Spatial and temporal variability of methane emissions and environmental conditions in a hyper-eutrophic fishpond

Znachor, Petr; Nedoma, Jiří; Kolar, Vojtech; Matoušů, Anna

doi:https://doi.org/10.5194/bg-20-4273-2023

Articles | Volume 20, issue 20

https://doi.org/10.5194/bg-20-4273-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-20-4273-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 20

Research article

|

19 Oct 2023

Research article |

| 19 Oct 2023

Spatial and temporal variability of methane emissions and environmental conditions in a hyper-eutrophic fishpond

Petr Znachor, Jiří Nedoma, Vojtech Kolar, and Anna Matoušů

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Final revised paper (published on 19 Oct 2023)
Supplement to the final revised paper
Preprint (discussion started on 19 Jan 2023)
Supplement to the preprint

Interactive discussion

Status: closed

RC1:
'Comment on bg-2023-4', Anonymous Referee #1, 10 Apr 2023

The authors describe the determination of methane emissions in a fishpond with special focus on controlling environmental conditions in the aquatic system and also in the atmosphere. Their work reveals the strong spatial and temporal variability, which has to be taken into account for several cases: for instance for the fishpond management, for the determination of regional carbon budget and the upscaling activities in climate modelling. I strongly support the statements regarding the consideration of this heterogeneity. However, as stated by the authors themselves, the amount of data is low in order to make a detailed consideration of the temporal variability (which is based on three dates in summer with three different sampling times). But all those who use such methods in the field know how much work is involved.
General comments:
I really appreciate the approach to consider the meteorological and atmospheric conditions as a controlling factor for greenhouse gas emissions. With this in mind, I recommend for future work the involvement of meteorological standard measurements into the monitoring program (such as air temperature, humidity and air pressure (especially to investigate the relation to ebullition fluxes); wind velocity and wind direction was already measured). Furthermore, also GHG concentration in ambient air can be a useful indicator to understand the temporal characteristics of emission processes in a better way.
At the end of the manuscript I expected a paragraph regarding recommendations for improved monitoring strategies for better estimation of methane emissions. The paper would gain a lot if all the recommendations made in the text were consolidated in one place in terms of best practice actions: how to measure, where, who often, which additional information is needed, ….
Some detailed comments:
Line 48-49 – Sanseverio et al., 2013 – in reference list 2012?
Line 70 – Jansen at al., 2020 – in reference list 2019?
Line 94 – 96 – you measure the values at the deepest point (at each sampling point or the deepest point of the pond?). It ist not clear to me at this point of the manuscript, later in text it becomes more clear. However, it would be good to mark this point in Fig. 1c as a prominent sampling point.
Line 101 – bbe_Moldaenke, Kiel
Line 202, Fig 2: As a comment – maybe the CV is not so well suited to show spatial heterogeneity of CH4 concentration. The mean values for July and August are very low with high SD, resulting in high CV values?
Line 479-481 – Beaulieu et al. not mentioned in main text
Line 577-579 – Ostrovsky et al. not mentioned in main text
Line 623-628 – Tranvik et al. not mentioned in main text

Citation: https://doi.org/10.5194/bg-2023-4-RC1
- AC1: 'Reply on RC1', Anna Matousu, 22 May 2023
  
