multi-dimensional digital soil mapping: past, present and future … · multi-dimensional digital...

Talk Outline

What is digital soil

mapping DSM?

Digital Soil Mapping

EM Instruments

Results, Discussion &

Conclusions

Multi-dimensional digital soil mapping:

Past, present and future research

John Triantafilis

EM4Soill

0 through 9 1961

Jasper Johns

Oil on canvas painting

Presented by the Friends of the Tate Gallery 1961

soil properties and

soil type.

in soil science, or "predictive soil mapping",

is the computer-assisted production of

digital maps of

What is DSM?

Digital soil mapping (wikipedia)

http://en.wikipedia.org/wiki/Soil_science

DSM involves the creation and population

of spatial soil information by the use of

field and

laboratory

observational methods

coupled with Pedometric methods such as

spatial and

non-spatial soil inference systems.

What is DSM?

Untitled

Herry Perry

Oil on board (painting)

Rothamsted Research (1932)


field

laboratory

It applies Pedometrics, which is the use of

mathematical and

statistical models

that combine information from soil

observations

with information contained in correlated

ancillary data

proximal instruments and

remote sensed images.

What is DSM?

Das Rudel (the pack)

Joseph Beuys

Volkswagon bus with twenty four wooden sleds, each with felt, belts,

flashlight, fat and stamped with Braunkreuz (brown paint)

Tate Modern, UK



Semi-automated techniques and

technologies are used to

acquire,

process and

visualize

information on soil and auxiliary information,

so that the end result is obtained at cheaper

cost

What is DSM?

L'Escargot

Henri Matisse

Gouache on paper, cut and pasted on paper mounted on canvas

on paper, unique

Purchased with assistance from the Friends of the Tate Gallery 1962

Electromagnetic (EM) induction

Techniques where induction coils are used

to measure magnetic fields

associated with current flow in the earth

What is electromagnetics (EM)?

Property of interest is CONDUCTIVITY

(i.e. apparent electrical conductivity-ECa)

What is physical property of interest?

ECa - millisiemens/metre (mS/m)

What units are it measured in?

Maxwell’s equations

Maxwell's equations describe

how electric and magnetic fields are

generated by

i) charges,

ii) currents, and

iii) changes of each other.

Why they are important for EM induction


Transmitter (Tx) Receiver (Rx)

EM instruments contain two sets of coils

located at opposite sides of instrument

What are components of an instrument?

Transmitter coil (Tx):

driven by AC current

at audio frequencies

to generate a sinusoidal

time-varying magnetic field

Receiver coil (Rx):

positioned on or near surface

of the earth some distance away from the

transmitter coil


How does an EM instrument work?

An alternating current (AC)

is introduced

into Transmitter coil (Tx)

(Tx) (Rx)



AC induces

primary magnetic field

Into/out of soil



As primary magnetic field

passes into/out of soil,

eddy currents generated in soil

What conducts a current in soil?

Soil properties

2:1 Smectite

Clay

type

Clay

content

1:1 Kaolin -

-

-

-

-

-

-

-

-

-

-

-

-

-

Water

content

Salt

content



Induces secondary magnetic field

into Receiver coil (Rx)

Soil properties that influence ECa

Clay content

Mineralogy (CEC)

Water content

Salt concentration

Temperature

Bulk density

Calibration

Applying a mobile electromagnetic sensing system (MESS)

to assess cause and management of soil salinization

Triantafilis, J., Huckel, A.I.,

Ahmed, M.F., Odeh, I.O.A.

18, 330-339

DSM of compositional particle-size fractions (PSFs)

using proximal and remotely sensed ancillary data

Buchanan S.M., Triantafilis, J.,

Odeh, I.O.A.

77, WB201-211

clay floodplains

prior stream Aeolian

sand

prior stream

clay floodplains

Aeolian

sand

Clay

content

Clay

content

5

10

15

20

Soil EC (ms/m)a

0 20 40 60 80 100

1

3

45

6

9

10

1113 12

2

8

21

7

15

16

18

1920

2217

14

Field level DSM of cation exchange capacity

using EM and a spatial regression model

Triantafilis, J., Lesch, S.M.,

La Lau, K., Buchanan, S.M. (2009)

47, 651-663

Dermosols

Vertosols?

