Reviews and Syntheses: Carbon biogeochemistry of Indian estuaries

Dutta, Manab Kumar; Sreelash, Krishnan; Padmalal, Damodaran; Ward, Nicholas D.; Bianchi, Thomas S.

doi:https://doi.org/10.5194/bg-2022-200

Preprints

https://doi.org/10.5194/bg-2022-200

Preprints

14 Oct 2022

| 14 Oct 2022

Status: this preprint was under review for the journal BG but the revision was not accepted.

Reviews and Syntheses: Carbon biogeochemistry of Indian estuaries

Manab Kumar Dutta, Krishnan Sreelash, Damodaran Padmalal, Nicholas D. Ward, and Thomas S. Bianchi

Abstract. The goal of this review is to provide a comprehensive overview of the magnitude and drivers of carbon cycling dynamics in the major estuaries of India. Data from a total of 32 estuaries along the Bay of Bengal (BB) and the Arabian Sea (AS) were compiled from the literature and re-analysed based on changes in season (wet vs. dry) and marine end-members (e.g., BB vs. AS). The estuaries are generally undersaturated in dissolved oxygen relative to the atmosphere and strongly influenced by local and regional precipitation patterns. Speciation of the dissolved inorganic carbon (DIC) pool is dominated by bicarbonate and primarily variability in DIC is controlled by a combination of carbonate weathering, the degree of precipitation, the length of the estuaries, in situ respiration, and mixing. Carbonate dissolution had the largest influence on DIC during the wet season, while respiration was the primary control of DIC variability in the estuaries connected with BB during the dry season. Interestingly, the influence of anaerobic metabolism on DIC is observed in the oxygenated mangrove dominated estuaries, which we hypothesize is driven by porewater exchange in intertidal sediments. Dissolved organic carbon (DOC) generally behaves non-conservatively in the studied estuaries. The DOC-particulate organic carbon (POC) inter-conversion and DOC mineralization are evident in the BB during the dry season and AS estuaries, respectively. The wet season δ¹³C_POC shows dominance of freshwater algae, C₃ plant material, as well as marine organic matter in POC. However, anthropogenic inputs are evident in some estuaries in eastern India during the dry season. POC respiration was identified in the AS; however, a link between POC and CH₄ is identified throughout both the regions. pCO₂ is controlled principally by respiration with freshwater discharge only playing a marginal important role in the BB. The AS estuaries act as a CO₂ source to the atmosphere; however, the BB estuaries vary between a source and sink. POC together with methanotrophy and dam abundance appear to control CH₄ concentrations, and all of the studied estuaries act as a CH₄ source to the atmosphere. Additionally, anthropogenic inputs and groundwater exchange also show potential influences in some cases. The Indian estuaries contribute 2.62 % and 1.09 % to the global riverine DIC and DOC exports to the ocean, respectively. The total CO₂ and CH₄ fluxes from Indian estuaries are estimated as ~9718 Gg yr^-1 and 3.27 Gg yr^-1, which contributes ~0.67 % and ~0.12 %, respectively, to global estimates of estuarine greenhouse gas emissions. While a qualitative idea on the major factors controlling the carbon biogeochemistry in India is presented through this work, a more thorough investigation including rate quantification of the above-mentioned mechanisms is essential for precise accounting of the C budget of Indian estuaries.

Received: 26 Sep 2022 – Discussion started: 14 Oct 2022

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.

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Manab Kumar Dutta, Krishnan Sreelash, Damodaran Padmalal, Nicholas D. Ward, and Thomas S. Bianchi

Status: closed

RC1:
'Comment on bg-2022-200', Anonymous Referee #1, 09 Nov 2022

Overview

The authors reviewed carbon biogeochemistry in the India Coast, presented its spatiotemporal variability and discussed the potential drivers. As a continuum between land and ocean, estuarine system is important while suffering a great spatiotemporal heterogeneity. Such study could help constrain this variation and better understand its essential role on global carbon budget. However, this manuscript of its current version still saves a large space for improvement, particularly from its data interpretation and content structure perspectives. I am afraid this manuscript will need a thorough revision to fit for the journal.



Major comments

(1) Traceable data is vital for a review article. Unfortunately, there is no clear pathway(s) for data sources in this manuscript. For example, how many sampling stations, how many observations for each estuary, sampling time, etc.? We even do not know if the authors are presenting annual average data or just one-time surveyed data. Why there is no standard deviation for each estuary data in figures? A proper conclusive data table (can be supplementary material) is badly needed to show its rigor and reliability.

