United States Environmental Protection Agency
Office of Water
Washington, DC
EPA 841-B-12-007
National Rivers and Streams Assessment
2013-2014
Quality Assurance
Project Plan
Version 2.2
September 2018
9 theNatio*
U.S. Environmental Protection Agency
Office of Wetlands, Oceans, and Watersheds
1200 Pennsylvania Avenue, NW
4503T
Washington, DC 20460

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National Rivers and Streams Assessment 2013-2014
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Quality Assurance Project Plan
Page lli Of XVI!!
Management Approvals: Signature indicates a phased approval for the National Rivers and Streams Assessment
(NRSA) Quality Assurance Project Plan (QAPP) (EPA 841 B 12 007), related Field Operations Manuals (FPA 841 8
12-009a and FPA 841-B 12 009b) and Laboratory Operations Manual (EPA 841-B-12-010). This approval covers
the changes described in the version history.
Previous phased approvals covered the following asppcts of the NRSA project as of the approved date:
held training and collection/shipping of all samples and environmental data as described in relevant
portion of the QAPP and the LOM: Water chemistry analyses as described tn the relevant podion of
the QAPP and the LOM; Benthic macroinvertebrale and microcystm analyses as describee! in the
relevant portion of the QAPP and the IOM; Fish Voucher {for Fish Assemblage indicator! as described
in the relevant portions of the QAPP and the LOM, Fish tissue plug analyses as described in the
relevant portions of the QAPP and the LOM: Pcnphyton analyses as described in the relevant
portions of the QAPP and the LOM; Revised microcystm analyses as described tn the relevant
portions of the QAPP and the LOM; Periphyton meta genomics collection/shipping as described in
relevant portion of the QAPP, Addendum to tbr> FOM, and the LOM
Sarah Lehnunn, NRSA Project QA Officer	Date
U S. EPA office of Water, Office of Wetlands, Oceans, and Watersheds
Washington. DC	" ~ "x,
t,-'	'~_1 -
Richard Mitchell, NRSA Projpct leader
U.S. EPA Office of w.m r office of Wetlands, Oceans, and Watersheds
Washington. DC

uate
Date
.A
Sii'san Holdsworth, Branch Chief
U S, EPA Office of Water, office of Wetlands, Oceans, and Watersheds
Washington, DC
'3^ * W^°?r4v--	\
Bf-rnice t. Smith, WRAPD Quality Assurance Coordinator	Date
U.S. EPA Office of Water, Office of Wetlands, Oceans, and Watersheds
Washington, DC
CYNTHIA SHIMANSKI
Cynthia N. Johnson, OWOW Quality Assurance Officer	Date
U.S. EPA Office of Water, Office of Wetlands, Oceans, and Watersheds
Washington, DC

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VERSION HISTORY
QAPP Date Approved
Changes Made
Version

1.0
5/22/2013
Not Applicable
1.1 to
2.1
Multiple
Phased Approvals
2.1-
2.2

Minor editorial and grammatical changes throughout QAPP;
List of acronyms and distribution list updated;
Approval Page- changed Quality Assurance Coordinator;
Distribution List- changed multiple persons positions and contact
information;
Section 2.1.1 and Figure 2.1 Changed project leader information;
Section 2.1.2—removed sentence about schedule and amended dates in
Figure 2.2;
Section 2.1.8- updated citation in text;
Table 2.2 - changed dates of proposed schedule;
Section 3.2.2 - Sentence added to describe equations;
Section 3.2.3- inserted footnote;
Section 3.2.3-final paragraph added on periphyton assemblage;
Table 6.1- footnote added to periphyton sections-
Section 6.1.2.2 moved below Table 6.3;
Table 6.9 - footnotes added into precision and accuracy columns;
Section 6.3.3- added revised paragraph on quality assurance objectives
for periphyton;
Oringal Tables 6.11- 6.13 and Sections 6.3.4- 6.3.5 removed from main
body of document and placed them in Appendix A;
Table 6.12- removed footnotes and changed MQO values
Table 6.15- changed precision and accuracy values. Removed footnotes-
References: replaced Stauffer paper with correct citation, added in
citation for 2008-09 NRSA paper. Fixed citations to include all authors;
Created Appendix A for archived periphyton information.

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S 'vP-mr-a.fn-u	uh:	;LivO!
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We have read the Quality Assurance Project Plan, Site Evaluation Guidelines, Field Operations Manuals,
and Laboratory Operations Manual for the National Rivers and Streams Assessment 2013/14 listed
below. Our agency/organization, agrees to abide by its requirements for work performed under the
NRSA 2013/14. Check appropriate boxes.
Quality Assurance Project Plan	~
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The complete documentation of overall NRSA project management, design, methods, and standards is
contained in five companion documents, including:
National Rivers and Streams Assessment 2013-14: Quality Assurance Project Plan EPA-841-B-12-007
National Rivers and Streams Assessment 2013-14: Site Evaluation Guidelines EPA-841-B-12-008
National Rivers and Streams Assessment 2013-14: Non-Wadeable Field Operations Manual EPA-841-B-
12-009a
National Rivers and Streams Assessment 2013-14: Wadeable Field Operations Manual EPA-841-B-12-
009b
National Rivers and Streams Assessment 2013-14: Laboratory Operations Manual EPA 841-B-12-010
Addendum to the National Rivers and Streams Assessment 2013-2014: Wadeable & Non-Wadeable Field
Operations Manuals
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 NRSA,
and is based on the guidelines developed and followed in the Western Environmental Monitoring and
Assessment Program (EMAP) (Peck et al. 2003). Methods described in this document are to be used
specifically in work relating to the NRSA. All project cooperators must 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. Reference
to "FOM" means both Field Operations Manuals —Wadeable, and Non-wadeable - if the associated text
applies to both.
The suggested citation for this document is:
USEPA. 2013. National Rivers and Streams Assessment 2013-14: Quality Assurance Project Plan. EPA-
841-B-12-007. U.S. Environmental Protection Agency, Office of Water, Washington, DC.

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TABLE OF CONTENTS
APPROVAL PAGE	Ill
VERSION HISTORY	iv
QUALITY ASSURANCE PROJECT PLAN REVIEW & DISTRIBUTION ACKNOWLEDGEMENT & COMMITMENT TO
IMPLEMENT THE NATIONAL RIVERS AND STREAMS ASSESSMENT 2013/14	V
NOTICE	VI
TABLE OF CONTENTS	VII
LIST OF FIGURES	X
LIST OF TABLES	X
ACRONYMS/ABBREVIATIONS	XII
DISTRIBUTION LIST	XV
1	EXECUTIVE SUMMARY	16
1.1	Background	16
1.2	Project Organization	16
1.3	Quality Assurance Project Plan	16
1.4	Survey Design	16
1.5	Information Management	16
1.6	Field Operations	17
1.7	Laboratory Operations	17
1.8	Peer Review	17
2	PROJECT OVERVIEW AND MANAGEMENT	19
2.1	Introduction	19
2.1.1	Project Organization	20
2.1.2	Project Schedule	24
2.1.3	Objectives	24
2.1.4	Target Population	25
2.1.5	Sample Frame	25
2.1.6	Expected Sample Size	25
2.1.7	Oversample	25
2.1.8	Field Protocol Development	26
2.1.9	Information Management	26
2.1.10	Assessment	27
2.2	Scope of QA Project Plan	27
2.2.1	Overview of Field Operations	27
2.2.2	Overview of Laboratory Operations	35
2.2.3	Data Analysis and Reporting	38
2.2.4	Peer Review	38
3	DATA QUALITY OBJECTIVES	40
3.1	Data Quality Objectives for the NRSA	40
3.2	Measurement Quality Objectives	40
3.2.1	Method Detection Limits	40
3.2.2	Sampling Precision, Bias, and Accuracy	41
3.2.3	Taxonomic Precision and Accuracy	43
3.2.4	Completeness	44

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3.2.5	Comparability	45
3.2.6	Representativeness	45
4	SURVEY DESIGN	46
4.1	Probability-Based Sampling Design and Site Selection	46
4.1.1	Target Population	46
4.1.2	Sample Frame	46
4.1.3	Revisit and Resample Sites	47
4.1.4	Evaluation of Sites	47
4.2	Hand-picked (Potential Reference) Site Selection	47
5	INFORMATION MANAGEMENT	49
5.1	Roles and Responsibilities	49
5.1.1 State/Tribe-Based Data Management	51
5.2	Overview of System Structure	52
5.2.1	Data Flow	52
5.2.2	Simplified Description of Data Flow	53
5.2.3	Core Information Management Standards	54
5.2.4	Data Formats	55
5.2.5	Public Accessibility	55
5.3	Data Transfer Protocols	56
5.4	Data Quality and Results Validation	57
5.4.1	Design and Site Status Data Files	57
5.4.2	Sample Collection and Field Data	58
5.4.3	Laboratory Analyses and Data Recording	59
5.4.4	Data Review, Verification, and Validation Activities	60
5.5	DataTransfer	62
5.5.1 Database Changes	63
5.6	Metadata	63
5.6.1	Parameter Formats	63
5.6.2	Standard Coding Systems	63
5.7	INFORMATION MANAGEMENT OPERATIONS	64
5.7.1	Computing Infrastructure	64
5.7.2	Data Security and Accessibility	64
5.7.3	Life Cycle	64
5.7.4	Data Recovery and Emergency Backup Procedures	64
5.7.5	Long-Term Data Accessibility and Archive	64
5.8	Records Management	65
INDICATORS	66
6.1	Water Chemistry and In-situ Measurements (Including chlorophyll-a-)	67
6.1.1	Introduction	67
6.1.2	Pertinent QA/QC Procedures	68
6.1.3	Q uality Con trol Procedures: Field Operations	75
6.2	Algal Toxin: Microcystin	78 ^
6.2.1	Sample Design and Methods	78 ^
6.2.2	Pertinent QA/QC Procedures	78 £!
6.3	Periphyton	80 q
6.3.1	Introduction	80 u
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6.3.2	Sampling Design and Methods	80 O
6.3.3	Quality Assurance Objectives	81	^
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6.3.4	Quality Control Procedures: Field Operations	81	<
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6.4	Benthic Macroinvertebrates	82
6.4.1	Introduction	82
6.4.2	Sampling Design	82
6.4.3	Quality Assurance Objectives	82
6.4.4	Pertinent QA/QC Procedures	83
6.4.5	Taxonomic QC	83
6.4.6	Taxonomic QC Review & Reconciliation	84
6.4.7	Quality Control Procedures: Field Operations	87
6.5	Fish Assemblage	87
6.5.1	Introduction	87
6.5.2	Sampling Design and Methods	87
6.5.3	Quality Assurance Objectives	88
6.5.4	Pertinent QA/QC Procedures	88
6.5.5	Taxonomic QC Review & Reconciliation	89
6.5.6	Quality Control Procedures: Field Operations	89
6.5.7	Quality Control Procedures: Laboratory Operations (Voucher Specimens)	91
6.6	Physical Habitat Quality	93
6.6.1	Introduction	93
6.6.2	Sampling Design and Methods	93
6.6.3	Quality Assurance Objectives	95
6.6.4	Quality Control Procedures: Field Operations	95
6.7	Fecal Indicator: Enterococci	96
6.7.1	Introduction	96
6.7.2	Sampling Design and Methods	96
6.7.3	Pertinent QA/QC Procedures	96
6.7.4	Data Management, Review, and Validation	98
6.8	Whole Fish Tissue Samples for Fillet Analysis	98
6.8.1	Introduction	98
6.8.2	Sampling Design and Methods	98
6.8.3	Pertinent QA/QC Procedures	100
6.8.4	Data Management, Review, and Validation	101
6.9	Fish Tissue Plugs	101
6.9.1	Introduction	101
6.9.2	Sampling Design and Methods	101
6.9.3	Pertinent QA/QC Procedures	102
6.9.4	Data Management, Review, and Validation	103
6.9.5	Quality Control Procedures: Laboratory Operations	104
7 FIELD AND BIOLOGICAL LABORATORY QUALITY EVALUATION AND ASSISTANCE VISITS	106
7.1 National Rivers and Streams Assessment Field Quality Evaluation and Assistance Visit Plan	106
7.1.1	Preparation Activities	106
7.1.2	Field Day Activities	107
7.1.3	Post Field Day Activities	107
7.1.4	Summary	108
7.2 NATIONAL RIVERS AND STREAMS ASSESSMENT LABORATORY QUALITY EVALUATION AND ASSISTANCE
VISIT PLAN	
7.2.1	Remote Evaluation/Technical Assessment
7.2.2	Water Chemistry Laboratories	
7.2.3	Inter-laboratory Comparison	
7.2.4	Assistance Visits	
7.2.5	NRSA 2013-14 Document Request Form Chemistry Laboratories
7.2.6	NRSA 2013-14 Document Request Form Biology Labs	
ix
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8	DATA ANALYSIS PLAN	113
8.1	Data Interpretation Background	113
8.1.1	Scale of Assessment	113
8.1.2	Selecting the Best Indicators	113
8.1.3	Defining Least Impacted Reference Condition	113
8.1.4	Determining Thresholds for Judging Condition	114
8.2	Geospatial Data	114
8.3	Datasets Used for the Report	114
8.3.1	Ecological Integrity	114
8.3.2	Stressor Status/Extent	114
8.3.3	Recreational value	115
8.4	INDICATOR DATA ANALYSIS	115
8.4.1	Water Chemistry and Chlorophyll a	115
8.4.2	Algal Toxins: Microcystins	115
8.4.3	Benthic Macroinvertebrate, Periphyton and Fish Assemblages	115
8.4.4	Physical Habitat	116
8.4.5	Enterococci	117
8.4.6	Fish Tissue Indicator (Fillets and Plugs)	118
9	REFERENCES	119
APPENDIX A - PLANNED QUALITY ASSURANCE FOR PERIPHYTON ID - ORIGINALLY IN SECTION 6	124
Formerly 6.3.3 Quality Assurance Objectives	124
Formerly 6.3.4 Pertinent QA/QC Procedures for ID Periphyton Sample	124
Formerly 6.3.5 Taxonomic QC Review & Reconciliation	125
LIST	URES
Figure 2.1 Project organization	23
Figure 2.2 Schedule	24
Figure 2.3 Base and oversample sites	26
Figure 2.4 Example site map	29
Figure 2.5 River and stream field surveys: site verification activities	32
Figure 2.6 Boatable river and stream sampling: summary of field activities	33
Figure 2.7 Wadeable stream sampling: summary of field activities	34
Figure 5.1 Conceptual model of dataflow into and out of the master SQL	54
Figure 6.1 Field measurement process: water chemistry samples	76
Figure 6.2 Analysis activities: water chemistry samples	77
LIST
Table 2.1 Critical logistics elements (from Baker and Merritt, 1990)	27
Table 2.2 Proposed schedule	39
Table 5.1 Summary of IM responsibilities	50
Table 5.2 Summary of software	56
Table 5.3 Summary sample and field data quality control activities: sample tracking	58
Table 5.4 Summary laboratory data quality control activities	59
Table 5.5 Data review, verification, and validation quality control activities	62
Table 6.1 Indicators and collection location	66
Table 6.2 Laboratory method performance requirements: water chemistry	68
Table 6.3 Laboratory quality control samples: water chemistry	70
Table 6.4 Data validation quality control: water chemistry	72
Table 6.5 Data reporting criteria: water chemistry	73

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Table 6.6 Constants for converting major ion concentration from mg/Lto^eo/L	74
Table 6.7 Factors to calculate equivalent conductivities of major ions	74
Table 6.8 Field quality control: water chemistry	75
Table 6.9 Measurement data quality objectives: microcystin	78
Table 6.10 Sample analysis quality control activities: microcystin	78
Table 6.11 Sample collection and field processing quality control: periphyton	81
Table 6.12 Measurement data quality objectives: benthic macroinvertebrates	82
Table 6.13 Laboratory quality control: benthic macroinvertebrates	85
Table 6.14 Sample collection and field processing quality control: benthic macroinvertebrates	87
Table 6.15 Measurement data quality objectives: fish community	88
Table 6.16 Sample collection and field processing quality control: fish community	89
Table 6.17 Sample receipt and processing quality control: fish community	91
Table 6.18 Laboratory quality control: fish voucher taxonomic identification	92
Table 6.19 Data validation: fish voucher taxonomic identification	93
Table 6.20 Field measurement methods: physical habitat	94
Table 6.21 Measurement data quality objectives: physical habitat	95
Table 6.22 Field quality control: physical habitat	95
Table 6.23 Measurement data quality objectives: pathogen-indicator DNA sequences	96
Table 6.24 Sample collection and field processing quality control: fecal indicator	96
Table 6.25 Laboratory quality control: pathogen-indicator DNA sequences	97
Table 6.26 Data validation quality control: fecal indicator	98
Table 6.27 Recommended target species: whole fish tissue collection	99
Table 6.28 Field data types: whole fish tissue samples for fillet analysis	100
Table 6.29 Field quality control: whole fish tissue samples for fillet analysis	100
Table 6.30 Data validation quality control: whole fish tissue samples for fillet analysis	101
Table 6.31 Recommended target and alternate species: fish tissue plug collection	102
Table 6.32 Field datatypes: fish tissue plug	103
Table 6.33 Field quality control: fish tissue plug	103
Table 6.34 Data validation quality control: fish tissue plug	104
Table 6.35 Measurement data quality objectives: fish tissue plug	104
Table 6.36 Lab quality control: fish tissue plug	104
Table 7.1 Equipment and supplies: field evaluation and assistance visits	107
Table 7.2 Summary: field evaluation and assistance visits	108
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A	Absorbance
AFDM	Ash-Free Dry Mass
Ascii	American Standard Code for Information Interchange
ASTM	American Society of Testing and Materials
Ca	Calcium
CAS	Chemical Abstract Service
CI	Chloride
Ct	Threshold Cycle
Cp	Crossing Point
CSDGM	Content Standards for Digital Geospatial Metadata
CSV	Comma Separated Values
CV	Coefficient of Variation
DO	Dissolved Oxygen
DOC	Dissolved Organic Carbon
DQO	Data Quality Objective
EMAP	Environmental Monitoring and Assessment Program
ENT	Enterococcus
EPA	Environmental Protection Agency
FGDC	Federal Geographic Data Committee
FOIA	Freedom of Information Act
FOM	Field Operations Manual
FR	Federal Registry
FTP	File Transfer Protocol
GIS	Geographic Information System
GPS	Global Positioning Device
HQ	Head Quarters
IBD	Ionic Balance Difference
IQG	Information Quality Guideline
IM	Information Management
ITIS	Integrated Taxonomic Information System
K	Potassium
LDL	Lower Detection Limit
LIMS	Laboratory Information Management System
LOM	Lab Operations Manual
LRL	Lower Reporting Limit
LT	Long Term
ISO	International Organization for Standardization
Mdb	a file-extension used in certain versions of Microsoft Access databases
MDL	Method Detection Levels (limit)
Mg	Magnesium
MMI	Multimetric Indicators
MQO	Measurement Quality Objective
MRLC	Multi-Resolution Land Characteristics
Na	Sodium
NABS	North American Benthological Society
NACEC	North American Commission for Environmental Cooperation
NAD	North American Datum
NAPA	National Association of Public Administration
NARS	National Aquatic Resources Survey
NAWQA	National Water-Quality Assessment Program
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NCCA	National Coastal Condition Assessment
NELAC	National Environmental Laboratory Accreditation Conference
NELAP	National Environmental Laboratory Accreditation Program
NERL	New England Regional Laboratory
ND	Not Detected
NHD	National Hydrology Database
NH3	Ammonia
NH4	Ammonium
NIST	National Institute of Standards
NLA	National Lakes Assessment
NLCD	National Land Cover Dataset
N02	Nitrite
N03	Nitrate
NRC	National Research Council
NRSA	National Rivers and Streams Assessment
NTU	Nephelometric Turbidity Units
NWCA	National Wetland Condition Assessment
O/E	"Observed" over "Expected"
OMB	Office of Management and Budget
ORD	Office of Research and Development
OW	Office of Water
PBT	Persistent Bioaccumulative Toxic Chemical
PC	Personal Computer
PctDiff	Percent Difference
PD	Percent Difference
PDE	Percent Difference in Enumeration
PE	Performance Evaluation
PFCs	Perfluorinated Chemicals
ppt	Parts Per Thousand
PRISM	Parameter-elevation Regressions on Independent Slopes Model
PTD	Percent Taxonomic Disagreement
QA	Quality Assurance
QAPP	Quality Assurance Protection Plan
QA/QC	Quality Assurance/Quality Control
QC	Quality Control
QPCR	Quantitative Polymerase Chain Reaction
QCCS	Quality Control Sample Check
QRG	Quick Reference Guide
R	A statististical software and graphics package
RBS	Relative Bed Stability
RL	Reporting Limit
RSD	Relative Standard Deviation
RTE
Rare, Threatened and Endangered
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SAS
Statistical Analysis System
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SDTD
Spatial Data Transfer Standard
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SEG
Site Evaluation Guideline
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Silica
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Standard Operating Procedures
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SQL
Standard Query Language
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Standard Reference Material
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STORET
Storage and Retrieval Data Warehouse
TOC
Total Organic Carbon
TP
Total Phosphorus
TSS
Total Suspended Solids
USGAO
United States General Accounting Office
USGS
United States Geological Survey
WED
Western Ecology Division
WSA
Wadeable Streams Assessment
WQX
Water Quality Exchange

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DISTRIBUTION LIST
This Quality Assurance Protection Plan (QAPP) and associated manuals or guidelines will be distributed to the
following EPA, senior staff participating in the NRSA and to State Water Quality Agencies or cooperators who will
perform the field sampling operations. The Quality Assurance (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.
National Monitoring Coordinators
Richard Mitchell
NRSA Project Leader
mitchell.richard@epa.gov
202-566-0644
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Sarah Lehman
NRSA Project QA Officer
lehmann.sarah@epa.gov
202-566-1379
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Cynthia N. Johnson
OWOW QA Officer
ioh nson.cvnthian@epa.gov
202- 566-1266
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Bernice L. Smith
NARS QA Cooridnator
smith.bernicel@epa.gov
202-566-1244
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Steven G. Paulsen
EPA ORD Technical Advisor
paulsen.steve@epa.gov
541-754-4428
Freshwater Ecology Branch Western Ecology Division, NHEERL,
ORD, EPA
200 S.W. 35th St. Corvallis, OR 97330
Marlys Cappaert, SRA
NARS Information Management
Coordinator
cappaert.marlvs@epa.gov
541-754-4467
541-754-4799 (fax)
Computer Science Corporation
200 S.W. 35th Street
Corvallis, OR 9733
Chris Turner, GLEC, Inc.
Contract Logistics Coordinator.
cturner@glec.com
715-829-3737
Great Lakes Environmental Center
739 Hastings Street
Traverse City, Ml 49686
Leanne Stahl
OST Fish Tissue Coordinator
stahl.leanne@epa.gov
202-566-0404
U.S. EPA Office of Water
Office of Science and Technology
Washington, DC
Regional Monitoring Coordinators
Tom Faber, Region 1
faber.tom@epa.gov
617-918-8672
U.S. EPA-Region 1
11 Technology Drive North Chelmsford, MA 01863
Darvene Adams, Region 2
adams.darvene@epa.gov
732-321-6700
USEPA-Region II
2890 Woodbridge Avenue Edison, NJ 08837
Louis Reynolds, Region 3
revnolds.louis@epa.gov
304-234-0244
U.S. EPA-Region III
303 Methodist Building Wheeling WV 26003
David Melgaard, Region 4
melgaard.david@epa.gov
404-562-9265
U.S.EPA-Region IV
61 Forsyth Street, S.W. Atlanta, GA 30303
Mari Nord, Region 5
nord.mari@epa.gov
312-353-3017
U.S. EPA - Region V
77 West Jackson Boulevard Chicago, IL 60604
Mike Schaub, Region 6
schaub.mike@epa.gov
214-665-7314
U.S. EPA-Region VI
1445 Ross Avenue -Suite 1200 Dallas, TX 75202
Gary Welker, Region 7
welker.garv@epa.gov
913-551-7177
U.S. EPA-Region VII
901 North Fifth Street Kansas City, KS 66101
Karl Hermann, Region 8
hermann.karl@epa.gov
303-312-6228
U.S. EPA-Region VIII
1595 Wynkoop St, Denver, CO 80202
Terry Fleming, Region 9
fleming.terrence@epa.gov
415-972-3452
U.S.EPA-Region IX
75 Hawthorne Street San Francisco, CA 94105
Gretchen Hayslip, Region 10
havslip.gretchen@epa.gov
206-553-1685
U.S. EPA-Region X,
1200 Sixth Avenue Seattle, WA 98101
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1 EXECUTIVE SUMMARY
1.1	Background
The National Rivers and Streams Assessment (NRSA) 2013-14 effort will provide important information
to states and the public about the condition of the nation's river and stream resources and key stressors
on a national and regional scale. The United States Environmental Protection Agency (EPA) developed
this Quality Assurance Protection Plan (QAPP) to support project participants and to ensure that the
final assessment is based on high quality data and known quality for its intended use, and information.
The QAPP contains elements of the overall project management, data quality objectives, measurement
and data acquisition, and information management for NRSA 2013-14. This QAPP is supported by
several other NRSA 2013-14 documents listed in the Notice section of this document. They describe in
detail the methods for sampling and analysis for all core indicators that are part of the NRSA, and
detailed quality control measures are described throughout the QAPP.
1.2	Project Organization
Overall project coordination is conducted by EPA's Office of Water (OW) in Washington, DC, with
technical support from the ORD's Western Ecology Division (WED) in Corvallis, Oregon. Each of the EPA
Regional Offices has identified regional coordinators (pg. XIV) to assist in implementing the survey and
coordinate with the state/tribal crews who collect the water and tissue samples following NRSA 2013-14
protocols. EPA began planning the NRSA 2013-14 with state, tribal, and other federal partners in 2011
and is continuing this partnership effort. EPA expects to report the results in December 2016 in
compliance with the Data Quality Act.
1.3	Quality Assurance Project Plan
The purpose of this QAPP is to document the project data quality objectives and quality
assurance/quality control measures that will be implemented in order to ensure that the data collected
meets those needs. The plan contains elements of the overall project management, data quality
objectives, measurement and data acquisition, and information management for the NRSA 2013-14 and
identifies where these elements are described in detail. This QAPP and its associated documents; the
Field Operations Manual, Laboratory Operations Manual and Site Evaluation Guidelines, are
interdependent, integrated and together make up the full QAPP for the NRSA 2013-14.
1.4	Survey Design
Sample collection for NRSA 2013-14 is designed to be completed during the index period of June
through the end of September 2013 and 2014. EPA used an unequal probability design to select 1800
streams and rivers (both wadeable and non-wadeable) from across the 48 conterminous United States.
To improve our ability to assess changes, the design includes revisits to 900 sites that were sampled
during the NRSA 2008-09 (420 l-4th order streams and 390 5th and above order streams and rivers). In
addition, approximately 200 reference sites will be sampled using the same techniques as the
probabilistic sites.
1.5	Information Management
Environmental monitoring efforts that amass large quantities of information from various sources
present unique and challenging data management opportunities. To meet these challenges, the NRSA
2013-14 employs a variety of well-tested information management (IM) strategies to aid in the

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functional organization and ensured integrity of stored electronic data. IM is integral to all aspects of the
NRSA 2013-14 from initial selection of sampling sites through the dissemination and reporting of final,
validated data.
A technical workgroup convened by the Environmental Protection Agency (EPA) Project Leader is
responsible for the development of a data analysis plan that includes a verification and validation
strategy. These processes are summarized in the data analysis plan section of this QAPP. Validated data
are transferred to the central database managed by NARS information management support staff
located at the Western Ecology Division facilities in Corvallis. This database is known as the National
Aquatic Resource Surveys Information Management System (NARS IM). All validated measurement and
indicator data from the NRSA 2013-14 are eventually transferred to EPA's Water Quality Exchange
(WQX) for archival in EPA's Storage and Retrieval Data Warehouse (STORET) warehouse for public
accessibility. NRSA 2013-14 IM staff provides support and guidance to all program operations in addition
to maintaining NARS IM.
1.6	Field Operations
Field data acquisition activities are implemented in a consistent manner across the entire country. Each
site is assigned a unique ID which identifies it throughout the pre-field, field, laboratory, analysis, and
data management phases of the project. Specific procedures for evaluating each sampling location and
for replacing non-sampleable sites are documented in NRSA 2013-14 Site Evaluation Guidelines (SEG,
EPA-841-B-11-005).
NRSA 2013-14 indicators include: in-situ, water chemistry and chlorophyll a, algal toxins (microcystins),
periphyton, benthic macroinvertebrates, fish assemblage, physical habitat, fecal indicators
(Enterococci), fish tissue plugs, and fish tissue fillet. During the 2014 field season, crews will collect an
additional sample for a periphyton meta-genomics research project at a subset of sites. Field
measurements and sampling methods are outlined in the NRSA 2013-14 FOMs(EPA 841-B-11-004) and
an Addendum to the NRSA 2013-14: Wadeable & Non-Wadeable FOMs for the periphyton meta-
genomics project. Field crews are trained on these methods at a required EPA-sponsored training
session. Field sampling assistance visits will be completed for each field crew for quality assurance
purposes.
1.7	Laboratory Operations
NRSA 2013-14 laboratory analyses are conducted either by state/tribal-selected laboratories or
"National Laboratories" set up by EPA to conduct analyses for any state/tribe which so elects. The
designated National Laboratories and state/tribal laboratories must comply with the Quality
Assurance/Quality Control (QA/QC) requirements described in this document and in the NRSA 2013-14:
Laboratory Operations Manual (LOM, EPA 841-B-11-004). Any laboratory selected to conduct analyses
with NRSA 2013-14 samples must demonstrate that it can meet the quality standards presented in this
NRSA 2013-14 QAPP and LOM.
1.8	Peer Review
Surveys undergo a thorough peer review process, where the scientific community and the public are
given the opportunity to provide comments on the report. Cooperators have been actively involved in
the development of the overall project management, design, indicator selection, and methods.
EPA utilizes a three-tiered approach for peer review of the Survey report:
¦ internal and external review by EPA, states, other cooperators and partners,

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¦	external scientific peer review, and
¦	public review.
Outside scientific experts from universities, research centers, and other federal agencies have been
instrumental in indicator development and will continue to play an important role in data analysis.

