the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 01 Aug 2022
Environmental and hydrologic controls on sediment and organic carbon export from a subalpine catchment: insights from a time-series
Abstract. Studies engaging in tracking headwater carbon signatures downstream remain sparse, despite their importance for constraining transfer and transformation pathways of organic carbon (OC) and developing regional-scale perspectives on mechanisms influencing the balance between remineralization and carbon export. Based on a 40-month time series, we investigate the dependence of hydrology and seasonality on the discharge of sediment and OC in a small Swiss subalpine watershed (Sihl River basin). We analyze concentrations and isotopic compositions (δ13C, F14C) of particulate OC and use dual-isotope mixing and machine learning frameworks to characterize and estimate source contributions, transport pathways, and export fluxes. The majority of transferred OC is sourced from plant biomass and soil material. Relative proportions of soil-derived particulate OC peak during the summer months, coinciding with maximum soil erosion rates. Bedrock-derived (petrogenic) OC abundant in headwater streams progressively decreases downstream in response to a lack of source material and efficient overprinting with biospheric organic matter, illustrating rapid OC transformation over short distances. Large variations in isotopic compositions observed during baseflow conditions converge and form a homogenous mixture enriched in OC and characterized by higher POC- F14C values following precipitation-driven events. We propose that storms facilitate surface runoff and shallow landsliding, resulting in the entrainment of fresh litter and surficial soil layers. Model results further indicate diverging mobilization pathways. Discharge and water stage describe the export of suspended sediment, while the prediction of POC fluxes is mostly supported by water stage and 1-day antecedent precipitation. Although particle transport in the Sihl River basin is mainly driven by hydrology, subtle changes in bedrock erosivity, slope angle, and floodplain extent likely have profound effects on the POC composition, age, and export yields.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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Supplement
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(28873 KB) - Metadata XML
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Supplement
(108 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-705', Anonymous Referee #1, 22 Aug 2022
In this manuscript, the authors present a substantially long time-series of isotopic and hydrographic measurements to understand carbon cycling patterns along the Sihl River and basin. The strength of this manuscript is its clear goal and approach. The study uses a mixture of "traditional" methods to measure carbon cycling (POC and DOC collection via filtration, and thorough subsequent geochemical analysis (2.3)) and new computational methods such as machine learning. Many of the terms / methods described in 2.5 and 2.6 are new to me as someone largely unfamiliar with machine learning algorithms; however, this does not negatively impact the article's "result traceability", and there is significant precedence provided for each decision via citation of previous literature.
One minor comment / question (Line 132). I'm unfamiliar with this method of storing DOC samples, and am surprised they were not frozen. I'm wondering if the effects of acidification versus freezing was considered in the method, or interpretation of results? See Walker et al., 2016 https://doi.org/10.1017/RDC.2016.48
Overall, I find this manuscript very strong and support straightforward publication.
Citation: https://doi.org/10.5194/egusphere-2022-705-RC1 -
AC2: 'Reply on RC1', Melissa Schwab, 03 Oct 2022
We appreciate the encouraging comments and wish to thank the reviewer for the effort and time spent reviewing the manuscript.
Current literature provides several accepted protocols for handling and storing dissolved organic carbon. Storage and preservation methods include a variety of containers (borosilicate vs HDPE), biocides (e.g., HgCl2, NaN3, HCl, HNO3), and storage temperatures (refrigerated vs frozen). The commonly recommended methods are frozen storage (Walker et al., 2017; Heinz and Zak, 2018) and the storage of acidified samples in cold temperatures (4º C) (Cook et al., 2016; Nachimuthu et al., 2020). However, both options are characterized by advantages and disadvantages. Thieme et al. (2016) and Walker et al. (2017) demonstrate that freezing might preserve dissolved organic carbon concentrations and isotopic compositions while Spencer et al. (2007) and Thieme et al. (2016) argue that freeze/thaw cycles likely affect chemical and optical compositions of dissolved organic matter. Opinions further differ regarding the pre-treatment of dissolved organic carbon for freshwater and marine water samples. Regardless of the preservation method, organic carbon will be subjected to decomposition and alteration with increasing storage time.
Due to the low concentrations of dissolved organic carbon concentrations in the Sihl River, 20 mL of sample material were concentrated in precombusted gas-tight 12 mL exetainer vials by repeated freeze-drying of 5 mL aliquots. The vials were stored frozen until further analysis. We have failed to include this preparation step in the methods and have revised section 2.3.
References
Cook S., Peacock M., Evans C. D., Page S. E., Whelan M., Gauci V. and Khoon K. L. (2016) Cold storage as a method for the long-term preservation of tropical dissolved organic carbon (DOC). Mires and Peat 18.
Heinz M. and Zak D. (2018) Storage effects on quantity and composition of dissolved organic carbon and nitrogen of lake water, leaf leachate and peat soil water. Water Res 130, 98–104.
