Dépôt numérique

A regional Bayesian POT model for flood frequency analysis.

Ribatet, Mathieu; Sauquet, Eric; Grésillon, Jean-Michel et Ouarda, Taha B. M. J. (2007). A regional Bayesian POT model for flood frequency analysis. Stochastic Environmental Research and Risk Assessment , vol. 21 , nº 4. pp. 327-339. DOI: 10.1007/s00477-006-0068-z.

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Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency analysis is a convenient way to reduce the estimation uncertainty. In this work, we propose a regional Bayesian model for short record length sites. This model is less restrictive than the index flood model while preserving the formalism of “homogeneous regions”. The performance of the proposed model is assessed on a set of gauging stations in France. The accuracy of quantile estimates as a function of the degree of homogeneity of the pooling group is also analysed. The results indicate that the regional Bayesian model outperforms the index flood model and local estimators. Furthermore, it seems that working with relatively large and homogeneous regions may lead to more accurate results than working with smaller and highly homogeneous regions.

Type de document: Article
Mots-clés libres: regional frequency analysis; Bayesian inference; index flood; L-moments; Markov Chain Monte Carlo
Centre: Centre Eau Terre Environnement
Date de dépôt: 11 janv. 2021 16:50
Dernière modification: 11 janv. 2021 16:50
URI: https://espace.inrs.ca/id/eprint/10893

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