Review Reports - Spatial-Temporal Dynamics of Water Conservation in Gannan in the Upper Yellow River Basin of China

Round 1

Reviewer 1 Report

This Manuscript presents interesting research about the application of the InVEST model for the evaluation of the water conservation function of Gannan in the Upper Yellow River Basin. Some corrections are suggested to improve the manuscript further.

- Line 36, in the Introduction, please explain the abbreviation WC – write the full name: water conservation (WC)

- There are some technical error in line 56.

- Line 135, instead of “refreshed” please use more appropriate word like “rescaled”, or “resampled”.

- In Table 2, please explain how you got the values of Kc and the Rooth depth

- Incomplete sentence in line 193.

- Please provide references for the Ecological Function Red Lines.

Author Response

Point 1: Line 36, in the Introduction, please explain the abbreviation WC – write the full name: water conservation (WC).

Response 1: Thanks! We have changed the full name of WC.

We changed the WC to water conservation (WC).

For details, see line 34.

Point 2: There are some technical error in line 56.

Response 2: Thanks! We have modified the technical error.

The main means of improving WC capacity is the search for vegetation types and their allocation patterns that are suitable for the area and increase effective water yield (WY).

For details, see lines 54-56.

Point 3: Line 135, instead of “refreshed” please use more appropriate word like “rescaled”, or “resampled”.

Response 3: Thanks! We have used the suggested appropriate vocabulary.

We have changed refreshed to resampled.

For details, see line 136.

Point 4: In Table 2, please explain how you got the values of Kc and the Rooth depth.

Response 4: Thanks! The following is the source of the values for Kc and Root depths.

Kc: It is calculated according to vegetation type by means of the leaf area index [31], referring to the InVEST manual and the results of existing studies [32].

Root depth: Taken from the China soil data sets checklist, related studies [32] and the InVEST model manual.

Kalma J D, Mcvicar T R, Mccabe M F. Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data[J]. Surveys in Geophysics, 2008, 29. https://doi.org/10.1007/s10712-008-9037-z.

Yang J, Xie B, Zhang D, et al.Climate and land use change impacts on water yield ecosystem service in the Yellow River Basin, China[J].Environmental Earth Sciences, 2021, 80(3). https://doi.org/10.1007/s12665-020-09277-9.

For details, see lines 147-148 and 149-150.

Point 5: Incomplete sentence in line 193.

Response 5: Thanks! We have revised the sentence expression.

The classification method of the importance for WC in Gannan was based on “Technical Guidelines for the Delineation of Ecological Protection Red Line”.

For details, see lines 198-199.

Point 6: Please provide references for the Ecological Function Red Lines.

Response 6: Thanks! We provide references to the ecological function red line.

The classification method of the importance for WC in Gannan was based on “Technical Guidelines for the Delineation of Ecological Protection Red Line” [37,38,39].

Song B, Liangdong J, Hui L I,et al.The Demarcation of Ecological Protection Red Line Based on Water Conversation Function[J].Ecology and Environmental Sciences, 2017. https://doi.org/10.16258/j.cnki.1674-5906.2017.10.004.

Xu D, Zou C, Xu M, et al. Ecological security pattern construction based on ecological protection redlines[J]. Biodiversity Science, 2015, 23(6): 740. https://doi.org/10.17520/biods.2015132.

Li W J, Ma L, Zang Z H, et al. Construction of ecological security patterns based on ecological red line in Erhai Lake Basin of southwestern China[J]. Journal of Beijing Forestry University, 2018, 40(7): 85-95. https://doi.org/10.13332/j.1000-1522.20170074.

For details, see lines 198-199.

Author Response File: Author Response.docx

Reviewer 2 Report

I think that the subject of the article is important, but it will be possible to publish it after some important revisions. These;

1-In the article title, a more attractive and reader-oriented title can be chosen instead of the evaluation word.

2-There is no need to enumerate the results in the summary part (line 19), which expresses the results of the research.

3- In the last sentence of the introduction, the aim of the article should be revised and it should be emphasized why the Gannan region was chosen.

4-The figures of the article should be made clearer.

5-Table 3 and, if any, 3 superscripts in the m3 expression in other points should be 6-What do ) and ( in

6-Table 3 mean? 7-The discussion section can also be compared with different regions. For example;

Yerli, C., & Sahin, U. (2021). An assessment of the urban water footprint and blue water scarcity: A case study for Van (Turkey). Brazilian Journal of Biology, 82.

