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Apport de la simulation conditionnelle géostatistique pour la prévision immédiate d'ensemble de pluies et l’alerte aux crues rapides

Abstract : Each year, flash floods, generated by small fast-responding catchments hit by intense rainfall, are responsible for huge human and economic losses. To mitigate these impacts, it is necessary to use forecasting systems combining meteorological and hydrological forecasts at small temporal and spatial scales. Because of the underlying difficulties, these systems have to be able to communicate the uncertainties of their forecasts. Uncertainties associated to observed or future rainfall are often seeing as those having the most important impact, in particularly in the case of flash floods localised on small areas.The main aim of this thesis is to study the potential of a geostatistical conditional simulation method to generate an ensemble of rainfall scenarios that can be used by a flash flood warning system. We seek to generate a reliable ensemble of rain fields by making the best use of the strengths of the measurements often available for nowcasting: the spatial and temporal properties of rainfall fields provided by the radar data and the rainfall intensities measured by rain gauges. In order to achieve our objectives, we use radar and rainfall data from 17 intense rainfall events observed in the Var region (south-east France) between 2009 and 2013.The first part of this thesis was devoted to taking into account the uncertainties on the observations of rainfall. For this purpose, the SAMPO-TBM generator developed at Irstea-Lyon is adapted to provide simulations of alternative rain fields to the observed radar rain field, while respecting the rainfall values observed by the rain gauges through a conditioned simulation. The evaluation of the generated fields shows that the method implemented is able to generate a reliable ensemble of rain fields and thus to propose a quantification of the uncertainties on the observed rain fields.In the second part of this thesis, the capacity of our method to be used for the nowcasting of rainfall is evaluated. Several methods are tested for the parameterization of the rainfall generator and for the adjustment of the outputs. These methods are evaluated by considering the main attributes of forecast quality, such as accuracy, reliability, precision, discrimination and overall forecast performance. The best method is the one estimating generator parameters over the last four hours, but also using only the last hour for the parameter related to the mean of the non-zero rainfall distribution, combined by the adjustment of the outputs based on the last forecast error.Finally, in the final part of this thesis, ensemble rainfall forecasts are used as inputs of the flash flood forecasting method AIGA developed at Irstea Aix-en-Provence. The AIGA method enables return period of the ongoing event to estimate at ungauged catchments. The 3th-7th November 2011 event in the Var region is used to illustrate the potential of our method. Nowcasting maps indicating, for different lead times and for the whole hydrological network of the region, the probability to exceed a given return period are produced. They are compared to the localization of observed damages collected from field surveys, illustrating a real interest for the real time crisis management
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Angélica Nardo Caseri. Apport de la simulation conditionnelle géostatistique pour la prévision immédiate d'ensemble de pluies et l’alerte aux crues rapides. Sciences de la Terre. AgroParisTech, 2017. Français. ⟨NNT : 2017AGPT0002⟩. ⟨tel-02949005⟩



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