the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Nov 2023
MPeat2D – A fully coupled mechanical-ecohydrological model of peatland development in two dimensions
Abstract. Higher dimensional models of peatland development are required to analyse the influence of spatial heterogeneity and complex feedback mechanisms. However, the current models exclude the mechanical process that leads to uncertainties in simulating the spatial variability of water table position, vegetation composition, and peat physical properties. Here, we propose MPeat2D, a peatland development model in two dimensions, which considers mechanical, ecological, and hydrological processes together with the essential feedback from spatial interactions. MPeat2D employs poroelasticity theory that couples fluid flow and solid deformation to model the influence of peat volume changes on peatland ecology and hydrology. To validate the poroelasticity formulation, the comparisons between numerical and analytical solutions of Mandel’s problems for two-dimensional test cases are conducted. The application of MPeat2D is illustrated by simulating peatland growth over 5000 years above the flat and impermeable substrate with free-draining boundaries at the edges, using constant and variable climate. In both climatic scenarios, MPeat2D produces lateral variability of water table depth, which results in the variation of vegetation composition. Furthermore, the drop of the water table at the margin increases the compaction effect, leading to a higher value of bulk density and a lower value of active porosity and hydraulic conductivity. These spatial variations obtained from MPeat2D are consistent with the field observations, suggesting plausible outputs from the proposed model. By comparing the results of MPeat2D to a one-dimensional model and a two-dimensional model without the mechanical process, the significance of mechanical-ecohydrological feedback on spatial heterogeneity, peatland shape, carbon accumulation, and resilience is highlighted.
-
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.
-
Preprint
(1717 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1717 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2535', Andrew Baird, 11 Dec 2023
Overview
This paper reports on an interesting new version of the MPeat model (Mahdiyasa et al., 2023) that simulates peatlands in 2D. The example used in the paper is a raised bog in cross section. The new model appears to have been set up correctly, and the numerical scheme reproduces analytical results for simple geometries very accurately. Much of the paper is given over to reporting on the simulation of the growth of a raised bog under a constant climate and a varying climate. The authors show that the 2D model gives different results from the 1D version of the model for the centre of the bog and explain how the differences are due to variations in peat properties between bog centre and margin in the 2D version. I think the paper complements the recent paper on the 1D model nicely and deserves to be published, although not in its current form, due to concerns I have about how the model is presented and compared with data and other (non poro-elastic) models. I explain these concerns below.
Presents results from a single model parameterisation
The authors present the results from a single model parameterisation. In a previous paper on the 1D model, Mahdiyasa et al. (2023) report modelled fluctuations of surface level of as much as 25 cm in response to variations in water-table position of about 50 cm. Such a large range in surface elevation seems generally implausible for Sphagnum peats, except floating mats in bog pools. In my experience, variations in surface elevation are typically a factor of four to five less than simulated by the 1D model. The authors cite Whittington and Price (2006) who report substantial changes in the position of the peat surface relative to the tubes of unanchored piezometers, but such instruments cannot be taken as reliable indicators of surface elevation. The parameterisation used in the current paper is different from that in Mahdiyasa et al. (2023) and the surface motion across the 2D model is not presented or discussed. However, I’d be interested in knowing what happens when the poro-elastic effect is ‘dialled down’. How different are the model results? At what point does the poro-elastic effect become of secondary importance compared to the ecological and hydrological processes? I think the paper would benefit from a short section looking at model sensitivity to the degree of poro-elasticity.
Comparisons with data
The authors compare the spatial pattern in their data with data from a blanket bog in Ireland. Although there is some overlap between raised bogs – which is what the authors simulate – and blanket bogs, the two peatland types can be quite different, and I am not sure it makes sense to compare the model of one type with the field results of the other. The authors also report that their simulated peat properties fall within the ranges reported in the literature. I don’t think such a comparison is that useful because properties such as hydraulic conductivity can show enormous variation across different peats – ‘peat’ is not a single soil type. This means that, almost regardless of the values simulated by the model, it will fit within the observed range. A somewhat different point applies to the model-data comparison for the rate of peat and carbon accumulation. As shown by Young et al. (2021) (https://www.nature.com/articles/s41598-021-88766-8) it is not possible to obtain past rates of net peat and carbon accumulation from the first derivative of the age-depth curve. Studies that purport to do so are, unfortunately, in error and shouldn’t be used for model-data comparisons.
