Robust sub-seasonal and seasonal drought forecasts are essential for water managers and stakeholders coping with water shortage. Many studies have been conducted to evaluate the performance of hydrological forecasts, that is, streamflow. Nevertheless, only few studies evaluated the performance of hydrological drought forecasts. The objective of this study, therefore, is to analyse the skill and robustness of meteorological and hydrological drought forecasts on a catchment scale (the Ter and Llobregat rivers in Catalonia, Spain), rather than on a continental or global scale. Meteorological droughts were forecasted using downscaled (5 km) probabilistic weather reforecasts (ECMWF-SEAS4). These downscaled data were also used to produce hydrological drought forecasts, derived from time series of streamflow data simulated with a hydrological model (LISFLOOD). This resulted in seasonal hydro-meteorological reforecasts with a lead time up to 7 months, for the time period 2002–2010. These monthly reforecasts were compared to two datasets: (1) droughts derived from a proxy for observed data, including gridded precipitation data and discharge simulated by the LISFLOOD model, fed by these gridded climatological data; and (2) droughts derived from in situ observed precipitation and discharge. Results showed that the skill of hydrological drought forecasts is higher than the climatology, up to 3–4 months lead time. On the contrary, meteorological drought forecasts, analysed using the Standardized Precipitation Index (SPI), do not show added value for short accumulation times (SPI1 and SPI3). The robustness analysis showed that using either a less extreme or a more extreme threshold leads to a large change in forecasting skill, which points at a rather low robustness of the hydrological drought forecasts. Because the skill found in hydrological drought forecasts is higher than the meteorological ones in this case study, the use of hydrological drought forecasts in Catalonia is highly recommended for management of water resources.
- Catchment scale
- Forecasting skill
- Hydro-meteorological droughts
- Sensitivity analysis