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Homepage>BS ISO 5667-20:2008 Water quality. Sampling Guidance on the use of sampling data for decision making. Compliance with thresholds and classification systems
sklademVydáno: 2008-04-30
BS ISO 5667-20:2008 Water quality. Sampling Guidance on the use of sampling data for decision making. Compliance with thresholds and classification systems

BS ISO 5667-20:2008

Water quality. Sampling Guidance on the use of sampling data for decision making. Compliance with thresholds and classification systems

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Označení normy:BS ISO 5667-20:2008
Počet stran:46
Vydáno:2008-04-30
ISBN:978 0 580 55352 3
Status:Standard
DESCRIPTION

BS ISO 5667-20:2008


This standard BS ISO 5667-20:2008 Water quality. Sampling is classified in these ICS categories:
  • 13.060.45 Examination of water in general

This part of ISO 5667 establishes principles, basic requirements, and illustrative methods for dealing with the use of sample data for decision making based on the assessment of the confidence that water quality:

  1. meets targets and complies with thresholds;

  2. has changed; and/or

  3. lies in a particular grade in a classification system.

This part of ISO 5667 also specifies methods for preliminary examination of the sensitivity of decisions to error and uncertainty, although it does not cover the full range of statistical techniques.

This part of ISO 5667 provides general advice on decision making related to constraint formulation for expression of thresholds and targets and the form and scale of sampling programmes.

NOTE 1 In the water industry, “standard” is commonly used to indicate the value or limit of a parameter of interest. However, in this part of ISO 5667, the term “threshold” is used to avoid confusion with published national, regional, and International Standards.

NOTE 2 This document is framed in terms of sampling and measurement of chemical concentrations, in particular those subject to strong day-to-day temporal variations. The principles apply, however, to any item estimated by sampling which is subject to random error, including microbiological and biological data, and data subject to strong spatial variations.