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Article

Sustainability of Duero Water Systems for Crop Production in Spain

by
Beatriz Lama-Pedrosa
,
Álvaro Sordo-Ward
*,
Paola Bianucci
and
Luis Garrote
Department of Civil Engineering, Hydraulics, Energy and Environment, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(1), 242; https://0-doi-org.brum.beds.ac.uk/10.3390/su16010242
Submission received: 15 November 2023 / Revised: 12 December 2023 / Accepted: 21 December 2023 / Published: 27 December 2023
(This article belongs to the Section Sustainable Water Management)
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Abstract

:
In recent decades, increased water demand combined with the effects of climate change has endangered water availability in many regions. In this context, sustainable water management has become a priority, seeking to balance human needs with the conservation of aquatic ecosystems. In the Duero basin (Spain), the availability of water is especially relevant for agricultural purposes, representing 93% of the total water needs. This study focuses on identifying and assessing the short-term sustainability of irrigated crop production in the Duero River basin. The maximum potential availability of surface water for irrigation was estimated and compared with the short-term agricultural surface water demand. The analysis was based on the use of a high-spatial-resolution (500 × 500 m) GIS-based model named WAAPA, and three indexes were used to evaluate and analyze the results. The results show that by analyzing the river basin in an aggregate form, the demands for irrigation were met, in which the reservoirs played an important role. When the analysis was downscaled to tributaries or even small streams, non-sustainable situations were identified. This shows the importance of using high-spatial-resolution models to improve, maintain, and achieve sustainability in the production of irrigated crops.

1. Introduction

Water systems provide valuable resources and different ecosystem services, but they often come into conflict. Therefore, it is crucial to establish a well-balanced management system to ensure the sustained provision of these services over time. In this sense, the concept of sustainability is linked to management and planning tasks, but it often does not have a clearly defined content. According to D. P. Loucks, sustainable water resource systems are characterized as systems engineered and controlled to fulfill and uphold social objectives while adhering to acceptable environmental and hydrological standards [1]. In Europe, the Water Framework Directive (WFD) [2,3] organizes river basin management to protect the ecological status of all water bodies. This framework does not address specific actions for environmental, economic, and social sustainability, but it proposes a process for the development and implementation of River Basin Management Plans, which define the territorial scope for water management. In Spain, the legal framework for water management predates the WFD, the Sustainable Development Goals (SDGs) [4], and the international commitments on climate change, like the European Green Deal (EGD) [5], and it is aligned with their sustainability objectives [6]. Furthermore, Spanish watersheds are an example of social sustainability, presented as a model of good governance where people work to solve water-related problems in places under stress [7,8].
Semi-arid countries with irrigation demands such as Spain, have worked to manage river basin management sustainably [8]. In Italy, the river basin authorities apply water balances to their territory to establish the volumetric reliability of demands [3]. Sordo-Ward et al. analyzed the potential water availability for European basins. The greatest vulnerabilities have been observed in Southwest Europe (Iberian Peninsula) and some basins in Italy and Greece [9,10]. California is a territory similar to Spain, with a similar population, landscape (agricultural and hydraulic), and climate. In the field of water management, both places have inequalities between the wetter regions and the drier (mainly agricultural) regions, with a favorable climate for fruit and vegetable development requiring extra water needs. Often, significant water deficits are solved by improving reservoir management systems [11]. The river basin authorities decided to incorporate sustainability indicators into the 2013 California Water Plan. They developed an indicator set called the Sustainability Indicators Framework to measure progress toward water sustainability [12,13].
After the transposition of the WFD into Spanish law, a Spanish regulation for water planning was developed (IPH, according to its Spanish acronym) [14]. The regulation establishes the need to set the environmental flow regimes in water bodies, which should be defined in terms of the characteristics and environmental needs of each fluvial segment within the analyzed system. IPH sets the reliability criteria to meet the urban, irrigation, and industrial demands. It is a simple binary criterion (compliant/non-compliant) and indicates whether a demand is considered satisfied or not. The Duero River Basin Management Plan (DRBMP) was carried out at the basin scale. It defines the scope of the water balance in the basin for water resource studies, demands, and management rules [15].
The European Environment Agency (EEA) considers precipitation, river flow, and water storage in snow and glaciers as measures of the availability of freshwater resources [16]. However, not all natural water resources are available to meet these demands due to the variability of their distribution in space and time. In this context, the Food and Agriculture Organization (FAO) presents a more realistic concept of water scarcity, understood as a relative concept, with an imbalance between supply and demand that varies according to local conditions (country, region, catchment area, basin, etc.) and under the existing conditions of institutional arguments and infrastructure [17]. In Spain, water resources systems have been classified according to the water balance as positive balance and negative balance (with structural deficit), with the risk of short-term shortage due to occasional insufficient resources in adverse hydrological events [18]. For this reason, the amount of water availability depends on the hydrological characteristics of the natural resource, the technological level of the exploitation system, and its operating rules. Water scarcity (lack of water availability), whether circumstantial or structural, entails socioeconomic and environmental impacts [19]. The Spanish Mediterranean climate is characterized by alternating droughts and floods and requires hydraulic infrastructures that guarantee water availability to transform the spatial and temporal irregularities of natural flow into a reserve for later use [20]. In Spain, the highest water consumption corresponds to irrigation (around 75% of total water resources) [21].
In semi-arid areas, regulation capacity is a fundamental factor for managers to be able to assess the scarcity of water resources. It is important to analyze the relationships between reservoir storage capacity, water supply yield, and instream flow needs to support downstream aquatic ecosystems with models that allow general explorations, which are applicable to other river basins [22]. In this context, the water supply should be linked to the reliability criteria of the exploitation system. Therefore, if the level of reliability of systems lowers and/or the regulation capacity increases, it would be possible to meet a higher demand or to mitigate the water deficit in the system and contribute to its sustainability.
Water resource management models support a variety of research applications, including the assessment of water availability, the allocation of water among competing uses, the evaluation of system performance, the identification of optimal system expansion, and the definition of suitable operating strategies [23,24]. Most allocation models are able to assess water scarcity in a basin under certain hydrological conditions by considering environmental requirements, water infrastructure, and the corresponding operating rules (mainly related to reservoirs). Among them, Aquatool [25,26], Ribasim [27], MIKE-BASIN [28], and WEAP [29] stand out. In the Spanish context, during the last decade, most studies addressing water system management and water allocation under droughts and water scarcity scenarios have been developed using AQUATOOL [25] and WAAPA [30] models. The implementation of these models can be seen in [31,32,33,34,35,36,37], among others. Sulis et al. indicated that simulation models provide information that can assist in enhancing the planning and management processes of the water resources system [38].
Many studies assess the performance of water systems by implementing a water allocation model regarding different factors that can affect water availability for the considered uses. To evaluate the systems’ behavior, mainly their capacities to satisfy the demands, these studies perform a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis [39] or the use of water scarcity and reliability indices. Different approaches have been used for the construction of these indices since their emergence in the 1980s [40]. These are important tools for accurately figuring out how river basins are used, making it easier to share this information and create guidelines for making policies. They can be simple averages of stored volume, water supply, evaporation, deficits, and the amount of water flowing out of a system [41]. Many of them are indicators of the water system’s performance and its sustainability for different users. Thus, Hashimoto et al. introduced that the operational status of water resource systems can be either satisfactory or unsatisfactory. They explained how well a system works using three concepts: reliability, resilience, and vulnerability [42]. Loucks et al. introduced a sustainability index. It helped determine the sustainability of the system for each user.
In addition, these indicators are used to measure the impact of climate change and regulatory capacity. Chavez-Jimenez et al. [31] analyzed the reliability of the water supply in the Guadalquivir, Ebro, and Duero basins. They used the AQUATOOL model and computed two indices: I1 and I2. I1 assesses the ratio between the water supply and the water needs (demands). I2 is similar to I1, but the amount of water supplied is considered to be associated with a given acceptable reliability. These indices constitute a support decision tool that helps to identify the optimal measures to implement. Chavez-Jimenez et al. [43] applied these indices and the WEAP model to evaluate, using the I1 index, the capacity of the Chira and Piura basins (Peru) for satisfying the urban and agricultural water demands under climate change scenarios. Granados et al. [32] analyzed the effect of climate change on potential water availability in Southern Europe basins (including the Duero basin). They used the WAAPA model to simulate water allocation under different emission scenarios. They assessed the resilience of the water systems regarding the regulation capacity by applying the attenuation index (IA) and the uncertainty index (IU). Their conclusions show that, in general, higher regulation capacities can help cushion the flow reduction due to climate change and the related uncertainty on the resulting water availability. Bianucci et al. [37] also showed the positive effect of regulation capacity on water availability. They applied the WAAPA model to basins across Europe considering different criteria for environmental flow determination and several climate change scenarios. Some indicators evaluate the imbalance between the supply and demand. Wang et al. [44] developed a hierarchical index system to assess the balance between water supply and demand, including a shortage water index. They studied the area of Qingdao (China) to evaluate which side (supply or demand) was the main cause of the imbalance. Wu et al. [45] applied the RIBASIM model to analyze the reliability of irrigation water supply, considering reliability a probabilistic concept. They developed the RA_IWS_Canal model by performing Monte Carlo simulations to assess the uncertainty associated with different factors that affect reliability. They performed a study over the Zhudong Canal basin in Northern Taiwan. They showed the usefulness of these kinds of models for optimal irrigation planning and management. Grigg [46] thought that models for water resource systems offer valuable information that often does not reach decision makers due to their complexity. The person creating the model can easily figure out if a demand’s reliability issue needs to be fixed using new water sources, improved infrastructure for water regulation or transport, or better demand management. Most of these indices are based on the reliability concept, which is the ratio between the water needs and the water effectively supplied to satisfy them. Others are expressed as the relationship between the potential water availability and the natural flows. All of them are useful indicators for water system performance analysis. However, to assess the system behavior in a water scarcity framework, it could be useful to combine the concepts of potential performance, water needs, supply, and resources.
As shown, several potential factors condition the sustainability of water resources systems: climate change, increasing water demand, inelasticity of water needs for some uses, uncertainty associated with many variables, development of hydraulic infrastructures (mainly reservoirs), efficiency of water use, water policy applied, increasing requirements of environmental flows, different water management schemes, and different visions for water planning, among others [47,48,49,50].
Within this framework, this study focuses on identifying and assessing the short-term sustainability of irrigated crop production along the Duero River basin. In this basin, irrigated crop production is fundamental in the economic and social context of this basin.

