xEPA
United States
Environmental Protection
Agency
Office Of Water
(WH550G)
EPA 813/B-92-002
July 1992
Definitions For The Minimum
Set Of Data Elements For
Ground Water Quality
Printed on Recycled Paper
-------
Definitions for the Minimum Set of
Data Elements for Ground Water Quality
U.S. Environmental Protection Agency
Office of Ground Water and Drinking Water
Washington, D.C.
July 1992
-------
ACKNOWLEDGEMENTS
This document represents a three year effort on the part of many individuals to
improve the protection of ground water resources through the use of data elements to
increase effective information sharing and cross media interaction.
The Environmental Protection Agency (EPA) staff principly involved in managing,
coordinating and developing this project were, Harriet Colbert, Caryle Miller, Robin
Heisler, Dr. Norbert Dee, Michelle Zenon and Jean Sammon. Jane Marshall and William
McCabe provided technical assistance and developed the well diagrams.
Many people from the State and Federal ground water community served on the
Minimum Set of Data Elements for Ground Water Quality Workgroup. The Workgroup
participants are listed in Appendix B.
-------
TABLE OF CONTENTS
Page No.
INTRODUCTION vii
GENERAL DESCRIPTOR 1
1. DATA SOURCES 3
GEOGRAPHIC DESCRIPTORS 5
2. LATITUDE 7
3. LONGITUDE 9
4. METHOD USED TO DETERMINE LATITUDE AND
LONGITUDE 11
5. DESCRIPTION OF ENTITY 17
6. ACCURACY OF LATITUDE AND LONGITUDE
MEASUREMENT 19
7. ALTITUDE 23
8. METHOD USED TO DETERMINE ALTITUDE 25
9. STATE FIPS CODE 29
10. COUNTY FIPS CODE 31
WELL DESCRIPTORS 33
11. WELL IDENTIFIER 35
12. WELL USE 37
13. TYPE OF LOG 41
14. DEPTH OF WELL AT COMPLETION 43
15. SCREENED/OPEN INTERVAL 47
-v-
-------
TABLE OF CONTENTS (continued)
Page No.
SAMPLE DESCRIPTORS 49
16. SAMPLE IDENTIFIER 51
17. DEPTH TO WATER 53
18. CONSTITUENT OR PARAMETER MEASURED 57
19. CONCENTRATION/VALUE 59
20. ANALYTICAL RESULTS QUALIFIER 61
21. QUALITY ASSURANCE INDICATOR 63
LIST OF FIGURES
Figure 1 Diagram to Illustrate Latitude and Longitude 10
Figure 2 Diagram to Illustrate Altitude 24
Figure 3 Diagram to Illustrate Depth of Well at Completion:
Screened Water Well 44
Figure 4 Diagram to Illustrate Depth of Well at Completion:
Open Hole Water Well 45
Figure 5 Diagram to Illustrate Screened/Open Interval 48
Figure 6 Diagram to Illustrate Depth to Water 54
Figure 7 Diagram to Illustrate Linking Related Data 72
APPENDICES 67
A Key Issues Involved in the Implementation of the
Minimum Set of Data Elements for Ground Water Quality 69
B List of Work Group Members 75
BIBLIOGRAPHIES 83
A Bibliography of Key References 85
B Bibliography of References Consulted But Not Used . . 91
-vi-
-------
INTRODUCTION
-vii-
-------
INTRODUCTION
Background
The protection of our nation's ground water resources is receiving widespread
attention at all levels of governmental the need to protect this vital resource to sustain
the life and health of citizens and the ecosystem becomes increasingly clear. As a part of
the Environmental Protection Agency's (EPA) continuing commitment to the protection
of the Nation's ground water resources and in keeping with its Ground Water Protection
Strategy for the 1990s1, the Agency has identified the critical need for improved means
for the collection, accessibility and utilization of ground water information. As such,
EPA's Office of Ground Water and Drinking Water is improving the accessibility,
transfer and use of information through the establishment of a Minimum Set of Data
Elements for Ground Water Quality (MSDE).
