University of Oulu

Xiao Huang, Hanna Silvennoinen, Bjørn Kløve, Kristiina Regina, Tanka P. Kandel, Arndt Piayda, Sandhya Karki, Poul Erik Lærke, Mats Höglind, Modelling CO2 and CH4 emissions from drained peatlands with grass cultivation by the BASGRA-BGC model, Science of The Total Environment, Volume 765, 2021, 144385, ISSN 0048-9697,

Modelling CO₂ and CH₄ emissions from drained peatlands with grass cultivation by the BASGRA-BGC model

Saved in:
Author: Huang, Xiao1; Silvennoinen, Hanna2; Kløve, Bjørn3;
Organizations: 1Norwegian Institute of Bioeconomy Research, Klepp Station, Norway
2Norwegian Institute of Bioeconomy Research, Ås, Norway
3Water, Energy and Environmental Engineering Research Unit, University of Oulu, Oulu, Finland
4Bioeconomy and Environment Unit, Natural Resources Institute Finland, Jokioinen, Finland
5Noble Research Institute, LLC, Ardmore, USA
6Thünen Institute for Climate-Smart Agriculture, Braunschweig, Germany
7Delta Water Management Research Unit, USDA-ARS, Jonesboro, USA
8Department of Agroecology, Aarhus University, Interdisciplinary Centre for Climate Change, Tjele, Denmark
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.5 MB)
Persistent link:
Language: English
Published: Elsevier, 2021
Publish Date: 2021-04-19


Cultivated peatlands under drainage practices contribute significant carbon losses from agricultural sector in the Nordic countries. In this research, we developed the BASGRA-BGC model coupled with hydrological, soil carbon decomposition and methane modules to simulate the dynamic of water table level (WTL), carbon dioxide (CO₂) and methane (CH₄) emissions for cultivated peatlands. The field measurements from four experimental sites in Finland, Denmark and Norway were used to validate the predictive skills of this novel model under different WTL management practices, climatic conditions and soil properties. Compared with daily observations, the model performed well in terms of RMSE (Root Mean Square Error; 0.06–0.11 m, 1.22–2.43 gC/m²/day, and 0.002–0.330 kgC/ha/day for WTL, CO₂ and CH₄, respectively), NRMSE (Normalized Root Mean Square Error; 10.3–18.3%, 13.0–18.6%, 15.3–21.9%) and Pearson’s r (Pearson correlation coefficient; 0.60–0.91, 0.76–0.88, 0.33–0.80). The daily/seasonal variabilities were therefore captured and the aggregated results corresponded well with annual estimations. We further provided an example on the model’s potential use in improving the WTL management to mitigate CO₂ and CH₄ emissions while maintaining grass production. At all study sites, the simulated WTLs and carbon decomposition rates showed a significant negative correlation. Therefore, controlling WTL could effectively reduce carbon losses. However, given the highly diverse carbon decomposition rates within individual WTLs, adding indicators (e.g. soil moisture and peat quality) would improve our capacity to assess the effectiveness of specific mitigation practices such as WTL control and rewetting.

see all

Series: Science of the total environment
ISSN: 0048-9697
ISSN-E: 1879-1026
ISSN-L: 0048-9697
Volume: 765
Article number: 144385
DOI: 10.1016/j.scitotenv.2020.144385
Type of Publication: A1 Journal article – refereed
Field of Science: 1172 Environmental sciences
218 Environmental engineering
Funding: We acknowledge support from the project “Climate smart use of Norwegian organic soils” (MYR, 2017-2022) funded by the Research Council of Norway (decision no. 281109).
Copyright information: © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (