Long-term satellite-based observations have helped quantify glacier mass change and the response of the hydrosphere to glacier changes. However, subaqueous mass loss associated with lake-terminating glaciers is not accounted for in geodetic methods, leading to an underestimation of glacier mass loss. Here we use multi-temporal satellite data and an empirical area–volume relationship to estimate the volume change of glacial lakes across the greater Himalaya and quantify subaqueous mass loss due to the replacement of ice with lake water. We show that proglacial lakes have increased 47% by number, 33 ± 2% by area and 42 ± 14% by volume from 2000 to 2020. The expansion of glacial lakes has resulted in 2.7 ± 0.8 Gt of subaqueous mass loss between 2000 and 2020, such that the previous estimate of total mass loss of lake-terminating glaciers in the greater Himalaya is underestimated by 6.5 ± 2.1%. Regionally, the largest underestimation (10 ± 4%) occurred in the central Himalaya, where glacial lake growth has been the most rapid. Our estimates reduce uncertainties in total glacier mass loss, provide important data for glacio-hydrological models and therefore also support the water recources management in this sensitive mountain region.
This is a preview of subscription content, access via your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Rent or buy this article
Get just this article for as long as you need it
Prices may be subject to local taxes which are calculated during checkout
The Landsat images used for glacial lake mapping are available from USGS at https://glovis.usgs.gov. The glacier mass-balance data used are from Hugonnet et al.15 and are available at https://doi.org/10.6096/13 (accessed 5 January 2022). The mapped glacial lakes in 1990, 2000, 2010, 2015 and 2020 provided as ArcGIS Shapefiles are available at https://doi.org/10.6084/m9.figshare.21708590. The bathymetric measurements for 16 proglacial lakes from our study, including latitude/longitude and lake depth of samples, provided as Microsoft Excel files are available at https://doi.org/10.6084/m9.figshare.21569175. Source data are provided with this paper.
The codes used for estimating glacier mass balance and the trend of glacier volume and area at grid scale are available at https://doi.org/10.6084/m9.figshare.21606384.
Veh, G., Korup, O. & Walz, A. Hazard from Himalayan glacier lake outburst floods. Proc. Natl Acad. Sci. USA 117, 907–912 (2019).
Zheng, G. et al. Increasing risk of glacial lake outburst floods from future Third Pole deglaciation. Nat. Clim. Change 11, 411–417 (2021).
Carrivick, J. L. & Tweed, F. S. Proglacial lakes: character, behaviour and geological importance. Quat. Sci. Rev. 78, 34–52 (2013).
Nie, Y. et al. A regional-scale assessment of Himalayan glacial lake changes using satellite observations from 1990 to 2015. Remote Sens. Environ. 189, 1–13 (2017).
Zhang, G., Yao, T., Xie, H., Wang, W. & Yang, W. An inventory of glacial lakes in the Third Pole region and their changes in response to global warming. Glob. Planet. Change 131, 148–157 (2015).
Wang, X. et al. Glacial lake inventory of high-mountain Asia in 1990 and 2018 derived from Landsat images. Earth Syst. Sci. Data 12, 2169–2182 (2020).
Liu, Q. et al. Interannual flow dynamics driven by frontal retreat of a lake-terminating glacier in the Chinese Central Himalaya. Earth Planet Sc. Lett. 546, 116450 (2020).
Basnett, S., Kulkarni, A. V. & Bolch, T. The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya, India. J. Glaciol. 59, 1035–1046 (2013).
Thakuri, S., Salerno, F., Bolch, T., Guyennon, N. & Tartari, G. Factors controlling the accelerated expansion of Imja Lake, Mount Everest region, Nepal. Ann. Glaciol. 57, 245–257 (2016).
Tsutaki, S. et al. Contrasting thinning patterns between lake- and land-terminating glaciers in the Bhutanese Himalaya. Cryosphere 13, 2733–2750 (2019).
Brun, F. et al. Heterogeneous influence of glacier morphology on the mass balance variability in High Mountain Asia. J. Geophys. Res. Earth Surf. 124, 1331–1345 (2019).
