Water Resour Manage (2009) 23:2085–2100DOI 10.1007/s11269-008-9371-4

Improving Cost Effectiveness of Irrigation Zoningfor Salinity Mitigation by Introducing Offsets

Thomas Spencer · Tihomir Ancev · Jeff Connor

Received: 17 January 2008 / Accepted: 22 October 2008 /Published online: 6 November 2008© Springer Science + Business Media B.V. 2008

Abstract Irrigation induced salinity is adversely affecting the agricultural industryand the environment in many countries around the world. Spatial location of irriga-tion enterprises has been identified as one important factor that needs to be takeninto account by policies aimed at mitigating salinity. In particular, policies aimedat restricting the location of irrigation enterprises have been recently proposed toaddress the irrigation induced salinity problem. This article compares and contraststhe costs of two versions of such a policy: a standalone irrigation zoning policy, wherenew irrigation enterprises are only allowed to locate in low salinity impact zones; anda salinity offsetting policy, where new irrigation enterprises can locate in high salinityimpact zones, provided that they offset their salinity impact elsewhere. A key findingis that the offsetting policy is both less costly and more effective in reducing salinitythan a standalone irrigation zoning policy. This is due to the presence of incentivesfor choosing “optimal” location of irrigation enterprises when the costs of salinityoffsets are taken into account.

Keywords Cost-effectiveness · Irrigation · Offsets · Salinity

T. SpencerFaculty of Law, University of Sydney, Sydney,NSW 2006, Australia

T. Ancev (B)Agricultural and Resource Economics (A04), University of Sydney,Sydney, NSW 2006, Australiae-mail: t.ancev@usyd.edu.au

J. ConnorCSIRO, Land and Water, Policy and Economics Research Unit,PMB2, Glen Osmond, SA 5064, Australia

2086 T. Spencer et al.

1 Introduction

Irrigation induced salinity has been an inadvertent follower and the ultimate doomof many prosperous agricultural systems throughout history (Hoffman and Durnford1999; Ghassemi et al. 1995). In some instances salinity occurs when salty shallowgroundwater table rises and encroaches into the crop root zone. Various technicalsolutions have been devised to control salinity problems of this type, mostly basedon the concept of keeping the salt flux away from the root zone of the crops,typically by means of some form of drainage (Konukcu et al. 2006). In other instancessalinity arises when drainage originating from irrigation activities carries salt intorivers and streams. Technical measures to alleviate salinity problems of this typeinclude the use of dilution flows, installing interception schemes, improving water useefficiency on and off-farm, and the disposal of saline drainage water into evaporationponds (Ghassemi et al. 1995; Heaney et al. 2001; Connor 2008). In addition tothese technical measures, the connection between the spatial location of irrigationenterprises and their contribution to river salinity has been noted (Scherer 1977;El-Ashry et al. 1985; Gardner and Young 1988). Accordingly, policies have beendevised that mandate or provide incentives for irrigation developments to locate inareas where they would cause less salinity impact (Duke and Gangadharan 2005).

Rising salinity levels as a consequence of drainage from intensive irrigation indus-try in Australia has been recognised as a significant threat to agricultural productivityand the environment (Adamson et al. 2007). To address the issue, irrigation zoningpolicy that restricts the location of new irrigation developments to areas wheresalinity impact is relatively low has been in place in the irrigation regions along theRiver Murray in Victoria, Australia, since 1994 (Sunraysia Rural Water Authority2002). Similar policy was recently introduced for the South Australian portion of theRiver Murray (DWLBC 2005). Under this policy, new irrigation developments inareas that are deemed to have high salinity impact are not allowed.

This paper assesses the cost effectiveness of two versions of this policy. Oneversion of the policy is termed ‘standalone irrigation zoning’, representing a policywhere locating new irrigation enterprises in the high salinity impact zones is pro-hibited. This version of the policy is currently in use in South Australia. The otherversion of the policy is termed ‘offsetting’, and it represents the possibility for newirrigation enterprises to locate in the high salinity impact areas provided that thesalinity impact from this new irrigation developments is offset by reducing salinityimpact elsewhere. Offsetting of this type has been recognised as a potential featurethat could be included in government policy, but it is not currently implemented(Government of South Australia 2005).

The motivation for this study is founded on the notion that while a standaloneirrigation zoning policy is likely to result in reduced salinity impact, it is also likely toincrease aggregate irrigation costs for the region. Since low salinity impact zones aretypically located further away from the river channel, zoning will increase aggregateirrigation costs as a result of higher water delivery costs, in particular due to increasedcosts of piping, and pumping water. Hence, an alternative arrangement that wouldachieve the same quantum of salinity mitigation, but at a lower cost to the irrigationindustry would be desirable.

The cost-effectiveness of policies designed to address environmental issues isfundamentally important to the environmental economics analysis. The problem

Cost effectiveness of irrigation zoning for salinity mitigation 2087

of irrigation induced salinity can be viewed as a typical problem of an unpricedexternality, whereby individual irrigators that cause salinity impacts do not takeinto account those impacts into their decision making process (Heaney et al. 2001).Policies based on technology or quantity standards (sometimes called ‘command-and-control’ policies) have been widely implemented to control externality problemsof this type (Heanley et al. 1997). A strict, standalone irrigation zoning policy is anexample of such a standard, where a strict provision on location of new irrigationenterprises is mandated (commanded), and the fulfilment of this provision is moni-tored (controlled). However, it has long been established in the economics literaturethat these type of standards are unnecessarily costly way to achieve improvements inenvironmental quality, and that offsetting can reduce the cost of achieving improvedenvironmental outcomes (Heanley et al. 1997, pp. 130–138).

