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

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• 作者：Hongtao Xing^a ; ^b ; Enli Wang^b ; ^{Enli.Wang@csiro.au} ; Chris J. Smith^b ; Denis Rolston^c ; Qiang Yu^a ; ^d
• 关键词：Nitrous oxide emission ; APSIM ; DAYCENT ; Decomposition ; CO2 flux
• 刊名：Geoderma
• 出版年：2011
• 出版时间：November, 2011
• 年：2011
• 卷：167-168
• 期：Complete
• 页码：328-339
• 全文大小：988 K

文摘

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.