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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. [ABSTRACT FROM AUTHOR]

The main purpose of this research is to investigate the effect of increasing porosity on concrete porous pavement (PP) clogging control. The delay due to the clogging process has been observed in order to extend pavement service life and improve storm water management performance in long term. By adding pumice to the pervious concrete mix design, porosity and permeability increased; hence, additional porosity for the accumulation of suspended solids has been formed. The results showed that adding the pumice as part of the concrete aggregates produces positive effect on the initial permeability. Affected by clogging, permeability of the specimens in which pumice was added reduced only 26%, 10%, and 29%, showing that the procedure successfully delays clogging and extends service life of the PP. Although adding pumice reduces the compressive strength, it is still within the acceptable range. By comparison the observed data with the results of the permeability prediction models, it is demonstrated that the models properly predict permeability of the pavement over time, in more than 73% of the observed data and the results of the prediction models merely less than 10% difference observed. The rainfall-runoff simulation indicates that adding pumice as part of the permeable concrete aggregates results in delaying of the clogging and improving the performance of concrete increasing the service life of permeable pavements. [ABSTRACT FROM AUTHOR]

This paper proposes a new framework to optimize the allocation of water resources considering two perspectives of water value and strategic management which is one of the novelties of this study. After identifying agricultural, industrial, and domestic water demands, a water allocation model is developed to maximize the net benefit of water delivered to each sector. Based on the characteristics of the study area which is the Namak Lake basin, water transfer from Dez tributaries can be considered as an uncertainty depending on the climate and political issues. So, the model is initially performed without considering water transfer and then water transfer is considered to enhance the flexibility. In addition, the initial model does not assign the weights to the plain. In the novel model, weights derived from questionnaires are applied to reflect experts' opinions and consider the priorities of the plains. Transferred water is then allocated from the strategic management perspective and the water value perspective (six possible combinations of perspectives and scenarios), and eleven independent variables are considered in the model. Also, GMCR + , the new version of the Graph Model for Conflict Resolution, is applied to visualize the possible scenarios and equilibrium states based on the status quo of the conflict. Based on the results, the first scenario of water value perspective is chosen which results in a significant water allocation to the industry and agriculture sectors (approximately 94% and 96%, respectively). Also, 94.6% of potable water is satisfied compared to the initial water needs. [ABSTRACT FROM AUTHOR]

Management and control of flood hazards, the most frequent natural disaster worldwide, has become a greater challenge due to the increasingly unpredictable precipitation and runoff due to climate change. As many rural areas in Iran are vulnerable to flash floods occurring mainly in the spring, more accurate plans are needed to help reduce the risk of related damage. To address this concern, a robust methodology using multi-objective optimization is proposed, which incorporates the large uncertainties in the modeling parameters defining the risk of flooding. The proposed framework has been implemented in the upper catchment of the Taleghanrood river in the Taleghan district in Iran, which is vulnerable to flooding. The results provide a detailed performance assessment of alternative infrastructure designs, which will help to increase the efficiency of flood management strategies. The optimization uses multi-criteria optimization evolutionary algorithms (MOEA) and Bayesian estimation concepts. The resulting specific design plans, as levees' height increases over a 50-year time horizon, for controlling floods under given scenarios reflect the uncertainty in the parameters. Article Highlights: A robust decision making model has been developed to address flood management scenarios. The proposed methodology addresses deep uncertainties in decision parameters. Sensitivity analysis of the plausible scenarios and discovers vulnerable scenarios has been done. [ABSTRACT FROM AUTHOR]

Stormwater runoff is a major concern in urban areas which is mostly the result of vast urbanization. To reduce urban stormwater runoff and improve water quality, low impact development (LID) is used in urban areas. Therefore, it is vital to find the optimal combination of LID controls to achieve maximum reduction in both stormwater runoff and pollutants with optimal cost. In this study, a simulation–optimization model was developed by linking the EPA Storm Water Management Model (SWMM) to the Multi-Objective Particle Swarm Optimization (MOPSO) using MATLAB. The coupled model could carry out multi-objective optimization (MOO) and find potential solutions to the optimization objectives using the SWMM simulation model outputs. The SWMM model was developed using data from the BUNUS catchment in Kuala Lumpur, Malaysia. The total suspended solids (TSS) and total nitrogen (TN) were selected as pollutants to be used in the simulation model. Vegetated swale and rain garden were selected as LID controls for the study area. The LID controls were assigned to the model using the catchment characteristics. The target objectives were to minimize peak stormwater runoff, TSS, and TN with the minimum number of LID controls applications. The LID combination scenarios were also tested in SWMM to identify the best LID types and combination to achieve maximum reduction in both peak runoff and pollutants. This study found that the peak runoff, TSS, and TN were reduced by 13%, 38%, and 24%, respectively. The optimal number of LID controls that could be used at the BUNUS catchment area was also found to be 25. [ABSTRACT FROM AUTHOR]

