the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jan 2024
Event based high resolution measurement of DOC-concentration and quality in a rural headwater catchment
Abstract. The export of dissolved organic carbon (DOC) from small river systems is a significant factor in the global carbon cycle. DOC quality can be used to identify the sources of carbon in headwater systems. High-resolution in-situ measurements in small headwater catchments can unveil fast changing patterns of DOC export and DOC quality during events. In this study, the influence of precipitation events on DOC export and changing DOC quality was analyzed using highly resolved discharge and DOC concentration and quality data of 5-minute time steps. Data analysis was conducted using spearman correlation analysis, hysteresis analysis and visual comparison of pre-event and event conditions. Measurements took place from January 2021 until August 2022 in a German lower mountain catchment with predominantly agricultural land use. While DOC export was lower than in other catchments the DOC quality followed a well-observed seasonal pattern and was significantly influenced by the antecedent wetness of the catchment and the length of precipitation events. The results showed that the use of in-situ high resolution measurements can provide a detailed insight into the DOC export dynamics of a catchment and can help to identify the most important drivers of DOC quality changes.
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RC1: 'Comment on egusphere-2024-230', Anonymous Referee #1, 14 Apr 2024
The paper presents a comprehensive analysis of the dynamics of dissolved organic carbon (DOC) export in small river systems, shedding light on its pivotal role in the carbon cycle. Through meticulous high-resolution in-situ measurements, the study elucidates the intricate relationship between precipitation events and DOC export, offering valuable insights into the mechanisms governing DOC quality changes. The use of Spearman correlation analysis, hysteresis analysis, and visual comparisons enhances the rigor of the findings, providing a robust framework for understanding the complexities of DOC dynamics. Particularly noteworthy is the identification of key drivers such as antecedent wetness and precipitation event duration, underscoring the nuanced interplay between environmental factors and DOC export patterns. The research's focus on the Nesselbach a German lower mountain catchment situated in the „westhessische Senke“ with predominantly agricultural land use adds a valuable regional perspective to the broader understanding of DOC dynamics. Overall, this paper represents a significant contribution to the field and tries to highlight the importance of high-resolution in-situ measurements in unraveling the complexities of DOC dynamics and informing future research and management strategies. However, there are still some minor points to improve upon.
- For me, it was not clear what the tangible benefit of the higher resolution compared to other studies using lower resolution constitutes. Since this is a major point in the study it would be most beneficial if this would be elaborated upon a little bit more and contrast the two approaches a little bit better.
- The method section is very nicely done. Equation number one seems to use the wrong units. The units on the right do not correspond to the units on the left.
- In the result section the details for „significant“, „positively correlated“, „highest“ and so on are missing. Here it would be nice to always provide the test and or the value.
Citation: https://doi.org/10.5194/egusphere-2024-230-RC1 -
AC1: 'Reply on RC1', Lukas Ditzel, 15 May 2024
Dear anonymous referee #1,
thank you very much for your helpful comments. Please find the reply below.
For me, it was not clear what the tangible benefit of the higher resolution compared to other studies using lower resolution constitutes. Since this is a major point in the study it would be most beneficial if this would be elaborated upon a little bit more and contrast the two approaches a little bit better
- Higher resolution allows for more detailed insights into the catchment based on the presumption, that DOC-Export dynamics mostly follow a hysteresis loop. These loops can be described and quantified more precisely with higher resolution data.
The method section is very nicely done. Equation number one seems to use the wrong units. The units on the right do not correspond to the units on the left.
- Equation #1 will be corrected.
In the result section the details for „significant“, „positively correlated“, „highest“ and so on are missing. Here it would be nice to always provide the test and or the value.
- Details on significance will be provided, including used test.
Citation: https://doi.org/10.5194/egusphere-2024-230-AC1
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RC2: 'Comment on egusphere-2024-230', Anonymous Referee #2, 08 May 2024
Ditzel and coauthors have provided a manuscript describing time series measurements of organic carbon in a small agriculturally dominated catchment. The most prominent conclusion from the work is shifts in DOC composition and quantity over seasonal changes with potential influences from land use.
First and foremost, I would like to commend the authors for collecting a very unique, and what I feel is a highly needed dataset. There is inherent need for long-term continuous measurements of DOC to better understand lateral carbon fluxes across terrestrial to aquatic interfaces, and there is certainly limited information in agricultural areas. The in-situ spectrophotometer (S::CAN) provides unique opportunity for addressing these questions. I also know from my own experiences the challenges when working with this instrument and I commend the authors for their efforts to deploy and collect this data over long periods of time.
