analysis of sediment yields within the auckland...

Analysis of Sediment Yields within the Auckland Region June TR 2009/064

Auckland Regional Council

Technical Report No.064 June 2009

ISSN 1179-0504 (Print)

ISSN 1179-0512 (Online)

ISBN 978-1-877528-76-7

Reviewed by: Approved for ARC Publication by:

Name: Amy Taylor Name: Grant Barnes

Position: Project Leader Land Position: Group Manager Monitoring and

Research

Organisation: Auckland Regional Council Organisation: Auckland Regional Council

Date: 27 May 2009 Date: 27 May 2009

Recommended Citation: Hicks, D.M.; Hoyle, J.; Roulston, H. (2009). Analysis of Sediment Yields within

Auckland Region. Prepared by NIWA for Auckland Regional Council. Auckland

Regional Council Technical Report 2009/064.

© 2008 Auckland Regional Council

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it are provided on an "as is" basis.

Analysis of Sediment Yields within the Auckland Region

D. M. Hicks

J. Hoyle

H. Roulston

Prepared for

Auckland Regional Council

NIWA Client report: CHC2009-041

May 2009

NIWA Project: ARC09501

National Institute of Water & Atmospheric Research Ltd

10 Kyle Street, Riccarton, Christchurch, 8011

P O Box 8602, Christchurch, 8440, New Zealand

Phone +64 3 348 8987, Fax +64 3 348 5548

www.niwa.co.nz

Contents

1 Executive Summary 8

1.1 Study objectives and approach 8

1.2 Mean annual basin sediment yields 8

1.3 Relationship between sediment yields and catchment characteristics 9

1.4 Magnitude-frequency relationships for storm sediment yields 9

1.5 Potential application of results 9

2 Introduction 10

2.1 Background and purpose 10

2.2 Objectives 10

3 Background Information 11

3.1 Catchment locations 11

3.2 Catchment characteristics 12

3.3 Data collected for sediment yield analysis 15

3.3.1 Mahurangi catchments - Wylie Road, Redwood Forest and Mahurangi College 15

3.3.2 Okura catchments – Awanohi Stream and Weiti Forest 19

3.3.3 Barwick catchment 24

3.3.4 Long Bay catchments – Lower Vaughan and Lower Awaruku 24

3.3.5 Mangemangeroa catchment 26

4 Analysis Methods 29

4.1 The sediment concentration rating approach 29

4.2 The storm event sediment yield rating approach 31

4.3 The Monte Carlo approach 33

4.4 Determining magnitude-frequency relationships for event sediment yields 34

5 Results 35

5.1 Rating relationships 35

5.2 Sediment yields 35

5.3 Annual yield variability 38

5.4 Sediment yield vs. catchment characteristics 41

5.5 Application of results and recommendations for further sediment monitoring 43

5.6 Event-yield magnitude-frequency relations 43

6 Conclusions 45

7 References 46

8 Appendix 1: Time series and rating plots 48

8.1 Wylie Rd 48

8.1.1 Time series plots 48

8.1.2 Sediment concentration rating 49

8.1.3 Event sediment yield rating 49

8.2 Redwood Forest 50




8.3 Mahurangi College 54




8.4 Awanohi Stream 58




8.5 Weiti Forest 61




8.6 Barwick 64



8.7 Lower Vaughan – Long Bay 66




8.8 Lower Awaruku – Long Bay 71




8.9 Mangemangeroa 76




9 Appendix 2: Monthly sediment yields 81

9.1 Wylie Rd 81

9.1.1 Derived from sediment concentration rating 81

9.1.2 Derived from event yield rating 81

9.2 Redwood Forest 82



9.3 Mahurangi College 83



9.4 Awanohi Stream 85



9.5 Weiti Forest 86



9.6 Barwick 86


9.7 Lower Vaughan – Long Bay 87



9.8 Lower Awaruku – Long Bay 88



9.9 Mangemangeroa 89



Reviewed by: Approved for release by:

Andrew Swales Jochen Schmidt

Analysis of Sediment Yields within the Auckland Region 8

1 Executive Summary

1.1 Study objectives and approach

Measurements of suspended sediment yields during storms at nine basins in

Waitemata Formation terrane under various land uses in the Auckland region were

analysed to determine event sediment yields and mean annual sediment yields. The

mean annual yields were estimated using three approaches: (i) by developing

suspended sediment concentration vs. water discharge ratings and combining these

with the water discharge record; (ii) by developing event sediment yield vs. event peak

water discharge ratings and combining these with a peaks-over-threshold series of

peak discharges extracted from the discharge record; and (iii) by a Monte Carlo

approach that combined the event sediment yield vs. peak discharge rating with

repeated samplings of the event peak-discharge magnitude-frequency distribution for a

standard 20-year period.

1.2 Mean annual basin sediment yields

During their respective periods of data collection, the basin specific annual average

sediment yields (averaged from the estimates from the three analysis approaches)

were:

Wylie Road (pastoral) 200 ±2 t/km2/yr (1.28 years of flow data)

Redwood Forest (exotic forest, before

harvesting)

172 ±19 t/km2/yr (2.68 years of flow data)

Redwood Forest (exotic forest, post

harvesting)

241 ±35 t/km2/yr (0.98 years of flow data)

Mahurangi College (pastoral) 88 ±19 t/km2/yr (26.25 years of flow data)

Awanohi Stream (native vegetation) 74 ±12 t/km2/yr (6.25 years of flow data)

Weiti Forest (exotic vegetation) 82 ±13 t/km2/yr (0.56 years of flow data)

Barwick (urban) 13 t/km2/yr (0.48 years of flow data)

Lower Vaughan-Long Bay (pastoral) 98 ±18 t/km2/yr (6.07 years of flow data)

Lower Awaruku-Long Bay (urban) 40 ±11 t/km2/yr (3.25 years of flow data)

Mangemangeroa (pastoral) 89 ±7 t/km2/yr (8.10 years of flow data)

The 27 year flow record at the Mahurangi College site enabled an estimate of annual

variability in sediment yields due to inter annual hydrological variability. This showed


annual sediment yield ranging over a factor-of-ten, with the three-year running-average

yield ranging over a factor-of-four.

1.3 Relationship between sediment yields and catchment characteristics

A correlation and multiple-regression analysis indicated that the variation in specific

sediment yield (SSY) in the dataset is due mainly to catchment rainfall (R), mean slope

(S), and land use. A predictive derived model is:

SSY (t/km2/yr) = (R (mm/yr) x S) ( 0.0035 %P + 0.0023 %F+ 0.00084 %U)

where %P, %F, and %U are the percentages of the catchment under pasture, mature

forest (whether native or exotic), and urbanised, respectively. This indicates that for a

given rainfall x slope product, the yields from forested areas are 2/3 those from pasture

areas, while the yields from urbanised areas are ¼ of those from pasture areas. A

comparison of yields from Redwood Forest between pre- and post-harvesting periods

showed that the forest harvesting increased the sediment yield by approximately 40%.

1.4 Magnitude-frequency relationships for storm sediment yields

A comparison of the event-yield magnitude-frequency relationships for all but the

Barwick catchment (which had too little data) showed that generally, the specific

sediment yields of events of given return period show similar variations among

catchments as do the average annual yields described above. The Mangemangeroa,

Vaughan, and Awaruku catchments showed sharply reduced event yields from events

with return periods smaller than about 3 months, suggesting either erosion threshold

or sediment exhaustion effects operating in these catchments.

1.5 Potential application of results

While the above results are based on only nine basins, most are statistically significant.

The study therefore offers promise that a model such as the one above, ideally

calibrated with more data, could provide the basis for a land use and rainfall driven

proxy for monitoring potential changes in sediment yield in the Auckland region. We

recommend ongoing sediment monitoring of sediment yield at a small number of key

sites in order to validate such predictions. Since all the study basins are formed in

Waitemata Formation terrane, the results may not apply to other lithologies, thus we

also recommend that sediment monitoring be extended to secure results for other

lithologies.


2 Introduction

2.1 Background and purpose

Sustainable management of the Auckland region’s land and aquatic environment

requires ongoing monitoring of various environmental parameters. Sediment in

receiving-water bodies is of concern, thus monitoring of sediment loads and yields is

required to identify and quantify its sources, manage its effects, and to measure trends

and the effectiveness of management measures. Since it is a prohibitive undertaking

to continuously monitor sediment in every basin across the region, an alternative is to

develop an understanding of how sediment yields vary with differing land use and

basin hydrological and physical characteristics and from this sediment yield on a

regional basis can be proxied by monitoring land use and hydrological parameters such

as rainfall or runoff.

Towards this understanding, this report presents results from sediment yield studies at

nine catchments under various land uses in the Auckland region. The basins are (Figure

1, Table 1): Wylie Road, Redwood Forest, Mahurangi College, Awanohi Stream, Weiti

Forest, Barwick, Lower Vaughan–Long Bay, Lower Awaruku–Long Bay, and

Mangemangeroa. Catchment areas range from 0.2 to 48.8 km2.

This report is intended to supplement and update an investigation into sediment yields

from five different catchments within the Auckland region conducted in 1994 (Hicks,

1994).

2.2 Objectives

The objectives of the study are to:

• Determine mean annual sediment yield over the period of flow record for each of

the nine basins, and provide estimates of the yield averaged over a longer

reference period.

• Determine magnitude/frequency relationships for event sediment yields over the

sampling period for each of the nine basins.

• Collate or extract information on catchment slope, land-cover, land use, and

mean annual rainfall, and report with sediment yield results for each of the nine

basins.

• Provide a preliminary analysis of relationships between mean annual sediment

yield and event sediment yield in terms of catchment characteristics, including

rainfall, runoff, slope, land use, and lithology.


3 Background Information

3.1 Catchment locations

Figure 1 Overview map of study catchment locations within the Auckland region


Table 1 NZTM coordinates of flow recorders in each catchment

Catchment Flow Recorder No. Easting Northing

Wylie Rd 6809 1746064 5968472

Redwood Forest 6810 1746347 5964219

Mahurangi College 6806 1748394 5969860

Awanohi Stream 7502 1751391 5938694

Weiti Forest 7505 1751872 5940969

Barwick 7214 1755483 5944045

Lower Awaruku – Long

Bay

7513

1756104 5938044

Lower Vaughan – Long

Bay

7506

1755415 5938716

Mangemangeroa 8304 1772331 5910516

3.2 Catchment characteristics

This section outlines key characteristics specific to each of the catchments examined

in this report. GIS techniques have been used to calculate catchment area and extract

representative measures of catchment lithology, land use, slope, mean annual rainfall

and runoff.

The boundary shapefiles for each catchment were provided by ARC, with the

catchment boundaries defined as the contributing area upstream of the flow recorder

relevant to each catchment (Table 1). The catchment areas are given in Table 2.

Catchment lithology data have been calculated from the Land Resource Inventory (LRI)

shapefile. The LRI shapefile was re-projected to the NZTM coordinate system and was

then intersected with each of the catchment boundary shapefiles. The resultant

shapefile provided areas of ‘Top rock’ geology contained in each study catchment. The

classes used in Table 2 are based on the North Island Rock Type Classification (Edition

1).

The land use breakdown was supplied by ARC and is based on the Land Cover

DataBase (LDCB), with either the LDCB1 (1996/1997) or LDCB2 (2000/2001) used,

depending on the time of sediment data collection. The relevant LCDB shapefile was

re-projected to the NZTM coordinate system and this was then intersected with the

catchment boundary shapefiles. The resultant shapefile provided areas of each land

cover in each study catchment. All lithologies and land uses present in each catchment

are listed in Table 2.

Catchment slope data were calculated by creating a slope surface in ArcGIS using the

Digital Elevation Model (DEM.img) provided by ARC. A cell size of 2m X 2m was

preserved during this process. Slope has been calculated as rise/run, (i.e. a slope of 1

equals 45o). Zonal statistics (mean, maximum, minimum and standard deviation) were

generated from this slope surface for each study catchment.


Mean annual rainfall data were calculated by creating a rainfall surface from the text

file provided by ARC. Figure 2 provides a representation of this rainfall surface. The

text file contained coordinates (in NZMG) with annual rainfall data in mm/yr. The rainfall

surface has a cell size of 1200m X 1200m and was re-projected into NZTM. Zonal

statistics were generated from this surface for each study catchment.

Mean annual runoff was calculated based on the mean water discharge over the

period of the flow record (in m3/s), divided by the catchment area (in m2), and

multiplied by the number of seconds in a year. This is multiplied by 1000 to give runoff

in mm/year.

The derived catchment characteristics are summarised in Table 2.

Figure 2 Mean annual rainfall in mm/year over the Auckland region Mean Annual Rainfall

1000

1100

1200

1300

1400

1500

1600

1700

1800

1900

Analysis of Sediment Yields within Auckland Region 14

Table 2 Summary of catchment characteristics

Wylie Road Redwood M. College Awanohi Weiti Barwick L. Vaughan L. Awaruku

Mangemangeroa

Catchment Area

(km2) 1.05 0.6 48. 5.27 1.70 0.24 2.17 2.66 4.44

Lithology (dominant) Sandstone

or coarse

siltstone

(100%)

Sandstone

or coarse

siltstone

(100%)

Sandstone

or coarse

siltstone

(83%),

Alluvium

(9%)

Sandstone

or coarse

siltstone

(81%),

Sheared

mixed

lithologies

(10%)

Mudstone

or fine

siltstone -

banded

(43%),

Sandstone

or coarse

siltstone -

banded

(21%)

Sandstone

or coarse

siltstone

(100%)

Sandstone

or coarse

siltstone

(89%),

Alluvium

(8%)

Sandstone or

coarse

siltstone

(91%)

Sandstone or

coarse siltstone

(100%)

Land use

Exotic vegetation 4.4 % 99.2 % 23.5 % 9.4 % 83.3 % 11.6 % 1.6 % 3.3 %

Horticulture 0.5 % < 0.1 %

Native vegetation 12.0 % 0.8 % 21.1 % 55.4 % 2.2 % 7 % 23.5 % 9.2 % 38.0 %

Pastoral 83.6 % 53.8 % 35.1 % 14.5 % 60.9 % 8.6 % 58.1 %

Urban 1.0 % 93 % 4.0 % 80.7 % 0.6 %

Other < 0.1 % < 0.1 %

Catchment Slope

(m/m)

Mean 0.32 0.40 0.27 0.32 0.25 0.22 0.24 0.19 0.29

Maximum 1.24 2.33 6.75 11.16 1.37 1.11 1.79 1.67 30.45

Minimum < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01

SD 0.15 0.2 0.22 0.19 0.15 0.15 0.17 0.15 0.28

Mean Annual Rainfall

(mm/yr) 1570 1483 1591 1221 1226 1224 1202 1199 1177

Mean Annual Runoff

(mm/yr) 1079 677 750 266 606 229 626 841 347


3.3 Data collected for sediment yield analysis

This section outlines the type of data collected in each catchment, when it was

collected, how it was collected, and the reason for sampling. The catchments have been

grouped into sub-regional groups, as catchments within each sub-region tend to have

the same method and reason for sampling. A timeline showing when the various types

of data were collected for each catchment is presented in Figure 3. A summary of the

total span of record for the sediment concentration, flow and rainfall data in each

catchment and the number of years of flow data available within that period of record

(i.e., period of record minus gaps in record) is presented in Table 3. Time-series plots of

water discharge and suspended sediment concentration at each site are included in

Appendix 1.

3.3.1 Mahurangi catchments - Wylie Road, Redwood Forest and Mahurangi College

The 48.83 km2 Mahurangi College catchment has a mixed land use. While pastoral

farming predominates, there are scattered patches of native bush and scrub, a

significant pine plantation, and an urban area (the Warkworth township). Wylies Road

and Redwood Forest are essentially single land use sub catchments of the larger

Mahurangi College catchment (Figure 4). The 1.05 km2 Wylies Road sub catchment is

pastoral (mostly sheep and beef farming). The 0.6 km2 Redwood Forest sub catchment

is within a commercial pine forest (classed as exotic vegetation) and was harvested

during the monitoring period, as detailed below.

Various studies relating to sediment yield have been conducted on these catchments. In

all cases, automated samples of suspended sediment were drawn from the stream,

collected as composited samples with 8 sub-samples to the bottle. Bottles are changed

when a trigger volume is reached and thus the bottles contain samples collected over

differing periods of time, depending on the stream flow. These samples can be

described as flow proportional sediment samples.

The Mahurangi Modelling Study was conducted to quantify sediment and other

contaminant output from the Mahurangi catchment to the Mahurangi Estuary. At the

beginning of 1994, ARC Environment and NIWA Ecosystems set up representative

catchment sites at the Mahurangi College, Wylie Road and Redwood Forest sites, along

with sampling stations in the harbour. The aim of this investigation was to collect data

from the catchment sites in order to calibrate a catchment model known as Basin New

Zealand (BNZ), while at the same time to collect water quality data in the harbour to

calibrate a hydrodynamic model known as System 21. These models were developed to

assist with planning and resource management decisions. Sediment samples were

collected simultaneously in all three catchments between July 1994 and June 1995. The

sampling methodology and a selection of the results from the Redwood Forest site are

presented in Becker and Ridley (1995), with further findings presented in Stroud and

Cooper (1997). In summary from these reports, the suspended sediment load for the


Wylies Road catchment (241 t/km2) was higher than that measured in the Redwood

Forest catchment (146 t/km2).


Figure 3 Periods of time over which sediment concentration, flow and rainfall data are available for each catchment

Continues

to 1921

1/0

1/1

982

1/0

1/1

984

1/0

1/1

986

1/0

1/1

988

1/0

1/1

990

1/0

1/1

992

1/0

1/1

994

1/0

1/1

996

1/0

1/1

998

1/0

1/2

000

1/0

1/2

002

1/0

1/2

004

1/0

1/2

006

1/0

1/2

008

Sediment

Flow

Rainfall Mangemangeroa

Barwick

Lower Vaughan

Wylie Rd

Redwood Forest

Awanohi

Weiti Forest

Mahurangi

Lower Awaruku


Figure 4 Aerial photograph (2006) and catchment boundaries of the Mahurangi College

catchment and the Wylie Road and Redwood Forest sub-catchments. The flow recorders

identified are at the downstream end of each catchment.

A study was also made of the sedimentation history and present day sedimentation

processes in the Mahurangi Estuary to determine how the estuary has responded to

historical changes in catchment sediment loads associated with landcover changes

following human settlement (Swales et al., 1997). The historical component of this

investigation included probing and coring the sediment column, stratigraphic analysis

of the cores, assessing channel infilling from historical soundings, determining

sediment accumulation rates from core stratigraphy and radiocarbon and pollen dating,

examining records of historical landcover, and estimating estuary sedimentation loads

from estuary infilling. These loads were compared with present day loads as computed


using the BNZ model described above. In summary, the estuary sedimentation load

deposited in the lower estuary since 1900 AD was found to average 702

tonnes/km2/yr, whereas the catchment suspended sediment load for the 20 years

preceding the report (1977-1997) averaged 448 tonnes/km2/yr.

In the 0.6 km2 Redwood Forest catchment, the sediment data were collected to

monitor the effects of the disturbance caused by roading and then logging on the

sediment loads carried by the Redwood Stream. Roading and salvage logging of the

basin commenced on 20 January 1997. General log harvesting commenced on 9 April

1997 and was completed on 11 February 1998. There were two periods of data

collection: the first (between May 1994 and July 1996) was in the pre harvest period

during which 546 bottles were collected and analysed for suspended sediment

concentration; the second was during the harvest period (between February 1997 and

March 1998) when 43 samples were collected and analysed for suspended sediment

concentration. Hicks and McKerchar (2000) observed no significant difference in

sediment concentration rating curves for the pre-harvest and harvesting periods, but

they did not examine event sediment yields.

For the Mahurangi College and Wylies Road catchments, the sediment concentration

data used in this study are essentially those obtained for the Mahurangi Modelling

Study over 1994/1995. During the sampling period, 21 flood events were captured in

the Wylies Road catchment and 34 in the Mahurangi College catchment. The additional

work carried out in the Redwood Forest catchment has provided a longer record of

sediment concentration data, with data available from 1994 – 1998 (Table 3).

Mahurangi has the longest flow record of all the catchments analysed in this study,

running from 11 June 1982 to 8 September 2008 with no gaps in the data record.

Redwood Forest has flow data collected over 4 years (from 10 May 1994 to 8 April

1998) with significant gaps (i.e., exceeding one week) between 22/5/1997 – 7/7/97 and

27/1/98 – 2/3/98. Wylie Road has a relatively short flow record from 19 April 1994 to 31

July 1995, but there are no gaps in this record.

3.3.2 Okura catchments – Awanohi Stream and Weiti Forest

The Awanohi Stream and Weiti Forest catchments described in this study both drain

into the Okura Estuary. The 5.27 km2 Awanohi catchment is predominantly a mixture

of pastoral land and native bush and scrub (Figure 5). Two hundred and twenty-eight

discrete sediment samples were collected in this catchment using an automatic Isco

sampler between February 2004 and October 2005. Twelve events occurred during

this period, with peak discharges ranging from 189 to 19,655 l/s. The 1.7 km2 Weiti

Forest catchment is predominantly an exotic pine forest catchment with some pastoral

land (Figure 6). Ninety-eight discrete sediment samples were collected in this

catchment using an automatic Isco sampler between April and


Table 3 Data availability for the study sites. The second column shows the number of years of

flow record, excluding gaps, and the number of runoff events for which there is sediment

concentration data adequate for determining event sediment yield. The span of record indicates

the beginning and end dates of data collection.

Data by

Catchment

No.

years/events Span of Record Comment

Wylie Rd

Sediment data 21 events May-94 Jul-95

Sediment samples are composited 8 sub samples

to the bottle.

Flow data 1.28 yrs Apr-94 Jul-95

Rainfall Aug-94 Aug-95 Site - Mahurangi at Wylie Rd

Redwood Forest

Sediment data 34 events May-94 Mar-98


to the bottle.

Flow data 3.67 yrs May-94 Apr-98 Level and flow rating in Hydstra and Tideda.

Rainfall Aug-94 Aug-01

Site - Mahurangi at Walkway. Good correlation

with nearby Mahurangi at Satellite dish.

Mahurangi

College

Sediment data 34 events Apr-94 Jul-95


to the bottle.

Flow data 26.25 yrs Jun-82 Sept-08 Level and flow rating in Hydstra

Rainfall - Dec-94 Sep-08

Sites - Mahurangi at Satellite Dish and Mahurangi

at Sewage Treatment. There is also a composite

record back to 1921.

Awanohi Stream

Sediment data 12 events Feb-04 Oct-05

Discrete sediment samples collected using Isco

sampler.

Flow data 6.25 yrs Jul-98 Oct-08

The flow site closed from March 1999 to March

2003.

Rainfall Sep-03 Nov-08 Site – Awanohi

Weiti Forest

Sediment data 6 events Apr-08 Jul-08


sampler.

Flow data 0.56 yrs Apr-08 Nov-08 90 degree v-notch weir

Rainfall Sep-03 Nov-08 Site – Awanohi.

Barwick

Sediment data none Sep-07 Dec-07


sampler.

Flow data 0.48 yrs Aug-07 Feb-08

Pipe flow - stormwater system - Unidata sensor

used to measure velocity and depth

Rainfall Aug-07 Aug-08 Site – Barwick

Lower Vaughan

Sediment data 15 events Jan-01 Oct-05


sampler.

Flow data 6.07 yrs Dec-00 Nov-08 Site closed between Aug 2001 and June 2003.

Rainfall Jul-97 Oct-07 Site - Glamorgan School. North Shore city gauge

Lower Awaruku

Sediment data 16 events Dec-00 Oct-05


sampler.


Flow data 3.25 yrs Nov-00 Oct-05

ARC site closed, NSC site data now used from

weir site upstream.

Rainfall Jul-97 Oct-07 Site - Glamorgan School. North Shore city gauge.

Mangemangeroa

Sediment data 57 events Nov-00 Mar-04

Calibrated turbidity sensor data collected by

Andrew Swales, NIWA.

Flow data 8.10 yrs Jul-00 Oct-08 Site 8304.

Rainfall Oct-01 Oct-08 Site 649937.

Figure 5 Aerial photograph (2006) and catchment boundary of the Awanohi Stream catchment.

Flow recorder 7502 is at the downstream end of the catchment.


Figure 6 Aerial photograph (2006) and catchment boundary of the Weiti Forest catchment. Flow

recorder 7505 is at the downstream end of the catchment.


July 2008 (which is a limited record). Six events occurred during this period, with peak

discharges ranging from 60 to 2,614 l/s. Flow data is available from 20 July 1998 to 1

October 2008 in the Awanohi catchment; however, the flow site was closed between

22/3/1999 and 4/3/2003, leaving a 4-year gap in the record. The Weiti catchment has a

relatively short flow record from 14 April 2008 to 6 November 2008, but there are no

gaps in this record. The V-notch weir installed at the Okura – Weiti Stream flow

recording station can be seen in Figure 7.

A previous sediment yield related study was undertaken in the Okura region in 1999.

This aimed to predict the risks of ecologically damaging sediment events occurring in

the estuary as a consequence of land disturbance associated with varying degrees of

rural intensification. Various aspects of this investigation and their findings are

presented in reports by Stroud et al. (1999), Norkko et al. (1999), and Green and

Oldman (1999). Stroud et al. (1999) used the computer simulation model WAM

(Watershed Assessment Model) to make predictions of sediment input to the Okura

Estuary from the surrounding Okura catchment (covering both the Weiti and Awanohi

sub-catchments). WAM is a physically based model that does not need calibration, and

therefore no sediment concentration data were collected in the Weiti Forest or

Awanohi Stream catchments as part of that Okura study (Stroud et al., 1999).

Figure 7 Photograph of the V-notch weir at the Okura – Weiti Stream flow recording station (site

no. 7505).


3.3.3 Barwick catchment

Barwick Estate is a small (0.24 km2) urban subdivision catchment that forms part of the

larger Whangaparoa catchment (Figure 8). Discrete sediment samples were collected

in this catchment using an automatic Isco sampler for the very short period between

September and December 2007. A continuous record of flow data is available over a

slightly longer period from 9 August 2007 to 1 February 2008. These data were

collected as part of an investigation to improve information on sediment entering

stormwater systems from small-lot developments (Hope, 2007). The aim was for data

to be collected over two periods: prior to the housing development and then during the

development process. The report provided by Hope (2007) only covers the period prior

to housing development while the catchment was in a grassed or ‘capped’ state, and 9

events are described. The data made available by the ARC for the present investigation

comprises a total of 44 samples, including 6 events. While the period of data collection

is essentially the same as that described in the Hope (2007) report, there appears to be

some discrepancy between the data used. Three of the events described in the Hope

(2007) report feature in the data provided (16/9/07, 18/10/07 and 6/12/07); however,

the remaining events described (2 in August and 4 in October) were not included in the

data provided for the present study. The limited sediment concentration data available

in the catchment prevented an event yield analysis; however, a sediment

concentration rating was established (see Sections 4 and 5.1).

3.3.4 Long Bay catchments – Lower Vaughan and Lower Awaruku

The 2.17 km2 Lower Vaughan and 2.66 km2 Lower Awaruku catchments sit adjacent to

each other in the Long Bay area (Figure 9). The Lower Vaughan is mainly pastoral, with

some native forest, while the Lower Awaruku is largely urban but has some native

forest and pasture. An initial sediment sampling program for this pair of catchments

was conducted by the Environmental Services section of the ARC during 2000 - 2002

in order to establish a means of determining the effects of future land use change in

this area. Results from this early investigation are presented in a draft report titled

‘Sediment Report.doc’ (author and date unknown). In both catchments, sediment

concentrations were only observed to be significant above a threshold flow (5.0 m3/s in

the Lower Vaughan and 5.5 m3/s in the Lower Awaruku), and an insufficient number of

events above the threshold flow occurred during the 2000-2002 sampling period. Since

that early report, additional flow and sediment data have been collected, and the

present report provides results from the full dataset.

