Soil and Water Assessment Tool-Based Prediction of Runoff Under Scenarios of Land Use/Land Cover and Climate Change Across Indian Agro-Climatic Zones: Implications for Sustainable Development Goals

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

This study deals with runoff predictions across three diverse Indian watersheds. The paper needs some improvements and lacks as stated below:

1.     The introduction is well-prepared, which provides the research gap, as well.

2.     Line 100, please explain why it is important to conduct this research in diverse agro-climatic zones. I mean you should highlight the contribution of handling diverse agro-climatic regions in the introduction.

3.     Line 174, you should explain what Figure 2 tells us. It is not common just to refer to the Figure.

4.     Line 179, please specify the collection and level of Landsat images. Besides, also state the series of Landsat such as Landsat 5 and Landsat 8.

5.     Line 199, concerning satellite data, we generally use image not photo. Please check and correct all cases in the text.

6.     Line 199-200, please write ArcGIS.

7.     Line 200-201, please check the word “underwent”. Is it correct grammatically?

8.     Line 201, the images are rectified geometrically, not radiometrically or atmospherically. Radiometric or atmospheric corrections are applied to satellite images. Besides, did you apply these corrections? If so, please explain how?

9.     Line 207, please write in the text how you collected validation points.

10.  Line 235-236, these two metrics are not enough to assess the results properly. Thus, please add RMSE, as well.

11.  Line 333, the title is so general that only rainfall and precipitation are not enough to reveal the presence of the climate change. Please change the title.

12.  Line 336-337, please write the time intervals considered in Figure 3. Are the graphs for one year or long term averages? To mention the climate change effects, it is required to analyze long-term climatic variables, at least 25-30 years.

13.  Line 376-378, as stated here, in the future projection studies, firstly you use 2005 and 2011 to simulate the 2017, and then you need to compare the simulated/projected 2017 and the available 2017 maps to provide the accuracies. Here you need to add a new figure to show both of these figures with accuracy of the 2017 projection image. Besides, the horizon between 2017 and 2030 and 2040 is so far. Thus, that means the accuracies of the projected images will be very low. So this issue should also be discussed.

Author Response

Response to Reviewer 1

General Comment: Dear Authors, this study deals with runoff predictions across three diverse Indian watersheds. The paper needs some improvements and lacks as stated below:

Response: Thank you for your valuable feedback and for highlighting areas for improvement in our manuscript. We appreciate the time and effort you have invested in providing detailed comments and suggestions, which have greatly contributed to refining our work. Below, we address each of your points systematically, and the corresponding modifications can be found in the revised manuscript.

Specific comments:

Comment 1: The introduction is well-prepared, which provides the research gap, as well.

Response: Thank you for your positive feedback on the introduction. We are glad that the research gap and context of the study were clearly presented.

Comment 2: Line 100, please explain why it is important to conduct this research in diverse agro-climatic zones. I mean you should highlight the contribution of handling diverse agro-climatic regions in the introduction.

Response: Thank you for your insightful suggestion. We have elaborated in the introduction on the importance of conducting this research in diverse agro-climatic zones. These regions represent varying hydrological, climatic, and land-use conditions, making them ideal for assessing the broader applicability of the findings. Highlighting these variations allows for a comprehensive understanding of runoff dynamics and their implications under changing LULC and climate scenarios, contributing to more effective and regionally tailored sustainable watershed management strategies. The updates can be found in lines [110 -113] in the revised manuscript.

Comment 3: Line 174, you should explain what Figure 2 tells us. It is not common just to refer to the Figure.

Response: Thank you for your constructive comment. We have expanded the explanation in the text to clearly describe the key information conveyed by Figure 2. Specifically, the figure illustrates the stepwise methodology employed in the study, integrating the SWAT model, CA-Markov LULC projections, and RCP-based climate scenarios to assess runoff dynamics. This explanation provides readers with a detailed understanding of the research workflow and its components, avoiding the need to rely solely on the figure. The updates can be found in lines [193-214] in the revised manuscript.

