the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Nov 2025
Global parameter sensitivity analysis of modelling water, energy and carbon dynamics in a temperate swamp
Abstract. Forested peatlands cover a land area of 7 x 105 km2 and store ~77 Pg C in Canada. However, the carbon (C) cycling of forested peatlands, particularly swamps, has been understudied. Few modelling studies have been done on temperate swamp C cycling partly because of the scarcity of field measurements in this ecosystem. These gaps create uncertainties in modelling the C dynamics of temperate swamps and consequently limit our understanding of this ecosystem. To improve our understanding of the processes, interactions and feedbacks that mediate temperate swamp C cycling, we simulated the long-term (40 years) plant processes, energy, water and C fluxes of Beverly Swamp, a well-preserved swamp in Southern Ontario using a process-based model (CoupModel). CoupModel v6 was systematically calibrated for Beverly Swamp using the Generalized Likelihood Uncertainty Estimate (GLUE) method and validated with field measurements. The GLUE approach and its multicriteria constraints reduced the uncertainties associated with the modelling process and reasonably improved some of the simulation outcomes when compared to the initial single run and prior uniform distribution. Global sensitivity analysis of the parameters identified the important parameters that greatly influence temperate swamp C flux simulations and the interconnections that exist between simulated variables and parameters. Plant-related processes and hydrological variables exerted the strongest control on soil respiration simulation. However, these dynamics may be altered as climate continues to warm in coming decades. Results from this study provide valuable knowledge for predicting the fate of swamp C cycle in the region under a changing climate.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-1368', Anonymous Referee #1, 22 Mar 2026
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RC2: 'Comment on egusphere-2025-1368', Anonymous Referee #2, 17 Jun 2026
This manuscript uses the GLUE method to calibrate CoupModel and investigate parameter uncertainty, equifinality, and processes controlling soil respiration in a temperate swamp ecosystem. The topic is relevant because temperate swamps remain relatively understudied compared with other peatland ecosystems. However, several issues need to be addressed before it can be considered for publication:
- The abstract is too general to be informative. For example, the statement "the GLUE approach and its multicriteria constraints reduced the uncertainties associated with the modelling process and reasonably improved some of the simulation outcomes" should specify which model variables or processes showed improved performance and provide quantitative evidence to support this claim. The magnitude of uncertainty reduction and the corresponding changes in model performance should be reported using relevant metrics, such as changes in RMSE, R², bias, or other appropriate evaluation metrics. The statement “Global sensitivity analysis of the parameters identified the important parameters that greatly influence temperate swamp C flux simulations and the interconnections that exist between simulated variables and parameters. Plant-related processes and hydrological variables exerted the strongest control on soil respiration simulation.” provides no information on the actual model parameters, processes, and variables involved.
- The manuscript would benefit from a careful review of the language and overall presentation by the senior authors. Too often the text is difficult to follow and fails to communicate substantive information (it is not necessarily wrong, but it is imprecise, vague, or insufficiently informative). For example, the opening statement “A recent modelling study indicated that many aspects of a swamp’s thermal, hydrological and biogeochemical conditions could be adequately modelled, gaining insight into the ecosystem’s response to disturbance” provides little concrete information regarding what was modeled or what specific insights were obtained. As written, the sentence serves primarily as a citation rather than a synthesis of previous findings. The subsequent statement “however, parameter estimation remained difficult given the scarcity of previous studies in swamps”, is also unclear. The connection between this statement and the findings of Afolabi et al. (2025) is not adequately explained. It is unclear whether the difficulty in parameter estimation arises from limited observational data for calibration and validation, insufficient understanding of key processes, a lack of previous modelling studies to constrain parameter ranges, or some combination of these factors. In fact, the remainder of the paragraph appears to suggest that the primary issue is the scarcity of observational data rather than the scarcity of previous studies. The authors should clarify the source of the uncertainty and present the motivation for the study more clearly and logically. The statement “Modelling studies have shown that there are interrelationships between biogeochemical and biophysical processes in peatlands” is misleading. The existence of interactions between biogeochemical and biophysical processes is a fundamental characteristic of peatland ecosystems and has been demonstrated through observational, experimental, and modelling studies, not something that modelling studies uniquely "showed." I will not list all such instances here. I encourage the authors to carefully review the text and improve the precision and clarity.
