Hourly Flow Forecasting in a Karst Watershed: The Iton River (France)

Rainfall–runoff models are widely used in water management and flood forecasting. In this study, we present a rainfall–runoff model to forecast hourly flows based on an artificial neural network (ANN). This model was developed and applied to the Iton watershed (northwestern France) to solve the problems of nonlinearity in the rainfall–runoff relationship resulting from karst and complex hydrogeological behaviors. The model design required several steps during which we were able to identify the model parameters and create the database needed to perform the flow rate forecast. This work has resulted in an ANN model able to perform an efficient prediction up to a 48 h time horizon. These results confirm that ANN models can play an important role in forecasting the nonlinear rainfall–runoff relationship encountered in many watersheds.

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Publication Details

Journal
Water
Published
2025-03-27
DOI
https://doi.org/10.3390/w17070977
Citations
2
Primary Topic
Hydrological Forecasting Using AI
Type
article
Field-Weighted Citation Impact
1.60
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article

Hourly Flow Forecasting in a Karst Watershed: The Iton River (France)

Ouissem Kharroubi, Ahmed Benamar, Mohamed-Tahar Ammami, Raouf Achour
2 citations
Water
Hydrological Forecasting Using AI
1.60
article

Hourly Flow Forecasting in a Karst Watershed: The Iton River (France)

Ouissem Kharroubi, Ahmed Benamar, Mohamed-Tahar Ammami, Raouf Achour
article en
2 citations

Abstract

Rainfall–runoff models are widely used in water management and flood forecasting. In this study, we present a rainfall–runoff model to forecast hourly flows based on an artificial neural network (ANN). This model was developed and applied to the Iton watershed (northwestern France) to solve the problems of nonlinearity in the rainfall–runoff relationship resulting from karst and complex hydrogeological behaviors. The model design required several steps during which we were able to identify the model parameters and create the database needed to perform the flow rate forecast. This work has resulted in an ANN model able to perform an efficient prediction up to a 48 h time horizon. These results confirm that ANN models can play an important role in forecasting the nonlinear rainfall–runoff relationship encountered in many watersheds.

WaterVol. 17(7)
Centre National de la Recherche Scientifique (FR), Université Le Havre Normandie (FR), Normandie Université (FR), École Spéciale des Travaux Publics (FR), Laboratoire Ondes et Milieux Complexes (FR), University of Jendouba (TN)
Clean water and sanitation
Openalex Percentile: Top 19%
Hydrological Forecasting Using AI
1.60
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Hourly Flow Forecasting in a Karst Watershed: The Iton River (France) — Ouissem Kharroubi, Ahmed Benamar, et al. · Water (2025) | TGRS Research Map | TGRS