the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 Mar 2026
Water storage trends derived from the GRACE/-FO global gravity-based groundwater product (G3P)
Abstract. The Global Gravity-based Groundwater Product (G3P) provides observations of global groundwater storage (GWS) variations, calculated from GRACE/-FO-derived terrestrial water storage (TWS) by subtracting the contributions of root zone soil moisture, glaciers, surface water storage, and snow water equivalent. As such, G3P provides the first globally consistent, publicly available groundwater dataset from satellite gravimetry for continental-scale trend assessment. Such data are a crucial observational constraint for assessing global groundwater depletion, recharge, and water storage trends related to climate change and human activities. A challenge is the reliable separation and quantification of long-term trends from stochastic signals attributable to natural climate variability (“climate noise”) and observational system errors. To address this, we introduce a trend-analysis framework that uses calibrated time-series models to account for trends, seasonal, and stochastic variations. The approach requires minimal assumptions about underlying processes and enables the separation of significant long-term trends of GWS and TWS from stochastic variability.
Applying this framework to 21.5 years of data, our results show (1) that groundwater depletion dominates freshwater decline at continental scales – most prominently in Asia (-55 km3 yr-1) – whereas ice mass loss remains the largest global contributor by component, and (2) reveal previously unobserved trends, including increasing groundwater storage in large parts of Africa (+37 km3 yr-1) and declining trends attributed to droughts, e.g., in Southern Africa, Asia, and parts of Europe. Our global aggregation of statistically significant trends indicates net volumetric GWS changes of -27 km3 yr-1 and TWS changes of -145 km3 yr-1 (excluding Antarctica and Greenland). We also find that many regions in the Northern Hemisphere are prone to climate-induced drying, with parts of Europe close to persistent long-term groundwater decline.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Hydrology and Earth System Sciences.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.-
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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Supplement
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- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2026-975', Anonymous Referee #1, 03 Jun 2026
- AC1: 'Reply on RC1', Roland Hohensinn, 14 Jul 2026
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RC2: 'Comment on egusphere-2026-975', Anonymous Referee #2, 26 Jun 2026
The article entitled "Water storage trends derived from the GRACE/-FO global gravity-based groundwater product (G3P)" discusses prospects and limitations of the newly available satellite-based global groundwater change assessment. I find the paper interesting and well within the scope of the journal. However, I also noted a few weaknesses that should be thoroughly addressed through a revision.
I think that it would be good to find indicative names for the clusters depicted in Fig. 2. Using the colors is not really helpful, since those can only be used with the Figure. There are common features in most of the clusters, and I strongly urge the authors to come up with a narrative to distinguish those groups.
There are quite a few inconsistencies in the nomenclature (e.g., identical units are abbreviated in different ways ) and various rather sloppy formulations. Some examples are given below. A careful revision of the full manuscript in terms of language and style seems urgently necessary.
The paper is heavily relying on abbreviations that are introduced at some point but later hardly used again. This applies in particular to abbreviations of certain mathematical methods, which have hardly any value apart from expert readers who might recognize the abbreviations from earlier encounters outside this manuscript. I think that this should be changed to make the article better readable.
line 29: "close to persistent" is not very precise wording
line 58 and 69: different ways for volume change units are given without an obvious reason. Please harmonize throughout the article.
line 84: There is an extensive body of (recent) literature from Donald Argus and colleagues on the use of GRACE data in California which should be cited here.
line 109: "long-period-transient-type apparent-secular trend" is a very much German construct. Please revise.
line 148: I am still not sure what an "uncertainty aware" assessment should be. Please elaborate and explain better.
line 152: Two times "limited" in a single line
line 155: demonstrated scalability has not been achieved, I believe. Please re-consider your statement.
line 165: I think that this is rather a sequential than a hierarchical approach.
line 199: It should rather read w.r.t. the temporal mean over the reference period. Same applies to line 204 (and elsewhere).
line 236: pre-analysis sounds wrong here
line 238: I think that overtones of the annual signal are meant here. Harmonics basically can have any frequency.
line 266: "gaps as-is" is a non-information. Please explain or remove.
line 277 and following: Various abbreviations listed here could be omitted since those are never used again: GLS, RMLE, MLE, OLS, PLWN.
line 301: space are missing in the equation.
line 311: "surface is calculated geodetically" sounds quite blatant for a trivial latitude
weighting.line 313: what is a "direct physical integration"?
line 625: why do you use bold font in the subsection on Asia only?
Citation: https://doi.org/10.5194/egusphere-2026-975-RC2 - AC2: 'Reply on RC2', Roland Hohensinn, 14 Jul 2026
Peer review completion
Post-review adjustments
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2026-975', Anonymous Referee #1, 03 Jun 2026
The paper describes a statistically based method to identify long and short term variability (trends and interannual variability) in TWS and GW. It also include analysis on the TWS components such as SWE, Soil moisture, surface water, and glacier. Th authors run their analysis on the G3P product. An already established framework that determines GWS from removing snow, soil moisture, etc. from GRACE/FO derived TWS estimates.
In general, I think the paper is a valuable contribution to the scientific community as it identifies trends and variabilities in GSW and TWS using the 21+ years of GRACE/FO record. The paper uses statistically robust methods to identify significance in the trends and compares their findings with previously defined trends.
I have a few recommendations, as noted next.