The primary objective of this paper is to determine whether introducing offsettingas a feature of an irrigation zoning policy can reduce the costs of achieving longterm salinity reduction in comparison to having a standalone irrigation zoning policywithout offsets. This is pursued by comparing the costs of standalone irrigationzoning policy to the costs of a policy that includes offsetting. At the same time, theexpected salinity impacts of the two versions of the policy are evaluated.

This study builds on prolific literature on the theory of environmental offsettingfor non-point source pollution (e.g. Shortle and Horan 2001; Randall and Taylor2000; and Stavins 2000). The empirical case study presented in this paper is conductedin the tradition of the physical-economic modelling literature recently reviewedby Heinz et al. (2007). Alternative policies to address irrigation induced salinitywith a particular focus on the River Murray and South Australia have been re-cently analysed. Connor et al. (2004) evaluate zoning, and Connor (2008) evaluatesmitigation using infrastructure to pump saline water away from the river. Dukeand Gangadharan (2005) evaluate the effect of salinity impact levies. The presentpaper goes beyond these studies to formulate a theoretical framework for a salinityoffsetting scheme and to empirically test the cost-effectiveness of the irrigationzoning policy with and without salinity offsetting.

2 Analytical Framework

Consider a conceptual model that incorporates some of the salient characteristics ofthe salinity problem along a river channel. For this purpose it is useful to imaginea region surrounding a river which can be delineated into a number of analysisareas. Each of these areas has a high and a low salinity impact zone defined withinits realms. This configuration is illustrated in Fig. 1. Classification of high and lowimpact zones is based on the potential to contribute to long term river salinity asa consequence of salt load coming from these zones. Within each zone there issome existent irrigation activity, and some new irrigation activity can potentially bedeveloped.

The cost of water delivery is assumed to differ across analysis areas and betweensalinity impact zones. Irrigators located further from or higher above the riverchannel face higher water delivery costs resulting from higher fixed costs (piping)and higher operation costs (pumping). It is assumed that salinity impact is inverselyrelated to the distance from and height above the river, in line with the principles

2088 T. Spencer et al.

Fig. 1 Configuration ofanalysis areas (a = i) andsalinity impact zones alonga river channel

of hydrogeology governing river salt loading (Knight et al. 2002). This means thatthere is generally higher salinity impact where costs of water delivery are low andvice versa.

In addition, it is assumed that salinity impact resulting from an irrigation devel-opment is higher if the development is located further upstream. This is reflecting asalient characteristic of the actual river systems that salt released to the river furtherupstream impacts greater number of downstream water users (Heaney et al. 2001).This is a fairly general assumption, and the actual magnitude of the salinity impactfrom each analysis area would depend on many other hydrologeological and soilcharacteristics (e.g. geological disposition of salt deposits, and surface–groundwaterconnectivity). In addition, the magnitude of the impact will depend on the proximityof a given irrigated agricultural region to a significant environmental or infrastructureasset that is being harmed by salinisation (i.e. the spatial distribution of the salinityimpact in relation to the value of environmental assets affected is important).Despite these limitations, the general notion that under similar circumstances thesalinity impact from upstream areas is generally more pronounced than that fromdownstream areas does reflect the reality of the river system considered in this paper.

2.1 Unregulated Irrigation Development

To establish a baseline, consider a situation where the location of new irrigationenterprises is not restricted. In the absence of regulation, the economic behaviourof irrigators can be analysed by looking at the whole irrigation industry in the region.From the irrigation industry’s perspective the objective is to maximise net revenues�, by choosing where to locate new irrigation enterprises:1

maxH a, z

∏=

∑

a∈A

∑

z∈Z

[(∑

c∈C

(da,c (pc yc − OCc)

) − WSCa,z

)Ha,z

].

a ∈ A = {1, . . . , n} , z ∈ Z = {HI, L} , c ∈ C = {l, . . . , m} (1)

1Net revenue is defined as the difference between total revenue from sale of agricultural products,and the total cost of producing those products.

Cost effectiveness of irrigation zoning for salinity mitigation 2089

The choice variable, Ha,z represents the number of hectares of new irrigationdevelopment established in analysis area a and impact zone z. The set A containsthe analysis areas, and is so ordered that a smaller number indicates that the analysisarea is located further downstream. Z represents the set of impact zones (high(HI) or low (L) salinity impact) within an individual area, and C represents theset of possible crops that could be grown in the region. pc is the price receivedfor crop c; yc represents the yield of crop c; OCc represents the costs of producingcrop c, excluding the cost of water delivery and application; WSCa,z representsaverage water delivery and application cost for area a and salinity impact zone z;da,c represents the proportion of crop c that is currently produced in a, such that0 ≤ da,c ≤ 1 and

∑c∈C

da,c = 1.

