KULIN/DUDININ CATCHMENTS WATER MANAGEMENT PLAN Appendix C Management Options Evaluation Final Report
Kulin/Dudinin Catchments Water Management Plan Appendix C – Management Options Evaluation Final Report May 2009
PO Box 3596
Australia Fair,
QLD 4215
Australia
Tel: +61 7 5564 0916
Fax: +61 7 5564 0946
e-mail: [email protected]
Web: www.dhigroup.com.au
Client
Western Australia Department of Water
Client’s representative
Mr Jason Lette
Project Kulin/Dudinin Catchment Water Management Plan
Project No
50575
Authors
Graeme Cox (GJC)
Tony Chiffings (TWC)
Ashley Prout
Date 02 March 2009
Approved by
4 Draft GJC TWC TWC 19/04/09
3 Final Report
2 Draft Report
1 Interim Report
Rev Description By Checked Approved Date
Key words
Salinity Management plan MIKE SHE
Classification
Open
Internal
Proprietary
Distribution No of copies
Western Australia department of Water Mr Jason Lette Office Copy
1 1
© DHI Water and Environment Pty Ltd 2009
The information contained in this document produced DHI Water and Environment Pty Ltd is solely for the use of the
Client identified on the cover sheet for the purpose for which it has been prepared and DHI Water and Environment Pty
Ltd undertakes no duty to or accepts any responsibility to any third party who may rely upon this document.
All rights reserved. No section or element of this document may be removed from this document, reproduced,
electronically stored or transmitted in any form without the written permission of DHI Water and Environment Pty Ltd.
All hard copies of this document are “UNCONTROLLED DOCUMENTS”. The “CONTROLLED” document is held in
electronic form by DHI Water and Environment Pty Ltd.
iii DHI Water & Environment
CONTENTS
1 INTRODUCTION ........................................................................................................... 1
2 MANAGEMENT OPTIONS ........................................................................................... 2 2.1 Engineering ..................................................................................................... 2 2.2 Modified Farming Practice ............................................................................... 2 2.3 Vegetation ....................................................................................................... 2
3 NUMERICAL MODELLING ........................................................................................... 3 3.1 Model Setup .................................................................................................... 3 3.2 Model Calibration ........................................................................................... 10 3.3 Base Case Results ........................................................................................ 12
3.3.1 Salt Concentration and Loads ............................................................ 27
3.4 Scenarios ...................................................................................................... 30 3.5 Fine Scale Modelling ..................................................................................... 32
3.5.1 Detention Basin .................................................................................. 37
3.6 Discussion ..................................................................................................... 38 3.6.1 Effectiveness of saltbush at lowering the water table.......................... 38
3.6.2 Deep Drain Discharges ...................................................................... 39
3.6.3 LASCAM Results ............................................................................... 40
3.7 Recommendations From Model Outcomes .................................................... 41
4 FINAL OPTIONS EVALUATION ................................................................................. 42 4.1 Effectiveness At Protecting Agricultural Production ....................................... 42 4.2 Cost ............................................................................................................... 43 4.3 Environmental Impacts .................................................................................. 44 4.4 Social Impacts ............................................................................................... 44 4.5 Operational & Governance Requirements ..................................................... 45
5 CONCLUSIONS .......................................................................................................... 46
6 REFERENCES ........................................................................................................... 47
FIGURES
Figure 1 Model extents and topographic grid. ............................................................................. 5 Figure 2 Daily rainfall used as input to the model. ....................................................................... 5 Figure 3 Daily potential evaporation used as inputs to the model. ............................................... 6 Figure 4 - Vegetation codes map (from Table 1) ......................................................................... 7 Figure 5 – Applied rooting depth pattern for crop, crop, bare fallow, crop, crop, pasture as model
input for generating soil water balance (Pattern was repeated as per Table 1). .......... 7 Figure 6 - Areas of the catchment (green) where detention storage was applied to represent
imperfect surface drainage. ......................................................................................... 8 Figure 7 - Soil types map (Codes in Table 2) ............................................................................ 10
iv DHI Water & Environment
Figure 8 – Initial (1950) depth to groundwater. .......................................................................... 11 Figure 9 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 12 Figure 10 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 13 Figure 11 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 14 Figure 12 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 15 Figure 13 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 16 Figure 14 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 17 Figure 15 – Simulated and observed ground water levels, (X axis is the date and Y axis depth
below ground (m)). .................................................................................................... 18 Figure 16 – Simulated catchment water balance from 1/1/1950 to 1/1/2008. ............................ 19 Figure 17 – Annual flow duration curve from MIKE SHE and other sources for comparison...... 19 Figure 18 – Mean annual recharge (UZ to SZ) from 1975 to 2008 (mm/yr). .............................. 20 Figure 19 – Groundwater recharge for different vegetation based on field leakage studies
throughout Australia (CSIRO). .................................................................................. 21 Figure 20 – Simulated depth to groundwater for December 2007. ............................................ 22 Figure 21 – Simulated area with water table within 1m. ............................................................ 23 Figure 22 – Simulated depth to groundwater for December 2029. ............................................ 24 Figure 23 – Simulated areas with water table within 1m for 2008 and 2030. ............................. 25 Figure 24 – Simulated Groundwater Cross Section A-B. ........................................................... 26 Figure 25 – Simulated Groundwater Long Section C-D (Dec 2029). ......................................... 26 Figure 26 – Typical simulation of overland flow during the January 2006 flood event................ 27 Figure 27 – Modelled runoff and salinity at the catchment outlet for the Base Case and Base
Case with 20% less rainfall. ...................................................................................... 29 Figure 28 – Modelled salt load at the catchment outlet for the Base Case. ............................... 29 Figure 29 – Drains implemented in MIKE SHE as SZ drainage at 2m below the ground in the
blue cells (Farmer mapped salinity is white hatch). ................................................... 33 Figure 30 – Calibrated deep drain flow. .................................................................................... 34 Figure 31 – Modelled salt load at the catchment outlet for Scenario 8 – Based Case (Fine Scale
model). ...................................................................................................................... 36 Figure 32 – Modelled salt load at the catchment outlet for Scenario 9 – Single deep drain linking
existing drains. .......................................................................................................... 36 Figure 33 – Modelled salt load at the Kulin\Dudinin Catchment outlet for Scenario 11 –
Combination. ............................................................................................................. 37 Figure 34 – Simulated inflow and outflow to the proposed 2ha detention basin......................... 38 Figure 35 – Simulated inflow and outflow to the proposed 6ha detention basin......................... 38
TABLES
Table 1 – Vegetation Rotations ................................................................................................... 6 Table 2 - Unsaturated zone soil type properties .......................................................................... 9 Table 3 - Saturated zone parameters ........................................................................................ 10 Table 4 - Simulated areas with shallow water table. .................................................................. 21 Table 5 – Scenarios simulated with the course resolution model. ............................................. 30 Table 6 – Summary of results from the course resolution modelling. ........................................ 31 Table 7 - Saturated zone Hydraulic Conductivity for fine scale model ....................................... 32 Table 8 – Scenarios simulated with the fine scale model. ......................................................... 34
v DHI Water & Environment
Table 9 - Summary of results from the fine resolution modelling. .............................................. 35 Table 10 – Summary statistics from LASCAM model. ............................................................... 40 Table 11 – Summary of model observations and resultant recommended management
strategies. ............................................................................................................... 41 Table 12 – Estimated Cost for Option B – Engineering. ............................................................ 43 Table 13 – Estimated Cost for Option C – Vegetation. .............................................................. 44
1 DHI Water & Environment
1 INTRODUCTION
This appendix details step two of the management plan development. The plan seeks to
provide a best practice mix of management options, as appropriate to achieve effective
and acceptable salinity management for the catchment. This encompasses at least
consideration of the following:
Engineering (eg banks, diversions, drains, groundwater pumping, pipes,
catchment storage);
Modified farming practice (e.g. use of perennials and alternative cropping
systems); and
Revegetation (eg Oil Mallees) and Remnant vegetation (protected, enhanced).
