Mapping Algal Blooms in Aquatic Ecosystems Using Long-Term Landsat Data: A Case Study of Yuqiao Reservoir from 1984–2022

Round 1

Reviewer 1 Report

The manuscript on Mapping Algal Blooms in Aquatic Ecosystems Using Long-term Landsat Data: A Case Study of Yuqiao Reservoir during 1984-2022 was written mostly clearly in a good style. The topic of the study is clear and interesting. The structure of the manuscript was not clear in parts and need to be reorganised. The discussion section would need the most improvement. Below is my specific questions, comments and suggestions:

Line 22: Abbreviation GF-2 PMS used without explanation. And, based on 1 image, not imagery.

Line 37: Is it the graphical abstract? The right panel is not easily understandable. If the subfigures have distinctions (a, b, c), they should be explained, or remove the letters. Abbreviation FACI should be explained. I suggest connecting the map of the waterbody and FACI figures more by moving the numbers on the x and y axes to the FACI figures and removing it from the map. Additionally, I suggest rotating the c subfigure 360degrees (so the reading is from to the bottom and Latitude axes will be the most outside (toward to the map) (similarly with b subfigure).

Line 44: in the word fragile “f” is not in the same font as rest.

Line 60: a in the pigment name should be in italics.

Line 66: Abbreviation FAI used for the first time, add explanation.

Line 108: Those 2 atmospheric correction algorithms should be explained. Abbreviations, why, etc.

Line 120-121: Explain why just one GF-2 vs Landsat 8 images were enough for method validation?

Line 144 and 146: Please add the (a) and (b) in front of the explanation.

Line 155-159: The sentence starting with “By combining…” and the following sentence need a reference or if it your result – then it needs to be explained in the results section.

Line 166: Are figure 3a and b results? Then it should be placed in the results section.

Lines 182-184: the one letter symbols need to be in italics.

Line 213: should be: “18.3-18.6 m”, delete an extra “m”.

Line 258: Abbreviation FACI used for the first time, add explanation.

Lines 269-273: I think this suit better to the methods section.

Line 280: Figure 4. Please remove the outside borderline from the plot area.  I suggest removing y- axes from 4b plot. Place 4d plot 4b plot. Currently there is an odd empty space there and it is more difficult to read the 4d plot. Also, it would make the look of the c and d plots better if you would use km2 instead of m2 for area. The Abbreviation LC8 is not explained and used only in plot 4a, I think its should be changes to Landsat 8 to be consistent. On the plots its GF2, while everywhere in text it is GF-2.

Lines 281-284: Replace LC 8 with Landsat 8.

Lines 308-312: This paragraph belongs to discussion section.

Line 341-346: This section with Figure 6 is a result and should be moved to the results section.

Line 350: Please add the used thresholds on plots 6c and 6d.

Lines 351-354: Please change the title of the Figure 6 accordingly: Comparison of the distribution of VS extracted by different methods on September 20, 1999, and July 15, 1998: (a-b) are true color images; (c-d) are VS extracted by FAI with different thresholds; and (e-f) are VS extracted by multi-index DTM.

Lines 355-361: This paragraph with figure 7 belongs also in results, the according discussion about the figures should be added to the discussion section. How exactly the water level should be used for the VPF threshold? Currently this paragraph is not clear. Figure 7 - is AV determined on all the data archives or on specific period? Please add this info to the title.

Line 365: Based on what you assume that the growth ranges of AV in adjacent years are similar?

Line 401: add space between number and unit.

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Reviewer 2 Report

The mapping of algal blooms (Abs) is a hot research topic. For inland waters, it is difficult research to distinguish AB from aquatic vegetation. This paper mapped Abs based on three indies (FAI, NDWI & NDVI) and DTM. It is an interesting work. I have some comments for this paper:

1, line 111-112: “images were visually screened to exclude images heavily affected by clouds, solar glare, or thick aerosols”, how to know the image with thick aerosol?

2, In this paper, the Landsat images were atmospheric corrected by LaSRC and LEDAPS, but which is the atmospheric correction algorithm for GF-2 PMS? And the Landsat surface reflectance data is thought to have large errors in inland waters, so why not use Rayleigh-correction data (just as Hu et al. (2010, JGR) did)?

3, line 124-125: The water level measurements were from Aug and Nov 2021, only two months of data were available, which weakens the credibility of the regression equation. The authors should add the water level date of other months.

4, line 148: “we calculated and recorded the NDVI, FAI, and NDWI indices for each image to establish quantitative relationships among them.” Please show me how many images were calculated in here and the temporal coverage of these images. If the data allows, please show me the water levels corresponding to these images.

5, eq 5: These are three different indices (FAI, NDWI and NDVI), representing different indicative meanings, and is it reasonable to compare them? Is there any support for this?

6, In Figure 3, the authors distinguished between water and vegetation before calculating the three indices, so how did the authors distinguish between water and vegetation before the algorithms of this paper?