The problem stated above is constrained by the maximum number of hectares onwhich development of new irrigation enterprises can take place in the whole region,which is determined by the amount of additional water available for irrigation in theregion, and the composition of the crop mix for the new irrigation enterprises.2 Thisconstraint can be represented as:

∑

c

(Ha,z,c • WRc

) ≤ W, (1.1)

where WRc represents the water requirement for crop c in megaliters (ML) perhectare per year, and W represents the volume of new water entitlements thatbecome available in the region (ML/year).

Maximizing the objective function in Eq. 1 subject to the stated constraint wouldresult in a solution that reflects the tendency of irrigation enterprises to locate asclose as possible to the river channel, driven by the water delivery cost.3 This isconsistent with reality, as large proportion of irrigation in the case study area of SouthAustralian Riverland is typically found near the river channel (Connor 2003).

2.2 Irrigation Zoning

In comparison to the no-regulation case presented above, the introduction of a stand-alone irrigation zoning policy prevents new irrigation development from locating inhigh impact zones. This modifies the objective function from the irrigation industry’s

2The additional water quantity can be provided by issuing new water entitlements in the region, orby buying (importing) existing water entitlements from other regions. The latter is the only possibleway to provide new water entitlements along the River Murray in Australia, as a result of an interjurisdictional agreement known as the Murray-Darling Basin Cap (Quiggin 2001).3Maximisation of the objective function (1) amounts to maximizing the difference between netrevenues from producing crops, and the cost of water delivery and application. Since the cost ofwater delivery is a function of the distance of the irrigation enterprise from the river channel (thegreater the distance, the higher the cost), locating closer to the river channel maximises the objectivefunction, and is hence an optimal location choice for new irrigation enterprises in the absence ofregulation.

2090 T. Spencer et al.

perspective. Under this policy, all new irrigation developments have to locate in thelow impact zones and hence the overall net revenues to the irrigation industry are:

∏Z =∑

a∈A

∏Za =

∑

a∈A

[(∑

c∈C

(da,c (pc yc − OCc)

) − WSCa,z=L

)Ha,z=L

](2)

where �Za denotes net revenues in any analysis area a under a standalone zoning

policy.

2.3 Introducing Offsets

When the irrigation zoning policy is augmented with an offsetting system, newirrigation developments can locate in both low and high salinity impact zones. In thiscase, the choice of where to locate new irrigation enterprises (Ha,z) from an irrigationindustry’s perspective may be formulated as the one that maximizes the following:

maxHa,z

∏T =∑

a∈A

[(∑

c∈C

(da,c (pc yc − OCc)

) − WSCa,z=L

)Ha,z=L

]

+∑

a∈A

[(∑

c∈C

(da,c (pc yc − OC)

) − WSCa,z=H − pcredit · Sa,z=H

)Ha,z=H

].

(3)

pcredit is the price of an offsetting credit—expressed in Australian Dollar (AUD)per elctroconductivity unit (EC) per annum—, and Sa,z=H represents the salinityimpact per hectare of irrigation located in the high salinity impact zone of analysisarea a. Both the price of an offsetting credit and the salinity impact are expressedat a parity that is common to all analysis areas and the zones within them. In thecase study of this paper, that parity is given by the electroconductivity unit (EC)reading at the measurement point of Morgan, South Australia. The significance ofthis measurement point is in that it represents a good indicator of the expectedquality of the water drawn for drinking water supply for the city of Adelaide. Alloffsetting credit prices and salinity impact reductions are expressed in terms ofthis parity.

2.3.1 Demand for Salinity Offsets

To analyse the demand for offsets, one proceeds by differentiating Eq. 3 with respectto Ha,z and setting the derivative equal to zero. This yields:

∂∏T

∂ Ha,z=L=

∑

c∈C

(da,c (pc yc − OCc)

) − WSCa,z=L = 0 (4)

∂∏T

∂ Ha,z=H=

∑

c∈C

(da,c (pc yc − OCc)

) − WSCa,z=H − pcreditSa = 0 . (5)

Cost effectiveness of irrigation zoning for salinity mitigation 2091

These simply state the optimality conditions for locating in the high and low salinityimpact zones, respectively.4 Equating Eqs. 4 and 5, which establishes a point ofindifference between locating in high or low salinity impact zone, and solvingsimultaneously gives:

p∗a,credit = WSCa,z=L − WSCa,z=H

Sa(6)

where p∗a,credit represents the maximum amount that a developer of a new irrigation

enterprise would be willing to pay for a salinity offset in the high impact zone ofan analysis area a. For any offset price less than this maximum willingness-to-pay(WTP), pcredit < p∗

a,credit, a developer will choose to buy the offset and to locatewithin the high impact zone of a. This will yield them:

∏T

a,z=H=

(∑

c∈C

(da,c (pc yc − OCc)

)−WSCa,z=H − pcredit · Sa,z=H,y

)Ha,z=H >

∏Z

a,

(7)

where �Ta,z=H is the net revenue under the salinity offsetting scheme (superscript T)

in area a, and �Za is the net revenue under the standalone zoning policy (super-

script Z ) in the same area. When the offset price is equal to the maximum WTP,pcredit = p∗

a,credit, a developer of a new irrigation enterprise will be indifferent betweenlocating in the high or the low impact zone (i.e. indifferent between paying the offsetprice when locating in a high impact zone, or incurring a higher cost of water deliverywhen locating in a low impact zone). If the offset price is greater than the maximumamount that the developer is willing to pay for credits in the area a, pcredit > p∗

a,credit,then the developer will locate new irrigation enterprises in the low salinity impactzone, and secure a net revenue which is equivalent to the net revenue obtained underthe standalone zoning policy. These observations lead to the following result:

Result 1 Under a salinity offsetting system, assuming negligible costs of transactingin offsets, the net revenues from a new irrigation development in each analysis areaare at least as large as those obtained under standalone irrigation zoning.