The authors don’t compare their predictions of peatland shape with data. Many raised bogs approximate a hemi-ellipse in cross section, but the MPeat2D results shown in Figures 5 and 8 show what seems to be a very different profile. I am not convinced the model has that much skill in representing overall peatland form. The authors are encouraged to compare the modelled cross-sectional shape with real raised bogs.
I understand the desire of the authors to produce some ‘generic’ model results, but it would also be useful, whether in this paper or a follow-up paper, to apply the model to a particular site to see how well it simulates overall peatland shape, peat properties, and the age-depth curve.
Comparison with DigiBog
In the discussion section the authors compare their model’s predictions with those from DigiBog. I can’t be sure, but they seem to have used an early prototype of DigiBog from 2012 which has long been superseded (since 2014). More recent versions of DigiBog produce a more realistic margin to raised bogs. The authors do not indicate how DigiBog was parameterised, so it is unclear what is being compared here. The DigiBog team, of which I am a member, would be happy to share more recent model code with the authors should they want to use it. Finally, the comparison with DigiBog should be reported in the Model Implementation and Results sections, and not just the Discussion; it is odd to report results in a discussion section.
Other processes
When building a model, modellers usually try and include all the key processes, leaving out those to which the model is not sensitive. There are many ways in which models such as DigiBog might be improved, such as the decay routines which are heavily empirical. The decision on what to include and exclude is also dependent on how much is known about a process. If information on the process is sparse then it will be difficult to include. I welcome the authors looking at the effects of poro-elasticity on peatland development, but I think there remains considerable uncertainty about the importance of the process. Other processes about which quite a lot is known include the build up, release, and dissolution of biogenic gas bubbles below the water table on an annual cycle. Bubbles may occupy more than 20% of the total peat volume, blocking pores and reducing the peat’s hydraulic conductivity, and also making the peat more buoyant. To me, these effects would seem to equal or perhaps exceed the effects of poro-elasticity and I would be interested in hearing, via the discussion section, what the authors thought about this possibility.
I have made more comments on a pdf of the paper and this is posted separately for the authors and the editor. Some of the points made on the pdf are covered in the comments above, but the authors are encouraged to respond to those that aren’t. Of particular importance is that Equation (17) is given wrongly – as reproduced, it is non-homogenous – I think specific storage should be replaced with specific yield.
I operate a policy of open reviewing and ask that my name be revealed to the authors.
Andy Baird,
Chair of Wetland Science, University of Leeds, UK;
11th December 2023.
-
AC1: 'Reply on RC1', Adilan Mahdiyasa, 09 Feb 2024
The authors would like to thank the reviewer Andy Baird for the time and effort in reviewing this manuscript and for recognizing the significance of this work. We have considered the comments and suggestions and provided our response in the attached PDF file.
-
AC1: 'Reply on RC1', Adilan Mahdiyasa, 09 Feb 2024
-
RC2: 'Comment on egusphere-2023-2535', Anonymous Referee #2, 22 Feb 2024
Mahdiyasa et al. developed a two-dimensional peatland process model that incorporates essential mechanical-ecohydrological feedbacks, which can simulate the spatial variability of an individual peatland, especially the differences in physical properties between the peatland centre and edge. The main difference from previous models is that the model considers mechanical deformation and simulates variable peat porosity and dry bulk density. Sensitivity simulations of MPeat2D successfully produce different vegetation compositions between the margin and the centre and show a higher bulk density and lower hydraulic conductivity at the peatland margin compared to the centre. The methodology on plant weight is interesting and the methods section is generally well described. Overall, I enjoyed reading this manuscript, which generates some new ideas about the development of peatland models. I recommend the acceptance of the manuscript after considering the following suggestions/comments.
