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Article

A Simplified Hydro-Economic Model of Guadalquivir River Basin for Analysis of Water-Pricing Scenarios

1
Department of Agricultural Economics, University of Cordoba & WEARE research group, 14071 Cordoba, Spain
2
Department of Economic Analysis, University of Seville & WEARE research group, 41018 Seville, Spain
*
Author to whom correspondence should be addressed.
Water 2020, 12(7), 1879; https://doi.org/10.3390/w12071879
Submission received: 21 May 2020 / Revised: 25 June 2020 / Accepted: 25 June 2020 / Published: 1 July 2020
(This article belongs to the Special Issue Institutions and Economics of Water Scarcity and Droughts)

Abstract

:
This study describes an economic model in the Guadalquivir river basin (Southern Spain) that considers inter-sectoral and hydrological effects of changes in water use as a response to various water-pricing policy scenarios. The main economic variables include water use, gross regional product, return flows in the river basin, and employment at sectoral and basin levels. The response of the different sectors to water pricing and of the sectoral productivity is derived from official data. The background of the model is based on previous research for the implementation of the UN System of Environmental-Economic Accounts and on the application of this framework to the Guadalquivir basin. Results based on the elicited curves illustrate that the structure of the demand function for irrigated agriculture passes from inelastic to elastic sections, while the function corresponding to the remaining economic sectors shows a continuous decreasing function with minor change in the elasticity structure of the curve. Results show that the impact of extreme measures of water pricing reduces water abstraction by up to 42% vs. the baseline scenario, with an economic reduction in regional Gross Domestic Product (GDP) of 1%.

1. Introduction

Water scarcity and increasing inter-sectoral competition for available water resources exacerbate the need for an efficient and sustainable allocation of water. In this context, water-pricing policies have been considered as a suitable economic instrument to guarantee the efficient management of the resource and to deal with growing socio-economic pressure. A large body of literature has explored the effectiveness of water-pricing policies in managing demand in alternative sectors (households, industry, agriculture, etc.) and in achieving certain conservation goals (see, for example, [1,2,3]). Most water economists argue that price-based approaches towards promoting a more efficient use of water resources (especially in those locations suffering from water scarcity) and/or towards achieving conservation goals are more cost-effective than non-price-based approaches [4]. However, pricing reforms explicitly designed for these purposes are rarely observed. The work of [2] contains several case studies of water-pricing reforms over agricultural, industrial, and residential sectors, and arrives at the conclusion that certain political economy factors (such as the reason for the reforms, the interest and the parties involved, the existing institutions, and the power systems) prevent the implementation of theoretically efficient pricing reforms.
At European Union (EU) level, the Water Framework Directive (WFD) [5] requires EU Member States to implement economic instruments in order to manage water resources and to achieve a good environmental and chemical status of surface and groundwater bodies. Specifically, the Directive highlights the importance of estimating the economic value of water uses, the cost of the associated water services, and how much of that cost is recovered from users, and encourages the use of water pricing as a tool to achieve an efficient use of water. Nevertheless, little advance has been made in this direction. According to the Commission’s Compliance Report [6] one of the main deficiencies in the WFD implementation involves the economic assessment of pricing measures and cost-recovery issues. Specifically, this report highlights the lack of methods for the calculation of costs (including environmental and resource costs) and benefits (including ecosystem services). Without these methods, neither will it be possible to ensure the implementation of effective pricing policies nor will disproportionate and inadequate measures be prevented.
Moreover, the WFD states that the level of cost recovery of water services should be analysed for certain water uses (including that of households, industry, and agriculture) and the characterization of water uses should refer to the basin as the level of management (Art. 5). Thus, the impacts of water-pricing should be both on a river basin scale and multi-sectoral. Finding ways to achieve positive economic outcomes in the management of water resources requires the aid of modelling tools to analyse the impact of alternative policy scenarios [7]. Following these recommendations, our model analyses not only the potential impacts of water-pricing policies (in various scenarios) on inter-sectoral water use and consumption, but also the effectiveness of these policies on the re-allocation of water between alternative uses within the river basin.
To this end, this study focuses on a strict economic point of view, since the main concept in order to determine water re-allocation among alternative uses is the economic concept of ‘value’. The economic value of a given level of water consumption is driven by the benefit derived from its use. Water value changes with the quantity and type of use [8], and therefore monetizing water use enables a comparison to be made between uses and introduces clarity to the economic implications of water-management-related decisions. In a mature water economy [9], when demand exceeds supply, then another relevant concept is that of ‘scarcity’. Water should be managed and allocated efficiently, that is, to maximize the value it provides to society. Under conditions of water scarcity, an economic focus, similar to that proposed in this study, helps identify efficient water allocations and reduce ‘wasteful’ practices. Additionally, the analysis of sectoral water demand and of its associated economic values of water facilitates the assessment of the effectiveness of public policies (i.e., water pricing), and identifies the trade-offs between resource uses.
There are numerous methods in the scientific literature for the assessment of the impact of re-allocation of water resources as response to economic policy measures, such as water pricing (see [10,11], among others). Nevertheless, studies have hitherto usually represented small spatial areas and/or addressed specific uses [12]. To the best of our knowledge, there are no studies available that analyse the effects of water-pricing policies on water use and consumption from a multi-sector approach and on a river basin scale where available water resources are depleted. This study aims to help fill this gap.
The proposed methodology simulates changes in water use for all relevant sectors in a river basin as the result of policy decisions regarding water-price measures. Price increases have been implemented by simulating various scenarios: baseline (current situation), financial and environmental cost-recovery scenarios, and two scenarios with major increases water costs. In order to test its applicability in a real context, the proposed methodology is applied to a specific case study: that of the Guadalquivir River Basin (GRB). The model requires a more detailed analysis of the irrigated sector, which is the greatest sector of consumption of water in the basin. The remaining economic sectors are taken into account via an estimation of water demand and economic productivity.

2. Materials and Methods

The Guadalquivir River Basin (GRB) contains 25% of Spain’s irrigated land and it is the longest of the southern rivers (657 km); it can thus be considered one of the most important river basins in Spain. It covers an area of 57,679 km2 and contains a population of 4.3 million. The basin has a Mediterranean climate with a heterogeneous distribution of precipitation. The annual average temperature is 16.8 °C, and the annual average precipitation is 573 mm, with a range between 260 mm and 983 mm (standard deviation of 161 mm). The main land uses in the basin are forestry (49.1%), agriculture (47.2%), urban areas (1.9%), and wetlands (1.8%) [13] (Figure 1).
The GRB is considered a mature closed basin where most of the water resources are already allocated across various uses (agricultural and non-agricultural) and there are growing pressures for new activities to use ‘additional’ resources such as reclaimed water and new reservoirs. The key factor influencing this situation is the agricultural sector, which is the largest user of water, with irrigated agriculture accounting for approximately 88% of total freshwater withdrawals in the basin. Due to its high irrigation efficiency (as a result of an intense modernisation of irrigation over recent decades), irrigated agriculture is competitive but still yields lower returns in comparison with other uses (industry, tourism, urban areas) in the basin. As water becomes scarcer, society turns to agriculture as a potential source of water, in the sense that this is the sector of major consumption and therefore efficiency of the use of water in the agricultural sector directly affects the availability of the resource.
The proposed methodology for the economic model estimates sector-specific demand curves because water demand may change with location (e.g., up-flow and down-flow agriculture) and type of water use (e.g., urban, industrial, agricultural). Therefore, the primary aim here is to assess the competing demands between different uses on a river basin scale. Additionally, the analysis will apply an economic approach to the assessment of the effects derived from alternative water-pricing scenarios where water demands constrain total use of the available resource within a one-period analysis, and hence it has a static nature. The methodology presented in this study reveals a deterministic approach since it considers a single-set of fixed boundary conditions (e.g., hydrological conditions) and parameters (e.g., constant price-elasticity of water demand). Therefore, no stochastic-determined variables are considered in the model.
Economic sectors are classified according the importance and the water-use typology. The proposed sectors of the demand for water services in the basin are:
(1)
Agriculture
(1a)
Rainfed agriculture
(1b)
Irrigated agriculture
(1c)
Livestock
(2)
Households
(3)
Industry
(4)
Services
(5)
Recreation
(6)
Energy
The valuation of water depends on whether the resource is considered an intermediate or a final commodity [14]. Water demand as an input to a production process (e.g., irrigated agriculture) can be derived upon the isolation of the marginal contribution of water to the total output value, and therefore a deductive estimation approach is required. Deductive techniques usually employ mathematical programming, although general equilibrium models and residual value methods also fall within this category. When water is a final consumption commodity (e.g., urban demand), inductive valuation techniques based on the econometric or statistical analysis of observed data to estimate price-response may be more appropriate. In Guadalquivir, as explained in greater detail below, either type of analytical approach is used, depending on the sector analysed. Regarding the agricultural sector, a deductive value methodology has been considered as more appropriate in order to assess crop and location differences across the GRB. Regarding the remaining economic sectors, a valuation based on estimated price-elasticities of water demand enable us to obtain water-use demand curves relative to changes in water pricing.
Therefore, the methodology used in this paper is organised in the following three phases:

2.1. Baseline Definition: An Appropriate Characterisation of the Economic Sectors in the Basin

Various sources have been used either for the observed original data or for the estimation of non-observed variables when necessary. The baseline scenario (Table 1) has been defined by employing the gross domestic product and employment by sector statistics from the Statistical National Institute, and the sectoral water use and prices from the Hydrological Plan by the Water Agency [13]. Global water abstractions in the GRB are estimated at 3614 Hm3 in 2012, where irrigated agriculture constitutes the greatest sector of consumption with 88% of the total water abstracted. Economic activities in the GRB generated around €66.1 × 109 in terms of GDP in 2012, which is equivalent to 7% of Spanish GDP. Over 73% of GDP in the GRB is concentrated in the service sector. Industrial activities amount to ≈18% of GDP, agricultural production ≈7%, and energy production ≈1%.

2.2. Estimation of Demand Curves with Respect to Water-Price Changes for the Various Economic Sectors

2.2.1. Irrigated Agriculture Sector

The irrigation sector has been modelled by dividing the basin into two main areas (upper and lower basin) and by simulating demand curves in the current baseline scenario per crop area given the data available. Table 2 shows the characterisation of the irrigated agriculture sector (upper and lower areas) in the GRB in 2012. The upper area of the GRB is characterised by a more diversified crop pattern, while the lower area principally comprises olive groves (≈80%) and open-air vegetables (≈11%).
The baseline price for irrigation is 0.06 EUR/m3 (Table 1) with a variable tier of approximately 30% (0.02 EUR/m3) and the rest as a flat rate. The agricultural sector’s response to water pricing has been simulated by adjusting irrigated crop area (internally) and converting irrigated areas into rainfed crops when the water price causes irrigation to be halted. This is an oversimplification since certain intra-sector intra-regional water trade may be possible, but this option remains outside the scope of this analysis.
The threshold price that makes the crop unprofitable has been estimated by the algorithm shown below. The value of the threshold indicator is specific for each crop and zone. When this indicator takes a negative value, then the irrigation should be terminated. The algorithm is defined as:
DGM (Differential GM) = (Irrigated GMi,j – Rainfed GMi,j)
Stop irrigation when: (DGMi,j – PwQi) ≤ 0
where GMi,j = Gross Margin of crop i in the zone j; Pw= water price; Qi =water use per hectare of crop i. Generally, the gross margins for any agricultural crop are determined by deducting variable costs from the gross farm income of a given crop for a given period of time (usually per year or per cropping season).

