Utilizing artificial neural network to measure stream flow in flood plain (Case study: Sepidroud watershed)

Publish Year: 1391
نوع سند: مقاله کنفرانسی
زبان: English
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IREC09_162

تاریخ نمایه سازی: 19 اسفند 1391

Abstract:

In this paper, stream flow forecasting in long term series of time, has been investigated by ANN model. For knowing the hydrological behavior and water management of Sepidroud River (North of Iran-Gilan) the present study focused on stream flow forecasting with artificial neural network. Ten years (2000-2009) historical inflow data, observed from the Sepidroud River, were selected ; then 10 years inflow of the Sepidroud River have been forecasted by neural network. Finally, the results obtained from forecasted data compared with observed data. The results showed that neural network could predict stream flow with high precision and the maximum error between predicted and observed data was 3% approximately

Authors

Alireza Mardookhpour

Ph.D.Department of Civil and Water Engineering,Lahijan Branch, Islamic Azad University

Freydoon Godarzvand Chegini

B.S. Department of Water Engineering, Lahijan Branch, Islamic Azad University, Lahijan

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