Dryland salinity management in the

Liverpool Plains catchment

Dryland salinity management in the

Liverpool Plains catchment

ABARE report for the Land and Water

Resources Research and Development

Corporation

Romy Greiner and Nigel Hall

ABARE

R. Greiner and N. Hall, Dryland Salinity Management in the Liverpool Plains Catchment, ABARE report for theLand and Water Resources Research and Development Corporation, February.

Australian Bureau of Agricultural and Resource Economics GPO Box 1563 Canberra 2601

Telephone (06) 272 2000 Facsimile (06) 272 2001 Internet http://www.abare.gov.au

B A R E is a professionally independent government economic research agency.

B A R E project 1099

DRYLAND SALINITY

Foreword

Dryland salinity and rising water tables have become a significant land degra- dation problem in various parts of Australia. They impose a range of costs on farmers by reducing production and damaging farm infrastructure and may damage other community capital. The National Dryland Salinity Program co- ordinates research with a focus on five catchments across Australia. They are the Liverpool Plains catchment in New South Wales, the Loddon-Campaspe region of Victoria, the Upper South East in South Australia, the Kent River catchment in Western Australia and the Upper Burdekin catchment in Queens- land. In each of these catchments coordinated research is under way to explore particular aspects of the management of dryland salinity.

The Land and Water Resources Research and Development Corporation and the Liverpool Plains Land Management Committee asked ABARE to take part in interdisciplinary and interagency research into the management of dryland salinity in the Liverpool Plains catchment in collaboration with the Depart- ment of Land and Water Conservation of New South Wales. ABARE's role was to carry out an economic survey and develop a catchment model of the interaction between land use, farm incomes and salinisation.

The development of a catchment model to analyse the economic relationships between land use and dryland salinity in a catchment is described in this report. The model combines economic and hydrogeological aspects of agricultural land use. The model is used to investigate the relationship between changes in land use and water table management and implications for dryland salinity.

BRIAN S. FISHER Executive Director

February 1997

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Acknowledgments

The authors would like to thank the farmers in the Liverpool Plains catchment and the researchers and officers of Commonwealth and state agencies for their help and support in this research. In particular Sheila Donaldson and Pru Lee of the Liverpool Plains Land Management Committee and its chair Jim McDonald have made significant efforts to support the project.

The authors would particularly like to thank Robyn Johnston and Melissa Street of the Australian Geological Survey Organisation, for compiling biophysical information and designing maps; Karla Abbs from the New South Wales Department of Land and Water Conservation; Dr Brian Keating from CSIRO Division of Tropical Crops and Pastures, and other members of the APSRU modelling group.

The authors would also like to thank the ABARE internal referees, Milly Lubulwa, Anthea McClintock, Sally Thorpe and Leeann Weston for reviewing the manuscript. Anthea also assisted in subsequent redrafting of the report.

The Land and Water Resources Research and Development Corporation pro- vided the funding for this research as part of the National Dryland Salinity Management Program.

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Contents

Summary

I . Introduction

2. The Liverpool Plains Physical characteristics Nature of the problem Catchment management

3. Method and model description Analytical approach Model components

4. Model specijication Objective function Land use options and rainfall variability Interfarm connections Salinisation Model simulations

5. Results and discussion Scenarios A: Effects of salinity hazard Scenarios B: Effect of terminal land value Scenarios C: Effect of rainfall variability

6. Conclusions

References

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Figures A The Liverpool Plains catchment B Unique mapping areas of the Liverpool Plains catchment C Schematic model of water flows in the Liverpool Plains catchment D Catchment model data sets E Integrating spatial data sets into the catchment mode F Functional relationships in the catchment model G Groundwater level and salt affected area H Current land use I Salt affected area depending on land value J Development of land use on dryland plains and Liverpool Range K Salt affected area under variable rainfall conditions

Tables 1 Major characteristics of the model farms 2 Crop yields depending on soil type, crop rotational position and

seasonal rainfall 3 Recharge depending on soil type, crop rotational position and

seasonal rainfall 4 Land use related recharge in Liverpool Range and hills: per season 5 Hydrogeological connections within the catchment 6 Average recharge and runoff from current land use

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Summary

The Liverpool Plains catchment is a highly productive agricultural area in northern New South Wales covering 1.2 million hectares. The area can be characterised as a landscape of black soil plains interspersed with hills and surrounded by mountain ranges.

Dryland salinisation has been identified as a threat to farming on the black soil plains. Salinisation is the result of a change in the catchment's water balance leading to a general trend of rising groundwater levels. This results in historic salt stores being mobilised and redistributed into the soil root zone and sur- face water. The process has been attributed to changes in land management over the past two centuries. Original perennial grasses, shrubs and trees have been largely cleared and replaced by improved pastures and crops. These land use systems have higher infiltration rates of rainfall than the original vegeta- tion.

A range of practices and policies have been proposed to manage the water bal- ance in the Liverpool Plains. Changes to present land use systems are perceived to be the key variables in water management. Proposed practices include oppor- tunity cropping, planting of perennial pasture species, tree planting and planting of saltbush on saline areas. These practices are being promoted by government agencies and Landcare groups and by the Liverpool Plains Land Management Committee.

The relationship between groundwater accessions and land management has been investigated using a catchment model. Essentially, this model seeks to investigate the spatial effects and time lags associated with water balance man- agement in a catchment. Use of a model allows researchers to abstract from a complex reality and quantify the relationships within the catchment system. It is then possible to test hypotheses about the applicability of selected land man- agement practices and policy instruments. However, the model is based on current knowledge and so the numerical results presented in this report should be regarded as a contribution to the development of strategies rather than providing strategies in themselves.

The scientific understanding of the hydrogeology and agronomy of the catch- ment that forms the basis of the model is continually being developed and the analysis here is to be regarded as preliminary. If the results presented in this report are to be used in a catchment planning sense, they need to be interpreted

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spatially using lower scale instruments such as Geographic Information Systems (GIs). As the science develops, the economic modelling can also be developed to improve understanding and contribute to policy development.

The model developed for this report was based on an existing single farm model developed to investigate salinisation on dryland farms in the Liverpool Plains catchment by Greiner (1994). This model was extended to represent the vari- ation across the catchment by differentiating four areas within the Liverpool Plains catchment that are distinct in their land use and hydrogeological char- acteristics. Each area is represented by a typical farm that has land use options associated with yields, recharge and runoff, and flows of ground and surface water. The model is referred to as SMAC (Spatial optimisation Model for Analysing Catchment management).