2.2.2. Non-Irrigated Economic Sectors

Once the current scenario is defined, the response of the different sectors can be simulated by using known elasticities of demand for the non-irrigated economic sectors. Thanks to [15], econometric approaches to estimate price-response and allocation effects from water-pricing changes have been widely used [16,17]. Nevertheless, the estimation of the water-price elasticity faces several challenges due to the existence of artificial price systems (such as, block-rate schedules) and to the variables and dataset used, among other shortcomings [11,18].
In the specific case of the GRB, the water use (abstractions) of non-irrigated economic sectors (i.e., energy, industry, services, and livestock) represents only 5% of the total water abstractions in the GRB, while that of households amounts to 7%. In order to simplify, this method uses price-elasticity estimates as appropriate instruments to model water-use demand curves. Moreover, and in the specific case of non-irrigated sectors, water-use demand functions are estimated by incorporating the following two assumptions:
  • The use of price-elasticity estimates, as given by [19] and [20]. Constant-price elasticity forms are common in water management models, and provide a proxy to estimate consumer surpluses [21];
  • The calibration of isoelastic demand curves by using estimated parameters upon a single point (Price, Water use) in year 2012 (latest contrasted data available).
Price elasticities of demand can be expected to be highly inelastic for non-irrigated uses, since there are few substitutes for water use in these economic sectors [22]. Thus, in our model, water for household, industrial, and service sectors can be expected to have a marginally higher value for a certain quantity of water consumed, since each unit of water is valued much more highly than that for irrigated agriculture and much less water is consumed [7].
Table 3 summarizes the estimates for the isoelastic demand equations, as well as parameter ‘K’, which is obtained by solving equation (2) for current water abstraction and price for each sector.
Q = Kpɛ
Elasticities (ɛ) for the different sectors can be found in Table 3, and have been assumed in accordance with [19,20].
The elicitation of each demand curve for each sector is illustrated by the following example, which corresponds to that of the household sector. This curve is calibrated by using the pair of known values (price = 1.9 EUR/m3, and water use = 261 Hm3 (Table 1)) for the year 2012, and by employing the elasticity parameter (−0.22) and the estimated K parameter for the household sector (300.58), as shown in Table 3. In this specific case, and for the sake of simplicity, no considerations regarding disposable family income have been made. The result is an elicited demand curve for the household sector in the GRB, as defined by the following expression:
Q = Kpɛ = 300.58p−0.22
Once the demand curve (water use vs. water price) is estimated for each sector, an aggregated demand curve can be obtained from the horizontal sum of all individual (or sector-specific) elicited functions. The aggregated demand curve represents the water demand for non-irrigated sectors.

2.3. Analysis of Changes in Water Use and Allocation as a Consequence of Changes in Water-Pricing Policies

Economic evaluation of simulated scenarios can provide insights into benefits and inefficiencies of alternative policy decisions at an ex-ante stage [8]. Additionally, the development of various scenarios is of value because it provides a basis for discussion and a framework for strategic planning [7]. In order to assess the global impacts of water pricing on water use and consumption in various economic sectors, price increases have been carried out by simulating the following scenarios:
  • Baseline (current situation)
  • Financial cost recovery (FCR)
  • Financial cost recovery + environmental cost (FCR+EC)
  • FCR + EC + 150%
  • FRC + EC + 300%
The values for the first two scenarios can be found in [23]. Financial cost-recovery instruments can be managed by public or private agents at various stages in the provision and management of water services. In order to calculate cost-recovery rates, it necessary to estimate what income public and private agents receive for the water services they provide. Based on the standard UN System of Environmental-Economic Accounts tables, cost-recovery ratios are computed by dividing the income generated from water services (as taxes, prices, or any other financial instrument) by the cost of their provision. The financial cost-recovery (FCR) index in the GRB in 2012 based on the UN System of Environmental-Economic Accounts is estimated at 75% for agricultural and livestock economic sectors, 87% for households and services, and 91% for industry. The environmental cost (EC) is defined as the cost of damage that the various water uses impose on the environment and ecosystems. The estimation of the environmental cost (EC) is defined by the Ministry of Environment and by the values for GRB found in the aforementioned hydrological plan [13]. The EC is estimated in the GRB in 2012 with an increase of 15% above the FCR. The latter two scenarios mean major price increases (of 150% and 300% respectively above FCR + (Ministry estimated) EC) in order to analyse the impact of extreme measures of water pricing.
The impact of changes in water use by irrigation that accounts for 88% of water use is not only concentrated in agriculture but also has a multiplier effect on the rest of the economy (mainly agri-food processing, but also other complementary industries) and on services (mainly transport and service providers to farms and food processing industries), which has been simulated by using the value found for California agriculture (similar to that of Guadalquivir) of 1.49, according to [24]. Due to this multiplier effect, when agricultural GDP (irrigation) increases by 1 EUR, then the GDP of the economy as a whole grows by 1.49 EUR (i.e., an additional 0.49 for the non-agricultural sectors).

