Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

The state of rock debris covering Earth’s glaciers

A Publisher Correction to this article was published on 14 August 2020

This article has been updated

Abstract

Rock debris can accumulate on glacier surfaces and dramatically reduce glacier melt. The structure of a debris cover is unique to each glacier and sensitive to climate. Despite this, debris cover has been omitted from global glacier models and forecasts of their response to a changing climate. Fundamental to resolving these omissions is a global map of debris cover and an estimate of its future spatial evolution. Here we use Landsat imagery and a detailed correction to the Randolph Glacier Inventory to show that 7.3% of mountain glacier area is debris covered and over half of Earth’s debris is concentrated in three regions: Alaska (38.6% of total debris-covered area), Southwest Asia (12.6%) and Greenland (12.0%). We use a set of new metrics, which include stage, the current position of a glacier on its trajectory towards reaching its spatial carrying capacity of debris cover, to quantify the state of glaciers. Debris cover is present on 44% of Earth’s glaciers and prominent (>1.0 km2) on 15%. Of Earth’s glaciers, 20% have a substantial percentage of debris cover for which the net stage is 36% and the bulk of individual glaciers have evolved beyond an optimal moraine configuration favourable for debris-cover expansion. Use of this dataset in global-scale models will enable improved estimates of melt over 10.6% of the global glacier domain.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Global distribution of supraglacial debris cover.
Fig. 2: Polar regions have less debris cover.
Fig. 3: Source-data composite images and examples from different locations on Earth with different metric values.
Fig. 4: Regional distributions of six metrics that relate to glacier health and debris-cover configuration.
Fig. 5: Using current stage and debris expansion potential to anticipate the trajectory of debris-cover evolution.
Fig. 6: Using current stage and moraine abundance to anticipate the trajectory of debris-cover evolution.

Similar content being viewed by others

Data availability

This study relied on publicly available data from the NASA/USGS Landsat program: https://earthexplorer.usgs.gov/. The glacier and debris-cover data that support the findings of this study are available at https://doi.org/10.5281/zenodo.3866466 and are described in the Supplementary Information.

Code availability

All of the code written for this study is available from the corresponding author upon request.

Change history

References

  1. Østrem, G. Ice melting under a thin layer of moraine, and the existence of ice cores in moraine ridges. Geogr. Ann. 41, 228–230 (1959).

    Google Scholar 

  2. Mattson, L. E. Ablation on debris covered glaciers: an example from the Rakhiot Glacier, Punjab, Himalaya. Intern. Assoc. Hydrol. Sci. 218, 289–296 (1993).

    Google Scholar 

  3. Evatt, G. W. et al. Glacial melt under a porous debris layer. J. Glaciol. 61, 825–836 (2015).

    Article  Google Scholar 

  4. Hock, R. et al. GlacierMIP—a model intercomparison of global-scale glacier mass-balance models and projections. J. Glaciol. 65, 453–467 (2019).

    Article  Google Scholar 

  5. Ragettli, S., Bolch, T. & Pellicciotti, F. Heterogeneous glacier thinning patterns over the last 40 years in Langtang Himal, Nepal. Cryosphere 10, 2075–2097 (2016).

    Article  Google Scholar 

  6. Thompson, S., Benn, D. I., Mertes, J. & Luckman, A. Stagnation and mass loss on a Himalayan debris-covered glacier: processes, patterns and rates. J. Glaciol. 62, 467–485 (2016).

    Article  Google Scholar 

  7. Benn, D. I. et al. 2012. Response of debris-covered glaciers in the Mount Everest region to recent warming, and implications for outburst flood hazards. Earth Sci. Rev. 114, 156–174 (2012).

    Article  Google Scholar 

  8. Kirkbride, M. P. in Encyclopedia of Snow, Ice and Glaciers (eds Singh V. P., Singh P. & Haritashya U. K.) 190–191 (Springer, 2011).

  9. Deline, P. Change in surface debris cover on Mont Blanc massif glaciers after the ‘Little Ice Age’ termination. Holocene 15, 302–309 (2005).