Two of the areas defined represent the upland areas, the Liverpool Range and hills, that are the main source of recharge of the regional groundwater system. The Liverpool Range is the largest contributor because of the high rainfall it receives. The hills encompass the other outcrops to the north of the Liverpool Range and the Hunter Mooki Thrust. Water from these areas flows to the black soil plains in the lower catchment. These flows occur through the movements of shallow groundwater and surface water. A significant percentage of the runoff water turns into recharge on the alluvial foot slopes of the ranges.

The irrigated plains and the dryland plains represent those farms that can be irrigated by pumping groundwater and those where this is not an option. While the irrigated and the dryland plains also contribute to recharge, landholders in these areas face the combined effect of their own actions and the land use on the hills and Liverpool Range.

The time lags and spatial effects associated with water flows and land use changes are captured by dynamic formulations of the catchment model which is run over a 30 year period. Each year has two growing seasons. Rainfall vari- ability is addressed by allowing for five different season types depending on rainfall.

Groundwater accessions from the hills and Liverpool Range contribute to the rising groundwater levels under the black soil plains that cause salinisation. There is no motive for farmers in the higher parts of the catchment to reduce groundwater accessions because they do not bear the costs associated with salinisation. In economic terms, this is called an externality problem. Unless there is some mechanism to encourage the upland farmers to take a catchment perspective, the whole burden of adjustment to rising groundwater will be borne by the farms on the black soil plains.

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This report shows the results of simulations where the model is applied from a catchment perspective by treating the whole catchment as a single manage- ment unit. An initial simulation of the model indicates that continuing current land management practices and levels of accessions to the groundwater would result in a large part of the dryland plains being salinised within 30 years. In the model, the most cost effective ways of reducing the expansion of, orelim- inating, salinity would be management changes on the Liverpool Range and the dryland plains. Cessation of cropping on the Liverpool Range, and planting increasing areas of lucerne and saltbush, with some trees, on the dryland plains would be the main changes. Pasture on the Liverpool Range would not be planted to trees to reduce groundwater accessions. At around 6 hectares of trees on the Liverpool Range for each hectare of salinity reduction the oppor- tunity cost of reducing grazing on the Range would be higher than the cost of managing the groundwater accessions on the dryland plains themselves.

The model results suggest that effective catchment management need not involve all landholders, even if it is seen as being worthwhile to limit the devel- opment of salinity. Even eliminating salinity would involve changes in land management in the Liverpool Range and the dryland plains, only. And the changes in the Liverpool Range would be limited to the cessation of cropping. The major effort in catchment management would, therefore, be directed at activities on the dryland plains. In the model the dryland plains are treated as a single unit. In practice, it is likely that there will be considerable inter- dependence between the actions of individual farmers on the dryland plains, so some form of coordinated approach is likely to be most cost effective in reducing or mitigating the effects of rising water tables.

The issue of whether or not salinisation will be halted before all the area at risk is salinised is explored. From a total catchment perspective, the costs of altering land management practices to control salinity must be less than the benefits of maintaining soil productivity. The analysis suggests that the level of benefits per hectare needed to stop salinisation is greater than the current or prospective farm land value per hectare under the price, agronomic and hydrogeological assumptions used. This indicates that a rational manager of the whole catchment would allow salinisation to continue on the dryland plains if only the returns to agriculture alone were considered. Costs of salinisation to other sectors or regions could affect this decision if they were large enough.

Rainfall variability is identified as another important factor affecting salinity. Series of wet seasons accelerate water table rise and salinisation. Below average rainfall conditions reduce salinity but cause low yields and loss of agricultural income. Depending on the run of seasons, the level of the water table and the area salinised is generally greater, but sometimes less, than that expected on

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the basis of average rainfall. That is, the distribution of outcomes from ran- domisation of seasons is skewed toward greater areas becoming salinised under varying rainfall compared to the areas likely to become salinised under average rainfall.

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I . Introduction

Dryland salinity and rising water tables have become a significant land degra- dation problem in various parts of Australia. They impose a range of costs on farmers by reducing production and damaging farm infrastructure and may also affect other people by damaging roads and other community capital. The biophysical processes involved are complex and the economic implications are serious. It has been estimated that 175 000 hectares in New South Wales are currently affected by dryland salinity (J. Bradd, Department of Land and Water Conservation, personal communication, December 1996). Up to 5 mil- lion hectares may eventually become saline (Bradd and Gates 1995).

The Land and Water Resources Research and Development Corporation and the Liverpool Plains Land Management Committee requested ABARE and the Department of Conservation and Land Management in New South Wales (now the Department of Land and Water Conservation) to work together on the issue of dryland salinity management, using the Liverpool Plains as a focus catch- ment. In the Liverpool Plains catchment there are some 1200 landholders most of whom contribute to andlor are confronted with soil salinisation (McDonald 1995).

Several management solutions have been suggested to address the causes of dryland salinisation in the Liverpool Plains. It has been recommended that farmers increase cropping frequency, adopt no till practices, increase the area of deep rooted perennials such as pastures, lucerne and trees, and adopt oppor- tunity cropping instead of a fallow when rainfall has been high to reduce acces- sions to the groundwater in wet years (Liverpool Plains Land Management Committee 1995). However, these recommendations have not been widely adopted by landholders.

The major impediments to land use change, as identified by a landholder work- shop in the Liverpool Plains in March 1996, are financial constraints, lack of management skills and experience (Liverpool Plains Land Management Com- mittee 1997). The financial constraint occurs because most of the practices proposed require investment and result in a reduction of farm income, at least in the short term.

Farmers who export their recharge to other areas face no economic incentives to change current land use practices. Farmers in discharge areas may also be reluctant to change, despite reductions in land productivity from salinisation.

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It is difficult for individual producers to address these issues in the existing policy and market framework because of the indirect nature of the processes, their spatial characteristics and the long time lags involved.

ABARE was engaged to develop a model to examine the likely changes in farm management practices arising from the effect of salinity on agricultural productivity and land values over a thirty year period. This report describes the dryland salinity situation on the Liverpool Plains and presents a catchment model that takes account of the interrelations of land use, farm incomes and salinisation in that catchment. The objectives are to examine, on a catchment scale, the extent of salinisation and the management responses made in dif- ferent parts of the catchment. The issues are considered under different assump- tions regarding the risk of salinisation and the possible declines in land values from productivity losses associated with salinisation. More generally, the aim of the project is to provide an analytical framework to contribute to the devel- opment of strategies to manage dryland salinisation. The model developed draws extensively on data generated by research into soils, hydrogeology and agronomy, some of which are preliminary.

2. The Liverpool Plains

Physical characteristics The Liverpool Plains catchment covers 1.2 million hectares in the north western slopes of New South Wales. The catchment is divided into two subcatchments: Mooki River to the east and Cox's Creek to the west. The subcatchments drain into the Namoi River (figure A).

The landscape is characterised by extensive alluvial black soils partly sur- rounded by ranges and dotted with hills. The Liverpool Plains are an extremely

The Liverpool ~iains catchment

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productive cropping and stock rearing area with an estimated annual value of production exceeding $150 million (Greiner 1994).

Location of the Liverpool Plains catchment

The Liverpool Range is a high rainfall area, only partly cleared, on the south west side of the catchment. The catchment is bounded on the east by the range formed by the Hunter Mooki Thrust, west of Tamworth. The two mountain systems partially enclose the catchment. Within the semicircle of the ranges are hills standing out in the flat plains. They were the first cropped areas in the catchment, being largely cleared during the 19th century. They are a major source of accessions to groundwater because, although their rainfall is less than that on the Liverpool Range, they are extensively cropped and have rela- tively porous soils.

The black soil plains are highly fertile cracking clays. They were used for grazing until the 1950s when, with the advent of more powerful machinery, it became possible to crop them. Before this time they had retained their orig- inal perennial grass cover. The plBins are the area in which salinity damage is -- beginning to show and where it is expected to increase in the future. The land use practices of landholders on the.plains also contribute significantly to regional groundwater accessions. Some of the plains are underlain by open gravel and sand formations, allowing irrigation from bores.

Nature of the problem At the time of European settlement the hills and ranges were heavily timbered and the plains were open grassland with some trees. The whole catchment is thought to have been hydrogeologically stable although sequences of wet or dry years may have affected the level of groundwater from year to year. Exten- sive clearing of native vegetation for farming has taken place since then to provide land for grazing and cropping (Sim and Urvin 1984).

In the past two decades there has been evidence of rising groundwater levels under a large percentage of the plains (Broughton 1994). For example, an increasing area of crop land now shows signs of waterlogging and dryland salinity and Lake Goran, formerly an ephemeral lake, has been full in most years (Dryland Salinity Management Working Group 1993).

The dryland salinisation examined in this study occurs where there is a rise of shallow groundwater levels in the low lying parts of a catchment. In this case, extensive areas of the most productive land within a catchment are at risk of becoming salt affected (Anderson, Britten and Francis 1992). Dryland salinity

8

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outbreaks may also occur through scalding, when the erosion of topsoil reveals saline subsoil or because of local groundwater movement at break of slope on hillsides.

The process of dryland salinisation is caused by a shift of the catchment's water balance toward increased accessions. Given the topography and the soils in a catchment, the magnitude of accessions to the groundwater system is deter- mined by land use and rainfall. Increased recharge to the groundwater system can cause a rise of groundwater levels in areas that display a hydrogeological predisposition. This process can lead to the mobilisation of salts stored in deep rocks and soil. Consequent soil salinisation causes yield depression, land man- agement problems, decline of natural vegetation, and damage to infrastructure such as buildings, roads, pipes and sports grounds (Oliver, Wilson, Gomboso and Muller 1996).

Catchment management In this report, the potential gains from changes in the land management prac- tices of farmers located in different parts of the Liverpool Plains catchment are examined. The changes in management practices are aimed at improving man- agement of the groundwater balance. To achieve this, the strategies need to be catchment specific, taking account of the catchment's hydrogeological prop- erties. Present farming structures and land uses must be considered while including potential alternatives and structural adjustment processes. An under- standing of the economic impact of both the problem and the solutions poten- tially available is fundamental to developing efficient catchment management strategies and controlling soil salinisation (Robertson 1995).

Areas within the catchment contribute different amounts of recharge water to the groundwater system and are affected by the resulting water table rise to varying degrees. Hence, depending on their location, landholders can generate and face different levels of costs from rising water tables and associated soil salinity (Greiner and Hall 1995).

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3. Method and model description

Development of an analytical framework for water table management in a catchment context poses a range of challenges. Greiner and Parton (1995) emphasise in particular the following aspects.

First, salinisation is characterised by time lags and spatial effects. The formu- lation of the physical mechanisms that lead to externalities associated with dryland salinisation, within the catchment, must be an integral part of the mod- - elling framework. !

I

Second, land use activities are thd major decision variables that influence the hydrological balance because different land uses have different levels of recharge. These differences are reflected in the hydrological balances under different land uses and the resulting levels of salinity may affect the profitability of particular land uses. Thus, there is a feedback relationship inherent in the land use salinisation system.

Third, it is essential to account for the fact that land use decisions are taken at the farm level. While a gross margin analysis may provide useful scoping infor- mation, only a whole farm budget can determine the absolute and compara- tive financial feasibility of land management options by taking account of capital and cash flow constraints.

Fourth, accessions to the groundwater system are strongly influenced by sporadic recharge events that occur after prolonged and heavy rain. Rainfall variability is a major driver of the salinity system. Hence there is an element of risk associated with alternative management plans in that one may need to consider costs and benefits in the context of the likelihood of extreme rainfall events.

Analytical approach The approach of regional, or catchment level, optimisation applies spatial equilibrium modelling theory (Baumol 1977; Lambert 1985). Land manage- ment is linked with the catchment scale hydrogeological processes that drive dryland salinisation. As different land use options will use available water to different extents, their impact on accessions to the groundwater system and on soil salinisation will differ. In turn, emerging salinity affects soil productivity and the land use options that are potentially available to farmers.

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To investigate the relationship between' land use, water table levels and salinity a catchment model was developed. The model is called SMAC (Spatial opti- misation Model for Analysing Catchment management). The model integrates the biophysical and economic aspects of land use that are relevant to addressing land and water management at the catchment scale. The model encompasses the spatial variation across the catchment by differentiating four areas within the Liverpool Plains catchment that are distinct in their land use and hydro- geological characteristics. In the model each area is characterised by a typical farm that has land use options associated with yields, recharge and runoff, and flows of ground and surface water. The farm units within the catchment are linked spatially and temporally through hydrogeological and market mecha- nisms, so that the model objective can be set to internalise the costs associated with water table management within the catchment.

