Articles | Volume 29, issue 6
https://doi.org/10.5194/hess-29-1525-2025
https://doi.org/10.5194/hess-29-1525-2025
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

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Cited articles

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Alstott, J., Bullmore, E., and Plenz, D.: Powerlaw: A python package for analysis of heavy-tailed distributions, PLoS One, 9, e95816, https://doi.org/10.1371/journal.pone.0085777, 2014. 
Arai, R., Toyoda, Y., and Kazama, S.: Runoff recession features in an analytical probabilistic streamflow model, J. Hydrol., 597, 125745, https://doi.org/10.1016/j.jhydrol.2020.125745, 2020. 
Barnes, B. S.: The structure of discharge-recession curves, EOS T. AGU, 20, 721–725, https://doi.org/10.1029/TR020i004p00721, 1939. 
Basso, S., Botter, G., Merz, R., and Miniussi, A.: PHEV! The PHysically-based Extreme Value distribution of river flows, Environ. Res. Lett., 16, 124065, https://doi.org/10.1088/1748-9326/ac3d59, 2021. 
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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.
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