U.S. Department of the Interior

U.S. Geological Survey

Data Series 1087 

Groundwater-Quality and Select Quality-Control Data from 

the National Water-Quality Assessment Project, January 

through December 2015, and Previously Unpublished Data 

from 2013 to 2014

WASHINGTON

IDAHO

MONTANA

OREGON

NORTH

DAKOTA MINNESOTA MAINE

WISCONSIN

CALIFORNIA

WYOMING

SOUTH

DAKOTA

NEW HAMPSHIRE

VERMONT

NEW YORK

NEVADA

UTAH

NEBRASKA

IOWA

PENNSYLVANIA

COLORADO

ILLINOIS

RHODE

ISLAND

OHIO

MICHIGAN

MI

NEW JERSERY

INDIANA

WEST VIRGINIA

MISSOURI

KANSAS

MARYLAND

DELAWARE

VIRGINIA

ARIZONA

KENTUCKY

NEW

MEXICO OKLAHOMA

TEXAS

NORTH

CAROLINA

ARKANSAS TENNESSEE

SOUTH CAROLINA

GEORGIA

FLORIDA

ALABAMA

MISSISSIPPI

LOUISIANNA

CONNECTICUT

MASSACHUSETTS

C A N A D A

M E X I C O

GULF OF MEXICO

ATLANTIC OCEAN

PACIFIC OCEAN

EXPLANATION

Principal aquifer study boundary

Sampled well, color indicates network type

Enhanced trends network

Major aquifer study

Land-use study

Principal aquifer study

Vertical flow-path study

125° 120° 115° 110° 105° 100° 95° 90° 85° 80° 75° 70° 65°

45°

40°

35°

30°

25°
Cover graphic. Groundwater study networks and wells sampled as part of the U.S. Geological Survey 

National Water-Quality Assessment Project from July through August 2013 and January through 

December 2015 for which water-quality data are included in this report.
Groundwater-Quality and Select QualityControl Data from the National WaterQuality Assessment Project, January 

through December 2015, and Previously 

Unpublished Data from 2013 to 2014

By Terri L. Arnold, Laura M. Bexfield, MaryLynn Musgrove, Paul E. Stackelberg, 

Bruce D. Lindsey, James A. Kingsbury, Justin T. Kulongoski, and Kenneth Belitz

Data Series 1087 

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

RYAN K. ZINKE, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2018

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

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For an overview of USGS information products, including maps, imagery, and publications, 

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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:

Arnold, T.L., Bexfield, L.M., Musgrove, M., Stackelberg, P.E., Lindsey, B.D., Kingsbury, J.A., Kulongoski, J.T., and Belitz, 

K., 2018, Groundwater-quality and select quality-control data from the National Water-Quality Assessment Project, 

January through December 2015, and previously unpublished data from 2013 to 2014: U.S. Geological Survey Data 

Series 1087, 68 p., https://doi.org/10.3133/ds1087.

ISSN 2327-638X (online)
iii

Foreword

Sustaining the quality of the Nation’s water resources and the health of our diverse ecosystems 

depends on the availability of sound water-resources data and information to develop effective, 

science-based policies. Effective management of water resources also brings more certainty and 

efficiency to important economic sectors. Taken together, these actions lead to immediate and 

long-term economic, social, and environmental benefits that make a difference to the lives of 

the almost 400 million people projected to live in the United States by 2050.

In 1991, Congress established the National Water-Quality Assessment (NAWQA) to address 

where, when, why, and how the Nation’s water quality has changed, or is likely to change in 

the future, in response to human activities and natural factors. Since then, NAWQA has been 

a leading source of scientific data and knowledge used by national, regional, state, and local 

agencies to develop science-based policies and management strategies to improve and protect 

water resources used for drinking water, recreation, irrigation, energy development, and ecosystem needs (https://water.usgs.gov/nawqa/applications/). Plans for the third decade of NAWQA 

(2013–23) address priority water-quality issues and science needs identified by NAWQA 

stakeholders, such as the Advisory Committee on Water Information and the National Research 

Council, and are designed to meet increasing challenges related to population growth, increasing needs for clean water, and changing land-use and weather patterns.

NAWQA is assessing the quality of groundwater used for public and domestic drinking-water 

supply. NAWQA obtains samples from public supply wells, domestic wells, and relatively shallow monitoring wells, and analyzes those samples for a large number of chemical constituents. 

These data are used to assess the suitability of the resource for human consumption, as well as 

to evaluate changes in groundwater quality over a variety of time scales. Groundwater quality 

also is assessed at multiple scales: locally, regionally, and nationally. Groundwater-quality data 

collected by the NAWQA Project during each year are published in annual data series reports. 

This report, the third in the series, combines groundwater-quality data collected at 502 sites 

to provide a summary of groundwater quality in selected aquifers across the Nation during the 

sampling period. All NAWQA reports are available online at https://water.usgs.gov/nawqa/bib/.

We hope this publication will provide you with insights and information to meet your waterresource needs and will foster increased citizen awareness and involvement in the protection 

and restoration of our Nation’s waters. The information in this report is intended primarily for 

those interested or involved in resource management and protection, conservation, regulation, 

and policymaking at the regional and national levels.

Dr. Donald W. Cline

Associate Director for Water

U.S. Geological Survey

v

Contents

Foreword ........................................................................................................................................................iii

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

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

Purpose and Scope .......................................................................................................................................2

Groundwater Study Design..........................................................................................................................2

Principal Aquifer Study Networks .....................................................................................................2

Basin and Range Carbonate-Rock Aquifers Principal Aquifer Study Network

(bnrcpas1)........................................................................................................................2

Floridan Aquifer System Principal Aquifer Study Network (florpas1) ................................9

High Plains Aquifer Principal Aquifer Study Network (hpaqpas1)....................................10

Mississippi Embayment-Texas Coastal Uplands Aquifer Systems Principal 

Aquifer Study Network (metxpas1) ...........................................................................10

Rio Grande Aquifer System Principal Aquifer Study Network (rgaqpas1).......................10

Decadal Trends Networks—Land-Use Study Networks .............................................................11

Central Columbia Plateau Agricultural Land-Use Study Network (ccptlusor1b)............11

Central Nebraska Basins Agricultural Land-Use Study Network (cnbrluscr1)...............11

Georgia-Florida Coastal Plain Drainages Agricultural Land-Use Study Network

(gaflluscr1).....................................................................................................................19

Lower Illinois River Basin Urban Land-Use Study Network (lirblusrc1)...........................19

Potomac River Basin and Delmarva Peninsula Urban Land-Use Study Network

(podllusrc1)....................................................................................................................19

San Joaquin-Tulare River Basins Agricultural Land-Use Study Network

(sanjluscr1a)..................................................................................................................19

Trinity River Basin Urban Land-Use Study Network (trinlusrc1)........................................19

Decadal Trends Networks—Major Aquifer Study Networks......................................................20

Apalachicola-Chattahoochee-Flint River Basins Major Aquifer Study Network

(acfbsus1) ......................................................................................................................20

San Joaquin-Tulare River Basins Major Aquifer Study Network (sanjsus1)...................20

Western Lake Michigan Drainages Major Aquifer Study Network (wmicsus1).............20

Enhanced Trends Networks..............................................................................................................20

Central Valley Enhanced Trends Network (cvaletn1) ..........................................................26

Columbia Plateau Enhanced Trends Network (clptetn1) ....................................................26

Edwards-Trinity Aquifer System Enhanced Trends Network (edtretn1)...........................26

Glacial Aquifer System Enhanced Trends Network (glacetn1)..........................................26

Mississippi Embayment Aquifer System Enhanced Trends Network (metxetn1)...........27

Northern Atlantic Coastal Plain Enhanced Trends Network (nacpetn1)..........................27

New England Crystalline-Rock and Glacial Aquifer System Enhanced Trends

Network (negxetn1) .....................................................................................................27

Rio Grande Aquifer System Enhanced Trends Network (rgaqetn1)..................................27

Vertical Flow-Path Study Networks.................................................................................................27

High Plains Aquifer Vertical Flow-Path Study Network (hpaqvfps1)................................28

Sample Collection and Analysis................................................................................................................28

Data Reporting..............................................................................................................................................28

Quality-Assurance and Quality-Control Methods ..................................................................................31
vi

Groundwater-Quality Data .........................................................................................................................31

Water-Quality Indicators ...................................................................................................................32

Inorganic Constituents.......................................................................................................................32

Organic Compounds...........................................................................................................................32

Radiochemistry....................................................................................................................................33

Constituents of Special Interest.......................................................................................................33

Summary........................................................................................................................................................33

Acknowledgments.......................................................................................................................................33

References Cited..........................................................................................................................................34

Appendix 1. Well Depth and Open Interval by Study Network .........................................................60

Appendix 2. High-Frequency Data from Enhanced Trends Networks.............................................62

Reference Cited............................................................................................................................................62

Appendix 3. Quality-Control Data and Analysis ..................................................................................63

Samples................................................................................................................................................63

Blank Sample Approach....................................................................................................................63

Blank Sample Counts .........................................................................................................................63

Constituent Concentrations in Blank Samples ..............................................................................65

References Cited..........................................................................................................................................66

Figures

1. Map showing groundwater study networks and wells sampled as part of the U.S.

Geological Survey National Water-Quality Assessment Project from July through

August 2013 and January through December 2015 for which water-quality data are

included in this report..................................................................................................................3

2. Map showing study area and wells sampled as part of the Basin and Range

Carbonate-Rock aquifers principal aquifer study network for the U.S. Geological

Survey National Water-Quality Assessment Project, July through August 2013 and

March through September 2015.................................................................................................4

3. Map showing study area and wells sampled as part of the Floridan aquifer system

principal aquifer study network for the U.S. Geological Survey National

Water-Quality Assessment Project, March through August 2015........................................5

4. Map showing study area and wells sampled as part of the High Plains aquifer

system principal aquifer study network for the U.S. Geological Survey National

Water-Quality Assessment Project, March through September 2015.................................6

5. Map showing study area and wells sampled as part of the Mississippi

Embayment-Texas Coastal Uplands aquifer system principal aquifer study network

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

through September 2015..............................................................................................................7

6. Map showing study area and wells sampled as part of the Rio Grande aquifer

system principal aquifer study network for the U.S. Geological Survey National

Water-Quality Assessment Project, May through September 2015.....................................8

7. Map showing study area and wells sampled as part of the Central Columbia

Plateau agricultural land-use study network for the U.S. Geological Survey

National Water-Quality Assessment Project, August through October 2015...................12

8. Map showing study area and wells sampled as part of the Central Nebraska

Basins agricultural land-use study network for the U.S. Geological Survey 

National Water-Quality Assessment Project, April through June 2015............................13
vii

9. Map showing study area and wells sampled as part of the Georgia-Florida Coastal

Plain drainages agricultural land-use study network for the U.S. Geological Survey

National Water-Quality Assessment Project, May 2015 ......................................................14

10. Map showing study area and wells sampled as part of the lower Illinois River Basin

urban land-use study network near St. Louis, Missouri, for the U.S. Geological

Survey National Water-Quality Assessment Project, July through August 2015 ............15

11. Map showing study area and wells sampled as part of the Potomac River Basin

and Delmarva Peninsula urban land-use study network near Washington, D.C., for

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

through August 2015...................................................................................................................16

12. Map showing study area and wells sampled as part of the San Joaquin-Tulare

River Basins agricultural land-use study network for the U.S. Geological Survey

National Water-Quality Assessment Project, July through August 2015..........................17

13. Map showing study area and wells sampled as part of the Trinity River Basin urban

land-use study network near Houston, Texas, for the U.S. Geological Survey

National Water-Quality Assessment Project, January through April 2015.......................18

14. Map showing study area and wells sampled as part of the ApalachicolaChattahoochee-Flint River Basins major aquifer study network for the 

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

August 2015..................................................................................................................................21

15. Map showing study area and wells sampled as part of the San Joaquin-Tulare

River Basins major aquifer study network for the U.S. Geological Survey National

Water-Quality Assessment Project, July through August 2015 ..........................................22

16. Map showing study area and wells sampled as part of the western Lake Michigan

drainages major aquifer study network for the U.S. Geological Survey National

Water-Quality Assessment Project, July through September 2015 ...................................23

17. Map showing study areas and wells sampled in the western United States as part

of the enhanced trends networks for the U.S. Geological Survey National

Water-Quality Assessment Project, January through December 2015.............................24

18. Map showing study areas and wells sampled in the eastern United States as part

of the enhanced trends networks for the U.S. Geological Survey National

Water-Quality Assessment Project, January through December 2015.............................25

19. Map showing study and wells sampled as part of the High Plains aquifer vertical

flow-path study network for the U.S. Geological Survey National Water-Quality

Assessment Project, April through August 2015 ...................................................................29

Tables

1. Information about wells that have environmental data included in this report...............40

1.1. Well depth by study network ....................................................................................................60

1.2. Length of open interval by study network ..............................................................................61

2.1. Web links to data collected at a high-frequency from enhanced trends networks........62

3.1. Summary of results for field blanks collected by the National Water-Quality 

Assessment Project from January 2015 to December 2015 ................................................64

3.2. Summary of results for field blanks collected by the National Water-Quality

Assessment Project from May 2012 to December 2015.......................................................64
viii

Conversion Factors

U.S. customary units to International System of Units (SI)

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 2.590 square kilometer (km2) 

Volume

teaspoon (tsp) 4928.82 microliter (mcL)

ounce, fluid (fl. oz) 29.5735 milliliter (ml)

Flow rate

million gallons per day (Mgal/d) 0.04381 cubic meter per second (m3

/s)

billion gallons per day (Bgal/d) 43.81 cubic meter per second (m3

/s)

Radioactivity

picocurie per liter (pCi/L) 0.037 becquerel per liter (Bq/L) 

Datum

Vertical coordinate information is referenced to either the North American Vertical Datum of 

1988 (NAVD 88) or the National Geodetic Vertical Datum of 1929 (NGVD 29) and is specified in 

tables where vertical datum is reported.

Altitude, as used in this report, refers to distance above the vertical datum.

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 in either milligrams per liter (mg/L), 

micrograms per liter (μg/L), or nanograms per liter (ng/L).

Activities for radioactive constituents in water are given in picocuries per liter (pCi/L).
ix

This report contains Chemical Abstracts Service (CAS) Registry Numbers®, which are 

registered trademarks of the American Chemical Society. The CAS recommends the verification 

of the CAS Registry Numbers through CAS Client ServicesSM.

Abbreviations

ASCII American Standard Code for Information Interchange

EPA U.S. Environmental Protection Agency

ETN enhanced trends network

HHB human-health benchmark

HHBP human-health benchmark for pesticides

ID identification

LRL laboratory reporting level

LT–MDL long-term method detection level

LUS land-use study

MAS major aquifer study

MDL method detection level

NAWQA National Water-Quality Assessment

NWQL National Water Quality Laboratory

PAS principal aquifer study

QC quality control

ssLc sample-specific critical level

ssMDC sample-specific minimum detectable concentration

USGS U.S. Geological Survey

VFPS vertical flow-path study

VOC volatile organic compound 

Groundwater-Quality and Select Quality-Control Data 

from the National Water-Quality Assessment Project, 

January through December 2015, and Previously 

Unpublished Data from 2013 to 2014

By Terri L. Arnold, Laura M. Bexfield, MaryLynn Musgrove, Paul E. Stackelberg, Bruce D. Lindsey, James A. 

Kingsbury, Justin T. Kulongoski, and Kenneth Belitz

Abstract

Groundwater-quality data were collected from 502 wells 

as part of the National Water-Quality Assessment Project of 

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

and are included in this report. Most of the wells (500) were 

sampled from January through December 2015, and 2 of them 

were sampled in 2013. The data were collected from five types 

of well networks: principal aquifer study networks, which 

are used to assess the quality of groundwater used for public 

water supply; land-use study networks, which are used to 

assess land-use effects on shallow groundwater quality; major 

aquifer study networks, which are used to assess the quality 

of groundwater used for domestic supply; enhanced trends 

networks, which are used to evaluate the time scales during 

which groundwater quality changes; and vertical flow-path 

study networks, which are used to evaluate changes in groundwater quality from shallow to deeper depths. Groundwater 

samples were analyzed for a large number of water-quality 

indicators and constituents, including major ions, nutrients, 

trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic 

speciation, chromium [VI], and perchlorate). These groundwater-quality data, along with data from quality-control samples, 

are tabulated in this report and in an associated data release. 

Some data from environmental samples collected in 2013 and 

quality-control samples collected in 2014 also are included 

in the associated data release; these data are associated with 

networks described in this report and have not been published 

previously.

Introduction

The National Water-Quality Assessment (NAWQA) 

Project of the U.S. Geological Survey (USGS) National WaterQuality Project was fully implemented in 1991 and operates 

in about 10-year long cycles. The NAWQA Project began 

its third cycle of studies in 2013. The NAWQA Project was 

designed to describe current water-quality conditions of the 

Nation’s freshwater streams, rivers, and aquifers; to describe 

how water quality is changing with time; to improve understanding of the natural and human factors that affect water 

quality; to forecast future water-quality conditions; and to 

assess effects of water-quality stressors on aquatic ecosystems 

(Rowe and others, 2010, 2013).

The NAWQA Project groundwater assessments focus 

on the quality of groundwater used for public and domestic 

drinking-water supply; groundwater susceptibility to degradation; effects of natural and human factors on source, transport, 

and flux of contaminants to and within aquifers; groundwaterquality contributions to surface-water quality; and current and 

historic management practices relative to groundwater quality. 

Groundwater quality is studied at multiple scales: locally, 

regionally, and nationally. The primary regional scale at which 

groundwater data are collected during the third cycle of the 

NAWQA Project is the scale of the principal aquifers (Burow 

and Belitz, 2014). A principal aquifer is defined as a regionally extensive aquifer or aquifer system that has the potential 

to be used as a source of potable water. Principal aquifers 

were selected for assessment based on their national ranking 

as sources of water used for public supply (Arnold and others, 

2016a). 

Groundwater-quality data collected by the NAWQA 

Project during each year are published in data series reports. 

The first two reports and associated data releases in this 

series published available data from samples collected May 

2012 through December 2013 (Arnold and others, 2016a, b) 

and January through December 2014 (Arnold and others, 

2017a, b). 
2 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Purpose and Scope

The purpose of this report is to present the analytical results of the groundwater-quality samples collected in 

2015 as part of the third cycle of NAWQA Project studies 

and to provide brief descriptions of the groundwater-quality 

study networks for use in subsequent publications. Types of 

constituents analyzed include the following: water-quality 

indicators, major and minor ions, nutrients, volatile organic 

compounds (VOCs), pesticides, radionuclides, and select 

constituents of special interest (arsenic speciation, chromium 

[VI], and perchlorate). The water-quality data are presented 

in tables formatted as tab-delimited American Standard Code 

for Information Interchange (ASCII) text files, which may be 

imported into spreadsheet, database, or statistical software for 

manipulation and analysis. These water-quality data tables 

are available from a data release, Arnold and others (2018), at 

https://doi.org/10.5066/F7XK8DHK. The data release includes 

data collected during 2015 and previously unpublished data 

from a few environmental samples collected in 2013 and a few 

quality-control (QC) samples collected in 2014. These previously unpublished data are associated with networks described 

in this report.

Groundwater Study Design

Groundwater-quality samples were collected from wells 

that were organized into networks (fig. 1) for study purposes. 

A network is a group of wells that have been selected for sampling based on specific hydrogeologic conditions, land use, 

or other design criteria. Many networks have wells that were 

sampled in multiple decadal sampling periods; however, if a 

network well was damaged or destroyed, had too little water, 

or the current owner would not permit sampling, then that 

well was not resampled during 2015. Maps and tables in this 

report and in Arnold and others (2018) have well identification 

(ID) numbers assigned by the NAWQA Project to identify the 

wells; because some wells could not be resampled, some networks do not have consecutively numbered NAWQA Project 

IDs. As used on maps showing network-specific information 

(figs. 2–19), the ID numbers are shown either as numbers 

only or a combination of numbers and letters that indicate a 

particular well within the network. The NAWQA well identification number listed in table 1 of this report (provided before 

the appendixes) and table 1 of Arnold and others (2018) are 

a combination of the network name and the NAWQA Project ID. Data from five primary types of groundwater study 

networks are presented in this report (fig. 1): principal aquifer 

study (PAS), land-use study (LUS), major aquifer study 

(MAS), enhanced trends networks (ETN), and vertical flowpath study (VFPS).

Wells in PAS, LUS, and MAS networks were selected 

randomly using an equal-area grid to divide the study area 

of each network (Scott, 1990). The equal-area grid method 

allows for evaluation of constituent concentrations at a 

regional scale (Belitz and others, 2010). For LUS networks, 

random potential sampling locations in each grid cell were 

generated by a software program (Scott, 1990), and monitoring wells were subsequently installed as near to the randomly 

selected locations as possible. Study areas for LUS networks 

included the areal extents of the primary aquifer and a specific 

land use (for example, orchard) of interest. For MAS and PAS 

networks, one well per grid cell was randomly selected from 

a population of existing domestic or public-supply wells (Gilliom and others, 1995; Scott, 1990). For PAS networks, if no 

public-supply well was available within a grid cell (for example, because permission to sample could not be obtained), an 

additional well was selected within an adjacent grid cell, not to 

exceed four wells in two adjacent grid cells. Equal-area grids 

used for network design are shown only on figures relating 

to PAS networks because the grids are not available for LUS 

or MAS networks designed during the first two decades of 

sampling.

The ETN and VFPS wells were selected from existing 

networks where possible. The ETN wells are in hydrogeologic 

settings where changes in hydrologic conditions, land use, 

or contaminant inputs are expected to be reflected quickly 

in groundwater (less than 10 years). The VFPS wells were 

“nested” wells with various depths collocated in a selected 

area to represent vertical gradients of groundwater flow to 

enhance the understanding of how contaminants move through 

aquifers over timespans of greater than a decade.

Principal Aquifer Study Networks

The PAS networks consist of public-supply wells, and 

water is sampled from the part of the aquifer used for the public drinking-water supply (Burow and Belitz, 2014). Publicsupply wells are generally the deepest wells sampled. Wells in 

PAS networks are sampled once to assess groundwater-quality 

conditions in the study areas. The extents of PAS network 

areas are based on the USGS (2003) map of principal aquifers 

and may be modified in some areas, as described in this report. 

Data from the following PAS networks are included in this 

report: Basin and Range carbonate-rock aquifers PAS network (bnrcpas1; fig. 2), Floridan aquifer system PAS network 

(florpas1; fig. 3), High Plains aquifer system PAS network 

(hpaqpas1; fig. 4), Mississippi Embayment-Texas Coastal 

Uplands aquifer system PAS network (metxpas1; fig. 5), and 

Rio Grande aquifer system PAS network (rgaqpas1; fig. 6).

Basin and Range Carbonate-Rock Aquifers 

Principal Aquifer Study Network (bnrcpas1)

The Basin and Range carbonate-rock aquifers underlie an 

area of about 16,000 square miles (mi2), which has a population of about 130,000 people primarily in western Utah and 

eastern Nevada, and small areas of Idaho, California, and 

Arizona (U.S. Bureau of the Census, 2010). The aquifers rank 
Groundwater Study Design 3

WASHINGTON

IDAHO

MONTANA

OREGON

NORTH

DAKOTA MINNESOTA

MAINE

WISCONSIN

CALIFORNIA

WYOMING

SOUTH

DAKOTA

NEW HAMPSHIRE

VERMONT

NEW YORK

NEVADA

UTAH

NEBRASKA

IOWA

PENNSYLVANIA

COLORADO

ILLINOIS

RHODE

ISLAND

OHIO

MICHIGAN

MI

NEW JERSERY

INDIANA

WEST VIRGINIA

MISSOURI

KANSAS

MARYLAND

DELAWARE

VIRGINIA

ARIZONA

KENTUCKY

NEW

MEXICO OKLAHOMA

TEXAS

NORTH

CAROLINA

TENNESSEE ARKANSAS

SOUTH CAROLINA GEORGIA

FLORIDA

ALABAMA

MISSISSIPPI

LOUISIANNA

CONNECTICUT

MASSACHUSETTS

C A N A D A

M E X I C O

GULF

OF

MEXICO

TA LANT CI

OCEAN

PACIFIC OCEAN

EXPLANATION

Principal aquifer study boundary

Sampled well, color indicates network type

Enhanced trends networkMajor aquifer studyLand-use studyPrincipal aquifer studyVertical flow-path study

0 500 100 200 300 400 MILES0 500 100 200 300 400 KILOMETERS

Base from U.S. Geological Survey digital data, 1:1,000,000 Albers Equal-Area Conic projectionStandard parallels 29°30' N. and 45°30' N.Central meridian 96°00' W.North American Datum of 1983

95° 65° 70° 75° 80° 85° 90° 100° 105° 110° 115° 120° 125°

45°40°35°30°25°

Figure 1. Groundwater study networks and wells sampled as part of the U.S. Geological Survey National Water-Quality Assessment Project from July through August 2013 and January through December 2015 for which water-quality data are included in this report.
4 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Salt

Lake

City

Los Angeles

Phoenix

Tucson

Las Vegas

Reno

Carson City

Fresno

Sacramento

San Francisco

Oakland

San Jose

UTAH

COLORADO

IDAHO

CALIFORNIA

NEVADA

ARIZONA

NEW MEXICO

OREGON

MEXICO

PACIFIC OCEAN

05

06

12

14

13

15

16

19

11

10

17

20 09

08

04

03

05

06

01

02

07

18

0 50 100 MILES

0 50 100 KILOMETERS

Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29o30' N. and 45o30' N.

Central meridian 96o00' W.

North American Datum of 1983

EXPLANATION

Equal-area grid cells used for

 randomized site selection

Basin and Range carbonate-rock 

 aquifers principal aquifer

 study network (bnrcpas1) 

 boundary

Sampled well and identification 

 number—See table 1 list for 

 network name bnrcpas1

01

Map area

Area of bnrcpas1

125° 120° 115°

40°

35°

30°

Figure 2. Study area and wells sampled as part of the Basin and Range Carbonate-Rock aquifers principal aquifer study network 

(bnrcpas1) for the U.S. Geological Survey National Water-Quality Assessment Project, July through August 2013 and March through 

September 2015.
Groundwater Study Design 5

Atlanta

Mobile

Augusta

Columbia

Jacksonville

Tallahassee

Orlando

Tampa-St. Petersburg

Miami

Fort

Lauderdale

Pensacola

ALABAMA

GEORGIA

SOUTH

CAROLINA

FLORIDA

GULF OF MEXICO

ATLANTIC OCEAN

01

02

03

04 05

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Base from U.S. Geological Survey digital data, 1:1,000,000 

Albers Equal-Area Conic projection

Standard parallels 29o30' N. and 45o30' N.

Central meridian 96o00' W.

North American Datum of 1983

EXPLANATION

Equal-area grid cells used for

 randomized site selection

Floridan aquifer system principal 

 aquifer study network 

 (florpas1) boundary

Sampled well and identification 

 number—See table 1 list for 

 network name florpas1

01

Map

area

Area of florpas1

88° 86° 84° 82° 80°

34°

32°

30°

28°

26°

Figure 3. Study area and wells sampled as part of the Floridan aquifer system principal aquifer study network (florpas1) for the U.S. 

Geological Survey National Water-Quality Assessment Project, March through August 2015.
6 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Cheyenne

Denver

Kansas

City

Wichita

Tulsa

Oklahoma

City

Lubbock

KANSAS

WYOMING

COLORADO

NEW MEXICO

OKLAHOMA

TEXAS

ARKANSAS

MISSOURI

NEBRASKA

SOUTH DAKOTA

IOWA

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29o30' N. and 45o30' N.

Central meridian 96o00' W.

North American Datum of 1983

EXPLANATION

Equal-area grid cells used for

 randomized site selection

High Plains aquifer principal 

 aquifer study network 

 (hpaqpas1) boundary

Sampled well and identification 

 number—See table 1 list for 

 network name hpaqpas1

01

Map area

Area of hpaqpas1

106° 104° 102° 100° 98° 96° 94°

42°

40°

38°

36°

34°

32°

Figure 4. Study area and wells sampled as part of the High Plains aquifer system principal aquifer study network (hpaqpas1) for the 

U.S. Geological Survey National Water-Quality Assessment Project, March through September 2015.
Groundwater Study Design 7

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Tulsa

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Rock

Fort Dallas

Worth

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Baton

Rouge

Austin New

Orleans

Houston

San Antonio

KANSAS

M E X I C O

ILLINOIS

MISSOURI KENTUCKY

OKLAHOMA

TEXAS

ARKANSAS TENNESSEE

ALABAMA

MISSISSIPPI

LOUISIANA

GULF OF MEXICO

100° 98° 96° 94° 92° 90° 88°

36°

34°

32°

30°

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0 40 80 120 160 200 MILES

0 40 80 120 160 200 KILOMETERS

Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

Oklahoma

City

EXPLANATION

Equal-area grid cells used for

 randomized site selection

Mississippi Embayment-Texas

 Coastal Uplands aquifer

 systems principal aquifer study

 network (metxpas1) boundary

Sampled well and identification 

 number—See table 1 list for 

 network name metxpas1

01

Map

area Area of metxpas1

Figure 5. Study area and wells sampled as part of the Mississippi Embayment-Texas Coastal Uplands aquifer system principal 

aquifer study network (metxpas1) for the U.S. Geological Survey National Water-Quality Assessment Project, July through September 

2015.
8 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

M E X I C O

UTAH COLORADO

ARIZONA NEW MEXICO

TEXAS

Albuquerque

Lubbock

El Paso

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

110° 108° 106° 104° 102°

36°

34°

32°

30°

Map

area

Area of rgaqpas1

EXPLANATION

Equal-area grid cells used for

 randomized site selection

Rio Grande aquifer system 

 principal aquifer study

 network (rgaqpas1) boundary

Sampled well and identification 

 number—See table 1 list for 

 network name rgaqpas1

01

Figure 6. Study area and wells sampled as part of the Rio Grande aquifer system principal aquifer study network (rgaqpas1) for the 

U.S. Geological Survey National Water-Quality Assessment Project, May through September 2015.
Groundwater Study Design 9

35th in the Nation as a source of groundwater for public supply; about 70 million gallons per day (Mgal/d) were pumped 

for this use in 2000 (Maupin and Barber, 2005; Arnold and 

others, 2016a). Land use overlying the Basin and Range 

carbonate-rock aquifers is predominantly undeveloped natural 

land cover (99 percent) with relatively small areas of agricultural or urban land, both of which are less than 1 percent of 

the area (Homer and others, 2015). Population density within 

the area is generally low. The rapidly growing urban areas of 

Salt Lake City, Utah, and Las Vegas, Nevada, are near, but not 

within, the boundary of the aquifers.

The Basin and Range carbonate-rock aquifers were 

described in detail by Harrill and Prudic (1998) and Schaefer 

and others (2005), and the descriptions are summarized here. 

The Basin and Range physiographic province is characterized 

by northeast-trending mountains and adjoining sedimentfilled basins and a complex geologic history. Bedrock, some 

of which is consolidated carbonate rocks, is present in the 

uplifted blocks of the mountains and beneath the basin fill 

in the valleys. The carbonate rocks have scattered zones of 

enhanced permeability developed along faults, fractures, and 

bedding planes. The carbonate-rock aquifers are composed 

of thick sequences of Paleozoic and Mesozoic limestone 

and dolomite with smaller amounts of shale, sandstone, and 

quartzite. The aquifers extend across topographic basins and 

mountain blocks in multibasin groundwater flow systems. 

Numerous flow systems within the carbonate-rock aquifers have been identified, each with their own recharge and 

discharge areas, structural controls, and potentially variable 

water quality. The carbonate-rock units generally are overlain by the basin-fill aquifer materials and may be hydraulically connected to them in some flow systems. The climate 

is generally arid to semiarid but highly variable because of 

large ranges in latitude and altitude across mountain ranges. 

Winter months have the most precipitation, and recharge is 

primarily from spring and summer melting of winter mountain 

snowpack (although most precipitation is lost to evapotranspiration because of the generally arid climate and high summer 

temperatures). Interbasin flow may be an important component 

of recharge or discharge in the solution-altered carbonate-rock 

aquifers. Because the carbonate rocks are quite thick in some 

areas—as much as 25,000 feet (ft)—groundwater flow may be 

deep. These regional flow systems discharge to large springs 

and streams, and through underflow, interbasin flow, and well 

withdrawal.

The Basin and Range carbonate-rock aquifers PAS 

network (bnrcpas1; fig. 2) includes 20 public-supply sites, 14 

of which are public-supply wells and 6 of which are springs. 

Sites were selected, using an equal-area grid of 20 cells. The 

area is sparsely populated, and public-supply wells and springs 

are not evenly distributed across the bnrcpas1 area. As a result, 

the equal-area grid was defined by placing 6.2-mile (mi) buffers around existing public-supply wells. The area of each cell 

was about 123 mi2. Two public-supply wells were sampled 

in Arizona, 1 public-supply well and 3 springs were sampled 

in Idaho, 3 public-supply wells and 1 spring were sampled in 

Nevada, and 8 public-supply wells and 1 spring were sampled 

in Utah. The wells typically ranged from 282 to 1,070 ft deep 

(appendix 1, table 1.1) and typically were open to the aquifer 

across intervals from 40 to 521 ft (appendix 1, table 1.2). The 

wells and springs, with two exceptions, were sampled between 

March and September 2015; the two public-supply wells in 

Arizona were sampled in July and August 2013.

Floridan Aquifer System Principal Aquifer Study 

Network (florpas1)

The Floridan aquifer system underlies an area of 84,000 

mi2, which has a population of about 16 million people in 

Mississippi, Alabama, Florida, Georgia, and South Carolina 

(U.S. Bureau of the Census, 2010). Withdrawals from this 

aquifer system are among the third largest in the United States 

for both public and domestic supply; withdrawals in 2000 

totaled 1,330 Mgal/d for public supply and 212 Mgal/d for 

domestic supply (Maupin and Arnold, 2010; Arnold and others, 2016a). Withdrawals are largest in Georgia and Florida, 

where it provides most of the public and irrigation water supply. Land use in the area overlying the Floridan aquifer system 

is primarily natural (72 percent) and agricultural land cover 

(17 percent) with a small percentage (11 percent) of urban and 

other developed land (Homer and others, 2015). Metropolitan 

areas surrounding Jacksonville, Florida, and Tampa, Fla., are 

included in the aquifer system area.

The Floridan aquifer system consists of Tertiary-aged 

carbonate rock sequences (Miller, 1986). Depending on 

location, the Floridan aquifer system can be under confined, 

semiconfined, or unconfined conditions. Recharge to the 

Upper Floridan aquifer primarily is in outcrop areas, and the 

general direction of groundwater flow is in all directions from 

the inland outcrop areas towards the coasts (Miller, 1986). 

Recharge also can be from streams or from downward movement of water from the overlying surficial aquifer and other 

shallow aquifers (Williams and Kuniansky, 2016). Rates of 

recharge from the surficial aquifer vary depending on the head 

potential between the surficial and Floridan aquifers and the 

presence of materials with relatively low permeability and low 

values of hydraulic conductivity (Miller, 1986). Relatively low 

permeability materials that act as confining units bound the 

Floridan aquifer system (Miller, 1986). Generally, the Floridan 

aquifer system functions as one aquifer; however, a discontinuous confining unit, in some locations, separates the aquifer 

system into two units, the Upper Floridan and Lower Floridan 

aquifers (Miller, 1986, Williams and Kuniansky, 2016). Both 

aquifers were sampled to characterize groundwater used for 

public supply in the Floridan aquifer system.

The Floridan aquifer system PAS network (florpas1; 

fig. 3) includes 60 public-supply wells. Wells were selected 

using an equal-area grid of 60 cells (average size, 1,375 mi2) 

that extended across 83,000 mi2 in parts of 4 States. All 

60 wells were sampled between March and August 2015. 

Wells in the florpas1 were typically about 169 to 788 ft deep 
10 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

(appendix 1, table 1.1) and had a wide range of open interval 

lengths (appendix 1, table 1.2).

High Plains Aquifer Principal Aquifer Study 

Network (hpaqpas1)

The High Plains aquifer underlies an area of 170,000 mi2, 

which has a population of about 2 million people in parts of 

Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, 

South Dakota, and Wyoming (U.S. Bureau of the Census, 

2010). The aquifer system ranks 13th in the Nation as a 

source of groundwater for public supply; about 390 Mgal/d 

were pumped for this use in 2000 (Maupin and Barber, 2005; 

Arnold and others, 2016a). The aquifer also is used extensively for agriculture, ranking first in the Nation as a source 

of groundwater for irrigation, with water pumped for irrigation an order of magnitude higher than for public supply 

(17,000 Mgal/d). Land use overlying the High Plains aquifer 

system is primarily natural (58 percent) and agricultural land 

(38 percent) with relatively small areas of urban and other 

developed land (4 percent) (Homer and others, 2015). About 

20 percent of the Nation’s irrigated agricultural land overlies 

the High Plains aquifer system. Urban areas that lie within the 

aquifer system’s overlying land are Cheyenne, Wyoming, and 

Amarillo, Lubbock, and Midland, Texas. Most of the population of the area resides in smaller towns and cities and rural 

areas. Urban development is much less widespread than agriculture in the area overlying the High Plains aquifer system.

The extensive area of the High Plains aquifer system 

includes a large range of topography and climate and, as a 

result, commonly is divided into three geographic subregions: 

Northern, Central, and Southern High Plains. Precipitation 

generally decreases from east to west, and temperatures 

increase from north to south (Thornton and others, 1997). The 

aquifer system was described in detail by McMahon and others (2007) and that description is summarized here. The High 

Plains aquifer system is generally unconfined and is composed 

of Tertiary and Quaternary age near-surface deposits that form 

six hydraulically connected hydrogeologic units. The Ogallala 

Formation, which has the largest areal extent of these units, 

consists primarily of unconsolidated clay, silt, sand, and gravel 

with locally cemented carbonate zones. Older sedimentary 

bedrock units underlie the aquifer system. Evaporation rates 

are some of the highest in the Nation because of high summer 

air temperatures and persistent winds. Because evaporation 

rates exceed precipitation across much of the study area, little 

water recharges the aquifer. Recharge to the aquifer is primarily from infiltration of irrigation water, diffuse infiltration from 

precipitation, focused infiltration of runoff from storms and 

irrigation water through streambeds and other topographic 

depressions, and upward movement of water from underlying 

aquifers (McMahon, 2001). Discharge from the aquifer primarily is to streams and underlying aquifers, and through irrigation-well pumping, through flow across the eastern boundary of the aquifer, and through evapotranspiration. Regional 

groundwater flow is generally from west to east. Water level 

has changed substantially in the High Plains aquifer because 

groundwater withdrawals have greatly exceeded recharge rates 

across much of the aquifer; water level declines are common 

across parts of Kansas, Oklahoma, New Mexico, and Texas.

The High Plains aquifer system PAS network (hpaqpas1, 

fig. 4) consists of 80 public-supply wells that were selected 

based on an equal-area grid. The area of each cell was about 

2,122 mi2. Data are presented in this report for 63 wells 

sampled between March and September 2015 in Colorado 

(7 wells), Kansas (11 wells), Nebraska (32 wells), New Mexico (4 wells), Oklahoma (4 wells), and Wyoming (5 wells). 

An additional 17 wells were sampled in Texas between May 

and July 2016. Wells in the hpaqpas1 that were sampled in 

2015 typically ranged from 110 to 497 ft deep with a median 

depth of about 230 ft (appendix 1, table 1.1); wells generally were open to the aquifer across a range of intervals, from 

20 to 231 ft, with a median interval of about 45 ft (appendix 1, 

table 1.2).

Mississippi Embayment-Texas Coastal Uplands 

Aquifer Systems Principal Aquifer Study 

Network (metxpas1)

Two regional aquifers, the Middle Claiborne aquifer and 

the Lower Claiborne-Upper Wilcox aquifer, were sampled to 

characterize groundwater used for public supply in the Mississippi Embayment-Texas Coastal Uplands aquifer systems PAS 

network (metxpas1; fig. 5). The Mississippi Embayment-Texas 

Coastal Uplands aquifer systems previously was described in 

Arnold and others (2017a, b) and is not repeated in this report.

The metxpas1 includes 89 public-supply wells distributed across the extent of the Middle Claiborne and Lower 

Claiborne-Upper Wilcox aquifers. Wells were selected using 

an equal-area grid that extended across 97,500 mi2 in parts 

of eight States as described in Arnold and others (2017b). 

Samples from 60 wells were collected in the Mississippi 

Embayment aquifer system between April and December 

2014—three of these wells were in the Mississippi River Valley alluvial aquifer (METXPAS1-22, -24, and -27; Arnold and 

others, 2017a, b). Samples from 32 wells were collected in 

the Texas Coastal Uplands between July and September 2015. 

Data from the 2015 sampling effort are presented in this report 

and the related data release (Arnold and others, 2018); data 

from the 2014 sampling effort were published in a previous 

report and data release (Arnold and others, 2017a, b). Wells 

in the metxpas1 sampled in 2015 were typically about 517 to 

2,214 ft deep (appendix 1, table 1.1) and had a wide range of 

open interval lengths (appendix 1, table 1.2).

Rio Grande Aquifer System Principal Aquifer 

Study Network (rgaqpas1)

The Rio Grande aquifer system underlies an area of 

29,000 mi2, which has a population of about 2 million people 
Groundwater Study Design 11

in Colorado, New Mexico, and Texas (U.S. Bureau of the 

Census, 2010). The Rio Grande aquifer system previously was 

described in Arnold and others (2017a, b) and the description 

is not repeated in this report.

The Rio Grande aquifer system PAS network (rgaqpas1, 

fig. 6) includes 79 wells and springs. The network design is 

based on an equal-area grid of 60 cells. Because parts of the 

area are sparsely populated and public-supply wells are not 

evenly distributed across the aquifer area, the grid was defined 

by placing 3.1 mi buffers around the existing public-supply 

wells, as described in Arnold and others (2017b). There were 

60 public-supply wells sampled in 2014 (Arnold and others, 

2017a, b). An additional 19 sites (16 wells and 3 springs) 

in New Mexico were sampled during 2015 and have data 

presented in this report and in Arnold and others (2018). These 

19 sites were selected to characterize geothermal waters and 

deep sedimentary brines that might contribute to—and affect 

the quality of—water withdrawn from public-supply wells in 

the Rio Grande aquifer system. The 16 wells sampled during 

2015 ranged from 133 to 1,653 ft deep with an average depth 

of about 659 ft (appendix 1, table 1.1).

Decadal Trends Networks—Land-Use Study 

Networks

The LUS networks are designed to facilitate analysis 

of land-use effects on shallow groundwater quality. Wells in 

LUS networks are sampled once per decade to assess temporal 

trends in water quality. Wells in LUS networks typically are 

shallow and screened near the water table to allow sampling 

of recently recharged groundwater that may exhibit chemical characteristics indicative of the surrounding land use. 

The LUS areas are determined by the areal extents of the 

primary aquifer and a targeted overlying land use (Lapham 

and others, 1995). Data from the following LUS networks are 

included in this report: Central Columbia Plateau agricultural 

LUS network (ccptlusor1b; fig. 7); Central Nebraska Basins 

agricultural LUS network (cnbrluscr1; fig. 8); Georgia-Florida 

Coastal Plain drainages agricultural LUS network (gaflluscr1; 

fig. 9); lower Illinois River Basin urban LUS network 

(lirblusrc1; fig. 10); Potomac River Basin and Delmarva 

Peninsula urban LUS network (podllusrc1; fig. 11); San 

Joaquin-Tulare River Basins agricultural LUS network 

(sanjluscr1a; fig. 12); and Trinity River Basin urban LUS 

network (trinlusrc1; fig. 13).

Central Columbia Plateau Agricultural Land-Use 

Study Network (ccptlusor1b)

The Central Columbia Plateau agricultural LUS network 

(ccptlusor1b; fig. 7) was designed to characterize the effects of 

intensively irrigated orchards on shallow groundwater quality. 

The study area of 2,500 mi2 is in south-central Washington and 

is contained within the Columbia Basin Irrigation Project area, 

a large-scale irrigation project through which a series of canals 

divert Columbia River water to a highly productive agricultural basin. The shallow aquifers in this area are unconsolidated basin-fill deposits; together with the underlying basaltic 

rocks, these aquifers make up the Columbia Plateau aquifer 

system (Whitehead, 1994).

The ccptlusor1b consists of 25 monitoring wells, which 

were installed throughout the study area in a sand and gravel 

aquifer. The targeted area for well installation originally was 

irrigated by sprinklers and rill-type irrigation. Over time, 

many areas have installed more efficient types of drip irrigation that often are metered by soil moisture levels. The wells 

originally were installed in areas dominated by various types 

of fruit trees (primarily apples) and grapes; however, the area 

has experienced rapid change in crop and irrigation types. 

The 21 wells with data presented in this report were sampled 

from August through October 2015. The sampled wells typically range from less than 19 ft to more than 73 ft deep with 

an average depth of 39 ft (appendix 1, table 1.1). Wells in the 

ccptlusor1b were sampled previously in 1994–95 and 2002.

Central Nebraska Basins Agricultural Land-Use 

Study Network (cnbrluscr1)

The Central Nebraska Basins agricultural LUS network 

(cnbrluscr1, fig. 8) wells were screened open to either the 

first presence of groundwater or just below the water table to 

provide a broad-scale evaluation of recently recharged groundwater that would most likely be affected by nearby land use. 

The study area is within the areal extent of the glacial till north 

of the Platte River in northeast Nebraska. This area of glacial 

till covers about 2,700 mi2 in the lower Elkhorn River Basin 

(Stanton and others, 2007). The hydrogeology of the study 

area is a very complex mixture of deep to shallow regional 

and local aquifers in the glaciated area of eastern Nebraska. 

The regional groundwater-flow direction in the study area is 

from northwest to the southeast (Flowerday and others, 1998). 

In most of the study area, the Cretaceous-age bedrock units 

underlying unconsolidated aquifers generally do not yield a 

sufficient amount of freshwater for most uses. Land use in the 

study area is dominated by agriculture and most water used in 

the study area is for cropland irrigation. Other primary water 

uses include publicly supplied drinking water, self-supplied 

domestic drinking water, industrial, and livestock (Stanton and 

others, 2007).

