United States Environmental Protection Agency

Office of Water

Office of Environmental Information 

Washington, DC

EPA 841-B-04-005

Wadeable Streams Assessment

Quality Assurance

Project Plan

August 2004
WADEABLE STREAMS ASSESSMENT:

QUALITY ASSURANCE PROJECT PLAN

Project Leader: Susan Holdsworth

U.S. Environmental Protection Agency

Office of Wetlands, Oceans, and Watersheds

1200 Pennsylvania Avenue, NW

4503T

Washington, DC 20460


W adeable Streams Assessment June 2004

QA Project Plan Page v

QUALITY ASSURANCE PROJECT PLAN

REVIEW & DISTRIBUTION ACKNOWLEDGMENT AND 

COMMITMENT TO IMPLEMENT

for

Wadeable Streams Assessment

We have read the QAPP and the methods manuals for the Wadeable Streams Assessment listed

below. Our agency/organization, , agrees to abide by its

requirements for work performed under our cooperative agreement for Demonstration of

Randomized Design for Assessment of Wadeable Streams (under CWA 104(b)(3)).

Quality Assurance Project Plan G

Site Evaluation Guidelines G

Field Operations Manual G

Benthic Laboratory Methods G

Water Chemistry Laboratory Manual G

Print Name 

Title 

(Principle Investigator)

 

Signature 

Date

Address: 

 

 

 

Phone: 

Fax: 

E-mail: 

Please return the signed original to the EPA QA officer for this cooperative agreement:

Otto Gutenson

U.S. EPA (4503T)

1200 Pennsylvania Ave, NW

Washington, DC 20460

202-566-1183 (phone)

202-566-1331 (fax)
W adeable Streams Assessment June 2004

QA Project Plan Page vi

Retain a copy for your files.

NOTICE

The complete documentation of overall WSA project management, design, methods,

and standards is contained in five companion documents, including: 

• Wadeable Streams Assessment: Quality Assurance Project PlanEPA 841-B-04- 

 005

• Wadeable Streams Assessment: Site Evaluation Guidelines EPA 841-B-04-008

• Wadeable Streams Assessment: Field Operations Manual EPA 841-B-04-004

• Wadeable Streams Assessment: Benthic Laboratory MethodsEPA 841-B-04-007

• Wadeable Streams Assessment: Water Chemistry Laboratory Manual EPA 841- 

 B-04-008

This document (Quality Assurance Project Plan) contains elements of the overall

project management, data quality objectives, measurement and data acquisition, and

information management for the WSA, and is based on the guidelines developed and

followed in the Western Environmental Monitoring and Assessment Program (Peck et

al. 2003). Methods described in this document are to be used specifically in work

relating to WSA. All Project Cooperators should follow these guidelines. Mention of

trade names or commercial products in this document does not constitute endorsement

or recommendation for use. More details on specific methods for site evaluation, field

sampling, and laboratory processing can be found in the appropriate companion

document(s) listed above.

The suggested citation for this document is:

USEPA. 2004 (draft). Wadeable Stream Assessment: Integrated Quality

Assurance Project Plan. EPA/841/B-04/005. U.S. Environmental Protection

Agency, Office of Water and Office of Research and Development, Washington,

DC.
W adeable Streams Assessment June 2004

QA Project Plan Page vii

DISTRIBUTION LIST

This QA Project Plan and associated manuals or guidelines will be distributed to the

following EPA, Tetra Tech, Inc. (Tt), and Great Lakes Environmental Center (GLEC)

senior staff participating in the WSA and to State Water Quality Agencies or

cooperators who will perform the field sampling operations. The Tt and GLEC QA

Officers will distribute the QA Project Plan and associated documents to participating

project staff at their respective facilities and to the project contacts at participating

laboratories, as they are determined.

Grant Coordinators

Name, Region Contact Information Organization Address

Darvene Adams,

Regions 1 & 2

(732) 321-6700

Adams.Darvene@epa.gov

USEPA - Region II

2890 Woodbridge Avenue, (MS220)

Edison, NJ 08837-3679

Larry Merrill, 

Region 3

(215) 814-5452

Merrill.Larry@epa.gov

U.S. EPA - Region III

1650 Arch Street

Philadelphia, PA 19103-2029

Susan Holdsworth, 

Region 4

(202) 566-1187

Holdsworth.Susan@epa.gov

USEPA

1200 Pennsylvania Avenue, NW

(4503T)

W ashington, DC 20460

Sarah Lehmann,

Region 5

(312) 353-5784

Lehmann.Sarah@epa.gov

U.S. EPA - Region V

77 W est Jackson Boulevard

Chicago, IL 60604-3507

Charlie Howell,

Region 6

(214) 665-8354

Howell.Charlie@epa.gov

U.S. EPA - Region VI , (6WQ-EW )

1445 Ross Avenue - Suite 1200

Dallas, TX 75202-2733

Susan Holdsworth,

Region 7

(202) 566-1187

Holdsworth.Susan@epa.gov

USEPA

1200 Pennsylvania Avenue, NW

(4503 T)

W ashington, DC 20460

Janet Hashimoto

Region 9

(415) 972-3452

Hashimoto.Janet@epa.gov

75 Hawthorne Street

San Francisco, CA 94105

Gretchen Hayslip,

Region 10

(206) 553-1685

Hayslip.Gretchen@epa.gov

U.S. EPA - Region X, ES-098

1200 Sixth Avenue

Seattle, W A 98101

Regional Monitoring Coordinators

Hilary Snook,

Region 1

617-918-8670

Snook.Hilary@epa.gov

U.S. EPA - Region I

11 Technology Drive

North Chelmsford, MA 01863-2431
W adeable Streams Assessment June 2004

QA Project Plan Page viii

Darvene Adams,

Region 2 see above see above

Larry Merrill, 

Region 3 see above see above

David Melgaard,

Region 4

(404) 562-9265

Melgaard.David@epa.gov

U.S.EPA - Region IV

61 Forsyth Street

Atlanta, GA 30303

Sarah Lehmann,

Region 5 see above see above

Charlie Howell,

Region 6 see above see above

Lyle Cowles, 

Region 7

(913) 551-7081

Cowles.Lyle@epa.gov

U.S. EPA - Region VII

726 Minnesota Avenue

Kansas City, KS 66101

Janet Hashimoto

Region 9 see above see above

Gretchen Hayslip,

Region 10 see above see above

Cooperators

Becky Weidman,

NEIW PCC

(978) 323-7929 ext. 229

Rweidman@neiwpcc.org 

NEIW PCC

Boott Mills South

100 Foot of John Street

Lowell, Massachusetts 01852

Chris Yoder,

CABB

(740) 517-2274

yoder@ilgard.ohiou.edu 

CABB

P.O. Box 21561

Columbus, Ohio 43221-0561

Mike Beiser 

MS DEQ (610) 664-3959

MS DEQ 

P.O. Box 20305

Jackson, Hinds, MS 39289-1305

Seva Joseph 

NM ED

(505) 827-0573

seva_joseph@nmenv.state.nm.us

NM ED 

Surface Water Quality Bureau

1190 Saint Francis Dr. 

Santa Fe, NM 87502

Ellen Dickey

DE DNREC

(302)-739-4771

Ellen.Dickey@state.de.us

DNREC

89 Kings Hwy

Dover, DE 19901

Richard Shertzer

 PA DEP

(717) 787-9637

rshertzer@state.pa.us

PA DEP

PO Box 8467

Harrisburg, PA 17105
W adeable Streams Assessment June 2004

QA Project Plan Page ix

Mike Miller,

W I DNR

608-267-2753

millema@dnr.state.wi.us

W I DNR

101 S. W ebster St.

PO Box 7921

Madison, W I 53707

Paul Kazyak,

MD DNR

410-260-8607

pkazyak@dnr.state.md.us

MD DNR

580 Taylor Ave., C-2

Annapolis, MD 21401

Larry W illis,

VA DEQ

540-562-6825

ldwillis@deq.state.va.us 

VA DEQ

P.O. Box 10009

 Richmond, VA 23240

John Wirts,

W V DEP

(304) 558-2837

jwirts@mail.dep.state.wv.us 

W V DEP

W atershed Assessment Section

1201 Greenbrier Street

Charleston, WV 25311

Eric Fleek,

NC DEM

919-733-6946

eric.fleek@ncm ail.net

NC DEM

1621 Mail Service Center

Raleigh, NC 27699

Jim Glover,

SC DHEC

(803) 898-4081

gloverjb@columb32.dhec.state.sc.us 

SC DHEC

2600 Bull St.

Columbia, SC 29205

Kristen Sanford,

GA DNR

(404)-675-1659

Kristen_Sanford@mail.dnr.state.ga.us 

GA DNR 

4220 International Parkway, Suite

101

 Atlanta, Georgia 30354

Debbie Arnwine,

TN DEC

615-532-0703

debbie.arnwine@state.tn.us 

TN DEC

401 Church Street

Nashville, TN 37243

Matt Combes,

MO DHE

(573) 882-9909 ext 3317

Matt.Combes@m dc.mo.gov

P.O. Box 180 

2709 W est Trum an Blvd. 

Jefferson City, MO 65102

Steve Haslouer,

KS DNR

(785) 296-0079

shasloue@kdhe.state.ks.us

KS DHE

1000 SW Jackson St., Suite 430

Topeka, KS 66612-1367

Tom W ilton,

IA DNR

515-281-8867

tom.wilton@dnr.state.ia.us 

IA DNR

W allace Bldg.

Des Moines, IA 50319

Don Huggins,

CPC

(785) 864-1548

dhuggins@ukans.edu 

University of Kansas

2101 Constant Avenue

Lawrence, KS 66047

Marty Matlock,

U. of Arkansas

(479) 575-2849

mm atlock@uark.edu

233 Engineering Hall

University of Arkansas

Fayetteville, AR 72701
W adeable Streams Assessment June 2004

QA Project Plan Page x

Bill Harrison,

TX CEQ

(512) 239-4602

bharriso@tnrcc.state.tx.us 

TCEQ

MC-165

P.O. Box 13087

Austin, TX 78753

Ron Klein

AKDEC

(907) 269-7595

ron_klein@ dec.state.ak.us 

Alaska Department of

Environmental Conservation 

Division of Air and W ater Quality 

555 Cordova Street

Anchorage, Alaska 99501

Dan Butler,

OK CC

405-979-2206

danb@okcc.state.ok.us 

OK CC

4000 Hammer Drive

Norman, OK 73026

Contractor Support

Michael Barbour,

Tetra Tech

(410) 356-8993

Michael.Barbour@tetratech.com 

10045 Red Run Blvd., Ste. 110

Owings Mills, MD 21117

Marlys Cappaert

CSC

(541) 754-4467

Cappaert.Marlys@epa.gov

200 S.W . 35th St.

Corvallis, OR 97330

Esther Peters, Tetra

Tech

(703) 385-6000

Esther.Peters@tetratech-ffx.com

10306 Eaton Pl., Ste. 340

Fairfax, VA 22030

Dennis McCauley, 

GLEC

(231) 941-2230

dmccauley@glec-tc.com

739 Hastings Street

Traverse City, MI 49686
W adeable Streams Assessment June 2004

QA Project Plan Page xi

TABLE OF CONTENTS

DISTRIBUTION LIST .............. .............. .............. ....... vii

LIST OF FIGURES .............. .............. .............. ......... xiii

LIST OF TABLES .............. .............. .............. .......... xiv

1.0 PROJECT PLANNING AND MANAGEMENT .............. .............. 1

1.1 Introduction .............. .............. .............. ....... 1

1.2 WSA Project Organization .............. .............. ......... 2

1.2.1 Project Schedule .............. .............. ......... 6

1.3 Scope of QA Project Plan .............. .............. .......... 7

1.3.1 Overview of Field Operations .............. .............. 7

1.3.2 Overview of Laboratory Operations .............. ......... 10

1.3.3 Data Analysis and Reporting .............. .............. 13

2.0 DATA QUALITY OBJECTIVES .............. .............. .......... 13

2.1 Data Quality Objectives for WSA .............. .............. ... 13

2.2 Measurement Quality Objectives .............. .............. ... 13

2.2.1 Method Detection Limits .............. .............. ... 14

2.2.2 Sampling Precision, Bias, and Accuracy .............. ..... 14

2.2.3 Taxonomic Precision and Accuracy .............. ........ 16

2.2.4 Completeness .............. .............. ........... 18

2.2.5 Comparability .............. .............. ........... 18

2.2.6 Representativeness .............. .............. ...... 18

3.0 SURVEY DESIGN .............. .............. .............. ...... 19

3.1 Probability-Based Sampling Design and Site Selection .............. 22

4.0 INFORMATION MANAGEMENT .............. .............. ......... 23

4.1 Data Policy .............. .............. .............. ....... 23

4.2 Overview of System

Structure...................................................................................................24

4.2.1 Design and Logistic Data

Bases.......................................................................................................24

4.2.2 Sample Collection and Field Data Recording............................ 26.

4.2.3 Laboratory Analyses and Data Recording.....................................27.

4.2.4 Data Review, Verification and Validation Activities.......................29.

4.3 Data Transfer................................................................................................30

4.4 Core Information Management Standards .............. ........... 31

4.4.1 Metadata .............. .............. .............. . . 3
W adeable Streams Assessment June 2004

QA Project Plan Page xii

4.4.2 Data Directory .............. .............. ........... 31

4.4.3 Data Catalog .............. .............. ........... 31

4.4.4 Data Formats .............. .............. ........... 31

4.4.5 Parameter Formats........................................................................34

4.4.6 Standard Coding Systems.............................................................32

4.5 Hardware and Software Control...................................................................32

4.6 Data Security............................................................................................ 33

5.0 INDICATOR..................................................................................................33

5.1 Benthic Macroinvertebrates .............. .............. ........ 33

5.1.1 Introduction .............. .............. ............. 33

5.1.2 Sampling Design .............. .............. ......... 35

5.1.3 Sampling and Analytical Methodologies .............. ..... 35

5.1.4 Quality Assurance Objectives .............. ............. 36

5.1.5 Quality Control Procedures: Field Operations .............. . 36

5.1.6 Quality Control Procedures: Laboratory Operations .......... 36

5.1.7 Data Management, Review and Validation .............. ... 36

5.1.8 Data Analysis Plan .............. .............. ........ 38

5.2 Physical Habitat Quality Indicator .............. .............. ... 39

5.2.1 Introduction .............. .............. ............. 39

5.2.2 Sampling Design .............. .............. ......... 41

5.2.3 Sampling Methodologies .............. .............. ... 41

5.2.4 Quality Assurance Objectives .............. ............. 41

5.2.5 Quality Control Procedures: Field Operations .............. . 43

5.2.6 Quality Control Procedures: Laboratory Operations .......... 43

5.2.7 Data Management, Review, and Validation .............. ... 44

5.3 Water Chemistry Indicator .............. .............. ......... 44

5.3.1 Introduction .............. .............. ............. 44

5.3.2 Sampling Design .............. .............. ......... 45

5.3.3 Sampling and Analytical Methodologies .............. ...... 45

5.3.4 Quality Assurance Objectives .............. ............. 46

5.3.5 Quality Control Procedures: Field Operations .............. . 50

5.3.6 Quality Control Procedures: Laboratory Operations .......... 50

5.3.7 Data Reporting, Review, and Management .............. ... 51

6.0 BIOLOGICAL FIELD AND LABORATORY QUALITY EVALUATION AND

ASSISTANCE VISITS .............. .............. .............. ...... 59

6.1 Field Quality Evaluation and Assistance Visit Plan .............. .... 61

6.2 Laboratory Quality Evaluation and Assistance Visit Plan .............. 64

7.0 REFERENCES .............. .............. .............. ......... 65
W adeable Streams Assessment June 2004

QA Project Plan Page xiii

LIST OF FIGURES

Figure 1. WSA Project Organization .............. .............. ........ 3

Figure 2. Timeline of WSA project activities .............. .............. . . 6

Figure 3. Site verification activities for stream field surveys. .............. .... 9

Figure 4. Summary of field activities stream and river sampling. .............. 11

Figure 5. Organization of information management system modeled after 

EMAP-W for the WSA ..............................................................................25

 Figure 6. Sampling design for the benthic indicator .............. .......... 34

Figure 7. Laboratory processing activities for the benthic indicator. ........... 40

Figure 8. Stream index sampling design for the water chemistry indicator. ...... 46

Figure 9. Sample processing activities for water chemistry samples ........... 52

Figure 10. Analysis activities for water chemistry samples .............. ..... 56
W adeable Streams Assessment June 2004

QA Project Plan Page xiv

LIST OF TABLES

Table 1. Critical logistics elements .............. .............. .......... 7

Table 2. General guidelines for analytical support laboratories .............. . 12

Table 3. Sample and field data quality control activities.......................................... 27

Table 4. Laboratory data quality control activities...................................................28

Table 5. Biological sample quality control activities.................................................28

Table 6. Data review, verification and validation quality control activities.............. 29

Table 7. Field and laboratory methods: benthic indicator .............. ..... 35

Table 8. Measurement data quality objectives: benthic indicator ............. 36

Table 9. Laboratory quality control: benthic macroinvertebrate sample 

processing....................................................................................37

Table 10. Laboratory quality control: benthic macroinvertebrate taxonomic 

identification .............. .............. .............. ... 37

Table 11. Data validation quality control: benthic indicator .............. ..... 38

Table 12. Research issues: benthic indicator .............. .............. . 38

Table 13. Field measurement methods: physical habitat indicator ............. 42

Table 14. Measurement data quality objectives: physical habitat indicator ...... 43

Table 15. Field quality control: physical habitat indicator .............. ...... 44

Table 16. Data validation quality control: physical habitat indicator ............ 44

Table 17. Research questions and hypotheses: water chemistry indicator ...... 45

Table 18. Analytical methodologies: water chemistry indicator .............. . 47

Table 19. Measurement data quality objectives: water chemistry indicator ...... 49

Table 20. Sample processing quality control: water chemistry indicator ........ 51

Table 21. Laboratory quality control samples: water chemistry indicator ........ 53

Table 22. Data validation quality control: water chemistry indicator ............ 57

Table 23. Data reporting criteria: water chemistry indicator .............. .... 58

Table 24. Constants for converting major ion concentrations .............. ... 59

Table 25. Factors to calculate equivalent conductivities .............. ....... 59
W adeable Streams Assessment August 2004 

QA Project Plan Page 1 of 71

1.0 PROJECT PLANNING AND MANAGEMENT

1.1 Introduction

Several recent reports have identified the need for improved water quality

monitoring and analysis at multiple scales. In 2000, the General Accounting Office

(USGAO,2000) reported that EPA and states cannot make statistically valid inferences

about water quality (via 305[b] reporting) and lack data to support key management

decisions. In 2001, the National Research Council (NRC,2000) recommended EPA

and states promote a uniform, consistent approach to ambient monitoring and data

collection to support core water quality programs. In 2002, the H. John Heinz III Center

for Science, Economics, and the Environment (Heinz Center,2002) found there are

inadequate data for national reporting on fresh water, coastal and ocean water quality

indicators. The National Association of Public Administrators (NAPA,2002) stated that

improved water quality monitoring is necessary to help states make more effective use

of limited resources. EPA’s Report on the Environment 2003 (USEPA, 2003) says that

there is insufficient information to provide a national answer, with confidence and

scientific credibility, to the question, “What is the condition of U.S. waters and

watersheds?”

