Abstract

Extreme events are rarely observed, so their analysis is generally based on observations of more frequent values. The relevance of the flood frequency analysis (FFA) method depends on its capability to estimate the frequency of extreme values with reasonable accuracy using extrapolation. An FFA method based on stochastic simulation of flood event is assessed based on its reliability and stability. For such an assessment, different training/testing decompositions are performed for a set of data from more than 1000 gauging stations. We showed that the method enables relevant ‘predictive’ estimates, e.g. by assigning correct return periods to the record values that are systematically absent in calibration datasets. The model is also highly stable vis-a-vis the sampling. This characteristic is linked to the use of regional statistical rainfall data and a simple rainfall–runoff model that requires the calibration of only one parameter.Editor D. Koutsoyiannis Associate editor Q. Zhang

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