Next Article in Journal
Estimation of Leaf Inclination Angle in Three-Dimensional Plant Images Obtained from Lidar
Previous Article in Journal
Content-Sensitive Multilevel Point Cluster Construction for ALS Point Cloud Classification
Previous Article in Special Issue
Satellite-Based Water Consumption Dynamics Monitoring in an Extremely Arid Area
Open AccessArticle
Peer-Review Record

Monitoring 40-Year Lake Area Changes of the Qaidam Basin, Tibetan Plateau, Using Landsat Time Series

Remote Sens. 2019, 11(3), 343; https://doi.org/10.3390/rs11030343
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Remote Sens. 2019, 11(3), 343; https://doi.org/10.3390/rs11030343
Received: 27 December 2018 / Revised: 31 January 2019 / Accepted: 2 February 2019 / Published: 9 February 2019

Round 1

Reviewer 1 Report

I would like to thank authors for providing detailed additional analysis, I think that after revision it is clear that this work is relevant and is worth publication in Remote Sensing journal.

In my opinion, the only unresolved issue is the impact of coarse resolution of MSS imagery. I urge authors for a more detailed analysis of it


P3 L113-116: Again, what impact has coarser resolution of MSS imagery on small glaciers and lakes delineation? Cited work [30] says explicitly that such downscaling does not provide any additional information "Although the spatial information cannot be truly downscaled, pixel size of these MSS images is consistent with other Landsat images." and "Furthermore, the most notable limitation which could be the initial source of inconsistency of classification is the different spatial resolution of remote sensing data. Although we have standardized the dataset to a pixel size of 30 m × 30 m, the coarse spatial resolution of MSS data (60 m × 60 m) in the years of 1973 and 1979 cannot be truly resampled to smaller spatial resolution. As a result, patches in the classification maps of 1973 and 1979 are relatively coarser than other maps. Meanwhile, small patches of mangroves in 1973 and 1979 have been neglected or recognized as large ones which also cause errors of landscape metrics. Moreover, because the study areas are relatively small, newly grown small patches in the two reserves may cause high fluctuations of some landscape metrics."

P11 L324: "retreated" - change to decreased

P16  L486: "retreating"

Author Response

1.       P3 L113-116: Again, what impact has coarser resolution of MSS imagery on small glaciers and lakes delineation? Cited work [30] says explicitly that such downscaling does not provide any additional information "Although the spatial information cannot be truly downscaled, pixel size of these MSS images is consistent with other Landsat images." and "Furthermore, the most notable limitation which could be the initial source of inconsistency of classification is the different spatial resolution of remote sensing data. Although we have standardized the dataset to a pixel size of 30 m × 30 m, the coarse spatial resolution of MSS data (60 m × 60 m) in the years of 1973 and 1979 cannot be truly resampled to smaller spatial resolution. As a result, patches in the classification maps of 1973 and 1979 are relatively coarser than other maps. Meanwhile, small patches of mangroves in 1973 and 1979 have been neglected or recognized as large ones which also cause errors of landscape metrics. Moreover, because the study areas are relatively small, newly grown small patches in the two reserves may cause high fluctuations of some landscape metrics."

[Response]: Thank you so much for this comment. We acknowledged the coarse spatial resolution of MSS data may have influences on delineating the extent of lake and glacier resulting in lower classification accuracy. However, in terms of lake numbers, we believe that coarse resolution of MSS data only has limited influence. We acknowledged this limitation in our study and added several sentences in Section 4.1 Uncertainties (highlighted in red):

“The most significant limitation comes from the different spatial resolutions of remotely sensed data acquired in different stages, which leads to the spatial inconsistency of initial classification results. The patches derived from MSS images contained many mixed pixels, resulting in a lower mapping accuracies and a higher uncertainty of the lake and glacier extent in 1977 (Table 3). With the limited resolution of MSS images in 1977, the smallest unit of objects identified from the image segmentation was determined as 0.036 km2. It means that the lakes smaller than 0.036 km2 failed to be captured in 1977. However, we focused on the lakes larger than 0.05 km2, meaning that the coarser spatial resolution has no substantial influence on the statistical analysis of lake number.”

