the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Aug 2025
Simulating carbon fluxes in boreal catchments: WSFS-Vemala model development and key insights
Abstract. Lakes and streams play an important role in the global carbon cycle through carbon sedimentation and evasion. The development of carbon processes in the water quality model WSFS-Vemala (Vemala) presents a significant advancement in simulating carbon dynamics, particularly in capturing both total organic (TOC) and inorganic (TIC) carbon processes and their contributions to carbon retention and emissions through a river/lake network. The model was tested in the Vantaanjoki catchment, located in southern Finland and covering an area of 1680 km2. The model's ability to simulate TOC and TIC loading across various land use and soil types aligns closely with reported literature values. The addition of organic acids to the total alkalinity definition improved pH simulations and thus the simulation of CO2 emissions in the acidic and organic rich waters of Finland. Annual CO2 emissions of 25 gC m2 yr-1 were simulated from lake Tuusulanjärvi, the largest lake in the catchment, and 223–260 gC m-2 yr-1 from the river network, while only 3 gC m-2 yr-1 was simulated as organic carbon burial in the lake sediments. The model's performance in estimating CO2 emissions shows good correlations with established ranges for lakes as well as good correlation with TOC and TIC loads across the river network. The inclusion of sedimentation and mineralization processes in the lake carbon budget underlines the necessity of accounting for both organic and inorganic pathways in carbon modelling. This improved representation of the carbon cycling in Vemala, linked with the phytoplankton growth and nutrient cycling, allow to distinguish between carbon losses to the atmosphere and long-term carbon storage in the sediments of inland waters. Overall, the enhanced Vemala model provides a robust foundation for understanding carbon cycling and supporting sustainable, integrated water resource management and scenario assessments from sub-catchments to the national scale.
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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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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-3255', Anonymous Referee #1, 12 Oct 2025
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AC1: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
We thank Reviewer 1 for the positive feedback on the manuscript and for acknowledging its clarity, novelty and relevance to the readers of Hydrology and Earth System Sciences. We have answered each comment separately in the attach document.
Citation: https://doi.org/10.5194/egusphere-2025-3255-AC1 -
AC3: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3255/egusphere-2025-3255-AC3-supplement.pdf
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AC1: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
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RC2: 'Comment on egusphere-2025-3255', Anonymous Referee #2, 10 Dec 2025
This work quantitatively predicts the dynamics of carbon flux at the scale of the river-lake aquatic ecosystem. The Vemala model was integrated into a hydrological model to simulate carbon flux driven by water flows. The evidence strongly supports their conclusions, and the findings hold great potential for providing new insights into the carbon cycle in river-lake systems. The reviewers only raised minor concerns for the authors to consider in the revised version:
1. Details regarding observation data collection are insufficient, such as the methods for collecting water/soil samples and measuring target parameters.
2. Only a single reference is provided for Eqs. 13–14 in the text. Additional references should be added to solidify the selection of coefficients.
3. Time series plots comparing simulated and observed TOC/TIC are missing in Sections 4.1.2–4.1.3, which undermines the validity of the NSE values presented in Table 3.
4. The limitations of the modeling approach require further discussion, such as the underlying assumptions of the dozens of sub-models.
Citation: https://doi.org/10.5194/egusphere-2025-3255-RC2 - AC2: 'Reply on RC2', Marie Korppoo, 16 Jan 2026
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-3255', Anonymous Referee #1, 12 Oct 2025
Review of Korpoo et al.
Overall, this is a well-written paper that describes an important modelling advance. While the model has been designed for Finnish conditions, the findings of this paper will be useful to a broad range of researches including those working with catchment or regional scale modelling, those interested in aquatic carbon cycling and climate issues as well as applied researchers having a responsibility to support decision makers.
The authors present a regional / national scale model of aquatic carbon production, transport and loss. To the best of my knowledge, this is the first model to attempt such national scale simulations with such a high degree of process fidelity.
One of the key strengths of this model is that it tracks the production, transport, transformation and loss of both total inorganic carbon (TIC) and total organic carbon (TOC).
