Niazi Mehran, Nietch Chris, Maghrebi Mahdi, Jackson Nicole, Bennett Brittany R, Tryby Michael, Massoudieh Arash
Food and Drug Administration, 10903 New Hampshire Ave., Silver Spring, MD 20993; formerly, National Risk Management Research Laboratory, Water Supply and Water Resources Division, U.S. EPA, 26 W. MLK Dr., Cincinnati, OH 45268.
National Risk Management Research Laboratory, Water Supply and Water Resources Division, U.S. EPA, 26 W. MLK Dr., Cincinnati, OH 45268.
J Sustain Water Built Environ. 2017 Jan 24;3(2). doi: 10.1061/jswbay.0000817.
The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peer-reviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.
暴雨管理模型（SWMM）是城市排水设计和规划中广泛使用的工具。已有数百篇经过同行评审的文章和会议论文描述了SWMM的应用。本综述着重于在同行评审文献中收集有关模型在校准和验证方面性能的信息。还介绍了该模型的主要发展历程和应用。研究结果为其他寻求快速参考以评估其独特SWMM应用完整性的人提供了帮助。差距分析评估了该模型在考虑绿色基础设施（GI）/低影响开发（LID）设计及其有效性的情况下进行水质模拟的能力。得出的结论是，SWMM概念模型的细节水平与其总体计算简约性之间取得了良好的平衡，使其成为适用于大中型水文应用的模型。然而，要实际模拟分散污染源、它们的归宿和迁移以及GI/LID实施情景的有效性，嵌入新的机理算法或为与其他模型耦合提供用户指导将是必要的。
