Dear Reviewer,

Thank you for your valuable time and important feedback. We will thoroughly review your comments, integrate the suggestions, and rectify inconsistencies and errors as early as possible. Your insights are essential for enhancing the manuscript. 

Best regards,

Motilal Ghimire

Dear reviewer, Thank you so much for your thorough and detailed evaluation of the manuscript. Your careful, line-by-line examination identified several errors, omissions, and unaddressed aspects within the text, figures, and tables. I have carefully reviewed my manuscript and incorporated almost all of your comments and suggestions. Please find the response to all comments in the PDF document attached herewith. 

Dear Reviewer,

Thank you for your insightful and valuable comments, which I believe have contributed to making the manuscript stronger and more acceptable. We have addressed all comments in the revised manuscript, including adding a validation discussion supported by relevant literature, clarifying the spatial scaling between MODIS and Landsat, conducting a quantitative accuracy and bias assessment, and expanding the uncertainty analysis. Comparisons between MODIS LST and station data, along with their limitations, are now included. Please find the response to comments in the attached document. 

Response to comments and suggestions from Reviewer-4

I read the manuscript by Ghimire et al., since the topic aligns with my interests. The manuscript aims to study snow and glacier dynamics using remote sensing datasets and analyze its relationship with climatic and topographic factors in less studied Karnali basin. While the subject matter is important, I regret to say that the paper is poorly prepared and has several issues regarding the data, methods, analysis, and results that may not meet the standards required for publication. I have several major comments and suggestions about the paper, but please disregard any that overlap with previous reviewers’ feedback.

Response :

We sincerely thank the reviewer for the candid and constructive comments on our manuscript “Dynamics of Snow and Glacier Cover in the Upper Karnali Basin, Nepal: An Analysis of Its Relationship with Climatic and Topographic Parameters.” We appreciate your detailed and critical feedback, which has helped us improve the manuscript. Below, we respond to every point, making sure that overlapping concerns already addressed in our responses to Reviewers 1–3 are not repeated unnecessarily. When relevant, we have revised the text, figures, and tables to improve clarity, methodological rigor, and scientific depth.

The language of the manuscript must be copy edited and polished.

1.    Introduction section: The structuring of the introduction must be improved reducing the over emphasis on social aspects, reviewing the key regional, national and basin scale studies (focus on more recent ones) substantiating with appropriate citations, identifying the gaps and explicitly developing the objectives (currently not stated clearly). Many sentences and paragraph seem unconnected. For example, L52 and L54  

Response: We have carefully revised the manuscript to enhance language, grammar, and overall flow, ensuring greater clarity and conciseness. We have updated the Introduction to reduce unnecessary emphasis on social aspects without avoiding essential socio-economic relevance. Current studies (e.g., Shrestha et al., 2019; Khadka et al., 2024) have been incorporated to place the research in a contemporary scientific context. Existing knowledge gaps, particularly regarding snow glacier dynamics in the mid-western Himalayas, are clearly identified and described. The study objectives are now clearly stated in the final paragraph. Logical linkages between paragraphs have also been improved, removing abrupt transitions noted at L52–L54.

2.    Study area: The study area is transboundary but is merely mentioned [see: (Shrestha et al., 2019; Khadka et al., 2024)]. Why is it focused only on upper Karnali  part and not on other sub-basins of Karnali river system, such as Bheri and West Seti, as these basins also have glacier and snow cover. Although the paper addresses snow cover and glaciers, the description of the study area deviates from the main focus. It should concentrate on providing a clear overview of the key cryospheric components, including state and status of clean and debris-covered glaciers, glacial lakes, and snow. Additionally, while snow and glaciers are affected by weather systems such as the monsoon and westerlies, the paper does not mention the climatology, trends in precipitation and temperature for the region. It is also important to note that several citations are missing; the sources for annual precipitation and temperature data should be included to support the claims made in the paper.

Response: The description of the study area has been revised. The Upper Karnali Basin covers above 50% of the total basin area at Chisapani at 225 m a.s.l., and according to et al. Bajracharya et al. (2011) indicate that this area covers about 66% of the total glacier area in the whole basin. Geologically, the Upper Karnai Basin covers the Lesser Himalaya, Higher Himalaya, and Tethys Himalaya (https://dmgnepal.gov.np/en/pages/general-geology-4128). The Upper Karnai Basin extend across Middle Mountain, High Mountain, High Himalaya and Tibetan Plateau. The climate varies from Polar Tundra in the glacier region to subtropical, temperate, and cold climates below 4000 m, with mean annual temperatures ranging from 27 °C to <- 12 °C and precipitation from 250 to ~ 1900 mm annually. The cryosphere zone of the study area basin encompasses both rain-bearing and rainshadow areas, influencing the distribution of snow and glaciers. Hence, from all the above characteristics, the study area represents the entire basin, including those of other glacier sub-basins such as West Seti and Bheri Basin. 

