2.2 Methodology
In this study a quantitative index for the Dam/Reservoir Circularity, denoted as CIDR, is defined, and applied for the first time. The step-by-step calculations are detailed below:
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 necessary to propose additional assessment and evaluation methods, techniques and tools. Those new developments have been proposed in the 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 (Jain and Ramsankaran 2019).
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 is 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 (Malczewski 1999). 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 (Dean 2020).
Step 2. Selection of most representative indicators
To evaluate the circularity of dam/reservoir water flow eleven indicators have been selected, using data at the local level in 18 dam reservoirs. These indicators are evaluated on a scale of 1–5, where 1 is the lowest, and 5 is the highest. However, some indicators´ score are the contrary. The CIDR was constructed by combining hydrological, economy, 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 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.
Demand Satisfaction (DS)
This parameter is closely related to Average historical dam capacity of dam/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 behaviour 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 index comprises the functional quality of the river system that in turn comprises naturalness of the flow regime, sediments availability and floodplain functionality. On the other hand, the quality of the riverbed is assessed which comprises naturalness of layout, continuity and naturalness of the bed and of longitudinal and lateral mobility. Final score is grouped in five labelled categories as very good (75–90), good (60–74), moderate (42–59), poor (21–41), very bad (0–20).
Clogging Risk (CR)
It is necessary to monitor the clogging of reservoirs. The results of these controls would serve to analyze the deviations with respect to what was foreseen in the project phase, to obtain more precise forecasts on the degree and rate of clogging and to adopt the most appropriate corrective measures. Among the effects of clogging in reservoirs, the following can be highlighted loss of water storage capacity and sediment retention in reservoirs.
Contamination Risk (CtR)
Dams/reservoirs are especially at risk of contamination by different contaminants from anthropogenic sources, since a change of 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' 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. The 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.
Step 3. Normalizing and Imputation of missing data
Normalization is required to make the indicators comparable when the have different measurement units, is that it 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.
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.
individual relevance of each one in the set.
Since this is a starting point of a real application of CE on a real water system (dam/reservoir), this study was set up a so-defined equal criteria set where all indicators of Dam/Reservoir Circularity are equally weighted.
Step 5. Aggregation
This is probably the most important stage in this research. It consists of the combination of all indicators. In this research it is considered MCA techniques, which are greatly suitable when working from a multidimensional approach. This phase considers the same individual weight assigned to each variable and is the last step in the development of a composite index. The main flowchart used to construct the CIDR is displayed in Fig. 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 of interpretation.