A WSDI framework describing GRACE terrestrial water storage deficit for monitoring and tracking the drought process and spatial pattern in the Loess Plateau, China

• A multi-component WSDIs framework is proposed to quantify the spatiotemporal evolution of drought based on GRACE data. • WSDI-TWSA exhibits the highest synchronicity with scPDSI, effectively capturing complex drought dynamics in the Weihe River Basin. • Cascade propagation chain of Meteorological→Agricultural→ Hydrological→Groundwater drought is clearly delineated. • Groundwater storage shows a significant response lag and a “decoupling” trend from meteorological drivers due to human activities. • WSDI component indices identify potential groundwater risks, providing a more comprehensive perspective for regional drought management. Drought is a complex phenomenon characterized by the spatiotemporal propagation of water deficits. Conventional surface-based drought indices often fail to fully capture the intricate feedback mechanisms within terrestrial water storage components. This study develops a multidimensional standardized Water Storage Deficit Index framework (WSDIs, including WSDI-TWSA, WSDI-GWSA, WSDI-SMSA, WSDI-CWSA, and WSDI-SWEA) based on GRACE satellite data, using the Wei River Basin on the Chinese Loess Plateau as a representative study area. The synchronicity between WSDIs and the traditional surface drought index (e.g., scPDSI, SPEI, SRI) is investigated to track the evolutionary trajectories of major historical drought events. The results indicate that (1) the WSDI comprehensive index WSDI-TWSA exhibits the highest gray relational grade with scPDSI, demonstrating its superiority in characterizing integrated drought conditions; (2) the WSDI component indexes effectively reveal the cascade propagation from meteorological → agricultural → surface hydrological → groundwater drought; and (3) a significant lag and “decoupling” phenomenon between GWSA and meteorological drivers are identified, exacerbated by anthropogenic interventions (e.g., irrigation). The WSDIs framework provides a robust tool for capturing the spatiotemporal patterns and internal mechanisms of drought, offering critical data support for risk mitigation and water resource allocation in water-scarce regions.