Assessing Water Sharing Rules in Unregulated Rivers in NSW: Mooki Riverageconsearch.umn.edu/bitstream/173974/2/Aluwihar.pdf · · 2017-04-01Assessing Water Sharing Rules in Unregulated

46th Annual Conference of the Australian Agricultural and Resource Economics

Society

Canberra, 13-15 February 2002

Assessing Water Sharing Rules in Unregulated Rivers in NSW: Mooki River

Aluwihare, P.B., Crean, J., Young, R.T

Economic Services Unit, NSW Agriculture1

The new Water Management Act (2000) requires water to be specifically allocated for

environmental purposes to try to improve river health. Water sharing plans are being

developed which establish extractive and environmental shares to river flows. A key

consideration in the development of these plans is the economic trade-offs associated

with different allocation options. In unregulated catchments, allocation rules typically

involve significant restrictions to extractive access at times of low river flows, which

also coincides with periods of environmental stress.

The highly variable nature of stream flows in unregulated catchments creates

challenges not only to the development of plausible sharing rules but also to the

assessment of their effects. In this paper proposed water sharing rules in the Mooki

sub-catchments in Northern NSW is examined. A combination of representative farm

(linear programming) and hydrology simulation modelling is used to explore these

effects.

Key words: flow sharing rules, modelling, farm-level economic impacts.

�

The views expressed in this paper are of the authors and not necessarily those of NSW Agriculture or

the New South Wales Government

Assessing water sharing rules in unregulated rivers

46th

Annual AARES Conference

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1. Introduction

Water policy reform has received considerable attention in recent years. This is due

to growing community concerns regarding environmental degradation in rivers and

wetlands, increasing evidence of the poor state of land resources in irrigation areas

and a greater government focus on improving the economic efficiency of water

allocation. Significant reforms to regulated rivers (those where flows are regulated by

major irrigation storages) and groundwater resources have been under way for several

years (Crean and Young 2001). The NSW Government is now implementing a suite

of reforms to the management of unregulated rivers.

In unregulated rivers across New South Wales (NSW), the absence of an efficient set

of rights governing access to water is one of the main factors contributing to a decline

in river health and preventing an improvement in the efficiency of water use. The

deterioration of stream health, decline in the condition of riparian vegetation, damage

to the habitat of threatened species and a decline in water quality (increase in salinity,

turbidity, and decline in dissolved oxygen) are the main environmental problems

found in unregulated rivers (DLWC 2001a). These problems are caused mainly by

the extraction of water during low and moderate flows. Natural low flows are

important for maintaining pool connectivity, minimising stagnation and stratification

of pools, and preventing concentration of pollutants (DLWC 2001a). Maintenance of

pools during dry periods is also critical for the survival of fish and aquatic species.

Excessive extraction of moderate flows affects the distribution of food and

transportation of sediments, nutrients and organic carbon downstream. Moderate

flows are also important for de-stratification of pools.

In addition to improving environmental outcomes, improving economic efficiency

and equity has emerged as a major issue in water management as competition for

surface water has increased. However, the absence of a clear specification of water

access rights has been a major barrier for the efficient management of water in the

unregulated rivers of NSW.


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The NSW government is currently addressing this poor specification of property

rights through the development of a suite of water sharing plans for each unregulated

river in the state. These are being developed by community based River Management

Committees (RMCs) and detail the way water is to be shared between the

environment, irrigators and other users.

Twelve environmental objectives have been established as a basis for the

development of water sharing plans (DLWC 2001b). These include the need to better

mimic natural flow variability and protect low and moderate flows. While the

economic benefits associated with these environmental improvements may be high,

changing the flow access rules may also impose significant costs on existing

irrigators. Therefore, in developing socially acceptable flow access rules the

committees need to consider trade-offs between water for the environment and for

other users. Natural resource management agencies, like NSW Agriculture, provide

support to RMCs in developing their water sharing plans. This includes assistance in

assessing the socio-economic trade-offs associated with various sets of river flow

access rules.

NSW Agriculture has provided a number of reports to RMCs evaluating trade-offs for

regulated rivers and for groundwater aquifers (Carter et al. 2000; Jayasuriya and

Crean 2000, 2001; Jayasuriya et al. 2001). However, the approaches developed for

regulated rivers and groundwater cannot be directly applied for unregulated rivers.

