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| Titel |
Identification of spatial and temporal contributions of rainfalls to flash floods using neural network modelling: case study on the Lez basin (southern France) |
| VerfasserIn |
T. Darras, V. Borrell Estupina, L. Kong-A-Siou, B. Vayssade, A. Johannet, S. Pistre |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 10 ; Nr. 19, no. 10 (2015-10-30), S.4397-4410 |
| Datensatznummer |
250120840
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| Publikation (Nr.) |
 copernicus.org/hess-19-4397-2015.pdf |
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| Zusammenfassung |
| Flash floods pose significant hazards in urbanised zones and have important
implications financially and for humans alike 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 improve the models of 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 (Knowledge eXtraction (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 Viols-le-Fort is shown to be the main contributor to
flash floods and the delay between surface and underground flooding is
estimated to be 3 h. 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–run-off
measurements. |
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