7, The manuscript algorithm base assumption is that AV is stationary, however some rootless aquatic vegetation will drift with the current. On another hand, algae will drift with the current to the aquatic vegetation area, how can the authors solve such a problem?

8, line 240-242: The authors use GF as a reference. GF has a higher spatial resolution than Landsat, but the accuracy of ABs recognition is also affected by other properties of the sensor (e.g. radiometric resolution, etc.), and there is no data in this paper that would suggest that GF is better than Landsat for ABs recognition, so what is the basis for the authors to do this?

9, eq 8 should be FACI = FAImean *AreaABs

10, From Fig. 4 (c & d), the difference between GF and L8 becomes larger when the area of AB is larger, why? Did the authors consider the problem of AB area calculation caused by the difference in spatial resolution between GF and L8?

11, For Figure 5, why is the FACI almost zero value in 1984-1993 and 2009-2013? The authors need to add the month or season to which the images used belonged.

12, The RESULT is too short, the authors should add a section on the results of the recognition of ABs (could be an example of a single date). From the current text, I can't be informed about the recognition results of the algorithm of this paper. What is the accuracy? What is the spatial distribution of the identified ABs and AVs? These should be shown in the RESULT section.

13, From Figures 6 &7, as shown in the red box in the screenshot, the DTM of this paper seems to recognize river bank and bare lake bottom (with high reflectivity) as vegetation, which suggests that the algorithm water body extraction is failing, and the reason for this may be the setting of the NDWI threshold. This could be the reason why the land-water boundary is incorrectly identified as ABs in Figure 8. It is reasonable to suspect that the NDWI and FAI in the algorithm of this paper did not work.

14, Have the authors compared the results of other classification methods inYuqiao? Liang et al.(2017) proposed a classification method for algae and aquatic vegetation in Lake Taihu.

Liang, Q., Zhang, Y., Ma, R., et al. (2017). A MODIS-Based Novel Method to Distinguish Surface Cyanobacterial Scums and Aquatic Macrophytes in Lake Taihu. Remote Sensing, 9, 133

15, The authors argue that anthropogenic activities such as fish cage culture have a profound effect on the dynamics of eutrophication in the water column, yet the distribution of ABs in the text is predominantly in the middle of the reservoir rather than close to the cages, why?

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Reviewer 3 Report

An interesting study with important new methods that has the potential for numerous applications

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Reviewer 4 Report

In this manuscript, the authors applied NDWI, NDVI, and FAI indices using the decision tree (DT) and vegetation presence frequency (VPF) method to classify water, algal blooms (ABs), and aquatic vegetation (AV) in the Yuqiao reservoir, utilizing long-term Landsat satellite data. While the work convincingly presents a spatial classification of water types, it could be more explicit about the reasons for choosing this specific method framework instead of alternatives for estimating algal blooms in inland waters using chlorophyll-a algorithms.

Specific Comments:

66: The acronym for FAI is missing. Please include it for clarity.

75: The manuscript should elaborate on why the ABs pattern is considered random and explore potential reasons for this observation. Does agricultural runoff associate with this phenomenon?

109: Since different Landsat data are used, it would be helpful to mention whether any quality control measures or sensor-specific calibrations were adopted to ensure data consistency and reliability.

129: The acronyms for NDVI, FAI, and NDWI are missing. Please include them to enhance readability.

Fig 2: It appears that VS only extracts the Algal bloom information. However, it seems contradictory that the NDVI is low in AV-dominated regions. The authors should address this inconsistency and provide an explanation for the observed results.

148: Instead of solely classifying water types using this method, the manuscript could consider estimating ABs and AV concentrations further. This addition would enhance the study's comprehensiveness and usefulness.

217: The manuscript should clarify why VPF should be set at 0.5, explaining the rationale behind this specific threshold value.

Figure 4: To aid interpretation, the authors can consider adding true-color images of both satellite data for comparison and reference.

270: The ICC of ABs indicates high consistency between Landsat and GF2 when only NDWI & NDVI are applied to GF2. Does this suggest that FAI is not essential for estimating ABs on Landsat as well? The manuscript should provide a clear explanation of these findings.

285: The heading "Long-term reconstruction" is confusing and requires clarification to better convey its intended meaning.

Fig 6: The true-color image of 19990920 shows high green reflectance, but the FAI (c) and DTM (e) maps indicate water type regions. The authors should address this discrepancy and provide a plausible explanation for the observed results.

By addressing these specific comments and clarifying the unclear sections, the manuscript will become more comprehensible, credible, and informative.

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Round 2

Reviewer 2 Report

The authors responded well to my comments. I agreed to accept the manuscript after the authors added the relevant discussion (Shortcomings of this study) to it.

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Reviewer 4 Report

The feedback and suggestions have been incorporated into the updated manuscript; therefore, I recommend it for publication.

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