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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #273395
Title: Impacts of biofuel expansion on soil quality and carbon dynamics in a central Iowa watershed

Author
item DAUGHTRY, CRAIG
item BEESON, PETER
item MILAK, S - SCIENCE SYSTEMS, INC.
item AKHMEDOV, B - SCIENCE SYSTEMS, INC.
item HUNT JR, EARLE
item SADEGHI, ALI
item TOMER, MARK

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/4/2011
Publication Date: 10/5/2011
Citation: Daughtry, C.S., Beeson, P.C., Milak, S., Akhmedov, B., Hunt, E.R., Sadeghi, A.M., Tomer, M.D. 2011. Impacts of biofuel expansion on soil quality and carbon dynamics in a central Iowa watershed [abstract]. NASA Carbon Cycle and Ecosystems Joint Science Workshop. 2011 CDROM.

Interpretive Summary:

Technical Abstract: Crop residues (plant litter) on the soil surface helps decrease soil erosion, increase water infiltration, increase soil organic matter, and improve soil quality. Thus, management of crop residues is an integral part of most conservation tillage systems. Crop residue cover is used to classify soil tillage intensity and assess the extent of conservation tillage practices. Removal of crop residue for feed or fuel reduces residue cover. Our objectives are 1) to evaluate the role of remote sensing for assessing soil tillage intensity and 2) to use process models for assessing the effects of crop management practices on soil and water quality as crop residue is removed for feed or fuel. The spectral properties of crop residues and soils were measured with ground-based spectroradiometers and airborne and satellite imaging spectrometers in crop production fields in MD, IN, and IA. Physically-based spectral indices that detect absorption features associated with cellulose and lignin were robust and required minimal surface reference data for mapping crop residue cover and soil tillage intensity across agricultural landscapes. Other biophysical characteristics of vegetation and soils, needed by the process models at field and watershed scales, can be derived directly or indirectly from remotely sensed data. Our initial test site was the South Fork watershed in central Iowa. Farmer surveys, surface reference data, and remotely sensed data provided spatially-explicit input data for the hydrologic and soil carbon models. Crop and soil management scenarios, including crop residue removal for biofuel, were evaluated using watershed- and field-scale models. The field-scale simulations demonstrated that relatively flat areas may be sustainable for removal of <80% corn residue and no-till management. This is not true for all geographic areas, soils, and slopes. An interconnected suite of models is required to adequately address the complex agronomic, environmental, and economic issues related to harvesting crop residues for biofuels.