Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-969-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Special issue:
A mathematical model to improve water storage of glacial lake prediction towards addressing glacial lake outburst floods
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- Final revised paper (published on 24 Feb 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 21 Feb 2024)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on hess-2024-24', Adam Emmer, 25 Mar 2024
- AC5: 'Reply on RC1', Miaomiao Qi, 22 Sep 2024
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CC1: 'Comment on hess-2024-24', Huayu Zhang, 12 Aug 2024
- AC2: 'Reply on CC1', Miaomiao Qi, 22 Sep 2024
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CC2: 'Comment on hess-2024-24', Huayu Zhang, 12 Aug 2024
- AC3: 'Reply on CC2', Miaomiao Qi, 22 Sep 2024
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RC2: 'Comment on hess-2024-24', Anonymous Referee #2, 18 Aug 2024
- AC1: 'Reply on RC2', Miaomiao Qi, 18 Sep 2024
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RC3: 'Comment on hess-2024-24', Anonymous Referee #3, 18 Aug 2024
- AC4: 'Reply on RC3', Miaomiao Qi, 22 Sep 2024
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Publish subject to revisions (further review by editor and referees) (07 Oct 2024) by Laura Brown
AR by Miaomiao Qi on behalf of the Authors (07 Oct 2024)
Author's response
Author's tracked changes
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ED: Referee Nomination & Report Request started (25 Oct 2024) by Laura Brown
RR by Adam Emmer (31 Oct 2024)
RR by Anonymous Referee #3 (01 Dec 2024)
ED: Publish subject to minor revisions (review by editor) (03 Dec 2024) by Laura Brown
AR by Miaomiao Qi on behalf of the Authors (05 Dec 2024)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (15 Dec 2024) by Laura Brown
ED: Publish as is (06 Jan 2025) by Thom Bogaard (Executive editor)
AR by Miaomiao Qi on behalf of the Authors (07 Jan 2025)
Manuscript
This study approximates glacial lake volume from simplified geometric representations of 4 main sub-types of moraine-dammed lakes, considering glacier-lake relationship (connected vs. unconnected) and lake width to length ratio. The performance of this new approach is reportedly better than the performance of other methods (comparison in Table 5).
However, this is not surprising if the authors used the dataset of 44 Himalayan lakes with measured bathymetries to determine their parameters (section 3.3), and then use the same data to compare the performance of various methods (section 4.2). I hope I understood this correctly since the validation procedure is not described clearly in methods section. If I get it correctly, such performance evaluation is weak. A proper validation would require two independent datasets (training and testing).
And the whole validation procedure is even more confusing since only 4 bathymetries are mentioned as input data for model validation in section 4.1. This is statistically not convincing, considering 4 sub-types of moraine-dammed lakes and number of parameters that are used. Further, a subset of 12 lakes is used in section 5.1 while 4 and 10 lakes are mentioned in Conclusions. This needs to be clarified.
The application section 4.3 is not linked to the methodology. It is not clear what was done and whether (and how?) all 13,166 lakes mapped by Wang et al. (2020) were classified according to the classification scheme used in this study and whether all these are moraine-dammed lakes?
At the end, the importance of this improvement in lake volume estimation for GLOF studies (the main justification throughout the study) is unclear unless other (and much larger) sources of uncertainties in GLOF studies (e,g, coming up with realistic scenarios of GLOF triggers and GLOF mechanism, plausible breach development and dimensions, associated shape of the outburst hydrograph curve, % of lake volume release, etc.) are addressed.
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L39-40: this definition is artificial; moraine-dammed lakes not only trap meltwater (how about water from liquid precipitation?); debris at or near the termini of glacier doesn’t necessarily need to be a moraine
L53: ice- or landslide-dammed lakes may be unstable too
L72-74: the peak discharge is rather linked to the magnitude of triggering event than lake volume
L77: how much was that?
L126-127: this indication is not clear since the ratio is dimensionless (really a width of 1 m?)
Fig. 2: please only display parameters that are further use (remove slope beta, points f and g)
Table 2: please clarify whether alpha is mean or median slope (as mentioned in Table 3); what is the influence of DEM acquisition date on alpha estimation?
Table 4: what is simulated lake depth – a mean? And what do the two values in error column refer to?
Table 5: some of the lakes (e.g. Imja Tsho or Jialong Co) are represented more than once. This may influence performance evaluation; the areas of Jialong Co do not match between Table 4 and 5)
L313-315: R^2 will always be very high (>0.95) for most of the methods
Figure 8: I don’t understand what is the meaning of these box plots unless it is connected to measured data? The XY graph type (inset) is way more meaningful and the authors may consider showing a panel with performance of all methods in XY graphs.
L339: the scaling up of the lake volume estimation procedure to the whole HMA is not properly described in methods.
L367-376: this seems bit out of the context. Clearly, large lakes are frequently considered risky since lake area / volume is commonly used as GLOF susceptibility criteria.
L375: the annual expansion rate +5.6% a^-1 over 32 years does not correspond to a reported growth of 178% over this period
L395: they are not flat (as documented in your Fig. 10)
L433: what is MDLVL?
L453: the term “outburst water storage” is not appropriate. What is estimated here is a lake volume / lake water storage. It doesn’t have much to do with outburst / outburst volume.
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To sum up, this study can help to improve moraine-dammed lake volume estimates in HMA. However, especially the validation process needs to be clarified and treated in statistically convincing way. I recommend major revisions.