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An Adaptive Surrogate Assisted CE-QUAL-W2 Model Embedded in Hybrid NSGA-II_ AMOSA Algorithm for Reservoir Water Quality and Quantity Management
Water Resources Management ( IF 3.9 ) Pub Date : 2020-03-18 , DOI: 10.1007/s11269-020-02510-x
Motahareh Saadatpour

Abstract

The Meimeh dam construction is a project, planned to provide sustainable livelihoods, social, and economic developments in the Meimeh River Basin, Ilam, Iran. However, due to the high concentration of TDS in the Meimeh River and its tributaries, river impoundment and water storage can be harmful to the Meimeh Reservoir. The upstream inflow control and the reservoir operation management in a selective withdrawal scheme (SWS) were used to mitigate the potential environmental degradation of Meimeh Reservoir’s low water quality. CE-QUAL-W2 and WEAP (Water Evaluation and Assessment Programming) models were employed to evaluate the effects of various upstream saline inflow control scenarios. The analysis indicated that the diversion of the Siyoul tributary flow rate in the Meimeh River could result in lower violations of Total Dissolved Solids (TDS) concentrations and better water supply satisfaction. Then, the optimal reservoir operation management strategies in a SWS were derived in the best upstream inflow control scenario. The adaptive surrogate-assisted WQSM (water quality simulation model), coupled to hybrid NSGA-II_AMOSA (Non-dominated Sorting Genetic Algorithm-II_Archived Multi-Objective Simulated Annealing) algorithm, has been applied to derive the suitable reservoir operation strategies in SWS, improve the water supply satisfaction and alleviate the adverse effects of reservoir outflow TDS violations. The performances of the best water quality and supply scenarios have been compared with the scenario based on the standard operation policy (SOP) in the Meimeh Reservoir. The results show that most violations of TDS criteria occur during the peak agricultural seasons and significant water deficit in some dry years happens in the SOP.



中文翻译:

混合NSGA-II_ AMOSA算法中嵌入的自适应替代辅助CE-QUAL-W2模型用于水库水质和水量管理

摘要

Meimeh大坝建设是一个项目,旨在为伊朗伊斯兰堡的Meimeh流域提供可持续的生计,社会和经济发展。但是,由于湄公河及其支流中TDS的高度集中,河流蓄水和蓄水可能对湄公河水库有害。选择性入水方案(SWS)中的上游入水控制和水库运行管理被用来缓解Meimeh水库水质低下的潜在环境恶化。使用CE-QUAL-W2和WEAP(水评估和评估程序)模型来评估各种上游盐水流入控制方案的效果。分析表明,Meimeh河中Siyoul支流流量的改道可以减少总溶解固体(TDS)浓度的违反,并提高供水满意度。然后,在最佳上游进水控制方案中,得出了水上作业中的最佳油藏调度管理策略。自适应替代辅助水质模拟模型,结合NSGA-II_AMOSA(非支配排序遗传算法-II_归档多目标模拟退火)算法,推导了SWS中合适的水库调度策略,改进了水文模拟方法。满足供水需求并减轻水库TDS违规的不利影响。最佳水质和供水方案的性能已与Meimeh水库中基于标准运行策略(SOP)的方案进行了比较。结果表明,大多数违反TDS标准的事件都发生在农业高峰期,而在某些干旱年份,SOP中出现了明显的缺水现象。

更新日期:2020-03-20
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