The Volunteer

Monitor's Guide To

Quality Assurance

Project Plans

United States

Environmental Protection

Agency

Office of Wetlands,

Oceans and Watersheds

4503F

EPA 841-B-96-003

September 1996
The Volunteer Monitor’s Guide to

Quality Assurance

Project Plans
Dear Reader:

Across the country, volunteers are monitoring the condition of streams, rivers, lakes,

reservoirs, estuaries, coastal waters, wetlands, and wells. The number and variety of these

projects are continually on the rise. So, too, is the complexity of the monitoring volunteers

conduct and the uses of the data they collect.

One of the most difficult issues facing volunteer environmental monitoring programs

today is data credibility. Potential data users are often skeptical about volunteer data -- they may

have doubts about the goals and objectives of the project, about how volunteers were trained,

about how samples were collected, handled and stored, or about how data were analyzed and

reports written. A key tool in breaking down this barrier of skepticism is the quality assurance

project plan.

The quality assurance project plan, or QAPP, is a document that outlines the procedures

that those who conduct a monitoring project will take to ensure that the data they collect and

analyze meets project requirements. It is an invaluable planning and operating tool that outlines

the project’s methods of data collection, storage and analysis. It serves not only to convince

skeptical data users about the quality of the project’s findings, but also to record methods, goals

and project implementation steps for current and future volunteers and for those who may wish

to use the project’s data over time.

Developing a QAPP is a dynamic, interactive process that should ideally involve quality

assurance experts, potential data users, and members of the volunteer monitoring project team. 

It is not an easy process. This document is designed to encourage and facilitate the development

of volunteer QAPPs by clearly presenting explanations and examples. Readers are urged to

consult, as well, the additional resources listed in the appendices to this document, and to contact

their state or U.S. Environmental Protection Agency (EPA) Regional quality assurance staff for

specific information or guidance on their projects. 

Sincerely,

Geoffrey H. Grubbs, Director

Assessment and Watershed Protection Division
Contents:

Executive Summary ............................................. i

Chapter 1 Introduction ........................................ 1

Chapter 2 Developing a QAPP .................................. 7

Chapter 3 Some Basic QA/QC Concepts ......................... 15

Chapter 4 Elements of a QAPP ................................ 23

Appendix A Glossary .......................................... 41

Appendix B EPA Regional Contacts .............................. 45

Appendix C References ........................................ 49

Appendix D Abbreviated QAPP Form ............................. 51

Acknowledgements

This manual was developed by the U.S. Environmental Protection Agency

through contract no. 68-C3-0303 with Tetra Tech, Inc. The project manager was

Alice Mayio, USEPA Office of Wetlands, Oceans, and Watersheds. Principal

authors include Margo Hunt, USEPA Region 2; Alice Mayio, USEPA; Martin

Brossman, USEPA; and Abby Markowitz, Tetra Tech, Inc. 

The authors wish to thank the many reviewers who provided constructive and

insightful comments to earlier drafts of this document. This guidance manual

would not have been possible without their invaluable advice and assistance.

Original illustations by Dave Skibiak and Emily Faalasli of Tetra Tech, Inc., and

Elizabeth Yuster of the Maryland Volunteer Watershed Monitoring Association.

September 1996
Executive Summary i

EXECUTIVE SUMMARY

EPA-funded monitoring

programs must have an

EPA-approved QAPP

before sample collection

begins. However, even

programs that do not

receive EPA money

should consider

developing a QAPP,

especially if data might

be used by state, federal,

or local resource

managers. 

he Quality Assurance Project Plan, or QAPP, is a written document that Toutlines the procedures a monitoring project will use to ensure that the

samples participants collect and analyze, the data they store and manage,

and the reports they write are of high enough quality to meet project needs.

U.S. Environmental Protection Agency-funded

monitoring programs must have an EPA-approved

QAPP before sample collection begins. However,

even programs that do not receive EPA money

should consider developing a QAPP, especially if

data might be used by state, federal, or local

resource managers. A QAPP helps the data user

and monitoring project leaders ensure that the

collected data meet their needs and that the quality

control steps needed to verify this are built into the

project from the beginning.

Volunteer monitoring programs have long

recognized the importance of well-designed

monitoring projects; written field, lab, and data management protocols; trained

volunteers; and effective presentation of results. Relatively

few programs, however, have tackled the task of preparing a

comprehensive QAPP that documents these important

elements. 

This document is designed to help volunteer program

coordinators develop such a QAPP. 

Steps to Developing a QAPP

Developing a QAPP is a dynamic, interactive process that

should ideally involve state and EPA regional QA experts,
ii The Volunteer Monitor’s Guide to Quality Assurance Project Plans

A QAPP helps the data

user and monitoring

project leaders ensure

that the data collected

meet their needs.

potential data users, and key members of the volunteer monitoring project. There

are 11 steps a volunteer monitoring project coordinator might take to prepare a

QAPP. These are:

Step 1: Establish a small team whose members will serve as advisors in

helping you develop the QAPP by offering feedback and guidance

throughout the entire process.

Step 2: Determine the goals & objectives of your project--why it’s needed,

who will use the data, and how the data will be used. 

Step 3: Collect background information to help you in designing your

project.

Step 4: Refine your project’s goals once you’ve collected more information.

Step 5: Design your project’s sampling, analytical & data requirements--

essentially, what, how, when, and where you’ll be monitoring.

Step 6: Develop an implementation plan that lays out project logistics.

Step 7: Draft your standard operating procedures (SOPs) & QAPP.

Step 8: Solicit feedback on your draft SOPs & QAPP from state or EPA

regional QA contacts and potential data users.
Executive Summary iii

The “PARCC”

Parameters

Taken together, the terms

Precision, Accuracy,

Representativeness,

Completeness, and

Comparability, comprise

the major data quality

indicators used to assess

the quality of your data. 

It is essential to

understand these terms

and to address them in

your QAPP. Chapter 3

of this document includes

a discussion of these indicators and gives

examples of how to evaluate the quality of your

data in relation to these terms.

According to EPA

guidance, 24 distinct

elements can be

included in a QAPP,

although not all

elements may be

necessary for all

programs.

Step 9: Revise your QAPP based on review

comments and submit it for approval.

Step 10: Once your QAPP is approved, begin your

monitoring program.

Step 11: Evaluate and refine your project over time,

and reflect any major changes in a revised

QAPP.

Basic QA/QC Concepts

It is important to understand the terminology of

quality assurance and quality control in order to

develop a QAPP. Key definitions include:

Precision -- the degree of agreement among repeated measurements of the

same characteristic. It may be determined by calculating the standard

deviation, or relative percent difference, among samples taken from the

same place at the same time. 

Accuracy -- measures how close your results are to a true or expected value

and can be determined by comparing your analysis of a

standard or reference sample to its actual value. 

Representativeness -- the extent to which

measurements actually represent the true

environmental condition or population at the time a

sample was collected.

Completeness -- the comparison between the amount

of valid, or usable, data you originally planned to

collect, versus how much you collected.

Comparability -- the extent to which data can be

compared between sample locations or periods of time

within a project, or between projects.

Elements of a QAPP 

According to EPA guidance, 24 distinct elements can be included in a QAPP,

although not all elements may be necessary for all programs. Which elements

you end up including in your QAPP depends on your project's goals, 

objectives, scope, data uses, and on the guidance you receive from your state or
iv The Volunteer Monitor’s Guide to Quality Assurance Project Plans

EPA regional quality assurance contacts. The 24 elements are grouped into four

overall categories and are listed below:

Project Management (elements 1-9)

1. Title and Approval Page

2. Table of Contents

3. Distribution List

4. Project/Task Organization

5. Problem Identification/ Background

6. Project/Task Description

7. Data Quality Objectives for Measurement Data

8. Training Requirements/Certification

9. Documentation and Records

Measurement/Data Acquisition (elements 10-19)

10. Sampling Process Design

11. Sampling Methods Requirements

12. Sample Handling and Custody Requirements

13. Analytical Methods Requirements

14. Quality Control Requirements

15. Instrument/Equipment Testing, Inspection, and Maintenance

Requirements

16. Instrument Calibration and Frequency

17. Inspection/Acceptance Requirements for Supplies

18. Data Acquisition Requirements

19. Data Management

Assessment and Oversight (elements 20-21)

20. Assessment and Response Actions

21. Reports

Data Validation and Usability (elements 22-24)

22. Data Review, Validation, and Verification Requirements

23. Validation and Verification Methods

24. Reconciliation with Data Quality Objectives
Chapter 1: Introduction 1

Chapter 1:

INTRODUCTION

Top 20

Parameters

Assessed by

Volunteer

Monitors

Water temperature

pH

Dissolved Oxygen

Macroinvertebrates

Debris clean-up

Habitat assessments

Nitrogen

Phosphorus

Turbidity

Coliform bacteria

Secchi depth

Aquatic vegetation

Flow

Birds/Wildlife

Fish

Watershed mapping

Rainfall

Photographic surveys

Salinity

Sediment assessments

Source: Directory of Volunteer

Environmental Monitoring

Programs, 4th Edition

cross the country, volunteers are monitoring the condition of streams, Arivers, lakes, reservoirs, estuaries, coastal waters, wetlands, and wells. 

The number and variety of these projects is continually on the rise; so,

too, is the complexity of the monitoring they conduct and the

uses of the data they collect.

Most volunteer monitoring projects evaluate the chemical,

physical, or biological condition of waters in a given watershed. 

They may address different kinds of waters—e.g., streams with 

associated embayments—and they may conduct several types of

monitoring activities. Some projects may address only one type

of monitoring in one type of waterbody, e.g., nutrient sampling

in estuaries. More

comprehensive projects may

take basic chemical

measurements of conditions

such as dissolved oxygen levels,

pH, or salinity, evaluate the

physical condition of streamside

habitat, and evaluate the

biological condition of aquatic

insects or vegetation. 

Not only do volunteer projects monitor many different

parameters and types of waters, they are also organized and

supported in many different ways. Volunteer monitoring

projects may be associated with state, interstate, local, or federal

agencies, with environmental organizations or universities, or may be entirely

independent. Financial support may come from government grants, partnerships

with business, endowments, independent fundraising efforts, corporate donations,

membership dues, or a combination of any and all of these sources. Most

volunteer projects are fairly small and have very

small budgets--based on EPA's latest Directory of

Volunteer Environmental Monitoring Programs,

4th Edition, we know that the median program

size is 25 volunteers, and the median annual

budget is under $5,000. However, there are also

volunteer programs with over 1,000 volunteers

and those with annual budgets of more than

$50,000.
Volunteer Monitoring Data Uses

53

84

120

127

160

213

225

226

288

333

439

Number of Programs

305(b)

Legislation

Enforcement

Water Classif/Stds

Habitat Restoration

Watershed Planning

NPS Assessment

Research

Local Decisions

Problem Identification

Education

0 100 200 300 400 500

2 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Source: Directory of Volunteer Environmental Monitoring

Programs, 4th Edition

Although the goals and

objectives of volunteer

projects vary greatly,

virtually all volunteers

hope to educate

themselves and others

about water quality

problems and thereby

promote a sense of

stewardship for the

environment. 

Although the goals and

objectives of volunteer

projects vary greatly, 

virtually all volunteers hope

to educate themselves and

others about water quality

problems and thereby

promote a sense of

stewardship for the

environment. Many projects,

in fact, establish these as

their goals. These projects

might be called primarily

education oriented.

Other projects seek a more

active role in the

management of local water

resources, and therefore

strive to collect data that can be used in making water quality management

decisions. Common uses of volunteer data include local planning decisions, such

as identifying where to route a highway; local priority setting, such as

determining which county lakes require restoration; screening for potential

pollution problems, which might then be investigated more thoroughly by water

quality agencies; and providing data for state water quality reports, which might

then be used for statewide or national priority setting. Projects doing this type of

monitoring might be called primarily data oriented. Data oriented volunteer

projects, in particular, must continuously wrestle with the issue of credibility.

