Introducing the Circularity Index for Dams/Reservoirs (CIDR)

Abstract

The world currently faces significant hydrologic changes associated with global climate change, such as changes in precipitation patterns, rising surface temperature, and increases in the frequency and intensity of floods and droughts, which will affect the design capacity and operating characteristics of dams/reservoirs. This brings new challenges to current water management strategies. This research is aimed to create, apply, and provide a novel indicator named Circularity Index for Dams/Reservoirs (CIDR) that allows the determination of the water circularity level on the dual dam/reservoir system; that is to evaluate the water efficiency levels and the circular water flows for the processes at a site. This new method has hydrological, economic, and environmental variables as well as social ones. This indicator is defined as the sum of the scores of the eleven indicators comprising the model multiplied by the weight. The method has been implemented giving the same weight for each indicator. It has been successfully applied in the 18 dam/reservoir systems managed by the Duero River Basin, located in the region of “Castilla y León” (Spain). The CIDR provides maximum information in a single indicator value ranging from 0 to 55. A higher value of CIDR indicates a better practice of water circularity management. The results probe the increased utility of the index and suggest that six dams/reservoirs present high circularity of water flow.

1. Introduction

Throughout human history, dams/reservoirs have served to increase the discharge of low flows to ensure adequate water supply services, irrigation, recharge of groundwater, pollution abatement, wildlife conservation, industrial use, recreation, storing water in times of surplus, hydropower and releasing it in times of shortage [1,2,3]. Mitigating floods and making a significant contribution to the efficient management of limited water resources that are unevenly distributed and subject to large seasonal fluctuations [4,5] are key contributions of dams/reservoirs. Economic growth, human habits, unsustainable use of water resources, and global population growth come together to make water a limited and scarce resource in both quantity and quality. This is leading to planet Earth facing a global water crisis that is threatening environmental sustainability [6]. Therefore, despite having a more advanced water management system, the world is experiencing a serious water crisis. Global environmental change has increasingly affected water quality and availability worldwide. This has meant that in some places where there is less availability of this resource, its circularity, the optimization of its use, as well as its reuse, have been promoted. Increasing urbanization and rapid depletion of resources have forced authorities to shift from a traditional linear system of take–make–use–dispose to a circular system of resource conservation [7]. Wastewater reuse is an alternate water supply to increasing water demand in water-scarce regions; however, its tremendous potential has not been recognized in many areas of the world. Therefore, water is a critical resource for the global economy, and it is currently trying to find its place within the emerging concept of the circular economy (CE).

CE in the water sector has been of great interest in recent years due to the imbalance of water resources and the linear approach prevailing in this sector of the take, use, and discharge of water [8,9,10]. This concept was introduced by Pearce and Turner [11] in “Economics of Natural Resources and the Environment”, although the concept has deep roots dating back to the 1960s. The core ideas of CE are the elimination of waste by design, respect for the social, economic, and natural environment, and resource-conscious business conduct [12]. The CE aims to eliminate waste and pollution, circulate products and materials, and regenerate nature, but what about water? There is no consensus in the literature on the concept of the CE of water, the terminology is ambiguous, changing, and developing. However, water in the environment follows a natural circular model that secures water resources by regulating water flow and ensuring water quality. In a study conducted by Morseletto et al. [13], the CE for water is defined as an economic framework for reducing, preserving, and optimizing water use through waste avoidance, efficient use, and quality retention, while ensuring environmental protection and conservation. They identify nine strategies for the CE of water: rethink, avoid, reduce, replace, reuse, recycle, cascade, store, and recover [14,15]. In this respect, and focused on the sustainable use of hydropower, an internationally interesting standard has emerged, called the Hydropower Sustainability Standard, developed by the international non-governmental organization International Hydropower Association [16]. This standard proposes an evidence-based methodology to certify the sustainability of hydropower projects in a comprehensive and transparent manner. This standard considers twelve parameters grouped into environmental, social, and governance aspects at two performance levels: good practice (minimum requirements) and best practice (advanced requirements).

Water management is becoming a global issue requiring new approaches to financing and resource management. The scientific community strongly advises the adoption of indices and indicators for improving circularity, water resources management, and progress toward sustainable development [17,18,19]. For this purpose, the need to improve the management of water generated in headwaters has led to the construction of dams/reservoirs to enable the synchronization of water demand and the timing of runoff production [20]. However, there is a huge controversy because an important part of the scientific and technical community considers that the construction of dams and reservoirs affects biodiversity in river ecosystems due to, among others, the induced changes in the natural flow regimes [21,22,23,24].