This is because of the highly variable nature of river flows, within and between years

and the complicated rules regarding flow extraction and application to crops. In this

paper a methodology developed to assess the on-farm impacts of flow rules for

unregulated rivers in NSW is discussed. This is done by reference to a study

undertaken for the Namoi Unregulated River Management Committee (NURMC) of

the Mooki Catchment in northern NSW.

The paper is structured as follows. Section 2 provides background information about

the Mooki Catchment. Flow rules developed for the Mooki by the NURMC are

outlined in Section 3. Section 4 contains a discussion of possible methodological

approaches for assessing the impacts of water sharing rules in unregulated catchments


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and the approach adopted in this study. Section 5 presents the results. Finally, a

discussion and conclusion are presented in Section 6.

2. The Mooki Sub-Catchment

The Mooki sub-catchment lies at the eastern end of the Namoi Valley located in

Northern NSW (Figure 1). The Mooki sub-catchment covers an area of about 840

square kilometers which is about 2 per cent of the Namoi Catchment area. Irrigated

agriculture is an important contributor to the regional economy of the Namoi Valley.

The value of irrigated agricultural production was around 290 million dollars in 1997

(NSW Agriculture 2001a). The Mooki sub-catchment was settled by European

graziers in the 1830s. Dryland cropping progressively expanded on the black alluvial

soils of the flood plain during the first half of the last century. Irrigation development

began in 1965 which also focused on the black alluvial soils of the flood plain.

Currently there are 23 irrigators licensed to extract water from the Mooki River.

About 50 percent of these have access to surface water only while the remainder has

access to both surface and groundwater. The total area authorised for irrigation using

surface water is around 3,500 ha. Currently, around 2,900 hectares have been

developed for irrigation (Powell 2001).

The irrigated agricultural enterprises in the Mooki sub-catchment include cotton,

wheat, maize, summer oilseeds and vegetables. Over the past two decades, the area of

cotton has expanded rapidly reflecting its relative profitability. Cotton and wheat

account for around 70 and 20 per cent of the irrigated area, respectively. Back to

back cotton and a cotton-wheat rotations are the most common practices in the

catchment. Furrow irrigation is the predominant irrigation method for all crops,

although there is some spray irrigation in the upper sub-catchment. Most irrigated

farms also have a dryland farming component. Sorghum and wheat are the most

commonly grown dryland crops in the catchment.


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2.1. River flows

The Mooki River is dependent on inflows from the Phillip, Warrah and Quirindi water

sources as well as localised rainfall in the Mooki sub-catchment. The Mooki River

displays a highly variable flow pattern. The daily pattern of flow for a typical year is

detailed in Figure 2. While the median daily flow is 10 MLs, it ranges from 0 to over

50,000 MLs. Due to the highly variable flow pattern and the small number of days on

which flow is available for extraction (around 35 percent of the time) on-farm water

storages are essential for ensuring irrigation availability throughout the irrigation

season.

Figure 2. Daily flow in the Mooki River, 1989

Note: The daily flows during days 291 to 351 have been truncated in order to present

a reasonable scale for other flow events. Actual daily flows reached maximum of

4,500 MLs.

0

500

1000

1500

2000

2500

3000

1 11 21 31 41 51 61 71 81 91101

111121

131141

151161

171181

191201

211221

231241

251261

271281

291301

311321

331341

351361

Day

MLs


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3. Rules for Sharing River Flows

3.1 Current Flow Sharing Rules

Currently, irrigation licences are based on the area irrigated irrespective of the volume

of water used. A “Commence to Pump”(CTP) threshold establishes the minimum

flow level that the river must reach before irrigators can start their pumps. This rule

aims to protect low flows and allow flow to build up to levels useful for irrigators in

down stream river reaches. In the Mooki sub- catchment one CTP level has been set

at 50 MLs/day.

3.2 Proposed Flow Sharing Rules

Under the Water Management Act 2000, all area based licences are being converted to

a volumetric basis to better define irrigators’ access rights, to encourage improved

irrigation efficiency and to facilitate trade. Volumetric entitlements have been

established by looking at the historical area of each crop type irrigated for each

irrigator. These areas were then multiplied by the theoretical water requirement for

each crop type for that climatic zone (different climatic zones were established across

the state).

