP4 CP5 CP6 CP7 CP8 CP9 CP9 CP10
Date
Incr
emen
tal p
aver
mov
emen
t (m
m)
168
movements. This monitoring was continued regularly from April 10th, 2013 to March
25th, 2015.
Seasonal moisture variations were observed at three locations over the two year period.
All these locations showed similar moisture profiles at deeper depths. However, there
were some differences in near surface measurements possibly due to local effects such
as slope differences, potholes and grass cover changes. The soil moisture changes were
observed to occur down to about 1.25 m over the monitored periods. The most
significant changes were observed in the top 0.75 m soils. Monthly moisture values of
near surface soils followed the rainfall pattern with a certain time lag. This time lag
indicated the influence of soil permeability. The seasonal heave and settlements were
observed in three magmatic extensometer located next to the neutron probe access
tubes. Similar to the moisture changes, most of the movements occurred in the top soil
layers. The maximum average seasonal ground movement was in the range of 40-50
mm. In addition to the magnetic extensometer readings, surface movements were
measured using paving blocks placed at certain grid points around the extensometer
locations. The levels of paving blocks confirmed the overall ground movement pattern
as shown in the extensometers. The monitoring data collected from this field monitoring
were used to developing a prediction model that is described in the next chapter.
169
6. MODELLING OF MOISTURE CHANGES IN EXPANSIVE SOIL
6.1 INTRODUCTION
As described in the previous chapter, the moisture changes of expansive soils under
open field condition in response to seasonal climate conditions were observed during
the regular site monitoring. These types of soil moisture changes occur during the
design life of a residential structure and the difference of changes in open ground and
covered areas can have substantial consequences on the performance of the structures.
Therefore, the footings of light weight structures must be designed to withstand such
conditions. It is impractical to monitor the expansive soil behaviour for a long period,
therefore, modelling such effects helps to observe the long term responses and to review
the relevant design procedures.
In this study, the finite element modelling approach was used to determine the long-
term moisture movement in expansive soil. More specifically, the Vadose/w package of
GeoSlope, a commercially available software, was used to analyse the soil and climate
interaction. The initial phase of the study was performed using a one dimensional model
to observe the vertical moisture movement in an open ground. The model was validated
using the Braybrook field data collected over a period of two years as presented in the
previous chapter. Using this validated model, the effect of different climate conditions
on soil moisture was investigated. The model was then extended into two dimensional
domain to observe the effect of cover slabs on lateral moisture movements. This chapter
describes the modelling approach, calibration and the model predictions.
6.2 FINITE ELEMENT MODELLING TOOL SELECTION
Much research has been undertaken on expansive soil modelling, however, the
objectives of these models varied considerably. The major limitation of previous studies
is the inability to consider direct soil climate interaction. Hung (2002) developed a
comprehensive model to observe expansive soil behaviour using the finite element
approach. The model uses the uncoupled and coupled approach to predict soil moisture
changes and the consequent volume changes. In the uncoupled approach, the soil
moisture changes were analysed first and then the results were used to determine the
volume changes in the next stage. In coupled approach, both soil moisture and the
170
volume changes analyse simultaneously . The uncoupled analysis was performed using
a partial differential equation solver called FlexPDE whereas the software COUPSO
(Pereira, 1996) was used to perform the coupled analysis.
In Hung’s (2002) study, soil moisture changes due to abnormal moisture conditions
such as leaky pipes and tree drying were considered. Since these models produce
moisture and volume changes, a number of input parameters are required. Elastic
parameters of the soil with respect to net normal stress and matric suction, elastic
parameters of water phase with respect to net normal stress and matric suction are the
main parameters required in these models. In addition, SWCC, coefficient of
permeability, Poisson's ratio and swelling index are also required. Certain assumptions
are commonly accepted in the modelling of expansive soil behaviour. For example, the
air phase is considered as continuous and the soil is considered as isotropic and non-
linear elastic material. Moreover, the pore water is treated as incompressible. The effect
of air diffusing through water, air dissolving in water and the movements of water
vapour are not considered. The effects of cover slabs on soil moisture were also
considered in these models. However, in Hung’s study, consideration of climate
condition is limited to only rainfall and the other climate influences were not
considered. The rainfall influence was considered as an external moisture source to the
soil. More details on these models can be found in previous literature (Hung, 2002, Vu
and Fredlund, 2004). Both coupled and uncoupled approaches resulted in a similar
outcome but the displacements from the coupled analysis were slightly smaller.
Wray (2005) developed a FORTRAN programme, “SUCH”, to predict the expansive
soil behaviour in a three dimensional domain. This model uses the moisture diffusion
concept suggested by Mitchell (1979) and the volume change model developed by
Wray (1997). The model can be used to investigate the moisture variation and volume
changes of soil in response to different edge conditions such as ponding, evaporation
and infiltration and tree drying. The model was validated for three different cities in
different countries. Climate effects on soil moisture were considered in the “SUCH”
model using surface suction boundary condition. Mitchell’s (1979) diffusion model
describes the suction variation in the top surface of the soil as sinusoidal variation
depending on a frequency related to the number of wetting-drying cycles per year. The
TMI of the areas was used to obtain the equilibrium suction from the correlation given
171
by Russam and Coleman (1961). This equilibrium suction is used as the bottom
boundary condition. Further details about this model have been previously described
(Mitchell, 1984a, Mitchell, 1979, Wray, 1997, Wray, 2005). While climate effects were
considered in this model, real weather data were not used. Therefore, a discrepancy can
be observed between the measured and predicted results in certain locations. This could
be due to an ineffectiveness of TMI in representing soil moistures at different climate
conditions.
Fatahi (2007) developed a comprehensive three dimensional model to study the changes
of soil suction induced by vegetation. He used ABACUS software and developed
specific sub routines using FORTRAN to accommodate the suction effects on moisture
flow through a porous media. Initial soil suction, evapotranspiration and the relevant
soil properties were used as input parameters. The hydraulic conductivity of soil was
not directly considered in this model due to inclusion of potential evapotranspiration
rate. The model produced soil suction and displacement in response to tree root drying.
However, real weather data was not used. In contrast, Jones et al. (2009) used a two
dimensional model to study the unsaturated behaviour of Adelaide clay. The purpose of
the model was to investigate the slope stability of saline clay soil due to flooding and
leaking pipes. SVFlux and SVSlope packages available in SVOffice (SVOffice, 2015)
were used to combine the unsaturated and saturated mechanics to develop the model.
SWCC and hydraulic conductivity of the soil were the main soil parameters used in this
model. In saline clays in Adelaide, osmotic suction is the dominant suction component
(Jones et al., 2009) and therefore, total suction was considered instead of matric suction
in developing SWCC. The climate effects were also included but were limited to rainfall
and evaporation. The balance between rainfall and potential evaporation was calculated
prior to determining whether the soil is drying or wetting, which reduced the number of
time steps to run the model. The model produces soil suction profiles at different times.
Rajeev et al. (2012) modelled the soil and climate interaction as a part of a study related
to the failure issues of pipes buried in expansive soils. A one dimensional soil column
was modelled using Vadose/w package in GeoSlope software (Geo-Slope, 2013). The
main soil parameters considered in this model were SWCC, hydraulic conductivity,
thermal conductivity and specific heat capacity. Soil properties were measured in two
different sites in Melbourne to validate the model and weather data was taken from
172
weather stations in the two sites. Regular soil moisture measurements were collected
using neutron probe technique. The model was capable of predicting soil moisture
profiles and temperature changes at different times and produced results in good
agreement with measured data.
The Vadose/w software is capable of handling climate boundary using readily available
weather data. The climate boundary condition includes rainfall, evaporation, relative
humidity, temperature and wind. The software uses actual evaporation instead of
potential evaporation in considering the climate effects on vadose zone. The actual
evaporation is calculated using the available rainfall and the other climate parameters.
In addition to the climate, the influence of vegetation and water ponding can also be
included. Vadose/w software tool is equipped with all the required conditions in this
study and hence it was selected to develop the finite element model.
6.3 MODELLING OF SOIL MOISTURE MOVEMENT USING VADOSE/W
The finite element models of investigating climate effects on expansive soils was
previously limited to selecting the flux boundary condition as potential evaporation
(Jones et al., 2009, Wray, 2005). But Vadose/w was developed to accommodate actual
evaporation using the observations from Wilson (1990). The actual evaporation is
calculated from Penman-Wilson formulation as shown in Equation 6-1.
AE = ΓQ + υEa
υA + Γ .…………….………….....……………………...…… Equation 6-1
AE = actual vertical evaporative flux (mm/day)
Γ = slope of the saturation vapour pressure versus temperature curve at the mean
temperature of the air (kPa/0C)
Q = net radiant energy available at the surface (mm/day)
υ = psychometric constant
Ea = f(υ)Pa (B-A)
173
f(υ) = function dependent on wind speed, surface roughness and eddy diffusion
= 0.35(1+0.15Ua)
Ua = wind speed (km/hr)
Pa = vapour pressure in the air above the evaporating surface (kPa)
B = inverse of the relative humidity of the air = 1/hA
A = inverse of the relative humidity at the soil surface = 1/hr
This formulation requires wind speed, relative humidity and net radiation from climate
parameters. However, if the net radiation data is not available, the evaporative flux can
also be calculated using Equation 6-2.
E = PE (hr − (
Vp.sat.air
Vp.sat.soil)hA
1 − (Vp.sat.air
Vp.sat.soil)hA
) …………..….…………………...…… Equation 6-2
E = evaporative flux (mm/day)
PE = user supplied potential evaporation (mm/day)
hr = relative humidity at the soil surface
Vp.sat.air = saturated vapour pressure of air
Vp.sat.soil= saturated vapour pressure of soil surface
hA = relative humidity of air above the soil surface
The temperature of the soil surface can be calculated using Equation 6-3 (Wilson, 1990)
for “no snow” conditions.
Ts = Ta +1
υf(υ)(Q − E) …………..….…………………...…… Equation 6-3
Ts = temperature at the soil surface (0C)
174
Ta = temperature of air above the soil surface (0C)
υ = psychometric constant
AE = actual vertical evaporative flux (mm/day)
Q = net radiant energy available at the surface (mm/day)
Vadose/w calculates the relative humidity and the water vapour pressure at the soil
surface using equations presented by Edlefsen and Anderson (1943) which are based on
thermodynamic relationships. The saturated vapour pressure at the soil surface is
dependent on the soil surface temperature, and it can be calculated as described by
Lowe (1977).
The effects of the vegetation on surface soils can be included in Vadose/w using three
different formulations. The variations of leaf area index and depth of the roots must be
specified as functions of the time period of the analysis. In addition, the moisture
limiting factor, which is dependent on the ability of vegetation to suck moisture from
soil at different sections, has to be specified.
The actual evaporation is limited by the water absorption from the vegetation and it is
calculated from Equation 6-4 (Vadose, 2013).
𝐴𝐸 = 𝐴𝐸∗[1 − (−0.21 + 0.7 × √𝐿𝐴𝐼)] ………….……………...…… Equation 6-4
AE* = actual vertical evaporative flux (mm/day)
AE = modified actual vertical evaporative flux (mm/day)
LAI = leaf area index
The potential transpiration is dependent on potential evaporation as can be defined in
Equation 6-5.
𝑃𝑇 = 𝑃𝐸(−0.21 + 0.7 × √𝐿𝐴𝐼) ………………….……………...…… Equation 6-5
PE = potential evaporation (mm/day)
175
PT = potential transpiration (mm/day)
The actual transpiration depends on the ability of tree roots to suck moisture from the
soil. Therefore, it is related to the plant moisture limiting factor and root depth, as
shown in Equation 6-6.
𝐴𝑇 = 𝑃𝑅𝑈 × 𝑃𝑀𝐿 ……….….…….…….....……………………...…… Equation 6-6
AT = actual transpiration (mm/day)
PML = plant moisture limiting factor
𝑃𝑅𝑈 =2𝑃𝑇
𝑅𝑇(1 −
𝑅𝑛
𝑅𝑇) 𝐴𝑛
RT = total thickness of root zone
Rn = the depth of the node in question
An = the nodal contributing area of the node in question
Then, the modified actual evaporative flux is used in governing flow equations.
Equations 6-7 and 6-8 show the governing differential equations for the one
dimensional coupled process of moisture and heat flow.
𝜕
𝜌𝜕𝑧(𝐷𝑉
𝜕𝑃𝑉
𝜕𝑧) +
𝜕
𝜕𝑧(𝑘𝑧
𝜕[𝑃
𝜌𝑔+ 𝑧]
𝜕𝑧) + 𝑄 = 𝜆
𝜕𝑃
𝜕𝑡 ………..…...…… Equation 6-7
𝐿𝑉
𝜕
𝜕𝑧(𝐷𝑉
𝜕𝑃𝑉
𝜕𝑧) +
𝜕
𝜕𝑧(𝑘𝑡𝑧
𝜕𝑇
𝜕𝑧) + 𝑄𝑡 + 𝜌𝑐𝑉𝑧
𝜕𝑇
𝜕𝑧= 𝜆𝑡
𝜕𝑇
𝜕𝑡 ..….…… Equation 6-8
ρ = water density,
z = elevation head,
Dv = vapour diffusivity coefficient
176
Pv = vapour pressure of soil moisture
kz = hydraulic conductivity in the z (vertical) direction
P = water pressure
g = acceleration due to gravity
Q = applied boundary flux
Λ = slope of the volumetric water content function
t = time
Lv = latent heat of vaporization
ktz = thermal conductivity in the z-direction
T = soil temperature,
Qt = applied thermal boundary flux
ρc = volumetric specific heat value
Vz = Darcy's water velocity in vertical direction
λt = volumetric specific heat value.
The above governing equations are solved in finite element method as programmed in
Vadose/w software. The detailed solving procedure can be found in the software manual
(Vadose, 2013). The key input parameters required to analyse those equations are
described in next section.
6.4 SOIL PARAMETERS
6.4.1 Soil Water Characteristic Curve (SWCC)
SWCC is the most important parameter considered in unsaturated soil mechanics
(Fredlund and Rahardjo, 1993). The Vadose/w model determines the nodal suction
values based on the applied flux boundary results in a particular time step and then
selects the corresponding hydraulic conductivity to disperse the moisture to surrounding
nodes. Therefore, SWCC governs the moisture movement modelling in Vadose/w.
177
There are three options available in Vadose/w to include the required SWCC of a soil
material. There are typical SWCCs for different soil types, available in Vadose/w to be
used in general studies. Those SWCCs are useful for preliminary studies, however, for
comprehensive studies, those typical curves may not be suitable. As a second option,
SWCCs can be estimated using basic soil properties of soil. The results from particle
size distribution and liquid limit are required to estimate the SWCC using a modified
method of Kovács (1981) model. Third, the software allows defining the measured
points and creating unique SWCC. The curve can be adjusted to obtain a smooth shape
of a SWCC while representing the measured points. Soil suctions and the corresponding
moisture contents were measured in this study as described in chapter 4 and the SWCC
curves were developed using Vadose/w software. SWCCs at different depths shown in
Figure 4-30 were used to develop the model.
6.4.2 Hydraulic conductivity function
Since it is difficult to measure the unsaturated hydraulic conductivity of soil, the
relationship between hydraulic conductivity and matric suction was estimated using
available prediction models as described in Chapter 4. Two correlations were
considered provided by Fredlund et al. (1994) and Van Genuchten (1980). It was
observed that the Van Genuchten (1980) model predicts high conductivity in high
suctions. The predictions from the method developed by Fredlund et al. (1994) provide
a closer match between predicted and measured moisture contents. Therefore, hydraulic
conductivity functions obtained from Fredlund et al. (1994) correlation were used in the
Vadose/w model (Figure 4-35). In the Braybrook site, bed-rock was not found up to
depth of 5 m, therefore 6 m of soil model was considered. Hydraulic property functions
were developed only up to about 2 m depth. Therefore, appropriate assumptions were
made in using hydraulic conductivity functions of the bottom layers as described in
section 6.7.1.
6.4.3 Thermal properties of soil
Full thermal soil materials in Vadose/w require specifying the thermal properties of soil
against the volumetric moisture content. Thermal conductivity and the specific heat
capacity of Basalt clay soils have linear variation with moisture content (Barry-
Macaulay et al., 2011, Barry-Macaulay et al., 2013, Rajeev et al., 2012). The sensitivity
analysis of the developed model (section 6.10.1) shows that thermal properties have
178
minimal impact on soil moisture content. Therefore, the thermal properties of soils were
not measured in this study and those properties available in literature (measured from
sites close to Braybrook) were used to develop the model. The variation of thermal
conductivity and specific heat capacity with volumetric moisture content were measured
in Altona soil by Rajeev et al. (2012). Altona is approximately 6 km from Braybrook
and has Basalt clay soil. Therefore, thermal properties shown in Figures 6-1 and 6-2
were taken from Altona site and used at appropriate depths to develop the Vadose/w
model in this study.
Figure 6-1: Thermal conductivity functions used in this study
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70
20
40
60
80
100
120
140
160
180
Ther
mal
con
duct
ivity
(kJ/
days
/m/°
C)
Volumetric moisture content
0 - 0.3 m 0.3 - 0.8 m 0.8 - 1.3 m 1.3 - 6.0 m
179
Figure 6-2: Specific heat capacity functions used in this study
The Vadose/w software requires defining a profile of an initial soil temperature to
calculate the relative humidity and the water vapour pressure at the soil surface. These
values were not measured in this study. However, observations of Rajeev et al. (2012)
suggest that there is a small spatial variation in soil temperature (measured at two sites
in suburbs which are about 20 km away from the Braybrook and have basaltic clay
soil). Hence, the measured soil temperature profile in Altona (Rajeev et al., 2012) was
used as soil temperature in Braybrook as shown in Figure 6-3.
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Vol
umet
ric S
peci
fic H
eat C
apac
ity (k
J/m
³/°C
)
Volumetric moisture content
0 - 0.3 m 0.3 - 0.8 m 0.8 - 1.3 m 1.3 - 6.0 m
180
Figure 6-3: Initial soil temperature function used in this study
6.5 CLIMATE DATA
Vadose/w uses five climate parameters to define the climate boundary condition that are
specified as daily inputs for the analysis period. Since the weather data has not been
monitored in the Braybrook site, the nearest Meteorology department weather station
was used to collect data. The main parameter is the rainfall, which is the moisture input
component. Essendon airport weather station has climate data starting from 1889. The
daily rainfall data was obtained for the period of 1889 to 2015. The software requires
specifying the starting and finishing time of rainfall. This information is difficult to
collect due to different rain patterns throughout a day, and hence it is not available.
Therefore, 0.00 and 24.00 hours were used as the starting and finishing time of rain by
assuming the rain occurred throughout the entire day. The variation of rainfall within
that time period was specified as a sinusoidal variation. The hourly rainfall variation
considered in Vadose/w software is shown in Figure 6-4 for a typical (assumed) data set
given in Table 6-1.
11 12 13 14 15 16 17 18
-1600
-1400
-1200
-1000
-800
-600
-400
-200
0
Soil temperature (0C)
Dep
th (m
m)
181
Table 6-1: Hourly rainfall distribution (sinusoidal) of daily rainfall – assumed data set
Hourly rainfall distribution (mm) Hour Day
1 Day 2
Day 3
Day 4
Day 5
Day 6
Day 7
1 0.000 0.000 0.000 0 0.000 0 0.000 2 0.014 0.021 0.007 0 0.003 0 0.011 3 0.056 0.084 0.028 0 0.011 0 0.045 4 0.122 0.183 0.061 0 0.024 0 0.098 5 0.208 0.312 0.104 0 0.042 0 0.167 6 0.309 0.463 0.154 0 0.062 0 0.247 7 0.417 0.625 0.208 0 0.083 0 0.333 8 0.525 0.787 0.262 0 0.105 0 0.420 9 0.625 0.937 0.313 0 0.125 0 0.500
10 0.711 1.067 0.356 0 0.142 0 0.569 11 0.778 1.166 0.389 0 0.156 0 0.622 12 0.819 1.229 0.410 0 0.164 0 0.655 13 0.833 1.250 0.417 0 0.167 0 0.667 14 0.819 1.229 0.410 0 0.164 0 0.655 15 0.778 1.166 0.389 0 0.156 0 0.622 16 0.711 1.067 0.356 0 0.142 0 0.569 17 0.625 0.938 0.313 0 0.125 0 0.500 18 0.525 0.787 0.262 0 0.105 0 0.420 19 0.417 0.625 0.208 0 0.083 0 0.333 20 0.309 0.463 0.154 0 0.062 0 0.247 21 0.208 0.313 0.104 0 0.042 0 0.167 22 0.122 0.183 0.061 0 0.024 0 0.098 23 0.056 0.084 0.028 0 0.011 0 0.045 24 0.014 0.021 0.007 0 0.003 0 0.011
Total (Daily rainfall - mm)
10 15 5 0 2 0 8
Figure 6-4: Hourly rainfall distribution used in vadose software (for data set given in Table 6-1)
0 24 48 72 96 120 144 1680.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
Rai
nfal
l (m
m)
Hours
Hourly rainfall (mm)
182
Solar radiation or evaporation is required to calculate the actual evaporation in
Vadose/w as described in section 6.3. However, solar radiation is not available for all
weather stations. Therefore, evaporation was used in this study to define a climate
boundary. Relative humidity, temperature and the wind speed data were also obtained
from Essendon airport weather station. These data is also treated as sinusoidal variation
in Vadose/w software (Vadose, 2013). Table 6-2 shows typical data set provided to the
climate boundary in Vadose/w software.
Table 6-2: Typical set of data used in climate boundary in Vadose/w software
Day
Temperature (0C)
Relative humidity (%) Wind Rainfall Rainfall period Evaporation
Max Min Max Min (m/s) (mm) Start (hr) End (hr) (mm/day)
1 23.9 9.8 83 47 7.8 0 0 24 4.2
2 17.4 12.7 93 82 9.7 0 0 24 3
3 26.8 10.1 84 61 9.2 0 0 24 0.8
4 24 15.2 55 50 15.8 0.2 0 24 7
5 22.2 14.6 73 68 8.6 0 0 24 4
6 15 12.3 100 96 11.4 6.3 0 24 1.2
7 18.6 8.6 77 62 9.7 3 0 24 0.2
8 17.7 8.8 85 74 9.7 0 0 24 4
9 16.4 8 100 65 15 0 0 24 2.8
10 16.7 8.1 61 54 12.8 3.6 0 24 2.4
6.6 VEGETATION INFLUENCE
The vegetation effects on surface soil moisture were considered in terms of three
functions in Vadose/w software, namely Loaf Area Index (LAI), Root Depth (RD) and
Plant Moisture Limiting (PML) factor. LAI accounts for the growth of vegetation
during the period of analysis. The portion of solar radiation absorbed by the leaves of
vegetation governs the amount that falls onto the surface soils (Vadose, 2013). The crop
growing season data can be used to develop the LAI variation during a year. While the
grass cover of Braybrook site was properly maintained throughout the monitoring
period, the growing of the grass cover depends on the weather condition of the area. In
183
the Braybrook site, the grass cover began to grow in March. It begins dying during the
summer and becomes deadly dry at the end of December. Hence the LAI function has
been defined from March to December. The variation of the grass cover in Braybrook is
shown in Figure 6-5. This grass cover was categorized as poor based on the
observations. LAI can vary with the density of the vegetation cover (Atwell et al.,
1999). Therefore, highest LAI was selected as 1.0 and the given typical function in
Vadose (2013) manual was modified accordingly. The LAI function used in the model
shows in Figure 6-6.
Figure 6-5: Grass cover in Braybrook site
The PML function defines the capability of vegetation to suck moisture from soils at
different soil suction levels. When the soil is saturated, vegetation can suck moisture at
its highest capability. This capability gradually reduces while soil is drying and
becomes impossible when the soil is dried below the wilting point. The typical PML
function given in Vadose/w manual shows that, below 1500 kPa suction, the trees
cannot draw moisture from the soil (wilting point). This typical function has been used
in this study (Figure 6-7).
184
Figure 6-6: Estimated leaf area index function for Braybrook site
Figure 6-7: Typical PML function used in the study (Vadose, 2013)
The effect of roots spread throughout the top soil layer was considered using a root
depth function. The depth of the root zone experiences a moisture loss due to tree root
drying. The root depth varies with the growth of the trees and hence it is varies during
the analysis period. The beginning and end times of this variation is similar to the LAI
function. In Braybrook, the clay soil layer becomes stiffer towards the bottom and
0 50 100 150 200 250 300 350 4000.00
0.25
0.50
0.75
1.00
Leaf
Are
a In
dex
Days in a year
0 200 400 600 800 1000 1200 1400 16000.0
0.2
0.4
0.6
0.8
1.0
1.2
Pla
nt m
oist
ure
limiti
ng fa
ctor
Matric suction (kPa)
185
therefore it is difficult for grass roots to proceed. A rich layer of grass roots was
observed in the top 100 mm and it was gradually sparser towards 300 mm depth. Apart
from some occasional roots, no grass roots were observed beyond 300 mm. Therefore,
the average depth of grass roots was considered as 200 mm. The root depth function
was taken from Rajeev et al. (2012) and modified to represent the roots up to 0.2 m
depth, as shown in Figure 6-8.
Figure 6-8: Root depth function for Braybrook site
6.7 DEVELOPMENT OF ONE DIMENSIONAL SOIL COLUMN
The vertical moisture movement in the Braybrook site was modelled in Vadose/w
software as a one dimensional (1D) soil column. The climate condition occurring on the
ground surface of an open area was applied to the surface layer. The soil properties
obtained from Braybrook at different depths were allocated to different layers of the soil
column. The variation of moisture content was given as the output of the model.
6.7.1 Selection of soil layers
The top layer of the soil column has to be modelled using the surface layer option in
Vadose/w software. The surface layer allows the application of a climate boundary. The
soil layers were defined as full thermal material where both thermal and hydraulic
property functions need to be specified.
