Using the Revised Universal Soil Loss Equation and Global Climate Models (CMIP6) to Predict Potential Soil Erosion Associated with Climate Change in the Talas District, Kazakhstan
, Kanat Zulpykharov 1,2,*, Aizhan Assylbekova 3, Nazym Zhengissova 1,3 and Omirzhan Taukebayev 1,3Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis study evaluate the influence of climate change on soil erosion in the Talas area by using the RUSLE model. I think there were many problems to be improved.
Firstly, the structure of this paper was not clear. For example, Introduction part need to be improved. I do not found the objectives of your paper. some paragraphs should be re-constructed.
Why selected RUSLE model? there are so many models in soil erosion.
Comments on the Quality of English Language
This study evaluate the influence of climate change on soil erosion in the Talas area by using the RUSLE model. I think there were many problems to be improved.
Firstly, the structure of this paper was not clear. For example, Introduction part need to be improved. I do not found the objectives of your paper. some paragraphs should be re-constructed.
Why selected RUSLE model? there are so many models in soil erosion.
Author Response
Response:
Thank you for your feedback on our study.
We recognize the need for improvement in the clarity of the Introduction section, particularly in articulating the objectives of the study. In the revised version, we provided a more explicit statement of the study's objectives to enhance understanding. We undertaked a careful reconstruction of paragraphs to ensure a more cohesive and logically flowing structure. This includes refining the Introduction for better readability. In the revised manuscript, we provided explanation for selecting the RUSLE model over other soil erosion models, addressing the rationale behind this choice.
Your feedback is instrumental in refining our work, and we appreciate your engagement.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe topic is quite interesting. English is good. Introduction is well prepared. However, paper is lacking the description of hypothesis and aim of the study. Discussion is too short and superficial. Applied soil classification is outdated. The abstract should be remodelled.
1. I suggest adding a word ‘model’ in the title: “The use of RUSLE and GCMs (CMIP6) models to predict potential soil erosion associated with climate change in the Talas district, Kazakhstan”
2. Use superscript in units, for example ha-1 not ha-1.
3. Instead of ‘square kilometres” use ‘km2’.
4. Line 22: Instead of ‘dangerous’ maybe you should use a term ‘at a moderate risk of erosion’. The area is not dangerous itself.
5. Lines 22-28: You should place these sentences before the results description, they describe the methodology: “The study used data collected from a total of eight weather stations spanning the time period from 1980 to 2014. These data were employed to evaluate the performance of global circulation models (GCMs) as well as an erosion model. The emission scenarios SSP245 and SSP585, which were developed from General Circulation Models (GCMs) including CESM2, GFDLCM4, GFDLCM4gr, IPSL CMA6LR, and NESM3, were used to forecast climatic conditions for three distinct timeframes in the future: 2040 (from 2026 to 2050), 2060 (including the years 2051 to 2075), and 2080 (ranging from 2076 to 2100).”
6. You state that the objective of your study was evaluating the influence of climate change on soil erosion using RUSLE. But the role of GCMs is very unclear.
7. Line 64: I suggest adding ‘mean air temperature’ (if you meant air temperature).
8. The abbreviation RUSTLE has already been explained in line 72, so there is no need to repeat a full name in lines 74—75. Similarly with all other abbreviations. Introduce them once at the beginning and then use abbreviations only. The full name of GCMs was mentioned in lines 83-84, there is no need to describe it again in lines 123 and 124.
9. You need to clearly indicate the hypothesis and objectives of your study in the last paragraph of the introduction section.
10. Line 108: You should write: “…according to Thrasher et al. [28]…”.
11. Line 109: You should include the period for which average temperatures were calculated.
12. Lines 112-113: I suggest adding average temperatures for winter and summer season (at least a ballpark).
13. Figure 1: In figure description you use letters, however they are missing from the picture. Also, pictures described with letter (a) should be placed on the left side of the picture. You should add a name of the country in part (a). Please enlarge the scales because they are illegible in this form. The same with legends. Please add units ( m atsl and mm, I suppose). I suggest changing the symbol of meteorological stations, it’s a little bit confusing and looks like indicator of precipitation.
14. Lines 125-127: Some abbreviations here are different from the abstract. Also, I think you should add here citation of Table A1, where the models are described in detail.
15. Line 165: “tool for forecasting and assessing soil erosion rates within a specific geographical region” you have already said that a couple of times.
16. Table 2: Please be consistent with decimal parts of the numbers, so 43.78, 44.24, 42.83, 43.74 etc. Also indicate directions (north and east). Is it average annual precipitation? What period does it refer to?
17. Lines 197-198: What SN stands for? And SAN?
18. Table 3: What year is this data from? This classification is outdated.
19. Table 4: If you want to place this table here, in the materials & methods section, it should be cited here.
20. Results section should start with the text, not a figure.
21. I think you should remove calculated values of R, K and P factors form materials & methods section – these are results.
22. Figure 2: it should be ‘map’ not ‘maps’. So b) soil erodibility map (singular, not plural). Please add a unit of soil loss.
23. Line 279: Please remove ‘refer to’.
24. Line 288: please remove ‘see’.
25. Lines 290-292: Please remove this sentence, as you have already said that and it belongs to materials and methods: “The cover management factor was determined using the Normalized Difference Vegetation Index (NDVI) in order to enhance the precision of data regarding vegetation cover density.”
26. Similarly lines 296-297: “The factor denoted as P, which represents management practice, was derived based on the land use and land cover (LULC) value of Talas District.”
27. Line 304: Is ‘nation’ the best word here to use?
28. Line 310; Please remove ‘for your perusal’.
29. Line 311: Total of? Your study area?
30. Lines 310-318: How did you choose these categories of soi erosion? Based on what? Also, why 0.07% is not included in classification? And why do you call it hazardous or dangerous? dangerous for who/what? Maybe you should use terms like: no loss, low, moderate, high and very high loss/soil erosion. Lines 315-318 repeat the data from the table. There is no need to describe the same thing twice.
31. Lines 322-345: This part belongs to materials & methods section.
32. Table 7: Please be consistent with decimal parts of the numbers. Also, I suggest explaining abbreviations in the footnote. Why some parts are given in bold?
33. You did not cite figure 3 in the text.
34. Lines 348-349: What is this sentence? Description of fig 3? It is too short to be an independent paragraph.
35. Lines381-382: This sentence should be placed in the discussion section.
36. The discussion section is too short and superficial.
37. Lines 430-438: lines 430-435 and 436-438 basically give the same information. Delete one of these paragraphs.
38. Line 448: Increase of what? Soil erosion? Precipitation? Trend?
Author Response
Response to Reviewer 2 Comments
We would like to thank the reviewer for a careful and thorough reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript.
Comments:
Point 1. I suggest adding a word ‘model’ in the title: “The use of RUSLE and GCMs (CMIP6) models to predict potential soil erosion associated with climate change in the Talas district, Kazakhstan”
Response 1: We added the word "model" to the title of the manuscript.
Point 2. Use superscript in units, for example ha-1 not ha-1.
Response 2: In response to your suggestion, we have revised the manuscript to represent units using superscript.
Point 3. Instead of ‘square kilometres” use ‘km2’.
Response 3: We have made the necessary adjustments throughout the manuscript, and 'km2' is now used consistently to represent square kilometers.
Point 4. Line 22: Instead of ‘dangerous’ maybe you should use a term ‘at a moderate risk of erosion’. The area is not dangerous itself.
Response 4: Thank you for this comment. In response to your recommendation, we have revised Line 22 to “moderate risk of erosion.”
Point 5. Lines 22-28: You should place these sentences before the results description, they describe the methodology: “The study used data collected from a total of eight weather stations spanning the time period from 1980 to 2014. These data were employed to evaluate the performance of global circulation models (GCMs) as well as an erosion model. The emission scenarios SSP245 and SSP585, which were developed from General Circulation Models (GCMs) including CESM2, GFDLCM4, GFDLCM4gr, IPSL CMA6LR, and NESM3, were used to forecast climatic conditions for three distinct timeframes in the future: 2040 (from 2026 to 2050), 2060 (including the years 2051 to 2075), and 2080 (ranging from 2076 to 2100).”
