Assessment of forecast skill of seasonal forecasts with the hydrologic model ParFlow/CLM to predict subsurface water resources under atmospheric drought conditions in central Europe

The repeated and severe droughts that have affected central Europe over the last years (2018, 2019, 2020, 2022) have triggered the need for sub-seasonal to seasonal forecasts of subsurface water resources. Such long-term forecasts are needed in several sectors such as agriculture, forestry, and water resources, to allow for elaborating and implementing management strategies able to deal with the reduced water resources.

In this context, we have developed a high-resolution (0.6km) monitoring and forecasting system of the terrestrial water cycle with the integrated, physics-based hydrologic model ParFlow/CLM over Germany and the surrounding regions. This model setup simulates the surface and 3D subsurface state and fluxes down to 60m depth, thereby covering the variably saturated zone as well as the saturated zone of shallow groundwater bodies. We use the seasonal 50-member ensemble forecast SEAS from the European Centre for Medium-Range Weather Forecasts (ECMWF) as atmospheric forcing for ParFlow/CLM. We calculate these forecasts over the whole available lead time, i.e., seven months, at the beginning of each meteorological season (March, June, September, and December).

In this study, we analyse the ability for the ParFlow/CLM seasonal forecasts to predict the evolution of water resources, and in particular total subsurface storage, water table depth, and groundwater recharge, during the summer drought of 2022. To evaluate the forecasting skill, the 50-member ensemble seasonal forecasts are compared with a reference time series simulated by forcing ParFlow/CLM by the first 24h of each daily HRES deterministic forecast from ECMWF, which has been validated against observations in a previous study.

Finally, we provide some examples on how these seasonal forecasts can be synthesized to assess the risk of water resources depletion due to atmospheric drought conditions, thus providing useful information for society, and, in particular, the agricultural, forestry, and water management sectors.