Dear Dr. Maria Paula de Silva,

Thank you very much for responding to the reviewers' comments carefully. We would be very grateful if you could submit the latest version of your manuscript, in which the referees' comments are taken into consideration, to us. Once we receive the manuscript from you, we will send it to them for furhter review.

Again thank you for your nice efforts to improve your paper.

Kind regards,

Koji Suzuki
Associate Editor

Dear Dr. de Silva,

We have received two reviewers' comments on your revised manuscript. One out of the two referees who reviewed the first version of your paper (i.e., Reviewer #1) was very pleased to find your modifications. However, Review #1 has still had some concerns about the use of S275–279 with reference to the satellite remote sensing of CDOM. Please clarify the advantage in S275–279 over aCDOM(440) in the remote sensing approach. Another former referee was not able to accept a review invitation for your revised manuscript, so I asked a new referee (Reviewer #2), who kindly provided you a number of points in terms of science and presentation (see below).

Therefore, we would appreciate it very much if you could make a further revised manuscript with point-by-point responses to the referees' comments. Once we receive these documents from you, I will send them to Review 2 soon.

Again thank you for your time and great efforts to improve the manuscript.

Kind regards,

Koji Suzuki
Associate Editor

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- Reviewer #1

I think the authors basically well replied to my comments and well revised the manuscript. However, I have not been convinced by the authors’ reply about S75-295. I agree with the authors’ description about the motivation of S275-295 as a proxy of CDOM quality (lines 32-38) and the authors’ discussion about DOM dynamics in the lakes of the floodplain during rising and receding water with S275-295 (lines 236-241). Thus, I have been convinced that S275-295 determined with water samples is a quite useful proxy in this studied region. However, I have not understood why we need information of S275-295 in addition to aCDOM from the satellite imagery in the region. The solid evidence observed between aCDOM and S275-295 during the rising period indicates that only aCDOM is enough to discuss DOM dynamics in the region in case of a study with the satellite imagery. If the authors have justification why we need S275-295 in addition to aCDOM for studies with the satellite imagery (NOT with water samples collected during field campaigns), please explain it in the revised manuscript. If the authors don’t have any justification, please remove (or weaken) the conclusion/discussion regarding with usefulness of determination of S275-295 from the satellite imagery in this studied region.

- Reviewer #2

I did not participate in the first round of review of this manuscript. I carefully read the manuscript and examined the authors’ revisions and their responses to the comments of the two previous reviewers. There is no doubt that the authors have made improvements. However, the revised article still poses substantial weakness in both presentation and science. Overall, the paper lacks readability and is superficial in the discussion of the results.



1. One of the most important conclusions of this article is: S275-295 is significantly related to aCDOM(440) during the rising phase and thus can be estimated through remote sensing of aCDOM(440). However, I bet if one replaces the data for Lakes Pan and Pir (rising phase) in Figure 7b with data for Lakes Bua and Mam (receding phase), the relationship between S275-295 and aCDOM(440) also holds, maybe even better. Hence, the argument that this relationship only exists during the rising phase does not make sense. It appears that the authors’ choice of the data for Figure 7b is arbitrary.

The results point to a significant relationship between S275-295 and aCDOM(440) for Lakes Bua and Mam when the data for the rising and receding phases are combined. However, such a relationship does not hold for Lakes Pan and Pir. A closer inspection of the data for Lakes Pan and Pir reveals that the aCDOM(440) values for these two lakes fell in a very narrow range (1-2 m-1) but that the S275-295 values were rather scattered (~0.0140-0.0165) regardless of the water phases (though the scattering is somewhat smaller during the rising phase).

The authors very briefly mentioned the presence of the shoulders in the absorption spectra between 245 and 290 nm (L172-173) but failed to discuss the effect of these shoulders on the calculated S275-295 values. As the wavelength range of these shoulders overlaps with that of S275-295, S275-295 is sensitive to both the magnitude and peak wavelength of the shoulders. Previous studies have shown that S275-295 displays large variability within small ranges of aCDOM if the absorption spectra possess short-UV shoulders (e.g. Xie et al. , 2012, Mar Chem). In fact, the shoulders for Lakes Pan and Pir appear to be more pronounced than those for the other two lakes (Figure 4). That may partly explains why the S275-295 data for Lakes Pan and Pir are more scattered. Note that the presence of significant short-UV shoulders may invalidate S275-295 as an indicator of CDOM MW and a tracer of degradation processes.

An alterative optical index that serves similar proxy roles to S275-295 is the E2/E3 quotien (i.e. the ratio of aCDOM at 250 nm to that at 365 nm), which has been long and widely used by studies of CDOM or humic substances in freshwater systems (e.g. De Haan, 1983, book: Aquatic and Terrestrial Humic Materials; Peuravuori and Pihlaja, 1997, Anal. Chim. Acta; Lou and Xie, 2006, Chemosphere). This ratio can largely circumvent the shoulders aforementioned. If aCDOM(250) is still marginally affected by the shoulders, one can use aCDOM at shorter wavelengths, e.g. aCDOM(245). I suggest that the authors try this index to see if it makes more sense for their data.