2. Materials and Methods

In this study, the evaluation of the sustainability of the irrigated crop production in the Spanish part of the Duero basin was carried out. The maximum potential availability of water for irrigation (PWA) was estimated and compared with the current demand for irrigation defined in the 2023 Spanish Duero River Basin Management Plan (DRBMP) [15]. The comparison was carried out at all points (nodes) of the river network where the demands are located. All nodes in the river network of the basin serve as accumulation points for water drained by a territory upstream. Also, upscaled analyses were performed at joints among the main river and tributaries, at the outlets of defined sub-basins, and in the entire Spanish part of the basin.
In this study, the PWA is defined as the annual water demand that can be satisfied at a point in the drainage network with a given reliability. PWA depends on the mean and variability of the monthly streamflow series, the storage availability for flow regulation, the monthly distribution of the demand, and the reliability indicator adopted. In this study, the reliability criterion was stated in the Spanish regulations of water planning (IPH). The restrictions of use due to environmental flow needs and the evaporation from the reservoir were also considered. The comparison between PWA and the current water needs was addressed based on the use of indexes. This provided an overall picture of the behavior of sub-basins and specific points of the river network to evaluate the sustainability of irrigated crop production.
Briefly, the WAAPA model was applied to simulate water allocation in each node of the Duero River network, considering natural surface water resources. Then, the PWA was computed. The PWA was compared to the surface water irrigation demand (SID, defined in the DBRMP) to evaluate sustainability. A group of indices was set for performing an objective sustainability assessment. These values were computed for each node in the river network (total of 308 nodes) and assessed at the basin and main subbasins (water management systems) levels. In addition, the performance along the main river course was evaluated. The model is described in Section 2.1. The data used to define the model topology, water resources (runoff), reliability, and current irrigation demands are detailed in Section 2.2. Finally, the indices used to assess the sustainability of the systems are defined in Section 2.3. Figure 1 shows a general scheme of the applied methodology.

2.1. Water Allocation Model

A GIS-based water resources model named “Water Availability and Adaptation Policy Analysis” (WAAPA) was applied to estimate the PWA along the Duero River and its tributaries (the Spanish part). This model simulates the operation of water resource systems, including their reservoirs. The basic topological unit of WAAPA is the river network. The main components are the inflows, reservoirs, and demands. WAAPA also includes ecological flows and evaporation losses for each reservoir belonging to the system of reservoirs. The input data for WAAPA are monthly inflows in the relevant nodes of the river network and reservoir data. WAAPA applies an algorithm with simple operating rules, where all reservoirs in the basin are jointly managed to satisfy the set of demands, preferably drawing water from reservoirs located upstream. The operational rules applied in this study were global distribution management; that is, at each node, their demands were supplied by all upstream reservoirs, and the environmental requirements for each river reach were satisfied. This simulation allowed the calculation of the PWA that could be provided at a given node in the river network, with the available water infrastructure and a given reliability criterion. The joint reservoir operation model maximized water availability as it minimized uncontrolled discharges.
The management criterion was designed to maximize water availability and thus may differ from actual management. However, this is a realistic scenario because it considers the constraints of establishing environmental flows as a restriction prior to the allocation of water to consumptive demands. The environmental flows were extracted from the DRBMP. As the urban demand represents less than 6% of the total, it was not considered in this study. The reliability criterion for irrigation was established according to the Spanish regulations of water planning (IPH). The time-based reliability for irrigation is defined as follows: maximum annual deficit of 50% of annual demand, maximum biannual deficit of 75% of annual demand, and maximum decennial deficit of 100% of annual demand.
The main results of WAAPA are the time series of maximum monthly volumes that can be supplied to each node of the river network with surface irrigation demand given the demand reliability, PWA, monthly reservoir storage values, monthly values of dam spills, and evaporation losses. Subsequently, at each node, the PWA was compared with the value of surface irrigation demand (SID) defined in the DRBMP [15] to evaluate its sustainability.

