Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment

Xing, H; Wang, E; Smith, CJ; Rolston, D; Yu, Q

Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment

Xing, H

Wang, E Smith, CJ Rolston, D Yu, Q

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Publication Type:: Journal Article
Citation:: Geoderma, 2011, 167-168 pp. 328 - 339
Issue Date:: 2011-11-01

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Field	Value	Language
dc.contributor.author	Xing, H https://orcid.org/0000-0001-6733-162X	en_US
dc.contributor.author	Wang, E	en_US
dc.contributor.author	Smith, CJ	en_US
dc.contributor.author	Rolston, D	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.date.issued	2011-11-01	en_US
dc.identifier.citation	Geoderma, 2011, 167-168 pp. 328 - 339	en_US
dc.identifier.issn	0016-7061	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18211
dc.description.abstract	Nitrous oxide (N2O), one of the primary green house gases (GHG), is an important contributor to the radiative forcing and chemistry of the atmosphere. Nitrous oxide emissions from soil are mainly due to denitrification. In this paper, we test sub-modules in the APSIM and DAYCENT models to simulate denitrification. The models were tested by comparison of predicted and measured N2O emission from an incubation experiment using 8.2 L soil cores. The N gas sub-modules in DAYCENT were based on the leaky pipe metaphor, that is, total N gas emissions are proportional to N cycling and gas diffusivity in the soil determines the relative amounts of N gas species emitted. The same approach was added to APSIM to enable simulation of N2O emission. The soil monoliths were irrigated three times during a two-week period and set on tension tables to control the suction at the base of each core. The results show that APSIM underestimates denitrification, whereas DAYCENT better predicted N2O emission from denitrification. In contrast, predictions of CO2 emissions were better from APSIM than DAYCENT. Modification to the temperature response for denitrification in APSIM improved the simulation significantly. The use of multiple soil layers in the simulations improved predictions, especially at low soil moisture content. Under these conditions, the layered approach better captures the impact of soil moisture distribution. Reducing the time step to hourly improve the prediction of N2O peaks and the daily total emissions, but there were still temporal mismatches between simulated and observed values. The denitrification algorithms in DAYCENT, combined with APSIM simulated CO2, together with an hourly time step and a layered approach, produced the best results. These results highlight the need for improvement to the APSIM denitrification sub-model. © 2011.	en_US
dc.relation.ispartof	Geoderma	en_US
dc.relation.isbasedon	10.1016/j.geoderma.2011.07.003	en_US
dc.subject.classification	Agronomy & Agriculture	en_US
dc.title	Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment	en_US
dc.type	Journal Article
utslib.citation.volume	167-168	en_US
utslib.for	0602 Ecology	en_US
utslib.for	0703 Crop and Pasture Production	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
utslib.for	07 Agricultural and Veterinary Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	167-168	en_US

Abstract:

Nitrous oxide (N2O), one of the primary green house gases (GHG), is an important contributor to the radiative forcing and chemistry of the atmosphere. Nitrous oxide emissions from soil are mainly due to denitrification. In this paper, we test sub-modules in the APSIM and DAYCENT models to simulate denitrification. The models were tested by comparison of predicted and measured N2O emission from an incubation experiment using 8.2 L soil cores. The N gas sub-modules in DAYCENT were based on the leaky pipe metaphor, that is, total N gas emissions are proportional to N cycling and gas diffusivity in the soil determines the relative amounts of N gas species emitted. The same approach was added to APSIM to enable simulation of N2O emission. The soil monoliths were irrigated three times during a two-week period and set on tension tables to control the suction at the base of each core. The results show that APSIM underestimates denitrification, whereas DAYCENT better predicted N2O emission from denitrification. In contrast, predictions of CO2 emissions were better from APSIM than DAYCENT. Modification to the temperature response for denitrification in APSIM improved the simulation significantly. The use of multiple soil layers in the simulations improved predictions, especially at low soil moisture content. Under these conditions, the layered approach better captures the impact of soil moisture distribution. Reducing the time step to hourly improve the prediction of N2O peaks and the daily total emissions, but there were still temporal mismatches between simulated and observed values. The denitrification algorithms in DAYCENT, combined with APSIM simulated CO2, together with an hourly time step and a layered approach, produced the best results. These results highlight the need for improvement to the APSIM denitrification sub-model. © 2011.

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