an economic analysis of shallow groundwater management for nature conservation and agricultural...

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An Economic Analysisof Shallow GroundwaterManagement for NatureConservation andAgricultural ProductionP. J. G. J. Hellegers , K. Oltmer , E. C. VanIerland & L. C. Van StaalduinenPublished online: 03 Aug 2010.

To cite this article: P. J. G. J. Hellegers , K. Oltmer , E. C. Van Ierland &L. C. Van Staalduinen (2001) An Economic Analysis of Shallow GroundwaterManagement for Nature Conservation and Agricultural Production,Journal of Environmental Planning and Management, 44:4, 545-559, DOI:10.1080/09640560120060957

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Journal of Environmental Planning and Management, 44(4), 545–559, 2001

An Economic Analysis of Shallow GroundwaterManagement for Nature Conservation and AgriculturalProduction

P. J. G. J. HELLEGERS*, K. OLTMER†, E. C. VAN IERLAND‡ &L. C. VAN STAALDUINEN** Department of Public Issues, Agricultural Economics Research Institute (LEI), PO Box29703, 2502 LS The Hague, The Netherlands. Email: [email protected]† Department of Spatial Economics, Free University, De Boelelaan 1105, 1081 HV Amsterdam,The Netherlands‡ Environmental Economics and Natural Resources Group, Wageningen University, PO Box8130, 6700 EW Wageningen, The Netherlands

(Received September 2000; revised March 2001)

ABSTRACT Lowering of shallow groundwater levels in agricultural areas with ecologi-cal value leads to desiccation of ecosystems. The aim of this paper is to develop a modelto study the trade-offs between the agricultural production value and the monetary valueof the ecological bene�ts of agricultural nature management as a result of changes inshallow groundwater levels. It shows that socially optimal groundwater levels depend on:(1) the agricultural production value; (2) the monetary value of nature; (3) the soil typeand vegetation; and (4) the relative share of agricultural area with ecological value intotal agricultural area.

Introduction

In many agricultural areas with special ecological value, agriculture and naturehave competing interests with respect to the management of the shallowgroundwater level. Especially since about 1950 the groundwater level in manyagricultural areas has been lowered, mainly by fast drainage and rapid dischargeof water to create crop cultivation conditions favourable to agriculture. In theNetherlands, ecosystems susceptible to hydrological changes have deteriorated,i.e. become desiccated, which is de�ned as the decline of the value of nature dueto falling groundwater levels. As a result, species adapted to wet and moistenvironments, such as Hottonia palustris (water violet) have disappeared. Thisexternality is not yet fully considered when determining optimal groundwaterlevels in agricultural areas with special ecological value and consequently thoseecosystems are seriously affected. Agriculture may play an important role withrespect to nature management, since farmland often provides a habitat for manyplant species and for birds. There is, however, a lack of insight into the costs ofagricultural production losses and the ecological bene�ts of agricultural naturemanagement caused by higher groundwater levels.

0964-0568 Print/1360-0559 Online/01/040545-15 Ó 2001 University of Newcastle upon TyneDOI: 10.1080/09640560120060957

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546 P. J. G. J. Hellegers, K. Oltmer, E. C. van Ierland & L. C. van Staalduinen

In the Netherlands about 600 000 ha of nature (including agricultural areaswith special ecological value) is desiccated. This is about 17% of the total surfaceof the Netherlands. Policy makers aim to reduce the area of desiccated nature byat least 40% by 2010 compared with the situation in 1985. The structurallowering of the groundwater level is, for 50%, attributed to increased drainagein land consolidation areas, for 30% to extraction of groundwater for public andindustrial purposes and for 20% to other causes, such as increased evapotranspi-ration, changed land use, irrigation and urbanization (Feddes et al., 1999). In thispaper we focus on changes in shallow groundwater levels due to rapid drainage.

Despite the importance of the desiccation problem in the Netherlands, theeconomic literature on modelling this externality has been limited, althoughmuch literature is available on modelling externalities from water management(e.g. Zilberman et al., 1993; Shah et al., 1995a, b). However, most of these studiesare concerned with water scarcity problems and the allocation of groundwaterbetween different users (e.g. Howitt & Lund, 1999) or with environmentalproblems due to the disposal of agricultural drainage water (e.g. Shah &Zilberman, 1991). Only a few studies focus on the valuation of ecological bene�tsresulting from changes in agricultural water management (e.g. Loomis et al.,1991; Cooper & Loomis, 1993).

