Quantifying groundwater drought hazards with the groundwater level deficit anomaly index (GLDAI)

Abstract Droughts diminish groundwater availability by reducing recharge and intensifying abstraction, yet most drought indices emphasize anomalies without quantifying the underlying deficit in groundwater storage. Drawing on 25 years of drought research, this study introduces the groundwater level deficit anomaly index (GLDAI), a metric that jointly represents groundwater anomalies and their associated deficits to better characterize drought severity. GLDAI captures dynamic groundwater responses by translating deviations from observed levels into meaningful deficit estimates, thereby offering a clearer depiction of hydrological stress than anomaly only indicators. Using monthly groundwater level records from 1,847 monitoring wells across Germany, GLDAI successfully identifies major groundwater droughts (1992, 2003, 2018–2020, 2021) while reducing severity estimates by 22.75% relative to anomaly based indices. Unlike the standardized groundwater level index (SGLI), which relies solely on long-term statistical deviations, GLDAI incorporates both groundwater demand and deficit magnitude. This distinction is critical in regions with shallow aquifers or high natural variability, where anomaly based indices may overestimate drought conditions by classifying statistically low, but hydrologically sufficient, levels as severe drought. A comparative assessment shows that from 1992 to 2021, the proportion of months classified as drought decreased by 4.4% when using GLDAI (SGLI: 19.7%; GLDAI: 15.3%). These findings demonstrate that GLDAI reduces overestimation of drought severity and provides a more realistic representation of groundwater stress. As such, GLDAI offers a robust framework for regional-to-global drought risk assessments and supports more effective groundwater management and mitigation planning.