0 50 100 150 200 250 300 350 400
-0.20
-0.15
-0.10
-0.05
0.00
Roo
t dep
th (m
)
Days in a year
Root depth (m)
186
The soil properties obtained for different depths were used in separate layers to
represent the soil profile. The sub layers of the soil column were modelled as separate
regions. In reality, the soil properties gradually vary with the depth and therefore the
changing layers can be barely identified. However, this is difficult to include in a model.
The soil samples were collected at different depths and their results represent the
corresponding depth of the sample. Therefore, the effects of discrete variation of soil
properties have to be expected from the model predictions.
Figure 6-9 shows the selection of layers and the properties used in Vadose/w model.
Since in Braybrook site bed-rock was not found up to 5 m, the depth of the one
dimensional soil model was considered more than 5 m. The hydraulic property
functions were developed only up to 2 m depth. Therefore, following appropriate
assumptions were made for SWCC and hydraulic conductivity functions for the bottom
layers. Figure 4-30 shows that Braybrook soils have similar SWCCs below surface layer
hence, the measured SWCC at 2.0 m is also used for the depths below 2 m. The bottom
layer, from 5 to 6 m, was considered as bed-rock. Hydraulic conductivity of the bottom
layer must be very low to prevent the moisture movement through bedrock (Rajeev et
al., 2012). Compacted clay with very low permeability can have saturated hydraulic
conductivity values in the range of 10-11 to 10-12 m/s (Benson and Trast, 1995).
Therefore, 1x10-12 m/s was used as saturated hydraulic conductivity of the bed-rock
layer. Hydraulic properties of soil gradually vary with the bulk density (Fu et al., 2011).
The basic soil properties and SWCCs are consistent in Braybrook site, as described in
Chapter 4. However, bulk density depends on the compaction of soil, which in this case
is governed by the surcharge. Therefore, a gradual variation of saturated hydraulic
conductivities of the soil between 2 and 5 m were considered to develop hydraulic
conductivity functions using the Fredlund et al. (1994) method. No-flow boundary
condition is specified at the bottom to represent the impermeable rock.
The moisture flow in soil can be adversely affected by the cracking behaviour of the
clay soils during the dry period. The cracking of soils occurs in different ways at
different locations of a site, and it is highly dependent on local effects. The crack depth
measurements in Braybrook site (Table 5-2) showed that the depth could vary even
within a small area. Therefore, it is difficult to model the cracks and their consequences.
187
Subsequently, the cracking of soils was not considered in Vadose/w model developed in
this study.
Figure 6-9: Summary of one-dimensional Vadose/w model
6.8 CALIBRATION OF 1D SOIL MODEL AGAINST MEASURED DATA
The one dimensional soil model was analysed for the period of regular monitoring in
Braybrook, from 10th April 2013 to 25th March 2015. Essendon airport is the nearest
weather station, which is 8 km away from the Braybrook, and it records all the required
daily climate data. Therefore, climate data collected from Essendon airport was used for
the calibration period. The initial moisture contents have been specified, as shown in
Figure 6-10(a). These data were collected from the neutron probe measurements on 10th
April 2013. The moisture measurements were collected only up to 3 m depth and, since
there is constant moisture content at the bottom layers, the same value was used up to 6
m depth. Figure 6-10(b) shows corresponding matric suction values obtained using
SWCCs at different depths given in Figure 4-30.
Distance - m-0.5 0.0 0.5 1.0 1.5
Ele
vatio
n - m
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Sub layer 3 (300-800 mm) 0.3 – 0.8 m 0.5 – 1.0 m
Sub layer 4 (800-1300 mm) 0.8 – 1.3 m 1.0 – 1.4 m
Sub layer 5 (1300-1800 mm) 1.3-1.8 m 1.5 – 1.8 m
Sub layer 6 (1800-2500 mm) 1.8 – 2.5 m
Sub layer 7 (2500-3500 mm)
Sub layer 8 (3500-5000 mm)
Sub layer 9 (5000-6000 mm)
Sub layer 1 (0-200 mm) 0 – 0.4 m
Hydraulic conductivity functionSub layers SWCC
No flow Boundary
Climate Boundary
0 – 0.3 mSub layer 2 (200-300 mm) 0 – 0.3 m 0 – 0.4 m
188
Figure 6-10: Initial moisture content measured at various depths; (b) corresponding suction at various depths
The analysis was performed using a laptop computer. The parallel direct equation solver
option available in Vadose/w was preferred over the direct equation solver option,
which makes the analysis faster (Vadose, 2013). Time steps were considered in days, a
main requirement in Vadose/w analysis. However, adaptive time steeping was used to
minimize the higher nodal head changes applied due to daily climate inputs during a
time step. The 1D model typically takes about 4 hours to analyse the model for a 100
year period.
The volumetric moisture contents obtained from the model were compared with the
measured values. There were errors in moisture contents recorded at TN6 as described
in section 5.4.1. Therefore, TN6 location was neglected in model validation. Figures 6-
11 to 6-14 show the comparison of model predictions and neutron probe measurements
at CN1 and CN2. Figure 6-11 shows the model predictions and measured volumetric
moisture contents at 0.35 m depth. It demonstrates that the model has reliably picked
the moisture changes in both wet and dry periods. However, certain offsets between
measurements and predictions can be observed at some dates. The least accuracy is due
to proximity to the surface where neutron moisture measurements could result in greater
0.30 0.32 0.34 0.36 0.38 0.40 0.42 0.44
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0100 1000 10000
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
b)
Average of CE1 and CE2
Volumetric moisture content
Dep
th (m
)
a)
Matric suction (kPa)
Dep
th (m
)
189
errors, cracking of top soils and variability of soil properties due to the presence of
organic matter. The surface moisture contents are largely affected by various local
influences such as slope differences, potholes, cracks and vegetation layer differences.
Apart from these influences, the ground surface directly interferes with the climate
conditions. Therefore, the surface moisture varies more frequently and the surface
moistures measured at different locations in the same site can have dissimilar values.
This phenomenon can be clearly observed in Figures 5-9 to 5-11, which show the same
day measurements of the CN1, CN2 and TN6 locations. Even though the CN1 and CN2
locations are within 10 m distance, in some days, different moisture contents at the
surface layers have been recorded. Therefore, the model results are difficult to compare
with the measurements close to surface.
Occasionally, these local influences can affect the moistures of the bottom layers. When
there are cracks on the surface, the rainfall and the runoff water can infiltrate easily
through them and increase the moisture contents of the bottom layers. This phenomenon
was observed in measurements made straight after rainy days during the summer. The
stagnated water on potholes can also infiltrate the bottom layers and can show high
moisture contents than other locations.
The surface layer moistures are largely affected by the rainfall, which is one of the main
components of climate boundary. Therefore, the moisture measurements followed the
pattern of daily rainfall variation shown in Figure 6-11. Figures 6-12 to 6-14 show that
the model can precisely predict the moisture changes at the bottom layers. The rainfall
influences the moisture contents at 0.6 m and 0.85 m whereas no moisture change was
recorded at 1.6 m during this calibration period.
190
Figure 6-11: Measured soil moisture contents at 0.35 m and model predictions with rainfall variation
Figure 6-12: Measured soil moisture contents at 0.60 m and model predictions with rainfall variation
10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140
5
10
15
20
25
30
35
40 Daily Rainfall (mm) CN1 - Neutron Probe Measurements at 0.35 m CN2 - Neutron Probe Measurements at 0.35 m Model Predictions at 0.35 m
Date
Dai
ly R
ainf
all (
mm
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric m
oist
ure
cont
ent
10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140
5
10
15
20
25
30
35
40 Daily Rainfall (mm) CN1 - Neutron Probe Measurements at 0.60 m CN2 - Neutron Probe Measurements at 0.60 m Model Predictions at 0.60 m
Date
Dai
ly R
ainf
all (
mm
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric m
oist
ure
cont
ent
191
Figure 6-13: Measured soil moisture contents at 0.85 m and model predictions with rainfall variation
Figure 6-14: Measured soil moisture contents at 1.60 m and model predictions with rainfall variation
Since CN1 and CN2 are close to each other, the average moisture contents at CN1 and
CN2 locations were considered as shown in Figures 6-15 to 6-18 which indicates that
model predictions are more consistent with the averaged measurements.
10/04/2013 10/08/2013 10/12/2013 10/04/2014 10/08/2014 10/12/20140
5
10
15
20
25
30
35
40 Daily Rainfall (mm) CN1 - Neutron Probe Measurements at 0.85 m CN2 - Neutron Probe Measurements at 0.85 m Model Predictions at 0.85 m
Date
Dai
ly R
ainf
all (
mm
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric m
oist
ure
cont
ent
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40 Daily Rainfall (mm) CN1 - Neutron Probe Measurements at 1.60 m CN2 - Neutron Probe Measurements at 1.60 m Model Predictions at 1.60 m
Date
Dai
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all (
mm
)
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0.1
0.2
0.3
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0.6
Vol
umet
ric m
oist
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Figure 6-15: Measured average soil moisture contents at 0.35 m and model predictions with rainfall variation
Figure 6-16: Measured average soil moisture contents at 0.60 m and model predictions with rainfall variation
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40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model Predictions at 0.35 m
Date
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)
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40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.60 m Model Predictions at 0.60 m
Date
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)
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0.1
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0.6
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193
Figure 6-17: Measured average soil moisture contents at 0.85 m and model predictions with rainfall variation
Figure 6-18: Measured average soil moisture contents at 1.60 m and model predictions with rainfall variation
Figure 6-19 shows moisture content profiles at two dates with extreme moisture
contents recorded at 0.35 m. This figure confirms that the model can reliably capture the
changes of moisture profiles. The other profiles for all the measurement dates are shown
in Appendix-E.
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5
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40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.85 m Model Predictions at 0.85 m
Date
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)
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40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 1.60 m Model Predictions at 1.60 m
Date
Dai
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mm
)
0.0
0.1
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0.6
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Figure 6-19: Actual measurements and model predictions for two extreme measurement dates; a) recorded wettest, b) recorded driest
Figure 6-20: Model predictions against neutron probe measured data
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 29/01/2014 CN1 - 29/01/2014 CN2 - 29/01/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 21/10/2013 CN1 - 21/10/2013 CN2 - 21/10/2013
a) b)
0.0 0.1 0.2 0.3 0.4 0.50.0
0.1
0.2
0.3
0.4
0.5
0.35 m 0.60 m 0.85 m 1.10 m 1.35 m 1.60 m 1.85 m 2.10 m 2.35 m 2.60 m 2.85 m
Mod
el p
redi
ctio
ns
Neutron probe measurements
Model predictions and Averages of CE1 & CE2 Neutron probe measurements
195
Overall, the 1D model results are within the limits of measured values and hence the
predictions against measured values, plotted in Figure 6-20, show a good correlation.
Therefore, this model can be considered as a validated model. However, it should be
noted that during the monitoring period of this study, extreme dry or wet climate events
were not recorded. Further, greater moisture changes occur in the surface soils, and the
neutron probe technique is less effective in capturing them. Hence, the impacts of an
extreme climate conditions could not be considered in the validation process.
This model has been used to observe the soil moisture changes due to different climate
conditions, which is described in the next chapter. Furthermore, this model has been
extended to a two dimensional model to observe the lateral moisture movements.
6.9 DEVELOPMENT OF TWO DIMENSIONAL SOIL MODEL
Since the 1D model predicts moisture changes of an open ground, it is interesting to
observe the climate induced moisture changes under a cover which simulates the effect
of a slab. A two dimensional (2D) model with a flexible cover slab and open area was
developed to observe the edge moisture variation which is also an important parameter
in footing design on expansive soils. In this model, the slab cover had no stiffness and
applied no load to the soil.
6.9.1 Selection of model parameters
The 2D model is an extension of the 1D model and, as such, most of the soil properties
are similar to the 1D model. Soils in the 2D model have same layered arrangement as
1D model and hence, they have same properties.
The only additional material property that must be considered for the 2D model is the
hydraulic conductivity in “x” direction, which governs the moisture flow in lateral
direction.
The moisture flow directions of soil depend on the anisotropic arrangement of soil
pores. Apart from the cracks, the soil grains govern the anisotropic arrangement. If the
grains have spherical shapes, then there will be an isotropic moisture flow. But most of
the clay soils have plate type grains and they tend to arrange in a layered pattern with
plat sides deposited on each other. Hence, the lateral moisture flow is usually higher in
layered soils than that of non-layered soils (Zaslavsky and Rogowski, 1969, Todd,
196
1980). In Braybrook, it was difficult to observe differences between soil layer patterns
or cracks in both vertical and lateral directions. Figure 6-21 shows a large piece of soil
taken from Braybrook, which shows the homogeneity of the soil in every direction.
Therefore, the vertical and lateral hydraulic conductivity were assumed to be the same
in Braybrook soils. However, this assumption is based on the visual inspection of the
soil. The elevation head was the only influence between vertical and lateral moisture
movement and was considered in the partial differential equation shown in Equation
6-7.
In addition to the soil and climate parameters specified in 1D model, there are additional
considerations incorporated in the 2D model and they are described in the next section.
Figure 6-21: A large soil chunk from Braybrook
6.9.1.1 Effect of flexible cover on soil moisture
The main purpose of the 2D model is to investigate the effect of climate on soil beneath
a covered area. The condition of cover was introduced by applying a “No flow”
boundary condition on a portion of surface layer. The rest of the surface layer is
considered as an open ground and hence the climate boundary was applied. A very low
hydraulic conductivity was specified for the 0.3 m thick layer below the “No flow”
197
boundary on surface. This prevents the moisture changes of that section of the model,
which represent the ideal condition of a 0.3 m deep slab.
The depth of edge beams of waffle/ stiffened raft slabs designed for H to E class site is
about 385 to 460 mm. When these slabs are placed the top soil is removed to level the
site. In addition, to avoid the side of the edge beams to be exposed, further excavation
may be done to bury the slab further below the natural ground surface. Hence, it is taken
the base of the edge beams on average to be about 300 mm from the natural ground
surface. The model represents a typical cover and therefore, a 300 mm deep uniform
layer was selected to avoid the complexity of slab-beam arrangement.
6.9.1.2 Selection of side boundary conditions
The 2D model represents the conditions of a house footing and the adjacent open area.
Therefore, the climate condition needs to be applied from both sides of the slab, which
represent the garden around the house. Only one side of the area was modelled to reduce
the analysis time. The no flow boundary was applied on the inner side of the slab to
represent the axis of symmetry.
The other end of the model contains variable moisture contents depending on the
climate condition and therefore a specific hydraulic boundary (head or flow) cannot be
specified. As a result, that side is selected to be far enough from the zone of interst such
that the effects of that boundary are minimal. This condition is defined as a far field
boundary condition in Vadose/w modelling (Vadose, 2013), and hence this boundary
can be ignored without specifying any condition. The length of the open area is selected,
such that the moisture changes at the margin of the open area are exactly the same as the
1D model results for the same analysis period. The size selection of the 2D model is
described in the next section.
The top surface outside the cover slab is provided with climate boundary similar to the
1D model. Similarly, the bottom surface is specified as No-flow boundary to represent
an impermeable rock.
6.9.1.3 Selection of model size
The depth of the 2D soil model was 6 m, similar to 1D soil column. The lengths of the
covered and open ground segments were selected based on a sensitivity analysis.
198
Different slab widths and open area widths were considered and the moisture changes at
various locations were observed. The following different model sizes were considered:
Model 1: Cover slab length 6 m and open area length 5 m
Model 2: Cover slab length 8 m and open area length 5 m
Model 3: Cover slab length 10 m and open area length 3 m
Model 4: Cover slab length 10 m and open area length 5 m
Figure 6-22 shows Model 1, which has a 6 m deep and 11 m long soil model with a 6 m
long cover slab. Since the 1D model suggested that most of the moisture changes occur
in soils above 4 m, a finer mesh has been used in the top 4 m of the model. More details
on mesh size selection are given in the next section. Boundary conditions were applied
as explained in section 6.9.1.2. Model 2 to Model 4 have the similar conditions as
Model 1 with changes only in slab length and the total model length. These models
were analysed for a 2 year period same as the 1D model calibration starting from 10th
April 2013 to 25th March 2015 using the climate data collected from Essendon airport
weather station.
The suction changes at 300 mm depth were examined in four different models. The
characteristic maximum and minimum values at that depth at different dates were
considered here, to be able to compare the results of four models. Figure 6-23 shows the
results of the characteristic highest and lowest suctions obtained for the two year period.
This figure also shows a sketch of the arrangement of model sizes based on “x” distance
which facilitates the interpretation of the results. The length of the models was
considered starting from the outside edge of the slab to be able to clearly express the
different model sizes. Figure 6-23 shows that all the models predicted similar results
and the results coincide with each other.
Model 1 and Model 4 were further checked for an analysis period of 100 years. The
climate data from Essendon airport weather station for the period of 1915 to 2014 were
used in this analysis. The analysis time taken for the model 1 was about 5 days. There
was a constant difference between driest and wettest moisture contents starting from
about -3m through -10m (symmetric axis) under the slab. The difference was about 1%
and it is due to the continuous lateral moisture flow along layer interface of the soil
model as the soil below 0.3 m has lower hydraulic conductivity compared to the top
199
soil. However, both models produced similar suction and moisture variations and
resulted higher moisture movement towards the inside of the slab. The smaller models
require less time for the analysis hence, Model 1, which has 6 m long cover slab and 5
m long open area, was selected to continue the 2D model analysis.
Figure 6-22: Two-dimensional Vadose/w model
Figure 6-23: Characteristic wettest and driest suctions at 300 mm depth taken from the 2D model with different sizes
Distance - m-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0
Elev
atio
n - m
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Climate BoundaryNo flow Boundary on cover slabAxis of symmetry
-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 52.00
2.25
2.50
2.75
3.00
3.25
3.50
3.75
4.00
Log
[Mat
ric S
uctio
n (k
Pa)]
Distance (m)
Model 1 (wettest) Model 1 (driest) Model 2 (wettest) Model 2 (driest) Model 3 (wettest) Model 3 (driest) Model 4 (wettest) Model 4 (driest)
Suction variation at 0.3 m soil layer
Cover slab Open area exposed to climate effects
300 mm
Soil
Model 1Model 2Model 3
Model 4
200
6.9.1.4 Effect of mesh size
The size of the mesh has an influence on modelling in terms of accuracy, convergence
of iterations and the analysis time (Vadose, 2013). Therefore, it is important to select
the optimum size of the mesh to develop a reliable and time effective model. The
Vadose/w model results are used in a separate model (developed using FLAC 3D
software) to analyse the changes on soil volume. According to the requirements of that
software, the same square mesh is preferred over the zone of interest of the Vadose/w
model.
The Vadose/w model response to mesh size was investigated by using different square
mesh sizes from 10 mm to 200 mm. The volumetric moisture contents at different
depths in a 30-day period were observed, as shown in Figure 6-24. This figure
illustrates that the 10 mm mesh has caused different results compared to the other
models. This could be due to poor convergence in finer mesh near the climate boundary
and the layer interfaces. Moreover, it takes more time to run the model. Mesh size 200
seems to be too large to develop a moisture profile to compare with field data. Apart
from the 10 mm and 200 mm mesh sizes the other models produced same results. Hence
by considering the efficient run time of the analysis, 100 mm mesh size was selected for
top soil layers. However, a coarser mesh was used for the soil below 4 m as shown in
Figure 6-22.
Figure 6-24: Soil moisture profiles obtained from models with different mesh sizes
0.15 0.20 0.25 0.30 0.35 0.40
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Volumetric moisture content
Dep
th (m
m)
Mesh size 10 mm Mesh size 25 mm Mesh size 50 mm Mesh size 100 mm Mesh size 200 mm
201
6.9.2 2D model predictions
The 2D model was analysed for the calibration period to compare the moisture contents
at the open area with the 1D model results. The moisture contents profiles at 4 m from
the slab edge (at distance 10 m, as shown in Figure 6-22) produced the same results as
the 1D model shown in Figures 6-11 to 6-14. The 2D model was used to obtain soil
moisture variations underneath cover slabs due to different climate conditions and the
results are presented in the next chapter.
6.10 MODEL GENERALIZATION
Predictions of the Vadose/w model depend on both material properties and input
parameters. The accuracy of the material model governs the moisture content and the
flow rate at different depth of the model. In actual conditions, the material properties
gradually vary along the depth of the soil. Soil layer separation cannot be clearly
identified and, therefore, field moisture profiles tend to be smooth. This condition
cannot be easily modelled because the material properties obtained from soils at
different depths must be specified for different layers. Since there is a difference in
properties between layers, it results in abrupt changes of moisture content at the
interface of the soil layers as evidenced in Figure 6-24. However, the effect of material
properties on soil moisture can be studied through a sensitivity analysis and then the
most sensitive parameters can be precisely defined.
In addition to the material properties, the input parameters can alter the model results
from actual measurements. Vadose/w model contains components of climate boundary
as input parameters. In this study, climate data obtained from a weather station 8 km
from the site and hence they may not represent the exact climate condition at Braybrook
site. Therefore, some sensitivity analysis for the climate data was also considered.
6.10.1 Sensitivity of the material model
There are four soil parameters specified in material model developed in Vadose/w
software. SWCC and hydraulic conductivity can be categorized as hydraulic properties
while thermal conductivity and specific heat capacity can be categorized as thermal
properties. The hydraulic properties are defined with respect to matric suction and the
thermal properties are defined against volumetric moisture content.
202
In this sensitivity analysis, the model with real soil property functions from measured
soil results was considered as the “control” model. Each of the material properties was
modified by ±20% and used separately. There were 8 modified parameter models
considered as follows:
20% increment and decrements of volumetric moisture contents corresponding
to suction values in all the SWCCs used in control model (Figure 6-25)
20% increment and decrements of hydraulic conductivities corresponding to
suction values in all the hydraulic conductivity functions used in control model
(Figure 6-26)
20% increment and decrements of thermal conductivities corresponding to
volumetric moisture contents in all the thermal conductivity functions used in
control model (Figure 6-27)
20% increment and decrements of specific heat capacities corresponding to
volumetric moisture contents in all the specific heat capacity functions used in
control model (Figure 6-28)
These changes applied to the soil parameters at the surface layer are shown in Figure
6-25 to 6-28. Similar changes were applied to the parameters of the other layers.
Figure 6-25: 20% changes applied to SWCC of surface layer in sensitivity analysis
0.01 0.1 1 10 100 1000 10000 1000000.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric W
ater
Con
tent
(m³/m
³)
Matric Suction (kPa)
Control input 20% Increment 20% Decrement
203
Figure 6-26: 20% changes applied to hydraulic conductivity of surface layer in sensitivity analysis
Figure 6-27: 20% changes applied to thermal conductivity of surface layer in sensitivity analysis
0.1 1 10 100 1000 10000
1E-12
1E-11
1E-10
1E-9
1E-8
1E-7
1E-6
Hyd
raul
ic c
ondu
ctiv
ity (m
/s)
Matric Suction (kPa)
Control input 20% Increment 20% Decrement
0.0 0.1 0.2 0.3 0.4 0.5 0.60
25
50
75
100
125
150
175
200
Ther
mal
Con
duct
ivity
(kJ/
days
/m/°
C)
Volumetric Water Content (m³/m³)
Control input 20% Increment 20% Decrement
204
Figure 6-28: 20% changes applied to specific heat capacity of surface layer in sensitivity analysis
6.10.1.1 Sensitivity analysis results
SWCC is the governing parameter of moisture changes of expansive soil (Fredlund and
Rahardjo, 1993) and this was reflected in the sensitivity results. Figure 6-29 illustrates
the percentage changes of moisture content at 0.3 m depth due to modifications of the
soil parameters. This figure shows the variation of results from 8 modified models
(given in the previous section) compared to the control model.
Figure 6-29: Sensitivity of soil parameters
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.70
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Vol
umet
ric S
peci
fic H
eat C
apac
ity (k
J/m
³/°C
)
Volumetric Water Content (m³/m³)
Control input 20% Increment 20% Decrement
-24 -20 -16 -12 -8 -4 0 4 8 12 16 20 24
Hydraulic conductivity
SWCC
Thermal conductivity
Specific Heat Capacity
Percentage change of moisture content
climate parameters at 0.3 m depth - 21/10/2013
Due to 20% Increment Due to 20% Decrement
205
Following conclusions were made from the results shown in Figure 6-29.
SWCC has been the most influential soil parameter of the material model.
Increments of the SWCC caused increments in soil moisture at 0.3m depth. 20%
change of the SWCCs resulted in about 22% change in soil moistures.
The hydraulic conductivity is the next important soil parameter. Since hydraulic
conductivity governs the moisture flow rate, the higher the hydraulic
conductivity at a node, the higher the capability of allowing moisture to flow
away. Therefore, changes of hydraulic conductivities are inversely proportional
to the soil moisture changes. 20% change in hydraulic conductivities resulted
in about 2% soil moisture change.
Thermal conductivity and specific heat capacity caused less than 1% changes in
soil moisture. Hence, soil moisture changes are less sensitive to the thermal
properties.
6.10.2 Sensitivity of climate parameters
The Vadose/w model associates five climate components as input parameters; rainfall,
evaporation, relative humidity, wind speed and temperature. The influence of each
component is different. Therefore, the model prediction should be considered with the
sensitivity of those parameters.
6.10.2.1 Rainfall
In this sensitivity analysis, three nearby weather stations were used where daily rainfall
data is available for the analysis period. These stations are located at different distances,
as given below.
Flemington racecourse: 4.1 km away from Braybrook
Essendon airport: 8.0 km away from Braybrook
Burnside: 10.2 km away from Braybrook
Figure 6-30 shows daily rainfall variation for a typical month. It is observed that all of
them have similar rainfall variation with a maximum daily rainfall difference of about 5
mm.
206
Figure 6-30: Daily rainfall variation of 3 locations around Braybrook (April 2013)
Some weather stations have only a certain type of weather data while others have all the
required data types. Since weather data types are dependent on each other, all the
required data collected from one weather station should provide better model
predictions. Essendon airport provides all the data for the Vadose/w model and hence
that weather station was considered in this study. These data was modified by 20% and
used in the model to observe the sensitivity of the rainfall on soil moisture.
