the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Jul 2025
Global mapping of lake-terminating glaciers
Abstract. Proglacial lakes at glacier termini have received widespread attention in the literature for their role in accelerating melt, velocity and contributing to cryospheric hazards. Although global and regional inventories for both glaciers and lakes exist, lake-terminating glaciers have not been consistently identified at the global scale. Based on the most recent global glacier inventory (RGI7), which so far only identifies some marine termini but none for lakes, we present a global inventory of lake-terminating glaciers, differentiating between three classes. The dataset corresponds to the year 2000 (± 1.5), matching to the timestamp of RGI7 outlines (2001, ± 6.2). We find that of 274,531 glaciers worldwide, 1.4 % terminate in lakes, varying between 0.5 and 6.7 % across 19 RGI regions. These glaciers account for 11.4 % of the total glacier area (0.2 to 41.8 % across regions). With multiple submitted flags available for 1260 individual glaciers, we find mapping conflicts to be low (6.7 %). The lake termini data set is available at https://doi.org/10.5281/zenodo.15524733 (Steiner et al., 2025) as well as at https://github.com/GLIMS-RGI/lake_terminating. This dataset is integrated into the forthcoming update to the RGI, v7.1.
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Status: open (until 29 Aug 2025)
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RC1: 'Review of "Global mapping of lake-terminating glaciers"', Penelope How, 25 Jul 2025
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Steiner et al. present a community-led effort to identify and categorise lake-terminating glaciers globally, which is compatible with the Randolph Glacier Inventory version 7.0 (RGI7) and intended for future integration. The dataset has been primarily generated manually through a concerted and coordinated effort from the authors. Initial categorisations have been formed from existing global and regional glacial lake inventories, drawing upon and uniting a large portion of the glacial lake mapping and monitoring efforts. Error is estimated based on comparing classifications from two operators, which reveals low mapping conflicts (6.7 %) that is indicative of a low uncertainty in the dataset.
The dataset itself is logical and clear to a large extent, as reflected in the dataset description manuscript. The dataset description paper is well written and a thorough companion to the dataset. My feedback is mainly on the dataset itself and the accompanying Github repository, with my primary focus being to ensure that the dataset is unambiguous to users in the glaciology/cryosphere research community and beyond. Github repository pull requests and issues corresponding to some of this feedback have been included here, and I have added my comments early in the review process so that a dialogue can continue on the Github repository if needed.
In all, I would recommend acceptance after these revisions. I am looking forward to seeing this dataset integrated with RGI7. Great work!
Dataset comments1. The naming of the lake-terminating glacier classifications
In the dataset and throughout the manuscript, the classifications to describe the relevance of lake presence are referred to as "lake level", "lake_level" and "lake level assessment". The term "lake level" is often used in reference to the water level of a lake, for example in remote sensing (e.g. Veh et al., 2025), modelling (e.g. Steffen et al., 2022), and in situ studies and monitoring efforts (e.g. Camassa et al., 2023).
I recommend that the naming convention is changed to something more suitable and less ambiguous. My suggestion would be "lake category" ("lake_catgy" in the gpkg field name), with Level 0-3 renamed to Category 0-3 (and capitalised throughout the manuscript).
2. Level 0 to Level 3 categories are not in sequential orderThe Level 0 to Level 3 relevance classifications are not in sequential order despite their numbering convention. Specifically, no lake contact (Level 0) is followed by > 50 % lake contact (Level 1), then < 50 % lake contact (Level 2), and then < 10 % and/or ambiguous lake contact (Level 3).
The classification levels should follow the magnitude of relevance sequentially, therefore my suggestion is:
- Category 0: no lake contact
- Category 1: < 10 % and/or ambiguous lake contact
- Category 2: < 50 % lake contact
- Category 3: > 50 % lake contact
Where "Level" is replaced by "Category" in accordance with the recommendation above. The dataset, processing scripts, manuscript, repository readme, and statistical analysis should also be updated accordingly.
3. Ambiguous relevance classificationsThe definitions of the relevance classifications (Level 0 to Level 3) differ between the ESSD manuscript and the Github repository readme, where the repo readme explicitly describes the relevance to glacier behaviour whereas the ESSD manuscript merely infers this. I would suggest amending the Github repository readme to align with the ESSD definitions, given that it is problematic to define an explicit connection between glacier-lake coverage and the certainty/amplitude of its impact on glacier behaviour. I have made a PR with these proposed changes: https://github.com/GLIMS-RGI/lake_terminating/pull/12.
Additionally, there appears to be ambiguity surrounding the criteria for each relevance classification. At various points in the manuscript, the relevance classification signifies:
i) The portion of terminus in contact with lake (e.g. Line 70-72).
ii) The perceived level of influence on the adjacent glacier based on visual indicators (e.g. Line 77-78)
iii) The operator certainty of the classification/ice contact (e.g. Line 76-77, 113-115)
Therefore, the relevance classification is ambiguous as it indicates more than one criteria. In future iterations of this dataset, I propose that criteria i) and ii) should be separated from iii), with a new field denoting the operator certainty. In addition, the criteria for the relevance classification should be revised and clarified in the manuscript (Line 63-84).
