EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Foreseeing the propensity of rivers to extreme floods

Stefano Basso1,2, Ralf Merz2,3, Larisa Tarasova2, and Arianna Miniussi4,2
Stefano Basso et al.
  • 1Norwegian Institute for Water Research (NIVA), Oslo, Norway (
  • 2Department of Catchment Hydrology, Helmholtz Centre for Environmental Research – UFZ, Halle (Saale), Germany
  • 3Institute of Geosciences and Geography, Martin-Luther University Halle-Wittenberg, Halle (Saale), Germany
  • 4P&C International, General Reinsurance, Cologne, Germany

Notwithstanding hundreds of years of efforts, flooding is still the most common natural disaster. A reliable assessment of the impending flood hazard is indeed an outstanding challenge with severe consequences. Mistaken estimates of the odds and magnitude of extreme floods especially result in huge economic losses due to widespread destruction of infrastructure and properties.

We show here that we can infer the propensity of rivers to generate extreme floods by means of two hydroclimatic and geomorphic descriptors of watersheds, which embody the spatial organization of the stream network and the characteristic streamflow dynamics of the river basin. These features are main determinants of a sharp increase of the magnitude of the rarer floods and of the flood value for which this marked growth of magnitude occurs, which we term flood divide as it separates ordinary from extreme floods. Their relevance is suggested by a novel ecohydrological approach to flood hazard assessment and confirmed by observations from hundreds of watersheds in the USA and Germany.

We first ascertained the capability of the method to distinguish between basins which do not and exhibit a flood divide, and its ability to dependably estimate its magnitude. We then applied a dimensional reduction tool to pinpoint key physioclimatic controls of the occurrence of flood divides, verifying our results against data. Finally, we utilized descriptors of these controls (namely the hydrograph recession exponent and streamflow variability) within binary logistic regression to predict the possible occurrence of flood divides and extreme floods in river basins. Repeated analyses for independent realizations of subsets of data indicate good prediction accuracy.

The identified controls of the propensity of rivers to generate extreme floods are readily estimated from primary hydroclimatic variables. The tool thus allows for inferring cases where extreme events shall be expected from short records of ordinary events, providing valuable information to raise awareness of the peril of floods in river basins.

This study summarizes results of the DFG-funded project "Propensity of rivers to extreme floods: climate-landscape controls and early detection - PREDICTED" (Deutsche Forschungsgemeinschaft - German Research Foundation, Project Number 421396820).

How to cite: Basso, S., Merz, R., Tarasova, L., and Miniussi, A.: Foreseeing the propensity of rivers to extreme floods, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2000,, 2023.

Supplementary materials

Supplementary material file