It is important to note that the setting of the problem is for the case of therapid drainage of shallow groundwater within the estuarine areas of the riversRhine, Meuse and Scheldt. This implies that we are dealing not with competitionfor scarce groundwater from deep aquifers, but with competing interests withrespect to shallow groundwater levels due to rapid drainage.

The main aim of this paper is to develop a model to analyse the trade-offbetween agricultural production values and the monetary value of ecologicalbene�ts of agricultural nature management as a result of changes in thegroundwater level. A comparative static economic analysis is used to compareannual losses to agriculture and annual gains to nature resulting from a shiftfrom privately to socially optimal groundwater levels. The consideration ofmonetary values for both foregone agricultural production and ecologicalbene�ts introduces an intersectoral trade-off in the optimization problem. Atten-tion will be paid to the potential role of economic incentives as a tool to achievesocially optimal groundwater levels. Moreover, the model will be applied to astudy area in the Netherlands.

The structure of the paper is as follows. The next section explains thetheoretical model developed to analyse the intersectoral trade-off. Then the dataand estimation procedure are described. The following section shows the resultsof the empirical analysis in the study area, which serves as an illustration of ourmodel. Insight is provided into the discrepancy between the privately andsocially optimal situation. The �nal section contains the main conclusions.

Theoretical Model

In the Netherlands crop growth and nature development both depend on theaverage shallow groundwater level in spring. The relationship is indirect,because crop growth and nature development are actually dependent on theavailability of soil moisture, which in turn is determined by shallow ground-water levels through capillary rise. Other factors, such as salinity, nutrient avail-

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An Economic Analysis of Shallow Groundwater Management 547

ability and acidity, also have an in�uence on crop yield and ecosystems. Highergroundwater levels recover nature, but may cause wet damage to agriculture.

Our model analyses the shift from the groundwater level that maximizes theobjective function of a private planner to the groundwater level that maximizesthe objective function of a social planner. The groundwater level relative to soilsurface is the decision variable. The optimal groundwater level of the privateplanner is obtained by maximization of the agricultural production value(equation (1)). The optimal groundwater level of the social planner is obtainedby maximization of the sum of the agricultural production value and themonetary value of ecological bene�ts of agricultural nature management (equa-tion (2)), which is based on a nature index (N) and an annual monetary value ofnature (V). Crop yields and the nature index both depend on the groundwaterlevel (equations (3) and (4)). The nature index measures ecological bene�ts ofagricultural nature management:

Max Oi 5 m

i 5 1YiPiAi (1)

Max ( Oi 5 m

i 5 1(YiPiAi) 1 NVAn) (2)

subject to:

Yi 5 fi(D) (f is inverted U shape) (3)

N 5 g(D) (g 9 , 0 and g 0 . 0, i.e. g is decreasing and convex) (4)

where

Yi 5 yield of crop i (tonnes/ha), for i 5 1, …, m;

Pi 5 price of crop i ( /tonne), for i 5 1, …, m;

Ai 5 area of crop i (ha), for i 5 1, …, m (total agricultural area A 5 Oi 5 m

i 5 1Ai);

N 5 nature index;

V 5 annual monetary value of nature for N 5 1 ( /ha);

An 5 area of agriculture with specific ecological values (ha) (with An P A);

D 5 average groundwater level in spring (centimetres below soil surface).

Fixed agricultural costs (such as sowing costs) remain constant and need notbe taken into account explicitly in the optimization. Variable agriculture costs(such as harvesting costs) are affected by the groundwater level, but changes infarm management practices will reduce these costs. In a more elaborate studythese costs could easily be introduced into the analysis, but they will hardlyaffect results. Costs of measures to raise the groundwater level are also notrelevant, because it concerns differential tuning of existing installations, whichcan be done at zero cost.

The following steps are taken to implement the model. The relationshipsbetween crop yields and groundwater level (equation (3)) have been estimated(step (a)) to calculate agriculturally optimal groundwater levels (equation (1))(step (b)). The relationship between the nature index and groundwater level(equation (4)) has been estimated and the monetary value of nature is derived(step (c)) to calculate the socially optimal groundwater level (equation (2)) (step(d)). Finally, the sensitivity of the results to various values of three parametersis studied (step (e)).

