River Flow Model Using Artificial Neural Networks

The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. In this research, an ANN was developed and used to model the rainfall-runoff relationship, in a catchment located in a semiarid and Mediterranean climate in Algeria...

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Bibliographic Details
Published inEnergy procedia Vol. 74; pp. 1007 - 1014
Main Authors Aichouri, Imen, Hani, Azzedine, Bougherira, Nabil, Djabri, Larbi, Chaffai, Hicham, Lallahem, Sami
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.08.2015
Subjects
Algeria
Artificial neural network
Catchment
MLP
modeling multiple regressions
Rainfall-runoff
semi arid climate
MLP
Catchment
modeling multiple regressions
semi arid climate
Rainfall-runoff
Algeria
Artificial neural network
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Summary:The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. In this research, an ANN was developed and used to model the rainfall-runoff relationship, in a catchment located in a semiarid and Mediterranean climate in Algeria. The performance of the developed neural network-based model was compared against multiple linear regression-based models using the same observed data. It was found that the neural network model consistently gives superior predictions. Based on the results of this research, artificial neural network modeling appears to be a promising technique for the prediction of flow for catchments in semi-arid and Mediterranean regions. Accordingly, the neural network method can be applied to various hydrological systems where other models may be inappropriate.
ISSN:1876-6102
1876-6102
DOI:10.1016/j.egypro.2015.07.832