The landholder consultation produced a number of management options that the
community was interested in pursuing. A numerical model was then developed to
determine the effectiveness of the proposed options at controlling groundwater levels
and the impact on surface water quantity and quality. The most effective and feasible
options were then refined and evaluated in terms of effectiveness at protecting
agricultural production, costs, and operational requirements (e.g. governance and
maintenance).
2 DHI Water & Environment
2 MANAGEMENT OPTIONS
Based on public consultation and committee input, interest was shown in the following
options for managing salinity in the catchment:
2.1 Engineering
These options help to prevent water from recharging and remove saline groundwater:
Surface water management: Incorporating surface water drains into farm and
catchment water to reduce opportunity for ponding and subsequent groundwater
recharge.
Deep drains: Using deep drains to lower watertables, preventing continued
accumulation of salts while allowing rainfall to leach salt from the upper soil
profile. This technique increases the rate of discharge, and consequently reduces
the area of groundwater discharge necessary to establish equilibrium.
Evaporation basins can be used to dispose of saline groundwater, or if suitable
conditions exist, water can be discharged to natural drainage lines.
2.2 Modified Farming Practice
To modify current agronomic practices with alternative, economically viable systems,
that increase evapotranspiration and reduce the amount of water percolating below the
root zone:
Alternative cropping systems: Crops and crop rotations that promote higher
water use e.g. continuous cropping verse pastures in a rotation.
Use of perennial plants: Deep rooted pastures which are capable of growing
throughout the year, and trees or fodder shrubs, which combine the advantages
of deep root systems and year round growth with higher water use, due to their
large leaf area.
2.3 Vegetation
Saltland pastures and crops: Saltland plants can provide some production from what is
otherwise generally unusable land.
Revegetate areas that maybe significant sources of recharge but offer low crop
potential. eg deep sands.
Revegetate areas at immediate risk of salinity (watertables 2-5 m and rising
trends) with perennials systems, continuos crops and trees (such as oil mallees).
Protect, manage and enhance the remnant vegetation: To maintain existing water
use and contribute to reducing groundwater recharge.
3 DHI Water & Environment
3 NUMERICAL MODELLING
The MIKE SHE modelling system was used to simulate the effectiveness of the
management options. It was selected for its ability to simulate realistic linkages between
surface water and groundwater, as well as dynamic distributed infiltration through the
unsaturated zone and vegetation-based soil-water deficits. In this context, MIKE SHE is
widely recognised as more reliable and defensible for decision-making. MIKE SHE is
regularly and independently reviewed as the most comprehensive and advanced model
for integrated catchment modelling (US Army Corp of Engineers et. al, 2002; Kaiser
Hill Company, 2001; Camp, Dresser and McKee, 2001; Aqua Terra et. al, 2001). Full
details of the MIKE SHE theory are given in the MIKE SHE User Manual (DHI, 2008).
3.1 Model Setup
The model domain covered the Dudinin Catchment and extended slightly into the
Lockhart River as shown in Figure 1. The horizontal model resolution was 200m. The
model topography was sampled from a 10m DEM provided by Department of
Agriculture and Food (DAFWA). Minor closed depressions in the model topographic
grid, which are generally an artefact of the DEM interpolation, were filled.
Historical daily rainfall and reference evaporation data was obtained from SILO data
drill (www.nrm.qld.gov.au/silo). To simulate future conditions the data from 1988 to
2008 was repeated into the future.
The land use\vegetation changes across the catchment were represented by different
rooting depths. Figure 4 shows spatial variation of vegetation and Table 1 shows the
corresponding vegetation rotations. The rooting depth was varied on a monthly basis
based on the following formulae:
Applied Rooting Depth = Crop Coefficient x Max rooting Depth x Calibration
Factor
Crop coefficients were obtained from AgET (Argent and George, 1997). The calibration
factor was used to tune the recharge amounts during calibration. Figure 5 shows the
calibrated rooting depth pattern for all vegetation excluding trees which were a constant
5000 mm.
5 DHI Water & Environment
Figure 1 Model extents and topographic grid.
Figure 2 Daily rainfall used as input to the model.
6 DHI Water & Environment
Figure 3 Daily potential evaporation used as inputs to the model.
Table 1 – Vegetation Rotations
Code Vegetation Rotation
1 Trees Constant Trees
2
Crop/pasture/fallow
post1950 1950 - 1965 Crop, Crop, Bare Fallow, Crop, Crop, Pasture
post1965 Crop, Crop, Pasture
3 Crop/pasture post1965 1950 - 1965 Trees
post1965 Crop, Crop, Pasture
4 Saltland post2007 post1950 Crop, Crop, Pasture
post2007 Bare Soil
7 DHI Water & Environment
Figure 4 - Vegetation codes map (from Table 1)
Figure 5 – Applied rooting depth pattern for crop, crop, bare fallow, crop, crop, pasture as model input
for generating soil water balance (Pattern was repeated as per Table 1).
Advice from the landowners on the committee was that for the period 1950 – 1965 most
farmers would apply a Crop/Pasture/Fallow cycle. Since 1965 approximately 2/3 of
farmers would have applied a 50/50 cropping/pasture cycle and the rest would have
continually cropped. This equates to an average of 75% cropping/25% pasture. This is
in line with the assumptions in the modellings which assume 67% cropping/33%
pasture post 1965.
Note, the extent and timing of assumed clearing is approximate. Code 3 (post 1965) in
Figure 4 was not all cleared in 1965, it was cleared over decades leading up to or around
1950 1951 1952 1953 1954 1955
[s]
0.0
0.5
1.0
[()]
Le
af A
re
a In
de
x
0
200
400
600
[millimeter]
Ro
ot D
ep
th
8 DHI Water & Environment
1965. It has also been suggested by the Committee that the Code 2 (cleared pre 1950)
could extend further up the valley. These approximations to the timing of the clearing of
the higher parts of the catchment may lead to lower confidence in the modelled water
tables in these areas. However the model has been calibrated to bore levels in this area
(Bore 14, 15 and 20) to minimise any bias and the salinity risks lie lower in the
catchment. Future modelling could be based on a better reconstructed clearing map.
The Dudinin and Kulin Creeks were explicitly represented as 1D channels (MIKE11)
with trapezoidal cross section (4-10m bed, 0.4m deep, 1:1 batters) and with the top of
bank aligned with the topographic grid. These channels were coupled to the aquifer
using a river bed only conductance with a very low leakage coefficient of 1e-20. This
leakage coefficient effectively limits significant exchange with the groundwater.
Observations note that groundwater does not directly intersect the creek beds (ie no
baseflow results), and is unlikely to during the simulation period. No overbank flooding
was allowed back out of the 1D channel (i.e. one way flow from overland flow to
channels) and kinematic routing was applied to both branches.
