Forest Road Erosion Control Using Multiobjective Optimization

Authors

  • Matthew Thompson,

    1. Respectively, Research Forester (Thompson), Rocky Mountain Research Station, USDA Forest Service, P.O. Box 7669, Missoula, Montana 59801
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  • John Sessions,

    1. Professor (Sessions) and Associate Professors (Boston, Skaugset), Department of Forest Engineering, Resources and Management, Oregon State University, Corvallis, Oregon 97331
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  • Kevin Boston,

    1. Professor (Sessions) and Associate Professors (Boston, Skaugset), Department of Forest Engineering, Resources and Management, Oregon State University, Corvallis, Oregon 97331
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  • Arne Skaugset,

    1. Professor (Sessions) and Associate Professors (Boston, Skaugset), Department of Forest Engineering, Resources and Management, Oregon State University, Corvallis, Oregon 97331
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  • David Tomberlin

    1. Economist (Tomberlin), National Marine Fisheries Service, Silver Spring, Maryland 20910.
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  • Paper No. JAWRA-09-0068-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.

(E-Mail/Thompson: mpthompson02@fs.fed.us)

Abstract

Thompson, Matthew, John Sessions, Kevin Boston, Arne Skaugset, and David Tomberlin, 2010. Forest Road Erosion Control Using Multiobjective Optimization. Journal of the American Water Resources Association (JAWRA) 46(4): 712-723. DOI: 10.1111/j.1752-1688.2010.00443.x

Abstract:  Forest roads are associated with accelerated erosion and can be a major source of sediment delivery to streams, which can degrade aquatic habitat. Controlling road-related erosion therefore remains an important issue for forest stewardship. Managers are faced with the task to develop efficient road management strategies to achieve conflicting environmental and economic goals. This manuscript uses mathematical programming techniques to identify the efficient frontier between sediment reduction and treatment costs. Information on the nature of the tradeoffs between conflicting objectives can give the decision maker more insight into the problem, and help in reaching a suitable compromise solution. This approach avoids difficulties associated with a priori establishment of targets for sediment reduction, preferences between competing objectives, and mechanisms to scale noncommensurate objectives. Computational results demonstrate the utility of this multiobjective optimization approach, which should facilitate tradeoff analysis and ideally promote efficient erosion control on forest roads.

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