Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3161-2024
https://doi.org/10.5194/hess-28-3161-2024
Research article
 | 
19 Jul 2024
Research article |  | 19 Jul 2024

To what extent do flood-inducing storm events change future flood hazards?

Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou

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Cited articles

Ahearn, E. A.: Flood of April 2007 and Flood-Frequency Estimates at Streamflow-Gaging Stations in Western Connecticut, U.S. Geological Survey Scientific Investigations Report 2009-5108, 40, http://pubs.usgs.gov/sir/2009/5108 (last access: 16 July 2023), 2009. 
Ahrendt, S., Horner-Devine, A. R., Collins, B. D., Morgan, J. A., and Istanbulluoglu, E.: Channel Conveyance Variability can Influence Flood Risk as Much as Streamflow Variability in Western Washington State, Water Resour. Res., 58, e2021WR031890, https://doi.org/10.1029/2021WR031890, 2022. 
Alahakoon, D., Halgamuge, S. K., and Srinivasan, B.: Dynamic self-organizing maps with controlled growth for knowledge discovery, IEEE Trans. Neural. Netw., 11, 601–614, https://doi.org/10.1109/72.846732, 2000. 
Alfieri, L., Feyen, L., Dottori, F., and Bianchi, A.: Ensemble flood risk assessment in Europe under high end climate scenarios, Global Environ. Chang., 35, 199–212, https://doi.org/10.1016/j.gloenvcha.2015.09.004, 2015. 
Anderson, S. W. and Konrad, C. P.: Downstream-Propagating Channel Responses to Decadal-Scale Climate Variability in a Glaciated River Basin, J. Geophys. Res.-Earth, 124, 902–919, https://doi.org/10.1029/2018JF004734, 2019. 
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Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
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