In the Lower Awaruku catchment, a total of 258 discrete sediment samples were

collected between December 2000 and October 2005 using an automatic Isco

sampler. These samples cover 16 flood events with peak discharges ranging from

1462 to 8120 l/s. Events 2 – 4 were discarded during the data analysis as there were

insufficient sediment samples or sediment samples were not collected during the peak

of the flood. Flow data for this catchment is available between 1 November 2000 and 7

October 2005, with a gap between 21/3/02 and 26/11/03. In the Lower Vaughan

catchment, a total of 298 discrete sediment samples were collected between January

2001 and October 2005 using an Isco sampler. These samples cover 15 flood events


with peak discharges ranging from 171 to 13368 l/s. Flow data for this catchment is

available between 21 December 2000 and 5 November 2008, with a gap between

24/8/01 and 13/6/03.

Figure 8 Aerial photograph (2006) and catchment boundary of the Barwick catchment. Flow

recorder 7502 is at the downstream end of the catchment.


Figure 9 Aerial photograph (2006) and catchment boundaries of the Lower Awaruku and Lower

Vaughan catchments in Long Bay. Flow recorder sites 7506 and 7513 are at the downstream

ends of their respective catchments.

3.3.5 Mangemangeroa catchment

The 4.44 km2 Mangemangeroa catchment is located approximately 18 km east of

Auckland City. The catchment land use is predominantly a mixture of pasture and

native bush and scrub (Figure 10). Changes to the Manakau City Proposed District Plan

have allowed subdivision of this catchment, and its use is beginning to change from


farmland to lifestyle blocks of about 0.5–2 Ha. The Mangemangeroa Creek is one of

three tidal creeks that discharge to Whitford Bay.

Several earlier studies have investigated sediment yields from the Mangemangaroa

catchment. Heighway (1999) studied the effect of urban intensification on sediment

yields. This showed a quick response to storm runoff in the Mangemangeroa

catchment, with suspended sediment levels reduced to pre-storm levels within hours

and baseflow stream levels recovered after 9-10 hours. This study also stated that

suspended sediment levels in the stream are typically very low in comparison to other

studies (but it was unclear which studies Heighway was referring to). Oldman and

Swales (1999) used results from the BNZ model to examine the sediment loads that

would be delivered to the Mangemangeroa Creek estuary under allowable land use

development scenarios. The load results were then used with a numerical model to

predict sedimentation patterns in the estuary. The BNZ modelling predicted that

median erosion losses would be 8,480 tonnes/year under the existing land use from

the total catchment of the estuary.

The sediment data used in the present study were collected between November 2000

and March 2004 by Andrew Swales of NIWA, Hamilton, and Auckland Regional Council

Environmental Services, and is a different dataset to that used in either of the studies

described above. A hydrometric station was established above the tidal reach in a 4 m

wide, straight channel section of the Mangemangeroa Creek. The main record of

sediment concentration was secured with a Downing Model-3 optical backscatter

sensor (OBS) that was mounted 0.35 m above the bed. This provided a burst-averaged

record every 10 minutes. An Isco auto-sampler was used in flow-proportional mode

during storm runoff to collect samples beside the sensor in order to derive a calibration

relationship between the burst-averaged OBS sensor output and suspended sediment

concentration. The calibration samples were analysed for total suspended sediment

concentration and particle size, which was determined using a time-of-transition

stream-scanning laser particle-sizer. The OBS was calibrated using the ≤ 63 µm (silt-

clay) fraction concentration from the stormwater samples, and a separate relation was

obtained between silt-clay concentration and total sediment concentration based on

the particle size analysis results. Flow data is available between 14 July 2000 and 22

October 2008, with a gap between 2/3/2004 and 6/5/2004.


Figure 10 Aerial photograph (2006) and catchment boundary of the Mangemangeroa catchment.

Flow recorder 8304 is at the downstream end of the catchment.


4 Analysis Methods Three approaches were used to establish mean annual sediment yields for the nine

catchments in this investigation. The first was to establish a ‘sediment concentration

rating’ relationship between instantaneous suspended sediment concentration and

water discharge. The second was to determine an ‘event yield rating’ relationship

between individual event sediment yields and event hydrological magnitude (indexed

by event peak discharge). These two ratings were then applied across the full period of

flow record. The third approach was based on the event yield ratings, but employed a

Monte Carlo technique to make repeated estimates of the sediment yield over a 20-

year reference period. Further details on each approach are given below.

4.1 The sediment concentration rating approach

For each of the catchments with discrete sediment concentration records (Awanohi

Stream, Lower Vaughan – Long Bay, Lower Awaruku – Long Bay, Barwick and Weiti

Forest), the sediment concentration rating relationship was established by plotting

instantaneous suspended sediment concentration (SSC) versus instantaneous water

discharge (Q). This rating was then applied to the water discharge record to integrate

the sediment yield over the period of flow record. The sediment yield was also

integrated only during quickflow periods, as defined in section 4.2.

In the case of the Mangemangeroa catchment, the burst-averaged optical backscatter

records were converted to SSC using Equations 1 and 2 below (Andrew Swales,

NIWA, pers comm.).

973.49*347.0 avgsilt OBSC Equation 1.

silttotal CSSC *73.1 Equation 2.

where Csilt is the concentration of the suspended silt-clay fraction in mg/l, OBSavg is

OBS sensor output in mV, and SSCtotal is the total suspended sediment concentration

in mg/l. Equation 1 is the average of three calibrations undertaken during the

monitoring period. The three calibration relationships showed negligible variation in the

slope and constants, with R2> 0.99 in all cases. The maximum Csilt recorded was 1800

mg/l.

A variation on the instantaneous rating approach was needed for the Mahurangi

College, Redwood Forest, and Wylie Road catchments since at these sites composite

automatic sampling was employed. This meant that 8 sub-samples were composited

on a flow-proportional basis into each sample bottle, with each sub-sample triggered

when a fixed volume of water had passed by the site. Thus, the SSC of the total

sample in a sample bottle represents the flow-weighted SSC over the time required to

collect the 8 sub-samples into the bottle, and hence SSC was plotted against the mean

water discharge over the time required to collect the 8 sub-samples. When the rating


curve was applied to predict SSC during the process of calculating sediment yield, it

was therefore necessary to apply it in a way consistent with how it was derived. Thus,

sediment yield was integrated in steps of equal discharge volume through the flow

record, and the mean discharge over each step was input to the rating curve.

In the case of Redwood Forest, separate sediment rating curves were developed for

the pre-harvesting and post-harvesting periods (i.e., before and after 20 January 1997).

A LOWESS (Locally-Weighted Scatterplot Smoothing) approach was used to fit the

ratings for each catchment, with the LOWESS ratings represented by a series of

power step-functions. Since the data were transformed to their logarithms for curve-

fitting, the LOWESS curve was adjusted for log-transformation bias using the approach

of Ferguson (1986). This adjustment scales with the exponential of the local standard

error of the curve-fitting in log units, and was calculated during the LOWESS fitting

process (in a process similar to that detailed by Hicks et al., 2000). An example

LOWESS-fit rating curve for Mahurangi at College site is shown in Figure 11.

Approximating the bias-adjusted LOWESS curves with step-functions simplifies the

calculation of yields and induces no significant error.

In all cases, the residuals of the observed log SSC values compared to the log SSC

values predicted by the LOWESS fit were examined for normality and for a time trend.

Inspection of the event yield rating plots in log-log space showed that the residuals

(i.e., log of observed event yield minus log of predicted event yield, or log of the ratio

of observed to predicted yield) were homoschedastic with peak discharge (i.e., the

scatter was of similar magnitude irrespective of peak discharge). Normality was

evaluated with the Kolmogorov-Smirnov test at the 5% significance level, while a time-

trend was evaluated by testing the hypothesis that the coefficient on a linear relation

between log(observed/predicted event yield) was significantly different from zero at

the 5% significance level. No trend is indicated if the coefficient is not significantly

different from zero.


Figure 11. Example of a suspended sediment concentration rating from Mahurangi College

catchment. The rating applied is a bias-corrected Lowess fit rating.

Mahurangi at College

1

10

100

1000

10000

1 10 100 1000 10000 100000 1000000

Flow (l/s)

SS

C (

mg

/l)

SSC (mg/l)

Bias-correceted Lowess rating

4.2 The storm event sediment yield rating approach

The sediment concentration records for all catchments in this study were patchy,

either in terms of there being gaps in the data (i.e., not all runoff events were sampled)

or in terms of data quality (e.g., too few samples during a runoff event). Accordingly,

the strategy was to accurately measure the sediment yield from storm runoff events

with adequate data, and from these determine relationships between storm sediment

yield and an appropriate index of event hydrological magnitude (such as peak flow or

event runoff). The approach varied depending on whether the sediment concentration

record comprised discrete measurements or was a composited record.

For each of the catchments with discrete sediment concentration records (Awanohi

Stream, Lower Vaughan – Long Bay, Lower Awaruku – Long Bay, Barwick and Weiti

Forest), individual storms with sufficient sediment concentration data were identified.

Typically, we then added synthetic SSC data points to the beginning and end of the

events, since the auto samplers usually missed sampling these (if we did not add

these synthetic values, the TIDEDA software could interpolate high SSC values

between adjacent events). The SSC values we assigned to the start and end of events

were based on an appreciation of the typical concentrations at the tails of storm events

at a given site.

The times for the beginning and end of events were based on the beginning and end

of quickflow. Quickflow is the part of the water runoff from a rainstorm that moves

quickly through a basin; the remainder of the runoff, termed the ‘delayed flow’, arrives

in the stream channels more slowly after moving through the ground and other areas

of temporary storage. Following the procedure of Hewlett and Hibbert (1967),

hydrographs were examined to assess the typical quickflow separation slope for each

site. Also, a minimum value of quickflow runoff was set for each site in order to


discard tiny quickflow ‚events‛ generated by noise in the stage record. This approach

provides an objective, repeatable way of identifying the beginning and end of storm

events and for deciding whether a multi-peak hydrograph represents one event or

several. The same approach was used for generating series of events when the event

ratings were applied to determine mean annual sediment yields. The quickflow

separation slopes and event runoff minima are included in Table 5.

The sediment yield over discrete events was computed by direct integration of the

sediment concentration and discharge records using the PSIM module of the TIDEDA

hydrological software package. The PSIM module was also used to extract various

hydrological measures of each event, including the peak discharge.

A different procedure for determining event sediment yields was used for the

catchments with composited samples (Mahurangi College, Redwood Forest, and

Wylie Road). This involved making a plot of the time-cumulative load represented by

each sample bottle (for each bottle, this equalled the measured SSC x the mean water

discharge over the compositing period x the duration of the compositing period). This

cumulative plot was then interpolated at the beginning and ends of storm runoff

events, with the differences indicating the event sediment yields.

At the Mangemangeroa catchment, we simply used results on event sediment yields

provided by Andrew Swales (NIWA, Hamilton, pers. comm.).

For each catchment, the event sediment yields were plotted against peak discharge

(l/s), quickflow runoff (mm), and total runoff (mm). The storm sediment yields were

found to correlate best with the storm peak discharge, as has been found in previous

studies of a similar nature (Hicks, 1990). Usually, the event yield vs. peak discharge

relationship was represented best by a power-law regression. The exceptions were

Awanohi and Lower Awaruku, which were generally better represented by a linear

relationship, with a power relationship only applicable at lower discharges to ensure

that the rating produced zero sediment yield at a zero value of peak discharge. The

power-fit regressions were adjusted for log-bias using the bias-correction factor of

Duan (1983) – which gave essentially the same correction as did Ferguson’s (1986)

method. The event yield vs. peak discharge rating relationships established for each

catchment were then used to estimate the yields in all events over the duration of the

flow record, providing average annual sediment yield estimates.

An example event yield rating is shown below for the Awanohi site (Figure 12).

Inspection of the event yield rating plots in log-log space showed that the residuals

(i.e., log of observed event yield minus log of predicted event yield, or log of the ratio

of observed to predicted yield) were homoschedastic with peak discharge (i.e., the

scatter was of similar magnitude irrespective of peak discharge) and were all normally

distributed (confirmed by the Kolmogorov-Smirnov test at the 5% significance level).

On this basis, a standard factorial error of the estimate was determined, and the

residuals were tested for a time-trend by testing the hypothesis that the coefficient on

a linear relation between log (observed/predicted event yield) was significantly

different from zero at the 5% significance level. No trend is indicated if the coefficient

is not significantly different from zero.


In the case of Redwood Forest, an event rating was first developed with data from the

full sediment monitoring period. However, the residual and time trend analyses

indicated a significant increase in sediment yield for a given event peak discharge after

the commencement of harvesting operations on 20 January 1997, thus separate event

ratings were developed for the pre- and post-harvesting periods.

Figure 12 Example of an event yield rating from Awanohi Stream catchment. This rating has a

linear relationship and no bias correction is required or applied.

Awanohi - Okura

y = 7.8991x - 567.44

R2 = 0.9948

100

1000

10000

100000

1000000

100 1000 10000 100000

Event Peak Discharge (l/s)

Even

t S

ed

imen

t Y

ield

(kg

)

4.3 The Monte Carlo approach

The Monte Carlo approach was based on the event sediment yield ratings, but instead

of using the actual event peak-discharge series captured by the flow record, it sampled

a probability distribution of event peak-discharges. For each site, the probability

distribution was fitted to all event peaks in the flow record with recurrence interval

greater than one month (on a peaks-over-threshold series). This distribution was

extrapolated out to a 20-year reference period and was then sampled to provide a 20-

year series of monthly peak discharges. The event yield rating was then applied to

convert this to a series of monthly event yields. Each event yield was multiplied by a

randomly-selected factor that scaled with the standard factorial error determined for

the event rating. The event yields, when totalled and divided by 20, gave an estimate

of the 20-year average annual sediment yield. Finally, the process was repeated 100

times, with the mean of the 100 realisations taken as the estimate of the annual

average yield and the standard deviation taken as a measure of the uncertainty induced

by the random occurrence of storms and the scatter in the event yield rating.

We consider that this approach helps (but does not completely) overcome the problem

of comparing sediment yields from basins monitored over short and non-overlapping

periods, since their yields over the monitoring period depend on what runoff events

occur. Key assumptions with the approach are that the event yield ratings and the

event peak-discharge frequency distributions do not vary with time, and that both of

these may be reliably extrapolated to higher peak discharges.


4.4 Determining magnitude-frequency relationships for event sediment yields

The event sediment yields generated from the flow record and event yield ratings, as

described in section 4.2, were used to produce event-yield magnitude-frequency plots.

Past experience has shown that these often contain useful information on the relative

importance of events of different return period (e.g., monthly compared with annual

events) and also sometimes show a land use effect (Hicks, 1994).


5 Results

5.1 Rating relationships

The sediment concentration ratings are plotted for each site in Appendix 1. Table 4

summarises the rating functions. The Redwood Forest data (Figure 23) are separated

between the pre- and post-harvesting periods, although the scatter is too large to

identify a significant overall difference in the rating relations (as Hicks and McKerchar,

2000, also found). Issues encountered during the data analysis at several sites are

discussed in Appendix 1.

The event analysis results are included in Appendix 1, along with the event yield rating

plots and plots showing how the residuals (observed yield / predicted yield) varied with

time. Table 5 summarises the event yield rating functions. The only site where the

residuals showed a significant time trend (at the 5% level) was at Redwood Forest

using the full dataset (Figure 25). On this basis, separate event yield ratings were fitted

for the pre-harvesting and post-harvesting periods (Figure 24).

The dataset at Barwick was too poor to complete an event yield analysis.

5.2 Sediment yields

The average annual specific sediment yields (t/km2/yr) derived by the three approaches

are listed in Table 6 and plotted on the top plot of Figure 13. The yields agree

reasonably well across the three approaches, although the sediment concentration

rating approach tends mostly to give a higher result than the event-yield approaches. In

part, this appears to be because the event-yield based approaches (which define

events in terms of discrete quickflow events that exceed a threshold quickflow runoff)

ignored sediment carried by the delayed flow (i.e., on event recessions after the

cessation of quickflow) and also ignored the sediment load carried by very small

events (typically with return periods less than 1 month). A measure of this effect was

found by using the sediment concentration rating approach to total just the sediment

load carried during quickflow events. The proportion of the load carried during

quickflow varied from 74% to 93% (Table 6). While this accounts for much of the

difference among yield estimates at some sites (e.g., Mahurangi, Awanohi), at other

sites the difference appears to be due more to sampling error in the rating relations

(which tends to be larger for the sediment concentration ratings). For example, it may

be that the sediment concentration rating approach is inclined to overestimate the load

during high winter base flows.

Because all of the approaches for estimating yields have advantages and

disadvantages, we suggest taking the average of the three results as representative,

with the standard deviation of the three results being indicative of the uncertainty

(there was only the sediment concentration rating based result determined from the


Barwick catchment, owing to the poor quantity of samples through runoff events).

These averaged yield results range from 13 t/km2/yr at the Barwick catchment up to

241 t/km2/yr at Redwood Forest after harvesting.

Table 4 Sediment concentration ratings determined for each catchment, including the overall

regression, standard factorial error and bias correction factor applicable to each.

SSC (mg/l) =

Overall

R2

Standard

Factorial

Error

Average Bias

Correction

Factor

Wylie Road

For Q<8.5: 11.54Q0.018

For Q < 58: 4.02Q0.51

For Q<373: 0.17Q1.29

For Q<1182: 192.36Q0.10

For Q>1182: 22.60Q0.41 0.74 1.86 1.06

Redwood pre-

harvesting

For Q<13: 21.4Q0.54

For Q<68: 3.67Q1.23

For Q<200: 371Q0.14

For Q<494: 0.1Q1.69

For Q>494: 2.81Q1.150 0.52 3.10 1.18

Redwood post-

harvesting

For Q<7: 0.566Q2.51

For Q<16: 163Q-0.39

For Q<35: 0.265Q1.92

For Q<91: 2.57Q1.28

For Q<162: 5.13Q1.13

For Q<262: 2538Q-0.087

For Q>262: 1.71Q1.22 0.66 3.10 1.18

Mahurangi College

For Q<1000: 12.1Q0.025

For Q<3190: 0.0163Q0.98

For Q<16730: 0.0057Q1.11

For Q<62630: 0.33Q0.69

For Q>62630: 0.149Q0.76 0.87 1.81 1.05

Awanohi

For Q< 1248: 1.3Q0.77

For Q>1248: 10.9Q0.47 0.82 1.78 1.04

Weiti

For Q<27: 9Q0.032

For Q<494: 0.162Q1.25

For Q>494: 1.82Q0.93 0.96 1.59 1.02

Barwick

For Q<1.64: 31Q0.26

For Q>1.64: 32Q0.2 0.21 3.22 1.2


Lower Vaughan For Q<300: 2.4Q0.57

For Q<1020: 0.87Q0.75

For Q<6342: 3.88Q0.532

For Q>6342: 1.62Q0.632 0.71 1.99 1.06

Lower Awaruku

For Q<120: 1.8Q0.752

For Q<580: 50.7Q0.055

For Q<3184: 0.136Q0.99

For Q>3184: 47.71Q0.259 0.44 2.25 1.1

Mangemangeroa

For Q<215: 0.176Q1.345

For Q<614: 123Q0.125

For Q<2864: 1.55Q0.807

For Q>2864: 1.15Q0.844 0.3 2.88 1.15

Table 5 Event yield ratings relating event sediment yield, Y (kg), to event peak discharge, Qp (l/s),

including the overall regression coefficient, standard factorial error, and bias correction factor

applicable to each. The bias correction factor is incorporated into the event yield relation’s

coeficient. Quickflow separation slope and minimum quickflow runoff are used to define storm

events (refer section 4.2).

Event Y (kg) =

Overall

R2

Standard

Factorial

Error

Bias

Correction

Factor

Quickflow

Separation

Slope

(ml/s2/km2)

Minimum

Quickflow

Runoff

(mm)

Wylie Road 1.01Qp1.19 0.9 1.6 1.12 1.0 1.0

Redwood pre-

harvesting 1.19Qp1.44 0.85 1.88 1.22

0.5 0.15

Redwood post-

harvesting 5.46Qp1.25 0.90 1.42 1.06

0.5 0.15

Mahurangi College 0.21Qp1.36 0.94 1.53 1.11 1.0 1.0

Awanohi

For Q<190: 4.9Qp1.05

For Q>190: 7.90Qp

567 0.98 1.19 N/A

0.9 1.0

Weiti 0.04Qp1.78 0.95 1.7 1.12 1.0 1.0

Barwick Too few events with adequate data to establish relationship

Lower Vaughan 0.39Qp1.209 0.85 2.25 1.18 2.6 1.0

Lower Awaruku

For Q<1520: 0.25Qp1.24

For Q>1520: 2.20Qp –

1185 0.87 1.42 N/A

2.0 1.0

Mangemangeroa

For Q>3354: 6.0Qp1.11

For Q<3354: 0.04Qp1.72 0.86 1.13 variable

1.5 1.0


Apart from the Barwick result, which should be viewed with caution owing to the short

(6 month) record period, these yield figures lie within the range of previous estimates

in the region. The harvesting at Redwood Forest appears to have increased the

sediment yield there by 24-53%, depending on the estimate, with an estimate-

averaged increase of 40%.

Monthly and annual sediment yields determined with the sediment concentration

rating and the event yield rating approaches are listed in Appendix 2.

5.3 Annual yield variability

An appreciation of the annual variability in sediment yield to be expected from year-to-

year variability in weather can be seen from Figure 14. This shows the annual specific

yields over the 26 calendar years of flow record at the Mahurangi College site as

estimated with the sediment concentration rating. The annual specific yield ranges

over a factor-of-ten, from 26 to 277 t/km2, with a mean of 109 t/km2 and a standard

deviation of 70 t/km2. Even the three-year running average yield ranges over a factor-

of-four. This hydrologically-driven annual variability indicates that yield estimates

among catchments with short and different record periods should be interpreted with

caution. The Mahurangi data shows no significant long-term trend with time.


Figure 13 Comparison of sediment yields, catchment characteristics, and record length at study

catchments.

Sediment Yield

0

50

100

150

200

250

300

Redw

ood -

post-h

arve

sting

Wylie R

oad

Redw

ood -

pre-

harv

estin

g

Oku

ra a

t Weiti

Man

geman

gero

a

Lower

Vau

ghan

Mah

urang

i College

Awan

ohi -

Oku

ra

Lower

Awar

uku

Bar

wick

Sp

ecif

ic s

ed

imen

t yie

ld (

t/km

2/y

r)

QC rating approach

Event yield rating approach

Monte Carlo simulation

Landuse

0%

20%

40%

60%

80%

100%

Redw

ood -

post-h

arve

sting

Wylie R

oad

Redw

ood -

pre-

harv

estin

g

Oku

ra a

t Weiti

Man

geman

gero

a

Lower

Vau

ghan

Mah

urang

i College

Awan

ohi -

Oku

ra

Lower

Awar

uku

Bar

wick

Pasture Native forest Exotic forest

Urban Horticulture Harvested forest

Runoff, Rainfall and Slope

0200400600800

10001200140016001800

Redw

ood -

post-h

arve

sting

Wylie R

oad

Redw

ood -

pre-

harv

estin

g

Oku

ra a

t Weiti

Man

geman

gero

a

Lower

Vau

ghan

Mah

urang

i College

Awan

ohi -

Oku

ra

Lower

Awar

uku

Bar

wick

Rain

fall

an

d R

un

off

(m

m/y

r)

0

0.1

0.2

0.3

0.4

0.5A

vera

ge s

lop

e (

m/m

)

Runoff

Rainfall

Mean slope

Length of flow record

0

5

10

15

20

25

30

Red

woo

d - p

ost-h

arve

s...

Wylie R

oad

Red

woo

d - p

re-h

arve

sting

Oku

ra a

t Weiti

Man

gem

ange

roa

Lower

Vau

ghan

Mah

uran

gi C

ollege

Awan

ohi - O

kura

Lower

Awar

uku

Barwick

Ye

ars

of

rec

ord


Table 6 Summary of catchment characteristics and mean annual specific sediment yields established using sediment concentration rating, event yield rating

and Monte Carlo approaches. Data appear in order of decreasing sediment yield when ranked with Monte Carlo result. The ± term on the Monte Carlo result is

the standard deviation of the simulated yields. The % values following the sediment yields from the sediment concentration rating approach show the % of

the yield carried during quickflow events.

Catchment

Area (km2)

Years of

flow

data

Lithology

(% catchment area)

Land use

(% catchment area)

Mean

Slope

(m/m)

Mean

Annual

Rainfall

(mm/yr)

Runoff

(mm/yr)

Specific Sediment

Yield

Sediment

concentration rating

approach (t/km2/yr)

(% during quickflow

events)

Specific

Sediment Yield

Event yield

rating approach

(t/km2/yr)

Specific

Sediment

Yield

Monte Carlo

approach

(t/km2/yr)

Specific

Sediment

Yield

Average and

standard

deviation of

estimates

(t/km2/yr)

Wylie Road 1.05 1.28 Sandstone or coarse

siltstone (100%)

Pastoral (84%), Native

Vegetation (12%)

0.32 1570 1079 199.6

(93%)

202.9 199.1 ±28 200 ±2

Lower Vaughan 2.17 6.07 Sandstone or coarse

siltstone (89 %),

Alluvium (8%)


Vegetation (24%)

0.24 1202 625 115.6

(91%)

79.8 98.3 ±20 98 ±18

Mangemangeroa 4.44 8.1 Sandstone or coarse

siltstone (100%)


Vegetation (38%)

0.29 1177 347 93.7

(77%)

80.8 92.0 ±8 89 ±7

Mahurangi

College

48.83 26.25 Sandstone or coarse

siltstone (83%),

Alluvium (9%)


Vegetation (24%)

0.27 1591 750 108.9

(89%)

71.4 75.3 ±8 88 ±19

Okura at Weiti 1.70 0.56 Mudstone or fine

siltstone - banded

(43%), Sandstone or

coarse siltstone -

banded (21%)

Exotic Vegetation

(83%), Pastoral (15%)

0.25 1226 607 87.6

(85%)

90.7 66.1 ±18 82 ±13

Awanohi - Okura 5.27 6.25 Sandstone or coarse

siltstone (81%),

Sheared mixed

lithologies (10%)

Native Vegetation

(55%), Pastoral (35%)

0.32 1221 266 87.3

(85%)

67.2 67.0 ±5 79.0 ±12

Redwood Forest 0.6 3.67 Sandstone or coarse

siltstone (100%)

Exotic Vegetation

(99%), Native

Vegetation (1%)

0.40 1483 677 Pre-harvesting: 183

(83%)

Post-harvesting: 280

(82%)

183

227

150 ± 19

215 ±15

172 ± 19

241 ±35

Lower Awaruku 2.66 3.25 Sandstone or coarse

siltstone (91%)

Urban (81%), Native

Vegetation (9%)

0.19 1199 841 51.0

(74%)

41.0 29.0 ±2 40.0 ±11

Barwick 0.24 0.48 Sandstone or coarse

siltstone (100%)

Urban (93%), Native

Vegetation (7%)

0.22 1224 228 12.9

(-)

No event data No event

data

13


Figure 14 Annual specific sediment yields and three-year running average yield between 1982

and 2008 at the Mahurangi College site.

Mahurangi College Annual Specific Yields

0

50

100

150

200

250

300

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Year

Sp

ecif

ic Y

ield

(t/

km

2)

Annual

3-year running average

Mean = 109 t/km2

5.4 Sediment yield vs. catchment characteristics

Relationships between specific sediment yield and catchment characteristics were

examined in three ways: from the plots on Figure 13, from a correlation matrix, and by

a multiple-regression analysis. In each case, the comparison was made in terms of the

average of the three yield-estimating approaches (as in the last column of Table 6).

