U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2008–5240

NATIONAL WATER QUALITY ASSESSMENT PROGRAM

Factors Affecting Water Quality in Selected Carbonate 

Aquifers in the United States, 1993–2005
Cover.

1. Penns Creek Valley in Centre County, Pa., in the Valley and Ridge carbonate aquifer (Photograph by Albert E. Becher, U.S. 

Geological Survey) 

2. Yates Spring in Decatur County, Ga., in the Floridan aquifer (Photograph by Alan M. Cressler, U.S. Geological Survey)

3. Housing development in southwestern Florida, near Tampa, Fla., in the Floridan aquifer (Photograph by Harley Means, Florida 

Geological Survey)

4. Range land in Uvalde County, Tex., in the Edwards-Trinity aquifer (Photograph by George Ozuma)

5. Shoshone springs in Great Basin National Park, Nev., in the Basin and Range carbonate aquifer (Photograph by Philip Gardner, U.S. 

Geological Survey)

6. Malone Spring near Niota, Tenn., in the Valley and Ridge carbonate aquifer (Photograph by Gregory C. Johnson, U.S. Geological 

Survey)

7. A sinkhole in Cumberland County, Pa., in the Valley and Ridge carbonate aquifer (Photograph by William E. Kochanov, Pennsylvania 

Geological Survey) 

1

5 2

4

6

7

3
Factors Affecting Water Quality in Selected 

Carbonate Aquifers in the United States, 

1993–2005

By Bruce D. Lindsey, Marian P. Berndt, Brian G. Katz, Ann F. Ardis, and 

Kenneth A. Skach

Scientific Investigations Report 2008–5240

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2009

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Lindsey, B.D., Berndt, M.P., Katz, B.G., Ardis, A.F., and Skach, K.A., 2009, Factors affecting water quality in selected 

carbonate aquifers in the United States, 1993–2005: U.S. Geological Survey Scientific Investigations Report 2008-

5240, 117 p. 
iii

Contents

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

Introduction.....................................................................................................................................................2

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

Description of Study Area ...................................................................................................................3

Aquifer Characteristics and Factors for Data Analysis...........................................................................8

Description of Aquifers........................................................................................................................8

Basin and Range Carbonate-Rock Aquifers ...........................................................................8

Biscayne Aquifer..........................................................................................................................8

Castle Hayne Aquifer ..................................................................................................................9

Edwards-Trinity Aquifer System................................................................................................9

Floridan Aquifer System ...........................................................................................................10

Mississippian Aquifers..............................................................................................................10

Ordovician Aquifers...................................................................................................................10

Ozark Plateaus Aquifer System...............................................................................................11

Piedmont and Blue Ridge Carbonate-Rock Aquifers...........................................................11

Prairie du Chien of the Cambrian-Ordovician Aquifer System...........................................11

Silurian-Devonian/Upper Carbonate Aquifers......................................................................12

Valley and Ridge Carbonate-Rock Aquifers ..........................................................................12

Hydrogeology................................................................................................................................................12

Degree of Confinement......................................................................................................................16

Karstification........................................................................................................................................17

Springs..................................................................................................................................................17

Recharge..............................................................................................................................................18

Sampling-Network Characteristics .................................................................................................18

Source Factors...........................................................................................................................20

Fate and Transport Factors ......................................................................................................29

Methods.........................................................................................................................................................31

Sample Collection and Processing..................................................................................................31

Quality-Assurance Methods and Results.......................................................................................31

Nitrate Blank Sample Results..................................................................................................31

Pesticide Blank and Spike Recovery Analysis .....................................................................31

Volatile Organic Compound Computational and Blank Analysis .......................................32

Statistical Methods Used to Analyze Water-Quality Data...........................................................32

Assessment Levels....................................................................................................................33

Wilcoxon Rank-Sum, Kruskal-Wallis, and Nonparametric Tukey’s Test ..........................33

Contingency Tables ...................................................................................................................33

Spearman’s Rank Correlation ..................................................................................................33

Logistic Regression ...................................................................................................................34

Analysis of Geochemical Data .........................................................................................................34

Drinking-Water Standards and Health-Based Screening Levels...............................................34

Water-Rock Interactions and Ground-Water Geochemistry................................................................35

Major Ions, Dissolved Solids, pH, and Mineral Saturation Indices............................................35
iv

Oxidation-Reduction Status ..............................................................................................................43

Correlations with Well Depth............................................................................................................51

Radon ..................................................................................................................................................52

Factors Affecting Anthropogenic Contaminants....................................................................................53

Nitrate ..................................................................................................................................................53

Distribution of Nitrate Concentrations ...................................................................................53

Factors Affecting Nitrate Concentrations .............................................................................53

Source Factors..................................................................................................................53

Fate and Transport Factors .............................................................................................55

Ground-Water Age ..................................................................................................55

Degree of Confinement...........................................................................................55

Karst Features ..........................................................................................................59

Redox Status.............................................................................................................59

Saturation Indexes and Geochemistry.................................................................59

Well-Specific Information ......................................................................................61

Interaction of Source, Fate, and Transport Factors ....................................................62

Pesticides.............................................................................................................................................65

Detection Levels and Data-Analysis Methods .....................................................................65

Occurrence and Distribution ...................................................................................................67

Assessment of Potential Human-Health Significance ........................................................69

Factors Affecting Occurrence of Frequently Detected Pesticides ...................................75

Aquifers and Study Types................................................................................................75

Source Factors..................................................................................................................75

Fate and Transport Factors .............................................................................................83

Interaction of Source, Fate, and Transport Factors ....................................................88

Volatile Organic Compounds.............................................................................................................93

Detection Levels and Data-Analysis Methods .....................................................................98

Occurrence and Distribution ...................................................................................................98

Assessment of Potential Human-Health Significance ......................................................100

Factors Affecting Occurrence of Frequently Detected Volatile Organic 

Compounds..................................................................................................................106

Summary......................................................................................................................................................106

Acknowledgments.....................................................................................................................................110

References Cited........................................................................................................................................110
v

Figures

1. Map showing locations of 12 selected carbonate aquifers or aquifer systems, other 

carbonate principal aquifers, areas of carbonate geology that are not principal

aquifers, sampling sites, and National Water-Quality Assessment (NAWQA) 

Program study units included in this study ..............................................................................4

2-3. Pie charts showing:

2. Ground-water withdrawals in the United States and the relative importance of

carbonate aquifers or aquifer systems, 2000..................................................................8

3. Median percentages of land use in a 1,640-foot radius around sampling 

sites for each of the 12 carbonate aquifers or aquifer systems ................................23

4-6. Box plots showing: 

4. Median population density from 1990 census in 1,640-foot radius around 

sampling sites in the 12 carbonate aquifers or aquifer systems ...............................25

5. Median values for nitrogen from septic systems, manure, fertilizer, and 

atmospheric deposition, and distribution of total nitrogen input from all 

sources for the 1,640-foot radius around sampling sites in the 12 carbonate 

aquifers or aquifer systems .............................................................................................27

6. Median application rates of selected pesticides for the 1,640-foot radius 

around sampling sites in the 12 carbonate aquifers or aquifer systems .................28

7. Piper diagrams for 12 carbonate aquifers or aquifer systems, 1993–2005 .......................39

8. Bar charts showing dominant-ion water types in 12 carbonate aquifers or aquifer 

systems, 1993–2005 ....................................................................................................................41

9. Graphs showing ratio of calcium plus magnesium to bicarbonate for each aquifer 

in 12 carbonate aquifers or aquifer systems, 1993–2005 .....................................................42

10-13. Box plots showing: 

10. Distribution of saturation index values for A) calcite and B) dolomite by 

aquifer and confinement category in 12 carbonate aquifers or aquifer

systems, 1993–2005 ...........................................................................................................44

11. Distribution of saturation index values for gypsum by aquifer and confinement 

category in 12 carbonate aquifers or aquifer systems, 1993–2005 ...........................45

12. Distribution of A) dissolved oxygen and B) dissolved organic carbon by 

aquifer and confinement category in 12 carbonate aquifers or aquifer

systems, 1993–2005 ...........................................................................................................47

13. Distribution of dissolved oxygen by aquifer and confinement category in 12 

carbonate aquifers or aquifer systems, 1993–2005......................................................48

14. Pie charts showing oxidation-reduction (redox) status categories in 12 carbonate

aquifers or aquifer systems, 1993–2005 ..................................................................................49

15-16. Bar charts showing: 

15. Redox status grouped by confinement category in 12 carbonate aquifers or

aquifer systems, 1993–2005..............................................................................................50

16. Redox status grouped by ground-water age in 12 carbonate aquifers or

aquifer systems, 1993–2005..............................................................................................50

17-21. Box plots showing: 

17. Distribution of radon values in aquifers and by confinement category in 12 

carbonate aquifers or aquifer systems, 1993–2005......................................................52

18. Distribution of concentrations of nitrate in 12 carbonate aquifers or aquifer

systems, 1993–2005 ...........................................................................................................54
vi

19. Distribution of concentrations of nitrate by ground water-age category in 

eight carbonate aquifers or aquifer systems, 1993–2005............................................57

20. Distribution of concentrations of nitrate by confinement category and aquifer

in 12 carbonate aquifers or aquifer systems, 1993–2005 ............................................58

21. Distribution of concentrations of nitrate related to the redox status in 12

carbonate aquifers or aquifer systems, 1993–2005......................................................61

21-22. Bar charts showing: 

22. Percent of detections for the herbicides atrazine, deethylatrazine (a

degradate of atrazine), simazine, metolachlor, and prometon by assessment 

level in 12 carbonate aquifers or aquifer systems sampled during 1993–2005 .......68

23. Frequencies of individual and multi-compound detections in relation to

A) aquifer or aquifer system, B) degree of confinement, and C) predominant 

land use around well ........................................................................................................70

24. Map showing sample locations and number of pesticides detected out of 47

pesticides analyzed in 12 carbonate aquifers or aquifer systems ....................................71

25-30. Graphs showing: 

25. Concentrations of dieldrin and human-health benchmarks in various land-use

categories in 12 carbonate aquifers or aquifer systems ............................................72

26. Concentrations of diazinon and human-health benchmarks in various land-use

categories in 12 carbonate aquifers or aquifer systems ............................................73

27. Concentrations of atrazine and human-health benchmarks in various land-use

categories in 12 carbonate aquifers or aquifer systems ...........................................74

28. Concentrations of simazine and human-health benchmarks in various

land-use categories in 12 carbonate aquifers or aquifer systems............................76

29. Concentrations of metolachlor and human-health benchmarks in various land

use categories in 12 carbonate aquifers or aquifer systems.....................................77

30. Concentrations of prometon and human-health benchmarks in various land

use categories in 12 carbonate aquifers or aquifer systems.....................................78

31. Map showing sample locations and comparison to human-health benchmarks for

atrazine, deethylatrazine, simazine, metolachlor, and prometon, in 12 carbonate 

aquifers or aquifer systems .....................................................................................................79

32-40. Bar charts showing: 

32. Frequency of detections of the five frequently occurring pesticides by aquifer, 

in 12 carbonate aquifers or aquifer systems, 1993–2005 ............................................80

33. Frequency of detections of the five frequently occurring pesticides by type of

National Water-Quality Assessment study in 12 carbonate aquifers or aquifer 

systems, 1993–2005 ...........................................................................................................80

34. Percent detections of atrazine and deethylatrazine by land use and

confinement category in 12 carbonate aquifers or aquifer systems, 

1993–2005 ............................................................................................................................89

35. Percent detections of metolachlor and simazine by land use and confinement

category in 12 carbonate aquifers or aquifer systems, 1993–2005 ..........................90

36. Percent detections of prometon by land use and confinement category in 12

carbonate aquifers or aquifer systems, 1993–2005 .....................................................91

37. Detection frequency for samples with one or more, two or more, three or

more, and four or more volatile organic compounds (VOCs) detected including 

all detections and at the 0.2 micrograms per liter assessment level in 12 

carbonate aquifers or aquifer systems, 1993–2005......................................................98
vii

38. Detection frequency for samples with one or more, two or more, three or 

more, and four or more volatile organic compounds (VOCs) detected at the

0.2 micrograms per liter assessment level by A) aquifer, B) confinement 

category, C) redox status, and D) land-use category in 12 carbonate aquifers 

or aquifer systems, 1993–2005.........................................................................................99

39. Detection frequencies of the eight most frequently detected volatile organic

compounds at the 0.2 micrograms per liter assessment level in 12 carbonate 

aquifers or aquifer systems, 1993–2005 .......................................................................100

40. Detection frequencies of the eight most frequently detected volatile organic

compounds in each aquifer at the 0.2 micrograms per liter assessment level 

in 12 carbonate aquifers or aquifer systems, 1993–2005 ..........................................101

41-44. Graphs showing: 

41. Concentrations and human-health benchmark quotient values for

chloroform by land-use category in 12 carbonate aquifers or aquifer 

systems, 1993–2005 .........................................................................................................102

42. Concentrations and human-health benchmark quotient values of

tetrachloroethene (PCE) by land-use category in 12 carbonate aquifers or 

aquifer systems, 1993–2005............................................................................................103

43. Concentrations and human-health benchmark quotient values of

trichloroethene (TCE) by land-use category in 12 carbonate aquifers or 

aquifer systems, 1993–2005............................................................................................104

44. Concentrations and human-health benchmark quotient values of

1,2-Dichloropropane by land-use category in 12 carbonate aquifers or 

aquifer systems, 1993–2005............................................................................................105

45. Bar chart showing detection frequencies of the eight most frequently detected

volatile organic compounds at the 0.2 micrograms per liter assessment level by 

A) confinement category, B) redox status, and C) land use in 12 carbonate 

aquifers or aquifer systems, 1993–2005 ................................................................................107
viii

Tables

1. Total ground-water withdrawals for 12 carbonate aquifers or aquifer systems, by 

aquifer and state, for irrigation, public-supply, and self-supplied industrial water 

uses, 2000.......................................................................................................................................6

2. Hydrologic properties of the 12 carbonate aquifers or aquifer systems included in 

study..............................................................................................................................................13

3. Summary of network names, National Water-Quality Assessment (NAWQA) study 

types, numbers of wells and springs sampled, and sampling time period in the 12 

carbonate aquifers or aquifer systems included in study ...................................................19

4. Summary of water use by National Water-Quality Assessment (NAWQA) study 

type in the 12 carbonate aquifers or aquifer systems included in study...........................21

5. Summary of site characteristics for wells and springs in the 12 carbonate aquifers 

or aquifer systems included in study.......................................................................................22

6. Summary of underground storage tanks in 3,280-foot radius around sampling sites in 

the 12 carbonate aquifers or aquifer systems included in study........................................26

7. Summary of median hydrologic characteristics for the 1,640-foot radius around 

sampling sites in the 12 carbonate aquifers or aquifer systems included in study.........29

8. Summary of median soil characteristics for the 1,640-foot radius around sampling 

sites in the 12 carbonate aquifers or aquifer systems included in study..........................30

9. Descriptive statistics for well depths and selected inorganic constituents in 12 

carbonate aquifers or aquifer systems, 1993–2005...............................................................36

10. Numbers of samples and median values for well depths and selected inorganic 

constituents by aquifer, in 12 carbonate aquifers or aquifer systems, 1993–2005 ..........37

11. Comparison of water properties and concentrations of major ions in wells with 

human-health benchmarks and non-health guidelines for drinking water, in 12 

carbonate aquifers or aquifer systems, 1993–2005...............................................................38

12. Threshold concentrations for identifying redox-status category ......................................46

13. Spearman’s rank correlations between well depth and selected water 

characteristics in 12 carbonate aquifers or aquifer systems, 1993–2005 .........................51

14. Spearman’s rank correlations between nitrate concentration in ground water and 

variables representing nitrogen sources, in 12 carbonate aquifers or aquifer 

systems, 1993–2005 ....................................................................................................................56

15. Spearman’s Rank correlations between nitrate concentration and fate and 

transport variables in 12 carbonate aquifers or aquifer systems, 1993–2005 ..................60

16. Comparison of nitrate mean rank concentrations by type of confinement and

land-use grouping in 12 carbonate aquifers or aquifer systems, 1993–2005....................62

17. Comparison of nitrate mean rank concentrations by redox-status category and

land-use grouping in 12 carbonate aquifers or aquifer systems, 1993–2005....................63

18. Comparison of nitrate mean rank concentrations by redox-status category and

land-use grouping for water recharged in 1953 or later, in 8 of the 12 carbonate 

aquifers or aquifer systems, 1993–2005 ..................................................................................64

19. Results of logistic regression model predicting probability of nitrate being 

detected at a threshold of greater than 4 milligrams per liter in 12 carbonate 

aquifers or aquifer systems, 1993–2005 ..................................................................................64

20. Detection frequency for 47 pesticides in 12 carbonate aquifers or aquifer systems, 

1993–2005 .....................................................................................................................................66

21. Method detection limits and common reporting levels for frequently detected

pesticides in 12 carbonate aquifers or aquifer systems, 1993–2005..................................68
ix

22. Spearman’s rank correlations between potential source factors and pesticides 

in 12 carbonate aquifers or aquifer systems, 1993–2005 ....................................................82

23. Comparison of detection frequency of pesticides for water recharged before

1953 and in 1953 or later for 8 of the 12 carbonate aquifers or aquifer systems, 

1993–2005 .....................................................................................................................................83

24. Comparison of detection frequency of pesticides for ground-water sites by

aquifer-confinement category in 12 carbonate aquifers or aquifer systems, 

1993–2005 ....................................................................................................................................84

25. Spearman’s rank correlations between site-specific factors and pesticides in 12 

carbonate aquifers or aquifer systems, 1993-2005 ..............................................................85

26. Results of logistic regression model predicting probability of atrazine being 

detected at a threshold of greater than 0.01 micrograms per liter in 12 carbonate 

aquifers or aquifer systems, 1993–2005 .................................................................................92

27. Results of logistic regression model predicting probability of deethylatrazine being 

detected at a threshold of greater than 0.01 micrograms per liter in 12 carbonate 

aquifers or aquifer systems, 1993–2005 .................................................................................93

28. Results of logistic regression model predicting probability of simazine being 

detected at a threshold of greater than 0.01 micrograms in 12 carbonate aquifers 

or aquifer systems, 1993–2005 .................................................................................................94

29. Results of logistic regression model predicting probability of metolachlor being 

detected at a threshold of greater than 0.01 micrograms per liter in 12 carbonate 

aquifers or aquifer systems, 1993–2005 .................................................................................94

30. Results of logistic regression model predicting probability of prometon being 

detected at a threshold of greater than 0.01 micrograms per liter in 12 carbonate 

aquifers or aquifer systems, 1993–2005 .................................................................................94

31. List of volatile organic compounds analyzed, number of detections greater than or 

equal to 0.2 micrograms per liter, and human-health-benchmark exceedances in 

12 carbonate aquifers or aquifer systems, 1993-2005 .........................................................95
x

Conversion Factors, Abbreviations, and Datums

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2)

Flow rate

cubic foot per second (ft3

/s) 0.02832 cubic meter per second (m3/s)

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

/s)

inch per year (in/yr) 25.4 millimeter per year (mm/yr)

Radioactivity

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

Transmissivity*

foot squared per day (ft2

/d) 0.09290 meter squared per day (m2/d)

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

°F=(1.8×°C)+32

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

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

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

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

*Transmissivity: The standard unit for transmissivity is cubic foot per day per square foot times 

foot of aquifer thickness [(ft3

/d)/ft2]ft. In this report, the mathematically reduced form, foot 

squared per day (ft2/d), is used for convenience.

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

25°C).

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).
xi

FOREWORD

The U.S. Geological Survey (USGS) is committed to providing the Nation with credible 

scientific information that helps to enhance and protect the overall quality of life and 

that facilitates effective management of water, biological, energy, and mineral resources 

(http://www.usgs.gov/). Information on the Nation’s water resources is critical to ensuring longterm availability of water that is safe for drinking and recreation and is suitable for industry, 

irrigation, and fish and wildlife. Population growth and increasing demands for water make the 

availability of that water, now measured in terms of quantity and quality, even more essential to 

the long-term sustainability of our communities and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 

1991 to support national, regional, State, and local information needs and decisions related to 

water-quality management and policy (http://water.usgs.gov/nawqa). The NAWQA Program is 

designed to answer: What is the condition of our Nation’s streams and ground water? How are 

conditions changing over time? How do natural features and human activities affect the quality 

of streams and ground water, and where are those effects most pronounced? By combining 

information on water chemistry, physical characteristics, stream habitat, and aquatic life, the 

NAWQA Program aims to provide science-based insights for current and emerging water issues 

and priorities. From 1991-2001, the NAWQA Program completed interdisciplinary assessments 

and established a baseline understanding of water-quality conditions in 51 of the Nation’s river 

basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/studyu.html). 

Multiple national and regional assessments are ongoing in the second decade (2001–2012) 

of the NAWQA Program as 42 of the 51 Study Units are reassessed. These assessments 

extend the findings in the Study Units by determining status and trends at sites that have been 

consistently monitored for more than a decade, and filling critical gaps in characterizing the 

quality of surface water and ground water. For example, increased emphasis has been placed 

on assessing the quality of source water and finished water associated with many of the 

Nation’s largest community water systems. During the second decade, NAWQA is addressing 

five national priority topics that build an understanding of how natural features and human 

activities affect water quality, and establish links between sources of contaminants, the 

transport of those contaminants through the hydrologic system, and the potential effects of 

contaminants on humans and aquatic ecosystems. Included are topics on the fate of agricultural 

chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in 

stream ecosystems, effects of nutrient enrichment on aquatic ecosystems, and transport of 

contaminants to public-supply wells. These topical studies are conducted in those Study Units 

most affected by these issues; they comprise a set of multi-Study-Unit designs for systematic 

national assessment. In addition, national syntheses of information on pesticides, volatile 

organic compounds (VOCs), nutrients, selected trace elements, and aquatic ecology are 

continuing. 

The USGS aims to disseminate credible, timely, and relevant science information to address 

practical and effective water-resource management and strategies that protect and restore water 

quality. We hope this NAWQA publication will provide you with insights and information to 

meet your needs, and will foster increased citizen awareness and involvement in the protection 

and restoration of our Nation’s waters. 
xii

The USGS recognizes that a national assessment by a single program cannot address all waterresource issues of interest. External coordination at all levels is critical for cost-effective 

management, regulation, and conservation of our Nation’s water resources. The NAWQA 

Program, therefore, depends on advice and information from other agencies—Federal, 

State, regional, interstate, Tribal, and local—as well as nongovernmental organizations, 

industry, academia, and other stakeholder groups. Your assistance and suggestions are greatly 

appreciated.

Matthew C. Larsen

Associate Director for Water
Abstract

Carbonate aquifers are an important source of water in 

the United States; however, these aquifers can be particularly susceptible to contamination from the land surface. The 

U.S. Geological Survey National Water-Quality Assessment 

(NAWQA) Program collected samples from wells and springs 

in 12 carbonate aquifers across the country during 1993–2005; 

water-quality results for 1,042 samples were available to 

assess the factors affecting ground-water quality. These aquifers represent a wide range of climate, land-use types, degrees 

of confinement, and other characteristics that were compared 

and evaluated to assess the effect of those factors on water 

quality. Differences and similarities among the aquifers were 

also identified. Samples were analyzed for major ions, radon, 

nutrients, 47 pesticides, and 54 volatile organic compounds 

(VOCs).

Geochemical analysis helped to identify dominant 

processes that may contribute to the differences in aquifer 

susceptibility to anthropogenic contamination. Differences 

in concentrations of dissolved oxygen and dissolved organic 

carbon and in ground-water age were directly related to the 

occurrence of anthropogenic contaminants. Other geochemical 

indicators, such as mineral saturation indexes and calciummagnesium molar ratio, were used to infer residence time, 

an indirect indicator of potential for anthropogenic contamination. Radon exceeded the U.S. Environmental Protection 

Agency proposed Maximum Contaminant Level (MCL) of 

300 picocuries per liter in 423 of 735 wells sampled, of which 

309 were drinking-water wells.

In general, land use, oxidation-reduction (redox) status, 

and degree of aquifer confinement were the most important 

factors affecting the occurrence of anthropogenic contaminants. Although none of these factors individually accounts 

for all the variation in water quality among the aquifers, a 

combination of these characteristics accounts for the majority of the variation. Unconfined carbonate aquifers that had 

high percentages of urban or agricultural land, or a combination of both, had higher concentrations and higher frequency 

of detections for most of the anthropogenic contaminants than 

areas with other combinations of land use and degree of aquifer confinement. Redox status is an indicator of more recently 

recharged water and affects the fate of some contaminants.

Median concentrations of nitrate were highest in the 

Valley and Ridge and Piedmont aquifers and lowest in the 

Biscayne, Castle Hayne, and Silurian-Devonian/Upper carbonate aquifers. Nitrate concentrations were significantly higher 

in unconfined aquifers than in confined aquifers and semiconfined/mixed confined aquifers (wells in aquifers with breached 

confining layers or wells open to both a confined and an 

unconfined aquifer). Water recharged after 1953 had significantly higher concentrations of nitrate than water recharged 

prior to 1953. Redox status was also a key factor affecting 

nitrate concentrations; in recently recharged waters, samples in 

oxic waters had significantly higher concentrations of nitrate 

than anoxic waters, regardless of land use in the area around 

the well. Samples from 54 wells (5 percent) exceeded the U.S. 

Environmental Protection Agency MCL of 10 mg/L for nitrate 

in drinking water. Most of the samples exceeding the drinkingwater standard (52 samples, or 5 percent) were in domestic 

supply wells in agricultural areas. The Piedmont and Valley 

and Ridge aquifers had the largest number of samples (45) 

exceeding the MCL; in the remaining aquifers only 9 samples 

had concentrations of nitrate that exceeded the MCL (about 

1 percent). None of the water recharged prior to 1953 and only 

a single sample from a confined aquifer had nitrate concentrations that exceeded 10 mg/L as N.

Wells were sampled for a minimum of 47 pesticides. 

Detection frequencies and comparisons varied depending on 

the assessment level used. At least 1 of the 47 pesticides was 

detected at 509 (50 percent) of the 1,027 sites where pesticide data were available using the ‘all detections’ assessment 

level—that is, including any quantified detection as well as 

any estimated values where the compound was definitively 

detected. Multiple pesticides were frequently detected in a 

sample of water from a site; 39 percent of the samples had two 

or more pesticides detected in the same sample, and 4 percent 

of the samples had six or more pesticides detected. Dieldrin 

was detected at 20 sites, 9 of which were from either domestic 

or public supply wells, at a concentration above the HealthBased Screening Level (HBSL) of 0.002 μg/L. Diazinon was 

detected at a concentration greater than the HBSL of 1 μg/L at 

a single site, which was also a domestic supply well. These are 

Factors Affecting Water Quality in Selected Carbonate 

Aquifers in the United States, 1993–2005

By Bruce D. Lindsey, Marian P. Berndt, Brian G. Katz, Ann F. Ardis, and Kenneth A. Skach
2 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

the only samples where a pesticide exceeded a human-health 

benchmark.

The most frequently occurring pesticide compounds 

were four herbicides—atrazine, simazine, metolachlor, and 

prometon—and deethylatrazine, a degradate of atrazine. These 

pesticides typically were detected at concentrations that were 

less than 10 percent of a human-health benchmark. Of the 

four frequently occurring pesticides, only samples for atrazine 

(4 percent) and simazine (0.1 percent) had concentrations that 

exceeded 10 percent of the human-health benchmark; most 

of these cases were in agricultural areas. It is important to 

note, however, that the most frequently occurring pesticide 

degradate compound—deethylatrazine—has no human-health 

benchmark. Using a common assessment level of 0.01 μg/L, 

four of the aquifers—Biscayne, Mississippian, Piedmont, and 

Valley and Ridge—had at least one of these five compounds 

detected in more than 30 percent of the wells sampled. These 

four aquifers, along with the Ordovician, Ozark Plateaus, and 

Prairie du Chien aquifers were the aquifers or aquifer systems 

that had concentrations of pesticides that exceeded 10 percent 

of a human-health benchmark. Water recharged after 1953 had 

a significantly higher percentage of detections of pesticides 

than water recharged before 1953, and water from unconfined 

aquifers had a significantly higher percentage of detections of 

pesticides than water from confined or semiconfined/mixed 

confined aquifers. Water from sites in unconfined aquifers, 

where land use was agricultural or urban, accounted for the 

vast majority of detections of pesticides. Dissolved oxygen 

concentration was positively related to pesticide occurrence, 

which likely reflects the positive association between dissolved oxygen concentration and recently recharged water.

Water samples were collected for analysis of VOCs at 

793 sites—154 samples were analyzed for 54 VOCs from 

1993 through 1995 and 639 samples were analyzed for 86 

VOCs from 1996 through 2005. Twenty percent of samples 

contained one or more VOCs at concentrations greater than or 

equal to 0.2 μg/L (159 of 793 samples). The aquifers with the 

highest percentage of samples containing one or more VOCs 

were the Castle Hayne (about 41 percent of samples) and 

Biscayne aquifers (34 percent). The most frequently detected 

VOCs were chloroform, tetrahydrofuran, tetrachloroethene 

(PCE), toluene, acetone, ethylmethylketone, methyl tert-butyl 

ether (MTBE), and trichloroethene (TCE). Low-level concentrations of VOCs occurred in a much larger percentage of a 

subset of the data (the 639 samples analyzed using a low-level 

analytical method). In these samples, 69 percent of the 639 

samples contained 1 or more VOCs, indicating the vulnerability of the carbonate aquifers to low-level VOC contamination. Four VOCs were detected at concentrations exceeding 

their respective MCLs in five samples, all of which were from 

drinking-water wells. Vinyl chloride concentrations exceeded 

the MCL of 2 μg/L in two samples from urban areas in the 

unconfined Biscayne aquifer. PCE, TCE, and 1,2-dichloropropane each had one sample with a concentration greater than 

their MCLs of 5 μg/L; these samples were from agricultural 

and urban areas in the unconfined Mississippian aquifer.

Water quality in the 12 carbonate aquifers was highly 

variable. Most of the samples met drinking-water standards. 

The occurrence of anthropogenic contaminants was related to 

contaminant sources but also was affected by degree of aquifer 

confinement, ground-water age, and redox status. Areas with 

higher amounts of agricultural or urban land in unconfined 

aquifers were the most likely to have elevated concentrations 

of anthropogenic contaminants.

Introduction

Carbonate aquifers and aquifer systems are an important 

global water resource, providing 25 percent of drinkingwater supplies to the global population (Quinlan and Ewers, 

1989), and in the contiguous United States, carbonate rocks 

cover 17 percent of the land surface (fig. 1) (Davies and 

others, 1984). Carbonate aquifers provide 22 percent of the 

United States public ground-water supply (fig. 2) (Maupin 

and Barber, 2005). The U.S. Geological Survey (USGS) has 

delineated the extent and composition of principal aquifers of 

the United States (U.S. Geological Survey, 2003), and 17 of 

these are designated as carbonate or sandstone and carbonate 

aquifers or aquifer systems (two or more related aquifers). 

The USGS National Water-Quality Assessment (NAWQA) 

Program has collected water-quality samples in many of these 

carbonate aquifers, and this report presents an analysis of the 

results of that sampling. These carbonate aquifers sampled as a 

part of the NAWQA Program have consistent and comparable 

data available on hydrogeology and geochemistry, and these 

data provide transferable scientific knowledge that could be 

applied to other carbonate aquifer systems. Carbonate aquifers considered in this study are not inclusive of all carbonate 

aquifers in the United States but rather represent a selection of 

aquifers studied by the NAWQA Program, which consequently 

allows for comparative study.

Carbonate aquifers commonly are referred to as karst 

aquifers. Karst is a term for the unique landscape that forms 

from the dissolution of carbonate rocks and other soluble 

rocks such as gypsum, which are more soluble than other 

types of geologic media. A karst aquifer is defined as an aquifer in which the flow of water is or can be appreciable through 

one or more of the following: joints, faults, bedding-plane 

partings, and cavities—any or all of which have been enlarged 

by dissolution (Field, 2002). Although karst aquifers can be in 

other bedrock types, most karst aquifers in the United States 

are in carbonate bedrock (White, 1993; Weary, 2006). Conversely, according to Quinlan and others (1991), “If there is 

carbonate rock, there is almost certainly some type of karst.” 

So, for purposes of this report, the carbonate aquifers can be 

considered karst aquifers as well, although they may have 

varying degrees of development of karst features.

Most of the permeability and hence transmissivity of the 

carbonate strata is formed when slightly acidic meteoric water 

dissolves and enlarges solution openings in the rock. White 
Introduction 3

(1993) describes the three levels of permeability types that 

can be found in karst aquifers, ranging from pores and vugs, 

to solutionally enlarged joints, fractures, and bedding-plane 

partings, to an integrated system of conduits of various sizes. 

Karst terranes are also characterized by features such as sinkholes, caves, springs, sinking streams, and underground drainage systems. The hydrologic properties of carbonate aquifers 

are highly variable, most notably in their heterogeneous 

permeability (Brahana and others, 1988). These aquifers are 

characterized by large fluctuations in water recharge and water 

supply, and respond rapidly to meteorological and hydrologic 

events.

 Because of the features of karst aquifers, every component of the aquifer can differ from a traditional porous 

medium: recharge can be focused through sinkholes or 

losing streams; transport can be non-Darcian (turbulent) in 

solution-enlarged conduits, with directions of flow dictated by 

geologic structure rather than gradient; and discharge can be 

focused at large springs. Furthermore, the porosity and permeability of the rock mass is continually evolving as a result of 

the chemical interactions between the rock and water moving 

through it. Most of these features that differ from a traditional 

porous medium increase the susceptibility of the carbonate aquifer to contamination. Water can enter the carbonate 

aquifers rapidly through sinkholes and travel rapidly through 

cracks, fissures, and conduits, hence making the system 

extremely susceptible to contamination. A better understanding of karst water resources requires an understanding of the 

unique features of carbonate aquifers and the differences and 

similarities between different carbonate aquifers.

Purpose and Scope

This report describes the factors affecting water quality 

in 12 selected carbonate aquifers in the United States. The 

carbonate aquifers detailed in this report were sampled as 

part of the NAWQA Program, implemented in 1991 to assess 

the condition of the nation’s streams and ground water. The 

carbonate aquifers sampled are (in alphabetical order): Basin 

and Range carbonate-rock aquifers, Biscayne aquifer, Castle 

Hayne aquifer, Edwards-Trinity aquifer system, Floridan aquifer system, Mississippian aquifers, Ordovician aquifers, Ozark 

Plateaus aquifer system, Piedmont and Blue Ridge carbonaterock aquifers, Prairie du Chien aquifer of the CambrianOrdovician aquifer system, Silurian-Devonian aquifers and 

Upper carbonate aquifer (combined), and Valley and Ridge 

carbonate-rock aquifers. Analytical results from ground-water 

samples from 865 wells and 177 springs from 14 NAWQA 

study units form the basis of this study. Samples were collected from 1993 to 2005. Properties and constituents analyzed 

include physical properties, major ions, nutrients, radon, 47 

pesticides, and 54 volatile organic compounds (VOCs).

Description of Study Area

The areas selected for this study included all aquifers in 

the United States designated on the USGS principal aquifer map (U.S. Geological Survey, 2003) as carbonate-rock 

or sandstone and carbonate-rock aquifers where the USGS 

NAWQA Program collected data (fig. 1). In principal aquifers designated as sandstone and carbonate, only that part of 

the aquifer that was carbonate was included in the study. The 

Cambrian-Ordovician aquifer is designated as a sandstone 

aquifer (U.S. Geological Survey, 2003); however, the Prairie 

du Chien aquifer is a part of the Cambrian-Ordovician aquifer 

that has carbonate lithology, so that aquifer was included in 

the study as well. The Silurian-Devonian and Upper carbonate aquifers are each principal aquifers; however, they were 

sampled as a single unit and are referred to as a single entity 

in this study. The study included data from all but 5 of the 17 

principal aquifers in the conterminous United States designated as carbonate or sandstone and carbonate. The SilurianDevonian and Mississippian aquifers are included in the study 

but have large areas without samples and are underrepresented 

with respect to the aquifer size (fig. 1). The sampling in the 

Edwards-Trinity aquifer system is concentrated in the southeastern part of the aquifer (fig. 1) where the majority of the 

water is used. Although a fairly substantial amount of the land 

area of the United States underlain by carbonate bedrock was 

not included in the study, only a relatively small amount of the 

areas designated as principal aquifers was not included in this 

study (fig. 1). This suggests that much of the land area of the 

United States that is underlain by carbonate bedrock and that 

is used as a substantial source of water was included in this 

study. Water-use data (fig. 2, table 1) indicate the importance 

of these aquifers as sources of drinking-water supply.

Carbonate aquifers are more extensive in the eastern 

United States, although the NAWQA Program also sampled 

water from carbonate aquifers in Texas, Nevada, and western 

Utah. The NAWQA study units that sampled carbonate aquifers included the Albemarle-Pamlico Drainages, ApalachicolaChattahoochee-Flint River Basins, Eastern Iowa Basins, 

Georgia-Florida Coastal Plain Drainages, Lower Susquehanna 

River Basin, Lower Tennessee River Basin, Nevada Basin and 

Range, Ozark Plateaus, Potomac River Basin, Santee River 

Basin and Coastal Drainages, South-Central Texas, Southern 

Florida Drainages, Upper Mississippi River Basin, and Upper 

Tennessee River Basin (fig. 1). The geographic distribution 

of these study units not only includes many of the carbonate 

aquifers, it also provides for a substantial amount of variability 

in precipitation, recharge, population density, and land use that 

allows comparisons of the effect of these characteristics on 

water quality.
4 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 1. Locations of 12 selected carbonate aquifers or aquifer systems, other carbonate principal aquifers, areas of carbonate geology that are not principal aquifers, sampling sites, and National Water-Quality Assessment (NAWQA) Program study units included in this study.

50°

40°30°

120° 110° 100° 90° 80° 70°

0 500 MILES 250

0 500 KILOMETERS 250

Base from U.S. Geological Survey digital data, 2003, 1:2,000,000Albers Equal-Area Conic projectionStandard parallels 25°00’N and 50°00’N, central meridian 96°00’W

50s

44

38 50

51

50

47

48

48

40

40

54

47

40

49

33

39

39

47

42s

42

42

53

Geology:AQUIFERS—U.S. Geological Survey, 2003AREAS OF CARBONATE GEOLOGY (not principal aquifers)—Nicholson and others, 2007a; Nicholson and others, 2007b; Ludington and others, 2007; Shaffer and others, 2007; Stoeser and others, 2007; Weary, 2008BASIN AND RANGE CARBONATE-ROCK AQUIFERS SUBCROP AREA—Thomas and others, 1986FLORIDAN AQUIFER SYSTEM OUTCROP AREA—Miller, 1990
Introduction

5

NAWQA Study Unit BoundariesAlbemarle-Pamlico DrainagesApalachicola Chattahoochee Flint River BasinsEastern Iowa BasinsGeorgia-Florida Coastal Plains DrainagesLower Susquehanna River BasinLower Tennessee River BasinNevada Basin and RangeOzark PlateausPotomac River BasinSantee River Basin and Coastal DrainagesSouth-Central TexasSouthern Florida DrainagesUpper Mississippi River BasinUpper Tennessee River Basin

123456789

1011121314

Number

on map

CARBONATE OR SANDSTONE AND CARBONATEPRINCIPAL AQUIFER NOT INCLUDED IN STUDYAREAS OF CARBONATE GEOLOGY THAT ARE NOT PRINCIPAL AQUIFERS

EXPLANATION

PRINCIPAL AQUIFERS WITH SAMPLES IN STUDY

EXPLANATION

SURFICIAL AQUIFERBISCAYNE AQUIFERFLORIDAN AQUIFER SYSTEM

South

Carolina

Georgia

Alabama

Mississippi Florida

Carbonate-rock Aquifers

42 Basin and Range carbonate-rock aquifers

42s Basin and Range carbonate-rock aquifers - Subcrop area

51 Biscayne aquifer54 Castle Hayne aquifer50 Floridan aquifer system

50s Floridan aquifer system - Subcrop area

48 Ordovician aquifers44 Ozark Plateaus aquifer system53 Piedmont and Blue Ridge carbonate-rock aquifers47 Silurian-Devonian aquifers49 Upper carbonate aquifer

Sandstone and Carbonate-rock Aquifers

38 Edwards-Trinity aquifer system40 Mississippian aquifers39 Valley and Ridge aquifers -- Carbonate-rock aquifer33 Cambrian-Ordovician aquifer system - Prairie du Chien

This map illustrates a two dimensional representation of a three-dimensional system. The principal aquifers of the Nation map (U.S. Geological Survey, 2003) -the source for this map- illustrates the areal extent of the uppermost aquifer. For this map, subcrop areas are shown for the Floridan aquifer system and Basin and Range carbonate-rock aquifer. For the other aquifers, productive aquifers may underlie other units, but the subcrop areas are not all shown on the map.

50°

40°30°

120° 110° 100° 90° 80° 70°

0 500 MILES 2500 500 KILOMETERS 250

9

8 1

2

5

14

11

4

12

3

7

7

10

13

6

NAWQA STUDY UNIT BOUNDARY

SAMPLING LOCATION Base modified from Miller, 1990

Base from U.S. Geological Survey digital data, 2003, 1:2,000,000Albers Equal-Area Conic projectionStandard parallels 25°00’N and 50°00’N, central meridian 96°00’W

Geology from U.S. Geological Survey, 2003

Figure 1. Locations of 12 selected carbonate aquifers or aquifer systems, other carbonate principal aquifers, areas of carbonate geology that are not principal aquifers, sampling sites, and National Water-Quality Assessment (NAWQA) Program study units included in this study.—Continued
6 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 1. Total ground-water withdrawals for 12 carbonate aquifers or aquifer systems, by aquifer and state, for irrigation, publicsupply, and self-supplied industrial water uses, 2000.—Continued

[Withdrawal data from Maupin and Barber (2005); Bold indicates totals for the aquifer; shading indicates states where samples were collected for current study]

Aquifer or aquifer system 

(name used in report) State

Total 

withdrawals Irrigation Public supply

Self-supplied 

industrial

Million gallons per day

Basin and Range carbonate-rock aquifers 

(Basin and Range) 73.6 0.50 71.2 1.92

Idaho .77 .00 .77 .00

Nevada .50 .50 .00 .00

Utah 72.3 .00 70.4 1.92

Biscayne aquifer 

(Biscayne) 812 114 698 .00

Florida 812 114 698 .00

Castle Hayne aquifer 

(Castle Hayne) 33.1 7.64 23.4 2.07

North Carolina 33.1 7.64 23.4 2.07

Edwards-Trinity aquifer system 

(Edwards-Trinity)1 740 282 411 47.2

Arkansas 7.54 .00 7.31 .23

Oklahoma 4.26 1.96 2.12 .18

Texas 729 280 402 46.8

Floridan aquifer system 

(Floridan) 3,640 1,930 1,330 385

Alabama 5.91 1.46 2.33 2.15

Florida 2,790 1,460 1,160 173

Georgia 782 436 142 205

South Carolina 57.6 28.5 24.5 4.61

Missippian aquifers 

(Mississippian)1 286 6.31 211 6.79

Alabama 42.3 1.64 34.6 6.12

Illinois 4.38 0 1.20 3.18

Indiana 2.88 .37 1.16 1.35

Iowa 7.01 .47 4.89 1.65

Kentucky 17.4 0 9.06 8.30

Maryland 1.08 .01 1.00 .07

Missouri 22.5 3.29 18.7 .48

Ohio 158 0 119 38.6

Pennsylvania 5.36 .06 3.74 1.56

Tennessee 24.1 .47 17.3 6.35

Virginia .07 0 .02 .05

West Virginia .88 0 .69 .19

Ordovician aquifers 

(Ordovician) 5.79 0.56 4.85 0.38

Kentucky 2.32 .00 1.94 .38

Tennessee 3.47 .56 2.91 .00

Ozark Plateaus aquifer system

(Ozark Plateaus) 165 20.5 131 14.0

Arkansas 8.44 1.23 7.16 .05

Kansas 7.12 .06 6.77 .29

Missouri 145 19.2 113 13.4

Oklahoma 4.30 .00 4.02 .28
Introduction 7

Table 1. Total ground-water withdrawals for 12 carbonate aquifers or aquifer systems, by aquifer and state, for irrigation, publicsupply, and self-supplied industrial water uses, 2000.—Continued

[Withdrawal data from Maupin and Barber (2005); Bold indicates totals for the aquifer; shading indicates states where samples were collected for current study]

Aquifer or aquifer system 

(name used in report) State

Total 

withdrawals Irrigation Public supply

Self-supplied 

industrial

Million gallons per day

Piedmont and Blue Ridge carbonate-rock aquifers

(Piedmont) 29.9 .35 17.8 11.8

Maryland 2.92 .25 .81 1.86

Pennsylvania 27.0 .10 17.0 9.93

Prairie du Chien of the Cambrian-Ordovician aquifer System

(Prairie du Chien)1 932 92.4 590 251

Illinois 149 3.79 116 29.8

Iowa 195 .40 61.0 134

Michigan 1.13 .35 .64 .14

Minnesota 271 26.4 209 35.6

Missouri 22.5 3.29 18.7 .48

Wisconsin 294 58.2 185 50.6

Silurian-Devonian/Upper carbonate aquifer 

(Silurian-Devonian/Upper carbonate) 256 27.8 172 56.4

Silurian-Devonian Illinois 55.9 5.77 47.6 2.51

Silurian-Devonian Indiana 41.7 4.53 33.8 3.37

Silurian-Devonian Iowa 49.8 .99 37.2 11.7

Silurian-Devonian Michigan 30.0 3.99 5.63 20.4

Silurian-Devonian Ohio 35.6 4.79 23.2 7.55

Silurian-Devonian Wisconsin 32.9 7.28 16.5 9.12

Upper carbonate Minnesota 9.55 .35 7.52 1.68

Valley and Ridge carbonate-rock aquifers 

(Valley and Ridge) 267 5.65 177 83.9

Alabama 71.2 .49 66.5 3.95

Georgia 39.7 3.35 24.4 11.9

Maryland 2.08 .17 1.64 .27

New Jersey 12.8 .12 9.66 3.07

Pennsylvania 69.9 .16 25.7 44.0

Tennessee 33.0 1.17 28.7 3.19

Virginia 30.8 .18 13.3 17.4

West Virginia 7.23 .01 7.08 .14

1

Aquifers are of mixed lithology, only the portion of these aquifers that are of carbonate lithology are included in the study; however, water-use totals are not 

broken out by the lithologic categories.
8 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Aquifer Characteristics and Factors for 

Data Analysis

In order to provide adequate background about the aquifers included in this study, information on the characteristics 

of the aquifers and other factors that can affect water quality is 

provided. Basic information about each aquifer is followed by 

a summary of important hydrogeologic characteristics of carbonate aquifers. The characteristics of the sampling networks 

with background information on the types and characteristics 

of sampling sites are summarized.

Description of Aquifers

Each of the 12 carbonate aquifers sampled for this study 

has unique characteristics. Information on the characteristics 

of the aquifers provides background that is useful in understanding the results of the water-quality analyses from each 

aquifer. The geography, lithology, climate, water use, and land 

use for each aquifer are described in this section.