2.2. Data and Study Area

The transboundary basin of the Duero River is the largest of the Iberian Peninsula. It belongs to Spain (80.4%) and Portugal (19.6% of the total area). The flow regime that the Portuguese part of the basin receives from the Spanish part of the basin is managed jointly according to the Albufeira agreement signed between the two countries in 2010 [51]. The length of the Spanish Duero River is 744.29 km. Its drainage area is 77,145 km2 with a mean annual runoff of 11,186 hm3/yr. The reservoir capacity of the basin in the Spanish territory (surface water) is around 7500 hm3, and the total annual demand (surface water plus groundwater) is 3870 hm3/yr. More than 3600 hm3/yr (93%) are used for agricultural purposes, of which 3535 hm3/yr are used for irrigation and 65 hm3/yr are used for livestock care. Approximately 225 hm3/yr (6%) are allocated to urban and residential use. The remaining 45 hm3/yr are allocated to industrial and other uses. Any management action on agricultural water use can have impacts on the rest of the uses and on the environmental objectives of the water bodies [15].
Territorial rural development plans propose irrigation modernization and an increase in irrigated land in the Duero basin for socioeconomic reasons [15,52,53,54]. However, in the provisional scheme of important issues [55] of the Spanish Duero River Basin Management Plan (DRBMP), it is necessary to reconsider the expansion of irrigation in process, 38,920 ha (7%) in 2027, for climatic reasons. DRBMP was published in early 2023. This plan shows the environmental flows and demands to be allocated in the basin.
The WAAPA model was applied to the Spanish territory of the International Duero River basin. Figure 2 shows the drainage areas corresponding to the seven (7) sub-basins that were considered in the study area. Upper and Lower Duero are sub-basins that contain the Duero axis. These catchments picked inflows up from the Esla, Pisuerga, and Adaja sub-basins. Reservoirs with a storage capacity of at least 1 hm3 (46 reservoirs) were considered within the study area. The regulation capacity of hydropower reservoirs was neglected because it was considered that hydropower operators are free to discretionally manage their reservoirs within the limits set by the Basin Authority. In addition, they often perform seasonal regulations. This practice, which increases the availability of water for consumption, was not included in the model.
The WAAPA model hydrographic network was derived from the GTOPO Hydro1k dataset [56]. The digital elevation model and the derived datasets of flow direction, flow accumulation, and sub-basins were used. The reservoir capacity data were obtained from the ICOLD World Register of Dams [57]. Each dam in the model was positioned on the river network to locate its elements in the space across the sub-basin. They were assigned a maximum storage volume and the corresponding flooded area. The intermediate values of the flooded area and storage were estimated by assuming a scaling proportional to the square and cube of the depth of the water, respectively, leading to an exponential relationship (1.5) between the storage volume and the water surface.
Monthly time series of flows were used as the input data for the WAAPA model. They were obtained from the SIMPA [58] hydrological model (SIMPA by its Spanish acronym), which is an integral system for the modeling of precipitation and inflow used in Spain for the evaluation of water resources in natural regimes. The series from 1940/41 to 2017/18 was used.
Table 1 presents the mean values of the main hydrological variables in the Spanish part of the Duero River basin. There is a 25.2%, relationship between rainfall and water resourcesbased on annual average values, although this relationship is not linear due to temporal and spatial irregularities in rainfall and hydrological factors. The Ministry of Ecological Transition and the Demographic Challenge (MITECO by its Spanish acronym) provides on its website the maps of the different hydrological variables obtained using the new simulations by the SIMPA model, which covers the hydrological years 1940/41 to 2017/18 (the period used for the last planning cycle) [59,60].
The main hydrological and hydraulic characteristics of each of the seven catchments of our model were calculated after the input data were compiled into a topological model. The area (A) of each catchment was determined from the GTOPO Hydro1k data set and is expressed in km2. The mean annual flow (F) of each stream and catchment in the model was derived from the corrected mean results of the SIMPA model and is expressed in hm3/yr. The number of dams and the storage volume information (V) for each reservoir were taken from the ICOLD World Register of Dams and are expressed in hm3. The surface irrigation demand (SID) of each catchment was derived from the DRBMP and is expressed in hm3/yr. These results were clustered into the model, and they are described in Table 2 and mapped in Figure 3. It should be noted that the study produced results for the reservoirs, the nodes, and the stretches of rivers, also called “reaches.” However, for the sake of simplicity, in the main body of the manuscript, these results were averaged and clustered into their respective sub-basins (or water systems).
Figure 4 shows the evolution of the mean annual flow along the Duero basin for a time slice from 1940/1941 to 2017/2018, graphically indicating the relative importance of its main tributaries, which correspond to the considered sub-basins. As accumulative values were represented, the growth of the variable was accompanied by a shift along the river from the headwaters downstream. Each point in the channel was positioned on the current according to its distance from Portugal. The jumps represent water inflows to the principal system, as the values of the variables were provided by the model at the nodes. The blue vertical lines indicate the point of the contribution of each sub-basin at its confluence with the main channel. The blue line of the inflow of the Adaja sub-basin was not plotted because it is a smaller jump and it is simultaneous with the Pisuerga sub-basin inflow point. The reaches of the Upper and Lower Duero sub-basins coincide with the main channel, and their differential contributions cannot be seen in Figure 4. The Esla sub-basin is the largest contributor to the Duero basin, followed by the Pisuerga sub-basin. The Tormes and Águeda sub-basins are the closest contributors to the Portugal border.

2.3. Sustainability Assessment

The maximum potential availability of surface water for irrigation (PWA) was determined for all nodes of our model (308 nodes in this study) to explore the effects of reservoir storage capacity on the short-term sustainability of surface irrigation demands in the Spanish part of the Duero River basin.
The PWA is defined as the annual water demand for surface irrigation that can be satisfied at any point in the stream network with a predetermined reliability. The PWA in this analysis was estimated using the Water Availability and Adaptation Policy Analysis (WAAPA) model. The volume of water available for irrigation was estimated by considering the reliability criterion established by the Spanish regulation of water planning (IPH). The PWA for irrigation was calculated once the volume for environmental flow regimes was accounted for and was not available for other uses, like irrigation. The environmental flow in each reach was derived from the DRBMP. The volume for urban supply was not considered. To support this decision, three main reasons are highlighted. First, more than 93% of the consumptive demand is destined for agricultural use and only 6% for urban water supply, the latter being always satisfied. Second, Spanish regulations assign the highest priority to urban water supply [14,15]. In the case of the Duero River basin, urban water supply would not significantly condition water management vulnerability, particularly compared with irrigation water needs. Thus, this study focused on water supply for irrigation purposes. Finally, the study focused only on the irrigation water supply and the corresponding system performance to avoid losing clarity in the presentation of the results and findings.
In order to establish whether the current surface irrigation demand (SID) could be sustainable, the analysis was performed in two stages: (1) estimation of the PWA for the hydrological series (SIMPA) in each node and reservoir and (2) comparison between the model response and SID from the DRBMP.
First, the monthly streamflow series is the inflow in the allocation model (WAAPA). Its output consists of the assessment of the PWA in each node of interest using the storage volume (V) of each sub-basin in the model. The results obtained were the monthly values accumulated along the river network. From these, the accumulated annual average values for the same nodes were calculated. These values represent the volume of water available for annual irrigation, with a certain reliability at each node. Reservoirs are nodes with water storage capacity. The capacity at each node determines the same property in the following reach.
Second, the annual demand for irrigation was taken from the DRBMP. These demands were located in the model, as indicated in this plan, and their accumulated values were calculated across the sub-basins. The comparison between the available water for irrigation (PWA) and current irrigation demands (SID) was made at each node. The PWA was greater/lesser than the SID locally, which tended to indicate a better/worse condition for assessing its sustainability.
In this study, PWA was estimated by considering only one type of demand in the system and irrigation demand with a constant monthly distribution. This choice was made because the true annual distribution of irrigation demands in each model node is known; therefore, the results could be contrasted in every node. PWA was obtained for irrigation reliability that is set by the Spanish guidelines of water planning (IPH). This reliability level was chosen as required by the Spanish normative.
To evaluate the significance of the trend toward non-sustainability in irrigation demand, three indices were used: the Performance Index (IP), the Improvement in Sustainability of Demands Index (IS), and the Usage Index (IU). The calculation of the indices was conducted at each node (308 nodes located in the river network) to estimate the sustainability of the irrigated crop production in the basin upstream of each node. The value of the indices at the node that corresponds to the outlet of each sub-basin represents the evaluation of the global functioning of the corresponding sub-basin and, therefore, the analysis of the sustainability of their irrigation demands. The Performance Index (IP) serves as a metric to assess how effectively water needs are met at any sub-basin or any point of the river network, providing an overall measure of the performance of the system. In this study, the criterion for reliability of demands was used as specified in the Spanish regulation for water planning (IPH). The numerical values for this indicator can be greater than, equal to, or less than one. The value assigned to the node of the outlet of a sub-basin represents the global assessment of that sub-basin.
Equation (1) is used to calculate the IP index:
IP = PWA/SID
PWA > SID → IP > 1 → satisfied demand
PWA = SID → IP = 1 → strictly satisfied demand
PWA < SID → IP < 1 → non-satisfied demand
If IP ≥ 1, the watershed upstream of the node under analysis has implemented enough measures to meet the demands, and it is non-vulnerable. If the value of IP < 1, it indicates a high probability that the demands are non-satisfied and the basin is vulnerable. Vulnerability is related to the magnitude of the damages, which are produced due to non-satisfied demands. To estimate the fraction of natural resources needed to satisfy the demand, the Improvement in Sustainability of Demands Index (IS) is used. Only when IP < 1, IS is applied. It is calculated as the ratio between the volume not allocated to the demands and the natural volume at the node under analysis. Its values can be negative or positive. The negative values indicate a lack of sustainability. Positive values allow us to estimate the percentage of natural resources needed to fully satisfy irrigation demands. High values of this indicator indicate a high percentage of resources to be mobilized to complete demands. However, low values of IS represent little effort in increasing the available resources that would complete the supply.
Equation (2) is used to calculate the IS index:
IS = (SID − PWA)/F
The possibility of regulating natural resources is limited. There is a threshold that should not be exceeded in order to maintain acceptable ecological conditions. A Usage Index IU is proposed to estimate the maximum natural resources available to increase the satisfied demands. It is especially important at points where the sustainability of demands depends on the increased regulation of natural resources.
Equation (3) is used to calculate the IU index:
IU = 1 − (SID/F)
The threshold value of the Usage Index (IU) varies for each specific sub-basin and tends to be higher for small drainage areas and for river networks with an irregular flow regime. For this case study, a threshold value equal to 0.5 was used. This index is important because, in those nodes, where IS is positive and IU is above the threshold, an increasing regulation solves or mitigates the deficits of supplied demands and therefore contributes to guaranteeing the sustainability of irrigated crops.

