Manaaki Whenua Landcare Research, Riddet Rd., Palmerston North, 4442, New Zealand.
Information and Computational Sciences Group, The James Hutton Institute, Craigiebuckler, Aberdeen, AB158QH, UK.
J Environ Qual. 2020 Sep;49(5):1168-1185. doi: 10.1002/jeq2.20119. Epub 2020 Aug 27.
Measurements of nitrous oxide (N 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 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 O modeling for different purposes and describe three commonly used process-based N O models (APSIM, DayCent, and DNDC).
测量农业一氧化二氮(N2O)排放对于理解复杂的土壤-作物-气候过程至关重要,但在可以进行测量的空间和时间范围上存在实际和经济限制。因此,N2O 模型具有重要的作用。由于模型的运行成本相对较低,因此可以将田间测量值外推到区域或国家尺度,模拟长时间跨度的排放,或运行情景以比较缓解措施。基于过程的模型也可以用作理解基本过程的辅助工具,因为它们可以模拟在现场难以区分的反馈和相互作用。然而,在应用模型时,重要的是要了解模型中的概念过程差异,不同模型中概念理解随时间的变化,以及模型的要求和限制,以确保模型非常适合调查目的和模拟的系统类型。本文的目的是为读者提供一个关于在建模时应考虑的一些重要问题的高级概述。这包括对广泛使用的模型的概念理解、常见的建模技术(如校准和验证)、评估模型拟合度、敏感性分析和不确定性评估。我们还回顾了不同目的的 N2O 建模示例,并描述了三个常用的基于过程的 N2O 模型(APSIM、DayCent 和 DNDC)。