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Water pollution escalates with rising waste discharge in river systems, as the rivers' limited pollution tolerance and constrained self-cleaning capacity compel the release of treated pollutants. Although several studies have shown that the non-dominated sorting genetic algorithm-II (NSGA-II) is an effective algorithm regarding the management of river water quality to reach water quality standards, to our knowledge, the literature lacks using a new optimization model, namely, the multi-objective cuckoo optimization algorithm (MOCOA). Therefore, this research introduces a new optimization framework, including non-dominated sorting and ranking selection using the comparison operator densely populated towards the best Pareto front and a trade-off estimation between the goals of discharges and environmental protection authorities. The suggested algorithm is implemented for a waste load allocation issue in Jajrood River, located in the North of Iran. The limitation of this research is that discharges are point sources. To analyze the performance of the new optimization algorithm, the simulation model is linked with a hybrid optimization model using a cuckoo optimization algorithm and non-dominated sorting genetic algorithms to convert a single-objective algorithm to a multi-objective algorithm. The findings indicate that, in terms of violation index and inequity values, MOCOA's Pareto front is superior to NSGA-II, which highlights the MOCOA's effectiveness in waste load allocation. For instance, with identical population sizes and violation indexes for both algorithms, the optimal Pareto front ranges from 1.31 to 2.36 for NSGA-II and 0.379 to 2.28 for MOCOA. This suggests that MOCOA achieves a superior Pareto front in a more efficient timeframe. Additionally, MOCOA can attain optimal equity in the smaller population size., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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.

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]

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]

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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]

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]

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]

This paper presents an efficient methodology for developing pollutant discharge permit trading in river systems considering the conflict of interests of involving decision-makers and the stakeholders. In this methodology, a trade-off curve between objectives is developed using a powerful and recently developed multi-objective genetic algorithm technique known as the Nondominated Sorting Genetic Algorithm-II (NSGA-II). The best non-dominated solution on the trade-off curve is defined using the Young conflict resolution theory, which considers the utility functions of decision makers and stakeholders of the system. These utility functions are related to the total treatment cost and a fuzzy risk of violating the water quality standards. The fuzzy risk is evaluated using the Monte Carlo analysis. Finally, an optimization model provides the trading discharge permit policies. The practical utility of the proposed methodology in decision-making is illustrated through a realistic example 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]

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]