This result can be analytically represented as:

∏ta =

⎧⎪⎪⎨

⎪⎪⎩

∏Ta,z=H = ∏Z

a if pcredit < p∗a,credit

∏Ta = ∏Z

a if pcredit = p∗a,credit

∏Ta,z=L >

∏Za if pcredit > p∗

a,credit

(8)

4Equations 4 and 5 represent first order conditions for optimality. The first equation states that at theoptimum, the marginal net revenue from allocating one more hectare of new irrigation enterprise inthe low salinity impact zone has to equal the marginal water delivery cost associated with this. Thesecond equation states that at the optimum, the marginal revenue from allocating one more hectareof new irrigation enterprise in high salinity impact zone has to be equal to the marginal water deliverycost plus the cost of purchasing the offset.

2092 T. Spencer et al.

The demand schedule for offsets, relating the quantity of offsets demanded (Qda)

in an area a to their price, pcredit can be represented as:

Q da =

⎧⎪⎪⎨

⎪⎪⎩

Sa · Ha,z=H if pcredit < p∗a,credit

[0, Sa · Ha,z=H

]if pcredit = p∗

a,credit

0 if pcredit > p∗a,credit

(9)

2.3.2 Supply of Salinity Offsets

Every year, a certain portion of the irrigation assets, including crops and waterdelivery assets in an irrigation region are due for replacement because they havecome to the end of their productive life. The irrigators can choose whether to replaceageing irrigation assets, or to cease irrigation activities and hence being creditedwith salinity offsets. If the irrigators choose to replace the irrigation assets, theywill continue producing irrigated crops and each year will be obtaining net revenue

from that activity of(∑

c∈Cda,c(pc yc − OCc)) − WSCa,z=H

)Ha,z=H,rep. If the irrigation

assets in the area are not replaced, and in the presence of an offsetting policy,irrigators are entitled to salinity offset credit, which they can sell and obtain a payoffof Sa · Ha,z=H,rep pcredit. The microeconomics of the decisions that irrigators face inthis circumstances is well described elsewhere (Dinar and Letey 1991) and will notbe elaborated here. An implicit assumption made in this paper is that only “cornersolutions” are possible, i.e. that an operator of depreciated irrigation assets eitherreplaces all of the assets, or does not replace any of the depreciated irrigation assets.In principle, the optimal solution can be anywhere between these two extremes, sothat “interior solutions” where some fraction of the irrigation assets in an area isreplaced are possible, and indeed plausible. The assumption of “corner solutions”was made for simplicity’s sake, and does not alter the generality of the obtainedresults. It can be easily relaxed, but would add to the complexity of the analyticalrepresentation.

The decision not to replace ageing irrigation assets under the existence offunctioning water market, and a system for salinity offsets, opens up two possibletransactions for the operator: selling their water entitlement, and selling of anysalinity reduction credits (offsets) that they may be entitled to. The interaction be-tween irrigation water trade and trade in salinity reduction credits has been recentlyexamined in the literature (Legras and Lifran 2006). In the current paper, only themarket for salinity offsets is considered, while the market for water entitlements istaken as given.

Having these explanations in mind, and following a similar procedure as in theanalysis of the demand, one can derive:

p∗ ∗a,credit =

∑c∈C

(da,c(pc yc − OCc

)) − WSCa,z=H

Sa, (10)

where p∗ ∗a,credit represents the ‘threshold supply price’ for salinity offset credits above

which no irrigation assets are replaced in area a. Below this price all irrigation assets

Cost effectiveness of irrigation zoning for salinity mitigation 2093

due for replacement in area a will be replaced and no credits will be supplied. Asupply schedule for salinity credits can be represented by:

Q sa =

⎧⎪⎪⎨

⎪⎪⎩

0 if pcredit < p∗ ∗a,credit

[0, Sa · Ha,z=H,rep

]if pcredit = p∗ ∗

a,credit

Sa · Ha,z=H,rep if pcredit > p∗ ∗a,credit

(11)

Similarly to the demand for salinity offsets, the higher the salinity impact resultingfrom irrigation development in an area, the lower the ‘threshold supply price’ abovewhich salinity offsets will be supplied.

3 Case Study Analysis

To provide empirical insight, the cost of an irrigation zoning policy with and withoutan offsetting system was estimated for the South Australian portion of the RiverMurray. The Riverland region of South Australia comprises an area of aroundten kilometres on either side of the Murray River, comprising around 45,000 haof irrigated land. It is one of Australia’s major horticultural regions with a grossvalue of agricultural production for the 2001/02 financial year of $810 million (ABS2005). In 1987, institutional rules allowing water trade across regions independentof the land title were introduced in the river Murray basin. As a result, water hasbeen trading into the case study region where high value horticultural crops can beprofitably produced (Bjornlund 2004). Irrigation activity within the Riverland hasbeen recently growing at a rate that exceeds the national average; however salinityimpacts resulting from this increased irrigation development threaten the long termsustainability of this growth (BTRE 2003, p. 98).