Model components Johnston, Abbs, Banks, Donaldson and Greiner (1995) define and describe eleven areas for the Liverpool Plains catchment which are similar in soil, topog- raphy, climate and hydrogeological processes. These areas are based on infor- mation from biophysical datasets, including geological and topographic data, hydrogeological mapping, land slope classification, climate data and soil land- scape mapping. Figure B shows a map of the Liverpool Plains catchment featuring these areas, which are referred to as unique mapping areas.

Unique mapping areas of the Liverpool Plains catchment This study uses a simplified version of four homogeneous areas and relies on preliminary estimates for the ground and surface water connections because of a lack of information regarding the hydrogeological linkages between the eleven unique mapping areas. The four areas used to represent the variety of landscapes in the Liverpool Plains catchment are referred to as the dryland plains, irrigated plains, Liverpool Range and hills.

The Liverpool Range and hills are recharge areas. The Liverpool Range con- sists of the basalt hills, basalt slopes and adjoining colluvial fans and covers 20 per cent of the catchment. It receives much higher rainfall than the remainder of the catchment. The hills are also a recharge area that makes up 40 per cent of the catchment.

The dryland plains and the irrigated plains represent the alluvial black soil plains that make up the remaining 40 per cent of the area under investigation. Areas with dryland farming only are distinguished from areas where ground- water pumping for irrigation takes place. Irrigation is restricted to areas where

I 1

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e Unique mapping areas of the Liverpool Plains catchment

o Liverpool Range Slopes o Liverpool Range Hills and Plateux o Garawilio Volconlcs o Pilliga Sandstone o TriassicIPermian Sediments 0 Werrie Bosalts 0 Hunter Mooki Slopes

Hunter Mooki Hills Black Earth Plains Meander Plains Outwash Plains Alluvial Sands

the main (Gunnedah) aquifer yields sufficient quantities of low salinity water. The irrigated plains area occupies a quarter of the total plains area.

The four areas described are connected in the spatial model through surface and groundwater flow. It is assumed that most recharge in the Liverpool Range and hills flows as shallow subsurface groundwater into the groundwater pool under the dryland and irrigated plains. This groundwater pool receives addi- tional water from surface runoff from the Liverpool Range and hills. The water from incompetent creeks, that is, creeks that disappear into the soil on the allu- vial fans at the edge of the black soil plains, directly recharges the ground- water aquifers. Figure C illustrates these flows.

Schematic model of water flows in the Liverpool Plains catchment

Farm characteristics The catchment model consists of four farm submodels which describe the prevailing farm organisation and land use systems, based on data collected in

12

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49 Schematic model of water flowsk the Liverpool Plains catchment

S-N cross section

Liverpooi Range Dryland Plains Hills Irrigated Plains

7

Q, = Narrabri Formation Q, = Gunnedah Formation P, = Bedrock

r= Recharge & runoff @ lnfiltrotion of runoff @Lateral shoiiow groundwater flow

r = lrrigotion @Pressure transmission @ Dischorge of groundwoter out of the catchment

ABARE's farm survey. The survey farms were grouped according to their loca- tion in the catchment with respect to the four homogeneous land areas identified. The survey averages were discussed with the Liverpool Plains Land Management Committee and used to develop the typical farm profiles for each area.

Table 1 shows the means and relative standard errors of selected major char- acteristics of four model farms. Relative standard error is a measure of the vari- ability of sample survey data (ABARE 1996). Cropping area is the area suitable for cropping. This was not available from the survey and so is derived from the work on unique mapping (Johnston et al. 1995).

Farm submodels The catchment model aggregates the behaviour of farm units to the catchment level. The individual farm submodels are based on the Model of the Farm Eco- nomics of Dryland Salinity (MoFEDS). MoFEDS was developed to investigate the implications of soil salinisation on dryland farms, in the salinisation zone, in the Liverpool Plains catchment. The objective of MoFEDS was to identify

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1 Major characteristics of the model farms Average perfarm

Dryland Irrigated Liverpool Unit plains plains Range

mean rse mean rse mean rse

Area of holding ha 1000 (17) 960 ( 1 2 ) 1600 (271 Cropping area ha 800 * 800 * 320 * Irrigated area ha 0 (na) 270 (37) 0 (na) Number of cattle no. 130 (23) 100 (25) 340 (201 Debt $'OOO 100 (39) 285 (28) 280 (54) Land value $m 1.0 (18) 2.0 (16) 1.8 (29)

* No relalive standard error (ne) can be calculated as this is not a survey estimate.

Hills

mean rse

an optimal path of farm land use while taking account of emerging salinisation to investigate tradeoffs between the income of a model farm and the salinisa- ---+

tion occurring on the property in a multipericd context (Greiner 1994). MoFEDS is a multidisciplinary model and integrates biophysical modules into the core structure of the farm management .model through a feedback structure.

For the catchment model, a soil hydrology and a crop growth simulation model is employed to provide coefficients on water use and yields (Keating, McCown and Cresswell 1995). Within the optimisation framework, a three dimensional water balance module simulates the implications of land use, rainfall and hydro- geological conditions on the movement of the water table. The farm water balance is translated into water table movement. The calculated water table then determines the area of salt affected land on the farm which in turn influ- - ences future soil productivity and land management decisions.

The spatial catchment model (SMAC) interconnects the activities of the four farms. Whereas the farm level model (MoFEDS) assumed hydrogeological conditions to be external variables to the single farm model, the catchment model includes spatial data sets that endogenously define these conditions. Figure D outlines the spatial and temporal data sets that define the model.

Catchment model data sets The spatial data are linked to a grid structure that is superimposed on the catch- ment map. It operates as a data base similar to a Geographic Information System (GIs) (figure E). The most relevant information here is the distinction between homogeneous areas within the catchment. As shown above, farms within one area have similar contribution, relevance and disposition to the development of soil salinity. They are also similar in agricultural productivity and their range

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@ Catchment model data sets

S~atial data sets Tem~oral data sets

unique mapping areas and - p[icelcost developments ground water flows - dlscount rate soil landscapes . seasonol rainfail conditions farm structures recharge to groundwater . land use practices and alternatives yields, land productivity - rechar e to groundwater .policies - saiinisaaon process -adoption and implementation - policies -structural adjustment

Catchment o timisation model ( Linear programming m d e i wi. sirnulolion subroutines 1 Results . spatial and temporal pattern of optimal land use over the catchment estimate of salt-affected area financial viability of farms . quantification of external effects associated with dryland salinisatlon distribution of costs associated with watertable rnanaaement -~ ~~ ~

scenario and factor sensitivity analyses -

suggestions towards the adjustment of current land use structures and practices . policy rec~mrnendatlon~