Comparison of the sediment yield and land use plots in Figure 13 shows that the

highest yields are linked with forest harvesting (Redwood Forest) and the lowest yields

occur in the urban catchments (Lower Awaruku, Barwick). In between, there appears

to be a trend for sediment yield to increase as the percentage pasture cover increases

(and forest decreases). The exceptions to this trend are Redwood Forest during the

pre-harvesting phase and the Okura-Weiti catchment, both of which show a higher

yield than might be expected. The high pre-harvesting yield at Redwood Forest may

well reflect the steeper slopes and relatively high rainfall there. The yield figures for the

largely-forested Okura-Weiti catchment may be higher than the long-term average

owing to the short record (6 months in 2008), since Figure 14 suggests that 2008

produced higher than average sediment yields at Mahurangi. It is of note that –

allowing for the estimated uncertainty – there is marginal difference in the yields

among the Lower Vaughan, Mangemangeroa, Mahurangi College, Okura-Weiti, and

Okura-Awanohi catchments (their yields range from 79-98 t/km2/yr). Thus among

these catchments at least, a land use influence does not appear to be strong.


The matrix of correlation coefficients for mean annual specific sediment yield,

catchment area, mean slope, mean annual rainfall, mean annual runoff, rainfall x slope

product (which is an index of rain power per unit catchment area), and % area under

pasture is shown in Table 7. The sediment yield result from Redwood Forest during

the post-harvesting phase was excluded from the correlation analysis (because that

was the only catchment subject to forest clearance). Specific sediment yield correlated

significantly (at the 5% level) with catchment mean slope and rainfall and correlated

best with the rain x slope product. There also appears to be a weak (but not

significant at 5% level) correlation of sediment yield with % pasture cover. This

suggests that apart from the clear influence of urban land use and forest harvesting

identified previously, the influence of land use on sediment yield (specifically the

degree of forest or pasture cover) may be being masked by the strong influence of

slope and rainfall.

Table 7 Matrix of correlation coefficients (r2) among specific sediment yield and catchment

characteristics. Values in bold are significant at the 0.05 level.

Area % Pasture

% Total

forest

cover

Slope Rainfall Rainfall

X Slope Runoff

Specific

sediment

yield

Area 1.00

% Pasture 0.26 1.00

% Total forest cover 0.00 -0.28 1.00

Slope 0.05 0.12 0.65 1.00

Rainfall 0.54 0.34 0.11 0.52 1.00

Rainfall X Slope 0.16 0.19 0.51 0.93 0.79 1.00

Runoff 0.16 0.36 -0.13 0.07 0.63 0.33 1.00

Specific sediment yield -0.07 0.48 0.35 0.78 0.68 0.85 0.61 1.00

Continuing on from the correlation analysis, a multiple regression analysis was

undertaken. Initially, a regression model was trialled relating mean annual specific

sediment yield (SSY) to rainfall (R), slope (S), rainfall x slope product (RS), % pasture

(%P) and % total forest (i.e., exotic and native combined - %F). This showed

significant contributions only from the rainfall x slope product and % pasture variables,

thus the final model developed was:

SSY (t/km2/yr) = 0.39 (R (mm/yr) x S) + 0.62 %P - 70 Equation 3.

The adjusted r2 for this model is 0.77 (i.e., the model explains 77% of the variance in

the sediment yields over the dataset), while the standard error of the estimate is 28

t/km2/yr.

An alternative non-linear regression model that also includes the % total forest and the

% urban (%U) is:

SSY (t/km2/yr) / (R (mm/yr) x S) = ( 0.0035 %P + 0.0023 %F+ 0.00084 %U)

Equation 4.


In this model, which has an adjusted r2 of 0.93, both % pasture and % forest made a

significant contribution to the regression and the standard error of the estimate is

0.069. The coefficients identify relative yields from pasture, forest, and urban areas in

the proportions 1: 0.66: 0.24.

In summary, what this regression analysis indicates is that the variation in specific

sediment yield in the dataset is due mainly to catchment rainfall, mean slope, and land

use; and, for a given rainfall x slope product, the yields from forested areas are 2/3

those from pasture areas, while the yields from urbanised areas are ¼ of those from

pasture areas. Also, from the results from Redwood Forest, we can add that forest

harvesting increases the sediment yield by approximately 40%.

Finally, we note that the regression results are based on the assumption that the mean

annual sediment yields estimated for each catchment are stationary; that is, they

should not be expected to vary significantly with time and length of record. As

observed at Mahurangi (section 5.3), the yield figures averaged over only a few years

do vary significantly. Thus, some of the variance in yields among the study sites must

be assigned to sampling error associated with the timing and length of record. The

Monte Carlo approach, by predicting event peak flows and yields over a standard 20-

year reference period and also by allowing for sampling error in the event yield rating

relations, attempts to avoid this factor. That the mean annual sediment yields used for

the regression analysis are close to those derived just from the Monte Carlo approach

(to well within the standard error of the estimate of the regression models) provides

reassurance that the relationships indicated by the regressional models are functional

rather than simply due to chance.

5.5 Application of results and recommendations for further sediment monitoring

While we caution that this analysis is based on only nine basins, nonetheless, most of

the results are statistically significant. The study therefore offers promise that a model

of the form of Equation 4, ideally calibrated with more data, could provide the basis for

a land use and rainfall driven proxy for monitoring potential changes in sediment yield

in the Auckland region (such as for state-of-the-environment reporting). We

recommend ongoing sediment monitoring of sediment yield at a small number of key

sites in order to validate such predictions.

Also, since all of the study basins are formed in Waitemata Formation lithologies, we

recommend that sediment sampling be extended to cover catchments in other

lithologies across the Auckland region, notably the Onerahi Chaos terrane in the

northern part of the region and perhaps the greywacke terrain in the southeast.

5.6 Event-yield magnitude-frequency relations

Event yield magnitude-frequency relations provide an alternative approach for

comparing sediment yield among catchments. Figure 15 shows how, generally, the

event specific sediment yields of given return period show similar variations among


catchments as do the average annual yields described above. Thus, for example, the

lowest yields from annual events (return period 1 year) are from the urban Awaruku

catchment and the highest are from Redwood Forest and Wylies Road.

Also, such plots can contain additional information about sediment sources. In the case

of the study basins, the Mangemangeroa, Vaughan, and Awaruku magnitude-

frequency relations reduce more steeply at return periods smaller than about 3 months

(T ~ 0.25 yr). This suggests a difference in the nature of sediment sources in these

catchments, with erosion sites only contributing substantial sediment amounts during

larger, less common events. In turn, this hints at either an erosion threshold or

sediment exhaustion effect on erosion processes in these catchments.

Figure 15 A comparison of the magnitude-frequency distributions of event sediment yields at all

catchments. T is event return period on a peaks-over-threshold series.

Event-yield Magnitude-frequency Relations

0.1

1

10

100

1000

0.01 0.1 1 10

T (yr)

Ev

en

t s

ed

ime

nt

yie

ld (

t/k

m2)

Redwood (forest - post harvesting)

Redwood (forest - pre-harvest)

Wyllie (pasture)

Weiti (forest)

Mangemangeroa (pasture, forest)

Vaughn (pasture)

Mahurangi (pasture, forest)

Awanohi (forest, pasture)

Awaruku (urban)


6 Conclusions The main conclusions of this study of sediment yields from nine catchments in

Auckland’s Waitemata Formation terrane are as follows:

• Specific suspended sediment yields ranged from 13 t/km2/yr at the Barwick

catchment up to 241 t/km2/yr at Redwood Forest after harvesting. Apart from

the Barwick result, which should be viewed with caution owing to the short (6

month) record period, these yield figures lie within the range of previous

estimates in the region.

• The harvesting at Redwood Forest increased the sediment yield there by about

40%.

• The 27 year flow record at the Mahurangi College site indicated that annual

sediment yields there should have ranged over a factor-of-ten due to inter-annual

hydrological variability. The three-year running-average yield ranged over a factor-

of-four.

• A correlation and multiple-regression analysis indicated that the variation in

specific sediment yield in the dataset is due mainly to catchment rainfall, mean

slope, and land use. For a given rainfall x slope product, the yields from forested

areas are 2/3 those from pasture areas, while the yields from urbanised areas are

¼ of those from pasture areas.

• A comparison of the event-yield magnitude-frequency relationships for all but the

Barwick catchment (which had too little data) showed that generally, the specific

sediment yields of events of given return show similar variations among

catchments as do the average annual yields described above. Two pasture

catchments and one urban catchment showed evidence of either erosion

threshold or sediment exhaustion effects during small, frequently-occurring

events.

• The study offers the promise that an empirical sediment yield predictive model

driven by rainfall and land use could proxy for monitoring potential changes in

sediment yield in the Auckland region.

• We recommend ongoing monitoring of sediment yield at a small number of key

sites in order to validate such predictions, plus limited-term monitoring of

sediment yields in other lithologies so that the empirical model can be calibrated

and applied beyond the Waitemata Formation terrane.


7 References Becker, K. and Ridley, G. 1995. Mahurangi Modelling Study – Redwood Site. Working

Report Number 62. ARC Environment.

Duan, N. 1983. Smearing estimate: a non-parametric retransformation method. Journal

of the American Statistical Association 78: 605-610.

Ferguson, R.I. 1986. River loads underestimated by rating curves. Water Resources

Research 22: 74-76.

Green, M.O. and Oldman, J.W. 1999. Deposition of flood-borne sediment in Okura

estuary. Prepared by NIWA for Auckland Regional Council. NIWA Client

Report ARC90242.

Heighway, S.A. 1999. Sediment Yield from a Catchment undergoing Urban

Intensification. Masters Thesis. University of Auckland.

Hewlett, J.D. and Hibbert, R.A. 1967. Factors affecting the response of small

watersheds to precipitation in humid areas. In: Forest Hydrology (W.E.

Sopper and H.W. Lull, eds), Pergamon: 275-290.

Hicks, D.M. 1994. Storm Sediment Yields from Basins with Various Landuses in

Auckland Area. Prepared by NIWA for Auckland Regional Council. NIWA

Client Report ARC802/1

Hicks, D.M. and McKerchar, A.I. 2000. Redwood Stream sediment yield. Prepared by

NIWA for Auckland Regional Council. NIWA Client Report CHC00/39.

Hope, M. 2007. Wade Trib at Barwick Estate 09/08/2007 – 07/12/2007. Report for

Auckland Regional Council.

Hicks, D.M. 1990. Suspended sediment yields from pasture and exotic forest basins.

In: Proceedings of the 1990 NZ Hydrological Society Symposium, Taupo,

November 1990.

Hicks, D.M., Gomez, B., and Trustrum, N.E. 2000. Erosion thresholds and suspended

sediment yields, Waipaoa River Basin, New Zealand. Water Resources

Research 36: 1129-1142.

Norkko, A., Thrush, S.F., Hewitt, J.E., Norkko, J., Cummings, V.J., Ellis, J., Funnell, G.

and Schultz, D. 1999. Ecological effects of sediment deposition in Okura


estuary. Prepared by NIWA for Auckland Regional Council. NIWA Client

Report ARC90243.

Oldman, J.W., Swales, A. 1999. Mangemangeroa Estuary Numerical Modelling and

Sedimentation. Prepared by NIWA for Auckland Regional Council. NIWA

Client Report ARC70224.

Stroud, M.J., Cooper, AB. 1997 Modelling sediment load to the Mahurangi Estuary.

Prepared by NIWA for Auckland Regional Council. NIWA Client Report

ARC60211.

Stroud, M.J., Cooper, A.B., Bottcher, A.B., Hiscock, J.G. and Pickering, N.B. 1999.

Sediment runoff from the catchment of Okura estuary. Prepared by NIWA for

Auckland Regional Council. NIWA Client Report ARC9024/1.

Swales, A., Hume, T.M., Oldman, J.W. and Green, M.O. 1997. Mahurangi Estuary:

Sedimentation History and Recent Human Impacts. Prepared by NIWA for

Auckland Regional Council. NIWA Client Report ARC60201.


8 Appendix 1: Time series and rating plots

8.1 Wylie Rd

8.1.1 Time series plots

Figure 16 Time series plot of Wylie Road discharge record, indicating the magnitude and timing of

flood events.

0

10000

20000

24000

Flo

w l/s

19940401 9406 9407 9408 9409 9410 9411 9412 9501 9502 9503 9504 9505 9506 9507 YYMM

site 6809 Flow at Wylie Road Flow l/s

Figure 17 Time series plot of Wylie Road flow record with sediment over plotted in pink (with

scale on right vertical axis).

0

2000

4000

6000

8000

05/1

994

06/1

994

07/1

994

08/1

994

09/1

994

10/1

994

11/1

994

12/1

994

01/1

995

02/1

995

03/1

995

04/1

995

05/1

995

06/1

995

07/1

995

08/1

995

Date

Flo

w (

l/s)

0

200

400

600

800

1000

1200

1400S

ed

imen

t C

on

cen

trati

on

(m

g/l

)

Flow (l/s)

Sediment Concentration (mg/l)


8.1.2 Sediment concentration rating

Figure 18 Wylie Road sediment concentration rating

Sediment Concentration Rating - Wylie Road

1

10

100

1000

10000

1 10 100 1000 10000 100000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)

Bias-corrected Lowess rating

8.1.3 Event sediment yield rating

Figure 19 Event sediment yield rating for Wylie Road

Event Yields - Wylie Road

0.1

1

10

100

1000

100 1000 10000 100000

Event Peak Discharge - Qp (l/s)

Even

t S

ed

imen

t Y

ield

(t)

Event yield (t)

Power (Event yield (t))

Overall R2 0.74

R2 0.90


Figure 20 Event yield residuals at Wylie Road examining whether there is a significant change in

event yield over time. The trend over time was found to not be significant in this catchment.

Event Yield Residuals - Wylie Road

0.1

1

10

06

/19

94

08

/19

94

09

/19

94

11

/19

94

01

/19

95

02

/19

95

04

/19

95

05

/19

95

07

/19

95

09

/19

95

Date

Re

sid

ua

ls (

ob

se

rve

d/p

red

icte

d)

Obs/pred

Linear (Obs/pred)

8.2 Redwood Forest



Figure 21 Time series plot of Redwood Forest discharge record, indicating the magnitude and

timing of flood events. Each graph shows 2 years of record. NB: The scale of the vertical axis

varies.