   Thanks again for your valuable comment.


2.       P11 L324: "retreated" - change to decreased

[Response]: Thank you for this comment and “retreated” has been change to “decreased” in the revised manuscript.

 

3.       P16  L486: "retreating"

[Response]: Thank you for this comment and “retreating” has been change to “retreat” in the revised manuscript.

 


Author Response File: Author Response.docx

Reviewer 2 Report

Major comments

Line 402: In the uncertainties section, the authors did focus on the impact of the different spatial resolutions used. They failed to discuss the impact of the instrument change (evolution of Landsat instrument through the period of study from Landsat 2 to Landsat 8) on their analysis.  It is better to give the readers a clear picture by adding one paragraph and citing papers related to that.

It is important to mention why these specific years were selected. Most of your text refer to the change of period as decadal. However, the first time frame is 13 years (1977-1990) and the last is 15 years (2000-2015). In addition, it is very important to check the cycle of the climate indices that significantly affect the climate of the region. For instance based on the Oceanic Nino Index (ONI), years of 1976, 1989 and 1990 are years of strong La Nina and 2015 was year of very strong El Nino event. I am not suggesting that the atmospheric indices ENSO have a significant impact on the region but it is very important to check. My point is the year selection can cause a bias to your outcome.

In your manuscript, it was indicated that the lake size was increased especially from 2000 to 2015. In the same time frame the PET was reduced significantly (figure 6 i). Can you explain where the source of water for the lakes is (MAP remains the uniform)? Is it from melting of the glaciers? Is there a ground water flow to the lakes?

Minor comments

Line 259 However, the lakes expanded the most significantly during the last period. Change the sentence with more appropriate one and to be clear add the timeframe (2000-2015).

Figure 4.  add title axis for the secondary axis.

From 306 1990 to 2000, the MAAT increased considerably with an average rate of 0.94 °C/10 yr, much higher 307 than that of the first period (Figure 6e). Please use the same unit (°C/10 yr or °C/1 yr) because it can mislead the readers.

Line 310: In the later 2000~2015 period, the rate of  MAAT increase was less than that in the previous two periods (Figure 6f). Please revise the sentence.

Line 377 the explanation given to the increase of the lake size due to mining of lithium seems to be weak. By building dam the companies are shifting the water from one place to another and this will lead to loss of water (due to infiltration and evaporation). In addition the companies are mining from the salt lake which leads to dry the salt lake. Both scenarios seem to contradict the conclusion made i.e. increase in the overall lake size.

Line 528  similar to the above comment.


Author Response

We thank the reviewer very much for the constructive comments on our manuscript. We have carefully considered all of the comments in further revised manuscript. Point-by-point responses to each comment are as follows:

 

Major comments:

1.       Line 402: In the uncertainties section, the authors did focus on the impact of the different spatial resolutions used. They failed to discuss the impact of the instrument change (evolution of Landsat instrument through the period of study from Landsat 2 to Landsat 8) on their analysis.  It is better to give the readers a clear picture by adding one paragraph and citing papers related to that.

[Response]: Thank you so much for this valuable comment. We agree on that evolution of Landsat instruments from Landsat 2 to Landsat 8 may influence our time series analysis. We have added several texts and cited related studies in Section 4.1 Uncertainties (highlighted in red) to address this comments. Detailed texts are as follows: 

 

“Landsat images are constantly improving due to new generations of satellites being launched with enhanced sensors [52]. The improvements are mainly manifested in the richness of spectral, spatial and radiometric resolution [53]. A plenty of studies reported result comparisons of different Landsat images in land cover classification. Landsat TM images were proved to be superior to Landsat MSS images and Landsat ETM+ images were superior to Landsat TM. Recent studies indicated Landsat OLI performed better than all the previous version of Landsat images. The findings in these studies were quite consistent with our results (Table 3). In addition, minor differences in wavelength exist between the same bands from different Landsat sensors, which might result in inconsistent threshold values of NDVI in different time periods and might further impact on the lake extraction results in this study.”