Response 5: We appreciate your keen observation regarding the organization of the manuscript. In response to your comment, we have restructured the manuscript to place the sentences from Lines 22-28 before the results description.
Point 6. You state that the objective of your study was evaluating the influence of climate change on soil erosion using RUSLE. But the role of GCMs is very unclear.
Response 6: Thank you for raising the question. GCMs provide us with crucial climate data, this climate data is fundamental for input into the RUSLE model, as it allows us to simulate and project potential changes in soil erosion patterns under different climate scenarios. By utilizing GCMs, we aim to enhance the accuracy and reliability of our assessments. These models help us capture the broader climate context within which soil erosion processes unfold, offering a comprehensive understanding of how changing climatic conditions may impact soil erosion dynamics.
Point 7. Line 64: I suggest adding ‘mean air temperature’ (if you meant air temperature).
Response 7: In response to your suggestion, we have revised Line 62 to added mention 'mean air temperature' to ensure clarity.
Point 8. The abbreviation RUSTLE has already been explained in line 72, so there is no need to repeat a full name in lines 74—75. Similarly with all other abbreviations. Introduce them once at the beginning and then use abbreviations only. The full name of GCMs was mentioned in lines 83-84, there is no need to describe it again in lines 123 and 124.
Response 8: Thank you for your feedback and suggestion. We will ensure that recommended abbreviations are introduced on lines 74-75, 126-127 etc. to improve readability and avoid duplication.
Point 9. You need to clearly indicate the hypothesis and objectives of your study in the last paragraph of the introduction section.
Response 9: Thank you for your valuable feedback regarding the structure of our study's introduction. We appreciate your attention to detail. In response to your suggestion, we enhanced the last paragraph of the introduction section to explicitly state our hypothesis and objectives.
Point 10. Line 108: You should write: “…according to Thrasher et al. [28]…”.
Response 10: We have revised Line 1115 to : '…according to KazHydromet' as recommended.
Point 11. Line 109: You should include the period for which average temperatures were calculated.
Response 11: Line 115: In response to your suggestion, we have revised the manuscript to include the period for which average temperatures were calculated.
Point 12. Lines 112-113: I suggest adding average temperatures for winter and summer season (at least a ballpark).
Response 12: Line 121: Thank you for your suggestion and we have included average temperatures for both the winter and summer seasons in the revised manuscript.
Point 13. Figure 1: In figure description you use letters, however they are missing from the picture. Also, pictures described with letter (a) should be placed on the left side of the picture. You should add a name of the country in part (a). Please enlarge the scales because they are illegible in this form. The same with legends. Please add units ( m atsl and mm, I suppose). I suggest changing the symbol of meteorological stations, it’s a little bit confusing and looks like indicator of precipitation.
Response 13: Thank you for your detailed observations and suggestions regarding Figure 1. We have changed Figure 1 and corrected all comments (Figure 1. Description of the Study Domain: (a) Kazhydromet spatial distribution of annual average precipitation from 1980 to 2014; (b) Digital Elevation Model (DEM); (c) Land cover and land use).
Point 15. Line 165: “tool for forecasting and assessing soil erosion rates within a specific geographical region” you have already said that a couple of times.
Response 15: Thank you for your comment. We removed the wording at line 166 to ensure clarity while avoiding unnecessary repetition.
Point 16. Table 2: Please be consistent with decimal parts of the numbers, so 43.78, 44.24, 42.83, 43.74 etc. Also indicate directions (north and east). Is it average annual precipitation? What period does it refer to?
Response 16: Thank you for your detailed feedback. We have revised the decimals and included directional indicators (north and east) in Table 2. We have also included information specifying the period covered by this data.
Point 17. Lines 197-198: What SN stands for? And SAN?
Response 17: Lines 199-200: We added the sentence “The equation SN = 1 – SAN/100 represents the relationship between SN and the percentage contents of sand (SAN), silt (SIL), clay (CLA), and organic matter (OM).”