3. Results

The proposed economic model has enabled demand curves to be elicited of water abstraction vs. water price increase in the alternative scenarios analysed in this study. Figure 2 shows the integration of demand curves (water use vs. water price) of irrigated agriculture (upper and lower areas) as well as the global (integrated) demand curve of the total irrigated agriculture in the GRB. The elicited curves illustrated that the structure of the ‘lower agricultural irrigated’ function, integrated basically by olives and open air vegetables, passes from inelastic to elastic sections, meanwhile the function corresponding to the ‘upper agricultural irrigated’, with a more diversified crop pattern, shows a continuous decreasing function with little changes in the elasticity-structure of the curve.
Figure 3 shows the integration of demand curves (water use vs. water price) of irrigated agriculture and the remaining economic sectors (non-irrigation), as well as the global (integrated) demand curve of the GRB. In this case, water abstraction excludes the inflow uses of energy (hydropower generation) and navigation uses. Hydropower has a lower priority in the GRB, since water is turbinated only when it is released for the interest of the other sectors, including environmental uses. Therefore, water available for hydropower is a by-product of decisions taken by the regulator in order to supply water to other sectors. In the case of navigation, this use is limited to the lower part of the GRB from the Atlantic Ocean near to Doñana National Park up to the inner-port of the city of Seville [13].
Based on the elicited curves, it can be clearly observed that the structure of the ‘irrigated agricultural’ curve passes from inelastic to elastic sections, while the curve corresponding to the remaining economic sectors (non-irrigation) shows a continuous decreasing function with minor changes in the elasticity structure of the curve.
Table 4 illustrates the response of water demand in all sectors as the water price increases as a response to the cost-recovery implementation.
Observation of Table 4 shows that the impact of extreme measures of water pricing reduces water abstraction by 42% vs. the baseline with the economic impact in regional GDP of a 1% reduction since agriculture (including livestock and rainfed agriculture), despite representing the sector most affected by the water pricing scenarios, constitutes only 7% of GDP. Results show that water pricing can induce water savings mainly by reducing water use in the irrigation sector although it should be considered that most of the socio-economic impact affects rural areas.
Table 5 shows the irrigated area per crop in the upper and lower areas in the various scenarios of water pricing. There is no change in the irrigation areas between the Baseline (Table 2), FCR, and FCR+EC scenarios because the increase of water pricing is insufficient to render the irrigated crops as unprofitable (inelasticity of the demand). The scenario for FCR + EC + 150% implies the substitution of crops, such as those of rice, winter cereals, sunflower, and populous, while the scenario for FCR + EC + 300% also affects maize, cotton, alfalfa, citrus, and olive (intensive) crops.

