Rising Lake Levels Across High Mountain Asia

Hassan, Javed; Nielsen, Karina; Colgan, William; Kayastha, Rijan Bhakta; Khadka, Mira; Khan, Shfaqat Abbas

doi:10.5194/egusphere-2026-808

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https://doi.org/10.5194/egusphere-2026-808

Preprints

02 Apr 2026

| 02 Apr 2026

Rising Lake Levels Across High Mountain Asia

Javed Hassan, Karina Nielsen, William Colgan, Rijan Bhakta Kayastha, Mira Khadka, and Shfaqat Abbas Khan

Abstract. High-altitude lakes across High Mountain Asia (HMA) are one of the critical freshwater reservoirs and sensitive indicators of climate change due to their remote locations and limited human disturbances. This study presents continuous water level estimates for 232 lakes across HMA from 2010 to 2024 using CryoSat-2 and ICESat-2 data. We analyzed temporal and spatial variations and inter-mission consistency in the lake water level across HMA. Our results reveal an overall increasing trend (median rate: +0.1 ± 0.01 m yr⁻¹), with 77 % of lakes experiencing rising levels and 91 % exhibiting statistically significant trends. We find a substantial regional heterogeneity with the Tibetan Plateau contributing dominantly to regional increase (0.07 ± 0.001 m yr⁻¹), while Himalayan lakes show persistent decline (0.04 ± 0.001 m yr⁻¹). Water level times series observed with the satellite altimetry missions CryoSat-2 and ICESat-2 intercomparison demonstrates strong consistency (80 % sign agreement, p = 0.013). Lake catchment scale analysis identifies precipitation as the dominant deriver of lakes water level variability (r = 0.42, p < 0.001), whereas lakes in glaciated catchments exhibit weak climate correlations despite significant increases in temperature, indicating nonlinear cryosphere buffering. We find systematic relationships between lake characteristics (area, elevation) and increasing water levels, with larger lakes generally showing more rapid growth. The contrasting hydrological responses with continued rising water levels in cryosphere influenced lakes and accelerating declines in precipitation sensitive lakes in Himalaya highlight divergent lake hydrological regimes. These findings underscore the critical importance of regional differentiation in understanding lake water storage changes and informing climate adaptation strategies for population vulnerable to these changes in the regions.

Received: 10 Feb 2026 – Discussion started: 02 Apr 2026

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Javed Hassan, Karina Nielsen, William Colgan, Rijan Bhakta Kayastha, Mira Khadka, and Shfaqat Abbas Khan

Status: final response (author comments only)

RC1:
'Comment on egusphere-2026-808', Anonymous Referee #1, 25 May 2026
Reviewer comments on manuscript EGUsphere-2026-808 “Rising Lake Levels Across High Mountain Asia” by Hassan et al.
General comments:
This manuscript analyzes lake-level changes across 232 lakes in High Mountain Asia from 2010 to 2024 using CryoSat-2 and ICESat-2 data. The results show heterogeneous lake-level changes across HMA, with overall increases in the Tibetan Plateau lakes and declining tendencies in the Himalaya. The authors further examine correlations between lake-level changes and ERA5-Land precipitation, temperature, and evaporation to interpret possible hydroclimatic controls. While the dataset and regional synthesis are useful, the manuscript’s current scientific contribution is somewhat limited by a largely descriptive analytical framework. The conclusions regarding climatic drivers, cryospheric buffering, and regional mechanisms are not fully supported by the current analyses. The study would benefit from more robust attribution framework, and a more explicit statement of its novelty relative to previous HMA lake-level studies.
Specific comments:
About innovation. The broader finding on the rising lake-level in the central Tibetan Plateau and declining tendency in the southern Tibetan Plateau/Himalayan region is already well established in the literature. The authors state that the majority of previous studies are confined to the Tibetan Plateau. While, existing studies have either extended the analysis to high-elevation lakes above 2500 m a.s.l. (e.g., Zhang et al., 2020) or to glacial lakes across the entire HMA (e.g., Wang et al., 2025). It is useful that the manuscript extends the lake-level record to 2010–2024, however a 15-year period does not necessarily provide a clear advantage for assessing long-term trends. The manuscript should more explicitly state the knowledge gap, not only in terms of “more lakes and longer time series,” but new process understanding. For example, does the study reveal post-2018 acceleration or deceleration in lake-level changes? Or does it identify regional differences that were not captured by previous TP- or HMA-wide studies?

Wang Y, Zheng D, Zhang G, Carrivick JL, Bolch T, et al. (2025). Patterns and change rates of glacial lake water levels across High Mountain Asia. National Science Review, 12(3): nwaf041.
Zhang, G., Yao, T., Xie, H., Yang, K., Zhu, et al. (2020). Response of Tibetan Plateau lakes to climate change - Trends, patterns, and mechanisms. Earth Science Reviews, 208
About mechanistic interpretation. The manuscript relates lake-level trends to ERA5-Land temperature, precipitation, and evaporation trends. This provides a reasonable first-order analysis, but the Discussion often moves from correlation to mechanistic interpretation. For example, the authors suggest that lake expansion on the Tibetan Plateau is mainly associated with increased precipitation, that glacierized catchments reflect cryospheric buffering, and that declining Himalayan lakes indicate precipitation sensitivity and reduced meltwater buffering. These interpretations are plausible, but correlation analyses alone are not sufficient to infer dominant mechanisms. Lake-level change integrates catchment runoff, direct precipitation over the lake, evaporation, groundwater exchange, glacier and snow melt, and possible outlet dynamics. The authors should therefore either moderate the mechanistic language or strengthen the analysis, for example by introducing a simple lake water-balance framework to guide interpretation.

About uncertainty. The climate-driver analysis is based on ERA5-Land temperature, precipitation, and evaporation. Reanalysis data especially precipitation are highly uncertain in high-mountain regions, and this uncertainty directly affects the interpretation of correlations between climate variables and lake-level changes. The authors should discuss this limitation more explicitly. If possible, comparison with another precipitation product would strengthen the analysis.

About Discussion. The discussion of glacier melt and permafrost contribution mainly relies on previous studies. Some statements on glacier-melt buffering and permafrost-related contributions cannot be directed supported by the lake-level and climate-correlation analyses. The manuscript should make clearer which process interpretations are directly supported by this study and which are inferred from prior literature.

About regional classification. The manuscript groups lakes into Tibetan Plateau, Himalaya, western HMA, and glacierized catchments, however, the criteria are not described explicitly. In particular, “glacierized catchments” overlap spatially with the other regions. It is not clear whether these are treated as an independent category or a cross-cutting classification.