3.    Data and method: This whole section is not explicit. Authors used Landsat 7, for which date? Landsat 7 have SLC failure after 2003, how were data gaps filled? How much was acceptable cloud cover %? Solely using NDSI and threshold >0.4 is questionable regarding the complexity of the landscape, particularly in mixed pixel scenarios where snow is interspersed with other land cover types and shadows. How were shadows removed or incorporated in optical images? Authors could have combined with other indices (such as NDVI), used automatic image thresholding etc. for improving classification accuracy.

Response: For the analysis of Landsat data, Landsat 7 ETM+ imagery was utilized exclusively for the period preceding the Scan Line Corrector (SLC) failure (2000–2003), with subsequent analyses relying on Landsat 5 TM and Landsat 8 OLI datasets. Only scenes exhibiting less than 20% cloud cover were selected to ensure data quality. To further reduce cloud contamination, the MODIS MOD10A2 8-day composite product was incorporated. Snow cover was delineated using a Normalized Difference Snow Index (NDSI) threshold greater than 0.4, supplemented by Normalized Difference Vegetation Index (NDVI) filtering to reduce misclassification with vegetation, and hillshade masks derived from Digital Elevation Models (DEM) to minimize shadow-related errors. Validation was conducted through visual cross-referencing with high-resolution imagery. 

4.    Why is the month composition of seasons different in this study (L138)? Nepal has four main seasons: post-monsoon (October–November), winter (December–February), pre-monsoon (March–May), and monsoon (June–September) [see, (DHM, 2017; Karki et al., 2020; Sharma et al., 2020)]. This will lead to contrast with previous studies and results can’t be compared; should be justified otherwise recalculation must be done throughout the paper.

Response: We acknowledge the reviewer’s concern regarding the definition of seasons. To improve clarity, we have explained that our grouping (Jan–Mar, Apr–Jun, Jul–Sep, Oct–Dec) reflects the hydrological phases of snow accumulation and ablation and was selected to minimize cloud contamination during the core monsoon period. These intervals largely overlap with the Department of Hydrology and Meteorology’s (DHM) four climatological seasons (post-monsoon, winter, pre-monsoon, monsoon). For example, our Jan–Mar period aligns with DHM’s Dec–Feb winter season, while Apr–Jun corresponds closely to DHM’s Mar–May pre-monsoon season. Thus, our results remain broadly comparable with previous studies while providing a more process-oriented representation of snow cover dynamics in the Upper Karnali Basin.

5.    What is the resolution of LST data used? Was ERA5 Land data checked for bias and performance? These products are utilized for climate analysis that have different spatial resolution. Chen et al. (2021) reports that ERA5 data have limitations in performance in high elevation region. L211;L217: What are those 204 locations? ERA5LAND data is gridded data, why and how 204 sample location is selected? Why not for all areas with maximum snow cover selected for analysis or analysis in different elevation bins not considered? This will lead to incorrect data, analysis and misinterpretation.

Response: Land Surface Temperature (LST) data with a spatial resolution of 1 km were acquired from MODIS Terra (MOD11A1) and Aqua (MYD11A1) via the NASA AppEEARS platform (Wan et al., 2015). Precipitation data were obtained from the ERA5-Land reanalysis dataset at approximately 9 km resolution (Hersbach et al., 2020). A total of 204 well-distributed grid points were chosen throughout the Upper Karnali Basin to represent various sub-basins and elevation zones. This sampling approach enabled us to capture spatial variability in climate trends while avoiding excessive redundancy, considering the coarse resolution of ERA5. It is important to note that ERA5 products have recognized limitations in high-altitude areas (Chen et al., 2021), so they were mainly used for analyzing trend correlations with snow cover rather than for direct validation at specific points.

 To improve representativeness further, additional analyses of LST trends were conducted by grouping results into elevation categories (2000–6000 meters above sea level), which confirmed consistent negative correlations between snow cover and temperature across different altitude ranges.

6.    Glacier mapping: Glacier mapping is a very rigorous task for ensuring correct delineation but it not provided in detail. Did author use seasonal snow free images to delineate glacier boundary? Was debris covered glacier included, if so, how was it delineated, especially for identifying terminus position. For the years 2000 and 2010, it can be obtained from ICIMOD inventories. L166: What’s the name of 12.5 m DEM?

Response: Glacie data from Ghimire et al. (2025), accepted for publication in the Journal for Earth System Science, was used in this study. Glacier boundaries were manually delineated using multi-sensor imagery to ensure accuracy across different time periods and spectral ranges. High-resolution images from Google Earth, Bing Maps, and RapidEye for the years 2000, 2010, and 2023 were combined with multispectral data from Landsat 7–9, Sentinel-2, and ASTER. Visual interpretation was improved by applying band ratios (Red/SWIR, NDSI), color composites (SWIR–NIR–Red), and thermal images to detect debris-covered ice. Topographic information from DEMs and geomorphological features such as moraines, meltwater channels, supraglacial ponds, and ice cliffs further aided the analysis. Glacier termini were digitized following established methods (Bajracharya & Shrestha, 2011; Kääb et al., 2012; Pfeffer et al., 2014), with multi-temporal verification to maintain consistency. Limited field data from the study area and the Khumbu region were used to validate the glacier boundaries. Accumulation zones and ridgelines were identified based on NDSI values above 0.7, spectral composites, and elevation thresholds derived from DEMs. Manual digitization allowed for clear differentiation between glaciers and adjacent snow or rock, resulting in precise glacier outlines.

