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One of the most effective strategies to reduce the impacts of drought is by issuing a timely and targeted warning from month to seasons ahead to end users. Yet to accurately forecast the drought hazard on a sub-seasonal to seasonal time scale remains a challenge, and usually, meteorological drought is forecasted instead of hydrological drought, although the latter is more relevant for several impacted sectors. Therefore, we evaluate the hydro-meteorological drought forecast skill for the pan-European region using categorical drought classification method. The results show that the hydrological drought forecasts outperform the meteorological drought forecasts. Hydrological drought forecasts even show predictive power (area with perfect prediction >50%) beyond 2 months ahead. Our study also concludes that dynamical forecasts, derived from seasonal climate forecasts, have higher predictability than ensemble streamflow predictions. The results suggest that further development of seasonal hydrological drought forecasting systems are beneficial, particularly important in the context of global warming, where drought hazard will become more frequent and severe in multiple regions in the world.