Enhancing the soil and water assessment tool model for simulating N2O emissions of three agricultural systems

被引:27
作者
Yang, Qichun [1 ]
Zhang, Xuesong [1 ,2 ]
Abraha, Michael [2 ,3 ]
Del Grosso, Stephen [4 ]
Robertson, G. P. [2 ,3 ,5 ]
Chen, Jiquan [2 ,6 ]
机构
[1] Pacific Northwest Natl Lab, Joint Global Change Res Inst, College Pk, MD 20740 USA
[2] Michigan State Univ, Great Lakes Bioenergy Res Ctr, E Lansing, MI 48824 USA
[3] Michigan State Univ, WK Kellogg Biol Stn, Hickory Corners, MI 49060 USA
[4] ARS, USDA, Ft Collins, CO 80526 USA
[5] Michigan State Univ, Dept Plant Soil & Microbial Sci, E Lansing, MI 48824 USA
[6] Michigan State Univ, Dept Geog Environm & Spatial Sci, E Lansing, MI 48824 USA
基金
美国国家科学基金会;
关键词
NITROUS-OXIDE EMISSIONS; DENITRIFICATION; CARBON; SWITCHGRASS; TEMPERATURE; MANAGEMENT; CROPLAND; IMPACTS; SWAT; TILLAGE;
D O I
10.1002/ehs2.1259
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Nitrous oxide (N2O) is a potent greenhouse gas (GHG) contributing to global warming, with the agriculture sector as the major source of anthropogenic N2O emissions due to excessive fertilizer use. There is an urgent need to enhance regional-/watershed-scale models, such as Soil and Water Assessment Tool (SWAT), to credibly simulate N2O emissions to improve assessment of environmental impacts of cropping practices. Here, we integrated the DayCent model's N2O emission algorithms with the existing widely tested crop growth, hydrology, and nitrogen cycling algorithms in SWAT and evaluated this new tool for simulating N2O emissions in three agricultural systems (i.e., a continuous corn site, a switchgrass site, and a smooth brome grass site which was used as a reference site) located at the Great Lakes Bioenergy Research Center (GLBRC) scale-up fields in southwestern Michigan. These three systems represent different levels of management intensity, with corn, switchgrass, and smooth brome grass (reference site) receiving high, medium, and zero fertilizer application, respectively. Results indicate that the enhanced SWAT model with default parameterization reproduced well the relative magnitudes of N2O emissions across the three sites, indicating the usefulness of the new tool (SWAT-N2O) to estimate long-term N2O emissions of diverse cropping systems. Notably, parameter calibration can significantly improve model simulations of seasonality of N2O fluxes, and explained up to 22.5%-49.7% of the variability in field observations. Further sensitivity analysis indicates that climate change (e.g., changes in precipitation and temperature) influences N2O emissions, highlighting the importance of optimizing crop management under a changing climate in order to achieve agricultural sustainability goals.
引用
收藏
页数:12
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