6.10.2.2 Evaporation
Soils lose moisture due to evaporation process at the surface. Therefore, it is an
important parameter in climate boundary. In the Vadose/w model, potential evaporation
should be specified to calculate the moisture flow (Equation 6-2). Potential evaporation
can be calculated from Penman method (Penman, 1948) using specifically measured
weather data. Since the potential evaporation depends on other climate components (for
example, temperature, rainfall and solar radiation) it is not a readily available in typical
weather stations. However, pan evaporation data can be directly collected from the
Bureau of Meteorology.
The difference of two evaporation types was investigated using measured weather data
in Fawkner. These data was provided by Dr. Pathmanathan Rajeev, which were
collected for research published elsewhere (Chan et al., 2010, Rajeev et al., 2012,
Rajeev and Kodikara, 2011). Penman potential evaporations were calculated from those
data for a two-year period. Pan evaporations were obtained for the same period from a
weather station, which is 6 km far from Fawkner. Figure 6-31 shows daily variation of
1/04/2013 8/04/2013 15/04/2013 22/04/2013 29/04/20130
1
2
3
4
5
6
7
Dai
ly ra
infa
ll (m
m)
Date
Flemington Racecourse Essendon airport Burnside
Total rainfallFlemington Racecource: 23.1 mm Essendon airport: 17.6 mmBurnside: 10.2 mm
207
pan evaporation and Penman potential evaporation for a two-year period. It shows that
both evaporations have similar values.
Figure 6-31: Variation of evaporation in Fawkner
Figure 6-32 suggests that pan evaporation data from 6 km away from the location can
reliably represent the calculated values. Therefore, in this study pan evaporation data
collected from Essendon airport weather station was used in the climate boundary.
Figure 6-32: Comparison of pan evaporation and Penman potential evaporation in Fawkner
1/06/2009 1/09/2009 1/12/2009 1/03/2010 1/06/2010 1/09/2010 1/12/2010 1/03/2011 1/06/20110
3
6
9
12
15 Pan Evaporation Penman Potential Evaporation
Evap
orat
ion
(mm
)
Date
Fawkner
0 5 10 150
5
10
15
Pen
man
Pot
entia
l Eva
pora
tion
Pan Evaporation
Fawkner
208
The pan evaporation data collected from Essendon airport weather station were
modified by 20% and used separately in sensitivity analysis models to observe the effect
of evaporation on soil moisture.
6.10.2.3 Relative humidity, temperature and wind
Maximum and minimum relative humidity values were collected from Essendon airport
weather station. They were also modified by 20% in the sensitivity analysis. However,
the minimum and maximum values were kept between 0 and 100. Temperature and
wind data were also collected from the same weather station and, again, 20%
modifications were made for the sensitivity analysis. However, minimum values were
kept to zero. These modified parameters were applied one at a time into the control
model and the resulted soil moisture predictions were observed.
6.10.2.4 Sensitivity analysis results
Figure 6-33 shows the moisture contents at 0.3 m depth due to 20% changes in each
climate parameters. Following conclusions were made regarding the sensitivity of
climate parameters using the results shown in Figure 6-33.
Rainfall is the main influence of soil moisture changes followed by evaporation
and relative humidity.
The higher the rainfall the greater the amount of water available for infiltration.
High relative humidity creates less evaporation and hence increase the soil
moistures at top layers. Therefore, rainfall and relative humidity are positively
correlated to the soil moisture change, whereas evaporation is negatively
correlated.
20% change in rainfall creates about 5% change in soil moisture at 0.3m depth.
20% change in evaporation crate about 3-4% change in soil moisture at 0.3m
depth
20% change in relative humiditys crates about 1.5-2.5% change in soil moisture
at 0.3m depth
Soil moistures are less sensitive to both temperature and wind
209
Figure 6-33: Sensitivity of climate parameters
6.10.2.5 Model response to vegetation effect
The vegetation layer affects the evaporation from soil surface by reducing the soil’s
exposure to the solar radiation. Therefore, soil moisture can be higher in a grass land
than in bare land. On the other hand, vegetation reduces the soil moisture due to
transpiration process. This depends on the depth of the root zone and the plant moisture
limiting function (Vadose, 2013). Soil moisture condition is a result of balance between
these two scenarios due to vegetation.
Vadose/w has an option to analyse the models including and excluding the vegetation
effect. Figure 6-34 shows the model predictions at 0.35 m with and without the
vegetation effect. Inclusion of vegetation has resulted in a high moisture condition at
surface layer. This is due to the prevention of evaporation as a result of grass cover.
Since the Braybrook site had a relatively shallow root zone, the transpiration process
has a small influence.
In the Vadose/w model, the influence of vegetation can be controlled using the root
depth function, leaf area index and plant moisture limiting factor described in section
6.6. In the Braybrook site, the grass cover was identified as LAE of 1 which is a poor
cover. However, if the grass cover is thicker and remains throughout the year, it can
significantly reduce the evaporation from the surface, which leaves more water to
-6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6
Rainfall
Evaporation
Relative Humidity
Temperature
Wind
Percentage change of moisture content
Sensitiviy of climate parameters at 0.5 m depth - 21/10/2013Due to 20% Increment Due to 20% Decrement
210
infiltrate. Hence a significant increase in soil moisture can be observed. However, if the
roots grow further down and are denser, they increase the water removal from the soil.
Therefore, selecting appropriate vegetation functions in Vadose/w analysis is important.
Inclusion and exclusion of vegetation effect can be considered in long term analysis
models to observe the soil moistures for different land conditions.
Figure 6-34: Effect of vegetation layer on soil moisture at Braybrook site
6.10.2.6 Model response to ponding effect
Rainwater can collect on ground surface because of varying local effects at different
places of the site. Cracks and potholes can hold water for some time and therefore
infiltration at those locations can become higher than other places. This effect can be
included in Vadose/w model by allowing ponding on the surface. If the ponding is
allowed in the analysis, the model does not consider runoff and keeps the excessive
precipitation at a time step for the subsequent evaporation or infiltration at later time
steps. Figure 6-35 shows the effect of the ponding allowed and ignored conditions on
soil moisture at 0.35 m. The ponding allowed condition resulted in higher moisture
contents at surface layer. The ponding effect has great influence on soil moisture after
heavy rain days.
Even though Braybrook generally has a flat ground surface, surface is uneven at some
places. Furthermore, cracks were observed during the summer. However, in general, the
pooling of water during wet periods was not observed. Therefore, ponding was not
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5
10
15
20
25
30
35
40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model prediction with Vegitation included Model prediction with Vegitation excluded
Date
Dai
ly R
ainf
all (
mm
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric m
oist
ure
cont
ent
211
allowed in the validated model. But these two scenarios can be considered in model
applications to observe the effect of local conditions.
Figure 6-35: Effect of ponding condition on soil moisture at Braybrook site
6.11 SUMMARY
This chapter describes the development of a finite element model to predict soil
moisture changes in response to climate conditions. Vadose/w package, available in
GeoSlope software, was used to develop the finite element model. A 1D soil column
was modelled using the material properties of Braybrook soils described in Chapter 4.
The model requires specifying SWCC, hydraulic conductivity, thermal conductivity and
the specific heat capacity of the soil. A sensitivity analysis suggested that the thermal
properties had a minimal impact on soil moisture changes. Therefore, thermal
conductivity and specific heat capacity obtained from literature related to a site close to
Braybrook were deemed appropriate for this research. The soil properties were defined
at different depths of the soil column to represent actual soil profile. The depth of the
soil column is governed by the location of bedrock. In Braybrook site, bedrock was not
hit at 4.5 m, therefore a 6 m deep soil column with bottommost meter (5m to 6m) of
bedrock was modelled. Soil properties of Braybrook soils were measured up to 2.5 m
depth. Braybrook soils have similar SWCCs below surface layer and therefore, the
measured SWCC at 2.0 m is also used for the depths below 2 m.. Since hydraulic
properties of soil gradually vary with the bulk density and the soil properties and are
consistent in Braybrook site, a gradual variation of saturated hydraulic conductivities of
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20
25
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40 Daily Rainfall (mm) Average Neutron Probe Measurements (CN1 and CN2) at 0.35 m Model prediction with Ponding not allowed Model prediction with Ponding allowed
Date
Dai
ly R
ainf
all (
mm
)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Vol
umet
ric m
oist
ure
cont
ent
212
the soil between 2 and 5 m were considered where bulk density is governed by the
surcharge. These saturated hydraulic conductivities were used to develop hydraulic
conductivity functions using the Fredlund et al. (1994) method.
The model requires specifying boundary conditions to represent the moisture flow
conditions. The climate boundary was specified at the top surface. Vadose/w software
uses daily inputs of rainfall, evaporation, relative humidity, wind and temperature to
define the climate boundary. These climate components were collected from a weather
station close to the Braybrook site. The no-flow boundary was defined at the bottom of
bedrock to prevent the moisture flow from bedrock.
This model was analysed for the two year period of field monitoring. The model
predicts soil moisture and suction profiles at different times. These predictions were
compared with the neutron moisture measurements described in Chapter 5. The results
showed a good agreement between soil moisture predictions and monitored data and
hence the model was considered as validated.
Next, the 1D model was extended to a 2D model to determine lateral moisture
movements. The only additional parameter required in the 2D model is hydraulic
conductivity in lateral direction. During the mass excavation in Braybrook site,
homogeneous soil chunks were found where no layer changes could be observed.
Hence, it was assumed the both lateral vertical hydraulic conductivities are the same in
Braybrook soils. The 2D model was developed to incorporate impervious cover in order
to observe the soil moisture beneath cover slabs due to the climate influences on
adjacent open ground.
The sensitivity analysis of the input parameters revealed that soil moisture changes are
mostly affected by SWCC of soils followed by the hydraulic conductivity. Rainfall is
the most sensitive climate component in changing soil moistures. Furthermore,
evaporation and relative humidly have significant impacts on soil moisture contents.
The responses of the models to vegetation effects and ponding conditions were also
considered. Grass covers prevent the evaporation and increase the water available for
the infiltration. Therefore, both grass covers and pooling effects significantly increase
the soil moisture. These sensitive input parameters must be given more attention in
obtaining soil moisture using prediction models. This model was then used to determine
213
the soil moisture changes due to long-term climate conditions, which is described in the
next chapter.
214
7. MODEL APPLICATIONS
7.1 OVERVIEW ON MODEL PREDICTIONS OF SOIL MOISTURES
The validated model described in the previous chapter was used to investigate the soil
moisture changes in response to various long-term climatic conditions. A number of
models were analysed to consider different site conditions and climate scenarios.
Following notations were used in this chapter to denote these different models.
VB1 1D Vadose/w model, Braybrook site, 6 m deep, period 1945-2015
(Section 7.1.1.1)
VB2 1D Vadose/w model, Braybrook site, 3 m deep, period 1945-2015
(Section 7.2.5)
FLAC 1D soil column developed in FLAC-3D software which uses moisture
predictions from Vadose/w models
VB3 1D Vadose/w model, Braybrook site, 6 m deep, short term wet condition,
period 1945-2018 (Section 7.3)
VB4 1D Vadose/w model, Braybrook site, 6 m deep, short term dry condition,
period 1945-2018 (Section 7.3)
VB5_A 1D Vadose/w model, Braybrook site, 6 m deep, typical average climate,
period 50 years (Section 7.4)
VB5_M 1D Vadose/w model, Braybrook site, 6 m deep, modified climate, period
50 years (Section 7.4)
2DVB1 2D Vadose/w model, Braybrook site, 6 m deep, period 1945-2015
(Section 7.5)
2DVB2 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover,
period 1983-1992 (Section 7.6.1)
2DVB_I 2D Vadose/w model, Braybrook site, 6 m deep, without flexible cover,
period 1945-2015 (Section 7.6.1)
215
2DVB3 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover,
period 1992-2010 (Section 7.6.2)
2DVB4_S 2D Vadose/w model, Braybrook site, 6 m deep, with flexible cover, soil
dipping towards slab edge, period 1992-2010 (Section 7.7.1)
VF1 1D Vadose/w model, Fawkner site, 3 m deep, period 1945-2015 (Section
7.1.1.1)
VF2 1D Vadose/w model, Fawkner site, 3 m deep, short term wet condition,
period 1945-2018 (Section 7.3)
VF3 1D Vadose/w model, Fawkner site, 3 m deep, short term dry condition,
period 1945-2018 (Section 7.3)
VF4_A 1D Vadose/w model, Fawkner site, 3 m deep, typical average climate,
period 50 years (Section 7.4)
VF4_M 1D Vadose/w model, Fawkner site, 3 m deep, modified climate, period
50 years (Section 7.4)
7.1.1 Prediction of soil moistures
The models described in this chapter were analysed using climate data collected from
Essendon airport weather station. Figure 7-1 shows the variation of annual rainfall from
Essendon airport weather station from 1945 to 2014. Isolated dry and wet years were
recorded pre-1995; however, overall, the rainfalls prior to 1995 can be considered
average conditions. However, a significant reduction of annual rainfall occurred during
the millennium drought (1996-2009). The drought-breaking rainfalls in 2010 and 2011
are clearly noticeable and created back-to-back extreme events. Since 2012, a gradual
reduction of annual rainfall was observed. Interestingly, 2014 was recorded as the
warmest year for Victoria (BoM, 2015b), which suggests that climate conditions are
heading towards another dry period (Hannam, 2015).
216
Figure 7-1: Annual rainfall recorded in Essendon airport weather station
The Vadose/w model developed in this study was used to investigate the soil moisture
changes due to these different conditions, including different climate predictions.
7.1.1.1 Sites considered in the long term model predictions
Soil moisture changes depend not only on the climatic conditions, but also on the soil
profile. AS2870 defines sites with clay soil deeper than 3 m as deep-seated moisture
sites. Braybrook has a clay soil profile deeper than 4.5 m; hence, it is one of the deep-
seated moisture sites. Therefore, a 6 m deep soil column was considered in Vadose/w
modelling for Braybrook site. The 1D Vadose/w model analysed for Braybrook to
consider the 1945-2015 period is denoted as VB1 hereafter.
The required soil parameters were found in Rajeev et al. (2012) for Fawkner, which is
another expansive soil site in Melbourne. This site is a nature strip located beside a
road, and it was used to investigate the effect of expansive soil on buried gas pipeline.
In contrast to Braybrook, Fawkner has a clay soil profile of up to only 2 m. Table 7-1
shows the details of the Fawkner soil which has a shallow profile. There are MH silts in
the top 300 mm. Brown coloured ashes were observed in the top layers, which appears
the signs of filled material. A high plasticity clay layer continues for only about 1.7 m
below the top layer before meeting the bedrock. Table 7-2 lists the soil properties of the
Fawkner site. Atterberg limits in the Fawkner site are lower than those of Braybrook,
which suggests that Fawkner soils are less reactive than Braybrook soils. This site was
not classified based on AS2870, because the Iss values are not available for Fawkner
soils. However, hydraulic and thermal properties are available in Rajeev et al. (2012)
1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 20150
200
400
600
800
1000
1200
Ann
ual R
ainf
all (
mm
)
1945-1995 1996-2009 2010-2011 2012-2014
217
and therefore another 1D model was analysed using them to observe the predictions in
the 1945-2015 period. This model is denoted as VF1 hereafter.
Table 7-1: Soil profile at Fawkner site (Rajeev et al., 2012)
Depth (m) Soil description
0.0-0.3 MH Silty Clay, brown ashes with root fibres, dry to moist
0.3-2.0 CH inorganic clay with high plasticity, brown ashes, moist, Stiff
Below 2.0 Basalt rock
Table 7-2: Geotechnical properties of Fawkner soil (Rajeev et al., 2012)
Depth (m)
Average dry
density (kN/m3)
Atterberg limits Ksat (m/s)
Liquid limit
Plastic limit
Plasticity index
0-0.25 19 69.1 22.4 46.7 2.25x10-5 0.25-0.75 19 70.4 20.1 50.3 1.97x10-9 0.75-1.0 19.9 60.3 17.5 42.8 2.3x10-10 1.0-1.5 20.5 65.9 20.7 45.2 2.3x10-10 1.5-2.1 20.3 61.5 19.5 42 2.3x10-10
7.1.1.2 Surface runoff considered in the long term model predictions
Models developed in Vadose/w software require climate data as an input parameter. The
software considers the runoff when the rainfall is distributed over 24 hours of the day
provided that the surface layer is saturated. The daily rainfall is considered in Vadose/w
models such that it is sinusoidal distributed throughout 24 hour period as described in
section 6.5 and Figure 6-4. Hence, even if the daily intensity is high, the hourly intensity
can be low, and the model has enough time for the infiltration. Therefore, depending on
the intensity of rainfalls on certain days, there can be sudden extreme changes in soil
moisture content in the model results. This phenomenon is highlighted in periods after
heavy rainfall. However, in most rainy days, rainfall is not distributed throughout but
falls at high intensity during part of the day and most of such rainwater runs off,
allowing only a small amount to infiltrate the soil. Therefore, in such intense rainy days,
a further correction is added to the data before they input to the model.
218
The higher the moisture content of the surface soil, the higher the runoff amount. There
is a well-established rational formula for surface runoff that considers that 50% to 70%
of rainfall can be runoff in suburban residential areas (Corbitt, 1999). Since the results
of this model will be used to design residential structures, a 60% runoff condition was
adopted during heavy rain periods. However, there were some days with extremely high
rainfall. For example, in February 2005, there were two days with more than 130 mm of
daily rainfall, which created flash flood conditions in parts of Melbourne. In modelling,
such high rainfall can make a huge impact on predicted moisture levels in deeper layers.
However, as the surface layer is saturated, the runoff amount will be greater than 60%.
Therefore, such extreme dates were adjusted accordingly in this model analysis. Based
on the observations of the model results, the following adjustments were made for the
long-term climate data sets:
If the summation of daily rainfall for the past 7 days (including the 7th day) is
less than or equal to 15 mm, no corrections were applied to the 7th day rainfall
(ractual)
If the summation of daily rainfall for the past consecutive days (including the 7th
day) is higher than 15 mm, the following corrections were applied to the 7th day
rainfall (ractual). The corrected rainfall (rcorrected) also depends on the amount of
ractual
I. If ractual> 10 mm and 0.4 x ractual≤ 10 mm, then rcorrected = 0.4 x ractual
II. If ractual> 10 mm and 0.4 x ractual> 10 mm, then rcorrected = 10 mm
III. If ractual≤ 10 mm then rcorrected = ractual
The climate data provided daily inputs into the Vadose/w models. However, the model
predictions were only saved for every 30-day interval in this analysis period to optimise
the analysis. The moisture of surface soils fluctuates more frequently because the soil
surface is directly exposed to climate conditions. Hence, 12-month average soil
moisture content levels were considered to observe the patterns of soil moisture
variation with the long-term changes in climate conditions. Moreover, 95th percentile
confident limits were considered to identify the variations in suction profiles in order to
investigate the characteristic changes in ΔU and Hs. The outcome of the models
developed in Vadose/w software was used to study ground movement changes as
describe in the next section.
219
7.1.2 Prediction of ground movement
Ground movement due to long-term climate conditions was calculated using three
different methods.
7.1.2.1 AS2870 method
The flow chart shown in Figure 7-2 was followed to obtain ys using the AS2870
method, which considers TMI of the particular period to obtain Hs. ΔU was considered
to be 1.2 pF as specified in the standard. Iss values of the Braybrook site were obtained
during the laboratory investigation described in Chapter 4 (Table 4-6). Those Iss values
were used for the Braybrook soil profile in the calculations shown in this chapter. Due
to the non-availability of Iss values, the AS2870 method was not used to obtain ys for the
Fawkner site.
Figure 7-2: Flow chart of AS2870 method
7.1.2.2 Vadose + AS2870 method
The next method of estimating ground movement is a combination of the Vadose/w
model predictions and the AS2870 method (flow chart shown in Figure 7-3). The
models developed in Vadose/w software produced soil suction profiles at every 30-day
interval. Characteristic maximum and minimum suctions were obtained from those
results for the different considered periods to determine ΔU and Hs. Then, ys values
were calculated using the AS2879 method. Similarly to the previous method, measured
Iss values were used for Braybrook soils. This method was not used in estimating ys in
Fawkner, because of the non-availability of Iss.
ysAS2870
Method
TMI
Hs
ΔU
Iss
220
Figure 7-3: Flow chart of Vadose/w + AS2870 method
7.1.2.3 Vadose + FLAC method
The third method of ground movement estimation is the use of the Vadose/w model
predictions as inputs in the FLAC model. A one-dimensional soil column was modelled
in FLAC3D software by another researcher as part of this comprehensive research
program.
This model considered the changes in the moisture content of soils and predicted the
corresponding ground movement using a function of soil moisture versus stiffness
(elastic modulus), shown in Figure 7-4. The soil stiffness was obtained at different
moisture contents using oedometer tests and power low method (Lu and Kaya, 2014).
This figure shows that the Braybrook soil has a stiffness of about 250 kPa at field
capacity (~33% of gravimetric moisture content), and it increases to about 1 MPa when
moisture content reduces to about 28%. The soil is modelled using the classical Winkler
springs. Poisson's ratio of the soil was assumed as 0.45. The shear modulus and bulk
modulus were obtained using elastic modulus and Poisson’s ratio. These properties
were obtained for both the Braybrook and Fawkner sites during the study. The soil
moisture predictions, saved at 30-day intervals, were fed into the FLAC model.
The FLAC model is a soil column developed in three-dimensional domain. The height
of the soil column is 5 m and meshed similarly to the 1D Vadose/w model down to the
depth of bedrock. It is fixed at the bottom (at the depth of bedrock) and then the rest of
the soil is allowed only vertical movement. The flow chart in Figure 7-5 shows the
estimation of ground movement using the Vadose/w and FLAC models.
Vadose model
SWCC
Hydraulic conductivity
Climate data
ys
Soil suction
profiles
Hs
ΔU
Characteristic
suction profiles
AS2870 Method
Iss
221
Figure 7-4: Soil stiffness versus moisture content relationship for Braybrook soil
Figure 7-5: Flow chart of Vadose/w + FLAC model
7.2 MODEL PREDICTIONS DUE TO LONG TERM CLIMATE CONDITIONS
The changes of the soil moisture in response to long-term climate conditions were
investigated for the Braybrook and Fawkner sites. The climate conditions from 1900 to
2015 were used in the analysis. Since the initial conditions were not known, the initial
conditions of the validated model were used in this long-term analysis. These initial
conditions were measured up to only about 3.0 m depth and the values of deeper depths
were assumed, as described in Chapter 6. Hence, the first 30 to 40 year predictions were
ignored, considering that the soil moisture requires time to reach an equilibrium state to
avoid the influence from the initial condition. The model results starting from 1945 are
0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24 0.26 0.28 0.300
5000
10000
15000
20000
25000
Soi
l stif
fnes
s (k
Pa)
Gravimetric Moisture Content
PickedY1
y = 563895x2 - 355467x + 56146
Vadose model
SWCC
Hydraulic conductivity
Climate data
Ground
movementFLAC model
Soil moisture vs strain
relationship
Soil moisture
profiles
222
considered in this section. There are three periods considered here, emphasising the
effect of millennium drought as given below.
1. 1945-1995: 50-year period prior to the millennium drought. Short-term severe
weather events occurred during this period. However, taking into account the
overall rainfall variation shown in Figure 7-1, this period can be considered as
showing average conditions in terms of the life span of a structure.
2. 1996-2009: millennium drought period in Victoria.
3. 2010-2011: two years of above average rainfall after the drought.
7.2.1 Variation of suction profiles
Minimum and maximum suction profiles were observed from the 1D model for the
three periods mentioned in the previous section to investigate the changes in ΔU and Hs.
Figure 7-6 shows major influences on characteristic suction profiles in Braybrook and
Fawkner. The minimum and the maximum suction profiles are plotted for the average
climate condition period. Drought conditions affected the dry suction profile while
heavy rainy periods affected the wet suctions. Therefore, Figure 7-6 shows only the
maximum suction for the 1996-2009 period and minimum suction profile for the 2010-
2011 period. Suction profiles have a champagne flute shape as observed in most of the
field investigations. The minimum and the maximum suction profiles in the 1945-1995
period shows that significant suction changes occurred down to about 3.0 m in
Braybrook (VB1 model). The suction profiles predicted by the model have slight
difference even at the bottom of the profile. However, suction changes less than 1% of
the ΔU were neglected. Hence, the depth that suction change reaches 1% of the ΔU was
considered as Hs. In Fawkner (VF1 model), changes were observed down to only about
1.4 m. Even though the climatic condition is similar in both sites, the location of
bedrock and the different clay properties created a significant difference in the depth of
suction change. Since moisture was able to penetrate deeper in the Braybrook site, the
fluctuations at the near surface soils are less than that of Fawkner. In Braybrook, at 0.3
m depth, suction changed by 1.3 pF prior to the drought period, whereas, in Fawkner,
the suction change at that depth was about 1.5 pF.
The maximum suction profile observed during the millennium drought period shifted to
the dry side in both sites. This highlights the effect of prolonged drought on soil
223
moisture levels, which consequently affects ground movement. However, this drying
effect occurred down to only about 1.4 m in Braybrook (where driest suction profile in
1996-2010 cross over the driest suction profile of 1945-1995 period), compared to 0.6
m in Fawkner. There is about 0.2 pF of additional suction change at 0.3 m depth due to
the drought conditions in both sites. The minimum suctions observed in the rainy period
show a shifting of suction profiles towards the wet side. However, these wet profiles did
not overtake the wet suction profile of average conditions during 1945-1995. Therefore,
this figure suggests that both sites have not fully recovered from the moisture deficit
they experienced during the millennium drought. This could be due to the greater deficit
condition in soil at the end of the Millennium drought. Moreover, the 2010-2011 wet
years were not as intense as the other wet years during 1945-1995 period as illustrated
in Figure 7-1.
Overall, these predictions suggest that not only climate conditions, but also soil
properties and site conditions, affect suction profiles. Hence, all of them need to be
considered in obtaining the design parameters, ΔU and Hs. Furthermore, the millennium
drought contributed dramatically to the changes in typical suction profiles.
