Abstract
In this study, the non-dominated sorting genetic algorithm (NSGA-II) is used for the multi-objective optimization of the Sefidrud reservoir in Northern Iran. The main objectives include water supply, hydropower generation and sediment flushing. In addition to some physical constraints such as the reservoir storage and the outlet flow, maximum flushing outflow and non-flushing in irrigation seasons, the environmental constraints as fish migration and spawning are taken into an account. After obtaining the Pareto optimal solutions by means of the weighted objective functions and non-symmetric Nash bargaining, various scenarios are defined. Then these scenarios are analyzed by introducing a new sustainability index. Furthermore, the different percentages of downstream water demand are considered in order to achieve a better evaluation of the scenarios. The results of study indicate that the optimal solutions are more sustainable than those of the current operation of Sefidrud reservoir, which increase the sediment flushing by 37 million tons compared to the current operation, with the same hydroelectric energy and downstream water supply. The proposed methodology could be used successfully in other reservoir operations including the sediment flushing.
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