Source-to-Sink Pathways of Dissolved Organic Carbon in the River-Estuary-Ocean Continuum: A Modeling Investigation

Yao, Jialing; Chen, Zhi; Ge, Jianzhong; Zhang, Wenyan

doi:https://doi.org/10.5194/bg-2024-2

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https://doi.org/10.5194/bg-2024-2

Preprints

12 Apr 2024

| 12 Apr 2024

Status: a revised version of this preprint was accepted for the journal BG and is expected to appear here in due course.

Source-to-Sink Pathways of Dissolved Organic Carbon in the River-Estuary-Ocean Continuum: A Modeling Investigation

Jialing Yao, Zhi Chen, Jianzhong Ge, and Wenyan Zhang

Abstract. Transport and cycling of dissolved organic carbon (DOC) are most active in estuaries. However, a comprehensive understanding of the sources, sinks, and transformation processes of DOC throughout the river-estuary-ocean continuum is yet to be derived. Taking the Changjiang Estuary and adjacent shelf sea as a case study area, this study applies a physics-biogeochemistry coupled model to investigate DOC cycling the river-estuary-ocean continuum. DOC is classified into two types depending on the origin, namely terrigenous DOC (tDOC) and marine DOC (mDOC). Simulation results were compared with observation and showed a satisfactory model performance. Our study indicates that in summer, the distribution of DOC in the Changjiang Estuary is driven by both hydrodynamics and biogeochemical processes, while in winter, it is primarily driven by hydrodynamics. The spatial transition from terrigenous-dominated DOC to marine-dominated DOC occurs mainly across the contour line of a salinity of 20 PSU. Additionally, the source-sink patterns in summer and winter are significantly different, and the gradient changes in chlorophyll-a indicate the transition between sources and sinks of DOC. A five-year averaged budget analysis of the model results indicates that the Changjiang Estuary has the capability to export DOC, with tDOC contributing 31 % and mDOC accounting for 69 %. The larger proportion of mDOC is primarily attributed to local biogeochemical processes. The model offers a novel perspective on the distribution of DOC in the Changjiang Estuary and holds potential for its application in future organic carbon cycling of other estuaries.

Received: 13 Mar 2024 – Discussion started: 12 Apr 2024

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Jialing Yao, Zhi Chen, Jianzhong Ge, and Wenyan Zhang

Status: closed

CC1:
'Comment on bg-2024-2', Y. Jun Xu, 16 Apr 2024

Line53: Discharge from the Changjiang River has changed since the Three Georges Dam was completed in 2003. The cited reference (Tian et al., 1993) is outdated and I would suggest the authors cite more recent publications, e.g., Zhang W et al. 2021 (https://doi.org/10.1016/j.geomorph.2021.108075) or Yin S et al. 2023 (http://dx.doi.org/10.1016/j.scitotenv.2023.162758)

Citation: https://doi.org/10.5194/bg-2024-2-CC1
- AC1:
  'Reply on CC1', Jialing Yao, 16 Apr 2024
  
  Thank you for your review and suggestion. I will update the citiation in the revision.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC1
  - CC2: 'Reply on AC1', Y. Jun Xu, 17 Apr 2024
    
    The thank the authors for their response to my previous comment.
    I have a couple of comments/suggestions:
    - This modeling work was performed for the period 2013-2017 and a value of 385 ppm was chosen for the atmospheric CO2 concentration for the five study years. However, the atmospheric CO2 conc. already reached 400 ppm in 2013, and with a ~3 ppm annual increase for the following years. Please discuss the possible effect of this CO2 setting on the modeling results.
    - 320-322: I would suggest the authors add more recent publications on the subject; for instance, Mekong River (Li S. et al., https://doi.org/10.1016/j.jhydrol.2013.09.024), Yellow River ( Ran, L. et al., https://doi.org/10.1016/j.jhydrol.2013.06.018), Mississippi River (Reiman & Xu, https://doi.org/10.1016/j.jhydrol.2019.124093).
    - 322-324: The Atchafalaya River is a large freshwater-swamp system and it is not affected by marine water. DOC removal in the system is mainly through the high connectivity of the river's braided channels with extensive floodplains and backwaters (see Xu et al., https://doi.org/10.1016/j.scitotenv.2024.171604; Xu YJ, https://doi.org/10.3390/w5020379)
    - L324-335: A considerable amount of estuarine DOC can be lost to the atmosphere via CO2 (e.g., He & Xu, https://doi.org/10.1007/s12237-017-0320-4). This aspect deserves to be discussed.
    
    Citation: https://doi.org/10.5194/bg-2024-2-CC2
    
    AC2: 'Reply on CC2', Jialing Yao, 06 May 2024
    
    Thank you very much for your insightful comments. Based on the suggestions you raised, our point-to-point response is listed below:
    
    1. Possible effect of underestimation of atmospheric of CO2 concentration
    Taking this issue into consideration, we adjusted the model configuration to set pCO2 at 400ppm with a increase 3ppm per year for sensitivity experiment. The model results indicate that the DOC concentration level remained almost unchanged. In addition, we have reviewed relevant literature. Mou et al. (2017, https://doi.org/10.1007/s10811-017-1089-3) conducted cultivation experiments on marine picocyanobacteria under ambient (380ppmv) and elevated (1000ppmv) CO2 levels. They found that it led to a reduction in cellular chlorophyll a, but did not observe any changes in DOC. Engel et al. (2013, https://doi.org/10.5194/bg-10-1291-2013) suggested that elevated pCO2 has a direct influence on DOC production. However, there is not obvious DOC accumulation after nutrient addition which is due to rapid utilization of fresh produced DOC by bacteria. Under certain circumstances, increased atmospheric CO2 concentrations can lead to an increase in seawater pCO2 levels. James A. et al. (2017, https://doi.org/10.1371/journal.pone.0173145) investigated the impact of increased seawater pCO2 on bacterioplankton. They proposed that elevated pCO2 levels (1000-1500ppm) increase the rate and magnitude of removal of organic carbon by bacterioplankton communities compared to low pCO2 levels (250-400ppm). This effect is attributed to the significant differences in pCO2 concentrations.
    Therefore, based on the model results and the aforementioned studies, the underestimation is minor compared to the actual value, and its impact on DOC concentration may be offset by other processes. Thus, the potential impact of underestimation on DOC is minor. In subsequent revision of the manuscript, we will update this value to better reflect the actual situation and discuss the potential impact of further enhanced pCO2 in future scenarios.
    
    2. 320-322 add publications
    In line 320-322, we would like to discuss the delivery and removal of terrigenous DOC in the river-estuary-ocean continuum. The literature you suggested appears to mainly focus on research conducted in the river segment. Nevertheless, we will add relevant discussion and cite relevant publications on this aspect.
    
    3. Removal of DOC in the Atchafalaya River
    We will add the following discussion on the points you raised (points 2-3):
    
    "Existing literature reveals that a significant part of tDOC delivered from rivers worldwide is depleted before entering the open ocean (Hedges et al., 1997; Opsahl and Benner, 1997; Looman et al., 2019). This signifies that tDOC is removed (mineralized) by biological and/or abiotic processes within the river-estuary section. A study of the Mississippi-Atchafalaya River system by Fichot and Benner (2014) suggested that biomineralization is the main process for the removal of tDOC in the system, and around ~40% of tDOC is removed during the transport within the estuary. Xu et al. (2024) concluded that the disconnection caused by levee can reduce the delivery and transformation of riverine dissolved carbon. This reflects that a portion of depletion of riverine DOC may stem from disconnection with wetlands caused by engineering constructions. In the York River estuary, Raymond and Bauer (2000) reported that the proportion of tDOC removed by bacteria is ~10%. Other studies have also substantiated that estuaries serve as a reactor and filter for DOC cycling. A study of the Pearl River estuary by He et al. (2010) suggested microbial degradation as the primary bioprocess for the removal of DOC (~31% in the mixing zone). Another study reveals that the loss of DOC in the Lena River estuary can reach ~10-20% (Alling et al., 2010). Dai et al. (2012) estimated the removal of DOC in the Artic estuaries to be approximately 20%. Kumar et al. (2022) suggested that during the dry season, the Godavari estuary could remove ~33% DOC by photodegradation and microbial respiration. In the Changjiang Estuary, a series of 12-day incubation experiments showed that ~17% of estuarine DOC was removed after biodegradation (Guo et al., 2021). Surface microbial incubations showed that the deletion of DOC varied between 5% and 39% (Ji et al., 2021). In the Yellow River, the DOC flux is estimated at round 0.06 Tg/yr, which would become smaller if DOC burial or decomposition in the estuary is taken into account (Ran et al., 2013). In our simulations, results indicate that the removal of tDOC can reach ~60% at an annual scale. "
    