    Article  Google Scholar 

  10. Tielidze, L. G. et al. Supra-glacial debris cover changes in the Greater Caucasus from 1986 to 2014. Cryosphere 14, 585–598 (2020).

    Article  Google Scholar 

  11. Kellerer‐Pirklbauer, A., Lieb, G. K., Avian, M. & Gspurning, J. The response of partially debris‐covered valley glaciers to climate change: the example of the Pasterze Glacier (Austria) in the period 1964 to 2006. Geogr. Ann. 90, 269–285 (2008).

    Article  Google Scholar 

  12. Shukla, A., Gupta, R. P. & Arora, M. K. Estimation of debris cover and its temporal variation using optical satellite sensor data: a case study in Chenab Basin, Himalaya. J. Glaciol. 55, 444–452 (2009).

    Article  Google Scholar 

  13. Quincey, D. J. & Glasser, N. F. Morphological and ice-dynamical changes on the Tasman Glacier, New Zealand, 1990–2007. Glob. Planet. Change 68, 185–197 (2009).

    Article  Google Scholar 

  14. Lambrecht, A. et al. A comparison of glacier melt on debris-covered glaciers in the northern and southern Caucasus. Cryosphere 5, 525–538 (2011).

    Article  Google Scholar 

  15. Bhambri, R., Bolch, T., Chaujar, R. K. & Kulshreshtha, S. C. Glacier changes in the Garhwal Himalaya, India, from 1968 to 2006 based on remote sensing. J. Glaciol. 57, 543–556 (2011).

    Article  Google Scholar 

  16. Glasser, N. F. et al. Recent spatial and temporal variations in debris cover on Patagonian glaciers. Geomorphology 273, 202–216 (2016).

    Article  Google Scholar 

  17. Sasaki, O., Noguchi, O., Zhang, Y., Hirabayashi, Y. & Kanae. S. A global high-resolution map of debris on glaciers derived from multi-temporal ASTER images. Preprint at https://doi.org/10.5194/tc-2016-222 (2016).

  18. Scherler, D., Wulf, H. & Gorelick, N. Global assessment of supraglacial debris‐cover extents. Geophys. Res. Lett. 45, 11798–11805 (2018).

    Article  Google Scholar 

  19. Rundquist, D. C. et al. The use of Landsat digital information for assessing glacier inventory parameters. IAHS 126, 321–331 (1980).

    Google Scholar 

  20. Herreid, S. et al. Satellite observations show no net change in the percentage of supraglacial debris-covered area in northern Pakistan from 1977 to 2014. J. Glaciol. 61, 524–536 (2015).

    Article  Google Scholar 

  21. Pfeffer, W. T. et al. The Randolph Glacier Inventory: a globally complete inventory of glaciers. J. Glacial. 60, 537–552 (2014).

    Article  Google Scholar 

  22. RGI Consortium Randolph Glacier Inventory—A Dataset of Global Glacier Outlines Version 6.0 (Global Land Ice Measurements from Space, 2017).

  23. 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).

    Article  Google Scholar 

  24. Meier, M. F. Proposed definitions for glacier mass budget terms. J. Glaciol. 4, 252–263 (1962).

    Article  Google Scholar 

  25. Kirkbride, M. P. & Deline, P. The formation of supraglacial debris covers by primary dispersal from transverse englacial debris bands. Earth Surf. Process. Landf. 38, 1779–1792 (2013).

    Article  Google Scholar 

  26. Thakuri, S. et al. Tracing glacier changes since the 1960s on the south slope of Mt Everest (central Southern Himalaya) using optical satellite imagery. Cryosphere 8, 1297–1315 (2014).

    Article  Google Scholar 

  27. Mölg, N., Bolch, T., Walter, A. & Vieli, A. Unravelling the evolution of Zmuttgletscher and its debris cover since the end of the Little Ice Age. Cryosphere 13, 1889–1909 (2019).

    Article  Google Scholar 

  28. 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).

