Consideration of sample size uncertainty for the regionalization of type-specific flood frequency analyses

The regionalisation of flood frequencies is a precondition for the estimation of flood statistics for ungauged basins. We propose a flood type-specific regionalization, to take into account the different flood-generating processes. The different flood types are classified according to their meteorological causes. Their probability distributions are modelled by type-specific distribution functions which are combined into one statistical annual mixture model. For regionalisation, we specified the parameters of each type-specific probability distribution separately with hierarchical clustering and regressions from catchment attributes. By selection of the most relevant features, depending on the flood type, the specifics of flood-generating processes were considered. This approach offers a higher degree of freedom for regionalisation as it describes the relationships between catchment characteristics, meteorological causes of floods and response of watersheds. However, as for many regionalisation procedures, uncertainty is created by different observation periods of the gauged catchments used for regionalisation. Due to different observation periods, extreme events can be included in one sample, while for the neighboring catchment with shorter observation period this may not be the case. This stochastic uncertainty results in a heterogeneity of second and third moments which may bias the regionalization. We analyzed different scenarios to take into account this uncertainty and to include the information of long observation periods as well as the occurrence of extreme events for correcting the distribution parameters accordingly. This leads to more homogeneous regionalisation results.