 

2.       It is important to mention why these specific years were selected. Most of your text refer to the change of period as decadal. However, the first time frame is 13 years (1977-1990) and the last is 15 years (2000-2015). In addition, it is very important to check the cycle of the climate indices that significantly affect the climate of the region. For instance based on the Oceanic Nino Index (ONI), years of 1976, 1989 and 1990 are years of strong La Nina and 2015 was year of very strong El Nino event. I am not suggesting that the atmospheric indices ENSO have a significant impact on the region but it is very important to check. My point is the year selection can cause a bias to your outcome.

[Response]: Thank you so much for this valuable comment.

(1)    The specific years were selected mainly based on the following reasons. The year of 1977 is the earliest time we can acquire abundant high quality images (cloud free on lakes) covering the whole study area and 2015 was the latest year when we performed this research. The years of 1990 and 2000 were chosen for decadal analysis. We have added several sentences to clarify the reason why we chose these years in section of Datasets

“The year of 1977 is the earliest time we can acquire abundant high quality images covering the whole study area and 2015 was the latest year when we started with this research. The years of 1990 and 2000 were chosen for decadal analysis.”  

(2)    We acknowledged that the La Nina and El Nino events may have a significant impact on regional meteorological environment. We referred to relevant studies and found that La Nina did occur in China in the years of 1976, 1989 and 1990 and El Nino event occurred in 2015. However, these climatic events have significant impacts mainly on precipitation anomaly in Southern China [1] and temperature anomaly in Northern China [2,3]. El Nino and La Nina events have a less impact on the rainfall in the Tibetan Plateau, resulting in limited impact on this study area.

 

3.       In your manuscript, it was indicated that the lake size was increased especially from 2000 to 2015. In the same time frame the PET was reduced significantly (figure 6 i). Can you explain where the source of water for the lakes is (MAP remains the uniform)? Is it from melting of the glaciers? Is there a ground water flow to the lakes?

[Response]: We thank the reviewer for this comment. We checked the figure 6(i) and found that the Y-axis scales in figure 6(i) were not consistent with the ones in figure 6(g) and figure 6(h). After the unification of Y-axis scales, figure 6(i) indicated that MAP increased remarkably and PET rose slightly during the period 2000-2015. In this study, we found that precipitation played the most significant role in lake area change in the QB. In addition, glacier retreat also increased water supplies to the lakes in the QB, resulting in the glacier-fed lakes expanded markedly, especially in the period 2000-2015 (Figure 10). In spite of the slight decrease in PET, the lakes expanded significantly in the last period due to the evident increase of precipitation and retreat of glaciers. The Figure 6(i) has been revised as follows:

 

Minor comments:

1.       Line 259 However, the lakes expanded the most significantly during the last period. Change the sentence with more appropriate one and to be clear add the timeframe (2000-2015).

[Response]: Thanks for your comment. We have modified this sentence and added the time fame. “However, the lakes expanded the most significantly during the last period” was changed to “However, the lakes expanded the most significantly during 2000-2015”.

 

2.       Figure 4.  add title axis for the secondary axis.

[Response]: Thanks for your comment and the modified figure was shown as follows:

Figure 4. Changes in lake area and number in the four stages between 1977 and 2015. The error bars represent the confidence level of 95%.

 

3.       From 306 1990 to 2000, the MAAT increased considerably with an average rate of 0.94 °C/10 yr, much higher 307 than that of the first period (Figure 6e). Please use the same unit (°C/10 yr or °C/1 yr) because it can mislead the readers.

[Response]: Thanks for your comment. We have unified the unit of MAAT increase to be °C/1 yr and “0.94 °C/10 yr” was changed to “0.094 °C/ yr”.

 

4.       Line 310: In the later 2000~2015 period, the rate of MAAT increase was less than that in the previous two periods (Figure 6f). Please revise the sentence.

