Challenges in analysing and modelling extreme floods: The case study of Ahr catchment
- University of Potsdam, Institute for Environmental Science and Geography, Hydrology and Climatology, Potsdam, Germany (bora.shehu@uni-potsdam.de)
The extreme weather conditions of July 2021 caused major flooding’s in multiple tributaries of the Meuse and Rhine rivers. Particularly the Ahr Valley in Germany was greatly affected, where exceptional damage and severe human loss was registered. Since then, several studies have been conducted to understand the extremity, the major driving forces, the particular mechanisms of this flood and the possible impacts of climate change on the generation of such an event. Here the main objective is to perform a hydrological analysis of the July 2021 Ahr event and discuss the challenges in modelling or analysing this event.
First, we show that particularly the rainfall field is associated with high uncertainty, as seen by the high variability between the different rainfall products available. The average areal rainfall volume can differ between products with as much as 50mm/day, which constitutes almost 55% of the rainfall volume estimated by Radolan. To capture the full uncertainty-range of the rainfall field, rainfall simulations conditioned both on radar and station observations are implemented.
Next, based on rainfall simulations and reconstructed discharge data, runoff coefficients (Rc) are shown to be ranging between 0.6 to 1.2 (median 0.7). These values are clearly higher than expected in continental climate (Rc ~ 0.20-0.51) and the latest 100-year return flood observed in 2016 (with Rc ~ 0.4). The high lower range suggests, that the dominant processes have changed, with slower components of surface runoff shifting to faster ones. This agrees well with the observed traces of erosion, surface water and flow paths in parts of the catchment.
Lastly, the reconstructed discharge data are also subjected to uncertainty due to lack of observations and the non-representativeness of the stage-discharge curve during the flood wave. Hence, high Rc values do not only originate from underestimated rainfall but as well from possible overestimated flood volume. For this purpose, discharge was estimated with the Larsim model. As expected due to the change of the dominant processes, the pre-event parameter set underestimates considerably the flood volume, while the post-calibration one agrees better with the reconstructed data. On both cases, the computed runoff coefficient ranges between 0.4 to 0.7.
To conclude, extraordinary events such as the July 2021 in Ahr Catchment, are accompanied with high uncertainty and as such are difficult to be analysed or modelled. Nevertheless, the results dictate that the surface runoff played an important role in July 2021. At the same time, it is clear that the landscape still has a considerable retention effect, between 30% and 50%, even for such a heavy rainfall.
How to cite: Shehu, B. and Bronstert, A.: Challenges in analysing and modelling extreme floods: The case study of Ahr catchment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18032, https://doi.org/10.5194/egusphere-egu24-18032, 2024.
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