The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low‐flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM‐simulated groundwater correlates strongly with 12‐month precipitation anomalies in low‐latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.

Although the use of the Gravity Recovery and Climate Experiment (GRACE) satellites to monitor groundwater storage changes has become commonplace, our evaluation suggests that careful processing of the GRACE data is necessary to extract a representative signal especially in regions with significant surface water storage (i.e., lakes/reservoirs). In our study, we use cautiously processed data sets, including GRACE, lake altimetry, and model soil moisture, to reduce scaling factor bias and compare GRACE‐derived groundwater storage changes to in situ groundwater observations over parts of East Africa. Over the period 2007–2010, a strong correlation between in situ groundwater storage changes and GRACE groundwater estimates (Spearman's ρ = 0.6) is found. Piecewise trend analyses for the GRACE groundwater estimates reveal significant negative storage changes that are attributed to groundwater use and climate variability. Further analysis comparing groundwater and satellite precipitation data sets permits identification of regional groundwater characterization. For example, our results identify potentially permeable and/or shallow groundwater systems underlying Tanzania and deep and/or less permeable groundwater systems underlying the Upper Nile basin. Regional groundwater behaviors in the semiarid regions of Northern Kenya are attributed to hydraulic connections to recharge zones outside the subbasin boundary. Our results prove the utility of applying GRACE in monitoring groundwater resources in hydrologically complex regions that are undersampled and where policies limit data accessibility.

The world's largest aquifers are a fundamental source of freshwater used for agricultural irrigation and to meet human water needs. Therefore, their stored volume of groundwater is linked with water security, which becomes more relevant during periods of drought. This work focuses on understanding large‐scale groundwater changes, where we introduce an approach to evaluate groundwater sustainability at a global scale. We employ a groundwater drought index to assess performance metrics (reliability, resilience, vulnerability, and a combined sustainability index) for the largest and most productive global aquifers. Spatiotemporal changes in total water storage are derived from remote sensing observations of gravity anomalies, from which the groundwater drought index is inferred. The results reveal a complex relationship between the indicators, while considering monthly variability in groundwater storage. Combining the drought and sustainability indexes, as presented in this work, constitutes a measure for quantifying groundwater sustainability. This framework integrates changes in groundwater resources due to human influences and climate changes, thus opening a path to assess progress toward sustainable use and water security.

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