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dc.contributor.author
Fuchs, Kathrin
dc.contributor.author
Merbold, Lutz
dc.contributor.author
Buchmann, Nina
dc.contributor.author
Bretscher, Daniel
dc.contributor.author
Brilli, Lorenzo
dc.contributor.author
Fitton, Nuala
dc.contributor.author
Topp, Cairistiona F. E.
dc.contributor.author
Klumpp, Katja
dc.contributor.author
Lieffering, Mark
dc.contributor.author
Martin, Raphaël
dc.contributor.author
Newton, Paul C. D.
dc.contributor.author
Rees, Robert M.
dc.contributor.author
Rolinski, Susanne
dc.contributor.author
Smith, Pete
dc.contributor.author
Snow, Val
dc.date.accessioned
2020-02-26T09:55:49Z
dc.date.available
2020-02-25T15:44:19Z
dc.date.available
2020-02-26T09:55:49Z
dc.date.issued
2020-01
dc.identifier.issn
0148-0227
dc.identifier.issn
2169-8953
dc.identifier.issn
2169-8961
dc.identifier.other
10.1029/2019jg005261
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/401680
dc.identifier.doi
10.3929/ethz-b-000401680
dc.description.abstract
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 N2O fluxes on annual timescales, while APSIM was 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.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
American Geophysical Union
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.title
Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 4.0 International
dc.date.published
2019-12-18
ethz.journal.title
Journal of Geophysical Research. Biogeosciences
ethz.journal.volume
125
en_US
ethz.journal.issue
1
en_US
ethz.journal.abbreviated
J. geophys. res. Biogeosciences
ethz.pages.start
e2019JG005261
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
Robust models for assessing the effectiveness of technologies and managements to reduce N2O emissions from grazed pastures (Models4Pastures)
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Washington, DC
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
en_US
ethz.grant.agreementno
154245
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
FACCE-JPI
ethz.date.deposited
2020-02-25T15:44:28Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-02-26T09:56:01Z
ethz.rosetta.lastUpdated
2021-02-15T08:17:35Z
ethz.rosetta.versionExported
true
ethz.COinS
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