Process-Based Modeling System Supporting Carbon Management Decisions and Reporting in U.S. Agricultural Lands
Stephen
M
Ogle, Colorado State University, ogle@nrel.colostate.edu
(Presenting)
Keith
Paustian, Colorado State University, keithp@nrel.colostate.edu
Chris
Potter, NASA Ames Research Center, chris.potter@nasa.gov
Richard
T
Conant, Colorado State University, conant@nrel.colostate.edu
Steven
Klooster, NASA Ames Research Center, sklooster@gaia.arc.nasa.gov
F
Jay
Breidt, Colorado State University, jbreidt@stat.colostate
Estimation tools are needed for decision-support and reporting associated with carbon management in US agricultural lands. Our objective has been to develop a process-based modeling framework to estimate carbon stock changes in croplands, and with a focus on the NACP Mid-Continent Intensive Campaign Region. Our approach integrates NASA-CASA production algorithms with soil process algorithms from Century, and estimates change in plant and soil C stock changes using 250m MODIS-EVI data, DAYMET weather and soil characteristics, in addition to soil management practices, such as tillage. Uncertainties are evaluated using an empirically-based approach with an independent set of measurement data. Moreover, the model framework is designed to project carbon trends, which can be driven with historical or projected climate patterns, along with statistical functions to predict EVI curves and account for their associated uncertainty in the process. After complete implementation, the model will support policy assessments and reporting of agricultural carbon stock changes to the UN Framework Convention on Climate Change. In addition, a web-based version will be available for farmers to assess carbon trends in their fields by simulating historical trends and projecting future scenarios according to management options.
NASA Carbon Cycle & Ecosystems Active Awards Represented by this Poster: