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Overcoming single model bias through GRACE and multi model data reveals Iran water storage depletion drivers

Yuan, Xilong, Wang, Fengwei, Zhou, Yunqi, and Zhou, Shijian, 2026. Overcoming single model bias through GRACE and multi model data reveals Iran water storage depletion drivers. Scientific Reports, 16(1):22206, doi:10.1038/s41598-026-51961-6.

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@ARTICLE{2026NatSR..1622206Y,
       author = {{Yuan}, Xilong and {Wang}, Fengwei and {Zhou}, Yunqi and {Zhou}, Shijian},
        title = "{Overcoming single model bias through GRACE and multi model data reveals Iran water storage depletion drivers}",
      journal = {Scientific Reports},
     keywords = {GRACE, Hydrological models, TWSA, Least-squares method, Linear trend, Earth Sciences, Physical Geography and Environmental Geoscience, Engineering, Environmental Engineering, Environmental Sciences, Environmental Science and Management},
         year = 2026,
        month = may,
       volume = {16},
       number = {1},
          eid = {22206},
        pages = {22206},
     abstract = "{Rapid changes in terrestrial water storage (TWS) pose serious threats to
        water security in arid and semi-arid regions such as Iran.
        However, the inherent uncertainties of individual hydrological
        models hinder robust assessments of the respective impacts of
        natural variability and anthropogenic influence on water storage
        dynamics in these areas. To address this issue, our study
        integrates GRACE/GRACE-FO satellite gravity data, five
        mainstream hydrological models (GLDAS-Noah, GLDAS-VIC, GLDAS-
        CLSM, ERA5, and WGHM), and GPM global precipitation data. Four
        observational datasets related to precipitation, runoff, and
        evapotranspiration were derived, and 64 different hydrological
        model combinations were constructed. These combinations were
        comprehensively evaluated against Mascon products as a
        benchmark. Ultimately, the model combination with the best
        fitting performance was selected for spatial and temporal
        variation analysis and attribution analysis. The findings reveal
        that: (1) The model combination constructed using ERA5-derived
        evapotranspiration and runoff data, combined with precipitation
        data from VIC/CLSM, exhibits the highest consistency with Mascon
        data. (2) In densely populated northern and southwestern
        regions, the natural water flux shows significant upward trends.
        Nevertheless, TWSA declines there because anthropogenic
        extraction (captured in the net residual) outweighs the natural
        increase, causing groundwater discharge to surface systems and
        amplifying evapotranspiration and runoff losses. (3) In sparsely
        populated arid central regions, TWSA remains relatively stable,
        with an average annual natural water anomaly change rate of
        approximately + 0.01 cm/yr, primarily due to the offsetting
        effects of precipitation and evapotranspiration. This study
        systematically evaluates the applicability of a multi-model
        approach in arid regions. The integrated hydrological modeling
        framework developed herein provides a methodology for selecting
        model configurations and quantifying associated uncertainties in
        water storage assessment, thereby offering a scientific basis
        for sustainable water resource management in arid environments.}",
          doi = {10.1038/s41598-026-51961-6},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026NatSR..1622206Y},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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