Figure 6 - Areas of the catchment (green) where detention storage was applied to represent
imperfect surface drainage.
9 DHI Water & Environment
Overland flow was simulated using the finite difference method with a Mannings n of
0.1. Detention storage of 30mm was applied to areas of the valley floor to simulate
imperfect surface drainage as shown in Figure 6. This accounts for subgrid scale
depressions. Any large depressions (e.g. towards the bottom of the catchment) are
explicitly represented in the topographic grid will retain water and overflow after a
runoff event.
Unsaturated zone was simulated using the 2 Layer Model. A DAFWA soils map of the
catchment was simplified to four basic soil types with the properties in Table 2. The
spatial extents of each soil type are shown in Figure 7. The soil properties were initially
estimated from the AgET soils database (Argent and George, 1997) but the final
properties where fine tuned during model calibration, particularly the saturated
hydraulic conductivity.
Table 2 - Unsaturated zone soil type properties
Soil Code 1 2 3 4
Name Valley Sandy
Duplex
Ironstone
Duplex
Salt Lakes
(m/s)
10 DHI Water & Environment
Figure 7 - Soil types map (Codes in Table 2)
The saturated zone was initially simulated in the coarser grid model (200m) using three
layers as parameterised below. The model was later altered to account for observed
permeability (from soil pits) and drain flows (50 m grid model).
Table 3 - Saturated zone parameters
Layer
Lower Level
(m below
surface)
Hydraulic Conductivity
(m/d) Specific
Yield (-) Horiz. Vert.
Sediments 3 1.04 0.10 0.1
Weathered 25* 0.05 0.05 0.1
Saprock 30 0.50 0.50 0.1 *25m except in valley floor below Kulin/Dudinin Creek confluences where 5m was used to
represent a palaeochannel in the bottom layer.
3.2 Model Calibration
There was limited data to calibrate the model. Groundwater data comprised of water
table levels measured at approximately 28 sites drilled by DAFWA and two by farmers.
The additional two sites, drilled in the 1950s for stock watering purposes, were also able
to be used as the water table at this time was recorded. The levels in 2007 measured
11 DHI Water & Environment
showed rises of 17 and 29m. These increases formed the basis to calibrating the
recharge component of the model. Approximately half of the remaining bores had data
from 2000 to 2007, while the other half had only one or two points measured in 2007.
The bore locations are shown in a figure in the main document.
The model was run from 1950 until 2007. The soil surface saturated hydraulic
conductivity was adjusted until the mean annual runoff was obtained that is similar to
measured from nearby catchments.
Rooting depth was then adjusted to get recharge/groundwater response observed in bore
records placing heavy reliance on the 1950 bores. The calibration plots are shown in the
next section.
Finally, the initial (1950) water table elevation across the model domain was adjusted
until the observed bores matched as closely as possible. The adopted levels are shown in
Figure 8 and indicate that levels of 15-18m below the valley floor, and elsewhere are at
the model bedrock (30m below). Note the ‘calibrated’ levels in the lower part of the
catchment are possibly deeper than might be expected. Additional bore information in
the valley floor from the 1950s would be the only way to support this but is unavailable.
Figure 8 – Initial (1950) depth to groundwater.
12 DHI Water & Environment
3.3 Base Case Results
Figure 9 to Figure 15 show the simulated depth to groundwater at a number of bores,
along with the observed water levels. Figure 9 shows the results for the two bores
drilled in the 1950s. The simulated rise is reasonably close for both bores indicating the
simulated recharge rates are suitable.
The other bores match closely with the exception of bores in the upland areas where the
measured levels are generally more than 30m below. See bore 07KU17. This may be
partially due to the deeper regolith higher in the catchment, which is not incorporated
into the model (eg 40 to 50m not 30m as assumed). Also some upland areas were
cleared after 1965 (eg Bores 07KU16-19), where as it was assumed in the model that all
upland areas were cleared in 1965. This would result in the model over estimating the
total recharge to the groundwater in these areas and hence higher than observe
groundwater levels.
It is interesting to note the simulated rate in rise (and hence recharge) is generally the
greatest in the 1960s and has reduced somewhat since then. This is supported by
anecdotal evidence (Mike Wilson, pers. comm., 2006) that indicates this period was
wetter than average where machinery commonly got bogged. Mean monthly rainfall
residuals analysis of rainfall also supports this result.
Figure 9 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
13 DHI Water & Environment
Figure 10 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
14 DHI Water & Environment
Figure 11 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
15 DHI Water & Environment
Figure 12 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
16 DHI Water & Environment
Figure 13 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
17 DHI Water & Environment
Figure 14 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
18 DHI Water & Environment
Figure 15 – Simulated and observed ground water levels, (X axis is the date and Y axis depth below
ground (m)).
Figure 16 shows the catchment water balance for the period of 1950 to 2008. The
average recharge is 21.5 mm/yr and surface runoff (River + OL boundary) is 5.1 mm/yr.
The surface runoff rate of 5 mm/yr is significantly influenced by the Jan 2006 flood
event. If this event was removed the rate would drop to approximately 3.5mm/yr which
is similar to the nearby Toolibin catchment. As a result it is concluded that the figures
obtained above are suitable for use in modelling catchment behaviour.
Figure 16 also shows the approximate percentage of the largest water balance
components. The groundwater recharge of 6% is basically the root cause of the salinity
problems in the catchment. Under preclearing conditions, the groundwater recharge
component would probably be less than 0.5% and the evapotranspiration would be
closer to 99%.
Figure 17 shows how the simulated annual flow duration curve compared with other
local sources of information. MIKE SHE produces similar flows to LASCAM but
compared to the Toolibin Gauge produces significantly more low flows (50 percentile
and less). This is probably due to the fact that the Toolibin catchment has significantly
more depression storage which prevents low flows from reaching the gauge.
19 DHI Water & Environment
Figure 16 – Simulated catchment water balance from 1/1/1950 to 1/1/2008.
Figure 17 – Annual flow duration curve from MIKE SHE and other sources for comparison.
0
1
10
100
1,000
10,000
100,000
0% 20% 40% 60% 80% 100%
Proportion of Time Less Than
An
nu
al F
low
(M
L/y
r)
Dudinin Ck Modelled
(MIKE SHE 1965-2005)
Dudinin Ck Modelled
(LASCAM 1965-2005)
Toolibin Gauged (609010
scaled for area 1979-
2005)
20 DHI Water & Environment
Figure 18 shows the mean annual recharge over the period of 1950 to 2008. The highest
recharge (38-48mm/yr) is occurring in the edges of the valley floor due to the combined
effect of the assumed earlier tree clearing and the lighter soils than in the valley. The
valley floor with the heavier soil averages 26mm/yr. The areas with trees retained have
virtually no recharge. Figure 19 supports the simulated recharge.
Figure 18 – Mean annual recharge (UZ to SZ) from 1975 to 2008 (mm/yr).
21 DHI Water & Environment
Figure 19 – Groundwater recharge for different vegetation based on field leakage studies throughout
Australia (CSIRO).
Figure 20 shows the simulated depth to groundwater for December 2007 overlayed by
areas perceived by the farmers as being salt affect (white hatching). The correlation is
reasonable however the simulated area within two metres is significantly larger than the
farmer perceived areas (8100ha vs. 3400ha). Two meters is generally assumed to be the
critical depth however this is dependent on soil type and decreases with sandy soils.
