Articles | Volume 16, issue 7
https://doi.org/10.5194/tc-16-2745-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-2745-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jul 2022
Research article |
| 14 Jul 2022
| 14 Jul 2022
Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau
Lingxiao Wang
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Huayun Zhou
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
University of the Chinese Academy of Sciences, Beijing 100049, China
Shibo Liu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
University of the Chinese Academy of Sciences, Beijing 100049, China
Erji Du
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Guangyue Liu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Yao Xiao
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Guojie Hu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Chong Wang
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Zhe Sun
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Zhibin Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Yongping Qiao
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Tonghua Wu
Cryosphere Research Station on the Qinghai–Xizang Plateau, State Key
Laboratory of Cryosphere Sciences, Northwest Institute of Eco-Environment and
Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
Chengye Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Xubing Li
School of Geographical Sciences, Nanjing University of Information
Science & Technology (NUIST), Nanjing 210044, China
Related authors
Jianting Zhao, Lin Zhao, Zhe Sun, Guojie Hu, Defu Zou, Minxuan Xiao, Guangyue Liu, Qiangqiang Pang, Erji Du, Zhibin Li, Xiaodong Wu, Yao Xiao, Lingxiao Wang, and Wenxin Zhang
The Cryosphere, 19, 4211–4236, https://doi.org/10.5194/tc-19-4211-2025, https://doi.org/10.5194/tc-19-4211-2025, 2025
Short summary
Short summary
We used the Moving-Grid Permafrost Model (MVPM) to simulate the permafrost thermal regime in West Kunlun (55,669 km², NW Qinghai–Tibet Plateau), driven by remote-sensing-based land surface temperature (LST; 1980–2022). The model showed high accuracy and stability. Despite ongoing warming (+0.40 °C per decade), permafrost extent remained stable, reflecting delayed deep responses. The permafrost thermal regime reveals altitude- and soil-dependent responses to climate change and offers valuable insights into thermal states in data-scarce regions.
Jianting Zhao, Lin Zhao, Zhe Sun, Fujun Niu, Guojie Hu, Defu Zou, Guangyue Liu, Erji Du, Chong Wang, Lingxiao Wang, Yongping Qiao, Jianzong Shi, Yuxin Zhang, Junqiang Gao, Yuanwei Wang, Yan Li, Wenjun Yu, Huayun Zhou, Zanpin Xing, Minxuan Xiao, Luhui Yin, and Shengfeng Wang
The Cryosphere, 16, 4823–4846, https://doi.org/10.5194/tc-16-4823-2022, https://doi.org/10.5194/tc-16-4823-2022, 2022
Short summary
Short summary
Permafrost has been warming and thawing globally; this is especially true in boundary regions. We focus on the changes and variability in permafrost distribution and thermal dynamics in the northern limit of permafrost on the Qinghai–Tibet Plateau (QTP) by applying a new permafrost model. Unlike previous papers on this topic, our findings highlight a slow, decaying process in the response of permafrost in the QTP to a warming climate, especially regarding areal extent.
Jianting Zhao, Lin Zhao, Zhe Sun, Guojie Hu, Defu Zou, Minxuan Xiao, Guangyue Liu, Qiangqiang Pang, Erji Du, Zhibin Li, Xiaodong Wu, Yao Xiao, Lingxiao Wang, and Wenxin Zhang
The Cryosphere, 19, 4211–4236, https://doi.org/10.5194/tc-19-4211-2025, https://doi.org/10.5194/tc-19-4211-2025, 2025
Short summary
Short summary
We used the Moving-Grid Permafrost Model (MVPM) to simulate the permafrost thermal regime in West Kunlun (55,669 km², NW Qinghai–Tibet Plateau), driven by remote-sensing-based land surface temperature (LST; 1980–2022). The model showed high accuracy and stability. Despite ongoing warming (+0.40 °C per decade), permafrost extent remained stable, reflecting delayed deep responses. The permafrost thermal regime reveals altitude- and soil-dependent responses to climate change and offers valuable insights into thermal states in data-scarce regions.
