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Application of the Water-Energy-Food Nexus system is essential for addressing Water-Energy-Food Security and Environmental Protection in urban agricultural areas. However, there is currently no standardized framework for measuring and comparing sustainability indicators in these areas using the WEF Nexus practices. This study proposes sustainability measurement indicators to evaluate the WEF Nexus sustainability. The Analytical Hierarchy Process (AHP) was employed to identify the most crucial indicators for policymakers. The WEF nexus sustainability indicators were selected based on three dimensions of sustainability: social, environmental, and economic. The study focused on Varamin, a semi-arid city in Tehran that serves as a center for urban agriculture. Research results indicate that water-related components are crucial in arid and semi-arid regions. Based on the environmental sustainability indicators, pollution prevention, with a priority of 52.8%, is a critical component of sustainability. Finally, several key indicators are recommended for decision-makers to address sustainability. Allocating national budgets to create environmental policies and increasing public education on environmental issues are two priorities for achieving sustainability goals. However, future studies should utilize the Analytic Network Process (ANP), which enables interdependencies among decision components, as the AHP approach has some limitations. [ABSTRACT FROM AUTHOR]

Waste load allocation (WLA) is a policy-making framework that can simultaneously consider multiple objectives, such as equity, environmental violations, and economic efficiency. This study developed a WLA framework focusing on equitable perspective from Rawls' theory of justice. For this purpose, the optimal scenarios were generated by calling the Streeter-Phelps equations for river simulation with the NSGA-II optimization algorithm. In addition, equity indicators were used to improve the optimization problem based on three objective functions simultaneously: minimizing treatment costs, environmental violation, and inequity. COPRAS method was also used to select the optimized WLA scenarios. Results showed that the optimal WLA scenario based on equity can improve the practicability of WLA in river system by deriving reasonably cost-effective and environmental friendly solutions with about 70% BOD removal for polluters in Haraz basin, northern Iran. Therefore, based on three dimensional multi-objectives WLA, equity could show its potential on highlighting optimal alternatives without extreme total cost or environmental violations. [ABSTRACT FROM AUTHOR]

Flood events in urban and non-urban areas have long-term devastating impacts on communities resulting in casualties and economic damages. Different interconnected concepts of flood management lead decision-makers to broaden their focus from traditional points of view to transcend the disciplinary boundaries of hydrological modeling. So, evaluating interconnected aspects of flood control requires configuring an Integrated Flood Management (IFM) system. In this research, a novel comprehensive framework is proposed to control floods in urban and non-urban areas using Low-Impact Development (LID) practices and detention dams, simultaneously. In the first step, urban and non-urban areas of the Darakeh catchment in Tehran, Iran, as the study area, are modeled using Storm Water Management Model (SWMM). Next, by coupling the SWMM with Pareto Envelope-based Selection Algorithm II (PESA-II), optimal management scenarios are generated considering four hydrological-economic objectives. Each management scenario specifies the optimal sites and dimensions of detention dams and the optimal location and area of LIDs in non-urban and urban areas, respectively. Indeed, the innovative IFM framework provides a multi-dimensional trade-off between upstream and downstream flood protection. Then, interactions among the main stakeholders with conflicting interests are incorporated into utility functions. Ultimately, using COmplex PRoportional ASsessment (COPRAS) and Nash bargaining methods the most capable management scenarios are selected based on stakeholders' preferences. Results showed that the IFM framework can be significantly effective in flood severity attenuation. Based on the findings, proposed method warrants peak flow reduction up to 60.04 and 53.50 percent at the inlet and outlet of the urban area. Besides, the Nash bargaining approach tends to select a scenario with a higher peak flow reduction compared to the COPRAS method. Also, results signify that each stakeholder's relative importance and preferences can remarkably impact the decision-making process. In addition to resolving conflicts arising from implementing flood control measures, this framework can incorporate divergent aspects of flood management into a reliable system. [Display omitted] • Addressing integrated urban-nonurban flood management catchments, simultaneously. • Evaluating optimal use of detention dams and LIDs from a novel point of view. • Using the COPRAS method for selecting the most appropriate management scenario. • Employing Nash Bargaining theory to conflict resolution in macro-flood management. [ABSTRACT FROM AUTHOR]