Given the above, I would recommend a major revision.
Citation: https://doi.org/10.5194/egusphere-2026-808-RC1
- AC1:
  'Reply on RC1', Javed Hassan, 01 Aug 2026
  Response to reviewers Reviewer: 1 (RC1)
  General Comments:
  This manuscript analyzes lake-level changes across 232 lakes in High Mountain Asia from 2010 to 2024 using CryoSat-2 and ICESat-2 data. The results show heterogeneous lake-level changes across HMA, with overall increases in the Tibetan Plateau lakes and declining tendencies in the Himalaya. The authors further examine correlations between lake-level changes and ERA5-Land precipitation, temperature, and evaporation to interpret possible hydroclimatic controls. While the dataset and regional synthesis are useful, the manuscript’s current scientific contribution is somewhat limited by a largely descriptive analytical framework. The conclusions regarding climatic drivers, cryospheric buffering, and regional mechanisms are not fully supported by the current analyses. The study would benefit from more robust attribution framework, and a more explicit statement of its novelty relative to previous HMA lake-level studies.
  Author’s response: We thank the reviewer for taking your time to review our manuscript and for providing thoughtful and constructive comments. Your comments have been very helpful in strengthening and improving our study. We agree that the initial version did not sufficiently distinguish the contribution of the present study from previous regional assessments and mechanistic interpretations of the relationships between lake water level changes and climate variables. We substantially revised the manuscript by clarifying the scientific contribution of our study, moderating the interpretation of climate-lake water level relationships, expanding the discussion of uncertainties associated with the climate data and altimetry analysis, and distinguishing more clearly between the findings of the present study and interpretations based on previous literature. We also revised the Abstract, Introduction, Methods, Results, Discussion, and Conclusions to improve the clarity, scientific rigor, and presentation of the manuscript. The detailed responses to each comment are provided below.
  Specific Comments:
  About innovation. The broader finding on the rising lake-level in the central Tibetan Plateau and declining tendency in the southern Tibetan Plateau/Himalayan region is already well established in the literature. The authors state that the majority of previous studies are confined to the Tibetan Plateau. While existing studies have either extended the analysis to high-elevation lakes above 2500 m a.s.l. (e.g., Zhang et al., 2020) or to glacial lakes across the entire HMA (e.g., Wang et al., 2025). It is useful that the manuscript extends the lake-level record to 2010–2024, however a 15-year period does not necessarily provide a clear advantage for assessing long-term trends. The manuscript should more explicitly state the knowledge gap, not only in terms of “more lakes and longer time series,” but new process understanding. For example, does the study reveal post-2018 acceleration or deceleration in lake-level changes? Or does it identify regional differences that were not captured by previous TP- or HMA-wide studies?
  
  Wang Y, Zheng D, Zhang G, Carrivick JL, Bolch T, et al. (2025). Patterns and change rates of glacial lake water levels across High Mountain Asia. National Science Review, 12(3): nwaf041.
  Zhang, G., Yao, T., Xie, H., Yang, K., Zhu, et al. (2020). Response of Tibetan Plateau lakes to climate change - Trends, patterns, and mechanisms. Earth Science Reviews, 208
  Author’s response: We agree that the general pattern of rising lake levels across much of the central and northern Tibetan Plateau and declining lake-level trends in parts of the southern Tibetan Plateau and Himalaya has been documented in previous studies. And extending the observational record to 2024 by themselves, does not constitute sufficient scientific advances. We have revised the manuscript to clarify the main contribution of this study with more detailed characterization of the spatial/temporal heterogeneity and persistence in lake water level changes underlying the broad regional patterns of lake level change across High Mountain Asia (HMA) within a common observational and analytical framework.
  We provide a spatially consistent assessment of lake-level variability for 232 large lakes across three geographic subregions of HMA using CryoSat-2 observations from 2010–2023 and ICESat-2 observations from 2018–2024. The extended observational record enables us to examine the temporal evolution of lake-level trends by comparing pre-2018 (2010–2017) and post-2018 (2018–2023) periods. These analysis reveals that the broad regional patterns comprise both persistent trends and substantial temporal shifts: 117 lakes (50.4%) maintained increasing trends in both periods, 38 lakes (16.4%) maintained declining trends, while 77 lakes (33.2%) changed the direction of their trends, including 52 lakes (22.4%) transitioning from declining to increasing levels and 25 lakes (10.8%) transitioning from increasing to declining. The median lake-level trend increased from +0.034 m/yr before 2018 to +0.095 m/yr after 2018, although this temporal evolution differed substantially among regions. The Tibetan Plateau showed a shift toward more positive trends, whereas western HMA shifted toward weaker or more negative trends, while Himalayan lakes retained negative median trends in both periods. We analysed statistical association of catchment-scale climate variations to examine whether these distinct lake level trajectories are with different climate variables, while avoiding attribution of individual water-balance contributions beyond what can be supported by the analysis. Together, these results demonstrate that the well-established regional patterns of lake level change across HMA mask substantial temporal evolution and spatially variability. By resolving changes in the persistence, acceleration, and reversal of lake-level trends within a consistent observational framework, the present study complements previous Tibetan Plateau-wide and HMA-wide assessments and provides new insight into the recent evolution of lake water level changes. We expanded the discussion to place our findings in the context of recent studies, including findings from Zhang et al. (2020) and (Wang et al., 2025) in the revised manuscript.
  About mechanistic interpretation. The manuscript relates lake-level trends to ERA5-Land temperature, precipitation, and evaporation trends. This provides a reasonable first-order analysis, but the Discussion often moves from correlation to mechanistic interpretation. For example, the authors suggest that lake expansion on the Tibetan Plateau is mainly associated with increased precipitation, that glacierized catchments reflect cryospheric buffering, and that declining Himalayan lakes indicate precipitation sensitivity and reduced meltwater buffering. These interpretations are plausible, but correlation analyses alone are not sufficient to infer dominant mechanisms. Lake -level change integrates catchment runoff, direct precipitation over the lake, evaporation, groundwater exchange, glacier and snow melt, and possible outlet dynamics. The authors should therefore either moderate the mechanistic language or strengthen the analysis, for example by introducing a simple lake water-balance framework to guide interpretation.
  
  Author’s response: We agree that correlations between lake level trends and ERA5-Land climate variables cannot by themselves establish the dominant mechanisms controlling lake level changes. As lake water level variability reflects the integrated effects of contributing hydrological components of catchment water balance. We revised the manuscript to clearly distinguish between statistical associations supported by our results and process-based attributions based on previous studies. We revised the discussion on positive/negative relationship between lake level trends and climate variables presented as a statistical association with the importance of variability, rather than as a direct estimate of contribution to lake level change.
  Our catchment-scale analysis shows precipitation variability as the climate variable most consistently associated with de-seasoned lake trends, with a significant positive correlation (r = 0.42, p < 0.001) except for lakes within glacierised catchments such as endorheic basins in Tibetan Plateau (Jiang et al., 2020; Zhang et al., 2017a; Zhang et al., 2017b). Although this statistical relationship does not by itself quantify the relative contributions of precipitation to lake level change. When compared with individual lake water level time series derived from satellite altimetry and in situ measurements, our estimates show strong agreement with previous studies (Lei et al., 2022; Zhang et al., 2019; Zhang et al., 2017b). The recent modest deceleration in growth rates observed in the ICESat-2 record (2018-2024) coincides with the decline in precipitation in our ERA5-Land analysis post-2021, suggesting the interannual precipitation variability as potential contributor to recent changes in lake level trajectories (Fig. S2). Lake expansion on Tibetan Plateau in recent decades have been attributed to precipitation, evaporation (Biskop et al., 2016; Yang et al., 2017), Snow and ice melt (Zhang et al., 2017b) ground Water (Lei et al., 2022). The increasing precipitation trend observed at meteorological station on Tibetan Plateau during 1978 to 2013, except in parts of the southeast (Zhang et al., 2017a), is broadly consistent with the spatial pattern of lake water level changes (Fig. 2).
  We similarly revised the discussion of Himalayan lakes to avoid attributing declining lake levels to precipitation deficits based on the correlation analysis. For lakes in glacierised catchments, we revised the weak correlations with contemporaneous ERA5-Land temperature, precipitation, and evaporation variables indicate that lake level variability cannot be directly explained by these variables alone and may involve delayed or nonlinear hydrological responses. The potential role of snow and glacier melt is discussed as a plausible interpretation supported by previous process-based studies, rather than as a mechanism demonstrated by results of our study. We also revised the limitations to clarify the correlations between lake level trends and individual climate variables should be interpreted as statistical associations. We hope these revisions provide an appropriate interpretation of the lake water level variations and climate variables while retaining its value as a first-order assessment.
  About uncertainty. The climate-driver analysis is based on ERA5-Land temperature, precipitation, and evaporation. Reanalysis data, especially precipitation, is highly uncertain in high-mountain regions, and this uncertainty directly affects the interpretation of correlations between climate variables and lake-level changes. The authors should discuss this limitation more explicitly. If possible, comparison with another precipitation product would strengthen the analysis.
  