    4. estuarine DOC lost to the atmosphere via CO2
    The process involving in DOC tranformation and outgas into the atmosphere in the form of CO2 is indeed worth considering. Our paper focuses on the fate and transformation of estuarine DOC in the river-estuary-ocean continuum, highlighting the influence of hydrodynamic and biological processes on DOC. The contribution of DOC to CO2 is also mediated through the decomposition/production of DOC by bacteria and planktonic organisms, leading to the generation/consumption of CO2. Although we can not quantify the amount of DOC that is transformed to atmospheric CO2 in our model, discussion will be added in our revision.
    
    "Along with the transport and transformation of DOC in the river-estuary-ocean continuum, there is also significant attention and discussion on the release of CO2 during this process. He and Xu (2017) observed that DOC concentration decreased from freshwater to saltwater, which may be caused by physical or biogeochemical effects, with CO2 outgassing being much higher in the mixing zone compared to the freshwater zone. Research on the Neuse River Estuary indicates that hurricanes increase the loading of DOC. Persistence of DOC allows decomposition to CO2, which was supported by measurements of air-sea CO2 fluxes taken in the weeks following the hurricane (Osburn et al., 2019). In the estuaries of the South Atlantic Bight, the loss of DOC delivered to the estuaries through photochemical oxidation accounts for 6.4 to 7.3% of the total annual degassing of CO2 to the atmosphere in one year (Reader and Miller, 2012). Maher and Eyre (2012) found that in three autotrophic estuaries in Australia, the export of organic carbon exceeded its import, suggesting that estuaries functioned as bioreactors, converting DIC into organic carbon, supporting these estuaries as net sink of atmospheric CO2. These studies all demonstrate the intimate relationship between the transformation of DOC and CO2. Quantification the direct and indirect contributions of DOC to CO2 based on physical and biochemical processes may require further investigation. "
    
    Citation: https://doi.org/10.5194/bg-2024-2-AC2
RC1:
'Comment on bg-2024-2', Anonymous Referee #1, 02 Jun 2024

This manuscript aims at applying a model that describes dissolved organic carbon dynamics at the Changjiang Estuary, in order to identify the different processes affecting DOC dynamics in this particular site.
In general the manuscript is well written and easy to follow in all its parts. Although I am not an expert on modeling, I was able to follow the description and the application of the model that the authors used. I cannot comment on the specifics on the model used, as I am not an expert in this field, but it was clear enough that the model was properly validated by observational data over a large time scale.
In my opinion however, the authors need to work on the discussion part of the manuscript to highlight the importance of this study. Some important questions need to be answered, such as: why is this model important? what new information it gives that improves the knowledge on this region? how these results/model can be of use in other regions?
The discussion needs therefore to be re written taking these questions in mind. In the current form the discussion contains mostly a literature review on previous studies, not properly compared to the results of this study.
Also the introduction strongly needs a revision in order to have an updated bibliography. There are too many outdated references, sometimes as the only ones, that can be updated with much more recent studies
Specific comments
Line 15: salinity has no units. To be checked throughout the entire manuscript.
Lines 23-24: “DOC is defined as the nonliving organic matter in the ocean that can pass a 0.5µm pore size filter…”. This definition is not correct. DOC is operationally defined as the organic carbon that passes through a 0.2 µm pore size filter. Sometimes also 0.77 µm pore size filter is used. Also the references here needs to be adjourned.
Lines 27-28: “DOC in estuaries is predominantly derived from river inputs and marine production”. In situ production processes should be mentioned too here. Also because they are mentioned later in the manuscript.
Line 78: SPM needs to be defined.
Lined 89-92: Here the authors introduce DOM, however in the manuscript only DOC is discussed. Either the authors mention only DOC or it should be clarified the link between DOC and DOM.
Line 96: Why the turnover time scales taken into account are limited to 70 years. Refractory DOC has a turnover time that is much larger than 70 years. For turnover time of DOC see Hansell, 2013 (https://doi.org/10.1146/annurev-marine-120710-100757).
Line 145: Table 1. Some data miss the data source. Where are these data coming from?
Line 159: Reference to figure S1. There should be also figure S2. These two figures are useful to understand the comparison between the observational data and the model data. However being two different figures and being the images (surface/bottom, summer/winter) displaced in a different order a comparison is difficult to make. I would suggest to merge these two figure together and displace the observational/modeled data next to each other.
By looking at these figures, I think it would be interesting to also highlight where there is least correspondence between the observations and the model and discuss that too.
Lines 167-168: “the seasonal average of the model results over the years 2013-2017 was calculated for all four seasons”. Why only summer and winter were chosen?
Line 181: In the caption of Figure 4 there is no details on the 6 panels. Also it is not specified if these plots are from observational or model data.
Line 242: “The released mDOC from bacteria is converted into semi-refractory mDOC”. This statement needs to be supported by a reference.
Line 250: Figure 5 is difficult to read, especially the dotted lines, which are too similar as color and too thin

Citation: https://doi.org/10.5194/bg-2024-2-RC1
- AC3: 'Reply on RC1', Jialing Yao, 02 Jul 2024
  
  Please see the reply in attached document.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC3
RC2:
'Comment on bg-2024-2', Anonymous Referee #2, 10 Jun 2024
Yao et al used a physical mixing coupled with biogeochemistry model to investigate DOC cycling in the Changjiang Estuary along the land to coastal ocean continuum. They find with their model that in the summer, DOC distributions are dependent on biogeochemical processes as well as physical mixing, while in the winter, physical mixing predominates. The study found that terrestrial DOC is not susceptible to bacterial consumption in the estuarine system, but highly susceptible to marine bacteria consumption. Finally, the estuary is a source of DOC to the coastal ocean.
I found the study interesting and suitable for publication after moderate revisions, and have a few major comments for the authors to consider, listed below:
I think the authors need to go more into depth about their model set up. Why is it that refractory DOC, which makes up a large portion of the total pool, is not accounted for in the model at all? Would that simply be grouped together with the semi-refractory pool? Please clarify.

It seems like the semi-refractory pool in the model is a closed loop and not connected to the semi-labile/labile pools of DOC, which the model in Figure 1 suggests are impacted mostly by phyto- and zoo-plankton. However, bacteria play a role in the conversion of labile to semi-labile DOC and semi-labile to semi-refractory (and so on). It also looks like from the arrows in the model setup in Figure 1 that bacteria are taking up non-photolabile DOC and converting it into the semi-refractory pool.

How does the model consider past work that DOM that has been photochemically altered can become more biologically labile? The authors mention something about this in the text (how aromatics are biologically resistant, but photochemically susceptible), but don’t really go into detail, as far as I can tell. Photo-transformed, newly biologically labile DOM may also enhance bacterial productivity. Please at least discuss this in the paper (papers from Medeiros https://doi.org/10.1002/2014GL062663, Mopper, and Zhou may provide some insights) and relate to where this may fit into the model.

While I like Figures 4 and 5 a lot, I think an additional figure or subplot showing DOC vs. salinity and a conserved mixing line would be informative to this study to show where and when it diverges from mixing.

There could be additional discussion. I think there is a lot to be discussed relating the findings to past studies that look at priming of DOM (Bianchi work), and how DOM may be refractory in one location / time, but when transported to a different location / time / set of environmental conditions, it may be more labile (Shen & Benner, 2018, among others). A more detailed discussion of why in the winter DOC is conserved and in the summer it isn’t would be valuable as well.

The English is overall good but I noticed several typos.

Specific comments:
Line 24: “non-living” organic matter. That’s not necessarily true because DOC is between 0.2-0.77 microns and small bacteria can pass through 0.77 microns (so their biomass would technically be a part of the DOC pool).
Line 31: Marine DOC is not mainly derived from local production. At the surface ocean, maybe 30-50% of it is autochthonous; the other >50% is refractory and allochthonous.
Line 58: Anthropogenic activities are mentioned here as being a part of the study but then aren’t referred to again.
Line 91- why would aromatic compounds precipitating with metal ions have anything to do with photo-oxidation? That line comes out of place.
Lines 93-95: I understand for simplicity sake to keep the model as two types of DOC, but recent studies have shown that DOC that is photodegraded can become more biologically labile. So does then this photodegraded DOC move into the other pool of DOC? (see major comment above)
Figure 2b. The sampling points are very difficult to see on top of the bathymetry background (those points for 2006 are virtually impossible to distinguish). I suggest changing the way the points look (maybe filling in the color, increasing the contract).
Line 143: “757 data points are for the bottom water” – What is the depth range of this bottom water?
Line 175: “significant contract” – is it statistical? If not please avoid using that term. Also, this is referring to DOC, right?
Lines 239-240 : Please re-orient the reader to Figure 1 when discussing phyto-/zooplankton and bacteria.
Line 280: Rates are reduced in winter. Makes sense. Please tie together biogeochemically / seasonally better why in the winter it’s mostly just physical processes, whereas in the summer there are biogeochemical influences.
Citation: https://doi.org/10.5194/bg-2024-2-RC2
- AC4: 'Reply on RC2', Jialing Yao, 04 Jul 2024
  
  Please see the reply in attached document.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC4

Status: closed

CC1:
'Comment on bg-2024-2', Y. Jun Xu, 16 Apr 2024

Line53: Discharge from the Changjiang River has changed since the Three Georges Dam was completed in 2003. The cited reference (Tian et al., 1993) is outdated and I would suggest the authors cite more recent publications, e.g., Zhang W et al. 2021 (https://doi.org/10.1016/j.geomorph.2021.108075) or Yin S et al. 2023 (http://dx.doi.org/10.1016/j.scitotenv.2023.162758)

Citation: https://doi.org/10.5194/bg-2024-2-CC1
- AC1:
  'Reply on CC1', Jialing Yao, 16 Apr 2024
  
  Thank you for your review and suggestion. I will update the citiation in the revision.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC1
  - CC2: 'Reply on AC1', Y. Jun Xu, 17 Apr 2024
    
    The thank the authors for their response to my previous comment.
    I have a couple of comments/suggestions:
    - This modeling work was performed for the period 2013-2017 and a value of 385 ppm was chosen for the atmospheric CO2 concentration for the five study years. However, the atmospheric CO2 conc. already reached 400 ppm in 2013, and with a ~3 ppm annual increase for the following years. Please discuss the possible effect of this CO2 setting on the modeling results.
    - 320-322: I would suggest the authors add more recent publications on the subject; for instance, Mekong River (Li S. et al., https://doi.org/10.1016/j.jhydrol.2013.09.024), Yellow River ( Ran, L. et al., https://doi.org/10.1016/j.jhydrol.2013.06.018), Mississippi River (Reiman & Xu, https://doi.org/10.1016/j.jhydrol.2019.124093).
    - 322-324: The Atchafalaya River is a large freshwater-swamp system and it is not affected by marine water. DOC removal in the system is mainly through the high connectivity of the river's braided channels with extensive floodplains and backwaters (see Xu et al., https://doi.org/10.1016/j.scitotenv.2024.171604; Xu YJ, https://doi.org/10.3390/w5020379)
    - L324-335: A considerable amount of estuarine DOC can be lost to the atmosphere via CO2 (e.g., He & Xu, https://doi.org/10.1007/s12237-017-0320-4). This aspect deserves to be discussed.
    
    Citation: https://doi.org/10.5194/bg-2024-2-CC2
    
    AC2: 'Reply on CC2', Jialing Yao, 06 May 2024
    
    Thank you very much for your insightful comments. Based on the suggestions you raised, our point-to-point response is listed below:
    
    1. Possible effect of underestimation of atmospheric of CO2 concentration
    Taking this issue into consideration, we adjusted the model configuration to set pCO2 at 400ppm with a increase 3ppm per year for sensitivity experiment. The model results indicate that the DOC concentration level remained almost unchanged. In addition, we have reviewed relevant literature. Mou et al. (2017, https://doi.org/10.1007/s10811-017-1089-3) conducted cultivation experiments on marine picocyanobacteria under ambient (380ppmv) and elevated (1000ppmv) CO2 levels. They found that it led to a reduction in cellular chlorophyll a, but did not observe any changes in DOC. Engel et al. (2013, https://doi.org/10.5194/bg-10-1291-2013) suggested that elevated pCO2 has a direct influence on DOC production. However, there is not obvious DOC accumulation after nutrient addition which is due to rapid utilization of fresh produced DOC by bacteria. Under certain circumstances, increased atmospheric CO2 concentrations can lead to an increase in seawater pCO2 levels. James A. et al. (2017, https://doi.org/10.1371/journal.pone.0173145) investigated the impact of increased seawater pCO2 on bacterioplankton. They proposed that elevated pCO2 levels (1000-1500ppm) increase the rate and magnitude of removal of organic carbon by bacterioplankton communities compared to low pCO2 levels (250-400ppm). This effect is attributed to the significant differences in pCO2 concentrations.
    Therefore, based on the model results and the aforementioned studies, the underestimation is minor compared to the actual value, and its impact on DOC concentration may be offset by other processes. Thus, the potential impact of underestimation on DOC is minor. In subsequent revision of the manuscript, we will update this value to better reflect the actual situation and discuss the potential impact of further enhanced pCO2 in future scenarios.
    
    2. 320-322 add publications
    In line 320-322, we would like to discuss the delivery and removal of terrigenous DOC in the river-estuary-ocean continuum. The literature you suggested appears to mainly focus on research conducted in the river segment. Nevertheless, we will add relevant discussion and cite relevant publications on this aspect.
    
    3. Removal of DOC in the Atchafalaya River
    We will add the following discussion on the points you raised (points 2-3):
    
    "Existing literature reveals that a significant part of tDOC delivered from rivers worldwide is depleted before entering the open ocean (Hedges et al., 1997; Opsahl and Benner, 1997; Looman et al., 2019). This signifies that tDOC is removed (mineralized) by biological and/or abiotic processes within the river-estuary section. A study of the Mississippi-Atchafalaya River system by Fichot and Benner (2014) suggested that biomineralization is the main process for the removal of tDOC in the system, and around ~40% of tDOC is removed during the transport within the estuary. Xu et al. (2024) concluded that the disconnection caused by levee can reduce the delivery and transformation of riverine dissolved carbon. This reflects that a portion of depletion of riverine DOC may stem from disconnection with wetlands caused by engineering constructions. In the York River estuary, Raymond and Bauer (2000) reported that the proportion of tDOC removed by bacteria is ~10%. Other studies have also substantiated that estuaries serve as a reactor and filter for DOC cycling. A study of the Pearl River estuary by He et al. (2010) suggested microbial degradation as the primary bioprocess for the removal of DOC (~31% in the mixing zone). Another study reveals that the loss of DOC in the Lena River estuary can reach ~10-20% (Alling et al., 2010). Dai et al. (2012) estimated the removal of DOC in the Artic estuaries to be approximately 20%. Kumar et al. (2022) suggested that during the dry season, the Godavari estuary could remove ~33% DOC by photodegradation and microbial respiration. In the Changjiang Estuary, a series of 12-day incubation experiments showed that ~17% of estuarine DOC was removed after biodegradation (Guo et al., 2021). Surface microbial incubations showed that the deletion of DOC varied between 5% and 39% (Ji et al., 2021). In the Yellow River, the DOC flux is estimated at round 0.06 Tg/yr, which would become smaller if DOC burial or decomposition in the estuary is taken into account (Ran et al., 2013). In our simulations, results indicate that the removal of tDOC can reach ~60% at an annual scale. "
    
    4. estuarine DOC lost to the atmosphere via CO2
    The process involving in DOC tranformation and outgas into the atmosphere in the form of CO2 is indeed worth considering. Our paper focuses on the fate and transformation of estuarine DOC in the river-estuary-ocean continuum, highlighting the influence of hydrodynamic and biological processes on DOC. The contribution of DOC to CO2 is also mediated through the decomposition/production of DOC by bacteria and planktonic organisms, leading to the generation/consumption of CO2. Although we can not quantify the amount of DOC that is transformed to atmospheric CO2 in our model, discussion will be added in our revision.
    
    "Along with the transport and transformation of DOC in the river-estuary-ocean continuum, there is also significant attention and discussion on the release of CO2 during this process. He and Xu (2017) observed that DOC concentration decreased from freshwater to saltwater, which may be caused by physical or biogeochemical effects, with CO2 outgassing being much higher in the mixing zone compared to the freshwater zone. Research on the Neuse River Estuary indicates that hurricanes increase the loading of DOC. Persistence of DOC allows decomposition to CO2, which was supported by measurements of air-sea CO2 fluxes taken in the weeks following the hurricane (Osburn et al., 2019). In the estuaries of the South Atlantic Bight, the loss of DOC delivered to the estuaries through photochemical oxidation accounts for 6.4 to 7.3% of the total annual degassing of CO2 to the atmosphere in one year (Reader and Miller, 2012). Maher and Eyre (2012) found that in three autotrophic estuaries in Australia, the export of organic carbon exceeded its import, suggesting that estuaries functioned as bioreactors, converting DIC into organic carbon, supporting these estuaries as net sink of atmospheric CO2. These studies all demonstrate the intimate relationship between the transformation of DOC and CO2. Quantification the direct and indirect contributions of DOC to CO2 based on physical and biochemical processes may require further investigation. "
    
    Citation: https://doi.org/10.5194/bg-2024-2-AC2
RC1:
'Comment on bg-2024-2', Anonymous Referee #1, 02 Jun 2024

This manuscript aims at applying a model that describes dissolved organic carbon dynamics at the Changjiang Estuary, in order to identify the different processes affecting DOC dynamics in this particular site.
In general the manuscript is well written and easy to follow in all its parts. Although I am not an expert on modeling, I was able to follow the description and the application of the model that the authors used. I cannot comment on the specifics on the model used, as I am not an expert in this field, but it was clear enough that the model was properly validated by observational data over a large time scale.
In my opinion however, the authors need to work on the discussion part of the manuscript to highlight the importance of this study. Some important questions need to be answered, such as: why is this model important? what new information it gives that improves the knowledge on this region? how these results/model can be of use in other regions?
The discussion needs therefore to be re written taking these questions in mind. In the current form the discussion contains mostly a literature review on previous studies, not properly compared to the results of this study.
Also the introduction strongly needs a revision in order to have an updated bibliography. There are too many outdated references, sometimes as the only ones, that can be updated with much more recent studies
Specific comments
Line 15: salinity has no units. To be checked throughout the entire manuscript.
Lines 23-24: “DOC is defined as the nonliving organic matter in the ocean that can pass a 0.5µm pore size filter…”. This definition is not correct. DOC is operationally defined as the organic carbon that passes through a 0.2 µm pore size filter. Sometimes also 0.77 µm pore size filter is used. Also the references here needs to be adjourned.
Lines 27-28: “DOC in estuaries is predominantly derived from river inputs and marine production”. In situ production processes should be mentioned too here. Also because they are mentioned later in the manuscript.
Line 78: SPM needs to be defined.
Lined 89-92: Here the authors introduce DOM, however in the manuscript only DOC is discussed. Either the authors mention only DOC or it should be clarified the link between DOC and DOM.
Line 96: Why the turnover time scales taken into account are limited to 70 years. Refractory DOC has a turnover time that is much larger than 70 years. For turnover time of DOC see Hansell, 2013 (https://doi.org/10.1146/annurev-marine-120710-100757).
Line 145: Table 1. Some data miss the data source. Where are these data coming from?
Line 159: Reference to figure S1. There should be also figure S2. These two figures are useful to understand the comparison between the observational data and the model data. However being two different figures and being the images (surface/bottom, summer/winter) displaced in a different order a comparison is difficult to make. I would suggest to merge these two figure together and displace the observational/modeled data next to each other.
By looking at these figures, I think it would be interesting to also highlight where there is least correspondence between the observations and the model and discuss that too.
Lines 167-168: “the seasonal average of the model results over the years 2013-2017 was calculated for all four seasons”. Why only summer and winter were chosen?
Line 181: In the caption of Figure 4 there is no details on the 6 panels. Also it is not specified if these plots are from observational or model data.
Line 242: “The released mDOC from bacteria is converted into semi-refractory mDOC”. This statement needs to be supported by a reference.
Line 250: Figure 5 is difficult to read, especially the dotted lines, which are too similar as color and too thin

Citation: https://doi.org/10.5194/bg-2024-2-RC1
- AC3: 'Reply on RC1', Jialing Yao, 02 Jul 2024
  
  Please see the reply in attached document.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC3
RC2:
'Comment on bg-2024-2', Anonymous Referee #2, 10 Jun 2024
Yao et al used a physical mixing coupled with biogeochemistry model to investigate DOC cycling in the Changjiang Estuary along the land to coastal ocean continuum. They find with their model that in the summer, DOC distributions are dependent on biogeochemical processes as well as physical mixing, while in the winter, physical mixing predominates. The study found that terrestrial DOC is not susceptible to bacterial consumption in the estuarine system, but highly susceptible to marine bacteria consumption. Finally, the estuary is a source of DOC to the coastal ocean.
I found the study interesting and suitable for publication after moderate revisions, and have a few major comments for the authors to consider, listed below:
I think the authors need to go more into depth about their model set up. Why is it that refractory DOC, which makes up a large portion of the total pool, is not accounted for in the model at all? Would that simply be grouped together with the semi-refractory pool? Please clarify.

It seems like the semi-refractory pool in the model is a closed loop and not connected to the semi-labile/labile pools of DOC, which the model in Figure 1 suggests are impacted mostly by phyto- and zoo-plankton. However, bacteria play a role in the conversion of labile to semi-labile DOC and semi-labile to semi-refractory (and so on). It also looks like from the arrows in the model setup in Figure 1 that bacteria are taking up non-photolabile DOC and converting it into the semi-refractory pool.

How does the model consider past work that DOM that has been photochemically altered can become more biologically labile? The authors mention something about this in the text (how aromatics are biologically resistant, but photochemically susceptible), but don’t really go into detail, as far as I can tell. Photo-transformed, newly biologically labile DOM may also enhance bacterial productivity. Please at least discuss this in the paper (papers from Medeiros https://doi.org/10.1002/2014GL062663, Mopper, and Zhou may provide some insights) and relate to where this may fit into the model.

While I like Figures 4 and 5 a lot, I think an additional figure or subplot showing DOC vs. salinity and a conserved mixing line would be informative to this study to show where and when it diverges from mixing.

There could be additional discussion. I think there is a lot to be discussed relating the findings to past studies that look at priming of DOM (Bianchi work), and how DOM may be refractory in one location / time, but when transported to a different location / time / set of environmental conditions, it may be more labile (Shen & Benner, 2018, among others). A more detailed discussion of why in the winter DOC is conserved and in the summer it isn’t would be valuable as well.

The English is overall good but I noticed several typos.

Specific comments:
Line 24: “non-living” organic matter. That’s not necessarily true because DOC is between 0.2-0.77 microns and small bacteria can pass through 0.77 microns (so their biomass would technically be a part of the DOC pool).
Line 31: Marine DOC is not mainly derived from local production. At the surface ocean, maybe 30-50% of it is autochthonous; the other >50% is refractory and allochthonous.
Line 58: Anthropogenic activities are mentioned here as being a part of the study but then aren’t referred to again.
Line 91- why would aromatic compounds precipitating with metal ions have anything to do with photo-oxidation? That line comes out of place.
Lines 93-95: I understand for simplicity sake to keep the model as two types of DOC, but recent studies have shown that DOC that is photodegraded can become more biologically labile. So does then this photodegraded DOC move into the other pool of DOC? (see major comment above)
Figure 2b. The sampling points are very difficult to see on top of the bathymetry background (those points for 2006 are virtually impossible to distinguish). I suggest changing the way the points look (maybe filling in the color, increasing the contract).
Line 143: “757 data points are for the bottom water” – What is the depth range of this bottom water?
Line 175: “significant contract” – is it statistical? If not please avoid using that term. Also, this is referring to DOC, right?
Lines 239-240 : Please re-orient the reader to Figure 1 when discussing phyto-/zooplankton and bacteria.
Line 280: Rates are reduced in winter. Makes sense. Please tie together biogeochemically / seasonally better why in the winter it’s mostly just physical processes, whereas in the summer there are biogeochemical influences.
Citation: https://doi.org/10.5194/bg-2024-2-RC2
- AC4: 'Reply on RC2', Jialing Yao, 04 Jul 2024
  
  Please see the reply in attached document.
  
  Citation: https://doi.org/10.5194/bg-2024-2-AC4

Jialing Yao, Zhi Chen, Jianzhong Ge, and Wenyan Zhang

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https://doi.org/10.5194/bg-2024-2-supplement

Jialing Yao, Zhi Chen, Jianzhong Ge, and Wenyan Zhang

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The transformation of dissolved organic carbon (DOC) in estuaries is vital for costal carbon cycling. We studied source-to-sink pathways of DOC in the Changjiang Estuary using a physics-biogeochemistry model. Results showed a transition from sink to source of DOC in the plume area during summer, with a transition from terrestrial-dominant to marine-dominant. Terrigenous and marine DOC exports account for about 31 % and 69 %, respectively.


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