In response to this need, the U.S. Environmental Protection Agency (EPA) Office

of Water (OW), in concert with EPA’s Office of Research and Development (ORD) and

the 10 EPA Regions, conceived of the Wadeable Streams Assessment (WSA) - a

national assessment of the condition of wadeable streams and rivers in the

conterminous U.S. This assessment was to be the first assessment on flowing waters

to be based on data collected using the same field and laboratory protocols and based

on a statistical survey design that would allow inferences about all waters based on a

sample of the streams across the country. The desire was to implement this effort in

cooperation with the States and other eligible entities. Therefore, OW issued a

Request for Pre-Proposals under Clean Water Act Section 104(b)(3) to invite eligible

applicants to participate in a demonstration project to apply a consistent set of

monitoring protocols and monitoring design to characterize the wadeable streams and

rivers across the United States. The WSA builds upon the Environmental Monitoring

and Assessment Program’s (EMAP) Western Study implemented by ORD, the EPA

Regions, States and Tribal nations in 12 western states. The WSA will provide

important information to the public about the status of wadeable streams and rivers,

information that does not currently exist for large parts of the country.

The WSA Quality Assurance Project Plan (QAPP) is designed to support the

participants in this project and to ensure that the final assessment is based on high

quality data and information. The QAPP contains elements of the overall project

management, data quality objectives, measurement and data acquisition, and

information management for the WSA. The participants in the WSA have agreed to

follow this QAPP and the protocols and design laid out in this document. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 2 of 71

The WSA was designed to work in concert with ORD’s Environmental Monitoring

and Assessment Program (EMAP). Between 2000 and 2004, EMAP West has

successfully sampled nearly 1000 streams from 12 states in the Western United States. 

WSA will sample the remaining 36 states with 500 sites selected using a probabilitybased design and the same field and laboratory protocols to complete sampling in the

48 contiguous states. WSA has two objectives:

! Estimate the current status in selected indicators of the condition of the

Nation's streams and tributaries on a regional basis with known statistical

confidence.

! Seek associations between selected indicators of natural and

anthropogenic stresses and indicators of condition of wadeable streams

and rivers .

Monitoring and assessment tools developed for EMAP will contribute to

improving the ecological assessments in WSA. These assessments will provide

estimates (with quantifiable uncertainty) of the biological integrity of the

macroinvertebrate communities in wadeable streams and rivers. Chemical and physical

habitat information, along with watershed characteristics will also be collected to assist

in explaining the patterns found in macroinvertebrate communities across the country. 

1.2 WSA Project Organization

The major areas of activity and responsibilities are described here and illustrated

in Figure 1. The overall coordination of the project will be provided by EPA's Office of

Water (OW) in Washington, DC, with technical support from the Western Ecology

Division (WED) of the Office of Research and Development (ORD) in Corvallis, Oregon

and the ten EPA Regional Offices. Because this project builds upon the EMAP western

study and integrates ecological data from that study, ORD will have a primary role in

training field crews and managing the complex data derived from the surveys and the

laboratory processing of the samples. This comprehensive quality assurance (QA)

program has been established to ensure data integrity and provide support for the

reliable interpretation of the findings from this project. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 3 of 71

Figure 1. WSA Project Organization
W adeable Streams Assessment August 2004 

QA Project Plan Page 4 of 71

Program level QA will be the responsibility of the OWOW QA Officer and the Project

QA Officer. A QA records system will be used to maintain indefinitely a permanent

hardcopy file of all WSA documentation from site selection to data analysis. This will

be housed in OW Headquarters Office. 

The primary responsibilities of the principals and cooperators are as follows:

Project Management:

EPA Project Leader – provides overall coordination of the project and makes decisions

regarding the proper functioning of all aspects of the project. Makes assignments and

delegates authority, as needed to other parts of the project organization.

EPA Project QA Lead - provides leadership, development and oversight of project level

quality assurance for WSA in Office of Water

EPA ORD Technical Advisor – advises the Project Leader on the relevant experiences

and technology developed within ORD’s EMAP that are to be used in this project.

Serves as primary point-of-contact for project coordination in the absence or

unavailability of Project Leader.

Project Coordination - contractor providing day-to-day coordination of field

implementation as well as technical development of analysis of data. 

Study Design:

The assessment will utilize data from two separate field studies: EMAP-West and a new

field effort in the eastern 36 States. The same sample survey design was used for

EMAP-West as well as the eastern 36 States. The design for both was developed by

ORD’s Western Ecology Division to ensure comparability. Site selection is part of the

study design.

Field Protocol Development:

The field sampling protocols were developed by ORD for use in EMAP and were

developed with the purpose of providing consistent and representative information

across the country. The EMAP protocols used in the western US will be used the

eastern States contributing to WSA.

Field Logistics:

Implementation Coordinator – a contractor who functions on behalf of the Project

Leader to support all phases of the field implementation of the project. Primary

responsibility is to ensure all aspects of the project, i.e., technical, logistical,

organizational, are operating as smoothly as possible. Serves as point-of-contact for

questions from field crews and cooperators for all activities.

Training - eight training sessions will be conducted in various locations throughout the

eastern US. The EMAP team from ORD’s Western Ecology Division will conduct the
W adeable Streams Assessment August 2004 

QA Project Plan Page 5 of 71

initial 2 training sessions and a third session that focuses on training the trainers. A

Tetra Tech team will conduct the remaining 4 training sessions with an observer from

ORD there to assist if needed. A monitoring specialist from each EPA Regional Office

will also participate in each of the trainings. Each field crew must have a crew leader

who has received 3 days of lecture and field training to prepare them for this study. At

the end of the training period, each team will conduct a day long sampling on their own

under the watch of the trainers. This field readiness review will be the final QA check of

the training sessions. All field crews will be audited early in their sampling schedule to

be certain any corrections will be made at the onset of sampling.

Field Implementation -Fifteen States, six cooperators and two contract teams staffed by

Tetra Tech and GLEC will conduct the field implementation to collect samples using the

WSA protocols. 

Field Quality Evaluation and Assistance Reviews - Each field team will be visited by a

trained team from either an EPA Region, GLEC or Tetra Tech. The purpose of this

field evaluation and assistance review is to observe the crews implementing the

protocols as trained and provide any assistance or corrections necessary. This is

intended to catch deviations from the protocols before they become widespread.

Sample Flow:

Field samples will be shipped by the crews to one of several locations. All water

samples will be sent to the Western Ecology Division laboratory staffed by Dynamac. 

The macroinvertebrate samples will be shipped to one of 6 States or Cooperator

laboratories or GLEC for identification. The field data sheets will be shipped to the

Western Ecology Division information management team staffed by CSC for scanning

and entry into the database. Each of the organizations processing samples will

electronically transfer the results to CSC using the naming conventions and standards

provided by CSC.

Information Management:

The first stage of data processing will be to take the input from each of the responsible

laboratories and enter them into a common database for final verification and validation. 

Once the final data sets are made available for the assessment, copies of the data will

be transferred to EPA’s STORET and EPA’s EMAP dataset for long-term storage and

access. Working copies of the final data sets will be distributed to the States and

Cooperators and maintained at WED for analysis leading to the assessment.

Assessment:

The final assessment will be developed by a team, led by OW, that will include Office of

Water, Office of Environmental Information, several ORD research facilities, EPA

Regional Monitoring Coordinators, interested States and Cooperators. All States will be 

invited to participate in collaborative process to interpret results and shape data

assessment and report. The final assessment will include an appendix describing the

quality of the data used in the assessment. The final assessment will be delivered to
W adeable Streams Assessment August 2004 

QA Project Plan Page 6 of 71

the Assistant Administrator for Office of Water in December of 2005.

1.2.1 Project Schedule

The U.S. EPA has responded to a State and OW goal to report on the quality of the

Nation’s streams by no later than December, 2005. Figure 2 gives an overview of the

major tasks leading up to the final report. These activities are described throughout the

QAPP.

Figure 2. Timeline of WSA project activities

1.3 Scope of QA Project Plan

This QA Project Plan addresses all aspects of the data acquisition efforts of

WSA, which focuses on the 2004 sampling of streams in the eastern United States. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 7 of 71

The QA plan also deals with the data integration necessary between WSA and EMAP

Western Pilot Study (2001-2004) to create one complete report on the ecological status

of the Nation’s streams.

Data from approximately 500 stream sites in the eastern two-thirds of the United

States will be integrated with data from approximately 1000 stream sites in the western

United States for a comprehensive assessment. Relevant Companion documents to

this QAPP are: WSA: Site Evaluation Guidelines, WSA: Field Operations Manual, WSA:

Benthic Laboratory Methods, and WSA: Water Chemistry Laboratory Manual.

1.3.1 Overview of Field Operations

Field data acquisition activities are implemented for WSA (Table 1), based on

guidance developed for earlier EMAP studies (Baker and Merritt 1990). Survey

preparation is initiated with selection of the sampling locations by the EMAP Design

group (WED in Corvallis). The list of sampling locations is distributed to the EPA

Regional Monitoring Coordinators and cooperators. With the sampling location list,

Cooperator’s field crews can begin site reconnaissance on the primary sites and

alternate replacement sites and begin work on obtaining access permission to each

site. Specific procedures for evaluating each sampling location and for replacing nontarget sites are documented in the WSA: Site Evaluation Guidelines. Scientific

collecting permits from State and Federal agencies will be procured, as needed by the

respective State or cooperating organization. The field teams will use standard field

equipment and supplies which are being provided by EPA and GLEC. Field logistic 

coordinators (GLEC and Tetra Tech) will work with Regional Monitoring Coordinators,

Cooperators, States and Contractors to make certain the field crews have the

equipment and supplies they require in a timely fashion. Detailed lists of equipment

required for each field protocol, as well as guidance on equipment inspection and

maintenance, are contained in the Field Operations Manual. 

Table 1. Critical logistics elements (from Baker and Merritt, 1990)

Logistics Plan Component Required Elements

Project Management Overview of Logistic Activities

Staffing and Personnel Requirements

Communications

Access and Scheduling Sampling Schedule

Site Access

Reconnaissance

Safety Safety Plan

W aste Disposal Plan

Procurement and Inventory Control Equipm ent, Supplies, and Services Requirements

Procurement Methods and Scheduling
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Training and Data Collection Training Program

Field Operations Scenario

Laboratory Operations Scenarios

Quality Assurance

Information Management

Assessment of Operations Field Crew Debriefings

Logistics Review and Recomm endations

Field measurements and samples are collected by trained teams. All members

of each field team will attend one EPA-sponsored training session before the field

season in their state. Field quality evaluation and assistance review visits will be

completed for each team. Each team is comprised of 3 members; the number of teams

will be determined by the site evaluation/reconnaissance teams depending on number

of reaches sampled. The number and size of teams depends on the duration of the

sampling window, geographic distribution of sampling locations, number and complexity

of samples and field measurements, and other factors. The training program stresses

hands-on practice of methods, comparability among crews, collection of high quality

data and samples, and safety. Training will be provided in seven central locations for

cooperators and contractors. Project organizations responsible for training oversight

are identified in Figure 1. Training documentation will be maintained by the Tetra Tech

Training Support Team.

 

For each sampling location, a dossier is prepared and contains the following

applicable information: road maps, copies of written access permissions, scientific

collection permits, coordinates of index sites, information brochures on the program for

interested land owners, a topographic map with the index site location marked, and

local area emergency numbers. Team leaders will contact landowners approximately 2

days before the planned sampling date. As the design requires repeat visits to selected

sampling locations, it is important for the field teams to do everything possible to

maintain good relationships with landowners. This includes prior contacts, respect of

special requests, closing gates, minimal site disturbance, and removal of all materials

including flagging and trash.

A variety of methods may be used to access a site, including vehicles and boats. 

Some sampling locations require teams to hike in, transporting all equipment in

backpacks. For this reason, ruggedness and weight are important considerations in the

selection of equipment and instrumentation. Teams may need to camp out at the

sampling location and so are equipped with the necessary camping equipment.

 

The site verification process is shown in Figure 3. Upon arrival at a site, the

location is verified by a Global Positioning System (GPS) receiver, landmark

references, and/or local residents. Samples and measurements for various indicators

are collected in a specified order (Figure 4). This order has been set up to minimize the

impact of sampling for one indicator upon subsequent indicators; for example, water

chemistry samples from streams are collected before collecting benthic invertebrates as

the benthic invertebrate method calls for kicking up sediments. All methods are fully
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Figure 3. Site verification activities for stream field surveys.

documented in step-by-step procedures in the WSA: Field Operations Manual (USEPA

2004). The manual also contains detailed instructions for completing documentation,

labeling samples, any field processing requirements, and sample storage and shipping. 

Any revision of methods must be approved in advance by the EPA Project Leader. 

Field communications will be available through Field Coordinators, regularly scheduled

conference calls, a Communications Center, or an electronic mail/bulletin board.
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Standardized field data forms are provided to the field crews as the primary means

of data recording. On completion, the data forms are reviewed by a field crew member

other than the person who initially entered the information. Prior to departure from the

field site, the field team leader reviews all forms and labels for completeness and legibility

and ensures that all samples are properly labeled and packed. Each site has a unique

identifier provided by the design. All jars from a site have the same number. If additional

jars are needed, extra labels are provided.

On return from a field sampling site (either to the field team's home office or to a

motel), completed data forms are sent to the information management staff at WED for

entry into a computerized data base. At WED, electronic data files are reviewed 

independently to verify that values are consistent with those recorded on the field data

form or original field data file. 

Samples are stored or packaged for shipment in accordance with instructions

contained in the field manual. Water samples that exceed time limitations will not be

used. Samples which must be shipped are delivered to a commercial carrier. The

recipient is notified to expect delivery; thus, tracing procedures can be initiated quickly in

the event samples are not received. Bills of lading and chain-of-custody forms are

completed for all transfers of samples maintained by the labs, with copies also

maintained by the field team. The implementation coordinator maintains a centralized

tracking system of all shipments. 

The field operations phase is completed with collection of all samples or expiration

of the sampling window. Following completion of all sampling, a debriefing session will

be scheduled (see Table 1). These debriefings cover all aspects of the field program and

solicit suggestions for improvements. 

1.3.2 Overview of Laboratory Operations

Holding times for samples vary with the sample types and analytes. Thus, some

analytical analyses begin as soon as sampling (e.g., water chemistry) begins while others

are not even initiated until sampling has been completed (e.g., benthic

macroinvertebrates). Analytical methods are summarized in the specific SOPs (manuals)

that are companion documents to this QAPP. In most cases, standard methods are used

and are referenced. Where experimental methods are used or standard methods are

modified, these methods are documented in the laboratory methods manual or in internal

documentation, and may be described in SOPs developed by the analytical laboratory

and benthic macroinvertebrate laboratory.
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Figure 4. Summ ary of field activities stream and river sampling.

Chemical samples will be analyzed by the contract laboratory maintained

by ORD Western Ecology Division. The physical habitat measurements are made in the

field and recorded on the field data sheets and then scanned into a database at the

information management center at ORD Western Ecology Division. Benthic

macroinvertebrate samples will be processed by State, other Cooperator, and contractor

facilities. Laboratories providing analytical support must have the appropriate facilities to

properly store and prepare samples, and appropriate instrumentation and staff to provide

data of the required quality within the time period dictated by the project. Laboratories
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are expected to conduct operations using good laboratory practices (Table 2).

All laboratories providing analytical support to WSA (benthic and water

chemistry) must adhere to the provisions of this integrated QAPP. Laboratories will

 provide information documenting their ability to conduct the analyses with the required

level of data quality. Such information will include results from interlaboratory

comparison studies, analysis of performance evaluation samples, control charts and

results of internal QC sample or internal reference sample analyses to document

achieved precision, bias, accuracy, and method detection limits. Contracted laboratories

will be required to provide copies of their SOPs and audit reports. Water chemistry

laboratories may also be required to successfully analyze at least one performance

evaluation sample for target analytes before routine samples can be analyzed. 

Laboratory operations will be evaluated by technical systems audits, performance

evaluation studies, and by participation in interlaboratory sample exchange. 

Table 2. Guidelines for analytical support laboratories

! A program of scheduled maintenance of analytical balances, water purification systems,

microscopes, laboratory equipment, and instrumentation.

! Checking and recording the composition of fresh calibration standards against the previous

lot. Acceptable comparisons are ±2 percent of the theoretical value.

