U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2020–1023

National Water Quality Program

Design and Methods of the California Stream Quality 

Assessment (CSQA), 2017
Front cover: Nacimiento River, California. 

Inset: eDNA sampling by U.S. Geological Survey personnel in Alisal Creek, California. Photographs by Alan Cressler, U.S. Geological Survey.

Back Cover: Top left: Map of Central California Coastal study area and sampling sites. 

Top right: Arroyo Seco at Elm Avenue Bridge, California. Photograph by Alan Cressler, U.S. Geological Survey.

Bottom left: Sediment sampling in Reclamation Ditch, California. Photograph by Alan Cressler, U.S. Geological Survey.

Bottom middle: Ceramic tile deployed to collect biofilms for pesticide analysis. Photograph by Barbara Mahler, U.S. Geological Survey.

Bottom right: Algae and invertebrate sampling in Alisal Creek, California. Photograph by Alan Cressler, U.S. Geological Survey.
Design and Methods of the California 

Stream Quality Assessment (CSQA), 2017

By Jason T. May, Lisa H. Nowell, James F. Coles, Daniel T. Button, 

Amanda H. Bell, Sharon L. Qi, and Peter C. Van Metre

National Water Quality Program

Open-File Report 2020–1023

U.S. Department of the Interior

U.S. Geological Survey
ii

U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, 

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U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

May, J.T., Nowell, L.H., Coles, J.F., Button, D.T., Bell, A.H., Qi, S.L., and Van Metre, P.C., 2020, Design and methods 

of the California stream quality assessment, 2017: U.S. Geological Survey Open-File Report 2020–1023, 88 p., 

https://doi.org/10.3133/ofr20201023.

ISSN 2331-1258 (online)
iii

Acknowledgment pages: Left page: Salinas River, California. Photograph by Alan Cressler, 

U.S. Geological Survey.

Right page: Jason May and Daniel Calhoun sampling for fish in Nanticoke Creek, NY, as part of the 

Northeast Stream Quality Assessment study. Photograph by Alan Cressler, U.S. Geological Survey.
iv
v

Acknowledgments

It is with deep appreciation and affection that 

we acknowledge the contributions of Jason 

Todd May to the planning and success of 

the California Stream Quality Assessment 

study. Sadly, Jason passed away on 

August 22, 2019, after a year-long 

illness. His efforts in study-site 

selection, organization of sampling 

crews, and data collection were 

invaluable in making the study a 

success. Jason’s efforts on this study 

are a reflection of his dedication as 

a scientist at the California Water 

Science Center, where his broad 

experience was highly valued and 

resulted in his co-authoring more than 

45 journal articles and U.S. Geological 

Survey reports. Jason was always willing 

to share his expertise with others inside 

and outside of the U.S. Geological Survey. 

His participation in the California Stream 

Quality Assessment and his dedication to quality 

science at the California Water Science Center 

will be missed.
vi

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Background............................................................................................................................................2

Purpose and Scope ..............................................................................................................................3

Study-Area Description .......................................................................................................................4

Study Design...................................................................................................................................................6

Site Selection Process .........................................................................................................................6

Sample Collection and Processing ...........................................................................................................18

Comprehensive Stressor Assessments ..........................................................................................18

Discrete Water-Quality Samples .............................................................................................22

Polar Organic Compound Integrative Samplers (POCIS) ....................................................23

Continuous Streamflow, Stage, and Water Temperature ...................................................23

Focused Studies ..................................................................................................................................25

Sampling Pesticides with Small-Volume Pesticide Automated Samplers .......................25

Sampling Pesticides in Biofilms ..............................................................................................26

Sampling Suspended Sediment with Passive Samplers .....................................................26

Ecological Surveys .............................................................................................................................28

Aquatic Biota ..............................................................................................................................28

Physical Habitat .........................................................................................................................29

Streambed and Bank Sediment ...............................................................................................29

Sample Analyses..........................................................................................................................................31

Comprehensive Stressor Assessments ..........................................................................................31

Discrete Water-Quality Samples .............................................................................................31

Polar Organic Compound Integrative Samplers ...................................................................32

Continuous Streamflow, Stage, and Water Temperature ...................................................32

Focused Studies ..................................................................................................................................33

Pesticides from the Small-Volume Pesticide Automated Samplers .................................33

Pesticide Analysis in Biofilms ..................................................................................................33

Suspended-Sediment Passive Samplers ...............................................................................33

Ecological Surveys .............................................................................................................................33

Aquatic Biota ..............................................................................................................................15

Physical Habitat .........................................................................................................................33

Streambed and Bank Sediment ...............................................................................................34

Sediment Toxicity Testing .........................................................................................................34

Quality Assurance and Quality Control ....................................................................................................35

Data-Management Procedures ................................................................................................................39

Summary........................................................................................................................................................41

References Cited..........................................................................................................................................41

Appendix 1 Description of the Sampling Timelines, Matrix, Collection, and Processing 

for Water, Sediment, and Ecological Samples ..........................................................................48

Appendix 2 Description of the U.S. Geological Survey National Water Quality 

Laboratory Schedules Used for Water, Bed Sediment, and Biofilms ....................................57

References Cited..........................................................................................................................................87
vii

Figures

1. Map showing locations of the Regional Stream Quality Assessment studies 

across the United States .............................................................................................................3

2. Map of the California Stream Quality Assessment study area, including 

sampling locations and generalized land cover ......................................................................5

3. Map showing locations of the 85 sites sampled for the California Stream 

Quality Assessment study, 2017 ...............................................................................................16

4. Graphs showing distribution of 85 California Stream Quality Assessment sites 

in relation to percent of cropland and percent of total urban for the whole basin 

and lower basin watershed delineation approaches ...........................................................17

5. Photograph showing a hydrologist moving an isokinetic sampler into position ..............23

6. Photograph showing deployed polar organic compound integrated sampler on 

cinder-block-and-cable infrastructure ...................................................................................24

7. Photographs showing the small-volume pesticide autosampler used to collect 

filtered water at sub-daily intervals for pesticide analysis at selected sites ...................26

8. Photograph showing installation of time-integrating suspended-sediment 

passive samplers by U.S. Geological Survey personnel ......................................................27

9. Photograph showing invertebrate sampling with a D-frame dip net by 

U.S. Geological Survey personnel ...........................................................................................29

10. Photograph showing collection of composite bed-sediment samples from a 

depositional area along a reach ..............................................................................................30

Tables

1. Characteristics of stream watersheds in the Central California Foothills and 

Coastal Mountains ecoregion of the United States that were assessed as part 

of the U.S. Geological Survey National Water-Quality Assessment Project, 

California Stream Quality Assessment, in 2017 .......................................................................7

2. Land-use classes from the National Water Quality Assessment wall-to-wall 

anthropogenic land use trends database were summed to create land-use types .......14

3. Thresholds and combinations of land-use types used to assign sites to unique 

land-use categories ...................................................................................................................15

4. Distribution of 85 California Stream Quality Assessment sites by land-use 

category for the whole basin and lower basin watershed delineations ...........................15

5. Summary of data collected at the California Stream Quality Assessment 

sites in 2017..................................................................................................................................19

6. Summary counts of environmental, field blank, replicate, and spike samples of 

stream water from the 85 stream sites sampled in the California Stream Quality 

Assessment of the U.S. Geological Survey National Water-Quality Assessment 

Project in 2017 .............................................................................................................................36

7. Summary counts of environmental, field replicate, field spike, and temporal 

samples of bed sediment collected from 82 stream sites in the California 

Stream Quality Assessment of the U.S. Geological Survey National 

Water-Quality Assessment Project in 2017 ............................................................................38
viii

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

micrometer (μm) 3.937×10−5 inch (in.)

nanometer (nm) 3.937×10−8 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd)

Area

square meter (m2) 0.0002471 acre

square meter (m2) 10.76 square foot (ft2)

square centimeter (cm2) 0.1550 square inch (ft2)

square kilometer (km2) 0.3861 square mile (mi2)

Volume

milliliter (mL) 0.0002642 gallon (gal)

liter (L) 0.2642 gallon (gal)

liter (L) 61.02 cubic inch (in3)

Flow rate

meter per second (m/s) 3.281 foot per second (ft/s)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

nanogram (ng) 3.527×10−11 ounce, avoirdupois (oz)

gram per square meter (g/m2) 0.0002048 pound per square foot (lb/ft2)

milligram per square meter (mg/m2) 0.000003277 ounce, avoirdupois, per square foot (oz/ft2)

Pressure

kilopascal (kPa) 0.1450 pound-force per inch (lbf/in [or psi])

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: 

 °F = (1.8 × °C) + 32.

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows: 

 °C = (°F – 32) / 1.8.
ix

Datum

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Supplemental Information

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm 

at 25 °C).

Concentrations of chemical constituents in water are given either in milligrams per liter 

(mg/L), micrograms per liter (μg/L), or nanograms per liter (ng/L). Concentrations of chemical 

constituents in bed sediment are given in micrograms per kilogram (μg/kg).

Abbreviations

ASE accelerated solvent extraction

ASR analytical service request

CERC Columbia Environmental Research Center

CSQA California Stream Quality Assessment

DAI direct aqueous injection

DOC dissolved organic carbon

eDNA environmental DNA

ELISA enzyme-linked immunosorbent assay

EPA U.S. Environmental Protection Agency

ESI electrospray ionization

GC/MS gas chromatography mass spectrometry

GC-MS/MS gas chromatography-tandem mass spectrometry

GIS geographic information system

INSTAAR Institute of Arctic and Alpine Research

LC-MS/MS liquid chromatography tandem mass spectrometry
x

NAWQA National Water-Quality Assessment

NHDPlus National Hydrography Dataset Plus

NIST National Institute of Standards and Technology 

NLCD National Land Cover Database

NWALT National Water-Quality Assessment Wall-to-Wall Anthropogenic Land Use Trends

NWQL National Water Quality Laboratory

NWIS National Water Information System

OPP Office of Pesticide Programs

OCRL Organic Chemistry Research Laboratory

OGRL Organic Geochemistry Research Laboratory

OTU operational taxonomic unit

PAH polycyclic aromatic hydrocarbon

PBDE polybrominated diphenyl ether

PCB polychlorinated biphenyl

PCFF Personal Computer Field Form

POCIS polar organic chemical integrative sampler

QA quality assurance

QC quality control

QW quality of water

RP reference point

RSQA Regional Stream Quality Assessment

RWB Reach-wide benthos

USGS U.S. Geological Survey

UVA ultraviolet absorbance

WQ water quality

WSC Water Science Center
Design and Methods of the California Stream Quality 

Assessment (CSQA), 2017

By Jason T. May†, Lisa H. Nowell, James F. Coles, Daniel T. Button, Amanda H. Bell, Sharon L. Qi, and 

Peter C. Van Metre

Abstract

During 2017, as part of the National Water-Quality 

Assessment Project, the U.S. Geological Survey conducted 

the California Stream Quality Assessment to investigate the 

quality of streams in the Central California Foothills and 

Coastal Mountains ecoregion, United States. The goal of the 

California Stream Quality Assessment study was to assess the 

health of wadeable streams in the region by characterizing 

multiple water-quality factors that are stressors to aquatic 

biota and by evaluating the relation between these stressors 

and biological indicators of stream health. Urbanization, 

agriculture, and modifications to streamflow are anthropogenic 

changes that affect water quality in the region; consequently, 

the study design primarily targeted sites and specific stressors 

associated with these activities. For the study, 85 stream sites 

were selected to represent the types and intensity of land use 

in the watershed; categories of site types were undeveloped, 

urban (low, medium, high), agriculture (low, high), and 

mixed (urban and agriculture). Most sites (about 70 percent) 

represent a gradient of urbanization from undeveloped to 

99-percent urbanized. At most of the sites, streamgages or 

pressure transducers were used to monitor stream discharge 

and stage, as well as temperature. Water-quality samples 

were collected routinely at all sites and were analyzed for 

major ions, organic contaminants, nutrients, and suspended 

sediment. Sampling frequency varied on the basis of site type 

and location. Discrete water samples were collected weekly 

and generally 6 times per site, except for 11 undeveloped sites 

that were sampled only 4 times (during the last 4 weeks). 

Water sampling began at sites in the southern part of the 

study on March 13, 2017, and at sites in the northern part of 

the study on April 3, 2017. Passive samplers were deployed 

at most sites for measurement of polar organic contaminants 

(pesticides and pharmaceuticals). In May 2017, coincident 

with completion of water-quality sampling, an ecological 

survey was conducted at each site to assess benthic algal and 

macroinvertebrate communities and instream habitat. During 

the ecological surveys, a single composite streambed-sediment 

sample was collected for chemical analysis and toxicity 

testing. In addition, a few focused studies were done at subsets 

of sites, namely, measuring pesticides using small-volume 

automated samplers, measuring pesticides in biofilms, and 

sampling suspended sediments using passive samplers. This 

report describes the various study components and methods 

of the California Stream Quality Assessment, including 

measurements of water quality, sediment chemistry, habitat 

assessments, and ecological surveys, as well as procedures for 

sample analysis, quality assurance and quality control, and 

data management.

Introduction

Many natural and anthropogenic stressors can affect 

stream ecosystems, and often the stressors that degrade 

streams are associated with land use in the watershed 

(U.S. Environmental Protection Agency, 2013, 2019). 

Variations in streamflow, habitat, temperature, and levels of 

sediment and nutrients are essential characteristics of natural 

stream ecosystems, but deviation from the natural patterns of 

streams can substantially alter their biological condition and 

ecological function (Lenat and Crawford, 1994; Gregory and 

Calhoun, 2007; Nagy and others, 2011). Organic contaminants 

differ from other stressors in that many are derived from 

human activities and, through various modes of action and 

toxicity, are potentially detrimental to aquatic life as well as to 

humans who use water resources. To efficiently manage water 

resources, it is important to understand the conditions under 

which stressors—individually or in combinations—adversely 

affect the biological condition of streams and the water 

resources valued by people. †Deceased August 22, 2019.
2 Design and Methods of the California Stream Quality Assessment, 2017

Multistressor effects are often assessed in the laboratory, 

under controlled conditions, or in the field at small-catchment 

scales (Townsend and others, 2008; Culp and others, 

2017). At these small scales, biogeochemical processes and 

complex environmental interactions can be manipulated 

and monitored; however, results of such studies are not 

readily extended over larger spatial scales. Alternatively, 

by characterizing the conditions of multiple streams over a 

large area, specific stressors and biological conditions can be 

evaluated on regional and national scales (U.S. Environmental 

Protection Agency, 2006; Herlihy and others, 2008); from 

such studies, empirical models have been developed to 

predict environmental stressors or the biological condition 

across national-scale disturbance gradients (Waite and others, 

2000; Klemm and others, 2003; Herlihy and others, 2006; 

Coles and others, 2012). To date (2020), most regional- and 

national-scale studies have not included organic contaminants 

among the studied stressors (such as U.S. Environmental 

Protection Agency, 2016) or have generally limited their 

evaluations to relations between land use and biological 

condition (such as Gregory and Calhoun, 2007; Cuffney and 

others, 2011; Brown and others, 2012).

The U.S. Geological Survey (USGS), through the 

National Water-Quality Assessment (NAWQA) Project, is 

performing studies to bridge the gap in stressor coverage at 

large spatial scales, by extensively characterizing stressors 

(including contaminants) at the regional scale, with enough 

sampling sites to promote development of empirical models. 

As such, the studies are intended to provide the public 

and policymakers with information about the human and 

environmental factors that have the greatest effects on stream 

quality by addressing the following objectives in five regions 

of the United States:

1. Determine the status of stream quality across the region 

on the basis of contaminants, nutrients, sediments, 

toxicity of the bed sediments, streamflow, habitat, and 

biological communities;

2. Evaluate the relative influence of contaminants, 

nutrients, sediment, streamflow, and habitat on biological 

communities in the streams;

3. Identify how the natural and anthropogenic 

characteristics of the watersheds are related to stressors 

measured at the stream-reach scale and how the 

condition of biological communities can be explained by 

these stressors.

4. Develop statistical models and management tools 

to predict the ecological health of wadeable streams 

throughout the region and how ecological health 

is associated with concentrations of contaminants, 

nutrients, and sediment.

Background

The USGS launched Cycle III of the NAWQA Project 

in 2013, which marked the beginning of NAWQA’s third 

decade of water-quality assessments for the Nation. In 1992, 

NAWQA began its Cycle I investigations, which aimed to 

characterize baseline water-quality conditions in the Nation’s 

streams and aquifers (Leahy and others, 1990). A decade 

later, NAWQA transitioned to Cycle II, which emphasized 

trends and modeling and included five “topical” studies 

designed to improve our understanding of environmental 

processes affecting water quality. The topical studies 

addressed (1) the fate and transport of agricultural chemicals, 

(2) effects of urbanization on stream ecosystems, (3) effects 

of nutrient enrichment on stream ecosystems, (4) transport of 

contaminants to public-supply wells, and (5) bioaccumulation 

of mercury in stream ecosystems. Cycle III is built on 20 years 

of studies that describe contaminant sources and their transport 

to receiving waters, and the effects of land use on stream 

quality and ecological condition.

One of the major objectives in Cycle III is to assess 

the occurrence and effects of multiple instream stressors on 

stream ecological condition. Designated as Regional Stream 

Quality Assessment (RSQA) studies, these studies characterize 

watershed and stream water-quality stressors and aquatic 

biological conditions to improve understanding of stressor 

effects at regional scales (https://webapps.usgs.gov/RSQA/). 

Each RSQA study is a short-term assessment of wadeable 

streams in a targeted region, generally delineated by the 

U.S. Environmental Protection Agency (EPA) ecoregions 

(Omernik and Griffith, 2014). Between 75 and 100 streams are 

sampled in each RSQA study to investigate stream ecology 

and the effects of stressors that are primarily associated with 

urban development and agricultural land use. Wadeable 

streams are selected across gradients in urban or agricultural 

land use, depending on the dominant land use(s) in the region. 

Weekly water sampling typically is done for 4–12 weeks 

(depending on region and site characteristics) for a wide range 

of chemical constituents, and continuous monitoring of flow 

or stage and temperature is done at all stream sites. The timing 

of this water-quality (WQ) index period—defined as the 4- to 

12-week period during which weekly discrete water samples 

were collected and analyzed for water-quality constituents—is 

designed to capture the spring and(or) early summer growing 

season, when pesticide and fertilizer applications are highest. 

Data from the WQ index period characterizes water-quality 

conditions antecedent to the ecological surveys, during which 

streambed sediment is collected for chemical analyses and 

toxicity testing, and stream habitat and biological communities 

are assessed.
Introduction 3

A RSQA study was conducted in the Central California 

Foothills and Coastal Mountains ecoregion (Omernik and 

Griffith, 2014) in 2017. Designated as the California Stream 

Quality Assessment (CSQA), this study included a network 

of 85 streams and associated watersheds, and was the last of 

five NAWQA Cycle III regional stream-quality assessment 

studies (fig. 1); other studies were the Midwest Stream Quality 

Assessment in 2013 (Garrett and others, 2017), the Southeast 

Stream Quality Assessment in 2014 (Journey and others, 

2015), the Pacific Northwest Stream Quality Assessment in 

2015 (Sheibley and others, 2017), and the Northeast Stream 

Quality Assessment in 2016 (Coles and others, 2019). Like the 

three most recent RSQA studies, the 2017 CSQA study was 

done to investigate stressors along an urban gradient because 

urbanization is particularly intense from San Francisco 

and Oakland to San Jose. Additional sites were selected to 

represent agriculture in the region, which includes vineyards, 

orchards, and various row crops, as well as mixed land uses.

Purpose and Scope

This report describes the design and methods of the 

CSQA study (Van Metre and others, 2017b). The methods 

described include the collection and processing of water- and 

sediment- quality samples, and surveys of stream habitat and 

algal and macroinvertebrate communities, at 85 stream sites. 

Methods also are described for several focused studies done at 

subsets of sites, and for the procedures of laboratory analysis, 

quality assurance (QA) and quality control (QC), and data 

management.

–130° –120° –110° –100° –90° –80° –70°

45°

40°

35°

30°

25°

PACIFIC

OCEAN

ATLANTIC

OCEAN

CANADA

MEXICO

Basemap image is the intellectual property of Environmental Systems Research Institute (Esri) 

and is used herein under license. Copyright© 2014 Esri and it’s licensors. All rights reserved.

Base modified from ESRI digital data, 1:70,000 (Esri, 2009). Basemap of states from

U.S. Geological Survey 1:2,000,000 Digital Data. Albers Equal-Area Conic projection, 

standard parallels 29o 30' and 45o 30', central meridian –96o

0 125 250 500 MILES

0 125 250 500 KILOMETERS

GULF OF

MEXICO

CSQA

PNSQA

NESQA

MSQA

SESQA

EXPLANATION

Land cover

Open water

Urban

Scrub/grass

Forest/wetlands

Pasture/hay

Cultivated crops

Stream quality assessment

study-area boundary

Figure 1. Locations of the Regional Stream Quality Assessment studies across the United States. (CSQA, California Stream Quality 

Assessment; MSQA, Midwest Stream Quality Assessment; NESQA, Northeast Stream Quality Assessment; PNSQA, Pacific Northwest 

Stream Quality Assessment; SESQA, Southeast Stream Quality Assessment).
4 Design and Methods of the California Stream Quality Assessment, 2017

Study-Area Description

The 85 CSQA streams are distributed over much of 

the Central California Foothills and Coastal Mountains 

ecoregion, an EPA Level III ecoregion, where urbanization 

and agriculture in the larger valleys are associated with 

degradation of stream health (Ode and others, 2011). The 

following information describing the Central California 

Foothills and Coastal Mountains ecoregion (hereafter coastal 

California, modified from Griffith and others, 2016) is 

summarized from Wiken and others (2011) and Omernik and 

Griffith (2014).

A primary distinguishing characteristic of the coastal 

California ecoregion is its Mediterranean climate of hot 

dry summers and cool moist winters. The mean annual 

temperature ranges from approximately 14 degrees Celsius 

(°C) to 18 °C, and the frost-free period ranges from 180 to 

365 days. The mean annual precipitation is 548 millimeters 

(mm) and ranges from 200 to more than 1,400 mm on higher 

peaks in the northern portion of the ecoregion. Coastal fogs 

provide some moisture in the dry season. Vegetative cover 

is composed mainly of chaparral and oak woodlands, with 

grasslands occurring in some lower elevations and patches of 

pine at higher elevations. This ecoregion surrounds the lower 

and flatter Central California Valley ecoregion (although the 

CSQA sampled only on the western side of the Central Valley; 

fig. 2), and mostly consists of coastal terraces, some open 

low mountains or foothills, parallel ranges and valleys, and 

areas of irregular plains in the south and near the border of the 

Central California Valley ecoregion.

The geology of the coastal California ecoregion consists 

of Cenozoic marine and non-marine sedimentary rocks 

and Mesozoic granitic rocks; coarse sediments are found 

on colluvial slopes. Dominant soil orders include Alfisols, 

Entisols, and Mollisols, with a thermic soil temperature regime 

and xeric soil moisture regime. Streamflow in the region 

is mostly ephemeral and intermittent, with a few perennial 

streams entering from adjacent highland ecoregions. The 

region generally lacks lakes, but a few ponds and reservoirs 

occur. Large areas are in ranch lands grazed by domestic 

livestock, and some valleys are major agricultural centers, 

such as the Salinas Valley and the vineyards of Napa and 

Sonoma, but in general, little land has been cultivated. The 

highest levels of urban development are in the San Francisco 

Bay Area.
Introduction 5

Napa

Oakland

Salinas

San Francisco

San Jose

San Luis

Obispo

Santa Barbara

Santa Maria

Santa Rosa

Sonoma

Basemap image is the intellectual property of Environmental Systems Research Institute (Esri) and 

is used herein under license. Copyright© 2014 Esri and its licensors. All rights reserved. Base 

modified from Esri digital data, 1:72,000 (Esri and others, 2014). State outlines from U.S. Geological 

Survey National Map Web Mercator Projection World Geodetic System of 1984 (WGS 84)

0 25 50 MILES

0 25 50 KILOMETERS

CALIFORNIA

Land-cover data modified from the National Water

Quality Assessment wall-to-wall anthropogenic

land use trends (NWALT) dataset (Falcone, 2015).

PACIFIC OCEAN

 EXPLANATION

Land cover

Developed

Semi-developed

Crops/pasture/hay

Low usage

Site type

Urban

Agriculture

Mixed

Undeveloped

124°

40°

38°

36°

122° 120°

Figure 2. California Stream Quality Assessment study area, including sampling locations and generalized land cover. Site type 

indicates the dominant land use in the lower basin of the watershed. Land cover integrates land use from the National Water Quality 

Assessment wall-to-wall anthropogenic land use trends database (Falcone, 2015) and cropland from the Statewide Cropping Layer 

2014 (Land IQ, LLC, 2017; California Department of Water Resources, 2019).
6 Design and Methods of the California Stream Quality Assessment, 2017

Study Design

The CSQA study was designed to assess differences 

in stream quality associated with urban and agricultural 

development in the region and to identify and measure specific 

stressors potentially causing ecological impairment. To the 

extent possible, sites were selected to represent a full urban 

gradient (ranging from undeveloped to a high percentage 

of urban land use) as well as agricultural indicator basins 

(representing crops characteristic of the region and with 

minimal urban land). However, watersheds with mixtures 

of urban and agricultural uses are very common in coastal 

California, and the selection of some mixed land-use basins 

could not be avoided. The CSQA sites are located within a 

single Level III ecoregion to minimize natural variability in 

biological communities and allow for a better understanding 

of how anthropogenic factors might affect water quality and 

ecological condition.

The CSQA study followed the general study design 

for a RSQA study: sampling water- and sediment-quality 

at 75–100 wadeable streams across a region during a 4- to 

12-week WQ index period (4–6 weeks in CSQA). Meanwhile, 

continuous streamflow (or stage) and water temperature 

data were collected, and the CSQA study culminated in an 

ecological survey of the sampling reach of the stream at the 

end of the WQ index period.

The three elements of the RSQA studies can be 

characterized as comprehensive stressor assessments, focused 

studies, and ecological surveys. Comprehensive stressor 

assessments were designed to be conducted at all sites, 

including assessment of basic water quality (such as major 

ions, nutrients, pesticides) in all discrete water samples, 

additional water-quality constituents (such as mercury, 

organic wastewater indicators, algal toxins) in discrete water 

samples at least once during the WQ index period, selected 

WQ constituents (pesticides and pharmaceuticals) that were 

accumulated (integrated) by passive samplers deployed 

during the WQ index period, and streamflow or stage and 

temperature data collected continuously throughout the WQ 

index period. Focused studies were conducted at a subset of 

sites to assess selected stressors in more detail; these consisted 

of pesticides in daily and weekly composite samples collected 

by autosamplers, pesticides in biofilms, and radionuclides 

and other constituents in suspended sediment collected by 

passive samplers. At the end of the WQ index period, the 

ecological surveys assessed physical habitat, surveyed aquatic 

biota communities, and sampled bed sediment for chemical 

analysis and toxicity testing. In the CSQA study, algal and 

macroinvertebrate communities were sampled during the 

ecological surveys. Unlike other RSQA studies, fish were not 

surveyed in CSQA because of concerns that electro-fishing in 

the CSQA streams might adversely affect sensitive species. 

Dates of sample collection for all elements of CSQA are 

shown by site in appendix table 1.1.

The CSQA presented some challenges that were unique 

relative to the previous RSQA studies: a longer pesticide 

application season, combined with variation in the timing of 

pesticide applications from south to north, and the potential 

for streams to go dry during late spring and early summer, 

especially in the south. Timing of the sampling activities 

to coincide with peak pesticide applications, especially for 

the more toxic insecticides and fungicides, was desirable to 

capture the highest potential exposure. Pesticide applications 

in coastal California generally occur earlier in the south than 

in the north, and the CSQA sampling regime was designed 

to accommodate this difference. Sampling from March 

through June over the entire study area would have been 

desirable from the perspective of pesticide exposure, but 

some small- to medium-sized streams in coastal California 

are intermittent, generally only flowing for a few months 

in late winter and spring. To improve the likelihood that 

continuous flow conditions would persist throughout the 

sampling period, an early sampling period was chosen, and 

the sites were divided into a “Southern” group (n=36; table 1) 

and a “Northern” group (n=49). The water sampling period 

was offset by 3 weeks between the Southern sites (March 13 

to April 21, 2017; table 1) and the Northern sites (April 3 to 

May 12, 2017).

Site Selection Process

Candidate sites for the CSQA study were identified from 

active and historical (inactive) USGS streamgages (n=125) 

and from sites monitored by the California Department 

of Fish and Wildlife (n=435). A few candidate sites had 

streamgages nearby that were operated by the county (such 

as Contra Costa, Napa, San Luis Obispo, Solano) or city 

(Vacaville, Petaluma). Additional State and local agencies and 

institutions were consulted for information about candidate 

sites, including the California State Water Resources Control 

Board, North Coast Regional Water Quality Control Board, 

San Francisco Regional Water Quality Control Board, 

Central Coast Regional Water Quality Control Board, San 

Francisco Estuary Institute, California Department of Pesticide 

Regulation, and researchers from University of California at 

Davis and University of California at Berkeley. Several sites 

that had not been previously sampled were identified to fill 

gaps in the distribution of land-use settings relative to design 

objectives. A geospatial database was created that included 

land-cover characteristics for the watersheds of candidate sites 

(Qi and Nakagaki, 2020).
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asU.S. Geological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.[Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map ID 

number1

NWIS station 

number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS)

Northern 

or 

Southern 

group

Basin 

area

(km2)

Whole basin 

land use

Lower basin 

land use2

48 11179100 ALAMEDA C NR FREMONT CA CA_Alameda 37.566602 –122.001628 N 1,654.4 Urban_low Urban_med 18 382035121575501 ALAMO C A TULARE RD BR 

NR VACAVILLE CA

CA_Alamo 38.343083 –121.96535 N 55.9 Urban_low Urban_med 

73 364003121373501 ALISAL C A FAIRVIEW AVE NR 

SALINAS CA

CA_Alisal 36.66725 –121.626999 S 105.2 Ag_high Mixed 

47 11176900 ARROYO DE LA LAGUNA A 

VERONA CA

CA_ArroyoDeLaLa 37.626599 –121.883013 S 1,045.6 Urban_low Urban_med 

27 380410122315501 ARROYO SAN JOSE A DIGITAL 

DR NR NOVATO CA

CA_ArroyoDig 38.069497 –122.531997 N 14.1 Urban_med Urban_med 

29 11182400 ARROYO DEL HAMBRE A 

MARTINEZ CA

CA_ArroyoMart 38.003255 –122.129965 N 38.0 Urban_low Urban_low 

28 380345122345201 ARROYO SAN JOSE A 

FAIRWAY DR NR NOVATO CA

CA_ArroyoNov 38.062272 –122.581152 N 2.3 Undeveloped Undevelope

75 11152000 ARROYO SECO NR SOLEDAD 

CA

CA_ArroyoSeco 36.280521 –121.322706 S 625.4 Undeveloped Undevelope

78 352934120395501 ATASCADERO C A W MALL BR 

A ATASCADERO CA

CA_Atascadero 35.492883 –120.665164 S 50.2 Urban_low Urban_med 

46 11181008 CASTRO VALLEY C A 

HAYWARD CA

CA_Castro 37.679931 –122.080519 N 14.4 Urban_high Urban_high 

79 352127120484501 CHORRO C A CHORRO C RD 

NR MORRO BAY CA

CA_Chorro 35.357508 –120.812464 S 105.0 Urban_low Ag_low 

74 363608121255201 CHUALAR C A CHUALAR 

CANYON RD NR CHUALAR CA

CA_ChuChuChu 36.6022 –121.430997 S 58.6 Undeveloped Undevelope

14 11465690 COLGAN C NR SANTA ROSA 

CA

CA_Colgan 38.402135 –122.733043 N 9.0 Urban_high Urban_high 

8 11456500 CONN C NR OAKVILLE CA CA_ConnOak 38.447278 –122.380556 N 146.1 Ag_low Ag_high 

17 11465660 COPELAND C A ROHNERT 

PARK CA

CA_Copeland 38.343248 –122.701932 N 14.9 Urban_med Urban_high 

66 11159200 CORRALITOS C A FREEDOM 

CA

CA_Corralitos 36.939397 –121.770506 S 70.8 Mixed Mixed 

33 11460000 CORTE MADERA C A ROSS CA CA_Corte 37.962979 –122.556922 N 46.7 Urban_med Urban_med 
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asGeological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.—Continued [Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map iden- tification number1 NWIS station number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS) Northern or Southern group Basin area (km2) Whole basin land use Lower basin land use2 

52 372303121542901 COYOTE C BL CHARCOT AVE NR SAN JOSE CA CA_CoyoteChar 37.384453 –121.907849 N 809.7 Urban_low Urban_high 57 371554121474101 COYOTE C A COYOTE RD NR SAN JOSE CA CA_CoyoteCoyote 37.264939 –121.794658 S 594.4 Urban_low Urban_med 60 11169800 COYOTE C NR GILROY CA CA_CoyoteGil 37.077723 –121.494383 S 282.5 Undeveloped Undevelope44 11180900 CROW C NR HAYWARD CA CA_Crow 37.70493 –122.043851 N 27.3 Urban_low Urban_low 

2 11465350 DRY C NR MOUTH NR HEALDSBURG CA CA_DryMouth 38.58741 –122.862216 N 565.0 Ag_low Mixed 

72 364138121373701 GABILAN C AB E LAUREL DR NR SALINAS CA CA_GabilanEastL 36.693963 –121.627252 S 107.7 Ag_low Mixed 69 11152600 GABILAN C NR SALINAS CA CA_GabilanSal 36.755792 –121.610501 S 95.1 Undeveloped Ag_low 30 375819122035801 GRAYSON C A GOLF CLUB RD NR PLEASANT HILL CA CA_Grayson 37.972091 –122.066128 N 36.5 Urban_high Urban_high 12 382619122531401 GREEN VALLEY C A GRATON CA CA_Green 38.438729 –122.887208 N 25.7 Mixed Mixed 53 11169025 GUADALUPE R ABV HWY 101 

