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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]

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]

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]

Effective groundwater management and allocation are essential from economic and social points of view due to increasing high-quality water demands. This study presents a review and bibliometric analysis of the popular techniques in groundwater management and allocation models, which have not yet been captured in the literature, as our knowledge allows. To this extent, the literature on this state-of-the-art is categorized based on four primary sectors intervening in efficient groundwater management. The first sector discusses the simulation and surrogate models as the central groundwater predictive models, wherein quantitative and qualitative groundwater models are scrutinized. The second section is dedicated to applying different classic and smart optimization models, followed by a summary of state-of-the-art works on applying accurate and heuristic optimization models in groundwater management. Third, uncertainty analysis techniques in conjunction with groundwater modeling are studied as analytical tools, approximation methods, and simulation methods to identify the most exciting subject fields. The fourth section reviews decision-making models coupled with groundwater models as multi-criteria decision-making, social choice, and game-theory models. Finally, a summary of this review and goals for future studies are presented. Additionally, several new ideas are recognized, advising scholars to find critical gaps in the field. [ABSTRACT FROM AUTHOR]

Naphthenic acids are a group of polar organic carboxylic acids that are present in crude oil naturally. They are cycloaliphatic carboxylic acids which have 10 to 16 carbons, which gained importance since the early twentieth century because of corrosion in oil refineries. Moreover, they are the most important environmental pollutants caused by oil extraction from oil sand reserves. Heavy crude oils which have high concentration of naphthenic acids are usually considered as poor-quality oil and sold at a lower price. Often, the high concentration of naphthenic acids in crude oil reduces the life of the equipment which are used in the exploration and refining process because of corrosion. Hence, researchers are increasingly interested in the chemical properties of naphthenic acids and the acidic components of the crude oils. The most popular methods for the identification and analysis of naphthenic acids are liquid and gas chromatography (GC), liquid-liquid extraction, Fourier transform infrared spectroscopy (FTIR), and solid-phase extraction (SPE). Naphthenic acids are the most important environmental pollutants caused by oil extraction from oil sand reserves. Previous studies have revealed that naphthenic acids can be absorbed by fish, but their distribution in different tissues of fish has not been specified. Experimental samples showed the highest toxicity to fish, while there was less toxicity to invertebrates and algae. Moreover, naphthenates have various industrial utilizations; they are used in synthetic detergents, corrosion inhibitors, lubricants, fuel and oil additives, wood preservatives, insecticides, fungicides, pesticides, wetting agents, napalm thickening agents, and oil desiccants that are utilized in painting and treating wood surfaces. [ABSTRACT FROM AUTHOR]

In process of flood risk management, there is usually a conflict between the governments, insurance companies and people as players in sharing financial responsibilities, because of how calculate insurance premium, compensation and governmental assistances. In order to this conflict resolution, in this paper a new methodology is proposed based on game theoretic approach by using Nash equilibrium method, that for the first time, the payoff functions of insurance companies and government have been associated to each other. In this method, according to maximization of player's payoffs, the best response has been found and for the first time, comprehensive financial model has been developed for sharing players' financial responsibilities in flood risk management plans. In order to increase the accuracy of flood insurance calculations, the parameters of deductible and franchise have been applied. The key findings indicate, success of flood risk management plans depend on purchasing flood insurance with full coverage and government financial assistances simultaneously. The developed flood insurance plan has most sensitivity to parameters of deductible and insurance rate. This model could be utilized as practical and academic model in flood risk management. The applicability and efficiency of the methodology are examined in Northeast of Tehran as capital of Iran. [ABSTRACT FROM AUTHOR]

Various approaches to quantifying resilience have sparked debate in past years. This study measures the social and hydraulic resilience of an Urban Drainage System (UDS) using two methodologies, i.e., a proposed index-based framework and a parametric-based Multi-Criteria Decision Making (MCDM) method. The former positions flexibility as a key property of the resilience concept, and after quantifying four characteristics of a flexible system, measures the flood resilience based on quantifying the two resilience components, i.e., flexibility and resistance; while. The latter calculates the resilience through a linear combination of the actual values and relative weights for different UDS sub-characteristics which best describe the resiliency of the system. The methodologies were applied to a basin, focusing on flooding as a disaster, to quantitatively evaluate the behavior of UDS under both single-event and long-term precipitation. The results of both methods were indicative of a relatively low level of flood resiliency for the UDS in the studied area. Among different scenarios examined for the studied region, using Best Management Practices (BMPs) was turned out to be an effective adaptive measure to enhance the UDS resilience to a higher level. [ABSTRACT FROM AUTHOR]

