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Examining the Possibilities: Generating Alternative Watershed-Scale BMP Designs with Evolutionary Algorithms

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Abstract

Recent studies in water resources planning and management show a gradual shift in the state of the art from numerous on-site structural stormwater Best Management Practice (BMP) designs to watershed-scale BMP design approaches that meet both target water quantity (peak flow) and quality (sediment reduction) criteria. Such regionally-strategic approaches are not only cost-effective but emphasize comprehensive, holistic watershed-scale management, an idea strongly promoted by the U.S. Environmental Protection Agency (US EPA) since the early 1990s. Implementing a watershed-scale design can prove difficult when decision-makers have differing and sometimes conflicting objectives. We present a methodology that integrates the semi-distributed watershed model Soil and Water Assessment Tool (SWAT) with an evolutionary algorithm, Species Conserving Genetic Algorithm (SCGA). In addition to identifying an optimal watershed-scale BMP design (e.g., type, size, location), SCGA simultaneously produces several near-optimal design alternatives using a user-specified distance metric. We demonstrate this decision-oriented framework on a watershed in southern Illinois. Results of this application yield several high-quality alternative designs appropriate for solving integrated watershed management problems.

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Abbreviations

SWAT:

Soil and Water Assessment Tool

BMP:

Best Management Practice

US EPA:

U.S. Environmental Protection Service

EA:

Evolutionary Algorithm

SCGA:

Species Conserving GA

EAGA:

Evolutionary Algorithm to Generate Alternatives

HRU:

Hydrological Response Unit

NRCS:

National Resources Conservation Service

USDA:

U.S. Department of Agriculture

CN:

Curve Number

MOPSO:

Multi-Objective Particle Swarm Optimization

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Acknowledgments

This research was supported by the U.S. Department of the Interior, the U.S. Geological Survey, and the Board of Trustees of the University of Illinois under Grant No. 06HQGR0185. The first author is grateful to M Sears and J Brajkovich for their Linux/computer support.

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Author notes

  1. Kimberly S. Artita

    Present address: Cardno ENTRIX, 391 College Ave., #406, Clemson, SC, 29631, USA

  2. Prakash Kaini

    Present address: Golder Associates, 44 Union Boulevard, Suite 300, Lakewood, CO, 80228, USA

Authors and Affiliations

  1. Department of Civil & Environmental Engineering, College of Engineering, Southern Illinois University Carbondale (SIUC), Mail Code 6603, Carbondale, IL, 62901, USA

    Kimberly S. Artita, Prakash Kaini & John W. Nicklow

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  1. Kimberly S. Artita
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  2. Prakash Kaini
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Correspondence to Kimberly S. Artita.

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Artita, K.S., Kaini, P. & Nicklow, J.W. Examining the Possibilities: Generating Alternative Watershed-Scale BMP Designs with Evolutionary Algorithms. Water Resour Manage 27, 3849–3863 (2013). https://doi.org/10.1007/s11269-013-0375-3

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