The impact of water-pricing policy in Spain:
an analysis of three irrigated areas
J. Berbel
a, J.A. GoÂmez-LimoÂn
b,*aDepartment of Agricultural Economics E.T.S.I.A.M. University of CoÂrdoba, Spain bDepartment of Agricultural Economics, E.T.S.II.AA. University of Valladolid,
Adva Madrid 57, 34071 Palencia, Spain
Accepted 2 April 1999
Abstract
Linear programming (LP) has been widely used to solve company resource allocation problems. The technique's ability to predict how companies will adjust to changes in a variety of exogenous factors is well known, and when used at company level, it enables us to avoid aggregation problems. The decision-maker's objective in this type of research is to maximize profit estimated as gross margin. We apply the LP model to three farms in three different irrigation units that, we believe, provide a representative sample of Spanish irrigated agriculture.
In focusing on the goals of this research we stress that water pricing as a single instrument for control of water use is not a valid means of significantly reducing agricultural water consumption. This is because consumption does not fall until prices reach such a level that farm income and agricultural employment are negatively affected. If water pricing is selected as a policy tool, among the consequences for agricultural sector will be that: farm income will decrease by around 40% before water demand decreases significantly. The impact of this reduction on rural areas that are dependent on irrigated agriculture will be catastrophic. Secondly there will be a reduction in the number of crops available for farming, with the consequence of a smaller number of alternatives and greater technical and economic vulnerability of the agricultural sector. Finally when water consumption decreases as a consequence of substitution of crops with higher demands for water (cotton, sugar beet, onions, corn) there will be a significant loss of employment both directly on farms and indirectly on processing facilities.
These conclusions are drawn from our analysis of three irrigation units in Spain, but we believe that they offer a realistic estimate of policy impacts on the irrigated sector of Spanish agriculture. Even if price increases are not a suitable policy because of the high negative impact, we suggest that a price (around 2 PTAs/m3) might be of interest in order to make farmers aware of the scarcity of
* Corresponding author. Tel.: +34-79-729048; fax: +34-79-712099.
E-mail address: limon@iaf.uva.es (J.A. GoÂmez-LimoÂn).
water resources, and to induce them to adopt water-saving technologies without affecting crop distribution. To make water pricing work properly under Spanish conditions, the revenues should be administered by ``Comunidades de Regantes'' for investment in environmental and water-saving activities, while revenues that are not appropriately invested could be transferred to the Regional Water Authority.#2000 Elsevier Science B.V. All rights reserved.
Keywords: Agricultural policy; Irrigated agriculture; Farm models; Environmental economics
1. Introduction
In Spain, irrigated agriculture is responsible for 60% of agricultural production, with only 19% of the cultivated area ± 3.6 million hectares ± consuming 80% of the total water supply. The Mediterranean climate means that the average productivity of irrigated agriculture, according to official 1997 data, is 339 000 PTAs/ha, as against 48 000 PTAs/ ha of non-irrigated land, i.e. a 700% average improvement in productivity when water is available.
The last severe drought (1989±1994) provided dramatic evidence of the scarcity of water resources in Spain, and of the vulnerability of irrigated agriculture to a reduction in water resources. The irrigated area in Spain is 11th in the world ranking and seventh in terms of the per capita ratio of 2.4 ha per person.
Traditionally, irrigation has been used to increase productivity and enable people to settle in rural areas. It is also an instrument for combating desertification. Irrigated agriculture employs 550 000 rural workers with a ratio of 7±8 higher labor input per unit area than non-irrigated land, and agribusiness (canning, frozen vegetables, export horticulture, etc.) depends on the raw materials supplied by irrigated agriculture.
Nevertheless, Spanish irrigation policy is not consistent with the importance of this strategic sector, as 30% of the irrigation infrastructure is more than 200 years old, 70% more than 90 years old and only 27% less than 20 years old. Older irrigation schemes are a historical heritage but losses in the distribution systems are enormous, and the introduction of new technologies (drip, etc.) is very difficult.
Spain's annual consumption of irrigation water is 7225 m3/ha, almost double the average of Mediterranean agriculture, but 40% of irrigation units have a water supply deficit, a situation that underlines the heterogeneity of irrigated agriculture holdings in this country. Moreover, there are a large number of small holdings (85% below 10 ha), resulting in highly extended distribution systems with high losses; 65% of irrigation infrastructures are based upon gravity systems.
2. Legislative framework
Spanish Law defines water as a ``public good'', which means that it cannot be sold in a market. Spanish land is divided among a number of Regional Water Authorities ± watershed management bodies ± (called ``Confederaciones Hidrograficas''), which are
government agencies who assign water to management units ``Comunidades de Regantes'' (CR). These are farmers' associations, which distribute water to the individual members of the irrigation units.
Historically, water resources have been developed by an old system of Government intervention, which has designed reservoirs, distribution systems, etc., and built public works. Not only has public intervention made irrigation possible, but the Government also organizes the CR irrigation units. Farmers pay the costs of distribution, maintenance of infrastructure, control and administration, etc., to their Comunidad de Regantes. This sum is collected by the CR and consists of two parts:
The common cost paid to the Government (called ``canon de riego'') for distributing the water from reservoirs to the CR.
The internal administration and maintenance cost of the CR itself.
This fixed cost is computed by the hectare and implies the annual availability of a maximum amount of water. Psychologically, each farmer tends to believe that he owns the water consumed because he is ``paying for it'', but this is a wrong assumption as he is paying only part of the distribution cost while the water itself is absolutely free.
As a consequence of this physical and socio-economic structure and legislative framework, a large amount of water is used to irrigate Common Agricultural Policy (CAP)-subsidized extensive crops with low productivity and demand for labor. The large amount of losses in the distribution channels, and the high level of water consumption at plot level have also helped to move the political consensus in the direction of modernizing legislation as the first step towards changing this situation.
The national discussion of water policy is also involved in an European discussion about changes in the Common Agricultural Policy orientation, in Agenda 2000, which will alter the orientation of agricultural policy in the direction of a greater emphasis on integrated rural development. Water is now regarded therefore as a resource for rural development rather than as a productive resource as it has been hitherto.
This paper hopes to contribute to this discussion by simulating the impact that a policy based upon price of water could have on agricultural production. Our methodology is based upon a simple linear programming (LP) model capable of analyzing the impact of the price of water through the study of relevant attributes.
3. Methodology and area of study
Our methodology attempts to reflect the viewpoint of the individual farmer as a member of a ``Comunidad de Regantes'' or irrigation unit. LP is a technique based on matrix algebra, and is capable of producing mathematical solutions in terms of maximizing or minimizing some stated objective (Bekene and Winterboer, 1973; Romero and Rehman, 1989). We hypothesize the objective to be the maximization of profit estimated as the gross margin of the farm (LimoÂn and Berbel, 1995; GoÂmez-LimoÂn et al., 1996).
3.1. Model definition
We define a system by means of a mathematical simplification of the variables and their interrelationships in order to understand the effects of modifications of the initial conditions (Patrick and Blake, 1980). Any system has variables that control the process and that belong to the decision-making process as ``decision variables'', e.g. farmer can decide on the level of use of water or the number and distribution of his crops (Bernardo et al., 1987).
The crop plan, therefore, results in changes in certain attributes of the system. Attributes are relevant functions that are deduced from the decision variables, but not all attributes are considered by the decision maker. For example, the demand for labor may be of interest to policy makers but irrelevant for decision makers. The attribute that is assigned a direction of improvement is called the objective function in LP, and in our case this is the gross margin as an estimator of profit.
In this study, we analyze not only the farmer's objectives, but also attributes of relevance to policy makers, as we explain in the following section.
3.1.1. Variables
Each of the three irrigation units discussed has a set of variablesXithat were described in the next section and are defined in Tables 3±5. These are the decision variables that can assume any value of the feasible set. The feasible set is defined by constraints of the system (land, agronomic restrictions, CAP requirements, etc.).
3.1.2. Objective
Our hypothesis is that the farmer wishes to maximize his profits, which is the objective of LP and the system, but this would require the computation of some very difficult concepts such as the general costs, depreciation, etc., that have been assigned to each decision variable, and this is a very subjective and difficult task. Therefore, we assume that the gross margin (GM) is a good estimator of profit (Sumpsi et al., 1997; SaÂnchez et al., 1997), and that the maximization of profit is equivalent to the maximization of gross margin (income less variable costs).
Tables 3±5 show for each decision variable the gross margin that will be incorporated into the decision-making process as the objective function.
GMXGMiXi: (1)
3.1.3. Constraints
3.1.3.1. Total cultivation area. All crops must add up to 100, in order to arrive at
percentages as the outcome of the model.
3.1.3.2. Common agricultural policy. A large proportion of agricultural income depends
asideactivity related to the subsidized crops (which are the majority).
X
XiSA100; (2)
SA>5% cereals; sunflower and legumes: (3)
Durum wheat is also constrained to be less than the historical quota assigned to each farmer, because production of durum wheat outside CAP assigned quota is not competitive against soft wheat in the areas. At regional level, this historical quota is obviously an upper limit.
A similar upper limit is put on the area cultivated for sugar beet, and once again we consider that the area assigned to this crop needs to be less than those planted between 1991/1992 and 1996/1997, because sugar beet cannot economically be produced over the assigned production quota.
3.1.3.3. Market and other constraints. Some of the crops are not subject to CAP rules but
marketing channels put an upper limit on short-term variations in areas planted. Obviously, potatoes, onions and alfalfa, for example, need to be produced in quantities that processing facilities, marketing system or livestock in the vicinity of the production area are capable of handling without price distortions.
We put an upper limit based upon the maximum historical cultivation in the period 1991/1992 to 1996/1997.
3.1.3.4. Rotational and agronomic considerations. It is regarded as a good agricultural
practice not to cultivate a crop such as cereal on the same plot as that which grew another cereal the previous year. This is called a rotational constraint. This limits the cultivated area for a crop to a maximum of 50% of total available area, and applies to all crops except alfalfa, which is treated below.
As alfalfa remains in cultivation for four years, and it is recommended to rest the plot for the following three years, we set up a constraint to respect this agronomic consideration.
X18 Alfalfa m
mnS
4
4310057:14: (4)
All the above information is included in the model on which the LP simulation is based. In Tables 1 and 2 we have included an example of the model for CR Bajo CarrioÂn.
Table 1 shows the value reached by the attributes, i.e. the relevant functions of the system that are interesting for policy making. We merely remark that they are not required to run the LP model (i.e. they are not real constraints). They are used only to calculate the total quantities of the attributes under consideration, as stated below.
3.1.4. Attributes
3.1.4.1. Water consumption. The projected consumption of water, measured in m3/ha, is
the variable that policy makers wish to control via changes in water management policy.
Table 1
LP Model for CR Bajo CarrioÂn (Palencia, Spain)
Decision S.WH S.WH S.WH BAR BAR BAR OAT OAT OAT CORN CORN S.B. S.B. S.B SUN SUN SUN ALF ALF S.A
Variables
Frequency 1 <57.14
Attributes
GM (PTAs/ha) 64 885 24 205 14 205 48 818 29 158 19 328 53 370 33 470 12 670 95 844 70 854 228 638 148 638 ÿ51 362 47 482 34 182 11 822 142 328 100 728 24 373 GM (PTAs/ha)
Water (m3/ha) 2880 1440 0 2880 1440 0 2880 1440 0 7200 5760 4200 3600 3000 2880 1440 0 7200 5760 0 Water (m3/ha)
W. revenue (PTAs/ha)
3.1.4.2. Economic impact. We measure the economic impact of changes in policy by measuring two variables:
agricultural income;
public revenue from water pricing.