A new approach was presented to manage simultaneously reservoir outflow quantity and quality. Two strategies were used to control reservoir outflow quality: (1) reservoir inflow control with Best Management Practices (BMPs) in the watershed and (2) outflow management by reservoir operational strategy. Soil and Water Assessment Tool (SWAT) model was linked to a reservoir water quality simulation model (CE-QUAL-W2), the linked watershed-reservoir model was coupled with Multi-Objective Particle Swarm Optimization algorithm (MOPSO) to find the best set of decisions to optimize the reservoir outflow quality and quantity objectives. The approach was applied to Alavian reservoir and its watershed, in Iran, for a 6-year time horizon. The results show the proposed approach could reduce reservoir outflow phosphorus concentration while increasing downstream water supply. The implemented BMPs outperformed the reservoir operational strategy in terms of reservoir outflow quality reducing outflow phosphorus concentration up to 45% comparing with current conditions. Among the four applied BMPs, filter strips had more effect on reducing nutrient loads. [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]

The natural water cycle in an urban catchment normally results from climate, physical characteristics and natural surface coverage. The hydrological process in urban catchments can drastically change due to urbanization, human activities, modified physiography and climate change. Urbanization typically results in a larger runoff volume, higher peak discharge, faster time of concentration as well as lower infiltration. It also has a significant impact on the precipitation intensity and patterns. Antecedent soil moisture, steep slopes and roughness will lead to uncertain rainfall-runoff behavior as well. Climate change will usually alter temperature, precipitation intensity and duration along with the runoff timing and magnitude. Various number of studies have proved that urbanization and climate change would have stronger effect on urban rainfall- runoff behavior than other factors. We have reviewed and investigated various and the most effective factors influencing urban runoff generation in this paper. Particularly, the anthropogenic, geomorphologic and meteorological impacts on urban surface runoff have been the focus of this review paper. The study gaps and suggestions for further research have also been discussed at the end. Finally, the best measures to be taken into consideration to mitigate urban excess runoff have been suggested in the final section. [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]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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 vast development of urban areas has resulted in the increase of stormwater peak runoff and volume. Water quality has also been adversely affected. The best management practices (BMPs) and low impact development (LID) techniques could be applied to urban areas to mitigate these effects. A quantity–quality model was developed to simulate LID practices at the catchment scale using the US Environmental Protection Agency Storm Water Management Model (US EPA SWMM). The purpose of the study was to investigate the impacts of LID techniques on hydrology and water quality. The study was performed in BUNUS catchment in Kuala Lumpur, Malaysia. This study applied vegetated swale and rain garden to assess the model performance at a catchment scale using real field data. The selected LIDs occupied 7% of each subcatchment (of which 40% was swale and 30% was rain garden). The LID removal efficiency was up to 40% and 62% for TN and TSS, respectively. The peak runoff reduction was up to 27% for the rainfall of up to 70 mm, and up to 19% for the rainfall of between 70 and 90 mm, respectively. For the longer storm events of higher than 90 mm the results were not as satisfactory as expected. The model was more effective in peak runoff reduction during the shorter rainfall events. As for the water quality, it was satisfactory in all selected rainfall scenarios. [ABSTRACT FROM AUTHOR]

Successful application of one-dimensional advection-dispersion models in rivers depends on the accuracy of the longitudinal dispersion coefficient (LDC). In this regards, this study aims to introduce an appropriate approach to estimate LDC in natural rivers that is based on a hybrid method of granular computing (GRC) and an artificial neural network (ANN) model (GRC-ANN). Also, adaptive neuro-fuzzy inference system (ANFIS) and ANN models were developed to investigate the accuracy of three credible artificial intelligence (AI) models and the performance of these models in different LDC values. By comparing with empirical models developed in other studies, the results revealed the superior performance of GRC-ANN for LDC estimation. The sensitivity analysis of the three intelligent models developed in this study was done to determine the sensitivity of each model to its input parameters, especially the most important ones. The sensitivity analysis results showed that the W/H parameter (W: channel width; H: flow depth) has the most significant impact on the output of all three models in this research.