Conceptual models of dissolved carbon fluxes considering interannual typhoon responses under extreme climates in a two-layer stratified lake

Lin, Hao-Chi; Nakayama, Keisuke; Tsai, Jeng-Wei; Chiu, Chih-Yu

doi:https://doi.org/10.5194/egusphere-2022-852

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https://doi.org/10.5194/egusphere-2022-852

Preprints

24 Oct 2022

| 24 Oct 2022

Conceptual models of dissolved carbon fluxes considering interannual typhoon responses under extreme climates in a two-layer stratified lake

Hao-Chi Lin, Keisuke Nakayama, Jeng-Wei Tsai, and Chih-Yu Chiu

Abstract. Extreme climates affect the seasonal and interannual patterns of carbon (C) distribution due to the regimes of river inflow and thermal stratification within lentic ecosystems. Typhoons rapidly load substantial amounts of terrestrial C into subtropical small lakes, renewing and mixing the water column. We developed conceptual dissolved C models and hypothesized that allochthonous C loading and river inflow intrusion may affect the dissolved inorganic C (DIC) and dissolved organic C (DOC) distributions in a small subtropical lake under these extreme climates. A two-layer conceptual C models was developed to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual time scales in a small subtropical lake (i.e., Yuan‒Yang Lake) while simultaneously considering autochthonous processes such as algal photosynthesis, remineralization, and vertical transportation. Monthly field samplings were conducted to measure DIC, DOC, and chlorophyll a concentrations to compare the temporal patterns of fluxes between typhoon years (2015–2016) and non-typhoon years (2017–2018). The results demonstrated that net ecosystem production was 3.14 times higher in the typhoon years than in the non-typhoon years in Yuan‒Yang Lake. The results suggested that the load of allochthonous C was the most crucial factor affecting the temporal variation of C fluxes in the typhoon years; on the other hand, the transportation rate shaped the seasonal C in the non-typhoon years due to thermal stratification within this small subtropical lake.

Received: 30 Aug 2022 – Discussion started: 24 Oct 2022

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Hao-Chi Lin et al.

Status: closed

RC1:
'Comment on egusphere-2022-852', Anonymous Referee #1, 20 Nov 2022

In this paper a two-layer conceptual C models was developed in a small subtropical lake to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual time scales. Monthly field samplings were conducted to measure DIC, DOC, and chlorophyll a concentrations to compare the temporal patterns of fluxes between typhoon years and non-typhoon years. It is an interesting study, and the manuscript need to be revised.

(1) Line 176-179, “ where, total lake volume (ð_{ð¡ðð¡ðð}, 53,544 m³) departs to the upper layer (ð_ð, 45,456 m³) and to the lower layer (ð_ð¿, 8,808 m³) (Equation 5), and where lake surface area (ð´_ð) is 36,000 m² and the bottom of lake area (ð´_ðµ) is 3,520 m². The interface is 2.5 m vertically, and the interface area (ð´ð¼) is 7,264 m² in YYL.” The volume of upper layer and lower layer may change in time of different month, it is not a constant number and better to give the explanations.

(2) Line 225-226 “2.3.3 NEP of DIC and DOC, The net ecosystem production was defined as the difference between primary production and ecological respiration due to photosynthesis and respiration via biota”. The net ecosystem production has close relationship with water temperature and solar radiation in each month, especially in non-typhoon years. So, the discussions on the effects on NEP by temperature and solar radiation may be important.

(3) In the discussion, the CO₂ emission flux in different month for the small subtropical lake may be more interesting.

Citation: https://doi.org/10.5194/egusphere-2022-852-RC1
- AC1:
  'Reply on RC1', Hao-Chi Lin, 03 Mar 2023
  Dear Referee # 1
  Thanks for your comments. The manuscript has been revised, taking into account your comments below (or Supplement).
  Thanks for your comment. We have added, “The water depth is steady and changes. However, the change in water depth ranges from 4.56 to 4.66 m during the typhoon period. Therefore, we can assume that the changes in lake volumes and areas were negligible.” in the manuscript.
  