Defu Zou, Lin Zhao, Guojie Hu, Erji Du, Guangyue Liu, Chong Wang, and Wangping Li
Earth Syst. Sci. Data, 17, 1731–1742, https://doi.org/10.5194/essd-17-1731-2025, https://doi.org/10.5194/essd-17-1731-2025, 2025
Short summary
Short summary
This study provides baseline data of permafrost temperature at 15 m depth on the Qinghai–Tibetan Plateau (QTP) over the period 2010–2019 at a spatial resolution of nearly 1 km, using 231 borehole records and a machine learning method. The average MAGT15 m of the QTP permafrost was −1.85 °C, with 90 % of the values ranging from −5.1 to −0.1 °C and 51.2 % exceeding −1.5 °C. The data can serve as a crucial boundary condition for deeper permafrost assessments and a reference for model simulations.
Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam., 14, 609–627, https://doi.org/10.5194/esd-14-609-2023, https://doi.org/10.5194/esd-14-609-2023, 2023
Short summary
Short summary
Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland-water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Jianting Zhao, Lin Zhao, Zhe Sun, Fujun Niu, Guojie Hu, Defu Zou, Guangyue Liu, Erji Du, Chong Wang, Lingxiao Wang, Yongping Qiao, Jianzong Shi, Yuxin Zhang, Junqiang Gao, Yuanwei Wang, Yan Li, Wenjun Yu, Huayun Zhou, Zanpin Xing, Minxuan Xiao, Luhui Yin, and Shengfeng Wang
The Cryosphere, 16, 4823–4846, https://doi.org/10.5194/tc-16-4823-2022, https://doi.org/10.5194/tc-16-4823-2022, 2022
Short summary
Short summary
Permafrost has been warming and thawing globally; this is especially true in boundary regions. We focus on the changes and variability in permafrost distribution and thermal dynamics in the northern limit of permafrost on the Qinghai–Tibet Plateau (QTP) by applying a new permafrost model. Unlike previous papers on this topic, our findings highlight a slow, decaying process in the response of permafrost in the QTP to a warming climate, especially regarding areal extent.
Tonghua Wu, Changwei Xie, Xiaofan Zhu, Jie Chen, Wu Wang, Ren Li, Amin Wen, Dong Wang, Peiqing Lou, Chengpeng Shang, Yune La, Xianhua Wei, Xin Ma, Yongping Qiao, Xiaodong Wu, Qiangqiang Pang, and Guojie Hu
Earth Syst. Sci. Data, 14, 1257–1269, https://doi.org/10.5194/essd-14-1257-2022, https://doi.org/10.5194/essd-14-1257-2022, 2022
Short summary
Short summary
We presented an 11-year time series of meteorological, active layer, and permafrost data at the Mahan Mountain relict permafrost site in northeastern Qinghai-Tibet Plateau. From 2010 to 2020, the increasing rate of active layer thickness was 1.8 cm-year and the permafrost temperature showed slight changes. The release of those data would be helpful to understand the impacts of climate change on permafrost in relict permafrost regions and to validate the permafrost models and land surface models.
Yi Zhao, Zhuotong Nan, Hailong Ji, and Lin Zhao
The Cryosphere, 16, 825–849, https://doi.org/10.5194/tc-16-825-2022, https://doi.org/10.5194/tc-16-825-2022, 2022
Short summary
Short summary
Convective heat transfer (CHT) is important in affecting thermal regimes in permafrost regions. We quantified its thermal impacts by contrasting the simulation results from three scenarios in which the Simultaneous Heat and Water model includes full, partial, and no consideration of CHT. The results show the CHT commonly happens in shallow and middle soil depths during thawing periods and has greater impacts in spring than summer. The CHT has both heating and cooling effects on the active layer.