The state of the art on indexes and their methodologies is very broad. United Nations Human Development Index (HDI), Human Poverty Index (HPI), and the Social Sustainable Aquifer Yield [25] are among the best-known examples. An aggregation of a set of indicators that represent the different dimensions of a phenomenon to be measured is called a composite index [26]. These indicators are like a mathematical model which provides an overall view of a set of partial indicators. The value of these indicators lies in their ability to synthesize information and provide a useful tool for decision-making [27]. The idea of summarizing complex phenomena in single numbers is a complex task and therefore there is no part of the composite index construction that cannot be challenged [28].

This paper contributes to the previous literature by proposing a novel index, based on water as a resource, named “Circularity Index for Dam/Reservoir (CIDR)” to assess, monitor and improve the circularity of dams/reservoirs. This is conducted through an additive approach that considers the circular perspective of the water, and its effects on the environment, economy, society, and hydraulic infrastructures.

This research is presented in five sections; this section (Introduction) briefly correlates circularity and water management in dams/reservoirs; next, the methodology is described followed by a description of the case study; finally, the results obtained are shown and discussed as well as the general conclusions from the study are outlined.

2. Methodology

The creation/definition of this novel and quantitative index for the Dam/Reservoir Circularity, denoted as CIDR, is defined as a methodological process in five steps.

2.1. Step 1: Theoretical Framework

The decisions on the evaluation and improvement of the circularity of dams and reservoirs are often complicated, multifaceted, and involve a variety of stakeholders with different objectives. This makes it necessary to propose additional assessment and evaluation methods, techniques, and tools. Those new developments have been proposed in an attempt to assist in decision-making and adequately respond to severe problems that mainly affect the water circularity largely to achieve an improvement in the efficiency of dams and reservoir operation. In this regard, the use of multi-criteria methods is an appropriate way to solve these problems and improve the decision-making process [29].

Multi-criteria analysis (MCA) is also known as multiple-criteria decision analysis (MCDA), multicriteria decision-making (MCDM), multi-dimensional decision-making (MDDM), or multi-dimensional decision-making (MDDM). Therefore, MCA is not a single specific method but envelops a high number of methods accounting for multiple decision criteria and objectives in the analysis of a problem. Given the deep variety of MCA, methods developed over the years, choosing which of the many multicriteria methods to use is complex. They have certain aspects in common in terms of (1) addressing an observed problem and reaching an overall end result, (2) considering different valuation dimensions, and (3) coefficient, which is commonly intended to represent the level of importance of a corresponding criterion relative to the other criteria under consideration which are named criterion weight. However, they differ in other aspects, such as (a) the approach taken (priori, progressive methods), (b) the assumed form of multicriteria preference function (additive, nonadditive, nonlinear), and (c) the type of question used to obtain preferences and judgments.

In this study, the simple additive model (SAW) method, which is known as the weighted summing method, has been selected due to its simplicity, less data requirement, and any provision to subjectively provide weights for the multiple criteria. At the same time, the disadvantage of SAW is that it requires the decision-maker to determine the importance of each indicator. This method is based on conducting the analysis with global scores, calculated as the sum of the single performance scores, which are performance ratings on each alternative on all indicators. An evaluation score is calculated for each alternative by multiplying the value given to the alternative of that indicator by the weights of relative importance directly assigned by the decision-maker, followed by a summing of the products for all criteria [30]. The criteria used in the selection of the weights in the research are multiple, such as weights that could be derived from past decisions regarding problems similar to the decision-making situation in question [31].

2.2. Step 2: Selection of Most Representative Indicators

To evaluate the circularity of dam/reservoir water flow, 11 indicators have been selected, using data at the local level in 18 dam reservoirs. In order to normalize and standardize the scores’ values, these indicators are evaluated on a scale of 1–5, where 1 is the lowest, and 5 is the highest. However, some indicators’ scores are contrary. The CIDR was constructed by combining hydrological, economic, environmental, and social variables. The variables selected are as follows:

• Average historical dam capacity (AHDC): It is defined as the volume of water which is enclosed within the boundaries of dam and another natural frontier. It is needed for flow regulation, and it is a nonrenewable resource because this capacity is steadily being lost to sedimentation.

• Initial construction cost (ICC): Principal quantity to use for the cost estimate of the dam is calculated taking into account preparatory works, diversion works, permanent works (excavation, concrete work, artificial plug, temporary equipment, road works, disposal area, and dam outlet and electric power gate. According to Petherram and McMahon [32] ICC is expressed as:

(1)$ICC=\frac{\left(\mathrm{223,934}\times {SURFACE}^{-0.598}\right)\times TOTAL CAPACITY\times 1000\times 0.66)}{\mathrm{1,000,000}}$

(The surface is expressed in ha × 10).

Since not all of these initial costs are known, their determination has been based on the above formulation. In the case that all of them are known, the proposed methodological approach allows the use of such actual value.

• Demand satisfaction (DS): This parameter is closely related to average historical dam capacity of dam/reservoir, as well as drought protection through rules for the operation of the reservoir. In general terms, the Duero River basin has maintained acceptable values of water resources availability with high AHDC values, and consequently, DS degree is also quite high. This behavior radically contrasts with south-eastern areas in Spain, which are clearly deficient.

• Risk caused (RC): There are many different sources of risk accomplice with dam’s reservoir. Risk exposure comprises different types of dam reservoir-related risks, including those to infrastructure, population, or resources. The risk can be to the dam itself and it can be residual risk.

• Expected economic benefits (EEB): A dam and reservoir may be used for a variety of activities such as flood control, water supply, irrigation, navigation, and recreation, with each benefit providing significant economic impacts on a local, national, regional, and local level.

• Ecological impact (EI): Dams/reservoirs are one of the most critical human interventions in the hydrological cycle and have harmful effects on the environment, as they disrupt natural ecological processes both upstream and downstream. They can alter river ecosystems, negatively impact biodiversity, cause physical and chemical changes that influence aquatic biota in a variety of ways, and modify the climate in their vicinity.

• Hydromorphological alteration (HA): This indicator is mainly based on the Water Framework Directive 2000/60/EC, under a threefold legal–scientific–management perspective. This one comprises the functional quality of the river system that in turn comprises naturalness of the flow regime, sediment availability, and floodplain functionality. On the other hand, the quality of the riverbed is assessed through continuity, naturalness of the bed, and longitudinal–lateral mobility, which comprises naturalness of layout. Final score is grouped into five labeled categories: very good (75–90), good (60–74), moderate (42–59), poor (21–41), and very bad (0–20).

• Silting risk and watershed erosion (SR_WE): It is necessary to monitor the reservoirs’ silting. The results of these controls would serve to analyze the deviations with respect to what was foreseen in the project phase, obtain more precise forecasts on the degree and rate of silting, and adopt the most appropriate preventive and mitigation measures. Among the effects of reservoirs’ silting, the following can be highlighted loss of water storage capacity and sediment retention in reservoirs with associated natural resource loss.

Given that sedimentation mitigation measure is not a matter of this research, the reader is referred to Schleiss et al. [33], where an exhaustive state-of-the-art and the main scientific advances in terms of prevention and mitigation measures against sedimentation in reservoirs are shown.

• Contamination risk (CtR): Dams/reservoirs are especially at risk of contamination by different contaminants from anthropogenic sources since a change in the sediment regime often occurs. Depending on the morphology and hydrological conditions, suspended particles with associated contaminants can settle and become part of the bottom sediments.

• Social perception (SP): Dam reservoirs affect the local population. There are several factors that influence how people who live in the proximity of dams view them. The key factors are economics, compensation for lost property, distance between people’s houses, and the dam structure.

• Flood mitigation (FM): The lamination of the avenues is one of the important effects of the dams with their reservoirs. The implementation of actions is required to reduce or eliminate the long-term risk of flood damage to dam infrastructure. Flood mitigation is an indicator that compares the laminated volume with the useful volume (dam/reservoir capacity). The score is grouped in five numerical equal intervals from 0 to 25 points, with the range 0–5 categorized as 1 and the range 20–25 as 5.

2.3. Step 3: Normalizing and Imputation of Missing Data

Normalization is required to make the indicators comparable when they have different measurement units, which consists of putting the different variables on the same scale. In this case, transformation of the data is not necessary, as each of the indicators evaluates the circularity of each dam reservoir on the same scale of 1–5.

There are no missing data in this study, the data were selected with the requirement that their values were all complete. Therefore, the data imputation phase is not necessary.

2.4. Step 4: Weighting

This step involves assigning weights to each of the indicators, according to the researcher’s criteria and according to the individual relevance of each variable in the set.

Since this is a starting point for a real application of CE on a real water system (dam/reservoir), this study set up a so-defined equal criteria set where all indicators of Dam/Reservoir Circularity are equally weighted.

2.5. Step 5: Aggregation—CIDR Index Definition

This final step is probably the most important stage in this research. It consists of the combination of all indicators in order to define CIDR index. In this research, it is considered MCA techniques, which are greatly suitable when working from a multidimensional approach. Therefore, CIDR index is defined as the sum of the scores of the indicators comprising the model multiplied by the weight:

(2)$\mathrm{C}\mathrm{I}\mathrm{D}\mathrm{R}=\sum _{\mathrm{i}=1}^{\mathrm{n}}({\mathrm{w}}_{\mathrm{i}}\times {\mathrm{I}\mathrm{n}\mathrm{d}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{t}\mathrm{o}\mathrm{r}}_{\mathrm{i}})$

where “n” is the total number of indicators, in this case, 11. This phase considers the same individual weight assigned to each variable. The main flowchart used to construct the CIDR is displayed in Figure 1.

With this data structure, the CIDR was created. It is designed in order to satisfy the following properties: (1) a specific unit of measurement criterion that eliminates both the unit of measurement and the effect of variability (2) synthesis independent of an “ideal unit”, since a set of “optimal values” is arbitrary, non-univocal and can vary with time (3) simple and easy to interpret.

3. Case Study

The design of the CIDR index that synthesizes the circularity of water in dam/reservoir systems requires the development of a set of theoretical and practical steps that must be applied to real data. In this sense, a total of 18 dam/reservoir systems, all belonging to and managed by the Duero River Basin (DRB) Authority, have been selected (Figure 2). Then, the main characteristics of these systems are described according to MITECO [34].

• Águeda system: It is located in the province of Salamanca, was completed in 1931 and its fundamental mission is to regulate the waters of the river that gives it its name. However, this task has proved to be practically impossible due to the low capacity of the reservoir, which with its 22 million cubic meters can barely retain the water it receives. The Águeda dam/reservoir, the so-called gravity type, has a height on foundations of 37.60 m and a length of 195.70 m at the crest.

• Aguilar de Campo system: It was commissioned in 1964 and is located in the province of Palencia. With a capacity of 247 million cubic meters, it plays a fundamental role in the regulation of the Pisuerga River. This infrastructure is part of a set of three reservoirs (together with “Cervera” and “La Requejada” reservoirs), whose main mission is to collect and control the waters. The dam that closes this reservoir has a height of 48 m counted from the foundations and a length of half a kilometer, which makes it one of the longest in the basin.

• Arlanzón system: It is one of the smallest in the DRB, and can only store 22 million cubic meters. The construction of the Arlanzón dam/reservoir was completed in 1933 and nowadays, in addition to regulating the river together with the Úzquiza reservoir, with which it forms a functional unit, the two together supply drinking water to Burgos and other smaller towns, allowing the irrigation of some 3500 hectares, as well as serving various industrial uses. The dam/reservoir is one of those known as curved gravity dams, with a height on foundations slightly higher than 47 m.

• Barrios de Luna system: It was put into service in 1956 and its main purpose is flow regulation. From the reservoir being turbined in its entirety between the mini-hydroelectric plant at the foot of the dam and that of “San Isidoro”, in Mora de Luna, being retained several kilometers downstream in the Selga de Ordás counter reservoir, whose function is to regulate and divert water to the Main Canal of the Órbigo, dedicated to the transport of water for irrigation, supplying the city of León and obtaining electrical energy.

• Camporredondo system: It stores 70 million cubic meters of water, and in addition to regulating the river, it creates an irrigation area that is of great importance for the economy of a large territory in the provinces of Palencia and Valladolid, which, thanks to the water, has changed over the years its traditional rainfed crops for more profitable ones, such as sugar beet, corn or alfalfa. It is one of the so-called curved gravity dams and for its construction, more than 172,000 cubic meters of cyclopean concrete were used.

• Castro de las Cogotas system: It is so named because it was built next to a Celtic “castro” in the province of Ávila, whose capital is just over 15 km away. The dam/reservoir collects the waters of the Adaja River, allowing the irrigation of an area of about 8000 hectares. It is also responsible for supplying drinking water to several towns in the provinces of Avila and Valladolid. It was completed in 1994, and is of the so-called double-curvature vault type, with a length of almost 300 m and a height of 66 m from the foundations.

• Cervera system: It began to provide service in 1923 and, in its origins, its fundamental mission was to secure the waters of the “Canal de Castilla”, a task later shared with other more modern ones. With a capacity of 10 million cubic meters, it is the smallest of all, with the exception of El Pontón Alto. It is a curved gravity dam with a height of just over 30 m above the riverbed and measures 130 m long. Some 40,000 cubic meters of concrete were used during its construction.

• Compuerto system: It is defined by the “Compuerto” reservoir Carrión River. This one came into service in 1960. This reservoir stores 95 million cubic meters of water, which, together with that of Camporredondo, guarantees the irrigation of some 50,000 hectares. The reservoir is part, together with Camporredondo and three others on the Pisuerga River of the so-called “Ruta de los Pantanos”. The Compuerto dam presents a typology of straight gravity dams where more than 260,000 cubic meters of concrete were used for its construction.

• Cuerda del Pozo system: It is located in the province of Soria and is the only one that regulates the Duero River at its headwaters. It is able to attract, a large number of tourists who enjoy the beaches created along its coast. It has a height of 36 m and a length of 425 m. Its dam/reservoir capacity, with 249 million cubic meters, places it among the six largest of all those built by the State in this hydrographic basin. It supplies drinking water to Soria and serves to irrigate 26,000 hectares up to its confluence with the Pisuerga River.

• Irueña system: The main purpose of this reservoir, which has a capacity of 110 million cubic meters, is to regulate the Águeda River and thus prevent the floods, which cyclically affect part of the city of Ciudad Rodrigo. It rises very close to Portugal and is 133 km long. The Irueña dam takes its name from an old Celtic castro, is very Romanized, and according to several historians was inhabited until the end of the Middle Ages. This castro is 30 m above the waters of the new reservoir.

• Linares de Arroyo system: It has the fundamental mission of regulating the waters of the Riaza River. With a capacity of 58 million cubic meters, it is the largest of all those regulating the Riaza and Duratón rivers and the largest of all those built in the province of Segovia. It is formed by a straight gravity dam, with a crest length of more than 100 m and a height of about 30 m from the riverbed. The construction of the dam/reservoir was completed in 1951 and, during the same year, more than 52,000 cubic meters of concrete were used.

• Pontón Alto system: The Pontón Alto dam/reservoir, in the Eresma River, has the smallest capacity of all those managed by the DRB Authority since it slightly exceeds 7 million cubic meters. Completed in 1993, its purpose is exclusively to supply water to the city of Segovia and other neighboring towns. For the construction of this reservoir, which occupies 80 hectares, a dam of the so-called double-curvature vault type has been built, measuring 48 m high from the foundations.

• Porma-Esla system: It was put into service in 1968. Formed by a gravity dam about 75 m high above the riverbed, it can store more than 300 million cubic meters of water. This reservoir plays a fundamental role in reducing the risk of numerous floods in the lands located hundreds of kilometers downstream. The dam/reservoir is more than 250 m long at its crest and about 345,000 cubic meters of concrete were used to build it. Due to this reservoir, it is possible to irrigate about 45,000 hectares.

• La Requejada system: “La Requejada” dam/reservoir is part of the trio of reservoirs that regulate the plentiful Pisuerga River. The three reservoirs together are capable of storing more than 322 million cubic meters of water, 65 of which remain in this one of “La Requejada”. Among the most significant characteristics of this river, it is worth mentioning that it is one that lends its waters to the “Canal de Castilla”, a very important work of civil engineering that was intended to provide an outlet for the agricultural products of the Castilian plateau to the sea in Cantabria. The dam is of the gravity type with a curved ground plan, has a height on foundations of about 60 m, and a length of 200 m.

• Riaño system: It is the largest of all the reservoirs built in the DRB. Its capacity, over 650 million cubic meters of water, is sufficient to guarantee the irrigation of 80,000 hectares located mainly in the province of León. The concrete wall which, is in the form of a vault is 337 m long and rises almost 100 m from the ground. The Riaño reservoir has more than 100 km of coastline and in its waters can be practiced, in addition to fishing, a wide variety of water sports.

• Santa Teresa system: It is the second largest (after Riaño) of all those built by the State in the DRB, with a volume of 496 million cubic meters. Located in the south of the province of Salamanca, it fulfills a fundamental mission in the regulation of the Tormes River. The dam that forms it was finished in the year 1960 and is the so-called straight gravity dam with a height of 60 m above the foundations and a length of more than half a kilometer. This reservoir allows the irrigation of some 65,000 hectares, as well as guaranteeing the supply of drinking water to numerous localities, including the city of Salamanca.

• Úzquiza system: It is a dam/reservoir of the so-called “loose materials” type, which means that it has been built with selected earth, with hardly any concrete used. It serves to regulate the Arlanzón River, and it has the important task of guaranteeing the supply of drinking water to the city of Burgos. It also makes possible the irrigation of 3500 hectares, as well as serving various industrial uses. It came into operation in 1989 and has a height on foundations of 65 m and a dam of 460 m long, with which it has been possible to close a reservoir with a capacity of 75 million cubic meters.

• Villameca system: It is one of the smallest state-owned ones in the Duero River Basin (DRB). Located in the northern zone (province of León), it only stores 20 million cubic meters of water. The beginning of the works took place in the decade of the 1930s of the last centuries and it was put into service in 1947. The straight gravity dam has a height of 31 m, a length of 173 m, and a thickness of 3.20 m at the top.

4. Results

4.1. Individual Values per Indicator

4.1.1. Average Historical Dam/Reservoir Capacity (AHDC)

The AHDC of the dam/reservoir has been calculated as the relationship between the average volume of the dam/reservoir in the previous ten years and its total capacity. The AHDC indicator is expressed in hm3 units. The mean value and standard deviation were 4.83 ± 0.38. The median value and interquartile range were of 5.00 for both statistics and the coefficient of variation of 0.08. Of the 18 studied dams/reservoirs, 15 (83.33%) have an AHDC equal to 5, and 3 (16.67%) have a value of 4. This indicates that the dams/reservoirs are continuing to be in good condition, since after a long period of dam operation, it is often necessary to assess the current storage.

4.1.2. Initial Construction Cost (ICC)

The achieved values vary within a minimum of 1 and a maximum of 5. The results obtained have an average value and a standard deviation of 2.22 and 0.59, respectively. The median value is 2, lower than the average. The 25th percentile is 1.00 and the 75th percentile has a value of 3.25.

The highest value for this indicator is 5 corresponding to the Riaño dam/reservoir and the lowest value to the Águeda, Arlanzón, Cervera, “Linares de Arroyo”, “Castro de las Cogotas” and Villameca dams/reservoirs.

4.1.3. Demand Satisfaction (%) (DS)

The values vary within a minimum of 4 in the Aguilar, Irueña, and La Requejada dams/reservoirs and a maximum value of 5 in all other dams/reservoirs studied. The results have an associated average and a standard deviation of 4.83 and 0.38, respectively. The median value and 25th–75th percentile is 5. The mean value is lower than the median. The coefficient of variation is 0.09.

4.1.4. Risk Caused (RC)

The RC has been calculated based on the new classification according to the potential risk of the infrastructure. The calculated RC has the values of 1 in 18 dams/reservoirs studied. Therefore, all dams of the Douro River are classified as type A, i.e., with high potential risk meaning that their failure could result in loss of life. There is a direct correlation between this classification and the cost induced by its collapse.

4.1.5. Expected Economic Benefits (EEB)

The EEB indicator has been calculated according to the uses of irrigation, water supply, regulation, electricity industry, defense against avenues, and recreation of dam/reservoir. The values vary within a minimum of 1 and 5. Of the 18 dams/reservoirs studied, 4 of them (22.22%) present an EEB with the highest values of 5 in Aguilar, Camporredondo, Compuerto, and “La Requejada” dams/reservoirs and a value of 1 in Pontón Alto dam/reservoir.

The results obtained have a mean and standard deviation of 3.39 ± 1.09 with a coefficient of variation of 0.32. The median value is 3, lower than the average. The 25th and 75th percentiles have a value of 3.00 and 4.25, respectively.

4.1.6. Ecological Impact (EI)

The values vary between a minimum of 2 and a maximum of 5. The results obtained have a mean and standard deviation of 3.78 and 0.65, respectively, with a coefficient of variation of 0.17. The median value is 4 and the interquartile range is 3.75–4.00. Of the 18 dams/reservoirs studied 14 (77.78) present an EI higher than 3. The EI has a value of 2 in the Úzquiza dam/reservoir, and 3 in the dams/reservoirs of Pontón Alto, Linares de Arroyo, and Riaño. The Aguilar dam/reservoir has a value of 5 and the rest of them present a value of 4.