Comment 4: Line 179, please specify the collection and level of Landsat images. Besides, also state the series of Landsat such as Landsat 5 and Landsat 8.

Response: Thank you for your valuable comment. The Landsat images used in this study were obtained from the United States Geological Survey (USGS) Earth Explorer platform. The study utilized Landsat 5 Thematic Mapper (TM) data from 2005 and 2011 and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data from 2017. All images belonged to Collection 1 Level-1. The updates can be found in lines [219 - 217] in the revised manuscript.

Comment 5: Line 199, concerning satellite data, we generally use image not photo. Please check and correct all cases in the text.

Response: Thank you for your meticulous observation. We have reviewed the manuscript thoroughly and replaced all occurrences of the term "photo" with "image" when referring to satellite data. This ensures the terminology aligns with standard practices in remote sensing and scientific writing. The updates can be found in line [245] in the revised manuscript.

Comment 6: Line 199-200, please write ArcGIS.

Response: Thank you for pointing out the need for consistency in naming. We have corrected the text, ensuring the software name is accurately represented throughout the manuscript. The updates can be found in line [248] in the revised manuscript.

Comment 7: Line 200-201, please check the word “underwent”. Is it correct grammatically?

Response: Thank you for your observation. We have carefully reviewed the usage of the word “underwent” in the context of the sentence. It was found to be grammatically correct as used. However, for improved clarity and precision, we have rephrased the sentence to ensure it aligns seamlessly with the context and flow of the text. The updates can be found in line [245] in the revised manuscript.

Comment 8: Line 201, the images are rectified geometrically, not radiometrically or atmospherically. Radiometric or atmospheric corrections are applied to satellite images. Besides, did you apply these corrections? If so, please explain how?

Response: Thank you for your insightful comment. You are correct that geometric rectification was applied to the images to ensure accurate spatial alignment. Additionally, radiometric and atmospheric corrections were performed to enhance the quality and reliability of the satellite imagery. The radiometric correction adjusted pixel values to account for sensor calibration, while the atmospheric correction removed distortions caused by atmospheric conditions. These corrections were applied using ENVI software, following established procedures for satellite data preprocessing. The updates can be found in lines [245-248] in the revised manuscript.

Comment 9:  Line 207, please write in the text how you collected validation points.

Response: Thank you for your thoughtful comment. We have elaborated on the process of collecting validation points in the text. Validation points were obtained from high-resolution satellite imagery and reliable ground-based datasets to ensure the accuracy of the LULC classification. The points were systematically selected to provide comprehensive spatial coverage across the study area and to represent all major LULC classes. This approach ensured a robust and reliable accuracy assessment of the generated LULC maps. The updates can be located in lines [254-258] in the revised manuscript.

Comment 10:  Line 235-236, these two metrics are not enough to assess the results properly. Thus, please add RMSE, as well.

Response: Thank you for your valuable suggestion. In response, we have incorporated the Root Mean Square Error (RMSE) alongside R² and NSE in the evaluation metrics for the calibration and validation phases of the SWAT model. This addition provides a more comprehensive assessment of model performance by addressing both relative and absolute error magnitudes, thereby enhancing the reliability of the results. The updates can be found in lines [289 & 370 -386] in the revised manuscript.

 

Comment 11:  Line 333, the title is so general that only rainfall and precipitation are not enough to reveal the presence of the climate change. Please change the title.

Response: Thank you for your valuable feedback. We have revised the title to better reflect the focus of this section on the analysis of climate change scenarios and their impacts on rainfall and hydrological patterns. The updated title, "Analysis of climate change scenarios on rainfall and hydrological patterns," ensures clarity and aligns with the objectives of the section. The updates can be found in lines [387] in the revised manuscript.

Comment 12: Line 336-337, please write the time intervals considered in Figure 3. Are the graphs for one year or long-term averages? To mention the climate change effects, it is required to analyze long-term climatic variables, at least 25-30 years.