Xiaowen Wang, Lin Liu, Yan Hu, Tonghua Wu, Lin Zhao, Qiao Liu, Rui Zhang, Bo Zhang, and Guoxiang Liu
Nat. Hazards Earth Syst. Sci., 21, 2791–2810, https://doi.org/10.5194/nhess-21-2791-2021, https://doi.org/10.5194/nhess-21-2791-2021, 2021
Short summary
Short summary
We characterized the multi-decadal geomorphic changes of a low-angle valley glacier in the East Kunlun Mountains and assessed the detachment hazard influence. The observations reveal a slow surge-like dynamic pattern of the glacier tongue. The maximum runout distances of two endmember avalanche scenarios were presented. This study provides a reference to evaluate the runout hazards of low-angle mountain glaciers prone to detachment.
Lin Zhao, Defu Zou, Guojie Hu, Tonghua Wu, Erji Du, Guangyue Liu, Yao Xiao, Ren Li, Qiangqiang Pang, Yongping Qiao, Xiaodong Wu, Zhe Sun, Zanpin Xing, Yu Sheng, Yonghua Zhao, Jianzong Shi, Changwei Xie, Lingxiao Wang, Chong Wang, and Guodong Cheng
Earth Syst. Sci. Data, 13, 4207–4218, https://doi.org/10.5194/essd-13-4207-2021, https://doi.org/10.5194/essd-13-4207-2021, 2021
Short summary
Short summary
Lack of a synthesis dataset of the permafrost state has greatly limited our understanding of permafrost-related research as well as the calibration and validation of RS retrievals and model simulation. We compiled this dataset, including ground temperature, active layer hydrothermal regimes, and meteorological indexes based on our observational network, and we summarized the basic changes in permafrost and its climatic conditions. It is the first comprehensive dataset on permafrost for the QXP.
Lihui Luo, Yanli Zhuang, Mingyi Zhang, Zhongqiong Zhang, Wei Ma, Wenzhi Zhao, Lin Zhao, Li Wang, Yanmei Shi, Ze Zhang, Quntao Duan, Deyu Tian, and Qingguo Zhou
Earth Syst. Sci. Data, 13, 4035–4052, https://doi.org/10.5194/essd-13-4035-2021, https://doi.org/10.5194/essd-13-4035-2021, 2021
Short summary
Short summary
We implement a variety of sensors to monitor the hydrological and thermal deformation between permafrost slopes and engineering projects in the hinterland of the Qinghai–Tibet Plateau. We present the integrated observation dataset from the 1950s to 2020, explaining the instrumentation, processing, data visualisation, and quality control.
Dong Wang, Tonghua Wu, Lin Zhao, Cuicui Mu, Ren Li, Xianhua Wei, Guojie Hu, Defu Zou, Xiaofan Zhu, Jie Chen, Junmin Hao, Jie Ni, Xiangfei Li, Wensi Ma, Amin Wen, Chengpeng Shang, Yune La, Xin Ma, and Xiaodong Wu
Earth Syst. Sci. Data, 13, 3453–3465, https://doi.org/10.5194/essd-13-3453-2021, https://doi.org/10.5194/essd-13-3453-2021, 2021
Short summary
Short summary
The Third Pole regions are important components in the global permafrost, and the detailed spatial soil organic carbon data are the scientific basis for environmental protection as well as the development of Earth system models. Based on multiple environmental variables and soil profile data, this study use machine-learning approaches to evaluate the SOC storage and spatial distribution at a depth interval of 0–3 m in the frozen ground area of the Third Pole region.
Xiangfei Li, Tonghua Wu, Xiaodong Wu, Jie Chen, Xiaofan Zhu, Guojie Hu, Ren Li, Yongping Qiao, Cheng Yang, Junming Hao, Jie Ni, and Wensi Ma
Geosci. Model Dev., 14, 1753–1771, https://doi.org/10.5194/gmd-14-1753-2021, https://doi.org/10.5194/gmd-14-1753-2021, 2021
Short summary
Short summary
In this study, an ensemble simulation of 55296 scheme combinations for at a typical permafrost site on the Qinghai–Tibet Plateau (QTP) was conducted. The general performance of the Noah-MP model for snow cover events (SCEs), soil temperature (ST) and soil liquid water content (SLW) was assessed, and the sensitivities of parameterization schemes at different depths were investigated. We show that Noah-MP tends to overestimate SCEs and underestimate ST and topsoil SLW on the QTP.
