The effects of peat thickness and water table depth on CO2 and N2O emissions from agricultural peatlands – a process-based modelling approach
Abstract. Peatlands are critical carbon (C) reservoirs, storing over a fifth of the global soil organic C stock. However, some peatlands are drained and cultivated for agricultural use, which makes them a significant source of greenhouse gas (GHG) emissions. Managing water table depth (WTD) is considered a key operation for mitigating GHG emissions in cultivated peatlands. Modelling the impacts of water management would be a cost-efficient way of studying its large-scale effects, both in the present and in the future. Here, we used the process-based model LandscapeDNDC (LDNDC) to assess the relationships between WTD, peat layer thickness and the GHG exchange. We simulated a boreal agricultural peatland (NorPeat, Finland), which was cultivated with silage grass and barley during the study years 2019–2022. The site was monitored with an eddy covariance (EC) tower, and divided into six drainage blocks with distinct peat profiles, each equipped with sensors for continuous water table measurements. The model performance was evaluated on a daily and seasonal level using EC measurements of carbon dioxide (CO2), nitrous oxide (N2O) and water fluxes for the study years, alongside with satellite retrievals of the leaf area index and three-year data from block-specific dark chamber flux measurements of CO2 and N2O. The LDNDC model was found to be suitable for drained peatland simulations, although the performance was the highest when verified against measurements from shallow peat soils. Although the simulated N2O annual balances were in the same range as the measurements, their accuracy was not as high as it was for CO2. To study the impact of WTD on GHG fluxes, we had three different scenarios in addition to the baseline runs with measured conditions; these scenarios had an average WTD of 50 cm, 30 cm and 15 cm below the soil surface. The study results showed a clear relationship between CO2 emissions and WTD (r = 0.84 between exposed organic matter and net ecosystem carbon balance). GHG mitigation was achieved in all scenarios with increased water table; even in the most modest scenario, the annual reduction from the baseline was 0.47 kg CO2e m-2 in deep peat blocks and 0.24 kg CO2e m-2 in shallow peat blocks. CO2 emissions were found to be more strongly affected than N2O emissions. In the highest water table scenario, which resembled conditions close to paludiculture, the net ecosystem exchange of CO2 became close to neutral. The implications of raising the WTD were found to be insensitive to model parameters that control evapotranspiration or organic matter decomposition. These findings highlight that even moderate water management practices are valuable in order to mitigate GHG emissions in cultivated peatlands.
Comment on "The effects of peat thickness and water table depth on CO2 and N2O emissions from agricultural peatlands - a process-based modelling approach" by Kajasilta et al., Biogeosciences
General comments
In this manuscript, authors applied LDNDC to simulate C and N dynamics in a single peatland field site following traditional grass-intensive crop rotation, and examined the change of net ecosystem carbon balance (NECB) and N2O emission under different prescribed peat thickness and water table depth. Although only one site is studied, this study also evaluated the capability of LDNDC to simulate C/N dynamics of peatland, which can be considered as a novel work. Though most works are solid, some key information is missing and shall be presented to fortify major findings. In addition, the description of the N cycle in LDNDC and its calibration is missing.
Specific comments:
Technical correction:
Line 79: "chemical soil properties" shall be "soil chemical properties"
Line 95: If both blocks 5up and 6up have similar peat layer thickness to block 5 and 6, I suggest changing the color of block 5up and 6up in Figure 1.
Line 125: "following (Vekuri et al., 2025)" shall be "following Vekuri et al. (2025), "?
Line 128: "gaps of two hours" shall be "gaps within two hours"?
Line 130: What is the size of the window for your moving average?
Line 131: The cited paper Vira et al. (2025) does not describe how you process measured ET?
Line 148: "LAI was evaluated using the methods described in" Do you have in-situ measurements of LAI you did evaluate against S2 products?
Line 154: "layer-wise representation" How did you define the soil layer depth, node depth and top/bottom boundary conditions for your soil water movement/dynamics module to simulate WTD dynamics?
Line 160: It seems like "Plamox" is an abbreviation. Can you tell readers the full name?
Line 162: What does "CanopyECM" mean?
Line 163: It seems like "MeTrx" is a module representing soil biogeochemical processes? Please provide the full name.