@ . Integrating spatial data sets Into the catchment model

3. UMA information

2. ABARE survey farms a

1. Catchment grid structure

a AC~UCI! lo cob on^ not shown 'ihiy

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Functional relationships -in the catchment model

Farms in Plalns UMAs Farms in uphill UMAs Dryiond and irrigated plains Liverpool Range and Hills

- Traditional resourcer lond. labour. capital

Finonciol management

land productivity Form income

prOductlon -.---.._..._ Exogenous factors :

L~inancial management 1 - o i n f a v o r i o l i - - Farm income

- farm Internal linkoaes I Prices ond -

..... hydrological processes

...... system vofiobility -- .--- Policies and programs - market mechanisms . - - policy implications

of land use options. The model includes best available information on the quan- titative components of regional groundwater flows between these spatial units over time.

Integrating spatial data sets into the catchment mode[ All model data sets have a temporal dimension to account for the long term character of the catchment management issue (figure D). Temporal data sets include policies and adoption behaviour of the farming community. A schematic summary of the elements and mechanisms that drive the catchment model is shown in figure F.

Functional relationships in the catchment model The catchment equilibrium model maximises the total net present value of agricultural land use in the catchment over 30 years plus terminal land values. Allowance is made for degradation of the catchment's natural resource base through soil salinisation. Salinisation reduces the regional income through the feedback relationships adopted in the model (Greiner 1994). The rationale for applying spatial equilibrium theory in a catchment context is documented in Salerian (1991).

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4. Model specijication

Objective function The objective in SMAC is to maximise the present value of net agricultural returns in the catchment, over a set period, plus the value of the farm in the final year. For the simulations reported here, the model is run for a 30 year period. To represent the catchment perspective without taking account of the actual financial situation of farms in the catchment, off-farm income, opening debt and opening off-farm assets were set to zero. The terminal value of the farm is the value of both saline and uon-saline land in year 30 less any closing debt. The terminal land value used in the model is an estimate of the market value of land unsalinised in year 30.

It is assumed that the past pattern of prices and productivity changes will con- tinue. That is, farm product prices will increase more slowly than farm input prices and most of the difference will be made up by increasing productivity. The general effect is represented in the model, in a simplified form, by setting output prices to decline by 0.5 per cent each year while input prices and phys- ical productivity remain the same.

The discount rate used in this analysis to represent the catchment landholders' cost of funds is estimated as the real rate of borrowing as measured in the infla- tion adjusted interest rate for 10 year Commonwealth Treasury bonds. The value of this discount rate is 7 per cent for 1994-95. No risk margin is added even though production and market risks exist.

It is also assumed that because of high groundwater levels, parts of the black soil plains are at the verge of experiencing soil salinisation.

Land use options and rainfall variability Land use variables are the key decision variables in the catchment model. Land uses are characterised for each area within the catchment in terms of their economic and environmental implications. The selection of land use options applicable in the model is based on discussions with farmers and agronomists in the Liverpool Plains and covers current land use practices and some poten- tial alternatives. This includes 'best management practices' as identified by Hooper (1995).

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On cropping land, the model accounts for both winter and summer crops. Two decision periods apply, which are the beginning of the winter and the summer seasons in each year of the optimisation period. The range of winter cereal activities is represented by wheat. Sorghum production is used as a proxy to represent summer cropping activities. Yield and recharge associated with each crop are functions of the soil type in the particular catchment area, the posi- tion of the crop in a rotation, and the seasonal rainfall.

Rainfall variability is the major external variable to the management of a catch- ment. In particular, rainfall directly influences crop yields and recharge to the groundwater system. Rainfall in the Liverpool Plains is highly variable. Over the past 100 years in this catchment, the coefficient of variation of rainfall was - 27 per cent. That is, rainfall was more than 27 per cent higher or lower than average rainfall, which is 606 mm, approximately one year in three.

The MoFEDS model distinguished three season types for both summer and winter seasons (Greiner 1994). In the spatial catchment model (SMAC), this approach is refined to account for five rainfall conditions in each of the two seasons. These conditions are very dry, dry, average, wet, very wet and repre- sent the 10, 30,70,90 and 100 percentiles of total in season rainfall, respec- tively. Allocating frequencies to these season types allows random selection of weather conditions for both seasons in each year, giving 25 rainfall possi- bilities for each year.

The effect of land use on the hydrological balance of the study area and the feedback to future land productivity is quantifiable. However, no field data were available to support a quantification of such functional relationships. It was decided to use a modelling tool to generate parameters to characterise the behaviour of the system. From the range of cropsoil simulation models avail- able for assessing the productivity of land use options and their environmental implications, APSIM (Agricultural Production Systems Simulator) was chosen as the most appropriate for the purpose of this exercise.

APSIM is a software shell that combines crop growth, soil and water balance models (Keating, McCown and Cresswell 1995). It has been validated for deep cracking black soils, which are the prevalent soils in the Liverpool Plains. Fur- ther advantages include its capacity to record relevant output in time intervals that match the catchment model's decision periods and its versatility in repre- senting different and complex agricultural management systems. Special APSIM runs were made using climatic, topographic and soil information for the Liverpool Plains. These runs modelled yield and recharge options using daily rainfall data for the period 1879 to 1993.

DRYLAND SALINITY

Crop yzelds depending on soil type, crop rotational position and seasonal 2 raifiJ,i

Alluvial black soil Red brown earth

Dry Average Wet Dry Average Wet

t/ha t/ha tlha t/ha Uha Wheat alf 3.0 4.1 5.4 0.5 1.5 2.2 Wheat asf 1.6 3.4 4.5 0.4 1.4 2.2 Sorghum alf 3.2 4.1 5.4 0.7 2.0 2.5 Sorghum asf 2.7 3.8 5.0 0.5 1.7 2.3 alf = after long fallow (previous fallow at least two seasons), asf = aftcr sholi fallow (fallow one season only).

Table 2 presents selected relationships between crop yield and rainfall on the black soils and red brown earths located on the hills and parts of the Liverpool Range. Table 3 presents estimated recharge to the groundwater under crops and fallows by season, soil type and level of rainfall. In some cases, no simu- lations were available for particular combinations of physical conditions and the estimates were generated by interpolation.

