Articles | Volume 22, issue 15
https://doi.org/10.5194/bg-22-3867-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-3867-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Aug 2025
Research article |
| 12 Aug 2025
| 12 Aug 2025
Groundwater–CO2 emissions relationship in Dutch peatlands derived by machine learning using airborne and ground-based eddy covariance data
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Laurent V. Bataille
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Bart Kruijt
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Wietse Franssen
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Wilma Jans
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Jan Biermann
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Anne Rietman
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
Alex J. V. Buzacott
Institute for Atmospheric and Earth System Research, University of Helsinki, 00014 Helsinki, Finland
Ype van der Velde
Faculty of Science, Earth and Climate, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, the Netherlands
Ruben Boelens
HydroLogic, 3811 HN Amersfoort, the Netherlands
Earth Systems and Global Change Group, Wageningen University, 6708 PB Wageningen, the Netherlands
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Tan J. R. Lippmann, Jacobus K. van Huissteden, Ype van der Velde, Veronique E. N. Boon, and Merit van den Berg
EGUsphere, https://doi.org/10.5194/egusphere-2026-2450, https://doi.org/10.5194/egusphere-2026-2450, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Peatlands either store carbon or release greenhouse gases depending on climate, water levels, and land management. We present an improved peatland model to better understand these processes. We validate the model at two sites in the Netherlands. The model reproduced observed carbon dioxide and methane exchange. This model can help to improve understanding of peatland emissions in response to environmental change.
Laurent Bataille, Bart Kruijt, Alexander Buzacott, Wilma Jans, Wietse Franssen, Jan Biermann, Hanne Berghuis, Quint van Giersbergen, Tom Heuts, Reinder Nouta, Niek Bosma, Ron Lootens, Hong Zhao, Merit van den Berg, Ype van de Velde, Christian Fritz, Gilles Erkens, and Ronald Hutjes
EGUsphere, https://doi.org/10.5194/egusphere-2026-3151, https://doi.org/10.5194/egusphere-2026-3151, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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Drained peatlands release large amounts of carbon dioxide, and raising water levels is widely proposed to reduce these emissions. We measured the yearly carbon balance at twenty sites across Dutch peatlands. Higher water tables were linked to lower emissions, a weak but fairly consistent effect. Site-to-site differences outweighed water level: land use and a clay layer over the peat strongly shaped emissions, so raising water levels works only if each site's intrinsic features are considered.
Anna Luisa Hemshorn de Sánchez, Wouter R. Berghuijs, Anne F. Van Loon, Dimmie Hendriks, and Ype van der Velde
Hydrol. Earth Syst. Sci., 30, 2667–2683, https://doi.org/10.5194/hess-30-2667-2026, https://doi.org/10.5194/hess-30-2667-2026, 2026
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This study explores how mean and extreme river flows respond to annual climate variability. Maps show where river flow is more sensitive to climate in Europe. Maximum flows are generally the most sensitive and minimum flows the least sensitive to precipitation changes. Sensitivities are influenced by many factors like climate, soil, and terrain. These findings improve our understanding of how rivers respond to climate and can support water management and disaster risk reduction across Europe.
Michiel K. van der Molen, Henk Snellen, Rupert Holzinger, Johannes G. M. Barten, Hong Zhao, Laurens Ganzeveld, Julie Fry, Wouter Peters, Maarten Krol, Jordi Vila-Guerau de Arrelano, and Bart Kruijt
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-99, https://doi.org/10.5194/essd-2026-99, 2026
Preprint under review for ESSD
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In 2021, a second tower was built in Loobos (NL-Loo) to measure carbon dioxide and water fluxes, as an Integrated Carbon Observing System (ICOS) Class 2 Ecosystem station. Instrumentation was installed to measure volatile organic compound and ozone fluxes. This paper describes the site’s geological and cultural history, ecosystem composition, instrumentation and ancillary ecosystem measurements. The paper goes into the quality of the measurements and continuity with respect to the first tower.
Hong Zhao, Han Dolman, Jan Elbers, Wilma Jans, Bart Kruijt, Eddy Moors, Henk Snellen, Jordi Vila-Guerau de Arellano, Wouter Peters, Maarten C. Krol, Ronald Hutjes, and Michiel van der Molen
Earth Syst. Sci. Data, 18, 2023–2045, https://doi.org/10.5194/essd-18-2023-2026, https://doi.org/10.5194/essd-18-2023-2026, 2026
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Under the Kyoto Protocol the carbon dioxide (CO2) balance for forest ecosystems was required to be measured. Consequently, CO2 flux measurements have been conducted in Loobos site in the Netherlands since 1996, becoming one of the 17 first FLUXNET sites globally. This paper provides a comprehensive overview of the instrumentation, data processing and the resulting data archive, enabling its further use in data analysis, model development and validation of satellite data retrievals.