Nachimuthu G., Watkins M. D., Hulugalle N. and Finlay L. A. (2020) Storage and initial processing of water samples for organic carbon analysis in runoff. MethodsX 7.
Spencer R. G. M., Bolton L. and Baker A. (2007) Freeze/thaw and pH effects on freshwater dissolved organic matter fluorescence and absorbance properties from a number of UK locations. Water Res 41, 2941–2950.
Thieme L., Graeber D., Kaupenjohann M. and Siemens J. (2016) Fast-freezing with liquid nitrogen preserves bulk dissolved organic matter concentrations, but not its composition. Biogeosciences 13, 4697–4705.
Walker B. D., Griffin S. and Druffel E. R. M. (2017) Effect of Acidified Versus Frozen Storage on Marine Dissolved Organic Carbon Concentration and Isotopic Composition. In Radiocarbon Cambridge University Press. pp. 843–857.
Citation: https://doi.org/10.5194/egusphere-2022-705-AC2
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AC2: 'Reply on RC1', Melissa Schwab, 03 Oct 2022
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RC2: 'Review of “Environmental and hydrologic controls on sediment and organic carbon export from a subalpine catchment: insights from a time-series” by Melissa Schwab and co-authors', Anonymous Referee #2, 30 Aug 2022
This manuscript presents a large dataset from a long-term (40 months) sampling campaign of river water and suspended sediment from a subalpine catchment in Switzerland. The authors generated a substantial amount of data, including a 40-month time-series of stable carbon isotopes and radiocarbon activity of dissolved and particulate organic carbon. Time-series data sets like this are incredibly valuable to the scientific community, particularly now as our field aims to mechanistically describe the feedbacks between climate change and the global carbon cycle. This manuscript addresses relevant scientific questions (i.e., what controls the magnitude and temporal variability of river organic carbon export?). The main dataset and introduction of statistical approaches are a great contribution to the field. The methods and statistical analyses used in this manuscript are state of the art, particularly the application of EA-IRMS for high throughput 14C measurements and the application of machine learning-based statistical analyses.
Overall, the manuscript is well-written, but there several points that need clarification and revision, as noted in the major points of concern and the detailed comments below. The authors do a nice job of presenting their data and using statistics to describe the distribution of the data, however, it seems that this manuscript is lacking robust interpretation of the statistical results. Based on the introduction of the paper, I expected their results to provide a mechanistic explanation linking geomorphic and hydrologic processes to organic carbon export from small headwater rivers. However, I was not able to take away any new ideas or significant conclusions from their data interpretation and discussion. Additionally, I find that some of the analyses are not entirely appropriate (i.e. the MixSIAR analysis) and should be either removed from the manuscript or redone to reflect appropriate endmember mixing. To make this manuscript of greater interest to the scientific community, the authors should also provide a framework for integrating their statistical results into Earth system models.
In summary, a number of revisions need to be made before this manuscript can be accepted for publication in EGU Biogeosciences. Major points of concern and suggestions for revising the manuscript are detailed in the attached PDF.
- AC1: 'Reply on RC2', Melissa Schwab, 03 Oct 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-705', Anonymous Referee #1, 22 Aug 2022
In this manuscript, the authors present a substantially long time-series of isotopic and hydrographic measurements to understand carbon cycling patterns along the Sihl River and basin. The strength of this manuscript is its clear goal and approach. The study uses a mixture of "traditional" methods to measure carbon cycling (POC and DOC collection via filtration, and thorough subsequent geochemical analysis (2.3)) and new computational methods such as machine learning. Many of the terms / methods described in 2.5 and 2.6 are new to me as someone largely unfamiliar with machine learning algorithms; however, this does not negatively impact the article's "result traceability", and there is significant precedence provided for each decision via citation of previous literature.
One minor comment / question (Line 132). I'm unfamiliar with this method of storing DOC samples, and am surprised they were not frozen. I'm wondering if the effects of acidification versus freezing was considered in the method, or interpretation of results? See Walker et al., 2016 https://doi.org/10.1017/RDC.2016.48
Overall, I find this manuscript very strong and support straightforward publication.
Citation: https://doi.org/10.5194/egusphere-2022-705-RC1 -
AC2: 'Reply on RC1', Melissa Schwab, 03 Oct 2022
We appreciate the encouraging comments and wish to thank the reviewer for the effort and time spent reviewing the manuscript.
