Publications related to the GRACE Missions (no abstracts)

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Reducing dependence on GRACE mascon datasets: bayesian–TCH fusion for robust groundwater storage anomaly diagnoses in the U‑shaped meander region of the Yellow River basin

Yang, Zhirui, Huang, Guohe, Li, Yongping, Zhou, Ya, Wang, Feng, Zhou, Xiong, Wei, Yiting, and Ren, Xinyue, 2026. Reducing dependence on GRACE mascon datasets: bayesian–TCH fusion for robust groundwater storage anomaly diagnoses in the U‑shaped meander region of the Yellow River basin. Journal of Hydrology, 677:135853, doi:10.1016/j.jhydrol.2026.135853.

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@ARTICLE{2026JHyd..67735853Y,
       author = {{Yang}, Zhirui and {Huang}, Guohe and {Li}, Yongping and {Zhou}, Ya and {Wang}, Feng and {Zhou}, Xiong and {Wei}, Yiting and {Ren}, Xinyue},
        title = "{Reducing dependence on GRACE mascon datasets: bayesian-TCH fusion for robust groundwater storage anomaly diagnoses in the U‑shaped meander region of the Yellow River basin}",
      journal = {Journal of Hydrology},
     keywords = {Bayesian three‑cornered hat (Bayesian‑TCH), Groundwater storage anomalies (GWSA), U‑shaped meander region, Yellow river basin, GRACE mascon solutions, Climate variability},
         year = 2026,
        month = sep,
       volume = {677},
          eid = {135853},
        pages = {135853},
     abstract = "{Groundwater storage changes in regions with scarce observations are
        increasingly being inferred from satellite gravimetry, but
        different institutional datasets can lead to inconsistent
        conclusions. Focusing on the U-shaped Meander Region of the
        Yellow River Basin, we examine the dependence of groundwater
        storage trends on the choice of satellite gravimetry datasets
        and implement a Bayesian three-cornered hat fusion strategy to
        obtain more robust groundwater storage anomaly (GWSA) estimates.
        This fusion strategy estimates institution-specific noise levels
        relative to a potential truth and uses them for Bayesian
        weighted fusion of the three GRACE-derived TWSA products. The
        results show that the five GWSA datasets give different
        conclusions about groundwater changes when trends are segmented
        around 2007. The GWSA dataset estimated using the Bayesian-TCH
        framework reduces regional mean uncertainty by about 50--80 \%
        and raises the signal-to-noise ratio above 20 dB. The Bayesian-
        TCH time series shows a near steady declining trend before 2007
        and, afterward, weakened seasonal coherence and a stronger role
        of human activities. This pattern is more consistent with
        independent understanding that the region is shifting from
        mainly climate driven variability to increasing impacts of
        sustained groundwater pumping and coal mining dewatering,
        whereas some GWSA datasets show stable recovery before the
        breakpoint and others still display climate dominated
        variability after the breakpoint.}",
          doi = {10.1016/j.jhydrol.2026.135853},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026JHyd..67735853Y},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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