Prediction of Extraordinarily High Floods Emerging From Heterogeneous Flow Generation Processes

Autor: Sumra Mushtaq, Arianna Miniussi, Ralf Merz, Larisa Tarasova, Francesco Marra, Stefano Basso
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Geophysical Research Letters, Vol 50, Iss 20, Pp n/a-n/a (2023)
Druh dokumentu: article
ISSN: 1944-8007
0094-8276
DOI: 10.1029/2023GL105429
Popis: 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.
Databáze: Directory of Open Access Journals
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