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Title: THE USE OF TERRAIN ANALYSIS AND CESIUM-137 DATA IN THE HYDROPEDOLOGIC MODELING OF SOIL ORGANIC CARBON

Author
item Venteris, Erik
item McCarty, Gregory
item Ritchie, Jerry

Submitted to: American Society of Agronomy Meetings
Publication Type: Abstract Only
Publication Acceptance Date: 10/1/2003
Publication Date: 11/4/2003
Citation: Venteris, E.R., McCarty, G.W., Ritchie, J.C. 2003. The use of terrain analysis and cesium-137 data in the hydropedologic modeling of soil organic carbon. Soil Science Society of America Meetings (S05-venteris86488-poster).

Interpretive Summary:

Technical Abstract: Soil organic carbon (SOC) distribution at the field scale is controlled by vegetative production, microbial oxidation, and transport by tillage and water and wind. Such processes are partially related to topography, so digital elevation models (DEMs) can potentially be used to make spatial models. Intense soil sampling was conducted in Ames, Iowa (tills with prairie potholes, mollisols), Coshocton, Ohio (residual/colluvial ultisols and alfisols), and Beltsville, Maryland (coastal plain ultisols). SOC and radioactive fallout 137Cs were measured. Regressions were calculated between carbon, 137Cs, and terrain attributes calculated from high-resolution (2-5m) DEMs. Attributes include indexes commonly used for soil wetness and erosion modeling (stream power, 2-D slope-length factor). In the Iowa, SOC was highly correlated (r2=0.8) to 137Cs and the wetness index (r2=0.7). In Ohio, results contrasted with management practice and topography. Steep watersheds and those with extensive tillage showed the highest correlation between 137Cs and SOC. Carbon was weakly predictable (r2=0.2-0.6) and erosion was not predictable from terrain parameters. Similar results were obtained in Maryland, where SOC was not strongly correlated to 137Cs or topographic parameters (r2~0.30). Simple terrain models work well on the glacial soils of central Iowa, consistent with past studies. However, topography alone is insufficient for carbon and erosion prediction for the Ohio and Maryland sites. Carbon and erosion models based on RUSLE and stream power are unlikely to be useful at the field scale for these locations.