  Thanks for your suggestion. We have added a paragraph about the seasonal change of DIC and DOC fluxes in the discussion.
  
  Thanks for your comment. We have added some sentences about the seasonal change of CO₂ emission in the discussion.
  
  Citation: https://doi.org/10.5194/egusphere-2022-852-AC1
RC2:
'Comment on egusphere-2022-852', Anonymous Referee #2, 18 Dec 2022

Overall, this is an interesting study that measured DOC, DIC and Chl a in a small lake monthly for two years of contrasting precipitation. Water inputs and outputs were estimated and the observed concentrations were compared to a model predicting daily concentrations and fluxes for a two year period. The model output was further explored by simulating results from two climate scenarios that altered the water distribution terms in the model. The motivation and objectives to understanding precipitation-driven influence on lake carbon cycling align with the journal scope and the results are likely of interest to readers if the work can be more clearly communicated. While the paper is generally well-organized, the methods and results lack detail and clarity. This manuscript requires further careful editing for English grammar and spelling throughout. I commend the authors for their efforts in merging field data collection with modeling on this important topic and I hope my comments below are constructive.

No data availability statement was included.

Given the small size and shallow depth of this lake, does a single volume model predict average DIC, DOC, Chl a, and CO2 evasion dynamics just as well as a two-layer model?

Line specific comments

66-67 Change “practical” to partial

81 Ejarque et al is not correctly cited in this sentence. The study was not a subtropical lake with typhoons. It was a mountain lake in the European Alps. However, the study is very relevant to this work and should be discussed in relation to the results in the discussion section.

110-111 More information is needed to understand what was measured. What wavelengths were used to measure QSE? If this was an in-situ measurement, how were the results corrected for particle, temperature interreferences? What instrument was used?

134-135 Was the portable fluorometer was used to measure Chl a? This should be specified.

154-156 Water level was measured at a single river input. Was discharge also measured? How was water input estimated for the many other rivers? Was direct precipitation over the lake surface area also accounted for?

157-160 35% doesn’t seem correct given the other precipitation values reported in the sentence. It also doesn’t appear to match table 1 values.

Equations 1-6 Consider adding a table that clearly identifies each term, its units, and whether or not it was measured or fitted. The many terms are difficult to follow and are not immediately explained in the text before new equations are introduced.

211 What is meant by absorption coefficient in units per day? Light attenuation typically has units per length.

215-216 What type of regression? Linear/nonlinear?

247 248 This sentence compares two periods of typhoon years.

281 “perfectly” is subjective. Quantify this comparison including errors.

286 Here alpha is referred to as a photosynthetic absorption rate, not a coefficient.

356-357 My understanding from the text above was that a mass balance was applied to remove the influx of riverine DOC from the NEP calculation. Otherwise, river inputs would dominate over autochthonous NEP in this small system. If riverine C is included in the NEP, then maybe NEP is not a good term for this model output. Perhaps it is better referred to as a DIC/DOC flux from mass balance.

710 I do not understand what is meant by “nonseasonal data” in this context. Can you use a different term?

Figure 6 should include confidence intervals for the daily modeled values.

Citation: https://doi.org/10.5194/egusphere-2022-852-RC2
- AC2:
  'Reply on RC2', Hao-Chi Lin, 03 Mar 2023
  Dear Referee # 2,
  We appreciate your positive and constructive comments. We have checked the manuscript thoroughly and completed an English proofreading. The manuscript has been revised, taking into account your comments below (or Supplement).
  General comments
  We have added the data availability section, "The data that support the findings of this study are adopted from our previous works, including Chiu et al. 2020, Lin et al. 2021, and Lin et al. 2022."
  
  Because the thermal stratification was a vital process that controls the vertical profile of carbon concentration in YYL (Lin et al. 2021), this suggests that the two-layer system is more reasonable for characterizing the DIC and DOC dynamics within the lake.
  
  References:
  
  Lin, H.-C., Chiu, C.-Y., Tsai, J.-W., Liu, W.-C., Tada, K., and Nakayama, K.: Influence of Thermal Stratification on Seasonal Net Ecosystem Production and Dissolved Inorganic Carbon in a Shallow Subtropical Lake, J. Geophys. Res. Biogeosci., 126, https://doi.org/10.1029/2020JG005907, 2021.
  
  Nakayama, K., Kawahara, Y., Kurimoto, Y., Tada, K., Lin, H.-C., Hung, M.-C., Hsueh, M.-L., and Tsai, J.-W.: Effects of oyster aquaculture on carbon capture and removal in a tropical mangrove lagoon in southwestern Taiwan, Sci. Total Environ, 156460, https://doi.org/10.1016/j.scitotenv.2022.156460, 2022.
  
  Line specific comments
  Line 66-67. Thank you, we have revised the typo.
  Line 81. Thank you for your suggestion. We have removed the citation and added some sentences about this paper in the discussion.
  Line 110-111. Thank you for your comment. We have added the specific wavelength (254 nm) in this sentence.
  Line 134-135. Thank you, we have added the wavelength in the sentence.
  Line 154-156. We used the storage function model to estimate the river discharge using precipitation over the inflow river basin, and Nash–Sutcliffe model efficiency coefficient for the water level was > 0.70; thank you.
  Line 157-160. The 35.6 % is via total typhoon rainfall (2,254 mm) over the total precipitation (6,332 mm) from 2015 to 2016. Sorry to make you confused.
  Equation 1-6. Thank you for your suggestion. Table 2 was added to explain the terms and units of Equations 1-6.
  Line 211. Thanks for your comment. The alpha_PU and alpha_PL are constants to obtain the absorption rates via Chlorophyll a concentrations, which are not the light attenuation (Table 2-3).
  Line 247-248. Yes, we have revised the sentence; thank you.
  Line 281. Thank you, we have removed “perfectly” from the text.
  Line 286. It is a coefficient, not the absorption rate. We have revised it; thank you.
  Line 356-357. Thanks for your suggestions. We have revised the terms thoroughly.
  Line 710. Thank you for your comment; we have changed “nonseasonal data” to “inter-annual data” in the manuscript.
  Figure 6. “Best-fit” means the best result for model fitting, so the data would not have a confidence interval. Nakayama et al. (2022) also have the best-fit results in figure 7. Thus, we cannot add the confidence interval in Figure 6; sorry about that.
  Reference:
  Nakayama, K., Kawahara, Y., Kurimoto, Y., Tada, K., Lin, H.-C., Hung, M.-C., Hsueh, M.-L., and Tsai, J.-W.: Effects of oyster aquaculture on carbon capture and removal in a tropical mangrove lagoon in southwestern Taiwan, Sci. Total Environ, 156460, https://doi.org/10.1016/j.scitotenv.2022.156460, 2022.
  
  Citation: https://doi.org/10.5194/egusphere-2022-852-AC2

Status: closed

RC1:
'Comment on egusphere-2022-852', Anonymous Referee #1, 20 Nov 2022

In this paper a two-layer conceptual C models was developed in a small subtropical lake to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual time scales. Monthly field samplings were conducted to measure DIC, DOC, and chlorophyll a concentrations to compare the temporal patterns of fluxes between typhoon years and non-typhoon years. It is an interesting study, and the manuscript need to be revised.

(1) Line 176-179, “ where, total lake volume (ð_{ð¡ðð¡ðð}, 53,544 m³) departs to the upper layer (ð_ð, 45,456 m³) and to the lower layer (ð_ð¿, 8,808 m³) (Equation 5), and where lake surface area (ð´_ð) is 36,000 m² and the bottom of lake area (ð´_ðµ) is 3,520 m². The interface is 2.5 m vertically, and the interface area (ð´ð¼) is 7,264 m² in YYL.” The volume of upper layer and lower layer may change in time of different month, it is not a constant number and better to give the explanations.

(2) Line 225-226 “2.3.3 NEP of DIC and DOC, The net ecosystem production was defined as the difference between primary production and ecological respiration due to photosynthesis and respiration via biota”. The net ecosystem production has close relationship with water temperature and solar radiation in each month, especially in non-typhoon years. So, the discussions on the effects on NEP by temperature and solar radiation may be important.

(3) In the discussion, the CO₂ emission flux in different month for the small subtropical lake may be more interesting.

Citation: https://doi.org/10.5194/egusphere-2022-852-RC1
- AC1:
  'Reply on RC1', Hao-Chi Lin, 03 Mar 2023
  Dear Referee # 1
  Thanks for your comments. The manuscript has been revised, taking into account your comments below (or Supplement).
  Thanks for your comment. We have added, “The water depth is steady and changes. However, the change in water depth ranges from 4.56 to 4.66 m during the typhoon period. Therefore, we can assume that the changes in lake volumes and areas were negligible.” in the manuscript.
  
  Thanks for your suggestion. We have added a paragraph about the seasonal change of DIC and DOC fluxes in the discussion.
  
  Thanks for your comment. We have added some sentences about the seasonal change of CO₂ emission in the discussion.
  
  Citation: https://doi.org/10.5194/egusphere-2022-852-AC1
RC2:
'Comment on egusphere-2022-852', Anonymous Referee #2, 18 Dec 2022

Overall, this is an interesting study that measured DOC, DIC and Chl a in a small lake monthly for two years of contrasting precipitation. Water inputs and outputs were estimated and the observed concentrations were compared to a model predicting daily concentrations and fluxes for a two year period. The model output was further explored by simulating results from two climate scenarios that altered the water distribution terms in the model. The motivation and objectives to understanding precipitation-driven influence on lake carbon cycling align with the journal scope and the results are likely of interest to readers if the work can be more clearly communicated. While the paper is generally well-organized, the methods and results lack detail and clarity. This manuscript requires further careful editing for English grammar and spelling throughout. I commend the authors for their efforts in merging field data collection with modeling on this important topic and I hope my comments below are constructive.

No data availability statement was included.

Given the small size and shallow depth of this lake, does a single volume model predict average DIC, DOC, Chl a, and CO2 evasion dynamics just as well as a two-layer model?

Line specific comments

66-67 Change “practical” to partial

81 Ejarque et al is not correctly cited in this sentence. The study was not a subtropical lake with typhoons. It was a mountain lake in the European Alps. However, the study is very relevant to this work and should be discussed in relation to the results in the discussion section.

110-111 More information is needed to understand what was measured. What wavelengths were used to measure QSE? If this was an in-situ measurement, how were the results corrected for particle, temperature interreferences? What instrument was used?

134-135 Was the portable fluorometer was used to measure Chl a? This should be specified.

154-156 Water level was measured at a single river input. Was discharge also measured? How was water input estimated for the many other rivers? Was direct precipitation over the lake surface area also accounted for?

157-160 35% doesn’t seem correct given the other precipitation values reported in the sentence. It also doesn’t appear to match table 1 values.

Equations 1-6 Consider adding a table that clearly identifies each term, its units, and whether or not it was measured or fitted. The many terms are difficult to follow and are not immediately explained in the text before new equations are introduced.

211 What is meant by absorption coefficient in units per day? Light attenuation typically has units per length.

215-216 What type of regression? Linear/nonlinear?

247 248 This sentence compares two periods of typhoon years.

281 “perfectly” is subjective. Quantify this comparison including errors.

286 Here alpha is referred to as a photosynthetic absorption rate, not a coefficient.

356-357 My understanding from the text above was that a mass balance was applied to remove the influx of riverine DOC from the NEP calculation. Otherwise, river inputs would dominate over autochthonous NEP in this small system. If riverine C is included in the NEP, then maybe NEP is not a good term for this model output. Perhaps it is better referred to as a DIC/DOC flux from mass balance.

710 I do not understand what is meant by “nonseasonal data” in this context. Can you use a different term?

Figure 6 should include confidence intervals for the daily modeled values.

Citation: https://doi.org/10.5194/egusphere-2022-852-RC2
- AC2:
  'Reply on RC2', Hao-Chi Lin, 03 Mar 2023
  Dear Referee # 2,
  We appreciate your positive and constructive comments. We have checked the manuscript thoroughly and completed an English proofreading. The manuscript has been revised, taking into account your comments below (or Supplement).
  General comments
  We have added the data availability section, "The data that support the findings of this study are adopted from our previous works, including Chiu et al. 2020, Lin et al. 2021, and Lin et al. 2022."
  
  Because the thermal stratification was a vital process that controls the vertical profile of carbon concentration in YYL (Lin et al. 2021), this suggests that the two-layer system is more reasonable for characterizing the DIC and DOC dynamics within the lake.
  
  References:
  
  Lin, H.-C., Chiu, C.-Y., Tsai, J.-W., Liu, W.-C., Tada, K., and Nakayama, K.: Influence of Thermal Stratification on Seasonal Net Ecosystem Production and Dissolved Inorganic Carbon in a Shallow Subtropical Lake, J. Geophys. Res. Biogeosci., 126, https://doi.org/10.1029/2020JG005907, 2021.
  
  Nakayama, K., Kawahara, Y., Kurimoto, Y., Tada, K., Lin, H.-C., Hung, M.-C., Hsueh, M.-L., and Tsai, J.-W.: Effects of oyster aquaculture on carbon capture and removal in a tropical mangrove lagoon in southwestern Taiwan, Sci. Total Environ, 156460, https://doi.org/10.1016/j.scitotenv.2022.156460, 2022.
  
  Line specific comments
  Line 66-67. Thank you, we have revised the typo.
  Line 81. Thank you for your suggestion. We have removed the citation and added some sentences about this paper in the discussion.
  Line 110-111. Thank you for your comment. We have added the specific wavelength (254 nm) in this sentence.
  Line 134-135. Thank you, we have added the wavelength in the sentence.
  Line 154-156. We used the storage function model to estimate the river discharge using precipitation over the inflow river basin, and Nash–Sutcliffe model efficiency coefficient for the water level was > 0.70; thank you.
  Line 157-160. The 35.6 % is via total typhoon rainfall (2,254 mm) over the total precipitation (6,332 mm) from 2015 to 2016. Sorry to make you confused.
  Equation 1-6. Thank you for your suggestion. Table 2 was added to explain the terms and units of Equations 1-6.
  Line 211. Thanks for your comment. The alpha_PU and alpha_PL are constants to obtain the absorption rates via Chlorophyll a concentrations, which are not the light attenuation (Table 2-3).
  Line 247-248. Yes, we have revised the sentence; thank you.
  Line 281. Thank you, we have removed “perfectly” from the text.
  Line 286. It is a coefficient, not the absorption rate. We have revised it; thank you.
  Line 356-357. Thanks for your suggestions. We have revised the terms thoroughly.
  Line 710. Thank you for your comment; we have changed “nonseasonal data” to “inter-annual data” in the manuscript.
  Figure 6. “Best-fit” means the best result for model fitting, so the data would not have a confidence interval. Nakayama et al. (2022) also have the best-fit results in figure 7. Thus, we cannot add the confidence interval in Figure 6; sorry about that.
  Reference:
  Nakayama, K., Kawahara, Y., Kurimoto, Y., Tada, K., Lin, H.-C., Hung, M.-C., Hsueh, M.-L., and Tsai, J.-W.: Effects of oyster aquaculture on carbon capture and removal in a tropical mangrove lagoon in southwestern Taiwan, Sci. Total Environ, 156460, https://doi.org/10.1016/j.scitotenv.2022.156460, 2022.
  
  Citation: https://doi.org/10.5194/egusphere-2022-852-AC2

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Short summary

We successfully developed conceptual models to know how the dissolved carbon distributions under the climate change within a subtropical small lake, considering the physical and biochemical processes. The typhoons were crucial disturbances in subtropical ecosystems, controlling the seasonal variation and primary production due to large amounts of carbon loading and rapidly well-mixing within the whole-lake. whole lake.


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