The cnbrluscr1 includes 27 monitoring wells, which were 

sampled from April through June 2015. The wells with data 

presented in this report were typically between 20 to 65 ft 

deep (appendix 1, table 1.1) with 5- to 10-ft screened intervals 

(appendix 1, table 1.2). Wells in the cnbrluscr1 were sampled 

previously in 2003 (Stanton and others, 2007).
12 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

River

Potholes

Reservoir

Columbia

WASHINGTON

Connell

Ellensburg

Ephrata

George

Kennewick

Moses

Lake

Othello

Mattawa

Pasco

Quincy

Royal

City Warden

Richland

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

120°40' 120°20' 120° 119°40' 119°20' 119°

47°

46°40'

46°20'

46°

Map area

Area of

ccptlusor1b

EXPLANATION

Extent of the orchard or vineyard 

 land used for well selection 

 in the Central Columbia Plateau 

 agricultural land-use study 

 network (ccptlusor1b)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name ccptlusor1b

01

Figure 7. Study area and wells sampled as part of the Central Columbia Plateau agricultural land-use study network (ccptlusor1b) for 

the U.S. Geological Survey National Water-Quality Assessment Project, August through October 2015.
Groundwater Study Design 13

Platte

River

Elkhorn

River

River

Missouri

Omaha

NEBRASKA

IOWA

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 5 10 15 20 25 MILES

0 5 10 15 20 25 KILOMETERS

97°30' 97° 96°30' 96°

42°30'

42°

41°30'

41°

Map area

Area of

cnbrluscr1

EXPLANATION

Extent of the agricultural land used 

 for well selection in the Central 

 Nebraska Basins agricultural 

 land-use study network 

 (cnbrluscr1)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name cnbrluscr1

01

Figure 8. Study area and wells sampled as part of the Central Nebraska Basins agricultural land-use study network (cnbrluscr1) for 

the U.S. Geological Survey National Water-Quality Assessment Project, April through June 2015.
14 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Ocmulgee

Alapaha

Little

Warrior

Creek

River

River

River

Abbeville

Adel

Alapaha

Arabi

Ashburn

Cordele

Enigma

Fitzgerald

Jacksonville

Lenox

Nashville

Ocilla

Poulan

Rebecca

Rhine

Rochelle

Sparks

Sumner

Sycamore

Sylvester

Tifton Ty Ty

Vienna

GEORGIA

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 2 4 6 8 10 MILES

0 2 4 6 8 10 KILOMETERS

83°50' 83°40' 83°30' 83°20' 83°10' 83°

32°

31°50'

31°40'

31°30'

31°20'

31°10'

Map area

Area of

gaflluscr1

EXPLANATION

Extent of the agricultural land used 

 for well selection in the 

 Georgia-Florida Coastal Plain 

 drainages agricultural land-use 

 study network (gaflluscr1)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name gaflluscr1

01

Figure 9. Study area and wells sampled as part of the Georgia-Florida Coastal Plain drainages agricultural land-use study network 

(gaflluscr1) for the U.S. Geological Survey National Water-Quality Assessment Project, May 2015.
Groundwater Study Design 15

Missouri River

Mississippi

River

ILLINOIS

MISSOURI

Alton

Belleville

Collinsville

East St.

Louis

Edwardsville

Granite

City

O'Fallon

Affton

Ballwin

Chesterfield

Ferguson

Florissant

Hazelwood

Kirkwood

Maryland

Heights

Mehlville

Oakville

O'Fallon

St.

Charles

St.

Louis

Spanish

Lake

University

City

Webster

Groves

Wildwood

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02

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Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 2 4 6 8 10 MILES

0 2 4 6 8 10 KILOMETERS

90°40' 90°30' 90°20' 90°10' 90° 89°50'

39°10'

39°

38°50'

38°40'

38°30'

Map area

Area of lirblusrc1

EXPLANATION

Extent of the urban land used for 

 well selection in the lower 

 Illinois River Basin urban 

 land-use study network 

 (lirblusrc1)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name lirblusrc1

01

Figure 10. Study area and wells sampled as part of the lower Illinois River Basin urban land-use study network (lirblusrc1) near 

St. Louis, Missouri, for the U.S. Geological Survey National Water-Quality Assessment Project, July through August 2015.
16 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Potomac

River

MARYLAND

VIRGINIA

Washington D.C

Barnesville

Berwyn

Heights Bowie

Brentwood

Brookeville

Capitol

Heights

Cheverly

Chevy

Chase

College Park

District

Heights

Forest

Heights

Gaithersburg

Glenarden Glen

Echo

Greenbelt

Hyattsville

Kensington

Laytonsville

Morningside

New

Carrollton

Poolesville

Rockville

Takoma

Park

Alexandria

Clifton

Fairfax

Falls

Church

Herndon

Manassas

Manassas

Park

Vienna

01 03 05 06

11

12 13

16

21

23

28

35

46

47

49

52

63

65

69

72

74

76

79

85

86

87

99

Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 2 4 6 8 10 MILES

0 2 4 6 8 10 KILOMETERS

77°20' 77°10' 77° 76°50'

39°10'

39°

38°50'

38°40'

Map area

Area of

podllusrc1

EXPLANATION

Extent of the urban land used for 

 well selection in the Potomac

 River Basin and Delmarva

 Peninsula urban land-use study 

 network (podllusrc1)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name podllusrc1

01

Figure 11. Study area and wells sampled as part of the Potomac River Basin and Delmarva Peninsula urban land-use study network 

(podllusrc1) near Washington, D.C., for the U.S. Geological Survey National Water-Quality Assessment Project, June through August 

2015.
Groundwater Study Design 17

San J oaquin

River

San Joaquin River

Kings

River

PACIFIC

OCEAN

Merced River

Tuolemne River

Mono Lake

Sacramento

Concord

Oakland

San

Francisco

San Jose

Fresno

CALIFORNIA

NEVADA

23

2221 19

20

02

16 17

15

13

14

11

10

12

09

08 07

05

06

03

04

02

01

122° 121° 120° 119°

38°

37°

36°

35°

0 20 40 60 80 100 MILES

0 20 40 60 80 100 KILOMETERS

Base from U.S. Geological Survey digital data, 1:1,000,000, 1:2,000,000, and 1:10,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

Map

area

Area of

sanjlusor1a

EXPLANATION

Extent of the agricultural land used 

 for well selection in the San 

 Joaquin-Tulare River Basins 

 agricultural land-use study 

 network (sanjluscr1a)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name sanjluscr1a

01

Figure 12. Study area and wells sampled as part of the San Joaquin-Tulare River Basins agricultural land-use study network 

(sanjluscr1a) for the U.S. Geological Survey National Water-Quality Assessment Project, July through August 2015.
18 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Lake

Houston

Buffalo

Bayou

Atascocita

Channelview

Cloverleaf

Conroe

Deer

Park

Friendswood

Houston

La Porte

Pasadena

Pearland

Spring

The

Woodlands

01

02

03

04

05

06 07

08

09

10

11

12

13

14

15 16

17

18

19

20

21

22

23

24

25

26 27

Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 2 4 6 8 10 MILES

0 2 4 6 8 10 KILOMETERS

95°40' 95°30' 95°20' 95°10'

30°10'

30°

29°50'

29°40'

Map

area

Area of trinlusrc1

EXPLANATION

Extent of the urban land used for 

 well selection in the Trinity River 

 Basin urban land-use study 

 network (trinlusrc1)

Boundary of primary aquifer

Sampled well and identification 

 number—See table 1 list for 

 network name trinlusrc1

01

Figure 13. Study area and wells sampled as part of the Trinity River Basin urban land-use study network (trinlusrc1) near Houston, 

Texas, for the U.S. Geological Survey National Water-Quality Assessment Project, January through April 2015.
Groundwater Study Design 19

Georgia-Florida Coastal Plain Drainages 

Agricultural Land-Use Study Network (gaflluscr1)

The Georgia-Florida Coastal Plain drainages agricultural 

LUS network (gaflluscr1, fig. 9) was designed to characterize 

the effects of agriculture on shallow groundwater quality in 

the surficial aquifer in south-central Georgia. The study area 

of 1,300 mi2 is an area of shallow groundwater in the surficial 

aquifer beneath cropland. The surficial aquifer is an unconfined sand and clay aquifer, about 10 to 60 ft thick (Metz and 

others, 2007). A clay confining unit separates the surficial 

aquifer from the Upper Floridan aquifer in parts of the study 

area. The Floridan aquifer system and its relation to the surficial aquifer are described in the section about the florpas1.

The gaflluscr1 includes 26 monitoring wells sampled in 

May 2015 (fig. 9). The wells with data included in this report 

were typically 20 to 65 ft deep (appendix 1, table 1.1). Wells 

in the network were previously sampled in 1994 and 2002 

(Berndt and others, 2014).

Lower Illinois River Basin Urban Land-Use Study 

Network (lirblusrc1)

The lower Illinois River Basin urban LUS network 

(lirblusrc1, fig. 10) wells near St. Louis, Missouri, were 

screened open to shallow glacial and alluvial deposits to provide a broad-scale evaluation of recently recharged groundwater that would most likely be affected by nearby urban land 

use. The lirblusrc1 area includes recently urbanized areas near 

St. Louis, Mo. This area covers about 5,700 mi2 near the Mississippi River.

The lirblusrc1 includes 26 monitoring wells. The wells 

with data included in this report were typically about 18 to 

52 ft deep (appendix 1, table 1.1) with 5-ft screened intervals 

(appendix 1, table 1.2). Samples were collected from 25 wells, 

11 in Missouri and 14 in Illinois, in July and August 2015. 

Wells in this network were sampled previously in 2005.

Potomac River Basin and Delmarva Peninsula 

Urban Land-Use Study Network (podllusrc1)

The Potomac River Basin and Delmarva Peninsula urban 

LUS network (podllusrc1, fig. 11) near Washington, D.C., 

was designed to characterize the effects of urban land use on 

shallow groundwater quality in the Piedmont and Blue Ridge 

crystalline-rock aquifers. The study area is about 1,800 mi2

and is defined as an area of shallow groundwater in urban and 

suburban areas within the Potomac River Basin near Washington, D.C., and Baltimore, Maryland. The Piedmont and Blue 

Ridge crystalline-rock aquifers consist of a variety of rock 

types such as gneiss, schist, phyllite, granite, and basalt (Chapman and others, 2013). Rocks are overlain by unconsolidated 

material called regolith, which is more permeable than the 

underlying bedrock and is important for storage and transmission of water. Most recharge to these aquifers is from local 

precipitation. Flow in the crystalline-rock aquifers is limited to 

fractures; thus, individual well yields are low in these aquifers 

relative to well yields in other bedrock types in the area (Trapp 

and Horn, 1997).

The podllusrc1 includes 28 monitoring wells (fig. 11). 

The wells with data included in this report typically were 45 to 

112 ft deep (appendix 1, table 1.1) with open intervals mostly 

between 13 and 85 ft (appendix 1, table 1.2). Samples for the 

current phase of monitoring were collected in June to August 

2015. Wells from the podllusrc1 were sampled previously in 

2003.

San Joaquin-Tulare River Basins Agricultural 

Land-Use Study Network (sanjluscr1a)

The San Joaquin-Tulare River Basins agricultural LUS 

network (sanjluscr1a, fig. 12) was designed to characterize 

shallow groundwater quality underlying agricultural land use 

in the eastern San Joaquin Valley of California. The eastern 

San Joaquin Valley is an area of intensive farming that also has 

a large urban population. The sanjluscr1a area is in the eastern 

alluvial fans physiographic region and has extensive and widespread deposits of coarse-grained sediment (Burow and others, 

1998; Thiros and others, 2010). The sanjluscr1a area of about 

520 mi2 is limited to areas where the predominant crops grown 

are corn, alfalfa, and vegetables; this crop grouping is one of 

the major types of agriculture in the area.

The sanjluscr1a includes 23 wells sampled between July 

and August 2015. The wells with data presented in this report 

typically ranged from 108 to 361 ft deep but generally were 

less than 200 ft deep (appendix 1, table 1.1). The wells are 

open to the aquifer across intervals of 20 to 174 ft (appendix 1, 

table 1.2). Wells in the sanjluscr1a were previously sampled in 

1994–95 and in 2002.

Trinity River Basin Urban Land-Use Study 

Network (trinlusrc1)

The Trinity River Basin urban LUS network (trinlusrc1, 

fig. 13) near Houston, Tex., was designed to characterize the 

quality of groundwater in the Chicot aquifer within the Coastal 

Lowlands aquifer system underlying urban land use within 

northwest Houston, Tex. The Coastal Lowlands aquifer system 

is unconsolidated to partially consolidated sand, silt, and clay 

of Oligocene to Holocene age (Ryder, 1996; Renken, 1998). 

The trinlusrc1 area (about 4,000 mi2) is in the southern part of 

the Trinity River Basin within northwest Houston, Tex.

The trinlusrc1 includes 27 wells sampled January through 

April 2015. Because the wells were sampled early in 2015, 

some of the blank samples were collected in November 2014 

to check the cleanliness of the sampling equipment. The wells 

with data included in this report typically were about 28 to 

80 ft deep (appendix 1, table 1.1) and had open intervals of 

around 10 ft (appendix 1, table 1.2). Wells in the trinlusrc1 

were previously sampled in 2003.
20 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Decadal Trends Networks—Major Aquifer 

Study Networks

The MAS networks were designed to reflect the resource 

used for domestic supply. The MAS networks generally consist of domestic-supply wells but also may include public-supply or other types of wells. Domestic-supply wells typically 

draw groundwater from shallower depths of the aquifer than 

do public-supply wells. Additionally, domestic-supply wells 

tend to draw smaller volumes of water from the aquifer than 

do public-supply wells. The MAS areas are determined by 

the areal extent of the primary aquifer and physiography and 

are designed to assess the condition of groundwater quality in 

the most heavily used aquifer in the area (Lapham and others, 

1995; Koterba and others, 1995). Wells in MAS networks are 

sampled once per decade to assess temporal trends in water 

quality. Data from the following MAS networks are included 

in this report: Apalachicola-Chattahoochee-Flint River Basins 

MAS network (acfbsus1; fig. 14), San Joaquin-Tulare River 

Basins MAS network (sanjsus1; fig. 15), and western Lake 

Michigan drainages MAS network (wmicsus1; fig. 16).

Apalachicola-Chattahoochee-Flint River Basins 

Major Aquifer Study Network (acfbsus1)

The Apalachicola-Chattahoochee-Flint River Basins 

MAS network (acfbsus1, fig. 14) was designed to characterize 

the quality of water used for water supply in the Floridan aquifer. The Floridan aquifer (previously described for florpas1) 

is a limestone and dolomite aquifer that is used heavily as a 

source of water supply in several southeastern States (Miller, 

1990). The acfbsus1 area of 3,900 mi2 is defined as those areas 

where the Upper Floridan aquifer lies within the ApalachicolaChattahoochee-Flint River Basins (Wangsness, 1997; Frick 

and others, 1998).

The acfbsus1 includes 27 wells. The wells with data 

included in this report typically were 78 to 249 ft deep 

(appendix 1, table 1.1) with open intervals of around 12 to 

164 ft (appendix 1, table 1.2). Samples for the current phase 

of monitoring were collected in August 2015. Wells in the 

acfbsus1 were sampled previously in 1995 and 2002 (Berndt 

and others, 2014).

San Joaquin-Tulare River Basins Major Aquifer 

Study Network (sanjsus1)

The San Joaquin-Tulare River Basins MAS network 

(sanjsus1, fig. 15) was designed to characterize the quality of 

shallow groundwater in the eastern San Joaquin Valley within 

the Central Valley aquifer system in the San Joaquin-Tulare 

Basins study unit in California. The eastern San Joaquin Valley is an area of intensive farming that also has a large urban 

population. The study area is in the eastern alluvial fans physiographic region and has extensive and widespread deposits of 

coarse-grained sediment (Burow and others, 1998; Thiros and 

others, 2010). The sanjsus1 area is about 520 mi2.

The sanjsus1 includes 26 wells sampled between July and 

August 2015. The wells with data presented in this report typically ranged from 106 to 464 ft deep (appendix 1, table 1.1) 

and had a mean well depth of 232 ft. The wells typically were 

open to the aquifer across intervals of 16 to 105 ft (appendix 1, 

table 1.2). Wells in the sanjsus1 were sampled previously in 

1995 and in 2002.

Western Lake Michigan Drainages Major Aquifer 

Study Network (wmicsus1)

The western Lake Michigan drainages MAS network 

(wmicsus1, fig. 16) was designed to characterize the quality of 

groundwater in the parts of the Cambrian-Ordovician aquifer that are most heavily used for water supply in that area. 

The western Lake Michigan drainages include those parts of 

eastern Wisconsin and the Upper Peninsula of Michigan that 

drain to Green Bay and Lake Michigan (Peters and others, 

1998). The wmicsus1 covers an area of about 8,100 mi2. The 

Cambrian-Ordovician aquifer in the vicinity of the wmicsus1 

is principally Cambrian- and Ordovician-age sandstone and 

dolomite. Land use and land cover overlying wmicsus1 (Saad, 

1996) is mainly forest and forested wetland in the north and 

agricultural land in the south. Urban land use in the wmicsus1 

area is mainly along the shores of Lake Winnebago and in the 

lower Fox River Valley from Appleton to Green Bay, Wisconsin. Most of the larger urban areas in the wmicsus1 area obtain 

most of their water from surface-water sources, such as Lake 

Winnebago, but some supplement this source with groundwater primarily from the Cambrian-Ordovician aquifer (Saad, 

1996).

The wmicsus1 includes 21 wells, mostly drinking-water 

supply wells, which were sampled July through September 

2015. The wells with data included in this report typically 

were 95 to 675 ft deep (appendix 1, table 1.1) with about 

20- to 307-ft open intervals (appendix 1, table 1.2). Wells in 

the wmicsus1 were previously sampled in 1995 and in 2002. 

Enhanced Trends Networks

An ETN consists of a small number of wells (typically 

two to four) that are sampled frequently to evaluate the time 

scales during which groundwater quality changes. Such 

changes might result from seasonal or annual variability in 

recharge, discharge, or contaminant loading (Rowe and others, 2013). Data from eight ETNs are included in this report 

(figs. 17–18): Central Valley ETN (cvaletn1), Columbia 

Plateau ETN (clptetn1), Edwards-Trinity aquifer system ETN 

(edtretn1), glacial aquifer system ETN (glacetn1), Mississippi 

Embayment aquifer system ETN (metxent1), Northern Atlantic Coastal Plain ETN (nacpetn1), New England crystallinerock and glacial aquifer system ETN (negxetn1), and the Rio 

Grande aquifer system ETN (rgaqetn1).
Groundwater Study Design 21

Chattahoochee

River

River

Apalachicola

River

FLORIDA

ALABAMA

GEORGIA

Lake

Seminole

Walter F.

George

Reservoir

Flint

Dothan

Marianna

Albany

Bainbridge

Blakely

Cairo

Camilla

Cordele

Dawson

Thomasville

Sylvester

01

02

03 04

05

06

07

08

09

10

11

12

13

14

15

16 17

18

19

20

21

22

23

24

25

26 27

Base from U.S. Geological Survey digital data, 1:1,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 5 10 15 20 25 MILES

0 5 10 15 20 25 KILOMETERS

85° 84°30' 84°

32°

31°30'

31°

30°30'

Map

area

Area of

acfbsus1

EXPLANATION

Boundary of primary aquifer and

 the Apalachicola-Chattahoochee-

 Flint River Basins major aquifer 

 study network (acfbsus1)

Sampled well and identification 

 number—See table 1 list for 

 network name acfbsus1

01

Figure 14. Study area and wells sampled as part of the Apalachicola-Chattahoochee-Flint River Basins major aquifer study 

network (acfbsus1) for the U.S. Geological Survey National Water-Quality Assessment Project, August 2015.
22 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

San J oaquin

River

San Joaquin River

Kings

River

PACIFIC

OCEAN

Merced River

Tuolemne River

Mono Lake

Sacramento

Concord

Oakland

San

Francisco

San Jose

Fresno

CALIFORNIA

NEVADA

01

02

03

04

05 06

07

08

09 10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

122° 121° 120° 119°

38°

37°

36°

35°

0 20 40 60 80 100 MILES

0 20 40 60 80 100 KILOMETERS

Base from U.S. Geological Survey digital data, 1:1,000,000, 1:2,000,000, and 1:10,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

Map

area

Area of

sanjsus1

EXPLANATION

Boundary of primary surficial aquifer 

 and the San Joaquin-Tulare River 

 Basins major aquifer study 

 network (sanjsus1)

Sampled well and identification 

 number—See table 1 list for 

 network name sanjsus1

01

Figure 15. Study area and wells sampled as part of the San Joaquin-Tulare River Basins major aquifer study network (sanjsus1) for 

the U.S. Geological Survey National Water-Quality Assessment Project, July through August 2015.
Groundwater Study Design 23

Green Bay

LAKE MICHIGAN

Lake

Winnebago

Lake Poygan

Lake Butte des Morts

MICHIGAN

WISCONSIN

Escanaba

Gladstone

Kingsford

Menominee

Appleton

Ashwaubenon

Berlin

Fond du

Lac

Green Howard Bay

Marinette

New

London

Oshkosh

Portage

Rhinelander

Ripon

Shawano

Stevens

Point

Sturgeon

Bay

Waupaca

Waupun

Wausau

Manitowoc

01

02

03 04

05

06

08 07

09

10

11

12

13

14

15

16

17

18

19

20

21

90° 89°30' 89° 88°30' 88° 87°30' 87° 86°30'

46°

45°30'

45°

44°30'

44°

Base from U.S. Geological Survey digital data, 1:1,000,000 and 1:10,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 10 20 30 40 50 MILES

0 10 20 30 40 50 KILOMETERS

Map

area Area of

wmicsus1

EXPLANATION

Boundary of primary surficial aquifer 

 and the western Lake Michigan 

 drainages major aquifer study 

 network (wmicsus1) 

Sampled well and identification 

 number—See table 1 list for 

 network name wmicsus1

01

Figure 16. Study area and wells sampled as part of the western Lake Michigan drainages major aquifer study network 

(wmicsus1) for the U.S. Geological Survey National Water-Quality Assessment Project, July through September 2015.
24 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

PACIFIC OCEAN

Fowler

Switch

Canal

Columbia River

Rio Grande

San Antonio River

Quadalupe

R iver

Medina River

M E X I C O

C A N A D A

WASHINGTON

IDAHO

MONTANA

OREGON

NORTH

DAKOTA

CALIFORNIA

WYOMING

SOUTH

DAKOTA

NEVADA

UTAH

NEBRASKA

COLORADO

KANSAS

ARIZONA

NEW

MEXICO OKLAHOMA

TEXAS

Boardman

Hermiston

Irrigon

Stanfield

Umatilla

WASHINGTON

OREGON

Calwa

Easton

Fresno

Sanger

Hatch

Rincon

Salem

Kingsbury Lakehills

New

Berlin

New

Braunfels

San Antonio

Santa

Clara Seguin

EDTRETN1–02EDTRETN1–01EDTRETN1–03

RGAQETN1–03RGAQETN1–02RGAQETN1–01

CVALETN1–01CVALETN1–02CVALETN1–03

CLPTETN1–01CLPTETN1–06CLPTETN1–04

CLPTETN1–04

CLPTETN1–01

CLPTETN1–06

CVALETN1–01CVALETN1–02CVALETN1–03

RGAQETN1–01

RGAQETN1–02

RGAQETN1–03

EDTRETN1–03

EDTRETN1–02

EDTRETN1–01

0 100 200 300 400 MILES0 100 200 300 400 KILOMETERS

0 5 1 2 3 4 MILES0 5 1 2 3 4 KILOMETERS

0 10 2 4 6 8 MILES0 10 2 4 6 8 KILOMETERS

0 20 5 10 15 MILES0 20 5 10 15 KILOMETERS Base from U.S. Geological Survey digital data, 1:2,000,000 Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.Central meridian 96°00' W.North American Datum of 1983

0 10 2 4 6 8 MILES

0 10 2 4 6 8 KILOMETERS

100° 105° 110° 115° 120° 125°

45°40°35°30°25° EXPLANATION

Sampled wellWell identification number (see table 1) CVALETN1–01

A

BCDE

Figure 17. Study areas and wells sampled, A, in the western United States as part of the enhanced trends networks for the U.S. Geological Survey National WaterQuality Assessment Project, January through December 2015. Detail of well locations for 

B, clptetn1; 

C, cvaletn1; 

D, rgaqetn1; and 

E, edtretn1.
Groundwater Study Design 25

GULF OF MEXICO

ATLANTIC OCEAN

LAKE MICHIGAN

Wolf River

TA AL

TN CI

OCEAN

CO CI TNALTA

AE N

Mississippi River

CT

C A N A D A

MINNESOTA

MAINE

WISCONSIN

NH

VT

NEW YORK

MICHIGAN

IOWA

MA

PENNSYLVANIA

ILLINOIS

RI

OHIO

NJ

INDIANA

WEST VIRGINIA

MISSOURI

VIRGINIA

KENTUCKY

MD

TEXAS

NORTH

CAROLINA

TENNESSEE

ARKANSAS

SOUTH CAROLINA

GEORGIA

ALABAMA

MISSISSIPPI

LOUISIANA FLORIDA

Amesbury Salisbury

Exeter

Hampton

NEW

HAMPSHIRE

MASSACHUSETTS

Bridgeville

Ellendale

Georgetown

Greenwood

Lewes

Long

Neck

Milton

TENNESSEE

ARKANSASWest

Memphis

Memphis

MICHIGAN

WISCONSIN

DELAWARE

Fitchburg

Green

Bay

La Crosse

Sheboygan

Milwaukee

StevensPoint

MINNESOTA

NACPETN1–01NACPETN1–02NACPETN1–03

NEGXETN1–03NEGXETN1–02NEGXETN1–01

GLACETN1–01GLACETN1–02

METXETN1–02METXETN1–01

GLACETN1–03GLACETN1–04GLACETN1–05

GLACETN1–01GLACETN1–02

GLACETN1–03GLACETN1–04GLACETN1–05

NEGXETN1–01 NEGXETN1–02

NEGXETN1–03

NACPETN1–03

NACPETN1–02

NACPETN1–01

METXETN1–02

METXETN1–01

0 5 1 2 3 4 MILES0 5 1 2 3 4 KILOMETERS

0 10 2 4 6 8 MILES0 10 2 4 6 8 KILOMETERS

0 5 1 2 3 4 MILES0 5 1 2 3 4 KILOMETERS 0 100 200 300 400 MILES

0 100 200 300 400 KILOMETERS

Base from U.S. Geological Survey digital data, 1:2,000,000Albers Equal-Area Conic projectionStandard parallels 29°30' N. and 45°30' N.Central meridian 96°00' W.North American Datum of 1983

0 20 MILES

0 20 KILOMETERS

IOWA

95° 65° 70° 75° 80° 85° 90°

50°45°40°35°30°25°

EXPLANATION

A

BCDE

Sampled wellWell identification number (see table 1) GLACETN1–01

Figure 18. Study areas and wells sampled, A, in the eastern United States as part of the enhanced trends networks for the U.S. Geological Survey National WaterQuality Assessment Project, January through December 2015. Detail of well locations for 

B, glacetn1; 

C, negxetn1; 

D, nacpetn1; and 

E, metxetn1.
26 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Wells in an ETN are instrumented for high-frequency 

measurement of selected parameters and they periodically 

have discrete measurements of additional parameters. The 

parameters measured at a high frequency differ among wells 

and networks but generally include parameters like temperature, dissolved oxygen, pH, and specific conductance. 

Data collected at a high frequency for wells in the ETNs are 

available online; links to the data are provided in appendix 2, 

table 2.1.

For periodic discrete sampling, the ETNs are divided 

into two groups of four networks that are sampled on a 4-year 

alternating cycle. Four networks are sampled approximately 

once every 2 months for 4 years, whereas the other four networks are sampled annually. After the first 4-year period, the 

sampling frequency switches; the networks that were sampled 

every 2 months during the first period are sampled annually, 

and the other four networks are sampled every 2 months. 

Water-quality data from the discrete sampling during 2015 are 

included in this report and in Arnold and others (2018).

Central Valley Enhanced Trends Network 

(cvaletn1)

The Central Valley ETN (cvaletn1; fig. 17A, C) in the 

Central Valley aquifer system is intended to aid in the understanding of the subsurface movement of groundwater constituents (in some cases contaminants from land-use practices) 

between the shallow and deep parts of the aquifer system. The 

environmental setting of cvaletn1 previously was described in 

Arnold and others (2017a, b) and is not repeated in this report.

The cvaletn1 is made up of three wells that represent 

different depths in the regional aquifer (table 1). Two wells 

are relatively shallow (CVALETN1–02, 320 ft deep; and 

CVALETN1–03, 234 ft deep), and one well is relatively deep 

(CVALETN1–01, 620 ft deep). All three wells in the cvaletn1 

were sampled previously in 2013 (Arnold and others, 2016a, 

b) and 2014 (Arnold and others, 2017a, b). During 2015, the 

CVALETN1–01 and CVALETN1–03 wells were sampled 

approximately once every 2 months between January and 

November; CVALETN1–02 was sampled once in October. 

Data from the 2015 sampling are included in this report and in 

Arnold and others (2018).

Columbia Plateau Enhanced Trends Network 

(clptetn1)

The Columbia Plateau ETN (clptetn1; fig. 17A, B) in the 

Columbia Plateau aquifer system was designed to investigate 

questions about how groundwater quality differs between 

the shallow basin-fill (unconsolidated deposits) aquifers and 

the deeper, underlying basaltic-rock aquifers and how water 

quality varies along the flow paths. The environmental setting 

of clptetn1 previously was described in Arnold and others 

(2017a, b) and is not repeated in this report.

The clptetn1 is made up of wells that represent different positions within the regional groundwater flow system at 

different depths (table 1). Well CLPTETN1–01 is a shallow 

(80 ft), domestic well in the sand and gravel aquifer. Well 

CLPTETN1–04 is a deep (1,116 ft), long-screened (926–

1,100 ft) supply well that is open to the basaltic-rock aquifers; 

this well is about 20 mi south of the Columbia River and is 

the most proximal of the three wells. Well CLPTETN1–06 is 

a shallow (40 ft) domestic well, also in the sand and gravel 

aquifer.

Wells CLPTETN1–02 and CLPTETN1–03 were sampled 

as part of the clptetn1 in 2014 (Arnold and others, 2017a, b); 

however, because of issues with sample quality and sampling 

access, these wells are no longer included in the clptetn1. 

Well CLPTETN1–01 also was sampled in 2014 (Arnold and 

others, 2017a, b). Wells CLPTETN1–01, CLPTETN1–04, 

and CLPTETN1–06 were sampled once in October 2015, and 

the data are included in this report and in Arnold and others 

(2018).

Edwards-Trinity Aquifer System Enhanced 

Trends Network (edtretn1)

The Edwards-Trinity aquifer system ETN (edtretn1; 

fig. 17A, E) was designed to evaluate temporal variability in 

groundwater quality in a dynamic karst aquifer. The environmental setting of edtretn1 previously was described in Arnold 

and others (2017a, b) and is not repeated in this report.

There are three wells in the edtretn1 (table 1) that are 

along an approximately north-to-south aquifer transect within 

the San Antonio metropolitan area (fig. 17E). One well is 

in the upgradient, unconfined recharge zone, and two wells 

are downgradient in the confined zone. The upgradient well 

(EDTRETN1–02) is 300 ft deep and open to the aquifer along 

the bottom 80 ft of its depth (table 1). The downgradient wells 

are 550 ft (EDTRETN1–01) and 1,550 ft (EDTRETN1–03) 

deep and are open to the aquifer throughout their length below 

the confined zone (table 1). The farthest downgradient well 

(EDTRETN1–03) is close to the southern boundary of the 

aquifer. Wells in the edtretn1 were first sampled as part of the 

edtretn1 in 2013 (Arnold and others, 2016a, b) and sampled 

again in 2014 (Arnold and others, 2017a, b). During 2015, the 

wells were sampled approximately bimonthly from January 

through December 2015, and these data are included in this 

report and in Arnold and others (2018).

Glacial Aquifer System Enhanced Trends 

Network (glacetn1)

The glacial aquifer system ETN (glacetn1; fig. 18A, B) 

was designed to identify the temporal variability and magnitude of observed changes in groundwater quality in agricultural areas of the glacial aquifer system. The environmental 

setting of glacetn1 previously was described in Arnold and 

others (2017a, b) and is not repeated in this report.
Groundwater Study Design 27

The glacetn1 consists of five wells distributed in two 

locations. A location in central Wisconsin has two monitoring wells: GLACETN1–01 (83 ft deep) and GLACETN1–02 

(34.5 ft deep). A location in southwestern Wisconsin has 

three wells: monitoring wells GLACETN1–03 (50 ft deep) 

and GLACETN1–04 (89 ft deep), and public-supply well 

GLACETN1–05 (125 ft deep). All the wells in the glacetn1 

were sampled once in September 2015, and these data are 

included in this report and in Arnold and others (2018). Wells 

GLACETN1–01 and GLACETN1–02 also were sampled in 

2014 (Arnold and others, 2017a, b).

Mississippi Embayment Aquifer System 

Enhanced Trends Network (metxetn1)

The Mississippi Embayment aquifer system ETN (metxetn1; fig. 18A, E) was designed to study how water quality 

in shallow and deep parts of the regional aquifer changes in 

response to changing hydrologic conditions and pumping. The 

environmental setting of metxetn1 previously was described in 

Arnold and others (2017a, b) and is not repeated in this report.

The metxetn1 consists of one well in the shallow aquifer 

(METXETN1–02, 90 ft deep) and one well in the Memphis 

aquifer (METXETN1–01, 624 ft deep) (table 1). The wells 

were first sampled as part of the metxetn1 in 2013 (Arnold 

and others, 2016a, b) and again in 2014 (Arnold and others, 

2017a, b). Sampling in 2015 was approximately bimonthly 

between February and December 2015, and these data are 

included in this report and in Arnold and others (2018).

Northern Atlantic Coastal Plain Enhanced Trends 

Network (nacpetn1)

The Northern Atlantic Coastal Plain ETN (nacpetn1; 

fig. 18A, D) in the Northern Atlantic Coastal Plain aquifer 

system provides an opportunity to study the movement of 

contaminants from the land surface downward into aquifers 

and the effects of recharge and pumping on the temporal variability of water quality. The environmental setting of nacpetn1 

previously was described in Arnold and others (2017a, b) and 

is not repeated in this report.

The nacpetn1 has three wells that are located across 

southern Delaware in different parts of the flow system at different depths (table 1). Well NACPETN1–03 (119 ft deep) is 

a public-supply well in southwestern Delaware near the center 

of the Delmarva Peninsula. Well NACPETN1–02 (139 ft 

deep) also is a public-supply well, one of several supply wells 

for a coastal town. Well NACPETN1–01 is a shallow monitoring well (22 ft) that is surrounded locally by agricultural 

land use. All three wells in the nacpetn1 were sampled once in 

2014 (Arnold and others, 2017a, b) and once in August 2015. 

Data from the 2015 sampling are included in this report and in 

Arnold and others (2018).

New England Crystalline-Rock and Glacial 

Aquifer System Enhanced Trends Network 

(negxetn1)

The New England crystalline-rock and glacial aquifer 

system ETN (negxetn1, fig. 18A, C) provides the opportunity 

to study the temporal variability of contaminants in groundwater from geologic sources as well as contaminants from manmade sources with changing inputs. The environmental setting 

of negxetn1 previously was described in Arnold and others 

(2017a, b) and is not repeated in this report.

The negxetn1 consists of three wells at different depths 

(table 1). Two of the wells are public-supply wells, one 

completed in glacial sediments (NEGXETN1–01, 83 ft deep) 

and the other one completed in the crystalline-rock aquifer 

(NEGXETN1–02, 492 ft deep), and are in the southern part 

of the network area. The third well is a domestic-supply well 

in the northern part (NEGXETN1–03, 176 ft deep). Wells in 

the negxetn1 were first sampled in 2014 (Arnold and others, 

2017a, b). The wells were sampled bimonthly January through 

November 2015, and these data are included in this report and 

in Arnold and others (2018).

Rio Grande Aquifer System Enhanced Trends 

Network (rgaqetn1)

The Rio Grande aquifer system ETN (rgaqetn1; fig. 17A, 

D) provides the opportunity to study temporal variability in 

the water quality of shallow groundwater affected by irrigation, river water infiltration, and variable hydrologic conditions in an arid climate. The environmental setting of rgaqetn1 

previously was described in Arnold and others (2017a, b) and 

is not repeated in this report.

The rgaqetn1 consists of three wells completed in the 

valley fill at different depths (table 1): two shallow wells that 

are screened across the water table (RGAQETN1–01, 23 ft 

deep; and RGAQETN1–03, 22 ft deep) and one deeper well 

(RGAQETN1–02, 60 ft deep). The wells were first sampled 

as part of the rgaqetn1 in 2014 (Arnold and others, 2017a, b). 

The wells were sampled again in May 2015, and these data are 

included in this report and in Arnold and others (2018).

Vertical Flow-Path Study Networks

The VFPS networks are designed to evaluate changes 

in groundwater quality over longer periods of time than the 

enhanced trends networks (ETN) and decadal trends networks 

(LUS and MAS networks). The wells in a VFPS network are 

selected from public, domestic, or monitoring wells and are 

collocated so that there is a representation of wells at different depths within the area to be studied. Evaluating vertical 

gradients of groundwater age and contaminant concentrations 

facilitates the understanding of changes in groundwater quality 

over periods of time greater than 10 years. VFPS networks 
28 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

generally are sampled once. Data from the High Plains aquifer 

VFPS network (hpaqvfps1; fig. 19) are included in this report.

High Plains Aquifer Vertical Flow-Path Study 

Network (hpaqvfps1)

The High Plains aquifer VFPS network (hpaqvfps1; 

fig. 19) was designed to help address questions of changes 

in water quality over time. The hpaqvfps1 is in the Eastern 

Nebraska hydrogeologic unit of the High Plains aquifer, 

where the Ogallala formation is thin or absent (Stanton and 

Fahlquist, 2006; Stanton and Qi, 2007). The High Plains 

aquifer is described earlier in this report for the hpaqpas1. The 

hpaqvfps1 consists of 34 wells selected from 2 existing decadal 

trends networks: the agricultural LUS network, hpgwlusag3; 

and the MAS network, hpgwsus4. The hpgwlusag3 network 

was designed to assess the quality of shallow groundwater 

beneath an area of extensive irrigated agriculture in the northern High Plains aquifer; the primary crops grown were corn 

and soybeans (Stanton and Fahlquist, 2006). The hpgwlusag3 

network was last sampled in 2004. The hpgwsus4 network was 

designed to assess the quality of groundwater at the depth used 

for domestic supply in the Eastern Nebraska hydrogeologic 

unit. The hpgwsus4 was last sampled in 2003. The hpaqvfps1 

wells typically range in depth from 95 to 217 ft (appendix 1, 

table 1.1). The wells generally were open to the aquifer across 

intervals of 10 to 47 ft (appendix 1, table 1.2), but most were 

open to less than 20-ft intervals.

Sample Collection and Analysis

Water-quality data from samples collected at 502 wells 

(fig. 1; table 1) are available in Arnold and others (2018); 

500 wells were sampled January through December 2015, 

and 2 wells were sampled July through August 2013. Groundwater samples were collected and processed using methods 

designed to yield samples that were representative of environmental conditions, minimally affected by contamination, 

and consistent nationwide (Koterba and others, 1995; Lapham 

and others, 1995; USGS, variously dated). All samples were 

collected at the wellhead (the point at which the groundwater 

exits the well near land surface) or as close to the wellhead 

as possible. This location was selected so that samples were 

collected before any treatment or blending potentially could 

alter constituent concentrations. Samples were collected and 

processed using prescribed protocols described in Koterba 

and others (1995), Lapham and others (1995), and the USGS 

National Field Manual (USGS, variously dated). Samples 

were analyzed at the USGS National Water-Quality Laboratory (NWQL) in Denver, Colorado, for water-quality indicators, nutrients and dissolved organic carbon, major and minor 

ions, trace elements, VOCs, pesticides, radon radiochemistry, 

and one item of special interest, arsenic speciation. Four radionuclide constituent concentrations (lead–210, polonium–210, 

radium–224, and radium–226) were analyzed by TestAmerica 

in Richlands, Washington, in 2014 and by ALS Environmental in Fort Collins, Colo., in 2015. Perchlorate concentrations were analyzed by Weck Laboratories, Inc. in Industry, 

California. Hexavalent chromium (chromium [VI]) concentrations were analyzed by the USGS Trace Metal Laboratory in 

Boulder, Colo.

The constituents for which samples were collected are 

listed in table 2 of Arnold and others (2018) and are organized 

by constituent class; constituent primary uses and sources; 

analytical schedules and sampling period; analytical method 

references; USGS parameter codes; comparison thresholds; 

reporting levels; number of analyses, detections, and detections above the reporting level; and the table in which the 

data for the constituent class are shown. Analytical schedules 

are groups of constituents for which laboratory analysis is 

requested. The USGS parameter code identifies the constituents, and the method reference indicates the laboratory method 

used to analyze the samples. The reported concentration of a 

constituent can be evaluated using the comparison threshold 

value. Of the comparison thresholds listed in table 2 of Arnold 

and others (2018), only the secondary maximum contaminant 

level is not health based.

In addition to discrete water-quality samples that are 

collected periodically, the ETN wells also are instrumented to 

measure basic water-quality parameters at a high frequency 

during specific periods throughout each day. Each well is 

instrumented with a water-quality sonde that contains temperature, specific conductance, pH, and dissolved oxygen probes. 

Some wells also are instrumented to measure nitrate. The 

sonde sits in a flow-through chamber that receives groundwater flow from near the wellhead. Measurements of the basic 

water-quality parameters are made when the well is pumping and groundwater is flowing through the system, which 

may range from 1 to 24 hours per day. Water-quality data are 

recorded by the sonde at different intervals, from 2 minutes to 

12 hours, depending on the network. The water-quality data 

are transmitted to a data collection platform where the data are 

stored and transmitted to the USGS National Water Information System (USGS, 2017) database by the Geostationary 

Operational Environmental Satellite network. The high-frequency data are reviewed, corrected, and approved according 

to recommendations for publishing continuous water-quality 

records (Wagner and others, 2006).

Data Reporting

Several conventions are used for the constituent concentrations that are reported as not detected in water-quality 

samples (censored data or concentrations that are reported by 

the laboratory as less than a specified value). Inorganic constituents (major ions, nutrients, and trace elements) are reported 

using long-term method detection levels (LT–MDL) as the 

reporting levels. The LT–MDL is the smallest concentration 
Data Reporting 29

Platte River

Loup River

Big Blue River

Republican 

River

Big

West Fork

River

Blue

Little

River

Blue

 NEBRASKA

KANSAS

Columbus

Crete

Grand

Island

Hastings

Kearney

Schuyler

York Seward

04

01

10

11

12

13

14

15

16

17

18

19

02

20

21

22

23

24

25

26

27

28

29

03

30

31

32

33

34

05

06

07

08

09

Base from U.S. Geological Survey digital data, 1:1,000,000 and 1:2,000,000

Albers Equal-Area Conic projection

Standard parallels 29°30' N. and 45°30' N.

Central meridian 96°00' W.

North American Datum of 1983

0 10 20 30 MILES

0 10 20 30 KILOMETERS

99° 98°30' 98° 97°30' 97°

41°30'

41°

40°30'

40°

Map area

EXPLANATION

Sampled well and identification 

 number—See table 1 list for 

 network name hpaqvfps1

01

Figure 19. Study and wells sampled as part of the High Plains aquifer vertical flow-path study network (hpaqvfps1) for the U.S. 

Geological Survey National Water-Quality Assessment Project, April through August 2015.
30 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

that can be measured and reported with 99-percent confidence 

that the concentration is greater than zero (Childress and others, 1999). The LT–MDL is similar to a method detection level 

(MDL; U.S. Environmental Protection Agency [EPA], 2015) 

with the added characteristic that it is determined from statistical analysis of laboratory QC data during an extended period 

(Bonn, 2008). Organic constituents (VOCs and pesticides) are 

reported using laboratory reporting levels (LRLs). An LRL for 

a constituent is typically about two times greater than the LT–

MDL and is defined as the concentration at which the chance 

of a false negative error is 1 percent (Childress and others, 

1999). In other words, there is 99-percent confidence at the 

LRL that a constituent has been correctly reported as absent.

The LRL is more protective than the LT–MDL against the 

chance of false negative errors; that is, the chance of incorrectly reporting that a constituent is absent in a water sample 

when it actually is present. The LT–MDL is defined in terms 

of false positive errors. For concentrations near the LT–MDL, 

the chance of incorrectly reporting that a constituent is present 

in a water sample when it actually is absent is 1 percent; however, the chance of a false negative error (incorrectly reporting 

that the constituent is absent when it actually is present) at the 

LT–MDL is 50 percent. In contrast, the LRL has a 1-percent 

chance of a false negative error. In other words, if a value 

is reported as less than an LRL, there is only a very small 

chance that it is present at a concentration greater than the 

LRL, whereas if a value is reported as less than an LT–MDL, 

there is a 50-percent chance that it is present at a concentration 

near but above the LT–MDL. The LRLs are used for reporting analytical results for VOCs and pesticides to allow for the 

robust analysis and interpretation of detection frequencies. The 

NWQL uses information-rich analytical methods such as gas 

chromatography or high-performance liquid chromatography 

for these constituents and often provides results that indicate 

the presence of these constituents at concentrations less than 

their LRLs.

A few constituents (for example, nitrate plus nitrite) 

are reported using MDLs or minimum reporting levels. The 

MDLs are calculated according to the EPA definition of an 

MDL, described previously as the minimum concentration of 

a substance that can be measured and reported with 99-percent 

confidence that the value is above zero (Patton and Kryskalla, 

2011; EPA, 2015). A minimum reporting level is a reporting 

level that is chosen by the laboratory, but it is not necessarily 

associated with any specific method of determination or statistical certainty (Bonn, 2008).

Radionuclides are reported using units of radioactive 

activity (picocuries per liter) rather than concentration. Reporting levels for these constituents are based on the samplespecific critical level (ssLc

) or sample-specific minimum 

detectable concentrations (ssMDCs) (McCurdy and others, 

2008). The ssLc and ssMDC are calculated for each sample 

from parameter values used during the actual analysis of the 

sample. The ssLc and ssMDC are analogous to the LT–MDL 

and LRL, respectively. The ssLc is defined as the smallest 

measured activity that indicates detection of the radionuclide, 

with no more than a 5-percent chance of a false positive detection (EPA, 2004). The specified probability associated with a 

critical level can vary, but it is typically 5 percent for radionuclides. Like the LT–MDL, the ssLc is a reporting level that is 

based on a specified probability of false positive errors; that is, 

incorrectly reporting that the radionuclide is present when it is 

actually absent. The ssMDC, like the LRL, is a reporting level 

that is based on a specified probability of false negative errors; 

that is, failing to report that the radionuclide is present. The 

ssMDC is defined as the activity at which there is 5-percent 

chance of a false negative error and typically is about two 

times greater than the ssLc (McCurdy and others, 2008).

The analytical methods for pesticides and VOCs in 

schedules 2437, 4436, and 4437 (table 2 of Arnold and others, 

2018) are new methods that were still in the process of USGS 

approval when samples were analyzed. Results for laboratory 

methods that are unapproved generally are not made available 

to the public by the USGS because the quality of the results 

could be affected by problems subsequently discovered during 

the process of method approval. For schedules 2437, 4436, 

and 4437, the method approval process revealed no substantial 

problems and resulted in no changes in the analytical process 

(Duane Wydoski, USGS, written commun., 2015), thus indicating that the data reported before approval for these methods 

were of sufficient quality for public release. However, LRLs 

for individual compounds may be adjusted when additional 

QC data for the method are obtained and examined. The data 

from schedules 2437, 4436, and 4437 are reported relative to 

interim reporting levels, which are similar to LRLs. The analytical methods for pesticide schedule 2437 (Sandstrom and 

others, 2016), and VOC schedules 4436 and 4437 (Rose and 

others, 2016), were approved and published in 2016.

During the period that samples were being analyzed by 

the NWQL for the data presented in this report, the laboratory 

implemented a new procedure for determining and revising 

reporting and detection levels for various constituents as an 

alternative to the LT–MDL procedure (Williams and others, 

2015). The new procedure involves using ASTM International’s Standard Practice D6091–07 (ASTM International, 2014) 

and supporting DQCALC software to verify or revise detection limits and reporting limits each year. Like the LT–MDL, a 

detection limit set using DQCALC (referred to as DLDQC) is 

the smallest concentration that can be measured and reported 

with 99-percent confidence that the concentration is greater 

than zero (less than or equal to a 1-percent chance if a false 

positive). A reporting level set by DQCALC (referred to as 

RLDQC) is greater than or equal to two times the DLDQC and 

has a less than or equal to 1 percent chance of falsely reporting 

the results as a nondetection for a sample that actually contains 

the analyte.

Concentrations below LT–MDLs, and concentrations 

between LT–MDLs and LRLs, are reported without any 

qualifiers in this report. Concentrations below LT–MDLs or 

between LT–MDLs and LRLs can be identified by comparing the reported concentrations with the LT–MDLs and LRLs 

listed by compound in table 2 of Arnold and others (2018). 
Groundwater-Quality Data 31

It is important to note that there is greater uncertainty associated with values less than LT–MDLs (regarding risk of false 

positive errors or inaccurate detections) and with values less 

than LRLs (regarding risk of false negative values or inaccurate nondetections) than with values that are greater than 

LT–MDLs, LRLs, or both.

The data presented in this report and associated data 

release (Arnold and others, 2018) are current as of the date of 

retrieval (May 31, 2017) from the National Water Information System (USGS, 2017). However, results for individual 

constituents (also called parameters) may be updated at a 

later date to correct a previously undetected error or to reflect 

improved information about the performance of a laboratory 

method. For example, LRLs may be adjusted when additional 

QC data for the method are examined. The well information 

and water-quality data presented in this report and the associated data release were reviewed by USGS personnel and 

subsequently verified by coauthors who are responsible for 

tracking the data.

Quality-Assurance and Quality-Control 

Methods

The quality-assurance plan for NAWQA Project groundwater samples was derived from previous NAWQA Project 

cycles of study (Koterba and others, 1995) and the USGS 

National Field Manual (USGS, variously dated). About 

14 percent of samples collected during any period are for 

data quality assurance and QC. Types of QC samples include 

equipment blanks, source solution blanks, field blanks, replicates, field spikes, and laboratory spikes. Data and results 

from statistical analysis of blank QC samples are presented in 

appendix 3 (tables 3.1 and 3.2).

Blanks are used to test for bias from an unintentional 

introduction of contamination to environmental samples. 

Equipment blanks are used to test whether equipment is clean 

and free of contamination. Source solution blanks are used 

to test whether the water used for the blank sample is free of 

contamination. Field blanks are used to test for contamination 

that may be introduced during sample collection, processing, 

handling, and analysis. Field blanks also are used to test for 

contamination from the environment around where the sample 

was collected. Replicates are samples that are collected at the 

same time and using the same method as the environmental 

sample. Replicates measure the variability of determining a 

concentration in samples that should be essentially identical. 

Spiked samples are used to measure the performance of analytical methods on an environmental water sample. A sample 

can be spiked in the field or the laboratory.

The number and type of QC samples planned for each 

network study depend on the number of wells sampled, the 

number of sampling teams that are involved in the sampling, 

and the constituents for which samples will be analyzed, as 

described in the following criteria:

• Equipment blanks are collected for nutrients, trace elements, and VOCs at the quantity of one blank for each 

team sampling the network.

• Source solution blanks are collected for nutrients, trace 

elements, and VOCs at the quantity of one blank for 

each team sampling the network. The VOCs have additional source solution blanks that are collected with 

each field blank.

• Field blanks are collected for major ions, nutrients, dissolved organic carbon, trace elements, and pesticides 

at the quantity of 1 blank for every 15 wells sampled 

or 1 blank for each team sampling the network 

(whichever results in a greater number of blanks). 

Field blanks are collected for VOCs at the quantity of 

1 blank for every 10 wells sampled or 1 blank for each 

team sampling the network (whichever results in a 

greater number of blanks).

• Replicate samples are collected for major ions, nutrients, dissolved organic carbon, trace elements, VOCs, 

and radionuclides at the quantity of 1 replicate for 

every 30 wells sampled. Replicate samples are collected for pesticides at the quantity of 1 replicate for 

every 15 wells.

• Field spikes are collected for pesticides at the quantity 

of 1 spike sample for every 30 wells sampled.

• Laboratory spikes are collected for VOCs at the quantity of 1 spike sample for every 30 wells sampled.

Statistical analysis of QC sample data can be used to 

evaluate the variability or bias of the data, sampling and 

sample handling procedures, and laboratory and (or) field 

methods and to ensure the environmental assessment samples 

represent true groundwater chemistry. The QC sample data 

provided in Arnold and others (2018) include water quality for 

all blank QC samples collected between January and December 2015 in association with the environmental sample data 

and a few results from earlier sampling periods that were not 

previously published. Data from the 2012–13 sampling period 

are presented in Arnold and others (2016a, b), and data from 

the 2014 sampling period are presented in Arnold and others 

(2017a, b).

Groundwater-Quality Data

Groundwater-quality data from 502 wells are included in 

this report. Groundwater samples were collected at 500 wells 

between January and December 2015 and at 2 wells between 

July and August 2013 (table 1). Samples were analyzed for 

about 380 constituents (table 2 of Arnold and others, 2018); 

however, not all wells were sampled for all constituents. 

Results of analyses are presented in tables 3–12 of Arnold 

and others (2018), which are organized by constituent class: 
32 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

water-quality indicators (table 3); nutrients and dissolved 

organic carbon (table 4); major and minor ions (table 5); trace 

elements (table 6); VOCs (tables 7); pesticides (table 8); radiochemistry (table 9); and special-interest constituents, including 

arsenic speciation (table 10), chromium (VI) (table 11), and 

perchlorate (table 12). The constituents for which samples 

were analyzed and the table in which the data are presented 

are listed in table 2 of Arnold and others (2018). Comparative 

benchmarks (thresholds) listed in that table provide context 

for evaluating the constituent concentration data in terms of 

human health and other characteristics relevant for drinkingwater use. Several types of thresholds are listed. The EPA 

maximum contaminant levels are legally enforceable drinkingwater standards that specify the maximum permissible level of 

a constituent that can be delivered to a user of a public water 

system. The EPA human-health benchmarks for pesticides 

(HHBPs) are nonenforceable screening levels for evaluating if 

a pesticide concentration in drinking-water sources may indicate a potential human-health risk (EPA, 2012). The HHBPs 

include benchmarks for cancer and noncancer health effects 

(EPA, 2013). The USGS Health-Based Screening Levels are 

nonenforceable benchmarks for constituents that do not have 

MCLs or HHBPs that can be used to evaluate if constituent 

concentrations may indicate a potential human-health concern (Toccalino, 2007; Toccalino and others, 2014). Like EPA 

HHBPs, USGS health-based screening levels are categorized 

in terms of cancer and noncancer health effects.

The groundwater-quality data from January to December 

2015 are presented in the format of tab-delimited ASCII text 

files and are available for download from Arnold and others 

(2018) along with complete metadata files that describe the 

contents of each text file. In addition to the complete metadata, 

each data file includes header lines that describe the source 

of the file. Header lines in the data files are indicated by the 

pound symbol (#), and the last line of the header is numbered. 

The first line after the header contains the column names for 

the tab-delimited data columns. The data may be imported into 

spreadsheet, database, or statistical software for manipulation and analysis. The data available from Arnold and others 

(2018) are referenced as tables 1–12 and appendix tables 3.3–

3.10 in this report.

Water-Quality Indicators

Water-quality indicators include water temperature, dissolved oxygen, specific conductance, pH, alkalinity, carbonate 

and bicarbonate (calculated from alkalinity), and turbidity 

(table 3 of Arnold and others, 2018). Water-quality indicators 

are measured in the field when the other water samples are 

collected (USGS, variously dated), and pH and specific conductance sometimes are also measured in the laboratory.

Water-quality indicators provide basic information about 

the general quality and geochemical conditions of the water. 

Dissolved oxygen is the concentration of oxygen dissolved in 

the water and is an indicator of reduction-oxidation (redox) 

conditions in the aquifer. Measurements of pH indicate the 

acidity or basicity of water. Dissolved oxygen and pH are 

important controls on the chemical reactions that can happen 

in water. Specific conductance is a measure of how well the 

water conducts electricity and indicates the relative amount of 

dissolved solids in the water. Alkalinity, carbonate, and bicarbonate indicate the hardness of water and are related to pH. 

Turbidity is a measure of the suspended solids in the water.

Inorganic Constituents

Inorganic constituents are most often naturally present 

in groundwater. Groundwater samples were analyzed for the 

following inorganic constituent classes: major and minor ions, 

nutrients and dissolved organic carbon, and trace elements 

(including metals; tables 4–6 of Arnold and others, 2018).

Nutrients include nitrogen and phosphorus compounds 

and dissolved organic carbon. Data for ammonia, nitrate plus 

nitrite, nitrite, total nitrogen, and phosphorus measured as 

orthophosphate are presented in table 4 of Arnold and others 

(2018). Nutrients are present naturally, but nutrient concentrations also are affected by human activities such as farming and 

wastewater disposal (Hem, 1992). Nitrogen was measured as 

total nitrogen and as the individual nitrogen species of nitrite, 

nitrate, and ammonia. Nutrient concentrations can affect the 

quality of groundwater for use as drinking water.

Major and minor ions are cations and anions that can be 

dissolved in water from geologic materials. Concentrations of 

major and minor ions can be used to classify water into different types (Hem, 1992; Hiscock, 2005). Waters with similar 

ion concentrations often have similar history, recharge areas, 

climate, mineralogy, and residence time (Güler and others, 

2002). Some major ions can affect the quality of water for 

drinking and other uses. Groundwater samples were analyzed 

for 10 major and minor ions and total dissolved solids (table 5 

of Arnold and others, 2018).

Trace elements consist of metals that are usually present in the environment in very small quantities (Hem, 1992). 

Trace elements often are dissolved in water from geologic 

materials, but concentrations of these elements also can be 

affected human activities such as mining. Many trace elements 

can affect the quality of groundwater for use as drinking water. 

Groundwater samples were analyzed for 22 trace elements 

(table 6 of Arnold and others, 2018).

Organic Compounds

Organic compounds are man-made chemicals and include 

VOCs and pesticides. VOCs are chemicals that tend to evaporate into the air and are in a variety of substances including 

disinfectants, solvents, paint, fumigants, asphalt, and fuel 

additives (Zogorski and others, 2006). Pesticides are chemical 

compounds used to control plant or insect pests and include 

fungicides, herbicides, and insecticides (Gilliom and others, 

2006). Many VOCs and pesticides, if present, can affect the 
Acknowledgments 33

quality of groundwater used for drinking water. Groundwater 

samples from 2015 were analyzed for 85 VOCs and 227 pesticides (tables 7 and 8 of Arnold and others, 2018).

Radiochemistry

Radiochemical constituents include radionuclides and 

measurements of radioactivity. Radionuclides are chemical 

constituents that are produced naturally by the decay of radioactive parent elements such as uranium and thorium. Sources 

of radionuclides in groundwater are geologic material such 

as rocks and soils (Hem, 1992). Radionuclides and measurements of radioactivity included in this report are α radioactivity, β radioactivity, radon (a dissolved gas), several isotopes of 

radium (radium-224, radium-226, and radium-228), polonium-210, and lead-210 (table 9 of Arnold and others, 2018). 

Uranium, which also is a radionuclide, is included with trace 

elements (table 6 of Arnold and others, 2018) because uranium 

is measured in units of mass concentration rather than as units 

of radioactivity. In total, groundwater samples were analyzed 

for eight radionuclides and measures of radioactivity.

Constituents of Special Interest

Several constituents of special interest were included 

for selected networks. Constituents of special interest were 

arsenic species (arsenate, arsenite, monomethylarsonate, and 

dimethylarsinate), which are derived from arsenic, hexavalent 

chromium (chromium [VI]), and perchlorate (tables 10–12 of 

Arnold and others, 2018). Arsenic and chromium are predominantly natural in origin but may have localized anthropogenic 

sources. Anthropogenic arsenic uses include metal and ore 

processing, glass production, fossil fuel combustion, wood 

preservatives, pesticides, semiconductor production, and 

pharmaceuticals (Garelick and others, 2008). Hexavalent chromium is chromium in the +6 oxidation state (six electrons lost 

from the atom) and is used in textile dyes, wood preservation, 

anticorrosive agents, and other surface coatings (Nriagu and 

Niebor, 1988). Geochemical conditions such as redox and pH 

affect the speciation of chromium and arsenic in groundwater 

(Hem, 1992). Most arsenic and chromium in groundwater is 

from geologic sources in rocks and soils. Perchlorate is an 

inorganic constituent used in rocket fuels, fireworks, safety 

flares, and other products; it is present in some fertilizers and 

may be present naturally at low concentrations in groundwater 

(Srinivasan and Sorial, 2009; Jackson and others, 2015).

Summary

As part of the third decadal cycle of the U.S. Geological 

Survey National Water-Quality Assessment Project, groundwater-quality data are being collected from well networks 

to assess water-quality conditions in the Nation’s principal 

aquifers and investigate changes in groundwater-quality conditions in selected land use and hydrogeologic settings. Groundwater-quality data are published in annual data series reports, 

of which this report is the third in the series.

Groundwater-quality data from 502 wells were collected 

from 5 types of well networks: principal aquifer study networks, land-use study networks, major aquifer study networks, 

enhanced trends networks, and vertical flow-path study networks. Within principal aquifer, land-use, and major aquifer 

study networks, study areas were divided into equal-area grids 

and wells were selected for sampling using a stratified random 

sampling design. The number of wells in principal aquifer 

networks ranged from about 20 to 63 wells per network for the 

studies included in this report. About 30 wells typically made 

up each land-use or major aquifer study network. Enhanced 

trends networks that were sampled in 2015 consisted of two to 

five wells that were selected at locations within aquifers where 

temporal changes in groundwater quality might be expected. 

One vertical flow-path study network was sampled in 2015.

Groundwater samples were analyzed for water-quality 

indicators and constituents, including nutrients, major and 

minor ions, trace elements, volatile organic compounds, pesticides, radiochemistry, and select special-interest constituents 

such as arsenic speciation, hexavalent chromium, and perchlorate. These groundwater-quality data are tabulated in this 

report and associated data release. Quality-control samples 

were collected along with environmental samples, and data 

from blank quality-control samples also are included in this 

report. The data release includes data collected during 2015 

and previously unpublished data from a few environmental 

samples collected in 2013 and a few quality-control samples 

collected in 2014. These previously unpublished data are associated with networks described in this report.

Acknowledgments

Many people in addition to the authors participated in 

providing information for this report. Bryant Jurgens and Tyler 

Johnson (both with the U.S. Geological Survey) provided tools 

for data compilation. Personnel in U.S. Geological Survey 

Water Science Centers, too numerous to name individually, 

collected, packaged, and shipped water samples to the laboratories for analysis and ensured results were entered into the 

U.S. Geological Survey National Water Information System.
34 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

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detection limit—revision 1.11: U.S. Code of Federal Regulations, Title 40, v. 24, pt. 136, app. B, accessed May 14, 

2015, at http://www.gpo.gov/fdsys/pkg/CFR-2012-title40-

vol24/pdf/CFR-2012-title40-vol24-part136-appB.pdf.

U.S. Geological Survey [USGS], 2003, Principal aquifers of 

the 48 conterminous United States, Hawaii, Puerto Rico, 

and the U.S. Virgin Islands: U.S. Geological Survey, digital 

data, accessed January 4, 2016, at http://water.usgs.gov/

GIS/metadata/usgswrd/XML/aquifers_us.xml.

U.S. Geological Survey [USGS], 2017, National Water 

Information System—Web interface: U.S. Geological 

Survey, accessed May 31, 2017, at https://doi.org/10.5066/

F7P55KJN.

U.S. Geological Survey [USGS], variously dated, National 

field manual for the collection of water-quality data: 

U.S. Geological Survey Techniques of Water-Resources 

Investigations, book 9, chaps. A1–A9, accessed January 4, 

2016, at https://pubs.water.usgs.gov/twri9A.

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, 

B.A., 2006, Guidelines and standard procedures for continuous water-quality monitors—Station operation, record 

computation, and data reporting: U.S. Geological Survey 

Techniques and Methods, book 1, chap. D3, 51 p., accessed 

January 4, 2016, at https://pubs.usgs.gov/tm/2006/tm1D3/.

Wangsness, D.J., 1997, The National Water-quality Assessment Program—Example of study unit design for the 

Apalachicola–Chattahoochee–Flint River Basin in Georgia, 

Alabama, and Florida, 1991–97: U.S. Geological Survey 

Open-File Report 97–48, 29 p., accessed September 14, 

2017, at https://pubs.usgs.gov/of/1997/ofr97-048/.

Whitehead, R.L., 1994, Ground water atlas of the United 

States—Idaho, Oregon, Washington: U.S. Geological Survey Hydrologic Atlas 730–H, accessed January 4, 2016, at 

https://pubs.usgs.gov/ha/ha730/ch_h/index.html.

Williams, Teresa, Foreman, W.T., Decess, Jessica, ReedParker, Carmen, and Stevenson, D.L., 2015, Changes to 

National Water Quality Laboratory (NWQL) procedures 

used to establish and verify laboratory detection and 

reporting limits: U.S. Geological Survey, National Water 

Quality Laboratory Technical Memorandum 15.02, 21 p., 

accessed January 4, 2016, at https://nwql.usgs.gov/Public/

tech_memos/nwql.2015-02.pdf.

Williams, L.J., and Kuniansky, E.L., 2016, Revised hydrogeologic framework of the Floridan aquifer system in Florida 

and parts of Georgia, Alabama, and South Carolina (ver 1.1, 

March 2016): U.S. Geological Survey Professional Paper 

1807, 140 p., 23 pls., accessed February 28, 2018, at https://

doi.org/10.3133/pp1807.
38 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Zagorsky, J.S., Carter, J.M., Ivahnenko, Tamara, Lapham, 

W.W., Moran, M.J., Rowe, B.L., Squillace, P.J., and Toccalino, P.L., 2006, The quality of our Nation’s waters—

Volatile organic compounds in the Nation’s ground water 

and drinking-water supply wells: U.S. Geological Survey 

Circular 1292, 101 p., accessed January 4, 2016, at http://

pubs.usgs.gov/circ/circ1292/.
Table 1
40 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report. [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface acfbsus1 ACFBSUS1–01 01 MAS Alabama Floridan aquifer system 95 65 95 acfbsus1 ACFBSUS1–02 02 MAS Alabama Floridan aquifer system 118 72 118 acfbsus1 ACFBSUS1–03 03 MAS Georgia Floridan aquifer system 80 72 80 acfbsus1 ACFBSUS1–04 04 MAS Georgia Floridan aquifer system 72 60 72 acfbsus1 ACFBSUS1–05 05 MAS Georgia Floridan aquifer system 220 130 220 acfbsus1 ACFBSUS1–06 06 MAS Georgia Floridan aquifer system 85 82 85 acfbsus1 ACFBSUS1–07 07 MAS Georgia Floridan aquifer system 181 41 181 acfbsus1 ACFBSUS1–08 08 MAS Georgia Floridan aquifer system 64 35 64 acfbsus1 ACFBSUS1–09 09 MAS Georgia Floridan aquifer system 138 55 138 acfbsus1 ACFBSUS1–10 10 MAS Georgia Floridan aquifer system 125 61 125 acfbsus1 ACFBSUS1–11 11 MAS Georgia Floridan aquifer system 245 70 200 acfbsus1 ACFBSUS1–12 12 MAS Georgia Floridan aquifer system 123 58 122.5 acfbsus1 ACFBSUS1–13 13 MAS Georgia Floridan aquifer system 225 62 225 acfbsus1 ACFBSUS1–14 14 MAS Georgia Floridan aquifer system 218 54 218 acfbsus1 ACFBSUS1–15 15 MAS Georgia Floridan aquifer system 98.5 62 98.5 acfbsus1 ACFBSUS1–16 16 MAS Georgia Floridan aquifer system 75 63 75 acfbsus1 ACFBSUS1–17 17 MAS Georgia Floridan aquifer system 370 120 370 acfbsus1 ACFBSUS1–18 18 MAS Georgia Floridan aquifer system 169 157.7 169 acfbsus1 ACFBSUS1–19 19 MAS Georgia Floridan aquifer system 100 75 100 acfbsus1 ACFBSUS1–20 20 MAS Georgia Floridan aquifer system na na na acfbsus1 ACFBSUS1–21 21 MAS Georgia Floridan aquifer system 105 42 105 acfbsus1 ACFBSUS1–22 22 MAS Georgia Floridan aquifer system 250 100 250 acfbsus1 ACFBSUS1–23 23 MAS Florida Floridan aquifer system 234 110 234 acfbsus1 ACFBSUS1–24 24 MAS Florida Floridan aquifer system 200 150 200

acfbsus1 ACFBSUS1–25 25 MAS Florida Floridan aquifer system 160 80 160acfbsus1 ACFBSUS1–26 26 MAS Florida Floridan aquifer system 115 98 115acfbsus1 ACFBSUS1–27 27 MAS Florida Floridan aquifer system 180 128 180
Table 1 41

