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@COMMENT This file was prepared using the NASA Astrophysics Data System (ADS)
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@ARTICLE{2026NatSR..16.4307A,
       author = {{Abbaszadeh}, Majid and {van Dam}, Tonie},
        title = "{GNSS evaluation of GRACE-assimilated water storage models over 89 river basins worldwide}",
      journal = {Scientific Reports},
     keywords = {Hydrological loading, GNSS, GRACE, Data assimilation, Engineering, Geomatic Engineering, Earth Sciences, Physical Geography and Environmental Geoscience},
         year = 2026,
        month = jan,
       volume = {16},
       number = {1},
          eid = {4307},
        pages = {4307},
     abstract = "{The gravity recovery and climate experiment (GRACE) and GRACE follow-on
        (GFO) gravity observations have significantly improved our
        understanding of the terrestrial water cycle. However, GRACE-
        assimilated (GA) hydrological models still differ significantly.
        This paper uses global navigation satellite system (GNSS) data
        to assess two global GA datasets: Global land water storage
        release 2 (GLWS2.0) and catchment land surface model GRACE data
        assimilation (CLSM-DA). From 2004 to 2019, the mean annual
        amplitude of equivalent water thickness (EWT) of these datasets
        differs by more than 25 mm over 40\% of the modeled land area,
        and the timing of peak water storage diverges by as much as
        30-days across 50\% of their domain. We compare the modeled
        hydrological loading vertical displacement predicted from these
        models with GNSS uplift data to compare and contrast the model
        quality. Using river basin boundary information from 89 rivers,
        we cluster 9,163 global GNSS stations, each with at least three
        years of daily data. Results show that CLSM-DA generally agrees
        better with GNSS data across more river basins. Its 100─300 mm
        larger annual water variation accounts for better agreement in
        Africa, Southeast Asia, and parts of South America. In regions
        like the Western United States and Eastern Europe, where both
        models estimate similar annual amplitudes, CLSM-DA's 30─60 day
        phase delay improves alignment with GNSS. This evaluation also
        reveals key limitations in both models, especially during
        extreme hydrological events such as droughts, and highlights the
        value of geodetic observations in advancing GA hydrological
        modeling.}",
          doi = {10.1038/s41598-025-31887-1},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026NatSR..16.4307A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}