Are 2D shallow-water solvers fast enough for early flood warning?  A comparative assessment on the 2021 Ahr valley flood event

Khosh Bin Ghomash, Shahin; Apel, Heiko; Caviedes-Voullième, Daniel

doi:https://doi.org/10.5194/nhess-24-2857-2024

Articles | Volume 24, issue 8

https://doi.org/10.5194/nhess-24-2857-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-24-2857-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 8

Research article

|

28 Aug 2024

Research article |

| 28 Aug 2024

Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event

Shahin Khosh Bin Ghomash, Heiko Apel, and Daniel Caviedes-Voullième

Data sets

Germany 2020 - Land cover based on Sentinel-2 data mundialis https://www.mundialis.de/en/germany-2020-land-cover-based-on-sentinel-2-data/

Data and Scripts for Advancing a High-Resolution Impact-based Early Warning System for Riverine Flooding H. Najafi et al. https://doi.org/10.48758/UFZ.14607

Digitales Geländemodell Gitterweite 10 m (DGM10) Bundesamt für Kartographie und Geodäsie https://gdz.bkg.bund.de/index.php/default/digitale-geodaten/digitale-gelandemodelle/digitales-gelandemodell-gitterweite-10-m-dgm10.html

Digitales Geländemodell Gitterweite 5 m (DGM5) Bundesamt für Kartographie und Geodäsie https://gdz.bkg.bund.de/index.php/default/digitale-geodaten/digitale-gelandemodelle/digitales-gelandemodell-gitterweite-5-m-dgm5.html

igitales Oberflächenmodell Gitterweite 1 m (DOM1) Bundesamt für Kartographie und Geodäsie https://gdz.bkg.bund.de/index.php/default/digitale-geodaten/digitale-gelandemodelle/digitales-oberfaechenmodell-dom1.html

Model code and software

SERGHEI (1.1.0) Daniel Caviedes Voullième et al. https://doi.org/10.5281/zenodo.8159542

Short summary

Early warning is essential to minimise the impact of flash floods. We explore the use of highly detailed flood models to simulate the 2021 flood event in the lower Ahr valley (Germany). Using very high-resolution models resolving individual streets and buildings, we produce detailed, quantitative, and actionable information for early flood warning systems. Using state-of-the-art computational technology, these models can guarantee very fast forecasts which allow for sufficient time to respond.