the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Jan 2026
The Global Gravity-based Groundwater Product (G3P)
Abstract. Groundwater is one of the most important freshwater resources for ecosystems and mankind. Because of its fundamental role in the Earth's water and energy cycles, groundwater has been declared an essential climate variable by GCOS, the Global Climate Observing System. Similar to other subsurface states and fluxes, groundwater is difficult to monitor at the global scale, with sufficient spatial coverage and over climate-relevant time scales. The Global Gravity-based Groundwater Product (G3P) is a global observation-based data set of large-scale groundwater storage variations. G3P capitalizes on the unique capability of GRACE and GRACE-FO satellite gravimetry as the only remote sensing technology to monitor subsurface mass variations. In a mass balance approach, satellite-based, in situ observation-based and model-based water storage variations of snow water equivalent, root-zone soil moisture, glacier mass, and surface water storage are subtracted from GRACE/-FO terrestrial water storage anomalies to result in monthly variations of groundwater storage. For this combination, the individual compartmental storage data are spatially filtered to be consistent with the spatial resolution of terrestrial water storage from satellite gravimetry. The G3P data set presented here covers the period 2002 to 2023 with monthly resolution on a 0.5° global grid and includes propagated uncertainty information. We describe the details of the G3P data processing chain and of each contributing data stream, provide examples of spatial and temporal groundwater storage variations represented by the G3P data set, and present exemplary evaluation results against in situ groundwater observations for three large aquifer systems. G3P is a prototype for an operational global groundwater service, under development as a cross-cutting extension of the existing portfolio of the Copernicus Climate Change Service C3S. The G3P data set is available via GFZ Data Services at https://doi.org/10.5880/G3P.2024.001 (Güntner et al., 2024).
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- RC1: 'Comment on essd-2025-797', Anonymous Referee #1, 05 Mar 2026
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CC1: 'Comment on essd-2025-797', Vadim Yapiyev, 19 Mar 2026
Dear Authors,
We have experience in using your dataset in the North Kazakhstan. (Güntner et al., 2024), on basin level, Yesil River Basin (a tributary of Irtysh (Ertis) river (see Ongdas et al., 2024). We found
In this cold, semi-arid environment, the application of the G3P product showed several unexpected results regarding the relationship between Terrestrial Water Storage Anomalies (TWSA) and Groundwater Storage Anomalies (GWSA):- Contradicting Annual Cycles: There appear to be contradicting annual cycles where the peak in TWSA coincides with the lowest levels in GWSA.
- Delayed Peaks: Unlike surface water components, GWSA does not peak in the spring (despite the dominance of spring snowmelt in the region) but is observed significantly later.
- Cold Season Decline: Observed GWSA decline occurs during the cold season (November–March), which is atypical for regional expectations of winter storage.
How would the authors explain our findings?
References:
Güntner A, Sharifi E, Haas J et al (2024) Global gravity-based ground- water product (G3P). V. 1.12. GFZ Data Serv. https://doi.org/10.5880/g3p.2024.001
Ongdas, N., Yapiyev, V., Stefan, C. et al. Lowland transboundary river in a cold, semi-arid steppe: review of the Yesil River basin. nviron Earth Sci 84, 496 (2025). https://doi.org/10.1007/s12665-025-12500-0
Citation: https://doi.org/10.5194/essd-2025-797-CC1 -
RC2: 'Comment on essd-2025-797', Ehsan Forootan, 25 May 2026
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Dear Authors,
I have read your manuscript with great interest. The study presents a data-driven “residual” approach to estimate groundwater storage, where time-variable terrestrial water storage (TWS) changes derived from GRACE and GRACE-FO are interpreted as the vertically integrated signal of total land water storage. Estimates of other land water components are then obtained from independent satellite observations or models and subtracted from TWS. To enhance consistency among the different datasets, the manuscript introduces spatial filtering techniques.
While the resulting groundwater estimates are potentially valuable, I believe several important technical issues need to be addressed to strengthen the robustness and interpretability of the results. These points likely require additional analysis, validation, and deeper discussion.
1. Filtering strategy
The filtering approach adopted from Sharifi et al. (2025) is not entirely convincing from a physical perspective. Defining an “optimal” filter based on maximizing correlations between individual storage components and TWS lacks a clear physical justification. If the objective is to ensure spectral consistency, a more transparent approach would be to represent the storage components in the spherical harmonic domain and apply filters consistent with GRACE(-FO) processing. This would allow consistency to be enforced directly in the spectral domain rather than through empirical tuning.2. Consistency of storage magnitudes
Even if the filtering approach is accepted, there is no guarantee that independently derived storage components (from models or other satellite products) will match the magnitude of GRACE(-FO) TWS. Such inconsistencies are well documented and can be substantial. They are more appropriately addressed through data assimilation frameworks that explicitly account for uncertainties and model–data discrepancies. I encourage the authors to consider and discuss this aspect, for example as highlighted in Getirana et al. (2025, GRL, Inconsistencies in GRACE‐Based Groundwater Storage Estimation—A Call for a Proper Use of Land Surface Models - Getirana - 2025 - https://doi.org/10.1029/2025GL119197).In addition, several offline data-merging approaches have been proposed in the literature that attempt to address such inconsistencies more systematically. These include ensemble-based approaches, statistical decomposition methods, and Bayesian merging frameworks (e.g., https://doi.org/10.5194/hess-18-2955-2014; doi:10.1016/j.rse.2013.09.025; https://doi.org/10.1016/j.scitotenv.2020.143579). A discussion of how the present method relates to or differs from these established techniques would significantly strengthen the manuscript.
3. Magnitude of groundwater estimates
The magnitude of the derived groundwater storage changes appears questionable, possibly due to over-filtering or the rescaling procedure. For instance, the spatial patterns and amplitudes shown in Figure 7 over Europe seem unrealistic. A comparison against independent estimates, such as outputs from global hydrological models (e.g., WGHM) or GRACE-based groundwater products (e.g., constrained estimates available via Figshare: https://doi.org/10.6084/m9.figshare.31073527), would be helpful to contextualize and validate the results.4. Rescaling procedure
The manuscript would also benefit from a clearer description of the rescaling methodology. While filtering is described, it is not sufficiently clear how the final amplitudes are restored or interpreted. Since end users are typically interested in physically meaningful magnitudes, a transparent explanation of how near-realistic amplitudes are ensured is essential.Overall, I believe the study addresses an important topic, and the proposed dataset could be valuable to the community. Addressing the points above, particularly with respect to methodological justification, consistency, and validation, would considerably improve the quality and reliability of the manuscript.
I hope these comments are helpful, and wish you all the best.
Ehsan ForootanCitation: https://doi.org/10.5194/essd-2025-797-RC2
Data sets
Global Gravity-based Groundwater Product (G3P) V. 1.12 A. Güntner et al. https://doi.org/10.5880/g3p.2024.001
Global Multi-Resolution Land Fraction and Land–Ocean Masks Derived from ESA CCI Water Bodies v4.0 (Version 1.0) E. Sharifi et al. https://doi.org/10.5880/G3P.2025.001
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Dear chief Editor,
Thank you for appointing me as a reviewer of the essd-2025-797 manuscript. Please, kindly find attached my comments.
Warm regards,