! Recording all analytical data in bound logbooks in ink, or on standardized recording forms.

! Monitoring and recording (in a logbook or on a recording form) temperatures and

performance of cold storage areas and freezer units. During periods of sample collection

operations, monitoring must be done on a daily basis.

! Verifying the efficiency of fume hoods.

 

! If needed, having a source of reagent water meeting American Society of Testing and

Materials (ASTM) Type I specifications for conductivity (< 1 :S/cm at 25 /C; ASTM 1984)

available in sufficient quantity to support analytical operations.

! Appropriate microscopes or other magnification for biological sample sorting and organism

identification.

! Labeling all containers used in the laboratory with date prepared, contents, and initials of the

individual who prepared the contents.

! Dating and storing all chem icals safely upon receipt. Chemicals are disposed of properly

when the expiration date has expired.

! Using a laboratory information management system to track the location and status of any

sample received for analysis.

! Reporting results using standard formats and units compatible with the information

managem ent system.
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1.3.3. Data Analysis and Reporting

A technical workgroup convened by and under the leadership of the EPA Project

Leader is responsible for outlining the final assessment report. Data analysis to support

this report will be conducted by the EMAP team at the Western Ecology Division 

Information management activities in support of this effort are discussed further in

Section 4. Data in the database are available to Cooperators for their own use upon

completion of the final verification and validation. The final data from the WSA will be

transferred to the OW STORET system and the EMAP information management system

administered at the Atlantic Ecology Division. 

2.0 DATA QUALITY OBJECTIVES

It is a policy of the U.S. EPA and its laboratories that Data Quality Objectives

(DQOs) be developed for all environmental data collection activities. Data quality

objectives are statements that describe the level of uncertainty that can be associated

with environmental data for their intended use. Data quality objectives thus provide the

criteria to design a sampling program within cost and resource constraints or technology

limitations imposed upon a project or study. 

2.1 Data Quality Objectives for WSA

 

Target DQOs established for WSA relate to the goal of describing the current

status in the condition of selected indicators of the condition of wadeable streams in the

conterminous U.S. and subregions of interest. The formal statement of the DQO for

national estimates is as follows:

! Estimate the proportion of stream length (± 5%) in the conterminous U.S. that falls

below the designated threshold for good conditions for selected

macroinvertebrates with 95% confidence.

For the subregions of interest (Omernik Level II Ecoregions) the DQO is:

! Estimate the proportion of stream length (± 15%) in a specific Level II Ecoregion

that falls below the designated threshold for good conditions for selected

macroinvertebrate measures with 95% confidence.

2.2 Measurement Quality Objectives

For each indicator, performance objectives (associated primarily with

measurement error) are established for several different attributes of data quality

(following Smith et al., 1988). Specific objectives for each indicator are presented in the

indicator section of this QAPP. The following sections define the data quality attributes
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(1)

and present approaches for evaluating them against acceptance criteria established for

the program.

2.2.1 Method Detection Limits

For chemical measurements, requirements for the method detection limit (MDL)

are established. The MDL is defined as the lowest level of analyte that can be

distinguished from zero with 99 percent confidence based on a single measurement

(Glaser et al., 1981). The MDL for an individual analyte is calculated as:

where t is a Students' t value at a significance level (") of 0.01 and n-1 degrees of

freedom (<), and s is the standard deviation of a set of n measurements of a standard

solution. The standard contains analyte concentrations between two and three times the

MDL objective, and is subjected to the entire analytical method (including any preparation

or processing stages). At least seven non-consecutive replicate measurements are

required to calculate a valid estimate of the MDL. Replicate analyses of the standard

should be conducted over a period of several days (or several different calibration

curves) to obtain a long-term (among-batch) estimate of the MDL.

Laboratories should periodically monitor MDLs on a per batch basis. Suggested

procedures for monitoring MDLs are: (1) to analyze a set of serial dilutions of a low level

standard, determining the lowest dilution that produces a detectable response; and (2) 

repeated analysis (at least seven measurements) of a low-level standard within a single

batch.

Estimates of MDLs (and how they are determined) are required to be submitted

with analytical results. Analytical results associated with MDLs that exceed the detection

limit objectives are flagged as being associated with an unacceptable MDL. Analytical

data that are below the estimated MDL are reported, but are flagged as being below the

MDL.

2.2.2 Sampling Precision, Bias, and Accuracy

 

Precision and bias are estimates of random and systematic error in a

measurement process (Kirchmer, 1983; Hunt and Wilson, 1986). Collectively, precision

and bias provide an estimate of the total error or uncertainty associated with an individual

measurement or set of measurements. Systematic errors are minimized by using

validated methodologies and standardized procedures. Precision is estimated from

repeated measurements of samples. Net bias is determined from repeated

measurements of solutions of known composition, or from the analysis of samples that

have been fortified by the addition of a known quantity of analyte. For analytes with large

ranges of expected concentrations, objectives for precision and bias are established in
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(2)

(3)

(4)

(5)

both absolute and relative terms, following the approach outlined in Hunt and Wilson,

1986. At lower concentrations, objectives are specified in absolute terms. At higher

concentrations, objectives are stated in relative terms. The point of transition between an

absolute and relative objective is calculated as the quotient of the absolute objective

divided by the relative objective (expressed as a proportion, e.g., 0.10 rather than as a

percentage, e.g., 10%). Final estimates will be calculated by the analysis staff at WED.

Precision in absolute terms is estimated as the sample standard deviation when

the number of measurements is greater than two: 

where is the value of the replicate, is the mean of repeated sample measurements,

and n is the number of replicates. Relative precision for such measurements is

estimated as the relative standard deviation (RSD, or coefficient of variation, [CV]):

where s is the sample standard deviation of the set of measurements, and equals the

mean value for the set of measurements.

Precision based on duplicate measurements is estimated based on the range of

measured values (which equals the difference for two measurements). The relative

percent difference (RPD) is calculated as:

where is the first measured value, is the second measured value. Precision

objectives based on the range of duplicate measurements can be calculated as:

where s represents the precision objective in terms of a standard deviation. Rangebased objectives are calculated in relative terms as:
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(6)

(7)

(8)

(9)

where RSD represents the precision objectives in terms of a relative standard deviation.

For repeated measurements of samples of known composition, net bias (B) is

estimated in absolute terms as:

where equals the mean value for the set of measurements, and T equals the

theoretical or target value of a performance evaluation sample. Bias in relative terms

(B[%]) is calculated as:

where equals the mean value for the set of measurements, and T equals the

theoretical or target value of a performance evaluation sample. 

Accuracy is estimated for some analytes from fortified or spiked samples as the

percent recovery. Percent recovery is calculated as:

where is the measured concentration of the spiked sample, is the concentration

of the unspiked sample, and is the concentration of the spike.

2.2.3 Taxonomic Precision and Accuracy

For WSA, taxonomic precision will be quantified by comparing whole-sample

identifications completed by independent taxonomists or laboratories. Accuracy of

taxonomy will be qualitatively evaluated through specification of target hierarchical levels

(e.g., family, genus, or species); and the specification of appropriate technical taxonomic

literature or other references (e.g., identification keys, voucher specimens). To calculate

taxonomic precision, 10 percent of the benthic macroinvertebrate samples will be

randomly-selected by Tetra Tech, the QA lab, sent by the WSA labs for re-identification

by Mike Winnell, Freshwater Benthic Services (FBS), 3250 Krause Rd. Petoskey, MI

49770 (Dr. Winnell’s extensive reference book bibliography is in the QA file at OWOW
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Hq and is available upon request.). Comparison of the results of whole sample reidentifications will provide a Percent Taxonomic Disagreement (PTD) calculated as:

where comppos is the number of agreements, and N is the total number of individuals in

the larger of the two counts. The lower the PTD, the more similar are taxonomic results

and the overall taxonomic precision is better. A measurement quality objective (MQO) of

15% is recommended for taxonomic difference or disagreement (overall mean #15% is

acceptable based on similar projects). Individual samples exceeding 15% are examined

for taxonomic areas of substantial disagreement, and the reasons for disagreement

investigated. 

Sample enumeration is another component of taxonomic precision. Sample

enumeration agreement will be checked with the same 10% of samples used to check

taxonomic precision. Final specimen counts for samples are dependent on the

taxonomist, not the rough counts obtained during the sorting activity. Comparison of

counts is quantified by calculation of percent difference in enumeration (PDE), calculated

as:

An MQO of 5% is recommended (overall mean of #5% is acceptable). Individual

samples exceeding 5% are examined to determine reasons for the exceedance.

Corrective actions for samples exceeding these MQOs can include defining the

taxa for which re-identification may be necessary (potentially even by third party), for

which samples (even outside of the 10% lot of QC samples) it is necessary, and where

there may be issues of nomenclatural or enumeration problems. Taxa lists will be

changed when disagreements are resolved by a third party.

Taxonomic accuracy is evaluated by having individual specimens representative of

selected taxa identified by recognized experts, usually contract or university affiliated

persons who have peer-reviewed publications for the taxonomic group they are

reviewing. Samples will be identified using the most appropriate technical literature that

is accepted by the taxonomic discipline and reflects the accepted nomenclature. The

Integrated Taxonomic Information System (ITIS, http://www.itis.usda.gov/) will be used to

verify nomenclatural validity and reporting. A reference collection will be compiled by

each lab as the samples are identified. Specialists in several taxonomic groups will verify

selected individuals of different taxa, as determined by the WSA workgroup.
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2.2.4 Completeness

Completeness requirements are established and evaluated from two perspectives. 

First, valid data for individual indicators must be acquired from a minimum number of

sampling locations in order to make subpopulation estimates with a specified level of

confidence or sampling precision. The objective of this study is to complete sampling at

95% or more of the 500 initial sampling sites and the 100 reference sites. Percent

completeness is calculated as: 

where V = number of measurements/samples judged valid, and T = total number

of planned measurements/samples. Within each indicator, completeness objectives are

also established for individual samples or individual measurement variables or analytes. 

These objectives are estimated as the percentage of valid data obtained versus the

amount of data expected based on the number of samples collected or number of

measurements conducted. Where necessary, supplementary objectives for

completeness are presented in the indicator-specific sections of this QAPP. 

2.2.5 Comparability

Comparability is defined as the confidence with which one data set can be

compared to another (Stanley and Verner, 1985; Smith et al., 1988). For all indicators,

comparability is addressed by the use of standardized sampling procedures, sampling

equipment and analytical methodologies by all sampling crews and laboratories. These

are also the same used to collect data in EMAP West studies. Comparability of data

within and among indicators is also facilitated by the implementation of standardized

quality assurance and quality control techniques and standardized performance and

acceptance criteria. For all measurements, reporting units and format are specified,

incorporated into standardized data recording forms, and documented in the information

management system. Comparability is also addressed by providing results of QA sample

data, such as estimates of precision and bias, conducting methods comparison studies

when requested by the grantees and conducting interlaboratory performance evaluation

studies among state, university, and WSA contract laboratories. If some incompatibility

between sampling crews comes to light, the data will be rejected.

2.2.6 Representativeness

Representativeness is defined as "the degree to which the data accurately and

precisely represent a characteristic of a population parameter, variation of a property, a

process characteristic, or an operational condition" (Stanley and Verner, 1985, Smith et

al., 1988). At one level, representativeness is affected by problems in any or all of the

other attributes of data quality.

At another level, representativeness is affected by the selection of the target
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surface water bodies, the location of sampling sites within that body, the time period

when samples are collected, and the time period when samples are analyzed. The

probability-based sampling design should provide estimates of condition of surface water

resource populations that are representative of the region. The individual sampling

programs defined for each indicator attempt to address representativeness within the

constraints of the sampling design and index sampling period. Holding time requirements

for analyses ensure analytical results are representative of conditions at the time of

sampling. Use of QC samples which are similar in composition to samples being

measured provides estimates of precision and bias that are applicable to sample

measurements.

3.0 SURVEY DESIGN

Many of the questions which USEPA’s Office of Water, States and Tribes are

attempting to address fundamentally require information about large numbers of systems

rather than individual systems. ORD has studied the role of monitoring surveys, their

evolution and the nature of existing federal monitoring programs, and can provide

information and assistance to the States and Tribes in this area.

The survey design for WSA is the same as used for EMAP-West. The design is a

sample survey design (a.k.a. probability design) that ensures a representative set of

sample sites from which inferences can be made about the target population. For the

WSA, the target population is all wadeable streams and rivers in the conterminous US. 

 

There is a large body of statistical literature dealing with sample survey designs

which addresses the problem of making statements about many by sampling the few

(e.g., Cochran 1977, Kish 1965, Kish 1987, Sarndal et al. 1992). Sample surveys have

been used in a variety of fields (e.g., election polls, monthly labor estimates, forest

inventory analysis, national wetlands inventory) to determine the status of populations

(large groups of sites) of interest, especially if the population is too numerous to census

or if it is unnecessary to census the population to reach the desired level of precision for

describing the population’s status. A key point in favor of probability based designs is

that they allow lower cost sampling programs because a smaller number of sites are able

to support conclusions with known accuracy and precision about status and trends of a

region.

Probability sampling surveys have been consistently used in some natural

resource fields. The National Agricultural Statistics Survey (NASS) conducted by the

U.S. Department of Agriculture and the Forest Inventory Analysis (FIA) conducted by the

U.S. Forest Service (Bickford et al. 1963, Hazard and Law 1989) have both used

probability based sampling concepts to monitor and estimate the condition and

productivity of agricultural and forest resources from a commodity perspective. National

Resources Inventory (NRI) was instituted initially because of concerns about the impact

of soil erosion on crop production. More recently, the National Wetland Inventory (NWI)

developed by the U.S. Fish and Wildlife Service (Wilen 1990) to estimate the extent of
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wetland acreage in the United States has used a probability based sampling design. But

no thorough review of all national programs has occurred until recently.

The survey designs used in EMAP to date have been documented in published

reports for each resource group and in the peer reviewed literature. Below a brief

description of the design concepts and the specific application for riverine systems is

provided. Much of this is extracted from various publications and from Stevens (1994)

which provides an excellent overview of the design concepts, issues and applications for

the entire program.

The EMAP sampling design strategy is based on the fundamental requirement for

a probability sample of an explicitly defined regional resource population, where the

sample is constrained to reflect the spatial dispersion of the population. 

A key property of a probability sample is that every element in the population has

some chance of being included in the sample. If this were not the case, then some parts

of the population might as well not exist, since no matter what, their condition could have

no influence on estimates of population characteristics. This property has a side benefit,

in that it forces an explicit and complete definition of the population being described. This

may seem trivial; however, in practice, it is almost never easy to tightly delimit a real,

physical population. For example, "lake" is a concept that has meaning for most people,

and the notion of "all lakes in the continental United States" would seem to define a

population. Nevertheless, an operational definition of membership is missing. The

operational definition must be complete enough to establish any body of water, from a

rain puddle up to Lake Superior, as either in or out of the population. Thus, the definition

must address such aspects as size limits (at least lower limits on area and depth), natural

lake versus constructed reservoir, temporal fluctuation (If a "lake" dries up during a

drought, is it still a lake? Was it a lake before the drought?), and amount of open water. 

Without such an operational definition, any statement about "all lakes in the United

States" has an unquantifiable vagueness. 

The stream resource does not fall neatly into either the discrete or extensive

category. The National Stream Survey (Messer et al., 1986; Overton, 1985) split streams

into reaches defined as the length of stream between confluences, or from the

headwaters down to the first confluence. Thus, streams were treated as a finite discrete

population. A grid was used to sample stream reaches by randomly placing a grid over a

topographic map of the area of interest, and then proceeding downhill along the fall line

until a stream reach was intersected. The approach that was taken avoids the necessity

of delimiting the resource areal units. The approach of EMAP-West is somewhat

different. The program focuses on the population of stream miles rather than stream

reaches. We wish to characterize the population in terms of the condition of length of

streams rather than numbers of stream reaches. Therefore, we want a sampling method

that samples a stream in proportion to its length; this is accomplished by viewing streams

as an extensive resource with length. The method described here is currently being used

in a pilot study, which among other goals, will examine the suitability of the method for a

larger study. 
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Stream traces are identified on 1:100,000-scale Digital Line Graphs, and a

Geographical Information System is used to intersect these with the sampling templates. 

Each stream segment within a template is identified and its length determined. The

endpoints of a segment are defined as confluences, headwaters ends, or intersections

with a template edge. Sets of connected segments of the same order are always kept

together in the sample selection process. The appropriate Strahler stream order is also

determined for each segment. 

Some differential weighting by size is necessary because of the predominance of

lower-order streams. The sample selection proceeds with inclusion probability for a

segment proportional to its length times the weight for its order. The total inclusion

probability for each template is calculated as the weighted sum of stream lengths in the

template, the templates are partitioned into groups using the partitioning algorithm

described for lakes, and the samples are selected in an analogous manner: the

partitions are randomized, the templates are randomized within the partitions, and the

sets of connected segments are randomized within the templates. The same systematic

selection protocol is used; however, in this case, the selection not only identifies the

stream segment to be sampled, but also identifies the point on that segment where the

sample is to be located. This is accomplished by recording the relative distance from the

beginning of the segment to the selected point on the segment. 

The types of questions which have been posed from various State and Tribal

agencies suggest that they would like to make statements about all streams and rivers. 

Clearly, sampling every mile of stream in the country is not economically feasible nor is it

necessary. Probability designs have been used in wide range of disciplines to address

this need (Converse 1987).

The primary objectives of this study are to estimate the condition of mapped

perennial wadeable streams and rivers, and the extent (total length) of mapped channels,

in conterminous states of the U.S. The objectives specify an interest in the target

population of wadeable perennial streams and rivers. 