[Response]: Thank you for this comment. The sentence was modified to “In the later 2000-2015 period, the increase rate of MAAT was less than that in the previous two periods (Figure 6f)”.

 

5.       Line 377 the explanation given to the increase of the lake size due to mining of lithium seems to be weak. By building dam the companies are shifting the water from one place to another and this will lead to loss of water (due to infiltration and evaporation). In addition the companies are mining from the salt lake which leads to dry the salt lake. Both scenarios seem to contradict the conclusion made i.e. increase in the overall lake size.

[Response]: Thanks for your comment. Previous studies have demonstrated that salt lake exploitations may lead to significant expansions of salt lakes, especially for the large salt lakes. I agree that mining from the salt lakes do lead to drought of salt lake (Figure 11). Building dams shifted the water from one place to another, might turning a small lake into dry salt lake. However, it also resulted in a larger lake newly formed, e.g. the East Taijinar Lake (Figure 11a) and Yi Ping Li Lake (Figure 11b). Sometimes, dams also led to lake expansion by preventing lake discharge. Several sentences were added in this section to enhance the instructions (highlighted in red).

 

 

 

References:

[1] Lau, K. M., & Weng, H. (2001). Coherent modes of global SST and summer rainfall over China: An assessment of the regional impacts of the 1997–98 El Nino. Journal of Climate, 14(6), 1294-1308.

[2] Zhang, R., & Sumi, A. (2002). Moisture circulation over East Asia during El Niño episode in northern winter, spring and autumn. Journal of the Meteorological Society of Japan. Ser. II, 80(2), 213-227.

[3] Zhai, P., Yu, R., Guo, Y., Li, Q., Ren, X., Wang, Y., ... & Ding, Y. (2016). The strong El Niño of 2015/16 and its dominant impacts on global and China's climate. Journal of Meteorological Research, 30(3), 283-297.

 

 

 


Author Response File: Author Response.docx

Reviewer 3 Report

General comments:

Li et al. present an analysis of lake and glacier area change in the Qaidam Basin of the Tibetan Plateau. The work is interesting and generally well presented; however, I would like to see some minor revisions before the study is published.

1.      You should make some comparisons to water storage change estimated from GRACE data e.g. https://doi.org/10.1371/journal.pone.0141442 and longer term climatic change e.g. https://doi.org/10.1016/j.yqres.2008.11.007

2.      Some of your figures have missing axes labels and scale bars. Please amend.

3.      You mention that images were chosen from September to October when the lakes reach their maximum extent with least ice cover (L103). However, there is no analysis showing how lakes expand seasonally. This should be added so it can be compared to the long term rate of change.

Specific comments:

L21. ‘glaciers have decreased in area by 259.16 km2…’ would be better.

L22. Remove ‘firstly’.

L37-39. The Tibetan Plateau alone has the largest quantify of ice expect the Arctic and Antarctic, or the TP and the Himalayan range?

L39. Change ‘stock’ to ‘store’.

L95. Spelling of ‘meteorological’ in Figure 1. What is the source of the DEM? Check the maximum elevation corresponds to the text. If the legend doesn’t correspond to just the basin, this needs clarifying, otherwise it’s not clear.

L97. Is there a reason TOA scenes were used rather than the surface reflectance product?

L99. ‘Landsat 8’.

L98-99. Define these sensors when the abbreviation is first used on L75.

L105. ‘..cloud cover..’.

L119. Was this to surface reflectance? If so please specify the climate data used for the correction.

L122. ‘mean’.

L124. Define SPLINA and LAPGRD.

L136. ‘land’ or define what land.

L137. Capitalise glacier and others. Change Period to Date here and Table 3, or state a range of dates e.g. 2000-2015.

L166. How was the NDWI range adjusted? Manually?

L168. Length and Rectangular shouldn’t be capitalised.

L185. If the glaciers are at 4000 m, the maximum elevation of the basin cannot be 3000 m (L84).

L187. Provide the correct citation for the SRTM DEM.

L213. Should this be times 100, not 100%.