  Author’s response: We agree that, although ERA5-Land provides consistent spatial and temporal coverage across HMA, its performance in high-elevation regions with complex topography is subject to uncertainties due to coarse spatial resolution, sparse ground observations, and systematic biases in the representation of precipitation. We have therefore expanded the discussion of ERA5-Land uncertainties and their implications for interpreting the climate variables and lake water level relationships. Previous evaluations indicate that ERA5-Land generally reproduces the broad spatial and temporal patterns of precipitation and temperature over the Tibetan Plateau, although systematic biases remain, particularly in precipitation estimates (Wu et al., 2023). Comparison with observations from 28 meteorological stations in the Qilian Mountains during 1980–2 018 showed that ERA5-Land captured the spatial patterns and temporal trends of monthly precipitation and temperature, while systematically overestimating precipitation amounts (Li et al., 2022). Over the eastern Tibetan Plateau, ERA5-Land reproduced the broad spatiotemporal evolution of regional rainfall events, with spatial correlations exceeding 0.8, although biases remained in rainfall characteristics (Hu and Yuan, 2021). Evaluations across the Tibetan Plateau similarly indicate that ERA5-Land captures broad precipitation and temperature patterns and their variability, while systematic regional biases persist (Wu et al., 2023). Given these uncertainties, in the revised manuscript the absolute magnitudes of ERA5-Land precipitation and evaporation trends with caution.
  
  About Discussion. The discussion of glacier melt and permafrost contribution mainly relies on previous studies. Some statements on glacier-melt buffering and permafrost-related contributions cannot be directed supported by the lake-level and climate-correlation analyses. The manuscript should make clearer which process interpretations are directly supported by this study and which are inferred from prior literature.
  
  Author’s response: We agree with the reviewer’s suggestion and revised the discussion to more clearly distinguish between results directly supported by our analysis and process-based interpretations based on previous studies. Our analysis shows that lakes within glaciated catchments exhibit rising water levels, while correlations with contemporaneous ERA5-Land temperature, precipitation, and evaporation are generally weak and statistically non-significant (r < 0.17). The observed weak correlations indicate that lake level variability in these catchments cannot be directly explained by the climate variables and may involve hydrological processes with delayed or nonlinear responses. The seasonal correlations identified for Gozha Lake are discussed as potential indications of the influence of snow storage and the timing of snow and ice melt, rather than as direct evidence of their contribution to lake water level change.
  
  To place our findings in a broader cryosphere context, we now discuss previous lake-catchment scale studies that have quantified contributions from glacier mass loss, ground-ice melt, and permafrost degradation to lake storage changes on the Tibetan Plateau and across HMA (Wang et al., 2022; Zhang et al., 2024). These studies provide estimates of cryosphere melt contributions to lake storage changes in individual catchments, supporting the plausibility of cryosphere related contributions to the rising lake levels. However, the relative importance of these processes likely varies among lakes and cannot be resolved from our regional correlation analysis alone. Similarly, the increase in median growth rates from 0.028 m yr^-1 during the CryoSat-2 period to 0.096 m yr^-1 during the ICESat-2 period is presented as a possible indication of enhanced meltwater contributions under sustained warming, rather than as direct evidence of increasing glacier melt contributions. We acknowledge that process-based investigation using lake water balance modelling and independent observations of glacier, snow, and permafrost change is required to quantify these contributions.
  
  About regional classification. The manuscript groups lakes into Tibetan Plateau, Himalaya, western HMA, and glacierized catchments, however, the criteria are not described explicitly. In particular, “glacierized catchments” overlap spatially with the other regions. It is not clear whether these are treated as an independent category or a cross-cutting classification.
  
  Author’s response: Thank you for pointing out the missing explanation on classification. We now include a description to clarify the regional classification in the Materials and Methods section. For regional analysis, we use HMA boundaries from Bolch et al. (2019) and group the lakes into three geographic subregions, the Tibetan Plateau, Himalaya, and western HMA. We merged the subregions located within the Tibetan Plateau and western HMA. In addition to the geographic classification, we analyzed water level variations of lakes located in glacierised catchments based on the presence of glaciers within the contributing lake catchment. Lakes in glacierised catchment classification is therefore a cross-cutting classification rather than a separate geographic region. Lakes within glacierised catchments can occur within the Tibetan Plateau, Himalaya, or western HMA and may therefore belong simultaneously to one geographic region and the glacierised catchment group.
  Complete response to the reviewers is also attached as a supplementary PDF.
  References:
  Biskop, S., Maussion, F., Krause, P., and Fink, M.: Differences in the water-balance components of four lakes in the southern-central Tibetan Plateau, Hydrol. Earth Syst. Sci., 20, 209-225, https://doi.org/10.5194/hess-20-209-2016, 2016.
  Bolch, T., Shea, J. M., Liu, S., Azam, F. M., Gao, Y., Gruber, S., Immerzeel, W. W., Kulkarni, A., Li, H., Tahir, A. A., Zhang, G., and Zhang, Y.: Status and Change of the Cryosphere in the Extended Hindu Kush Himalaya Region. In: The Hindu Kush Himalaya Assessment: Mountains, Climate Change, Sustainability and People, Wester, P., Mishra, A., Mukherji, A., and Shrestha, A. B. (Eds.), Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-92288-1_7, 2019.
  Hu, X. and Yuan, W.: Evaluation of ERA5 precipitation over the eastern periphery of the Tibetan plateau from the perspective of regional rainfall events, International Journal of Climatology, 41, 2625-2637, https://doi.org/10.1002/joc.6980, 2021.
  Jiang, L., Nielsen, K., Andersen, O. B., and Bauer-Gottwein, P.: A Bigger Picture of how the Tibetan Lakes Have Changed Over the Past Decade Revealed by CryoSat-2 Altimetry, Journal of Geophysical Research: Atmospheres, 125, e2020JD033161, https://doi.org/10.1029/2020JD033161, 2020.
  Lei, Y., Yang, K., Immerzeel, W. W., Song, P., Bird, B. W., He, J., Zhao, H., and Li, Z.: Critical Role of Groundwater Inflow in Sustaining Lake Water Balance on the Western Tibetan Plateau, Geophysical Research Letters, 49, e2022GL099268, https://doi.org/10.1029/2022GL099268, 2022.
  Li, Y., Qin, X., Liu, Y., Jin, Z., Liu, J., Wang, L., and Chen, J.: Evaluation of Long-Term and High-Resolution Gridded Precipitation and Temperature Products in the Qilian Mountains, Qinghai–Tibet Plateau, Frontiers in Environmental Science, Volume 10 - 2022, https://doi.org/10.3389/fenvs.2022.906821, 2022.
  Wang, L., Zhao, L., Zhou, H., Liu, S., Du, E., Zou, D., Liu, G., Xiao, Y., Hu, G., Wang, C., Sun, Z., Li, Z., Qiao, Y., Wu, T., Li, C., and Li, X.: Contribution of ground ice melting to the expansion of Selin Co (lake) on the Tibetan Plateau, The Cryosphere, 16, 2745-2767, https://doi.org/10.5194/tc-16-2745-2022, 2022.
  Wang, Y., Zheng, D., Zhang, G., Carrivick, J. L., Bolch, T., Ren, W., Guo, L., Su, J., Yuan, S., and Li, X.: Patterns and change rates of glacial lake water levels across High Mountain Asia, National Science Review, 12, https://doi.org/10.1093/nsr/nwaf041, 2025.
  Wu, X., Su, J., Ren, W., Lü, H., and Yuan, F.: Statistical comparison and hydrological utility evaluation of ERA5-Land and IMERG precipitation products on the Tibetan Plateau, Journal of Hydrology, 620, 129384, https://doi.org/10.1016/j.jhydrol.2023.129384, 2023.
  Yang, K., Yao, F., Wang, J., Luo, J., Shen, Z., Wang, C., and Song, C.: Recent dynamics of alpine lakes on the endorheic Changtang Plateau from multi-mission satellite data, Journal of Hydrology, 552, 633-645, https://doi.org/10.1016/j.jhydrol.2017.07.024, 2017.
  Zhang, G., Chen, W., and Xie, H.: Tibetan Plateau's Lake Level and Volume Changes From NASA's ICESat/ICESat-2 and Landsat Missions, Geophysical Research Letters, 46, 13107-13118, https://doi.org/10.1029/2019GL085032, 2019.
  Zhang, G., Yao, T., Piao, S., Bolch, T., Xie, H., Chen, D., Gao, Y., O'Reilly, C. M., Shum, C. K., Yang, K., Yi, S., Lei, Y., Wang, W., He, Y., Shang, K., Yang, X., and Zhang, H.: Extensive and drastically different alpine lake changes on Asia's high plateaus during the past four decades, Geophysical Research Letters, 44, 252-260, https://doi.org/10.1002/2016GL072033, 2017a.
  Zhang, G., Yao, T., Shum, C. K., Yi, S., Yang, K., Xie, H., Feng, W., Bolch, T., Wang, L., Behrangi, A., Zhang, H., Wang, W., Xiang, Y., and Yu, J.: Lake volume and groundwater storage variations in Tibetan Plateau's endorheic basin, Geophysical Research Letters, 44, 5550-5560, https://doi.org/10.1002/2017GL073773, 2017b.
  Zhang, G., Yao, T., Xie, H., Yang, K., Zhu, L., Shum, C. K., Bolch, T., Yi, S., Allen, S., Jiang, L., Chen, W., and Ke, C.: Response of Tibetan Plateau lakes to climate change: Trends, patterns, and mechanisms, Earth-Science Reviews, 208, 103269, https://doi.org/10.1016/j.earscirev.2020.103269, 2020.
  Zhang, Z., Li, X., Zhou, C., Zhao, Y., Zhao, G., and Tang, Q.: Linking ground ice and glacier melting to lake volume change in the Dogai Coring watershed on the Tibetan Plateau, Journal of Hydrology, 629, 130581, https://doi.org/10.1016/j.jhydrol.2023.130581, 2024.
  
