The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Lake volume and groundwater storage variations in Tibetan Plateau's endorheic basin
Open accessAbstract
The Tibetan Plateau (TP), the highest and largest plateau in the world, with complex and competing cryospheric‐hydrologic‐geodynamic processes, is particularly sensitive to anthropogenic warming. The quantitative water mass budget in the TP is poorly known. Here we examine annual changes in lake area, level, and volume during 1970s–2015. We find that a complex pattern of lake volume changes during 1970s–2015: a slight decrease of −2.78 Gt yr−1 during 1970s–1995, followed by a rapid increase of 12.53 Gt yr−1 during 1996–2010, and then a recent deceleration (1.46 Gt yr−1) during 2011–2015. We then estimated the recent water mass budget for the Inner TP, 2003–2009, including changes in terrestrial water storage, lake volume, glacier mass, snow water equivalent (SWE), soil moisture, and permafrost. The dominant components of water mass budget, namely, changes in lake volume (7.72 ± 0.63 Gt yr−1) and groundwater storage (5.01 ± 1.59 Gt yr−1), increased at similar rates. We find that increased net precipitation contributes the majority of water supply (74%) for the lake volume increase, followed by glacier mass loss (13%), and ground ice melt due to permafrost degradation (12%). Other term such as SWE (1%) makes a relatively small contribution. These results suggest that the hydrologic cycle in the TP has intensified remarkably during recent decades.
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
Cites
A Threshold Selection Method from Gray-Level Histograms
Otsu, N. (1979) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1979.4310076 · Cited by 43,398
The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features
McFEETERS, S. K. (1996) · International Journal of Remote Sensing · doi:10.1080/01431169608948714 · Cited by 7,725
The Global Land Data Assimilation System
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., et al. (2004) · Bulletin of the American Meteorological Society · doi:10.1175/bams-85-3-381 · Cited by 5,614
High-resolution mapping of global surface water and its long-term changes
Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016) · Nature · doi:10.1038/nature20584 · Cited by 5,513
Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings
Yao, T., Thompson, L., Yang, W., Yu, W., Gao, Y., Guo, X., Yang, X., Duan, K., Zhao, H., Xu, B., et al. (2012) · Nature Climate Change · doi:10.1038/nclimate1580 · Cited by 2,887
Self-citationLakes as sentinels of climate change
Adrian, R., O'Reilly, C. M., Zagarese, H., Baines, S. B., Hessen, D. O., Keller, W., Livingstone, D. M., Sommaruga, R., Straile, D., Van Donk, E., et al. (2009) · Limnology and Oceanography · doi:10.4319/lo.2009.54.6_part_2.2283 · Cited by 1,946
Estimating the volume and age of water stored in global lakes using a geo-statistical approach
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016) · Nature Communications · doi:10.1038/ncomms13603 · Cited by 1,779
A global inventory of lakes based on high-resolution satellite imagery
Verpoorter, C., Kutser, T., Seekell, D. A., & Tranvik, L. J. (2014) · Geophysical Research Letters · doi:10.1002/2014gl060641 · Cited by 1,504
Space geodesy constrains ice age terminal deglaciation: The global ICE‐6G_C (VM5a) model
Peltier, W. R., Argus, D. F., & Drummond, R. (2015) · Journal of Geophysical Research: Solid Earth · doi:10.1002/2014jb011176 · Cited by 1,470
Qiu, J. (2008) · Nature · doi:10.1038/454393a · Cited by 1,425
A Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009
Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr, J., Berthier, E., Hock, R., Pfeffer, W. T., Kaser, G., et al. (2013) · Science · doi:10.1126/science.1234532 · Cited by 1,281
Self-citationFeng, W., Zhong, M., Lemoine, J., Biancale, R., Hsu, H., & Xia, J. (2013) · Water Resources Research · doi:10.1002/wrcr.20192 · Cited by 908
Self-citationCrétaux, J.-F., Arsen, A., Calmant, S., Kouraev, A., Vuglinski, V., Bergé-Nguyen, M., Gennero, M.-C., Nino, F., Abarca Del Rio, R., Cazenave, A., et al. (2011) · Advances in Space Research · doi:10.1016/j.asr.2011.01.004 · Cited by 751
Derivation and analysis of a high-resolution estimate of global permafrost zonation
Gruber, S. (2012) · The Cryosphere · doi:10.5194/tc-6-221-2012 · Cited by 729
Yang, M., Nelson, F. E., Shiklomanov, N. I., Guo, D., & Wan, G. (2010) · Earth-Science Reviews · doi:10.1016/j.earscirev.2010.07.002 · Cited by 642
Rapid loss of lakes on the Mongolian Plateau
Tao, S., Fang, J., Zhao, X., Zhao, S., Shen, H., Hu, H., Tang, Z., Wang, Z., & Guo, Q. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1411748112 · Cited by 584
Asoka, A., Gleeson, T., Wada, Y., & Mishra, V. K. (2017) · Nature Geoscience · doi:10.1038/ngeo2869 · Cited by 537
Zhang, G., Yao, T., Xie, H., et al. (2015) · Global and Planetary Change · doi:10.1016/j.gloplacha.2015.05.013 · Cited by 505
Self-citationEarth's surface water change over the past 30 years
Donchyts, G., Baart, F., Winsemius, H., Gorelick, N., Kwadijk, J., & van de Giesen, N. (2016) · Nature Climate Change · doi:10.1038/nclimate3111 · Cited by 483
Fan, Y., & van den Dool, H. (2004) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2003jd004345 · Cited by 475
Kääb, A., Treichler, D., Nuth, C., & Berthier, E. (2015) · The Cryosphere · doi:10.5194/tc-9-557-2015 · Cited by 461
A half‐century of changes in China's lakes: Global warming or human influence?
