v>EPA
United States
Environmental Protection
Agency
Office of Research and
Development
Washington DC 20460
EPA/600/R-98/025
March 1998
A Field Study to Compare
Performance of Stainless
Steel Research Monitoring
Wells with Existing
On-Farm Drinking Water
Wells in Measuring
Pesticide and Nitrate
Concentrations
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EPA/600/R-98/025
March 1998
A FIELD STUDY TO COMPARE
PERFORMANCE OF STAINLESS
STEEL RESEARCH MONITORING
WELLS WITH EXISTING ON-FARM
DRINKING WATER WELLS IN
MEASURING PESTICIDE AND
NITRATE CONCENTRATIONS
by
Charles N. Smith, William R.Payne, Jr.1, John D. Pope Jr.1,
Jonathan H. Winkie1 and Rudolph S. Parrish2
1 Ecosystems Research Division
National Exposure Research Laboratory
U.S. Environmental Protection Agency
Athens, Georgia 30605-2700
2SQC Systems, INC.
2351 College Station Road
Athens, Georgia 30605
National Exposure Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Printed on Recycled Paper
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Notice
The U. S. Environmental Protection Agency through its Office of Research and
Development funded and managed the research described here. It has been subjected to the
Agency's peer and administrative review and has been approved for publication as an EPA
document.
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DISCLAIMER
This report was prepared and reviewed by the National Exposure Research Laboratory's
Ecosystems Research Division in Athens Georgia, and approved for publication.
This paper reports the results of research only. Mention of trade names, products, or
services does not convey, and should not be interpreted as conveying, official EPA approval,
endorsement or recommendation by the U. S. Environmental Protection Agency.
in
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FOREWORD
As environmental controls become more costly to implement and the penalties of
judgement errors become more severe, environmental quality management requires more
efficient management tools based on greater knowledge of the environmental phenomena to be
managed. The National Exposure Research Laboratory's Ecosystems Research Division (ERD)
in Athens, GA, conducts research on organic and inorganic pollutants and land use perturbations
that create direct and indirect, chemical and non-chemical stressor exposures and potential risks
to humans and ecosystems. Athens-ERD conducts experimental field research, model
development and field testing, to produce integrated analysis frameworks and systems models
to assess the exposure and response to stressors of ecological and human exposure at regional,
basin and watershed scales.
Because of the toxicity and persistence of agricultural chemicals (pesticides, nutrients)
and their extensive use in modern agriculture, the leaching of these chemicals from agricultural
fields and the resulting concentrations in ground water are an environmental concern. The Little
Coharie Watershed located in Sampson County, North Carolina, is an excellent watershed to
conduct ground water contamination exposure research given the wide diversity of agriculture
and landowner cooperation. Results of this study indicate that rural areas of the southeastern
coastal plains are particularly vulnerable to ground water contamination due to multiple cropping
systems; large poultry, swine, and cattle operations; wide use of agricultural chemicals; shallow
ground water; coarse-textured soil; and high rainfall.
The report is intended to provide guidance on whether adequate ground water quality
information can be obtained from routinely installed drinking water wells in place of stainless-
steel research monitoring wells.
Rosemarie C. Russo, Ph.D.
Director
Ecosystems Research Division
Athens, Georgia
IV
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ABSTRACT
Existing drinking water wells are widely used for the collection of ground water samples
to evaluate chemical contamination. The well comparison study reported here was conducted
to compare pesticide and nitrate data from specially designed stainless-steel research
monitoring wells with data from nearby existing on-farm drinking water wells. Results could help
to determine whether adequate information for contamination can be obtained from routinely
installed drinking water wells for use in making decisions and for development of future study
designs (e.g., should wells be monitoring wells or existing wells). The study was conducted in
the Little Coharie Watershed, a 158.2 square mile area located in the coastal plain region of
eastern North Carolina. A total of 99 wells were used for monitoring nitrate-nitrogen and
screening for 21 pesticides over 6 sampling dates (Mar93, Jul93, Nov93, Mar94, May94, Jun94).
Data were collected from 21 research wells and 78 existing on-farm wells located at 74 sites
within the watershed.
Statistical analysis indicates that research monitoring wells provide a greater probability
of detecting pesticides in ground water than existing on-farm wells. Thirty percent of all wells
sampled had observed pesticide residues for at least one sampling date, but only 2% of the
pesticides detected exceeded the maximum contaminant level (MCL). Pesticides were found in
52% of the research wells (none exceeding the MCL) versus 23% of the existing wells. Two
existing wells had pesticide concentrations exceeding the MCL (atrazine 6.5 ppb, and alachlor
6.2 ppb). The ranges of concentrations for the other pesticides frequently found were 2.3-18.3
ppb for carbofuran; 0.2-63.7 ppb for metolachlor; 0.8-4.3 ppb for fluometuron; and 0.2-0.7 ppb
formethomyl.
Percentage of Wells with Detectable Pesticides
Atrazine
Fluometuron
Carbofuran
Metolachlor
Alachlor
Carbaryl
14.0%
6.2%
5.3%
5.3%
3.0%
2.0%
Methomyl 2.0%
Butylate 1.0%
Chlorothalonil 1.0%
Linuron 1.0%
Simazine 1.0%
Pesticides detected in a well were usually found in samples taken at repeated sampling
events and in some cases multiple residues were observed. Detectable pesticide levels were
found more frequently during June and July sampling events than during other months. No
pesticides were found in wells greater than 80 feet deep. The pesticides found are used on
tobacco, cotton, corn, soybeans, and vegetables. The data indicate that research wells and on-
farm wells near soybean crops are more likely to have detectable pesticides. There is a much
weaker indication that sites near cotton also are more likely to have detectable pesticides, and
there is a similarly weak indication that a nearby tobacco crop tends to decrease the likelihood of
detecting pesticides.
Results of 6 sampling events showed 97% of all wells had observed concentrations of
nitrate-N, ranging from 0.1 to 30.1 ppm. For the 515 samples analyzed, the nitrate-N mean
was 7.08 ppm with a standard deviation of 6.01 (coefficient of variation = 85 %). Thirty-eight
samples (7%) showed no nitrate. Nitrate-N exceeded the MCL of 10 ppm in 131 cases (25%).
Nitrate-N exceeded the MCL at least once in 52% of the existing wells at primary sites compared
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to 29% at additional sites and 57% at research wells. Samples collected during March 1993 and
1994 show higher mean levels of nitrate-N, but the March 1994 mean was significantly different
from the other sampling events. There was not a significant difference between research wells
and existing wells with regard to the proportion of wells that exceeded the MCL at some point,
whereas there was evidence of a difference between existing wells at the primary sites and
existing wells at the additional sites.
Several techniques for the determination of nitrate-N were compared. A colorimetric
procedure (EM Science, Reflectoquant System) was used to measure nitrate-N on-site. This
procedure compared favorably with the laboratory ion chromatography procedure in the 1 to 40
ppm range and provided a fast, reliable, and cost-effective method.
VI
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CONTENTS
Disclaimer ------------------------------ ---------------------------------- ; HI
Foreword ------------------------------------------------------------- - --------------------- iv
-. - -. -.-_----- \/
~ ---------- * ------- -------------- - v
_____.____.__.__._________ _._._____-.__«_______-__.\/ti
~ -------- ~"~ ----- ' ----- ------------ . _ vii
_»«.-___.»-»-* _-__.-.«____ _-. _-.__-_»«.-._,_--._- _. --.-.-«-. -_- .-.j v"
IA
Tables --------------------- - -------------------------------------------- - -------------- - ------ xi
Acknowledgments ------------------------ - ----- - ----------------------------- - ------------ xii
Chapter 1. Introduction- ---------- ---------------------------- - ----------------- 1
Chapter 2. Summary ---------------------------- - ------------------- - --------------- - ----- 2
Chapters. Conclusions ------------------------------ - --------------------------- ------ 3
Chapter 4. Description of the well comparison study -------- - ---------------- 4
Experimental Design- ------------------------ - ------------------------ 4
Research and Existing Well Designs ------------ - --------------- 1 1
Protocols for Sampling Wells ------------------------- - ------------ 14
Research Monitoring Wells ----------- ------ - ---------- 14
Existing Wells ------------------------ - --------------- - ------- 16
Chemical analysis ------------- - -------- - --------------------- - - 16
Pesticides --------------------------------------------------- 16
Nitrate-Nitrogen ----------------------- -------------------- 20
Chapter 5. Statistical Analysis of the Well Comparison Study ----------------- 22
Research Hypotheses --------------------------------- - -------------- 22
Statistical Analysis Approach -------- - --------------------------- 23
Pesticide Detection- -------------------- - -------------------- - ------ -24
Individual Pesticides ----------------------------------------- 25
Analysis by Region --------------- - ------------------------- 25
Analysis by Site ------------------------- - --------------------- 27
Analysis by Crop -------------- - ------------------------------- 27
Effect of Other Factors ----------------------------- - -------- 27
Nitrate-Nitrogen Detection ------------------------------------------- 29
Descriptive Statistics ------------------------------------- -^29
Exceedance of Nitrate-Nitrogen MCL ------------------ 31
Analysis by Region -------------------- - --------------------- 31
A r\o I\/GIO h\/ ^ii*.--! __ _-._._.-.---.-._.---.....-- ^'S
/Aricuyoio uy oiic; ------ _--- ^^j
Analysis by Crop ------------------------------------- - -------- 33
Effects of Other Factors on High Nitrate Levels ------ 33
VII
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Relationship Between Nitrate-Nitrogen >MCL and
Pesticide Detection 33
Correlations 34
Distributions of Measured Nitrate-Nitrogen Levels34
Effects Due to Regions and Sampling Times 42
Statistica I S u m m a ry 51
References
-53
Appendices
-54
-55
-59
-77
1. Crop by site and year
2. Field sampling data
3. Well installation and characterization, 1992
4. Comparison of methods for nitrate-nitrogen in groundwater, 85
June 1994
5. Aquachek nitrate-nitrogen test strip results using blind spikes 89
in distilled water (visual color comparison)
6. Nitrate-nitrogen concentrations in research (A) and existing 90
well (B,C) samples
7. Pesticide concentrations in research (A) and existing well 96
(B,C) samples
VIII
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FIGURES
Page
1. Location of Little Coharie Watershed, Sampson County, 5
North Carolina
2. Measured precipitation for rainfall events during 1993-
3. Measured precipitation for rainfall events during 1994-
6
7
8
4. Little Coharie Watershed with 10 sampling segments and
location of research and existing well sites-original design
5. Little Coharie Watershed with 6 sub-watersheds and 9
location of research and existing well sites (GPS Design)
6. Design of stainless-steel research monitoring well and - 12
Installation
-13
-13
-15
-15
7. Installation of research monitoring well, site 21A
8. Installation of protective cover on research monitoring well-
9. Purging research well for sampling, site 13A
10. Research monitoring well, site 20A
11. Cumulative distribution of difference between nitrate-N levels 35
in research and existing wells at primary sites
12. Cumulative distributions for nitrate-N levels in research and 36
existing wells over all sites and all sampling times
13. Cumulative distributions for nitrate-N levels in research wells 37
over all sites for individual sampling times
14. Cumulative distributions for nitrate-N levels in existing wells 38
over all sites for individual sampling times
15. Cumulative distributions for nitrate-N levels in existing wells 39
by sampling time at (a) primary sites and (b) additional sites
-40
16.Cumulative distributions for nitrate-N levels in existing wells for-
all sampling times at primary sites and additional sites
17. Cumulative distributions for nitrate-N levels in research and 41
existing wells for all sampling times at primary sites
IX
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18. Cumulative distributions for nitrate-N levels in research and-
existing wells by sampling time at primary sites
19. Cumulative distributions for nitrate-N levels in existing wells
by sampling time at primary sites and additional sites
20. Cumulative distributions for nitrate-N levels in research and
existing wells by subbasin at primary sites
21. Cumulative distributions for nitrate-N levels in existing wells
by subbasin at primary sites and additional sites
-45
49
x
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TABLES Page
1. Distance between research well and existing well using GPS data -10
2. Summary of Pesticides detected and confirmed 24
3. Comparison of pesticide detection in research and existing wells 25
for individual pesticides
4. a. Pesticide detection by subregion
Eviof"in/t \A/O!!O Ofi
L_AloUl iy Vvcllo~~"~~~~~-^Q
Research wells ~ 26
b. Pesticide detection by subbasin
5. Frequency of detection of pesticides by crop type 27
6. Results from full logistic regression model for pesticide 28
detection
7. Results of stepwise logistic regression procedure for 28
pesticide detection
8. a. Nitrate-N mean concentrations by site type-- 29
b. Nitrate-N mean concentrations by subregion 29
c. Nitrate-N mean concentrations by subregion and site type 29
d. Nitrate-N mean concentrations by subbasin 30
e. Nitrate-N mean concentrations by subbasin and site type 30
9. a. Nitrate-N >MCL by subregion
C violin /"i \A/olIo *^O
[ZAlollI iy VVfcJllo"1"------------------------------------------------ - o^.
E5oooQ rv^h \A/O!!O _._»___ *^O
r\c?ot?c*i \-rl I WC3llo - \j£~
b. Nitrate-N >MCL by subbasin
Existing
Researc
10. Frequency of nitrate-N levels exceeding MCL by crop type 33
11 .a. Preliminary analysis of variance for differences between 42
nitrate-N levels: research versus existing wells at primary
sites
b. Analysis of variance for nitrate-N levels in research and 51
existing wells
XI
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ACKNOWLEDGMENTS
The authors gratefully appreciate the cooperation of the North Carolina Cooperative
Extension Service, Sampson County, North Carolina State University and the cooperation of 54
volunteer landowners. Special appreciation is expressed to Mr. George Upton, Sampson
County Cooperative Extension Director and a member of his staff, Mr. Ronnie Warren. Without
their assistance and cooperation, this study would not have been possible.
We also acknowledge Mr. Andy Paeng, formerly of EPA Athens-ERD, for his assistance
in analytical method development for nitrate-N and pesticides, GC/MS confirmation, and field
sampling. We appreciate the work of Mr. Tom Sweetser, a Senior Environmental Employee of
the National Council of Senior Citizens at Athens-ERD, for his assistance in research well
installation and field sampling. We appreciate Mr. Charles Till of EPA Region IV for his technical
assistance and advice on the installation of research monitoring wells using Region IV protocols.
We thank Ms. Linda Hazlett of SQC Systems, Inc., for her assistance on statistical analysis.
We thank three technical reviewers for their helpful suggestions to improve the report:
1. Mr. James N. Carleton, EPA, OPPTS/OPP, Health Effects Division, Occupational and
Residential Exposure Branch, Washington, DC.
2. Dr. James K. Wolf, EPA, OPP/EFED/EFGWB, Washington, DC.
3. Dr. Raymond Milosh, State of North Carolina Department of Environment, Health and Natural
Resources, Raleigh, NC
The authors gratefully acknowledge Mr. Bob Ryans, Athens-ERD and Mr. Heinz Kollig,
Senior Environmental Employee (SEE) for their editoral review and helpful suggestions.
XII
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Chapter 1.
INTRODUCTION
In the past 20 years, public health concerns have increased regarding possible exposure
to contaminated ground water used as a drinking water supply. Agricultural chemicals, including
pesticides and nitrates, have been detected in ground water at various sites across the country
(Hallberg 1989, USEPA 1990, USEPA 1992, Hoheisel etal. 1992, Burkart and Kolpin 1993,
Wiles et al. 1994, Maas et al. 1995). Rural private drinking water wells do not have regulatory
requirements for water quality monitoring. Rural areas of the southeastern coastal plains are
particularly vulnerable to ground water contamination because of farm practices (multiple
cropping systems, wide use of agricultural chemicals), physical conditions (shallow ground
water, coarse-textured soil), and high rainfall. According to recent study results (Time 1995),
concentrations of atrazine and cyanazine were found in tap-water above the federal standards in
much of the midwest from samples collected every few days during mid May-July 1995 in 30
communities.
Most monitoring studies have relied on samples collected from existing drinking water
wells rather than from specially installed monitoring wells. The National Pesticide Survey of
Drinking Water Wells (USEPA 1992) conducted in 1988-90 indicated, however, that existing
wells may be subject to built-in bias and that sample quality may be questionable due to a
number of factors, such as well construction practices and materials, location, type of use, etc.
Because of ground Water contamination concerns, monitoring programs are needed to
provide accurate assessments of ground water quality. Specialized monitoring wells, however,
are very expensive, and it would be of substantial benefit if existing drinking water wells could
routinely and reliably be used for assessing ground water quality.
Our study was designed to address five objectives:
(a) Compare research monitoring wells to existing wells with regard to their capability to provide
samples appropriate for detecting certain chemicals (i.e., pesticides and nitrates) that might exist
in various concentrations in ground water associated with agricultural operations;
(b) Estimate concentrations of target chemicals on a watershed level and assess distributions;
(c) Determine whether there are differences among subregions of the watershed with respect to
chemical concentrations or occurrence of particular chemical constituents;
(d) Determine whether there is any evidence of an influence on chemical concentrations
imparted by specific types of agricultural operations or practices or other site-specific
characteristics;
(e) Assess the predictive capability of computer models designed to predict chemical
concentrations in ground water, such models being parameterized/calibrated according to either
general or watershed-specific criteria.
This report addresses research objectives a,c, and d by describing the watershed design
and presenting results of the comparison of research wells versus existing drinking water wells
for assessing ground water quality. A large database of pesticide and nitrate-nitrogen
concentrations generated during the course of the study is available for model testing.