Point 18. Table 3: What year is this data from? This classification is outdated.
Response 18: We've implemented some revisions in paper and we have opted to remove Table 3 from our manuscript.
Point 19. Table 4: If you want to place this table here, in the materials & methods section, it should be cited here.
Response 19: We added a citation for Table 4 in the Materials & Methods section
Point 20. Results section should start with the text, not a figure.
Response 20: Thank you for your valuable input. We appreciate your guidance regarding the organization of the Results section. We will make the necessary adjustment to ensure the Results section begins with descriptive text, providing an introduction before presenting any figures.
Point 21. I think you should remove calculated values of R, K and P factors form materials & methods section – these are results.
Response 21: Thank you for your comment. Based on your suggestion, we made the necessary adjustment and relocate the calculated values of R, K, and P factors from the Materials & Methods section to the Results section.
Point 22. Figure 2: it should be ‘map’ not ‘maps’. So b) soil erodibility map (singular, not plural). Please add a unit of soil loss.
Response 22: In response to your suggestions,we have changed "maps" to "map", "soil erodibility maps" to "soil erodibility map" to reflect the singular form.
Point 23. Line 279: Please remove ‘refer to’.
Response 23: We have removed the word "refer to".
Point 24. Line 288: please remove ‘see’.
Response 24: We have removed the word "see".
Point 25. Lines 290-292: Please remove this sentence, as you have already said that and it belongs to materials and methods: “The cover management factor was determined using the Normalized Difference Vegetation Index (NDVI) in order to enhance the precision of data regarding vegetation cover density.”
Response 25: We have removed the sentence "The cover management factor was determined using the Normalized Difference Vegetation Index (NDVI) in order to enhance the precision of data regarding vegetation cover density".
Point 26. Similarly lines 296-297: “The factor denoted as P, which represents management practice, was derived based on the land use and land cover (LULC) value of Talas District.”
Response 26: This sentence has been removed as well.
Point 27. Line 304: Is ‘nation’ the best word here to use?
Response 27: we have changed the word "nation" to "country"
Point 28. Line 310; Please remove ‘for your perusal’.
Response 28: We have revised Line 313 by removing the phrase 'for your perusal' as suggested.
Point 29. Line 311: Total of? Your study area?
Response 29: Line 314: Thank you for this comment. The phrase "Total of" was intended to introduce the cumulative values related to our study area. We have added the words "of study area".
Point 30. Lines 310-318: How did you choose these categories of soi erosion? Based on what? Also, why 0.07% is not included in classification? And why do you call it hazardous or dangerous? dangerous for who/what? Maybe you should use terms like: no loss, low, moderate, high and very high loss/soil erosion. Lines 315-318 repeat the data from the table. There is no need to describe the same thing twice.
Response 30: We reconsidered our approach and incorporate a more standardized terminology such as "no loss," "low," "moderate," "high," and "very high" for soil erosion levels.
Point 31. Lines 322-345: This part belongs to materials & methods section.
Response 31: line 252-275: We have made the necessary adjustments and relocated Lines 322-345 to the Materials & Methods section for a more coherent presentation of our study methodology.
Point 32. Table 7: Please be consistent with decimal parts of the numbers. Also, I suggest explaining abbreviations in the footnote. Why some parts are given in bold?
Response 32: We ensured consistency in the decimal parts of the numbers in Table 6. We added the sentences : The study used data obtained from a cumulative of eight meteorological stations spanning the years 1980 to 2014. These data were employed to evaluate the performance of global circulation models (GCMs) as well as an erosion model. The aforementioned criteria, namely NSE, RMSE, KGE, and R2, were used to identify the best five GCMs. The top five models namely CESM2, GFDLCM4, GFDLCM4gr, IPSL CMA6LR and NESM3 were selected and highlighted in bold in Table 6. Furthermore, a set of five GCMs (SSP245 and SSP585 emission scenarios) was used to generate three distinct time periods for the purpose of predicting climatic variables that are pertinent to the Talas area. The estimation of potential climatic changes for three distinct time intervals, namely 2040 (2026–2050), 2060 (2051–2075), and 2100 (2076–2100), may be assessed based on the baseline period of 1980-2014.
Point 33. You did not cite figure 3 in the text.
Response 33: We added cite figure 3 in the Line: 338
Point 34. Lines 348-349: What is this sentence? Description of fig 3? It is too short to be an independent paragraph.
Response 34: We modified our manuscript and chanched this sentences. Line: 338-362
Point 35. Lines381-382: This sentence should be placed in the discussion section.
Response 35: Thank you for your feedback regarding Lines 381-382. In the revised version, we ensured to incorporate this sentence appropriately within the discussion section. Line: 414-416
- The discussion section is too short and superficial.
Response 36: Thank you for your feedback. We acknowledge the observation that it may be perceived as too short and superficial. We revised and expanded the discussion, providing a more analysis of the results, their implications, and potential avenues for further research.
Point 37. Lines 430-438: lines 430-435 and 436-438 basically give the same information. Delete one of these paragraphs.
Response 37: We deleted Line: 436-438
Point 38. Line 448: Increase of what? Soil erosion? Precipitation? Trend?
Response 38: Thank you for your comment. We added in Line 457 :“average erosion”
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for Authorsplease find my remarks in the attached pdf file
Comments for author File: Comments.pdf
Author Response
Response to Reviewer 3 Comments
Thank you for your detailed and positive assessment of our paper. We sincerely appreciate your thoughtful comments and constructive feedback. We are pleased to hear that you found the design of the paper sound, the exposition clear, and the comparison of various climate forecast models valuable.
Your acknowledgment of the paper's value and the clarity of its presentation are encouraging. We are committed to addressing your feedback and improving the paper further.
Reviewer 4 Report
Comments and Suggestions for AuthorsThe manuscript estimated the potential soil erosion in the Talas dis-3trict, Kazakhstan at different stages in the future, based on the RUSLE model and CMIP6 climate data. The author had done a lot of work, and the results provide useful information to carry out soil and water conservation work i in the Talas dis-3trict, Kazakhstan. However, some parts of the manuscript still need to be improved. My specific comments and suggestions are detailed below:
1) In the abstract section, the main research findings of this study should be provided, clearly indicating the spatial distribution characteristics of potential soil erosion.
2) In the introduction section, the feasibility of using GCM model data for this study should be demonstrated, and it should be pointed out in which studies the model data has been adopted in the past.
3) In the introduction section, it is recommended to include the relevant introduction of Kazakhstan in section 2.1.
4) In the introduction section, it should be clearly pointed out the purpose and innovation of this study, as well as the shortcomings of previous research.
5) In section 2.1, the terrain, geomorphology, and vegetation characteristics of the study area should be introduced.
6) The font in the figures in this study is too small, it is recommended to make new modifications.
7) The language tense in the manuscript should be carefully checked.
8) It is recommended to draw Taylor plots to compare the differences in potential soil erosion caused by different climate models.
9) It is suggested that the discussion part be divided into 2-3 themes for detailed discussion.
10) In the conclusion part, it should be further streamlined to highlight the main conclusions of this study.
Comments on the Quality of English LanguageNo
Author Response
Response to Reviewer 4 Comments
We would like to thank the reviewer for a careful and thorough reading of this manuscript and for the thoughtful comments and constructive suggestions, which help to improve the quality of this manuscript.
Comments:
Point 1. In the abstract section, the main research findings of this study should be provided, clearly indicating the spatial distribution characteristics of potential soil erosion.
Response 1: Thank you for your comment. We have added the sentence: Also, the spatially distributed result showed that the southern part of the territory of the Talas region has been confirmed by great erosion over the historical and also for the future period.
Point 2. In the introduction section, the feasibility of using GCM model data for this study should be demonstrated, and it should be pointed out in which studies the model data has been adopted in the past.
Response 2: Thank you for your feedback. In response to your comment, we have made the following additions: Multiple studies have investigated climate patterns in Central Asia at different scales, employing various climate models. Gao et al. [33] assessed precipitation outputs from 30 Global Circulation Models (GCMs) under the Coupled Model Inter-comparison Project Phase 6 (CMIP6) from 1951 to 2014, focusing on six climate zones in arid Central Asia. Duulatov et al. [11] used GCMs from CMIP5 to assess rainfall changes for radiative concentration pathways (RCPs) 2.6 and 8.5. Ta et al. [34] employed CMIP5 to evaluate the ability of 37 GCMs to simulate historical precipitation in Central Asia. Gulakhmadov [35] et al. used five GCMs from CMIP5 to project precipitation (Pr), maximum temperature (Tmx), and minimum temperature (Tmn) in the Vakhsh River Basin of CA for RCPs 4.5 and 8.5. Salehie et al. [36] selected CMIP6 GCMs to project climate changes over the Amu Darya River Basin. Gafforov et al. [37] utilized CMIP5 (RCPs 4.5 and 8.5) to evaluate the impact of climate change on rainfall-runoff erosivity in the Chirchik–Akhangaran Basin, Uzbekistan. Golian et al. [30] used CMIP6 models to assess future climate change effects on mine sites in Kazakhstan, considering Shared Socioeconomic Pathways (SSPs) 245 and 585. Lei et al. [38] evaluated CMIP6 models and a multi-model ensemble (MME) for extreme precipitation over arid Central Asia. These studies collectively contribute to our understanding of climate variability and change in Central Asia, utilizing a range of models, scenarios, and assessments focused on different aspects of the climate system. For the initial time in the Talas region, the study evaluates anticipated alterations in future precipitation using the recent CMIP6 models for the Revised Universal Soil Loss Equation (RUSLE).
Point 3. In the introduction section, it is recommended to include the relevant introduction of Kazakhstan in section 2.1.
Response 3: Thank you for this comment. In response to your recommendation, we have added: The Talas district, with Karatau as its administrative center, is a constituent part of the Zhambyl region in the southern area of Kazakhstan. The district comprises a total of 24 settlements, which are organized into 13 rural districts. The study area possesses several distinctive geographical characteristics and is situated within the Talas district of the Zhambyl region.
Point 4: In the introduction section, it should be clearly pointed out the purpose and innovation of this study, as well as the shortcomings of previous research.
Response 4: Thank you for your feedback. The purpose of this study is to assess the current state of soil erosion using the RUSLE model and a combination of global climate models under CMIP6 in the Talas region of Kazakhstan. To the best of our knowledge, similar studies using a combination of the RUSLE model with the CMIP6 have not yet been conducted in the Talas region of Kazakhstan in Central Asia.
Point 5: In Section 2.1, the terrain, geomorphology, and vegetation characteristics of the study area should be introduced.
Response 5: Thank you for your feedback and suggestions. In response to your suggestion, we have added: The Talas region can be described in geomorphological terms as follows: the southern part is characterized by mountains, specifically the Karatau mountain range, while the northern part is predominantly flat, consisting of the accumulative and denudation plains of the Shu-Sarysu depression situated on the Turan plate. The southwestern mountainous boundary of the region is characterized by the Karatau mountain system, which is a mid-mountain relief formed by tectonic-denudation processes 120. The soil and vegetation cover, as well as the current natural systems in the research region, are directly influenced by the prevailing meteorological conditions. The mountainous part of the region is characterized by arid mountain steppes situated atop undulating plains. The dominant soil types in the mountainous regions are mountain gray-chestnut and mountain gray soils. In the intermountain valleys, the predominant soil types are light northern gray soils and meadow gray soils. The soils in the flat region developed under arid desert circumstances and are characterized by meadow-gray soils in the slopes. To the north, there were further occurrences of gray soils referred to as northern light gray soils. The valley of the Talas River contains meadow soils, which are occasionally accompanied by light brown tacro-like soils in certain areas. Moyynkum is a desert characterized by sandy terrain, where the absence of surface moisture hinders the development of soil, resulting in a predominance of sandy substrate. Depressions contain soils that are either takyr or takyr-like. The primary forms of vegetation consist of mountain wormwood, steppes, and phryganoids, which are upland xerophytes.
Point 6 The font in the figures in this study is too small, it is recommended to make new modifications.
Response 6: Thank you for bringing attention to the font size in the figures. We made the necessary modifications to increase the font size in the figures.
Point 7. The language tense in the manuscript should be carefully checked.
Response 7: Thank you for your feedback. We reviewed and corrected the language tense throughout the manuscript to ensure consistency and clarity.
Point 8. It is recommended to draw Taylor plots to compare the differences in potential soil erosion caused by different climate models.
Response 8: Thank you for your suggestion. We implemented this recommendation in the revised manuscript.
Point 9. It is suggested that the discussion part be divided into 2-3 themes for detailed discussion.
Response 9: The utilization of the Revised Universal Soil Loss Equation (RUSLE) inside arid and semi-arid environments might provide distinct outcomes that hold significance in comprehending and effectively addressing soil erosion in such areas [10, 11, 55]. Our examination of the existing state of soil erosion in the Talas area, employing the RUSLE model, has provided valuable insights into the magnitude and spatial distribution of erosional processes. Central Asia is susceptible to the adverse effects of climate change, including heightened variability in precipitation, severe weather issues, and droughts [8, 57]. Also, arid and semi-arid regions exhibit heightened susceptibility to soil erosion as a consequence of factors such as restricted plant coverage, irregular and strong precipitation patterns, and delicate soil characteristics [56]. The alterations in the magnitude and volume of precipitation are mostly influenced by the intricate mechanisms of the hydrological cycle inside the Earth's atmosphere [17, 57]. These modifications may lead to alterations in precipitation patterns, such as an increase in the intensity of rainfall events in some areas and the occurrence of lengthy periods of drought in others [18]. Precipitation patterns may also show seasonal and regional variations. Areas with higher erosion risk can receive priority for re-vegetation or terracing, while areas with lower risk can be conserved as they are. The process of soil erosion modeling is inherently complex due to the geographical and temporal variability of soil loss, which is influenced by several elements and their intricate interrelationships. When making predictions about soil loss in unfamiliar areas, it is crucial to possess knowledge of both the estimations and the corresponding uncertainty. Multiple studies have shown that erosion densities beyond a value of 1 result in a higher occurrence of precipitation erosion compared to precipitation activity [53, 54]. Rainfall erosivity, the power of rainfall to cause soil erosion, is an essential factor in soil erosion studies [58]. In the context of climate change, understanding and modeling the relationship between rainfall erosivity and shifting climate patterns is critical for effective soil conservation and land management. The findings of our research indicate that the subject region exhibits a susceptibility to water erosion. The mean annual R coefficient demonstrated comparable values across various Global Climate Models (GCMs). Consequently, the observational data consistently rose in the southern regions. Various global studies consistently demonstrate an increase in rainfall throughout different time periods and geographical areas [59]. These fluctuations are probably associated with changes in the frequency and intensity of precipitation, rising temperatures, and changes in land use. This susceptibility to water erosion in the studied region underscores the importance of addressing the evolving climate patterns for sustainable soil conservation and land management practices. As climate change continues to exert its influence, understanding the intricate dynamics of rainfall erosivity becomes a cornerstone in developing effective strategies to mitigate soil erosion. The mean annual R coefficient, exhibiting comparable values across various Global Climate Models (GCMs), adds a level of robustness to our findings. This consistency suggests that, despite variations in model outputs, there is a coherent trend in the susceptibility of the region to water erosion. Numerous studies have characterized and evaluated soil erosion in Central Asia and our results coincide with the results of the above studies, with specific focus by Duulatov et al. [11], Mukanov et al. [10] and Gafforov et al. [55], conducted the assessment at the Central Asian scale. The incorporation of climate projections from the CMIP6 GCM enhances the pre-dictive capacity of our study. By integrating climatic data into the RUSLE model, we can simulate and anticipate potential alterations in soil erosion patterns under varying climatic scenarios. In our future research, can be create hydrological models to assess soil erosion under different land use types.
Point 10. In the conclusion part, it should be further streamlined to highlight the main conclusions of this study.