Rong-hua, M., Duan, H., Hu, C., Feng, X., Li, A., Ju, W., Jiang, J., & Yang, G. (2010) · Geophysical Research Letters · doi:10.1029/2010gl045514 · Cited by 373
Lake Volume Monitoring from Space
Crétaux, J.-F., Abarca-del-Río, R., Bergé-Nguyen, M., Arsen, A., Drolon, V., Clos, G., & Maisongrande, P. (2016) · Surveys in Geophysics · doi:10.1007/s10712-016-9362-6 · Cited by 334
Zhang, G., Yao, T., Piao, S., Bolch, T., Xie, H., Chen, D., Gao, Y., O'Reilly, C. M., Shum, C. K., Yang, K., et al. (2017) · Geophysical Research Letters · doi:10.1002/2016gl072033 · Cited by 323
Self-citationIncreased mass over the Tibetan Plateau: From lakes or glaciers?
Zhang, G., Yao, T., Xie, H., Kang, S., & Lei, Y. (2013) · Geophysical Research Letters · doi:10.1002/grl.50462 · Cited by 312
Self-citationSheng, Y., Song, C., Wang, J., Lyons, E. A., Knox, B. R., Cox, J. S., & Gao, F. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2015.12.041 · Cited by 232
Yang, R., Zhu, L., Wang, J., Ju, J., Ma, Q., Turner, F., & Guo, Y. (2016) · Climatic Change · doi:10.1007/s10584-016-1877-9 · Cited by 151
A lake data set for the Tibetan Plateau from the 1960s, 2005, and 2014
Wan, W., Long, D., Hong, Y. E., Ma, Y., Yuan, Y., Xiao, P., Duan, H., Han, Z., & Gu, X. (2016) · Scientific Data · doi:10.1038/sdata.2016.39 · Cited by 149
Differences in the water-balance components of four lakes in the southern-central Tibetan Plateau
Biskop, S., Maussion, F., Krause, P., & Fink, M. (2016) · Hydrology and earth system sciences · doi:10.5194/hess-20-209-2016 · Cited by 139
Using GRACE to constrain precipitation amount over cold mountainous basins
Behrangi, A., Gardner, A., Reager, J. T., & Fisher, J. B. (2016) · Geophysical Research Letters · doi:10.1002/2016gl071832 · Cited by 56
Self-citationWang, Q., Yi, S., & Sun, W. (2016) · Geophysical Journal International · doi:10.1093/gji/ggw293 · Cited by 45
Self-citationAssessing uncertainty and sensor biases in passive microwave data across High Mountain Asia
Smith, T., & Bookhagen, B. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.03.037 · Cited by 42
Cited by
Global lake responses to climate change
Woolway, R. I., Kraemer, B. M., Lenters, J. D., Merchant, C. J., O’Reilly, C. M., & Sharma, S. (2020) · Nature Reviews Earth & Environment · doi:10.1038/s43017-020-0067-5 · Cited by 1,538
Zhang, G., Yao, T., Chen, W., Zheng, G., Shum, C. K., Yang, K., Piao, S., Sheng, Y., Yi, S., Li, J., et al. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.11.038 · Cited by 455
Self-citationMassive collapse of two glaciers in western Tibet in 2016 after surge-like instability
Kääb, A., Leinss, S., Gilbert, A., Bühler, Y., Gascoin, S., Evans, S. G., Bartelt, P., Berthier, E., Brun, F., Chao, W.-A., et al. (2018) · Nature Geoscience · doi:10.1038/s41561-017-0039-7 · Cited by 367
Self-citationChen, F., Zhang, J., Liu, J., Cao, X., Hou, J., Zhu, L., Xu, X., Liu, X., Wang, M., Wu, D., et al. (2020) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2020.106444 · Cited by 353
Self-citation
Metadata
- Authors
- Zhang, G., Yao, T., Shum, C. K., Yi, S., Yang, K., Xie, H., Feng, W., Bolch, T., Wang, L., Behrangi, A., Zhang, H., Wang, W., Xiang, Y., & Yu, J.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2017-06-02
- Volume
- 44
- Issue
- 11
- Pages
- 5550-5560
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2611057588
- Cited by
- 458
- References
- 32
- FWCI
- 20.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
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.