There is also a time lag from when the groundwater approaches the surface and when
salinity effects can be seen, which could explain some of the difference also. Table 4
shows that 3400ha corresponds to somewhere between 0.5m and 1m to the water table.
Based on this, 1m was adopted as the critical depth to groundwater to classify an area as
salt affected in further analysis.
Table 4 - Simulated areas with shallow water table.
Depth To Water Table
2008
Area
2030
Area
ha %* ha %*
Less than 0.5m 870 2 1580 3
Less than 1m 4150 7 8000 14
Less than 2m 7990 14 12800 22
Less then 3.5m 12040 21 17200 30
Notes: * Percent of total catchment
Figure 21 shows the growth of the shallow water table area over time. The period from
2000 to 2005, shows a reduction in area reflecting a period of low rainfall years. This
result is supported by observed bore levels. The period from 1992 to 2000 was a
somewhat wetter period that saw the area grow quickly. As the rainfall and potential
evaporation from 1988-2008 were repeated in the model for estimating future changes,
a similar pattern is simulated of a quick rise from 2012 to 2018, followed by a reduction
from 2018 to 2030. Note that even though the shallow water table area may decrease
over a period, the salt affected area is unlikely to reduce as fast, if at all. This is because
the salt will accumulate in the soil profile during the period of shallow water table and
22 DHI Water & Environment
remain in the soil profile even if the water table reduces. Some downward leaching of
salt may occur in the soil profile due to rainfall, but this process is even less likely
during these corresponded lower rainfall periods. Low permeabilities also suggest
reversibility in salt accumulation is likely to be a lengthy process.
Figure 21 also shows the model outcome is quite sensitive to lower future rainfall
which could be possible under climate change.
Figure 20 – Simulated depth to groundwater for December 2007.
23 DHI Water & Environment
Figure 21 – Simulated area with water table within 1m.
Figure 22 shows the depth groundwater in December 2029 and Table 4 shows the
corresponding areas.
0
2,000
4,000
6,000
8,000
10,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Are
a w
ith
wa
tert
ab
le w
ith
in 1
m (
ha
)
Base Case
Base Case with 20% less rain
25 DHI Water & Environment
Figure 23 – Simulated areas with water table within 1m for 2008 and 2030.
26 DHI Water & Environment
Figure 24 – Simulated Groundwater Cross Section A-B.
.
Figure 25 – Simulated Groundwater Long Section C-D (Dec 2029).
27 DHI Water & Environment
Figure 26 – Typical simulation of overland flow during the January 2006 flood event.
Figure 26 gives an indication of how MKE SHE simulates overland flow using the Finite
Difference Method. Water flows from cell to cell depending on the surrounding water
elevations (diffusive flow equation). This allows the effect of large depressions and
increased infiltration time on flow paths to be simulated. This has been observed to be
an important phenomena affecting salinity in the catchment.
3.3.1 Salt Concentration and Loads The salt concentration in runoff from wheatbelt catchments is complex, dynamic over
time and space and often strongly related to flow. There are limited flow and salt
concentration data available from the study and nearby catchments which makes the
task of estimating the impact of the various management options difficult. To allow
basic estimates of salt concentration and total salt load to be made for the purpose of
option comparison, the salt load at the study catchment outlet was calculated. This was
based on the following estimates of salt concentrations from various runoff sources:
Good Land Runoff: 400 mg/L
This is the runoff from areas that express no signs of salinity and is the average
concentration in runoff typically measured in the Kulin Catchment from areas
with no significant signs of salinity (e.g. upstream of the existing drains in
Dudinin Ck and from the upper parts of Kulin Ck.). It is also typical of the
average concentrations found in the Toolibin catchment prior to 1980.
28 DHI Water & Environment
Salt Land Runoff: 12,500 mg/L
Dogramaci et al (2004) analysed the salinity from Lake Toolibin catchment from
the salinity record over the last 20 years and suggested that the surface water
salinity has increased from ~ 900 mg/L to ~ 1,800 mg/L for an 8% increase in
area underlain by shallow watertable. Assuming the runoff rate from this land is
the same as the rest of the catchment, this 900 mg/L increase would require an
average concentration of 11,250mg/L (900/0.08) from the salt land. Another
source of salt generation data from saline land is that of a CRC Future Farm
Industries project, at Yealering, located 50 km west of the Kulin-Dudinin
Catchment. At this site, a 25 ha bunded saline paddock (a control area for a
saltland treatment) yielded 0.37 t/ha/yr (pers. comm. George R, 2008).
Assuming an average runoff rate from the saline land is 3.2 mm/yr, this equates
to an average concentration of 11,500mg/L.
Saltland Perennial Runoff: 6,000 mg/L
This is based on preliminary results from the same CRC FFI project at
Yealering. At this site, a 25 ha bunded saline paddock with saltland perennial
vegetation is producing runoff with approximately half the salt concentration of
a control area with no treatment (pers. comm. George R, 2008). These are
preliminary results at and early stage in the project and may change over time.
This trial has also shown that the runoff volume from the saltland perennial
vegetation is approximately half that of a control area with no treatment (pers.
comm. George R, 2008). This observation has been incorporated into the load
calculations also.
Groundwater discharge: 25,000 mg/L
This is based on the average concentration measured from bores in the area and
the existing deep drains discharge measured mostly in 2006. Note, due to in-
drain and in-stream evaporation losses, it is estimated that groundwater driven
streamflow would need to consistently exceed 5 to 10 L/s before Dudinin Creek
would flow continuously to the end of the catchment. At this time, particularly
in winter, flow would reach lower into the catchment. In the mean time, the salt
load will be precipitated on the creek bed and required significant surface runoff
events to mobilise it.
Based on these concentrations and the results simulated by MIKE SHE (runoff,
flow, areas with groundwater within 1m and area planted to saltland perennials
(vegetation options), the averaged salt concentration and loads were calculated on an
annual basis at the catchment outlet. Figure 27 and Figure 28 show these results for
the Base Case (Do Nothing) Scenario.
While this method is simplistic, it does allow a simple and transparent method of
estimating the averaged salt concentration and loads with the purpose of comparing
management options.
Figure 27 shows the simulated runoff is dominated by large and infrequent flood
events. These events occur every 5 to 10 years but appear to have increased in
magnitude from 1988 to 2008. This is repeated in the forecast time period due to the
repetition of the climatic data. Figure 27 also shows the simulated stream flow
29 DHI Water & Environment
salinity started rising in 1970 and accelerated after 1991 with some periods of
reduction. This is inline with the growth of the shallow water table area over time
(Figure 21) including the reduction during dryer period. These reductions maybe an
artefact of the modelling assumption and it maybe that a ‘ratchet’ effect (up only)
actually occurs. Figure 27 also shows the simulated stream flow salinity is quite
sensitive to the future rainfall with a 20% reduction causing the simulated stream
flow salinity to plateau.
Figure 28 shows the salt load from the catchment is increasing but dominated by
large and infrequent flood events which ‘flush’ the majority of the salt through the
system. The background salt (from rainfall) that comes off the catchment naturally
is relatively consistent as expected, but the salt from the salt land becomes
prominent after 1989 and increases into the future.
Figure 27 – Modelled runoff and salinity at the catchment outlet for the Base Case and Base Case with
20% less rainfall.