0

1000

2000

2400

Flo

w l/s

19940101 9404 9407 9410 9501 9504 9507 9510 YYMM

site 6810 Flow at Redwood Forest Flow l/s

0

500

1000

1200

Flo

w l/s

19960101 9604 9607 9610 9701 9704 9707 9710 YYMM


0

200

400

480

Flo

w l/s

19980101 9804 9807 9810 9901 9904 9907 9910 YYMM



Figure 22 Time series plot of Redwood Forest sediment concentration record with discharge over

plotted in blue (with scale on right vertical axis).

0

4000

8000

12000

16000

20000

05/1

994

12/1

994

06/1

995

01/1

996

07/1

996

02/1

997

08/1

997

03/1

998

Date

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

0

100

200

300

400

500

600

700

800

900

1000

Dis

ch

arg

e (

l/s)

Sediment Concentration

Flow (l/s)


Figure 23 Redwood Forest sediment concentration rating

Sediment Concentration Ratings - Redwood Forest

1

10

100

1000

10000

100000

0.1 1 10 100 1000 10000

Discharge (l/s)

Se

dim

en

t C

on

ce

ntr

ati

on

(m

g/l)

Pre-harvesting bias-corrected

LOWESS rating

Pre-harvesting

Post-harvesting

Post-harvesting bias-corrected

LOWESS rating

A close inspection of the Redwood Forest sediment concentration rating data, and the residuals

from the LOWESS rating relations, showed a bias induced by a relatively small number of

samples collected in 1996. Effectively, what was happening was that the samples collected in

GAP

in

dataset


1996 were at times of high base flow, whereas the LOWESS-fit rating was dominated by the

more numerous samples collected during 1995 over a range of base flows. This meant that the

sediment concentration rating was over-estimating the sediment yield during the high base flow

period of 1996. For this reason, the sediment concentration rating based yield estimate during

the pre-harvesting phase was made for the period 10 May 1994 through 31 December 1995, for

which we were satisfied that the rating was representative. For this 1.63 year period, the

sediment yield determined from the sediment concentration rating approach (179 t) agreed well

with the yield integrated directly from the almost continuous span of composited auto-samples

(169 t), as reported by Hicks and McKerchar (2000).


Figure 24 Event yield rating at Redwood Forest

Event Yields - Redwood Forest

100

1000

10000

100000

10 100 1000 10000


Ev

en

t S

ed

ime

nt

Yie

ld (

kg

)

Post-harvesting

Pre-harvesting

Power (Post-harvesting)

Power (Pre-harvesting)


Figure 25

Event yield residuals at Redwood Forest for a relation fitted to the full dataset. The trend over

time was found to be significant in this catchment. Harvesting commenced in January 1997.

Event Yield Residuals - Redwood Forest

0.1

1

10

03

/19

94

09

/19

94

04

/19

95

10

/19

95

05

/19

96

12

/19

96

06

/19

97

01

/19

98

07

/19

98

Date

Re

sid

ua

ls (

ob

se

rve

d/p

red

icte

d)

Obs/pred

Linear (Obs/pred)

8.3 Mahurangi College


Figure 26 Time series plot of Mahurangi College discharge record. Each graph shows 4 years of

record. NB: The scale of the vertical axis varies.

0

100000

200000

250000

Flo

w l/s

19820101 8207 8210 8301 8304 8307 8310 8401 8404 8407 8410 8501 8504 8507 8510 YYMM

site 6806 Flow at Mahurangi College Flow l/s

0

50000

100000

125000

Flo

w l/s

19860101 8607 8610 8701 8704 8707 8710 8801 8804 8807 8810 8901 8904 8907 8910 YYMM



0

50000

100000F

low

l/s

19900101 9007 9010 9101 9104 9107 9110 9201 9204 9207 9210 9301 9304 9307 9310 YYMM


0

100000

160000

Flo

w l/s

19940101 9407 9410 9501 9504 9507 9510 9601 9604 9607 9610 9701 9704 9707 9710 YYMM


0

100000

160000

Flo

w l/s

19980101 9807 9810 9901 9904 9907 9910 0001 0004 0007 0010 0101 0104 0107 0110 YYMM


0

100000

160000

Flo

w l/s

20020101 0207 0210 0301 0304 0307 0310 0401 0404 0407 0410 0501 0504 0507 0510 YYMM


0

100000

160000

Flo

w l/s

20060101 0607 0610 0701 0704 0707 0710 0801 0804 0807 0810 0901 0904 0907 0910 YYMM



Figure 27 Time series plot of Mahurangi College flow record with sediment over plotted in pink

(with scale on right vertical axis).

0

20000

40000

60000

80000

10000003/1

994

05/1

994

07/1

994

08/1

994

10/1

994

12/1

994

01/1

995

03/1

995

05/1

995

06/1

995

08/1

995

Date

Dis

ch

arg

e (

l/s)

0

200

400

600

800

1000

1200

1400

1600

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

Discharge (l/s)

Sediment Concentration (mg/l)


Figure 28 Sediment concentration rating at Mahurangi College

Sediment Concentration Rating - Mahurangi at College

1

10

100

1000

10000

1 10 100 1000 10000 100000 1000000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.87



Figure 29 Event yield rating at Mahurangi College

Event Yields - Mahurangi at College

1

10

100

1000

10000

100 1000 10000 100000 1000000


Even

t S

ed

imen

t Y

ield

(t)

Yield (t)

Power (Yield (t))

Figure 30 Event yield residuals at Mahurangi College examining whether there is a significant

change in event yield over time. The trend over time was found to not be significant in this

catchment.

Event Yield Residuals - Mahurangi at College

0.1

1

10

03/1

994

04/1

994

06/1

994

08/1

994

09/1

994

11/1

994

01/1

995

02/1

995

04/1

995

05/1

995

07/1

995

09/1

995

Date

Resid

uals

(o

bserv

ed

/pre

dic

ted

)

Obs/pred

Linear (Obs/pred)

R2 0.94


8.4 Awanohi Stream


Figure 31 Time series plot of Awanohi Stream discharge record, indicating the magnitude and

timing of flood events. Each graph shows 2 years of record. No data is available for 1999-2002.

NB: The scale of the vertical axis varies in this figure.

0

5000

8000

flow

l/s

19980101 9804 9807 9810 9901 9904 9907 9910 YYMM

flow l/s

GAP IN DISCHARGE RECORD

0

10000

20000

flow

l/s

20030101 0304 0307 0310 0401 0404 0407 0410 YYMM

flow l/s

0

5000

10000

12500

flow

l/s

20050101 0504 0507 0510 0601 0604 0607 0610 YYMM

flow l/s

0

10000

20000

25000

flow

l/s

20070101 0704 0707 0710 0801 0804 0807 0810 YYMM

flow l/s


Figure 32 Time series plot of Awanohi Stream sediment concentration record, with discharge

over plotted in black (with scale on right vertical axis). NB: The scale of the vertical axis varies in

this figure.

0

1000

1600

Sed

. C

on

c.

mg/l

20040101 0403 0404 0405 0406 0407 0408 0409 0410 0411 0412 YYMM

Sed. Conc. mg/l

0

12500

20000

flow l/s

0

500

1000

1250

Sed

. C

on

c.

mg/l

20050101 0503 0504 0505 0506 0507 0508 0509 0510 0511 0512 YYMM

Sed. Conc. mg/l

0

1600

3200

4000

flow l/s


Figure 33 Awanohi Stream sediment concentration rating.

Sediment Concentration Rating - Awanohi - Okura

1

10

100

1000

10000

1 10 100 1000 10000 100000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.82



Table 8 Event characteristics and yields for Awanohi Stream.

Start date

(yyyymmdd)

Start time

(hhmmss)

Quick

flow

sed.

yield

(kg)

Event

sed.

yield

(kg)

Quick

flow

(mm)

Total

runoff

(mm)

Peak

Discharge

(l/s)

Peak

sed.

Conc.

(mg/l)

Quick

flow

event

duration

(hr)

Event

1 20040202 000900 157113 157113 31.2 35.2 19655 1596 17.9

2 20040228 120900 88570 88625 35.8 43.6 11694 888 21.1

3 20040514 132400 35525 36853 10.4 15.5 5317 1004 19.6

4 20040604 022400 262 956 0.1 5.4 189 75 9.4

5 20040618 121800 26411 26640 8.7 12.6 3575 1353 21.1

6 20040720 193400 8318 8747 5.3 9.2 1242 359 18.4

7 20041007 070900 10208 12036 3.7 10.9 1331 710 23.2

8 20050618 093700 4569 5535 1.8 4 612 452 10.7

10 20050624 070400 6443 7285 6.3 14.5 1016 162 23.1

11 20050706 064400 28491 29690 8.9 20.8 2876 1162 31.4

12 20051006 205900 8867 9498 3.4 6.6 1767 745 11.4

Figure 34 Event yield rating for Awanohi Stream

Event Yields - Awanohi - Okura

100

1000

10000

100000

1000000

100 1000 10000 100000


Even

t S

ed

imen

t Y

ield

(kg

)

Series1

Linear (Series1)

Overall R2 0.98


Figure 35 Event yield residuals at Awanohi Stream examining whether there is a significant

change in event yield over time. The trend over time was found to not be significant in this

catchment.

Event Yield Residuals - Awanohi - Okura

0.1

1

10

01/2

004

04/2

004

08/2

004

11/2

004

02/2

005

05/2

005

09/2

005

Date

Resid

uals

(o

bserv

ed

/pre

dic

ted

)

Obs/pred

Linear (Obs/pred)

8.5 Weiti Forest


Figure 36 Time series plot of Weiti Forest discharge record, indicating the magnitude and timing

of flood events. Less than 1 year of discharge data is available for this catchment.

0

1000

2000

3000

Flo

w l/s

20080101 0803 0804 0805 0806 0807 0808 0809 0810 0811 0812 YYMM

Flow l/s


Figure 37 Time series plot of Weiti Forest sediment concentration record, with discharge over

plotted in black (with scale on right vertical axis).

0

500

1000

1500

1875

Sed.

Conc.

mg/l

20080101 0803 0804 0805 0806 0807 0808 0809 0810 0811 0812 YYMM

Sed. Conc. mg/l

0

800

1600

2400

3000

Flow l/s


Figure 38 Sediment concentration rating for Weiti Forest

Sediment Concentration Rating - Okura - Weiti

1

10

100

1000

10000

1 10 100 1000 10000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.96



Table 9 Event characteristics and yields for Weiti Forest

Start date

(yyyymmdd)

Start time

(hhmmss)

Quick

flow

sed.

yield

(kg)

Event

sed.

yield

(kg)

Quick

flow

(mm)

Total

runoff

(mm)

Peak

Discharge

(l/s)

Peak

sed.

Conc.

(mg/l)

Quick

flow

event

duration

(hr)

Event

1 20080429 023000 30 57 0.16 1.1 60 42 7.5

2 20080429 213000 1186 1229 2.3 4 451 417 8.4

3 20080504 202500 2476 2560 3.9 7.9 760 394 8.7

4 20080622 041000 9130 9586 6.5 10.5 816 1392 18.4

5 20080726 061500 9239 9395 12.7 21.6 746 728 26.4

6 20080729 105500 38646 38738 27.2 38.2 2614 1684 32.5

Figure 39 Event yield rating for Weiti Forest

Event Yields - Okura-Weiti Stream

1

10

100

1000

10000

100000

1 10 100 1000 10000


Even

t S

ed

imen

t Y

ield

(kg

)

Event yield (kg)

Power (Event yield (kg))

R2 0.95


Figure 40 Event yield residuals at Weiti Forest examining whether there is a significant change in

event yield over time. The trend over time was found to not be significant in this catchment.

Event Yield Residuals - Okura - Weiti Stream

0.1

1

10

04

/20

08

05

/20

08

06

/20

08

06

/20

08

07

/20

08

07

/20

08

08

/20

08

Date

Re

sid

ua

ls (

ob

se

rve

d/p

red

icte

d)

Obs/pred

Linear (Obs/pred)

8.6 Barwick


Figure 41 Time series plot of Barwick discharge record, indicating the magnitude and timing of

flood events. Less than 1 year of discharge data is available for this catchment.

0

200000

400000

600000

800000

937500

20070701 0709 0710 0711 0712 0801 0802 0803 0804 0805 0806 YYMM

Flow ml/s


Figure 42 Time series plot of Barwick sediment concentration record, with discharge overplotted

in black (with scale on right vertical axis). NB: Less than 6 months of sediment data is available

for this catchment

0

1000

2000

3000

20070701 0708 0709 0710 0711 0712 YYMM

Sed. Conc. mg/l

0

312500

625000

937500

Flow ml/s


Figure 43 Sediment concentration rating for Barwick catchment

Sediment Concentration Rating - Barwick

1

10

100

1000

10000

0.001 0.01 0.1 1 10 100 1000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.21


8.7 Lower Vaughan – Long Bay


Figure 44 Time series plot of Lower Vaughan discharge record, indicating the magnitude and


varies in this figure.

0

10000

16000

20000101 0004 0007 0010 0101 0104 0107 0110 YYMM

Flow l/s

0

10000

16000

20020101 0204 0207 0210 0301 0304 0307 0310 YYMM

Flow l/s

0

10000

20000

25000

20040101 0404 0407 0410 0501 0504 0507 0510 YYMM

Flow l/s

0

20000

40000

20060101 0604 0607 0610 0701 0704 0707 0710 YYMM

Flow l/s

0

10000

16000

20080101 0804 0807 0810 0901 0904 0907 0910 YYMM

Flow l/s


Figure 45 Time series plot of Lower Vaughan sediment concentration record, with discharge

overplotted in black (with scale on right vertical axis). There is a gap in the sediment

concentration record with the top graph displaying sediment concentration in period 1 and the

bottom two graphs displaying period 2. NB: The scale of the vertical axis varies in this figure.