King, O., Bhattacharya, A., Bhambri, R. & Bolch, T. Glacial lakes exacerbate Himalayan glacier mass loss. Sci. Rep. 9, 18145 (2019).
Shugar, D. H. et al. Rapid worldwide growth of glacial lakes since 1990. Nat. Clim. Change 10, 939–945 (2020).
Ng, F., Liu, S., Mavlyudov, B. & Wang, Y. Climatic control on the peak discharge of glacier outburst floods. Geophys. Res. Lett. 34, L21503 (2007).
Hugonnet, R. et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726–731 (2021).
Kääb, A., Berthier, E., Nuth, C., Gardelle, J. & Arnaud, Y. Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas. Nature 488, 495–498 (2012).
Gardner, A. S. et al. A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science 340, 852–857 (2013).
Brun, F., Berthier, E., Wagnon, P., Kääb, A. & Treichler, D. A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016. Nat. Geosci. 10, 668–673 (2017).
Miles, E. et al. Health and sustainability of glaciers in High Mountain Asia. Nat. Commun. 12, 2868 (2021).
Shean, D. E. et al. A systematic, regional assessment of High Mountain Asia glacier mass balance. Front. Earth Sci. 7, 363 (2020).
Bhattacharya, A. et al. High Mountain Asian glacier response to climate revealed by multi-temporal satellite observations since the 1960s. Nat. Commun. 12, 4133 (2021).
Bolch, T., Pieczonka, T. & Benn, D. Multi-decadal mass loss of glaciers in the Everest area (Nepal Himalaya) derived from stereo imagery. Cryosphere 5, 349–358 (2011).
King, O. et al. Six decades of glacier mass changes around Mt Everest are revealed by historical and contemporary images. One Earth 3, 608–620 (2020).
Farías-Barahona, D. et al. Detailed quantification of glacier elevation and mass changes in South Georgia. Environ. Res. Lett. 15, 034036 (2020).
Larsen, C. F., Motyka, R. J., Arendt, A. A., Echelmeyer, K. A. & Geissler, P. E. Glacier changes in southeast Alaska and northwest British Columbia and contribution to sea level rise. J. Geophys. Res. 112, F01007 (2007).
Rignot, E., Rivera, A. & Casassa, G. Contribution of the Patagonia icefields of South America to sea level rise. Science 302, 434–437 (2003).
Braun, M. H. et al. Constraining glacier elevation and mass changes in South America. Nat. Clim. Change 9, 130–136 (2019).
Truffer, M. & Motyka, R. J. Where glaciers meet water: subaqueous melt and its relevance to glaciers in various settings. Rev. Geophys. 54, 220–239 (2016).
Benn, D. I., Warren, C. R. & Mottram, R. H. Calving processes and the dynamics of calving glaciers. Earth Sci. Rev. 82, 143–179 (2007).
Chen, F. et al. Annual 30 m dataset for glacial lakes in High Mountain Asia from 2008 to 2017. Earth Syst. Sci. Data 13, 741–766 (2021).
Fujita, K. et al. Potential flood volume of Himalayan glacial lakes. Nat. Hazards Earth Syst. Sci. 13, 1827–1839 (2013).
Cook, S. J. & Quincey, D. J. Estimating the volume of Alpine glacial lakes. Earth Surf. Dyn. 3, 559–575 (2015).
Huggel, C., Kääb, A., Haeberli, W., Teysseire, P. & Paul, F. Remote sensing based assessment of hazards from glacier lake outbursts: a case study in the Swiss Alps. Can. Geotech. J. 39, 316–330 (2002).
Cuffey, K. M. & Paterson, W. S. B. The Physics of Glaciers (Academic Press, 2010).
Maurer, J. M., Schaefer, J. M., Rupper, S. & Corley, A. Acceleration of ice loss across the Himalayas over the past 40 years. Sci. Adv. 5, eaav7266 (2019).
Pronk, J. B., Bolch, T., King, O., Wouters, B. & Benn, D. I. Contrasting surface velocities between lake- and land-terminating glaciers in the Himalayan region. Cryosphere 15, 5577–5599 (2021).