Basin and Range Carbonate-Rock Aquifers

The Basin and Range carbonate-rock aquifers (hereafter 

referred to as the Basin and Range aquifer) of Nevada and 

Utah is one of the largest regional aquifers in the country, 

covering 92,000 mi2

 of the Great Basin (Schaefer and others, 

2005). The Great Basin is in the northern part of the Basin 

and Range Physiographic Province, a large area in the western 

United States with north-trending mountains separated by 

basins or valleys. The subcrop extent of the aquifer is much 

larger than its outcrop area (fig. 1). The Great Basin contains 

Igneous and

 metamorphic 

Sandstone

Other

(Total 77,000 millon gallons per day) (Total 16,000 millon gallons per day)

Ground-water withdrawals

for all categories

Ground-water withdrawals

for public supply Unconsolidated and

 semiconsolidated sand

 and gravel

Carbonate and

 carbonate-sandstone

EXPLANATION

Figure 2. Ground-water withdrawals in the United States and the relative importance of carbonate aquifers or aquifer 

systems, 2000 (Maupin and Barber, 2005).

two aquifer systems: an upper basin-fill aquifer and a lower 

carbonate-rock aquifer. The Basin and Range aquifer is comprised of thick sequences of limestone and dolomite with some 

shale, sandstone, and quartzite that underlie several topographic basins (Planert and Williams, 1995). The mountains 

commonly range in altitude from 8,000 to 10,000 ft above 

NAVD 88, and the topographic basins commonly range in 

altitude from 4,000 to 6,000 ft (Schaefer and others, 2005).

The climate in the area is generally arid to semiarid, 

although the mountains cause some climatic variability. Mean 

annual precipitation ranges from less than 5 in/yr in the basins 

and valleys in the south to 16 in/yr in the mountainous regions 

in the north (Prudic and others, 1995). Mean annual temperatures range from about 30°F in the northern valleys to about 

60°F in the extreme southern valleys.

Although land use in the area is primarily rangeland 

(Schaefer and others, 2005), with less forest and a smaller 

percentage of urban land, Las Vegas and Salt Lake City are 

located within the boundaries of the Basin and Range aquifer 

and are two of the fastest-growing cities in the western United 

States (Schaefer and others, 2005). Along with anticipated 

future population growth comes increased demands on the 

ground water. The carbonate-aquifer system represents a 

likely source of water for Las Vegas and Salt Lake City. Total 

ground-water withdrawal in 2000 for the Basin and Range 

aquifer was 73.6 Mgal/d, most of which (71.2 Mgal/d) was 

used for public supply (table 1).

Biscayne Aquifer

The Biscayne aquifer underlies an area of approximately 

4,000 mi2

 in four counties in southeastern and southernmost 

Florida (fig. 1). The Pleistocene-age rocks of the Biscayne 
Aquifer Characteristics and Factors for Data Analysis 9

the Coastal Plain ranges from about 44–48 in/yr (Trapp and 

Meisler, 1992); average annual temperature is about 55°F.

The Castle Hayne aquifer is the primary source of ground 

water for industrial, agricultural, and domestic users in the 

eastern coastal plain. Ground-water withdrawals in North 

Carolina for the year 2000 were 33.1 Mgal/d (table 1). About 

70 percent of total withdrawals (23.4 Mgal/d) are for public 

supply; about a quarter of the total is used for irrigation.

Edwards-Trinity Aquifer System

The Edwards-Trinity aquifer system comprises an area of 

approximately 77,000 mi2

 extending from southeastern Oklahoma through much of west and central Texas (fig. 1). Most 

of the aquifer system is in the Great Plains Physiographic 

Province. In Texas, the Edwards-Trinity aquifer system is 

comprised of Cretaceous-age rocks (Barker and Ardis, 1996) 

and includes three interrelated aquifers: the Edwards-Trinity 

aquifer, the Edwards (Balcones Fault Zone) aquifer, and the 

Trinity aquifer (Ryder, 1996). The Edwards-Trinity and Trinity aquifers are partly stratigraphically equivalent and exhibit 

some hydraulic connectivity.

The Edwards-Trinity aquifer underlies an area of approximately 34,000 mi2

 in west-central Texas. The Edwards (Balcones Fault Zone) aquifer stretches in a narrow band across 

approximately 3,000 mi2

 in south-central Texas and consists of 

highly fractured and faulted limestone and dolomite. The Trinity aquifer underlies an area of approximately 41,000 mi2

 from 

south-central Texas to southeastern Oklahoma and consists 

of interbedded sandstone, sand, limestone, and shale. For this 

national study, ground-water samples were collected from the 

Edwards aquifer and the Trinity aquifer only in Texas. Within 

the area of study, altitudes range from about 2,000 ft in the 

north to less than 1,000 ft above NAVD 88 on its southeastern 

margin (Barker and Ardis, 1996). In this report ‘EdwardsTrinity’ refers to the aquifer system rather than the aquifer of 

the same name.

Climate in the area is classified as subhumid, subtropical in the eastern part, and semiarid in the west. Almost all 

precipitation occurs as rainfall, ranging from west to east from 

less than 12 in. to about 30 in., respectively (Ryder, 1996). 

Mean annual temperature varies geographically from about 

66°F to 69°F. Land use in the study area is about half forested, 

with slightly less than half agricultural and grassland and 

less than 5 percent urban. The San Antonio metropolitan area 

(2000 population was 1.7 million) dominates the distribution 

of urban population in the study area.

The Edwards aquifer of the Balcones Fault Zone is one 

of the most productive carbonate aquifers in the United States 

(Maclay, 1995). The U.S. Environmental Protection Agency 

(USEPA) designated the Edwards aquifer as a sole-source 

aquifer in the San Antonio area, where it provides water to 

more than 1.5 million people. The total ground-water withdrawal from the Edwards-Trinity aquifer system in 2000 

was 740 Mgal/d of which withdrawal for public supply was 

411 Mgal/d (table 1).

aquifer are predominantly highly permeable limestone, as well 

as some less permeable sandstone and sand. The Biscayne 

aquifer is shallow and unconfined, covered generally by a thin 

veneer of soil. It is thickest near the coast, particularly at its 

northeast extent, and thins to the west. A clayey confining unit 

about 1,000 ft thick separates the Biscayne aquifer from the 

stratigraphically older Floridan aquifer system. Altitude in the 

area studied ranges from about 0 to 300 ft above NAVD 88.

Climate is humid subtropical characterized by relatively 

high annual temperatures averaging from about 72°F to 77°F. 

Annual precipitation ranges from 40 to 65 in. (McPherson and 

others, 2000).

Land use is primarily urban along the Atlantic coast; 

intense agricultural development exists along the southeastern 

edge of the Everglades as well as around Lake Okeechobee. 

There are also vast regions of wetlands in southern Florida.

The Biscayne aquifer is the sole source of drinking water 

for approximately 3 million people in a rapidly growing urban 

area along the Atlantic coast—from Boca Raton to the Florida 

Keys, including the major population center of Miami. Most 

of the drinking water along the southeastern Florida coast is 

pumped from the Biscayne aquifer (McPherson and others, 2000). In 2000, about 812 Mgal/d was withdrawn from 

the Biscayne aquifer; of this, more than three quarters of the 

total water withdrawal (698 Mgal/d) is used for public supply 

(table 1).

Castle Hayne Aquifer

The North Atlantic Coastal Plain aquifer system underlies an area of approximately 50,000 mi2

 extending along the 

Coastal Plain Physiographic Province from the North Carolina-South Carolina border to southern New Jersey (fig. 1). 

The North Atlantic Coastal Plain aquifer system comprises 

six regional aquifers in early Cretaceous- to Holocene-age 

deposits (Trapp and Horn, 1997). The vertical sequence of 

aquifers is as follows: the surficial aquifer, the Chesapeake 

aquifer, the Castle Hayne-Aquia aquifer, the Severn-Magothy 

aquifer, the Peedee-upper Cape Fear aquifer, and the Potomac 

aquifer. The productive limestone rocks of the Castle Hayne 

aquifer in the North Carolina Coastal Plain, a local part of 

the Castle Hayne-Aquia aquifer, comprise the only carbonate 

aquifer within the North Atlantic Coastal Plain aquifer system. 

The Castle Hayne aquifer is Eocene-Oligocene-age limestone 

(Trapp and Meisler, 1992), sandy marl, and limey sand and is 

considered to be a major aquifer except for areas where the 

transmissivity of the aquifer is less than 1,000 ft2

/d. The aquifer consists of a thick section of highly permeable limestone in 

southeastern North Carolina. The province borders the Atlantic 

Ocean; land surface is generally flat; altitudes increase slightly 

away from the coast. Land use in the area is a patchwork of 

wetlands, forested, and agricultural lands (Spruill and others, 

1998).

Climate in the Coastal Plain Physiographic Province is 

characterized as humid subtropical. Precipitation in most of 
10 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

 Floridan Aquifer System

The Floridan aquifer system underlies an area of 

approximately 100,000 mi2

 in the Coastal Plain Physiographic 

Province. The aquifer covers a large area that includes most of 

Florida, southeastern Georgia, and parts of southern Alabama, 

Mississippi, and South Carolina (Johnston and Bush, 1988) 

(fig. 1). The Floridan aquifer system is composed of a thick 

sequence of Tertiary-age carbonate rocks. These formations 

are hydraulically connected in varying degrees and form a 

regional hydrologic unit, albeit with substantial differences 

in the water-bearing properties. Aquifer thicknesses generally 

increase seaward and are thin near the northern limit of the 

aquifer. The Floridan aquifer system is hydrologically defined 

on the basis of permeability (Miller, 1986). In most places, the 

aquifer system is divided into the Lower and Upper Floridan 

aquifers, which are separated by a confining unit called the 

middle confining unit or semiconfining unit (where it is less 

than 100 ft thick). Numerous large springs, which are major 

discharge points, issue from the Upper Floridan aquifer, 

mostly in unconfined or thinly confined areas. Altitudes vary 

slightly from north to south; topography is hilly in South 

Georgia, and relief is flat southward.

The climate ranges from temperate in the north to subtropical in the south. Average annual temperatures range from 

60°F to 70°F from north to south. Precipitation averages about 

55 in/yr, but varies with land-surface altitude. For instance, in 

the east-central area, average annual precipitation is 45 in/yr, 

whereas in the Florida panhandle, the average annual precipitation is 60 in/yr (U.S. Geological Survey, 1986).

The predominant land-use categories on the Floridan 

aquifer system are forest (about 38 percent), agriculture (about 

26 percent), wetlands (almost 20 percent), and urban (less than 

10 percent).

 The Floridan aquifer system is one of the most productive aquifers in the world (Miller, 1990). It is a multi-use 

system; in addition to providing water to several large cities (Daytona Beach, Jacksonville, Orlando, Tallahassee, and 

St. Petersburg in Florida, and Brunswick and Savannah in 

Georgia) and extensive rural regions, the aquifer is extensively 

pumped for industrial and irrigation water supplies (Johnston 

and Bush, 1988; Marella and Berndt, 2005). In 2000, the 

irrigation and public-supply withdrawals from the Floridan 

aquifer system were 1,930 Mgal/d and 1,330 Mgal/d, respectively (table 1).

Mississippian Aquifers

The Mississippian aquifers cover a large part of the 

central United States, but the part included in this study lies 

predominantly within the Interior Low Plateaus Physiographic 

Province (Fenneman and Johnson, 1946), which extends from 

Indiana south to northern Alabama (fig. 1). The Mississippianage carbonates are predominantly limestone, but some 

dolostones and chert are also present.

These limestone aquifers are referred to locally as the 

Mississippian Plateau aquifers in Kentucky (Plebuch and 

others, 1985) and the Highland Rim aquifer system in Tennessee (Brahana and Bradley, 1986a). The limestone aquifers that yield the largest quantities of water are the Upper 

Mississippian Monteagle Limestone, the Ste. Genevieve 

Limestone, and the St. Louis Limestone. Where the Monteagle, the Ste. Genevieve, and the St. Louis are thin or missing, 

such as in the southwestern part of central Tennessee, the 

Warsaw Limestone along with chert and limestone beds of the 

Fort Payne Formation are the principal aquifers. Land-surface 

altitudes range from 500 to 1,300 ft above NAVD 88. Average 

annual precipitation is about 55 in/yr.

Predominant land use in the area is agricultural (pasture and cropland) (Kingsbury and Shelton, 2002), although 

chicken production is a growing industry.

As part of the NAWQA Program, ground water was sampled from carbonate aquifers underlying the Eastern Highland 

Rim, where these aquifers are an important source of drinkingwater supply (Woodside and others, 2004). In Alabama and 

Tennessee, the estimated ground-water withdrawal from the 

Mississippian aquifers was 66.4 Mgal/d in 2000. Public supply 

was 51.9 Mgal/d, of which the City of Huntsville, Ala., is a 

major user (table 1).

Ordovician Aquifers

Carbonate rocks of Ordovician age are the principal aquifers in large areas of central Kentucky and central Tennessee 

in the Interior Low Plateaus Physiographic Province (fig. 1). 

These carbonate-rock aquifers consist of limestone with some 

dolomite (Brahana and Bradley, 1986b). The aquifers are 

separated by confining units of shale and shaly limestone. The 

Middle Ordovician High Bridge and Stones River Groups and 

the Lexington Limestone and equivalent rocks are the most 

important carbonate-rock aquifers. The Ordovician carbonates are the predominant geologic units in the Outer and Inner 

Nashville Basin.

The NAWQA Program sampled ground water from the 

Ordovician aquifer within the Nashville Basin in Tennessee. 

Climate in the area is temperate, warm, and humid. Average 

temperatures range from 56°F to 61°F; the average annual 

temperature is about 59°F (U.S. Department of Commerce, 

1995). The area has low to moderate relief with some small 

hills and knobs. Land-surface altitudes generally are about 

700 ft above NAVD 88.

Average annual precipitation in the lower Tennessee 

River Basin is about 56 in. (U.S. Department of Commerce, 

1995). Precipitation increases from west to east, generally corresponding to the increase in altitude from west to east.

Land use in the Outer and Inner Nashville Basin, approximately the same geographic extent of the Ordovician aquifers 

in the area included in the study, is 60 percent agricultural 

(Kingsbury and others, 1999). The majority of the agricultural 

land is pasture. The predominant crops in the area are corn and 

soybeans. Urban land overlies about 1 percent of the area.
Aquifer Characteristics and Factors for Data Analysis 11

Total ground-water withdrawals from the Ordovician aquifers for Tennessee and Kentucky are 3.47 and 

2.32 Mgal/d, respectively (table 1), most of which is used for 

public supply.

Ozark Plateaus Aquifer System

The Ozark Plateaus aquifer system underlies most of 

southern Missouri, a large area of northern Arkansas, and 

small areas of southeastern Kansas and northeastern Oklahoma (fig. 1). Ozark Plateaus aquifer system rocks are Cambrian- to Mississippian-age limestones and dolomites that also 

contain beds of sandstone and chert. The confining units are 

mostly shale but also contain low permeability carbonates and 

sandstone.

The Ozark Plateaus aquifer system is composed of three 

individual aquifers; from shallowest Springfield Plateau aquifer (Mississippian age rocks), to the Ozark aquifer (comprised 

largely of Ordovician rocks with some Devonian rocks), to 

the deepest St. Francois aquifer (Cambrian rocks). These three 

aquifers are stratigraphically separated by two confining units. 

Ground water from the Springfield Plateau and Ozark aquifers 

was sampled for the NAWQA study. The Springfield Plateau 

aquifer is unconfined (except in its westernmost extent) and 

crops out in southwestern Missouri. The Ozark aquifer, the 

thicker (thick sequences of dolomites, sandstones, and shales) 

and more widespread of the aquifers, is the primary water 

source regionally (Miller and Appel, 1997; Renken, 1998). 

The term “Ozark Plateaus” is the name of an aquifer system, 

a NAWQA study unit, and a physiographic province. As used 

in this report, the term “Ozark Plateaus” refers to the aquifer 

system unless otherwise noted.

Topography in the Ozark Plateaus ranges from flat-lying 

to rugged; altitudes reach 1,772 ft above NAVD 88. The 

climate of the area is temperate. Mean annual precipitation 

ranges from about 38 to 48 in. (Adamski and others, 1995), 

and mean annual temperature ranges from 56 to 60oF.

Land use in the Ozark Plateaus study area is a mix of forested land and agricultural land (Adamski and others, 1995). 

Agricultural land is commonly pastureland. Urban areas are 

minor, representing less than 2 percent of land use.

The aquifer system is the source of freshwater for most 

public and self-supplied domestic water users in the area 

(Imes and Emmett, 1994). The total ground-water withdrawals for 2000 from the Ozark Plateaus aquifer system were 

165 Mgal/d, of which 131 Mgal/d was public supply (table 1).

Piedmont and Blue Ridge Carbonate-Rock 

Aquifers

The boundaries of the Piedmont and Blue Ridge aquifer system are coincident with the Piedmont and Blue Ridge 

Physiographic Provinces. These provinces are bounded on 

the north and west by the Valley and Ridge and New England 

Physiographic Provinces (Fenneman and Johnson, 1946) 

and on the south and east by the Coastal Plain Physiographic 

Province. The Piedmont and Blue Ridge aquifers extend in a 

band from eastern Alabama through Georgia, South and North 

Carolina, north to Virginia, West Virginia, Maryland, Pennsylvania, and New Jersey (Trapp and Horn, 1997) (fig. 1). 

Rocks in the Piedmont and Blue Ridge Provinces are crystalline, carbonate, and sedimentary (Briel, 1997). The principal 

aquifer in carbonate rock in the Piedmont is the Piedmont and 

Blue Ridge carbonate-rock aquifer. This report focuses on 

the ground water sampled from the carbonate aquifers in the 

Piedmont; therefore, this aquifer is referred to hereafter as the 

Piedmont aquifer. In northern New Jersey, southeastern Pennsylvania, and eastern Maryland, these Precambrian and lower 

Paleozoic carbonate rocks form a series of long, narrow blocks 

interspersed with granite and gneiss.

In the area of the Piedmont aquifer in Pennsylvania and 

Maryland, the average annual temperature is about 54°F. 

Precipitation ranges from 38 to more than 48 in/yr (Risser and 

Siwiec, 1996).

The predominant land use overlying the Piedmont aquifer 

is agricultural (at over 80 percent), and 15 percent of the 

remainder is categorized as urban (Lindsey and others, 2006).

 Although the carbonate-rock aquifers cover only about 

3 percent of the Piedmont and Blue Ridge Provinces, they are 

a substantial local source of water (Trapp and Horn, 1997). 

Approximately 30 Mgal/d (table 1) is withdrawn from the 

Piedmont aquifer, primarily from Pennsylvania, supplying 

water to about 44 percent of the population in that area (Lindsey and others 2006).

Prairie du Chien of the Cambrian-Ordovician 

Aquifer System

The Cambrian-Ordovician aquifer system lies within 

the Central Lowland and the Superior Upland Physiographic 

Provinces (Fenneman and Johnson, 1946). Cambrian- and 

Ordovician-age sandstones and carbonates constitute most of 

the bedrock and subcrop beneath glacial drift in southeastern 

Minnesota, northeastern Iowa, Wisconsin, northern Illinois, 

and extreme northwestern Indiana (fig. 1) (Olcott, 1992). 

The Cambrian-Ordovician aquifer system consists of three 

aquifers separated by two leaky confining units and capped by 

a confining unit. The three aquifers are the St. Peter-Prairie du 

Chien-Jordan, the Ironton-Galesville, and the Mount Simon. 

The Prairie du Chien Group consists of upper and lower dolomite units with an intervening sandstone unit. The NAWQA 

Program sampled ground water from the Prairie du Chien 

aquifer, the middle dolomite unit of Ordovician age. Surface 

topography is generally smooth with some gently rolling hills 

and dissected uplands. The climate ranges from cold winters 

to cool summers; mean annual temperatures range from 44 

to 46°F. Average annual precipitation increases from 24 to 44 

in. from northwest to southeast. The predominant land uses in 

the area are agricultural, forest, and urban (Fong and others, 

1998).
12 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

The St. Peter-Prairie du Chien-Jordan aquifer is a multiunit aquifer that is a major source of ground water for Iowa 

and Minnesota. The aquifer in Minnesota is the principal 

source of water for domestic wells and municipal wells in 

suburban communities surrounding the Minneapolis-St. Paul 

metropolitan area (Fong and others, 1997). Total ground water 

withdrawn from the Cambrian Ordovician aquifer system in 

Minnesota was 271 Mgal/d, more than 75 percent of which 

was for public supply (table 1).

The Prairie du Chien aquifer is the only aquifer referred 

to in this study by a name that is not a principal aquifer, 

because the sampling was limited to a specific (carbonatebedrock) part of the principal aquifer that is otherwise mostly 

noncarbonate bedrock. The specific aquifer name ‘Prairie du 

Chien’ is used to describe this area rather than the principal 

aquifer name ‘Cambrian-Ordovician.’

Silurian-Devonian/Upper Carbonate Aquifers

The Silurian-Devonian and Upper carbonate aquifers 

were sampled in eastern Iowa and southern Minnesota (fig. 1). 

The Silurian-Devonian aquifer consists of 200–400 ft of 

limestone, dolomite, sandstone, shale, and evaporite deposits 

(Olcott, 1992). The boundary between Silurian-Devonian and 

Upper carbonate aquifers is a facies change in northern Iowa. 

The Upper carbonate aquifer consists of 250–600 ft of Ordovician- and Devonian-age limestone, dolomite, and shale. Both 

of these aquifers are primarily unconfined. The Devonian-age 

carbonate rocks are present in both aquifers, but the Silurianage units are absent in the Upper carbonate aquifer. The area is 

characterized by low relief to gently rolling topography.

The continental climate brings hot summers (average 

of 71°F) and cold winters (average 20°F) to the area. Mean 

annual temperature is 47°F (Schnoebelen and others, 1999), 

and precipitation averages about 30 to 36 in/yr (Kalkhoff and 

others, 2000)

 Agriculture is the dominant land use in the area, covering 

over 90 percent of the area (Savoca and others, 1999).

Water use in 2000 from the Upper carbonate aquifer in 

Minnesota totaled 9.55 Mgal/d and from the Silurian-Devonian aquifer in Iowa was 49.8 Mgal/d (table 1).

The Silurian-Devonian/Upper carbonate aquifers are 

two individual principal aquifers, but they were sampled as a 

single unit and therefore are grouped together for this study.

Valley and Ridge Carbonate-Rock Aquifers

The Valley and Ridge carbonate-rock aquifers are in 

the Valley and Ridge Physiographic Province. The carbonate 

aquifer extends from Alabama to New Jersey, including parts 

of Georgia, Tennessee, West Virginia, Virginia, Maryland, 

Pennsylvania, and New Jersey (fig. 1). Only the carbonate 

aquifers in the Valley and Ridge are included in this study; 

therefore, the aquifer is hereafter referred to as the Valley and 

Ridge aquifer. The Valley and Ridge consists of a long, narrow 

belt of folded and faulted Paleozoic rocks. The Valley and 

Ridge is characterized by a series of sub-parallel northeasttrending ridges. The aquifer is the widest in Pennsylvania and 

is bounded by the Blue Ridge and Piedmont Provinces to the 

southeast and by the Appalachian Plateaus to the northwest 

(Trapp and Horn, 1997). The Great Valley in Pennsylvania 

is floored with lower Paleozoic carbonate rocks and shale. 

The most productive Valley and Ridge aquifers are within the 

limestone and dolomite rocks (of Cambrian and Ordovician 

age) in the valleys.

The climate varies from north to south; average annual 

temperatures range from 59°F in Eastern Tennessee (Hampson and others, 2000) to 46°F in northeastern Pennsylvania 

(Fischer, 1999). Precipitation averages about 40 in/yr, but in 

areas of higher altitude in the Valley and Ridge, precipitation 

can be as high as 90 in/yr (Hampson and others, 2000).

For the Valley and Ridge aquifer, forested land makes up 

47 percent of the land area, and agricultural land use covers about 27 percent of the land area (Vogelmann and others, 

2001). In the northern Great Valley, the percentage of agricultural land use is much greater; 78 percent of the carbonate aquifer in the Great Valley in the Lower Susquehanna 

River Basin study unit underlies agricultural land (Risser and 

Siwiec, 1996).

Water use in the Valley and Ridge carbonate aquifer totaled 267 Mgal/d; 177 Mgal/d was for public supply 

(table 1).

Hydrogeology

The 12 carbonate aquifers selected for study have similar 

overall lithology (limestone and (or) dolomite) and mineralogy 

(calcite, dolomite, and trace amounts of other evaporite minerals such as gypsum in some rocks). Some carbonate aquifers 

are interlayered with sandstones or shales (Mississippian, 

Piedmont, and Valley and Ridge) or crystalline rocks (Piedmont). However, differences in geology, aquifer properties 

(such as porosity and transmissivity), extent of karstification, 

degree of confinement, and climate (precipitation, temperature, and recharge) all are key factors that account for variations among these 12 aquifers in major-ion chemistry, pH, 

oxidation-reduction (redox) status, and ground-water residence 

time. Additional factors (lithology, stratigraphy, geomorphology, structural, and tectonic), described by Brahana and others 

(1988), affect the evolving porosity and permeability of carbonate rocks (and hence water quality) for carbonate aquifers 

in North America. Differences in pH and redox status in an 

aquifer can greatly affect the movement and fate of contaminants and trace elements in ground water.

Generalized hydrogeologic properties for the 12 carbonate aquifers are included in table 2, but it is worth noting that 

there can be a wide range in aquifer properties and confinement conditions within each of these systems. This section 

describes some of the important hydrogeologic differences 
Hydrogeology

13

Table 2. Hydrologic properties of the 12 carbonate aquifers or aquifer systems included in study.

Aquifer or 

aquifer system

Location 

 (states)

Approximate areal 

extent, 

square miles

Composition Depositional age Thickness, feet

Basin and Range Nev., Utah, Calif., Ariz., Idaho, 

Oreg.

50,000 Limestone, dolomite, layers of shale, 

sandstone, and quartzite

Cambrian-Permian up to 25,000

Biscayne Fla. 3,600 Shelly limestone, sand infilling of 

large voids

Pleistocene-Pliocene 20–250

Castle Hayne N.C. 11,500 Limestone, calcirudite, calcarenite, 

sandy marl, fine to coarse calcareous sand in N.C.

Eocene-Oligocene <10–1,000

Edwards-Trinity Tex., Okla. 77,000 Limestone, dolomite, evaporite Cretaceous 3300–700

Floridan Fla., Ga., S.C., Ala. 100,000 Limestone, dolomite Tertiary (Eocene-Oligocene) 40–2,500Mississippian Tenn., Ala., Ky., Ind. 120,000 Limestone Mississippian 100–400

Ordovician Tenn., Ky. Thin-bedded limestones and 

dolostones (mostly in Tenn.) interbedded with shales

Ordovician, CambrianOrdovician large variations over short distances

Ozark Plateaus Mo., Ark., Okla. 50,000 Limestone, dolomite; some sandstones Cambrian-Mississippian 200–400 (Springfield Plateaus); 1,000–3,000 

(Ozark aquifer)

Piedmont Pa., Md. 900 Limestone, dolomite, marble Precambrian-Ordovician 34,700–8,000

Prairie du Chien Minn., Wis. 4,000 Limestone, dolomite Lower Ordovician 0–335Silurian-Devonian/ 

Upper carbonate

Iowa, Wis., Ill., Mich., Ind., Ohio 212,400 Limestone, sandstone, small amts 

gypsum

Silurian-Devonian 200–400

Valley and Ridge N.J., Pa., Md., W.Va., Va., N.C., Ga., 

Ala.

15,300 Limestone, dolomite, with interbedded clastics Cambrian, Ordovician, Silurian, Devonian, 

Mississippian

38,000

1 Noncontinuous.2 Iowa only.3 Formations are folded, faulted or tilted. Formation thickness may not be equal to aquifer thickness.4 The maximum potable thickness is about 1,000 feet.
14 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 2. Hydrologic properties of the 12 carbonate aquifers or aquifer systems included in study.—Continued Aquifer or aquifer system Confinement Composition of confining material Areal extent of confinement, percent Thickness of confining unit, feet Porosity Transmissivity, feet squared per day Basin and Range Unconfined to confined Clastic sedimentary, volcanic rocks Variable Variable Secondary dissolution along fractures, and conduits 13–130,000 Biscayne Unconfined, but overlying sand cover provides storage Unconfined None none Primary: highly porous shelly material 75,000–300,000 Castle Hayne Unconfined, but thin confining unit in N.C. Clay and sandy clay Variable Generally less than 50 in N.C. Secondary 10,000–70,000 Edwards-Trinity Unconfined to confined Clay, limestone 60–70 0–2,000 Secondary dissolution along fractures, and conduits 10,000–5,000,000 Floridan Unconfined to confined Clay and silt 50–80 0–400 Dual: conduits, porous matrix 10,000–1,000,000 Mississippian

Variable—mostly unconfined Regolith, clay, silt, chert Variable 10–100 Secondary: chert gravel and rubble at top of rock, 

fractures and conduits

30–4,400 (Tenn.)

Ordovician Unconfined to confined Shale and shaly limestone Variable large variations over short distances Secondary dissolution along fractures, and conduits large variations over short distances

Ozark Plateaus Variable—mostly unconfined Shale, dolomite Springfield Plateaus aquifer is variably 

confined; Ozark aquifer is mostly unconfined

less than 100 Secondary dissolution along 

fractures, faults, and conduits

highly variable

Piedmont Unconfined to confined Shale, crystalline rocks 

or poorly fractured carbonate rock

Variable Secondary dissolution along 

joints, fractures

20–30,000

Prairie du Chien Unconfined to confined Glacial and alluvial 

deposits

Variable <50–450 Secondary: fractures, vugs, 

caverns, conduits

12,000

Silurian-Devonian/ 

Upper carbonate

Mostly unconfined Shale 25 percent Secondary dissolution along 

fractures, bedding plane openings

360,000 (unconfined areas)–1,200 (confined 

areas)

Valley and Ridge Unconfined to confined Shale, clay, poorly fractured limestone Variable Secondary dissolution along fractures, and conduits 15–120,000
Hydrogeology

15

Table 2. Hydrologic properties of 12 carbonate aquifers or aquifer systems included in study.—Continued

Aquifer or 

aquifer system

Karst features, 

types

Approximate age of 

ground water, 

years

Water-quality 

issues References

Basin and Range Springs, caverns 1,000s; interbasin movement of 

ground water with deep circulation

Rapid urban growth Winograd and Thordarson (1975); Harrill and Prudic (1998); Schaefer and 

others (2005); Planert and Williams (1995)

Biscayne None Urban, saltwater intrusion Renken and others (2005); Bradner and 

others (2005); Radell and Katz (1991)

Castle Hayne Some karst features in outcrop areas or 

unconfined areas

Saltwater intrusion Trapp and Meisler (1992); Miller (1999); 

Winner and Coble (1996)

Edwards-Trinity Sinkholes, large conduit systems, springs recent–200 (average residence 

time)

Urban Barker and Ardis (1996); Maclay and 

Small (1983); Maclay and Land (1988); Maclay (1995)

Floridan Sinkholes, large conduit systems, numerous 

springs

10–40 unconf.;10,000–30,000 

conf.

Urban, agriculture Miller (1986, 1999); Sprinkle (1989) 

Marella (2004)

Mississippian Sinkholes, springs, caverns <10–35 Agriculture, urban Kingsbury and others (1999); Kingsbury 

and Shelton (2002); Plebuch and others (1985)

Ordovician Sinkholes, caverns, springs young Agriculture Webbers (2003); Miller (1999)

Ozark Plateaus Sinkholes, springs, large conduit systems, 

caverns

Agriculture, urban Adamski and others (1995); Adamski 

(1997, 2000); Peterson (2002); Imes (1987); Renken (1998)

Piedmont Sinkholes, springs 0–20 Agriculture, urban Lindsey and others (2006); Trapp and 

Horn (1997)

Prairie du Chien Caverns, conduits slightly younger in unconfined 

area, young and old mixtures

Agriculture Young (1992); Fong and others (1998); 

Olcott (1992)

Silurian-Devonian/ 

Upper carbonate

Sinkholes, springs, conduits Agriculture Savoca and others (1999); Olcott (1992); 

Hershey (1969); Tucci and McKay (2006)

Valley and Ridge Sinkholes, springs, caverns 0–20 Agriculture, urban Parizek and others (1971); Swain and 

others (2004)
16 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

among these aquifers that can result in ground-water-quality 

variations. More detailed information about each aquifer system can be obtained from the references provided in table 2. 

Differences in land-use activities that affect the occurrence of 

anthropogenic contaminants in these ground-water systems are 

discussed in subsequent sections. In addition, natural groundwater flow is affected by the amount of pumpage in each 

aquifer system. The estimated amount of ground water withdrawn from each aquifer system for various uses is presented 

in table 1.

The rocks that comprise these carbonate aquifers have 

different depositional and post-depositional histories. Depositional environments determine to a large extent the properties of carbonate aquifers, because they affect texture, fabric, 

and original porosity and permeability (Brahana and others, 

1988). The age of rocks for eight of the aquifers ranges from 

Precambrian to Paleozoic (Piedmont, Valley and Ridge, Basin 

and Range, Mississippian, Ordovician, Ozark Plateaus, Prairie 

du Chien, and Silurian-Devonian/Upper carbonate) to Pleistocene (Biscayne aquifer), with Cretaceous rocks comprising the 

Edwards-Trinity aquifer system and Tertiary rocks comprising the Floridan aquifer system and the Castle Hayne aquifer 

(table 2). Primary porosity associated with these aquifer 

systems ranges from 1 to more than 50 percent, but subsequent diagenetic processes (compaction, cementation, and 

dolomitization) and dissolution have affected both porosity 

and permeability. In addition, structural forces associated with 

tectonic movement have caused deformation (folding, faulting, 

and fracturing) of rocks in several systems (Edwards-Trinity, 

Ozark Plateaus, Piedmont, and Valley and Ridge aquifers/

aquifer systems). Faults are especially important hydrogeologic features. The extent of the Edwards-Trinity aquifer system is generally coincident with a major fault zone. Aquifers 

in carbonate rocks of Precambrian to Cretaceous age typically 

yield water primarily from solution openings. The SilurianDevonian/Upper carbonate and Ordovician aquifers are in 

layered limestones and dolomites of Paleozoic age, in which 

solution openings are locally well developed. Likewise, in the 

Piedmont and Valley and Ridge carbonate aquifers, dissolution 

has occurred along structural planes, such as bedding, cleavage, or other joints, and has greatly enhanced permeability by 

forming interconnected conduit networks.

Aquifers in carbonate rocks of Tertiary and younger age 

have different porosity and permeability characteristics than 

aquifers in Cretaceous and older carbonate rocks. The aquifers 

in Tertiary and younger rocks (Castle Hayne aquifer, Floridan 

aquifer system, and Biscayne aquifer) contain strata that were 

deposited in warm marine waters on shallow shelves and are 

mostly platform carbonate deposits in which intergranular 

porosity is present as well as large solution openings (Miller, 

1999). However, the hydrogeology of these younger systems can be highly complex and variable. For example, the 

sequence of rocks in the Floridan aquifer system was deposited in different environments that result in wide variations in 

texture, from coarse coquina that is extremely permeable to 

micrite that is almost impermeable. Subsequent dolomitization 

has changed the original texture and mineralogy of the carbonate rocks by increasing the volume of connected pore space in 

fine-grained limestones and calcite or dolomite overgrowths.

Degree of Confinement

The thickness and type of sediments that overlie the 

different carbonate aquifers can affect the flux of water from 

the surface to the carbonate-rock material (Brahana and others, 1988) and hence the development of secondary porosity, 

permeability, transmissivity, recharge rate, and ground-water 

residence time. Therefore, the susceptibility of an aquifer to 

contamination from land-surface activities can be directly 

related to the degree of confinement. Unfortunately, the definition of confinement is not consistent among study areas. The 

degree of confinement in this study is defined generally by the 

presence of lower permeability rocks or unconsolidated material overlying the aquifer or aquifer systems (see table 2).

Variable degrees of confinement occur within all 12 

carbonate aquifers (table 2). The Biscayne, Mississippian, 

Ordovician, Piedmont, and Valley and Ridge aquifers have 

been classified as unconfined (table 2); however, some confinement by low-permeability material may occur locally in 

some of these systems. The Mississippian aquifer is overlain 

by relatively thick regolith or residuum (up to 100 ft in some 

places). The Basin and Range aquifer is considered to be confined because of the long, deep flowpaths (Susan Thiros, U.S. 

Geological Survey, written commun., 2007), and the fact that 

the carbonate aquifer is typically overlain by low-permeability 

volcanic rocks (Schaefer and others, 2005). The Castle Hayne 

aquifer is confined or unconfined based on the presence or 

absence of the Castle Hayne confining unit (Giese and others, 

1997). The Edwards-Trinity aquifer system is confined where 

it is fully saturated and buried (Groschen, 1996) and unconfined otherwise. The Upper Floridan aquifer is considered to 

be unconfined when it occurs near the surface or is covered by 

a thin layer of permeable sediments; semiconfined or poorly 

confined when there is less than 100 ft of lower-permeability 

sediments overlying the aquifer or if the overlying material 

is breached by sinkholes; and confined when the thickness 

of overlying low-permeability sediments exceeds 100 ft. The 

Prairie du Chien aquifer is considered to be confined where 

it is overlain by less permeable bedrock units or by at least 

10 ft of clay or clay-rich glacial till, and the aquifer is considered to be unconfined where those units are not present (Fong 

and others, 1998). In the Silurian-Devonian/Upper carbonate 

aquifer, Savoca and others (1999) considered a well to be 

‘protected’ if it was overlain by a confining unit or 100 ft of 

glacial material. Their description of ‘protected’ wells was 

considered equivalent to ‘confined’ for this study. Intense folding and thrust faulting followed by erosion of sandstone strata 

have resulted in near-surface exposure of the limestones that 

comprise the Valley and Ridge aquifer and generally result in 

the aquifer being unconfined.
Hydrogeology 17

Parts of the Upper Floridan and the Ozark aquifer do not 

fall into either confinement category and have been categorized as follows. The Upper Floridan aquifer is considered to 

be semiconfined in areas where the confining unit is less than 

100 ft thick or breached (Miller, 1986). For the Ozark aquifer, 

the term ‘mixed confinement’ was used in cases where a given 

well had a long open interval and was open to both the upper 

unconfined aquifer and the lower confined aquifer (Daniel 

Yeatts, U.S. Geological Survey, written commun., 2007). 

The shale confining unit for the Ozark aquifer generally is 

less than 100 ft thick where it is overlain by the Springfield 

Plateaus aquifer, but the Ozark aquifer is mostly unconfined 

where it occurs near the surface. The age of ground water, 

which typically refers to the time since recharge, is related to 

aquifer confinement (Cook and Böhlke, 2000), ground-water 

flow patterns, and other aquifer properties (Focazio and others, 1998, 2002). In shallow flow systems that are unconfined, 

such as in the Biscayne aquifer, ages of ground water can vary 

from days to tens of years. In deeper aquifer systems, such as 

in confined parts of the Floridan aquifer system, ground-water 

age can reach tens of thousands of years along long flowpaths 

(Plummer and Sprinkle, 2001). However, short-circuiting of 

water through sinkholes and other solution features can result 

in mixtures of young and old water in parts of many carbonate aquifer systems (Plummer and others, 1998) and affect the 

quality of water withdrawn by public supply wells (Katz and 

others, 2007; Metz and others, 2007).

In this report, differences in geochemistry and contaminant occurrence among the 12 carbonate aquifers are evaluated 

relative to the degree of confinement. Wells in each aquifer 

were grouped into three categories (unconfined, semiconfined 

or mixed confined, and confined) for detailed statistical analysis. The number of samples that were considered as mixed 

confinement was very small; therefore, they were lumped with 

the semiconfined category for analysis, as they are neither 

confined nor unconfined.

Karstification

Considerable variability in permeability within and 

among each of the carbonate aquifers has resulted from carbonate dissolution along joints, bedding planes, cavities, and 

faults, which has produced small to large conduits at different 

depths. Recharge water that contains carbon dioxide (forming 

carbonic acid) and organic acids can readily dissolve carbonate rocks to depths of about 300 ft where the rocks crop out or 

are covered by a thin layer of noncarbonate material (Miller, 

1999). The end result of extensive carbonate-rock dissolution 

is expressed at the land surface as karst topography, characterized by sinking streams, sinkholes, caves, and other types 

of solution openings and by internal surface-water drainage 

systems. Almost all carbonate terranes are underlain by one 

or more karst aquifers (Quinlan and others, 1991); however, 

these authors state that the degree of karstification can vary 

considerably, and the “absence or unrecognized presence of 

sinkholes, and other karst features does not mean that a karst 

aquifer is not present.”

In karst terranes, water typically enters the carbonaterock aquifers rapidly through large openings (solutionally 

enlarged fractures), and contaminants in the water can be 

transported though pipe-like or channel-like openings called 

conduits, rapidly spreading through the aquifers. The length 

and depth of caves and fissures vary widely across the study 

areas and are related to topographic relief, thickness of soluble 

rock, geologic structure, and position of the water table. Quinlan and others (1991) grouped karst aquifers into a continuum 

of three categories—hypersensitive karst aquifers, moderately 

sensitive karst aquifers, and slightly sensitive (non-karst) 

aquifers—on the basis of the sensitivity of their response to 

variations in recharge, storage, and flow and the relative vulnerability to point and nonpoint sources of contamination at 

the land surface. It is beyond the scope of this study to characterize in detail the degree of sensitivity of each aquifer system 

with respect to its response to fluctuations in recharge, storage, 

and flow. However, it is worth mentioning prominent karst 

features that have been noted for some of the aquifers. In the 

Edwards-Trinity aquifer system, large caves and fissures are 

present to a depth of 600 ft, and fissure systems and passages 

of single caves commonly extend for more than 1 mi (Davies 

and others, 1984). In the Ozark Plateaus, caves with passages 

1,000 ft or more long are common, and most cave passages 

extend to depths of less than 100 ft (Davies and others, 1984). 

In parts of the Upper Floridan aquifer in northern Florida, 

cave passages of several miles recently have been mapped by 

cave divers (Florida Department of Environmental Protection, 

2007).

This study used the generalized location of karst areas in 

the United States shown on a national atlas karst map (Davies 

and others, 1984). The map by Davies and others (1984) eventually will be replaced by a new national karst map (Weary, 

2006). This new geographic information system-based, 

soluble-rock map will better display surficial karstic features 

from various data sources including state geologic maps and 

will include the distribution and density of caves, sinkholes, 

and other karst features. This new map is considered a work in 

progress because issues still need to be resolved about the lack 

of consistency in spatial precision and lithologic classification, 

and the difficulties in obtaining statewide and regional information on cave locations and other solution features.

Springs

In most karstic aquifer systems, springs are important ground-water-discharge features (Meinzer, 1927). As 

one might expect from variations in topography, hydraulic 

gradient, recharge, and degree of karstification among these 

carbonate aquifers, there is a large variation in the number of 

springs and the volume of water that they discharge. Springwater chemistry can reveal important information about 

aquifer water quality, because a spring integrates ground water 
18 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

spatially, vertically, and temporally from an aquifer (Rosenau 

and others, 1977). Spring flow is controlled by the size of the 

ground-water contributing area, hydraulic gradient, the amount 

of recharge, and the size of the openings through which the 

springs discharge (Meinzer, 1927). Springs in unconfined 

and poorly confined parts of an aquifer generally can have 

large seasonal fluctuations in flow. Large volumes of water 

move quickly in and out of the aquifer, and concentrations of 

dissolved solids tend to be lower than in areas of slower flow 

through small pores in the carbonate matrix.

Few if any springs are present in the Biscayne aquifer; 

in contrast, the Floridan aquifer system contains 33 first-magnitude springs, each of which discharge more than 100 ft3

/s 

(greater than 62 Mgal/d). Most of the springs that discharge 

water from the Floridan aquifer system are in areas where the 

aquifer is exposed at the land surface or is covered by less than 

100 ft of clayey confining material. A smaller number of largevolume springs also are associated with the Edwards-Trinity 

aquifer system and the Basin and Range aquifer. Smaller-volume springs or seeps are found in the Mississippian aquifer, 

Valley and Ridge aquifer, and the Ozark Plateaus aquifer 

system. Spring-water samples were collected from six aquifers 

or aquifer systems—Edwards-Trinity, Floridan, Mississippian, 

Valley and Ridge, Basin and Range, and Ozark Plateaus.

Berndt and others (2005) compared water chemistry in 

samples from 226 wells and 176 springs in selected carbonate aquifers to determine if water from springs and wells has 

similar concentrations of selected properties and constituents 

such as dissolved solids, dissolved oxygen, nitrate, and calcite 

and dolomite saturation index (S.I.). Samples were collected in 

seven carbonate aquifers/aquifer systems—Edwards-Trinity, 

Floridan, Mississippian, Basin and Range, Valley and Ridge, 

Springfield Plateau, and Ozark (samples from the Springfield 

Plateau and Ozark aquifers were combined into the Ozark 

Plateaus aquifer system in the current study). Although concentrations of nitrate were only significantly different between 

spring and well samples in one of the seven aquifers, concentrations of dissolved oxygen were significantly different 

between well and spring samples in four of the seven aquifers. 

Median calcite and dolomite S.I. values were significantly different between well and spring samples in three of the seven 

aquifers. Springs probably represent mixtures of younger 

water from shallower parts of the aquifer flow systems and 

thus may receive water from those parts of the flow system 

that are most susceptible to contamination from land-use 

practices. The collection of water from springs is critical to 

adequately characterize water quality and vulnerability to 

contamination in carbonate aquifers (Adamski and Pugh, 

1996; Adamski, 2000; Berndt and others, 2005). Because the 

differences in concentrations of anthropogenic contaminants in 

wells and springs were generally not significant, water-quality 

data from springs are analyzed along with data from wells 

from the studied aquifers in this report.

Recharge

The 12 carbonate aquifers are in areas of the United 

States where there is a large variability in climate, which in 

turn affects the amount of rainfall and estimated recharge to 

each aquifer. Annual average precipitation is low in Nevada 

where the Basin and Range aquifer is present (5–16 in. in 

the valleys but ranges from 8 to more than 60 in. over the 

mountains where most recharge occurs) (Schaefer and others, 

2005), but ranges to more 60 in. over parts of Florida where 

the Floridan aquifer system is unconfined. However, the actual 

amount of recharge to each aquifer varies substantially within 

each study unit and among the aquifers due to soil type, topography, streamflow characteristics, faults and fractures, solution 

openings, distribution of precipitation, and pumpage patterns. 

Recharge estimates are included in this report as a possible 

factor affecting water quality in carbonate aquifers.

Sampling-Network Characteristics

The following description of the sampling-site networks 

provides a basic overview of the study types, water use, 

characteristics of sampling sites, the land use, and potential 

contaminant sources in the area around the sampling sites and 

the potential factors affecting transport of contaminants to the 

sampling sites. These ancillary data sets will be used in the 

analysis of the water quality in the 12 carbonate aquifers.

Sampling for this study was conducted as a part of a 

USGS national program, and therefore, the networks have 

similar characteristics (Koterba and others, 1995). All 

1,042 samples were collected as a part of 1 of 5 basic types of 

ground-water studies. Each study type had different objectives; however, they were components of an overall program 

objective of characterizing ground-water resources in these 

aquifers. The major-aquifer study was a broad characterization of water quality in the aquifer, typically from domesticsupply wells. The land-use study focused on a specific land 

use (agricultural or urban) and typically included domesticsupply wells for agricultural land-use studies. In the urban 

land-use studies, monitoring wells were drilled, and in some 

cases, older abandoned wells were sampled. Some landuse-study networks had a companion network with a small 

number of reference wells (two to three wells) that were from 

areas where land use was not expected to affect water quality. The ‘spring’ study type was made up entirely of springs. 