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2 PROJECT OVERVIEW AND MANAGEMENT
2.1 Introduction
Several publications 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, states, and
tribes collectively 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, states, and tribes 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 that there is not adequate 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 and tribes make more effective use of limited resources. EPA's Report on the Environment 2003
(USEPA 2003) states 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?'
In response to this need, the Office of Water (OW), in partnership with states and tribes, has begun a
program to assess the condition of the nation's waters via a statistically valid approach. The current
assessment, the National Rivers and Streams Assessment 2013-14 (referred to as NRSA 2013-14
throughout this document), builds upon the National Rivers and Streams Assessment 2008-09, the
Wadeable Streams Assessment (WSA) implemented by EPA in 2004 to monitor and assess the condition
of the nation's wadeable stream resources, as well as other National Aquatic Resource Surveys (NARS)
surveys such as the National Coastal Condition Assessment (NCCA), the National Lakes Assessment (NLA)
and the National Wetland Condition Assessment (NWCA). The NRSA 2013-14 effort will provide
important information to states and the public about the condition of the nation's river and stream
resources and key stressors on a national and regional scale. It will also provide a change analysis from
the NRSA 2008-09 and the WSA 2004.
EPA developed this QAPP to support project participants and to ensure that the final assessment is
based on high quality data and known quality for its intended use, and information. The QAPP contains
elements of the overall project management, data quality objectives, measurement and data
acquisition, and information management for NRSA 2013-14. EPA recognizes that states and tribes may
add elements to the survey, such as supplemental indicators, that are not covered in the scope of this
integrated QAPP. EPA requires that any supplemental elements are addressed by the states, tribes, or
their designees, in a separate approved QAPP. This document covers all core NRSA 2013-14 QA
activities. The NRSA 2013-14 participants have agreed to follow this QAPP and the protocols and design
laid out in this document, and its associated documents - the NRSA 2013-14 Field Operations Manuals
(FOMs), Lab Operations Manual (LOM), and Site Evaluation Guidelines (SEG).
This cooperative effort between states, tribes, and federal agencies makes it possible to produce a
broad-scale assessment of the condition of the Nation's rivers and streams with both a known
confidence and scientific credibility. Through this survey, states and tribes have the opportunity to
collect data that can be used to supplement their existing monitoring programs or to begin development
of new programs.
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The NRSA 2013-14 has three main objectives:
¦	Estimate the current status, trends, and changes in selected ecological and recreational
indicators of the condition of the nation's rivers and streams with known statistical
confidence;
¦	Seek associations between selected indicators of natural and anthropogenic stresses and
indicators of ecological condition; and
¦	Assess changes from the earlier Wadeable Streams Assessment and NRSA 2008-09.
2.1.1 Project Organization
The responsibilities and accountability of the various principals and cooperators are described here and
illustrated in (Figure 2.1). Overall, the project will be coordinated by the Office of Water (OW) in
Washington, DC, with support from EPA Western Ecology Division (WED) in Corvallis, Oregon. Each EPA
Regional Office has identified a Regional EPA Coordinator who is part of the EPA team providing a critical
link with state and tribal partners. Cooperators will work with their Regional EPA Coordinator to address
any technical issues. A 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.
Contractor support is provided for all aspects of this project. Contractors will provide support ranging
from implementing the survey, sampling and laboratory processing, data management, data analysis,
and report writing. Cooperators will interact with their Regional EPA Coordinator and the EPA Project
Leader regarding contractual services.
The primary responsibilities of the principals and cooperators are as follows:
Project Leader: Richard Mitchell, EPA Office of Water
¦	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.
¦	Leads the NRSA Steering Committee and establishes needed technical workgroups.
¦	Interacts with EPA Project Team on technical, logistical, and organizational issues on a
regular basis.
EPA Field Logistics Coordinator: Ellen Tarquinio, EPA Office of Water
¦	EPA employee who functions to support implementation of the project based on technical
guidance established by the EPA Project Leader and serves as point-of-contact. for questions
from field crews and cooperators for all activities.
¦	Tracks progress of field sampling activities.
EPA Project OA Lead: Sarah Lehmann, EPA Office of Water
¦	Provides leadership, development, and oversight of project-level quality assurance for
NARS.
¦	Assembles and provides leadership for a NRSA 2013-14 Quality Team.
¦	Maintains official, approved QAPP.
¦	Maintains all training materials and documentation.
¦	Maintains all laboratory accreditation files.

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EPA Technical Advisor: Steven Paulsen, EPA ORD Western Ecology Division
¦	Advises the Project Leader on the relevant experiences and technology developed within
the Office of Research and Development (ORD) that may be used in this project.
¦	Facilitates consultations between NRSA personnel and ORD scientists.
Laboratory Oversight Coordinator: Ellen Tarquinio, EPA HQ
¦	Ensures participating laboratories complete sample analysis following LOM.
¦	Ensures participating laboratories follow QA activities.
¦	Ensures data submitted within the specified timelines.
¦	Coordinates activities of individual lab Task Order Project Officers to ensure
methods are followed and QA activities take place.
Information Management Coordinator: Marlys Cappaert, SRA International, Inc.
¦	A contractor who functions to support implementation of the project based on technical
guidance established by the EPA Project Leader and Alternate EPA Project Leader.
¦	Oversees all sample shipments and receives data forms from the Cooperators.
¦	Oversees all aspects of data entry and data management for the project.
EPA QA Officer (QAO): Cynthia N. Johnson, EPA Office of Water
¦	Functions as an independent officer overseeing all quality assurance (QA) and quality
control (QC) activities.
¦	Responsible for ensuring that the OA program is implemented thoroughly and adequately to
document the performance of all activities.
Regional EPA Coordinators
¦	Assists EPA Project Leader with regional coordination activities.
¦	Serves on the Technical Experts Workgroup and interacts with Project Facilitator on
technical, logistical, and organizational issues on a regular basis.
¦	Serves as primary point-of-contact for the Cooperators.
Steering Committee (Technical Experts Workgroup): States, EPA, Academics, Other Federal
Agencies
¦	Provides expert consultation on key technical issues as identified by the EPA Coordination
crew and works with Project Facilitator to resolve approaches and strategies to enable data
analysis and interpretation to be scientifically valid.
Cooperator(s): States, Tribes, United States Geological Survey (USGS), Others
¦	Under the scope of their assistance agreements, plans and executes their individual studies
as part of the cross jurisdictional NRSA 2013-14 and adheres to all QA requirements and
standard operating procedures (SOPs).
¦	Interacts with the Grant Coordinator, Project Facilitator and EPA Project Leader regarding
technical, logistical, organizational issues.
Field Sampling Crew Leaders
¦	Functions as the senior member of each Cooperator's field sampling crew and the point of
contact for the Field Logistics Coordinator.

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¦	Responsible for overseeing all activities of the field sampling crew and ensuring that the
project field method protocols are followed during all sampling activities.
National Laboratory Task Order Managers
¦	Responsible for managing activities of the national contract laboratories.
¦	Provides direction to national and state labs on methods, timelines and QA activities to
ensure all actions are followed.
¦	Provides updates to EPA Lab Coordinator on the sample processing status of labs and any
questions or concerns raised by participating labs in regards to timelines and deliverables.
Field Logistics Coordinator (FLC): Chris Turner, Great Lakes Environmental Center, Inc.
¦	A contractor who functions to support implementation of the project based on technical
guidance established by the EPA Field Logistics Coordinator and the Project Leader.
¦	Serves as point-of-contact for questions from field crews and cooperators for all activities.
¦	Tracks progress of field sampling activities.

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Project Management
Project Lead - Richard Mitchell, EPA OW
Project QA - Sarah Lehmann, EPA OW
Technical Advisor - Steve Paulsen. EPA ORD
Study Design
Tony Olsen, EPA ORD
Quality Assurance
^	Cynthia N.
Johnson, EPA OW
Field Logistics
Implementation Coordinator
Training
EPA HQ EPA ORD, EPA Regions, Contractors
Field Implementation
EPA HQ EPA Regions, States, Tribes,
Contractors
Indicator Team
Field Protocols
NRSA 2013-14 Steering
Committee
f)

Sample Collection
In Situ measurements
Water Chemistry /Chlorophyll a
Microcystins
Periphyton
Benthic Macroinvertebrates
Fish Assemblage
Physical Habitat
Fecal Indicators (Enterocci)
Fish Tissue Plugs
Fish Tissue Fillets
Laboratory Pr
EPA Lab Task C rder Managers
EPA HQ-El
Information
EPA WED -M
Final
:ssing Oversight
en Tarquinio
Management
irlys Cappaert
Data
Web, STOR1T/WQX-OW

Assessment
OW - Lead
EPA ORD, EPA Regions, States, Tribes, Federal Partners,
Cooperators

Figure 2.1 Project organization

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2.1.2 Project Schedule
Training and field sampling will be conducted in 2013 and 2014. Figure 2.2 gives an overview of the
major tasks leading up to the final report.
2011	2012
2013-2014 2013-2016 2017-2019

research
design
field
lab / data
report
survey planning




-
pilot studies
-




select indicators

-
-



design frame

-




select sites

-




implementation





manuals

-
-


field training


-


sampling season


-


sample processing





data analysis



-

draft report




-
peer review




-
final report




-
Figure 2.2 Schedule
2.1.3 Objectives
The objectives, or design requirements, for the NRSA are to produce:
¦	Estimates of the 2013-2014 status of flowing waters nationally and regionally (9 aggregated
Omernik ecoregions);
¦	Estimates of the 2013-2014 status of wadeable streams and non-wadeable rivers nationally
and regionally (9 aggregated Omernik ecoregions); and	h
¦	Estimates of the change in status in wadeable streams between 2013-2014, 2008-2009 and	^
2004, nationally and regionally (9 aggregated Omernik ecoregions) and estimates of the lu
changes in status of all rivers/streams between 2013-2014 and 2008-2009, nationally and <
regionally (9 aggregated Omernik ecoregions). <
Omernik Ecoregions: Ecoregions as areas with generally similar ecosystems and with similar types,	Q
qualities, and quantities of environmental resources. The Omernik ecoregion system is hierarchical and	<
considers the spatial patterns of both the living and non-living components of the region. It is broken	§
into 4 levels currently. Ecoregion boundaries were determined by examining patterns of vegetation,	>
animal life, geology, soils, water quality, climate, and human land use, as well as other living and non-	>
living ecosystem components.	°
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2.1.4	Target Population
The target population consists of all streams and rivers within the 48 contiguous states that have flowing
water during the study index period excluding portions of tidal rivers up to head of salt defined as .05
parts per thousand (ppt) measured in the field. The study index period extends from the end of June to
the end of September and is characterized by low flow or base flow conditions. State crews that request
an early start due to the condition of streams in their area can be granted permission to begin in May
with direction from the EPA Project Lead. The target population includes the Great Rivers (i.e. main stem
of the Mississippi River). Run-of-the-river ponds and pools are included while reservoirs are excluded
(those that have greater than 7-day retention period).
2.1.5	Sample Frame
The sample frame was derived from the National Hydrography Dataset (NHD), in particular NHD-Plus.
Attributes from NHD-Plus and additional attributes added to the sample frame that are used in the
survey design include: (1) state, (2) EPA Region, (3) USGS National Water Quality Assessment (NAWQA)
Mega Region, (4) Omernik Ecoregion Level 3 (North American Commission for Environmental
Cooperation (NACEC) version), (4) WSA aggregated ecoregions (nine and three regions), (5) Strahler
order, (6) Strahler order categories (1st, 2nd, ..., 7th and 8th +), (6) FCode, (7) Urban, and (8) Frame07.
2.1.6	Expected Sample Size
Expected sample size is 1800 flowing water sites: 420 sites revisited from the NRSA 2008-09 l-4th order,
450 new sites from 1st to 4th order, 390 sites from the NRSA 2008-09 5th- 10th order and 450 new sites
from 5th to 10th order. The study is designed to sample 1800 probabilistic, 200 repeat and 200 hand-
picked (potential reference) (2200 total) river and stream sites across the country.
2.1.7	Oversample
For the NRSA 2013-14 design, the over sample list of sites is nine times the expected sample size within
each state, Figure 2.3. The large over sample size was done to accommodate those states who may
want to increase the number of sites sampled within their state for a state-level design and to provide
an adequate number of replacement sites.

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Design Sites for the
2013-2014 National Rivers & Streams Assessment
Legend
A NRSA 2013-14 Base Sites
NRSA 2013-14 Oversample Sites
Figure 2.3 Base and oversample sites
2.1.8	Field Protocol Development
The field sampling protocols for ecological indicators are based on protocols used in the WSA (USEPA
2006b) and the NRSA 2008-09 (USEPA 2016) These protocols were developed by ORD for use in the
EMAP1 program and were developed with the purpose of providing consistent and representative
information across the country. During the initial design phase of the project, collaborators and partners
worked to refine those protocols for use in the NRSA 2008-09 and the NRSA 2013-14. This involved
modifications to the original protocols used in the EMAP program for use in the Great Rivers, tidal
systems, and sites that were in between a wadeable and a beatable system. Field protocols for
collection of fish for fish tissue are based on protocols from EPA's Office of Science and Technology
(USEPA 2000).
2.1.9	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 WQX/ STORET and
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EPA's NARS IM 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.
2.1.10 Assessment
The final assessment will be developed by a team, led by OW, which will include several ORD research
facilities, EPA Regional Monitoring Coordinators, interested states/tribes, and cooperators. All
States/Tribes will be invited to participate in a collaborative process to interpret results and shape the
data assessment and report. The final assessment will include an appendix describing the quality of the
data used in the assessment.
2.2 Scope of QA Project Plan
This QAPP addresses all aspects of the data acquisition efforts of the NRSA, which focuses on the 2013
and 2014 sampling of 2200 river and stream sampling events in the contiguous United States. This QA
plan also addresses the data integration necessary to create one complete report on the ecological and
human health status of the nation's rivers and streams based on selected indicators.
Relevant Companion documents to this QAPP are: NRSA 2013-14: Site Evaluation Guidelines (SEG), NRSA
2013-14: Field Operations Manuals (FOM), and NRSA 2013-14: Laboratory Operations Manual (LOM).
See introductory pages for citation information for each document.
2.2.1 Overview of Field Operations
Field data acquisition activities are implemented for the NRSA (Table 2.1), based on guidance developed
for earlier Environmental Monitoring and Assessment Program (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 (pg
XIV) and all 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 non
target sites are documented in the SEG. Scientific collecting permits from state and federal agencies will
be procured, as needed by the respective State or cooperating organization. Site maps have been
provided to assist in the site evaluation process. Three maps are available: an aerial image, topographic
map, and road map, an example of one of the maps is provided in Figure 2.4.
Table 2.1 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
Waste Disposal Plan
Procurement and Inventory Control
Equipment, Supplies, and Services Requirements
Procurement Methods and Scheduling

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Logistics Plan Component
Required Elements
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 Recommendations

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2013-2014 National Rivers and Streams Assessment
Tennessee Site: TNS9-0921
Scale:
Imagery Date:
Imagery Source:
1:24,000
2009
ESRI World Imagery
I Meters
LU
Figure 2.4 Example site map	O
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2.2.1.1	Equipment and Supplies
The field crews will use standard field equipment and supplies which are being provided by EPA and
EPA's Field Logistics Coordinator (FLC). The FLC 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 FOMs.
2.2.1.2	Request Form
Field crews will submit requests for field forms, labels and site kits via an electronic form (Appendix B).
This form will be submitted to the NARS IM Coordinator who will ensure that the request reaches the
appropriate entity. Crews must submit sampling schedules at or before the time of submitting request
forms. Crews should submit the form at least two weeks prior to their desired sampling date.
2.2.1.3	Base Kit
The Base Kit is comprised of the subset of durable equipment and supplies needed for NRSA 2013-14
sampling that is provided by USEPA through the FLC. Typically, one Base Kit is provided to each field
crew and contains some of the equipment that is used throughout the field season. See FOMs for a list
of the items provided by USEPA in the Base Kit. We anticipate that this equipment will be available for
use in future NRSA efforts.
2.2.1.4	Site Kit
A Site Kit contains the subset of consumable supplies (i.e., items used up during sampling or requiring
replacement after use) provided by USEPA through the FLC. TheSsite Kit for core indicators will contain
all the sample bottles and labels necessary for sampling a single site. A new Site Kit is provided for each
site sampled. A separate Site Kit will be prepared and distributed for collection of whole fish tissue
samples for fillet analysis at designated sampling sites. See FOMs for the consumable items that will be
provided by USEPA. See the Addendum to the FOMs for the consumable items that will be provided by
USEPA for the periphyton meta-genomics research pilot conducted at a subset of sites during 2014.
2.2.1.5	Field Crew Supplied Items
The field crew will also supply particular items for the field sampling day. These are typical field
equipment (like a Global Positioning Device (GPS)), or boat equipment and might also include supplies
from the previous surveys. See FOMs for the items that the field crew will need to provide.
2.2.1.6	Quick Reference Guide
Field crews will receive a NRSA 2013-14 Quick Reference Guide (ORG) containing tables and figures
summarizing field activities and protocols from the NRSA 2013-14 FOMS. The QRG is meant to be used
in the field to give NRSA 2013-14 field crews a list of the required sampling protocols at each site. While
comprehensive, the steps contained in this QRG are not as detailed as the descriptions found within the
NRSA 2013-14 FOM. The user is assumed to have attended field training and completely read and
understood the FOM before using this QRG at a field site. This waterproof handbook will be a field
reference used by field crews after completing a required field training session. The field crews are also
required to keep the QRG and FOM available in the field for reference and for possible protocol
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2.2.1.7	Site Evaluation Guidelines
The NRSA 2013-14 SEG outlines the process to compile the final list of candidate sites for sampling. The
process includes locating a candidate river/stream, evaluating the site to determine if it meets the
criteria for inclusion in the target population and is accessible for sampling, and if not, replacing it with
an alternate candidate river/stream.
2.2.1.8	Lab Operations Manual
The methods used for the laboratory sample analysis are available in the NRSA 2013-14 LOM.
2.2.1.9	Field Training
Field measurements and samples are collected by trained crews. Each Field Crew Leader and a minimum
of one other field crew member, preferably the fish taxonomist, must be trained at an EPA-sponsored
training session prior to the start of the field season, along with as many crew members as possible. EPA
will provide the four-day training sessions in a number of locations around the country for cooperators
and contractors. It is required that field crews attend all four days of training in their entirety. The
training program stresses hands-on practice of methods, comparability among crews, collection of high
quality data and samples, and safety. All field crews providing field operational support to NRSA 2013-14
must adhere to the provisions of this integrated QAPP, FOM, and SEG. Trainers will maintain a list of all
personnel trained and provide the information to the NRSA Project Lead and the QA Project Lead.
Training documentation will be maintained by the NARS QA Lead in NRSA 2013-14 QA files. Field crews
may not operate without a trained field crew leader and another trained field crew member present.
Collection and analysis of samples can involve significant risks to personal health and safety. All field
crews should develop a safety plan according to the requirements of their organization. Additional
information on health and safety can be found in the FOM. It is the responsibility of the group safety
officer or project leader from participating organizations, however, to ensure that the necessary safety
courses are taken by all field personnel and that all safety policies and procedures are followed.
2.2.1.11	Field Quality Evaluation and Assistance Reviews (auditing)
Each crew will be visited by a trained person from an EPA Region, Headquarters, or contractor.
Evaluation and assistance visits will be conducted with each Field Crew early in the sampling and data
collection process, and corrective actions will be conducted in real time. These visits provide EPA with a
basis for the uniform evaluation of the data collection techniques, and an opportunity to conduct
procedural reviews to minimize data loss due to improper technique or interpretation of program
guidance. The field visit evaluations will be based on the uniform training, plans, and checklists.
2.2.1.12	Field Activities
Typically, each field crew is comprised of four to five members. The number and size of crews depends
on the duration of the sampling window, geographic distribution of sampling locations, number and
complexity of samples and field measurements, and other factors. A variety of methods may be used to
access a site. Some sampling locations require crews to hike in, transporting all equipment in backpacks.
For this reason, ruggedness and weight are important considerations in the selection of equipment and
instrumentation. Crews may need to camp out at the sampling location and may need to provide
themselves with the necessary camping equipment.
2.2.1.10 Health and Safety

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For each sampling location, a dossier will be prepared by the field crew 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. Crew leaders
will contact landowners at least two days before the planned sampling date. As the design requires
repeat visits to select sampling locations, it is important for the field crews 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.
The site verification process is shown in Figure 2.5. Upon arrival at a site, the location is verified by a GPS
receiver, landmark references, and/or local contacts.
Samples and measurements for various indicators are collected in a specified order (see example work
flows in Figure 2.6 and Figure 2.7). This order has been set up to minimize the impact of sampling for
one indicator upon subsequent indicators; for example, water chemistry samples from rivers and
streams are collected before collecting benthic invertebrates as the benthic invertebrate method calls
for kicking up sediments which would likely impact the quality of the water sample. Crews may choose
to allocate resources as they see fit, but should always be careful not to compromise samples. All
methods are fully documented in step-by-step procedures in the NRSA FOMs.
Site Verification Activities
PRE-VISIT PREPARATION
I
• Contact landowner to inform of visit and confirm access
!
( • Review site dossier and maps for directions and access requirements
_	I	^
{ SITE VERIFICATION DATA \
Record directions to site	[
•	Confirm identity of stream or river
•	Site description
•	Determine location with GPS
Determine sampling status
LOCATE SAMPLING & MEASUREMENT SITES
STREAMS
•	Locate index site and determine location with GPS
•	Locate upper and lower ends of sampling reach (40
channel widths)
•	Establish habitat transects across channel (11 per reach)
Figure 2.5 River and stream field surveys: site verification activities

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Whole Crew
Group B Activities;
Group AActiuRies:
RETURN TO STAGING AREA
Filter chlorophy1l-a sample;
prepare for transport
Collect periphyton samples
Collect fecal indicator
sample at last transect
Prepare peri phyton samples
for transport
Preserve berrthic samples
prepare for transport
Filter fecal indicator sample;
prepare for transport
Collect benthic sanples
SHIP SAMPLES
Measure in temperature
pH, DO.&conductwty
Collect water chemistry,
chlorophyll-a and microcystin
samples
Conduct physical habitat
characterizations
Report sampling ewnt through Site and Sam-
ple Status Form
Reiriew data forms for completeness
Inventory supplies for next sampling event,
Request additional supplies if needed
Inspect and clean boat, mo-
tor, fitrailerto prevent trans-
fer of nuisance species and
contaminants
Prepare forms, equipment & supplies
RETURNTO STAGING AREA
LOCATE & TRAVEL TO X-SITE
LOCATE & TRAVEL TO PHYSICAL HABITAT STATIONS
Calibrate multi-parameter probe
Load equipment and supplies onto boat(s) (jf boatable)
Clean and onganize equipment for loading
Conduct fish assessment
Collect fish tissue samples
Prepare fish tissue samples for
transport
Locate X site
\&rify s'rte as target
Determine launch site a set upstaging area
Figure 2.6 Boatable river and stream sampling: summary of field activities

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Whole Crew
Locate X site
Vferify site as target
Set up staging area
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Group A Activities:
Prepare forms, equipment & supplies
Lay out sampling reach (from X-site to Transect
11
BEGIN SAMPLING ACTIVITIES AT TRANSECT A





Conduct physical habitat
characterizations


1
t


Collect benthie sanples

Collect periphyton samples
Collect fecal indicator
sample at last transect
Group B Activities
Calibrate mufti-parameter probe
4
Lay out sampling reach (from X-site to Transect K)
RETURN TO TRANSECT F (X-SITE)
4 ~~
Measure temperature
pH, DO, 8 conductivty
Collect water chemistry,
chlorophyll-a and microeystin
samples
TRAVEL TO TRANSECT A
Conduct fish assessment
RETURN TO STAGING AREA
Preserve berithie sample®
prepare for transport
Inspect and clean boat, mo-
tor, Strailerto prevent trans-
fer of nuisance species and
contaminants
1
Filter fecal indicator sample;
prepare for transport
Filter chlorophytl-a sample;
prepare for transport
Prepare periphyton samples
for transport
Clean and organize equipment for loading
Collect fish tissue samples
RETURNTO STAGING AREA
Prepare fish tissue samples for
transport
Review data forms for completeness
Inventory supplies for next sampling event,
Request additional supplies if needed
Report sampling event through Site and Sam-
ple Status Form
SHIP SAMPLES
Figure 2.7 Wadeable stream sampling: summary of field activities

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The FOMs also contains detailed instructions for completing documentation, labeling samples, any field
processing requirements, and sample storage and shipping. Field communications will be through Field
Crew Leaders, and will involve regularly scheduled conference calls or contacts with the NRSA 2013-14
Communications Center.
Standardized field data forms are the primary means of data recording. For NRSA 2013-14, crews will
have the option to use paper or electronic forms. On completion, the data forms are reviewed by a
person other than the person who initially entered the information. Prior to departure from the field
site, the field crew leader reviews all forms and labels for completeness and legibility and ensures that
all samples are properly labeled and packed. This review process will be done for either form of data
collection (paper or electronic).
Upon return from field sampling to the office, field crews using paper forms send completed data forms
to the information management staff at WED in Corvallis, Oregon for entry into a computerized
database. Field crews using electronic forms send completed forms via email as soon as they have
access to email. At WED, the IM team review electronic data files independently to verify that values are
consistent with those recorded on the field data form or original field data file (Section 5.4.2).
Field crews store or package samples for shipment in accordance with instructions contained in the
FOM, including taking precautions to ensure holding times are not exceeded. Samples which must be
shipped are delivered by field crews to a commercial carrier; copies of bills of lading or other
documentation are maintained by the crew. Using the pertinent tracking form, crews notify the NARS IM
Center about sample shipment; thus, tracking procedures can be initiated quickly in the event samples
are not received. Chain-of-custody forms are completed by the crews for all transfers of samples, with
copies maintained by the field crew. The FLC or NARS IM team will follow up with field crews about any
missing samples and/ or incomplete files.
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 (Table 2.1). These
debriefings cover all aspects of the field program and solicit suggestions for improvements.
2.2.2 Overview of Laboratory Operations
Holding times for surface water samples vary with the sample types and analyte. Field crews begin some
analytical measurements during sampling (e.g., in situ measurements) while other analytical
measurements are not initiated until sampling has been completed (e.g., water chemistry, microcystins,
fecal indicators (Enterococci)). Analytical methods are summarized in the LOM. When available,
standard methods are used and are referenced. Where experimental methods are used or standard	g
methods are modified, these methods are documented in the laboratory methods manual or in internal	^
LU
documentation, and the laboratory coordinator will work with appropriate experts to describe them in	w
Standard Operating Procedures (SOPs) developed by the analytical laboratories.	z
Contractor and/or cooperator laboratories will perform chemical, physical, and biological analyses.
National contract labs will process most samples. Where those labs are currently in place, EPA
has identified them here. Dynamac, a lab managed by the ORD Western Ecology Division, will analyze
water chemistry and chlorophyll-a samples. A national contract lab, EnviroScience, will analyze
microcystin samples. EPA anticipates that a few pre-approved state labs may opt to analyze samples for
microcystins. A national contract lab, PG Environmental, will conduct benthic macroinvertebrate	q
identifications as will a few pre-approved state labs. A national contract lab, EnviroScience, will conduct [3
periphyton identifications as will a few pre-approved State labs. EPA's National Exposure Research	g
Laboratory (NERL) will analyze samples for enterococci and the periphyton meta-genomics indicator	^
35

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pilot project. National contract labs will analyze fish tissue plugs, PG Environmental, and fish tissue filet
samples, Microbac. A national contractor, PG Environmental, will conduct fish identification vouchers
for quality control purposes as will a few pre-approved state labs/fish taxonomists. Field crews record
the physical habitat measurements in the field on the field data sheets. Field crews send data from the
forms either electronically, if using the NRSA electronic form application, or by mail, if using the hard
copy forms to the NARS IM team. The NARS IM team uploads data provided electronically or scans field
forms into the NARS IM database.
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 are expected to conduct operations using
good laboratory practices. The following are general guidelines for analytical support laboratories:
¦	A program of scheduled maintenance of analytical balances, water purification systems,
microscopes, laboratory equipment, and instrumentation.
¦	Verification of the calibration of analytical balances using class "S" weights which are
certified by the National Institute of Standards and Technology (NIST)
(http://www.nist.gov/).
¦	Verification of the calibration of top-loading balances using NIST-certified class "P" weights.
¦	Checking and recording the composition of fresh calibration standards against the previous
lot of calibration standards. Participating laboratories will keep a percentage of the previous
lot of calibration standard to check against the next batch of samples processed. This will
ensure that a comparison between lots can occur. Acceptable comparisons are less than or
equal to two percent of the theoretical value. (This acceptance is tighter than the method
calibration criteria.)
¦	Recording all analytical data in bound logbooks in ink, or on standardized recording forms.
¦	Verification of the calibration of uniquely identified daily use thermometers using NIST-
certified thermometers.
¦	Monitoring and recording (in a logbook or on a recording form) temperatures and
performance of cold storage areas and freezer units (where samples, reagents, and
standards may be stored). During periods of sample collection operations, monitoring must
be done on a daily basis.
¦	An overall program of laboratory health and safety including periodic inspection and
verification of presence and adequacy of first aid and spill kits; verification of presence and
performance of safety showers, eyewash stations, and fume hoods; sufficiently exhausted
reagent storage units, where applicable; available chemical and hazardous materials
inventory; and accessible material safety data sheets for all required materials.
¦	An overall program of hazardous waste management and minimization, and evidence of
proper waste handling and disposal procedures (90-day storage, manifested waste streams,
etc.).
¦	If needed, having a source of reagent water meeting American Society of Testing and
Materials (ASTM) Type I specifications for conductivity (< 1 piS/cm at 25 °C; ASTM 2011)
available in sufficient quantity to support analytical operations.
¦	Appropriate microscopes or other magnification for biological sample sorting and organism
identification.
¦	Approved biological identification and taxonomic keys/guides for use in biological
identification (zooplankton, phytoplankton, diatoms, benthic macroinvertebrates) as
appropriate.

