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Identification of Spatial and Temporal Contributions of Rainfalls to Flash Floods Using Neural Network Modelling: Case Study on the Lez Basin (Southern France) : Volume 12, Issue 4 (08/04/2015)

By Darras, T.

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Book Id: WPLBN0004012324
Format Type: PDF Article :
File Size: Pages 38
Reproduction Date: 2015

Title: Identification of Spatial and Temporal Contributions of Rainfalls to Flash Floods Using Neural Network Modelling: Case Study on the Lez Basin (Southern France) : Volume 12, Issue 4 (08/04/2015)  
Author: Darras, T.
Volume: Vol. 12, Issue 4
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Kong-A-Siou, L., Vayssade, B., Pistre, S., Darras, T., Johannet, A., & Estupina, V. B. (2015). Identification of Spatial and Temporal Contributions of Rainfalls to Flash Floods Using Neural Network Modelling: Case Study on the Lez Basin (Southern France) : Volume 12, Issue 4 (08/04/2015). Retrieved from http://hawaiilibrary.net/


Description
Description: LGEI, École des mines d'Alès, 6 avenue de Clavières, 30319 Alès CEDEX, France. Flash floods pose significant hazards in urbanised zones and have important human and financial implications in both the present and future due to the likelihood that global climate change will exacerbate their consequences. It is thus of crucial importance to better model these phenomena especially when they occur in heterogeneous and karst basins where they are difficult to describe physically. Toward this goal, this paper applies a recent methodology (KnoX methodology) dedicated to extracting knowledge from a neural network model to better determine the contributions and time responses of several well-identified geographic zones of an aquifer. To assess the interest of this methodology, a case study was conducted in Southern France: the Lez hydrosystem whose river crosses the conurbation of Montpellier (400 000 inhabitants). Rainfall contributions and time transfers were estimated and analysed in four geologically-delimited zones to estimate the sensitivity of flash floods to water coming from the surface or karst. The Causse de Viol-le-Fort is shown to be the main contributor to flash floods and the delay between surface and underground flooding is estimated to be three hours. This study will thus help operational flood warning services to better characterise critical rainfall and develop measurements to design efficient flood forecasting models. This generic method can be applied to any basin with sufficient rainfall–runoff measurements.

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

Excerpt
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