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Temporal and spatial variability of groundwater storage derived from downscaled GRACE data in the transboundary Bug River Basin (Poland–Ukraine–Belarus border region)

Solovey, Tatiana, Śliwińska–Bronowicz, Justyna, Janica, Rafał, Stradczuk, Anna, and Brzezińska, Agnieszka, 2025. Temporal and spatial variability of groundwater storage derived from downscaled GRACE data in the transboundary Bug River Basin (Poland–Ukraine–Belarus border region). Science of the Total Environment, 1009:181023, doi:10.1016/j.scitotenv.2025.181023.

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@ARTICLE{2025ScTEn100981023S,
       author = {{Solovey}, Tatiana and {{\'S}liwi{\'n}ska-Bronowicz}, Justyna and {Janica}, Rafa{\l} and {Stradczuk}, Anna and {Brzezi{\'n}ska}, Agnieszka},
        title = "{Temporal and spatial variability of groundwater storage derived from downscaled GRACE data in the transboundary Bug River Basin (Poland-Ukraine-Belarus border region)}",
      journal = {Science of the Total Environment},
     keywords = {Groundwater storage, Terrestrial water storage, GRACE, GRACE-FO, Downscaling, Random forest, Poland─Ukraine─Belarus borderland},
         year = 2025,
        month = dec,
       volume = {1009},
          eid = {181023},
        pages = {181023},
     abstract = "{This study presents an enhanced approach for estimating groundwater
        storage (GWS) dynamics using downscaled Gravity Recovery and
        Climate Experiment (GRACE) data combined with Global Land Data
        Assimilation System (GLDAS) outputs in the transboundary Bug
        River Basin. We applied three innovations to improve satellite-
        based GWS estimation. First, we applied the random forest (RF)
        algorithm to downscale GRACE terrestrial water storage (TWS)
        data to 0.1{\textdegree} {\texttimes} 0.1{\textdegree}
        resolution, using precipitation, evapotranspiration, runoff, and
        soil moisture as predictors. Second, we introduced a novel
        cumulative component to the GLDAS-based TWS change indicator,
        representing vadose-zone water equivalent, which depends on
        groundwater level (GWL) depth. This adaptation accounted for
        hydrodynamic conditions by extending the accumulation period
        with increasing GWL depth, effectively reducing phase shifts and
        temporal delays relative to the in-situ GWS observations common
        in prior studies. Third, satellite-based GWS estimates were
        calibrated using in-situ groundwater measurements combined with
        RF and kriging. The proposed approach significantly improved
        consistency between satellite-derived and in-situ GWS
        (correlation coefficients between 0.66 and 0.95), enhancing the
        reliability of groundwater monitoring. The GWS seasonal
        variability and amplitude were found to strongly depend on
        vadose zone properties and GWL depth. Despite an overall decline
        in total TWS, GWS in the Bug River Basin remained stable,
        reflecting system resilience to climatic fluctuations. Our
        methodology enhances groundwater monitoring and forecasting in
        transboundary catchments and enables the development of
        continuous changes in GWS in time and space, which is
        particularly important for regions with a sparse network of in-
        situ observations.}",
          doi = {10.1016/j.scitotenv.2025.181023},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025ScTEn100981023S},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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