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(a) Relationships between Crop Yields and Groundwater Level

The agronomic relationship between crop yields and groundwater level is aninverted U shape, because there is yield depression if the groundwater level iseither too high or too low, with the optimum somewhere in between. In the �rstcase, the availability of air and oxygen in the soil, the nitrogen supply and thesoil temperature are suboptimal. In the second case, water supply might beinsuf�cient to guarantee optimal crop growth (van der Schaaf & Witte, 1997).The quadratic (equation (5)) and cubic function (equation (6)) re�ect a parabolicshape; b 0, b 1, b 2 and b 3 are crop-speci�c parameters. The use of other inputs, suchas fertilizer, is assumed to be constant and their impact is re�ected in theconstant b 0 of the production function:

Yi 5 b 0 1 b 1D 1 b 2D2 (5)

Yi 5 b 0 1 b 1D 1 b 2D2 1 b 3D3 (6)

(b) Agriculturally Optimal Groundwater Level

The privately optimal groundwater level for agriculture can be calculated bysetting the �rst derivative of the agricultural production value with respect tothe groundwater level equal to zero (equation (7)). The agricultural productionvalue is the sum of the production values of various crops, which can becalculated by multiplying crop yields, prices and areas:

d S Oi 5 m

i 5 1YiPiAiD

D5 0 (7)

(c) Relationship between the Nature Index and Groundwater Level

Beusekom et al. (1990) show that conservation values of plant species declineexponentially with falling groundwater levels. More recently, an attempt torelate water management to the value of nature has been made by Witte (1998).Both studies show that the relationship between the value of nature and thegroundwater level depends on the soil type and the composition of the veg-etation. In comparison with a sandy soil, the capillary rise in a loamy soil is moreintense. Accordingly, damage to nature due to falling groundwater levels ismore severe on sandy than on loamy soils. Changes in the groundwater levelalso have a larger impact on the value of vegetation with many ‘wet species’than on vegetation with many ‘dry species’. The nature index re�ects therelationship between the conservation value of ecological bene�ts and ground-water level. The steepness of the nature index (S) depends on the soil type andthe composition of the vegetation. The nature index is estimated for an exponen-tial function with a constant term ( a ) on the basis of observations derived fromrelationships presented by Beusekom et al. (1990) (equation (8)). These relation-ships are commonly accepted in the Netherlands:

N 5 a eSD (8)

In order to calculate the monetary value of the ecological bene�ts, the natureindex is multiplied by an annual monetary value of nature per hectare for anature index equal to 1.

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(d) Socially Optimal Groundwater Level

The social optimum can be derived by equalizing the absolute values of the �rstderivatives of the agricultural production value and the ecological bene�ts of theagricultural nature management function with respect to the groundwater level(equation (9)):

) S Oi 5 m

i 5 1YiPiAiD

D) 5 U (NVAn)

DU (9)

According to the neo-Paretian criterion, there are allocation pro�ts, if theabsolute value of gains to nature (i.e. change in the groundwater level from D*to D**) exceeds the absolute value of losses to agriculture (equation (10)).Winners are able to compensate losers if the following condition is ful�lled:

u g(D**)VAn 2 g(D*)VAn u . U Oi 5 m

i 5 1fi(D**)PiAi 2 Oi 5 m

i 5 1fi(D*)PiAi U (10)

(e) Sensitivity Analysis

The results of the model depend particularly on the characteristics of the natureindex and the annual monetary valuation of nature. In order to analyse theimpact on the results, the sensitivity to various values of the following threeparameters is assessed. Firstly, the effect of another soil type and composition ofthe vegetation on the results is studied. Secondly, the extent to which differentannual monetary values of nature (V) in�uence the results is tested. Finally,the impact of changes in the relative share of agricultural area with specialecological value in relation to total agricultural area will be investigated (An/A).

Data and Estimation

The model was applied in an empirical analysis to a desiccated study area. TheEastern Cattle Area in the Netherlands (see Figure 1) was chosen becauseagriculture and nature are obviously competing with respect to the shallowgroundwater level in this area.

The main agricultural activities in the Eastern Cattle Area are dairy farmingand cattle breeding. The total area comprises 300 000 ha and consists mainly ofsandy podzol soil. The crops considered in the analysis are grassland, maize,potatoes, sugar beet and grain. The cropping pattern, crop yields and crop pricesare shown in Table 1. These crop yields are assumed to be maximum yields,because we suppose that they are harvested at agriculturally optimal ground-water levels. This seems reasonable to assume, since in the second half of the20th century groundwater levels were lowered to create favourable cultivationconditions.

The relationships between crop yields and groundwater level for �ve cropsare estimated for quadratic and cubic functional forms. The ordinary least-squares method is used. The data for the regression analysis, describing theimpact of the groundwater level on physical yields of the various crops, arederived from depression percentages of the yield depression tables for sandypodzol soil developed by Werkgroep HELP (1987). These tables are commonly

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Figure 1. Location of the Eastern Cattle Area in the Netherlands. Scale: 1:3 300 000.

Table 1. Cropping pattern, physical crop yields and prices for the Eastern CattleArea in 1992

Grass Maize Potatoes Sugar beet Grain

Cropping pattern (%) 60 25 5 5 5Physical crop yields (tonnes/ha) 61.3 43.0 46.0 60.9 4.6Price ( /tonne) 21.2 38.7 52.1 45.1 208.7

Source: Agricultural Economics Research Institute (LEI) Dutch Farm Accountancy Data Network, whichis based on a representative sample of farms.

used to determine changes in crop yields due to land consolidation projects. Adescription of the derivation of the data is given in the Appendix of the presentpaper. The regression is based on observations of crop yields for groundwaterlevels varying between 10 cm and 260 cm below soil surface, with an interval of5 cm. Statistics of the data are shown in Table 2.

The observations, describing the impact of groundwater levels on the conser-vation value, are derived from vegetation- and soil-speci�c relationships pre-sented by Beusekom et al. (1990). Two sets of observations have been used toshow the sensitivity of the results to another soil type and composition of thevegetation. The �rst set of observations relates to vegetation with many ‘dryspecies’ on loamy soils. The second set of observations relates to vegetation withmany ‘wet species’ on sandy soils. For both sets of observations the �rst damage

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Table 2. The mean, standard error of the mean and standard deviation of the data


Mean of crop yields (tonnes/ha) 54.2 37.1 38.8 53.7 4.0Standard error of mean 0.76 0.57 0.70 0.70 0.06Standard deviation of crop yields 5.5 4.1 5.0 5.0 0.4

Source: Based on 51 observations derived from the depression tables of Werkgroep HELP (1987).

to nature can be observed if the average groundwater level in spring becomeslower than 20 cm below soil surface. For the �rst set of observations, half thetotal value of nature is lost (N 5 0.5) at a groundwater level of 90 cm below thesoil surface. Only one-quarter remains (N 5 0.25) at 160 cm. For the second set ofobservations, half the total value of nature is lost (N 5 0.5) at 55 cm below thesoil surface and only one-quarter remains (N 5 0.25) at 90 cm. This means thatvegetation with many ‘wet species’ on sandy soils is more sensitive to lowergroundwater levels than is vegetation with many ‘dry species’ on loamy soils.

Monetary valuation of nature is not easy to establish because many of thegoods and services provided are not marketed. Several techniques for theeconomic valuation of nature have been developed (e.g. the contingent valuationmethod, the travel cost method and the hedonic pricing method). Studies showdifferent monetary values of nature, which vary within a wide range (seeCostanza et al., 1998). Public bene�ts of agricultural nature management onDutch peat meadow land were estimated by means of the contingent valuationmethod by Brouwer & Slangen (1997), who found a value of about 1600/ha.Since this value is derived for peat soil instead of sandy podzol soil, bene�ttransfer is questionable. However, because of the lack of a more accurateestimation, we use 1600/ha for the monetary value of nature (V) as abenchmark in our analysis and assess the sensitivity of the results to anothermonetary value of nature, namely 1000/ha.

Finally, we assume that the size of the agricultural area with special ecologicalvalue is one-quarter of the total agricultural area in our study area, because20–25% of total agricultural land has special ecological values in the Netherlands(Slangen, 1992). We use this share as a kind of reference. The impact of changesin this share on the results is assessed in a sensitivity analysis.

Results

The observations and the estimated quadratic and cubic functions are shown inFigure 2 for the yield of grass. The cubic form describes the observed data betterthan does the quadratic form, especially for the domain we focus on in ouranalysis. A theoretical disadvantage of the cubic form is that multiple optima arepossible, but this is no problem for the domain analysed. It is interesting to notethat the negative impact of wet damage on crop yield is larger than the negativeimpact of drought damage (the left part of the curve is steeper than the rightpart).

On the basis of the graphic representation and the signi�cance of the valuesof all estimated parameters and the values of the adjusted R2, which are higher

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Figure 2. Observed and estimated relationship between the annual yield of grassand groundwater level.