They must prove to skeptics that their volunteers collect

good-quality data that is:

= consistent over time and within projects and group

members

= collected and analyzed using standardized and

acceptable techniques

= comparable to data collected in other assessments using

the same methods

These projects must adopt protocols that are straightforward

enough for volunteers to master and yet sophisticated

enough to generate data of value to resource managers. 

This delicate and difficult path cannot be successfully

navigated without a quality assurance plan that details a
Chapter 1: Introduction 3

Why Should You Develop

a QAPP?

The QAPP is an invaluable planning and

operating tool that should be developed in the early

stages of the volunteer monitoring project. 

Even if a volunteer monitoring project does not

receive any EPA money through grants, the

coordinating group should still consider developing a

QAPP, especially if it is a data oriented

project and seeks to

have its information

used by state, federal, or

local resource

managers. 

Few water quality

agencies will use

volunteer data unless

methods of data

collection, storage, and analysis can be documented. 

Clear and concise documentation of procedures also

allows newcomers to the project to continue

monitoring using the same methods as those who

came before them. 

This is particularly important to a volunteer project

that may see volunteers come and go and that intends

to establish a baseline of water quality information that

can be compared over time. 

A Quality Assurance

Project Plan, or QAPP,

is a written document

outlining the procedures

a monitoring project

will use to ensure the

data it collects and

analyzes meets project

requirements.

project's standard operating procedures in the field and lab,

outlines project organization, and addresses issues such as

training requirements, instrument calibration, and internal

checks on how data are collected, analyzed, and reported. 

Just how detailed such a plan needs to be depends to a large

extent on the goals of the volunteer monitoring project.

What Is a Quality Assurance

Project Plan?

A Quality Assurance Project Plan, or QAPP, is a written

document outlining the procedures a monitoring project will

use to ensure the data it collects and analyzes meets project

requirements. The U.S. Environmental Protection Agency

(EPA) has issued interim guidance that establishes up to 24

distinct elements of a QAPP (see Appendix C: References). 

Together, these elements of a QAPP comprise a project's quality assurance

system. As we will discuss below, not all 24 elements need be addressed in every

QAPP.

By law, any EPA-funded monitoring project must have an EPA-approved QAPP

before it can begin collecting samples. The

purpose of this requirement is to ensure that the

data collected by monitoring projects are of

known and suitable quality and quantity.

Typical sources of EPA funding for volunteer

monitoring projects include Lake Water

Quality Assessment Grants (under Section 314

of the Clean Water Act) or grants under the

nonpoint source pollution control program

(Section 319 of the Clean Water Act). Quality

assurance staff in each of EPA's 10 regional

offices are available to review volunteer

monitoring QAPPs and have authority to

recommend approval or disapproval of QAPPs. 

In addition, volunteer monitoring coordinators

and individual EPA project officers in the EPA

Regions may be able to assist projects seeking

advice on the preparation of QAPPs. (See

Appendix A, Regional Quality Assurance

Contacts.) 

About This Document

The purpose of this document is to provide

volunteer monitoring programs with the

information they need to develop a quality
4 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

The purpose of this

document is to provide

volunteer monitoring

programs with the

information they need to

develop a quality assurance

project plan.

assurance project plan. It does not suggest specific field,

laboratory, or analytical techniques or procedures, and is

not a "how to" manual. It is organized as follows:

Executive Summary introduces the reader to the steps

involved in developing a QAPP, fundamental QA/QC

concepts, and the basic elements of a QAPP.

Chapter 1: Introduction provides background on

volunteer monitoring, discusses the purposes of QAPPs,

and outlines the structure of this document.

Chapter 2: Developing a QAPP outlines the steps a

volunteer monitoring project should take as it moves toward developing a quality

assurance system, documenting its procedures in a QAPP, seeking approval of its

QAPP, and updating the QAPP over time. 

Chapter 3: QA/QC: Basic Concepts introduces basic quality assurance/quality

control (QA/QC) concepts and definitions that are needed in developing a quality

assurance system and a QAPP. Examples from a fictional project--the Volunteer

Creek Monitoring Project--are used to illustrate these concepts.

Chapter 4: Elements of a QAPP presents the basic elements of a volunteer

monitoring quality assurance project plan (QAPP), again with examples from the

QAPP of the fictional Volunteer Creek Monitoring Project. 

Appendix A: Glossary defines various terms and concepts associated with quality

assurance and control.

Appendix B: EPA Regional Contacts is a list of people within EPA who can

assist, and offer guidance to, volunteer monitoring programs. Each of the 10
Chapter 1: Introduction 5

Volunteer monitoring

programs are strongly

urged to consult the

references listed in

Appendix C for further

information on quality

assurance/quality control

and the Quality Assurance

Project Plan process.

EPA regions has a volunteer monitoring coordinator as well as QA staff. This

appendix also shows which states and U.S. territories are within each of the 10

regions.

Appendix C: References is a list of documents and

articles relevant to volunteer monitoring and quality

assurance issues. All EPA volunteer monitoring

documents are available by contacting the National

Volunteer Monitoring Coordinator at USEPA. The

address is given in the appendix.

Appendix D: Abbreviated QAPP Form is an example of

the layout and structure of a quality assurance project

plan. Some programs may wish to adapt this form to fit

their plan.

◆◆◆◆◆

This document is not intended as a stand-alone reference

document. Volunteer monitoring programs are strongly

urged to consult the references listed in Appendix C for

further information on quality assurance/quality control and the Quality

Assurance Project Plan process.
6 The Volunteer Monitor’s Guide to Quality Assurance Project Plans
Chapter 2: Developing a QAPP 7

Chapter 2:

DEVELOPING A QAPP

STEPS TO DEVELOPING A

QAPP

step 1: Establish a QAPP team

step 2: Determine the goals & objectives of your project

step 3: Collect background information

step 4: Refine your project

step 5: Design your projects sampling, analytical & data

requirements

step 6: Develop an implementation plan

step 7: Draft your standard operating procedures (SOPs) &

QAPP

step 8: Solicit feedback on your draft SOPs & QAPP

step 9: Revise your QAPP & submit it for final approval

step 10: Begin your monitoring project

step 11: Evaluate and refine your QAPP

he purpose of this chapter is to discuss the steps a volunteer monitoring Tprogram might take in preparing a quality assurance project plan

(QAPP). If your plan does not need to be approved by EPA (that is, you

are not receiving EPA grant or contract money to conduct your monitoring), you

need not submit your QAPP for EPA

approval. In that case, consult your

data users, such as the state or county

water quality agency, regarding their

QAPP requirements. 

Developing a QAPP is a dynamic,

interactive process. Seek as much

feedback as possible from those who

have gone before you in the QAPP

development process. You will be

investing a substantial amount of time

and energy, but don’t be discouraged. 

The person who writes the QAPP is

usually the one who ends up with the

most technical expertise and

monitoring insights. Your efforts will

pay off in a living document that

helps current and future volunteers,

staff, and data users understand

exactly how your project works. 

STEP 1

Establish a small QAPP team

It will be helpful to pull together a small team of two or three people who can

help you develop the QAPP. Include representatives from groups participating in

the monitoring project who have technical expertise in different areas of the

project.

Take the time to establish contact with your state, local or EPA Quality

Assurance Officer, or other experienced volunteer organizations. Remember, if

you are getting any EPA funding through a grant or contract, EPA must approve

your QAPP. However, even if EPA approval isn’t needed, you can consult with
8 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Why are you developing

this monitoring project? 

Who will use its

information, and how will it

be used? If you don't have

answers to these questions,

you may flounder when it

comes time to put your

QAPP down on paper.

EPA QA representatives if you need advice. Let them know a bit about your

project, and find out if they have any resources that might help you out (such as a

copy of an approved volunteer monitoring QAPP, or specific regional guidance

on preparing plans). Also ask your QA contact if he or she would be willing to

review your draft plan. 

STEP 2

Determine the

goals and

objectives of your

project

Why are you developing this

monitoring project? Who will

use its information, and how will

it be used? What will be the basis

for judging the usability of the

data collected? If you don't have

answers to these questions, you

may flounder when it comes time

to put your QAPP down on paper. 

Project goals could include, for example:

= identifying trends in a lake to determine if nuisance

vegetation problems are on the rise 

= monitoring in conjunction with the county health

department to be sure a beach is safe for swimmers

= teaching local elementary schoolers about stream

macroinvertebrates

= monitoring the effectiveness of a stream restoration

project

 

Write down your goal. The more specific your project's

goal, the easier it will be to design a QAPP. Identify the

objectives of your project--that is, the specific statements

of how you will achieve your goal. For example, if your project's goal is to

identify trends in a lake plagued by nuisance vegetation, your objectives might be

to collect three years of data on weed beds, algae, and nutrients, and to develop

yearly reports for nearby lake residents. 
Chapter 2: Developing a QAPP 9

Knowing the use of the

collected data will help

you determine the right

kind of data to collect,

and the level of effort

necessary to collect,

analyze, store, and

report it...Each use of

volunteer data has

potentially different

requirements. 

Knowing the use of the collected data will help you

determine the right kind of data to collect, and the level of

effort necessary to collect, analyze, store, and report it. 

Volunteer monitoring data can be used to screen for

problems, educate youth and the community, supplement

state agency data, help set statewide priorities for pollution

control, and a myriad of other uses. Each use of volunteer

data has potentially different requirements. 

Your project should be designed to meet the needs of your

data users. Data users can include the volunteers

themselves, state water quality analysts, local planning

agencies, parks staff, or many others. You will also

probably need to strike a balance between data quality and

available resources.

STEP 3

Collect background information 

As you learn more about the area you are choosing to monitor, you will be better

able to design an effective monitoring project. Begin by contacting programs and

agencies that might already monitor in your area. Talk to the state water quality

agency, the county and/or city environmental office, local universities, and

neighboring volunteer monitoring programs. Ask about their sampling locations,

what parameters they monitor and what methods they use. 

If they are already monitoring in your chosen area, find out if they will share their

data, and identify what gaps exist that your project could fill. If no monitoring is

ongoing, find out what kind of data your local or state agencies could use (if one

of your goals is that these agencies use your data), where they would prefer you

locate your sampling sites, and what monitoring

methods they recommend. Government

agencies are not likely to use your data

unless it fills a gap in their monitoring

network and was collected using

approved protocols.

A watershed survey can help you set the

foundation for your monitoring project

design. This is simply a practical

investigation of how the watershed works, its

history, and its stressors. For information on

conducting a watershed survey, consult Volunteer

Stream Monitoring: A Methods Manual (Draft,

April 1995, EPA 841-D-95-001).
10 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Once you've collected

background information

for your project and

coordinated with

potential data users, you

may find it necessary to

refine your original

project goals and

objectives.

STEP 4

Refine your project

Once you've collected background information for your project and coordinated

with potential data users, you may find it necessary to refine your original project

goals and objectives. You may have found, for example, that the county already

regularly monitors weed and algae growth in your lake. In

that case, your project might better examine nutrient inputs

from tributaries, lake water clarity, or other parameters. 

Don't hesitate to reevaluate your project goals and

objectives. Now is the best possible time to do so: before

you've invested time, money, and effort in equipment

purchases, training, grant proposals and quality assurance

plan development. 

