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@ARTICLE{2026RemS...18.3013W,
       author = {{Wang}, Xingying and {Liu}, Shengjie and {Hu}, Litang and {Sun}, Jianchong and {Zhang}, Junchao and {Zhu}, Zhenyuan},
        title = "{Groundwater Storage Dynamics and Attribution in the Wei River Basin Based on Dynamic Downscaling}",
      journal = {Remote Sensing},
     keywords = {Wei River Basin, GRACE, dynamic downscaling, groundwater storage changes, contribution of human activities, soil erosion correction},
         year = 2026,
        month = sep,
       volume = {18},
       number = {17},
          eid = {3013},
        pages = {3013},
     abstract = "{What are the main findings? In this study, a dynamically downscaling
        groundwater storage model, specifically corrected for soil
        erosion mass loss, was developed and revealed a west-to-east
        decreasing gradient in groundwater storage across the Wei River
        Basin. Human activities are the primary driver of regional
        groundwater dynamics, contributing over 80\% to storage changes
        in most years, far exceeding natural climate factors like
        precipitation and evapotranspiration. In this study, a
        dynamically downscaling groundwater storage model, specifically
        corrected for soil erosion mass loss, was developed and revealed
        a west-to-east decreasing gradient in groundwater storage across
        the Wei River Basin. Human activities are the primary driver of
        regional groundwater dynamics, contributing over 80\% to storage
        changes in most years, far exceeding natural climate factors
        like precipitation and evapotranspiration. What are the
        implications of the main findings? Integrating soil erosion
        corrections into GRACE data processing provides a critical
        methodological reference for accurately isolating groundwater
        signals in loess plateaus or other severe erosion-prone basins
        globally. The dominance of human-induced depletion and
        significant seasonal volatility in the mid-lower reaches
        urgently require policymakers to prioritize strict anthropogenic
        extraction controls over relying on natural recharge.
        Integrating soil erosion corrections into GRACE data processing
        provides a critical methodological reference for accurately
        isolating groundwater signals in loess plateaus or other severe
        erosion-prone basins globally. The dominance of human-induced
        depletion and significant seasonal volatility in the mid-lower
        reaches urgently require policymakers to prioritize strict
        anthropogenic extraction controls over relying on natural
        recharge. Intensive groundwater exploitation in the Wei River
        Basin (WRB) has caused severe depletion. While Gravity Recovery
        and Climate Experiment (GRACE) satellites monitor these changes,
        their coarse resolution fails to account for soil erosion-
        induced mass loss on the Loess Plateau limit basin-scale
        accuracy. To address this, we developed the groundwater storage
        model to dynamically downscale GRACE data to the resolution of
        0.05{\textdegree} grid. This physically based model integrates
        Darcy's law, water-balance principles, and an innovative
        correction for soil erosion mass migration. Validated against
        well data with maximum correlative coefficient of 0.73, the
        model reveals a severe groundwater decline of 55.89 {\texttimes}
        {}10$^{8}$ m$^{3}$/year from 2003 to 2023. The high-resolution
        results successfully capture localized over-extraction hotspots
        in the Guanzhong Plain, showing a west-to-east decreasing
        gradient in groundwater storage along the Wei River channel.
        Furthermore, quantitative analysis indicates that human
        activities, including primarily agricultural and urban
        extraction, are the overwhelming drivers, accounting for over
        80\% of storage depletion. This framework provides a robust
        methodological reference for isolating groundwater signals in
        erosion-prone regions and supports refined water management in
        semi-arid basins.}",
          doi = {10.3390/rs18173013},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026RemS...18.3013W},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}