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¦	Labeling all containers used in the laboratory with date prepared contents, and initials of the
individual who prepared the contents.
¦	Dating and storing all chemicals 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 electronically using standard formats and units compatible with NARS IM
(see LOM for data templates). These files will be labeled properly by referencing the
indicator and/or analyte and date.
All laboratories providing analytical support to NRSA 2013-14 must adhere to the provisions of this
integrated QAPP and LOM. Laboratories will provide information documenting their ability to conduct
the analyses with the required level of data quality prior to data analysis. Different requirements will be
provided based on the type of analysis being completed by the laboratory (i.e. chemistry vs. biological
analyses).
Laboratories will send the documentation to the Quality Assurance Lead at EPA Headquarters (or other
such designated parties) in NRSA 2013-14 QA files. Such information may include the following,
depending on the evaluation by the Project Quality Assurance Officer.
¦	Signed Quality Assurance Project Plan by the laboratory performing analysis;
¦	Signed Laboratory Form;
¦	Valid Accreditation or Certification;
¦	Laboratory's Quality Manual and/or Data Management Plan;
¦	Method Detection Limits (MDL);
¦	Demonstration of Capability (DOC);
¦	Results from inter-laboratory comparison studies;
¦	Analysis of performance evaluation samples; and
¦	Control charts and results of internal QC sample or internal reference sample analyses to
Other requirements may include:
¦	Participation in calls regarding laboratory procedures and processes with participating
laboratories;
¦	Participation in a laboratory technical assessment or audit;
¦	Participation in performance evaluation studies; and
¦	Participation in inter-laboratory sample exchange.
See Section 6 of this QAPP for additional information related to laboratory certification. All qualified
laboratories shall work with the NARS IM Center to track samples as specified by the NARS IM Lead.
2.2.2.1 Water Chemistry and Chlorophyll A Lab Quality Evaluation
Participating laboratories will send requested documentation to the NRSA 2013-14 QA Team for
evaluation of qualifications. The NRSA 2013-14 QA Team will maintain these records in the project QA
file.
Document achieved precision, bias, accuracy.

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2.2.2.2 Biological Laboratory Quality Evaluation
The NRSA 2013-14 Quality Team requested and, whenever possible, reviewed the past performance of
biological laboratories. The biological laboratories shall adhere to the quality assurance objectives and
requirements as specified for the pertinent indicators in the LOM.
2.2.3	Data Analysis and Reporting
A technical data analysis and reporting workgroup convened by the EPA Project Leader is responsible for
development of a data analysis plan that includes a verification and validation strategy. These processes
are summarized in the data analysis sections of this QAPP. The periphyton meta-genomics pilot project
team is responsible for data analysis associated with this research indicator. This effort will proceed on a
separate timeline from the core NRSA assessment.
Validated data are transferred to the central database, the National Aquatic Resource Surveys
Information Management database, NARS IM, managed by IM support staff located at WED in Corvallis.
IM activities are discussed further in Section 5. Data in the NARS IM database are available to
cooperators for use in development of indicator metrics. All validated measurement and indicator data
from NRSA 2013-14 are eventually transferred to EPA's Water Quality Exchange (WQX) and then the
National STORET warehouse. The periphyton meta-genomics data, as research data, will not be
incorporated into NARS IM.
2.2.4	Peer Review
The NRSA 2013-14 report will undergo a thorough peer review process, where the scientific community
and the public will be given the opportunity to provide comments. Cooperators have been actively
involved in the development of the overall project management, design, methods, and standards
including the drafting of five key project documents:
¦	Quality Assurance Project Plan
¦	Site Evaluation Guidelines
¦	Field Operations Manuals (Wadeable and Non-wadeable)
¦	Laboratory Operations Manual
Outside scientific experts from universities, research centers, and other federal agencies have been
instrumental in indicator development and will continue to play an important role in data analysis. EPA
will utilize a three-tiered approach for peer review of the Survey: (1) internal and external review by
EPA, states, other cooperators and partners, (2) external scientific peer review, and (3) public review.
Once data analysis has been completed, cooperators will examine the results. Comments and feedback
from the cooperators will be incorporated into the draft report. Following review by cooperators, the
scientific peer review will occur. The public comment period will take place following incorporation of
scientific peer review comments and other EPA and cooperator reviews. This public comment period is
important to the process and will allow EPA to garner a broader perspective for clarifying the results
before the final report is issued. The public peer review is consistent with the Agency and the Office of
Management and Budget's (OMB's) revised requirements for peer review.
Below are the proposed measures EPA will implement for engaging in the peer review process:
¦	Follow the Agency's Information Quality Guidelines (IQG) and complete the IQG checklist.
¦	Develop and maintain a public website with links to standard operating procedures, quality
assurance documents, fact sheets, scientific peer review feedback, and final report.

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¦	Conduct technical workgroup meetings composed of scientific experts, cooperators, and
EPA to evaluate and recommend data analysis options and indicators.
¦	Complete data validation on all chemical, physical and biological data.
¦	Conduct final data analysis with workgroup to generate assessment results.
¦	Engage peer review contractor to identify external peer review panel.
¦	Develop draft report presenting assessment results.
¦	Develop final draft report incorporating input from cooperators and results from data
analysis group to be distributed for peer a review.
¦	Issue Federal Register (FR) Notice announcing document availability and hold public
comment (30-45 days).
¦	Consider public comments and produce a final report.
The proposed peer review schedule is provided below in Table 2.2 and is contingent upon timeliness of
data validation and schedule availability for regional meetings and experts for data analysis workshop.
Table 2.2 Proposed schedule
Proposed Schedule
Activity
May 2013- November 2015
Data validation
Fall/Winter 2015
Data analysis workshop
2016-2017
Internal peer review meetings (e.g., web conferences) with states, cooperators,
participants
Fall 2018
Draft released for external peer review
2019
Final Report

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3 DATA QUALITY OBJECTIVES
It is a policy of the U.S. EPA that Data Quality Objectives (DQOs) be developed for all environmental data
collection activities following the prescribed DQO Process. DQOs are qualitative and quantitative
statements that clarify study objectives, define the appropriate types of data, and specify the tolerable
levels of potential decision errors that will be used as the basis for establishing the quality and quantity of
data needed to support decisions (USEPA 2006). 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. DQOs are typically expressed in terms of acceptable uncertainty (e.g., width of an uncertainty
band or interval) associated with a point estimate at a desired level of statistical confidence (USEPA 2006).
The DQO Process is used to establish performance or acceptance criteria, which serve as the basis for
designing a plan for collecting data of sufficient quality and quantity to support the goals of a study (USEPA
2006). As a general rule, performance criteria represent the full set of specifications that are needed to
design a data or information collection effort such that, when implemented, it will generate newly-
collected data that are of sufficient quality and quantity to address the project's goals (USEPA 2006).
Acceptance criteria are specifications intended to evaluate the adequacy of one or more existing sources
of information or data as being acceptable to support the project's intended use (USEPA 2006).
3.1	Data Quality Objectives for the NRSA
Target DQOs established for the NRSA 2013-14 relate to the goal of describing the current status of
selected indicators of the condition of rivers and streams in the conterminous U.S. and ecoregions of
interest.
The formal statement of the DQO for national estimates is as follows:
¦	Estimate the proportion of rivers/streams (± 5%) in the conterminous U.S. that fall below the
designated threshold for good conditions for selected measures with 95% confidence.
For the ecoregions of interest the DQO is:
¦	Estimate the proportion of rivers/streams (± 15%) in a specific ecoregion that fall below the
designated threshold for good conditions for selected measures with 95% confidence.
For estimates of change, the DQOs are:
¦	Estimate the proportion of rivers/ streams (± 7%) in the conterminous U.S. that have changed
condition classes for selected measures with 95% confidence.
3.2	Measurement Quality Obj ectives
For each indicator, performance objectives (associated primarily with measurement error) are established
for several different attributes of data quality (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 and present approaches for evaluating them against acceptance criteria established for the
program.
3.2.1 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% confidence
based on a single measurement (1) (Glase et al., 1981). The MDL for an individual analyte is calculated as:

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Equation 3.1
MDL = oi,v^»-i]x s
where t is a Students' t value at a significance level (a) 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. Standard solutions should contain
analyte concentrations between two and three times the MDL objective, and should be subjected to the
entire analytical method (including any preparation or processing stages). At least seven non-consecutive
replicate measurements of a standard solution 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 shall 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.
3.2.2 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 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. The equations presented in Section 3.2.2 are general equations
used for water chemistry indicators only. Additional accuracy, precision, and bias equations provided in
the individual sections in Section 6.
Precision in absolute terms is estimated as the sample standard deviation when the number of
measurements is greater than two:
n
Equation 3.2
Where:
lis the value of the replicate,
X is the mean of repeated sample measurements, and

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n is the number of replicates.
Relative precision for such measurements is estimated as the relative standard deviation (RSD, or
coefficient of variation, [CV]):
Equation 3.3 RSD = ^zx\QQ
x
Where:
5 is the sample standard deviation of the set of measurements, and
X 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:
Equation 3.4 RPD

v A + B
v	j
: 100
Where:
A is the first measured value, and
B is the second measured value.
Precision objectives based on the range of duplicate measurements can be calculated as:
Equation 3.5 Critical Range s x a/2
Where:
s represents the precision objective in terms of a standard deviation. Range-based objectives are
calculated in relative terms as:
Equation 3.6 Critical RPD = RSD x -Jl
Where:
RSD represents the precision objectives in terms of a relative standard deviation.
For repeated measurements of samples of known composition, net bias (6) is estimated in absolute terms
as:
Equation 3.7 B — X—T
Where:
X equals the mean value for the set of measurements and
i/i
LU
T equals the theoretical or target value of a performance evaluation sample.	>
Bias in relative terms [B(%)\ is calculated as:	lu
O
Equation 3.8 B(%) =	xlOO	t
T	<
3
Where:	^
<
		I—
X equals the mean value for the set of measurements, and	cj
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Tequals 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:
3.2.3 Taxonomic Precision and Accuracy 2
For the NRSA, 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% of the biological samples from each
participating laboratory will be randomly-selected by EPA HQ, and sent to an independent taxonomist for
re-identification. Comparison of the results of whole sample re-identifications will provide a Percent
Taxonomic Disagreement (PTD) calculated as:
Where:
comppos is the number of agreements, and
N\s 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) for benthic macroinvertebrates
and fish. Individual samples exceeding 15% are examined for taxonomic areas of substantial
disagreement, and the reasons for disagreement investigated. Periphyton and algal samples have a higher
PTD due to the variance amongst species (perhaps as much as 50%).
Sample enumeration is another component of taxonomic precision with macroinvertebrates. 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:
Equation 3.9 % recovery = —- :	Lxl00
s
Where:
Cis is the measured concentration of the spiked sample,
Ci is the concentration of the unspiked sample, and
Cs is the concentration of the spike.
Equation 3.10
comp
2 See page 48 and Section 6.3 for modifications EPA implemented for periphyton due to issues that arose during
the QC process. The original process which was not completed is included as Appendix A.

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Equation 3.11
Labi + Lab2
v
An MQO of 5% is recommended (overall mean of < 5% is acceptable) for several biological samples, while
others will have higher PDE's. This is based on the laboratory approaches used and the nature of the
indicator.
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 specimens 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.gov/). Encyclopedia of Life ( EOL) or the Catalogue
of Life (COL) 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 NRSA workgroup.
Update for the Periphyton Assemblage - During the taxonomic precision and accuracy analysis for the
periphyton assemblage data (soft algae and diatoms), two issues arose that required us to alter our
approach and use of these data for the NRSA assessment. First, we originally proposed to implement QC
for taxonomic precision and accuracy that was developed for use with benthic macroinvertebrate
samples. Under that process, QC taxomists assess the same specimens as the primary taxonomists and a
direct comparison is done to evaluate precision and accuracy. As a result of differences in how periphyton
samples are processed, including microscope equipment and subsampling procedures, taxonomists had
difficulty ensuring that they were identifying the same specimens in the sample. This meant we could not
apply PTD and PDE equations intended. EPA attempted to modify the planned approach by looking at
relative abundance of individual taxa being identified by both the primary and QC taxonomists but ran
into resource constraints which cut short the analysis of the modified approach. EPA is working with USGS
and others to evaluate the modified QC approach and to develop other methods to improve the data
quality of both the soft algae and diatom assemblage data.
3.2.4 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 1800 initial sampling sites and the 200 reference
sites. Percent completeness is calculated as:
Equation 3.12 %C = V/Tx 100
Where:
V = number of measurements/samples judged valid, and
T = total number of planned measurements/samples.

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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.
3.2.5	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 training, 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 and WSA
studies. Comparability of data within and among indicators is also facilitated by the implementation of
standardized quality assurance and quality control techniques aand 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. . If some incomparability between sampling crews comes to light, the data collected by those crews
will be evaluated and possibly rejected.
3.2.6	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, 1986, 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 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
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4 SURVEY DESIGN
The survey design for the NRSA 2013-14 is the same as used for the previous NRSA 2008-09 and EMAP-
West plus the Great Rivers and the tidal system surveys. 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 NRSA, the target population is all rivers and streams in the
conterminous US, excluding sites below the head of salt and reservoirs.
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, and 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.
The survey designs used in EMAP to date have been documented in published reports for each resource
group and in the peer reviewed literature. A brief description of the design concepts and the specific
application for riverine systems is provided below. 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.
4.1 Probability-Based Sampling Design and Site Selection
4.1.1	Target Population
The target population for NRSA 2013-14 includes all stream and river channels (natural and constructed)
mapped at 1:100,000 scale within the conterminous U.S, excluding sites below the head of salt and
reservoirs.
4.1.2	Sample Frame
The NRSA 2013-14 sample frame are all derived from the National Hydrography Dataset-Plus (NHD-Plus)
stream and river channel segments coded as412, 413, 999,414, 415. 3The National Hydrography Dataset
(NHD) is the surface water component of The National Map. The NHD is a digital vector dataset used by
geographic information systems (GIS). It contains features such as lakes, ponds, streams, rivers, canals,
dams and stream gages. These data are designed to be used in general mapping and in the analysis of
surface-water systems. NHDPIus is an integrated suite of application-ready geospatial data sets that
incorporate many of the best features of the National Hydrography Dataset (NHD), the National
Elevation Dataset (NED), and the Watershed Boundary Dataset (WBD). Further information about the
codes used within the NHD-Plus can be found on the NHD webpage (http://www.horizon-
systems.com/NHDPIus/index.php).
3 These refer to the old digital line graph file codes used in the NHD. These codes are: rapid, stream, braided
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This frame is subdivided into two major parts: (1) all National Hydrography Database (NHD)-Plus stream,
river and canal segments coded as perennial, and (2) all NHD-Plus stream, river and canal segments
coded as non-perennial, i.e., 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 NRSA project using a hierarchical randomization design process described by
Stevens and Olsen (1999, 2003, 2004). The NHD served as the frame representing streams and rivers in
the US. Data from approximately 1800 river and stream sites in the United States will be used in the
assessment and sampled over a two-year index period. This total sample size will allow national
reporting as well as regional reporting at the scale of 9 aggregated Omernik Level II ecoregions, the ten
EPA Regions and 10-15 major drainage basins. Several states have added additional sites to be able to
report on the condition of streams and/or rivers within their boundaries.
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.
4.1.3	Revisit and Resample Sites
Of the sites visited in the field and found to be target sites, a total of 10% will be revisited. The 10% are
designated by the EPA for each state - 2 wadeable and two non-wadeable per state. 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 over the sampling season.
In addition, 420 NRSA 2008-2009 1st-4th order sites and 390 5th order and above sites from the NRSA
2008-2009 will be resampled during the 2013 and 2014 sampling season to evaluate change from the
NRSA and the WSA.
4.1.4	Evaluation of 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 Reach File
version 3.0 (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 used in order until the desired sample size designated for the
state has been achieved.
4.2 Hand-picked (Potential Reference) Site Selection
EPA selected a set of potential reference sites to sample in NRSA 2013-14. This hand-picked set of
candidate sites comes from various sources. States submitted potential reference sites for selection as
well as EPA Regional offices and the USGS. Previously sampled reference sites were also evaluated for
re-sampling. Field crews will sample 50% of the reference sites previously sampled in NRSA 2008-2009
during the NRSA 2013-2014 field seasons. Final targeted sites were selected based on geographic
distribution to ensure spatial coverage, distribution across the resource type, and landowner
permission.
Although crews will sample these potential reference sites during this field season, the final set of
reference rivers/streams, (i.e., those that EPA will use in the assessment), will be determined after the
complete set of data is returned. At that point, EPA will run a set of screening criteria similar to that

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used in NRSA 2008-09. This screening approach can be found in the NRSA 2012 report,
http://water.epa.gov/type/rsl/monitoring/riverssurvey/index.cfm.

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5 INFORMATION MANAGEMENT
Environmental monitoring efforts that amass large quantities of information from various sources
present unique and challenging data management opportunities. To meet these challenges, the NRSA
2013-14 employs a variety of well-tested information management (IM) strategies to aid in the
functional organization and ensured integrity of stored electronic data. IM is integral to all aspects of the
NRSA 2013-14 from initial selection of sampling sites through the dissemination and reporting of final,
validated data. And, by extension, all participants in the NRSA 2013-14 have certain responsibilities and
obligations which also make them a part of the IM system. This "inclusive" approach to managing
information helps to:
¦	Strengthen relationships among NRSA 2013-14 cooperators;
¦	Increase the quality and relevance of accumulated data; and
¦	Ensure the flexibility and sustainability of the NRSA 2013-14 IM structure.
This IM strategy provides a congruent and scientifically meaningful approach for maintaining
environmental monitoring data that will satisfy both the scientific and technological requirements of the
NRSA 2013-14.
5.1 Roles and Responsibilities
At each point where data and information are generated, compiled, or stored, the NRSA 2013-14 IM
team must manage the information (Table 5.1). 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 that use data.
The IM system also includes both hardcopy and electronic means of generating, storing, organizing and
archiving data, and the effort to achieve a functional IM process is all encompassing. To that end, all
participants in the NRSA 2013-14 play an integral part within the IM system. The following table
provides a summary of the IM responsibilities identified by NRSA 2013-14 group. Specific information on
the field crew responsibilities for tracking and sending information is found in the FOMs.

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Table 5.1 Summary of IM responsibilities.
NRSA 2013-14
Contact
Primary Role
Responsibility
Group



Field Crews
State/tribal
partners and
contractor or
other field
crews (regional
EPA, etc.)
Acquire in-situ
measurements and
prescribed list of
biotic/abiotic
samples at each site
targeted for the
survey
Complete and review field data forms and sample tracking forms
for accuracy, completeness, and legibility.
Ship/fax field and sample tracking forms to NARS IM Center so
information can be integrated into the central database.
Work with the NARS IM Center staff to develop acceptable file
structures and electronic data transfer protocols should there be
a need to transfer and integrate data into the central database.
Provide all data as specified in FOM, SEG or as negotiated with
the NRSA Project Leader.
Maintain open communications with NARS IM Center regarding
any data issues.
Analytical
Laboratories
State/tribal
partners and
contractors
Analyze samples
received from field
crews in the
manner appropriate
to acquire
biotic/abiotic
indicators/measure-
ments requested.
Review all electronic data transmittal files for completeness and
accuracy (as identified in the QAPP).
Work with the NARS IM Center staff to develop file structures and
electronic data transfer protocols for electronically-based data.
Submit completed sample tracking forms to NRSA 2013-14 IM
Center so information can be updated in the central database.
Provide all data and metadata as specified in the laboratory
transmittal guidance section of the LOM, with specific templates
for each indicator or as negotiated with the NRSA Project Leader.
Maintain open communications with NRSA 2013-14 IM Center
regarding any data issues.
IM Center staff
USEPAORD
NHEERL
Western
Ecology
Division-
Co rvallis,
Contractors
Provides support
and guidance for all
IM operations
related to
maintaining a
central data
management
system for NRSA
2013-14
Develop/update field data forms.
Plan and implement electronic data flow and management
processes.
Manage the centralized database and implement related
administration duties.
Receive, scan, and conduct error checking of field data forms.
Monitor and track samples from field collection, through
shipment to appropriate laboratory.
Receive data submission packages (analytical results and
metadata) from each laboratory.
Run automated error checking, e.g., formatting differences, field
edits, range checks, logic checks, etc.
Receive verified, validated, and final indicator data files (including
record changes and reason for change) from QA reviewers.
Maintain history of all changes to data records from inception
through delivery to WQX.
Organize data in preparation for data verification and validation
analysis and public dissemination.
Implement backup and recovery support for central database.
Implement data version control as appropriate.

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NRSA 2013-14
Contact
Primary Role
Responsibility
Group



Project Quality
Assurance
Manager
USEPA Officeof
Water
Review and
evaluate the
relevancy and
quality of
information/data
collected and
generated through
the NRSA 2013-14
surveys.
Monitor quality control information.
Evaluate results stemming from field and laboratory audits.
Investigate and take corrective action, as necessary, to mitigate
any data quality issues.
Issue guidance to NRSA 2013-14 Project Leader and IM Center
staff for qualifying data when quality standards are not met or
when protocols deviate from plan.
Steering
Committee
NRSA Project
Lead and other
team
members, EPA
Regional and
ORD
staff,states,
tribes, other
federal
agencies
Provide technical
recommendations
related to data
analysis, reporting
and overall
implementation
Provide feedback and recommendations related to QA, data
management, analysis, reporting and data distribution issues
Review and comment on QA and information management
documentation (QAPP, data templates, etc.).
Data Analysis
and Reporting
Team
USEPA Office
of Water, ORD
WED, Partners
Provide the data
analysis and
technical support
for NRSA 2013-14
reporting
requirements
Provide data integration, aggregation and transformation support
as needed for data analysis.
Provide supporting information necessary to create metadata.
Investigate and follow-up on data anomalies using identified data
analysis activities.
Produce estimates of extent and ecological condition of the target
population of the resource.
Provide written background information and data analysis
interpretation for report(s).
Document in-depth data analysis procedures used.
Provide mapping/graphical support.
Document formatting and version control.
Develops QA report for management.
Data
Finalization
Team
TBD
Provides data
librarian support
Prepare NRSA 2013-14 data for transfer to USEPA public web-
servers).
Generate data inventory catalog record (Science Inventory
Record).
Ensure all metadata is consistent, complete, and compliant with
USEPA standards.
5.1.1 State/ Tribe-Based Data Management
Some state and tribal partners will be managing activities for both field sampling and laboratory
analyses and may prefer to handle data management activities in-house. While the NARS program
encourages states and tribes to use these in-house capabilities, it is imperative that NRSA 2013-14
partners understand their particular role and responsibilities for executing these functions within the

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context of the national program. If a state or tribe chooses to do IM in-house, the state or tribe must
perform all of the functions associated with the following roles:
¦	Field Crew—including shipping/faxing of field data forms to the IM Coordinator (NRSA 2013-
14 paper or electronic field forms must be used and the original field forms must be sent to
the NARS IM Center as outlined in the NRSA 2013-14 FOM).
¦	Quality Control Team for laboratory data.
¦	NRSA QA Project Officer for ensuring that laboratory results meet specified QA
requirements.
¦	All data will flow from the state or tribe to the NARS IM Center. Typically, the state or tribe
will provide a single point of contact for all things related to NRSA 2013-14 data. However, it
may be advantageous for the NARS IM Center staff to have direct communication with the
state or tribe participating laboratories to facilitate the transfer of data, a point that may be
negotiated between the primary state or tribal contact, the regional coordinator and the
NRSA 2013-14 Project Leader (with input from the NARS IM Center staff).
¦	Data transfers to the NARS IM Center must be timely. States and tribes must submit all
initial laboratory results (i.e., those that have been verified by the laboratory and have
passed all internal laboratory QA/QC criteria) in the appropriate format to NARS IM Center
by May 2014 (for 2013 data) and March 2015 (for 2014 data), in order to meet NRSA 2013-
14 product deadlines.
¦	Data transfers must be complete. For example, laboratory analysis results submitted by a
state or tribe must be accompanied by related quality control and quality assurance data,
qualifiers code definitions, contaminant/parameter code cross-references/descriptions, test
methods, instrumentation information and any other relevant laboratory-based
assessments or documentation related to specific analytical batch runs.
¦	The state or Tribe will ensure that data meet minimum quality standards and that data
transfer files meet negotiated content and file structure standards.
The NARS IM Center will provide the necessary guidance for IM requirements. Each group that will
perform in-house IM functions will incorporate these guidelines as is practicable or as previously
negotiated.
5.2 Overview of System Structure
In its entirety, the NARS IM system includes site selection and logistics information, sample labels and
field data forms, tracking records, mapping and analytical data, data validation and analysis processes,
reports, and archives. NARS IM staff provides support and guidance to all program operations in
addition to maintaining a central database management system for the NRSA data.
The central repository for data and associated information collected for use by NRSA 2013-14 is a	H
secure, access-controlled server located at WED-Corvallis. This database is known as the NARS IM. Data	[S
are stored and managed on this system using the Structured Query Language (SQL). Data review (e.g.,	^
verification and validation) and data analysis (e.g., estimates of status and extent) are accomplished	^
primarily using programs developed in either Statistical Analysis System (SAS) or 'R' language software	^
packages.	^
-z.
o
5.2.1 Data Flow	h
<
The NRSA 2013-14 will accumulate large quantities of observational and laboratory analysis data. To	^
manage this information appropriately, it is essential to have a well-defined data flow model and	2
52

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documented approach for acquiring, storing, and summarizing the data. This conceptual model (Figure
5.1) helps focus efforts on maintaining organizational and custodial integrity, ensuring that data
available for analyses are of the highest possible quality.
5.2.2 Simplified Description of Data Flow
There are several components associated with the flow of information, these are:
¦	Communication between the NARS IM Center and the various data contributors (e.g., field
crews, laboratories and the data analysis and reporting team) is vital for maintaining an
organized, timely, and successful flow of information and data.
¦	Data are captured or acquired from four basic sources; field data transcription, laboratory
analysis reporting, automated data capture, and submission of external data files (e.g.,
Geographic Information Systems (GIS) data) encompassing an array of data types (site
characterization, biotic assessment, sediment and tissue contaminants, and water quality
analysis). Data capture generally relies on the transference of electronic data, e.g., optical
character readers and email, to a central data repository. However, some data must be
transcribed by hand in order to complete a record.
¦	Data repository or storage provides the computing platform where raw data are archived,
partially processed data are staged, and the "final" data, assimilated into a final, user-ready
data file structure, are stored. The raw data archive is maintained in a manner consistent
with providing an audit trail of all incoming records. The staging area provides the IM Center
staff with a platform for running the data through all of its QA/QC paces as well as providing
data analysts a first look at the incoming data. This area of the data system evolves as new
data are gathered and user-requirements are updated. The final data format becomes the
primary source for all statistical analysis and data distribution.
¦	Metadata—a descriptive document that contains information compliant with the Content
Standards for Digital Geospatial Metadata (CSDGM) developed by the Federal Geographic
Data Committee (FGDC).