Sustainable urban stormwater management presents challenges due to uncertainties and conflicting stakeholder preferences. In this regard, our research introduces a comprehensive framework that integrates self-organization map (SOM) and many-objective robust decision-making (MORDM) methods to bridge the knowledge gap between deep uncertainty and conflict resolution. To do so, first, MORDM generates optimal strategies for the implementation of low-impact development (LID) practices and quantifies their robustness under different uncertain scenarios. Then, the results are integrated into the SOM framework, wherein multi-dimensional decision space can be classified and stakeholders are enabled to navigate their satisfaction to reach a subset of robust strategies. Finally, to determine the most suitable management strategy, a novel game theory-based group multicriteria decision-making (GT-GMCDM) method is employed, which can effectively consider stakeholders' conflicts in the selection process. Results from applying the proposed methodology in District 10 of Tehran municipality, Iran, demonstrate that the selected alternative can reduce TSS contamination load and runoff volume (RV) by 30% and 27%, respectively. Indeed, findings prove that in addition to improving stormwater quality and quantity, the suggested methodology can simultaneously consider stakeholders' preferences and find a reliable strategy. This study also offers valuable insights into robust stormwater management, with a focus on ensuring the sustainability of urban environments. [ABSTRACT FROM AUTHOR]

Excessive usage of fossil fuels and high emission of greenhouse gases have increased the earth's temperature and consequently have led to changes in wind and wave regimes. The main effects of climate change on oceans are warming of the ocean water, melting of ice, acidification of ocean water, and change in the ocean currents. The main effects of climate change on coastal regions are change in the coast hydrodynamics, sea level rise, change in wave height, coastal erosion, coastal structure damage, food shortage, and storms. Due to the importance of waves in the coastal zone and its effect on erosion and sedimentation, it is necessary to study wave changes. In this study, the effect of climate change on wave specifications was evaluated in the southern coast of the Caspian Sea in Noshahr Port. To simulate wave parameters, the third generation spectral Simulating WAves Nearshore (SWAN) model was used. Wave modeling was carried out using the SWAN numerical model for two 30-yearly periods, including the control period (1984 to 2014) and the future period (2051 to 2080). For wave modeling in the control period, the European Center for Average Weather Forecast wind field was used, and for the future period, a downscaled wind field from Coordinated Regional Downscaling Experiment projection, which was sponsored by World Climate Research Programme, based on the most recent emission scenarios RCP2.6, RCP4.5, and RCP8.5, was used. The model results were calibrated and verified with buoy-recorded data. The effect of the climate change on the wave parameters was evaluated by studying the differences between the patterns in three scenarios and the control period. Results showed that the 30-year maximum significant wave height will increase because of climate change, and the wave direction will not change. In addition, the intensity of storms will increase in the future. [ABSTRACT FROM AUTHOR]

Although the effectiveness of best management practices (BMPs) in reducing urban flooding is widely recognized, the improved sustainability achieved by implementing BMPs in upstream suburban areas, reducing downstream urban floods, is still debated. This study introduces a new definition of urban drainage system (UDS) sustainability, focusing on BMP usage to enhance system performance after adaptation to climate change. Three types of hydraulic reliability index (HRI) plus robustness and improvability indices were used to quantify the potential enhanced sustainability of the system in a changing climate, together with a climate change adaptability index (CCAI). The sustainability of UDS for the safe conveyance of storm-water runoff was investigated under different land-use scenarios: No BMP, BMP in urban areas, and BMP inside and upstream of urban areas, considering climate change impacts. Rainfall–runoff simulation alongside drainage network modelling was conducted using a storm-water management model (US EPA SWMM) to determine the inundation areas for both base-line and future climatic conditions. A new method for disaggregating daily rainfall to hourly, proposed to provide a finer resolution of input rainfall to SWMM, was applied to a semi-urbanized catchment whose upstream runoff from mountainous areas may contribute to the storm-water runoff in downstream urban parts. Our findings confirm an increase in the number of inundation points and reduction in sustainability indices of UDS due to climate change. The results present an increase in UDS reliability from 4% to 16% and improvements in other sustainability indicators using BMPs in upstream suburban areas compared to implementing them in urban areas. [ABSTRACT FROM AUTHOR]