For the purposes of this analysis the region was delineated into seventeen Landand Water Management Plan (LWMP) areas. This is presented in Fig. 2. Each areawas classified into a high impact zone (z = HI) and a low impact zone (z = L), excepttwo—Monash only had a low impact zone and Gurra Gurra Lakes only had a highimpact zone.

Irrigated agriculture in the region is represented by five major crops: almonds,grapes, oranges, apricots, and potatoes. In 2005 these crops represented 85% of totalirrigated agriculture in the region by acreage. For the purposes of the empiricalstudy, the total amount of new irrigation development in the region was assumedto follow the trend of irrigation expansion observed over the last 5–10 years in theSouth Australian Riverland, which was around ten percent per annum (BTRE 2003,p.158). This expansion in irrigated area was the main driver of the demand for offsets.

On the supply side it was assumed that offsets purchased by the enterprises thatchoose to locate in a high salinity impact zone are supplied by other irrigationenterprises that decide not to continue with their existing irrigation activity. In eachof the analysis areas some of the existing irrigation assets used in production ofcrops (consisting of both current irrigated crop acreage and/or infrastructure forwater delivery and application) are assumed to become fully depreciated and requirereplacement if normal production is to continue. This can occur through the processof crop ageing (e.g. almond plantations in South Australia are typically replacedevery 25 years), and through depreciation of infrastructure assets related to irrigation

2094 T. Spencer et al.

Fig. 2 Analysis areas in the South Australian Riverland. Source: Walker et al. (2005)

water delivery and application (e.g., the main pipes and sprinkler systems are fullyamortized over 20 years). The rate at which assets are due for replacement usedin this analysis was based on empirical information from the region. The possibilityof not replacing these depreciated irrigation assets, and hence not continuing withirrigation activities, which in turn means that salinity impact will be reduced, was themain driver of salinity offsets supply.

Conceptually, further efficiency gains could be possible if offsets were also allowedfor irrigators who improve irrigation practice in ways that reduce drainage and thusreduce salinity impact. The drawback with such an approach is that it would requireexpensive monitoring of on-farm irrigation management, and modelling to relatepractices to salinity impact. The offsetting modelled here, like the zoning policythat it augments, requires much less monitoring; it only requires knowledge of thearea developed for irrigation. Thus the offset policy that is simulated is in essence afeasible second-best policy that allows trading in salinity impact-weighted hectaresof area developed for irrigation, rather than in salinity per se.

The crop mix for the new irrigation enterprises was assumed to be the sameas the crop mix of the existing irrigation enterprises in each analysis area. Yields,prices, fixed and variable costs for each of these crops were obtained from Walkeret al. (2005). Average crop water requirements, the costs of using existing waterentitlements, as well as the costs of acquiring and using new water entitlements wereobtained from the same source. The approach taken here was that of a representativefarm (Kobrich et al. 2003), which meant that irrigation enterprises of the same kind(i.e. growing a given irrigated crop) within a single analysis area were assumed tobe similar with respect to irrigation technology and other agricultural productionaspects. While this approach has shortcomings since it assumes away some inherent

Cost effectiveness of irrigation zoning for salinity mitigation 2095

differences between individual farm operators, including some of their economicand environmental characteristics, it is adequate for the present study, because theanalysis areas in the present case study are small, and it might be expected thatvariation in irrigation and production technology among enterprises within a smallarea would not be highly significant. In addition, the representative farm approachis taken only to represent the irrigation and production technology aspects for aparticular kind of enterprise, and in a single analysis area. The variability betweenenterprises in various analysis areas with respect to the cost of water supply and thesalinity impact is maintained and analysed in detail. Indeed it is this variability ofcost between analysis areas—and between high and low salinity impact zones—thatimpacts on the cost-effectiveness of the policy regime.

Further data were collected from other sources. The impact of river water salinityon crop yields was taken into account by using the data published in Lantzke andCalder (2005). This was done by incorporating the reported yield reduction as a resultof increased salinity level for each of the considered crops—which in turn affects thegross margin for each crop—into the optimisation model.

Water delivery costs were calculated based on average distances and elevationof various analysis areas, costs of piping and electricity costs. The salt load andthe salinity impact from each of the areas under a given distribution of crops wereestimated with the SIMPACT model (Miles et al. 2001). The SIMPACT modelestimates drainage impact on groundwater levels, and the way that elevated salinegroundwater levels transmit hydrologic pressure causing increased salt loading in theriver. It predicts spatially varying salt load per megalitre of drainage.

For simplicity, and in order to match annual demand with the annual supplyof offsets, rather than having to match demand and supply of salinity offsets overthe lifetime of an irrigation development, it was assumed that the offsets are onlytransacted on an annual basis.