Springs were included in some of the other networks study 

types, but the network maintained the name of the primary 

sampling objective. The fourth type of study was the sourcewater-quality assessments that were focused on water quality 

in public-supply wells. The last type of study was a flowpath 

study. These were typically wells installed along a flowpath 

in a small area and were only included in this analysis in one 

case where the wells were spread out over a large area. The 

sampling sites included 865 wells and 177 springs. If a site 

was sampled multiple times, only the most recent sample was 
Hydrogeology 19

Table 3. Summary of network names, National Water-Quality Assessment (NAWQA) study types, numbers of wells and springs 

sampled, and sampling time period in the 12 carbonate aquifers or aquifer systems included in study.—Continued

Aquifer or 

aquifer sytem Network name Study type Site type

Number of 

sampling 

sites

Sample 

collection period

Basin and Range nvbrsus4 Major-Aquifer Study Wells 12 2003

nvbrsus4 Major-Aquifer Study Springs 12 2003

Biscayne sofllusot1 Reference Wells Wells 3 1996–97

sofllusrc1a Urban Land-Use Study Wells 30 1996–97

sofllusrc1b Urban Land-Use Study Wells 2 1996

soflsus1 Major-Aquifer Study Wells 30 1998

Castle Hayne albesus5 Major-Aquifer Study Wells 2 1994

albesus7 Major-Aquifer Study Wells 30 2002–04

Edwards-Trinity sctxlusrc1 Urban Land-Use Study Wells 30 1998

sctxrefre1 Reference Wells Wells 1 2000

sctxspr2 Spring Study Springs 6 1997

sctxsus1 Major-Aquifer Study Wells 28 1996

sctxsus2 Major-Aquifer Study Wells 30 1996

sctxsus3 Major-Aquifer Study Wells 30 1997

Floridan acfbsus1 Major-Aquifer Study Wells 33 1995–2002

acfbsus2 Spring Study Springs 22 1995

gafldwgs1 Source Water-Quality Assessment Wells 15 2002–04

gafldwgs2 Source Water-Quality Assessment Wells 15 2002–03

gafllusrc1b Urban Land-Use Study Wells 16 2002

gaflrefot1 Reference Wells Wells 2 2002

gaflsus2 Major-Aquifer Study Wells 30 2002–03

gaflsus3 Major-Aquifer Study Wells 30 2002

gaflsus4 Major-Aquifer Study Wells 30 2005

santsus2 Major-Aquifer Study Wells 30 1998

Mississippian ltenlusag1 Agricultural Land-Use Study Wells 32 2000–01

ltenreffo1 Reference Wells Wells 1 2000

ltenspr1 Spring Study Springs 2 1999

ltenspr2 Spring Study Springs 1 2000

ltensus1 Major-Aquifer Study Wells 30 1999

Ordovician ltenspr2 Spring Study Springs 9 2000

ltensus2 Major-Aquifer Study Wells 31 2000

Ozark Plateaus ozrklusag1a Agricultural Land-Use Study Wells 20 1994

ozrklusag1b Spring Study Springs 22 1993–94

ozrklusag2a Agricultural Land-Use Study Wells 20 1995

ozrklusag2b Spring Study Springs 20 1993–95

ozrksus1 Major-Aquifer Study Wells 12 1993–94

ozrksus2a Major-Aquifer Study Wells 30 1993

ozrksus2b Spring Study Springs 30 1993

ozrksus3a Major-Aquifer Study Wells 16 1993

ozrksus3b Spring Study Springs 18 1993

Piedmont lsuslusag1 Agricultural Land-Use Study Wells 30 1993

Prairie du Chien umissus3 Major-Aquifer Study Wells 12 1996

umissus4 Major-Aquifer Study Wells 18 1996

Silurian-Devonian/Upper carbonate eiwasus1 Major-Aquifer Study Wells 33 1996
20 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 3. Summary of network names, National Water-Quality Assessment (NAWQA) study types, numbers of wells and springs 

sampled, and sampling time period in the 12 carbonate aquifers or aquifer systems included in study.—Continued

Aquifer or 

aquifer sytem Network name Study type Site type

Number of 

sampling 

sites

Sample 

collection period

Valley and Ridge lsuslusag2 Agricultural Land-Use Study Wells 30 1994

lsuslusag3 Agricultural Land-Use Study Wells 30 1995

lsuslusur1 Urban Land-Use Study Wells 20 1995

podlreffo1 Reference wells Wells 2 2002

potofpsag2 Agricultural Flowpath Study Wells 10 1995

potolusag1 Agricultural Land-Use Study Wells 29 1993–2002

utenspr1 Spring Study Springs 35 1997

utensus1 Major-Aquifer Study Wells 30 1998–99

used in this study. The breakdown of samples by study type is 

539 from major-aquifer studies, 191 from agricultural land-use 

studies, 98 from urban land-use studies, 10 from an agricultural flowpath study, 9 from reference sites, 165 from spring 

studies, and 30 from source-water-quality assessments. The 

sampling-site networks, type of study, the number of springs 

and wells associated with each network, and the sampling time 

period are given in table 3. The current study was conducted 

by compiling all NAWQA studies that had been conducted 

in carbonate aquifers. Thus, this does not represent a random 

sampling design that represents all aquifers and land-use types 

equally.

The water use associated with the sampling sites in the 

various study types is given in table 4. Domestic water use 

from private wells was predominant overall. The second most 

frequent water use was “unused,” which, except in the case of 

springs, indicates a monitoring well or an abandoned domestic 

well. Public water use from production wells characterized the 

source-water-quality assessment networks, as well as a large 

number of the wells from major-aquifer studies. A variety of 

miscellaneous water uses characterize the rest of the sites. The 

water use has some effect on potential water-quality issues. 

Public-supply wells are typically deeper, are pumped more 

heavily, and have better well-construction characteristics than 

most of the other well types. The unused springs and wells 

may be the least protected, because they are not designed to 

produce water for human consumption. Overall, the variety 

of water use, study type, and site type represents various parts 

of the aquifer systems; shallow monitoring wells represent 

recently recharged water, deeper domestic and public supply 

wells represent the deeper system, and springs represent the 

discharge points of the system.

A summary of the characteristics of the sampling sites is 

included in table 5. The Biscayne and Castle Hayne aquifers 

had the shallowest median depth to water, and the Basin and 

Range aquifer and the Edwards-Trinity aquifer system had 

the deepest median depths to water. Shallowest median well 

depths were in the Biscayne and Mississippian aquifers, and 

the Basin and Range aquifer and the Edwards-Trinity aquifer system had the deepest median well depth. The depth to 

the top of the open interval is the shallowest point at which 

water can flow into a well. In most cases, this is given as the 

bottom of the casing or the depth to a well screen; however, 

if information on specific water-bearing zones is available, 

this is the distance to the shallowest water-bearing zone. The 

median depth to the top of the open interval was smallest 

in the Biscayne and Ordovician aquifers. The median depth 

to the top of the open interval was also largest in the Basin 

and Range aquifer and the Edwards-Trinity aquifer system. 

The well-construction data are indicative of the variety in 

the aquifer characteristics. Some aquifers are shallow with a 

high water table, and others are deep with a lower water table. 

These factors could be important in determining the presence 

of contaminants in wells; however, because of the nature of 

carbonate aquifers, contaminants can travel rapidly to deep 

parts of these aquifers.

Source Factors

Several potential sources of contamination were compiled for use as variables to explain water-quality results. 

These included information on land use, population density, 

nitrogen sources, and underground storage tanks. In most 

cases, these data were compiled for the NAWQA Program 

for a 1,640-ft (500-m) radius around the sampling sites. The 

arbitrary 1,640-ft radius area is not assumed to be the actual 

contributing area to the sampling site, but the data compiled 

for this area are considered to be representative of land-surface 

activities in the area near the sampling site.

The land-use data are from the National Land Cover Data 

(NLCDE) data sets (U.S. Geological Survey, 1999; Price and 

others, 2007), which are enhanced by the GIRAS data sets to 

include the addition of categories for orchards, tundra, residential with forest, and residential without forest (Price and others, 2007). This data set represents land use in the early 1990s. 

For much of the data analysis, the NLCDE codes were lumped 
Hydrogeology 21

Table 4. Summary of water use by National Water-Quality Assessment (NAWQA) study type in the 12 carbonate aquifers or 

aquifer systems included in study.

Study type Sub-type Water use Number of sites

Major-Aquifer Study Domestic 339

Other1 53

Public Supply 78

Unused 69

Land-Use Study Urban Domestic 7

Other1 7

Public Supply 2

Unused 82

Agricultural Domestic 155

Other1 4

Unused 32

Reference Wells Domestic 1

Other1 1

Unused 7

Spring Study Domestic 43

Other1 35

Public Supply 6

Unused 81

Source-Water-Quality Assessment Public Supply 30

Agricultural Flowpath Study Domestic 10

1

“Other” category includes aquaculture, commercial, dewatering, industrial, industrial cooling, institutional, irrigation, other, power, recreation, stock.
22 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 5. Summary of site characteristics for wells and springs in the 12 carbonate aquifers or aquifer systems included in study. Aquifer or aquifer system Numbers of sites Water levels, depth to water, feet below land surface Total depth, feet below land surface Depth to top of open interval, feet below land surface

Total number 

of sites

Number of 

springs

Number of 

wells

Number of 

sites

Minimum

Median

Maximum

Number of 

sites

Mimimum

Median

Maximum

Number of 

sites

Mimimum

Median

Maximum

Basin and Range 24 12 12 114 2-185 3 760 12 278 890 1,979 12 122 455 1,197

Biscayne 65 0 65 63 1 5 28.6 64 10 45 165 63 5 24 165

Castle Hayne 32 0 32 25 3.67 10.32 32.18 32 22 94 350 30 12 71 350

Edwards-Trinity 125 6 119 69 5 178 447 104 80 385 2,700 91 0 201 2,700

Floridan 224 22 202 128 .82 28.54 179.53 201 33 170 840 180 20 88.5 800

Mississippian 66 3 63 62 1 22.22 72.66 63 14 53 157 61 6 33 157

Ordovician 40 9 31 70 5.18 27.02 106.2 31 22 125 300 30 6 20 300

Ozark Plateaus 188 90 98 48 .3 47.9 194 92 32 183 1,769 44 10 83 1,769

Piedmont 30 0 30 30 6.8 31.13 84.44 30 75 160 200 30 41 98 175

Prairie du Chien 30 0 30 30 13.38 78.96 239 30 66 177 380 30 12 144 380

Silurian-Devonian/Upper carbonate 33 0 33 25 11.45 58.58 222.4 33 32 225 750 20 18 143.5 507

Valley and Ridge 186 35 151 150 0 50.79 262 151 30 158 670 125 11 84 670

1Some improved springs have reported water levels.2Negative water level is estimate of hydraulic head from a flowing well.
Hydrogeology 23

Valley and Ridge

N=186

Prairie du Chien

N=30

Ordovician

N=40

Edwards-Trinity

N=125

Floridan

N=224

Silurian-Devonian/

Upper carbonate

N=33

Mississippian

N=66

N=188

Ozark Plateaus Piedmont

N=30

Basin and Range Biscayne

Urban Agricultural Forested Wetland

Shrubland Grassland Other

Castle-Hayne

N=24 N=65 N=32

EXPLANATION

MEDIAN LAND USE

N = NUMBER OF SITES

Figure 3. Median percentages of land use in a 1,640-foot radius around sampling sites for each of the 12 

carbonate aquifers or aquifer systems (U.S. Geological Survey, 1999; Price and others, 2007).
24 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

into categories of agricultural, urban, forested, shrubland, or 

wetlands. The land-use data sets were processed to summarize 

the data for the 1,640-ft radius around each sampling site. 

Figure 3 illustrates the median value from a summary land use 

surrounding individual wells in each of the aquifers.

The mix of land-use types is an indication of potential 

sources of contamination in these aquifers. All but two of 

the aquifers are dominated by a mixture of agricultural and 

forested land use. The Biscayne aquifer is largely overlain 

by urban areas, and the Basin and Range aquifer is overlain 

largely by shrub land. The Mississippian, Silurian-Devonian/

Upper carbonate, Ozark Plateaus, Piedmont, Prairie du Chien, 

and Valley and Ridge aquifers/aquifer systems are dominated 

by agricultural land use. For some data-analysis purposes, 

individual sampling sites were assigned a predominant land 

use using one of four general land-use designations (agricultural, urban, mixed land use, and undeveloped) used by 

Gilliom and others (2006). A sampling site with greater than 

50 percent agricultural land use and less than 5 percent urban 

land use was determined to be predominantly agricultural. A 

sampling site with greater than 25 percent urban land use and 

less than 25 percent agricultural land use was determined to be 

predominantly urban. A sampling site with less than 25 percent 

agricultural and less than 5 percent urban land use was determined to be predominantly undeveloped. Any sampling site 

not meeting those three definitions was determined to have 

predominantly mixed land use, typically meaning a combination of both urban and agricultural land use with neither one 

dominant.

Population density is another factor considered as a 

possible indicator of contaminant sources. Population characteristics were also processed for the 1,640-ft radius for the 

1990 census (U.S. Bureau of Census, 1990, 1991) and the 

2000 census (GeoLytics, 2001; U.S. Bureau of Census, 2001) 

The Biscayne aquifer underlies areas with the highest median 

population density, followed by the Piedmont aquifer (fig. 4). 

The high population density of land overlying the Piedmont 

aquifer is interesting, because the Piedmont also has the highest median percentage of agricultural land, so it is a densely 

populated agricultural area. The area around the sampling sites 

in the Basin and Range aquifer is largely unpopulated.

The density of storage tanks can be a factor affecting 

the presence of VOCs. The density of the various categories 

of storage tanks is greatest in the Biscayne aquifer (table 6) 

(Vista Information Solutions, 1999). The median density of 

storage tanks in the other aquifers is zero. The maximum 

density value however for the storage tanks is much larger in 

most of the aquifers. The implications of this distribution are 

that most wells probably have little or no exposure to VOC 

contamination from storage-tank leaks, but a few sampling 

sites in most of the aquifers have a large number of storage 

tanks as potential sources of VOC contamination.

Another potential source of contamination is the estimated nitrogen input from various sources. These variables 

have been compiled for the 1,640-ft radius around sampling 

sites for atmospheric deposition of nitrogen and nitrogen from 

manure and fertilizer (Ruddy and others, 2006). Estimates of 

nitrogen from septic systems were made by using census data 

and equation (1).

N-Septic = POPDENS × (SEWSEP/100) ×

 0.785 × 6.72 lb/yr-person × 0.454 kg/lb (1)

where

N-Septic is the nitrogen input from septic systems, in 

kilograms per year,

POPDENS is the population density in the 1,640-ft 

radius, in persons per square kilometer 

(U.S. Bureau of Census, 1990, 1991),

SEWSEP is the percent of the housing units on septic 

systems (U.S. Bureau of Census, 1992)

0.785 is a conversion of the area of the 1,640-ft 

(500-m) radius to square kilometers,

6.72 lb/yr is an estimate for nitrogen production per 

person for human septic effluent (U.S. 

Environmental Protection Agency, 2002), 

and

0.454 is a conversion from pounds to kilograms.

Equation 1 probably results in a slight overestimation, because 

it assumes equal distribution of the population among areas 

with public sewer and septic systems; however, for the small 

area in the 1,640-ft radius, the overestimation can be ignored. 

The sum of nitrogen from atmospheric deposition, fertilizer, 

manure, and septic systems is used as the total nitrogen input 

in the buffer area. The median values for nitrogen sources and 

the distribution of the sources of nitrogen are given on figure 5. It is important to note that although the value of nitrogen 

from septic systems is relatively small, it is discharged beneath 

the ground, unlike the other sources, particularly fertilizer 

and manure, which are applied to the land surface and are 

subject to plant uptake. Septic systems typically are located 

in relatively close proximity to domestic wells, increasing the 

probability of a direct connection between the septic system 

and the well, especially in karst areas.

The estimated agricultural application rate of pesticides is 

shown for atrazine, simazine, and metolachlor (fig. 6). These 

herbicides are the three most frequently occurring compounds 

analyzed by the NAWQA Program (Gilliom and others, 2006) 

that have application-rate information available (Nakagaki 

and Wolock, 2005). The application estimates are based on 

agricultural uses only and do not account for nonagricultural 

applications. The application rates for atrazine are highest 

in the Silurian-Devonian/Upper carbonate and the Piedmont 

aquifers. For most aquifers, atrazine has the highest application rate of the three pesticides. Simazine application is 

typically much lower than the rate for the other two pesticides; 

the Piedmont and Prairie du Chien aquifers have the highest 

median simazine application rates. Metolachlor application 

rates are highest in the Silurian-Devonian/Upper carbonate 

and the Piedmont aquifer.
Hydrogeology 25

Basin and Range

Biscayne

Castle-Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Praire du Chien

Silurian-Devonian/ Upper carbonate

Valley and Ridge

POPULATION DENSITY, 1990 CENSUS, IN PERSONS PER SQUARE MILE

10,000

1,000

100

10

1

0.1

EXPLANATION 

75th percentile

Median

25th percentile

10th percentile

90th percentile

Figure 4. Median population density from 1990 census in 1,640-foot radius around sampling sites in the 12 carbonate aquifers 

or aquifer systems (U.S. Bureau of Census, 1990, 1991).
26 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 6. Summary of underground storage tanks in 3,280-foot radius around sampling sites in the 12 carbonate aquifers or aquifer 

systems included in study.

[Storage tank data from Vista Information Solutions (1999); Total storage tanks does not equal the sum of the other columns; each column is calculated individually]

Aquifer or 

aquifer system

Number 

of sites Statistic

Storage tanks in 3,280-foot radius

Underground Leaking-underground Above ground Total storage 

tanks

Basin and Range 24 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 0 0 0 0

Biscayne 65 Minimum 0 0 0 0

Median 5 2 2 9

Maximum 33 26 16 65

Castle Hayne 32 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 7 4 0 11

Edwards-Trinity 125 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 57 23 16 91

Floridan 224 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 54 19 46 119

Mississippian 66 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 18 4 1 23

Ordovician 40 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 3 1 0 4

Ozark Plateaus 188 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 25 10 2 35

Piedmont 30 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 0 1 1 1

Prairie du Chien 30 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 14 4 3 15

Silurian-Devonian/Upper carbonate 33 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 3 2 0 5

Valley and Ridge 186 Minimum 0 0 0 0

Median 0 0 0 0

Maximum 24 27 12 63
Hydrogeology 27

DISTRIBUTION OF TOTAL NITROGEN INPUT 

FROM ALL SOURCES, IN KILOGRAMS PER 

YEAR IN A 1,640-FOOT RADIUS AREA

 AROUND THE SITE

MEDIAN NITROGEN INPUT BY SOURCE, 

IN KILOGRAMS PER YEAR IN A 1,640-FOOT 

RADIUS AREA AROUND THE SITE

0

4,000

8,000

12,000

16,000

0

4,000

8,000

12,000

16,000

SOURCE OF NITROGEN

Farm fertilizer

Septic systems

Manure

Nonfarm fertilizer

Atmospheric deposition

Basin and Range

Biscayne

Castle-Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Praire du Chien

Silurian-Devonian/ Upper carbonate

Valley and Ridge

EXPLANATION 

75th percentile

Median

25th percentile

10th percentile

90th percentile

Figure 5. Median values for nitrogen from septic systems, manure, fertilizer, and atmospheric deposition, 

and distribution of total nitrogen input from all sources for the 1,640-foot radius around sampling sites in the 12 

carbonate aquifers or aquifer systems.
28 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Atrazine

Metolachlor

Simazine

100

80

60

40

20

0

10

8

6

4

2

0

100

80

60

40

20

0

PESTICIDE APPLICATION, IN KILOGRAMS PER YEAR

Basin and Range

Biscayne

Castle-Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Praire du Chien

Silurian-Devonian/ Upper carbonate

Valley and Ridge

EXPLANATION 

75th percentile

Median

25th percentile

10th percentile

90th percentile

Figure 6. Median application rates of selected pesticides for the 1,640-foot radius around sampling sites in the 12 

carbonate aquifers or aquifer systems (data for 1997 agricultural use only, Nakagaki and Wolock, 2005).
Hydrogeology 29

Table 7. Summary of median hydrologic characteristics for the 1,640-foot radius around sampling sites in the 12 

carbonate aquifers or aquifer systems included in study.

[Dunne overland flow, Wolock (2003a); Horton overland flow, Wolock (2003b); Runoff, Gebert and others (1987); Recharge, Wolock 

(2003c)]

Aquifer or 

aquifer system

Dunne 

Overland 

Flow 

(percent)

Horton 

overland 

flow 

(percent)

Recharge 

(inches 

per year)

Runoff 

(inches 

per year)

Basin and Range 0.0 0.0 0.0 0.8

Biscayne 6.0 1.0 3.0 8.2

Castle Hayne 5.0 4.0 8.0 18.8

Edwards-Trinity 1.0 26.0 1.0 2.7

Floridan 6.0 2.0 5.0 11.3

Mississippian 5.0 7.0 9.0 25.8

Ordovician 4.0 4.2 8.0 25.3

Ozark Plateaus 3.6 6.0 4.0 11.3

Piedmont 2.7 4.0 9.0 18.0

Prairie du Chien 2.0 2.0 3.0 5.8

Silurian-Devonian/Upper carbonate 2.0 4.0 3.0 7.3

Valley and Ridge 3.0 3.2 9.0 19.1

Fate and Transport Factors

In addition to potential sources of contaminants, data 

potentially related to movement of contaminants through 

the aquifer were compiled for each site. As with the source 

factors, the 1,640-ft radius was used, not necessarily as an 

indicator of the contributing area to the sampling site but as a 

representation of the conditions in the area. Transport factors 

relate to the physical movement of the water and contaminants. Fate factors are related to the potential transformation 

or degradation of the contaminant as it travels through the 

ground-water system.

Four hydrologic variables, Dunne overland flow, Horton 

overland flow, recharge, and runoff, are used as indicators of 

the predominant pathway for movement of water through the 

hydrologic system. These variables have been compiled as 

national data sets and are summarized in table 7. The overland-flow variables represent two mechanisms for generation 

of surface runoff. Dunne overland flow (Wolock, 2003a) is 

caused by saturation of surface areas. Horton overland flow 

(Wolock, 2003b) is a result of precipitation rates that exceed 

infiltration rates. Runoff (Gebert and others, 1987) is longterm average streamflow. Recharge was calculated by Wolock 

(2003c). The hydrologic variables illustrate the variation in climate; Dunne overland flow is highest in the humid southeast 

and lowest in the Basin and Range. The data set also illustrates 

the pathways that the water travels; Horton overland flow is 

highest in the Edwards-Trinity aquifer system, and recharge is 

greatest in the Mississippian, Piedmont, and Valley and Ridge 

aquifers. All of the hydrologic characteristics are considered 

transport factors.

Soils characteristics also are considered to be potential 

indicators of fate and transport of contaminants. Soils data 

from State Soil Geographic Data (STATSGO, U.S. Department of Agriculture, Natural Resources Conservation Service, 

1994; Wolock, 1997) were compiled for the 1,640-ft radius. 

This data set includes characteristics such as permeability, soil 

thickness, organic-matter content, particle size, and hydrologic groupings (table 8). Particle size can have an effect on 

transport of contaminants. Smaller particle sizes, such as clay, 

are associated with slow infiltration rates; however, macropore 

flow and karst features allow bypassing of the soil profile in 

some cases. Hydrologic groups are ordered from A to D with 

group A having the lowest runoff potential and D having the 

highest runoff potential (U.S. Department of Agriculture, 

2007). Soils overlying the Biscayne aquifer, Castle Hayne 

aquifer, and Floridan aquifer system are dominated by the sand 

fraction, whereas silt and clay are more prevalent for most of 

the other aquifers. Hydrologic group B, with moderate infiltration rates, was the predominant hydrologic group with the 

exception of the Basin and Range, Castle Hayne aquifers, and 

the Edwards-Trinity aquifer system, which were dominated 

by soil hydrologic group D. Organic matter was highest in the 

Biscayne aquifer, and slightly higher in the Silurian-Devonian/

Upper carbonate and Prairie du Chien aquifers than in the rest 

of the aquifers. Organic matter is a factor that can affect the 

fate and transport of contaminants, whereas all the other soils 

characteristics are considered transport factors.
30 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 8. Summary of median soil characteristics for the 1,640-foot radius around sampling sites in the 12 carbonate aquifers or aquifer systems included in study. [Soils data from U.S. Department of Agriculture, Natural Resources Conservation Service (1994); Wolock (1997); Soils drainage class compiled by Schwarz and Alexander (1995)] Aquifer or aquifer system Median particle size, percent Hydrologic group, percent Other soil properties

Sand

Silt

Clay

A 

(High infiltration)

B

(Moderate 

infiltration)

C

(Poor infiltration)

D

(Very poor 

infiltration)

Organic matter 

(Percent)

Available water 

capacity 

 (fraction)

Depth to seasonally 

high water table 

(feet)

Thickness of soil 

examined 

 (inches)

Permeability 

(inches per hour)

Bulk density (grams 

per cubic 

 centimeter)

Drainage class1

Slope (percent)

Basin and Range 39 42 16 3 44 4 30 0.5 0.1 6.0 60.0 3.9 1.4 3.0 6.0

Biscayne 91 6 3 0 74 0 10 3 .1 .5 22.9 12.6 1.5 6.0 .9

Castle Hayne 61 21 18 8 7 7 29 1 .1 1.3 60.0 6.9 1.4 5.5 1.2

Edwards-Trinity 12 45 45 0 3 28 61 1 .1 6.0 36.2 .8 1.4 3.0 4.8

Floridan 70 13 16 26 11 12 9 0 .1 3.3 60.0 6.9 1.5 4.4 1.9

Mississippian 12 48 37 0 75 19 6 0 .2 4.5 60.0 1.3 1.4 3.3 4.1

Ordovician 13 48 35 0 66 27 7 1 .1 5.8 53.6 1.7 1.4 3.1 6.9

Ozark Plateaus 20 42 39 0 58 30 4 1 .1 5.5 57.7 1.6 1.4 3.1 12.3

Piedmont 9 54 36 0 84 14 0 1 .2 5.3 69.6 1.4 1.4 3.2 6.1

Prairie du Chien 32 42 15 2 70 8 0 2 .2 4.7 60.0 3.1 1.5 3.5 5.5

Silurian-Devonian/Upper carbonate 29 44 25 0 73 2 0 2 .2 4.1 60.0 1.8 1.5 4.4 2.7

Valley and Ridge 13 50 36 0 84 14 0 1 .2 5.3 60.0 1.4 1.4 3.2 8.2

1Drainage class: 1= excessive, 2 = somewhat excessive, 3 = well drained, 4 = moderately drained, 5 = somewhat poorly drained, 6 = poorly drained, 7 = very poorly drained.
Methods 31

Methods

The following sections describe the methods used to 

collect data for this project. Results of the quality-assurance 

program are analyzed. Treatment of nondetections specific 

to this report and statistical methods used to analyze data are 

described. The programs used for analysis of geochemical data 

are described, and methods used to determine potential health 

affects of water-quality analyses are explained.

Sample Collection and Processing

The NAWQA Program has rigorous protocols to ensure 

that the data collected are of known and good quality. Water 

samples were collected using established USGS protocols 

and procedures to obtain a representative sample and avoid 

contamination (Koterba and others, 1995). All the networks 

were designed using a similar approach to well selection in 

order to ensure geographic coverage and random distribution 

of the sample locations. Water-quality samples were analyzed 

at the USGS National Water Quality Laboratory in Denver, 

Colo. The quality of the environmental data was determined 

by analysis of blanks and spikes that were collected as part of 

each study. Blanks were collected to quantify the probability 

of cross contamination from sample to sample. Contaminated 

blanks would indicate an increased possibility of a falsepositive result, that is, a reported concentration for a contaminant where none is present, or the contaminant concentrations 

are greater than the true concentration. Spikes indicate the 

accuracy of the reported results. A spiked sample is prepared 

by adding a known quantity of a target analyte to a known 

volume of water collected from the aquifer. These differ from 

laboratory-control samples in that they are prepared in natural 

water and can indicate the effects of matrix interference and 

sample handling on recovery of the analyte.

Quality-Assurance Methods and Results

A summary of the results of the quality-assurance methods is provided to illustrate potential issues related to data 

quality. Blank samples indicate the ability to obtain samples 

that are not influenced by contamination from a previous site 

or other sources. Spikes indicate the ability to correctly quantify concentrations in environmental samples.

Nitrate Blank Sample Results

Nitrate was detected at a concentration of greater than 

0.06 mg/L in 11 percent of the 130 blank samples; the maximum concentration detected in a blank was 0.21 mg/L. The 

contamination is likely because of the ubiquitous nature of 

nitrate in water samples and in the environment. Nitrate was 

detected in 76 percent of the 1,037 environmental samples. 

A ratio of environmental detection frequency to blank detection frequency of five or less is used as an indication that 

contamination should be considered in the interpretation of 

the environmental data (Martin and others, 1998). The ratio 

of contamination in blanks to the rate of detection in environmental samples was greater than five. When comparing the 

environmental concentrations to the maximum blank concentration, 86 percent of the samples with reported concentrations of nitrate were greater than the maximum concentration 

detected in any blank sample. A small number of environmental samples may be affected by low levels of contamination; 

this may have a minimal affect on the statistical analysis of the 

data.

Pesticide Blank and Spike Recovery Analysis

Pesticide contamination in blank samples was evaluated 

by using all the ground-water blanks from the 14 study units 

that were included in this study if the blank samples were 

collected during the year of sampling and in the carbonate 

network. The results of the blank samples also were compared to a national summary of field blanks conducted by the 

NAWQA Program (Martin and others, 1998). The number of 

blank samples for the study ranged from 97 to 102 for the 5 

pesticides that were most frequently detected. The analysis of 

the blank data indicates a low percentage of samples affected 

by contamination and low concentrations in those samples. 

The overall number of samples with contaminated blanks 

was low (0 to 4 percent) and similar to the national level for 

all five of the pesticides analyzed. The number of detections 

of pesticides in blanks is higher for pesticides that are widely 

used and frequently detected (Martin and others, 1998).

The effect of contamination on the analysis of the environmental data depends on the relative frequency of detection 

of pesticides in blanks and environmental samples and the 

concentrations in blanks compared to the typical concentrations in environmental samples. Most blank samples did not 

have detectable concentrations of pesticides. The highest 

frequency of detection in blank samples was metolachlor, at 

4 percent. For all the pesticides selected for detailed study 

except for metolachlor, the detection frequency of the pesticide in environmental samples was an order of magnitude 

greater than the detection frequency in blank samples, hence, 

these detection frequencies are higher than the ratio of five 

used by Martin and others (1998) as an indication that contamination should be considered in the interpretation of the 

environmental data for pesticides. Metolachlor, with a ratio 

of four, is slightly lower than the ratio of five suggested by 

Martin and others as an indicator that contamination may need 

to be considered when interpreting results. One other way to 

evaluate the blank data is to compare the highest concentration in the blanks to all detections in environmental samples. 

When comparing the highest concentrations detected in blank 

samples to the concentrations in environmental samples, 

between 68 and 100 percent of the detections in environmental 

samples had concentrations greater than the highest concentration detected in any blank. The highest concentrations in 
32 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

blanks were typically an order of magnitude lower than the 

concentrations detected in environmental samples. The combination of the detection-frequency ratios and the comparison 

of concentration ranges indicates that contamination is not a 

major factor to consider in the analysis of the environmental 

data for four of the five pesticides, and may be a factor affecting analysis of data for metolachlor.

Spiked samples were submitted to determine the ability of the sampling program to detect a pesticide when it is 

present and to determine the accuracy of that finding. The 

spike program consisted of adding 0.1 μg of a pesticide to a 

1 L water sample to create a 0.1 μg/L solution. Because the 

spike was added to an environmental sample that may have 

already contained pesticides, the evaluation of spike recovery 

has to consider the measured concentration of pesticides in the 

unspiked environmental sample. For each spiked sample, there 

was a corresponding environmental sample. If a pesticide 

was detected in the environmental sample, the concentration 

from the environmental sample was subtracted from the value 

in the spiked sample, prior to comparing the measured value 

for the spike to the expected value for the spike (eq. 2). For a 

sample in which no pesticide was detected in the corresponding environmental sample, no such adjustment was necessary. 

The data were evaluated to determine false negatives (no 

pesticide detected when a known concentration was added to 

the sample) and the average recovery of the spike from the 

samples.

Percent recovery = 100 × (CSpiked - CSample) / Ctheoretical (2)

The analysis of the pesticide spike data indicates no false 

negatives; that is, the pesticides were detected in all the spiked 

samples. When calculating the percent recovery, the four of 

the five pesticides selected for the study were found to have 

recovery percentages (94 to 100 percent) that were similar to 

the recoveries in the rest of the NAWQA Program as summarized by Martin (1999). It is worth noting that deethylatrazine 

has a low percent recovery [52 percent in the current study, 

31 percent in Martin (1999)]. The USGS National Laboratory 

reports all values for deethylatrazine as ‘estimated’ values 

because of this known poor recovery. Therefore, the concentrations of deethylatrazine used in this study are likely to be 

biased low. No attempt was made to adjust the concentrations 

of deethylatrazine during data analysis to account for this low 

recovery rate.

Volatile Organic Compound Computational and 

Blank Analysis

The minimum laboratory reporting levels (LRLs) for 

VOCs varied greatly between compounds and over time. Prior 

to April 1996, the minimum LRL was 0.2 μg/L for all VOCs 

except DBCP, which had a minimum LRL of 1.0 μg/L (Carter 

and others, 2008). Of the 793 samples analyzed for VOCs, 

154 samples (19 percent) were collected prior to April 1996, 

including data from 5 of the aquifers/aquifer systems—53 

samples in the Valley and Ridge, 49 samples in the Ozark Plateaus, 30 samples in the Piedmont, 20 samples in the Floridan, 

and 2 samples in the Castle Hayne. For the Ozark Plateaus and 

Piedmont, all of the VOC data were collected prior to April 

1996, and for the Valley and Ridge, 45 percent of the data 

were collected prior to April 1996. In order to compare samples at concentrations less than 0.2 μg/L, a subset of samples 

would have to be used and comparisons could only be made 

between 10 aquifers. Also, the reporting levels varied among 

individual compounds after April 1996. The use of 0.2 μg/L as 

an assessment level for calculation of detection frequencies for 

VOCs allowed the comparison of VOC compounds for all 793 

samples and among all 12 aquifers.

The detection of some VOCs in equipment and field 

blank samples indicated potential for contamination of 

environmental samples during the sample-collection process. 

VOCs with the highest detection frequencies in blank samples 

at the 0.2 μg/L assessment level were acetone (19 percent of 

samples), ethylmethylketone (8 percent), toluene (6 percent), 

carbon disulfide (6 percent), tetrahydrofuran (5 percent), 

tetrachloroethene (4 percent) and 1,2,4-trimethylbenzene 

(4 percent) and chloroform (2 percent). At the 0.2 μg/L assessment level, however, these VOCs were found to have a low 

probability (less than 0.1 percent) of remaining contamination after the native water rinsing that followed field-blank 

collection and preceded the collection of each environmental 

sample (John Zogorski, U.S. Geological Survey, written commun., 2008). This native water rinsing has been shown to be 

highly effective in reducing the potential carryover of contaminants from equipment and sample lines to ground-water 

samples (Taglioli and others, 2001). Thus, the high frequency 

of detection of some VOCs in blank samples overestimates the 

potential occurrence of cross-contamination of environmental 

samples.

Statistical Methods Used to Analyze WaterQuality Data

Interpretation of the water-quality data included use of 

several statistical methods. Descriptive and nonparametric 

statistics were used in this report to summarize and compare 

the concentrations of field characteristics, major and trace 

inorganic constituents, nutrients, pesticides, VOCs, and dissolved organic carbon. Methods included comparisons of 

water quality among groupings using the Wilcoxon rank-sum 

test and the nonparametric Tukey’s test, comparisons of groupings where both variables were categorical using contingency 

tables, comparison of water quality to continuous explanatory 

variables using the Spearman’s rank correlation, and comparison of water quality to explanatory variables using discrete 

categories using logistic regression. For all statistical tests, an 

alpha value of 0.05 was used. An alpha value of 0.05 indicates 

a 95-percent probability that the statistical result is not due 

to random chance. Thus, a probability or p-value less than or 

equal to 0.05 indicates a statistically significant result.
Methods 33

Assessment Levels

Data-analysis methods were chosen to account for the 

fact that, in some cases, a large percentage of the data had 

concentrations less than the LRL. The term ‘laboratory reporting level’ used herein refers to the value that differentiates a 

nondetection from any reported quantified value by use of 

a less than ‘<’ remark. An estimated or ‘E’ value refers to 

values that are reported where the compound was definitively 

detected in a sample, but the value has a greater degree of 

uncertainty because it is approaching the lower analytical 

capability of the instrumentation. ‘E’ values are typically less 

than the LRL. The term ‘assessment level’ refers to assigning 

a common level for analyzing data for a constituent or a group 

of constituents. An assessment level is used to make consistent 

comparisons among constituents or studies using multiple 

reporting levels.

For some constituents, LRLs were constant; therefore, 

nonparametric statistical analyses using ranks accounted for 

the nondetects by setting the concentration of all nondetects to 

a single value below the LRL prior to ranking. In cases where 

there were multiple LRLs throughout the study period, other 

considerations had to be taken into account. For example, in a 

ranking scheme, a value of < 0.2 μg/L cannot be compared to 

a value of < 0.001 μg/L. The only conclusion that can be made 

about these two values is that both are < 0.2 μg/L. Therefore, 

in a data set in which there were two or more LRLs, all data, 

including quantified detections at values less than the highest LRL, were analyzed using an assessment level based on 

the higher reporting limit. In the previous example, the higher 

LRL of 0.2 μg/L would be used as the assessment level. VOCs 

were handled in this way. The other option in analyzing these 

data is to analyze the subset of data that has the lower reporting limit and not use the data with the higher reporting limit. 

In some cases, the assessment level of ‘all detections’ is used. 

This allows the most data to be retained but creates a bias in 

that areas with the higher reporting limit appear to have fewer 

detections, which may or may not be the case.

For analysis of pesticides, the handling of values below 

the LRL was different and is based on the method used by 

Gilliom and others (2006). Each pesticide sample includes 

a result and a remark code. If the remark field is empty, the 

value in the result field is a quantified detection at a concentration greater than the LRL. If the remark field is a less than 

(“<”), the value is less than the LRL, indicating that there was 

no definitive analytical evidence for the occurrence of the 

compound at a measurable concentration. If the remark field is 

an ‘E,’ the value is an estimated value, as previously defined. 

The value associated with a sample having a “<” remark is 

the LRL for that pesticide. LRLs varied during the period of 

1993–2005; however, for a given year, each pesticide typically had a common LRL. If a sample had a “<” remark, and a 

value greater than the common LRL, this indicates the reporting limit was intentionally raised for that particular sample 

because of issues such as sample dilution prior to analysis. 

Cases with a raised LRL were not included in the data analysis. When ranking pesticides for a statistical test, all nondetects are assigned a rank lower than the lowest reported or ‘E’ 

value, and results with ‘E’ values and quantified detections are 

assigned ranks on the basis of their reported value, a method 

used in other national assessments of pesticides (Gilliom and 

others, 2006).

Wilcoxon Rank-Sum, Kruskal-Wallis, and 

Nonparametric Tukey’s Test

The Wilcoxon rank-sum test was used to test for differences in values or concentrations between two groups of data 

(SAS Institute, Inc., 1989a, 1989b; Helsel and Hirsch, 2002, 

p. 118). A probability, or p-value, of less than 0.05 was used as 

an indicator of a significant difference.

When comparing differences in the values or concentrations of several independent groups, the Kruskal-Wallis 

test was used (SAS Institute, Inc., 1989a, 1989b; Helsel and 

Hirsch, 2002, p. 159). If the Kruskal-Wallis test indicated 

differences among the groups, the nonparametric Tukey’s test 

(SAS Institute, Inc., 1989a, 1989b; Helsel and Hirsch, 2002, 

p. 200) was used to determine the ordering of the groups. This 

test assigns a common letter to groups that are not statistically 

different. A p-value of 0.05 was used as an indicator of significant differences for this test as well. Because the data are not 

normally distributed, the Tukey’s test was performed on the 

ranks of the values rather than the values themselves and the 

results refer to mean ranks rather than medians.

Contingency Tables

When analyzing data where both the explanatory and 

response variables are categorical, contingency tables are 

used. An example of this would be when a compound is either 

detected or not detected, and the comparison category is a 

grouping variable. This test can determine whether the number 

of detections of the compound is related to the comparison 

group (Helsel and Hirsch, 2002, p. 378). A matrix analysis 

is conducted to determine whether or not the distribution of 

detections differs among groups. P-values of less than 0.05 

indicate a 95-percent probability that the differences among 

groups are not due to random chance.

Spearman’s Rank Correlation

In cases where there is a continuous explanatory variable 

and a continuous response variable, a Spearman’s rank correlation test (Helsel and Hirsch, 2002, p. 217) was conducted. A 

continuous variable can have any value within a certain range. 

An example of this type of comparison is the comparison of 

the application rate of fertilizer (continuous explanatory variable) to the concentration of nitrate (continuous response variable). The Spearman’s rank correlation method uses ranks of 

data to determine a monotonic relation between the explanatory variable and the response variable. The statistics produced 

by the Spearman’s rank correlation are the Spearman’s rho 

coefficient and the p-value. P-values of less than 0.05 indi-
34 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

cate a 95-percent confidence that a monotonic relation exists 

between the explanatory variable and the response variable. 

That is, an increase in the explanatory variable is correlated 

to an increase in the response variable. The values of Spearman’s rho range from -1 to 1; larger absolute values indicate a 

stronger relation. The sign of Spearman’s rho is an indicator of 

whether the relation has a positive or negative slope. Negative 

values of Spearman’s rho are referred to as inverse correlations in this report. The Spearman’s rank correlation was used 

for interpreting concentrations of nitrate and pesticides.

Logistic Regression

A discrete variable has values that are limited to specific 

categories, such as greater than or less than a specified threshold. In cases where the response variable is discrete, logistic 

regression can be used to determine the probability of the 

response variable exceeding a threshold. An example of this 

would be testing whether increases in pesticide application 

rate causes an increased probability of that pesticide exceeding 

the detection limit. The probability of an event occurring is 

defined by equation 3:

p

e

e

x x x

x x x

i i

i i

 

     

     

   

   

0 1 1 2 2

0 1 1 2 2 1

...

... (3)

where ß0

 is the intercept, x1 is explanatory variable 1, ß1 is 

the slope coefficient of x1

, x2 is explanatory variable 2, ß2 is 

the slope coefficient of x2

, xi is explanatory variable i, ßi is 

the slope coefficient of xi (Helsel and Hirsch, 2002, p. 396). 

Analyzing the results of logistic regression is more complicated than analyzing the results of linear regression. Statistics 

that are important are 1) the overall significance of the model, 

2) the value of explanatory variables and corresponding 

p-value, 3) the Hosmer-Lemeshow results, 4) the generalized 

r-square, 5) the maximum rescaled r-square, and 6) the percent 

concordance.

The overall significance of the model, indicated by 

p-values less than 0.05, indicates that the model with explanatory variables is better at predicting the probability of an event 

occurring than an intercept-only model. The significance of 

the explanatory variables, indicated by p-values less than 0.05, 

indicates that a specific explanatory variable improves the 

model in its ability to predict the probability of an event occurring. The Hosmer-Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 1989) tests whether or not the outcomes 

predicted by the model are significantly different than the 

outcomes from the original data. P-values of a Hosmer-Lemeshow test that are less than 0.05 indicate the model predictions 

and the data are significantly different; however, the model 

predictions should fit the data. Therefore, p-values less than 

0.05 indicate a poor model fit. There is no r-square value that 

can be produced by the logistic regression model that is identical to the r-square value from linear regression; however, some 

substitutes for the r-square value have been calculated. The 

generalized r-square value (Cox and Snell, 1989) is based on 

maximizing the log-likelihood and is a generalized method of 

estimating an r-square value. The maximum-rescaled r-square 

value (Nagelkerke, 1991) is another method that approximates 

the linear-regression r-square. Although neither of these statistics can be interpreted as the percentage of variance explained 

by the model, they can be used as comparisons of one model 

to another.

The terms concordance and discordance also are used in 

describing results of logistic regression. These statistics are 

calculated by comparing every possible combination of data 

points where one event is equal to ‘1’ and the other event is 

equal to ‘0.’ If the predicted probability for the case with event 

equal to ‘1’ is higher than the predicted probability for the case 

with the event equal to ‘0,’ that pair is concordant. The opposite case would be discordant, and ties are counted; however, 

concordance is the primary statistic used in this report.

Analysis of Geochemical Data

The geochemical program Aquachem was used to construct Piper diagrams and determine major-ion water types 

using concentrations of major ions (Waterloo Hydrogeologic 

Inc., 2005). The program PHREEQCI was used to determine 

calcite and dolomite S.I. (Charlton and Parkhurst, 2002; 

Parkhurst and Appelo, 1999).

Drinking-Water Standards and Health-Based 

Screening Levels

Concentrations of contaminants are compared to Maximum Contaminant Levels (MCLs) or Secondary Maximum 

Contaminant Levels (SMCLs) for regulated compounds (U.S. 

Environmental Protection Agency, 2006) and to USGS HealthBased Screening Level (HBSL) concentrations for unregulated 

compounds. MCLs are enforceable standards determined 

on the basis of potential human-health effects, and represent 

the highest level of a contaminant that is allowed in drinking 

water used for public supply. SMCLs are non-enforceable 

Federal guidelines regarding cosmetic effects (such as tooth or 

skin discoloration) or aesthetic effects (such as taste, odor, or 

color) of drinking water. HBSLs are estimates of benchmark 

concentrations used to evaluate water-quality data in a humanhealth context. They were developed collaboratively by the 

USGS, U.S. Environmental Protection Agency, New Jersey 

Department of Environmental Protection, and Oregon Health 

& Science University (Toccalino and others, 2004). HBSLs 

are not regulatory standards and are not enforceable; however, 

HBSLs can be used as management tools to help prioritize 

contaminants that may merit further study or monitoring and 

to provide an early indication of contaminant concentrations of 

potential human-health concern in water resources (Toccalino 

and others, 2006).
Water-Rock Interactions and Ground-Water Geochemistry 35

Water-Rock Interactions and GroundWater Geochemistry

In carbonate aquifers, the dissolution of aquifer minerals, such as calcite and dolomite, is an important geochemical 

process that controls the major-ion composition and pH of 

ground water. Assessment of dominant-ion water types and 

ion ratios can provide quantitative information about mineralwater interactions. In addition, the determination of saturation 

indices with respect to certain minerals (calcite, dolomite, and 

gypsum) using thermodynamic models is useful to gain an 

improved understanding of the factors that influence groundwater geochemistry (Stumm and Morgan, 1981). Analysis of 

concentrations of dissolved oxygen in ground water aid in 

determining the oxidation and reduction reactions that play 

an important role in controlling many chemical processes 

in ground water, such as the speciation of various naturally 

occurring elements and the transformation and biodegradation 

of anthropogenic compounds such as nitrate, pesticides, and 

VOCs. Examination of concentrations of major ions, pH, and 

dissolved solids with depth in the aquifer can provide a means 

to assess the importance of ground-water residence time as a 

controlling factor on major-ion geochemistry.

Major Ions, Dissolved Solids, pH, and Mineral 

Saturation Indices

Previous studies of carbonate aquifers have shown that 

dissolution of aquifer minerals is a major geochemical process 

that controls the major-ion composition and pH of ground 

water (Sprinkle, 1989; Thomas and others, 1996; Adamski, 

2000). However, water from the 12 carbonate aquifers showed 

considerable variability in pH, major-ion composition, and 

concentrations of dissolved solids (table 9). The median pH 

value for all samples was 7.1, and medians ranged from 6.54 

in the Mississippian aquifer to 7.4 in the Floridan aquifer 

system and the Prairie du Chien aquifer (medians were 7.3 

and 7.35 in the Basin and Range and Castle Hayne aquifers). 

The median bicarbonate concentration in all samples was 

249 mg/L—the lowest median bicarbonate concentration was 

121 mg/L in the Mississippian aquifer, and the highest median 

concentration was 336 mg/L in the Silurian-Devonian/Upper 

carbonate aquifer (table 10). Median concentrations of calcium 

and magnesium in all samples were 63.7 and 10.4 mg/L, 

respectively. Median concentrations of calcium ranged from 

27.8 mg/L in the Mississippian aquifer to about 99.8 mg/L 

in the Biscayne aquifer, and median magnesium concentrations ranged from 2.2 mg/L in the Castle Hayne aquifer to 

25 mg/L in the Silurian-Devonian/Upper carbonate aquifers 

and 25.5 mg/L in the Prairie du Chien aquifers (table 10). The 

median concentration of sulfate for all samples was 9.4 mg/L, 

and median concentrations in individual aquifers ranged from 

0.3 mg/L in the Castle Hayne aquifer to 54.8 mg/L in the 

Basin and Range aquifer. Concentrations of dissolved solids 

ranged from 7 to 5,370 mg/L; the median concentration was 

269 mg/L (table 10). Median concentrations of dissolved 

solids in individual aquifers ranged from 139 mg/L in the 

Mississippian aquifer to 391.5 mg/L in the Piedmont and 

417.8 mg/L in the Basin and Range aquifers (table 10).

Comparison of major-ion concentrations and pH values 

to MCLs or SMCLs (U.S. Environmental Protection Agency, 

2006) indicated that few samples exceeded MCLs or SMCLs 

for pH, chloride, fluoride, sulfate or dissolved solids. Comparisons were made for data from all wells and for data from 

drinking-water wells (domestic and public supply wells). 

Fluoride was the only major ion or water property for which 

an MCL has been established, and less than 1 percent of 

wells (all wells or drinking-water wells) exceeded the MCL 

of 4 mg/L (table 11). About 13 percent of all wells and nearly 

16 percent of drinking-water wells had fluoride concentrations 

within 10 percent of the MCL. Dissolved solids concentrations exceeded the SMCL of 500 mg/L in about 7 percent of 

wells and nearly 8 percent of drinking-water wells. For pH, 

about 6 percent of samples from all wells and about 4 percent 

of drinking-water wells had values outside the SMCL range of 

6.5–8.5. SMCLs for chloride (250 mg/L), fluoride (4 mg/L), 

and sulfate (250 mg/L) were exceeded in less than 3 percent of 

wells (all wells or drinking-water wells).

As one would expect from the dissolution of calcite 

and dolomite in the selected carbonate aquifers, most water 

samples contained calcium, bicarbonate, and magnesium as 

dominant ions (fig. 7). The most commonly occurring majorion water types among all samples were calcium-bicarbonate 

(42 percent of the samples) and calcium-magnesium-bicarbonate (40 percent). About 18 percent of samples were classified 

as a mixed water type, indicating more than one cation or 

anion was dominant with the exception of Ca-Mg-HCO3

 and 

Ca-Mg-SO4

. One percent of samples had sodium-bicarbonate 

as dominant ions and 0.2 percent had sodium-chloride as 

dominant ions.

Calcium-bicarbonate was the dominant major-ion water 

type in water from the Biscayne (71 percent of 62 samples), 

Castle Hayne (72 percent of 30 samples), and Floridan 

(61 percent of 204 samples) aquifers/aquifer systems (fig. 8). 

Calcium-magnesium-bicarbonate was the dominant major-ion 

water type in the Piedmont (63 percent of 30 samples), Prairie 

du Chien (100 percent of 29 samples), Silurian-Devonian/

Upper carbonate (64 percent of 33 samples), and Valley and 

Ridge aquifers (63 percent of 186 samples), reflecting the 

presence of dolomite in these aquifer systems. Water samples 

from the Edwards-Trinity, Mississippian, Ordovician, and 

Ozark Plateaus aquifers/aquifer systems did not have one 

dominant water type, but three water types were noted in 

similar amounts—calcium-bicarbonate, calcium-magnesiumbicarbonate, and mixed water types, reflecting the diverse 

mineralogy and hydrogeology present in these systems. The 

Basin and Range aquifer samples were the only samples where 

the dominant water type was not calcium-bicarbonate or 

calcium-magnesium-bicarbonate—75 percent of 24 samples 

were classified as mixed water type.
36 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 9. Descriptive statistics for well depths and selected inorganic constituents in 12 carbonate aquifers or aquifer systems, 

1993–2005.

[Concentrations are expressed as milligrams per liter, except as noted; μg/L, micrograms per liter; S.I., saturation index]

Variable

Number 

of 

observations

Median 25th 

percentile

75th 

percentile Maximum

Well depth, feet 842 160 98.0 270.0 2,700

Temperature, degrees Celsius 1,033 17.4 14.1 23.1 53.3

Specific conductance, microsiemens per centimeter 1,023 469 309 610 9,180

Dissolved solids 1,027 269 183 357 5,370

Dissolved oxygen 1,029 4.3 .3 7.1 20.5

pH, standard units 1,034 7.1 6.9 7.4 9.0

Bicarbonate 980 248.7 166.5 315.2 690.0

Calcium 1,030 63.7 44.0 85.0 550.0

Magnesium 1,030 10.4 3.3 21.0 270.0

Sodium 1,030 5.4 2.6 11.7 1,763

Potassium 1,030 1.2 .7 2.1 117.2

Sulfate 1,027 9.4 3 23 2,100

Chloride 1,027 8.0 3.7 17 2,747

Silica 1,030 9.8 8.1 12.3 68.9

Fluoride 1,027 .1 .1 .2 5.5

Strontium, μg/L 425 220.0 92.3 606.1 43,950

Barium, μg/L 603 25.0 10.2 42.2 1,000

Boron, μg/L 217 13.9 9.5 22.4 1,388

Bromide 992 .04 .02 .08 9.50

Nitrate as nitrogen 1,037 .9 .06 2.6 25.0

Organic carbon 1,006 .4 .3 .9 36.0

Radon, picocuries per liter 735 360.0 160.0 630.0 5,994

S.I.-Calcite 973 -.07 -.26 .06 .65

S.I.-Dolomite 973 -.74 -1.39 -.24 1.29

S.I.-Gypsum 1,025 -2.63 -3.26 -2.19 -.06

Calcium to magnesium molar ratio 1,029 3.20 1.50 10.60 80.04

Charge balance error, percent 978 -8.15 -10.01 -6.00 56.15
Methods 37

Table 10. Numbers of samples and median values for well depths and selected inorganic constituents by aquifer, in 12 carbonate 

aquifers or aquifer systems, 1993–2005.

[Concentrations are expressed as milligrams per liter, except as noted; μS/cm, microsiemens per centimeter; μg/L, micrograms per liter; S.I., saturation index; 

–, no data]

Constituent

Basin and Range

Biscayne

Castle-Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Number of samples 24 65 32 125 215 66 40 185 30 30 33 186

Well depth, feet 890 45 94 385 170 53 125 183 160 177 225 158

Temperature, degrees Celsius 27.5 25.2 18.2 23.4 22.8 17.7 16.3 15.0 13.1 12.3 12.1 13.5

Specific conductance, μS/cm 679.5 624.0 406.5 556.0 305.0 235.0 514.5 391.0 654.0 555.5 589.0 526.0

Dissolved solids 417.8 379.0 264.8 323.0 189.0 139.0 306.0 218.0 391.5 300 341.0 295.1

Dissolved oxygen 2.65 .14 .13 5.95 .7 5.20 1.90 6.65 5.95 .92 .10 7.10

pH, standard units 7.30 6.80 7.35 6.98 7.4 6.54 6.95 7.12 7.30 7.38 7.15 7.20

Bicarbonate 258.0 303.5 245.0 301.8 160.4 121.0 279.5 229.0 257.0 300.7 336.0 271.5

Calcium 53.8 99.8 69.5 81.0 47.0 27.8 69.7 56.0 74.5 66.5 75.0 68.2

Magnesium 20.6 3.9 2.2 15.0 3.8 3.3 8.1 8.1 24.5 25.5 25.0 18.0

Sodium 42.4 21.4 7.3 8.5 4.6 2.1 5.0 3.6 5.7 4.3 8.6 3.8

Potassium 8.0 2.4 1.5 1.1 .6 .5 1.6 1.0 2.0 1.35 2.1 1.5

Sulfate 54.8 17.0 .3 16.9 3.5 2.7 25.6 5.6 37.5 16 24.0 14.0

Chloride 39.6 32.8 8.0 14.0 6.1 3.4 5.6 5.4 18.5 2.95 2.3 9.0

Silica 22.2 6.8 23.1 12.0 12.2 8.5 8.0 9.6 9.4 19 12.0 8.6

Fluoride .69 .24 .17 .20 .2 .10 .21 .10 .10 .2 .50 .10

Strontium, μg/L 606.3 911.5 209.4 316.2 95.7 – – – – – – 200.0

Barium, μg/L 67.0 20.0 11.4 38.0 7.0 19.0 22.8 41.0 – 46.0 – 63.3

Boron, μg/L 230.1 – 16.0 50.2 13.2 – – – – – – 7.0

Bromide .11 .07 .05 .10 .03 .02 .02 .04 .03 .04 .04 .03

Nitrate as ntirogen .31 .05 .06 1.23 .06 1.35 .44 1.10 11.00 .12 .05 3.50

Organic carbon .30 11.00 2.51 .40 .42 .40 .83 .40 .30 .60 1.20 .30

Radon, picocuries per liter 482 440 104 168 184 579 222 280 710 410 290 481

S.I.-Calcite .08 -.15 .08 -.07 -.01 -1.19 -.29 -.23 .10 .21 -.08 -.06

S.I.-Dolomite .14 -1.34 -1.07 -.56 -.82 -3.01 -1.11 -1.38 -.23 .23 -.46 -.66

S.I.-Gypsum -2.03 -2.25 -4.21 -2.33 -3.26 -3.39 -2.23 -2.89 -2.00 -2.42 -2.16 -2.39

Calcium-magnesium molar ratio 1.51 14.49 20.55 3.03 7.96 3.19 2.94 3.85 1.78 2.48 1.72 1.87

Charge balance error, percent -6.54 -8.59 27.92 -8.78 -6.81 -8.63 -8.97 -10.29 -6.99 -4.89 -7.85 -8.42
38 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 11. Comparison of water properties and concentrations of major ions in wells with human-health benchmarks and non-health 

guidelines for drinking water, in 12 carbonate aquifers or aquifer systems, 1993–2005.

[mg/L, milligrams per liter; –, not applicable; drinking-water wells includes domestic and public supply well types]

Property or major ion

Number 

of 

wells

Type of drinking-water 

regulation Wells exceeding drinking-water regulation

Maximum 

contaminant 

level1

Secondary 

 maximum 

contaminant 

level2

Maximum 

contaminant 

level

Ten percent of 

maximum 

contaminant 

level

Secondary 

maximum 

contaminant 

level

Number Percent Number Percent Number Percent

Water Properties

pH, in standard units 1,041 – 6.5 - 8.53 – – – – 64 6.1

(pH in drinking-water wells) 665 27 4.1

Major Ions, in mg/L

Chloride 1,033 – 250 – – – – 9 .9

(Chloride in drinking-water wells) 662 4 .6

Fluoride 1,033 4 2 3 0.3 138 13.4 22 2.1

(Fluoride in drinking-water wells) 662 3 .5 103 15.6 17 2.6

Sulfate 1,033 – 250 – – – – 21 2.0

(Sulfate in drinking-water wells) 662 15 2.3

Dissolved solids (DS) 1,033 – 500 – – – – 74 7.2

(DS in drinking-water wells) 662 51 7.7

1

 Maximum contaminant levels are National Primary Drinking Water Regulations (NPDWRs or primary standards) established by the U.S. Environmental 

Protection Agency (USEPA) that are legally enforceable standards that apply to public water systems. Primary standards protect public health by limiting the 

levels of contaminants in drinking water (U.S. Environmental Protection Agency, 2006).

2

 Secondary maximum contaminant levels are National Secondary Drinking Water Regulations (NSDWRs or secondary standards) established by USEPA 

that are non-enforceable guidelines regulating contaminants that may cause cosmetic effects (such as skin or tooth discoloration) or aesthetic effects (such as 

taste, odor, or color) in drinking water. USEPA recommends secondary standards to water systems but does not require systems to comply (U.S. Environmental Protection Agency, 2006).

3

 Samples with pH less than 6.5 or pH greater than 8.5 exceed the SMCL
Methods 39

Figure 7. Piper diagrams for 12 carbonate aquifers or aquifer systems, 1993–2005.

Basin and Range

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Biscayne

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Castle-Hayne

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Edwards-Trinity

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Floridan

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Mississippian

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Unconfined Confined

EXPLANATION

Semiconfined or 

mixed confined

Confinement

undetermined
40 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 7. Piper diagrams for 12 carbonate aquifers or aquifer systems, 1993–2005.—Continued

Confinement

undetermined

Ordovician

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Ozark Plateaus

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Piedmont

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Prairie du Chien

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Silurian-Devonian/

Upper carbonate

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Valley and Ridge

0

80

60

40

20

80

60

40

20

80

60

40

20

0 0

0

80

60

100 100

100 100

40

20

60

80

100

20

40

0

100

80

60

40

20

0

Cl + SO4

Mg

Ca Na + K HCO3 Cl

Ca + Mg

SO4

Unconfined Confined

EXPLANATION

Semiconfined or 

mixed confined
Water-Rock Interactions and Ground-Water Geochemistry 41

Water from certain carbonate aquifers showed considerable variability in the composition of major ions (fig. 8). 

The most variability within aquifers or aquifer systems was 

seen in the Basin and Range (24 samples), Castle Hayne (32 

samples), Floridan (224 samples), Mississippian (66 samples), 

and Ordovician (40 samples) (fig. 8). In areas where the 

Floridan aquifer system is poorly confined and confined, 

sodium-bicarbonate was the water type in 8 of 30 samples (in 

South Carolina) and sodium is a major cation for 30 percent of 

samples. Katz (1992) and Sprinkle (1989, p. 31) hypothesized 

that cation exchange is the likely geochemical process that 

accounts for this water type in the Upper Floridan aquifer.

Additional evidence for calcite and dolomite dissolution 

as the major geochemical process that controls the major-ion 

composition can be gleaned from the relation between molar 

concentrations of calcium plus magnesium and bicarbonate. 

The molar concentration of bicarbonate (in millimoles per 

liter) would be two times the sum of the molar concentrations 

of calcium and magnesium if calcite and dolomite mineral 

dissolution was the dominant process. Most water samples 

plot along a line with a 2:1 slope (bicarbonate to calcium plus 

magnesium), except for water from the Piedmont aquifer and 

selected samples in the Basin and Range, Edwards-Trinity, 

and Silurian-Devonian/Upper carbonate aquifers/aquifer 

systems, all of which show excess amounts of calcium plus 

magnesium (fig. 9). These aquifers had median concentrations 

of sulfate ranging from 17 to 42 mg/L, which were greater 

than 9.6 mg/L, the median for all samples. In the EdwardsTrinity aquifer system, the excess amount of calcium possibly 

is related to the presence of gypsum in the aquifer materials, 

because several of these samples are calcium-sulfate type 

waters (fig. 9). In the Basin and Range and Silurian-Devonian/

Upper carbonate aquifers, the excess calcium may reflect 

longer residence times of ground water because the median 

concentrations of dissolved solids in these two aquifers (418 

and 341 mg/L, respectively) were higher than most other 

aquifers (table 10). The Ordovician aquifer also had a median 

concentration of sulfate in this range at 25.6 mg/L, but this 

does not appear to be related to concentrations of calcium and 

magnesium (or gypsum).

 Water types and ion ratios provide important information about mineral-water interactions; however, they do not 

disclose how the chemical composition of water changes as 

it moves through the various carbonate-aquifer systems. One 

method commonly used assumes that all dissolved species 

are at equilibrium, which allows the use of thermodynamic 

models to calculate the distribution of dissolved species. In 

this study, the computer program PHREEQC (Parkhurst and 

Appelo, 1999) is used to calculate the distribution and activities of dissolved species and the saturation state of ground 

water with respect to minerals (calcite, dolomite, and gypsum) 

and gases (such as carbon dioxide). The S.I. is a measure of 

the departure from equilibrium and is expressed as:

S.I. = log (IAP/KT) (4)

where

S.I. is saturation index,

IAP is the ion activity product of the components 

of the solid or gaseous phase, and

KT is the solid or gaseous phase solubility 

equilibrium product at the specified 

temperature (at the time of sampling).

0

20

40

60

80

100

All samples

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ Upper carbonate

Valley and Ridge

PERCENT OF SAMPLES

Calcium-bicarbonate

Calcium-magnesium-sulfate

Mixed

Sodium-chloride

Sodium-bicarbonate

Calcium-magnesium-bicarbonate

Figure 8. Dominant-ion water types in 12 carbonate aquifers or aquifer systems, 1993–2005.
42 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

CALCIUM+MAGNESIUM, IN MILLIMOLES PER LITER

0

2

4

6

8

10

12

0

2

4

6

8

10

12

BICARBONATE, IN MILLIMOLES PER LITER

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

0

2

4

6

8

10

12

Castle Hayne

Edwards-Trinity

Basin and Range Biscayne

Floridan Mississippian

Ordovician Ozark Plateaus Piedmont

Prairie du Chien Silurian-Devonian/

Upper carbonate

Valley and Ridge

0 5 10 15 20 0 5 10 15 20 0 5 10 15 20

0 5 10 15 20 0 5 10 15 20 0 5 10 15 20

0 5 10 15 20 0 5 10 15 20 0 5 10 15 20

0 5 10 15 20 0 5 10 15 20 0 5 10 15 20

EXPLANATION

Line showing 2:1 ratio for Ca+Mg to HCO3

DOMINANT ION WATER TYPE

Calcium-bicarbonate

Calcium-magnesium-sulfate

Mixed

Sodium-chloride

Sodium-bicarbonate

Calcium-magnesium-bicarbonate

Figure 9. Ratio of calcium plus magnesium to bicarbonate for each aquifer in 12 carbonate aquifers or aquifer systems, 

1993–2005.
Water-Rock Interactions and Ground-Water Geochemistry 43

When S.I. is equal to 0, the solid or gaseous phase is in equilibrium with the ground water. When S.I. is less than 0, the 

solid or gaseous phase is undersaturated, which means that 

the phase has thermodynamic potential to dissolve. When S.I. 

is greater than 0, the solid or gaseous phase is supersaturated, 

and the phase has the potential to precipitate or volatilize.

The S.I. values with respect to calcite, dolomite, and 

gypsum for water from the 12 carbonate aquifers were highly 

variable and reflect differences in their mineralogy. Most S.I. 

values with respect to calcite are within the -0.2 to 0.2 range 

considered to be at equilibrium with respect to calcite; however, most water samples from the Mississippian and Ordovician aquifers have calcite S.I. values lower than -0.2 (table 10; 

fig. 10). Median S.I. values with respect to calcite range from 

-1.19 in the Mississippian aquifer to 0.21 in the Prairie du 

Chien aquifer. The S.I. values with respect to dolomite showed 

that samples from most aquifers are undersaturated with 

respect to dolomite, except for the Basin and Range and Prairie du Chien aquifers. The Basin and Range carbonate aquifers 

are composed of limestone and dolomite (Plume, 1995) and 

the Prairie du Chien aquifer is composed of dolomite (Young 

and Siegel, 1992). Median S.I. values for dolomite ranged 

from -3.01 in the Mississippian aquifer to 0.23 in the Prairie 

du Chien aquifer. Water samples from all the carbonate aquifers are undersaturated with respect to gypsum (fig. 11). The 

median S.I. with respect to gypsum was -2.63 for all samples, 

and medians in individual aquifers ranged from -4.21 in the 

Castle Hayne aquifer to -2.00 in the Piedmont aquifer.

Geochemical indicators such as S.I. values and calciummagnesium ratios are used in studies of karst aquifers to infer 

the residence time of the water, or whether flow in the aquifer 

is dominated by conduit flow or diffuse flow through fractures or pores. Previous studies have shown that waters with 

the longer transport times associated with diffuse flow and 

fracture permeability typically are more saturated with respect 

to calcite than waters moving rapidly through a conduit 

system with much less contact time with the bedrock. Data 

from White (1988) from karst waters in the North Central 

Appalachian Mountains show that diffuse-flow springs and 

wells have a higher S.I. with respect to calcite (-0.24 and 

-0.13, respectively) than conduit-flow springs (-0.89). The S.I. 

values, however, also vary relative to other issues such as the 

purity of the carbonate rock and pH, temperature, and source 

of the recharge water. A study in the Valley and Ridge aquifer 

by Langmuir (1971) indicated that the degree of saturation 

with respect to calcite and dolomite increased with residence 

time; however, this study also points out the control of lithology (limestone or dolomite) in these processes. A study in the 

Ordovician aquifer in Kentucky (Scanlon and Thrailkill, 1987) 

found that the calcite S.I. values did not differ significantly 

among major springs and high-level springs (analogous to 

conduit and diffuse springs in White’s study).

Studies of the Ordovician aquifer in Kentucky determined that, in a limestone aquifer with a uniformly distributed 

minor amount of dolomite, higher calcium-magnesium ratios 

may indicate longer residence times (Scanlon, 1989). Another 

study in that area found that calcium-bicarbonate type water 

was frequently contaminated with nitrate, whereas calciummagnesium-bicarbonate type water was not. This was attributed to the occurrence of calcium-bicarbonate water type in 

the shallow part of the aquifer, which is most susceptible to 

contamination, and the calcium-magnesium-bicarbonate water 

type occurring in the parts of the aquifer with longer residence 

time, allowing for denitrification (Scanlon, 1990). A study of 

cave drip waters in the Edwards aquifer indicated a similar 

relation between calcium-magnesium ratios and residence time 

(Musgrove and Banner, 2004).

The geochemical studies cited typically included detailed 

knowledge of the flowpath and specific lithology (limestone or 

dolomite), which are critical in interpreting mass transfer and 

reaction rates. In the present study, lithology at the location of 

the well is known, but the proximity of nearby lithologies and 

the position of the well on the flowpath is not known. Residence time is known for a subset of the wells and is limited 

to designations of recharge before 1953 or recharge in 1953 

and later. The applicability of these indicators would be very 

different in a pure limestone aquifer than in a dolomite or 

limestone and dolomite aquifer. Thus, these geochemical indicators are important to analyze with respect to anthropogenic 

contaminants, but the techniques developed for a given region 

may not be transferrable and may be difficult to interpret on a 

national scale.

Data from the current study were analyzed for patterns 

indicating relations between geochemical indicators and conduit flow or residence time. Age-dating information was only 

available for a subset of 476 samples; however, a comparison 

on the basis of age of recharge water (from tritium concentrations, not including samples indicating mixed ground-water 

age) showed that samples representing water recharged before 

1953 had higher concentrations of magnesium, more positive 

values of calcite S.I., more positive values of dolomite S.I., 

and lower calcium-magnesium ratios than samples representing water recharged in 1953 or later (Wilcoxon rank-sum test, 

p-value less than 0.05 for each comparison). These results support the relations posed by White (1988) and Scanlon (1989), 

and although a specific designation of conduit or diffuse flow 

may not be possible, a general relation between these measures and residence time is evident.

Oxidation-Reduction Status

Oxidation and reduction (redox) reactions play an important role in controlling many chemical processes in ground 

water, such as the speciation of naturally occurring elements 

(including sulfur, arsenic, and iron) and the transformation 

and biodegradation of anthropogenic compounds (including 

nitrate, pesticides, and VOCs). Redox reactions are typically microbially mediated in ground water and involve the 

transfer of electrons from one material to another. Inorganic 

compounds that can accept electrons and that allow oxidation 

of organic material are called electron acceptors (Chapelle, 
44 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

24 63 32 124 63 40 145 30 204 18633 158 97 715

CALCITE SATURATION INDEX

 -6

 -5

 -4

 -3

 -2

 -1

 0

 1

 -7

 -6

 -5

 -4

 -3

 -2

 -1

 0

 1

 -8

 -9

24 63 32 124 63 40 145 30 204 18633 158 97 715

DOLOMITE SATURATION INDEX

29

29

Castle Hayne

Edwards-Trinity

Biscayne

Basin and Range

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Valley and Ridge

Silurian-Devonian/ Upper carbonate

Unconfined

Semiconfined

or mixed

confined

Confined

715

90th percentile

75th percentile

Number of samples

Median

25th percentile

10th percentile

EXPLANATION

A

B

Figure 10. Distribution of saturation index values for A) calcite and B) dolomite by aquifer and confinement category in 

12 carbonate aquifers or aquifer systems, 1993–2005.
Water-Rock Interactions and Ground-Water Geochemistry 45

GYPSUM SATURATION INDEX

-6

-5

-4

-3

-2

-1

0 24 64 32 125 66 40 185 30 211 29 18633 158 110 754

Castle Hayne

Edwards-Trinity

Biscayne

Basin and Range

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Valley and Ridge

Silurian-Devonian/ Upper carbonate

Unconfined

Semiconfined

or mixed

confined

Confined

EXPLANATION

754

90th percentile

75th percentile

Number of samples

Median

25th percentile

10th percentile

Figure 11. Distribution of saturation index values for gypsum by aquifer and confinement category in 12 carbonate 

aquifers or aquifer systems, 1993–2005.
46 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

1993). The most common electron acceptors in natural environments are oxygen, nitrate, iron, sulfate, and carbon dioxide. 

The electron donor is typically organic carbon, but sulfide 

minerals and anthropogenic organic compounds also can act as 

electron donors.

Dissolved oxygen in ground water originates from the 

atmosphere and is depleted in ground-water flow systems 

through reaction with organic carbon and other electron 

donors. Recently recharged, shallow ground water often contains more dissolved oxygen than older, deeper ground water.

The median concentration of dissolved oxygen in all samples 

from the carbonate aquifers was 4.3 mg/L; however, median 

concentrations in individual aquifers and aquifer systems 

ranged from 0.1 mg/L in the Biscayne, Castle Hayne, SilurianDevonian/Upper carbonate aquifers to 6.6 mg/L in the Ozark 

Plateaus aquifer system (fig. 12). Median concentrations of 

dissolved oxygen were also less than 1.0 mg/L in the Floridan aquifer system and the Prairie du Chien aquifer (fig. 12; 

table 10).

Concentration of dissolved oxygen varied by confinement categories in some aquifers or aquifer systems. In the 

Floridan aquifer system, the highest median concentration 

of dissolved oxygen was 4.3 mg/L in the 94 samples from 

areas where the aquifer is unconfined; median concentrations 

were 0.3 and 0.1 mg/L in semiconfined and confined areas, 

respectively (fig. 13). Similar results were seen in the Ozark 

Plateaus, Prairie du Chien, and Silurian-Devonian/Upper 

carbonate, where concentrations of dissolved oxygen were 

highest in the unconfined areas. In contrast, concentrations of 

dissolved oxygen were similar in water from wells in confined 

and unconfined areas in the Edwards-Trinity aquifer system 

(medians of 5.8 and 6.0, respectively) (fig. 13). Concentrations 

of dissolved oxygen were also elevated in the confined Basin 

and Range aquifer where the median was 2.6 mg/L. Differences in concentrations of dissolved oxygen are likely related 

to timing and amounts of recharge, presence of karst features 

such as sinkholes and large conduits, and presence of dissolved organic carbon.

Concentrations of dissolved organic carbon varied among 

the aquifers and aquifer systems. Dissolved organic carbon 

in ground water originates naturally from organic material 

but also may be contributed to ground water through waste 

disposal and animal production. The median concentration 

of dissolved organic carbon in all samples from the carbonate aquifers is low (0.4 mg/L), and median concentrations 

ranged from 0.3 mg/L in the Basin and Range, Piedmont, and 

Valley and Ridge aquifer systems to 11 mg/L in the Biscayne 

aquifer. The aquifers with the highest median concentrations 

of dissolved organic carbon—Biscayne (11 mg/L), Castle 

Hayne (2.51 mg/L), and Silurian-Devonian/Upper carbonate 

(1.2 mg/L) aquifers—were the three aquifers with the lowest 

median dissolved oxygen concentrations (table 10, fig. 12). 

Organic carbon is likely limiting the amount of oxygen in 

the ground water in these systems. The Biscayne and Castle 

Hayne aquifers are located in coastal areas and the wells 

are fairly shallow with shallow depths to water [10 ft or less 

Table 12. Threshold concentrations for identifying redoxstatus category.

[≥, greater than or equal to; >, greater than; <, less than; NA, no threshold 

applicable]

Redox-status 

category

Water-quality threshold 

(milligrams per liter)

Dissolved 

oxygen Manganese Iron

Oxic ≥ 0.5 < 0.05 < 0.1

Mixed source ≥ .5 > .05 > .1

Anoxic < .5 NA NA

(table 5)], but the median depth to water was much greater 

(about 59 ft) in the Silurian-Devonian/Upper carbonate aquifer 

(table 5). The Biscayne aquifer receives recharge directly from 

surface water, especially canals. Water samples from canals 

in southeastern Florida have a median concentration of total 

organic carbon of 21 mg/L; concentrations range from 5.0 to 

46 mg/L (Radell and Katz, 1991).

Redox status in ground water varied among the carbonate 

aquifers (fig. 14). Redox status was determined on the basis of 

threshold concentrations of dissolved oxygen, manganese, and 

iron (McMahon and Chapelle, 2008) and were used to group 

the water-quality samples into three groups—oxic, mixed 

source, and anoxic (table 12). The percentage of samples 

designated as oxic was highest in the Valley and Ridge aquifer 

(91 percent), Edwards-Trinity aquifer system (85 percent), and 

Ozark Plateaus aquifer system (83 percent). Aquifers with the 

most samples designated as anoxic were the Biscayne (91 percent), Silurian-Devonian/Upper carbonate (91 percent), and 

Castle-Hayne (84 percent).

Comparison of samples according to redox status and 

confinement categories showed that most of the samples collected from unconfined areas were designated as oxic, and 

samples from confined areas contained similar numbers of 

samples designated as anoxic and oxic. Sixty-five percent 

(666 samples) of the 1,027 samples had a redox status designated as oxic, 29 percent were anoxic, and 6 percent were 

mixed. The majority of the samples were from sites classified 

as unconfined (75 percent of all sites), and within unconfined 

areas, 75 percent of these samples were designated as oxic 

(fig. 15). In confined areas, 52 percent of samples were designated as anoxic, and 43 percent were designated as oxic.

Classification of samples into groups on the basis of age 

of recharge water (from tritium concentrations) showed that 

most of the samples representing water recharged after 1953 

were designated as oxic (fig. 16). About 85 percent of 476 

samples represent recharge of water from 1953 or later and 

about 77 percent of these samples were classified as oxic. 

The high percentages of samples designated as anoxic in the 

older water samples (representing recharge prior to 1953) are 

consistent with the assumption that oxygen is consumed over 

time (McMahon and Chapelle, 2008).
Water-Rock Interactions and Ground-Water Geochemistry 47

A

B

6

8

10

0

 2

4

0

5

10

15

20

25

30

30 64 32 124 216 64 40 188 30 33 185 163 110 760

DISSOLVED OXYGEN CONCENTRATION,

 IN MILLIGRAMS PER LITER 

30 65 27 123 214 66 40 173 30 33 184 154 110 745

DISSOLVED ORGANIC CARBON

 CONCENTRATION, 

IN MILLIGRAMS PER LITER

29

29

Unconfined

Semiconfined

or mixed

confined

Confined Castle Hayne

Edwards-Trinity

Biscayne

Basin and Range

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Valley and Ridge

Silurian-Devonian/ Upper carbonate

EXPLANATION

214

90th percentile

75th percentile

Number of samples

Median

25th percentile

10th percentile

Figure 12. Distribution of A) dissolved oxygen and B) dissolved organic carbon by aquifer and confinement category in 12 

carbonate aquifers or aquifer systems, 1993–2005.
48 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 DISSOLVED OXYGEN CONCENTRATION, IN MILLIGRAMS PER LITER

30 64 19 10 35 89 29 93 64 40 12 17 159 30 94 18 15 185

 6

 8

 10

 0

 2

 4

10 20

Confined Castle Hayne

Confined Edwards-Trinity

Unconfined Biscayne

Confined Basin and Range

Confined Floridan

Unconfined Mississippian

 Unconfined Ordovician

Confined Ozark Plateaus

Unconfined Piedmont

Confined Prairie du Chien

Unconfined Valley and Ridge

Confined Silurian-Devonian/

Upper carbonate

Unconfined Castle Hayne

Unconfined Edwards-Trinity

Semiconfined Floridan

Unconfined Floridan

Mixed confined Ozark Plateaus

Unconfined Ozark Plateaus

Unconfined Prairie du Chien

Unconfined Silurian-Devonian/

Upper carbonate

EXPLANATION

159

90th percentile

75th percentile

Number of samples

Median

25th percentile

10th percentile

AQUIFER-CONFINEMENT CATEGORY

Confined

Semiconfined/Mixed confined

Unconfined

Figure 13. Distribution of dissolved oxygen by aquifer and confinement category in 12 carbonate aquifers or 

aquifer systems, 1993–2005.
Water-Rock Interactions and Ground-Water Geochemistry 49

Valley and Ridge

N=186

Prairie du Chien

N=30

Ordovician

N=40

Edwards-Trinity

N=125

Floridan

N=224

Silurian-Devonian/

Upper carbonate

N=33

Mississippian

N=66

N=188

Ozark Plateaus Piedmont

N=30

Basin and Range Biscayne Castle-Hayne

N=24 N=65 N=32

EXPLANATION

N = NUMBER OF SITES

REDOX-STATUS CATEGORY (see table 12 for definitions)

Anoxic Mixed source Oxic

Figure 14. Oxidation-reduction (redox) status categories in 12 carbonate aquifers or aquifer systems, 

1993–2005.
50 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Confined Semiconfined

or mixed confined Unconfined

100

90

80

70

60

50

40

30

20

10

0

PERCENT OF SAMPLES

Anoxic

Mixed source

Oxic

Figure 15. Redox status grouped by confinement category in 12 carbonate aquifers or 

aquifer systems, 1993–2005.

Anoxic

Mixed source

Oxic

100

90

80

70

60

50

40

30

20

10

0

PERCENT OF SAMPLES

Recharge prior to 1953 Recharge 1953 or later

Figure 16. Redox status grouped by ground-water age in 12 

carbonate aquifers or aquifer systems, 1993–2005.
Water-Rock Interactions and Ground-Water Geochemistry 51

 Correlations with Well Depth

The relative concentrations of inorganic constituents 

(major ions, pH, and dissolved solids) are related to depth in 

the aquifer (well depth below land surface) and indicate the 

importance of ground-water residence time as a controlling 

factor on major-ion geochemistry. Wells in the Biscayne and 

Mississippian aquifers were the most shallow (median well 

depths of 45 and 53 ft, respectively) and water from these 

two aquifers had the lowest median pH values (6.80 and 6.54, 

respectively) (table 10). The water samples from the Mississippian aquifer also had the lowest median concentrations of 

dissolved solids, bicarbonate, calcium, sodium, potassium, 

and chloride, implying that samples from these wells have 

had shorter residence time than samples from other wells and 

(or) aquifers. The deepest wells were in the Basin and Range 

aquifer (median well depth 890 ft), and water from these wells 

had the highest median concentrations of sodium, potassium, 

chloride, silica, and fluoride, indicating that samples from 

these wells likely had longer residence times than samples 

from other wells and (or) aquifers.

Concentrations and values of many major ions and field 

characteristics were significantly correlated with well depth, 

which indicates that the position along a ground-water flowpath and ground-water residence time are important controlling variables. Results of the Spearman’s rank correlation test 

(table 13) showed that values of specific conductance and 

pH, as well as concentrations of dissolved solids, magnesium, 

sodium, potassium, bicarbonate, silica, fluoride, barium, 

boron, bromide, calcite S.I., and dolomite S.I. were significantly correlated with well depth and had positive correlation 

coefficients, indicating values or concentrations increased as 

well depth increased. Concentrations of calcium, dissolved 

organic carbon, calcium-magnesium ratios, and radon also 

were inversely correlated with well depth, indicating concentrations or values decreased as well depth increased. Temperature and concentrations of dissolved oxygen, chloride, and 

strontium were not significantly correlated with well depth. 

The positive relation of magnesium, calcite S.I., and dolomite 

S.I. with well depth and the inverse relation between calciummagnesium ratios and well depth are consistent with the 

concepts of White (1988) and Scanlon (1990), in that water 

from deeper wells would have longer residence times and 

be closer to saturation with respect to calcite and dolomite, 

and also have a lower calcium-magnesium ratio. The inverse 

correlation between calcium and well depth may indicate ion 

exchange with sodium, which has a positive correlation with 

well depth.

Table 13. Spearman’s rank correlations between well depth and selected water characteristics in 

12 carbonate aquifers or aquifer systems, 1993–2005.

[NS, correlation not significant–p-value greater than 0.05; <, less than]

Constituent Number of 

samples

Correlation 

coefficient p-value

Temperature 849 NS 0.24

Specific conductance 846 0.09 .01

Dissolved solids 846 .08 .02

Dissolved oxygen 845 NS .73

pH 849 .27 < .0001

Bicarbonate 809 .09 .01

Calcium 847 -.07 .05

Magnesium 847 .34 < .0001

Sodium 847 .13 < .0001

Potassium 847 .16 < .0001

Sulfate 845 .18 < .0001

Chloride 845 NS .64

Silica 847 .39 < .0001

Fluoride 842 .27 < .0001

Strontium 413 NS .81

Barium 512 .25 < .0001

Boron 210 .22 < .0001

Bromide 778 .27 < .0001

Dissolved organic carbon 828 -.27 < .0001

Calcite saturation index 797 .15 < .0001

Dolomite saturation index 797 .42 < .0001

Calcium-magnesium molar ratio 797 -.34 < .0001

Radon 651 -.29 < .0001
52 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Unconfined

Semiconfined

or mixed

confined

Confined

0

1,000

2,000

3,000

RADON CONCENTRATION, IN PICOCURIES PER LITER

22 65 30 88 139 31 39 30 32 178 29 118 66 548

Proposed Maximum

 Contaminant Level

4,000

Castle Hayne

Edwards-Trinity

Biscayne

Basin and Range

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Valley and Ridge

Silurian-Devonian/ Upper carbonate

52

EXPLANATION

548

90th percentile

75th percentile

Number of samples

Median

25th percentile

10th percentile

Figure 17. Distribution of radon values in aquifers and by confinement category in 12 carbonate aquifers or aquifer 

systems, 1993–2005.

Radon

Radon concentrations were highly variable in the individual carbonate aquifers, and median concentrations ranged 

from 104 pCi/L in the Castle Hayne aquifer to 710 pCi/L in 

the Piedmont aquifer (table 10). The median concentration 

of radon for all samples in carbonate aquifers was 360 pCi/L 

(table 9). The maximum value was 5,994 pCi/L in the Floridan 

aquifer system. Most radon concentrations in water from the 

Basin and Range, Biscayne, Mississippian, Piedmont, Prairie 

du Chien, and Valley and Ridge aquifers were greater than the 

USEPA proposed MCL of 300 pCi/L (fig. 17) (U.S. Environmental Protection Agency, 2006). Median radon concentrations were highest in the water in unconfined areas—the 

median concentration was 401 pCi/L in unconfined areas (548 

samples) compared to 267 pCi/L in semiconfined/mixed confined areas (66 samples) and 230 pCi/L in confined areas (124 

samples). Radon exceeded the proposed MCL in 423 of 735 

wells sampled, of which 309 were drinking-water supplies.
Factors Affecting Anthropogenic Contaminants 53

Factors Affecting Anthropogenic 

Contaminants

The NAWQA Program sampled a number of constituents 

that are considered anthropogenic contaminants. The primary 

anthropogenic contaminants that were widely sampled for 

and analyzed were nitrate, pesticides, and VOCs. The following sections detail the concentrations, occurrence, and factors 

affecting nitrate, pesticides, and VOCs in the 12 carbonate 

aquifers.

Nitrate

Nitrate is potentially the most widespread contaminant in 

ground water (Hallberg and Keeney, 1993). Nitrogen is widely 

used as a fertilizer for agricultural activities and is also present 

in human waste, animal waste, and combustion by-products; 

therefore, the land surface is exposed to a large amount of 

nitrogen from various sources. Nitrogen in soils can be in 

the form of organic nitrogen, ammonia (NH4

), nitrite (NO2), 

or nitrate (NO3

). Nitrate is a highly soluble form of nitrogen 

that can readily leach into the ground water and can also be 

denitrified to the form of N2

 gas. The concentrations of nitrate 

in ground water are a concern because of the potential humanhealth effects, specifically methemoglobinemia in infants, 

which has led the USEPA to set the drinking-water standard 

for nitrate at 10 mg/L as nitrogen or “as N” (U.S. Environmental Protection Agency, 2006). The widespread occurrence 

of nitrate, in combination with its potential for human health 

effects, makes nitrate in ground water an important issue to 

understand.

Distribution of Nitrate Concentrations

Samples from 1,037 wells and springs were analyzed 

for nitrate by the NAWQA Program in the 12 carbonate 

aquifers. The laboratory results for nitrate are reported as 

NO3

 plus NO2, in milligrams per liter as N; however, because 

NO2

 concentrations are very low (877 of the 1,037 samples 

were less than the LRL of 0.01 mg/L and the 95th percentile 

was 0.02 mg/L), the value of NO3

 plus NO2 is assumed to be 

equivalent to NO3

 as N and is referred to hereafter as nitrate. 

Nitrate was detected at concentrations greater than 0.06 mg/L 

in 793 of 1,037 samples. Concentrations ranged from below 

the detection limit of 0.06 mg/L to 25 mg/L. Although not all 

the sample locations represent drinking-water supplies, the 

majority are used for public or domestic supply. Many of those 

samples from sites that are not used for drinking water are representative of a part of a flow system that is a drinking-watersupply aquifer. When comparing the results to the USEPA 

drinking-water standard for nitrate, samples from 54 sites 

exceed the MCL of 10 mg/L, of which 52 sites were sources 

used for domestic supply. The exceedances were mostly from 

the Valley and Ridge aquifer, with 26 samples exceeding the 

MCL (14 percent), and the Piedmont aquifer, with 19 samples 

exceeding the MCL (63 percent). In the rest of the aquifers, 

only nine samples (about 1 percent) exceeded the MCL for 

nitrate. Median nitrate concentrations were highest in the 

Piedmont and Valley and Ridge carbonate aquifers, and lowest 

in the Biscayne, Castle Hayne, and Silurian-Devonian/Upper 

carbonate aquifers (fig. 18).

The results in figure 18 should be interpreted in the context of the design of the studies that were used in each aquifer. 

Sampling is not equally distributed among each aquifer or 

land-use type. Wells in some of the aquifers are predominantly 

of a single land use, and in some cases, shallow wells in that 

land use were targeted for study (table 3). The characteristics of the wells sampled also vary among the aquifer types 

(table 5). The land-use distribution near the wells is illustrated 

in figure 3. Thus the potential factors affecting nitrate concentration differ among the various aquifers. This range of 

network and well characteristics, however, provides an opportunity to analyze the potential effect of these characteristics in 

carbonate aquifers.

Factors Affecting Nitrate Concentrations

Concentrations of nitrate in the 12 carbonate aquifers are 

related to the inherent susceptibility of the aquifer to contamination, the intensity of the source of nitrogen, and the interaction between the two. Water from wells in agricultural landuse studies had higher median concentrations than water from 

wells in other study types. Nitrate concentrations were rarely 

elevated in confined aquifers and in wells where age-dating 

indicated that the water was predominantly recharged prior 

to 1953. The concentrations of nitrate were closely related to 

the redox status of the water. The susceptibility of the aquifer 

to contaminants is based on transport factors and includes 

physical factors that allow nitrate to move into the aquifer, as 

well as biological and chemical factors that may facilitate or 

attenuate the movement of nitrate. The intensity of the source 

of nitrogen is determined by surrogates such as land use and, 

where possible, estimates of the actual amount of nitrogen at 

the land surface.

Source Factors

Nitrogen in ground water typically is from nonpoint 

sources. Some of the major nonpoint sources are fertilizers, 

animal manure, atmospheric deposition, and septic systems. 

The intensity of most of these nitrogen sources has been compiled for a 1,640-ft radius around each well from records of 

fertilizer sales, animal density, and measurements of nitrogen 

in precipitation (fig. 5). A general indicator of the intensity of 

nitrogen sources is land use; agricultural land use typically is 

the largest contributor of nitrogen. Both land use and nitrogen 

sources are continuous variables in this data set; therefore, 

the Spearman’s rank correlation was used to determine the 

relations between these variables and nitrate concentration in ground water from carbonate aquifers. The strongest 
54 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 18. Distribution of concentrations of nitrate in 12 carbonate aquifers or aquifer systems, 1993–2005.

0

5

10

15

20

25

NITRATE CONCENTRATION,

 IN MILLIGRAMS PER LITER AS N

Valley & Ridge

Silurian-Devonian/ Upper carbonate

 Piedmont

Ozark Plateaus

Ordovician

Castle-Hayne

Mississippian

Floridan

 Edwards-Trinity

Biscayne

Basin & Range

 Praire du Chien

30 Number of values

EXPLANATION 

75th percentile

Median

25th percentile

Minimum value

Maximum value

24 65 32 125 221 66 40 187 30 29 33 185

Maximum contaminant

level for nitrate 
Factors Affecting Anthropogenic Contaminants 55

correlation was between agricultural land use and nitrate 

concentration. Strong positive correlations were also noted 

between potential nitrogen sources (manure, fertilizer, septic 

systems, and atmospheric deposition) and nitrate concentration 

(table 14). A weak positive correlation was found between the 

population on private septic systems and nitrate concentration. 

Correlations within individual aquifers are highly dependent 

on the number of samples, which accounts for the small number of significant correlations for the aquifers with 30 or fewer 

samples.

When analyzing these data by study types, water from 

wells in the agricultural land-use studies and the agricultural 

flowpath study had the highest median concentrations of 

nitrate, and water from wells in the other study types, with less 

agricultural land use, had lower nitrate concentrations. The 

distribution of nitrogen by atmospheric deposition is relatively 

even, and the population on private septic systems is apparently a minor contributing factor in nitrate concentration; 

therefore, the factors that have the most variation are those 

related to agricultural land use. Although much of the nitrogen 

applied to the agricultural land is taken up by plants, the difference between application from all sources and crop uptake 

is apparently large enough to make agricultural land use a 

major factor affecting elevated concentrations of nitrate.

Fate and Transport Factors

The movement of nitrate in ground water from a source 

to the sampling point depends on numerous factors that are 

collectively termed fate and transport factors. Transport factors include the speed at which the water travels, the distance 

from the recharge area to the well, and whether or not there 

is a confining layer. Fate factors are microbial and geochemical processes that affect transformations to the constituent 

of concern during the movement of the water. Most of these 

factors cannot be measured directly; however, data collected at 

a sampling point can be used to infer some of these processes. 

Dissolved oxygen concentration, dissolved organic carbon 

concentration, soils characteristics, and well characteristics 

are indirect measures of these processes. Some wells had data 

from age-dating tracers that could be used to determine traveltime in the aquifer. Some of the variables that can be used as 

indicators of fate and transport factors include water-quality 

measurements, calculated mineral saturation indexes, hydrologic variables, well-construction data, and soils information. 