Response: Thank you for your valuable comment. The time intervals considered in Figure 3 have been clarified in the revised manuscript. The graphs represent long-term averages, with the historical period covering monthly averages from 2005 to 2017, and the future scenarios, RCP 4.5 and RCP 8.5, based on long-term monthly averages till 2030 and 2040. This approach ensures the analysis effectively captures long-term climatic trends and reflects the impacts of climate change on rainfall and hydrological patterns. The updates can be found in lines [404 - 407] in the revised manuscript.

Comment 13:  Line 376-378, as stated here, in the future projection studies, firstly you use 2005 and 2011 to simulate the 2017, and then you need to compare the simulated/projected 2017 and the available 2017 maps to provide the accuracies. Here you need to add a new figure to show both of these figures with accuracy of the 2017 projection image. Besides, the horizon between 2017 and 2030 and 2040 is so far. Thus, that means the accuracies of the projected images will be very low. So, this issue should also be discussed.

Response: Thank you for your valuable comment. We have used LULC data from 2005 and 2011 to simulate the 2017 map and compared it with the actual 2017 map, showing perfect matching between the predicted map and the actual map of 2017 with overall accuracy of over 90%. A new figure has been added to the manuscript, showing a comparison of the simulated and actual 2017 LULC maps. Additionally, we have discussed the potential limitations of long-term projections, such as for 2030 and 2040, emphasizing the increasing uncertainties due to dynamic changes in socio-economic and environmental factors over extended temporal horizons. These updates ensure transparency and address the issue of projection accuracy over time. The updates can be found in lines [367-369 & 456-469 & 733-743] in the revised manuscript.

Reviewer 2 Report

Comments and Suggestions for Authors First, I deeply appreciate the development of this paper. In this paper, the authors discussed the relationship between land use and runoff under climate change scenarios in agro-climatic zones of India. This study proposed an interesting approach. The authors focused on three major river basins in India to estimate the impact of climate change on runoff.   1. In the introduction, the authors clearly demonstrated and expressed the research ideas. In addition, the research objectives have been addressed. It is very good. Is it possible to add more recent research works related to the research topic that were published in 2023 and 2024?   2. As for the section of methodology, I am curious whether it is possible to come up with more literature to demonstrate the feasibility of the research methods chosen by the authors?   3. In Section 3, the authors revealed the proportional components of SAP towards specific SDGs. Is it possible to come up with a clearer explanation for this ratio?   4. It is worth providing the research limitations and suggestions for the future-related research.   5. It is worth briefly mentioning the main contribution and originality in the introduction part.   Overall, it is a well-organised paper. It is my honor to review this paper. I wish all the best to authors.

 

Author Response

Response to Reviewer 2

General Comment: First, I deeply appreciate the development of this paper. In this paper, the authors discussed the relationship between land use and runoff under climate change scenarios in agro-climatic zones of India. This study proposed an interesting approach. The authors focused on three major river basins in India to estimate the impact of climate change on runoff.  

Response: Thank you for your positive and encouraging feedback. We are pleased that you found the study’s approach and its focus on the relationship between LULC, runoff, and climate change in India’s agro-climatic zones to be of interest. Your acknowledgment of the methodology and its relevance to understanding the impacts of climate change on major river basins is greatly appreciated. We hope that the insights presented in this paper contribute meaningfully to sustainable watershed management and climate adaptation strategies.

Specific comments:

Comment 1: In the introduction, the authors clearly demonstrated and expressed the research ideas. In addition, the research objectives have been addressed. It is very good. Is it possible to add more recent research works related to the research topic that were published in 2023 and 2024?  

Response: Thank you for your positive feedback and your valuable suggestion to include more recent research works. We have reviewed and incorporated additional studies published in 2023 and 2024 that are relevant to the research topic. These recent works provide updated perspectives on the relationship between LULC, runoff, and climate change, particularly within agro-climatic zones. By including these references, the introduction now reflects the most current advancements in the field and strengthens the context and significance of our study. The updates can be found in lines [73-85] in the revised manuscript.