Table 3. Estimation results of the relationship between annual crop yields andgroundwater level for the cubic functional form (with the t-values in parentheses)

Parameter b 0 b 1 b 2 b 3 Adjusted R2

Grass 47 503.236 (70.62) 395.996 (18.93) 2 3.380 ( 2 19.06) 0.007 (16.50) 0.97Maize 27 228.796 (64.37) 410.222 (31.19) 2 3.271 ( 2 29.33) 0.007 (25.18) 0.98Potatoes 28 822.508 (62.65) 456.818 (31.93) 2 3.733 ( 2 30.78) 0.008 (26.58) 0.98Sugar beet 38 936.056 (65.07) 556.699 (29.92) 2 4.319 ( 2 27.38) 0.009 (23.33) 0.97Grain 2 884.929 (75.36) 44.129 (37.07) 2 0.344 ( 2 34.06) 0.0007 (28.77) 0.98

Table 4. Optimal groundwater levels (centimetres below soil surface) and relatedmaximum yield of cubic functions


Optimal groundwater level (cm) 75.3 89.2 83.7 89.5 87.5Maximum yield (tonnes/ha) 61.0 42.9 45.6 60.6 4.6

for the cubic than for the quadratic functions, we preferred the cubic to thequadratic functional form. Estimation results of the cubic functional form for the�ve crops are shown in Table 3. Optimal groundwater levels and related yieldsof the cubic functions are shown in Table 4.

Figure 3 shows that no changes in cropping pattern could be expected in theanalysis as a result of adjustments in the groundwater level, at prices for 1992.The gross production value per hectare of a certain crop will not become higheror lower than that of another crop if the groundwater level changes, as isillustrated by the fact that curves do not intersect. Gross production values ofcrops might, however, change when agricultural product prices change andchanges in groundwater levels might affect cropping patterns in that case.

The relationship between the agricultural production value and groundwaterlevel (equation (11)) is derived by regression of calculated agricultural pro-

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Figure 3. Relationship between gross production values and groundwater level, atprices for 1992.

duction values on the groundwater level. The agricultural production value(APV in /ha) is speci�ed as follows:

APV 5 1063.569 1 11.942D 2 0.098D2 1 0.0002D3 (11)

The relationship between the nature index and groundwater level (equation (8))is estimated. For vegetation with many ‘dry species’ on loamy soils, a 5 1.22 andS 5 2 1, whereas for vegetation with many ‘wet species’ on sandy soils, a 5 1.49and S 5 2 2. The negative value of S shows that the monetary value of ecologicalbene�ts declines with falling groundwater levels.

The agricultural production value and the monetary value of ecologicalbene�ts of 4 ha of farmland, both as a function of the groundwater level, arepresented in Figure 4. The social value is the sum of the agricultural productionvalue of these 4 ha and the value of ecological bene�ts of 1 ha of the 4 ha, sinceonly one-quarter has ecological value.

The agriculturally optimal groundwater level is 81 cm below soil surface. Theassociated agriculturally optimal production value is 1494.2/ha, which isequivalent to 5976.7 for 4 ha (see point A in Figure 4). At the agriculturallyoptimal groundwater level, the monetary value of ecological bene�ts is 868.8(see point B). Figure 4 shows that there will be losses to agriculture and natureif groundwater levels are deeper than the agricultural optimum, which is notattractive for either interest. If groundwater levels are less deep than theagricultural optimum, there will be losses to agriculture, but gains to nature.

The socially optimal groundwater level is 56.6 cm below soil surface. Theassociated socially optimal value is 6956.6 (see point C in Figure 4), of which

5846.7 is for agriculture and 1109.9 for nature. Annual agricultural lossesresulting from the shift from a private to a social optimum are 130 for 4 ha andannual gains to nature are 241.1.

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Figure 4. The social value, agricultural production value and value of ecologicalbene�ts (for V 5 1600 and vegetation with many ‘dry species’ on loamy soils) of

4 ha of farmland.

At the agriculturally optimal groundwater level of 81 cm the social value of 4ha of farmland is 6845.5 (see point D). At a groundwater level of 33.8 cm, thesame social value could be achieved (see point E). It becomes clear that thedistribution of welfare between agriculture and nature can be different for thesame social value. Any groundwater level between 33.8 and 81 cm increases thesocial value compared with the agricultural optimum. Within this range theabsolute value of gains to nature exceeds the absolute value of losses toagriculture (equation (10)) and there are allocation pro�ts according to theneo-Paretian criterion. The winners are able to compensate the losers and thetwo parties may negotiate a compensating transfer. Whether real compensationhas to be paid depends on the assignment of well de�ned rights to lowergroundwater levels, reaching agreement and policy decisions.

At the social optimum the annual marginal losses and gains to agriculture andnature from changing the groundwater level by 1 cm at that point (equation (9))are 11.1 (see point A in Figure 5). If the social planner were to introduce acharge system, the size of these annual marginal losses and gains gives anindication of the level of charges farmers would have to face to restrain themfrom lowering the groundwater level by 1 cm. The annual charges farmerswould have to face to restrain them from lowering the groundwater level froma social to a private optimum (by 24.4 cm) would have to be at least equal to thepotential annual gains to agriculture. In our case-study these annual gainsamount to 130 for 4 ha.

Theoretically, charges could be used as a tool to achieve the social optimum.In practice, it would be complicated for the following reasons. First, location-speci�c circumstances should be taken into account. Secondly, groups of farmerswill be affected by a change in the groundwater level and this makes it dif�cultto apply a tax system. Thirdly, tax revenues will be small compared withtransaction costs. Finally, farmers seem to be risk-averse with respect to wet

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Figure 5. First derivative of agricultural production value function and value ofecological bene�ts function.

damage and the impact of a charge on water demand seems to be small belowa certain level.

The impact of another soil type and composition of the vegetation and ofanother annual monetary value of nature on socially optimal outcomes is shownin Table 5. Socially optimal groundwater levels vary in the sensitivity analysisbetween 66.4 cm and 31.6 cm below the soil surface. Annual agricultural lossesresulting from the shift from a private to a social optimum vary between 44.7and 578.4 for 4 ha. This is 0.7–9.7% of the agricultural optimum productionvalue. Annual gains to nature resulting from this shift range between 85.5 and

796. The increase in social value varies between 40.8 and 217.6 for 4 ha.

Table 5. Results of the sensitivity analysis of the impact of another soil type andvegetation and of another annual monetary value of nature on socially optimaloutcomes (annual values ( ) for 4 ha of farmland; 1 ha of these 4 ha of farmland

also has ecological value)

Loamy Loamy Sandy SandySoil type and soil, ‘dry soil, ‘dry soil, ‘wet soil, ‘wetcomposition of the vegetation species’ species’ species’ species’

Annual monetary value of nature (V) 1600 1000 1600 1000

Optimal groundwater level 56.6 66.4 31.6 61.2(centimetres below soil surface)Agricultural production value 5846.7 5932.0 5398.3 5892.9Value of ecological bene�ts 1109.9 628.5 1267.8 438.4Social value 6956.6 6560.5 6666.1 6331.3Losses to agriculturea 130.0 44.7 578.4 83.8Gains to naturea 241.1 85.5 796.0 143.6Marginal losses/gains per centimetreb 11.1 6.3 25.4 8.8

a Losses and gains in the social optimum compared with the agricultural optimum.b Marginal losses and gains in the social optimum from changing the groundwater level by 1 cm.

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Figure 6. Impact of changes in the relative share of agricultural area with specialecological value to total agricultural area (An/A) on the socially optimal

groundwater level.

Figure 6 shows the results of the sensitivity analysis performed to analyse theimpact of changes in the ratio of agricultural area with special ecological valueto total agricultural area (An/A) on the socially optimal groundwater level. Weuse a constant monetary value of nature (V), although this value will vary withthe size of area with nature. We should expect diminishing marginal returns tonature. In our analysis a lower monetary value of nature has a similar impact onsocially optimal groundwater levels as a decrease in the relative share of areawith special ecological value. In order to isolate the impact of changes in therelative share of area with ecological bene�ts, we use a constant monetary valueof nature. Figure 6 shows that the relative share of area with ecological value isimportant for the socially optimal groundwater level. If all agricultural areashave special ecological value, the groundwater level will be fully attuned tonature (20 cm below the soil surface). Agricultural losses will be 15% of theagricultural optimum production value in that case.

Conclusions

In this paper a model is developed to analyse the intersectoral trade-off betweenagricultural production values and the monetary value of ecological bene�ts asa result of changes in the groundwater level. Insight is provided into the gainsand losses to nature and agriculture resulting from a shift from privately tosocially optimal groundwater levels. This model has been illustrated by anempirical analysis in a study area, which identi�es existing gaps in knowledge.Although results are illustrative, some general conclusions can be drawn.

The study shows that agricultural production losses for achieving the sociallyoptimal groundwater level are higher for vegetation with many ‘wet species’ onsandy soils than for vegetation with many ‘dry species’ on loamy soils. Also,losses will increase if society attaches a higher annual monetary value to natureand if the relative share of agricultural areas with special ecological value in thetotal agricultural area becomes larger. The study also shows that agricultural wetdamage losses are more serious than drought damage losses.

