Estimation of Nonlinear Muskingum Model Parameter Using Differential Evolution
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Abstract
The accurate estimation of Muskingum model parameter is essential to give flood routing for flood control in water resources management. The Muskingum model continues to be a popular method for flood routing, and its parameter estimation is a global optimization problem with the main objective to find a set of optimal model parameter values that attains a best fit between observed and computed flow. Although some techniques have been employed to estimate the parameters for Muskingum model, an efficient method for parameter estimation in Muskingum model is still required to improve the computational precision. Therefore, in this paper, the differential evolution (DE) algorithm is studied for estimation of Muskingum model parameter. A case study with actual data from previous literature, the experimental results showed an excellent performance in its optimization result and performance analysis and demonstrates that DE is an alternative technique to estimate the parameters of the Muskingum model.
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Acknowledgments
This work is supported by the Natural Science Research Program of Henan Province Educational Committee (No. UNSPECIFIED2010B570002) and the Scientific Research Foundation of North China Institute of Water Conservancy and Hydroelectric Power for High-Level Talents (No. UNSPECIFIED200821). The writers gratefully acknowledge the many suggestions and comments provided by the editors and anonymous reviewers, which have greatly improved the paper.
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© 2012 American Society of Civil Engineers.
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Received: Jun 3, 2010
Accepted: May 19, 2011
Published online: May 21, 2011
Published in print: Feb 1, 2012
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