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Chapter 2
SUMMARY
Stainless-steel research monitoring wells were found to provide a greater probability of
detecting pesticides in groundwater than existing on-farm wells. For nitrate, there was not a
significant difference between the research wells and existing on-farm wells relative to the
detection of values exceeding the MCL whereas there was evidence of a difference between
existing wells at the 21 primary wells sites and existing wells at the 56 additional sites.
Thirty percent of all wells sampled had observed pesticides residues in at least one
sampling date, but only 2% of the pesticides detected exceeded the MCL. Pesticides were found
in 52% of the research wells (none exceeding the MCL) versus 23% of the existing wells. Two
existing wells had pesticide concentrations exceeding the MCL (atrazine 6.5 ppb, and alachlor
6.2 ppb). The ranges of concentrations for the other pesticides frequently found were 2.3-18.3
ppb for carbofuran, 0.2-63.7 ppb for metolachlor, 0.8-4.3 ppb forfluometuron, and 0.2-0.7 ppb
for methomyl.
Atrazine was the most frequently detected pesticide found in all wells with 14% of the
detections, followed by fluometuron at 6.2%; carbofuran and metolachlor at 5.3%; alachlor at
3%; carbaryl and methomyl at 2%; and butylate, chlorothalonil, linuron and simazine at 1%. The
pesticides detected were usually found at repeated sampling events and in some cases multiple
residues were observed, but no pesticides were found in wells greater than 80 feet deep.
Wells near soybean crops were more likely to have detectable pesticides; wells near
cotton crops were a much weaker indicator. A tobacco crop tended to decrease the likelihood of
detecting pesticides.
Results of 6 sampling events showed 97% of all wells had observed concentrations of
nitrate-N ranging from 0.1 to 30.1 ppm. For the 515 samples analyzed, the nitrate-N mean was
7.08 ppm with a standard deviation of 6.01 (coefficient of variation = 85%). Thirty-eight samples
(7%) showed no nitrate. Nitrate-N exceeded the MCL in 131 cases (25%). Nitrate-N exceeded
the MCL at least once in 52% of the existing wells at primary sites compared to 29% at additional
sites and 57% at research wells.
For nitrate-N levels above the MCL, no factors other than site type (i.e., primary versus
additional) were identified to be associated with differential likelihood levels. There was a high
correlation between nitrate-N and TDS values, but not for pesticides.
For nitrate-N determinations, a colorimetric procedure (EM Science, Reflectoquant
System) compared favorably with the laboratory ion chromatography procedure in the 1 to 40
ppm range and provided a fast, reliable, cost-effective method.
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Chapters
CONCLUSIONS
Results of the study indicate that research monitoring wells provide a greater probability
of detecting pesticides in ground water than existing on-farm wells. For nitrate, there was not a
significant difference between the research wells and existing on-farm wells.
Additional research is needed regarding chemical exposure from rural drinking water in
the southeast-for example, inclusion of Endocrine Disruptoc Compounds (EDC), degradation
products in addition to parent compounds, chemical combinations, and the development of an
automated well monitoring system. Rural areas of the southeastern coastal plains are
particularly vulnerable to ground water contamination due to multiple cropping systems; large
poultry, swine, and cattle operations; wide use of agricultural chemicals; shallow ground water;
coarse-textured soil; and high rainfall.
It is recommended that future drinking water exposure studies include more frequent
sampling periods in order to determine peak potential human exposure dose levels and the most
vulnerable periods, such as after major rainfall events and chemical applications in the spring
and summer months.
This study was terminated prematurely in the spring of the second crop year (1994), after
15 months involving only six sampling events. We were unable to obtain the 3 years of pesticide
data normally recommended for a statistically valid database. In June 1994, the watershed
experienced a period of heavy rainfall and flooding. Sampling during July 1994 would have
provided vital exposure information and was critical to the well comparison and model testing
objectives. Therefore, the database is lacking in sufficient pesticide data for the well comparison
study and to test predictive exposure models adequately on a watershed scale (i.e. PRZM,
PATRIOT and others). We could not sample as frequently as needed to define the seasonal
and spatial variations in well water quality needed to determine peak human exposure periods.
Soil profile sampling to provide pesticide leaching data in the unsaturated zone, which was
scheduled for the second year, was not accomplished.
The 158.2 square mile (101,248-acres) Little Coharie watershed is an excellent area to
conduct multimedia (surface water, groundwater, soil, air) human and ecological exposure
research studies given the wide diversity of agriculture, landowner cooperation, background
water quality, GPS mapping and our findings of chemicals in groundwater at significant levels. It
would take several man-years to establish/characterize a comparable test watershed in another
location.
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Chapter 4
DESCRIPTION OF THE WELL COMPARISON STUDY
A 2-year ground water quality research project was conducted in the Little Coharie
Watershed , a 158.2 square mile area located in Sampson County, North Carolina, that drains
into the Cape Fear River Basin (see Figure 1). The research study was conducted by the
Ecosystems Research Division, Athens, Georgia, of EPA's National Exposure Research
Laboratory in cooperation with the North Carolina Cooperative Extension Service, North
Carolina State University, the U. S. Department of Agriculture, and 54 volunteer landowners
within the Little Coharie Watershed. The watershed is predominantly rural and includes a
diversity of cropping systems (tobacco, cotton, corn, soybeans, and vegetables), chemical uses,
and large animal operations (hogs, turkeys and cattle). Sampson County is a major agricultural
production area in the southeast. Its agricultural income is within the top 10 counties in the
United States, it is the leading county for swine production in the United States, and it is the
second-ranking county for turkey production in North Carolina. Sampson County, the largest
county in North Carolina, is located in the Coastal Plain physiographic province. Elevation
ranges from 20 feet above sea level in the southwestern corner to 210 feet above sea level in
the northwestern part of the county. The land surface is mostly level to gently sloping, (Brandon,
1985). The elevation range of the Little Coharie Watershed is 50 to 210 feet established by using
Global Positioning System (GPS) equipment.
Daily observations of precipitation and temperature were obtained throughout the study
period (1993-94) from a nearby weather station (about 5 miles from the east side of the
watershed) located at the Horticultural Crop Research Station in Clinton, NC. Annual
precipitation during 1993 and 1994 was 51.3 and 42.2 inches, respectively. Figures 2 and 3
display measured daily rainfall data collected during the study period.
Experimental Design
The Little Coharie watershed was divided into ten subregions or watershed segments (i.e.,
strata) of approximately equal areas for purposes of ensuring adequate sampling, accurate
representation, estimability, and controlled variance (Figure 4). Well sites were allocated
according to proportional allocation rules across strata and balance was sought with respect to
crop types. Candidate sites were selected so that edge-of-field or within-field sampling would be
assured in all cases. The final sites represented the most predominant
crops/operations/practices occurring in the region. Sites also were selected with an eye toward
comparing results across crop/operation/practice types (Appendix 1). In selecting appropriate
sites for research well installation with farmers as landowners, researchers conducted visual
inspection of potential farm sites and sent a project brochure and an inquiry to the landowner to
ascertain whether he or she would be willing to participate.
At the time the study was designed in 1992, ten arbitrary sampling segments were
established based on the assumption that the watershed system was uniform. In 1995 after the
study was terminated, USDA's National Conservation Research Service (NCRS) provided a
digitized Hydrologic Unit Map of the Little Coharie watershed boundary (NAD-83,NC State
Plane), indicating that the watershed consisted of six subbasins (J26, J27, J28, J29, J30, and
J31) based on soil characteristics (Figure 5). GPS equipment was used to locate all the well
sites. Well data points were overlaid on the NCRS boundary map using the NC State Plane
coordinates. This provided precise locational data points for use in mapping chemical
concentrations and conducting future model testing.
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North Carolina
Fear River Bas
Sampson County
FIGURE 1. Location of Little Coharie Watershed, Sampson County,
North Carolina
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RESLAKGH WL.LL
EXISTING WELL
FIGURE 4. Little Coharie Watershed with 10 sampling segments
and location of research and existing well sites-original design
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LITTLE COHARIE WATERSHED
SAMPSON COUNTY, NORTH CAROLINA
J31 SINCLAIR LAKE (8293 ACRES)
J30 OPOSSUM SWAMP-LITTLE COHARIE (13633 ACRES)
J29 CAESAR SWAMP (8284 ACRES)
J28 MILL SWAMP-LITTLE COHARIE (34600 ACRES)
J27 BEARSKIN SWAMP (16017 ACRES)
J26 LOWER LITTLE COHARIE (20445 ACRES)
RESEARCH WELL
EXISTING WELL
BENCH MARK
BENCH MAR* JEANNE
FIGURE 5. Little Coharie Watershed with 6 sub-watersheds and
location of research and existing well sites by GPS
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At each primary research site, an established existing well that was deemed adequate for
periodic sampling was identified in close proximity to an agricultural field. For comparison
purposes, a research well was installed in as close proximity as possible to the existing well so
that each well effectively would provide samples from the same ground water (that is, with
minimal adverse spatial variability) (Table 1). Wells identified in Table 1 as "A" are research
wells, and wells noted as "B" and "C" are existing wells. Wells labeled as B were used primarily
for drinking water, and wells labeled as C were used for agricultural purposes.
This paired approach allowed for a direct comparison between existing and research wells
at the same site. The intention was to determine whether existing wells would provide
sufficiently equivalent samples, compared to specially designed research monitoring wells. If
existing wells provided adequate data, their large scale use would be possible for both ground
water assessment and model parameterization/testing.
The research wells were installed in near-optimal positions for sampling ground water that
might be impacted directly by agricultural operations, whereas existing wells usually were sites in
less optimal positions. Thus, the data from the two types of wells provide a comparison of wells
of ideal construction and optimal location to wells of unknown construction and, in most cases,
less than optimal location. The primary emphasis in this study was not on assessing impacts of
agricultural practices on drinking water quality. Subsequent modeling efforts, however, very
likely would address this issue, and such models rely heavily on accurate parameterization with
regard to source terms at the point where contaminants enter the ground water.
In addition to the paired wells, 56 other existing wells (B and C) were selected for monitoring
that, collectively, would provide watershed-level and stratum-level estimates for chemical
constituents. This meant that, in addition to individual paired comparisons as described above,
there also could be comparisons between well types for means computed within strata.
Collectively, the existing wells over the entire watershed and all of the research wells could
be used to obtain estimates of means, and distributions could be evaluated at the watershed
level after taking into account variation due to subregions and other factors. Such information
should be useful in modeling efforts.
Table 1. Distance Between Research Well and Existing Well using GPS Data
WELLS DISTANCE (feet, accuracy+/-30)
1A-1B
2A-2B
3A-3B
4A-4B
5A-5B
6A-6B
7A-7B
8A-8B
9A-9B
10A-10B
11A-11B
12A-12B
13A-13B
89
276
224
128
140
84
227
439
300
95
167
1178
172
10
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14A-14B
14A-14C
15A-15B
16A-16B
17A-17B
18A-18B
19A-19B
20A-20B
21A-21B
784
543
756
125
364
78
390
292
254
Research and Existing Well Designs
In 1992, 21 specially designed stainless-steel research monitoring wells
(Figure 6) were installed by ERD-Athens staff using a CME-75 drill rig (Figure 7). Wells were
located randomly throughout the watershed to provide reliable ground water quality data near
agricultural fields. Each well was located down slope and near the edge of agricultural row-
cropped fields where they would cause only minimum interference with on-going farm activities
and in close proximity to existing shallow wells so that valid, data comparisons could be made.
Well site number 21 is an exception, it was located in the center of a field. The research wells
ranged in maximum depth from 20 to 35 feet with a mean of 25.7 feet (Appendix 2). Existing
comparison wells ranged in depth from 12 to 250 feet, with a mean of 29.7 feet. At each site,
locations of septic tanks/drain fields and hog houses/waste lagoons were identified so that
research wells would not be installed in close proximity to these systems.
The design and installation of research monitoring wells followed general guidelines
provided by EPA Region IV, Environmental Services Division, Athens, Georgia (1991).
Exploratory drilling using a 4-in solid-stem auger was conducted initially to identify soil layers by
depth and to determine the depth at which to locate the well screen above a confining clay layer,
(Appendix 3). Each well borehole was completed using an 8-in hollow-stem auger equipped with
a hinged trap-door head. Once the desired depth was reached, the hollow-stem auger was filled
with water to provide a positive pressure to keep ground water from entering the auger. A 2-in
stainless steel well casing (0.010 in opening, 10 feet long with bottom end cap wire-wrapped
screen) was lowered into the hollow-stem auger. One 50-lb bag of well-rounded Ottawa sand
was poured in the annular space surrounding the well casing in the hollow stem auger to
develop a sand pack extending to about 2 feet below the bottom of the well screen. The trap
door was opened by holding the well casing in place and simultaneously raising the auger. Sand
was added and the auger extracted slowly. This procedure was repeated until the sand was at
least 2 feet above the top of the well screen. Then, volclay grout was mixed to a density of 10.2
Ib/gallon using a grout machine. The grout was pumped and tremied into the annular space to
ground elevation to provide a seal with the borehole. The well casing was left about 2 feet
above ground level.
After installation, the well'was developed by the backwashing technique, using the drill rig
pump. A protective casing (4 inches square, 5 feet long) with hinged cap was installed over the
well casing, extending 3 feet above the ground surface. To install the protective casing, grout
was removed around the well casing to a depth of 1 foot. (Figure 8) The protective casing was
then pushed into the grout. A concrete surface pad (3 ft X 3 ft X 4 in) was constructed around the
protective casing, extending into the annulus to the top of the volclay grout seal. Four metal
fence posts were driven into the ground at each corner of the surface pad to serve as protective
guards. A lock was placed on the protective casing cap to secure the well and an identification
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Protective Post
Concrete Pad
3'X3'X4" ^
Protective Cover/Lock
Volclay Grout
\
Stainless Steel
(2" Dia.)
Sand Pack
Stainless Steel
Well Screen
(2" Dia., 10' Length)
FIGURE 6. Design of stainless-steel research monitoring well and Installation
12
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FIGURE 7. Installation of research monitoring well, site 21A
FIGURE 8. Installation of protective cover on research monitoring well
13
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number was placed on top of the cap. All equipment used was cleaned with a steam pressure
washer after each well installation. Examples of research monitoring wells are shown in Figure 9
and Figure 10.
Existing wells were usually 1.5 in PVC or galvanized pipes with 2 ft in length wire-mesh well
points, driven into the shallow aquifer. Historical data on well installation was unavailable for
existing wells. According to landowners, when a well screen deteriorated, a new casing and
screen is installed at a new location or in the same borehole. Some installations were bored
wells, 20-30 in diameter (sites 2, 3, 36, 46, 49 and 75). Deep wells, greater than 30 ft, were drill
wells. Existing wells ranged in depth from 12 to 250 ft with a mean of 29.6 ft (Appendix 1).
Protocols for Sampling Wells
Sampling dates were March 23-31 (days 82-90, preplanting), July 13-21 (days 194-202),
and November 9-16 (313-320) in 1993 and February 28-March 7 (days 59-66), May 16-18 (days
136-138) and June 20-27 (days 171-178) in 1994. Water samples were collected from all wells
except when winter conditions prevented sampling of two existing wells (sites 4, 17) or the pump
was removed by vandals (site 10).
Research monitoring wells
The depth of static water below ground level was determined using a battery-operated water
level indicator. Depth measurements were made prior to purging and the sensor was rinsed
each time with deionized water before and after use. About 1 gallon of well water was collected
in a stainless-steel bucket using a Teflon bailer and used to prime the gasoline-operated
centrifugal pump that was used to purge the well. The bucket and Teflon bailer with stainless
steel cable were rinsed with deionized water and drained prior to collecting water for use in
flushing and cleaning pump and hose. The pump hose, with foot valve attached, was lowered to
the bottom of the well casing. The hose and pump were filled with water from the well to be
sampled. A 25-ft garden hose was connected to the pump to discharge the water from the site.
The purging process usually required about 30 minutes to collect a representative sample of
formation water (3 to 5 volumes of a static water column) or until measurements of pH,
conductivity and temperature stabilized. Conductivity (mg/I) was reported as Total Dissolved
Solid (TDS) because the meter that was used relates conductivity of a standard concentration to
a TDS value. The well was purged initially from the bottom, then was purged by slowly moving
the foot valve upward to near the middle and top of the water column. When the measurement
parameters stabilized or when the designated purging time elapsed, the hose was slowly pulled
from the well while the pump continued to operate. When the pump lost its prime, the engine
was stopped and a sample was collected using a 1.5-in Teflon bailer with a stainless steel cable.
Five volumes of the bailer were collected near the top, middle and bottom of the water column
and composited in a stainless steel pail. The sample was mixed and two 1-quart amber bottles
with teflon-lined caps were filled for chemical analysis. The samples were placed on ice for
transport to the analytical laboratory.
Prior to going to the field, the Corning pH meter, Checkmate Model 90 was supplied with
new batteries and checked for calibration. Calibration was conducted again in the field at the
beginning and at mid-day. The instrument was calibrated using a two point system as outlined in
the operations manual. Additional recalibrations were conducted at the discretion of the analyst.
Calibration of the pH meter was conducted using various standard pH buffer solution packages
14
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FIGURE 9. Purging research well for sampling, site 13A
FIGURE 10. Research monitoring well, site 20A
15
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(4.00, 7.00 and 10.0). The electrode was thoroughly rinsed with deionized water when changing
buffer solutions, and when measuring a sample.
A Coming conductivity meter, Checkmate Model 90, was used and calibrated for two points
against air and a conductivity standard (Corning #473623) as described in the operations
manual. Calibration was conducted at the beginning of each workday and at mid-day.