In addition to an annual volume limit, flow variability requires a mechanism by which

each flow event can be shared between irrigators, the environment and others users.

A generic approach has been developed across the state to divide river flows into four

categories. These are based on a flow duration curve (Figure 3) and are defined as

follows:

1. Basic low flows - very low flows not available for extraction. As a general rule

flows exceed this level for 95 percent of days (the 95th

percentile).

2. Class A - low flows generally between the 95th

and 80th

percentile.

3. Class B - low to moderate flows generally between the 80th

and 50th

percentile.


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4. Class C - moderate to high flows, freshes and floods. Refers to flows generally

between the 50th

and 0 percentile (flows exceed this level less than 50 per cent of

the days).

Irrigators are permitted to extract a proportion of flows in each flow class. The

proportion is determined for each river and is usually based on historical extraction

levels. The volume of water allowed for extraction by irrigators determined by this

method is called the “Bulk Extraction Volume” (BEV). Water management

committees in unregulated rivers have been determining the daily share of water

between extractive users and the environment through establishment of BEVs for

different flow classes.

In the case of the Mooki River, A and B class flows do not exist due to the highly

ephemeral nature of the stream (Powell, 2001). Given the high demand for river

flows, Class C flows have been further divided into three sub-classes (C1, C2 and

C3). Three flow sharing options were proposed by the Namoi Unregulated River

Management Committee (NURMC) for sharing river flows within these classes (see

Powell, 2001) which are summarised in Table 1.

Figure3. Flow duration curve for the Mooki River

Source: DLWC (2001a)

0

100

200

300

400

500

600

700

800

900

1000

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

% of time flow is exceeded

Meg

ali

tres

per

da

y

Class AClass B

Class C

Basic low

flows


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The current rules represent the ‘base case’ against which the proposed flow sharing

options are compared. Under the base case, irrigators could access all river flows

above the CTP level (50 MLs/day). In practice irrigators only extract a proportion of

flows because of limits on pump and on-farm storage capacities. There is effectively

no BEV currently in place.

Table 1. Proposed flow sharing options in the Mooki

Flows class Flow level

MLs/day

Bulk Extraction Volume (MLs)

Option 2A Option 2B Option 3

CTP 100 Nil Nil Nil

C 1 100 - 1,000 800 600 600

C 2 1,000 – 3,000 1,500 1,500 900

C 3 > 3,000 2,100 2,100 2,100

The flow sharing Options (2A, 2B, and 3) provided in Table 1 impose varying levels

of restriction on the amount of water which can be extracted by irrigators within C1

and C2 classes. Access to C3 class flows is constant across all flow sharing options.

The BEV is distributed among individual irrigators in proportion to their licensed

entitlement but is restricted by physical ability to extract water. Individual flow

extraction will continue to depend on pump capacity and the size of on-farm storage.

Some additional rostering arrangements may be established by irrigators to ensure

equitable access to the resource given the differing location of individual farms along

the river. Currently, no rostering rules are practiced with upstream irrigators getting

first access to each flow. In the absence of any existing rostering arrangement, some

assumptions were made about how water was shared among individuals. These are

outlined in section 4.


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4. Methodology

4.1 Overview

Water policy reforms generally involve some form of modification of property rights

involving a re-allocation of resources. Resource re-allocation decisions are commonly

assessed in a benefit-cost framework. The economic efficiency of different allocation

policies can be assessed by comparing the social benefits and costs associated with

each policy. Underpinning the benefit-cost framework the ‘potential Pareto

improvement’ criterion states that resource re-allocation decisions are efficient if

those who are made better off can compensate those who are made worse off and still

be in a better situation. Of course, for the criterion to be satisfied it is not necessary

for compensation to be actually paid.

There are, however, a number of difficulties associated with adopting the standard

benefit cost analysis framework when considering issues that are likely to yield

environmental benefits, like increased water allocations to the environment. The

major difficulty relates to the appropriate valuation of environmental benefits

(particularly those in the non-use category) so that they can be incorporated into a

benefit-cost framework. To overcome some of the conceptual arguments regarding

valuation, a variation on the standard benefit cost framework can be adopted through

the use of an ‘opportunity cost’ or ‘threshold value’ approach. The threshold value

approach avoids the need to directly place monetary values on environmental goods.