The MSDE project was developed as a result of a Ground Water Data
Requirements Analysis which was completed in 1987. An issue consistently identified
during the conduct of the requirements analysis was the need to improve access to
ground water data and the need to standardize elements used in data base development
to increase information sharing capabilities. In response, EPA conducted a workshop in
1988 to discuss development of a minimum set of data elements for ground water
quality.2 The goals of the workshop participants were to a) achieve consensus on a
minimum set of data elements that would facilitate the collection and sharing of ground
water and related data across agencies and b) identify implementation issues that must
be resolved to encourage collection of an MSDE throughout the ground water
community. The workshop participants developed a draft list of data elements. An EPA
Order (7500. 1) was established in 1989 which made the elements and their use a
requirement for EPA and its contractors. The Order stated that "a dictionary defining
elements in the minimum data set will be developed by the Office of Ground Water
Protection" (now the Ground Water Protection Division).3 At that time, a draft
1 U.S. Environmental Protection Agency, Office of The Administrator, Protecting
The Nation's Ground Water: EPA's Strategy for The 1990s. The Final Report Of The
EPA ground water Task Force, EPA Publication No. 21Z-1020, July 1991.
2 U.S. Environmental Protection Agency, Office of ground water Protection, ŁEA
Workshop to Recommend A Minimum Set of Data Elements for Ground Water:
Workshop Findings Report. EPA 440/6-88-005, June 1988.
3 U.S. Environmental Protection Agency, EPA Order - Minimum Set of Data
Elements For Ground Water. September 1989.
-IX-
-------
Introduction
definition for each element was recommended by the Office of Ground Water
Protection.4
The development of the final list of elements and their definitions involved an
intensive, iterative process of drafting and peer review by an MSDE Work Group of over
100 representatives from EPA, other Federal Agencies, and the States. The list of work
group members is provided in Appendix B. It has taken approximately four years to
complete this project. The primary task of the Work Group was to comment on and
provide recommended changes to the elements' names and draft definitions. The Work
Group completed two separate review cycles of element names and draft definitions with
suggested data conventions.5
Purpose
EPA is pleased to present this document that identifies and defines a minimum set
of data elements for ground water quality. The purpose of this document is to present
the definitions for a minimum set of key ground water data elements that are needed to
share data efficiently within the ground water community at all levels of government.
The data elements in the minimum set were selected based on the following criteria:
those elements that are needed to communicate ground water data
across related programs;
those elements that are common to all programs and completely
adequate for some programs;
those elements that provide a road map to other ground water data;
and
those elements that provide a link between ground water quality
and well location information.
Implementation of the MSDE will be useful under the following conditions:
When States, Federal agencies or other officials are considering creating
a new ground water quality data base; or
4U.S. Environmental Protection Agency, Office of Ground Water Protection,
Minimum Set of Data Elements for Ground Water: DEFINITIONS and FORMATS.
January 1990 (unpublished).
5Ibid., July 23, 1990.
-x-
-------
Introduction
officials want to modernize an existing data base. Officials may wish to
modernize their data base because they have a significant amount of new
data or because they want to help move their agency(ies) towards
achieving consistency among its data bases.
The use of the MSDE is required in both of these circumstances for EPA and its
contractors, and States are encouraged to voluntarily adopt its use in State data base
systems. It is also important to remember that this document represents the minimum
data elements one should include when selecting elements for information collection
activities pertaining to ground water quality. In addition to the elements in this
minimum set, Agencies should collect data for any element that they feel is necessary for
the effective management of their ground water resources. This document does not
preclude the EPA or its contractors from imposing more stringent accuracy
requirements. For example, an EPA Regional Office may choose to require data
providers to report a more stringent degree of accuracy than is indicated in the MSDE
for the Latitude data element.
Data Element Presentation
This document is organized by data element. The 21 elements in the minimum set
are presented on the following page. The elements are divided into four categories:
(1) General descriptor;
(2) Geographic descriptors;
(3) Well descriptors; and
(4) Sample descriptors.
Throughout this document, the term "well(s)" is used to mean well(s), spring(s) or other
ground water locations. Some elements, however, may not apply to all types of ground
water locations. For example, element 13-- Screen/Open Interval ~ will not apply to
springs. Such limitations of data elements will be noted in the text.
This document provides the following four components for each data element:
the element's name;
the element's definition;
a discussion of the element's definition; and
examples of possible data conventions for the element.
The element's name is the most succinct and widely recognized name for that
particular element. The element's definition is a concise statement of the meaning of
the data element in the context of the minimum set of data elements for ground water
-XI-
-------
Introduction
quality. The discussion section presents the purpose of the element and elaborates on
and clarifies its definition.