2.4. Limitations of the Study

Although the proposed methodology is appropriate to be used in any basin, a limitation lies in the reduced number of basins analyzed. Consequently, the results and conclusions are conditioned to the specific characteristics of the Duero basin and its sub-basins. Thus, further analyses should include a larger number of water systems with distinctive characteristics to deeply assess the effectiveness of these indices when evaluating the basin performance.
As stated, to allocate water demands, in this study, WAAPA applied an algorithm with simple operating rules, where all reservoirs in the basin are jointly managed to satisfy the set of demands. This hypothesis could be derived from higher PWA compared with the other operating rules.
This study focused on regulation issues, environmental flows, and comparisons between PWA and current water demand at different spatial levels. However, many other potential factors could condition sustainability, such as climate change, increasing water demand, uncertainty associated with many variables, inelasticity of water needs for some uses, development of hydraulic infrastructures (mainly reservoirs), efficiency of water use, water policies applied, increasing requirements of environmental flows, different water management schemes applied, water management inefficiencies, and different visions on water planning. Although an important challenge, their integration is an excellent research line to continue to be developed.
Although the irrigation of crops is the main water demand in the basin (93% of the total current demand), there is a percentage (7%) corresponding to others that were not considered in this study. By applying this hypothesis, the resulting PWA could be higher compared with the inclusion of all demand uses.
The IPH reliability requirements were applied in this study. The use of other reliability criteria could condition the results.
Although the WAAPA model is a high-resolution model, it uses input data from diverse sources that introduce an inherent uncertainty.

3. Results and Discussion

The management of storage volume in the WAAPA model to calculate potential water availabilities (PWA) for irrigation maximizes the outcomes at each node (and for topological reasons, in each stream). The computation of accumulative availabilities consistently availabilities more favorable outcomes than the calculation conducted without accounting for the system capacities and the resources present in preceding nodes through which water flows. A more disaggregated management could reduce availability.
PWA was estimated at each node of the sub-basins considering the reliability criterion established by the Spanish guidelines of water planning (IPH) and the state flows post-implementation of environmental volume (DRBMP). Environmental maintenance volume is considered a restriction to water systems, so it cannot be used to satisfy the demands. The relaxation/tightening of the reliability criteria or the environmental maintenance standards would modify the results. The values of irrigation demands, SID, are obtained from DRBMP. The variable to be evaluated is its accumulated value obtained at each node of the sub-basin.
Figure 5 shows the longitudinal results obtained from representing the spatial evolution of the volume of the reservoir, in hm3 (V), the potential mean annual volume to satisfy irrigation, in hm3/yr (PWA), and the volume of annual surface irrigation demand, in hm3/yr (SID), along the axis of the Duero. The graphical representation of the vertical black lines follows the same criteria as those in Figure 4.
In Figure 5, the jumps observed in the mean annual surface irrigation demand accumulated along the Duero River represent the aggregation of demand at different points of the main watercourse. The highest demand occurs in the Esla sub-basin, followed by the Pisuerga sub-basin. These demands must be met with the potential water availability (PWA) for use by the model. Additionally, a complementary hydraulic infrastructure, such as tanks, canals, and pipes, makes it possible to share water reserves in the same sub-basin and spatially expand the water supply over a certain distance. It is, therefore, logical to aggregate the results by sub-basin (and river reaches) in order to identify vulnerable areas, where current hydraulic capacities may be prone to water deficits. It can also be seen in Figure 5 that both the Lower Duero sub-basin and part of the Upper Duero sub-basin have accumulated PWA deficits in relation to the accumulated SID. The Lower Duero and Upper Duero sub-basins appear as areas of global deficit, with annual global deficits of 80% and 20%, respectively, of surface water needed for irrigation (a more detailed analysis is presented later in the manuscript).
Figure 6 represents the spatial distribution of the variables used in this study. Streams are colored as they assume the values assigned by the WAAPA model to their input nodes. Cumulative values were represented for all variables; thus, higher variable values were reached in the flow direction. The nodes representing the outlets of the sub-basins contain their aggregated information and results. The variables of annual mean flow, storage volume, and potential water availability are fundamental elements related to the supply of water management. The basic topological unit of WAAPA is the capability of the river network in the sub-basins, so the WAAPA model allows the user to obtain a clear picture of the behavior of the reservoirs in all catchments. The input data for WAAPA in Figure 6 are as follows: mean annual flow, F ((a) in blue); storage volume, V ((b) in brown); and surface irrigation demand, SID ((c) in green). The demand values were considered assigned to the nodes along the river network according to the description of the DRBMP. The cumulative values of SID were calculated for the entire river network (including the main course and tributaries) to be compared with the corresponding values of PWA. The output data from WAAPA in Figure 6 are as follows: potential water availability, PWA ((d) in grey). All of the mentioned variables were shown to provide a perspective on the supply of water in the river network and sub-basins.
By considering the total values of the Duero basin, it is apparent that 10,674 hm3/yr of F and 3000 hm3 of V make it possible to obtain 2812 hm3/yr of PWA. The current SID is 2246 hm3/yr. Overall, the volumes corresponding to reserves and availability for this use are remarkably close to the existing demand for irrigation. Either regulation capacity manifests itself within a singular year (intra-annual) or across consecutive years (inter-annual), encompassing the storage volume during wet months or years to facilitate subsequent release during dry periods. Ordinarily, the storage volume is less than the average annual inflow and varies in accordance with the duration of the regulation period and the seasonality of the flow. In the Duero basin, water availability closely corresponds to the storage volume. When the storage volume is increased, the availability along the Duero River network also increases and shows stability in the hydrological regime of the basin.
The IP index is shown in Figure 7. Vulnerability issues appear in all the sub-basins. The Esla, Adaja, Tormes, and Águeda sub-basins have globally sustainable demands in the short term, although locally, there is a lack of supply. The Pisuerga, Upper Duero and Lower Duero sub-basins present global problems. Global issues are identified when the final stream of the sub-basin appears in red. Many reasons could cause this situation: demand excess, lack of regulatory efforts, inadequate management, and conflict with non-consumptive demands, among others. As an example, the analysis of the lower and upper parts of the Duero River is developed. Analyzing and presenting the results from different perspectives (Figure 5, Figure 6 and Figure 7 and Table 3) with a high degree of spatial detail allows us to explain the possible causes of the water deficits identified in the Lower Duero and Upper Duero River networks. Lower and Upper Duero sub-basins present similar specific (per km2) mean runoff, mean irrigation demands, and ratios between them, which are 4.9 and 4.7, respectively (Figure 3). However, the percentage of the mean annual flow regulation capacity of each sub-basin is 3% and 21%, respectively (Figure 2 and Figure 3), and most of the tributaries of the upper part have reservoirs (5) compared with the lower part (1). Then, by analyzing only the sub-basins, it can be seen that most tributaries with the regulated flow can meet the demands in the Upper Duero and in the main river from its origin to the confluence of the last tributary before the sub-basin outlet. In the Lower Duero sub-basin, without the possibility of regulating flows, deficits are present in its principal tributaries and in the main river. However, the analysis of the lower part of the Duero River is more complex because it receives the flow contributions from upstream and important tributaries, and it is affected by the sustainability situation of all of them.
The operation rules applied by WAAPA consider that all reservoirs in the basin upstream of the point of analysis are managed jointly to meet all the demand, using the so-called “global distribution management” where the basin is fully interconnected among reservoirs and demands. At each node, its demands are supplied by all upstream reservoirs. Therefore, at each node, the accumulated reservoir volumes and the accumulated demands up to that point through the sub-basins are virtually placed for allocation. This hypothesis maximizes the PWA results but also accumulates deficits in adding system failures. Thus, the lower part of the Duero River is also affected by the upstream rivers that present deficits or surpluses. Although the lower part of Duero River significantly increases its mean annual flow (Figure 4, natural conditions) due to the confluence of the Pisuerga and Adaja rivers, both tributaries present problems in the last river reaches before their outlets. The same is true for the Upper Duero River (Figure 7). It should be noted that environmental flow requirements were also considered in the entire Duero River network, decreasing the PWA. In summary, the lower part of the Duero River presents a small capacity to regulate flows, receives deficits from its main tributaries, the Upper Duero River and its own sub-basin, and environmental flow requirements decrease the available water for other uses. All these factors contribute to compromising sustainability along the lower part of the Duero River.
Figure 8 shows the IS values along the fluvial network of the sub-basins. The value of the Improvement in Sustainability of Demands Index (IS) for the network was computed at each node. Negative values (in blue) indicate that there are no problems with the short-term sustainability of irrigation demands. Most of the sub-basins are problem-free. Positive values (colored according to scale) estimate the percentage of natural resources to be mobilized to solve the short-term sustainability problems of irrigation demands. It is also noted that a large part of the network affected by irrigation shortages can solve this situation by increasing its regulation by a small percentage (less than 20%).
Figure 9 shows a graphical representation of the estimated level of use of the natural resources of the sub-basins if the irrigation demand was completely satisfied using the value of the Usage Index (IU). Values of this index above 0.5 indicate the potential for increased regulation of resource mobilization for irrigation. Values of this index below 0.5 indicate a high use of natural resources. In the second case, the existence of surpluses that could be regulated is not clear.
The Spanish part of the Duero basin presents values of IP = 1.25, IS < 0, and IU = 0.78. Therefore, after the implementation of the environmental flows in its channels, its aggregate irrigation demand is satisfied, requiring no further regulation for its sustainability and the level of use of natural resources is very acceptable, according to the adopted criterion. However, aggregate values can mask the existing issues in smaller areas. Considering the natural flow of water, it is sensible to inspect the drainage network of the sub-basins in the reverse direction to identify local problems. The scope of the analysis can be changed by moving upstream along the channel from the Portugal border.
The Águeda and Tormes sub-basins show significant surpluses. It is important to consider that the Duero basin is international. The Albufeira agreement [51] establishes a set of rules for the distribution of water resources between Spain and Portugal, considering factors such as weather conditions and water availability. Therefore, the average annual accounting of natural resources is less than 10,674 hm3/yr. It is reasonable to consider that the surpluses from these sub-basins bordering Portugal are allocated for the fulfillment of this treaty because certain volumes must be allowed to flow into Portugal annually.
Table 3 provides a quantitative overview of the operation of the sub-basins. The Esla, Adaja, Tormes, and Águeda sub-basins display overall sustainable demands in the short term. Overall, the Pisuerga and Upper Duero sub-basins have IP values of less than one, although they are close to it. Given that their Usage Indexes surpass 0.5, it is possible to sustain their global demands in the short term with regulatory efforts. Based on the IS results, there is a need to increase the use of natural volumes in the Pisuerga and Upper Duero sub-basins by 1% and 4%, respectively. The Lower Duero sub-basin is unique as it has a particularly limited regulation capacity. Numerous hydroelectric reservoirs in this area, which were not previously considered, could potentially be employed. A mixed use might be feasible to fulfill part of the demand.
Occasionally, localized problems have been found in specific streams within the sub-basins. They are vulnerable streams, as shown in Figure 7. The tributaries implicated are listed below, together with their respective values pertaining to the improvement in the sustainability of the demands index (IS) and the usage index (IU), as detailed in Table 4. The geographical location of these zones is shown in Figure 10. This more detailed analysis is made possible by calculating the indexes at each node. In these particular instances, environmental maintenance can compromise the sustainability of irrigation demands based on the adopted threshold value. The methodology employed reveals nodes (streams) where ensuring the sustainability of demand is challenging because the availability does not reach the required threshold and there are no surpluses that could enhance it through increased storage volume.
In the rest of the sub-basins with potential problems, according to Figure 8, the increase in resources to meet irrigation demand should not expose environmental sustainability to risk, especially when the environmental flows are considered as a restriction of use to the regulation systems.
Finally, the results of the study are particularly significant as they systematically analyzed the current conditions of irrigation demands in the Duero River basin [15,52,53,54,55]. Additionally, we took into account the governance aspects of water resources in Spain [2,3,14,15]. It is important to note that our findings are contingent on environmental maintenance, as emphasized in the existing research [2,3,4,5,6,15]. Furthermore, we underscore the transferability of our methodology to other river basins, contributing to the broader discourse on water resource management [16,17,19]. The evolving paradigms of water governance need the integration of innovative methodologies. This study not only identifies the importance of considering water availability in a watershed but also proposes a methodology applicable to diverse hydrological contexts [30,31,32,33,34,35,36,37]. It aligns with the current need for comprehensive water management strategies that incorporate both quantitative assessments and robust result evaluations, as advocated in recent literature [40].