Comment 2: As for the section of methodology, I am curious whether it is possible to come up with more literature to demonstrate the feasibility of the research methods chosen by the authors?

Response: Thank you for your insightful comment and for emphasizing the importance of demonstrating the feasibility of the research methods. In response, we have included additional references to recent and relevant studies that validate the chosen methods, such as the use of the SWAT model for hydrological simulations, CA-Markov for LULC projections, and climate scenario analysis using RCPs. These references highlight the applicability and reliability of these methods across diverse geographical and climatic settings, thereby reinforcing the methodological framework of our study. The updates can be found in lines [179-214] in the revised manuscript.

Comment 3: In Section 3, the authors revealed the proportional components of SAP towards specific SDGs. Is it possible to come up with a clearer explanation for this ratio?

Response: Thank you for your valuable comment. We have clarified the explanation of the ratio in Section 3. The ratio was calculated by dividing the number of matching targets for a specific SDG by the total number of targets associated with that SDG. This method ensures a proportional representation of SAP contributions toward each SDG, providing a transparent and quantifiable basis for assessing alignment with sustainable development goals. The updates can be found in lines [569 & 579 & 590 & 600 & 611 & 621] in the revised manuscript.

Comment 4: It is worth providing the research limitations and suggestions for the future-related research.

Response: Thank you for your valuable comment. We have added a dedicated section following the conclusion to discuss the research limitations and provide suggestions for future research. The limitations include the focus on only three agro-climatic zones, the restricted fine-scale accuracy due to the resolution of climate and satellite data, and the uncertainties in long-term LULC and climate projections. For future research, we recommend expanding the methodology to encompass additional regions, using higher-resolution datasets, integrating machine learning techniques for enhanced predictive performance, and incorporating sediment data in SWAT calibration to better evaluate erosion dynamics. These suggestions aim to guide future studies towards more comprehensive and sustainable watershed management strategies. The updates can be found in lines [733-743] in the revised manuscript.

Comment 5:  It is worth briefly mentioning the main contribution and originality in the introduction part.

Response: Thank you for your valuable comment. We have revised the introduction to explicitly highlight the main contribution and originality of this study. Specifically, the study addresses the significant research gap in runoff prediction tailored to India’s diverse agro-climatic zones by employing the SWAT model to analyze the Wunna, Bharathapuzha, and Mahanadi watersheds. These watersheds, representing distinct agro-climatic zones with diverse hydrological, climatic, and LULC characteristics, provide a robust framework for assessing the impacts of LULC and climate changes on runoff dynamics. Additionally, this study is the first to evaluate the implications of anticipated runoff changes in agro-climatic regions in relation to the sustainable development goals (SDGs), offering a novel perspective on sustainable watershed management. The updates can be found in lines [105-114] in the revised manuscript.

Overall comment: Overall, it is a well-organised paper. It is my honor to review this paper. I wish all the best to authors.

Response: Thank you for your encouraging and positive feedback. We deeply appreciate your thorough review and kind words. Your insightful comments and suggestions have greatly helped us improve the quality and clarity of the paper. It has been an honor to receive your valuable input.

Reviewer 3 Report

Comments and Suggestions for Authors

This is a very interesting text, with valuable research for identifying water risks in territories under urbanization risk. I suggest some minor modifications that could enhance the article's robustness:

1. The maps in Figure 1 are not very explicit for readers unfamiliar with the specific geographies of India. Adding a more readable regional map is recommended, as the current size makes it difficult to assess.

2. The methodology used shows good innovation, but it seems necessary to situate it within more critical GIS literature, such as PPGIS, Community Mapping, Applied Socio-Spatial Statistics like MGWR, and other alternatives that could provide a differentiating factor to this methodological strategy.

3. The discussion is overly descriptive, likely due to a literature review that did not offer theoretical tools for critically engaging with the findings. I suggest reviewing literature on spatial inequalities, such as water Gini, the Shannon index for environmental hazard distribution, and/or infrastructural inequalities in territories. This is important since the findings present an opportunity for critique that is currently underutilized.

