Comprehensive Use of GNSS Vertical Deformation and GRACE/GFO Data to Invert the Joint Drought Index of Three Central China Provinces

Terrestrial water storage (TWS) is a key parameter for understanding regional water cycles and climate change. To address the low spatial resolution and temporal gaps of Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On) data, as well as the uneven spatial distribution of Global Navigation Satellite System (GNSS) stations, this study integrates GNSS vertical deformation with GRACE/GFO Mascon data to jointly invert and conduct an in-depth analysis of TWS changes and hydrological drought characteristics in three central Chinese provinces (Hubei, Hunan, and Jiangxi) from January 2011 to June 2023. For missing parts of GRACE and GNSS data, different methods were effectively employed to fill the gaps. The optimal weighting factors were then determined using the Akaike Bayesian Information Criterion (ABIC), leading to the inversion of TWS variations. Combined with hydrometeorological data (precipitation, evapotranspiration, and runoff), drought monitoring was further conducted. The results indicate that joint inversion effectively integrates the high-frequency spatial signals of GNSS with the large-scale smoothing features of GRACE. The spatial distribution of the annual TWS amplitude obtained from different methods (GRACE, GNSS-Green, GNSS-Slepian, and Joint) showed high consistency, generally exhibiting a pattern of lower values in the northwest and higher values in the southeast. Using the TWS derived from joint inversion, a drought index (Joint-DSI) was constructed, successfully identifying and tracking seven major drought events in the study area. Among these, the drought from April 2017 to November 2018 lasted the longest (20 months), while the event from August 2022 to June 2023 was the most severe, with a peak deficit of 142.303 km³. This study demonstrates that the joint inversion method can effectively overcome the spatiotemporal limitations of single observation techniques, providing a high-precision, high-resolution, and reliable geodetic approach for regional water resource management and extreme drought monitoring.