4. Conclusions

This research is relevant because of the economic importance of the production of irrigated crops in the Duero River basin. Furthermore, in January 2023, a new basin management plan began to be applied, and mandatory environmental flow regimes were established in all watercourses of the basin. Finally, the basin authorities established mandatory values of demand reliability. Thus, the irrigation demand is satisfied only if it meets the predefined volumetric and temporal guarantee standards.
The WAAPA is a high spatial resolution GIS-based model that computes the potential water availability (PWA) for irrigation at each node of a high-density river network, including main courses, tributaries, and small waterways, and allows for a deeper spatial analysis compared with other numeric models.
This study presents a methodology to assess the sustainability of the current irrigation demands (SID) defined in the DRBMP. The analysis reveals variations in surface water irrigation demands along the Duero River, with certain sub-basins, such as Esla and Pisuerga, having higher demands. Due to the origin of the PWA variable, in the short term, the sustainability of the production of irrigated crops depends on the natural runoff in the waterways and the volume storage in reservoirs.
The management of storage volume in the WAAPA model plays a crucial role in maximizing the outcomes for potential water availabilities for irrigation at each node in the Duero basin. Disaggregated management could lead to reduced water availability.
The inclusion of environmental flows causes a decrease in water availability for irrigation. Environmental maintenance volume is considered a restriction on water systems, and it cannot be used to satisfy demands. Changes in the environmental maintenance standards can affect the results. From another perspective, the existence of several dams and reservoirs ensures water availability to achieve the required environmental flow. Even if the outcomes are not sustainable in some irrigated areas, the environmental flow is always satisfied (not shown in this study).
A method for conducting an analysis of irrigation demands was proposed, involving the calculation of various indexes at each node of the river network. These indexes are described as universal, implying that they can be applied to any water system. They are simple and user-friendly tools, so they can be easily incorporated into the assessment of several water systems. The index-based methodology efficiently reveals significant information. This study introduces indices like IP, IS, and IU to assess short-term sustainability, the potential for improvement in meeting demands, and the level of use of water resources. Through computation at each node within the sub-basins, the indexes estimated at nodes located in the lower part of the basins raise greater concern than those located in the upper part. This is because the concluding segments of the sub-basins aggregate all their resources and capacities. According to the values obtained from the indexes in the entire Duero River basin (IP = 1.25; IS < 0; and IU = 0.78) in the short term, the existence of reservoirs confirms high effectiveness to better satisfy the irrigation demand. Vulnerabilities are identified in various sub-basins.
This analysis was also performed at each node of the sub-basins and the results were tabulated by sub-basins and graphically displayed in a distributed manner across them. Different sub-basins exhibit varying levels of sustainability. Lower Duero and part of the Upper Duero sub-basin are identified as areas with accumulated deficits in potential water availability compared to surface irrigation demand, indicating global deficits of 80% and 20%, respectively. The Esla, Adaja, Tormes, and Águeda sub-basins display overall sustainable demands, while the Pisuerga and Upper Duero sub-basins could sustain global demands with regulation works. Thus, areas whose demands might be exposed to non-sustainability were identified. In the most problematic areas of the sub-basins, strengthening hydraulic infrastructure and performing detailed studies of environmental flows are key measures to mitigate deficits in the sustainability of irrigated crop production. In this study, the existence of dams and reservoirs was shown to be essential elements to ensure the sustainability of irrigated crop production.
After verifying that there is a surplus of natural resources in many streams, there is a possibility of increasing the water availability by regulating water resources to achieve and ensure the sustainability of crop production.
In a spatially distributed model (500 × 500 m), the results for the entire Duero River network captured the combined implications of the sustainability of irrigated crop production, environmental considerations, and water resources management.
Finally, a method to assess the sustainability of irrigated crop production is proposed, which includes the modeling of exploitation systems, consideration of current demands, and environmental and governmental constraints on management. This case study examined the real situation of the sub-basins and river network in the Spanish part of the Duero basin, but it could be applied to other basins and scenarios.
Further research will be conducted according to the following research objectives:
  • Exploring the usefulness of the proposed indices to assess the climate change influence on the water system vulnerability.
  • Performing an economic analysis considering both the costs and benefits related to the adoption of measures aimed at guaranteeing the sustainability of irrigated crop production.
  • Developing a methodology capable of integrating most of the factors mentioned that impact the sustainability of basins.
  • Extending the analysis to a longer time horizon, considering most of the factors simultaneously.
These analyses can provide a more complete picture of the challenges and opportunities associated with the sustainability and management of river basins.

