Articles | Volume 19, issue 10
https://doi.org/10.5194/hess-19-4397-2015
https://doi.org/10.5194/hess-19-4397-2015
Research article
 | 
30 Oct 2015
Research article |  | 30 Oct 2015

Identification of spatial and temporal contributions of rainfalls to flash floods using neural network modelling: case study on the Lez basin (southern France)

T. Darras, V. Borrell Estupina, L. Kong-A-Siou, B. Vayssade, A. Johannet, and S. Pistre

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Short summary
Flash floods are important hazards in urbanised zone and constitute important human and financial stakes. This paper applies a novel methodology, KnoX, dedicated to extract knowledge from a neural network model. It was shown that KnoX method could help to better characterize processes of both surface and underground floods. A case study is chosen in France: the Lez karst hydrosystem whose river crosses the city of Montpellier (400 000 inhabitants). Results will help flood warning services.