Abstract

The objective of this work is
studying the
transformation of the rainfall into rain off in area scale catchment of North East of Algeria by artificial neural networks (ANNs). In this paper, we used simulation and the forecast per ANN and we adopted model conceptual GR2M to validate the results obtained per ANN. In this case, it is necessary to bring a sample of hydro meteorological data to knowing the rains, the evapotranspiration and the flows of the station to be modeled. Results obtained per ANN show superior result compared to the traditional modeling approaches (GR2M). Indeed, the coefficient of correlation is very significant (R ² exceeds 0.95) and the very weak quadratic error.

Keywords: GR2M, Rain fall, Modeling, Algeria, Runoff.

Information

Item Type:	Journal
Divisions:	» Laboratory of Management, Maintenance and Rehabilitation Of Facilities and Urban Infrastructure » Faculty of Science and Technology
ePrint ID:	357
Date Deposited:	2015-05-24
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/357

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