Drinking water distribution systems (DWDS) are some of the critical components of a drinking water system, providing water supply services to our growing populations. To maintain the safety of the drinking water supply, the water distributed through these systems needs to be regularly disinfected to ensure that it remains free of pathogens and to minimize the risk of contamination during distribution. In DWDS, balancing the risks of excessive chlorine and microbial contamination is crucial for public health due to chlorine additions in the storage tanks of these systems. Proposing effective risk-mitigation strategies requires simulations of plausible contamination scenarios and input from local experts, given the challenge of maintaining an appropriate residual chlorine level that is effective but not excessive. In addition, excessive discharge of chlorine into the environment can result in increased water pollution levels and the production of harmful disinfection byproducts, such as trihalomethanes, posing a threat to the health of waterbodies and having implications for total maximum daily loads (TMDLs). Here, we presented a framework that couples the analytical hierarchy process (AHP) with water quality simulations for decision making related to mitigating the risk of contamination to DWDS for extreme chlorine levels. We demonstrated this framework on a section of a DWDS in a highly populated city, where an accidental overapplication of chlorine resulted in the chlorine level in the tank being excessively high. Various local experts provided input about important decision criteria, their relative importance, and potential risk-mitigation strategies. Using the input in our framework, we determined important decision criteria and identified geographic zones of the DWDS at risk of chlorine contamination. The presented framework can be used in preventing chlorine contamination risks in DWDS located in other population centers. It was found that the areas closest to the tank, in terms of distance or time of travel, are more vulnerable due to the potential for rapid dispersion of contaminants. The results demonstrated the importance of incorporating expert opinions into the decision-making process and highlighted the capability of AHP in risk assessments. Future research can explore other decision-making methods, consider demographic characteristics of affected populations, and apply our presented framework to entire drinking water systems to further improve risk-mitigation strategies for preventing chlorine contamination risks in DWDS located in other population centers. [ABSTRACT FROM AUTHOR]

Variations in quality or quantity of reservoir discharges and of wastewater treatment plants (WWTP) are typical sources of uncertainty in controlling and management of river water quality downstream. This study evaluates and discusses the impacts of these operation-based uncertainties on waste load allocation (WLA) policies, like water quality trading (WQT), by Monte-Carlo simulation. For this purpose, we chose the Sefidrud River in northern Iran and developed an economic-based WLA in this area through a simulation-optimisation approach. The river with 1150 reaches is simulated by coding in MATLAB and linked to a multi-objective particle swarm optimization (MOPSO) algorithm in which the two objectives are minimisation of environmental violations and abatement costs. For uncertainty analysis through Monte-Carlo simulation, river flow and kinetic rates, dissolved oxygen (DO) at headwater, pollution loads of dischargers, and temperature are considered as primary variables. Results show that the success of WLA is mostly reliant on the DO concentration of headwater, occurrence of seasonal floods, and river aeration rate. The implications of the findings are also analysed for WQT. In particular, the above uncertainties are highlighted as possible threats for the success of discharge permit markets because polluters could be penalised or rewarded for uncertainties regardless of their pollution discharges. Consequently, effective WQT under uncertainty is likely to lead to a need for more monitoring to resolve potential disputes from uncertainties. [ABSTRACT FROM AUTHOR]

With the experience of storm surges along Persian Gulf of Iran it is needed to simulate storms in coastal areas and study the protection techniques in order to protect communities and industrial facilities in coastal areas. Mangrove forests play a unique role in attenuating storm surge during tropical cyclones. MIKE21 FM is an applicable software for simulating cyclones within coastal environments. A hydrodynamic model is used to analyze the attenuating role of the protected area of mangroves between Gheshm Island and Khamir Port mangroves under a realistic conditions by updating the calibrated Manning's coefficient based on the land cover data to incorporate the mangrove effect with modifying bottom friction and characteristics of cyclone Gonu 2007 which is the strongest cyclone recorded in the Arabian Sea and Persian Gulf. In this research we measured the maximum surge levels in both scenarios (in situ conditions and the condition which mangrove forest is neglected); maximum storm tide reduction by mangroves (MSTRM) by mangroves and maximum storm tide reduction rate by mangroves (MSTRRM). Also inundation maps are presented aiming to measure the areas rescued from inundation and the areas inundated caused by mangroves. The simulations shows that the minimum and maximum storm tide reduction rate by mangroves are 5.32% and 34.88% respectively. [ABSTRACT FROM AUTHOR]