Cited articles
Bense, V., Kooi, H., Ferguson, G., and Read, T.: Permafrost degradation as a
control on hydrogeological regime shifts in a warming climate, J.
Geophys. Res.-Earth Surf., 117, F03036, https://doi.org/10.1029/2011JF002143, 2012.
Berardino, P., Fornaro, G., Lanari, R., and Sansosti, E.: A new algorithm
for surface deformation monitoring based on small baseline differential SAR
interferograms, Geoscience and Remote Sensing, IEEE Transactions on, 40,
2375–2383, 2002.
Bian, D., Bian, B., La, B., Wang, C., and Chen, T.: The Response of Water
Level of Selin Co to Climate Change during 1975–2008, Acta
Geographica Sinica, 65, 313–319, 2010 (in Chinese).
Brun, F., Treichler, D., Shean, D., and Immerzeel, W. W.: Limited
contribution of glacier mass loss to the recent increase in Tibetan Plateau
lake volume, Front. Earth Sci., 8, 582060, https://doi.org/10.3389/feart.2020.582060, 2020.
Buckel, J., Reinosch, E., Hördt, A., Zhang, F., Riedel, B., Gerke, M., Schwalb, A., and Mäusbacher, R.: Insights into a remote cryosphere: a multi-method approach to assess permafrost occurrence at the Qugaqie basin, western Nyainqêntanglha Range, Tibetan Plateau, The Cryosphere, 15, 149–168, https://doi.org/10.5194/tc-15-149-2021, 2021.
Chen, C. W. and Zebker, H. A.: Phase unwrapping for large SAR
interferograms: Statistical segmentation and generalized network models,
IEEE T. Geosci. Remote, 40, 1709–1719, 2002.
Chen, J., Liu, L., Zhang, T., Cao, B., and Lin, H.: Using persistent
scatterer interferometry to map and quantify permafrost thaw subsidence: A
case study of Eboling Mountain on the Qinghai–Tibet Plateau, J.
Geophys. Res.-Earth Surf., 123, 2663–2676, 2018.
Chen, J., Wu, Y., O'Connor, M., Cardenas, M. B., Schaefer, K., Michaelides,
R., and Kling, G.: Active layer freeze-thaw and water storage dynamics in
permafrost environments inferred from InSAR, Remote Sens. Environ.,
248, 112007, https://doi.org/10.1016/j.rse.2020.112007, 2020.
Chen, J., Wu, T., Zou, D., Liu, L., Wu, X., Gong, W., Zhu, X., Li, R., Hao,
J., and Hu, G.: Magnitudes and patterns of large-scale permafrost ground
deformation revealed by Sentinel-1 InSAR on the central Qinghai-Tibet
Plateau, Remote Sens. Environ., 268, 112778, https://doi.org/10.1016/j.rse.2021.112778, 2022.
Cheng, G.: The mechanism of repeated-segregation for the formation of thick
layered ground ice, Cold Reg. Sci. Technol., 8, 57–66, 1983.
Daout, S., Doin, M. P., Peltzer, G., Socquet, A., and Lasserre, C.:
Large-scale InSAR monitoring of permafrost freeze–thaw cycles on the
Tibetan Plateau, Geophys. Res. Lett., 44, 901–909, 2017.
Daout, S., Dini, B., Haeberli, W., Doin, M.-P., and Parsons, B.: Ice loss in
the Northeastern Tibetan Plateau permafrost as seen by 16 yr of ESA SAR
missions, Earth Planet. Sc. Lett., 545, 116404, https://doi.org/10.1016/j.epsl.2020.116404, 2020.
Deij, Y., Nima, J., Qianba, O., Zeng, L., and Luosang, Q.: Lake Area
Variation of Selin Tso in 1975–2016 and Its Influential Factors, Plateau
and Mountain Meteorology Research, 38, 35–41, https://doi.org/10.3969/j.issn.1674-2184.2018.02.006, 2018 (in Chinese).