3.1.4.3. Social impact. We have mentioned that irrigated agriculture is a principal source
of employment in many rural areas of Spain. For this reason, any change in policy rules will significantly affect the social structure of rural areas.
Labor is therefore computed as the sum of labor for all farming activities, and its attribute function will be as follows:
X
TLiXiTL: (5)
3.1.4.4. Environmental impact. The main environmental impact is water consumption
itself, with the creation of mosaic landscapes and crop diversity and humid areas. In addition to this positive impact, however, there is a rise in the consumption of fertilizers and chemicals that are the main source of non-point pollution in agriculture.
We use fertilizer demand as an indicator of the environmental impact of irrigated agriculture.
The model described above is only suitable for use in the short run, giving the result of the optimal crop plan for the set of farmers. This model was first solved using the current price for water, i.e., 0 PTAs/m3, giving us the quantity of water consumed as an attribute value. The demand curve for water can then be obtained by resolving the same model a number of times, in each case changing the activities' (crops) gross margins for different (hypothetical) water prices. The price of water has thus been parametrized from 0 to 50 PTAs/m3, cutting the gross margin of each crop on the basis of its water requirements. Another possible way to obtain the demand curve for water would be to limit the effective quantity of water available at various levels within a relevant range and to assume that this represents a free input. In this case, the demand curve is derived from the shadow prices of water constraints. We believe that under appropriate formulation of
Table 2
Selected crops by irrigation area
CR BembeÂzar CR Fuente Palmera CR Bajo CarrioÂn
Cotton Cotton Wheat (soft)
Corn Sunflowers Barley
Sunflowers Wheat (soft) Oats
Wheat (soft) Wheat (hard) Sugar beet
Wheat (hard) Sugar beet Corn
Sugar beet Potatoes Sunflowers
Potatoes Set-aside Alfalfa
Onions Set-aside
Set-aside
water constraints and the required adjustments in the activities' gross margin, both options will yield identical demand functions.
Only the first option has been considered for this study due to more of its facility for LP algebra profane people understanding.
3.2. Area of study
We apply the LP model to three farms in three different irrigation units, treating them as a representative sample of Spanish irrigated agriculture. We selected the CRs on the basis of availability of data and our own experience:
1. Comunidad de Regantes BembeÂzar (Sevilla), 2. Comunidad de Regantes Fuente Palmera (Cordoba), 3. Comunidad de Regantes Bajo CarrioÂn (Palencia).
The first unit is located in the Mid-Guadalquivir Valley, and consists of 11 900 irrigated hectares. Most irrigation is by furrow, and is based on a gravity infrastructure. Water is distributed to the plots by perforated polyethylene tubes. Our interest in this unit is as an example of a traditional non-pressurized distribution system, with very high productivity as a consequence of optimal physical conditions.
The second unit is also located in the Mid-Guadalquivir Valley, with 5260 irrigated hectares under pressurized pumped water from the River Guadalquivir. This is a good example of a modern system of sprinklers and drip irrigation. Consumption is lower than in the CR BembeÂzar because pumped water has a significant cost for the farmer (around 9.1 PTAs/m3).
Finally, CR Bajo CarrioÂn, with its 6600 ha, was selected to demonstrate the impact in a Northern region of the country, with less advantageous soil and climate conditions than the Southern examples. The unit is located in the Mid-Duero Valley (Fig. 1). Farms are irrigated by furrow with sprinklers only being used for sugar beet.
3.3. Data acquisition
This research took particular care to gather high-quality data on the technical and economic systems employed by the individual farms. Information was obtained from Government sources (regional and national), Confederaciones Hidrograficas (River Valley Authorities), Comunidades de Regantes and from publications and interviews with local agricultural extension services.