Author Contributions

Conceptualization, L.G., B.L.-P. and Á.S.-W.; methodology, L.G., B.L.-P. and Á.S.-W.; data processing, B.L.-P. and P.B.; software, L.G., B.L.-P., Á.S.-W. and P.B.; validation, L.G. and Á.S.-W.; writing—original draft preparation, B.L.-P.; writing—review and editing, B.L.-P., L.G., P.B. and Á.S.-W.; visualization, B.L.-P. and P.B.; supervision, Á.S.-W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Spanish Ministry of Science and Innovation, grant number PID2019-105852RA-I00: “Simulation of climate scenarios and adaptation in water resources systems (SECA-SRH)”.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

The authors would like to thank Alban Kuriqi for his valuable comments and recommendations on this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Loucks, D.P. Quantifying trends in system sustainability. Hydrol. Sci. J. 1997, 42, 513–530. [Google Scholar] [CrossRef]
  2. European Parliament. Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the field of water policy. C Off. J. Eur. Communities 2000, 327, 1–72. [Google Scholar]
  3. European Commission. Common implementation strategy for the water framework directive (2000/60/EC). In Directive, Water Framework. Guidance Document 7; European Commission: Brussels, Belgium, 2003. [Google Scholar]
  4. Sachs, J.D. From millennium development goals to sustainable development goals. Lancet 2012, 379, 2206–2211. [Google Scholar] [CrossRef] [PubMed]
  5. European Union (EU). European Green Deal: Striving to Be the First Climate-Neutral Continent; European Commission: Brussels, Belgium, 2019. [Google Scholar]
  6. Naciones Unidas. Informe Mundial de las Naciones Unidas Sobre el Desarrollo de los Recursos Hídricos 2021: El Valor del Agua; UNESCO: París, France, 2021. [Google Scholar]
  7. Bergstrom, T.C. The uncommon insight of Elinor Ostrom. Scand. J. Econ. 2010, 112, 245–261. [Google Scholar] [CrossRef]
  8. Nordman, E. The Uncommon Knowledge of Elinor Ostrom: Essential Lessons for Collective Action; Island Press: Washington, DC, USA, 2021. [Google Scholar]
  9. Gorguner, M.; Kavvas, M.L. Modeling impacts of future climate change on reservoir storages and irrigation water demands in a Mediterranean basin. Sci. Total Environ. 2020, 748, 141246. [Google Scholar] [CrossRef]
  10. Sordo-Ward, A.; Granados, A.; Iglesias, A.; Garrote, L.; Bejarano, M.D. Adaptation Effort and Performance of Water Management Strategies to Face Climate Change Impacts in Six Representative Basins of Southern Europe. Water 2019, 11, 1078. [Google Scholar] [CrossRef]
  11. Pulido Velázquez, M. 5 Lecciones de la Sequía en California. iAgua Web Site. 2016. Available online: https://www.iagua.es/blogs/manuel-pulido/5-lecciones-sequia-california (accessed on 8 December 2023).
  12. Shilling, F.; Khan, A.; Juricich, R.; Fong, V.; Hodge, D. Water sustainability indicators for California water management. In World Environmental and Water Resources Congress; American Society of Civil Engineers: Reston, VA, USA, 2015; pp. 2341–2349. [Google Scholar] [CrossRef]
  13. Georgakakos, A.; Yao, H.; Kistenmacher, M.; Graham, N.; Cheng, F.-Y.; Spencer, C.; Shamir, E. Value of adaptive water resources management in Northern California under climatic variability and change: Reservoir management. J. Hydrol. 2012, 412–413, 34–46. [Google Scholar] [CrossRef]
  14. Ministerio de Medio Ambiente, y Medio Rural y Marino. Instrucción de Planificación Hidrológica (IPH). Orden ARM/2656/2008, de 10 de Septiembre, por la que se Aprueba la Instrucción de Planificación Hidrológica. BOE-A-2008-15340. Madrid, España. 2008. Available online: https://www.boe.es/eli/es/o/2008/09/10/arm2656 (accessed on 14 November 2023).
  15. Ministerio para la Transición Ecológica y el Reto Demográfico (MITECO). Plan Hidrológico de la Parte Española de la Demarcación Hidrográfica del Duero, CHD, 2023. Real Decreto 35/2023, de 24 de Enero, por el que se Aprueba la Revisión de los Planes Hidrológicos de las Demarcaciones Hidrográficas del Cantábrico Occidental, Guadalquivir, Ceuta, Melilla, Segura y Júcar, y de la Parte Española de las Demarcaciones Hidrográficas del Cantábrico Oriental, Miño-Sil, Duero, Tajo, Guadiana y Ebro. BOE-A-2023-3511. Madrid, España. 2023. Available online: https://www.boe.es/eli/es/rd/2023/01/24/35 (accessed on 14 November 2023).
  16. EEA. Water Resources across Europe—Confronting Water Scarcity and Drought; Report Nº 2/2009; Office for Official Publications of the European Communitie: Copenhagen, Denmark, 2009; ISSN 1725-9177. [Google Scholar]
  17. Organización de la Naciones Unidas para la Alimentación y la Agricultura (FAO). Afrontar la Escasez de Agua. Un Marco de Acción para la Agricultura y la Seguridad Alimentaria; Informe sobre temas hídricos; FAO: Roma, Italy, 2013; p. 80. [Google Scholar]
  18. Ministerio de Medio Ambiente (MMA). Libro Blanco del Agua en España; Centro de Publicaciones del Ministerio de Medio Ambiente: Madrid, España, 2000. [Google Scholar]
  19. Pulido Velázquez, M.; Escriva-Bou, A.; Macián Sorribes, H. Balance Hídrico Actual y Futuro en las Cuencas en España, Déficits Estructurales e Implicaciones Socioeconómicas; No. eee2020-38; FEDEA: Madrid, España, 2020; Available online: https://documentos.fedea.net/pubs/eee/eee2020-38.pdf (accessed on 14 November 2023).
  20. Ministerio para la Transición Ecológica y el Reto Demográfico (MITECO). Perfil Ambiental de España 2021. Informe Basado en Indicadores; Resumen Ejecutivo; MITECO: Madrid, España, 2022. [Google Scholar]
  21. Berbel, J.; Expósito, A.; Gutiérrez-Martín, C.; Mateos, L. Effects of the Irrigation Modernization in Spain 2002–2015. Water Resour. Manag. 2019, 33, 1835–1849. [Google Scholar] [CrossRef]
  22. Vogel, R.M.; Sieber, J.; Archfield, S.A.; Smith, M.P.; Apse, C.D.; Huber-Lee, A. Relations among storage, yield, and instream flow. Water Resour. 2007, 43, W05403. [Google Scholar] [CrossRef]
  23. Jaffe, M.; Al-Jayyousi, O. Planning Models for Sustainable Water Resource Development. J. Environ. Plan. Manag. 2002, 45, 309–322. [Google Scholar] [CrossRef]
  24. Loucks, D.P.; van Beek, E. Water resource systems modeling: Its role in planning and management. In Water Resource Systems Planning and Management; Springer: Cham, Switzerland, 2017. [Google Scholar] [CrossRef]
  25. Andreu, J.; Capilla, J.; Sanchís, E. AQUATOOL, a generalized decision-support system for water-resources planning and operational management. J. Hydrol. 1996, 177, 269–291. [Google Scholar] [CrossRef]
  26. Andreu, J.; Solera, A.; Capilla, J.; Ferrer, J. Modelo SIMGES para Simulación de Cuencas. Manual de Usuario v3.0; Universitat Politécnica de Valencia: Valencia, España, 2007. [Google Scholar]
  27. Delft Hydraulics. RIBASIM River Basin Simulation Program Operating Manual and Description; Delft Hydraulics: Delft, The Netherlands, 2004. [Google Scholar]
  28. Danish Hydraulic Institute (DHI). Mikebasin: Operating Manual and Description; DHI: Hørsholm, Denmark, 1997. [Google Scholar]
  29. Raskin, P.; Sieber, J.; Huber-Lee, A. Water Evaluation and Planning System: User Guide for WEAP21; Tellus Institute: Boston, MA, USA, 2001. [Google Scholar]
  30. Sordo-Ward, A.; Bejarano, M.; Granados, I.; Garrote, L. Facing Future Water Scarcity in the Duero-Douro Basin: Comparative Effect of Policy Measures on Irrigation Water Availability. J. Water Resour. Plan. Manag. 2020, 146, 04020011. [Google Scholar] [CrossRef]
  31. Chávez-Jiménez, A.; De Lama, B.; Garrote, L.; Martín-Carrasco, F.; Sordo-Ward, A.; Mediero, L. Characterisation of the sensitivity of water resources systems to climate change. Water Resour. Manag. 2013, 27, 4237–4258. [Google Scholar] [CrossRef]
