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Learn about the significance of Quality Assurance in water quality monitoring. Explore definitions, volunteer monitors' responsibilities, good documentation practices, data evaluation, and DEQ's use of secondary data. Understand the importance and role of QA/QC activities and the responsibilities of volunteer monitors. Discover how proper documentation and data evaluation enhance the quality and usability of monitoring data. Gain insights into DEQ's assessment methodology and requirements for data quality. Get equipped with tools to ensure water quality standards are maintained.
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Water Quality Monitoring-Quality Assurance/Quality Control- May 17, 2012
Presentation Outline: • Why is Quality Assurance Important? • Definitions • Volunteer Monitors’ QA Responsibilities • Good Documentation • Data Evaluations • DEQ’s Use of Secondary Data
Why Do Volunteers Monitor? You believe that someone can put the data to good use!
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
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
Volunteer Monitor’s QA Responsibilities • Show you know what you are doing and doing it right
Volunteer Monitor’s QA Responsibilities • Show you know what you are doing and doing it right
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.
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.
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
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)
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