Figure 7-6: Predicted characteristic suction profiles; a) Braybrook-VB1 model and b) Fawkner-VF1 model
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-2.4
-2.1
-1.8
-1.5
-1.2
-0.9
-0.6
-0.3
0.0
Log (Matric Suction)
Dep
th (m
)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min
50 yrs and extremes
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min
50 yrs and extremes
-0.3
a) b)
224
7.2.2 Variation of soil moisture contents
Figures 7-7 and 7-8 show the variation of volumetric moisture content in the Braybrook
and Fawkner sites respectively. Monthly results indicate more fluctuation near the
surface (at 0.1 m) and hence it is difficult to identify the trend of moisture change.
Therefore, the 12-month moving average moisture variation at 0.1 m is also plotted on
each figure. The 12-month average moisture variation clearly demonstrates the
reduction in soil moisture during the drought period from 1996 to 2009. The surface
moisture increased immediately after the drought-breaking rainfalls in 2010 and 2011,
but has started to reduce since 2012 due to the reduction in rainfalls in 2012 to 2014.
However, the volumetric moisture content at about Hs (3.0 m for Braybrook and 1.5 m
for Fawkner) is constant throughout all the periods in both sites.
Figure 7-7: Variation of volumetric moisture content near surface and at Hs– Braybrook (VB1 model)
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55 at 0.1 m - 12 month average results at 0.1 m - monthly results at 3.0 m - monthly results Daily rainfall (mm)
Date
Vol
umet
ric m
oist
ure
cont
ent
POND_OFF
0
25
50
75
100
125
150
Dai
ly ra
infa
ll (m
m)
225
Figure 7-8: Variation of volumetric moisture content near surface and at Hs – Fawkner (VF1model)
7.2.3 Variation of ground movement
Ground movements subsequent to soil moisture changes were obtained using the
different methods described in section 7.1.2.
Figure 7-9 shows the variation of ground movement obtained using VB1 predictions
and the FLAC model (Vadose + FLAC method described in section 7.1.2.3). The
seasonal fluctuations of ground surface are clearly shown in this figure and the recorded
droughts in Melbourne during the considered period are also evident. Before 1950, the
seasonal ground movement (within a year) was about 25 mm. This period was greatly
affected by the World War II drought, which occurred from 1937 to 1945. The ground
appears to recover from that drought after 1950 and then average conditions can be
observed until the 1990s. The seasonal ground movement is about 40 mm during this
period, despite few droughts experienced in this period, as shown in Figure 7-9. The
ground shows a settling trend during these events. The 12-month moving average
movement clearly illustrates the long-term trends. The millennium drought seems to be
the most severe drought, with seasonal ground movement reduced to about 20 mm
within this period. The effect of an above average rainfall period is also clearly visible
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55 at 0.1 m - 12 month average results at 0.1 m - monthly results at 1.5 m - monthly results Daily rainfall (mm)
Date
Vol
umet
ric m
oist
ure
cont
ent
POND_OFF
0
25
50
75
100
125
150
Dai
ly ra
infa
ll (m
m)
226
after 2010, which indicates a short term ground heaving. However, the ground was not
able to fully recover from the drought and remains in a moisture deficit condition.
Moreover, another dry period was observed from 2012, as shown in annual rainfall
(Figure 7-1); hence, the ground has begun to settle.
After the 1950’s, ground movement was considered to be in average condition. Based
on peak values, Figure 7-9 suggests that there was a total ground movement (peak to
peak) of approximately 80 mm prior to the millennium drought. A trend of ground
settlement started from around 1997 consequent to the dry period. The additional
ground movement that occurred due to the millennium drought is about 15 mm.
Figure 7-9: Braybrook ground movement prediction from VB1 and FLAC model
Figure 7-10 shows the variation of ground movement obtained from the VF1 model and
FLAC model (Vadose + FLAC method described in section 7.1.2.3). Because of the less
reactive and shallower soil profile, ground fluctuations in Fawkner are smaller than
those of Braybrook. Subsequently, the Fawkner site appears to be less sensitive to
extreme climate events. The effect of the World War II drought is also lesser in
Fawkner than in Braybrook. The seasonal ground movement in Fawkner is about 20
mm during 1950 to 1995. This was reduced to about 10 mm within the millennium
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
60
Wo
rd W
ar 2
dro
ug
ht
~193
7-19
45
Rep
ort
ed d
rou
gh
t
~196
5-19
68
Rep
orte
d d
rou
gh
t,
~198
2-19
83A
sh W
edn
esd
ay,
Feb
198
3
Bla
ck S
atu
rday
,
Feb
2009
Mill
enn
ium
d
rou
gh
t,
~199
6-~2
009
Ground movement 12 month average
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
ys = ~ 80 mm
Additional ys = ~ 15 mm
227
drought period. Based on peak values, Figure 7-10 suggests that there was a total
ground movement of 37 mm prior to the millennium drought. An additional 7 mm of
ground movement occurred due to the millennium drought. This increment is 19%
compared to the ground movement in the pre-drought period.
Figure 7-10: Fawkner ground movement prediction from VF1 and FLAC model
7.2.4 Comparison of ground movement estimations
7.2.4.1 Influence of millennium drought of ground movement
In this section, the AS2870 method and the predictions from the VB1 and VF1 models
were used to estimate ground movement using the three methods described in section
7.1.2. The estimations were obtained for two periods (1945-1995 and 1945-2012),
excluding and including the millennium drought.
Firstly, ground movements were calculated using the AS2870 method only (described
in section 7.1.2.1). TMI was calculated using Method 1 (explained in Chapter 3) and it
is -6 for the period from 1945 to 1995. TMI is -9 for the total period including the
millennium drought and wet conditions (1945-2012). According to AS2870 (2011), the
climatic conditions belong to climate class 3 for both periods. Therefore, the proposed
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-35-30-25-20-15-10
-505
10152025303540
Wo
rd W
ar 2
dro
ug
ht
~193
7-19
45
Rep
ort
ed d
rou
gh
t
~196
5-19
68
Rep
orte
d d
rou
gh
t,
~198
2-19
83A
sh W
edn
esd
ay,
Feb
198
3
Bla
ck S
atu
rday
,
Feb
2009
Mill
enn
ium
d
rou
gh
t,
~199
6-~2
009
Ground movement 12 month average
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
ys = ~ 37 mm
Additional ys = ~ 7 mm
228
Hs is 2.3 m for both periods. AS2870 (2011) recommended a ΔU of 1.2 pF irrespective
of the climatic condition. These values and measured Iss values were used to estimate ys
of Braybrook. Iss values for Fawkner are not available and therefore this calculation was
not considered for Fawkner site.
Ground movement in Braybrook was also calculated using the VB1 model results and
the AS2870 method together (method described in section 7.1.2.2). The calculation
given in the AS2870 method considered the area of the minimum and maximum suction
profile by approximating the shape to a triangle. The triangular shape is defined using
ΔU and Hs. Figure 7-11 shows that there is a very high suction change near the ground
surface. Therefore, if ΔU is taken from the surface suction change of model predictions,
it will add a large area, which is outside of the actual champagne flute shape.
Further, during the construction of footings, the topsoil is normally removed. For waffle
slabs, they are placed at this new surface level, whereas stiffened slabs would involve
digging trenches for the stiffening beams. Hence, the slab would normally be founded
below the natural ground surface. Therefore, in this calculation, ΔU is considered at 0.3
m depth below the ground surface. The AS2870 method was used only for the
Braybrook site using measured Iss values.
Figure 7-11: Idealized characteristic suction profiles in Braybrook site (VB1 model)
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max
50 yrs and extremes
-0.3
229
These round movement calculations were compared with the ground movement results
described in section 7.2.3. Table 7-3 lists the summary of estimation of ys for Braybrook
using the different methods explained above. According to the AS2870 method,
Braybrook has similar ys values irrespective of the periods. Consequently, Braybrook
was classified as E in both periods. When Hs and ΔU are taken from the Vadose/w
model, the Braybrook site is classified as E class in both periods. However, there is an
additional estimated ground movement of 18 mm due to extreme climate conditions
after 1995. The ground movement in response to different climatic conditions was
properly expressed in the FLAC model results, because this method does not simplify
the suction variation into a triangular shape but calculates ground movement due to
changes in successive monthly moisture profiles which directly obtained from the
Vadose/w model. It predicted an additional 15 mm in the Braybrook site due to the
millennium drought. Overall, the model predictions highlight the influence of the
millennium drought on ground movement, which created an approximately 15% to 20%
increment.
Table 7-3: Estimation of ys for Braybrook site
Method 1945 - 1995 period 1945 - 2012 period Percentage
increment of ys
Hs (m)
ΔU (pF)
ys (mm)
Site class
Hs (m)
ΔU (pF)
ys (mm)
Site class
AS2870 2.3 1.2 83 E 2.3 1.2 83 E 0 Vadose + AS2870
3.0 1.3 116 E 3.0 1.5 134 E 16
Vadose + FLAC
-* -* 80 E -* -* 95 E 19
-* :- not involved in this method
7.2.4.2 Ground movements in 25 year periods
AS2870 recommends considering at least 25 years to calculate TMI in determining the
effect of climate conditions on ground movement. Section 3.3.5.3 suggests that the
effects of isolated extreme events are neutralized by considering a higher number of
years in the TMI calculation. Hence, the use of a longer period (or all available data)
may not represent the actual condition of the soil. However, selecting a limited number
230
of years makes the TMI biased, if there are influential short-term climate events. Hence,
in this study, the climate conditions in 25-year periods were investigated to observe the
TMI changes and the ground movements emphasizing the impact of the millennium
drought. Table 7-4 shows the 5 different periods during 1950 to 2014. TMI values were
calculated using Method 1 (explained in Chapter 3) and then the climate zones were
selected as specified in AS2870 (2011).
Table 7-4: 25 year periods and corresponding TMI
Period TMI Climate zone (AS2870, 2011)
1950-1974 -4 2 1960-1984 -7 3 1970-1994 -6 3 1980-2004 -12 3 1990-2014 -16 4
Hs and ΔU were selected from the standard for the corresponding climate zone. Table
7-5 lists ys calculations for 25-year periods.
Table 7-5: Estimation of ys based on AS2870 (2011) for Braybrook
Period Hs (m)
ΔU (pF)
ys (mm)
Site class
1950-1974 1.8 1.2 66 H2 1960-1984 2.3 1.2 83 E 1970-1994 2.3 1.2 83 E 1980-2004 2.3 1.2 83 E 1990-2014 3.0 1.2 107 E
According to Table 7-5, the Braybrook site classification changed from H2 to E during
25-year periods. The influence of drought reduced the TMI value in the last two 25-year
blocks. Since Hs increased from 2.3 m to 3.0 m when changing the climate zone from 3
to 4, the estimated ys was increased.
The 25-year blocks were considered in the Vadose/w model predictions. In contrast to
the standard specifications, the model predictions have shown that the ΔU has changed
as a result of climate conditions. Hs of Braybrook is higher than that of Fawkner, but
both sites have shown no changes in Hs during the 25-year periods (Figure 7-12).
231
Figure 7-12: Changes in characteristic suction profiles within 25 year periods; a) Braybrook -VB1 model and b) Fawkner-VF1 model
Hs and ΔU were taken from the Vadose/w model, which is shown in Figure 7-12(a). The
crack depth is considered as 0.75 of Hs. Measured Iss values were considered along the
depth of the Braybrook soil profile. Table 7-6 summarises the ys estimation for
Braybrook using different methods. The calculations and model predictions shown in
Table 7-6 are broadly consistent with the AS2870 method calculations given in Table
7-5. The effect of the millennium drought can be observed in the last 25-year block in
1990-2014. Table 7-7 shows that ys of the Fawkner site has also increased due to the
inclusion of the drought period in 1990-2014, but the magnitude of increment is lower
than that of Braybrook. This is possibly due to the less reactivity and the shallower soil
profile in Fawkner. However, these values suggest that the impacts of extreme events
can possibly be captured using the AS2870 method by reducing the average period of
TMI.
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-3.0
-2.7
-2.4
-2.1
-1.8
-1.5
-1.2
-0.9
-0.6
-0.3
0.0
Log (Matric Suction)
Dep
th (m
)
1950-1974 Characteristic min 1950-1974 Characteristic max 1960-1984 Characteristic min 1960-1984 Characteristic max 1970-1994 Characteristic min 1970-1994 Characteristic max 1980-2004 Characteristic min 1980-2004 Characteristic max 1990-2014 Characteristic min 1990-2014 Characteristic max
25 yr periods
a) b)
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
1950-1974 Characteristic min 1950-1974 Characteristic max 1960-1984 Characteristic min 1960-1984 Characteristic max 1970-1994 Characteristic min 1970-1994 Characteristic max 1980-2004 Characteristic min 1980-2004 Characteristic max 1990-2014 Characteristic min 1990-2014 Characteristic max
25 yr periods
-0.3
232
Table 7-6: Estimation of ys for 25 year periods – Braybrook site
Period Vadose + AS2870 Method Vadose + FLAC
Method Hs (m)
ΔU (pF)
ys (mm)
Site class
ys (mm)
Site class
1950-1974 3.0 1.2 107 E 70 H2 1960-1984 3.0 1.2 107 E 70 H2 1970-1994 3.0 1.3 116 E 85 E 1980-2004 3.0 1.3 116 E 85 E 1990-2014 3.0 1.3 116 E 101 E
Table 7-7: Estimation of ys for 25 year periods – Fawkner site
Period Vadose + FLAC
Method ys (mm) Site class
1950-1974 38 M 1960-1984 32 M 1970-1994 37 M 1980-2004 37 M 1990-2014 44 H1
7.2.5 Effects of the depth of bedrock on ground movement
The bedrock depth is frequently observed to be within 2 m to 4 m in the Western
suburbs of Melbourne. However, in the Braybrook site, the depth to the bedrock is
greater. The model was therefore developed up to 6 m depth. The measured soil
properties were available down to only about 2.5 m depth. In this research, a second,
modified model was created using the same soil properties, assuming that the bedrock is
located at 3 m depth. This model is denoted as VB2 hereafter. The VB2 model can be
considered as a general case for typical basaltic soil sites in the Western suburbs. The
VB2 model was developed with a 4 m soil column and the bottommost meter was
considered as the bedrock. The SWCCs of soils were considered similar to the VB1
model. The Ksat of soils between 1.8 m and 3 m were considered to be decreasing
gradually from the measured value at 1.8 m to the Ksat of bedrock. Then, the hydraulic
conductivity functions were developed accordingly as explained in Chapter 4.
Figure 7-13 shows the characteristic suction profiles obtained from the VB2 model. The
surface suction values highly depend on extreme climate events; hence, they are similar
233
to the results of the actual model with bedrock at 5 m. However, the shallower bedrock
caused a reduction in the depth of suction change. The VB2 model predicts that the Hs
is approximately 2.7 m for the pre-drought period. The suction profiles in this period
can be considered as typical shapes similar to the VB1 model results. The millennium
drought moved the dry suction profile further towards the dry side and the wettest
suction profile recorded after drought-breaking rainfalls was within the typical suction
profile. Figure 7-13 also shows the idealised triangular shapes drawn to calculate ys
using the AS2870 guideline.
Figure 7-13: Changes in characteristic suction profiles -VB2 model; a) Extreme profiles in three periods b) Idealized triangles for AS2870 calculations
Figure 7-14 shows the variation of ground movement obtained for the Braybrook site
using the VB2 and FLAC models. The fluctuations of the ground due to seasonal
movements in this figure are similar to the predictions of the VB1 model shown in
Figure 7-9. The seasonal ground movement was about 40 mm during the pre-drought
period and reduced to 25 mm during the millennium drought. Figure 7-14 shows that
there was a total ground movement (peak to peak) of 85 mm prior to the millennium
drought. Approximately 16 mm of additional ground movement occurred due to the
millennium drought.
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.02.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Log (Matric Suction)
Dep
th (m
)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max
a) b)
-0.3
Log (Matric Suction)
Dep
th (m
)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min
234
Figure 7-14: Ground movement prediction from VB2 and FLAC model
Table 7-8 shows a summary of estimation of ys using the VB2 model predictions and
the AS2870 method. The standard recommends similar Hs and ΔU values, even for the
modified case, because they are only dependent on climate conditions. Therefore, the ys
calculation for this modified case is essentially similar to the actual model (section
7.2.3) and produced no changes due to the inclusion of the millennium drought.
Although the Hs of the VB2 model is less than that of the VB1 model, the ys calculation
based on the Vadose and AS2870 method show similar ys values. The additional ground
movement of 16 mm due to millennium drought caused an increase of about 15% in the
typical ys. Similarly, in the Vadose and FLAC model, an additional 16 mm caused an
increase to the ys value of about 19%. According to the model predictions for 6 m and 3
m deep bedrock soil profiles, there was a 15% to 20 % increase in ground movement
due to the millennium drought.
Even though the depth of the bedrock is reduced in this analysis to consider the effect of
depth of bedrock, it is not considered to be less than the Hs limit of 3 m observed in the
VB1 model. It is only reduced to represent the typical depth of Bedrock in Melbourne
area. Hence, in this case, Hs is not affected by bedrock and the ground movement was
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-40
-30
-20
-10
0
10
20
30
40
50
60
70 Ground movement 12 month average
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
ys = ~ 85 mm
Additional ys = ~ 16 mm
235
not expected to be reduced. However, the bedrock represents a no-flow boundary in the
model, which the reduction of depth of this impervious layer resulted in greater
moisture fluctuations at top layers during the analysis. These fluctuations resulted in a
slight increase of ground movement.
Table 7-8: Estimation of ys for Braybrook site with bedrock at 3m depth (from VB2 model)
Method 1945 - 1995 period 1945 - 2012 period Percentage
increment of ys
Hs (m)
ΔU (pF)
ys (mm)
Site class
Hs (m)
ΔU (pF)
ys (mm)
Site class
AS2870 2.3 1.2 83 E 2.3 1.2 83 E 0 Vadose + AS2870
2.7 1.3 105 E 2.7 1.5 121 E 15
Vadose + FLAC
-* -* 85 E -* -* 101 E 19
-* :- not involved in this method
7.2.6 Effects of site drainage condition on ground movement
Runoff conditions govern the availability of water for infiltration into the soil. Since this
study focused on soil moisture changes in regards to urban residential footing design, an
appropriate runoff condition for residential areas was used, as explained in section
7.1.1.2. However, different runoff conditions can cause different soil moisture results
and hence it is important to maintain proper conditions to minimise possible damages.
In this section, different runoff conditions were considered to observe the possible
influences on ground movement. Figure 7-15 shows the soil moisture predictions from
the Vadose/w model without using a runoff correction. Hence, even if the daily rainfall
is much higher and spread over a few hours of the day, the full rainwater amount is
made available for infiltration until the saturation is achieved. This condition is similar
to flat, open areas of grassland with poor drainage. The predictions show that, in such
cases there is a considerable change in soil moisture even at deeper layers. This analysis
emphasizes the significance of a runoff correction in the Vadose/w model.
236
Figure 7-15: Soil moisture predictions without any runoff correction
In the earlier models presented in this chapter, a surface runoff correction of 60% was
considered. To provide further understanding of the effect of different levels of runoff,
another case of 30% runoff correction was analysed. Figure 7-16 shows the ground
movement predictions for the conditions of 60%, 30% and no runoff corrections.
Figure 7-16 indicates that the ground can have very high heave movements during wet
periods if the site has a poor drainage condition. In contrast, all the different runoff
conditions will produce similar ground movements during dry periods. There was a
considerable wet period in the early 1990s before the millennium drought. Hence, the
grounds were in a heaved state at the beginning of the drought and this has been the
main reason for the resulting excessive settlements within the drought period. The 60%
runoff correction considered in the above sections predicted a settlement of about 95
mm within this period. If the runoff condition is 30%, the settlement will increase by
about 20%. The condition with no runoff correction will increase it by about 45%.
Therefore, as expected, ground movement can be significantly reduced by providing
proper site drainage around a residential structure. A proper drainage condition (slope
away from the footing) with an appropriate runoff condition will minimise the water
available to infiltrate the soil underneath the footings.
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 20150.25
0.30
0.35
0.40
0.45
0.50
0.55 at 1.0 m depth at 2.0 m depth at 3.0 m depth at 4.0 m depth Daily rainfall (mm)
Date
Vol
umet
ric m
oist
ure
cont
ent
POND_OFF
0
50
100
150
Dai
ly ra
infa
ll (m
m)
237
Figure 7-16: Ground movement predictions with different runoff conditions
7.3 SHORT TERM CLIMATE VARIATIONS
In order to further examine ground movement due to different weather scenarios, more
models were analysed for an additional 4-year wet period as extended versions of the
models described in section 7.2.2. In this case, both the Braybrook and Fawkner soils
were considered. The climate data set used in the VB1 model was modified to include
an additional 4-year wet period at the end of 2014. The climate forecast of the wet
period was created by replicating the climate condition of the years 2010 and 2011 over
4 years. Hence, the soil moisture changes were considered from 1945 to 2018 with a
forecasted wet period in 2015-2018. The Braybrook model analysed using this climate
data set is denoted as VB3 hereafter. The Fawkner model is denoted as VF2.
Similarly, another 4 years of dry weather was forecast by replicating the climate
condition of 2013 and 2014. This condition was then added to the end of the climate
data set used in VB1. This data set was then used to consider the effect of a short-term
dry period. The Braybrook and Fawkner models analysed using this climate data set are
denoted as VB4 and VF3 respectively.
1945 1952 1959 1966 1973 1980 1987 1994 2001 2008 2015-50
0
50
100
150
200 No surface runoff No surface runoff (12 month average) 30% surface runoff 30% surface runoff (12 month average) 60% surface runoff 60% surface runoff (12 month average)
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
238
Figure 7-17 shows the variation of the 12-month moving average ground movement
obtained from the VB1, VB3 and VB4 model predictions fed into the FLAC model. The
VB3 model outcome suggests that if a wet climate condition occurs in the next 4 years,
the ongoing settling trend will terminate and the ground will reach conditions similar to
2011. However, 4 years is not enough to recover from the millennium drought and to
reach the typical conditions experienced in the pre-1995 period. VB3 model was
analysed further with 2 more years of wet climate condition similar to 2010-2011. The
results suggest that the ground would recover to the condition it had in the 1980s in
about six years in total.
The VB4 model predictions suggest that the ground will remain in the moisture deficit
condition experienced during the millennium drought. A similar outcome was observed
in the Fawkner site from the VF2 and VF3 models, shown in Figure 7-18. Since
Fawkner has a less reactive and shallower soil profile than Braybrook, changes due to
short-term climate conditions create smaller changes in ground movement. Hence, both
the wet and dry 4-year models showed only small changes in terms of the 12-month
moving average. Further, this emphasises the impact of soil and site conditions on
ground movement in terms of recovery from extreme climate events. However, this
model does not consider cracking of soils which accelerates the wetting process after a
severe dry period in an actual condition. The cracks allow water to fill in and start to
wet the deeper soils. Hence, the recovery process could be faster in actual condition
than the model prediction.
239
Figure 7-17: 12 month moving average ground movement – Braybrook
Figure 7-18: 12 month moving average ground movement –Fawkner
1945 1953 1961 1969 1977 1985 1993 2001 2009 2017-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
60 from VB3 model - Predicted wet climate: 2015 - 2018 from VB4 model - Predicted dry climate: 2015 - 2018 from VB1 model - Actual climate: 1945 - 2014
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
1945 1953 1961 1969 1977 1985 1993 2001 2009 2017-25
-20
-15
-10
-5
0
5
10
15
20
25 from VF2 model - Predicted dry climate: 2015 - 2018 from VF3 model - Predicted wet climate: 2015 - 2018 from VF1 model - Actual climate: 1945 - 2014
Date
Gro
und
mov
emen
t (m
m)
POND_OFF
240
7.4 LONG TERM CLIMATE PREDICTIONS
Climate predictions for Australia suggest that the ongoing drying trend will continue
into the future (Austroads, 2004, Smith et al., 2009, Hughes, 2003). Most Australian
cities will experience a reduction in rainfall and an increase in temperature. According
to the average of several scenarios, there would be a reduction in annual rainfall by
about 14% and an increase in temperature by 2.5 0C within the typical 100-year period.
These predictions were incorporated in the 1D models developed in Vadose/w software
to observe possible future changes in soil moisture content.
In this case, the climate data set period of 1987-1992 from Essendon airport was chosen
and considered as an average weather condition. This 5-year period was replicated over
50 years to create a typical average climate data set. Then, the Austroads (2004) climate
predictions were applied to this data set. Minimum and maximum temperatures were
modified to show a gradual increase of 1.25 0C at the end of the 50 years. A gradual
reduction of rainfall was also applied to the average data set, such that there is a total
reduction of 7% by the end of the 50-year period. 1D models developed in Vadose/w
software were analysed for these climate data sets for both the Braybrook and Fawkner
soil properties. The Braybrook models analysed using average and modified climate
data are denoted as VB5_A and VB5_M respectively. Similarly, the Fawkner models
are denoted as VF4_A and VF4_M.
Figures 7-19 and 7-20 show changes in ground movement due to predicted climate
changes. They clearly indicate that there would be an additional settlement in ground
surface due to predicted conditions compared to the average typical condition. The
Braybrook site indicated 12 mm of additional settlement, whereas Fawkner indicated 6
mm. The settlement in Braybrook appears to be severe compared to Fawkner, which is
due to the shallower bedrock and less reactive soil in Fawkner.
241
Figure 7-19: Effect of long-term climate predictions on ground movement – Braybrook
Figure 7-20: Effect of long-term climate predictions on ground movement – Fawkner
2013 2018 2023 2028 2033 2038 2043 2048 2053 2058-8
-4
0
4
8
12
16
20
24
28
32
36 from VB5_A model from VB5_M model
Number of years
Gro
und
mov
emen
t (m
m)
POND_OFF - typical vs predicted
12 mm
0 5 10 15 20 25 30 35 40 45 50
2013 2018 2023 2028 2033 2038 2043 2048 2053 2058-8
-6
-4
-2
0
2
4
6
8
10
12
14
16
18
20
from VF4_A model from VF4_A model
Number of years
Gro
und
mov
emen
t (m
m)
POND_OFF - typical vs predicted
6 mm
0 5 10 15 20 25 30 35 40 45 50
242
The moisture deficit condition of the soils would create conditions for severe results.
For example, failures in water pipes or excessive garden watering could create severe
differential movements due to the ability of soil to have high absorption. Thus, potential
climate change can create such situations.
7.5 SOIL MOISTURE CHANGES BENEATH COVER SLABS
The effects of long-term climate conditions were further studied using the 2D model to
observe the changes underneath the footing, together with some effects from abnormal
conditions.
The 2D model was mainly developed to observe the lateral soil moisture movements
beneath cover slabs. The model predictions were used to examine the changes in edge
moisture variation, which is an important parameter in residential footing design.
The long-term climate data used in the 1D model explained in section 7.1 was used in
the 2D model. Hence, the effects of different climate conditions on the extent of
moisture change from the slab edge (‘e’ distance) in three periods were considered and
described in this section. The 2D model incorporated a 0.3 x 6 m cover slab and 5 m
long open area, as shown in Figure 6-22. The cover slab was assumed to be perfectly
flexible with no applied load. Hence, the slab is just a cover in this analysis. The soil
moisture variation underneath the cover slab (at 300 mm depth) was used to investigate
the changes in ‘e’ distance. This model was analysed for the same climate data used in
the VB1 model and this is denoted as 2DVB1 hereafter.
Figure 7-21 shows the variation of soil moisture at 300 mm depth during the period
1945–2015. All the soils were at about 35% volumetric moisture content at the initial
stage. Figure 7-21 shows that even though the slab shields the soils beneath it from
climate influences, the moistures changed up to a significant distance. The far end has
been defined as a no-flow boundary (prevents moisture movement), which is the axis of
symmetry. The 2D model results show that there is a slight change in soil moisture even
at the far end of the slab. This is due to long term equilibrium occurring under the slab
where impacts of climate conditions at the outside of the edge cannot be reached.
However, this moisture change is less than 1% within 70 years and hence can be
considered negligible.
243
Figure 7-21: Predicted moisture variation with the distance at 300 mm depth in Braybrook soil
Since soil suction is the preferred parameter over moisture content, the suction variation
under the cover slab was considered to examine the changes in ‘e’ distance. There was a
slight continuous change in suction that proceeded towards the far end of the slab,
similar to the moisture variation shown in Figure 7-21. It was corrected by adjusting all
the suctions by adding an offset to make no suction variation at the far end. Figure 7-22
shows the corrected critical suctions along the 300 mm depth layer. Since the wettest
suction profile during the 2-year wet period in 2010 and 2011 was found within the
suction profiles of the typical condition in 1945-1995 as shown in Figure 7-6(a), the
post-drought period was not considered here. However, the driest suction during 1996-
2010 was plotted to observe the effects of the millennium drought.
During wet periods, the soil moisture content increased due to water infiltration. Hence,
edges of the slabs tended to heave due to the swelling of surrounding soils. This was
identified as an edge heave condition. During a dry period, moisture content reduces
and thus soils around the slab edge settle down, which is referred to as edge settlement.
In Figure 7-22, the suctions on the ‘y’ axis were plotted in the reverse direction to
graphically identify the edge heave and edge settlement conditions. The ‘e’ distances
0 1 2 3 4 5 6 7 8 9 10 110.22
0.24
0.26
0.28
0.30
0.32
0.34
0.36
0.38
0.40
0.42
0.44
Axis of symmetry6 m long cover slab Open area exposed to climate effects
Volu
met
ric m
oist
ure
cont
ent
Distance (m)
300 mm
Soil
244
obtained were compared to the initial condition shown in Figure 7-22. The suction
variations in 1945-1995 show the typical ‘e’ distance in the Braybrook soil, which is
about 4 m for edge heave condition and 3 m for centre heave condition. The extraction
of soil moisture is difficult compared to absorption. Hence, the soil moisture changes in
the edge heave condition continued far into the bottom of the slab, compared to the
centre heave condition. However, during the millennium drought, the variation of the
driest suctions closely approached the similar ‘e’ distance as the edge heave condition.
Figure 7-22: Predicted edge moisture variation (e) at 300 mm depth in Braybrook soil
AS2870 provides two equations for ‘e’ distance for centre heave (can be treated as edge
settlement) and edge heave conditions, as given in Equations 7-1 and 7-2 respectively,
𝑒 =𝐻𝑠
8+
𝑦𝑚
36; For centre heave condition ……..……………...………... Equation 7-1
𝑒 = 0.2 × 𝐿 ≤ 0.6 +𝑦𝑚
25; For edge heave condition ………....………... Equation 7-2
where ‘Hs’ is the design depth of suction change in metres, ‘ym’ is differential mound
movement in millimetres and ‘L’ is slab length in metres.
0 1 2 3 4 5 6 7 8 9 10 112.50
2.75
3.00
3.25
3.50
3.75
4.00
4.25
4.50
Edge settlement
Edge heave
Intial condition
Characteristic wettest suctions 1945-1995 Characteristic driest suctions 1945-1995 Characteristic driest suctions 1996-2010
Log
(Mat
ric s
uctio
n)
Distance (m)
6 m long cover slab Open area exposed to climate effects300 mm
Soil
Axis of symmetry
245
These equations estimate ‘e’ in metres. The value of ym depends on ys and the heave
condition as shown in Table 7-9. The Mitchell's method shown in Table 7-9 provides
conservative values for ym and hence for ‘e’ distance. Therefore, this method was used
to calculate ‘e’ distance in this section to compare with the model predictions. ys values
obtained from the AS2870 estimation and the 1D model (described in section 7.2.3 and
Table 7-3) were used to obtain ‘e’ distance from Equations 7-1 and 7-2. ‘e’ distance
given in Equation 7-2 depends on the slab length and is limited by ym. Since the cover
in the 2D model represents only half of the cover, it can be taken as an infinitely long
slab. Hence, in the edge heave condition, ‘e’ distance was taken from the limit related to
ym in Equation 7-2. The values taken from these equations are compared with the 2D
model predictions in Table 7-10.
Table 7-9: relationship of ym and ys (AS2870, 2011)
Table 7-10: Comparison of changes in 'e' distances
Heave condition Method
1945 - 1995 period 1945 - 2009 period Hs (m)
ys (mm)
e (m)
Hs (m)
ys (mm)
e (m)
Centre heave
AS2870 2.3 83 1.9 2.3 83 1.9 1D Vadose model 3.0 80 1.9 3.0 95 2.2
2D Vadose model (Figure 7-22)
-* -* 3.0 -* -* 3.5
Edge heave
AS2870 -* 83 2.9 -* 83 2.9 1D Vadose model -* 80 2.8 -* 95 3.3
2D Vadose model (Figure 7-22)
-* -* 4.0 -* -* 4.0
-* :- not involved in this method
As described in section 7.2.3, the AS2870 model estimates the same ys values for the
two periods excluding and including the millennium drought condition. As a result, both
Heave condition
ym for Walsh's method
ym for Mitchell's method
Centre heave 0.7 ys 0.7 ys Edge heave 0.5 ys 0.7 ys
246
Equations 7-1 and 7-2 produce the same ‘e’ values for those two periods. However,
these two equations are sensitive to the difficulty of extraction and absorption of soil
moisture and therefore the calculated ‘e’ value in the edge heave condition is higher
than that of the centre heave condition. The predicted ys values from VB1 model were
used in Equations 7-1 and 7-2 to calculate ‘e’ distances. The results show an increase of
about 15% in ‘e’ distance in both heave conditions due to the millennium drought. The
2DVB1 model results suggested that ‘e’ distance is higher than the calculated values
based on ys. Furthermore, there is also a 20% increase in ‘e’ due to the millennium
drought. Since the wettest recorded condition in the rainy period (2010 and 2011) was
within the average conditions (Figure 7-6(a)), there is no change in ‘e’ distance in edge
heave condition for pre- and post-drought periods.
The 2DVB1 model indicates that the moisture can proceed far underneath the slab
compared to the predictions from the VB1 model and the AS2870 method. This
moisture change is governed by the hydraulic conductivity in the lateral direction, as
described in the previous chapter. At the Braybrook site, there is a change in soil layers
at 300 mm depth. The hydraulic conductivity of soils below 300 mm is lower than the
top layer. Hence, the moisture prefers to accumulate on the layer interface than
penetrate the below soil. These moistures then tend to travel along the lateral direction.
In actual conditions, this phenomenon may not occur, and the cracks can accelerate the
vertical moisture movement that reduces the moisture change in lateral direction.
Hence, the magnitude of ‘e’ distance can be lower in actual condition. However, in
terms of percentage change of ‘e’, the model results suggest that the millennium
drought created an increase of 15% to 20%.
7.6 CHANGES OF THE MOUND PROFILES
In addition to the estimation of the ‘e’ distance via soil moisture predictions, the 2D
Vadose/w model results were fed into the FLAC model (described in section 7.1.2.3) to
observe the variation of mound shapes. The FLAC model is essentially a one-
dimensional soil column. In this case, the 2D Vadose/w model results at several discrete
points along the width of the model were saved separately to produce moisture profiles
at those points. These profiles were then used in the one dimensional soil column in the
FLAC model to obtain ground movement at the discrete points to draw the mound
247
shape. Nine discrete points were selected at 1 m intervals both underneath the slab and
open ground, as shown in Figure 7-23. The cover slab was 6 m long; therefore, those
discrete points selected were symmetrical to the slab edge.
There are certain limitations in using the 2D Vadose/w model results in the FLAC
model to obtain the ground movement. As the one-dimensional soil column in the
FLAC model does not consider the movement of adjacent soils, the predictions appear
to be higher than actual conditions. In actual conditions, the shear effects in adjacent
soil particles restrain the free movement and reduce severe movements in adjacent soils.
Such influences can be observed near the edge of the slab where greater changes in ΔU
and Hs occur in adjacent soils. The FLAC model outcome showed greater mound slope
near the slab edge where actual conditions would create a smooth mound shape. This
issue can be overcome by developing a two-dimensional FLAC model that considers
the shear effects. This part of the model development is yet to be finalised and the
FLAC model development is out of the scope of this PhD research.
Figure 7-23: Discrete points along the distance where soil moisture variations considered to obtain ground movement
Distance - m-0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0
Elev
atio
n - m
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
Climate BoundaryNo flow Boundary on cover slab
2m 3m 4m 5m 6m 7m 8m 9m 10m
Axis of symmetry
248
The generated deflected shapes (mound shapes) due to heave and settlement conditions
were considered in this case to identify the mound parameters (ym, ys and ‘e’ distance)
as defined in AS2870. Therefore, the worst dry period and wet period were selected
based on Figure 7-9. Based on the ground movements shown in Figure 7-9, the
Braybrook site had a gradual heave condition from 1983 to 1992 followed by a
settlement condition, during the millennium drought, until 2010. If a slab had been
constructed in 1983, it would have experienced the maximum edge heave in 1992.
Similarly, if a slab had been constructed in 1992, it would have experienced the
maximum edge settlement at the end of 2010. Therefore, the 1983-1992 and 1992-2010
periods were selected to observe the mound shapes in edge heave and edge settlement
conditions. The following sections describe the predictions of those mound shapes.
7.6.1 Slab subjected to heave condition (1983 to 1992)
The 2D Vadose/w model with cover slab (similar to the model shown in Figure 7-23)
was analysed for the period of 1983-1992 to represent the situation of a newly placed
slab in 1983. This model is denoted as 2DVB2 hereafter. The 2DVB2 model requires
the defining of initial moisture conditions at each node point of the model. Hence,
another 2D model with the same size as that shown in Figure 7-23 was analysed without
any cover slab. This model was essentially developed to define initial moisture content
at different starting points of any model to be considered with a cover slab and is
denoted as 2DVB_I. Analysis of the 2DVB_I model for the period from 1945 to 2012
produced identical results to the VB1 model described in section 7.2. However, since it
is a two-dimensional model of the same size, it can be used to define the initial moisture
contents corresponding to all the nodes in the 2DVB2 model.
Figures 7-24 to 7-26 show the characteristic minimum and maximum suction profiles at
certain discrete points along the width of the model. The changes of suctions are
minimal at 3 m distance, which indicates only a small ground movement. The ΔU and
Hs increase towards the edge of the slab and as expected have the highest values at the
open ground. These ΔU and Hs values were used to calculate ground movement at the
discrete points based on AS2870 procedure. Measured Iss values were used along the
depth to represent the Braybrook soil condition. In addition, the monthly variations in
moisture profiles at those discrete points were used in the 1D FLAC model to obtain the
ground movements. The ground movements along the distance are shown in Table 7-11.
249
Figure 7-24: Suction profiles during 1983-1992 at distances 3 m and 4 m from axis of symmetry
Figure 7-25: Suction profiles during 1983-1992 at distances 5 m and 6 m from axis of symmetry
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 3 m Characteristic max at 3 m
-0.3 -0.3
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 4 m Characteristic max at 4 m
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 5 m Characteristic max at 5 m
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 6 m Characteristic max at 6 m
-0.3-0.3
250
Figure 7-26: Suction profiles during 1983-1992 at distances 7 m and 8 m from axis of symmetry
Figure 7-27 demonstrates that the calculations using Vadose/w + AS2870 method are in
strong agreement with the FLAC model predictions. However, the ground movement
results given in Table 7-11 show differences in some values, especially at the open
ground which may be due to the idealisation of suction triangles in AS2870 procedure.
Moreover, the AS2870 method considers the effect of crack depth, such that movement
is higher at the depths below the crack depth. This effect is enhanced in open ground
where Hs values are higher compared to the soil under the slab.
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 7 m Characteristic max at 7 m
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 8 m Characteristic max at 8 m
-0.3-0.3
251
Figure 7-27: Maximum edge heave profile during 1983-1992
Table 7-11: Ground movement estimation during 1983-1992
Parameter Distance from axis of symmetry
2m 3m 4m 5m 6m 7m 8m 9m 10m ΔU (pF) 0.17 0.21 0.30 0.44 0.87 1.16 1.19 1.20 1.20 Hs (m) 1.0 1.0 1.3 1.5 2.0 2.0 2.0 2.0 2.0
ys (mm) from Vadose + AS2870 method 5 6 12 20 52 70 72 72 72
Ground movement (mm)from Vadose +
FLAC method 4 6 10 17 46 57 60 61 61
7.6.2 Slab subjected to settlement condition (1992 to 2010)
Similar to the edge heave condition investigated in 2DVB2 model, the centre heave
condition was also considered during a wet period. Since there was a wet period
recorded before the millennium drought, the soils continued to settle starting from a
high value in 1992. This model considered the climate condition from 1992 to 2010 and
0 1 2 3 4 5 6 7 8 9 10 11-10
0
10
20
30
40
50
60
70
Edge heave
FLAC model predictions Vadose model predictions+ AS2870 method
Gro
und
mov
emen
t (m
m)
Distance (m)
6 m long cover slab Open area exposed to climate effects300 mm
Soil
Axis of symmetry
Extent of cover
Intial condition
252
is denoted as 2DVB3 hereafter. The 2DVB_I model was employed to obtain the initial
moisture contents in 1992 and then the 2DVB3 model was analysed up to 2010.
Figures 7-28 to 7-30 show the characteristic minimum and maximum suction profiles at
certain discrete points along the width of the model. The changes of suctions are
minimal at 3 m distance indicating only a small ground movement, similar to the edge
heave condition. The ΔU and Hs increase towards the edge of the slab and as expected
have the highest values at the open ground. These ΔU and Hs values were used to
calculate ground movement at those discrete points based on AS2870 procedure. The
FLAC model was also used to obtain ground movements at the discrete points using
monthly soil moisture profiles.
Figure 7-28: Suction profiles during 1992-2010 at distances 3 m and 4 m from axis of symmetry
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 3 m Characteristic max at 3 m
-0.3 -0.3
Log (Matric Suction)D
epth
(m)
Characteristic min at 4 m Characteristic max at 4 m
253
Figure 7-29: Suction profiles during 1992-2010 at distances 5 m and 6 m from axis of symmetry
Figure 7-30: Suction profiles during 1992-2010 at distances 7 m and 8 m from axis of symmetry
Figure 7-31 shows the edge settlement profile obtained from the two methods. Similar
to the edge heave case, both methods produced similar mound shapes. Table 7-12 shows
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 5 m Characteristic max at 5 m
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 6 m Characteristic max at 6 m
-0.3 -0.3
1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
01.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
-6
-5
-4
-3
-2
-1
0
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 7 m Characteristic max at 7 m
Log (Matric Suction)
Dep
th (m
)
Characteristic min at 8 m Characteristic max at 8 m
-0.3 -0.3
254
the ground movement values from both methods. The corresponding location values are
similar in both methods apart from values at the open area, which is possibly due the
consideration of crack with in Vadose + AS2870 method. Further, the FLAC model
results show a sudden settlement near the slab edge, which caused this difference. This
is possibly due to the non-availability of shear resistance from adjacent soils, which is
lacking in the one-dimensional soil column in the FLAC model.
Figure 7-31: Maximum centre heave profile during 1992-2010
Table 7-12: Ground movement estimation during 1992-2010
Parameter Distance from axis of symmetry
2m 3m 4m 5m 6m 7m 8m 9m 10m ΔU (pF) 0.12 0.23 0.49 0.55 0.84 1.15 1.17 1.18 1.18 Hs (m) 0.9 1.0 1.2 1.5 2.0 2.5 2.5 2.5 2.5
ys (mm) from Vadose + AS2870 method 3 7 18 25 51 86 88 89 89
Ground movement (mm)from Vadose +
FLAC method 2 5 10 19 60 73 77 79 79
0 1 2 3 4 5 6 7 8 9 10 11
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
10
Edge settlement
FLAC model predictions Vadose model predictions+ AS2870 method
Gro
und
mov
emen
t (m
m)
Distance (m)
6 m long cover slab Open area exposed to climate effects300 mm
Soil
Intial condition
Axis of symmetry
Extent of cover
255
7.6.3 Comparison of mound shape predictions
Based on the 2DVB2 and 2DVB3 model results described in the previous two sections,
important parameters for mound shapes can be identified. The ground movement
immediately under the edge of the slab (ym) and the movement in open ground (ys) can
be compared in each mound shape. The ratios between these two parameters are
proposed in Walsh’s and Mitchell’s methods as listed in AS2870 and shown in Table
7-9. Table 7-13 shows those ratios obtained from the modelling results presented in the
previous two sections. For the edge heave condition in 1983-1992 in the Braybrook site,
ym/ys factors are 0.7 and 0.8. For the edge settlement condition in 1992-2010 in the
Braybrook site, ym/ys factors are 0.6 and 0.8. These values are in line with the proposed
0.7 factor in Mitchell’s method. By using more analyses of different sites, these
relationships, including ‘e’ distance, can be established.
Table 7-13: Mound shape parameters obtained from models
Method
Edge heave (1983-1992)
Edge settlement (1992-2010)
ys (m)
ym (m) ym/ys ys
(m) ym (m) ym/ys
Vadose + AS2870 72 52 0.7 89 51 0.6
Vadose + FLAC 61 46 0.8 79 60 0.8
7.7 EFFECT OF ABNORMAL MOISTURE CONDITIONS
Climate conditions can significantly affect moisture conditions around and underneath
slabs, as described in the above section. These influences can be exaggerated due to
improper maintenance of the area adjacent to footings, which includes non-attendance
to broken water pipes. The author observed house construction sites and visited some
damaged houses during the study period. In most cases, the soils around the footing
were not given adequate attention during construction. In some cases, rainwater
downpipes were not connected to the drain lines, which created significant amounts of
water next to the slab edges during the construction period. Moreover, some sites have
open areas with slopes towards the footing. Some new houses had additions after
constructions, such as pavements with slopes towards the houses. As a result, runoff
water flowed towards the slab, which increased the amount of water available for
256
infiltration. In this study, the modelling of a sloping ground was used to investigate soil
moisture changes.
7.7.1 Soil slope towards the cover slab
In this case, a mild slope of 1:50 towards the cover slab was introduced over the 5 m
length of open area in the 2D Vadose/w model. The model was analysed from 1945 to
2012 to observe the suction changes in different climate conditions. This model will be
denoted as the 2DVB4_S model hereafter. Since the effect of the slope of open ground
and consequent water collection next to the slab was required in the 2DVB4_S model, a
ponding effect available in Vadose/w software was used. In this case, the model allows
water to travel along the dip and collect at the lowest point of the surface. Hence, more
water is available for infiltration at the edge of the slab. The 2DVB4_S model results
were compared with the 2DVB1 model, which had no slope in any direction and
pooling on the surface was also not allowed. Figure 7-32 shows the suction variation at
300 mm depth observed in the 2DVB1 and 2DVB4_S models.
Figure 7-32: Comparison of lateral moisture movement at 300 mm depth in with and without slope condition
0 1 2 3 4 5 6 7 8 9 10 11
2.6
2.8
3.0
3.2
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
5.0
0.45 pF
Soil
1
}Distance (m)
Log
(Mat
ric s
uctio
n)
1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min 1945-1995 Characteristic min 1945-1995 Characteristic max 1996-2010 Characteristic max 2011-2012 Characteristic min
Open area exposed to climate effects
300 mm
Soil
}from 2DVB1model
}from 2DVB4_Smodel
6 m long cover slab
50Axis of symmetry
257
Since rainwater can flow towards the cover, the moisture content of the soils next to
slab edge is higher in the 2DVB4_S model than in the 2DVB1 model. Specifically, the
amount of water available to move laterally beneath the cover slab is substantially
increased. This phenomenon reaches significant proportions in 2011 and 2012, the two
years of above average rainfalls after the millennium drought. During this wet period,
suction at the edge of the slab is 0.45 pF lower in the 2DVB4_S model than in the
2DVB1 model, which emphasises the influence of water flow, and collects near the slab
edge. The decrease in moisture content during the drought period was also lower in the
2DVB4_S model predictions than in the 2DVB1 model. This is because the additional
amount of water available at the slab edge moves into the soils beneath and decreases
the deficit. Taken together, the model results suggest that soil moisture changes beneath
covers can be significantly increased due to slopes towards the footing.
7.8 SUMMARY
This chapter describes the applications of the finite element models developed in this
study to predict soil moisture changes. The models were used to determine soil moisture
changes due to several long-term climate scenarios and site conditions. In addition to
the Braybrook site, Fawkner, another reactive soil site in Melbourne, was also
considered. Fawkner has a shallower soil profile and less reactive soils than Braybrook.
Each analysed model was denoted based on the considered climate data set and the site
conditions. The model predictions were then used to obtain ground movements using
three different methods - the AS2870 method, the Vadose + AS2870 method and the
Vadose + FLAC method.
The long-term climate data were taken from Essendon airport weather station for the
analysis period of 1900 to 2015. The initial conditions were not known for these periods
and hence the initial conditions corresponding to calibration (given in Chapter 6) were
used. However, the model results for the first 30 to 40 years were ignored to avoid the
effects of the initial condition. The model results considered the period commencing 50
years before the millennium drought. This period was divided into three sections based
on the millennium drought: pre-drought (1945-1995), millennium drought (1996-2010)
and the wet period after the drought (2011-2012). The condition in the 1945-1995
period was considered as the average climate condition during a lifespan of a structure.
258
ΔU and Hs values were obtained from the models’ results for different periods. There
was a very high suction change observed at the ground surface, which is due to direct
interaction with climate conditions. Nevertheless, during the construction of footings,
the top soil is normally removed and the slab would typically be founded below the
natural ground surface. Therefore, in this calculation, ΔU is considered at 0.3 m depth,
below the ground surface.
The predictions of VB1 (the Braybrook model for 1945-2012) suggest that between
1945 and 1995, ΔU and Hs for Braybrook were 1.3 pF and 3.0 m respectively.
Similarly, VF1 (the Fawkner model for 1945-2012) suggests that Fawkner had ΔU and
Hs of 1.5 pF and 1.8 m respectively. Deep-seated moisture change was observed in the
VB1 model as Braybrook has a deep soil profile. However, because of the shallower
soil profile in Fawkner, the VF1 model showed a smaller Hs value than VB1 for the
Fawkner site. Since the moisture movements continue at a deeper depth in Braybrook,
the fluctuations and changes near the surface (at 0.3 m depth) were less than those of
Fawkner. Both the VB1 and VF1 models predicted that these sites experienced an
additional increase of suction of 0.2 pF due to the moisture deficit created by the
millennium drought. Ground movement predictions of the FLAC model using the VB1
and VF1 model results showed variations in seasonal ground moments. These results
suggest that the millennium drought was the worst drought recorded during the past 70
years and highlight the settlement trend during the 1996-2009 period. According to the
ground movement calculations from these model results, the millennium drought
created a 15% to 20% increase in the ground movement experienced in the pre-drought
period. This increment was not captured by the AS2870 method, which depends on
average TMI over the calculated period. However, when the TMI was calculated in 25-
year blocks instead of over the total period, the impact of the drought was reflected in
the ground movements.
The VB2 model was analysed to consider the effect of the depth of bedrock. Here, the
bedrock of Braybrook was assumed to be at 3 m, which represents the typical condition
of a basaltic soil site. This model resulted in a lesser Hs value (2.7 m) but the ΔU was
the same as in VB1, indicating the influence of bedrock on the depth of Hs. ΔU
primarily depends on soil properties and extreme climate conditions. However, the VB2
259
model also predicted a 15% to 20% increase in ground movement due to the millennium
drought.
The Vadose/w software considers the runoff when the rainfall is distributed over 24
hours of the day provided that the surface layer is saturated. The daily rainfall is treated
in Vadose/w models such that it is a sinusoidal distribution over 24 hours and hence,
even if the daily intensity is high, the hourly intensity can be low. However, in most
rainy days, rainfall is not evenly spread throughout but falls at high intensity during
certain parts of the day, and most of such rainwater runs off, allowing only a small
amount to infiltrate the soil. Therefore, in such intense rainy days, a further correction is
added to the data before they input to the model. A surface runoff correction of 60%
(typical value for urban residential areas) was considered in all the models discussed
here. Further models were analysed to determine the influence of site drainage
conditions on ground movement. In this case, 30% and zero runoff corrections were
considered. A lower surface runoff is associated with greater availability of water for
infiltration. Hence, poor drainage conditions will create greater ground movements.