A SAN JOSE CA

CA_GuadalupeA 37.37383 –121.933013 S 406.4 Urban_med Urban_high 

54 371814121525601 GUADALUPE R A WILLOW 

GLEN WAY NR SAN JOSE CA

CA_GuadalupeB 37.303947 –121.88225 S 219.0 Urban_med Urban_high 

38 375257122050001 LAS TRAMPAS C A 

LAFAYETTE CA

CA_LasTrampas 37.882397 –122.099997 N 20.4 Urban_low Urban_med 

22 381740122395901 LICHAU C A PENNGROVE CA CA_Lichau 38.294481 –122.666361 N 20.0 Mixed Mixed 62 11153650 LLAGAS C NR GILROY CA_LlagasGilroy 36.987449 –121.527162 S 218.9 Mixed Mixed 59 370512121361901 LLAGAS C A SAN MARTIN 

AVE A SAN MARTIN CA

CA_LlagasMartin 37.086742 –121.605206 S 73.0 Urban_low Mixed 

58 11153470 LLAGAS C AB CHESBRO RES 

NR MORGAN HILL CA

CA_LlagasMorgan 37.148333 –121.768333 S 24.9 Undeveloped Undevelope

82 11141280 LOPEZ C NR ARROYO 

GRANDE CA

CA_Lopez 35.23553 –120.472386 S 54.1 Undeveloped Undevelope

55 371738121555901 LOS GATOS C A E HAMILTON 

AVE NR CAMPBELL CA

CA_LosGatos 37.2939 –121.933 S 119.1 Urban_low Urban_high 
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asGeological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.—Continued[Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map identification 

number1

NWIS station 

number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS)

Northern 

or 

Southern 

group

Basin 

area

(km2)

Whole basin 

land use

Lower basin 

land use2

1 383719122462501 MAACAMA C A CHALK HILL 

RD BR NR HEALDSBURG CA

CA_Maacama 38.621958 –122.773689 N 118.0 Ag_low Ag_low 

7 11466800 MARK WEST C NR MIRABEL 

HEIGHTS CA

CA_MarkWMir 38.494078 –122.853326 N 652.0 Mixed Mixed 

5 383109122363301 MARK WEST C A TARWATER 

RD NR CALISTOGA CA

CA_MarkWTar 38.519047 –122.609222 N 10.5 Undeveloped Undevelope

51 372500122081201 MATADERO C A JOSINA AVE A 

PALO ALTO CA

CA_Matadero 37.4168 –122.136592 S 16.1 Urban_med Urban_high 

11 11466170 MATANZAS C A SANTA ROSA 

CA

CA_Matanzas 38.438801 –122.702487 N 57.0 Mixed Urban_med 

19 382017122161101 MILLIKEN C BL HEDGESIDE 

AVE NR NAPA CA

CA_Milliken 38.338155 –122.269874 N 45.0 Urban_low Urban_low 

35 375701121564401 MT DIABLO C A CLAYTON CA CA_MtDiablo 37.950364 –121.945647 N 42.7 Urban_low Urban_med 77 11148900 NACIMIENTO R BL SAPAQUE 

C NR BRYSON CA

CA_NaciBryson 35.788579 –121.093805 S 403.3 Undeveloped Undevelope

3 383321122302101 NAPA R A BALE LN NR DEER 

PARK CA

CA_NapaBale 38.555946 –122.505915 N 116.5 Ag_low Ag_low 

21 11458300 NAPA C A NAPA CA_NapaNapa 38.301859 –122.303863 N 38.9 Urban_low Urban_med 71 364155121363901 NATIVIDAD C NR SALINAS CA CA_Natividad 36.6987 –121.610722 S 25.9 Ag_low Mixed 15 382346122521201 UNNAMED TRIB A 

MONTGOMERY RD NR SEBASTOPOL CA

CA_NoNameMonty 38.396125 –122.870039 N 14.9 Mixed Mixed 

64 365718121444301 UNNAMED TRIB A PAULSEN 

RD NR FREEDOM CA

CA_NoNamePaul 36.955181 –121.745631 S 42.8 Mixed Mixed 

26 11459500 NOVATO C A NOVATO CA CA_Novato 38.107698 –122.579981 N 46.5 Urban_low Urban_med 83 11141050 ORCUTT C NR ORCUTT CA CA_Orcutt 34.88359 –120.494888 S 49.3 Urban_low Mixed 63 365736121250801 PACHECO C A SAN FELIPE RD 

NR DUNNEVILLE CA

CA_Pacheco 36.959818 –121.418968 S 395.3 Undeveloped Ag_high 

68 11159000 PAJARO R A CHITTENDEN CA CA_PajaroChit 36.900231 –121.597721 S 3,071.5 Ag_low Mixed 67 11159500 PAJARO R A WATSONVILLE 

CA

CA_PajaroWat 36.905297 –121.7514 S 3,284.6 Ag_low Mixed 
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asGeological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.—Continued [Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map iden- tification number1 NWIS station number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS) Northern or Southern group Basin area (km2) Whole basin land use Lower basin land use2 

24 381519122385601 PETALUMA R NR PETALUMA CA CA_Petaluma 38.255189 –122.648971 N 87.1 Mixed Mixed 31 375807122124001 PINOLE C BL ALHAMBRA VALLEY RD NR PINOLE CA CA_Pinole 37.968652 –122.210997 N 13.4 Undeveloped Undevelope70 11152650 RECLAMATION DITCH NR SALINAS CA CA_Reclamation 36.704959 –121.704948 S 274.6 Mixed Mixed 

4 383305122311901 RITCHEY C NR DEER PARK CA CA_Ritchey 38.551424 –122.521015 N 6.4 Undeveloped Undevelope

76 11150500 SALINAS R NR BRADLEY CA CA_Salinas 35.930243 –120.868791 S 6,570.4 Undeveloped Undevelope49 372716122080801 SAN FRANCISQUITO C DS OF NEWELL RD BR A PALO ALTO CA_SanFranPalo 37.454383 –122.136631 N 99.9 Urban_med Urban_high 50 11164500 SAN FRANCISQUITO C A STANFORD UNIVERSITY CA CA_SanFranStan 37.423273 –122.18941 S 97.4 Urban_med Urban_med 43 374336122095801 SAN LEANDRO C A ALVARADO ST A SAN LEANDRO CA CA_SanLeandro 37.726608 –122.166178 N 114.8 Urban_low Urban_high 81 351436120405201 SAN LUIS OBISPO C A LOS 

OSOS VLY RD NR SAN LUIS OB

CA_SanLObispo 35.243333 –120.681111 S 107.2 Urban_low Urban_med 

45 11181000 SAN LORENZO C A HAYWARD 

CA

CA_SanLorenzo 37.685486 –122.064407 N 97.8 Urban_low Urban_med 

39 375220122104201 SAN PABLO C A MORAGA 

WAY A ORINDA CA

CA_SanPabloMor 37.864508 –122.172306 N 4.4 Urban_med Urban_med 

37 375312122113501 SAN PABLO C A ORINDA CA CA_SanPabloOr 37.886553 –122.193119 N 20.9 Urban_med Urban_med 34 375746122195501 SAN PABLO C A EL PORTAL 

DR A SAN PABLO CA

CA_SanPabloPort 37.9628 –122.331997 N 104.0 Urban_med Urban_med 

40 374933122001301 SAN RAMON C A LA GONDA 

WAY A DANVILLE CA

CA_SanRamonDan 37.825711 –122.003539 N 87.5 Urban_med Urban_med 

42 11182500 SAN RAMON C A SAN RAMON 

CA

CA_SanRamonSan 37.772983 –121.994682 N 15.6 Urban_low Urban_low 

13 11466200 SANTA ROSA C A SANTA 

ROSA CA

CA_SantaSanta 38.436579 –122.72471 N 144.6 Urban_low Urban_high 
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asGeological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.—Continued[Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map identification 

number1

NWIS station 

number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS)

Northern 

or 

Southern 

group

Basin 

area

(km2)

Whole basin 

land use

Lower basin 

land use2

9 11466320 SANTA ROSA C A 

WILLOWSIDE RD NR SANTA ROSA CA

CA_SantaWillow 38.44519 –122.807213 N 197.5 Urban_med Mixed 

84 11135250 SANTA YNEZ R A 13TH ST 

BRIDGE A VAFB NR LOMPOC CA

CA_SantaYnezLom 34.676617 –120.553389 S 2,283.2 Undeveloped Ag_high 

85 11128500 SANTA YNEZ R A SOLVANG 

CA

CA_SantaYnezSol 34.584987 –120.144593 S 1,498.9 Undeveloped Mixed 

56 371620122005801 SARATOGA C A BRAEMAR DR 

A SARATOGA CA

CA_Saratoga 37.272252 –122.016288 S 26.2 Urban_low Urban_med 

41 374708122132801 SAUSAL C A OAKLAND CA CA_Sausal 37.785681 –122.224339 N 10.2 Urban_med Urban_high 10 382634122315201 SONOMA C A ADOBE CYN RD 

NR KENWOOD CA

CA_SonomaAdobe 38.4427 –122.531 N 10.3 Undeveloped Undevelope

20 11458500 SONOMA C A AGUA 

CALIENTE CA

CA_SonomaAgua 38.323247 –122.494426 N 150.5 Mixed Mixed 

23 381556122280201 SONOMA C A WATMAUGH RD 

BR NR SONOMA CA

CA_SonomaWat 38.265797 –122.467397 N 188.0 Mixed Mixed 

80 351725120395901 STENNER C A MURRAY AVE A 

SAN LUIS OBISPO CA

CA_Stenner 35.2904 –120.666319 S 23.2 Urban_low Urban_low 

25 381441122064301 SUISUN C A ROCKVILLE CA CA_Suisan 38.244797 –122.111997 N 125.5 Ag_low Ag_high 65 365634121264001 TEQUISQUITA SLOUGH A 

SHORE RD NR DUNNEVILLE CA

CA_Tequisquita 36.9427 –121.4445 S 301.6 Ag_low Ag_high 

16 382245122001601 ULATIS C A FARRELL RD NR 

VACAVILLE CA

CA_Ulatis 38.379169 –122.004319 N 27.9 Ag_low Mixed 

61 365955121350601 UVAS C A MILLER AVE A 

GILROY CA

CA_UvasMiller 36.998533 –121.584958 S 178.7 Undeveloped Mixed 

36 375413122033301 WALNUT C A CIVIC DR A 

WALNUT CREEK CA

CA_Walnut 37.903669 –122.059217 N 204.4 Urban_med Urban_high 

32 375808122172601 WILKIE C A SANTA RITA RD 

NR RICHMOND CA

CA_Wilkie 37.968842 –122.290553 N 3.2 Urban_high Urban_high 
Table 1. Characteristics of stream watersheds in the Central California Foothills and Coastal Mountains ecoregion of the United States that were asGeological Survey National Water-Quality Assessment Project, California Stream Quality Assessment, in 2017.—Continued [Latitude and longitude of water quality sample location based on the North American Datum of 1983 and shown in decimal degrees. The column heading “Northern or Southerlocation of sites in the San Francisco Bay area; sampling began the week of March 13, 2017, for the Southern group and April 3, 2017, for the Northern group. Sampling frequenwater samples collected at that site. Abbreviations: ID, identification; km2, square kilometer; NWIS, U.S. Geological Survey National Water Information System database; N, n

Map iden- tification number1 NWIS station number NWIS station name Field identifier Latitude (NWIS) Longitude (NWIS) Northern or Southern group Basin area (km2) Whole basin land use Lower basin land use2 

6 383039122502401 WINDSOR C A MARK WEST STATION RD NR WINDSOR CA CA_Windsor 38.510957 –122.839956 N 65.1 Mixed Mixed 

1Map identification number refers to site numbers in figure 3. 2Lower basin land use indicates the dominant land use in the lower part of the watershed extending 5 kilometers from the sampling location. Land-use subcategories are defin3Major site type, based on dominant land use in lower basin. Site types are shown in figure 2.
Study Design 13

Watershed delineations and characteristics were 

available for streams with active USGS streamgages. 

For other candidate sites, catchment boundaries from the 

National Hydrography Dataset Plus (NHDPlus Version 2; 

U.S. Environmental Protection Agency and U.S. Geological 

Survey, 2012) were used as the watershed boundaries by 

selecting all upstream catchments from the segment on 

which the candidate site was located. Nationally available, 

digital geographic information systems (GIS) data layers (for 

example, the National Land Cover Database [NLCD], Homer 

and others, 2015) were overlain on the catchment-derived 

watersheds, and characteristics of the watersheds were 

assessed and summarized from these data layers for use during 

site selection.

After initial screening, based on GIS characteristics 

and prioritization of gaged and historically monitored sites, 

the remaining sites were evaluated with the use of satellite 

imagery (Google Earth®, https://www.google.com/earth/) for 

general watershed characteristics, potential stressor sources 

(for example, water treatment plants, industrial complexes, 

golf courses), and accessible sampling reach locations. An 

objective during this step of site selection was to distribute 

sites widely across the region and to represent the full range of 

undeveloped, agricultural, and urban land uses present. This 

“desk-top reconnaissance” was applied to about 330 sites, 

of which 129 were selected for field reconnaissance. A 

field reconnaissance of these sites was conducted by USGS 

staff during winter and spring 2017. Field observations for 

each site included evaluating the site for access and safety, 

assessing general stream characteristics to determine locations 

for water-quality sampling, and identifying a 150-meter 

(m) stream reach with riffle habitat suitable for conducting 

ecological surveys. Field notes and photography were 

recorded onsite by using field-reconnaissance forms on an 

electronic tablet; afterwards, information from these forms 

was compiled into spreadsheets for use in site review and 

final selection.

Final site selection was based on the field reconnaissance 

and on the distribution of land use in the candidate watersheds, 

again with the objective of representing the range of urban 

and agricultural development in the region. The distribution 

of the final 85 sites by land-use type was evaluated at two 

scales using the NAWQA Wall-to-Wall Anthropogenic Land 

Use Trends (NWALT) data layers (Falcone, 2015) for whole 

drainage basins (WB) and for the lower drainage basin only 

(LB; table 1). The LB boundaries were created by intersecting 

a 5-kilometer (km) buffer around the sampling site within 

the drainage basin boundary, consistent with the 5-km scale 

used by the State of California to assess ecological condition 

and contamination in streams (Ode and others, 2011). 

The purpose of using the LB approach was to capture the 

influence on water quality of land use upstream and close 

to the sampling location. Some headwater streams flow 

from relatively undeveloped hills of the California Coast 

Ranges into an intensely developed valley. In such cases, the 

WB characteristics might indicate a relatively undeveloped 

basin, even though the site might be strongly affected by 

proximal development.

The NWALT data provided a more detailed delineation 

of urban land uses than is available in NLCD (U.S. Geological 

Survey, 2014). A two-step process was applied, starting with 

the NWALT data, to assign a land-use category to each site. 

NWALT land-use “classes” (as described in Falcone, 2015, 

such as high density residential developed and cultivated 

crops) were combined into summed land-use “types” (such as 

Total Urban or Total Agriculture) to represent the types and 

degree of urban development and agriculture in the watersheds 

of sites (table 2). Each site was then assigned to a land-use 

category (Urban, Agriculture, Mixed, or Undeveloped) and 

a “land-use subcategory” (such as Urban_high, Ag_high, 

Undeveloped) on the basis of combinations and threshold 

levels of the various land-use types in the watershed (table 3). 

On the basis of visual inspections of the basins in satellite 

imagery (Google Earth®), NWALT data occasionally appeared 

to misrepresent some types of agricultural land in California; 

specifically, nurseries, greenhouses, orchards, and vineyards 

were classified in some cases as urban or semi-developed 

land. Such apparent errors were confirmed by consulting the 

Statewide Crop Mapping 2014 dataset (Land IQ, LLC, 2017), 

which is the official dataset of the California Department 

of Water Resources (CDWR) for determining agricultural 

land use and irrigated acres (California Department of Water 

Resources, 2019) and which indicated that the percentage 

of agricultural land was underestimated in some basins. In 

these cases, the assigned land-use category was adjusted to 

reflect the visual characteristics (such crop fields, greenhouses, 

orchards) and cropping patterns from the CDWR dataset.

The final 85 sites are widely distributed across the region 

(fig. 2). Individual site locations are shown in fig. 3, numbered 

in relation to site names in table 1. There were more mixed 

sites and fewer undeveloped sites for watershed delineations at 

the LB scale than at the WB scale (table 4), possibly because 

there was generally more undeveloped land in the upper basin. 

This intensification of development in the vicinity of the 

sampling site is seen by comparing plots of the WB and LB 

of site distributions in relation to two primary land-use types: 

total urban and cropland (fig. 4). In each of the WB and LB 

delineations, a large subset of sites represented a full urban 

gradient reasonably well, without the complicating factor of 

high levels of agricultural land use also within the watersheds. 

More mixed land-use sites were apparent at the LB scale 

(fig. 4; table 4). Of the 85 sites, 39 were classified as having 

some degree of urban land use at both the LB and WB scales; 

however, only 5 sites were classified as Agricultural sites 

at both the LB and WB scales. Although there is extensive 

agriculture in some watersheds in the region, most of it is 

mixed with urban development.
14 Design and Methods of the California Stream Quality Assessment, 2017

Table 2. Land-use classes from the National Water Quality Assessment wall-to-wall anthropogenic land use trends database were 

summed to create land-use types.

[The parenthetical numbers are the assigned numeric class designations from the National Water Quality Assessment wall-to-wall anthropogenic land use trends 

(NWALT) dataset (Falcone, 2015). Thresholds were applied to these land-use types to assign each site to a land-use category (as in table 3). Abbreviation: —, 

not applicable]

NWALT land-use classes1

Land-use types

Dense 

urban

Total 

urban

Extended 

urban Cropland Total agriculture

Total 

developed

Low 

usage

 Water (11) — — — — — — X

 Wetlands (12) — — — — — — X

 Dev_MajorTransp (21) X X X — — X —

 Dev_CommServices (22) X X X — — X —

 Dev_IndusMilitary (23) X X X — — X —

 Dev_Recreation (24) — X X — — X —

 Dev_ResidHigh (25) — X X — — X —

 Dev_ResidLowMed (26) — X X — — X —

Dev_Other (27) — X X — — X

 SemiDev_UrbHigh (31) — (2) X — — X —

 SemiDev_UrbLowMed (32) — — X — — X —

SemiDev_AnthroOth (33) — — X — — X

 Prod_Mining (41) — — — — — X —

 Prod_Crops (43) — — — X X X —

 Prod_PastureHay (44) — — — — X X —

 Prod_GrazingPot (45) — — — — X X —

 LowUse (50) — — — — — — X

 VeryLowUse_Conserv (60) — — — — — — X

1Dev_CommServices, developed, commercial/services, class 22; Dev_IndusMilitary, developed, industrial/military, class 23; Dev_MajorTransp, developed, 

major transportation, class 21; Dev_Other, developed, other, class 27; Dev_Recreation, developed, recreation, class 24; Dev_ResidHigh, developed, residential 

high density, class 25; Dev_ResidLowMed, developed, residential low-medium density, class 26; SemiDev_AnthroOth, semi-developed, anthropogenic other, 

class 33; SemiDev_UrbHigh, semideveloped, urban interface high, class 31; SemiDev_UrbLowMed, semi-developed, urban interface low-medium, class 32; 

Prod_Crops, production, crops, class 43; Prod_GrazingPot, production, grazing potential, class 45; Prod_Mining, production, mining/extraction, class 41; Prod_

PastureHay, production, pasture/hay, class 44; LowUse, no other land use, class 50; VeryLowUse_Conserv, no other land use and in a protected area, conservation, class 60; Water, water, class 11; Wetlands, wetlands, class 12.

2For the California Stream Quality Assessment study, total urban excluded the SemiDev_UrbHigh class because in California, this NWALT class sometimes 

mischaracterized agricultural land containing scattered buildings (such as vineyards, nurseries) as semi-developed urban high. In other Regional Stream Quality 

Assessment studies, however, total urban included the SemiDev_UrbHigh class.
Study Design 15

Table 3. Thresholds and combinations of land-use types used to assign sites to unique land-use categories.

[Land-use types used in the conditions below are defined in table 2, and are based on land-use data from the National Water Quality Assessment wall-to-wall 

anthropogenic land use trends (NWALT) dataset (Falcone, 2015). Abbreviations: >, greater than; %, percent; <, less than; —, not applicable]

Land use 

subcategory

Conditions (all must be met, except as indicated in OR statements)

Urban AND Agriculture AND Other

Major land use category: Urban

 Urban_high>20% Dense urban OR >75% Total urban<10% Cropland AND <25% Total agricultu

 Urban_med25–75% Total urban<10% Cropland AND <25% Total agricultu

 Urban_low5–25% Total urban OR >25% Extended urban<10% Cropland AND <25% Total agricultre  Total urban > Crop

 Major land use category: Agriculture

 Ag_high<10% Total urban AND <25% Extended urban>25% Cropla

 Ag_low<10% Total urban AND <25% Extended urban5–25% Cropland OR >25% Total agricultre  Crops > Total u

Major land use category: Mixed

 Mixed>10% Total urban OR >25% Extended urban>10% Cropland OR >25% Total agricultr

Major land use category: Undeveloped

 Undeveloped<5% Total urban AND <25% Extended urban<5% Cropland AND <25% Total agricultu

Table 4. Distribution of 85 California Stream Quality Assessment 

sites by land-use category for the whole basin and lower basin 

watershed delineations.

[Land-use categories are defined in table 3.]

Land-use category Whole basin Lower basin

 Urban_high 4 15

 Urban_med 15 20

 Urban_low 24 5

 Ag_high 1 5

 Ag_low 11 4

 Mixed 13 24

 Undeveloped 17 12
16 Design and Methods of the California Stream Quality Assessment, 2017

74

78

79

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81

75

76

77

82

83

84

85

122° 120°

38°

36°

0 15 30 60 MILES

0 15 30 60 KILOMETERS

Basemap image is the intellectual property of Environmental Systems Research 

Institute (Esri) and is used herein under license. Copyright© 2014 Esri and its 

licensors. All rights reserved. Base modified from Esri digital data, 1:70,000 

(Esri, 2009). Basemap of states from U.S. Geological Survey digital data, 1:2,000,000.

Albers Equal-Area Conic projection, standard parallels 45° 30' and 60° 30', central

meridian –120°, North American Datum of 1983

EXPLANATION

Lower basin land use

Ag_high

Ag_low

Mixed

Undeveloped

Urban_high

Urban_med

Urban_low

Map identification

number

77

CALIFORNIA

NEVADA

1

3

4 5

6

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9

2

8 10 12

15

16

18 19

22

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28 30 34 32 31

41

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PACIFIC OCEAN

Figure 3. Locations of the 85 sites sampled for the California Stream Quality Assessment study, 2017. Sites are color-coded by lower 

basin land-use subcategory (as defined in table 3). Site names are listed by map identification number in table 1.
Study Design 17

100

80

60

40

20

0

0 20 40 60 80 100

Total urban, in percent

100

80

60

40

20

0

Total urban, in percent

Cropland, in percent

0 20 40 60 80 100

Cropland, in percent

A. Whole basin

B. Lower basin

Figure 4. Distribution of 85 California Stream Quality Assessment sites in relation to 

percent of cropland and percent of total urban (as defined in table 2) for A, the whole 

basin; and B, lower basin watershed delineation approaches. Data are from Qi and 

Nakagaki (2020).
18 Design and Methods of the California Stream Quality Assessment, 2017

Sample Collection and Processing

The types of data and the intervals at which samples 

were collected varied among the sites according to land-cover 

type and associated potential stressors. Data collection and 

sampling routines were categorized nominally by three 

study-design components (table 5). The comprehensive 

stressor assessments identify the various water-quality 

constituents that were collected at all sites. Although the 

study design called for measuring streamflow or stage and 

continuous temperature at all sites, some sites are missing 

stage or temperature data because pressure or temperature 

sensors were either not deployed or were lost in the field 

owing to high flow conditions. The focused studies component 

was composed of limited investigations at subsets of streams 

that focused on the occurrence and timing of specific stressors 

potentially affecting the condition of those streams. The 

ecological surveys component identified sampling activities 

associated with the ecological surveys done at the end of the 

index period at all sites.

The various constituents in each study design component 

are characterized in table 5 by the time interval at which they 

were collected: discrete, integrated, or continuous. Discrete 

samples characterized stream conditions at a specific point in 

time and could be collected at multiple times during the study 

(for example, “Basic quality of water (QW)” constituents, 

table 5) or collected only once during the study (for example, 

“N and O isotopes,” table 5). Integrated data were collected by 

passive sampling devices that were deployed during the study 

to represent an average or cumulative condition of the stream 

(for example, polar organic chemical integrative sampler; 

POCIS, table 5). Continuous data (such as streamflow, stage, 

temperature; table 5) were recorded at 15-minute intervals. 

All constituents included in Ecological Surveys (table 5) 

were measured once to represent conditions at a point in time 

and, therefore, the data are discrete; however, because these 

constituents generally acclimate to environmental variations 

over time, they typically reflect integrated conditions.

USGS staff who participated in the CSQA study 

received training before data collection activities, including 

instructions specific to water-quality sampling, focused 

studies, and ecological surveys. For example, the use 

of low-level analytical methods necessitated that water 

samples be collected according to “parts-per-billion” 

protocols (U.S. Geological Survey, 2006). During weeks 

when water-quality data were collected at all 85 sites, nine 

2-person teams of USGS staff were deployed. To ensure 

consistency among the water-quality teams, training for the 

collection and processing of water-quality samples occurred 

in February 2017 for all personnel involved with sample 

collection. Classroom water-quality training was followed 

by field-training exercises to work through all sampling and 

processing procedures in the field before the start of sampling. 

The sample collection timelines, sample types collected 

at sites, and sample collection, processing, and handling 

procedures are summarized in appendix 1 and described 

briefly here.

Ecological survey teams were trained in consistent 

sampling protocols, including State of California protocols for 

the collection of algae and aquatic macroinvertebrates (Ode 

and others, 2016), and USGS protocols for habitat surveys 

(Fitzpatrick and others, 1998) and bed-sediment collection 

(Shelton and Capel, 1994; Radtke, 2005). Before beginning 

the sampling trip, participants gathered at a local stream and 

instructors demonstrated the various protocols for collecting 

each sample type. The participants completed a full ecological 

collection at the training location. The ecological sampling 

coordinator visited each 5-person team during the sampling 

trip to verify techniques and clarify any questions.

Comprehensive Stressor Assessments

To allocate resources effectively among the 85 sites, 

various water-quality constituents were sampled at different 

frequencies during the study; the differences in sampling 

among sites generally were based on intensities of watershed 

development. The WQ index period, described in the 

“Background” section, was 6 weeks for 74 of the 85 sites and 

4 weeks for the other 11 sites (all of which were classified 

as “Undeveloped” at both the WB and LB scales). These 

undeveloped sites were sampled during the last 4 weeks of the 

6-week study period.

The 6-week WQ index period was March 13 to April 21, 

2017, for the Southern sites, and April 3 to May 12 for the 

Northern sites. Details of the sampling schedule indicating the 

weeks that constituents were sampled at individual sites are 

provided in appendix 1, table 1.1.
Table 5. Summary of data collected at the California Stream Quality Assessment sites in 2017.[Constituents are categorized by the study-design components: Comprehensive Stressor Assessments, Focused Studies, and Ecological Surveys. Notes and abbreviations: See foquality of water (QW) constituents. Abbreviations: C, continuous sample; D, discrete samples; I, integrative sample. Numerical value in cell indicates number of discrete samsample collected; —, not sampled. Streamflow or stage: Egage, gaging station for an external agency other than U.S. Geological Survey (USGS); Gage, USGS gaging station; installed to record stream stage. Ecological Surveys were conducted once at sites near the end of the water-quality index period: Aquatic Biota, invertebrate and algal samples cSediment: Tx, two temporal samples were collected prior to collecting sediment during ecological survey; Sediment Toxicity Test, sediment tested on survival of invertebrates: Hyalella. Other abbreviations: N, nitrogen; NWIS; U.S. Geological Survey National Water Information System database; O, oxygen; POCIS, polar organic chemical integrativsediment]

Site information Comprehensive stressor assessments Focused studies 

NWIS station 

number Field identifier

Basic 

QW1

(D)

Mercury

(D)

Organic 

waste 

indicators

(D)

Pharmaceuticals

(D)

Glyphosate 

analysis

(D)

N and O 

isotopes

(D)

Algal 

toxins

(D)

POCIS

(I)2

Streamflow or 

stage

(C)3

Temperature

(C)3

Pesticide 

autosampler

(I)

Biofilm 

pesticides

(I)

SS 

passive 

sampler

(I)

Aqua

bio

(D

11179100 CA_Alameda 6 3 3 3 2 1 1 — Gage — — — — x 382035121575501 CA_Alamo 6 3 3 3 2 1 1 — Egage — — x — x 364003121373501 CA_Alisal 6 3 3 3 2 1 1 — — x — — — x 11176900 CA_ArroyoDeLaLa 6 3 3 3 2 1 1 x Gage x — x — x 380410122315501 CA_ArroyoDig 6 3 3 3 2 1 1 x PT x — x — x 11182400 CA_ArroyoMart 6 3 3 3 2 1 1 x — — — x — x 380345122345201 CA_ArroyoNov 4 2 1 1 — 1 1 x — — — x — x 11152000 CA_ArroyoSeco 4 2 1 1 — 1 1 — Gage x — x — x 352934120395501 CA_Atascadero 6 3 3 3 2 1 1 x — x — x — x 11181008 CA_Castro 6 3 3 3 2 1 1 x Gage — L — x x 352127120484501 CA_Chorro 6 3 3 3 2 1 1 x PT x — — — x 363608121255201 CA_ChuChuChu 4 2 1 1 — 1 1 x — — — x — x 11465690 CA_Colgan 6 3 3 3 2 1 1 x Gage x — x — x 11456500 CA_ConnOak 6 3 3 3 2 1 1 x Gage — x x — x 11465660 CA_Copeland 6 3 3 3 2 1 1 x Gage x — x — x 11159200 CA_Corralitos 6 3 3 3 2 1 3 — Gage x — x — x 11460000 CA_Corte 6 3 3 3 2 1 1 x Gage x — x — x 372303121542901 CA_CoyoteChar 6 3 3 3 2 1 1 — — — x — — x 371554121474101 CA_CoyoteCoyote 6 3 3 3 2 1 1 x — — — x — x 11169800 CA_CoyoteGil 4 2 1 1 — 1 1 x Gage x — — — x 11180900 CA_Crow 6 3 3 3 2 1 1 x Gage — — — x x 11465350 CA_DryMouth 6 3 3 3 2 1 1 x Gage — — — — — 364138121373701 CA_GabilanEastL 6 3 3 3 2 1 1 x — x — x — x 11152600 CA_GabilanSal 6 3 3 3 2 1 1 x — x — — — x 375819122035801 CA_Grayson 6 3 3 3 2 1 1 x — — — — — x 382619122531401 CA_Green 6 3 3 3 2 1 1 x — — — x — x 11169025 CA_GuadalupeA 6 3 3 3 2 1 1 x Gage — — — — x 371814121525601 CA_GuadalupeB 6 3 3 3 2 1 1 — — — — — — x 375257122050001 CA_LasTrampas 6 3 3 3 2 1 1 x — — — x — x 381740122395901 CA_Lichau 6 3 3 3 2 1 1 x PT x — x — x 11153650 CA_LlagasGilroy 6 3 3 3 2 1 3 x Gage — — x — x 370512121361901 CA_LlagasMartin 6 3 3 3 2 1 3 x PT x — — — x 11153470 CA_LlagasMorgan 4 2 1 1 — 1 1 x — — — — — x 11141280 CA_Lopez 4 2 1 1 — 1 1 x Gage x — x — x 371738121555901 CA_LosGatos 6 3 3 3 2 1 1 x — — — x — x 383719122462501 CA_Maacama 6 3 3 3 2 1 1 x PT x — x — x 
Table 5. Summary of data collected at the California Stream Quality Assessment sites in 2017.—Continued [Constituents are categorized by the study-design components: Comprehensive Stressor Assessments, Focused Studies, and Ecological Surveys. Notes and abbreviations: See foquality of water (QW) constituents. Abbreviations: C, continuous sample; D, discrete samples; I, integrative sample. Numerical value in cell indicates number of discrete samsample collected; —, not sampled. Streamflow or stage: Egage, gaging station for an external agency other than U.S. Geological Survey (USGS); Gage, USGS gaging station; installed to record stream stage. Ecological Surveys were conducted once at sites near the end of the water-quality index period: Aquatic Biota, invertebrate and algal samples cSediment: Tx, two temporal samples were collected prior to collecting sediment during ecological survey; Sediment Toxicity Test, sediment tested on survival of invertebrates: Hyalella. Other abbreviations: N, nitrogen; NWIS; U.S. Geological Survey National Water Information System database; O, oxygen; POCIS, polar organic chemical integrativsediment] Site information Comprehensive stressor assessments Focused studies 

NWIS station number Field identifier Basic QW1 (D) Mer- cury (D) Organic waste indica- tors (D) Phar- ma- ceuti- cals (D) Glypho- sate analysis (D) N and O iso- topes (D) Algal toxins (D) POCIS (I)2 Stream- flow or stage (C)3 Tem- pera- ture (C)3 Pes- ticide auto- sampler (I) Bio- film pesti- cides (I) SS passive sam- pler (I) Aqu

ic bi

(D

11466800 CA_MarkWMir 6 3 3 3 2 1 1 x Gage x — — — — 383109122363301 CA_MarkWTar 4 2 1 1 — 1 1 x — — — x — x 372500122081201 CA_Matadero 6 3 3 3 2 1 1 x Gage x — x — x 11466170 CA_Matanzas 6 3 3 3 2 1 1 x Gage x x x — x 382017122161101 CA_Milliken 6 3 3 3 2 1 1 x PT x — x — x 375701121564401 CA_MtDiablo 6 3 3 3 2 1 1 x — — — x — x 11148900 CA_NaciBryson 4 2 1 1 — 1 1 x Gage — — x — x 383321122302101 CA_NapaBale 6 3 3 3 2 1 1 x PT x x x — x 11458300 CA_NapaNapa 6 3 3 3 2 1 1 x PT x — x — x 364155121363901 CA_Natividad 6 3 3 3 2 1 1 x PT x — x — x 382346122521201 CA_ NoNameMonty 6 3 3 3 2 1 1 x PT x — x — x 365718121444301 CA_NoNamePaul 6 3 3 3 2 1 3 — PT x — — — x 11459500 CA_Novato 6 3 3 3 2 1 1 x Gage x — x — x 11141050 CA_Orcutt 6 3 3 3 2 1 1 — Gage x — — — x 365736121250801 CA_Pacheco 6 3 3 3 2 1 3 — PT x — x — x 11159000 CA_PajaroChit 6 3 3 3 2 1 3 — Gage x — — — x 11159500 CA_PajaroWat 6 3 3 3 2 1 3 x — — — — — x 381519122385601 CA_Petaluma 6 3 3 3 2 1 1 x PT x — — — — 375807122124001 CA_Pinole 4 2 1 1 — 1 1 — — — — — — x 11152650 CA_Reclamation 6 3 3 3 2 1 1 x Gage x — x — x 383305122311901 CA_Ritchey 4 2 1 1 — 1 1 x PT x — x — x 11150500 CA_Salinas 6 3 3 3 2 1 1 — Gage x — — — x 372716122080801 CA_SanFranPalo 6 3 3 3 2 1 1 — — — — — — x 11164500 CA_SanFranStan 6 3 3 3 2 1 1 x Gage x — — — x 374336122095801 CA_SanLeandro 6 3 3 3 2 1 1 x — — — — — x 351436120405201 CA_SanLObispo 6 3 3 3 2 1 1 — PT x — x — x 11181000 CA_SanLorenzo 6 3 3 3 2 1 1 — Gage — — — — x 375220122104201 CA_SanPabloMor 6 3 3 3 2 1 1 — — — — x — x 375312122113501 CA_SanPabloOr 6 3 3 3 2 1 1 — — — — x x x 375746122195501 CA_SanPabloPort 6 3 3 3 2 1 1 x — — — — — x 374933122001301 CA_SanRamonDan 6 3 3 3 2 1 1 x — — — x — x 11182500 CA_SanRamonSan 6 3 3 3 2 1 1 x Gage — — x — x 11466200 CA_SantaSanta 6 3 3 3 2 1 1 x Gage x — x — x 11466320 CA_SantaWillow 6 3 3 3 2 1 1 x Gage x — x — x 
Table 5. Summary of data collected at the California Stream Quality Assessment sites in 2017.—Continued[Constituents are categorized by the study-design components: Comprehensive Stressor Assessments, Focused Studies, and Ecological Surveys. Notes and abbreviations: See foquality of water (QW) constituents. Abbreviations: C, continuous sample; D, discrete samples; I, integrative sample. Numerical value in cell indicates number of discrete samsample collected; —, not sampled. Streamflow or stage: Egage, gaging station for an external agency other than U.S. Geological Survey (USGS); Gage, USGS gaging station; installed to record stream stage. Ecological Surveys were conducted once at sites near the end of the water-quality index period: Aquatic Biota, invertebrate and algal samples cSediment: Tx, two temporal samples were collected prior to collecting sediment during ecological survey; Sediment Toxicity Test, sediment tested on survival of invertebrates: Hyalella. Other abbreviations: N, nitrogen; NWIS; U.S. Geological Survey National Water Information System database; O, oxygen; POCIS, polar organic chemical integrativsediment]

Site information Comprehensive stressor assessments Focused studies 

NWIS station 

number Field identifier

Basic 

QW1

(D)

Mercury

(D)

Organic 

waste 

indicators

(D)

Pharmaceuticals

(D)

Glyphosate 

analysis

(D)

N and O 

isotopes

(D)

Algal 

toxins

(D)

POCIS

(I)2

Streamflow or 

stage

(C)3

Temperature

(C)3

Pesticide 

autosampler

(I)

Biofilm 

pesticides

(I)

SS 

passive 

sampler

(I)

Aqu

ic bi

(D

11135250 CA_

SantaYnezLom

6 3 3 3 2 1 1 x — x — x — x 

11128500 CA_SantaYnezSol 6 3 3 3 2 1 1 x Gage x — — — x 371620122005801 CA_Saratoga 6 3 3 3 2 1 1 x — — — x — x 374708122132801 CA_Sausal 6 3 3 3 2 1 1 x — — — x — x 382634122315201 CA_SonomaAdobe 4 2 1 1 — 1 1 x — — — x — x 11458500 CA_SonomaAgua 6 3 3 3 2 1 1 x Gage x — — — x 381556122280201 CA_SonomaWat 6 3 3 3 2 1 1 x PT x — — — x 351725120395901 CA_Stenner 6 3 3 3 2 1 1 x PT x — — — x 381441122064301 CA_Suisan 6 3 3 3 2 1 1 x Egage — — x x x 365634121264001 CA_Tequisquita 6 3 3 3 2 1 3 x PT x — x — x 382245122001601 CA_Ulatis 6 3 3 3 2 1 1 x Egage — — x x x 365955121350601 CA_UvasMiller 6 3 3 3 2 1 1 — — x — x — x 375413122033301 CA_Walnut 6 3 3 3 2 1 1 — Egage — — x — x 375808122172601 CA_Wilkie 6 3 3 3 2 1 1 x — — — x — x 383039122502401 CA_Windsor 6 3 3 3 2 1 1 — PT x — x — x 

1Basic QW constituents: suspended sediment, major ions, nutrients, pesticides, supplemental pesticides, glyphosate immunoassay, and dissolved organic carbon.2Data at some sites were missing because sample or instrument was lost.3Continuous stage or temperature data were missing at some sites because pressure or temperature sensors were either not deployed or lost in the field owing to high flow con
22 Design and Methods of the California Stream Quality Assessment, 2017

Discrete Water-Quality Samples

During the WQ index period of each site, Basic QW 

samples were collected weekly for analysis of nutrients, major 

ions, dissolved organic carbon, pesticides (using an expanded 

target analyte list relative to prior RSQA studies), glyphosate 

by immunoassay, and suspended-sediment concentration 

(table 5; appendix 1, table 1.1). Additional water samples were 

collected or parameters were measured during selected weeks 

during the WQ index period at all 85 stream sites, unless 

specified otherwise, for the following: mercury (2–3 times 

during the study), organic waste indicators (1–3 times), 

pharmaceuticals (1–3 times), glyphosate by chemical analysis 

(2 times at 83 sites), stable isotopes 15N and 18O (1 time), 

and algal toxins (1 time at 77 sites, 3 times at 8 sites, plus 

2 times at 1 nearby lake site). The weeks of the WQ index 

period during which these additional samples were collected 

or parameters were measured are specified in appendix 1, 

table 1.1. For algal toxins, one water sample was collected 

during the last week of the study period at all stream sites. In 

addition, two water samples were collected on July 11 and 25, 

2017, at eight stream sites in the Pajaro River Basin and at one 

site in Pinto Lake (into which the Pajaro River flows), because 

of a history of microcystin contamination there (California 

Water Boards, 2014; Gibble and Kudela, 2014).

Water-quality samples were collected and processed 

following standard USGS protocols described in the 

National Field Manual (Wilde and others, 2009). Before 

collecting samples from the field, all field equipment was 

cleaned according to USGS protocols and then rinsed with 

native water immediately before samples were collected. 

In general, discrete water samples were collected for most 

analytes by an isokinetic, equal-width increment method 

(U.S. Geological Survey, 2006; fig. 5) where subsamples 

were collected at 10 increments across the stream with either 

a DH-81 or DH-95 sampler (Davis, 2005). The sampler has 

a precleaned Teflon cap and nozzle assembly that fitted a 

1-liter (L) Teflon bottle (U.S. Geological Survey, 2006). Each 

incremental sample was placed immediately into a precleaned, 

acid- and methanol-rinsed Teflon churn for compositing 

before processing.

Water from the Teflon churn was not used for mercury 

analysis because ultra-trace concentration clean-sampling 

procedures and equipment were necessary to collect and 

process the samples for low-concentration total mercury and 

methylmercury analysis (U.S. Environmental Protection 

Agency, 1996; Lewis and Brigham, 2004). Water for mercury 

samples was collected separately as grab samples from the 

centroid of flow at about 0.3 m below the water surface in a 

1-L Nalgene bottle. These samples were collected three times 

at the 6-week sites and two times at the 4-week sites (table 5, 

appendix 1, table 1.1). In addition, the dissolved organic 

carbon (DOC) samples were collected as grab samples from 

the centroid of flow; because mercury bioavailability is related 

to DOC levels in the aquatic environment, collecting mercury 

and DOC samples using the same method was deemed 

important to establish a relation between the two constituents. 

Filtering of samples utilized low-level mercury sampling 

techniques as described in the USGS Field Manual (Wilde and 

others, 2009, Section 5.6.4.B). After filtering, samples were 

preserved using ultrapure hydrochloric acid (Hydrochloric 

Acid 34–37 percent OmniTrace®), and filters were frozen 

(Wilde and others, 2009). Samples were processed at either 

a USGS California Laboratory or at the USGS Mercury 

Research Laboratory in Middleton, Wisconsin. Samples 

processed in California were shipped to the USGS Mercury 

Research Laboratory for mercury analysis.

A separate water sample was collected at all sites to 

determine concentrations of the algal toxin microcystin in 

streams (table 5; appendix 1, table 1.1) and at one lake site. 

These water samples were frozen (–20 °C) and shipped 

overnight to the USGS Organic Geochemistry Research 

Laboratory (OGRL) in Lawrence, Kansas, for processing 

and analysis.

When stream conditions did not meet the requirements 

for collecting equal-width increment subsamples with 

the Teflon churn (which required a velocity greater than 

1.5 feet per second [ft/s]), samples were collected either by 

a multivertical grab (for velocity less than 1.5 ft/s, width 

greater than 10 feet [ft]), or by a grab from the centroid of 

flow (for velocity less than 1.5 ft/s, width less than 10 feet, 

depth less than 1 foot). When flow conditions were too 

high to safely collect equal-width increment subsamples, a 

single-point grab sample was collected from the bank or by 

wading as far as possible into the stream. For grab samples, 

water was collected directly into sample bottles for unfiltered 

constituents and into a precleaned 1-L Teflon sample bottle for 

filtered constituents; samples were subsequently filtered from 

that bottle into sample bottles (appendix 1, table 1.3).

California had a relatively wet year in 2017, particularly 

during the month of February, which preceded the study 

period. Overall, monthly runoff in California was higher 

during the March 3–May 13, 2017, study period than the 

average value over the previous 30 water years (a water year 

is the period beginning October 1st of one year and ending 

September 30th of the next year; https://ca.water.usgs.gov/

california-drought/california-drought-runoff.html). High flow 

conditions occurred in some streams, in which case grab 

samples had to be collected (as described earlier in the text). 

At three Northern sites, high flow conditions at the end of 

the study period prevented collection of ecological samples, 

so ecological survey data were available for only 82 sites 

(appendix 1, table 1.1).

Field properties of specific conductance, pH, dissolved 

oxygen, and water temperature were measured at the time of 

each weekly water-quality sampling with a field-calibrated 

multiparameter sonde, as described in the USGS National 

Field Manual (Wilde, 2008). The measurements were made at 

five locations within the water-quality sampling transect and 

averaged. When the stream width was less than 10 ft (3 m), 

field parameters were measured from the centroid of flow.
Sample Collection and Processing 23

Polar Organic Compound Integrative 

Samplers (POCIS)

Two POCIS housed within a single canister were 

deployed for between 33 and 38 days (about 5 weeks) at 

each of the 85 sites during the WQ index period; one POCIS 

from each canister was analyzed for pesticides and one for 

pharmaceuticals. Canisters were lost or compromised (such 

as by burial in sediment or exposure to air) at 21 sites, leaving 

64 sites with valid POCIS samples (table 5; appendix 1, 

table 1.1). The POCIS are integrative samplers that contain 

the sorbent Oasis HLB (Waters, Milford, Mass.) and are 

designed to accumulate moderately water-soluble (polar or 

hydrophilic) organic compounds from surface water (Alvarez, 

2010). Oasis HLB is considered a universal sorbent in 

environmental analyses and has been used to extract a wide 

assortment of chemical classes from water. The use of Oasis 

HLB in the POCIS allows for estimation of time-weighted 

average concentrations of target chemicals (pesticides 

and pharmaceuticals) over the deployment period, if a 

chemical-specific water “sampling rate” has been determined. 

Extracts of POCIS samples were analyzed for contaminants 

by using modified versions of the water methods for these 

chemical groups (Van Metre and others, 2017a).

Field deployment followed the guidelines provided 

in Alvarez (2010). A stream location was required to have 

enough depth (about 0.5 ft, or 15 centimeters [cm]) for the 

POCIS to remain submerged during the deployment period 

and be protected from excessive sediment accumulation, 

flood debris, and vandalism. Effective anchoring systems 

were adopted on the basis of site-specific characteristics 

(for example, sandy versus rocky substrate, streamflow 

variability, and so forth). The POCIS canister was attached 

to the same structure as the temperature data logger at many 

sites (see section “Continuous Streamflow, Stage, and Water 

Temperature”), either on the rebar or on the streamgage 

orifice pipe. Others were deployed in the centroid of flow 

and attached to a cinder block (fig. 6). Field records were 

maintained that included the site name; date and time of 

deployment and retrieval; and observations of streambed 

substrate, streamflow conditions, and water clarity.

Quality control (QC) POCIS samples collected in the 

field included replicates and blanks and are described in 

the “Quality Assurance and Quality Control” section. All 

environmental POCIS and QC canisters were stored on ice 

during transport to and from the field location. After the 

deployment period, the POCIS were retrieved from the sites 

and immediately sealed in their respective canisters; all 

environmental POCIS, QC canisters, and log sheets were 

shipped to the USGS Columbia Environmental Research 

Center (CERC), Columbia, Missouri, in coolers with wet ice.

Continuous Streamflow, Stage, and 

Water Temperature

The sampling design called for measurement of 

streamflow or stage at all sites, as well as continuous 

temperature. However, stage or temperature data were 

missing at some sites because pressure or temperature sensors 

were either not deployed or lost in the field due to high flow 

conditions. Overall, streamflow or stage was obtained at 

54 sites and continuous temperature at 46 sites; details are 

provided in table 5.

Figure 5. A hydrologist moves an isokinetic sampler into position. Photograph by Stephanie 

Kula, U.S. Geological Survey.
24 Design and Methods of the California Stream Quality Assessment, 2017

U.S. Geological Survey streamgages were active at 

28 sites and provided stream stage and streamflow discharge at 

15-minute intervals (table 5). Four sites had continuous stage 

data from streamgages operated by county or city agencies. 

Pairs of pressure transducers (one in the water column and one 

in the air, as described farther on in the text) were successfully 

deployed at 19 sites, and these units were programmed to 

record stream stage at 15-minute intervals. Neither flow nor 

stage was monitored at the remaining 34 sites. The pressure 

transducers were the HOBO U20-001-04 digital loggers 

(specifications are in appendix 1, table 1.2). The units were 

deployed during February 2017, before the start of the WQ 

index periods, and were retrieved in the fall of 2017. Guidance 

from the manufacturer and the USGS was followed for 

deployment, calibration, and maintenance of the units (Sauer 

and Turnipseed, 2010; Onset Computer Corporation, 2014).

Full deployment of pressure transducers at a site included 

the installation of two units per site: one unit mounted in 

the water column to measure changes in water pressure as 

the water level changed, and one unit mounted in the air to 

measure barometric pressure to provide a correction factor for 

calculating stream stage with the water-pressure transducer 

data. The units were placed inside a vertical 2-inch polyvinyl 

chloride pipe mounted to a bridge support or directly to a 

metal post driven into the streambed. The water-pressure units 

were mounted at a depth where they would remain continually 

submerged, and the barometric-pressure units were typically 

mounted to a tree, bridge structure, pipe, or post. Both units 

were programmed to record on 15-minute intervals for the 

duration of the study.

Establishing a baseline water-level was necessary 

immediately after deployment of the pressure transducer in 

the water so that measurements of water pressure could be 

converted to actual water level. A reference point (RP), on 

which changes in water level were based, was established 

upstream from the pool that held the submerged unit. 

Typically, the RP was a mark scribed on a permanently fixed 

structure near the attached unit, such as a bridge support or 

wing wall; a measurement from the RP to the water surface 

was the “tape down” distance. An arbitrary datum was then 

established that was greater than the distance between the 

RP and the channel bottom, and this datum would cover all 

low stages and ensure no negative stage values; typically, 

10 feet was used as the water level at the streamgage datum. 

The distance from the RP to the surface of the water at time 

of deployment was used to establish the initial stream stage. 

In addition, measurements from the RP to water surface were 

made during every site visit by the water-quality sampling 

crew, so that these values could be used to check data for 

consistency and quality.

Figure 6. Deployed polar organic compound integrated sampler on cinder-block-and-cable 

infrastructure. Photograph by Celeste Journey, U.S. Geological Survey.
Sample Collection and Processing 25

Water temperature was continuously monitored at 2 sites 

with streamgages, 23 sites with instream pressure transducers, 

and 21 sites with digital temperature data loggers; continuous 

temperature was not recorded at the remaining 39 sites. The 

pressure transducers included temperature sensors that were 

used to record water temperature at 15-minute intervals. 

Deployment of a single pressure transducer mounted in 

the water column was sufficient to measure continuous 

temperature. Although pressure transducers were successfully 

deployed to measure stage at only 19 sites, instream pressure 

transducers recorded temperature at an additional 4 sites. At 

some stream sites that did not have a streamgage or pressure 

transducer recording temperature, digital data loggers recorded 

temperature at 15-minute intervals. These devices were 

deployed from early winter 2017 through the end of the study 

in order to provide a water-temperature dataset inclusive 

of all sampling activities. Where possible, loggers were 

deployed approximately 0.3 ft (10 cm) above the streambed, 

out of direct sunlight, and attached to rebar anchored into the 

streambed or to stable parts of streamgage infrastructure (for 

example, orifice pipe). In most cases, the HOBO Water Temp 

Pro v2 U22 loggers were deployed (device specifications are 

in appendix 1, table 1.2). Guidance from the manufacturer and 

the U.S. Forest Service concerning deployment, calibration, 

and maintenance generally was followed (Dunham and others, 

2005; Onset Computer Corporation, 2012).

Focused Studies

Three types of focused studies were conducted at selected 

sites (table 5). Small-volume autonomous water samplers 

were deployed at five sites to collect daily composited water 

samples for pesticide analysis. Ceramic tiles were deployed at 

54 sites to provide a substrate for the growth of biofilms that 

were collected and analyzed for selected pesticides. Passive 

suspended-sediment samplers were deployed at five sites to 

collect time-integrated samples of suspended sediment.

Sampling Pesticides with Small-Volume 

Pesticide Automated Samplers

A small-volume autonomous water autosampler 

(hereafter, “pesticide autosampler”) was designed and built 

at Portland State University, Oregon, to collect fixed-point, 

small-volume samples (McWhirter, 2020) for analysis of 

pesticides in water. In a collaborative study with EPA, the 

autosamplers were used at a subset of five CSQA sites to 

determine whether increasing sampling frequency would 

improve the accuracy of characterizations of instream 

pesticide stressor conditions to which biota were subjected. 

Although weekly discrete samples of pesticides were collected 

at all sites during the WQ index periods, discrete samples 

can miss short-term “spikes” in high concentrations that are 

potentially acutely toxic. The pesticide autosamplers were 

deployed at five Northern stream sites to collect daily and 

weekly composite samples over an approximately 6-week 

WQ index period: two high urban sites, one medium urban 

site, one high agriculture site, and one low agriculture site, 

as classified by lower-basin scale land use (tables 1 and 

5, cross referenced). The autosampler was discontinued at 

one high urban site owing to repeated flooding. As part of 

this collaborative study with EPA, autosamplers also were 

deployed at two agricultural sites in the Central Valley (outside 

the CSQA study area), Cache Creek and Putah Creek.

The pesticide autosamplers (fig. 7) were programmed to 

collect multiple aliquots to form daily and weekly composite 

samples of stream water during successive 1-week periods. 

An aliquot of stream water was collected every 6 hours into 

daily composite vials (four aliquots per vial, with the “day” 

typically starting around noon) and every 12 hours into the 

weekly composite vial. Thus, eight vials were filled per week 

for 7 daily samples and 1 weekly sample. In addition, a ninth 

vial containing a known pesticide spike mixture in native 

stream water was placed in the autosampler at the start of 

the week; this QC sample was used to assess the potential 

for compound degradation during the weekly collection 

period. A 6-milliliter (mL) aliquot of a 1:1 methanol-water 

mixture was added, as a preservative, to each of the nine vials 

before deployment.

Over the 6 weeks of operation, the pesticide autosamplers 

were serviced each week on either Monday or Tuesday. Two 

units were available for each site, so that one unit could be 

serviced in the laboratory and exchanged in the field for the 

deployed unit. This arrangement minimized interruption by 

allowing ample time to remove and replace sample vials, 

charge batteries, clean tubing, and replace consumable 

components such as filters. Before deployment, each vial was 

labeled with the station identification number, vial number, 

date, and initial weight. Daily composite samples (vials 1 

through 7) were analyzed for pesticide concentrations by 

the EPA Office of Pesticide Programs (OPP) Analytical 

Chemistry Laboratory in Fort Meade, Maryland. Sample 

splits of the weekly composite sample (vial 9) and the spike 

sample (vial 8) were analyzed for pesticides by both the 

USGS National Water Quality Laboratory (NWQL) in Denver, 

Colorado, and the OPP laboratory. Analytical service request 

(ASR) forms (USGS) and cooler inventory forms (USGS and 

EPA) were included with sample shipments, and barcodes 

were affixed to each vial as an auxiliary data identifier and 

tracking method.
26 Design and Methods of the California Stream Quality Assessment, 2017

Sampling Pesticides in Biofilms

A focused study was conducted in CSQA to determine 

whether pesticides bioaccumulate in biofilms (Barbara Mahler, 

written commun., 2020), which consist of fungi, bacteria, 

algae, and microfauna enclosed in a mucopolysaccharide 

matrix attached to a surface exposed to streamflow. This 

complex organic microlayer can retain organic contaminants, 

much like DOC (Sabater and others, 2007). Unglazed 

ceramic tiles were deployed at 54 sites that represented all 

land-use categories across the study area (tables 1 and 5, cross 

referenced) in February or March 2017. Tiles were secured 

to a concrete block about 30 cm thick using water-resistant 

cement, and three replicate tiles were distributed along the 

reach for a deployment period of at least 60 days (appendix 1, 

table 1.6). At each site, the biofilm that had grown on the tiles 

was removed by scraping and composited into a clean glass 

jar, placed in a cooler with ice, and delivered to the USGS 

Organic Chemistry Research Laboratory, Sacramento, Calif. 

Samples were kept frozen at the laboratory until extraction and 

analysis were done for insecticides. Quality control samples 

consisted of one field replicate sample, four laboratory blank 

samples, and three laboratory matrix spikes.

Sampling Suspended Sediment with 

Passive Samplers

Suspended-sediment samples were collected from five 

Northern sites by using time-integrating suspended-sediment 

passive samplers (Phillips and others, 2000). The fine 

sediments (less than 63 micrometers [μm]) were analyzed 

for major and trace elements, particle size, and radionuclides 

to assess sources and ages of sediment in the stream. These 

suspended-sediment passive samplers were deployed at three 

urban sites (one high, one medium, and one low urban), one 

agricultural site, and one mixed site, as characterized by 

lower-basin land use (tables 1 and 5, cross referenced).

A B

Figure 7. The small-volume pesticide autosampler used to collect filtered water at sub-daily intervals for pesticide analysis at selected

sites: A, autosampler internals and the polyvinyl chloride housing (from McWhirter, 2020; photograph by Kevin McWhirter, Portland 

State University); and B, a hydrologic technician retrieving samples from the autosampler during deployment in the stream. Photograph 

by Peter Van Metre, U.S. Geological Survey. The samplers were designed and built at Portland State University (McWhirter, 2020).
Sample Collection and Processing 27

The suspended-sediment passive samplers were attached 

to metal posts that were driven into the streambed and were 

oriented so that the conical end (fig. 8) faced into the flow. 

Typically, four samplers were installed in the channel in two 

pairs; each pair consisted of a lower sampler placed below the 

water level at base flow and the paired sampler placed above 

the lower sampler. If base flows were especially low at the 

time of deployment, the top sampler was allowed to be out 

of the water; in such cases, the top samplers would collect 

sediment only at flows higher than base flow.

The suspended-sediment passive samplers were deployed 

on January 24 or 25, 2017, and remained deployed for 

approximately 16 weeks, through early May, inclusive of the 

WQ index period. Sediment was retrieved every 2–3 weeks 

or following a large flow event, allowing enough time for 

sufficient sediment to accumulate for analyses of major and 

trace elements and radionuclides. To collect the sediment 

samples, the tubes were removed from their posts, the end 

caps were opened, and all the water and sediment were poured 

into a single 5-gallon plastic bucket. A spray bottle filled with 

deionized water was used to rinse any remaining sediment 

from the tubes. After collecting the samples, the tubes were 

cleaned with a brush and deionized water, then rinsed with 

native water. The water-sediment mixture was stored at 

room temperature in the 5-gallon bucket until the sediment 

settled to the bottom (usually 3–7 days), then the clear water 

was siphoned off and discarded. The remaining composite 

sediment sample was shipped on wet ice to the USGS 

Baltimore Sediment Laboratory, Md., where it was wet sieved 

with deionized water using a 63-μm polyester sieve. The 

sieved slurry was collected in glass bowls and dried at 65 °C 

for 2 or more days. The dried sediment was removed with 

a plastic utensil, and aliquots of the fine sediment (less than 

63 μm) were shipped to multiple laboratories (see “Sample 

Analyses” section) for inorganic chemical analyses. For 

about 10 percent of samples, if sufficient sediment mass was 

available, duplicate aliquots (QC split samples) were analyzed 

for major and trace elements, and particle size.

Figure 8. Installation of time-integrating suspended-sediment passive samplers by U.S. 

Geological Survey personnel. Photograph by Celeste Journey, U.S. Geological Survey.
28 Design and Methods of the California Stream Quality Assessment, 2017

Ecological Surveys

Data collected during the ecological surveys characterize 

aquatic biota, physical habitat, and sediment contaminants 

along a 150-m sampling reach for each site (table 5). Five 

teams, each consisting of six USGS employees, were deployed 

across the region to conduct the surveys at all sites during 

May 2017, after the end of the WQ index period. The median 

number of days between the end of water-quality sampling and 

the ecological survey was 3 days for the Northern sites and 

18 days for the Southern sites. As noted previously, no surveys 

were conducted at three sites (table 5; appendix table 1.1) 

where high water prohibited safe sampling during the targeted 

time of the ecological survey. Although the data collected 

during the ecological surveys were based on discrete samples, 

biological and habitat data generally represent integrative 

conditions over a longer, undefined time period. For example, 

sediment chemistry is affected by erosional processes and 

contaminant persistence, the species structure of aquatic 

biological communities depends on water-quality conditions 

that occur over the life cycles of the organisms, and the 

physical habitat of a stream reach typically is strongly affected 

by many years of hydrologic events and human actions.

The 150-m sampling reach was segmented with 

11 equally spaced cross-sectional transects (primary transects) 

that were set 15 m apart along the reach, and 10 secondary 

transects, each set approximately midway between a 

pair of primary transects. All field data were recorded on 

electronic forms by using hand-held tablet computers. Field 

data collected from the habitat surveys, and field records 

for the algal and macroinvertebrate samples destined for 

laboratory analyses, were loaded into the USGS BioData 

database, the USGS repository for aquatic bioassessment data 

(U.S. Geological Survey, 2016).

Aquatic Biota

Benthic macroinvertebrate and algal communities 

were sampled by the reach-wide benthos (RWB) method 

using standard protocols from the Surface Water Ambient 

Monitoring Program (SWAMP) of the State of the California 

State Water Resources Control Board (Ode and others, 

2016). The RWB method entails sampling throughout 

the reach at measurement points systematically placed in 

relation to the 11 primary transects established within the 

reach. Quantitative subsamples from the 11 transects were 

then combined into a single composite sample for each of 

benthic macroinvertebrates and algae. The goal of the RWB 

method is to represent the ecological condition throughout 

the reach. The RWB method was used for consistency 

with other bioassessment data in California and to enable 

calculation of the California Stream Condition Index (Rehn 

and others, 2015).

Benthic macroinvertebrate samples were collected before 

algal samples at a point 1 m downstream from each primary 

transect using a D-frame net with 500-μm mesh openings 

(fig. 9). Samples were collected starting with the downstream 

transect; a 0.09-square-meter (1-square-foot) sampling station 

was sited along the transect at a distance 25 percent of wetted 

width from the left bank (with left and right determined 

when facing downstream). Moving upstream, the sampling 

positions within successive transects were alternated between 

the center, right, and left positions along the transect (50, 75, 

and 25 percent of wetted width, respectively), cycling through 

this order repeatedly. If the targeted section of the stream 

was too deep to wade, the collection occurred as close to the 

targeted location as possible. Organisms were separated from 

the substrate; heavy organisms were removed by hand, larger 

rocks were scrubbed, and then the streambed was vigorously 

kicked for 30 seconds while capturing the material in the net.

Material was transferred from the net to a sieve bucket, 

where transect samples were composited, then emptied 

onto a double sieve with 0.635-cm (0.25-inch) mesh atop a 

500-μm mesh. Gravel and detritus were removed from the 

upper sieve and larger predaceous macroinvertebrates caught 

on the top sieve were preserved immediately in 95-percent 

ethanol to reduce the chances of other specimens being 

consumed or damaged. Large or rare macroinvertebrates, 

such as crayfish and large mollusks, were photographed and 

released in accordance with collection permit procedures. 

The sample remaining on the lower sieve was transferred into 

one or more 1-L polystyrene wide-mouth bottles filled to no 

more than 50 percent with the sample material and preserved 

with 95-percent ethanol. Identification and enumeration of 

macroinvertebrate taxa (generally to either genus or species 

taxonomic levels) were completed by the NWQL.

Benthic algal samples were collected at each transect 

after the benthic macroinvertebrate samples were collected, 

and at a location approximately 0.25 m upstream from where 

the macroinvertebrates were collected. At each sampling 

location, the dominant substrate type was identified, and a 

pipe sampler, which was 40 mm long with an opening of 

approximately 12 square centimeters, was placed against 

the substrate. Hard substrates, such as cobble or wood, were 

lifted from the water, scrubbed with a stifle-bristled brush, 

and rinsed into the 500-mL wide-mouth polystyrene bottle. In 

soft substrates, such as sand or detritus, the pipe sampler was 

pressed into the substrate to a depth of approximately 0.5 cm, 

and a spatula was slid under the sampler to collect a thin 

sediment core, which was then rinsed into the sample bottle. 

For immobile hard substrates, such as boulders, bedrock, or 

concrete, the tip of a syringe was used to dislodge and suction 

algae from the area delimited by the pipe sampler, and the 

material then was emptied into the sample bottle.
Sample Collection and Processing 29

Five aliquots were removed from the composite 

sample for various analyses. Four aliquots were filtered 

onto glass-fiber filters with 0.47-μm pore size. Two of these 

aliquots were placed on dry ice and shipped to the NWQL for 

analysis of chlorophyll a and pheophytin a (in one sample), 

and biomass, as ash-free dry mass (in a second sample). The 

two remaining 0.47-μm filtered aliquots were retained frozen 

as backups in the event of sample loss or damage, or in case 

additional material was needed for analysis. A fifth aliquot 

was put into a 2-mL vial and shipped to the Institute of Arctic 

and Alpine Research (INSTAAR) Diatom Laboratory at the 

University of Colorado, Boulder, for environmental DNA 

(eDNA) analysis. The remainder of the composite sample 

was preserved with buffered formalin at a concentration of 

approximately 5 percent and sent to the INSTAAR Laboratory 

for taxonomic identification and enumeration of diatoms.

Physical Habitat

Following collection of biological samples, the physical 

habitat of the reach was characterized using USGS protocols 

(Fitzpatrick and others, 1998). Descriptive and quantitative 

measurements were made across each primary transect and 

included geomorphic channel unit type (pool, riffle, or run), 

stream depth, substrate size at five locations (right and left 

edges of water, the center of the channel, and midway between 

channel edges and channel midpoint), stream wetted width, 

bank height, canopy cover at mid-transect, macrophyte 

coverage, and the presence of bars, islands, and potential 

fish habitat features. Substrate size also was measured across 

the secondary transects, at the same five locations described 

previously in the text. The surface-water gradient was 

measured over the entire 150-m reach, and the average slope 

from the top to the bottom of the reach was determined.

Streambed and Bank Sediment

During the ecological surveys, one composite sediment 

sample was collected from the wetted streambed and another 

composite sample was collected from the stream banks 

(table 5). At seven sites, wetted streambed samples were 

collected twice prior to the ecological surveys, during the 

first and fourth weeks of sampling at these sites (appendix 1, 

table 1.1). These additional samples were identified as 

“temporal sediment samples” and, in combination with 

results from samples collected during the ecological survey, 

will be used to evaluate how sediment chemistry varied over 

the sampling period. The sites where temporal sediments 

were collected are identified with “T” in the column labeled 

“Streambed Sediment,” under “Ecological Surveys,” 

in table 5.

Figure 9. Invertebrate sampling with a D-frame dip net by U.S. Geological Survey 

personnel. Photograph by Alan Cressler, U.S. Geological Survey.
30 Design and Methods of the California Stream Quality Assessment, 2017

The composite streambed-sediment sample was 

collected by following established USGS protocols (Shelton 

and Capel, 1994; Radtke, 2005), with some modifications, 

described as follows. Four-inch (about 10-cm) stainless-steel 

cylinders and stainless-steel spatulas were used to collect 

the sediment. Multiple collections of sediment were made 

from depositional areas along the 150-m sampling reach, 

targeting locations where fine-grained sediments accumulated 

(fig. 10). Depositional zones across the reach were sampled 

in approximate proportion to their bottom surface area. 

The collection method required pushing the stainless-steel 

cylinder into the streambed to a depth of 2 cm, then sliding the 

spatula under the cylinder to support the enclosed streambed 

core. Each streambed core was lifted gently out of the water 

to minimize the loss of fine material, and all cores were 

composited in a large plastic bucket. Approximately 6–10 L 

of streambed material was collected for the sample. Samples 

were sieved in the field by using a 2-mm stainless-steel sieve 

that rested on top of the bucket.

The bulk bed-sediment sample was placed on ice in 

the field and transported to a USGS research facility in 

Menlo Park, Calif., where samples were homogenized and 

split into aliquots for various analyses. Each sample was 

homogenized by using a kitchen mixer with a stainless-steel 

bowl and a bread-dough-style paddle operated at low speed. 

Before the CSQA study, RSQA staff had tested several 

streambed-sediment samples to determine the mixing time 

necessary to achieve a reasonably homogeneous sample; about 

30 seconds was used for initial mixing, then about 15 seconds 

for additional mixing between removal of aliquots.

Sample aliquots (2-mm sieve) were shipped chilled to 

various laboratories for toxicity testing and analyses of organic 

constituents. Subsamples of streambed sediment were shipped 

to the USGS Maryland-Delaware-D.C. Water Science Center 

(WSC) in Baltimore, Md., where they were wet sieved with 

deionized water using a 63-μm polyester sieve. The sieved 

slurry was collected in glass bowls and dried at 650 °C for 2 or 

more days. The dried sediment was removed with a plastic 

utensil, and aliquots of the fine sediment (sieved at less than 

63 μm) were shipped to multiple laboratories for analysis 

of inorganic chemicals and carbon. Altogether, sediment 

samples were collected from 82 sites, and aliquots were 

analyzed for the following constituents at all sites: current-use 

pesticides, polycyclic aromatic hydrocarbons (PAH) and 

other semivolatile compounds, organic wastewater indicators, 

hormones, halogenated organics (all sieved at 2 mm), trace 

and major elements, organic carbon, radionuclides (all 

sieved at 63 μm), and grain size. Temporal sediment samples 

collected at the nine sites (table 5) were analyzed for PAHs, 

organic wastewater indicators, hormones, radionuclides, trace 

and major elements, organic carbon, and microcystins.

Bed sediment was used to conduct standardized ambient 

whole-sediment toxicity tests at the USGS CERC, in 

accordance with American Society for Testing and Materials 

International (2016) and U.S. Environmental Protection 

Agency (2000) methods. Tests were performed with the 

amphipod Hyalella azteca (28-day exposures) at all sites 

and with the midge larvae Chironomus dilutus (10-day 

exposures) at 41 sites (table 5) to measure potential effects of 

contaminants on survival and growth.

Figure 10. Collection of composite bed-sediment samples from a depositional area along 

a reach. Photograph by Alan Cressler, U.S. Geological Survey.
Sample Analyses 31

The bank sediment sample was collected at 

5–10 locations along the sampling reach where an exposed 

or eroding bank was observed on either side of the stream. At 

each location, sediment was collected by using a precleaned 

plastic trowel to scrape a vertical furrow from above the 

water line to the top of the exposed bank (about 1-cm depth 

into the bank). The bank scrapes were composited as a single 

sample in a 1-L plastic jar. Bank material was stored on wet 

ice and shipped to the USGS Maryland-Delaware-D.C. WSC 

in Baltimore, Md., where it was wet-sieved (2-mm) and 

dried; aliquots were sent to AGAT Laboratories, Mississauga, 

Ontario, Canada (https://www.agatlabs.com/index.cfm), for 

analyses of trace and major elements, and organic carbon.

Sample Analyses

This section describes chemical analyses of constituents 

in water and sediment samples, taxonomic analyses of 

biological samples, and processing of real-time data recorded 

by data-logging instruments in the field. Most of the chemical 

analyses of water and sediment samples were conducted by the 

NWQL or laboratories contracted by the NWQL, using either 

NWQL or EPA methods and schedules (appendix 2, tables 2.1

to 2.12), which are briefly described in this section; exceptions 

where other methods were used are noted. Analytical results 

for constituents in water and sediment from the NWQL were 

uploaded to the Water-Quality System database (QWDATA) 

in the National Water Information System (NWIS) of the 

USGS for storage and archiving. Results for each sample in 

QWDATA were uniquely identified by station identification 

number, date, time, and medium code. Additionally, each 

CSQA sample was labeled with a unique barcode as a backup 

sample-tracking identifier. Algal and macroinvertebrate 

samples were analyzed at the NWQL University of Colorado, 

Boulder, Colo., as described farther onin the text. Continuous 

data recorded by data-logging instruments, such as streamflow 

(or stage) and temperature, did not require laboratory analyses 

so they were processed at the USGS WSC in Sacramento, 

Calif. (the local WSC).

Comprehensive Stressor Assessments

Discrete Water-Quality Samples

Discrete water samples were collected weekly during 

the WQ index periods (table 5; appendix 1, table 1.1) 

and analyzed for nutrients, major ions, DOC, ultraviolet 

absorbance (UVA), and pesticides by the NWQL. Samples 

for major ions and nutrients were analyzed by the NWQL 

using various methods (appendix 2, tables 2.1 and 2.2). 

Specifically, total phosphorus concentrations were determined 

by colorimetry according to EPA method 365.1 (O’Dell, 

1993). Dissolved ammonia, nitrite, and orthophosphate 

colorimetric analyses are described by Fishman (1993). 

Dissolved nitrate-plus-nitrite concentrations were determined 

by low-level enzyme reduction colorimetry with an automated 

discrete analyzer, as described by Patton and Kryskalla (2011). 

Concentrations of dissolved cations were determined by 

inductively coupled plasma-atomic emission spectroscopy 

(Fishman, 1993), and concentrations of dissolved anions were 

determined by ion chromatography, as described by Fishman 

and Friedman (1989).

For analysis of pesticides, discrete water samples were 

syringe filtered (0.7-μm pore size glass-fiber) into 20-mL vials. 

Two pesticide schedules were run on the filtered samples: 

a broad-spectrum method to determine 225 pesticides and 

degradates (LCM60, the same pesticide method used in prior 

RSQA studies; appendix 2, table 2.3.1) and a supplemental 

schedule of 30 pesticides and degradates (LCM75; appendix 2, 

table 2.3.2). For both schedules, pesticides were analyzed 

by direct aqueous injection (DAI) liquid chromatography 

tandem mass spectrometry (LC-MS/MS; Sandstrom and 

others, 2016). The original 225 pesticides and pesticide 

degradates represent a broad range of chemical classes and 

were selected on the basis of criteria such as the amount 

of current use, probability of occurrence in streams and 

groundwater, toxicity to humans or aquatic organisms, and 

precision of analytical methods (Norman and others, 2012). 

The supplemental schedule contains additional high-priority 

pesticides, including neonicotinoid and diamide insecticides 

and fungicides, and was run on an Agilent model 6495 

LC-MS/MS instrument, which is more sensitive than the 

Agilent 6460 models used for the original method (Sandstrom 

and others, 2016). For the original LCM60 method, recoveries 

for most of the 225 analytes ranged from 80 to 120 percent in 

the water types tested, with relative standard deviations of less 

than 30 percent. The method detection limits (MDL) ranged 

from 1 to 106 nanograms per liter (ng/L) for most of the 

225 analytes, with current reporting levels (RLDQC) ranging 

from 2 to 360 ng/L for these analytes (appendix 2, table 2.3.1). 

For the supplemental pesticide method LCM75, recoveries 

were in the 80- to 120-percent range for all but one of the 

30 pesticide analytes. All 30 analytes had MDLs ranging from 

1 to 28 ng/L and RLDQCs from 2 to 56 ng/L (appendix 2, 

table 2.3.2).

Weekly discrete whole-water samples were analyzed for 

suspended-sediment concentrations at the USGS California 

Sediment Laboratory in Menlo Park, Calif. Methods for 

processing suspended-sediment concentrations included use 

of wet-sieving filtration and are described in Guy (1969) and 

Knott and others (1993).

Filtered and particulate methylmercury were analyzed in 

grab water samples (see “Sample Collection and Processing” 

section) at the USGS Mercury Research Laboratory in 

Middleton, Wis., by gas chromatographic separation with 

cold vapor atomic fluorescence spectrometry (DeWild and 

others, 2002, 2004). Filtered and particulate total mercury 

were analyzed by oxidation, purge and trap, and cold 

vapor atomic fluorescence spectrometry (method 1631, 

revision E; U.S. Environmental Protection Agency, 2002). 
32 Design and Methods of the California Stream Quality Assessment, 2017

The USGS Mercury Research Laboratory also analyzed 

DOC in grab samples collected weekly, as well as ultraviolet 

absorbance at 254 nanometers (UVA254) in grab samples 

collected concurrently with the mercury samples.

Human-use pharmaceuticals and organic wastewater 

indicator compounds were analyzed three times for the 6-week 

sites and once for the 4-week sites (table 5; appendix 1, 

table 1.1). Pharmaceutical samples were syringe filtered 

(0.7-μm pore size glass-fiber) into 20-mL vials and analyzed 

at the NWQL for 113 compounds by DAI LC-MS/MS 

(appendix 2, table 2.4; Furlong and others, 2008, 2014). 

Organic wastewater indicator samples were collected as whole 

water samples into 1-L baked amber glass bottles and analyzed 

at the NWQL for 69 compounds by gas chromatography mass 

spectrometry (GC/MS; appendix 2, table 2.5; Zaugg and 

others, 2006).

Weekly filtered water samples were analyzed for 

glyphosate by using an enzyme-linked immunosorbent assay 

(ELISA) at the USGS Texas Water Science Center (Mahler 

and others, 2017). For all but 11 sites, glyphosate also was 

analyzed twice during the study period (table 5; appendix 1, 

table 1.1) at the Kansas OGRL by using solid-phase extraction 

and LC-MS/MS (Meyer and others, 2009). These data were 

used to evaluate quality control of the data analyzed by using 

the ELISA method.

Stable nitrogen (15N) and oxygen (18O) isotopes of 

nitrate were measured once at all sites (table 5; appendix 1, 

table 1.1). Samples were filtered into bottles and frozen until 

nitrate concentration data were received and then shipped 

to the USGS Reston Stable Isotope Laboratory in Reston, 

Virginia. Isotopic analyses were done by following the 

method of Coplen and others (2012). Dissolved nitrate in 

water is converted to nitrous oxide (N2O) by denitrifying 

bacteria, and the nitrous oxide is analyzed for nitrogen and 

oxygen isotopic abundance by continuous-flow isotope-ratio 

mass spectrometry.

For analysis of the microcystins class of algal toxins, 

water samples were processed and analyzed by the OGRL 

following methods outlined in Loftin and others (2016). 

Unfiltered samples were lysed by three sequential freeze-thaw 

cycles at −20 °C and 25 °C and then syringe filtered through 

0.7-μm glass fiber filters and frozen until analysis. Algal toxins 

were quantified by using the microcystin ELISA method with 

a minimum reporting level of 0.10 micrograms per liter.

Polar Organic Compound Integrative Samplers

The POCIS were processed for analysis of pesticides 

and pharmaceuticals by using the methods described in 

Alvarez (2010) and Van Metre and others (2017a). At CERC, 

the sample from each POCIS was individually extracted 

with methanol, and extracts were concentrated to 1 milliliter 

(mL). Concentrated extracts were sealed in 1-mL amber 

glass ampules and shipped to the NWQL in Denver, Colo., 

for analysis. At the NWQL, the extracts were transferred to 

analytical vials and diluted 1:100, which was required so as 

not to overwhelm the instrument with the high concentrations 

of some compounds and to prevent ionization suppression 

or enhancement of internal standards by the POCIS 

extracts during LC-MS/MS analysis. Laboratory blank and 

laboratory-fortified spike samples were prepared by using 

comparable volumes of methanol and then were processed 

along with the POCIS extracts. The extracts were analyzed for 

concentrations of the original 225 pesticides and degradates 

(LCM60; appendix 2, table 2.3.1), and pharmaceuticals 

(appendix 2, table 2.4), by using the LC-MS/MS methods 

described previously for the discrete water samples.

Continuous Streamflow, Stage, and 

Water Temperature

Discharge data collected at active USGS streamgages 

(28 sites) were continuously telemetered to the public in real 

time via the USGS NWIS database. Four additional sites had 

streamgages operated by outside agencies, and 19 sites had 

pressure transducers installed to continuously measure stream 

stage. At these 19 sites, the raw stage data were processed 

with the HOBOware graphing and analysis software (Onset 

Computer Corporation, 2014). This process included applying 

corrections to the stage values with barometric pressure 

readings and comparing tape-down measurements from 

the reference point to the water surface to ensure that the 

instruments functioned consistently and reliably while they 

were in service.

The water temperature data were also processed with the 

HOBOware software (Onset Computer Corporation, 2012); 

values were checked for outliers that could indicate that the 

data logger was out of the water, such as with very low flow 

conditions. The general procedure used to assess the validity 

of temperature readings that appeared inordinately high was 

to first review streamflows at the site to determine whether the 

high temperature values corresponded in time to minimal stage 

values, then compare these temperature values with those of 

nearby sites to assess whether the data logger was recording 

air rather than water temperature. Erroneous water temperature 

data were subsequently deleted from the data file.
Sample Analyses 33

Focused Studies

Pesticides from the Small-Volume Pesticide 

Automated Samplers

Daily composite samples from the pesticide autosamplers 

(vials 1 through 7) were analyzed for pesticide concentrations 

by the EPA OPP Analytical Chemistry Laboratory. Sample 

splits of the weekly composite sample (vial 9) and the spike 

sample (vial 8) were analyzed for pesticide concentrations by 

the NWQL in Denver, Colo., as well as the OPP laboratory. 

The NWQL analyzed one split sample for 225 current-use 

pesticides (appendix 2, table 2.3.1) following the methods 

described earlier in the text (Sandstrom and others, 2016). 

The OPP laboratory used the same direct aqueous-injection 

LC-MS/MS method and instrument model (Agilent Model 

6460) used by the NWQL (Sandstrom and others, 2016), with 

similar detection levels, to analyze for 222 pesticides and 

degradates (appendix 2, table 2.12).

Pesticide Analysis in Biofilms

Biofilms were analyzed for 94 current-use pesticides 

(appendix table 2.11) at the USGS Organic Chemistry 

Research Laboratory (OCRL) in Sacramento, Calif., by using 

pressurized solvent extraction, cleanup with carbon/alumina 

(adapted from Hladik and McWayne, 2012), followed by 

GC-MS/MS analysis (instrument methods from Hladik and 

others, 2016).

Suspended-Sediment Passive Samplers

Aliquots of fine fractions (less than 63 μm) of suspended 

sediment collected from passive samplers and of streambed 

sediment were analyzed for major and trace elements by 

AGAT Laboratories, Mississauga, Ontario, Canada, using 

inductively coupled plasma-optical emission spectroscopy 

and inductively coupled plasma-mass spectrometry, following 

dissolution in a mixture of hydrochloric, nitric, perchloric, and 

hydrofluoric acids (similar to the method documented in Smith 

and others, 2013). Particle size was measured at the USGS 

Maryland-Delaware-D.C. WSC in Baltimore, Md., using a 

laser in situ scattering transmissometer (LISST-100X; Gellis 

and others, 2018). Additional aliquots of suspended sediment 

and streambed sediment (63-μm sieved) were analyzed 

for radionuclides (lead-210, radium-226, cesium-137, and 

beryllium-7) at the USGS Sediment Radioisotope Laboratory 

in Menlo Park, Calif. Radionuclides were analyzed by using 

a high-resolution gamma spectrometer with an intrinsic 

germanium detector, following methods described in Van 

Metre and others (2004).

Ecological Surveys

Aquatic Biota

Benthic macroinvertebrate samples were processed 

by the Biological Unit of the NWQL using a methodology 

similar to that used in the State of California’s Surface Water 

Ambient Monitoring Program (SWAMP; Woodard and others, 

2012). Briefly, the sample was sorted to attain a minimum 

of 600 organisms, which then were identified to the lowest 

possible taxonomic level (generally the species or genus 

level). Quality assurance was verified in both the sorting step 

and the taxonomic step by a second taxonomist, following 

the QA/QC procedures in Moulton and others (2000). 

Taxonomic and enumeration results were uploaded to BioData 

(U.S. Geological Survey, 2016).

Benthic algal samples were processed in the field by 

filtering onto 0.47-μm glass-fiber filters. The filters were 

analyzed at the NWQL for chlorophyll a and pheophytin a

by using EPA method 445.0 and for algal ash-free dry mass 

by using USGS method B-3520-85 (appendix 2, table 2.10; 

Britton and Greeson, 1989; Arar and Collins, 1997).

Algal samples preserved with formalin were analyzed 

for diatom community composition and abundance at the 

INSTAAR laboratory at the University of Colorado, Boulder, 

following NAWQA protocols (Charles and others, 2002) 

with the following modification. Four replicate slides of the 

diatoms were made by using Battarbee chambers to obtain 

random distribution of cells on cover slips (Battarbee, 1973). 

A pre-count collection of voucher flora was created, based 

on examination of 80 percent of the algal slides. The voucher 

flora included images of all taxa encountered, with a greater 

number of images for rare and previously unknown taxa. 

The images were sorted into operational taxonomic units 

(OTUs) and assigned OTU codes. Samples and their order of 

analysis were randomly assigned to two analysts. Ten percent 

of samples were reanalyzed by each analyst, and 10 percent 

of samples were analyzed in cross comparison. Finally, OTU 

codes were translated into formal scientific names following 

the taxonomy in the USGS BioData program and Diatoms 

of the United States (Spaulding and others, 2010). Voucher 

slides, digested material, and the voucher flora were archived 

at INSTAAR. The soft algae fractions of the samples were 

stored at INSTAAR for possible analysis at a later time.

Physical Habitat

Data collected from habitat surveys were recorded on 

electronic field forms and reviewed later in the office by 

USGS staff. Any values on the field forms that were suspect 

(such as typographical errors) were resolved, and the data 

were archived for a future data release.
34 Design and Methods of the California Stream Quality Assessment, 2017

Streambed and Bank Sediment

Aliquots of bulk (homogenized, 2-mm sieved) 

streambed sediment were analyzed for grain size at the 

USGS Missouri Sediment Laboratory in Rolla, Mo. Major 

and trace elements and organic carbon were analyzed in 

aliquots of streambed sediment (less than 63 μm) by AGAT 

Laboratories using the same methods described earlier in the 

text for the suspended-sediment passive samples. Aliquots of 

the streambed samples (less than 63 μm) were analyzed for 

radionuclides at the USGS Sediment Radioisotope Laboratory 

in Menlo Park, Calif., using the same methods described 

earlier in the text for the suspended-sediment passive samples.

Aliquots of streambed sediment (less than 2 mm) 

were sent to the USGS NWQL for analysis of three organic 

contaminant schedules. One aliquot was analyzed for organic 

wastewater indicator compounds by using accelerated 

solvent extraction (ASE), solid-phase extraction cleanup, and 

GC/MS (appendix 2, table 2.6; Burkhardt and others, 2006). 

A custom method was used for selected organohalogens 

in sediment (chlorinated and brominated compounds 

including insecticides, polychlorinated biphenyls [PCBs], 

and polybrominated diphenyl ethers [PBDEs]), in which 

the sample was extracted by ASE, followed by solid-phase 

extraction cleanup and analysis by electron-capture negative 

ionization mode GC/MS with selected ion monitoring 

(appendix 2, table 2.8; reported in Mahler and others, 

2009; Wagner and others, 2014). Hormone compounds 

in bed sediment were analyzed using a custom method 

(appendix 2, table 2.9) consisting of pressurized solvent 

extraction, then two solid-phase extraction steps to isolate the 

compounds and further clean the extract (Fischer and others, 

2015), followed by compound derivatization and analysis 

by gas chromatography with tandem mass spectrometry 

(GC-MS/MS) using procedures similar to Foreman and 

others (2012). An additional aliquot of streambed sediment 

(less than 2 mm) was sent to RTI Laboratories, Livonia, 

Michigan (https://rtilab.com/), for analysis of 17 PAHs using 

EPA method 8270D (U.S. Environmental Protection Agency, 

2014), with extraction by ASE and analysis by GC/MS with 

selected ion monitoring (appendix 2, table 2.7). Another 

aliquot of streambed sediment (less than 2 mm) was analyzed 

for 118 pesticides (most of which are in current use) at the 

USGS OCRL in Sacramento, Calif., by using pressurized 

solvent extraction, followed by a series of cleanup procedures 

(gel permeation chromatography and SPE with either carbon/

alumina or Florisil), followed by GC/MS analysis (Hladik and 

McWayne, 2012).

Bank material (less than 2 mm) was analyzed for 

grain size at the USGS Maryland-Delaware-D.C. WSC, 

Baltimore, Md. Major and trace elements and organic 

carbon were analyzed by AGAT Laboratories, Mississauga, 

Ontario, Canada.

Sediment Toxicity Testing

Whole sediment toxicity tests were conducted with the 

amphipod Hyalella azteca (28-day exposures) and with the 

midge Chironomus dilutus (10-day exposures), following 

methods in U.S. Environmental Protection Agency (2000) 

and American Society for Testing and Materials International 

(2016), with detailed test conditions noted in Moran and others 

(2017). As much as 1.8 L (assuming a 50/50 split of solids and 

liquids) of the composited streambed sediment was used for 

toxicity testing. Testing for each species included endpoints 

of survival, weight, and biomass of test organisms. Exposures 

were conducted at 23 °C in 300-mL beakers containing 

100 mL of sediment with two volume additions per day of 

overlying water. Ten organisms were exposed in each beaker 

with four replicate beakers per site. Endpoints were survival, 

growth (dry weight for amphipods and ash-free dry weight for 

midge), and biomass for each test species. Response of each 

endpoint for each species was compared to a standard control 

sediment from Spring River, Mo. (Besser and others, 2015). 

Comparisons also were made using a reference envelope 

approach, which addresses the variability observed from 

reference sediments that were primarily from undeveloped 

watersheds, had minimal levels of contamination, and showed 

acceptable biological performance, as defined in Kemble and 

others (2013).
Quality Assurance and Quality Control 35

Quality Assurance and Quality Control

This section describes the QA/QC procedures for 

stressor assessments (specifically, constituents in discrete 

water samples, POCIS samples, and streambed-sediment 

samples), as well as for overall project-specific training and 

management. QA/QC procedures for the focused studies were 

described in the “Sample Collection and Processing” section. 

For the ecological surveys, QA/QC procedures are built into 

the taxonomic identification process and are described in the 

“Sample Analyses” section.

Quality assurance/quality control for project data is an 

iterative process that begins when samples are collected, 

continues through the establishment of sample records 

in NWIS, and ends with the final acceptance of data as 

reviewed and approved or, in rare cases, rejected. This 

process allows for a continuous review of records by field 

personnel, laboratory analysts, RSQA team data managers, 

QW specialists, and other team members. Specific database 

scripts were developed to check sample coding logic and 

to generate data tables in multiple formats for data review 

and confirmation.

Quality assurance/quality control procedures maintain 

the integrity, accuracy, and legal defensibility of results from 

data collection and assessment. Documented USGS QA/

QC policies and procedures for environmental sampling 

were implemented in the study to ensure that the data can 

be interpreted properly and are scientifically defensible 

(Mueller and others, 1997; U.S. Geological Survey, 2006). 

Quality control samples were collected to identify, quantify, 

and document bias and variability in data that result from 

the sampling procedure (through field QC sampling) and 

laboratory procedures (through laboratory QC sampling). 

Field QC sampling is used to estimate bias and variability 

from sample collection, processing, shipping, and handling of 

samples. Laboratory QC sampling documents the variability of 

analytical methods and sample preparation in the laboratory.

To ensure that all field crews followed consistent sample 

collection and processing procedures, classroom training 

was held for field personnel before the sampling period. In 

addition, all personnel worked through a full suite of sample 

collection and sample processing procedures in the field just 

before the start of the CSQA sampling period. To maximize 

efficiency in the field, all sampling scheduling and preparation 

of weekly sampling supplies were handled centrally by USGS 

personnel who had provided similar support to previous 

RSQA studies. Sample bottle packs were assembled at the 

USGS Sacramento Field Office by USGS staff at least 1 week 

before sampling. The bottle packs consisted of the necessary 

bottles, filters, preservatives, labels, and ASRs for each stream 

site. Centralizing the assembly and distribution of sample 

bottle packs helped ensure that correct sample coding, sample 

schedules, and timing of QC samples matched the sampling 

plan and reduced errors in the sample login process at the 

analytical laboratories.

The QC samples for constituents measured in water 

included field blanks, field matrix spikes, and replicates 

(table 6; appendix 1, table 1.1). The QA/QC plan was 

designed to have 5 percent or more QC samples for inorganics 

and 10 percent for organics, to ensure that QC samples were 

distributed across the region (spatially) and study period 

(temporally), and to assign collection of QC samples to 

every field crew. Field blanks were used to test whether field 

cleaning procedures would adequately remove any equipment 

contamination introduced by sampling at previous sites 

and to ensure that sample collection, processing, handling, 

and shipping did not result in contamination (Mueller and 

others, 1997; U.S. Geological Survey, 2006). Field replicates 

provided a measure of the variability introduced during 

sample processing and analysis (Mueller and others, 1997; 

U.S. Geological Survey, 2006). When water samples were 

collected from the churn, two aliquots of water were split 

from the churn into separate containers and analyzed as field 

replicates (split replicates). When grab samples were collected, 

replicates were collected sequentially directly from the stream. 

Field and laboratory matrix spikes were used to assess the 

potential bias for analytes in a particular sample matrix. Bias 

is estimated from spiked samples by calculating the percentage 

of the added analyte (spike material) that is measured 

(recovered) in the sample at the laboratory (Mueller and 

others, 1997; U.S. Geological Survey, 2006). Recovery can be 

either greater than or less than 100 percent, so the bias can be 

either positive or negative. However, matrix interference and 

analyte degradation generally result in a negative bias.

Field blanks were collected once from 16 to 18 sites for 

each of the basic laboratory schedules (major ions, nutrients, 

dissolved organic carbon, pesticides, and glyphosate by 

immunoassay; table 6) that were part of the comprehensive 

stressor assessments. The targeted number of total QC 

samples per analytical schedule was 10 percent for organic 

contaminants and 5 percent for inorganic constituents, 

with QC samples distributed throughout the study area, the 

study period (appendix table 1.1), and among the nine field 

crews. CSQA field QC samples represented 5–8 percent 

of environmental samples for major ions, nutrients, and 

DOC; 11 percent for mercury; and 16–18 percent for the 

broad-spectrum pesticide methods, glyphosate by LC-MS/MS, 

pharmaceuticals, and organic wastewater indicators, all of 

which met the frequency recommendations (table 6).

For pesticides, pharmaceuticals, and organic wastewater 

indicators, field blanks and field replicates each represented 

about 3–5 percent of the environmental samples (table 6). 

Field matrix spikes were created for analyses of all organic 

contaminants, with the exception of glyphosate analysis by 

immunoassay. The frequency of the field matrix spikes ranged 

from 5 to 10 percent for organic contaminants, depending 

on the laboratory schedule (table 6). For glyphosate by 

immunoassay, laboratory matrix spikes (not shown in table 6) 

were analyzed, which represented an additional 2 percent of 

environmental samples.
36 Design and Methods of the California Stream Quality Assessment, 2017

Table 6.

Type of 

sample

Sample 

counts

Ratio of QC to 

environmental samples

(percent)

Actual Recommended1

Laboratory schedule: Major ions

 Environmental 488 7.6 5

Blank 16 3.3

 Replicate 21 4.3 —

 Spike 0 0 —

Laboratory schedule: Nutrients

 Environmental 488 7.6 5

Blank 16 3.3

 Replicate 21 4.3 —

 Spike 0 0 —

Laboratory schedule: Dissolved organic carbon

 Environmental 485 5.0 5

Blank 17 3.5

 Replicate 20 4.1 —

 Spike 0 0 —

Laboratory schedule: Pesticides

 Environmental 488 17.4 10

Blank 18 3.7

 Replicate 22 4.5 —

 Spike 45 9.2 —

Laboratory schedule: Supplemental pesticides

 Environmental 488 17.6 10

Blank 18 3.7

 Replicate 21 4.3 —

 Spike 47 9.6 —

Laboratory schedule: Glyphosate (immunoassay)

 Environmental 487 7.6 10

Blank 16 3.3

 Replicate 21 4.3 —

 Spike 20 20 —

Table 6. —Continued

Type of 

sample

Sample 

counts

Ratio of QC to 

environmental samples

(percent)

Actual Recommended1

Laboratory schedule: Pharmaceuticals

 Environmental 233 16.3 10

Blank 11 4.7

 Replicate 13 5.6 —

 Spike 14 6.0 —

Laboratory schedule: Organic wastewater indicators

 Environmental 233 15.9 10

Blank 12 5.2

 Replicate 12 5.2 —

 Spike 13 5.6 —

Laboratory schedule: Glyphosate (OGRL)

 Environmental 147 15.0 10

Blank 9 6.1

 Replicate 13 8.8 —

Laboratory schedule: Mercury

 Environmental 244 11.1 5

Blank 14 5.7

 Replicate 13 5.3 —

 Spike 0 0 —

Laboratory schedule: Algal toxins

 Environmental 84 12 10

Blank 5 6

 Replicate 5 6 —

 Spike 0 0 —

Laboratory schedule: Isotopes

 Environmental 84 10.7 5

Blank 0 0

 Replicate 9 10.7 —

 Spike 0 0 —

1Recommendations for total QC samples are 10 percent of environmental 

samples for organic constituents and 5 percent for inorganic constituents.

2Although no field matrix spike samples were analyzed, laboratory matrix 

spike samples (not shown in this table) represented an additional 4 percent of 

environmental samples.

Table 6. Summary counts of environmental, field blank, replicate, and spike samples of stream water from the 85 stream sites sampled 

in the California Stream Quality Assessment study of the U.S. Geological Survey National Water-Quality Assessment Project in 2017.

[OGRL, U.S. Geological Survey Organic Geochemistry Research Laboratory in Lawrence, Kansas; QC, quality control; —, not applicable]
Quality Assurance and Quality Control 37

Quality assurance/quality control procedures generally 

were simpler for sediment samples than for water samples 

and included the use of field replicates (splits of composite 

bed-sediment samples) as well as (for pesticides) laboratory 

blanks and laboratory matrix spikes. In addition, two 

additional streambed samples (for a total of three samples 

per site) were collected at a subset of seven sites to assess 

temporal variability in bed-sediment contaminants. Counts 

of environmental and QC samples for constituents in bed 

sediment are shown in table 7. Field replicates represented 

11 percent of environmental samples for pesticides, PAHs, 

organic wastewater indicators, hormones, halogenated organic 

compounds, trace elements, radionuclides, and grain size. For 

pesticides in sediment, the laboratory blanks and laboratory 

matrix spikes analyzed each represented about 7 percent of 

environmental samples (table 7).

Quality assurance included maintaining standardized 

sample collection and handling protocols among all field 

personnel as described in the National Field Manual 

(U.S. Geological Survey, variously dated) for water and 

sediment sampling and in Moulton and others (2002) for 

ecological sampling. All sampling and handling protocols 

were reviewed by field personnel involved in the CSQA study 

during training courses, before field work began. Additionally, 

several programs exist in the USGS Quality Systems 

Branch to help document the quality of project results. For 

laboratory analyses conducted by the NWQL, documented 

QC included double-blind analyses of blanks for organic and 

inorganic constituents in water and provision of graphical and 

tabular control data for the analytical lines. Field personnel 

involved in the CSQA study are tested annually to verify their 

proficiency in collecting field data, including temperature, pH, 

dissolved oxygen, alkalinity, and specific conductance.

For POCIS samples, field QC samples included replicates 

and blanks, and their total number represented 20 percent of 

the environmental POCIS samples (appendix 1, table 1.5). 

Field replicate samples were obtained by deploying a second 

canister containing 2 POCIS, one for each of the pesticide 

and pharmaceutical schedules, at seven sites (11 percent). At 

six sites (9 percent), the environmental POCIS sample was 

accompanied by a field blank that was used to assess any 

accumulation of target and nontarget compounds from the 

air during shipment and deployment. All POCIS and blank 

canisters were stored on ice during transport to and from the 

field location. The blank canisters were open to the air at 

the same time and place as the environmental POCIS were 

exposed to air during deployment and retrieval. Between 

deployment and retrieval of the environmental POCIS 

samples, the POCIS blank canisters were kept sealed and 

stored between –20 and 0 °C.

Water-quality data from each sampling event were 

reviewed for completeness, precision, bias, and transcription 

errors when received from the laboratory as part of the 

QA/QC procedures. Water-quality and sediment-quality data 

were stored in the NWIS database; the data are available 

for retrieval at https://nwis.waterdata.usgs.gov/nwis/sw and 

through the data retrieval application at the RSQA project 

website (https://webapps.usgs.gov/RSQA/). The NWQL 

provides all QA/QC documentation for analytical services at 

https://nwql.usgs.gov/Public/quality.shtml. Data also will be 

published in ScienceBase.

Temperature calibration checks were completed on 

the HOBO U20 and U22 units before deployment and after 

retrieval according to the USGS National Field Manual 

(Wilde, 2008). The USGS WSC in Columbus, Ohio, maintains 

a commercially refrigerated water bath specifically for the 

purposes of thermometer and temperature sensor calibration. 

The bath is calibrated to a National Institute of Standards and 

Technology (NIST)-certified thermometer, and calibration 

checks on temperature sensors are conducted at 3.00, 10.05, 

15.03, 25.05, 30.04, and 40.03 °C. Units found to be within 

their performance range are certified for deployment. Pressure 

transducer units also were checked that their barometric 

pressure reading was within 1 percent of a NIST-certified 

barometer before deployment and after retrieval. This was 

done at the atmospheric pressure for the USGS WSC in 

Columbus, Ohio. Air pressure transducer readings from 

sensors were not checked against NIST-certified barometers in 

the field. However, continuous readings were verified during 

the correction process against water-quality sonde readings 

measured during discrete sampling.

Continuous temperature and pressure data processing 

was done by a single person to maintain consistency within 

the CSQA study and included the following steps. Data were 

evaluated for erroneous readings at the start of deployment 

and the end of retrieval for situations where the device was 

actively logging data while in route to the site or stream. These 

data were removed. The data were then plotted to identify 

significant spikes or dips in the record, including possible 

loss of record. Spikes in the data that were inconsistent with 
38 Design and Methods of the California Stream Quality Assessment, 2017

observed changes in air temperature, weather events, or flow, 

or that were not corroborated with other nearby records, were 

removed from the record.

Table 7. Summary counts of environmental, field replicate, field 

spike, and temporal samples of bed sediment collected from 82 

stream sites in the California Stream Quality Assessment study of 

the U.S. Geological Survey National Water-Quality Assessment 

Project in 2017.

[Temporal bed sediment samples, which were collected at 7 sites (table 5), are 

not included in environmental sample counts and percentages of QC samples. 