Having said that, I feel the manuscript struggles significantly in its presentation of a clear scientific framework that addresses what could be a very novel use of such a dataset. I think that it could be highly beneficial for the manuscript should the authors consider additional collaboration from other parties with interest in DOM optics, long term monitoring, and lateral carbon flux. Having a subject matter expert in this space could help the authors improve the manuscript in the following ways:
1) Identifying key knowledge gaps in this field for which this dataset can answer and framing the introduction and discussion better around those knowledge gaps.
2) Using terminology and interpretation of DOM optics in a manner consistent with the current field and body of literature
3) The identification of key high-level findings relevant to the knowledge gaps and scientific questions for which a results/discussion can be framed – and also highlighting their novelty. Currently, there is too much effort to explain minute details within the dataset rather than using the dataset to answer key scientific questions in a novel manner.
4) Overall manuscript presentation. This includes the presentation of results/discussion in a clear and coherent format. Paragraphs, for example, are overly long – often jumbling many topics together with no clear flow. Sentence structure, spelling, and grammar need significant improvement. See below one example of many instances throughout where sentence structure hinders legibility of the manuscript:
“As a basic nutrient it contributes to the carbon budget of river systems but also as a basic nutrient”
Based on the comments above, I believe the manuscript requires considerable revision before it could be published in a manner that would be beneficial to the broader scientific community. In an effort to pinpoint some key areas of focus to help the authors, I have put some additional high level major comments below.
- Introduction
-The introduction is missing key literature support and justification for this study. Why is there a need for long term measurements? How can this help improve carbon export from these small catchments? Why are agricultural systems important for DOC composition and fluxes? What information is already available for the influence of agriculture on DOC composition? There is plenty of literature on this topic already. Seems the discussion is focused on big rivers, but the study is in a small catchment. What is the importance of small agricultural catchments, and how might their characteristics/hydrology impact DOC fluxes? What is hysteresis and why is it important? How can it be used to answer DOC flux questions?
-The manuscript defines DOC as "good" or "bad" quality – "good" quality being highly aromatic/resilient DOC and low quality being DOC that is broken down and is more prone to other processes. I strongly challenge this notion that there is a “good” vs “bad” quality DOC and the use of quality here is strongly misleading. For instance, DOC is introduced as “good” quality, but in the same sentence says that same “good” quality is bad for water quality. So in that vein, what does quality actually mean? It is important to note that DOC behaves differently depending on the biogeochemical process. I might make the argument that the same highly aromatic “good” quality DOC defined in this paper is actually “bad” quality for microbial processes since these compounds are typically not what microbes like to eat. So, it is my recommendation to remove any reference to “quality” as it is to subjective and confusing. I recommend using the term “composition” instead.
Line 83 (Major aims): What is meant by a “relevant precipitation event”?
- Methods
-Study Site: It is not defined here that this is in Germany. Germany is only mentioned in abstract. Figure 1 needs more geographical context for non-German/European readers. Please add a map of Germany with the location of the catchment within and highlight any relevant features needed for context – for instance the broader watershed or the “European uplands” as mentioned in the manuscript.
-From what time frame does the study represent?
-In situ measurements: The manuscript uses data collected from the spectro::lyzer (S::CAN) and uses the “universal calibration” set forth within the instrument to obtain DOC fluxes. There are a number of inherent challenges with this:
- a) It is well established that this “universal calibration” is unreliable, particularly in headwater catchments. It is commonplace for studies that want to use the instrument for DOC/nitrate measurements to come up with their own calibrations that are specific to their catchment. See the following recent examples: Vaughan et al., 2017 (https://doi.org/10.1002/2017WR020491); Gaviria-Salazar et al., 2023 (https://doi.org/10.1002/lom3.10559). If one is to use this “universal calibration” from the instrument, it is absolutely imperative to show validation for the system of interest over varying temporal scales, including both seasonal and event specific. The authors mentioned that there were some spot measurements taken for validation, however this data is not shown. But I feel this is strongly needed to justify this and validate the results of the study.
- b) DOC measurements from the spectro::lyzer are absorbance based. These are strongly influenced by turbidity. Measurements using this instrument must be turbidity corrected for accurate DOC concentrations (See Gaviria-Salazar et al., 2023). I would assume in an agricultural catchment that turbidity can be pretty high during precipitation events, which leads me to believe that without validation, that DOC measurements collected during storm events during this study would be unreliable if they are not turbidity corrected. I would encourage the authors to address this directly in the manuscript.