- Objective ii: “present acceptable model structure and parameter distribution for simulating temperate swamp C”. How is “acceptable” defined? Are there quantitative criteria used to determine whether a model structure or parameter distribution is acceptable?
- Method: The criteria used to define behavioral simulations require further justification. The manuscript states that the thresholds were inspired by measurement uncertainty and previous modelling experience, but it is unclear how the specific R2 or ME thresholds for each variable were determined. Please provide a more rigorous justification for the selected thresholds and evaluate the sensitivity of the posterior parameter distributions to these choices.
- I am not fully convinced that differences between prior and posterior parameter distributions provide a robust measure of parameter sensitivity. Such differences may reflect parameter constraint or identifiability under the chosen observations and behavioral thresholds, and depend on the choice of prior parameter ranges. Please clarify the distinction between parameter sensitivity and parameter constraint/identifiability within the GLUE framework and discuss the implications for the interpretation of the results.
- The rationale for selecting 1998–2000 as the calibration period and 2022–2023 as the validation period is unclear. Please explain why these years were chosen, if observations between 2000-2022 are available, it would be helpful to justify why they were not used for calibration or validation.
- Figure 4: The temporal resolution of the validation data (2022–2023) appears substantially coarser than that of the calibration data (1998–2000), with the validation observations appearing to be monthly averages. Please clarify the temporal resolution of the observations and simulations shown in this figure. If different temporal aggregations were used for calibration and validation, please justify this choice and discuss how it may affect the comparison of model performance between the two periods.
- The scientific contribution of the study remains somewhat unclear. What new insights are obtained that were not already shown in Afolabi et al., Metzger et al. studies? Are the dominant controls, parameter sensitivities, equifinality patterns, or hydrological influences in temperate swamps fundamentally different from those reported for bogs or fens?
Citation: https://doi.org/10.5194/egusphere-2025-1368-RC2
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The manuscript addresses a relevant topic and applies established modelling and uncertainty analysis approaches; however, several substantive issues need to be addressed before it can be considered for publication. A moderate revision is recommended.
The scientific contribution remains somewhat limited. The study mainly applies existing methods (CoupModel + GLUE + GSA) to a swamp system, but the advancement beyond previous studies is not sufficiently articulated. The authors should clearly define the key scientific questions and explicitly state what new insights are gained at the process or system level.
Section 5.1 should be moved to the Discussion section. Its current content focuses on interpretation and mechanism explanation rather than presenting new results. Integrating it into the Discussion would improve the logical coherence of the manuscript.
The data basis raises concerns regarding robustness. Key calibration and validation datasets are sparse and temporally inconsistent (e.g., combining 1998–2000 and 2022–2023 observations). The authors should better justify this strategy and discuss its implications for model reliability and uncertainty.
The treatment of lateral water flow using proxy data is a critical assumption. Although acknowledged, it is not sufficiently quantified. A more rigorous uncertainty assessment or sensitivity discussion specific to this assumption is needed.
The Results section is overly descriptive, particularly in terms of parameter sensitivity rankings. The authors should better synthesize the findings, highlight dominant controls, and link them more explicitly to physical processes rather than listing parameter importance.
The Discussion is currently insufficient in depth. It should be strengthened by (i) systematic comparison with existing studies (especially bog and fen systems), (ii) clearer interpretation of process interactions, and (iii) explicit discussion of model limitations and applicability.
Model structural limitations need to be more explicitly addressed. The use of a one-dimensional model for a spatially heterogeneous swamp system may constrain interpretation, and this should be critically discussed.
The manuscript would benefit from improved integration between sections. Currently, the linkage between objectives, methods, results, and conclusions is somewhat loose. The authors should ensure that each objective is clearly addressed and revisited in the results and discussion.
Overall, the manuscript has a solid foundation, but requires deeper analysis, clearer positioning of its contribution, and improved discussion to meet publication standards.