@COMMENT This file was generated by bib2html_grace.pl <https://sourceforge.net/projects/bib2html/> version 0.94
@COMMENT written by Patrick Riley <https://sourceforge.net/users/patstg/>
@COMMENT This file was prepared using the NASA Astrophysics Data System (ADS)
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@ARTICLE{2026JHyd..67936335F,
       author = {{Feng}, Bo and {Xu}, Yan and {Jiang}, Nan and {Guo}, Biaobiao and {Yin}, Peng and {Guo}, Ao and {Xu}, Tianhe and {Schuh}, Harald},
        title = "{Reconstructing terrestrial water storage and quantifying drought evolution in Australia using LSTM networks}",
      journal = {Journal of Hydrology},
     keywords = {GNSS, GRACE, Terrestrial water storage, LSTM, Drought monitoring},
         year = 2026,
        month = oct,
       volume = {679},
          eid = {136335},
        pages = {136335},
     abstract = "{High-precision monitoring of Terrestrial Water Storage (TWS) is critical
        amid climate-driven increases in drought severity. To overcome
        the inherent limitations of the Gravity Recovery and Climate
        Experiment (GRACE)---coarse spatial resolution and data gaps and
        the Global Navigation Satellite System (GNSS)---uneven station
        distribution and high-frequency noise, we introduce a Long
        Short-Term Memory (LSTM) framework. This framework reconstructs
        high-quality TWS across Australia by integrating Equivalent
        Water Height (EWH) time series, meteorological data, and
        temporal markers to effectively capture GNSS-GRACE
        discrepancies. Joint inversion results demonstrate substantial
        spatiotemporal consistency with Global Land Data Assimilation
        System (GLDAS), GRACE, and precipitation records. Notably, the
        LSTM-enhanced EWH significantly improves agreement with
        benchmarks: the correlation with GRACE reached 0.854 in the
        Northern Territory and surged from 0.290 to 0.656 in station-
        sparse Western Australia. Crucially, the model successfully
        bridges the GRACE mission gap, ensuring TWS continuity.
        Furthermore, the quantification of drought evolution (2011--
        2023) using a derived Drought Severity Index (LSTM-DSI) and
        NscPDSI revealed a correlation of 0.663, demonstrating robust
        consistency in capturing extreme hydrological signals. By
        integrating the temporal resolution of GNSS with the physical
        stability of GRACE, this multi-source fusion approach provides a
        robust foundation for investigating hydroclimatic interactions
        in Australia.}",
          doi = {10.1016/j.jhydrol.2026.136335},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026JHyd..67936335F},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}