Reza Kerachian is a Professor at the School of Civil Engineering, University of Tehran in Iran, and a Young Affiliate of The World Academy of Sciences (TWAS). He has published more than 150 articles in peer-reviewed journals and 230 papers in conference proceedings. Prof. Kerachian is Editor-in-charge of Iran-Water Resources Research (Journal of Iranian Water Resources Association) and in editorial boards of four other journals. He has also supervised 20 PhD and 80 MSc theses. Phone: 0098-21-61112176 Address: School of Civil Engineering, University of Tehran, Enghelab Ave., Tehran, Iran.
In this study, a new methodology is presented for simultaneous agricultural water and return flow... more In this study, a new methodology is presented for simultaneous agricultural water and return flow (waste load) allocation in rivers. In this methodology, an objective function based on Conditional Value at Risk (CVaR) and a Nonlinear Interval Number Programming (NINP) technique are utilized. The CVaR can handle uncertainties in the form of probability distributions, while NINP incorporates uncertain inputs which are only available as intervals. This CVaR-NINP framework is used for agricultural water and return flow allocation planning under uncertainty. In this paper, to reduce the amount of saline return flow discharged into the river, a part of return flow of each agricultural network is diverted to an evaporation pond. Some meta-models based on Artificial Neural Network (ANN) are trained and validated using the results of Soil, Water, Atmosphere and Plant (SWAP) simulation model to reliably approximate the quantity and Total Dissolved Solids (TDS) load of agricultural return flows in a critical 7-day period. The effectiveness of the proposed methodology is examined through applying it to a part of Karkheh River catchment in the southwestern part of Iran. The results confirm the applicability of the model in incorporating the main uncertainties and generating water and waste load allocation policies in the form of interval numbers.
Genetic Algorithms (GAs) are population based global search methods that can escape from local op... more Genetic Algorithms (GAs) are population based global search methods that can escape from local optima traps and find the global optima regions. However, near the optimum set their intensification process is often inaccurate. This is because the search strategy of GAs is completely probabilistic. With a random search near the optimum sets, there is a small probability to improve current
In this paper, an integrated framework is proposed for urban runoff management. To control and im... more In this paper, an integrated framework is proposed for urban runoff management. To control and improve runoff quality and quantity, Low Impact Development (LID) practices are utilized. In order to determine the LIDs' areas and locations, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which considers three objective functions of minimizing runoff volume, runoff pollution and implementation cost of LIDs, is utilized. In this framework, the Storm Water Management Model (SWMM) is used for stream flow simulation. The non-dominated solutions provided by the NSGA-II are considered as management scenarios. To select the most preferred scenario, interactions among the main stakeholders in the study area with conflicting utilities are incorporated by utilizing bargaining models including a non-cooperative game, Nash model and social choice procedures of Borda count and approval voting. Moreover, a new social choice procedure, named pairwise voting method, is proposed and applied. Based on each conflict resolution approach, a scenario is identified as the ideal solution providing the LIDs' areas, locations and implementation cost. The proposed framework is applied for urban water quality and quantity management in the northern part of Tehran metropolitan city, Iran. Results show that the proposed pairwise voting method tends to select a scenario with a higher percentage of reduction in TSS (Total Suspended Solid) load and runoff volume, in comparison with the Borda count and approval voting methods. Besides, the Nash method presents a management scenario with the highest cost for LIDs' implementation and the maximum values for percentage of runoff volume reduction and TSS removal. The results also signify that selection of an appropriate management scenario by stakeholders in the study area depends on the available financial resources and the relative importance of runoff quality improvement in comparison with reducing the runoff volume.
Environmental Monitoring and Assessment, Jul 1, 2008
This paper presents an efficient methodology for developing pollutant discharge permit trading in... more 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.
In this study, a methodology combining a water quality simulation model and a hybrid genetic algo... more In this study, a methodology combining a water quality simulation model and a hybrid genetic algorithm (HGA) is developed for determining optimal operating policies for different reservoir outlets. The water quality simulation model is based on an adaptive neural fuzzy ...