The approach is based upon estimating the ‘opportunity costs’ which would be the

consequence of a particular resource decision. The opportunity costs are then directly

compared to the environmental outcomes (quantified in non monetary terms) which

are expected from the proposal.

The impacts on irrigated agriculture of water reforms can be analysed at two levels.

The first at a broader regional scale, and second at a more disaggregated catchment or

farm level. The latter approach is adopted in this study. There is a range of techniques

available for assessing farm level impacts of water policy reforms. These techniques

range from simple budgeting methods to optimisation methods. However, the


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selection of the method depends ultimately on the purpose of the analysis and the

nature of the problem being addressed.

The community based approach to the implementation of water reforms provides the

overall context for farm level analyses undertaken by NSW Agriculture. The purpose

of quantitative work within this context is to facilitate social choice. More

specifically, it is to provide information to help RMCs understand how the farm level

financial impacts of water sharing options are distributed so that appropriate trade-

offs can be made. The central role that RMCs have in the process and their broad

community representation (with varying levels of understanding of economics)

suggests that relatively straightforward methodological approaches should be used.

Methodological approaches should meet simplicity and transparency requirements

whilst also remaining sufficiently rigorous to capture real effects.

The types of problems proposed by RMCs commonly involve some form of

restriction to the access of water resources. The significance of these restrictions will

depend on climatic conditions that influence both the availability of river flow for

extraction and water demand. When climatic variability is likely to influence the

relative effects of water management options, then more stochastic methodologies are

required (eg. simulation).

NSW Agriculture has adopted various representative farm modelling methods to

analyse the on-farm impacts of re-allocation of water in NSW catchments. Cater et al.

(2000) adopted a simple whole farm budgeting method to estimate benefits or farm

returns for analysing the on-farm impacts of groundwater re-allocation rules in the

Namoi Valley. However, in estimating net farm returns this method elicited farmer

response to changed water availability directly from the farmers concerned. Many of

these responses were found to be irrational, designed more to influence policy

outcomes of the study, rather than accurately reflecting rational farmer behaviour. As

such they did not optimise resource allocation or minimise risk.

Modelling at a catchment and farm level is a widely used approach analysing

problems in agriculture and water resource management (Crean et al. 2001).

Catchment level modelling considers differentiated agriculture demand sites

(agricultural production zones or nodes) where each agricultural demand site can be


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modelled as a single farm. Farm scale modelling is done by selecting a representative

farm or farms depending on the variability of farm characteristics in the catchment.

NSW Agriculture has adopted farm scale modelling to evaluate the on-farm impacts

of environmental flow rules in regulated river catchments in NSW (Jayasuriya and

Crean 2000; Jayasuriya et al. 2001). However, these models cannot be applied

directly to unregulated rivers because they use total seasonal water availability instead

of weekly or daily water availability. In addition, the reliance on on-farm storages by

irrigators on unregulated rivers further complicates the modelling of water balance

and irrigator behaviour. Modelling of irrigation on unregulated rivers therefore needs

to consider the dynamic nature of water management within the economic model.

4.2. The Approach

This study adopted a combination of hydrology simulation and linear programming

(LP) to evaluate alternative flow sharing options in the Mooki sub-catchment. The

principle reason for adopting a simulation approach was to consider the variability of

impacts due to the nature of stream flows and climatic conditions. Historical rainfall

and stream flow data indicate that the Mooki sub-catchment is a highly variable

system (see Figure 2). This suggests that using a deterministic or average year

analysis would not adequately represent the farm level impacts of different flow

sharing options because changes in river flow availability directly impact on the area

of irrigated crops and hence farm returns.

It is assumed that farmers respond to reductions in water availability by changing

their crop mix to make the best use of available water and convert part of the area laid

out for irrigation to dryland production. The income from this area will be estimated

by the gross margin for an equivalent area of dryland crop. The model assumes that

daily BEV is perfectly shared by all irrigators. The approach is shown schematically

in Figure 4. The hydrology simulation and farm level optimisation models are

discussed in the following sections.


