Publications related to the GRACE Missions (no abstracts)

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Unravelling soil moisture uncertainties in GRACE groundwater modelling

Kalu, Ikechukwu, Ndehedehe, Christopher E., Ferreira, Vagner G., Janardhanan, Sreekanth, and Kennard, Mark J., 2025. Unravelling soil moisture uncertainties in GRACE groundwater modelling. Journal of Hydrology, 650:132489, doi:10.1016/j.jhydrol.2024.132489.

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@ARTICLE{2025JHyd..65032489K,
       author = {{Kalu}, Ikechukwu and {Ndehedehe}, Christopher E. and {Ferreira}, Vagner G. and {Janardhanan}, Sreekanth and {Kennard}, Mark J.},
        title = "{Unravelling soil moisture uncertainties in GRACE groundwater modelling}",
      journal = {Journal of Hydrology},
     keywords = {GRACE, Gravity Recovery and Climate Experiment, MDB, Murray Darling Basin, {\ensuremath{\Delta}}TWS, Changes in Terrestrial Water Storage, GLDAS, Global Land Data Assimilation System, CMIP5, Coupled Model Intercomparison Project Phase 5, ESM, Earth System Model, CESM, Community Earth System Models, SMOS, Soil Moisture and Ocean Salinity, LSM, Land Surface Models, CSR, Centre for Space Research, JPL, Jet Propulsion Lab, GFZ, Geo Forschungs Zentrum, CLSM, Catchment Land Surface Model, VIC, Variable Infiltration Capacity, AWO, Australian Water Outlook, AWRAL, Australian Water Resource Assessment Landscape model, ASRIS, Australian Soil Resources Information System, WGHM, WaterGAP Global Hydrological Model, WMIP, Water Monitoring Information Portal, GLWD, Global lakes and Wetland Database, GRanD, Global Reservoir and Dam, SW, Surface Water, GWL, Groundwater Level, SWL, Standing Water Level, BOM, Bureau of Meteorology, Soil moisture, GRACE, Groundwater, Murray Darling Basin, SVM},
         year = 2025,
        month = apr,
       volume = {650},
          eid = {132489},
        pages = {132489},
     abstract = "{Soil moisture data is essential for estimating groundwater storage
        anomalies (GWSA) from the Gravity Recovery and Climate
        Experiment (GRACE) data, but the general lack of direct in-situ
        root-zone soil moisture observations has typically resulted in a
        reliance on modelled soil moisture estimates instead. These
        model-simulated soil moisture profiles {\textendash} upper (0 to
        10 cm), lower (10 to 100 cm), and deep layers (100 to 200 cm),
        are characterized by large uncertainties due to the
        simplification and parameterization of soil moisture processes
        in hydrological models. It is thus crucial to account for these
        uncertainties and understand how they affect the estimation of
        groundwater storage changes based on GRACE data. In this study,
        we evaluated the contributions and impacts of different soil
        moisture profiles on GRACE-derived groundwater storage (between
        2002 and 2016) modelling uncertainties over the Murray Darling
        Basin (MDB) using statistical and machine learning regression.
        We observed that the lower layer exhibited the strongest
        correlation with base GWSA, particularly during 2006 to 2009 (r
        = 0.99, RMSE = 7.50 mm). Bootstrap analysis indicated that the
        lower layer consistently had the largest absolute coefficient
        weights, signifying its predominant influence on GWSA
        predictions. The deep layer contributed the least during 2010 to
        2013, while the upper layer was highly dynamic and introduced a
        26.8 \% more uncertainty rating when compared to the lower
        layer. Regression analysis showed the lower layer maintained the
        smallest confidence interval widths, confirming its reliability.
        The Monte Carlo resampling corroborated these findings, with the
        lower layer maintaining the most consistent relationship with
        base GWSA across all periods. The lower layer's steadier state
        and lower susceptibility to surface disturbances provided more
        accurate predictions than other layers. This study advances the
        modelling of groundwater storage from space by improving our
        understanding of the uncertainties introduced by the different
        soil moisture layers. It will be helpful for better and accurate
        freshwater reporting and management.}",
          doi = {10.1016/j.jhydrol.2024.132489},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..65032489K},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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