the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assessing Terrestrial Water Storage Change Since the 1980s
Abstract. Water availability for societies and ecosystems depends upon Terrestrial Water Storage (TWS), yet global, spatially resolved measurements are largely unavailable before the advent of the Gravity Recovery and Climate Experiment (GRACE) gravimetric measurements in 2002. By exploiting a larger set of model and observations-based datasets than previously considered, along with statistical and machine learning techniques, we advance understanding of TWS changes since the 1980s, including accounting for human water management (HWM).
A decline in TWS during 2002–2019 is identified for three global hydrologic models with HWM and bias-corrected precipitation forcing (-0.91 to -0.06 mm yr-1) with only one showing larger decreases than observed by GRACE observations (-0.80 mm y-1). We further identify a longer-term decline in TWS during 1980–2019 in these models, linked with regional precipitation decreases and the net effects of HWM through TWS drawdowns over northern India, southwest U.S. and northeastern China, yet the amplitude of the global land trends remains poorly quantified, ranging from -0.72 to +0.04 mm y-1. Statistical / Machine Learning (ML) reconstructions are found to match GRACE variability but their fidelity in the pre-GRACE/FO period remains unknown.
A stronger decline in TWS since 1980 in the European Centre for Medium-range Weather Forecasts 5th generation reanalysis (ERA5) enhanced land component (ERA5-Land) is linked to an artificial drop in precipitation around 2000–2002 in ERA5 that is most pronounced over equatorial central Africa, northeastern China and the northern Argentina / La Plata region. Our findings urge caution in inferring changes in hydroclimate variables from ERA5-Land and other reanalyses due to inhomogeneities in the assimilated observational data. Continued emphasis on bias corrections to hydrometeorological data and better modeling of HWM are crucial to improving all retrospective analyses of changes in land surface hydrology and terrestrial water stores.
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Status: open (until 02 Jul 2026)
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RC1: 'Comment on egusphere-2026-2539', Anonymous Referee #1, 31 May 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2539/egusphere-2026-2539-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2026-2539-RC1 -
AC1: 'Reply on RC1', Franklin Robertson, 04 Jun 2026
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The authors thank the reviewer for providing a variety of suggestions that will lead to the improvement of our paper. The reviewer statement that the analysis is interesting and that the main conclusions appear reasonable is an important assessment.
Two of the most substantive critiques of our paper involve (1) the claim that the choice of title is too broad and (2) the uneven use of the Satellite LASER Ranging (SLR) data. Regarding the title, our survey of four different methodologies for determining terrestrial water storage (TWS) included GRACE determinations, global hydrologic models, a state-of-the-art land reanalysis, and statistical methods. The breadth of these approaches led us to view this work as an “assessment” of current abilities. We acknowledge that our discussion in the paper is more heavily slanted toward the ERA5 land reanalysis. In large part this is because we were able to use precipitation observations / analyses, the ISIMIP3a model experiment results, and records of satellite sensor availability to more deeply assess its performance. However, we did intercompare all of the four methodologies in terms of variability and trends, pointing out the abilities and limitations of each. We suspect that our conclusions section needs to state more clearly that support for a continued downward trend in TWS, however varied in amplitude among the estimates, does constitute an assessment of current estimates by available methods. We will reconsider the title and, pending comments from other reviewers, try to formulate a clearer and more informative version.
In terms of the SLR data, you are correct that the SLR trend should be included in Table 3. Regarding its inclusion in Table 2, the SLR mascons or “footprints” are quite large, covering multiple river basins, which makes them difficult to compare to the gridded data in Figure 2. Furthermore , the SLR data does not extend back to 1980. In any case we could provide a supporting SLR figure in an Appendix to the paper. These changes will be made in a subsequent revision to the present paper.
Further criticisms involve formatting of the manuscript, many acronyms and other elements of style. Revisions to our paper will insure we adhere to HESS style. We will also streamline the presentation for readability. Please note that we did provide a list of abbreviations as noted on page 2.
We’re confident that a subsequent revision, pending comments from other reviewers, will satisfy the concerns raised in your evaluation.
Citation: https://doi.org/10.5194/egusphere-2026-2539-AC1
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AC1: 'Reply on RC1', Franklin Robertson, 04 Jun 2026
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