A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands.
Wednesday, November 6, 2013: 2:55 PM
Tampa Convention Center, Room 37 and 38, Third Floor
Varaprasad Bandaru, Pacific Northwest National Lab., College Park, MD, Roberto C. Izaurralde, Battelle Pacific NW Lab., College Park, MD, Ritivik Sahajpal, Department of Geographical Sciences, University of Maryland, College Park, MD, India, Rasmus M Houborg, Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology, Kingdom of Saudi Arabia, Saudi Arabia and Zurita Milla, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.