Determining the optimized policies in the exploitation of groundwater water resources is a complicated issue, especially when there are several different managers with conflicting goals. The current study presents a new multi-purpose method to reach a compromise among different stakeholders by determining optimal social policies and sustainable hydro-environmental management of underground water resources. This method simultaneously considers qualitative and quantitative simulation and optimization, stakeholders' preferences, and uncertainty analysis. In this study, the recharge was determined and incorporated in MODFLOW groundwater current model and MT3DMS pollution transfer model by using the hydrological model SWAT. In addition, DREAM (zs) algorithm (derived from algorithms based on Markov chain Monte Carlo) was used to examine the uncertainty of MODFLOW model parameters. The optimal head and TDS rate were determined in the studied aquifer by linking the model with MOPSO. Then, the Pareto frontier derived from the previous step, was utilized to determine the allocation rate of groundwater resources among a set of non-dominated solutions using Social Choice Rules (SCR) including Condorcet, Median Voting Rule (MVR), and Fallback Bargaining (FB) including unanimity fallback bargaining and fallback bargaining with impasse. The results showed that almost all the selected methods of conflict resolution in this research behaved similarly, and their results were not significantly different from each other. However, the comparison of these methods indicated that the MVR with the minimum reduction in withdrawal discharge and the maximum elevation in response to optimal allocation policies had the best performance. The amount of water extracted from the study area is about 540 million m3/year, which reaches 395 million m3/year. [ABSTRACT FROM AUTHOR]

The co-transport of pollutants with colloidal particles to lower depths of groundwater and porous environments has been demonstrated in many studies in recent three decades. Despite the numerous researches, all experimental and numerical studies of pollutant transfer in the presence of colloidal particles have been carried out in one dimension, which causes significant errors in this phenomenon. In this study, the two-dimensional transfer experiment of chromium in the presence of bentonite colloidal particles is done in saturated porous media. In order to conduct the experiment in two-dimensional conditions, the sampling was done in central and lateral of the last experiment column section. The results have been demonstrated that the transmission along the longitudinal direction is higher than lateral in the three tests of the transfer of chromium, bentonite, and chromium in the presence of bentonite colloidal particles at the beginning of the experiment, and due to completed mixing in the section, it reached to a constant value as lateral samples. While the presence of bentonite colloidal particles facilitates the transfer of chromium in both longitudinal and lateral directions, increasing the bentonite colloidal particle concentration causes more getting stuck of colloid particles between the sand grains and reduction of the chromium transfer in both longitudinal and lateral directions. So, it can be concluded that transfer in the lateral direction is lower in bentonite colloidal particles compared with chromium, and the reason is the bentonite colloidal particles getting stuck between sand grains, which is exacerbated by increasing the concentration of the bentonite. Also, due to the chromium co-transport with colloid particles in the fraction of chromium total transport, increasing the bentonite concentration causes decreasing the chromium lateral transfer. [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]

The lack of long term observed data is the main challenge in many simulation-based studies for identification of nutrient critical source areas (CSAs). This study explored the effect of calibration of the Soil and Water Assessment Tool (SWAT) on identification of nutrient CSAs and evaluated capability of this model for finding CSAs under the limited data condition. For this purpose, the Zrebar Lake watershed in Iran was used to assess the variations in total phosphorus and total nitrogen CSAs identified by both calibrated and uncalibrated SWAT models. In this study, a modified version of SWAT model was used for calibration the model considering observed lake water quality data and also for simulation of lake water quality and quantity interactions with the watershed management practices. The nutrient CSAs identified by calibrated and uncalibrated models showed that the irrigated farmlands were the main sources of nutrients discharged into the lake in which alfalfa, apple and tobacco were marked as the most polluting cultivations. It was also concluded that CSAs were not considerably different based on the calibrated and uncalibrated models. This validates the capabilities of SWAT on marking CSAs for areas with lack of long term observed data. [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]

Given the limited fresh water resources available, evaporation from dam reservoirs and freshwater lakes whereby large amounts of water resources are lost is now becoming a serious challenge in hydrology and water resource management. In this study, Kohli and Frenken (KF) method and the KF modified (MKF) (for the modification of this method, level I (250 m) reference evapotranspiration (RET) data were obtained from the FAO's WaPOR Product (FWP) which is a ready product based on remote sensing (RS)) were utilized to estimate reservoir evaporation (RE) in seventeen stations in Iran for the period of 9 years: 2009–2018. The current study includes four distinct steps, as follows. In the first step, the KF method was evaluated with the ground data (measured), and the ready RS product was then validated in the second step. In the third step, we evaluated the MKF method. Finally, in the fourth step, a number of statistical indices were evaluated for each of the methods in order to examine its performance. The results indicated that there was no significant difference between the estimated evaporation values using KF method and the measured values based on the statistical indices. As such, the validation of the ready RS product was acceptable for all dam reservoirs. Moreover, it was found that coefficients of the MKF equation for all stations had a relatively high degree of reliability (R〉0.871). Also, these coefficients had a wide range of variations in different regions, so using a fixed coefficient for all stations will have a relatively large error. The findings also revealed that using the MKF method can improve the performance of the KF method from 0.11 to 9.28%. [ABSTRACT FROM AUTHOR]

The accelerated trend of urbanization as well as industrial development in Karaj can be mentioned as the major reasons for speeding up the exploitation of water resources in this study area, through the recent decades. The increase in industrial, domestic and agricultural water consumptions, as a result of the abovementioned development, has been accompanied by an irregular and wasteful extraction of groundwater resources considering drought in the recent years and reduced precipitation in the Middle East. The above direction has resulted in dire consequences such as unbelievable drop in groundwater level and reduced aquifer storage while several springs and qanats were deserted and dried up. Therefore, an accurate study of groundwater status, reasons for groundwater level drop and consequences besides presenting solutions for conservation and balancing groundwater should be known as the most critical issues for this area, since stepping out of the current situation requires reasonable policies for exploiting from the aquifer. Therefore, by utilizing MATLAB interface in this research, three scenarios entitled optimistic situation, pessimistic situation and continuing current situation were defined to predict groundwater level of Karaj study area until water year of 2023–2024. According to the results, 12.834, 19.089 and 4.906 m water level drops were computed for continuing current situation, pessimistic situation and optimistic situation, respectively. [ABSTRACT FROM AUTHOR]

Urbanization and climate change are causing numerous side effects on groundwater resources. In this study, an integrated modeling approach by linking soil and water application tool (SWAT), modular finite difference groundwater flow (MODFLOW), and three-dimensional variable-density groundwater flow coupled with multi-species solute and heat transport (SEAWAT) models were used to exhibit responses of groundwater systems, in terms of flow and salt concentrations to current and future climatic and anthropogenic changes. Future climate scenarios for periods of 2010-2040 were generated from the Canadian Global Coupled Model (CGCM) for scenarios A1B, B1, and A2 which was downscaled by the Long Ashton Research Station weather generator (LARS-WG) providing precipitation and temperature patterns for the period 2018-2040. The GCM’s outputs were applied to SWAT model to estimate recharge rate for the ten scenarios designed to assess the sensitivity of the aquifer to urbanization and climate change. The estimated recharge rate from SWAT was utilized as an input in numerical groundwater model to evaluate saltwater intrusion (SWI), changes in freshwater storage within the aquifer system, and changes in groundwater level. Based on the results of each scenario’s simulation, increase of pumping rate yield by future population growth will have more adverse effects on the unconfined aquifer. The derived information from this study can be used to improve future works by developing a better understanding of the managed and unmanaged response of freshwater storage and unconfined groundwater systems to climate change and anthropogenic activities. [ABSTRACT FROM AUTHOR]