Publications related to the GRACE Missions (no abstracts)

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A simplified drought indicator based on high-resolution GRACE terrestrial water storage anomalies

Kalu, Ikechukwu, Ndehedehe, Christopher E., Ferreira, Vagner G., Janardhanan, Sreekanth, Currell, Matthew, Adeyeri, Oluwafemi E., Okwuashi, Onuwa, and Kennard, Mark J., 2025. A simplified drought indicator based on high-resolution GRACE terrestrial water storage anomalies. Journal of Hydrology, 662:134035, doi:10.1016/j.jhydrol.2025.134035.

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@ARTICLE{2025JHyd..66234035K,
       author = {{Kalu}, Ikechukwu and {Ndehedehe}, Christopher E. and {Ferreira}, Vagner G. and {Janardhanan}, Sreekanth and {Currell}, Matthew and {Adeyeri}, Oluwafemi E. and {Okwuashi}, Onuwa and {Kennard}, Mark J.},
        title = "{A simplified drought indicator based on high-resolution GRACE terrestrial water storage anomalies}",
      journal = {Journal of Hydrology},
         year = 2025,
        month = dec,
       volume = {662},
          eid = {134035},
        pages = {134035},
     abstract = "{Hydrological drought indices based on meteorological data do not fully
        reflect impacts on hydrological systems, and the coarse spatial
        resolution of GRACE data limits its usefulness for local-scale
        drought assessment. To address this, we developed fine-scale
        drought indices based on Gravity Recovery and Climate Experiment
        (GRACE)-derived terrestrial water storage anomalies (TWSA) using
        a statistical downscaling approach. This was achieved by
        employing a Random Forest machine learning algorithm to
        integrate key water budget terms (i.e., precipitation,
        evapotranspiration, runoff and deep drainage) into the original
        GRACE grids to achieve a drought index at 5 km spatial
        resolution. The resulting downscaled GRACE drought index (dGdi)
        is effective for localized drought predictions, providing a
        comprehensive picture of hydrological and climatic conditions
        over major river basins in Australia. Application of this
        downscaled drought index over the Canning Basin, Western
        Australia, reveals long-term drought evolutions indicating that
        the region is at a risk of a permanent shift in ecosystem
        composition (e.g., dominance of drought-tolerant invasive
        species), land degradation and aquifer depletion. Overall, we
        found that global climate indices have weak influences on
        Australia's drought progression. The Back Propagation Neural
        Network confirmed these indices contribute to drought occurrence
        in the Canning (r = 0.37) and Central Eromanga (r = 0.36)
        Basins. The dGdi developed in this study supports local-scale
        drought assessment by capturing changes in key biophysical
        indicators and effectively highlighting intensifying drought
        patterns. Given its reliance on widely available water budget
        variables and its adaptability to diverse hydrological settings,
        the dGdi can be extended to other regions beyond Australia for
        enhanced drought monitoring and water resource management.}",
          doi = {10.1016/j.jhydrol.2025.134035},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2025JHyd..66234035K},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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