0

500

800

20010101 0103 0104 0105 0106 0107 0108 0109 0110 0111 0112 YYMM

Sed. Conc. mg/l

0

10000

16000

Flow l/s

GAP IN SEDIMENT CONCENTRATION RECORD

0

500

1000

20040101 0403 0404 0405 0406 0407 0408 0409 0410 0411 0412 YYMM

Sed. Conc. mg/l

0

12500

25000

Flow l/s

0

500

800

20050101 0503 0504 0505 0506 0507 0508 0509 0510 0511 0512 YYMM

Sed. Conc. mg/l

0

3125

5000

Flow l/s



Figure 46 Sediment concentration rating for Lower Vaughan – Long Bay

Sediment Concentration Rating - Lower Vaughan - Long Bay

1

10

100

1000

1 10 100 1000 10000 100000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.71



Table 10 Event characteristics and yields at Lower Vaughan – Long Bay

Start date

(yyyymmdd)

Start time

(hhmmss)

Quick

flow

sed.

yield

(kg)

Event

sed.

yield

(kg)

Quick

flow

(mm)

Total

runoff

(mm)

Peak

Discharge

(l/s)

Peak

sed.

Conc.

(mg/l)

Quick

flow

event

duration

(hr)

Event

1 20010111 90500 47 80 0.2 2.6 171 31 6.1

2 20010402 120500 409 442 3.9 8.5 856 54 12.6

3 20010412 180500 5036 5059 31.5 37.5 5280 114 15.8

4 20010502 154000 11238 11268 29.6 33.5 7111 340 10.4

5 20010511 180500 32861 32870 37.7 41.1 13386 684 10.8

6 20010525 203500 5634 5818 16.1 24.4 3164 501 15.1

7 20010525 152000 719 920 4.4 13.6 592 76 13.6

8 20010530 500 4929 4956 25.2 31.1 6074 209 13.0

9 20040514 222400 18697 18698 20.2 22.2 6935 847 7.6

10 20040618 124400 18223 18267 19.4 25.6 5542 858 16.8

11 20040720 204900 3495 3776 6.5 12.5 977 271 12.5

12 20041007 120900 9543 9631 9.2 12.0 2541 680 9.4

13 20050918 30900 1509 1723 3.0 6.1 766 305 8.0

14 20051002 121200 3694 3991 5.1 9.8 1996 639 10.4

15 20051006 215900 1824 1890 3.6 5.3 1150 327 6.4


Figure 47 Sediment yield rating for Lower Vaughan – Long Bay catchment

Event Yields - Lower Vaughan - Long Bay

1

10

100

1000

10000

100000

100 1000 10000 100000


Even

t S

ed

imen

t Y

ield

(kg

)

Event yield (kg)

Power (Event yield (kg))

Figure 48 Event yield residuals at Lower Vaughan – Long Bay examining whether there is a

significant change in event yield over time. The trend over time was found to not be significant in

this catchment.

Event Yield Residuals - Lower Vaughan - Long Bay

0.1

1

10

10/2

000

04/2

001

11/2

001

05/2

002

12/2

002

06/2

003

01/2

004

08/2

004

02/2

005

09/2

005

03/2

006

Date

Resid

uals

(o

bserv

ed

/pre

dic

ted

)

Obs/pred

Linear (Obs/pred)

R2 0.85


8.8 Lower Awaruku – Long Bay


Figure 49 Time series plot of Lower Awaruku discharge record, indicating the magnitude and



0

2000

4000

6000

8000

9375

20000101 0004 0007 0010 0101 0104 0107 0110 YYMM

Flow l/s

0

1000

2000

3000

3750

20020101 0204 0207 0210 0301 0304 0307 0310 YYMM

Flow l/s

0

5000

10000

15000

20040101 0404 0407 0410 0501 0504 0507 0510 YYMM

Flow l/s


Figure 50 Time series plot of Lower Awaruku sediment concentration record, with discharge over

plotted in black (with scale on right vertical axis). There is a gap in the sediment concentration

record with the top graph displaying sediment concentration in period 1 and the bottom two

graphs displaying period 2. NB: The scale of the vertical axis varies in this figure.

0

500

800

20010101 0103 0104 0105 0106 0107 0108 0109 0110 0111 0112 YYMM

Sed.Conc. mg/l

0

6250

10000

Flow l/s

GAP IN SEDIMENT CONCENTRATION RECORD

0

500

800

20040101 0403 0404 0405 0406 0407 0408 0409 0410 0411 0412 YYMM

Sed.Conc. mg/l

0

10000

16000

Flow l/s

0

200

400

625

20050101 0503 0504 0505 0506 0507 0508 0509 0510 0511 0512 YYMM

Sed.Conc. mg/l

0

2000

4000

6250

Flow l/s



Figure 51 Sediment concentration rating for Lower Awaruku – Long Bay

Sediment Concentration Rating - Lower Awaruku - Long Bay

1

10

100

1000

10000

1 10 100 1000 10000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Overall R2 0.44



Table 11 Event characteristics and yields for Lower Awaruku – Long Bay

Start date

(yyyymmdd)

Start time

(hhmmss)

Quick

flow

sed.

yield

(kg)

Event

sed.

yield

(kg)

Quick

flow

(mm)

Total

runoff

(mm)

Peak

Discharge

(l/s)

Peak

sed.

Conc.

(mg/l)

Quick

flow

event

duration

(hr)

Event

1 20001211 125500 6569 6631 3.6 4.21 3647 1093 2.2

2 20010502 153000 16300 16351 16 18.1 8120 743 5.3

3 20010510 100500 1149 1207 3.6 5.8 1578 130 5.6

4 20010525 203000 6708 7146 5.2 10.5 3530 529 6.8

5 20010530 11000 4028 4298 5.4 9.2 2905 357 4.8

6 20040514 221800 10357 10414 11.9 13.8 6067 433 4.7

7 20040618 132800 12377 12982 10 22.6 5778 658 11.1

8 20040720 181900 2806 3102 4.9 12.2 1470 207 11.3

9 20041007 131800 6198 6479 6.9 11.2 2890 382 6.9

10 20050624 91300 4371 4844 9.6 31.9 2091 313 15.1

11 20050706 42900 12292 12541 12.1 20.4 4953 525 11.1

12 20051002 113200 4903 5196 10.2 19.1 3636 247 11.5

13 20051006 200900 2634 2901 5.7 10.7 3230 194 5.3

14 20001211 125500 6569 6631 3.57 4.21 3647 1093 2.2

15 20010502 153000 16300 16351 16 18.1 8120 743 5.3

16 20010510 100500 1149 1207 3.63 5.8 1578 130 5.6

Figure 52 Event yield rating for Lower Awaruku catchment

Event Yields - Lower Awaruku - Long Bay

100

1000

10000

100000

1000 10000


Even

t S

ed

imen

t Y

ield

(kg

)

Event yield (kg)

Linear (Event yield (kg))

Overall R2 0.87


Figure 53 Event yield residuals at Lower Awaruku – Long Bay examining whether there is a


this catchment.

Event Yield Residuals - Lower Awaruku - Long Bay

0.1

1

10

03/2

000

10/2

000

04/2

001

11/2

001

05/2

002

12/2

002

06/2

003

01/2

004

08/2

004

02/2

005

09/2

005

03/2

006

Date

Resid

uals

(o

bserv

ed

/pre

dic

ted

)

Obs/pred

Linear (Obs/pred)

Overall R2 0.21


8.9 Mangemangeroa


Figure 54 Time series plot of Mangemangeroa discharge record, indicating the magnitude and



0

5000

8000

20000101 0004 0007 0010 0101 0104 0107 0110 YYMM

Flow l/s

0

5000

10000

20020101 0204 0207 0210 0301 0304 0307 0310 YYMM

Flow l/s

0

5000

10000

12500

20040101 0404 0407 0410 0501 0504 0507 0510 YYMM

Flow l/s

0

2000

4000

6250

20060101 0604 0607 0610 0701 0704 0707 0710 YYMM

Flow l/s

0

5000

8000

20080101 0804 0807 0810 0901 0904 0907 0910 YYMM

Flow l/s


Figure 55 Time series plot of Mangemangeroa sediment concentration record, with discharge

over plotted in black (with scale on right vertical axis). NB: The scale of the vertical axis varies in

this figure.

0

2000

3200

20000101 0003 0004 0005 0006 0007 0008 0009 0010 0011 0012 YYMM

Sed. Conc. mg/l

0

156250

250000

Flow ml/s

0

1000

2000

2500

20010101 0103 0104 0105 0106 0107 0108 0109 0110 0111 0112 YYMM

Sed. Conc. mg/l

0

3200000

6400000

8000000

Flow ml/s

0

2000

3200

20020101 0203 0204 0205 0206 0207 0208 0209 0210 0211 0212 YYMM

Sed. Conc. mg/l

0

6250000

10000000

Flow ml/s

0

2000

3200

20030101 0303 0304 0305 0306 0307 0308 0309 0310 0311 0312 YYMM

Sed. Conc. mg/l

0

5000000

8000000

Flow ml/s

0

1000

2000

20040101 0403 0404 0405 0406 0407 0408 0409 0410 0411 0412 YYMM

Sed. Conc. mg/l

0

4000000

8000000

Flow ml/s



Figure 56 Sediment concentration rating for Mangemangeroa catchment.

Sediment Concentration Rating - Mangemangeroa

1

10

100

1000

10000

10 100 1000 10000

Flow (l/s)

Sed

imen

t C

on

cen

trati

on

(m

g/l

)

SSC (mg/l)


Data from flows less than 50 l/s were excluded from the sediment concentration rating fitting for

the Mangemangeroa site. This was because inspection of the sediment concentration time-

series data (Figure 56), generated from the OBS record, showed a very ‚noisy‛ signal at base

flows. Possibly this was due to the sensor detecting light back-scattered from the bed. For the

yield analysis, the LOWESS-fitted sediment concentration rating at flows above 50 l/s was

extrapolated to lower flows.

Overall R2 0.30



Figure 57 Event yield rating for Mangemangeroa catchment

Event Yields - Mangemangeroa

0.01

0.1

1

10

100

1000

100 1000 10000


Even

t S

ed

imen

t Y

ield

(t)

Event yield (t)

Power (event yield (t)) - LOWESS

Figure 58 Event yield residuals at Mangemangeroa catchment examining whether there is a


this catchment.

Event Yield Residuals - Mangemangeroa

0.1

1

10

04/2

001

07/2

001

11/2

001

02/2

002

05/2

002

09/2

002

12/2

002

03/2

003

06/2

003

10/2

003

01/2

004

04/2

004

Date

Resid

uals

(o

bserv

ed

/pre

dic

ted

)

Overall R2 0.86


Table 12 Event characteristics and yields at Mangemangeroa catchment

Start Date Start Time Peak Q (l/s) Event Yield (t)

20010715 102000 1537 8.006

20010808 013000 1034 4.671

20010830 194000 4130 69.563

20010831 234000 1592 5.743

20010904 170000 6218 109.316

20010906 151000 1207 3.461

20010915 162000 549 0.768

20011022 154000 672 1.913

20011028 101000 766 1.911

20011107 010000 803 2.084

20011207 062000 699 2.317

20011208 211000 1254 4.479

20011215 091000 6515 89.877

20011224 015000 1176 3.003

20020109 184000 2410 25.333

20020314 101000 1663 14.499

20020425 161000 321 0.645

20020618 160000 237 0.68

20020620 021000 8276 134.567

20020707 212000 2091 11.311

20020711 192000 3747 106.73

20020712 082000 7672 113.143

20020722 225000 746 1.774

20020814 082000 1457 7.774

20020815 080000 979 3.238

20020919 062000 1381 6.948

20021016 091000 368 0.828

20021018 182000 1010 4.661

Start Date Start Time Peak Q (l/s) Event Yield (t)

20021207 142000 166 0.237

20030109 173000 1086 8.696

20030303 034000 168 0.168

20030310 152000 252 0.299

20030311 150000 723 2.392

20030328 065000 304 0.485

20030502 144000 222 0.759

20030521 194000 1066 19.732

20030522 025000 731 5.213

20030608 240000 267 2.021

20030609 173000 1663 27.975

20030707 180000 1053 9.873

20030708 012000 370 1.719

20030728 093000 324 0.197

20030729 201000 502 2.547

20030820 035000 1381 14.961

20030820 032000 218 0.556

20030902 022000 331 0.845

20030904 143000 699 6.383

20030905 190000 723 2.376

20030921 123000 734 7.367

20030921 020000 214 0.469

20031003 202000 3355 30.3

20031011 225000 2240 19.675

20031012 31000 6846 86.653

20031209 173000 164 0.09

20031210 55000 229 0.182


9 Appendix 2: Monthly sediment yields This appendix tabulates monthly suspended sediment yields for each study site based

on application of the sediment concentration ratings listed in Table 4 and the event

yield ratings listed in Table 5 to the flow records. Results are presented only for

months through which there is a complete flow record. The annual totals sum the

yields for the months of complete record.

9.1 Wylie Rd

9.1.1 Derived from sediment concentration rating

Table 13 Monthly sediment yields in tonnes from the Wylie Road catchment.

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

1994 2.7 84.6 2.6 10.7 23.8 0.8 0.2 125.3

1995 0.8 0.3 94.8 8.0 3.6 17.4 124.9

9.1.2 Derived from event yield rating

Table 14 Monthly sediment yields in tonnes from the Wylie Road catchment.


1994 0.9 31.8 0.9 7.2 18.7 0.4 0.0 59.8

1995 1.3 0.6 122.4 7.0 2.8 10.6 68.1 212.8


9.2 Redwood Forest


Table 15 Monthly sediment yields in tonnes from the Redwood Forest catchment. NB: a ‘?’

represents a gap in the flow record. Pre-harvesting rating used up to December 1995; post-

harvesting rating used from January 1997.


1994 0.11 25.6 0.46 1.36 9.38 0.9 0.21 38.02

1995 0.27 0.22 63.9 9.38 3.9 12.77 23.12 3.64 1.83 3.29 6.14 10.04 138.5

1996 Inadequate sampling - rating not reliable for 1996

1997 3.14 0.84 19.17 0.43 0.07 ? 3.49 14.83 96.5 13.55 6.45 1.41 159.88

1998 0.74 ? 6.28 7.02


Table 16 Monthly sediment yields in tonnes from the Redwood Forest catchment. NB: a ‘?’

represents a gap in the flow record. Pre-harvesting rating used up to December 1996; post-

harvesting rating used from January 1997.