STEP 5

Design your project’s sampling,

analytical, and data

requirements

Once you feel comfortable with your project's goals and objectives, and have

gathered as much background information as possible on the area you will be

monitoring, it is time to focus on the details of your project. Convene a planning

committee consisting of the project coordinator, key volunteers, scientific

advisors, and data users, along with your QAPP team. This committee should

address the following questions:

= What parameters or conditions will you monitor, and which are most

important to your needs? Which are of secondary importance?

= How good does your monitoring data need to be?

= How will you pick your sampling sites, and how will you identify them over

time?

= What methods or protocols will you use for sampling and analyzing samples?

= When will you conduct the monitoring?

= How will you manage your data and ensure your data are credible?
Chapter 2: Developing a QAPP 11

Your standard operating

procedures (SOPs) are

the details on all the

methods you expect

your volunteers to use. 

This can serve as the

project handbook you

give your volunteers. 

As a general rule, it is a good idea to start small and build to a more ambitious

project as your volunteers and staff grow more experienced.

STEP 6

Develop an implementation plan

You've done the hard part once you've developed your monitoring project design. 

The next step is to decide the particulars -- the logistics, if you will. These are,

essentially, the whos and whens of your project.

Determine who will carry out individual tasks such as volunteer training, data

management, report generation, assuring lab and field quality assurance, and

recruiting volunteers. If you send your samples to an outside lab, choose the lab

and specify why you chose it.

Set up schedules for when you will recruit and train

volunteers, conduct sampling and lab work, produce reports,

and report back to volunteers or the community.

STEP 7

Draft your standard operating

procedures and QAPP

Now it's time to actually write your standard operating

procedures and develop a draft QAPP. Your standard

operating procedures (SOPs) are the details on all the

methods you expect your volunteers to use and can serve as

the project handbook you give your volunteers. Remember,

there are many SOPs already available for sampling and

analytical procedures. Where possible,

adapt your procedures from existing

methods and modify them as needed to fit

your project objectives. Be sure to

reference and cite any existing methods

and documents you use in your project. 

You should append your standard

operating procedures to your QAPP and

refer to them throughout the QAPP

document. Use the elements described in

Chapter 4 as your guide in developing a

draft QAPP. Your written plan can be

elaborate or simple, depending on your project goals.
12 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Based on the comments

you receive from the

review of your draft

plan, you may have to

revise your QAPP.

STEP 8

Solicit feedback on your draft SOPs and

QAPP

Draft QAPP in hand, your next step is to run the draft by people "in the know." 

These are, primarily, state and EPA Regional volunteer monitoring coordinators

and Quality Assurance Officers, EPA project officers, and any other agency data

users (such as a representative from the county planning

office or Natural Resource Conservation Service, if you are

collecting data you hope they will use). Ask for their

feedback and suggestions. Expect their review to take up to

two or three months (times will vary).

While you are waiting for comments, you should probably

try out your procedures with volunteers on a trial basis, to

see if they really work. Don't plan to use the data at this

early stage, however; you will probably be finding quirks in

your plan, and the data will not be accepted by your data

users until the QAPP is approved and accepted. 

You may find that some of your QA contacts resist the idea of reviewing your

draft plan. This is because they are often quite overburdened. Don't give up;

after a reasonable time has elapsed since you submitted your plan, call back and

inquire if you should submit the draft elsewhere for review. Solicit all the

comments you can, from as many sources as possible. 

STEP 9

Revise your QAPP and submit it for final

approval

Based on the comments you receive from the review of your draft plan, you may

have to revise your QAPP. This could involve simply being more specific about

existing methods and quality control procedures in the plan, or actually modifying

your procedures to meet agency requirements. Once you have revised or finetuned your QAPP, submit it to the proper agency for formal approval.

Final review/approval can take a couple of months. During this time, you may be

asked to incorporate additional comments, although this is less likely if you had

previously asked the approving official to review your draft.

Note: If you are developing a QAPP simply to document your methods and are

not working in cooperation with a state, local, or federal agency, you need not

submit a QAPP for review and approval. 
Chapter 2: Developing a QAPP 13

STEP 10

Once the QAPP is approved, begin your

monitoring project

Once you've received EPA and/or state approval of your QAPP, your monitoring

project can begin. Follow the procedures described in your QAPP to train

volunteers and staff, conduct sampling, analyze samples, compile

results, and develop any reports.

STEP 11

Evaluate and refine

your project over time

As time goes on, you may decide to

improve on sampling techniques, site

selection, lab procedures or any of the other elements of your

monitoring project design. Project evaluation should occur

during the course of your project rather than after the project or a

sampling season is completed.

If you make any substantive changes in your QAPP, document them and seek

EPA/state approval for the changes. A phone call to your QA official can help

you determine if the changes require a new QAPP. Also, always be prepared for

formal audits or QC inquiries from data users during the course of your project. 
14 The Volunteer Monitor’s Guide to Quality Assurance Project Plans
Chapter 3: Some Basic QA/QC Concepts 15

Chapter 3:

SOME BASIC QA /QC

CONCEPTS

QA ensures that your

data will meet defined

standards of quality

with a stated level of

confidence.

QC Measures

Internal Quality Control is a set of

measures that the project undertakes

among its own samplers and within its

own lab to identify and correct analytical

errors. Examples include lab analyst

training and certification, proper

equipment calibration and

documentation, laboratory analysis of

samples with known concentrations or

repeated analysis of the same sample, and

collection and analysis of multiple

samples from the field.

External Quality Control is a set of

measures that involves laboratories and

people outside of the program. These

measures include performance audits by

outside personnel, collection of samples

by people outside of the program from a

few of the same sites at the same time as

the volunteers, and splitting some of the

samples for analysis at another lab. 

External and internal QC measures are

described in more detail in the “QC

Samples” box at the end of this chapter.

s coordinator of a volunteer monitoring program, you are probably Ainvolved in many aspects of project planning, sample collection,

laboratory analysis, data review, and data assessment. You should be

considering quality assurance and quality control activities in every one of these

steps. 

Quality assurance (QA) refers to the overall management

system which includes the organization, planning, data

collection, quality control, documentation, evaluation, and

reporting activities of your group. QA provides the

information you need to ascertain the quality of your data

and whether it meets the requirements of your project. QA

ensures that your data will meet defined standards of quality

with a stated level of confidence.

Quality control (QC) refers to the routine technical activities

whose purpose is, essentially, error control. Since errors

can occur in either the field, the laboratory or in the

office, QC must be part of each of these functions. QC

should include both internal and external measures (see

side box).

Together, QA and QC help you produce data of known

quality, enhance the credibility of your group in

reporting monitoring results, and ultimately save time

and money. However, a good QA/QC program is only

successful if everyone consents to follow it and if all

project components are available in writing. The Quality

Assurance Project Plan (QAPP) is the written record of

your QA/QC program.

This chapter is designed to introduce you to the

terminology of quality assurance/quality control. The

key terms we will be addressing are: precision, accuracy

(sometimes referred to as bias), representativeness,

completeness, comparability, and sensitivity. You will
16 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Measures of precision,

accuracy,

representativeness,

completeness,

comparability, and

sensitivity help us

evaluate sources of

variability and error and

thereby increase

confidence in our data.

be seeing these terms again, so you may want to spend some

time getting to know them. 

In natural systems, such as streams, lakes, estuaries, and

wetlands, variability is a factor of life. Changes in

temperature, flow, sunlight, and many other factors affect

these systems and the animals that inhabit them. Variability

also occurs when we attempt to monitor such systems. Each

of us reads, measures, and interprets differently; we may

also apply different levels of effort in how we monitor. The

equipment we use may be contaminated, broken or

incorrectly calibrated. These and many other differences

can lead to variability in monitoring results. Measures of

precision, accuracy, representativeness, completeness,

comparability, and sensitivity help us evaluate sources of

variability and error and thereby increase confidence in our

data.

Because all projects have different goals, data users and uses, capabilities, and

methods, this document cannot tell you what levels of precision, accuracy,

representativeness, completeness, comparability, and sensitivity are acceptable for

your individual project. You will need to consult your advisory panel (in

particular, your data users), the laboratory you deal with, and peer reviewers to

determine acceptance criteria for your

monitoring project.

Precision

Precision is the degree of agreement

among repeated measurements of the

same characteristic on the same

sample or on separate samples

collected as close as possible in time

and place. It tells you how consistent

and reproducible your field or

laboratory methods are by showing

you how close your measurements are

to each other. It does not mean that

the sample results actually reflect the

"true" value, but rather that your

sampling and analysis are giving

consistent results under similar

conditions. 

Typically, precision is monitored

through the use of replicate samples or
s

n

i 1

(X1 X)

2

n 1

RSD s

X

×100 RPD

(X1 X2)×100

(X1 X2

)÷2

Chapter 3: Some Basic QA/QC Concepts 17

STANDARD DEVIATION

The Volunteer Creek Monitoring Project wants to determine the

precision of its temperature assessment procedure. They have

taken 4 replicate samples:

Replicate 1 (X1) = 21.1 C0

Replicate 2 (X2) = 21.1 C0

Replicate 3 (X3) = 20.5 C0

Replicate 4 (X4) = 20.0 C0

To determine the Standard Deviation (s), use the following

formula:

where x = measured value of i

the replicate, x = mean of

replicate measurements, n =

number of replicates, = the

sum of the calculations for each

measurement value--in this case,

X1 through X4

First, figure out the mean, or

average of the sample measurements. Mean = (X + X + X + X ) 1 2 3 4

÷ 4. In this example, the mean is equal to 20.68 C. 0

Then, for each sample measurement (X1 through X4), calculate the

next part of the formula. For X1 and X2, the calculation would

look like this:

(21.1 - 20.68) = (-0.42) = 0.1764 = 0.0588 2 2

4-1 3 3

For X3 the calculation would be 0.0108; and for X4 it would be

0.1541

Finally, add together the calculations for each measurement and

find the square root of the sum: 0.0588 + 0.0588 + 0.0108 +

0.1541 = 0.2825. The square root of 0.2825 is 0.5315.

So, the standard deviation for temperature is 0.532 (rounded off).

RELATIVE STANDARD

DEVIATION

If we use the same replicate measurements as

above in the standard deviation example, we

can determine the Relative Standard

Deviation (RSD), or coefficient of variation,

using the following formula:

where s =

standard

deviation and x

 = mean of

replicate 

samples. 

We know s = 0.5315 and that x = 20.68. So,

the RSD = 2.57. This means that our

measurements deviate by about 2.57%.

RELATIVE PERCENT

DIFFERENCE

If the Volunteer Creek project had only two replicates (21.1 C0

and 20.5 C) they would use Relative Percent Difference (RPD) 0

to determine precision. 

where X = the larger of 1

the two values and X2 =

the smaller of the two

values. In this example,

X = 21.1 and X = 20.5 . 1 2

0 0

RPD = (21.1-20.5) x 100 = 60.00 = 2.88

(21.1+20.5) ÷ 2 20.8

So, in this example, the RPD between our sample measurements is

2.88%. 

measurements. Replicate samples are

two or more samples taken from the

same place at the same time.

When you have many replicate

samples, determine precision by

calculating the standard deviation(s)

of the samples. The standard

deviation indicates the range of

variation in the measurements you've

taken. Many of today's calculators

perform the standard deviation

calculation. 

The relative standard deviation

(RSD), or coefficient of variation,

expresses the standard deviation as a

percentage. This is generally easier

for others to understand. The smaller

the relative standard deviation (or

standard deviation), the more precise

your measurements.

When you have only two replicate

samples, determine precision by

calculating the relative percent

difference (RPD) of the two samples. 

Again, the smaller the relative percent

difference, the more precise your

measurements.
Inaccurate Inaccurate

Accurate Inaccurate

18 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

ACCURACY

Attendance at QC training sessions is required for Volunteer

Creek monitors. In the field, monitors use a Jones Wide-Range

pH Kit, which covers a full range of expected pH values. During

a recent training session, the monitors recorded the following

results when testing a pH standard buffer solution of 7.0 units.