Recalibrations were also conducted at the discretion of the analyst.
Existing wells
Samples at existing wells were collected from the faucet closest to the pump. A 25-ft garden
hose was connected to the faucet for purging. Measurements of temperature, conductivity and
pH were made and recorded on a field data sheet to determine whether the stored water was
removed from the system. A sample was collected directly from the faucet, not from the purging
hose, into two 1-quart amber glass bottles with Teflon-lined caps and placed on ice for transport
to the analytical laboratory. Depth to water and well depth measurements were not made
because of problems associated with disconnecting the plumbing system. Depths of existing
wells were obtained from the landowner.
Chemical Analysis
The samples were collected by ERD-Athens staff, placed on ice, and taken to an EPA
mobile laboratory (located in Clinton, NC) equipped for nitrate-N analysis and pesticide
extractions. For quality control checks, duplicates were taken from approximately 10 to 15% of
the sites and integrated into the analysis system marked as routine samples. Distilled water
blanks also were introduced on a routine basis. In Clinton, the samples were extracted for
pesticides and analyzed for nitrate-N by an EPA contractor. The contractor informed EPA field
sampling staff daily of well samples exceeding the EPA Maximum Contaminant Level (MCL) of
10 ppm nitrate-N. In many cases, these wells were resampled. One liter of the sample was
extracted for pesticides analysis using solid phase extraction procedures (SFE), and a 2-ml
portion of the sample was analyzed for nitrate-N using ion chromatography. All analyses in this
report were done in terms of nitrate-nitrogen even though sometimes reported as nitrate only.
Pesticides
Twenty-one pesticides were selected for screening:
Alachlor (LASSO) 2-chloro-2'-6'diethyI-N-(methoxymethyl)-acetanilide
Ametryn (EVIC) 2-(ethylamino)-4-isopropylamino-6-methyl-thio-s-triazine
Atrazine (AATREX) 2-chloro-4-ethylamino-6-isipropylamino-s-triazine
Butylate (SUTAN) S-ethyl diisobutyithiocarbamate
Captan (ORTHOCIDE) cis-N-trichloromethylthio-4-cyclohexene-1,2-
dicarboximide
Carbaryl (SEVIN) 1-naphthyl-N-methylcarbamate
Carbofuran (FURADAN) 2,3-dihydro-2,2-dimethyl-7-benzofurantl methylcarbamate
Chloropyrifos (LORSBAN) O,O-diethyl O-(3,5,6»trichloro-2- pyridinyl)
phosphorothioate
Chlorothalonil (BRAVO) tetrachloroisophthalonitrile
Cyanazine (BLADEX) 2-[[4-chloro-6-(ethylamino)-1,3,5-triazin-2~yl]amimo]-2-
methylpropionitrile
16
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Diazinon (SPECTRACIDE) O,O-diethyl O-(2-isopropyl-6-methyl-4-pyrimidinyl)
phosphorothioate
Dimethoate (CYGON) O.O-dimethyl-S (N-methylcarbamoylmethyl)
phosphorodithioate
Endosulfan (THIODAN) 6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a- hexahydro6,9-methano-2,4,3-
benzod ioxathiepi n-3-oxid e
Fluormeturon (COTORAN) 1,1-dimethyl-3-(a,a,a-trifluoro-m-tolyl) urea
Linuron (LOROX) 3-(3,4-dichlorophenyl)-1-m ethoxy-1- methylurea
Malathion (CYTHION) O,O-dimethyl phosphorodithioate of diethyl
mercaptosuccinate
Methomyl (LANNATE) S-methyl-N-((methylcarbanoyl)oxy)-thioacetimidate
Metolachlor (DUAL) 2-chIoro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-
methyl) acetamide
Parathion (NIRAN) O,O-diethyl-O-(4-nitrophenyl) phosphorothioate
Propachlor (RAMROD) 2-chloro-N-isopropylacetanilide
Simazine (PRINCEP) 2-chloro-4,6-bis(ethylamino)-s-triazine
The extraction and determination of pesticides in ground water samples was performed
using a modification of EPA Method 525.1 and 525.2 for pesticides. The SFE extracts were
refrigerated (4 degrees centigrade), and transported to the Athens laboratory for analysis by gas
and liquid chromatography.
Five modifications to method 525.1 and 525.2 were adopted:
o samples were not preserved but were iced immediately and extracted within 12-14 hours of
sampling;
o a C-8 bonded phase disk was used instead of a C-18;
o an acetone prewash was used instead of ethyl acetate/methylene chloride;
o after the sample was passed through the disk, the pesticide residues were eluted with
acetone instead of ethyl acetate/methylene chloride;
o all sample extracts were subjected to analysis by capillary gas chromatography using
electron capture (GC/ECD) and nitrogen phosphorus (GC/NP) detection systems
and high performance liquid chromatography using a post column reaction system
(HPLC/PCRS).
The samples were not preserved because they were iced immediately after sampling,
shipped to the lab within 4-6 hours, and extracted within 14 hours. There were no significant
differences in the data from samples extracted immediately after sampling and the data from
samples extracted within 14 hours. When the samples were received from the field, they were
refrigerated at 4°C until extraction. Disks (47-mm diameter) containing a silica solid matrix with
a chemically bonded C-8 organic phase (Empore , 3M Company) were used to rapidly extract
several samples simultaneously. After the disks were conditioned with acetone.and methanol,
the samples were passed through the disks. Available data showed no relationship between
flow rate and recovery, so the vacuum was adjusted for maximum flow. The analytes were then
eluted with three 5-ml portions of acetone; the extract was refrigerated at 4°C and transported
back to the Athens laboratory.
The refrigerated acetone extracts were analyzed within 30 days after sample collection. At
that time, the acetone was removed and the residue made to volume in isooctane for analysis by
gas chromatography using electron capture (EGD) and nitrogen-phosphorus (NP) detection
systems. Samples whose chromatograms contained peak(s) with a retention time matching the
17
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compounds of interest were subjected to qualitative gas chromatography/mass spectrometry
(GC/MS) confirmation techniques.
Pesticide samples were analyzed with a Waters Carbamate Analysis System consisting of:
o Model 600E system controller
o Reagent pumps
o Waters U6K sample injector
o Model 470 scanning fluorescence detector
o Whatman Partisil 10 ODS-2 4.6x250-mm column
o System interface module (SIM)
o Temperature control module
o Hewlett Packard Series 1050 degasser
o Hewlett Packard Desk Jet 500 printer
o NEC Multisync 2A monitor
o NEC Powermate 386/33i CPU
o Millenium 2010 Software version 2.0.
The Hewlett Packard 5890 Series II gas chromatograph was equipped with:
o Nitrogen-phosphrous detector SPB-5 fused silica capillary column, 15-m x
0.53-mm x 0.50-^m df
o Split-splitless injector
o Electron capture detector SE-30 30-m x 0.32-mm ID x 1.0-^m df. capillary
column
o Hewlett Packard autosampler and injector
o Hewlett Packard 3396A integrator.
The Hewlett Packard 5890 Series II gas chromatograph-mass spectrometer (GC/MS) equipped
with:
o Hewlett Packard (HP-5 MS), 5% phenyl-methyl silicone,
(30-m x 0.25-mm i.d. x 0.25-yu film coating column.
o Hewlett Packard 5972 Series mass selective detector
o Hewlett Packard autosampler (HP7673) and injector
o Hewlett-Packard G1034C ChemStation
Sample extracts that were previously analyzed by GC-ECD and GC-NPD and found to have
a chromatographic peak with retention times corresponding to those of the target pesticides
were also analyzed by GC-MS for identification and/or verification. All quantitative analyses,
however, were performed by either GC-ECD or GC-NPD.
Sample components were identified by comparing the retention times (RT) and mass
spectra of each chromatographic peak with databases contained in two computer reference
libraries. The first library was the commercially-available Wiley database (Hewlett Packard) of
138,000 mass spectra supplied with the GC-MS system. The second library was created in-
house by analyzing analytical standards of compounds (pesticides) known to have been used or
thought to have been used in the watershed where the samples were collected. The mass
spectrum and the retention time of each compound in this database was obtained using the
same GC-MS and analytical conditions as those used to analyze the field samples.
18
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Gas Chromatographic Conditions
Mode:
Capillary Column":
30 sec
250 °C
Carrier Gas:
Carrier Gas Linear Velocity:
Sample Injection Size:
Injector Purge Delay:
Injector Temperature:
Gas Chromatograph Conditions:
Initial Temperature: 100 °C
Initial Hold Time 5 min
Rate Temperature Program: 8°C/min
Final Column Temperature: 280 °C
Final Hold Time 4.5 min
Mass Spectrometer
Interface Temperature: 280 °C
Mass Spectrometer Conditions:
Splitless injection
Hewlett-Packard (HP-5 MS), 5% phenyl-methyl silicone,
(30-m x 25-mm i.d. x 0.25-yum film coating)
Helium
32 cm/sec
Auto Tuning Standard:
Standard Auto Tune:
MS Temperature:
Electron Multiplier:
Solvent Delay Time:
Mode:
Scan Range:
Scan Rate:
Perfluorotributylamine (PFTBA)
Tuned automatically to meet the
manufacturers specifications
175 °C
1800v
4.0 min
SCAN
35 to 435 mass units
1.8 scans/sec
After GC or GC/MS procedures were complete, the isooctane was removed with dry
nitrogen and the residue was brought to volume with 30% acetonitrile-water. The sample was
mixed with a vortex mixer and injected into a Waters liquid chromatograph with a post column
reaction system (HPLC/PCRS) specific for carbamates.
GC Determination:ECD, NP Detection systems.
Method recovery: 60 -125% for atrazine, alachlor, fluometuron, metolachlor, butylate,
chlorothalonil, linuron, and simazine.
Minimum Detection Limits (MDL): 50 ppt -1 ppb, depending on compound.
HPLC Determination: Carbamate-specific post column reaction system.
Method Recovery Range: from 79-110% for methomyl, carbaryl, and carbofuran.
Minimum Detection Limit (MDL): 0.2 ppb.
To compare the effectiveness of a liquid-liquid extraction (methylene chloride shakeout)
procedure to the solid phase extraction procedure (C-8 Empore disks), the samples from the
research and nearby comparison wells were extracted using both procedures during the March,
May, and June 1994 sampling events. The liquid-liquid shakeouts were performed on-site
immediately after sampling. These data indicate good correlation between the Empore solid
phase extraction method and the liquid-liquid extraction procedure for the compounds selected
19
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for this study. Older liquid-liquid extraction techniques require the use of large amounts of
chlorinated solvents; therefore, newer solvent-sparing liquid-liquid extraction procedures were
investigated. It is recommended that a liquid-liquid procedure be used for studies requiring
analysis of certain carbamate pesticides, such as aldicarb and oxamyl.
Nitrate-Nitrogen
EPA Method 300.0, The Determination of Inorganic Anions in Water bv Ion Chromatographv.
was the primary method for the analysis of nitrate-N in well water.
During the second year of sampling, three techniques for the determination of nltrate-N were
used-the ion chromatographic procedure (Method 300.0) and two colorimetric procedures
[AQUACHEK test strips (Environmental Test Systems, Inc.) and a procedure using a Merck
Reflectoquant system (EM Science Inc.)]. The results of the three methods for June 1994 are
shown in Appendix 4.
Nitrate-N samples were analyzed with a Waters ion chromatograph consisting of:
o Waters 431 Conductivity Detector
o Waters 590 Solvent Delivery System
o Dynatech Autosampler with 10O-^L loop
o Alltech Ion Suppressor
o Hewlett Packard 3396 Series II Integrator
o Sarasep-AN1 Column with Waters Precolumn Module
MDL = 0.1 ppm
Merck Reflectoquant Analysis System (RQflex meter)
MDL=1.0ppm
Aquachek Water Quality Test Strips (nitrate, nitrite)
MDL = Approximately 1.0 ppm
During the March, May, and June 1994 sampling periods, nitrate-N levels in the well water
samples were screened in the field using AQUACHEK water quality test strips as per
manufacturers instructions-and repeated in the mobile laboratory. The data indicate the
Aquachek system is an adequate screening procedure that could eliminate costly, time
consuming chromatographic analysis on water samples that fall in the <1.0 ppm (ND) to 5 ppm
range. The Aquachek strips are very easy to use, but the results are only a rough estimate of
the nitrate-N concentration and this technique should only be used for preliminary screening.
A comparison of results by three individuals using the Aquachek system on a series of blind
spikes is shown in Appendix 5. These data, although not conclusive, demonstrate the test to be
dependent on an individual's perception of color.
For the May and June 1994 sampling periods, the Reflectoquant System was used in
addition to the AQUACHEK strips to screen nitrate samples in the field. The Reflectoquant
System, which is more expensive and requires some basic instruction, removes the subjectivity
of color comparison charts by measuring the concentration based on the light reflected from the
test strip. The meter makes two measurements simultaneously and displays the average for
increased accuracy. The procedure can be used in the field and the nitrate-N concentration is
20
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known within minutes after taking the sample. This is important for drinking water wells with high
concentrations, because the well can be resampled immediately to provide a check analysis.
Additional data are needed, but the elimination of the ion chromatography procedure and
the use of the Reflectoquant system would permit the sampling of a much larger population,
thereby improving the quality of the data for statistical purposes. When compared to the 1C
method, Reflectoquant is very cost effective in terms of equipment and labor. Results from the
Reflectoquant system compare favorably with the 1C results in the 1 to 40 ppm range for
nitrate-N. (Appendix 4)
If only the AQUACHEK strips are used for field screening, samples falling in the 5-10 ppm
range or greater should be confirmed with the Reflectoquant system and/or taken to the lab for
analysis using ion chromatography.
All analytical support for this effort was conducted by an EPA contractor, Technology
Applications, Inc. in an EPA field mobile laboratory onsite at Clinton, NC, or at EPA's
Ecosystems Research Division, Field Research Annex, Athens, GA. An approved QA/QC plan
for the contractor's work was developed prior to any analysis. Analytical results for nitrate-N and
pesticides are shown in Appendices 6 and 7.
21
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Chapter 5
STATISTICAL ANALYSIS OF THE WELL COMPARISON STUDY
The statistical analysis included data from 74 sites with a total of 99 wells of which 78 were
existing wells and 21 were research wells. Four of the existing wells were co-located with other
existing wells (sites 14, 39, 58, 75). Three other sites (44, 47, 52) had been identified as
possible sampling sites but wells were not sampled there. One deep well (site 24) was not
considered in comparative analyses, leaving 73 sites and 98 wells for analysis. Sites 1-21 were
referred to as "primary" sites and sites 22-77 were referred to as "additional" sites. One research
well was installed at each primary site.
The well samples in this study were obtained over 6 sampling dates during a period of 15
months (Mar93, Jul93, Nov93, Mar94, May94, Jun94). All wells were sampled each time except
that during one period (May94) only the wells at primary sites were sampled. Data were
obtained on nitrate concentrations and on concentrations of several pesticides. Nitrates were
much more prevalent than pesticides, a fact that affected the analysis approach and the degree
to which hypotheses involving pesticides could be addressed. Other data that were measured or
gathered included: pH, conductivity (TDS), depth to water, well screen depth, history of crops
grown at the sites, and distance between wells within sites.
Initial data review and communications with project staff resulted in corrections to some
data. Modifications to the original datasets included the following:
Well #406 was relabeled as #39C
Well #66C was relabeled as #40B
Well #70C was relabeled as #77B
Well #24B was not used in the analysis because of its relatively extreme depth
Sites #44, #47, #52 were not sampled
Site #30, SampTime 2: Sample lost, previously indicated as 0.0 Nitrate-N
Research Hypotheses
The two research questions were:
1. Are the chemical concentrations obtained from research monitoring wells
(Model A) from the same distribution as those concentrations obtained from
existing wells (Model B) when both are placed in the same or similar
conditions?
2. Are there differences between Model A and Model B for nitrate-N and
various pesticides observed in well water when compared to measurements of
pH, conductivity, depth to water, well depths, and crop type by watershed
segment.
These questions can be restated in null form hypotheses as follows:
(a) Observations of nitrate-N/pesticide concentrations from existing wells are derived from
the same statistical distribution as are observations from research wells when such wells are
situated in similar environmental conditions.
22
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(b) After adjusting for concomitant factors (including pH, conductivity, depth to water, well
screen depth, and crop type across the watershed), there are no differences between
nitrate/pesticide observations from existing wells and those from research wells.
Statistical Analysis Approach
Initially, the statistical distributions for nitrate-N were assessed for each well type (i.e.,
research and existing) without adjustment for other factors. The distributions were examined for
normality and for outliers. Because pesticides were expected to occur in the wells with low
frequency, the corresponding data were not expected to be sufficiently extensive to permit a
similar distribution analysis.
For hypothesis (a), the nonparametric two-sample Kolmogorov-Smirnov procedure
(Hollander and Wolfe, 1973) was used to test whether two samples could have come from the
same parent distribution. This test could be applied at each individual sampling time assuming
that there was no adverse inter-strata variation that might otherwise preclude combining data .
from different strata. Thus, an effort was made first to test whether there was any evidence for
such variation. Analysis of variance was employed to address this concern and to identify any
strata that might have extremely diverse levels of nitrate-N. The number of sites per stratum
affects the precision of the corresponding estimates of experimental error.
The sampling design was sufficient to allow either set of wells to be used to estimate a
watershed-level distribution, but not to estimate with desired accuracy distributions within strata.
