Impacts of Land Use and Land Cover on Water Quality at Multiple Buffer-Zone Scales in a Lakeside City

Round 1

Reviewer 1 Report

This study investigates the effect of land-use types on water quality parameters of Poyang Lake in China with consideration on buffer scale and seasons. Despite it is an interesting topic and hard work of the authors, the manuscript must be significantly revised. Particularly, the title of the study does not represent the study purposes and the main findings of the study. Also, the study purposes were not clearly stated. In part, this issue is associated with English problems. I found awkward expressions in many places in the manuscript. In method section, I think that selecting key water quality parameters by using factor analysis is questionable since RDA was adopted. Each water quality parameter represents a certain aspect of water characteristics, and I am not sure why the authors had to select key parameters. At the same time, buffer scale interval is not consistent (e.g., 500 m, 800 m, 1000 m, 1,200 m, 1,500m and 1,800 m) and it should be justified. I strongly recommend to revise the manuscript substantially and have English-proof editing process from a professional editing agency before resubmit. I attached a PDF file containing my specific comments.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

The aim of this work is to analyze the relationship between landuse and water quality in urban lakeshore area. The results are not surprising, the proximity of the construction area worsens, the proximity of the forest area improves water quality. In the coastal area of ​​the lake, the analysis of this relationship is indeed incomplete.

The most important error is this study is very descriptive. A more specific method should have been used to explain the causes of the relationship. That is, how and why different landuse data affect water quality. There is no answer to this "why" word. Additional explanation needed.

Further explanation is needed as to why you consider the 19 sampling sites to be one and why you do not analyze their impact separately. A separate buffer zone should be assigned to each sampling point. Then the relationship would be clearer. Thus, the average of the 19 values is given, from which the tendency of change can only be estimated. The relationship between effect and consequence is thus difficult to relate. Further explanation is needed as to why the individual effects were not measured.

An additional explanation would be important: what does it mean that the quality of water good or bad, and from what perspective do you evaluate the thresholds?

Instead of or adjacent to the bufferzones, I would consider very important to calculate the range - eg. softrware range estmation. The ten parameters used can have very different ranges, the result of which may give an answer to how realistic the relationships analyzed are.

There should be a very clear distinction between landuse and land cover. The website quoted gives land cover data (https://earthexplorer.usgs.gov.). Finally, landuse generates information using this data (line 137), which requires an explanation because it is not correct.

In addition to the fact that there are several examples, what is the cause using an IT method (redundancy analysis), why not a traditional statistical one.  Justify why.

Author Response

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Round 2

Reviewer 2 Report

I do not see much improvement in the criticisms. Please reply separately or implement it in some way.

Author Response

Response to Reviewer 2 Comments

Current Comments:

       I do not see much improvement in the criticisms. Please reply separately or implement it in some way.

       Response: Thank you for your comments concerning our manuscript. In order to express our revised content more clearly, we have rearranged and replied to your last comments. (I also attached this document, please see the attachment)

Last Comments:

The aim of this work is to analyze the relationship between landuse and water quality in urban lakeshore area. The results are not surprising, the proximity of the construction area worsens, the proximity of the forest area improves water quality. In the coastal area of the lake, the analysis of this relationship is indeed incomplete. 

Response: We appreciate the reviewer for carefully evaluating the manuscript. The comments are very helpful for improving our paper. We have read the comments carefully and made corrections in the hope of getting your approval. We listed the comments in the letter point by point, and the responses to the comments are as follows:

Point 1: The most important error is this study is very descriptive. A more specific method should have been used to explain the causes of the relationship. That is, how and why different land use data affect water quality. There is no answer to this "why" word. Additional explanation needed.

Response 1: Thank you for pointing this. We think this research makes a great sense in the research of demonstrating the relationship between the land-use types and water quality on buffer zone scales, yet our study is not aimed to the mechanism but the application side of the management of land use and water quality. The consequently statistics-oriented research outcomes can serve future water quality optimisation and environmental restoration as a part of fundamental datasets. For example, in L218-219 “Thus, it should be considered to increase vegetation within large buffer zones to reduce the concentrations of harmful substances into water bodies.” and in L197-198 “The result suggests that the construction land should be at least 1200 m away from the water bodies. The same is true of bare land, which must be at least 1500 m from the water bodies.” 

