| 24 Jun 2026
High-resolution global groundwater storage anomalies: A 1 km downscaled dataset
Abstract. The global depletion of groundwater poses a significant challenge to water security. However, the coarse spatial resolution of GRACE satellite observations obscures fine-scale hydrological dynamics and limits the separation of localized anthropogenic extraction signals from large-scale climatic forcing. To address this limitation, we present a high-resolution (1 km), continuous monthly dataset of global groundwater storage anomalies (GWSA) covering the period from 2002 to 2020. The dataset is generated using a production framework that integrates Singular Spectrum Analysis (SSA) for temporal gap filling and an aquifer-stratified machine learning approach driven by 19 high-resolution hydroclimatic and geophysical predictors. To ensure robustness and spatial consistency, multiple predictive approaches were evaluated as part of a quality control procedure, and the most stable model was selected for final production based on multi-scale validation. Cross-scale evaluation shows that the downscaled dataset preserves the large-scale spatial patterns of the original GRACE observations with high agreement (R2 = 0.972, RMSE = 2.10 cm). Independent validation using 1,518 in situ monitoring wells, combined with a geographically stratified specific yield matrix for dimensional conversion, further demonstrates the ability of the dataset to capture long-term groundwater variability across diverse hydrogeological conditions (R2 = 0.44, p < 0.01). The resulting 1 km dataset provides enhanced spatial detail and enables the identification of sharp nonlinear boundaries associated with intensive human pumping, as well as spatial polarization patterns in groundwater storage changes. This dataset offers a reliable, observation-constrained resource for water resource assessment, hydrological modeling, and studies of coupled climate and human influences on groundwater systems.
The authors pursue the ambitious objective of developing a global, high-resolution GWSA dataset at a spatial resolution of 1 km. Although the resulting data set could provide a useful resource for groundwater research, the manuscript does not adequately demonstrate its reliability. My major comments are as follows.
(1) As shown in Table 1, TWSA data extend through the end of 2025, whereas the other input data sets end in 2020. This five-year temporal mismatch requires justification. Why was the GWSA data set not updated through 2025? Other satellite-based products that are regularly updated and currently available should be considered to extend the temporal coverage of the input data.
(2) The validation is insufficient to establish the reliability of the proposed data set. First, the estimated GWSA should be evaluated against available groundwater-level observations from monitoring wells. Second, the authors should select representative groundwater basins and compare their GWSA estimates with those reported in previous regional studies, with particular attention to differences in temporal variability, magnitude, and long-term trends. Third, comparisons with simulations from existing continental- or global-scale land surface and groundwater models would provide an additional independent assessment. Validation should not be limited to correlation analysis against an existing GWSA product. For comparisons with monitoring-well observations, the authors should also present and interpret time-series plots to determine whether the estimated GWSA captures observed seasonal fluctuations, interannual variability, and long-term trends.
(3) Products derived from different data sources should be systematically compared and cross-validated. The manuscript should quantify the consistency and discrepancies among these products and discuss how differences in data sources propagate into the final GWSA estimates.
(4) As shown in Table 2, assigning a uniform specific yield value to each of the seven regions may not adequately represent the spatial heterogeneity of aquifer properties. Because GWSA estimates derived from groundwater-level observations are sensitive to Sy, the authors should evaluate the sensitivity of their results to the selected Sy values and discuss the uncertainty introduced by this regional parameterization.
(5) The manuscript should provide a more detailed description of how temporal data gaps in the GRACE and GRACE-FO records were handled. The authors should specify the gap-filling method, its underlying assumptions, and the uncertainty it introduces into the reconstructed GWSA time series.
(6) Each abbreviation should be defined only at its first occurrence and used consistently thereafter. Repeatedly spelling out a term after its abbreviation has already been defined is unnecessary.