An ensemble groundwater prediction (EGP) system to forecast groundwater levels in alluvial aquifers in Switzerland

Abstract. Groundwater is a key source of freshwater for drinking water supply and agricultural irrigation on a global scale. Groundwater in Switzerland (and beyond) is traditionally regarded as a reliable source of freshwater. Recent extreme drought events (i.e., in 2018, 2020, and 2022) have shown, however, that groundwater does respond to these events and can cause problems in water supply and groundwater availability. With hydrological extremes becoming more frequent, there is a growing need for early warning systems and improved forecasting. This study develops and tests a scalable ensemble groundwater prediction (EGP) system with a 32-day lead time. The system combines extended-range precipitation and temperature forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) with the lumped-parameter groundwater model Pastas. Forecasts were evaluated at six monitoring wells across Switzerland, representing diverse hydrogeological settings, and compared against naive persistence and climatology benchmarks. Results indicate that the EGP system produces skillful forecasts up to one month ahead, with Spearman correlations exceeding 0.77 for most wells. However, the required model–data complexity varies: in long-memory aquifers, forecasts driven by recent meteorology and climatology are sufficient, while in short-memory systems, meteorological forecast data adds clear value. Forecast skill in mountainous regions (e.g., Davos) remains limited due to difficulties in predicting local meteorology. These findings highlight both the potential and the limitations of short-term groundwater forecasting. Future work should explore larger lead times, particularly in slow-responding aquifers, and investigate methods to improve forecasts in alpine environments.