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ECOLOGICAL INDICATOR FIELD AND LABORATORY DATA FLOW
LABORATORY
SAMPLE
COLLECTION
FIELD DATA COLLECTION
SAMPLE
Portable
SAMPLE
ANALYSIS
Labeled ^^5
Samples
Forms
RECEPT
Recorders
LABORATORY
INFORMATION
MANAGEMENT
SYSTEM
i Notebook PC
(&J
Sample
Tracking
Form(s)
0 AO C
REVIEW
OTHER
DATA FILES
(e.g., Survey
design, GIS
attribute data)
OFFICE
REVIEW
=p RAW DATA
SUBMISSION PACKA
RAW DATA
SUBMISSION PACKAGE
INFORMATION
MANAGEMENTCENTE
(WED-Corvallis)
DATA ENTRY
RAW DATA FILES
(HflRS IM Spec)
NARS IM
SQL SERVER
QA review
Create flat
files for use
with SAS or R
Relational
1 record per datum
VERIFIED DATA FILES
Update
records in
SQL tables
Data i Data
Table j Table
2 ! 3
Data
Table
QA review
VAL DATED DATA F LES
FINAL INDICATOR
DATA FILES
FINAL DATA
RECORDS
(EPA WATER
QUALITY
EXCHANGE
[WQX])
Permanent
Archival
FINAL DATA
RECORDS
(Flat files)
Posted to
Webpage or
FTP site
TA
ANALYSIS
ASSESSMENT DATA FILES
(Extent and status estimates)
Figure 5.1 Conceptual model of data flow into and out of the master SQL
The following sections describe core information management standards, data transfer protocols, and
data quality and results validation. Additionally, Section 5.4 describes the major data inputs to the
central database and the associated QA/QC processes used to record, enter, and validate measurement
and analytical data collected.
5.2.3 Core Information Management Standards
The development and organization of the NARS IM system is compliant with current EPA guidelines and
standards. 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; and
Data catalog documentation.
e?
<
o
i—
<
2
cc
O
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NRSA 2013-14 is committed to compliance with all applicable regulations and guidance concerning
hardware and software procurement, maintenance, configuration control, and QA/QC. To that end, the
NRSA 2013-14 team has adopted several IM standards that help maximize the ability to exchange data
within the study and with other aquatic resource surveys or similar large-scale monitoring and
assessment studies (e.g. NARS, past EMAP and R-EMAP studies). Specific information follows.
5.2.4	Data Formats
5.2.4.1	Attribute Data
¦	SQL Tables;
¦	SAS Data Sets;
¦	R Data Sets4; and
¦	American Standard Code for Information Interchange (Ascii) Files: Comma-Separated values,
or space-delimited, or fixed column.
5.2.4.2	GISData
¦	ARC/INFO native and export files; compressed .tar file of ARC/INFO workspace; and
¦	Spatial Data Transfer Standard (SDTS; FGDC 1999) (format available upon request).
5.2.4.3	Standard Coding Systems
¦	Sampling Site: (EPA Locational Data Policy; EPA 1991);
¦	Coordinates: Latitude and Longitude in decimal degrees (±0.002);
¦	Datum: NAD83;
¦	Chemical Compounds: Chemical Abstracts Service (CAS 1999) (http://www.cas.org/) ;
¦	Species Codes: Integrated Taxonomic Information System when possible; and
¦	Land cover/land use codes: Multi-Resolution Land Characteristics; National Hydrography
Dataset Plus Version 1.0 (NHDPIus 2005).
5.2.5	Public Accessibility
While any data created using public funds are subject to the Freedom of Information Act (FOIA), some
basic rules apply for general public accessibility and use. Briefly, those rules are:
¦	Program must comply with Data Quality Act before making any data available to the public
and person generating data must fill out and have a signed Information Quality Guidelines
package before any posting to the Web or distribution of any kind.
¦	Data and metadata files are made available to the contributor or participating group for
review or other project-related use from NARS IM or in flat files before moving to an EPA-
approved public website.
¦	Data to be placed on a public website will undergo QA/QC review according to the approved
QAPP.
¦	Only "final" data (those used to prepare the final project report) are readily available
through an EPA-approved public website.
4 R is a free software programming language and a software environment for statistical computing and graphics.
The R language is widely used among statisticians and data miners for developing statistical software and data
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As new guidance and requirements are issued, the NARS IM staff will assess the impact upon the IM
system and develop plans for ensuring timely compliance.
5.3 Data Transfer Protocols
Field crews are expected to send in hard copies of field forms or use the provided electronic field forms
containing in situ measurement and event information to the NARS IM Center defined in the FOM for
submission. Laboratories will submit electronic data files. Field crews and laboratories must submit all
sample tracking and analytical results data to the NARS IM Center in electronic form using a standard
software package to export and format data. Data submission templates for laboratories are included in
the LOM. Examples of software and the associated formats are:
Table 5.2 Summary of software
Software	Export Options (file extensions)
Microsoft Excel"
xls, xlsx, csv, formatted txt delimited
Microsoft Access"
mdb, csv, formatted txt delimited
SAS"
csv, formatted txt delimited
R
csv, formatted txt delimited
All electronic files must be accompanied by appropriate documentation (e.g., metadata, laboratory
reports, QA/QC data and review results). This documentation must contain sufficient information to
identify field contents, field formats, qualifier codes, etc. It is very important to keep EPA informed of
the completeness of the analyses. Labs may send files periodically, before all samples are analyzed, but
EPA must be informed that more data are pending if a partial file is submitted. All data files sent by the
labs must be accompanied by text documentation describing the status of the analyses, any QA/QC
problems encountered during processing, and any other information pertaining to the quality of the
data. Following is a list of general transmittal requirements each laboratory, state, or tribal based IM
group should consider when packaging data for electronic transfer to the IM Center:
¦ Provide data in row/column data file/table structure - see Appendix E in LOM for templates.
All cooperators and contractors should further consider the following:
a.	Include NRSA site and sample ID provided on the sample container label in a field
for each record (row) to ensure that each data file/table record can be related to a
site visit.
b.	Use a consistent set of column labels.
c.	Use file structures consistently.
d.	Use a consistent set of data qualifiers.
e.	Use a consistent set of units.	h
f.	Include method detection limit (MDL) as part of each result record.	lu
g.	Include reporting limit (RL) as part of each result record for water chemistry.	w
(T)
h.	Provide a description of each result/QC/QA qualifier.	<
i.	Provide results/measurements/MDL/RL in numeric form.	<
j. Maintain result qualifiers (e.g., <, Not Detected (ND)) in a separate column.	^
k. Use a separate column to identify record-type. For example, if QA or QC data are	O
included in a data file, there should be a column that allows the IM staff to readily	<
identify the different result types.	^
I. Include laboratory sample identifier.	2
~z.
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m. Include batch numbers/information so results can be paired with appropriate
QA/QC information,
n. Include "true value" concentrations, if appropriate, in QA/QC records,
o. Include a short description of preparation and analytical methods used to analyze
samples (where appropriate) either as part of the record or as a separate
description for the test(s) performed on the sample. For example, EPAxxxx.x,
ASTMxxx.x, etc. Provide a broader description (e.g., citation) if a non-standard
method is used.
p. Include a short description of instrumentation used to acquire the test result (where
appropriate). This may be reported either as part of the record or as a separate
description for each test performed on the sample. For example, GC/MS-ECD, ICP-
MS, etc.
q. Ensure that data ready for transfer to NARS IM are verified and validated, and
results are qualified to the extent possible (final verification and validation are
conducted by EPA).
r. Data results must meet the specified requirements for each indicator found in the
LOM as specified by contract or agreement,
s. Identify and qualify missing data (why are the data missing?),
t. Submit any other associated quality assurance assessments and relevant data
related to laboratory results (i.e., chemistry, nutrients). Examples include summaries
of QC sample analyses (blanks, duplicates, check standards, matrix spikes) standard
or certified reference materials, etc.), results for external performance evaluation or
proficiency testing samples, and any internal consistency checks conducted by the
laboratory. For requirements, please see specific indicator sections of this QAPP and
LOM.
Laboratories will work with the NARS IM Coordinator to establish a data load process into NARS IM.
5.4 Data Quality and Results Validation
Data quality is integrated throughout the life cycle of the data. This includes development of appropriate
forms, labels etc. for capturing data as well as verifying data entry, results, and other assessments.
Indicator workgroup experts, the data analysis and reporting team submit any recommended changes to
the Project QA Coordinator who recommends and submits any changes (deletions, additions,
corrections) to the NARS IM data center for inclusion in the validated data repository. All explanation for
data changes is included in the record history.
5.4.1 Design and Site Status Data Files
The site selection process described in Section 4 produces a list of candidate sampling locations,	h
inclusion probabilities, and associated site classification data (e.g., target status, ecoregion, etc.). The	^
Design Team provides this file to the NRSA 2013-14 Project Leader, who in turn distributes to the IM	g
staff, and field coordinators. Field coordinators determine ownership and contacts for acquiring	<
permission to access each site, and conduct site evaluation and reconnaissance activities. Field crews	<
document information from site evaluation and reconnaissance activities following the SEG and the	z
FOM. The site evaluation spreadsheets are submitted to the Project Lead by the field crews. The NARS	Q
IM Center compiles all information such as ownership, site evaluation, and reconnaissance information	<
for each site into a "site status" data file. Any missing information from the site status data file is	^
O
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identified and a request is made by the NARS IM Center to the field crew (or site evaluator) to complete
the record.
5.4.2 Sample Collection and Field Data
Field crews record sampling event observational data in a standard and consistent manner using field
data collection forms (Appendix B of the NRSA 2013-14 FOM). Prior to initiation of field activities, the
NARS IM staff works with the indicator leads and analytical support laboratories to develop standardized
field data forms and sample labels. Adhesive labels, completed by the field crews, have a standard
recording format and are affixed to each sample container. Field protocols include precautions to ensure
that label information remains legible and the label remains attached to the sample.
NRSA 2013-14 provides two options for completing field forms: electronic data entry using pre-
developed e-forms or "traditional" paper. Paper forms are printed for field crews on water resistant
paper. Copies of the field data forms and instructions for completing each form are documented in the
NRSA 2013-14 FOM. Recorded data whether through e-forms or paper are reviewed upon completion of
data collection and recording activities by the Field Crew Leader. 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 by field crews if possible, and data considered as suspect
are qualified using a flag variable. The field sampling crew enters explanations for all flagged data in a
comments section. Field crews transmit e-forms to the NARS IM Staff by selecting the "submit" button
as described in the FOM. Alternately, field crews, ship completed paper field data forms to the NARS IM
staff for entry into the central database management system.
All samples are tracked from the point of collection. Tracking of samples refers to the documentation of
the specified location of each sample in the centralized NARS IM Center database. This is done by
requiring that field crews ensure that copies of the shipping and custody record accompany all sample
transfers; other copies are transmitted to the IM Center. Each sample has a custody record that
laboratory manager is required to enter into NARS IM Center upon receipt of sample. The IM Center
tracks samples 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 the FOMs.
Procedures for completion of sample labels and field data forms and use of personal computers (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 5.3. Additional QA/QC checks or procedures specific to individual indicators are described
in the LOM.
Table 5.3 Summary sample and field data quality control activities: sample tracking
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 sampling crew
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Data Qualifiers
Defined qualifier codes used on data form; qualifiers explained in comments section on
data form
Sample Custody
Records
Unique sample ID and tracking form information entered in LIMS; sample shipment
and receipt confirmed
Sample Tracking
Sample condition inspected upon receipt and noted on tracking form with copies sent
to NRSA Field Logistics Coordinator and/or IM
Data Entry
Data entered using customized entry screens that resemble the data forms; entries
reviewed manually or by automated comparison 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 records, including raw data, archived in an organized manner. For example,
following verification/validation of the last submission into the NARS database, it is
copied to a terabit external hard drive and sent to the Project Leader for inclusion in
his project file, scheduled as 501, permanent records.
Processed samples and reference collections of taxonomic specimens submitted for
cataloging and curing at an appropriate museum facility
5.4.3 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. The lab reports any discrepancies, damaged samples, or missing samples to
the NARS IM staff and NRSA 2013-14 Project Lead electronically.
Most of the laboratory analyses for the NRSA 2013-14 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 NRSA 2013-14
indicators are described in Section 6. Additional QA/QC procedures specific to individual indicator and
parameter analyses are described in the LOM and the QAPP. Biological sample analyses are generally
based on current acceptable practices within the particular biological discipline. Some QC checks and
procedures applicable to most NRSA 2013-14 biological samples are described in the LOM and the QAPP.
Table 5.4 provides a summary of the lab data QC activities for NRSA 2013-14.
Table 5.4 Summary laboratory data 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 instruments according to manufacturer's recommendations for each
specific indicator; recalibrate or replace before analyzing any samples
QC Data
Maintain control charts, determine LT-MDLs and achieved data attributes; include
QC data summary (narrative and compatible electronic format) in submission
package
<
o
i—
<
QC
o
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Data Recording
Use software compatible with NARS 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 specimen
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 laboratory manager
¦	Data
¦	Data qualifiers and explanations
¦	Electronic format compatible with NARS IM
¦	Documentation of file and database structures
¦	Metadata: variable descriptions and formats
¦	Summary report of any problems and corrective actions implemented
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 coordinator or by supervisory personnel. Errors are corrected by
laboratory personnel 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 Protection Plan and established procedures for recording,
reviewing, and validating analysis data.
Once analytical data have passed all of the laboratory's internal review procedures, the lab prepares and
transfers a submission package using the prescribed templates in the LOM. The contents of the
submission package are largely dictated by the type of analysis (physical, chemical, or biological.
Remaining sample material and voucher specimens may be transferred to EPA's designated laboratory
or facilities as directed by the NRSA 2013-14 Project Lead. All samples and raw data files (including
logbooks, bench sheets, and instrument tracings) are to be retained by the laboratory for three years or
until authorized for disposal, in writing, by the EPA Project Leader. Deliverables from contractors and
cooperators, including raw data, are permanent as per EPA Record Schedule 258
(http://www.epa.gov/records/policy/schedule/sched/258.htm). EPA's project records are scheduled 501
(http://www.epa.gov/records/policy/schedule/sched/501.htm) and are also permanent.
i—
5.4.4 Data Review, Verification, and Validation Activities	w
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.	2
5.4.4.1 Paper Forms	z
o
The NARS IM Center either optically scans or transcribes information from field collection forms into an	p
electronic format (sometimes using a combination of both processes). During the scanning process,	^
incoming data are subjected to a number of automated error checking routines. Obvious errors are	q
corrected immediately at the time of scanning. Suspected errors that cannot be confirmed at the time of ^
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scanning are qualified for later review by someone with the appropriate background and experience
(e.g., a chemist or aquatic ecologist). The process continues until the transcribed data are 100% verified
or no corrections are required.
5.4.4.2	Electronic Forms
The NARS IM Center directly uploads information from the electronic field collection forms into their
database. During the upload process, incoming data are subjected to a number of automated error
checking routines. Omissions and errors are automatically noted in an email message to the field crew
lead.
5.4.4.3	Additional Review
Additional validation is accomplished by the NARS IM Center staff using a specific set of guidelines and
executing a series of programs (computer code) to check for: correct file structure and variable naming
and formats, outliers, missing data, typographical errors and illogical or inconsistent data based on
expected relationships to other variables. Data that fail any check routine are identified in an "exception
report" that is reviewed by an appropriate scientist for resolution.
The NARS IM Center brings any remaining questionable data to the attention of the EPA Project QA
Officer and individuals responsible for collecting the data for resolution. The EPA Project QA Officer
evaluates all data to determine completeness and validity. Additionally, the data are run through a
rigorous inspection using SQL queries or other computer programs such as SAS or R to check for
anomalous data values that are especially large or small, or are noteworthy in other ways. Focus is on
rare, extreme values since outliers may affect statistical quantities such as averages and standard
deviations.
The EPA Project QA Officer examines all laboratory quality assurance (QA) information to determine if
the laboratory met the predefined data quality objectives - available through the QAPP. Some of the
typical checks made in the processes of verification and validation are described in Table 5.5.
Automated review procedures may be used. The primary purpose of the initial checks is to confirm that
each 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. They will either be corrected, replaced
with a new acceptable value from sample reanalysis, or confirmed suspect after sample reanalysis. 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 NARS IM
System. Any suspect data will be flagged for data qualification.
The NARS IM staff, with the support of the NRSA 2013-14 Quality Team, correct and qualify all
questionable data. Copies of the raw data files are maintained in NARS IM, generally in active files until
completion of reporting and then in archive files. Redundant copies of all data files are maintained and
all files are periodically backed up to the EPA HQ shared G drive system.

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Table 5.5 Data review, verification, and validation quality control activities
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
Determine if Measurement Quality Objective (MQOs) and
project DQOs 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
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. Multivariate techniques have also been used in detecting
extreme or outlying values in environmental data sets (Meglen, 1985; Garner et al., 1991; Stapanian et
al., 1993).
The Quality Team reviews suspect data 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, the Quality Team qualifies the data 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 activity 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 site.
5.5 Data Transfer
Field crews may transmit data electronically; hardcopies of completed data and sample tracking forms
are sent via express courier service. Copies of raw, verified, and validated data files are transferred from
the QA lead to the IM staff for inclusion in the central IM system. All transfers of data are conducted
using a means of transfer, file structure, and file format that has been approved by the EPA IM Project
lead. Data files that do not meet the required specifications will not be incorporated into the centralized
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5.5.1 Database Changes
The NARS IM Center staff complete data corrections at the lowest level to ensure that any subsequent
updates will contain only the most correct data. The NARS IM Center sends back laboratory results
found to be in error to the originator (e.g., analysis laboratory) for correction. After the originator makes
any corrections, the entire batch or file is resubmitted to the NARS IM Center. The NARS IM Center uses
these resubmissions to replace any previous versions of the same data.
The NARS IM Center uses a version control methodology when receiving files. This methodology is
explained in the following sentences. Incoming data are not always immediately transportable into a
format compatible with the desired file structures. When this situation occurs, the IM staff creates a
copy of the original data file, which then becomes the working file in which any formatting changes will
take place. The original raw data will remain unchanged. This practice further ensures the integrity of
the data and provides an additional data recovery avenue, should the need arise.
All significant changes are documented by the NARS IM Center staff. The NARS IM Center includes this
information in the final summary documentation for the database (metadata).
After corrections have been applied to the data, the NARS IM Center will rerun the validation programs
to re-inspect the data.
If requested by the NARS Project QA Officer and funds are available, the NARS IM Center will implement
database auditing features to track changes.
5.6 Metadata
All metadata will be kept according to the Federal Geographic Data Committee, Content standard for
digital geospatial metadata, version 2.0. FGDC-STD-001-1998 (FGDC 1998).
5.6.1	Parameter Formats
The following parameter formats will be used:
•	Sampling Site (EPA Locational Data Policy (USEPA 1991)
•	Latitude and Longitude in decimal degrees {+/- 7.4), Negative longitude values (west of the
prime meridian)
•	Datum: 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
5.6.2	Standard Coding Systems
The following standard coding systems will be used:
•	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)

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5.7 INFORMATION MANAGEMENT OPERATIONS
5.7.1	Computing Infrastructure
Electronic data are collected and maintained within a central server housed at WED using a Windows
Server 2003 R2 (current configuration) or higher computing platform in SQL native tables for the primary
data repository and SAS® native data sets or R datasets for data analysis. Official IM functions are
conducted in a centralized environment.
5.7.2	Data Security and Accessibility
The NARS IM Center ensures that all data files in NARS IM 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 NRSA 2013-14
collaborators. Validated data files are accessible only to users specifically authorized by the NRSA 2013-
14 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 by the NARS IM Center. This ensures that if one system is destroyed or
incapacitated, IM staff can reconstruct the databases. Procedures developed to archive the data,
monitor the process, and recover the data are described in IM documentation.
Data security and accessibility standards implemented for NRSA 2013-14 IM meet EPA's standard
security authentication (i.e., username, password) process in accordance to EPA's Information
Management Security Manual (1999; EPA Directive 2195 Al) and EPA Order 2195.1 A4 (2001D). Any
data sharing requiring file transfer protocol (FTP) or internet protocol is provided through an
authenticated site.
5.7.3	Life Cycle
Data may be retrieved electronically by the NRSA 2013-14 team, partners and others throughout the
records retention and disposition lifecycle or as practicable (Section 5.4).
5.7.4	Data Recovery and Emergency Backup Procedures
The NARS IM Center maintains several backup copies of all data files and of the programs used for
processing the data. Backups of the entire system are maintained off-site by the NARS IM Center. ThelM
process used by the NARS IM Center for NRSA 2013-14 uses system backup procedures. The NARS IM
Center backs up and archives the central database according to procedures already established for EPA
Western Ecology Division and NARS IM. All laboratories generating data and developing data files are
expected to establish procedures for backing up and archiving computerized data.
5.7.5	Long-Term Data Accessibility and Archive
All data are transferred by OW's Water Quality Exchange (WQX) team working with the NARS IM Team
to U.S. EPA's agency-wide WQX data management system for archival purposes. WQX is a repository for
water quality, biological, and physical data and is used by state environmental agencies, EPA and other
federal agencies, universities, and private citizens. Data from the NRSA 2013-14 project will be run
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uploaded, states and tribes and the public will be able to download data (using Oracle software) from
their region. Data will also be provided in flat files on the NARS website.
5.8 Records Management
Removable storage media (i.e., CDs, USB Drives) and paper records are maintained in a centrally located
area at the NARS IM Center. Paper records will be returned to OW once the assessment is complete. The
IM Team identifies and maintains files using standard divisional procedures as established by EPA
Western Ecology Division. Records retention and disposition comply with U.S. EPA directive 2160
Records Management Manual (July, 1984) in accordance with the Federal Records Act of 1950.

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6 INDICATORS
A description of the NRSA indicators is found in Table 6.1.
Table 6.1 Indicators and collection location
Indicator
Description
Specs/Location in Sampling Reach
In Situ measurements (pH,
DO, temperature,
conductivity)
Measurements for temperature,
pH, dissolved oxygen (DO), and
conductivity taken to detect
extremes in condition that might
indicate impairment.
One set of measurements taken at the
index site; readings are taken at 0.5 m
depth, or at mid-depth if depth is less
than one meter.
Water chemistry (TP, TN [NH4,
NOs), basic anions and
cations, alkalinity [ANC],
dissolved organic compound
(DOC), TOC, TSS, conductivity
Water chemistry measurements
will be used to determine the
acidic conditions and nutrient
enrichment, as well as
classification of water chemistry
type.
Collected from a depth of 0.5 m at the
index site.
Chlorophyll-a
Chlorophyll-a is used to determine
algal biomass in the water.
Collected as part of water chemistry and
periphyton samples.
Microcystin
Measurement used to determine
the harmful algal bloom biomass
in the water.
Collected from a depth of 0.5 m at the
index site.
Periphyton5
Periphyton community
information is used to assess the
biological health of rivers and
streams algal community. The
NRSA will measure attributes of
the overall structure and function
of the periphyton community,
diversity and abundance to
evaluate biological integrity.
Collected from 11 locations systematically
placed at each site and combined into a
single composite sample. Sub-sampled for
taxonomy, chlorophyll-a and Ash Free Dry
Mass (AFDM).
In 2014, a 4th subsample will be collected
at a subset of sites for the periphyton
meta-genomics research pilot.
Benthic macroinvertebrate
assemblage (Littoral)
Benthic macroinvertebrate
community information is used to
assess the biological health of
rivers and streams. The NRSA will
measure attributes of the overall
structure and function of the
benthic macroinvertebrate
community, diversity,
abundances, etc to evaluate
biological integrity.
Collected from 11 locations systematically
placed at each site and combined into a
single composite sample.
i/i
QC
		O
I—
<
5 Because of issues that occurred and were uncovered during QC, EPA is not reporting on the periphyton indicator.	^
Additional work continues to improve the quality of the dataset and diatom taxonomic proceses.	2
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Fish Assemblage
The assessment will measure
specific attributes of the overall
structure and function of the
ichthyofaunal community to
evaluate biological integrity and
water quality.
Sampled throughout the sampling reach
at specified locations.
Physical habitat assessment
The physical habitat assessment
of the sampling reach and the
riparian zone (the region lying
along a bank)
Measurements collected throughout the
sampling reach at specified locations.
Fecal indicator (Enterococci)
Enterococci are bacteria that are
endemic to the guts of warm
blooded creatures. These
bacteria, by themselves, are not
considered harmful to humans
but often occur in the presence of
potential human pathogens (the
definition of an indicator
organism).
Collected at the last transect one meter
off the bank
Fish Tissue Plug
Fish Tissue plugs will provide Target species collected throughout the
information on the national sampling reach at every site,
distribution of Hg, a
bioaccumulative and toxic
chemical in fish species.
Fish Tissue Fillet
Fish Tissue Fillet samples for Hg Target species collected throughout the
and PFCs will focus on analysis of sampling reach at 453 pre-selected sites,
fillet tissue because of associated
human consumption and health
risk implications.
6.1 Water Chemistry and In-situ Measurements (Including chlorophyll-a-)
6.1.1 Introduction
Ecological indicators based on field and laboratory collected river 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. Data are collected for chlorophyll-a to provide
information on the algal loading and gross biomass of blue-greens and other algae within each stream
and river.
Detailed sample collection and handling procedures are described in the FOMs.

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6.1.2 Pertinent QA/QC Procedures
A single central laboratory and some state laboratories will analyze the water chemistry samples. The
specific quality control procedures used by each laboratory are implemented to ensure that:
¦	Objectives established for various data quality indicators being met.
¦	Results are consistent and comparable among all participating laboratories.
The central laboratory demonstrated in previous studies that it can meet the required Laboratory
Reporting Levels( RLs) (USEPA 2004). All laboratories will follow the QA/QC procedures outlined in the
QAPP and the LOM will be followed to ensure these Laboratory RLs are met. A summary and diagram of
the QA processes related to water chemistry samples for the NRSA 2013-14 is found in Figure 6.2.
6.1.2.1 Laboratory Performance Requirements
Table 6.2 summarizes the pertinent laboratory performance requirements for the water chemistry
indicators.
Table 6.2 Laboratory method performance requirements: water chemistry
Analyte
Units
Potential
Lower Reporting
Transitio
Precision
Bias


Range of
Limit7
n Value8
Objective9
Objective10


Samples6




Conductivity
l_iS/cm at
25°C
1 to 15,000
2.0
20
± 2 or±10%
± 2 or 5%
pH (laboratory)
Standard
(Std) Units
3.5 to 10
N/A
5.75
>5.75 = ±0.15
<5.75 = ±0.07
>5.75 = ±0.05
<5.75 = ±0.15
Turbidity
Nephelome
trie
Turbidity
Units (NTU)
0 to 44,000
2.0
20
± 2 or±10%
± 2 or±10%
Dissolved
Organic Carbon
(DOC)
mg C/L
0.1 to 109
0.20
< 1
> 1
± 0.10 or
±10%
± 0.10 or
±10%
Estimated from samples analyzed at the WED-Corvallis laboratory between 1999 and 2005 for TIME, EMAP-West, and WSA streams
from across the U.S.
The lower reporting limit is the lowest value that needs to be quantified (as opposed to just detected), and represents the value of the
lowest nonzero calibration standard used. It is set to 2 times the long-term method detection limit, following USGS Open File Report
99-193 New Reporting Procedures Based on Long-Term Method Detection Levels and Some Considerations for Interpretations of Water-
Quality Data Provided by the U.S. Geological Survey National Water Quality Laboratory.
Value at which performance objectives for precision and bias switch from absolute (< transition value) to relative > transition value).
Two-tiered approach based on Hunt, D. T.E. and A.L. Wilson. 1986. The Chemical Analysis of Water: General Principles and Techniques.
2nd ed. Royal Society of Chemistry, London, England.
For standard samples, precision is estimated as the standard deviation of repeated measurements across batches at the lower
concentration range, and as percent relative standard deviation of repeated measurements across batches at the higher concentration
range.
For pH precision, the looser criteria apply to more highly alkaline samples. For NRSA, that is less of a concern than the ability to measure
acidic samples accurately and precisely.	O
I—
Bias (systematic error) is estimated as the difference between the mean measured value and the target value of a performance	^
evaluation and/or internal reference samples at the lower concentration range measured across sample batches, and as the percent	^
difference at the higher concentration range.	2
68

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Analyte
Units
Potential
Range of
Samples6
Lower Reporting
Limit7
Transitio
n Value8
Precision
Objective9
Bias
Objective10
Ammonium
(NH4)
mg N/L
Oto 17
0.02 (1.4 neq/L)
0.10
± 0.01 or
±10%
± 0.01 or
±10%
Nitrate-Nitrite
(N03-N02)
mg N/L
0 to 360 (as
nitrate)
0.02
0.10
± 0.01 or
±10%
± 0.01 or
±10%
Total Nitrogen
(TN)
mg/L
0.1 to 90
0.02
0.10
± 0.01 or
±10%
± 0.01 or
±10%
Total
Phosphorus (TP)
Hg P/L
0 to 22,000
4
20
± 2 or±10%
± 2 or±10%
Sulfate (S04)
mg SO4/L
0 to 5,000
0.50 (10 neq/L)
2.5
±0.25 or
±10%
±0.25 or
±10%
Chloride (CI)
mg Cl/L
0 to 5,000
0.20 (6 neq/L)
1
± 0.10 or
±10%
± 0.10 or
±10%
Nitrate (N03)
mg N/L
0 to 360
0.02 (4 neq/L)
0.1
± 0.01 or
±10%
± 0.01 ±10%
Calcium (Ca)
mg Ca/L
0.04 to
5,000
0.10 (5 neq/L)
0.5
± 0.05 or
±10%
± 0.05 or
±10%
Magnesium (Mg)
mg Mg/L
0.1 to 350
0.10 (8 neq/L)
0.5
± 0.05 or
±10%
± 0.05 or
±10%
Sodium (Na)
mg Na/L
0.08 to
3,500
0.10 (4 neq/L)
0.5
± 0.05 or
±10%
± 0.05 or
±10%
Potassium (K)
mg K/L
0.01 to 120
0.10 (2 neq/L)
0.5
± 0.05 or
±10%
± 0.05 or
±10%
Silica (Si02)
mgSiOz/L
0.01 to 100
0.10
0.5
± 0.05 or
±10%
± 0.05 or
±10%
Total Suspended
Solids (TSS)
mg/L
0 to 27,000
2
10
±1 or ±10%
±1 or ±10%
True Color
PCU
0 to 350
5
50
±5 or ±10%
±5 or ±10%
Chlorophyll a
M-g/L (in
extract)
0.7 to
11,000
0.5
15
± 1.5 or ±10%
± 1.5 or ±10%

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Table 6.3 summarizes the pertinent laboratory quality control samples for the water chemistry
indicators.
Table 6.3 Laboratory quality control samples: water chemistry
QC Sample Analytes
Description
Frequency
Acceptance
Corrective Action
Type and


Criteria

Description




Laboratory/
All except TSS

Once per day
Control limits
Prepare and analyze new
Reagent
(ForTSS, the lab

prior to
< LRL
blank. Determine and
Blank
will filter a

sample

correct problem (e.g.,

known volume

analysis

reagent contamination,

of reagent water



instrument calibration, or

and process the



contamination introduced

filters per



during filtration) before

method)



proceeding with any





sample analyses.