4. I recommend integrating the study's limitations into the conclusions.

5. Figure 6 would benefit from being divided into three separate figures, allowing for a clearer view of the composition of these maps and including the names of the marked areas.

I believe these changes could improve the communication of the research results, foster better dialogue with international literature, and contribute more significantly to knowledge.

Author Response

Response to Reviewer 3

General Comments: This is a very interesting text, with valuable research for identifying water risks in territories under urbanization risk. I suggest some minor modifications that could enhance the article's robustness.

Response: Thank you for your encouraging and constructive feedback. We are pleased that you find the research valuable in identifying water risks in territories under urbanization risk. We appreciate your suggestions and have incorporated the recommended minor modifications to enhance the article's robustness. These revisions aim to improve clarity, strengthen the methodology, and provide more comprehensive insights into the study’s findings. The updates can be found in the revised manuscript, and we hope the changes align with your expectations.

Specific comments:

Comments 1: The maps in Figure 1 are not very explicit for readers unfamiliar with the specific geographies of India. Adding a more readable regional map is recommended, as the current size makes it difficult to assess.

Response: Thank you for your valuable comment. We have revised Figure 1 to include a more detailed and readable regional map. The updated map provides better context by highlighting key geographic features, regional boundaries, and the locations of the study watersheds (Wunna, Bharathapuzha, and Mahanadi) in relation to India’s broader geography. This enhancement ensures improved clarity and accessibility for readers unfamiliar with the specific geographies of India. The updates can be found in lines [139-140] and the revised Figure 1 in the manuscript.

Comments 2:  The methodology used shows good innovation, but it seems necessary to situate it within more critical GIS literature, such as PPGIS, Community Mapping, Applied Socio-Spatial Statistics like MGWR, and other alternatives that could provide a differentiating factor to this methodological strategy.

Response: Thank you for your insightful comment. We have revised the methodology section to situate our approach within broader GIS literature. While tools like public participation GIS (PPGIS) and community mapping excel in participatory decision-making and incorporating stakeholder perspectives, and multi-scale geographically weighted regression (MGWR) is effective for exploring spatial relationships across scales, these methods are less suited for capturing the dynamic interactions between land-use changes, climate variability, and hydrological processes over time. By integrating the SWAT model with cellular automata (CA)-Markov modeling, high-resolution satellite imagery, and RCP-based climate projections, the methodology employed in this study provides a robust framework for assessing runoff patterns. This approach offers a comprehensive understanding of the complex interplay between LULC changes and climate scenarios, making it uniquely effective for addressing water resource management challenges in diverse watersheds. The updates can be found in lines [179-192] in the revised manuscript.

Comments 3: The discussion is overly descriptive, likely due to a literature review that did not offer theoretical tools for critically engaging with the findings. I suggest reviewing literature on spatial inequalities, such as water Gini, the Shannon index for environmental hazard distribution, and/or infrastructural inequalities in territories. This is important since the findings present an opportunity for critique that is currently underutilized.

Response: Thank you for your thoughtful and constructive comment. We have revised the discussion section to incorporate theoretical tools and frameworks such as the water Gini coefficient and Shannon index, as well as references to infrastructural inequalities. These additions provide a more critical engagement with the findings, allowing us to explore spatial disparities in water resource distribution, the uneven impacts of urbanization, and vulnerabilities to hydrological extremes. Specifically, we have used the water Gini coefficient to highlight inequalities in water resource allocation and the Shannon index to analyze the spatial distribution of environmental hazards and the effects of urban expansion on runoff patterns. By situating our findings within these frameworks, we have provided a deeper critique and emphasized the broader socio-environmental implications of the results. The updates can be found in lines [643-713] in the revised manuscript.

Comments 4: I recommend integrating the study's limitations into the conclusions.

