Performance Investigation of Nakagami- Distribution to Derive Flood Hydrograph by Genetic Algorithm Optimization Approach
Publication: Journal of Hydrologic Engineering
Volume 15, Issue 8
Abstract
In this study, two-parameter Nakagami- distribution has been introduced along with two-parameter gamma (GM), three-parameter generalized logistic (GLG), three-parameter Pearson type 3 (PT3), and three-parameter generalized extreme value distributions for the derivation of flood hydrographs for gauged catchments. Parameters of these distributions have been optimized using genetic algorithm (GA) in MATLAB v. 7.1 GA toolbox. Observed storm events of three catchments have been used to evaluate the efficiency of the hydrographs generated by these distributions. A validation test has been performed on the different storm event data set of one of the catchments and results were found satisfactory. Statistical estimators (viz., coefficient of efficiency, root-mean squared error, and mean absolute percent error), which indicate the efficiency of the optimization technique in deriving flood hydrographs have been used to find out the rank of these distributions for deriving the hydrographs for the particular catchments.
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Acknowledgments
The writers wish to thank Dr. R. K. Rai (Water Resources Consultant), DHI (India) Water, Environment, and Health, New Delhi (India), Mr. Aniruddha Chandra, M.E. (Communication Engg.), Lecturer, NIT Durgapur, West Bengal, and Mr. Biswamohan Goswami, Superintending Engineer (Civil), DVC for their constructive suggestions to improve the quality of the paper. The writers wish to thank the anonymous reviewers for their constructive suggestions to improve the quality of the paper.
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Information
Published In
Journal of Hydrologic Engineering
Volume 15 • Issue 8 • August 2010
Pages: 658 - 666
Copyright
© 2010 ASCE.
History
Received: May 6, 2009
Accepted: Dec 14, 2009
Published online: Jan 8, 2010
Published in print: Aug 2010
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