Urbanization growth leads to shifting hydrological factors which in turn represent a challenge for urban stormwater management. In this situation, policy strategies can be employed by governments to incentivize stakeholders to use green infrastructure for effective runoff management. This study presents a novel framework evaluating the application of Low-Impact Development (LID) practices for runoff quality and quantity management from a socio-economic point of view. The proposed framework investigates the potential of cooperative game theory to find a fair allocation based on the concept of justice. In this regard, first, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was coupled with the Storm Water Management Model (SWMM) to find optimal runoff management scenarios considering minimization of runoff volume, peak flow, Total Suspended Solid (TSS) load, and costs of LIDs implementation. In the next step, in order to conflict resolution, stakeholders' preferences and interactions were incorporated into the cooperative game theory to determine management scenarios' worth of coalition. In the third step, benefits are allocated among stakeholders by defining three different sharing rules. Then, to select the most capable runoff management scenario, social choice methods of Condorcet choice, Borda scoring, and median voting rule support cooperative game decisions. The proposed methodology is explored in District 10 of Tehran municipality in Iran. According to the findings, solutions with stricter plans for runoff management correspond to more worth of coalition. In addition, the higher worth of coalition, the higher the reduction of peak flow, TSS load, and the total runoff volume. The results also reveal that the Borda scoring procedure tends to select scenarios with less reduction in TSS load, runoff volume, and peak flow in comparison with the others, and as expected, the minimum value for the worth of coalition. Additionally, the cooperative game targets a management scenario with the highest worth of coalition and the maximum value for the reduction in runoff volume, peak flow, and TSS removal. Our framework warrants runoff volume, TSS load, and peak flow can be reduced by 32.8, 31.9, and 32.7 percent, respectively. This framework, in addition to incentivize the stakeholders for implementing runoff management strategies, can effectively consider their conflict of interests in the decision-making process. [Display omitted] • Urban runoff quality and quantity are managed using cooperative game theory. • The coupled simulation-optimization model is applied to find optimal solutions. • Three allocation systems are applied to share the benefits among stakeholders. • Social choice theories support game theory for selecting the best scenario. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-objective robust decision-making is demonstrated for urban runoff management. • The SWMM- NSGA-II coupled model generates urban runoff management scenarios. • Alternatives' robustness against deep uncertainty is evaluated under climatic change. • System Vulnerabilities are discovered using PRIM and CART. Decision-makers in urban water systems have long searched for robust runoff management alternatives that can resist deviations from the performance for which they were designed. In this study, with the development of a new comprehensive framework consisting of Many- Objective Robust Decision-Making (MORDM) and Storm Water Management Model (SWMM), robust alternatives for the implementation of Low Impact Development (LID) practices are presented under future climate change. The proposed methodology has been applied to District 10 of the Tehran municipality, located in the central part of Tehran, Iran. In the first step, the performances of General Circulation Models (GCMs) in predicting rainfall in the base period (1986–2005) were compared, and MPI-ESM-LR was selected as the best model for predicting rainfall in the future period (2021–2040). In the next step, by developing the SWMM hydrological model, runoff quality and quantity were simulated under RCP8.5 and RCP2.6. By coupling SWMM with the NSGA-II multi-objective evolutionary algorithm and specifying objective functions, the most optimal LIDs implementation scenarios were produced. Then, well-characterized uncertainties were changed into deep uncertainties, and the robustness of each design alternative was quantified using two robustness assessment methods. Finally, system vulnerabilities were discovered using the patient rule induction method (PRIM) and classification and regression tree (CART). This study showed that scenarios with a higher percentage of LIDs are more robust against deep uncertainties. Using different RCP scenarios also revealed that methodological selection of future climate scenarios can affect the robustness of candidate alternatives. Implementing SWMM-MORDM enables decision-makers to effectively generate runoff management scenarios and visually evaluate their robustness against deep uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, a new methodology is proposed for waste load allocation in river systems using the decision support system (DSS) for the graph model for conflict resolution II (GMCRII), multi-criteria decision making (MCDM) analysis and the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. Minimization of total treatment and penalty costs and minimization of biological oxygen demand violation of standards at the check point are considered as the main objectives of this study. At first, the water quality along the river was simulated using the Streeter-Phelps (S-P) equation coupled with the MOPSO model. Thereby a trade-off curve between the objectives is obtained and a set of non-dominated solutions is selected. In the next step, the best alternative is chosen using MCDM techniques and the GMCRII DSS package and non-cooperative stability definitions. The applicability and efficiency of the methodology are examined in a real-world case study of the Sefidrud River in the northern part of Iran. [ABSTRACT FROM AUTHOR]

This study focuses on the challenge of using a multiple pollutant transferable discharge permit market for operating wastewater treatment plants. It uses an analytical case of Sefidrud River in Iran with two checkpoints. It shows that the operating limitations for simultaneous biochemical oxidation demand (BOD) and total nitrogen (TN) removal may convert the economically optimal waste load allocation (WLA) to a framework with lack of incentives. Therefore, water quality trading (WQT) may lose its economical advantages. In this case, a third parameter, such as dissolved oxygen is recommended as an index for assigning market interactions. In spite of economical and practical success, this approach made WLA become a more complicated and uncertain policy. It was totally concluded that using single parameter WQT is only recommended for areas with small agricultural activities or lakes. Otherwise, the integrated discharged permit and reclaimed water market is proposed instead for simultaneous BOD and TN management. [ABSTRACT FROM AUTHOR]