-
AC2: 'Reply on RC2', Adilan Mahdiyasa, 04 Mar 2024
The authors would like to thank the reviewer for the time and effort in reviewing this manuscript and for recognizing the significance of this work. We have considered the comments and suggestions and provided our response in the attached PDF file.
-
AC2: 'Reply on RC2', Adilan Mahdiyasa, 04 Mar 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2535', Andrew Baird, 11 Dec 2023
Overview
This paper reports on an interesting new version of the MPeat model (Mahdiyasa et al., 2023) that simulates peatlands in 2D. The example used in the paper is a raised bog in cross section. The new model appears to have been set up correctly, and the numerical scheme reproduces analytical results for simple geometries very accurately. Much of the paper is given over to reporting on the simulation of the growth of a raised bog under a constant climate and a varying climate. The authors show that the 2D model gives different results from the 1D version of the model for the centre of the bog and explain how the differences are due to variations in peat properties between bog centre and margin in the 2D version. I think the paper complements the recent paper on the 1D model nicely and deserves to be published, although not in its current form, due to concerns I have about how the model is presented and compared with data and other (non poro-elastic) models. I explain these concerns below.
Presents results from a single model parameterisation
The authors present the results from a single model parameterisation. In a previous paper on the 1D model, Mahdiyasa et al. (2023) report modelled fluctuations of surface level of as much as 25 cm in response to variations in water-table position of about 50 cm. Such a large range in surface elevation seems generally implausible for Sphagnum peats, except floating mats in bog pools. In my experience, variations in surface elevation are typically a factor of four to five less than simulated by the 1D model. The authors cite Whittington and Price (2006) who report substantial changes in the position of the peat surface relative to the tubes of unanchored piezometers, but such instruments cannot be taken as reliable indicators of surface elevation. The parameterisation used in the current paper is different from that in Mahdiyasa et al. (2023) and the surface motion across the 2D model is not presented or discussed. However, I’d be interested in knowing what happens when the poro-elastic effect is ‘dialled down’. How different are the model results? At what point does the poro-elastic effect become of secondary importance compared to the ecological and hydrological processes? I think the paper would benefit from a short section looking at model sensitivity to the degree of poro-elasticity.
Comparisons with data
The authors compare the spatial pattern in their data with data from a blanket bog in Ireland. Although there is some overlap between raised bogs – which is what the authors simulate – and blanket bogs, the two peatland types can be quite different, and I am not sure it makes sense to compare the model of one type with the field results of the other. The authors also report that their simulated peat properties fall within the ranges reported in the literature. I don’t think such a comparison is that useful because properties such as hydraulic conductivity can show enormous variation across different peats – ‘peat’ is not a single soil type. This means that, almost regardless of the values simulated by the model, it will fit within the observed range. A somewhat different point applies to the model-data comparison for the rate of peat and carbon accumulation. As shown by Young et al. (2021) (https://www.nature.com/articles/s41598-021-88766-8) it is not possible to obtain past rates of net peat and carbon accumulation from the first derivative of the age-depth curve. Studies that purport to do so are, unfortunately, in error and shouldn’t be used for model-data comparisons.
The authors don’t compare their predictions of peatland shape with data. Many raised bogs approximate a hemi-ellipse in cross section, but the MPeat2D results shown in Figures 5 and 8 show what seems to be a very different profile. I am not convinced the model has that much skill in representing overall peatland form. The authors are encouraged to compare the modelled cross-sectional shape with real raised bogs.
I understand the desire of the authors to produce some ‘generic’ model results, but it would also be useful, whether in this paper or a follow-up paper, to apply the model to a particular site to see how well it simulates overall peatland shape, peat properties, and the age-depth curve.