I do have a number of reservations about this paper that I hope the authors will have the opportunity to address in a revised version.
The authors present their model as a tool for simulating total organic carbon and total inorganic carbon. This is appropriate for boreal conditions where there is typically very little particulate organic carbon and the underlying geology for the most part precludes high levels of particulate inorganic carbon (e.g., carbonate –derived rocks). I suggest the authors either refer to dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) throughout (as they seem to be doing from statements made on line 154), or note that in the environment for which this model has been developed, only a small fraction of the total aquatic carbon is in a particulate form. Using DOC instead of TOC could also make more clear the separation between soil organic carbon and organic carbon in the aquatic phase.
As the authors present their work as a new contribution to our ability to model aquatic carbon ,I suggest deleting information about N and P simulations (e.g., Table 3). Either that or provide a rationale for why nitrogen and phosphorus simulation results should be included in this study.
My biggest concerns about this paper arise from statements made on lines 134 and lines 153-157. On line 134, the authors state that “SOC and DIC can be mineralized into DIC that is simulated as a loss from the system to the air”. Paraphrasing lines 153-157, they appear to state that alkalinity is a proxy for TIC which in turn includes CO2, HCO3- and CO3_2-.
I would be grateful if the authors could clarify whether or not they are using the regression on line 156 to estimate the sum of CO2, HCO3- and CO3_2-. If they are doing so, I would appreciate a stronger motivation for the decision.
My second concern about lines 134 and 153-157 is that they seem to state that terrestrial DIC is modelled twice, once as a breakdown product of SOC and / or TOC (line 134) and once as an empirical soil-related property (lines 153-157). Why? Doing so seems to violate a carbon mass balance as the DIC produced through mineralization leaves the system to contribute to atmospheric warming while the regression takes no explicit account of terrestrial carbon mineralization. This really needs a better explanation and justification.
From the text on lines 225-230, it appears that the authors calibrated to loads. This is poor practice for demonstrating the skill of a biogeochemical model. Any calibration that does a reasonable job of reproducing the observed flow has a high probability of generating misleadingly high Nash Sutcliffe Efficiencies. Please consider either recalibrating to concentrations or present performance statistics based on modelled and observed concentations.
Minor questions
L108 – how is soil temperature include in the model ? are measured time series used or is soil temperature simulated in some manner?
L112-115 – Please provide some additional description of the Vemala conceptual model. After reading this text multiple times, it is still not entirely clear to me how the model represents the landscape. Is a watershed built up of “small brook catchments” or is some other approach used? I presume the model is semi-distributed as opposed to grid based? Having this type of background information would be quite useful to other modelers attempting to work at the same scale as Vemala.
L125 – Again, some more detail about the model structure would be appreciated. The authors note that carbon concentrations change with depth in both peat and mineral soils. Is this phenomenon represented in Vemala through different carbon contents in the unsaturated soil layer and groundwater layer?
L132- How are annual litter inputs added to the system? Are inputs prorated across every day of the year or is another approach used?
L135 – I presume TOC produced in the leaching zone can percolate vertically to groundwater?
L145-148 – please provide numeric soil organic matter (SOM) levels for the SOM classification presented here; this information could be in the Supplementary Information
L156 – how were the values in Table 2 obtained? Are they directly from Korka-Niemi (2001) or did the authors do the calibration themselves?
L165 – presumably a triprotic model is being used for DOC dissociation? Please identify which one. From statements made later in the manuscript, I presume it is the model of Hruska et al. (2003) ?
L172 – phytoplankton settling in one of a number of processes that can lead to TOC sedimentation. Geochemical coagulation may be important in some circumstances. If phytoplankton settling in the only TOC process simulated in Vemala, please note that it may not be the only process operating in reality.
Equations 3, 5 – please consider different left hand side terms for equations 3 and 5. It is a bit confusing to have them both described as “Alk” (I know there is the subscript “n” in equation 3 but that does not help terribly much)
Figures 3 b and c should be bigger if they are to be useful
Lines 295-300 – please provide more detail as to how flows at the Tuusulanjarvi outflow were estimated.