4. Discussion

A recent report by the EEA [25] acknowledges the inelastic nature of water demand in many sectors: “price does not appear to be a significant determinant of water demand”. The results obtained by our study are in line with this assumption. The ‘lower agricultural irrigated’ function, largely comprising olives and open-air vegetables, presents elastic sections, while the function corresponding to the ‘upper agricultural irrigated’ scenario with a more diversified crop pattern, shows a continuously decreasing function with minor changes in the elasticity structure of the curve. The same holds true with the remaining economic sectors (non-irrigation), including the household sector. Regarding the use of water price as an instrument to induce water saving in the household sector, the EEA in its review of eight EU countries [25] concludes that: “(..) in France, Germany and Spain, the results for the household sector suggest that the prices set have a relatively minor effect on the quantity of water demanded (i.e., water demand is inelastic to price).”
The Blueprint for the water strategy document [26] follows the dominant narrative (supported by environmental NGOs, political bodies, and research institutes) in the lines: “irrigation demand is inefficient because water cost is heavily subsidized and consequently, water is too cheap. When water price increases, the demand will be reduced and then sustainability is achieved.” An example of this narrative can be found in reports issued by the European Environmental Agency (2013), which include statements such as: “(…) increasing irrigation water prices to meet full cost recovery would maximise water use efficiency” [27] (p. 34). However, this statement contradicts the empirical observation contained in the same document, which holds that water-conserving investments depend on “incentives generated by quantity constraints and the limited role of prices” [27] (p. 43). In our study, there is no change in the irrigation abstraction between the baseline, FCR, and FCR + (Ministry estimated) EC scenarios because the increase of water pricing is insufficient to render the sector unprofitable. Major price increase scenarios (150% and 300% respectively above FCR + (Ministry estimated) EC are necessary in order to decrease the gross water abstraction for irrigation. Our results are in line with those of [28] and [29], where the authors conclude that, in the case of irrigated agriculture for moderate price increases (i.e., water cost increases to reach financial cost recovery), the response is limited, and a disproportionate price increase is necessary.
Finally, it is worth mentioning that the proposed methodology presents several limitations. One such limitation originates from the fact that no transaction costs are considered, nor are social benefits and costs that have been derived from the re-allocation of the resource, since their estimation would involve considerable difficulties [21,30], and they therefore remain outside the scope of this study. Economic models enable the economic impacts to be analysed of different management policies or decisions (e.g., water-pricing). Although it is widely accepted that no single method can capture all the dimensions associated with allocating water across all its many uses and locations at a catchment level [30], findings should be treated cautiously since there may be an inevitable gap between modelling research and its application in decision-making. This gap could be minimised by the inclusion of this type of analysis in policy assessments of a more integrated and/or holistic nature [17,31], thereby analysing policies from broader perspectives and various angles [32]. Only in this way will decision-makers attain sufficient relevant information to successfully handle decision processes.

5. Conclusions

This research focuses both on the potential impacts of water-pricing policies on water use in various economic sectors in a Southern European river basin, and on the effect that these policies incur on the re-allocation of water between alternative uses within the river basin.
The WFD [5] adopts an integrated approach to water management and grants a critical role to economic instruments, such as the use of “water pricing” and “full cost recovery” (Article 9), as efficient measures to achieve environmental objectives. However, this study concludes that the role of prices remains limited regarding water-use reduction although it does remain a key instrument for achieving cost recovery for water services to ensure the maintenance and financing of existing and future water infrastructure.
The exploratory model developed herein may serve policy makers in their assessment of the potential effects of water-pricing policies on the water used and on consumption from an inter-sector approach.

Author Contributions

The authors contributed equally to the conceptualization, development, writing, and editing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The authors have received financial support from MINECO-Grant: AGL-2014-53417-R.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Guadalquivir River Basin District. (Source: Guadalquivir River Basin Authority (GRBA)).
Figure 1. Guadalquivir River Basin District. (Source: Guadalquivir River Basin Authority (GRBA)).
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Figure 2. Elicited demand curves of water abstraction vs. water price increase (irrigation sector).
Figure 2. Elicited demand curves of water abstraction vs. water price increase (irrigation sector).
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Figure 3. Elicited demand curves of water abstraction vs. water price increase (all sectors).
Figure 3. Elicited demand curves of water abstraction vs. water price increase (all sectors).
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Table 1. Characterisation of the economic sectors in the basin. Guadalquivir 2012.
Table 1. Characterisation of the economic sectors in the basin. Guadalquivir 2012.
SectorsWater Used (106 m3)GDP (106 EUR)Employment (103 Person)Price (EUR/m3)
Rainfed Agriculture-140743-
Irrigated Agriculture3183.192585790.060
Livestock18.63733220.084
Households261.00--1.900
Industry (non-energy)68.0012,1752281.112
Services63.0048,5819081.900
Recreation1.001000.025
Energy19.00626120.049
Total3613.8266,1171249-
Source: Authors’ own based on Statistical National Institute and [13].
Table 2. Characterisation of the irrigated agriculture sector in the basin. Guadalquivir 2012.
Table 2. Characterisation of the irrigated agriculture sector in the basin. Guadalquivir 2012.
CropsIrrigated Area (ha)Irrigated Area (%)Water Use (m3/ha)Irrigated GM (€/ha)Rainfed GM (€/ha)
UpperLowerUpperLower
Rice38,69808.98%0.00%10,4507870
Maize16,69729933.87%0.70%50001000300
Winter cereals64,14911,74014.88%2.76%1900500300
Cotton58,813309513.64%0.73%50001118250
Sunflower24,97713155.79%0.31%2600206100
Sugar beet12,7806732.96%0.16%45001765300
Alfalfa495033001.15%0.78%45001145300
Vegetables (Open-Air)35,18446,0008.16%10.82%45004911250
Vegetables (Protected)226500.53%0.00%450017,454300
Citrus38,47633468.92%0.79%54001490750
Grape165016500.38%0.39%40002694500
Olive (table)34,64408.03%0.00%12901265400
Olive (oil)60,920324,51014.13%76.31%12901480550
Olive (intensive)35,16718,9328.16%4.45%50001480550
Almond180066000.42%1.55%500029001150
Populous011000.00%0.26%5400500400
Total431,170425,254100.00%100.00%
Source: Authors’ own based on [13].
Table 3. Estimated parameters for sectoral water demand. Guadalquivir 2012.
Table 3. Estimated parameters for sectoral water demand. Guadalquivir 2012.
SectorsElasticity (ɛ)K (Estimated)
Livestock−0.299.11
Households−0.22300.58
Industry (non-energy)−0.2970.12
Services−0.3880.40
Recreation−0.290.34
Energy−0.890.37
Source: Authors’ own based on [19,20].
Table 4. Estimated water withdrawal vs. scenarios of water pricing. Guadalquivir 2012.
Table 4. Estimated water withdrawal vs. scenarios of water pricing. Guadalquivir 2012.
Gross Water Abstraction (hm3) GDP (106 EUR)
IrrigationNon-IrrigationTotal% WaterAgricultureNon-AgricultureTotal GDP% GDP
Baseline31834313614100%399260,74264,781100%
FCR3183399358299%399260,74264,781100%
FCR+EC *3183383356699%399260,78964,828100%
FCR+ EC * + 150%2420293271375%398860,65664,715100%
FCR + EC * + 300%1266256152242%366560,48864,22599%
Source: Authors’ own. FCR = Financial Cost Recovery. EC * = Environmental cost defined by the Ministry of Environment [13].
Table 5. Irrigated area per crop in the scenarios of water pricing.
Table 5. Irrigated area per crop in the scenarios of water pricing.
CropsIrrigated Area (ha)
FCR
Irrigated Area (ha)
FCR + EC *
Irrigated Area (ha)
FCR + EC * + 150%
Irrigated Area (ha)
FCR + EC * + 300%
UpperLowerUpperLowerUpperLowerUpperLower
Rice38,698038,69800000
Maize16,697299316,697299316,697299300
Winter cereals64,14911,74064,14911,7400000
Cotton58,813309558,813309558,813309500
Sunflower24,977131524,97713150000
Sugar beet12,78067312,78067312,78067312,780673
Alfalfa49503300495033004950330000
Vegetables (Open-Air)35,18446,00035,18446,00035,18446,00035,18446,000
Vegetables (Protected)22650226502265022650
Citrus38,476334638,476334638,476334600
Grape16501650165016501650165016501650
Olive (table)34,644034,644034,644034,6440
Olive (oil)60,920324,51060,920324,51060,920324,51060,920324,510
Olive (intensive)35,16718,93235,16718,93235,16718,93200
Almond18006600180066001800660018006600
Populous01100011000000
Total431,170425,254431,170425,254303,346411,100149,244379,433
Source: Authors’ own. FCR = Financial Cost Recovery. EC * = Environmental cost defined by the Ministry of Environment [13].

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M., B.-M.M.; A., E.; J., B. A Simplified Hydro-Economic Model of Guadalquivir River Basin for Analysis of Water-Pricing Scenarios. Water 2020, 12, 1879. https://doi.org/10.3390/w12071879

AMA Style

M. B-MM, A. E, J. B. A Simplified Hydro-Economic Model of Guadalquivir River Basin for Analysis of Water-Pricing Scenarios. Water. 2020; 12(7):1879. https://doi.org/10.3390/w12071879

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M., Borrego-Marín María, Expósito A., and Berbel J. 2020. "A Simplified Hydro-Economic Model of Guadalquivir River Basin for Analysis of Water-Pricing Scenarios" Water 12, no. 7: 1879. https://doi.org/10.3390/w12071879

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