Figure 28 – Modelled salt load at the catchment outlet for the Base Case.
0
1,000
2,000
3,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Str
ea
mfl
ow
Sa
lin
ity
(m
g/L
TD
S)
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
Ru
no
ff (
ML
/yr)
Runoff - Base Case
Streamflow Salinty- Base Case
Streamflow Salinty- Base Case less 20% rain
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Sa
lt L
oa
d (
t/y
r)
Groundwater Discharge Salt
Saltland Runoff Salt
Catchment Runoff Salt
30 DHI Water & Environment
3.4 Scenarios
Based on the salinity management options discussed in section 2, a number of scenarios
were defined to test in the numerical model. These are given in Table 5. Scenario 0 and
1 were discussed in the previous section. For the other scenarios, the model was run
from 2008 to 2030. The results are summarised in Table 6.
Table 5 – Scenarios simulated with the course resolution model.
Scenario
Number Scenario Description
0 Base Case (Do Nothing) as defined in sections above
1 Base Case (Do Nothing) with 20% less rainfall
2 Trees replanted on all upland areas code 2 (65% of catchment)
3 Continuous cropping on arable land i.e. no perennial pastures.
4 2m deep drains covering area within 1m at Dec 2007 (4100ha)
5 Single deep drain parallel to Dudinin Ck linking existing drains
6 Surface Water Management - No depression storage on valley floor
7 Saltland Perennial System covering area within 1m at Dec 2007 (4100ha)
31 DHI Water & Environment
Table 6 – Summary of results from the course resolution modelling.
Scen
ario
Scenario
Short
Description
Area with
water table
less than
1m in 2030
(ha)
Change in
2030 Area
Compared
to Base
Case
(ha)
(%)*
Mean
Salinity
Concentra-
tion
2025-2030
(mg/L) #
Mean
Runoff
Volume
2025-2030
(ML/yr)
Mean Salt
Load 2025-
2030
(t/yr)
0 Base Case 8,000 0 1,800 16,400 29,100
1 Base Case 20%
less rainfall
3,800
-3,200
-40% 1,200 10,100 11,600
2 Trees on all
upland areas
7,100
-900
-11% NA NA NA
3 Deep rooted
farming
5,400
-2,600
-32% NA NA NA
4 2m Deep
drains (4100ha)
4,100
-3,900
-49% 17,400 17,400 70,900
5
Single deep
drain linking
existing drains
7,500
-500
-6% 13,800 16,700 41,400
6 Surface Water
Management
7,800
-200
-2% NA NA NA
7
Saltland
Perennial
System **
2,100
-5,900
-74% ~1,700 ~15,900 ~22,200
Notes:
* Percent reduction from Base Case area is also given. In 2008, 4100ha was modelled with
water table less than 1m.
# Time weighted mean based on the mean annual concentration for each of the 5 years summed
and then divided by 5. This is significantly higher than the flow weighted mean which may be
calculated by dividing the last column by the second last column. Time weighted mean is used
because it is not affected by floods as much.
** A significant limitation of the model is the fact that there is no restriction in the water use by
vegetation and the salt concentration in the ground water. The model assumes that if the
groundwater rises into the root zone then the vegetation can extract that water. With the very
saline groundwater experienced in the study catchments it is unlikely the vegetation will be able
to use much of this water. Some proposed vegetation maybe able to use saline groundwater (eg
Salt bush and lucerne) but this will be restricted by the high groundwater salinity. This attribute
of the model will lead to a significant over estimation of the effectiveness of this scenario at
managing the catchment salinity. Local empirical data suggests that saltland plantings reduce
watertables by between 0.1 to 0.5m.
32 DHI Water & Environment
3.5 Fine Scale Modelling
Due to difficulty in modelling the existing deep drains observed flows, a finer scale
model was developed (50m grid). Overland flow simulation had to be simplified to the
lumped model in MIKE SHE as the model run times became too large. The saturated
zone hydraulic conductivities were recalibrated to those given in Table 7. These values
are supported by the test pits which generally showed low hydraulic conductivities and
are in line with published values (George 1992). However these values are significantly
lower than those adopted for the course scale model. The calibration results for the
deep drain flow are shown in Figure 30.
Table 7 - Saturated zone Hydraulic Conductivity for fine scale model
Layer Hydraulic Conductivity (m/d)
Horz. Vert.
Sediments 0.010 0.001
Weathered 0.010 0.001
Saprock 0.50 0.050
Based on the outcomes from the course-scale model, the management options were
refined to those shown in Table 8. For each scenario, the model was run from 2008 to
2030. The results are summarised in Table 9 and shown graphically in Figure 31, Figure
32 and Figure 33. These figures all show that the majority of the salt movement occurs
during the years with large flow events. The contribution from saltland is the dominant
source of salt post 2000 and grows into the future. Figure 32 shows that although the
load from the deep drains is less than 10% of the total load, it is quite consistent and
during the years with no major runoff events is the dominant source with over 90% of
the load. This would generally express itself as was experienced when the existing
drains were open; creek flow being of high salinity concentration for much longer than
previously experienced. Figure 33 shows the total load of the combination option is
approximately half of the load from the other figures and the ground water contribution
(from the deep drains) is almost non existent. This is because the vegetation is assumed
to be planted right up to the edge of the drains and thereby limiting the inflow into the
drains.
33 DHI Water & Environment
Figure 29 – Drains implemented in MIKE SHE as SZ drainage at 2m below the ground in the blue
cells (Farmer mapped salinity is white hatch).
34 DHI Water & Environment
Figure 30 – Calibrated deep drain flow.
Table 8 – Scenarios simulated with the fine scale model.
Scenario
Number Scenario Description
8 Base Case (Do Nothing)
9
Engineering Option:
Single deep drain parallel to Dudinin Ck linking existing drains and
extending to upstream of Commonwealth Road where a detention basin
will be sited.
Drain lengths: 13km existing and 13km new. Drain Depth: 2m deep.
10
Vegetation Option:
Saltland perennials (e.g. saltbush blocks and alleys) on areas identified as
showing signs of salinity by farmers in 2007 - 4100ha
Areas identified as at risk by 2030 to be treated with a 10% tree (Eg Oil
Mallee), 20% perennial plants (E.g. Lucerne), and remainder continuous
cropping system. Total 4000ha
11 Combined Engineering and Vegetation Option
(Scenario 9 and 10 treatments combined)
0
1
2
3
4
5
6
7
8
9
10
Ap
r-2
00
4
Ju
n-2
00
4
Au
g-2
00
4
Oct-
20
04
De
c-2
00
4
Fe
b-2
00
5
Ap
r-2
00
5
Ju
n-2
00
5
Au
g-2
00
5
Oct-
20
05
De
c-2
00
5
Fe
b-2
00
6
Ap
r-2
00
6
Ju
n-2
00
6
Au
g-2
00
6
Dra
in F
low
(L
/s)
Modelled
Observed
35 DHI Water & Environment
Table 9 - Summary of results from the fine resolution modelling.