One estimate of extent is provided by River Reach File Version 3 (RF3) which is

based on digitized blue lines from 1:100,000 scale maps. Based on prior information, it is

known that RF3 incorrectly codes some stream segments. Incorrect code information

occurs for (1) designating Strahler stream order; (2) delineating perennial and

intermittent, (3) defining natural versus constructed channels, including newly modified

channels, and (4) distinguishing irrigation return flow from irrigation delivery channels. In

some cases, RF3 includes stream channels that are not actually present, due to (1) no

definable channel present, (2) location is wetland/marsh with no defined channel, or (3)

channel may be an impoundment. RF3 may also exclude some stream channels due to

(1) mapping inconsistencies in construction of 1:100,000 maps, (2) digitization of map

blue lines, or (3) inadequacy of photo information used to develop maps, e.g. heavily

forested areas with low order streams. This study assumes that RF3 includes all stream

channels specified by the definition of the target population. That is, if stream channels

exist that are not included in RF3, they will not be addressed by this study.
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A secondary outcome of estimating the extent of the stream channel resource will

be estimates on the amount of miscoding present in RF3. Those stream segments

actually selected in the survey sample that are found to be miscoded will be submitted to

RF3 staff for correction. 

3.1 Probability-Based Sampling Design and Site Selection

Target Population: Within the conterminous U.S, all wadeable stream and river channels

(natural and constructed) mapped at 1:100,000 scale

Sample Frame: RF3 stream and river channel segments coded as R, S, T, N, W, (412,

413, 999) and U (414, 415).

This frame is subdivided into two major parts: (1) all RF3 stream, river and canal

segments coded as perennial, and (2) all RF3 stream, river and canal segments coded

as non-perennial, ie, all other stream, river and canal segments. The purpose of

subdividing the frame is to allow a sampling focus on systems that have an exceedingly

high probability of being flowing waters during the index sampling period.

Sites were selected for the WSA project using a hierarchical randomization design

process described by Stevens and Olsen (1999, 2003, 2004). The national hydrography

database (NHD) served as the frame representing streams and rivers in the US. Data

from approximately 500 stream sites in the eastern two-thirds of the United States will be

integrated with data from approximately 1000 stream sites in the western United States

for a comprehensive assessment. This total sample size will allow national reporting as

well as regional reporting at the scale of Omernik Level II ecoregions, the ten EPA

Regions and 10-15 major drainage basins.

Key features of the approach are (1) utilizing survey theory for continuous

populations within a bounded area, (2) explicit control of the spatial dispersion of the

sample through hierarchical randomization, (3) unequal probability of selection by

Strahler order, and (4) nested subsampling to incorporate intensified sampling in special

study regions.

Revisit Sites: Of the sites visited in the field and found to be target sites, a total of 10%

will be revisited. The 10% will be the first 10% of the sites visited. The primary purpose

of this revisit set of sites is to allow variance estimates that would provide information on

the extent to which the population estimates might vary.

Site Evaluation Sites: The number of sites that must be evaluated to achieve the

expected number of field sites that can be sampled can only be estimated based on

assumptions concerning expected error rates in RF3, percent of landowner refusals, and

percent of physically inaccessible sites. Based on the estimates gained in previous

studies, a list of alternate sites was selected at the same time as the base sites. These

alternate sites will be using in order until the desired sample size of 50 per region has

been achieved.
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4.0 INFORMATION MANAGEMENT

Like QA, information management (IM) is integral to all aspects of the WSA from

initial selection of sampling sites through dissemination and reporting of final, validated

data. QA and QC measures implemented for the IM system are aimed at preventing

corruption of data at the time of their initial incorporation into the system and maintaining

the integrity of data and information after incorporation into the system. The general

organization of, and QA/QC measures associated with, the IM system are described in

this section.

Long-term data from WSA, which includes data from the EMAP-West survey

activities and the survey activities conducted directly under WSA in the eastern 36

States, will be maintained in STORET and the EMAP data system at ORD’s Atlantic

Ecology Division. Project data management activities will be handled at EPA’s Western

Ecology Division and will be compliant with all relevant EPA and Federal data standards. 

Data will be shipped from sample processing laboratories to WED no later than March

2005. 

4.1 Data Policy

The WSA requires a continuing commitment to the establishment, maintenance,

description, accessibility, and long-term availability of high-quality data and information. 

All data used in the WSA will be maintained, following final verification and validation of

dataset, in EPA’s STORET and EPA’s EMAP data system.

Full and open sharing of the full suite of data and published information produced

by the study is a fundamental objective. Data and information will be available without

restriction for no more than the cost of reproduction and distribution. Where possible, the

access to the data will be via the World Wide Web through STORET and EMAP to keep

the cost of delivery to a minimum and to allow distribution to be as wide as possible. All

data collected by this study will be publicly available following verification and validation

of the dataset.

Organizations and individuals participating in the Study will ship all samples in a

timeline consistent with the field operations manual. Field data sheets will be sent

directly to WED for data entry. All laboratories processing samples will send final

electronic dataset to WED by March 2005. Data and metadata will be available for

assessment preparation by June 2005. Final dataset with metadata will be available via

STORET and EMAP at the time of delivery of the final report, December 2005.

All data sets and published information used in the study will be identified with a

citation; for data sets an indication of how the data may be accessed will be provided.

Data from this study will be maintained indefinitely. All EPA data policies will be followed

including EPA data standards, GIS, etc., as discussed in section 4.3. 
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4.2 Overview of System Structure

At each point where data and information are generated, compiled, or stored, the

information must be managed. Thus, the IM system includes all of the data-generating

activities, all of the means of recording and storing information, and all of the processes

which use data. The IM system includes both hardcopy and electronic means of

generating, storing, and archiving data. All participants in the WSA have certain

responsibilities and obligations which make them a part of the IM system. In its entirety,

the IM system includes site selection and logistics information, sample labels and field

data forms, tracking records, map and analytical data, data validation and analysis

processes, reports, and archives. IM staff supporting the WSA at WED provide support

and guidance to all program operations in addition to maintaining a central data base

management system for the WSA data.

The central repository for data and associated information collected for use by the

WSA is a DEC Alpha server system located at WED-Corvallis. The general organization

of the information management system is presented in Figure 5. Data are stored and

managed on this system using the Statistical Analysis System (SAS) software package. 

This centrally managed IM system is the primary data management center for the WSA

research conducted at WED and elsewhere. The IM staff receives, enters, and maintains

data and information generated by the site selection process (see Section 3), field

sample and data collection, map-based measurements, laboratory analyses, and

verification and validation activities completed by the states, cooperators and contractors. 

In addition to this inflow, the IM system provides outflow in provision of data files to WSA

staff and other users. The IM staff at WED is responsible for maintaining the security

integrity of both the data and the system.

The following sections describe the major inputs to the central data base and the

associated QA/QC processes used to record, enter, and validate measurement and

analytical data collected for EMAP surface waters research projects. Activities to

maintain the integrity and assure the quality of the contents of the IM system are also

described.

4.2.1 Design and Logistics Data Bases

The site selection process described in Section 3 produces a list of candidate

sampling locations, inclusion probabilities, and associated site classification data (e.g.,

target status, ecoregion, stream order, etc.). This “design” data base is provided to the

IM staff, implementation coordinators, and field coordinators. Field coordinators

determine ownership and contacts for acquiring permission to access each site, and

conduct reconnaissance activities. Ownership and reconnaissance information for each

site are compiled into a “logistics” data base. Generally, standardized forms are used 
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Figure 5. Organization of information management system modeled after EMAP-WEST for W SA.

during reconnaissance activities. Information from these forms may be entered into a

SAS compatible data management system. Whether in electronic or hardcopy format, a

copy of the logistics data base is provided to the IM for archiving storage.
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4.2.2 Sample Collection and Field Data Recording 

Prior to initiation of field activities, the IM staff works develops standardized field

data forms and sample labels. Preprinted adhesive labels having a standard recording

format are completed and affixed to each sample container. Precautions are taken to

ensure that label information remains legible and the label remains attached to the

sample. Examples of sample labels are presented in the field operations manual.

 

Field sample collection and data forms are designed in conjunction with IM staff to

ensure the format facilitates field recording and subsequent data entry tasks. All forms

which may be used onsite are printed on water-resistant paper. Copies of the field data

forms and instructions for completing each form are documented in the field operations

manuals. Recorded data are reviewed upon completion of data collection and recording

activities by a person other than the one who completed the form. Field crews check

completed data forms and sample labels before leaving a sampling site to ensure

information and data were recorded legibly and completely. Errors are corrected if

possible, and data considered as suspect are qualified using a flag variable. The field

crew enters explanations for all flagged data in a comments section. Completed field

data forms are transmitted to the IM staff at WED for entry into the central data base

management system.

All samples are tracked from the point of collection. Hardcopy tracking and

custody forms are completed by the field crews. Copies of the shipping and custody

record accompany all sample transfers; other copies are transmitted to the IMC and

applicable indicator lead. Samples are tracked to ensure that they are delivered to the

appropriate laboratory, that lost shipments can be quickly identified and traced, and that

any problems with samples observed when received at the laboratory are reported

promptly so that corrective action can be taken if necessary. Detailed procedures on

shipping and sample tracking can be found in Section 8.2 of the Field Operations Manual

Procedures for completion of sample labels and field data forms, and use of PCs

are covered extensively in training sessions. General QC checks and procedures

associated with sample collection and transfer, field measurements, and field data form

completion for most indicators are listed in Table 3. Additional QA/QC checks or

procedures specific to individual indicators are described in the indicator sections in

Section 5 of this QAPP. 
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Quality Control

Activity Description and/or Requirements

Contamination

Prevention

All containers for individual site sealed in plastic bags until use; specific

contamination avoidance measures covered in training

Sample

Identification

Pre-printed labels with unique ID number on each sample

Data Recording Data recorded on pre-printed forms of water-resistant paper; field crew

reviews data form s for accuracy, com pleteness, and legibility

Data Qualifiers Defined qualifier codes used on data form; qualifiers explained in comments

section on data form

Sample Custody Unique sample ID and tracking form information entered in LIMS; sam ple

shipment and receipt confirmed

Sample Tracking Sample condition inspected upon receipt and noted on tracking form with

copies sent to Indicator Lead, Communications Center, and/or IM

Data Entry Data entered using customized entry screens that resemble the data forms;

entries reviewed manually or by automated com parison of double entry

Data Submission Standard format defined for each measurement including units, significant

figures, and decimal places, accepted code values, and required field width

Data Archival All data archived in an organized manner for a period of seven years or until

written authorization for disposition has been received from the Surface

W aters Technical Director.

Table 3. Sample and field data quality control activities

4.2.3 Laboratory Analyses and Data Recording

Upon receipt of a sample shipment, analytical laboratory receiving personnel

check the condition and identification of each sample against the sample tracking record. 

Each sample is identified by information written on the sample label and by a barcode

label. Any discrepancies, damaged samples, or missing samples are reported to the IM

staff and indicator lead by telephone.

Most of the laboratory analyses for the WSA indicators, particularly chemical and

physical analyses, follow or are based on standard methods. Standard methods

generally include requirements for QC checks and procedures. General laboratory

QA/QC procedures applicable to most WSA indicators are described in Table 4. 

Additional QA/QC samples and procedures specific to individual indicator analyses are

described in the indicator sections in Part II of this QAPP. Biological sample analyses

are generally based on current acceptable practices within the particular biological

discipline. Some QC checks and procedures applicable to most WSA biological samples

are described in Table 5. Additional QA/QC procedures specific to individual biological

indicators are described in the indicator sections in Part II of this QAPP.

A laboratory's IM system may consist of only hardcopy records such as bench

sheets and logbooks, an electronic laboratory information management system (LIMS),

or some combination of hardcopy and electronic records. Laboratory data records are

reviewed at the end of each analysis day by the designated laboratory onsite QA
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Quality Control

Activity Description and/or Requirements

Sorting/Enumeration Re-sort 10% of samples and check counts of organisms

Taxonom ic Nomenclature Use accepted common and scientific nom enclature and unique entry

codes

Taxonomic Identifications Use standard taxonomic references and keys; maintain bibliography of

all references used

Independent Identifications Uncertain identifications to be confirmed by expert in particular taxa

Duplicate Identifications At least 5% of all samples completed per taxonomist reidentified by

different analyst; less than 10% assigned different ID

Taxonom ic

Reasonableness Checks

Species or genera known to occur in given conditions or geographic

area

Table 5. Biological sample quality control activities

Quality Control

Activity Description and/or Requirements

Instrument

Maintenance

Follow manufacturer's recommendations and specific guidelines in methods;

maintain logbook of maintenance/repair activities

Calibration Calibrate according to manufacturer's recommendations and guidelines given

in Section 6; recalibrate or replace before analyzing any samples

QC Data Maintain control charts, determine MDLs and achieved data attributes; include

QC data summ ary in submission package

Data Recording Use software compatible with EMAP-SW IM system; check all data entered

against the original bench sheet to identify and correct entry errors.

Review other QA data (e.g. condition upon receipt, etc.) for possible problems

with sample or specimens.

Data Qualifiers Use defined qualifier codes; explain all qualifiers

Data Entry Automated comparison of double entry or 100% manual check against original

data form

Submission

Package

Includes: Letter by the laboratory manager; data, data qualifiers and

explanations; electronic format compatible with EMAP-SW IM system,

documentation of file and data base structures, variable descriptions and

formats; summ ary report of any problems and corrective actions implemented

Table 4. Laboratory data quality control activities

coordinator or by supervisory personnel. Errors are corrected if possible, and data

considered as suspect by laboratory analysts are qualified with a flag variable. All

flagged data are explained in a comments section. Private contract laboratories

generally have a laboratory quality assurance plan and established procedures for

recording, reviewing, and validating analysis data.

Once analytical data have passed all of the laboratory's internal review

procedures, a submission package is prepared and transferred to the IM staff. The

contents of the submission package are largely dictated by the type of analysis (physical,

chemical, or biological), but generally includes at least the elements listed in Tables 4 or

5. All samples and raw data files (including logbooks, bench sheets, and instrument

tracings) are to be retained for a period of seven years or until authorized for disposal, in

writing, by the WSA Project Leader.
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Quality Control Activity Description and/or Requirements

Review any qualifiers associated with

variable

Determine if value is suspect or invalid; assign validation

qualifiers as appropriate

Summarize and review replicate sam ple

data

Identify replicate samples with large variance; determine

if analytical error or visit-specific phenomenon is

responsible

Determine if data quality objectives have

been achieved

Determine potential impact on achieving research and/or

program objectives

Exploratory data analyses (univariate,

bivariate, multivariate) utilizing all data

Identify outlier values and determine if analytical error or

site-specific phenomenon is responsible

Confirm assumptions regarding specific

types of statistical techniques being

utilized in development of metrics and

indicators

Determine potential impact on achieving research and/or

program objectives

Table 6. Data review, verification, and validation quality control activities

4.2.4 Data Review, Verification, Validation Activities

Raw data files are created from entry of field and analytical data, including data for

QA/QC samples and any data qualifiers noted on the field forms or analytical data

package. After initial entry, data are reviewed for entry errors by either a manual

comparison of a printout of the entered data against the original data form or by

automated comparison of data entered twice into separate files. Entry errors are

corrected and reentered. For biological samples, species identifications are corrected for

entry errors associated with incorrect or misspelled codes. Errors associated with

misidentification of specimens are corrected after voucher specimens have been

confirmed and the results are available. Files corrected for entry errors are considered to

be raw data files. Copies of all raw data files are maintained in the centralized IM

system.

Some of the typical checks made in the processes of verification and validation are

described in Table 6. Automated review procedures may be used. The primary purpose

of the initial checks is to confirm that a data value present in an electronic data file is

accurate with respect to the value that was initially recorded on a data form or obtained

from an analytical instrument. In general, these activities focus on individual variables in

the raw data file and may include range checks for numeric variables, frequency

tabulations of coded or alphanumeric variables to identify erroneous codes or misspelled

entries, and summations of variables reported in terms of percent or percentiles. In

addition, associated QA information (e.g., sample holding time) and QC sample data are

reviewed to determine if they meet acceptance criteria. Suspect values are assigned a

data qualifier until they can be corrected or confirmed as unacceptable and replaced with

a new acceptable value from sample reanalysis.

A second review is conducted after all analyses have been completed and the raw

data file is created. The internal consistency among different analyses or measurements
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conducted on a sample is evaluated. Examples of internal consistency checks include

calculation of chemical ion balances or the summation of the relative abundances of taxa. 

Samples identified as suspect based on internal consistency checks are qualified with a

flag variable and targeted for more intensive review. Data remain qualified until they can

be corrected, are confirmed as acceptable in spite of the apparent inconsistency, or until

new acceptable values are obtained from sample reanalysis. Upon completion of these

activities, copies of the resultant data files are transmitted for archival storage.

In the final stage of data verification and validation, exploratory data analysis

techniques may be used to identify extreme data points or statistical outliers in the data

set. Examples of univariate analysis techniques include the generation and examination

of box-and-whisker plots and subsequent statistical tests of any outlying data points. 

Bivariate techniques include calculation of Spearman correlation coefficients for all pairs

of variables in the data set with subsequent examination of bivariate plots of variables

having high correlation coefficients. Recently, multivariate techniques have been used in

detecting extreme or outlying values in environmental data sets (Meglen, 1985; Garner et

al., 1991; Stapanian et al., 1993). A software package, SCOUT, developed by EPA and

based on the approach of Garner et al. (1991) may be used for validation of multivariate

data sets.

Suspect data are reviewed to determine the source of error, if possible. If the error

is correctable, the data set is edited to incorporate the correct data. If the source of the

error cannot be determined, data are qualified as questionable or invalid. Data qualified

as questionable may be acceptable for certain types of data analyses and interpretation

activities. The decision to use questionable data must be made by the individual data

users. Data qualified as invalid are considered to be unacceptable for use in any

analysis or interpretation activities and will generally be removed from the data file and

replaced with a missing value code and explanatory comment or flag code. After

completion of verification and validation activities, a final data file is created, with copies

transmitted for archival and for uploading to the centralized IM system.

