| Summary: | 碩士 === 中原大學 === 土木工程研究所 === 99 === This research develops an SWMM Parameters Optimization Model (SPOM) to reduce the cost of time in calibrating parameters of SWMM automatically. It uses Genetic Algorithm Library for optimizing the hydrological and geographical parameters of SWMM-RUNOFF module and SWMM-EXTRAN module. The SPOM is used as the core of WEB SWMM Parameters Optimization Model (WEB-SPOM) to facilitate the operations of SPOM.
In this research, Zhung-Gung drainage system in Taipei city is employed as a case study, and the past typhoon rainfall and actual manhole water level are collected to be the input data of SPOM. First, SPOM is used to verify the optimum parameter from nine typhoon events one by one, and confer the accuracy of interior Genetic Algorithm parameters. Then, the accuracy of parameters from the nine typhoon events is validated. Finally, the optimum parameter differences between simulated manhole water level and actual manhole water level are compared; the parameters and efficiency before and after optimization are analyzed. USWS (urban sewer warning system), a web-based system, is improved by replacing the optimized parameters of SWMM and imposing SPOM on USWS to demonstrate the proposed approach.
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