Global Research Alliance N2O chamber methodology guidelines: Summary of modeling approaches Article Swipe
Donna Giltrap
,
Jagadeesh Yeluripati
,
Pete Smith
,
Nuala Fitton
,
Ward Smith
,
Brian Grant
,
Christopher D. Dorich
,
Jia Deng
,
K. Topp
,
Mohamed Abdalla
,
Lìyı̌n Liáng
,
Val Snow
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1002/jeq2.20119
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1002/jeq2.20119
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).
Related Topics
Concepts
Process (computing)
Conceptual model
Field (mathematics)
Calibration
Simulation modeling
Sensitivity (control systems)
Computer science
Process modeling
Environmental science
Mathematical model
Systems engineering
Management science
Engineering
Environmental engineering
Mathematics
Process optimization
Database
Electronic engineering
Operating system
Pure mathematics
Mathematical economics
Statistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/jeq2.20119
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jeq2.20119
- OA Status
- hybrid
- Cited By
- 29
- References
- 97
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3040385605
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3040385605Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/jeq2.20119Digital Object Identifier
- Title
-
Global Research Alliance N2O chamber methodology guidelines: Summary of modeling approachesWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-07-01Full publication date if available
- Authors
-
Donna Giltrap, Jagadeesh Yeluripati, Pete Smith, Nuala Fitton, Ward Smith, Brian Grant, Christopher D. Dorich, Jia Deng, K. Topp, Mohamed Abdalla, Lìyı̌n Liáng, Val SnowList of authors in order
- Landing page
-
https://doi.org/10.1002/jeq2.20119Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jeq2.20119Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jeq2.20119Direct OA link when available
- Concepts
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Process (computing), Conceptual model, Field (mathematics), Calibration, Simulation modeling, Sensitivity (control systems), Computer science, Process modeling, Environmental science, Mathematical model, Systems engineering, Management science, Engineering, Environmental engineering, Mathematics, Process optimization, Database, Electronic engineering, Operating system, Pure mathematics, Mathematical economics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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29Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 7, 2023: 4, 2022: 5, 2021: 4Per-year citation counts (last 5 years)
- References (count)
-
97Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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