Scen
ario
Scenario
Short
Description
Area with
water table
less than
1m in 2030
(ha)
Change in
2030 Area
Compared
to Base
Case
(ha)
(%)*
Mean
Salinity
Concentra-
tion
2025-2030
(mg/L) #
Mean
Runoff
Volume
2025-
2030
(ML/yr)
Mean Salt
Load 2025-
2030
(t/yr)
8 Base Case 12,530 0 2,200 17,170 39,300
9
Single deep
drain linking
existing
drains
12,375
-155
(-1%)
2,200
+25,000 Drain
17,130
+130
Drain
38,800
+3,200
Drain
10 Vegetation**
@ 4,155
-8,375
(-67%) 1,210 15,800 19,100
11 Combination
@
4,000
-8,530
(-67.5%)
1,180
+25,000 Drain
15,800
+65 Drain
18,600
+1,600
Drain
Notes:
* Percent reduction from Base Case area is also given.
# Time weighted mean based on the mean annual concentration for each of the 5 years
summed and then divided by 5. This is significantly higher than the flow weighted
mean which can be calculated by dividing the last column by the second last column.
Time weighted mean highlights is used because it is not affected by floods as much.
** Scenario 10 results were not explicitly modelled but estimated based on the results
from Scenario 9 and 11.
@ A significant limitation of the model is the fact that there is no restriction in the water
use by vegetation and the salt concentration in the ground water. The model assumes
that if the groundwater rises into the root zone then the vegetation can extract that water.
With the very saline groundwater experienced in the study catchments it is unlikely the
vegetation will be able to use much of this water. Some proposed vegetation maybe able
to use saline groundwater (eg Salt bush and lucerne) but this will be restricted by the
high groundwater salinity. This attribute of the model will leads to a significant over
estimation of the effectiveness of this scenario at managing the catchment salinity.
36 DHI Water & Environment
Figure 31 – Modelled salt load at the catchment outlet for Scenario 8 – Based Case (Fine Scale
model).
Figure 32 – Modelled salt load at the catchment outlet for Scenario 9 – Single deep drain linking
existing drains.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Sa
lt L
oa
d (
t/y
r)
Groundwater Discharge Salt
Saltland Runoff Salt
Catchment Runoff Salt
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Sa
lt L
oa
d (
t/y
r)
Groundwater Discharge Salt
Saltland Runoff Salt
Catchment Runoff Salt
37 DHI Water & Environment
Figure 33 – Modelled salt load at the Kulin\Dudinin Catchment outlet for Scenario 11 – Combination.
3.5.1 Detention Basin To manage the expected low flows in drier years (Figure 34), a detention basin is
proposed for Scenario 9 and 11 at or near Commonwealth Road, at the end of the
proposed single deep drain running parallel to Dudinin Ck linking existing drains. The
purpose of this basin is not to evaporate all of the drain flow, but to store salt during low
flow periods and to over flow during high flow periods when it is intended a significant
creek flow will dilute the salt. The size of the basin will determine the effectiveness at
achieving this. Figure 34 and Figure 35 show the simulated inflow (from Scenario 9
model) and outflow (from simple water balance) from a 2ha and 6ha basin respectively.
These results suggest the basin may need to be at least 6ha. However, it is thought the
MIKE SHE model maybe overestimating the drain flows, particular the peak flows. It is
also likely that if Scenario 11 is adopted as a management option then the vegetation
component of it may reduce the drain flows, particularly if the vegetation options are
planted right up to the drains. Further analysis is recommended if this detention basin is
to proceed.
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
20
05
20
10
20
15
20
20
20
25
Year
Sa
lt L
oa
d (
t/y
r)
Groundwater Discharge Salt
Saltland Runoff Salt
Catchment Runoff Salt
38 DHI Water & Environment
Figure 34 – Simulated inflow and outflow to the proposed 2ha detention basin.
Figure 35 – Simulated inflow and outflow to the proposed 6ha detention basin.
3.6 Discussion
3.6.1 Effectiveness of saltbush at lowering the water table The native saltbush, Atriplex nummularia, is a deep-rooted perennial shrub tolerant of
drought, saline soils and shallow water tables. This plant has been shown to lower water
tables and stabilise soil. It can therefore reduce salinity impact in vulnerable areas as its
deep rooting ability will ensure that recharge is reduced. Saltbush has water efficient
leaves, deep roots and a strong osmotic (cell sap) force. This means saltbush can extract
0
5
10
15
20
25
30
Jan
2008
Jan
2010
Jan
2012
Jan
2014
Jan
2016
Jan
2018
Jan
2020
Jan
2022
Jan
2024
Jan
2026
Jan
2028
Date
Flo
w (
L/s
)Basin Inflow
Basin Outflow
0
5
10
15
20
25
30
Jan
2008
Jan
2010
Jan
2012
Jan
2014
Jan
2016
Jan
2018
Jan
2020
Jan
2022
Jan
2024
Jan
2026
Jan
2028
Date
Flo
w (
L/s
)
Basin Inflow
Basin Outflow
39 DHI Water & Environment
more soil moisture (70% of available soil moisture), from a greater depth (down to 5m)
and saline water.
Ferdowsian et. al. (2002) showed that saltbush can lower groundwater levels to below
the capillary fringe and thus prevent ongoing worsening of soil salinity at the surface.
Judging from two bores that they established and monitored for 56 months, the effect of
saltbush on watertable levels was mostly achieved within 30 months after planting.
After that period, saltbush managed to keep groundwater levels at bay and prevent them
from rising again. There are impediments preventing saltbush from further lowering the
watertable. Groundwater salinity (27,000 mg/L) and high salt storage (i.e. >15 Kg/m3)
are likely to be prominent amongst these limiting factors.
It appears that the saltbush is not drawing on the highly saline groundwater below
depths of 1.5 to 2 m. In many areas increased concentration of chloride beneath stands
of saltbushes can become a problem (see for example Barrett-Lennard and Malcolm,
1999). However, in the environmental studied, the production system appears to be
sustainable, subject to survival of the saltbush plants. Because this part of the landscape
has a one-dimensional groundwater flow system (i.e. movement is predominantly up
and down, not to the side) salt build-up in the root zone of the saltbush plants will be
moderated. This may not be the case where saline groundwater from another area flows
to the root zone and replaces the depleted watertable.
This research is supported by local anecdotal experience by A Bowey (pers. comm.
2009) who has used saltbush as a salinity management tool for a number of years in the
lower Kulin Catchment.
Note though, Slavich et. al. (1999) conducted a very thorough study examining the
water use of salt bush in NSW and found that although saltbush can establish and grow
slowly on highly saline land, its capacity to transpire saline groundwater is small
relative to recharge from rainfall. This could be due to the limited leaf area (LIA 0.35)
as a result of grazing pressure and salinity build-up from the use of groundwater
restricting the effective rooting depth to less than 0.6m.
Based on this information, it appears saltbush can be an effective method of preventing
ongoing worsening of soil salinity at the soil surface but there are some limitations
including:.
Saltbush needs to be established early enough so that salinity is not given time to
build-up in the root zone and significantly restrict the saltbush rooting depth.
Grazing pressure should be managed so that it does not significantly limit the
leaf area.
In area with significant lateral groundwater movement (e.g. break of slope),
saltbush’s effectiveness could decrease over time as the lateral ground water
movement continually brings more salt into the root zone.
3.6.2 Deep Drain Discharges As a comparison to the drain discharges modelled here, other studies from the wheatbelt
have observed the following flows:
40 DHI Water & Environment
Beynon Road Drain: Discharge flow data for the 2m drain measured at
0.14L\s\km (average of winter end summer flow).