Another approach for addressing hypothesis (a) was to examine paired values for the existing
and research wells, according to location, and then assess the distribution of the differences
between the paired values. Regression methods also were used in this context. The frequency
with which nitrate-N exceeded the MCL was investigated for both types of wells. For pesticides,
the data were too sparse for a continuous-based analysis with respect to distribution
comparisons. The frequency of detection of pesticides, however, was examined in each type of
well. The rates of detection of pesticides in both, types of wells at the same site were compared.
For hypothesis (b), the possible effects of other factors were considered.. In cases of
nitrate-N exceeding the MCL or of pesticide detection, univariate analyses were conducted for
various factors that were classified into discrete levels. Such analyses were based on 2 x K
contingency tables, and Fisher's exact test was used for testing the hypothesis that there was no
association between the factor and the relative frequency of the outcomes for the response
variable. The Cochran-Mantel-Haenszel procedure (Fleiss 1981) was used to test for
association adjusting for watershed segments. A multivariate logistic regression analysis was
employed to examine the joint effects of different factors on the binary response variables just
described. That method tests for differences between the existing wells and research wells while
adjusting for other factors. For some analyses, the detection of any pesticide was used as a
response variable.
The odds of an event, such as pesticide detection or exceedance of the MCL for nitrates,
have been considered in the analysis (odds = p/[1-p] where p=event probability). Odds ratios
are computed for cases where certain events either occur or do not occur for each of two groups.
Although the odds ratio derives from other types of studies, it was used here to provide a simple
descriptive measure of increased or decreased likelihood of pesticide detection or exceedance
of nitrate-N MCL in wells of one type compared to Wells of another type. In general terms, the
odds ratio indicates the factor by which the likelihood of an event is believed to be increased for
the specified group when compared to a reference group.
23
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Pesticide Detection
Thirty percent of all wells sampled had observed pesticides detected and confirmed for at
least one sampling date, but only 2% of the pesticides detected exceeded the maximum
contaminant level (MCL). Pesticides were found in 52% of the research wells (none exceeding
the MCL) versus 23% of the existing wells. Two existing wells had pesticide concentrations
exceeding the MCL--atrazine 6.5 ppb and alachlor 6.2 ppb. Table 2 provides a summary of
pesticides detected and confirmed in well samples.
Table 2. Summary of Pesticides Detected and Confirmed
MEAN MINIMUM MAXIMUM
Alachlor
Atrazine
Butylate
Carbaryl
Carbofuran
Chlorothalonil
Fluometuron
Linuron
Methomyl
Metolachlor
Simazine
N=number of samples with detected and confirmed pesticide
Atrazine was the most frequently detected pesticide found in all wells with 14% of the
detections, followed by fluometuron at 6.2%; carbofuran and metolachlor at 5.3%; alachlor at
3%; carbaryl and methomyl at 2%; and butylate, Chlorothalonil, linuron and simazine at 1%. The
pesticides detected were usually found at repeated sampling events, and in some cases multiple
residues were observed, but no pesticides were found in wells greater than 80 feet deep.
Each well was examined across all six sampling times for detection of any pesticide. If a
pesticide was detected at any time, the well was scored as positive, otherwise, as negative. The
research (R) and existing (E) well groups were compared using Fisher's exact test. The existing
wells were stratified further into two groups according to location: primary sites 1-21 (EP) and
additional sites 22-76 (EA). The term primary site is used here to denote those sites at which
research monitoring wells were installed. At each site, only one existing well was utilized to
avoid selection bias; the "C" wells were omitted for the following analyses.
The number of wells in which pesticides of any type were detected during the entire
sampling period are as follows:
a. R(11/21=52%) vs E(17/73=23%); p=0.015
b. EA(12/52=23%) vs EP(5/21=24%) vs R(11/21=52%); p=0.052
c. EP vs R; p=0.055
d. EA vs EP; p>0.999
2.15(N=7)
0.69 (N=33)
0.05 (N=1)
3.15 (N=2)
7.03 (N=11)
0.19(N=1)
2.26 (N=11)
0.70 (N=1)
0.45 (N=2)
13.09(N=12)
0.19 (N=1)
ppu
0.09
0.10
0.05
1.40
2.29
0.19
0.82
0.70
0.20
0.20
0.19
6.18
6.54
0.05
4.90
18.32
0.19
4.31
0.70
0.70
63.69
0.19
24
-------
Each p-va!ue corresponds to a test of the hypothesis that the detection rates are the same.
It may be concluded that there is a statistically significant difference between the likelihood
of detecting pesticides in research wells versus existing wells. Pesticides were found in 52% of
the research wells versus 23% of the existing wells. Borrowing from epidemiologic methodology,
an odds ratio was computed to describe the relative likelihood of pesticide detection in research
wells compared to existing wells. The unadjusted odds ratio (OR) was 3.4 (95% C.I.: 1.4 - 9.7),
indicating a higher incidence of detected pesticides in research wells. There was no evidence of
a significant difference between existing wells at the primary sites versus existing wells at the
additional sites. Adjusting for watershed segment (i.e., subregion), we found that the adjusted
odds ratio was 3.6 (95% C.I.: 1.3 -10.0) and the associated test of no association between
pesticide detection and well type was rejected (p=0.013). Results were similar when adjusting
forsubbasin.
Individual pesticides
Each individual pesticide was tested with regard to association between well type and
pesticide detection. Table 3 summarizes the results.
Table 3. Comparison of Pesticide Detection in Research and Existing Wells for
Individual Pesticides
Pesticide
Atrazine*
Fluometuron
Methomyl
Metolachlor
Carbofuran
Chlorothalonil
Linuron
Alachlor*
Butylate
Carbaryl
Simazine
Research
(N=21)
Existing
(N=73)
29(6)
19(4)
10(2)
10(2)
10(2)
5(1)
0(0)
0(0)
0(0)
0(0)
0(0)
10(7)
3(2)
0(0)
4(3)
4(3)
0(0)
1(1)
1(1)
1(1)
3(2)
1(1)
p-value
0.066
0.021
0.048
0.310
0.310
0.223
>0.999
>0.999
>0.999
>0.999
>0.999
OR Conf (OR)
3.8
8.4
2.5
2.5
1.2-12.2
1.8-39.5
0.4-15.1
0.4 - 15.1
"Four existing "C" wells were not used for these computations. Two of these (#58, 75) contained
alachlor and one (#75) contained atrazine. If included, the rates for existing wells become 11 %
(n=8) for atrazine (p=0.076; OR=3.3, Cl=1.0 -10.4) and 4% (n=3) for alachlor (p>0.999). Neither
pesticide was detected in both "B" and "C" wells at any site.
Analysis by region
Tables 4a and 4b show the frequencies of pesticide detection, as described above, for each
of the ten regions of the watershed and separately for each subbasin. Because sample sizes
within each region are too small to produce effective tests for differences across regions, such
tests were not conducted.
25
-------
Table 4a. Pesticide Detection by Subregion
Existing wells
Subregion
Pesticide
Not
detected
Detected
Total
1
5
3
8
2
6
1
7
3
5
2
7
4
6
2
8
5
6
2
8
6
6
2
*
8
7
6
1
7
8
5
2
7
9
5
2
7
10
6
0
6
Total
56
17
73
Research wells
Subregion
Pesticide
Not
detected
Detected
Total
1
2
1
3
2
1
1
2
3
0
2
2
4
0
2
2
5
2
0
2
6
1
1
2
7
1
1
2
8
1
1
2
9
1
1
2
10
1
1
2
Total
10
11
21
Table 4b. Pesticide Detection by Subbasin
Existing wells
Subregion
Pesticide
Not
detected
Detected
Total
J26
12
3
15
J27
9
2
11
J28
14
6
20
J29
3
1
4
J30
9
3
12
J31
1
0
1
OUT
8
2
10
Total
56
17
73
Research wells
Subregion
Pesticide
Not
detected
Detected
Total
J26
2
2
4
J27
2
1
3
J28
3
3
6
J29
0
1
1
J30
2
2
4
J31
0
0
0
OUT
1
2
3
Total
10
11
21
26
-------
Analysis by site
At the primary sites, pesticide occurrence was observed for paired research and existing
wells over all sampling times combined. Of 21 paired wells, there were 4 cases (19%) where
both types of wells were positive for pesticides, 9 (43%) where they were both negative, 7 (33%)
where the research well was positive and the existing well was negative, and 1 (5%) where the
existing well was positive but the research well was not. For these data, there is agreement in
62% of the cases and disagreement in 38% of cases. Given detectable pesticides in a research
well, one could expect to detect them also in a corresponding existing well about 36% of the time
when the wells are sampled repeatedly over a time period as in this study.
Paired research and existing wells also were examined in this fashion using data individually
measured for each sampling time. Of 118 pairs, there were 9 cases (8%) where both types of
wells were positive for pesticides, 84 (71%) where they were both negative, 17 (14%) where the
research well was positive and the existing well was negative, and 8 (7%) where the existing well
was positive but the research well was not. Forlhese data, there is agreement in 79% of the
cases and disagreement in 21 % of cases.
Analysis by crop .
With respect to pesticide detection in a well observed over time, sites at which a particular
crop was grown were compared to sites where the crop was not grown. Table 5 summarizes, for
each crop individually, the proportion of wells where pesticides were detected.
Table 5. Frequency of Detection of Pesticides by Crop Type
Crop Sites with crop Sites without crop p-value
0.041
0.210
0.368
0.644
0.748
>0.99 .
*winter wheat, barley, fallow, winter rye, bermuda grass, Christmas trees, pasture, millet,
tomatoes, sweet potatoes, collards, etc.
In these unadjusted analyses, only soybeans are significantly associated with an increased
pesticide detection rate.
Effects of other factors
Other factors were examined in stepwise logistic regression analysis in an effort to
determine whether any known variables were associated with pesticide detection. In addition to
well type (i.e., research vs existing) and site type (primary vs additional), these included well
depth (considered shallow if < 20 feet deep) and crop information as follows: corn, tobacco,
cotton, soybeans, vegetables (tomatoes, sweet potatoes, collards, watermelon, green beans,
Irish potatoes, peas, cantaloupe, cucumbers, and pepper), and other (winter wheat, barley,
fallow, winter rye, bermuda, Christmas trees, pasture, and millet). Crops were considered to be
associated with a site if they were listed as having been grown at the site during any recent
27
Soybeans
Cotton
Tobacco
Other*
Vegetables
Corn
18/44(41%)
10/25(40%)
10/41 (24%)
12/36 (33%)
3/13(23%)
16/55(29%)
10/50(20%)
18/69(26%)
18/53(34%)
16/58(28%)
25/81 (31%)
12/39(31%)
-------
growing season (1992-1994). Other factors specific to the wells were considered but could not
be used in the analysis due to missing values or other mathematical dependencies. Factors that
were specific to the water samples were not considered in this analysis.
In a full model implementation for screening purposes, the odds ratios obtained are shown
in Table 6. Higher odds ratios indicate a greater likelihood of detecting pesticides in wells of a
given characterization when compared to a reference group. The reference group for this
analysis is a non-shallow existing well at a primary site with no crop. Lower odds ratios indicate
a lesser likelihood of detection.
Table 6. Results from Full Logistic Regression Model for Pesticide Detection
Factor OR p-value
RvsE 3.7 0.066
Addl vs Primary 1.8 0.416
Shallow well 0.5 0.196
Corn 0.8 0.669
Tobacco 0.5 0.282
Cotton 3.2 0.072
Soybeans 3.9 0.023
Vegetables 0.5 0.452
Other 1.3 0.644
Table 7 shows a subsequent stepwise procedure resulting in a reduced model.
Table 7. Results of Stepwise Logistic Regression Procedure for Pesticide Detection
Factor OR p-value
RvsE
Soybeans
Cotton
Tobacco
3.3
3.0
2.3
0.5
0.035
0.037
0.129
0.145
This stepwise reduction indicates that research wells and sites near soybean crops are more
likely to have detectable pesticides. There is a much weaker indication that sites near cotton
crops also are more likely to have detectable pesticides, and there is a similarly weak indication
that a nearby tobacco crop tends to decrease the likelihood of detecting pesticides.
The use of crop information in this fashion does not imply a direct cause-effect relationship.
Different application rates, timing, usage, and uptake and conversion issues may be important.
28
-------
Nitrate-Nitrogen Detection
Descriptive statistics
In 515 samples analyzed for nitrate-N, there was a mean of 7.08 ppm and standard
deviation of 6.01 (coefficient of variation = 85%), the variability being due partly to well type,
sampling date, subregion (or subbasin), site within region, and other factors. Thirty eight of 515
samples (7%) showed no nitrate-N. Descriptive statistics are given in Tables 8a-8e for site type,
subregions, subbasins, and for primary wells and existing wells both at primary and at additional
sites, over all sampling times. The unadjusted mean for all research well samples was 9.1
(n=125) and, for existing wells, it was 6.4 (n=390). The unadjusted mean of all primary site
samples was 8.9 (n=250) and, for additional sites, it was 5.4 (n=265).
Table 8a. Nitrate-N Mean Concentrations by Site Type
SITE TYPE
Research Primary
Existing Primary
Existing Additional
N
MEAN STDERROR SD COEFVAR
125 9.14
125 8.66
265 5.35
0.55
0.60
0.31
6.19
6.72
5.01
67.7
77.6
93.5
Table 8b. Nitrate-N Mean Concentrations by Subregion
SUBREGN N MEAN STDERROR SD COEFVAR
1
2
3
4
5
6
7
8
9
10
60
49
49
59
53
53
46
49
53
44
7.50
5.52
9.92
9.95
5.11
7.17
4.46
8.90
6.97
4.29
0.63
0.38
1.26
0.66
0.61
1.08
0.72
0.96
0.61
0.76
4.89
2.66
8.81
5.07
4.46
7.87
4.87
6.70
4.44
5.03
65.2
48.2
88.8
50.9
87.3
109.7
109.3
75.3
63.7
117.2
Table 8c. Nitrate-N Mean Concentrations by Subregion and Site Type
SUBREGN SITETYPE N MEAN STDERROR SD COEFVAR
1
1
1
2
2
2
3
3
ExisAddl .
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
25
17
18
25
12
12
25
12
5.83
9.49
7.93
5.40
5.56
5.74
5.82
13.36
0.97
1.35
0.83
0.54
0.70
0.87
0.78
3.83
4.85
5.56
3.51
2.71
2.41
3.01
3.90
13.28
83.2
58.6
44.3
50.2
43.4
52.4
67.0
99.4
29
-------
RschPrim
12 15.03
2.03
7.04
46.9
4
4
4
5
5
5
6
6
6
7
7
7
8
8
8
9
9
9
10
10
10
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
29
18
12
30
12
11
29
12
12
27
7
12
25
12
12
30
11
12
20
12
12
8.02
9.64
15.09
5.65
7.09
1.48
2.45
11.00
14.75
5.54
1.07
4.01
6.46
11.90
10.99
6.07
8.68
7.66
1.31
4.83
8.73
0.76
1.11
1.29
0.82
1.33
0.41
0.61
2.49
2.11
1.10
0.30
0.86
1.65
1.01
0.77
0.94
0.70
1.04
0.40
1.43
1.60
4.08
4.70
4.47
4.49
4.60
1.35
3.30
8.61
7.30
5.73
0.80
2.96
8.25
3.49
2.66
5.14
2.31
3.61
1 .79
4.96
5.55
50.9
48.8
29.6
79.4
64.9
91.2
1.34.7
78.3
49.5
103.5
74.2
74.0
127.7
29.3
24.2
84.7
26.6
47.1
136.8
102.6
63.6
Table 8d. Nitrate-N Mean Concentrations by Subbasin
SUBBASIN N MEAN STDERROR SD COEFVAR
J26
J27
J28
J29
J30
J31
106
76
142
27
90
5
6.94
10.48
4.60
9.76
7.60
2.88
0.48
0.83
0.32
1.06
0.49
0.41
4.93
7.27
3.79
5.53
4.66
0.91
71.0
69.3
82.4
56.6
61.3
31.8
Table 8e. Nitrate-N Mean Concentrations by Subbasin and Site Type
SUBBASIN SITETYPE N MEAN STDERROR SD COEFVAR
J26
J26
J26
ExisAddl
ExisPrim
RschPrim
59
23
24
5.38
9.93
7.93
0.72
0.72
0.54
5.51
3.45
2.64
102.4
34.8
33.3
30
-------
J27
J27
J27
J28
J28
J28
J29
J29
J29
J30
J30
J30
J31
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
ExisPrim
RschPrim
ExisAddl
40 6.37
18 14.84
18 15.25
76
31
35
4.73
3.78
5.02
15 7.52
6 16.42
6 8.70
36
30
24
6.92
6.40
10.13
5 2.88
1.07
0.98
1.20
0.40
0.72
0.71
1.39
0.58
1.00
0.73
0.49
1.23
0.41
6.78
4.15
5.11
3.49
4.02
4.20
5.38
1.43
2.45
4.41
2.70
6.01
0.91
106.5
28.0
33.5
73.7
106.3
83.6
71.6
8.7
28.2
63.7
42.2
59.3
31.8
Exceedance of nitrate-N MCL
The nitrate-N MCL of 10 ppm was exceeded in 131 of 515 (25%) samples. For individual
sites, the nitrate-N MCL was exceeded at least once during the 6 sampling times as follows
(R=research wells, E=existing wells, P=primary sites, A=additional sites):
a. R(12/21 =57%) vs £(26/73=36%); p=0.085
b. EA(15/53=29%) vs EP(11/21 =52%) vs RP(12/21 =57%); p=0.033
c. EP vs RP; p>0.999
d. EA vs EP; p=0.066
There was not a significant difference between research wells and existing wells with regard
to the proportion of wells that exceeded the nitrate-N MCL at some point; whereas there was
evidence of a difference between existing wells at the primary sites and existing wells at the
additional sites.
