Abstract
<abstract> <p>This research presents a novel optimization modeling framework for the existing Soil and Water Assessment Tool (SWAT), which can be used to optimize perennial feedstock production. This novel multi-objective evolutionary algorithm (MOEA) uses SWAT outputs to determine optimal spatial placement of variant cropping systems, considering environmental impacts from land-cover change and management practices. The final solution to the multi-objective problem is presented as a set of Pareto optimal solutions, where one is suggested considering the proximity to the ideal vector [1,0,0,0]. This unique approach provides a well-suited method to assist researchers and stakeholders in understanding the environmental impacts when cultivating biofuel feedstocks. The application of the proposed MOEA is illustrated by analyzing SWAT's example data set for Lake Fork Watershed. Nine land-cover scenarios were evaluated in SWAT to determine their optimal spatial placement considering maximizing biomass production while minimizing sediment yield, organic nitrogen yield, and organic phosphorous yield.</p> </abstract>
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