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Improvement of Bayesian MCMC approaches for regional flood frequency analyses

Abstract : Flood frequency analyses are often based on continuous series at gauging stations. However, the length of the available data sets is usually too short to provide reliable estimates of extreme design floods. Hence, hydrologists have tried to make use of alternative sources of information to enrich the datasets used for the statistical inferences. Three main approaches were therefore proposed. The first consists in extending the information in time, making use of historical and paleoflood data. The second, spatial extension, consists in merging statistically homogeneous data to build large regional data samples. Recently, a combination of the two techniques aiming at including regional estimated extreme discharges at ungauged sites in regional flood frequency analyses has been proposed\nocite{Gaume2010}. This paper presents a consolidation of this approach and its comparison with the standard regional flood frequency approach proposed by Hosking \& Wallis. Extreme peak discharges estimated at ungauged sites my be of great value for the evaluation of large return period (typically over 100 years) flood quantiles. They should therefore not be neglected despite the uncertainties associated to these estimates. It is shown here that these extremes can be relatively straightforwardly taken into account in regional flood frequency analyses.
keyword : HYDROLOGIE
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Chi Cong Nguyen. Improvement of Bayesian MCMC approaches for regional flood frequency analyses. Hydrology. UNIVERSITÉ DE NANTES, 2012. English. ⟨tel-00851169⟩

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