How Do Climate Change and Deglaciation Affect Runoff Formation Mechanisms in the High-Mountain River Basin of the North Caucasus?

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study analyses the effects of climate change on discharge formation in North Caucasus basin, where there are high mountain and large glaciers, affecting discharge. They calibrated the ECOMAG hydrological model to assess future variations of discharge, and sensitivity of discharge to change in air temperature, glacier area, and precipitation.

The study is overall clear. The goals are evident such as the scientific importance of the study. I would recommend some minor revisions to provide the reader some useful data and possibly increase the clarity of the study.

 

Line 19- increase in runoff in autumn is probably also due to the shift between solid and liquid precipitation, not only to increase in snowmelt.

Line 22 – specify the time period when you assessed these changes, both future scenarios and historical.

Line 53 – please provide the data of total area of glacier in Greater Caucasus if available

Line 105 – provide also the area of the basin please

Figure 2 a) I think it would be more interesting to report the value of the trend instead of the p value, which is somehow already reported by empty circles.

Figure 3 a), if possible do not use smoothed lines if the data are not continuous.

Table 1. Table 2. Figure 4. I would move the results of hydrological modelling in results section. Which parameters were object of calibration? How did you calibrate snow and ice melt? Please expand how you used stable isotope. Some of these data, like average temperature, precipitation, and isotopes could be worth a graph also to provide information regarding local climate of the area. Provide also assessed discharge and ice melt. I suppose red color in figure 4a) represents modelled data and blue observed but it is better to specify it.

Lines 213-219. I did not completely understand the scenarios considered. I think the acronyms are not too effective. For example, “pre+5 (10, 20)% is an increase in precipitation of 5 (10, 20)%” what is the increase in precipitation considered? What are referring to the numbers in the parentheses?

Lie 278 – provide some data regarding average and peak ice thickness of considered glaciers.

Line 306. I would add the sign “-“ to negative number even if you specified it was a decrease.

Line 338-349 You don’t mention the effects of air temperature on the change in evapotranspiration.

Line 458, 460. The value reported in mm is the average contribute over the basin? I suggest to report the percentage of discharge contribute given by snow, ice and rainfall. Also mm of evapotranspiration, or the percentage of net precipitation (precipitation minus evapotranspiration) would be interesting.

Author Response

Comment 1: The study analyses the effects of climate change on discharge formation in North Caucasus basin, where there are high mountain and large glaciers, affecting discharge. They calibrated the ECOMAG hydrological model to assess future variations of discharge, and sensitivity of discharge to change in air temperature, glacier area, and precipitation.

The study is overall clear. The goals are evident such as the scientific importance of the study. I would recommend some minor revisions to provide the reader some useful data and possibly increase the clarity of the study.

Response 1: We thank the reviewer for the comments.

Comment 2: Line 19 - increase in runoff in autumn is probably also due to the shift between solid and liquid precipitation, not only to increase in snowmelt.

Response 2: Yes, we’ve added this point to clarify that the rise in autumn runoff is not just caused by earlier snowmelt but also by the increasing proportion of rain (liquid precipitation) over snow (solid precipitation) due to warmer temperatures. This shift further boosts runoff during the autumn season.

Comment 3: Line 22 – specify the time period when you assessed these changes, both future scenarios and historical.

Response 3: Thank you for your comment! We have now specified the time periods: the future changes (2070–2099) are assessed relative to the historical baseline (1977–2005).

Comment 4: Line 53 – please provide the data of total area of glacier in Greater Caucasus if available

Response 4: We have now included the total glacier surface area data for the Greater Caucasus. In 1960, the total glacier surface area was 1674.9 ± 70.4 km². By 1986, glacier surface area had decreased to 1482.1 ± 64.4 km², and by 2014 to 1193.2 ± 54.0 km².

Comment 5: Line 105 – provide also the area of the basin please

Response 5: Thank you for your note. We’ve now included the basin’s area (20,600 km²) in the article.

Comment 6: Figure 2 a) I think it would be more interesting to report the value of the trend instead of the p value, which is somehow already reported by empty circles.

Response 6: We agree that the trend value is important for interpretation, and we explicitly report it in the figure legend. However, we retained the p-values to provide a standardized metric for statistical significance, complementing the visual representation in the plot. This aligns with common practices in the field, ensuring clarity for readers assessing both effect size and uncertainty.

Comment 7: Figure 3 a), if possible do not use smoothed lines if the data are not continuous.

Response 7: In Figure 3(a), we’ve replaced the smoothed lines with straight connecting lines.

Comment 8: Table 1. Table 2. Figure 4. I would move the results of hydrological modelling in results section. Which parameters were object of calibration? How did you calibrate snow and ice melt? Please expand how you used stable isotope. Some of these data, like average temperature, precipitation, and isotopes could be worth a graph also to provide information regarding local climate of the area. Provide also assessed discharge and ice melt. I suppose red color in figure 4a) represents modelled data and blue observed but it is better to specify it.

Response 8: We thank the reviewer for their valuable comments. Following the recommendations, we have moved the hydrological modeling results to the "Results" section (now Section 4.1), including Tables 1 and 2 (now 2 and 4). To ensure greater transparency in the calibration process, we have added a new Table 3 listing the key calibrated parameters.

A more detailed description of the calibration, including validation using glacier mass-balance measurements, isotope samplings and remote sensing data (MODIS), is provided in a separate paper (Pavlyukevich et al., 2025). The model was validated using satellite MODIS spectroradiometer data on catchment snow cover, which showed that the model correctly simulated the intra-annual course of snow cover change. The coefficient of determination for average monthly snow cover values was 0.85, with a relative error of 20%. The results of the validation of the runoff formation model based on the isotope analysis results show that, firstly, the model reflects the intra-annual variability of the fed-sources. Secondly, the proportion of meltwater runoff naturally decreases, while the proportion of precipitation runoff increases from upstream to downstream. The validation of the model against mass balance measurements of reference glaciers in the central Caucasus (Djankuat and Garabashi) revealed that the processes of snow and ice melting and redistribution in such dissected terrain are more complex in reality, leading to systematic errors. The best agreement was achieved for the Garabashi glacier, with an average relative error of 12%.

In the caption of Figure 4a, we clarified that the red line represents modeled discharge, blue line indicates observed discharges.

Comment 9: Lines 213-219. I did not completely understand the scenarios considered. I think the acronyms are not too effective. For example, “pre+5 (10, 20)% is an increase in precipitation of 5 (10, 20)%” what is the increase in precipitation considered? What are referring to the numbers in the parentheses?

Response 9: We appreciate your feedback and have revised the description of the scenarios to improve clarity. The modifications are as follows:

1. Reduction in the modern glacier area (scenario led): 75%, 50%, and 25% of the current glaciation area (scenarios led 75, led 50, led 25), the absence of glaciers (scenario led 0);
2. Change in actual daily precipitation (scenario pre): pre+5%, pre+10%, pre+20% is an increase in precipitation of 5, 10, 20%, and pre-5%, pre-10%, pre-20% is a decrease in precipitation of 5, 10, 20%, respectively;
3. Changes in the actual air temperature (scenario temp): temp+2, temp+4, temp+6 is an increase in air temperature by 2, 4, 6 °C, respectively.

Comment 10: Line 278 – provide some data regarding average and peak ice thickness of considered glaciers.

Response 10: On average, glaciers in the studied region exhibit an area-weighted mean ice thickness of approximately 58.6 m. The maximum ice thickness reaches 257 m, based on elevation-band-averaged data. We have added this information in the revised manuscript.

Comment 11: Line 306. I would add the sign “-“ to negative number even if you specified it was a decrease.

