机构地区:[1]UCD School of Biology & Environmental Science and UCD Earth Institute, University College Dublin, Dublin, Ireland [2]Institute of Biological & Environmental Sciences, University of Aberdeen, Scotland, UK [3]Teagasc Environment Research Centre, Johnstown Castle, Wexford, Ireland [4]Department of Plant Ecology, Justus-Liebig-University Giessen, Giessen, Germany
出 处:《Agricultural Sciences》2016年第8期503-520,共19页农业科学(英文)
摘 要:Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake weGlobally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we
关 键 词:Greenhouse Gases Arable Lands Input Parameters Process-Based Models IRELAND
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