Biofuel feedstock optimization considering different land cover scenarios and watershed impacts
With an increased demand for renewable energy production, especially the conversion of biomass to biofuels, perennial grasses are gaining interest as a renewable source of biofuel feedstocks. Identifying the trade-offs between bioenergy crop cultivation and nutrient runoff, erosion, and water requirements will be important as the demand for these crops continues to grow. The primary objective of this study is develop an integrated optimal control model that estimates the potential effects on water quality and demand and soil erosion from cultivating switchgrass and other perennial grasses instead of conventional crops at the watershed scale. The Soil and Water Assessment Tool is used to model these land use changes. In this research, we developed an optimization method based on genetic algorithms to evaluate different land cover change scenarios and their effect at the watershed level by coupling the SWAT model with a multi-objective genetic algorithm, that takes into consideration the minimization of nutrient loading, sediment yield due to erosion at the watershed outlet, the effects on regional water resources, while maximizing biomass production. The optimal control model will help further the understanding of the environmental impacts of cultivating biofuel feedstocks and is intended to aid policy makers and stakeholders when making decisions to increase feedstock production.
Vance, Rodney Wayne, "Biofuel feedstock optimization considering different land cover scenarios and watershed impacts" (2014). ETD Collection for University of Texas, El Paso. AAI3682498.