L227. What is AMOS 22.0?

L248. ‘Overall’.

L252. Change ‘this year’ to ‘in 2015’.

L262. Please add a scale bar and the source of the river dataset.

L265. Label the primary and secondary y axes. State what the error bars represent.

L267. Why is the ‘~’ symbol used? If they were precise classes it should be ‘‒’. Change here and throughout.

L272. ’50 km’.

L293. Add scale bars. Define ‘AP’. Change ‘The lost lake’ and ‘The new lake’ to something different. Perhaps newly formed lakes and disappeared lakes.

L303. Remove the full stop after ‘yr’.

L317. Please add the regression formula and R2 values to the graphs.

L330. Please add a scale bar.

L332. Please label the y axes ‘Area (km2)’ and state what the error bars represent.

L406. What is ‘angular effect’ and ‘scanning time’?

L411. ‘researchers’ or change to ‘studies’.

L435. Remove comma before ‘Results’.

L468. What version of the inventory did you use for the comparison?

L474. Add Y axes label.

L486. Change ‘treating’ to ‘retreat’.
L494. Add a reference to support this statement.

L506. Are there any references you can use to support impacts on road safety?

L523. Add a space ‘area >0.5’.


Author Response

We thank the reviewer very much for the constructive comments on our manuscript. We have carefully considered all of the comments in further revised manuscript. Point-by-point responses to each comment are as follows:

 

1.       You should make some comparisons to water storage change estimated from GRACE data e.g. https://doi.org/10.1371/journal.pone.0141442 and longer term climatic change e.g. https://doi.org/10.1016/j.yqres.2008.11.007.

[Response]: Thank you so much for this comment. We have added the comparison in water storage change of the QB in the section 4.2 “Comparison between this study and previous studies on the TP (highlighted in red)” The added texts are as follows:

“The results in this study were also consistent with the findings in the study of Jiao’s [61], which indicated that the water storage in the QB increased during 2002-2013, while our study found that the lakes expanded significantly during the same time.”

We discussed the climatic changes in section 3.2, however we believe that longer term climatic change is not in the scope of this study. Thanks again for your comment and suggest.    

2.       Some of your figures have missing axes labels and scale bars. Please amend.

[Response]: We apologize for this mistake. The missing axes and scale bars were added in revised manuscript.

3.       You mention that images were chosen from September to October when the lakes reach their maximum extent with least ice cover (L103). However, there is no analysis showing how lakes expand seasonally. This should be added so it can be compared to the long term rate of change.

[Response]: Thank you so much for this comment. All of our analysis is annual based. The reason why we chose the images acquired in Sep. to Oct. is to minimize the impacts of seasonality on the annual analysis. In future, with the availability of the data more concern with analysis of seasonal effect on lakes will be conducted. Thanks again for your suggest.

 

Specific comments:

1.       L21. ‘glaciers have decreased in area by 259.16 km2…’ would be better.

[Response]: Thank you so much for this comment. The sentence “Meanwhile, glaciers have retreated by an area of 259.16 km2 in the past four decades.” has been changed to “Meanwhile, glaciers have decreased in area by 259.16 km2 in the past four decades.”

 

2.       L22. Remove ‘firstly’.

[Response]: It was modified in revised manuscript and thank you.

 

3.       L37-39. The Tibetan Plateau alone has the largest quantify of ice expect the Arctic and Antarctic, or the TP and the Himalayan range?

[Response]: Thanks for this comment. As the Himalayan range belongs to the Tibetan Plateau, the whole TP has the largest quantify of ice expect the Arctic and Antarctic.

 

4.       L39. Change ‘stock’ to ‘store’.

[Response]: Thanks for this comment. The word “stock” has been changed to “store”.

 

5.       L95. Spelling of ‘meteorological’ in Figure 1. What is the source of the DEM? Check the maximum elevation corresponds to the text. If the legend doesn’t correspond to just the basin, this needs clarifying, otherwise it’s not clear.

