Rainfall-runoff modeling of flash floods in the absence of rainfall forecasts: the case of “Cévenol flash floods” |
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Authors: | Mohamed Toukourou Anne Johannet Gérard Dreyfus Pierre-Alain Ayral |
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Affiliation: | (1) State Office for Water Management, Kempten, Germany;(2) Flood Forecast River Main, Bavarian Environment Agency, Hof, Germany;(3) Department of Hydrology and River Basin Management, Technical University Munich, Munich, Germany;(4) Flood Information Centre, Bavarian Environment Agency, Munich, Germany |
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Abstract: | “Cévenol flash floods” are famous in the field of hydrology, because they are archetypical of flash floods that occur in populated
areas, thereby causing heavy damages and casualties. As a consequence, their prediction has become a stimulating challenge
to designers of mathematical models, whether physics based or machine learning based. Because current, state-of-the-art hydrological
models have difficulty performing forecasts in the absence of rainfall previsions, new approaches are necessary. In the present
paper, we show that an appropriate model selection methodology, applied to neural network models, provides reliable two-hour
ahead flood forecasts. |
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