Current literature provides several accepted protocols for handling and storing dissolved organic carbon. Storage and preservation methods include a variety of containers (borosilicate vs HDPE), biocides (e.g., HgCl2, NaN3, HCl, HNO3), and storage temperatures (refrigerated vs frozen). The commonly recommended methods are frozen storage (Walker et al., 2017; Heinz and Zak, 2018) and the storage of acidified samples in cold temperatures (4º C) (Cook et al., 2016; Nachimuthu et al., 2020). However, both options are characterized by advantages and disadvantages. Thieme et al. (2016) and Walker et al. (2017) demonstrate that freezing might preserve dissolved organic carbon concentrations and isotopic compositions while Spencer et al. (2007) and Thieme et al. (2016) argue that freeze/thaw cycles likely affect chemical and optical compositions of dissolved organic matter. Opinions further differ regarding the pre-treatment of dissolved organic carbon for freshwater and marine water samples. Regardless of the preservation method, organic carbon will be subjected to decomposition and alteration with increasing storage time.
Due to the low concentrations of dissolved organic carbon concentrations in the Sihl River, 20 mL of sample material were concentrated in precombusted gas-tight 12 mL exetainer vials by repeated freeze-drying of 5 mL aliquots. The vials were stored frozen until further analysis. We have failed to include this preparation step in the methods and have revised section 2.3.
References
Cook S., Peacock M., Evans C. D., Page S. E., Whelan M., Gauci V. and Khoon K. L. (2016) Cold storage as a method for the long-term preservation of tropical dissolved organic carbon (DOC). Mires and Peat 18.
Heinz M. and Zak D. (2018) Storage effects on quantity and composition of dissolved organic carbon and nitrogen of lake water, leaf leachate and peat soil water. Water Res 130, 98–104.
Nachimuthu G., Watkins M. D., Hulugalle N. and Finlay L. A. (2020) Storage and initial processing of water samples for organic carbon analysis in runoff. MethodsX 7.
Spencer R. G. M., Bolton L. and Baker A. (2007) Freeze/thaw and pH effects on freshwater dissolved organic matter fluorescence and absorbance properties from a number of UK locations. Water Res 41, 2941–2950.
Thieme L., Graeber D., Kaupenjohann M. and Siemens J. (2016) Fast-freezing with liquid nitrogen preserves bulk dissolved organic matter concentrations, but not its composition. Biogeosciences 13, 4697–4705.
Walker B. D., Griffin S. and Druffel E. R. M. (2017) Effect of Acidified Versus Frozen Storage on Marine Dissolved Organic Carbon Concentration and Isotopic Composition. In Radiocarbon Cambridge University Press. pp. 843–857.
Citation: https://doi.org/10.5194/egusphere-2022-705-AC2
-
AC2: 'Reply on RC1', Melissa Schwab, 03 Oct 2022
-
RC2: 'Review of “Environmental and hydrologic controls on sediment and organic carbon export from a subalpine catchment: insights from a time-series” by Melissa Schwab and co-authors', Anonymous Referee #2, 30 Aug 2022
This manuscript presents a large dataset from a long-term (40 months) sampling campaign of river water and suspended sediment from a subalpine catchment in Switzerland. The authors generated a substantial amount of data, including a 40-month time-series of stable carbon isotopes and radiocarbon activity of dissolved and particulate organic carbon. Time-series data sets like this are incredibly valuable to the scientific community, particularly now as our field aims to mechanistically describe the feedbacks between climate change and the global carbon cycle. This manuscript addresses relevant scientific questions (i.e., what controls the magnitude and temporal variability of river organic carbon export?). The main dataset and introduction of statistical approaches are a great contribution to the field. The methods and statistical analyses used in this manuscript are state of the art, particularly the application of EA-IRMS for high throughput 14C measurements and the application of machine learning-based statistical analyses.
Overall, the manuscript is well-written, but there several points that need clarification and revision, as noted in the major points of concern and the detailed comments below. The authors do a nice job of presenting their data and using statistics to describe the distribution of the data, however, it seems that this manuscript is lacking robust interpretation of the statistical results. Based on the introduction of the paper, I expected their results to provide a mechanistic explanation linking geomorphic and hydrologic processes to organic carbon export from small headwater rivers. However, I was not able to take away any new ideas or significant conclusions from their data interpretation and discussion. Additionally, I find that some of the analyses are not entirely appropriate (i.e. the MixSIAR analysis) and should be either removed from the manuscript or redone to reflect appropriate endmember mixing. To make this manuscript of greater interest to the scientific community, the authors should also provide a framework for integrating their statistical results into Earth system models.
In summary, a number of revisions need to be made before this manuscript can be accepted for publication in EGU Biogeosciences. Major points of concern and suggestions for revising the manuscript are detailed in the attached PDF.
- AC1: 'Reply on RC2', Melissa Schwab, 03 Oct 2022
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Melissa Sophia Schwab
Hannah Gies
Chantal Valérie Freymond
Maarten Lupker
Negar Haghipour
Timothy Ian Eglinton
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(28873 KB) - Metadata XML
-
Supplement
(108 KB) - BibTeX
- EndNote
- Final revised paper