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 n...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.展开更多
基金This work was funded by the DOE Great Lakes Bioenergy Research Center(DOE BER Office of Science DE-FC02-07ER64494,DOE BER Office of Science KP1601050,DOE EERE OBP 20469-19145)the NASA New Investigator Award(NNH13ZDA001N)+1 种基金Terrestrial Ecology Program(NNH12AU03I and NNX17AE66G)NSF INFEWS(1639327).
文摘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.