Response 11: To improve clarity, we have now added "-" signs for all decreases and "+" signs for increases throughout this section.

Comment 12: Line 338-349 You don’t mention the effects of air temperature on the change in evapotranspiration.

Response 12: Thank you for your comment. Following the temperature increase, evaporation from the surface of the studied Terek River basin also rises. Under the RCP2.6 scenario, evaporation is projected to increase by 8% by the last third of the 21st century, while under the RCP8.5 scenario, it will rise by more than 25%. We have now added these changes in the revised manuscript.

Comment 13: Line 458, 460. The value reported in mm is the average contribute over the basin? I suggest to report the percentage of discharge contribute given by snow, ice and rainfall. Also mm of evapotranspiration, or the percentage of net precipitation (precipitation minus evapotranspiration) would be interesting.

Response 13: Yes, the reported value in mm represents the average contribution over the basin. We chose to present absolute values (mm) because percentages can obscure the actual magnitudes and make cross-comparisons more difficult. Note that rainfall-derived runoff is already adjusted for evapotranspiration. We have also added information on evaporation trends.

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors,

Your paper "How do climate change and deglaciation affect runoff formation mechanisms in the high-mountain river basin of the North Caucasus?"  gives a detailed  analysis of runoff dynamics in a glacier-fed mountain basin under climate change.  The integration of the ECOMAG hydrological model with CORDEX forecasts and the GloGEMflow-DD glacier model provides a stable foundation for long-term simulation.  The incorporation of diverse observational datasets (MODIS, WGMS, isotopes, weather stations) enhances credibility, particularly given the data-scarce setting. 

The study presents an assessment of the various roles of snow, ice, and rainfall in runoff formation and for the rigorous sensitivity studies on major drivers.

Some modifications could further boost the manuscript. The degree-day melt model, albeit pragmatic, is a simplification that might benefit from a quick comparison with more physically-based alternatives.  

In addition, various methodological restrictions marginally reduce the extent of the conclusions.  Even though there isn't any radiative data, using a degree-day melt module is still a simplistic guess that doesn't properly show how the energy interactions work in glacier dynamics, especially when things become really bad. A more explicit reference to other, more complex energy-based methodologies, even for comparison reasons, would strengthen the critical depth of the study.  Moreover, the lack of clear coverage of extreme events such as flash floods or glacial lake outburst floods (GLOFs), despite being referenced in the discussion, is a striking omission considering the rising relevance of such occurrences in the Caucasus under the RCP8.5 scenario.

The presentation, although generally straightforward, might be improved in specific areas: several complicated figures would benefit from greater clarity through more detailed legends and summary boxes highlighting major anomalies or patterns.  A synthetic map illustrating spatial changes (glaciation, isohyets, gauge placements, sensitive zones) would increase overall knowledge.

In summary, this article offers a solid contribution to hydrological modeling in alpine ecosystems under climate change. It warrants publishing after some minor adjustments, mainly to clarify key statistics, fully express the limitations of the melt model, and add a discussion box in the conclusion outlining the consequences for other analogous glaciated places.

Sincerely,

Author Response

Comment 1: Dear authors,

Your paper "How do climate change and deglaciation affect runoff formation mechanisms in the high-mountain river basin of the North Caucasus?"  gives a detailed  analysis of runoff dynamics in a glacier-fed mountain basin under climate change.  The integration of the ECOMAG hydrological model with CORDEX forecasts and the GloGEMflow-DD glacier model provides a stable foundation for long-term simulation.  The incorporation of diverse observational datasets (MODIS, WGMS, isotopes, weather stations) enhances credibility, particularly given the data-scarce setting.

The study presents an assessment of the various roles of snow, ice, and rainfall in runoff formation and for the rigorous sensitivity studies on major drivers.

Response 1: We thank the reviewer for the comments.

Comment 2: Some modifications could further boost the manuscript. The degree-day melt model, albeit pragmatic, is a simplification that might benefit from a quick comparison with more physically-based alternatives. 

In addition, various methodological restrictions marginally reduce the extent of the conclusions.  Even though there isn't any radiative data, using a degree-day melt module is still a simplistic guess that doesn't properly show how the energy interactions work in glacier dynamics, especially when things become really bad. A more explicit reference to other, more complex energy-based methodologies, even for comparison reasons, would strengthen the critical depth of the study. 

Response 2: Indeed, in our other study, we compared the glacier runoff estimates from our model with the energy-balance model A-Melt (Pavlyukevich et al., 2025), and the results showed reasonable agreement.

In the Discussion section, we acknowledge the limitations of the simplified degree-day approach in representing the full complexity of glacier melt processes, particularly in extreme scenarios where energy balance dynamics become crucial. We also highlight alternative, more sophisticated methods, such as energy-balance modeling.

However, applying energy-balance models at such a regional scale remains challenging due to the high demand for input data (e.g., radiative fluxes, albedo, turbulent heat fluxes), which are often unavailable across large areas. The degree-day approach offers a practical compromise between accuracy and feasibility in data-scarce regions.

This part of the discussion is presented below: «The temperature-index melt model used in the simulations [69] is too simple and does not account for several key processes influencing glacial melt. Glaciologists are developing more advanced methods of accounting for glacier dynamics on the basis of energy balance, but it is difficult to apply these methods on a regional scale because of the large amount of input data needed. For example, the JULES [70], GLIMB [71] or AMelt [72] models use an energy-balance method in contrast to the index-temperature method. These models require more detailed meteorological data, such as long- and shortwave radiation balance, wind speed, air humidity, and atmospheric pressure data, as inputs. Therefore, simpler approaches are used for regional runoff modeling in large basins [73–75]. To improve accuracy, coupling complex energy-balance glacial and hydrological models that can help predict future discharge changes more reliably is essential, especially in large glacier-fed rivers, where meltwater plays a crucial role. A better representation of glaciers is particularly important for assessing the impact of climate change, especially during warm and extreme years.»

Comment 3: Moreover, the lack of clear coverage of extreme events such as flash floods or glacial lake outburst floods (GLOFs), despite being referenced in the discussion, is a striking omission considering the rising relevance of such occurrences in the Caucasus under the RCP8.5 scenario.

Response 3: The current study focuses specifically on assessing the direct impacts of glacier degradation and climatic changes on river runoff, which is why these extreme events were not covered in detail. However, we fully acknowledge their growing relevance in the Caucasus under the RCP8.5 scenario.

In fact, GLOFs and their impacts are the subject of a separate, ongoing investigation by our team. Previous work (Kornilova et al., 2021) has demonstrated that the influence of GLOFs can be assessed for specific events through a combined approach integrating runoff formation models and hydrodynamic modeling. We plan to expand this methodology in future research to provide a more comprehensive analysis of extreme hydrological events in the region.

Comment 4: The presentation, although generally straightforward, might be improved in specific areas: several complicated figures would benefit from greater clarity through more detailed legends and summary boxes highlighting major anomalies or patterns.  A synthetic map illustrating spatial changes (glaciation, isohyets, gauge placements, sensitive zones) would increase overall knowledge.

Response 4: We are pleased to note that Figure 1 in the original submission already incorporates the key spatial elements mentioned in your feedback, including the distribution of meteorological stations, hydrological gauges, glaciation extent, hydrographic networks, and a digital elevation model of the study region.

Comment 5: In summary, this article offers a solid contribution to hydrological modeling in alpine ecosystems under climate change. It warrants publishing after some minor adjustments, mainly to clarify key statistics, fully express the limitations of the melt model, and add a discussion box in the conclusion outlining the consequences for other analogous glaciated places.