Reestablish statistical





control by analyzing three





blank samples.
Filtration
All dissolved
ASTM Type II
Prepare once
Measured
Measure archived
Blank
analytes
reagent
per week
concentrations
samples if review of other


water
and archive.
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QC Sample Analytes	Description
Type and
Description
Frequency Acceptance Corrective Action
Criteria
Calibration
QCCS
For turbidity, a
QCCS is prepared
at one level for
routine analyses
(USEPA 1987).
Additional QCCSs
are prepared as
needed for
samples having
estimated
turbidities
greater than 20
NTU.

Before and
after sample
analyses
±10% or
method
criteria
Repeat QCCS analysis.
Recalibrate and analyze
QCCS.
Reanalyze all routine
samples (including PE and
field replicate samples)
analyzed since the last
acceptable QCCS
measurement.
Laboratory
Duplicate
Sample
All analyses

One per
batch
Control limits
< precision
objective
If results are below LRL:
Prepare and analyze split
from different sample
(volume permitting).
Review precision of QCCS
measurements for batch.
Check preparation of split
sample. Qualify all
samples in batch for
possible reanalysis.
Standard
Reference
Material
(SRM)
When available
for a particular
analyte

One analysis
in a
minimum of
five separate
batches
Manufacturers
certified range
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
samples are conducted.
Reestablish control by
three successive
reference standard
measurements that are
acceptable. Qualify all
sample batches analyzed
since the last acceptable
reference standard
measurement for possible
reanalysis.
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QC Sample
Type and
Description
Analytes
Description
Frequency
Acceptance
Criteria
Corrective Action
Matrix
Only prepared

One per
Control limits
Select two additional
Spike
when samples

batch
for recovery
samples and prepare
Samples
with potential


cannot exceed
fortified subsamples.

for matrix


100±20%
Reanalyze all suspected

interferences are



samples in batch by the

encountered



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).
6.1.2.2 Data Reporting, Review, and Management
Checks made of the data in the process of review and verification is summarized in Table 6.4. Data
reporting units and significant figures are summarized in Table 6.5.
The Project QA Officer is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 6.4 Data validation quality control: water chemistry
Activity or Procedure
Requirements and Corrective Action
Range checks, summary 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 |aeq/L
%IBD < ±25%.
If total ionic strength > 100 |aeq/L
%IBD <±10%.
Determine which analytes, if any, are the largest contributors to
the ion imbalance. Review suspect analytes for analytical error
and reanalyze.
Flag = unacceptable %IBD
If analytical error is not indicated, qualify sample to attribute
imbalance to unmeasured ions. Reanalysis is not required.
Flag = %IBD outside acceptance criteria due to
unmeasured ions
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Activity or Procedure
Requirements and Corrective Action
Conductivity check:
Compare measured conductivity of each
sample to a calculated conductivity based
on the equivalent conductance of major
ions in solution (Hillman et al., 1987).
If measured conductivity < 25 |j.S/cm,
([measured - calculated] -r- measured) < ±25%.
If measured conductivity > 25 |j.S/cm,
([measured - calculated] -r- 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.
Review data from QA samples (laboratory
Performance evaluation (PE) samples,
and inter-laboratory comparison
samples).
Indicator QC Coordinator determines impact and possible
limitations on overall usability of data based on the specific issue.
Table 6.5 Data reporting criteria: water chemistry
Measurement
Units
No. Significant
Figures
Maximum No.
Decimal Places
DO
mg/L
2
1
Temperature
°C
2
1
PH
pH units
3
2
Carbon, total & dissolved organic
mg/L
3
1
ANC
|aeq/L
3
1
Conductivity
|j.S/cm at 25 °C
3
1
Calcium, magnesium, sodium, potassium,
ammonium, chloride, nitrate, and sulfate
|aeq/L
3
1
Silica
mg/L
3
2
Total phosphorus
M-g/L
3
0
Total nitrogen
mg/L
3
2
Nitrate-Nitrite
mg/L
3
2
Ammonia
mg/L
3
2
Turbidity
NTU
3
0
True color
PCU
2
0
TSS
mg/L
3
1
Chlorophyll a
ug/l
3
2
QC
O
I—
The ion balance for each sample is computed using the results for major cations, anions, and the	^3
measured acid neutralizing capacity. The percent ion difference (%IBD) for a sample is calculated as:	o
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Percent ion difference (%IBD)
V cations - T" anions)- ANC
Equation 6.1 %IBD =				r	1
ANC + 2_, anions + ^ cations + 2\H J
Where:
ANC is the acid neutralization capacity; cations are the concentrations of calcium, magnesium, sodium,
potassium, and ammonium (converted from mg/L to |a,eq/L); anions are the concentrations of chloride,
nitrate, and sulfate (converted from mg/L to |a,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 |a,eq/L are presented in
Table 6.6. For the conductivity check, equivalent conductivities for major ions are presented in Table
6.7.
Table 6.6 Constants for converting major ion concentration from mg/L to |ieq/L
Analyte	Conversion from mg/L to |a,eq/Ln
Calcium
49.9
Magnesium
82.3
Potassium
25.6
Sodium
43.5
Ammonium
55.4
Chloride
28.2
Nitrate
16.1
Sulfate
20.8
Table 6.7 Factors to calculate equivalent conductivities of major ions12
Ion
Equivalent
Conductance per
mg/L (|o,S/cm at 25
°C)
Ion
Equivalent
Conductance per mg/L
(|4,S/cm at 25 °C)
Calcium
2.60
Nitrate
1.15
Magnesium
3.82
Sulfate
1.54
Potassium
1.84
Hydrogen
3.5 x10s 13
Sodium
2.13
Hydroxide
1.92 x10s
Ammonium
4.13
Bicarbonate
0.715
Chloride
2.14
Carbonate
2.82
i/i
11	Measured values are multiplied by the conversion factor.	q
I—
12	From Hillman etal. (1987).	<
13	Specific conductance per mole/L, rather than per mg/L.	2
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6.1.3 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities.
Crews will measure water chemistry field measurements with a calibrated multiprobe. The crews will
calibrate the DO, pH, and conductivity prior to each sampling event in the field. Crews will test the
temperature meter against a thermometer that is traceable to the National Institute of Standards (NIST)
at least once per sampling season. Field crews will verify that all sample containers are uncontaminated
and intact, and that all sample labels are legible and intact. A summary of field quality
controlprocedures for water chemistry is presented in Table 6.8 and a visual description is laid out in
Figure 6.1.
Before leaving the field, the crews will:
¦	Check the label to ensure that all written information is complete and legible.
¦	Place a strip of clear packing tape over the label, covering the label completely.
¦	Record the sample ID number assigned to the water chemistry sample on the Sample
Collection Form.
¦	Enter a flag code and provide comments on the Sample Collection Form if there are any
problems in collecting the sample or if conditions occur that may affect sample integrity.
¦	Store the sample on wet ice in a cooler.
¦	Recheck all forms and labels for completeness and legibility.
Table 6.8 Field quality control: water chemistry
Check Description	Frequency Acceptance Criteria Corrective Actions
Check calibration of
multiprobe
Prior to each
sampling day
Specific to instrument
Adjust and recalibrate, redeploy gear
Check calibrated
sounding rod
Each site
Depth measurements
for all sampling points
Obtain best estimate of depth where
actual measurement not possible
Check integrity of
sample containers and
labels
Each site
Clean, intact
containers and labels
Obtain replacement supplies
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FIELD MEASUREMENT PROCESS: WATER CHEMISTRY INDICATOR
PRE-DEPARTURE CHECK
Fail
Replace Probe
and/or Instrument
Probe Inspectrion
Electronic Checks
Test Calibration
Pass
1st time
FIELD CALIBRATION
QC CHECK
Fail
QC Sample Measurement
Performance Evaluation
Measurement	^
2nd time
Pass
CONDUCT
MEASUREMENTS
AND RECORD DATA
Qualify Data
QC CHECK
Fail
QC Sample Measurement
Duplicate Measurement
Qualify Data
Pass
Fail
REVIEW
DATA FORM
Qualify Data
Correct Errors
Pass
ACCEPT FOR DATA ENTRY
Figure 6.1 Field measurement process: water chemistry samples
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PREPARE QC SAMPLES
Laboratory Blank
Fortified Sample
Laboratory Split Sample
PREPARE QC SAMPLES
SAMPLEPROCESSING
QC Check Samples (QCCS)
Internal Reference Sample
CALIBRATION
Contamination
or Biased
Calibration
Laboratory\^
Blank 	>
Pass
Fail
LT-MDL
QCCS
Recheck
LT-MDL QCCS
Insert randomly
into sample batch
Pass
Fail
Calibration
QCCS
Pass ^
SAMPLES
Pass
Accept Batch
for Entry
and Verification
Pass
Fail
Review
Results
Re-Calibrate
Re-analyze
Previous Samples
Calibration
QCCS
Fail
Pass
Qualify batch
for possible
re-analysis
SAMPLES
Pass
Fail
Calibration
QCCS
Figure 6.2 Analysis activities: water chemistry samples
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6.2 Algal Toxin: Microcystin
6.2.1	Sample Design and Methods
Detailed sample collection and handling procedures are found in the FOMs.
6.2.2	Pertinent QA/QC Procedures
6.2.2.1 Quality Assurance Objectives
MQOs for absorbances are given in Table 6.9. General requirements for comparability and
representativeness are addressed in Section 2.
Table 6.9 Measurement data quality objectives: microcystin
Variable or Measurement
Precision
Accuracy
Completeness
Algal Toxin Indicator
±15%14
±15%15
NA
6.2.2.2 QA Values and Objectives
Quality control for the microcystin indicator are listed in Table 6.10.
Table 6.10 Sample analysis quality control activities: microcystin
Quality Control Activity Description and Requirements	Corrective Action
Kit - Shelf Life
Is within its expiration date listed on kit
box.
If kit has expired, then discard
or set aside for training
activities.
Kit - Contents
All required contents must be present
and in acceptable condition. This is
important because Abraxis has
calibrated the standards and reagents
separately for each kit.
If any bottles are missing or
damaged, discard the kit.
Calibration
All of the following must be met:
o Standard curve must have a
correlation coefficient of >0.99;
o Average absorbance value, A0,
for SO must be >0.80; and
o Standards S0-S5 must have
decreasing average absorbance
values. That is, if A, is the
average of the absorbance
values for S,, then the
If any requirement fails:
•	Results from the analytical
run are not reported.
•	All samples in the analytical
run are reanalyzed until
calibration provides
acceptable results.
14	For microcystin, the precision for a sample is re[prted in terms of the percent coefficient of variation (%CV) of its
absorbance values. For %CV calculation, see the Laboratory Operations Manual. Relative Standard Deviation (RSD)
is the same as the %CV. Because many of the plate reader software programs provide the CV in their output, the	£2
procedure presents the quality control requirements in terms of %CV instead of RSD.	^
<
15	For microcystin, accuracy us calculated by comparing the average concentration of the kit control with the	^
required range (0.75 + 0.185).	2
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absorbance average values must
be; Ao > Ai > A2 > A3 > A4 >As
Kit Control
The average concentration value of the If either requirement fails:
duplicates (or triplicate) must be within , r . ...
• Results from the analytical
the range of 0.75 + - 0.185 ug/L. That is, .
run are not reported
results must be between 0.565 and
0.935. • The lab evaluates its
Negative Control
The values for the negative control processes, and if
replicates must meet the following appropriate, modifies its
requirements: processes to correct
. . possible contamination or
0 All concentration values must be
, other problems.
< 0.15 ng/L (i.e., the reporting
limit); and • The lab reanalyzes all
0 One or more concentration samples in the analytical
results must be nondetectable run until the controls meet
(i.e., <0.10 ng/L) the requirements.
Sample Evaluations
All samples are run in duplicate. Each If %CV of the absorbance for
duplicate pair must have %CV<15% the sample>15%, then:
between its absorbance values. „ , , ,
•	Record the results for both
duplicates.
•	Report the data for both
duplicate results as Quality
Control Failure "QCF"; and
•	Re-analyze the sample in a
new analytical run. No
samples are to be run
more than twice.
If the second run passes, then
the data analyst will exclude
the data from the first run. If
both runs fail, the data analyst
will determine if either value
should be used in the analysis
(e.g., it might be acceptable to
use data if the CV is just slightly
over 15%).
Results Within
Calibration Range
All samples are run in duplicate. If both If one or both duplicates
of the values are less than the upper register as 'HIGH,' then the
calibration range (i.e., 5.0 ng/L for sample must be diluted and re-
undiluted samples), then the run until both results are within
requirement is met. the calibration range. No
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External Quality Control
Sample
External QC Coordinator, supported by
QC contractor, provides 1-2 sets of
identical samples to all laboratories and
compares results.
samples are to be run more
than twice.
Based upon the evaluation, the
External QC Coordinator may
request additional information
from one or more laboratories
about any deviations from the
Method or unique laboratory
practices that might account
for differences between the
laboratory and others. With
this additional information, the
External QC Coordinator will
determine an appropriate
course of action, including no
action, flagging the data, or
excluding some or all of the
laboratory's data.
6.3 Periphyton
6.3.1	Introduction
Periphyton are diatoms and soft-bodied algae that are attached or otherwise associated with channel
substrates. They can contribute to the physical stability of inorganic substrate particles, and provide
habitat and structure. Periphyton are useful indicators of environmental condition because they
respond rapidly and are sensitive to a number of anthropogenic disturbances, including habitat
destruction, contamination by nutrients, metals, herbicides, hydrocarbons, and acidification.
6.3.2	Sampling Design and Methods
Detailed sample collection and handling procedures are described in FOM. Field collected periphyton
samples will be subdivided into three samples for the analysis of community identification, chlorophyll a
and AFDM. In the 2014 sampling year, crews will subset a fourth sample from the composite periphyton
sample for use in the periphyton meta-genomics pilot research effort.
Analysis: Community identification samples are preserved, processed, enumerated, and organisms
identified to the lowest possible taxonomic level (generally genus) using specified standard keys and
references. Processing and archival methods are based on USGS NAWQA methods (Charles et al. 2003).
Detailed procedures are contained in the LOM.
Chlorophyll a sub-samples will be filtered in the field and analyzed in the laboratory according to the
procedures outlined in the LOM.
AFDM subsamples will be filtered in the field and analyzed in the laboratory according to the procedures
outlined in the laboratory operations manual.
The periphyton meta-genomics subsample will be collected in the field and shipped to the lab as
described in the Addendum to the FOMs. These samples will be analyzed at an EPA ORD lab and the
analysis will be separate from the main NRSA project. ORD is developing a separate QAPP for this work.
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6.3.3 Quality Assurance Objectives
During the taxonomic precision and accuracy analysis for the periphyton assemblage data (soft algae
and diatoms), two issues arose that required us to alter our approach and use of these data for the
NRSA assessment. First, we originally proposed to implement QC for taxonomic precision and accuracy
that was developed for use with benthic macroinvertebrate samples. Under that process, QC taxomists
assess the same specimens as the primary taxonomists and a direct comparison is done to evaluate
precision and accuracy. As a result of differences in how periphyton samples are processed, including
microscope equipment and subsampling procedures, taxonomists had difficulty ensuring that they were
identifying the same specimens in the sample. This meant we could not apply PTD and PDE equations as
intended. EPA attempted to modify the planned approach by looking at relative abundance of individual
taxa being identified by both the primary and QC taxonomists but ran into resource constraints which
cut short implementation of the modified approach. EPA is working with USGS and others to evaluate
the modified QC approach and to develop other methods to improve the data quality of both the soft
algae and diatom assemblage data. Information on the periphyton ID MQOs and QC process originally
planned for NRSA can be found in Appendix A.
The QA procedures for periphyton chlorophyll a and AFDM are identical to the water chemistry
chlorophyll a procedures. The water chemistry labs will perform the sample analysis for all of these
samples and follow the same QA procedures laid out in Section 6.1. General requirements for
comparability and representativeness are addressed in Section 2. The MQOs for the periphyton meta-
genomics subsample will be found in the ORD QAPP.
6.3.4 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOM. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Flag codes are
recorded and comments provided on the Sample Collection Form to denote any problems encountered
in collecting the sample or the presence of any conditions that may affect sample integrity. A summary
of field quality control procedures for periphyton samples is presented in Table 6.11.
Table 6.11 Sample collection and field processing quality control: periphyton
Quality Control Activity Description and Requirements	Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement
supplies
Sample Storage (field)
Store samples on wet ice and in a dark place (cooler)
Discard and recollect
sample
Homogenize composite
Thoroughly mix samples before processing to ensure that
the sample material is evenly distributed throughout the
composite
Discard and recollect
sample
Processing samples in the
field
Use the appropriate filter or preservative for each type of
sample prepared from the composite
Discard and prepare a
replacement subsample
from the composite
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Quality Control Activity
Description and Requirements
Corrective Action
Holding times
The frozen chlorophyll and AFDM filters are shipped
immediately on wet ice. The ID sample preserved with
formalin solution is held in a refrigerator and must be
shipped on wet ice within 2 weeks of collection. The
FROZEN periphyton meta-genomic samples must be
shipped within 1 week of collection on dry ice.
Qualify samples
6.4 Benthic Macroinvertebrates
6.4.1	Introduction
The benthic macroinvertebrate assemblage found in sediments and on substrates of streams and rivers
reflect an important aspect of the biological condition of the stream or river. The response of benthic
communities to various stressors can often be used to determine the type of stressor and to monitor
trends (Klemm et al1990). The overall objectives of the benthic macroinvertebrate indicators are to
detect stresses on community structure in rivers and streams and to assess and monitor the relative
severity of those stresses. The benthic macroinvertebrate indicator procedures are based on various
bioassessment literatures (Barbour et al. 1999, Hawkins et al. 2000, Peck et al. 2003).
6.4.2	Sampling Design
Detailed sample collection and handling procedures are described in the FOM.
Analysis: Community identification samples are preserved, processed, enumerated, and organisms
identified to the lowest possible taxonomic level (generally genus) using specified standard keys and
references. Detailed procedures are contained in the LOM.
6.4.3	Quality Assurance Objectives
Measurement quality objectives (MQOs) are given in Table 6.12, Section 3.2. General requirements for
comparability and representativeness are addressed in Section 2. The MQOs given in Section 3.2
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
sorting and picking accuracy (defined and procedure in LOM Section 4.4.1) is estimated from
examinations (repicks) of randomly selected residues by experienced taxonomists.
Table 6.12 Measurement data quality objectives: benthic macroinvertebrates
Variable or Measurement
Precision
Accuracy
Completeness

Sort and Pick
N/A
10%
99%

Identification
15%
5%
99%

he completeness objectives are established for eacl
h 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
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variance components, and may impact the representativeness of these estimates because of possible
bias in the set of measurements obtained.
6.4.4	Pertinent QA/QC Procedures
6.4.4.1 Sorting and Subsampling QC
¦	A QC Analyst will use 6-10X microscopes to check all sorted grids from the first five samples
processed by a sorter to ensure that each meets the acceptable criteria for percent sorting
efficiency (PSE), which is 90%. This will not only apply to inexperienced sorters, but also to
those initially deemed as "experienced." Qualification will only occur when sorters achieve
PSE > 90% for five samples consecutively.
¦	The QC Officer will calculate PSE for each sample as follows:
Equation 6.2 Percent sorting efficiency (PSE).
PSE = ——— x 100
A + B
Where: A = number of organisms found by the primary sorter, and B = number of
recoveries (organisms missed by the primary sort and found during the QC check).
¦	If the sorting efficiency for each of these five consecutive samples is > 90% for a particular
individual, this individual is considered "experienced" and can serve as a QC Officer. In the
event that an individual fails to achieve > 90% sorting efficiency, he or she will be required
to sort an additional five samples to continue to monitor their sorting efficiency. However, if
he or she shows marked improvement in sorting efficiency prior to completion of the next
five samples, achieving > 90% sorting efficiency, the QA Officer may, at his/her discretion,
consider this individual to be "experienced". Do not calculate PSE for samples processed by
more than one individual.
¦	After individuals qualify, 10% (1 out of 10, randomly selected) of their samples will be
checked.
¦	If an "experienced" individual fails to maintain a > 90% PSE as determined by QC checks, a
QC Officer will perform QC checks on every grid of five consecutive samples until a > 90%
sorting efficiency is achieved on all five. During this time, that individual will not be able to
perform QC checks.
6.4.5	Taxonomic QC
6.4.5.1	Internal Taxonomic QC
As directed by the EPA QA Coordinator, an in-house QC Analyst will conduct an internal 10% re-
identification of all samples identified by that laboratory to ensure that each meets the acceptable
criteria for percent identification efficiency which is 85%.
If the individual fails to maintain a > 85% identification as determined by QC checks, previous samples
will be re-counted and identified.
6.4.5.2	External Taxonomic QC
¦	Upon receipt of the data, the EPA QA Coordinator for macroinvertebrates will randomly
select 10% of the samples. The EPA QA Coordinator will then have the original laboratory
send those samples to a QC taxonomist (another experienced taxonomist who did not
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participate in the original identifications). The original laboratory will complete a chain-of-
custody form and send with the samples and notify NARS IM.
The QC taxonomist will perform whole-sample re-identifications, taking care to ensure
inclusion of all slide-mounted specimens and completing another copy of the Benthic
Macroinvertebrate Taxonomic Bench Sheet for each sample. The QC taxonomist will label
each bench sheet with the term "QC Re-ID." As each bench sheet is completed, the QC
taxonomist will fax it to the NARS QA Coordinator.
The EPA QA Coordinator will compare the taxonomic results (counts AND identifications)
generated by the primary and QC taxonomists for each sample and calculate percent
difference in enumeration (PDE) and percent taxonomic disagreement (PTD) as measures of
taxonomic precision (Stribling et al. 2003) as follows:
Equation 6.3 Percent difference in enumeration (PDE).
W -ftJ
PDE=*—	— xlOO
nx +n2
Where: rii is the number of specimens counted in a sample by the first taxonomist and
n2 is the number of specimens counted by the QC taxonomist.
The recommendation for PDE is 5% or less.
Equation 6.4 Percent taxonomic disagreement (PTD).
PTD =
1-
COmPpos
N
100
Where: compp0s is the number of agreements (positive comparisons) and N is the total
number of specimens in the larger of the two counts.
¦	A PTD of 15% or less is recommended for taxonomic difference (overall mean < 15% is
acceptable). The NRSA QA Officer will examine individual samples exceeding 15% for
taxonomic areas of substantial disagreement, and investigate the reasons for disagreement.
A reconciliation call between the primary and secondary taxonomist will facilitate this
discussion of samples that do not meet specified criteria.. The NRSA QA officer, along with
the QC taxonomist and the primary taxonomist, will investigate results greater than this
value and they will note them for indication of error patterns or trends.
¦	Corrective actions include determining problem areas (taxa) and consistent disagreements
and addressing problems through taxonomist interactions. These actions help to rectify
disagreements resulting from identification to a specific taxonomic level.
6.4.6 Taxonomic QC Review & Reconciliation
The EPA QA Coordinator prepares a report or technical memorandum to quantify aspects of taxonomic
precision, assess data acceptability, highlight taxonomic problem areas, and provide recommendations
for improving precision. This report is submitted to the HQ Project Management Team, with copies sent
to the primary and QC taxonomists. Another copy is maintained in the project file. Significant
differences may result in the re-identification of samples by the primary taxonomist and a second QC
check by the secondary taxonomist.	g
Each laboratory prepares reference/ voucher samples. These samples will be identified and digitally	h
referenced (a photograph with taxonomic information superimposed on the photograph and in the file	^
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name) and will be included in an electronic file folder on the NARS Sharefile. All samples are stored at
the laboratory until the Project Lead notifies the lab regarding disposition.
Table 6.13 Laboratory quality control: benthic macroinvertebrates
Check or Sample	Frequency	Acceptance Criteria Corrective Action
Description
SAMPLE PROCESSING AND SORTING
Sample pickate examined
by different analyst
within lab
10% of all samples
completed per
analyst
PSE > 90%
If < 90%, examine all
residuals of samples by
that analyst and retrain
analyst
Sorting QC Officer counts
number of organisms not
found in sorted grids
All samples
Sorter achieves PSE
>90% in 5 consecutive
samples. Sorter is now
considered
"experienced"
Sorting QC Officer checks
all samples until
acceptance criteria met
Sorting QC Officer counts
number of organisms not
found in sorted grids for
experienced sorters
1 in 10 samples
completed per sorter
Sorter achieves PSE
>90%
If <90%, examine all
sorted grids in samples
assigned to sorter since
last achieving proficiency
(i.e., PSE>90%). Sorter
loses "experienced"
status and must again
show proficiency by
achieving PSE >90% in 5
consecutive samples. If
the sorter shows marked
improvement in their
sorting efficiency prior to
completion of the next
five samples, the Sorting
QC Officer may, at his/her
discretion, consider this
individual to be
"experienced" and check
only 1 in the next 10
samples.
External QC Coordinator
evaluates grid and quarter
data to determine if the
sample was well mixed as
demonstrated by
consistency in counts
between grids (or quarters)
All grids and quarters
within each sample
Sorter demonstrates
relative consistency for
90% of assigned
samples
If <90%, evaluate
whether: 1) the sorter's
consistency is similar to
other sorters; or 2) few
samples were assigned
the sorter. If neither
explanation applies, EPA's
External QC Coordinator
contacts the laboratory to
discuss possible corrective
action (e.g., resorting of
sorter's samples).
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IDENTIFICATION
Duplicate identification by
Internal Taxonomy QC
Officer
1 in 10 samples per
taxonomist
PTD <15%
If PTD >15%, re-identify
all samples completed by
that taxonomist since last
meeting the acceptance
criteria, focusing on taxa
of concern.
Independent identification
by outside, expert,
taxonomist
All uncertain taxa
Uncertain
identifications to be
confirmed by expert in
particular taxa
Record both tentative and
independent IDs.
External QC
10% of all samples
completed per
laboratory
PDE <5%
PTD < 15%
If PDE > 5%, implement
recommended
corrective actions.
If PTD > 15%,
implement
recommended
corrective actions.
Use of widely/commonly
accepted taxonomic
references by all NRSA labs
For all identifications
All keys and references
used by each lab must
be on bibliography
prepared by one or
more additional NRSA
labs or in WQX (see
Section 4.4.1 for
retrieval instructions).
This requirement
demonstrates the
general acceptance of
the references by the
scientific community
If a lab proposes to use
other references, the lab
must obtain prior
permission from Project
QA Officer before
submitting the data with
the identifications based
upon the references.
Prepare reference
collection
Each new taxon per
laboratory
Complete reference
collection to be
maintained by each
individual laboratory
Internal Taxonomy QC
Officer periodically
reviews data and
reference collection to
ensure reference
collection is complete and
identifications are
accurate.
DATA VALIDATION
Taxonomic "reasonable-
ness" checks
All data sheets
Taxa known to occur
in given rivers or
streams or geographic
area
Second or third
identification by expert
in that taxon.
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6.4.7 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by
the training and experience of project staff and documentation of sampling activities. Field crews enter
a flag code and provide comments on the Sample Collection Form if there are any problems in collecting
the sample or if conditions occur that may affect sample integrity. Specific quality control measures for
field operations are listed in Table 6.14.
Table 6.14 Sample collection and field processing quality control: benthic macroinvertebrates
Quality Control Activity
Description and Requirements
Corrective Action
Check integrity of
sample containers and
labels
Clean, intact containers and labels
Obtain replacement
supplies
Sample Collection
Keep the individual benthic macroinvertebrate subsamples wet
while in the sieve bucket as each subsequent subsample is
collected
Discard and recollect
sample if sample is not
preserved
Sample Collection
Carry a small amount of ethanol to immediately preserve larger
predaceous invertebrates to reduce the chance that other
specimens will be consumed or damaged
Qualify samples
Sample Processing
(field)
Preserve with 95% ethanol. Fill jarsl/3 full of material to reduce
the chance of organisms being damaged
Qualify sample. If
sample is deteriorated,
discard sample and
recollect
Sample Storage (field)
Store benthic samples in a cool, dark place until shipment to
analytical lab
Discard and recollect
sample
Holding time
Preserved samples can be stored indefinitely; periodically check
jars and change the ethanol if sample material appears to be
degrading
Qualify samples
6.5 Fish Assemblage
6.5.1	Introduction
Monitoring of the fish assemblage is an integral component of many water quality management
programs. The assessment will measure specific attributes of the overall structure and function of the
ichthyofaunal community to evaluate biological integrity and water quality.
6.5.2	Sampling Design and Methods
Detailed sample collection and handling procedures are described in the FOMs.
Analysis: Community identification samples are preserved, processed, enumerated, and organisms
identified to the lowest possible taxonomic level (generally genus) using specified standard keys and
references. Detailed procedures are contained in the LOM.
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6.5.3 Quality Assurance Objectives
MQOs are given in Table 6.15. General requirements for comparability and representativeness are
addressed in Section 2. Precision is calculated as percent efficiency, estimated from independent
identifications of organisms in randomly selected samples. The MQO for accuracy is evaluated by having
individual specimens representative of selected taxa identified by recognized experts.
Table 6.15 Measurement data quality objectives: fish community
Variable or Measurement
Precision
Accuracy
Completeness
Identification
15%
15%
99%
6.5.4 Pertinent QA/QC Procedures
¦	The EPA Project QA Officer will randomly select 10% of the samples for QA analysis. The EPA
Project QA Officer will then have the field crews voucher samples in the field and send them
to a QC taxonomist (another experienced taxonomist who did not participate in the original
identifications). The field crew and laboratory will complete a chain-of-custody form and
send with the samples.
¦	The QC taxonomist will perform whole-sample re-identifications, taking care to ensure
inclusion of all samples and completing fish voucher Taxonomic Bench Sheet for each
sample. As each bench sheet is completed, email it to the Project Lead.
¦	The EPA Project QA officer will compare the taxonomic results (counts AND identifications)
generated by the field crews and QC taxonomists for each sample and calculate percent
difference in enumeration (PDE) and percent taxonomic disagreement (PTD) as measures of
taxonomic precision (Stribling et al. 2003) as follows:
Equation 6.5 Percent difference in enumeration (PDE).
In, -n\
PDE=*—	— xlOO
+no
Where: nl is the number of specimens counted in a sample by the field taxonomist
and nl is the number of specimens counted by the QC taxonomist.
Equation 6.6 Percent taxonomic disagreement (PTD).
PTD =
1-
comPPos
N
100
Where: comppos is the number of agreements (positive comparisons) and N is the
total number of specimens in the larger of the two counts.
The recommendation for PDE is 5% or less.
A PTD of 15% or less is recommended for taxonomic difference (overall mean < 15% is
acceptable). Individual samples exceeding 15% are examined for taxonomic areas of
substantial disagreement, and the reasons for disagreement investigated. A reconciliation
call between the primary and secondary taxonomist will facilitate this discussion. Results
greater than this value are investigated and logged for indication of error patterns or trends.
Corrective actions include determining problem areas (taxa) and consistent disagreements
and addressing problems through taxonomist interactions. These actions help to rectify
disagreements resulting from identification to a specific taxonomic level.
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6.5.5	Taxonomic QC Review & Reconciliation
The EPA Project QA Officer prepares a report or technical memorandum to quantify aspects of
taxonomic precision, assess data acceptability, highlight taxonomic problem areas, and provide
recommendations for improving precision. This report is submitted to the HQ Project Management
Team, with copies sent to the field and QC taxonomists. Another copy is maintained in the project file.
Significant differences may result in the re-identification of samples by the primary taxonomist and a
second QC check by the secondary taxonomist.
Each laboratory prepares reference/ voucher samples. These samples will be identified and digitally
referenced (a photograph with taxonomic information superimposed on the photograph and in the file
name) and will be included in an electronic file folder on the NARS Sharefile. All samples are stored at
the laboratory until the Project Lead notifies the lab regarding disposition.
6.5.6	Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities.
An experienced fish taxonomist will identify the collected fish specimens in the field. All specimens must
be identified by common name as listed in Appendix D of the FOMs. The biologist may choose to retain
certain specimens for identification or verification in the laboratory. These samples are retained at the
discretion of the fish taxonomist and are separate from the official voucher specimens that must be
collected at 10% of each field crews' sites to be re-identified by an independent taxonomist.
A summary of field quality control procedures for the fish community indicator is presented in Table
6.16.
Table 6.16 Sample collection and field processing quality control: fish community
Quality Control Activity Description and Requirements	Corrective Action
Check integrity of
sample containers and
labels
Clean, intact containers and labels
Obtain replacement supplies
Set up electrofishing
equipment
An experienced fisheries biologist sets up the
unit. Determine if appropriate fish capture
results are achieved.
If results are poor, adjustments are
made to the pulse width and voltage
to sample effectively and minimize
injury/mortality.
Determine if electroshocker is
functioning properly; if not use
backup (e.g. generator).
Comparable effort
Reset unit clock to document button time (700
seconds per transect).
If button time is not metered,
estimate it with a stop watch and
flag the data.
Comparable effort
No more than 1 person is netting at any one
time.
Limit number of crew members with
nets.
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Quality Control Activity Description and Requirements	Corrective Action
Field Processing
Fish should be released in a location that
prevents the likelihood of their recapture.
Flag data if fish were released in area
where recapture was possible
Field Processing
The fisheries biologist will identify specimens in
the field using a standardized list of common
names.
Indicator lead will contact crews to
resolve discrepancies in names.
Sample Collection
The biologist may retain uncertain specimens for
ID or verification in the laboratory. These
samples are retained at the discretion of the
biologist and are separate from the official
voucher specimens that must be collected at
10% of each field crews' sites to be re-identified
by an independent taxonomist.
Flag data. If crew does not collect
voucher at specified site, NRSA QA
Officer will identify additional QA
sites for collection.
Sample Collection -
Taxonomic QC samples
EPA selected sites designated for independent,
taxonomic confirmation of fish assemblage
taxonomy. A minimum of 1 complete voucher is
required for each field taxonomist and will
consist of either preserved specimen(s) or digital
images representative of all species in the
sample, even common species.
If crew does not collect voucher at
specified site, EPA Project QA Officer
will identify additional QA sites for
collection.
Sample Preservation
Fish retained for laboratory ID or vouchers are
preserved with 10% buffered formalin. All
personnel must read and should follow the
appropriate guidelines for handling formalin in
the field. An MSDS can be found at the following
website.
(http:/Vwww.osha.gov/pls/oshaweb/owadisp.sh
If vouchers are not adequately
preserved, new vouchers must be
collected at the next field site.
ow document?p id=10076&p table=standards)