  Citation: https://doi.org/10.5194/egusphere-2026-808-AC1
RC2:
'Comment on egusphere-2026-808', Anonymous Referee #2, 11 Jun 2026

General comments
This is an interesting submission using altimetry data to characterise changing lake levels across High Mountain Asia. It is well-structured and the methods appear to follow a well-established workflow. The findings are broadly consistent with previous regional studies, offering some new insights into spatial variability in lake-level trends. There are several aspects that I think could (should) be addressed before the manuscript is accepted; in particular the uncertainty quantification seems optimistic and the attribution of observed changes to climatic drivers rather simplistic (which needs acknowledging/discussing), and the framing of the work around 'glacial lakes' is somewhat misleading since they are not included in any of the analysis.
Specific comments
- The uncertainties calculated for each dataset look optimistic to me - there is some brief consideration, or acknowledgement, that the correlation errors are not accounted for, but how about accounting for things like the bias correction, given that a substantial number of the lakes show a different offset? How does this propagate into the presented trends? While the sign agreement of the trends derived by the two sensors is high, the rates of change (0.15 m/a-1 vs 0.052 m/a-1) are substantially different. How can this inconsistency be accounted for (and can some of that discussion/acknowledgement of the additional uncertainties that go beyond random noise - sensor mismatches for example) be included in the manuscript?

- The climate attribution is currently quite limited and probably overstated. The correlation between precipitation and lake levels is modest and only some of the subsets show significant relationships. As stated early in the manuscript these lakes integrate fluctuations in the contribution of meltwater, precipitation, permafrost thaw and groundwater so it's a complex picture, and probably doesn't conform to a linear relationship anyway. Even more so if you include storage effects and lags in meltwater routing for example. There should be a more extensive part to the discussion that acknowledges the different components of the water balance more directly and the fact that the analysis is limited by the resolution of the climate data and the absence of a lagged/multivariate/non-linear analysis.

- There are quite a number of citations within the manuscript that are not within the reference list - which on the face of it might seem to be a minor oversight but it makes it difficult for reviewers to properly evaluate how robust the argument being presented is (and therefore ultimately undermines the strength of this argument).

- Given that the study focuses solely on lakes of surface area > 20km2, all of the text about glacial lakes expanding (and becoming hazardous - with reference to GLOF events) seems somewhat redundant. I suggest those sentences in the introduction and the discussion should be removed.
Technical corrections (numbers refer to lines within the manuscript)
Is the title totally representative of what is presented, given that the abstract acknowledges heterogeneity across the TP and there is a decline in lake levels for the Himalaya?

21: declines should be presented as a negative number?

24: deriver = driver?

25: 'glacierised' here and throughout if you mean that the catchment currently has ice cover?

28: is growth the correct word here (and throughout)? This implies a lateral expansion to me, which your data do not assess. I suggest being consistent and using 'water level rise' instead.

40-45: this is an awkward sentence with too many parts to it. Can it be broken down a little bit? And checked for grammar too (lines 40-41 in particular)?

46: 'so understanding their...'

47: what is 'this' here - the antecedent is unclear

52: 'In the meantime' refers here to the previous studies of the previous sentence I think, but then it's specified as 'since 1990'. Maybe just delete the first three words to avoid any confusion/conflict.

Figure 1: I can't see lake I. Also where the labels are overlayed directly onto the lake circle they are difficult to make out. Also the caption states A-J, not A-I.

Figure 1: The placement of a (largely) results figure here in the introduction is a bit odd?

Section 2: how were multiple datapoints over each lake handled? Mean? Median? And which ERA-5 cell was selected for the climate analyses? (sorry if I missed these)

134-135: how were regulated lakes identified/derived?

138: correct the (R)

159: why is this 238 lakes?

160: is this systematic bias an average value? give the range if so? and why does it only apply to 77% of lakes?? What is the case for the other 23%!?

164: full-stop (not comma)

183: 179+54=233...?

Figure 2: I don't see any shading, as described in the caption

Figure 2: Is it possible to add the data points (in light grey for example) from which the relationships are derived?

Figure 2: The Himalaya combined line doesn't seem to be altered from the Cryosat one - is that real?

200-205: Couldn't this be a test for difference on a per-lake basis?

203-204: Might the reader see some numbers on how well the rates of change compare - in a scatterplot for example? Could all of the lake values be shown for the overlap period?

216-219: The total number of lakes here is significantly short of 232. why is that?

Figure 3: The splitting of the Cryosat data into two periods confused me for a bit here - is this introduced earlier in the manuscript or does an explanation need adding?

247: the start to this sentence is missing. 'The lakes in western HMA showed a consistent pattern, with 7 out of 12 experiencing...'?

266: On 'the' Tibetan Plateau...

Figure 4: These data look like they still have a seasonal signal to me...?

294: Lake catchments in 'the' Himalaya experience...?

Table 1 probably needs moving up as it includes important information about how many lakes are analysed per sensor per period (which accounts for some of my comments above)

lines 375-376: odd capital letters here

400: 'the' lake water budget. (full stop)

426: 'aligning'

425: I agree, but that's why they're large in the first place, so it doesn't account for why the relative rate of change is higher.

444-446: this study says nothing about glacial lakes and even less about GLOF hazards so I think this sentence can be removed.

473: citations should come after 'runoff' not 'presents'

Table S1: why are there 238 lakes here (232 referred to in the caption)?