ABSTRACT When an inter-basin water transfer is expected among basins with some level of unfriendl... more ABSTRACT When an inter-basin water transfer is expected among basins with some level of unfriendliness or hostility, ignoring political considerations, which are generally not integrated in economic investigations, can impede an integrated and efficient management. In this paper, a new economic-political methodology is proposed for the optimal and efficient allocation of water resources among water users in inter-basin water transfer systems. The proposed framework quantifies both the economic payoffs using an “n-person real fuzzy cooperative game”, and the political formation prospect of any coalition, using a Modified Political Accounting System (MPAS). The proposed economic-political methodology is applied to a large scale inter-basin water allocation problem including water donor and receiving basins struggling with water scarcity. The results show how including political considerations in the study may provide a more satisfactory solution compared to the just cost-effective water allocations.
ABSTRACT This paper presents a new game theoretic methodology for water and discharge permit allo... more ABSTRACT This paper presents a new game theoretic methodology for water and discharge permit allocation to agricultural zones in shared rivers. The methodology consists of four main steps: (1) initial allocation of water rights and pollutant discharge permits, (2) forming possible coalitions and optimal water and discharge permit reallocation to water users participating in a coalition to increase their total net benefit, (3) equitable benefit reallocation by utilizing some solution concepts in cooperative game theory, and (4) identifying the best water and pollutant discharge permit allocation strategies by minimizing the maximum regret in the system. A new linear form for crop water production function is used in the objective function of the water allocation optimization models. To show the efficiency and applicability of the methodology, it is applied to the Karoon-Dez river system in Iran.
In this study, a new methodology is presented for simultaneous agricultural water and return flow... more In this study, a new methodology is presented for simultaneous agricultural water and return flow (waste load) allocation in rivers. In this methodology, an objective function based on Conditional Value at Risk (CVaR) and a Nonlinear Interval Number Programming (NINP) technique are utilized. The CVaR can handle uncertainties in the form of probability distributions, while NINP incorporates uncertain inputs which are only available as intervals. This CVaR-NINP framework is used for agricultural water and return flow allocation planning under uncertainty. In this paper, to reduce the amount of saline return flow discharged into the river, a part of return flow of each agricultural network is diverted to an evaporation pond. Some meta-models based on Artificial Neural Network (ANN) are trained and validated using the results of Soil, Water, Atmosphere and Plant (SWAP) simulation model to reliably approximate the quantity and Total Dissolved Solids (TDS) load of agricultural return flows in a critical 7-day period. The effectiveness of the proposed methodology is examined through applying it to a part of Karkheh River catchment in the southwestern part of Iran. The results confirm the applicability of the model in incorporating the main uncertainties and generating water and waste load allocation policies in the form of interval numbers.
Genetic Algorithms (GAs) are population based global search methods that can escape from local op... more Genetic Algorithms (GAs) are population based global search methods that can escape from local optima traps and find the global optima regions. However, near the optimum set their intensification process is often inaccurate. This is because the search strategy of GAs is completely probabilistic. With a random search near the optimum sets, there is a small probability to improve current
In this paper, an integrated framework is proposed for urban runoff management. To control and im... more In this paper, an integrated framework is proposed for urban runoff management. To control and improve runoff quality and quantity, Low Impact Development (LID) practices are utilized. In order to determine the LIDs' areas and locations, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which considers three objective functions of minimizing runoff volume, runoff pollution and implementation cost of LIDs, is utilized. In this framework, the Storm Water Management Model (SWMM) is used for stream flow simulation. The non-dominated solutions provided by the NSGA-II are considered as management scenarios. To select the most preferred scenario, interactions among the main stakeholders in the study area with conflicting utilities are incorporated by utilizing bargaining models including a non-cooperative game, Nash model and social choice procedures of Borda count and approval voting. Moreover, a new social choice procedure, named pairwise voting method, is proposed and applied. Based on each conflict resolution approach, a scenario is identified as the ideal solution providing the LIDs' areas, locations and implementation cost. The proposed framework is applied for urban water quality and quantity management in the northern part of Tehran metropolitan city, Iran. Results show that the proposed pairwise voting method tends to select a scenario with a higher percentage of reduction in TSS (Total Suspended Solid) load and runoff volume, in comparison with the Borda count and approval voting methods. Besides, the Nash method presents a management scenario with the highest cost for LIDs' implementation and the maximum values for percentage of runoff volume reduction and TSS removal. The results also signify that selection of an appropriate management scenario by stakeholders in the study area depends on the available financial resources and the relative importance of runoff quality improvement in comparison with reducing the runoff volume.