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Figure 4. Schematic of the modelling approach

4.2. Stream flow simulation model (Sacramento model)

The Sacramento model was used by DLWC to simulate stream flows. It is a

continuous rainfall-runoff model that generates stream flows from rainfall and

evaporation records. The principle of the model is that it uses soil moisture

accounting to simulate the water balance within the catchment.

4.3. Farm level optimisation model

A single representative farm was used in the analysis to represent all irrigators who

have access to surface water entitlements. This was done for two reasons. First,

because the homogeneous nature of farming systems in the sub-catchment. Cater et

al. (2000) undertook a GIS analysis of farm size and various attributes, such as

irrigation entitlement and on-farm storage size and found that these attributes to be

relatively homogeneous. Key features of the representative farm were based on

information derived from earlier irrigation surveys and advice from local irrigators

and advisory staff. The main characteristics of the representative farm are provided in

Table 2. Overhead costs for the representative farm were derived from a survey

conducted of 22 irrigators in the Mooki and Cox's Creek catchments for an MDBC

project by Bennett and Bray (2001).

Sacramento Hydrology

Model

– Generate stream

flow data for 88 years

Individual daily

flow shares

Flow rules

Farm level

Optimisation Model


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Some of the key economic data used in the economic model are discussed below:

Gross margins – gross margins of crops used in the model were obtained from the

Farm Enterprise Budgets for Northern NSW (NSW Agriculture 2001b). Gross

margins are estimated in year 2000 prices.

Overhead costs for the representative farm include costs such as wages for

permanent labour, administration costs, capital depreciation, etc.

Cost of water includes pumping costs and water charges.

Table 2. Key features of the representative farm.

Key physical characteristics

Total farm size (Ha) 442

Surface irrigated area (Ha) 162

Dry land area (Ha) 280

On-farm storage size (MLs) 729

Pump capacity MLs/day 125

Surface water entitlement (ML) 1,294

Irrigated crop mix (%)

Irrigated Wheat 25%

Irrigated Cotton 61%

Irrigated Maize 14%

Dry land crop mix (%)

Wheat 50%

Sorghum 50%

Farm overhead costs $75,500

The objective function of the farm level optimisation model is to maximise total

annual net farm income, Z, which is given by,

KAcZMax ii

n

i

.

Subject to:

LAa jiij

n

i

1


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Where:

Z is annual total net farm income,

c is gross margin per unit area of land for crop i,

A is area cultivated under crop i,

K is the total annual overhead cost for the farm,

a is the amount of resource j used per unit of crop i,

L is the maximum availability of resource j.

Net farm income is a measure of farm profit and measures the return to the operator

for their labour and management and return to all capital investment on the farm. The

model considered number of resource constraints. Constraints on production

resources were monthly water availability and annual water entitlement and land laid

out for irrigation and dryland area. The other constraints were specific crop

constraints, pump capacity, and on-farm storage capacity. A capital constraint is

embedded in the specific crop constraints. A cotton-wheat crop rotation was specified

given it is the most commonly practiced crop rotation in the area.

Monthly flow availability for extraction was estimated by aggregating the daily

extractable flow. Daily extractable flow was estimated by proportionally allocating

daily BEV based on annual entitlement (pro rata basis). The model assumes all river

water is routed through the on-farm storage before being applied to crops. This

irrigation flow path requires a series of equations to represent the water availability

constraint. These include an on-farm storage water balance equation and an on-farm

storage capacity constraint.

On-farm storage water balance

The on-farm storage water balance is governed by the on-farm storage continuity

equation. The linear equation representing the continuity equation is as follows:

eWSS tttt 11


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Where:

St is the amount of water stored in time t,

It is the amount of water pumped into storage in time t,

Wt-1 is the amount of water released from the storage for irrigation in time t-1,

et is the storage losses in time t (evaporation and seepage).

The storage capacity constraint is as follows

CS t

Where, C is the capacity of the on-farm storage.

Estimation of crop demand (gross irrigation demand) was an important part of

estimating the model coefficients needed to determine monthly storage release. The

following equation was used to estimate monthly irrigation requirements.

IR = ETc – ERF – RSM + PI

GIR = IR * IE

Where,

IR is the irrigation requirement at root zone,

ETc is the crop evapo-transpiration,

ERF is the effective rainfall,

RSM is the residual soil moisture at the time of planting,

PI is the pre-irrigation requirement.