MINIMUM SET OF DATA ELEMENTS FOR GROUND WATER QUALITY
Element Category
Element Names
General Descriptor:
describes where the well
information is
maintained
1. Data Sources
Geographic Descriptors:
describe the well or
spring in relation to the
earth's surface
2. Latitude
3. Longitude
4. Method Used to Determine Latitude and Longitude
5. Description of Entity
6. Accuracy of Latitude and Longitude Measurement
7. Altitude
8. Method Used to Determine Altitude
9. State FIPS-a/ Code
10. County FIPS-a/ Code
Well Descriptors:
describe various features
of a well or spring
11. Well Identifier
12. Well Use
13. Type of Log
14. Depth of Well at Completion
15. Screened/Open Interval
Sample Descriptors:
describe different
aspects of collecting,
analyzing, and recording
the results of a ground
water sample
16. Sample Identifier
17. Depth to Water
18. Constituent or Parameter Measured
19. Concentration/Value
20. Analytical Results Qualifier
21. Quality Assurance Indicator
-/ Federal Information Processing Standard.
And finally, the examples section presents various means of establishing a data
convention for the element.
The intent in presenting examples is to serve as a guide and offer suggestions on
how the information could be presented in a data base. EPA is not prescribing formats
or data conventions for most of the elements in the minimum set. EPA considers the
-Xll-
-------
Introduction
need to develop formats for these data elements to be the responsibility of those who
will oversee the actual physical design of the data base.
A number of different examples of data formats are presented for each element
due to the realization that a format that is appropriate for one data base may not be
appropriate for another. However, the first example listed under each element
represents widely accepted design practices of storing data fields separately. Adopting
this preferred data format will help make data bases more consistent and will ease data
sharing. The first example decomposes individual components of the element into
separate fields that are listed on separate lines. For example, element 7~ Altitude ~
has three components: 1) the measuring point; 2) the altitude of the measuring point;
and 3) the units the altitude measurement is expressed in. The preferred example
format for the altitude element, therefore, decomposes these components as illustrated in
the following example:
L
+ 00100
M
where L represents the measuring point for this hypothetical well is the land surface;
+00100 is the altitude of the measuring point and M reveals that the altitude was
measured in meters. Decomposing the components of an element into separate fields
will help data users interpret the data and make it easier for data base managers to
correct data errors if necessary. For more information on storing data element
components in separate fields, as well as other key considerations involving the
implementation of the MSDE, see Appendix A.
Specific formats or data conventions are not prescribed for most of the elements,
however, the MSDE does prescribe formats for a number of data elements to assure
compliance with EPA and Federal Information Processing Standards policy. Required
EPA formats in this document are the Locational Data Policy (LDP) and the Facility
Identification Data Standards (FIDS).6'7 The LDP establishes the principles for
collecting and documenting latitude/longitude coordinates for facilities, sites and
monitoring and observation points under the jurisdiction of EPA. The FIDS establishes
a data standard for unique facility identification codes to be maintained in all EPA data
collections containing information on facilities regulated by EPA. The FIDS codes are
complied with in the Well Identifier data element. Federal Information Processing
6 U.S. EPA, Office of Information Resources Management, Information Resources
Management Policy Manual - Locational Data, April 8, 1991.
7 U.S. EPA, Office of Information and Resources Management, Information
Management and Services Division, EPA Order - Facility Identification Data Standard.
April 9, 1990.
-Xlll-
-------
Introduction
Standards (FIPS) establish Federal government-wide standards for a variety of data.
Throughout this document, FIPS codes have been complied with for dates, State Codes
and County Codes.
As a result of the two peer review cycles, some of the data element names and
definitions changed several times before the final elements and definitions were selected.
Major differences between the final list of elements and earlier versions, such as the list
in the EPA Order establishing the elements as Agency policy, are as follows:
The three elements pertaining to source organizations for various data
are combined into a single new element called Data Sources.
Latitude and Longitude are separated into two separate data elements
based on the EPA Locational Data Policy.
The two elements Depth to Top and Depth to Bottom of Open Section
are combined into one element named Screened/Open Interval. The
information collected under this new element will remain the same, the
only difference is the data will be reported as an interval under a single
element instead of two elements.
Other differences in the final list and previous versions are minor changes in
nomenclature for the purpose of clarification.