6.5.6.1 Voucher Specimens
Approximately 10% of each field crews' sites will be randomly pre-selected for re-identification by an
independent QA/QC taxonomist. These samples will be selected in coordination from the EPA Project
QA Officer. A minimum of one complete voucher is required for each person performing field taxonomy
and will consist of either preserved specimen(s) or digital images representative of all species in the
sample, even common species. Multiple specimens per species can be used as vouchers, if necessary
(i.e., to document different life or growth stages, or sexes). Note that a complete sample voucher does
not mean that all individuals of each species will be vouchered, only enough so that independent
verification can be achieved.
For species that are retained, specimen containers should be labeled with the sample number, site ID
number, site name, and collection date. There should be no taxonomic identification labels in or on the
container.	i/i
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Digital images should be taken as voucher documentation for species that are recognized as Rare.	h
Threatened, or Endangered (RTE) they should not be harmed or killed. Very common and well-known, or y
very large-bodied species may also be recorded by digital images; however, these can be preserved at	§
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the discretion of the taxonomist. Labeling, within the image, should be similar to that used for preserved
samples and not include taxonomic identification. Guidance for naming photo files is provided below in
the photovouchering section.
6.5.6.2 Photovouchering
Digital imagery should be used for fish species that cannot be retained as preserved specimens (e.g., RTE
species; very large bodied; or very common). Views appropriate and necessary for an independent
taxonomist to accurately identify the specimen should be the primary goal of the photography.
Additional detail for these guidelines is provided in Stauffer et al. (2001). The Field Logistics Coordinator
will distribute this document to all field crews electronically via the sharefile site. The recommended
specifications for digital images to be used for photovouchering include: 16-bit color at a minimum
resolution of 1024x768 pixels; macro lens capability allowing for images to be recorded at a distance of
less than 4 cm; and built-in or external flash for use in low-light conditions. Specimens should occupy as
much of the field of view as possible, and the use of a fish board is recommended to provide a reference
to scale (i.e., ruler or some calibrated device) and an adequate background color for photographs.
Information on Station ID, Site Name, Date and a unique species ID (i.e., A, B, C, etc.) should also be
captured in the photograph, so that photos can be identified if file names become corrupted. All
photovouchered species should have at least a full-body photo (preferably of the left side of the fish)
and other zoom images as necessary for individual species, such as lateral line, ocular/oral orientation,
fin rays, gill arches, or others. It may also be necessary to photograph males, females, or juveniles.
Images should be saved in medium- to high-quality jpeg format, with the resulting file name of each
picture noted on the Fish Collection Form. It is important that time and date stamps are accurate as this
information can also be useful in tracking the origin of photographs. It is recommended that images
stored in the camera be transferred to a PC or storage device at the first available opportunity. At this
time, the original file should be renamed to follow the logic presented below:
NRSAF01_CTSS003_20130326.jpg
Where: F=fish, 01=tag number, CTSS003=state (Connecticut) and site number, and 20130326=date
(yyyymmdd).
Field crews should maintain files for the duration of the sampling season. Notification regarding the
transfer of all images to the existing database will be provided at the conclusion of the sampling.
6.5.7 Quality Control Procedures: Laboratory Operations (Voucher Specimens)
6.5.7.1 Sample Receipt and Processing
QC activities associated with sample receipt and processing are presented in Table 6.17. The
communications center and information management staff is notified of sample receipt and any
associated problems as soon as possible after samples are received.
Table 6.17 Sample receipt and processing quality control: fish community
Quality Control
Activity
Description and Requirements
Corrective Action
Sample Log-in
Upon receipt of a sample shipment, laboratory
personnel check the condition and identification of
each sample against the sample tracking record.
Discrepancies, damaged, or missing
samples are reported to the IM
staff and indicator lead
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Sample Storage
Samples Stored in formalin in dark room or
photovouchers kept on external hard drive
Qualify sample as suspect for all
analyses
Holding time
Not Applicable
Qualify samples
Preservation
Vouchers are stored on formalin
Qualify samples
6.5.7.2 Analysis of Samples
Specific quality control measures for laboratory operations are listed in Table 6.18 and
Table 6.19.
Table 6.18 Laboratory quality control: fish voucher taxonomic identification
Check or Sample
Frequency
Acceptance Criteria Corrective Action
Description


Use widely/commonly
accepted taxonomic
references
All identifications
All keys and
references used
must be on
bibliography
prepared by the field
and QC taxonomists
For all field crew
identifications, EPA will
convert field crew's
use of common names
to taxonomic
references
Independent identification
by outside, expert,
laboratory fish taxonomist
("QC taxonomist")
When field taxonomist
cannot identify
specimen
Identification by QC
taxonomist (who
must be a different
individual than the
field taxonomist)
Replace field crew's
"unknown"
identification with
determination by QC
taxonomist
External QC
Approximately 10% of
all sites sampled by
each field taxonomist
PTD < 15%
If PTD > 15%, review
data for possible
explanations;
otherwise, insert data
qualifier for field crew
identifications
Calculate average PTD for
field taxonomist
Each sample submitted
to the QC taxonomist
PTD < 15%
If PTD > 15%, consult
with NARS QA Officer
for appropriate action.
Conduct assistance visit
EPA may choose to
visit any laboratory
Visit conducted
using checklist
Performance and any
recommended
improvements
described in debrief
with laboratory staff
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Table 6.19 Data validation: fish voucher taxonomic identification
Check or
Frequency
Acceptance
Corrective
Sample

Criteria
Action
Description



Data
All data
Genera
Data qualifiers
Validation:
sheets
known to
on data that
Taxonomic

occur in given
fail
"reasonable-

rivers/streams
reasonableness
ness" checks

or geographic
check. No


area
further



corrective



action steps.
6.6 Physical Habitat Quality
6.6.1	Introduction
Naturally occurring differences in physical habitat structure and associated hydraulic characteristics
among surface waters contributes too 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.
For the NRSA, indicators derived from data collected on physical habitat quality will be used to help
explain or characterize stream and river conditions relative to biological response and trophic state
indicators. Specific groups of physical habitat attributes important in stream and river 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 multi-metric approaches, to classify streams and rivers and to monitor biologically relevant changes
in habitat quality and intensity of disturbance.
6.6.2	Sampling Design and Methods
As the physical habitat indicator is based on field measurements and observations, there is no sample
collection associated with this indicator. At NRSA 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 and river 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.
i/i
Field measurements, observations, and associated methodology for the protocol are summarized in	o
Table 6.20. Detailed procedures for completing the protocols are provided in the FOM.	<
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There are no sample collections or laboratory analyses associated with the physical habitat
measurements.
Table 6.20 Field measurement methods: physical habitat
Variable or
Measurement Units	Summary of Method	References
THALWEG PROFILE

Thalweg depth
cm
Measure max depth at 100-150 points for wadeable or 200
points for non-wadeable along reach with surveyor's rodor
sonar equipment
US EPA
http://www.epa.g
ov/emap/
Wetted width
0.1m
Measure wetted width with range finder or measuring
tape on perpendicular line to mid-channel line
US EPA
http://www.epa.g
ov/emap/
Habitat class
none
Visually estimate channel habitat using defined class
descriptions
Frissell et al, 1986
WOODY DEBRIS TALLY

Large woody
debris
# of pieces
Use pole drag and 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
%/ degrees
Backsight between cross-section stations using clinometer,
rangefinder, compass, surveyor's level & tripod
Robison &
Kaufmann, in
prep.; Stack, 1989
Substrate size
mm
At 5 points on cross section, estimate size of one selected
particle using defined class descriptions
Wolman, 1954;
Bain et al, 1985;
Plafkin et al, 1989
Bank angle
degrees
Use clinometer and surveyors rod to measure angle
Platts et al, 1983
Bank incision
0.1m
Visually estimate height from water surface to first terrace
of floodplain
US EPA
http://www.epa.g
ov/emap/
Bank undercut
cm
Measure horizontal distance of undercut
US EPA
http://www.epa.g
ov/emap/
Bankfull width
0.1m
Measure width at top of bankfull height
US EPA
http://www.epa.g
ov/emap/
Bankfull height
0.1m
Measure height from water surface to estimated water
surface during bankfull flow
US EPA
http://www.epa.g
ov/emap/
Canopy cover
points of
inter-
section
Count points of intersection on densiometer at specific
points and directions on cross-section
Lemmon, 1957;
Mulvey et al,
1992
Riparian
vegetation
structure
percent
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
US EPA
http://www.epa.g
ov/emap/
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Variable or
Measurement
Units
Summary of Method
References
Fish cover, algae,
macrophytes
percent
Visually estimate in-channel features 5 m on either side of
cross section
US EPA
http://www.epa.g
ov/emap/
Human influence
none
Estimate presence/absence of defined types of
anthropogenic features
US EPA
http://www.epa.g
ov/emap/
STREAM DISCHARGE

Discharge
m/s or
L/min.
Velocity-Area method, Portable Weir method, timed
bucket discharge method
Linsley et al, 1982
6.6.3 Quality Assurance Objectives
Measurement data quality objectives (measurement DQOs or MQOs) are given in Table 6.21. General
requirements for comparability and representativeness are addressed in Section 2. The MQOs given in
Table 6.21 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., NRSA sites,
revisit sites, state comparability sites). 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.
Table 6.21 Measurement data quality objectives: physical habitat
Variable or Measurement
Precision
Accuracy
Completeness
Field Measurements and Observations
±10%
NA
90%
Map-Based Measurements
±10%
NA
100%
NA = not applicable
6.6.4 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Specific quality control
measures are listed in Table 6.22 for field measurements and observations.
Table 6.22 Field quality control: physical habitat
Check Description
Frequency
Acceptance Criteria
Corrective Actions
Check totals for cover class
Each
Sum must be reasonable (best
Repeat observations
categories (vegetation type, fish
transect
professional judgment)

cover)



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Check completeness of thalweg
Each site
Depth measurements for all
Obtain best estimate of
depth measurements

sampling points
depth where actual



measurement not



possible
6.7 Fecal Indicator: Enterococci
6.7.1	Introduction
The primary function of collecting water samples for Pathogen Indicator Testing is to provide a relative
comparison of fecal pollution indicators for national rivers and streams. The concentration of
Enterococci (the current bacterial indicator for fresh and marine waters) in a water body correlates with
the level of more infectious gastrointestinal pathogens present in the water body. While some
Enterococci are opportunistic pathogens among immuno-compromised human individuals, the presence
of Enterococci is more importantly an indicator of the presence of more pathogenic microbes (bacteria,
viruses and protozoa) associated with human or animal fecal waste.
6.7.2	Sampling Design and Methods
Detailed sample collection and handling procedures are described in the FOMs.
6.7.3	Pertinent QA/QC Procedures
6.7.3.1 Quality Assurance Objectives
Measurement quality objectives (MQO) are given in Table 6.23. General requirements for comparability
and representativeness are addressed in Section 2.
Table 6.23 Measurement data quality objectives: pathogen-indicator DNA sequences
Variable or Measurement16	Method Precision Method Accuracy Completeness
SPC & ENT DNA sequence numbers of
Calibrators & Standards by AQM
RSD=50%
50%
95%
ENT CCEs by dCt RQM
RSD = 70%
35%
95%
ENT CCEs by ddCt RQM
RSD = 70%
50%
95%
6.7.3.2 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Specific quality control
measures are listed in Table 6.24 for field measurements and observations.
Table 6.24 Sample collection and field processing quality control: fecal indicator
		i/i
QC
O
16 AQM = Absolute Quantitation Method; dCt=delta (change) of control treated; RQM = Relative Quantitation	^
Method; SPC = Sample Processing Control (Salmon DNA/Sketa) (note - Sketa is a reagent); CCEs = Calibrator Cell	^
Equivalents; RSD= Relative Standard Distribution; ENT=Enterococci	2
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Quality Control Activity
Description and Requirements
Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement
supplies
Sterility of sample
containers
Sample collection bottle and filtering apparatus are sterile
and must be unopened prior to sampling. Nitrile gloves
must be worn during sampling and filtering
Discard sample and
recollect in the field
Sample Collection
Collect sample at the last transect to minimize holding time
before filtering and freezing
Discard sample and
recollect in the field
Sample holding
Sample is held in a cooler on wet ice until filtering
Discard sample and
recollect in the field
Field Processing
Sample is filtered and filters are frozen on dry ice within six
hours of collection
Discard sample and
recollect in the field
Field Blanks
Field blanks must be filtered at 10% of sites
Review blank data and
flag sample data
6.7.3.3 Quality Control Procedures: Laboratory Operations
Specific quality control measures for laboratory operations are listed in Table 6.25.
Table 6.25 Laboratory quality control: pathogen-indicator DNA sequences
Check or Sample Frequency	Acceptance Criteria	Corrective Action
Description
SAMPLE PROCESSING
Re-process sub-
samples
(Lab Duplicates)
10% of all
samples
completed per
laboratory
Percent Congruence <70%
RSD
If >70%, re-process additional sub-
samples
qPCR ANALYSIS
Duplicate analysis
by different
biologist within lab
10% of all
samples
completed per
laboratory
Percent Congruence <70%
RSD
If >70%, determine reason and if
cause is systemic, re-analyze all
samples in question
Use single stock of
E. faecalis calibrator
For all qPCR
calibrator
samples for
quantitation
All calibrator sample Cp (Ct)
must have an RSD < 50%.
If calibrator Cp (Ct) values exceed an
RSD value of 50% a batch's
calibrator samples shall be re-
analyzed and replaced with new
calibrators to be processed and
analyzed if RSD not back within
range
DATA PROCESSING & REVIEW
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Check or Sample
Description
Frequency
Acceptance Criteria Corrective Action
100% verification
All qPCR
All final data will be checked
Second tier review by contractor
and review of qPCR
amplification
against raw data, exported
and third tier review by EPA
data
traces, raw and
data, and calculated data


processed data
printouts before entry into


sheets
LIMS and upload to Corvallis,



OR database

6.7.4 Data Management, Review, and Validation
Checks made of the data in the process of review, verification, and validations are summarized in Table
6.26. 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 NRSA Project
Coordinator. Once data have passed all acceptance requirements, data is submitted to NARS IM and
coordinated with the NRSA data Information Coordinator.
Table 6.26 Data validation quality control: fecal indicator
Check Description
Frequency
Acceptance Criteria
Corrective Action
Duplicate sampling
Duplicate composite
samples collected at
10% of sites
Measurements should be
within 10 percent
Review data for reasonableness;
determine if acceptance criteria
need to be modified
Field filter blanks
Field blanks filtered at
10% of sites
Measurements should be
within 10 percent
Review data for reasonableness;
determine if acceptance criteria
need to be modified
6.8 Whole Fish Tissue Samples for Fillet Analysis
6.8.1	Introduction
Fish are time-integrating indicators of persistent pollutants, and contaminant bioaccumulation in fish
tissue has important human and ecological health implications. The NRSA fish tissue fillet collection will
provide information on the national distribution of selected chemical residues (mercury and PFCs) in
predator fish species from select 5th order and larger streams and rivers of the conterminous United
States.
The fish tissue indicator procedures are based on EPA's National Study of Chemical Residues in Lake Fish
Tissue (USEPA 2000a) and EPA's Guidance for Assessing Chemical Contaminant Data for Use in Fish
Advisories, Volume 1 (Third Edition) (USEPA 2000b).
6.8.2	Sampling Design and Methods
The NRSA crews will collect fish for the tissue indicator from approximately 450 5th order and larger
NRSA sites. Fish tissue samples must consist of a composite of fish (i.e., five individuals of one predator
species that will collectively provide greater than 500 grams of fillet tissue) from each site. Tissue
sampling may require additional effort (temporally and/or spatially) beyond that of the fish community
structure sampling.
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Field crews will consist of one experienced fisheries biologist and one field technician. The experienced
on-site fisheries biologist will select the most appropriate electrofishing gear type(s) for a particular site.
The appropriate sampling equipment will be based on the size/depth of each site, and deployment will
target recommended predator species (Table 6.27). Accurate taxonomic identification is essential to
prevent mixing of species within composites. Five fish will be collected per composite at each site, all of
which must be large enough to provide sufficient tissue for analysis (i.e., 500 grams of fillets,
collectively). Fish in each composite must all be of the same species, satisfy legal requirements of
harvestable size (or be of consumable size if there are no harvest limits), and be of similar size so that
the smallest individual in the composite is no less than 75% of the total length of the largest individual. If
the recommended target species are unavailable, the on-site fisheries biologist will select an alternative
species (i.e., a predator species that is commonly consumed in the study area, with specimens of
harvestable or consumable size, and in sufficient numbers to yield a composite)
Table 6.27 Recommended target species: whole fish tissue collection

Family name
Common name
Scientific name
Length Guideline
(Estimated
Minimum)


Spotted bass
Micropterus punctulatus
~280 mm


Largemouth bass
Micropterus salmoides
~280 mm

Centrarchidae
Smallmouth bass
Micropterus dolomieu
~300 mm


Black crappie
Pomoxis nigromaculatus
~330 mm


White crappie
Pomoxis annularis
~330 mm


Channel catfish
Ictalurus punctatus
~300 mm

Ictaluridae
Blue catfish
Ictalurus furcatus
~300 mm
a.
to
a!

Flathead catfish
Pylodictis olivaris
~300 mm
£?
ro
l-

Sauger
Sander canadensis
~380 mm

Percidae
Walleye
Sander vitreus
~380 mm


Yellow perch
Perca flavescens
~330 mm

Moronidae
White bass
Morone chrysops
~330 mm

Esocidae
Northern pike
Esox lucius
~430 mm

Chain pickerel
Esox niger
~430 mm


Brown trout
Salmo trutta
~300 mm

Salmonidae
Cutthroat trout
Oncorhynchus clarkii
~300 mm

Rainbow trout
Oncorhynchus mykiss
~300 mm


Brook trout
Salvelin us fon tinalis
~330 mm
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6.8.2.1 Sampling and Analytical Methodologies
Detailed methods and handling for samples are found in the NRSA 2013-14 FOM.
6.8.3 Pertinent QA/QC Procedures
6.8.3.1 Quality Assurance Objectives
General requirements for comparability and representativeness are addressed in Section 2. The
relevant quality objectives for fish tissue fillet sample collection activities are primarily related to sample
handling issues. Types of field sampling data needed for the fish tissue indicator are listed in Table 6.28.
Methods and procedures described in this QAPP and the FOMs are intended to reduce the magnitude of
the sources of uncertainty (and their frequency of occurrence) by applying:
¦	standardized sample collection and handling procedures, and
¦	use of trained scientists to perform the sample collection and handling activities.
Table 6.28 Field data types: whole fish tissue samples for fillet analysis
Variable or Measurement Measurement Endpoint or Unit
Fish specimen
Species-level taxonomic identification
Fish length
Millimeters (mm), total length
Composite classification
Sample identification number
Specimen count classification
Specimen number
6.8.3.2 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Specific quality control
measures are listed in Table 6.29 for field measurements and observations.
Table 6.29 Field quality control: whole fish tissue samples for fillet analysis
Quality Control Activity Description and Requirements	Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement
supplies
Set up electrofishing
equipment
An experienced fisheries biologist sets up the unit. If
results are poor, adjustments are made to the pulse
width and voltage to sample effectively and minimize
injury/mortality
Adjust voltage in field
Field Processing
The fisheries biologist will identify specimens in the
field using a standardized list of common names (App.
D of the FOMs)
Labs verify. If not same
species, sample not
composited
Sample Collection
The biologist will retain five specimens of the same
species to form the composite sample
Labs verify. If not same
species, sample not
composited
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Quality Control Activity
Description and Requirements
Corrective Action
Sample Collection
The length of the smallest fish must be at least 75% of
If fish out of length range

the length of the longest fish
requirement, EPA


contacted for instructions
6.8.4 Data Management, Review, and Validation
Checks made of the data in the process of review, verification, and validation is summarized in Table
6.30. For the whole fish tissue fillet data, 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 NRSA
Lead. Once data have passed all acceptance requirements, data submitted to EPA Coordinator.
Table 6.30 Data validation quality control: whole fish tissue samples for fillet analysis
Check Description Frequency	Acceptance Criteria	Corrective Action
Composite validity
check
All composites
Each routine composite
sample must have five fish
of the same species
For non-routine composite samples, EPA
indicator lead contacted for instructions
before processing begins
75% rule
All composites
Length of smallest fish in
the composite must be at
least 75% of the length of
the longest fish.
For non-routine composite samples, EPA
indicator lead contacted for instructions
before processing begins
6.9 Fish Tissue Plugs
6.9.1 Introduction
Fish are time-integrating indicators of persistent pollutants, and contaminant bioaccumulation in fish
tissue has important human and ecological health implications. The NRSA fish tissue plug will provide
information on the national distribution of mercury in fish species from all streams and rivers of the
conterminous United States.
6.9.2 Sampling Design and Methods
The NRSA crews will collect fish for the fish tissue plug from all NRSA sites where target fish are
collected. The fish tissue plug indicator samples will be collected using the same gear and procedures
used to collect the fish assemblage. Collection of individual specimens for fish tissue occurs in the
sample reach during the fish assemblage sampling. Samples should be taken from the species listed in
the target list found in Table 6.31. If the target species are unavailable, the fisheries biologist will select
an alternative species (i.e., a species that is commonly consumed in the study area, with specimens of
harvestable or consumable size) to obtain a sample from the species that are available. Recommended
and alternate target species are given in Table 6.31.	g
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Table 6.31 Recommended target and alternate species: fish tissue plug collection

Family name
Common name
Scientific name
Length Guideline
(Estimated
Minimum)