Soil

mineralogy

DSM available water content

using proximal and remotely sensed data

Gooley, L., Huang, J.,

Page, D., Triantafilis, J.

30, 139-151

Trangie Cowal Trangie Cowal

Water

content

lAn error budget for mapping field-scale soil salinity at

various depths using different sources of ancillary data

Huang, J., Barrett-Lennard, E., Kilminster, T.,

Sinott, A., Triantafilis, J. Salt

content

79, 1717-1728

terraGIS: web-based platform for delivery

of DSM for cotton growing areas of Australia

Huang, J., Buchanan, S.M.

Bishop, TFA, Triantafilis, J.

In press

EM38

Proximal

0.75

1.5

Depth (m)

h v

EM instruments

EM38v

EM38h

Operating Frequency:

14kHz

DSM

clay content,

CEC,

water content and salinity

Tx Rx

1m

Root zone

Application

Sub-soil

0

http://www.geonics.com/

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

0-1

.5 m

0-0

.75

m

What you can measure…

…with a EM38

1.0

2.0

6.0

3.0

4.0

5.0

EM38MK-2

Proximal Depth (m)

h v

EM instruments

EM38v

EM38h


14.5kHz

Tx Rx

1m

Root zone

Application

Sub-soil

0


0.75

1.5

0.375

0.75


…with a EM38MK-2

1.0

2.0

6.0

3.0

4.0

5.0

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

0-1

.5 m

0-0

.75

m

0-0

.75

m

0-0

.37

5 m

Application

Measurement

Proximal

6

3

Vadose

zone

Shallow

groundwater

tables

EM31v

EM31h

Geonics EM31


10kHz


Tx

Rx

Depth (m)

h v 0

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m

0-3

.0 m

0-1

.0 m


…with a EM31

1.0

2.0

6.0

3.0

4.0

5.0

30

15

7

Application

Geonics EM34

EM34-40

EM34-20

EM34-10

Proximal

Vadose

zone

Shallow

groundwater

tables


6.4, 1.6 and 0.4 kHz

Tx Rx

EM instruments

Depth (m)

h 0

DUALEM-421

State-of-the-art

LAMBERT, George, ‘Across the black soil plains’, 1899, Oil on canvas

TRIANTAFILIS, John, ‘Across the clay alluvial plains’, 2009, GEOS3721 Field Trip

http://www.dualem.com/


9.0 kHz

Geonics EM38

Geonics EM31

0-2.0 m

0-6.0 m

0-0.5 m

0-1.5 m

0-1.0 m

0-3.0 m

DUALEM-421

Theoretical depth of sa measurement


DUALEM-421

State-of-the-art


Tx

Rx

Rx

Rx

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m


…with a DUALEM-421

1.0

2.0

6.0

3.0

4.0

5.0

DUALEM- 21 http://www.dualem.com/

UNSW-CSSRI collaboration

Tx Rx

Rx

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m



1.0

2.0

6.0

3.0

4.0

5.0

@ UNSW Sydney

Commercially available instruments

Seeing is believing:

DSM using ancillary data and numerical clustering

to identify management zones

Jingyi Huang,

Rod Nielson, Michael Sefton, John Triantafilis

DSM:

Ancillary Data


Conclusions

Problem

Definition?

DSM:

Data Modelling

FuzME

Australian Sugarcane

Australian sugarcane is grown in alluvial-

estuarine areas of NE Queensland,

characterised by

i) sodic and/or

ii) infertile sandy soil

Introduction

From a production perspective there is a

need therefore to

i) ameliorate (ie. gypsum) and

ii) fertilise (ie. lime) the soil.

Best-practice amelioration and fertiliser

requires knowledge of soil variation to

maximise yield and minimise losses

BUT this will also require information about

i) soil physical (eg. clay) and

ii) chemical (eg. ESP, Exch. Ca/Mg)

because they determine ameliorant and

nutrient availability.