Once verified and validated, data files are made available for use in various types

of interpretation activities, each of which may require additional restructuring of the data

files. These restructuring activities are collectively referred to as "data enhancement." In

order to develop indicator metrics from one or more variables, data files may be

restructured so as to provide a single record per stream site. To calculate site population

estimates based on individual measurements or indicators, missing values and suspect

data points may need to be replaced with alternate data (such as a value from a replicate

measurement) or values calculated from predictive relationships based on other

variables. 

4.3 Data Transfer

Field crews may transmit data electronically via modem or floppy disc; hardcopies

of completed data and sample tracking forms may be transmitted to the IM staff at WED

via portable facsimile (FAX) machine or via express courier service. Copies of raw,

verified, and validated data files are transferred from states, cooperators, and contractors

to the IM staff for inclusion in the central IM system. All transfers of data are conducted
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using a means of transfer, file structure, and file format that has been approved by the IM

staff. Data files that do not meet the required specifications will not be incorporated into

the centralized data access and management system. 

4.4 Core Information Management Standards

Participants will adhere to the “Core Information Management Standards for the

EMAP Western Study.” National and international standards will be used to the greatest

extent possible. This section details a list of standards pertaining to information

management that all participants in the WSA agree to follow. The goal of these core

standards is to maximize the ability to exchange data with other studies conducted under

the monitoring framework of the Committee on the Environment and Natural Resources

(CENR 1997). The main standards are those of the Federal Geographic Data Committee

(FGDC 1999), the National Spatial Data Infrastructure (NSDI 1999), and the National

Biological Information Infrastructure (NBII 1999).

4.4.1 Metadata

Federal Geographic Data Committee Content standard for digital geospatial

metadata, version 2.0. FGDC-STD-001-1998 (FGDC 1998), including the Biological Data

Profile and the Biological Names and Taxonomy Data Standards developed by the

National Biological Information Infrastructure (NBII 1999).

For tabular data, metadata that meet the FGDC content standard are contained by

a combination of the EMAP Data Directory and the EMAP Data Catalog. For ARC/INFO

coverages, the metadata are in the .DOC file embedded in the coverage. This file stays

with the coverage. When the coverage is moved to the EMAP public web sites, it will be

duplicated to an ASCII text file.

4.4.2 Data Directory

The EMAP Data Directory is maintained as an Oracle database. The guidelines

are given in Frithsen and Strebel (1995), Frithsen (1996a, b) and USEPA (1996b).

Other data: Environmental Information Management system (EIMS 1999). EMAP

Directory entries are periodically uploaded to the EIMS. The EIMS will become EPA’s

node for the National Spatial Data Infrastructure and will make directory information

available to other federal agencies through the Z39.50 protocol in accordance with the

US Global Change Research Program (USGCRP 1998)

4.4.3 Data Catalog

Data catalog standards are given in Frithsen and Strebel (1995), Frithsen (1996a),

and USEPA (1996c).

4.4.4 Data Formats

4.4.4.1 Attribute data 

ASCII files: comma-separated values, or space-delimited, or fixed column

SAS export files
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Oracle

4.4.4.2 GIS data 

ARC/INFO export files; compressed .tar file of ARC/INFO workspace

Spatial Data Transfer Standard (SDTS) (FGDC 1999) format available on request

4.4.5 Parameter Formats

Sampling Site (EPA Locational Data Policy (USEPA 1991)

Latitude and Longitude in decimal degrees (+/- 7.4)

Negative longitude values (west of the prime meridian)

NAD83

Date: YYYYMMDD (year, month, day)

Hour: HHMMSS (hour, minute, second)

Greenwich mean time

Local time

Data loaded to STORET will take on the STORET formats upon loading.

4.4.6 Standard Coding Systems

Chemical Compounds: Chemical Abstracts Service (CAS 1999)

Species Names: Integrated Taxonomic Information system (ITIS 1999)

Land cover/land use codes: Multi-Resolution Land Characteristics (MRLC 1999)

4.5 Hardware and Software Control

All automated data processing (ADP) equipment and software purchased for or

used in WSA surface waters research is subject to the requirements of the federal

government, the particular Agency, and the individual facility making the purchase or

maintaining the equipment and software. All hardware purchased by EPA is identified

with an EPA barcode tag label; an inventory is maintained by the responsible ADP

personnel at the facility. Inventories are also maintained of all software licenses; periodic

checks are made of all software assigned to a particular PC.

The development and organization of the IM system is compliant with guidelines

and standards established by the EMAP Information Management Technical

Coordination Group, the EPA Office of Environmental Information (OEI), and the EPA

office of Administrative Resources Management (OARM). Areas addressed by these

policies and guidelines include, but are not limited to, the following: 

! Taxonomic Nomenclature and Coding 

! Locational data

! Sampling unit identification and reference

! Hardware and software

! Data catalog documentation

The WSA is committed to compliance with all applicable regulations and guidance

concerning hardware and software procurement, maintenance, configuration control, and
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QA/QC. As new guidance and requirements are issued, the WSA information

management staff will assess the impact upon the IM system and develop plans for

ensuring timely compliance.

4.6 Data Security

All data files in the IM system are protected from corruption by computer viruses,

unauthorized access, and hardware and software failures. Guidance and policy

documents of EPA and management policies established by the IM Technical

Coordination Group for data access and data confidentiality are followed. Raw and

verified data files are accessible only to the WSA collaborators. Validated data files are

accessible only to users specifically authorized by the EPA Project Leader. Data files in

the central repository used for access and dissemination are marked as read-only to

prevent corruption by inadvertent editing, additions, or deletions.

Data generated, processed, and incorporated into the IM system are routinely

stored as well as archived on redundant systems. This ensures that if one system is

destroyed or incapacitated, IM staff will be able to reconstruct the data bases. 

Procedures developed to archive the data, monitor the process, and recover the data are

described in IM documentation.

Several backup copies of all data files and of the programs used for processing

the data are maintained. Backups of the entire system are maintained off-site. System

backup procedures are utilized. The central data base is backed up and archived

according to procedures already established for WED. All laboratories generating data

and developing data files must have established procedures for backing up and archiving

computerized data. 

5.0 INDICATORS

5.1 Benthic Macroinvertebrates

5.1.1 Introduction

The benthic invertebrate assemblage found in sediments and on substrates of

streams reflect an important aspect of the biological condition of the stream. The

response of benthic communities to various stressors can often be used to determine the

type of stressor and to monitor trends (Klemm et al., 1990). The overall objectives of the

benthic invertebrate indicators are to detect stresses on community structure in wadeable

streams and to assess and monitor the relative severity of those stresses. The benthic

invertebrate indicator procedures are based on various recent bioassessment literature

(Barbour et al. 1999, Hawkins et al. 2000, Peck et al. 2003).
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Figure 6. Sampling design for the benthic indicator.

5.1.2 Sampling Design

Benthic invertebrates are collected at randomly selected sampling locations on the

cross-sectional transects established along the stream reach. A composite of

invertebrates is collected from a multi-habitat approach and consists of sampling pools,

riffles, runs, and glides. The index sampling design is illustrated in Figure 6.
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5.1.3 Sampling and Analytical Methodologies

Sample Collection: Benthic invertebrates are collected from an approximately 930

cm2 (0.09 m2) area randomly selected at each of 11 cross-sectional transects. Samples

collected using a modified D-frame kick-net (500 :m mesh) procedure are composited

together to produce a 1.02 m2 areal sample. Samples are field-processed to remove

large detritus(rinsed and inspected for organisms) and preserved in ethanol. Detailed

sampling and processing procedures are described in section of the field operations

manual. A condensed description of key elements of the field activities is provided for

easy reference onsite.

Analysis: Preserved composite samples are sorted, enumerated, and

invertebrates identified to the genus level (see Attachment 4 of the Benthic Laboratory

Manual) using specified standard keys and references. Processing and archival methods

are based on standard limnological practices. Detailed procedures are contained in the

laboratory operations manual and cited references. There is no maximum holding time

associated with preserved benthic invertebrate samples. Five hundred benthic organism

count is the target number to match the EMAP West protocal. A 10% external check is

standard QA for EMAP West. For operational purposes of the WSA, laboratory sample

processing should be completed by March 2005. Table 7 summarizes field and analytical

methods for the benthic invertebrates indicator.

Table 7. Field and laboratory methods: benthic indicator

Variable or

Measurement

QA

Class

Expected

Range

and/or Units

Summary of Method References

Sample

Collection

C NA One-man D-frame kick net (500

: mesh) used to collect

organisms, which are

com posited from 11 transects

Barbour et al. 1999,

Peck et al. 2003,

W SA Field Operation

Manual 2004

Sorting and

Enumeration

C 0 to 500

organisms

Random systematic selection of

grids with target of 500

organisms from sample

W SA Benthic

Laboratory Methods

2004

Identification C genus Specified keys and references

 C = critical, N = non-critical quality assurance classification.

5.1.4 Quality Assurance Objectives

Measurement quality objectives (MQOs) are given in Table 8. General

requirements for comparability and representativeness are addressed in Section 2. The

MQOs given in Table 8 represents the maximum allowable criteria for statistical control

purposes. Precision is calculated as percent efficiency, estimated from examination of

randomly selected sample residuals by a second analyst and independent identifications

of organisms in randomly selected samples. The MQO for picking accuracy is estimated

from examinations (repicks) of randomly selected residues by experienced taxonomists.
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Table 8. Measurement data quality objectives: benthic indicator

Variable or Measurement Precision Accuracy Completeness

Sort and Pick 95% 90% 99%

Identification 85% 90%a 99%

 NA = not applicable

 

a

 Taxonomic accuracy, as calculated using Equation 10 in Section 2.

The completeness objectives are established for each measurement per site type

(e.g., probability sites, revisit sites, etc.). Failure to achieve the minimum requirements

for a particular site type results in regional population estimates having wider confidence

intervals. Failure to achieve requirements for repeat and annual revisit samples reduces

the precision of estimates of index period and annual variance components, and may

impact the representativeness of these estimates because of possible bias in the set of

measurements obtained.

5.1.5 Quality Control Procedures: Field Operations

Specific quality control measures are listed in Table 9 for field operations.

5.1.6 Quality Control Procedures: Laboratory Operations

Specific quality control measures are listed in Table 10 for laboratory operations. 

Figure 6 presents the general process for collecting and analyzing benthic invertebrate

samples.

5.1.7 Data Management, Review, and Validation

Checks made of the data in the process of review, verification, and validation are

summarized in Table 11. The Project Facilitation Team is ultimately responsible for

ensuring the validity of the data, although performance of the specific checks may be

delegated to other staff members. Once data have passed all acceptance requirements,

computerized data files are prepared in a format specified for the WSA project by EMAP

and copied onto a floppy diskette. The diskettes are transferred to the WSA IM

Coordinator (Marlys Cappaert) for entry into a centralized data base. A hard copy output

of all files accompanies each diskette.

A reference specimen collection is prepared as new taxa are encountered in

samples. This collection consists of preserved specimens in vials and mounted on slides

and is provided to the responsible EPA laboratory as part of the analytical laboratory

contract requirements. The reference collection is archived at the responsible EPA

laboratory.
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Table 9.Laboratory Quality Control: benthic macroinvertebrate sample processing

Check or

Sample

Description Frequency Acceptance Criteria Corrective Action

SAMPLE PROCESSING (PICK AND SORT)

Sample

residuals

examined by

different

analyst

within lab

10% of all

samples

completed

per analyst

Efficiency of picking $90% If <90%, exam ine all

residuals of samples by

that analyst and retrain

analyst

Sorted

samples

sent to

independent lab

10% of all

samples

Accuracy of contractor laboratory

picking and identification $90%

If picking accuracy <90%,

all samples in batch will be

reanalyzed by contractor

Table 10: Laboratory Quality Control: benthic macroinvertebrate taxonomic identification

 

Check or

Sample

Description Frequency Acceptance Criteria Corrective Action

Duplicate

identification

by different

taxonomist

within lab

10% of all

samples

completed

per

laboratory

Efficiency $85% If #85%, reidentify all

samples completed by that

taxonomist

Independent

identification

by outside

taxonomist

All

uncertain

taxa

Uncertain identifications to be

confirmed by expert in particular

taxa

Record both tentative and

independent IDs

Use

widely/com

monly

excepted

taxonom ic

references

For all

identificatio

ns

All keys and references used

must be on bibliography

prepared by another laboratory

If other references desired,

obtain permission to use

from Project QA Officer

Prepare

reference

collection

Each new

taxon per

laboratory

Complete reference collection to

be maintained by each individual

laboratory

Benthic Lab Manager

periodically reviews data

and reference collection to

ensure reference collection

is complete and

identifications are accurate
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Sample residuals, vials, and slides are archived by each laboratory until the WSA

Project Leader has authorized, in writing, the disposition of samples. All raw data

(including field data forms and bench data recording sheets) are retained in an organized

fashion indefinitely or until written authorization for disposition has been received from the

WSA Project Leader.

Table 11: Data validation quality control: benthic indicator

Check Description Frequency Acceptance Criteria Corrective Action

Taxonomic "reasonableness"

checks

All data

sheets

Genera known to occur in

given stream conditions or

geographic area

Second or third

identification by

expert in that taxon

5.1.8 Data Analysis Plan

Specific research issues to be addressed from this year's activities and the

ecological attributes or metrics associated with the benthic indicator are summarized in

Table 12.

Table 12. Research issues: benthic indicator

Research Issues Design Strategy

Variance Estimates Obtain estimates of variance components from duplicate samples and revisits to

sites.

Indicator Development

and Evaluation

Identify best set of ecological attributes or metrics that are broadly applicable to

assessing biological condition and are informative as to detection and

characterization of impairment. Candidate attributes are selected measures of

richness, O/E, representatives of sensitive taxa. These are based on EPA’s

biological condition graient attributes as part of the aquatic life use initiative.

Methods Comparability Use standardized guidelines ( from the NWQMC Methods and Data Comparability

Board) for methods comparability studies (to measure precision and sensitivity

along environmental and disturbance gradients), and select ecological attributes

best suited to compare performance of methods (e.g., compositional metrics, or

richness adjusted for reference).

Threshold Development

for Assessment

Develop general expectations for each attribute (for each ecoregion) from

collection of reference sites sampled with WSA methods. Supplement with

information from states and existing data where methods differences are not an

issue. Combining data for an integrated assessment is based on minimizing

sampling bias. Explore the use of thresholds based on % difference, e.g., 20%

deviation from reference as a consistent means of evaluating biological condition

across ecoregions.

Biological Condition Develop an ordinal scale related to a biological condition gradient to reflect

varying degrees of quality.
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5.2 Physical Habitat Quality Indicator

5.2.1 Introduction

Naturally occurring differences in physical habitat structure and associated

hydraulic characteristics among surface waters contributes to much of the observed

variation in species composition and abundance within a zoogeographic province. 

Structural complexity of aquatic habitats provides the variety of physical and chemical

conditions to support diverse biotic assemblages and maintain long-term stability. 

Anthropogenic alterations of riparian physical habitat, such as channel alterations,

wetland drainage, grazing, agricultural practices, weed control, and streambank

modifications such as revetments or development, generally act to reduce the complexity

of aquatic habitat and result in a loss of species and ecosystem degradation. References

are in Table 13.
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Figure 7: Laboratory Processing Activities for the benthic indicator
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For WSA, indicators derived from data collected on physical habitat quality will be

used to help explain or characterize stream condition relative to biological response and

trophic state indicators. Specific groups of physical habitat attributes important in stream

ecology include: channel dimensions, gradient, substrate; habitat complexity and cover;

riparian vegetation cover and structure; anthropogenic alterations; and channel-riparian

interaction (Kaufmann, 1993). Overall objectives for this indicator are to develop

quantitative and reproducible indices, using both multivariate and multimetric

approaches, to classify streams and to monitor biologically relevant changes in habitat

quality and intensity of disturbance.

5.2.2 Sampling Design

As the physical habitat indicator is based on field measurements and

observations, there is no sample collection associated with this indicator. Field crews are

provided with 1:24,000 maps with the midpoint (index site) of the stream reach marked. 

At WSA sites, eleven cross-sectional measurement transects are spaced at equal

intervals proportional to baseflow channel width, thereby scaling the sampling reach

length and resolution in proportion to stream size. A systematic spatial sampling design

is used to minimize bias in the selection of the measurement sites. Additional

measurements are made at equally spaced intervals between the cross-sectional sites. 

A “rapid” assessment of habitat quality of the entire sampling reach is conducted based

on the Rapid Bioassessment Protocol (RBP; Barbour et al., 1999).

5.2.3 Sampling Methodologies

Field Measurements: Field measurements, observations, and associated

methodology for the protocol are summarized in Table 13; methodology for the RBP is

described in Barbour et al. (1999) and in the WSA Field Operations Manual (2004). 

Detailed procedures for completing both protocols are provided in the field operations

manual; equipment and supplies required are also listed. All measurements and

observations are recorded on standardized forms which are later entered in to the central

EMAP surface waters information management system at WED-Corvallis.

There are no sample collection or laboratory analyses associated with the physical

habitat measurements.

5.2.4 Quality Assurance Objectives

Measurement data quality objectives (measurement DQOs or MQOs) are given in

Table 14. General requirements for comparability and representativeness are addressed

in Section 2. The MQOs given in Table 14 represent the maximum allowable criteria for

statistical control purposes. Precision is determined from results of revisits by a different

crew (field measurements) and by duplicate measurements by the same crew on a

different day.

The completeness objectives are established for each measurement per site type (e.g.,

WSA sites, revisit sites, state comparability sites). Failure to achieve the minimum
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requirements for a particular site type results in regional population estimates having

wider confidence intervals. Failure to achieve requirements for repeat and annual revisit

samples reduces the precision of estimates of index period and annual variance

components, and may impact the representativeness of these estimates because of

possible bias in the set of measurements obtained.