1994 0.47 11.07 0.52 1.66 5.5 0.52 0 19.74

1995 0.37 0.72 69.7 16.84 3.16 8.66 17.97 1.29 4.9 4 3.88 11.43 142.92

1996 0.32 0.98 5.87 1.87 15.19 32.08 27.01 13.1 34.86 1.03 0 24.32 156.63

1997 3.12 1.3 23.67 0.72 0 ? 3.43 13.18 62.83 11.79 3.85 1.29 125.18

1998 0 ? 11.99 11.99


9.3 Mahurangi College


Table 17 Monthly sediment yields in tonnes from the Mahurangi College catchment.


1982 742 46 197 115 13 5 1118

1983 3 5 8 70 21 308 447 102 104 1144 41 1122 3376

1984 16 27 222 23 161 117 359 1843 407 72 16 1162 4425

1985 662 302 739 469 7738 474 903 753 964 48 358 273 13683

1986 1361 411 16 5 78 78 573 1122 500 56 13 13 4227

1987 5 5 13 140 11 130 645 40 428 118 233 1695 3464

1988 16 17 1540 34 163 83 5180 1928 353 102 83 801 10300

1989 3592 29 11 54 67 137 126 1778 1656 348 176 16 7991

1990 8 5 110 10 107 213 544 1264 168 80 8 8 2525

1991 5 8 121 140 11 31 284 565 114 43 16 11 1347

1992 46 5 8 13 40 91 1138 487 415 447 52 37 2779

1993 5 2 3 13 123 1869 51 158 350 16 23 8 2622

1994 37 2 3 5 24 75 1645 83 311 498 26 5 2715

1995 13 15 2191 168 126 420 1425 80 75 129 249 179 5071

1996 11 44 62 39 279 3271 988 1213 1750 27 10 1888 9581

1997 27 17 496 10 115 1954 380 538 1389 204 41 13 5186

1998 5 7 62 8 37 581 9763 2156 75 174 96 46 13010

1999 8 5 8 277 83 29 241 126 355 72 1130 16 2351

2000 19 5 5 57 158 1506 2373 252 26 16 715 16 5148

2001 21 27 8 573 2338 111 214 198 5324 123 109 187 9235

2002 24 19 21 13 126 4023 2427 104 127 21 21 8 6935

2003 142 40 557 36 112 122 1213 498 381 664 26 62 3854

2004 8 394 16 5 96 171 445 75 18 169 8 40 1446

2005 24 48 5 3 51 161 897 21 83 1053 41 46 2433

2006 214 24 19 829 252 150 51 1294 518 520 10 8 3890

2007 8 3 1133 13 5 39 2598 1979 207 37 18 129 6170

2008 8 462 27 804 635 946 3736 809 7427



Table 18 Monthly sediment yields in tonnes from the Mahurangi College catchment.


1982 22 251 0 122 80 0 0 476

1983 0 0 0 70 0 167 266 61 95 409 0 424 1492

1984 0 18 172 0 126 89 265 764 127 180 0 869 2610

1985 764 130 496 310 3163 263 390 534 1151 0 284 176 7661

1986 816 374 0 0 61 26 417 838 311 32 0 0 2876

1987 0 0 13 130 0 116 435 0 262 80 236 1012 2285

1988 0 0 737 0 81 0 2300 1386 328 35 82 1188 6135

1989 1468 0 0 77 36 84 97 1067 889 395 95 0 4207

1990 0 0 131 0 54 168 509 1211 188 90 0 0 2351

1991 0 0 74 131 0 0 236 590 100 0 0 0 1132

1992 69 0 0 0 37 28 759 397 379 427 35 46 2176

1993 0 0 0 0 138 667 0 100 235 0 0 0 1140

1994 51 0 0 0 14 65 689 50 230 349 0 0 1449

1995 0 17 2106 166 67 344 1433 66 70 125 218 118 4731

1996 0 35 82 37 262 1095 654 629 1354 21 0 973 5140

1997 0 19 580 0 126 507 725 316 1164 200 40 0 3678

1998 0 0 77 0 40 284 5009 1399 65 166 114 35 7189

1999 0 0 0 37 333 0 112 119 424 75 661 0 1761

2000 26 0 0 108 123 609 1498 328 0 0 518 0 3210

2001 19 17 0 470 1903 95 146 235 3771 163 84 156 7057

2002 26 20 0 0 119 2170 1943 88 161 0 23 0 4550

2003 148 19 331 0 126 93 439 998 356 644 0 53 3207

2004 0 312 0 0 78 122 312 38 0 189 0 18 1068

2005 19 37 0 0 45 108 569 0 71 765 39 66 1718

2006 176 31 0 468 133 119 53 603 387 354 0 0 2325

2007 0 0 513 0 0 36 1627 1821 224 0 0 155 4377

2008 0 244 0 1061 755 710 1967 770 5508


9.4 Awanohi Stream


Table 19 Monthly sediment yields in tonnes from the Awanohi Stream catchment. NB: a ‘?’

represents a gap in the flow record


1998 110.9 9.6 26.2 5.4 7.0 159.1

1999 1.3 0.0 ? ? ? ? ? ? ? ? ? ? 1.3

2000 ? ? ? ? ? ? ? ? ? ? ? ?

2001 ? ? ? ? ? ? ? ? ? ? ? ?

2002 ? ? ? ? ? ? ? ? ? ? ? ?

2003 ? ? ? 8.6 28.1 73.9 187.0 66.2 51.8 125.9 1.8 3.2 546.4

2004 0.5 283.5 1.3 0.0 40.2 28.8 21.7 14.7 5.2 11.8 0.0 2.1 409.9

2005 0.8 0.0 0.0 0.0 1.9 19.4 46.9 3.7 4.9 72.9 1.0 0.3 151.8

2006 3.7 0.0 0.0 83.2 39.6 11.9 0.3 113.6 40.7 228.5 0.8 0.3 522.6

2007 0.3 0.0 88.7 0.0 0.0 3.4 90.3 88.7 3.6 180.5 0.5 1.1 457.0

2008 0.0 1.7 0.3 11.7 38.0 54.2 218.3 88.4 0.8 413.3


Table 20 Monthly sediment yields in tonnes from the Awanohi Stream catchment. NB: a ‘?’



1998 18.25 92.2 0.0 13.2 3.8 4.4 131.9

1999 ? ? ? ? ? ? ? ? ? ? ?

2000 ? ? ? ? ? ? ? ? ? ? ? ? ?

2001 ? ? ? ? ? ? ? ? ? ? ? ? ?

2002 ? ? ? ? ? ? ? ? ? ? ? ? ?

2003 ? ? 56.75 9.8 31.2 102.0 63.5 151.5 43.0 111.2 0.0 5.5 574.5

2004 0.0 257.0 0.0 0.0 46.3 27.7 9.2 7.3 7.2 9.9 0.0 0.0 364.7

2005 0.0 0.0 0.0 0.0 0.0 11.7 48.4 5.0 5.1 55.6 0.0 0.0 125.9

2006 7.3 0.0 0.0 106.8 29.1 5.5 0.0 41.6 34.4 85.8 0.0 0.0 310.6

2007 0.0 0.0 40.5 0.0 0.0 44.1 84.7 101.4 0.0 170.7 0.0 0.0 441.4

2008 0.0 2.9 0.0 17.5 37.6 53.3 117.6 113.9 342.9


9.5 Weiti Forest


Table 21 Monthly sediment yields in tonnes from the Weiti Forest catchment.


2008 4.0 6.7 57.1 14.1 0.4 0.4 82.6


Table 22 Monthly sediment yields in tonnes from the Weiti Forest catchment.


2008 3.0 6.4 8.0 56.8 12.7 0.0 0.0 87.0

9.6 Barwick


Table 23 Monthly sediment yields in tonnes from the Barwick catchment.


2007 0.40 0.14 0.16 0.70

2008 0.05 0.05

There was no event yield rating derived for the Barwick site, owing to the low quality

and short duration of the record.


9.7 Lower Vaughan – Long Bay


Table 24 Monthly sediment yields in tonnes from the Lower Vaughan catchment. NB: a ‘?’



2001 1.1 1.3 0.1 23.3 96.9 1.6 4.7 ? ? ? ? ? 129.0

2002 ? ? ? ? ? ? ? ? ? ? ? ? 0.0

2003 ? ? ? ? ? ? 58.4 17.9 18.8 72.1 0.5 0.5 168.2

2004 0.2 142.9 0.7 0.5 18.5 15.7 7.5 4.1 2.4 6.2 1.1 2.4 202.2

2005 1.6 0.8 0.8 0.2 0.9 4.0 15.3 1.3 1.5 23.1 0.3 0.1 50.1

2006 0.9 0.0 0.1 82.9 23.8 5.9 1.3 30.5 22.5 94.6 0.7 0.9 264.0

2007 1.1 0.3 95.6 1.9 1.5 2.8 56.5 97.7 8.0 229.3 0.4 0.3 495.4

2008 0.0 0.3 0.1 4.1 32.9 10.6 141.6 24.5 0.6 1.3 216.1


Table 25 Monthly sediment yields in tonnes from the Lower Vaughan catchment. NB: a ‘?’



2001 0.2 1.0 0.0 13.8 81.7 0.0 1.7 0.6 ? ? ? ? 98.9

2002 ? ? ? ? ? ? ? ? ? ? ? ? 0.0

2003 ? ? ? ? ? 0.4 12.3 47.5 12.6 53.6 0.0 0.0 126.4

2004 0.0 126.3 0.0 0.0 18.1 13.2 2.3 0.6 1.5 5.1 0.0 0.0 167.0

2005 0.0 0.0 0.0 0.0 0.0 1.7 12.5 0.0 1.2 14.1 0.0 0.0 29.5

2006 0.6 0.0 0.0 82.6 17.4 0.9 0.7 20.9 14.9 70.7 0.0 0.0 208.7

2007 0.0 0.0 40.0 0.0 0.0 0.0 44.3 84.2 7.3 126.3 0.0 0.0 302.1

2008 0.0 0.0 0.0 5.4 29.8 6.8 58.4 18.0 0.0 0.9 119.2


9.8 Lower Awaruku – Long Bay


Table 26 Monthly sediment yields in tonnes from the Lower Awaruku catchment. NB: a ‘?’



2000 4.6 4.6

2001 2.4 10.1 0.5 19.7 51.4 5.5 10.7 14.4 5.8 0.8 1.0 2.4 124.7

2002 0.7 0.6 ? ? ? ? ? ? ? ? ? ? 1.3

2003 ? ? ? ? ? ? ? ? ? ? ? 6.1 6.1

2004 3.6 81.6 1.2 3.7 27.6 19.5 11.8 8.3 5.8 11.3 2.2 8.0 184.5

2005 2.4 2.8 3.4 0.6 10.1 16.6 34.1 6.7 14.7 91.3


Table 27 Monthly sediment yields in tonnes from the Lower Awaruku catchment. NB: a ‘?’



2000 4.2 7.4 11.6

2001 0.9 7.3 0.0 12.2 53.5 6.2 6.4 8.8 3.0 0.0 0.0 0.7 99.1

2002 0.0 0.0 1.54 ? ? ? ? ? ? ? ? ? 1.5

2003 ? ? ? ? ? ? ? ? ? ? 9 7.6 16.6

2004 6.1 50.3 0.0 5.6 23.6 16.4 5.8 6.3 4.9 11.8 4.8 5.3 140.8

2005 0.9 3.0 6.2 0.0 12.0 9.3 26.1 4.0 8.1 15.0 84.6


9.9 Mangemangeroa


Table 28 Monthly sediment yields in tonnes from the Mangemangeroa catchment. NB: a ‘?’



2000 61.1 28.0 1.3 1.8 0.3 92.5

2001 0.0 3.9 0.0 9.1 20.6 9.3 47.4 107.9 194.4 7.0 7.3 172.8 579.6

2002 11.0 0.7 11.2 1.0 2.1 119.8 185.6 14.2 11.7 7.0 1.8 1.1 367.2

2003 4.3 0.0 7.5 1.6 12.3 23.8 23.0 16.1 22.8 176.0 0.5 1.3 289.2

2004 0.8 270.2 ? ? ? 45.4 14.2 20.6 1.3 8.0 0.8 6.7 368.0

2005 0.3 0.0 7.5 0.0 0.0 0.0 229.5 6.2 11.7 100.2 0.3 0.3 355.8

2006 2.4 0.0 0.0 14.8 166.9 20.7 7.0 103.4 8.0 30.0 1.8 0.3 355.3

2007 1.3 0.0 9.6 1.3 1.3 7.5 159.9 27.1 2.1 16.6 0.5 2.1 229.4

2008 0.0 0.0 0.8 22.3 58.7 21.5 353.5 178.6 1.0 636.5


Table 29 Monthly sediment yields in tonnes from the Mangemangeroa catchment. NB: a ‘?’



2000 32.6 75.0 37.5 0.0 0.0 0.0 145.1

2001 0.0 0.0 0.0 5.5 7.0 0.0 33.2 68.7 119.6 6.9 4.2 123.1 368.2

2002 36.3 0.0 14.6 0.0 0.0 134.1 153.5 11.7 10.6 6.2 0.0 0.0 367.0

2003 7.0 0.0 0.0 0.0 6.8 14.6 6.7 10.6 10.4 157.6 0.0 0.0 213.7

2004 0.0 192.1 0 0 43.5 71.9 4.5 13.1 0.0 2.6 0.0 12.0 339.6

2005 0.0 0.0 22.1 0.0 0.0 0.0 307.2 9.9 29.5 78.4 0.0 0.0 447.1

2006 0.0 0.0 0.0 0.0 132.5 3.9 8.4 62.0 6.8 46.7 0.0 0.0 260.2

2007 0.0 0.0 10.9 0.0 0.0 9.4 128.1 31.9 0.0 24.5 0.0 0.0 204.8

2008 0.0 0.0 0.0 55.4 90.4 0.0 233.5 165.7 0.0 544.9

analysis of sediment yields within the auckland...

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