EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting

Ervin Zsoter1, Christel Prudhomme1, Elisabeth Stephens2, and Hannah Cloke2,3
Ervin Zsoter et al.
  • 1European Centre for Medium-Range Weather Forecasts, UK
  • 2Department of Geography and Environmental Science, University of Reading, UK
  • 3Department of Earth Sciences, Uppsala University,Sweden

Global flood forecasting systems rely on definition of flood thresholds for identifying upcoming flood events. Existing methods for flood threshold definition can often be based on reanalysis datasets and single thresholds, used for all forecast lead times, but this leads to inconsistencies between how the extreme flood events are represented in the flood thresholds and the ensemble forecasts.

This paper explores the potential benefits of using river flow ensemble reforecasts to generate flood thresholds that can deliver improved reliability and skill. Using the Copernicus Emergency Management Service’s Global Flood Awareness System, the impact of the dataset and the method used to sample the annual maxima to define flood thresholds, are analysed in terms of threshold magnitude, forecast reliability and skill for different flood severity levels and lead times.

It was found that the variability of the threshold magnitudes, when estimated from the different annual maxima samples, can be extremely large, as can the subsequent impact on forecast skill. It was also found that reanalysis-based thresholds should only be used for the first few days, after which ensemble-reforecast-based thresholds, that vary with forecast lead time and can account for the forecast bias trends, provide more reliable and skilful flood forecasts.



How to cite: Zsoter, E., Prudhomme, C., Stephens, E., and Cloke, H.: Using ensemble reforecasts to generate flood thresholds for improved global flood forecasting, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16303,, 2021.


Display file