Optimal land use planning on selection and placement of energy crops for sustainable biofuel production

Cibin Raj, Purdue University

Abstract

Perennial grasses such as Miscanthus and switchgrass and crop residues have been identified as a potential long-term biofuel feedstock sources for the USA. However, the environmental impacts of bioenergy crop production need to be carefully evaluated such that effective sustainable production practices can be developed. Introduction of bioenergy crops to traditional commercial agriculture will require considerable land use and management changes, and may have long-term environmental impacts on hydrology and water quality. Some of these new land use and management scenarios may have detrimental environmental impacts, while some may be beneficial compared to the current land use/management practices. Environmental benefits of energy crop production can be increased by careful selection and placement of energy crops in the landscape in a manner that both biomass production and sustainability goals can be met. The overarching goal of this study was to estimate potential impacts of bioenergy crop production on watershed scale hydrology and water quality and to develop a multi-objective optimization framework for optimal selection and placement of energy crops at watershed scale for sustainable bioenergy production. Perennial grasses, Miscanthus and switchgrass, and crop residue from corn stover were considered as candidate bioenergy sources for the study watershed, Wildcat Creek watershed located in the Midwestern US. The distributed hydrological model SWAT (Soil and Water Assessment Tool) was used to simulate energy crop growth, hydrology and water quality. The model was parameterized and growth algorithms were improved to represent perennial crop growth and were validated using the field data collected at the Purdue University Water Quality Field Station located near the study watershed. The SWAT model vegetative filter strip (VFS) representation was also modified to represent energy crop growth in filter strip areas. These improvements also considered water and nutrients from source areas routed through VFS area. A multi-level spatial optimization framework (MLSOPT) was developed and used for watershed scale optimal section and placement of energy crops. The framework in combination with AMALGAM (Multi ALgorithm Genetically Adaptive Method) as the optimization algorithm and SWAT model as simulation model was used to develop optimal energy crop placement options for the watershed with various environmental tradeoffs as objective functions. The results indicated corn stover removal for bioenergy production can reduce stream flow, nitrate and mineral phosphorus loading and can increase sediment and organic nitrogen loading at the watershed outlet. The model results also indicated that the watershed response to stover removal was sensitive to watershed characteristics and management inputs, such as, slope and amount of fertilizer applied. Potential energy crop impacts with thirteen plausible energy crop scenarios in the watershed indicated overall improvement in water quality with introduction of perennial energy crops. Parameter uncertainty analysis indicated minimal effects of parameter uncertainty on bioenergy crop impact analysis. The bioenergy optimization framework was found robust in solution convergence and computational efficiency (about 20 fold compared to single level spatial optimization). However, spatial distributions of energy crops were sensitive to environmental tradeoffs considered as objective functions. The watershed scale environmental impacts of energy crops estimated by the study can guide stakeholders in developing watershed management plans. The optimization framework can be used to identify the best suitable locations for energy crop placement with maximum biomass production and minimum environmental impacts. The framework enables spatial optimization research with options for studying different possible optimization scenarios and comparisons across optimization results.

Degree

Ph.D.

Advisors

Chaubey, Purdue University.

Subject Area

Environmental Studies|Agricultural engineering|Environmental engineering

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