Abbreviations: NAV, not available; QC, quality control; —, not applicable]

Type of sample Sample counts

Ratio of QC to environmental 

samples

(percent)

Actual Recommended1

Laboratory schedule: Pesticides

 Environmental 82 26 10

 Replicate 9 11 —

Blank2 6 7.3

 Spike2 6 7.3 —

 Temporal NAV NAV —

Laboratory schedule: Polycyclic aromatic hydrocarbons

 Environmental 82 11 10

 Replicate 9 11 —

 Temporal 14 0 —

Laboratory schedule: Organic wastewater indicators

 Environmental 82 11 10

 Replicate 9 11 —

 Temporal 12 0 —

Laboratory schedule: Hormones

 Environmental 82 11 10

 Replicate 9 11 —

 Temporal 13 0 —

Laboratory schedule: Halogenated organics

 Environmental 82 11 10

 Replicate 9 11 —

 Temporal 12 0 —

Laboratory schedule: Trace elements

 Environmental 81 11 5

 Replicate 9 11 —

 Temporal 14 0 —

Laboratory schedule: Grain size

 Environmental 82 11 5

 Replicate 9 11 —

 Temporal 0 0 —

Laboratory schedule: Radionuclides

 Environmental 82 11 5

 Replicate 9 11 —

 Temporal 14 0 —

1Recommendations for total QC samples are 10 percent of environmental 

samples for organic constituents and 5 percent for inorganic constituents.

2Laboratory blanks and laboratory matrix spikes were analyzed for pesticides in bed sediment.
Data-Management Procedures 39

Data-Management Procedures

An important goal of data management for the CSQA 

study is to have the data reviewed, approved, and stored 

in a USGS approved database that is appropriate for the 

specific type of data (for example, water quality, streamflow 

or stage, and biological). Because CSQA sampling sites 

were only in California, data entry and retrieval for sites 

were managed by the local WSC. The NWIS station 

number that is used to identify a site (table 1) is the master 

indexing and retrieval element for accessing data specific 

to the site. The NWIS database is the repository for most 

of the water-quality and streamflow data, which constitute 

most of the CSQA data. Additionally, a data-management 

team composed of national RSQA staff and local CSQA 

staff was created to facilitate the data-management process. 

Centralization of the data-management process was adopted 

to ensure consistency among all RSQA study areas and the 

respective WSCs. Nine main steps were implemented in the 

data-management process:

1. Sampling matrix and sample coding design;

2. Electronic field form use, including barcoding;

3. Sample status checks at all laboratories;

4. NWIS sample record checks;

5. Data transfer from laboratory to NWIS;

6. Establishment of project networks;

7. Sample coding and field parameter checks;

8. Data quality checks;

9. Approval of data in NWIS and other databases, 

as appropriate.

Sites for the CSQA study were assigned the appropriate 

network designations in NWIS ProjectNetworks (Dupré 

and others, 2013), which allows integration with similar 

sites across many regions and designation of the network 

type in NWIS. These network designations were obtained 

from the project planning documents and, where possible, 

kept consistent with other network designations used in 

previous regional studies. ProjectNetworks documentation 

enabled local CSQA personnel to establish their sites in 

NWIS ProjectNetworks.

Before the start of sampling, the manager of the 

data-management team (henceforth, data manager) prepared 

a matrix that would be the sampling design and coding plan 

for all aspects of the field activities. The sampling matrix 

distributed QC samples approximately equally across sites, 

sample teams, and time periods for optimum coverage. The 

matrix also served as a summary for the type, frequency, and 

location of environmental and QC samples to be collected 

(appendix 1, table 1.1). A sample coding scheme was 

developed by the data manager that was used by the CSQA 

sampling teams to ensure a well-structured and manageable 

dataset. Additionally, training and written guidelines for 

sampling coding were made available to sampling teams 

before the start of sampling.

Most of the CSQA sampling teams used the Personal 

Computer Field Form (PCFF) version 7.2 software created 

by the USGS, which provides electronic field forms for data 

collection at sampling sites. Some field teams did not use the 

PCFF; in these cases, field data were recorded on paper field 

forms and then transferred to electronic digital forms in the 

office. In any case, the use of PCFF did not preclude the use 

of paper field forms when sampling; a two-page standardized 

form for CSQA water-quality field notes was routinely used 

at all sites to record basic site conditions when samples were 

collected and to affix bar codes that identified the samples. 

The bar codes are unique identifiers used to associate specific 

sample types with a site and the sampling event. The PCFF 

software streamlines the process of uploading (logging in) 

field data and sampling codes to NWIS by automatically 

generating the batch load files required by NWIS (qwsample 

and qwresult) and thereby improves the efficiency of data 

flow from field and laboratory to database. The information 

uploaded to NWIS for each sample is stored under a unique 

number associated with that sample, as are all results received 

later from the laboratory. In addition, the automation of data 

upload to NWIS limits the incidence of transcription errors 

that can occur during the manual entry of data into NWIS. The 

field-supply manager provided ASRs to the sampling teams 

each week along with the corresponding bottle sets.

Sample shipment schedules were established before 

the start of sampling for CSQA, and generally shipments 

were made twice per week (appendix 1, table 1.4). Sampling 

teams and other local WSC personnel were responsible 

for the shipment process. The data manager tracked the 

shipments to verify that the shipped samples were received 

at each laboratory (1) within the correct holding times, 

(2) in the proper condition (for example, chilled samples 

received at the appropriate temperature of 4 °C or less), and 

(3) with proper documentation. The data manager worked 

with the laboratories to correct problems with mislabeled 

samples or ASRs in a timely manner and to communicate 

problem-resolution approaches to local WSC personnel. 

During this process, the data manager also established the 
40 Design and Methods of the California Stream Quality Assessment, 2017

connection between the USGS Laboratory Information 

Management System used to transfer sample results and the 

NWIS database used to store and receive sample results.

During sampling and the corresponding establishment 

of sample records in NWIS, the data manager inspected 

sample coding and procedures to ensure that sample records 

were established properly and in a consistent manner. Sample 

coding or the procedures of coding were modified if found to 

be inaccurate or inconsistent. These modifications involved 

changes or corrections to sample time offsets, sample type 

coding, or other documentation at the NWQL or in NWIS. 

Modifications in sample coding or procedures related to 

data management or sample submittal were communicated 

immediately to sampling teams to ensure that appropriate 

adjustments were made before the next sampling.

Most of the laboratories used for CSQA sample analysis 

transmitted sample results through the Water Quality Data 

Exchange (QWDX) for automatic upload into the NWIS 

database. For those laboratories without the ability to use 

QWDX, sample results were loaded into NWIS by using 

manually created batch files. Batch files were created by 

the data manager upon receipt of electronic data from the 

laboratory and were loaded into NWIS by the data manager 

or the database administrator for the local WSC. The data 

manager verified that the batch files of data were properly 

loaded into NWIS.

Similarly, the Ecology Sampling Coordinator verified that 

algal, macroinvertebrate, and habitat data were properly loaded 

into BioData and into the ScienceBase digital data repository 

supported by the USGS (https://www.sciencebase.gov/catalog/

item/5e15f326e4b0ecf25c55c034). Data files provided through 

email by laboratories and data not applicable to NWIS (for 

example, CERC toxicity data) were stored electronically 

in the RSQA team database rather than in NWIS. These 

data, and data such as QC sample results not publicly 

available through NWIS, will be released separately through 

USGS ScienceBase.

After sampling was completed, the data manager 

inspected the NWIS sample records for completeness 

regarding field data collection, including stream measurements 

(streamflow, stage, sampling points, stream width, and so 

forth), field parameters (pH, air and water temperature, 

specific conductance, dissolved oxygen), and sample coding 

(sample purpose, purpose of site visit, sampling method, 

sampler type, and multiple QC-related sample codes). 

Manual checks were made for each sample, and any needed 

corrections were communicated to WSC personnel.

National RSQA staff scientists reviewed the water-quality 

and sediment-quality results received from the laboratories. 

The water-quality data reviews included identification and 

review of extremes in the data (outliers), inconsistencies or 

unexpected results, major differences between environmental 

samples and replicates, detected values in blanks, surrogate 

recoveries, and analyte recoveries in spike samples, as 

well as review of sample coding. The RSQA staff scientists 

communicated requests for reruns, reloads, and verification 

of results to the laboratory; they worked closely with the 

data manager to verify completeness and accuracy of sample 

results. After completion of data review by RSQA staff, 

the database administrator at the USGS California WSC in 

Sacramento, Calif., changed the data quality indicator (DQI), 

depending on the results of the review, for groups of parameter 

types to “reviewed and accepted” (R) or, in a few rare cases, 

“reviewed and rejected” (Q).

Water-quality, sediment, and ecological survey data 

will be available to the public in NWIS and ScienceBase, as 

well as at the RSQA mapping and data application website, 

which allows mapping, querying, and data downloads 

(https://webapps.usgs.gov/RSQA/#!/download).
References Cited 41

Continuous stage and temperature data measured by 

the HOBO U20-001-04 digital loggers were reviewed and 

corrected as described in the “Quality Assurance and Quality 

Control” section and will be published in ScienceBase.

Summary

This report describes the design and methods used during 

an intensive regional study, designated by the California 

Stream Quality Assessment (CSQA), to assess stream quality 

in the central coastal region of California, United States, where 

the larger valleys contain intense urbanization or agriculture, 

or both. This is the last of five regional stream-quality 

assessment (RSQA) studies conducted by the U.S. Geological 

Survey (USGS). The overall goal of the RSQA studies is 

to improve the understanding of multiple water-quality 

stressors that affect wadeable streams throughout the region 

by evaluating relations between these stressors and biological 

indicators of stream health. The RSQA study design has 

three elements: comprehensive stressor assessments, focused 

studies, and ecological surveys. In CSQA, 85 wadeable stream 

sites were selected throughout the Central California Foothills 

and Coastal Mountains (an EPA Level III ecoregion) to 

determine the occurrence and levels of multiple stressors, and 

to assess stream habitat and the condition of aquatic algal and 

macroinvertebrate communities during spring 2017. A wide 

variety of potential stressors was assessed in the CSQA study, 

including nutrients, trace elements and major ions in water, 

several classes of organic contaminants in water and sediment, 

suspended sediment, and flow alteration. Data on water and 

sediment-quality constituents came from discrete, continuous, 

and integrative samples collected at all sites, supplemented by 

in-depth characterizations of selected stressors from focused 

studies conducted at subsets of sites.

The 85 sites were divided into a Southern group 

(36 sites) and a Northern group (49 sites). Water quality was 

measured at all sites during either a 4- or 6-week period from 

mid-March to mid-May 2017, with sampling at the Southern 

sites starting 3 weeks earlier than at the Northern sites. After 

the water-quality sampling period, an ecological survey 

was conducted at each site in May 2017 to assess algal and 

macroinvertebrate communities, the presence of harmful 

algal toxins, contaminants in sediment, sediment toxicity to 

amphipods and midge larvae, and the physical habitat of the 

stream. This report describes procedures used for sample 

collection and processing, sample analyses, quality assurance 

and quality control, and data management.

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48 Design and Methods of the California Stream Quality Assessment, 2017

Appendix 1. Description of the Sampling Timelines, Matrix, Collection, and 

Processing for Water, Sediment, and Ecological Samples

Table 1.1. Sampling matrix for the 85 sites sampled as part of the U.S. Geological Survey California Stream Quality Assessment in 2017 

is provided as a downloadable Excel file available at https://doi.org/10.3133/sir20201023.

Table 1.2. Onset Computer Corporation specifications for the HOBO Water Temp Pro v2 U22 and U20 water-level loggers used to 

monitor continuous water temperature and water level, respectively, at selected stream sites as part of the California Stream Quality 

Assessment study of the U.S. Geological Survey National Water-Quality Assessment Project in 2017.

[°C, degree Celsius; °F, degree Fahrenheit; ±, plus or minus; m/s, meter per second; kPa, kilopascal; psi, pound per square inch; m, meter; ft. foot; FS, full scale 

pressure; cm, centimeter; <, less than]

Specifications Range

HOBO® Water Temp Pro v2 U22 Logger

Operation range–40 to 70 °C (–40 to 158 °F) in air; maximum sustained temperature of 50 °C (122 °F) in w

 Accuracy±0.21 °C from 0 to 50 °C (±0.38 °F from 32 to 122 °

 Resolution 0.02 °C at 25 °C (0.04 °F at 77 °F)

 Response time (90 percent)5 minutes in water; 12 minutes in air moving 2 m/s (typica

 Stability (drift)0.1 °C (0.18 °F) per ye

HOBO® U20-001-04 Water Level Logger

Operation range0 to 145 kPa (0 to 21 psi); approximately 0 to 4 m (0 to 13 ft)

water depth at sea level

 Accuracy±0.75 percent FS, 0.3 cm (0.01 ft) wat

 Resolution<0.014 kPa (0.063 psi); 0.14 cm (0.005 ft) wat

 Pressure response time (90 percent)<1 seco
References Cited Appendix 1 49

Table 1.3. Description of the data collection and processing steps for water samples collected during the U.S. Geological Survey 

California Stream Quality Assessment study in 2017.

[4.5 N H2SO4, 4.5 normal sulfuric acid; 7.5N HNO3, 7.5 normal nitric acid; AR, acid-rinsed; DH-81 and DH-95, sampling devices; DOC, dissolved organic 

carbon; EWI, equal-width increment sampling protocol; ft, foot; ft/s, foot per second; HCl, hydrochloric acid; Hg, mercury; L, liter; LS, Kansas; m, meter; 

mL, milliter; poly, polyethylene bottle; TX, Texas; UVA, ultraviolet absorbance; —, not applicable; < less than; >, greater than. Sample type labels are 

designated by the National Water Quality Laboratory: BGC, baked, amber glass wide-mouth jar, chilled; FA, filtered, acidified cations; FCC, filtered, chilled 

nutrients; FU, filtered, unpreserved anions; GCC, baked, amber glass bottle, chilled; GLY2, glyphosate by U.S. Geological Survey Kansas Water Science Center; 

IMMGLY, glyphosate by immunoassay; OWI, organic wastewater indicators; PEST, pesticide; PHARM, pharmaceutical; RU, raw, unpreserved physical properties; SSC, suspended sediment concentration; WCA, whole, chilled, acidified nutrients]

Steps

Method

EWI, >1.5 ft/s and depth >1 ft Multivertical grab, <1.5 ft/s

and width >10 ft (3 m)

Grab in centroid of flow, <1.5 ft/s,

width <10 ft (3 m) and depth <1 ft

Data collection based on stream width, depth, and velocity

1 Set up tagline and determine width of 10 

increments in transect.

 Set up tagline and determine width of 

5–10 increments in transect.

 Field rinse sample bottles in centroid of 

flow; then collect directly from stream.

2Determine transit rate using DH-8

(wading) or DH-95 (from bridge) and 

field rinse sample bottles/churn.

 Field rinse 1-L sample bottle and churn. 1-L poly jar (SSC).

3 Collect water samples at 10 increments 

using same transit rate; composite in 

churn.

Use DH-81/no nozzle or dip 1-

sample bottle with hand (wading) or 

weighted bottle sampler (bridge) at each 

increment; composite in churn.

1-L GCC (sample label OWI

4 — — 1125 mL clear poly bottle (sample label 

WCA).

5 — — 250 mL clear poly bottle (sample label 

RU).

6 — —500 mL BG

7 — — Collect 1-L sample using sample bottles 

in centroid of flow.

8Collect field parameters at five location

9Collect grab samples for DOC/UVA and Hg in centroid of flo

Process samples in field vehicle or station

10 Fill raw-sample bottles from churn.

 1-L poly jar (SSC).

1-L GCC (OWI

 125 mL clear poly 1(WCA).

 250 mL clear poly (RU).

fill 500 mL BGC amber glass jar fo

organics from churn, filtered in step 17.

 Fill raw-sample bottles from churn.

 1-L poly jar (SSC).

1-L GCC (OWI

 125 mL clear poly 1(WCA).

 250 mL clear poly (RU).

fill 500 mL BGC amber glass jar fo

organics from churn, filtered in step 17.

No churn required—bottles filled directl

from stream (see steps 1–7).

11Acidify WCA with 4.5N H2SO4 (1 vial).Acidify WCA with 4.5N H2SO4 (1 vial).Acidify WCA with 4.5N H2SO4 (1 

12Filter with capsule filter from chur

 250 mL clear AR poly 1(FA).

 125 mL brown poly (FCC).

 250 mL clear poly (FU).

 125 mL brown poly (Isotopes).

Filter with capsule filter from chur

 250 mL clear AR poly 1(FA).

 125 mL brown poly (FCC).

 250 mL clear poly (FU).

 125 mL brown poly (Isotopes).

Filter with capsule filter from 1-

 250 mL clear AR poly (FA).

 125 mL brown poly (FCC).

 250 mL clear poly (FU).

 125 mL brown poly (Isotopes).

13Acidfy FA with 7.5N HNO3.Acidfy FA with 7.5N HNO3.Acidfy FA with 7.5N
50 Design and Methods of the California Stream Quality Assessment, 2017

Table 1.3. Description of the data collection and processing steps for water samples collected during the U.S. Geological Survey 

California Stream Quality Assessment study in 2017.—Continued

[4.5 N H2SO4, 4.5 normal sulfuric acid; 7.5N HNO3, 7.5 normal nitric acid; AR, acid-rinsed; DH-81 and DH-95, sampling devices; DOC, dissolved organic 

carbon; EWI, equal-width increment sampling protocol; ft, foot; ft/s, foot per second; HCl, hydrochloric acid; Hg, mercury; L, liter; LS, Kansas; m, meter; 

mL, milliter; poly, polyethylene bottle; TX, Texas; UVA, ultraviolet absorbance; —, not applicable; < less than; >, greater than. Sample type labels are 

designated by the National Water Quality Laboratory: BGC, baked, amber glass wide-mouth jar, chilled; FA, filtered, acidified cations; FCC, filtered, chilled 

nutrients; FU, filtered, unpreserved anions; GCC, baked, amber glass bottle, chilled; GLY2, glyphosate by U.S. Geological Survey Kansas Water Science Center; 

IMMGLY, glyphosate by immunoassay; OWI, organic wastewater indicators; PEST, pesticide; PHARM, pharmaceutical; RU, raw, unpreserved physical properties; SSC, suspended sediment concentration; WCA, whole, chilled, acidified nutrients]

Steps

Method

EWI, >1.5 ft/s and depth >1 ft Multivertical grab, <1.5 ft/s

and width >10 ft (3 m)

Grab in centroid of flow, <1.5 ft/s,

width <10 ft (3 m) and depth <1 ft

14Filter with syringe filter from churn o

BGC.

Filter with syringe filter from churn o

BGC.

Filter with syringe filter from churn o

BGC.

Syringe filtration: Prep syringe and filter by (1) pull 10 mL through the needle, invert, plunge to 30 mL, shake and dispose of water

(2) pull 5 mL through the needle, removing the needle and adding filter, and squirting the water through filter..

 Add 10 mL to 20 mL PEST.

 Fill 40 mL half full TX immunoassay 

(bottle label IMMGLY).

 Add 10 mL to 20-mL vial (bottle label 

PHARM).

Fill two 40-mL vials 24 mL each, K

Glyphosate (bottle label GLY2).

 Add 10 mL to 20 mL PEST.

 Fill 40 mL half full TX immunoassay 

(bottle label IMMGLY).

 Add 10 mL to 20-mL vial (bottle label 

PHARM).

Fill two 40-mL vials 24 mL each, K

Glyphosate (bottle label GLY2).

 Add 10 mL to 20 mL PEST.

 Fill 40 mL half full TX immunoassay 

(bottle label IMMGLY).

 Add 10 mL to 20-mL vial (bottle label 

PHARM).

Fill two 40-mL vials 24 mL each, K

Glyphosate (bottle label GLY2).

15Filter DOC with Aquaprep capsule filte

 Condition aquaprep with organic blank 

water.

Let the first 10 mL to waste then fil

two 40-mL vials to neck.

Filter DOC with Aquaprep capsule filte

 Condition aquaprep with organic blank 

water.

Let the first 10 mL to waste then fil

two 40-mL vials to neck.

Filter DOC with Aquaprep capsule filte

 Condition aquaprep with organic blank 

water.

Let the first 10 mL to waste then fil

two 40-mL vials to neck.

16 Acidify mercury sample (10 mL of 

ultraclean HCl).

 Acidify mercury sample (10 mL of 

ultraclean HCl).

 Acidify mercury sample (10 mL of 

ultraclean HCl).

Other data collection and clean up

17 Take a reference point measurement for 

stage, double-check field sheets for 

completeness.

 Take a reference point measurement for 

stage, double-check field sheets for 

completeness.

 Take a reference point measurement for 

stage, double-check field sheets for 

completeness.

18 Field clean tubing, churn, and 1-L 

sample bottle and cap, if re-using.

 Field clean tubing, churn, and 1-L 

sample bottle and cap, if re-using.

 Field clean tubing, churn, and 1-L 

sample bottle and cap, if re-using.

19Field clean tubing for DOC, if re-using.Field clean tubing for DOC, if re-using.Field clean tubing for DOC, if re-

1Acid preservation required.
Appendix 1. Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples Appendix 1 51

Table 1.4. Description of the bottle types, laboratory schedules, and preservation protocols by parameter group for samples collected 

by the U.S. Geological Survey California Stream Quality Assessment study in 2017.

[Laboratories: CA OCRL, U.S. Geological Survey (USGS) California Organic Chemistry Research Laboratory, Sacramento, Calif.; CERC, USGS 

Columbia Environmental Research Center, Columbia, Mo.; CSL, USGS California Water Science Center Sediment Laboratory, Santa Cruz, Calif.; GD 

Lab, USGS Geologic Division Laboratory, Denver, Colo.; MRL, USGS Mercury Research Laboratory, Middleton, Wisc.; NWQL, USGS National Water 

Quality Laboratory, Denver, Colo.; OGRL, USGS Kansas Organic Geochemistry Research Laboratory, Lawrence, Kans.; RSIL, USGS Reston Stable Isotope 

Laboratory, Reston, Va.; TX WSC, USGS Texas Water Science Center, Austin, Tex. Abbreviations: BEDSED, halogenated compounds, organic wastewater 

indicators, hormones, PAHs, pesticides, major and trace elements; GLY2, glyphosate by liquid chromatography tandem mass spectrometry; L, liter; MERC, 

total mercury and total methylmercury; mL, milliliter; N, normal; PAHs, current use pesticides, major and trace elements, radionuclides; POCIS, polar organic 

chemical integrative sampler; poly, polyetheylene; RTH, richest targeted habitat; >, greater than. Container label assigned by the National Water Quality 

Laboratory: FA, filtered, acidified cations; FCC, filtered, chilled nutrients; FU, filtered, unpreserved anions; OWI, organic wastewater indicators; PEST, 

pesticide; PHARM, pharmaceutical; RU, raw, unpreserved physical properties; WCA, whole, chilled, acidified nutrients]

Parameter group Laboratory or 

schedule Container (label) Source Preservation

Water samples

BASIC

 Major ions NWQL 2590 250-mL acid-rinsed poly bottle 

(FA)

Churn, capsule filte  7.5N nitri

acid

 250-mL clear poly bottle (FU)Churn, capsule filt

 Churn, raw

 250-mL clear poly bottle (RU) Churn, raw

 Nutrients NWQL 2711 125-mL white poly bottle 

(WCA)

 Churn, raw 4.5N sulfuric 

acid

 125-mL brown poly bottle 

(FCC)

Churn, capsule filt

 Pesticides NWQL 2437 20-mL amber glass septum vial 

(PEST)

Churn, syringe filt

 Supplemental pesticides NWQL LC9045 20-mL amber glass septum vial 

(9045)

Churn, syringe filt

 Dissolved organic carbon and 

ultraviolet absorbance at 254 

nanometers

 MRL (2) 40-mL amber glass septum 

vials

 Grab, 250-mL 

amber glass, disc 

filter

 Suspended sediment (concentration 

only)

 CSL 1-L poly wide-mouth bottle Churn, raw

 Immunoassay (glyphosate) TX WSC 40-mL amber glass septum vialChurn, syringe filte  Freeze if hel

> week

OWI

Organic wastewater indicators (OWI  NWQL 443  1-L, baked amber glass bottl

(OWI)

 Churn, raw

PHARM

 Pharmaceuticals NWQL 2440 20-mL amber glass septum vial 

(PHARM)

Churn, syringe filt

GLY2

 GlyphosateOGR  40-mL amber glass septum via

(PEST)

Churn, syringe filt

MERC

Total and methylmercury, filtered wate

and particulate

 MRL 1-L Nalgene bottle Grab Ultrapure 

hydrochloric 

acid

ISOTOPES

 Nitrogen and oxygen isotopes RSIL 125-mL clear poly bottleChurn, capsule filt

Sediment samples
52 Design and Methods of the California Stream Quality Assessment, 2017

Table 1.4. Description of the bottle types, laboratory schedules, and preservation protocols by parameter group for samples collected 

by the U.S. Geological Survey California Stream Quality Assessment study in 2017.—Continued

[Laboratories: CA OCRL, U.S. Geological Survey (USGS) California Organic Chemistry Research Laboratory, Sacramento, Calif.; CERC, USGS 

Columbia Environmental Research Center, Columbia, Mo.; CSL, USGS California Water Science Center Sediment Laboratory, Santa Cruz, Calif.; GD 

Lab, USGS Geologic Division Laboratory, Denver, Colo.; MRL, USGS Mercury Research Laboratory, Middleton, Wisc.; NWQL, USGS National Water 

Quality Laboratory, Denver, Colo.; OGRL, USGS Kansas Organic Geochemistry Research Laboratory, Lawrence, Kans.; RSIL, USGS Reston Stable Isotope 

Laboratory, Reston, Va.; TX WSC, USGS Texas Water Science Center, Austin, Tex. Abbreviations: BEDSED, halogenated compounds, organic wastewater 

indicators, hormones, PAHs, pesticides, major and trace elements; GLY2, glyphosate by liquid chromatography tandem mass spectrometry; L, liter; MERC, 

total mercury and total methylmercury; mL, milliliter; N, normal; PAHs, current use pesticides, major and trace elements, radionuclides; POCIS, polar organic 

chemical integrative sampler; poly, polyetheylene; RTH, richest targeted habitat; >, greater than. Container label assigned by the National Water Quality 

Laboratory: FA, filtered, acidified cations; FCC, filtered, chilled nutrients; FU, filtered, unpreserved anions; OWI, organic wastewater indicators; PEST, 

pesticide; PHARM, pharmaceutical; RU, raw, unpreserved physical properties; WCA, whole, chilled, acidified nutrients]

Parameter group Laboratory or 

schedule Container (label) Source Preservation

BEDSED

 Halogenated compoundsNWQL 809  125-mL baked amber glas

wide-mouth jar

 Composite sediment

 Polycyclic aromatic hydrocarbons and 

other semivolatile organic compounds

 NWQL 5506 125-mL baked amber glass 

wide-mouth jar

 Composite sediment

Organic wastewater indicators (OWI  NWQL 543  125-mL baked amber glas

wide-mouth jar

 Composite sediment

 Current use pesticidesCA OCR  125-mL baked amber glas

wide-mouth jar

 Composite sediment

 Major and trace elements GD Lab 125-mL poly wide-mouth jar Composite sediment

 Hormones NWQL 4434 125-mL baked amber glass 

wide-mouth jar

 Composite sediment

 Radionuclides Gellis and others, 

2017

 125-mL poly wide-mouth jar Composite sediment

Algae samples

CHL

 Periphyton biomass, chlorophyll-a NWQL 1632(2) glass-fiber filters (GFF)RTH, GFF filer  Fr

POCIS samplers

POCIS

 Current use pesticides CERCPOC

Organic wastewater indicators (OWI  CERCP

 Pharmaceuticals CERCPOC
Appendix 1. Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples Appendix 1 53

Table 1.5. Deployment dates for Polar Organic Chemical Integrative Samplers deployed by the U.S. Geological Survey California 

Stream Quality Assessment in 2017.

[Begin date, date that POCIS (polar organic chemical integrative samplers) were deployed in the stream; End date, date that POCIS were retrieved from the 

stream; g, gram; mm/dd/yyyy, month/day/year; N/A, not applicable; No., number; NWIS, U.S. Geological Survey National Water Information System database; 

wt, weight]

NWIS station number Field identifier No. of 

POCIS

Sorbent wt 

per POCIS

(g)

Begin date

(mm/dd/yyyy)

End date

(mm/dd/yyyy)

No. 

days Sample type

38371912246250  CA_Maacama 2 0.2 04/03/2017 05/08/2017 3  Environment

 11465350 CA_DryMouth 2 0.2 04/03/2017 05/08/2017 35 Environmental

 11465350 CA_DryMouth 2 0.2 04/03/2017 05/08/2017 35 Replicate

 11465350 CA_DryMouth 2 0.2 04/03/2017 05/08/2017 35 Field blank

1146680  CA_MarkWMir 2 0.2 04/04/2017 05/09/2017 3  Environment

 11466320 CA_SantaWillow 2 0.2 04/05/2017 05/10/2017 35 Environmental

38261912253140  CA_Green 2 0.2 04/05/2017 05/10/2017 3  Environment

 11466170 CA_Matanzas 2 0.2 04/04/2017 05/09/2017 35 Environmental

 11466200 CA_SantaSanta 2 0.2 04/06/2017 05/11/2017 35 Environmental

 11465690 CA_Colgan 2 0.2 04/06/2017 05/11/2017 35 Environmental

38234612252120  CA_NoNameMonty 2 0.2 04/05/2017 05/10/2017 3  Environment

 11465660 CA_Copeland 2 0.2 04/04/2017 05/09/2017 35 Environmental

1145850  CA_SonomaAgua 2 0.2 04/03/2017 05/08/2017 3  Environment

38174012239590  CA_Lichau 2 0.2 04/04/2017 05/09/2017 3  Environment

38155612228020  CA_SonomaWat 2 0.2 04/03/2017 05/08/2017 3  Environment

38151912238560  CA_Petaluma 2 0.2 04/04/2017 05/09/2017 3  Environment

 11459500 CA_Novato 2 0.2 04/05/2017 05/10/2017 35 Environmental

 11459500 CA_Novato 2 0.2 04/05/2017 05/10/2017 35 Replicate

 11459500 CA_Novato 2 0.2 04/05/2017 05/10/2017 35 Field blank

38041012231550  CA_ArroyoDig 2 0.2 04/05/2017 05/10/2017 3  Environment

38034512234520  CA_ArroyoNov 2 0.2 04/03/2017 05/08/2017 3  Environment

 11460000 CA_Corte 2 0.2 04/06/2017 05/11/2017 35 Environmental

383321122302101CA_NapaBale 2 0.2 04/04/2017 05/09/201735  Environme

38330512231190  CA_Ritchey 2 0.2 04/03/2017 05/08/2017 3  Environment

38310912236330  CA_MarkWTar 2 0.2 04/03/2017 05/08/2017 3  Environment

38263412231520  CA_SonomaAdobe 2 0.2 04/03/2017 05/08/2017 3  Environment

38224512200160  CA_Ulatis 2 0.2 04/03/2017 05/08/2017 3  Environment

 11456500CA_ConnOak 2 0.2 04/04/2017 05/09/2017 3  Environment

38201712216110  CA_Milliken 2 0.2 04/06/2017 05/11/2017 3  Environment

1145830  CA_NapaNapa 2 0.2 04/05/2017 05/10/2017 3  Environment

1145830  CA_NapaNapa 2 0.2 04/05/2017 05/10/2017 3  Replica

1145830  CA_NapaNapa 2 0.2 04/05/2017 05/10/2017 3  Field bla

38144112206430  CA_Suisan 2 0.2 04/06/2017 05/11/2017 3  Environment

1118240  CA_ArroyoMart 2 0.2 04/05/2017 05/10/2017 3  Environment

37581912203580  CA_Grayson 2 0.2 04/06/2017 05/11/2017 3  Environment

37581912203580  CA_Grayson 2 0.2 04/06/2017 05/11/2017 3  Replica

37581912203580  CA_Grayson 2 0.2 04/06/2017 05/11/2017 3  Field bla

37580812217260  CA_Wilkie 2 0.2 04/03/2017 05/08/2017 3  Environment

 375746122195501 CA_SanPabloPort 2 0.2 04/03/2017 05/08/2017 35 Environmental

 375701121564401 CA_MtDiablo 2 0.2 04/06/2017 05/11/2017 35 Environmental
54 Design and Methods of the California Stream Quality Assessment, 2017

Table 1.5. Deployment dates for Polar Organic Chemical Integrative Samplers deployed by the U.S. Geological Survey California 

Stream Quality Assessment in 2017.—Continued

[Begin date, date that POCIS (polar organic chemical integrative samplers) were deployed in the stream; End date, date that POCIS were retrieved from the 

stream; g, gram; mm/dd/yyyy, month/day/year; N/A, not applicable; No., number; NWIS, U.S. Geological Survey National Water Information System database; 

wt, weight]

NWIS station number Field identifier No. of 

POCIS

Sorbent wt 

per POCIS

(g)

Begin date

(mm/dd/yyyy)

End date

(mm/dd/yyyy)

No. 

days Sample type

 375257122050001 CA_LasTrampas 2 0.2 04/04/2017 05/10/2017 36 Environmental

 374933122001301 CA_SanRamonDan 2 0.2 04/05/2017 05/10/2017 35 Environmental

1118250  Ca_SanRamonSan 2 0.2 04/05/2017 05/10/2017 3  Environment

37470812213280  CA_Sausal 2 0.2 04/06/2017 05/11/2017 3  Environment

37433612209580  CA_SanLeandro 2 0.2 04/06/2017 05/11/2017 3  Environment

1118090  CA_Crow 2 0.2 04/05/2017 05/10/2017 3  Environment

1118100  CA_Castro 2 0.2 04/03/2017 05/08/2017 3  Environment

 11164500 CA_SanFranStan 2 0.2 03/16/2017 04/20/2017 35 Environmental

37250012208120  CA_Matadero 2 0.2 03/16/2017 04/20/2017 3  Environment

 11176900 CA_ArroyoDeLaLa 2 0.2 03/14/2017 04/17/2017 34 Environmental

 11176900 CA_ArroyoDeLaLa 2 0.2 03/14/2017 04/17/2017 34 Replicate

 11169025 CA_GuadalupeA 2 0.2 03/13/2017 04/17/2017 35 Environmental

 11169025 CA_GuadalupeA 2 0.2 03/13/2017 04/17/2017 35 Replicate

 11169025 CA_GuadalupeA 2 0.2 03/13/2017 04/17/2017 35 Field blank

37173812155590  CA_LosGatos 2 0.2 03/15/2017 04/19/2017 3  Environment

 371554121474101 CA_CoyoteCoyote 2 0.2 03/14/2017 04/18/2017 35 Environmental

 371554121474101 CA_CoyoteCoyote 2 0.2 03/14/2017 04/18/2017 35 Replicate

37162012200580  CA_Saratoga 2 0.2 03/15/2017 04/19/2017 3  Environment

 370512121361901 CA_LlagasMartin 2 0.2 03/13/2017 04/17/2017 35 Environmental

1116980  CA_CoyoteGil 2 0.2 03/13/2017 04/18/2017 3  Environment

 11153470 CA_LlagasMorgan 2 0.2 03/13/2017 04/17/2017 35 Environmental

 11153650 CA_LlagasGilroy 2 0.2 03/14/2017 04/18/2017 35 Environmental

 11159500 CA_PajaroWat 2 0.2 03/15/2017 04/19/2017 35 Environmental

 11152600 CA_GabilanSal 2 0.2 03/15/2017 04/19/2017 35 Environmental

 365634121264001 CA_Tequisquita 2 0.2 03/16/2017 04/20/2017 35 Environmental

 365634121264001 CA_Tequisquita 2 0.2 03/16/2017 04/20/2017 35 Field blank

 11152650 CA_Reclamation 2 0.2 03/13/2017 04/17/2017 35 Environmental

 364155121363901 CA_Natividad 2 0.2 03/15/2017 04/19/2017 35 Environmental

36413812137370  CA_GabilanEastL 1 0.2 03/15/2017 04/19/2017 3  Environment

36360812125520  CA_ChuChuChu 2 0.2 03/13/2017 04/18/2017 3  Environment

11148900CA_NaciBryson 2 0.2 03/13/2017 04/20/201738  Environme

 352934120395501 CA_Atascadero 2 0.2 03/16/2017 04/20/2017 35 Environmental

35212712048450  CA_Chorro 2 0.2 03/15/2017 04/19/2017 3  Environment

 351725120395901 CA_Stenner 2 0.2 03/15/2017 04/17/2017 33 Environmental

1114128  CA_Lopez 2 0.2 03/13/2017 04/18/2017 3  Environment

 11135250CA_SantaYnezLom 2 0.2 03/14/2017 04/18/2017 3  Environment

11128500CA_SntaYnezSol 2 0.2 03/13/2017 04/17/201735  Environme

3854430921636POCIS Spike 1 2 0.2 N/A N/A /A  S

3854430921636POCIS Spike 2 2 0.2 N/A N/A /A  S

3854430921636POCIS Spike 3 2 0.2 N/A N/A /A  S
Appendix 1. Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples Appendix 1 55

Table 1.6. Deployment dates for ceramic tiles used to collect biofilms for pesticide analysis as part of the U.S. Geological Survey 

California Stream Quality Assessment study in 2017.

