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Water Quality Monitoring -Quality Assurance/Quality Control-

Water Quality Monitoring -Quality Assurance/Quality Control-. May 17, 2012. Presentation Outline:. Why is Quality A ssurance Important ? Definitions Volunteer Monitors’ QA Responsibilities Good Documentation Data Evaluations DEQ’s Use of Secondary Data. Why Do Volunteers Monitor?.

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Water Quality Monitoring -Quality Assurance/Quality Control-

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  1. Water Quality Monitoring-Quality Assurance/Quality Control- May 17, 2012

  2. Presentation Outline: • Why is Quality Assurance Important? • Definitions • Volunteer Monitors’ QA Responsibilities • Good Documentation • Data Evaluations • DEQ’s Use of Secondary Data

  3. Why Do Volunteers Monitor? You believe that someone can put the data to good use!

  4. Monitoring Goals

  5. Why Is Quality Assurance Important?

  6. Definitions • Quality Assurance (QA) • A set of operating principles, which if strictly followed during sample collection and analysis, will produce data of known and defensible quality

  7. Definitions • Quality Control (QC) • Activities that are implemented to evaluate the effectiveness of QA activities • Used to produce and document the quality of the data

  8. Volunteer Monitor’s QA Responsibilities • Show you know what you are doing and doing it right

  9. Volunteer Monitor’s QA Responsibilities • Show you know what you are doing and doing it right

  10. Good Documentation • Metadata are data descriptors or qualifiers that document the when, where, what, why, how, and “how good” of sample collection and analysis. • The more background information (metadata) you can provide, the more valuable your data will be for multiple purposes and users.

  11. Good Documentation • Electronically “flagging” questionable data is another tool to help document data quality. • These flags and comments constitute a type of metadata—essentially, the data manager’s professional judgment that there is some question about the validity of a particular result.

  12. Data Evaluation • Evaluate the field and laboratory data to determine if the data meets project objectives • Use aQC Checklist • Determine how the data that doesn’t meet requirements affect the usability of the data • Screen data for outliers • Flag data as appropriate

  13. DEQ’s Use of Secondary Data • Data must be of known quality for DEQ to use the data for decision-making. Secondary data must include the following minimal requirements: • Data < 10 years • Written documentation (i.e., QAPP or SAP) • QA/QC documentation • Notes indicating deviations from QAPP or SAP • Data location information (i.e., latitude/longitude)

  14. DEQ’s Assessment Methodology Data used by DEQ for assessments must meet certain requirements that are specific to each pollutant group. Pollutant Specific Assessment Methods

  15. DEQ’s Data Quality Assessment

  16. QA/QC Summary

  17. Questions?

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