Grid technology reliability for flash flood forecasting: end-user assessment
Identifieur interne : 000634 ( Main/Exploration ); précédent : 000633; suivant : 000635Grid technology reliability for flash flood forecasting: end-user assessment
Auteurs : Vincent Thierion [France] ; Pierre-Alain Ayral [France] ; Jacob Geisel [France] ; Sophie Sauvagnargues [France] ; Olivier Payrastre [France]Source :
- Journal of Grid Computing [ 1570-7873 ] ; 2011-01-10.
English descriptors
- mix :
Abstract
The flash flood forecasting is one of the most important challenges for research in hydrology. The anticipation of extreme hydrological scenarios through rainfall-runoff models is still limited, mainly because of the high uncertainty of rainfall forecasts and of limited computing resources. The authors propose to simulate an ensemble of potential hydrological scenarios in order to support the forecaster's decision-making process. The developed applicative layer takes advantage of the computing capabilities of grid technology, significantly enhancing the management of independent modelling operations in an operational lead time. A set of experimentations is deployed in order to firstly assess efficiency of this applicative layer and secondly to gauge more broadly the potentialities of grid to handle flood crisis management operations. Finally, in managing more than one hundred hydrological simulations simultaneously, this experimental platform opens new perspectives for the improvement of hydrological forecast modelling, limited until now by recurrent lack of computing resources.
Url:
DOI: 10.1007/s10723-010-9173-9
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">The flash flood forecasting is one of the most important challenges for research in hydrology. The anticipation of extreme hydrological scenarios through rainfall-runoff models is still limited, mainly because of the high uncertainty of rainfall forecasts and of limited computing resources. The authors propose to simulate an ensemble of potential hydrological scenarios in order to support the forecaster's decision-making process. The developed applicative layer takes advantage of the computing capabilities of grid technology, significantly enhancing the management of independent modelling operations in an operational lead time. A set of experimentations is deployed in order to firstly assess efficiency of this applicative layer and secondly to gauge more broadly the potentialities of grid to handle flood crisis management operations. Finally, in managing more than one hundred hydrological simulations simultaneously, this experimental platform opens new perspectives for the improvement of hydrological forecast modelling, limited until now by recurrent lack of computing resources.</div>
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