Iran-Water Resources Research

Iran-Water Resources Research

Parameter Estimation of Nash Conceptual Model Using Genetic Algorithm and Ordinary Least SquareLS Methods

Document Type : Original Article

Authors
S.M Hosseini 1
B Zahraie 2
A Hourfar 3
1 . Ph.D. Student, College of Water and Soil Engineering, University of Tehran, Karaj, Iran.
2 Assistant professor, Sschool of Ccivilivil Engineering, University of Tehran, Tehran, Iran
3 Assistant professor, College of Water and Soil Engineering, University of Tehran, Karaj, Iran
Abstract
This study is focused on two parameter estimation methods of Ordinary Least Square (OLS) and binary code Genetic Algorithm (GA) for estimating the k, n Nash conceptual model parameters. The efficiency of these methods is compared by applying the calibrated models in simulating seven rainfall-runoff events in Heng-Chi watershed in north of Taiwan. The results of the goodness of fit criteria indicate that GA method has better performance in terms of coefficient of efficiency and has reduced the coefficient of variation of error in simulated discharge and error in peak discharge. 
Keywords
parameter estimation
Nash conceptual model
Ordinary Least Square
Genetic algorithm
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Iran-Water Resources Research
Volume 2, Issue 2
Spring 2006
Pages 10-12

  • Receive Date 31 January 2006
  • Revise Date 24 May 2006
  • Accept Date 14 October 2006