Understanding the spatial distribution of peat soils and other hydromorphic organic soils is essential for terrestrial carbon storage, biodiversity, and sustainable land management. In addition to these overarching purposes, there is now an urgent need to better localize these soils in the wake of the recently adopted European Nature Restoration Law (NRL). The NRL requires EU member states to formulate plans for the restoration of organic soils under agriculture (and other land-uses such as forest) constituting drained peatlands from 2026 onwards. A comprehensive, high-resolution map of peat and other hydromorphic organic soils covering the entire Austrian territory (i.e. land-uses other than agriculture) to support this objective is currently lacking.

To model the distribution of these soils across Austria, we propose a strategy based on regression and machine learning (ML), driven by legacy occurrence data and spatial covariates. Owing to the nature of the legacy data, we define six operational classes of peat and other hydromorphic organic soils, derived from the Austrian Soil Taxonomy in conjunction with the IPCC 2013 Wetlands Supplement. Response variables (i.e., expected soil classes) are constructed by re-classifying 14 legacy datasets containing land-use specific information on soils and/or vegetation. These include the Agricultural Soil Map of Austria, the Austrian Soil Taxation Survey, the Austrian Soil Information System BORIS, various forest site and vegetation mapping projects and the currently updated Austrian moorland protection database. In the process, real point data is supplemented by synthetic points generated by sampling from input polygon maps.

Separate occurrence probability models are built for each response class using (ensembles of) Environmental Niche Models (ENMs, also known as Species Distribution Models). These models predict the likelihood of occurrence for each peat soil type based on spatially explicit, high-resolution predictor variables (100m and higher). Covariates include soil properties, climate, relief features from Digital Elevation Models (DEMs), vegetation indices from remote sensing, and parent material, following the well-established SCROPAN approach of Digital Soil Mapping. The final indicative map is created by combining predictions from individual models. We employ cross-validation to tune ML hyperparameters and assess predictive model performance. Additionally, external evaluation will be carried out through a field campaign in spring 2025. A total of 90 transects will be established to collect data on soils and vegetation which will serve map validation and iterative model refinement.

The resulting indicative map will depict peat and hydromorphic organic soil distribution across Austria at high spatial resolution. Amongst others, it will serve as valuable guidance for field campaigns that likely will precede any targeted restoration measures under the NRL.

How to cite: Forstner, S. J., Brunner, T., Schwaighofer, I., Weninger, T., Weiß, M., Egger, G., Tulipan, M., Schmidt, A., Schwienbacher, M., Müller, R., Glatzel, S., Kessler, D., Starlinger, F., Kapitany, E., Wrbka, T., Haslmayr, H.-P., Hummel, C., Englisch, M., and Baumgarten, A.: Indicative mapping of peat and other hydromorphic organic soils across Austria with legacy data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19334, https://doi.org/10.5194/egusphere-egu25-19334, 2025.

Peatland is an important storage of carbon (C) and nitrogen (N) on the earth surface. They have played a vital role in regulating the global climate through their capacity for C and N sequestration. Human activities including peatland drainage, burning, and conversion for agriculture transform peatlands from C sinks into greenhouse gas (GHG) sources. In Ireland, approximately 20% of the land area is peatland, over 95% of them have been degraded through anthropogenic activities. To assess the impact of peatland management on nitrous oxide (N₂O) emission, this study utilised the LICOR auto chamber and smart chamber coupled with state-of-the-art portable gas analysers to determine the N₂O emissions from grass-based agricultural peatland in Ireland. The site-specific characteristics that drive GHG production and can act as proxies for emissions (water table height and nutrient status) were also explored. Refined emission factors (EFs) were developed for N amendments applied in both drained and rewetted peatland. N amendments including mineral N fertiliser, cattle urine and sheep urine were applied to simulate real agricultural activities on peatland. The results obtained so far showed that peak N₂O emissions occurred on the day of N application and in the presence of rainfall. The cumulative N₂O emission showed significant difference between both drained and rewetted peatland. The outputs of this work will directly contribute to the Ireland National Inventory Report and provide insight for climate mitigation and peatland rehabilitation activities.

How to cite: Shi, W., Fenton, O., Richards, K., and Saunders, M.: Assessing Agricultural Peatland Emissions of Nitrous Oxide in Ireland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13823, https://doi.org/10.5194/egusphere-egu25-13823, 2025.

The release and uptake of greenhouse gases (GHGs), including CO₂, CH₄, and N₂O, are closely tied to land use practices, with drained peatlands representing significant emission sources. According to Iceland’s National Inventory Report to the UNFCCC, emissions from drained peatlands are the largest single contributor to the country's total GHG emissions. While international research highlights peatland restoration as an effective strategy for reducing GHG emissions, the validity of such actions in Iceland has been limited due to a lack of country-specific data.