Using the data outlined above, an optimisation model was set-up to simulateregional net revenues from the new irrigation developments, and the resultingsalinity impact under three scenarios: (1) a baseline scenario, where no restrictionon development of new irrigation enterprises has been imposed; 2) a stand aloneirrigation zoning scenario, where new irrigation can only take place in low salinityimpact zones; and 3) an offseting scenario, where new irrigation enterprise can locatein high salinity impact zones provided the salinity impact is offset.

Scenarios 1 through 3 were solved as optimisation problems using the objectivefunctions corresponding to Eqs. 1, 2 and 3, respectively. In each case the objectivefunction was maximised subject to the constraint 1.1 as discussed in the theorysection. For the salinity offset scenario the demand and supply schedules for salinityoffsets were parameterized by varying the price of salinity credits and repeatedlyresolving the problem for each parameterised value.

4 Results

The results for all scenarios are summarised in Table 1. Under the baseline scenario,as expected, most new irrigation development located in the high impact zones. Thiscorresponds well with previous empirical findings. In 2001, when an inventory ofirrigated areas was conducted for the case study area, 33,903 ha were located in what

2096 T. Spencer et al.

Tab

le1

Cos

ts,s

alin

ity

impa

ct,q

uant

ity

and

pric

eof

salin

ity

cred

its

unde

rth

eth

ree

polic

ysc

enar

ios

Ann

ualc

ost

Net

salin

ity

impa

ctN

umbe

rof

offs

ets

trad

edP

rice

ofcr

edit

sA

vera

geco

stof

redu

cing

(AU

D)

(EC

incr

ease

per

annu

m,a

s(E

Cun

its

per

annu

m,a

s(A

UD

/EC

unit

/sa

linit

yre

adin

gat

mea

sure

dat

Mor

gan,

SA)

mea

sure

dat

Mor

gan,

SA)

per

annu

m)

Mor

gan,

SAby

1E

C

Bas

elin

esc

enar

io:

Unr

estr

icte

dir

riga

tion

02.

5867

00

0Sc

enar

io1:

Zon

ing

wit

hno

offs

ets

458,

900

0.26

700

019

7,83

0Sc

enar

io2:

Salin

ity

offs

ets

357,

501

0.18

700.

0292

9,32

814

8,98

0

Cost effectiveness of irrigation zoning for salinity mitigation 2097

is now classified as high impact zones and 10,452 hectares in what is now classified aslow impact zones (Connor 2003).

The overall annual net revenue from new irrigation development activities forthe whole region under this scenario was AUD 3,627,733.5 The average long-runexpected salinity impact from new irrigation development under this scenario wasestimated to be 2.5867 electro-conductivity (EC) units per annum at the monitoringreference point in Morgan, South Australia, near the mouth of the river. Salinityimpact at this rate over a decade or more would lead to a substantial increase in riversalinity. In the absence of any policy to address location of irrigation enterprises, andto aim at reducing this substantial increase in stream salinisation, greater crop yieldlosses and water infrastructure salinity damage can be expected (MDBMC 1999).According to the MDBC Basin Salinity Management Strategy agreement, the SouthAustralian Government is required to take actions to mitigate this substantial impact(MDBMC 2001).

Under the standalone irrigation zoning scenario all new irrigation had to locate inthe low impact zones. The overall annual net revenue from new irrigation activitiesfor the whole region under this scenario was AUD 3,168,833. The salinity impactunder this scenario was estimated to be 0.267 EC units per annum as measured bythe expected increase in EC reading at Morgan, SA. This represents a considerablylower impact compared to the baseline scenario.

Under the offsetting scenario, new irrigation can be located both in low and highsalinity impact zones, provided that the salinity impact from new developments inhigh impact zones are offset with salinity credits. The overall annual net revenuefor the whole region under this scenario was AUD 3,270,232. Net salinity impactunder this scenario was estimated to be 0.187 EC units per annum as measured by theexpected increase in EC reading at Morgan, SA. The estimated equilibrium quantityof salinity offsets was 0.02 EC units per annum (at Morgan, SA parity), which wasabout 11% of the overall annual salinity impact. The associated equilibrium price ofoffsets was AUD 929,328 per EC unit per annum.

5 Discussion

The results obtained from simulating the three scenarios indicate several importantfindings. Firstly, the location of irrigation enterprises is indeed an important factorto consider in order to prevent an increase of salt load growth in irrigation intensiveregions, such as the case study region in South Australia. A standalone irrigationzoning policy that will rigidly restrict the location of new irrigation developmentswill result in significant reduction of the salinity impact. However, the cost of thispolicy will be higher than the cost of an alternative policy that allows offsetting ofsalinity impacts. The cost for irrigators to comply with a stand alone zoning policyis estimated to be AUD 458,900 in comparison to the baseline case, while the costof complying with a zoning policy augmented with offsetting is estimated to beAUD 357,400. This implies that incorporation of offsetting reduces the estimatedcost of zoning by AUD 101,000 per year, or by 22%. Whether these cost savings are

5Australian dollar (AUD). 1 AUD = 0.65 USD; 1 AUD = 0.50 EUR in October 2008.

2098 T. Spencer et al.

large enough to justify the implementation of offsetting within the existing zoningpolicy will crucially depend on the size of the costs for administering, monitoringand transacting within the offsetting scheme. While estimation of these costs wasbeyond the scope of the current paper, particularly due to lack of any availabledata that could be used to estimate these costs, research in this direction is of animmediate interest. Costs of transacting in the context of achieving environmentaloutcomes under alternative set of policies in an agricultural basin were evaluatedby McCann and Easter (1999). The approach taken in that paper can be used toevaluate transaction costs of salinity offsetting, provided that data specific to the casestudy region is gathered.

A policy that incorporates salinity offsets also achieves a greater reduction of theoverall salinity impact level compared to the standalone zoning policy. The reductionof salinity impact achieved with the offseting policy is superior compared to thestandalone zoning policy as a result of the greater flexibility in location choices. Whenoffsetting is not allowed, new irrigation developments have to locate in low impactzones. Even though the salinity impact in these zones is relatively small, it is not beingoffset by the reduction of salinity impact elsewhere. When offsetting is introduced,some of the new irrigation developments that would have otherwise located in thelow impact zones will locate in high impact zones. While their salinity impact will begreater, it will be fully offset by reduction of salinity impact in other areas.

For the existing irrigation enterprises, the possibility of offsetting creates anopportunity cost to the decision to replace depreciated irrigation assets. This deter-mines the supply side for offsets. On the other hand, given the substantial costs ofoffsets, new irrigation enterprises will tend to locate in those areas where relativelyfewer offsetting credits will be required. This determines the demand side for offsets.

The cost advantage of a zoning policy augmented with offsets can be furtherillustrated by comparing the average costs of reducing salinity impact. Under thestandalone irrigation zoning scenario a reduction of 2.32 EC units as measured inMorgan, SA is achieved compared to unregulated irrigation location scenario. Thetotal cost of achieving this reduction, measured as reduction of net revenue to theirrigation industry in the region was estimated to be AUD 458,900. This amounts toan average cost of AUD 197,830 per 1 EC unit reduction as measured at Morgan,SA. When a similar calculation was conducted for the salinity offsetting scenario, theaverage cost of salinity reduction amounted to AUD 148,980 per 1 EC unit reductionas measured at Morgan, SA. This highlights the cost-effectiveness of the salinityoffsetting policy as compared to the standalone irrigation zoning policy.

6 Summary and Conclusion

The paper addressed the problem of choosing policies for mitigating irrigationinduced salinity at least-cost. Since the spatial location of irrigation enterprises isone important factor in determining the salinity impact of those enterprises, policiesthat restrict location choices have been proposed and implemented to addressthe problem. One such policy is the irrigation zoning, recently adopted in SouthAustralia. The paper compares this with an alternative policy, where the locationof new irrigation enterprises is not restricted per-se, but any new developments in

Cost effectiveness of irrigation zoning for salinity mitigation 2099

areas that are designated as “high salinity impact” are required to offset their salinityimpact by reduction of salinity impact elsewhere.

Key theoretical findings are that a zoning policy augmented with offsetting willbe as profitable as standalone irrigation zoning policy in any analysis area. Thisresult was tested in an empirical study. The study simulated three scenarios usingoptimisation methods: a baseline scenario under which the location of new irrigationenterprises was unregulated, a standalone irrigation zoning scenario, and a salinityoffsetting scenario. The results suggest that both standalone irrigation zoning andirrigation zoning policy augmented with offsetting will substantially reduce salinityimpact when compared to the baseline scenario, and will do so at very reasonablecosts. Direct comparison of the standalone zoning and offsetting scenarios howevershows that an offsetting policy achieves a better salinity outcome and at a lower costthan standalone zoning policy.

Several conclusions can be drawn from the above discussion. Influencing thelocation of irrigation enterprises in order to mitigate irrigation induced salinity,either by quantity regulation, as presented here, or by price regulation (Duke andGangadharan 2005), is a sound policy option. However, a mandating regulation inthe form of irrigation zoning is going to be more costly and less effective in achievingreduction of salinity impact, as compared to a more flexible, incentive based policy.An offsetting policy using salinity credits is one such policy, and the empirical findingsreported here show that it is superior to a standalone zoning policy, both in terms ofcosts and in terms of salinity impact reduction.

References

Adamson D, Mallawaarachchi T, Quiggin J (2007) Water use and salinity in the Murray-DarlingBasin: a state-contingent model. Aust J Agric Resour Econ 51:263–281

Australian Bureau of Statistics (ABS) (2005) Year book of Australia: agriculture, crops 1301.0.Available via: http://www.abs.gov.au/Ausstats/abs@.nsf/0/84A6B87A0262F4EBCA256F7200832FF1?Open#Links

Bjornlund H (2004) Formal and informal water markets—drivers of sustainable rural communities?Water Resour Res 40(40):9, W09S07. doi:10.1029/2003 WR002852

Bureau of Transport and Regional Economics (BTRE) (2003) Investment trends in the lowerMurray Darling Basin, Working Paper 58, Department of Transport and Regional Services,Canberra

Connor J (2003) Reducing the cost to South Australia of achieving agreed salinity targetsin the River Murray. Final report to Department of Water, Land and Biodiversity Con-servation, South Australia, CSIRO Land and Water. Available via: http://www.clw.csiro.au/publications/consultancy/2003/reducing_cost_salinity.pdf