Response: Thank you for your valuable suggestion. In response, we have integrated the study's limitations into the conclusion section to provide a balanced perspective. These limitations include the study’s focus on three agro-climatic zones, the restricted fine-scale accuracy due to the resolution of climate and satellite data, and the inherent uncertainties in long-term LULC and climate projections. By incorporating these points, the conclusion now offers a comprehensive summary of the study's contributions while acknowledging areas for improvement and future research directions. The updates can be found in lines [733-743] in the revised manuscript.

Comments 5: Figure 6 would benefit from being divided into three separate figures, allowing for a clearer view of the composition of these maps and including the names of the marked areas.

Response: Thank you for your valuable comment. In response, we have divided Figure 6 into three separate figures, with each figure focusing on one of the watersheds: Wunna, Bharathapuzha, and Mahanadi. This revision provides a clearer and more detailed view of the composition of the maps. Additionally, we have included the names of the marked areas directly on each map to enhance readability and context. These updates improve the accessibility and understanding of the maps for readers. The updates can be found in lines [529-536] and the revised figures in the manuscript.

Overall comment: I believe these changes could improve the communication of the research results, foster better dialogue with international literature, and contribute more significantly to knowledge.

Response: Thank you for your encouraging and constructive feedback. We appreciate your thoughtful suggestions, which have helped us refine the communication of our research results and enhance their alignment with international literature. By incorporating your recommendations, we have strengthened the discussion, improved the presentation of findings, and provided a more robust contribution to the existing body of knowledge. We are confident that these changes will make the study more impactful and accessible to a wider audience.

Reviewer 4 Report

Comments and Suggestions for Authors

Summary

The paper describes a study to predict runoff from three diverse Indian watersheds from climate change scenarios. Using sophisticated methods and analysis the study quantifies the extent of change in the range of land uses and land cover. It then relates these changes to the Sustainable Development Goals.

Assessment

This is an excellent paper and study and the authors are commended for their very clear explanation of the method and the excellent analysis of the changes. The method is scientifically sound and replicable given access to the data which are available from the authors.

The strength of the study lies in the comprehensiveness of the method and its coverage; no weaknesses were detected. Linking the results to the Sustainable Development Goals demonstrates its consideration of the policy implications arising from the study. The discussion and conclusions are consistent with the findings. Limitations to the study are identified but these do not detract from its worth.

The Figures and Tables are clear and it is particularly useful that the location of the watersheds within India is shown in Figure 1. The authors declare no conflict of interest. The English is quite satisfactory. All the references are from the past decade and self-citation is not evident.

Specific Comments

Line 247-259 Bias correction of data. Does this bias correction remove any gradual increase in temperature, precipitation etc due to climate change?

Figure 5 It would assist the reader if the meanings of each of the acronyms were included here.

Author Response

Response to Reviewer 4

Summary: The paper describes a study to predict runoff from three diverse Indian watersheds from climate change scenarios. Using sophisticated methods and analysis the study quantifies the extent of change in the range of land uses and land cover. It then relates these changes to the Sustainable Development Goals.

Response: Thank you for your thoughtful and concise summary of our study. We are pleased that you recognize the study’s aim to predict runoff across diverse Indian watersheds under climate change scenarios and its methodological rigor in quantifying land use and land cover changes. Additionally, we appreciate your acknowledgment of the study's linkage to sustainable development goals (SDGs), which highlights the broader relevance and implications of our research. Your positive feedback reinforces the significance of this work in advancing sustainable watershed management and climate adaptation strategies.

Assessment

Comment 1: This is an excellent paper and study and the authors are commended for their very clear explanation of the method and the excellent analysis of the changes. The method is scientifically sound and replicable given access to the data which are available from the authors.

Response: Thank you for your kind and encouraging feedback. We are delighted that you found the paper to be of high quality, with a clear explanation of the methodology and an excellent analysis of the changes. Your acknowledgment of the scientific rigor and replicability of the method is greatly appreciated. We hope that the availability of the data and the transparent methodology will enable other researchers to build upon our findings and contribute further to this important area of study.

Comment 2: The strength of the study lies in the comprehensiveness of the method and its coverage; no weaknesses were detected. Linking the results to the Sustainable Development Goals demonstrates its consideration of the policy implications arising from the study. The discussion and conclusions are consistent with the findings. Limitations to the study are identified but these do not detract from its worth.

Response: Thank you for your encouraging feedback and for recognizing the strengths of our study. We are pleased that the comprehensiveness of the methodology and its coverage have been appreciated, and we value your acknowledgment of the linkage between our results and the Sustainable Development Goals, which was a key focus of our work. Additionally, we are glad that the discussion and conclusions were found to align well with the findings and that the identification of limitations was seen as constructive without diminishing the study’s value. Your positive assessment motivates us to continue pursuing impactful research in this area.

Comment 3: The Figures and Tables are clear and it is particularly useful that the location of the watersheds within India is shown in Figure 1. The authors declare no conflict of interest. The English is quite satisfactory. All the references are from the past decade and self-citation is not evident.

Response: Thank you for your positive feedback on the clarity of the Figures and Tables. We are glad that you found the inclusion of the watershed locations within India in Figure 1 particularly useful for providing context. We also appreciate your acknowledgment of the satisfactory language quality and the use of recent references, ensuring the study remains current and relevant. Your encouraging comments reinforce the strengths of this study, and we thank you for taking the time to review it thoroughly.

Specific Comments

Comments 1: Line 247-259 Bias correction of data. Does this bias correction remove any gradual increase in temperature, precipitation etc due to climate change?

Response: Thank you for your thoughtful comment. The bias correction method used in this study, specifically the delta change method, does not remove the gradual increase in temperature, precipitation, or other climate change-related trends. Instead, it adjusts the outputs of general circulation models (GCMs) to better match observed local data while preserving the climate change signals. The delta change method works by applying a change factor based on the ratio of future to historical mean values from GCM outputs, which ensures that future projections reflect the local climate attributes and variations. Therefore, while the method corrects for biases such as overestimation of wet days or underestimation of extreme precipitation events, it retains the long-term climate change trends, including gradual increases in temperature and precipitation. This allows the model to accurately incorporate climate change impacts into the hydrological projections. Kindly, see lines [] in the revised manuscript.

Comments 2: Figure 5 It would assist the reader if the meanings of each of the acronyms were included here?

Response: Thank you for your valuable suggestion. We have revised Figure 5 to include the meanings of all acronyms used in the figure. This ensures that the figure is more accessible and user-friendly for readers who may not be familiar with the specific terminology. By providing the full forms of the acronyms, we aim to enhance clarity and improve the understanding of the figure’s content. The updates can be found in lines [458-462 & 465-469] and the revised Figure 5 in the manuscript.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Author,

Thank you for the revisions. The paper now can be pulished after conducting a minor revision. Please add in text how you eliminated SLC-off failure of Landsat / images.

All the best.

Author Response

Response to Reviewer 1

General Comment: Thank you for the revisions. The paper now can be pulished after conducting a minor revision.

Response: Thank you for the positive feedback. We are glad that the manuscript meets the journal’s standards and are committed to promptly addressing minor revisions to facilitate its publication.

Specific comment: Please add in text how you eliminated SLC-off failure of Landsat / images.

Response: Thank you for bringing up this important point. In the revised manuscript, we have included a detailed explanation of how the SLC-off failure in Landsat 7 ETM+ images was addressed. Specifically, we applied an advanced gap-filling technique to ensure data continuity and accuracy using ENVI software. Missing pixel values were reconstructed using spatial interpolation methods that leveraged the spectral properties of neighboring valid pixels, preserving spatial coherence. This method ensured that the reconstructed areas were consistent with the surrounding landscape and maintained the integrity of the spectral and spatial data. The updated description has been added to Section [Satellite data processing], ensuring clarity for readers regarding this aspect of the methodology (See lines [247-253] in the revised manuscript).