GIR is the gross irrigation requirement (ex on-farm storage),

IE is the irrigation efficiency (conveyance and application).

Since data was not available, residual soil moisture and pre-irrigation requirements

were not considered in the estimation. Crop ET (ETc) values were estimated by NSW

Agriculture’s Water Use Efficiency Unit using the Penmann and Monteith method

were used in estimating crop water requirements (NSW Agriculture 2001c). Effective

rainfall for each crop was estimated using monthly rainfall multiplied by crop

effectiveness factors. Gross irrigation requirement was estimated at 70 per cent


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irrigation efficiency. Since the estimated GIR is a theoretical one, a factor (0.3 ) was

used to scale it down to represent more realistic irrigation requirements. The scaling

factor was determined by comparing the estimated GIR and irrigator reported GIR.

The irrigators generally under irrigate by 30 per cent compared to theoretical crop

water requirements (NSW Agriculture 2001b). This under irrigation is reflected in

the yields used in the analysis.

5. Results

5.1. Impact on average net farm income

The financial impacts of flow sharing options using the farm level modelling

approach are provided in Table 3. From the results it can be seen that the introduction

of Options 2A, 2B and 3 are expected to result in a decrease in net farm income of

5.0%, 5.1% and 5.9%, respectively. All three Options will have statistically

significant impact on irrigators. While there was no statistically significant difference

in impacts between Options 2A and 2B, the restriction in access to C2 class flows

under Option 3 reduce farm performance to a greater degree.

Table 3. Summary of impacts using the representative farm model with river flow data

Current Rule Rule 2A Rule 2B Rule 3

Whole Farm Gross Margin (WFMG)

- Average ($)

- Standard deviation ($)

278,284

17,737

268,209

28,935

267,928

29,020

266,396

30,196

Net Farm Income (NFI)

- Average ($)

- Standard deviation ($)

202,784

17,737

192,709

28,935

192,428

29,020

190,896

30,196

Impact on WFGM % -3.6 -3.7 -4.3

Impact on NFI % -5.0 -5.1 -5.9

T-test results( Comparing means against

the mean of current rule), at 5%

2.78 2.85 3.18


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5.2. Distribution of impacts across years

Figure 5 illustrates the impacts of flow sharing options across the 88-year simulation

period. This shows that impacts are higher in dry years. However, the incidence of

impacts is complicated by the operation of the on-farm storage (OFS), the timing of

river flows and the subsequent effect of the flow sharing rules on BEV's.

Consequently, impacts occur only in a proportion of dry years. The non-normal

distribution of impacts of flow sharing options is reflection of the non-normal river

flow pattern. Standard statistic theory suggests that, under a non-normal distribution,

a comparison of means may only lead to false conclusions. Analysis of the

distribution of impacts of different water sharing options was therefore undertaken

using cumulative probability distribution function (CDF) as suggested by Anderson et

al. (1977).

Figure 6 provides a summary of results in the form of cumulative distribution

functions (CDFs). This shows that for around 70 percent of the years, Option 2A, 2B

and 3 are expected to reduce farm incomes by 0-4%. For around 20 per cent of time

incomes may fall by 5-22%, and for around 10 per cent of years they are expected to

fall by between 23-51%.

Figure 5. Impact of flow sharing options, 1905-1992

0%

10%

20%

30%

40%

50%

60%

1905 1909 1913 1917 1921 1925 1929 1933 1937 1941 1945 1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989

Year

Dec

reas

e in

Net

Far

m I

nco

me

($)

Option 2A

Option 2B

Option 3


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Figure6. Cumulative probability distribution of impacts, 1905-1992

6. Discussion and Conclusions

The focus of this study was to develop a methodology capable of evaluating flow

rules for unregulated river catchments. The paper is based on a study undertaken on

behalf of the Namoi Unregulated River Management Committee to analyse the on-

farm impacts of three proposed flow options for the Mooki sub-catchment.

The major task of this study was to develop a method capable of accommodating the

ephemeral nature of river flows and the opportunistic water management practices

adopted by irrigators in unregulated rivers.

The study used a combination of hydrology simulation and LP optimisation modelling

techniques to develop a farm scale model to estimate the impacts of flow rules. The

Sacramento model was mainly used to simulate natural river flows for 88 years.

Linear programming was subsequently used to construct the economic model. The

LP model was able to incorporate the dynamic nature of irrigation flow management,

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55%

Decrease in Net Farm Income (%)

Pro

ba

bil

ity

Option 2A

Option 2B

Option 3

Analysis of variability

- 70% of years Options 2A/2B/3 reduce farm incomes by 0-4%

- 20% of years Options 2A/2B/3 reduce farm incomes by 5-22%

-10% of years Options 2A/2B /3 reduce farm income by 23 -51%


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where irrigators need to optimise flow extraction and on-farm storage to maximise

farm returns.

The model was successful in predicting impacts in different flow and climatic years

and was therefore seen as helpful in assessing the impacts of flow options developed

by the NURMC. The model can also be used to predict optimal on-farm storage

capacities for different annual volumetric flow extraction limits. This can be done by

varying the on-farm storage capacity for a given annual flow extraction limit

(entitlement). This output can then be incorporated in a cost benefit analysis to

identify optimal storage capacity.

As with many models this model also makes a number of simplifying assumptions.

The assumption of the flow path – from river to on-farm storage to crop– is not the

only way of irrigation practiced in unregulated rivers. For example, irrigators may

irrigate by directly pumping water from the river onto crops. When this occurs, this

model may underestimate net farm income, thereby over estimating the impacts of

changes in flow rules. The other assumption of this model is that it models irrigation

monthly irrigation rather than more frequently as would be practiced by irrigators.

This assumption also tends to under estimate the magnitude of impacts.


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References

Anderson, J. R., Dillon, J. L., and Hardaker, B.J., 1977, Agricultural Decision

Analysis, Iowa State University, Iowa.

Bennett, R. L and Bray, S., 2001, Summary of responses to Murray Darling Basin

Commission (MDBC) Project No. 19002, Irrigation Futures Framework Modelling,

Breeza Plains Farmer Survey, NSW Agriculture, Gunnedah.

Carter, A., Crean, J. and Young, R. 2000, Impacts of Ground Water Re-allocation

options in the Namoi Valley, NSW Agriculture, Orange.

Crean, J. and Young, R., 2001, “Modelling the farm level implications of water

reforms in NSW, Australia”, invited to ACIAR water policy workshop, Bangkok,

June.

Crean, J., Jayasuriya, R. and Jones, R., 2001, “Regional agricultural implications of

environmental flows in the Murrumbidgee Valley, Australia”, invited paper to

ACIAR water policy workshop, Bangkok, June.

DLWC, 2001a, Water Sharing Plans for the Unregulated Phillip, Mooki, Quirindi

and Warrah, Department of Land and Water Conservation, Tamworth.

DLWC, 2001b, Advice to Water Management Committees, No 6, Water extraction

volumes and daily flow shares in unregulated rivers, Department of Land and Water

Conservation, Sydney.

Jayasuriya, R., Crean, J., 2000, The on-farm impacts of ground water management

scenarios in the lower Murrambidgee, NSW Agriculture, Orange.

Jayasuriya, R., Crean, J., 2001, The on-farm impacts of environmental flow rules in

the Lachlan Valley, NSW Agriculture, Orange.


46th


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Jayasuriya, R., Crean, J. and Hanna, R., 2001, Economic assessment of water charges

in Lachlan Valley, NSW Agriculture, Orange.

NSW Agriculture, 2001a, The Draft Namoi Catchment Irrigation Profile, Water Use

Efficiency and Advisory Unit, NSW Agriculture, Dubbo

NSW Agriculture, 2001b, Farm Enterprise Budgets, NSW Agriculture, Tamworth.

NSW Agriculture and Department of land and Water Conservation, 2001c,

Volumetric Conversion of Irrigation Licences on Unregulated Rivers: Theoretical

Determination of Annual Volumetric Entitlements, NSW Agriculture, Dubbo.

Powell, S., 2001, The Draft Interim Flow Access Rules: Mooki sub-catchment. A

report to the Namoi Unregulated River Management Committee, DLWC, Tamworth.

Documents

Assessing Water Sharing Rules in Unregulated Rivers in NSW: Mooki Riverageconsearch.umn.edu/bitstream/173974/2/Aluwihar.pdf · · 2017-04-01Assessing Water Sharing Rules in Unregulated