Carrivick, J. L., Tweed, F. S., Sutherland, J. L. & Mallalieu, J. Toward numerical modeling of interactions between ice-marginal proglacial lakes and glaciers. Front. Earth Sci. 8, 577068 (2020).
Sugiyama, S. et al. Ice speed of a calving glacier modulated by small fluctuations in basal water pressure. Nat. Geosci. 4, 597–600 (2011).
Bolch, T. et al. in The Hindu Kush Himalaya Assessment: Mountains, Climate Change, Sustainability and People (eds Wester, P. et al.) 209–255 (Springer, 2019).
Zhang, G. et al. Glacial lake evolution and glacier–lake interactions in the Poiqu River basin, central Himalaya, 1964−2017. J. Glaciol. 65, 347–365 (2019).
Haritashya, U. et al. Evolution and controls of large glacial lakes in the Nepal Himalaya. Remote Sens. 10, 798 (2018).
Linsbauer, A. et al. Modelling glacier-bed overdeepenings and possible future lakes for the glaciers in the Himalaya—Karakoram region. Ann. Glaciol. 57, 119–130 (2016).
Furian, W., Maussion, F. & Schneider, C. Projected 21st-century glacial lake evolution in High Mountain Asia. Front. Earth Sci. 10, 821798 (2022).
Marzeion, B. et al. Partitioning the uncertainty of ensemble projections of global glacier mass change. Earths Future 8, e2019EF001470 (2020).
Rounce, D. R., Hock, R. & Shean, D. E. Glacier mass change in High Mountain Asia through 2100 using the open-source Python Glacier Evolution Model (PyGEM). Front. Earth Sci. 7, 331 (2020).
Kraaijenbrink, P. D. A., Bierkens, M. F. P., Lutz, A. F. & Immerzeel, W. W. Impact of a global temperature rise of 1.5 degrees Celsius on Asia’s glaciers. Nature 549, 257–260 (2017).
Furian, W., Loibl, D. & Schneider, C. Future glacial lakes in High Mountain Asia: an inventory and assessment of hazard potential from surrounding slopes. J. Glaciol. 67, 653–670 (2021).
Farinotti, D. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Nat. Geosci. 12, 168–173 (2019).
Dimri, A. P. et al. A review of atmospheric and land surface processes with emphasis on flood generation in the southern Himalayan rivers. Sci. Total Environ. 556, 98–115 (2016).
Bolch, T. et al. The state and fate of Himalayan glaciers. Science 336, 310–314 (2012).
RGI-Consortium Randolph Glacier Inventory—A Dataset of Global Glacier Outlines Version 6.0 (NSIDC, 2017); https://doi.org/10.7265/4m1f-gd79
Salerno, F. et al. Glacial lake distribution in the Mount Everest region: uncertainty of measurement and conditions of formation. Glob. Planet. Change 92–93, 30–39 (2012).
Ageta, Y. et al. Expansion of glacier lakes in recent decades in the Bhutan Himalayas. In IAHS-Publication 264: Debris-covered Glaciers, Proc. Workshop, Seattle, Washington, USA (eds Nakawo, M. et al.) 165−176 (IAHS, 2000).
Harrison, S. et al. Climate change and the global pattern of moraine-dammed glacial lake outburst floods. Cryosphere 12, 1195–1209 (2018).
Wang, W. et al. Integrated hazard assessment of Cirenmaco glacial lake in Zhangzangbo valley, Central Himalayas. Geomorphology 306, 292–305 (2018).
Yao, X., Liu, S., Sun, M., Wei, J. & Guo, W. Volume calculation and analysis of the changes in moraine-dammed lakes in the north Himalaya: a case study of Longbasaba lake. J. Glaciol. 58, 753–760 (2012).
Falátková, K., ŠOBR, M., Kocum, J. & JANSKÝ, B. Hydrological regime of Adygine lake, Tien Shan, Kyrgyzstan. Geografie 119, 320–341 (2014).
Bolch, T., Buchroithner, M., Peters, J., Baessler, M. & Bajracharya, S. Identification of glacier motion and potentially dangerous glacial lakes in the Mt Everest region/Nepal using spaceborne imagery. Nat. Hazards Earth Syst. Sci. 8, 1329–1340 (2008).
Watson, C. S. et al. Mass loss from calving in Himalayan proglacial lakes. Front. Earth Sci. 7, 342 (2020).
NASADEM Merged DEM Global 1 Arc Second Version 001 (NASA, accessed 25 July 2022).
Fujita, K., Sakai, A., Nuimura, T., Yamaguchi, S. & Sharma, R. R. Recent changes in Imja glacial lake and its damming moraine in the Nepal Himalaya revealed by in situ surveys and multi-temporal ASTER imagery. Environ. Res. Lett. 4, 045205 (2009).
Hanshaw, M. N. & Bookhagen, B. Glacial areas, lake areas, and snow lines from 1975 to 2012: status of the Cordillera Vilcanota, including the Quelccaya Ice Cap, northern central Andes, Peru. Cryosphere 8, 359–376 (2014).
O’Gorman, L. Subpixel precision of straight-edged shapes for registration and measurement. IEEE Trans. Pattern Anal. Mach. Intell. 18, 746–751 (1996).
Hall, M. J., van den Boogaard, H. F. P., Fernando, R. C. & Mynett, A. E. The construction of confidence intervals for frequency analysis using resampling techniques. Hydrol. Earth Syst. Sci. 8, 235–246 (2004).
Manly, B. F. Randomization, Bootstrap and Monte Carlo Methods in Biology: Texts in Statistical Science 3rd edn (Chapman and Hall/CRC, 2018).
Huss, M. Density assumptions for converting geodetic glacier volume change to mass change. Cryosphere 7, 877–887 (2013).
This study was supported by grants from the Second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0201), Basic Science Center for Tibetan Plateau Earth System (BSCTPES, NSFC project no. 41988101-03), the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20100300), the National Natural Science Foundation of China (41871056, 41831177), the Dragon 4 programme supported by ESA and MOST (4000121469/17/I-NB), the Swiss National Science Foundation (IZLCZ2_169979/1, 200021E_177652/1) and the National Aeronautics and Space Administration grants 80NSSC20K1595 and 80NSSC20K1296. We are grateful to C. Huang, Y. Xiang, S. Wang, J. Pronk, M. Peng, T. Zhang, J. Luo, F. Xu, T. Zhou and M. Zhao for joint fieldwork and to S. Rinzin and N. Khadka for collecting bathymetry measurements. We thank General Geological and Environmental Monitoring Station, Tibet Autonomous Region for providing in situ lake-level data of Guangxie Co.
The authors declare no competing interests.
Peer review information
Nature Geoscience thanks Alexandre Bevington, Désirée Treichler and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the Nature Geoscience team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 Spatial coverage of Landsat images used for mapping lakes and the location of proglacial lakes with bathymetry measurements.
a, Number and footprint of Landsat images used for mapping glacial lakes in 2020 in the greater Himalaya. b, Proglacial lakes with bathymetry measurements. Proglacial lakes with bathymetry measurements, including 16 lakes in this study and 34 lakes from previously published studies. The insets show the uncrewed surface vessel used for measuring lake depth (left) and a sketch of the bathymetry measuring system (right).
Extended Data Fig. 2 Multi-temporal proglacial lake number and area changes during 1990−2020 in the greater Himalaya.
a, The ratios by area of lake type (status 2020) and glacier terminus type (RGI v6.0). b, Newly formed proglacial lakes. c, Change and rate of change of proglacial lake area on a 1° × 1° grid. Linear trend of lake area in 1990, 2000, 2010, 2015, 2020 and acceleration on decadal proglacial lake area change rate (1990–2000, 2000–2010, 2010–2020) by least squares regression are shown, with + signs at a significance level of 0.05. d, Changes in the number (bars) and decadal number (dashed lines) of proglacial lakes in the greater Himalaya, and several subregions (HK-Hindu Kush, KK-Karakoram, WH-Western Himalaya, CH-Central Himalaya, EH-Eastern Himalaya, NQ-Nyainqêentanglha, HD-Hengduan) from 1990 to 2020. e, Multi-temporal area (bars) and decadal area change (dashed lines) of proglacial lakes in the whole greater Himalaya, and several subregions from 1990 to 2020.