2. The authors claim that they “do not have data to corroborate the optical analyses regarding the origin and molecular weight of DOM” (L241-242). In fact, in addition to S275-295 (but see comment 1 above), another important optical index to characterize CDOM is SUVA254. Since the authors have DOC data (Table 1), why do not calculate SUVA254, which is an indicator of aromaticity. If aCDOM(254) is “biased” by the UV-shoulders, choose a shorter wavelength such as 245 nm to calculate SUVA. Moreover, the short-UV shoulders could be linked to in situ production of certain bio-molecules (e.g. Yamashita, Y., Tanoue, E., 2009, Limnol. Oceanogr.; Andrew et al., 2013, Mar Chem), which offers additional information for elucidating the sources of CDOM (a background absorption spectrum of terrigenous CDOM superimposed by biogenic signatures from in situ production).

3. In the authors’ response to Reviewer 2’s comment 5, they stated ” During the receding limp and low water DOM pools become more homogeneous again due to both photodegradation and biodegradation as shown in Figure 3”. I do not see Figure 3 provides any information on photodegradation and biodegradation. Moreover, if these processes are important, why are they not discussed in the manuscript?

4. The optical data need to be discussed along with other relevant information, such as water temperature, water depth, water column stratification (if any), water renewal times, chlorophyll a concentration, turbidity, solar insolation, etc. These variables are important to the physical, biological, and (photo) chemical processes that control the transport, production, and consumption of DOM in these lakes. The discussion should be focused on 1) why there are large seasonal variations in CDOM in the two “isolated” lakes but not in the two river-connected lakes; 2) why CDOM differs both quantitatively and qualitatively between these two groups of lakes.




The entire manuscript is strewn with irregular English syntax and imprecise expressions, making it hard to read and damaging its scientific value. Please do a thorough language editing (preferably by seeking professional assistance) and clarify the confusions. Here, I just name a few examples:

L112-113: SR is defined as the ratio of the spectral slope between 275 and 295 nm (S275-295) to that between 350 and 400 nm (S350-400). Equation 3 does not describe how SR is calculated. I think what you wanted to say is that S350-400 is also calculated using Equation 3.

L126-127: This is a very confusing sentence.

L142-143: “Based on….”. This is an incomplete sentence.

L158-159: “No spatial variation…with lake”. Within each lake or across all lakes? If it were the former, you would only see 8 CDOM absorption spectra (i.e. 2 for each lake *2 water phases) in Figure 4. If it were the latter, you would only see 2 spectra (i.e. 2 water phases). Figure 3 and Figure 7 also demonstrate that there must have been significant spatial variations within each lake and across different lakes.

L156-159: Figure 3 has never been cited in the main text but I think it should appear here.

L163-167: Please present the data (e.g. range, mean, s.d.) for each lake and each phase first and then discuss the significance of difference between the lakes and phases.

L170: Need to explain why you abruptly switched from aCDOM(440) to aCDOM(254) here. I suggest that you combine sections 3.1 and 3.2 and consistently use aCDOM(440).

L172-173: “It is also noticeable the presence of shoulder between 245 and 290 nm in the absorption spectra” → “Shoulders between 245 and 290 nm in the absorption spectra are also noticeable”. This is the only place where these shoulders were mentioned. The authors stopped short of discussing their potential biogeochemical implications and their effects on the calculated S275-295 (see comments 1 & 2 on science).

L176-180: Overall, all S275-295 values fall in a rather small range. Please present the statistics in a table to support your argument that there are significant differences in S275-295 between different phases and different lakes.

L181-184: Please present statistic data (e.g. R^2, p-value, etc.) to support your argument that there is a significant relationship between SR and S275-295. The data in Figure S1 are actually quite scattered. Moreover, SR was only briefly here mentioned in the Results section and has never been discussed in the Discussion section.

L187: Please justify “the good fit” with statistics.

L208-29: “The water level in the floodplain is quite similar between the rising and receding seasons, suggesting that the flood pulse is the major factor explaining the variability of those optical variables”. This is confusing. Where was the water level measured? In each lake? All lakes had the same water levels? Water level changes with time (Figure 3). Are you referring to the average water levels of the rising and receding phases? Is the water level linked to the food pulse?

Table 1: DOC data are not adequately described and discussed in the main text.

Table 1: add water temperature, aCDOM(440), SUVA at an appropriate wavelength, S275-295 or E2/E3 (see comment 1 on science).

Figure 1: For what year or years were the water flow rate?

Figure 2: Remove it. Can be easily incorporated into the main text.

Figure 3: To which lake does the water level refer? The average of all lakes or all lakes had the same water levels?

Figure 4: What does the grey box represent?

Figure 6: remove or combine with Figure 7.

Dear Dr. Maria Paula da Silva,

Thank you very much for taking into account the helpful comments from the last reviewer so carefully. The referee and I were pleaased to find significant improvements on your manuscript. Now it is a great pleasure to accept your manuscript for publication in Biogeosciences.

Again thank you for choosing the journal Biogeosciences.

Kind regards,

Koji Suzuki
Associate Editor