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

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Show simple item record Xing, Hongtao en_US Wang, Enli en_US Smith, Chris en_US Rolston, Denis en_US Yu, Qiang en_US
dc.contributor.editor en_US 2012-10-12T03:33:37Z 2012-10-12T03:33:37Z 2011 en_US
dc.identifier 2011000008 en_US
dc.identifier.citation Xing Hongtao et al. 2011, 'Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment', Elsevier Inc., vol. 167-168, pp. 328-339. en_US
dc.identifier.issn 0016-7061 en_US
dc.identifier.other C1 en_US
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. en_US
dc.language English en_US
dc.publisher Elsevier Inc. en_US
dc.relation.isbasedon en_US
dc.title Modelling nitrous oxide and carbon dioxide emission from soil in an incubation experiment en_US
dc.parent Geoderma en_US
dc.journal.volume 167-168 en_US
dc.journal.number en_US
dc.publocation Netherlands en_US
dc.identifier.startpage 328 en_US
dc.identifier.endpage 339 en_US SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 070300 en_US
dc.personcode 0000072172 en_US
dc.personcode 0000062390 en_US
dc.personcode 0000050029 en_US
dc.personcode 0000072173 en_US
dc.personcode 107001 en_US
dc.percentage 50 en_US Crop and Pasture Production en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US
dc.location.activity en_US
dc.description.keywords Nitrous oxide emission; APSIM; DAYCENT; Decomposition; CO2 flux en_US
dc.staffid 107001 en_US

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