Constructing a geography of heavy-tailed flood distributions: insights from common streamflow dynamics

Wang, Hsing-Jui; Merz, Ralf; Basso, Stefano

doi:https://doi.org/10.5194/hess-29-1525-2025

Articles | Volume 29, issue 6

https://doi.org/10.5194/hess-29-1525-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-29-1525-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 6

Research article

|

20 Mar 2025

Research article |

| 20 Mar 2025

Constructing a geography of heavy-tailed flood distributions: insights from common streamflow dynamics

Hsing-Jui Wang, Ralf Merz, and Stefano Basso

Supplement

https://doi.org/10.5194/hess-29-1525-2025-supplement

Data sets

SRTM 90m Digital Elevation Database v4.1 CGIAR Consortium for Spatial Information https://cgiarcsi.community/data/srtm-90m-digital-elevation-database-v4-1/

Abfluss Bayern Bayerisches Landesamt für Umwelt https://www.gkd.bayern.de/de/fluesse/abfluss

Global Runoff Database Bundesanstalt für Gewässerkunde https://grdc.bafg.de/data/data_portal_guide/

Global Dams and Reservoirs Dataset: GeoDAR v.1.0 J. Wang et al. https://doi.org/10.5281/zenodo.6163413

MOPEX NOAA-National Weather Service-Office of Hydrologic Development https://hiscentral.cuahsi.org/pub_network.aspx?n=5599

GeoDAR: Georeferenced global Dams And Reservoirs dataset for bridging attributes and geolocations J. Wang et al. https://doi.org/10.5281/zenodo.6163413

Short summary

Extreme floods are more common than expected. Knowing where these floods are likely to occur is key for risk management. Traditional methods struggle with limited data, causing uncertainty. We use common streamflow dynamics to indicate extreme flood propensity. Analyzing data from Atlantic Europe, northern Europe, and the US, we validate this novel approach and unravel intrinsic linkages between regional geographic patterns and extreme flood drivers.