Optimal Parameter Estimation for Muskingum Model Using a CSS-PSO Method. (5th November 2013)

• Record Type: Journal Article
• Authors: Talatahari, S.; Sheikholeslami, R.; Farahmand Azar, B.; Daneshpajouh, H.
• Other Names: Chen Shengyong Academic Editor.
• Is Part Of: Advances in mechanical engineering. Volume 2013(2013)
• Publication Date: 2013-11-05
• Subjects: Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1155/2013/480954
• Languages: English
• ISSNs: 1687-8132

Abstract

Abstract : Limited availability of hydrologic data is a major hurdle for implementation of detailed hydrologic models. In cases where available data is limited, simple hydrologic models such as linear Muskingum model consisting of a minimum number (one or two) of model parameters are more desirable. As an alternative to the conventional mathematical approaches, this paper applies a new hybrid metaheuristic algorithm based on charged system search and particle swarm optimization for identifying the parameters of the linear Muskingum model. In order to evaluate the new algorithm, a numerical example is utilized and the results are compared to those of other algorithms. The results reveal the performance of the algorithm to optimize parameter estimation of the Muskingum model.