Line 169: "as soils may exhibit substantial annual losses" shall be "as soil organic carbon may exhibit substantial annual losses"
Line 172: "The module handles the dynamics of water within the soil profile" can be simplified "The module handles the soil water movement, and accounts for the amount of precipitation intercepted by foliage, infiltration, ..."
Line 173: "possible changes in snow cover and ice content in the soil" This requires air temperature and soil temperature profile. How does your model obtain this information? By calculation or use prescribed temperature profile?
Line 174: "Evapotranspiration follows the potential evapotranspiration and is limited either by the amount of surface water or remaining potential evapotranspiration, whichever is reached first." Actual evapotranspiration (AET) is different from potential evapotranspiration (PET), which can only be equivalent if you are calculating ET from a submerged surface. In your case however, you have drained peatland blocks during a certain time period, so they are different. Please clarify.
Line 180: "The default value of spinupdeltac is 0, corresponding to the original equilibrium assumption, but it can now be set to reflect user-defined annual changes." What is the value of this "user-defined annual changes" in your study?
Line 186: "we increased the decomposition rates" What method did you use to determine the increment of the decomposition rate?
Line 187: "model initialises most of the carbon and nitrogen in two pools that represent young and old organic matter," Should this be labile vs. recalcitrant? Also, how did you determine their relative proportion without observation?
Line 189: "resulted in spurious blockwise variability in soil respiration" can you describe how spurious it is? For example, respiration in a certain block becomes extremely high or low? Also, I am confused that authors change parameter values but claim "no differences in the parameterisation between the blocks", then why is there a blockwise variability in soil respiration?
Line 199: "we adjusted parameters handling the photosynthesis activity (H2OREF_A) and stomata closing (H2OREF_GS)" Can you show me the actual name of these parameters? If readers cannot get detailed information about these parameters, the rest of the description on how you adjust these parameters to "avoid underestimating the GPP" does not make sense.
Line 202: "The drought periods were not seen in EC measurements" If you don't have observation based evidence, how can you be sure that low GPP is problematic?
Line 226 - 236: This shall be part of calibration not initialization.
Line 254: How did you treat tillage in LDNDC? For example, change the soil porosity and the base decomposition rate of C/N pools after tillage?
Line 256: The rest 1% of biomass is removed from the site or is kept alive?
Line 267: Do you also calculate CH4? If not, why is the ambient CH4 level mentioned in this study?
Line 268: Remove "the" from "similar to the those measured"
Line 314: Is the length of the vector equivalent to the length of the observed time series?
Line 336: Describe how you define and calculate N2O balances?
Line 348: "Soil measurements during the winter time were unreliable and should not be emphasized due to the measurement problems when the soil is frozen or close to that point." This is not your result. Shall move to section 2.
Figure 7: It seems like some of the modeled values are repeating, reflected by the almost same modeled values against completely different values from chamber measurement. Can you explain this phenomenon?
Line 463: "However, the simulated respiration differed between shallow and deep peat fields, which led the model to underestimate the ecosystem respiration for the shallow peat fields and overestimate it for deep peat fields." can be simplified to "However, the model underestimates the ecosystem respiration for the shallow peat fields and overestimates it for deep peat fields." Also, you can merge this one with the previous one paragraph.
Line 466: "the other years were either under or overestimated by up to a factor of two". Can you provide a certain evaluation about how this over-/underestimation of N2O can bring impact to your major conclusion of N2O balances under different WTD scenarios?
Line 482: "supports the hypothesis that increasing the water table can suppress nitrification and subsequently reduce the availability of nitrate for denitrification" Did LDNDC produce the similar phenomenon? I believe most of the popular models have these two fluxes as output so I would recommend authors to check model outputs.
Line 500: "This sensitivity analysis showed that our findings regarding the CO2 emissions were more robust to parametrisation than the absolute CO2 emissions." Can you rephrase this sentence? It is a bit tough for me to interpret?
Line 512: Incomplete sentence. "The scenario with a 50 cm average WTD required on average a 31 cm higher water table for deep peat blocks and a 44 cm higher water table in shallow peat blocks"
Line 519: "below the organic soil horizon in the shallow peat blocks". What is the depth of the O horizon for shallow and deep peat blocks, respectively?
Table S1. Add explanation of all parameters you have calibrated in table S1.