[Response]: Thanks for this comment. Sorry for the misspelling and modified. The SRTM DEM (30m) database was obtained from USGS and the source of the DEM was clarified in the section of Datasets in revised manuscript (highlighted in red): 

“In addition, Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) with a 1-arc second (30 m) resolution obtained from USGS (https://www.usgs.gov/) was employed in topographic Analysis.”

The maximum elevation in the section of Study area has been modified according to values of SRTM DEM data. Thanks again.

 

6.       L97. Is there a reason TOA scenes were used rather than the surface reflectance product?

[Response]: Thanks for this comment. The downloaded data were TOA scenes. However, all the scenes have been performed atmospheric correction. All the final data used in this study were surface reflectance. 

 

7.       L99. ‘Landsat 8’.

[Response]: Thanks for this comment. “Landsat8” was changed to “Landsat”.

 

8.       L98-99. Define these sensors when the abbreviation is first used on L75.

[Response]: We appreciate this comment. We think it’s better to use “Landsat images” to summarize “Landsat MSS/TM/ETM+/OLI images” in Introduction section. Their full names were mentioned in section Datasets (highlighted in red).

 

9.       L105. ‘..cloud cover..’.

[Response]: Thanks for this comment. We have changed “cloud covers” to “cloud cover” in revised manuscript.

 

10.   L119. Was this to surface reflectance? If so please specify the climate data used for the correction.

[Response]: We appreciate this comment. The parameters of average elevation, scene center coordinates, sensor type, flight date and time, atmospheric model, and information about aerosol distribution, visibility and water vapor conditions were used for atmospheric correction. The added texts were highlighted in section 2.2 Datasets.

 

11.   L122. ‘mean’.

[Response]: Thanks for this comment. We have changed “Mean” to “mean” in revised manuscript.

 

12.   L124. Define SPLINA and LAPGRD.

[Response]: Thanks for this comment. SPLINA and LAPGRD are two programs of ANUSPLIN, designed by Australian National University (ANU). We failed to find their full names per their description.

 

13.   L136. ‘land’ or define what land.

[Response]: Thanks for this comment. We have changed “lands” to “land”.

 

14.   L137. Capitalise glacier and others. Change Period to Date here and Table 3, or state a range of dates e.g. 2000-2015.

[Response]: Thanks for this comment. “Glacier and others” were capitalized and “Period” was changed to “Year”.

 

15.   L166. How was the NDWI range adjusted? Manually?

[Response]: Thanks for this comment. NDWI range was adjusted manually. This section was modified in revised manuscript as follows: “The NDWI index was built in eCognition and an optimal threshold was determined to delineate water surfaces from other land covers by adjusting the range of NDWI manually.” 

 

16.   L168. Length and Rectangular shouldn’t be capitalized.

[Response]: Thanks for this comment and “Length and Rectangular” was changed to “length and rectangular”.

 

17.   L185. If the glaciers are at 4000 m, the maximum elevation of the basin cannot be 3000 m (L84).

[Response]: Thanks for this comment and the maximum elevation of the basin in L84 has been corrected according to the DEM data.

 

18.   L187. Provide the correct citation for the SRTM DEM.

[Response]: Thanks for this comment. In revised manuscript, we have added the information of SRTM DEM data in the section of 2.2 Datasets (highlighted in red):

“In addition, Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) with a 1-arc second (30 m) resolution obtained from USGS (https://www.usgs.gov/) was employed in topographic analysis.”

 

19.   L213. Should this be times 100, not 100%.

[Response]: The correction has been done and thanks.

 

20.   L227. What is AMOS 22.0?

[Response]: Thanks for this comment and citation [46] was added to introduce AMOS 22.0, statistical software used for Structural Equation Modeling.

 

21.   L248. ‘Overall’.

[Response]: Thanks for this comment and “Over all” was changed to “Overall”.

 

22.   L252. Change ‘this year’ to ‘in 2015’.

[Response]: Thanks for this comment and “this year” was changed to “in 2015”.