Response 10: Thank you for your feedback. We have revised the conclusion: This study utilized observational data spanning 35 years and the RUSLE model with a combination of several GCMs to estimate soil erosion and evaluate the impact of various factors, including precipitation, soil characteristics, topography, land use, and conservation efforts, on erosion susceptibility in the Talas District. The findings indicate that the mean annual soil erosion rate observed over the study period ranges from 0 to 127 (t y^ (-1)). Approximately 56.29% of the study area exhibits a low susceptibility to soil erosion, with an additional 33.56% classified as a moderate risk and 7.36% deemed at high risk of erosion. Additionally, the main General Circulation Models (GCMs) used for the SSPs 245 and 585 were evaluated, focusing on temporal spans for the near and far future—specifically, 2040 (2026-2050), 2060 (2051-2075), and 2080 (2076-2100). The assessment revealed a moderate increase in precipitation levels compared to the reference point, with predicted growth rates of 21.4%, 24.2%, and 26.4% for the years 2030, 2050, and 2070, respectively. Moreover, the research highlighted a positive correlation between soil erosion and precipitation, evidenced by a proportional increase in average erosion of 34%, 35.5%, and 38.9% during the respective time periods. The integration of the RUSLE and GCMs furnishes actionable insights, empowering scientists and stakeholders to make informed decisions regarding land management, conservation, and climate resilience.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper evaluate the current state of soil erosion by using RUSLE model and CMIP6 climate model. I think there is little novelty and some problems to be addressed. In Introduction section, its objectives is not distinct. what questions you want to resolve is not clear.
1. In line 88, a period is missed.
2. Is there only two meteoreogical stations in this study aea? (Fig.1)
3. Section 2.3 and 2.5 is too long, I think you can make it short.
4. In Fig.2, the acuuracy of numbers should be consistent.
5. In Fig3 and Fig4 and Fig5, I cannot see the difference among most of the figures dervied from different models.
Comments on the Quality of English Language
it needs to be improved.
Author Response
Response to Reviewer 1 Comments
Comments:
This paper evaluate the current state of soil erosion by using RUSLE model and CMIP6 climate model. I think there is little novelty and some problems to be addressed. In Introduction section, its objectives is not distinct. what questions you want to resolve is not clear.
We would like to thank the reviewer for a careful and thorough reading of this manuscript. The purpose of this study is to assess the current state of soil erosion using the RUSLE model and a combination of global climate models under CMIP6 in the Talas region of Kazakhstan. To the best of our knowledge, similar studies using a combination of the RUSLE model with the CMIP6 have not yet been conducted in the Talas region of Kazakhstan in Central Asia.
- In line 88, a period is missed.
Response 1: Thank you for bringing this to our attention. We corrected the missing period in line 88.
- Is there only two meteorological stations in this study area? (Fig.1)
Response 2: Thank you for your feedback. We have two meteorological stations within our territory. Consequently, we opted to utilize nearby stations.
- Section 2.3 and 2.5 is too long; I think you can make it short.
Response 3: Thank you for your feedback. We reviewed some sentences and subsequently excluded them.
- In Fig.2, the accuracy of numbers should be consistent.
Response 4: Thank you for your suggestion regarding Figure 2. We made the necessary adjustments.
- In Fig3 and Fig4 and Fig5, I cannot see the difference among most of the figures derived from different models.
Response 5: Thank you for this comment. To avoid uncertainties and biases in future soil erosion predictions, statistical correlation techniques were used to select the best-fitting model that shows greater correlation when compared with historical observational data.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors did a great job improving the article. They answered all my questions and made the suggested changes. Congratulations. I strongly recommend the publication of this manuscript.
Author Response
Response to Reviewer 2 Comments
Thank you very much for your positive feedback! We're pleased that you are satisfied with the improvements made to the article. Your comments and questions were valuable in refining the manuscript. We appreciate your recommendation for publication and are grateful for your support.
Round 3
Reviewer 1 Report
Comments and Suggestions for AuthorsI still think there is no novelty in this paper. The authors also did not know how to organize a research paper.
Comments on the Quality of English LanguageI still think there is no novelty in this paper. The authors also did not know how to organize a research paper.