The nitrate-N MCL was exceeded in 52% of existing wells at primary sites compared to 29%
at additional sites. The unadjusted odds ratio was 2.4 (95% C.I.: 0.9 - 6.4; p=0.078). Adjusting
for watershed segment, we found that the adjusted odds ratio was 2.8 (95% C.I.: 1.0 - 8.2) and
the corresponding test of no association between primary and additional sites was nearly
significant (p=0.060). Results were similar when controlling for subbasins.
Analysis by region
Tables 9a and 9b show the frequencies with which nitrate-N levels exceeded the MCL for
each of the ten subregions and six subbasins, respectively. No additional tests were performed
due to small sample sizes within regions.
31
-------
Table 9a. Nitrate-N > MCL by Subregion
Existing wells
Subregion
Nitrate-N
At/Below MCL
Above MCL
Total
1
6
2
8
2
4
3
7
3
4
3
7
4
5
3
8
5
5
3
8
6
6
2
8
7
5
2
7
8
4
3
7
9
3
4
7
10
5
1
6
Total
47
26
73
Research wells
Subregion
Nitrate-N
At/Below MCL
Above MCL
Total
1
1
2
3
2
1
1
2
3
0
2
2
4
0
2
2
5
2
0
2
6
0
2
2
7
2
0
2
8
1
1
2
9
1
1
2
10
1
1
2
Total
9
12
21
Table 9b. Nitrate-N > MCL by Subbasin
Existing wells
Subregion
Nitrate-N
At/Below MCL
Above MCL
Total
J26
7
8
15
J27
6
5
11
J28
16
4
20
J29
2
2
4
J30
8
4
12
J31
1
0
1
OUT
7
2
10
Total
47
26
73
Research wells
Subregion
Nitrate-N
At/Below MCL
Above MCL
Total
J26
3
1
4
J27
0
3
3
J28
4
2
6
J29
0
1
1
J30
1
3
4
J31
0
0
0
OUT
1
2
3
Total
9
12
21
32
-------
Analysis by site
At the primary sites, nitrate-N above the MCL was observed for paired research and existing
wells over all sampling times combined. Of 21 paired wells, there were 7 cases (33%) where
both types of wells were higher than the MCL, 5 (24%) where they were both below, 5 (24%)
where the research well was above and the existing well was below, and 4 (19%) where the
existing well was above but the research well was not. For these data, there is agreement in
57% of the cases and disagreement in 43% of cases. Given nitrates above the MCL in a
research well, one could expect to find nitrate-N above the MCL in a corresponding existing well
about 58% of the time when the wells are sampled repeatedly over a time period as in this study.
Analysis by crop
With respect to nitrate-N above the MCL in a well observed over time, sites at which a
particular crop was grown were compared to sites where the crop was not grown. Table 10
summarizes, for each crop individually, the proportion of wells where nitrate-N levels exceeded
the MCL. - '
Table 10. Frequency of Nitrate-N Levels Exceeding MCL by Crop Type
Crop Sites with crop Sites without crop p-value
Soybeans
Cotton
Tobacco
Other
Vegetables
Corn
20/44 (45%)
11/25(44%)
19/41 (46%)
16/36 (44%)
6/13(46%)
25/55 (45%)
18/50
27/69
19/53
22/58
32/81
13/39
(36%)
(39%)
(36%)
(38%)
(40%)
(33%)
0.403
0.812
0.397
0.666
0.763
0.289
In these unadjusted analyses, none of the crops was significantly associated with an increased
rate of high nitrate-N levels.
Effects of other factors on high nitrate-N levels
For screening purposes, several factors were included in a logistic regression model of
nitrate-N exceedances above the MCL, similar to that described above for pesticide detection.
There were no significant terms identified in this general model. Stepwise logistic regression did
identify successfully a difference due to site type (i.e., primary versus additional) with an odds
ratio of 2.6, indicating a greater likelihood of finding levels of nitrate-N above the MCL at primary
sites.
Relationship between nitrate-N > MCL and pesticide detection
There was no statistically significant association between pesticide detection and levels of
nitrate-N above the MCL. Fifteen of 39 (38%) wells that had nitrate-N above the MCL at some
time also had evidence of pesticide compared to 15 of 59 that had lower nitrate-N levels
(p=0.186).
33
-------
Correlations
Pairwise correlations were nonzero for the following variables:
Variables Correlation
Nitrate-N, TDS
Nitrate-N, pH
Nitrate-N, Well Depth
TDS, pH
pH, Well Depth
Temp, H20 Depth
0.79
-0.49
-0.20
-0.34
0.44
0.25
A scatter plot of nitrate-N vs TDS shows general linearity, and simple linear regression of
nitrate-N on TDS has R2=0.62 with slope=0.14 (p<.001). Considering only wells at primary sites,
there was a correlation of 0.48 between nitrate-N levels in research wells and existing wells.
Distributions of measured nitrate-N levels
Frequency distributions for nitrate-N were examined and are depicted in the form of
empirical cumulative distribution functions for comparison purposes. These are displayed in
attached figures for several cases. In each, the nonparametric two-sample Kolmogorov-Smirnov
(K-S) test was applied to test for differences between distributions.
Paired differences were formed by subtracting individual nitrate-N concentrations for existing
well samples from those for research wells at each sampling time for the 21 primary sites. The
median difference was -0.20 (range: -14.2 to 24.9). The distribution of these differences is
shown in Figure 11 along with a fitted normal distribution. The one-sample K-S goodness of fit
test for normality was not significant at the 0.05 level (p=0.055).
The distribution of nitrate-N levels for research well samples (n=125) were compared to
existing well samples (n=399), as depicted in Figure 12. This unadjusted overall test was highly
significant (p<0.001), with research well nitrate-N levels being stochastically larger than existing
well values.
Distributions for individual sampling times for research wells are shown collectively in Figure
13; there are no apparent differences. Similarly, distributions for existing wells over individual
sampling times (Figure 14) shows general agreement for all except those collected during
sampling date 5, in which samples from primary sites only were obtained. Further examination
shows similar distributions for existing wells at primary sites over sampling times (Figure 15a)
and existing wells at additional sites over sampling times (Figure 15b). These were combined
for all sampling times in Figure 16 and tested with the K-S procedure, in which a significant
difference was indicated (p<0.001). Further testing using all values from all sampling dates for
comparison between research wells and existing wells at primary sites (Figure 17) was not
statistically significant (p=0.155). Testing research versus existing wells over individual sampling
times for primary sites (Figure 18) reveals similar results, as does testing existing primary wells
versus existing additional wells (Figure 19). Additional cumulative distribution plots are displayed
in Figures 20 and 21 for nitrates over individual regions and subbasins.
The finding of significant differences in nitrate-N concentrations between existing primary
wells and existing additional wells, but not between research and existing primary wells, is
34
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consistent with results for exceeding the MCL given above. It also is of importance in
determining how further analysis should be conducted.
Effects due to regions and sampling times
As a preliminary analysis, differences between nitrate-N levels from research wells and
those from existing wells at the primary sites were examined in analysis of variance using as -
factors the stratification regions and sampling times. The analysis of variance is given in Table
11a. There was no evidence of a significant difference due to regions (or subbasins, data not
shown). There was only a weak indication of differences across sampling times.
Table 11 a. Preliminary Analysis of Variance for Differences Between Nitrate-N Levels:
Research Versus Existing Wells at Primary Sites
Source DF
Region 9
Site(Region) 11
SampTime 5
Region x SampTime 45
Residual 47
Total 117
MS
105.3
239.0
22.4
16.2
14.0
0.44
1.60
1.16
Pr>F
0.886
0.178
0.308
The error term for testing Region is Site(Region). The error term for testing SampTime and
Region x SampTime is SampTime x Site(Region).
A more general analysis of variance was performed for nitrate-N levels considering as
effects: regions, research-vs-existing wells, primary-vs-additional sites, and sampling time. The
results are shown in Table 11b. The analysis shows no evidence of significant differences due
to regions or to type of well (R2 = 0.86). There is evidence (p=0.055) of differences between
primary and additional sites (factor listed as "Site group"). There also is evidence of differences
in nitrate-N means due to sampling time (p=0.024); unadjusted means for each sampling time
are given in the table following 11b. The root mean squared error is 2.52, which reflects the
variability of observations within wells. Estimates of other components of variance also follow
this table.
50
-------
Table 11b. Analysis of Variance for Nitrate-N Levels in Research and Existing Wells
Source DF
Region 9
Site group 1
Region x Site group 9
Site(Region x Site group) 53
Well type 1
Region x Well type 9
Treatment x Site(Region x Site group) 11
Sampling time 5
Residual 416
MS
220.0
608.4
84.0
157.6
24.2
57.4
122.7
16.7
6.4
F
1.4
3.9
0.53
0.20
0.47
2.6
Pr>F
0.213
0.055
0.844
0.666
0.868
0.024
Site group refers to primary or additional sites. Well type refers to research or existing wells.
The error term for testing Region, Site group, and Region x Site group is Site(Region x Site
type). The error term for testing Well type and Region x Well type is Treatment x Site(Region x
Site group).
Mean
8.73
7.76
6.99
6.74
6.68
6.53
N
41
93
96
94
96
95
Unadjusted means are given below for each sampling time. A multiple-comparison
procedure indicates that sampling time 5 differs significantly from all other dates and that time 4
differs from times 2, 3, and 6. It is important to note that the mean for time 5 is based only on
sampling at primary sites (additional sites were not sampled on date 5).
Sampling
Time
5
4
1
6
3
2
The estimate of the variance component for Site(Region x Site group) was 7.1, and for
Trt x Site(Region x Site group) it was 20.5.
Statistical Summary
In view of the evidence described in this report, research hypothesis (a) must be rejected for
pesticides. The hypothesis should not be rejected for nitrates, even though nitrates were seen in
different concentrations when considering primary versus additional sites. This latter observation
could not be attributed to other factors that were part of the available data, but does raise a
question as to its cause. Further field data may be required to resolve the issue.
Hypothesis (b) was addressed by examining other factors in logistic regression analysis for
pesticides and for nitrate-N exceedance above the MCL. For pesticides, factors identified as
having prognostic value included soybeans, cotton, and tobacco, in which case there was still a
significant difference between research and existing wells after adjustment. For nitrate-N levels
above the MCL, no factors other than site type (i.e., primary versus additional) were identified to
be associated with differential likelihood levels. There was a high correlation between nitrate-N
and TDS values.
51 . '
-------
Results from analyses conducted over watershed segments (i.e., subregions) did not differ.
appreciably when reformulated in terms of subbasins. Subbasin information was not available at
the time this study was designed. With the exception of the few outliers mentioned above, there
were no obvious inconsistencies regarding individual observations in the database. The data
quality appears to be very high. In addition, there were no contradictory results obtained in the
statistical analyses.
52
-------
REFERENCES
Brandon, C. E. 1985. Soil Survey of Sampson County, North Carolina, U.S. Department of
Agriculture, Soil Conservation Service. ;
Burkart, M. R. and D. W. Kolpin. 1993. Hydrologic and Land-Use Factors Associated with
Herbicides and Nitrate in Near-Surface Aquifers. J. Environ. Qual. 22:646-656.
Fleiss, J. L. 1981. Statisitcal Methods for Rates and Proportions. New York, John Wiley and
Sons.
Hallberg, G.R. 1989. Pesticide pollution of Groundwater in the Humid United States. Agric. Eco.
and Environ. 26:299-367.
Hoheisel, C., J. Karrie, S. Lees, L. Davies-Hilliard, P. Hannon, R. Bingham, E. Behl, D. Wells,
and E. Waldman. 1992. Pesticides in Ground Water Database. A Compilation of Monitoring
Studies: 1971-1991 National Summary. EPA 734-12-92-001 U. S. Environmental Protection
Agency: Arlington, VA.
Hollander, M. and D. Wolfe. 1973. Nonparametric Statistical methods. (Book). New York, John
Wiley and Sons.
Mass, R.P., D. J. Kuchen, S.C. Patch, B.T. Peek, and D. L. Van Engelen. 1995. Pesticides in
Eastern North Carolina Rural Supply Wells: Land Use Factors and Persistence. J. Environ. Qual.
24:426-431.
Time, 1995. Health Report, August 28, 1995., p 25.
U.S. EPA, 1989. The Determination of Inorganic Anions in Water by Ion Chromatography -
Method 300.0, U. S. Environmental Protection Agency, Cincinnati, OH.
U.S. EPA. 1990. National Survey of Pesticides in Drinking Water Wells. Phase I Report. USEPA-
579/9-90-015. U. S. Environmental Protection Agency, Washington, DC.
U.S. EPA, 1991. Environmental Compliance Branch Standard Operating Procedures and Quality
Assurance Manual. Region IV, U.S. Environmental Protection Agency, Athens, GA.
U.S. EPA. 1992. National Pesticide Survey Update and Summary of Phase II Results. USEPA-
570/9-91-021. U. S. Environmental Protection Agency, Washington, DC.
U.S. EPA, 1994. Determination of Organic Compounds in Drinking Water by Liquid-Solid
Extraction and Capillary Column Gas Chromatography/Mass Spectrometry,,
Method 525.1 Revision 2.2 (July 1991), 525.2 Revision 1.0 (February 1994)
U. S. Environmental Protection Agency, Cincinnati, OH.
Wiles, R., B Cohen, C. Campbell and S. Eiderkin. 1994. Tap Water Blues, Herbicides in
Drinking Water. Environmental Working Group, Washington, DC. 276 p.
53
-------
Appendices
54
-------
CROP BY SITE AND YEAR
SITE
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1992
corn
tobacco,
sweet potato
cotton
soybean
soybean
tobacco
tobacco
watermelon
soybean
corn
corn
collard
cotton
soybean
corn
soybean .
soybean
cotton
soybean
corn
soybean
tobacco
corn
cotton
tobacco
1993
corn
tobacco
tobacco
soybean
sweet potato
tobacco
soybean
corn
tobacco
corn
soybean
tobacco
soybean
soybean
collard
cotton
tobacco
wheat (winter)
soybean
corn
corn
cotton
soybean
corn
soybean .
tobacco
corn
cotton
tobacco
1994
soybean
tobacco
sweet potato
wheat (winter)
tobacco
rye (winter)
soybean
com
wheat (winter)
corn
Irish potato
corn
greenbean
wheat (winter)
corn
soybean
wheat (winter)
fallow (upslope)
corn (downslope)
cotton
barley
corn
soybean
tobacco
corn
cotton
tobacco
55
-------
SITE 1992
1993
1994
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
corn
soybean
tobacco
cotton
cotton
cotton
tobacco
fallow
-
soybean
bermuda
-
-
-
-
-
Christmas trees
-
-
-
-
-
corn
soybean
barley (winter) ,
rye (winter)
tobacco
soybean
corn
tobacco
tobacco
cotton
pasture
winter rye
pasture
corn
soybean
bermuda
pasture
fallow
corn
pasture
corn
tobacco
pasture
corn
Christmas trees
corn
corn
tobacco
watermelon
pasture
millet
corn
soybean
tobacco ...
cotton
cotton
tobacco
cotton
pasture
winter rye
pasture
corn
tobacco
bermuda
pasture
fallow
corn.
pasture
corn
tobacco
pasture
corn
Christmas trees
corn
corn
soybean
tobacco
tobacco
pasture
soybean
56
-------
SITE 1992
35
36
37 pasture
38
39
40
41
42
43
45
46
48
49 -
50
51
53 -
54
55
56
57
58
1993
sweet potato
tobacco
pasture
soybean
bermuda
bermuda
corn
tobacco
soybean
soybean
corn
cotton
soybean
corn
cotton
corn
cotton
cotton
watermelon
sweet potato
pasture
pasture
corn
pasture
soybean
corn
corn
1994
fallow
tobacco
pasture
soybean
bermuda
bermuda
corn
tobacco
corn
corn
cotton
soybean
soybean
corn
cotton
corn
cotton
cotton
corn
tobacco
corn
pasture
cotton
pasture
soybean
corn
corn
57
-------
SITE 1992
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
1993
soybean
corn
tobacco
bermuda
cotton
sweet potato
corn
peas
cotton
cotton
cotton
corn
corn
cotton
corn
corn
tobacco
soybean
corn
tobacco
soybean
cotton
tobacco
com
corn
soybean
tobacco
corn
pasture
watermelon
tomato
cantaloupe
1994
corn
bermuda .
soybean
cotton
tobacco
corn
cotton
cotton
tobacco
corn
corn
soybean
soybean
corn
tobacco
cotton
tobacco
corn
soybean
corn
tobacco
tobacco
pasture
cucumber
pepper
75
76
corn
pasture
corn
pasture
58
-------
WELL
SITE
1A
1A
1A
1A
1A
1A
2A
2A
2A
2A
2A
2A
3A
3A
3A
3A
3A
3A
4A
4A
4A
4A
4A
4A
5A
5A
5A
5A
5A
5A
6A
6A
6A
6A
6A
6A
SAMPLING
DATE
03-23-93
07-14-93
11-09-93
03-01-93
05-17-94
06-20-94
03-23-93
07-14-93
11-09-93
02-28-94
05-16-94
06-21-94
03-23-93
07-13-93
11-10-93
03-04-94
05-17-94
06-21-94
03-23-93
07-13-93
11-09-93
03-01-94
05-17-94
06-21-94
03-23-93
07-14-93
,11-10-93
03-01-94
05-16-94
06-20-94
03-23-93
07-16-93
11-11-93
03-01-94
, 05-17-94
06-21-94
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
PH
3.34
4.88
4.49
4.01
4.67
4.60
4.54
4.80
4.30
4,34
4.48
4.64
4.30
5.00
4.71
5.82
4.80
4.64
4.20
4.70
6.22
4.72
5.73
6.43
4.42
4.60
4.36
4.28
4.58
4.43
4.32
4.40
4.15
4.34
4.37
4.60
COND.