Comparison with DigiBog
In the discussion section the authors compare their model’s predictions with those from DigiBog. I can’t be sure, but they seem to have used an early prototype of DigiBog from 2012 which has long been superseded (since 2014). More recent versions of DigiBog produce a more realistic margin to raised bogs. The authors do not indicate how DigiBog was parameterised, so it is unclear what is being compared here. The DigiBog team, of which I am a member, would be happy to share more recent model code with the authors should they want to use it. Finally, the comparison with DigiBog should be reported in the Model Implementation and Results sections, and not just the Discussion; it is odd to report results in a discussion section.
Other processes
When building a model, modellers usually try and include all the key processes, leaving out those to which the model is not sensitive. There are many ways in which models such as DigiBog might be improved, such as the decay routines which are heavily empirical. The decision on what to include and exclude is also dependent on how much is known about a process. If information on the process is sparse then it will be difficult to include. I welcome the authors looking at the effects of poro-elasticity on peatland development, but I think there remains considerable uncertainty about the importance of the process. Other processes about which quite a lot is known include the build up, release, and dissolution of biogenic gas bubbles below the water table on an annual cycle. Bubbles may occupy more than 20% of the total peat volume, blocking pores and reducing the peat’s hydraulic conductivity, and also making the peat more buoyant. To me, these effects would seem to equal or perhaps exceed the effects of poro-elasticity and I would be interested in hearing, via the discussion section, what the authors thought about this possibility.
I have made more comments on a pdf of the paper and this is posted separately for the authors and the editor. Some of the points made on the pdf are covered in the comments above, but the authors are encouraged to respond to those that aren’t. Of particular importance is that Equation (17) is given wrongly – as reproduced, it is non-homogenous – I think specific storage should be replaced with specific yield.
I operate a policy of open reviewing and ask that my name be revealed to the authors.
Andy Baird,
Chair of Wetland Science, University of Leeds, UK;
11th December 2023.
-
AC1: 'Reply on RC1', Adilan Mahdiyasa, 09 Feb 2024
The authors would like to thank the reviewer Andy Baird for the time and effort in reviewing this manuscript and for recognizing the significance of this work. We have considered the comments and suggestions and provided our response in the attached PDF file.
-
AC1: 'Reply on RC1', Adilan Mahdiyasa, 09 Feb 2024
-
RC2: 'Comment on egusphere-2023-2535', Anonymous Referee #2, 22 Feb 2024
Mahdiyasa et al. developed a two-dimensional peatland process model that incorporates essential mechanical-ecohydrological feedbacks, which can simulate the spatial variability of an individual peatland, especially the differences in physical properties between the peatland centre and edge. The main difference from previous models is that the model considers mechanical deformation and simulates variable peat porosity and dry bulk density. Sensitivity simulations of MPeat2D successfully produce different vegetation compositions between the margin and the centre and show a higher bulk density and lower hydraulic conductivity at the peatland margin compared to the centre. The methodology on plant weight is interesting and the methods section is generally well described. Overall, I enjoyed reading this manuscript, which generates some new ideas about the development of peatland models. I recommend the acceptance of the manuscript after considering the following suggestions/comments.
-
AC2: 'Reply on RC2', Adilan Mahdiyasa, 04 Mar 2024
The authors would like to thank the reviewer for the time and effort in reviewing this manuscript and for recognizing the significance of this work. We have considered the comments and suggestions and provided our response in the attached PDF file.
-
AC2: 'Reply on RC2', Adilan Mahdiyasa, 04 Mar 2024
Peer review completion
Journal article(s) based on this preprint
Model code and software
MPeat2D Adilan Widyawan Mahdiyasa https://doi.org/10.5281/zenodo.10050891
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 617 | 222 | 38 | 877 | 25 | 26 |
- HTML: 617
- PDF: 222
- XML: 38
- Total: 877
- BibTeX: 25
- EndNote: 26
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Cited
Adilan Widyawan Mahdiyasa
David John Large
Matteo Icardi
Bagus Putra Muljadi
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1717 KB) - Metadata XML