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Accurate parameter estimation based catchment modeling systems requires considerable work to establish credibility. In this paper, a methodology for parameter estimation of hydrologic simulation model is proposed to simultaneously include several rainfall events using Shannon entropy. The proposed methodology uses Genetic Algorithm(GA) optimization techniques for the Storm Water Management Model (SWMM). Shannon entropy theory was applied to calculate weights according to each rainfall event in study area. A case study application was undertaken using the Milyang-dam basin, in Korea. Three events are applied to calculate Shannon entropy weights. Then, Nash-Sutcliffe Efficiency(NSE) & Root Mean Square Error(RMSE) are compared with those from single event. This study suggests that the proposed methodology is capable of providing effective parameter estimation method.


Session R65, Parameter Estimation: Optimization Applications in Water Resources



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