4.1.7. Hydromorphological Alteration (HA)

The results of the hydromorphological alteration vary within a minimum of 2 and a maximum of 5. The HA has a mean and standard deviation of 3.44 and 0.71, with a median value of 3.00. The interquartile range is 3.00–4.00 and the coefficient of variation is 0.21.

The HA has a value of 5 in the Villameca dam/reservoir and 2 in the Arlanzón dam/reservoir.

4.1.8. Silting Risk and Watershed Erosion (SR_WE)

The values vary within a maximum of 2 in 3 dams/reservoirs (Aguilar, Irueña, and La Requejada), and in the rest, they have a minimum value of 1. The results achieved show a mean and deviation standard of 1.17 ± 0.38. The median and 25th–75th percentiles statistics have values of 1.00 and a coefficient of variation of 0.32. The average is higher than the median value in this indicator.

4.1.9. Contamination Risk (CtR)

The values vary within a minimum of 2 in several dams/reservoirs (Águeda, Barrios de Luna, Cervera, Cuerda del Pozo, Riaño, Pontón Alto, and Úzquiza), and a maximum value of 4 in Aguilar, Compuerto, La Requejada, and Villameca dams/reservoirs. The mean is 2.83 and the standard deviation is 0.79 with a variation coefficient of 0.28. The median value is 3.00, lower than the average. The interquartile range is between 2.00 (25th) and 3.25 (75th).

4.1.10. Social Perception (SP)

The SP means and standard deviations in the results found are as follows 4.28 ± 0.99 and median (interquartile range: 75th–25th) 5.00 (3.75–5.00). The variation coefficient takes the value of 0.22. The values of this indicator range between 2 and 5. Of the 18 dam/reservoir studies 4 (22.22%) present an SP between 2 (Villameca dam/reservoir) and 3 (Santa Teresa, Linares of Arroyo, and Arlanzón dams/reservoirs).

4.1.11. Flood mitigation (FM)

The values have an associated average and a standard deviation of 2.78 ± 1.52 and a mean of 2.78 and the 25th percentile and 75th percentile have a value of 2.00 and 5.00. The dams/reservoirs with the highest values, i.e., out of 5 represent 22.22% and they are Águeda, the Requejada, Castro de las Cogotas, and Úzquiza. The value is lower with the value of 1 corresponding to the Arlanzón, Compuerto, and Irueña dams/reservoirs.

4.2. Total CIDR Index Score

The results summarized in Figure 3 reveal important differences between the different dams/reservoirs. They have a minimum of 29 in the dams/reservoirs of Arlanzón and a maximum of 39 in the Aguilar dam/reservoir. The average and the deviation standard of this index is 34.33 ± 2.59. The median and interquartile ranges have a value of 35 and 3.25 (75th–25th: 36.00–32.75), respectively.

There are 3 dams/reservoirs (16.67%) with a value lower than percentile 25, that is the case of Arlanzón with 89 years, Linares de Arroyo with 71 years, and Pontón alto with 30.

There are 4 dams/reservoirs (22.22%) that present a value within the percentile 25 and less than the median (Cervera, Úzquiza, Villameca, Santa Teresa dams/reservoirs). The other 4 dams/reservoirs have a CIDR value equal to the median with a value of 35, which is the case of Castro de las Cogotas, Cuerda del Pozo, La Requejada, and Barrios de Luna.

Furthermore, there are 3 dams/reservoirs (16.67%) that present a value equal to the percentile 75. Among them, these dams/reservoirs stand out Irueña, Riaño, Camporredondo, and Águeda dams/reservoirs.

Finally, of the 18 dams/reservoirs studied, 3 (16.67%) present a higher value to the 75th percentile: Compuerto and Porma dams/reservoirs with punctuation of 37 and 38, respectively, and Aguilar with a score of 39 has the highest value.

It is worth noting the score of the Irueña and Águeda reservoirs (CIDR = 36) as well as Camporrendo and Riaño (CIDR = 36), pairs of subsystems, are in close proximity to each other (see Figure 3). This equality of values may indicate that the infrastructures and measures adopted to improve water circularity have produced homogeneous results in both geographical areas, although the uses and characteristics of these reservoirs are different. This fact, on the one hand, allows internal validation of the proposed index, and on the other highlights the applicability of CIDR to assess the effectiveness of tailored measures to increase water circularity. Please, see Supplementary Materials section to CIDR definition.