    Article  Google Scholar 

  29. Scherler, D., Bookhagen, B. & Strecker, M. R. Hillslope–glacier coupling: the interplay of topography and glacial dynamics in High Asia. J. Geophys. Res. Earth Surf. 116, F02019 (2011).

    Article  Google Scholar 

  30. Nagai, H., Fujita, K., Nuimura, T. & Sakai, A. Southwest-facing slopes control the formation of debris-covered glaciers in the Bhutan Himalaya. Cryosphere 7, 1303–1314 (2013).

    Article  Google Scholar 

  31. Banerjee, A. & Wani, B. A. Exponentially decreasing erosion rates protect the high-elevation crests of the Himalaya. Earth Planet. Sci. Lett. 497, 22–28 (2018).

    Article  Google Scholar 

  32. Anderson, R. S. A model of ablation-dominated medial moraines and the generation of debris-mantled glacier snouts. J. Glaciol. 46, 459–469 (2000).

    Article  Google Scholar 

  33. Anderson, L. S. & Anderson, R. S. Modeling debris-covered glaciers: response to steady debris deposition. Cryosphere 10, 1105–1124 (2016).

    Article  Google Scholar 

  34. Jouvet, G., Huss, M., Funk, M. & Blatter, H. Modelling the retreat of Grosser Aletschgletscher, Switzerland, in a changing climate. J. Glaciol. 57, 1033–1045 (2011).

    Article  Google Scholar 

  35. Hambrey, M. J. et al. Sedimentological, geomorphological and dynamic context of debris-mantled glaciers, Mount Everest (Sagarmatha) region, Nepal. Quat. Sci. Rev. 27, 2361–2389 (2008).

    Article  Google Scholar 

  36. Immerzeel, W. W. et al. Importance and vulnerability of the world’s water towers. Nature 577, 364–369 (2020).

    Article  Google Scholar 

  37. Kienholz, C. et al. Derivation and analysis of a complete modern-date glacier inventory for Alaska and northwest Canada. J. Glaciol. 61, 403–420 (2015).

    Article  Google Scholar 

  38. Mölg, N., Bolch, T., Rastner, P., Strozzi, T. & Paul, F. A consistent glacier inventory for Karakoram and Pamir derived from Landsat data: distribution of debris cover and mapping challenges. Earth Syst. Sci. Data 10, 1807–1827 (2018).

    Article  Google Scholar 

  39. Paul, F. et al. On the accuracy of glacier outlines derived from remote-sensing data. Ann. Glaciol. 54, 171–182 (2013).

    Article  Google Scholar 

  40. Citterio, M. & Ahlstrøm, A. P. The aerophotogrammetric map of Greenland ice masses. Cryosphere 7, 445–449 (2013).

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by Northumbria University, privately by the first author, and by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement no. 772751, RAVEN, Rapid mass losses of debris-covered glaciers in High Mountain Asia. S.H. thanks D. Quincey, M. Truffer, J. Brown and E. Miles for helpful comments and discussions.

Author information

Authors and Affiliations

Authors

Contributions

S.H. designed and conducted the study, interpreted the results, made the figures and wrote the manuscript. F.P. secured the institutional funding, helped interpret the results and contributed to the writing.

Corresponding author

Correspondence to Sam Herreid.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary handling editors: Stefan Lachowycz; Heike Langenberg

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Landsat satellite imagery used to map debris cover.

The footprint of each manually selected Landsat image is shown colored by the date of acquisition. The histogram inset shows the number of scenes per year differentiated by sensor and is broken down per region in the Supplementary Information.

Extended Data Fig. 2 Landsat image coverage with no overlap.

Landsat image footprints over Alaska and Western Canada are outlined and colored by acquisition data illustrating the preference given to more recent imagery and the removal of overlapping image area.

Extended Data Fig. 3 Amending the RGI v6.0.

Southern Andes as an example of the manual steps taken to identify and remove FP glacier error, area in shadow and cloud covered area; and identify and add FN errors in every RGI region. The wider shapes, or lassos, were used to tag enclave shapes initially mapped as debris cover with a specific error or true (by omission) classification. This lasso approach enables the manual work conducted in this study to be used again in future inventories with any desired modifications.