Long fallowing is a management strategy that seeks:to increase soil moisture to maximise crop yields. This strategy is successful on alluvial black soils, which have a high soil water storage capacity, and proves a particular advan- tage in seasons with below average rainfall.

The implications of rainfall variability can be explained using a traditional long fallow based wheat sorghum rotation on black soil. After the wheat harvest, the land is fallowed for the next summer and winter, then planted to a sorghum crop and fallowed for the subsequent winter and summer, before being again sown to wheat. The duration of this sequence is three years with two harvests. From table 3 it can be seen that this rotation produces an average annual recharge of 33 mm under average rainfall conditions. However, annual recharge may be as low as zero if all these seasons are very dry and as high as 185 mm if the seasons are very wet.

Perennial vegetation cover reduces recharge in comparison to all cropping regimes. In areas whcre deep rooted perennials have access to groundwater, improved growth may lead to a negative point water balance that can lower water tables. This study assumes that perennial grasses, lucerne, saltbush pastures and trees can extract water out of the system in the dryland plains and irrigated plains during dry and average rainfall seasons.

The Liverpool Range receives significantly more rainfall than the rest of the catchment. Estimates suggest that average annual rainfall may be twice the

19

DRYLAND SALINITY

3 Recharge depending on soil type, crop rotationalposition and seasonal rainfall: mm oer growing season

Alluvial black soil Red brown earth

Very dry Average Very wet Very dry Average Very wet

mm mm mm mm mm mm

Crops Wheat alf 1 15 45 15 50 100 Wheat asf 0 15 45 15 50 100 Wheat dc 0 1 40 0 15 I00 Sorghum alf 3 15 50 20 40 80 Sorghum asf 0 10 35 20 40 80 Sorghum dc 0 0 5 5 20 60

Fallows Winter asf 0 30 90 15 75 175 Winter asc 0 4 70 10 50 150 Summer awf 0 30 200 30 90 230 Summer awc 0 5 140 5 80 230 Craps: alf = after long fallow; asf = after shalt fallow; de = double crop planted into stubble of previous crop. Fallows: asf = afler summer fallow: asc = after summer crop; awc = afler winter crop; awf = after winter fallow.

rain that Gunnedah receives (R. Banks, Department of Land and Water Con- servation, Gunnedah, personal communication, March 1996). This translates into significantly higher runoff and recharge from land uses on the Liverpool Range in comparison to the hills. Table 4 shows the recharge estimates for the Liverpool Range and Hills for major land uses and seasonal rainfall conditions.

Inte$arm connections Figure C schematically outlines the hydrogeological connections between the major land units specified for the catchment. The water balance of the dryland plains and irrigated plains is not only a function of rainfall and vegetation water use, resulting in total recharge for the respective area. In addition, it is deter- mined by the amount of water received from the hills and the Liverpool Range areas.

In discussion with Ray Evans from the Australian Geological Survey Organ- isation and George Gates from the Department of Land and Water Conserva- tion, a hypothesis was established about the hydrogeological connections within the catchment. The hypothesis is outlined in table 5.

A significant percentage of the recharge on the Liverpool Range and hills con- 1 tributes to the groundwater pool under the dryland plains and irrigated plains through shallow lateral groundwater flow. This hydrogeological connection is

20 / \

DRYLAND SALINITY

4 Land use related recharge in Liverpool Range and hills: per season

Winter Trccs Pasture Crop Fallow

Summer Trees Pasture Crop Fallow

Liveroo01 Ranee Hills

Very dry Average Very wet Very dry Average Very wet

mm mm mm

5 Hydrogeological connections within the catchment

Proportion of area recharge that flows

Type of water connection and source to the dryland plains

Lateral shallow groundwater flow Liverpool Range 60 Hills 33

Runoff infiltration Liverpool Range

Very dry season 80 Average season 50 Very wet season 30

Hills Very dry season 40 Average season 27 Very wet season 13

stronger between the Liverpool Range and the plains than it is for the hills. Similarly runoff infiltration is greater from the Liverpool Range due to the higher rainfall. So called incompetent creeks coming from the Liverpool Range will flood only in wet seasons, canying most runoff water across the dryland and irrigated plains. In average and dry years the creeks do not flow. Instead, the runoff infiltrates in the vicinity of the alluvial fans and adds to the ground- water pool under the dryland and irrigated plains.

2 1

- DRYLAND SALINITY

There is subsurface drainage of water out of the catchment, estimated at approx- imately 310 000 megalitres a year. For parts of the plains, irrigation from groundwater is an important factor in the water balance. Groundwater is pumped from the Gunnedah aquifer (figure C). This reduces the water pressure in this aquifer which controls the depth of the upper aquifer in the Narrabri forma- tion. In the dryland plains, this option does not exist and therefore the distinction between dryland plains and irrigated plains is necessary.

Salinisation The treatment of salinisation in the model is illustrated in figure G. Salinisa- tion is a function of the depth of groundwater table below the soil surface. Two critical water levels define the emergence of slight and severe soil salinity. Slight salinisation results in a reduction of crop yields and a reduction in the crop options. Slight salinisation is reversible by lowering the water table. Severe _--- salinisation cannot be reversed even if water tables decline below the critical level. The only land use options available are leaving the land bare or saltland agronomy options that involve thq establishment of salt tolerant perennial

@ Groundwater level and salt affected area

1

. i

t

O Slightly salt affected land (reversible) BiSJ Severly salt affected land (irreversible)

Critical water level above which slight salinisation occurs *. Critical water level above which severs salinisation occurs

DRYLAND SALINITY

plants. Suitable plants include saltbush and salt tolerant trees. The productivity of saltland agronomy options is low.

How depth of groundwater affects salinity

See figure A.

Model simulations Three sets of simulations are presented, each of which investigates one aspect of catchment management over a planning period of thirty years. The model adopts a catchment perspective. That is, the entire catchment is simulated as if belonging to one owner.

The variables investigated are:

(A) The assumption made about the risk of dryland salinity emerging on the black soil plains,

(B) The effects of different levels of penalty for salinisation, in the final year, on the sustainability of land use.

(C) The effects of rainfall variability.

DRYLAND SALINITY

5. Results and discussion

Scenarios A: Effects of salinity hazard Dryland salinity has only recently been found to be a potentially serious problem in the Liverpool Plains. It is likely that this change in understanding would lead to changes in the management of land in the catchment. This is explored in the first two investigations which compare optimal land use without a salinity hazard (the way the situation was thought to be in the past) and optimal land use with a salinity hazard (the way it is now thought to be).

