Volume No. 2 Issue No.: 4B Page No.: 790-795 April-June 2008

 

RAINFALL-RUNOFF RELATIONSHIP OF ZAYANDEHRUD DAM BASIN BY MULTI LAYER PERCEPTRON NEURAL NETWORK

 

Masoud Nasri*1, Reza Modarres2 and Mohammad Taghi Dastorani3

1. Islamic Azad University, Ardestan Branch, Ardestan (Iran)
2. Faculty of Natural Resources, Isfahan University of Technology, Isfahan (Iran)
3. Faculty of Natural resources, Yazd University, Yazd (Iran)

 

Received on : October 20, 2007

 

ABSTRACT

 

Rainfall-runoff relationship is one of the most important and complex hydrological processes whose perception is very important in hydrology and water resources. A plenty of physical and statistical models have been developed for this that apply some parameters due to this relationship. The application of artificial neural network as a black box model is one of the methods to evaluate rainfall-runoff relationship. In this study, rainfall-runoff relationship of Plasjan Basin, upstream Zayandehrud River, is evaluated using multilayer perceptron network. Due to high variation of observed series, 3 daily rainfall series of regional stations and daily discharge of Plasjan station were first normalized and according to autocorrelation and cross correlation of rainfall-runoff data, 6 variables were selected for input of the network and a 4-hidden-layer network was found to be more valid comparing with other networks.

 

Keywords : Artificial neural network, Rainfall-runoff relationship, Multilayer perceptron, Validation, Autocorrelation

 

 

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