- As a reader, I am lost to what the main novelty of the paper is as many previous references exist that determine long and short term variability using GRACE/FO data. I think it resides in determining trends using G3P, globally and for an extended time-period (21+years). I recommend the authors to simplify and reinforce what are the key novelties.
- The reviewer (as well as other readers) might not as familiar with many of the statistical terms/methods that are described in 2.2. I recommend streamlining or explain in a more simple words these as much as possible and try to the best of their possibilities to make these statistics methods more easily digestible.
- While I think the cluster analysis (fig 2) makes sence from a statistical prespective, I am finding hard to connect or link it to a physically meaningful hydrological meaning. Can the authors be more explicit about why a specifc trend in one ares can be represented the same way as the trend in an other area? If we then show higher resolution trends (Fig 4), whats the needs to report the cluster analysis? Again, it is not clear what is the added value of the cluster analysis, please clarify or perhaps move to a supplementary text?
- In order to determine GWS, G3P removes single components of SWS, SWE, etc. While I think most of these are satellite derived, SWS is model based (according to 191-194) if so, how are human driven (diversions, dams, etc) fluxes/storages represented?
- Along the same line, if only root zone soil moisture is used (182-185) how are irrigation driven changes of the SURFACE soil moisture being accounted for? Please add caveats about this.
- Section 3.2 is the core of the paper in my opinion. I would emphasize it by adding a table to summarize also how the authors results agree or disagree with previously reported analysis. This will also help with framing the novelty point (above).
- Finally, I found some typos here and there, please re-read accordingly to identify any grammar issues. Example: 111: “This [IS] a strong..” 715-716: some words are missing perhaps? 725: fix parathesis in the
Citation: https://doi.org/10.5194/egusphere-2026-975-RC1 - AC1: 'Reply on RC1', Roland Hohensinn, 14 Jul 2026
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RC2: 'Comment on egusphere-2026-975', Anonymous Referee #2, 26 Jun 2026
The article entitled "Water storage trends derived from the GRACE/-FO global gravity-based groundwater product (G3P)" discusses prospects and limitations of the newly available satellite-based global groundwater change assessment. I find the paper interesting and well within the scope of the journal. However, I also noted a few weaknesses that should be thoroughly addressed through a revision.
I think that it would be good to find indicative names for the clusters depicted in Fig. 2. Using the colors is not really helpful, since those can only be used with the Figure. There are common features in most of the clusters, and I strongly urge the authors to come up with a narrative to distinguish those groups.
There are quite a few inconsistencies in the nomenclature (e.g., identical units are abbreviated in different ways ) and various rather sloppy formulations. Some examples are given below. A careful revision of the full manuscript in terms of language and style seems urgently necessary.
The paper is heavily relying on abbreviations that are introduced at some point but later hardly used again. This applies in particular to abbreviations of certain mathematical methods, which have hardly any value apart from expert readers who might recognize the abbreviations from earlier encounters outside this manuscript. I think that this should be changed to make the article better readable.
line 29: "close to persistent" is not very precise wording
line 58 and 69: different ways for volume change units are given without an obvious reason. Please harmonize throughout the article.
line 84: There is an extensive body of (recent) literature from Donald Argus and colleagues on the use of GRACE data in California which should be cited here.
line 109: "long-period-transient-type apparent-secular trend" is a very much German construct. Please revise.
line 148: I am still not sure what an "uncertainty aware" assessment should be. Please elaborate and explain better.
line 152: Two times "limited" in a single line
line 155: demonstrated scalability has not been achieved, I believe. Please re-consider your statement.
line 165: I think that this is rather a sequential than a hierarchical approach.
line 199: It should rather read w.r.t. the temporal mean over the reference period. Same applies to line 204 (and elsewhere).
line 236: pre-analysis sounds wrong here
line 238: I think that overtones of the annual signal are meant here. Harmonics basically can have any frequency.
line 266: "gaps as-is" is a non-information. Please explain or remove.
line 277 and following: Various abbreviations listed here could be omitted since those are never used again: GLS, RMLE, MLE, OLS, PLWN.
line 301: space are missing in the equation.
line 311: "surface is calculated geodetically" sounds quite blatant for a trivial latitude
weighting.line 313: what is a "direct physical integration"?
line 625: why do you use bold font in the subsection on Asia only?
Citation: https://doi.org/10.5194/egusphere-2026-975-RC2 - AC2: 'Reply on RC2', Roland Hohensinn, 14 Jul 2026
Peer review completion
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Cited
1 citations as recorded by crossref.
Junyang Gou
Ulrich Meyer
Vincent Humphrey
Wouter Dorigo
Eva Boergens
Benedikt Soja
Alexander Gruber
Laura Jensen
Annette Eicker
Michael Rast
Andreas Güntner
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(26439 KB) - Metadata XML
-
Supplement
(6714 KB) - BibTeX
- EndNote
- Final revised paper
The paper describes a statistically based method to identify long and short term variability (trends and interannual variability) in TWS and GW. It also include analysis on the TWS components such as SWE, Soil moisture, surface water, and glacier. Th authors run their analysis on the G3P product. An already established framework that determines GWS from removing snow, soil moisture, etc. from GRACE/FO derived TWS estimates.
In general, I think the paper is a valuable contribution to the scientific community as it identifies trends and variabilities in GSW and TWS using the 21+ years of GRACE/FO record. The paper uses statistically robust methods to identify significance in the trends and compares their findings with previously defined trends.
I have a few recommendations, as noted next.