Extended Data Fig. 4 Estimation of the equilibrium line from mapped debris cover.

Map view and cross-section cartoon illustrating the method used in this study to estimate the position of the equilibrium line for glaciers with 7% debris cover and/or >10 km2 debris-covered area. Equilibrium line is estimated by locating the upper-most debris exposure, extending the point of exposure to the full glacier width and adjusting the position up-glacier by a factor of d. d is the glacier specific distance between the true equilibrium line and the first down-glacier emergence of englacial debris.

Extended Data Fig. 5 Cases where the equilibrium line location estimates are incorrect.

Landsat image of glaciers in Svalbard (a) and corresponding results from this study (b) showing examples of where equilibrium line estimates (yellow line) derived from mapped debris cover fails. Equilibrium lines shown on grey glaciers did not meet the 7% debris cover and/or >10 km2 debris-covered area criteria and were not included in any further metric derivation or results. Glaciers shown as blue met the criteria to be included in the study but also are shown to have errors. The source for error include (1) sparse debris cover producing nonsensical equilibrium lines; (2) imperfect flow divides drawn in ambiguous cases within RGI v6.0 causing unphysical equilibrium line estimates; (3) the unusual case where debris cover is present up-glacier but is not sufficiently present at lower reaches of the glacier to be detected by the debris mapping algorithm; (4) a portion of a glacier’s ablation zone is debris free and big enough to cause the glacier width buffer to inaccurately extend the ablation zone area to encompass the full width of the glacier. While this sample region was selected due to a concentration of errors, (5) shows a location where equilibrium line location was predicted as intended.

Extended Data Fig. 6 Comparison between the global debris map presented here and the global debris map from (ref. 18).

Error, true positive rate and precision are calculated under the assumption that results from this study are correct. The basis of this assumption is the additional manual editing that was conducted within this study, where (ref. 18) used unaltered RGI v6.0. Greenland was excluded from the comparison due to the different spatial domains considered. The values used to make this figure are given in the Supplementary Information.

Extended Data Fig. 7 Examples illustrating errors in the RGI and (ref. 18).

Two example locations are shown to illustrate a setting where heavy editing to the RGI was required (Central Asia) and almost no editing of the RGI was required (Alaska). The bottom two panels show the comparison of results from this study and those of (ref. 18). A clear undercounting of debris by (ref. 18) is apparent in both regions where in Alaska the methods of (ref. 18) are examined without influence from the RGI editing conducted in this study while the errors in Central Asia show a compound error in (ref. 18) composed of both an undercounting of true debris cover and an over counting where off-glacier area is erroneously classified as debris cover.

Extended Data Table 1 Global debris cover results and errors in RGI v6.0 presented as regional percentages.

All values are given for glaciers with a surface area greater than or equal to 1 km2 that fall within the considered spatial domain. ‘% RGI6.0 considered’ is unedited RGI v6.0 glacier area with i. glaciers smaller than 1 km2 removed and ii. area outside of the Landsat image composite (Extended Data Fig. 1) removed divided by entirely unaltered RGI v6.0 glacier area. ‘% SamRGI considered’ is the edited glacier area within the Landsat image composite divided by the edited glacier area inside and outside of the Landsat image composite.

Extended Data Table 2 Global debris cover results and errors in the RGI v6.0 presented as areas (km2).

Glacier area includes corrections to the RGI. These results exclude glaciers with a surface area less than 1 km2. Glacier area in shadow, including other visually uncertain shapes classified as debris, were removed from the debris map but not removed from the RGI.

Supplementary information

Supplementary Information

Supplementary Text, Figs. 1–6, Tables 1–4, description of Data 1–3, and references.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Herreid, S., Pellicciotti, F. The state of rock debris covering Earth’s glaciers. Nat. Geosci. 13, 621–627 (2020). https://doi.org/10.1038/s41561-020-0615-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41561-020-0615-0

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing