River flooding mechanisms and their changes in  Europe revealed by explainable machine learning

Jiang, Shijie; Bevacqua, Emanuele; Zscheischler, Jakob

doi:https://doi.org/10.5194/hess-26-6339-2022

Articles | Volume 26, issue 24

https://doi.org/10.5194/hess-26-6339-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-6339-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 24

Research article

|

16 Dec 2022

Research article |

| 16 Dec 2022

River flooding mechanisms and their changes in Europe revealed by explainable machine learning

Shijie Jiang, Emanuele Bevacqua, and Jakob Zscheischler

Supplement

https://doi.org/10.5194/hess-26-6339-2022-supplement

Data sets

Global Runoff Database Federal Institute of Hydrology https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser

E-OBS gridded dataset ECA & D https://www.ecad.eu/download/ensembles/download.php

he Global Streamflow Indices and Metadata Archive - Part 1: Station catalog and Catchment boundary H. X. Do, L. Gudmundsson, M. Leonard, and S. Westra https://doi.org/10.1594/PANGAEA.887477

Watershed Boundaries of GRDC Stations Federal Institute of Hydrology https://www.bafg.de/GRDC/EN/02_srvcs/22_gslrs/222_WSB/watershedBoundaries.html

Digital Elevation - Global 30 Arc-Second Elevation (GTOPO30) EROS https://doi.org/10.5066/F7DF6PQS

Model code and software

An interpretive deep learning framework for identifying flooding mechanisms S. Jiang https://doi.org/10.5281/zenodo.4686106

Short summary

Using a novel explainable machine learning approach, we investigated the contributions of precipitation, temperature, and day length to different peak discharges, thereby uncovering three primary flooding mechanisms widespread in European catchments. The results indicate that flooding mechanisms have changed in numerous catchments over the past 70 years. The study highlights the potential of artificial intelligence in revealing complex changes in extreme events related to climate change.