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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Soil Management and Sugarbeet Research » Research » Publications at this Location » Publication #354457
Title: Enhancing the soil and water assessment tool model for simulating N2O emissions of three agricultural systems

Author
item YANG, QICHUN - Global Change Research Institute
item ZHANG, XUESONG - Global Change Research Institute
item ABRAHA, MICHAEL - Michigan State University
item Del Grosso, Stephen - Steve
item ROBERTSON, G - Michigan State University
item CHEN, JIQUAN - Michigan State University

Submitted to: Ecosystem Health and Sustainability
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/3/2017
Publication Date: 2/22/2017
Citation: Yang, Q., Zhang, X., Abraha, M., Del Grosso, S.J., Robertson, G.P., Chen, J. 2017. Enhancing the soil and water assessment tool model for simulating N2O emissions of three agricultural systems. Ecosystem Health and Sustainability. (2):e01259. 10.1002/ehs2.1259.
DOI: https://doi.org/10.1002/ehs2.1259

Interpretive Summary: Nitrous oxide is a potent greenhouse gas (GHG) contributing to global warming, with the agriculture sector as the major source of human caused emissions, mostly 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 represent emissions to improve assessment of environmental impacts of cropping practices. Here, we integrated the DayCent model's nitrous oxide emission algorithms with the existing widely tested crop growth, hydrology, and nitrogen cycling algorithms in SWAT and evaluated this new tool for simulating emissions in three agricultural systems (a continuous corn site, a switchgrass site, and a smooth brome grass site) located at the Great Lakes Bioenergy Research Center fields in southwestern Michigan. These three systems represent different levels of management intensity, with corn, switchgrass, and smooth brome grass receiving high, medium, and zero fertilizer application, respectively. Results indicate that the enhanced SWAT model with default parameterization reproduced well the magnitudes of nitrous oxide emissions across the three sites, indicating the usefulness of the new tool to estimate long-term emissions of diverse cropping systems. Further sensitivity analysis indicates that climate change (changes in precipitation and temperature) influences nitrous oxide emissions, highlighting the importance of optimizing crop management under a changing climate to achieve agricultural sustainability goals.

Technical Abstract: 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.