Figure 4 – consider a separate plot for the Tuusulanjarvi outflow
Table 3 – please present NSE for concentrations, not loads in all cases
Line 485 – could the authors present any connection to PREBAS here? Is PREBAS simulating higher litter fall inputs over the study period and could tis account for the increase in DOC? I would appreciate it if the authors could also comment on peat soil drainage as a factor behind increasing TOC. I was under the impression there was little or no new drainage of Finnish peat soils?
Line 495 – What are the consequences, if any, of simulating alkalinity as a conservative tracer? It seems to imply that there will be no evasion of CO2 to the atmosphere but perhaps I misunderstand.
Figure A3 – In my opinion, Figure A3 is more convincing than Figure 7, why not switch these figures between the main text and SI?
Citation: https://doi.org/10.5194/egusphere-2025-3255-RC1 -
AC1: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
We thank Reviewer 1 for the positive feedback on the manuscript and for acknowledging its clarity, novelty and relevance to the readers of Hydrology and Earth System Sciences. We have answered each comment separately in the attach document.
Citation: https://doi.org/10.5194/egusphere-2025-3255-AC1 -
AC3: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3255/egusphere-2025-3255-AC3-supplement.pdf
-
AC1: 'Reply on RC1', Marie Korppoo, 16 Jan 2026
-
RC2: 'Comment on egusphere-2025-3255', Anonymous Referee #2, 10 Dec 2025
This work quantitatively predicts the dynamics of carbon flux at the scale of the river-lake aquatic ecosystem. The Vemala model was integrated into a hydrological model to simulate carbon flux driven by water flows. The evidence strongly supports their conclusions, and the findings hold great potential for providing new insights into the carbon cycle in river-lake systems. The reviewers only raised minor concerns for the authors to consider in the revised version:
1. Details regarding observation data collection are insufficient, such as the methods for collecting water/soil samples and measuring target parameters.
2. Only a single reference is provided for Eqs. 13–14 in the text. Additional references should be added to solidify the selection of coefficients.
3. Time series plots comparing simulated and observed TOC/TIC are missing in Sections 4.1.2–4.1.3, which undermines the validity of the NSE values presented in Table 3.
4. The limitations of the modeling approach require further discussion, such as the underlying assumptions of the dozens of sub-models.
Citation: https://doi.org/10.5194/egusphere-2025-3255-RC2 - AC2: 'Reply on RC2', Marie Korppoo, 16 Jan 2026
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Marie Korppoo
Inese Huttunen
Markus Huttunen
Maiju Narikka
Jari Silander
Tom Jilbert
Martin Forsius
Pirkko Kortelainen
Niina Kotamäki
Cintia Uvo
Anna-Kaisa Ronkanen
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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Review of Korpoo et al.
Overall, this is a well-written paper that describes an important modelling advance. While the model has been designed for Finnish conditions, the findings of this paper will be useful to a broad range of researches including those working with catchment or regional scale modelling, those interested in aquatic carbon cycling and climate issues as well as applied researchers having a responsibility to support decision makers.
The authors present a regional / national scale model of aquatic carbon production, transport and loss. To the best of my knowledge, this is the first model to attempt such national scale simulations with such a high degree of process fidelity.
One of the key strengths of this model is that it tracks the production, transport, transformation and loss of both total inorganic carbon (TIC) and total organic carbon (TOC).
I do have a number of reservations about this paper that I hope the authors will have the opportunity to address in a revised version.
The authors present their model as a tool for simulating total organic carbon and total inorganic carbon. This is appropriate for boreal conditions where there is typically very little particulate organic carbon and the underlying geology for the most part precludes high levels of particulate inorganic carbon (e.g., carbonate –derived rocks). I suggest the authors either refer to dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) throughout (as they seem to be doing from statements made on line 154), or note that in the environment for which this model has been developed, only a small fraction of the total aquatic carbon is in a particulate form. Using DOC instead of TOC could also make more clear the separation between soil organic carbon and organic carbon in the aquatic phase.
