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A DECISION ANALYSIS APPROACH TO TMDL IMPLEMENTATION DECISIONS: MERCURY TMDLS IN THE SAN FRANCISCO BAY AREA

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Abstract:

This paper describes a decision analysis approach to TMDL implementation decisions for mercury using a hypothetical mine-impacted tributary in the San Francisco Bay as an example. Decision analysis is a theoretically sound approach for making significant decisions under uncertainty (see, e.g., Howard, 1968; 1988; Keeney and Raiffa, 1976; Clemen, 1996; Merkhofer, 1999). The Bayesian probabilistic nature of decision analysis makes it ideal for integrating diverse information, including the results from scientific and engineering models, cost and benefit models, empirical data, and expert judgment. One significant advantage of a decision analysis approach is its explicit separation of a decision problem into alternatives, information, and preferences. This, in theory, allows decision makers and stakeholders to separate “what we know” from “what we want”. It is hypothesized that a more explicit separation of information and values/preferences will focus the debate. While traditional decision analysis assumes a single rational decision maker (where “single” may also denote a group that agrees on information and preferences), it can be extended to multiple decision maker situations in a variety of ways. Evaluating various extensions of decision analysis in a TMDL implementation stakeholder context is one of the primary goals of this on-going study. It is hypothesized that, in general, decision analysis provides a helpful decision framework for a TMDL implementation planning/stakeholder process in many circumstances.

Document Type: Research Article

DOI: http://dx.doi.org/10.2175/193864703784828336

Publication date: January 1, 2003

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  • Proceedings of the Water Environment Federation is an archive of papers published in the proceedings of the annual Water Environment Federation® Technical Exhibition and Conference (WEFTEC® ) and specialty conferences held since the year 2000. These proceedings are not peer reviewed.

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