The assessment of artificial neural network rainfall-runoff models under different input meteorological parameters. Case study: Seybouse basin, Northeast Algeria

• Autorzy: Aoulmi Yamina , Marouf Nadir , Amireche Mohamed

Identyfikatory

DOI

10.24425/jwld.2021.138158

• Języki publikacji: EN

Abstrakty

EN

Over the past two decades, artificial neural networks (ANN) have exhibited a significant progress in predicting and modeling non-linear hydrological applications, such as the rainfall-runoff process which can provide useful contribution to water resources planning and management. This research aims to test the practicability of using ANNs with various input configurations to model the rainfall-runoff relationship in the Seybouse basin located in a semi-arid region in Algeria. Initially, the ANNs were developed for six sub-basins, and then for the complete watershed, considering four different input configurations. The 1^st (ANN I_P) considers only precipitation as an input variable for the daily flow simulation. The 2^nd (ANN II) considers the 2^nd variable in the model input with precipitation; it is one of the meteorological parameters (evapotranspiration, temperature, humidity, or wind speed). The third (ANN III_P,T,HUM) considers a combination of temperature, humidity, and precipitation. The last (ANN V_{P,ET,T,HUM,Vw}) consists in collating different meteorological parameters with precipitation as an input variable. ANN models are made for the whole basin with the same configurations as specified above. Better flow simulations were provided by (ANN II_P,T) and (ANN II_P,Vw) for the two stations of Medjez-Amar II and Bordj-Sabath, respectively. However, the (ANN V_{P,ET,T,HUM,Vw})’s application for the other stations and also for the entire basin reflects a strategy for the flow simulation and shows enhancement in the prediction accuracy over the other models studied. This has shown and confirmed that the more input variables, as more efficient the ANN model is.

Słowa kluczowe

EN

artificial neural networks; ANNs; meteorological parameters; rainfall-runoff; semi-arid region; Seybouse basin; various input configurations

• Wydawca: Wydawnictwo ITP
• Czasopismo: Journal of Water and Land Development
• Rocznik: 2021
• Tom: no. 50
• Strony: 38--47
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Aoulmi Yamina

• University of Larbi-Ben-M’hidi, Faculty of Sciences and Applied Sciences, Department of Hydraulic, Laboratory of Ecology and Environment, PO Box 358, 04000 Oum El Bouaghi, Algeria

• https://orcid.org/0000-0002-8146-9649

autor

Marouf Nadir

• University of Larbi-Ben-M’hidi, Faculty of Sciences and Applied Sciences, Department of Hydraulic, Laboratory of Ecology and Environment, PO Box 358, 04000 Oum El Bouaghi, Algeria

• https://orcid.org/0000-0002-7445-7527

autor

Amireche Mohamed

• University of Larbi-Ben-M’hidi, Faculty of Sciences and Applied Sciences, Department of Hydraulic, Laboratory of Ecology and Environment, PO Box 358, 04000 Oum El Bouaghi, Algeria

• https://orcid.org/0000-0002-4145-1057

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