Muratoğlu, A. (2020). Üretimin su ayak izinin incelenmesi: Diyarbakır ili için bir vaka çalışması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35(2), 845-858.

Muratoglu, A. (2019). Water footprint assessment within a catchment: A case study for Upper Tigris River Basin. Ecological Indicators, 106, 105467.

8- Conclusion section should be developed. More clear and specific outputs should be included.

Since the language of the article is understandable, I don't think it needs any major corrections.

Author Response

Point 1: In the article title, a more attractive and reader-oriented title can be chosen instead of the evaluation word.

Response 1: Thanks! We have revised the title of the manuscript.

Spatial-temporal Dynamics of Water Conservation in Gannan in the Upper Yellow River Basin of China

For details, see lines 2-3.

Point 2: There is no need to enumerate the results in the summary part (line 19), which expresses the results of the research.

Response 2: Thanks! We have amended this sentence.

1) The overall trend of WC capacity in Gannan is increasing during the period 2000-2020.

For details, see lines 18-19.

Point 3: In the last sentence of the introduction, the aim of the article should be revised and it should be emphasized why the Gannan region was chosen.

Response 3: Thanks! We have amended these sentences.

Gannan is located in the upper Yellow River Basin of China, which has large areas of grasslands, forests and wetlands. And It recharges 11.4% of the total runoff of the Yellow River. It has become an important water recharge area for the Yellow River and is an important part of the “Chinese Water Tower” [22,23]. By quantifying its WC function, this study provides a scientific basis for regional envi-ronmental and ecological planning and establishment.

Yao Y, Deng Z, Yin D, et al.Climatic changes and eco-environmental effects in the Yellow River important water source supply area of Gannan Plateau[J].Geographical Research, 2007, 26(4):844-852. https://doi.org/10.1002/jrs.1570.

Min Y, Fen-Zi W. Based on Energy Evaluation for Agricultural Ecological System of Gannan Tibetan Autonomous Prefecture[J]. Research of Agricultural Modernization, 2009, 30(1):95-97. https://doi.org/10.1093/molbev/msn221.

For details, see lines 104-109.

Point 4: The figures of the article should be made clearer.

Response 4: Thanks! We modify the resolution of the images.

Figures 1-8.

Fig. 1. The location of Gannan.

Fig. 2. Interannual variations of annual average precipitation, potential evapotranspiration, actual evapotranspiration, WY and WC in the Gannan from 2000 to 2020.

Fig. 3. Interannual variation of WC in Gannan and 8 watersheds from 2000 to 2020 (DB: Diebe County; HZ: Hezuo City, LT: Lintan County, LQ: Luqu County, MQ: Maqu County, XH: Xiahe County, ZQ: Zhouqu County, ZN: Zhuoni County, GN: Gannan; Red dashed line: linear fit between time and regional WC).

Fig. 4. Interannual variations of WC coefficient in Gannan and 8 watersheds from 2000 to 2020. (DB: Diebe County, HZ: Hezuo City, LT: Lintan County, LQ: Luqu County, MQ: Maqu County, XH: Xiahe County, ZQ: Zhouqu County, ZN: Zhuoni County, GN: Gannan; Red dashed line: linear fit between time and regional WC coefficient).

Fig. 5. Spatial distribution of WY in Gannan from 2000 to 2020.

Fig. 6. Spatial distribution of WC in Gannan from 2000 to 2020.

Fig. 7. Correlation analysis between the WC and the main climate factors (P: precipitation, Ksat: soil saturated hydraulic conductivity, TI: topographic index, AET: actual evapotranspiration, PAWC: plant available water content, ASL: elevation, PET: potential evapotranspiration, V: flow coefficient, SD: soil depth; WR: WC).

Fig. 8. Interannual variations of annual average precipitation (a, d), evapotranspiration (b, e) and WC (c, f) in Gannan.

For details, see lines 131, 218, 230, 248, 264, 274, 295, 300.

Point 5: Table 3 and, if any, 3 superscripts in the m3 expression in other points should be 6-What do) and (in

Response 5: Thanks! We have amended the figures in Table 3.

Table 3 Total amount of WC of different land use patterns in Gannan from 2000 to 2020.

Year	WC of each land use type						Total amount of WC（10⁸m³）
Year	Farmland（10⁸m³）	Woodland（10⁸m³）	Grassland（10⁸m³）	Water（10⁶m³）	Residential area（10⁶m³）	Unused land（10⁸m³）	Total amount of WC（10⁸m³）
2000	1.51（1.81%）	35.70（42.82%）	40.95（49.12%）	0.07（0.08%）	0.04（0.05%）	5.11（6.13%）	83.37
2005	1.77（1.79%）	42.75（43.13%）	48.59（49.02%）	0.08（0.08%）	0.06（0.06%）	5.87（5.92%）	99.12
2010	1.48（1.78%）	34.39（41.44%）	42.12（50.76%）	0.07（0.08%）	0.05（0.06%）	4.87（5.87%）	82.98
2015	1.28（1.73%）	30.85（41.71%）	37.25（50.37%）	0.06（0.08%）	0.05（0.07%）	4.47（6.04%）	73.96
2020	1.91（1.72%）	48.85（44.10%）	53.40（48.21%）	0.11（0.10%）	0.10（0.09%）	6.38（5.76%）	110.76

For details, see line 321.

Point 6: Table 3 mean?

Response 6: Thanks! The following is our interpretation of Table 3.

Table 3 is the total water conservation for different land use types in Gannan from 2000 to 2020.

For details, see line 321.

Point 7: The discussion section can also be compared with different regions. For example;

Yerli, C., & Sahin, U. (2021). An assessment of the urban water footprint and blue water scarcity: A case study for Van (Turkey). Brazilian Journal of Biology, 82.

Muratoğlu, A. (2020). Üretimin su ayak izinin incelenmesi: Diyarbakır ili için bir vaka çalışması. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35(2), 845-858.

Muratoglu, A. (2019). Water footprint assessment within a catchment: A case study for Upper Tigris River Basin. Ecological Indicators, 106, 105467.

Response 7: Thanks! We have added a paragraph comparing it with different regions.

For example, a global assessment of the sensitivity of runoff to changes in precipitation, potential evapotranspiration and other factors is based on the budyko method. The study found that surface water resources are most sensitive to changes in precipitation on a global scale [47]. As WFcrop's WFblue was higher than the world average, it was reduced by changing crop patterns or synchronising crop planting and harvesting dates to periods favourable to precipitation [50]. A bottom-up approach was used to analyse the blue and green water footprints of the Upper Tigris River Basin (UTRB, Turkey) from 2010 to 2018. The results of the study found that reducing evaporation rates, capturing more rainwater and providing more advanced irrigation methods are the main preventive measures to reduce the water footprint of any basin [51]. Based on a comparative study of different regions, climatic factors, i.e. precipitation and evaporation, were found to be the most critical drivers of change in WC [34].

Berghuijs W R, Larsen J R, Emmerik T H M V, Woods R A. A Global Assessment of Runoff Sensitivity to Changes in Precipitation, Potential Evaporation, and Other Factors. Water Resources Research, 2017, 53. https://doi.org/10.1002/2017WR021593.

Yerli C, Sahin U. An assessment of the urban water footprint and blue water scarcity: A case study for Van (Turkey)[J]. Brazilian Journal of Biology, 2021, 82. https://doi.org/10.1590/1519-6984.249745.

Muratoglu A. Water footprint assessment within a catchment: A case study for Upper Tigris River Basin[J]. Ecological Indicators, 2019, 106: 105467. https://doi.org/10.1016/j.ecolind.2019.105467.

Hu W, Li G, Gao Z, et al. Assessment of the impact of the Poplar Ecological Retreat Project on WATER CONSERVATION in the Dongting Lake wetland region using the InVEST model[J]. Science of the Total Environment, 2020, 733: 139423. https://doi.org/10.1016/j.scitotenv.2020.139423.

For details, see lines 372-384.

Point 8: Conclusion section should be developed. More clear and specific outputs should be included.

Response 8: Thanks! We have amended the expression of the conclusion.

Changes in WC function are the result of a combination of climate, soil and land use. The correlation coefficients between the WC and each influence factor are P (0.77) > Ksat (0.14) > V (0.12) > ASL (1.4×10^-16) > TI (1.3×10^-16) > PAWC (-0.02) > SD (-0.2) > PET (-0.62) > AET (-0.63). The southwest and southeast are extremely important WC areas in Gannan (mainly Grade IV and V). We need to give adequate attention and priority to conservation. In the last 20 years, the amount of WC in Gannan has generally shown an increasing trend, and effective measures should continue to be taken to improve the quality of the ecological environment and to enhance water resources protection. Therefore, this study recommends the implementation of an artificial climate project based on ecological restoration in Gannan of the upper Yellow River Basin to effectively monitor climate change dynamics. At the same time, a national nature reserve should be established in the southwestern part of Gannan to expand the ecological protection area center on the southwestern part.