This study seeks to fill this gap by measuring the GHG dynamics of a drained and subsequently restored peatland at the farm Lækur in W-Iceland. Drained for livestock pasture 65 years ago but never cultivated, this site represents the dominant land use category for drained peatlands in Iceland. In this research, GHG, water, and energy fluxes are measured using the eddy covariance method, complemented by additional data on climatic variables, groundwater levels, soil moisture, and soil temperature.

The eddy covariance system was installed in January 2023. Preliminary results for 2023 indicate an annual net CO₂ emission of 1734.87 g m⁻² y⁻¹, negligible net CH₄ flux, an annual evapotranspiration of 420,416.10 g m⁻² y⁻¹, and equivalent rainfall of 420.42 mm y⁻¹.

The project uses a two-phase research approach: (1) baseline assessment of GHG fluxes under drained conditions and (2) ongoing monitoring post-rewetting (2025 onward). The study provides a comprehensive analysis of diurnal, seasonal, and annual GHG flux dynamics in drained peatlands and evaluates the initial impacts of rewetting. By generating high-quality, site-specific data, this research aims to inform the development of effective peatland restoration strategies as a GHG mitigation measure in Iceland and beyond.

How to cite: Salimi, A., Bjarnadóttir, B., Óskarsson, H., and D.Sigurðsson, B.: CO₂, CH₄, and Water Fluxes of a Drained Peatland in W-Iceland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13958, https://doi.org/10.5194/egusphere-egu25-13958, 2025.

However, due to slow biogeochemical processes, the carbon accumulation in peatlands typically occurs at a low rate. In addition, peatlands that have been degraded or drained from land-use conversion become net carbon sources, as is the case with 82 % of the peatlands in Switzerland.

Restoring drained peatlands is therefore widely recognised as a nature-based solution for carbon removal. With the development of carbon market, carbon credits from rewetting peatlands are often issued based on generalised estimates on avoided emissions. However, information on long-term greenhouse gas (GHG) exchanges in restored peatlands remains scarce, with limited spatiotemporal coverage and inconsistent outcomes likely stemming from varying climate conditions, initial states, vegetation types, and restoration approaches. Consequently, there is an urgent need to account for site-specific carbon dynamics and improve the methodologies for assessing the GHG balance when evaluating carbon credit schemes for peatland restoration.

In this study, we use simulations of the well-established Terrestrial Biosphere Model, LPX-Bern, to investigate peatland carbon dynamics in Switzerland. Combined with empirical estimates based on field measurements, the modelled peatland carbon storage from the preindustrial period to the present day is analysed under natural processes, land use, and different restoration scenarios to assess the peatland restoration potentials. The results are compared with a carbon credit scheme using max.moor, a conservative estimate on avoided emissions following rewetting according to a generalised carbon density (56 kg C m^-2) for a peatland in Niremont, Switzerland.

We demonstrate that, over a 50-year timeframe, the dynamically simulated peatland carbon storage indicates a substantial overestimation, up to 43 %, of avoided emissions by the max.moor approach for the Niremont site. This highlights the necessity of incorporating approaches with increased accuracy on estimating peatland restoration impacts on carbon dynamics and GHG exchanges. Moreover, future climate change is expected to exacerbate the uncertainties associated with these estimates. This work thus contributes to advancing the understanding of peatland restoration impacts on GHG exchanges and feedback to climate change.

How to cite: Sun, Q., Faher, L., and Davin, É.: Evaluating Carbon Dynamics and Carbon Credits of Peatland Restoration in Switzerland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11999, https://doi.org/10.5194/egusphere-egu25-11999, 2025.

Baselines are a critical factor in peatland conservation or restoration projects in the voluntary carbon market, because a project's climate impact is measured by the difference between realised emissions and a baseline representing business-as-usual. Because business-as-usual encompasses a range of possible outcomes, the baseline is inherently uncertain. Baselines for peatland carbon projects present additional challenges because land use change at one location can drive greenhouse gas emissions elsewhere in the peatland. These effects occur because of the critical role of waterlogging in protecting peatland belowground carbon stocks, and imply that not only the area of land converted but also its spatial distribution exerts an important control on anthropogenic CO₂ emissions from peatlands.

To avoid bias and over-crediting, it is desirable to derive a baseline for peatland carbon projects that represents a weighted average across the range of possible outcomes, while considering the hydrological impacts of changing mosaics of land use on peatland greenhouse gas balances. We describe a pixel-matching approach to peatland baseline emissions that uses land use change modelling to produce an ensemble of land use trajectories collectively representing business-as-usual.  Emissions are then averaged across these realisations to produce an approximation of expected business-as-usual emissions.  We discuss the challenges involved in implementing this scheme while balancing rigor, simplicity, robustness and ease-of-use.

