Enhancing the soil and water assessment tool model for simulating N2O emissions of three agricultural systems. Issue 2 (22nd February 2017)

• Record Type: Journal Article
• Authors: Yang, Qichun; Zhang, Xuesong; Abraha, Michael; Del Grosso, Stephen; Robertson, G. P.; Chen, Jiquan
• Is Part Of: Ecosystem health and sustainability. Volume 3:Issue 2(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-02-22
• Subjects: agriculture -- climate change -- greenhouse gas -- sensitivity analysis; Ecosystem health -- Periodicals; Environmental health -- Periodicals; Environmental policy -- Periodicals; Environmental engineering -- Periodicals; Environmental ethics -- Periodicals; Ecosystem management -- Periodicals; Ecosystem management; Environmental engineering; Environmental ethics; Environmental health; Environmental policy; Periodicals; 577
• DOI: 10.1002/ehs2.1259
• Languages: English
• ISSNs: 2096-4129

Abstract

Abstract: Nitrous oxide (N2 O) is a potent greenhouse gas (GHG) contributing to global warming, with the agriculture sector as the major source of anthropogenic N2 O 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 N2 O emissions to improve assessment of environmental impacts of cropping practices. Here, we integrated the DayCent model's N2 O emission algorithms with the existing widely tested crop growth, hydrology, and nitrogen cycling algorithms in SWAT and evaluated this new tool for simulating N2 O 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 N2 O emissions across the three sites, indicating the usefulness of the new tool (SWAT‐N2 O) to estimate long‐term N2 O emissions of diverse cropping systems. Notably, parameter calibration can significantly improve model simulations of seasonality of N2 O 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 N2 O emissions, highlighting the importance of optimizing crop management under a changing climate in order to achieve agricultural sustainability goals.