[Begin date, date that tiles were deployed in the stream; End date, date that tiles were retrieved from the stream; mm/dd/yyyy, month/day/year; No., number; 

NWIS, U.S. Geological Survey National Water Information System database]

NWIS station number Field identifier Begin date

(mm/dd/yyyy)

End date

(mm/dd/yyyy)

No. of days 

deployed

38203512157550  CA_Alamo 03/08/2017 05/11/2017 

 11176900 CA_ArroyoDeLaLa 03/07/2017 05/17/2017 71

38041012231550  CA_ArroyoDig 03/08/2017 05/11/2017 

1118240  CA_ArroyoMart 03/07/2017 05/15/2017 

38034512234520  CA_ArroyoNov 03/08/2017 05/10/2017 

 11152000 CA_ArroyoSeco 03/04/2017 05/06/2017 63

 352934120395501 CA_Atascadero 02/11/2017 05/07/2017 85

36360812125520  CA_ChuChuChu 02/12/2017 05/05/2017 

 11465690 CA_Colgan 03/09/2017 05/12/2017 64

 11456500CA_ConnOak 03/09/2017 05/14/2017 

 11465660 CA_Copeland 03/09/2017 05/12/2017 64

 11159200 CA_Corralitos 03/03/2017 05/06/2017 64

 11460000 CA_Corte 03/08/2017 05/11/2017 64

 371554121474101 CA_CoyoteCoyote 02/14/2017 05/10/2017 85

36413812137370  CA_GabilanEastL 02/12/2017 05/03/2017 

38261912253140  CA_Green 03/09/2017 05/13/2017 

 375257122050001 CA_LasTrampas 03/07/2017 05/16/2017 70

38174012239590  CA_Lichau 03/08/2017 05/09/2017 

 11153650 CA_LlagasGilroy 03/06/2017 05/07/2017 62

1114128  CA_Lopez 02/11/2017 05/10/2017 

37173812155590  CA_LosGatos 02/14/2017 05/04/2017 

38371912246250  CA_Maacama 03/09/2017 05/10/2017 

38310912236330  CA_MarkWTar 03/09/2017 05/10/2017 

37250012208120  CA_Matadero 02/14/2017 05/02/2017 

 11466170 CA_Matanzas 03/10/2017 05/16/2017 67

38201712216110  CA_Milliken 03/08/2017 05/12/2017 

 375701121564401 CA_MtDiablo 03/07/2017 05/15/2017 69

11148900CA_NaciBryson 03/04/2017 05/08/201

383321122302101CA_NapaBale 03/09/2017 05/15/201

1145830  CA_NapaNapa 03/08/2017 05/12/2017 

 364155121363901 CA_Natividad 02/12/2017 05/03/2017 80

38234612252120  CA_NoNameMonty 03/09/2017 05/13/2017 

 11459500 CA_Novato 03/08/2017 05/10/2017 63

36573612125080  CA_Pacheco 02/13/2017 05/05/2017 

 11152650 CA_Reclamation 03/05/2017 05/04/2017 60

38330512231190  CA_Ritchey 03/09/2017 05/15/2017 

 351436120405201CA_SanLObispo 02/10/2017 05/09/2017 

 375220122104201 CA_SanPabloCam 03/07/2017 05/17/2017 71

 375312122113501CA_SanPabloOr 03/07/2017 05/14/2017 

 374933122001301 CA_SanRamonDan 03/07/2017 05/13/2017 67

1118250  CA_SanRamonSan 03/07/2017 05/13/2017 
56 Design and Methods of the California Stream Quality Assessment, 2017

Table 1.6. Deployment dates for ceramic tiles used to collect biofilms for pesticide analysis as part of the U.S. Geological Survey 

California Stream Quality Assessment study in 2017.—Continued

[Begin date, date that tiles were deployed in the stream; End date, date that tiles were retrieved from the stream; mm/dd/yyyy, month/day/year; No., number; 

NWIS, U.S. Geological Survey National Water Information System database]

NWIS station number Field identifier Begin date

(mm/dd/yyyy)

End date

(mm/dd/yyyy)

No. of days 

deployed

 11466200 CA_SantaSanta 03/10/2017 05/16/2017 67

 11466320 CA_SantaWillow 03/10/2017 05/11/2017 62

 11135250CA_SantaYnezLom 02/10/2017 05/11/2017 

37162012200580  CA_Saratoga 02/14/2017 05/03/2017 

37470812213280  CA_Sausal 03/08/2017 05/12/2017 

38263412231520  CA_SonomaAdobe 03/09/2017 05/17/2017 

38144112206430  CA_Suisan 03/08/2017 05/12/2017 

 365634121264001 CA_Tequisquita 02/13/2017 05/05/2017 81

38224512200160  CA_Ulatis 03/08/2017 05/11/2017 

 365955121350601 CA_UvasMiller 02/13/2017 05/07/2017 83

 375413122033301 CA_Walnut 03/07/2017 05/16/2017 70

37580812217260  CA_Wilkie 03/07/2017 05/13/2017 

38303912250240  CA_Windsor 03/10/2017 05/11/2017 
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms 57

Appendix 2 Description of the U.S. Geological Survey National Water Quality 

Laboratory Schedules Used for Water, Bed Sediment, and Biofilms

Table 2.1. U.S. Geological Survey National Water Quality Laboratory Schedule 2590 for major ions in water.

[CAS, Chemical Abstracts Service1; IC, ion chromatography; ICP/AES, inductively coupled plasma/atomic emission spectroscopy; ltmdl, long-term method 

detection limit; mg/L, milligram per liter; mrl, minimum reporting level; NWIS, USGS National Water Information System; NWQL, U.S. Geological Survey 

(USGS) National Water Quality Laboratory; —, no data; μS/cm, microsiemens per centimeter at 25 degrees Celsius]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS 

number

Reporting 

level Unit Reporting level type Method citation Method

 Calcium 659 00915 PLA11 7440-70-2 0.022 mg/L ltmdl Fishman (1993) ICP/AES

 Chloride 1571 00940 IC022 16887-00-6 0.02 mg/L ltmdl Fishman and 

Friedman (1989)

 IC

 Magnesium 663 00925 PLA11 7439-95-4 0.011 mg/L ltmdl Fishman (1993) ICP/AES

 Potassium 2773 00935 PLO03 7440-09-7 0.03 mg/L ltmdl Fishman (1993) ICP/AES

 Sodium 675 00930 PLA11 7440-23-5 0.06 mg/L ltmdl Fishman (1993) ICP/AES

Specific conductance

laboratory

69 90095 WHT03 — 5 μS/cm mrl Fishman and 

Friedman (1989)

 Wheatstone 

Bridge

 Sulfate 1572 00945 IC022 14808-79-8 0.02 mg/L ltmdl Fishman and 

Friedman (1989)

 IC

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.

Table 2.2. U.S. Geological Survey National Water Quality Laboratory Schedule 2711 for nutrients in water.

[CAS, Chemical Abstracts Service1; EPA, U.S. Environmental Protection Agency; ltmdl, long-term method detection limit; mdl, method detection limit; 

mg/L, milligram per liter; N, nitrogen; NWIS, USGS National Water Information System; NWQL, U.S. Geological Survey (USGS) National Water Quality 

Laboratory; —, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS 

number

Reporting 

level Unit Reporting level type

Method 

citation Method

 Nitrogen, ammonia as N 3116 00608 00048 7664-41-7 0.01 mg/L ltmdl Fishman 

(1993)

 Colorimetry

 Nitrogen, nitrite 3117 00613 00049 14797-65-0 0.001 mg/L mdl Fishman 

(1993)

 Colorimetry

 Nitrogen, nitrite + nitrate 3156 00631 RED01 — 0.04 mg/L mdl Patton and 

Kryskalla 

(2003, 2011)

 Colorimetry, 

enzyme reduction, low 

level

 Phosphorus 2333 00665 CL021 7723-14-0 0.004 mg/L ltmdlO’Dell (1993  EPA 365

 Phosphorus, phosphate, 

ortho

3118 00671 00048 14265-44-2 0.004 mg/L ltmdl Fishman 

(1993)

 Colorimetry

 Total nitrogen (ammoni

a+nitrite+nitrate+organ

ic), unfiltered

2756 62855 AKP01 17778-88-0 0.05 mg/L ltmdl Patton and 

Kryskalla 

(2003, 2011)

 Colorimetry

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
58 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 1H-1,2,4-Triazole 68498 LCM60 288-88-0 22 ng/L RLDQC

 2,3,3-Trichloro-2-propene-1-sulfonic acid (TCPSA) 68691 LCM60 65600-62-6 55 ng/L RLDQC

 2,4-D 68500 LCM60 94-75-7 62 ng/L RLDQC

2,4-D-d3, surrogate, water,filtered, percent recovery (surrogate) 91986 LCM60 202480-67-9 N/A pct N

 2-(1-Hydroxyethyl)-6-methylaniline 68611 LCM60 196611-19-5 54 ng/L RLDQC

 2-[(2-Ethyl-6-methylphenyl)amino]-1-propanol 68595 LCM60 61520-53-4 5 ng/L RLDQC

 2-Amino-N-isopropylbenzamide 68503 LCM60 30391-89-0 4 ng/L RLDQC

 2-Aminobenzimidazole 68502 LCM60 934-32-7 9 ng/L RLDQC

 2-Chloro-2’,6’-diethylacetanilide 68525 LCM60 6967-29-9 5 ng/L RLDQC

 2-Chloro-4,6-diamino-s-triazine {CAAT} (Didealkylatrazine) 68547 LCM60 3397-62-4 24 ng/L RLDQC

 2-Chloro-4-isopropylamino-6-amino-s-triazine 68552 LCM60 6190-65-4 11 ng/L RLDQC

 2-Chloro-6-ethylamino-4-amino-s-triazine {CEAT} 68550 LCM60 1007-28-9 20 ng/L RLDQC

 2-Chloro-N-(2-ethyl-6-methylphenyl)acetamide 68521 LCM60 32428-71-0 5 ng/L RLDQC

 2-Hydroxy-4-isopropylamino-6-amino-s-triazine 68659 LCM60 19988-24-0 4 ng/L RLDQC

2-Hydroxy-4-isopropylamino-6-ethylamino-s-triazine {OIET} 68660 LCM60 2163-68-0 8 ng/L RLD

 2-Hydroxy-6-ethylamino-4-amino-s-triazine 68656 LCM60 7313-54-4 100 ng/L RLDQC

 2-Isopropyl-6-methyl-4-pyrimidinol 68505 LCM60 2814-20-2 8 ng/L RLDQC

 3,4-Dichlorophenylurea 68226 LCM60 2327-02-8 108 ng/L RLDQC

 3-Hydroxycarbofuran 68508 LCM60 16655-82-6 16 ng/L RLDQC

 3-Phenoxybenzoic acid 68873 LCM60 3739-38-6 61 ng/L RLDQC

 3-Phenoxybenzoic acid-13C6 (surrogate) 90516 LCM60 — N/A pct N/A

 4-(Hydroxymethyl)pendimethalin 68511 LCM60 56750-76-6 114 ng/L RLDQC

 4-Chlorobenzylmethyl sulfoxide 68514 LCM60 24176-68-9 3.2 ng/L RLDQC

 4-Hydroxy molinate 68515 LCM60 66747-12-4 7 ng/L RLDQC

 4-Hydroxychlorothalonil 68336 LCM60 28343-61-5 98 ng/L RLDQC

 4-Hydroxyhexazinone A 68517 LCM60 72576-13-7 3 ng/L RLDQC

 Acephate 68519 LCM60 30560-19-1 10 ng/L RLDQC

 Acetochlor 68520 LCM60 34256-82-1 10 ng/L RLDQC

 Acetochlor oxanilic acid 68522 LCM60 194992-44-4 65 ng/L RLDQC

 Acetochlor sulfonic acid 68523 LCM60 187022-11-3 320 ng/L RLDQC

 Acetochlor sulfynilacetic acid 68524 LCM60 618113-86-3 176 ng/L RLDQC

 Acetochlor-d11 (surrogate) 90517 LCM60 1189897-44-6 N/A pct N/A

 Alachlor 65064 LCM60 15972-60-8 27 ng/L RLDQC

 Alachlor oxanilic acid 68526 LCM60 171262-17-2 60 ng/L RLDQC

 Alachlor sulfonic acid 68871 LCM60 142363-53-9 360 ng/L RLDQC

 Alachlor sulfynilacetic acid 68527 LCM60 494847-39-1 128 ng/L RLDQC

 Alachlor-d13 (surrogate) 90518 LCM60 1015856-63-9 N/A pct N/A

 Aldicarb 68528 LCM60 116-06-3 8 ng/L RLDQC

 Aldicarb sulfone 68529 LCM60 1646-88-4 20 ng/L RLDQC
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 59

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Aldicarb sulfoxide 68530 LCM60 1646-87-3 2.2 ng/L RLDQC

 Ametryn 68533 LCM60 834-12-8 2.6 ng/L RLDQC

 Asulam 68536 LCM60 3337-71-1 50 ng/L RLDQC

 Atrazine 65065 LCM60 1912-24-9 6.8 ng/L RLDQC

 Azinphos-methyl 65066 LCM60 86-50-0 8 ng/L RLDQC

 Azinphos-methyl oxon 68211 LCM60 961-22-8 15 ng/L RLDQC

 Azoxystrobin 66589 LCM60 131860-33-8 3 ng/L RLDQC

Bentazon 68538 LCM60 25057-89-0 9 ng/L RLD

Bifenthrin 65067 LCM60 82657-04-3 19 ng/L RLD

Bromacil 68542 LCM60 314-40-9 5.6 ng/L RLD

Bromoxynil 68543 LCM60 1689-84-5 60 ng/L RLD

Butachlor sulfonic acid (surrogate) 90624 LCM60 187022-12-4 N/A pct N

Butralin 68545 LCM60 33629-47-9 5 ng/L RLD

Butylate 65068 LCM60 2008-41-5 10 ng/L RLD

 Carbaryl 65069 LCM60 63-25-2 5.6 ng/L RLDQC

 Carbaryl-d7 (surrogate) 90519 LCM60 362049-56-7 N/A pct N/A

 Carbendazim 68548 LCM60 10605-21-7 10 ng/L RLDQC

 Carbendazim-d4 (surrogate) 90520 LCM60 291765-95-2 N/A pct N/A

 Carbofuran 65070 LCM60 1563-66-2 5 ng/L RLDQC

 Carbofuran-d3 (surrogate) 90521 LCM60 1007459-98-4 N/A pct N/A

 Carboxy molinate 68549 LCM60 66747-13-5 54 ng/L RLDQC

 Chlorimuron-ethyl 68872 LCM60 90982-32-4 8.8 ng/L RLDQC

 Chlorosulfonamide acid 68551 LCM60 — 60 ng/L RLDQC

 Chlorpyrifos 65072 LCM60 2921-88-2 3 ng/L RLDQC

 Chlorpyrifos oxon 68216 LCM60 — 4.4 ng/L RLDQC

 Chlorsulfuron 61678 LCM60 64902-72-3 50 ng/L RLDQC

cis-Bifenthrin acid/cis-Cyhalothrin acid/cis-Tefluthrin acid 68553 LCM60 68127-59-3 105 ng/L RLD

 cis-Permethrin 68769 LCM60 61949-76-6 4.2 ng/L RLDQC

 cis-Permethrin-13C6 (surrogate) 90558 LCM60 — N/A pct N/A

 Cyanazine 66592 LCM60 21725-46-2 50 ng/L RLDQC

 Dacthal monoacid 68560 LCM60 887-54-7 2700 ng/L RLDQC

Dechlorofipronil 68561 LCM60 — 3.8 ng/L RLD

 Dechlorometolachlor 68562 LCM60 126605-22-9 2 ng/L RLDQC

 Deethylatrazine-d6 (surrogate) 90522 LCM60 — N/A pct N/A

Deiodo flubendiamide 68563 LCM60 1016160-78-3 10 ng/L RLD

 Deisopropyl prometryn 68564 LCM60 4147-57-3 2.8 ng/L RLDQC

Demethyl fluometuron 68591 LCM60 3032-40-4 3.6 ng/L RLD

Demethyl hexazinone B 68566 LCM60 56611-54-2 3 ng/L RLD

Demethyl norflurazon 68567 LCM60 23576-24-1 4 ng/L RLD
60 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Desamino metribuzin 68568 LCM60 35045-02-4 9 ng/L RLDQC

 Desamino-diketo metribuzin 68569 LCM60 52236-30-3 200 ng/L RLDQC

Desulfinylfipronil 66607 LCM60 205650-65-3 3.8 ng/L RLD

Desulfinylfipronil amide 68570 LCM60 1115248-09-3 10 ng/L RLD

 Diazinon 65078 LCM60 333-41-5 2.8 ng/L RLDQC

 Diazinon oxon 68236 LCM60 — 4 ng/L RLDQC

 Diazinon-d10 (surrogate) 90523 LCM60 100155-47-3 N/A pct N/A

 Dicamba 68571 LCM60 1918-00-9 800 ng/L RLDQC

 Dichlorvos 68572 LCM60 — 52 ng/L RLDQC

 Dicrotophos 68573 LCM60 141-66-2 4 ng/L RLDQC

 Didemethyl hexazinone F 68574 LCM60 56611-54-2 10 ng/L RLDQC

Diflubenzuron 68576 LCM60 35367-38-5 6 ng/L RLD

Diflubenzuron-d4 (surrogate) 90524 LCM60 1219795-45-5 N/A pct N

Diflufenzopyr 68577 LCM60 109293-97-2 72 ng/L RLD

Diketonitrile-isoxaflutole 68578 LCM60 143701-75-1 24 ng/L RLD

 Dimethachlor sulfonic acid (surrogate) 90625 LCM60 — N/A pct N/A

 Dimethenamid 68580 LCM60 87674-68-8 3 ng/L RLDQC

 Dimethenamid oxanilic acid 68581 LCM60 380412-59-9 85 ng/L RLDQC

 Dimethenamid SAA 68583 LCM60 — 189 ng/L RLDQC

 Dimethenamid sulfonic acid 68582 LCM60 205939-58-8 79 ng/L RLDQC

 Dimethoate 66596 LCM60 60-51-5 4.6 ng/L RLDQC

 Disulfoton 67595 LCM60 298-04-4 11 ng/L RLDQC

 Disulfoton oxon 68586 LCM60 126-75-0 2 ng/L RLDQC

 Disulfoton oxon sulfone 68588 LCM60 2496-91-5 6 ng/L RLDQC

 Disulfoton oxon sulfoxide 68587 LCM60 2496-92-6 6 ng/L RLDQC

 Disulfoton sulfone 68589 LCM60 2497-06-5 9 ng/L RLDQC

 Disulfoton sulfoxide 68590 LCM60 2497-07-6 4 ng/L RLDQC

 Diuron 66598 LCM60 330-54-1 5 ng/L RLDQC

 Diuron-d6 (surrogate) 90808 LCM60 — N/A pct N/A

 Diuron-d6 (surrogate) N/A — N/A pct N/A

 EPTC 65080 LCM60 759-94-4 206 ng/L RLDQC

EPTC degradate R248722 68594 LCM60 65109-69-5 4 ng/L RLD

 Ethoprophos 68596 LCM60 13194-48-4 5 ng/L RLDQC

 Etoxazole 68598 LCM60 153233-91-1 4.2 ng/L RLDQC

 Fenamiphos 68599 LCM60 22224-92-6 4.6 ng/L RLDQC

 Fenamiphos sulfone 68600 LCM60 31972-44-8 5 ng/L RLDQC

 Fenamiphos sulfoxide 68601 LCM60 31972-43-7 5 ng/L RLDQC

 Fenbutatin oxide 68602 LCM60 13356-08-6 120 ng/L MRL

 Fentin 68603 LCM60 668-34-8 30 ng/L RLDQC
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 61

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Fipronil 66604 LCM60 120068-37-3 4 ng/L RLDQC

 Fipronil amide 68604 LCM60 205650-69-7 9.2 ng/L RLDQC

Fipronil sulfide 66610 LCM60 120067-83-6 4.2 ng/L RLD

 Fipronil sulfonate 68605 LCM60 209248-72-6 96 ng/L RLDQC

 Fipronil sulfone 66613 LCM60 120068-36-2 5.6 ng/L RLDQC

 Flubendiamide 68606 LCM60 272451-65-7 4.4 ng/L RLDQC

 Flumetsulam 61679 LCM60 98967-40-9 17 ng/L RLDQC

 Fluometuron 68608 LCM60 2164-17-2 10 ng/L RLDQC

 Fonofos 65084 LCM60 944-22-9 11 ng/L RLDQC

 Halosulfuron-methyl 61680 LCM60 100784-20-1 12 ng/L RLDQC

 Hexazinone 65085 LCM60 51235-04-2 3.6 ng/L RLDQC

 Hexazinone Transformation Product C 68612 LCM60 72585-88-7 2 ng/L RLDQC

 Hexazinone Transformation Product D 68613 LCM60 30243-77-7 294 ng/L RLDQC

 Hexazinone Transformation Product E 68614 LCM60 72576-14-8 76 ng/L RLDQC

 Hexazinone Transformation Product G 68713 LCM60 — 22 ng/L RLDQC

 Hexazinone-d6 (surrogate) 90527 LCM60 1219804-22-4 N/A pct N/A

Hydroxy didemethyl fluometuron 68619 LCM60 — 50 ng/L RLD

Hydroxy monodemethyl fluometuron 68617 LCM60 — 12 ng/L RLD

 Hydroxyacetochlor 68615 LCM60 60090-47-3 20 ng/L RLDQC

 Hydroxyalachlor 68616 LCM60 56681-55-1 6 ng/L RLDQC

 Hydroxydiazinon 68618 LCM60 29820-16-4 11 ng/L RLDQC

Hydroxyfluometuron 68620 LCM60 — 56 ng/L RLD

 Hydroxymetolachlor 68622 LCM60 131068-72-9 2.4 ng/L RLDQC

 Hydroxyphthalazinone 68623 LCM60 — 28 ng/L RLDQC

 Hydroxysimazine 68624 LCM60 2599-11-3 120 ng/L RLDQC

 Imazamox 68625 LCM60 114311-32-9 30 ng/L RLDQC

 Imazaquin 61682 LCM60 81335-37-7 18 ng/L RLDQC

 Imazethapyr 61683 LCM60 81335-77-5 8 ng/L RLDQC

 Imidacloprid 68426 LCM60 138261-41-3 16 ng/L RLDQC

 Indoxacarb 68627 LCM60 173584-44-6 5.2 ng/L RLDQC

Isoxaflutole 68632 LCM60 141112-29-0 18 ng/L RLD

Isoxaflutole acid metabolite RPA 203328 68633 LCM60 142994-06-7 9.2 ng/L RLD

Kresoxim-methyl 67670 LCM60 143390-89-0 5 ng/L RLD

 Lactofen 68638 LCM60 77501-63-4 10 ng/L RLDQC

 Linuron 68639 LCM60 330-55-2 5.6 ng/L RLDQC

 Linuron-d6 (dimethyl-d6) (surrogate) 90529 LCM60 1219804-76-8 N/A pct N/A

 Linuron-d6 (dimethyl-d6) (surrogate) N/A 1219804-76-8 N/A pct N/A

 Malaoxon 68240 LCM60 1634-78-2 2.4 ng/L RLDQC

 Malathion 65087 LCM60 121-75-5 5.4 ng/L RLDQC
62 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Malathion-d10 (diethyl-d10) (surrogate) 90552 LCM60 347841-48-9 N/A pct N/A

 MCPA 68641 LCM60 94-74-6 95 ng/L RLDQC

 Metalaxyl 68437 LCM60 57837-19-1 6 ng/L RLDQC

 Metconazole 66620 LCM60 125116-23-6 5 ng/L RLDQC

 Methamidophos 68644 LCM60 10265-92-6 10 ng/L RLDQC

 Methidathion 65088 LCM60 950-37-8 8.4 ng/L RLDQC

 Methomyl 68645 LCM60 16752-77-5 3 ng/L RLDQC

 Methomyl oxime 68646 LCM60 13749-94-5 8,000 ng/L RLDQC

 Methoxyfenozide 68647 LCM60 161050-58-4 2.2 ng/L RLDQC

 Methyl paraoxon 68648 LCM60 950-35-6 19 ng/L RLDQC

 Metolachlor 65090 LCM60 51218-45-2 3.2 ng/L RLDQC

 Metolachlor hydroxy morpholinone 68649 LCM60 61520-54-5 10 ng/L RLDQC

 Metolachlor oxanilic acid 68650 LCM60 152019-73-3 149 ng/L RLDQC

 Metolachlor sulfonic acid 68651 LCM60 171118-09-5 68 ng/L RLDQC

 Metolachlor-d6 (propyl-d6) (surrogate) 90553 LCM60 1219803-97-0 N/A pct N/A

 Metribuzin 68652 LCM60 21087-64-9 20 ng/L RLDQC

Metribuzin DK 68653 LCM60 56507-37-0 236 ng/L RLD

 Molinate 65091 LCM60 2212-67-1 28 ng/L RLDQC

 Myclobutanil 66632 LCM60 88671-89-0 7 ng/L RLDQC

 N-(3,4-Dichlorophenyl)-N’-methylurea 68231 LCM60 3567-62-2 5 ng/L RLDQC

 Naled 68654 LCM60 300-76-5 56 ng/L RLDQC

 Nicosulfuron 61685 LCM60 111991-09-4 12 ng/L RLDQC

 Nicosulfuron-d6 (surrogate) 90554 LCM60 1189419-41-7 N/A pct N/A

Norflurazon 67685 LCM60 27314-13-2 3.4 ng/L RLD

 Novaluron 68655 LCM60 116714-46-6 50 ng/L RLDQC

O-Ethyl-O-methyl-S-propylphosphorothioate 68597 LCM60 76960-87-7 5 ng/L RLD

O-Ethyl-S-methyl S-propyl phosphorodithioate 68657 LCM60 76936-72-6 3 ng/L RLD

O-Ethyl-S-propyl phosphorothioate 68658 LCM60 31110-62-0 64 ng/L RLD

Omethoate (Dimethoate oxon) 68661 LCM60 1113-02-6 2 ng/L RLD

Orthosulfamuron 68662 LCM60 213464-77-8 6 ng/L RLD

Oryzalin 68663 LCM60 19044-88-3 12 ng/L RLD

Oxamyl 68664 LCM60 23135-22-0 2 ng/L RLD

Oxamyl oxime 68665 LCM60 30558-43-1 5 ng/L RLD

Oxyfluorfen 65093 LCM60 42874-03-3 500 ng/L RLD

 Paraoxon 68666 LCM60 311-45-5 3.4 ng/L RLDQC

 Pendimethalin 65098 LCM60 40487-42-1 10 ng/L RLDQC

 Phorate 68668 LCM60 298-02-2 11 ng/L RLDQC

 Phorate oxon 68669 LCM60 2600-69-3 55 ng/L RLDQC

 Phorate oxon sulfone 68670 LCM60 2588-06-9 20 ng/L RLDQC
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 63

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Phorate oxon sulfoxide 68671 LCM60 2588-05-8 7 ng/L RLDQC

 Phorate sulfone 68672 LCM60 2588-04-7 36 ng/L RLDQC

 Phorate sulfoxide 68673 LCM60 2588-03-6 4.6 ng/L RLDQC

 Phthalazinone 68675 LCM60 90004-07-2 15 ng/L RLDQC

 Piperonyl butoxide 65102 LCM60 51-03-6 60 ng/L RLDQC

 Profenofos 68676 LCM60 41198-08-7 3 ng/L RLDQC

 Prometon 67702 LCM60 1610-18-0 4 ng/L RLDQC

 Prometryn 65103 LCM60 7287-19-6 4.2 ng/L RLDQC

 Propanil 66641 LCM60 709-98-8 12 ng/L RLDQC

 Propargite 68677 LCM60 2312-35-8 2 ng/L RLDQC

 Propazine 68678 LCM60 139-40-2 3.2 ng/L RLDQC

 Propiconazole 66643 LCM60 60207-90-1 6 ng/L RLDQC

 Propoxur 68679 LCM60 114-26-1 3.2 ng/L RLDQC

 Propyzamide 67706 LCM60 23950-58-5 2.4 ng/L RLDQC

 Prosulfuron 61687 LCM60 94125-34-5 10 ng/L RLDQC

 Pyraclostrobin 66646 LCM60 175013-18-0 2.4 ng/L RLDQC

 Pyridaben 68682 LCM60 96489-71-3 2.4 ng/L RLDQC

 Pyriproxyfen 68683 LCM60 95737-68-1 3 ng/L RLDQC

 sec-Acetochlor oxanilic acid 68684 LCM60 152019-74-4 55 ng/L RLDQC

 sec-Alachlor oxanilic acid 68685 LCM60 628324-79-8 110 ng/L RLDQC

 Siduron 68686 LCM60 1982-49-6 5 ng/L RLDQC

 Simazine 65105 LCM60 122-34-9 7.2 ng/L RLDQC

 Sulfentrazone 68687 LCM60 122836-35-5 18 ng/L RLDQC

 Sulfometuron-methyl 68688 LCM60 74222-97-2 4 ng/L RLDQC

 Sulfosulfuron 68689 LCM60 141776-32-1 11 ng/L RLDQC

 Sulfosulfuron ethyl sulfone 68690 LCM60 — 2.8 ng/L RLDQC

 Tebuconazole 66649 LCM60 107534-96-3 15 ng/L RLDQC

 Tebuconazole-d6 (surrogate) 90555 LCM60 — N/A pct N/A

 Tebufenozide 68692 LCM60 112410-23-8 2 ng/L RLDQC

 Tebupirimfos oxon 68694 LCM60 — 2 ng/L RLDQC

 Tebupirimphos 68693 LCM60 96182-53-5 2 ng/L RLDQC

 Tebuthiuron 68695 LCM60 34014-18-1 3 ng/L RLDQC

 Tebuthiuron TP 104 68575 LCM60 59962-53-7 5.6 ng/L RLDQC

 Tebuthiuron TP 109 68621 LCM60 59962-54-8 11 ng/L RLDQC

Tebuthiuron TP 109 (OH) 68697 LCM60 139888-73-6 38 ng/L RLD

Tebuthiuron TP el108 68696 LCM60 39222-73-6 10 ng/L RLD

 Tebuthiuron Transformation Product 106 68714 LCM60 16279-27-9 32 ng/L RLDQC

 Terbacil 68698 LCM60 5902-51-2 21 ng/L RLDQC

 Terbufos 68699 LCM60 13071-79-9 6.8 ng/L RLDQC
64 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.3.1. U.S. Geological National Water Quality Laboratory Schedule 2437 for current-use pesticides in filtered water.—Continued

[Methods are described in Sandstrom and others (2016). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; N/A, not applicable; 

ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; RLDQC, reporting level based on DQCALC software and procedure, 

as described in NWQL Technical Memorandum 15.02; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Terbufos oxon 68700 LCM60 56070-14-5 4 ng/L RLDQC

 Terbufos oxon sulfone 68701 LCM60 56070-15-6 11 ng/L RLDQC

 Terbufos oxon sulfoxide 68702 LCM60 56165-57-2 4 ng/L RLDQC

 Terbufos sulfone 68703 LCM60 56070-16-7 11 ng/L RLDQC

 Terbufos sulfoxide 68704 LCM60 10548-10-4 3 ng/L RLDQC

 Terbuthylazine 66651 LCM60 5915-41-3 3.6 ng/L RLDQC

 Tetraconazole 66654 LCM60 112281-77-3 7 ng/L RLDQC

 Thiobencarb 65107 LCM60 28249-77-6 4.2 ng/L RLDQC

 Thiobencarb-d10 (surrogate) 90556 LCM60 1219804-12-2 N/A pct N/A

 trans-Permethrin 68708 LCM60 61949-77-7 3.8 ng/L RLDQC

 Triallate 68710 LCM60 — 12 ng/L RLDQC

 Tribufos 68711 LCM60 78-48-8 2 ng/L RLDQC

 Triclopyr 68712 LCM60 55335-06-3 88 ng/L RLDQC

Trifloxystrobin 66660 LCM60 141517-21-7 2.8 ng/L RLD

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 65

Table 2.3.2. U.S. Geological National Water Quality Laboratory custom method LCM75 for supplemental pesticides and degradates in 

filtered water.