  32. Granados, A.; Sordo-Ward, A.; Paredes-Beltrán, B.; Garrote, L. Exploring the Role of Reservoir Storage in Enhancing Resilience to Climate Change in Southern Europe. Water 2021, 13, 85. [Google Scholar] [CrossRef]
  33. Paredes-Beltran, B.; Sordo-Ward, A.; de-Lama, B.; Garrote, L. A Continental Assessment of Reservoir Storage and Water Availability in South America. Water 2021, 13, 1992. [Google Scholar] [CrossRef]
  34. Monico, V.; Solera, A.; Bergillos, R.; Paredes-Arquiola, J. and Andreu, J. Effects of environmental flows on hydrological alteration and reliability of water demands. Sci. Total Environ. 2022, 810, 151630. [Google Scholar] [CrossRef]
  35. Aguila, E.; Cardich, R.; Ramos-Fernández, L. Desarrollo y aplicación del modelamiento de calidad del agua con GESCAL-AQUATOOL en el río Lurín-Lima-Perú. Tecnol. Y Cienc. Del Agua 2022, 1–41. [Google Scholar] [CrossRef]
  36. Pardo-Loaiza, J.; Bergillos, R.; Solera, A.; Paredes-Arquiola, J.; Andreu, J. Habitat alteration assessment for the management of environmental flows in regulated basins. J. Environ. Manag. 2022, 319, 115653. [Google Scholar] [CrossRef]
  37. Bianucci, P.; Sordo-Ward, A.; Lama-Pedrosa, B.; Garrote, L. How do environmental flows impact on water availability under climate change scenarios in European basins? Sci. Total Environ. 2023, 911, 168566. [Google Scholar] [CrossRef]
  38. Sulis, A.; Sechi, G.M. Comparison of generic simulation models for water resource systems. Env. Model Softw. 2013, 40, 214–225. [Google Scholar] [CrossRef]
  39. Krysanova, V.; Dickens, C.; Timmerman, J.; Varela-Ortega, C.; Schlüter, M.; Roest, K.; Huntjens, P.; Jaspers, F.; Buiteveld, H.; Moreno, E.; et al. Cross-Comparison of Climate Change AdaptationStrategies Across Large River Basins in Europe, Africa and Asia. Water Resour. Manag. 2010, 24, 4121–4160. [Google Scholar] [CrossRef]
  40. Pedro-Monzonís, M.; Solera, A.; Ferrer, J.; Estrela, T.; Paredes-Arquiola, J. A review of water scarcity and drought indexes in water resources planning and management. J. Hydrol. 2015, 527, 482–493. [Google Scholar] [CrossRef]
  41. Vigerstol, K. Drought Management in Mexico’s Rio Bravo Basin. Master’s Thesis, University of Washington, Seattle, WA, USA, 2002. [Google Scholar]
  42. Hashimoto, T.; Stedinger, J.R.; Loucks, D.P. Reliability, resiliency and vulnerability criteria for water resource system performance evaluation. Water Resour. Res. 1982, 18, 14–20. [Google Scholar] [CrossRef]
  43. Chávez-Jiménez, A.; Gozález-Zeas, D.; Buguña, N.; Martínez, A. The Role of Regulation in Meeting Water Demands under Climate Change. Water Resour. Manag. 2018, 32, 4031–4044. [Google Scholar] [CrossRef]
  44. Wang, T.; You, J.; Ma, Z.; Xiao, P. Water Supply-Demand Situation Analysis Based on a Hierarchical Index System. Water Resour. Manag. 2022, 36, 4485–4498. [Google Scholar] [CrossRef]
  45. Wu, S.-J.; Mai, J.-S.; Lin, Y.-H.; Yeh, K.-C. Modeling Probabilistic-Based Reliability Analysis for Irrigation Water Supply Due to Uncertainties in Hydrological and Irrigation Factors. Sustainability 2022, 14, 12747. [Google Scholar] [CrossRef]
  46. Grigg, N.S. Management framework for large-scale water problems. J. Water Resour. Plan. Manag. 1996, 122, 296–300. [Google Scholar] [CrossRef]
  47. OECD. Sustainable Management of Water Resources in Agriculture; OECD Publishing: Berlin, Germany, 2010; ISSN 22245081. [Google Scholar]
  48. Perveen, S.; James, L.A. Multiscale effects on spatial variability metrics in global water resources data. Water Resour. Manag. 2010, 24, 1903–1924. [Google Scholar] [CrossRef]
  49. Pérez-Foguet, A.; Giné Garriga, R. Analyzing water poverty in basins. Water Resour. Manag. 2011, 25, 3595–3612. [Google Scholar] [CrossRef]
  50. Loucks, D.P.; van Beek, E. Water Resource Systems Planning and Management: An Introduction to Methods, Models, and Applications; Springer: Cham, Switzerland, 2017. [Google Scholar] [CrossRef]
  51. Ministerio de Asuntos Exteriores y de Cooperación. Protocolo de Revisión del Convenio sobre Cooperación para la Protección y el Aprovechamiento Sostenible de las Aguas de las Cuencas Hidrográficas Hispano-Portuguesas y el Protocolo Adicional, Suscrito en Albufeira el 30 de Noviembre de 1998, Hecho en Madrid y Lisboa el 4 de abril de 2008. BOE-A-2010-652. Madrid, España. 2010. Available online: https://www.boe.es/eli/es/ai/2008/04/04/(1) (accessed on 14 November 2023).
  52. Ministerio de Agricultura, Pesca y Alimentación. El Plan Nacional de Regadíos. Ing. Del Agua 1999, 6, 13–26. [Google Scholar] [CrossRef]
  53. Junta de Castilla y León. Programa de Impulso de Infraestructuras Agrarias de Interés General. Regadío en Castilla y León. Instituto Tecnológico Agrario de Castilla y León (ITACyL) Web Site. 2020. Available online: https://www.itacyl.es/ingenieria-rural/programa-impulso (accessed on 14 November 2023).
  54. Ministerio de Agricultura, Alimentación y Medio Ambiente. Plan Hidrológico de la parte española de la Demarcación Hidrográfica del Duero, CHD, 2016. Real Decreto 1/2016, de 8 de Enero, por el que se Aprueba la Revisión de los Planes Hidrológicos de las Demarcaciones Hidrográficas del Cantábrico Occidental, Guadalquivir, Ceuta, Melilla, Segura y Júcar, y de la Parte Española de las Demarcaciones Hidrográficas del Cantábrico Oriental, Miño-Sil, Duero, Tajo, Guadiana y Ebro. BOE-A-2016-439. Madrid, España. 2016. Available online: https://www.boe.es/eli/es/rd/2016/01/08/1/con (accessed on 14 November 2023).
  55. Ministerio para la Transición Ecológica y el Reto Demográfico. Esquema de Temas Importantes de la Parte Española de la Demarcación Hidrográfica del Duero. Resumen Ejecutivo. Tercer Ciclo de Planificación Hidrológica. Confederación Hidrológica del Duero (CHD) Website. 2020. Available online: https://www.chduero.es/esquema-temas-importantes (accessed on 14 November 2023).
  56. EROS, USGS. HYDRO1k Elevation Derivative Database; Tech. Rept.; U.S. Geological Survey Centre for Earth Resources Observation and Science (EROS): Garretson, SD, USA, 2008. [Google Scholar]
  57. ICOLD. World Register of Dams, WRD (World Register of Dams/Registre Mondial des Barrages). 2018. Available online: https://www.icold-cigb.org/GB/publications/world-register-of-dams.asp (accessed on 23 June 2022).
  58. Estrela, T.; Quintas, L. El sistema Integrado de Modelización Precipitación-Aportación SIMPA. Ing. Civ. 1996, 104, 43–52. Available online: https://ingenieriacivil.cedex.es/index.php/ingenieria-civil/article/view/1153 (accessed on 14 November 2023).
  59. Confederación Hidrográfica del Duero O.A. Anejo 2. Inventario de Recursos Hídricos Naturales. 2022. Available online: https://www.chduero.es/documents/20126/1883851/PHD22-27_020_00_InvRecHid-v09+%281%29.pdf/e3d71f24-06c3-5d1e-3fe9-dfb89ebf086b?t=1666613983463 (accessed on 12 December 2023).
  60. Ministerio para la Transición Ecológica y el Reto Demográfico. Evaluación De recursos Hídricos en Régimen Natural en España (1940/41–2017/18). Modelo SIMPA. 2019. Available online: https://www.miteco.gob.es/content/dam/miteco/es/agua/temas/evaluacion-de-los-recursos-hidricos/cedex-informeerh2019_tcm30-518171.pdf (accessed on 14 November 2023).
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Figure 1. General scheme of the proposed methodology.
Figure 1. General scheme of the proposed methodology.