Doin, M. P., Twardzik, C., Ducret, G., Lasserre, C., Guillaso, S., and
Jianbao, S.: InSAR measurement of the deformation around Siling Co Lake:
Inferences on the lower crust viscosity in central Tibet, J.
Geophys. Res.-Sol. Ea., 120, 5290–5310, 2015.
Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H.,
Maussion, F., and Pandit, A.: A consensus estimate for the ice thickness
distribution of all glaciers on Earth, Nat. Geosci., 12, 168–173, 2019.
French, H. and Harbor, J.: The Development and History of Glacial and
Periglacial Geomorphology, Treatise on Geomorphology, Academic Press,
https://doi.org/10.1016/B978-0-12-374739-6.00190-1, 2013.
French, H. M.: The periglacial environment, John Wiley & Sons, ISBN 978-1-119-13278-3, 2017.
Günther, F., Overduin, P. P., Yakshina, I. A., Opel, T., Baranskaya, A. V., and Grigoriev, M. N.: Observing Muostakh disappear: permafrost thaw subsidence and erosion of a ground-ice-rich island in response to arctic summer warming and sea ice reduction, The Cryosphere, 9, 151–178, https://doi.org/10.5194/tc-9-151-2015, 2015.
Guo, W., Liu, S., Xu, J., Wu, L., Shangguan, D., Yao, X., Wei, J., Bao, W.,
Yu, P., and Liu, Q.: The second Chinese glacier inventory: data, methods and
results, J. Glaciol., 61, 357–372, 2015.
Guo, Y., Zhang, Y., Ma, N., Xu, J., and Zhang, T.: Long-term changes in
evaporation over Siling Co Lake on the Tibetan Plateau and its impact on
recent rapid lake expansion, Atmos. Res., 216, 141–150, 2019.
Hwang, C.-W., Cheng, Y. S., Yang, W. H., Zhang, G., Huang, Y. R., Shen, W.
B., and Pan, Y.: Lake level changes in the Tibetan Plateau from Cryosat-2,
SARAL, ICESat, and Jason-2 altimeters, Terr. Atmos. Ocean. Sci., 30, 1–18,
2019.
Jin, H., Huang, Y., Bense, V. F., Ma, Q., Marchenko, S. S., Shepelev, V. V.,
Hu, Y., Liang, S., Spektor, V. V., and Jin, X.: Permafrost Degradation and
Its Hydrogeological Impacts, Water, 14, 372, https://doi.org/10.3390/w14030372, 2022.
Jolivet, R., Agram, P. S., Lin, N. Y., Simons, M., Doin, M. P., Peltzer, G.,
and Li, Z.: Improving InSAR geodesy using global atmospheric models, J. Geophys. Res.-Sol. Ea., 119, 2324–2341, 2014.
Kokelj, S. V. and Jorgenson, M.: Advances in thermokarst research,
Permafrost Periglac. Process., 24, 108–119, 2013.
Lanari, R., Lundgren, P., Manzo, M., and Casu, F.: Satellite radar
interferometry time series analysis of surface deformation for Los Angeles,
California, Geophys. Res. Lett., 31, L23613, https://doi.org/10.1029/2004GL021294, 2004.
Lantuit, H. and Pollard, W.: Fifty years of coastal erosion and
retrogressive thaw slump activity on Herschel Island, southern Beaufort Sea,
Yukon Territory, Canada, Geomorphology, 95, 84–102, 2008.
Lei, Y., Yao, T., Bird, B. W., Yang, K., Zhai, J., and Sheng, Y.: Coherent
lake growth on the central Tibetan Plateau since the 1970s: Characterization
and attribution, J. Hydrol., 483, 61–67, 2013.
Lei, Y., Yang, K., Wang, B., Sheng, Y., Bird, B. W., Zhang, G., and Tian,
L.: Response of inland lake dynamics over the Tibetan Plateau to climate
change, Clim. Change, 125, 281–290, 2014.
Li, X., Long, D., Huang, Q., Han, P., Zhao, F., and Wada, Y.: High-temporal-resolution water level and storage change data sets for lakes on the Tibetan Plateau during 2000–2017 using multiple altimetric missions and Landsat-derived lake shoreline positions, Earth Syst. Sci. Data, 11, 1603–1627, https://doi.org/10.5194/essd-11-1603-2019, 2019.
Li, Y., Liao, J., Guo, H., Liu, Z., and Shen, G.: Patterns and potential
drivers of dramatic changes in Tibetan lakes, 1972–2010, PloS one, 9,
e111890, https://doi.org/10.1371/journal.pone.0111890, 2014.
Li, Z., Zhao, R., Hu, J., Wen, L., Feng, G., Zhang, Z., and Wang, Q.: InSAR
analysis of surface deformation over permafrost to estimate active layer
thickness based on one-dimensional heat transfer model of soils, Sci.
Rep.-UK, 5, 15542, https://doi.org/10.1038/srep15542, 2015.
Liu, L., Schaefer, K., Zhang, T., and Wahr, J.: Estimating 1992–2000
average active layer thickness on the Alaskan North Slope from remotely
sensed surface subsidence, J. Geophys. Res.-Earth Surf.,
117, F01005, https://doi.org/10.1029/2011JF002041, 2012a.
Liu, S., Guo, W., and Xu, J.: The second glacier inventory dataset of China
(version 1.0) (2006–2011), TPDC [data set], https://doi.org/10.3972/glacier.001.2013.db, 2012b.
Lu, P., Han, J., Li, Z., Xu, R., Li, R., Hao, T., and Qiao, G.: Lake
outburst accelerated permafrost degradation on Qinghai-Tibet Plateau, Remote
Sens. Environ., 249, 112011, https://doi.org/10.1016/j.rse.2020.112011, 2020.
Ma, Q., Jin, H.-J., Bense, V. F., Dong-Liang, L., Marchenko, S. S., Harris,
S. A., and Lan, Y.-C.: Impacts of degrading permafrost on streamflow in the
source area of Yellow River on the Qinghai-Tibet Plateau, China, Adv.
Clim. Change Res., 10, 225–239, https://doi.org/10.1016/j.accre.2020.02.001, 2020.
Mackay, J. R.: Downward water movement into frozen ground, western arctic
coast, Canada, Can. J. Earth Sci., 20, 120–134, 1983.
Meng, K., Shi, X., Wang, E., and Liu, F.: High-altitude salt lake elevation
changes and glacial ablation in Central Tibet, 2000–2010, Chinese Sci.
B., 57, 525–534, 2012.
Pepe, A. and Lanari, R.: On the extension of the minimum cost flow algorithm
for phase unwrapping of multitemporal differential SAR interferograms, IEEE
T. Geosci. Remote, 44, 2374–2383, 2006.
Qiao, B., Zhu, L., and Yang, R.: Temporal-spatial differences in lake water
storage changes and their links to climate change throughout the Tibetan
Plateau, Remote Sens. Environ., 222, 232–243, 2019.
Reinosch, E., Buckel, J., Dong, J., Gerke, M., Baade, J., and Riedel, B.: InSAR time series analysis of seasonal surface displacement dynamics on the Tibetan Plateau, The Cryosphere, 14, 1633–1650, https://doi.org/10.5194/tc-14-1633-2020, 2020.
Shiklomanov, N. I., Streletskiy, D. A., Little, J. D., and Nelson, F. E.:
Isotropic thaw subsidence in undisturbed permafrost landscapes, Geophys.
Res. Lett., 40, 6356–6361, 2013.
Song, C., Huang, B., Richards, K., Ke, L., and Hien Phan, V.: Accelerated
lake expansion on the Tibetan Plateau in the 2000s: Induced by glacial
melting or other processes?, Water Resour. Res., 50, 3170–3186, 2014.
Streletskiy, D. A., Shiklomanov, N. I., Little, J. D., Nelson, F. E., Brown,
J., Nyland, K. E., and Klene, A. E.: Thaw subsidence in undisturbed tundra
landscapes, Barrow, Alaska, 1962–2015, Permafrost Periglac.