7.5

7.4

6.7

7.2

6.8

7.3

6.5

7.2

6.8

7.0

7.4

7.2

Accuracy = average value - true value

The average of these measurements is equal to 7.08 units. Since

we know that the reference or “true” value is 7.0 units, the

difference between the average pH value is off or biased by + 0.08

units. This level of accuracy is satisfactory for the data quality

objectives of the project.

PRECISION, BIAS, AND

ACCURACY

Accuracy

Accuracy is a measure of confidence in a measurement. The smaller the

difference between the measurement of a parameter and its "true" or expected

value, the more accurate the

measurement. The more precise or

reproducible the result, the more

reliable or accurate the result.

Measurement accuracy can be

determined by comparing a sample

that has a known value, such as a

standard reference material or a

performance evaluation sample, to a

volunteer's measurement of that

sample (see note below). 

Increasingly, however, some

scientists, especially those involved

with statistical analysis of

measurement data, have begun to use

the term "bias" to reflect this error in

the measurement system and to use

"accuracy" as indicating both the

degree of precision and bias (see

"bullseye" figure at left). For the

purpose of this document, the term

"accuracy" will be used.

If you are concerned that other components of a sample matrix (e.g., soil or

sludge) may be interfering with analysis of a parameter, one way to measure

accuracy is to add a known concentration of the parameter to a portion of the

sample. This is called a spiked

sample. The difference between the

original measurement of the

parameter in the sample and the

measurement of the spiked sample

should equal (or be close to) the added

amount. The difference indicates

your ability to obtain an accurate

measurement. 

For many parameters such as secchi

depth and macroinvertebrate

abundance, no standard reference or

performance evaluation samples exist. 

In these cases, the trainer's results may

be considered the reference value to
Chapter 3: Some Basic QA/QC Concepts 19

which the volunteer's results are compared. This

process will help evaluate if the volunteer

measurements are biased as compared to the

trainer's.

If you are monitoring biological conditions by

collecting and identifying specimens, maintaining

a voucher collection is a good way to determine if

your identification procedures are accurate. The

voucher collection is a preserved archive of the

organisms your volunteers have collected and

identified. An expert taxonomist can then provide a "true"

value by checking the identification in the voucher collection.

It is important to note that the relationship between a voucher

collection and accurate identification cannot be expressed

numerically in your QAPP. Rather, the QAPP document should

indicate that you have a voucher collection and describe how it is

used to evaluate consistent accurate identification in your

program.

Note: Standard reference material (in the form of solids or solutions with a

certified known concentration of pollutant) can be obtained from a variety of

companies, including the National Institute of Standard and Technologies, that

sell quality control, proficiency, or scientific reference materials.

Representativeness

Representativeness is the extent to which measurements actually depict the true

environmental condition or population you are evaluating. A number of factors

may affect the representativeness of your data. For instance, are your sampling

locations indicative of the waterbody? Data collected just below a pipe outfall is 

not representative of an entire stream. Minimizing the effects of variation is

critical in the development of your sampling design.

Completeness

Completeness is a measure of the number of samples you must take to be able to

use the information, as compared to the number of samples you originally

planned to take. Since there are many reasons why your volunteers may not

collect as many samples as planned, as a general rule you should try to take more

samples than you determine you actually need. This issue should be discussed

within your QAPP team and by peer reviewers before field activities begin.
%C=

v

T

x100

20 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

COMPLETENESS

The Volunteer Creek Monitoring project planned to collect 20

samples, but because of volunteer illness and a severe storm, only

17 samples were actually collected. Furthermore, of these, two

samples were judged invalid because too much time elapsed

between sample collection and lab analysis. Thus, of the 20

samples planned, only 15 were judged valid. 

The following formula is used to determine Percent

Completeness (%C).

where v = the number of planned

measurements judged valid and T = the

total number of measurements.

In this example, v = 15 and T = 20. In

this case, percent completeness would

be 75 percent. Is this enough information to be useful? 

To calculate percent completeness,

divide the number of measurements

that have been judged valid by the

total number of measurements you

originally planned to take and then

multiply by 100. 

Remember, completeness

requirements can be lowered if extra

samples are factored into the project. 

The extra samples in turn, increase the

likelihood of more representative data.

Comparability

Comparability is the extent to which

data from one study can be compared

directly to either past data from the current project or data from another study. 

For example, you may wish to compare two seasons of summer data from your

project or compare your summer data set to one collected 10 years ago by state

biologists.

Using standardized sampling and analytical methods, units of reporting, and site

selection procedures helps ensure comparability. 

However, it is important to keep in mind that some

types of monitoring rely heavily on best professional

judgement and that standard methods may not always

exist.

Detection Limit

The term detection limit can apply to monitoring and

analytical instruments as well as to methods. In general,

detection limit is defined as the lowest concentration of

a given pollutant your methods or equipment can detect

and report as greater than zero. Readings that fall below the detection limit are

too unreliable to use in your data set. Furthermore, as readings approach the

detection limit (that is, as they go from higher, easier-to-detect concentrations to

lower, harder-to-detect concentrations) they become less and less reliable. 

Manufacturers generally provide detection limit information with high-grade

monitoring equipment such as meters.

Measurement Range

The measurement range is the range of reliable measurements of an instrument or

measuring device. Preassembled kits usually come with information indicating
Chapter 3: Some Basic QA/QC Concepts 21

The general rule is that 

10% of samples should

be quality control (QC)

samples.

the measurement range that applies. For example, you might

purchase a kit that is capable of detecting pH falling between 6.1

and 8.1. However, pH can theoretically range from 0.0 to 14.00. 

If acidic conditions (below 6) are a problem in the waters you

are monitoring, you will need to use a kit or meter that is

sensitive to the lower pH ranges.

Quality Control (QC) Samples

Contamination is a common source of error in both sampling

and analytical procedures. QC samples help you identify when

and how contamination might occur. For most projects, there is

no set number of field or laboratory QC samples which must be

taken. The general rule is that 10% of samples should be QC

samples. This means that if 20 samples are

collected, at least one additional sample must

be added as a QC sample. The laboratory

must also run its own QC samples. For a new

monitoring project or for a new analytical

procedure, it is a good idea to increase the

number of QC samples

(up to 20%) until you

have full confidence in

the procedures you are

using. 

When the project is over, determine data quality by

evaluating the results of all the QC samples and determining

precision and accuracy. For QC samples that are not blind

to the lab, require the lab to calculate and report precision and accuracy results. 

Lab reported precision and accuracy results can then be checked during data

validation. 

The decision to accept data, reject it, or accept only a portion of it is should be

made after analysis of all QC data. Various types of QC samples are described in

the box on the next page.
22 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

QC SAMPLES

 

= A field blank is a “clean” sample, produced

in the field, used to detect analytical 

problems during the whole process

(sampling, transport, and lab analysis). To

create a field blank, take a clean sampling

container with "clean" water (i.e., distilled

or deionized water that does not contain

any of the substance you are analyzing

for) to the sampling site. Other sampling

containers will be filled with water from

the site. Except for the type of water in

them, the field blank and all site samples

should be handled and treated in the same

way. For example, if your method calls

for the addition of a preservative, this

should be added to the field blank in the

same manner as in the other samples.

When the field blank is analyzed, it

should read as analyte-free or, at a

minimum, the reading should be a

factor of 5 below all sample results. 

= An equipment or rinsate blank is a

“clean” sample used to check the

cleanliness of sample collection

equipment. This type of blank is

used to evaluate if there is

carryover contamination from reuse

of the same sampling equipment. 

A sample of distilled water is

collected in a sample container

using regular collection

equipment and analyzed as a

sample. 

= A split sample is one sample that is divided

equally into two or more sample containers

and then analyzed by different analysts or

labs. Split samples are used to measure

precision. Samples should be thoroughly

mixed before they are divided. Large errors

can occur if the analyte is not equally

distributed into the two containers. A

sample can be split in the field, called a field

split, or in the laboratory, a lab split. The

lab split measures analytical precision while

the field split measures both analytical and

field sampling precision. In addition, a

sample split in the field and submitted to the

laboratory without informing the laboratory

represents a blind sample. Split samples can

also be submitted to two different

laboratories for analysis to measure the

variability in results between laboratories

independently using the same analytical

procedures. 

= Replicate samples are obtained when two

or more samples are taken from the same

site, at the same time, using the same

method, and independently analyzed in

the same manner. When only two

samples are taken, they are sometimes

referred to as duplicate samples. These

types of samples are representative of the

same environmental condition.

Replicates (or duplicates) can be used to

detect both the natural variability in the

environment and that caused by field

sampling methods.

= Spiked samples are samples to

which a known concentration of the

analyte of interest has been added. 

Spiked samples are used to

measure accuracy. If this is done in

the field, the results reflect the

effects of preservation, shipping,

laboratory preparation, and

analysis. If done in the laboratory,

they reflect the effects of the

analysis from the point when the

compound is added, e.g. just prior

to the measurement step. Percent

recovery of the spike material is

used to calculate analytical accuracy.
Chapter 4: Elements of a QAPP 23

Chapter 4:

ELEMENTS OF A QAPP

ELEMENTS OF A QAPP

Project Management (elements 1-9)

1. Title and Approval Page

2. Table of Contents

3. Distribution List

4. Project/Task Organization

5. Problem Identification/ Background

6. Project/Task Description

7. Data Quality Objectives for Measurement Data

8. Training Requirements/ Certification

9. Documentation and Records

Measurement/Data Acquisition (elements 10-19)

10. Sampling Process Design

11. Sampling Methods Requirements

12. Sample Handling and Custody Requirements

13. Analytical Methods Requirements

14. Quality Control Requirements

15. Instrument/Equipment Testing, Inspection, and

Maintenance Requirements

16. Instrument Calibration and Frequency

17. Inspection/Acceptance Requirements for Supplies

18. Data Acquisition Requirements

19. Data Management

Assessment and Oversight (elements 20-21)

20. Assessment and Response Actions

21. Reports

Data Validation and Usability (elements 22-24)

22. Data Review, Validation, and Verification

Requirements

23. Validation and Verification Methods

24. Reconciliation with Data Quality Objectives

his chapter discusses the 24 elements of a Quality Assurance Project Plan, Tas outlined in EPA quality assurance guidance, EPA Requirements for

Quality Assurance Project Plans for Environmental Data Operations

(EPA QA/R-5, August 1994). It is very likely that not all elements will apply to

your project. This is an issue that should be discussed with your QAPP team and

any group who will be approving the QAPP. If your project does not require all

24 elements, indicate in your QAPP which elements you will not be including. 

This will make review and approval of your QAPP faster and easier.

Throughout this chapter, brief examples are included. The examples are drawn

from a fictional monitoring project--the Volunteer Creek Monitoring Project. 

They are not intended to be

comprehensive, but rather simply to

help illustrate the type of information

that might be included in the elements

of a QAPP. For more information, you

may wish to contact other volunteer

monitoring programs with approved

QAPPs.

TITLE AND 1 APPROVAL PAGE

Your title page should include the

following:

= title and date of the QAPP

= names of the organizations

involved in the project

= names, titles, signatures, and

document signature dates of all

appropriate approving officials

such as project manager, project

QA officer, and, if the project is

funded by EPA, the EPA project

manager and QA officer.
PROJECT MANAGER

Lucy Nugent

Volunteer Creek

Watershed Association

FIELD LEADER

Sam Gracey

Volunter Creek

Watershed Association

LABORATORY LEADER

Tessa Berry

Professor of Biology

at State University

DATA PROCESSING

LEADER

Zoe Ruben

Volunteer Creek

Watershed Association

QA OFFICER

Rufus Tabs

County Department

of Public Works

QA OFFICER

Tessa Berry

Professor of Biology

at State University

24 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 4 

Project/Task Organization 

In addition to the project officers shown, the

Volunteer Creek Monitoring Project also has an

Advisory Panel consisting of representatives

from EPA, the state Department of

Environmental Conservation (DEC), and the

County Department of Public Works (DPW). 

