[article]
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 |
in JRBM : International journal of river basin management > Vol. 10 N° 3 (Juillet 2012) . - pp. 281-292
[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 |
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