Location: Soil Management and Sugarbeet Research
Project Number: 3012-11000-011-06-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Jul 1, 2014
End Date: May 31, 2019
To assist ARS in producing future U.S. Agriculture and Forestry Greenhouse Gas Inventories and assess the impacts of different crop management practices at the national scale. These efforts will facilitate collaborative efforts between ARS and CSU to continue simulation model development, testing, and refinement of input data to predict the impacts of changing climate and management on greenhouse gas (GHG) emissions, crop yields and soil carbon content.
Major products so far include the 32d edition of the USDA GHG inventory published in 2011 the web accessible GRACEnet/REAP data discovery, retrieval and management system released in 2013. Major improvements in the 3rd edition of the inventory include using annual survey data from the USDA National Resources Inventory (NRI) for grazed systems, making N additions to soils from grazing animals consistent with N excretion data, and improving estimates of NO3 leaching, and more complete calculations for uncertainty calculations. Model improvements, tests, and applications used to generate data for the inventory have been reported in 10 journal and several presentations at meetings and symposia. The DAYCENT model was used to perform life cycle analysis for different perennial and annual biofuel cropping systems and high resolution NRI data have been implemented for future GHG inventory simulations. In addition to producing and improving future editions of the USDA GHG Inventory, general goals for the next 5 years include evaluating additional biofuel cropping systems (e.g., energy cane), developing software to automate model simulations and comparisons of outputs with measurements, and further investigating how changes in land use and climate impact crop yields and GHG fluxes. Production and improvement of the U.S. Agriculture and Forestry Greenhouse Gas Inventory requires applying and improving the models used to calculate emissions and their associated uncertainty ranges. Use of more refined model input data, further comparison of model outputs with field measurements from the GRACEnet database and measurements from South America and Australia, and increased computing capacity lead to more accurate national scale estimates and better characterization of the regional and temporal patterns of emissions. ARS will interact with CSU to incorporate programming expertise, high capacity computing clusters, and data collection into the inventory analyses. CSU will assist ARS in evaluating the impacts and feasibility of different cropping systems, including biofuels by implementing and testing the ability of models to represent the impacts of improved N management technologies and perform regional analysis to identify local best management practices.