(mg/l)
NA
61.0
76.2
85.2
60.2
92.9
NA
82.0
78.0
78.8
78.8
80.9
NA
68.0
48.3
58.7
41.7
44.4
NA
41.0
41.3
38.2
47.5
42.4
NA
94.0
93.8
104.0
109.0.
159.0
NA
208.0
154.0
134.0
127.0
138.0
TEMP
(C)
16.8
20.9
16.2
13.2
17.2
29.0
16.5
22.0
n/a
. 13.5
18.2
23.1
16.7
21.3
17.3
14.3
19.1
21.0
20.6
22.2
14.8
14.7
17.3
22.0
19.2
22.0
17.9
15.3
19.3
24.1
16.0
20.0
18.5
13.9
18.6
22.1
DEPTH OF
WELL
(FT)
30
30
30
30
30
30
20
20
20
20
20
20
30
30
30
30
30
30
35
35
35
35
35
35
30
30
3.0
30
30
30
25
25
25
25
25
25
DEPTH TO
WATER
(FT)
12.0
13.6
14.6
12.5
13.2
13.0
6.3
10.2
10.2
8.7
9.5
8.0
6.7
10.7
14.0
11.0
12.0
, 12.7
13.7
16.3
19.2
17.5
17.5
17.7
13.2
16.7
16.8
'14.2
15.8
16.3
4.5
11.0
9.5
7.0
NA
10.7
NA = Not Analyzed
NS = Not Sampled
59
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
7A
7A
7A
7A
7A
7A
8A
8A
8A
8A
8A
8A
9A
9A
9A
9A
9A
9A
10A
10A
10A
10A
10A
10A
11A
11A
11A
11A
11A
11A
12A
12A
12A
12A
12A
12A
DATE
COLLECTED
03-24-93
07-16-93
11-11-93
03-04-94
05-17-94
06-21-94
03-24-93
07-19-93
11-11-93
03-04-94
05-17-94
06-21-94
03-24-93
07-15-93
11-12-93
03-07-94
NS
06-22-94
03-26-93
07-15-93
11-10-93
03-01-94
05-16-94
06-22-94
03-25-93
07-14-93
11-10-93
03-01-94
05-16-94
06-20-94
03-25-93
07-15-93
11-10-93
03-01-94
05-17-94
06-23-94
pH
4.26
4.60
4.53
4.43
5.07
4.33
4.45
4.60
4.50
4.50
5.03
4.97
5.32
6.10
6.00
6.04
NS
5.63
4.46
4.52
4.72
4.57
5.43
5.11
NA
4.50
4.39
4.32
4.37
4.72
4.67
4.60
4.52
4.91
5.46
4.77
COND.
(mg/l)
NA
75.0
63.2
63.3
72.0
65.0
NA
69.0
41.4
68.9
84.8
86.4
NA
27.0
23.5
27.3
NS
26.3
NA
57.7
54.8
50.3
61.7
55.3
NA
64.2
65.5
67.0
79.8
70,5
NA
75.0
78.7
73.4
77.4
76.0
TEMP.
(C)
17.3
19.2
18.9
17.7
18.3
28.0
15.3
19.6
22.5
16.4
NA
NA
15.9
22.0
15.2
17.3
NS
NA
14.2
18.8
16.8
10.8
NA
17.5
NA
23.0
19.5
14.5
NA
27.6
13.5
23.5
19.1
12.2
NA
24.9
DEPTH OF
WELL
(FT)
30
30
30
30
30
30
25
25
25
25
25
25
20
20
20
20
20
20
20
20
20
20
20
20
25
25
25
25
25
25
20
20
20
20
20
20
DEPTH TO
WATER
(FT)
3.4
9.0
6.8
2.7
6.5
4.7
4.0
8.2
8.5
3.4
7.3
7.6
13.7
7.3
4.5
3.3
NS
4.7
2.2
7.0
4.7
2.5
4.5
NA
6.0
8.8
10.0
8.0
8.4
9.0
4.0
' 5.5
5.8
4.8
5.4
NA
NA = Not Analyzed
NS = Not Sampled
60
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
13A
13A
13A
13A
13A
ISA
14A
14A
14A
14A
14A
14A
15A
15A
15A
15A
15A
15A
16A
16A
16A
16A
16A
16A
17A
17A
17A
17A
17A
17A
18A
18A
18A
18A
18A
18A
DATE
COLLECTED
03-24-93
07-15-93
11-12-93
03-01-94
05-18-94
06-23-94
03-25-93
07-19-93
11-11-93
03-05-94
05-17-94
06-22-94
03-25-93
07-15-93
11-11-93
03-04-94
05-18-94
06-22-94
03-25-93
07-16-93
11-11-93 .
03-04-94
05-18-94
06-22-94
03-26-93
07-19-93
11-11-93
03-05-94
05-17-94
06-21-94
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22'-94
PH
4.58
5.00
4.64
4.68
5.53
5.05
4.13
4.31
4.15
4.26
4.34
4.38
4.39
4.90
4.48
4.60
4.89
4.32
4.41
4.75
4.63
4.95
4.73
4.62
4.36
4.63
4.62
4.60
4.77
5.37
4.49
4.50
4.42
4.33
4.64
4.45
COND.
(mg/l)
NA
86.0
39.2
44.0
44.3
43.1
NA
128.0
97.3
149.0
137.0
137.0
NA
75.0
100.0
66.0
74.5
75.8
NA
101.0
88.8
105.0
120.0
126.0
NA
72.3
41.3
47.1
40.7
36.5
NA
68.0
57.0
73.9
65.1
75.5
TEMP.
(C)
17.5
19.7
14.8
14.6
17.8
20.1
17.9
22.5
23.6
17.9
19.0
20.9
17.4
23.0
18.5
18.8
NA
22.5
15.1
25.0
15.7
17.2
17.3
NA
15.8
21.0
17.3
14.8
18.2
20.6
17.2
21.3
19.3
15.5
18.8
23.8
DEPTH OF
WELL
(FT)
25
25
25
25
25
25
30
30
30
30
30
30
25
25
25
25
25
25
25
25
25
25
25
25 .
20
20
20
20
20
20
20
20
20
20
20
20
DEPTH TO
WATER
(FT)
7.0
12.3
11.0
8.3
11.6
10.3
9.9
14.4
13.2
9.0
12.3
12.8
4.2
7.3
8.7
4.7
7.3
NA
4.6
9.8
6.7
5.4
7.6
6.5
0.0
4.7
1.3
0.5
NA
1.3
1.6
4.8
4.3
2.5
4.6
4.4
NA = Not Analyzed
NS = Not Sampled
61
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
19A
19A
19A
19A
19A
19A
20A
20A
20A
20A
20A
20A
21A
21A
21A
21A
21A
21A
DATE
COLLECTED
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
03-26-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
pH
4.39
4.75
4.61
4.43
5.00
4.72
4.36
4.55
4.67
4.69
4.84
4.74
4.60
5.20
4.78
4.75
5.31
4.87
COND.
(mg/l)
NA
44.5
36.9
32.2
34.9
37.2
NA
62.0
57.0
54.0
47.9
56.5
NA
38.0
63.8
157.0
53.2
69.3
TEMP.
(C)
15.7
18.7
17.6
19.2
NA
NA
17.2
21.9
19.0
16.3
17.7
NA
16.5
19.5
19.7
15.9
17.9
22.4
DEPTH OF
WELL
(FT)
30
30
30
30
30
30
30
30
30
30
30
30
25
25
25
25
25
25
DEPTH TO
WATER
(FT)
6.7
11.3
10.3
7.3
10.0
11.4
5.7
9.5
6.8
5.5
7.3.
NA
6.2
7.7
5.8
6.0
NA
6.5
NA = Not Analyzed
NS = Not Sampled
62
-------
FIELD SAMPLING DATA
LITTLE COHAR1E WATERSHED
WELL
SITE
1B
1B
1B
1B
1B
1B
2B
2B
2B
2B
2B
2B
3B
3B
3B
3B
3B
3B
4B
4B
4B
4B
4B
4B
5B
5B
5B
5B
5B
5B
6B
6B
6B
6B
6B
6B
DATE
COLLECTED
03-23-93
07-14-93
11-09-93
03-01-93
05-17-94
06-20-94
03-23-93
07-14-93
11-09-93
02-28-94
05-16-94
06-21-94
03-23-93
07-13-93
11-10-93
03-04-94
05-17-94
06-21-94
03-23-93
07-13-93
11-09-93
03-01-94
05-17-94
06-21-94
03-23-93
07-14-93
11-10-93
03-01-94
05-16-94
06-20-94
03-23-93
07-16-93
11-11-93
03-01-94
05-17-94
06-21-94
PH
3.85
4.72
4.52
4.48
4.80
4.60
NA
5.70
5.76
5.60
5.93
5.01
NA
5.50
5.02
5.19
5.10
5.20
7.60
NA
4.81
NA
5.23
4.81
NA
4.90
4.84
5.16
5.01
4.83
NA
4.80
4.40
4'.73
4.42
4.43
COND.
(mg/l)
NA
91.7
87.9
107.0
83.5
92.9
NA
109.0
120.0
120.0
111.0
111.0
NA
17.8
18.1
18.9
18.7
17.1
NA
NA
47.0
NA
48.8
68.8
NA
79.0
76.6
87.8
90.9
91.1
NA
174.0
136.0
158.0
157.0
156.0
TEMP.
(C)
17.3
19.6
15.6
13.7
17.1
29.0
NA
22.0
13.5
11.2
23.1
NA
NA
21.0
16.0
16.5
20.6
25.7
18.2
NA
15.8
NA
NA
24.8
NA
23.0
18.0
11.9
21.3
24.1
NA
25.0
20.3
10.8
19.1
27.9
DEPTH OF
WELL
(FT)
28
28
28
28
28
28
38
38
38
38
38
38
80
80
80
80
80
80
80
80
80
80
80
80
20
20
20
20
20
20
20
20
20
20
20
20
NA = Not Analyzed
NS = Not Sampled
63
-------
FIELD SAMPLING DATA
LITTLE COHARIE. WATERSHED
WELL
SITE
7B
7B
7B
7B
7B
7B
8B
8B
8B
8B
8B
8B
9B
9B
9B
9B
9B
9B
10B
10B
10B
10B
10B
10B
11B
10B
10B
10B
10B
10B
12B
12B
12B
12B
12B
12B
DATE
COLLECTED
03-24-93
07-16-93
11-11-93
03-04-94
05-17-94
06-21-94
03-24-93
07-19-93
11-11-93
03-04-94
05-17-94
06-21-94
03-24-93
07-15-93
11-12-93
03-07-94
NS
06-22-94
03-26-93
07-15-93
11-10-93
03-01-94
05-16-94
06-22-94
03-25-93
07-14-93
11-10-93
03-01-94
05-16-94
06-20-94
03-25-93
07-15-93
11-10-93
03-01-94
05-17-94
06-23-94
PH
NA '
4.80
5.40
5.16
5.66
5.24
NA
4.90
4.46
4.54
4.80
4.78
NA
4.60
4.49
4.61
4.79
4.46
NS
NS
NS
NS
NS
4.79
NA
4.60
4.90
4.19
4.43
4.47
NA
5.10
4.79
5.11
5.04
5.09
COND.
(mg/l)
NA
38.0
33.6
36.4
38.4
44.1
NA
105.0
87.3
92.4
100.0
100.0
NA
97.0
110.0
97.3
107.0
113.0
NS
NS
NS
NS
NS
77.9
NA
67.6
81.0
108.0
54.6
103.0
NA
17.0
16.7
17.4
18.3
18.8
TEMP.
(C)
NA
20.0
19.5
20.5
20.8
25.0
NA
21.9
20.0
17.1
NA
NA
NA
34.0
14.7
14.2
NA
NA
NS
NS
NS
NS
NS
18.2
NA
23.0
20.9
13.0
23.3
29.2
NA
25.0
16.5
12.5
NA
24.2
DEPTH OF
WELL
(FT)
27
27
27
27
27
27
21
21
21
21
21
21
12
12
12
12
12
12
15
15
15
15
15
15
25
25
25
25
25
25
18
18
18
18
18
18
NA = Not Analyzed
NS = Not Sampled
64
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
13B
13B
13B
13B
13B
13B
14B
14B
14B
14B
14B
14B
15B
15B
15B
15B
15B
15B
16B
16B
16B
16B
16B
16B
17B
17B
17B
17B
17B
17B
18B
18B'
18B
18B
18B
18B
DATE
COLLECTED
03-24-93
07-15-93
11-12-93
03-01-94
05-18-94
06-23-94
03-25-93
07-19-93
11-11-93
03-05-94
05-17-94
06-22-94
03-25-93
07-15-93
11-11-93
03-04-94
05-18-94
06-22-94
03-25-93
07-16-93 .
11-11-93
03-04-94
05-18-94
06-22-94
03-26-93
07-19-93
11-11-93
03-05-94
05-17-94
06-21-94
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
PH
NA
5.10
4.98
5.15
5.69
5.30
NA
4.95
4.52
4.47
4.68
4.77
NA
6.00
6.43
6.80
5.48
5.52
NA
4.90
4.62
4.72
4.76
4.42
NA
4.75
4.72
NA
5.24
5.14
NA
5.20
4.75
4.65
5.60
4.53
COND.
(mg/l)
NA
98.0
48.4
43.3
47.8
48.6
NA
47.0
42.6
49.9
47.9
49.1
NA
33.0
23.0
22.1
26.2
20.4
NA
171.0
134.0
139.0
139.0
142.0
NA
35.5
36.6
NA
32.3
35.9
NA
41.0
39.5
42.7
45.1
47.6
TEMP.
(C)
NA
21.8
13.2
14.8
18.5
19.9
NA
27.5
17.5
17.2
23.6
17.0
NA
23.0
14.1
20.1
18.9
22.2
NA
21.9
15.3
17.1
17.3
NA
NA
21.0
16.0
NA
21.1
22.9
NA
20.0
19.7
17.9
17.6
25.3
DEPTH OF
WELL
(FT)
18
18
18
18
18
18
25
25
25
25
25
25
20
20
20
20
20
20
25
25
25
25
25
25
20
20
20
20
20
20
20
20
20
20
20
20
NA = Not Analyzed
NS = Not Sampled
65
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
19B
19B
19B
19B
19B
19B
20B
20B
20B
20B
20B
20B
21 B
21 B
21 B
21B
21 B
21 B
22B
22B
22B
22B
22B
22B
23B
23B
23B
23 B
23 B
23B
24B
24B
24B
24B
24B
24B
DATE
COLLECTED
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
03-25-93
07-19-93
11-12-93
03-05-94
05-18-94 '
06-22-94
03-26-93
07-19-93
11-12-93
03-05-94
05-18-94
06-22-94
03-26-93
07-14-93
1.1-10-93
03-01-94
NS
06-24-94
03-26-93
07-14-93
11-10-93
03-03-94
NS
06-24-94
03-26-93
07-14-93
11-10-93
03-03-94
NS
06-24-94
PH
NA
4.78
4.80
5.09
5.60
4.77
NA
5.29
5.00
5.61
5.29
4.83
NA
4.70
4.43
4.50
4.81
4.97
NA
4.90
4.47
NA
NS
4.55
NA
4.95
47.30
5.18
NS
4.56
NA
8.00
8.02
8.39
NS
7.67
COND.
(mg/l)
NA
65.0
61.9
61.1
61.1
65,8
NA
56.6
66.4
48.0
75.2
76.9
NA
116.0
113.0
101.0
121.0
126.0
NA
118.0
101.0
130.0
NS
98.6
NA
48.1
47.3
50.3
NS
54.7
NA
312.0
277.0
286.0
NS
309.0
TEMP.
(G)
NA
21.3
17.9
19.0
NA
NA
NA
24.0
17.7
16.0
17.8
NA
NA
21.0
21.8
17.9
18.3
25.7
NA
21.0
18.3
13.2
NS
NA
NA
24.0
20.1
14.2
NS
NA
NA
26.0
16.5
14.5
NS
NA
DEPTH OF
WELL ,
(FT)
30
30
30
30
30
30
30
30
30
30
30
30
25
25
25
25
25
25
12
12
12
12
12
12
18
18
18
18
18
18
250
250
250
250
250
250
NA = Not Analyzed
NS = Not Sampled
66
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
DATE
COLLECTED
PH
COND.
(mg/l)
TEMP.
(C)
DEPTH OF
WELL
(FT)
25B
25B
25B
25B
25B
25B
26B
26B
26B
26B
26B
26B
27B
27B
27B
27B
27B
27B
288
28B
28B
28B
28B
28B
29B
29B
29B
29B
29B
29B
30B
SOB
SOB
SOB
SOB
SOB
03-26-93
07-14-93
11-10-93
03-03-94
NS
06-24-94
03-29-93
07-14-93
11-15-93
03-03-94
NS
06-24-94
03-25-93
07-14-93
11-15-93
03-03-94
NS
06-24-94
03-25-93
07-15-93
11-15-93
03-03-94
NS
06-24-94
03-29-93
07-15-93
11-10-93 ,
03-03-94
NS
06-24-94
03-29-93
07-15-93
11-15-93
03-03-94
NS
06-24-94
NA -
6.10
6.02
6.02
NS
5.48
NA
7.00
6.92
6.80
NS
6.68
NA
5.70
4.80
5.07
NS
5.26
NA
5.30
4.90
5.10
NS
4.99
NA
4.80
6.00
4.86
NS
4.56
NA
.4.70
4.62
5.1.1
NS
4.48
NA
22.0
60.8
21.8
NS
23.9
NA
64.0
65.0
62.4
NS
76.8
NA
53.0
58.6
99.9
NS
66.3
NA
62.0
53.6
57.4
NS
61.7
NA
29.6
49.2
0.8
NS
33.7
NA
97.0
83.1
167.0
NS
95.0
NA
22.0
17.6
14.6
NS
NA
NA
24.0
21.7
14.8
NS ,
NA
NA
21.5
22.1
15.0
NS
NA
NA
31.2
20.9
15.0
NS
NA
NA
20.3
17.3
NA
NS
NA
NA
22.0
19.6
15.1
NS
NA
30
30
30
30
30
30
160
160
160
160
160
160
18
18
18
18
18
18
20
20
20
20
20
20
15
15
15
15
15
15
24
24
24
24
24
24
NA = Not Analyzed
NS = Not Sampled
67
-------
FIELD SAMPLING DATA
LITTLE CQHARIE WATERSHED
WELL
SITE
31 B
31 B
31B
31B
31B
31B
32B
32B
32B
32B
32B
32B
33B
33B
33B
33B
33B
33B
34B
34B
34B
34B
34B
34B
35B
35B
35B
35B
35B
35B
36B
36B
36B
36B
36B
36B
DATE
COLLECTED
03-29-93
07-15-93
11-09-93
03-03-94
NS
06-24-94
03-25-93
07-13-93
11-09-93
03-03-94
NS
06-24-94
03-29-93
07-13-93
11-09-93
03-03-94
NS
06-24-94
03-25-93
07-13-93
11-09-93
03-03-94
NS
06-24-94
03-29-93
07-14-93
11-10-93
03-03-94
NS
06-21-94
03-27-93
07-14-93
11-10-93
03-03-94
NS
06-24-94
pH
NA
5.30
4.30
5.36
NS
4.64
NA
NA
4.63
4.30
NS
4.81
NA
5.20
5.10
4.52
NS
4.61
NA
4.70
4.87
4.88
NS
4.93
NA
6.00
5.62
5.61
NS
5.30
NA
5.50
4.81
5.52
NS
5.72
COND.
(mg/l)
NA
29.3
36.5
40.1
NS
43.7
NA
NA
59.3
52.1
NS
57.3
NA
48.5
40.7
44.4
NS
51.4
NA
116.0
83.6
90.7
NS
96.6
NA
18.3
18.5
19.5
NS
26.7
NA
114.0
60.4
42.2
NS
36.2
TEMP.
(C)
NA
20.2
16.9
NA
NS
NA
NA
NA ..
16.0
12.2
NS
NA
NA
22.0
17.1
12.2
NS
NA
NA
22.8
17.0
11.6
NS
NA
NA
22.0
16.4
14.7
NS
NA
NA
23.0
17.3
14.1
NS
NA
DEPTH OF
WELL
(FT)
13
13
13
13
13
13
18
18
18
18
18
18
15
15
15
15
15
15
20
20
20
20
20
20
60
60
60
60
60
60
20
20
20
20
20
20
NA = Not Analyzed
NS = Not Sampled
68
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL DATE pH
SITE COLLECTED
COND.
(mg/l)
TEMP.
(C)
DEPTH OF
WELL
(FT)
37B
37B
37B
37B
37B
37B
38B
38B
38B
38B
38B
38B
39B
39B
39B
39B
39B
39B
40B
40B
40B
40B
40B
40B
41B
41B
41B
41B
41B
41B
42B
42B
42B
42B
42B
42B
03-29-93
07-14-93
11-10-93
03-03-94
NS
06-24-94
03-27-93
07-14-93
11-09-93
03-03-94
NS
06-24-94
03-27-93
07-13-93
11-09-93
03-03-94
NS
06-24-94
03-27-93
07-13-93
11-09-93
03-03-94
NS
06-24-94
03-27-93
07-13-93 .
11-09-93
03-03-94
NS
06-24-94
03-29-93
07-20-93
11-15-93.
03-02-94
NS
06-24-94
NA
6.84
6.63
7.56
NS
6.14
NA
6.30
6.36
6.23
NS
5.95
NA
5.30
5.46
5.34
NS
5.07
NA
5.24
5.12
5.62
NS
5.52
NA
NA
4.69
4.80
NS
4.40
NA
4.72
4.54
4.55
NS
4.68
NA
66.2
63.4
59.4
NS
64.8
NA
48.4
49.3
46.7
NS
49.0
NA
33.8
40.9
40.1
NS
34.1
NA
35.0
31.1
140.0
NS
46.6
NA
NA
83.1
66.5
NS
73.2
NA
63.0
59.1
237.0
NS
75.8
NA
24.6
. 15.7
15.6
NS
NA
NA
21.0
14.2
13.7
NS
NA
NA
21.0
15.6
13.7
NS
NA
NA
25.0
16.6
14.3
NS
NA
. - NA
NA
16.2
11.5
NS
NA
NA
19.9
18.7
14.8
NS
NA
50
50
50
50
50
50
60
60
60
60
60
60
18
18
18
18
18
18
20
20
20
20
20
20
20
20
20
20
20
20
16
16
16
16
16
16
NA = Not Analyzed
NS = Not Sampled
69
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
43B
43B
43B
43B
438
43B
44B
44B
44B
44B
44B
44B
45B
45B
45B
45B
45B
45B
46B
46B
46B
46B
46B
46B
47B
47B
47B
47B
47B
47B
48B
48B
48B
48B
48B
48B
DATE
COLLECTED
03-29-93
07-20-93
11-15-93
03-04-94
NS
06-24-94
NS
NS
NS
NS
NS
NS
03-30-93
07-21-93
11-13-93
03-04-94
NS
06-27-94
03-30-93
07-21-93
11-13-93
03-07-94
NS
06-27-94
NS
NS
NS
NS
NS
NS
03-30-93
07-20-93
11-13-93
03-05-94
NS
06-23-94
NA
5.28
4.61
5.03
NS
4.91
NS
NS
NS
NS
NS
NS
NA
4.60
4.31
4.39
NS
4.31
NA
4.80
5.33
4.49
NS
5.11
NS
NS
NS
NS
NS
NS
NA
5.06
4.41
4.53
NS
4.69
COND.
(mg/l)
NA
64.3
56.1
78.6
NS
65.6
NS
NS
NS
NS
NS
NS
NA
62.0
64.0
60.4
NS
77.0
NA
93.6
45.0
115.0
NS
71.7
NS
NS
NS
NS
NS
NS
NA
77.0
76.0
75.7
NS
83.5
TEMP. '
(C)
NA
20.6
19.9
17.6
NS
NA
NS
NS
NS ,
NS
NS
NS
NA
20.3
20.4
19.2
NS
NA
NA
19.6
18.9
14.2
NS
NA '
NS
NS
NS
NS
NS
NS
NA
21.4
18.8
17.1
NS
NA .
DEPTH OF
WELL
(FT)
22
22
22
22
22
22
NS
NS
NS
NS
NS
NS
18
18
18
18
18
18
22
22
22
22
22
22
NS
NS
NS
NS
NS
NS
18
18
18
18
18
18
NA = Not Analyzed
NS = Not Sampled
70
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
49B
49B
49B
49B
49B
49B
SOB
SOB
SOB
SOB
SOB
SOB
51B
51B
51B
51B
51B
51B
52B
52B
52B
52B
52B
52B
53B
53B
53B
53B
53B
53B
54B
54B
54B
54B
54B
54B
DATE
COLLECTED
03-30-93
07-19-93
11-13-93
03-07-94
NS
06-25-94
03-30-93
07-19-93
11-13-93
03-05-94
NS
06-25-94
03-30-93
07-19-93
11-12-93
03-07-94
NS
06-23-94
NS
NS
NS
NS
NS
NS
03-29-93
07-19-93
11-12-93
03-07-94
NS
06-25-94
03-30-93
07-19-93
11-15-93
03-07-94
NS
06-25-94
PH
NA
5.40
5.09
5.42
NS
5.12
NA-
4.80
4.34
4.61
NS
4.46
NA
5.28
4.72
4.84
NS
5.10
NS
NS
NS
NS
NS
NS
NA
5.55
5.45
5.14
NS
5.29
NA
4.75
4.51
4.59
NS
4.74
COND.
(mg/l)
NA
18.2
20.0
31.1
NS
20.5
NA
49.2
48.5
50.0
NS
45.5
NA
20.1
41.5
29.8
NS
34.8
NS
NS
NS,
NS
NS
NS
NA
39.0
42.6
45.0
NS
45.0
NA
63.5
68.2
80.1
NS
59.5
TEMP.
(C)
NA
21.6
21.3
19.6
NS
NA
NA
20.6
19.3
18.6
NS
NA
NA
23.6
18.8
23.5
NS
NA
NS
NS
NS
NS
NS
NS
NA
22.3
19.4
18.6
NS
NA
NA
25.4
20.6
17.4
NS
NA
DEPTH OF
WELL
(FT)
15
15
15
15
15
15
18
18
18
18
18
18
40
40
40
40
40
40
NS
NS
NS
NS
NS
NS
40
40
40
40
40
40
13
13
13
13
13
13 '
NA = Not Analyzed
NS = Not Sampled
71
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
55B
55B
55B
55B
55B
55B
56B
56B
56B
56B
56B
56B
57B
57B
57B
57B
57B
57B
58B
58B
58B
58B
58B
58B
59B
59B
59B
59B
59B
59B
60B
60B
60B
60B
60B
60B
DATE
COLLECTED
03-30-93
07-20-93
11-16-93
03-07-94
NS
06-25-94
03-30-93
07-20-93
11-15-93
03-07-94
NS
06-25-94
03-30-93
07-20-93
11-15-93
03-07-94
NS
NS
03-30-93
07-20-93
11-15-93
03-07-94
NS
06-25-94
03-30-93
07-20-93
11-15-93
03-07-94
NS
06-25-94
03-29-93
07-19-93
11-13-93
03-07-94
NS
06-25-94
pH
NA
4.73
4.63
4.48
NS
4.32
NA
4:78
4.62
4.65
NS
4.53
NA
4.81
4.52
4.79
NS
NS
NA
5.45
4.89
4.84
NS
5.02
NA
5.01
4.59
4.67
NS
4.74
NA
4.86
4.80
4.85
NS
4.47
COND. TEMP.
(mg/l) (C)
NA NA
144.0 20.1
103.0 19.9
128.0 18.8
NS NS
12.1 NA
NA NA
62.0 23.3
64.0 20.5
60.2 17.4
NS NS
63.7 NA
NA NA
83.0 22.0
74.7 22.7
62.5 16.4
NS NS
NS NS
NA NA
40.0 22.9
40.8 20.3
42.8 21.1
NS NS
42.5 NA
NA NA
85.0 20.8
97.3 20.9
50.4 21.8
NS NS
47.9 NA
NA NA
59.0 21.7
56.0 20.5
56.2 21.3
NS NS
58.6 NA
DEPTH OF
WELL
(FT)
18
18
18
18
18
18
20
20
20
20
20
20
13
13
13
13
13
13
25
25
25
25
25
25
20
20
20
20
20
20
18
18
18
18
18
18
NA = Not Analyzed
NS = Not Sampled
72
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
61B
61B
61B
61B
61B
61B
62B
62B
62B
62B
62B
62B
63B
63B
63B
63B
63B
63B
64B
64B
64B
64B
64B
64B
65B
65B
65B
65B
65B
65B
66B
66B
66B
66B .
66B
66B
DATE
COLLECTED
03-30-93
07-20-93
11-13-93
03-07-94
NS
06-25-94
03-29-93
07-20-93
11-13-93
03-07-94
NS
06-25-94
03-29-93
07-21-93
11-13-93
03-04-94
NS
06-27-94
03-29-93
07-21-93
11-13-93
03-07-94
NS
06-27-94
03-29-93
07-21-93
11-13-93
03-07-94
NS
06-27-94
03-30-93
07-20-93
11-15-93
03-04-94
NS
06-27-94
PH
NA
5.08
4.60
4.95
NS
4.86
NA
4.80
4.49
4.64
NS
5.02
NA
4.85
4.46
4.57
NS
4.61
NA
4.89
4.35
4.47
NS
4.50
NA
5.06
4.72
4.84
NS
4.77
NA
4.55
4.39
4.43
NS
4.41
COND.
(mg/l)
NA
19.9
23.0
20.0
NS
20.1
NA
51.0
51.4
54.0
NS
58.1
NA
56.0
55.9
47.8
NS
51.6
NA
46.0
53.7
54.6
NS
49.3
NA
39.0
34.2
32.0
NS
33.8
NA
80.0
74.6
83.3
NS
85.6
TEMP.
(C)
NA
26.6
17.5
19.6
NS
NA
NA
21.2
20.3
20.8
NS
NA
NA
22.0
18.8
16.7
NS
NA
NA
21.0
19.4
17.3
NS
NA
NA
20.3
18.8
18.5
NS
NA
NA
19.5
21.9
19.5
NS
NA
DEPTH OF
WELL
(FT)
20
20
20
20
20
20
15
15
15
15
15
15
20
20
20
20
20
20
25
25
25
25
25
25
15
15
15
15
15
15
20
20
20
20
20
20
NA = Not Analyzed
NS = Not Sampled
73
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
67B
67B
67B
67B
67B
67B
68B
68B
68B
68B
68B
68B
69B
69B
69B
69B
69B
69B
70B
70B
70B
70S
70B
70B
71 B
71B
71B
71B
71B
71B
72B
72B
72B
72B
72B
72B
DATE
COLLECTED
03-30-93
07-20-93
11-11-93
03-04-94
NS
06-27-94
03-30-93
07-20-93
11-15-93
03-02-94
NS
06-27-94
03-31-93
07-19-93
11-12-93
03-05-94
NS
06-23-94
03-31-93
07-16-93
11-15-93
03-04-94
NS
06-25-94
03-31-93
07-15-93
11-15-93
03-04-94
NS
06-24-94
03-31-93
07-15-93
11-15-93
03-04-94
NS
06-25-94
pH
NA
5.06
5.73
4.70
NS
4.75
NA
4.69
4.54
4.76
NS
4.69
NA
4.69
4.47
4.68
NS
4.65
NA
6.70
5.74
5.29
NS
6.41
NA
5.50
4.84
5.29
NS
4.81
NA
5.70
5.15
4.80
NS
5.36
COND. TEMP.
(mg/l) (C)
NA NA
29.7 19.6
27.1 18.4
30.2 19.1
NS NS
32.4 NA
NA NA
65.2 20.3
52.9 22.0
52.6 13.3
NS NS
55.2 NA
NA NA
58.0 24.7
61.9 18.2
61.0 21.3
NS NS
61.8 NA
NA NA
47.0 21.0
48.3 20.9
38.2 17.5
NS NS
51.2 NA
NA NA
39.0 19.0
36.8 22.3
38.2 17.5
NS NS
46.6 NA
NA NA
22.0 19.0
23.6 22.8
22.8 18.1
NS NS
23.4 NA
DEPTH OF
WELL
(FT)
22
22
22
22
22
22
30
30
30
30
30
30
35
3.5
35
35
35
35
100
100
100
100
100
100
18
18
18
18
18
18
22
22
22
22
22
22
MA = Not Analyzed
NS = Not Sampled
74
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
73B
73B
73B
73B
73B
73B
74B
74B
74B
74B
74B
74B
75B
75B
75B
75B
75B
75B
76B
76B
76B
76B
76B
76B
DATE
COLLECTED
03-31-93
07-16-93
11-15-93
03-04-94
NS
06-25-94
03-31-93
07-15-93
11-15-93
03-04-94
NS
06-25-94
03-31-93
07-15-93
11-16-93
03-01-94
NS
06-23-94
NS
NS
11-16-93
03-07-94
NS
06-25-94
PH
NA
5.30
4.84
5.06
NS
5.02
NA
6.70
6.31
6.23
NS
6.07
NA
5.20
5.34
6.21
NS
5.02
NS
NS
4.82
4.94
NS
4.81
COND.
(mg/l)
NA
59.0
57.1
51.1
NS
62.3
NA
44.0
43.9
42.5
NS
46.0
NA
20.0
20.1
22.6
NS
23.2
NS
NS
72.4
63.8
NS
95.1
TEMP.
(C)
NA
21.0
20.6
16.9
NS
NA
NA
21.0
19.9
15.3
NS
NA
NA
20.2
19.8
12.9
NS
NA
NS
NS
20.3
18.0
NS
NA
DEPTH OF
WELL
(FT)
30
30
30
30
30
30
20
20
20
20
20
20
20
20
20
20
20
20
18
18
18
18
18
18
NA = Not Analyzed
NS = Not Sampled
75
-------
FIELD SAMPLING DATA
LITTLE COHARIE WATERSHED
WELL
SITE
4C
4C
4C
4C
4C
4C
14C
14C
14C
14C
14C
14C
58C
58C
58C
58C
58C
58C
66C
66C
66C
66C
66C
66C
70C
70C
70C
70C
70C
70C
75C
75C
75C
75C
75C
75C
DATE
COLLECTED
03-23-93
07-13-93
11-09-93
NS
NS
NS
NS
07-19-93
11-11-93
03-05-94
05-17-94
06-22-94
NS
07-20-93
11-15-93
03-07-94
NS
NS
03-30-93
07-20-93
11-15-93
03-04-94
NS
06-27-94
03-31-93
07-16-93
11-15-93
03-04-94
NS
06-24-94
03-31-93
07-15-93
11-16-93
NS
NS,
06-23-94
pH
NA
NA
6.19
NS
NS
NS
NS
4.85
4.52
4.62
4.93
4.69
NS
5.15
4.80
4.88
NS
NS
NA
4.78
4.36
4.60
NS
4.38
NA
6.50
6.38
6.10
NS
6.09
NA
4.70
5.01
NS
NS
5.27
COND.
(mg/l)
NA
NA
50.9
NS
NS
NS
NS
48.0
44.8
52.1
53.4
52.4
NS
22.0
24.6
25.3
NS
NS
NA
75.0
78.3
73.8
NS
78.1
NA
40.1
43.8
38.6
NS
41.3
NA
37.0
36.5
NS
NS
45.5
TEMP.
(C)
NA
NA
15.5
NS
NS
NS
NS
26.5
21.8
16.4
19.3
22.5
NS
22.8
22.8
21.2
NS
NS
NA
21.3
20.9
20.6
NS
NA
NA
21.0
20.9
20.3
NS
NA
NA
20.3
21.2
NS
NS
NA
DEPTH OF
WELL
(FT)
18
18
18
18
18
18
25
25
25
25
25
25
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
NA = Not Analyzed
NS = Not Sampled
76
-------
Well Installation and Characterization, 1992
Site 1: Segment 9
0-2 ft mostly sand
2-1 Oft sandy clay
10-12 ft more clay than sand
12-14 ft clay
14-20 ft mixed, with mostly sand
20-35 ft water bearing sand (sand poorly graded)
well depth-30 ft
water yield-15 to 20 gallon/minute
weilscreen-18to28ft
well located downslope of corn field in large valley and approximately 300 ft upslope
from old lagoon, and 89 ft from existing well
sand-5 bags
grout-7 bags
crop-corn
exiting well-pipe with screen
Site 2:Segment 10
0-7 ft sand
7-13 ft yellow-tan sandy clay
13-15 ft gray, sandy clay
15-30 ft dark gray clay
well depth-20 ft
water yield-1 to 2 gallon/minute
well screen-8 to 18ft
sand-6 bags
grout-6 bags
well located 276 ft from existing well
crop-tobacco and sweet potatoes
existing well-30 ft bored
Site 3:Segment 10
0-3 ft sandy loam
3-7 ft sandy clay (yellow tan)
7-10 ft sandy clay (more coarse than above layer)
10-16 ft same as above layers but less clay
16-20 ft wet silty sand
20-25 ft silty sand
25-30 ft silty sand
30-33 ft silty sand
33 ft clay
well depth-30 ft
water yield-2.5 gallon/minute
sand-8 bags
grout-6 bags
well screen 18 to 28 ft
well located 224 ft from existing wells
77
-------
Two existing wells located adjacent to each other:
1. Bored well (20-in casing), 30 ft deep, not used in 3 years
2. Drilled well, 80 ft
crop-cotton
Site 4:Segment 9
0-2 ft dry. powdery sand
2-5 ft sandy clay
6-10 ft red/gray streaked hard clay
10-15 ft tan/gray streaked hard pliable clay
15-17.5 ft tan/gray streaked hard pliable clay
17,5-20 ft fine moist red sand mottled with white sand
20-23 ft fine moist tan sand
23-25 ft water bearing sand ..
25-30 ft water bearing sand
30-35 ft water bearing sand
well depth-35 ft
water yield-4 gallon/minute
well screen-23 to 33 ft
sand-8.5 bags
grout-4.5 bags
Two existing wells
1. shallow existing (galvanized pipe) well 18 ft, no evidence of usage, no faucet or pump
2. deep (80 ft) existing well, located 128 ft downslope of research well. Widespread
evidence of chemical use around well with many used pesticide containers
crop-soybean
Site 5:Segment 8
0-2 ft sand, loamy
2-4 ft some clay, mostly sand
4-5 ft tan clay streaked with red and white sand
5-10 ft red "brick" clay streaked with white sand
10-16 ft sandy clay, more red/white clay than sand
16-20 ft fine moist sand
well depth-30 ft
water yield 6 gallon/minute
wellscreen-18to28ft
well located 140 ft from existing well
sand-8 bags
grout-3 1/2 bags
crop-soybean and tobacco
existing well-pipe with screen
Site 6:Segment 6
0-2 ft fine, dry, gray sand
2-5 ft course sand, tan near 2 ft and red near 5 ft
5-8 ft sand with red ctay
78
-------
8-1 Oft yellow sand
10-15 ft moist water bearing sand
15-24 ft moist water bearing sand
24-25 ft clay
well depth-25 ft
water yield-10 gallon/minute
wellscreen-13to23ft
well located 84 ft from existing well
sand-8 bags
grout-2.5 bags
crop-tobacco
existing well-pipe with screen
Site 7:Segment 6
0-2 ft gray sand
2-4 ft sandy clay
4-5 ft mostly clay, light tan
5-10 ft gray moist clay
10-15 ft moist white sand
15-20 ft water bearing sand, yellow-tan
well depth-30 ft
water yield-> 12 gallon/min
well screen 17 to 27 ft
sand-8 bags
grout-3 bags
well located 227 ft from existing well
crop-soybean and corn
existing well-pipe with screen
Site 8:Segment 4
0-4 ft sand yellow-tan
4-5 ft sandy clay
5-9 ft moist sand
9-10 ft water bearing sand
10-15 ft water bearing coarse sand
well depth-25 ft
water yield-11.5 gallon/minute
wellscreen-13to23ft
well located 439 ft from existing well
sand-7.5 bags
grout-2 bags
crpp-collard and cotton
existing well-pipe with screen
Site 9:Segment 5
0-4 ft sandy clay
4-5 ft gray fine sand
5-8 ft gray sand with gravel
8-1 Oft black clay
79
-------
10-15 ft black clay
15-20 ft black clay
20-25 ft black clay
well depth-20 ft
water yield-5 gallon/minute
well screen-8 to 18 ft
sand-8 bags
grout-2 bags
well located 300 ft from existing well
crop-soybean and corn
existing well-pipe with screen
Site 10:Segment 7
0-6 in gray sandy clay
6 in-4 ft yellow sandy clay
4-5 ft red-gray clay
5-6 ft tan clay
6-8 ft fine sand, tan
8-10 ft fine white moist sand
10-15 ft water bearing white sand
well depth-20 ft
water yield-6 gallon/minute
well screen-8 to 18ft
sand-7 bags
grout-2 bags
well located 95 ft from existing well
crop-soybean
existing well-pipe with screen
Site 11:Segment8
0-4.5 ft sand, yellow
4.5-5 ft sand with some clay, yellow
5-8 ft red sandy clay
8-10 ft sand, yellow
10-14 ft course moist yellow sand
14-15 ft burgundy red sand (moist)
15-20 ft water bearing sand
20 ft yellow sand
well depth-25 ft
water yield-2.5 gallon/minute
wellscreen-13to23ft
sand-8 bags
grout-3 bags
well located 167 ft from existing well
crop-soybean
existing well-pipe with screen
80
-------
Site 12:Segment 7
0-5 ft sand, some clay, tan color
5-9 ft sand, some clay, tan color
9-10 ft wet water bearing sand
10-11ft wet water bearing sand
11-14 ft brownish gray clay
14-15 ft dark clay, gray with green streaks
well depth-20 ft
water yield-1.0 gallon/minute
wellscreen-8 to 18ft
sand-8 bags
grout-2 bags
well located 1178 ft from existing well
crop-cotton and soybean
existing well-pipe with screen
Site 13:Segment 5
0-4 ft tan clay, loamy
4-5 ft hard clay tan with red streaks
5-10 ft hard clay tan with red streaks
10-14 ft hard clay
14-15 ft moist tan sand
15-20 ft water bearing course sand, tan with white streaks
well depth-25 ft
water yield^S gallon/minute
well screen-13 to 23 ft
sand-8 bags
grout-2.25 bags
well located 172 ft from existing well,
hog lot 50 ft upgradiant of well
crop-corn
existing well-pipe with screen
Site 14:Segment4
0-6 in top soil
6 in-2 ft orange sandy clay
2-5 ft red sandy clay
5-10 ft red sandy clay, more clay at 9 ft
10-14 ft red brick clay .
14-15 ft white sandy clay
15-17 ft orange sandy clay
17-25 ft coarse red and yellow sand
well depth-30 ft
water yield-8.5 gallon/minute
well screen-18 to 28 ft
sand-8 bags
grout-3 bags
well located 784 ft from existing well (B) and 543 ft from existing well (C)
81
-------
crop-soybean,tobacco and corn
existing well-pipe with screen
Site 15:Segment 3
0-1 ft top soil
1-4 ft sandy clay
4-5 ft coarse sand medium clay
5-9 ft coarse sand slight clay
9-1 Oft wet sand
10-15 ft water bearing white sand
15-23 ft coarse sand with gravel
23-25 ft orange clay
well depth-25 ft
water yield-15-20 gallon/minute
wellscreen-13to23ft
sand-7 bags
grdut-2.5 bags
well located 756 ft from existing well
crop-cotton, tobacco
existing well-pipe with screen
Site 16:Segment3
0-6 in top soil
6 in-5 ft yellow sand
5-10 ft wet yellow sand
10-14 ft wet yellow sand
14-15 ft gray clay layer
15-25 ft water bearing coarse white sand
well depth-25 ft
water yield-15-20 gallon/minute
wellscreen-13to28ft
sand-6.5 bags
grout-2.5 bags
well located 125 ft from existing well
crop-corn,soybean
existing well-pipe with screen
Site 17:Segment 1
0-5 ft gray sand
5-9 ft yellow sand
9-1 Oft white sand
10-11 ft gravely sand, poorly graded
11-15 ft white sand
15-18 ft white sand
18-19 ft white sandy clay
20-25 ft black clay (hard)
well depth-20 ft
water yield-15 to 20 gallon/minute
well screen-9 to 19 ft
82
-------
sand-6.5 bags
grout-2 bags
well located 364 ft from existing well
crop-tobacco
existing well-pipe with screen
Site 18:Segment 1
0-1 ft mostly sand, some clay
1-5 ft yellow sand
6-10 ft red clay
10-15 ft clay with some sand
15-20 ft red clay some sand
20-25 ft red clay very hard
well depth-20 ft
water yield-3.0 gallon/minute
well screen-8 to 18ft
sand-8bags
grout- 3 bags
well located 78 ft from existing well
crop-cotton
existing well-pipe with screen
Site 19:Segment 2
0-6 in sandy top soil
6 in-5 ft sandy clay with progressively more clay with depth
5-9 ft red clay with some sand
9-10 ft yellow sand with some clay
10-15 ft wet yellow sand
15-19 ft coarse water bearing yellow sand
19-20 ft coarse white sand
20-22 ft coarse white sand
22-25 ft coarse yellow sand
25-27 ft coarse yellow sand
27-30 ft black clay
well depth-30 ft
water yield-10 gallon/minute
well screen-18 to 28 ft
sand-8 bags
grout-4.5 bags
well located 390 ft from existing well
crop-cotton
existing well-pipe with screen
Site 20:Segment 2
0-6 in top soil
6in-3 ft sand
3-5 ft sandy clay
5-7 ft red sand some clay
7-10 ft wet brown sand
10-12 ft white clay
83
-------
12-15 ft water bearing white sand with some clay
15-20 ft coarse yellow sand
well depth-30 ft
water yield-15 to 20 gallon/minute
well screen-18 to 28 ft
sand-7 bags
grout-4.5 bags
well located 292 ft from existing well
crop-cotton and tobacco
existing well-pipe with screen
Site 21:Segment 1
0-6 in black top soil
6 in-2 ft brown sand
2-5 ft yellow-orange sand some clay
5-10 ft coarse wet yellow sand
10-13 ft coarse wet yellow sand
13-15 ft coarse wet white sand
15-20 ft coarse wet white sand
20-25 ft reddish-brown wet sand
well depth-25 ft
water yield-10 gallon/minute
well screen-13 to 23 ft
sand-6.5 bags
grout-3 bags
well located 254 ft from existing well
crop-fallow at well installation, later winter rye
existing well-2 in PVC
84
-------
COMPARISON OF METHODS
NITRATE-NITROGEN IN GROUND WATER, JUNE 1994
Field methods - Aquachek test strips (visual determination) - Merck Reflectoquant System
Lab method - Ion chromatographic determination (1C)
All results in parts per million (PPM) nitrate-nitrogen
ND = None Detected NA = Not Analyzed
SITE NUMBER
1A
IB
2A
2B
3A.
3B
4A
4B
5A
5B
6A
6B
7A
7B
8A
8B
9A
9B
10A
10B
11A
11B
12A
12B
AQUACHEK STRIP
10
10
5
10
5
0
2-3
10
15
12
25
>20
7-10
2-3
8
>10
ND
15
1-2
2
12
15
4-5
REFLECTOQUANT
9.0
9.7
7.9
10.2 .
5.2
0
4.3
10.4
14.9
11.5
20.1
21.7 ,
6.1
3.4
9.9
17.2
ND
9.7
2.0
2.3
9.3
14.2
6.6
0.7
ION CHROMAT.
8.8
9.9
7.9
9.0
5.8
0.5
5.6
11.4
13.6
10.7
18.3
21.9
6.6
2.0
9.0
14.6
ND
12.6
2.6
2.6
9.1
13.9
6.7
0.7
85
-------
SITE NUMBER
13A
13B
14A
14B
14C
15A
15B
16A
16B
17A
17B
18A
18B
19A
19B
20A
20B
21A
21 B
G-1
G-2
G-3
22
23
24
25
26
27
28
AQUACHEK STRIP
1-2
2
15-18
5
5
5-7
ND
<25
15-20
3
3
8.9
4
2
3-4
>4
5-6
9-10
>10
ND
ND
ND
10-15
6-7
ND
2
ND
1-2
4
RQFLEX METER
2.3
2.5
20.3
7.2
7.2
9.0
ND
21.7
21.4
4.1
3,4
7.9
7.0
3.8
5.7
6.6
9.1
7.7
15.9
0.2
NA
NA
14.7
6.6
ND
1.1
NA
NA
NA
ION CHROM.
2.3
2.4
21.7
7.7
7.7
10.2
0.5
24.5
25.1
3.3
1.9
10.8
7.7
3.8
5.1
6.3
10.0
1-0.2
17.3
0.4
0.3
0.4
15.3
7.3
ND
1.0
0.3
1.3
2.7
86
-------
SITE NUMBER
29
30
31
32
33
34
35
36
37
38
39
40
41 -
42
43
44 REJECTED
45
46
47 REJECTED
48
49
50
51
52 REJECTED
53
54
55
56
57
AQUACHEK STRIP
>2
8
3
6-7
3-4
10
>1
2
ND
ND
ND
ND-
6-7
ND
2-3
>250 ft.
12
5
10
>1
5
2
WATER
5-6
10
12
8-10
COULD NOT
SAMPLE
RQFLEX METER
NA
10.6
NA
8.1
5.6
9.9
1.2
3.2
NA
NA
NA
NA
7.0
NA
NA
10.6
NA
~
10.6
NA
5.4
4.1
TREATMENT
NA
6.3
11.1
6.3
PUMP
INOPERABLE
ION CHROM.
2.3
11.8
2.6
8.6
6.5
11.5
0.9
2.6
0.3
ND
0,5
0.5 .
8.3
ND
3.0
10.9
4.7
10.8
0.2
5.9
2.3
SYSTEM
3.2
5.5
9.6
6.9
87
-------
SITE NUMBER
58
59
60
61
62
63
64
65
66B
66C
67
68
69
70
71
72
73
74
75B
75C
76 (99)
AQUACHEK
METER
5
8-10
10
ND
5
5
6
2
9
10
3
5
5
ND
7
1
8-9
ND
<1
<2
7-9
RQFLEX METER
5.0
6.8
7.7
NA
NA
5.0
5.6
2.2
9.7
10.2
2.5
5.4
6.1
NA
4.3
NA
7.5
NA
1.4
4.3
9.5
ION CHROM.
5.3
6.7
8.4
ND
5.0
4.7
5.4
1.8
10.8
10.4
2.2
5.2
7.9
ND
4.9
1.1
8.7
ND
1.0
2.3
10.0
88
-------
AQUACHEK NITRATE-NITROGEN TEST STRIP RESULTS USING BLIND
SPIKES IN DISTILLED WATER (VISUAL COLOR COMPARISON)
B & J - Senior level analytical chemists
T - Lab helper with no formal training
Sample
Number
1
2
3
4
5
6
7
8
9
10
11
12
Cone. PPM
NO3-N
3.4
9.0
0.2
0.0
5.7
2.3
1.1 -
9.0
0.2
1.1
33.9
2.3
Subject B.
Concentration
2
5-6
ND
ND
3
1
>1
>5
ND
>1
>25
1
Subject J.
Concentration
2
5-10
ND
ND
5
2
1
5-10
ND
0-1
20-50
>2
Subject T.
Concentration
3
9
ND
ND
3
2
ND
6
ND
0.5
20
1.5
89
-------
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