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Theoretically, charges on lowering the groundwater level could be used as atool to achieve the social optimum, although in practice it would be complicated.Compensating payments could be used to redistribute welfare—the costs andbene�ts—between the affected parties.

Finally, we should like to note that insight into losses and gains to agricultureand nature can support policy decisions about the introduction of economicincentives or other policy instruments into water management to recover desic-cated ecosystems in agricultural areas.

Acknowledgements

The authors would like to thank Peter Nijkamp, Flip Witte and David Zilber-man, and two anonymous reviewers for their valuable comments.

References

Beusekom, C.F. van, Farjon, J.M.J., Foekema, F., Lammers, B., Molenaar, J.G. de & Zeeman, W.P.C.(1990) Handbook of Groundwater Management for Nature, Wood and Landscape (The Hague, SDU) (inDutch).

Brouwer, R. & Slangen, L.H.G. (1997) Contingent valuation of the public bene�ts of agriculturalwildlife management: the case of Dutch peat meadow land, European Review of AgriculturalEconomics, 25, pp. 53–72.

Cooper, J. & Loomis, J. (1993) Testing whether waterfowl hunting bene�ts increase with greaterwater deliveries to wetlands, Environmental and Resource Economics, 3, pp. 545–561.

Costanza, R., d’Arge, T., Groot, R. de, Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S.,O’Neill, R.V., Paruelo, J., Raskin, R.G., Sutton, P. & Belt, M. van den (1998) The value of theworld’s ecosystem services and natural capital, Ecological Economics, 25, pp. 3–15.

Feddes, R.A., Koopmans, R.W.R. & Dam, J.C. van (1999) Agrohydrology (Wageningen, WageningenUniversity).

Howitt, R.E. & Lund, J.R. (1999) Measuring the economic impact of environmental reallocations ofwater in California, American Journal of Agricultural Economics, 81, pp. 1268–1272.

Loomis, J., Hanemann, M., Kanninen, B. & Wegge, T. (1991) Willingness to pay to protect wetlandsand reduce wildlife contamination from agricultural drainage, in: A. Dinar & D. Zilberman (Eds)The Economics and Management of Water and Drainage in Agriculture (Dordrecht, Kluwer).

Oltmer, K. (1999) Economic Instruments in Water Management and Desiccation in the Netherlands, Report2.99.05 (The Hague, LEI).

Schaaf, S. van der & Witte, J.P.M. (1997) Introduction to Landscape Hydrology (Wageningen, Wagenin-gen University).

Shah, F. & Zilberman, D (1991) Government policies to improve intertemporal allocation of water inregions with drainage problems, in: A. Dinar & D. Zilberman (Eds) The Economics and Managementof Water and Drainage in Agriculture (Dordrecht, Kluwer).

Shah, F., Zilberman, D. & Chakravorty, U. (1995a) Technology adoption in the presence of anexhaustible resource: the case of groundwater extraction, American Journal of Agricultural Economics,77, pp. 291–299.

Shah, F., Zilberman, D. & Lichtenberg, E. (1995b) Optimal combination of pollution prevention andabatement policies: the case of agricultural drainage, Environmental and Resource Economics, 5,pp. 29–49.

Slangen, L.H.G. (1992) Policies for nature and landscape conservation in Dutch agriculture: anevaluation of objectives, means, effects and programme costs, European Review of AgriculturalEconomics, 19, pp. 331–350.

Werkgroep HELP (1987) The Impact of Water Management on Agricultural Production (Utrecht,Mededelingen Landinrichtingsdienst 176) (in Dutch).

Witte, J.P.M. (1998) National Water Management and the Value of Nature, Unpublished PhD Thesis(Wageningen, Wageningen University).

Zilberman, D., Wetzstein, M. & Marra, M. (1993) The economics of nonrenewable and renewableresources, in: G. Carlson, D. Zilberman & J. Miranowski (Eds) Agricultural and EnvironmentalResource Economics (New York, Oxford University Press).

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Appendix

The data for the regression analysis, describing the impact of the groundwater level on the physicalyield of grass and arable crops, are derived from HELP code H2b, number 61 of depression tablesG7 and B7 for sandy podzol soil developed by Werkgroep HELP (1987). These tables show wet anddrought damage depression percentages for various groundwater levels. Depression percentages aresoil-speci�c and are given for grassland as well as arable land. The drought depression percentagesfor arable land are based on a weighted average of a certain cropping pattern. Drought depressionsfor the different arable crops can be derived from the average yield depressions of arable land onthe basis of given crop- and soil-speci�c formulas (Werkgroep HELP, 1987, table 8). Since precipi-tation and evaporation vary by district, correction factors have to be used to adjust yield depression�gures by district (Werkgroep HELP, 1987). Only those factors which lead to a decrease in netproduction are considered in the depressions of the HELP tables. The depressions are based onprecipitation and evaporation patterns over a period of 30 years. The depressions hold as an averagefor a number of years. The impact of weather effects (from year to year and within years) is thereforeconsidered implicitly in the analysis. Depressions are based on hydrological model simulations, �eldexperiments and expert judgements.

