BASINS-STAR: An Evolutionary Algorithm-Based Decision Support Framework for Watershed Water Quality Management

Autor: S. Ranji Ranjithan, Jason L. Dorn, Kishan Chetan, Thomas L. Murray, Albert Whangbo, Can Kuterdam, Amey Parandekar
Rok vydání: 2001
Předmět:
Zdroj: Bridging the Gap.
DOI: 10.1061/40569(2001)46
Popis: Watershed management requires consideration of multitude of factors affecting water quality at the watershed-scale while integrating point and non-point sources of pollution and control. EPA's TMDL development tool, Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) provides a GIS-based framework to assist in this process. The development of management strategies using BASINS to meet water quality goals is necessarily a trial-and-error process. Finding management strategies that consider water quality as well as a multitude of other design issues simultaneously via a trial-and-error process is inefficient. This paper introduces BASINS-STAR (BASINS STrategy, Analysis, and Reporting system), a new set of tools to assist decisions-makers explore and identify alternative management strategies. The main engine of BASINS-STAR is a genetic algorithm-based optimization technique, which is coupled with additional tools such as an uncertainty propagation tool, a solution reporting system, and an incremental strategy development system to form a decision support framework. This paper describes these tools and demonstrates its application through an illustrative case study.
Databáze: OpenAIRE