These variables have been compiled for the 1,640-ft radius 

around the well, and correlations between these variables and 

nitrate concentration are used to infer possible fate and transport mechanisms that facilitate or impede movement of nitrate.

Ground-Water Age

Nitrate concentrations and age-dating tracers were available for a subset of 486 of the wells sampled (not including 

samples with a mixed ground-water age). Although a small 

number of samples could be assigned a specific recharge date 

from CFCs or other techniques, most samples were categorized as having recharge dates that were prior to 1953 or 1953 

and later. Therefore, all samples were assigned a recharge 

date of pre-1953 or 1953 and after, in order to be comparable. 

The samples with age dates represent a subset of the entire 

data set. No age-dating data were available in the Basin and 

Range, Castle Hayne, Ordovician, or Piedmont aquifers. All 

samples with recharge dates prior to 1953 were from wells 

(no springs). Of these 74 wells, 34 were from areas designated 

as confined, 6 were from semiconfined or mixed confinement, and 34 were unconfined. Aquifers or aquifer systems 

in the subset of wells that had recharge dates prior to 1953 

include the Edwards-Trinity, Floridan, Ozark Plateaus, Prairie 

du Chien, and Silurian-Devonian/Upper carbonate. Samples 

with recharge dates of 1953 and after included 317 wells and 

95 springs. Of these, 40 were from confined aquifers, 9 were 

from semiconfined or mixed confinement, and 363 were 

from unconfined aquifers. Aquifers or aquifer systems in the 

subset of wells that had recharge dates after 1953 include the 

Biscayne, Edwards-Trinity, Floridan, Mississippian, Ozark 

Plateaus, Prairie du Chien, Silurian-Devonian/Upper carbonate, and Valley and Ridge. A Wilcoxon rank-sum analysis 

showed that the median concentration of nitrate in the older 

water (less than 0.06 mg/L) was significantly lower than the 

median concentration of nitrate in water that was recharged 

more recently (1.4 mg/L) (p-value less than 0.0001) (fig. 19). 

This result is possibly a combination of source factors—older 

water was recharged when application rates of fertilizer and 

manure were much lower—and fate and transport factors—the 

longer traveltimes allowed for processes such as denitrification to occur. No sample from a well with a recharge date 

prior to 1953 had a concentration of nitrate that exceeded the 

USEPA MCL of 10 mg/L.

Degree of Confinement

The presence of a confining layer is a key factor affecting nitrate transport to ground water. A determination of the 

degree of aquifer confinement—unconfined, semiconfined, 

mixed confinement (wells penetrating more than one aquifer 

type), or confined—was made for all but three of the wells 

and springs. A nonparametric Tukey’s test indicated that the 

median concentration of nitrate from wells in unconfined 

aquifers (1.4 mg/L) was higher than those in semiconfined/

mixed confined or confined aquifers (fig. 20) (p-value less 

than 0.0001). Both the confined and semiconfined/mixed 

confined categories had median concentrations below the 

detection limit of 0.06 mg/L. All samples that had concentrations of nitrate that exceeded the USEPA MCL of 10 mg/L 

were from wells in an unconfined aquifer, with the exception 

of one sample from a well in a confined aquifer. That sample 

was identified by the age-dating tracers as having a mixture of 

old and young water, which typically indicates a ‘short-circuit’ 

in the system allowing old water to be mixed with younger 

water. The comparison of confinement categories by aquifer 

also illustrates the importance of confinement. In most of the 

confined aquifers, nitrate concentrations are low. In cases 
56 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 14. Spearman’s rank correlations between nitrate concentration in ground water and variables representing nitrogen sources, in 12 carbonate aquifers or aquifer systems, 1993–2005. [Land use from U.S. Geological Survey (1999); Price and others (2007); Census data from U.S. Bureau of Census (1990, 1991, 1992); Nitrogen source data from Ruddy and others (2006); NS, cor- relation not significant–p-value greater than 0.05] Category Variable

All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Number of samples 137 30 65 32 125 236 66 40 187 30 30 33 197

Land use Percent agricultural land 

use

0.43 NS 0.29 NS NS 0.21 0.43 NS 0.43 NS NS NS 0.68

Percent forest land use -.13 NS NS NS -.39 NS -.46 NS -.25 NS NS NS -.67

Percent wetlands -.35 NS NS NS NS -.31 NS NS NS NS NS NS NS

Census data Population density, 1990 .06 NS NS NS .33 NS NS NS NS NS NS NS NS

Population on private septic 

systems

.19 NS .43 NS NS NS NS NS .24 NS NS NS NS

Potential nitrogen 

sources and land use

Nitrogen from atmospheric deposition, septic 

systems, fertilizer, and manure

.30 NS NS NS .29 .20 NS NS .49 NS NS NS .52
Factors Affecting Anthropogenic Contaminants 57

Figure 19. Distribution of concentrations of nitrate by ground water-age category in eight 

carbonate aquifers or aquifer systems, 1993–2005.

Recharge date

prior to 1953

Recharge date 

1953 or later

0

5

10

15

20

25

GROUND-WATER-AGE CATEGORY

74 412

NITRATE CONCENTRATION,

 IN MILLIGRAMS PER LITER AS N

74 Number of values

EXPLANATION 

75th percentile

Median

25th percentile

Minimum value

Maximum value

Recharge date prior to 1953: (74 wells )

34 Confined

6 Semiconfined or mixed confined

34 Unconfined

Edwards-Trinity, Floridan, Ozark Plateaus, Prairie du Chien,

 and Silurian-Devonian/Upper carbonate aquifers

Recharge date 1953 or later: (317 wells and 95 springs)

40 Confined

9 Semiconfined or mixed confined

363 Unconfined

Biscayne, Edwards-Trinity, Floridan, Mississippian,

 Ozark Plateaus, Prairie du Chien, Silurian-Devonian/Upper

 carbonate, and Valley and Ridge aquifers 

Maximum contaminant

level for nitrate 
58 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 20. Distribution of concentrations of nitrate by confinement category and aquifer in 12 carbonate aquifers or aquifer systems, 

1993–2005.

24 65 19 10 35 90 30 93 66 40 12 17 159 30 101 20 10 18 15 186 Confined Castle Hayne Confined Edwards-Trinity Unconfined Biscayne Confined Basin and Range Confined Floridan Unconfined Mississippian Unconfined Ordovician Confined Ozark Plateaus Unconfined Piedmont Confined Prairie du Chien Unconfined Valley and Ridge Confined Silurian-Devonian/ Upper carbonate Unconfined Castle Hayne Unconfined Edwards-Trinity Semiconfined Floridan Unconfined Floridan Mixed confined Ozark Plateaus Unconfined Ozark Plateaus Unconfined Prairie du Chien Unconfined Silurian-Devonian/ Upper carbonate

Unconfined Confined Semiconfined

or mixed confined

AQUIFER-CONFINEMENT CATEGORY

Maximum contaminant

level for nitrate 

768 92 157

A C B 30

25

20

15

10

5

0

30

25

20

15

10

5

0

Maximum contaminant

level for nitrate 

EXPLANATION

30 Number of values

75th percentile

Statistical group from 

nonparametric Tukey’s Test*

Median

25th percentile

Minimum value

Maximum value

A

*Mean rank concentration of groups with the 

same letter not significantly different based on 

nonparametric Tukey’s test

AQUIFER-CONFINEMENT CATEGORY

Confined

Semiconfined/Mixed confined

Unconfined

 IN MILLIGRAMS PER LITER AS N

NITRATE CONCENTRATION,

 IN MILLIGRAMS PER LITER AS N

NITRATE CONCENTRATION,
Factors Affecting Anthropogenic Contaminants 59

where an aquifer has both confined and unconfined areas, the 

unconfined area has higher nitrate concentrations in all except 

one of the comparisons (fig. 20).

Karst Features

Presence of karst features is a potential indicator of transport of contaminants to ground water. The categories from the 

karst map of Davies (1970) are generally divided by karstfeature size into ‘long’ (fissures, tubes, and caves over 1,000 ft 

long; 50 ft to over 250 ft vertical extent), ‘short’ (fissures, 

tubes, and caves generally less than 1,000 ft long; 50 ft or 

less vertical extent), and ‘absent.’ Categories are then subdivided on the basis of bedrock type, dip angle, and presence of 

noncarbonate rock overlying carbonate rock. A Kruskal-Wallis 

test was used to make comparisons of nitrate concentrations 

among main karst-feature categories (long, short, and caves 

absent) and showed no significant difference among these 

categories at a 95-percent confidence interval. Comparisons of 

karst-feature categories grouped by predominant land-use type 

also showed no significant differences with the exception of a 

subset in which the ‘urban karst features absent’ category had 

a statistically significant higher nitrate concentration than the 

urban areas with karst features. In some cases, wells from the 

current study plotted outside of the area mapped as carbonate 

on the Davies map. These wells were alternately treated as 

‘karst features absent’ and included in the analysis, and as ‘no 

data’ and thus excluded from the analysis. Neither method of 

analysis of those wells changed the findings.

This general lack of correlation between nitrate concentrations and the categories from the national karst map is most 

likely related to the scale of the national karst data set. Several 

hundred wells are in aquifers identified as carbonate but are 

not located within the area designated by the national karst 

map as carbonate, so some of the areas designated as ‘karst 

features absent’ may be incorrectly identified from the karst 

map. Also, the categories of ‘short’ and ‘long’ both could have 

karst features measuring in the hundreds of feet in length, so 

both could potentially have similar effects on water quality at 

a specific well.

Because of the potential importance of karst features, 

and the lack of explanatory power of the categories from the 

national karst map, an attempt was made to gather data on 

individual sinkholes and make comparisons between sinkhole 

density and water quality. Although these data are available 

for some states, the data are unavailable for much of the study 

area, thus negating the possibility of a comprehensive analysis 

of this issue for the entire data set.

Redox Status

A key factor in determining the fate of nitrate is the 

redox status of the water sampled. This is important because it 

affects the possibility or degree of denitrification. As previously described, redox status was determined as oxic, anoxic, 

or mixtures of two or more types of waters if water-quality 

measurements indicated a mix over a range of redox states. 

A nonparametric Tukey’s test indicated a significant relation 

between redox conditions and nitrate concentrations (fig. 21); 

oxic waters had the highest nitrate concentrations, followed by 

mixed-source waters, and anoxic waters had the lowest nitrate 

concentrations.

As noted in the section on geochemistry, redox status is 

closely related to ground-water age and degree of confinement 

(figs. 14 and 15). A confining layer or a long transport distance 

can affect ground-water age. Water that is in the aquifer for a 

long period of time has an increased likelihood of having the 

oxygen that was dissolved in the water depleted by microbial 

or chemical activity. Organic carbon is essential for the microbial processes that utilize the oxygen.

Dissolved oxygen concentration can be an indicator of 

microbial processes, flowpath length, or soil characteristics. 

Denitrifying bacteria are facultative and will only use nitrate 

as an oxygen source in the absence of free dissolved oxygen 

(Chapelle, 1993). Therefore, aquifers with concentrations of 

dissolved oxygen greater than 1.0 mg/L typically have sufficient oxygen available so that microbial denitrification does 

not remove large quantities of nitrate. A Spearman’s rank correlation indicated a strong positive statistical relation between 

nitrate concentration and dissolved oxygen concentration 

(table 15). This correlation was strong for the entire data set, 

but also within individual aquifers; 7 of the 12 aquifer groups 

had significant correlations and positive correlation coefficients that were 0.50 or greater. Dissolved oxygen, therefore, 

is an important factor determining the presence and concentration of nitrogen. The presence of dissolved oxygen can be an 

indicator of short flowpath length, but microbial consumption 

rates of oxygen are dependent on numerous factors and cannot be directly converted to ground-water traveltime. Karst 

conduits can also have turbulent flow that mixes atmospheric 

air with ground water after recharge, which can also be a 

cause of higher concentrations of dissolved oxygen. Both short 

flowpaths and conduit flow increase the likelihood of nitrate 

being present. Organic carbon is also necessary for the microbial processes that result in denitrification. Dissolved organic 

carbon concentration was inversely correlated with dissolved 

oxygen concentration and nitrate concentration for the entire 

data set, although this inverse correlation was not consistent 

within most of the aquifers (table 15). Aquifers that lack dissolved organic carbon and are well oxygenated are, therefore, 

more likely to transport nitrate longer distances from the 

source than aquifers with higher dissolved organic carbon and 

anaerobic conditions.

Saturation Indexes and Geochemistry

Saturation indexes for calcite and dolomite were compared to nitrate concentration in order to evaluate their utility 

as indicators of residence time or conduit flow systems. 

Calcite and dolomite S.I. can be related to several factors, 

including residence time in the aquifer and the purity of the 

mineral in the aquifer material. Results of the Spearman’s rank 

correlation showed significant inverse correlations between 
60 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 15. Spearma

n’s Rank correlations between nitrate concentration and fate and transport variables in 12 carbonate aquifers or aquifer systems, 1993–2005.

[NS, correlation not significant–p-value greater than 0.05]

Category Variable All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Number of samples 30 65 32 125 236 66 40 187 30 30 33 197

Water-quality 

characteristics

Dissolved oxygen 0.68 0.67 0.25 NS 0.50 0.71 0.55 0.56 0.46 0.43 0.65 0.52 0.40

pH NS .43 NS NS -.18 NS NS -.44 -.36 NS NS NS .18

Specific conductance NS NS NS NS -.34 -.34 NS NS NS .45 NS NS .56

Dissolved organic carbon -.33 NS -.28 NS NS -.63 NS NS .26 .45 NS NS .22

Geochemical 

indicators

Calcite saturation index NS NS NS NS -.19 NS NS -.36 -.26 NS -.45 -.44 .49

Dolomite saturation index -.06 NS NS NS -.55 -.22 NS -.52 -.42 NS -.44 -.57 .43

Calcium-magnesium molar ratio NS NS NS NS .53 .27 NS .50 .41 NS NS .40 .15

Well-specific data Water level .22 NS NS NS -.36 .28 .25 NS NS NS NS -.53 NS

Well depth NS -.64 NS -.35 NS NS NS NS NS NS NS -.43 -.20

Depth to top of open interval NS -.59 NS NS NS NS NS NS -.40 NS NS NS NS
Factors Affecting Anthropogenic Contaminants 61

dolomite S.I. and nitrate concentration in the Edwards-Trinity, 

Floridan, Ordovician, Ozark Plateaus, Prairie du Chien, and 

Silurian Devonian/Upper carbonate aquifers/aquifer systems. 

Significant inverse correlations were also noted between 

calcite S.I. and nitrate concentration for the Edwards-Trinity, 

Ordovician, Ozark Plateaus, Prairie du Chien, and Silurian 

Devonian/Upper carbonate aquifers/aquifer systems (table 15). 

The inverse correlations between calcite and dolomite S.I. and 

nitrate concentration may be because a higher S.I. is associated 

with water that has a longer residence time in the aquifers, 

which has already been shown to be related to lower nitrate 

concentrations. In the case of the Valley and Ridge aquifer, the 

correlation between both calcite and dolomite S.I. and nitrate 

concentration is positive. This is most likely because water 

from wells and springs in the Upper Tennessee River Basin 

study unit had low concentrations of nitrate and was undersaturated with respect to calcite and dolomite. In contrast, wells 

in the Lower Susquehanna and Potomac River Basin study 

units had some of the highest concentrations of nitrate and 

were closer to saturation with respect to calcite and dolomite, 

thus making this correlation positive in the Valley and Ridge. 

These differences in nitrate concentration are mainly attributable to the greater percentage of agricultural land use in the 

Lower Susquehanna and Potomac River Basin study units. In 

the overall data set, the lack of correlation between calcite S.I. 

and nitrate concentration, and the weak correlation between 

dolomite S.I. and nitrate concentration may be because land 

use has more of an effect on nitrate concentrations than the 

geochemical indicators of residence time, similar to the situation within the Valley and Ridge aquifer.

Calcium-magnesium ratios were positively correlated 

with nitrate concentration in the Edwards-Trinity, Floridan, 

Ordovician, Ozark Plateaus, Silurian Devonian/Upper carbonate, and Valley and Ridge aquifers/aquifer systems. This 

finding is in concordance with the findings of Scanlon (1990), 

who found higher nitrate concentrations in calcium type water 

than in calcium-magnesium type water. The strongest geochemical correlations with nitrate concentration were dolomite 

S.I. and calcium-magnesium ratios, which support the concept 

that residence time, and thus concentrations of nitrate, are 

related to the evolution of water from a calcium water type to 

a calcium-magnesium water type.

Well-Specific Information

Well-construction data such as water level, well depth, 

and depth to top of open interval also are used as indicators of 

transport distance. A shallow depth to water can mean a short 

transport distance, which could lead to higher concentrations 

of nitrate, but very shallow water depths can lead to waterlogged soils that have also been shown to inhibit movement of 

nitrate (Nolan and others, 2002); water level can have either a 

positive or inverse relation with nitrate concentration depending on which factor is dominant. Deep wells imply a greater 

depth to the water-bearing zone, which typically is used as an 

indicator that water has a longer traveltime between recharge 

and entering the well. Depth to top of open interval similarly 

Figure 21. Distribution of concentrations of nitrate related to the redox status in 12 carbonate aquifers or aquifer systems, 

1993–2005.

Maximum contaminant level for nitrate 

REDOX-STATUS CATEGORY

EXPLANATION 

OXIC MIXED SOURCE ANOXIC

663 65 294

A B C

30 Number of values

75th percentile

Statistical group from 

nonparametric Tukey’s Test*

Median

25th percentile

Minimum value

Maximum value

A

*Mean rank concentration of groups with the same letter 

not significantly different based on nonparametric Tukey’s test

Oxic = Samples with dissolved oxygen concentration 

 greater than or equal to 0.5, both iron concentration 

 less than 100 and manganese concentration less than 50

Mixed Source = Samples with dissolved oxygen concentration 

 greater than 0.5, and either iron concentration greater than 

 100 or manganese concentration greater than 50

Anoxic = Samples with dissolved oxygen concentration 

 less than 0.5

30

25

20

15

10

5

0

NITRATE CONCENTRATION,

 IN MILLIGRAMS PER LITER AS N
62 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 16. Comparison of nitrate mean rank concentrations by type of confinement and land-use grouping in 12 carbonate aquifers or 

aquifer systems, 1993–2005.

[Shading indicates aquifer-confinement category]

Aquifer-confinement 

 category

Predominant 

land-use 

grouping

Number of 

samples Mean rank

Statistical Group from 

nonparametric Tukey’s test 

(groups with the same letter are 

not significantly different)

Unconfined Agricultural 329 724 A

Unconfined Mixed land use 185 538 B

Confined Urban 31 471 B C

Unconfined Urban 131 436 B C D

Unconfined Undeveloped 123 430 B C D

Confined Mixed land use 35 383 B C D E

Confined Undeveloped 32 357 C D E F

Confined Agricultural 59 341 C D E F

Semiconfined or mixed confined Agricultural 22 324 C D E F

Semiconfined or mixed confined Mixed land use 32 293 D E F

Semiconfined or mixed confined Urban 27 230 E F

Semiconfined or mixed confined Undeveloped 28 180 F

indicates a depth to the shallowest water-bearing zone but 

is also an indicator of the thickness of the unconsolidated 

material above bedrock. In the entire data set, water level and 

nitrate concentration had a weak positive correlation. Water 

level was inversely correlated with nitrate concentration in the 

Edwards-Trinity aquifer system and Silurian-Devonian/Upper 

carbonate aquifer and positively correlated with nitrate concentration in the Floridan aquifer system and the Mississippian 

aquifer. Well depth was inversely correlated with nitrate 

concentration in the Basin and Range, Castle Hayne, SilurianDevonian/Upper carbonate, and Valley and Ridge aquifers 

individually (table 15). Depth to top of open interval was 

inversely correlated with nitrate concentration for the Basin 

and Range aquifer and the Ozark Plateaus aquifer system.

Interaction of Source, Fate, and Transport Factors

The analysis of transport factors has illustrated how 

ground-water age, degree of confinement, dissolved oxygen 

concentration, and well depth all affect nitrate concentrations. The analysis of source factors indicates a strong relation 

between nitrate concentration and agricultural land. It is not 

possible to tell from these analyses, however, whether these 

variables are actually independent. For example, all the wells 

in unconfined aquifers may be in areas that have a higher percentage of agricultural land than wells in confined aquifers, 

making the analysis of confinement a surrogate for land use. 

In order to assess the combined effect of transport and source 

factors, the data were analyzed by combinations of source and 

transport characteristics.

One combination of source and transport factors is an 

analysis of the combined effect of degree of confinement and 

land use. From the previous analysis, aquifers with confining layers and semiconfined aquifers or aquifers with mixed 

confinement would be less susceptible to elevated nitrate 

concentrations than unconfined aquifers. Agricultural land 

use, having been identified as a significant factor in determining nitrate concentration, is a source factor. Analysis of the 

combination of degree of confinement and land-use groups 

indicates that, for unconfined aquifers, nitrate concentrations 

vary by land-use category, with the highest concentrations 

in the agricultural areas and the lowest concentrations in the 

undeveloped areas (table 16). This pattern is not evident in 

confined aquifers. In fact, the wells in confined aquifers with 

agricultural land use around the well had lower nitrate concentrations than wells in confined aquifers with undeveloped land 

use around the well. This result is not unexpected in confined 

aquifers, because the recharge area for these wells may be far 

removed from the locations of the wells sampled. The semiconfined/mixed confined group had the lowest concentrations 

of nitrate overall. A nonparametric Tukey’s test showed that 

the category with the combination of agricultural land use and 

unconfined aquifer type has significantly higher concentrations of nitrate than all the other categories (p-value less than 

0.0001).

An analysis of nitrate concentrations in relation to the 

combination of redox status and land-use groupings shows 

a similar pattern with respect to the land-use groups. Within 

each of the redox-status categories of oxic, mixed-source 

waters, and anoxic waters, a pattern related to sources is evident; the highest nitrate concentrations are in agricultural areas 

and the lowest in undeveloped areas (table 17). The primary 

factor, however, appears to be the redox status; most of the 

oxic waters have the highest nitrate concentrations, and most 
Factors Affecting Anthropogenic Contaminants 63

of the anoxic waters have the lowest nitrate concentrations. 

The land-use/source factor appears to be a secondary grouping variable. To further evaluate this issue, the data also were 

analyzed using only those samples designated as having water 

recharged after 1953. Samples of old water could alter the 

analysis because they are designated with a land-use category 

that may not have been present at the time of recharge. In this 

analysis of younger water only, the effect of redox status is 

even more evident. All the highest ranks for nitrate concentrations are oxic waters, and all the lowest ranks for nitrate 

concentrations are anoxic waters (table 18). Even the samples 

from undeveloped areas in oxic waters had higher nitrate 

concentrations than water from agricultural areas in anoxic 

waters. This analysis only includes samples from 8 of the 12 

aquifers but illustrates that redox status can be a more important factor than land use in determining nitrate concentrations.

Another way to analyze the interaction between variables 

is to build regression models to determine which factors are 

the most important in determining nitrate concentration. A 

logistic regression model was built to determine the probability that nitrate would exceed a concentration of 4 mg/L. 

Explanatory factors that were included in the model were factors that had a statistically significant correlation with nitrate 

concentration (tables 14 and 15) and included soils characteristics and hydrologic variables (described and summarized on 

tables 7 and 8). Some of these variables are highly correlated 

with each other, and although they provide unique information 

in a correlation context, they do not provide useful information in a regression. Therefore, not every variable that had a 

significant correlation with nitrate concentration was included 

in the model. Variables that were significant in the model but 

had a sign that was the opposite of the result of the Spearman’s rank correlation result were removed from the model. 

Models that had a Hosmer-Lemeshow test p-value of less than 

0.05 were rejected, and the variable with the highest p-value in 

that model was removed to create subsequent models. Degree 

of confinement is a categorical variable but has an important 

effect on nitrate concentration; therefore, a numeric variable 

was created to represent the aquifer confinement. Confined 

aquifers were assigned a value of 1, semiconfined/mixed 

confined aquifers were assigned a value of 2, and unconfined 

aquifers were assigned a value of 3. This is not exactly in 

order of the nitrate concentrations in these areas but made the 

most hydrologic sense. Reversing the values assigned to confined aquifers with the semiconfined/mixed confined aquifers 

had little effect on the statistical results.

The results of the logistic regression model showed that 

the probability of nitrate concentration exceeding 4 mg/L was 

positively related to an increase in dissolved oxygen concentration and potential nitrogen input from all sources, and 

inversely related to percent soils in hydrologic group D (which 

indicates poorly drained soils), calcium-magnesium ratio 

(which indicates longer residence time), and percent forested 

land (table 19). These are variables that represent a combination of source factors and transport factors. The logistic regression model is sensitive to the selected threshold (4 mg/L) and 

to the input variables, but the significant variables were fairly 

consistent in the alternate models attempted. The regression 

model had a concordance of 89.7 percent. This indicates that 

when comparing the predicted probability values for sites that 

exceeded 4 mg/L to predicted probability for sites with concentrations less than 4 mg/L, the sites that exceeded 4 mg/L 

Table 17. Comparison of nitrate mean rank concentrations by redox-status category and land-use grouping in 12 carbonate aquifers 

or aquifer systems, 1993–2005.

[Shading indicates redox-status category]

Redox-status 

category

Predominant 

land-use 

grouping

Number of 

samples Mean rank

Statistical Group from 

nonparametric Tukey’s test 

(groups with the same letter are 

not significantly different)

Oxic Agricultural 298 763 A

Oxic Urban 86 630 A B

Oxic Mixed land use 159 598 B C

Mixed Source Agricultural 25 527 B C D

Oxic Undeveloped 120 461 C D E

Mixed Source Mixed land use 19 393 D E F

Mixed Source Urban 10 316 E F G

Anoxic Agricultural 85 248 F G

Anoxic Mixed land use 70 232 F G

Anoxic Urban 91 205 G

Anoxic Undeveloped 48 191 G

Mixed Source Undeveloped 11 184 G
64 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 19. Results of logistic regression model predicting probability of nitrate being detected at a threshold of 

greater than 4 milligrams per liter in 12 carbonate aquifers or aquifer systems, 1993–2005.

Parameter Parameter 

estimate Chi-square p-value Standardized estimate

Intercept -2.79 72.0 < 0.0001

Hydrologic group D soils -.08 20.1 < .0001 -1.04

Dissolved oxygen .35 98.1 < .0001 .66

Percent forested land -.04 33.4 < .0001 -.59

Nitrogen from atmospheric deposition, septic systems, 

fertilizer, and manure

.0002 25.8 < .0001 .30

Calcium-magnesium molar ratio -.024 4.7 .031 -.15

had a higher predicted probability 89.7 percent of the time. 

The r-square value (not the same as the r-square value for linear regression) was 0.30, and the maximum rescaled r-square 

value was 0.51. These values indicate the model is moderately good for explaining the factors affecting the probability 

of nitrate exceeding the threshold concentration of 4 mg/L. 

Model validation was not attempted, because this model was 

created for explanatory purposes and not predictive purposes.

Previous studies within each of the 12 aquifers provide 

additional insight on factors affecting nitrate concentrations in 

ground water. The factors described in these studies were generally categorized into issues related to sources (agricultural 

land use), susceptibility to contaminant infiltration (karst features), and fate and transport through the aquifer (denitrification, degree of confinement, and ground-water age). All these 

factors interact with each other in determining the vulnerability of the aquifer. For example, confined aquifers may have 

older water, which is more likely to undergo denitrification, 

and areas with karst features and agricultural land are more 

vulnerable to nitrate contamination than an area with only one 

of those characteristics.

Agricultural land use was mentioned as a key factor in 

several studies. In the Mississippian aquifer, higher concentrations of nitrate were associated with agricultural land use 

(Woodside and others, 2004). Intensity of agricultural land use 

was a factor affecting nitrate concentration in ground water 

in the Piedmont aquifer and the northern part of the Valley 

and Ridge aquifer (Lindsey and others, 1997). Ferrari and 

Ator (1995) found that the percentage of row-crop land use 

near a well was more likely to cause elevated concentrations 

of nitrate than pasture land in the Valley and Ridge. In the 

southern part of the Valley and Ridge aquifer, where nitrate 

concentrations were lower, the percentage of row-crop land 

use was only 4 percent (Johnson, 2002). The lower percentage of row-crop land use in the southern part of the Valley and 

Ridge aquifer compared to the northern part of that aquifer is a 

likely reason for the relatively lower concentrations of nitrate 

(Hampson and others, 2000).

For the Floridan aquifer system, areas with numerous 

karst features were at the greatest risk for elevated nitrate 

concentrations (Berndt and others, 1998). Karst features 

were noted as a potential route of contamination in the 

Mississippian aquifer (Woodside and others, 2004). For the 

Table 18. Comparison of nitrate mean rank concentrations by redox-status category and land-use grouping 

for water recharged in 1953 or later, in 8 of the 12 carbonate aquifers or aquifer systems, 1993–2005.

[Shading indicates redox-status category]

Redox-status 

category

Predominant 

land-use 

grouping

Number of 

samples Mean rank

Statistical Group from 

nonparametric Tukey’s test 

(groups with the same letter are not 

significantly different)

Oxic Agricultural 131 262 A

Oxic Urban 42 217 A

Oxic Mixed land use 77 207 A B

Oxic Undeveloped 58 146 B C

Anoxic Agricultural 10 121 C D

Anoxic Mixed land use 12 108 C D

Anoxic Urban 53 60 D
Factors Affecting Anthropogenic Contaminants 65

Ozark Plateaus aquifer system, karst features were found to be 

an important factor affecting ground-water quality (Petersen 

and others, 1998). Karst features were noted as potential 

causes of the high concentration of nitrate in ground water in 

the Piedmont aquifer and the northern part of the Valley and 

Ridge aquifer (Lindsey and others, 1997).

The characteristics of aquifers that would either enhance 

or prevent denitrification were noted in several studies. The 

low concentrations of nitrate in the Biscayne aquifer and the 

Castle Hayne aquifer are consistent with the fact that these 

aquifers are overlain by organic-rich soils, which can increase 

microbiological activity and enhance denitrification (Spruill 

and others, 1998). In the Mississippian aquifer, denitrification 

was associated with samples with low dissolved oxygen concentrations, which was attributed to the attenuated movement 

of water through the overlying fine-grained soils (Woodside 

and others, 2004). In the Ordovician aquifer, denitrification 

was also noted as a factor affecting nitrate concentrations 

(Woodside and others, 2004). The exchange of air in the 

unsaturated zone, leading to high dissolved oxygen concentrations and thus little opportunity for denitrification, was also 

noted as a factor related to elevated nitrate concentrations in 

the Piedmont aquifer and the northern part of the Valley and 

Ridge aquifer (Lindsey and others, 1997).

Presence of a confining layer and the location of a confined aquifer with respect to the recharge area were found to 

be important in several aquifers. The Edwards-Trinity aquifer 

system is highly transmissive, but it is confined where the 

urban and agricultural land uses overlie the aquifer, with more 

undeveloped land uses located in the recharge area (Bush and 

others, 2000). For the Ozark Plateaus aquifer system, the presence of a confining layer was related to lower nitrate concentrations (Petersen and others, 1998). In the Silurian-Devonian/

Upper carbonate aquifers, nitrate concentrations were much 

lower in areas protected by a bedrock confining unit or more 

than 100 ft of Quaternary-age deposits (Savoca and others, 1999). Water in the Basin and Range aquifer sampled in 

discharge areas tends to be very old (thousands of years) and 

located a long distance away from the recharge areas, making 

the presence of anthropogenic contaminants unlikely. Water 

sampled near an outcrop was more likely to have contaminants 

detected (Schaefer and others, 2005).

The comparison of the factors affecting nitrate concentrations, as determined by studies within individual aquifers, to 

the factors affecting nitrate concentrations in the 12 aquifers 

illustrates a similar pattern of factors. In some cases, the 

degree of confinement is a major factor within an aquifer; in 

others, karst features, organic carbon concentrations, dissolved 

oxygen concentrations, flowpath length, or land use may be 

the factor that is the most important for that area. Most of the 

aquifers probably are affected by the same factors to a certain 

degree; however, the factors that are the most important vary 

among the 12 aquifers.

The concentrations of nitrate in the 12 carbonate aquifers were related to several factors. Karst features may be a 

primary factor, but data were not available to allow quantitative analysis of the presence of karst features for this study. 

Redox status appears to be a very important factor in determining nitrate concentration. Other physical characteristics 

controlling nitrate concentration that could be quantified are 

land use, composition of soils, and degree of confinement. 

Ground-water age is important because of the link to sources 

and denitrification, but age is closely related to other factors 

such as confinement. Geochemical indicators such as calcium 

S.I., dolomite S.I., and calcium-magnesium ratio are important 

in some aquifers and are surrogates for residence time.

Pesticides

Samples were collected from wells or springs for pesticide analysis at 1,027 sites for 47 pesticides or pesticide 

degradates (table 20). Each site is represented by data from 

one sampling event. For sites with multiple samples, the most 

recent sample was used for this study. The primary method of 

pesticide analysis for these samples was gas chromatography/

mass spectrometry with selected-ion monitoring (Zaugg and 

others, 1995), which provides low-level analyses. The results 

of pesticide sampling for the 12 carbonate aquifers are analyzed with respect to the distribution of pesticides, a screening-level assessment of potential human-health concerns, and 

factors affecting concentrations and detections of pesticides.

Detection Levels and Data-Analysis Methods

The pesticide data include a high proportion of nondetects, frequently resulting in data sets that are highly censored 

from a data-analysis standpoint. In addition, analytical sensitivity and LRLs vary within and among pesticides, resulting 

in multiple censoring levels, and the data include estimated 

values that are reliable detections but less certain quantitative determinations. In order to understand techniques used 

to analyze the pesticide data, it is necessary to understand 

how nondetects and estimated values were treated for various 

statistical methods.

The frequency of detecting a pesticide above a given 

concentration is directly affected by the threshold concentration level used to determine whether or not a concentration 

is considered a detection, with fewer detections for higher concentration thresholds. Three types of concentration thresholds 

are referred to and used in this report:

1. Laboratory Reporting Levels (LRLs): A LRL is the “less 

than” concentration reported when a pesticide is determined to not be present (for example: < 0.005 μg/L).

2. Common Assessment Levels: Common assessment 

levels are used to allow a common comparison among 

samples for the same pesticide if the LRL changed over 

time or to allow comparisons among several pesticides 

that had different LRLs.
66 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 20. Detection frequency for 47 pesticides in 12 carbonate aquifers or aquifer systems, 1993–2005.—Continued

[Pesticide types: D, degradate; H, herbicide; I, insecticide; N/A, Not applicable, MCL, Maximum Contaminant Level (U.S. Environmental Protection Agency, 

2006); HBSL, Health-Based Screening Level (Toccalino and others, 2007)]

Pesticide name Pesticide 

type

Number of 

analyses

Number of 

detections1

Percent 

detections

Benchmark 

level 

(μg/L) 

[upper HBSL] 2

Benchmark 

type

Benchmark 

exceedance

Deethylatrazine D 1,021 383 37.5 NONE N/A N/A

Atrazine H 1,020 379 37.2 3 MCL 0

Prometon H 1,027 187 18.2 400 HBSL 0

Simazine H 1,027 178 17.3 4 MCL 0

Metolachlor H 1,027 153 14.9 700 HBSL 0

Tebuthiuron H 1,017 99 9.7 1000 HBSL 0

p,p ́-DDE D, I 992 30 3.0 .1 [10] HBSL 0

Alachlor H 1,018 28 2.8 2 MCL 0

Dieldrin I 1,019 21 2.1 .002 [.2] HBSL 20

Diazinon I 1,024 12 1.2 1 HBSL 1

Cyanazine H 990 11 1.1 1 HBSL 0

2,6-Diethylaniline D 1,024 7 .7 NONE N/A N/A

EPTC H 989 6 .6 200 HBSL 0

Carbaryl I 1,025 6 .6 40 [4,000] HBSL 0

Metribuzin H 1,024 6 .6 90 HBSL 0

Chlorpyrifos I 1,019 5 .5 2 HBSL 0

Trifluralin H 1,023 5 .5 20 HBSL 0

Carbofuran I 989 4 .4 40 MCL 0

Napropamide H 988 4 .4 800 HBSL 0

Acetochlor H 853 3 .3 1 [100] HBSL 0

Butylate H 989 3 .3 400 HBSL 0

Lindane I 990 3 .3 .2 MCL 0

Pebulate H 990 3 .3 50 HBSL 0

Benfluralin H 1,027 3 .3 4 HBSL 0

Propanil H 988 2 .2 6 HBSL 0

Terbacil H 989 2 .2 90 HBSL 0

Dacthal (DCPA) H 1,027 2 .2 70 HBSL 0

Pendimethalin H 1,025 2 .2 70 HBSL 0

Pronamide H 1,025 2 .2 1 [100] HBSL 0

Linuron H 991 1 .1 5 HBSL 0

Propargite I 991 1 .1 1 [100] HBSL 0

alpha-HCH I 992 0 .0 .006 [.6] HBSL 0

Azinphos-methyl I 1,026 0 .0 10 HBSL 0

cis-Permethrin I 1,027 0 .0 4 [400]3 HBSL 0

Disulfoton I 992 0 .0 .9 HBSL 0
Factors Affecting Anthropogenic Contaminants 67

Table 20. Detection frequency for 47 pesticides in 12 carbonate aquifers or aquifer systems, 1993–2005.—Continued

[Pesticide types: D, degradate; H, herbicide; I, insecticide; N/A, Not applicable, MCL, Maximum Contaminant Level (U.S. Environmental Protection Agency, 

2006); HBSL, Health-Based Screening Level (Toccalino and others, 2007)]

Pesticide name Pesticide 

type

Number of 

analyses

Number of 

detections1

Percent 

detections

Benchmark 

level 

(μg/L) 

[upper HBSL] 2

Benchmark 

type

Benchmark 

exceedance

Ethalfluralin H 992 0 0.0 30 HBSL 0

Ethoprop I 992 0 .0 1 [100] HBSL 0

Fonofos I 1,027 0 .0 10 HBSL 0

Malathion I 1,027 0 .0 50 HBSL 0

Molinate H 992 0 .0 .7 HBSL 0

Parathion I 992 0 .0 .02 HBSL 0

Parathion-methyl I 1,027 0 .0 1 HBSL 0

Phorate I 1,027 0 .0 4 HBSL 0

Propachlor H 992 0 .0 1 [100] HBSL 0

Terbufos I 1,027 0 .0 .4 HBSL 0

Thiobencarb H 992 0 .0 70 HBSL 0

Triallate H 992 0 .0 20 HBSL 0

1

Assessment level of ‘all detections’ used for this analysis.

2

Some compounds have a high and a low value for HBSLs. For those compounds that have both a high and a low value, the high value is given in brackets.

3

HBSLs were not developed for cis-Permethrin; concentrations of cis-Permethrin can be compared to the HBSL range of 4-400 μg/L for Permethrin 

(Toccalino and others, 2007)

3. Human-Health Benchmarks: USEPA MCLs (U.S. 

Environmental Protection Agency, 2006) and HBSLs. 

HBSLs are benchmark concentrations of contaminants in 

water that may be of potential concern for human health, 

if exceeded. HBSLs are non-enforceable benchmarks 

that were developed by the USGS in collaboration with 

USEPA and others using USEPA methodologies for establishing drinking-water guidelines and the most current, 

USEPA peer-reviewed, publicly available human-health 

toxicity information (Toccalino and others, 2004, 2007).

For some data analyses, all detections, including estimated or ‘E’ values (reliable detections with less certain 

quantitative determinations), are used even if they are below 

LRLs for unqualified quantitation. When comparing pesticides 

to each other, a common assessment level of 0.01 μg/L is used 

so that the detection rates are comparable. A very small number of samples had LRLs that were higher than the maximum 

common LRL (table 21). Nondetections with LRLs greater 

than the maximum common LRL are likely indications of 

analytical problems such as matrix interference (Gilliom and 

others, 2006), and therefore were not included in the statistical 

analysis.

The variation in frequency of pesticide detections in 

relation to the reporting level or assessment level used for the 

analysis is shown in figure 22. Some comparisons can be misleading if care is not taken; for example, the relative change 

from the ‘all detections’ assessment level to the 0.01 μg/L 

assessment level is greatest for prometon and least for atrazine 

and deethylatrazine. Thus, statistical analyses using the ‘all 

detections’ assessment level could have a different outcome 

than if the 0.01 μg/L assessment level were used.

Statistical methods used to evaluate pesticide concentration as a continuous variable used the rank of concentration rather than the reported value, because the data are not 

normally distributed and generally do not conform to a single 

distribution (Helsel and Hirsch, 2002). When ranking pesticides for a statistical test, all nondetects were assigned a rank 

lower than the lowest ‘E-coded’ value. All quantified detections, including those coded as estimated, were assigned ranks 

on the basis of the reported values. This method has been used 

in other national assessments of pesticides and has a detailed 

explanation in Gilliom and others (2006).

Occurrence and Distribution

Initial analysis of pesticide occurrence focused on 

the presence of the 47 pesticides analyzed. Analysis of ‘all 

detections,’ regardless of data LRLs, indicates that 1 or more 

pesticides were detected in 509 of the 1,027 samples (50 percent). Detections of multiple pesticides in the same sample 

were common; 401 samples had 2 or more pesticides detected 
68 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

PESTICIDE

PERCENT OF DETECTIONS

ASSESSMENT LEVEL

40

35

30

25

20

15

10

5

0

Atrazine Deethylatrazine Simazine Metolachlor Prometon

All detections

0.01 μg/L

Figure 22. Percent of detections for the herbicides atrazine, deethylatrazine (a degradate 

of atrazine), simazine, metolachlor, and prometon by assessment level in 12 carbonate 

aquifers or aquifer systems sampled during 1993–2005.

Table 21. Method detection limits and common reporting levels 

for frequently detected pesticides in 12 carbonate aquifers or 

aquifer systems, 1993–2005.

Pesticide

Maximum 

long-term 

method 

detection 

limit1

Maximum 

common 

laboratory 

reporting limit 

(CRLMAX)1

Number of 

nondetects 

with reporting 

limit 

exceeding 

CRLMAX

Atrazine 0.004 0.007 7

Deethylatrazine .003 .006 6

Metolachlor .006 .013 0

Prometon .007 .018 0

Simazine .006 .011 0

1

Gilliom and others, 2006.
Factors Affecting Anthropogenic Contaminants 69

(39 percent), and 45 samples had 6 or more pesticides detected 

(4 percent).

The data collected for pesticide analysis cover a time 

period in which there were a number of major changes in 

pesticide use, including the introduction and increased use of 

acetochlor and declining use of cyanazine and alachlor (Gilliom and others, 2006). The samples for this study, however, 

were not collected in a manner that allows interpretation of 

relations between temporal usage trends and pesticide occurrence. Therefore, interpretation of the pesticide data does not 

take into account the potential effect of changes in pesticide 

use during the sampling period.

The frequency of pesticide detections varied widely 

among the 12 aquifers (figs. 23 and 24). The three aquifers 

with the most frequent detections were the Biscayne, Piedmont, and Valley and Ridge aquifers, which had at least 1 

of the 47 pesticides detected in more than 80 percent of the 

samples, and multiple detections per sample were common. 

In the Piedmont and Valley and Ridge aquifers, in particular, more than 10 percent of the samples had more than six 

pesticides detected. The three aquifers with the least frequent 

detections were the Basin and Range, Castle Hayne, and 

Silurian-Devonian/Upper carbonate aquifers, with one or 

more pesticides detected in less than 20 percent of samples. 

The other six aquifers sampled were intermediate between 

these high and low frequencies. As mentioned previously, the 

sampling within each aquifer was not balanced with respect 

to land use and type of well sampled, so the results within 

aquifers may not reflect the actual distribution of pesticide 

occurrence in each aquifer. This range of characteristics can, 

however, be used to interpret the factors affecting pesticides 

occurrence in carbonate aquifers.

Assessment of Potential Human-Health 

Significance

Potential human-health significance of pesticides 

in drinking water was evaluated by comparing measured 

concentrations to human-health benchmarks. MCLs were 

used as benchmarks for compounds regulated under the Safe 

Drinking Water Act, and HBSLs were used as benchmarks 

for unregulated compounds. As previously stated, not all the 

sample locations represent drinking-water supplies, but the 

majority of the sites are used for public or domestic supply; 

therefore, comparisons to human-health benchmarks determined for drinking water are presented as a way to put the 

sampling results in context. Of the 47 pesticides analyzed, 5 

have MCLs, 40 have HBSLs, and 2 have no human-health 

benchmarks available (table 20). For carcinogens, HBSLs 

are presented as an HBSL range (table 20), representing the 

contaminant concentration in drinking water that corresponds 

to an excess lifetime cancer risk of 1 chance in 1 million to 1 

chance in 10 thousand (Toccalino and others, 2007). For this 

analysis, in addition to comparing concentrations to humanhealth benchmarks (MCLs or HBSLs), benchmark quotients 

(BQ) were calculated to determine how close a concentration 

is to the benchmark. A BQ is calculated by dividing a concentration by its human-health benchmark, so a sample with 

a BQ of 1 has a concentration equal to its benchmark level. 

For unregulated carcinogens, BQ values were calculated using 

the low end of the HBSL range, which corresponds to a 1 in 

1 million cancer risk. When a BQ is greater than or equal to 

0.1, it is at a concentration that is at or above 10 percent of the 

human-health benchmark, and on this basis may warrant continued monitoring and evaluation. Regular monitoring of contaminants with a BQ greater than 0.1 would enable analysis of 

trends in their occurrence and provide an early indication of 

concentrations that approach MCLs or HBSLs (Toccalino and 

others, 2007). Thus, BQ values can be used as a planning tool 

so that potential issues can be identified as early as possible.

No sample had a pesticide concentration that was greater 

than a USEPA MCL; however, two pesticides had concentrations that were greater than HBSLs in one or more samples. 

Dieldrin concentrations were greater than the HBSL of 

0.002 μg/L in 20 samples, 9 of which were from either domestic or public supply wells. Dieldrin is an insecticide that has 

been banned in the United States since 1987 but had a detection frequency of 2 percent (table 20). Dieldrin concentrations were greater than the HBSL in one or more wells in the 

Biscayne, Floridan, Mississippian, Ozark Plateaus, Piedmont, 

and Valley and Ridge aquifer/aquifer system (fig. 25). Most 

of these samples were from wells in urban or mixed land-use 

areas. The highest concentration of dieldrin was 0.81 μg/L in 

a sample from a site in an agricultural area in the Mississippian aquifer. That site was not used as a source of drinking 

water. The frequent exceedances of the HBSLs for dieldrin is 

because of its environmental persistence and the relatively low 

HBSL (0.002 μg/L), reflecting its relatively high toxicity. A 

diazinon concentration of 19 μg/L was greater than the HBSL 

(1 μg/L) in a single sample from a domestic supply well in 

the Prairie du Chien aquifer (fig. 26). Two other samples, both 

from domestic supply wells, had BQ values between 0.1 and 

1, one in the Floridan aquifer system and the other in the Prairie du Chien aquifer (fig. 26). Diazinon, also an insecticide, 

was detected in about 1 percent of the samples. None of the 

other pesticides were detected at concentrations greater than 

either a MCL or HBSL.

The most frequently detected pesticides were the herbicides atrazine, prometon, simazine, metolachlor, and the atrazine degradate deethylatrazine (table 20). Although humanhealth benchmarks for these pesticides were not exceeded 

in any samples, BQs for atrazine were greater than 0.1 for 

35 samples in agricultural areas (Mississippian, Ordovician, 

Ozark Plateaus, Piedmont, Prairie du Chien, and Valley and 

Ridge aquifer/aquifer system), 4 samples in mixed land-use 

areas (Ozark Plateaus, Piedmont, Prairie du Chien, and Valley 

and Ridge aquifer/aquifer system), and 2 samples in urban 

areas (Biscayne and Valley and Ridge aquifers) (fig. 27). 

