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Decentralization-based optimization of detention reservoir systems for flood reduction in urban drainage areas

机译:基于分散的城市水库减洪滞洪库系统优化

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The paper introduces a decentralized approach to optimizing the flood reduction efficiency of multiple detention reservoirs in urban areas. The flood reduction effects of a detention reservoir system were regionally assessed, and a new model was then created using an optimization technique which involved coupling extraordinary particle swarm optimization with a flood simulation engine, Storm Water Management Model, EPA-SWMM, to identify optimal outlet designs for a detention reservoir system. When applied to the To Lich drainage network (Hanoi, Vietnam) the proposed method outperformed the present design, reducing flooding under the design flood event. The performance of the approach was verified by comparing it with the overall objective function of total flooded volume for different design floods. The better performance of the decentralized optimization approach described here, in terms of local and regional flood management, illustrated its effectiveness for urban flooding reduction.
机译:本文介绍了一种分散式方法,以优化城市多个滞留水库的防洪效率。区域评估了一个蓄水池系统的防洪效果,然后使用一种优化技术创建了一个新模型,该技术涉及将非常规粒子群优化与洪水模拟引擎(雨水管理模型,EPA-SWMM)结合起来,以确定最佳出口拘留水库系统的设计。当应用于To Lich排水网络(越南河内)时,建议的方法优于本设计,从而减少了设计洪水事件下的洪水。通过将其与不同设计洪水的总洪水量的总体目标函数进行比较,验证了该方法的性能。就本地和区域洪水管理而言,此处描述的分散优化方法的更好性能说明了其对减少城市洪水的有效性。

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