-DOM optics: Sr and SUVA are properties of chromophoric DOM (CDOM). They are not representative of the entire DOC pool. So, Sr for instance cannot be stated as an indicator of DOC molecular weight because there are non-light absorbing components of the DOC pool. It is an indicator of CDOM molecular weight. Furthermore, Sr is not exclusively an indicator of photochemistry. Yes, photochemistry can impact Sr, but Sr is also impacted by source and other biogeochemical processes. This should be clarified.
-Discharge and Smoothing: It was unclear to me how this Nivus ultra sonic probe was used to calculate discharge for open streams? Some additional information on the setup, how the measurements were collected, and discharge extrapolated is needed. A conceptual figure could be beneficial. There were also a number of steps taken for discharge smoothing. I think a Supporting Information with some additional discussion and figures would help with this as it was hard to follow based on the text alone.
-An explanation of metrics by which storms were delineated and chosen to include in statistical analyses is needed.
-Need a section explaining statistics used
Results/Discussion/Conclusion
-At a high level, I recommend putting DOC concentration first then composition. Apart from the challenges already listed above, the major challenge with this section is that there is no clear novelty. The primary finding is that DOC loads increase with precipitation. There are further inferences that land cover may be important, however, this study was not designed to test the impact of agriculture directly and comparative references within the literature that could justify this conclusion are minimal. The generalized interpretation of hysteresis indies are valid, but it is unclear there broader utility for answering key questions related to this dataset.
Please find below some additional minor comments for this section
-There are many references to significant correlations throughout without any statistics associated with the statements.
-line 245: Unclear why this is considered an outlier based on text.
-line 255-258: Novelty?
-line 270: overrepresentation of discharge in calculation of flux? Unclear what is meant by this?
-line 273-275: wording, unclear the interpretation
-line 278-280: wording, explanation again unclear
-line 290: The parameters DNT30 and AI60 need further explanation on why they are linked with DOC in other studies and what that means. It is unclear how one would interpret a relationship between these indices and DOC parameters
-line 300: Is there an explanation for why DOC might be different for the spring?
-line 300-308: It would be more appropriate to incorporate more multi-way statistical approaches when discussing multiple different controls on DOC.
-line 315: Higher insulation in the summer?
-line 330: discussion of riparian vs distal sources… are there any other measurements in the catchment that would support this? Such as soil data?
-line 334: Unclear wording – and unclear based on the study design how land cover could be stated as important
Line 338-341: I feel like there is something here that could be better explored in disentangling the seasonal differences. I encourage authors to expand on this more with more complete interpretations.
Line 387: Again, unclear how land use can be attributed as a contributor of DOC here as this was not a part of the study design, and the manuscript comparisons are with only 1 other forested study. This is not enough to make conclusive statements.
Figures/Tables
-Figure 2a. I recommend adding directionality to this figure with some arrows so we can more clearly see the trend.
Figure 2b is labeled as DOC but the legend says nitrate. Note that if Figure 2b is in fact DOC, this would be anticlockwise hysteresis, contrary to what is stated in Figure 2a. Please correct and clarify.
Figure 3 and Figure 6 would benefit from being a single annotated figure
Figure 4 is illegible in the current pre-print format. I might also recommend finding ways to delineate the storms of interest on this figure if possible.
Figure 5: It is unclear what this figure represents. Is this an average of all storms during the designated seasons or is it one storm? How are the storms delineated as pre- and post- event? Is there a consistent metric for changes in discharge that defines the beginning and end of an event?
Figure 7: It is unclear what is meant to be represented by this figure. I might recommend an alternative figure, one that uses a DOC hysteresis index vs a flushing index, which could then be color coded by DOC load or season. I think this would provide a better understanding of the hydrological conditions and controls on DOC export of the seasons. There is an example of this in the Vaughan et al. reference above.
Table 1-3: Unclear what these tables represent. Is this for the entire event or just at the peak? Better explanation of storm delineation is needed as suggested in the comment above. I might also recommend the authors consider more creative ways to display this data for the main text and move these tables to a supporting information.
Citation: https://doi.org/10.5194/egusphere-2024-230-RC2 -
AC2: 'Reply on RC2', Lukas Ditzel, 25 May 2024
Dear Anonymous Referee #2,
Thank you very much for your helpful and detailed comments. We greatly appreciate the effort you put into reviewing our manuscript and your recommendations for its improvement.
Please find our detailed responses to your comments in the attached supplement PDF.
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