EGU24-16095, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-16095
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data. 

Anais Couasnon1,3, Laurène Bouaziz3, Ruben Imhoff3, Hessel Winsemius3, Mark Hegnauer3, Niek van der Sleen4, Robert Slomp4, Leon van Voorst2, and Henk van den Brink2
Anais Couasnon et al.
  • 1Vrije Universiteit Amsterdam, Institute for Environmental Studies, Amsterdam, Netherlands
  • 2Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
  • 3Deltares, Delft, The Netherlands
  • 4Rijkswaterstaat, The Netherlands

Understanding extreme discharge behavior is of importance for flood design and risk management. For example, estimates of large extreme discharge return periods such as the 100-year return period or higher are often needed as a basis for flood hazard maps or dike design. Yet, frequency analysis based on decade-long discharge records show a large uncertainty for these frequencies, among others due to the statistical uncertainty from the distribution parameters.  This is not the case for the shape parameter, a key parameter that describes the upward or downward curvature of the tail of the distribution and thus an indicator of extreme discharge behavior. 

This study provides robust estimates of the shape parameter by using the 1,040 years of synthetic daily discharge generated for the Meuse catchment as part of the EMfloodResilience project from the Interreg Euregio Meuse-Rhine program. The spatially-distributed hydrological model wflow_sbm, calibrated and validated for the Meuse catchment, is forced with 16 synthetic climate ensembles of 65 years representative for the current climate from the physically-based KNMI regional climate model RACMO climate model at a daily and hourly time step. The annual maxima (AM) from hydrological years (Oct-Sep) are retrieved from these continuous time series, and a GEV distribution is fit to the AM. We observe a clear spatial pattern of the shape parameter across the Meuse catchment. Using this large dataset of shape parameters, we also review the possible reasons for the different tail behavior obtained with respect to rainfall statistics, catchment characteristics and river systems following the In doing so, we aim to bridge the extreme value statistical modelling with our current understanding of the extreme hydrological signatures present in the catchment.

How to cite: Couasnon, A., Bouaziz, L., Imhoff, R., Winsemius, H., Hegnauer, M., van der Sleen, N., Slomp, R., van Voorst, L., and van den Brink, H.: Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16095, https://doi.org/10.5194/egusphere-egu24-16095, 2024.