• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.597-604
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• 2020

Muskingum, a hydrologic channel flood routing, is a method of predicting outflow by using the relationship between inflow, outflow, and storage. As many studies for Muskingum model were suggested, parameters were gradually increased and the calculation process was complicated by many parameters. To solve this problem, an optimization algorithm was applied to the parameter estimation of Muskingum model. This study applied the Advanced Nonlinear Muskingum Model considering continuous flow (ANLMM-L) to Wilson flood data and Sutculer flood data and compared results of the Linear Nonsingum Model incorporating Lateral flow (LMM-L), and Kinematic Wave Model (KWM). The Sum of Squares (SSQ) was used as an index for comparing simulated and observed results. Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was applied to the parameter estimation of ANLMM-L. In Wilson flood data, ANLMM-L showed more accurate results than LMM-L. In the Sutculer flood data, ANLMM-L showed better results than KWM, but SSQ was larger than in the case of Wilson flood data because the flow rate of Sutculer flood data is large. EBHS-CGS could be appplied to be appplicable to various water resources engineering problems as well as Muskingum flood routing in this study.