[Method is equivalent to that in Sandstrom and others (2016), except that the instrument used is an Agilent model 6495 LC-MS/MS. Parameter names are 

as shown in the U.S. Geological Survey (USGS) National Water Information System (NWIS) database and do not include special characters or formatting. 

Abbrteviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; N/A, not applicable; ng/L, nanogram per liter; NWQL, USGS National Water 

Quality Laboratory; pct, percent; RSD, relative standard deviation; —, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

Mean 

recovery 

(percent)

RSD 

(percent)

 2,6-Dichlorobenzamide 9045 52656 LCM75 2008-58-4 3.3 ng/L irl 106.4 13.2

 Acetamiprid 9045 68302 LCM75 135410-20-7 11 ng/L irl 105.5 10.2

 Acetamiprid-13C6 (surrogate) 9045 90453 LCM75 — N/A pct irl — —

 Aminocyclopyrachlor 9045 52651 LCM75 858956-08-8 2.2 ng/L irl 113.2 16.3

Benzovindiflupyr 9045 52652 LCM75 1072957-71-1 2.2 ng/L irl 103.2 10

Bicyclopyrone 9045 52653 LCM75 352010-68-5 5.2 ng/L irl 106.6 10

Boscalid 9045 67550 LCM75 188425-85-6 3.9 ng/L irl 108.2 10

 Chlorantraniliprole 9045 51856 LCM75 500008-45-7 3 ng/L irl 107.0 12.2

 Clothianidin 9045 68221 LCM75 210880-92-5 6 ng/L irl 105.5 11.0

 N-(2-Chlorothiazol-5-ylmethy1)-

N’-methylguanidine (TMG)

9045 52661 LCM75 635283-91-9 3.9 ng/L irl 118.1 11.1

 N-(2-Chloro-5-thiazolyl methyl)-

N’-nitroguanidine (TZNG)

9045 52660 LCM75 135018-15-4 19 ng/L irl 102.0 11.3

 Clothianidin-d3 (surrogate) 9045 90452 LCM75 1262776-24-8 N/A pct irl — —

 Cyantraniliprole 9045 51862 LCM75 736994-63-1 4.6 ng/L irl 83.7 14.8

 Cyantraniliprole degradate INJSE769045 52662 LCM75 — 7 ng/L irl 101.7 15.0

 Cyantraniliprole degradate INK5A799045 52663 LCM75 — 13 ng/L irl 86.7 18.9

 Cyantraniliprole degradate INRNU719045 52664 LCM75 — 14 ng/L irl 104.5 13.7

 Cyprodinil 9045 67574 LCM75 121552-61-2 7.6 ng/L irl 105.0 10.3

 Dimethomorph 9045 68373 LCM75 110488-70-5 2.9 ng/L irl 104.4 10.1

 Dinotefuran 9045 68379 LCM75 165252-70-0 2.8 ng/L irl 106.4 11.3

 Fluopicolide 9045 51852 LCM75 239110-15-7 3 ng/L irl 106.0 9.6

 Flutriafol 9045 67653 LCM75 76674-21-0 2.2 ng/L irl 103.8 18.9

 Fomesafen 9045 52654 LCM75 72178-02-0 7.5 ng/L irl 104.3 12.0

 Imazosulfuron 9045 52655 LCM75 122548-33-8 4.1 ng/L irl 105.4 11.4

 Imidacloprid 9045 68426 LCM75 138261-41-3 14 ng/L irl 107.7 13.3

 Imidacloprid-d4 (surrogate) 9045 90537 LCM75 1015855-75-0 N/A pct irl — —

Imidacloprid-olefin 9045 52782 LCM75 115086-54-9 8.9 ng/L irl 115.4 9

 Myclobutanil 9045 66632 LCM75 88671-89-0 2.7 ng/L irl 106.8 10.4

 Pyrimethanil 9045 67717 LCM75 53112-28-0 9 ng/L irl 107.0 12.9

Sulfoxaflor 9045 52657 LCM75 946578-00-3 3.1 ng/L irl 109.6 9

 Tebuconazole-d6 (surrogate) 9045 90555 LCM75 — N/A pct irl — —

 Thiacloprid 9045 68485 LCM75 111988-49-9 3.3 ng/L irl 106.4 10.4

 Thiamethoxam 9045 68245 LCM75 153719-23-4 2.8 ng/L irl 109.0 13.1

 Thiamethoxam-d3 (surrogate) 9045 90451 LCM75 1294048-82-0 pct irl — —

 Tribenuron-methyl 9045 52650 LCM75 101200-48-0 56 ng/L irl 34.3 73.1

 Zoxamide 9045 67768 LCM75 156052-68-5 2.3 ng/L irl 102.8 9.4

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
66 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.4. U.S. Geological Survey National Water Quality Laboratory Schedule 2440 for pharmaceutical compounds in water.

[Methods are described in Furlong and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; 

mrl, minimum reporting level; N/A, not applicable; ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 1,7-Dimethylxanthine (p-Xanthine) 67446 LCM56 611-59-6 87 ng/L irl

 10-Hydroxy-amitriptyline 67995 LCM56 64520-05-4 8.3 ng/L irl

 Abacavir 68022 LCM56 136470-78-5 8.2 ng/L irl

 Acetaminophen 67436 LCM56 103-90-2 7.1 ng/L irl

 Acetaminophen-d3 (surrogate) 91775 LCM56 — N/A pct mrl

 Acyclovir 67484 LCM56 59277-89-3 22 ng/L irl

 Albuterol 67437 LCM56 18559-94-9 6.7 ng/L irl

 Albuterol-d9 (surrogate) 91772 LCM56 — N/A pct mrl

 Alprazolam 68250 LCM56 28981-97-7 21 ng/L irl

 Amitriptyline 67522 LCM56 50-48-6 37 ng/L irl

 Amphetamine 67461 LCM56 300-62-9 8.1 ng/L irl

 Amphetamine-d6 (surrogate) 91784 LCM56 — N/A pct mrl

 Antipyrine 67477 LCM56 60-80-0 116 ng/L irl

 Atenolol 67502 LCM56 29122-68-7 13 ng/L irl

 Atrazine 65065 LCM56 1912-24-9 19 ng/L irl

Benztropine 67997 LCM56 86-13-5 24 ng/L i

Betamethasone 67485 LCM56 378-44-9 114 ng/L i

Bupropion 67439 LCM56 34911-55-2 17 ng/L i

Caffeine 67440 LCM56 58-08-2 90 ng/L i

Caffeine (trimethyl-13C3) (surrogate) 91781 LCM56 — N/A pct m

 Carbamazepine 67441 LCM56 298-46-4 11 ng/L irl

 Carisoprodol 67498 LCM56 78-44-4 12 ng/L irl

 Chlorpheniramine 67497 LCM56 132-22-9 4.6 ng/L irl

 Cimetidine 67442 LCM56 51481-61-9 27 ng/L irl

 Citalopram 67505 LCM56 59729-33-8 6.5 ng/L irl

 Clonidine 67518 LCM56 4205-90-7 60 ng/L irl

 Codeine 67443 LCM56 76-57-3 88 ng/L irl

 Codeine-d6 (surrogate) 91786 LCM56 371151-94-9 N/A pct mrl

 Cotinine 67444 LCM56 486-56-6 6.3 ng/L irl

 Cotinine-d3 (surrogate) 91783 LCM56 — N/A pct mrl

 Dehydronifedipine 67445 LCM56 67035-22-7 24 ng/L irl

 Desmethyldiltiazem 67999 LCM56 — 12 ng/L irl

 Desvenlafaxine 68251 LCM56 93413-62-8 7.4 ng/L irl

 Dextromethorphan 67468 LCM56 125-71-3 8.2 ng/L irl

 Diazepam (valium) 67499 LCM56 439-14-5 2.2 ng/L irl

 Diazepam-d5 surrogate (surrogate) 91790 LCM56 65854-76-4 N/A pct mrl

 Diltiazem 67519 LCM56 42399-41-7 10 ng/L irl

 Diltiazem-d3 (surrogate) 91773 LCM56 — N/A pct mrl

 Diphenhydramine 67447 LCM56 147-24-0 5.7 ng/L irl

 Diphenhydramine-d3 (surrogate) 91788 LCM56 — N/A pct mrl
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 67

Table 2.4. U.S. Geological Survey National Water Quality Laboratory Schedule 2440 for pharmaceutical compounds in water.—

Continued

[Methods are described in Furlong and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; 

mrl, minimum reporting level; N/A, not applicable; ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Duloxetine 67448 LCM56 116539-59-4 36 ng/L irl

 Erythromycin 67449 LCM56 114-07-8 53 ng/L irl

 Ezetimibe 67487 LCM56 163222-33-1 63 ng/L irl

 Fadrozole 68012 LCM56 102676-47-1 7.3 ng/L irl

 Famotidine 68000 LCM56 76824-35-6 10 ng/L irl

Fenofibrate 67489 LCM56 49562-28-9 6.2 ng/L i

 Fexofenadine 67510 LCM56 83799-24-0 19 ng/L irl

 Fluconazole 67478 LCM56 86386-73-4 71 ng/L irl

 Fluoxetine 67450 LCM56 54910-89-3 26 ng/L irl

 Fluoxetine-d6 (surrogate) 91789 LCM56 — N/A pct mrl

 Fluticasone 67529 LCM56 90566-53-3 4.6 ng/L irl

 Fluvoxamine 67521 LCM56 54739-18-3 53 ng/L irl

 Gabapentin 52817 LCM56 60142-96-3 400 ng/L RLDQC

 Glipizide 68001 LCM56 29094-61-9 148 ng/L mrl

 Glyburide 68002 LCM56 10238-21-8 3.9 ng/L irl

 Guanylurea 52816 LCM56 141-83-3 400 ng/L RLDQC

 Hexamethylenetetramine 52815 LCM56 100-97-0 110 ng/L RLDQC

 Hydrocodone 67506 LCM56 125-29-1 10 ng/L irl

 Hydrocodone-d3 (surrogate) 91779 LCM56 — N/A pct mrl

 Hydrocortisone 67459 LCM56 50-23-7 147 ng/L irl

 Hydroxyzine 68005 LCM56 68-88-2 7.4 ng/L irl

 Iminostilbene 67481 LCM56 256-96-2 145 ng/L irl

Ketoconazole 68014 LCM56 65277-42-1 113 ng/L i

 Lamivudine 68018 LCM56 134678-17-4 16 ng/L irl

 Lidocaine 67462 LCM56 137-58-6 15 ng/L irl

 Loperamide 67515 LCM56 53179-11-6 11 ng/L irl

 Loratadine 67488 LCM56 79794-75-5 6.9 ng/L irl

 Lorazepam 67470 LCM56 846-49-1 116 ng/L irl

 Meprobamate 67464 LCM56 57-53-4 86 ng/L irl

 Metaxalone 67504 LCM56 1665-48-1 15 ng/L irl

 Metformin 67492 LCM56 657-24-9 13 ng/L irl

 Methadone 67500 LCM56 76-99-3 7.6 ng/L irl

 Methadone-d9 (surrogate) 91777 LCM56 — N/A pct mrl

 Methocarbamol 67501 LCM56 532-03-6 8.7 ng/L irl

 Methotrexate 67525 LCM56 59-05-2 52 ng/L irl

 Methyl-1H-benzotriazole 67514 LCM56 29385-43-1 141 ng/L irl

 Metoprolol 67523 LCM56 51384-51-1 27 ng/L irl

 Morphine 67458 LCM56 57-27-2 14 ng/L irl

 Nadalol 68006 LCM56 42200-33-9 80 ng/L irl
68 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.4. U.S. Geological Survey National Water Quality Laboratory Schedule 2440 for pharmaceutical compounds in water.—

Continued

[Methods are described in Furlong and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; 

mrl, minimum reporting level; N/A, not applicable; ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Nevirapine 68017 LCM56 129618-40-2 15 ng/L irl

 Nicotine 67493 LCM56 54-11-5 57 ng/L irl

 Nizatidine 67479 LCM56 76963-41-2 19 ng/L irl

 Nordiazepam 68252 LCM56 1088-11-5 41 ng/L irl

 Norethindrone 67434 LCM56 68-22-4 10 ng/L irl

Norfluoxetine 67451 LCM56 56161-73-0 199 ng/L i

Norfluoxetine-d6 (surrogate) 91776 LCM56 — N/A pct m

 Norsertraline 67532 LCM56 87857-41-8 192 ng/L irl

 Norverapamil 68007 LCM56 67018-85-3 8.5 ng/L irl

Omeprazole 67512 LCM56 73590-58-6 5.6 ng/L i

Oseltamivir 67511 LCM56 196618-13-0 14 ng/L i

Oxazepam 67469 LCM56 604-75-1 140 ng/L i

Oxycodone 67495 LCM56 76-42-6 24 ng/L i

Oxycodone-d3 (surrogate) 91778 LCM56 — N/A pct m

 Paroxetine 67527 LCM56 61869-08-7 20 ng/L irl

 Penciclovir 68021 LCM56 39809-25-1 40 ng/L irl

 Pentoxifylline 67480 LCM56 6493-05-6 9.3 ng/L irl

 Phenazopyridine 68008 LCM56 94-78-0 13 ng/L irl

 Phendimetrazine 67496 LCM56 634-03-7 31 ng/L irl

 Phenytoin 67466 LCM56 57-41-0 188 ng/L irl

 Piperonyl butoxide 67435 LCM56 51-03-6 3 ng/L irl

 Prednisolone 67483 LCM56 50-24-8 150 ng/L irl

 Prednisone 67467 LCM56 53-03-2 168 ng/L irl

 Promethazine 67524 LCM56 60-87-7 50 ng/L irl

 Propoxyphene 68009 LCM56 469-62-5 17 ng/L irl

 Propranolol 67516 LCM56 525-66-6 26 ng/L irl

 Pseudoephedrine 67460 LCM56 — 11 ng/L irl

 Pseudoephedrine-d3 surrogate (surrogate) 91787 LCM56 — N/A pct mrl

 Quinine 68011 LCM56 130-95-0 79 ng/L irl

 Ractopamine 52814 LCM56 97825-25-7 20 ng/L RLDQC

 Raloxifene 67530 LCM56 84449-90-1 9.7 ng/L irl

 Ranitidine 67452 LCM56 66357-35-5 192 ng/L irl

 Sertraline 67528 LCM56 79617-96-2 16 ng/L irl

 Sitagliptin 67531 LCM56 790712-60-6 97 ng/L irl

 Sulfadimethoxine 67503 LCM56 122-11-2 65 ng/L irl

 Sulfamethizole 67476 LCM56 144-82-1 104 ng/L irl

 Sulfamethoxazole 67454 LCM56 723-46-6 26 ng/L irl

 Sulfamethoxazole-(phenyl-13C6) (surrogate) 91782 LCM56 — N/A pct mrl

 Tamoxifen 68015 LCM56 10540-29-1 80 ng/L mrl
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 69

Table 2.4. U.S. Geological Survey National Water Quality Laboratory Schedule 2440 for pharmaceutical compounds in water.—

Continued

[Methods are described in Furlong and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; 

mrl, minimum reporting level; N/A, not applicable; ng/L, nanogram per liter; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 Temazepam 67471 LCM56 846-50-4 18 ng/L irl

 Temazepam-d5 (surrogate) 91780 LCM56 — N/A pct mrl

 Theophylline 67494 LCM56 58-55-9 41 ng/L irl

 Thiabendazole 67455 LCM56 148-79-8 4.1 ng/L irl

 Thiabendazole-d4 (surrogate) 91769 LCM56 — N/A pct mrl

 Tiotropium 67508 LCM56 186691-13-4 43 ng/L irl

 Tramadol 67517 LCM56 27203-92-5 15 ng/L irl

 Triamterene 67475 LCM56 396-01-0 5.2 ng/L irl

 Trimethoprim 67456 LCM56 738-70-5 19 ng/L irl

 Trimethoprim-d9 (surrogate) 91774 LCM56 — N/A pct mrl

 Valacyclovir 67507 LCM56 124832-26-4 163 ng/L irl

 Venlafaxine 67534 LCM56 93413-69-5 4.4 ng/L irl

 Verapamil 67472 LCM56 52-53-9 15 ng/L irl

 Warfarin 67457 LCM56 81-81-2 6 ng/L Irl

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
70 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.5. U.S. Geological Survey National Water Quality Laboratory Schedule 4433 for organic wastewater indicator compounds in 

water.

[Methods are described in Zaugg and others (2006). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information System 

(NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; mL, milliliter; mrl, minimum reporting level; N/A, not applicable; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data; μg/L, microgram per liter]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 1,4-Dichlorobenzene 34571 GCM99 106-46-7 0.08 μg/L irl

 1-Methylnaphthalene 81696 GCM99 90-12-0 0.04 μg/L irl

2,2’,4,4’-Tetrabromodiphenylether (PBDE 47) 63147 GCM99 5436-43-1 0.04 μg/L i

 2,6-Dimethylnaphthalene 62805 GCM99 581-42-0 0.04 μg/L irl

 2-Methylnaphthalene 30194 GCM99 91-57-6 0.04 μg/L irl

 3,4-Dichlorophenyl isocyanate 63145 GCM99 102-36-3 0.32 μg/L irl

 3-beta-Coprostanol 62806 GCM99 360-68-9 1.6 μg/L irl

 3-Methyl-1(H)-indole (Skatole) 62807 GCM99 83-34-1 0.04 μg/L irl

3-tert-Butyl-4-hydroxy anisole (BHA) 61702 GCM99 121-00-6 0.16 μg/L i

 4-Cumylphenol 62808 GCM99 599-64-4 0.04 μg/L irl

4-n-Octylphenol 62809 GCM99 1806-26-4 0.02 μg/L i

4-Nonylphenol diethoxylate (NP2EO), all isomers 61703 GCM99 — 1.6 μg/L i

4-Nonylphenol monoethoxylate (NP1EO), all isomers 61704 GCM99 104-35-8 1.6 μg/L i

4-tert-Octylphenol 62810 GCM99 140-66-9 0.4 μg/L i

4-tert-Octylphenol diethoxylate, aka OP2EO 62486 GCM99 2315-61-9 0.2 μg/L i

4-tert-Octylphenol monoethoxylate, aka OP1EO 62485 GCM99 2315-67-5 0.6 μg/L i

 5-Methyl-1H-benzotriazole 61944 GCM99 136-85-6 0.32 μg/L irl

 Acetophenone 62811 GCM99 98-86-2 0.4 μg/L irl

 Acetyl hexamethyl tetrahydronaphthalene (AHTN) 62812 GCM99 21145-77-7 0.04 μg/L irl

 Anthracene 34220 GCM99 120-12-7 0.02 μg/L irl

 Anthraquinone 62813 GCM99 84-65-1 0.04 μg/L irl

 Atrazine 39630 GCM99 1912-24-9 0.16 μg/L irl

Benzo[a]pyrene 34247 GCM99 50-32-8 0.02 μg/L i

Benzophenone 62814 GCM99 119-61-9 0.08 μg/L i

 beta-Sitosterol 62815 GCM99 83-46-5 4.8 μg/L irl

 beta-Stigmastanol 61948 GCM99 19466-47-8 3.4 μg/L irl

Bis(2-ethylhexyl) phthalate 39100 GCM99 117-81-7 2 μg/L i

Bisphenol A 62816 GCM99 80-05-7 0.04 μg/L i

Bisphenol A-d3 (surrogate) 62839 GCM99 — N/A pct m

Bromacil 30234 GCM99 314-40-9 0.16 μg/L i

Bromoform 32104 GCM99 75-25-2 0.16 μg/L i

Caffeine 81436 GCM99 58-08-2 0.08 μg/L i

Caffeine-C13 (surrogate) 62840 GCM99 — N/A pct m

 Camphor 62817 GCM99 76-22-2 0.08 μg/L irl

 Carbaryl 39750 GCM99 63-25-2 0.06 μg/L irl

 Carbazole 77571 GCM99 86-74-8 0.02 μg/L irl

 Chlorpyrifos 38932 GCM99 2921-88-2 0.12 μg/L irl

 Cholesterol 62818 GCM99 57-88-5 1.6 μg/L irl

 Cotinine 61945 GCM99 486-56-6 0.08 μg/L irl
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 71

Table 2.5. U.S. Geological Survey National Water Quality Laboratory Schedule 4433 for organic wastewater indicator compounds in 

water.—Continued

[Methods are described in Zaugg and others (2006). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information System 

(NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; irl, interim reporting level; mL, milliliter; mrl, minimum reporting level; N/A, not applicable; NWQL, USGS National Water Quality Laboratory; pct, percent; —, no data; μg/L, microgram per liter]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 d-Limonene 62819 GCM99 5989-27-5 0.16 μg/L irl

Decafluorobiphenyl (surrogate) 62841 GCM99 434-90-2 N/A pct m

 Diazinon 39570 GCM99 333-41-5 0.32 μg/L irl

 Dichlorvos 30218 GCM99 62-73-7 0.08 μg/L irl

 Diethyl phthalate 34336 GCM99 84-66-2 0.4 μg/L irl

 Fluoranthene 34376 GCM99 206-44-0 0.02 μg/L irl

 Fluoranthene-d10 (surrogate) 62842 GCM99 93951-69-0 N/A pct mrl

Hexahydrohexamethylcyclopentabenzopyran (HHCB) 62823 GCM99 1222-05-5 0.04 μg/L i

 Indole 62824 GCM99 120-72-9 0.04 μg/L irl

 Isoborneol 62825 GCM99 124-76-5 0.09 μg/L irl

 Isophorone 34408 GCM99 78-59-1 0.05 μg/L irl

 Isopropylbenzene 77223 GCM99 98-82-8 0.04 μg/L irl

 Isoquinoline 62826 GCM99 119-65-3 0.8 μg/L irl

 Menthol 62827 GCM99 89-78-1 0.32 μg/L irl

 Metalaxyl 04254 GCM99 57837-19-1 0.16 μg/L irl

 Methyl salicylate 62828 GCM99 119-36-8 0.08 μg/L irl

 Metolachlor 82612 GCM99 51218-45-2 0.04 μg/L irl

 N,N-Diethyl-meta-toluamide (DEET) 61947 GCM99 134-62-3 0.04 μg/L irl

 Naphthalene 34696 GCM99 91-20-3 0.02 μg/L irl

 p-Cresol 77146 GCM99 106-44-5 0.08 μg/L irl

 para-Nonylphenol (total) (branched) 62829 GCM99 84852-15-3 1.6 μg/L irl

 Pentachlorophenol 39032 GCM99 87-86-5 1.6 μg/L irl

 Phenanthrene 34461 GCM99 85-01-8 0.02 μg/L irl

 Phenol 34694 GCM99 108-95-2 0.16 μg/L irl

 Prometon 39056 GCM99 1610-18-0 0.16 μg/L irl

 Pyrene 34469 GCM99 129-00-0 0.02 μg/L irl

 Sample volume 99963 GCM99 — N/A mL irl

 Tetrachloroethylene 34475 GCM99 127-18-4 0.16 μg/L irl

 Tributyl phosphate 62832 GCM99 126-73-8 0.064 μg/L irl

 Triclosan 61708 GCM99 3380-34-5 0.32 μg/L irl

 Triethyl citrate (ethyl citrate) 62833 GCM99 77-93-0 0.04 μg/L irl

 Triphenyl phosphate 62834 GCM99 115-86-6 0.08 μg/L irl

 Tris(2-butoxyethyl)phosphate 62830 GCM99 78-51-3 0.64 μg/L irl

 Tris(2-chloroethyl)phosphate 62831 GCM99 115-96-8 0.16 μg/L irl

 Tris(dichloroisopropyl)phosphate 61707 GCM99 13674-87-8 0.32 μg/L Irl

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
72 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.6. U.S. Geological Survey National Water Quality Laboratory Schedule 5433 for organic wastewater indicator compounds in 

bed sediment.

[Methods are decribed in Burkhardt and others (2006). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: NWQL, USGS National Water Quality Laboratory; 

CAS, Chemical Abstracts Service1; N/A, not applicable; μg/kg, microgram per kilogram; pct, percent; g, gram; irl, interim reporting level; —, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

 1,4-Dichlorobenzene 80256 63163 GM008 106-46-7 100 μg/kg irl

 1-Methylnaphthalene 80257 63165 GM008 90-12-0 100 μg/kg irl

2,2’,4,4’-Tetrabromodiphenylether (PBDE 47) 80313 63166 GM008 5436-43-1 100 μg/kg i

 2,6-Dimethylnaphthalene 80258 63167 GM008 581-42-0 100 μg/kg irl

 2-Methylnaphthalene 80259 63168 GM008 91-57-6 100 μg/kg irl

 3-beta-Coprostanol 80261 63170 GM008 360-68-9 1,000 μg/kg irl

 3-Methyl-1(H)-indole (Skatole) 80262 63171 GM008 83-34-1 100 μg/kg irl

3-tert-Butyl-4-hydroxy anisole (BHA) 80263 63172 GM008 121-00-6 300 μg/kg i

 4-Cumylphenol 80264 63173 GM008 599-64-4 100 μg/kg irl

4-n-Octylphenol 80265 63174 GM008 1806-26-4 100 μg/kg i

 4-Nonylphenol (sum of all isomers) 80307 63175 GM008 104-40-5 1,500 μg/kg irl

4-Nonylphenol diethoxylate (NP2EO), all isomers 80302 63200 GM008 — 2,000 μg/kg i

4-Nonylphenol monoethoxylate (NP1EO), all isomers 80303 63221 GM008 104-35-8 1,000 μg/kg i

4-tert-Octylphenol 80266 63176 GM008 140-66-9 100 μg/kg i

4-tert-Octylphenol diethoxylate, aka OP2EO 80304 63201 GM008 2315-61-9 100 μg/kg i

4-tert-Octylphenol monoethoxylate, aka OP1EO 80305 63206 GM008 2315-67-5 500 μg/kg i

 Acetophenone 80267 63178 GM008 98-86-2 300 μg/kg irl

 Acetyl hexamethyl tetrahydronaphthalene (AHTN) 80268 63179 GM008 21145-77-7 100 μg/kg irl

 Anthracene 80269 63180 GM008 120-12-7 100 μg/kg irl

 Anthraquinone 80270 63181 GM008 84-65-1 100 μg/kg irl

 Atrazine 80271 63182 GM008 1912-24-9 200 μg/kg irl

Benzo[a]pyrene 80272 63183 GM008 50-32-8 100 μg/kg i

Benzophenone 80273 63184 GM008 119-61-9 100 μg/kg i

 beta-Sitosterol 80274 63185 GM008 83-46-5 1,000 μg/kg irl

 beta-Stigmastanol 80275 63186 GM008 19466-47-8 1,000 μg/kg irl

Bis(2-ethylhexyl) phthalate 80286 63187 GM008 117-81-7 500 μg/kg i

Bisphenol A 80276 63188 GM008 80-05-7 100 μg/kg i

Bisphenol A-d3 (surrogate) 80277 90735 GM008 — N/A pct i

Bromacil 80278 63189 GM008 314-40-9 1,000 μg/kg i

 Camphor 80279 63192 GM008 76-22-2 100 μg/kg irl

 Carbazole 80280 63194 GM008 86-74-8 100 μg/kg irl

 Chlorpyrifos 80281 63195 GM008 2921-88-2 100 μg/kg irl

 Cholesterol 80282 63196 GM008 57-88-5 500 μg/kg irl

 d-Limonene 80287 63203 GM008 5989-27-5 100 μg/kg irl

Decafluorobiphenyl (surrogate) 80283 90737 GM008 434-90-2 N/A pct i

 Diazinon 80284 63198 GM008 333-41-5 100 μg/kg irl

 Diethyl phthalate 80285 63202 GM008 84-66-2 200 μg/kg irl

 Fluoranthene 80288 63208 GM008 206-44-0 100 μg/kg irl

 Fluoranthene-d10 (surrogate) 80289 90738 GM008 93951-69-0 N/A pct irl
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 73

Table 2.6. U.S. Geological Survey National Water Quality Laboratory Schedule 5433 for organic wastewater indicator compounds in 

bed sediment.—Continued

[Methods are decribed in Burkhardt and others (2006). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: NWQL, USGS National Water Quality Laboratory; 

CAS, Chemical Abstracts Service1; N/A, not applicable; μg/kg, microgram per kilogram; pct, percent; g, gram; irl, interim reporting level; —, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

Hexahydrohexamethylcyclopentabenzopyran (HHCB) 80290 63209 GM008 1222-05-5 100 μg/kg i

 Indole 80291 63210 GM008 120-72-9 200 μg/kg irl

 Isoborneol 80292 63211 GM008 124-76-5 100 μg/kg irl

 Isophorone 80293 63212 GM008 78-59-1 100 μg/kg irl

 Isopropylbenzene 80294 63213 GM008 98-82-8 200 μg/kg irl

 Isoquinoline 80295 63214 GM008 119-65-3 200 μg/kg irl

 Menthol 80296 63215 GM008 89-78-1 100 μg/kg irl

 Metolachlor 80299 63218 GM008 51218-45-2 100 μg/kg irl

 N,N-Diethyl-meta-toluamide (DEET) 80300 63219 GM008 134-62-3 200 μg/kg irl

 Naphthalene 80301 63220 GM008 91-20-3 100 μg/kg irl

 p-Cresol 80306 63222 GM008 106-44-5 500 μg/kg irl

 Phenanthrene 80309 63224 GM008 85-01-8 100 μg/kg irl

 Phenol 80310 63225 GM008 108-95-2 100 μg/kg irl

 Prometon 80311 63226 GM008 1610-18-0 100 μg/kg irl

 Pyrene 80312 63227 GM008 129-00-0 100 μg/kg irl

 Sample weight, grams 80320 91100 GM008 — N/A g irl

 Tributyl phosphate 80317 63231 GM008 126-73-8 100 μg/kg irl

 Triclosan 80318 63232 GM008 3380-34-5 100 μg/kg irl

 Triphenyl phosphate 80319 63234 GM008 115-86-6 100 μg/kg irl

 Tris(2-butoxyethyl)phosphate 80314 63229 GM008 78-51-3 300 μg/kg irl

 Tris(2-chloroethyl)phosphate 80315 63230 GM008 115-96-8 200 μg/kg irl

 Tris(dichloroisopropyl)phosphate 80316 63235 GM008 13674-87-8 200 μg/kg Irl

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

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74 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.7. U.S. Environmental Protection Agency Laboratory Schedule for polycyclic aromatic hydrocarbons in bed sediment, using 

U.S. Environmental Protection Agency method 8270D.

[Methods are described in U.S. Environmental Protection Agency (2014). Abbreviations: μg/kg, microgram per kilogram; pct, percent; N/A, not applicable]

Parameter name Reporting level Unit

 Acenaphthylene, bed sediment, recoverable, dry weight 25 μg/kg

 Acenaphthene, bed sediment, recoverable, dry weight 25 μg/kg

 Anthracene, bed sediment, recoverable, dry weight 25 μg/kg

Benzo[b]fluoranthene, bed sediment, recoverable 25 μg/

Benzo[k]fluoranthene, bed sediment, recoverable 25 μg/

Benzo[a]pyrene, bed sediment, recoverable, dry weight 25 μg/

 Chrysene, bed sediment, recoverable, dry weight 25 μg/kg

 Fluoranthene, bed sediment, recoverable, dry weight 25 μg/kg

 9H-Fluorene, bed sediment, recoverable, dry weight 25 μg/kg

 Indeno[1,2,3-cd]pyrene, bed sediment, recoverable, dry weight 25 μg/kg

 Naphthalene, bed sediment, recoverable, dry weight 25 μg/kg

 Phenanthrene, bed sediment, recoverable, dry weight 25 μg/kg

 Pyrene, bed sediment, recoverable, dry weight 25 μg/kg

Benzo[ghi]perylene, bed sediment, recoverable, dry weight 25 μg/

Benzo[a]anthracene, bed sediment, recoverable, dry weight 25 μg/

 Dibenzo[a,h]anthracene, bed sediment, recoverable, dry weight 25 μg/kg

 2-Methylnaphthalene, bed sediment, recoverable, dry weight 25 μg/kg

 Moisture content, bed sediment, dry weight N/A pct
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 75

Table 2.8. U.S. Geological Survey National Water Quality Laboratory custom method 8093 for halogenated organic compounds in bed 

sediment.

[Methods are described in Mahler and others (2009), and Wagner and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) 

National Water Information System (NWIS) database and do not include special characters or formatting. Abbreviations: NWQL, USGS National Water 

Quality Laboratory; CAS, Chemical Abstracts Service1; N/A, not applicable; μg/kg, microgram per kilogram; pct, percent; g, gram; irl, interim reporting level; 

—, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

2,2’,4,4’-Tetrabromodiphenylether (PBDE 47) 81563 63166 GM014 5436-43-1 0.2 μg/kg i

 Triclosan 81541 63232 GM014 3380-34-5 4 μg/kg irl

 alpha-Endosulfan 81542 63259 GM014 959-98-8 0.2 μg/kg irl

 beta-Endosulfan 82198 63260 GCM14 33213-65-9 0.2 μg/kg irl

Benfluralin 81521 63265 GM014 1861-40-1 0.2 μg/kg i

 cis-Chlordane 81540 63271 GM014 5103-71-9 0.2 μg/kg irl

 trans-Chlordane 81537 63272 GM014 5103-74-2 0.2 μg/kg irl

 Chlorpyrifos 81530 63273 GM014 2921-88-2 0.2 μg/kg irl

Cyfluthrin 81571 63279 GM014 68359-37-5 0.2 μg/kg i

 lambda-Cyhalothrin 81565 63280 GM014 91465-08-6 0.2 μg/kg irl

 Dacthal 81529 63282 GM014 1861-32-1 0.2 μg/kg irl

 Dieldrin 81545 63289 GM014 60-57-1 0.1 μg/kg irl

 Endosulfan sulfate 82195 63298 GCM14 1031-07-8 0.4 μg/kg irl

 Fipronil 81534 63313 GM014 120068-37-3 0.1 μg/kg irl

Fipronil sulfide 81532 63314 GM014 120067-83-6 0.1 μg/kg i

Desulfinylfipronil 81526 63316 GM014 — 0.1 μg/kg i

 cis-Nonachlor 81552 63338 GM014 5103-73-1 0.1 μg/kg irl

 trans-Nonachlor 81538 63339 GM014 39765-80-5 0.1 μg/kg irl

Oxyfluorfen 81546 63341 GM014 42874-03-3 4 μg/kg i

 p,p’-DDT 81556 63345 GM014 50-29-3 4 μg/kg irl

 p,p’-DDD 81553 63346 GM014 72-54-8 2 μg/kg irl

 p,p’-DDE 81544 63347 GM014 72-55-9 1 μg/kg irl

 Pendimethalin 81535 63353 GM014 40487-42-1 1 μg/kg irl

Tefluthrin 81522 63377 GM014 79538-32-2 0.5 μg/kg i

Trifluralin 81520 63390 GM014 1582-09-8 0.2 μg/kg i

 Hexachlorobenzene 81523 63631 GM014 118-74-1 0.1 μg/kg irl

 Methyl triclosan 81543 63639 GM014 4640-01-1 6 μg/kg irl

 Pentachloronitrobenzene 81525 63650 GM014 82-68-8 0.1 μg/kg irl

 Tetradifon 81566 63665 GM014 116-29-0 0.2 μg/kg irl

 Pentachloroanisole 81524 64119 GM014 1825-21-4 0.1 μg/kg irl

PCB, congener, iupac #49 81528 64725 GM014 41464-40-8 2 μg/kg i

PCB, congener, iupac #52 81527 64726 GM014 35693-99-3 1 μg/kg i

PCB, congener, iupac #70 81536 64727 GM014 32598-11-1 2 μg/kg i

PCB, congener, iupac #101 81539 64729 GM014 37680-73-2 1 μg/kg i

PCB, congener, iupac #110 81547 64730 GM014 38380-03-9 1 μg/kg i

PCB, congener, iupac #118 81550 64731 GM014 31508-00-6 0.1 μg/kg i

PCB, congener, iupac #138 81555 64732 GM014 35065-28-2 0.1 μg/kg i

PCB, congener, iupac #146 81551 64733 GM014 51908-16-8 0.1 μg/kg i
76 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.8. U.S. Geological Survey National Water Quality Laboratory custom method 8093 for halogenated organic compounds in bed 

sediment.—Continued

[Methods are described in Mahler and others (2009), and Wagner and others (2014). Parameter names are as shown in the U.S. Geological Survey (USGS) 

National Water Information System (NWIS) database and do not include special characters or formatting. Abbreviations: NWQL, USGS National Water 

Quality Laboratory; CAS, Chemical Abstracts Service1; N/A, not applicable; μg/kg, microgram per kilogram; pct, percent; g, gram; irl, interim reporting level; 

—, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

PCB, congener, iupac #149 81549 64734 GM014 38380-04-0 1 μg/kg i

PCB, congener, iupac #151 81548 64735 GM014 52663-63-5 0.1 μg/kg i

PCB, congener, iupac #170 81564 64736 GM014 35065-30-6 0.1 μg/kg i

PCB, congener, iupac #174 81559 64737 GM014 38411-25-5 0.1 μg/kg i

PCB, congener, iupac #177 81560 64738 GM014 52663-70-4 0.1 μg/kg i

PCB, congener, iupac #180 81561 64739 GM014 35065-29-3 0.1 μg/kg i

PCB, congener, iupac #183 81558 64740 GM014 52663-69-1 0.1 μg/kg i

PCB, congener, iupac #187 81557 64741 GM014 52663-68-0 0.1 μg/kg i

PCB, congener, iupac #194 81568 64742 GM014 35694-08-7 0.1 μg/kg i

PCB, congener, iupac #206 81570 64743 GM014 40186-72-9 0.1 μg/kg i

2,3’,4,4’-Tetrabromodiphenyl ether (PBDE 66) 81567 64852 GM014 189084-61-5 0.1 μg/kg i

2,3’,4’,6-Tetrabromodiphenyl ether (PBDE 71) 81562 64853 GM014 189084-62-6 0.1 μg/kg i

2,2’,3,4,4’-Pentabromodiphenyl ether (PBDE 85) 81573 64854 GM014 182346-21-0 0.1 μg/kg i

2,2’,4,4’,5-Pentabromodiphenyl ether (PBDE 99) 81572 64855 GM014 60348-60-9 0.2 μg/kg i

2,2’,4,4’,6-Pentabromodiphenyl ether (PBDE 100) 81569 64856 GM014 189084-64-8 0.1 μg/kg i

2,2’,3,4,4’,5’-Hexabromodiphenyl ether (PBDE138) 81576 64857 GM014 182677-30-1 0.1 μg/kg i

2,2’,4,4’,5,5’-Hexabromodiphenylether (PBDE 153) 81575 64858 GM014 68631-49-2 0.1 μg/kg i

2,2’,4,4’,5,6’-Hexabromodiphenyl ether (PBDE 154) 81574 64859 GM014 207122-15-4 0.1 μg/kg i

2,2’,3,4,4’,5’,6-Heptabromodiphenyl ether (PBDE 183) 81577 64860 GM014 207122-16-5 0.1 μg/kg i

Oxychlordane 81533 64866 GM014 27304-13-8 1 μg/kg i

 Pentabromotoluene 81554 64867 GM014 87-83-2 1 μg/kg irl

1,2-Bis(2,4,6-tribromophenoxy)ethane 81578 64868 GM014 37853-59-1 0.1 μg/kg i

Octachlorostyrene 81531 65217 GM014 29082-74-4 1 μg/kg i

 bis(Hexachlorocyclopentadieno) cyclooctane [Dechlorane 

Plus]

81583 65220 GM014 13560-89-9 1 μg/kg irl

PCB congener 202-13C12 (surrogate) 81581 90802 GM014 105600-26-8 N/A pct N

 Sample weight, grams 81582 91137 GM014 — N/A g N/A

4,4’-Dibromooctafluorobiphenyl (surrogate) 81579 91785 GM014 10386-84-2 N/A pct N

p,p’-DDT-d8 (surrogate) 81580 91828 GM014 — N/A pct N

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 77

Table 2.9. U.S. Geological Survey National Water Quality Laboratory Schedule 6434 for hormone compounds in bed sediment.

[Custom method derived from Foreman and others (2012). Parameter names are as shown in the U.S. Geological Survey (USGS) National Water Information 

System (NWIS) database and do not include special characters or formatting. Abbreviations: CAS, Chemical Abstracts Service1; g, gram; N/A, not applicable; 

irl, interim reporting level; MRL, minimum reporting level; pct, percent; μg/kg, microgram per kilogram; —, no data]

Parameter name

NWIS 

parameter 

code

NWIS 

method 

code

CAS number Reporting 

level Unit Reporting level type

11-Ketotestosterone 64467 GM006 564-35-2 0.52 μg/kg M

 16-Epiestriol-2,4-d2 (surrogate) 91684 GM006 366495-94-5 N/A pct

 17-alpha-Estradiol 64468 GM006 57-91-0 0.2 μg/kg irl

 17-alpha-Ethynylestradiol 63207 GM006 57-63-6 0.2 μg/kg irl

 17-alpha-Ethynylestradiol-2,4,16,16-d4 (surrogate) 91805 GM006 350820-06-3 N/A pct

 17-beta-Estradiol 63164 GM006 50-28-2 0.4 μg/kg irl

17-beta-Estradiol-13,14,15,16,17,18-13C6 (surrogate) 91757 GM006 — N/A p

 3-beta-Coprostanol 63170 GM006 360-68-9 50 μg/kg MRL

 4-Androstene-3,17-dione 64473 GM006 63-05-8 0.5 μg/kg irl

Bisphenol A 63188 GM006 80-05-7 20 μg/kg M

Bisphenol-A-d16 (surrogate) 67310 GM006 96210-87-6 N/A p

 Cholesterol 63196 GM006 57-88-5 120 μg/kg MRL

 Cholesterol-d7 (surrogate) 90772 GM006 83199-47-7 N/A pct

 cis-Androsterone 63607 GM006 53-41-8 0.5 μg/kg irl

 cis-Androsterone-2,2,3,4,4-d5 (surrogate) 91808 GM006 89685-22-3 N/A pct

 Dihydrotestosterone 64484 GM006 521-18-6 1 μg/kg irl

 Epitestosterone 64477 GM006 481-30-1 1 μg/kg irl

 Equilenin 63204 GM006 517-09-9 0.52 μg/kg irl

 Equilin 64479 GM006 474-86-2 4 μg/kg irl

 Estriol 64480 GM006 50-27-1 0.52 μg/kg irl

 Estriol-2,4,16,17-d4 (surrogate) 91617 GM006 — N/A pct

 Estrone 63205 GM006 53-16-7 0.5 μg/kg irl

Estrone-13,14,15,16,17,18-13C6 (surrogate) 91758 GM006 — N/A p

 Medroxyprogesterone-d3 (surrogate) 91686 GM006 162462-69-3 N/A pct

 Mestranol 63638 GM006 72-33-3 0.4 μg/kg irl

 Mestranol-2,4,16,16-d4 (surrogate) 91813 GM006 — N/A pct

 Nandrolone-16,16,17-d3 (surrogate) 91687 GM006 120813-22-1 N/A pct

 Norethindrone 63644 GM006 68-22-4 0.4 μg/kg irl

 Progesterone 63657 GM006 57-83-0 3 μg/kg irl

 Progesterone-2,3,4-13C3 (surrogate) 90512 GM006 327048-87-3 N/A pct

 Sample weight, grams 91116 GM006 — N/A g

 Testosterone 64485 GM006 58-22-0 0.4 μg/kg irl

 trans-Diethyl-1,1,1’,1’-d4-stilbesterol-3,3’,5,5’-d4 (surrogate) 91809 GM006 91318-10-4 N/A pct

 trans-Diethylstilbestrol 63620 GM006 56-53-1 0.33 μg/kg MRL

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78 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.10. U.S. Geological Survey National Water Quality Laboratory Schedule 1632 for chlorophyll a, pheophytin a, and ash-free dry 

mass in periphyton.

[NWQL, U.S. Geological Survey (USGS) National Water Quality Laboratory; NWIS, USGS National Water Information System; CAS, Chemical 

Abstracts Service1; g/m2, gram per square meter; mg/m2, milligram per square meter; mrl, minimum reporting level; lrl, laboratory reporting level; 

EPA, U.S. Environmental Protection Agency; —, no data]

Parameter name

NWQL 

lab 

code

NWIS 

parameter 

code

NWIS 

method 

code

CAS 

number

Reporting 

level Unit Reporting level type Method citation Method

Biomass, periphyton, ash free dr

weight

2751 49954 GRV15 — 0.1 g/m2 mrlBritton and Greeson

1987

 USGS 

Method 

B-3520-85

 Chlorophyll a 3153 70957 00050 479-61-8 0.1 mg/m2 lrl Arar and Collins, 

1997

 EPA 445.0

 Periphyton, biomass, ash weight611 00572 GRV15 — 0.1 g/m2 mrlBritton and Greeson

1987

 USGS 

Method 

B-3520-85

 Periphyton, biomass, dry weight603 00573 GRV15 — 0.1 g/m2 mrlBritton and Greeson

1987

 USGS 

Method 

B-3520-85

 Pheophytin a, periphyton

80253 62359 00050 603-17-8 0.1 mg/m2 lrl Arar and Collins, 

1997

 EPA 445.0

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms 79

Table 2.11. U.S. Geological Survey Organic Chemistry Research Laboratory Schedule for pesticides in sediment and biofilms.

[Method is described in Hladik and McWayne (2012). Abbreviations: NWIS, USGS National Water Information System; CAS, Chemical Abstracts Service1; 

g, gram; MDL, method detection level; μg/kg, microgram per kilogram; —, no data; na, not applicable]

Compound CAS number NWIS parameter code 

for bed sediment

MDL in sediment

(μg/kg)

MDL in biofilms 

(μg/kg) for 5 g 

sample

 2-Chloro-2,6-Diethylacetanilide 

(CDEPA)

6967-29-9 68876 1.3 1.3

 3,4-Dichloroaniline 95-76-1 66585 1.3 1.3

 3,5-Dichloroaniline 626-43-7 67538 1.5 1.5

 Alachlor 15972-60-8 04006 0.6 0.6

 Allethrin 584-79-2 66588 1.7 1.7

 Atrazine 1912-24-9 39631 1.5 1.5

 Azinphos-methyl 86-50-0 64150 1.7 1.7

 Azoxystrobin 131860-33-8 66591 0.9 0.9

Benfluralin (Benefin) 1861-40-1 68878 1.7 1

Bifenthrin 82657-04-3 64151 0.6 0

Boscalid 188425-85-6 67552 1.2 1

Butralin 33629-47-9 68880 1.6 1

Butylate 2008-41-5 64152 1.3 1

 Captan 133-06-2 68324 3.1 na

 Carbaryl 63-25-2 64153 1.2 1.2

 Carbofuran 1563-66-2 64154 1.2 1.2

 Chlorothalonil 1897-45-6 62904 1.1 na

 Chlorpyrifos 2921-88-2 81404 0.9 0.9

 Clomazone 81777-89-1 67564 2.0 2.0

 Coumaphos 56-72-4 68882 1.2 1.2

 Cycloate 1134-23-2 64155 0.8 0.8

Cyfluthrin 68359-37-5 65109 1.3 1

 Cyhalofop-butyl 122008-85-9 68884 0.8 0.8

 Cyhalothrin 68085-85-8 68356 0.7 0.7

 Cypermethrin 52315-07-8 64156 1.2 1.2

 Cyproconazole 94361-06-5 66595 1.0 na

 Cyprodinil 121522-61-2 67576 1.7 na

 DCPA (Dacthal) 1861-32-1 62905 1.7 1.7

 Deltamethrin 52918-63-5 65110 1.3 1.3

 Diazinon 333-41-5 39571 1.6 1.6

 Difenoconazole 119446-68-3 67584 1.0 na

 Dimethomorph 110488-70-5 68375 1.5 na

 Dithiopyr 97886-45-8 68886 1.3 1.3

 EPTC 759-94-4 64158 0.8 0.8

 Esfenvalerate 66230-04-4 64159 1.0 1.0

Ethalfluralin 55283-68-6 64160 1.2 1

 Etofenprox 80844-07-1 67606 1.0 1.0

 Famoxadone 131807-57-3 67611 1.7 na

 Fenarimol 60168-88-9 67615 1.4 na

 Fenbuconazole 114369-43-6 67620 1.8 na

 Fenhexamide 126833-17-8 67624 2.5 na

 Fenpropathrin 39515-41-8 65111 1.0 1.0

Appendix 2
80 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.11. U.S. Geological Survey Organic Chemistry Research Laboratory Schedule for pesticides in sediment and biofilms.—

Continued

[Method is described in Hladik and McWayne (2012). Abbreviations: NWIS, USGS National Water Information System; CAS, Chemical Abstracts Service1; 

g, gram; MDL, method detection level; μg/kg, microgram per kilogram; —, no data; na, not applicable]

Compound CAS number NWIS parameter code 

for bed sediment

MDL in sediment

(μg/kg)

MDL in biofilms 

(μg/kg) for 5 g 

sample

 Fenpyroximate 134098-61-6 68888 1.9 1.9

 Fenthion 55-38-9 62046 2.0 2.0

 Fipronil 120068-37-3 66606 1.6 1.6

Fipronil desulfinyl — 66609 1.8 1

Fipronil desulfinyl amide — 68891 2.0 2

Fipronil sulfide 120067-83-6 66612 1.5 1

 Fipronil sulfone 120068-36-2 66615 1.0 1.0

 Fluazinam 79622-59-6 67638 2.1 na

 Fludioxinil 131341-86-1 67642 2.5 2.5

 Flufenacet 142459-58-3 68893 1.0 1.0

 Flumetralin 62924-70-3 68895 1.2 1.2

 Fluoxastrobin 361377-29-9 67647 1.2 na

 Flusilazole 85509-19-9 67651 2.2 na

 Flutolanil 66332-96-5 68897 2.1 2.1

 Flutriafol 76674-21-0 67655 1.1 na

 Hexazinone 51235-04-2 64161 0.9 0.9

 Imazalil 35554-44-0 67664 1.8 na

 Indoxacarb 173584-44-6 68899 2.4 na

 Iprodione 36734-19-7 66618 0.9 0.9

Kresoxim-methyl 143390-89-0 67672 0.5 0

 Malathion 121-75-5 35931 1.0 1.0

 Metalaxyl 57837-19-1 68439 1.9 na

 Metconazole 125116-23-6 66622 1.2 1.2

 Methidathion 950-37-8 62047 1.8 1.8

 Methoprene 40596-69-8 66625 1.6 1.6

 Methyl parathion 298-00-0 39601 1.1 1.1

 Metolachlor 51218-45-2 04005 0.7 0.7

 Molinate 2212-67-1 64163 1.0 1.0

 Myclobutanil 88671-89-0 66634 1.7 1.7

 Napropamide 15299-99-7 64164 0.9 0.9

 Novaluron 116714-46-6 68901 1.1 1.1

Oxadiazon 19666-30-9 68903 1.4 1

Oxyfluorfen 42874-03-3 64165 1.9 1

 p,p’-DDD 72-54-8 39311 1.0 1.0

 p,p’-DDE 72-55-9 39321 1.0 1.0

 p,p’-DDT 50-29-3 39301 0.8 0.8

 Pebulate 1114-71-2 64166 0.9 na

 Pendimethalin 40487-42-1 64167 0.8 na

 Pentachloroanisole 1825-21-4 49460 1.1 1.1

 Pentachloronitrobenzene 82-68-8 49446 1.1 1.1

 Pebulate 1114-71-2 — na 0.9

 Pendimethalin 40487-42-1 — na 0.8
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 81

Table 2.11. U.S. Geological Survey Organic Chemistry Research Laboratory Schedule for pesticides in sediment and biofilms.—

Continued

[Method is described in Hladik and McWayne (2012). Abbreviations: NWIS, USGS National Water Information System; CAS, Chemical Abstracts Service1; 

g, gram; MDL, method detection level; μg/kg, microgram per kilogram; —, no data; na, not applicable]

Compound CAS number NWIS parameter code 

for bed sediment

MDL in sediment

(μg/kg)

MDL in biofilms 

(μg/kg) for 5 g 

sample

 Permethrin 52645-53-1 64168 0.9 0.9

 Phenothrin 26002-80-2 65112 0.9 0.9

 Phosmet 732-11-6 64169 0.9 0.9

 Piperonyl butoxide 51-03-6 64170 1.2 1.2

 Prodiamine 29091-21-2 68905 1.4 1.4

 Prometon 1610-18-0 82402 2.7 2.7

 Prometryn 7287-19-6 78688 1.3 1.3

 Propanil 709-98-8 66642 2.2 2.2

 Propargite 2312-35-8 68907 2.2 2.2

 Propiconazole 60207-90-1 66645 1.1 1.1

 Propyzamide (Pronamide) 23950-58-5 67708 1.5 1.5

 Pyraclostrobin 175013-18-0 66648 1.1 na

 Pyridaben 96489-71-3 68909 1.2 1.2

 Pyrimethanil 53112-28-0 67719 1.1 na

 Resmethrin 10453-86-8 65113 1.3 1.3

 Simazine 122-34-9 39046 1.3 1.3

tau-fluvalinate 69409-94-5 65114 1.2 1

 Tebuconazole 107534-96-3 66650 1.2 na

 Tebupirimfos — 68911 1.5 1.5

 Tebupirimfos oxon 96182-53-5 68913 2.0 na

Tefluthrin 79538-32-2 67733 0.7 0

 Tetraconazole 112281-77-3 66656 1.1 1.1

 Tetradifon 116-29-0 68915 2.0 2.0

 Tetramethrin 7696-12-0 66659 0.9 0.9

 Thiazopyr 117718-60-2 68917 1.9 1.9

 Thiobencarb 28249-77-6 64171 0.6 0.6

 Triadimefon 43121-43-3 67743 1.5 1.5

 Triadimenol 55219-65-3 67748 1.5 na

 Triallate 2303-17-5 68919 1.4 1.4

 Tribuphos 78-48-8 39050 2.2 2.2

Trifloxystrobin 141517-21-7 66662 1.0 1

Triflumizole 68694-11-1 67755 1.1 

Trifluralin 1582-09-8 62902 0.9 0

 Triticonazole 131983-72-7 67760 1.8 na

 Vinclozolin 50471-44-8 67765 1.2 1.2

 Zoxamide 156052-68-5 67770 1.1 1.1

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
82 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

 1H-1,2,4-Triazole ESI+ 11 288-88-0

 2-(1-Hydroxyethyl)-6-methylaniline (HEMA) ESI+ 47 196611-19-5

 2-(2-Ethyl-6-methyl-phenyl)aminopropan-1-ol ESI+ 2 61520-53-4

 2,4-D ESI– 31 94-75-7

 2-Aminobenzimidazole ESI+ 4 934-32-7

 2-Amino-N-isopropylbenzamide ESI+ 2 30391-89-0

 2-Chloro-N-(2-ethyl-6-methylphenyl)acetamide ESI+ 2 32428-71-0

 2-Hydroxy-4-isopropylamino-6-amino-s-triazine ESI+ 2 19988-24-0

 2-Hydroxy-6-ethylamino-4-amino-s-triazine ESI+ 3 7313-54-4

 2-Hydroxyatrazine ESI+ 4 2163-68-0

 3,4-Dichlorophenylurea ESI+ 72 2327-02-8

 3-Hydroxycarbofuran ESI+ 8 16655-82-6

 3-Phenoxybenzoic acid ESI– 30 3739-38-6

 4-(Hydroxymethyl)pendimethalin ESI– 106 56750-76-6

 4-Chlorobenzylmethyl sulfoxide ESI+ 2 24176-68-9

 4-Hydroxy molinate ESI+ 3 66747-12-4

 4-Hydroxychlorothalonil ESI– 49 28343-61-5

 4-Hydroxyhexazinone A ESI+ 1 72576-13-7

4-Hydroxy-tert-fluometuron ESI+ 10

 Acephate ESI+ 5 30560-19-1

 Acetochlor ESI+ 5 34256-82-1

Acetochlor OA ESI– 45 194992-44

 Acetochlor SA ESI– 50 187022-11-3

 Acetochlor SAA ESI– 88 618113-86-3

 Alachlor ESI+ 6 15972-60-8

Alachlor OA ESI– 42 171262-17

 Alachlor SA ESI– 140 142363-53-9

 Alachlor SAA ESI– 84 494847-39-1

 Aldicarb ESI+ 4 116-06-3

 Aldicarb sulfone ESI+ 10 1646-88-4

 Aldicarb sulfoxide ESI+ 1 1646-87-3

 Ametryn ESI+ 1 834-12-8

 Asulam ESI+ 59 3337-71-1

 Atrazine ESI+ 2 1912-24-9

 Azinphos-methyl ESI+ 4 86-50-0

 Azinphos-methyl oxon ESI+ 7 961-22-8

 Azoxystrobin ESI+ 1 131860-33-8

Bentazone ESI– 11 25057-89

Bifenthrin ESI+ 250 82657-04

Bromacil ESI+ 3 314-40

Bromoxynil ESI– 39 1689-84
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 83

Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.—Continued

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

Butralin ESI+ 4 33629-47

Butylate ESI+ 3 2008-41

 Carbaryl ESI+ 3 63-25-2

 Carbendazim ESI+ 1 10605-21-7

 Carbofuran ESI+ 2 1563-66-2

 Carboxy molinate ESI+ 11 66747-13-5

 Chlorimuron-ethyl ESI+ 4 90982-32-4

 Chlorosulfonamide acid ESI– 37 130-45-0

 Chlorpyrifos ESI+ 25 2921-88-2

 Chlorpyrifos oxon ESI+ 2 5598-15-2

 Chlorsulfuron ESI+ 25 64902-72-3

 cis-Permethrin ESI+ 100 61949-76-6

 Cyanazine ESI+ 25 21725-46-2

 Dacthal monoacid ESI– 250 887-54-7

Dechlorofipronil ESI– 3

 Dechlorometolachlor ESI+ 10,000 126605-22-9

 Deethylatrazine ESI+ 5 6190-65-4

Deiodo flubendiamide ESI+ 4 1016160-78

 Deisopropyl prometryn ESI+ 1 4147-57-3

 Deisopropylatrazine ESI+ 10 1007-28-9

Demethyl hexazinone B ESI+ 1 56611-54

Demethyl norflurazon ESI+ 2 23576-24

Desulfinylfipronil ESI– 7 205650-65

Desulfinylfipronil Amide ESI– 8 1115248-09

 Diazinon ESI+ 2 333-41-5

 Diazinon oxon ESI+ 1 962-58-3

 Dicamba ESI– 250 1918-00-9

 Dichlorvos ESI+ 26 62-73-7

 Dicrotophos ESI+ 2 141-66-2

 Didealkylatrazine ESI+ 25 3397-62-4

Diflubenzuron ESI+ 5 35367-38

Diflufenzopyr ESI– 44 109293-97

Diketonitrile isoxaflutole ESI– 31 143701-75

 Dimethachlor SA ESI– 10

 Dimethenamid ESI+ 1 87674-68-8

Dimethenamid OA ESI– 42 380412-59

 Dimethenamid SA ESI– 39 205939-58-8

 Dimethenamid SAA ESI– 94 —

 Dimethoate ESI+ 1 60-51-5

 Dimethoate oxon ESI+ 1 1113-02-6

 Disulfoton ESI+ 12 298-04-4
84 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.—Continued

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

 Disulfoton oxon ESI+ 1 126-75-0

 Disulfoton oxon sulfone ESI+ 3 2496-91-5

 Disulfoton oxon sulfoxide ESI+ 100 2496-92-6

 Disulfoton sulfone ESI+ 4 2497-06-5

 Disulfoton sulfoxide ESI+ 2 2497-07-6

 Diuron ESI+ 2 330-54-1

 EPTC ESI+ 103 759-94-4

EPTC R248722 ESI+ 2 65109-69

 Ethoprop ESI+ 2 13194-48-4

 Etoxazole ESI+ 3 153233-91-1

 Famoxadone ESI+ 150 131807-57-3

 Fenamiphos ESI+ 1 22224-92-6

 Fenamiphos sulfone ESI+ 2 31972-44-8

 Fenamiphos sulfoxide ESI+ 2 31972-43-7

 Fenbutatin oxide ESI+ 100 13356-08-6

 Fentin ESI+ 8 668-34-8

 Fipronil ESI– 8 120068-37-3

 Fipronil amide ESI– 8 205650-69-7

Fipronil sulfide ESI– 9 120067-83

 Fipronil sulfonate ESI– 48 209248-72-6

 Fipronil sulfone ESI– 8 120068-36-2

 Flubendiamide ESI– 8 272451-65-7

 Flumetsulam ESI+ 8 98967-40-9

 Fluometuron ESI+ 1 2164-17-2

 Fonofos ESI+ 5 944-22-9

 Halosulfuron-methyl ESI+ 11 100784-20-1

 Hexazinone ESI+ 1 51235-04-2

 Hexazinone TP C ESI+ 1 72585-88-7

 Hexazinone TP D ESI– 100 30243-77-7

 Hexazinone TP E ESI– 38 72576-14-8

 Hexazinone TP F ESI+ 38 56611-55-3

 Hexazinone TP G ESI+ 11 —

Hydroxy mono demethyl fluometuron ESI+ 5

 Hydroxyalachlor ESI+ 6 56681-55-1

 Hydroxydiazinon ESI+ 5 29820-16-4

Hydroxyfluometuron ESI+ 4

 Hydroxyphthalazinone ESI+ 40 —

 Hydroxysimazine ESI+ 3 2599-11-3

 Hydroxytebuthiurion ESI+ 25 59962-54-8

 Imazamox ESI+ 14 114311-32-9

 Imazaquin ESI+ 9 81335-37-7
Appendix 2 Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Bed Sediment, and Biofilms Appendix 2 85

Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.—Continued

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

 Imazethapyr ESI+ 10 81335-77-5

 Imidacloprid ESI+ 5 138261-41-3

 Indoxacarb ESI+ 12 173584-44-6

Isoxaflutole ESI+ 15 141112-29

Isoxaflutole acid RPA 203328 ESI– 6 142994-06

Kresoxim-methyl ESI+ 4 143390-89

 Lactofen ESI+ 10 77501-63-4

 Linuron ESI+ 3 330-55-2

 Malaoxon ESI+ 1 1634-78-2

 Malathion ESI+ 2 121-75-5

 MCPA ESI– 48 94-74-6

 Metalaxyl ESI+ 3 57837-19-1

 Metconazole ESI+ 2 125116-23-6

 Methamidophos ESI+ 3 10265-92-6

 Methidathion ESI+ 5 950-37-8

 Methomyl ESI+ 2 16752-77-5

 Methomyl oxime ESI+ 250 13749-94-5

 Methoxyfenozide ESI+ 1 161050-58-4

 Metolachlor ESI+ 4 51218-45-2

 Metolachlor hydroxy morpholinone ESI+ 14 61520-54-5

Metolachlor OA ESI– 74 152019-73

 Metolachlor SA ESI– 40 171118-09-5

 Metribuzin ESI+ 10 21087-64-9

 Metribuzin DA ESI+ 4 35045-02-4

Metribuzin DADK ESI– 100 52236-30

Metribuzin DK ESI– 140 56507-37

 Molinate ESI+ 9 2212-67-1

 Myclobutanil ESI+ 5 88671-89-0

 N-(3,4-Dichlorophenyl)-N-methylurea ESI+ 5 3567-62-2

 Naled ESI+ 15 300-76-5

 Nicosulfuron ESI+ 7 111991-09-4

Norflurazon ESI+ 3 27314-13

 Novaluron ESI+ 50 116714-46-6

O-Ethyl-O-methyl-S-propyl phosphorothioate ESI+ 2 76960-87

Orthosulfamuron ESI+ 3 213464-77

Oryzalin ESI– 5 19044-88

Oxamyl ESI+ 1 23135-22

Oxamyl oxime ESI+ 3 30558-43

Oxyfluorfen ESI+ 500 42874-03

 Paraoxon ESI+ 2 311-45-5

 Paraoxon-methyl ESI+ 12 950-35-6
86 Design and Methods of the California Stream Quality Assessment, 2017

Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.—Continued

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

 Parathion-methyl ESI+ 250 298-00-0

 Pendimethalin ESI+ 3 40487-42-1

 Phorate ESI+ 3 298-02-2

 Phorate oxon ESI+ 2 2600-69-3

 Phorate oxon sulfone ESI+ 10 2588-06-9

 Phorate oxon sulfoxide ESI+ 3 2588-05-8

 Phorate sulfone ESI+ 4 2588-04-7

 Phorate sulfoxide ESI+ 2 2588-03-6

 Phosmet ESI+ 10,000 732-11-6

 Phthalazinone ESI+ 6 90004-07-2

 Piperonyl butoxide ESI+ 2 51-03-6

 Profenofos ESI+ 1 41198-08-7

 Prometon ESI+ 2 1610-18-0

 Prometryn ESI+ 1 7287-19-6

 Pronamide ESI+ 2 23950-58-5

 Propanil ESI+ 5 709-98-8

 Propargite ESI+ 2 2312-35-8

 Propazine ESI+ 2 139-40-2

 Propiconazole ESI+ 3 60207-90-1

 Propoxur ESI+ 2 114-26-1

 Prosulfuron ESI+ 5 94125-34-5

 Pymetrozine ESI+ 1 123312-89-0

 Pyraclostrobin ESI+ 1 175013-18-0

 Pyridaben ESI+ 2 96489-71-3

 Pyrimidinol ESI+ 10,000 2814-20-2

 Pyriproxyfen ESI+ 2 95737-68-1

sec-Alachlor-OA ESI– 68 628324-79

 Siduron ESI+ 2 1982-49-6

 Simazine ESI+ 5 122-34-9

 Sulfentrazone ESI– 25 122836-35-5

 Sulfometuron-methyl ESI+ 2 74222-97-2

 Sulfosulfuron ESI+ 25 141776-32-1

 Sulfosulfuron ethyl sulfone ESI+ 1 —

 Tebuconazole ESI+ 2 107534-96-3

 Tebufenozide ESI+ 1 112410-23-8

 Tebupirimfos ESI+ 1 96182-53-5

 Tebupirimfos oxon ESI+ 1 —

 Tebuthiuron ESI+ 1 34014-18-1

 Tebuthiuron TP 104 ESI+ 3 59962-53-7

 Tebuthiuron TP 106 ESI+ 40 16279-27-9

Tebuthiuron TP 108 ESI+ 5 39222-73
References Cited Appendix 2 87

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Table 2.12. U.S. Environmental Protection Agency Laboratory Schedule for pesticides in filtered water from small-volume pesticide 

autosamplers.—Continued

[EPA, U.S. Environmental Protection Agency; CAS, Chemical Abstracts Service1; ESI+, positive electrospray ionization mode; ESI–, negative electrospray 

ionization mode; MDL, method detection level; ng/L, nanograms per liter; —, no data]

EPA parameter name Method MDL

(ng/L) CAS number

Tebuthiuron TP 109 (OH) ESI+ 13 139888-73

 Terbacil ESI+ 15 5902-51-2

 Terbufos ESI+ 4 13071-79-9

 Terbufos oxon ESI+ 2 56070-14-5

 Terbufos oxon sulfone ESI+ 5 56070-15-6

 Terbufos oxon sulfoxide ESI+ 2 56165-57-2

 Terbufos sulfone ESI+ 5 56070-16-7

 Terbufos sulfoxide ESI+ 1 10548-10-4

 Terbuthylazine ESI+ 1 5915-41-3

 Tetraconazole ESI+ 5 112281-77-3

 Thiobencarb ESI+ 2 28249-77-6

 trans-Permethrin ESI+ 100 61949-77-7

 Triallate ESI+ 10 2303-17-5

 Triallate SA ESI– 27 65600-62-6

 Tribuphos ESI+ 5 78-48-8

 Triclopyr ESI– 44 55335-06-3

Trifloxystrobin ESI+ 1 141517-21

1This report contains CAS Registry Numbers®, which is a Registered Trademark of the American Chemical Society. CAS recommends the verification of the 

CAS Registry Numbers through CAS Client ServicesSM.
88 Design and Methods of the California Stream Quality Assessment, 2017

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For more information concerning the research in this report, contact the

 Director, California Water Science Center

U.S. Geological Survey

6000 J Street, Placer Hall

Sacramento, California 95819

https://ca.water.usgs.gov

Publishing support provided by the U.S. Geological Survey 

Science Publishing Network, Sacramento Publishing Service Center
May and others—Design and Methods of the California Stream Quality Assessment (CSQA), 2017—Open-File Report 2020–1023

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201023