Spotted bass
Micropterus punctulatus
~280 mm


Largemouth bass
Micropterus salmoides
~280 mm

Centrarchidae
Smallmouth bass
Micropterus dolomieu
~300 mm


Black crappie
Pomoxis nigromaculatus
~330 mm


White crappie
Pomoxis annularis
~330 mm


Channel catfish
Ictalurus punctatus
~300 mm

Ictaluridae
Blue catfish
Ictalurus furcatus
~300 mm


Flathead catfish
Pylodictis olivaris
~300 mm


Sauger
Sander canadensis
~380 mm

Percidae
Walleye
Sander vitreus
~380 mm


Yellow perch
Perca flavescens
~330 mm

Moronidae
White bass
Morone chrysops
~330 mm

Esocidae
Northern pike
Esox lucius
~430 mm

Chain pickerel
Esox niger
~430 mm


Brown trout
Salmo trutta
~300 mm
0J
"
Salmonidae
Cutthroat trout
Oncorhynchus clarkii
~300 mm
a.
to
a!
Rainbow trout
Oncorhynchus mykiss
~300 mm
£?
ro
l-

Brook trout
Salvelin us fontinalis
~330 mm

Cyprinidae
Northern pikeminnow
Ptychocheilus oregonensis
~300 mm


Bluegill
Lepomis macrochirus
~200 mm
£
B
£
Centrarchidae
Rock bass
Ambloplites rupestris
~200 mm
5

Redbreast sunfish
Lepomis auritus
~200 mm
6.9.2.1 Sampling and Analytical Methodologies for Field Operations and Laboratory Analyses
Detailed methods and handling for samples are found in the FOM. The laboratory method for fish tissue
is performance based. Example standard operating procedures are provided in Appendix F of the LOM.
6.9.3 Pertinent QA/QC Procedures
6.9.3.1 Quality Assurance Objectives
The relevant quality objectives for fish tissue plug sample collection activities are primarily related to
sample handling issues. Types of field sampling data needed for the fish tissue plugs are listed in Table
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6.32. Methods and procedures described in this QAPP and the FOMs are intended to reduce the
magnitude of the sources of uncertainty (and their frequency of occurrence) by applying:
¦	standardized sample collection and handling procedures, and
¦	use of trained scientists to perform the sample collection and handling activities.
Table 6.32 Field data types: fish tissue plug
Variable or Measurement
Measurement Endpoint or Unit
Fish specimen
Species-level taxonomic identification
Fish length
Millimeters (mm), total length
Fish weight
Grams (g)
6.9.3.2 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOMs. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Specific quality control
measures are listed in Table 6.33 for field measurements and observations.
Table 6.33 Field quality control: fish tissue plug
Quality Control Activity Description and Requirements	Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement supplies
Set up electrofishing
equipment
An experienced fisheries biologist sets up the
unit. If results are poor, adjustments are made to
the pulse width and voltage to sample effectively
and minimize injury/mortality
Adjust voltage in field
Field Processing
The fisheries biologist will identify specimens in
the field using a standardized list of common
names (App. D of the FOMs)
Labs verify. If not same species,
sample not composited
Sample Collection
The fisheries biologist will retain 2 specimens of
the same species to form the composite sample
If not the same species, sample
not composited
Sample Collection
The length of the smallest fish must be at least
75% of the length of the longest fish
If fish out of length range
requirement, EPA contacted for
instructions
6.9.4 Data Management, Review, and Validation
Checks made of the data in the process of review, verification, and validation is summarized in Table
6.34. 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	q
standardized forms and logbooks) are retained in an organized fashion for seven years or until written	<
authorization for disposition has been received from the NRSA Project Coordinator. Once data have	^
passed all acceptance requirements, data submitted to EPA Coordinator.	?
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Table 6.34 Data validation quality control: fish tissue plug
Check Description
Frequency
Acceptance Criteria
Corrective Action
75% rule
All composites
Length of smallest fish in the
Indicator lead will review


composite must be at least 75% of
composite data and advise the lab


the length of the longest fish
before processing begins
6.9.5 Quality Control Procedures: Laboratory Operations
Table 6.35 Measurement data quality objectives: fish tissue plug
Variable or Measurement
MDL
Quantitation Limit
Mercury
0.47 ng/g
5.0 ng/g
Table 6.36 Lab quality control: fish tissue plug
Activity
Evaluation/Acceptance Criteria
Corrective Action
Demonstrate competency
for analyzing fish samples
to meet the performance
measures
Demonstration of past experience with
fish tissue samples in applying the
laboratory SOP in achieving the method
detection limit
EPA will not approve any
laboratory for NRSA sample
processing if the laboratory
cannot demonstrate
competency. In other
words, EPA will select
another laboratory that can
demonstrate competency
for its NRSA samples
Check condition of sample
when it arrives.
Sample issues, such as punctures or rips
in wrapping; missing label; temperature;
adherence to holding time requirements;
sufficient volume for test. All samples
should arrive at the laboratory frozen
Assign appropriate
condition code identified in
Appendix 3
Store sample appropriately.
While stored at the
laboratory, the sample must
be kept at a maximum
temperature of -20° C.
Check the temperature of the freezer per
laboratory's standard operating procedures
Record temperature of sample
upon arrival at the laboratory.
If at any other time, samples
are warmer than required,
note temperature and
duration in comment field
Analyze sample within holding
time
The test must be completed within the
holding time (i.e., 1 year). If the original test
fails, then the retest also must be conducted
within the holding time
Perform test, but note reason
for performing test outside
holding time. EPA expects that
the laboratory will exercise
every effort to perform tests
before the holding time
expires
Maintain quality control
specifications from
selected method/SOP (that
Data meet all QC specifications in the
selected method/SOP
If data do not meet all QC
requirements, rerun sample
or qualify data. If the lab
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meets the measurement
data quality objectives)
Maintain the required MDL
Use consistent units for QC
samples and field samples
Maintain completeness
Evaluate for each sample
Verify that all units are provided in wet
weight units and consistently
Completeness objective is 95% for all
parameters
believes the data are to be
qualified without rerunning
sample, the lab must
consult with the EPA Survey
QA Lead before proceeding
If MDL could not be
achieved, then provide
dilution factor or QC code
and explanation in the
comment field
If it is not possible to
provide the results in the
same units as most other
analyses, then assign a QC
code and describe the
reason for different units in
the comments field of the
database
Contact the EPA Survey QA
Lead immediately if issues
affect laboratory's ability to
meet completeness
objective
l/l
QC
O
I—
<
u
105
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7 FIELD AND BIOLOGICAL LABORATORY QUALITY EVALUATION AND
ASSISTANCE VISITS
7.1 National Rivers and Streams Assessment Field Quality Evaluation and
Assistance Visit Plan
Evaluation and assistance visits (AV) will be conducted with each field crew early in the sampling and
data collection process, if possible, and corrective actions will be conducted in real time. These visits
provide both a quality check for the uniform evaluation of the data collection methods and an
opportunity to conduct procedural reviews, as required, minimizing data loss due to improper technique
or interpretation of field procedures and 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 visit also provides
the field crews with an opportunity to clarify procedures and offer suggestions for future improvements
based on their sampling experience preceding the visit. The field 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 field
crew collecting and contributing data under this program; hence no data will be recorded to the project
database that was produced by an 'unaudited' process or individual. The field evaluations will be based
on the evaluation plan and field evaluation checklist.
One or more designated EPA or Contractor staff members who are qualified (i.e. have completed
training) in the procedures of the NRSA 2013-14 field sampling operations will visit trained state, tribal,
contractor, and EPA field sampling crews during sampling operations on site. If membership of a field
crew changes, and at least two of the members have not been evaluated previously, the field crew must
be evaluated again during sampling operations as soon as possible to ensure that all members of the
field crew understand and can perform the procedures. If a deviation is needed from the process
described here, the staff member conducting the AV must contact the NRSA Project Lead. The NRSA
Project Lead will contact the NRSA Project QA Officer to determine an acceptable course of action.
The purpose of this on-site visit will be to identify and correct deficiencies during field sampling
operations. The process will involve preparation activities, field day activities and post field day activities
as described in the following sections. Additionally, conference calls with crews may be held
approximately every two weeks to discuss issues as they come up throughout the sampling season.
7.1.1 Preparation Activities
¦	Each Field Crew Evaluator will schedule an assistance visit with their designated crews in
consultation with the Contractor Field Logistics Coordinator, Regional NRSA Coordinator,
and respective Field Sampling Crew Leader. Ideally, each Field Crew will be evaluated within
the first two weeks of beginning sampling operations, so that procedures can be corrected
or additional training provided, if needed.
¦	Each Evaluator is responsible for providing their own field gear sufficient to accompany the
Field Sampling Crews during a complete sampling cycle. Schedule of the Field visits will be
made by the Evaluator in consultation with the respective Field Crew Leader. Evaluators
should be prepared to spend additional time in the field if needed (see below).
¦	Each Field Crew Evaluator will ensure that field crews are aware of their visit plans and all
capacity and safety equipment will be provided for the Field Crew Evaluator.
¦	Each Field Crew Evaluator will need to bring the items listed in Table 7.1.
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Table 7.1 Equipment and supplies: field evaluation and assistance visits
Type
Item
Quantity
Form
Appendix B (see FOM 2013/14)
1
Documentation
NRSA 2013-14 Field Operations Manuals
NRSA 2013-14 Quality Assurance Project Plan
Clipboard
Pencils (#2, for data forms)/Pen (or computer for electronic versions)
Field notebook (optional)
1
1
1
1
1
Gear
Field gear (e.g., protective clothing, sunscreen, insect repellent, hat, water,
food, backpack, cell phone)
As
needed
7.1.2	Field Day Activities
¦	The Field Crew Evaluator will review the Field Evaluation & Assistance Visit Checklist with
each crew during the field sampling day and establish and plan and schedule for their
evaluation activities for the day.
¦	The Field Crew Evaluator will view the performance of a field crew through one complete
set of sampling activities as detailed on the checklist.
¦	Scheduling might necessitate starting the evaluation midway on the list of tasks at a site,
instead of at the beginning. In that case, the Field Crew Evaluator will follow the crew to the
next site to complete the evaluation of the first activities on the list.
¦	If the field crew misses or incorrectly performs a procedure, the Field Crew 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 Field Crew Evaluator is to provide additional training and guidance
so that the procedures are being performed consistent with the FOM, all data are recorded
correctly, and paperwork is properly completed at the site.
¦	When the sampling operation has been completed, the Field Crew Evaluator will review the
results of the evaluation with the field crew before leaving the site (if practicable), noting
positive practices and problems (i.e., weaknesses [might affect data quality]; deficiencies
[would adversely affect data quality]). The Field Crew Evaluator will ensure that the field
crew understands the findings and will be able to perform the procedures properly in the
future.
¦	The Field Crew Evaluator will review the list and record responses or concerns from the field
crew, if any; on the checklist (this may happen throughout the field day).
¦	The Field Crew Leader will sign the checklist after this review.
7.1.3	Post Field Day Activities
¦	The Field Crew Evaluator will review the checklist that evening and provide a summary of
findings, including lessons learned and concerns.
¦	If the Field Crew Evaluator finds major deficiencies in the field crew operations (e.g., less
than two members, equipment, or performance problems) the Field Crew Evaluator must
contact the EPA NRSA 2013-14 Project Lead. The EPA NRSA 2013-14 Project Lead will
contact the EPA NRSA 2013-14 Project Officer to determine the appropriate course of
action. Data records from sampling sites previously visited by this Field Crew will be checked
to determine whether any sampling sites must be redone.
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¦	The Field Crew Evaluator will retain a copy of the checklist and submit to the EPA NRSA QA
Officer either via Fed-Ex or electronically.
¦	The EPA NRSA 2013-14 Project Lead and EPA NARS QA Project Officer or authorized
designee will review the returned Field Evaluation and Assistance Visit Checklist, note any
issues, and check off the completion of the evaluation for each field crew.
7.1.4 Summary
Table 7.2 summarizes the plan, checklist, and corrective action procedures.
Table 7.2 Summary: field evaluation and assistance visits
Field
Evaluation
Plan
Field
Evaluation
Checklist
Corrective
Action
Procedures
The Field Crew Evaluator:
•	Arranges the field evaluation visit in consultation with the QA Officer, Regional NRSA
Coordinator, and respective Field Sampling Crew Leader, ideally within the first two weeks of
sampling
•	Observes the performance of a crew through one complete set of sampling activities
•	Takes note of errors the field crew makes on the checklist and immediately point these out to
correct the mistake
•	Reviews the results of the evaluation with the field crew before leaving the site, noting positive
practices, lessons learned, and concern
The Field Crew Evaluator:
•	Observes all pre-sampling activities and verifies that equipment is properly calibrated and in
good working order, and protocols are followed
•	Checks the sample containers to verify that they are the correct type and size, and checks the
labels to be sure they are correctly and completely filled out
•	Confirms that the field crew has followed NRSA protocols for locating the river/stream X point
•	Observes the index site sampling, confirming that all protocols are followed
•	Observes the littoral sampling and habitat characterization, confirming that all protocols are
followed
•	Records responses or concerns, if any, on the Field Evaluation and Assistance Checklist
•	If the Field Crew Evaluator's findings indicate that the field crew is not performing the
procedures correctly, safely, or thoroughly, the Evaluator must continue working with this field
crew until certain of the crew's ability to conduct the sampling properly so that data quality is
not adversely affected.
•	If the Field Crew Evaluator finds major deficiencies in the cield crew operations the Evaluator
must contact the EPA NRSA 2013/2014 Project Lead.
7.2 NATIONAL RIVERS AND STREAMS ASSESSMENT LABORATORY QUALITY
EVALUATION AND ASSISTANCE VISIT PLAN
As part of the NRSA 2013-14, field samples will be collected at each assessment site. These samples will
be sent to laboratories cooperating in the assessment. To ensure quality, each Project Cooperator
laboratory analyzing samples from the NRSA 2013-14 will receive an evaluation from an NRSA Lab
Evaluator. All project cooperator laboratories will follow these guidelines.
No national program of accreditation for laboratory processing for many of our indicators currently
exists. For this reason, a rigorous program of laboratory evaluation has been developed to support the
NRSA 2013-14.
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Given the large number of laboratories participating in the NRSA 2013-14, it is not feasible to perform
an assistance visit17 (AV) on each of these laboratories. An AV would include an on-site visit to the
laboratory lasting at least a day. As a result, the EPA Headquarters Project Management Team will
conduct remote review of laboratory certifications and accreditations of all laboratories. Additionally,
EPA will include an inter-laboratory comparison between some laboratories (mainly for biological
indicators). If issues arise from the remote review or inter-laboratory comparison that cannot be
resolved remotely then the EPA Quality Team and/or contractors will perform an on-site visit to the
laboratory. This process is in keeping with EPA's Policy to Assure Competency of Laboratories, Field
Sampling, and Other Organizations Generating Environmental Measurement Data under Agency-Funded
Acquisitions.
7.2.1 Remote Evaluation/Technical Assessment
A remote evaluation procedure has been developed for performing assessment of all laboratories
participating in the NRSA 2013-14.
The NRSA QA Team will conduct laboratory evaluation prior to data analysis to ensure that the
laboratories are qualified and that techniques are implemented consistently across the multiple
laboratories generating data for the program. The EPA National Aquatic Resource Surveys team has
developed laboratory evaluation plans to ensure uniform interpretation and guidance in the procedural
reviews.
The NRSA Quality Team is using a procedure that requests the laboratory to provide documentation of
its policies and procedures. For the NRSA 2013-14 project, the Quality Team is requesting that each
participating laboratory provide the following documentation:
¦	The laboratory's Quality Manual, Quality Management Plan or similar document.
¦	Standard Operating Procedures (SOPs) for each analysis to be performed.
¦	Long term Method Detection Limits (MDLs) for each instrument used and Demonstration of
Capability for each analysis to be performed.
¦	A list of the laboratory's accreditations and certifications, if any.
¦	Results from Proficiency Tests for each analyte to be analyzed under the NRSA 2013-14
If a laboratory has clearly documented procedures for sample receiving, storage, preservation,
preparation, analysis, and data reporting; has successfully analyzed Proficiency Test samples (if required
by EPA, EPA will provide the PT samples); has a Quality Manual that thoroughly addresses laboratory
quality including standard and sample preparation, record keeping and QA non-conformance;
participates in a nationally recognized or state certification program; and has demonstrated ability to
perform the testing for which program/project the audit is intended, then the length of an on-site visit
will be minimum, if not waived entirely. The QA Team will make a final decision on the need for an
actual on-site visit after the review and evaluation of the documentation requested.
If a laboratory meets or exceeds all of the major requirements and is deficient in an area that can be
corrected remotely by the lab, suggestions will be offered and the laboratory will be given an
opportunity to correct the issue. The QA Team will then verify the correction of the deficiency remotely.
project.
19 The evaluation of the labs is being considered an Assistance Visit rather than an audit because the evaluation is
designed to provide guidance to the labs rather than as "inspection" as in a traditional audit.
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The on-site visit by EPA and/or a contractor should only be necessary if the laboratory fails to meet the
major requirements and is in need of help or fails to produce the requested documentation.
In addition, all labs must sign a Lab Signature Form (see NRSA 2013-14 LOM) indicating that they will
abide by the following:
¦	Utilize procedures identified in the NRSA 2013-14 LOM (or equivalent). If using equivalent
procedures, please provide procedures manual to demonstrate ability to meet the required
MQOs.
¦	Read and abide by the NRSA 2013-14 Quality Assurance Project Plan (QAPP) and related
Standard Operating Procedures (SOPs).
¦	Have an organized IT system in place for recording sample tracking and analysis data.
¦	Provide data using the template provided in the Lab Operations Manual.
¦	Provide data results in a timely manner. This will vary with the type of analysis and the
number of samples to be processed. Sample data must be received no later than May 1,
2014 for samples collected in 2013 and May 1, 2015 for samples collected in 2014 or as
otherwise negotiated with EPA.
¦	Participate in a lab technical assessment or audit if requested by EPA NRSA staff (this may
be a conference call or on-site audit).
If a lab is participating in biology analyses, they must, in addition, abide by the following:
¦	Use taxonomic standards outlined in the NRSA 2013-14 Lab Manual.
¦	Participate in taxonomic reconciliation exercises during the field and data analysis season,
which include conference calls and other lab reviews (see more below on Inter-laboratory
comparison).
7.2.2	Water Chemistry Laboratories
The water chemistry laboratory approval process which is outlined on in the previous paragraphs of this
section is deemed appropriate because many laboratories participate in one or more national laboratory
accreditation programs such as the National Environmental Laboratory Accreditation Program (NELAP),
International Organization for Standardization (ISO-17025) as well as various state certification
programs which include strict requirements around documentation and procedures as well as site visits
by the accrediting authority. It is built off of the process used by the NLA 2012. The laboratories
participating in NRSA 2013-14 meet these qualifications and as such have demonstrated their ability to
function independently. This process is one that has been utilized in Region 3 for many years and is
designed around the national accrediting programs listed above.
7.2.3	Inter-laboratory Comparison
The NRSA OA plan includes an inter-laboratory investigation for the laboratories performing analysis on
benthic macroinvertebrates, and periphyton data for the NRSA 2013-14. This process is defined as an
inter-laboratory comparison since the same protocols and method will be used by both laboratories as
described in this manual. The QA plan also includes an independent taxonomist (EPA Contractor) to re-
identify 10% of the samples from each laboratory. No site visit is envisioned for these laboratories
unless the data submitted and reviewed by EPA does not meet the requirements of the inter-laboratory
comparison described.
7.2.4	Assistance Visits
Assistance Visits will be used to:
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¦	Confirm the NRSA 2013-14 Laboratory Operations Manual (LOM) methods are being
properly implemented by cooperator laboratories.
¦	Assist with questions from laboratory personnel.
¦	Suggest corrections if any errors are made in implementing the lab methods.
Evaluation of the laboratories will take the form of administration of checklists which have been
developed from the LOM to ensure that laboratories are following the methods and protocols outlined
therein. The checklist will be administered on-site by a qualified EPA scientist or contractor.
See LOM for copies of the Document Request form used for both the Biological laboratories and the
Chemical laboratories.
7.2.5 NRSA 2013-14 Document Request Form Chemistry Laboratories
EPA and its state and tribal partners will conduct a survey of the nation's rivers and streams. This
National River and Streams Assessment (NRSA), is designed to provide statistically valid regional and
national estimates of the condition of rivers and streams. Consistent sampling and analytical procedures
ensure that the results can be compared across the country. As part of the NRSA 2013-14, the Quality
Assurance Team will conduct a technical assessment to verify quality control practices in your laboratory
and its ability to perform chemistry analyses under this project. Our review will assess your laboratory's
ability to receive, store, prepare, analyze, and report sample data generated under EPA's NRSA 2013-14.
The first step of this assessment process will involve the review of your laboratory's certification and/or
documentation. Subsequent actions may include (if needed): reconciliation exercises and/or a site visit.
All laboratories will need to complete the following forms:
If your lab has been previously approved within the last 5 years for the specific parameters:
¦	A signature on the attached Laboratory Signature Form indicates that your laboratory will
follow the quality assurance protocols required for chemistry laboratories conducting
analyses for the NRSA 2013-14. A signature on the QAPP and the LOM Signature Form
indicates that you will follow both the QAPP and the LOM.
If you have not been approved within the last 5 years for the specific parameters in order for us to
determine your ability to participate as a laboratory in the NRSA, we are requesting that you submit
the following documents (if available) for review:
¦	Documentation of a successful quality assurance audit from a prior National Aquatic
Resource Survey (NARS) that occurred within the last 5 years (if you need assistance with
this please contact the individual listed below).
¦	Documentation showing participation in a previous NARS for Water Chemistry for the same
parameters/methods.
Additionally, we request that all laboratories provide the following information in support of your
capabilities, (these materials are required if neither of the two items above are provided):
¦	A copy of your Laboratory's accreditations and certifications if applicable (i.e. NELAC, ISO,
state certifications, North American Benthological Society (NABS), etc.).
¦	An updated copy of your Laboratory's QAPP.
¦	Standard Operating Procedures (SOPs) for your laboratory for each analysis to be performed
(if not covered in 2013/14 NRSA LOM).
¦	Documentation attesting to experience running all analytes for the 2013/14 NRSA, including
chlorophyll a and Ash Free Dry Mass (AFDM).
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This documentation may be submitted electronically via e-mail to forde.kendra@epa.gov. Questions
concerning this request can be submitted forde.kendra@epa.gov (202-566-0417) or
tarquinio.ellen@epa.gov (202-564-2267).
7.2.6 NRSA 2013-14 Document Request Form Biology Labs
EPA and its state and tribal partners will conduct a survey of the nation's rivers and streams. This
National River and Streams Assessment (NRSA), is designed to provide statistically valid regional and
national estimates of the condition of rivers and streams. Consistent sampling and analytical procedures
ensure that the results can be compared across the country. As part of the 2013/14 NRSA, the Quality
Assurance Team will conduct a technical assessment to verify quality control practices in your laboratory
and its ability to perform biology analyses under this project. Our review will assess your laboratory's
ability to receive, store, prepare, analyze, and report sample data generated under EPA's 2013/14 NRSA.
The first step of this assessment process will involve the review of your laboratory's certification and/or
documentation. Subsequent actions may include (if needed): reconciliation exercises and/or a site visit.
All laboratories will need to complete the following forms:
¦	If your laboratory has been previously approved within the last 5 years for the specific
parameters: A signature on the attached Laboratory Signature Form indicates that your
laboratory will follow the quality assurance protocols required for biology laboratories
conducting analyses for the 2013/14 NRSA.A signature on the QAPP and the LOM Signature
Form indicates you will follow both the QAPP and the LOM.
If you have not been approved within the last 5 years for the specific parameters, in order for us to
determine your ability to participate as a laboratory in the NRSA, we are requesting that you submit
the following documents (if available) for review:
¦	Documentation of a successful quality assurance audit from a prior National Aquatic
Resource Survey (NARS) that occurred within the last 5 years (if you need assistance with
this please contact the individual listed below).
¦	Documentation showing participation in previous NARS for this particular indicator.
Additionally, we request that all laboratories provide the following information in support of your
capabilities, (these materials are required if neither of the two items above are provided):
¦	A copy of your Laboratory's accreditations and certifications if applicable (i.e. NELAC, ISO,
state certifications, NABS, etc.).
¦	Documentation of NABS (or other) certification for the taxonomists performing analyses (if
applicable).
¦	An updated copy of your Laboratory's QAPP.
¦	Standard Operating Procedures (SOPs) for your lab for each analysis to be performed (if not
covered in NRSA 2013-14 LOM).
This documentation may be submitted electronically via e-mail to forde.kendra@epa.gov. Questions
concerning this request can be submitted forde.kendra@epa.gov (202-566-0417) or
tarquinio.ellen@epa.gov (202-564-2267).
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8 DATA ANALYSIS PLAN
The Data Analysis Plan describes the general process used to evaluate the data for the survey. It outlines
the steps taken to assess the condition of the nation's rivers and streams and identify the relative
impact of stressors on this condition. Results from the analysis will be included in the final report and
used in future analyses. The data analysis plan will likely be refined and clarified as the data are analyzed
by EPA and states.
8.1 Data Interpretation Background
The basic intent of data interpretation is to evaluate the occurrence and distribution of parameters
throughout the population of rivers and streams in the conterminous United States within the context of
regionally relevant expectations for least disturbed reference conditions. This is analyzed using a
cumulative distribution function (CDF). Based on information from the cumulative distribution function,
the analysis will also categorize the condition of water for most indicators as good, fair, poor, and
unassessed (for various reasons such as samples not collected, quality assurance issues, etc.). Because of
the large-scale and multijurisdictional nature of this effort, the key issues for data interpretation are
unique and include: the scale of assessment, selecting the best indicators, defining the least impacted
reference conditions, and determining thresholds for judging condition.
8.1.1	Scale of Assessment
This will be the second national report on the ecological condition of the nation's rivers and streams
(and the third for wadeable systems) using comparable methods. EPA selected the sampling locations
for the assessment using a probability based design, and developed rules for selection to meet certain
distribution criteria, while ensuring that the design yielded a set of rivers and streams that would
provide for statistically valid conclusions about the condition of the population of rivers/streams across
the nation. A challenge that this mosaic of waterbodies poses is developing a data analysis plan that
allows EPA and other partners to interpret data and present results at a large, aggregate scale.
Additional information on data analysis procedures used for NRSA 2008-09 and proposed for NRSA
2013-14 can be found in the NRSA 2008-2009 Technical Report
(http://water.epa.gov/type/rsl/monitoring/riverssurvey/index.cfm).
8.1.2	Selecting the Best Indicators
Indicators should be applicable across all reporting units, and must be able to differentiate a range of
conditions. The Agency formed a steering committee for these discussions. Starting with the NRSA
08/09 indicators, the Committee, comprised of EPA, state and other representatives provided advice
and recommendations to the Agency on indicator selection/refinement.
EPA developed screening and evaluation criteria which included indicator applicability on a national
scale, the ability of an indicator to reflect various aspects of ecological condition, and cost-effectiveness.
8.1.3	Defining Least Impacted Reference Condition
Reference condition data are necessary to describe expectations for biological conditions under least
disturbed setting. The NRSA 2013-14 project team will use an approach similar to that used in NRSA
2008-09, which is described in detail in the NRSA 08/09 Technical Appendix
http://water.epa.gov/type/rsl/monitoring/riverssurvey/index.cfm.
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8.1.4 Determining Thresholds for Judging Condition
This reference site approach is used to set expectations and benchmarks for interpreting the data on
river/stream condition. The range of conditions found in the reference sites for an ecoregion describes a
distribution of those biological or stressor values expected for least disturbed condition. The
benchmarks used to define distinct condition classes (e.g., good, fair, poor / least disturbed,
intermediate, most disturbed) will be drawn from this reference distribution. Typically, EPA's approachis
to examine the range of values for a biological or stressor indicator in all of the reference sites in a
region, and to use the 5th percentile of the reference distribution for that indicator to separate the most
disturbed of all sites from moderately disturbed sites. (Note: depending on the indicator, data analysis
groups and indicator leads may recommend alternative percentiles which will be reviewed by EPA).
Using the 5th percentile means that rivers/streams in the most disturbed category are worse than 95% of
the best sites used to define reference condition. Similarly, the 25th percentile of the reference
distribution can be used to distinguish between moderately disturbed sites and those in least disturbed
condition. This means that rivers/streams reported as least disturbed are as good as 75% of the sites
used to define reference condition.
8.2	Geospatial Data
Geospatial data is an integral part of data analysis for the NRSA 2013-14, as it has been for all other
surveys. The following activities are anticipated: review of coordinate data and corrections, watershed
delineations, and computing landscape metrics. Through the site evaluation process, rivers/streams that
have changed or are inaccurately represented in the National Hydrography Dataset (NHD) will be noted
and provided to EPA's NHD team.
8.3	Datasets Used for the Report
The datasets available for use in the report will be developed based on the data collected during
2013/2014, data from the NRSA 08/09 report and data from the WSA report (the NRSA 08/09 and WSA
data will be used for trends/change analyses, as part of reference condition development, and for
defining taxonomic names and autecology records). Additionally, threshold values based on EPA water
quality criteria and World Health Organization values will be applied to the NRSA 2013-14 data for the
human health related indicators. Geospatial files will include river/stream coverage and watershed
delineations based on NHD+, the National Land Cover Dataset (NLCD), and Parameter-elevation
Regressions on Independent Slopes Model (PRISM).
The survey will use indicators to assess ecological integrity; extent of stressors impacting integrity; and
the recreational value of rivers/streams.
8.3.1	Ecological Integrity
Ecological integrity describes the ecological condition of rivers/streams based on different assemblages
of the aquatic community and their physical habitat. The indicators include benthic macroinvertebrates,
periphyton and fish assemblages.
8.3.2	Stressor Status/Extent
Stressor indicators describe the extent of key parameters on the condition of rivers/streams as well as
the relative risk and attributable risk associated with stressors. The indicators include nutrients, physical
habitat (the riparian and instream zones) and excess sediments among others.
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8.3.3 Recreational value
Recreational indicators address the ability of the population to support recreational uses such as
swimming, fishing and boating. The protection of these uses is one of the requirements in the Clean
Water Act under 305(b). The extent of algal toxins (microcystin), fish tissues above human health
criteria, and Enterococci will serve as the primary indicators of recreational value.
8.4 INDICATOR DATA ANALYSIS
8.4.1	Water Chemistry and Chlorophyll a
A wide array of water chemistry parameters will be measured, including DO, pH, total N, total P, ANC,
DOC, NH4, N03-N04, S04, CL, NO3, Ca, Mg, Na, K, Si02, TSS, True Color, and chlorophyll-o. Values for
these parameters and their distribution will be reported. Water chemistry analysis is critical for
interpreting the biological indicators. Chlorophyll-o, and nutrient measurements will be used to
determine the extent of these key stressors on aquatic life and to assess relative risk/attributable risk.
8.4.2	Algal Toxins: Microcystins
Cyanobacteria (blue-green algal) blooms are common midsummer to late fall events that occur in many
waters throughout the United States. Algal toxin production has been identified as a significant potential
human health problem that has been associated with many of these bloom events. However, little is
known about the general occurrence of algal toxins in the pelagic zones of these water bodies, where
extensive blooms are less likely to occur than in near-shore areas.
The data analysis team will analyze the total (whole water) concentrations of microcystins (total) in
rivers/streams throughout the United States using a standardized immunoassay test. In addition, the
data analysis team will analyze and interpret the data for microcystin occurrence and concentration in
the context of other environmental data that is collected as part of the NRSA assessment (e.g. nutrients,
chlorophyll, turbidity, specific conductance, pH).
8.4.3	Benthic Macroinvertebrate, Periphyton and Fish Assemblages
Benthic macroinvertebrate and zooplankton assemblage will be analyzed using both multi-metric indices
(MMI) (modeled for all assemblages; and potentially modeled and traditional for benthic
macroinvertebrates) and observed/expected indices (O/E) models. The MMI approach summarizes
various assemblage attributes, such as composition, tolerance to disturbance, trophic and habitat
preferences, as individual metrics or measures of the biological community. Candidate metrics are
evaluated for aspects of performance and a subset of the best performing metrics are combined into an
index known as a Macroinvertebrate Index of Biotic Condition. This index is then used to rank the
condition of the resource.
The predictive model or O/E approach estimates the expected taxonomic composition of an assemblage
in the absence of human stressors, using a set of least-disturbed sites and other variables related to
natural gradients, such as elevation, stream size, latitude and longitude. The resulting models are then
used to estimate the expected taxa composition (taxa richness) at each site sampled. The number of
expected taxa actually observed at a site is compared to the number of expected taxa as an Observed
Expected ratio or index. Departure from a ratio of one indicate that the taxonomic composition in the
sample differs from that expected under least -disturbed conditions. The greater the departure from
one, the greater the sample differs from the least disturbed condition.
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EPA scientists will develop a separate data analysis plan for research related to the periphyton meta-
genomics indicator.
8.4.4 Physical Habitat
An assessment of river and stream (fluvial) physical habitat condition is a major component of the NRSA.
The assessment focuses on streambed stability and excess fine sediments, instream habitat cover
complexity, riparian vegetation, and riparian human disturbances. These four indicators are generally
important throughout the U.S. Furthermore, the project team had reasonable confidence in factoring
out natural variability to determine expected values and the degree of anthropogenic alteration of the
habitat attributes represented by these indicators.
8.4.4.1	Relative Bed Stability and Excess Fines
Streambed characteristics (e.g., bedrock, cobbles, silt) are often cited as major controls on the species
composition of macroinvertebrate, periphyton, and fish assemblages in streams (e.g., Hynes 1970,
Cummins 1974, Platts et al. 1983, Barbour et al. 1999, Bryce et al., 2008, 2010). Along with bedform
(e.g., riffles and pools), streambed particle size influences the hydraulic roughness and consequently the
range of water velocities in a stream channel. It also influences the size range of interstices that provide
living space and cover for macroinvertebrates and smaller vertebrates. Accumulations of fine substrate
particles (excess fine sediments) fill the interstices of coarser bed materials, reducing habitat space and
its availability for benthic fish and macroinvertebrates (Hawkins et al. 1982 Platts et al. 1983, Rinne
1988). In addition, these fine particles impede circulation of oxygenated water into hyporheic habitats
reducing egg-to-emergence survival and growth of juvenile salmonids (Suttle et al. 2004). Streambed
characteristics are often sensitive indicators of the effects of human activities on streams (MacDonald et
al. 1991, Barbour et al. 1999, Kaufmann et al. 2009). Decreases in the mean particle size and increases in
streambed fine sediments can destabilize stream channels (Wilcock 1997, 1998) and may indicate
increases in the rates of upland erosion and sediment supply (Lisle 1981, Dietrich et al. 1998).
The scaled median streambed particle size is expressed as Relative Bed Stability (RBS), calculated as the
ratio of the geometric mean diameter, Dg, divided by Dcbf, the critical diameter (maximum mobile
diameter) at bankfull flow (Gordon et al., 1992), where Dg is based on systematic streambed particle
sampling ("pebble counts") and Dcbf is based on the estimated streambed shear stress calculated from
slope, channel dimensions, and hydraulic roughness during bankfull flow conditions.
8.4.4.2	Instream Habitat Cover Complexity
Although the precise mechanisms are not completely understood, the most diverse fish and
macroinvertebrate assemblages are usually found in streams that have complex mixtures of habitat
features: large wood, boulders, undercut banks, tree roots, etc. (Kovalenko et al. 2011). When other
needs are met, complex habitat with abundant cover should generally support greater biodiversity than
simple habitats that lack cover (Gorman and Karr 1978, Benson and Magnuson 1992). Human use of
streams and riparian areas often results in the simplification of this habitat, with potential effects on
biotic integrity (Kovalenko et al., 2011). For this assessment, EPA proposes to continue the use of a
measure (XFC_NAT in Kaufmann et al., 1999) that sums the amount of instream habitat consisting of
undercut banks, boulders, large pieces of wood, brush, and cover from overhanging vegetation within a
meter of the water surface, all of which are estimated visually by NRSA field crews.
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8.4.4.3	Riparian Vegetation
The importance of riparian vegetation to channel structure, cover, shading, inputs of nutrients and large
wood, and as a wildlife corridor and buffer against anthropogenic disturbance is well recognized
(Naiman et al. 1988, Gregory et al. 1991). Riparian vegetation not only moderates stream temperatures
through shading, but also increases bank stability and the potential for inputs of coarse and fine
particulate organic material. Organic inputs from riparian vegetation become food for stream organisms
and provide structure that creates and maintains complex channel habitat.
EPA proposes to continue evaluating the cover and complexity of riparian vegetation based on the
metric XCMGW, which is calculated from visual estimates made by field crews of the areal cover and
type of vegetation in three layers: the ground layer (<0.5m), mid-layer (0.5-5.0 m) and upper layer (>5.0
m). The separate measures of large and small diameter trees, woody and non-woody mid-layer
vegetation, and woody and non-woody ground cover are all visual estimates of areal cover. XCMGW
sums the cover of woody vegetation summed over these three vegetation layers, expressing both the
abundance of vegetation cover and its structural complexity. Its theoretical maximum is 3.0 if there is
100% cover in each of the three vegetation layers. XCMGW gives an indication of the longevity and
sustainability of perennial vegetation in the riparian corridor (Kaufmann et al. 1999).
8.4.4.4	Riparian Human Disturbances
Agriculture, roads, buildings, and other evidence of human activities in and near the stream and river
channel may exert stress on aquatic ecosystems and may also serve as indicators of overall
anthropogenic stress. EPA's 1992 stream monitoring workshop recommended field assessment of the
frequency and extent of both in-channel and near-channel human activities and disturbances (Kaufmann
1993). The vulnerability of the stream network to potentially detrimental human activities increaseswith
the proximity of those activities to the streams themselves. NRSA follow Stoddard et al. (2005b) and U.S.
EPA (2006) in using a direct measure of riparian human disturbance that tallies 11 specific forms of
human activities and disturbances (walls, dikes, revetments or dams; buildings; pavement or cleared
lots; roads or railroads; influent or effluent pipes; landfills or trash; parks or lawns; row crop agriculture;
pasture or rangeland; logging; and mining) at 22 separate locations along the stream reach, and weights
them according to how close to the channel they are observed (W1_HALL in Kaufmann et al. 1997).
Observations within the stream or on its banks are weighted by 1.5, those within the 10 x 10 meter
plots are weighted by 1.0, and those visible beyond the plots are weighted by 0.5. The index W1_HALL
ranged from 0 (no observed disturbance) to ~7 (e.g., equivalent to four or five types of disturbance
observed in the stream, throughout the reach; or seven types observed within all 22 riparian plots
bounding the stream reach). Although direct human activities certainly affect riparian vegetation
complexity and layering measured by the Riparian Vegetation Index (previous paragraph),the Riparian
Disturbance Index is more encompassing, and differs by being a direct measure of observable human
activities that are presently or potentially detrimental to streams.
8.4.5 Enterococci
Enterococci are bacteria that live in the intestinal tracts of warm-blooded animals, including humans,
and therefore indicate possible contamination of streams and rivers by fecal waste. Epidemiological
studies conducted at beaches affected by human sources of fecal contamination have established a
relationship between the density of enterococci in ambient waters and the elevated incidence of
gastrointestinal illness in swimmers. For the NRSA, water samples are analyzed using a process known
as quantitative polymerase chain reaction, or qPCR, a methodology that facilitates the detection of DNA
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sequences unique to these bacteria. Analysts compare the NRSA results to a new EPA qPCR threshold
for protecting human health in ambient waters designated for swimming.
8.4.6 Fish Tissue Indicator (Fillets and Plugs)
Mercury is widely distributed in the environment, due to both natural processes and human activities.
Measuring mercury levels is critical because about 80% of all fish consumption advisories currently
involve mercury. Analysts compare results of the fish tissue indicator analyses to EPA's human health
screening value that, if exceeded, can be harmful to human health. If PFCs are analyzed, analysts will
compare results of the fish tissue to human health screening values.
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9 REFERENCES
ASTM D1193 - 06(2011) Standard Specification for Reagent Water
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.
Benson, B. J. and John J. Magnuson. 1992. Spatial heterogeneity of littoral fish assemblages in lakes:
relation to species diversity and habitat structure. Canadian Journal of Fisheries and Aquatic Sciences
49:1493-1500.
Bryce, S.A., G.A. Lomnicky, P.R. Kaufmann, L.S. McAllister, and T.L. Ernst. 2008. Development of
Biologically-Based Sediment Criteria in Mountain Streams of the Western United States. N. Am. J. Fish.
Manage. 28: 28:1714-1724.
Bryce, S.A., Lomnicky, G.A, and P.R. Kaufmann. 2010. Protecting Sediment-Sensitive Aquatic Species in
Mountain Streams through the Application of Biologically-Based Criteria Streambed Sediment Criteria. J.
North American Benthological Soc. 29(2):657-672.
CAS. 1999. Chemical Abstracts Service web site (http://www.cas.org).
Charles, D. F., C. Knowles, and R.S. Davis. 2003. Protocols for the analysis of algal samples collected as
part of the U.S. Geological Survey National Water-Quality Assessment program. Patrick Center For
Environmental Research, The Academy Of Natural Sciences. Report No. 02-06.
Cochran, W.G. 1977. Sampling Techniques. John Wiley and Sons: New York.
Cummins, K. W. 1974. Structure and function of stream ecosystems. Bioscience 24:631-641.
Diaz-Ramos, S., D.L. Stevens, Jr., and A.R. Olsen. 1996. EMAP Statistics Methods Manual. EPA/620/R-
96/XXX. Corvallis, OR: U.S. Environmental Protection Agency, Office of Research and Development,
National Health and Environmental Effects Research Laboratory.
Dietrich, W. E., R. Real de Asua, J. Coyle, B. Orr, and M. Trso. 1998. A validation study of the shallow
slope stability model, SHALSTAB, in forested lands of Northern California. Stillwater Ecosystem,
Watershed & Riverine Sciences. Berkeley, CA. 59 pp.
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.
i/i
LU
Garner, F.C., M.A. Stapanian, and K.E. Fitzgerald. 1991. Finding causes of outliers in multivariate	u
environmental data. Journal of Chemometrics 5: 241-248.	^
LU
U_
LU
en
119
-------
National Rivers and Streams Assessment 2013-2014
Version 2.2, September 2018
Quality Assurance Project Plan
Page 120 of 127
Gorman, Owen T., and James R. Karr. 1978. Habitat Structure and Stream Fish Communities. Ecology
59:507-515.
Glaser, 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-.
Gregory, S. V., F. J. Swanson, W. A. McKee, and K. W. Cummins. 1991. An ecosystem perspective of
riparian zones. Bioscience 41:540-551.
Hawkins, C.P., M.L. Murphy., and N.H. Anderson. 1982. Effects of canopy, substrate composition, and
gradient on the structure of macroinvertebrate communities in Cascade Range streams of Oregon.
Ecology 63:1840 -1856.
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.
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.
Hynes, H.B.N. 1970. The ecology of running waters. University Toronto Press.
Hunt, D.T. E., and A.L. Wilson. 1986 The Chemical Analysis of Water: General Principles and Techniques.
Second edition. Royal Society of Chemistry, 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.
Kauffman, J. B., R. L. Beschta, N. Otting, and D. Lytjen. 1997. An ecological perspective of riparian and
stream restoration in the western United States . Fisheries 22(5):12-24.
Kaufmann, P.R., P. Levine, E.G. Robison, C. Seeliger, and D.V. Peck. 1999. Quantifying Physical Habitat in
Wadeable Streams. EPA 620/R-99/003. Environmental Monitoring and Assessment Program, U.S.
Environmental Protection Agency, Corvallis, OR.
Kaufmann, P.R., D.P. Larsen, and J.M. Faustini, 2009. Bed Stability and Sedimentation Associated with
Human Disturbances in Pacific Northwest Streams. J. Am. Water Resources Assoc. 45(2):434-459.
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.
LU
Kovalenko, I., B. Zdyrko, A. Magasinski, B. Hertzberg, Z. Milicev, R. Burtovyy, I. Luzinov, G. Yushin.. 2011.	^
A Major Constituent of Brown Algae for Use in High-Capacity Li-Ion Batteries. Science 334, 75: DOI:	a:
10.1126/science.	tu
oe
120
-------
National Rivers and Streams Assessment 2013-2014
Version 2.2, September 2018
Quality Assurance Project Plan
Page 121 of 127
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.
Lisle, T. E. 1981. Channel recovery from recent large floods in north coastal California: rates and
processes. Pages 153-160, in: R. N. Coates (ed.), Proceedings, Symposium on Watershed Rehabilitation
in Redwood National Park and Other Pacific Coastal Areas; 25-28 August 1981; Areata, California.
Sacramento, California: Center for Natural Resources Studies of JMI, Inc.
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.
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.
Naiman, R. J., K. L. Fetherston, S. J. McKay, and J. Chen. 1998. Riparian forests. Pages 289-323 in R. J.
Naiman and R. E. Bilby, editors. River ecology and management: lessons from the Pacific coastal
ecoregion. Springer-Verlag, New York, New York, USA.
NAPA. 2002. Environment.gov. National Academy of Public Administration. ISBN: 1-57744-083-8. 219
pages.
National Institute of Standard and Technology: (http://www.nist.gov/)
NRC. 2000. Ecological Indicators for the Nation. National Research Council.
Oblinger-Childress, C.J., W. T. Foreman, B.F. Connor, T.J. Maloney.1999. "New Reporting Procedures
Based on Long-Term Method Detection Levels and Some Considerations for Interpretations of Water-
Quality Data Provided by the U.S. Geological Survey National Water Quality Laboratory", United States
Geological Survey.
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 National
Rivers and 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.
R. Development Core Team. 2004. R: A language and environment for statistical computing. Vienna,
Austria: R Foundation for Statistical Computing.
Rinne, J.N. 1988. Grazing effects on stream habitat and fishes: research design considerations. N. Amer.
J. Fish Manage. 8(2).	^
LU
Robison, E.G. and R.L. Beschta. 1990. Characteristics of coarse woody debris for several coastal streams	z
LU
of southeast Alaska, USA. Canadian Journal of Fisheries and Aquatic Sciences 47(9):1684-1693.
U_
LU
cc
121
-------
National Rivers and Streams Assessment 2013-2014
Version 2.2, September 2018
Quality Assurance Project Plan
Page 122 of 127
Robison, E.G., and P.R. Kaufmann. (In preparation). Evaluating and improving and objective rapid
technique for defining pools in small National Rivers and Streams.
Sarndal, C.E., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. Springer-Verlag.
New York. 694 pp.
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.
Thesis, M.S. Oregon State University. 109pp.
Strahler, A. N. 1952. Hypsometric (area-altitude) analysis of erosional topology, Geological Society of
America Bulletin 63 (11): 1117-1142.
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.
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.
Stoddard, M.A., and Hayes, J.P. 2005. The influence of forest management on headwater stream
amphibians at multiple spatial scales. Ecol. Applic. 15:811- 823.
STORET. 1999. The STORET web site. (Http://www.epa.gov/OWOW/STORET)
Stribling, J.B., 2003. Determining the quality of taxonomic data. The North American Benthological
Society. 22(4):621-631.
Stauffer, J.R., J. Karish and T.D. Stecko. 2001. Guidelines for Using Digital Photos as Fish Vouchers for
Pennsylvania Fishes. The Pennsylvania State University and National Park Service.
Suttle, K.B., M.E. Power, J.M. Levine, C. McNeely.. 2004. How Fine Sediment in Riverbeds Impairs
Growth and Survival of Juvenile Salmonids. Ecological Applications, 14(4), 2004, pp. 969-974.
U.S.EPA. July 1984. Order 2160 Records Management Manual, U.S. Environmental Protection Agency,
Washington, DC.
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.
-------
National Rivers and Streams Assessment 2013-2014
Version 2.2, September 2018
Quality Assurance Project Plan
Page 123 of 127
U.S. EPA. 1996b. Addendum to: Guidelines for the information management directory. U.S. EPA,
NHEERL. Atlantic Ecology Division. Narragansett, Rl.
U.S.EPA. 1999. Information Security Manual 2195A1
U.S. EPA. September 1999. Order 2195.1 A4. Agency Network Security Policy Standards of Ethical
Conduct for Employees of the Executive Branch. U.S. Office of Government Ethics.
U.S. EPA. 2000. National Study of Chemical Residues in Fish. U.S. Environmental Protection Agency,
Office of Science and Technology, Washington, D.C. EPA- 823-R-02-005.
U.S. EPA. 2000b. Quality Assurance Project Plan for Analytical Control and Assessment Activities in the
National Study of Chemical Residues in Lake Fish Tissue. U.S. Environmental Protection Agency, Office of
Science and Technology, Washington, D.C. EPA-823-R-02-006.
U.S. EPA. 2003. Draft Report on the Environment. ORD and OEI. EPA-260-R-02-006.
U.S. EPA. 2006. Guidance on Systematic Planning Using the Data Quality Objectives Process (EPA QA/G-
4). EPA/240/B-06/001. U.S. Environmental Protection Agency, Office of Environmental Information,
Washington, D.C. http://www.epa.gov/quality/qs-docs/g4-final.pdf.
U.S. EPA. 2006a. Draft Guidance for Implementing the January 2001 Methylmercury Water Quality
Criterion. EPA-823-B-04-001. U.S. Environmental Protection Agency, Office of Water, Washington, D.C.
U.S.EPA. 2006b. Wadeable Streams Assessment: A Collaborative Survey of the Nation's Streams. EPA
841-B-06-002.
U.S. EPA. 2009. The National Study of Chemical Residues in Lake Fish Tissue. EPA 823-R-09-006.
U.S. EPA. 2011. National Health and Environmental Effects Research Laboratory. Level III Ecoregions of
the Continental United States. Revised December 2011.
http://www.epa.gov/wed/pages/ecoregions/level iii iv.htm.
U.S. EPA. 2016. National Rivers and Streams Assessment 2008-2009: A Collaborative Survey (EPA/841/R-
16/007). Washington, DC. March 2016.
U.S. EPA. Environmental Monitoring and Assessment Program (EMAP.) http://www.epa.gov/emap/.
U.S. General Accounting Office (USGAO). 2000. Water Quality. GAO/RCED-OO-54.
U.S. Geological Survey-National Hydrography Dataset (NHD). (http://www.nhd.usgs.gov).
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.
Wilcock PR. 1997. A Method for Predicting Sediment Transport in Gravel-bed Rivers. Report to the
United States Forest Service, Rocky Mountain Forest and Range Experiment Station: Fort Collins, CO.
Wilcock PR. 1998. Two-fraction model of initial sediment motion in gravel-bed rivers. Science 280: 410-
412.
Wolman, M.G. 1954. A method of sampling coarse river-bed material. Transactions of the American
Geophysical Union 35(6):951-956.
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Appendix A - Planned Quality Assurance for Periphyton ID - Originally
in Section 6
Formerly 6.3.3 Quality Assurance Objectives
MQOs that were originally planned for the periphyton ID samples are given in Formerly Table 6.11 and
Table 6.12Error! Reference source not found.. Three different measurement data quality objectives
were planned for evaluating the periphyton data, but as described in Section 6.2 issues arose with
implementing them andultimately the data were not used in the NRSA:
Diatoms - Percent Taxonomic Disagreement (PTD) and Percent Difference in
Enumeration (PDE)).
Soft algae - Percent Difference (PctDiff). Targets are shown in Formerly Error!
Reference source not found, and Formerly Error! Reference source not found..
Formerly Table 6.11 Measurement data quality objectives: diatom periphyton
Variable or Measurement
Precision
Accuracy
Completeness
Enumeration
25%
15%
99%
Identification
25%
15%
99%
Formerly Table 6.12 Measurement data quality objectives: soft bodied algae periphyton
Variable or Measurement
Precision
Accuracy
Completeness
Identification
50%a
50%b
99%
a As measured by PctDiff
Formerly 6.3.4 Pertinent QA/QC Procedures for ID Periphyton Sample
Quality control activities and data validation are summarized in Error! Reference source not found, and
Formerly Table . Equations used are presented below. Percent disagreement in enumeration (PDE):
measure of taxonomic precision for diatoms comparing the number of organisms, nh counted in a
sample by the primary taxonomist with the number of organisms, n2, counted by the secondary
taxonomist.
\n, —
pde = 1—	— x 100
nx + n2
Percent taxonomic disagreement (PTD): measure of taxonomic precision for diatoms comparing the
number of agreements (positive comparisons, compp0s) of the primary taxonomist and internal or
external QC taxonomists. In the following equation, N is the total number of organisms in the larger of
the two counts.
PTD =
1-
COmPpos
: 100
N
Percent Difference (PctDiff): measure of difference for soft algae that compares the enumerations for
the taxa within a sample, as reported by the primary taxonomist (a) and secondary laboratory (b), as
follows:
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PctDiff = 1 -
¦yi=total # species
2-'i=i

