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. We propose an objective framework for selecting rainfall hazard mapping models in a region starting from raingauge data. Our methodology is based on the evaluation of severalgoodness-of-fit scores at regional scale in a cross-validation framework,allowing us to assess the goodness-of-fit of the rainfall cumulativedistribution functions within the region but with a particular focus on theirtail. Cross-validation is applied both to select the most appropriatestatistical distribution at station locations and to validate the mapping ofthese distributions. To illustrate the framework, we consider daily rainfallin the Ardeche catchment in the south of France, a 2260 km 2 catchment with strong inhomogeneity in rainfall distribution. We compareseveral classical marginal distributions that are possibly mixed over seasonsand weather patterns to account for the variety of climatological processestriggering precipitation, and several classical mapping methods. Among thosetested, results show a preference for a mixture of Gamma distribution overseasons and weather patterns, with parameters interpolated with thin platespline across the region.

Mapping rainfall hazard based on rain gauge data: an objective cross-validation framework for model selection