Process., 28, 566–572, 2016.
Sun, F., Ma, R., He, B., Zhao, X., Zeng, Y., Zhang, S., and Tang, S.:
Changing Patterns of Lakes on The Southern Tibetan Plateau Based on
Multi-Source Satellite Data, Remote Sensing, 12, 3450, https://doi.org/10.3390/rs12203450, 2020.
Tong, K., Su, F., and Xu, B.: Quantifying the contribution of glacier
meltwater in the expansion of the largest lake in Tibet, J.
Geophys. Res.-Atmos., 121, 11158–11173, https://doi.org/10.1002/2016JD025424, 2016.
Treichler, D., Kääb, A., Salzmann, N., and Xu, C.-Y.: Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes, The Cryosphere, 13, 2977–3005, https://doi.org/10.5194/tc-13-2977-2019, 2019.
Usai, S.: A least squares database approach for SAR interferometric data,
Geoscience and Remote Sensing, IEEE Transactions on, 41, 753–760, 2003.
Wu, Z., Zhao, L., Liu, L., Zhu, R., Gao, Z., Qiao, Y., Tian, L., Zhou, H.,
and Xie, M.: Surface-deformation monitoring in the permafrost regions over
the Tibetan Plateau, using Sentinel-1 data, Sci. Cold Arid
Reg., 10, 114–125, 2018.
Yang, Y., Wu, Q., Yun, H., Jin, H., and Zhang, Z.: Evaluation of the
hydrological contributions of permafrost to the thermokarst lakes on the
Qinghai–Tibet Plateau using stable isotopes, Global Planet. Change,
140, 1–8, 2016.
Yang, Y., Wu, Q., Jin, H., Wang, Q., Huang, Y., Luo, D., Gao, S., and Jin,
X.: Delineating the hydrological processes and hydraulic connectivities
under permafrost degradation on Northeastern Qinghai-Tibet Plateau, China,
J. Hydrol., 569, 359–372, 2019.
Zhang, G.: The lakes larger than 1 km2 in Tibetan Plateau (V3.0) (1970s–2021), National Tibetan Plateau Data Center [data set], https://doi.org/10.11888/Hydro.tpdc.270303, 2019.
Zhang, G., Yao, T., and Kang, S.: Water balance estimates of ten greatest
lakes in China using ICESat and Landsat data, Chin. Sci. Bull.,
58, 2664–2678, 2013 (in Chinese).
Zhang, G., Yao, T., Shum, C., Yi, S., Yang, K., Xie, H., Feng, W., Bolch,
T., Wang, L., and Behrangi, A.: Lake volume and groundwater storage
variations in Tibetan Plateau's endorheic basin, Geophys. Res.
Lett., 44, 5550–5560, 2017.
Zhang, G., Chen, W., and Xie, H.: Tibetan Plateau's lake level and volume
changes from NASA's ICESat/ICESat-2 and Landsat Missions, Geophys.
Res. Lett., 46, 13107–13118, 2019.
Zhang, G., Yao, T., Xie, H., Yang, K., Zhu, L., Shum, C., Bolch, T., Yi, S.,
Allen, S., and Jiang, L.: Response of Tibetan Plateau's lakes to climate
changes: trend, pattern, and mechanisms, Earth-Sci. Rev., 208, 103269, https://doi.org/10.1016/j.earscirev.2020.103269,
2020.
Zhang, G., Bolch, T., Chen, W., and Crétaux, J.-F.: Comprehensive
estimation of lake volume changes on the Tibetan Plateau during 1976–2019
and basin-wide glacier contribution, Sci. Total Environ., 772,
145463, https://doi.org/10.1016/j.scitotenv.2021.145463, 2021a.
Zhang, G., Ran, Y., Wan, W., Luo, W., Chen, W., Xu, F., and Li, X.: 100 years of lake evolution over the Qinghai–Tibet Plateau, Earth Syst. Sci. Data, 13, 3951–3966, https://doi.org/10.5194/essd-13-3951-2021, 2021b.