Of the 41 samples with BQ greater than 0.1 for atrazine, 31 

were from domestic supply wells. Only one sample, from a 

domestic well in an agricultural area of the Valley and Ridge 
70 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 23. Frequencies of individual and multi-compound detections in relation to A) aquifer or aquifer system, B) degree of 

confinement, and C) predominant land use around well. Results are based on analysis of 47 pesticide compounds in 12 carbonate 

aquifers or aquifer systems during 1993–2005 (assessment level, all detections).

1 or more pesticides

2 or more pesticides

4 or more pesticides

6 or more pesticides

1 or more pesticides

2 or more pesticides

4 or more pesticides

6 or more pesticides

20

40

60

80

100

Confined Semiconfined

or mixed confined Unconfined

0

20

40

60

80

100

Agricultural Mixed Undeveloped Urban

PERCENT OF SAMPLES

PERCENT OF SAMPLES

B C

AQUIFER-CONFINEMENT CATEGORY PREDOMINANT LAND USE AROUND WELL

0

0

10

20

30

40

50

60

70

80

90

100

1 or more pesticides

2 or more pesticides

4 or more pesticides

6 or more pesticides

PERCENT OF SAMPLES

A

Basin and Range

Biscayne

Castle-Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Praire du Chien

Silurian-Devonian/ Upper carbonate

Valley and Ridge
Factors Affecting Anthropogenic Contaminants

71

50°

40°30°

120° 110° 100° 90° 80° 70°

0 500 MILES 2500 500 KILOMETERS 250

CARBONATE BEDROCK AQUIFER OR AQUIFER SYSTEM

SUBCROP AREA OF AQUIFER OR AQUIFER SYSTEM

NUMBER OF PESTICIDES DETECTED OUT OF 47 COMPOUNDS ANALYZED

0 1

EXPLANATION

2–5 6–10

Figure 24. Sample locations and number of pesticides detected out of 47 pesticides analyzed in 12 carbonate aquifers or aquifer systems (assessment level, all detections).
72 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 25. Concentrations of dieldrin and human-health benchmarks in various land-use categories in 12 carbonate aquifers or 

aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds (U.S. Environmental 

Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated compounds (Toccalino and others, 

2004).

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

0.001 0.01 0.1 1 10 100

DIELDRIN CONCENTRATION, 

IN MICROGRAMS PER LITER

0.01 0.1 1

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

10 100

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Dieldrin concentration

Dieldrin HBSL [0.002 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY
Factors Affecting Anthropogenic Contaminants 73

0.001 0.01 0.1 1 10 100

DIAZINON CONCENTRATION, 

IN MICROGRAMS PER LITER

0.001 0.01 0.1 1 10 100

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Diazinon concentration

Diazinon HBSL [1 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY

Figure 26. Concentrations of diazinon and human-health benchmarks in various land-use categories in 12 carbonate aquifers or 

aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds (U.S. Environmental 

Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated compounds (Toccalino and others, 

2004).
74 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

0.001 0.01 0.1 1 10 100

ATRAZINE CONCENTRATION, 

IN MICROGRAMS PER LITER

0.00001 0.0001 0.001 0.01 0.1 1

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Atrazine concentration

Atrazine MCL [3 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY

Figure 27. Concentrations of atrazine and human-health benchmarks in various land-use categories in 12 carbonate aquifers or 

aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds (U.S. Environmental 

Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated compounds (Toccalino and others, 

2004).
Factors Affecting Anthropogenic Contaminants 75

aquifer, had a BQ greater than 0.1 for simazine (fig. 28), and 

no samples for prometon or metolachlor had BQs greater than 

0.1 (figs. 29 and 30). It is important to note that deethylatrazine, the pesticide compound with the largest number of 

detections, is one of the three compounds that does not have a 

MCL or an HBSL and therefore is not analyzed in this context. 

The geographic distribution of detections and BQs for the 

herbicides atrazine, simazine, metolachlor, and prometon are 

illustrated in figure 31. The remaining 40 pesticides had detection frequencies of less than 10 percent (table 20). Of those 

40 pesticides, concentrations were typically low relative to 

benchmarks. Only two samples each of lindane and cyanazine 

and one sample each for alachlor, acetochlor, and propargite 

had a BQ greater than 0.1.

Overall, results indicate that concentrations of the 

pesticides studied rarely exceeded available water-quality 

benchmarks for human health. Of the 44 compounds for which 

benchmarks are presently available, only 2 insecticides had 

concentrations greater than their benchmarks; the majority of 

the exceedances were for dieldrin (2 percent of samples). In 

addition, only atrazine had BQ values that were frequently 

greater than 0.1, indicating a potential priority for monitoring 

in agricultural areas in the Valley and Ridge aquifer. These 

findings closely match the findings of the national study of 

pesticides by Gilliom and others (2006) that indicated dieldrin 

accounted for the vast majority of cases where ground-water 

samples exceeded human-health benchmarks, and atrazine was 

the most frequently detected pesticide.

Factors Affecting Occurrence of Frequently 

Detected Pesticides

The most frequently detected pesticides were the herbicides atrazine, simazine, prometon, metolachlor, and the 

atrazine degradate deethylatrazine (table 20). The statistical 

analysis of the pesticide data focuses primarily on these five 

frequently detected compounds, because statistical techniques 

used in this analysis are not effective if detection frequency 

is less than 10 percent. Occurrence of the five frequently 

detected pesticides in carbonate aquifers was evaluated with 

respect to a number of different factors, including aquifer, 

type of study, fate and transport factors, and source factors. A 

combination of issues such as pesticide use, amount and type 

of agricultural land use, degree of confinement, ground-water 

age, and other issues causes the patterns of pesticide occurrence. Some of these factors are related to the sources of the 

contaminants, and others are indicators of transport of the 

pesticide from the land surface to the sampling point. The following is an analysis of the factors related to the occurrence of 

pesticides in carbonate aquifers.

Aquifers and Study Types

Detections of these five frequently occurring pesticide 

compounds varied widely among the carbonate aquifers. 

Frequencies of detection at a common assessment level of 

0.01 μg/L were greatest in the Biscayne, Mississippian, Piedmont, and Valley and Ridge aquifers, which had one or more 

of the five compounds detected in greater than 30 percent of 

the wells sampled, and least in the Basin and Range, Castle 

Hayne, Floridan, and Ozark Plateaus aquifer/aquifer systems, 

in which no pesticide had a detection frequency of greater than 

10 percent (fig. 32).

 Detection frequencies also varied with the type of 

study. In particular, agricultural and urban land-use studies 

had a higher rate of detection of the five frequently occurring 

pesticides than the other types of studies (fig. 33), which is 

generally expected because most of the sampled wells in these 

studies were relatively shallow and surrounded by agricultural or urban land uses [results of a nonparametric Tukey’s 

test confirmed that the agricultural and urban land-use study 

wells were shallower than wells in the major-aquifer studies 

or the source-water-quality assessments (p-value less than 

0.0001)]. Consistent with their shallower depth, available 

age-dating data show that the wells in agricultural and urban 

land-use studies almost all had water recharged in 1953 or 

later, whereas the major-aquifer studies tended to have more 

water classified as recharged before 1953. The percentage 

of samples with one or more pesticides detected and the percentage of samples with multiple detections per sample were 

greater in the unconfined aquifers than in the semiconfined/

mixed confined or confined aquifers. The only samples 

with more than six pesticides detected were from sites in 

unconfined aquifers. The percentage of samples with one or 

more pesticides detected and the percentage of samples with 

multiple detections were greater in the agricultural and urban 

areas than in areas with mixed land use or undeveloped land 

use (fig. 23.)

Source Factors

Analysis of detections of the five frequently occurring 

pesticides indicates a pattern in which pesticides are more 

frequently detected in agricultural and urban areas, where 

pesticides are most heavily used (figs. 23 and 33). Most of the 

studies with atrazine detected in greater than 50 percent of the 

samples were agricultural land-use studies. Some studies did 

not follow this pattern. Studies in urban areas in the EdwardsTrinity aquifer system and the Biscayne aquifer also had high 

detection frequencies that may be related to source areas not 

matching the land use near the sampling site (the study in the 

Edwards-Trinity aquifer system was a spring study) or the 

urban use of atrazine. A few studies had high percentages of 

agricultural land use but low detection frequencies of atrazine. 

The studies in the Silurian-Devonian/Upper carbonate aquifer 

and the Ozark Plateaus aquifer system had relatively low 

frequencies of pesticide detections; however, the exceptions to 

the pattern in those areas are likely because of transport factors 

such as the presence of a confining unit.

The Spearman’s rank correlation test was used to evaluate relations between concentrations of the five frequently 

detected pesticides and various potential source factors 
76 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

0.001 0.01 0.1 1 10 100

SIMAZINE CONCENTRATION, 

IN MICROGRAMS PER LITER

0.00001 0.0001 0.001 0.01 0.1 1

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Simazine concentration

Simazine MCL [4 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY

Figure 28. Concentrations of simazine and human-health benchmarks in various land-use categories in 12 carbonate aquifers or 

aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds (U.S. Environmental 

Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated compounds (Toccalino and others, 

2004).
Factors Affecting Anthropogenic Contaminants 77

Figure 29. Concentrations of metolachlor and human-health benchmarks in various land use categories in 12 carbonate aquifers or 

aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds (U.S. Environmental 

Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated compounds (Toccalino and others, 

2004).

0.001 0.01 0.1 1 10 100

METOLACHLOR CONCENTRATION, 

IN MICROGRAMS PER LITER

0.000001 0.00001 0.0001 0.001 0.01 0.1 1

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Metolachlor concentration

Metolachlor HBSL [700 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY
78 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

0.001 0.01 0.1 1 10 100 0.001 0.01 0.1 1

PROMETON CONCENTRATION, 

IN MICROGRAMS PER LITER

0.00001 0.0001

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Prairie du Chien

Piedmont

Valley and Ridge

Ordovician

Silurian-Devonian/

Upper carbonate

BENCHMARK QUOTIENT VALUE

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Prometon concentration

Prometon HBSL [400 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

LAND-USE CATEGORY

Figure 30. Concentrations of prometon and human-health benchmarks in various land use categories in 12 carbonate 

aquifers or aquifer systems (assessment level, all detections). MCL is Maximum Contaminant Levels for regulated compounds 

(U.S. Environmental Protection Agency, 2006); HBSL is Health-Based Screening Level concentrations for unregulated 

compounds (Toccalino and others, 2004).
Factors Affecting Anthropogenic Contaminants

79

50°

40°30°

120° 110° 100° 90° 80° 70°

0 500 MILES 2500 500 KILOMETERS 250

Benchmark Quotient (BQ) = Measured concentration/Maxium contaminant level OR Health-based screening level. BQ does not apply to deethylatrazine.

CARBONATE BEDROCK AQUIFER OR AQUIFER SYSTEM

SUBCROP AREA OF AQUIFER OR AQUIFER SYSTEM

EXPLANATION

SAMPLING RESULT FOR ATRAZINE, DEETHYLATRAZINE, SIMAZINE, METOLACHLOR, AND PROMETON

None of the five compounds detectedAt least one compound detected, BQ less than 0.1At least one compound detected, BQ greater than or equal to 0.1

Figure 31. Sample locations and comparison to human-health benchmarks for atrazine, deethylatrazine, simazine, metolachlor, and prometon, in 12 carbonate aquifers or aquifer systems (assessment level, all detections).
80 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Figure 32. Frequency of detections of the five frequently occurring pesticides by aquifer, in 12 carbonate aquifers or 

aquifer systems, 1993–2005 (common assessment level, 0.01 μg/L).

0

10

20

30

40

50

60

70

80

90

ATRAZINE

DEETHYLATRAZINE

SIMAZINE

PROMETON

METOLACHLOR

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Silurian-Devonian/ Upper carbonate

Piedmont

Valley and Ridge

Ordovician

Prairie du Chien

PERCENT DETECTIONS GREATER THAN 0.01 MICROGRAMS PER LITER

Urban

Land-Use

Study

0

10

20

30

40

50

60

70

Agricultural

Land-Use

Study

Major-Aquifer

Study

Source-WaterQuality

Assessment

STUDY TYPE

PERCENT DETECTIONS GREATER THAN 

0.01 MICROGRAMS PER LITER

Spring

Study

ATRAZINE

DEETHYLATRAZINE

SIMAZINE

PROMETON

METOLACHLOR

Figure 33. Frequency of detections of the five frequently occurring pesticides by 

type of National Water-Quality Assessment study in 12 carbonate aquifers or aquifer 

systems, 1993–2005 (common assessment level, 0.01 μg/L).
Factors Affecting Anthropogenic Contaminants 81

(table 22). This test analyzes for a monotonic relation between 

the pesticide concentration and the explanatory variable. These 

results can be difficult to interpret because of the large amount 

of interaction among the explanatory variables, but this step is 

conducted to help determine potential variables to use in the 

later multivariate analysis.

Pesticide occurrence was compared to land use and the 

application rate of pesticides. Data on the percentage of land 

covers during the mid-1990s from the National Land Cover 

Data (NLCD) have been compiled for a 1,640-ft (500 m) 

radius around each well in the NAWQA data set (U.S. Geological Survey, 1999; Price and others, 2007). Data on the use 

of pesticides in 1997 in this radius around each well in the 

NAWQA data set were estimated by Nakagaki and Wolock 

(2005), by extrapolating county-level pesticide-use data to 

agricultural land in each county. Population data from the 

1990 U.S. Census (U.S. Bureau of Census, 1990, 1991) and 

2000 U.S. Census (GeoLytics, 2001; U.S. Bureau of Census, 

2001) were used to estimate the population density. The use 

of these data for the 1,640-ft radius does not imply that the 

defined circle is the recharge area of a well, but it serves as 

an indication of activities at the land surface in the immediate 

vicinity of the well.

The largest rank correlation coefficients were between 

individual pesticides and the agricultural application rate of 

that pesticide. The pesticide-use estimates were available for 

both 1992 and 1997. Pesticide-use estimates were tested during statistical analysis, including using 1992-use estimates for 

all samples, 1997-use estimates for all samples, and a combination of 1992-use estimates for samples collected in the early 

part of the study and 1997-use estimates for those samples collected later in the study. The differences in the results of these 

tests were minor, but the 1997-use estimates provided the best 

correlations with pesticide occurrence and were used for the 

statistical analysis. Atrazine, deethylatrazine, simazine, and 

metolachlor were significantly correlated with the estimated 

agricultural application rate of the active ingredient within a 

1,640-ft radius of the well (table 22). Estimates of prometon 

use were not available.

All five of the pesticide compounds had statistically 

significant positive correlations with agricultural land use 

(table 22). Prometon, a general-use herbicide not registered for 

agricultural uses, had the weakest correlation with agricultural 

land use (table 22). The five compounds also were inversely 

correlated to the percentage of forested land use. In addition, 

all five pesticides, particularly atrazine, deethylatrazine, and 

prometon were positively correlated to population density 

(table 22). Prometon is an herbicide used for highway and utility right-of-ways and around structures and, as noted above, 

is not labeled for use on crop land. The positive correlation 

between prometon and both urban and agricultural land use is 

likely to be a reflection of the use of prometon in both urban 

and rural settings as a general-use herbicide. The relation 

between atrazine and population density is likely because of 

its use for right-of-ways, landscaping, and turf-grass management.

When correlations between source factors and pesticides 

were determined within each aquifer, the pattern of correlations for most source factors was similar to the pattern 

seen in the overall data set. For atrazine and deethylatrazine, 

the Edwards-Trinity, Ozark Plateaus, and Valley and Ridge 

aquifers/aquifer systems had significant correlations between 

sources and pesticides (table 22). For metolachlor, the correlations between sources and pesticides were the strongest 

for samples from the Valley and Ridge aquifer. The EdwardsTrinity, Ozark Plateaus, and the Valley and Ridge had significant correlations between pesticide source factors and prometon concentration. For simazine, the correlations were most 

significant for the Valley and Ridge aquifer. One of the few 

cases where the correlations indicated different results was for 

the Valley and Ridge aquifer, in which urban land use had an 

inverse correlation with atrazine and deethylatrazine concentration. This was the opposite of the correlations found for the 

rest of the data set. In the Valley and Ridge aquifer, atrazine 

was detected in nearly every sample; however, concentrations 

were lower in the urban areas than in the agricultural areas, 

which is why this correlation is reversed from the findings in 

the other areas. In general, though, the pattern of correlations 

between pesticides and sources was similar in individual aquifers to the pattern determined for the entire data set.

The correlations (or lack thereof) for the source factors 

are affected by several issues. Because of lower numbers of 

samples and detections when analyzing for correlations by 

individual aquifer, fewer correlations were statistically significant. The correlations are constrained by the type of study; 

significant correlations were found between pesticide use and 

pesticide concentration in land-use studies (shallow wells) but 

not in major-aquifer studies or source-water-quality assessments (deeper wells). Also, the significant correlations were 

in aquifers with high percentages of agricultural land use. For 

aquifers where a pesticide was detected in less than 10 percent 

of the samples, the Spearman’s rank correlation was not 

calculated because the results could be misleading when based 

on such a small number of observations. The Basin and Range 

and Castle Hayne aquifers did not have sufficient numbers of 

detections of any pesticides for the Spearman’s rank correlation test to be run. In general, the Biscayne and Piedmont 

aquifers had few significant correlations between source 

factors and pesticides. Lindsey and others (2006) reported 

similar results in the Piedmont aquifer. The degree of confinement has an effect on whether or not potential source data are 

correlated to pesticide occurrence. For wells in unconfined 

aquifers, which comprise most of the data, the correlations 

were similar in significance and magnitude to the correlations 

from the entire data set. Correlations between source factors 

and pesticide occurrence were weak or non-existent for wells 

in confined aquifers, reflecting their greater isolation from 

surface sources. The number of samples, type of sampling network, amount of agricultural land use, and degree of confinement all affect the outcome of the Spearman’s rank correlation 

tests. For the most part, there is much less variation within an 

aquifer for an explanatory variable than the amount of variation among aquifers.
82 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 22. Spearman’s rank correlations between potential source factors and pesticides in 12 carbonate aquifers or aquifer systems, 1993–2005. [Pesticide-use data from Nakagaki and Wolock (2005); land use from U.S. Geological Survey (1999) and Price and others (2007); census data from U.S. Bureau of Census (1990, 1991, 1992); Spearman’s rho only shown for correlations with p-values less than 0.05; NA, not applicable because of a detection rate less than 10 percent; NS, correlation not significant–p-value greater than 0.05] Category Variable All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Missississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/

Upper carbonate

Valley and Ridge

Number of samples 1,027 24 65 32 122 223 66 40 177 30 30 33 185

Atrazine

Pesticide Use Atrazine application rate 0.36 NA NS NA NS NS 0.30 NS NS 0.44 NS NS 0.68

Land Cover Row crop, Hay and Pasture .28 NA NS NA NS NS NS NS NS NS .47 NS .58

Forest -.31 NA NS NA NS NS -.30 NS -.18 -.40 NS NS -.60

Urban NS NA NS NA .37 NS NS NS .25 NS NS NS -.27

Census 1990 population density .33 NA NS NA .59 NS -.25 NS .25 NS NS NS NS

Deethylatrazine

Pesticide Use Atrazine application rate .38 NA NS NA NS NS .28 NS NS .48 NS NS .71

Land Cover Row crop, Hay and Pasture .29 NA NS NA NS NS NS NS NS NS .43 NS .61

Forest -.31 NA -.31 NA NS NS NS NS -.18 NS NS NS -.63

Urban NS NA NS NA .40 NS NS NS .23 NS NS NS -.30

Census 1990 population density .32 NA NS NA .58 NS -.32 NS .24 NS NS NS NS

Simazine

Pesticide Use Simazine application rate .28 NA NS NA NS NA NA NA NA NS NA NA .43Land Cover Row crop, Hay and Pasture .23 NA NS NA NS NA NA NA NA NS NA NA .37

Forest -.25 NA -.33 NA NS NA NA NA NA NS NA NA -.55

Urban NS NA NS NA .25 NA NA NA NA NS NA NA NS

Census 1990 population density .24 NA NS NA .42 NA NA NA NA NS NA NA .21

Metolachlor

Pesticide Use Metolachlor application rate .35 NA .48 NA NA NA NS NA NA NS NA NS .30

 Land Cover Row crop, Hay and Pasture .24 NA NS NA NA NA NS NA NA NS NA NS .19

Forest -.21 NA NS NA NA NA NS NA NA NS NA NS -.47

Urban NS NA NS NA NA NA NS NA NA NS NA NS NS

Census 1990 population density .16 NA NS NA NA NA NS NA NA NS NA NS .31

Prometon

Land Cover Row crop, Hay and Pasture .12 NA NS NA NS NA NS NS NS NS NA NA NS

Forest -.23 NA NS NA -.18 NA -.27 NS NS NS NA NA -.40

Urban .15 NA NS NA .35 NA .33 NS .18 NS NA NA .22

Census 1990 population density .32 NA .26 NA .34 NA NS NS .27 NS NA NA .48
Factors Affecting Anthropogenic Contaminants 83

Table 23. Comparison of detection frequency of pesticides for water recharged before 1953 and in 1953 or later for 8 of the 12 

carbonate aquifers or aquifer systems, 1993–2005.

Pesticide

Recharge date group and numbers of detections1 Statistics from contingency tables

Water recharged before 

1953 detections 

(65 samples)

Water recharged in 1953 or 

later detections 

(410 samples)

Chi-square value from 

contingency table

p-value from 

Chi-square test

Atrazine 4 172 30.8 0.0001

Deethylatrazine 2 176 38.0 .0001

Simazine 2 69 8.3 .0039

Metolachlor 2 50 4.8 .029

Prometon 2 73 9.1 .003

1

Assessment level for this analysis is ‘all detections.’

Fate and Transport Factors

Transport factors can facilitate or prevent the movement 

of the pesticide from the source to the sampling point. These 

factors are not always directly measurable but include degree 

of confinement, characteristics of soils, hydrology, and well 

construction. Geochemistry and ground-water age are results 

of transport factors that can be measured, and ground-water 

age is also a fate factor. Fate factors represent conditions that 

enhance or impede degradation of a pesticide in the aquifer.

Ground-water age, which is the length of time between 

ground-water recharge and the time of sampling, can be 

thought of as both a transport factor (pesticide travels slowly 

through the aquifer and thus had not arrived at the sampling 

point) or a fate factor (pesticide moves so slowly through the 

aquifer that degradation occurred prior to sampling). Agedating tracers and pesticide analyses were available for a 

subset of 483 of the wells sampled, including wells in 8 of the 

12 carbonate aquifers. As previously discussed, many of the 

samples with age-dating tracers were categorized as recharged 

prior to 1953 (old, 65 samples) or 1953 and later (young, 410 

samples). Eight samples were designated as mixtures of young 

and old water. The mixed-age waters are not included in the 

statistical analysis because of the small number of samples 

in that category. Pesticides were more frequently detected in 

waters designated as young than in waters designated as old. 

Using a contingency table analysis, the difference between the 

rate of detection between old and young water was statistically 

significant for all of the five compounds evaluated—atrazine, deethylatrazine, simazine, metolachlor and prometon 

(table 23). The statistics indicate that ground-water age is an 

important factor indicating the likelihood that pesticides are 

present. This finding is not surprising, because these compounds were not in use when the old water was recharged. The 

age data were not adequate to allow comparisons among more 

discrete intervals of ground-water age.

Another factor related to transport is the presence or 

absence of a confining layer. A confining layer can be a 

physical barrier to movement of water and pesticides, at least 

greatly slowing movement. The water in confined aquifers is 

usually older than in unconfined aquifers. As previously discussed, the correlations between pesticide concentrations and 

sources were weak or non-existent for wells in confined aquifers, possibly because the recharge area is not close to the well 

itself or the confined water is too old to contain pesticides. 

Comparisons of detections of pesticides in confined, semiconfined/mixed confined, and unconfined aquifers indicated a 

statistically significant higher frequency of pesticide detection 

for unconfined aquifers (table 24).

Soil properties also can influence the transport and fate 

of pesticides because water and pesticides move from land 

surface to ground water during recharge. The soils characteristics summarized for the 1,640-ft radius around the well were 

compared to pesticide occurrence, but correlations commonly 

were contradictory. One of these contradictions is that all the 

pesticides had a statistically significant inverse correlation to 

the percentage of sand, and a positive correlation to percentage 

of silt and percentage of clay. In the case of carbonate aquifers, it may be an indication that infiltration through the soils 

is not necessarily the route for pesticide transport. Issues such 

as macropore flow and, more importantly, karst features that 

allow water to bypass the clay soils are likely to be the reason 

for the unexpected correlation between clay and pesticides. 

Bouwer (1990) and Graham and others (1992) have both noted 

the importance of preferential flowpaths through fractures, 

wormholes, and root holes in clay soils. Soil organic matter 

can affect fate and transport of pesticides because pesticides 

tend to bind to the organic matter, which reduces pesticide 

transport to ground water, and organic matter can also affect 

the degradation of pesticides; however, the correlations 

between pesticide occurrence and soil organic matter for the 

overall data set were weak or not existent. It is also important 

to note that soils are highly correlated with other factors such 

as land use, thus making conclusions on the basis of a Spearman’s rank correlation between soils and pesticides, although 

statistically sound, a less than definitive answer. Thus, the 

analysis of soils will be further explored in the multivariate 

analysis.
84 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Dissolved oxygen concentrations in ground water can be 

an indicator of processes that influence either the fate or the 

transport of pesticides. One of the most important processes 

associated with pesticide fate is microbial metabolism, which 

can lead to the oxidation of organic matter and some pesticides 

along with the simultaneous consumption of dissolved oxygen, 

when the latter is present at detectable concentrations (aerobic conditions). Because several of the chemical pathways 

by which atrazine is transformed by microorganisms involve 

oxidation (dealkylation to form deethylatrazine, deisopropyl 

atrazine and, through the further dealkylation of either of these 

products, deethyl deisopropyl atrazine), high concentrations 

of dissolved oxygen might be expected to be correlated with 

lower concentrations of atrazine.

Concentrations of dissolved oxygen are also related, however, to flowpath length, connectivity to the atmosphere, and 

subsurface residence time and thus to the transport of atrazine 

and other surface-derived contaminants. In solution-weathered 

carbonate aquifers that are dominated by short flowpaths 

through subsurface conduits, the water in the aquifer tends to 

have high concentrations of dissolved oxygen, presumably 

because of rapid transport rates. Additionally, some of these 

subsurface flow channels can be partially filled with air, leading to the physical mixing of the air and water in the conduits, 

and thus a further elevation of concentrations of dissolved 

oxygen above those contributed by the atmosphere prior to 

recharge. Thus, for a given depth below the water table, high 

concentrations of dissolved oxygen imply more rapid transport 

through the aquifer than do lower concentrations.

In aquifers with pesticide sources at the land surface, 

the concentrations of atrazine (or any other pesticide that is 

oxidized by microorganisms in situ) might therefore be either 

directly or inversely correlated with concentrations of dissolved oxygen, depending on whether transport or transformation (respectively) exerts the greater control. Indeed, both 

patterns of correlation between atrazine and oxygen concentrations have been observed during previous studies (Barbash 

and Resek, 1996). In the present investigation, the concentrations of each of the most frequently detected pesticides were 

positively correlated with dissolved oxygen concentrations 

(table 25). For atrazine and deethylatrazine, this pattern was 

also observed within some of the individual aquifers. These 

results suggest that in the highly oxygenated aquifers examined for this study, transport may exert a greater control 

over the concentrations of these pesticides than microbial 

transformation, even for those compounds such as atrazine, 

deethylatrazine, simazine (Kaufman and Kearney, 1970) and 

metolachlor (Seybold and Mersie, 1999) that undergo microbial oxidation.

Dissolved organic carbon has a strong inverse correlation 

with pesticide concentration in the Biscayne, Floridan, and 

Prairie du Chien aquifers. In the Edwards-Trinity, Ordovician, 

Piedmont, and Valley and Ridge aquifers/aquifer systems, the 

correlation between dissolved organic carbon and pesticides 

was typically positive, which is counter to what would be 

expected. In the Ordovician, Piedmont, and Valley and Ridge 

aquifers, agricultural land use is positively correlated with 

soil organic carbon, so this may be the cause of this finding. 

In general, the aquifers with the positive correlation between 

pesticides and dissolved organic carbon had very low concentrations of dissolved organic carbon and very small variability 

in the concentrations of dissolved organic carbon.

Comparisons of geochemical indicators to pesticides 

showed correlations between calcium-magnesium ratios, 

calcite S.I., and dolomite S.I. with pesticides were weak or 

non-existent when using all data (table 25). For calcite S.I. and 

dolomite S.I., the result is affected by the correlations within 

the Valley and Ridge, which were opposite from the correlations in the other aquifers. Correlations with pesticides within 

individual aquifers are affected by the numbers of pesticide 

detections. The calcium-magnesium ratio was correlated 

with atrazine and deethylatrazine in the Edwards-Trinity, 

Floridan, Silurian-Devonian/Upper carbonate, and Valley and 

Ridge aquifers/aquifer systems. Inverse correlations between 

dolomite S.I. and atrazine and deethylatrazine were detected 

in the Edwards-Trinity, Floridan, Ozark Plateaus, Prairie du 

Chien, and Silurian-Devonian/Upper carbonate aquifers/

aquifer systems. These correlations are concordant with the 

Table 24. Comparison of detection frequency of pesticides for ground-water sites by aquifer-confinement category in 12 carbonate 

aquifers or aquifer systems, 1993–2005.

Pesticide

Aquifer-confinement category and numbers of detections1 Statistics from contingency tables

Confined 

(146 samples)

Semiconfined or 

mixed confined 

(110 samples)

Unconfined 

(768 samples)2

Chi-square 

value

p-value from 

Chi-square test

Atrazine 21 5 353 110. 0.0001

Deethylatrazine 30 5 348 90.4 .0001

Simazine 4 6 167 43.1 .0001

Metolachlor 5 1 148 43.4 .0001

Prometon 8 8 171 30.5 .0001 1

Assessment level for this analysis is ‘all detections.’

2

Only 761 samples for unconfined category for atrazine and 762 samples for unconfined category for deethylatrazine.
Factors Affecting Anthropogenic Contaminants

85

Table 25. Spearman’s rank correlations between site-specific factors and pesticides in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued[Spearman’s rho only shown for correlations with p-values less than 0.05; NA, not applicable ; NS, correlation not significant–p-value greater than 0.05]

Constituent All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Missississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Number of samples 1,027 24 65 32 122 223 66 40 177 30 30 33 185

Atrazine

Dissolved oxygen 0.31 NA NS NA 0.31 0.42 NS NS NS NS 0.84 0.43 0.31

Dissolved organic carbon NS NA -.37 NA .29 -.37 NS 0.33 NS 0.41 NS NS .26Calcium-magnesium molar ratio NS NA NS NA .63 .40 NS .56 NS NS NS .51 .21

Calcite saturation index NS NA NS NA NS NS NS NS -0.21 NS -.69 NS .55

Dolomite saturation index NS NA NS NA -.58 -.23 NS NS -.25 NS -.62 -.56 .45

Casing length -.10 NA NS NA -.27 NS NS NS NS NS NS NS NS

Well depth -.19 NA NS NA -.35 NS -0.27 NS NS NS NS NS -.21

Water level NS NA NS NA NS NS NS NS NS NS NS NS NS

Deethylatrazine

Dissolved oxygen .34 NA NS NA .43 .38 NS NS .21 NS .84 .43 .34

Dissolved organic carbon NS NA -.55 NA .28 -.39 NS NS .24 NS -.41 NS .25Calcium-magnesium molar ratio NS NA NS NA .68 .37 NS .63 NS NS NS .52 .19

Calcite saturation index .07 NA NS NA -.17 NS NS NS -.25 NS -.70 NS .55

Dolomite saturation index NS NA NS NA -.66 -.19 NS NS -.27 NS -.62 -.56 .47

Casing length NS NA NS NA NS -.19 NS NS NS NS NS NS .18

Well depth -.14 NA NS NA -.24 NS NS NS NS NS NS NS -.17

Water level .08 NA NS NA NS NS NS NS NS .45 NS NS NS
86 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 Table 25. Spearman’s rank correlations between site-specific factors and pesticides in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued [Spearman’s rho only shown for correlations with p-values less than 0.05; NA, not applicable ; NS, correlation not significant–p-value greater than 0.05] Constituent All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Missississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Simazine

Dissolved oxygen 0.27 NA NS NA 0.24 NA NA NA NA NS NA NA 0.17

Dissolved organic carbon NS NA -0.40 NA .28 NA NA NA NA NS NA NA .34

Calcium-magnesium molar ratio NS NA NS NA .52 NA NA NA NA NS NA NA .28

Calcite saturation index .16 NA NS NA NS NA NA NA NA NS NA NA .46

Dolomite saturation index .12 NA NS NA -.50 NA NA NA NA NS NA NA .34

Casing length NS NA NS NA -.22 NA NA NA NA NS NA NA NS

Well depth -.07 NA NS NA -.33 NA NA NA NA NS NA NA -.30

Water level .10 NA NS NA NS NA NA NA NA NS NA NA -.20

Metolachlor

Dissolved oxygen .2 NA NS NA NA NA 0.22 NA NA NS NA NS .15

Dissolved organic carbon -.07 NA -.41 NA NA NA NS NA NA 0.39 NA NS .3

Calcium-magnesium molar ratio NS NA NS NA NA NA NS NA NA NS NA 0.32 .30

Calcite saturation index .15 NA NS NA NA NA NS NA NA NS NA -.44 .43

Dolomite saturation index .09 NA NS NA NA NA NS NA NA NS NA -.49 .30

Casing length NS NA NS NA NA NA NS NA NA NS NA NS NS

Well depth -.11 NA NS NA NA NA NS NA NA NS NA NS -.27

Water level NS NA NS NA NA NA NS NA NA NS NA NS -.17
Factors Affecting Anthropogenic Contaminants

87

Table 25. Spearman’s rank correlations between site-specific factors and pesticides in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued[Spearman’s rho only shown for correlations with p-values less than 0.05; NA, not applicable ; NS, correlation not significant–p-value greater than 0.05]

Constituent All data

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Missississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie du Chien

Silurian-Devonian/ 

Upper carbonate

Valley and Ridge

Prometon

Dissolved oxygen 0.18 NA NS NA NS NA NS NS NS NS NA NA NS

Dissolved organic carbon NS NA -0.26 NA 0.22 NA NS 0.34 NS 0.37 NA NA 0.34

Calcium-magnesium molar ratio NS NA NS NA .24 NA 0.25 NS NS NS NA NA .31

Calcite saturation index .09 NA NS NA NS NA NS NS NS NS NA NA .36

Dolomite saturation index NS NA NS NA -.23 NA NS NS NS NS NA NA .20

Casing length NS NA .41 NA NS NA NS NS NS NS NA NA NS

Well depth NS NA .43 NA NS NA NS NS NS NS NA NA -.21

Water level NS NA NS NA -.27 NA NS NS NS NS NA NA -.17
88 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

concepts that calcium-magnesium ratios and dolomite S.I. are 

indicators of residence time, as previously discussed. In the 

Valley and Ridge aquifer the correlation between both calcite 

S.I. and dolomite S.I. with atrazine, deethylatrazine, simazine, 

metolachlor, and prometon were all positive. This opposite 

correlation in the Valley and Ridge aquifer was evident when 

analyzing nitrate also, and is likely due to the greater amount 

of agricultural land use in the part of the Valley and Ridge 

where the water is closer to saturation with respect to calcite 

and dolomite.

Water levels and well-construction data such as well 

depth and depth to the top of the open interval are also used as 

indicators of vertical transport distance. A shallow water level 

would indicate a short distance between the land surface and 

the water table in an unconfined aquifer. Well depth and depth 

to top of open interval both determine the depth at which 

water can enter the well. Larger depth to top of open interval 

indicates that the water has to travel deeper into the aquifer 

in order to be drawn into the well. The total depth of the well 

may indicate that the water-bearing zones are deep, but that 

may not be true if the open interval between the bottom of the 

casing and the bottom of the well is large.

The depth to the top of the open interval was inversely 

correlated with atrazine for the entire data set and within the 

Edwards-Trinity aquifer system (table 25). This indicates a 

tendency for wells with shallow casings to have higher concentrations of atrazine. That correlation was not present for 

deethylatrazine, simazine, metolachlor, or prometon.

Well depth was inversely correlated with atrazine, 

deethylatrazine, simazine, and metolachlor for the overall data 

set as well as several individual aquifers, indicating lower 

concentrations of pesticides in deeper wells. Well depth had 

a positive correlation with prometon in the Biscayne aquifer, 

but this aquifer has very shallow well depths. Correlations 

between water levels and pesticide concentrations were weak 

or nonexistent. The exception was in the Valley and Ridge 

aquifers, where inverse correlations were found between water 

level and metolachlor and prometon.

Interaction of Source, Fate, and Transport Factors

The occurrence of pesticides in ground water is ultimately determined by a combination of source, fate, and transport factors. The analysis of all three factors is an important 

step in identifying variables affecting pesticide occurrence, but 

analyzing the interaction among them is needed to provide the 

best understanding of pesticides in ground water. Multivariate 

analysis is essential because of the multiple factors involved 

simultaneously and because many of the factors are correlated 

among themselves.

One way to analyze the combination of source and transport factors is to group the categories that were previously 

identified as important factors on an individual basis. Two 

variables strongly associated with pesticide detections were 

land use and degree of confinement, representing one important source variable and one important transport variable. 

Analysis of the detection frequency of pesticides using degree 

of confinement and land-use categories indicates a consistent 

pattern (figs. 34-36). The detection frequency for all five 

pesticides was greater in unconfined aquifers than in confined 

aquifers for all land-use groupings. Using the ‘all detections’ 

assessment level, the frequency of detection for agricultural 

and urban land-use groupings is greater than the mixed land 

use and undeveloped settings for all unconfined aquifers and 

most confined aquifers. The only categories in which there 

were no detections were in confined or semiconfined/mixed 

confined aquifers. This example indicates that, although both 

land use and degree of confinement are important factors 

affecting the occurrence of pesticides independently, the combined effect of both of these factors provides an even more 

powerful explanation of pesticide occurrence in carbonate 

aquifers. The samples from wells in the unconfined aquifers 

with agricultural, urban, or mixed land use make up 71 percent 

of the samples, yet they account for 87 percent of the detections for atrazine, 85 percent for deethylatrazine, 92 percent 

for simazine, 90 percent for metolachlor, and 90 percent for 

prometon.

Effects of the combinations of factors affecting pesticide 

occurrence are further illustrated by comparing the Piedmont 

and Silurian Devonian/Upper carbonate aquifers, two of the 

aquifers with high percentages of agricultural land use and 

the highest use of atrazine and metolachlor (fig. 6). Although 

the study in the Silurian-Devonian/Upper carbonate aquifer 

was not designed as a land-use study, the percentage of land 

use around the sampling sites (fig. 3) was similar to that of 

the agricultural land-use study in the Piedmont aquifer. The 

depths to water, well depths, and depth to top of open interval 

for wells in the Silurian-Devonian/Upper carbonate aquifer 

were slightly larger than for wells in the study in the Piedmont 

aquifer (table 5). These aquifers both had pesticide application rates that were appreciably higher than in any of the other 

aquifers (fig. 6), yet the occurrence of these pesticides was 

quite different from each other. Atrazine and deethylatrazine 

were detected at a concentration greater than 0.01 μg/L in 

about 80 percent of the samples in the Piedmont aquifer, but 

only 12 percent in the Silurian Devonian/Upper carbonate 

aquifer (fig. 32). Metolachlor was detected in about 20 percent 

of the samples in the Piedmont aquifer and about 3 percent of 

the samples in the Silurian Devonian/Upper carbonate aquifer. 

The differences in detection frequency, despite similar high 

application rates, indicate the influence of factors that affect 

transport. Many of the samples in the Silurian Devonian/

Upper carbonate aquifer were classified as having a recharge 

date prior to 1953. Using the 10 samples in this area that were 

considered young ground water, the detection frequency was 

50 percent for atrazine and deethylatrazine and 30 percent for 

metolachlor, much closer to the frequency in the Piedmont. 

The degree of aquifer confinement had a similar influence. All 

the wells in the Piedmont sampled unconfined ground water, 

and all the detections of atrazine, deethylatrazine, and metolachlor were in the unconfined part of the Silurian Devonian/

Upper carbonate aquifer. Concentrations of dissolved organic 
Factors Affecting Anthropogenic Contaminants 89

Agricultural Urban Mixed Undeveloped

LAND-USE CATEGORY

ATRAZINE

DEETHYLATRAZINE

PERCENT OF DETECTIONS PERCENT OF DETECTIONS

Agricultural: greater than 50 percent agricultural land use 

 and less than 5 percent urban land use 

Urban: greater than 25 percent urban land use and less 

 than 25 percent agricultural land 

Undeveloped: less than 25 percent agricultural and 

 less than 5 percent urban 

Mixed land use: all other combinations

LAND USE IN 1,640-FOOT RADIUS AROUND WELL

Unconfined

Confined

CONFINEMENT CATEGORY

Semiconfined or mixed confined

70

60

50

40

30

20

10

0

70

60

50

40

30

20

10

0

Figure 34. Percent detections of atrazine and deethylatrazine by land use and 

confinement category in 12 carbonate aquifers or aquifer systems, 1993–2005 

(assessment level, all detections).
90 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Agricultural Urban Mixed Undeveloped

LAND-USE CATEGORY

SIMAZINE

METOLACHLOR

PERCENT OF DETECTIONS PERCENT OF DETECTIONS

70

60

50

40

30

20

10

0

70

60

50

40

30

20

10

0

Unconfined

Confined

CONFINEMENT CATEGORY

Semiconfined or mixed confined

Agricultural: greater than 50 percent agricultural land use 

 and less than 5 percent urban land use 

Urban: greater than 25 percent urban land use and less 

 than 25 percent agricultural land 

Undeveloped: less than 25 percent agricultural and 

 less than 5 percent urban 

Mixed land use: all other combinations

LAND USE IN 1,640-FOOT RADIUS AROUND WELL

Figure 35. Percent detections of metolachlor and simazine by land use and 

confinement category in 12 carbonate aquifers or aquifer systems, 1993–2005 

(assessment level, all detections).
Factors Affecting Anthropogenic Contaminants 91

Unconfined

Confined

CONFINEMENT CATEGORY

Semiconfined or mixed confined

Agricultural Urban Mixed Undeveloped

LAND-USE CATEGORY

PROMETON

PERCENT OF DETECTIONS

70

60

50

40

30

20

10

0

Agricultural: greater than 50 percent agricultural land use 

 and less than 5 percent urban land use 

Urban: greater than 25 percent urban land use and less 

 than 25 percent agricultural land 

Undeveloped: less than 25 percent agricultural and 

 less than 5 percent urban 

LAND USE IN 1,640-FOOT RADIUS AROUND WELL

Mixed land use: all other combinations

Figure 36. Percent detections of prometon by land use and confinement 

category in 12 carbonate aquifers or aquifer systems, 1993–2005 (assessment 

level, all detections).
92 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

carbon were also higher in the Silurian Devonian/Upper 

carbonate aquifer than in the Piedmont aquifer (fig. 16), which 

can affect the fate of pesticides. This more detailed comparison of two specific areas shows that transport factors sometimes must be combined with source factors to sufficiently 

explain the occurrence of atrazine or metolachlor. The aquifer 

characteristics that allow the pesticides to persist and move 

into the aquifer also must be present.

Logistic regression analysis is another way to determine 

the most significant factors affecting pesticide occurrence. 

Logistic regression analyzes the significance of multiple 

explanatory variables in determining whether the response 

variable exceeds a certain threshold, keeping only those 

variables that are statistically significant in the equation. The 

relative importance of the significant variables in the model 

is determined by the standardized estimate, which normalizes 

each variable so that the magnitude is relative to a common reference point. In the case of pesticides, the regression 

identifies those variables that are significant in determining 

the probability that a pesticide is likely to be detected above a 

selected threshold. Variables that were previously identified as 

having a significant individual correlation with the pesticide 

were used as the basis for the regression. Some variables were 

not included because missing data for one variable eliminates 

the entire case from the regression. The determination as to 

whether elimination of the variable or losing the missing cases 

was more important was done on a case-by-case basis. Well 

depth and depth to top of open interval were eliminated from 

the regression because of this. In some cases, explanatory 

variables were highly correlated with each other, such as soils 

and land use. In those cases, the variable that was considered 

more likely to be the determining variable was kept in the 

model. Percent agricultural land was too closely correlated 

with atrazine application rate to keep both variables in the 

model. The variable for degree of confinement was coded as 

a numeric group variable, with a value of 1 corresponding to 

confined aquifers, 2 corresponding to semiconfined/mixed 

confined, and 3 corresponding to unconfined aquifers; the 

same approach as was used for the logistic regression analysis 

for nitrate.

A logistic regression model was created to analyze the 

probability of atrazine exceeding 0.01 μg/L or greater. The 

predictor variables significant in this model were, in order 

of importance, atrazine application rate on agricultural land, 

degree of confinement, concentration of dissolved oxygen, percent urban land, population density, and recharge 

(table 26). All these factors had a positive relation with atrazine exceeding 0.01 μg/L. An alternate model using percent 

agricultural land instead of atrazine application rate was similar to but slightly weaker than the model selected. The model 

had a concordance of 87, an r-squared value of 0.30, and a 

maximum rescaled r-squared value of 0.45. The final model 

variables were checked for multicollinearity using the variance 

inflation factor (VIF), and the VIF for all variables was less 

than 2.5, indicating multicollinearity was not a major issue. 

This model was one of several that could be used to analyze 

atrazine occurrence. Model results differ somewhat depending 

on the threshold used for detection and the variables used as 

input for the model; however, most results were very similar 

to the results in table 26. Because logistic regression analyzes 

these variables simultaneously, the standardized estimate can 

be used as an indication of the importance of the variables 

relative to each other. Three of the four highest standardized 

estimates are related to either land use or degree of confinement. The variables of recharge and population density are 

statistically significant but less important in predicting atrazine 

occurrence.

The logistic regression model for deethylatrazine indicated the same general pattern of explanatory variables as the 

model for its parent pesticide, atrazine, with the exception that 

population density was not significant in this model (table 27). 

Similar to the results for atrazine, the model indicates that 

unconfined aquifers with high atrazine application rates on 

agricultural land and (or) a high percent of urban land use 

are likely to have deethylatrazine concentrations that exceed 

0.01 μg/L. The model had a concordance of 87.8, an r-squared 

Table 26. Results of logistic regression model predicting probability of atrazine being detected at a threshold of greater than 

0.01 micrograms per liter in 12 carbonate aquifers or aquifer systems, 1993–2005.

[<, less than]

Parameter Parameter 

estimate Chi-square p-value Standardized estimate

Intercept -6.6 92.3 < 0.0001

Atrazine application rate .11 96.9 < .0001 0.81

Aquifer-confinement category 1.06 19.9 < .0001 .42

Dissolved oxygen .17 27.2 < .0001 .31

Urban land use .01 10.8 .001 .24

Population density 1990 .001 9.0 .003 .19

Recharge .08 8.8 .003 .16
Factors Affecting Anthropogenic Contaminants 93

Table 27. Results of logistic regression model predicting probability of deethylatrazine being detected at a threshold of greater than 

0.01 micrograms per liter in 12 carbonate aquifers or aquifer systems, 1993–2005.