Table 13. Field measurem ent methods: physical habitat indicator.

Variable or

Measurement Units

QA

Class Summary of Method References

THALW EG PROFILE

Thalweg depth cm C Measure maximum depth at 100-150

points along reach with surveyor's

rod and meter stick

W etted width 0.1m C Measure wetted width with meter

stick or measuring tape on

perpendicular line to mid-channel

line

Habitat class none N Visually estimate channel habitat

using defined class descriptions

Frissell et al, 1986

W OODY DEBRIS TALLY

Large woody

debris

number

of

pieces

N Visually estimate amount of woody

debris in baseflow channel using

defined class descriptions

Robison and

Beschta, 1990

CHANNEL AND RIPARIAN CROSS-SECTIONS

Slope and

bearing

percent/

degrees

C Backsight between cross-section

stations using clinometer,

rangefinder compass, and tripod

Stack, 1989;

Robison and

Kaufmann, in

prep.

Substrate size mm C At 5 points on cross section,

estimate size of one selected particle

using defined class descriptions

W ollman, 1954;

Bain et al, 1985;

Plafkin et al, 1989

Bank angle degrees N Use clinometer and surveyors rod to

measure angle

Platts et al, 1983

Bank incision 0.1m N Visually estimate height from water

surface to first terrace of floodplain

Bank undercut cm N Measure horizontal distance of

undercut

Bankful width 0.1m N Measure width at top of bankful

height

Bankful height 0.1m N Measure height from water surface

to estimated water surface during

bankful flow
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Table 13. Field measurem ent methods: physical habitat indicator.

Variable or

Measurement Units

QA

Class Summary of Method References

Table 14. Measurement data quality objectives: physical habitat indicator

Variable or Measurement Precision Accuracy Completeness

Field Measurements and Observations ±10%* NA 90%

Map-Based Measurements ±10% NA 100%

 NA = not applicable *Not for RBP measures

Canopy cover points

of intersection

C Count points of intersection on

densiometer at specific points and

directions on cross-section

Lemm on, 1957;

Mulvey et al, 1992

Riparian

vegetation

structure

percent N Observations of ground cover,

understory, and canopy types and

coverage of area 5 m on either side

of cross section and 10 m back from

bank

Fish cover,

algae,

macrophytes

percent C Visually estimate in-channel features

5 m on either side of cross section

Human

influence

none C Estimate presence/absence of

defined types of anthropogenic

features

STREAM DISCHARGE

Discharge m/s or

L/min.

N Velocity-Area m ethod, Portable W eir

method, timed bucket discharge

method

Linsley et al, 1982 

5.2.5 Quality Control Procedures: Field Operations

Specific quality control measures are listed in Table 15 for field measurements and

observations.

5.2.6 Quality Control Procedures: Laboratory Operations

There are no laboratory operations associated with this indicator.
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Table 15. Field quality control: physical habitat indicator

Check Description Frequency Acceptance Criteria

Corrective

Actions

Check totals for cover

class categories

(vegetation type, fish

cover) 

Each transect Sum must be

reasonable

(best professional

judgement)

Repeat

observations

Check completeness

of thalweg depth

measurem ents

Each site Depth m easurem ents

for all sampling points

Obtain best

estim ate of depth

where actual

measurement not

possible

Check calibration of

multiprobe

Prior to each sampling

day

Specific to instrument Adjust and

recalibrate, 

redeploy gear

5.2.7 Data Management, Review, and Validation

Checks made of the data in the process of review, verification, and validation are

summarized in Table 16. The Indicator Lead is ultimately responsible for ensuring the

validity of the data, although performance of the specific checks may be delegated to

other staff members. All raw data (including all standardized forms and logbooks) are

retained in an organized fashion for seven years or until written authorization for

disposition has been received from the WSA Project Coordinator.

Table 16. Data validation quality control: physical habitat indicator

Check Description Frequency Acceptance Criteria Corrective Action

Estimate precision of

measurements based on

repeat visits by different

crews

At least 2 team s visit

stream 1 time each at

10% of streams (may

be same team or

different teams)

Measurem ents

should be within 10

percent

Review data for

reasonableness;

Determine if

acceptance criteria

need to be modified

5.3 Water Chemistry Indicator

5.3.1 Introduction

Ecological indicators based on lake and stream water chemistry information

attempt to evaluate stream condition with respect to stressors such as acidic deposition

and other types of physical or chemical contamination. Data are collected for a variety of

physical and chemical constituents to provide information on the acid-base status of each

stream, water clarity, primary productivity, nutrient status, mass balance budgets of

constituents, color, temperature regime, and presence and extent of anaerobic

conditions.
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At each stream site, crews fill one 4-L Cubitainer and two 60-mL syringes with

stream water. These samples are stored in a cooler packed resealable plastic bags filled

with ice and shipped to the analytical laboratory within 24 hours of collection. The

primary function of the water chemistry information is to determine:

• Acid-base status

• Trophic state (nutrient enrichment)

• Chemical stressors

• Classification of water chemistry type

Specific research questions and hypotheses to be addressed from this year's activities

are listed in Table 17.

Table 17. Research questions and hypotheses: water chemistry indicator

W SA Design Evaluation: Obtain estimates of regional variation.

Indicator Development and Evaluation: Development of chemical classes based on different types of

chemical stressors (e.g., acid min drainage), examine relationship of chemical condition/stress to

watershed landuse, and develop indicator(s) of chemical condition (e.g., trophic state [Carlson, 1977]).

5.3.2 Sampling Design

The plot design for stream sampling is shown in Figure 7. The plot design for

water chemistry sampling is based on that used for the Wadeable Streams Assessment

(Kaufmann et al., 1988). At each stream, a single index site is located at the midpoint of

the designated stream reach. At each index site, a single water sample is collected. .

5.3.3 Sampling and Analytical Methodologies

Sample Collection: At the stream index site, a water sample is prepared from a

series of eight 500-mL grab samples collected from the upper portion of the water

column. In lotic systems the flowing water gives a composite from different parcels.

These grab samples are composited into a single 4-L bulk water sample. Two syringe

samples for closed system measurements are collected by immersing each 60 ml syringe

into the stream at the index site and drawing water from under the surface into the

syringe without exposure to the atmosphere. Detailed procedures for sample collection

and handling are described in the field operations manual.
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Figure 8. Stream index sam pling design for the water chem istry indicator.

Analysis: Table 18 summarizes analytical methodologies for the chemical

parameters. Analytical methods are based on EPA-validated methods, modified for use

with aqueous samples of low ionic strength. Modified methods are thoroughly

documented in the laboratory methods handbook prepared for the Aquatic Effects

Research Program ( U.S. EPA, 1987).

5.3.4 Quality Assurance Objectives

Measurement data quality objectives (measurement DQOs or MQOs) are given in

Table 19. General requirements for comparability and representativeness are addressed

in Section 2. The MQOs given in Table 19 represent the maximum allowable criteria for

statistical control purposes. Method detection limits are monitored over time by repeated

measurements of low level standards and calculated using Equation 2-1. For major
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cations and anions, the required MDLs are approximately equivalent to 1.0 :eq/L (0.5

:eq/L for nitrate). The analytical laboratory may report results in mg/L; these results are

converted to :eq/L for interpretation. For total suspended solids determinations, the

"detection limit" is defined based on the required sensitivity of the analytical balance.

For precision, the objectives presented in Table 19 represent the 99 percent

confidence intervals about a single measurement and are thus based on the standard

deviation of a set of repeated measurements (n > 1). Precision objectives at lower

concentrations are equivalent to the corresponding MDL. At higher concentrations, the

precision objective is expressed in relative terms, with the 99 percent confidence interval

based on the relative standard deviation (Section 2). Objectives for accuracy are equal

to the corresponding precision objective, and are based on the mean value of repeated

measurements. Accuracy is generally estimated as net bias or relative net bias (Section

2). For total phosphorus and total nitrogen measurements, accuracy is also determined

from analyses of matrix spike samples (also sometimes called fortified samples) as

percent recovery (Section 2). Precision and bias are monitored at the point of

measurement (field or analytical laboratory) by several types of QC samples described in

the Section 5.3.6, and from performance evaluation (PE) samples

Table 18. Analytical methodologies: water chemistry indicator

Analyte

QA

Class Expected Range Summary of Method References

pH, closed

system

C 3 to 9 pH units Sample collected and

analyzed without exposure

to atmosphere;

electrometric determination

(pH meter and glass

combination electrode)

EPA 150.6 (modified);

U.S. EPA (1987)

pH, equilibrated N 3 to 9 pH units Equilibration with 300 ppm

CO2 for 1 hr prior to

analysis; Electrometric

determination (pH meter

and glass combination

electrode)

EPA 150.6 (modified);

U.S. EPA (1987)

Acid

Neutralizing

Capacity (ANC)

C -100 to 5,000 :eq/L Acidimetric titration to pH #

3.5, with modified Gran plot

analysis

EPA 310.1 (modified);

U.S. EPA (1987)

Carbon,

dissolveda

inorganic (DIC),

closed system

N 0.1 to 50 m g C/L Sample collected and

analyzed without exposure

to atmosphere; acidpromoted oxidation to CO2

,

with detection by infrared

spectrophotometry

U.S. EPA (1987)

Carbon,

dissolved

organic (DOC)

C 0.1 to 30 m g C/L UV-promoted persulfate

oxidation, detection by

infrared spectrophotom etry.

EPA 415.2, U.S. EPA

(1987)

Conductivity C 1 to 500 :S/cm Electrolytic (conductance

cell and meter)

EPA 120.6, U.S. EPA

(1987)
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Analyte

QA

Class Expected Range Summary of Method References

Aluminum, total

dissolved

C 10 to 1,000 :g/L Atomic absorption spectroscopy (graphite furnace)EPA 202.2; U.S. EPA

(1987)

Aluminum,

monom eric and

organic

monom eric

N 0 to 500 :g/L Collection and analysis

without exposure to atmosphere. Portion of

sample passed through a

cation exchange column

before analysis to obtain

estimate of organic-bound

fraction. Colorimetric

analysis (automated

pyrocatechol violet).

APHA 3000-Al E.; APHA

(1989), U.S. EPA (1987)

Major Cations (dissolved)

 Calcium

 Magnesium

 Sodium

 Potassium

C

C

C

C

0.02 to 76 mg/L

(1 to 3,800 :eq/L)

0.01 to 25 mg/L

(1 to 2,000 :eq/L)

0.01 to 75 mg/L

(0.4 to 3.3 :eq/L)

0.01 to 10 mg/L

(0.3 to 250 :eq/L)

Atomic absorption spectroscopy (flame)EPA 200.6, U.S. EPA

(1987)

Ammonium N 0.01 to 5 m g/L

(0.5 to 300 :eq/L)

Colorimetric (automated

phenate)

EPA 350.7; U.S. EPA

(1987)

Major Anions, dissolved

 Chloride

 Nitrate

 Sulfate

C

C

C

0.03 to 100 mg/L

(1 to 2,800 :eq/L)

0.06 to 20 mg/L

(0.5 to 350 :eq/L)

0.05 to 25 mg/L

(1 to 500 :eq/L)

Ion chromatography EPA 300.6; U.S. EPA

(1987)

Silica, dissolved N 0.05 to 15 mg/L Autom ated colorimetric

(molybdate blue)

EPA 370.1 (modified),

U.S. EPA (1987)

Phosphorus,

total

C 0 to 1000 :g/L Acid-persulfate digestion

with autom ated colorimetric

determination (molybdate

blue)

USGS I-4600-78;

Skougstad et al. (1979),

U.S. EPA (1987)
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Analyte

QA

Class Expected Range Summary of Method References

Nitrogen, total N 0 to 25,000 :g/L Alkaline persulfate digestion with determination of

nitrate by cadmium reduction and determination of

nitrite by automated

colorimetry (EDTA/sulfanilimide).

EPA 353.2 (modified);

U.S. EPA (1987)

True Color N 0 to 300 Platinum

Cobalt Units (PCU)

Visual com parison to

calibrated glass color disks

EPA 100.2 (modified),

APHA 204 A.; U.S. EPA

(1987)

Turbidity N 1 to 100 Nephelometric Turbidity

Units (NTU)

Nephelom etric APHA 214 A., EPA

180.1; U.S. EPA (1987)

Total

Suspended

Solids (TSS)

N 1 to 200 m g/L Gravimetric EPA 160.3; APHA

(1989)

Table 19. Measurement data quality objectives: water chemistry indicator

Variable or Measurement

Method

Detection

Limit Precision and Accuracy

Transition 

Valuea Completeness

Oxygen, dissolved NA ±0.5 mg/L NA 95%

Tem perature NA ±1 ±C NA 95%

pH, closed system and

equilibrated

NA ±0.075 or ±0.15 pH units pH 5.75 95%

Acid Neutralizing Capacity NA ±5 :eq/L or ±5% 100 :eq/L 95%

Carbon, dissolved

inorganic, closed system

0.10 mg/L 0.10 mg/L or 10% 1 mg/L 95%

Carbon, dissolved organic 0.1 m g/L ±0.1 mg/L or ±10% 1 mg/L 95%

Conductivity NA ±1 :S/cm or ±2% 50 :S/cm 95%

Aluminum, total dissolved,

total monomeric, and

organic monom eric

10 :g/L ±10 :g/L or ±10% 100 :g/L 95%

Major Cations:

Calcium

Magnesium

Sodium

Potassium

0.02 mg/L

0.01 mg/L

0.02 mg/L

0.04 mg/L

±0.02 mg/L or ±5%

±0.01 mg/L or ±5%

±0.02 mg/L or ±5%

±0.04 mg/L or ±5%

0.4 m g/L

0.2 m g/L

0.4 m g/L

0.8 m g/L

95%

Ammonium 0.02 mg/L ±0.02 mg/L or ±5% 0.4 m g/L 95%
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Variable or Measurement

Method

Detection

Limit Precision and Accuracy

Transition 

Valuea Completeness

Major Anions:

Chloride

Nitrate

Sulfate

0.03 mg/L

0.03 mg/L

0.05 mg/L

±0.03 mg/L or ±5%

±0.03 mg/L or ±5%

±0.05 mg/L or ±5%

0.6 m g/L

0.6 m g/L

1 mg/L

95%

Silica 0.05 mg/L ±0.05 mg/L or ±5% 1 mg/L 95%

Phosphorus, total 1 :g/L ±1 :g/L or ±5% 20 :g/L 95%

Nitrogen, total 1 :g/L ±1 :g/L or ±5% 20 :g/L 95%

True Color NA ±5 PCU or ±10% 50 PCU 95%

Turbidity NA ±2 NTU or ±10% 20 NTU 95%

Total Suspended Solids 0.1 mg ±1 mg/L or ±10% 10 m g/L 95%

 NA = not applicable

 

a

 Represents the value above which precision and bias are expressed in relative terms.

.5.3.5 Quality Control Procedures: Field Operations

Water chemistry field measurements are optional for this project.

5.3.6 Quality Control Procedures: Laboratory Operations

5.3.6.1 Sample Receipt and Processing 

QC activities associated with sample receipt and processing are presented in

Table 20. The communications center and information management staff are notified of

sample receipt and any associated problems as soon as possible after samples are

received. The general schemes for processing stream water chemistry samples for

analysis is presented in Figure 9. In addition to the four syringes prepared in the field,

several additional aliquots are prepared from bulk water samples. Ideally, all analyses

are completed within a few days after processing to allow for review of the results and

possible reanalysis of suspect samples within seven days. Critical holding times for the

various analyses are the maximum allowable holding times, based on current EPA and

American Public Health Association (APHA) requirements (American Public Health

Association, 1989). Analyses of samples after the critical holding time is exceeded will

likely not provide representative data. 

5.3.6.2 Analysis of Samples 

QC protocols are an integral part of all analytical procedures to ensure that the

results are reliable and the analytical stage of the measurement system is maintained in

a state of statistical control. Most of the QC procedures described here are detailed in
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the references for specific methods. However, modifications to the procedures and

acceptance criteria described in this QAPP supersede those presented in the methods

references. Information regarding QC sample requirements and corrective actions are

summarized in Table 21. Figure 10 illustrates the general scheme for analysis of a batch

of water chemistry samples, including associated QC samples.

5.3.7 Data Reporting, Review, and Management

Checks made of the data in the process of review, verification, and validation are

summarized in Table 22. Data reporting units and significant figures are given in Table

23. The Indicator Lead is ultimately responsible for ensuring the validity of the data,

although performance of the specific checks may be delegated to other staff members. 

Table 20. Sample processing quality control: water chemistry indicator

Quality

Control

Activity Description and Requirements Corrective Action

Sample

Storage

Store samples in darkness at 4/C

Monitor tem perature daily

Qualify sample as suspect for

all analyses

Holding time Complete processing bulk samples within 48 hours of

collection

Qualify samples

Aliquot

Containers

and

Preparation 

Rinse collection bottles 2 times with stream water to be

sampled 

Filtration 0.4 :m polycarbonate filters required for all dissolved

analytes except DIC (0.45 :m)

Rinse filters and filter chamber twice with 50-ml portions

of deionized water, followed by a 20-mL portion of

sample. Repeat for each filter used on a single sample.

Rinse aliquot bottles with two 25 to 50 mL portions of

filtered sample before use. 

Preservation Use ultrapure acids for preservation.

Add sufficient acid to adjust to pH < 2. Check pH with

indicator paper.

Record volume of preservative on container label.

Store preserved aliquots in darkness at 4/C until

analysis.

Holding

Times for

preserved

aliquots

Closed system determinations from syringe samples

must be completed within 72 hours of collection.

Holding times for other analyses holding times range

from 3 days to 6 months, based upon current APHA

criteria.