As the authors present their work as a new contribution to our ability to model aquatic carbon ,I suggest deleting information about N and P simulations (e.g., Table 3). Either that or provide a rationale for why nitrogen and phosphorus simulation results should be included in this study.
My biggest concerns about this paper arise from statements made on lines 134 and lines 153-157. On line 134, the authors state that “SOC and DIC can be mineralized into DIC that is simulated as a loss from the system to the air”. Paraphrasing lines 153-157, they appear to state that alkalinity is a proxy for TIC which in turn includes CO2, HCO3- and CO3_2-.
I would be grateful if the authors could clarify whether or not they are using the regression on line 156 to estimate the sum of CO2, HCO3- and CO3_2-. If they are doing so, I would appreciate a stronger motivation for the decision.
My second concern about lines 134 and 153-157 is that they seem to state that terrestrial DIC is modelled twice, once as a breakdown product of SOC and / or TOC (line 134) and once as an empirical soil-related property (lines 153-157). Why? Doing so seems to violate a carbon mass balance as the DIC produced through mineralization leaves the system to contribute to atmospheric warming while the regression takes no explicit account of terrestrial carbon mineralization. This really needs a better explanation and justification.
From the text on lines 225-230, it appears that the authors calibrated to loads. This is poor practice for demonstrating the skill of a biogeochemical model. Any calibration that does a reasonable job of reproducing the observed flow has a high probability of generating misleadingly high Nash Sutcliffe Efficiencies. Please consider either recalibrating to concentrations or present performance statistics based on modelled and observed concentations.
Minor questions
L108 – how is soil temperature include in the model ? are measured time series used or is soil temperature simulated in some manner?
L112-115 – Please provide some additional description of the Vemala conceptual model. After reading this text multiple times, it is still not entirely clear to me how the model represents the landscape. Is a watershed built up of “small brook catchments” or is some other approach used? I presume the model is semi-distributed as opposed to grid based? Having this type of background information would be quite useful to other modelers attempting to work at the same scale as Vemala.
L125 – Again, some more detail about the model structure would be appreciated. The authors note that carbon concentrations change with depth in both peat and mineral soils. Is this phenomenon represented in Vemala through different carbon contents in the unsaturated soil layer and groundwater layer?
L132- How are annual litter inputs added to the system? Are inputs prorated across every day of the year or is another approach used?
L135 – I presume TOC produced in the leaching zone can percolate vertically to groundwater?
L145-148 – please provide numeric soil organic matter (SOM) levels for the SOM classification presented here; this information could be in the Supplementary Information
L156 – how were the values in Table 2 obtained? Are they directly from Korka-Niemi (2001) or did the authors do the calibration themselves?
L165 – presumably a triprotic model is being used for DOC dissociation? Please identify which one. From statements made later in the manuscript, I presume it is the model of Hruska et al. (2003) ?
L172 – phytoplankton settling in one of a number of processes that can lead to TOC sedimentation. Geochemical coagulation may be important in some circumstances. If phytoplankton settling in the only TOC process simulated in Vemala, please note that it may not be the only process operating in reality.
Equations 3, 5 – please consider different left hand side terms for equations 3 and 5. It is a bit confusing to have them both described as “Alk” (I know there is the subscript “n” in equation 3 but that does not help terribly much)
Figures 3 b and c should be bigger if they are to be useful
Lines 295-300 – please provide more detail as to how flows at the Tuusulanjarvi outflow were estimated.
Figure 4 – consider a separate plot for the Tuusulanjarvi outflow
Table 3 – please present NSE for concentrations, not loads in all cases
Line 485 – could the authors present any connection to PREBAS here? Is PREBAS simulating higher litter fall inputs over the study period and could tis account for the increase in DOC? I would appreciate it if the authors could also comment on peat soil drainage as a factor behind increasing TOC. I was under the impression there was little or no new drainage of Finnish peat soils?
Line 495 – What are the consequences, if any, of simulating alkalinity as a conservative tracer? It seems to imply that there will be no evasion of CO2 to the atmosphere but perhaps I misunderstand.
Figure A3 – In my opinion, Figure A3 is more convincing than Figure 7, why not switch these figures between the main text and SI?