Narambeen Drainage System: Producing 6ML/d of baseflow from
approximately100km of 2.5 to 3 m drain or 0.7 L/s/km (SKM, 2007). CSIRO
reports numbers of 0.6 L/s/km (CSIRO, Ali et al, 2000)
8 Mile drains, 2.5 m, Mean drain base flow 1 L/sec or ~0.1 L/s/km
Dumbleyung drains, 2 m; 55 km at ~4 L/sec or <0.1 L/s/km
The Scenario 9 modelling for this study shows an average of 5 L/s for 26 km (13 km old
and 13 km new) of drain or 0.2L/s/km. This maybe twice the actual.
3.6.3 LASCAM Results As a comparison to the result presented here, Table 10 shows summary statistics from
CSIRO’s LASCAM modelling with No Drainage scenario. The period 2018 to 2023
was selected so a large flow event (equivalent to 1990 rainfall event) was included
which significantly affects the outcomes and is more comparable to the Table 8 values.
The results for the Kulin/Dudinin Catchment in Table 8 are comparable to Table 10
although the flows is lower from LASCAM. Table 10 also shows the relative salt
contribution of the Kulin/Dudinin Catchment compared to the other major sources in
the vicinity.
Table 10 – Summary statistics from LASCAM model.
Location
Mean Runoff Volume
(ML/yr)
Mean Salt Load
(t/yr)
Kulin/Dudinin Catchment before joining
Lake Jilikin Outflow 4,557 37,055
Lake Jilikin Outlet 7,695 230,850
Camm River- before joins Lochart 11,390 100,967
41 DHI Water & Environment
3.7 Recommendations From Model Outcomes
The numerical modelling has been very useful at helping stakeholders to understand and
visualise the salinity issue at the local level and in a quantitative fashion. Whilst the
model has some limitations, the results provide useful observations that enable the
following recommendations to be made.
Table 11 – Summary of model observations and resultant recommended management strategies.
Modelling Observation Recommended Management Strategy
Deep Drains adds a lot of salt to the
surface waters in dry years but in
wet years the salt load from the
saltland delivers most of the load.
Drained water should be separated from
surface water and disposal options may be
required for dry years with overflow in wet
years.
Deep Drains at close spacings may
have a significant affect on reducing
areas with high water tables.
Introduce deep drains where permeability and
benefit are favourable taking into account
disposal issues.
Saltland Perennial System have a
significant affect on reducing area
with high water tables. Model
overestimates benefit.
Plant saltland perennial crops into areas too
saline for cropping. (Block on Type 1, Alleys
Type 3 & Type 2)
Deeper rooted crop rotations have
a moderate affect to reduce the rate
of water table rise.
Promote and implement deeper rooted crop
rotations into farming systems of the whole
catchment.
Future rainfall has a significant
affect on the areas with high water
table and at risk.
An adaptive management strategy would be
beneficial in terms of when and where actions
should be triggered.
Replanting trees higher in the
catchment has minor impact to
2030.
Don’t put much effort in here from a salinity
point of view.
Surface water management has
minimal impact on water tables.
Model may under estimate benefit.
Use to manage freshwater flow and enable
better production on valley floors.
42 DHI Water & Environment
4 FINAL OPTIONS EVALUATION
Based on these findings the following options were taken to the landholders for
consideration in the form of a community forum. These options generally follow the
scenarios of fine scale modelling.
OPTION A – DO NOTHING
The existing drains remain blocked and no other management changes are made in the
catchment to address the further onset of salinity changes into the future.
OPTION B – ENGINEERING
Single deep drain parallel to Dudinin Ck linking existing drains and extending down to
upstream of Commonwealth Road where a detention basin will be sited. This options is
discussed in more detail in the body of the plan.
OPTION C – VEGETATION
A mixture of vegetation options on areas identified as at risk by 2030. This options is
discussed in more detail in the body of the plan.
OPTION D - COMBINATION
A combination of Engineering and Vegetation options defined above.
The evaluation of these management options needs to give due consideration to
effectiveness at protecting agricultural production, costs, environmental impacts, social
impacts and operational requirements (e.g. governance and maintenance). These are
briefly discussed below.
4.1 Effectiveness At Protecting Agricultural Production
The estimated effect of each option on agricultural land productivity in order of
decreasing effectiveness is:
Option C - Vegetation: 7% of the catchment becomes significantly salt affected and
14% of the catchment is less productive because it is planted to saltland perennials and
oil mallee alleys.
Option D - Combination: 7% of the catchment becomes significantly salt affected and
14% of the catchment is less productive because it is planted to saltland perennials and
oil mallee alleys. This reduces the income to the community and viability of farming
operations.
Option B - Engineering: 22% of the catchment becomes significantly salt affected
because only 150ha is reclaimed.
Option A – Do Nothing: 22% of the catchment becomes significantly salt affected.
43 DHI Water & Environment
4.2 Cost
The estimated 20 year cost for implementing each option in order of increasing cost is:
Option A - Do Nothing: $0
Option B - Engineering: $690,000
Option C - Vegetation: $5,690,000
Option D - Combination: $6,380,000
Note these costs do not include economic losses due to increasing salinity such as lost
agricultural production, infrastructure damage, lost water supplies, etc.
Details of these figure is given in Table 12 and Table 13. Note Table 12 is the total cost
estimate for the engineering option but this option could be implemented in Stages
discussed in the main document. The components required for each stage are shown in
the comment column of Table 12.
Table 12 – Estimated Cost for Option B – Engineering.
Captal Cost
Item Amount Units Unit Cost Cost Comment
Surface Water Drain Construction 8 km 5,000$ 40,000$ Stage 1 - Diversion Drain around Kulin Creek
Diversion Structure 1 - 10,000$ 10,000$ Stage 1
Deep Drain Construction 13 km 13,000$ 169,000$
Stage 3 - 13km Aerterial Drain to connect the
existing drains
Road and Creek Crossings 13 - 5,000$ 65,000$
Stage 3 - A crossing every kilometre, culverts under
shire roads
Detention Basin 4 Ha 13,000$ 52,000$ Stage 3
Subtotal for Capital 336,000$
Overheads & Contingency 30 % 100,800$
Overall Capital Cost 436,800$
Operation and Maintenance Cost (over 20yr)*
Item Unit Cost/yr
Surface Drain Maintenance 8 km/yr 200$ 32,000$
Deep Drain Maintenance 26 km/yr 400$ 208,000$ Proposed (13km) and exisiting drains (13km)
Detention Basin Maintenance 4 ha/yr 200$ 16,000$
Subtotal for Operation and Maintenance 256,000$
Total Cost 692,800$
* Assumes No Net Present Value Discounting Applied
44 DHI Water & Environment
Table 13 – Estimated Cost for Option C – Vegetation.
4.3 Environmental Impacts
One indicator of environmental impact is the salt load travelling through and leaving the
catchment. Assuming the salt in all options is not retained within the catchment but is
exported from the system, the environmental impact for each option in order of
increasing impact is:
Option C - Vegetation: An average of 19,000 t/yr of salt leaves the catchment in
2030. This option also has the advantage of providing increased catchment vegetation
which may promote increased biodiversity.
Option D - Combination: An average of 20,000 t/yr of salt leaves the catchment in
2030. This option also has the advantage of protecting some infrastructure, paddocks
and providing increased catchment vegetation which may promote increased
biodiversity.
Option A - Do Nothing: An average of 39,000 t/yr of salt leaves the catchment in
2030.
Option B - Engineering: An average of 42,000 t/yr of salt leaves the catchment in
2030.
