PhD position at ENIT (Tarbes) and IMFT (Toulouse): Impact model for the evaluation of the flooding risk.

Context and objectives:

The term “flash flood” refers to sudden floods having high peak discharges in a short response time. They result from a combination of meteorological and hydrological factors. Intense storm events delivering high amounts of rain water appear to be the first condition for flash flooding to be initiated. Watershed characteristics such as small catchments (under 500 km2 ) or steep slopes are associated with short and rapid flood timing. Flash floods are one of the most destructive hazards in the Mediterranean region and have caused casualties and billions of euros of damages in France over the last two decades. The recent case of June 2013 occurred in the Pyrenees killed 2 people and resulted in thousands of victims. The damages were estimated at about 134 million euros. The contrasted topography, the complexity of the continental surfaces in terms of geology and land use, the difficulty to characterize the initial moisture state of the catchments make these extreme events very difficult to assess and predict. The proposed PhD will aim at improving the understanding of the hydrological response by contemporary use of empirical and analytical (or rainfall-runoff) modelling. The ambition is to develop an operational methodology for the anticipation of the risk of inundation. The work will include an inter-comparison of models dedicated to flash flood prediction and allowing the characterization of the resulting risk. The proposed work will therefore contribute to the building of a relevant methodology of risk evaluation for a better protection of the population. The long-standing collaboration between the IMFT and the SCHAPI2 will facilitate the transfer of knowledge to the appropriate operational services.

Keywords: flash flood, risk, hydrological modelling, bayesian networks

Description of the work: The planning of the PhD is as follows:

− A review of the literature of the mechanistic models derived from fluid mechanics and of the risk models integrating the uncertainty to evaluate the probability of determination of a flood.

− Development of an impact model: definition of the important variables and implementation of the bayesian networks in successive stages.

− Comparison of the results of the empirical model with an existing rainfall-runoff model on the same data set.

− Possible coupling of the 2 models in order to directly take into account the parameters uncertainty in the rainfall-runoff model.

Required qualifications: Master’s degree with good knowledge in the field of distributed hydrological modeling. Good knowledge of the programming language FORTRAN is required. Skills in mathematics and English are also essential. Knowledge in statistics and probability and, more particularly, in the field of bayesian networks would be appreciated but are not mandatory.

Duration and salary: The position will be funded for 3 years by the INPT and based at the ENIT for the implementation of the model and at the IMFT for the implementation of the process oriented model. The net monthly salary will be about 1 500 euros.

Contact for application: The application must include a letter of application describing the motivation for the position, a curriculum vitae and, whenever possible, the names, phones and email addresses of two referees. The set must be sent to francois.peres@enit.fr and Helene.Roux@imft.fr. Additional information can be obtained from the advisors.

Application deadline: June 15, 2015

PDF INFO: PhD position at ENIT (Tarbes) and IMFT (Toulouse)

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