1. Making Data Count: Why you need/want a QAPP
Mary Skopec, Ph.D.
Watershed Monitoring and Assessment Section
Iowa Department of Natural Resources

2. QAPP Defined Quality Assurance Project Plan Outlines procedures
Standard Operating Procedures
Planning and Operations Tool
What, When, Where, How Often, Repeat
Links Goals to Actions
Will your project be successful?

3. Why QAPP?
“One of the most difficult issues facing volunteer environmental monitoring programs today is data credibility”….
Geoffrey H. Grubbs, EPA Director of Assessment and Watershed Protection

4. Why QAPP
“Potential data users are often skeptical about volunteer data – they have doubts about the goals and objectives of the project, about how the volunteers are trained, about how samples were collected, handled and stored, or about how data were analyzed and reports written.”…..

5. Why QAPP
“A key tool in breaking down this barrier of skepticism is the quality assurance project plan.”

6. Why QAPP? Brings scientific credibility and transparency to your work
Allows you to train new volunteers
Allows results to be evaluated for Best Management Plans (BMPs) and their impact on the watershed

7. Iowa Credible Data Law
The department shall use credible data when doing any of the following:
Developing and reviewing any water quality standard.
Developing any statewide water quality inventory or other water assessment report.
Determining whether any water of the state is to be placed on or removed from any section 303(d) list.

8. Iowa Credible Data Law
Determining whether any water of the state is supporting its designated use or other classification.
Establishing a total maximum daily load for any water of the state.

9. Iowa Credible Data Law
"Credible data" means scientifically valid chemical, physical, or biological monitoring data collected under a scientifically accepted sampling and analysis plan, including quality control and quality assurance procedures.

10. Iowa Credible Data Law
Data are not credible data unless the data originates from studies and samples collected by the department, a professional designee of the department, or a qualified volunteer.

11. Producing the QAPP
Click your heels three times and repeat…”there is no place like home”..
Use existing resources from EPA, DNR, other projects.
Time consuming, but necessary.

13. Basic QAPP Elements Project Goal and Objectives
Where to collect a sample
When to collect a sample
How to collect a sample
How to analyze or ship a sample
Minimum acceptable QA/QC
Minimum acceptable results and allowable reportable results
Data reduction and analysis techniques

14. (congratulations on a job well done)
Johnson and Iowa County Coalition Snapshot and Rapid Creek Watershed QAPP
QA/WM/07-01
(congratulations on a job well done)

15. JAICWC Goal
The goal of this monitoring is to design and implement a series of sampling events that will assess the water quality and general health of the Rapid Creek Watershed and water quality throughout other watersheds in Johnson and Iowa counties.

16. Objectives Data Collection Needs To Support These Objectives
Specific objectives of these monitoring events include:
Establish baseline conditions for determining stream health based on chemical, physical, habitat, and biological parameters.
Assess the health of the watershed and target areas within the watershed in need of water quality improvement.
Assist local watershed councils and partners in making environmental management decisions in their local and regional watersheds.
Enlist community involvement in their local watershed.
Collect data that may aid in the prioritization of watershed areas for Best Management Practices (BMPs).
Data Collection Needs To Support These Objectives

17. Project Organization

18. For Each Subproject, Site Selection

19. Analyte Matrix Sample Container Preservative Holding Time
Analytical Method
Ammonia
Nitrogen as N
Water
250 ml plastic
H2SO4 to pH <2; Cool to 4 ◦C
28 days
LAC J
Chloride, Field
None
Immediate
Hach® brand, silver nitrate titrant, Range: mg/L
E. coli Bacteria (UHL)
120 ml clear plastic
0.008% NA2S2O3; Cool to 4 ◦C
<6 hours; >6 still report
EPA 1603 (modified mTEC)
E. coli Bacteria (DNR)
15 ml clear plastic
24 hours
SM 9223B
Nitrate+Nitrite Nitrogen
EPA 353.2
Nitrate Nitrogen, Field
Hach® brand, nitrate test strip, Range: 0-50 mg/L
Nitrite Nitrogen Field
Hach® brand, nitrite test strip, Range: 0-3 mg/L
Dissolved Oxygen, Field
Chemetric® brand test kit, Indigo Carmine Method, Range: 1-12 mg/L
pH, Field
Hach® brand, pH test strip, Range: 4-9
Phosphate, Ortho-, Field
Chemetric® brand test kit, Stannous Chloride Method, Range: 0-1 & 1-10 mg/L
Temperature, Field
Enviro-Safe® Armor-Case thermometer containing safe, non-mercury liquid.
Transparency, Field
60 cm polycarbonate tube with 4.5 cm standard Secchi disk design in bottom.

20. Training
Volunteers assisting with the JAICWC Snapshot event and the Rapid Creek Watershed Project are encouraged to attend a ten-hour Level 1 IOWATER Workshop.

21. Sample Collection/Analysis/Data Transfer Procedures
IOWATER Field Methods
UHL Laboratory Analysis
Snapshot Methods
Excel Spreadsheets
IOWATER database
STORET

22. Reports
In no less than one month before the Spring Snapshot sampling, a report produced by the IOWATER Snapshot Coordinator and the JAICWC Project Coordinator will be made available to the persons listed on the Approval Signature page and each person listed in Table 1.

23. Reports
A Fact Sheet will be generated, summarizing the data and observations collected in the Rapid Creek Watershed. This Fact Sheet will be presented to the Johnson County Soil and Water Conservation Board of Supervisors

24. JAICWC QAPP Provides a “living” document of activities.
Provides for transfer of knowledge to future volunteers/staff/etc.
Absolutely Critical for Producing Quality, Accepted Data

25. Questions?

26. Quality Assurance/Quality Control
Quality Assurance – refers to the organization, planning, data collection, quality control, documentation, evaluation, and reporting activities of your group.
Quality Control – routine technical activities for error control. Both field and laboratory aspects.

27. Basic QA/QC Concepts
Precision – degree of agreement among repeated measurements.
Accuracy – measures how close your results are to a true or expected value.
Representativeness – extent to which measurements actually represent the true condition at the time a sample was collected.
Completeness – comparison between the amount of valid, or usable, data you planned to collect versus how much you collected.
Comparability – extent to which data can be compared between sample locations or periods of time within a project, or between projects.