Each of the leaders shown serves on the

Advisory Panel. Major responsibilities of all

personnel are detailed in the Volunteer Creek

SOPs, attached to this document. The primary

data users are the state DEC and the County

DPW.

TABLE OF CONTENTS 2 A Table of Contents should include section headings with appropriate

page numbers and a list of figures and tables.

DISTRIBUTION LIST 3 List the individuals and organizations that will receive a copy of your

approved QAPP and any subsequent revisions. Include representatives

of all groups involved in your monitoring effort.

PROJECT / 4 TASK

ORGANIZATION

Identify all key personnel

and organizations that are

involved in your program,

including data users. List

their specific roles and

responsibilities. In many

monitoring projects, one

individual may have

several responsibilities. 

An organizational chart is

a good way to graphically

display the roles of key

players.
Chapter 4: Elements of a QAPP 25

 ELEMENT 5

Problem Definition/Background 

Volunteer Creek flows through an urbanizing watershed. As more communities are built, the quantity of

stormwater runoff will increase. Working together, local residents and government agencies have developed

plans to implement best management practices, or BMPs, designed to minimize the potential negative water

quality impacts to Volunteer Creek.

The organizers of the monitoring project, including the Volunteer Creek Watershed Association, the County

Department of Public Works and the State Department of Natural Resources, want to document conditions of

the stream before and after development to evaluate the effects of stormwater management BMPs. 

The data collected will be used by the county and state to evaluate how well these BMPs are working and to

help identify specific problems that require further attention or study. The watershed association will also use

the data to educate residents on the connections between land-use and water quality.

PROBLEM DEFINITION / BACKGROUND 5 In a narrative, briefly state the problem your monitoring project is

designed to address. Include any background information such as

previous studies that indicate why this project is needed. Identify how your data

will be used and who will use it. 

PROJECT /TASK DESCRIPTION 6 In general terms, describe the work your volunteers will perform and

where it will take place. Identify what kinds of samples will be taken,

what kinds of conditions they will measure, which are critical, and which are of

secondary importance. Indicate how you will evaluate your results--that is, how

you will be making sense out of what you find. For example, you may be

comparing your water quality readings to State or EPA standards, or comparing

your macroinvertebrate evaluations to State-established reference conditions or

historical information. 
MAJOR TASK CATEGORIES J F M A M J J A S O N D

volunteer recruitment, training, and re-training X X X X X X

monthly pH, temp., turbidity, & dissolved oxygen sampling X X X X X X X X X X X X

seasonal macroinvertebrate & habitat assessments X X X

lab analysis X X X

data processing, analysis & reporting X X X X X X

26 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 6

Project/Task Description 

From January through March 1996, the Watershed Association will conduct initial volunteer recruitment and

training in conjunction with the county and state. A second recruitment drive as well as training and retraining

sessions will be held from August to October. 

Monthly water sampling of temperature, pH, turbidity, and dissolved oxygen will occur throughout the calendar

year at each of 20 sites. At the same sites, macroinvertebrate and habitat assessments will be conducted in

March, July, and October. In order to characterize the stream and to create a baseline of data, each of these

evaluations is a critical component of the overall study. For informational and educational purposes, volunteers

will also record characteristics such as water odor and color during each assessment. Macroinvertebrate

taxonomy will take place in April, August, and November at the state university biology laboratory.

Following each assessment, all data will be entered into the computerized management system and analyzed. 

Interim report of findings will be produced and distributed in May and September. A final, year-end report will

be produced and distributed in January 1997.

Include an overall project timetable that outlines beginning and ending dates for

the entire project as well as for specific activities within the project. The

timetable should include information about sampling frequency, lab schedules,

and reporting cycles.

DATA QUALITY OBJECTIVES FOR 7 MEASUREMENT DATA

Data Quality Objectives (DQOs) are the quantitative and qualitative terms you

use to describe how good your data need to be to meet your project's objectives. 

DQOs for measurement data (referred to here as data quality indicators) are

precision, accuracy, representativeness, completeness, comparability, and

measurement range. Provide information on these indicators, in quantitative

terms if possible. See Chapter 3 for a further discussion of these terms.

Since it is important to develop a QAPP prior to monitoring, it may not be

possible to include actual numbers for some of the data quality measurements
Matrix Parameter Precision Accuracy MR*

water pH ±20% ±0.5 3 to 10.5 units

water temperature ±20%

water dissolved oxygen ±20% ±0.3mg/L 1 to 20 mg/l

water turbidity ±20% ±0.2mg/L 0 to 1000 NTU

Chapter 4: Elements of a QAPP 27

 ELEMENT 7

Data Quality Objectives for 

Measurement Data 

Precision, Accuracy, Measurement Range

The following table illustrates the precision, accuracy and

measurement range for the Volunteer Creek pH, temperature,

turbidity, and dissolved oxygen assessments.

* MR = measurement range

Representativeness

In the Volunteer Creek project's assessment, representativeness

depends largely on randomized sampling. The creek is a highgradient stream with a predominance of riffle habitats. Monitoring

sites selected for this study are indicative of that habitat type and the

program uses sampling techniques developed for high-gradient

streams. In addition, for the macroinvertebrate collection, volunteers

sample at three locations within the riffle and then composite

(combine) the samples so as to be more generally reflective of the

entire riffle habitat.

Comparability

One of the ways that the Volunteer Creek program ensures

comparability is to follow the monitoring protocol established by the

State for assessment and analysis. Volunteers also use standardized

taxonomic keys to identify macroinvertebrates to the family level. 

Completeness

There are no legal or compliance uses anticipated for the Volunteer

Creek data. In addition, there is no fraction of the planned data that

must be collected in order to fulfill a statistical criteria. It is expected

that samples will be collected from at least 90% of the sites unless

unanticipated weather conditions prevent sampling.

within the first version of the

document. You will need,

however, to discuss your goals

or objectives for data quality

and the methods you will use

to make actual determinations

after monitoring has begun. 

You must also discuss at what

point changes will be made if

project specifications are not

achieved. Data quality

indicators should be given for

each parameter you are

measuring, in each "matrix"

(i.e., substance you are

sampling from, such as water

or sediment). The easiest way

to present quantitative

information is in a table. 

In some types of monitoring, 

particularly macroinvertebrate

monitoring and habitat

assessment, some data quality

indicators cannot be

quantitatively expressed. In

that case, you can fulfill this

requirement of the QAPP by

citing and describing the

method used and by providing

as many of the data quality

indicators as possible (e.g.,

completeness, 

representativeness, and

comparability) in narrative

form.

Precision is the degree of

agreement among repeated

measurements of the same

characteristic, or parameter, and gives information about the consistency of your

methods.

Accuracy is a measure of confidence that describes how close a measurement is

to its “true” value.
28 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 8

Training Requirements/ 

 Certification 

Volunteer Creek monitors participate in a two-day field

training course conducted by state and local water quality

personnel. On the first day, volunteers are instructed

how to calibrate equipment and perform physical and

chemical tests and analyses. The second day is devoted to

macroinvertebrate and habitat sampling. Volunteers for

the taxonomy lab receive a separate day of training. All

participants are required to attend an annual refresher

course as well.

Performance is evaluated in the field and the lab. During

initial and renewal training sessions, volunteers perform

a simultaneous dip-in determination of pH, temperature, 

and dissolved oxygen. Volunteers also determine

turbidity levels of water samples using meters at the lab. 

In addition, during training, participants conduct

macroinvertebrate sampling in small groups with

trainers. To evaluate volunteer skill in the taxonomy lab,

volunteers are trained and re-trained using previously

identified samples from earlier assessments.

Volunteer Creek

Monitoring Project

__________

Training Session

9:00 am

TODAY

Measurement Range is the range of

reliable readings of an instrument or

measuring device, as specified by the

manufacturer.

Representativeness is the extent to which

measurements actually represent the true

environmental condition.

Comparability is the degree to which data

can be compared directly to similar

studies. Using standardized sampling,

analytical methods, and units of reporting

helps to ensure comparability.

Completeness is the comparison between

the amount of data you planned to collect

versus how much usable data you

collected, expressed as a percentage.

TRAINING REQUIREMENTS / CERTIFICATION 8 Identify any specialized training or certification requirements your

volunteers will need to successfully

complete their tasks. Discuss how

you will provide such training, who

will be conducting the training, and

how you will evaluate volunteer

performance.
Site #: Site Location:

Date: / / Time: AM PM

Team Captain: Phone #:

Address:

Other Monitoring Team Members:

VOLUNTEER CREEK MONITORING PROJECT

Chapter 4: Elements of a QAPP 29

 ELEMENT 9

Documentation and Records 

Each Volunteer Creek field sampling sheet must be completed on-site at the time sampling occurs. Volunteers

record site number, location, the date and time the sample was collected, and the name of each team member. 

Contact information for the team captain or monitor responsible for returning field sheets and

macroinvertebrate samples to the watershed association office is also included on each field sheet.

Volunteers make a copy of each field sheet and keep the copy with their records. The original is returned to the

Volunteer Creek Watershed Association office along with the macroinvertebrate sample (if taken). Field sheets

are archived for three years. After macroinvertebrate samples have been identified, laboratory record sheets are

maintained in the watershed association office for three years. Hard copies of all data as well as computer

back-up disks are

maintained by the

Association. A

macroinvertebrate

voucher collection is

maintained by the

state university

biology lab for five

years.

DOCUMENTATION AND RECORDS 9 Identify the field and laboratory information and records you need for

this project. These records may include raw data, QC checks, field data

sheets, laboratory forms, and voucher collections. Include information on how

long, and where, records will be maintained. Copies of all forms to be used in the

project should be attached to the QAPP.
Happy Lakes Community

Townhouses

Happy Lake

Site #2

Site #1

Volunteer Creek Blvd. Site #3

Volunteer Park

Picnic Area

Site #4

Urban Creek

Volunteer Creek

30 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 10

Sampling Process Design 

Volunteer Creek monitoring sites are sampled monthly for pH, temperature, turbidity, and dissolved oxygen. In

March, July and October, a macroinvertebrate and habitat assessment is conducted at each site. Monitoring sites are

identified by a number and a location. 

If possible, volunteers are asked to wait at least 10 days after a heavy rain or snowfall before sampling. If this is not

possible, they are instructed to contact the Field Leader so that this information can be noted immediately. In

addition, if volunteers cannot conduct the scheduled sampling, they are instructed to contact the Field Leader as

soon as possible, so that an alternative monitor can be found. Volunteers are instructed to work in teams of at least

two people. Three team members are recommended for the macroinvertebrate sampling. If a scheduled team

cannot conduct the sampling together, the team captain

is instructed to contact the Field Leader so that

arrangements can be made for a substitute.

Prior to final site selection, permission to access

the stream is obtained from all property owners. 

If for some reason access to the site is a problem,

the team captain is instructed to contact the Field

Leader. All constraints and safety plans are

detailed in the Volunteer Creek SOPs.

