2012 International Conference on Environmental Modelling and Software. Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial Meeting
Emerging cellulosic bioenergy markets can provide land managers with additional options for crop production decisions. For example, integrating dedicated bioenergy crops such as perennial grasses and short rotation woody species within the agricultural landscape can have positive impacts on several environmental processes including increased soil organic matter in degraded soils, reduced sediment and nutrient loading in watersheds, and lower green house gas fluxes. Implementing this type of diverse bioenergy production system to maximize the potential environmental benefits requires a detailed understanding of the many interwoven aspects of environmental landscapes. This paper presents a dynamic framework-based integrated modeling and data management strategy that can design sustainable bioenergy cropping systems within the existing row crop production landscape of the Midwestern U.S. Critical environmental processes— including soil erosion from wind and water, and soil organic matter changes—are quantified by this integrated model to determine sustainable removal rates of agricultural residues for bioenergy production at the sub-field scale. Seven land management options for a 59 ha Iowa field are examined using the integrated model. These include a baseline case of sustainable residue removal and various incorporations of rye cover cropping and switchgrass use in marginal land. Relative to the baseline metrics, the adoption of rye cover crops with sustainable residue removal increases the total biomass sustainably available for biofuel production by 289% and reduces soil loss by 42%. Combining rye cover crops while displacing less productive and at-risk areas of the field with switchgrass increases the sustainable biomass available by 436% and decreases soil loss by 64%.
Koch, Joshua; Muth, David J. Jr.; and Bryden, Kenneth M., "An Integrated Modeling and Data Management Strategy for Cellulosic Biomass Production Decisions" (2012). Ames Laboratory Conference Papers, Posters, and Presentations. 87.