This information was complemented by direct questioning and cost accounting of farms belonging to the irrigation units. We can thus describe the system in terms of the following activities and parameters that describe crops, yields, prices, subsidies and inputs. From this we deduce the relevant attributes of the system: margins, income, variable and fixed costs, employment, consumption, etc.
3.3.1. Crops
We focus on the annual herbaceous crops that represent the largest proportion of irrigated production in the areas of study. As herbaceous crops are the most common
system of production in the area, they can be regarded as good simulators of short-term farmer behavior when water policy is modified. We also include alfalfa because of its significant share of land in some of these areas.
The European Common Agricultural Policy (CAP) obliges farmers who are growing these crops to set aside land if they wish to receive subsidies for agricultural production. Crops available for the farmers' decision-making process vary in each area as a function of farming and physical conditions.
3.3.2. Yields
We wished to give the system as much freedom as possible regarding land and water allocation. For this reason, each activity (crop) was allocated a range of different intensities of water use, giving farmers the opportunity to select various levels of water supply.
Yields, inputs and crop choices were determined by interviews and by questioning farmers from each irrigation unit. The results are shown in Tables 3±5, where we can see that a crop may have different activities (e.g. cotton is represented by four different decision variables or activities). The crop is followed by a number representing thousands of cubic meters of water utilized per hectare. ``Cotton 8'' (X1) means cotton irrigated with 8000 m3, yielding 4500 kg/ha. Similarly, ``Cotton 7'' (X2) estimated a yield of 3950 kg./ha, ``Cotton 6'' (X3) yields 3400 kg/ha and finally ``Cotton 5'' (X4) 2850 kg./ ha, below which level cultivation is not technically viable.
Fig. 1. Location of areas of study.
Table 3
Crop alternatives in CR BembeÂzar
Crop Variable Yield
Sunflowers 2 X15 3333 31.0 62 413 165 736 56 096 109 640 1.3
Sunflowers 1.5 X16 2500 31.0 62 413 139 913 53 602 86 311 0.8
Table 4
Crop alternatives in CR Fuente Palmera
Crop Variable Yield
Sunflowers1.5 X9 2250 31.0 68 654 138 404 61 710 76 694 1.3
Table 5
Crop alternatives in CR Bajo CarrioÂn
Crop Variable Yield
Sunflowers 2.8 X15 2300 30.2 48 262 117 722 70 240 47 482 2.6
Sunflowers 1.4 X16 1800 30.2 48 262 102 622 68 440 34 182 2.2
We also modeled non-irrigated crops such as ``Wheat 0'', (durum and soft) implying standard rain field conditions. Climatic conditions in Spain only permit wheat, barley, oats, and sunflowers to be grown under rain-only water supply.
In this sense it is important to point out that the functions of water used for different crops (especially cotton, sugar beet and corn) estimated by the farmers are almost linear. This suggests that application efficiency does not change with water use for these crops, which is a critical assumption inherent in the analysis. This circumstance has important consequences for the results.
Finally, set-aside is another activity linked to crop planning. Available activities vary for each area from 15 to 22 crops, combined with water supply.
3.3.3. Prices
Prices applied to crops are averages for each area obtained from official statistics and direct questioning.
3.3.4. Subsidies
Subsidies depend upon the European Union's ``Common Agricultural Policy'' (CAP), and were therefore obtained from official publications. We should mention that the northern area, (Bajo CarrioÂn) receives a subsidy of 400 PTAs/Tm for sugar beet.
Some of the subsidies are paid for cotton and sugar beet via industrial processors. They thus entail a higher price paid to the farmer and are included in the price.
3.3.5. Income
Income is an important attribute of the system as it defines total agricultural output. Income is computed by the simple multiplication of yields and prices, plus subsidies when appropriate.