Four, or 20%, of the sampling sites surround

Volunteer Creek Boulevard, which is being

widened to accommodate growing residential and

commercial development. They are located as

follows:

Site #1 adjacent to the new townhome

development in the Happy Lakes

Community

Site #2 downstream of the confluence with Urban

Creek

Site #3 at the crossing of Volunteer Creek

Boulevard

Site #4 within Volunteer Park, adjacent to the

picnic area

SAMPLING PROCESS DESIGN 10 Outline the experimental design of the project including

information on types of samples required, sampling frequency,

sampling period (e.g., season), and how you will select sample sites and identify

them over time. Indicate whether any constraints such as weather, seasonal

variations, stream flow or site access might affect scheduled activities, and how

you will handle those constraints. Include site safety plans. You may cite the

sections of your program's SOPs which detail the sampling design of the project,

in place of extensive discussion.
Matrix Parameter Sampling 

Equipment

Sample Holding 

Container

Method 

Sample 

Preservative

Maximum 

Holding Time

water pH Jones pH color 

comparator kits

screw top, glass 

sample bottle

none immediately

water temperature Smith armored 

thermometer

none, measurement 

taken instream

none immediately

water dissolved oxygen Jones DO kit screw top, glass 

sample bottle

none immediately

water turbidity Jones turbidity meter screw top glass 

sample bottle

store on ice 48 hours

substrate macroinvertebrates 3' X 3' kicknet; 500 

micron mesh

1 liter plastic 

wide-mouth bottle

90% ethyl 

alcohol

6 weeks

Chapter 4: Elements of a QAPP 31

 ELEMENT 11

Sampling Methods Requirements 

The Volunteer Creek SOP, attached to this document, contains detailed information on all sampling protocols

and equipment. The table below summarizes a portion of this information.

SAMPLING METHODS REQUIREMENTS 11 Describe your sampling methods. Include information on

parameters to be sampled, how samples will be taken, equipment

and containers used, sample preservation methods

used, and holding times (time between taking

samples and analyzing them). If samples are

composited (i.e., mixed), describe how this will

be done. Describe

procedures for

decontamination

and equipmentcleaning. (For

example, kick nets

need to be

thoroughly rinsed

and examined for clinging organisms between

sampling events.) Most of this information can be

presented in a table or you may also cite any SOPs

that contain this information.
VOLUNTEER CREEK PROJECT

MACROINVERTEBRATE SAMPLE LABEL

FIELD INFORMATION:

Site #: Location: 

Sample Number of 

Preservation Method: Gear: 

Date: / / Time: AM PM

Team Captain: 

Phone #: 

LAB INFORMATION:

Date: / / Time: AM PM

Analyst: 

Phone #: 

32 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 12

Sample Handling and Custody Requirements 

All macroinvertebrate samples collected as part of the

Volunteer Creek project are labeled in the field. The

chain-of-custody for these samples is as follows: In

the field, samples are the responsibility of, and stay

with, the team captain. Once samples have been

collected they are returned, by the monitoring team

captain, to the Volunteer Creek Watershed

Association office for temporary storage. The date

and time of arrival is recorded by the Field Leader

who is then responsible for transporting samples to

the university laboratory for analysis. The date and

time of arrival is also recorded at the lab by the

Laboratory Leader. After samples are analyzed,

laboratory information is added to the label. Samples

are then stored and maintained in the university's

biological lab for a minimum of three years. A chainof-custody form is used to record all transport and

storage information

SAMPLE HANDLING AND CUSTODY 12 REQUIREMENTS

Sample handling procedures apply to projects that bring samples from the field to

the lab for analysis, identification, or storage. 

These samples should be properly

labeled in the field. At a

minimum, the sample identification

label should include sample

location, sample number, date and

time of collection, sample type,

sampler's name, and method used

to preserve sample.

Describe the procedures used to

keep track of samples that will be

delivered or shipped to a laboratory for analysis. Include any chain-of-custody

forms and written procedures field crews and lab personnel should follow when

collecting, transferring, storing, analyzing, and disposing of samples. 
Chapter 4: Elements of a QAPP 33

 ELEMENT 13 

Analytical Methods 

Requirements 

In the Volunteer Creek project, pH, temperature and

dissolved oxygen are measured using protocols

outlined in the Citizen's Program for the Chesapeake

Bay's Citizen Monitoring Manual. Protocols for

measuring turbidity come from the EPA document,

Volunteer Stream Monitoring: A Methods Manual. 

Macroinvertebrate and habitat assessment methods and

equipment are based on the protocols established by

the state monitoring program. Each of these protocols

is detailed in the Volunteer Creek SOP, attached to this

document.

 ELEMENT 14 

Quality Control Requirements 

Replicate samples for all measurement parameters are

taken at three (randomly selected) sites of the 20

Volunteer Creek monitoring sites during each

sampling period (i.e. monthly for pH, temperature,

turbidity, and dissolved oxygen and seasonally for

macroinvertebrates). Additional QC samples include 

split samples and field blanks, each taken at 10% of the

sites.

In addition, at least three of the macroinvertebrate

samples will be reidentified by the laboratory leader

during each lab session. Both a macroinvertebrate

voucher and reference collection will be maintained. If

sampler problems are found, the data is either thrownout or qualified, depending on the degree of the

problem, and arrangements made for monitor

retraining. All volunteers are retrained at least once a

year in both field and lab procedures by professional

personnel. 

ANALYTICAL METHODS REQUIREMENTS 13 List the analytical methods and equipment needed for the analysis

of each parameter, either in the field or the lab. If your program

uses standard methods, cite

these. If your program's

methods differ from the

standard or are not readily

available in a standard

reference, describe the

analytical methods or cite

and attach the program's

SOPs.

QUALITY CONTROL REQUIREMENTS 14 List the number and

types of field and

laboratory quality control samples

your volunteers will take. (See

Chapter 3 for a discussion of quality

control samples.) This information

can be presented in a table. If you use

an outside laboratory, cite or attach

the lab's QA/QC plan.

QC checks for biological monitoring

programs can be described

narratively, and, if appropriate, should

include discussion of replicate sample

collection, cross checks by different

field crews, periodic sorting checks of

lab samples, and maintenance of

voucher and reference collections. 

Describe what actions you will take if

the QC samples reveal a sampling or

analytical problem. 
34 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 15 

Instrument/Equipment Testing, 

Inspection, and Maintenance 

Requirements 

As part of its instrument and equipment maintenance, the Volunteer Creek project performs a variety of tests. 

Before usage, the mercury column of each thermometer is inspected for breaks. Replacement thermometers

are available from the Field Leader at the Watershed Association office. All pH and DO kits are checked to be

sure all reagents, bottles, droppers, and color comparators are clean and in good working order. Reagents are

replaced annually according to manufacturer's recommendations. Reagents and replacement bottles are

available from the Field Leader. The turbidity meters are inspected by the Lab Manager prior to each

sampling event and maintenance logs are kept on each meter. The Field Leader maintains a maintenance log

book to track scheduled maintenance on all equipment. All records and equipment are held at the Volunteer

Creek Watershed Association offices.

 ELEMENT 16 

Instrument Calibration 

and Frequency 

The Volunteer Creek project’s turbidity meters will be

calibrated, prior to each sampling event, according to

the manufacturer’s instructions and using the

manufacturer's turbidity standards. Calibration results

are recorded in a log book and maintained by the Lab

Manager. Calibration procedures and standards are

contained in the SOP manual, available upon request.

INSTRUMENT / 15 EQUIPMENT

TESTING, INSPECTION ,

AND MAINTENANCE

REQUIREMENTS

Describe your plan for routine inspection

and preventive maintenance of field and

lab equipment and facilities. Identify what

equipment will be routinely inspected, and

what spare parts and replacement equipment will be on hand to keep field and lab

operations running smoothly. Include an equipment maintenance schedule, if

appropriate.

INSTRUMENT CALIBRATION AND 16 FREQUENCY

Identify how you will

calibrate sampling and

analytical instruments. 

Include information on

how frequently

instruments will be

calibrated, and the types

of standards or certified

equipment that will be

used to calibrate

sampling instruments. 

Indicate how you will

maintain calibration
Chapter 4: Elements of a QAPP 35

 ELEMENT 17

Inspection and Acceptance 

Requirements for Supplies 

The Volunteer Creek project uses kick-nets for

macroinvertebrate assessments. The nets are 3' X 3'

attached to cylindrical wooden poles. The mesh used

is 500 micron and is consistent with that used by the

state monitoring program. Netting, cut into

appropriate size squares, is purchased from a scientific

supply house. Poles and hardware are purchased from

a local supplier. All supplies and equipment are

purchased under the supervision of the Field Leader.

Nets are assembled by shop students at Volunteer

Creek High School. After assembly, all nets are

inspected by the Field Leader. Any net that does not

meet standards is taken apart and reassembled, if

possible. Nets that cannot be reassembled are used for

educational demonstrations. Kits and extra reagents

are ordered from Smith and Jones Chemical Supply

Company and inspected upon arrival by the Field

Leader. Broken bottles and incomplete kits are

shipped back to the manufacturer for replacement.

 ELEMENT 18

Data Acquisition Requirements 

For the Volunteer Creek macroinvertebrate assessment

analysis, pollution tolerance values assigned to

organisms and metric calculation formulas are taken

from the literature and documentation provided by the

state water quality agency. U.S.G.S. 7.5 minute

topographic maps are used to identify site locations,

land-use activities, and landscape features during an

initial watershed survey.

records and ensure that records can be traced to each instrument. Instrument

calibration procedures for biological monitoring programs should include routine

procedures that ensure that equipment is clean and in working order. 

INSPECTION 17 AND

ACCEPTANCE

REQUIREMENTS FOR

SUPPLIES

Describe how you determine if

supplies such as sample bottles, nets,

and reagants are adequate for your

program's needs.

DATA ACQUISITION REQUIREMENTS 18 Identify any types of

data your project uses

that are not obtained through your

monitoring activities. Examples of

these types of data include historical

information, information from

topographical maps or aerial photos,

or reports from other monitoring

groups. Discuss any limits on the use

of this data resulting from uncertainty

about its quality.
36 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 19

Data Management 

Field data sheets are inspected and signed by the sampling team captain before leaving the site. Field sheets are

given to the field leader at the end of the sampling day for review. Within 72 hours, the field leader will contact any

samplers whose field sheets contain significant errors or omissions.

The lab manager will review sample labels for turbidity and macroinvertebrate samples and remove from the dataset

any that cannot be attributed to specific samplers, have not been properly preserved, or that exceed the maximum

holding time. The laboratory manager will also sign-off on lab bench sheets after all QC checks have been

completed. These bench sheets will be transported to the Watershed Association offices so that the data can be

entered.

All data will be entered into a “Volbase” computerized spreadsheet/data base program designed for this project and

compatible with hardware and software used by both the state and county water resource agencies. As a QC check,

finalized data will be reviewed by a second individual.

DATA 19 MANAGEMENT

Trace the path your data take, from field

collection and lab analysis to data storage

and use. Discuss how you check for

accuracy and completeness of field and

lab forms, and how you minimize and

correct errors in calculations, data entry to

forms and databases, and report writing. 

Provide examples of forms and checklists. 

Identify the computer hardware and

software you use to manage your data. 

ASSESSMENTS AND 20 RESPONSE ACTIONS

Discuss how you evaluate field, lab, and data management

activities, organizations (such as contract labs) and individuals in

the course of your project. These can include evaluations of

volunteer performance (for example, through field visits by staff or

in laboratory refresher sessions); audits of systems such as

equipment and analytical procedures; and audits of data quality

(e.g., comparing actual data results with project quality objectives).

Include information on how your project will correct any problems

identified through these assessments. Corrective actions might

include calibrating equipment more frequently, increasing the
Chapter 4 : Elements of a QAPP 37

 ELEMENT 20 

Assessment and Response Actions 

Review of Volunteer Creek field activities is the responsibility of the Field Leader, in conjunction with the

Project Manager and the Quality Assurance Officer. Each field team will be accompanied and their

performance evaluated by one of these individuals once a year. If possible, volunteers in need of performance

improvement will be retrained on-site during the evaluation. In addition, volunteers attend yearly training

renewal workshops. If errors in sampling techniques are consistently identified, retraining may be scheduled

more frequently. 