(2) Following the first major concern, then the data interpretation is problematic. First, the data visualization needs improvement, why only list Sundarbans and Hooghly Estuary sampling stations in Fig.1? Differences on estuaries or dry/wet cycle cannot be well distinguished in both figures and supplementary figures. Second, the way of data processing is also unclear, for example, how do the authors conduct statistical analysis, t-test? two-way ANOVA? any process to meet the assumptions? In supplementary figures, several estuaries are excluded to meet a high p-value relationship seems arbitrary and misleading, same as the threshold 6800 μatm for CO₂. Is there any reason/accordance to do so?

Also, I have a feeling that the authors messed with riverine and estuarine data. For example, in Line 815 the “~10.30 Tg C yr^-1” belongs to riverine export fluxes (Krishna et al., 2019) rather than “export fluxes from Indian estuaries”, and the following discussion (Lines 819–831) is all about riverine C exports. Accordingly, in Fig. 7 export flux values may put in wrong place. Similarly, I do not think there are so many dams built in coastal estuaries list in Table 1. This is the reason why readers are curious about the data details, if so, I would suggest the authors clarify each estuary area/coordinates and further check about the data.

(3) The manuscript structure is organized in a research article format instead of a review. In addition, the separated discussions on DIC, DOC, POC, CO₂, CH₄ read super repetitive and distracting. In fact, carbon biogeochemistry is comprehensive and synthesized, drivers (e.g. hydrologic, biochemical, etc.) on any single carbon species would further impact on other carbon interactivities and then the entire carbon budget. Re-organization of manuscript structure to look at the drivers more synthetically is highly recommended.

(4) Many important information are missing, such as temperature gradient, wind speeds, net ecosystem productions, submarine groundwater discharge rates, two end-members values, etc., these are decisive to estuarine carbon biogeochemistry. Also, I am curious about the anthropogenic impact on estuarine carbon biogeochemistry. It seems the anthropogenic discharges in this study are mostly referred as sewage discharges to upper rivers, then how to identify the anthropogenic carbon in lower estuarine area proportionally?

Line comments

Line 210: more details on “statistical analysis”.

Line 347: references.

Line 348: “DIC addition/removal” details.

Line 399: should be “riverine DIC” instead of “estuarine DIC”

Line 483: the difference between “Terrestrial DOC” and “Riverine DOC” ?

Line 492: where is “Fig. 12A”?

Line 540-543: the purpose for comparing regional DOC/DON to POC/PON? or DOC fraction in global coastal ocean?

Line 552-553: you cannot say this unless the data about POC/DOC from two end-members.

Line 570: why 6800 μatm threshold?

Line 579: further explain “a decrease of aerobic bacterial activity with increasing DOC”

Line 616: further explain “freshwater mixing is not the major driver of POC”, as it shows lower salinity with higher POC and 13C values.

Line 668-671: more direct evidence is needed to evaluate anthropogenic impact on pCO₂ rather than population density. For example, anthropogenic pCO₂ is 100 μatm out of total pCO₂ 400 μatm in Estuary A, where as anthropogenic pCO₂ is 200 μatm out of total pCO₂ 1000 μatm in Estuary B.

Line 686: where is “Fig. 21”?

Line 695-696: wrong statement “nitrification plays crucial role in increasing pH”

Line 699: “unlikely”

Line 712-713: details for FCO2

Link 862: where is “Table 6”

Tables and Figures

Table 1: add coordinates, references

Table 2: are they annual averaged numbers? Standard deviation?

Table 5: confusing table, please improve

Fig. 1: why only zoom in two estuaries? Instead display C3 and C4 plants area, population density is more important to be visualized.

Fig. 2 - Fig. 6: cannot distinguish that data between dry and wet, standard deviation needed.

Fig. 6: estuarine export fluxes values should be river-borne C, the figure is unnecessary if only two components are evaluated.

For all supplementary figures: there is no spatial information, reason why exclude several estuarine data, the number of observations are too small, standard deviations? Data interpretation seems unconvincing due to potential data manipulation.

Citation: https://doi.org/10.5194/bg-2022-200-RC1
- AC1: 'Reply on RC1', Manab Kumar Dutta, 30 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-200/bg-2022-200-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/bg-2022-200-AC1
RC2:
'Comment on bg-2022-200', Anonymous Referee #2, 25 Nov 2022

This study compiled the data of carbon dynamics in the estuaries of India and overviewed the regulating factors of carbon dynamics and the contribution of Indian estuaries on global carbon budgets. This approach is helpful to understand the role of continental estuaries on global carbon cycling. However, this version of manuscript contains major concerns which the authors have to improve before publication. In particular, I think the analytical approach and the interpretation of data should be revised substantially.

First, the authors discussed the mechanism of regulating factors of carbon dynamics mainly based on correlation between carbon and other physicochemical parameters but the results of these analysis were not shown in main Figures. If these analyses are substantially used in discussion section, the main text figures and tables should be restructured according to the main agenda. In addition, the statistical analysis must pay attention to the multicollinearity of multivariate variables. For example, there is a correlation between river flow and population density, which may have a combined effect on carbon concentrations. I think the author should try some analytical methods such as principal component analysis.

Although they mentions various regulating factors, it is very difficult to understand from the manuscript what is the key controlling factor. I suggest that important factors should be extracted and discussed based on the statistical results of the above multivariate analyses.

The analysis with outliers removed is also very arbitrary. I think the variability of freshwater endmember would cause such outliers. My recommendation is to analyze the effects of mixing and biogeochemical processes in estuaries separately from the determinants of the river endmember values.

Line comment

203) I think the compiled dataset is very useful for further studies. Don’t you open this via any repository?

208) What kind of statistical analyses did you use? You have to explain the approach.

224) You often indicate in this manuscript how large or small by %, is this comparison only rivers for which you have data for both wet and dry seasons? If you are compiling all data, you will have a bias due to the different rivers you are averaging.

Fig. 2-6) This value is average in each estuary? At least, you should show error bars. Is possible, you should show whisker plots.

In result section) You used “higher” or “lower” terms. These are based on statistical analysis? All comparisons should be based on statistical analyses.

245) Basically, outliers should not be arbitrarily removed. It would be interesting to discuss the factors that cause freshwater endmembers to vary.

253, 266) Is the average also higher than in estuaries around the world?

256) Here, “peak” may not be suitable. Higher-lower or heavier-lighter are often used.

265) for dry season?

290) unit

327) Rainfall dilute riverine DIC?

331) These values are averages with the broad salinity range? It is difficult to differentiate the mixing effect from the freshwater endmember variability.

332) BB and AS use different fitting curves, but aren't they just different ranges of precipitation? I think it would be more general if the same relationship equation could be used to explain the difference.

392) Also degassing of CO2?

402) Rivers with large population densities may have large dilution of river flow. Multivariate analysis may be effective.

420) The relationship between precipitation and DIC should also be discussed comprehensively. DIC supply due to carbonate weathering may dominate in rivers with low precipitation.

468) This paragraph is redundant because it is a general statement.

492) Fig. 12?

496) p=0.06 is not significant

521) There may be a combined effect of river discharge and population density.

536) This may also be an effect of multicollinearity.

578) Splitting a fitting line is arbitrary if there is no meaning in 6800 µatm. The influence of other variables should be considered.

595) Without an OM source mixing model (using more than 2 variables), it is difficult to discuss the contribution of each carbon source. For example, d13C value of -24~-19‰ can be explained by the mixing between C3 and C4 without marine origin.

630) I think the quantity and quality of POC cause the decomposition and O2 consumption rather than isotopic fractionation. Isotope fractionation doesn't happen that often with degradation (if it did, POC would be noticeably reduced).

653) Why? It is interesting.

Citation: https://doi.org/10.5194/bg-2022-200-RC2
- AC2: 'Reply on RC2', Manab Kumar Dutta, 30 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-200/bg-2022-200-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/bg-2022-200-AC2

Status: closed

RC1:
'Comment on bg-2022-200', Anonymous Referee #1, 09 Nov 2022

Overview

The authors reviewed carbon biogeochemistry in the India Coast, presented its spatiotemporal variability and discussed the potential drivers. As a continuum between land and ocean, estuarine system is important while suffering a great spatiotemporal heterogeneity. Such study could help constrain this variation and better understand its essential role on global carbon budget. However, this manuscript of its current version still saves a large space for improvement, particularly from its data interpretation and content structure perspectives. I am afraid this manuscript will need a thorough revision to fit for the journal.



Major comments

(1) Traceable data is vital for a review article. Unfortunately, there is no clear pathway(s) for data sources in this manuscript. For example, how many sampling stations, how many observations for each estuary, sampling time, etc.? We even do not know if the authors are presenting annual average data or just one-time surveyed data. Why there is no standard deviation for each estuary data in figures? A proper conclusive data table (can be supplementary material) is badly needed to show its rigor and reliability.

(2) Following the first major concern, then the data interpretation is problematic. First, the data visualization needs improvement, why only list Sundarbans and Hooghly Estuary sampling stations in Fig.1? Differences on estuaries or dry/wet cycle cannot be well distinguished in both figures and supplementary figures. Second, the way of data processing is also unclear, for example, how do the authors conduct statistical analysis, t-test? two-way ANOVA? any process to meet the assumptions? In supplementary figures, several estuaries are excluded to meet a high p-value relationship seems arbitrary and misleading, same as the threshold 6800 μatm for CO₂. Is there any reason/accordance to do so?

Also, I have a feeling that the authors messed with riverine and estuarine data. For example, in Line 815 the “~10.30 Tg C yr^-1” belongs to riverine export fluxes (Krishna et al., 2019) rather than “export fluxes from Indian estuaries”, and the following discussion (Lines 819–831) is all about riverine C exports. Accordingly, in Fig. 7 export flux values may put in wrong place. Similarly, I do not think there are so many dams built in coastal estuaries list in Table 1. This is the reason why readers are curious about the data details, if so, I would suggest the authors clarify each estuary area/coordinates and further check about the data.

(3) The manuscript structure is organized in a research article format instead of a review. In addition, the separated discussions on DIC, DOC, POC, CO₂, CH₄ read super repetitive and distracting. In fact, carbon biogeochemistry is comprehensive and synthesized, drivers (e.g. hydrologic, biochemical, etc.) on any single carbon species would further impact on other carbon interactivities and then the entire carbon budget. Re-organization of manuscript structure to look at the drivers more synthetically is highly recommended.

(4) Many important information are missing, such as temperature gradient, wind speeds, net ecosystem productions, submarine groundwater discharge rates, two end-members values, etc., these are decisive to estuarine carbon biogeochemistry. Also, I am curious about the anthropogenic impact on estuarine carbon biogeochemistry. It seems the anthropogenic discharges in this study are mostly referred as sewage discharges to upper rivers, then how to identify the anthropogenic carbon in lower estuarine area proportionally?

Line comments

Line 210: more details on “statistical analysis”.

Line 347: references.

Line 348: “DIC addition/removal” details.

Line 399: should be “riverine DIC” instead of “estuarine DIC”

Line 483: the difference between “Terrestrial DOC” and “Riverine DOC” ?

Line 492: where is “Fig. 12A”?

Line 540-543: the purpose for comparing regional DOC/DON to POC/PON? or DOC fraction in global coastal ocean?

Line 552-553: you cannot say this unless the data about POC/DOC from two end-members.

Line 570: why 6800 μatm threshold?

Line 579: further explain “a decrease of aerobic bacterial activity with increasing DOC”

Line 616: further explain “freshwater mixing is not the major driver of POC”, as it shows lower salinity with higher POC and 13C values.

Line 668-671: more direct evidence is needed to evaluate anthropogenic impact on pCO₂ rather than population density. For example, anthropogenic pCO₂ is 100 μatm out of total pCO₂ 400 μatm in Estuary A, where as anthropogenic pCO₂ is 200 μatm out of total pCO₂ 1000 μatm in Estuary B.

Line 686: where is “Fig. 21”?

Line 695-696: wrong statement “nitrification plays crucial role in increasing pH”

Line 699: “unlikely”

Line 712-713: details for FCO2

Link 862: where is “Table 6”

Tables and Figures

Table 1: add coordinates, references

Table 2: are they annual averaged numbers? Standard deviation?

Table 5: confusing table, please improve

Fig. 1: why only zoom in two estuaries? Instead display C3 and C4 plants area, population density is more important to be visualized.

Fig. 2 - Fig. 6: cannot distinguish that data between dry and wet, standard deviation needed.

Fig. 6: estuarine export fluxes values should be river-borne C, the figure is unnecessary if only two components are evaluated.

For all supplementary figures: there is no spatial information, reason why exclude several estuarine data, the number of observations are too small, standard deviations? Data interpretation seems unconvincing due to potential data manipulation.

Citation: https://doi.org/10.5194/bg-2022-200-RC1
- AC1: 'Reply on RC1', Manab Kumar Dutta, 30 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-200/bg-2022-200-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/bg-2022-200-AC1
RC2:
'Comment on bg-2022-200', Anonymous Referee #2, 25 Nov 2022

This study compiled the data of carbon dynamics in the estuaries of India and overviewed the regulating factors of carbon dynamics and the contribution of Indian estuaries on global carbon budgets. This approach is helpful to understand the role of continental estuaries on global carbon cycling. However, this version of manuscript contains major concerns which the authors have to improve before publication. In particular, I think the analytical approach and the interpretation of data should be revised substantially.

First, the authors discussed the mechanism of regulating factors of carbon dynamics mainly based on correlation between carbon and other physicochemical parameters but the results of these analysis were not shown in main Figures. If these analyses are substantially used in discussion section, the main text figures and tables should be restructured according to the main agenda. In addition, the statistical analysis must pay attention to the multicollinearity of multivariate variables. For example, there is a correlation between river flow and population density, which may have a combined effect on carbon concentrations. I think the author should try some analytical methods such as principal component analysis.

Although they mentions various regulating factors, it is very difficult to understand from the manuscript what is the key controlling factor. I suggest that important factors should be extracted and discussed based on the statistical results of the above multivariate analyses.

The analysis with outliers removed is also very arbitrary. I think the variability of freshwater endmember would cause such outliers. My recommendation is to analyze the effects of mixing and biogeochemical processes in estuaries separately from the determinants of the river endmember values.

Line comment

203) I think the compiled dataset is very useful for further studies. Don’t you open this via any repository?

208) What kind of statistical analyses did you use? You have to explain the approach.

224) You often indicate in this manuscript how large or small by %, is this comparison only rivers for which you have data for both wet and dry seasons? If you are compiling all data, you will have a bias due to the different rivers you are averaging.

Fig. 2-6) This value is average in each estuary? At least, you should show error bars. Is possible, you should show whisker plots.

In result section) You used “higher” or “lower” terms. These are based on statistical analysis? All comparisons should be based on statistical analyses.

245) Basically, outliers should not be arbitrarily removed. It would be interesting to discuss the factors that cause freshwater endmembers to vary.

253, 266) Is the average also higher than in estuaries around the world?

256) Here, “peak” may not be suitable. Higher-lower or heavier-lighter are often used.

265) for dry season?

290) unit

327) Rainfall dilute riverine DIC?

331) These values are averages with the broad salinity range? It is difficult to differentiate the mixing effect from the freshwater endmember variability.

332) BB and AS use different fitting curves, but aren't they just different ranges of precipitation? I think it would be more general if the same relationship equation could be used to explain the difference.

392) Also degassing of CO2?

402) Rivers with large population densities may have large dilution of river flow. Multivariate analysis may be effective.

420) The relationship between precipitation and DIC should also be discussed comprehensively. DIC supply due to carbonate weathering may dominate in rivers with low precipitation.

468) This paragraph is redundant because it is a general statement.

492) Fig. 12?

496) p=0.06 is not significant

521) There may be a combined effect of river discharge and population density.

536) This may also be an effect of multicollinearity.

578) Splitting a fitting line is arbitrary if there is no meaning in 6800 µatm. The influence of other variables should be considered.

595) Without an OM source mixing model (using more than 2 variables), it is difficult to discuss the contribution of each carbon source. For example, d13C value of -24~-19‰ can be explained by the mixing between C3 and C4 without marine origin.

630) I think the quantity and quality of POC cause the decomposition and O2 consumption rather than isotopic fractionation. Isotope fractionation doesn't happen that often with degradation (if it did, POC would be noticeably reduced).

653) Why? It is interesting.

Citation: https://doi.org/10.5194/bg-2022-200-RC2
- AC2: 'Reply on RC2', Manab Kumar Dutta, 30 Mar 2023
  
  The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-200/bg-2022-200-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/bg-2022-200-AC2

Manab Kumar Dutta, Krishnan Sreelash, Damodaran Padmalal, Nicholas D. Ward, and Thomas S. Bianchi

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https://doi.org/10.5194/bg-2022-200-supplement

Manab Kumar Dutta, Krishnan Sreelash, Damodaran Padmalal, Nicholas D. Ward, and Thomas S. Bianchi

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Short summary

Indian estuaries contribute to 2.62 % and 1.09 % of global riverine DIC and DOC export to the ocean, respectively. Major Indian estuaries emit ~9718 Gg yr^-1 and 3.27 Gg yr^-1 of CO₂ and CH₄ to the atmosphere, respectively, which contributes ~0.67 % and ~0.12 % to global CO₂ and CH₄ outgassing from estuaries.


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