4. Dataset directory naming/structuring conventionsIt is difficult to locate the dataset itself in the Github/Zenodo repository alongside the data handling scripts and documentation. I propose renaming the directory from "tables" to "dataset" in order to make this clearer, and ensuring that only the finalised dataset is in the top level of the "dataset" directory (i.e. moving all un-collated operator definitions to a sub-directory). I have opened a pull request to the Github repository (https://github.com/GLIMS-RGI/lake_terminating/pull/11) with these proposed changes.
5. The Greenland periphery glacier outlines .gpkg file is missing from datasethttps://github.com/GLIMS-RGI/lake_terminating/issues/10
Line-by-line paper comments
I don't have many line-by-line comments, largely because the language and communication of the findings presented in the manuscript are to an excellent standard. Therefore, my line-by-line comments are largely remarks, questions and figure/table queries.
Line 19-20: I am unsure about the general statement that calving "remains poorly constrained with scattered observations", especially given that two of the three references to support this are over 15 years old. Can the statement be amended to better reflect the advances in calving modelling and integration into system models over recent years.
Line 28-31: I did not realise that these two global inventories differed so greatly, therefore it is good to see this reported here. Do you know why the difference is so vast? Is this a reflection of the difference in classification approaches and/or discrepancies in manual intervention?
Line 49: Great to see the processing script openly provided for this.
Line 58: Was there any specific reason for choosing a lake size threshold of 0.01 sq km? Was this problematic in cases where an existing inventory only contained lakes with a higher minimum size threshold (e.g. Greenland, with a minimum size of 0.05 sq km)?
Line 79: Repetition of "these".
Table 2: I would like to see the entry type (i.e. string, integer, float) for each of these fields, mainly to guide users who are importing these using R or Python. Also, a short description for each field should be added, similar to those described in Lines 124-128.
Line 123-127: The AutoTerm field is not defined here, in Table 2, or in the Github repository. I am guessing this is a categorisation of the level to which an external glacial lake inventory dataset was used?
Line 149: "...(Table 3,Figure 5 and 6)." >> "...(Table 3, Figure 5 and 6)."
Table 3: I think the region name should be included here, if possible, rather than having to refer to Table 1.
Line 194-216: An additional table would neatly summarise and compliment these findings (i.e. "Table 4. Statistics from independent flag submissions of glacier classifications")
Line 218-220: Are these discussions openly available, for instance through issue postings on the Github repository? I think this could be a great approach to open, transparent discussion and resolutions in future iterations of this dataset. If you would like to use the repository as a user contribution portal then I would recommend: 1) adding a section to the readme on how to contribute; 2) adding an issue template to guide users in writing their contributions; and 3) adding a repo action to check the compatibility of user contributions (e.g. ensuring the submission is a .csv with all essential fields included).
Line 228: The .gpkg information should be included when describing the format and contents of the .csv tables (Line 123-127), rather than at the end of the manuscript. In addition, the geographic projection (OGC:CRS84) and field descriptions (i.e. fid, IDs, aut_trm, lak_lvl, image_d, imag_dt, invntr_, cntrbtr, notes) of the gpkg files should also be included. Perhaps the field description names in the .gpkg files could be incorporated into Table 2.
Line 254-256: Normally ESSD publications require a section, or some comment, and how this dataset could be used in future work. I think a couple of comments could easily be added to the Conclusions here, tying back to the relevant literature highlighted in the introduction.
ReferencesCamassa, R. et al. (2023) Extreme seasonal water-level changes and hydraulic modeling of deep, high-altitude, glacial-carved, Himalayan lakes. Sci Rep 13, 11705. https://doi.org/10.1038/s41598-023-37667-z
Steffen, T. et al. (2022) Volume, evolution, and sedimentation of future glacier lakes in Switzerland over the 21st century, Earth Surf. Dynam., 10, 723–741, https://doi.org/10.5194/esurf-10-723-2022
Veh, G. et al. (2025) Progressively smaller glacier lake outburst floods despite worldwide growth in lake area. Nat Water 3, 271–283. https://doi.org/10.1038/s44221-025-00388-w
Citation: https://doi.org/10.5194/essd-2025-315-RC1
Data sets
GLIMS-RGI Lake-terminating glaciers: v1.1-subm Jakob Steiner, William Armstrong, Will Kochtitzky, Robert McNabb, Rodrigo Aguayo, Tobias Bolch, Fabien Maussion, Vibhor Agarwal, Iestyn Barr, Mike Cloutier, Katelyn DeWater, Frank Donachie, Yoann Drocourt, Siddhi Garg, Gunjan Joshi, Byron Guzman, Stanislav Kutuzov, Thomas Loriaux, Caleb Mathias, Brian Menounos, Evan Miles, Aleksandra Osika, Kaleigh Potter, Adina Racoviteanu, Brianna Rick, Miles Sterner, Guy Tallentire, Levan Tielidze, Rebecca, White, Kunpeng Wu, and Whyjay Zheng https://doi.org/10.5281/zenodo.15524733
Model code and software
A database of lake-terminating categories for the RGI Jakob Steiner, William Armstrong, Will Kochtitzky, Robert McNabb, Rodrigo Aguayo, Tobias Bolch, and Fabien Maussion https://github.com/GLIMS-RGI/lake_terminating
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