For details, see lines 457-468.

Author Response File: Author Response.docx

Reviewer 3 Report

I would like to thank the authors for their hard work on this manuscript. I have the following comments:

This study applied the InVEST model to assesses the water conservation (WC) function of Gannan, China. The results were presented in term of total average annual WC, spatial distribution of the average annual WC in Gannan from 2000 to 2020, responses of water conservation to key factors including climate factor, land use and land cover as well as spatial classification of the importance of water conservation.

There are many papers have been published with the applying the InVEST model to assess the water conservation in many areas as well as focusing on the similar terms of water conservation. This study just changed the area of the study. Furthermore, the author should incorporate the discussion together with results following the pattern of the academic article. This manuscript is not enough academic contribution and novelty to publish. For improve their manuscript, they should study on knowledge gap of apply the InVEST model for assessing water conservation and present their work following the pattern of academic article.

Comments for author File: Comments.pdf

Author Response

Response: Thanks! We accept your suggestions.

We chose to do a study on the evaluation of the water conservation function of Gannan in the upper Yellow River Basin of China mainly because:

1) There has been little or no previous research on water conservation in the Gannan region. In this study, we chose Gannan in the upper Yellow River Basin of China and used the InVEST model to assess the water conservation function of the area. Gannan is an important water conservation recharge area in the upper Yellow River and an important ecological security barrier for the country. Its special geographical location and ecological status play an irreplaceable role in water conservation and recharge, climate regulation, soil and water conservation, and biodiversity maintenance in the Yellow River Basin. Originating in Qinghai and becoming a river in Gannan, the Yellow River plays a very important role in maintaining the safety of the Yellow River and the ecological security and economic development of the entire basin. The importance of ecological protection and construction in the source area of the Yellow River is not only related to the economic and social development of Gannan, but also to the ecological security and sustainable economic development of the entire Yellow River Basin. We have also referred to this addition in this study.

2) This study not only evaluates the water conservation function of the Gannan region using the InVEST model, but also analyses the drivers of water conservation in the region and classifies the importance of water conservation in the region. This is also reflected in this study.

The details are as follows:

For details, see lines 104-109, 3.3, 4.2 and 4.3.

Author Response File: Author Response.docx

Reviewer 4 Report

Comments for author File: Comments.pdf

The language needs extensive revision.

Author Response

Point 1: The two sentences between line 55 and 56 are incomplete.

Response 1: Thanks! We have modified the error.

The main means of improving WC capacity is the search for vegetation types and their allocation patterns that are suitable for the area and increase effective water yield (WY).

For details, see lines 54-56.

Point 2: The sentence between line 70 and 71 needs reference/citation since it delivers critical message to justify the use the InVEST Model.

Response 2: Thanks! We added references.

Compared to other models, the InVEST model has better data sources and accuracy of results [10,11,12].

Vigerstol K L, Aukema J E. A comparison of tools for modeling freshwater ecosystem services [J]. Journal of environmental management, 2011, 92(10): 2403-2409. https://doi.org/10.1016/j.jenvman.2011.06.040.

Gao J, Li F, Gao H, et al.The impact of land-use change on water-related ecosystem services: a study of the Guishui River Basin, Beijing, China [J]. Elsevier, 2017. https://doi.org/10.1016/j.jclepro.2016.01.049.

Yang D, Liu W, Tang L, et al. Estimation of water provision service for monsoon catchments of South China: Applicability of the InVEST model [J]. Landscape and Urban Planning, 2019, 182:133-143. https://doi.org/10.1016/j.landurbplan.2018.10.011.

For details, see lines 67-68.

Point 3: Line 120: the paper claims that precipitation is high in the study area. However, the 400- 700 mm annual rainfall is not high. Rather it is low.

Response 3: Thanks! We changed the language.

There is more precipitation, and the geographical distribution varies significantly.

For details, see lines 122.

Point 4: In Table 1, the paper stated that topographic index was calculated from DEM and soil depth. However, inclusion of soil depth in this case seems not correct and needs amendment.

Response 4: Thanks! We modified the expression.

