Biogeosciences
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Articles | Volume 22, issue 15
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.
https://doi.org/10.5194/bg-22-3867-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 15
Research article
 | 
12 Aug 2025
Research article |  | 12 Aug 2025

Groundwater–CO2 emissions relationship in Dutch peatlands derived by machine learning using airborne and ground-based eddy covariance data

Laura M. van der Poel, Laurent V. Bataille, Bart Kruijt, Wietse Franssen, Wilma Jans, Jan Biermann, Anne Rietman, Alex J. V. Buzacott, Ype van der Velde, Ruben Boelens, and Ronald W. A. Hutjes

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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.
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