title: Optimization of bioenergy crop selection and placement based on a stream health indicator using an evolutionary algorithm.
abstract: The emission of greenhouse gases continues to amplify the impacts of global climate change. This has led to the increased focus on using renewable energy sources, such as biofuels, due to their lower impact on the environment. However, the production of biofuels can still have negative impacts on water resources. This study introduces a new strategy to optimize bioenergy landscapes while improving stream health for the region. To accomplish this, several hydrological models including the Soil and Water Assessment Tool, Hydrologic Integrity Tool, and Adaptive Neruro Fuzzy Inference System, were linked to develop stream health predictor models. These models are capable of estimating stream health scores based on the Index of Biological Integrity. The coupling of the aforementioned models was used to guide a genetic algorithm to design watershed-scale bioenergy landscapes. Thirteen bioenergy managements were considered based on the high probability of adaptation by farmers in the study area. Results from two thousand runs identified an optimum bioenergy crops placement that maximized the stream health for the Flint River Watershed in Michigan. The final overall stream health score was 50.93, which was improved from the current stream health score of 48.19. This was shown to be a significant improvement at the 1% significant level. For this final bioenergy landscape the most often used management was miscanthus (27.07%), followed by corn-soybean-rye (19.00%), corn stover-soybean (18.09%), and corn-soybean (16.43%). The technique introduced in this study can be successfully modified for use in different regions and can be used by stakeholders and decision makers to develop bioenergy landscapes that maximize stream health in the area of interest.
authors.affiliation: Department of Biosystems and Agricultural Engineering, 524 S. Shaw Lane, Room 216, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Matthew R
authors.initials: MR
authors.lastname: Herman
authors.affiliation: Department of Biosystems and Agricultural Engineering, 524 S. Shaw Lane, Room 216, Michigan State University, East Lansing, MI 48824, USA. Electronic address: pouyan@msu.edu.
authors.forename: A Pouyan
authors.initials: AP
authors.lastname: Nejadhashemi
authors.affiliation: Department of Biosystems and Agricultural Engineering, 524 S. Shaw Lane, Room 216, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Fariborz
authors.initials: F
authors.lastname: Daneshvar
authors.affiliation: Department of Biosystems and Agricultural Engineering, 524 S. Shaw Lane, Room 216, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Abouali
authors.affiliation: Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Dennis M
authors.initials: DM
authors.lastname: Ross
authors.affiliation: Department of Biosystems and Agricultural Engineering, 524 S. Shaw Lane, Room 216, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Sean A
authors.initials: SA
authors.lastname: Woznicki
authors.affiliation: Physical Sciences Division, Department of Statistics, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D056804:Biofuels; D018556:Crops, Agricultural; D062070:Hydrology / Q000379:methods*; D008824:Michigan; D008962:Models, Theoretical; D006109:Poaceae; D045483:Rivers; D012434:Secale; D012987:Soil; D013025:Glycine max; D003313:Zea mays
chemical_list: D056804:Biofuels; D012987:Soil
keywords: Bioenergy; Genetic algorithm; Index of biological integrity; Stream health