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Global Research Alliance N 2 O chamber methodology guidelines: Summary of modeling approaches
Author(s) -
Giltrap Donna,
Yeluripati Jagadeesh,
Smith Pete,
Fitton Nuala,
Smith Ward,
Grant Brian,
Dorich Christopher D.,
Deng Jia,
Topp Cairistiona FE,
Abdalla Mohamed,
Liáng Lìyǐn L.,
Snow Val
Publication year - 2020
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.1002/jeq2.20119
Subject(s) - process (computing) , field (mathematics) , conceptual model , calibration , sensitivity (control systems) , computer science , simulation modeling , process modeling , environmental science , mathematical model , systems engineering , management science , engineering , environmental engineering , mathematics , statistics , process optimization , mathematical economics , database , electronic engineering , pure mathematics , operating system
Measurements of nitrous oxide (N 2 O) 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, N 2 O 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 scales, to 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 modeling. This includes conceptual understanding of widely used models, common modeling techniques such as calibration and validation, assessing model fit, sensitivity analysis, and uncertainty assessment. We also review examples of N 2 O modeling for different purposes and describe three commonly used process‐based N 2 O models (APSIM, DayCent, and DNDC).