Nutrient Management

Introduction

Moreover, samples are required

i) across the field and

ii) at multiple depths

to ascertain what constrains yield and/or

productivity

Problem definition

So how can a farmer manage variation of

so many properties when sampling and

analysis is expensive ($180/sample)?

Nutrient Management

Can we use digital soil mapping (DSM)…

Potential solution?

1. To value add to limited soil data

2. Using easier to acquire ancillary data

3. And non-spatial inference models

…to make soil

management zones

Electromagnetic induction: DUALEM-421

Using easier to acquire ancillary data

Measures ECa at various depths

Gamma-ray spectrometry: Rx700

Measures g-rays in top 0-0.30 m

Aims

In a sugarcane field in Herbert Valley:

a) Can we use

easier to acquire ancillary data

such as proximal sensing

i) g-ray (RS-700) and

ii) EM - DUALEM-421 data

to identify soil management zones;

b) Do these DSM derived

Soil management zones relate to

differences in topsoil (0-0.3 m) and

subsoil (0.6-0.9 m) properties;

i) Clay, CEC, ESP, pH

ii) Exch, Ca, Mg, Na and K

iii) or yield percent variation.

High - K

Int. - K

Low - K

Int. - U

Low – U

Int. - Th

Low - Th

Int. - Th

Low - Th

g-ray (RS-700)

Easier to acquire ancillary data

DUALEM-421

1mPcon

1mHcon

2mPcon

2mHcon


Int. - ECa

Low - ECa

Yield percent variation

2014

2015

2016


High – Y%V

Int - Y%V

k = 2

k = 3

k = 4

k = 5

How many classes (k)/management zones?

Objective management zones

?

When k = 3,

Topsoil (0-0.3m)

clay, sand,

CEC,

ESP,

Exch. Ca, Mg

are all minimised

Subsoil (0.6-0.9m)

clay,

ESP,

exch. Ca, Na,

are all minimised

How many classes (k)/management zones?

The best number of zones

y = Xt + Zu + e

Clay (%)

CEC (cmol(+)/kg)

ESP (%)

pH

Topsoil (0-0.3m) properties

4 t/ha

2 t/ha 4 t/ha

Gypsum (6 easy steps)

Just add gypsum

Can we upscale to a farm scale?

Research Question

Gamma-ray and EM data coupled with

clustering produce soil management zones

related to differences in soil properties

important for amelioration and fertilisation.

Implications including;

(i) more efficient application of gypsum to

ameliorate topsoil sodicity,

(ii) more efficient application of lime to

improve topsoil infertility, and

(iii) potential to define zones which can be

used to develop strip trials of;

a) varieties, and

b) gypsum and fertiliser

requirement

DSM of soil landscape units

at the district scale

Zare, E., Huang, J.,

Triantafilis, J.,

clay floodplains

prior stream Aeolian

sand

prior stream

clay floodplains

Aeolian

sand

Clay

content

Computers and Electronics in Agriculture 127 (2016) 510–520

Develop a visNIR spectral library

To predict

i) soil physical

(eg. Clay and sand) and

ii) chemical

(eg. CEC, ESP,

Exch. Ca/Mg

pH

Organic Carbon)

because they determine

ameliorant and

nutrient availability.

Regional scale

ARC – Linkage

Research Questions and partners

Can we

-upscale farm scale zoning

-improve water use efficiency

-develop industry spectral index

Partner cash (/annum)

Herbert Cane Productivity Services Ltd

– Salary of Michael Sefton ($100k)

DAVCO Farming Pty Ltd

– Usual consulting/surveys ($50k)

Mirawhinney Lime/Gypsum

– Fertiliser ($50k)

Backpaddock (Soil analysis)

– Fertiliser recommendation ($50k)

Talk Outline

Problem

Definition?

Materials and

Methods


Conclusions

EM4Soill

Now you see it…now you don’t:

Time-lapse imaging of soil moisture

Huang J, Scudiero E, Choo H, Clary W,

Corwin D, Triantafilis J

Problem definition

A constant need to measure/monitor?

