How does the seasonal forecast quality of hydrological extremes vary in space and time?

The scientific advancement in hydrological modeling along with the progress in numerical weather forecasting has allowed the generation of useful hydro-climate services providing skillful simulations and reliable forecasts. To meet the needs from the climate-dependent socio-economic sectors, such as energy production and public water supply, there is a need to quantify the predictability of hydrological extremes. In this study, seasonal hydrological reforecasts were generated across about 35,400 basins in Europe using the E-HYPE hydrological model for the period 1993-2015. The service setup uses seasonal predictions of daily mean precipitation and temperature from the fifth-generation seasonal forecasting system of the European Centre for Medium-Range Weather Forecasts (ECMWF SEAS5). Hydrological forecast predictability was analyzed with respect to the simulated streamflow climatology. The assessment was conducted on both high and low streamflow and therefore the Brier Skill Score (BSS) was used for 10th, 90th and 95th weekly percentiles for different initializations and lead times. Results show that overall hydrological extremes over Europe are well predicted in terms of BSS, with spatial and temporal variability depending on the initialization month and lead time. The results contribute to identifying different geographical areas and times where the seasonal hydrological forecasts provide an added-value on the long-term predictability of, and hence preparedness to, flooding and droughts, which consequently benefit regional and even national decision-making in various socio-economic sectors.