How to cite: Cobb, A., Dommain, R., Ng, J., Arassah, F. I., Darmawan, A., Bediako, A. A., Hartmann, J., Jaya, F., Markant, H., Moritz, F., and Sánchez-Alandete, P.: Aggregate baselines for tropical peatland restoration and conservation projects, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19224, https://doi.org/10.5194/egusphere-egu25-19224, 2025.

Peatland restoration is a key climate mitigation strategy due to the high carbon storage capacity of peat soils. In the European Union (EU), more than half of peatlands have been drained - primarily for agriculture and forestry - resulting in significant greenhouse gas (GHG) emissions. Rewetting these areas can substantially reduce emissions and support the EU’s goal of net-zero CO₂ emissions by 2050. Essential for tracking progress toward mitigation targets is the precise accounting of GHG emissions from peatlands. While EU countries already report peatland emissions under the UNFCCC, comprehensive accounting for managed wetlands (including peatlands) will only become mandatory in 2026. However, comparability is limited: Peatland emissions are reported across diverse (land-use) categories, soil types, and GHGs, resulting in fragmented reporting with incomplete coverage by many countries. Additionally, countries employ diverse methods, datasets, and emission factors, leading to inconsistencies. This study analyses the methods EU countries use to report GHG emissions from peatlands, focusing on Germany and its neighbouring countries. Specifically, it addresses (1) the methodological differences between and within countries, identifying major inconsistencies, and (2) the extent to which these differences affect reported emissions and their comparability. Using a standardized evaluation framework, we quantify the impact of methodological differences on GHG inventories and visualize variations in CO₂-equivalent emissions per hectare of peatland. We also apply these methodologies conceptually to peatland sites with varying characteristics to demonstrate how methodological choices shape reporting outcomes. The results provide a detailed quantification of the discrepancies in reporting for peatland emissions and their effects. This study thus contributes to advancing research to harmonize peatland GHG reporting across the EU and improve comparability.

How to cite: Borel, P., Bosch, S., Kunstmann, H., Kunz, J., Kurz, S., and Fiener, P.: Methods for greenhouse gas accounting of peatlands: A comparative analysis of EU and German approaches, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7401, https://doi.org/10.5194/egusphere-egu25-7401, 2025.

Rewetting of organic-rich agricultural soils is a management strategy to reduce CO₂ emissions and meet policy targets for agricultural GHG emissions. Denmark has committed to support the rewetting of at least 100,000 ha of agricultural peat soils by 2030. The climate benefits of this initiative depend on emissions before and after rewetting, particularly CO₂ emissions, which have been assessed using national emission factors. However, recent studies suggest that modelling CO₂ emissions as a function of mean annual water table depth (WTD) provides a more accurate assessment than fixed emission factors. Despite these advances, large uncertainties and knowledge gaps remain in the estimation of GHG emissions from agricultural peat soils, particularly in relation to the effect of land use and environmental factors such as peat depth, organic carbon (OC) content, water table depth and soil moisture. 

Most controlled studies of GHG emissions from drained peat soils have focused on the topsoil where microbial activity is higher than in the subsoil. However, drained subsoils contribute to overall GHG fluxes, but the controlling factors need to be clarified. Some studies suggest that CO₂ emissions increase proportionally to WTD, i.e., with equal importance of drained topsoil and subsoil compartments, while other data suggest that deeper  WTD have progressively less effect on CO₂ fluxes. In addition, topsoil and subsoil may differ in their sensitivity to environmental changes, such as temperature and moisture fluctuations, influenced by climate change. Therefore, understanding how topsoil and subsoil differ in their contribution to GHG fluxes is critical for developing predictive models and supporting climate-smart peatland management strategies.

Drained OC-rich soils are hotspots for CO₂ emissions, but the continued microbial mineralization means that the OC content transitions to that of mineral soils. Yet, it remains unclear how the residual OC content controls the rate of CO₂ emissions. The Danish definition of organic soils includes soils with >6% OC, while other countries use thresholds of >12% OC or higher. Hence, soils with 6-12% OC are part of the Danish GHG inventory, but there is a lack of data on the CO₂ emissions from these soils. Recent studies suggest that soils with 6-12% OC can emit CO₂ at similar rates as soils with >12% OC, and that emissions from soils with 6-12% OC may be underestimated. The refinement of CO₂ emission estimates for 6-12% OC soils is critical for the accuracy of national inventories, but also for crediting the climate benefits of initiatives to rewet drained organic soils.

In brief, this poster invites discussion on the progress and knowledge gaps in estimating CO₂ emissions from agricultural peat soils, e.g., in relation to the role of subsoils and the OC content.

How to cite: Elsgaard, L.: Progress and knowledge gaps in estimating CO2 emissions from organic-rich agricultural soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9488, https://doi.org/10.5194/egusphere-egu25-9488, 2025.