Open AccessEnhancing the soil and water assessment tool model for simulating N 2 O emissions of three agricultural systems
Author(s) -
Yang Qichun,
Zhang Xuesong,
Abraha Michael,
Del Grosso Stephen,
Robertson G. P.,
Chen Jiquan
Publication year - 2017
Publication title -
ecosystem health and sustainability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.956
H-Index - 21
ISSN - 2332-8878
DOI - 10.1002/ehs2.1259
Subject(s) - soil and water assessment tool , environmental science , greenhouse gas , watershed , agriculture , swat model , fertilizer , cropping , hydrology (agriculture) , cropping system , agronomy , drainage basin , ecology , streamflow , engineering , geography , cartography , geotechnical engineering , machine learning , computer science , biology
Nitrous oxide (N 2 O) is a potent greenhouse gas (GHG) contributing to global warming, with the agriculture sector as the major source of anthropogenic N 2 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 N 2 O emissions to improve assessment of environmental impacts of cropping practices. Here, we integrated the DayCent model's N 2 O emission algorithms with the existing widely tested crop growth, hydrology, and nitrogen cycling algorithms in SWAT and evaluated this new tool for simulating N 2 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 N 2 O emissions across the three sites, indicating the usefulness of the new tool (SWAT‐N 2 O) to estimate long‐term N 2 O emissions of diverse cropping systems. Notably, parameter calibration can significantly improve model simulations of seasonality of N 2 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 N 2 O emissions, highlighting the importance of optimizing crop management under a changing climate in order to achieve agricultural sustainability goals.