Compared to the 60% runoff considered in VB1, 30% and zero runoff increase the
maximum observed ground movement by 20% and 45%, respectively.
The 1D models were also used to determine the ground movement due to predicted
climate conditions. In this case, 4 years of wet and dry climate conditions were
forecasted for 2015-2018 using past climate data. These climate data sets were used to
analyse 1D models from 1945 to 2018. The model results from a forecasted wet climate
condition suggest that the ongoing settling trend will terminate due to wet conditions
and the ground conditions will be similar to those experienced in 2011. However, 4
years of wet climate conditions is not sufficient to allow the grounds to fully recover
from the moisture deficit caused by the millennium drought period. However, in actual
condition, cracks allow rainwater to move deep into the soil and accelerate the wetting
process. Therefore, in actual condition, a further recovery could have been observed by
such 4 years of above average rainfall. The model results from a forecasted dry climate
condition showed that a dry period will drag the soils back to a drought condition at the
end of 2018. The changes in ground movement in the Fawkner site due to these
different climate conditions are smaller than in Braybrook. This is due to the shallower
and less reactive soil profile in Fawkner.
260
Moreover, long-term climate predictions were also considered using 1D models.
Reported climate predictions suggest an ongoing drying with an increase in temperature
and a decrease in rainfall. These changes were applied to a data set of typical average
climate conditions over 50 years. Model predictions suggest that both Braybrook and
Fawkner soils will experience a moisture deficit due to an ongoing drying compared to
the typical average condition. At the end of the 50-year period, Braybrook will
experience an additional 12 mm settlement, whereas Fawkner will experience half of
that.
The 2D model developed in Vadose/w software was used to determine the soil moisture
changes in the lateral direction. A perfectly flexible cover was introduced into the 2D
model to investigate the soil moisture changes beneath the cover due to climate
influences on an adjacent open area. The results of this model (2DVB1) were also
useful in identifying changes in ‘e’ distance due to different climate conditions. The ‘e’
distances obtained from these models were compared with those of the AS2870 method.
The model predictions suggested that the millennium drought has created an increase of
15% to 20% in ‘e’ distances. Since the AS2870 method produced the same ys for the
1945-1995 and 1945-2009 periods, the change in ‘e’ distance was not captured using
this method.
Changes in soil mound shapes beneath cover slabs were also investigated using the 2D
model results. To observe edge heave and edge settlement conditions, two periods of the
most extreme wet and dry climate conditions were identified: 1983-1992 and 1992-2010
respectively. Then, two different models were analysed for climate conditions in these
periods. The moisture predictions of these models were used in a one-dimensional soil
column in the FLAC model to determine the ground movement at several discrete
points along the distance from the axis of symmetry. ys values were also calculated
based on the AS2870 method using characteristic suction profiles at these discrete
points. Considering mound profiles in both edge heave and edge settlement conditions,
the calculations based on the AS2870 method are in strong agreement with the FLAC
model predictions. However, the FLAC model predictions showed a steep slope in
mound profiles near the edge of the slab. This is possibly because the one-dimensional
soil column in the FLAC model does not consider the shear effects between adjacent
soils. The shear interaction in adjacent soils will reduce sudden high deflection of
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discrete points and hence produce a smooth mound profile. A full 2D model in FLAC
will overcome this issue; however, development of the 2D model in FLAC is yet to be
completed and is beyond the scope of this thesis.
Further analyses in the 2D models in Vadose/w software were performed to observe the
effects of abnormal moisture sources on soil moisture changes. A cover slab was
modelled with adjacent soils dipping towards it. The sloping ground creates runoff
towards the slab edge and increases the water available for infiltration. This model
(2DVB4_S) was analysed for 1945 to 2012 and then compared with the control model
(2DVB1). The predictions indicated that the sloping ground significantly increased the
soil moisture at the edge of the slab. In fact, during the wet period in 2010 and 2011, the
characteristic suction at the slab edge was 0.45 pF lower in the sloping ground case
compared to the control model.
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8. CONCLUSIONS AND FUTURE WORK
8.1 OVERVIEW OF THE STUDY
Prior investigations have suggested that the Victorian climate has changed over the last
few decades. In addition, back-to-back extreme climate events were observed in the
recent past and more of these events are expected in the future. These changes affect the
soil moisture conditions and have a severe impact on volume changes in expansive
soils. Recent media reports and anecdotal evidence suggest that a large number of
houses were damaged as a result of footing movements which may have been caused by
climate related soil moisture changes. Hence, it is timely that the consideration of
climate influence and the procedure of estimating ground movement in the standard of
residential footing design are reviewed.
The procedure outlined in the AS2870 for calculating characteristic ground movement
was investigated, with a particular emphasis on climate influences. A field site was
established to monitor the expansive soil behaviour. A site in Braybrook, which is in the
Western suburbs of Melbourne, was selected for field monitoring. Braybrook has a
consistent profile of extremely reactive basaltic clays. The purpose of the field site was
to collect a comprehensive dataset of soil properties and monitor soil moisture changes
and the subsequent ground movement over several seasons. A one dimensional finite
element model using Vadose/w software was developed to investigate the soil moisture
changes in response to climate conditions. The finite element model was based on the
measured expansive soil properties of Braybrook site and the climate data collected
from a nearby weather station to define boundary condition of the model. The model
was validated against the soil moisture data collected from the Braybrook site
monitoring. The model was then extended to a two dimensional model to observe the
moisture changes in soil beneath cover slabs due to climate influences on adjacent open
ground. These models were used to analyse the soil moisture changes due to long-term
climate conditions including recent extreme events. Furthermore, the soil moisture
changes in response to various climate scenarios were examined. The soil moisture
predictions were used as the input to another model developed by another researcher
using FLAC3D as a part of this comprehensive research study. The FLAC3D model
was developed to predict the ground movements due to the changes in soil moisture
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conditions. The development of the FLAC3D model is out of the scope of this PhD
thesis however, the soil moisture and ground movement predictions are discussed in this
thesis. The model predictions of moisture and suction changes and ground movements
due to different climate conditions were compared with the estimations based on the
AS2870 method.
8.2 SUMMARY OF CONCLUSIONS
8.2.1 Ground movement, climate changes and TMI
The estimation of ground movement in footing design is dependent on factors affecting
the volume change behaviour of expansive soils, such as degree of reactivity of the soil
and amount of moisture change. The moisture changes in soil are created by several
sources including climate condition and manmade causes.
The method of estimating ground movement in the AS2870 provides a simplified
approach to obtain ys value of an undeveloped site for the purpose of site classification.
This method uses Iss to account for the degree of reactivity of soils. AS2870 considers
soil moisture changes by means of idealized suction profile which is defined using ∆U
and Hs. The standard procedure allows for correlation of Hs with the climate condition
of the area using the TMI. The depth of bedrock and water table affect the Hs. The
Standard provides a single ΔU value (1.2 pF) for all parts of Australia, irrespective of
the climate or site condition.
There are certain weaknesses in AS2870 in estimating ground movement one of which
is the lack of definition of the basis of TMI assumed in the Standard. Several methods
are available to calculate the TMI and each method can produce different values. Four
methods for calculating TMI were presented in Chapter 3 and their results compared,
Since each TMI calculation method produces different values, the correlation between
TMI and Hs generates different values for the same climate condition. This can result in
different footing designs. It was found that the method noted as “Method 1” produces
the closest results to those in AS2870.
In addition, the use of different averaging periods for TMI also produces different
values. Specifically, the more years used in the average calculation, the lesser the
sensitivity to isolated extreme weather events, such as droughts. The long-term average
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TMI is appropriate to reflect long-term trends. However, for the residential footing
design, this averaging period must be considered together with more soil specific
parameters. Furthermore, it was found that the TMI largely depends on rainfall and,
hence, linear correlations were observed between annual rainfall and TMI variations in
most of cities in Victoria. The influence of the other climate components, such as
evaporation and relative humidity are not critical in determining soil moisture changes.
Furthermore, the climate zone map given in the Standard was developed based on
climate data from 1940-1960. However, in Australia, there has been a change in the
climate over the last few decades. The TMI trend of the last 50 years is clearly showing
the ongoing drying. If the same trend continues, it means that the TMI will also reduce.
The drying trend is forecasted by climate models such as that by CSIRO. Irrespective of
the TMI calculation method, it appears that there is an ongoing drying in the Victorian
climate. The modifications to AS2870 in the 2011 edition captured the changes of TMI
due to the drying effect experienced in the last 25 years. However, this may not be
sufficient to capture ongoing changes predicted for the future. Moreover, the values of
Hs and ΔU have not been updated in the Standard to reflect the recent changes and
possible future changes.
The findings presented in Chapter 3 also highlight an issue in estimating the degree of
reactivity of soil in terms of Iss. The shrink swell test, which is used to determine Iss, is
recommended in AS2870 to assess soil reactivity. The corresponding standard of the
test (AS1289) specifies Iss as a constant for a given soil type. In this research, soils
collected from different sites at different times of the year were tested and a number of
Iss values were obtained for the same soil. The results indicated that the Iss increases
with increasing in situ moisture. Even though the experimental data is limited, this
suggests the dependency of Iss on in situ moisture content, which is in contrast to the
assumptions outlined in the AS1289.7.1.1. Specifically, it can result in different footing
designs for a particular site, when the soils are tested at different times of the year.
Hence, Iss values should be reported with the initial moisture content of the soil and the
results considered in relation to the site climatic conditions.
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8.2.2 Characterization of typical basaltic clay in Western Melbourne
As part of the research study described in this thesis, a field site was established to
collect the required data related to expansive soils in Melbourne. A comprehensive data
set was developed for the typical basaltic clay soils as found in Braybrook, located in
West Melbourne.
The data set consists of basic soil properties and some specific expansive soil
parameters. The basic properties include Atterberg limits, linear shrinkage, specific
gravity and clay content. The plastic limit of Braybrook clay varies from 20 to 25 %
while the liquid limit varies from 70 to 80%. Based on these results, the Braybrook soil
was categorised as CH type in the Unified soil classification. The linear shrinkage
varies by approximately 20% and the clay content of soils below 0.5 m is about 45%.
The clay content of the surface layer is less than that of deep soils, which reflects the
presence of silts and organic matter in the top soil. All of these properties are consistent
in the soils below the surface layer. The bedrock was not encountered in the Braybrook
site, even though the boreholes were cored down to 4.5 m.
In addition to the basic soil properties, some specific properties were investigated to
classify the site and examine the behaviour of expansive soils. The shrink swell index
was calculated to vary from 4 to 6% and, based on this index, the Braybrook was
classified as an extremely reactive site. However, X-Ray Diffraction tests revealed that
there was more than 50% of Quartz in the mineral composition of Braybrook clay.
However, Braybrook soils have less than 10% of sand. Hence, this Quartz content could
represent fine sediments, which have clay size and silt size minerals. Importantly, there
is more than 30% of Montmorillonite in the mineral composition in Braybrook clay,
which is the primary cause of the expansiveness.
In addition to the clay mineralogy, the hydraulic conductivity and SWCC functions
were developed for Braybrook soils to use in the prediction models. Matric suction and
volumetric moisture contents were employed which provided the coordinates of the
SWCC. Hyprop, WP4C and filter papers were used to measure the suctions values at
different moisture levels. Osmotic suction obtained from the filter paper method was
used to convert total suctions into matric suction measured from WP4C. A correlation
was developed between volumetric and gravimetric moisture contents of Braybrook
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soils. This correlation was used to obtain volumetric moistures from measured
gravimetric moistures corresponding to WP4C and filter paper suctions. Since the
Braybrook site has a constant soil profile throughout the depth, the SWCC functions are
assumed to be similar in deep soils. However, the presence of organic matter caused a
different SWCC for the surface soils.
The saturated hydraulic conductivity of surface soils was found in the range of 10-7 m/s.
The hydraulic conductivities were reduced in deeper soils due to a higher clay content
and density. The saturated hydraulic conductivities of deeper soils were in the range of
10-9 m/s. Hydraulic conductivity functions of unsaturated soils were developed using
these values and SWCCs.
This unique data set is beneficial for both practitioners and researchers. It provides the
characteristics of typical basaltic clay found in West Melbourne, which are useful in site
classification and modelling.
8.2.3 Field monitoring of expansive soil behaviour
The field monitoring of a typical expansive soil site was performed in this study to
collect the data required to calibrate and validate the prediction models. The soil
moisture changes were monitored using neutron probe technique and the corresponding
ground movements were monitored using magnetic extensometers. Paving blocks were
placed at several locations to monitor the ground movement using a surveying level.
The neutron probe reads the number of neutrons that react with soil moisture during
measurements. Therefore, in this study, a calibration equation was developed between
neutron counts and volumetric moisture content. The calibration equation, which has
0.86 coefficient of determination, provides the corresponding volumetric moisture
content to the neutron count measurements. The field monitoring continued regularly
from April 10th, 2013 to March 25th, 2015. Seasonal moisture variations were observed
at three locations over the two-year period. All three locations showed similar moisture
profiles at deeper depths. However, there were some differences in near surface
measurements possibly due to local effects such as slope differences, potholes and grass
cover changes. The soil moisture changes were observed up to 1.25 m over the
monitoring period. The most significant changes were observed in the top 0.75 m soils.
Moisture contents of near surface soils followed the rainfall pattern with a certain time
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lag. The seasonal heave and settlements were observed in three magmatic extensometers
located next to the neutron probe access tubes. Similar to the moisture changes, most of
the movements occurred in the top soil layers. The maximum seasonal ground
movement was in the range of 40-50 mm.
8.2.4 Finite element modelling approach of expansive soil and climate
interaction
The expansive soil properties and the data collected from regular monitoring were used
to develop finite element model using Vadose/w to predict soil moisture changes due to
climate conditions. The model requires specifying SWCC, hydraulic conductivity,
thermal conductivity and the specific heat capacity of the soil. The thermal properties
had a minimal impact on soil moisture changes, as suggested by sensitivity analysis.
Therefore, thermal conductivity and specific heat capacity were obtained from a site
close to Braybrook described in the literature. The soil properties were defined to a
depth of 6 m deep soil column to represent the soil profile. The climate boundary was
specified at the top surface and it includes daily inputs of rainfall, evaporation, relative
humidity, wind and temperature. These climate components were collected from
Essendon airport - a weather station close to the Braybrook site. The no-flow boundary
was defined at the bottom to simulate the effect of bedrock.
This model was analysed for the two-year period of field monitoring from 2013 to 2015.
The model predicts soil moisture and suction profiles as daily outputs. These predictions
were compared with the neutron moisture measurements. The results showed a good
agreement between soil moisture predictions and field measurements and hence the
model was considered as validated.
In order to study the soil moisture beneath a flexible cover, the 1D model was extended
to a 2D model. The observations of homogeneous soil in Braybrook soil suggest that the
lateral hydraulic conductivity, which is the only additional parameter required in the 2D
model, is similar to the hydraulic conductivity in the vertical direction. The results at
open area exposed to climate effects in the 2D model showed same moisture changes as
1D model for the period of field monitoring. However, the results of mound shapes
obtained from 2D models depend on the assumptions of lateral hydraulic conductivity.
The sensitivity analysis of the input parameters revealed that soil moisture changes are
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mostly affected by the SWCC of soils followed by the hydraulic conductivity. A 20%
change in SWCC and hydraulic conductivity resulted in 22% and 2% change in soil
moisture, respectively, at 0.3 m below the surface. Rainfall is the most critical climate
component in changing soil moistures. The responses of the models to vegetation
effects and pooling situations were also considered. Grass covers prevent the
evaporation and increase the water available for the infiltration. Therefore, both grass
covers and pooling effects significantly increase the soil moisture.
The effect of cracks was not included in these models. The presence of cracks can
significantly change the moisture content of soils even at deeper depths. The cracks
allow rainwater to infiltrate and hence increase the moisture content of deep soils.
Therefore, in actual conditions during the rainy days of summer, the moisture may
increase abruptly. This is not captured in the models described in this thesis.
8.2.5 Prediction of ground movement due to several site conditions and
climate scenarios
The finite element models were used to investigate the soil moisture, suction and
ground movement due to long term climate conditions. In addition to the Braybrook
site, Fawkner - another reactive soil site in Melbourne - was considered. Fawkner has a
shallower soil profile and less reactive soils compared to Braybrook. The long-term
climate data taken from Essendon airport weather station were considered in the
analyses as Braybrook and Fawkner sites are close to each other. The model results
were considered for a period starting 50 years before the severe millennium drought.
The total period was divided in three based on the millennium drought; pre drought
(1945-1995), millennium drought (1996-2010) and the wet period after the drought
(2011-2012).
The predictions of the models developed in Vadose/w software were used to obtain ΔU
and Hs values in different periods. The corresponding ground movements were
calculated using the AS2870 method. In addition, the model results were fed into a one-
dimensional soil column developed in FLAC-3D software to predict ground movement.
The predictions suggest that during 1945-1995, ΔU and Hs of Braybrook were 1.3 pF
and 3.0 m, respectively. Deep-seated moisture change was observed in Braybrook
because of the deeper soil profile. The 1D model was modified to determine these
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parameters if Braybrook had a shallower soil profile with bedrock at 3 m, which is the
general condition of basaltic soil sites in West Melbourne. However, the modified
model results suggested only a small reduction of Hs (2.7 m). ΔU appears to be a
dependent on climate conditions and properties of top soils.
Even though the climate conditions are the same in both Fawkner and Braybrook, the
Fawkner site had ΔU of 1.5 pF and Hs of 1.8m during 1945-1995. This is due to the
shallower soil profile in Fawkner. Further, the hydraulic conductivities of Fawkner soils
below the top layer are lower compared to Braybrook. Therefore, moisture flow is
restricted through deeper soils, which creates higher fluctuations in top soils and hence
higher ∆U.
Both Braybrook and Fawkner sites showed an additional increase of ΔU of 0.2 pF at the
end of the millennium drought that resulted in additional ground movement. The FLAC
model showed that the millennium drought produced the greatest ground movement
(settlement) during the past 70 years. In fact, the model results suggest that the
millennium drought created a 15-20% increase in the ground movement compared to
the pre-drought period. AS2870 provides a method to calculate ys for an undeveloped
site experiencing normal climate condition. Therefore, isolated extreme climate
conditions may not be captured in the AS2870 approach. Consequently, the impact of
the millennium drought would not have been captured in its estimation of the surface
movement, which depends on average TMI over a long period. However, when the TMI
was calculated in 25 year blocks instead of 50 year period, the impact of the drought
was reflected in the calculated ground movements.
A surface runoff correction of 60% (typical value for urban residential area) was used in
the prediction models. However, the effect of different site drainage condition on soil
moisture and ground movement was also investigated. A lower surface runoff results in
more water available for infiltration. Hence, poor drainage condition will create higher
ground movements. Compared to the 60% runoff correction considered, 30% and zero
runoff corrections will increase the maximum observed ground movement by 20 and
45% respectively.
Further, the validated model was used to determine the ground movement due to future
climate scenarios. In this case, 4 years of wet and dry climate conditions were
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artificially forecasted for the period 2015-2018 using past climate data. These climate
data sets were used to analyse the 1D model from 1945 to 2018. The model results in
both Braybrook and Fawkner suggested that the ongoing settling trend would terminate
and the ground will reach a similar condition to that experienced in 2011. However, 4
years of wet climate condition is not sufficient to allow the grounds to completely
recover from the moisture deficit caused by millennium drought. However, in actual
condition, cracks allow rainwater to move deep into the soil, and accelerate the wetting
process. Therefore, in actual condition, a further recovery could have been observed by
such four years of above average rainfall.
Long-term climate predictions were also considered using the 1D models. A set of
climate data representing typical average climate condition was considered. It was
modified to integrate the ongoing drying trend reported by climate predictions
(Austroads, 2004). Models predictions suggest that both Braybrook and Fawkner soils
would experience a moisture deficit due to ongoing drying compared to the typical
average condition. At the end of 50 year period, Braybrook would experience an
additional 12 mm settlement whereas Fawkner would experience half of that.
The 2D model developed in Vadose/w software was used to determine the soil moisture
changes in the lateral direction. A perfectly flexible cover was introduced in the 2D
model to investigate the soil moisture changes beneath the cover due to climate
influences on an adjacent open area. The 2D model was used to determine the changes
in soil mound shapes beneath a flexible cover. To observe the highest edge heave and
edge settlement conditions, two periods of the worst wet and dry climate condition were
identified;1983-1992 and 1992-2010, respectively. Then, two different models were
analysed for climate conditions in these periods. The soil moisture predictions were
used in the FLAC model to determine the ground movement at several discrete
locations measured from the axis of symmetry. The ys values were also calculated based
on the AS2870 method using characteristic suction profiles at these discrete locations.
Considering mound profiles in both edge heave and edge settlement conditions, the
calculations based on AS2870 method are in strong agreement with the FLAC model
predictions. The model results suggest that this approach is effective in predicting
mound shapes for slabs placed at different times (i.e., slabs constructed during wet or
dry periods).
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Additional analyses using the 2D models were performed to observe the effects of
abnormal moisture sources on soil moisture changes. The condition of a cover slab with
adjacent surface slope towards it was modelled. The sloping ground creates a runoff
towards the slab edge and increases the water available for infiltration. The predictions
indicated that this case resulted in a significantly wet condition in soils at the edge of
the slab. In fact, during the wet period in 2010 and 2011, the characteristic suction at the
slab edge is 0.45 pF lower in sloping ground case compared to the control model with
no slopes. .
In conclusion, the models developed in this study provide a comprehensive and versatile
approach to investigate soil moisture and ground movement due to different climate and
manmade conditions. They can be used not only to obtain ΔU and Hs but also to
determine variation in ground movement and mound shapes. Consequently, correlations
of the ground movement induced by various climate scenarios can be established using
further investigations of different soil types. These models will therefore greatly assist
the development of design tools for the footings of light structures.
8.3 RECOMMENDATIONS FOR FUTURE WORK
Even though, the research described in this thesis is a part of a comprehensive group
research programme, there were some limitations in the study, which opens various
paths for future research.
The models developed in this study were validated only for the Braybrook site for a
period of 2 years. However, more analysis is required, including different sites with
various soils and site conditions. Further analysis is essential for the provision of
generalized conclusions in expansive soil behaviour in response to the changes in
climate conditions.
The Vadose/w model developed in this study considers a crack free soil profile.
However, most of the clay soils experience cracking during dry weather conditions. In
fact, there were more than 1 m deep cracks observed in Braybrook site during the
summer. This condition can result in sudden increments of the moisture contents at deep
soils due to infiltration of runoff water through the cracks. It can affect the depth of soil
moisture change. Moreover, the cracks can reduce the vertical soil movement due to
272
availability of space to volume changes in the lateral direction. The cracking of soils
depends on various factors, including the climate, soil type and the local effects. Hence
it is difficult to generalize the way of crack propagation. However, since the cracks can
impact Hs and ys values, adopting the cracking behaviour in models could be effective
in designing residential structures on expansive soils.
In addition, the differential equations used in the Vadose/w model are limited only for
the “No snow” condition in climate. Hence, modifications must be employed
accordingly to use this model in analysing soil moisture changes in alpine areas.
Furthermore, the Vadose/w model only considers the effect of vegetation in terms of
grass cover. In most cases, grass covers reduce the amount of solar radiation available
on soil surface. This reduces the evaporation resulting in an increment in soil moisture.
Importantly, the effect of tree roots is different from grass covers. Tree roots absorb
moisture from deep soils and reduce the soil moistures. Therefore, the soil experiences
additional deficits and settlement due to trees. This phenomenon has been a common
cause for differential settlements in houses with trees in the influential zone. The
influence of trees must be considered in reference to a structure which is affected by
various factors, including the soil type, distance from the structure, type of tree canopy
and distribution of roots. The model developed in this study can be extended in future
research to include the influence of trees.
In addition to the potential advancements in the Vadose/w model, the development of
the 2D FLAC model is also an area for future research. The development of the 2D
FLAC modal began as part of this comprehensive research program but is yet to be
finalized. The 2D FLAC model overcomes the issues of neglecting shear effects of
adjacent soils in the 1D FLAC model when estimating ground movement profiles. The
2D FLAC model will predict the ground movement underneath cover slabs and,
therefore, will be highly useful in estimating mound shapes of slabs placed at different
times and exposed to different climate scenarios.
Apart from the possible upgrades to the models, the results of the model described in
this thesis can be utilized into a standard procedure. Since this model can produce soil
moisture and ground movement due to different climate conditions, they can be
categorized into a rationalized form. For example, the climate conditions could be
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classified based on the severity of the extreme events and the prediction scenarios. The
severities can be categorized based on return periods. Then, the influence of those
climate events on footing design parameters can be specified for use in design
guidelines, for example changes in ΔU, Hs and ys based on the severity of extreme
events. This will allow footing designers to obtain relevant parameters based on the
expectable climate conditions, quality and financial feasibility of the construction rather
than depending solely on the past climate conditions. For, example; if a home owner
desires a house which can withstand severe climate events, the model can be employed
to obtain ground movements for climate conditions with appropriate extreme events.
However, such designs may require higher construction cost. Moreover, such a
procedure requires model predictions from a number of expansive soil sites.
