Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
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DOI：
10.1029/2019jg005261
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发表时间：
2020-01-01
影响因子：
3.7
通讯作者：
Snow, Val
中科院分区：
文献类型：
--
作者：
Fuchs, Kathrin;Merbold, Lutz;Snow, Val
基于过程的模型有助于评估不断变化的管理做法和气候对草地等农业系统的产量和温室气体排放的影响。它们可用于使用第三级方法构建国家温室气体清单。然而，一氧化二氮(N2O)通量的准确模拟仍然具有挑战性。模型受到我们对土壤-植物-微生物相互作用的理解以及测量输入参数的不确定性对模拟输出的影响的限制。为了提高模型的性能，需要针对现场测量进行彻底的评估。在瑞士的田间试验中，获得了两种管理措施(典型施肥与增施三叶草和不施肥)下N2O排放的实验数据。我们用三个常用的生物地球化学模型(两个变种中的DayCent，两个变种中的PaSim，两个变种中的APSIM)对四年的数据进行了多模型评估。在年时间尺度上，DayCent模型对N-2O通量的模拟精度最高，而APSIM对日N2O通量的模拟精度最高。与使用政府间气候变化专门委员会(IPCC-Swiss)衍生的瑞士农业温室气体清单方法(IPCC-Swiss)估计的年通量相比，多模型集合平均减少了41%的估计年通量误差，但个别模型在系统上并不比IPCC-Swiss更准确。模型集合高估了以三叶草为基础的治疗的N2O缓解效果(测量：39-45%；集合：52-57%)，但比IPCC-Swiss(IPCC-Swiss：72-81%)更准确。这些结果表明，多模式集合对于估计气候和管理对N2O排放的影响是有价值的。
Process-based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N2O) fluxes remain challenging. Models are limited by our understanding of soil-plant-microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N2O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N-2 O fluxes on annual timescales, while APSIMwas most accurate for daily N2O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)-derived method for the Swiss agricultural GHG inventory (IPCC-Swiss), but individual models were not systematically more accurate than IPCC-Swiss. The model ensemble overestimated the N2O mitigation effect of the clover-based treatment (measured: 39-45%; ensemble: 52-57%) but was more accurate than IPCC-Swiss (IPCC-Swiss: 72-81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N2O emissions.