Stream Flow Prediction in Flood Plain by Using Artificial Neural Network (Case Study: Sepidroud Watershed)

Author

Assistant Professor, Department of civil engineering, Islamic Azad University, Lahijan, Iran

Abstract

In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed data. Results showed that neural network could predict stream flow with high precision and the maximum error percentage in data prediction was about 3.

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