Directory UMM :Data Elmu:jurnal:A:Agricultural Water Management:Vol43.Issue2.Mar2000:
Agricultural Water Management 43 (2000) 219±238
The impact of water-pricing policy in Spain:
an analysis of three irrigated areas
J. Berbela, J.A. GoÂmez-LimoÂnb,*
a
Department of Agricultural Economics E.T.S.I.A.M. University of CoÂrdoba, Spain
b
Department 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: [email protected] (J.A. GoÂmez-LimoÂn).
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 5 6 - 6
220
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
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
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
221
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 (GoÂmez-LimoÂn and Berbel, 1995; GoÂmezLimoÂn et al., 1996).
222
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
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 variables Xi that 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.
X
(1)
GM
GMi Xi :
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
upon CAP subsidies, and farmers cannot survive outside CAP rules that affect most of the
crops available for cultivation. Therefore, following CAP rules, we should include set
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
aside activity related to the subsidized crops (which are the majority).
X
Xi SA 100;
SA > 5% cereals; sunflower and legumes:
223
(2)
(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
4
S
100 57:14:
mn
43
(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.
224
Table 1
LP Model for CR Bajo CarrioÂn (Palencia, Spain)
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
2.8
1.4
0
2.8
1.4
0
2.8
1.4
0
7.2
5.7
4.2
3.6
3
2.8
1.4
0
7.2
5.7
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
X19
S.A
SA
Objective
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 Max
Constraints
Land
CAP 1
CAP 2
1
ÿ0.05
ÿ0.5
1
1
1
1
1
1
CAP 3
Market 1
Rotation 1
Rotation 2
Rotation 3
Frequency 1
Attributes
GM (PTAs/ha)
Water (m3/ha)
W. revenue
(PTAs/ha)
Direct labor
(Days/ha)
Fertilizer
(N.F.U./ha)
Water price
(PTAs/m3)
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
ÿ0.05
1
1
ÿ0.05
1
1
ÿ0.05
1
1
1
1
1
1
1
ÿ0.5
The impact of water-pricing policy in Spain:
an analysis of three irrigated areas
J. Berbela, J.A. GoÂmez-LimoÂnb,*
a
Department of Agricultural Economics E.T.S.I.A.M. University of CoÂrdoba, Spain
b
Department 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: [email protected] (J.A. GoÂmez-LimoÂn).
0378-3774/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S 0 3 7 8 - 3 7 7 4 ( 9 9 ) 0 0 0 5 6 - 6
220
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
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
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
221
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 (GoÂmez-LimoÂn and Berbel, 1995; GoÂmezLimoÂn et al., 1996).
222
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
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 variables Xi that 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.
X
(1)
GM
GMi Xi :
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
upon CAP subsidies, and farmers cannot survive outside CAP rules that affect most of the
crops available for cultivation. Therefore, following CAP rules, we should include set
J. Berbel, J.A. GoÂmez-LimoÂn / Agricultural Water Management 43 (2000) 219±238
aside activity related to the subsidized crops (which are the majority).
X
Xi SA 100;
SA > 5% cereals; sunflower and legumes:
223
(2)
(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
4
S
100 57:14:
mn
43
(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.
224
Table 1
LP Model for CR Bajo CarrioÂn (Palencia, Spain)
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
2.8
1.4
0
2.8
1.4
0
2.8
1.4
0
7.2
5.7
4.2
3.6
3
2.8
1.4
0
7.2
5.7
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17
X18
X19
S.A
SA
Objective
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 Max
Constraints
Land
CAP 1
CAP 2
1
ÿ0.05
ÿ0.5
1
1
1
1
1
1
CAP 3
Market 1
Rotation 1
Rotation 2
Rotation 3
Frequency 1
Attributes
GM (PTAs/ha)
Water (m3/ha)
W. revenue
(PTAs/ha)
Direct labor
(Days/ha)
Fertilizer
(N.F.U./ha)
Water price
(PTAs/m3)
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
ÿ0.5
1
1
ÿ0.05
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