All field and laboratory activities may be reviewed by state and EPA quality assurance officers as requested. 

Systems and data quality audits are performed by the QA Officer twice yearly. Any identified procedural

problems will be corrected based on recommendations from the QA Officer.

 ELEMENT 21

Reports 

Volunteer Creek Interim reports will be produced and

distributed in May (data collected from January-April)

and September (data collected from May-August). A

year-end report will be produced and distributed in

January of the following year (data collected from

September-December, as well as full-year results). The

Project Manager is responsible for all report production

and distribution. Reports will be forwarded to the

county, state, regional EPA office, and other members

of the Advisory Panel. These reports will consist of

data results, interpretation of data (if possible),

information on project status, volunteer highlights,

results of QC audits and internal assessments. 

Summaries of all reports, highlighting the assessment

results, project status, and volunteer achievements, will

be distributed to all volunteers and Watershed

Association members.

number of regularly scheduled training sessions, or rescheduling field or lab

activities. 

REPORTS 21 Identify the frequency, content, and distribution of reports to data

users, sponsors, and

partnership organizations that detail

project status, results of internal

assessments and audits, and how QA

problems have been resolved.
38 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

 ELEMENT 22

Data Review, Validation, and Verification Requirements 

All Volunteer Creek field and laboratory data is reviewed by the Project Manager, QA Officer, and Data Processing

Leader to determine if the data meet QAPP objectives. In addition, personnel from the State Department of Natural

Resources who are not directly connected to this project will also review data on a quarterly basis. Decisions to

reject or qualify data are made by the Project Manager and the QA Officer.

 ELEMENT 23

Validation and Verification 

Methods 

As part of the Volunteer Creek protocol, any sample

readings out of the expected range are reported to the

Field Leader. A second sample is taken by the Field

Leader as soon as possible to verify the condition. 10-

20% of the macroinvertebrate samples are reidentified

as a method of verifying data. and ensuring data

quality. If an error of greater than 5% is found, all

samples from that sampling period will be reidentified

and the taxonomist(s) retrained. 

Once the data has been entered into the Volunteer

Creek database, the Data Processing Leader will print

out the data and proofread it against the original data

sheets. Errors in data entry will be corrected. Outliers

and inconsistencies will be flagged for further review,

or discarded. Problems with data quality will be

discussed in the interim and final reports to data users.

DATA REVIEW, VALIDATION AND 22 VERIFICATION REQUIREMENTS

State how you review data and make decisions regarding accepting, rejecting, or

qualifying the data. All that is needed here is a brief statement of what will be

done, by whom.

VALIDATION AND VERIFICATION 23 METHODS

Describe the procedures you use to validate and verify data. This can include, for

example, comparing computer entries to field data sheets; looking for data gaps;

analyzing quality control data such as chain of custody information, spikes, and

equipment calibrations; checking calculations; examining raw data for outliers or

nonsensical readings; and

reviewing graphs, tables

and charts. Include a

description of how errors,

if detected, will be

corrected, and how

results will be conveyed

to data users. 
Chapter 4 : Elements of a QAPP 39

 ELEMENT 24

Reconciliation with Data Quality Objectives 

As soon as possible after each sampling event, calculations and determinations for precision, completeness, and

accuracy will be made and corrective action implemented if needed. If data quality indicators do not meet the

project’s specifications, data may be discarded and resampling may occur. The cause of failure will be

evaluated. If the cause is found to be equipment failure, calibration/ maintenance techniques will be reassessed

and improved. If the problem is found to be sampling team error, team members will be retrained. Any

limitations on data use will be detailed in both interim and final reports, and other documentation as needed.

If failure to meet project specifications is found to be unrelated to equipment, methods, or sample error,

specifications may be revised for the next sampling season. Revisions will be submitted to the state and EPA

quality assurance officers for approval.

RECONCILIATION WITH DATA QUALITY 24 OBJECTIVES

Once the data results are compiled, describe the process for determining whether

the data meet project objectives. This should include calculating and comparing

the project’s actual data quality indicators (precision, accuracy, completeness,

representativeness, and comparability) to those you specified at the start of the

project, and describing what will be done if they are not the same. Actions might

include discarding data, setting limits on the use of the data, or revising the

project's data quality objectives.
40 The Volunteer Monitor’s Guide to Quality Assurance Project Plans
Appendix A: Glossary 41

Appendix A:

GLOSSARY

Data Quality Objectives

(DQOs) specify the quality

of the data needed in

order to meet the

monitoring project's

goals.

Accuracy. A data quality indicator, accuracy is the extent of agreement between

an observed value (sampling result) and the accepted, or true, value of the

parameter being measured. High accuracy can be defined as a combination

of high precision and low bias.

Analyte. Within a medium, such as water, an analyte is a property or substance to

be measured. Examples of analytes would include pH, dissolved oxygen,

bacteria, and heavy metals.

Bias. Often used as a data quality indicator, bias is the degree of systematic error

present in the assessment or analysis process. When bias is present, the

sampling result value will differ from the accepted, or

true, value of the parameter being assessed.

Blind sample. A type of sample used for quality control

purposes, a blind sample is a sample submitted to an

analyst without their knowledge of its identity or 

composition. Blind samples are used to test the

analyst’s or laboratory’s expertise in performing the

sample analysis.

Comparability. A data quality indicator, comparability is the

degree to which different methods, data sets, and/or

decisions agree or are similar. 

Completeness. A data quality indicator that is generally expressed as a

percentage, completeness is the amount of valid data obtained compared to

the amount of data planned.

Data users. The group(s) that will be applying the data results for some purpose. 

Data users can include the monitors themselves as well as government

agencies, schools, universities, businesses, watershed organizations, and

community groups. 

Data quality objectives (DQOs). Data quality objectives are quantitative and

qualitative statements describing the degree of the data’s acceptability or

utility to the data user(s). They include indicators such as accuracy,

precision, representativeness, comparability, and completeness. DQOs

specify the quality of the data needed in order to meet the monitoring 
42 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

project's goals. The planning process for ensuring environmental data are of

the type, quality, and quantity needed for decision making is called the DQO

process.

Detection limit. Applied to both methods and equipment, detection limits are the

lowest concentration of a target analyte that a given method or piece of

equipment can reliably ascertain and report as greater than zero.

Duplicate sample. Used for quality control purposes, duplicate samples are two

samples taken at the same time from, and representative of, the same site

that are carried through all assessment and analytical procedures in an

identical manner. Duplicate samples are used to measure natural variability

as well as the precision of a method, monitor, and/or analyst. More than two

duplicate samples are referred to as replicate samples.

Environmental sample. An environmental sample is a specimen of any material

collected from an environmental source, such as water or macroinvertebrates

collected from a stream, lake, or estuary.

Equipment or rinsate blank. Used for quality control purposes, equipment or

rinsate blanks are types of field blanks used to check specifically for

carryover contamination from reuse of the same sampling equipment (see

field blank).

Field blank. Used for quality control purposes, a field blank is a “clean” sample

(e.g., distilled water) that is otherwise treated the same as other samples

taken from the field. Field blanks are submitted to the analyst along with

all other samples and are used to detect any contaminants that may be

introduced during sample collection, storage, analysis, and transport.

Instrument detection limit. The instrument detection limit is the lowest

concentration of a given substance or analyte that can be reliably detected by

analytical equipment or instruments (see detection limit).

Matrix. A matrix is a specific type of medium, such as surface water or sediment,

in which the analyte of interest may be contained.

Measurement Range. The measurement range is the extent of reliable readings

of an instrument or measuring device, as specified by the manufacturer.

Method detection limit (MDL). The MDL is the lowest concentration of a given

substance or analyte that can be reliably detected by an analytical procedure

(see detection limit).
Appendix A: Glossary 43

Quality Assurance (QA) is

an integrated

management system

designed to ensure that a

product or service meets

defined standards of

quality with a stated level

of confidence.

Performance evaluation (PE) samples. Used for quality

control purposes, a PE sample is a type of blind

sample. The composition of PE samples is unknown to

the analyst. PE samples are provided to evaluate the

ability of the analyst or laboratory to produce analytical

results within specified limits.

Precision. A data quality indicator, precision measures the

level of agreement or variability among a set of

repeated measurements, obtained under similar

conditions. Precision is usually expressed as a

standard deviation in absolute or relative terms.

Protocols. Protocols are detailed, written, standardized

procedures for field and/or laboratory operations. 

Quality assurance (QA). QA is an integrated management

system designed to ensure that a product or service meets defined standards

of quality with a stated level of confidence. QA activities involve planning

quality control, quality assessment, reporting, and quality improvement.

Quality assurance project plan (QAPP). A QAPP is a formal written document

describing the detailed quality control procedures that will be used to

achieve a specific project’s data quality requirements.

Quality control (QC). QC is the overall system of technical activities designed to

measure quality and limit error in a product or service. A QC program

manages quality so that data meets the needs of the user as expressed in a

quality assurance project plan. 

Relative standard deviation (RSD). RSD is the standard deviation of a parameter

expressed as a percentage and is used in the evaluation of precision.

Relative percent difference (RPD). RPD is an alternative to standard deviation,

expressed as a percentage and used to determine precision when only two

measurement values are available. 

Replicate samples. See duplicate samples.

Representativeness. A data quality indicator, representativeness is the degree to

which data accurately and precisely portray the actual or true environmental

condition measured.

Sensitivity. Related to detection limits, sensitivity refers to the capability of a

method or instrument to discriminate between measurement responses
44 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Standard Reference

Materials (SRMs) are

produced by the U. S.

National Institute of

Standards and

Technology (NIST) and

characterized for absolute

content independent of

any analytical method.

representing different levels of a variable of interest.

The more sensitive a method is, the better able it is to

detect lower concentrations of a variable.

Spiked samples. Used for quality control purposes, a spiked

sample is a sample to which a known concentration of

the target analyte has been added. When analyzed, the

difference between an environmental sample and the

analyte’s concentration in a spiked sample should be

equivalent to the amount added to the spiked sample.

Split sample. Used for quality control purposes, a split

sample is one that has been equally divided into two or

more subsamples. Splits are submitted to different

analysts or laboratories and are used to measure the

precision of the analytical methods.

Standard reference materials (SRM). An SRM is a certified material or

substance with an established, known and accepted value for the analyte or

property of interest. Employed in the determination of bias, SRMs are used

as a gauge to correctly calibrate instruments or assess measurement methods. 

SRMs are produced by the U. S. National Institute of Standards and

Technology (NIST) and characterized for absolute content independent of

any analytical method.

Standard deviation(s). Used in the determination of precision, standard deviation

is the most common calculation used to measure the range of variation

among repeated measurements. The standard deviation of a set of

measurements is expressed by the positive square root of the variance of the

measurements.

Standard operating procedures (SOPs). An SOP is a written document detailing

the prescribed and established methods used for performing project

operations, analyses, or actions. 

True value. In the determination of accuracy, observed measurement values are

often compared to true, or standard, values. A true value is one that has

been sufficiently well established to be used for the calibration of

instruments, evaluation of assessment methods or the assignment of values

to materials.

Variance. A statistical term used in the calculation of standard deviation,

variance is the sum of the squares of the difference between the individual

values of a set and the arithmetic mean of the set, divided by one less than

the numbers in the set.
Appendix B: EPA Regional Contacts 45

Appendix B:

EPA REGIONAL CONTACTS

Which EPA region are you in?

Region 1: CT, MA, ME, VT, NH, RI

Region 2: NY, NJ, VI, PR

Region 3: DE, DC, MD, PA, VA, WV

Region 4: AL, FL, GA, KY, MS, NC, SC, TN, 

Region 5: IL, IN, MI, MN, OH, WI

Region 6: AR, LA, NM, OK, TX

Region 7: IA, KS, MO, NE

Region 8: CO, MT, ND, SD, UT, WY

Region 9: AZ, CA, NV, GU, HI, AS

Region 10: AK, ID, OR, WA

ach of EPA’s 10 Regional offices has a volunteer monitoring coordinator Eand quality assurance officers who can be of assistance to volunteer

programs. Listed below are the contact names for each region, as of

September 1, 1996. These contacts may change over time.

EPA Regional

Volunteer Monitoring

Coordinators

Diane Switzer

USEPA Region 1 

(EMS-LEX)

60 Westview Street

Lexington, MA 02173

617-860-4377

Diane Calesso

USEPA Region II

Environmental Services Division

2890 Woodbridge Avenue

Raritan Depot Bldg. 10

Edison, NJ 08837-3679

908-906-6999 

calesso.diane@epamail.epa.gov

Pete Weber

USEPA Region III

3WP13

841 Chestnut Bldg.

Philadelphia, PA 19107

215-566-5749

Chuck Kanetsky

USEPA Region III

841 Chestnut Bldg.

Philadelphia, PA 19107

215-566-2735

David Melgaard

USEPA Region IV

Watershed Section

345 Courtland Street

Atlanta, GA 30365

404-347-2126 (x6590)

Tom Davenport

USEPA Region V

77 W. Jackson Blvd. 

Chicago, IL 60604

312-886-7804

Mike Bira

USEPA Region VI (6WQS)

1445 Ross Avenue

12th Floor, Suite 120

Dallas, TX 75202-2733

214-665-6668
46 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Jerry Pitt

USEPA Region VII

726 Minnesota Avenue

Kansas City, KS

913-551-7766

Paul McIver

USEPA Region VIII

999 18th Street, Suite 500

Denver, CO 80202-2405

303-312-6056

Phil Johnson

USEPA Region VIII

999 18th Street, Suite 500

Denver, CO 80202-2405

303-312-6084

Ed Liu

USEPA Region IX

75 Hawthorne Street

San Francisco, CA 94105

415-744-1934

Andrea Lindsay

USEPA Region X

1200 Sixth Avenue

Seattle, WA 98101

206-553-1287

Drew Puffer

Gulf of Mexico Program

Building 1103

Stennis Space Ctr, MS 39529-620

601-688-3913

Alice Mayio, National Volunteer

Monitoring Coordinator 

USEPA (4503F)

401 M Street, SW

Washington, DC 20460

202-260-7018

Regional Quality

Assurance Officers

Nancy Barmakian 

USEPA Region I

New England Regional Lab

60 Westview Street

Lexington, MA 02173-3185

617-860-4684

Robert Runyon

USEPA Region II

2890 Woodbridge Avenue

Edison, NJ 08837

908-321-6645

Charles Jones, Jr.

USEPA (3ES00) Region III

841 Chestnut Street, 8th Floor

Philadelphia, PA 19107

215-566-7210

Diann Sims

USEPA (3ES30) Region III

Central Regional Lab

201 Defense Highway, Suite 200

Annapolis, MD 21401

Claudia Walters

USEPA Region III

Chesapeake Bay Program Office

410 Severn Avenue, Suite 109

Annapolis, MD 21403

Gary Bennett

USEPA/Region IV

960 College Station Road

Athens, GA 30605-2720

706-546-3287

Willie Harris

MQAB/ESD/EPA (5SMQA)

Region V

77 West Jackson

Chicago, IL 60604
Appendix B: EPA Regional Contacts 47

Lisa Feldman

USEPA/ESD Region VI

10625 Fallstone

Houston, TX 77099

Alva Smith

USEPA (6EQ) Region VI

1445 Ross Avenue

Suite 1200

Dallas, TX 75202-2733

Ernest L. Arnold

USEPA/EST Region VII

25 Funston Road

Kansas City, KS 66115

913-551-5194

Rick Edmonds (SES-AS)

USEPA/ESD Region VIII

Suite 500

999 18th Street

Denver, CO 80202-3405

303-293-0993

Vance Fong

USEPA Region IX (MD P-3-2)

75 Hawthorn Street

San Francisco, CA 94105

415-744-1492

Barry Towns

USEPA (OEA-095) Region X

1200 Sixth Avenue

Seattle, WA 98101

206-553-1675
48 The Volunteer Monitor’s Guide to Quality Assurance Project Plans
Appendix C: References 49

Appendix C:

REFERENCES

The following presentation paper topics, specifically

relavant to quality assurance and quality control issues,

are contained in the proceedings documents from past

national volunteer monitoring conferences:

Proceedings of Third National Citizens’ Volunteer

Water Monitoring Conference. 

• Goal Setting and Organizing

• Study Design

• Training Monitors

• Integrated Monitoring Systems

• Enforcement and Compliance Monitoring

• Procedures for Collecting Quality Data

• Meeting Scientific Standards for Biological

Monitoring

• Deciding Data Objectives

• River and Stream Monitoring Techniques

• Lake Monitoring Techniques

• Wetland Monitoring Techniques

• Estuary Monitoring Techniques

• Computer Data Management

• Data Application and Presentation

Proceedings Fourth National Citizens’ Volunteer

Monitoring Conference.

• Designing Your Water Quality Study

• Assuring Quality Data

• Defining Data Use

• Using Your Data to Evaluate Your Volunteer

Monitoring Program

• Geographic Information Systems and Volunteer

Monitoring Data

• Managing Your Data: Some Basic Principles

• Data Analysis for the Technically Impaired

• Macroinvertebrate Monitoring

• Bacteria Testing

• Monitoring Restoration and Pollution Prevention

Activities

Both of these documents are available upon request from

the EPA National Volunteer Monitoring Coordinator.

Directory of Volunteer Environmental Monitoring Programs, 4th Edition. EPA

841-B-94-001, January 1994. U.S. Environmental Protection Agency,

Office of Water, Washington, DC. 

EPA Requirements for Quality Assurance Project Plans (QAPP) for

Environmental Data Operations. 

EPA/QA/R-5. August 1994. U.S.

Environmental Protection Agency,

Office of Water, Washington, DC.

Generic Quality Assurance Project Plan

Guidance for Programs Using

Community Level Biological

Assessment in Wadable Streams and

Rivers. EPA 841-B-95-004, July 1995. 

U.S. Environmental Protection Agency,

Office of Water, Washington, DC. 

Guidance for Data Quality Assessment. 

EPA QA/G-9, March 1995. U.S.

Environmental Protection Agency,

Office of Research and Development,

Washington, DC.

Guidance for the Preparation of Standard

Operating Procedures (SOPs) for

Quality-Related Documents. EPA

QA/G-6. November 1995. U.S.

Environmental Protection Agency,

Quality Assurance Division.

Integrating Quality Assurance into Tribal

Water Programs: A Resource Guide

for Reliable Water Quality Data

Collection. U.S. Environmental

Protection Agency Region 8, Denver,

Colorado.
50 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

Proceedings of the Fourth National Citizen’s Volunteer Water Monitoring

Conference. EPA 841/R-94-003, February 1995. U.S. Environmental

Protection Agency, Office of Water, Washington, DC. 

Proceedings of the Third National Citizen’s Volunteer Water Monitoring

Conference. EPA 841/R-92-004, September 1992. U.S. Environmental

Protection Agency, Office of Water, Washington, DC. 

Volunteer Estuary Monitoring: A Methods Manual. EPA 842-B-93-004,

December 1993. U.S. Environmental Protection Agency, Office of Water,

Washington, DC. 

Volunteer Lake Monitoring: A Methods Manual. EPA 440/4-91-002,

December 1991. U.S. Environmental Protection Agency, Office of Water,

Washington, DC. 

The Volunteer Monitor: Building Credibility. Volume 4, number 2, Fall 1992. 

Eleanor Ely, ed. San Francisco, CA.

The Volunteer Monitor: Managing and Presenting Your Data. Volume 7,

number 1, Spring 1995. Eleanor Ely, ed. San Francisco, CA.

Volunteer Stream Monitoring: A Methods Manual (Field Test Draft). EPA 841

D 95-001. April 1995. U.S. Environmental Protection Agency, Office of

Water, Washington, DC. 

Volunteer Water Monitoring: A Guide for State Managers. EPA 440/4-90-010,

August 1990. U.S. Environmental Protection Agency, Office of Water,

Washington, DC.
Appendix D: Abbreviated QAPP Form 51

Appendix D:

ABBREVIATED QAPP FORM

hat follows is an example of an optional abbreviated quality assurance project plan Wform. You may be able to use it as a model for your project’s QAPP. However, be

sure to consult your state or EPA regional QA officers to determine if use of this form

(or a modified version) is acceptable to them, and for specific information on required elements

for your project.

1. Title and Approval Page

(Project Name)

(Responsible Agency)

(Date)

Project Manager Signature

Name/Date

Project QA Officer Signature

Name/Date

USEPA Project Manager Signature

Name/Date

USEPA QA Officer Signature

Name/Date

2. Table of Contents

List sections with page numbers, figures, tables, references, and appendices (attach pages).
52 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

3. Distribution List

Names and telephone numbers of those receiving copies of this QAPP. Attach additional page,

if necessary.

i.

ii.

iii.

iv.

v.

vi.

vii.

viii.

ix.

x.

4. Project/Task Organization

List key project personnel and their corresponding responsibilities.

Name Project Title/Responsibility

Advisory Panel (contact)

Project Manager

QA Officer

Field/Sampling Leader

Laboratory Manager/Leader

5. Problem Definition/Background

A. Problem Statement
Appendix D: Abbreviated QAPP Form 53

B. Intended Usage of Data

6. Project/Task Description

A. General Overview of Project

B. Project Timetable

Activity Projected Start Date Anticipated Date of

Completion
54 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

7. Measurement Quality Objectives

A. Data Precision, Accuracy, Measurement Range

Matrix Parameter Measurement Accuracy Precision

Range

B. Data Representativeness

C. Data Comparability

D. Data Completeness

Parameter No. Valid Samples No. Valid Samples Percent Complete

Anticipated Collected &

Analyzed
Appendix D: Abbreviated QAPP Form 55

8. Training Requirements and Certification

A. Training Logistical Arrangements

Type of Volunteer Training Frequency of Training/Certification

B. Description of Training and Trainer Qualifications

9. Documentation and Records

10. Sampling Process Design

A. Rationale for Selection of Sampling Sites
56 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

B. Sample Design Logistics

Type of Number of Sampling Sampling

Sample/ Samples Frequency Period

Parameter

Biological

Physical

Chemical

11. Sampling Method Requirements

Parameter Sampling Equipment Sampling Method

12. Sample Handling and Custody Procedures
Appendix D: Abbreviated QAPP Form 57

13. Analytical Methods Requirements

14. Quality Control Requirements

A. Field QC Checks

B. Laboratory QC Checks

C. Data Analysis QC Checks

15. Instrument/Equipment Testing, Inspection, and

Maintenance Requirements

Equipment Type Inspection Frequency Type of Inspection
58 The Volunteer Monitor’s Guide to Quality Assurance Project Plans

16. Instrument Calibration and Frequency

Equipment Type Calibration Frequency Standard or Calibration

Instrument Used

17. Inspection/Acceptance Requirements

18. Data Acquisition Requirements

19. Data Management

20. Assessment and Response Actions
Appendix D: Abbreviated QAPP Form 59

21. Reports

22. Data Review, Validation, and Verification

23. Validation and Verification Methods

24. Reconciliation with DQO’s