To standardize for dam/reservoir variation, the results for the various indicator endpoints were divided into three classes of the same length on the basis of the absolute value distribution as follows. The 33rd and 67th percentiles were determined for each end value, and each dam/reservoir was classified as “low” (1–33 percentile), “medium” (34–66 percentile), or “high” (67–100 percentile) by comparing each dam/reservoir endpoint value with the relevant percentile values. The values of percentiles 33 and 66 were 33.00 and 35.54, respectively. Figure 4 presents the ranked value of CIDR for the 18 dams/reservoirs. The value which exceeds the 67th percentile is considered the one with the highest circularity of water (Figure 4).

In overall terms, the dams/reservoirs managed by the DRA display a suitable water circularity, measured in terms of CIDR. Seven reservoirs are classified as “High-CIDR” and five as “Medium-CIDR”, which represents 67% of the total number of reservoirs analyzed. In addition, of the reservoirs with “Low-CIDR”, three of them show a CIDR equal to 33, a value very close to the “Medium” class.

5. Discussion and Conclusions

In general terms, the regulation function of water is the main reason for the existence of reservoirs. It seems clear that constructing an integral circularity assessment framework is required and it would support a strategic circular water management approach. In this paper, eleven indicators are proposed for constructing the CIDR index in order to assess and improve the circularity of dams/reservoirs for water management. The CIDR index has been applied experimentally in the dams/reservoirs of the community of Castilla and León (Spain) belonging to the Duero Hydrographic Demarcation. This approach may assist stakeholders to formulate decisions based on CIDR to enhance circularity in the water sector on dams/reservoirs ultimately leading to water and environmental conservation. The dams/reservoirs were divided into three categories (low, medium, and high) based on percentiles of CIDR total value.

The CIDR index comprises a pioneering initiative that may allow simplifying and quantifying the water management circularity. Furthermore, it may be helpful for the identification of those dam/reservoir systems that present greater deficiencies in water circularity to facilitate the planning of various improvement actions and guide stakeholders in their decision-making process. In this sense, the use of the CIDR index can also help policies formulate to enhance water management and its assessment. Furthermore, the CIDR can also help to improve the communication between the different water actors, by means of developing management strategies as well as opportunities for water to approach the circular perspective in dams/reservoirs.

The creation and implementation of the CIDR open several new research lines that have been considered from now on. It is important to consider the possibility of incorporating some criteria in the weighting of indicators for the calculation of the CIDR. Furthermore, in order to generalize the use of CIDR, this index should be tested in different dams/reservoirs.

Empirically, for this research, the CIDR revealed that seven dams/reservoirs present a high water circularity, and seven of them are low. The results for the CIDR are very high, above the 66th percentile in seven dams/reservoirs. The values for CIDR are equal to or above the 75th percentile in seven dams/reservoirs and they have been classified as CIDR high.

The CIDR index provides a novel pragmatic approach for water resource managers to quantify dam/reservoir water circularity objectively. These results would allow the managers, stakeholders, and water planners to easily know the most problematic dams and reservoirs from the point of view of water circularity and to develop greater use of water without serious economic, hydrogeological, or social problems. This approach will undoubtedly have a positive impact on the effectiveness and efficiency of water use through effective planning that positively affects water resource governance.

Author Contributions

C.P.-A. and J.-L.M. conceived, designed, and led the research. All authors made the research conceptualization and analytical development. C.P.-A. and S.Z. have edited the figures. J.-L.M. supervised all actions. The Discussion and Conclusions sections were addressed by all authors, and all authors wrote the paper. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Acknowledgments

This work was developed within the framework of the SID_REDES project, supported by the Ministry of Science and Innovation. The authors thank the University of Salamanca for the facilities made available in order to undertake this research.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The founding sponsors had no role in the design of the study; in writing the manuscript; nor in the decision to submit the article for publication.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures

Figure 1. General methodology for the design and computation of CIDR.

Figure 2. Location of case studies. Source: MITECO [34], modified by authors.

Figure 3. Total CIDR index score on case study. Source: MITECO [34], modified by authors.

Figure 4. Ranked values of CIDR on 18 dams/reservoirs. Blue indicates CIDR higher than the 67th percentile, ochre indicates CIDR between 34th and 66th percentiles, and red indicates CIDR lower than 33rd percentile.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15122268/s1, Table S1: CIDR definition. Score.

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