4.4 Social Impacts
The estimated social impact for each option in order of increasing social impact is:
Option C - Vegetation: 7% of the catchment becomes significantly salt affected plus
14% of the catchment is less productive such as saltland perennials and oil mallee
Captal Cost
Item Amount Units Unit Cost Cost Comment
Salinity Type 1: Saltbush - block planting 1830 ha 350$ 640,500$
350 plants per ha x $1 seeding + $260ha for
spraying & planting
Salinity Type 2 & 3: Saltbush alleys with pasture in
between 668 ha 435$ 290,580$
4m wide @ 15m alleys = ~25% perennial cover at
350 plants per ha x $1 seeding + $260ha for
spraying & planting
Salinity Type 4: Reduced Recharge Vegetation System:
Oil Malees, Perennial Pasture, Cropping option 5502 ha 301$ 1,653,901$
7m wide @ 60m alleys = ~11.6% perennial cover at
350 plants per ha x $1 seeding + $260ha for
spraying & planting
Rest of Catchment: Cropping systems that reduced
recharge through use of more water 50000 - -$ -$ E.g. continuous cropping
Subtotal for Capital 2,584,981$
Overheads & Contingency 20 % 516,996$
Overall Capital Cost 3,101,977$
Operation and Maintenance Cost (over 20yr)* Unit Cost/yr
Salinity Type 1: Saltbush - block planting 1830 ha 18$ 640,500$ 5% of upfront cost
Salinity Type 2 & 3: Saltbush alleys with pasture in
between 668 ha 22$ 290,580$ 5% of upfront cost
Salinity Type 4: Reduced Recharge Vegetation System:
Oil Malees, Perennial Pasture, Cropping option 5502 ha 15$ 1,653,901$ 5% of upfront cost
Subtotal for Operation and Maintenance 2,584,981$
Total Cost 5,686,959$
* Assumes No Net Present Value Discounting Applied
45 DHI Water & Environment
alleys. As these treatments are generally not as productive as grain growing, this
reduces the income to the community and viability of farming operations.
Option D - Combination: 7% of the catchment becomes significantly salt affected plus
14% of the catchment is less productive such as saltland perennials and oil mallee
alleys. As these treatments are generally not as productive as grain growing, this
reduces the income to the community and viability of farming operations. Also the flow
of saline deep drainage water through landholders properties can cause social
disharmony.
Option A – Do Nothing: 22% of the catchment becomes significantly salt affected. As
these treatments are generally not as productive as grain growing, this reduces the
income to the community and viability of farming operations.
Option B - Engineering: 22% of the catchment still becomes less productive salt
affected land. As these treatments are generally not as productive as grain growing, this
reduces the income to the community and viability of farming operations. Also the flow
of saline deep drainage water through landholder’s properties can cause social
disharmony.
4.5 Operational & Governance Requirements
The estimated operational and governance requirements for each option in order of
increasing complexity is:
Option A – Do Nothing: Requirements as they exist today.
Option C – Vegetation: Minimal requirements. Each landowner manages their own
implementation and maintenance.
Option B - Engineering: Significant requirements. The arrangements can range from
‘no formal governance structure’ where each landowner manages their own
implementation and maintenance. However the responsibilities, risks and liabilities are
unclear.
A more complex governance arrangement could be a ‘Drainage Management Authority’
where:
Shire or Roe VROC establishes a ‘Drainage Management Authority’ within its
structure, and provides full cost recovery service
Landholders retain ownership, lease land to ‘Drainage Management Authority’
Funds raised from landholders owning main drain alignment, with funds collected from
other landholders as they connect to the system
‘Drainage Management Authority’ reports operations through normal procedures
Risk and liabilities identified and documented.
Option D - Combination: Requires the arrangements of both Options B and C.
46 DHI Water & Environment
5 CONCLUSIONS
The landholder consultation process produced a number of management options that the
community was interested in analysing. A numerical model was developed to determine
the effectiveness of the options at controlling groundwater levels and the impact on
surface water quantity and quality. The most effective and feasible options were then
refined and evaluated in terms of effectiveness at protecting agricultural production,
costs, environmental impacts, social impacts and operational requirements (e.g.
governance and maintenance). The outcomes could be summarised as:
Vegetation options seem to be the most useful option for mitigating the effects
of secondary salinity but must be established before category 1 salinity levels
are reached. However, this is not without a significant cost for establishment,
maintenance and reduced productivity compared to current cropping systems.
Engineering options in the form of deep drains were not shown to be generally
effective or economic at mitigating the effects of secondary salinity due to the
low hydraulic conductivity of the soil in the valley floor. However, it is
recognised that the analysis may under estimate the effectiveness, especially in
areas of the catchment where the hydraulic conductivity of the soils are higher or
where improved designs are used (eg parallel drains). Once category 1 levels of
salinity are reached deep drains represent the only possible solution and
therefore it is also acknowledged that some landowners may still desire to use
deep drains as a management options and this option should be allowed if
suitable disposal methods for the saline water can be developed to all
stakeholders satisfactions. In this regard consideration could be given to larger
detention or evaporation basins.
47 DHI Water & Environment
6 REFERENCES
Aqua Terra, West Consultants and Gartner Lee for Tampa Bay Water, May 2001, Scientific
Review of the Integrated Hydrologic Model ISGW/CNTB and summary of comparison
Argent, R.M. and George, R.J., 1997. ‘AgET’ - A water balance calculator for dryland salinity
management - MODSIM ‘97, International Congress on Modelling and Simulation, Hobart 8-11
December, pp 5.
Barrett-Lennard, E.G. and Malcolm, C.V., 1999, Increased concentration of chloride beneath
stands of saltbushes (Atriplex species) suggest substantial use of groundwater: Australian Journal
of Experimental Agriculture, 39, 949-55,
Camp, Dresser and McKee, 2001, Evaluation of Integrated Surface Water and Groundwater
Modeling Tools and summary of rankings
DHI, 2008, MIKE SHE User Manual, DHI, Denmark
Dogramaci, S., George, R., Mauger, G., and Ruprecht, J., 2004, Water balance and salinity trend,
Toolibin catchment, Western Australia, Department of Conservation and Land Management
Ferdowsian R., D.J. Pannell and M. Lloyd 2002. Explaining groundwater depths in saltland:
impacts of saltbush, rainfall, and time trends, SEA Working Paper 02/09, School of Agricultural
and Resource Economics, University of Western Australia, Crawley, Australia.
http://cyllene.uwa.edu.au/~dpannell/dpap0209.htm
George, R.J., 1992. Hydraulic properties of groundwater systems in the saprolite and sediments
of the wheatbelt, Western Australia. Journal of Hydrology, 130:251-278.
Kaiser Hill Company, 2001, Model Code and Scenario Selection Report Site-Wide Water
Balance for Rocky Flats Environmental Technology Site and summary of rankings
P. G. Slavich, K. S. Smith, S. D. Tyerman, G. R. Walker, Water use of grazed salt bush
plantations with saline watertable, Agricultural Water Management, Volume 39, Issues 2-3, 25
February 1999, Pages 169-185, ISSN 0378-3774, DOI: 10.1016/S0378-3774(98)00077-8.
US Army Corp of Engineers, South Florida Water Management District, and Kimley-Horn and
Assoc. Inc., 2002, Everglades Agricultural Area - Model Evaluation Report