Usefulness of the reversible jump Markov chain Monte Carlo model in regional flood frequency analysis.

Ribatet, Mathieu; Sauquet, Eric; Grésillon, Jean-Michel et Ouarda, Taha B. M. J. (2007). Usefulness of the reversible jump Markov chain Monte Carlo model in regional flood frequency analysis. Water Resources Research , vol. 43 , nº 8. W08403. DOI: 10.1029/2006WR005525.

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Résumé

Regional flood frequency analysis is a convenient way to reduce estimation uncertainty when few data are available at the gauging site. In this work, a model that allows a non‐null probability to a regional fixed shape parameter is presented. This methodology is integrated within a Bayesian framework and uses reversible jump techniques. The performance on stochastic data of this new estimator is compared to two other models: a conventional Bayesian analysis and the index flood approach. Results show that the proposed estimator is absolutely suited to regional estimation when only a few data are available at the target site. Moreover, unlike the index flood estimator, target site index flood error estimation seems to have less impact on Bayesian estimators. Some suggestions about configurations of the pooling groups are also presented to increase the performance of each estimator.

Type de document:	Article
Mots-clés libres:	extreme value theory; regional frequency analysis; reversible jump
Centre:	Centre Eau Terre Environnement
Date de dépôt:	28 nov. 2019 19:42
Dernière modification:	16 févr. 2021 17:57
URI:	https://espace.inrs.ca/id/eprint/9495

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