Zhang, Y., Fattahi, H., and Amelung, F.: Small baseline InSAR time series
analysis: Unwrapping error correction and noise reduction, Comput.
Geosci., 133, 104331, https://doi.org/10.1016/j.cageo.2019.104331, 2019.
Zhang, Y., Xie, C., Wu, T., Zhao, L., Wu, J., Wu, X., Li, R., Hu, G., Liu,
G., and Wang, W.: New permafrost is forming on the exposed bottom of Zonag
Lake on the Qinghai-Tibet Plateau, Sci. Total Environ., 815, 152879, https://doi.org/10.1016/j.scitotenv.2021.152879,
2022.
Zhao, L. and Sheng, Y.: Permafrost and environment changes on the
QinghaiTibetan Plateau, Science Press, Beijing, China, ISBN 9787030581334, 2019 (in Chinese).
Zhao, L., Hu, G., Zou, D., Wu, X., Ma, L., Sun, Z., Yuan, L., Zhou, H., and
Liu, S.: Permafrost Changes and Its Effects on Hydrological Processes on
Qinghai-Tibet Plateau, B. Chinese Acad.
Sci., 34, 1233–1246, 2019 (in Chinese).
Zhao, L., Zou, D., Du, E., Hu, G., Pang, Q., Xiao, Y., Li, R., Sheng, Y.,
Wu, X., Sun, Z., Wang, L., Wang, C., Ma, L., Zhou, H., and Liu, S.: Changing
climate and the permafrost environment on the Qinghai-Tibet (Xizang)
Plateau, Permafrost Periglac. Process., 31, 396–405, https://doi.org/10.1002/ppp.2056, 2020.
Zhou, H., Zhao, L., Tian, l., Wu, Z., Xie, M., Yuan, L., Ni, J., Qiao, Y.,
Gao, Z., and Shi, J.: Monitoring and analysis of surface deformation in the
permafrost area of Wudaoliang on the Tibetan Plateau based on Sentinel-1
data, J. Glaciol. Geocryol., 41, 525–536, 2019 (in Chinese).
Zhu, L., Wang, J., Ju, J., Ma, N., Zhang, Y., Liu, C., Han, B., Liu, L.,
Wang, M., and Ma, Q.: Climatic and lake environmental changes in the Serling
Co region of Tibet over a variety of timescales, Sci. Bull., 64,
422–424, 2019a.
Zhu, L., Zhang, G., Yang, R., Liu, C., Yang, K., Qiao, B., and Han, B.: Lake
Variations on Tibetan Plateau of Recent 40 Years and Future Changing
Tendency, B. Chinese Acad. Sci., 34,
1254–1263, 2019b (in Chinese).
Zou, D., Zhao, L., Sheng, Y., Chen, J., Hu, G., Wu, T., Wu, J., Xie, C., Wu, X., Pang, Q., Wang, W., Du, E., Li, W., Liu, G., Li, J., Qin, Y., Qiao, Y., Wang, Z., Shi, J., and Cheng, G.: A new map of permafrost distribution on the Tibetan Plateau, The Cryosphere, 11, 2527–2542, https://doi.org/10.5194/tc-11-2527-2017, 2017.
Zwieback, S. and Meyer, F. J.: Top-of-permafrost ground ice indicated by remotely sensed late-season subsidence, The Cryosphere, 15, 2041–2055, https://doi.org/10.5194/tc-15-2041-2021, 2021.
Short summary
Selin Co has exhibited the greatest increase in water storage among all the lakes on the Tibetan Plateau in the past decades. This study presents the first attempt to quantify the water contribution of ground ice melting to the expansion of Selin Co by evaluating the ground surface deformation since terrain surface settlement provides a
windowto detect the subsurface ground ice melting. Results reveal that ground ice meltwater contributed ~ 12 % of the lake volume increase during 2017–2020.
Selin Co has exhibited the greatest increase in water storage among all the lakes on the Tibetan...