[<, less than]

Parameter Parameter 

estimate Chi-square p-value Standardized estimate

Intercept -5.9 62.9 < 0.0001

Atrazine application rate .10 63.6 < .0001 0.69

Urban land use .03 57.7 < .0001 .44

Aquifer-confinement category 1.07 18.9 < .0001 .43

Hydrologic group D soils -.03 15.7 < .0001 -.34

Dissolved oxygen .18 26.8 < .0001 .34

Dunne overland flow -.23 14.3 .0002 -.29

Recharge .11 10.5 .001 .21

value of 0.33, and a maximum rescaled r-squared value of 

0.51.

The logistic regression models for simazine (table 28), 

metolachlor (table 29), and prometon (table 30) also had 

results generally similar to the models for atrazine. For simazine, urban and agricultural land uses were the most important 

variables, followed by degree of confinement. Several soil 

and hydrology related variables are statistically significant in 

this model, including Dunne overland flow (inversely correlated), the amount of moderately well-drained soils, and 

available water capacity. Although simazine was not strongly 

correlated with urban land use in the Spearman’s rank correlation (table 22), urban land use was an important predictive variable in the logistic regression model. The model for 

simazine had a concordance of 90.6, an r-squared value of 

0.21, and a maximum rescaled r-squared value of 0.45. The 

logistic regression model for metolachlor varies from the 

other models in that degree of confinement is not a significant 

variable, and the land-use-related variables are not among the 

strongest predictive variables. The model included an inverse 

association with poorly drained soils and a positive association 

with recharge, concentration of dissolved oxygen, metolachlor 

application rate, and population density as the significant 

variables (table 29). The model for metolachlor had a concordance of 82.2, an r-squared value of 0.10, and a maximum 

rescaled r-squared value of 0.24, indicating that this is one of 

the weaker models. The logistic regression model for prometon had results similar to the models for the other pesticides 

(table 30), with a positive relation to agricultural and urban 

land uses and degree of confinement and an inverse relation to 

poorly drained soils and calcium-magnesium ratio. The model 

for prometon had a concordance of 82.7, an r-squared value of 

0.12, and a maximum rescaled r-squared value of 0.26, indicating that this is also one of the weaker models.

Overall, the logistic regression models show patterns 

for the individual pesticides that have recurring themes. The 

degree of aquifer confinement is one of the most important explanatory variables in all but one of the models. One 

or more source variables are significant in all the models. 

The source factor of application rate on agricultural land is 

significant for the four pesticides with use data, and land use 

variables of agricultural or urban land use are also significant 

for all models. Several other variables are statistically significant but typically less important in predicting pesticide 

occurrence. Population density is a significant variable in 

many of the models. Hydrology and soils variables were also 

significant. Recharge, a measure of the flux of water through 

the ground-water system, always had a positive relation to 

pesticide occurrence. The presence of well-drained soils 

tended to increase the probability of a pesticide exceeding 

the selected threshold, and poorly drained soils decreased 

the probability of a pesticide exceeding the threshold. Dunne 

overland flow represents runoff from saturated soils through 

which water can no longer infiltrate, thus resulting in overland 

flow, and is an inverse factor with respect to pesticide occurrence. These results indicate that a combination of source, fate, 

and transport factors affect the detections and concentrations 

of pesticides.

Volatile Organic Compounds

Water samples were collected for analysis of VOCs 

at 793 sites from the 12 carbonate aquifers—154 samples 

were analyzed for 54 VOCs from 1993 through 1995 (Rose 

and Schroeder, 1995) and 639 samples were analyzed for 86 

VOCs from 1996 through 2005 (Connor and others, 1998). 

The results of VOC sampling for the 12 carbonate aquifers are 

analyzed with respect to the distribution of VOCs, a screeninglevel assessment of potential human-health concerns, and factors affecting the distribution of VOC detection frequencies. 

Table 31 lists all the VOCs analyzed for this study, the number 

of samples analyzed, the number of detections, and the detection frequencies for each VOC analyzed.
94 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 30. Results of logistic regression model predicting probability of prometon being detected at a threshold of greater than 

0.01 micrograms per liter in 12 carbonate aquifers or aquifer systems, 1993–2005.

[<, less than]

Parameter Parameter 

estimate Chi-square Probability Standardized estimate

Intercept -8.1 41.1 < 0.0001

Percent agricultural land .03 25.3 < .0001 0.65

Percent urban land .04 32.8 < .001 .63

Aquifer-confinement category 1.34 12.1 .0005 .54

Hydrologic group D soils -.04 5.9 .0144 -.45

Calcium-magnesium molar ratio -.04 6.9 .009 -.25

Table 28. Results of logistic regression model predicting probability of simazine being detected at a threshold of greater than 

0.01 micrograms in 12 carbonate aquifers or aquifer systems, 1993–2005.

[<, less than]

Parameter Parameter 

estimate Chi-square p-value Standardized estimate

Intercept -11.3 70.9 < 0.0001

Percent urban land .04 27.9 < .0001 0.72

Percent agricultural land .04 20.7 < .0001 .71

Aquifer-confinement category 1.17 11.2 .0008 .47

Dunne overland flow -.37 14.0 .0002 -.47

Dissolved oxygen .17 15.2 < .0001 .32

Soil available water capacity 14.56 8.5 .0036 .29

Hydrologic group B soils .02 6.5 .0111 .29

Simazine application rate .13 23.0 < .0001 .24

Table 29. Results of logistic regression model predicting probability of metolachlor being detected at a threshold of greater than 

0.01 micrograms per liter in 12 carbonate aquifers or aquifer systems, 1993–2005.

[<, less than]

Parameter Parameter 

estimate Chi-square p-value Standardized estimate

Intercept -4.45 95.8 < 0.0001

Hydrologic Group D soils -.05 5.2 .022 -0.57

Dissolved oxygen .15 11.6 .0006 .28

Recharge .15 11.2 .0008 .28

Metolachlor application rate .03 18.7 < .0001 .21

Population density 1990 .001 10.1 .0015 .20
Factors Affecting Anthropogenic Contaminants 95

Table 31. List of volatile organic compounds analyzed, number of detections greater than or equal to 0.2 micrograms per liter, and 

human-health-benchmark exceedances in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued

[DBP, disinfection by-product; FUM, fumigant-related compound; GAS, gasoline hydrocarbons, oxygenates, and oxygenate degradates; PC, personal care 

and domestic use product; REF, refrigerants and propellant; SOL, solvent; SYN, organic synthesis compound; μg/L, micrograms per liter; MCL, Maximum 

contaminant level; HBSL, Health-based screening level; N/A, not applicable]

Name

Type of 

compound

Number of 

detections 

greater 

than or 

equal to 

0.2 μg/L

Percent 

detection 

greater 

than or 

equal to 

0.2 μg/L

Number 

of 

detections 

at any 

concentration

Number 

of 

analyses

Maximum 

concentration 

(μg/L)

Benchmark 

level 

(μg/L)

Benchmark 

type1

Percent 

greater 

than 

benchmark

Percent 

detection 

at any 

concentration

Chloroform DBP 57 7.2 229 793 61 2

80 MCL 0 28.9

Tetrahydrofuran SOL 22 3.4 23 639 1,430 NONE 3.6

Tetrachloroethene (PCE) SOL 23 2.9 118 792 5.01 5 MCL .1 14.9

Toluene3 GAS 18 2.3 81 793 12 1,000 MCL 0 10.2

Acetone SOL 15 2.3 15 639 6.97 6,000 HBSL 0 2.3

Ethylmethylketone SOL 14 2.2 17 639 17.6 NONE 2.7

Methyl tert-butyl ether (MTBE) GAS 17 2.1 33 793 51 NONE 4.2

Trichloroethene (TCE) SOL 15 1.9 38 793 7.48 5 MCL .1 4.8

Xylene GAS 3 1.9 3 154 41 10,000 MCL 0 1.9

1,1,1-Trichloroethane SOL 11 1.4 35 793 3 200 MCL 0 4.4

1,2,4-Trimethylbenzene4 GAS 10 1.3 19 793 12 NONE 2.4

cis-1,2-Dichloroethene SOL 10 1.3 28 793 4.4 NONE 3.5

Carbon disulfide SYN 7 1.1 130 639 1.85 700 HBSL 0 20.3

Dichlorodifluoromethane (CFC-12) REF 7 .9 17 793 2.0 1,000 HBSL 0 2.1

Tribromomethane DBP 7 .9 17 793 3.09 2

80 MCL 0 2.1

4-Isopropyltoluene GAS 6 .8 18 793 3.0 NONE 2.3

Bromodichloromethane DBP 5 .6 31 793 3.50 2

80 MCL 0 3.9

Dibromochloromethane DBP 5 .6 18 793 2.89 2

80 MCL 0 2.3

1,1-Dichloroethane SOL 4 .5 16 793 .58 NONE 2.0

Dichloromethane SOL 4 .5 17 793 1.9 5 MCL 0 2.1

Naphthalene GAS 4 .5 6 793 2.02 100 HBSL 0 .8

Benzene GAS 3 .4 31 793 4.4 5 MCL 0 3.9

Carbon tetrachloride SOL 3 .4 7 793 .60 5 MCL 0 .9

Trichlorofluoromethane (CFC-11) REF 3 .4 14 793 1.57 2,000 HBSL 0 1.8

Diisopropyl ether (DIPE) GAS 1 .3 2 610 2.07 NONE .3

1,1-Dichloroethene SOL 2 .3 16 793 1.00 7 MCL 0 2.0

1,2-Dichlorobenzene SOL 2 .3 3 793 .27 NONE .4

1,2-Dichloropropane FUM 2 .3 22 793 6.4 5 MCL .1 2.8

1,3,5-Trimethylbenzene GAS 2 .3 5 793 4.00 NONE .6

Chlorobenzene SOL 2 .3 8 793 .53 100 MCL 0 1.0

1,1,2-Trichlorotrifluoroethane (CFC-113) REF 2 .3 9 793 .30 200,000 HBSL 0 1.1

Ethylbenzene GAS 2 .3 18 793 8.7 700 MCL 0 2.3

Isopropylbenzene GAS 2 .3 9 793 1.94 700 HBSL 0 1.1

n-Butylbenzene GAS 1 .3 2 793 .26 NONE .3

n-Propylbenzene SOL 2 .3 6 793 2.11 NONE .8

sec-Butylbenzene GAS 1 .3 2 793 .43 NONE .3

Vinyl chloride SYN 2 .3 3 793 4.68 2 MCL 0 .4

1,2,3-Trimethylbenzene GAS 1 .2 4 639 1.32 NONE .6
96 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Table 31. List of volatile organic compounds analyzed, number of detections greater than or equal to 0.2 micrograms per liter, and 

human-health-benchmark exceedances in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued

[DBP, disinfection by-product; FUM, fumigant-related compound; GAS, gasoline hydrocarbons, oxygenates, and oxygenate degradates; PC, personal care 

and domestic use product; REF, refrigerants and propellant; SOL, solvent; SYN, organic synthesis compound; μg/L, micrograms per liter; MCL, Maximum 

contaminant level; HBSL, Health-based screening level; N/A, not applicable]

Name

Type of 

compound

Number of 

detections 

greater 

than or 

equal to 

0.2 μg/L

Percent 

detection 

greater 

than or 

equal to 

0.2 μg/L

Number 

of 

detections 

at any 

concentration

Number 

of 

analyses

Maximum 

concentration 

(μg/L)

Benchmark 

level 

(μg/L)

Benchmark 

type1

Percent 

greater 

than 

benchmark

Percent 

detection 

at any 

concentration

2-Ethyltoluene GAS 1 0.2 5 639 2.07 NONE 0.8

Isobutylmethylketone SOL 1 .2 3 639 .20 NONE .5

m- + p-Xylene GAS 1 .2 25 639 14.71 NONE 3.9

o-Xylene GAS 1 .2 10 639 9.50 NONE 1.6

Prehnitene GAS 1 .2 1 639 .25 NONE .2

Styrene GAS 1 .1 31 793 3.45 100 MCL 0 3.9

1,1-Dichloropropene SYN 0 0 0 793 N/A N/A 0

1,1,1,2-Tetrachloroethane SOL 0 0 0 793 N/A N/A 0

1,1,2-Trichloroethane SOL 0 0 0 793 N/A N/A 0

1,1,2,2-Tetrachloroethane SOL 0 0 0 793 N/A N/A 0

1,2-Dibromo-3-chloropropane (DBCP) FUM 0 0 0 793 N/A N/A 0

1,2-Dibromoethane (EDB) FUM 0 0 0 793 N/A N/A 0

1,2-Dichloroethane SOL 0 0 1 793 .16 5 MCL 0 .1

1,2,3-Trichloropropane SYN 0 0 0 793 N/A N/A 0

1,2,3-Trichlorobenzene SYN 0 0 0 793 N/A N/A 0

1,2,4-Trichlorobenzene SOL 0 0 0 793 N/A N/A 0

1,3-Dichlorobenzene SOL 0 0 2 793 .08 600 HBSL 0 .3

1,3-Dichloropropane FUM 0 0 0 793 N/A N/A 0

1,4-Dichlorobenzene FUM 0 0 16 793 .5 NONE 2.0

3-Chloro-1-propene SYN 0 0 0 639 N/A N/A 0

2-Chlorotoluene SOL 0 0 1 793 .13 NONE .1

2-Hexanone SOL 0 0 0 639 N/A N/A 0

2-Methyl-2-propenitrile SYN 0 0 0 639 N/A N/A 0

2,2-Dichloropropane FUM 0 0 0 793 N/A N/A 0

4-Chlorotoluene SOL 0 0 0 793 N/A N/A 0

Acrolein SYN 0 0 0 269 N/A N/A 0

Acrylonitrile SYN 0 0 0 639 N/A N/A 0

Bromobenzene SOL 0 0 1 793 0 NONE .1

Bromochloromethane PC 0 0 1 793 .02 90 HBSL 0 .1

Bromomethane FUM 0 0 0 793 N/A N/A 0

Chloroethane SOL 0 0 1 793 .06 NONE .1

Chloromethane SYN 0 0 74 797 .10 NONE 9.3

cis-1,3-Dichloropropene FUM 0 0 0 793 N/A N/A 0

Dibromomethane SOL 0 0 2 793 .05 NONE .3

Diethyl ether SOL 0 0 2 639 .06 NONE .3

Ethyl methacrylate SYN 0 0 0 639 N/A N/A 0
Factors Affecting Anthropogenic Contaminants 97

Table 31. List of volatile organic compounds analyzed, number of detections greater than or equal to 0.2 micrograms per liter, and 

human-health-benchmark exceedances in 12 carbonate aquifers or aquifer systems, 1993-2005.—Continued

[DBP, disinfection by-product; FUM, fumigant-related compound; GAS, gasoline hydrocarbons, oxygenates, and oxygenate degradates; PC, personal care 

and domestic use product; REF, refrigerants and propellant; SOL, solvent; SYN, organic synthesis compound; μg/L, micrograms per liter; MCL, Maximum 

contaminant level; HBSL, Health-based screening level; N/A, not applicable]

Name

Type of 

compound

Number of 

detections 

greater 

than or 

equal to 

0.2 μg/L

Percent 

detection 

greater 

than or 

equal to 

0.2 μg/L

Number 

of 

detections 

at any 

concentration

Number 

of 

analyses

Maximum 

concentration 

(μg/L)

Benchmark 

level 

(μg/L)

Benchmark 

type1

Percent 

greater 

than 

benchmark

Percent 

detection 

at any 

concentration

Hexachloroethane SOL 0 0 0 639 N/A N/A 0

Hexachlorobutadiene SYN 0 0 0 793 N/A N/A 0

Methyl acrylate SYN 0 0 0 639 N/A N/A 0

Methyl methacrylate SYN 0 0 0 639 N/A N/A 0

Iodomethane SYN 0 0 11 639 1.05 NONE 1.7

Isodurene GAS 0 0 2 639 .10 NONE .3

tert-Butylbenzene GAS 0 0 0 793 N/A N/A 0

tert-Butyl ethyl ether GAS 0 0 2 639 .02 NONE .3

tert-Pentyl methyl ether GAS 0 0 2 639 .17 NONE .3

trans-1,2-Dichloroethene SOL 0 0 2 793 .03 100 MCL 0 .3

trans-1,3-Dichloropropene FUM 0 0 0 793 N/A N/A 0

trans-1,4-Dichloro-2-butene SYN 0 0 0 639 N/A N/A 0

Vinyl acetate SYN 0 0 0 126 N/A N/A 0

Vinyl bromide SYN 0 0 0 545 N/A N/A 0

1

U.S. Environmental Protection Agency, 2006; Toccalino and others, 2007.

2

Part of total trihalomethane maximum contaminant level of 80 μg/L.

3

Included concentrations greater than or equal to 0.03 μg/L.

4

Included concentrations greater than or equal to 0.05 μg/L.
98 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Detection Levels and Data-Analysis Methods

Assessment levels are used to allow a common comparison among samples for the same VOC if the reporting level 

changed over time, or to allow comparisons among several 

VOCs that have different reporting levels. As stated previously, prior to 1996, the LRL was 0.2 μg/L for most compounds, so comparisons between data collected before 1996 

(154 samples) and from 1996 through 2005 (639 samples) can 

only be made by comparing percent detections at the 0.2 μg/L 

assessment level. For these reasons, comparisons of the detection frequencies among the VOCs and the 12 aquifers throughout this section were computed for detections greater than or 

equal to 0.2 μg/L.

Occurrence and Distribution

Twenty percent of samples contained one or more VOCs 

at the 0.2 μg/L assessment level, about 8 percent of samples 

contained two or more VOC detections per sample, about 

4 percent of samples contained three or more VOC detections, 

and about 2 percent contained four or more VOC detections 

per sample (fig. 37). The percent of samples in these carbonate 

aquifers containing one or more VOCs was similar to findings 

from national studies (which also include some of the data 

used in this report) where 19 percent of samples contained 

one or more VOCs at concentrations greater than or equal to 

0.2 μg/L (Zogorski and others, 2006, p. 16). Among the aquifers, the percent of samples with one or more VOCs detected 

at the 0.2 μg/L assessment level ranged from 8 percent in the 

Basin and Range aquifer to 41 percent in the Castle-Hayne 

aquifer (fig. 38A). Altogether, seven of the carbonate aquifers 

or aquifer systems had more than 20 percent of samples with DETECTION FREQUENCY, IN PERCENT100

80

60

40

20

0 Detections greater than or

equal to 0.2 micrograms

per liter

Detections at all

concentrations

NUMBER OF VOCs DETECTED

PER SAMPLE

1 or more

2 or more

3 or more

4 or more

Figure 37. Detection frequency for samples with one or more, 

two or more, three or more, and four or more volatile organic 

compounds (VOCs) detected including all detections and at the 

0.2 micrograms per liter assessment level in 12 carbonate aquifers 

or aquifer systems, 1993–2005.

one or more VOCs per sample—Biscayne (34 percent), Castle 

Hayne (41 percent), Mississippian (21 percent) Ozark Plateaus 

(22 percent), Piedmont (27 percent), Silurian-Devonian/Upper 

carbonate (27 percent) and Valley and Ridge (24 percent) 

(fig. 38Aa).

A larger percent of VOC occurrence was evident for a 

subset of 639 samples that were collected during 1996–2005 

and analyzed using the low-level analytical method. Sixtynine percent of the 639 samples contained 1 or more VOC 

detections per sample, about 40 percent of samples contained 

2 or more VOC detections, about 27 percent of samples 

contained 3 or more VOC detections, and about 16 percent 

contained 4 or more VOC detections (fig. 37). The percent of 

samples in these carbonate aquifers containing one or more 

VOCs was higher than the findings from national studies 

(which also include some of the data used in this report)—in 

the national studies about half of wells sampled contained 

one or more VOCs at an assessment level of 0.02 μg/L and 

19 percent contained one or more VOCs at a level of 0.2 μg/L 

(Zogorski and others, 2006, p. 16). The finding that one or 

more VOCs were detected in nearly 70 percent of the samples 

analyzed using the low-level method demonstrates the vulnerability of many of the carbonate aquifers to low-level VOC 

contamination.

The percentage of samples with one or more VOC detections per sample did not vary by degree of confinement or 

redox status but did vary by land use. At the 0.2 μg/L assessment level, the percent of samples with one or more VOC 

detections was similar between unconfined (22 percent of 

samples) and confined areas (19 percent), with a lower percentage for semiconfined/mixed confined areas (13 percent)

(fig. 38B). Similarly, the percent of sites with two or more 

VOC detections per sample was similar for unconfined (6 percent) and confined areas (8 percent) with a lower percentage 

for sites in semiconfined/mixed confined areas (1 percent). 

Less than 3 percent of sites contained four or more VOCs 

in any of the confinement categories at the 0.2 μg/L assessment level. The percentage of samples with one or more VOC 

detections per sample were similar for the three redox-status 

categories at the 0.2 μg/L assessment level—23 percent of 

the anoxic samples contained one or more VOC detections, 

18 percent of mixed-source samples and 19 percent of oxic 

samples (fig. 38C). Fewer than 3 percent of samples contained 

four or more VOCs per sample in any of the redox-status categories. The lack of variability by redox status is likely due to 

the fact that some of the VOCs persist under oxic conditions, 

and others persist under anoxic conditions. Among land-use 

categories, the percentage of samples with one or more VOC 

detections was higher in sites categorized as urban (31 percent 

of samples) than in the mixed land use (21 percent), undeveloped (16 percent), or agricultural (13 percent) land-use areas 

(fig. 38D) at the 0.2 μg/L assessment level. Four percent of 

samples contained four or more VOCs per sample in the urban 

land-use category but fewer than 2 percent of samples contained four or more VOCs in the agricultural, mixed land use, 

or undeveloped land-use categories.
Factors Affecting Anthropogenic Contaminants 99

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Silurian-Devonian/ Upper carbonate

Piedmont

Valley and Ridge

Ordovician

Prairie du Chien

DETECTION FREQUENCY, IN PERCENT50

40

30

20

10

0

DETECTION FREQUENCY, IN PERCENT50

40

30

20

10

0

DETECTION FREQUENCY, IN PERCENT50

40

30

20

10

0

DETECTION FREQUENCY, IN PERCENT50

40

30

20

10

0

Unconfined Semiconfined

or mixed confined Confined

Oxic Mixed source Anoxic

Agricultural Urban Mixed Undeveloped

24 65 32 123 216 33 40 49 30 30 33 118

546 97 147

468 44 275

246 180 203 164

A

B

C

D

Number of VOCs detected

per sample

1 or more

2 or more

3 or more

4 or more

EXPLANATION

Number of VOCs detected

per sample

1 or more

2 or more

3 or more

4 or more

EXPLANATION

Number of VOCs detected

per sample

1 or more

2 or more

3 or more

4 or more

EXPLANATION

Number of VOCs detected

per sample

1 or more

2 or more

3 or more

4 or more

EXPLANATION

Figure 38. Detection frequency for samples with one or more, two or more, three or 

more, and four or more volatile organic compounds (VOCs) detected at the 0.2 micrograms 

per liter assessment level by A) aquifer, B) confinement category, C) redox status, and 

D) land-use category in 12 carbonate aquifers or aquifer systems, 1993–2005.
100 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Thirteen VOCs were detected in 1 percent or more samples at the 0.2 μg/L assessment level, and detection frequencies were variable among the aquifers. Chloroform was the 

most frequently detected VOC and was detected in 7.2 percent 

of the samples from all 12 aquifers (fig. 39). Chloroform was 

detected most frequently in the Mississippian aquifer (18 percent of samples) and the Valley and Ridge aquifer (14 percent 

of samples) and it was not detected in any samples at the 

0.2 μg/L assessment level in five aquifers—Basin and Range, 

Castle Hayne, Piedmont, Prairie du Chien, and SilurianDevonian/Upper carbonate aquifers (fig. 40). Tetrahydrofuran 

was the second most frequently detected VOC at the 0.2 μg/L 

assessment level (3.4 percent in all 12 aquifers) and its occurrence was highly variable—it was detected in 30 percent of 

the samples in the Castle Hayne aquifer and in 3 percent or 

less of samples in the other aquifers. Tetrachloroethene (PCE) 

was detected in 2.9 percent of samples at the 0.2 μg/L assessment level—it was detected in 21 percent of the samples from 

the Silurian-Devonian/Upper carbonate aquifer, 9 percent of 

the Mississippian, 7 percent of the Valley and Ridge aquifer 

samples and less than 4 percent in the other aquifers at the 

0.2 μg/L assessment level. PCE was not detected in any samples from the Basin and Range, Biscayne, Castle Hayne, Piedmont, or Prairie du Chien aquifers at the 0.2 μg/L assessment 

level (fig. 40). Toluene was detected in 2.3 percent of samples 

at the 0.2 μg/L assessment level—it was detected in 8 percent 

of samples from the Biscayne aquifer and about 6 percent of 

samples from the Castle Hayne, and Silurian-Devonian/Upper 

carbonate aquifers. Toluene was detected in less than 4 percent 

of samples from the other aquifers. Toluene was not detected 

Chloroform

Tetrahydrofuran

Tetrachloroethene (PCE)

Toluene

Acetone

Ethylmethylketone

Methyl tert-butyl ether (MTBE)

Trichloroethene (TCE)

10

8

6

4

2

0

DETECTION FREQUENCY, IN PERCENT

Figure 39. Detection frequencies of the eight most frequently 

detected volatile organic compounds at the 0.2 micrograms 

per liter assessment level in 12 carbonate aquifers or aquifer 

systems, 1993–2005.

in samples from the Basin and Range, Piedmont, and Prairie 

du Chien aquifers at the 0.2 μg/L assessment level (fig. 40).

Assessment of Potential Human-Health 

Significance

Concentrations of VOCs were compared to human-health 

benchmarks (MCLs and HBSLs) to determine the potential 

impacts of these compounds on human health. BQ values were 

calculated and represent the concentration of a given VOC 

divided by the MCL or HBSL (figs. 41–44). Although chloroform was the most frequently detected VOC (table 31), concentrations were all less than the human-health benchmarks. 

Chloroform concentrations were compared to the MCL for 

total trihalomethanes of 80 μg/L (U.S. Environmental Protection Agency, 2006) and no concentrations were found above 

this level—concentration of other trihalomethanes analyzed 

were less than 5 μg/L (table 31). Two samples in urban areas 

in the unconfined Valley and Ridge aquifer did have chloroform BQ values greater than 0.1 (fig. 41A), indicating the 

concentrations were within an order of magnitude of the MCL. 

The maximum concentration of chloroform was 61 μg/L in a 

monitoring well in an urban land-use area in the unconfined 

Valley and Ridge aquifer.

Four VOCs—vinyl chloride, PCE, trichloroethene (TCE), 

and 1,2-dichloropropane—were each detected at concentrations exceeding an MCL. Each of these exceedances occurred 

in drinking-water supplies. Vinyl chloride was detected in two 

samples from the unconfined Biscayne aquifer at concentrations of 4.7 and 3.2 μg/L, which exceeded the MCL of 2 μg/L. 

Both of the sites where vinyl chloride was detected were in 

anoxic samples in urban areas. PCE, TCE, and 1,2-dichloropropane had one sample each in unconfined areas of the 

Mississippian aquifer with a concentration greater than the 

MCL—the MCL is 5 μg/L for each of these VOCs (U.S. 

Environmental Protection Agency, 2006) (figs. 42–44). PCE 

was detected at a concentration of 5.01 μg/L in one sample 

from a public supply well in a predominantly urban area, TCE 

was detected at a concentration of 7.5 μg/L in one sample 

from a domestic supply well in an agricultural area (fig. 43), 

and 1,2,-dichloropropane was detected at a concentration of 

6.4 μg/L in one sample from a spring in an agricultural area 

that is used for domestic supply (fig. 44). Nine samples had 

PCE concentrations within an order of magnitude of the MCL 

(fig. 42), eight samples had TCE concentrations within an 

order of magnitude of the MCL (fig. 43), and two samples 

had 1,2-dichloropropane concentrations within an order of 

magnitude of the MCL (fig. 44). These occurrences of concentrations within an order of magnitude of the MCL occurred in 

agricultural, urban, and mixed land-use areas (figs. 42–44), but 

all were in samples from unconfined areas. About 70 percent 

of the 793 samples with VOC analyses were categorized as 

unconfined, so the higher numbers of VOC occurrences in this 

category are not surprising.
Factors Affecting Anthropogenic Contaminants 101

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Silurian-Devonian/ Upper carbonate

Piedmont

Valley and Ridge

Ordovician

Prairie du Chien

Biscayne

Basin and Range

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ozark Plateaus

Silurian-Devonian/ Upper carbonate

Piedmont

Valley and Ridge

Ordovician

Prairie du Chien

Chloroform

Tetrahydrofuran

Tetrachloroethene (PCE)

Toluene

Acetone

Ethylmethylketone

Methyl tert-butyl ether (MTBE)

Trichloroethene (TCE)

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

30

20

10

DETECTION FREQUENCY, IN PERCENT

0

Not sampledNot sampled

Not sampledNot sampled

Figure 40. Detection frequencies of the eight most frequently detected volatile organic compounds in each aquifer at the 

0.2 micrograms per liter assessment level in 12 carbonate aquifers or aquifer systems, 1993–2005.
102 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Shaded area represents concentrations reported that were less than 0.2 μg/L.

Samples collected prior to April 1996 (154 samples in five aquifers) were analyzed

when the minimum laboratory reporting level for VOCs was 0.2 μg/L, thus

comparisons can not be made among all aquifers in the shaded area.

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Chloroform concentration

Total trihalomethanes MCL [80 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

0.001 0.01 0.1 1 10 100

BENCHMARK QUOTIENT VALUE

Silurian-Devonian/

Upper carbonate

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie Du Chien

Valley and Ridge

CHLOROFORM CONCENTRATION, 

IN MICROGRAMS PER LITER

0.00001 0.0001 0.001 0.01 0.1 1 10

Figure 41. Concentrations and human-health benchmark quotient values for chloroform by land-use category in 12 carbonate 

aquifers or aquifer systems, 1993–2005.
Factors Affecting Anthropogenic Contaminants 103

Shaded area represents concentrations reported that were less than 0.2 μg/L.

Samples collected prior to April 1996 (154 samples in five aquifers) were analyzed

when the minimum laboratory reporting level for VOCs was 0.2 μg/L, thus

comparisons can not be made among all aquifers in the shaded area.

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Tetrachloroethene (PCE) concentration

Tetrachloroethene (PCE) MCL [5 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

0.001 0.01 0.1 1 10

BENCHMARK QUOTIENT VALUE

Silurian-Devonian/

Upper carbonate

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie Du Chien

Valley and Ridge

0.0001 0.001 0.01 0.1 1 10

MICROGRAMS PER LITER

TETRACHLOROETHENE CONCENTRATION, 

Figure 42. Concentrations and human-health benchmark quotient values of tetrachloroethene (PCE) by land-use category in 12 

carbonate aquifers or aquifer systems, 1993–2005.
104 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Shaded area represents concentrations reported that were less than 0.2 μg/L.

Samples collected prior to April 1996 (154 samples in five aquifers) were analyzed

when the minimum laboratory reporting level for VOCs was 0.2 μg/L, thus

comparisons can not be made among all aquifers in the shaded area.

Benchmark quotient value of 0.1—Values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—Values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = Trichloroethene (TCE) concentration

Trichloroethene (TCE) MCL [5 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

0.001 0.01 0.1 1 10

BENCHMARK QUOTIENT VALUE

Silurian-Devonian/

Upper carbonate

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie Du Chien

Valley and Ridge

0.0001 0.001 0.01 0.1 1 10

MICROGRAMS PER LITER

TRICHLOROETHENE CONCENTRATION, 

Figure 43. Concentrations and human-health benchmark quotient values of trichloroethene (TCE) by land-use category in 12 

carbonate aquifers or aquifer systems, 1993–2005.
Factors Affecting Anthropogenic Contaminants 105

0.001 0.01 0.1 1 10

BENCHMARK QUOTIENT VALUE

Shaded area represents concentrations reported that were less than 0.2 μg/L.

Samples collected prior to April 1996 (154 samples in five aquifers) were analyzed

when the minimum laboratory reporting level for VOCs was 0.2 μg/L, thus

comparisons can not be made among all aquifers in the shaded area.

Benchmark quotient value of 0.1—values

 greater than this line are within one order

 of magnitude of a MCL or HBSL

Benchmark quotient value of 1.0—values

 greater than this line indicate concentrations

 of potential human-health concern

Benchmark quotient value (BQ) = 1,2-Dichloropropane concentration

1,2-Dichloropropane MCL [5 μg/L]

Undeveloped

Mixed

Agriculture

Urban

EXPLANATION

Silurian-Devonian/

Upper carbonate

Basin and Range

Biscayne

Castle Hayne

Edwards-Trinity

Floridan

Mississippian

Ordovician

Ozark Plateaus

Piedmont

Prairie Du Chien

Valley and Ridge

0.0001 0.001 0.01 0.1 1 10

MICROGRAMS PER LITER

1,2-DICHLOROPROPANE CONCENTRATION,

Figure 44. Concentrations and human-health benchmark quotient values of 1,2-dichloropropane by land-use category in 12 

carbonate aquifers or aquifer systems, 1993–2005.
106 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Factors Affecting Occurrence of Frequently 

Detected Volatile Organic Compounds

The eight most frequently detected VOCs—chloroform, 

tetrahydrofuran, PCE, toluene, acetone, ethylmethylketone, 

methyl tert-butyl ether (MTBE), and TCE—differed in their 

detection frequencies among the carbonate aquifers studied 

and these differences are likely related to various natural and 

anthropogenic factors, including hydrogeology, water chemistry, and land use. Comparison of the detection frequencies 

of the eight most frequently detected VOCs among categories of confinement and land use at the sampling site, as well 

as redox status of the water sample, were used to assess the 

importance of the factors affecting VOC occurrence in the 12 

carbonate aquifers. Previous national studies have shown that 

VOC occurrence in ground water was associated with natural and anthropogenic factors, the most common of which is 

dissolved oxygen concentration—other factors include urban 

land use, hazardous-waste facilities, gasoline storage sites, 

septic systems, climate, well characteristics, and soil characteristics (Zogorski and others, 2006). In this study, similarities 

and differences were seen in the factors associated with the 

occurrence of different types of VOCs, including trihalomethanes (including disinfection by-products such as chloroform), 

solvents (PCE, TCE, and chloromethane) and gasoline hydrocarbons and oxygenates (toluene and MTBE).

Differences in the detection frequencies by degree of 

confinement, redox status, and land use demonstrate that the 

occurrence of the eight most frequently detected VOCs—

chloroform, tetrahydrofuran, toluene, PCE, acetone, ethylmethylketone, MTBE, TCE—are associated with different 

land uses and are affected differently by degree of confinement and redox status in ground water. Chloroform was 

detected most frequently at the 0.2 μg/L assessment level in 

sites categorized as unconfined (10 percent), in oxic samples 

(11 percent), and from areas where the predominant land use 

was urban (14 percent) (fig. 45A, B, and C), indicating that 

these settings are the most vulnerable to contamination from 

chloroform. The occurrence of chloroform has been associated with oxygenated waters, the percentage of urban land, the 

number of hazardous-waste facilities, and septic-tank density 

near the well sites (Squillace and Moran, 2006; Zogorski and 

others, 2006).

Five of the eight most frequently detected VOCs were 

solvents—tetrahydrofuran, PCE, acetone, ethylmethylketone, 

and TCE. Although detection frequencies were low in each 

category (most were less than 5 percent) some similarities and 

differences were noted among the five solvents (figs. 45A, 

B, and C). The five solvents were most frequently detected 

in urban land-use settings, except for acetone, which was 

detected most frequently in urban and mixed land-use settings 

(fig. 45C). Tetrahydrofuran, acetone, and ethylmethylketone 

were detected most frequently in anoxic water (fig. 45B) and 

in confined or semiconfined/mixed confined areas (fig. 45A). 

The greater frequency of detection in anoxic water may 

indicate these three VOCs are more persistent under anoxic 

conditions. If tetrahydrofuran does persist under anoxic 

conditions, this may explain the high detection frequency of 

that compound in the Castle-Hayne aquifer, which has low 

concentrations of dissolved oxygen and no wells in the ‘oxic’ 

redox-status category. PCE was detected at similar frequencies 

in confined areas and unconfined areas and TCE was detected 

most frequently in unconfined areas. PCE was detected more 

frequently in mixed source and oxic samples than in anoxic 

samples and TCE was detected most frequently in oxic samples. The findings are similar to the results of the analysis of 

national VOC data (Zogorski and others, 2006), which showed 

that the occurrence of PCE and TCE were associated with 

septic system density, the percentage of urban land use, and 

oxic water (which includes the mixed source redox category 

used in this report).

The gasoline hydrocarbon, toluene, and the gasoline 

oxygenate, MTBE, showed different occurrence patterns 

among the categories of confinement, redox status, and land 

use. Toluene was detected most frequently in confined areas, 

in anoxic samples, and in undeveloped and urban land-use 

settings, whereas MTBE was detected most frequently in 

unconfined areas, in oxic samples, and in urban land-use settings (fig. 45A, B, and C). This is also similar to the results of 

the analysis of national VOC data (Zogorski and others, 2006), 

which showed that toluene was more persistent in anoxic 

water, and MTBE was more persistent in oxic water. The high 

detection frequency of toluene in undeveloped areas may be 

because many of the detections were in confined areas, where 

the predominant land use near the well may be different than 

the predominant land use in the recharge area.

Summary

Carbonate aquifers provide an abundant supply of water 

to a large percentage of the population of the United States. 

The USGS National Water-Quality Assessment (NAWQA) 

Program has collected water-quality samples from 1993 

through 2005 at 1,042 sites in 12 of the principal carbonate 

aquifers of the United States. These aquifers/aquifer systems include the Basin and Range, Biscayne, Castle Hayne, 

Edwards-Trinity, Floridan, Mississippian, Ordovician, Ozark 

Plateaus, Piedmont, Prairie du Chien (part of the CambrianOrdovician aquifer), Silurian-Devonian/Upper carbonate (the 

Upper carbonate aquifer is a small carbonate aquifer lumped 

with the Silurian-Devonian aquifer for this study), and the Valley and Ridge. Some of these aquifers contain other lithologic 

units such as sandstone, but only wells completed in the carbonate parts of the aquifers were included in this study. These 

carbonate aquifers share the common characteristic of carbonate lithology, but otherwise, the hydrogeologic characteristics 

of these aquifers vary widely.

Most of the aquifers have fracture permeability, with 

varying degrees of solutional enlargement that increases 

transmissivity; thus, all these aquifers are referred to as karst 
Summary 107

DETECTION FREQUENCY, IN PERCENT DETECTION FREQUENCY, IN PERCENT DETECTION FREQUENCY, IN PERCENT

A

B

C

15

10

5

0

15

10

5

0

Chloroform

Tetrahydrofuran

Tetrachloroethene (PCE)

Toluene

Acetone

Ethylmethylketone

Methyl tert-butyl ether (MTBE)

Trichloroethene (TCE)

Anoxic

Mixed source

Oxic

Confined

Semiconfined or mixed confined

Unconfined

Agriculture

Urban

Mixed land use

Undeveloped

Figure 45. Detection frequencies of the eight most frequently detected volatile 

organic compounds at the 0.2 micrograms per liter assessment level by A) confinement 

category, B) redox status, and C) land use in 12 carbonate aquifers or aquifer systems, 

1993–2005.
108 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

aquifers. Some aquifers, however, such as the Biscayne, also 

have a significant component of primary porosity in the rock 

matrix. Karst-feature development also varies among these 

aquifers; sinkholes, caverns, and springs are common in most 

of the aquifers. These features play an important role in the 

recharge, transport, and discharge of water and contaminants 

in the aquifers.

The physical characteristics of the natural and anthropogenic features in the carbonate aquifers have an effect on 

water quality. The climate varies from an arid environment in 

the southwest, to subtropical in the southeast, to temperate in 

the central and northeastern parts of the United States. This 

variation affects the recharge and flux of water through the 

systems. The carbonate aquifers can be unconfined, sometimes with bedrock exposed at the land surface. In other areas, 

the carbonate aquifers are confined by layers of materials of 

varying thickness and permeability. The nature and thickness 

of these materials provide a variable level of protection for 

the aquifer from contaminants. These characteristics affect the 

typical construction of wells drilled in each aquifer. Wells in 

these aquifers range from very shallow in the Biscayne aquifer 

(tens of feet) to thousands of feet deep in several of the other 

aquifers. The land use overlying these aquifers is also highly 

variable, ranging from urban to agricultural, to forested and 

shrub land. The type and intensity of human activity at the 

land surface also has a potential effect on the quality of water 

in the aquifer.

Geochemical analysis of the water indicated that most 

waters had a near-neutral pH; the median was 7.1. Water 

from shallower aquifers that were thought to have a shorter 

residence time had lower pH, and pH had a strong positive 

correlation with well depth. Major ions and dissolved solids 

also showed positive correlations with increasing well depth, 

and these constituents are indicators of ground-water residence 

time, which is a controlling factor in aquifer geochemistry. 

Dominant major ions were calcium, magnesium, and bicarbonate. The relation between molar concentrations of calcium 

plus magnesium and bicarbonate indicated that calcite and 

dolomite dissolution were the dominant processes controlling 

major-ion composition. Saturation indices were calculated 

for numerous minerals. Most samples were considered to 

be at equilibrium with respect to calcite and undersaturated 

with respect to dolomite. The exceptions to this were that the 

Mississippian and Ordovician aquifers were undersaturated 

with respect to calcite, and the Prairie du Chien and Basin and 

Range aquifers were at equilibrium with respect to dolomite.

The oxidation-reduction (redox) status was highly variable; the Biscayne, Castle Hayne, Floridan, Prairie du Chien, 

and Silurian-Devonian/Upper carbonate aquifers/aquifer systems had median concentration of dissolved oxygen less than 

1.0 mg/L. In most cases, wells in confined aquifers had lower 

concentrations of dissolved oxygen than wells in unconfined 

aquifers. Differences in concentrations of dissolved oxygen 

are likely related to timing and amounts of recharge, presence 

of karst features such as sinkholes and large conduits, and 

presence of dissolved organic carbon. Median concentrations 

of dissolved organic carbon were highest in the Biscayne 

(11 mg/L), Castle Hayne (2.51 mg/L), and Silurian-Devonian/

Upper carbonate (1.2 mg/L) aquifers—the three aquifers with 

the lowest median concentrations of dissolved oxygen—

organic carbon is likely enhancing the rate of oxygen consumption in the ground water in these systems.

The median radon concentration for all samples in 

carbonate aquifers was 360 pCi/L. Most radon concentrations 

in water from the Basin and Range, Biscayne, Mississippian, 

Piedmont, and Prairie du Chien aquifers were greater than 

the USEPA-proposed maximum contaminant level (MCL) of 

300 pCi/L. Radon concentrations were highest in the water 

from wells in unconfined aquifers. Several geochemical 

measures or indicators were found to be important explanatory 

variables for the anthropogenic contaminants. These include 

factors directly related to fate such as concentrations of dissolved oxygen (or redox status) and dissolved organic carbon, 

as well as indicators of residence time, such as calcite S.I., 

dolomite S.I., and the calcium-magnesium ratio.

Nitrate was detected in 793 of 1,037 samples (76 percent). Concentrations ranged from below the detection limit 

of 0.06 mg/L to 25 mg/L. Nitrate concentrations exceeded 

the USEPA MCL of 10 mg/L in 54 samples (5 percent). The 

majority of the sites with concentrations exceeding the MCL 

were in the Valley and Ridge and Piedmont aquifers. The rate 

of exceedance of the MCL in the remaining 10 aquifers was 

about 1 percent. Median concentrations of nitrate were highest 

in the Piedmont and Valley and Ridge aquifers and lowest in 

the Biscayne, Castle Hayne, and Silurian-Devonian/Upper carbonate aquifers. Nitrate concentrations were related to source 

factors and transport factors.

Agricultural land use and the total nitrogen input from 

atmospheric deposition, fertilizer, manure, and septic systems 

were the source factors with the strongest positive correlation 

with nitrate concentrations. Ground-water age was a significant factor affecting nitrate concentration. Water recharged 

prior to 1953 had significantly lower median concentrations 

of nitrate than water recharged in 1953 or later. In addition, 

water from wells in confined aquifers and semiconfined/mixed 

confined aquifers had statistically significant lower nitrate 

concentrations than water from wells in unconfined aquifers. 

Dissolved oxygen concentration had a strong positive correlation with nitrate concentration, indicating that redox processes 

in the aquifer play an important role in the fate and transport 

of nitrate. Among waters with recharge dates later than 1953, a 

comparison of oxic and anoxic waters with a gradient of landuse types showed that oxic water in the area with the lowest 

potential nitrogen source (undeveloped) had greater nitrate 

concentrations than anoxic water with the highest potential 

nitrogen source (agricultural). This indicates that the redox status of the water is a more important controlling factor affecting nitrate concentration than land use. Nitrate concentrations 

were positively correlated with calcium-magnesium ratios and 

inversely correlated with calcite or dolomite S.I., which are 

indicators of longer residence time in the aquifer. Dissolved 

organic carbon concentration had an inverse correlation with 
Summary 109

nitrate concentrations and dissolved oxygen concentrations, 

indicating the importance of carbon in the nitrogen cycle.

Any single source or transport factor is not likely to control the concentration of nitrate. The Silurian-Devonian/Upper 

carbonate aquifer had the second-highest loadings of nitrogen 

but had the second-lowest median concentration of nitrate. A 

combination of the degree of aquifer confinement and land use 

provides a good explanation of the distribution of the concentrations of nitrate in the carbonate aquifers. A logistic regression model was built to assess the interaction of the source and 

transport variables. The variables that were significant in this 

model were the percent of soils in hydrologic group D (soils 

with a high runoff potential, an inverse relation), concentration 

of dissolved oxygen, percent forested land (inverse relation), 

calcium-magnesium ratio (inverse relation), and the input of 

nitrogen from all sources.

Pesticide samples were collected at 1,027 sites in the 

carbonate aquifers. At least 1 pesticide out of a schedule of 47 

pesticides analyzed was detected at 509 of the sites (50 percent). Multiple pesticides were frequently detected; 39 percent 

of the samples had two or more pesticides detected in the same 

sample, and 4 percent of the samples had six or more pesticides detected.

Only two pesticides were detected at a concentration that 

exceeded a human-health benchmark. Dieldrin was detected at 

20 sites at a concentration greater than the value for the HBSL 

of 0.002 μg/L; 9 of these sites were used as drinking-water 

sources. The maximum concentration of dieldrin detected was 

0.81 mg/L. Diazinon was detected at a concentration greater 

than the HBSL of 1 μg/L at a single well used for domestic 

supply.

The most frequently detected pesticides were atrazine, 

deethylatrazine, simazine, metolachlor, and prometon. When 

comparing the concentrations of these pesticides to a threshold of 10 percent of the human-health benchmark, only 41 

atrazine samples (4 percent) and 1 simazine sample (0.1 percent) exceeded that threshold. For these five compounds, the 

Biscayne, Mississippian, Piedmont, and Valley and Ridge 

aquifers had the highest detection frequencies; at least one of 

the pesticides was detected in 30 percent of the wells in those 

four aquifers. The Basin and Range, Castle Hayne, Floridan, 

and Ozark Plateaus aquifers/aquifer systems had the lowest 

detection rates for these five pesticides; less than 10 percent 

of the wells in those aquifers had one or more of the five most 

frequently occurring pesticides detected. All the frequently 

detected pesticides had positive correlations with agricultural 

land use and the application rate of the pesticide, if it was 

available. Atrazine, simazine, and prometon had a positive 

correlation with urban land use. The detections of pesticides 

were related to ground-water age and degree of confinement; 

samples of younger water and water from unconfined aquifers 

had a statistically significant higher rate of pesticide detection than samples of older water and water from aquifers with 

mixed confinement or confined aquifers. Dissolved oxygen 

concentration had a positive correlation with pesticide concentration. This is likely because well-oxygenated waters are 

young rather than any direct cause-and-effect relation because 

the degradation processes of some of these pesticides require 

oxygen. Dissolved organic carbon had an inverse correlation 

with pesticide concentrations in some aquifers, and a positive 

correlation in others. In the cases where the correlation was 

positive, it is likely that the correlation was a result of land 

use and not concentration of dissolved organic carbon. Several 

of the pesticides showed positive correlations with calciummagnesium ratios and inverse correlations with calcite or 

dolomite S.I., which are indicators of longer residence time in 

the aquifer.

