Abstract #300354

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JSM 2003 Abstract #300354
Activity Number: 362
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics & the Environment
Abstract - #300354
Title: Regionalized Assessment of Clean Water Act Standards
Author(s): Eric P. Smith*+ and Keying Ye
Companies: Virginia Polytechnic Institute and State University and Virginia Polytechnic Institute and State University
Address: Dept. of Statistics, Blacksburg, VA, 24061-0001,
Keywords: Bayesian analysis ; mixed models ; watersheds ; standards assessment ; environmental statistics ; pollution assessment
Abstract:

Under section 303(d) of the Clean Water Act, states must identify water segments, where loads of pollutants are violating numeric water quality standards. The most commonly applied approach is to use a raw score approach, in which a stream segment is listed as impaired when greater than 10% of the measurements of water quality conditions exceed a numeric criteria. In the water monitoring process, decisions are often made from data collected on a quarterly (or less frequent) sampling basis for a two-year cycle, which results in a sample of eight observations. Direct estimators from samples of this size are likely to be unreliable and unstable. When data are part of a regional assessment it is possible to use a regional model and "borrow strength" from related areas to find more accurate estimates for an individual area. Typically, estimates from small area estimation methods are more precise than those made using just the individual site information. In this presentation, we describe the use of small area estimation techniques and Bayesian approaches to make the decision to list the segment.

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