x 100
yi=total # species
A>i=l
max^a-i, b{)
Formerly 6.3.4.1 Internal Taxonomic QC
The internal QC taxonomist will randomly select 10% of the diatom slides and 10% of the soft algae
subsamples for an independent count and identification by the Internal QC Taxonomist. As appropriate,
calculate the PctDiff, PDE, and PTD. If any do not meet the QA requirements, perform a third count and
reidentification for the sample.
Formerly 6.3.4.2 External Taxonomic QC
On receipt of the data after initial identification, the EPA External QA Coordinator, or an independent
EPA-selected QC contractor, will randomly select 10% of the samples from each lab subject to the
following constraints:
a)	If the primary laboratory received fewer than 30 samples, then the QC contractor randomly
selects three samples for the evaluation.
b)	For each taxonomist identified on the list, the QC contractor ensures that one or more of his/her
samples are selected.
This QA will pertain to both the hard and soft bodied algae samples (diatom and soft algal samples). The
EPA External QA Coordinator will direct the original laboratory to send those samples to an external QC
taxonomist, a second experienced taxonomist who did not participate in the original identifications. The
EPA External QA Coordinator will direct the laboratory where to send the soft bodied algae and where
to send the diatom samples for each QC sample selected. The original laboratory will complete a chain-
of-custody form and send it with the samples.
Formerly 6.3.4.3 Diatom and Soft Bodied Algae Re-identification
The periphyton labs will send permanent mounted diatom slides to the diatom QC taxonomist. The
remaining volume from the sample will be sent to the QC taxonomist as directed by EPA.
¦	The Extern al QC taxonomist will follow the same protocols for identification of the diatom
samples as laid out in the LOM.
¦	The EPA External QC Coordinator, or an independent EPA-selected QC contractor, compares the
taxonomic results generated by the primary and QC taxonomists for each sample and calculate
percent difference using percent difference equation from above.
¦	Where: a and b are the relative proportions recorded for a given taxon by the primary
taxonomist (a) and the External QC taxonomist (b).
¦	Values will be a combination of subsampling error and taxonomic error.
¦	If it appears that high percent difference for soft-bodied algae are due to subsampling
inconsistency, then determine and implement appropriate corrective actions working with the
EPA External QA Coordinator. In addition, disagreements resulting from identification to a
specific taxonomic level, creating the possibility to double-count "unique" or "distinct" taxa shall
be rectified through corrective actions working with the EPA QA Coordinator.
Formerly 6.3.5 Taxonomic QC Review & Reconciliation
The EPA External QA Coordinator, or an independent EPA-selected QC contractor, prepares a
spreadsheet, report or technical memorandum (as specified by EPA) to quantify aspects of taxonomic
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precision, assess data acceptability, highlight taxonomic problem areas, and provide recommendations
for improving precision. This report is submitted to the HQ Project Management Team, with copies sent
to the primary and QC taxonomists. Another copy is maintained in the project file. Significant
differences will result in the re-identification of samples by the primary taxonomist and a second QC
check by the secondary taxonomist. Quality control activities and data validation are summarized in
Formerly Table 6.13 and Formerly Table 6.14.
Each laboratory prepares reference/ voucher samples. Soft-bodied algal samples are placed in glass
containers with appropriate preservative (formalin). These samples will be identified and digitally
referenced (a photograph with taxonomic information superimposed on the photograph and in the file
name) and will be included in an electronic file folder on the NARS ShareFile. All samples are stored at
the laboratory until the Project Lead notifies the lab regarding disposition.
Formerly Table 6.13 Quality control: all activities
Check or Sample
Frequency
Acceptance Criteria
Corrective Action
Description



Internal QC Taxonomist
All samples
No obvious problems such
Slide is discarded and replaced
verifies that diatom

as bubbles under the
with a new slide
slide is appropriate for

coverslip

diatom analysis



Duplicate identification
1 in 10 samples per
PctDiff<50% (soft algae)
If any criterion is exceeded,
by Internal QC
taxonomist, with a
PDE < 15% (diatoms)
perform a third count and
Taxonomists
minimum of 1 NRSA
PTD < 25% (diatoms)
reidentification for the sample.

sample

Independent
All uncertain taxa
Uncertain identifications
Record both tentative and
identification by

to be confirmed by expert
independent IDs
outside, expert,

in particular taxa

taxonomist



External QC
10% of all samples
PctDiff<50% (soft algae)
Attempt to reconcile results

completed per
PDE < 15% (diatoms)
during a conference call with

laboratory
PTD < 25% (diatoms)
EPA and the two
laboratories. Document
unresolved disagreements
for the data analyst to
determine if lowest practical
level (e.g., species) is
appropriate, or if
identification should be to
the level that both labs found
(e.g., class)
Use of
For all identifications
All keys and references
If a lab proposes to use other
widely/commonly

used by each lab must be
references, the lab must identify
accepted taxonomic

on bibliography prepared
them in the database.
references by all NRSA

by one or more additional

labs

NRSA labs or in BioData
(see Section 9.7 for
retrieval instructions). This
requirement demonstrates
the general acceptance of
the references by the

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scientific community.

Prepare reference
collection
Each new taxon per
laboratory
Complete reference
collection to be
maintained by each
individual laboratory
Internal Taxonomy QC Officer
periodically reviews data and
reference collection to ensure
reference collection is complete
and identifications are accurate
Formerly Table 6.14 Data validation: periphyton
Check or Sample
Description
Frequency
Acceptance Criteria
Corrective Action
Taxonomic
All data
Taxa known to occur in given
Second or third identification
"reasonable-ness"

rivers or streams or geographic
by expert in that taxon
checks

area

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