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Underestimated mass loss from lake-terminating glaciers in the greater Himalaya

Nature Geoscience volume 16, pages 333–338 (2023)Cite this article

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Abstract

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.

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Fig. 1: Schematic illustration of unaccounted-for subaqueous mass loss of lake-terminating glaciers in the greater Himalaya for 2000–2020 by geodetic methods.
Fig. 2: Change in proglacial lake volume between 2000 and 2020.
Fig. 3: Underestimated subaqueous mass loss of lake-terminating glaciers for the period 2000 to 2020.
Fig. 4: Subaqueous ice loss derived using our empirical approach compared with bathymetry measurements and those derived using the consensus ice thickness estimates.

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Data availability

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.

Code availability

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.

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Acknowledgements

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.

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  1. Tobias Bolch

    Present address: Institute of Geodesy, Graz University of Technology, Graz, Austria

Authors and Affiliations

  1. State Key Laboratory of Tibetan Plateau Earth System Science, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    Guoqing Zhang, Tandong Yao, Wenfeng Chen, Mengmeng Wang & Weicai Wang

  2. School of Geography and Sustainable Development, University of St Andrews, St Andrews, UK

    Tobias Bolch & Owen King

  3. Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA

    David R. Rounce

  4. Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany

    Georg Veh

  5. Department of Geography, University of Zurich, Zurich, Switzerland

    Simon K. Allen

  6. Institute for Environmental Science, University of Geneva, Geneva, Switzerland

    Simon K. Allen

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Contributions

G.Z. and T.B. designed the study with contributions from D.R.R. G.Z. wrote the draft of the manuscript. T.B., D.R.R., G.V., O.K., S.K.A., T.Y., W.C. and W.W. edited the manuscript. M.W. mapped the glacial lakes. W.C. estimated the glacier mass balance. All authors contributed to the final form of the study.

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Correspondence to Guoqing Zhang or Tobias Bolch.

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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.

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Extended data

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.

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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

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