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Calibration probabiliste d'un modèle de propagation d'avalanches pour le calcul de périodes de retour, le zonage et l'optimisation d'ouvrages de protection

Abstract : Avalanche predetermination is a multivariate extreme statistical problem. For engineering, design values and return periods are often used in a questionable manner. The aim of this work is to propose a rigorous framework coupling numerical modelling and field data. The different information and uncertainty sources are brought together and quantified using hierarchical Bayesian modelling schemes. MCMC simulations are used to perform the on site calibration of a complex numerical avalanche model. In the predictive phase, return period is defined as a one-to-one mapping of the runout distance. This allows evaluating all reference scenarios corresponding to the chosen design values. Finally, as soon as hazard consequences are quantified as a function of its magnitude, a decisional approach can be used for the design of defence structures. This is illustrated by the optimisation of an avalanche dam.
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Submitted on : Friday, May 22, 2009 - 9:03:37 AM
Last modification on : Wednesday, March 16, 2022 - 9:36:01 AM
Long-term archiving on: : Thursday, June 10, 2010 - 8:42:03 PM

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Nicolas Eckert, Eric Parent, Mohamed Naaim. Calibration probabiliste d'un modèle de propagation d'avalanches pour le calcul de périodes de retour, le zonage et l'optimisation d'ouvrages de protection. 41èmes Journées de Statistique, SFdS, Bordeaux, May 2009, Bordeaux, France, France. pp.6. ⟨inria-00386583⟩

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