Soil water content (w) is required for

crop yield optimization and

water use efficiency improvement.

Unfortunately, thermogravimetric (w)

method is too

labour intensive,

time-consuming, and

expensive (r needs measuring)

to be practical at the field scale.

To improve efficiency, instruments have

been developed to measure temporal

variation of q at point locations:

TDR

Capacitance probes

Neutron probe

What would be ideal?

If you could afford the time and money?

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

q1

q2

q3

q4

q5

Many have shown potential, for example

Can we map q using EM?


9.0 kHz

Geonics EM38

Geonics EM31

0-2.0 m

0-6.0 m

0-0.5 m

0-1.5 m

0-1.0 m

0-3.0 m

DUALEM-421

Theoretical depth of ECa measurement

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m

0-3

.0 m

0-1

.0 m

0-1

.5 m

0-0

.5 m

0-1

.5 m

0-0

.5 m



1.0

2.0

6.0

3.0

4.0

5.0

http://emtomo.com

EM4Soil

Quasi-2d and 3d inversion software

EM4Soil

Inverted ECa (s)

Electromagnetic conductivity image

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

Research Question

Can we use a

+

1-dimensional inversion software

To generate EMCI to represent

time-lapse

soil moisture status

single frequency and

multiple array

EM4Soil

DUALEM-421

Materials and methods

Field is 32 ha and farmed with irrigated

alfalfa (Medicago sativa L.), used for

consumption on-farm in a dairy feed lot.

Average properties of dairy lagoon water

from March 2008 to June 2009 were:

• pH water is slightly alkaline (pH = 7.8)

• slightly saline ECiw (1.63 dS/m) and SARw

(4.3), water infiltration problems unlikely

Study field


Centre pivot irrigation:

• Sprinklers (~ 2 m)

• Wheel tracks (~48 m)

DUALEM-421

Measurements

Day

1 (28 August, 2014)

2 (29 August)

3 (30 August)

4 (31 August)

6 (2 September)

8 (4 September)

12 (8 September)

Soil sampling

Measurements

Day

1 (28 August, 2014)

2 (29 August)

3 (30 August)

4 (31 August)

6 (2 September)

8 (4 September)

12 (8 September)

Laboratory analysis

Measurements

Particle size analysis (Soil texture)

Clay

Silt

Sand

Gravel

ECe – dS/m

r – g/cm3

q – cm3/cm3

Results

Particle size analysis

Clay

Sand

Silt Gravel

q – cm3/cm3

DUALEM-1

0.5

1.5

Hcon

Pcon

Root zone

Profile

DUALEM-4

2.0

6.0

Vadose

Zone

Vadose

zone

DUALEM-2

1.0

3.0

Subsoil

Vadose

Zone

DUALEM421 ECa measurements (only day 1)

Results

DUALEM421 ECa (1mHcon – all days)

Day 1

Day 12

Results

Site 1 Site 2 Site 3 Site 4 Site 5

Estimated s

Day 1 s (mS/m)

versus q

Calibration

s (mS/m) versus q (cm3/cm3)

/ Validation

q (cm3/cm3)

s (m/Sm)

q (cm3/cm3)

q (cm3/cm3)

Day 1

Predicted

q verse soil texture

Loam Sandy Loam

Loamy sand

Deep drainage (?)

Day 1 Day 2 Day 3 Day 4 Day 6 Day 8 Day 12

Predicted

q

Available water content (~)

Day 1 - Day 12

Research Question

YES WE CAN use a

+


To generate EMCI to represent

time-lapse

soil moisture status


multiple array

EM4Soil

DUALEM-421

Conclusion

Research Question

Conclusions

EMCI is capable of predicting field-scale q

at any depth and on different days with one

predictive model and with sufficient

resolution and efficiency.

Implications including;

(i) improved timing of irrigations at

planting and germination,

(ii) evaluation of uniformity of irrigation

across a field, and

(iii) sufficient control of site-specific

irrigation to optimize water use

efficiency and match the leaching

requirement throughout a field.