In the scenario where dryland salinity is not a problem (simulated by setting the water table at a depth where there is no risk of dryland salinity emerging) the model replicates the present land use pattern in the catchment, with minor variaf ons. The only change is that the cropping frequency is increased on the irrigated and dryland plains, and consequently recharge is slightly reduced. Figure H shows the current land use regime for the four areas and table 6 shows the corresponding average recharge and runoff.

Current land use Broughton (1994) estimates that 195 000 hectares of black soil plains might become salt affected if no action is taken to control the rise of water table. This situation was simulated using the model and is referred to as 'business as usual'. The model was run with accessions forced to be within 10 per cent of the initial

Land area Current iand use

D land Plains with Liverpool Hills %ins Irrigation ~ a n g e

DRYLAND SALINITY

6 Average recharge and runoff from current land use

Recharge Runoff

Dryland plains Irrigated plains Liverpool Range Hills

level to simulate a continuation of current accessions into the future. In this simulation the area salinised reached 191 000 hectares in the final year of the simulation. This simulation implies that land use decisions that ignore the salinity hazard, taken on the expectation that there will be no salinisation, would result in a large area lost to salinity. The following model runs investigate whether, and to what extent, salinisation can be reduced through land use change.

Scenarios B: Eflect of terminal land value The second variable under investigation is the value of land that is unsalinised in the terminal year of the model runs. The terminal land value is intended to represent the value in the final year modelled of the stream of income expected to accrue beyond that time. For the model runs reported here, the value ranges from zero to $8800 per hectare.

Three types of developments are possible. First, the rate of salinisation may be reduced in comparison to the 'business as usual' situation but remain pos- itive. This represents a situation where, at some point in the future, the entire area at risk would be salinised. Second, after an initial rise in salinity, the rate of salinisation may stabilise at zero. In this case, a stable level of salinity would be maintained. Third, the rate of salinisation may become negative and the area salinised fall over time. This would be achieved by land use change which reduces the water table and recovers slightly salt affected land.

Fully salinised land has virtually no income producing potential. If the area salinised is expected to remain constant from the closing year of the model, multiplying the area unsalinised in that year by the per hectare value of pro- ductive land should give a good approximation of the value, at that time, of discounted future expected net income. The model results indicate that it would be worthwhile, from a catchment perspective, to at least stabilise the area salinised if the terminal land value that produces a stable area of salinised land in the model is less than or equal to the a reasonable estimate of the per hectare value of productive land. On the other hand, if a modelled value much higher

DRYLAND SALINITY

than the per hectare value of productive land is required to stabilise the area salinised, the model results indicate that it is not economically worthwhile to stabilise salinity, from a catchment perspective.

Land value in the closing year modelled is unknown but inferences can be made. The price and yield assumptions made in the model involve falling real prices of farm products and stable productivity. In these circumstances land values are more likely to fall than rise so that current real land values could be above values at the end of the optimisation period. An alternative approach is to divide farm incomes derived from land in the final period by a discount rate to obtain a capitalised value of an infinite future income stream as an estimate of land value at that time.

Figure I presents the relationship between the terminal land value and the cal- culated encroachment of salinity over time. Some salinity develops even with the highest terminal land value because of current land use patterns and the time lag between recharge reduction and impacts on potentially salinised land.

Salt ajfected area depending on terminal land value The dotted line in figure I represents the business as usual scenario which is the worst case simulated. Optimising resource use with zero land value in year 30 almost halves the salt affected area at the end of the planning period but the salinisation rate remains clearly positive. At this rate of salinisation, the salinity maximum would be reached in about eighty years. A higher land value in year 30 of $2200 further slows the rate of salinisation.

@ Salt affected area depending on land value

Terminal land value so $2200

S44W

$6600

1 10 20 30 Year

DRYLAND SALINITY

A land value in year 30 of $4400 reduces the rate of salinisation to zero in year 18 and maintains the year 18 salinised area beyond that year. The stable level of salinity is calculated at about 38 000 hectares. Higher land values of $6600 and $8800 result in a decline in salinised area late in the planning period, after an initial rise to about 30 000 hectares.

The current average land value per hectare in the dryland plains is about $1000 based on ABARE survey estimates. An alternative estimate of land value in the closing years of the simulation can be made from the model by dividing the average net income generated in the last five years of optimisation by the discount rate. This gives a model based estimate of land value in the final year of about $1440 a hectare. Both of these values are well below the critical value of $4400 a hectare.

Development of land use on dryland plains and Liverpool Range The land use changes which occur under the assumption of a terminal land value of $4400 are presented in figure J. Land use in the irrigated plains and the hills remains unchanged from the present day situation. The land use changes are a combination of response to salinity and water table control measures. On the dryland plains, saltbush pasture is adopted on salt affected cropping and pasture land, lucerne becomes a more important part of rotations and some pasture area is planted to trees for water table management. In the Liverpool Range cropping is abandoned within a few years, and this helps to control salinity on the dryland plains. The change from cropping to pasture in the Liverpool Range contributes more than a fifth to the reduction in recharge on the dryland plains.

The cost to the Liverpool Range, in gross margin terms, is less than the cost of reducing recharge directly on the dryland plains. However, the cost of further reducing recharge on the dryland plains by changing pastures to trees on the Liverpool Range is estimated to be higher than the cost of making the same reductions in accessions on the dryland plains themselves. If the Liverpool Range and dryland plains were being managed separately rather than as a single catchment, then the Liverpool Range would have no incentive to act to reduce accessions in the dryland plains.

The higher level of salinity control on the assumption of higher terminal land values is achieved through converting more cropping land in the dryland plains to saltbush pasture. Retiring land in the Liverpool Range from grazing (with either tree planting or allowing regrowth) does not feature in any of the model runs reported here. Tt would take about 6 hectares of tree planting in the Liverpool Range to reduce salinisation on the plains by one hectare.

2 7

DRYLAND SALINITY

@ Development of land use on dryland plains and Liverpool Range

Area of dryland plains

Soltbush

Trees

Posture

Lucerne

I Cropping

1 10 20 30 Year

Area of liverpool Range

Trees

Pasture

I Cropping

Scenarios C: Effect of rainfall variability The third scenario variable (C) deals with rainfall variability. As explained pre- viously, the model can deal with rainfall variability. However, the previous simulations assume average seasonal rainfall in winter and summer. The recharge in an average season is less than the average of recharges over all seasons. For example, for a winter fallow on black soil, recharge in an 'average' winter is 4 mm. In comparison, the mean or weighted average is 3 1 mm. This is calculated by weighting the seasonal infiltration values in table 3, using probabilities of levels of rainfall derived from 100 years of historical data. Hence, assuming average rainfall conditions over the optimisation period may introduce a bias into the results by underestimating recharge.