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

bnrcpas1 BNRCPAS1–01 01 PAS Arizona Basin and Range carbonate-rock aquifers 520 na 520*bnrcpas1 BNRCPAS1–02 02 PAS Arizona Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–03 03 PAS Nevada Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–04 04 PAS Nevada Basin and Range carbonate-rock aquifers 350 50 350bnrcpas1 BNRCPAS1–05 05 PAS Nevada Basin and Range carbonate-rock aquifers 565 205 565bnrcpas1 BNRCPAS1–06 06 PAS Nevada Basin and Range carbonate-rock aquifers 291 na 291*bnrcpas1 BNRCPAS1–07 07 PAS Utah Basin and Range carbonate-rock aquifers 980 696 736bnrcpas1 BNRCPAS1–08 08 PAS Utah Basin and Range carbonate-rock aquifers 520 480 520bnrcpas1 BNRCPAS1–09 09 PAS Utah Basin and Range carbonate-rock aquifers 280 200 280bnrcpas1 BNRCPAS1–10 10 PAS Utah Basin and Range carbonate-rock aquifers 721 178 710bnrcpas1 BNRCPAS1–11 11 PAS Utah Basin and Range carbonate-rock aquifers 269 149 269bnrcpas1 BNRCPAS1–12 12 PAS Utah Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–13 13 PAS Utah Basin and Range carbonate-rock aquifers 525 100 505bnrcpas1 BNRCPAS1–14 14 PAS Utah Basin and Range carbonate-rock aquifers 620 420 620bnrcpas1 BNRCPAS1–15 15 PAS Utah Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–16 16 PAS Utah Basin and Range carbonate-rock aquifers 1,205 695 1,205 bnrcpas1 BNRCPAS1–17 17 PAS Idaho Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–18 18 PAS Idaho Basin and Range carbonate-rock aquifers na na nabnrcpas1 BNRCPAS1–19 19 PAS Idaho Basin and Range carbonate-rock aquifers 382 302 382bnrcpas1 BNRCPAS1–20 20 PAS Idaho Basin and Range carbonate-rock aquifers na na naccptlusor1b CCPTLUSOR1B–01 01 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 42 37 42ccptlusor1b CCPTLUSOR1B–02 02 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 30 24.5 29.5ccptlusor1b CCPTLUSOR1B–03 03 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 28 17.5 27.5ccptlusor1b CCPTLUSOR1B–04 04 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 28 23 28ccptlusor1b CCPTLUSOR1B–05 05 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 56 50.4 55.6ccptlusor1b CCPTLUSOR1B–06 06 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 49 43.5 48.5ccptlusor1b CCPTLUSOR1B–07 07 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 25 19.5 24.5ccptlusor1b CCPTLUSOR1B–08 08 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 28 23 28
42 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface ccptlusor1b CCPTLUSOR1B–09 09 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 23 18 23 ccptlusor1b CCPTLUSOR1B–10 10 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 70 64 69 ccptlusor1b CCPTLUSOR1B–11 11 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 73 68 73 ccptlusor1b CCPTLUSOR1B–12 12 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 15 10 15 ccptlusor1b CCPTLUSOR1B–13 13 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 19 14 19 ccptlusor1b CCPTLUSOR1B–14 14 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 24 19 24 ccptlusor1b CCPTLUSOR1B–15 15 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 19 14 19 ccptlusor1b CCPTLUSOR1B–16 16 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 33 28 33 ccptlusor1b CCPTLUSOR1B–17 17 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 34 28.5 33.5 ccptlusor1b CCPTLUSOR1B–18 18 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 73 67.3 72.8 ccptlusor1b CCPTLUSOR1B–19 19 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 29 24 29 ccptlusor1b CCPTLUSOR1B–20 20 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 25 20 25 ccptlusor1b CCPTLUSOR1B–21 21 LUS Washington Columbia Plateau basin-fill and basaltic-rock aquifers 90 80 90 clptetn1 CLPTETN1–01 01 ETN Oregon Columbia Plateau basin-fill and basaltic-rock aquifers 80 79 80 clptetn1 CLPTETN1–04 04 ETN Oregon Columbia Plateau basin-fill and basaltic-rock aquifers 1,116 926 1,100 clptetn1 CLPTETN1–06 06 ETN Oregon Columbia Plateau basin-fill and basaltic-rock aquifers 40 na 40* cnbrluscr1 CNBRLUSCR1–01 01 LUS Nebraska Glacial aquifer system 25 15 25 cnbrluscr1 CNBRLUSCR1–02 02 LUS Nebraska Glacial aquifer system 17 7 17 cnbrluscr1 CNBRLUSCR1–03 03 LUS Nebraska Glacial aquifer system 32 22 32 cnbrluscr1 CNBRLUSCR1–04 04 LUS Nebraska Glacial aquifer system 30 20 25 cnbrluscr1 CNBRLUSCR1–05 05 LUS Nebraska Glacial aquifer system 45 35 45 cnbrluscr1 CNBRLUSCR1–06 06 LUS Nebraska Glacial aquifer system 35 29.8 34.8 cnbrluscr1 CNBRLUSCR1–07 07 LUS Nebraska Glacial aquifer system 39 34 39 cnbrluscr1 CNBRLUSCR1–08 08 LUS Nebraska Glacial aquifer system 22 17 22

cnbrluscr1 CNBRLUSCR1–09 09 LUS Nebraska Glacial aquifer system 15 10 15cnbrluscr1 CNBRLUSCR1–10 10 LUS Nebraska Glacial aquifer system 65 60 65cnbrluscr1 CNBRLUSCR1–11 11 LUS Nebraska Glacial aquifer system 35 25 35cnbrluscr1 CNBRLUSCR1–12 12 LUS Nebraska Glacial aquifer system 20 15 20
Table 1 43

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

cnbrluscr1 CNBRLUSCR1–13 13 LUS Nebraska Glacial aquifer system 53** 48 53cnbrluscr1 CNBRLUSCR1–14 14 LUS Nebraska Glacial aquifer system 29 24 29cnbrluscr1 CNBRLUSCR1–15 15 LUS Nebraska Glacial aquifer system 65 55 65cnbrluscr1 CNBRLUSCR1–16 16 LUS Nebraska Glacial aquifer system 32 27 32cnbrluscr1 CNBRLUSCR1–17 17 LUS Nebraska Glacial aquifer system 20 15 20cnbrluscr1 CNBRLUSCR1–18 18 LUS Nebraska Glacial aquifer system 24 13.5 23.5cnbrluscr1 CNBRLUSCR1–19 19 LUS Nebraska Glacial aquifer system 45 40 45cnbrluscr1 CNBRLUSCR1–20 20 LUS Nebraska Glacial aquifer system 60 50 60cnbrluscr1 CNBRLUSCR1–21 21 LUS Nebraska Glacial aquifer system 25 15 25cnbrluscr1 CNBRLUSCR1–22 22 LUS Nebraska Glacial aquifer system 25 20 25cnbrluscr1 CNBRLUSCR1–23 23 LUS Nebraska Glacial aquifer system 39 29 39cnbrluscr1 CNBRLUSCR1–24 24 LUS Nebraska Glacial aquifer system 30 19.5 29.5cnbrluscr1 CNBRLUSCR1–25 25 LUS Nebraska Glacial aquifer system 57 52 57cnbrluscr1 CNBRLUSCR1–26 26 LUS Nebraska Glacial aquifer system 25 19.5 24.5cnbrluscr1 CNBRLUSCR1–27 27 LUS Nebraska Glacial aquifer system 73 68 73cvaletn1 CVALETN1–01 01 ETN California Central Valley aquifer system 620 410 610cvaletn1 CVALETN1–02 02 ETN California Central Valley aquifer system 320 160 310cvaletn1 CVALETN1–03 03 ETN California Central Valley aquifer system 234 214 224edtretn1 EDTRETN1–01 01 ETN Texas Edwards-Trinity aquifer system 550 317 550edtretn1 EDTRETN1–02 02 ETN Texas Edwards-Trinity aquifer system 300 220 300edtretn1 EDTRETN1–03 03 ETN Texas Edwards-Trinity aquifer system 1,550 1,320 1,550 florpas1 FLORPAS1–01 01 PAS Georgia Floridan aquifer system na na naflorpas1 FLORPAS1–02 02 PAS Georgia Floridan aquifer system 168 111 168florpas1 FLORPAS1–03 03 PAS Georgia Floridan aquifer system na na naflorpas1 FLORPAS1–04 04 PAS Georgia Floridan aquifer system na na naflorpas1 FLORPAS1–05 05 PAS Georgia Floridan aquifer system na na naflorpas1 FLORPAS1–06 06 PAS Georgia Floridan aquifer system 400 157 400florpas1 FLORPAS1–07 07 PAS Georgia Floridan aquifer system 775 470 775
44 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface florpas1 FLORPAS1–08 08 PAS Georgia Floridan aquifer system 840 501 840 florpas1 FLORPAS1–09 09 PAS Georgia Floridan aquifer system na na na florpas1 FLORPAS1–10 10 PAS Georgia Floridan aquifer system na na na florpas1 FLORPAS1–11 11 PAS Georgia Floridan aquifer system na na na florpas1 FLORPAS1–12 12 PAS Georgia Floridan aquifer system 525 250 525 florpas1 FLORPAS1–13 13 PAS Georgia Floridan aquifer system 576 262 576 florpas1 FLORPAS1–14 14 PAS Georgia Floridan aquifer system 590 na 590* florpas1 FLORPAS1–15 15 PAS Georgia Floridan aquifer system 289 210 289 florpas1 FLORPAS1–16 16 PAS Georgia Floridan aquifer system na na na florpas1 FLORPAS1–17 17 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–18 18 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–19 19 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–20 20 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–21 21 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–22 22 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–23 23 PAS Florida Floridan aquifer system 170 114 170* florpas1 FLORPAS1–24 24 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–25 25 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–26 26 PAS Florida Floridan aquifer system 621 304 621* florpas1 FLORPAS1–27 27 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–28 28 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–29 29 PAS Florida Floridan aquifer system 578 248 578* florpas1 FLORPAS1–30 30 PAS Florida Floridan aquifer system na na na florpas1 FLORPAS1–31 31 PAS Florida Floridan aquifer system na na na

florpas1 FLORPAS1–32 32 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–33 33 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–34 34 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–35 35 PAS Florida Floridan aquifer system na na na
Table 1 45

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

florpas1 FLORPAS1–36 36 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–37 37 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–38 38 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–39 39 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–40 40 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–41 41 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–42 42 PAS Florida Floridan aquifer system 140 na 140*florpas1 FLORPAS1–43 43 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–44 44 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–45 45 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–46 46 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–47 47 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–48 48 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–49 49 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–50 50 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–51 51 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–52 52 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–53 53 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–54 54 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–55 55 PAS Florida Floridan aquifer system 265 85 265*florpas1 FLORPAS1–56 56 PAS Florida Floridan aquifer system na na naflorpas1 FLORPAS1–57 57 PAS South 

Carolina

Floridan aquifer system 195 135 180

florpas1 FLORPAS1–58 58 PAS South 

Carolina

Floridan aquifer system 200 123 200

florpas1 FLORPAS1–59 59 PAS Alabama Floridan aquifer system 204 na 204*florpas1 FLORPAS1–60 60 PAS Alabama Floridan aquifer system 700 630 660
46 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface gaflluscr1 GAFLLUSCR1–01 01 LUS Georgia Surficial aquifer system 24 13.5 23.5 gaflluscr1 GAFLLUSCR1–02 02 LUS Georgia Surficial aquifer system 31 21 31 gaflluscr1 GAFLLUSCR1–03 03 LUS Georgia Surficial aquifer system 17 7 17 gaflluscr1 GAFLLUSCR1–04 04 LUS Georgia Surficial aquifer system 22 12 22 gaflluscr1 GAFLLUSCR1–05 05 LUS Georgia Surficial aquifer system 57 46 56 gaflluscr1 GAFLLUSCR1–06 06 LUS Georgia Surficial aquifer system 32 21.3 31.3 gaflluscr1 GAFLLUSCR1–07 07 LUS Georgia Surficial aquifer system 32 21.3 31.3 gaflluscr1 GAFLLUSCR1–08 08 LUS Georgia Surficial aquifer system 27 16.3 26.3 gaflluscr1 GAFLLUSCR1–09 09 LUS Georgia Surficial aquifer system 19 9 19 gaflluscr1 GAFLLUSCR1–10 10 LUS Georgia Surficial aquifer system 32 21.5 31.5 gaflluscr1 GAFLLUSCR1–11 11 LUS Georgia Surficial aquifer system 45 30 40 gaflluscr1 GAFLLUSCR1–12 12 LUS Georgia Surficial aquifer system 30 20 30 gaflluscr1 GAFLLUSCR1–13 13 LUS Georgia Surficial aquifer system 40 20 40 gaflluscr1 GAFLLUSCR1–14 14 LUS Georgia Surficial aquifer system 20 10 20 gaflluscr1 GAFLLUSCR1–15 15 LUS Georgia Surficial aquifer system 25 15 25 gaflluscr1 GAFLLUSCR1–16 16 LUS Georgia Surficial aquifer system 45 30 40 gaflluscr1 GAFLLUSCR1–17 17 LUS Georgia Surficial aquifer system 65 35 65 gaflluscr1 GAFLLUSCR1–18 18 LUS Georgia Surficial aquifer system 20 10 20 gaflluscr1 GAFLLUSCR1–19 19 LUS Georgia Surficial aquifer system 29 19 29 gaflluscr1 GAFLLUSCR1–20 20 LUS Georgia Surficial aquifer system 41 25 35 gaflluscr1 GAFLLUSCR1–21 21 LUS Georgia Surficial aquifer system 70 40 70 gaflluscr1 GAFLLUSCR1–22 22 LUS Georgia Surficial aquifer system 37 27 37 gaflluscr1 GAFLLUSCR1–23 23 LUS Georgia Surficial aquifer system 49 38.5 48.5 gaflluscr1 GAFLLUSCR1–24 24 LUS Georgia Surficial aquifer system 64 53.5 63.5

gaflluscr1 GAFLLUSCR1–25 25 LUS Georgia Surficial aquifer system 51 26 46gaflluscr1 GAFLLUSCR1–26 26 LUS Georgia Surficial aquifer system 37 21 36glacetn1 GLACETN1–01 01 ETN Wisconsin Glacial aquifer system 83 80 83glacetn1 GLACETN1–02 02 ETN Wisconsin Glacial aquifer system 35 24.5 34.5
Table 1 47

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

glacetn1 GLACETN1–03 03 ETN Wisconsin Glacial aquifer system 50 45.1 50.1glacetn1 GLACETN1–04 04 ETN Wisconsin Glacial aquifer system 89 84 89glacetn1 GLACETN1–05 05 ETN Wisconsin Glacial aquifer system 125 na 125*hpaqpas1 HPAQPAS1–01 01 PAS New Mexico High Plains aquifer 220 195 220*hpaqpas1 HPAQPAS1–02 02 PAS New Mexico High Plains aquifer 200 85 195hpaqpas1 HPAQPAS1–03 03 PAS New Mexico High Plains aquifer 133 67 132.5hpaqpas1 HPAQPAS1–04 04 PAS New Mexico High Plains aquifer 110 na 110*hpaqpas1 HPAQPAS1–05 05 PAS Colorado High Plains aquifer 145 105 145hpaqpas1 HPAQPAS1–06 06 PAS Colorado High Plains aquifer 307 245 305hpaqpas1 HPAQPAS1–07 07 PAS Colorado High Plains aquifer 245 195 245hpaqpas1 HPAQPAS1–08 08 PAS Colorado High Plains aquifer 150 132 150hpaqpas1 HPAQPAS1–09 09 PAS Colorado High Plains aquifer 355 291 355hpaqpas1 HPAQPAS1–10 10 PAS Colorado High Plains aquifer 297 271.5 291.5hpaqpas1 HPAQPAS1–11 11 PAS Colorado High Plains aquifer 141 111 141hpaqpas1 HPAQPAS1–12 12 PAS Wyoming High Plains aquifer 116 22 116hpaqpas1 HPAQPAS1–13 13 PAS Wyoming High Plains aquifer 361 240 320hpaqpas1 HPAQPAS1–14 14 PAS Wyoming High Plains aquifer 500 190 500hpaqpas1 HPAQPAS1–15 15 PAS Wyoming High Plains aquifer 665 290 665hpaqpas1 HPAQPAS1–16 16 PAS Wyoming High Plains aquifer 446 61 360hpaqpas1 HPAQPAS1–17 17 PAS Nebraska High Plains aquifer 190 148 188hpaqpas1 HPAQPAS1–18 18 PAS Nebraska High Plains aquifer 440 320 440hpaqpas1 HPAQPAS1–19 19 PAS Nebraska High Plains aquifer 211 171 211hpaqpas1 HPAQPAS1–20 20 PAS Nebraska High Plains aquifer 54 32 43hpaqpas1 HPAQPAS1–21 21 PAS Nebraska High Plains aquifer 211 197 209hpaqpas1 HPAQPAS1–22 22 PAS Nebraska High Plains aquifer 68 52 68hpaqpas1 HPAQPAS1–23 23 PAS Nebraska High Plains aquifer 252 158 252hpaqpas1 HPAQPAS1–24 24 PAS Nebraska High Plains aquifer 314 212 312hpaqpas1 HPAQPAS1–25 25 PAS Nebraska High Plains aquifer 298 198 298
48 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface hpaqpas1 HPAQPAS1–26 26 PAS Nebraska High Plains aquifer 155 130 150 hpaqpas1 HPAQPAS1–27 27 PAS Nebraska High Plains aquifer 378 335 375 hpaqpas1 HPAQPAS1–28 28 PAS Nebraska High Plains aquifer 81 53 78 hpaqpas1 HPAQPAS1–29 29 PAS Nebraska High Plains aquifer 730 640 700 hpaqpas1 HPAQPAS1–30 30 PAS Nebraska High Plains aquifer 180 140 180 hpaqpas1 HPAQPAS1–31 31 PAS Nebraska High Plains aquifer 98 75 95 hpaqpas1 HPAQPAS1–32 32 PAS Nebraska High Plains aquifer 330 270 315 hpaqpas1 HPAQPAS1–33 33 PAS Nebraska High Plains aquifer 364 314 364 hpaqpas1 HPAQPAS1–34 34 PAS Nebraska High Plains aquifer 230 140 230 hpaqpas1 HPAQPAS1–35 35 PAS Nebraska High Plains aquifer 140 109 135 hpaqpas1 HPAQPAS1–36 36 PAS Nebraska High Plains aquifer 268 173 268 hpaqpas1 HPAQPAS1–37 37 PAS Nebraska High Plains aquifer 340 280 340 hpaqpas1 HPAQPAS1–38 38 PAS Nebraska High Plains aquifer 465 380 460 hpaqpas1 HPAQPAS1–39 39 PAS Nebraska High Plains aquifer 325 130 325 hpaqpas1 HPAQPAS1–40 40 PAS Nebraska High Plains aquifer 180 60 120 hpaqpas1 HPAQPAS1–41 41 PAS Nebraska High Plains aquifer 90 45 90 hpaqpas1 HPAQPAS1–42 42 PAS Nebraska High Plains aquifer 447 348 443 hpaqpas1 HPAQPAS1–43 43 PAS Nebraska High Plains aquifer 190 140 180 hpaqpas1 HPAQPAS1–44 44 PAS Nebraska High Plains aquifer 360 317 357 hpaqpas1 HPAQPAS1–45 45 PAS Nebraska High Plains aquifer 360 255 335 hpaqpas1 HPAQPAS1–46 46 PAS Nebraska High Plains aquifer 112 88 98 hpaqpas1 HPAQPAS1–47 47 PAS Nebraska High Plains aquifer 300 260 300 hpaqpas1 HPAQPAS1–48 48 PAS Nebraska High Plains aquifer 117 96 116 hpaqpas1 HPAQPAS1–49 49 PAS Kansas High Plains aquifer 247 80 241

hpaqpas1 HPAQPAS1–50 50 PAS Kansas High Plains aquifer 127 94 127hpaqpas1 HPAQPAS1–51 51 PAS Kansas High Plains aquifer 110** 85 110hpaqpas1 HPAQPAS1–52 52 PAS Kansas High Plains aquifer 146 125 146hpaqpas1 HPAQPAS1–53 53 PAS Kansas High Plains aquifer 436 243 436
Table 1 49

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

hpaqpas1 HPAQPAS1–54 54 PAS Kansas High Plains aquifer 545 322 545hpaqpas1 HPAQPAS1–55 55 PAS Kansas High Plains aquifer 212 192 212hpaqpas1 HPAQPAS1–56 56 PAS Kansas High Plains aquifer 194 na 194*hpaqpas1 HPAQPAS1–57 57 PAS Kansas High Plains aquifer 122 99 118hpaqpas1 HPAQPAS1–58 58 PAS Kansas High Plains aquifer 270 230 270hpaqpas1 HPAQPAS1–59 59 PAS Kansas High Plains aquifer 146 na 146*hpaqpas1 HPAQPAS1–60 60 PAS Oklahoma High Plains aquifer 276 206 236hpaqpas1 HPAQPAS1–61 61 PAS Oklahoma High Plains aquifer 324 215 315hpaqpas1 HPAQPAS1–62 62 PAS Oklahoma High Plains aquifer 188 168 188hpaqpas1 HPAQPAS1–63 63 PAS Oklahoma High Plains aquifer 300 na 300*hpaqvfps1 HPAQVFPS1–1 01 VFPS Nebraska High Plains aquifer 230 210 230hpaqvfps1 HPAQVFPS1–10 10 VFPS Nebraska High Plains aquifer 200 100 200hpaqvfps1 HPAQVFPS1–11 11 VFPS Nebraska High Plains aquifer 92 77 87hpaqvfps1 HPAQVFPS1–12 12 VFPS Nebraska High Plains aquifer 183 173 183hpaqvfps1 HPAQVFPS1–13 13 VFPS Nebraska High Plains aquifer 118 102.7 112.7hpaqvfps1 HPAQVFPS1–14 14 VFPS Nebraska High Plains aquifer 200 180 200hpaqvfps1 HPAQVFPS1–15 15 VFPS Nebraska High Plains aquifer 112 97 107hpaqvfps1 HPAQVFPS1–16 16 VFPS Nebraska High Plains aquifer 190 130 190hpaqvfps1 HPAQVFPS1–17 17 VFPS Nebraska High Plains aquifer 124 108 118hpaqvfps1 HPAQVFPS1–18 18 VFPS Nebraska High Plains aquifer 59 43 53hpaqvfps1 HPAQVFPS1–19 19 VFPS Nebraska High Plains aquifer 98 82.7 92.7hpaqvfps1 HPAQVFPS1–2 02 VFPS Nebraska High Plains aquifer 129 113.9 123.9hpaqvfps1 HPAQVFPS1–20 20 VFPS Nebraska High Plains aquifer 109 93.3 103.3hpaqvfps1 HPAQVFPS1–21 21 VFPS Nebraska High Plains aquifer 156 130 150hpaqvfps1 HPAQVFPS1–22 22 VFPS Nebraska High Plains aquifer 180 160 180hpaqvfps1 HPAQVFPS1–23 23 VFPS Nebraska High Plains aquifer 94 78.1 88.1hpaqvfps1 HPAQVFPS1–24 24 VFPS Nebraska High Plains aquifer 54 38.1 48.1hpaqvfps1 HPAQVFPS1–25 25 VFPS Nebraska High Plains aquifer 134 118 128
50 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface hpaqvfps1 HPAQVFPS1–26 26 VFPS Nebraska High Plains aquifer 158 138 158 hpaqvfps1 HPAQVFPS1–27 27 VFPS Nebraska High Plains aquifer 136 132 136 hpaqvfps1 HPAQVFPS1–28 28 VFPS Nebraska High Plains aquifer 99 83.1 93.1 hpaqvfps1 HPAQVFPS1–29 29 VFPS Nebraska High Plains aquifer 128 112.9 122.9 hpaqvfps1 HPAQVFPS1–03 03 VFPS Nebraska High Plains aquifer 158 143 153 hpaqvfps1 HPAQVFPS1–30 30 VFPS Nebraska High Plains aquifer 114 98.1 108.1 hpaqvfps1 HPAQVFPS1–31 31 VFPS Nebraska High Plains aquifer 129 113 123 hpaqvfps1 HPAQVFPS1–32 32 VFPS Nebraska High Plains aquifer 160 140 160 hpaqvfps1 HPAQVFPS1–33 33 VFPS Nebraska High Plains aquifer 114 98.5 108.5 hpaqvfps1 HPAQVFPS1–34 34 VFPS Nebraska High Plains aquifer 202 192 202 hpaqvfps1 HPAQVFPS1–04 04 VFPS Nebraska High Plains aquifer 118 102.8 112.8 hpaqvfps1 HPAQVFPS1–05 05 VFPS Nebraska High Plains aquifer 119 103 113 hpaqvfps1 HPAQVFPS1–06 06 VFPS Nebraska High Plains aquifer 185 165 185 hpaqvfps1 HPAQVFPS1–07 07 VFPS Nebraska High Plains aquifer 210 180 210 hpaqvfps1 HPAQVFPS1–08 08 VFPS Nebraska High Plains aquifer 170 150 170 hpaqvfps1 HPAQVFPS1–09 09 VFPS Nebraska High Plains aquifer 232 192 232 lirblusrc1 LIRBLUSRC1–01 01 LUS Missouri Glacial aquifer system 29 23.8 28.8 lirblusrc1 LIRBLUSRC1–02 02 LUS Missouri Glacial aquifer system 23 17.4 22.4 lirblusrc1 LIRBLUSRC1–03 03 LUS Missouri Glacial aquifer system 8 5 8 lirblusrc1 LIRBLUSRC1–04 04 LUS Missouri Glacial aquifer system 34 28.7 33.7 lirblusrc1 LIRBLUSRC1–05 05 LUS Missouri Glacial aquifer system 15 9.7 14.7 lirblusrc1 LIRBLUSRC1–06 06 LUS Missouri Glacial aquifer system 43 37.4 42.4 lirblusrc1 LIRBLUSRC1–07 07 LUS Missouri Glacial aquifer system 24 18.2 23.2 lirblusrc1 LIRBLUSRC1–08 08 LUS Missouri Glacial aquifer system 21 15.9 20.9

lirblusrc1 LIRBLUSRC1–09 09 LUS Missouri Glacial aquifer system 29 23.9 28.9lirblusrc1 LIRBLUSRC1–10 10 LUS Missouri Glacial aquifer system 20 14.5 19.5lirblusrc1 LIRBLUSRC1–11 11 LUS Missouri Glacial aquifer system 28 22.1 24.1lirblusrc1 LIRBLUSRC1–12 12 LUS Illinois Glacial aquifer system 44 38 43
Table 1 51

