Submitted to: American Society of Agronomy Meetings
Publication Type: Abstract only
Publication Acceptance Date: 5/15/2008
Publication Date: 10/5/2008
Citation: Doraiswamy, P.C., Akhmedov, B., Causarano, H., Daughtry, C.S., McCarty, G.W., Serbin, G. 2008. Modeling regional soil carbon sequestration rates across the U.S. Corn Belt [abstract]. American Society of Agronomy Meetings. 2008 CDROM. Interpretive Summary:
Technical Abstract: Soil organic carbon (SOC) sequestration can potentially mitigate the increase in atmospheric CO2, and reduce global warming in the short term. Land-use and soil management (including tillage and crop rotations) affect SOC balance and can be significant for the improvement of soil quality and productivity, and to reduce greenhouse gas emissions. We used the Environmental Policy Integrated Climate (EPIC) model to study the long term impact of soil and crop management practices on SOC sequestration across Iowa, Illinois, and Indiana. The EPIC model used spatially defined land-use, soil, and climate data. Cropland areas were identified with land cover classification from Landsat imagery. Soil properties were derived from SSURGO and STATSGO databases, and daily weather variables were obtained from meteorological stations within the study area. Non-spatial ancillary data such as fertilizer rates, tillage practices, and residue management data were currently available only at the state level. The potential use of visible/ near-infrared satellite imagery at multi-resolutions for mapping soil tillage and surface residue levels was investigated as part of this research. Supervised classification technique was applied to map tillage practices using QuickBird, SPOT, and AWiFS imagery. Simulations of current SOC stocks in the top 20 cm varied considerably (11–157 Mg C ha-1) and were largely controlled by tillage practices, clay content, slope, and elevation. SOC sequestration rate estimates for the period 2008–2018 varied between -0.28 and 0.52 Mg C ha-1 yr-1 depending on topography. The overall accuracy of fall tillage classification for the SPOT scene was greater that 90%. In conclusion, our approach proved valid for evaluating impacts of management practices but further studies are needed for mapping tillage practices.