the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Jul 2024
Glacier-level and gridded mass change in the rivers' sources in the eastern Tibetan Plateau (ETPR) from 1970s to 2000
Abstract. The highly glacierized eastern part of the Tibetan Plateau is the key source region for seven major rivers: Yangtze, Yellow, Lancang-Mekong, Nu-Salween, Irrawaddy, Ganges, and Brahmaputra rivers. These rivers are vital freshwater resources for more than one billion people downstream for their daily life, irrigation, industrial use, and hydropower. However, the glaciers have been receding during the last decades and are projected to further decline which will profoundly impact the water availability of these larger river systems. Although few studies have investigated glacier mass changes in these river basins since the 1970s, they are site and temporal specific and limited by data availability. Hence, knowledge of glacier mass changes is especially lacking for years prior to 2000. We therefore applied digital elevation models (DEMs) derived from large scale topographic maps based on aerial photogrammetry from the 1970s and 1980s and compared them to the Shuttle Radar Topography Mission (SRTM) DEM to provide a complete picture of mass change of glaciers in the region. The mass changes are presented on individual glacier bases with a resolution of 30 m and are also aggregated into gridded formats at resolutions of 0.1° and 0.5°. Our database consists of 13117 glaciers with a total area of ~21695 km2. The annual mean mass loss of glaciers is -0.30 ± 0.12 m w.e. in the whole region. This is larger than the previous site-specific findings, the surface thinning increases on average from west to east along the Himalayas-Hengduan mountains with the largest thinning in the Irrawaddy basin. Comparisons between the topographic map-based DEMs and DEMs generated based on Hexagon KH-9 metric camera data for parts in the Himalayas demonstrate that our dataset provides a robust estimation of glacier mass changes. However, the uncertainty is high in high altitudes due to the saturation of aerial photos over low contrast areas like snow surface on a steep terrain. The dataset is well suited for supporting more detailed climatical and hydrological analyses and is available at https://doi.org/10.11888/Cryos.tpdc.301236 (Liu et al., 2024).
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RC1: 'Comment on essd-2024-255', Romain Hugonnet, 18 Sep 2024
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Review of Zhu et al., “Glacier-level and gridded mass change in the source rivers in the eastern Tibetan Plateau (ETPR) from 1970s to 2000” in discussion in ESSD, August 2024
by Romain Hugonnet, University of Washington
General
I reviewed a previous ESSD submission of this study (https://essd.copernicus.org/preprints/essd-2022-473/).
This manuscript by Zhu et al. presents a glacier elevation change and mass change estimate for the eastern Tibetan Plateau. This dataset is based on historical topographic maps and spy satellite imagery from the 70s, compared to the Shuttle Radar Topography Mission of February 2000. There are little glacier mass change estimates before the 2000, and hence the main added value of this study is to extend the observational period of glacier mass change back to the 70s.
Overall, this is an interesting study that has greatly improved since the past submission that I reviewed. I still have a couple of main comments, less crucial than the ones of my previous review yet still important, as well as a couple of other minor remarks described below.
Improvement since last submission
The authors have satisfactorily addressed most of the main concerns from my previous review:
- They introduce an additional penetration correction for the X-band instead of neglecting it (based on Zhou et al., 2018),
- They have revisited their uncertainty analysis to account for the long-range correlation of errors that are common in both KH-9 DEMs and SRTM DEMs (based on Hugonnet et al., 2022), and thus crucial to propagate errors to glacier mass changes,
- They have removed their elevation-dependent correction due to the biases it can create for glacier mass balance estimation (based on Gardelle et al., 2012),
- Additionally, the authors seem to have revised several statements and references that were either convoluted or not relevant.
Main comments
1/ Report confidence level
This was a remark in my past review. Maybe I have missed it, but I couldn’t find the confidence level in the text. The authors should specify if their reported uncertainties throughout the paper refer to +/- 1 sigma (68% confidence level) or +/- 2 sigma (95% confidence level).
2/ Grid-level aggregation
It is my understanding that regional hypsometric interpolation was performed in this study (line 197; missing reference to McNabb et al., 2019), yet it is directly followed by the statement “In our data products, we have preserved the elevation changes without applying interpolation”. I’m not sure I understand: Does the above statement only refer to elevation change maps? Surely this interpolation is used for glacier mass change estimates, otherwise it would be useless. Please clarify. This clarification also joins the topic of grid-level aggregation: In this section, glaciers are discarded based on their ratio of valid data in ablation or accumulation zones. Does this only concern the non-interpolated elevation changes?
Additionally, the most crucial point for grid-aggregation is that it seems that the authors clipped elevation change maps by their desired tile size (0.1°x0.1° or 0.5°x0.5°), then reproduced the same computations done at the glacier level.
The assumptions of mass conversion and its uncertainty (Huss, 2013) only apply for glacier-wide estimates (as flux divergence is compensated at the glacier scale). Splitting the glaciers in pieces during the tiling invalidates that assumption. Depending on the size of glaciers in the eastern Tibetan plateau, authors should justify that the tiling is large enough to compensate for this effect (tile size much larger than individual glaciers in the region). I’m expecting that 0.5°x0.5° should not be a problem. However 0.1°x0.1° might be at the very limit, and either require to add uncertainty during the density conversion or to be dropped entirely.
3/ Unclear error propagation for regional scale
In the abstract and in line 348: “The average elevation difference for the period from 1970s to 2000 was -9.52 ± 4.16 m, corresponding to a mass balance of -0.30 ± 0.12 m w.e. yr-1”.
This is unclear: Is this an estimate for the regional-scale glacier mass change with error propagation, or a per-glacier mean value (so area-weighted with this unit) for both the mean estimate and the uncertainty estimate?
While the mean of these two variables is the same (area-weighted), their uncertainty represent two very different things: that of the total regional mass loss, or that of a single-glacier mass loss on average. If the authors' estimates are intended to represent total regional mass loss, they will need to add additional error propagation steps from the glacier scale to the regional scale, based on correlated errors in density conversion, glacier areas and elevation change. Typically, density conversion errors are assumed 100% correlated, while area not necessarily, and the authors have already estimated the long-range correlations in elevation change errors.
4/ Polishing the text
The text would benefit from more streamlining (typos, some unfinished or convoluted statements), and in certain cases some additional English proof-reading.
For instance:
- 78: “The elevation difference derived from the comparison”: “Elevation differences derived from…”,
- 106: “5 to8 m”: typo space missing,
- 185-187: Gardelle et al. (2013) is the wrong reference for this correction, should be Gardelle et al. (2012),
- 320: “Statistical uncertainties”: no need for “statistical” before “uncertainties” across the entire section,
- 511: “sources”: missing something here… “different”?
These are only examples I took note of here and there, I leave the detailed polishing to the authors.
Minor comments:
24: “However, the glaciers have been receding during the last decades and are projected to further decline which will profoundly impact the water availability of these larger river systems.” This is an over-statement, glacier have moderate impact of water availability, which is only relevant in times of drought. See Gascoin (2013). Should also adjust for this in the introduction.
Fig. 7/8: These figures related to the analysis of section 2.5.1 look like they were generated with the Python package xDEM, which should then be cited either in the Methods or Code availability, or both.
On that topic: It would be great for the authors to share their code through an open repository in a “Code availability” section, for reproducibility of their dataset, and for other researchers to build on their efforts! (which seems especially important for an ESSD publication)
Additional references (not listed in the study)
Gascoin, S. (2023). A call for an accurate presentation of glaciers as water resources. WIREs. Water. https://doi.org/10.1002/wat2.1705
Gardelle, J., Berthier, E., & Arnaud, Y. (2012). Impact of resolution and radar penetration on glacier elevation changes computed from DEM differencing. Journal of Glaciology, 58(208), 419–422.
Citation: https://doi.org/10.5194/essd-2024-255-RC1 -
RC2: 'Comment on essd-2024-255', Niccolò Dematteis, 15 Nov 2024
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Dear authors,
please consider the following comments and adjust your manuscript accordingly.
i) Table 1 basic information -> try using something less generic than "basic", like general information
ii) Table 1 RGI7.0 has been released few years ago . You could use this data to calculate the glacial extent e or at least specify the year of reference of RGI6.0
iii) Figure 2 You should add some details to the caption. For instance, what are the coloured box? Plus, you should use the common convention of flowchart. E.g., a diamond represents a decision, while rectangles are processes. You can refer to the Wikipedia web page https://en.wikipedia.org/wiki/Flowchart or other sources to see what shapes represent what.
iv) Figured 3 and 5 you should specify the source of the basemap. If the figures have been created with specific libraries, you should specify this as well.
v) Suppl Table 1 Add details to the caption
vi) Suppl Figure 2 A legend is missing (what are the different colours?). Add a background image or country boundaries, because it is very hard to understand the geographical setting.Dataset
Please add the references to the citations in the readme file and convert it in pdfCitation: https://doi.org/10.5194/essd-2024-255-RC2 -
EC1: 'Comment on essd-2024-255', Niccolò Dematteis, 19 Nov 2024
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Dear authors,
unfortunately, of 15 scientists that I invited to review your manuscript, only one has accepted. Therefore, since four months have passed since your submission, I decided to make a review by myself, which you can see in the posted comments. This decision also came out because I believe that your work is already mature enough to proceed in the review process. I want to be clear: your manuscript has not yet been accepted, but it is in a good way. You must positively answer the questions raised by reviewer 1 and mine.
All the best,
Niccolò Dematteis
Citation: https://doi.org/10.5194/essd-2024-255-EC1 -
AC1: 'Reply on EC1', yu zhu, 21 Nov 2024
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We would like to express our sincere gratitude for your efforts in processing our manuscript. We understand that reviewers have busy schedules, and many experts do not have sufficient time to review manuscripts. We also invited some scholars from Europe and India to provide community comments on our paper in past few months, but they did not have enough time to do so. Therefore, we are very grateful for your review. Your insightful comments and suggestions have been very helpful to us. We will address all the points raised by you and Dr. Hugonnet (Reviewer #1) in the revised version as soon as possible.
Citation: https://doi.org/10.5194/essd-2024-255-AC1
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AC1: 'Reply on EC1', yu zhu, 21 Nov 2024
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Data sets
Glacier-level and gridded mass change in the rivers' sources in the eastern Tibetan Plateau (1970s-2000) (Version 3) S. Liu et al. https://doi.org/10.11888/Cryos.tpdc.301236
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