3.3.6. Variable costs
Data were collected from more than 50 farmers from the three irrigation units. We considered 16 categories plus simulated water cost that described as inputs and variable costs.
1. Seeds 2. Fertilisers 3. Chemicals 4. Machinery:
Preparation
Fertilizing
Seeding
Cultivation
Irrigation
Harvesting
Transport
5. Labour 6. Cost of water
Payment to Water Authority
Cost paid to the Comunidad de Regants
Electricity/fuel cost of pumping
Simulated price of water (to be parametrized from 0 to 50 PTAs/m3).
Tables 3±5 summarize total variable costs (when price of water is zero).
3.3.7. Gross margin
The above data enabled us to compute gross margin by means of simple calculations. Gross margin is defined as total income less total variable costs. We use this parameter as the best estimator of profit and thus as the function to be considered as a goal for the LP model.
4. Results
4.1. Water consumption
We optimized the system by maximizing gross margin when price is varied from its present level (zero) to 50 PTAs/m3. The results for each of the three irrigation units are shown in Fig. 2.
This shows a classic demand curve that reflects farmers' adaptation to rising costs of production inputs. We see three different demand curves, which depend upon the local conditions of climate, soil and technical environment. However, we can also discern some similarities that are relevant for policy making and which we want to emphasize.
Fig. 2. Irrigation water demand.
We have divided the demand curve into three segments according to economic and technical characteristics as defined below:
Segment A (inelastic): the farmer makes a very small or zero response to price increases. He thus maintains his existing crop distribution and demand for water.
Segment B (elastic): the farmer responds to price by reducing water consumption. He changes crop plans by growing crops that consume less water, and some non-irrigated crops may even appear in the decision plan.
Segment C (non-efficient): demand is once again inelastic, and there is no response to price increases.
These segments are limited by water price values that differ for each area and that are shown in Table 6 below.
This change in water consumption behavior may be explained by changes in the crop plan, as an adaptation to the rising cost of water. The adaptation pattern may be seen in Table 7.
We can see that segment ``A'' is characterized by crops with high water consumption (cotton, corn, sugar beet), but as the price of water increases, corn is replaced by winter cereals (wheat, etc.) and sunflowers. It should be noted that this inelastic stage is mainly due to the linearity observed above in the estimated production function used to derive the yields.
Segment ``C'' is characterized by the use of water almost exclusively for horticultural crops (onions, potatoes) with the rest of the land growing non-irrigated field crops (dry cereals and sunflower).
Table 6
Demand segments (PTAs/m3)
CR BembeÂzar CR Fuente Palmeraa CR Bajo CarrioÂn
Segment A (inelastic) 0±13 0±6 0±10
Segment B (elastic) 14±26 7±27 11±18
Segment C (inefficient) >26 >27 >18
aCR Fuente Palmera has an additional cost of 9.1 PTAs/m3.
Source: own elaboration.
Table 7
Crop plan by demand segments
Segment CR BembeÂzar CR Fuente Palmera CR Bajo CarrioÂn A Cotton, corn, sugar beet
and vegetables
Cotton, sugar beet and vegetables
Corn, sugar beet and alfalfa; winter cereals
B Cotton and corn reduced; sunflowers and wheat
4.2. Economic impact
Pricing of water results in a serious reduction in farm income, as a result of two factors that operate in the same direction.
Public revenue payment for water implies that income is transferred from the private farming sector to the public sector, in this case for redistribution for environmental works or integrated rural development. However, in the first instance it is a burden to be borne by the farmer.
The farmer responds to price increases by reducing his water consumption through changes in crop plans, introducing less profitable crops as substitutes for more valuable water-demanding crops. This change significantly decreases farmers' incomes.
If we analyze the effects on farm income by describing it in terms of these three demand segments, we can observe some differences in Table 8.
The fall in income is more severe in segment ``A'', with a reduction ranging from 25% (CR Fuente Palmera) to 40% (the two other areas). The income lost in the private sector is transferred directly to the public sector via water revenues because in segment ``A'', crop plans are not modified significantly, and water demand is maintained.
The implications of this finding are relevant for policy-making since, if water pricing is the only instrument for decreasing water consumption, the existence of the primary inelastic segment that does not respond to price rises until it reaches a level of 7±14 PTAs/m3 implies that farm income will fall significantly before it affects water consumption.
Segment B reflects the fact that substitutions and variations in crop plans take place as adaptations to further rises in the price of water, implying that the transfer of income from farming to the public sector is not as direct as in segment ``A'', and any growth in public revenue is slower than in segment ``A'' when crop plans were not modified. In other words, falls in farm income are primarily due to crop substitutions and only secondly due to transfer to public revenue. This segment implies that public revenue should reach a maximum value when farm incomes have fallen by about 75%.
Finally, the behavior of farmers in segment ``C'' suggests that water prices have risen beyond the economic viability of the agricultural systems, and that in consequence, water-price rises to such levels imply simultaneously a reduction in water consumption and a decrease in public revenues, as water consumption falls faster than its price rise.
Segment ``C'' is not efficient from the political and economic point of view as water demand is relatively inelastic, i.e. it does not respond to further price increases, while public-sector revenues fall as the system cannot adapt to this price level.
4.3. Social impact
Pricing of water causes a serious reduction in farm labor since farmers respond to price increases by reducing water consumption through changes in crop plans, introducing less profitable crops to substitute for higher value/higher labor, crops with high water demand. This implies the substitution of water-demanding crops such as cotton in the South and sugar beet in the North by less demanding and more mechanized crops such as cereals and sunflowers. Table 9 summarizes these observations, analyzing them in terms of the three demand-curve segments.
Table 8
Income and public revenue by demand segment
Segment CR BembeÂzar CR Fuente Palmera CR Bajo CarrioÂn
rMB (PTAs/ha) revenue (PTAs/ha) rMB (PTAs/ha) revenue (PTAs/ha) rMB (PTAs/ha) revenue (PTAs/ha)
A 92 205 (42.8%) 99 205 25 756 (24.6%) 10 670 50 350 (43.9%) 50 350
B 64 978 (28.0%) ÿ60 931 17 177 (16.6%) ÿ5 827 20 453 (17.8%) ÿ19 489
C 12 043 (5.2%) ÿ27 685 3 191 (3.1%) ÿ4 843 28 881 (25.2%) ÿ30 905
Total 176 226 (79.6%) 46 124 (44.6%) 99 684 (87.1%)
Values inside parentheses are percentage reductions from initial gross margin. Source: own elaboration.
J.
Berbel,
J.A.
Go
Âmez-Limo
Ân
/
Agricultu
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W
ater
Managem
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(2000)
219±238
Logically, segment ``A'', which is characterized by stability in crop planning, does not see any decrease in labor inputs. However, segment ``B'', which is characterized by crop plan changes, leads to important decreases in labor input. Nevertheless, we may point out different responses in Southern Spain than in Northern Spain, due to the different importance of sugar beet in the two regions.
Obviously the changes in segment ``C'' are even more drastic. We should stress that rural Spain depends on agriculture as its main source of employment, and that a reduction in income as projected by price increases above those of segment ``A'' (i.e. prices beyond 7±14 PTAs/m3) will affect dramatically rural employment.
4.4. Environmental impact
Table 9 in the previous section showed that water pricing leads to a significant reduction in fertilizer use as a result of reduced water consumption through changes in farmers' crop plans, as less productive crops are introduced. Agricultural production is directly related to the most limiting factor in Mediterranean climates, water availability, especially when temperatures and solar radiation are at their highest levels.
Obviously, as farmers substitute crops in order to save water, fertilizer use also decreases, and we should remember that fertilizer use beyond soil capacity when water is not available has a negative impact both on soil structure (salinization) and crop yields. Reduction in the use of fertilizer use starts in segment ``B'' with a reduction of 45% to 60% in the areas of study. This will obviously have a positive impact in the reduction of non-point chemical pollution by agriculture.
Nevertheless, various authors claim that fertilizer efficiency is more dependent on the use of sound fertilizing techniques and sound irrigation practices than on the total amount of fertilizer used. Serious efforts should be put into minimizing the impact of fertilizer through rural extension services and agricultural research.
5. Concluding remarks
An important consideration is that we find that the number of available crops in the areas of study is very small, while almost all crops cultivated by farmers under irrigation
Table 9
Variations in labor and fertilizer
Segment CR BembeÂzar CR Fuente Palmera CR Bajo CarrioÂn
rLabor
Total 10.0 270.0 7.0 127.0 5.7 160.0
Source: own elaboration.
are under CAP control. Cotton in Southern Spain and sugar beet in Northern Spain are the basis for the economic viability of irrigation, and consequently for rural development and subsistence. We suggest that public and private efforts should be put into reducing the heavy dependency of irrigated agriculture (and rural areas) on a very narrow range of crops.
In focusing on the goals of this research we wish to stress that water-pricing as a single instrument for controlling water use is not an appropriate means of significantly reducing agricultural water consumption. This is because consumption is not reduced until prices reach such a level that they negatively affect farm income and agricultural employment. If water pricing is selected as a policy tool, we estimate that among the consequences for the agricultural sector will be:
Economic: farm incomes will decrease by between 25% and 40% before water demand
starts to decrease significantly. The impact of such a reduction on rural areas that depend upon irrigated agriculture will be catastrophic.
Agronomic: there will be a reduction in the range of crops available for farming, with
the consequence of a smaller number of alternative strategies available to the farmer, and a more technically and economically vulnerable agricultural sector.
Social: when water consumption decreases as a result of the substitution of crops with
higher demands (cotton, sugar beet, onions, corn) there will be a significant loss of employment both directly on farms and indirectly at processing facilities.
Environmental: there will be a reduction in fertilizer use, but the environmental impact
of fertilizer use could be significantly reduced in any case by improved agricultural practices, so that it is difficult to determine the direct environmental benefits of pricing water.
These conclusions are drawn from the analysis of limited number of irrigated units in Spain, but we consider that they permit us to make a realistic estimate of potential policy impacts on the irrigated sector of Spanish agriculture.
6. Proposals
From a methodological point of view, we affirm our interest in continuing research into modeling irrigated agriculture, especially when changes in irrigation policy are under discussion. It would be interesting to complement short-term analyses of response with long-term dynamic adaptation models, including analyses of technical change (adoption of water-saving techniques, etc.). Furthermore, in order to construct more realistic models, multicriteria techniques should be adopted in further research on irrigated agriculture.
We have demonstrated that the short-term impact of water pricing will be negative on agriculture and the rural population. Nevertheless, a low price (around 2 PTAs/m3) could be of interest in order to make farmers aware of water resource scarcity, and to induce them to adopt water-saving technologies without affecting their selection of crops.
In order to make water-pricing work properly in Spanish conditions, we suggest that the revenue should be administered by the Comunidades de Regantes. As these
institutions are run by the farmers themselves, their financial resources could be invested in environmental works and water-saving technologies. Only revenues that are not appropriately invested should be transferred to the Regional Water Authority in order to keep the system under control.
Acknowledgements
This research was financed by the ComisioÂn Interministerial de Ciencia y TecnologõÂa under project HID96. The authors wish to thank Hugh Allen for editing the English language in our work, and the FederacioÂn Nacional de Comunidades de Regantes, TEPRO Consultores Agricolas, Pedro Ruiz AvileÂs, Antonio Rodriguez, Ana Salas and Juan JimeÂnez for their technical assistance during the research. The useful comments provided by an anonymous reviewer are also appreciated.
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