The top section of figure K shows examples of variable rainfall runs. They are the runs with the highest, lowest, and median areas salinised at the end of the planning period. The bias is tested by comparing the run where salinity is

DRYLAND SALINITY

Salt affected area under Gariable rainfall conditions

Worst end-salinity

Median end-salinity

40

no*+

Year

'Average' rainfall condnions

1 10 20 30 Year

stabilised with average rainfall conditions with the mean of the series of 19 runs with variable rainfall and the same terminal land value. The rainfall is selected randomly for summer and winter for each of the 30 years simulated subject to the rainfall probabilities established over the last 100 years of rain- fall at Gunnedah. The bottom section of figure K summarises the findings.

Salt affected area under variable rainfall conditions Prolonged wet periods produce extreme accessions to the groundwater system that flow through to the area affected by high water tables and salinity. In dry periods, the salt affected area may decline if slightly salt affected land recovers to full productivity. The rainfall sequence with the lowest salinity also has the lowest objective value. This is because the sequence of low rainfall seasons that reduces salinisation also reduces crop and pasture yields and profits.

DRYLAND SALINITY

6. Conclusions

Current land use patterns in the Liverpool Plains are very similar to those obtained when the model is set to run without a salinity problem. This was the situation thought to exist until recent years. However, given that there are areas with high water tables on the Liverpool Plains and that there is a salinisation risk, the business as usual simulation shows that a continuation of current prac- tices may lead to a continuing rise of water table on the dryland plains that could be associated with large areas becoming salinised and consequent losses of agricultural income.

The decisions faced by a single manager for the catchment as a whole can be viewed in terns of three sets of tradeoffs. First are the tradeoffs between alter- native ways of limiting groundwater accessions or mitigating the effects of those accessions in each of the four areas of the catchment. Second is the tradeoff between seeking to reduce accessions to the water table from outside the dryland plains, for example by reducing cropping or increasing tree planting on the Liverpool Range and changing land management on the plains. Finally there is a tradeoff between the costs of salinity prevention or mitigation measures in aggregate and the benefits of having less land salinised - the net income stream from the area saved from salinisation.

Insight into the first two sets of tradeoffs can be gained from those model runs in which salinity is stabilised or reduced. The major changes in land use in those model runs are on the dryland plains. Saltbush pasture is planted on the salt affected land, trees are established for water table control and lucerne is an important part of the crop rotation. In the Liverpool Range, recharge is reduced by converting cropping on the alluvial fans to perennial pasture. In none of the runs is retirement of land from grazing in the Liverpool Range (either tree planting or allowing regrowth) part of the solution. Tree planting, changing cropping patterns and other enterprise changes on the dryland plains are more cost effective ways to limit or overcome the effects of salinity than is reducing groundwater accessions from the Liverpool Range (at least in part because it would take about 6 hectares of trees in the Liverpool Range for each one hectare reduction of salinity on the plains). The model does not indicate any land use change on the hills or irrigated plains for managing catchment salinity.

The model results suggests that effective catchment management need not involvc all landholders, even if it is seen as being worthwhile to limit the devel-

DRYLAND SALINITY

opment of salinity. Even eliminating salinity would involve changes in land management in the Liverpool Range and the dryland plains only. And the changes in the Liverpool Range would be limited to the cessation of cropping. The major effort in catchment management would, therefore, be directed at activities on the dryland plains. In the model the dryland plains are treated as a single unit and the analysis abstracts from the management problems of indi- vidual farmers with limited information. In practice, it is likely that there will be considerable interdependence between the actions of individual farmers on the dryland plains, so some form of coordinated approach is likely to be most cost effective in reducing or mitigating the effects of rising water tables.

Regarding the second set of tradeoffs, the model runs reported here suggest that it would be economic from a catchment perspective to stabilise the area salinised (at around 38 000 hectares) if the value of protecting an additional hectare of land from salinity were to be around $4400 in 30 year's time. The current average value of land in the dryland plains is estimated, from the farm survey, to be about $1000 a hectare. An estimate of land value in year 30, made using the model, is about $1400 a hectare. Both these values are well below the critical value of $4400 a hectare so that the expected value of land alone would not justify stabilising or reducing the area salinised.

It is possible that farm incomes, and thus land values in future, could be higher than current levels for a number of reasons, including increased productivity or higher commodity prices. It is also possible that current land values are reduced by the risk of future salinisation so that land prices of non salinised land would be higher in a sustainable situation. These possibilities were not examined in this research.

Unless there is an expectation that farm land prices will increase substantially, economic forces alone will not prevent the entire area at risk eventually becoming salinised. However, the analysis excludes any costs from salinisa- tion that occur outside the catchment or outside agriculture. These could include possible increased salt load in the Namoi River and damage to social infra- structure such as roads.

Rainfall variability is an important factor affecting salinity and agricultural output. Series of wet years accelerate water table rise and salinisation. Below average rainfall conditions assist the control of salinity but cause lower crop and pasture yields and loss of agricultural income. Depending on the run of seasons, the level of water table and salinity control is generally less, but some- times greater, than that expected on the basis of average rainfall. Thus the effect of varying rainfall is to skew the estimated areas salinised upwards compared with those estimated under average rainfall.

DRYLAND SALINITY

References

ABARE 1996, Farm Surveys Report 1996, Canberra.

Anderson, J., Britten, R. and Francis, J. 1992, Dryland Salinity ( I ) The Causes, Department of Conservation and Land Management, Department of Water Resources, Sydney.

Banks, R. G. 1995, Soil landscapes of the Curlewis 1:100000 Sheet, Depart- ment of Conservation and Land Management, Sydney.

Baumol, W.J. 1977, Economic Theory and Operations Analysis, 4th edn, Pren- tice Hall, Englewood Cliffs.

Bradd, J. and Gates, G. 1995, The progression from site investigation to GIs analysis to map dryland salinity hazard in NSW, Paper presented at the Murray Darling 1995 Workshop, Murray Darling Basin Commission Ground- water Working Group, Wagga Wagga, 11-13 September.

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Greiner, R. 1994, Economic assessment of dryland salinity in the Liverpool Plains, University of New England, Armidale.

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