Water quality trading is a sustainable framework for surface water quality management. It uses discharge permits to reduce the total treatment costs. For example, the case of Gharesoo River in Iran shows that the nitrogen permit market between point and non-point sources is 37% more economical than the command and control framework. Nevertheless, the cost saving may be reduced to 6% by the end of the study period (2050). This depression may be due to the limited technical support for wastewater treatment plants. Therefore, an integrated market is recommended in which the discharge permits and the reclaimed water are traded simultaneously. In this framework, the allocation of secondary treated domestic wastewater for irrigation can provide capacity for other pollutants to discharge into the surface water. This innovative approach may decrease the total treatment costs by 63% at present, while 65%, may be achieved by the end of the study period. Furthermore, this market is able to determine the environmental penalty, trading permits, and reuse prices. For example, the maximum ratio of the average reuse price to the penalty cost is determined as 1 to 10. It is introduced as an incentive indicator for stakeholders to consider the integrated market. Consequently, the applicability and the efficiency of using this approach are verified long term. [ABSTRACT FROM AUTHOR]

In this paper, a new Cooperative Trading Discharge Permit (CTDP) methodology is designed for estimating equitable and efficient treatment cost allocation among dischargers in a river system considering their conflicting interests. The methodology consists of two main steps: (1) initial treatment cost allocation and (2) equitable treatment cost reallocation. In the first step, a Pareto front among objectives is developed using a powerful and recently developed multiobjective genetic algorithm known as Nondominated Sorting Genetic Algorithm-II (NSGA-II). The objectives of the optimization model are considered to be the average treatment level of dischargers and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. The best non-dominated solution on the Pareto front, which provides the initial cost allocation to dischargers, is selected using the Young Bargaining Theory (YBT). In the second step, some cooperative game theoretic approaches are utilized to investigate how the maximum saving cost of participating dischargers in a coalition can be fairly allocated to them. The final treatment cost allocation provides the optimal trading discharge permit policies. The practical utility of the proposed methodology for river water quality management is illustrated through a realistic case study of the Zarjub river in the northern part of Iran. [ABSTRACT FROM AUTHOR]

The transport of pollutants inside the groundwater system is profoundly affected by absorption and transmission via colloid or soil particles. Therefore, it is essential to investigate the significant pollutants (Such as hexavalent chromium (Cr(VI))) transfer in the presence of colloid particles that can facilitate or retain this transfer. For this purpose, an experiment is carried out in a saturated porous media column to study the bentonite concentration, flow velocity and sand grain size effects on co-transport of Cr(VI) with bentonite. The results of this study demonstrated that the colloid particles facilitate the transfer of Cr(VI) by 30% in 200 mg/l bentonite colloids concentration. The amount of transmitted Cr(VI) is decreased by increasing the bentonite colloids concentration from 200 mg/l to 300 mg/l. As the flow velocity increased from 2 cm/min to 3.3 cm/min, the amount of transferred Cr(VI) increased by 7%. The results show that with reducing the sand grain size, the amount of transmitted bentonite and Cr(VI) is reduced that this effect is more sensible in bentonite transport. As a result, it can be noted that the bentonite colloidal particles according to its concentration and experimental conditions, may facilitate or retain the Cr(VI) transport and sand gradation has a significant impact on colloid and pollutant transmission. • Bentonite concentration can be estimated by turbidity of samples with high accuracy. Presence of bentonite will facilitate the transport of Cr+6 in porous media by 30%. • Increasing the bentonite leads to a decrease in the void space and the Cr+6 transferring. • There is an optimum bentonite concentration in which the Cr+6 pollutant transport would be maximum. • Reduction in grain particles diameter decreased the bentonite and adhered Cr+6 transfer. • Increasing the flow velocity increases the Cr+6 transport in the presence of bentonite. [ABSTRACT FROM AUTHOR]

• A model framework is advanced for recognizing robust waste load allocation (WLA) plans under climate change. • Coupled SWAT and BorgMOEA models to optimize WLA. • WLAs are produced under different AOGCMs and emission scenarios. • Ranges of the uncertainties lead to a polluted dam reservoir with higher probability are discovered by PRIM and CART methods. In recent years, uncertainties in climate change have made the allocation of waste load a severe challenge. This research develops a new model framework integrating a soil and water assessment tool (SWAT) for hydrological simulation of the river basin, Borg many-objective evolutionary algorithm (Borg MOEA) for optimization, and a software for many-objective robust decision making (OpenMORDM) to minimize these uncertainties and identifying the most robust waste load allocation plans resisting the impact of system uncertainties. This framework has been applied to the Golgol River basin, Iran, which is the main source of the Ilam dam water supply. In this study, first, temperature and precipitation were predicted in 2080–2099. Then, The SWAT model was used to simulate runoff and biochemical oxygen demand (BOD). Afterward, by specifying the objective functions, the Borg MOEA produced the most optimal waste load allocation scenarios in the driest month of the future (August), So that the amount of BOD in the dam reservoir remains less than 5 mg/L. In the next step, the robustness of the solutions analyzed using OpenMORDM. Then, the results were analyzed using the patient rule induction method (PRIM) and classification and regression tree (CART) methods to identify the system vulnerability domains and minimizing false positives. Through the analysis, four climate scenarios have been used to explain how the methodological selection of them affects the resulting candidate planning solutions. The results indicated that individual design selections from the water managers or researchers could influence the efficacy of the model framework, which in turn results in failure of the most robust waste-load allocation strategies under future climate change. [ABSTRACT FROM AUTHOR]

Allocating water to organizational stakeholders poses a vital challenge to water managers. Organizations which benefit from water as the primary factor input attempt to achieve their objectives using cost-effective and quick-return strategies, such as increasing the water rights. In such circumstances, lack of water probably results in the conflict. Recognizing the management approaches, organizational priorities, and the stakeholders' influence power can play a dominant role in analyzing the future of such conflicts. In this paper, we analyzed the conflict of water allocation in Ilam dam among organizational stakeholders. We defined the strategies based on the background of the game and organizational objectives. The influence power of stakeholders and the numerical weights of strategies were quantified based on the expert judgment method. The relative priorities of strategies were then calculated for each state of the conflict. We used the GMCR + model to study the actions of stakeholders. Results suggest that the Jihad Agriculture Organization and the Water and Wastewater Company withdraw more water; hence, there exists no water to meet the environmental water right. In this case, the participation of the third party, such as the Governorship and the Justice can change the future of the conflict, and result in moving to the optimal state. However, results from Inverse GMCR analysis demonstrate that Justice is the most influential third party that can move the conflict towards a desired equilibrium (optimal case). [ABSTRACT FROM AUTHOR]

Groundwater should be considered as the most important drinking water resource in arid/semi-arid regions such as Karaj, Iran. Provision of drinking water with a preeminent quality is, accordingly, a real matter of concern in these regions. Despite being an essential factor for rating of under exploitation water wells, Water Quality Index (WQI) entails conflicting issues. As a result, Multiple-criteria decision making (MCDM) models, such as Technique for order preference by similarity to ideal solution (TOPSIS), Compromise Programing (CP) and Ordered Weighted Averaging (OWA) operators were adopted to alleviate contradictions involving WQI index. In the current paper, compromise programming was utilized assuming p = 1&2 and the average value of ranks attained from all the above MCDMs (Averaged value rating) was correspondingly cited as a rating reference. Putting the above MCDM models into practice, ultimately, led to striking variations not only in the rankings but in category of water wells. It was clarified that compromise programming when p values are assumed to be 1 and 2 (CP (p = 1) & CP (p = 2)), TOPSIS and OWA could be recognized as proper techniques to eliminate contradictions involving ranking by WQI index. [ABSTRACT FROM AUTHOR]

Hydropower is essential for global electricity production, but it consumes water by evaporation from the reservoir surface. Here, a new approach is introduced in relation to modelling the water footprint of electricity (WFe) from hydropower. Two of the most important variables in calculating the WFe are volume of evaporation (EV) and electricity production (EP). In this study, the random forest (RF) model was used to predict both EV and EP. For analysing hybrid models, wavelet transform was used and wavelet RF (WRF) models were developed. After decomposing the input variables by wavelet transform, the relief algorithm (RA) was used to recognize important components and inserted into the RF model. The proposed approach was applied at Mahabad Hydropower in Iran. The results suggest that applying the wavelet transform on input data and using algorithms such as RA can be regarded as a good approach for modelling of EV and EP. [ABSTRACT FROM AUTHOR]