Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
Résumé
Process‐based models are useful for assessing the impact of changing management practicesand 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, accuratesimulations of nitrous oxide (N2O)fluxes remain challenging. Models are limited by our understanding ofsoil‐plant‐microbe interactions and the impact of uncertainty in measured input parameters on simulatedoutputs. 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 versusincreased clover and no fertilization) were acquired in a Swissfield experiment. We conducted a multimodelevaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM intwo variants) comparing four years of data. DayCent was the most accurate model for simulating N2Ofluxeson annual timescales, while APSIM was most accurate for daily N2Ofluxes. The multimodel ensemble averagereduced the error in estimated annualfluxes by 41% compared to an estimate using the IntergovernmentalPanel 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 ensembleoverestimated 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 multimodelensembles are valuable for estimating the impact of climate and management on N2O emissions.
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