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Towards global groundwater recharge estimation from GRACE–constrained GLDAS–CLSM data

Ferreira, Vagner and Ndehedehe, Christopher, 2026. Towards global groundwater recharge estimation from GRACE–constrained GLDAS–CLSM data. Hydrogeology Journal, .

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BibTeX

@ARTICLE{2026HydJ..tmp..207F,
       author = {{Ferreira}, Vagner and {Ndehedehe}, Christopher},
        title = "{Towards global groundwater recharge estimation from GRACE-constrained GLDAS-CLSM data}",
      journal = {Hydrogeology Journal},
     keywords = {Groundwater recharge, GLDAS, GRACE, Groundwater statistics, Groundwater storage fluctuation, Remote and satellite sensing},
         year = 2026,
        month = sep,
     abstract = "{Accurate estimation of groundwater recharge at regional to global scales
        is e{\ss}ential for sustainable water resource management, yet
        current methods lack consistency. This study introduces the
        groundwater storage fluctuation (GSF) method to derive gro{\ss}
        recharge, total discharge (including both natural and human-
        related outflows that cannot be distinguished without additional
        data), and net recharge from GRACE-constrained GLDAS-2.2 CLSM
        groundwater storage (GWS) anomalies. Based on monthly GWS
        fluxes, the GSF method requires no seasonal templates or
        specific recharge-event identification. Global mean annual
        recharge for 2004-2024 is estimated at 16,081.5 km$^{3}$/year,
        consistent with existing global hydrological models and multi-
        study averages (14,806 {\ensuremath{\pm}} 1,721 km$^{3}$/year).
        Recharge ranges from <100 mm/year in arid zones to >300 mm/year
        in humid tropical areas, with a non-significant global trend of
        0.34 mm/year. Arid basins show the highest interannual
        variability, with coefficients of variation of 48\% for the
        Murray-Darling Basin (Australia), 40\% for S{\~a}o Francisco
        (Brazil), and 36\% for Colorado (USA). Validation against an
        Australian chloride ma{\ss} balance (CMB) dataset shows strong
        spatial agreement ({\ensuremath{\rho}} = 0.82). In the Murray-
        Darling Basin, CMB validation confirms this performance
        ({\ensuremath{\rho}} = 0.83 and a standard deviation, STD, of
        32.1 mm/year). The underlying GWS, validated against 259
        boreholes in the basin, correlates at 0.47 with an STD of 33.9
        mm, within the bootstrap uncertainty limit of 38.2 mm. Results
        should be interpreted at GRACE's effective resolution
        ({\ensuremath{\sim}}300 km), and grid-cell estimates in data-
        sparse or low signal-to-noise ratio areas should be used with
        caution.}",
          doi = {10.1007/s10040-026-03169-1},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026HydJ..tmp..207F},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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