  Dear Referee,
  we are thankful for your stimulating comments, suggestions, and recommendations. Below is our detailed, step-by-step response, your comments are in bold, followed by our responses.
  At the end of the manuscript, I expected a paragraph regarding recommendations for improved monitoring strategies for better estimation of methane emissions. The paper would gain a lot if all the recommendations made in the text were consolidated in one place in terms of best practice actions: how to measure, where, who often, which additional information is needed, ….
  As suggested, we added a separate paragraph with our recommendations at the end. For clarity, we inserted it right here.
  “For improved monitoring strategies, however, a continuous measurement approach like eddy covariance is generally more efficient than traditional sampling at regular intervals. Eddy covariance accounts for temporal variability and provides high temporal resolution data by continuously measuring wind speed, gas concentration, and vertical turbulent fluxes to estimate methane emissions (Erkillä et al., 2018). More importantly, it also offers spatially integrated measurements, averaging emissions over a larger area and therefore accounts for pond spatial heterogeneity. However, it's worth noting that the choice of monitoring approach depends on various factors, including the specific objectives, available resources, and the characteristics of the emission sources. To accurately capture both short-term variability and lake spatial heterogeneity of methane ebullition and diffusion fluxes, the most efficient approach was found to be a combination of continuous measurements with traditional methods including floating chambers, anchored funnels and boundary model calculations (Schubert et al., 2012, Podgrajsek et al., 2014, Erkillä et al., 2018). This integrated approach would provide a comprehensive understanding of methane emissions, enabling better estimation and more effective mitigation efforts.”
  Some detailed comments:
  Line 48-49 – Sanseverio et al., 2013 – in reference list 2012?
  Corrected to 2012.
  Line 70 – Jansen at al., 2020 – in reference list 2019?
  Corrected to 2019.
  Line 94 – 96 – you measure the values at the deepest point (at each sampling point or the deepest point of the pond?). It is not clear to me at this point of the manuscript, later in text it becomes more clear. However, it would be good to mark this point in Fig. 1c as a prominent sampling point.
  Done, see a new version of Fig. 1c and the description.
  "Figure 1. Location (a, b; copyright www.d-maps.com; https://d-maps.com/carte.php?num_car=2232&lang=en and https://d-maps.com/carte.php?num_car=265046&lang=en; modified) and bathymetric map (c; credit Jiří Jarošík) of the sampled Dehtář fishpond: Blue lines indicate hydrological connections; red dots representing the sampling points. Highlighted sampling point at the dam depicts the deepest site where vertical profiles were measured. Numbers indicate isobath depth."
  Line 101 – bbe_Moldaenke, Kiel
  Corrected.
  Line 202, Fig 2: As a comment – maybe the CV is not so well suited to show spatial heterogeneity of CH4 concentration. The mean values for July and August are very low with high SD, resulting in high CV values?
  We used the CV as a commonly used simple and easily interpretable parameter describing variability. As the value of CV is normalized for mean (CV=100 x standard deviation / mean) it allows comparing of different variables which may attain different numerical (mean) values. It reflects RELATIVE variability of values observed at different sampling points. Values in July and August are generally low but unequal, so CV is high. In September, values are high but more evenly distributed so CV is lower. Therefore, in our opinion, the used of CV is OK.
  Line 479-481 – Beaulieu et al. not mentioned in main text
  Deleted from the reference list.
  Line 577-579 – Ostrovsky et al. not mentioned in main text
  Deleted from the reference list.
  Line 623-628 – Tranvik et al. not mentioned in main text
  Deleted from the reference list.
  
  Citation: https://doi.org/10.5194/bg-2023-4-AC1
RC2:
'Comment on bg-2023-4', Anonymous Referee #2, 02 May 2023

The work of Znachor and co-authors describes the spatial and temporal variability of methane emissions from a large fish-pond.
This subject is certainly very important as the influence of small water bodies on the global budget is often not well constrained. Also, the problem of temporal variability is seldom assessed. However, there are some draw backs in the study:
Introduction: clarification which parameters react on which time scale…. And why these parameters are important for the spatio temporal variability…?

L 107 ff: it would be interesting to see the variations at one fixed station during the day..!
How long did it take to set up all the sampling sites?
The correction of the parameters for temporal variations is based on the assumption that the fluctuations are linear between the measured time points? But I would assume that at least oxygen (or parameters related to photosynthesis) vary with a sinus curve….
If all data were corrected for this temporal variation, how can you assess this influence later on with the statistics, as daytime variation?
The sampling scheme to assess the temporal and spatial variations are not well explained, and confusing…? May be a table would help here, with the deep station compared with the other stations.

