The DOI matches its Crossref record.
Dwindling groundwater resources in northern India, from satellite gravity observations
Abstract
Northern India and its surroundings, home to roughly 600 million people, is probably the most heavily irrigated region in the world. Temporal changes in Earth's gravity field in this region as recorded by the GRACE satellite mission, reveal a steady, large‐scale mass loss that we attribute to excessive extraction of groundwater. Combining the GRACE data with hydrological models to remove natural variability, we conclude the region lost groundwater at a rate of 54 ± 9 km 3/yr between April, 2002 (the start of the GRACE mission) and June, 2008. This is probably the largest rate of groundwater loss in any comparable‐sized region on Earth. Its likely contribution to sea level rise is roughly equivalent to that from melting Alaskan glaciers. This trend, if sustained, will lead to a major water crisis in this region when this non‐renewable resource is exhausted.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Emerging trends in global freshwater availability
Rodell, M., Famiglietti, J. S., Wiese, D. N., Reager, J. T., Beaudoing, H. K., Landerer, F. W., & Lo, M.-H. (2018) · Nature · doi:10.1038/s41586-018-0123-1 · Cited by 2,107
Recent contributions of glaciers and ice caps to sea level rise
Jacob, T., Wahr, J., Pfeffer, W. T., & Swenson, S. (2012) · Nature · doi:10.1038/nature10847 · Cited by 992
Self-citationAli, A., & Erenstein, O. (2017) · Climate Risk Management · doi:10.1016/j.crm.2016.12.001 · Cited by 671
Global sea-level budget 1993–present
WCRP Global Sea Level Budget Group (2018) · Earth System Science Data · doi:10.5194/essd-10-1551-2018 · Cited by 624
High‐resolution modeling of human and climate impacts on global water resources
Wada, Y., de Graaf, I. E. M., & van Beek, L. P. H. (2016) · Journal of Advances in Modeling Earth Systems · doi:10.1002/2015ms000618 · Cited by 217
Metadata
- Authors
- Tiwari, V. M., Wahr, J., & Swenson, S.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2009-09
- Volume
- 36
- Issue
- 18
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W1971918252
- Cited by
- 807
- References
- 0
- FWCI
- 18.84
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dwindling groundwater resources in northern India, from satellite gravity observations. https://app.cochat.ai/papers/10.1029/2009gl039401
- The paper
- Tiwari, V. M., Wahr, J., & Swenson, S. (2009). Dwindling groundwater resources in northern India, from satellite gravity observations. Geophysical Research Letters. https://doi.org/10.1029/2009gl039401
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.