Environmental Monitoring and Assessment, Jul 1, 2008
This paper presents an efficient methodology for developing pollutant discharge permit trading in... more 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.
In this study, a methodology combining a water quality simulation model and a hybrid genetic algo... more In this study, a methodology combining a water quality simulation model and a hybrid genetic algorithm (HGA) is developed for determining optimal operating policies for different reservoir outlets. The water quality simulation model is based on an adaptive neural fuzzy ...
ABSTRACT When an inter-basin water transfer is expected among basins with some level of unfriendl... more ABSTRACT When an inter-basin water transfer is expected among basins with some level of unfriendliness or hostility, ignoring political considerations, which are generally not integrated in economic investigations, can impede an integrated and efficient management. In this paper, a new economic-political methodology is proposed for the optimal and efficient allocation of water resources among water users in inter-basin water transfer systems. The proposed framework quantifies both the economic payoffs using an “n-person real fuzzy cooperative game”, and the political formation prospect of any coalition, using a Modified Political Accounting System (MPAS). The proposed economic-political methodology is applied to a large scale inter-basin water allocation problem including water donor and receiving basins struggling with water scarcity. The results show how including political considerations in the study may provide a more satisfactory solution compared to the just cost-effective water allocations.
ABSTRACT This paper presents a new game theoretic methodology for water and discharge permit allo... more ABSTRACT This paper presents a new game theoretic methodology for water and discharge permit allocation to agricultural zones in shared rivers. The methodology consists of four main steps: (1) initial allocation of water rights and pollutant discharge permits, (2) forming possible coalitions and optimal water and discharge permit reallocation to water users participating in a coalition to increase their total net benefit, (3) equitable benefit reallocation by utilizing some solution concepts in cooperative game theory, and (4) identifying the best water and pollutant discharge permit allocation strategies by minimizing the maximum regret in the system. A new linear form for crop water production function is used in the objective function of the water allocation optimization models. To show the efficiency and applicability of the methodology, it is applied to the Karoon-Dez river system in Iran.
This paper presents a new methodology for developing operating rules for conjunctive use of surfa... more This paper presents a new methodology for developing operating rules for conjunctive use of surface and groundwater. Bayesian Networks-based operating rules are trained and verified using the results of a multi-objective optimization model. Reduction of pumping costs, improving the groundwater quality, water supply with acceptable quality and controlling the groundwater table fluctuations are considered as objective functions of the optimization model. In order to provide Pareto fonts among these conflicting objectives, the combination of MODFLOW and MT3D groundwater quantity and quality simulation models and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used. The best solutions on the Pareto fronts, which are selected using the Young and Nash bargaining theories, are used to train and verify Bayesian Networks (BNs). In real-time water allocation from surface and groundwater resources, the BNs-based rules can be used without any need to run the time consuming optimization and conflict resolution models. The proposed methodology is applied to the conjunctive use of water resources in the Tehran region, Iran. The results show that using the operating rules can improve the groundwater quality and control the groundwater table fluctuations in the study area.
The conjunctive use of surface and groundwater resources is one alternative for optimal use of av... more The conjunctive use of surface and groundwater resources is one alternative for optimal use of available water resources in arid and semiarid regions. The optimization models proposed for conjunctive water allocation are often complicated, nonlinear, and computationally intensive, especially when different stakeholders are involved that have conflicting interests. In this article, a new conflict-resolution methodology developed for the conjunctive use of surface and groundwater resources using Nondominated Sorting Genetic Algorithm II (NSGA-II) and Young Conflict-Resolution Theory (YCRT) is presented. The proposed model is applied to the Tehran aquifer in the Tehran metropolitan area of Iran. Stakeholders in the study area have conflicting interests related to water supply with acceptable quality, pumping costs, groundwater quality, and groundwater table fluctuations. In the proposed methodology, MODFLOW and MT3D groundwater quantity and quality simulation models are linked with the NSGA-II optimization model to develop Pareto fronts among the objectives. The best solutions on the Pareto fronts are then selected using YCRT. The results of the proposed model show the significance of applying an integrated conflict-resolution approach to conjunctive use of surface and groundwater resources in the study area.
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Papers by Reza Kerachian