Preprints
https://doi.org/10.5194/bg-2022-56
https://doi.org/10.5194/bg-2022-56
 
17 Mar 2022
17 Mar 2022
Status: this preprint is currently under review for the journal BG.

Modeling nitrous oxide emissions from agricultural soil incubation experiments using CoupModel

Jie Zhang1, Wenxin Zhang2, Per-Erik Jansson3, and Søren O. Petersen1 Jie Zhang et al.
  • 1Department of Agroecology, iClimate, Aarhus University, Tjele, Denmark
  • 2Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
  • 3Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Stockholm, Sweden

Abstract. Efforts to develop effective climate mitigation strategies for agriculture require methods to estimate nitrous oxide (N2O) emissions from soil. Process-based biogeochemical models have been used for such estimations but were mainly tested with field-scale measurements. In this study, results from a short-term (43-day) factorial incubation experiment were used to investigate the ability of a process-oriented model (CoupModel) to estimate N2O and carbon fluxes, and soil mineral nitrogen (N) dynamics. This study identified the sensitivities of model parameters when estimating three output variables using a global sensitivity analysis approach. Our results suggested that important parameters regarding N2O flux estimates were linked to the decomposability of soil organic matter (e.g. organic C pool sizes) and the denitrification process (e.g. Michaelis constant and denitrifier respiratory rates). The model was able to simulate low-magnitude daily and cumulative N2O fluxes with model errors (MEs) close to zero, but tended to underestimate N2O fluxes as observed daily values increased over 0.1 g N m-2 day-1. Besides, the response of N2O emissions to soil moisture was not well reflected in the model, probably related to the indirect involvement of soil moisture response function in the denitrification process. We also evaluated ancillary variables regarding N cycling, which indicates that more frequent measurements and additional types of observed data such as soil oxygen content and the microbial sources of emitted N2O are required to further evaluate model performance and biases. The current description of the N cycling process in the model may not consistently represent the temporal scale of nitrification and denitrification processes behind N2O emissions. The major challenges for calibration are associated with high sensitivities of denitrification parameters to initial soil moisture abiotic conditions and residue amendment. For the development of process-based models, we suggest there is a need to address soil heterogeneity, and to revisit current subroutines of moisture response functions.

Jie Zhang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2022-56', Anonymous Referee #1, 09 May 2022
  • CC1: 'Comment on bg-2022-56', Lorenzo Brilli, 10 May 2022
  • RC2: 'Comment on bg-2022-56', Anonymous Referee #2, 13 May 2022

Jie Zhang et al.

Jie Zhang et al.

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Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework, and also suggests future steps of model development which has implications on the broader communities of ecosystem modelers.
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