 

23.   L262. Please add a scale bar and the source of the river dataset.

[Response]: Thanks for this comment. A scale bar was added and the source of the river dataset was added to introduce the river dataset used in this study (highlighted in red): The river dataset was derived from Geographic Information System (GIS) Basic Data of China (http://www.ngcc.cn/).

 

24.   L265. Label the primary and secondary y axes. State what the error bars represent.

[Response]: Thanks for this comment. We added a sentence “The error bars represent the confidence level of 95%.” to state what the error bars mean.

Figure 4. Changes in lake area and number in the four stages between 1977 and 2015. The error bars represent the confidence level of 95%.

 

25.   L267. Why is the ‘~’ symbol used? If they were precise classes it should be ‘‒’. Change here and throughout.

[Response]: Thanks for this comment and all the ‘~’ was changed to ‘‒’.

 

26.   L272. ’50 km’.

[Response]: Thanks for this comment and modified.

 

27.   L293. Add scale bars. Define ‘AP’. Change ‘The lost lake’ and ‘The new lake’ to something different. Perhaps newly formed lakes and disappeared lakes.

28.    

29.   [Response]: As suggested, the changes have been done. ‘AP’ was defined when it first appeared in Line 210. Please see Figure 5

Figure 5. Spatial distribution of decadal lake changes in the QB: 1977-1990 (a); 1990-2000 (b); and 2000-2015 (c).

30.   L303. Remove the full stop after ‘yr’.

[Response]: Thanks for this comment and modification has been done.

 

31.   L317. Please add the regression formula and R2 values to the graphs.

[Response]: Thanks for this comment and the modified Figure 6 was shown as follows:

Figure 6. Annual variations in climatic factors. a, b, c represent annual changes in MAAT, MAP, and PET in the QB between 1977 and 2015, respectively. d, e, f represent the annual changes in MAAT and g, h, i represent the annual changes in MAP and PET during the periods 1977-1990, 1990-2000, and 2000-2015, respectively.

 

 

32.   L330. Please add a scale bar.

[Response]: Thanks for this comment and the modified Figure 7 was shown as follows:

Figure 7. Spatial distribution of glaciers in the QB in 2015.

 

33.   L332. Please label the y axes ‘Area (km2)’ and state what the error bars represent.

[Response]: Thanks for this comment and the modified. A sentence “The error bars represent the confidence level of 95%.” was added to state what the error bars mean.

Figure 8. Changes of glacier area between 1977 and 2015. The error bars represent the confidence level of 95%.

 

34.   L406. What is ‘angular effect’ and ‘scanning time’?

[Response]: Thanks for this comment. As we didn’t discuss the mapping bias of lakes and glaciers due to the uncertainties of angular effect and scanning time, ‘angular effect’ and ‘scanning time were removed in revised manuscript.

 

35.   L411. ‘researchers’ or change to ‘studies’.

[Response]: Thank you so much for this comment and modification has been done.

 

36.   L435. Remove comma before ‘Results’.

[Response]: We thank the reviewer for this comment and modification has been done.

 

37.   L468. What version of the inventory did you use for the comparison?

[Response]: Thanks for this comment and modified. Version 5.0 of the inventory was use for the comparison.

 

38.   L474. Add Y axes label.

[Response]: Thanks for this comment and modification has been done.

 

L486. Change ‘treating’ to ‘retreat’.

[Response]: Thanks for this comment and ‘treating’ was changed to ‘retreat’ in revised manuscript.


L494. Add a reference to support this statement.

[Response]: Thanks for this comment. We have added a new reference [62] to support this statement.

 

L506. Are there any references you can use to support impacts on road safety?

[Response]: Thanks for this comment. Yes, we have added a reference to support impacts on road safety. One sentence wAS added in line 524(highlighted in red):

“Recent study indicated that the significant expansion of salt lakes formed a threat to ecological environment and major engineering facilities in the Hoh Xil region of the TP [65].”

 

L523. Add a space ‘area >0.5’.    

[Response]: Thanks for this comment and modified.

 


Author Response File: Author Response.docx

Back to TopTop