In regional flood frequency analysis it is of interest to estimate high quantiles of a local riverflow distribution by gathering information from similar stations in the neighborhood. E. g., thepopular Index Flood (IF) approach is based on an assumption termed regional homogeneity,which states that the quantile curves of those stations only differ by a site-specific factor, theso-called index flood, and it is assumed that the station's distribution is known up to somefinite-dimensional parameter. In this context the method of probability weighted moments (orequivalently L-moments) is most popular for parameter estimation. While the observationsoften can be regarded as independent in time, a challenge arises from the fact that river flows from nearby stations are strongly dependent in space. To the best of our knowledge, none of theapproaches from the literature based on the IF-model and on L-moments is able to take spatialdependence adequately into account. Our goal is to fill this gap. We present asymptotic theorythat does not ignore inter-site dependence, which, for instance, allows to evaluate estimationuncertainty. As an application of this theory, a test procedure to check for regional homogeneityunder index-flood assumptions is given and reviewed in a simulation study.
展开▼