Besides, on your question, we also added some inferences about why different land-use data affect water quality in the text, such as in L204-208 “TP is positively correlated with agricultural land in general, indicating that agricultural activities might be responsible for nutrient input in rivers and lakes. In agricultural lands, excessive fertilisers, runoff, and soil erosion can lead to an increase in sediment, nutrients, chemical contaminants, and organic matter into the water body.” 

Point 2: Further explanation is needed as to why you consider the 19 sampling sites to be one and why you do not analyze their impact separately. A separate buffer zone should be assigned to each sampling point. Then the relationship would be clearer. Thus, the average of the 19 values is given, from which the tendency of change can only be estimated. The relationship between effect and consequence is thus difficult to relate. Further explanation is needed as to why the individual effects were not measured.

Response 2: We thank the reviewer for the helpful suggestion. The aim of the manuscript is to quantify the association between land use/land cover (LULC) and water quality in space and time (i.e., the whole lakeside area in different seasons). Therefore, we only analyse the average of the 19 values. Accordingly, we modified Figure 3 to show the mean proportion of land use types (y-axis) of all sampling sites by buffer scale (x-axis).

Point 3: An additional explanation would be important: what does it mean that the quality of water good or bad, and from what perspective do you evaluate the thresholds?

Response 3: Thank you for pointing this out. Before selecting representative water quality indicators, we compared the water quality parameters with the World Health Organization [1] and Chinese State Standards (CSS) [2] for drinking water (Table 1). Due to all the parameters exceed standards, it is unnecessary to analyse the range of each water quality parameters. Instead of analysing the water quality individually, we used redundancy analysis (RDA) to investigate the relationship between LULC and water quality, and the relationship is clearly shown in the biplots (Figure 4 and 6). The angle in the biplots between the arrows indicates the magnitude of the correlation, and the smaller the angle, the higher the correlation.

Table 1. Range in values of water quality variables in waters.

Point 4: Instead of or adjacent to the buffer zones, I would consider very important to calculate the range - e.g. Software range estimation. The ten parameters used can have very different ranges, the result of which may give an answer to how realistic the relationships analyzed are.

Response 4: Thank you for the valuable comment. We first selected 500 m, 1000 m and 1500 m according to Ref [3] (Ref [30] in the manuscript), but the results were not significant. Hence, we interpolated two inner buffers (800 and 1200 m) and extended outer to 1800 m; six buffer zones are then used to show more details for our analysis.

Analysing the influence of LULC around the site on each water quality parameter is helpful to demonstrate the characteristics of different water quality parameters, which is an important field in the management of land use. However, we think this paper has not yet reached the level of refinement research. It is a comprehensive evaluation and analysis research. This study can show more emphasis on the overall influence of LULC on several types of water quality parameters, so as to provide a basis for subsequent refinement research.

Point 5: There should be a very clear distinction between land use and land cover. The website quoted gives land cover data (https: //earthexplorer.usgs.gov.). Finally, land use generates information using this data (line 137), which requires an explanation because it is not correct.

Response 5: Thank you for the constructive comment. We’re sorry to confuse you with the ambiguous descriptions. The necessary change in the statement has been made in the revised manuscript as well as in the referred figure and table accordingly.

Point 6: In addition to the fact that there are several examples, what is the cause using an IT method (redundancy analysis), why not a traditional statistical one.  Justify why.

Response 6: Thank you for pointing this out. The analysis of the impacts of the LULC on the water quality indicators is a complex process, which requires simultaneous analysis of the relationship between two sets of variables. It can be seen from the original text L119-122 (Revised text in L118-121): “The greatest advantage of an RDA is that this statistical method can independently maintain the contribution of each explanatory variable for each dependent variable, without performing a simple analysis for the explanatory variable vector and converting some of the variables into virtual complex variables”. The analysis of the relationship between the two sets of variables by RDA is more intuitive and more accessible than traditional methods. Therefore, compared with conventional methods, we think redundancy analysis is more suitable for this study.

[1] WHO, Guidelines for Drinking-Water Quality, 3rd ed., Volume 1 (2006)-Recommendations, Word Health Organization, Geneva.

[2] Chinese Ministry of Health, P.R. China, Chinese State Standards (CSS) for Drinking Water Quality (GB5749-2006), 2006.

[3] Carey, R.O.; Migliaccio, K.W.; Li, Y.; Schaffer, B.; Kiker, G.A.; Brown, M.T. Land use disturbance indicators and water quality variability in the Biscayne Bay Watershed, Florida. ECOL INDIC 2011, 11, 1093-1104.

Author Response File: Author Response.docx