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Title: Integrating the Epic Model with spatially defined land use, soil, weather and tillage data

Author
item Doraiswamy, Paul
item CAUSARANO, H - VISITING SCIENTIST
item BAKYT, A - SSAI
item Daughtry, Craig
item MILAK, SUSHIL - SSAI
item McCarty, Gregory
item Serbin, Guy

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/15/2008
Publication Date: 4/28/2008
Citation: Doraiswamy, P.C., Causarano, H.J., Bakyt, A., Daughtry, C.S., Milak, S., McCarty, G.W., Serbin, G. 2008. Integrating the Epic model with spatially defined land use, soil, weather and tillage data [abstract]. 2008 NASA Carbon cycle and Ecosystems Joint Science Workshop. 2008 CDROM.

Interpretive Summary:

Technical Abstract: Land-use and soil management (including tillage and crop rotations) affect soil organic carbon (SOC) balance and can be significant for the improvement of soil quality and productivity, and greenhouse gas emissions. The Environmental Policy Integrated Climate (EPIC) model was used to study the long term impact of soil and crop management practices on SOC sequestration in the U.S. Corn Belt. EPIC was integrated with 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. The potential use of visible/ near-infrared imagery at multi-resolutions was evaluated for mapping soil tillage and surface residue levels. The spectral angle mapping supervised classification technique was applied to map tillage practices using QuickBird, SPOT, and AWiFS imagery. Simulated 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 uncertainty of simulation results were calculated at ~28% for regional simulations, but it reduced to ~10% for site specific simulations. 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.