Paul Waldmann, Max Eckl, Leon Knez, Klaus-Dirk Gottschaldt, Alina Fiehn, Christian Mallaun, Michał Gałkowski, Christoph Kiemle, Ronald Hutjes, Thomas Röckmann, Huilin Chen, and Anke Roiger
Atmos. Meas. Tech., 19, 185–210, https://doi.org/10.5194/amt-19-185-2026, https://doi.org/10.5194/amt-19-185-2026, 2026
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Nitrous oxide and methane emissions from agriculture need to be reduced, therefore emissions must be understood to effectively mitigate them. This is the first approach to measure those emissions aircraft-based, to assess their magnitude and drivers. We identified emission hotspots and temporal changes in agricultural emissions in the Netherlands. Our approach is applicable to further greenhouse gas emitters, therefore it builds a step towards more comprehensive emission quantification.
Asta Laasonen, Alexander Buzacott, Kukka-Maaria Kohonen, Erik Lundin, Alexander Meire, Mari Pihlatie, and Ivan Mammarella
Biogeosciences, 22, 7505–7518, https://doi.org/10.5194/bg-22-7505-2025, https://doi.org/10.5194/bg-22-7505-2025, 2025
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Carbon monoxide (CO) is an important indirect greenhouse gas, but its terrestrial sinks and sources are poorly understood. We present the first CO flux measurements using the eddy covariance method in an Arctic peatland. Our results show that CO fluxes are dominated by two processes: radiation-driven emissions and soil uptake. Dry peatland areas acted as CO sinks, while wetter areas were CO sources. Our findings suggest that current global models may underestimate Arctic CO emissions.
R. Willem Vervoort, Floris F. van Ogtrop, Mina Tambrchi, Farzina Akter, Alexander J. V. Buzacott, Jason S. Lessels, James P. Moloney, Dipangkar Kundu, Feike A. Dijkstra, and Thomas F. A. Bishop
Earth Syst. Sci. Data, 17, 6113–6127, https://doi.org/10.5194/essd-17-6113-2025, https://doi.org/10.5194/essd-17-6113-2025, 2025
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A detailed water quality dataset for a 1000 km2 catchment in New South Wales, Australia is presented. The water quality data for surface and groundwater was collected over 14 years and contains more than 1000 records. Despite missing values and different sampling methods and groups, the data provides a consistent overview of the hydrogeochemistry of the catchment. This dataset is valuable for global modelling studies as well as better understanding of local dryland salinity and water quality processes.
Ralf C. H. Aben, Daniël van de Craats, Jim Boonman, Stijn H. Peeters, Bart Vriend, Coline C. F. Boonman, Ype van der Velde, Gilles Erkens, and Merit van den Berg
Biogeosciences, 21, 4099–4118, https://doi.org/10.5194/bg-21-4099-2024, https://doi.org/10.5194/bg-21-4099-2024, 2024
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Drained peatlands cause high CO2 emissions. We assessed the effectiveness of subsurface water infiltration systems (WISs) in reducing CO2 emissions related to increases in water table depth (WTD) on 12 sites for up to 4 years. Results show WISs markedly reduced emissions by 2.1 t CO2-C ha-1 yr-1. The relationship between the amount of carbon above the WTD and CO2 emission was stronger than the relationship between WTD and emission. Long-term monitoring is crucial for accurate emission estimates.
Merit van den Berg, Thomas M. Gremmen, Renske J. E. Vroom, Jacobus van Huissteden, Jim Boonman, Corine J. A. van Huissteden, Ype van der Velde, Alfons J. P. Smolders, and Bas P. van de Riet
Biogeosciences, 21, 2669–2690, https://doi.org/10.5194/bg-21-2669-2024, https://doi.org/10.5194/bg-21-2669-2024, 2024
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Drained peatlands emit 3 % of the global greenhouse gas emissions. Paludiculture is a way to reduce CO2 emissions while at the same time generating an income for landowners. The side effect is the potentially high methane emissions. We found very high methane emissions for broadleaf cattail compared with narrowleaf cattail and water fern. The rewetting was, however, effective to stop CO2 emissions for all species. The highest potential to reduce greenhouse gas emissions had narrowleaf cattail.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
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Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Alexa Marion Hinzman, Ylva Sjöberg, Steve W. Lyon, Wouter R. Berghuijs, and Ype van der Velde
EGUsphere, https://doi.org/10.5194/egusphere-2023-2391, https://doi.org/10.5194/egusphere-2023-2391, 2023
Preprint archived
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An Arctic catchment with permafrost responds in a linear fashion: water in=water out. As permafrost thaws, 9 of 10 nested catchments become more non-linear over time. We find upstream catchments have stronger streamflow seasonality and exhibit the most nonlinear storage-discharge relationships. Downstream catchments have the greatest increases in non-linearity over time. These long-term shifts in the storage-discharge relationship are not typically seen in current hydrological models.
