Prediction of Extraordinarily High Floods Emerging From Heterogeneous Flow Generation Processes

Abstract

River floods are generated by various processes that, if disregarded, may induce errors in flood hazard assessment. This is particularly relevant where events extraordinarily larger than the typical floods have been observed, that is, for rivers with a flood divide in their flood-frequency curves. We identify 11 such cases in a large set of German catchments and test a statistical approach that accounts for different runoff-generation processes to predict the magnitude and frequency of extraordinarily high floods. We observe that in catchments with a flood divide, ordinary peaks are generated by different runoff-generation processes and the distribution of at least one process is heavy-tailed. By accounting for the different tail behaviors of multiple processes, we can reproduce flood-frequency curves in these catchments. Our findings shed light on the origin of flood divides and set a method to improve the estimation of high flood quantiles in these high-risk cases.