Calculations were based on the number of watersheds rasters, soil depth and percentage slopes of the study area, combined with the use of ArcGIS spatial analysis tools.

The topographic index (TI), one of the indicators of water conservation, is calculated as follows:

Among the data needed are the number of watershed grids, the depth of the soil and the percentage slope of the study area.

Wang Y, Ye A, Peng D, et al. Spatiotemporal variations in water conservation function of the Tibetan Plateau under climate change based on InVEST model[J]. Journal of Hydrology: Regional Studies, 2022, 41: 101064.

Li M, Liang D, Xia J, et al. Evaluation of water conservation function of Danjiang River Basin in Qinling Mountains, China based on InVEST model[J]. Journal of environmental management, 2021, 286: 112212.

Yu X X, Zhou B, Yang Z G. Evaluation of water conservation function in mountain forest areas of Beijing based on InVEST model[J]. Scientia silvae sinicae, 2012, 48(10): 1-5.

For details, see line 142.

Point 5: The first sentence of line 193 tends to be a title instead of in-text sentence. It need correction.

Response 5: Thanks! We have revised the sentence expression.

The classification method of the importance for WC in Gannan was based on “Technical Guidelines for the Delineation of Ecological Protection Red Line”.

For details, see lines 198-199.

Point 6: The total area coverage of the study area is not mentioned in the paper.

Response 6: Thanks! We supplemented the study area.

The total area of the region is 4.5×10⁴ km².

For details, see lines 117-118.

Point 7: Table 2 (Line 41): Sources of Kc and root depths are not mentioned and need to be clarified.

Response 7: Thanks! The following is the source of the values for Kc and Rooth depths.

Kc: It is calculated according to vegetation type by means of the leaf area index [31], referring to the InVEST manual and the results of existing studies [32].

Root depth: Taken from the China soil data sets checklist, related studies [32] and the InVEST model manual.

For details, see lines 147-148 and 149-150.

Point 8: The paper presented couple of techniques to generate the water conservation aspects of the region. It also specifies the data required and their sources. Once the methods are specified, the paper needs to show the raw data in a summarized way.

Response 8: Thanks! We accept your suggestion.

Table S1 Raw data on precipitation and potential evapotranspiration

Index/year	2000	2005	2010	2015	2020
Precipitation	505.73	589.88	551.13	472.26	631.51
Potential evapotranspiration	147.35	162.66	204.06	157.70	150.30

Table S2 Raw data on PAWC

ID	T_SAND	T_SILT	T_CLAY	T_OC	T_OM	PAWC
11828	36	43	21	0.65	1.12069	0.176158
11843	36	43	21	0.65	1.12069	0.176158
11860	53	24	23	0.51	0.87931	0.190628
11895	36	43	21	0.65	1.12069	0.176158
11916	34	41	25	1.64	2.827586	0.165421
11918	82	8	10	1.02	1.758621	0.128313
11928	23	54	23	2.09	3.603448	0.129683
12208	44	35	21	0.75	1.293103	0.185689
12212	38	39	23	1.95	3.362069	0.172448
12221	35	43	22	1.37	2.362069	0.16353
12231	35	42	23	1.26	2.172414	0.16574
12256	42	38	20	1.45	2.5	0.173703
12343	15	29	56	2.27	3.913793	0.229909
12346	15	29	56	2.27	3.913793	0.229909
12347	39	39	22	1.65	2.844828	0.170867
12348	39	39	22	1.65	2.844828	0.170867
12359	35	33	32	39.4	67.93103	21.50746
12361	20	40	40	33.63	57.98276	15.49053
12513	56	38	6	1.41	2.431034	0.192053
12519	56	38	6	1.41	2.431034	0.192053
12527	31	49	20	2.02	3.482759	0.151883
12529	37	46	17	3.14	5.413793	0.199006
12532	35	45	20	3.02	5.206897	0.192159
12533	35	45	20	3.02	5.206897	0.192159
12535	46	34	20	1.13	1.948276	0.179877
12560	46	34	20	1.13	1.948276	0.179877
12573	56	38	6	1.41	2.431034	0.192053
12687	41	37	22	0.74	1.275862	0.18343
12717	41	37	22	0.74	1.275862	0.18343
12736	0	0	0	0	0	0.54509

Table S3 Raw data on Ksat

ID	T_SAND	T_CLAY	T_OC	T_OM	T_ECE	T_GRAVEL	S_SAND	S_CLAY	S_OC	S_OM	S_ECE	S_GRAVEL	T	S	Ksat
11828	36	21	0.65	1.12069	0.4	6	34	23	0.43	0.741379	0.3	10	0.49	0.39	53.6448
11843	36	21	0.65	1.12069	0.4	6	34	23	0.43	0.741379	0.3	10	0.49	0.39	53.6448
11860	53	23	0.51	0.87931	0.1	5	47	30	0.3	0.517241	0.2	10	0.49	0.21	42.672
11895	36	21	0.65	1.12069	0.4	6	34	23	0.43	0.741379	0.3	10	0.49	0.39	53.6448
11916	34	25	1.64	2.827586	0.1	4	34	29	0.78	1.344828	0.1	16	0.37	0.22	35.9664
11918	82	10	1.02	1.758621	0.1	10	56	32	0.4	0.689655	0.1	10	2.17	0.16	142.0368
11928	23	23	2.09	3.603448	0.1	4	26	22	0.89	1.534483	0.1	17	0.39	0.35	45.1104
12208	44	21	0.75	1.293103	0.2	14	40	25	0.47	0.810345	0.3	18	0.47	0.3	46.9392
12212	38	23	1.95	3.362069	0.1	2	40	23	0.67	1.155172	0.1	4	0.46	0.45	55.4736
12221	35	22	1.37	2.362069	0.2	3	35	21	0.48	0.827586	0.1	5	0.47	0.5	59.1312
12231	35	23	1.26	2.172414	0.1	3	29	33	0.5	0.862069	0.1	5	0.44	0.11	33.528
12256	42	20	1.45	2.5	0.1	10	45	20	0.5	0.862069	0.1	19	0.53	0.33	52.4256
12343	15	56	2.27	3.913793	0.1	1	24	52	0.81	1.396552	0.1	1	0.06	0.03	5.4864
12346	15	56	2.27	3.913793	0.1	1	24	52	0.81	1.396552	0.1	1	0.06	0.03	5.4864
12347	39	22	1.65	2.844828	0.1	4	37	28	0.69	1.189655	0.1	3	0.48	0.19	40.8432
12348	39	22	1.65	2.844828	0.1	4	37	28	0.69	1.189655	0.1	3	0.48	0.19	40.8432
12359	35	32	39.4	67.93103	0.1	28	52	25	38.46	66.31034	0.1	5	0.13	0.3	26.2128
12361	20	40	33.63	57.98276	0.1	1	47	27	32.89	56.7069	0.1	2	0.14	0.24	23.1648
12513	56	6	1.41	2.431034	0.1	13	0	0	0	0	0	0	1.94	0	118.2624
12519	56	6	1.41	2.431034	0.1	13	0	0	0	0	0	0	1.94	0	118.2624
12527	31	20	2.02	3.482759	0.1	17	37	19	0.84	1.448276	0.1	32	0.42	0.24	40.2336
12529	37	17	3.14	5.413793	0.1	4	33	21	0.8	1.37931	0.1	5	0.69	0.3	60.3504
12532	35	20	3.02	5.206897	0.1	6	0	0	0	0	0	0	0.53	0	32.3088
12533	35	20	3.02	5.206897	0.1	6	0	0	0	0	0	0	0.53	0	32.3088
12535	46	20	1.13	1.948276	0.1	24	0	0	0	0	0	0	0.44	0	26.8224
12560	46	20	1.13	1.948276	0.1	24	0	0	0	0	0	0	0.44	0	26.8224
12573	56	6	1.41	2.431034	0.1	13	0	0	0	0	0	0	1.94	0	118.2624
12687	41	22	0.74	1.275862	0.1	4	37	29	0.36	0.62069	0.1	3	0.49	0.17	40.2336
12717	41	22	0.74	1.275862	0.1	4	37	29	0.36	0.62069	0.1	3	0.49	0.17	40.2336
12736	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Point 9: Line 192-199: Grading on the importance of water conservation variations need scientific justification or reliable source before using it.

Response 9: Thanks! We provided the references.

The classification method of the importance for WC in Gannan was based on “Technical Guidelines for the Delineation of Ecological Protection Red Line” [37,38,39]. In addition, the classification of the importance of WC in Gannan was carried out by combining the quantile classification method in ArcGIS software [40,41].

Xu D, Zou C, Xu M, et al. Ecological security pattern construction based on ecological protection redlines[J]. Biodiversity Science, 2015, 23(6): 740. https://doi.org/10.17520/biods.2015132.

Yubin B, Ting L I, Hui L, et al.Spatial and temporal changes of water conservation of Loess Plateau in northern Shaanxi province by InVEST model[J].Geographical Research, 2016. https://doi.org/10.11821/dlyj201604006.

For details, see lines 198-201.

Point 10: Figure 2 and Figure 3: Having nine figures with almost the same patterns can be merged to one graph with nine distinct regression lines that will reduce the number of pages of the paper on one hand and becomes easy for comparison of the nine watersheds.

Response 10: Thanks!

These two images represent the total water conservation and the water conservation factor respectively, which we could not combine for the following reasons:

1) The two images represent each of the 8 sub-basins and the total basin. It would be more appropriate to divide them into 9 images in order to clarify the trend of increase and decrease in water conservation volume and water conservation factor in different areas.

2) The water conservation volume and water conservation factor in each sub-basin and total basin are different and it would be slightly crowded to put the slope of change formula in one image.

For details, see lines 230 and 248

Point 11: Line 204: the paper claims a significant upward trend on the water conservation of the study area. However, trend analysis is one of the statistical testing techniques and this paper only generate regression line based on five temporal data for which claiming significant trend is not acceptable. At least values of the following variables need to be presented before the result section: (average annual rainfall, average annual potential evapotranspiration, plant available water content, organic matter, Zhang coefficient, and topographic index)

Response 11: Thanks! We give the values of some variables.

The precipitation, potential evapotranspiration, actual evapotranspiration, WY and WC of Gannan from 2000 to 2020 are shown in Fig. 2. The mean annual precipitation in the study area during the study period was 791.44 mm, with an overall interannual trend of a slight decrease in precipitation at a rate of 1.79 mm/a. The mean potential evapotranspiration was 774.78 mm, with an increasing trend over the last 20 years at a rate of 3.29 mm/a. The lowest value of potential evapotranspiration occurred in 2003 (673.20 mm) and the highest value in 2018 (925.86 mm). The mean annual actual evapotranspiration in the basin is 555.22 mm, with relatively stable inter-annual variability and an increasing trend of 0.83 mm/a. Thus, more than 70.15% of the annual precipitation in the basin is returned to the atmosphere through actual evapotranspiration.

Fig. 2. Interannual variations of annual average precipitation, potential evapotranspiration, actual evapotranspiration, WY and WC in the Gannan from 2000 to 2020.

For details, see lines 208-217.

Point 12: The paper general tends to conclude about the significance/insignificance of the trends. But, this is not applicable to this study (as explained above). So, must be corrected (eg. At line 218, 224 and others)

Response 12: Thanks! We corrected the expression.

During this period, the annual average WC in Gannan is about 90.04×10⁸m³, with an overall increasing trend (13.70×10⁸m³/10a). The maximum value was 110.77×10⁸m³ in 2020 and the minimum value was 73.96×10⁸m³ in 2015. The annual mean WC varied considerably between regions, with the highest in the southwest (23.37×10⁸m³) and the lowest in the northeast (2.75×10⁸m³). from 2000 to 2020, there was an overall upward trend in WC in all regions of Gannan. Southwest, northwest and east have more obvious upward trends (3.065×10⁸m³/10a, 2.325×10⁸m³/10a and 2.219×10⁸m³/10a, respectively).

During this period, the average annual WC coefficient for Gannan was 0.462, with an interannual trend similar to the amount of WC, with an overall upward trend (1.48×10^-2/10a).

Among them, the WC coefficients of the southwest and west show a more obvious upward trend (0.83×10^-2/10a and 1.66×10^-2/10a, respectively), indicating that the WC function in these two regions is gradually increasing. In contrast, the WC coefficient for the southeast showed a decreasing trend (-6.45×10^-2/10a), indicating a gradual weakening of the WC function in this region.

Of these, precipitation has a positive effect on WC, presenting a positive correlation to WC (0.77). Actual and potential evapotranspiration had a negative effect on WC, showing a negative correlation with WC (-0.63 and -0.62, respectively).

For details, see lines 222-229, 236-238, 243-247 and 392-395.

Point 13: Figure 7 (Line 278): Correlation coefficient of two of the same variables need to be 1. In figure 7, the correlation between P and P is shown to be 0.82. Similarly between AET and AET as 0.97. How? It does not give sense.

Response 13: Thanks! We have modified the figure.

The correlation coefficient between two identical variables is 1. In this study, when analysing the correlation between P and P and between AET and AET, the correlation coefficient was not 1 because the outliers were not removed when the parameters were entered, so the correlation coefficient has now been corrected.

For details, see line 295.

Point 14: Figure 7 (Line 278): How DEM (digital elevation model) become a variable and subjected to correlation. After all, DEM is not a variable. It shall be corrected as ‘elevation’ in this case.

Response 14: Thanks! We have modified the figure.

For details, see line 295.

Point 15: Figure 7 (Line 278): The figure does not provide scientific evidence to analyze the response of water conservation to key climate factors. It can be removed from the paper.

Response 15: Thanks! We have modified the figure.

For details, see line 295.

Point 16: Recommendations from line 410 –to- 427 are not related to the outputs of the research and tends to be out of the scope. If this study is a consultancy report, these recommendations may work. Otherwise, recommendations shall be emanated from the research itself.

Response 16: Thanks! We revised our recommendations for the study.

By analysing the spatial and temporal characteristics of WC in Gannan and its influencing factors, this study proposes the following countermeasures for promoting natural environmental management and economic and social development in the upper Yellow River Basin. 1) Build grass squares, create shrub belts, fence and seal, replant grass species and zone rotational grazing to improve grassland ecological benefits. 2) Strengthen the restoration and management projects of forest ecosystems, consolidate the achievements of returning farmland to forests and increase the area of vegetation cover. 3) Protect and restore wetland ecosystems, stabilise water recharge in the Yellow River, prevent downstream disruptions and flood storage. 4) Adhere to the ecological red line, implement key natural forest management and conservation projects in the ecological red line area, and carry out the pilot construction of a comprehensive biodiversity observatory and grassland greening observation area.

For details, see lines 439-450.

Point 17: Line 435-to-436: the conclusion section does not need quantity of water conservation. In actual sense, the paper does not have conclusion.

Response 17: Thanks! We have revised the conclusion statement.

Changes in WC function are the result of a combination of climate, soil and land use. The correlation coefficients between the WC and each influence factor are P (0.77) > Ksat (0.14) > V (0.12) > ASL (1.4×10-16) > TI (1.3×10-16) > PAWC (-0.02) > SD (-0.2) > PET (-0.62) > AET (-0.63). The southwest and southeast are extremely important WC areas in Gannan (mainly Grade IV and V). We need to give adequate attention and priority to conservation. In the last 20 years, the amount of WC in Gannan has generally shown an increasing trend, and effective measures should continue to be taken to improve the quality of the ecological environment and to enhance water resources protection. Therefore, this study recommends the implementation of an artificial climate project based on ecological restoration in Gannan of the upper Yellow River Basin to effectively monitor climate change dynamics. At the same time, a national nature reserve should be established in the southwestern part of Gannan to expand the ecological protection area centered on the southwestern part.

For details, see lines 457-468.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Line 384-385; Precipitation in Gannan decreases from southwest to northeast, with the average an- 384 nual precipitation in most areas being around 549 mm (50). I think the reference in this sentence is incorrect. It's worth reviewing again. After this correction, the article is ready for acceptance.

Author Response

Point 1: Line 384-385; Precipitation in Gannan decreases from southwest to northeast, with the average an- 384 nual precipitation in most areas being around 549 mm (50). I think the reference in this sentence is incorrect. It's worth reviewing again. After this correction, the article is ready for acceptance.

Response 1: Thanks! We have revised the cited references.

Precipitation in Gannan decreases from southwest to northeast, with the average annual precipitation in most areas being around 549 mm [52].

Xu Lin, Li Yu, Wang Lili. Study on the Comprehensive Tourism Development Patternin Periphery Minority Area: A Case Study of Gannan Tibetan Autonomous Prefecture of Gansu Province, China. Population, Resources and Environment in China, 2007(3). https://doi.org/10.1080/10042857.2007.10677517.

For details, see line 384-385.

Thank you again for your valuable revision suggestions and your confirmation of our revision reply.

Author Response File: Author Response.docx

Reviewer 3 Report

Thank you very much for your revision version that revised according to the comments and suggestions.

Author Response

Thank you very much again for your valuable revision suggestions and for affirming our revision reply.

Author Response File: Author Response.docx

Reviewer 4 Report

The comments are well addressed.

Author Response

Thank you very much again for your valuable revision suggestions and for affirming our revision reply.

Author Response File: Author Response.docx