Global Research Alliance N 2O chamber methodology guidelines: Summary of modeling approaches

Donna Giltrap*, Jagadeesh B. Yeluripati, Pete Smith, Nuala Fitton, Ward N Smith, Brian Grant, Christopher D Dorich, Jia Deng, CFE Topp, Mohamed Abdalla, Liyin L. Liang, Val Snow

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)
71 Downloads (Pure)


Measurements of nitrous oxide (N2O) emissions from agriculture are essential for understanding the complex soil-crop-climate processes, but there are practical and economic limits to the spatial and temporal extent over which measurements can be made. Therefore, N2O models have an important role to play. As models are comparatively cheap to run, they can be used to extrapolate field measurements to regional or national scale, simulate emissions over long time periods, or to run scenarios to compare mitigation practices. Process-based models can also be used as an aid to understanding the underlying processes as they can simulate feedbacks and interactions that can be difficult to distinguish in the field.
However, when applying models, it is important to understand the conceptual process differences in models, how conceptual understanding changed over time in various models, and the model requirements and limitations to ensure that the model is well suited to the purpose of the investigation and the type of system being simulated. The aim of this paper is to give the reader a high level overview of some of the important issues that should be considered when modelling. This includes conceptual understanding of widely used models, common modelling techniques such as calibration/validation, assessing model fit, sensitivity analysis and uncertainty assessment. We also review examples of N2O modelling for different purposes and describe three commonly used process-based N2O models (APSIM, DayCent, and DNDC).
Original languageEnglish
Pages (from-to)1168-1185
Number of pages18
JournalJournal of Environmental Quality
Issue number5
Early online date30 Jun 2020
Publication statusPrint publication - Sept 2020


  • Process-based
  • Empirical
  • Uncertainty
  • Goodness-of-fit
  • Sensitivity analysis
  • Nitrous Oxide/analysis
  • Soil
  • Agriculture


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