Citation: https://doi.org/10.5194/egusphere-2026-808-RC2
- AC2:
  'Reply on RC2', Javed Hassan, 01 Aug 2026
  Response to Reviewer: 2 (Reply on RC2)
  General comments:
  This is an interesting submission using altimetry data to characterise changing lake levels across High Mountain Asia. It is well-structured and the methods appear to follow a well-established workflow. The findings are broadly consistent with previous regional studies, offering some new insights into spatial variability in lake-level trends. There are several aspects that I think could (should) be addressed before the manuscript is accepted; in particular the uncertainty quantification seems optimistic and the attribution of observed changes to climatic drivers rather simplistic (which needs acknowledging/discussing), and the framing of the work around 'glacial lakes' is somewhat misleading since they are not included in any of the analysis.
  Author’s response: We thank the reviewer for taking the time to review our manuscript and for providing thorough and constructive comments. The suggestions have been very helpful in improving the clarity and scientific presentation of the manuscript. We appreciate the positive comments regarding the overall structure of the manuscript and the methodological framework. Following the comments and suggestions we have substantially revised the manuscript to address the concerns. Specifically, we expanded the discussion of uncertainties by clarifying the distinction between statistical and systematic uncertainties, providing additional discussion of residual inter-mission differences, and including new analyses of CryoSat-2 and ICESat-2 consistency during the overlap period. We moderated the interpretation of lake water level changes and climate analysis together with the limitations of the ERA5-Land climate data. We revised the framing of the manuscript to focus consistently on large lakes (>20 km²) across High Mountain Asia and removed the discussion of glacial lake expansion and GLOF hazards from the Introduction and Discussion, revised the terminology throughout the manuscript. We also addressed all technical comments, corrected inconsistencies in the supplementary material, revised figures and captions. We hope these revisions have improved the manuscript. The detailed responses to each comment are provided below.
  Specific comments
  The uncertainties calculated for each dataset look optimistic to me - there is some brief consideration, or acknowledgement, that the correlation errors are not accounted for, but how about accounting for things like the bias correction, given that a substantial number of the lakes show a different offset? How does this propagate into the presented trends? While the sign agreement of the trends derived by the two sensors is high, the rates of change (0.15 m/a-1 vs 0.052 m/a-1) are substantially different. How can this inconsistency be accounted for (and can some of that discussion/acknowledgement of the additional uncertainties that go beyond random noise - sensor mismatches for example) be included in the manuscript?
  
  Author’s response: Thank you for highlighting weaknesses in the uncertainty propagation. We agree that the statistical uncertainty estimates presented in the original manuscript did not explicitly distinguish between measurement uncertainty and additional systematic sources of uncertainty associated with mission intercomparison trends. We revised both the Methods and Discussion sections to clarify the scope of the reported uncertainty estimates and to discuss the limitations associated with residual inter-mission differences.
  The uncertainty estimates reported in this study represent the statistical uncertainties associated with the annual lake level estimates and linear trend fitting. We now clarify that these uncertainties do not include systematic sources of error, such as residual inter-mission bias, geoid differences, retracking differences, or spatially correlated measurement errors. During the overlap period (2018-2023), intercomparison shows a mean vertical offset of +2.74 m between CryoSat-2 and ICESat-2. This offset is statistically significant for 79% of lakes, indicating generally consistent inter-mission differences across the majority of lakes (183 of 232). We therefore applied a -2.74 m correction to ICESat-2 timeseries for the mission intercomparison. Because this correction represents a constant vertical offset, it is not expected to influence linear trend estimates unless the inter-mission bias varies with time. Nevertheless, we now acknowledge that residual lake-specific offsets and other systematic inter-mission differences may contribute additional uncertainty to the combined 2010 to 2024 trend estimates and are not propagated within the reported statistical uncertainties.
  Regarding the difference in trend magnitudes derived from CryoSat-2 and ICESat-2. We have expanded the Discussion to emphasize that these differences should not be interpreted solely as sensor inconsistencies because the two missions sample different periods. The revised manuscript now includes an analysis comparing lake level trends before and after 2018, about (33.2%) changed the direction of their trends between the two periods. This temporal evolution indicates that differences between CryoSat-2 and ICESat-2 derived trend magnitudes cannot be attributed solely to inter-mission measurement differences, as the two missions also sample different phases of lake level evolution. We also expanded the Discussion of systematic uncertainties and the mission intercomparison (Fig. S1 and Fig. S6) to more explicitly acknowledge these limitations.
  The climate attribution is currently quite limited and probably overstated. The correlation between precipitation and lake levels is modest and only some of the subsets show significant relationships. As stated early in the manuscript these lakes integrate fluctuations in the contribution of meltwater, precipitation, permafrost thaw and groundwater so it's a complex picture, and probably doesn't conform to a linear relationship anyway. Even more so if you include storage effects and lags in meltwater routing for example. There should be a more extensive part to the discussion that acknowledges the different components of the water balance more directly and the fact that the analysis is limited by the resolution of the climate data and the absence of a lagged/multivariate/non-linear analysis.
  
  Author’s response: We thank the reviewer for this constructive comment. We agree that lake level variability reflects the combined influence of multiple components of the lake water balance and ERA5-Land correlation analysis cannot alone provide direct attribution of their relative contributions. We revised the manuscript to moderate the mechanistic interpretation. Statements implying direct climatic control have been replaced with more cautious interpretations based on statistical associations. We clarified the distinguish between results supported by our study and process-based attributions based on previous studies. Specifically, highlighting the precipitation as the climate variable most consistently associated with de-seasoned lake level trends. This statistical relationship does not by itself quantify the relative contributions of precipitation to lake level change. For lakes in glaciated catchments, we revised the interpretation to emphasize that weak correlations with contemporaneous temperature, precipitation, and evaporation indicate that lake water level variability cannot be directly explained by the climate variables and may instead reflect hydrological processes with delayed or nonlinear responses.
  We added the following statement to clearly define the scope of our climate analysis: Lake level change represents the integrated response of catchment runoff from precipitation, evaporation, snow and ice melt, groundwater exchange, and catchment storage processes. Consequently, the correlations presented here should be interpreted as first-order statistical associations rather than direct attribution of individual water-balance components.
  The limitations associated with the ERA5-Land climate data are discussed in greater detail. While ERA5-Land provides consistent spatiotemporal coverage, its performance in high elevations with complex topography remains uncertain due to coarse resolution, sparse ground observations and systematic biases in precipitation representation (Orsolini et al., 2019; Tazi et al., 2024). Comparison with 28 meteorological stations in the Qilian Mountains during 1980-2018 showed that ERA5-Land captured the spatial patterns and temporal trends of monthly precipitation and temperature, while the amount of precipitation exhibited systematic overestimation (Li et al., 2022). Over the eastern Tibetan Plateau, ERA5-Land captured the broad spatiotemporal evolution of regional rainfall events, with spatial correlations >0.8, but exhibited biases in rainfall characteristics (Hu and Yuan, 2021). Evaluations over the Tibetan Plateau indicate that ERA5-Land can reproduce broad spatial and temporal patterns of precipitation and temperature, although systematic biases remain, particularly for precipitation on Tibetan Plateau (Wu et al., 2023b). Consequently, absolute magnitudes of precipitation and evaporation trends should be interpreted cautiously, though relative variability is generally reliable.
  There are quite a number of citations within the manuscript that are not within the reference list - which on the face of it might seem to be a minor oversight but it makes it difficult for reviewers to properly evaluate how robust the argument being presented is (and therefore ultimately undermines the strength of this argument).
  
  Author’s response: We thank the reviewer for identifying this oversight. Number of citations were omitted from the reference list because of a technical issue during manuscript preparation. We have carefully reviewed and included all citations in the reference list in the revised manuscript. The missing references included:
  Introduction: (Pekel et al., 2016), (Woolway et al., 2020), (Miles et al., 2021), (Zhang et al., 2023), (Zheng et al., 2021), (Brun et al., 2020), (Zhou et al., 2015).
  Method: (Villadsen et al., 2015), (Pavlis et al., 2012), (Sheng et al., 2016), (Mann, 1945), (Kendall, 1975).
  Given that the study focuses solely on lakes of surface area > 20km², all of the text about glacial lakes expanding (and becoming hazardous - with reference to GLOF events) seems somewhat redundant. I suggest those sentences in the introduction and the discussion should be removed.
  
  Author’s response: We removed the discussion of glacial lake expansion and associated GLOF hazards from Introduction and Discussion sections. The Introduction now focuses on the role of large high-altitude lakes as indicators of regional hydrological change, the spatial heterogeneity of lake level variability across High Mountain Asia, and the motivation for establishing a consistent multi-mission satellite altimetry record. The Discussion section has also been revised to focus on the interpretation of the observed lake level changes, comparison with previous studies, and the scientific contributions of our study, rather than hazards associated with glacial lakes.
  Technical corrections (numbers refer to lines within the manuscript)
  Is the title totally representative of what is presented, given that the abstract acknowledges heterogeneity across the TP and there is a decline in lake levels for the Himalaya?
  
  Author’s response: We agree that, given the regional heterogeneity in lake level changes and the persistent declines observed in the Himalaya, the original title was not fully representative of the study. Following the suggestion, we revised the title to "Lake Level Changes Across High Mountain Asia from CryoSat-2 and ICESat-2" to better reflect the scope and findings of the study.
  21: declines should be presented as a negative number?
  
  Author’s response: Decline values are now presented with negative number in the revised manuscript, “whereas Himalayan lakes experienced persistent decline (-0.04 ± 0.001 m yr^-1) while western HMA displayed more heterogeneous behavior.”
  24: deriver = driver?, 25: 'glacierised' here and throughout if you mean that the catchment currently has ice cover?
  
  Author’s response: The sentence has been rephrased as "Catchment-scale climate analysis indicates that precipitation is the climate variable most consistently associated with lake-level variability, whereas lakes in glacierised catchments exhibit weak correlations with contemporaneous climate variables despite significant regional warming, suggesting that cryosphere processes may modulate hydrological responses."
  We used the term "glacierised catchments" throughout the revised manuscript to refer to catchments with present-day glacier cover.
  28: is growth the correct word here (and throughout)? This implies a lateral expansion to me, which your data do not assess. I suggest being consistent and using 'water level rise' instead.
  
  Author’s response: We agree that the term "growth" may imply lateral lake expansion rather than changes in lake water level. The rephrased the sentence as “We find systematic relationships between lake characteristics (area, elevation) and increasing water levels, with larger lakes generally showing higher rates of water-level rise.”
  40-45: this is an awkward sentence with too many parts to it. Can it be broken down a little bit? And checked for grammar too (lines 40-41 in particular)?
  
  Author’s response: We rephrased the sentence as “The HMA, often referred to as the “Third Pole” has undergone rapid warming in recent decades, particularly over the Tibetan Plateau, where warming rates of 0.50-0.67°C/decade have been reported (Kuang and Jiao, 2016; Niu et al., 2021; Wu et al., 2023a). These warming rates exceed the global average (Duan and Xiao, 2015) have contributed to accelerating glacier mass loss (Hugonnet et al., 2021; Zemp et al., 2025) and reduced snow persistence (Muhammad, 2024), along with precipitation changes (Na et al., 2024; Ouyang et al., 2020).”
  46: 'so understanding their...'
  
  Author’s response: We rephrased the sentence as “Lakes within the region integrate these interacting processes, and understanding their long-term behavior is essential for quantifying the hydrological response to climate change.”
  47: what is 'this' here - the antecedent is unclear
  
  Author’s response: The sentence has been removed from the revised manuscript.
  52: 'In the meantime' refers here to the previous studies of the previous sentence I think, but then it's specified as 'since 1990'. Maybe just delete the first three words to avoid any confusion/conflict.
  
  Author’s response: We removed the line 52 with 'In the meantime, …' and revised the paragraph to improve clarity and the logical flow of the Introduction as, “Lake water levels across HMA exhibit substantial spatial and temporal heterogeneity. On the Tibetan Plateau, lake levels and storage decreased from 1970s to 1990s and increased thereafter, with rising trends in the northern and central Tibetan Plateau contrasting with declines reported in parts of the southern Tibetan Plateau (Song and Sheng, 2016; Zhang et al., 2017b; Zhang et al., 2023). These contrasting patterns have been associated with regional differences in lake water balance components such as precipitation, evaporation, glacier and snow melt, permafrost dynamics (Lei et al., 2014; G Zhang et al., 2017b). The relative contributions of these processes vary across HMA because of strong regional gradients in climate, topography, glacier cover, and hydrological regimes, resulting in diverse lake-catchment environments (Wang et al., 2025; Zhang et al., 2020). Previous studies have shown that precipitation is a dominant contributor to lake water level variability across the Tibetan Plateau, whereas snow and ice melt make a comparatively limited contribution to recent lake volume change (Brun et al., 2020). At shorter timescales, extreme precipitation anomalies previously lead to abrupt lake level changes on Tibetan Plateau (Lei et al., 2019; Song and Sheng, 2016), underscoring the sensitivity of lake water storage to both persistent climate forcing and episodic hydroclimatic variability. Consequently, understanding changes in lake water levels at the regional scale requires observations that can resolve spatial differences in lake responses while providing sufficient temporal coverage to characterize their evolution.”
  Figure 1: I can't see lake I. Also where the labels are overlayed directly onto the lake circle they are difficult to make out. Also the caption states A-J, not A-I. Figure 1: The placement of a (largely) results figure here in the introduction is a bit odd?
  
  Author’s response: We revised Figure 1 to improve clarity and consistency. The time series subplots have been rearranged from panel A to I. Positions have also been adjusted to avoid overlapping between labels and the lake trend circles. The missing label ‘I’ has been placed, and the figure caption has been corrected. Lake boundaries are now also displayed on the basemap to better illustrate the study locations.
  The aim of placing Figure 1 at the end of the Introduction was also to introduce the study area, regional division of High Mountain Asia, and spatial distribution of the analysed lakes, while also providing an overview of the observed lake water-level changes. To clarify this dual purpose, we revised the figure caption.
  Please refer to the attached response file (PDF) for the revised Figure 1 Overview of the study area and spatial distribution of analysed lake across High Mountain Asia (HMA). The regional boundaries of the Tibetan Plateau, Himalaya, and western HMA follow Bolch et al. (2019) are shown with black outlines. Each circle represents an individual lake, circle color shows CryoSat-2 derived lake water level trend from 2010 to 2023, corresponding to the colorbar. The circle size is scaled by area of each lake. (A to J) Water level timeseries of selected lakes showing CryoSat-2 observations (black; 2010–2023) and ICESat-2 observation (brown; 2018–2024). The y-axis in each subplot represents lake water level in meters (EGS2008).
  Section 2: how were multiple datapoints over each lake handled? Mean? Median? And which ERA-5 cell was selected for the climate analyses? (sorry if I missed these)
  
  Author’s response: Instead of using mean/median of multiple along-track observations within each lake, we apply the mixture distribution approach described in Nielsen et al. (2015), which assumes observations follow a mixture of Gaussian and Cauchy distributions. We revised the Materials and Methods section to clarify how multiple altimetry observations over each lake were combined.
  “The water level time series is reconstructed via the method presented in Nielsen et al. (2015). All valid altimetry observations falling within the lake boundary are combined through the state-space model to estimate a single monthly lake water level together with its associated uncertainty. In summary, the model includes a random walk as the process part to account for the temporal correlation, and the observations are assumed to follow a mixture between the Normal and Cauchy distributions to ensure robustness of the water level estimates. The Cauchy distribution is characterized by heavier tails compared to the Normal distribution. In contrast to assuming that the observations only follow a normal distribution, the mixture distribution reduces the influence of extreme observations on the estimated mean.”
  We revised the Climate data analysis section to clarify the ERA5-Land data analysis over lake catchment. “For each lake, climate variables are extracted as the spatial average over the corresponding lake catchment using all ERA5-Land grid cells intersecting the catchment.”
  134-135: how were regulated lakes identified/derived?
  
  Author’s response: We thank the reviewer for highlighting the missing statement to identify lake where water levels are regulated. Regulated lakes were identified through lake names in the lake database used in this study, where reservoirs and impounded water bodies (e.g. Maharana Pratap Reservoir and Ramganga Reservoir) are provided and visual inspection of high-resolution satellite imagery in the Interactive Map, where dam structures were clearly visible (e.g. Ranjit Sagar Lake, Toktogul Skoye, Erher Hai, and Cheng Hai). We included clarification in the revised manuscript “Regulated lakes are identified from reservoir classifications in the lake database (Sheng et al., 2016) and by visual inspection of high-resolution satellite imagery, where dam structures were clearly visible.”
  138: correct the (R)
  
  Author’s response: Thank for pointing out the mistake ® is now corrected (R).
  159: why is this 238 lakes?
  
  Author’s response: Thank you for pointing out this error. The value 238 was a typographical error. The correct number of analysed lakes is 232 and has been corrected in the manuscript.
  160: is this systematic bias an average value? give the range if so? and why does it only apply to 77% of lakes?? What is the case for the other 23%!?
  
  Author’s response: Intercomparison during the overlapping period (2018-2023) shows a mean vertical offset of +2.74 m between ICESat-2 and CryoSat-2 measurements. This offset is statistical significance (p < 0.05) for 79% of the lakes (183 of 232), indicating generally consistent inter-mission differences across the majority of lakes. We therefore applied a constant -2.74 m correction to ICESat-2 timeseries for the mission intercomparison. For the remaining lakes (49), the estimated offsets are not statistically significant. Since the majority of lakes exhibited a consistent inter-mission bias, we applied the mean offset as a constant vertical correction for the mission intercomparison. We include further description for further clarification in the revised manuscript.
  “Intercomparison during the overlapping period (2018-2023) shows a mean vertical offset of +2.74 m between ICESat-2 and CryoSat-2 measurements. This offset is statistical significance (p < 0.05) for 79% of the lakes (183 of 232), indicating generally consistent inter-mission differences across the majority of lakes. We therefore applied a -2.74 m correction to ICESat-2 timeseries for the mission intercomparison. Because this correction is applied as a constant vertical offset, it is not expected to influence linear trend estimates unless the inter-mission bias varies with time. Residual lake-specific offsets and other systematic inter-mission differences may nevertheless contribute additional uncertainty to individual lake trend estimates and are not represented in the statistical uncertainties reported here. The reported uncertainties therefore represent uncertainties associated with the annual lake level estimates and linear trend fitting, and do not include systematic sources of error such as residual inter-mission bias, geoid differences, retracking differences, or spatially correlated measurement errors, which are discussed further in Section 4.”
  164: full-stop (not comma)
  
  Author’s response: Replaced comma with full-stop.
  183: 179+54=233...?
  
  Author’s response: Thank you for identifying this typo-error. The number of lakes with declining water levels is incorrectly reported as 54. The correct value is 53. This has been corrected in the revised manuscript.
  Figure 2: I don't see any shading, as described in the caption. Figure 2: Is it possible to add the data points (in light grey for example) from which the relationships are derived? Figure 2: The Himalaya combined line doesn't seem to be altered from the Cryosat one - is that real?
  
  Author’s response: Thank you for these helpful suggestions. The uncertainty associated with the regional uncertainty-weighted mean trends is small therefore the shaded are largely not clear with the trend lines. We considered adding individual data points to Figure 2, however, because the figure is intended to illustrate regional temporal trajectories, plotting individual lake trend estimates substantially reduced the clarity of the figure. We revised the Figure to add regional trends derived from the CryoSat-2 for the overlap period (2018–2023), visual comparison with the ICESat-2 trends (2018–2024). We have now added a new supplementary Figure S6 comparing lake-level trends from CryoSat-2 and ICESat-2 for all 232 lakes during the overlap period. The caption of Figure 2 has been revised to clarify the uncertainty representation.
  Please refer to the attached response file (PDF) for the revised Figure 2 Regional lake water-level trends across HMA derived from (a) CryoSat-2 (blue, 2010–2023), CryoSat-2 overlap period (blue dash, 2018–2023), ICESat-2 (red, 2018–2024), and the combined record after bias correction (green, 2010–2024); (b) lakes within glacierized catchments; (c) the Tibetan Plateau; (d) the Himalaya; and (e) western High Mountain Asia. The shaded uncertainty band represents the standard error (1 ) of the regional uncertainty-weighted mean trend. (f) Spatial distribution of lakes, with the different regions outlined in black.
  200-205: Couldn't this be a test for difference on a per-lake basis?
  
  Author’s response: we assessed the agreement between CryoSat-2 and ICESat-2 using multiple complementary metrics for each lake during the overlap period (2018–2023), including the mean bias and standard deviation of the differences, correlation of the lake level time series also shown in the Figure S1 with representative examples of lake level agreement, and agreement in the direction of the estimated trends (80% sign agreement). These metrics indicate generally consistent behaviour between the two missions across the majority of lakes. We therefore consider these analyses to provide a robust assessment of inter-mission consistency.
  203-204: Might the reader see some numbers on how well the rates of change compare - in a scatterplot for example? Could all of the lake values be shown for the overlap period?
  
  Author’s response: Following the suggestion, we added a new supplementary Figure S6 comparing lake level trends derived independently from CryoSat-2 and ICESat-2 for all 232 lakes during the overlapping period (2018–2023). The comparison demonstrates strong agreement between the two missions (r = 0.92, p < 0.001), with an RMSE of 0.20 m/yr, a mean bias of −0.06 m/yr, and 80% agreement in the direction of change.
  Please refer to the attached response file (PDF) for the revised New Figure S6. Comparison of lake level trends derived from CryoSat-2 and ICESat-2 during the overlapping period (2018 – 2023). Each analysed lake is represented by a point, with colors indicating geographic regions. Solid circles show trends that are statistically significant in both missions (p < 0.05), while hollow circles show trends that are not significant in one or both missions.
  216-219: The total number of lakes here is significantly short of 232. why is that?
  
  Author’s response: Thank you for pointing this out. The numbers in this paragraph refer only to the Tibetan Plateau subset rather than to the complete dataset of 232 lakes. We agree the existing text was not sufficiently clear and may have caused confusion. The text has been revised to explicitly state the number of lakes within the Tibetan Plateau before presenting the regional statistics. “Among the 2011 lakes on the Tibetan Plateau, CryoSat-2 (2010 to 2023) based results show increasing lake levels at a rate of 0.18 m/yr, with 113 lakes (54%) showing consistent increasing trends (>0.1 m/yr), only 14 showed stable water levels (-0.01 to 0.01 m/yr) and the number of lakes with a strong decreasing trends (<-0.1 m/yr) is relatively low (7 lakes).”
  Figure 3: The splitting of the Cryosat data into two periods confused me for a bit here - is this introduced earlier in the manuscript or does an explanation need adding?
  
  Author’s response: The CryoSat-2 trend is divided into the pre-overlap (2010-2017) and overlap (2018-2023) periods visual comparison with the ICESat-2 trend. We revised the figure caption in the manuscript to clarify.
  Figure 3. Water-level and climate variability for representative lakes on the Tibetan Plateau. (a) Location of Qinghai Hu Lake (blue), lake catchment boundary shown in black. (b) Monthly lake water-level time series derived from CryoSat-2 (2010–2023) and ICESat-2 (2018–2024). Point colours indicate the season of observation (correspond to the color bar), and standard deviation of lake levels is shown in grey. (c) Linear trends in lake water level derived from CryoSat-2 (blue) and ICESat-2 (yellow). For visual comparison with the ICESat-2 observations, the CryoSat-2 trend is shown separately for the pre-overlap (2010–2017) and overlap (2018–2023) periods. (d) Monthly anomalies in air temperature (T, °C), precipitation (P, mm), and evaporation (E, mm) derived from ERA5-Land. The same layout is shown for Hala Har Hu Lake, Gozha Lake, Dogai Coring Lake, Taro Co Lake, and Dogaicoring Qangco Lake.
  247: the start to this sentence is missing. 'The lakes in western HMA showed a consistent pattern, with 7 out of 12 experiencing...'?
  
  Author’s response: The sentence has been revised for clarity as follow “Among the 12 lakes studied in western HMA, 7 lakes experienced increasing water level during 2010 to 2023 based on CryoSat-2, with a mean rate of 0.13 m yr-1. ICESat-2 results show the slowdown in water levels rise during 2018 to 2024, with the mean trend decreasing to near zero (Fig. 2e).”
  266: On 'the' Tibetan Plateau...
  
  Author’s response: The sentence has been revised " On the Tibetan Plateau, where most lakes are located, correlations with all three climate variables are weak and statistically not significant (r = 0.09).”
  Figure 4: These data look like they still have a seasonal signal to me...?
  
  Author’s response: The time series shown in panel b and c of Figure 4 represent the monthly lake water level estimates from CryoSat-2 and ICESat-2. De-seasonalization was applied for the trend analysis.
  294: Lake catchments in 'the' Himalaya experience...?
  
  Author’s response: The sentence has been revised “Lake catchments in the Himalayan experience an increase in temperature during summer (+0.06 ± 0.01℃/yr) and autumns (+0.08 ± 0.04℃/yr) which is statistically significant. Winter precipitation shows a significant decline (-0.07 ± 0.03 mm/yr), while other seasons exhibit weaker, non-significant trends.”
  Table 1 probably needs moving up as it includes important information about how many lakes are analysed per sensor per period (which accounts for some of my comments above)
  
  Author’s response: The table has been moved to section 3.1. in the Results section, before the presentation of regional lake-level changes.
  lines 375-376: odd capital letters here
  
  Author’s response: Thank you for highlighting the mistake. We revised the sentence. “Lake expansion on Tibetan Plateau in recent decades have been attributed to precipitation, evaporation (Biskop et al., 2016; Yang et al., 2017), snow and ice melt (Zhang et al., 2017b) ground Water (Lei et al., 2022). The increasing precipitation trend observed at meteorological station on Tibetan Plateau during 1978 to 2013, except in parts of the southeast (Zhang et al., 2017a), is broadly consistent with the spatial pattern of lake water level changes (Fig. 2).”
  400: 'the' lake water budget. (full stop)
  
  Author’s response: The sentence has been rephrased. “At the lake-catchment scale, Zhang et al. (2024) attributed 62.5% of the increase in Dogai Coring lake storage during 2014-2020 to glacier mass loss and 19.3% to permafrost degradation, while ground ice melt contributed an estimated 12% of Selin Co lake volume expansion during 2017-2020 (Wang et al., 2022).”
  426: 'aligning'
  
  Author’s response: The sentence has been revised as suggested. “This pattern is particularly evident on the Tibetan Plateau aligning with the finding of Zhang et al. (2019), though weak (r = 0.09) statistical correlations, indicating that other catchment properties modulate this relationship such as precipitation.”
  425: I agree, but that's why they're large in the first place, so it doesn't account for why the relative rate of change is higher.
  
  Author’s response: We agree that the original statement overinterpreted the observed relationship. The discussion has been revised to avoid inferring a mechanistic explanation from the observed association. We revised text: “The systematic relationship between lake area and water-level change rates across most regions, with the largest lakes (>1000 km²) showing the most rapid increases, suggests that lake size is associated with the magnitude of observed water level change. This pattern is particularly evident on the Tibetan Plateau aligning with the finding of Zhang et al. (2019), though weak (r = 0.09) statistical correlations, indicating that other catchment properties modulate lake level variability.”
  444-446: this study says nothing about glacial lakes and even less about GLOF hazards so I think this sentence can be removed.
  
  Author’s response: We agree that this paragraph should reflect the main scientific contributions of the study and avoid overemphasizing hazards that are beyond the scope of our analysis. We revised the paragraph. “The heterogeneous lake responses documented in this study highlight the strong spatial variability of hydrological change across HMA. Continued water-level rise across much of the Tibetan Plateau contrasts with persistent declines in the Himalaya, indicating that lake responses vary substantially among different hydroclimatic and cryosphere settings. Lakes within glaciated catchments exhibit weak contemporaneous relationships with precipitation, temperature, and evaporation, indicating that lake level variability represents the integrated response of multiple hydrological processes rather than direct climatic forcing alone. By combining CryoSat-2 (2010–2023) and ICESat-2 (2018–2024), this study provides regionally consistent multi-mission assessment of lake water-level variability across 232 large lakes in HMA, enabling direct comparison of temporal trajectories among contrasting hydrological settings. These observations establish an important reference for evaluating future changes in alpine water storage, improving understanding of regional hydrological responses to climate change, and supporting the development and evaluation of hydrological models for HMA.”
  473: citations should come after 'runoff' not 'presents'
  
  Author’s response: Thank you for the suggestion. We now moved the citations before ‘presents’ as suggested. “The climate-change exposure represented by 250 million people dependent on HMA runoff (Immerzeel et al., 2020; Pritchard, 2019) presents a strong impetus to improve our understanding of the lake water level variability across HMA.”
  Table S1: why are there 238 lakes here (232 referred to in the caption)?
  
  Author’s response: Thank you for identifying this inconsistency. The Supplementary Material by mistake contained an incorrect version of Table S1. Table S1 has been replaced with the correct version, which is fully consistent with the analyses presented in the manuscript. Please refer to the attached response file for the revised Table S1 Group statistics of median lake level change rates by their magnitudes for all 232 lakes across HMA.
  The complete response to the reviewer (Reply on RC2) is also attached as a supplementary PDF.
  References:
  Biskop, S., Maussion, F., Krause, P., and Fink, M.: Differences in the water-balance components of four lakes in the southern-central Tibetan Plateau, Hydrol. Earth Syst. Sci., 20, 209-225, https://doi.org/10.5194/hess-20-209-2016, 2016.
  Bolch, T., Shea, J. M., Liu, S., Azam, F. M., Gao, Y., Gruber, S., Immerzeel, W. W., Kulkarni, A., Li, H., Tahir, A. A., Zhang, G., and Zhang, Y.: Status and Change of the Cryosphere in the Extended Hindu Kush Himalaya Region. In: The Hindu Kush Himalaya Assessment: Mountains, Climate Change, Sustainability and People, Wester, P., Mishra, A., Mukherji, A., and Shrestha, A. B. (Eds.), Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-92288-1_7, 2019.
  Brun, F., Treichler, D., Shean, D., and Immerzeel, W. W.: Limited Contribution of Glacier Mass Loss to the Recent Increase in Tibetan Plateau Lake Volume, Frontiers in Earth Science, 8, https://doi.org/10.3389/feart.2020.582060, 2020.
  Duan, A. and Xiao, Z.: Does the climate warming hiatus exist over the Tibetan Plateau?, Scientific Reports, 5, 13711, https://doi.org/10.1038/srep13711, 2015.
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  Citation: https://doi.org/10.5194/egusphere-2026-808-AC2

Javed Hassan, Karina Nielsen, William Colgan, Rijan Bhakta Kayastha, Mira Khadka, and Shfaqat Abbas Khan

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https://doi.org/10.5194/egusphere-2026-808-supplement

Javed Hassan, Karina Nielsen, William Colgan, Rijan Bhakta Kayastha, Mira Khadka, and Shfaqat Abbas Khan

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Short summary

High-altitude lakes in High Mountain Asia (HMA) are important sources of freshwater and sensitive indicators of environmental change. Using satellite data from 2010 to 2024, we examine water level changes in 232 lakes across HMA. Results show rising lake levels on the Tibetan Plateau, while lakes in the Himalaya are declining. These contrasting patterns highlight strong regional differences and provide valuable information for understanding water availability and associated hazards.


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