QUALITY ASSURANCE PROJECT PLAN OUTLINE

      1. Project Organization
        1. Identify by job titles those individuals using data
        2. Identify Project Officers:
          1. Project Director - reviews all work
          2. WQM Specialist - oversees QA
          3. Technicians - field and lab
          4. Sampling Specialist - oversees field work
          5. Lab Specialist - oversees lab work
          6. Data Specialist - oversees data QC
          7. Data Reviewer - analyzes data accuracy
          8. Regional WQM Coordinator
          9. State CZM contact
      2. Problem Definition/Background
        1. Describe original rational for project
        2. Define problem
      3. Project Description
        1. Data quality objectives
        2. Project narrative
        3. Special training and certification
        4. Documentation and record-keeping
      4. Sampling Process Design
        1. Justify monitoring plan design
          1. Justify Sites
            1. Site location - longitude & latitude
            2. River mile
            3. Data representativeness, comparability
            4. Homogeneity of system
          2. Access
          3. Stream flow & depth
          4. Tidal fluctuations
          5. Weather variables
        2. Schedule of milestones
      5. Sampling Process Procedures Table
        1. Parameter
        2. Procedure
        3. Container
        4. Preservation
        5. Sample number and location
      6. Sample Handling (chain of custody)
      7. Analytical Methods
        1. Project objectives in numeric terms
        2. Why doing project/what is data used for?
          1. Testing ecological hypothesis
          2. Verify permit compliance
          3. Support permit issuance/revision
          4. Verify WQ standards
        3. Detection levels
        4. Reporting units
        5. Levels of confidence
          1. Standard deviation
          2. % Bias
        6. Comparability
          1. Consistent reporting units
          2. Standardized analytical methods
          3. Standard data format
        7. Representativeness
          1. Degree data accurately and precisely represents water's characteristics
      8. QC Requirements for Each Analysis
        1. QC procedure
          1. Spike
          2. Split
          3. Replicate
          4. Blank
          5. Calibration check
        2. Per cent of samples that are QC
          1. Project beginning 50%
          2. Maintenance of project 5% field samples/10% lab samples
          3. Data validity and verification methods
            1. Process
            2. Response to problems
      9. Data Reconciliation
        1. Process to assure data meets requirements & objectives
        2. Actions to correct invalid data
Adapted from "Integrating Quality Assurance Into Tribal Water Programs", Chris Lehnertz, EPA Region 8.
"Guidance for Preparation of Combined Work/Quality Assurance Project Plans for Environmental Monitoring" Office of Water Regulations and Standards, US EPA, Washington, DC. May, 1984.
"WET Manual". Wells National Estuarine Research Reserve. Wells, Maine, 1993.
"Volunteer Estuary Monitoring: A Methods Manual. US Environmental Protection Agency, Office of Water. December, 1993.
"Rapid Bioassessement Protocols for Use in Streams and Rivers - Benthic Macroinvertebrates and Fish. US Environmental Protection Agency, Office of Water. May, 1989.
Clear Water: A Guide to Water Quality Monitoring. Esperanza Stancioff, University of Maine Cooperative Extension Service. University of Maine, Orono. November, 1992.

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SAMPLE OF QUALITY CONTROL PROTOCOLS - BIOLOGICAL SAMPLING:
Macroinvertebrates | Fecal Coliform | Aquatic Vegetation | Intertidal Organisms

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