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A_1
10. APPENDICES
A: HYPROP MEASUREMENTS OF BRAYBROOK SOIL
Depth 0 – 0.3 meters
HYPROP TEST RESULTS SHEET
SITE: Braybrook DEPTH: 0-0.3 m
SAMPLE DATE : 1/05/2014 TEST DATE : 23/09/2014
INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 371.5 g
Hyprop data corrected data
Matric Suction
(pF)
Moisture content
from Hyprop
(%)
Water volume (cm3)
Gravimetric moisture
content (%)
Matric Suction
(kPa)
Corrected Volumetric moisture content
1.14 52.51 130.75 35.19 1.38 0.5012 1.16 52.50 130.72 35.18 1.44 0.5011 1.21 52.48 130.68 35.17 1.63 0.5010 1.22 52.51 130.75 35.19 1.67 0.5012 1.28 52.47 130.65 35.16 1.91 0.5009 1.33 52.44 130.58 35.15 2.16 0.5007 1.38 52.41 130.51 35.13 2.40 0.5006 1.43 52.37 130.41 35.10 2.71 0.5003 1.48 52.33 130.31 35.07 3.02 0.5001 1.51 52.29 130.20 35.04 3.21 0.4998 1.53 52.25 130.10 35.02 3.36 0.4995 1.54 52.20 129.97 34.98 3.50 0.4992 1.56 52.13 129.79 34.93 3.65 0.4988 1.58 52.06 129.62 34.89 3.81 0.4983 1.60 52.02 129.52 34.86 4.01 0.4981 1.63 51.98 129.42 34.83 4.24 0.4978 1.65 51.93 129.32 34.81 4.43 0.4976 1.66 51.89 129.21 34.78 4.59 0.4973 1.68 51.84 129.08 34.74 4.79 0.4969 1.70 51.80 128.98 34.71 4.98 0.4967 1.71 51.76 128.87 34.69 5.14 0.4964 1.73 51.70 128.74 34.65 5.33 0.4961 1.73 51.21 127.51 34.32 5.37 0.4929 1.75 51.66 128.64 34.62 5.56 0.4958 1.75 51.13 127.31 34.27 5.58 0.4924 1.77 51.59 128.47 34.58 5.82 0.4954 1.77 51.05 127.11 34.21 5.89 0.4919
A_2
1.78 51.29 127.72 34.38 6.01 0.4935 1.79 51.52 128.30 34.53 6.14 0.4950 1.80 50.95 126.87 34.15 6.27 0.4913 1.80 50.86 126.63 34.08 6.37 0.4907 1.81 51.44 128.09 34.48 6.47 0.4944 1.82 50.76 126.40 34.02 6.56 0.4901 1.83 51.37 127.92 34.43 6.73 0.4940 1.85 50.67 126.16 33.96 7.00 0.4894 1.86 50.57 125.92 33.89 7.24 0.4888 1.88 50.46 125.65 33.82 7.50 0.4881 1.89 50.35 125.38 33.75 7.69 0.4874 1.90 50.26 125.15 33.68 7.93 0.4868 1.91 50.17 124.91 33.62 8.15 0.4862 1.92 50.06 124.64 33.55 8.39 0.4855 1.93 49.95 124.37 33.48 8.61 0.4848 1.95 49.85 124.14 33.41 8.85 0.4841 1.96 49.75 123.87 33.34 9.10 0.4834 1.97 49.64 123.60 33.27 9.33 0.4827 1.98 49.53 123.33 33.20 9.57 0.4820 1.99 49.42 123.07 33.12 9.84 0.4813 2.01 49.30 122.76 33.04 10.12 0.4805 2.02 49.20 122.50 32.97 10.40 0.4798 2.03 49.07 122.20 32.89 10.69 0.4790 2.04 48.95 121.90 32.81 10.94 0.4782 2.05 48.83 121.60 32.73 11.22 0.4774 2.05 48.58 120.96 32.56 11.30 0.4757 2.06 48.71 121.30 32.65 11.40 0.4766 2.06 48.46 120.66 32.48 11.48 0.4748 2.08 48.34 120.36 32.40 12.08 0.4740 2.10 48.21 120.03 32.31 12.59 0.4731 2.12 48.06 119.67 32.21 13.06 0.4721 2.12 47.94 119.37 32.13 13.12 0.4713 2.13 47.81 119.04 32.04 13.46 0.4704 2.14 47.24 117.62 31.66 13.74 0.4665 2.15 47.66 118.67 31.94 14.19 0.4694 2.15 47.38 117.98 31.75 14.26 0.4675 2.16 47.51 118.31 31.84 14.45 0.4684 2.17 47.09 117.26 31.56 14.76 0.4655 2.22 46.95 116.90 31.46 16.71 0.4645 2.24 46.81 116.57 31.37 17.54 0.4636 2.26 46.67 116.21 31.28 18.24 0.4626 2.28 46.52 115.85 31.18 18.88 0.4615 2.29 46.37 115.45 31.07 19.50 0.4604 2.30 46.24 115.13 30.99 20.14 0.4595 2.32 46.09 114.77 30.89 20.70 0.4585 2.33 45.93 114.38 30.78 21.33 0.4574 2.33 45.78 113.98 30.68 21.63 0.4563 2.35 45.63 113.63 30.58 22.23 0.4553 2.37 45.48 113.24 30.48 23.28 0.4541 2.38 45.32 112.85 30.37 24.10 0.4530 2.40 45.18 112.49 30.28 24.95 0.4520
A_3
2.41 45.02 112.10 30.17 25.70 0.4509 2.42 44.85 111.68 30.06 26.49 0.4497 2.44 44.68 111.26 29.95 27.29 0.4485 2.45 44.51 110.84 29.83 28.12 0.4472 2.46 44.33 110.39 29.71 28.97 0.4459 2.48 44.15 109.94 29.59 29.92 0.4446 2.49 43.98 109.52 29.48 30.83 0.4434 2.50 43.80 109.07 29.36 31.77 0.4421 2.52 43.62 108.62 29.24 32.81 0.4407 2.53 43.46 108.21 29.12 33.81 0.4395 2.54 43.30 107.83 29.02 34.91 0.4384 2.56 43.14 107.41 28.91 36.06 0.4371 2.57 42.98 107.03 28.81 37.15 0.4360 2.58 42.82 106.61 28.70 38.28 0.4348 2.60 42.65 106.20 28.58 39.45 0.4335 2.61 42.47 105.76 28.46 40.74 0.4322 2.62 42.29 105.31 28.35 41.98 0.4308 2.64 42.12 104.87 28.23 43.35 0.4295 2.65 41.94 104.43 28.11 44.77 0.4282 2.67 41.77 104.02 28.00 46.34 0.4269 2.68 41.60 103.58 27.88 47.86 0.4256 2.69 41.42 103.14 27.76 49.55 0.4242
Depth 0.3 – 0.8 meters
HYPROP TEST RESULTS SHEET
SITE: Braybrook DEPTH: 0.5 m
SAMPLE DATE : 1/05/2014 TEST DATE : 19/05/2014
INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 349.2 g
Hyprop data Corrected data
Matric Suction
(pF)
Moisture content
from Hyprop
(%)
Water volume (cm3)
Gravimetric moisture
content (%)
Matric Suction
(kPa)
Corrected Volumetric moisture content
0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147
A_4
0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 0.25 51.44 128.09 36.68 0.18 0.5147 1.82 51.43 128.06 36.67 6.64 0.5147 1.80 51.41 128.01 36.66 6.35 0.5145 1.76 51.39 127.96 36.64 5.70 0.5144 1.68 51.37 127.91 36.63 4.73 0.5143 1.51 51.36 127.89 36.62 3.25 0.5142 0.25 51.44 128.09 36.68 0.18 0.5147 1.50 51.31 127.76 36.59 3.14 0.5139 1.68 51.28 127.69 36.57 4.80 0.5137 1.78 51.26 127.64 36.55 5.96 0.5136 1.84 51.24 127.59 36.54 6.93 0.5134 1.89 51.20 127.49 36.51 7.78 0.5132 1.93 51.17 127.41 36.49 8.57 0.5130 1.97 51.14 127.34 36.47 9.29 0.5128 2.00 51.11 127.26 36.44 9.98 0.5126 2.03 51.07 127.16 36.42 10.67 0.5124 2.05 51.03 127.06 36.39 11.27 0.5121 2.07 51.00 126.99 36.37 11.86 0.5119 2.10 50.96 126.89 36.34 12.45 0.5117 2.12 50.93 126.82 36.32 13.12 0.5115 2.14 50.88 126.69 36.28 13.84 0.5111 2.16 50.83 126.57 36.24 14.35 0.5108 2.17 50.79 126.47 36.22 14.76 0.5106 2.18 50.75 126.37 36.19 15.21 0.5103 2.20 50.70 126.24 36.15 15.74 0.5100 2.21 50.65 126.12 36.12 16.14 0.5097 2.22 50.60 125.99 36.08 16.52 0.5093 2.23 50.55 125.87 36.05 16.94 0.5090 2.24 50.49 125.72 36.00 17.30 0.5086 2.25 50.43 125.57 35.96 17.66 0.5082 2.25 50.38 125.45 35.92 17.95 0.5079 2.26 50.32 125.30 35.88 18.20 0.5075 2.27 50.26 125.15 35.84 18.54 0.5071 2.28 50.21 125.02 35.80 18.97 0.5068 2.29 50.14 124.85 35.75 19.45 0.5064 2.30 50.08 124.70 35.71 19.91 0.5060 2.31 50.01 124.52 35.66 20.37 0.5055 2.32 49.95 124.38 35.62 20.80 0.5051 2.33 49.88 124.20 35.57 21.23 0.5046 2.34 49.81 124.03 35.52 21.68 0.5042 2.34 49.74 123.85 35.47 22.08 0.5037 2.35 49.66 123.65 35.41 22.54 0.5032 2.36 49.60 123.50 35.37 22.96 0.5028 2.37 49.53 123.33 35.32 23.44 0.5023 2.38 49.45 123.13 35.26 23.88 0.5018
A_5
2.39 49.37 122.93 35.20 24.38 0.5013 2.40 49.30 122.76 35.15 24.89 0.5008 2.40 49.22 122.56 35.10 25.35 0.5003 2.41 49.15 122.38 35.05 25.82 0.4998 2.42 49.07 122.18 34.99 26.24 0.4993 2.43 48.98 121.96 34.93 26.73 0.4987 2.43 48.90 121.76 34.87 27.16 0.4981 2.44 48.82 121.56 34.81 27.67 0.4976 2.45 48.74 121.36 34.75 28.18 0.4971 2.46 48.65 121.14 34.69 28.64 0.4965 2.47 48.57 120.94 34.63 29.17 0.4959 2.47 48.48 120.72 34.57 29.65 0.4953 2.48 48.39 120.49 34.50 30.20 0.4947 2.49 48.30 120.27 34.44 30.69 0.4941 2.50 48.20 120.02 34.37 31.26 0.4934 2.50 48.12 119.82 34.31 31.70 0.4929 2.51 48.03 119.59 34.25 32.21 0.4923 2.52 47.93 119.35 34.18 32.73 0.4916 2.52 47.85 119.15 34.12 33.19 0.4910 2.53 47.75 118.90 34.05 33.73 0.4903 2.54 47.66 118.67 33.98 34.36 0.4897 2.54 47.57 118.45 33.92 34.99 0.4891 2.55 47.47 118.20 33.85 35.73 0.4884 2.56 47.37 117.95 33.78 36.39 0.4877 2.57 47.27 117.70 33.71 37.07 0.4870 2.58 47.17 117.45 33.63 37.84 0.4863 2.59 47.07 117.20 33.56 38.55 0.4856 2.59 46.97 116.96 33.49 39.26 0.4849
2.601 46.87 116.71 33.42 39.90 0.4842 2.608 46.77 116.46 33.35 40.55 0.4835 2.616 46.67 116.21 33.28 41.30 0.4828 2.623 46.57 115.96 33.21 41.98 0.4821 2.631 46.48 115.74 33.14 42.76 0.4815 2.642 46.38 115.49 33.07 43.85 0.4808 2.654 46.28 115.24 33.00 45.08 0.4801 2.665 46.18 114.99 32.93 46.24 0.4794 2.676 46.08 114.74 32.86 47.42 0.4787 2.688 45.98 114.49 32.79 48.75 0.4780 2.701 45.88 114.24 32.72 50.23 0.4772 2.713 45.77 113.97 32.64 51.64 0.4765 2.725 45.67 113.72 32.57 53.09 0.4757 2.738 45.56 113.44 32.49 54.70 0.4750
A_6
Depth 0.8 – 1.3 meters
HYPROP TEST RESULTS SHEET
SITE: Braybrook DEPTH: 1.0 m
SAMPLE DATE : 1/05/2014 TEST DATE : 19/05/2014
INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 345.9 g
Hyprop data Corrected data
Matric Suction
(pF)
Moisture content
from Hyprop
(%)
Water volume (cm3)
Gravimetric moisture
content (%)
Matric Suction
(kPa)
Corrected Volumetric moisture content
1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.56 52.96 131.87 38.12 3.64 0.5273 1.77 52.91 131.75 38.09 5.82 0.5270 1.92 52.89 131.70 38.07 8.24 0.5268 2.00 52.87 131.65 38.06 10.07 0.5267 2.06 52.85 131.60 38.04 11.53 0.5266 2.10 52.83 131.55 38.03 12.47 0.5265 2.12 52.80 131.47 38.01 13.15 0.5263 2.14 52.78 131.42 37.99 13.71 0.5262 2.15 52.75 131.35 37.97 14.16 0.5260 2.16 52.72 131.27 37.95 14.52 0.5258 2.17 52.69 131.20 37.93 14.89 0.5256 2.18 52.66 131.12 37.91 15.21 0.5254 2.19 52.63 131.05 37.89 15.42 0.5253 2.19 52.59 130.95 37.86 15.35 0.5250 2.18 52.55 130.85 37.83 15.24 0.5248 2.19 52.51 130.75 37.80 15.35 0.5245 2.19 52.48 130.68 37.78 15.49 0.5243 2.20 52.43 130.55 37.74 15.67 0.5240 2.20 52.38 130.43 37.71 15.92 0.5237 2.21 52.35 130.35 37.68 16.26 0.5235 2.22 52.30 130.23 37.65 16.60 0.5232 2.23 52.24 130.08 37.61 16.83 0.5228 2.23 52.19 129.95 37.57 17.14 0.5225
A_7
2.24 52.14 129.83 37.53 17.50 0.5222 2.25 52.09 129.70 37.50 17.86 0.5219 2.27 52.04 129.58 37.46 18.54 0.5216 2.29 51.98 129.43 37.42 19.28 0.5212 2.30 51.92 129.28 37.38 19.86 0.5208 2.31 51.87 129.16 37.34 20.28 0.5205 2.31 51.81 129.01 37.30 20.61 0.5202 2.32 51.73 128.81 37.24 20.94 0.5196 2.33 51.67 128.66 37.20 21.28 0.5193 2.33 51.61 128.51 37.15 21.53 0.5189 2.34 51.55 128.36 37.11 21.88 0.5185 2.35 51.48 128.19 37.06 22.18 0.5181 2.35 51.41 128.01 37.01 22.44 0.5176 2.36 51.33 127.81 36.95 22.86 0.5171 2.37 51.27 127.66 36.91 23.23 0.5167 2.37 51.19 127.46 36.85 23.55 0.5162 2.38 51.11 127.26 36.79 23.93 0.5157 2.39 51.04 127.09 36.74 24.38 0.5153 2.40 50.96 126.89 36.68 24.89 0.5148 2.40 50.89 126.72 36.63 25.35 0.5143 2.41 50.81 126.52 36.58 25.88 0.5138 2.42 50.73 126.32 36.52 26.42 0.5133 2.43 50.65 126.12 36.46 26.98 0.5128 2.44 50.56 125.89 36.40 27.54 0.5122 2.45 50.48 125.70 36.34 28.12 0.5117 2.46 50.40 125.50 36.28 28.58 0.5112 2.46 50.31 125.27 36.22 28.51 0.5106 2.45 50.22 125.05 36.15 27.99 0.5100 2.45 50.13 124.82 36.09 27.93 0.5094 2.45 50.04 124.60 36.02 28.05 0.5088 2.45 49.94 124.35 35.95 28.38 0.5082 2.46 49.84 124.10 35.88 29.04 0.5075 2.47 49.74 123.85 35.81 29.72 0.5068 2.48 49.64 123.60 35.73 30.41 0.5062 2.49 49.54 123.35 35.66 31.12 0.5055 2.50 49.45 123.13 35.60 31.84 0.5049 2.52 49.35 122.88 35.53 32.73 0.5043 2.52 49.25 122.63 35.45 33.42 0.5036 2.53 49.15 122.38 35.38 34.04 0.5029 2.54 49.05 122.13 35.31 34.43 0.5023 2.54 48.95 121.89 35.24 34.83 0.5016 2.55 48.85 121.64 35.17 35.65 0.5009 2.56 48.75 121.39 35.09 36.48 0.5003 2.57 48.65 121.14 35.02 37.33 0.4996 2.58 48.55 120.89 34.95 38.19 0.4989 2.59 48.45 120.64 34.88 39.08 0.4982 2.60 48.34 120.37 34.80 39.90 0.4975 2.61 48.23 120.09 34.72 40.74 0.4967 2.62 48.12 119.82 34.64 41.30 0.4960 2.62 48.01 119.54 34.56 41.21 0.4952 2.62 47.90 119.27 34.48 41.30 0.4945
A_8
2.62 47.80 119.02 34.41 41.88 0.4938 2.63 47.69 118.75 34.33 42.46 0.4930 2.63 47.60 118.52 34.27 42.95 0.4924 2.64 47.51 118.30 34.20 43.55 0.4918
2.648 47.42 118.08 34.14 44.46 0.4912 2.657 47.32 117.83 34.06 45.39 0.4905 2.666 47.23 117.60 34.00 46.34 0.4899 2.677 47.13 117.35 33.93 47.53 0.4892 2.687 47.04 117.13 33.86 48.64 0.4885 2.698 46.95 116.91 33.80 49.89 0.4879 2.708 46.86 116.68 33.73 51.05 0.4873 2.719 46.76 116.43 33.66 52.36 0.4866
2.73 46.67 116.21 33.60 53.70 0.4860 2.742 46.58 115.98 33.53 55.21 0.4853 2.752 46.48 115.74 33.46 56.49 0.4846 2.763 46.39 115.51 33.39 57.94 0.4840 2.774 46.3 115.29 33.33 59.43 0.4833 2.788 46.2 115.04 33.26 61.38 0.4826
Depth 1.3 – 1.8 meters
HYPROP TEST RESULTS SHEET
SITE: Braybrook DEPTH: 1.5 m
SAMPLE DATE : 1/05/2014 TEST DATE : 19/05/2014
INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 346.8 g
Hyprop data Corrected data
Matric Suction
(pF)
Moisture content
from Hyprop
(%)
Water volume (cm3)
Gravimetric moisture
content (%)
Matric Suction
(kPa)
Corrected Volumetric moisture content
1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.09 52.43 130.55 37.64 1.24 0.5232 1.60 52.44 130.58 37.65 3.94 0.5232 1.79 52.42 130.53 37.64 6.17 0.5231 1.89 52.41 130.50 37.63 7.83 0.5230 1.96 52.40 130.48 37.62 9.10 0.5230 2.00 52.39 130.45 37.62 10.09 0.5229 2.04 52.38 130.43 37.61 10.86 0.5229 2.06 52.36 130.38 37.59 11.51 0.5227 2.08 52.35 130.35 37.59 11.99 0.5227
A_9
2.09 52.33 130.30 37.57 12.42 0.5226 2.11 52.31 130.25 37.56 12.79 0.5224 2.12 52.28 130.18 37.54 13.03 0.5222 2.12 52.26 130.13 37.52 13.15 0.5221 2.12 52.23 130.05 37.50 13.27 0.5219 2.13 52.20 129.98 37.48 13.40 0.5217 2.13 52.17 129.90 37.46 13.49 0.5216 2.13 52.14 129.83 37.44 13.61 0.5214 2.14 52.11 129.75 37.41 13.87 0.5212 2.15 52.08 129.68 37.39 14.09 0.5210 2.15 52.05 129.60 37.37 14.26 0.5208 2.16 52.01 129.50 37.34 14.29 0.5206 2.15 51.97 129.41 37.31 14.16 0.5203 2.15 51.94 129.33 37.29 14.06 0.5201 2.15 51.90 129.23 37.26 14.16 0.5199 2.16 51.86 129.13 37.24 14.45 0.5196 2.17 51.82 129.03 37.21 14.89 0.5194 2.19 51.77 128.91 37.17 15.38 0.5191 2.20 51.73 128.81 37.14 15.85 0.5188 2.22 51.68 128.68 37.11 16.41 0.5185 2.23 51.63 128.56 37.07 16.98 0.5182 2.24 51.58 128.43 37.03 17.46 0.5179 2.25 51.53 128.31 37.00 17.91 0.5175 2.26 51.47 128.16 36.96 18.32 0.5172 2.27 51.42 128.04 36.92 18.71 0.5168 2.28 51.36 127.89 36.88 19.14 0.5165 2.29 51.31 127.76 36.84 19.68 0.5161 2.31 51.25 127.61 36.80 20.28 0.5158 2.32 51.18 127.44 36.75 20.84 0.5153 2.33 51.13 127.31 36.71 21.33 0.5150 2.34 51.07 127.16 36.67 21.73 0.5146 2.34 51.00 126.99 36.62 22.03 0.5142 2.35 50.93 126.82 36.57 22.39 0.5137 2.36 50.86 126.64 36.52 22.70 0.5133 2.36 50.79 126.47 36.47 22.96 0.5128 2.37 50.72 126.29 36.42 23.28 0.5124 2.37 50.65 126.12 36.37 23.55 0.5119 2.38 50.57 125.92 36.31 23.88 0.5114 2.38 50.50 125.75 36.26 24.21 0.5109 2.39 50.42 125.55 36.20 24.55 0.5104 2.40 50.34 125.35 36.14 24.89 0.5099 2.40 50.27 125.17 36.09 25.23 0.5095 2.41 50.19 124.97 36.04 25.53 0.5089 2.41 50.11 124.77 35.98 25.88 0.5084 2.42 50.03 124.57 35.92 26.30 0.5079 2.43 49.94 124.35 35.86 26.67 0.5073 2.43 49.86 124.15 35.80 27.16 0.5068 2.44 49.77 123.93 35.73 27.61 0.5062 2.45 49.68 123.70 35.67 27.99 0.5056 2.45 49.60 123.50 35.61 28.44 0.5051 2.46 49.51 123.28 35.55 28.91 0.5045
A_10
2.47 49.43 123.08 35.49 29.38 0.5039 2.48 49.34 122.86 35.43 29.92 0.5033 2.48 49.25 122.63 35.36 30.41 0.5027 2.49 49.16 122.41 35.30 30.97 0.5021 2.50 49.07 122.18 35.23 31.55 0.5015 2.51 48.98 121.96 35.17 32.14 0.5009 2.52 48.90 121.76 35.11 32.73 0.5004 2.52 48.81 121.54 35.05 33.34 0.4998 2.53 48.72 121.31 34.98 34.04 0.4992 2.54 48.63 121.09 34.92 34.75 0.4986 2.55 48.53 120.84 34.84 35.56 0.4979 2.56 48.44 120.62 34.78 36.31 0.4973 2.57 48.34 120.37 34.71 37.15 0.4966 2.58 48.24 120.12 34.64 38.02 0.4960 2.59 48.14 119.87 34.56 38.90 0.4953 2.60 48.03 119.59 34.49 39.90 0.4945 2.61 47.93 119.35 34.41 40.93 0.4938 2.62 47.82 119.07 34.33 41.88 0.4931 2.63 47.73 118.85 34.27 42.85 0.4925 2.64 47.63 118.60 34.20 43.85 0.4918 2.65 47.53 118.35 34.13 44.98 0.4911 2.66 47.43 118.10 34.05 45.81 0.4904 2.67 47.34 117.88 33.99 46.77 0.4898
2.682 47.25 117.65 33.93 48.08 0.4891 2.694 47.15 117.40 33.85 49.43 0.4885 2.706 47.06 117.18 33.79 50.82 0.4878 2.719 46.96 116.93 33.72 52.36 0.4871 2.733 46.86 116.68 33.65 54.08 0.4864 2.746 46.76 116.43 33.57 55.72 0.4857
2.76 46.66 116.18 33.50 57.54 0.4850 2.774 46.56 115.93 33.43 59.43 0.4843 2.788 46.46 115.69 33.36 61.38 0.4836 2.802 46.36 115.44 33.29 63.39 0.4829 2.817 46.25 115.16 33.21 65.61 0.4821 2.832 46.14 114.89 33.13 67.92 0.4814 2.847 46.04 114.64 33.06 70.31 0.4806
A_11
Depth 1.8 – 2.3 meters
HYPROP TEST RESULTS SHEET
SITE: Braybrook DEPTH: 2.0 m
SAMPLE DATE : 1/05/2014 TEST DATE : 27/08/2014
INITIAL VOLUME OF SAMPLE : 249.0 cm3 OVEN DRY WEIGHT OF SAMPLE : 329.9 g
Hyprop data Corrected data
Matric Suction
(pF)
Moisture content
from Hyprop
(%)
Water volume (cm3)
Gravimetric moisture
content (%)
Matric Suction
(kPa)
Corrected Volumetric moisture content
1.47 47.52 118.33 35.86808 2.94 0.5074 1.60 47.51 118.31 35.86 3.94 0.5074 1.89 47.51 118.29 35.86 7.82 0.5073 2.00 47.51 118.29 35.86 9.89 0.5073 2.04 47.50 118.28 35.85 11.07 0.5073 2.07 47.49 118.26 35.85 11.72 0.5072 2.08 47.49 118.24 35.84 12.11 0.5072 2.09 47.48 118.23 35.84 12.42 0.5071 2.10 47.42 118.07 35.79 12.56 0.5067 2.11 47.46 118.17 35.82 12.74 0.5070 2.11 47.47 118.19 35.83 12.76 0.5070 2.12 47.39 118.00 35.77 13.06 0.5065 2.13 47.38 117.97 35.76 13.34 0.5064 2.13 47.36 117.93 35.75 13.58 0.5063 2.14 47.35 117.90 35.74 13.87 0.5062 2.15 47.33 117.85 35.72 14.16 0.5061 2.16 47.31 117.80 35.71 14.42 0.5059 2.17 47.29 117.76 35.70 14.69 0.5058 2.17 47.27 117.71 35.68 14.96 0.5057 2.18 47.25 117.66 35.67 15.24 0.5055 2.19 47.23 117.61 35.65 15.56 0.5054 2.20 47.21 117.56 35.63 15.85 0.5053 2.21 47.19 117.50 35.62 16.18 0.5051 2.22 47.16 117.43 35.60 16.48 0.5049 2.23 47.14 117.38 35.58 16.83 0.5048 2.23 47.11 117.31 35.56 17.14 0.5046 2.24 47.09 117.24 35.54 17.50 0.5044 2.25 47.06 117.17 35.52 17.86 0.5042 2.26 47.02 117.09 35.49 18.20 0.5040 2.27 47.00 117.02 35.47 18.58 0.5038 2.28 46.96 116.93 35.44 18.97 0.5035
A_12
2.29 46.93 116.86 35.42 19.32 0.5033 2.29 46.90 116.77 35.40 19.68 0.5031 2.30 46.86 116.69 35.37 20.09 0.5028 2.31 46.83 116.62 35.35 20.46 0.5026 2.32 46.80 116.53 35.32 20.84 0.5024 2.33 46.76 116.44 35.30 21.23 0.5021 2.34 46.72 116.34 35.26 21.63 0.5018 2.34 46.69 116.25 35.24 22.03 0.5016 2.35 46.64 116.14 35.21 22.44 0.5013 2.36 46.61 116.06 35.18 22.86 0.5011 2.37 46.57 115.95 35.15 23.28 0.5008 2.37 46.52 115.84 35.11 23.71 0.5005 2.38 46.48 115.74 35.08 24.15 0.5002 2.39 46.43 115.61 35.05 24.60 0.4998 2.40 46.39 115.51 35.01 25.06 0.4995 2.41 46.34 115.38 34.98 25.59 0.4991 2.42 46.28 115.24 34.93 26.12 0.4987 2.43 46.22 115.10 34.89 26.67 0.4983 2.43 46.17 114.96 34.85 27.16 0.4979 2.44 46.12 114.83 34.81 27.67 0.4976 2.45 46.05 114.67 34.76 28.18 0.4971 2.46 45.99 114.53 34.72 28.71 0.4967 2.47 45.94 114.38 34.67 29.31 0.4963 2.48 45.88 114.24 34.63 29.92 0.4959 2.48 45.82 114.09 34.58 30.48 0.4955 2.49 45.76 113.93 34.54 30.97 0.4950 2.50 45.70 113.79 34.49 31.55 0.4946 2.51 45.64 113.64 34.45 32.14 0.4942 2.51 45.57 113.48 34.40 32.73 0.4937 2.52 45.50 113.30 34.34 33.34 0.4932 2.53 45.44 113.15 34.30 33.96 0.4927 2.54 45.38 112.99 34.25 34.59 0.4923 2.55 45.30 112.81 34.19 35.32 0.4917 2.56 45.24 112.64 34.14 36.06 0.4913 2.57 45.17 112.48 34.09 36.81 0.4908 2.57 45.10 112.29 34.04 37.58 0.4902 2.58 45.02 112.11 33.98 38.37 0.4897 2.59 44.95 111.92 33.93 39.17 0.4892 2.60 44.87 111.74 33.87 39.99 0.4886 2.61 44.79 111.53 33.81 40.93 0.4880 2.62 44.71 111.33 33.75 41.88 0.4874 2.63 44.63 111.12 33.68 42.85 0.4868 2.64 44.55 110.92 33.62 43.85 0.4862 2.65 44.47 110.73 33.57 44.87 0.4857 2.66 44.38 110.51 33.50 46.03 0.4850 2.67 44.29 110.28 33.43 47.10 0.4843 2.68 44.20 110.06 33.36 48.31 0.4836 2.70 44.11 109.83 33.29 49.55 0.4830 2.71 44.03 109.62 33.23 50.93 0.4824 2.72 43.93 109.40 33.16 52.24 0.4817 2.73 43.84 109.17 33.09 53.70 0.4810
A_13
2.74 43.75 108.94 33.02 55.34 0.4803 2.76 43.66 108.71 32.95 56.89 0.4796 2.77 43.56 108.46 32.88 58.75 0.4789 2.78 43.46 108.21 32.80 60.67 0.4781
B_1
B: WP4C MEASUREMENTS OF BRAYBROOK SOIL
Depth 0 – 0.3 meters
WP4C TEST RESULTS SHEET
SITE: Braybrook DEPTH: 0-0.3 m
SAMPLE DATE : 1/05/2014 TEST DATE : 21/09/2014
GMC Total
Suction (pF)
Osmotic suction (kPa)
Matric suction (Kpa)
VMC
0.2241 4.23 700.00
998.24 0.36 0.1866 4.38 1698.83 0.31 0.0864 5.89 76924.71 0.16
Depth 0.3 – 0.8 meters
WP4C TEST RESULTS SHEET
SITE: Braybrook DEPTH: 0.5 m
SAMPLE DATE : 2/08/2013 TEST DATE : 23/08/2013
GMC Total
Suction (pF)
Osmotic suction (kPa)
Matric suction (Kpa)
VMC
0.2090 4.59 3190.45 0.3387 0.1607 4.89 7062.47 0.2734 0.1583 5.09 11602.69 0.2700 0.1352 5.18 14435.61 0.2367 0.1344 5.26 700 17497.01 0.2355 0.1186 5.44 26842.29 0.2118 0.1110 5.56 35607.81 0.2001 0.1106 5.60 39110.72 0.1995 0.0978 5.75 55534.13 0.1793 0.0917 5.95 88425.09 0.1695
B_2
Depth 0.8 – 1.3 meters
WP4C TEST RESULTS SHEET
SITE: Braybrook DEPTH: 1.0 m
SAMPLE DATE : 2/12/2013 TEST DATE : 12/12/2013
GMC Total
Suction (pF)
Osmotic suction (kPa)
Matric suction (Kpa)
VMC
0.2090 4.59 2790.45 0.3387 0.2167 4.62 3068.69 0.3487 0.1920 4.76 4654.40 0.3163 0.1883 4.80 5209.57 0.3114 0.1879 4.86 1100 6144.36 0.3108 0.1607 4.89 6662.47 0.2734 0.1583 5.09 11202.69 0.2700 0.1352 5.18 14035.61 0.2367 0.1344 5.26 17097.01 0.2355 0.1186 5.44 26442.29 0.2118 0.1110 5.56 35207.81 0.2001 0.1106 5.60 38710.72 0.1995 0.0978 5.75 55134.13 0.1793 0.0921 5.95 88025.09 0.1701
B_3
Depth 1.3 – 1.8 meters
WP4C TEST RESULTS SHEET
SITE: Braybrook DEPTH: 1.5 m
SAMPLE DATE : 2/12/2013 TEST DATE : 9/12/2013
GMC Total
Suction (pF)
Osmotic suction (kPa)
Matric suction (Kpa)
VMC
0.2494 4.28 805.46 0.3896 0.2480 4.32 989.30 0.3880 0.2494 4.34 1087.76 0.3896 0.2387 4.35 1100 1138.72 0.3765 0.2413 4.39 1354.71 0.3796 0.2309 4.42 1530.27 0.3667 0.1903 4.71 4028.61 0.3140 0.1438 5.16 13354.4 0.2493 0.1093 5.56 35207.81 0.1975
Depth 1.8 – 2.3 meters
WP4C TEST RESULTS SHEET
SITE: Braybrook DEPTH: 2.0 m
SAMPLE DATE : 1/05/2014 TEST DATE : 21/06/2014
GMC Total
Suction (pF)
Osmotic suction (kPa)
Matric suction (Kpa)
VMC
0.23 4.58
2500
1301.89 0.37 0.21 4.68 2286.30 0.34 0.27 4.49 590.30 0.41 0.24 4.59 1390.45 0.37 0.11 5.65 45173.68 0.18
C_1
C: FILTER PAPER SUCTION MEASUREMENTS OF BRAYBROOK SOIL
Depth 0.3 – 0.8 meters
FILTER PAPER TEST RESULTS SHEET
SITE: Braybrook
DEPTH: 0.5 m TEST NO: 1
Test Started: 15/07/2014 Test Finished: 7/08/2014
Moisture content of the sample (%) 23.01 VMC 0.3669
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 25.4049 25.5658 25.5296 25.401 25.12 3.37 2346.46 Matric 13.7186 13.8282 13.8012 13.715 27.15 3.21 1630.47 Osmotic suction (kPa) 716
DEPTH: 0.5 m
TEST NO: 2
Test Started: 27/06/2014 Test Finished: 14/07/2014
Moisture content of the sample (%) 36.84 VMC 0.5161
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 13.6482 13.9971 13.9119 13.6461 31.26 2.89 778.98 Matric 15.7289 15.862 15.8172 15.7266 46.91 1.67 47.07 Osmotic suction (kPa) 732
C_2
DEPTH: 0.5 m TEST NO: 3
Test Started: 27/06/2014 Test Finished: 14/07/2014 Moisture content of the sample (%) 29.05 VMC 0.4387
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 15.3069 15.6545 15.5707 15.3048 30.73 2.93 857.94 Matric 14.598 14.7254 14.6889 14.5965 37.88 2.38 237.82 Osmotic suction (kPa) 620
Depth 0.8 – 1.3 meters
FILTER PAPER TEST RESULTS SHEET
SITE: Braybrook
DEPTH: 1.0-1.5 m
TEST NO: 1
Test Started: 2/12/2013 Test Finished: 14/12/2013
Moisture content of the sample (%) 24.41 VMC 0.3845
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 21.3068 21.64140099 21.5686 21.3058 27.32 3.20 1579.98 Matric 21.1157 21.2833 21.2393 21.1141 33.87 2.69 488.49 Osmotic suction (kPa) 1091
C_3
Depth 1.8 – 2.3 meters
FILTER PAPER TEST RESULTS SHEET
SITE: Braybrook
DEPTH: 1.5-2.0 m
TEST NO: 1
Test Started: 15/07/2014 Test Finished: 7/08/2014
Moisture content of the sample (%) 21.11 VMC 0.3423
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 13.9589 14.118 14.0846 13.9534 21.27 3.67 4682.07 Matric 13.5377 13.699 13.6604 13.5314 25.04 3.38 2379.47 Osmotic suction (kPa) 2302.59
DEPTH: 1.5-2.0 m
TEST NO: 2
Test Started: 27/06/2014 Test Finished: 14/07/2014
Moisture content of the sample(%) 23.15 VMC 0.3687
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 13.5367 13.8664 13.8054 13.5355 22.16 3.60 3990.43 Matric 13.9589 14.074 14.0455 13.9558 28.32 3.12 1321.71 Osmotic suction (kPa) 2668.72
C_4
DEPTH: 1.5-2.0 m
TEST NO: 3
Test Started: 27/06/2014 Test Finished: 14/07/2014
Moisture content of the sample(%) 23.45 VMC 0.3725
Suction type
Cold tare
mass (g)
Cold tare + wet filter paper (g)
Hot tare +
dry filter paper
(g)
Hot tare
mass (g)
Filter paper water
content (%)
Suction from
standard ASTM D5298
(log[kPa])
Suction converted into kPa
Total 14.996 15.3268 15.2637 14.993 22.20 3.60 3958.11 Matric 14.5433 14.6602 14.6324 14.5412 28.18 3.13 1354.54 Osmotic suction (kPa) 2603.57
D_1
D: SATURATED HYDRAULIC CONDUCTIVITY MEASUREMENTS OF BRAYBROOK SOIL
Depth 0.0 – 0.4 meters
Type of Material Undisturbed clay soil Depth (m) 0.0-0.4 Location Braybrook Date Sampled 24/07/2014 Tested by Aruna Karunarathne Date Tested 30/10/2014
Material Specification Saturation Duration 24 hrs
Curing Duration 24 hrs
Sample Diameter (mm) 50.00
Reading Duration 48 hrs Water Temperature 20 (°C) Sample Area (cm2) 19.63
Epoxy Curing 24 hrs Flow direction Downward Sample height (cm) 10.60 Water density at test temperature (gr/cm3) 0.9982071
Readings
No Time after starting test (sec)
Reading Q (cm3)
Time (sec)
q (cm3/sec)
Top Pressure (kPa)
Bottom pressure (kPa)
Δ h (cm) i=Δh/L k
(m/sec) k (m/day)
1 90000 127.94 13.59 3600 0.0037736 410.4 407.9 24.48 2.31 8.32E-07 7.19E-02 2 93600 141.52 12.44 3600 0.003455 410.4 407.9 24.48 2.31 7.62E-07 6.58E-02 3 97200 153.96 12.58 3600 0.0034942 410.4 407.9 24.48 2.31 7.71E-07 6.66E-02 4 100800 166.54 12.35 3600 0.0034292 410.4 407.9 24.48 2.31 7.56E-07 6.53E-02 6 104400 178.88 12.15 3600 0.0033747 410.4 407.9 24.48 2.31 7.44E-07 6.43E-02 7 108000 191.03 3600 410.4 407.9 24.48 2.31
Average value 7.73E-07 6.68E-02
D_2
Depth 0.5 – 1.0 meters
Type of Material Undisturbed clay soil Depth (m) 0.5-1.0 Location Braybrook Date Sampled 24/07/2014 Tested by Aruna Karunarathne Date Tested 10/10/2014
Material Specification Saturation Duration 24 hrs
Curing Duration 24 hrs
Sample Diameter (mm) 50.00
Reading Duration 48 hrs Water Temperature 20 (°C) Sample Area (cm2) 19.63
Epoxy Curing 24 hrs Flow direction Downward Sample height (cm) 9.50 Water density at test temperature (gr/cm3) 0.9982071
Readings
No Time after starting test (sec)
Reading Q (cm3)
Time (sec)
q (cm3/sec)
Top Pressure (kPa)
Bottom pressure (kPa)
Δ h (cm) i=Δh/L k (m/sec) k
(m/day)
1 7200 2.41 0.878 1800 0.0004878 535 533 19.58 2.062 1.21E-07 1.04E-02 2 9000 3.288 0.937 1800 0.0005206 535 533 19.58 2.062 1.29E-07 1.11E-02 3 10800 4.225 1.039 1800 0.0005772 535 533 19.58 2.062 1.43E-07 1.23E-02 4 12600 5.264 1.248 1800 0.0006933 535 533 19.58 2.062 1.71E-07 1.48E-02 5 14400 6.512 1.317 1800 0.0007317 535 533 19.58 2.062 1.81E-07 1.56E-02 6 16200 7.829 1.32 1800 0.0007333 535 533 19.58 2.062 1.81E-07 1.57E-02 7 18000 9.149 1.276 1800 0.0007089 535 533 19.58 2.062 1.75E-07 1.51E-02 8 19800 10.425 1800 535 533 19.58 2.062
Average value 1.57E-07 1.36E-02
D_3
Depth 1.0 – 1.4 meters
Type of Material Undisturbed clay soil Depth (m) 1.0-1.4 Location Braybrook Date Sampled 24/07/2014 Tested by Aruna Karunarathne Date Tested 23/09/2014
Material Specification Saturation Duration 24 hrs
Curing Duration 24 hrs
Sample Diameter (mm) 50.00
Reading Duration 48 hrs Water Temperature 20 (°C) Sample Area (cm2) 19.63
Epoxy Curing 24 hrs Flow direction Downward Sample height (cm) 8.90 Water density at test temperature (gr/cm3) 0.9982071
Readings
No Time after starting test (sec)
Reading Q (cm3)
Time (sec)
q (cm3/sec)
Top Pressure (kPa)
Bottom pressure (kPa)
Δ h (cm) i=Δh/L k (m/sec) k (m/day)
1 39600 0.821 0.025 1800 1.389E-05 520 518 19.58 2.201 3.21E-09 2.78E-04 2 41400 0.846 0.027 1800 0.000015 520 518 19.58 2.201 3.47E-09 3.00E-04 3 43200 0.873 0.027 1800 0.000015 520 518 19.58 2.201 3.47E-09 3.00E-04 4 45000 0.9 0.025 1800 1.389E-05 520 518 19.58 2.201 3.21E-09 2.78E-04 5 46800 0.925 0.026 1801 1.444E-05 520 518 19.58 2.201 3.34E-09 2.89E-04 6 48600 0.951 0.03 1800 1.667E-05 520 518 19.58 2.201 3.86E-09 3.33E-04 7 50400 0.981 1800 520 518 19.58 2.201
Average value 3.43E-09 2.96E-04
D_4
Depth 1.5 – 1.8 meters
Type of Material Undisturbed clay soil Depth (m) 1.5-1.8 Location Braybrook Date Sampled 24/07/2014 Tested by Aruna Karunarathne Date Tested 18/11/2014
Material Specification Saturation Duration 24 hrs
Curing Duration 24 hrs
Sample Diameter (mm) 50.00
Reading Duration 48 hrs Water Temperature 20 (°C) Sample Area (cm2) 19.63
Epoxy Curing 24 hrs Flow direction Downward Sample height (cm) 11.2 Water density at test temperature (gr/cm3) 0.9982071
Readings
No Time after starting test (sec)
Reading Q (cm3)
Time (sec)
q (cm3/sec)
Top Pressure (kPa)
Bottom pressure (kPa)
Δ h (cm) i=Δh/L k (m/sec) k (m/day)
1 97200 2.870 0.069 3600 1.916E-05 408.0 405.5 24.48102913 2.185806172 4.47E-09 3.86E-04 2 100800 2.939 0.022 3600 6.111E-06 408.0 405.5 24.48102913 2.185806172 1.42E-09 1.23E-04 3 104400 2.961 0.021 3600 5.833E-06 408.0 405.5 24.48102913 2.185806172 1.36E-09 1.17E-04 4 108000 2.982 0.019 3600 5.278E-06 408.0 405.5 24.48102913 2.185806172 1.23E-09 1.06E-04 5 111600 3.001 0.023 3600 6.389E-06 408.0 405.5 24.48102913 2.185806172 1.49E-09 1.29E-04 6 115200 3.024 3600 408.0 405.5 24.48102913 2.185806172
Average value 1.99E-09 1.72E-04
E_1
E: MODEL CALIBRATION DATA
ACTUAL MEASUREMENTS
Location CN1 – Volumetric moisture contents from Neutron probe
Depth from GL (m)
CN1 10/04/2
013
CN1 20/06/2
013
CN1 21/08/2
013
CN1 21/10/2
013
CN1 11/12/2
013
CN1 29/01/2
014
CN1 26/02/2
014
CN1 1/04/20
14
CN1 1/05/20
14
CN1 5/06/20
14
CN1 8/07/20
14
CN1 12/11/2
014
CN1 25/03/2
015
-0.35 0.33 0.41 0.43 0.44 0.43 0.30 0.28 0.27 0.36 0.36 0.37 0.34 0.35 -0.6 0.34 0.39 0.42 0.41 0.41 0.35 0.34 0.32 0.33 0.33 0.33 0.35 0.35 -0.85 0.36 0.36 0.38 0.38 0.38 0.37 0.36 0.35 0.35 0.34 0.34 0.34 0.35 -1.1 0.34 0.34 0.35 0.34 0.35 0.35 0.35 0.35 0.34 0.34 0.34 0.34 0.35 -1.35 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 -1.6 0.37 0.36 0.36 0.37 0.37 0.36 0.37 0.36 0.36 0.36 0.36 0.36 0.37 -1.85 0.37 0.36 0.36 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.36 -2.1 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 -2.35 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 -2.6 0.37 0.38 0.37 0.37 0.38 0.37 0.38 0.37 0.37 0.37 0.37 0.38 0.38 -2.85 0.37 0.38 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.37 0.37 0.38 0.38
E_2
Location CN2– Volumetric moisture contents from Neutron probe
Depth from GL (m)
CN2 10/04/2
013
CN2 20/06/2
013
CN2 21/08/2
013
CN2 21/10/2
013
CN2 11/12/2
013
CN2 29/01/2
014
CN2 26/02/2
014
CN2 1/04/20
14
CN2 1/05/20
14
CN2 5/06/20
14
CN2 8/07/20
14
CN2 12/11/2
014
CN2 25/03/2
015
10/04/2013
20/06/2013
21/08/2013
21/10/2013
11/12/2013
29/01/2014
26/02/2014
1/04/2014
1/05/2014
5/06/2014
8/07/2014
12/11/2014
25/03/2015
-0.35 0.33 0.32 0.36 0.36 0.36 0.22 0.21 0.21 0.27 0.27 0.28 0.24 0.29 -0.6 0.33 0.37 0.39 0.40 0.40 0.34 0.33 0.33 0.34 0.34 0.34 0.37 0.38 -0.85 0.36 0.37 0.40 0.40 0.40 0.38 0.35 0.34 0.36 0.36 0.36 0.38 0.38 -1.1 0.37 0.35 0.40 0.35 0.36 0.36 0.35 0.35 0.35 0.36 0.35 0.36 0.36 -1.35 0.37 0.36 0.35 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37 -1.6 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37 -1.85 0.38 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.38 0.37 0.38 0.38 -2.1 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37 0.38 0.38 -2.35 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37 0.38 0.38 -2.6 0.38 0.37 0.37 0.37 0.38 0.38 0.37 0.37 0.38 0.38 0.37 0.39 0.39 -2.85 0.38 0.37 0.38 0.37 0.38 0.38 0.37 0.37 0.38 0.38 0.37 0.39 0.39
E_3
Average of locations CN1 and CN2– Volumetric moisture contents from Neutron probe
Depth from GL (m)
10/04/2013
20/06/2013
21/08/2013
21/10/2013
11/12/2013
29/01/2014
26/02/2014
1/04/2014
1/05/2014
5/06/2014
8/07/2014
12/11/2014
25/03/2015
-0.35 0.33 0.36 0.39 0.40 0.39 0.26 0.25 0.24 0.32 0.31 0.32 0.29 0.32 -0.6 0.33 0.38 0.40 0.41 0.41 0.34 0.33 0.33 0.34 0.34 0.34 0.36 0.37
-0.85 0.36 0.37 0.39 0.39 0.39 0.38 0.35 0.35 0.35 0.35 0.35 0.36 0.36 -1.1 0.35 0.34 0.37 0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.34 0.35 0.35
-1.35 0.37 0.36 0.35 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 -1.6 0.37 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.36 0.37 0.36 0.37 0.37
-1.85 0.37 0.36 0.36 0.37 0.36 0.36 0.36 0.36 0.37 0.37 0.37 0.37 0.37 -2.1 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.37
-2.35 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.38 -2.6 0.38 0.38 0.37 0.37 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.38 0.38
-2.85 0.38 0.38 0.38 0.37 0.38 0.37 0.38 0.37 0.38 0.37 0.37 0.38 0.38
E_4
MODEL PREDICTIONS – Volumetric moisture contents
Y (m) Model
10/04/2013
Model 20/06/2
013
Model 21/08/2
013
Model 21/10/2
013
Model 11/12/2
013
Model 29/01/2
014
Model 26/02/2
014
Model 01/04/2
014
Model 01/05/2
014
Model 05/06/2
014
Model 08/07/2
014
Model 12/11/2
014
Model 25/03/2
015
-4.00 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.90 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.80 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.70 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.60 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.50 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.40 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.30 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.20 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.10 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-3.00 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.90 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.80 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.70 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.60 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.50 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.40 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38
-2.30 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.37
-2.20 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37
-2.10 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-2.00 0.38 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
E_5
-1.90 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.80 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.70 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.60 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.50 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.40 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.30 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-1.20 0.37 0.37 0.37 0.37 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37
-1.10 0.37 0.36 0.37 0.38 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.36
-1.00 0.36 0.36 0.37 0.38 0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.36 0.36
-0.90 0.36 0.35 0.39 0.39 0.39 0.38 0.37 0.37 0.36 0.36 0.36 0.36 0.35
-0.80 0.33 0.35 0.41 0.39 0.38 0.37 0.36 0.35 0.35 0.35 0.35 0.35 0.33
-0.70 0.33 0.35 0.41 0.39 0.38 0.36 0.35 0.34 0.34 0.34 0.34 0.34 0.32
-0.60 0.33 0.37 0.41 0.39 0.38 0.36 0.35 0.34 0.34 0.34 0.34 0.34 0.31
-0.50 0.33 0.38 0.41 0.39 0.37 0.35 0.34 0.33 0.34 0.34 0.34 0.34 0.31
-0.40 0.34 0.40 0.40 0.39 0.37 0.35 0.34 0.32 0.34 0.33 0.34 0.33 0.30
-0.30 0.33 0.39 0.38 0.36 0.35 0.32 0.31 0.30 0.32 0.31 0.32 0.31 0.28
-0.20 0.33 0.37 0.35 0.33 0.34 0.29 0.28 0.27 0.30 0.29 0.30 0.28 0.25
-0.10 0.32 0.38 0.33 0.29 0.35 0.24 0.23 0.24 0.30 0.32 0.29 0.24 0.21
0.00 0.27 0.38 0.30 0.17 0.32 0.10 0.14 0.14 0.29 0.36 0.26 0.13 0.15
E_6
Figures – Volumetric moisture content profiles obtained from Neutron probe
measurements and model
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 10/04/2013 CN1 - 10/04/2013 CN2 - 10/04/2013
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
) Model - 20/06/2013 CN1 - 20/06/2013 CN2 - 20/06/2013
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 21/10/2013 CN1 - 21/10/2013 CN2 - 21/10/2013
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 21/08/2013 CN1 - 21/08/2013 CN2 - 21/08/2013
E_7
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 11/12/2013 CN1 - 11/12/2013 CN2 - 11/12/2013
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 29/01/2014 CN1 - 29/01/2014 CN2 - 29/01/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 26/02/2014 CN1 - 26/02/2014 CN2 - 26/02/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 1/04/2014 CN1 - 01/04/2014 CN2 - 01/04/2014
E_8
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 5/06/2014 CN1 - 05/06/2014 CN2 - 05/06/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 1/05/2014 CN1 - 01/05/2014 CN2 - 01/05/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 12/11/2014 CN1 - 12/11/2014 CN2 - 12/11/2014
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 8/07/2014 CN1 - 08/07/2014 CN2 - 08/07/2014
E_9
0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60
-4
-3
-2
-1
0
Volumetric moisture content
Dep
th (m
)
Model - 25/03/2015 CN1 - 25/03/2015 CN2 - 25/03/2015