Extended Data Fig. 3 Field photos for lakes with bathymetry measurements (DD/MM/YYYY).
All 16 proglacial lakes were newly measured in 2020 and 2021 for this study. Insets show that each proglacial lake has an outflow keeping the lake level relatively constant. The increase of proglacial lake volume is mainly due to glacier retreat.
Extended Data Fig. 4 Bathymetry measurements.
Tracks of the bathymetry measurements for the 16 proglacial lakes newly measured for this study.
Extended Data Fig. 5 Interpolated bathymetry.
Lake depth calculated using Kriging interpolation for the 16 proglacial lakes newly measured for this study.
Extended Data Fig. 6 Spatial-temporal patterns of lake changes of Guangxie Co (Lat: 29.4646 °N; Long: 96.5017 °E).
a, Spatial pattern of lake area changes from 1999 to 2020. The outline of Midui Glacier from glacier inventory (RGI v6.0) derived from image on 08 September, 2005 is also shown. b, Time series of lake area change from 1999 to 2020. Error bar is the uncertainty of delineated lake boundary. c, Daily relative lake level data of in-situ measurements by pressure transducer from 27 April, 2014 to 31 August, 2021. Photos taken by T. Zhou showing Guangxie Co, parent glacier (Midui Glacier), water outlet and water level gauge.
Extended Data Fig. 7 Spatial-temporal patterns of lake changes of Jiongpu Co (30.6642 °N; 94.4777 °E).
a, Spatial pattern of lake area changes from 2001 to 2020. b, Time series of lake area change from 2001 to 2020. Error bar is the uncertainty of delineated lake boundary. c, Field photo taken on 07 October, 2011 by Wei Yang. Background photo taken on 18 August, 2019 by Yanbin Liu showing Jiongpu Co, water outlet, and parent glacier.
Extended Data Fig. 8 Spatial-temporal patterns of lake changes of Galong Co (28.3180 °N; 85.8421 °E).
a, Spatial pattern of lake area changes from 2000 to 2020. b, Time series of lake area change from 2000 to 2020. Error bar is the uncertainty of delineated lake boundary. c, Field photo taken on 30 September, 2019.
Extended Data Fig. 9 Elevation difference in lateral moraine and water levels of Galong Co.
a, Elevation profiles from NASADEM and ICESat-2 along tracks A and B. NASADEM was acquired in February 2000 and ICESat-2 was acquired on 10 November, 2018. b, Elevation profiles from NASADEM and ICESat-2 along track C. c, Water levels between 2000 and 2021. Lake level in 2000 was derived from NASADEM, between 2006 and 2011 from AW3D30, between 2010 and 2015 from TanDEM-X, and 2018 to 2021 from ICESat-2.
Extended Data Fig. 10 Preliminary global estimate of the portion of underestimated subaqueous ice mass loss of lake-terminating glaciers between 2000 and 2020.
The preliminary underestimated subaqueous mass loss (% and Gt) in each RGI region and globally are shown. The size of the diameter represents the total mass loss of lake-terminating glaciers in each regions and globally. The global lake data is based on Shugar et al.13. Future work should seek to refine these estimates using by improving glacial lake inventories and determining a global or regional volume-area relationship as the relationship applied here was based on bathymetric surveys in the greater Himalaya.
Source Data Fig. 2
Statistical Source Data.
Source Data Fig. 3
Statistical Source Data.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhang, G., Bolch, T., Yao, T. et al. Underestimated mass loss from lake-terminating glaciers in the greater Himalaya. Nat. Geosci. 16, 333–338 (2023). https://doi.org/10.1038/s41561-023-01150-1