L 125 ff, The Calculation of the diffusive flux is missing some crucial parameters: how was k determined? Which atmospheric CH4 concentration was used?
Discussion:
L310 ff: Could you give an estimate how many stations would be needed for your lake to get a good coverage of the variability? Could you calculate and plot the CV for n = 3, n=4…. n=16 samples
The results are well related to other studies, however explanations or reasons for the obtained results in this study are missing.
L316 ff: Why was the highest CH4 flux in your lake at the deepest station? Could you give any ideas?
L352: why did you find highest ebullition rates in September in your lake?

Further minor comments can be found in the attached pdf file.

Citation: https://doi.org/10.5194/bg-2023-4-RC2
- AC2: 'Reply on RC2', Anna Matousu, 22 May 2023
  
  Dear Referee,
  we are thankful for your stimulating comments, suggestions, and recommendations. For the sake of clarity, you will find our detailed, step-by-step responses in the attached pdf file, your comments are in bold, followed by our responses.
  
  Citation: https://doi.org/10.5194/bg-2023-4-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (05 Jun 2023) by Andrew Thurber

AR by Anna Matousu on behalf of the Authors (08 Jun 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (12 Jun 2023) by Andrew Thurber

RR by Anonymous Referee #1 (19 Jun 2023)

RR by Anonymous Referee #3 (09 Aug 2023)

Suggestions for revision or reasons for rejection

Znachor et al. have assembled a thoughtfully-executed study on methane emissions from a small water body. In three intensive sampling campaigns conducted in July, August, and September of the same year, they found that water depth was the most consistent predictor of methane fluxes in this system. This work is important given high uncertainty in the global methane budget and the role of small inland water bodies in it. Therefore, the research is suitable for publication in Biogeosciences, but the framing of the manuscript can be improved.
Specifically, it seems that the context of the studied small water body is not fully explored. This is an anthropogenic (though well-established) fishpond, which the authors describe as being intensively managed. However, the specific management practices in place at Dehtar fishpond are never described. It seems that as a fishpond specifically, the management goals would be to 1) produce fish and then 2) reduce environmental externalities (like methane emissions); what trade-offs might be invoked between these goals? Finally, as a hypereutrophic system, how might the results here apply to other hypereutrophic systems, including those that are not managed for aquaculture?
The manuscript could also use some polish in terms of careful editing, although the author’s meaning was generally unimpeded. I applaud the work that went into producing this dataset and wish the team the best of luck with their revisions.

Line edits:
48-49, After reading the references cited here, I remain skeptical that phytoplankton are themselves producing methane, please qualifying this statement by reframing with an appropriate term such as “preliminary” or “potential”.
76, Missing digits in Lat/Long?
324-330, It is unclear which ponds are being referred to in these two sentences. Upper layers being O2 saturated and sediments being anoxic does not consistently fit the data from Fig. 6, but the next sentence starts with “In such [systems]”.
333, Here too, which kinds of ponds?
339 – 349, Is it that ebullition is the dominate pathway in hyper-eutrophic ponds, or most small water bodies?
377, Is 4 to 24 mg L-1 O2 meant to be the gradient here? If so, “…a gradient of more than 4°C and 20 mg L-1 O2” would be clearer.
424, Be specific about your estimate here, what is the value?
432-444, formatting issue

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ED: Publish subject to minor revisions (review by editor) (09 Aug 2023) by Andrew Thurber

AR by Anna Matousu on behalf of the Authors (22 Aug 2023) Author's response Author's tracked changes Manuscript

ED: Publish as is (07 Sep 2023) by Andrew Thurber

AR by Anna Matousu on behalf of the Authors (12 Sep 2023) Manuscript

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Short summary

We conducted intensive spatial sampling of the hypertrophic fishpond to better understand the spatial dynamics of methane fluxes and environmental heterogeneity in fishponds. The diffusive fluxes of methane accounted for only a minor fraction of the total fluxes and both varied pronouncedly within the pond and over the studied summer season. This could be explained only by the water depth. Wind substantially affected temperature, oxygen and chlorophyll a distribution in the pond.