Our regression is based on 51 observations of crop yields for groundwater levels varying between10 cm and 260 cm below the soil surface, with an interval of 5 cm. These yields are calculated withthe help of the depression percentages presented in Table A1, which are derived from the depressiontables developed by Werkgroep HELP (1987). Physical crop yields presented in Table 1 are assumedto be maximum values of crop yields, since we suppose that they are harvested at agriculturallyoptimal groundwater levels. The optimal groundwater level for grassland is 60 cm below the soilsurface and for arable crops it is 100 cm below the soil surface (there is no depression in that case:see Table A1). In order to obtain a complete data set (51 observations for each crop), depressionpercentages that cannot be attained by means of the depression tables are calculated by linearinterpolation. The complete data set used for the estimation is presented in Oltmer (1999, appendixC).

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Tab

leA

1.Y

ield

dep

ress

ion

per

cen

tage

s(m

inim

um

and

max

imu

mcr

opyi

eld

s( Y

)(to

nnes

/ha

)in

1992

inp

aren

thes

es)

Yie

ldd

epre

ssio

n(%

)a

Gro

und

wat

erM

aize

dPo

tato

esd

Suga

rbe

etd

Gra

ind

leve

l(cm

)G

rass

land

bA

rabl

ela

ndc

Z5

XZ

51.

15X

10.

5Z

50.

85X

20.

5Z

51.

05X

22.

5

1021

3131

( Y5

29.7

)31

( Y5

31.7

)31

( Y5

42.0

)31

( Y5

3.2)

1517

2727

2727

2720

—23

2323

2323

2510

1515

1515

1530

5—

——

——

352

99

99

950

06

66

66

600

( Y5

61.3

)2

22

22

701

——

——

—75

1—

——

——

100

—0

0( Y

543

.0)

0( Y

546

.0)

0( Y

560

.9)

0( Y

54.

6)10

53

X5

4Z

54

Z5

5.1

Z5

2.9

Z5

1.7

110

4X

54

Z5

4Z

55.

1Z

52.

9Z

51.

714

08

X5

9Z

59

Z5

10.8

5Z

57.

15Z

56.

9515

010

X5

12Z

512

Z5

14.3

Z5

9.7

Z5

10.1

170

15X

516

Z5

16Z

518

.9Z

513

.1Z

514

.320

021

X5

23Z

523

Z5

26.9

5Z

519

.05

Z5

21.6

526

025

( Y5

46.0

)X

526

Z5

26Z

530

.4Z

521

.6Z

524

.8

aSi

nce

prec

ipit

atio

nan

dev

apor

atio

nin

the

stud

yar

eaar

eco

mpa

rabl

ew

ithpr

ecip

itati

onan

dev

apor

atio

nin

the

refe

renc

edi

stri

ct,

the

yiel

dde

pres

sion

sdo

not

need

tobe

corr

ecte

d(W

erkg

roep

HEL

P,19

87).

bD

epre

ssio

nsof

tabl

eG

7fo

rsa

ndy

podz

olso

il,H

ELP

cod

eH

2b,n

umbe

r61

(Wer

kgro

epH

ELP,

1987

).cD

epre

ssio

nsof

tabl

eB7

for

sand

ypo

dzol

soil,

HEL

Pco

deH

2b,n

umbe

r61

(Wer

kgro

epH

ELP,

1987

).d

Dro

ught

depr

essi

ons

( Z)f

orth

edi

ffer

enta

rabl

ecr

ops

are

der

ived

from

the

aver

age

yiel

dde

pres

sion

sof

arab

lela

nd( X

)on

the

basi

sof

give

ncr

op-

and

soil-

spec

i�c

form

ulas

(Wer

kgro

epH

ELP,

1987

,tab

le8)

.The

dep

ress

ions

for

mai

zeon

sand

yso

ilsar

eta

ken

asa

refe

renc

ean

dd

ono

tha

veto

bem

odi�

ed.

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an economic analysis of shallow groundwater management for nature conservation and agricultural...

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