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

lirblusrc1 LIRBLUSRC1–13 13 LUS Illinois Glacial aquifer system 19 13.8 18.8lirblusrc1 LIRBLUSRC1–14 14 LUS Illinois Glacial aquifer system 44 38 43lirblusrc1 LIRBLUSRC1–15 15 LUS Illinois Glacial aquifer system 54 48.1 53.1lirblusrc1 LIRBLUSRC1–16 16 LUS Illinois Glacial aquifer system 37 31 36lirblusrc1 LIRBLUSRC1–17 17 LUS Illinois Glacial aquifer system 31 25.4 30.4lirblusrc1 LIRBLUSRC1–18 18 LUS Illinois Glacial aquifer system 60 53.5 58.5lirblusrc1 LIRBLUSRC1–19 19 LUS Illinois Glacial aquifer system 20.5** 14.5 20.5lirblusrc1 LIRBLUSRC1–20 20 LUS Illinois Glacial aquifer system 17 11.5 16.5lirblusrc1 LIRBLUSRC1–21 21 LUS Illinois Glacial aquifer system 24 18.6 23.6lirblusrc1 LIRBLUSRC1–22 22 LUS Illinois Glacial aquifer system 47 41.1 46.1lirblusrc1 LIRBLUSRC1–23 23 LUS Illinois Glacial aquifer system 24 18.6 23.6lirblusrc1 LIRBLUSRC1–24 24 LUS Illinois Glacial aquifer system 43 37.9 42.9lirblusrc1 LIRBLUSRC1–25 25 LUS Illinois Glacial aquifer system 38 32.9 37.9metxetn1 METXETN1–01 01 ETN Tennessee Mississippi Embayment-Texas Coastal Uplands aquifer system 624 520 624metxetn1 METXETN1–02 02 ETN Tennessee Mississippi Embayment-Texas Coastal Uplands aquifer system 90 80 90metxpas1 METXPAS1–61 61 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,080 na 1,080*metxpas1 METXPAS1–62 62 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 696 na 696*metxpas1 METXPAS1–63 63 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 630 na 630*metxpas1 METXPAS1–64 64 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,072 na 1,072*metxpas1 METXPAS1–65 65 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 697 na 697*metxpas1 METXPAS1–66 66 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 156 na 156*metxpas1 METXPAS1–67 67 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 740 na 740*metxpas1 METXPAS1–68 68 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 510 na 510*metxpas1 METXPAS1–69 69 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 423 na 423*metxpas1 METXPAS1–70 70 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 2,376 na 2,376*metxpas1 METXPAS1–71 71 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 530 na 530*metxpas1 METXPAS1–72 72 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 695 na 695*metxpas1 METXPAS1–73 73 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 750 na 750*
52 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface metxpas1 METXPAS1–74 74 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 4,261 na 4,261* metxpas1 METXPAS1–75 75 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 560 na 560* metxpas1 METXPAS1–76 76 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 880 na 880* metxpas1 METXPAS1–77 77 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 825 na 825* metxpas1 METXPAS1–78 78 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 565 na 565* metxpas1 METXPAS1–79 79 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 653 na 653* metxpas1 METXPAS1–80 80 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 2,082 na 2,082* metxpas1 METXPAS1–81 81 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,960 na 1,960* metxpas1 METXPAS1–82 82 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,064 na 1,064* metxpas1 METXPAS1–83 83 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,572 na 1,572* metxpas1 METXPAS1–84 84 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,220 na 1,220* metxpas1 METXPAS1–85 85 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,033 na 1,033* metxpas1 METXPAS1–86 86 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,054 na 1,054* metxpas1 METXPAS1–87 87 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,250 na 1,250* metxpas1 METXPAS1–88 88 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 800 na 800* metxpas1 METXPAS1–89 89 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,306 na 1,306* metxpas1 METXPAS1–90 90 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,580 na 1,580* metxpas1 METXPAS1–91 91 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 1,314 na 1,314* metxpas1 METXPAS1–92 92 PAS Texas Mississippi Embayment-Texas Coastal Uplands aquifer system 515 na 515* nacpetn1 NACPETN1–01 01 ETN Delaware Northern Atlantic Coastal Plain aquifer system 22 19 22 nacpetn1 NACPETN1–02 02 ETN Delaware Northern Atlantic Coastal Plain aquifer system 139 85 135 nacpetn1 NACPETN1–03 03 ETN Delaware Northern Atlantic Coastal Plain aquifer system 119 100 119 negxetn1 NEGXETN1–01 01 ETN New Hampshire Glacial aquifer and New England crystalline-rock aquifers 83 73 83 negxetn1 NEGXETN1–02 02 ETN New 

Hampshire

Glacial aquifer and New England crystalline-rock aquifers 492 88 492

negxetn1 NEGXETN1–03 03 ETN New 

Hampshire

Glacial aquifer and New England crystalline-rock aquifers 176.3 na 176.3*
Table 1 53

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

podllusrc1 PODLUSRC1–01 01 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 50** 19 50podllusrc1 PODLUSRC1–03 03 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 45 38 45podllusrc1 PODLUSRC1–05 05 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 68.8 53.5 68.8podllusrc1 PODLUSRC1–06 06 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 45 18.5 45podllusrc1 PODLUSRC1–11 11 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 59.8 33 59podllusrc1 PODLUSRC1–12 12 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 65.4 30 65podllusrc1 PODLUSRC1–13 13 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 75** 20 75podllusrc1 PODLUSRC1–16 16 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 64.8 23 64.8podllusrc1 PODLUSRC1–21 21 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 45.1 18 45.1podllusrc1 PODLUSRC1–23 23 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 77 30 77podllusrc1 PODLUSRC1–28 28 LUS Maryland Piedmont and Blue Ridge crystalline-rock aquifers 43.2 15 43.2podllusrc1 PODLUSRC1–35 35 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 120.4 17.5 120podllusrc1 PODLUSRC1–46 46 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 47** 33 47podllusrc1 PODLUSRC1–47 47 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 61.6 20 61.6podllusrc1 PODLUSRC1–49 49 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 82** 18.5 82podllusrc1 PODLUSRC1–52 52 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 62** 14 62podllusrc1 PODLUSRC1–63 63 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 78.9 52.5 78.9podllusrc1 PODLUSRC1–65 65 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 62** 11 62podllusrc1 PODLUSRC1–69 69 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 58.9 38 58.9podllusrc1 PODLUSRC1–72 72 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 77** 12.5 77podllusrc1 PODLUSRC1–74 74 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 44** 33 44podllusrc1 PODLUSRC1–76 76 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 67.1 53 67.1podllusrc1 PODLUSRC1–79 79 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 55 36.5 55podllusrc1 PODLUSRC1–85 85 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 120 27 120podllusrc1 PODLUSRC1–86 86 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 56** 23 56
54 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface podllusrc1 PODLUSRC1–87 87 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 72** 23 72 podllusrc1 PODLUSRC1–89 89 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 50 40 50 podllusrc1 PODLUSRC1–99 99 LUS Virginia Piedmont and Blue Ridge crystalline-rock aquifers 96 na 96* rgaqetn1 RGAQETN1–01 01 ETN New Mexico Rio Grande aquifer system 22.6 7.5 17.5 rgaqetn1 RGAQETN1–02 02 ETN New Mexico Rio Grande aquifer system 60 40 60 rgaqetn1 RGAQETN1–03 03 ETN New Mexico Rio Grande aquifer system 22 11.5 21.5 rgaqpas1 RGAQPAS1U–01 01 PAS New Mexico Rio Grande aquifer system 223 210 220 rgaqpas1 RGAQPAS1U–02 02 PAS New Mexico Rio Grande aquifer system 165.5 134.7 154.7 rgaqpas1 RGAQPAS1U–03 03 PAS New Mexico Rio Grande aquifer system 1,321.5 1,290 1,310 rgaqpas1 RGAQPAS1U–04 04 PAS New Mexico Rio Grande aquifer system 1,723 991 1,711 rgaqpas1 RGAQPAS1U–05 05 PAS New Mexico Rio Grande aquifer system 427 396.1 416.1 rgaqpas1 RGAQPAS1U–06 06 PAS New Mexico Rio Grande aquifer system 198 167.2 187.2 rgaqpas1 RGAQPAS1U–07 07 PAS New Mexico Rio Grande aquifer system 42 na 42* rgaqpas1 RGAQPAS1U–08 08 PAS New Mexico Rio Grande aquifer system 1,194 479 1,184 rgaqpas1 RGAQPAS1U–09 09 PAS New Mexico Rio Grande aquifer system 520 na 520* rgaqpas1 RGAQPAS1U–10 10 PAS New Mexico Rio Grande aquifer system 306 276 296 rgaqpas1 RGAQPAS1U–11 11 PAS New Mexico Rio Grande aquifer system 100 na 100* rgaqpas1 RGAQPAS1U–12 12 PAS New Mexico Rio Grande aquifer system 800 na 800* rgaqpas1 RGAQPAS1U–13 13 PAS New Mexico Rio Grande aquifer system 177 na 177* rgaqpas1 RGAQPAS1U–14 14 PAS New Mexico Rio Grande aquifer system 200 na 200* rgaqpas1 RGAQPAS1U–15 15 PAS New Mexico Rio Grande aquifer system 1,525 1,515 1,520 rgaqpas1 RGAQPAS1U–16 16 PAS New Mexico Rio Grande aquifer system na na na rgaqpas1 RGAQPAS1U–17 17 PAS New Mexico Rio Grande aquifer system 1,630 1,580 1,620 rgaqpas1 RGAQPAS1U–18 18 PAS New Mexico Rio Grande aquifer system na na na

rgaqpas1 RGAQPAS1U–19 19 PAS New Mexico Rio Grande aquifer system na na nasanjluscr1a SANJLUSCR1A–01 01 LUS California Central Valley aquifer system 160 140 160sanjluscr1a SANJLUSCR1A–02 02 LUS California Central Valley aquifer system 127 107 127sanjluscr1a SANJLUSCR1A–03 03 LUS California Central Valley aquifer system 125 105 125
Table 1 55

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

sanjluscr1a SANJLUSCR1A–04 04 LUS California Central Valley aquifer system 108 na 108*sanjluscr1a SANJLUSCR1A–05 05 LUS California Central Valley aquifer system 125 105 125sanjluscr1a SANJLUSCR1A–06 06 LUS California Central Valley aquifer system 130 110 130sanjluscr1a SANJLUSCR1A–07 07 LUS California Central Valley aquifer system 115 95 115sanjluscr1a SANJLUSCR1A–09 09 LUS California Central Valley aquifer system 110 na 110*sanjluscr1a SANJLUSCR1A–10 10 LUS California Central Valley aquifer system 165 na 165*sanjluscr1a SANJLUSCR1A–11 11 LUS California Central Valley aquifer system 417 na 417*sanjluscr1a SANJLUSCR1A–12 12 LUS California Central Valley aquifer system 212 na 212*sanjluscr1a SANJLUSCR1A–13 13 LUS California Central Valley aquifer system 200 140 200sanjluscr1a SANJLUSCR1A–14 14 LUS California Central Valley aquifer system 160 120 160sanjluscr1a SANJLUSCR1A–15 15 LUS California Central Valley aquifer system 200 180 200sanjluscr1a SANJLUSCR1A–16 16 LUS California Central Valley aquifer system 55 35 55sanjluscr1a SANJLUSCR1A–17 17 LUS California Central Valley aquifer system 200 150 190sanjluscr1a SANJLUSCR1A–19 19 LUS California Central Valley aquifer system 147 na 147*sanjluscr1a SANJLUSCR1A–20 20 LUS California Central Valley aquifer system 118 na 118*sanjluscr1a SANJLUSCR1A–21 21 LUS California Central Valley aquifer system 366 192 366sanjluscr1a SANJLUSCR1A–22 22 LUS California Central Valley aquifer system 280 220 280sanjluscr1a SANJLUSCR1A–23 23 LUS California Central Valley aquifer system 313 na 313*sanjluscr1a/ 

sanjsus1

SANJLUSCR1A–18/SANJSUS1–02

18 (luscr1a)or 02 (sus1)

LUS/

MAS

California Central Valley aquifer system 182 158 182

sanjluscr1a/ 

sanjsus1

SANJLUSCR1A–08/SANJSUS1–01

08 (luscr1a)or 01 (sus1)

LUS/

MAS

California Central Valley aquifer system 108 na 108*

sanjsus1 SANJSUS1–03 03 MAS California Central Valley aquifer system 160 na 160*sanjsus1 SANJSUS1–04 04 MAS California Central Valley aquifer system 215 195 215sanjsus1 SANJSUS1–05 05 MAS California Central Valley aquifer system 110 92 110sanjsus1 SANJSUS1–06 06 MAS California Central Valley aquifer system 182 162 182sanjsus1 SANJSUS1–07 07 MAS California Central Valley aquifer system 121 116 121sanjsus1 SANJSUS1–08 08 MAS California Central Valley aquifer system 120 80 120
56 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface sanjsus1 SANJSUS1–09 09 MAS California Central Valley aquifer system 72 25 72 sanjsus1 SANJSUS1–10 10 MAS California Central Valley aquifer system 145 105 145 sanjsus1 SANJSUS1–11 11 MAS California Central Valley aquifer system 124 64 124 sanjsus1 SANJSUS1–12 12 MAS California Central Valley aquifer system 120 40 120 sanjsus1 SANJSUS1–13 13 MAS California Central Valley aquifer system 104 38 63 sanjsus1 SANJSUS1–14 14 MAS California Central Valley aquifer system 340 na 340* sanjsus1 SANJSUS1–15 15 MAS California Central Valley aquifer system 73 na 73* sanjsus1 SANJSUS1–16 16 MAS California Central Valley aquifer system 236 200 236 sanjsus1 SANJSUS1–17 17 MAS California Central Valley aquifer system 300 na 300* sanjsus1 SANJSUS1–18 18 MAS California Central Valley aquifer system 400 na 400* sanjsus1 SANJSUS1–19 19 MAS California Central Valley aquifer system 336 na 336* sanjsus1 SANJSUS1–20 20 MAS California Central Valley aquifer system 310 210 310 sanjsus1 SANJSUS1–21 21 MAS California Central Valley aquifer system 232 160 232 sanjsus1 SANJSUS1–22 22 MAS California Central Valley aquifer system 300 200 300 sanjsus1 SANJSUS1–23 23 MAS California Central Valley aquifer system 350 200 350 sanjsus1 SANJSUS1–24 24 MAS California Central Valley aquifer system 200 160 200 sanjsus1 SANJSUS1–25 25 MAS California Central Valley aquifer system 702 602 702 sanjsus1 SANJSUS1–26 26 MAS California Central Valley aquifer system 485** 475 485 trinlusrc1 TRINLUSRC1–01 01 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5 trinlusrc1 TRINLUSRC1–02 02 LUS Texas Coastal lowlands aquifer system 41 28 38 trinlusrc1 TRINLUSRC1–03 03 LUS Texas Coastal lowlands aquifer system 53.5 40.5 50.5 trinlusrc1 TRINLUSRC1–04 04 LUS Texas Coastal lowlands aquifer system 43.5 30.5 40.5 trinlusrc1 TRINLUSRC1–05 05 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5 trinlusrc1 TRINLUSRC1–06 06 LUS Texas Coastal lowlands aquifer system 53 40 50

trinlusrc1 TRINLUSRC1–07 07 LUS Texas Coastal lowlands aquifer system 26.5 13.5 23.5trinlusrc1 TRINLUSRC1–08 08 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5trinlusrc1 TRINLUSRC1–09 09 LUS Texas Coastal lowlands aquifer system 23.5 10.5 20.5trinlusrc1 TRINLUSRC1–10 10 LUS Texas Coastal lowlands aquifer system 32.5 19.5 29.5
Table 1 57

Table 1. Information about wells that have environmental data included in this report.—Continued[MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study]

Network 

name

Well 

identification number

Identification 

number shown 

on figures 

2–19

Network 

type State Aquifer

Well depth, 

in feet 

below land 

surface

Depth to 

perforation 

top, in feet 

below land 

surface

Depth to 

perforation 

bottom, in feet 

below land 

surface

trinlusrc1 TRINLUSRC1–11 11 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5trinlusrc1 TRINLUSRC1–12 12 LUS Texas Coastal lowlands aquifer system 27.5 14.5 24.5trinlusrc1 TRINLUSRC1–13 13 LUS Texas Coastal lowlands aquifer system 33 23 33trinlusrc1 TRINLUSRC1–14 14 LUS Texas Coastal lowlands aquifer system 28.5 15.5 25.5trinlusrc1 TRINLUSRC1–15 15 LUS Texas Coastal lowlands aquifer system 46.5 33.5 43.5trinlusrc1 TRINLUSRC1–16 16 LUS Texas Coastal lowlands aquifer system 28.5 15.5 25.5trinlusrc1 TRINLUSRC1–17 17 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5trinlusrc1 TRINLUSRC1–18 18 LUS Texas Coastal lowlands aquifer system 33.5 20.5 30.5trinlusrc1 TRINLUSRC1–19 19 LUS Texas Coastal lowlands aquifer system 66.2 51.2 61.2trinlusrc1 TRINLUSRC1–20 20 LUS Texas Coastal lowlands aquifer system 41 28 38trinlusrc1 TRINLUSRC1–21 21 LUS Texas Coastal lowlands aquifer system 30 20 30trinlusrc1 TRINLUSRC1–22 22 LUS Texas Coastal lowlands aquifer system 73 60 73trinlusrc1 TRINLUSRC1–23 23 LUS Texas Coastal lowlands aquifer system 48 38 48trinlusrc1 TRINLUSRC1–24 24 LUS Texas Coastal lowlands aquifer system 53.5 38.5 48.5trinlusrc1 TRINLUSRC1–25 25 LUS Texas Coastal lowlands aquifer system 118.5 105.5 115.5trinlusrc1 TRINLUSRC1–26 26 LUS Texas Coastal lowlands aquifer system 83.5 68.5 78.5trinlusrc1 TRINLUSRC1–27 27 LUS Texas Coastal lowlands aquifer system 38.5 25.5 35.5wmicsus1 WMICSUS1–01 01 MAS Wisconsin Cambrian-Ordovician aquifer system 123 65 123wmicsus1 WMICSUS1–02 02 MAS Wisconsin Cambrian-Ordovician aquifer system 210 179 210wmicsus1 WMICSUS1–03 03 MAS Wisconsin Cambrian-Ordovician aquifer system 320 135 320wmicsus1 WMICSUS1–04 04 MAS Wisconsin Cambrian-Ordovician aquifer system 111 66 111wmicsus1 WMICSUS1–05 05 MAS Wisconsin Cambrian-Ordovician aquifer system 466 324 466wmicsus1 WMICSUS1–06 06 MAS Wisconsin Cambrian-Ordovician aquifer system 179 125 179wmicsus1 WMICSUS1–07 07 MAS Wisconsin Cambrian-Ordovician aquifer system 102 42 102wmicsus1 WMICSUS1–08 08 MAS Wisconsin Cambrian-Ordovician aquifer system 95 63 95wmicsus1 WMICSUS1–09 09 MAS Wisconsin Cambrian-Ordovician aquifer system 95 80 95wmicsus1 WMICSUS1–10 10 MAS Wisconsin Cambrian-Ordovician aquifer system 675 457 675wmicsus1 WMICSUS1–11 11 MAS Wisconsin Cambrian-Ordovician aquifer system 140 119 140
58 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project Table 1. Information about wells that have environmental data included in this report.—Continued [MAS, major aquifer study; na, information is not available and cannot be assumed; PAS, principal aquifer study; *, information is unavailable about the bottom of perforation, but it is assumed to be bottom of well (well_depth); LUS, land-use study network; ETN, enhanced trends network; **, the recorded well depth was less than the recorded depth to the bottom of the perforated interval but is assumed to be the depth to the bottom of the perforated interval; VFPS, vertical flow-path study] Network name Well identification number Identification number shown on figures 2–19 Network type State Aquifer Well depth, in feet below land surface Depth to perforation top, in feet below land surface Depth to perforation bottom, in feet below land surface wmicsus1 WMICSUS1–12 12 MAS Wisconsin Cambrian-Ordovician aquifer system 870 235 870 wmicsus1 WMICSUS1–13 13 MAS Wisconsin Cambrian-Ordovician aquifer system 125 97 125 wmicsus1 WMICSUS1–14 14 MAS Wisconsin Cambrian-Ordovician aquifer system 346 120 346 wmicsus1 WMICSUS1–15 15 MAS Michigan Cambrian-Ordovician aquifer system 432 332 432 wmicsus1 WMICSUS1–16 16 MAS Michigan Cambrian-Ordovician aquifer system 46 na 46* wmicsus1 WMICSUS1–17 17 MAS Michigan Cambrian-Ordovician aquifer system 483 212 483 wmicsus1 WMICSUS1–18 18 MAS Michigan Cambrian-Ordovician aquifer system 137 na 137* wmicsus1 WMICSUS1–19 19 MAS Michigan Cambrian-Ordovician aquifer system 290 252 290 wmicsus1 WMICSUS1–20 20 MAS Michigan Cambrian-Ordovician aquifer system 305 203 305 wmicsus1 WMICSUS1–21 21 MAS Michigan Cambrian-Ordovician aquifer system 31 28 31
Appendixes 1–3
60 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Appendix 1. Well Depth and Open Interval by Study Network

Table 1.1. Well depth by study network.

[ETN, enhanced trends network; nc, not calculated; LUS, land-use study; MAS, major aquifer study; PAS, principal aquifer 

study; VFPS, vertical flow-path study] Network type Network name Number of wells in network with data presented in this report Numbr of wells with 

well depth data

Well depth, in feet below land surface

Minimum

10th percentile25th percentile

Median

75th percentile95th percentile

Maximum

Mean

ETN clptetn1 3 3 40 nc nc 80 nc nc 1,116 nc

ETN cvaletn1 3 3 234 nc nc 320 nc nc 620 nc

ETN edtretn1 3 3 300 nc nc 550 nc nc 1,550 nc

ETN glacetn1 5 5 34.5 nc nc 83 nc nc 125 nc

ETN metxetn1 2 2 90 nc nc 357 nc nc 624 nc

ETN nacpetn1 3 3 22 nc nc 119 nc nc 139 nc

ETN negxetn1 3 3 83 nc nc 176.3 nc nc 492 nc

ETN rgaqetn1 3 3 22 nc nc 22.6 nc nc 60 nc

LUS ccptlusor1b 21 21 15 19 24.5 29 48.5 73.1 90 39

LUS cnbrluscr1 27 27 15 20 24.8 32 45 65 73 36

LUS gaflluscr1 26 26 17 20 25.4 31.8 45 64.8 70 37

LUS lirblusrc1 25 25 8 17.9 21.4 29.3 42.9 52.2 60 31

LUS podllusrc1 28 28 43.2 45 50 62 75.5 111.6 120.4 66

LUS sanjluscr1a 23 23 55 108.4 121.5 160 200 360.7 417 179

LUS trinlusrc1 27 27 23.5 28.1 32.8 33.5 50.5 80.4 118.5 44

MAS acfbsus1 27 26 64 77.5 98.9 131.5 213.5 248.8 370 156

MAS sanjsus1 26 26 72 106 120.3 191 307.5 463.8 702 232

MAS wmicsus1 21 21 31 95 111 179 346 675 870 266

PAS bnrcpas1 20 13 269 282.2 350 520 620 1,070 1,205 556

PAS florpas1 60 17 140 169.2 200 400 590 788 840 426

PAS hpaqpas1 63 63 54 110.4 145.5 230 335 496.5 730 259

PAS metxpas1 32 32 156 516.5 647.3 852.5 1264 2,214.3 4,261 1,089 

PAS rgaqpas1 19 16 42 132.8 192.8 366.4 1,225.9 1,653.3 1,723 660

VFPS hpaqvfps1 34 34 53.6 95.0 113.7 131.5 182.3 217 232 144
Appendix 1 61

Table 1.2. Length of open interval by study network.

