Optimizing Structural Best Management Practices Using SWAT and Genetic Algorithm to Improve Water Quality Goals

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• 作者：Prakash Kaini (1) pkaini@golder.com
  Kim Artita (1)
  John W. Nicklow (2)
• 关键词：Genetic algorithm &#8211 ; Watershed modeling &#8211 ; Treatment goals &#8211 ; SWAT &#8211 ; Silver Creek &#8211 ; Structural BMPs
• 刊名：Water Resources Management
• 出版年：2012
• 出版时间：May 2012
• 年：2012
• 卷：26
• 期：7
• 页码：1827-1845
• 全文大小：544.7 KB
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• 作者单位：1. Department of Civil and Environmental Engineering, Southern Illinois University Carbondale (SIUC), Mail Code 6603, Carbondale, IL 62901, USA2. Department of Civil and Environmental Engineering, College of Engineering, Southern Illinois University Carbondale (SIUC), Mail Code 6603, Carbondale, IL 62901, USA
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Hydrogeology
  Geotechnical Engineering
  Meteorology and Climatology
  Civil Engineering
  Environment
  
• 出版者：Springer Netherlands
• ISSN：1573-1650

文摘

A genetic algorithm (GA), an evolutionary optimization technique, is coupled with a semi-distributed hydrologic model, Soil and Water Assessment Tool (SWAT) to find an optimum combination of structural Best Management Practices (BMPs) that meets the treatment goals at a watershed scale. The structural BMPs considered in the study are detention ponds, parallel terraces, filter strips, grassed waterways, and grade stabilization structures which are all applicable in agricultural watersheds. The decision variables in the optimization model are the type, size, and location of BMPs which minimize the construction cost and simultaneously reduce sediment and nutrients to target levels at the watershed outlet. The model is demonstrated on the Silver Creek, a sub-watershed of the Lower Kaskaskia watershed in Illinois. The model is used to compare three different sediment and nutrient reduction cases (i.e. 20%, 40%, and, 60%) at the watershed outlet.