Response 5: Thank you for your positive assessment and constructive feedback. We appreciate your suggestions. In the discussion section, we already address comparisons with other glaciated basins. This part of the discussion is presented below: « Runoff trends in different mountain regions are strongly influenced by the timing of peak water, which is significantly positively correlated with the glacierized area, current ice cover fraction, and basin latitude [63]. In catchments where peak water has not yet occurred, glacier contributions to runoff are expected to continue increasing in the near future because of ongoing glacier mass loss. Conversely, in basins that have already surpassed the peak water phase, a gradual decline in glacier-fed runoff is an-ticipated, reflecting diminishing ice reserves. Studies in high-alpine catchments of the Swiss Alps [64] demonstrate a consistent pattern in glacierized basins: an initial phase of increased annual discharge is followed by a decline, primarily driven by progressive glacier retreat. In addition to glacier dynamics, long-term precipitation trends are also highly important. By the end of the century, a larger fraction of precipitation is ex-pected to occur in liquid form, while the contribution of snowmelt to total runoff will decrease. Similar findings are reported for Himalayan watersheds [65], where in-creased runoff has been observed in both highly and moderately glacierized basins, although for different reasons. In more glacierized basins, runoff growth is driven by intensified glacier melt, whereas in less glacierized areas, increased precipitation plays a dominant role. In the Tien Shan–Pamir–Karakoram region, which encompasses the southern slopes of the Karakoram region and extends into the Himalayas, runoff is projected to increase continuously until the 2050s because of a combination of glacier melt and rising precipitation [66]. According to the research [67] on the interior of Tien-Shan, glacier retreat and snow cover reduction in response to warming have al-ready led to changes in the seasonal structure of runoff, with higher summer‒autumn discharge due to glacial melt and reduced spring runoff traditionally driven by snowmelt.»

Reviewer 3 Report

Comments and Suggestions for Authors

• I recommend explaining the way of calculation for mass balance dynamics of representative glaciers (row 142).
• I recommend changing the formal arrangement of the lines in Figure 6 to make them better distinguishable.
• Is there exists a limitation and any uncertainty of the temperature-index model in comparison to more complex energy balance models?

 

Author Response

Comment 1: I recommend explaining the way of calculation for mass balance dynamics of representative glaciers (row 142).

Response 1: Thank you for your suggestion. We have added references to the relevant studies on the mass balance dynamics of the Djankuat (Popovnin et al., 2024) and Garabashi (Rototaeva et al., 2019) glaciers, which provide detailed descriptions of the applied methodologies.

Comment 2: I recommend changing the formal arrangement of the lines in Figure 6 to make them better distinguishable.

Response 2: Thank you for your suggestion. We have updated Figure 6, making the actual values line bold and dashed for better clarity.

Comment 3: Is there exists a limitation and any uncertainty of the temperature-index model in comparison to more complex energy balance models?

Response 3: In the Discussion section, we acknowledge the limitations of the simplified degree-day approach in representing the full complexity of glacier melt processes, particularly in extreme scenarios where energy balance dynamics become crucial. We also highlight alternative, more sophisticated methods, such as energy-balance modeling. This part of the discussion is presented below: «The temperature-index melt model used in the simulations [69] is too simple and does not account for several key processes influencing glacial melt. Glaciologists are developing more advanced methods of accounting for glacier dynamics on the basis of energy balance, but it is difficult to apply these methods on a regional scale because of the large amount of input data needed. For example, the JULES [70], GLIMB [71] or AMelt [72] models use an energy-balance method in contrast to the index-temperature method. These models require more detailed meteorological data, such as long- and shortwave radiation balance, wind speed, air humidity, and atmospheric pressure data, as inputs. Therefore, simpler approaches are used for regional runoff modeling in large basins [73–75]. To improve accuracy, coupling complex energy-balance glacial and hydrological models that can help predict future discharge changes more reliably is essential, especially in large glacier-fed rivers, where meltwater plays a crucial role. A better representation of glaciers is particularly important for assessing the impact of climate change, especially during warm and extreme years.»