Analysis of the interaction of source, transport, and fate 

factors showed that a combination of land use and degree of 

confinement explained the patterns of detections of pesticides. Wells in unconfined areas with urban, mixed land use, 

or agricultural land use had a higher frequency of pesticide 

detection than confined aquifers with other land-use types. 

The detections in the unconfined areas with these land-use 

types make up 71 percent of the samples, but nearly 90 percent 

of the detections of the frequently detected pesticides. The 

logistic regression models built for each of the five frequently 

occurring pesticides also showed the importance of land use 

and degree of confinement; one of the land-use variables was 

significant in each of the regression models, and degree of 

confinement was significant in all but one of the regression 

models.

VOCs were detected in 20 percent of samples at concentrations greater than or equal to 0.2 μg/L (159 of 793 samples). 

About 8 percent of samples contained two or more VOC 

detections per sample, about 4 percent of samples contained 

three or more VOC detections, and about 2 percent of samples 

contained four or more VOC detections. VOCs were detected 

in a larger percent of samples when all concentrations were 

included for a subset of 639 samples that were analyzed using 

a low-level analytical method. Sixty-nine percent of the 639 

samples contained 1 or more VOCs, about 40 percent of 

samples contained 2 or more VOC detection per sample, about 

27 percent of samples contained 3 or more VOC detections, 

and about 16 percent contained 4 or more VOC detections. 

Detection frequencies for VOCs were slightly higher for 

samples in areas with urban or mixed land use than in areas 

with agricultural or undeveloped land use, but did not vary 

significantly among confinement categories or redox-status 

categories. Thirteen VOCs were detected in 1 percent or 

more samples at the 0.2 μg/L assessment level, and detection 

frequencies were variable among the aquifers. The most frequently detected VOCs at the 0.2 μg/L assessment level were 

chloroform (detected in 7.2 percent of samples), tetrahydrofuran (3.4 percent), PCE (2.9 percent), toluene (2.3 percent), 

acetone (2.3 percent), ethylmethylketone (2.2 percent), MTBE 

(2.1 percent), and TCE (1.9 percent). These VOCs differed 

in their detection frequencies among the carbonate aquifers 

studied and these differences are likely related to various natural and anthropogenic factors, including hydrogeology, water 

chemistry, and land use.
110 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Chloroform was detected most frequently at the 0.2 μg/L 

assessment level in sites categorized as unconfined (10 percent), in oxic samples (11 percent), and from areas where 

the predominant land use was urban (14 percent). Detection 

frequencies for five solvents—tetrahydrofuran, PCE, acetone, 

ethylmethylketone, and TCE—were lower in each category 

(most were less than 5 percent). These VOCs were most 

frequently detected in urban land-use settings but detection 

frequencies varied among the redox status and confinement 

categories. Tetrahydrofuran, acetone, and ethylmethylketone 

were detected most frequently in anoxic water and in confined 

or semiconfined/mixed confined areas. PCE was detected at 

similar frequencies in confined areas and unconfined areas, 

and TCE was detected most frequently in unconfined areas. 

PCE was detected more frequently in mixed source and oxic 

samples than in anoxic samples and TCE was detected most 

frequently in oxic samples. The gasoline hydrocarbon, toluene, 

and the gasoline oxygenate, MTBE, showed different occurrence patterns among the categories of confinement, redox 

status, and land use. Toluene was detected most frequently in 

confined areas, in anoxic samples, and in undeveloped and 

urban land-use settings. MTBE was detected most frequently 

in unconfined areas, in oxic samples, and in urban land-use 

settings.

Four VOCs—vinyl chloride, PCE, TCE, and 1,2-dichloropropane—were each detected at concentrations exceeding 

an MCL in a small number of samples. Vinyl chloride concentrations exceeded the MCL of 2 μg/L in two samples—the 

samples were anoxic and from urban areas in the unconfined 

Biscayne aquifer. Three samples exceeded MCLs for PCE, 

TCE, and 1,2-dichloropropane (MCL for each is 5 mg/L) in 

unconfined areas of the Mississippian aquifer.

This study of water quality in carbonate aquifers provided an opportunity to compare and contrast the factors 

affecting the concentrations and occurrence of anthropogenic 

contaminants. The study used a combination of networks 

with variations in land use, degree of confinement, and target 

depths, which affected the comparisons among aquifers. This 

range of characteristics, however, allowed the identification of 

several important factors that affect water quality in carbonate 

aquifers. These findings can be used to help those involved in 

the protection and management of these important aquifers.

Acknowledgments

The authors would like to acknowledge the USGS scientists who collected the data used for this report, along with 

the numerous well owners who allowed the sampling to take 

place. The authors would like to thank Kerie Hitt and Naomi 

Nakagaki of the USGS for their work in compiling statistics for the areas around NAWQA wells from national data 

sources. We would also like to thank Lynn Fahlquist (USGS) 

for summarizing land-use and other information for the wells 

used in this study. We also acknowledge the following USGS 

scientists for their technical reviews of the report: Robert 

Gilliom, Neil Dubrovsky, Michael Moran, and Charles Taylor. 

We also acknowledge Eliza Gross of the USGS for GIS assistance in creating maps, and David Weary and Daniel Doctor 

of the USGS for providing their interpretations of the nationalscale mapping of areas of carbonate geology.

References Cited

Adamski, J.C., 1997, Nutrients and pesticides in ground water 

of the Ozark Plateaus in Arkansas, Kansas, Missouri, and 

Oklahoma: U.S. Geological Survey Water-Resources 

Investigations Report 96–4313, 28 p.

Adamski, J.C., 2000, Geochemistry of the Springfield Plateau 

aquifer of the Ozark Plateaus Province in Arkansas, Kansas, 

Missouri, and Oklahoma, USA: Hydrological Processes, 

v. 14, p. 849–866.

Adamski, J.C., Petersen, J.C., Freiwald, D.A., and Davis, J.V., 

1995, Environmental and hydrologic setting of the Ozark 

Plateaus study unit, Arkansas, Kansas, Missouri, and Oklahoma: U.S. Geological Survey Water-Resources Investigations Report 94–4022, 69 p.

Adamski, J.C., and Pugh, A.L., 1996, Occurrence of pesticides 

in ground water of the Ozark Plateaus Province: Journal of the American Water Resources Association, v. 32, 

p. 97–105.

Barbash, J.E., and Resek, E.A., 1996, Pesticides in ground 

water—Distribution, trends, and governing factors: Chelsea, Mich., Ann Arbor Press, 598 p.

Barker, R.A., and Ardis, A.F., 1996, Hydrogeologic framework of the Edwards-Trinity aquifer system, West-Central 

Texas: U.S. Geological Survey Professional Paper 

1421-B, 61 p.

Berndt, M.P., Hatzell, H.H., Crandall, C.A., Turtora, M., 

Pittman, J.R., and Oaksford, E.T., 1998, Water quality in 

the Georgia-Florida Coastal Plain, Georgia and Florida, 

1992–96: U.S. Geological Survey Circular 1151, 34 p.

Berndt, M.P., Katz, B.G., Lindsey, B.D., Ardis, A.F., and 

Skach, K.A., 2005, Comparison of water chemistry in 

spring and well samples from selected carbonate aquifers in 

the United States, in Kuniansky, E.L., ed., U.S. Geological 

Survey Karst Interest Group Proceedings, Rapid City, South 

Dakota, September 12–15, 2005: U.S. Geological Survey 

Scientific Investigations Report 2005–5160, p. 74–81.

Bouwer, H., 1990, Agricultural chemicals and groundwater 

quality: Journal of Soil and Water Conservation, v. 45, 

no. 2, p. 184–189.
References Cited 111

Bradner, Anne, McPherson, B.F., Miller, R.L., Kish, George, 

and Bernard, Bruce, 2005, Quality of ground water in 

the Biscayne aquifer in Miami-Dade, Broward, and Palm 

Beach Counties, Florida, 1996–1998, with emphasis on 

contaminants: U.S. Geological Survey Open-File Report 

2004–1438, 20 p.

Brahana, J.V., and Bradley, M.W., 1986a, Preliminary delineation and description of the regional aquifers of Tennessee—

Highland Rim Aquifer System: U.S. Geological Survey 

Water-Resources Investigations Report 82–4054, 38 p.

Brahana, J.V., and Bradley, M.W., 1986b, Preliminary delineation and description of the regional aquifers of Tennessee—

The central basin aquifer system: U.S. Geological Survey 

Water-Resources Investigations Report 82–4002, 35 p.

Brahana, J.V., Thrailkill, J., Freeman, T., and Ward, W.C., 

1988, Carbonate rocks, in Back, W., Rosenshein, J.S., and 

Seaber, P.R., eds., The geology of North America, v. O-2, 

Hydrogeology: Boulder, Colo., Geological Society of 

America, p. 333–352.

Briel, L.I., 1997, Water quality in the Appalachian Valley and 

Ridge, the Blue Ridge, and the Piedmont Physiographic 

Provinces, eastern United States: U.S. Geological Survey 

Professional Paper 1422-D, 115 p.

Bush, P.W., Ardis, A.F., Fahlquist, Lynne, Ging, P.B., Hornig, 

C.E., and Lanning-Rush, Jennifer, 2000, Water quality in 

south-central Texas, Texas, 1996–98: U.S. Geological 

Survey Circular 1212, 32 p.

Carter, J.M., Lapham, W.W., and Zogorski, J.S., 2008, Occurrence of volatile organic compounds in aquifers of the 

United States., Journal of the American Water Resources 

Association (JAWRA), v. 44, no. 2, p. 399–416.

Chapelle, F.H., 1993, Ground-water microbiology and geochemistry, John Wiley and Sons: New York, 448 p.

Charlton, S.R., and Parkhurst, D.L., 2002, PHREEQCI—

A graphical user interface to the geochemical model 

PHREEQC: U.S. Geological Survey Fact Sheet 031–02, 

2 p.

Connor, B.F., Rose, D.L., Noriega, M.C., Murtagh, L.K., and 

Abney, S.R., 1998, Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory—determination of 86 Volatile Organic compounds in water by gas 

chromatography⁄mass spectrometry, including detections 

less than reporting limits: U.S. Geological Survey OpenFile Report 97–829, 78 p.

Cook, P.G., and Böhlke, J.K., 2000, Determining timescales 

for groundwater flow and solute transport, in Cook, P.G., 

and Herczeg, A.L., eds., Environmental tracers in subsurface hydrology: Kluwer Academic Publishers, p. 1–30.

Cox, D.R., and Snell, E.J., 1989, Analysis of binary data (3d 

ed.): CRC Press, 236 p.

Davies, W.E., 1970, Karstlands and cavern areas, in The 

National Atlas of the United States of America: United 

States Department of the Interior, Geological Survey, p. 77, 

scale 1:17,000,000.

Davies, W.E., Simpson, J.H., Ohlmacher, G.C., Kirk, W.S., 

and Newton, E.G., 1984, Engineering aspects of karst, 

national atlas, 38077-AWNA-07M-00, 1 sheet p.

Fenneman, N.M., and Johnson, D.W., 1946, Physical division of the United States: U.S. Geological Survey, scale 

1:7,000,000, 1 sheet.

Ferrari, M.J., and Ator, S.W., 1995, Nitrate in ground water 

in the Great Valley carbonate subunit of the Potomac River 

Basin: U.S. Geological Survey Water-Resources Investigations Report 95–4099, 6 p.

Field, M.S., 2002, A lexicon of cave and karst terminology 

with special reference to karst hydrology: Washington, 

D.C., National Center for Environmental Assessment, 

Office of Research and Development, U.S. Environmental 

Protection Agency, EPA/600/R-02/003, 214 p.

Fischer, J.M., 1999, National Water-Quality Assessment Program, Delaware River Basin: U.S. Geological Survey Fact 

Sheet 056–99, 6 p.

Florida Department of Environmental Protection, 2007, 

Wakulla Spring—A giant among us: Florida’s Springs, 

accessed October 2007 at http://www.floridasprings.org/

exploration/featured/wakulla/.

Focazio, M.J., Plummer, L.N., Böhlke, J.K., Busenberg, 

E., and Bachman, L.J., 1998, Preliminary estimates of 

residence times and apparent ages of ground water in the 

Chesapeake Bay watershed, and water quality from a survey 

of springs: U.S. Geological Survey Water-Resources 

Investigations Report 97–4225, 75 p.

Focazio, M.J., Reilly, T.E., Rupert, M.G., and Helsel, D.R., 

2002, Assessing ground-water vulnerability to contamination—Providing scientifically defensible information for 

decision makers: U.S. Geological Survey Circular 1224, 

33 p.

Fong, A.L., Andrews, W.J., and Stark, J.R., 1997, Groundwater quality in the Prairie du Chien-Jordan/Trempealeau 

Aquifer in Minnesota and Wisconsin, 1996: Program and 

Abstracts of the 42nd Annual Midwest Groundwater Conference, Coralville, IA, October 22–24, 1997, p. 18.
112 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Fong, A.L., Andrews, W.J., and Stark, J.R., 1998, Waterquality assessment of part of the Upper Mississippi River 

Basin, Minnesota and Wisconsin—Ground-water quality in 

the Prairie du Chien-Jordan aquifer, 1996: U.S. Geological Survey Water-Resources Investigations Report 98–4248, 

45 p.

Gebert, W.A., Graczyk, D.J., and Krug, W.R., 1987, Average 

annual runoff in the United States 1951–80: U.S. Geological Survey Hydrologic Investigations Atlas 710, scale 

1:7,500,000, 1 sheet [digital data], accessed June 13, 2002, 

at http://water.usgs.gov/lookup/getspatial?runoff

GeoLytics, 2001, CensusCD 2000/Short Form Blocks: East 

Brunswick, N.J., GeoLytics [digital data on CDROM].

Giese, G.L., Eimers, J.L., and Coble, R.W., 1997, Simulation 

of ground-water flow in the coastal plain aquifer system 

of North Carolina: U.S. Geological Survey Professional 

Paper 1404-M, 142 p.

Gilliom, R.J., Barbash, J.E., Crawford, C.G., Hamilton, P.A., 

Martin, J.D., Nakagaki, Naomi, Nowell, L.H., Scott, J.C., 

Stackelberg, P.E., Thelin, G.P., and Wolock, D.M., 2006, 

The quality of our Nation’s waters—Pesticides in the 

Nation’s streams and ground water, 1992–2001: U.S. Geological Survey Circular 1291, 172 p., accessed December 

18, 2007, at http://pubs.water.usgs.gov/circ1291/.

Graham, R.C., Ulery, A.L., Neal, R.H., and Teso, R.R., 1992, 

Herbicide residue distributions in relation to soil morphology in two California vertisols: Soil Science, v. 153, no. 2, 

p. 115–121.

Groschen, G.E., 1996, Hydrogeologic factors that affect the 

flowpath of water in selected zones of the Edwards aquifer, San Antonio region, Texas: U.S. Geological Survey 

Water-Resources Investigations Report 96–4096, 73 p.

Hallberg, G.R., and Keeney, D.R., 1993, Nitrate, in Alley, 

W.M., ed., Regional ground-water quality: New York, Van 

Nostrand Reinhold, 634 p.

Hampson, P.S., Treece, M.W., Jr., Johnson, G.C., Ahlstedt, 

S.A., and Connell, J.F., 2000, Water quality in the Upper 

Tennessee River Basin, Tennessee, North Carolina, Virginia, 

and Georgia 1994–98: U.S. Geological Survey Circular 

1205, 32 p.

Harrill, J.R., and Prudic, D.E., 1998, Aquifer systems in the 

Great Basin region of Nevada, Utah, and adjacent states; 

Summary report: U.S. Geological Survey Professional 

Paper 1409-A, 66 p.

Helsel, D.R., and Hirsch, R.W., 2002, Statistical methods in 

water resources: Techniques of Water-Resources Investigations of the United States Geological Survey, Book 4, 

Hydrologic Analysis and Interpretation, Chapter A3, 510 p.

Hershey, H.G., 1969, Geologic map of Iowa: Iowa Geological Survey, 1 sheet.

Hosmer, D.W., and Lemeshow, S., 1989, Applied logistic 

regression: New York, Wiley and Sons, 307 p.

Imes, J.L., 1987, Major geohydrologic units in and adjacent 

to the Ozark Plateau Province, Missouri, Arkansas, Kansas, 

Oklahoma; Ozark aquifer: U.S. Geological Survey Hydrologic Atlas 711-E, scale 1:750,000.

Imes, J.L., and Emmett, L.F., 1994, Geohydrology of the 

Ozark Plateaus aquifer system in parts of Missouri, Arkansas, Oklahoma, and Kansas: U.S. Geological Survey 

Professional Paper 1414-D, 127 p.

Johnson, G.C., 2002, Water quality of springs in the Valley 

and Ridge Physiographic Province in the Upper Tennessee River Basin, 1997: U.S. Geological Survey WaterResources Investigations Report 02–4180, 24 p.

Johnston, R.H., and Bush, P.W., 1988, Summary of the hydrology of the Floridan aquifer system in Florida and in parts of 

Georgia, South Carolina, and Alabama: U.S. Geological 

Survey Professional Paper 1403-A, 24 p., 4 pls.

Kalkhoff, S.J., Barnes, K.K., Becher, K.D., Savoca, M.E., 

Schnoebelen, D.J., Sadorf, E.M., Porter, S.D., and Sullivan, 

D.J., 2000, Water quality in the Eastern Iowa Basins, Iowa 

and Minnesota, 1996–98: U.S. Geological Survey Circular 

1210, 37 p., available online at http://pubs.water.usgs.gov/

circ1210/.

Katz, B.G., 1992, Hydrochemistry of the Upper Floridan 

aquifer, Florida: U.S. Geological Survey Water-Resources 

Investigations Report 91–4196, 37 p.

Katz, B.G., Crandall, C.A., Metz, P.A., McBride, W.S., and 

Berndt, M.P., 2007, Chemical characteristics, water sources 

and pathways, and age distribution of ground water in the 

contributing recharge area of a public-supply well near 

Tampa, Florida, 2002–05: U.S. Geological Survey Scientific Investigations Report 2007–5139, 83 p.

Kaufman, D.D., and Kearney, P.C., 1970, Microbial degradation of s-triazine herbicides: Residue Reviews, v. 32, 

p. 235–265.

Kingsbury, J.A., Hoos, A.B., and Woodside, M.D., 1999, 

Environmental setting and water-quality issues in the lower 

Tennessee River basin: U.S. Geological Survey WaterResources Investigations Report 99–4080, 44 p.

Kingsbury, J.A., and Shelton, J.M., 2002, Water quality of the 

Mississippian carbonate aquifer in parts of middle Tennessee and northern Alabama, 1999: U.S. Geological Survey 

Water-Resources Investigations Report 02–4083, 36 p.
References Cited 113

Koterba, M.T., Wilde, F.D., and Lapham, W.W., 1995, 

Ground-water data-collection protocols and procedures for 

the National Water-Quality Assessment Program—Collection and documentation of water-quality samples and 

related data: U.S. Geological Survey Open-File Report 

95–399, 113 p.

Langmuir, D., 1971, The geochemistry of some carbonate 

ground waters in central Pennsylvania: Geochimica et 

Cosmochimica Acta, v. 35, p. 1023–1045.

Lindsey, B.D., Falls, W.F., Ferrari, M.J., Zimmerman, T.M., 

Harned, D.A., Sadorf, E.M., and Chapman, M.J., 2006, 

Factors affecting occurrence and distribution of selected 

contaminants in ground water from selected areas in the 

Piedmont aquifer system, eastern United States, 1993–

2003: U.S. Geological Survey Scientific Investigations 

Report 2006–5104, 72 p.

Lindsey, B.D., Loper, C.A., and Hainly, R.A., 1997, Nitrate in 

ground water and stream base flow in the Lower Susquehanna River Basin, Pennsylvania and Maryland: U.S. 

Geological Survey Water-Resources Investigations Report 

97–4146, 66 p.

Ludington, S., Moring, B.C., Miller, R.J., Stone, P.A., Bookstrom, A.A., Bedford, D.R., Evans, J.G., Haxel, G.A., Nutt, 

C.J., Flyn, K.S., and Hopkins, M.J., 2007, Preliminary 

integrated geologic map databases for the United States, 

Western states: California, Nevada, Arizona, Washington, 

Oregon, Idaho, and Utah, Version 1.3: U.S. Geological 

Survey Open-File Report 2005–1305, accessed October 31, 

2008, at http://pubs.usgs.gov/of/2005/1305/.

Maclay, R.W., 1995, Geology and hydrology of the Edwards 

aquifer in the San Antonio area, Texas: U.S. Geological 

Survey Water-Resources Investigations Report 95–4186, 

64 p.

Maclay, R.W., and Land, L.F., 1988, Simulation of flow in the 

Edwards aquifer, San Antonio region, Texas, and refinement 

of storage and flow concepts: U.S. Geological Survey 

Water-Supply Paper 2336-A, 48 p.

Maclay, R.W., and Small, T.A., 1983, Hydrostratigraphic 

subdivision and fault barriers of the Edwards aquifer, southcentral Texas, U.S.A., in Back, W., and LaMoreaux, P.E., 

eds., V.T. Stringfield Symposium, Process in karst hydrology: Journal of Hydrology, v. 61, p. 127–146.

Marella, R.L., 2004, Water withdrawals, use, discharge, and 

trends in Florida, 2000: U.S. Geological Survey Scientific 

Investigations Report 2004–5151, 90 p.

Marella, R.L., and Berndt, M.P., 2005, Water withdrawals and 

trends from the Floridan aquifer system in the southeastern 

United States, 1950–2000: U.S. Geological Survey Circular 1278, 20 p.

Martin, J.D., 1999, Quality of pesticide data for environmental water samples collected for the National Water-Quality 

Assessment Program, 1992–96, and examples of the use 

of quality-control information in water-quality assessments: accessed Jan. 21, 2007, at http://ca.water.usgs.gov/

pnsp/rep/qcsummary/.

Martin, J.D., Gilliom, R.J., and Schertz, Terry, 1998, Summary 

and evaluation of pesticides in field blanks collected for 

the National Water-Quality Assessment Program, 1992–

1995: U.S. Geological Survey Open-File Report 98–412, 

102 p.

Maupin, M.A., and Barber, N.L., 2005, Estimated withdrawals 

from principal aquifers in the United States, 2000: U.S. 

Geological Survey Circular 1279, 46 p.

McMahon, P.B., and Chapelle, F.H., 2008, Redox processes 

and water quality of selected principal aquifer systems: Ground Water, v. 46, no. 2, p. 259–271.

McPherson, B.F., Miller, R.L., Haag, K.H., and Bradner, 

Anne, 2000, Water-quality in southern Florida; Florida, 

1996–98: U.S. Geological Survey Circular 1207, 32 p., 

available online at http://pubs.water.usgs.gov/circ1207/.

Meinzer, O.E., 1927, Large springs in the United States: U.S. 

Geological Survey Water-Supply Paper 557, 94 p.

Metz, P.A., Delzer, G.C., Berndt, M.P., Crandall, C.A., and 

Toccalino, P.L., 2007, Anthropogenic organic compounds 

in ground water and finished water of community water 

systems in the northern Tampa Bay Area, Florida, 2002–

04: U.S. Geological Survey Scientific Investigations 

Report 2006–5267, 48 p.

Miller, J.A., 1986, Hydrogeologic framework of the Floridan 

aquifer system in Florida and in parts of Georgia, South 

Carolina, and Alabama: U.S. Geological Survey Professional Paper 1403-B, 91 p., 33 pls.

Miller, J.A., 1990, Ground water atlas of the United States—

Segment 6, Alabama, Florida, Georgia, South Carolina: U.S. Geological Survey Hydrologic Investigations 

Atlas 730-G, 28 p.

Miller, J.A., 1999, Ground water atlas of the United States, 

Introduction and national summary: U.S. Geological Survey Hydrologic Atlas 730-A, 36 p.

Miller, J.A., and Appel, C.L., 1997, Ground water atlas of 

the United States—Segment 3, Kansas, Missouri, and 

Nebraska: U.S. Geological Survey Hydrologic Investigations Atlas 730-D, 24 p.

Musgrove, M., and Banner, J.L., 2004, Controls on the spatial 

and temporal variability of vadose dripwater goechemistry, 

Edwards aquifer, central Texas: Geochimica et Cosmochimica Acta, v. 68, p. 1,007–1,020.
114 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Nagelkerke, N.J.D., 1991, A note on the general definition 

of the coefficient of determination: Biometricka, v. 66, 

p. 403–412.

Nakagaki, Naomi, and Wolock, D.M., 2005, Estimation of 

agricultural pesticide use in drainage basins using land 

cover maps and county pesticide data: U.S. Geological 

Survey Open-File Report 2005–1188, 46 p.

Nicholson, S.W., Dicken, C.L., Foose, M.P., and Mueller, 

J.A.L., 2007a, Preliminary integrated geologic map databases for the United States: Minnesota, Wisconsin, Michigan, Illinois, and Indiana, Version 1.1: U.S. Geological 

Survey Open-File Report 2005–1355, accessed October 31, 

2008, at http://pubs.usgs.gov/of/2004/1355/.

Nicholson, S.W., Dicken, C.L., Horton, J.D., Foose, M.P., and 

Mueller, J.A.L., and Hon, R., 2007b, Preliminary integrated 

geologic map databases for the United States: Connecticut, 

Maine, Massachusetts, New Hampshire, New Jersey, Rhode 

Island, and Vermont, Version 1.1: U.S. Geological Survey 

Open-File Report 2005–1272, accessed October 31, 2008, 

at http://pubs.usgs.gov/of/2006/1272/.

Nolan, B.T, Hitt, K.J., and Ruddy, B.C., 2002, Probability of 

nitrate contamination of recently recharged ground waters 

in the conterminous United States: Environmental Science 

and Technology, v. 36, no. 10, p. 2138–2145.

Olcott, P.G., 1992, Ground water atlas of the United States—

Iowa, Michigan, Minnesota, Wisconsin: U.S. Geological 

Survey Hydrologic Investigations Atlas 730-J, 31 p.

Parizek, R.R., White, W.B., and Langmuir, D., 1971, Hydrogeology and geochemistry of folded and faulted rocks of 

the central Appalachian type and related land-use problems: Pennsylvania State University Mineral Sciences 

Experimental Station Circular 82, 210 p.

Parkhurst, D.L., and Appelo, C.A.J., 1999, User’s guide to 

PHREEQC (Version 2)—A computer program for speciation, batch reaction, one-dimensional transport, and inverse 

geochemical calculations: U.S. Geological Survey WaterResources Investigations Report 99–4259, 310 p.

Petersen, J.C., Adamski, J.C., Bell, R.W., Davis, J.V., Femmer, 

S.R., Freiwald, D.A., and Joseph, R.L., 1998, Water quality 

of the Ozark Plateaus, Arkansas, Kansas, Missouri, and 

Oklahoma, 1992–95: U.S. Geological Survey Circular 

1158, 33 p.

Peterson, E.W., 2002, Movement of nitrate through regolith 

covered karst terrane, northwest Arkansas: Journal of 

Hydrology, v. 256, p. 35-47.

Planert, Michael, and Williams, J.S., 1995, Ground water 

atlas of the United States—Segment 1, California, 

Nevada: U.S. Geological Survey Hydrologic Investigations Atlas 730-B, 28 p.

Plebuch, R.O., Faust, R.J., Townsend, M.A., 1985, Potentiometric surface and water quality in the Principal Aquifer, 

Mississippian Plateaus region, Kentucky: U.S. Geological 

Survey Water-Resources Investigations Report 84–4102, 

45 p.

Plume, R.W., 1995, Hydrogeologic framework of the Great 

Basin region of Nevada, Utah, and adjacent states: U.S. 

Geological Survey Professional Paper 1409-B, 64 p., 5 pls.

Plummer, L.N., and Sprinkle, C.L., 2001, Radiocarbon dating 

of dissolved inorganic carbon in groundwater from confined 

parts of the Upper Floridan aquifer, Florida, USA: Hydrogeology Journal, v. 9, p. 127–150.

Plummer, L.N., Busenberg, E., Drenkard, S., Schlosser, P., 

Ekwurzel, B., Weppernig, R., McConnell, J.B., and Michel, 

R.L., 1998, Flow of river water into a karstic limestone 

aquifer—2. Dating the young fraction in groundwater 

mixtures in the Upper Floridan aquifer near Valdosta, Georgia: Applied Geochemistry, v. 13, no. 8, p. 1017–1043.

Price, C.V., Nakagaki, Naomi, Hitt, K.J., and Clawges, R.M., 

2007, Enhanced historical land-use and land-cover data sets 

of the U.S. Geological Survey: U.S. Geological Survey 

Data Series 240 [digital data], accessed December 19, 2007, 

at http://pubs.usgs.gov/ds/2006/240/.

Prudic, D.E., Harrill, J.R., and Burbey, T.J., 1995, Conceptual 

evaluation of regional ground-water flow in the carbonaterock province of the Great Basin, Nevada, Utah, and adjacent states: U.S. Geological Survey Professional Paper 

1409-D, 102 p.

Quinlan, J.F., and Ewers, R.O., 1989, Subsurface drainage in 

the Mammoth Cave Area, in White, W.B., and White, E.L., 

eds., Karst hydrology—Concepts from the Mammoth Cave 

Area: New York, Van Nostrand Reinhold, p. 65–103.

Quinlan, J.F., Smart, P.L., Schindel, G.M., Alexander, E.C., 

Edwards, A.J., and Smith, A.R., 1991, Recommended 

administrative/regulatory definition of karst aquifer, 

principles for classification of carbonate aquifers, practical 

evaluation of vulnerability of karst aquifers, and determination of optimum sampling frequency at springs, in Quinlan, 

J.F., and Stanley, A., eds., Hydrology Ecology Monitoring and Management of Ground Water in Karst Terranes. 

Proceedings of the Third Conference, Nashville, Tennessee, National Ground Water Association, Dublin, Ohio, 

p. 573–635.

Radell, M.J., and Katz, B.G., 1991, Major-ion and selected 

trace-metal chemistry of the Biscayne aquifer, southeast 

Florida: U.S. Geological Survey Water-Resources Investigations Report 91–4009, 18 p.

Renken, R.A., 1998, Ground water atlas of the United States—

Segment 5, Arkansas, Louisiana, Mississippi: U.S. Geological Survey Hydrologic Investigations Atlas 730-F, 28 p.
References Cited 115

Renken, R.A., Dixon, Joann, Koehmstedt, John, Lietz, A.C., 

and others, 2005, Impact of anthropogenic development on 

coastal ground-water hydrology in southeastern Florida, 

1900–2000: U.S. Geological Survey Circular 1275, 77 p.

Risser, D.W., and Siwiec, S.F., 1996, Water-quality assessment 

of the Lower Susquehanna River Basin, Pennsylvania and 

Maryland—Environmental setting: U.S. Geological Survey Water-Resources Investigations Report 94–4245, 70 p.

Rose, D.L., and Schroeder, M.P., 1995, Methods of analysis by 

the U.S. Geological Survey National Water Quality Laboratory— determination of volatile organic compounds in 

water by purge and trap capillary gas chromatography⁄mass 

spectrometry: U.S. Geological Survey Open-File Report 

94-708-W, 26 p.

Rosenau, J.C., Faulkner, G.L., Hendry, C.W., Jr., and Hull, 

R.W., 1977, Springs of Florida: Florida Department of 

Natural Resources, Bureau of Geology Bulletin No. 31.

Ruddy, B.C., Lorenz, D.L., and Mueller, D.K., 2006, Countylevel estimates of nutrient inputs to the land surface of the 

conterminous United States, 1982–2001: U.S. Geological 

Survey Scientific Investigations Report 2006–5012, 17 p.

Ryder, P.D., 1996, Ground water atlas of the United States—

Segment 4, Oklahoma, Texas: U.S. Geological Survey 

Hydrologic Investigations Atlas 730-E, 30 p.

SAS Institute Inc., 1989a, SAS/STAT User’s Guide, Fourth 

Edition, Volume 1: Cary, N.C., SAS Institute Inc., 943 p.

SAS Institute Inc., 1989b, SAS/STAT User’s Guide, Fourth 

Edition, Volume 2: Cary, N.C., SAS Institute Inc., 846 p.

Savoca, M.E., Sadorf, E.M., and Akers, K.K., 1999, Groundwater quality in the eastern part of the Silurian-Devonian 

and Upper Carbonate Aquifers in the Eastern Iowa Basins, 

Iowa and Minnesota, 1996: U.S. Geological Survey 

Water-Resources Investigations Report 98–4224, 31 p.

Scanlon, B.R., 1989, Physical controls on hydrochemical 

variability in the Inner Bluegrass Karst Region of Central 

Kentucky: Ground Water, v. 27, no. 5, p. 639–646.

Scanlon, B.R., 1990, Relationships between groundwater 

contamination and major ion chemistry in a karst aquifer: Journal of Hydrology, v. 119, p. 271–291.

Scanlon, B.R., and Thrailkill, J., 1987, Chemical similarities 

among physically distinct spring types in a karst terrain: Journal of Hydrology, v. 89, p. 259–279.

Schaefer, D.H., Thiros, S.A., and Rosen, M.R., 2005, Groundwater quality in the carbonate-rock aquifer of the Great 

Basin, Nevada and Utah: U.S. Geological Survey Scientific Investigations Report 2005–5232, 32 p.

Schnoebelen, D.J., Becher, K.D., Bobier, M.W., and Wilton, 

Thomas, 1999, Selected nutrients and pesticides in streams 

of the Eastern Iowa Basins, 1970–95: U.S. Geological 

Survey Water-Resources Investigations Report 99–4028, 

65 p.

Schwarz, G.E., and Alexander, R.B., 1995, State Soil Geographic (STATSGO) Data Base for the conterminous United 

States: U.S. Geological Survey Open-File Report 95–449, 

accessed December 19, 2007, at http://water.usgs.gov/GIS/

metadata/usgswrd/XML/ussoils.xml

Seybold, C.A., and Mersie, W., 1999, Metolachlor fate and 

mobility in a tidal wetland soil: Wetlands, v. 19, no. 1, 

p. 228–235.

Shaffer, N.R., Sowder, K.H., Weibel, C.P., Wolfe, M.E., and 

Paylor, R.L., 2007, Map showing industrial minerals operations and carbonate regions affected by solution features in 

Illinois, Indiana, Kentucky, and Ohio: Indiana Geological 

Survey Open-File Study 07–02.

Sprinkle, C.L., 1989, Geochemistry of the Floridan aquifer 

system in Florida and parts of Georgia, South Carolina, 

and Alabama: U.S. Geological Survey Professional Paper 

1403-I, 105 p., 9 pls.

Spruill, T.B., Harned, D.A., Ruhl, P.M., Eimers, J.L., McMahon, G., Smith, K.E., Galeone, D.R., and Woodside, M.D., 

1998, Water quality in the Albemarle-Pamlico Drainage 

Basin, North Carolina and Virginia, 1992–95: U.S. Geological Survey Circular 1157, 36 p.

Squillace, P.J., and Moran, M.J., 2006, Factors associated with 

sources, transport, and fate of volatile organic compounds in 

aquifers of the United States and implications for groundwater management and assessments: U.S. Geological 

Survey Scientific Investigations Report 2005–5269, 40 p.

Stoeser, D.B., Green, G.N., Morath, L.C., Heran, W.D., 

Wilson, A.B., Moore, D.W., and Van Gosen, B.S., 2007, 

Preliminary integrated geologic map databases for the 

United States, Central states: Montana, Wyoming, Colorado, New Mexico, North Dakota, South Dakota, Nebraska, 

Kansas, Oklahoma, Texas, Iowa, Missouri, Arkansas, and 

Louisiana, Version 1.2: U.S. Geological Survey OpenFile Report 2005–1351, accessed October 31, 2008, at 

http://pubs.usgs.gov/of/2005/1351/.

Stumm, Werner, and Morgan, J.J., 1981, Aquatic chemistry: New York, John Wiley and Sons, 780 p.

Swain, L.A., Mesko, T.O., and Hollyday, E.F., 2004, Summary of the hydrogeology of the Valley and Ridge, Blue 

Ridge, and Piedmont Physiographic Provinces in the eastern 

United States: U.S. Geological Survey Professional Paper 

1422-A, 23 p.
116 Factors Affecting Water Quality in Selected Carbonate Aquifers in the United States, 1993–2005 

Taglioli, B.L., Delzer, G.C., and Zogorski, J.S., 2000, Study 

Design and Analytical Results Used to Evaluate Carry-over 

Contamination by VOCs in Surface- and Ground-water 

Sampling Procedure: U.S. Geological Survey Open File 

Report 2000–384, 36 p.

Thomas, J.M., Mason, J.L., and Crabtree, J.D., 1986, Groundwater levels in the Great Basin region of Nevada, Utah, 

and adjacent states: U.S. Geological Survey Hydrologic 

Investigations Atlas 694-B, scale 1:1,000,000, 2 sheets.

Thomas, J.M., Welch, A.H., and Dettinger, M.D., 1996, Geochemistry and isotope hydrology of representative aquifers 

in the Great Basin region of Nevada, Utah, and adjacent 

states: U.S. Geological Survey Professional Paper 1409-

C, 100 p.

Toccalino, P.L., Norman, J.E., Booth, N.L., and Zogorski, J.S., 

2007, Health-based screening levels—A tool for evaluating 

what water-quality data may mean to human health: U.S. 

Geological Survey, National Water-Quality Assessment 

Program, accessed June 5, 2007, at http://water.usgs.gov/

nawqa/HBSL/.

Toccalino, P.L., Norman, J.E., Phillips, R.H., Kauffman, L.J., 

Stackelberg, P.E., Nowell, L.H., Krietzman, S.J., and Post, 

G.B., 2004, Application of health-based screening levels to 

ground-water quality data in a state-scale pilot effort: U.S. 

Geological Survey Scientific Investigations Report 2004–

5174, 64 p.

Toccalino, P.L., Rowe, B.L., and Norman, J.E., 2006, Volatile 

organic compounds in the Nation’s drinking-water supply 

wells—What findings may mean to human health: U.S. 

Geological Survey Fact Sheet 2006–3043, 4 p.

Trapp, Henry, Jr., and Horn, M.A., 1997, Ground water atlas 

of the United States—Delaware, Maryland, New Jersey, 

North Carolina, Pennsylvania, Virginia, and West Virginia: U.S. Geological Survey Hydrologic Investigations 

Atlas HA 730-L, 24 p.

Trapp, Henry, Jr., and Meisler, Harold, 1992, The Regional 

Aquifer system underlying the Northern Atlantic Coastal 

Plain in parts of North Carolina, Virginia, Maryland, 

Delaware, New Jersey, and New York—Summary: U.S. 

Geological Survey Professional Paper 1404-A, 33 p.

Tucci, Patrick, and McKay, R.M., 2006, Hydrogeology and 

simulation of ground-water flow in the Silurian-Devonian 

Aquifer System, Johnson County, Iowa: U.S. Geological 

Survey Scientific Investigations Report 2005–5266, 78 p.

U.S. Bureau of the Census, 1990, Cartographic boundary 

files—1990 Census block group [digital data]: accessed 

February 14, 2003, at http://www.census.gov/geo/www/cob/

bg1990.html

U.S. Bureau of the Census, 1991, Census of population and 

housing, 1990—Public Law (P.L.) 94–171 [digital data on 

CDROM]: Washington, D.C., U.S. Bureau of the Census.

U.S. Bureau of the Census, 1992, Census of population 

and housing—Summary tape file 3A [digital data on 

CDROM]: Washington, D.C., U.S. Bureau of the Census.

U.S. Bureau of the Census, 2001, Cartographic boundary 

files—2000 Census block group [digital data]: accessed 

August 2002 at http://www.census.gov/geo/www/cob/

bg2000.html

U.S. Department of Agriculture, Natural Resources Conservation Service, 1994, State Soil Geographic (STATSGO) data 

base for the United States and Puerto Rico [digital data on 

CDROM]: Fort Worth, Tex., U.S. Department of Agriculture.

U.S. Department of Agriculture, 2007, National engineering 

handbook, Part 630 Hydrology, Chapter 7 Hydrologic soil 

groups: Washington, D.C., U.S. Department of Agriculture, Natural Resources Conservation Service, NEH 630.07, 

14 p.

U.S. Department of Commerce, 1995, Climatology of the 

United States: Monthly station normals for temperature, precipitation, and heating and cooling degree days, 

1961–90, TD-9641: Asheville, North Carolina, National 

Climatological Data Center, (digital data set).

U.S. Environmental Protection Agency, 2002, Onsite Wastewater Treatment Systems Manual: Office of Water, Office 

of Research and Development Report EPA/625/R-00/008, 

175 p.

U.S. Environmental Protection Agency, 2006, 2006 Edition of 

the drinking water standards and health advisories: Washington, D.C., U.S. Environmental Protection Agency, Office 

of Water, EPA 822-R-06-013, 18 p

U.S. Geological Survey, 1986, National water summary1985; 

Hydrologic events and surface-water resources: U.S. Geological Survey Water-Supply Paper 2300, 506 p.

U.S. Geological Survey, 1999, National land cover data 

(NLCD) [digital data]: accessed June 16, 2005, at 

http://edc.usgs.gov/products/landcover/nlcd.html

U.S. Geological Survey, 2003, Principal aquifers of the 48 

conterminous United States, Hawaii, Puerto Rico, and 

the U.S. Virgin Islands: accessed February 2005 at 

http://www.nationalatlas.gov/mld/aquifrp.html

U.S. Geological Survey, 2005, Preliminary integrated geologic 

map databases for the United States: U.S. Geological 

Survey Open-File Report 2005–1351, 44 p.
References Cited 117

Vista Information Solutions, 1999, StarView Real Estate Version 2.6.1, Users Guide: Vista Information Solutions, San 

Diego, Calif., 228 p.

Vogelmann, J.E., Howard, S.M., Yang, L., Larson, C.R., 

Wylie, B.K., and VanDriel, N., 2001, Completion of the 

1990’s national land cover dataset for the conterminous 

United States from Landsat Thematic Mapper data and 

ancillary data sources: Photogrammetric Engineering and 

Remote Sensing, v. 67, p. 650–662.

Waterloo Hydrogeologic Inc., 2005, Aquachem Version 5.0 

User’s Manual: Waterloo, Ontario, Waterloo Hydrogeologic, Inc., 328 p.

Weary, D.J., 2006, Compilation of national-scale karst data by 

the U.S. Geological Survey with emphasis on the southeastern United States: Geological Society of America Southeastern Section meeting, Abstracts with Programs, v. 38, 

no. 3, p. 84.

Weary, D.J, 2008, Preliminary map of potentially karstic 

carbonate rocks in the central and southern Appalachian 

states: U.S. Geological Survey Open-File Report 2008–

1154, accessed October 31, 2008, at http://pubs.usgs.gov/

of/2008/1154/.

Webbers, Ank, 2003, Ground-water use by public water-supply systems in Tennessee, 2000: U.S. Geological Survey 

Open-File Report 03-47, 90 p.

White, W.B., 1988, Geomorphology and hydrology of karst 

terrains: New York, Oxford University Press, 464 p.

White, W.B., 1993, Analysis of Karst Aquifers, in Alley, W.M., 

Regional ground water quality: New York, Van Nostrand 

Reinhold, 634 p.

Winner, M.D., Jr., and Coble, R.W., 1996, Hydrogeologic 

framework of the North Carolina Coastal Plain: U.S. Geological Survey Professional Paper 1404-I, 106 p. 

Winograd, I.J., and Thordardson, William, 1975, Hydrogeologic and hydrochemical framework, south-central Great 

Basin, Nevada-California, with special reference to the 

Nevada Test Site: U.S. Geological Survey Professional 

Paper 712-C, 125 p.

Wolock, D.M., 1997, STATSGO soil characteristics for the 

conterminous United States: U.S. Geological Survey 

Open-File Report 97–656 [digital data], accessed February 

17, 2004, at http://water.usgs.gov/lookup/getspatial?muid

Wolock, D.M., 2003a, Saturation overland flow estimated by 

TOPMODEL for the conterminous United States: U.S. 

Geological Survey Open-File Report 03–264, digital 

data set, available online at http://water.usgs.gov/lookup/

getspatial?satof48

Wolock, D.M., 2003b, Infiltration-excess overland flow 

estimated by TOPMODEL for the conterminous United 

States: U.S. Geological Survey Open-File Report 03–310, 

digital data set, available online at http://water.usgs.gov/

lookup/getspatial?ieof48

Wolock, D.M., 2003c, Estimated mean annual natural groundwater recharge in the conterminous United States: U.S. 

Geological Survey Open-File Report 03–311, digital 

data set, available online at http://water.usgs.gov/lookup/

getspatial?rech48grd

Woodside, M.D., Hoos, A.B., Kingsbury, J.A., Powell, J.R., 

Knight, R.R., J Garrett, J.W., Mitchell, R.L., III, and Robinson, J.A., 2004, Water quality in the Lower Tennessee 

River Basin, Tennessee, Alabama, Kentucky, Mississippi, 

and Georgia, 1999–2001: U.S. Geological Survey Circular 

1233, 34 p.

Young, H.L., 1992, Hydrogeology of the Cambrian-Ordovician aquifer system in the northern Midwest, United 

States: U.S. Geological Survey Professional Paper 

1405-A, 55 p.

Young, H.L., and Siegel, D.I., 1992, Hydrogeology of the 

Cambrian-Ordovician aquifer system in the northern Midwest, United States, with a section on ground-water quality: U.S. Geological Survey Professional Paper 1405-B, 

99 p, 1 pl.

Zaugg, S.D., Sandstrom, M.W., Smith, S.G., and Fehlberg, 

K.M., 1995, Methods of analysis by the U.S. Geological 

Survey National Water Quality Laboratory—Determination of pesticides in water by C-18 solid-phase extraction 

and capillary-column gas chromatography/mass spectrometry with selected-ion monitoring: U.S. Geological 

Survey Open-File Report 95–181, 49 p., available online 

at http://wwwnwql.cr.usgs.gov/Public/pubs/OFR95-181/

OFR95-181.html

Zogorski, 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.

Lindsey—Factors Affecting Water Quality in Selected Carbonate Aquifers in the Untied States, 1993–2005—Scientific Investigations Report 2008-5240

50s

44

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48

40

40 54

47

40

49

33

39

39

47

42s

42

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EXPLANATION

Carbonate-rock Aquifers

42 Basin and Range carbonate-rock aquifers 42s Basin and Range carbonate-rock aquifers - Subcrop area

51 Biscayne aquifer

54 Castle Hayne aquifer

50 Floridan aquifer system 50s Floridan aquifer system - Subcrop area

48 Ordovician aquifers

44 Ozark Plateaus aquifer system

53 Piedmont and Blue Ridge carbonate-rock aquifers

47 Silurian-Devonian aquifers 49 Upper carbonate aquifer

Sandstone and Carbonate-rock Aquifers

38 Edwards-Trinity aquifer system

40 Mississippian aquifers

39 Valley and Ridge aquifers -- Carbonate-rock aquifer

33 Cambrian-Ordovician aquifer system - Prairie du Chien