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@ARTICLE{2026RemS...18.2633W,
       author = {{Wang}, Yinan and {Xu}, Guangyu and {Zhang}, Tengxu and {Wang}, Leyang},
        title = "{Comprehensive Use of GNSS Vertical Deformation and GRACE/GFO Data to Invert the Joint Drought Index of Three Central China Provinces}",
      journal = {Remote Sensing},
     keywords = {GNSS vertical displacement, terrestrial water storage, GRACE, joint inversion, hydrological drought},
         year = 2026,
        month = aug,
       volume = {18},
       number = {15},
          eid = {2633},
        pages = {2633},
     abstract = "{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 km$^{3}$. 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.}",
          doi = {10.3390/rs18152633},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026RemS...18.2633W},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}