2003Journal of Water Resources Planning and ManagementRequires access

Implications of Applying Statistically Based Procedures for Water Quality Assessment

Leonard Shabman, Eric P. Smith

Open publisher page 20 citations

Abstract

Assessment of water quality conditions as required by Section 303d of the Clean Water Act must rely on limited monitoring data. Because data are limited there will always be the potential for error when deciding if water quality standards are being met. However, the informed use of statistical procedures makes it possible to describe and manage these errors. We make the case for using such procedures in water quality assessment and draw the implications for the monitoring data for water quality standard setting, arguing that standard setting must accommodate the limits of the monitoring data and the statistical procedures that will be used for water quality assessment.

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What this paper is about

Assessment of water quality conditions as required by Section 303d of the Clean Water Act must rely on limited monitoring data. Because data are limited there will always be the potential for error when deciding if water quality standards are being met. However, the informed use of statistical procedures makes it possible to describe and manage these errors. We make the case for using such procedures in water quality assessment and draw the implications for the monitoring data for water quality standard setting, arguing that standard setting must accommodate the limits of the monitoring data and the statistical procedures that will be used for water quality assessment.

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OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Assessment of water quality conditions as required by Section 303d of the Clean Water Act must rely on limited monitoring data. Because data are limited there will always be the potential for error when deciding if water quality standards are being met. However, the informed use of statistical procedures makes it possible to describe and manage these errors. We make the case for using such procedures in water quality assessment and draw the implications for the monitoring data for water quality standard setting, arguing that standard setting must accommodate the limits of the monitoring data and the statistical procedures that will be used for water quality assessment.

Key concepts: Quality (philosophy), Water quality, Data quality, Computer science, Risk analysis (engineering), Reliability engineering, Environmental science, Engineering

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