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OSTRICH-SWMM: A new multi-objective optimization tool for green infrastructure planning with SWMM

机译:OSTRICH-SWMM:一种新的多目标优化工具,用于使用SWMM进行绿色基础设施规划

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摘要

The installation of Green Infrastructure (GI) can revitalize communities while reducing sewage overflows and improving runoff quality. However, determining the proper GI investment is a challenging management task. Numerical hydrologic models, such as the Storm Water Management Model (SWMM), are the primary design tool for GI. A new open-source multi-objective SWMM optimization tool was developed by connecting SWMM with the existing Optimization Software Toolkit for Research Involving Computational Heuristics (OSTRICH). In contrast to similar tools, it is open-source and has a large selection of parallelized algorithms. A case study of stormwater management in Buffalo, New York, demonstrated how the tool can illuminate trade-offs between the cost of rain barrel placement and the resulting reduction in combined sewer overflows. In the future, this tool could be used to optimize different types of GI features and contribute to a broader decision support framework for urban land use and stormwater management.
机译:绿色基础设施(GI)的安装可以使社区恢复活力,同时减少污水溢出并提高径流质量。然而,确定适当的地理标志投资是一项具有挑战性的管理任务。诸如雨水管理模型(SWMM)等数字水文模型是地理标志的主要设计工具。通过将SWMM与现有的用于计算启发式研究的优化软件工具包(OSTRICH)连接起来,开发了一种新的开源多目标SWMM优化工具。与类似的工具相比,它是开源的,并且有大量并行算法可供选择。在纽约州布法罗市进行的雨水管理案例研究表明,该工具如何阐明在放置雨桶的成本与减少的下水道合并溢流之间的取舍。将来,该工具可用于优化不同类型的地理标志功能,并为城市土地使用和雨水管理提供更广泛的决策支持框架。

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