Sample results are qualified as

being in violation of holding

time requirements.
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Figure 9. Sample processing activities for water chemistry

samples.
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Table 21. Laboratory quality control samples: water chemistry indicator

QC Sample Type

(Analytes), and

Description Frequency

Acceptance

Criteria Corrective Action

Laboratory Blank: (all

analyses except pH and

total suspended

solids[TSS])

Reagent Blank: (DOC, Al

[total, monomeric, and

organic monomeric], ANC,

NH4

+

, SiO2)

Once per

batch prior

to sam ple

analysis

Control limits < ±MDL Prepare and analyze new

blank. Determine and

correct problem (e.g.,

reagent contamination,

instrument calibration, or

contamination introduced

during filtration) before

proceeding with any

sample analyses.

Reestablish statistical

control by analyzing three

blank samples.

Filtration Blank: (All

dissolved analytes,

excluding syringe samples)

ASTM Type II reagent water

processed through filtration

unit. 

Prepare

once per

week and.

archive

Measured concentrations <

MDL

Measure archived

samples if review of other

laboratory blank

information suggest

source of contam ination is

sample processing.

Detection Limit Quality

Control Check Sam ple

(QCCS): (All analyses

except true color, turbidity,

and TSS)

Prepared so concentration

is approxim ately four to six

times the required MDL. 

Once per

batch

Control limits < ±MDL Confirm achieved MDL by

repeated analysis of

appropriate standard

solution. Evaluate

affected samples for

possible re-analysis.

Calibration QCCS: 

For turbidity, a QCCS is

prepared at one level for

routine analyses (U.S. EPA,

1987). Additional QCCSs

are prepared as needed for

samples having estimated

turbidities greater than 20

NTU.

For total suspended solids

determinations, QCCS is a

standard weight having

mass representative of

samples.

Before and

after

sample

analyses

Control limits < precision

objective: Mean value < bias

objective

Repeat QCCS analysis.

Recalibrate and analyze

QCCS.

Reanalyze all routine

samples (including PE

and field replicate

samples) analyzed since

the last acceptable QCCS

measurem ent. 
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QC Sample Type

(Analytes), and

Description Frequency

Acceptance

Criteria Corrective Action

Internal Reference Sam ple: 

(Suggested when available

for a particular analyte)

One

analysis in

a minimum

of five

separate

batches

Control limits < precision

objective.

Mean value < bias objective

Analyze standard in next

batch to confirm

suspected imprecision or

bias.

Evaluate calibration and

QCCS solutions and

standards for

contamination and

preparation error. Correct

before any further

analyses of routine

sam ples are conducted. 

Reestablish control by

three successive

reference standard

measurem ents which are

acceptable. 

Qualify all sample batches

analyzed since the last

acceptable reference

standard measurement

for possible reanalysis.

Laboratory Replicate

Sample: (All analyses)

For closed system analyses,

a replicate sample

represents a second

injection of sample from the

sealed syringe.

One per

batch

Control limits < precision

objective

If results are below MDL:

Prepare and analyze split

from different sample

(volume permitting).

Review precision of

QCCS measurements for

batch.

Check preparation of split

sample.

Qualify all sam ples in

batch for possible

reanalysis.
W adeable Streams Assessment August 2004 

QA Project Plan Page 55 of 71

QC Sample Type

(Analytes), and

Description Frequency

Acceptance

Criteria Corrective Action

Matrix spike sam ples: (Only

prepared when samples

with potential for matrix

interferences are

encountered)

One per

batch

Control limits for recovery

cannot exceed 100±20%

 Select two additional

samples and prepare

fortified subsamples.

Reanalyze all suspected

samples in batch by the

method of standard

additions. Prepare three

subsamples (unfortified,

fortified with solution

approximately equal to the

endogenous

concentration, and

fortified with solution

approximately twice the

endogenous

concentration.
W adeable Streams Assessment August 2004 

QA Project Plan Page 56 of 71

Figure 10. Analysis activities for water chemistry samples.
W adeable Streams Assessment August 2004 

QA Project Plan Page 57 of 71

Table 22. Data validation quality control: water chemistry indicator

Activity or Procedure Requirements and Corrective Action

Range checks, summ ary statistics, and/or

exploratory data analysis (e.g., box and

whisker plots)

Correct reporting errors or qualify as suspect or invalid.

Review holding times Qualify value for additional review

Ion balance: Calculate percent ion balance

difference (%IBD) using data from cations,

anions, pH, and ANC.

If total ionic strength # 100 :eq/L, %IBD # ±25%.

If total ionic strength > 100 :eq/L, %IBD # ±10%. 

Determine which analytes, if any, are the largest

contributors to the ion imbalance. Review suspect

analytes for analytical error and reanalyze.

If analytical error is not indicated, qualify sample to attribute

imbalance to unmeasured ions. Reanalysis is not required.

Flag= unacceptable %IBD

Flag= %IBD outside acceptance criteria due to

unmeasured ions

Conductivity check: Compare measured

conductivity of each sample to a calculated

conductivity based on the equivalent

conductances of major ions in solution

(Hillman et al., 1987).

If m easured conductivity # 25 :S/cm,

 ([measured ! calculated] ÷ measured) # ±25%.

If measured conductivity > 25 :S/cm,

 ([measured ! calculated] ÷ measured) # ±15%.

Determine which analytes, if any, are the largest

contributors to the difference between calculated and

measured conductivity.

Review suspect analytes for analytical error and reanalyze.

If analytical error is not indicated, qualify sample to attribute

conductivity difference to unmeasured ions. Reanalysis is

not required.

Aluminum check: Compare results for

organic monom eric aluminum, total

monom eric aluminum, and total dissolved

alum inum . 

[organic m onomeric] < [total monomeric] < [total dissolved].

Review suspect measurement(s) to confirm if analytical

error is responsible for inconsistency. 

ANC check: Calculate ANC based on pH

and DIC. Compare to measured ANC

Review suspect m easurem ents for samples with results

outside of acceptance criteria. Determine if analytical error

or non-carbonate alkalinity are responsible for lack of

agreement.

Review data from QA sam ples (laboratory

PE samples, and interlaboratory comparison

samples)

Compare with results from other years to determine

comparability. Determine impact and possible limitations

on overall usability of data
W adeable Streams Assessment August 2004 

QA Project Plan Page 58 of 71

Table 23. Data reporting criteria: water chemistry indicator

Measurement Units

No.

Significant

Figures

Maximum No.

Decimal Places

Dissolved Oxygen mg/L 2 1

Tem perature /C 2 1

pH pH units 3 2

Carbon, dissolved inorganic mg/L 3 2

Carbon, dissolved organic mg/L 3 1

Acid neutralizing capacity :eq/L 3 1

Conductivity :S/cm at 25 /C 3 1

Aluminum (total dissolved, total 

monom eric, and organic

monom eric)

:g/L 3 0

Calcium, magnesium, sodium,

potassium, ammonium, chloride,

nitrate, and sulfate

:eq/L 3 1

Silica mg/L 3 2

Total phosphorus and total nitrogen :g/L 3 0

Turbidity NTU 3 0

True color PCU 2 0

Total suspended solids mg/L 3 1

The ion balance for each sample is computed using the results for major cations,

anions, and the measured acid neutralizing capacity. The percent ion difference (%IBD)

for a sample is calculated as:

where ANC is the acid neutralization capacity, cations are the concentrations of calcium,

magnesium, sodium, potassium, and ammonium, converted from mg/L to :eq/L, anions

are chloride, nitrate, and sulfate (converted from mg/L to :eq/L), and H+ is the hydrogen

ion concentration calculated from the antilog of the sample pH. Factors to convert major

ions from mg/L to :eq/L are presented in Table 24. For the conductivity check,

equivalent conductivities for major ions are presented in Table 25.
W adeable Streams Assessment August 2004 

QA Project Plan Page 59 of 71

Table 24. Constants for converting major ion concentrations from mg/L to :eq/L

Analyte Conversion from

mg/L to :eq/La

Calcium 49.9

Magnesium 82.3

Potassium 25.6

Sodium 43.5

Ammonium 55.4

Chloride 28.2

Nitrate 16.1

Sulfate 20.8

a

 Measured values are m ultiplied by the conversion factor.

Table 25. Factors to calculate equivalent conductivities of major ionsa

Ion Equivalent

Conductance per

mg/L (:S/cm at 25 /C)

Ion Equivalent

Conductance per

mg/L (:S/cm at 25 /C)

Calcium 2.60 Nitrate 1.15

Magnesium 3.82 Sulfate 1.54

Potassium 1.84 Hydrogen 3.5 × 105 b

Sodium 2.13 Hydroxide 1.92 × 105 b

Ammonium 4.13 Bicarbonate 0.715

Chloride 2.14 Carbonate 2.82

a

 From Hillman et al. (1987).

b

 Specific conductance per mole/L, rather than per mg/L.

6.0 FIELD AND BIOLOGICAL LABORATORY QUALITY EVALUATION

AND ASSISTANCE VISITS

No national program of accreditation for benthic macroinvertebrate collections and

sample processing currently exists. However, national standards of performance and

audit guidance for biological laboratories are being considered by the National

Environmental Laboratory Accreditation Conference (NELAC). For this reason, a

rigorous program of field and laboratory evaluation and assistance visits has been

developed to support the Wadeable Streams Assessment Program. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 60 of 71

Procedural review and assistance personnel are trained to the specific

implementation and data collection methods detailed in the WSA field operations manual. 

Plans and checklists for field evaluation and assistance visit have been developed to

reinforce the specific techniques and procedures for both field and laboratory

applications. The plans and checklists are included in this section and describe the

specific evaluation and corrective actions procedures.

It is anticipated that evaluation and assistance visits will be conducted with each

Field Team early in the sampling and data collection process, and that corrective actions

will be conducted in real time. These visits provide a basis for the uniform evaluation of

the data collection techniques, and an opportunity to conduct procedural reviews as

required to minimize data loss due to improper technique or interpretation of program

guidance. Through uniform training of field crews and review cycles conducted early in

the data collection process, sampling variability associated with specific implementation

or interpretation of the protocols will be significantly reduced. The field visits evaluations,

while performed by a number of different supporting collaborator agencies and

participants, will be based on the uniform training, plans, and checklists. This review and

assistance task will be conducted for each unique crew collecting and contributing data

under this program; hence no data will be recorded to the project database that were

produced by an ‘unaudited’ process, or individual. 

Similarly, laboratory evaluation and assistance visits will be conducted early in the

project schedule and soon after sample processing begins at each laboratory to ensure

that specific laboratory techniques are implemented consistently across the multiple

laboratories generating data for the program. Laboratory evaluation and checklists have

been developed to ensure uniform interpretation and guidance in the procedural reviews. 

These laboratory visits are designed such that full corrective action plans and remedies

can be implemented in the case of unacceptable deviations from the documented

procedures observed in the review process without recollection of samples. 

The Field and Laboratory Evaluation and Assistance Visit Plans are described in

sections 6.1 and 6.2. 

6.1 NATIONAL WADEABLE STREAMS ASSESSMENT FIELD QUALITY

EVALUATION AND ASSISTANCE VISIT PLAN

Evaluators: One or more designated EPA or Contractor staff members who are

qualified (i.e., have completed training) in the procedures of the WSA field

sampling operations.

 

To Evaluate: Field Sampling Teams during sampling operations on site.

Purpose: To identify and correct deficiencies during field sampling operations.

1. Tetra Tech project staff will review the Field Evaluation and Assistance Visit Plan and

Check List with each Evaluator during field operations training sessions. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 61 of 71

2. The Tetra Tech QA Officer or authorized designee will send a copy of the final Plan

and 4-part carbonless copy versions of the final Check List pages, envelopes to return

the Check Lists, a clipboard, pens, and WSA QAPP and Field Operations Manual to

each participating Evaluator.

3. Each Evaluator is responsible for providing their own field gear sufficient to

accompany the Field Sampling Teams (e.g., protective clothing, sunscreen, insect

repellent, hat, hip boots or waders, water bottle, food, back pack, cell phone) during a

complete sampling cycle. Schedule of the Field visits will be made by the Evaluator in

consultation with the Tetra Tech QA Officer and respective Field Crew Leader. 

Evaluators should be prepared to spend additional time in the field if needed

(see below).

4. Tetra Tech and the Regional Monitoring Coordinators will arrange the schedule of

visitation with each Field Team, and notify the Evaluators concerning site locations,

where and when to meet the team, and how to get there. Ideally, each Field Team will

be evaluated within the first two weeks of beginning sampling operations, so that

procedures can be corrected or additional training provided, if needed. GLEC or EPA

Evaluators will visit Tetra Tech Field Teams and Tetra Tech or EPA Evaluators will

visit GLEC Field Teams. Any EPA or Contractor Evaluator may visit State Field

Teams.

5. A Field Team for the WSA consists of a three-person crew where, at a minimum, the

Field Crew Leader is fully trained.

6. If members of a Field Team changes, and a majority (i.e., two) of the members have

not been evaluated previously, the Field Team must be evaluated again during

sampling operations as soon as possible to ensure that all members of the Field

Team understand and can perform the procedures.

7. The Evaluator will view the performance of a team through one complete set of

sampling activities as detailed on the Field Evaluation and Assistance Check List.

a. Scheduling might necessitate starting the evaluation midway on the list of tasks at

a site, instead of at the beginning. In that case, the Evaluator will follow the team

to the next site to complete the evaluation of the first activities on the list.

b. If the Team misses or incorrectly performs a procedure, the Evaluator will note this

on the checklist and immediately point this out so the mistake can be corrected on

the spot. The role of the Evaluator is to provide additional training and guidance

so that the procedures are being performed consistent with the Field Operations

Manual, all data are recorded correctly, and paperwork is properly completed at

the site.

c. When the sampling operation has been completed, the Evaluator will review the

results of the evaluation with the Field Team before leaving the site (if practicable),
W adeable Streams Assessment August 2004 

QA Project Plan Page 62 of 71

noting positive practices and problems (i.e., weaknesses [might affect data

quality], deficiencies [would adversely affect data quality]). The Evaluator will

ensure that the Team understands the findings and will be able to perform the

procedures properly in the future.

d. The Evaluator will record responses or concerns, if any, on the Field Evaluation

and Assistance Check List.

e. If the Evaluator's findings indicate that the Field Team is not performing the

procedures correctly, safely, or thoroughly, the Evaluator must continue working

with this Field Team until certain of the Team's ability to conduct the sampling

properly so that data quality is not adversely affected.

f. If the Evaluator finds major deficiencies in the Field Team operations (e.g., less

than three members, equipment or performance problems) the Evaluator must

contact one of the following QA officials:

Dr. Esther Peters, Tetra Tech QA Officer (703-385-6000)

Ms. Robin Silva-Wilkinson, GLEC QA Officer (231-941-2230)

Mr. Otto Gutenson, EPA WSA Project QA Officer (202-566-1183)

The QA official will contact the Project Implementation Coordinator (Michael

Barbour – 410-356-8993) or Project Technical Advisor (Steve Paulsen – 541-754-

4428) to determine the appropriate course of action.

Data records from sampling sites previously visited by this Field Team will be

checked to determine whether any sampling sites must be redone.

g. Complete the Field Evaluation and Assistance Check List, including a brief

summary of findings, and ensure that all Team members have read this and

signed off before leaving the Team.

8. Retain the back copy of each page of the Field Evaluation and Assistance Check List

(color: ____________ ). Fasten the pages of the check list for each Field Team

together with a paper clip.

9. Mail the remaining pages of each completed Field Evaluation and Assistance Check

List to

Dr. Esther Peters

Tetra Tech, Inc.

10306 Eaton Place, Suite 340

Fairfax, VA 22030

10. The Tetra Tech QA Officer or authorized designee will review the returned Field

Evaluation and Assistance Check Lists, note any issues, check off the completion

of the evaluation for each Field Team, and distribute the remaining pages of each
W adeable Streams Assessment August 2004 

QA Project Plan Page 63 of 71

check list as follows:

Original: Tetra Tech QA Officer file, Fairfax, VA

Color: _________ Tetra Tech Project Manager file, Owings Mills, MD

Color: _________ WSA QA Officer file, Washington, DC

6.2 NATIONAL WADEABLE STREAMS ASSESSMENT LABORATORY

QUALITY EVALUATION AND ASSISTANCE VISIT PLAN

Evaluators: One or more designated Contractor staff members who are qualified

(i.e., have completed training) in the procedures of the WSA biological laboratory

operations.

 

To Evaluate: Biological laboratories performing subsampling, sorting, and 

taxonomic procedures to analyze collected stream samples.

Purpose: To identify and correct deficiencies during laboratory operations.

1. Tetra Tech project staff will review the Laboratory Evaluation and Assistance Visit

Plan and Check List with each Evaluator prior to conducting laboratory evaluations. 

2. The Tetra Tech QA Officer or authorized designee will send a copy of the final Plan

and 4-part carbonless copy versions of the final Check List pages, envelopes to return

the Check Lists, a clipboard, pens, and WSA QAPP and Benthic Laboratory Methods

manual to each participating Evaluator.

3. Schedule of lab visits will be made by the Evaluator in consultation with the Tetra

Tech QA Officer and the respective Laboratory Supervisor Staff. Evaluators should

be prepared to spend additional time in the laboratory if needed (see below).

4. Tetra Tech will arrange the schedule of visitation with each participating Laboratory,

and notify the Evaluators concerning site locations, where and when to visit the

laboratory, and how to get there. Ideally, each Laboratory will be evaluated within the

first two weeks following initial receipt of samples, so that procedures can be

corrected or additional training provided, if needed. 

