  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.
