Of the four most important atmospheric greenhouse gasses (GHG) enriched through human activities, only nitrous oxide (N₂O) emissions are due primarily to agriculture. However, reductions in the application of synthetic N fertilizers could have significant negative consequences for a growing world population given the crucial role that these fertilizers have played in cereal yield increases since WWII. Increasing N use efficiency (NUE) through precision management of agricultural N in space and time will therefore play a central role in the reduction of agricultural N₂O emissions. Precision N management requires a greater understanding of the spatio-temporal variability of factors supporting N management decisions such as crop yield, water and N availability, utilization and losses.

We present an overview of a large, collaborative, multi-disciplinary project designed to both improve our basic understanding of nitrogen (N), carbon (C) and water (H₂O) spatio-temporal dynamics for wheat-based cropping systems on complex landscapes, and develop management tools to optimize water- and nitrogen-use efficiency for these systems and landscapes. Major components of this project include: (a) cropping systems experiments addressing nitrogen application rate and seeding density for different landscape positions; (b) GHG flux experiments and monitoring; (c) soil microbial genetics and stable isotope analyses to elucidate biochemical pathways for N₂O production; (d) proximal soil sensing for construction of detailed soil maps; (e) LiDAR and optical remote sensing for crop growth monitoring; (f) hydrologic experiments, monitoring, and modeling; (g) refining the CropSyst simulation model to estimate biophysical processes and GHG emissions under a variety of management and climatic scenarios; and (h) linking farm-scale enterprise budgets to simulation modeling in order to provide growers with economically viable site-specific climate-friendly farming guidance.