Now you see it…now you don’t:

Time-lapse imaging of soil moisture

Huang J, Scudiero E, Clary W,

Corwin D, Triantafilis J

Published on-line

20 JUL 2016

Mapping soil moisture across an irrigated field

using electromagnetic conductivity imaging

Huang J, Scudiero E, Choo H,

Corwin DL, Triantafilis J

163, 285-294

Comp. Elect. Agric. 132, 76-85

Temperature-dependent hysteresis effects

on EM inudction instruments

Jingyi Huang, Budiman Minasny, Brett Whelan,

Alex B. McBratney, John Triantafilis

Monitoring soil water dynamics using electromagnetic

conductivity imaging and the ensemble Kalman Filter

Jingyi Huang, Alex B. McBratney,

Budiman Minasny, John Triantafilis

285, 76-93

549, 62–78

3D soil water nowcasting using electromagnetic

conductivity imaging and the ensemble Kalman filter

Jingyi Huang, Alex B. McBratney,

Budiman Minasny, John Triantafilis

Digital soil mapping of available water content using

proximal and remotely sensed data.

Huang, J, Davies, G.B., Bowd, D.,

Monteiro Santos, F.A., Triantafilis, J.

30, 139-151

An inversion approach to generate electromagnetic

conductivity images from signal data

Triantafilis, J.

Monteiro Santos, F.A.,

clay floodplains prior

stream

palaeochannel

clay floodplains prior

stream

palaeochannel

Env. Mod. Software 43: 88-95

Talk Outline

Quasi-3D modelling of dryland and irrigation salinity

using a DUALEM data and EM4Soil inversion modelling

Huang J, Kiliminster T, Zare E

Barrett-Lennard E, Monteiro Santos FA, Triantafilis J

Problem

Definition?

Materials and

Methods

EM4Soill


Conclusions

Problem definition (dryland salinity)

Significance of soil salinisation

In the wheat-sheep belt of WA a substantial

area of land is affected by dryland salinity,

due to saline shallow watertables.

This is because perennial native vegetation

that used most rainfall, replaced with annual

crops/pastures, that use less.

To understand limitation and determine best

management, concentrations of salt needs

determination with variation mapped.

Meredin WA: dryland salinity

Problem definition (dryland salinity)

This is because it is insidious

Meredin WA: dryland salinity

Problem definition (irrigation salinity)

Significance of soil salinisation

In many part of the highly productive

Murray-Darling Basin irrigation salinity, due

to saline shallow watertables.

This is because irrigation inefficiencies have

resulted in mobilisation of stored Aeolian,

cyclical and connate salts.

To understand limitation and determine best

management, concentrations of salt needs

determination with variation mapped. Bourke NSW: irrigation salinity

Problem definition (irrigation salinity)


Bourke NSW: irrigation salinity

Problem definition


Meredin WA:

Bourke NSW

dryland salinity

irrigation salinity

Problem definition (DSM)

Use of EM instruments and LR

Proximal EM instruments are being used

because they enable efficient mapping

without extensive soil sampling.

One approach is to make LR between ECa

and average ECe (e.g. 0-1.0 m) (e.g.

Amezketa and del Valle de Lersundi, 2008).

Another is to use ECa to make relationships

with ECe at various depths of interest. For

example (Yao and Yang, 2010).

Research Question

Can we use a

+


To generate quasi-3d EMCI

to represent

dryland and irrigation salinity status


multiple array

EM4Soil

DUALEM-1


Meredin WA

Bourke NSW

DUALEM-421


9.0 kHz

Geonics EM38

Geonics EM31

0-2.0 m

0-6.0 m

0-0.5 m

0-1.5 m

0-1.0 m

0-3.0 m

DUALEM-421

Theoretical depth of sa measurement

Average properties of dairy lagoon water

from March 2008 to June 2009 were:

• pH water is slightly alkaline (pH = 7.8)

• slightly saline ECiw (1.63 dS/m) and SARw

(4.3), water infiltration problems unlikely

DUALEM- 1 Survey

Area: 36 ha.

