Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1029/2024WR038667
Licence creative commons licence
Title (Primary) Estimation of extreme floods using a statistical and conceptual mModel of the hydrological response
Author Devò, P.; Basso, S.; Marani, M.
Source Titel Water Resources Research
Year 2025
Department CATHYD
Volume 61
Issue 5
Page From e2024WR038667
Language englisch
Topic T5 Future Landscapes
Data and Software links https://doi.org/10.5281/ZENODO.15262058
Supplements https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1029%2F2024WR038667&file=2024WR038667-sup-0001-Supporting+Information+SI-S01.pdf
Keywords hydrology; catchment hydrology; extreme streamflow/discharge
Abstract The robust estimation of flood peak discharge values is critical for designing mitigation measures and increasing preparedness to natural hazards. Traditional flood estimation methods are, however, severely limited by data series shorter than the return period of interest, as they only use annual maxima or a few values above a high threshold. Here we couple two recent advances in flood estimation from short data samples, namely the Metastatistical Extreme Value Distribution (MEVD) and a conceptual model of flood generation processes, the Physically based Extreme Value (PhEV) distribution of river flows. The result is a methodology, defined through a few hydrologic attributes describing runoff generation and catchment response, to estimate extreme discharge in poorly gauged basins, which we test on data from 178 catchments in Germany. We find that extremes are best estimated when PhEV runoff-generation parameters are set using the long-term mean discharge and precipitation depth, while catchment response parameters are estimated by statistical fitting to observed peak streamflow values. This estimation method interestingly outperforms a methodology in which all parameters are tuned to optimize the reproduction of the statistics of observed peak streamflow values. Our results show that the median relative error associated with MEVD-PhEV, across the large data set explored, consistently remains between −50% and +50%. Hence, MEVD-PhEV yields useful estimates of extreme flows with limited observational information and with no need of preselecting a suitable distribution for ordinary peak discharge values, a step that is substituted by the inclusion of catchment hydrologic information.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=30893
Devò, P., Basso, S., Marani, M. (2025):
Estimation of extreme floods using a statistical and conceptual mModel of the hydrological response
Water Resour. Res. 61 (5), e2024WR038667 10.1029/2024WR038667