7.    Results: The section is disorganized and makes it difficult to identify which results correspond to which dataset and analysis. Additionally, the presentation of the results is cumbersome and should be streamlined for better readability. These issue are also mentioned by earlier reviewers too. L185 in which year?

Response: The Result section has been organized and refined in response to the suggestions from the previous reviewer as well. 

L194 Summer monsoon season is considered both accumulation and ablation season in Nepal (see (Wagnon et al., 2013)).

Response: Addressed in previous comments (Comment  4)

8.    Figure 4: Where are trends for other months? Why are lines smoothed?

Response: Addressed in previous comments (Comment  4)

9.    L245 China Karnali: its clear that authors want to mean Karnali originating from China. Since there is no such name it should be described first to clear confusion among readers.

Response: Corrected as Humla Karnali (China) and incorporated 

10.    L267: 100 m for Landsat or MODIS? Fig.7, Fig 8 drawn utilizing which data?

Response:  We have used MODIS data

11.    Section 4.5: the unit of area is presented in ha, suggestion to use consistently throughout the ms, either  sq. km or ha. Glacier basins is unclear and not shown in map anywhere, supplementary can be used in such case.

Response : Corrected 

12.    Discussion: L414—418: The Westerly wind system is more pronounced in the study area, which significantly brings snowfall during winter and pre -monsoon seasons. Though potential shift in precipitation (shift from snow to rain) is noted in Everest Nepal, more analysis is need for study area to claim this. The reduction to snow over in winter might also be due to the weakening of the westerly.

Response: We appreciate the reviewer's comment. While the westerly system does influence winter and pre-monsoon snowfall, unlike Everest, a more detailed local analysis is required to confirm any snow-to-rain transition in our basin. We have clarified this point in the discussion. 

13.    L415: In winter, if the temperature is less than zero then precipitation facilitate snow accumulation.     

Response: We agree and have specified that winter precipitation adds to snow accumulation only if temperatures stay below 0 °C.

14.    Discussion could be strengthened by comparing and contrasting with other regions of Nepal and Himalayas. Some literature suggestions for improvement of discussion and paper (https://doi.org/10.1007/s10113-023-02142-y; https://doi.org/10.1007/s10584-011-0181-y; https://doi.org/10.1016/j.scitotenv.2021.148648; https://doi.org/10.3126/jist.v25i2.33729;  https://doi.org/10.1016/j.earscirev.2019.103043)

(These references and suggested literature are examples from the review process and can be used to enhance the writing. They are not intended solely for citation purposes.)

Response: Thank you for the suggestion. We agree and have added relevant literature to strengthen the discussion and place our findings in the broader cryosphere context of Nepal and the Himalayas.

References 

Bajracharya, S. R., & Shrestha, B. (2011). The status of glaciers in the Hindu Kush-Himalayan region (p. 127). International Centre for Integrated Mountain Development (ICIMOD).

Chen, Y., Sharma, S., Zhou, X., Yang, K., Li, X., Niu, X., ... & Khadka, N. (2021). Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya. Atmospheric Research, 250, 105365.

Ghimire M, Sharma TPP, Chauhan R, Gurung SB, Devkota S, Sharma KP, Shrestha D, Wei Z, Timalsina N (2025) Status and changes in glaciers in the Upper Karnali Basin, West Nepal: assessing topographic influences on area, fragmentation, and volume. J Earth Syst Sci (Accepted). 

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., ... & Thépaut, J. N. (2020). The ERA5 global reanalysis. Quarterly journal of the royal meteorological society, 146(730), 1999-2049.

Kääb, A., Berthier, E., Nuth, C., Gardelle, J., & Arnaud, Y. (2012). Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas. Nature, 488(7412), 495-498.

Karki, R., Hasson, S. U., Schickhoff, U., Scholten, T., Böhner, J., & Gerlitz, L. (2020). Near surface air temperature lapse rates over complex terrain: a WRF based analysis of controlling factors and processes for the central Himalayas. Climate Dynamics, 54(1), 329-349.

Khadka, N., Zheng, G., Chen, X., Zhong, Y., Allen, S. K., & Gouli, M. R. (2024). An ice-snow avalanche triggered small glacial lake outburst flood in Birendra Lake, Nepal Himalaya. Natural Hazards, 1-9.

Pfeffer, W. T., Arendt, A. A., Bliss, A., Bolch, T., Cogley, J. G., Gardner, A. S., ... & Randolph Consortium. (2014). The Randolph Glacier Inventory: a globally complete inventory of glaciers. Journal of glaciology, 60(221), 537-552.

Wan, W., Xiao, P., Feng, X., Li, H., Ma, R., Duan, H., & Zhao, L. (2014). Monitoring lake changes of Qinghai-Tibetan Plateau over the past 30 years using satellite remote sensing data. Chinese Science Bulletin, 59(10), 1021-1035.