Ubolya Wanthanaporn, Iwan Supit, Bert van Hove, and Ronald W. A. Hutjes
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-56, https://doi.org/10.5194/hess-2023-56, 2023
Revised manuscript not accepted
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We evaluated the potential use of SEAS5 seasonal forecasting for Mainland Southeast Asia. The temperature and precipitation skills are tested. We subsequently implemented a hydrological model VIC to produce seasonal streamflow forecasts. SEAS5 is skilful to forecast temperature and rainfall as well as streamflow, but with strong seasonal and regional dependence. Overall, SEAS5 and hydrological forecasts show skill that can potentially be used for hydrological/agricultural management.
Cindy Quik, Ype van der Velde, Jasper H. J. Candel, Luc Steinbuch, Roy van Beek, and Jakob Wallinga
Biogeosciences, 20, 695–718, https://doi.org/10.5194/bg-20-695-2023, https://doi.org/10.5194/bg-20-695-2023, 2023
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In NW Europe only parts of former peatlands remain. When these peatlands formed is not well known but relevant for questions on landscape, climate and archaeology. We investigated the age of Fochteloërveen, using radiocarbon dating and modelling. Results show that peat initiated at several sites 11 000–7000 years ago and expanded rapidly 5000 years ago. Our approach may ultimately be applied to model peat ages outside current remnants and provide a view of these lost landscapes.
Jim Boonman, Mariet M. Hefting, Corine J. A. van Huissteden, Merit van den Berg, Jacobus (Ko) van Huissteden, Gilles Erkens, Roel Melman, and Ype van der Velde
Biogeosciences, 19, 5707–5727, https://doi.org/10.5194/bg-19-5707-2022, https://doi.org/10.5194/bg-19-5707-2022, 2022
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Draining peat causes high CO2 emissions, and rewetting could potentially help solve this problem. In the dry year 2020 we measured that subsurface irrigation reduced CO2 emissions by 28 % and 83 % on two research sites. We modelled a peat parcel and found that the reduction depends on seepage and weather conditions and increases when using pressurized irrigation or maintaining high ditchwater levels. We found that soil temperature and moisture are suitable as indicators of peat CO2 emissions.
Tanya Juliette Rebecca Lippmann, Monique Heijmans, Han Dolman, Ype van der Velde, Dimmie Hendriks, and Ko van Huissteden
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-143, https://doi.org/10.5194/gmd-2022-143, 2022
Preprint withdrawn
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To assess the impact of vegetation on GHG fluxes in peatlands, we developed a new model, Peatland-VU-NUCOM (PVN). These results showed that plant communities impact GHG emissions, indicating that plant community re-establishment is a critical component of peatland restoration. This is the first time that a peatland emissions model investigated the role of re-introducing peat forming vegetation on GHG emissions.
Yousef Albuhaisi, Ype van der Velde, and Sander Houweling
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-55, https://doi.org/10.5194/bg-2022-55, 2022
Manuscript not accepted for further review
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An important uncertainty in the modelling of methane emissions from natural wetlands is the wetland area. It is important to get the spatiotemporal covariance between the variables that drive methane emissions right for accurate quantification. Using high-resolution wetland and soil carbon maps, in combination with a simplified methane emission model that is coarsened in six steps from 0.005° to 1°, we find a strong relation between wetland emissions and the model resolution.
Thomas Janssen, Ype van der Velde, Florian Hofhansl, Sebastiaan Luyssaert, Kim Naudts, Bart Driessen, Katrin Fleischer, and Han Dolman
Biogeosciences, 18, 4445–4472, https://doi.org/10.5194/bg-18-4445-2021, https://doi.org/10.5194/bg-18-4445-2021, 2021
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Satellite images show that the Amazon forest has greened up during past droughts. Measurements of tree stem growth and leaf litterfall upscaled using machine-learning algorithms show that leaf flushing at the onset of a drought results in canopy rejuvenation and green-up during drought while simultaneously trees excessively shed older leaves and tree stem growth declines. Canopy green-up during drought therefore does not necessarily point to enhanced tree growth and improved forest health.
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Short summary
We combine two types of carbon dioxide (CO2) data from Dutch peatlands in a machine learning model: from fixed measurement towers and from a light research aircraft. We find that emissions increase with deeper water table depths (WTDs) by 4.6 tons of CO2 per hectare per year for each 10 cm deeper WTD on average. The effect is stronger in winter than in summer and varies between locations. This variability should be taken into account when developing mitigation measures.
We combine two types of carbon dioxide (CO2) data from Dutch peatlands in a machine learning...
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