[ETN, enhanced trends network; nc, not calculated; LUS, land-use study; MAS, major aquifer study; PAS, principal aquifer 

study; na, not available; VFPS, vertical flow-path study] Network type Network name Number of wells in network with data presented in this report Number of wells with open interval data

Length of open interval, in feet

Minimum

10th percentile25th percentile

Median

75th percentile95th percentile

Maximum

Mean

ETN clptetn1 3 2 1 nc nc 87.5 nc nc 174 nc

ETN cvaletn1 3 3 10 nc nc 150 nc nc 200 nc

ETN edtretn1 3 3 80 nc nc 230 nc nc 233 nc

ETN glacetn1 5 4 3 nc nc 5 nc nc 10 nc

ETN metxetn1 2 2 10 nc nc 57 nc nc 104 nc

ETN nacpetn1 3 3 3 nc nc 19 nc nc 50 nc

ETN negxetn1 3 2 10 nc nc 207 nc nc 404 nc

ETN rgaqetn1 3 3 10 nc nc 10 nc nc 20 nc

LUS ccptlusor1b 21 21 5 5 5 5 5 10 10 6

LUS cnbrluscr1 27 27 5 5 5 5 10 10 10 7

LUS gaflluscr1 26 26 10 10 10 10 10 27.5 30 13

LUS lirblusrc1 25 25 2 5 5 5 5 5 6 5

LUS podllusrc1 28 27 7 12.8 19.7 31 48.5 84.5 102.5 37

LUS sanjluscr1a 23 14 20 20 20 20 40 99.9 174 40

LUS trinlusrc1 27 27 10 10 10 10 10 10 13 10

MAS acfbsus1 27 26 3 11.7 26 57.5 115.5 163.8 250 73

MAS sanjsus1 26 19 5 16.4 22 40 76 105 150 52

MAS wmicsus1 21 19 3 19.8 31.5 58 163.5 307.4 635 119

PAS bnrcpas1 20 11 40 40 80 200 382.5 521 532 243

PAS florpas1 60 14 30 48.3 62 211.5 311.8 333.2 339 189

PAS hpaqpas1 63 59 10 19.8 25 45 94 230.6 375 74

PAS metxpas1 32 0 na na na na na na na na

PAS rgaqpas1 19 10 5 9.5 20 20 35 713.3 720 158

VFPS hpaqvfps1 34 34 4 10 10 10 20 47 100 18
62 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Appendix 2. High-Frequency Data from Enhanced Trends Networks

High-frequency data collected at enhanced trends 

network sites are available from the National Water Information System (U.S. Geological Survey, 2017) online database 

(table 2.1). The links in table 2.1 below provide access to 

the high-frequency data on the web. To access the data for 

the period covered by this report, the user should open the 

National Water Information System web page at https://doi.

org/10.5066/F7P55KJN. The user should then change the 

Table 2.1. Web links to data collected at a high-frequency from enhanced trends networks.

[See figures 17–18 of this report for locations of enhanced trends networks. NAWQA, National Water-Quality Assessment]

Network name NAWQA Project 

well identification number Link to data collected at a high frequency

clptetn1 CLPTETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=455415119314601

clptetn1 CLPTETN1–04 https://waterdata.usgs.gov/nwis/uv?site_no=454554119121801

clptetn1 CLPTETN1–06 https://waterdata.usgs.gov/nwis/uv?site_no=454919119184701

cvaletn1 CVALETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=364200119420001

cvaletn1 CVALETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=364200119420002

cvaletn1 CVALETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=364200119420003

edtretn1 EDTRETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=293116098334101

edtretn1 EDTRETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=293516098325501

edtretn1 EDTRETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=292331098294501

glacetn1 GLACETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=443320089212303

glacetn1 GLACETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=443320089212304

glacetn1 GLACETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=431053090042702

glacetn1 GLACETN1–04 https://waterdata.usgs.gov/nwis/uv?site_no=431053090042701

glacetn1 GLACETN1–05 https://waterdata.usgs.gov/nwis/uv?site_no=431037090043401

metxetn1 METXETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=351113089513401

metxetn1 METXETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=351111089512501

nacpetn1 NACPETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=384637075153201

nacpetn1 NACPETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=384526075091601

nacpetn1 NACPETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=384428075355701

negxetn1 NEGXETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=425311070535801

negxetn1 NEGXETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=425400070545401

negxetn1 NEGXETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=425651070573701

rgaqetn1 RGAQETN1–01 https://waterdata.usgs.gov/nwis/uv?site_no=323733107011002

rgaqetn1 RGAQETN1–02 https://waterdata.usgs.gov/nwis/uv?site_no=324007107095501

rgaqetn1 RGAQETN1–03 https://waterdata.usgs.gov/nwis/uv?site_no=324955107180902

Reference Cited

U.S. Geological Survey, 2017, National Water Information 

System—Web interface: U.S. Geological Survey, accessed 

May 31, 2017, at https://doi.org/10.5066/F7P55KJN.

begin and end dates to retrieve the data for the period January 

1, 2015, to December 31, 2015. 

Some of the enhanced trends network sites may have 

different equipment installed and may collect different 

parameters than others. Additionally, some sites have missing 

records for various parameters because of equipment failures 

at various times during the data-collection period.
Appendix 3 63

Appendix 3. Quality-Control Data and Analysis

Samples

Quality-control (QC) samples are routinely collected 

along with the environmental groundwater samples. The third 

cycle of the NAWQA groundwater studies began in 2013 but 

there was a small pilot study in 2012. The entire third cycle 

sampling period currently is May 2012–December 2015; 

this period is hereafter referred to as “the Cycle 3 sampling 

period”. Data from the environmental and QC blank and 

replicate samples from the 2012–13 sampling period were 

presented in Arnold and others (2016a, b), and from the 2014 

sampling period were presented in Arnold and others (2017a, 

b). The Arnold and others (2017a, b) publications also presented data for selected spike samples collected in 2012–14. 

This current report presents a summary of blank samples from 

the entire Cycle 3 sampling period (May 2012–December 

2015) as well as the January–December 2015 sampling period 

covered by this report. A summary of results from blank 

samples collected during the sampling period January–December 2015 is shown in table 3.1, and a summary for the Cycle 3 

sampling period is shown in table 3.2. Data from the blank QC 

samples from the January–December 2015 sampling period 

are presented in tables 3.3–3.10 of Arnold and others (2018).

Blank Sample Approach

Blank samples are QC samples that are used to determine if water samples might become contaminated during 

sample collection, field processing, transport, or laboratory 

analysis. Blank samples are collected using blank water that 

has been prepared to be free of detectable concentrations of 

the constituents of interest. An equipment blank generally is 

collected in a controlled environment (such as a laboratory) 

before field sampling begins and is intended to evaluate the 

suitability of the equipment and equipment cleaning protocols 

for the established data-quality requirements. A field blank is 

subjected to all the same aspects of sample collection, field 

processing, preservation, transportation, and laboratory handling as an environmental sample and is intended to evaluate 

the potential for these procedures to be sources of contamination. A source solution blank is a sample of the water used to 

collect the equipment and field blanks and is intended to verify 

that the blank water itself has no detectable concentrations of 

the constituents of interest. Because field blanks are collected 

under conditions most comparable to conditions affecting 

environmental samples, these blanks are most directly representative of potential sources of contamination to environmental samples and were the focus of this initial evaluation of 

blank-sample results.

Results of the initial evaluation of data from field blanks 

for major and trace elements, nutrients, volatile organic 

compounds (VOCs), and pesticide compounds collected during the 2015 sampling period of January–December 2015 and 

the Cycle 3 sampling period are presented in this report. Data 

from 2015 are published in this report, data from 2012–13 

are published in Arnold and others (2016a, b), and data from 

2014 are published in Arnold and others (2017a, b). About 75 

to 80 percent of the field blanks collected for each of these 

constituents during the Cycle 3 sampling period have been 

associated with groundwater sites that are sampled using a 

dedicated pump (primarily public-supply and domestic wells), 

and the rest have been associated with groundwater sites that 

are sampled using a portable sampling pump (monitoring 

wells). The objective of this initial evaluation of field blanks 

was to determine if environmental concentrations of these 

constituents as reported by the National Water-Quality Laboratory (NWQL, Denver, Colorado) are suitable for comparison 

to their corresponding human-health benchmarks (HHBs) or 

to U.S. Environmental Protection Agency (EPA) secondary 

maximum contaminant levels (SMCLs) if HHBs have not 

been established. The HHBs are a set of health-based comparison thresholds that include EPA maximum contaminant levels 

(MCLs), health-based screening levels (HBSLs), and humanhealth benchmarks for pesticides (HHBPs). Further evaluation 

of results for blank samples, such as through methods used by 

Olsen and others (2010), Bender and others (2011), Fram and 

others (2012), or Davis and others (2014), would be needed to 

determine if inadvertent contamination of samples with certain 

constituents would affect the interpretation of environmental 

concentrations of those constituents for objectives other than 

those presented in this report.

Blank Sample Counts

The total number of blank samples and the number of 

field blanks collected for groundwater sites differs by constituent group during both the 2015 sampling period and the 

Cycle 3 sampling period (tables 3.1 and 3.2, respectively). 

Data for all blank samples from the 2015 sampling period are 

presented in tables 3.3–3.10 of Arnold and others (2018). All 

blank samples collected during the Cycle 3 sampling period 

were analyzed using the corresponding laboratory methods 

listed in table 2 of Arnold and others (2016b, 2017a, 2018). 

Of the 457 VOC blank samples collected during the Cycle 3 

sampling period, 28 were collected in 2012 or early 2013 and 

analyzed for an older analytical schedule using purge and trap 

gas chromatography/mass spectrometry (Gilliom and others, 

2006; Zogorski and others, 2006); 429 were collected in 2013–

15 and analyzed using the most recent analytical schedule and 

laboratory methods (purge and trap gas chromatography/mass 

spectrometry and heated purge and trap gas chromatography/

mass spectrometry). Of the 143 pesticide blank samples collected during the Cycle 3 sampling period, 8 were collected 
64 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

Table 3.1. Summary of results for field blanks collected by the National Water-Quality Assessment Project from January 2015 to 

December 2015.

 [VOCs, volatile organic compounds; HHB, human-health benchmark; SMCL, secondary maximum contaminant level]

Type of summary

Major and minor 

elements 

(not including 

dissolved solids)

Trace 

elements Nutrients VOCs Pesticide compounds

Total number of blank samples 47 99 100 107 37

Number of field blanks 42 43 44 37 32

Number of constituents analyzed 10 22 5 85 227

Number of constituents detected in field blanks 8 20 3 15 5

Number of constituents detected in field blanks that 

have an HHB 0 17 2 7 3

Number of constituents detected in field blanks that 

have an SMCL 3 4 0 0 0

Largest ratio of the maximum concentration in a field 

blank to the corresponding HHB, in percent Not applicable 4.8 0.63 2.4 0.001

Largest ratio of the maximum concentration in a field 

blank to the corresponding SMCL, in percent 1.7 51 Not applicable Not applicable Not applicable

Table 3.2. Summary of results for field blanks collected by the National Water-Quality Assessment Project from May 2012 to December 

2015.

 [VOCs, volatile organic compounds; HHB, human-health benchmark; SMCL, secondary maximum contaminant level]

Type of summary

Major and minor 

elements 

(not including 

dissolved solids)

Trace 

elements Nutrients VOCs Pesticide compounds

Total number of blank samples 302 352 350 457 143

Number of field blanks 155 154 156 152 132

Number of constituents analyzed 10 22 5 129 272

Number of constituents detected in field blanks 9 21 4 25 21

Number of constituents detected in field blanks that 

have an HHB 1 18 2 12 15

Number of constituents detected in field blanks that 

have an SMCL 4 5 0 0 0

Largest ratio of the maximum concentration in a field 

blank to the corresponding HHB, in percent 0.4 4.8 0.67 2.4 0.25

Largest ratio of the maximum concentration in a field 

blank to the corresponding SMCL, in percent 14 199 Not applicable Not applicable Not applicable
Appendix 3 65

in 2012 and analyzed for an older analytical schedule using 

gas chromatography/mass spectrometry; 135 were collected 

in 2013–15 and analyzed using the most recent analytical 

schedule and laboratory method (direct aqueous injection 

liquid chromatography tandem mass spectrometry). One 

blank sample collected in 2014 was analyzed using both an 

older and the most recent analytical schedule. Not included in 

table 3.1 are sample counts for special analytes collected only 

in selected well networks during the Cycle 3 sampling period: 

arsenic species, perchlorate, and hexavalent chromium; only 

1 to 9 field blanks were collected for each of these analytes in 

January–December 2015. 

Constituent Concentrations in Blank Samples

Of the 10 major or minor elements included in laboratory 

analysis (not including analysis for dissolved-solids concentration), 8 were detected in at least 1 field blank collected in 2015 

(table 3.1); 9 elements were detected in at least 1 field blank 

(table 3.2) collected during the Cycle 3 sampling period. Only 

one of the major or minor elements detected during the Cycle 

3 sampling period (fluoride) had an HHB (table 2 of Arnold 

and others, 2018); four (chloride, fluoride, sulfate, and iron) 

had SMCLs. The maximum concentration for fluoride in any 

field blank from the Cycle 3 sampling period was 0.4 percent 

of its corresponding HHB. For chloride, fluoride, and sulfate, 

the maximum concentration in any field blank from the Cycle 

3 sampling period was less than 1 percent of the corresponding 

SMCL; for iron, the maximum concentration was 14 percent 

of its corresponding SMCL.

Of the 22 trace elements included in laboratory analysis, 

20 were detected in at least 1 field blank collected in 2015 

(table 3.1), and 21 were detected in at least 1 field blank 

from the Cycle 3 sampling period (table 3.2). Of the 21 trace 

elements detected in field blanks from the Cycle 3 sampling 

period, 18 (antimony, arsenic, barium, beryllium, boron, 

cadmium, chromium, copper, lead, manganese, molybdenum, 

nickel, selenium, silver, strontium, thallium, uranium, and 

zinc) had HHBs (table 2 of Arnold and others, 2018); 5 (aluminum, copper, manganese, silver, and zinc) had SMCLs. For 

11 of the 18 detected trace elements with HHBs, the maximum 

concentration measured in a field blank from the Cycle 3 

sampling period was less than 1 percent of the corresponding 

HHB; for the remaining 7 trace elements (antimony, arsenic, 

beryllium, copper, lead, nickel, and thallium), the maximum 

concentration was less than 5 percent of the HHB. For silver 

and zinc, the maximum concentration measured in a field 

blank from the Cycle 3 sampling period was less than 1 percent of the corresponding SMCL; for copper and manganese, 

the maximum concentration was less than 4 percent of the 

corresponding SMCL. However, for aluminum the maximum 

concentration was nearly 200 percent of the corresponding 

SMCL. Results for blind blanks submitted to NWQL to evaluate laboratory data quality indicate false positive detections of 

aluminum in blank samples submitted to the laboratory during 

July and August 2014 and during August–December 2015 

(USGS Inorganic Blind Sample Project, https://bqs.usgs.gov/

ibsp/). Investigation of this issue by the NWQL indicated sporadic contamination at concentrations of as much as 63 μg/L 

from about July 2014 through December 2015, although the 

source of contamination and, therefore, the exact magnitude of 

contamination and the period(s) affected were not established 

(Tedmund Struzeski, USGS Inorganic Blind Sample Project, 

written commun., 2015). For NAWQA Project field blanks 

collected through the end of December 2015, reported detections of aluminum above the laboratory reporting limit were 

in blank samples collected primarily between May 29 and July 

16, 2014, and between March 25 and September 8, 2015.

Also regarding trace elements, the maximum concentration of manganese (1.83 μg/L) reported in a field blank 

from the Cycle 3 sampling period was less than 1 percent of 

the corresponding HHB of 300 μg/L. However, the USGS 

Office of Water Quality has documented random low-level 

contamination of water samples with manganese from certain 

capsule filters used by the NAWQA Project and across the 

USGS from about October 1, 2008, to about September 30, 

2014 (USGS Office of Water Quality, written commun., July 

1, 2016). Cobalt, which has no corresponding HHB, similarly 

was documented to be randomly introduced to water samples 

by the capsule filters. Blank samples for cobalt and manganese 

that were collected for the NAWQA Project during this period 

were evaluated to determine the possible effects of this contamination on environmental samples, and evaluation results 

were described in appendix 3 of Arnold and others (2017b).

Of the five nutrients or groups of nutrients that the laboratory analyzes directly (as opposed to the nutrients with calculated results), three were detected in at least one field blank 

collected in 2015 (table 3.1), and four were detected in at least 

one field blank from the Cycle 3 sampling period (table 3.2). 

Two of the nutrients detected in field blanks from the Cycle 

3 sampling period (nitrite and nitrate) have HHBs (table 2 of 

Arnold and others, 2018); none have SMCLs. For each of the 

two nutrients with HHBs, the maximum concentration measured in a field blank from the Cycle 3 sampling period was 

less than 1 percent of the corresponding threshold.

Blank samples collected in 2012 were analyzed for 

85 VOCs, and blank samples collected in 2013 through 2015 

were analyzed for a different (but partially overlapping) list of 

85 VOCs; the change in laboratory methods and constituent 

lists resulted in a total of 129 different VOCs being included 

in the overall dataset of blank results. In total, 15 VOCs were 

detected in at least 1 field blank collected in 2015 (table 3.1), 

and 25 VOCs were detected in at least 1 field blank from the 

Cycle 3 sampling period (table 3.2). Of the 12 compounds 

detected in field blanks from the Cycle 3 sampling period 

(1,1-dichloroethene, 1,2-dibromo-3-chloropropane, 1,4-dichlorobenzene, benzene, carbon disulfide, dichloromethane, ethylbenzene, m-xylene plus p-xylene, o-xylene, styrene, toluene, 

and trichloromethane), all have HHBs (table 2 of Arnold and 

others, 2018) and none have SMCLs. For 9 of the 12 VOCs 

with HHBs, the maximum concentration measured in a blank 
66 Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project

was less than 1 percent of the corresponding HHB threshold; 

for the remaining 3 VOCs (1,1-dichloroethene, 1,2-dibromo3-chloropropane, and dichloromethane), the maximum concentration was less than 3 percent of the corresponding HHB 

threshold.

Blank samples collected in 2012 were analyzed for 

137 pesticide compounds, and blank samples collected in 2013 

through 2015 were analyzed for 227 pesticide compounds; 

the change in laboratory methods and constituents resulted in 

272 pesticide compounds being included in the overall dataset 

of blank results. Five pesticide compounds were detected in at 

least one field blank collected in 2015 (table 3.1), and 21 pesticide compounds were detected in at least one field blank from 

the Cycle 3 sampling period (table 3.2). Of the 15 compounds 

detected in field blanks from the Cycle 3 sampling period 

(atrazine, metolachlor, nicosulfuron, piperonyl butoxide, 

aldicarb sulfone, bromacil, cis-permethrin, desulfinylfipronil, 

diflubenzuron, imazethapyr, metribuzin, oxamyl, propiconazole, tebuthiuron, and trans-permethrin), all have HHBs 

(table 2 of Arnold and others, 2018) and none have SMCLs. 

For all the pesticide compounds with HHBs, the maximum 

concentration measured in a field blank was about 0.25 percent 

or less of the corresponding HHB threshold.

A few of the special analytes collected in only selected 

well networks were detected in one or more field blanks from 

the Cycle 3 sampling period. The one field blank collected in 

2015 for arsenic speciation had no detections. Five field blanks 

were collected for arsenic speciation during the Cycle 3 sampling period. In these five field blanks, there were no detections of three arsenic species (arsenite, dimethylarsinate, and 

monomethylarsonate), but arsenate was detected in one field 

blank at a concentration of 1.51 μg/L, which is about 15 percent of the HHB of 10 μg/L for total arsenic. Therefore, it is 

possible that contamination could limit the suitability of arsenate results for comparison with the arsenic HHB. Perchlorate 

was not detected in any of the nine field blanks collected during 2015, or in any of the 14 total field blanks collected during 

the Cycle 3 sampling period. Hexavalent chromium was 

detected in one of the seven field blanks collected in 2015 at 

a concentration of 0.2 μg/L, which is 5.0 percent of the upper 

cancer HBSL of 4 μg/L. Hexavalent chromium was detected 

in 2 of the 14 field blanks from the Cycle 3 sampling period at 

a maximum concentration of 0.3 μg/L, which is 7.5 percent of 

the upper cancer HBSL. Corresponding total chromium values 

typically are reported by the same USGS Trace Metal Laboratory in Boulder, Colo., that analyzes for hexavalent chromium. 

For the seven hexavalent chromium field blanks collected in 

2015, six had corresponding total chromium results, and no 

detections of total chromium were reported. Of the 13 samples 

from the Cycle 3 sampling period that had total chromium 

results reported by this laboratory, 2 field blanks had a detection of total chromium at concentrations as much as 0.6 μg/L, 

which is 0.6 percent of the HHB of 100 μg/L. Therefore, it 

seems that there is minimal potential for contamination of 

hexavalent chromium or total chromium from the USGS Trace 

Metal Laboratory to affect comparison of these values to 

HHBs.

The maximum concentrations of major and minor ions, 

nutrients, VOCs, and pesticide compounds in field blanks from 

the Cycle 3 sampling period are all substantially less than the 

thresholds used by the NAWQA Project to distinguish between 

low and moderate concentrations (50 percent of the HHB or 

SMCL for inorganic constituents, and 10 percent of the HHB 

for organic constituents); therefore, results of the field blank 

samples for these constituent groups indicate minimal potential for effects of contamination on the number of groundwater samples that would be classified as having moderate or 

high concentrations relative to current HHBs or SMCLs. For 

trace elements, the maximum concentrations in field blanks 

from the Cycle 3 sampling period also are substantially less 

than the relevant thresholds with the exception of aluminum. 

Because data from laboratory blind blanks and from NAWQA 

Project field blanks indicate that laboratory contamination 

might have affected aluminum results considerably for some 

environmental samples from late May 2014 through at least 

December 2015, aluminum results from this period cannot be 

classified positively as moderate or high relative to the SMCL 

of 50 μg/L. 

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For more information about this publication, contact

Director, USGS Central Midwest Water Science Center 

405 N. Goodwin 

Urbana, IL 61801

(217) 328–8747

For additional information visit https://il.water.usgs.gov

Publishing support provided by the 

Rolla Publishing Service Center

Arnold and others—Groundwater-Quality and Select Quality-Control Data from the National Water-Quality Assessment Project—Data Series 1087 

ISSN 2327-638X (online)

https://doi.org/10.3133/ds1087