Sites: 10,000

Spacing: 20 m

Materials & methods (dryland salinity)

Soil sampling

Sites: 15 (7th percentile)

Depths: 0.00-0.25 m,

0.25-0.50 m,

0.50-0.75 m, &

0.75-1.00 m

Materials & methods (dryland salinity)

Materials & methods (irrigation salinity)

DUALEM-421 Survey

Area: 30 ha

Sites: 5,000

Spacing: 50 m

Materials & methods (irrigation salinity)

Soil sampling

Sites: 20 (5th percentile)

Depths: 0-0.3,

0.3-0.6 m,

0.6-0.9 m, and

0.9-1.2 m

Laboratory analysis

ECe – dS/m

Materials & methods

1mPcon

Results & Discussion (dryland salinity)

1mHcon

1mPcon

1mHcon

DUALEM- 1 Survey

Results & Discussion (irrigation salinity)

1mHcon 1mPcon

2mPcon

1mPcon

1mHcon

2mHcon

2mPcon

4mHcon

4mPcon

4mPcon

DUALEM-421 Survey

http://emtomo.com

EM4Soil

Quasi-2d and 3d inversion software

EM4Soil

Results & Discussion

Soil sampling and laboratory ECe Predicted s from EM4Soil modelling

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

s1

s2

s3

s4

s5

ECe1

ECe2

ECe3

ECe4

ECe5

ECe1

ECe2

ECe3

ECe4

ECe5

ECe1

ECe2

ECe3

ECe4

ECe5

ECe1

ECe2

ECe3

ECe4

ECe5

Validation

Quasi-3D MLR


0.00 - 0.25 m


0.25 - 0.50 m 0.50 - 0.75 m

0 - 2 dS/m

2 - 4 dS/m

16 - 24 dS/m


0 - 2 dS/m

2 - 4 dS/m

16 - 24 dS/m

Calibration


s (mS/m-1)

EC

e (m

S/m

-1)

ECe = 4.12 + 0.017 s

Validation

Quasi-3D MLR


0.75 - 1.00 m

0.00 - 0.25 m 0.25 - 0.50 m 0.50 - 0.75 m

4 - 8 dS/m

16 - 32 dS/m

> 32 dS/m


4 - 8 dS/m

16 - 32 dS/m

> 32 dS/m


Research Question

Conclusion

Meredin, WA

Bourke, NSW

Research Question

YES WE CAN use a


multiple array

Research Question

+


To generate quasi-3d EMCI

to represent

dryland and irrigation salinity status


multiple array

EM4Soil

DUALEM-1 DUALEM-421

Research Question

Conclusion

EMCI is a viable means of mapping ECe at

field scale with sufficient resolution and

accuracy for dryland/irrigation management.

Capability has ramifications including ability

to monitor salinity using time-lapse for;

(i) Revegetate landscape upslope, and

(ii) Rotation cropping to use water in

landscape year round.

Capability has ramifications including ability

to monitor salinity using time-lapse for;

(i) improved timing and uniformity of

irrigation across a field, and

(ii) sufficient control of site-specific

irrigation to optimize water use.

Meredin, WA

Bourke, NSW

Mapping salinity in three-dimensions

using a DUALEM-421 and EM inversion software

Zare, E., Huang, J.,


79, 1729-1740

Potential to map depth-specific soil OM across an olive grove

using quasi-2d and quasi-3d inversion of DUALEM-21 data

Huang J, Pedrera-Parrilla A, Vanderlinden K,

Taguas EV, Gómez, JA, and Triantafilis J

Catena, 152, 207-217

Inferring leachate plume preferential flow paths using a

DUALEM-421 and quasi-3 dimensional inversion model.

Triantafilis, J., Ribeiro J,

Page, D., and Monteiro Santos, F.A.

s = 22.5 P

lum

e

(2013) 12, 2.

Modelling coastal salinity using a

DUALEM-421 and inversion software.

Davies, G.B., Huang, J,


(2015) 424-431.

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