Connor J (2008) The economics of River Murray salinity management with salt interception. WaterResour Res 44:W03401. doi:10.1029/2006WR005745

Connor J, Butters S, Clifton C, Ward J (2004) Trialling incentive-based policy to control drylandsalinity in the Bet Bet catchment, north central Victoria, working with science and society. In:Proceedings of the salinity solutions conference, 2–5 August, Bendigo

Department of Water, Land and Bio-diversity Conservation (DWLBC) (2005) River MurraySalinity Zoning Fact Sheet, Government of South Australia. Available via: http://www.dwlbc.sa.gov.au/murray/salinity/zoning.html? friendly=printable

Dinar A, Letey J (1991) Agricultural water marketing, allocative efficiency and drainage reduction.J Environ Econ Manage 20:210–223

Duke C, Gangadharan L (2005) Regulation in environmental markets: what can we learn fromexperiments to reduce salinity? Aust Econ Rev 38:459–69

El-Ashry MT, Van Schilfgaarde J, Schiffman S (1985) Salinity pollution from irrigated agriculture.J Soil Water Conserv 40:48–52

2100 T. Spencer et al.

Gardner RL, Young RA (1988) Assessing strategies for control of irrigation-induced salinity in theUpper Colorado River Basin. Am J Agric Econ 70:37–49

Ghassemi F, Jakeman AJ, Nix HA (1995) Salinisation of land and water resources. University ofNew South Wales Press, Sydney

Government of South Australia (2005) Regional impact assessment statement: River Murray SalinityZoning. Available via: http://www.southaustralia.biz/library/RIAS_Salinity_Zoning-10.pdf

Heanley N, Shogren JF, White B (1997) Environmental economics in theory and practice. OxfordUniversity Press, New York

Heaney A, Beare S, Bell R (2001) Evaluating improvements in irrigation efficiency as a salinitymitigation option in the South Australian Riverland. Aust J Agric Resour Econ 45:477–493

Heinz I, Pulido-Velazquez M, Lund JR, Andreu J (2007) Hydro-economic modeling in River BasinManagement: implications and applications for the European water framework directive. WaterResour Manage 21:1103–1125

Hoffman GJ, Durnford DS (1999) Drainage design for salinity control. In: Skaggs RW, vanSchilfgaarde J (eds). Agricultural drainage. Agronomy No. 38. American Society of Agronomy,pp 579–614

Knight JH, Gilfeder M, Walker G (2002) Impacts of irrigation and dryland development on ground-water discharge to rivers—a unit response approach to cumulative impacts analysis. Technicalreport 03/02, CSIRO Land and Water

Kobrich C, Rehman T, Khan M (2003) Typification of farming systems for constructing represen-tative farm models: two illustrations of the application of multivariate analyses in Chile andPakistan. Agric Syst (76):141–157

Konukcu F, Gowing JW, Rose DA (2006) Dry drainage: a sustainable solution to salinity problemsin irrigation areas? Agric Water Manag 83:1–12

Lantzke N, Calder T (2005) Water salinity and crop irrigation, Farmnote 34/2004. Department ofAgriculture Western Australia, Perth

Legras S, Lifran R (2006) Designing water markets to manage coupled externalities: a pre-liminary analysis, LAMETA, WP 2006–11, 23 p. Available via: http://www.lameta.univ-montp1.fr/Fr/Productions/Autres.php

McCann L, Easter WK (1999) Transaction costs of policies to reduce agricultural phosphorus pollu-tion in the Minnesota River. Land Econ 75:402–414

Miles MW, Kirk JA, Meldrum DD (2001) Irrigation SIMPACT: a salt load assessment model for newhighland irrigation along the River Murray in SA. Environmental and socio-economic databases.Government of South Australia, Adelaide

Murray Darling Basin Ministerial Council (MDBMC) (1999) The salinity audit of the MurrayDarling Basin – A 100 year perspective. Murray Darling Basin Commission, Canberra

Murray Darling Basin Ministerial Council (MDBMC) (2001) Basin salinity management strategy2001–2015. Murray Darling Basin Commission, Canberra

Quiggin J (2001) Environmental economics of the Murray Darling River System. Aust J AgricResour Econ 45:67–94

Randall A, Taylor MA (2000) Incentive-based solutions to agricultural environmental problems:recent developments in theory and practice. J Agric Appl Econ 32:221–234

Scherer CR (1977) Water allocation and pricing for control of irrigation-related salinity in a RiverBasin. Water Resour Res 13:225–238

Shortle J, Horan RD (2001) The economics of nonpoint pollution control. J Econ Surv 15:255–289Stavins R (2000) Experience with market-based environmental policy instruments, discussion paper

01–58. Resources for the Future, Washington, DCSunraysia Rural Water Authority (2002) Refinement of the river salinity impact zoning system. The

Irrigator 1:6–17Walker G, Doble R, Mech T, Lavis T, Bluml M, MacEwan R, Stenson M, Wang E, Jolly I,

Miles M, McEwan K, Bryan B, Ward J, Rassam D, Connor J, Smith C (2005) Lower Murraylandscape futures phase one report”, CSIRO Publishing. Available via: http://www.clw.csiro.au/publications/consultancy/2005/LMLF_Project_Phase_One_Report.pdf