Documents disponibles écrits par cet auteur

Comparison of stream flow predicted in a forest watershed using different modelling procedures / M. Reza Ghanbarpour in JRBM : International journal of river basin management, Vol. 10 N° 3 (Juillet 2012) 

Public ISBD [article]  in JRBM : International journal of river basin management > Vol. 10 N° 3 (Juillet 2012) . - pp. 281-292 Titre : Comparison of stream flow predicted in a forest watershed using different modelling procedures : ARMA, ANN, SWRRB, and IHACRES models Type de document : texte imprimé Auteurs : M. Reza Ghanbarpour, Auteur ; Maryam Amiri, Auteur ; Mehdi Zarei, Auteur Année de publication : 2012 Article en page(s) : pp. 281-292 Note générale : Hydraulique Langues : Anglais (eng) Mots-clés : Stream  flow  Prediction  Model  accuracy  Kasilian  watershed  Iran Résumé : Stream flow prediction is crucial for water resource planning and management at the watershed scale. This study investigates various modelling approaches, namely, autoregressive integrated moving average, deseasonalized autoregressive moving average, artificial neural network (ANN), simulator for water resources in rural basins, and identification of hydrographs and components from rainfall, evaporation, and stream (IHACRES) models, to simulate and predict stream flow in Kasilian watershed in northern Iran. This research represents a case study on forest watershed modelling with the lack of enough hydro-meteorological data. The comparison of the prediction performance of the models was done based on some error estimation criteria. The results indicate that the ANN and IHACRES models perform better than the two other modelling approaches. The advantages and disadvantages of different hydrological models are discussed. ISSN : 1571-5124 En ligne : http://www.tandfonline.com/doi/full/10.1080/15715124.2012.699893 [article] Comparison of stream flow predicted in a forest watershed using different modelling procedures : ARMA, ANN, SWRRB, and IHACRES models [texte imprimé] / M. Reza Ghanbarpour, Auteur ; Maryam Amiri, Auteur ; Mehdi Zarei, Auteur . - 2012 . - pp. 281-292. Hydraulique Langues : Anglais (eng) in JRBM : International journal of river basin management > Vol. 10 N° 3 (Juillet 2012) . - pp. 281-292 Mots-clés : Stream  flow  Prediction  Model  accuracy  Kasilian  watershed  Iran Résumé : Stream flow prediction is crucial for water resource planning and management at the watershed scale. This study investigates various modelling approaches, namely, autoregressive integrated moving average, deseasonalized autoregressive moving average, artificial neural network (ANN), simulator for water resources in rural basins, and identification of hydrographs and components from rainfall, evaporation, and stream (IHACRES) models, to simulate and predict stream flow in Kasilian watershed in northern Iran. This research represents a case study on forest watershed modelling with the lack of enough hydro-meteorological data. The comparison of the prediction performance of the models was done based on some error estimation criteria. The results indicate that the ANN and IHACRES models perform better than the two other modelling approaches. The advantages and disadvantages of different hydrological models are discussed. ISSN : 1571-5124 En ligne : http://www.tandfonline.com/doi/full/10.1080/15715124.2012.699893