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Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
Author(s) -
Fuchs Kathrin,
Merbold Lutz,
Buchmann Nina,
Bretscher Daniel,
Brilli Lorenzo,
Fitton Nuala,
Topp Cairistiona F. E.,
Klumpp Katja,
Lieffering Mark,
Martin Raphaël,
Newton Paul C. D.,
Rees Robert M.,
Rolinski Susanne,
Smith Pete,
Snow Val
Publication year - 2020
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2019jg005261
Subject(s) - greenhouse gas , environmental science , nitrous oxide , grassland , climate change , biogeochemical cycle , agriculture , atmospheric sciences , meteorology , agronomy , ecology , geography , geology , biology
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 (N 2 O) 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 N 2 O 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 APSIM was most accurate for daily N 2 O 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 N 2 O 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 N 2 O emissions.