Author
Tatarko, John | |
NELSON, R - Enersol Resources, Inc | |
Ascough Ii, James |
Submitted to: World Wide Web
Publication Type: Other Publication Acceptance Date: 9/12/2014 Publication Date: 2/19/2015 Citation: Tatarko, J., Nelson, R.G., Ahuja, L.R. 2015. Dataset: Soil erosion and organic matter for central Great Plains cropping systems under residue removal. National Ag Library. http://dx.doi.org/10.15482/USDA.ADC/1167058. Interpretive Summary: The diversity of land, climate, and potential feedstocks within the United States Central Great Plains (CGP) requires production systems that preserve the soil, water, and air resource while providing optimal resource use to maintain or enhance localized soil and environmental quality. This study examined average annual changes in soil erosion from rainfall and wind forces and trends in soil organic matter as a function of commodity and/or bioenergy-based crop rotations, yield variations, and different field management practices, including residue removal across all broadly grouped soils in select areas of the CGP. Soil erosion and soil organic matter were analyzed on individual soil groups using the RUSLE2 water erosion model and the WEPS wind erosion model. Results are arranged by Crop Management Zones and year simulated yield. Technical Abstract: The diversity of geo-climatic land bases and potential feedstocks within the United States Central Great Plains (CGP) requires sustainable production that provides optimal resource utilization while maintaining or enhancing localized soil and environmental quality as much as possible. This study examined average annual changes in soil erosion from rainfall and wind forces and trends in soil organic carbon (SOC) as a function of commodity and/or bioenergy-based crop rotations, yield variations, and different field management practices, including residue removal across all land capability class (LCC) I-VIII soils in select areas of the CGP. Soil erosion and SOC (proxied by a soil conditioning index, or SCI) were analyzed on individual soil map unit components using the RUSLE2 and WEPS models. Results are arranged by Crop Management Zones and year simulated yield. |