5. The Evaluator will view the performance of the laboratory sorting process and QC

Officer through one complete set of sample processing activities as detailed on the

Laboratory Evaluation and Assistance Check List.

a. Scheduling might necessitate starting the evaluation midway on the list of tasks for
W adeable Streams Assessment August 2004 

QA Project Plan Page 64 of 71

processing a sample, instead of at the beginning. In that case, the Evaluator will

view the activities of the Sorter when a new sample is started to complete the

evaluation of the first activities on the list.

b. If a Sorter or QC Officer misses or incorrectly performs a procedure, the Evaluator

will note this on the checklist and immediately point this out so the mistake can be

corrected on the spot. The role of the Evaluator is to provide additional training

and guidance so that the procedures are being performed consistent with the

Benthic Laboratory Methods manual, all data are recorded correctly, and

paperwork is properly completed at the site.

c. When the sample has been completely processed, the Evaluator will review the

results of the evaluation with the Sorter and QC Officer, noting positive practices

and problems (i.e., weaknesses [might affect data quality], deficiencies [would

adversely affect data quality]). The Evaluator will ensure that the Sorter and QC

Officer understand the findings and will be able to perform the procedures properly

in the future.

d. The Evaluator will record responses or concerns, if any, on the Laboratory

Evaluation and Assistance Check List.

e. If the Evaluator's findings indicate that Laboratory staff are not performing the

procedures correctly, safely, or thoroughly, the Evaluator must continue working

with these staff members until certain of their ability to process the sample

properly so that data quality is not adversely affected.

f. If the Evaluator finds major deficiencies in the Laboratory operations, the Evaluator

must contact one of the following QA officials:

Dr. Esther Peters, Tetra Tech QA Officer (703-385-6000)

Mr. Dennis McCauley, GLEC QA Officer (231-941-2230)

Mr. Otto Gutenson, EPA WSA Project QA Officer (202-566-1183)

The QA official will contact the Project Implementation Coordinator (Michael

Barbour – 410-356-8993) or Project Technical Advisor (Steve Paulsen – 541-754-

4428) to determine what should be done.

Data records from samples previously processed by this Laboratory will be

checked to determine whether any samples must be redone.

g. Complete the Laboratory Evaluation and Assistance Check List, including a brief

summary of findings, and ensure that the Sorter and QC Officer have read this

and signed off before leaving the Laboratory.

6. Retain the back copy of each page of the Laboratory Evaluation and Assistance
W adeable Streams Assessment August 2004 

QA Project Plan Page 65 of 71

Check List (color: ____________ ). Fasten the pages of the check list for each Sorter

together with a paper clip.

Mail the remaining pages of each completed Laboratory Evaluation and Assistance

Check List to

Dr. Esther Peters

Tetra Tech, Inc.

10306 Eaton Place, Suite 340

Fairfax, VA 22030

7. The Tetra Tech QA Officer or authorized designee will review the returned Laboratory

Evaluation and Assistance Check Lists, note any issues, check off the completion of

the evaluation for each participating Laboratory, and distribute the remaining pages of

each check list as follows:

Original: Tetra Tech QA Officer file, Fairfax, VA

Color: _________ Tetra Tech Project Manager file, Owings Mills, MD

Color: _________ WSA QA Officer file, Washington, DC

7.0 REFERENCES

American Public Health Association. 1989. Standard Methods for the Examination of

Water and Wastewater. Seventeenth Edition. American Public Health Association,

Washington, D.C.

Bain, M.B., J.T. Finn, and H.E. Booke. 1985. Quantifying stream substrate for habitat

analysis studies. North American Journal of Fisheries Management 5:499-500.

Baker, J.R. and G.D. Merritt, 1990. Environmental Monitoring and Assessment Program:

Guidelines for Preparing Logistics Plans. EPA 600/4-91-001. U.S. Environmental

Protection Agency. Las Vegas, Nevada.

Barbour, M.T., J. Gerritsen, B.D. Snyder, and J.B. Stribling. 1999. Rapid Bioassessment

Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic

Macroinvertebrates, and Fish. Second Edition. EPA/841-B-99-002. U.S.

Environmental Protection Agency, Office of Water, Assessment and Watershed

Protection Division, Washington, D.C.

Bickford, C.A., C.E. Mayer, and K.D. Water. 1963. An Efficient Sampling Design for 

Forest Inventory: The Northeast Forest Resurvey. Journal of Forestry. 61: 826-833.
W adeable Streams Assessment August 2004 

QA Project Plan Page 66 of 71

CAS. 1999. Chemical Abstracts Service web site (http://www.cas.org)

Carlson, R.E. 1977. A trophic state index for lakes. Linmology and Oceanography

22(2):361-369.

CENR. 1997. Integrating the Nation’s Environmental Monitoring and Research Networks

and Programs: A Proposed Framework. Committee on Environment and Natural

Resources, National Science and Technology Council, Washington, DC, USA.

Chaloud, D.C., J.M. Nicholson, B.P. Baldigo, C.A. Hagley, and D.W. Sutton. 1989. 

Handbook of Methods for Acid Deposition Studies: Field Methods for Surface Water

Chemistry. EPA 600/4-89/020. U.S. Environmental Protection Agency, Washington,

D.C.

Cochran, W.G. 1977. Sampling Techniques. 3rd edition. John Wiley & Sons. New

York. 428 pp.

Converse, J.M. 1987. Survey Research in the United States: Roots and Emergence

1890-1960. University California Press. Berkeley, CA. 564 pp.

EIMS. 1999. Environmental Information Management System (EIMS) web site. 

(Http://www.epa.gov/eims)

FGDC. 1998. Content standard for digital deospatial metadata, version 2.0. FGDCSTD-001-1998. Federal Geographic Data Committee. Washington, DC. 

(Http://www.fgdc.gov)

Frissell, C.A., W.J. Liss, C.E. Warren, and M.D. Hurley. 1986. A hierarchical framework

for stream habitat classification: viewing streams in a watershed context. Environ.

Mgmt. 10(2): 199-214.

Frithsen, J.B. 1996a. Suggested modifications to the EMAP data set directory and

catalog for implementation in US EPA Region 10,. Draft. June 10, 1996. Report

prepared for the U.S. Environmental Protection Agency. National Center for

Environmental Assessment. Washington, DC. By Versar, Inc., Columbia, MD.

Frithsen, J.B. 1996b. Directory Keywords: Restricted vs. unrestricted vocabulary. Draft,

May, 21, 1996. Report prepared for the U.S. Environmental Protection Agency,

National Center for Environmental Assessment, Washington, DC., by Versar, Inc.

Columbia, MD.

Frithsen, J.B., and D.E. Strebel. 1995. Summary documentation for EMAP data:

Guidelines for the information management directory. 30 April 1995. Report prepared

for U.S. Environmental Protection Agency, Environmental and Assessment Program

(EMAP), Washington, DC. Prepared by Versar, Inc., Columbia, MD.
W adeable Streams Assessment August 2004 

QA Project Plan Page 67 of 71

Garner, F.C., M.A. Stapanian, and K.E. Fitzgerald. 1991. Finding causes of outliers in

multivariate environmental data. Journal of Chemometrics. 5: 241-248.

Glase, J.A., D.L. Foerst, G.D> McKee, S.A. Quave, and W.L. Budde. 1981. Trace

analyses of waste-waters. Environmental Science & Technology. 15: 1426-1435.

Hawkins, C. P., R. H. Norris, J. N. Hogue, and J. W. Feminella. 2000. Development and

evaluation of predictive models for measuring the biological integrity of streams.

Ecological Applications 10:1456-1477.

Hazard, J.W., and B.E. Law. 1989. Forest Survey Methods Used in the USDA Forest

Service,. EPA/600/3-89/065. NTIS PB89 220 594/AS. U.S. EPA Environmental

Research Laboratory. Corvallis, Oregon.

Hillman, D.C., S.H. Pia, and S.J. Simon. 1987. National Surface Water Survey: Stream

Survey (Pilot, Middle Atlantic Phase I, Southeast Screening, and Episode Pilot)

Analytical Methods Manual. EPA 600/8-87-005. U.S. Environmental Protection

Agency, Las Vegas, Nevada.

Heinz Center. 2002. The State of the Nation’s Ecosystems. The Cambridge University

Press.

Hunsaker, C. T., and D. E. Carpenter. 1990. Environmental Monitoring and Assessment

Program: ecological indicators. Office of Research and Development, U. S.

Environmental Protection Agency, Research Triangle Park, North Carolina.

EPA-600-3-90-060. 

Hunt, D.T. E., and A.L. Wilson. 1986 The Chemical Analysis of Water: General

Principles and Techniques. Second edition. Royal Society of Chemistyr, London,

England. 683 pp.

ITIS. 1999. Integrated Taxonomic Information System web site

(http://www.itis.usda.gov/itis).

Kaufmann, P.R. (ed.). 1993. Physical Habitat. IN: R.M. Hughes (ed.) Stream Indicator

and Design Workshop. EPA600/R-93/138. U.S. Environmental Protection Agency,

Corvallis, Oregon.

Kaufmann, P.R., A. T. Herlihy, J.W. Elwood, M.E. Mitch, W.S. Overton, M.J. Sale, J.J..

Messer, K.A. Cougan, D.V. Peck, K.H. Reckhow, A,J, Kinney, S.J. Christie, D.D.

Brown, C.A. Hagley, and H.I. Jager. 1988. Chemical Characteristics of Streams in

the Mid-Atlantic and Southeastern United States. Volume I: Population Descriptions

and Physico-Chemical Relationships. EPA 600/3-88/021a. U.S. Environmental

Protection Agency, Washington, D.C.
W adeable Streams Assessment August 2004 

QA Project Plan Page 68 of 71

Kish, L. 1965. Survey Sampling. John Wiley & Sons. New York. 643 pp.

Kish, L. 1987. Statistical Design for Research. John Wiley & Sons. New York. 267 pp.

Kirchmer, C.J. 1983. Quality control in water analysis. Environmental Science &

Technology. 17: 174A-181A.

Klemm, D.J., P.A. Lewis, F. Fulk, and J.M. Lazorchak. 1990. Macroinvertebrate Field

and Laboratory Methods for Evaluating the Biological Integrity of Surface Waters. 

EPA 600/4-90/030. U.S. Environmental Protection Agency, Cincinnati, Ohio.

Lemmon, P.E. 1957. A new instrument for measuring forest overstory density. J. For.

55(9): 667-669.

Linsley, R.K., M.A. Kohler, and J.L.H. Paulhus. 1982. Hydrology for Engineers. 

McGraw-Hill Book Co. New York.

Meglen, R.R. 1985. A quality control protocol for the analytical laboratory. Pp. 250-270

IN: J.J. Breen and P.E. Robinson (eds). Environmental Applications of

Cehmometrics. ACS Symposium Series 292. American Chemical Society,

Washington, D.C.

Messer, J.J., C.W. Ariss, J.R. Baker, S.K. Drousé, K.N. Eshleman, P.R. Kaufmann, R.A. 

Linthurst, J.M. Omernik, W.S. Overton, M.J. Sale, R.D. Schonbrod, S.M. Stambaugh,

and J.R. Tuschall, Jr. 1986. National Surface Water Survey: National Stream Survey,

Phase I-Pilot Survey. EPA-600/4-86/026. Washington, D.C: U.S. Environmental

Protection Agency.

MRLC. 1999. Multi-Resolution Land Characteristics web site (http://www.epa.gov/mrlc)

Mulvey, M., L. Cato, and R. Hafele. 1992. Oregon Nonpoint Source Monitoring

Protocols Stream Bioassessment Field Manual: For Macroinvertebrates and Habitat

Assessment. Oregon Department of Environmental Quality Laboratory Biomonitoring

Section. Portland, Oregon. 40pp.

NAPA. 2002. Environment.gov. National Academy of Public Administration. 

ISBN: 1-57744-083-8. 219 pages.

NBII. 1999. The NBII Biological Metadata Standard. National Biological Information

Infrastructure web site (http://www.nbii.gov)

NSDI. 1999. National Spatial Data Infrastructure web site

(http://www.fgdc.gov/nsdi/nsdi.html)

NRC. 2000. Ecological Indicators for the Nation. National Research Council. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 69 of 71

Washington, DC. National Academy Press.

Overton, W.S., 1985. Draft Sampling Plan for Streams in the National Surface Water 

Survey. July 1986. Technical Report 114. Corvallis, Oregon: Department of

Statistics, Oregon State University.

Overton, W. S., D. White, and D. L. Stevens, Jr. 1991. Design Report for EMAP, the

Environmental Monitoring and Assessment Program. U. S. Environmental Protection

Agency, Office of Research and Development, Washington, D.C. EPA-600-3- 91-053. 

Paulsen, S.G., D.P. Larsen, P.R. Kaufmann, T.R. Whittier, J.R. Baker, D. Peck, J.

McGue, R.M. Hughes, D. McMullen, D. Stevens, J.L. Stoddard, J. Lazorchak, W.

Kinney, A.R. Selle, and R. Hjort. 1991. EMAP - surface waters monitoring and

research strategy, fiscal year 1991. EPA-600-3-91-002. U.S. Environmental

Protection Agency, Office of Research and Development, Washington, D.C. and

Environmental Research Laboratory, Corvallis, Oregon.

Peck, D.V., J.M. Lazorchak, and D.J. Klemm (editors). 2003. Unpublished draft. 

Environmental Monitoring and Assessment Program – Surface Waters: Western Pilot

Study Field Operations Manual for Wadeable Streams. EPA/xxx/x-xx/xxxx. U.S.

Environmental Protection Agency, Washington, D.C.

Plafkin, J.L., M.T. Barbour, K.D. Porter, S.K. Gross, and R.M. Hughes. 1989. Rapid Bioassessment Protocols for Use in Streams and Rivers: Benthic Macroinvertebrates

and Fish. EPA 440/4-89/001. U.S. Environmental Protection Agency, Office of

Water, Washington, D.C.

Platts, W.S., W.F. Megahan, and G.W. Minshall. 1983. Methods for Evaluating Stream,

Riparian, and Biotic Conditions. USDA Forest Service, Gen. Tech. Rep. INT-183. 

71pp.

Robison, E.G. and R.L. Beschta. 1990. Characteristics of coarse woody debris for

several coastal streams of southeast Alaska, USA. Canadian Journal of Fisheries and

Aquatic Sciences 47(9):1684-1693.

Robison, E.G., and P.R. Kaufmann. (In preparation). Evaluating and improving and

objective rapid technique for defining pools in small wadeable streams.

Sarndal, C.E., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. 

Springer-Verlag. New York. 694 pp.

Skougstad, M.W., M.J. Fishman, L.C. Friedman, D.E. Erdman, and S.S. Duncan (eds.). 

1979. Method I-4600-78, Automated Phosphomolybdate Colorimetric Method for

Total Phosphorus. IN: Methods for Determination of Inorganic Substances in Water

and Fluvial Sediments: Techniques of Water-Resources Investigations of the United
W adeable Streams Assessment August 2004 

QA Project Plan Page 70 of 71

States Geological Survey. Book 5, Chapter A1. U.S. Government Printing Office,

Washington, D.C.

Smith, F., S. Kulkarni, L. E. Myers, and M. J. Messner. 1988. Evaluating and presenting

quality assurance data. Pages 157-68 in L.H. Keith, ed. ACS Professional Reference

Book. Principles of Environmental Sampling. American Chemical Society,

Washington, D.C. 

Stack, B.R. 1989. Factors Influencing Pool Morphology in Oregon Coastal Streams. 

M.S. Thesis, Oregon State University. 109pp.

Stanley, T.W., and S.S. Verner. 1986. The U.S. Environmental Protections Agency's

quality assurance program. pp. 12-19 IN: J.K. Taylor and T.W. Stanley (eds.). Quality

Assurance for Environmental Measurements. ASTM STP 867, American Society for

Testing and Materials, Philadelphia, Pennsylvania.

Stapanian, M.A., F.C. Garner, K.E. Fitzgerald, G.T. Flatman, and J.M. Nocerino. 1993. 

Finding suspected causes of measurement error in multivariate environmental data. 

Journal of Chemometrics. 7: 165-176. 

Stevens, D. L., Jr., 1994. Implementation of a National Monitoring Program. Journal

Environ. Management 42:1-29.

Stevens, D.L., Jr., and A.R. Olsen. 1999. Spatially restricted surveys over time for

aquatic resources. Journal of Agricultural, Biological and Environmental Statistics. 

4:415-428.

Stevens, D.L., Jr., and A.R. Olsen. 2003. Variance estimation for spatially balanced

samples of environmental resources. Environmetrics. 14:593-610.

Stevens, D.L., Jr., and A.R. Olsen. 2004. Spatially-balanced sampling of natural

resources. Journal of American Statistical Association. 99:262-278.

STORET. 1999. The STORET web site. (Http://www.epa.gov/OWOW/STORET)

U.S. EPA. 1987. Handbook of Methods for Acid Deposition Studies: Laboratory

Analyses for Surface Water Chemistry. EPA/600/4-87/026. U.S. Environmental

Protection Agency, Office of Research and Development, Washington, D.C.

U.S. EPA. 1991. IRM Policy Manual. Chapter 13. Locational data.

U.S. EPA. 1996b. Addendum to: Guidelines for the information management directory. U.S.

EPA, NHEERL. Atlantic Ecology Division. Narragansett, RI.

U.S. EPA. 2003. Draft Report on the Environment. ORD and OEI. EPA-260-R-02-006. 
W adeable Streams Assessment August 2004 

QA Project Plan Page 71 of 71

U.S.GAO. 2000. Water Quality. GAO/RCED-00-54.

USGCRP. 1998. Data Management for Global Change Research. Policy Statements for the

National Assessment Program. July 1998. U.S. Global Change Research Program. National

Science Foundation. Washington, DC.

Wilen, B.O. 1990. The U.S. Fish and Wildlife Service’s National Wetlands Inventory. in

S. J. Kiraly, R. A. Cross, J. D. Buffington (Eds.) Federal Coastal Wetlands Mapping

Programs (U.S. Department of the Interior Fish and Wildlife Service, Washington,

D.C., 1990), FWS Biological Report 90(18), pp. 9-20.

Wolman, M.G. 1954. A method of sampling coarse river-bed material. Transactions of

the American Geophysical Union 35(6):951-956.