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Figure 2. Area of study with its water management scheme in WAAPA. The 7 sub-basins considered in this study are represented by white colors. The triangles represent reservoirs, the dots represent nodes, and the lines represent rivers.
Figure 2. Area of study with its water management scheme in WAAPA. The 7 sub-basins considered in this study are represented by white colors. The triangles represent reservoirs, the dots represent nodes, and the lines represent rivers.
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Figure 3. Inputs and main characteristics considered for this study mapped by sub-basin: area (A); mean annual flow (F); storage volume (V); and surface irrigation demand (SID).
Figure 3. Inputs and main characteristics considered for this study mapped by sub-basin: area (A); mean annual flow (F); storage volume (V); and surface irrigation demand (SID).
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Figure 4. Evolution of mean annual flow along the axis of the Duero.
Figure 4. Evolution of mean annual flow along the axis of the Duero.
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Figure 5. Profiles of reservoir volume (V) in hm3, volume available for irrigation (PWA) in hm3/yr, and volume of surface water irrigation demand (SID) in hm3/yr, along the axis of the Duero.
Figure 5. Profiles of reservoir volume (V) in hm3, volume available for irrigation (PWA) in hm3/yr, and volume of surface water irrigation demand (SID) in hm3/yr, along the axis of the Duero.
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Figure 6. Spatial distribution of the variables used in this study. Accumulated values are plotted. Input data for the WAAPA model: (a) mean annual flows, F, in hm3/yr; (b) storage volume, V, in hm3/yr. Output data from the WAAPA model: (d) potential water availability, PWA, in hm3/yr. Contrast variable: (c) surface irrigation demand, SID, in hm3/yr.
Figure 6. Spatial distribution of the variables used in this study. Accumulated values are plotted. Input data for the WAAPA model: (a) mean annual flows, F, in hm3/yr; (b) storage volume, V, in hm3/yr. Output data from the WAAPA model: (d) potential water availability, PWA, in hm3/yr. Contrast variable: (c) surface irrigation demand, SID, in hm3/yr.
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Figure 7. Graphical analysis of the short-term sustainability of accumulated demands in the Duero River. Vulnerable reaches, where PWA is less than SID, are represented in red (1); and the non-vulnerable reaches, where PWA is greater than or equal to SID, are represented in blue (0).
Figure 7. Graphical analysis of the short-term sustainability of accumulated demands in the Duero River. Vulnerable reaches, where PWA is less than SID, are represented in red (1); and the non-vulnerable reaches, where PWA is greater than or equal to SID, are represented in blue (0).
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Figure 8. Graphical representation of the possibilities for improving the short-term sustainability of irrigation demands in the Duero basin. Negative values (in blue) indicate no problems with the short-term sustainability of irrigation demands. Positive values (colored according to scale) estimate the percentage of natural resources to mobilize to solve the short-term sustainability problems of irrigation demands.
Figure 8. Graphical representation of the possibilities for improving the short-term sustainability of irrigation demands in the Duero basin. Negative values (in blue) indicate no problems with the short-term sustainability of irrigation demands. Positive values (colored according to scale) estimate the percentage of natural resources to mobilize to solve the short-term sustainability problems of irrigation demands.
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Figure 9. Graphical representation of the level of use of natural resources in the Duero basin using the value of the Usage Index (IU) in the event that the demands are completely satisfied.
Figure 9. Graphical representation of the level of use of natural resources in the Duero basin using the value of the Usage Index (IU) in the event that the demands are completely satisfied.
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Figure 10. Graphical representation of possible critical areas in the Duero basin. In green (with a value of one) are the areas in which IS > 0 and IU < 0.5.
Figure 10. Graphical representation of possible critical areas in the Duero basin. In green (with a value of one) are the areas in which IS > 0 and IU < 0.5.
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Table 1. Annual mean values of precipitation (PRE), potential evapotranspiration (PET), actual evapotranspiration (RET), soil moisture (SM), infiltration (INF), underground runoff (URUN), surface runoff (SRUN), and total input (F) of the Spanish part of the Duero river basin (1940/41-2017/18).
Table 1. Annual mean values of precipitation (PRE), potential evapotranspiration (PET), actual evapotranspiration (RET), soil moisture (SM), infiltration (INF), underground runoff (URUN), surface runoff (SRUN), and total input (F) of the Spanish part of the Duero river basin (1940/41-2017/18).
AreaPREPETRETSMINFURUNSRUNF
km2mm/yrmm/yrmm/yrmm/yrmm/yrmm/yrmm/yrhm3/yr
77,14557688543047082816411,186
Table 2. Main hydrological and hydraulic characteristics of the sub-basins examined in this study.
Table 2. Main hydrological and hydraulic characteristics of the sub-basins examined in this study.
Sub-BasinArea
km2		Mean Annual Flow
hm3/yr		Storage Volume
hm3		Surface Irrigation Demand
hm3/yr
Esla17,45145451393974
Pisuerga17,3712241583543
Upper Duero12,9361221293258
Adaja78843778553
Lower Duero77389206188
Tormes7386893505219
Águeda620647913511
Table 3. Main numerical results of the sub-basins considered in this study. They are global results.
Table 3. Main numerical results of the sub-basins considered in this study. They are global results.
Sub-BasinMean
Annual Flow F
hm3/yr		Storage
Volume
V
hm3		Surface
Irrigation Demand SID
hm3/yr		Potential Water Availability PWA
hm3/yr		IUIPIS
Esla4545139397413870.791.42-
Pisuerga22415835435210.760.960.01
Upper Duero12212932582060.790.800.04
Adaja3778553920.861.74-
Lower Duero9206188350.800.190.17
Tormes8935052194350.751.99-
Águeda479135111360.9812.36-
Table 4. Value of improvement in sustainability of demands index (IS) and usage index (IU) in potentially critical areas for meeting irrigation demands.
Table 4. Value of improvement in sustainability of demands index (IS) and usage index (IU) in potentially critical areas for meeting irrigation demands.
Sub-BasinTributaryISIU
EslaJamúz0.2–0.40–0.25
PisuergaEsgueva0.6–0.80.25–0.50
Upper DueroRiaza0.2–0.40.25–0.50
Lower DueroZapardiel0.6–0.80.25–0.50
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Lama-Pedrosa, B.; Sordo-Ward, Á.; Bianucci, P.; Garrote, L. Sustainability of Duero Water Systems for Crop Production in Spain. Sustainability 2024, 16, 242. https://0-doi-org.brum.beds.ac.uk/10.3390/su16010242

AMA Style

Lama-Pedrosa B, Sordo-Ward Á, Bianucci P, Garrote L. Sustainability of Duero Water Systems for Crop Production in Spain. Sustainability. 2024; 16(1):242. https://0-doi-org.brum.beds.ac.uk/10.3390/su16010242

Chicago/Turabian Style

Lama-Pedrosa, Beatriz, Álvaro Sordo-Ward, Paola Bianucci, and Luis Garrote. 2024. "Sustainability of Duero Water Systems for Crop Production in Spain" Sustainability 16, no. 1: 242. https://0-doi-org.brum.beds.ac.uk/10.3390/su16010242

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