EPA believes that as a result of the intense review of these elements and their
definitions by the Work Group, this document represents the most critical elements and
most technically-accurate definitions for a minimum set of data elements for ground
water quality. In developing this final document, EPA considered every comment
registered by the Work Group and drafted the definitions based upon the weight of
evidence provided by the Work Group. Where necessary, EPA resolved issues using its
best professional judgment.
With this document, EPA presents the final list of elements comprising the
minimum set of data elements for ground water quality and the elements' definitions.
The Ground Water Protection Division, Office of Ground Water and Drinking Water, is
pleased to offer this document as one of many continuing commitments to support the
protection of our Nation's ground water resources.
-xiv-
-------
GENERAL DESCRIPTOR
-1-
-------
GENERAL DESCRIPTOR
1. DATA SOURCES
DEFINITION: The names of the organizations to direct questions regarding the
following data: (1) latitude and longitude coordinates, (2) altitude,
(3) well log information, (4) sample collection and (5) laboratory
sample analyses.
DISCUSSION: The purpose of this element is to provide a point of contact to whom
data users can direct questions pertaining to the following data: (1)
latitude and longitude coordinates, (2) altitude, (3) well log
information, (4) sample collection and (5) laboratory sample analyses.
For the source of data for the well log, data providers should list the
organization(s) which stores the logs. Although the organization
maintains the log, the organization may not have the authority to
release information from the log. Authority to release information
may have to come from the well owner. In such cases, the
organization listed should be able to provide the name of the well
owner. Data providers should list those organizations that are best
qualified to answer questions regarding the particular data type. Such
questions may include detailed inquiries regarding the methods used
to collect coordinates or samples, or apparent anomalies in the data.
The definition of this element does not require data providers to list
contact names or telephone numbers of the organizations since this
information may change frequently. Data managers, however, may
choose to require this or any other data source information that they
feel is necessary to meet their needs. Since there may be several data
sources for a given well, the field for this element will be a repeating
field.
The following examples suggest a few means of expressing a data
convention for this element. For these examples, the following
abbreviations are suggested for each data type:
a = altitude; sc = sample collection; w = well log information;
e = latitude/longitude coordinates; sa = laboratory sample analysis
-3-
-------
Data Sources
EXAMPLES:
COMPUTER FORMATTED DATA
Dept. Environmental Management
Ground Water Section
Montgomery
AL
36130
w
Georgia Geological Survey
Atlanta
GA
30365
USEPA
Region X
Geographic Information Systems Section
Seattle
WA
98101
e
DATA SOURCE REPRESENTED
Department of Environmental Management
Ground Water Section
Montgomery, Alabama 36130
data source for well log information
Geological Survey, State of Georgia
Atlanta, Georgia 30365
data source for altitude
U.S. Environmental Protection Agency
Region 10
Geographic Information Systems Section
Seattle, Washington 98101
data source for latitude/longitude coordinates
-4-
-------
GEOGRAPHIC DESCRIPTORS
-5-
-------
GEOGRAPHIC DESCRIPTOR
2. LATITUDE
DEFINITION: A coordinate representation that indicates a location on the surface
of the earth using the earth's equator as the latitude origin, reported
in degrees (D), minutes (M), seconds ( S ) and fractions of a second in
decimal format (if fractions of a second are available). A "+" (plus)
symbol represents latitudes north of the equator. A "-" (minus)
symbol represents latitudes south of the equator.
DISCUSSION: The purpose of this element is to provide a standardized locational
coordinate that will assist data users in geographically locating a wells
(For an illustration of Latitude, see Figure 1.) Due to an increasing
need for precise, reliable locational coordinates, and the emergence
of sophisticated geographic information system (GIS) data bases,
latitude and longitude have become the national standards for
locational information. Therefore, to promote consistency in the
collection and reporting of locational information, data providers are
required to use these national locational standards.
EPA has specified formatting requirements in its policy on locational
data.9 The latitude coordinate must be expressed in decimal format
that allows possible precision to the ten-thousandths of seconds and
be preceded by either a "+" (plus) or "-" (minus) symbol to represent
wells north or south of the equator, respectively. Latitude will be
reported in this format: +/-DDMMSS.SSSS.10
The following examples provide some samples of the data convention
for this element. These examples are consistent with the format
outlined in EPA's locational data policy.
EXAMPLES: +300510.1000
represents latitude 30° 05' 10. 1" north of the equator.
+421005.0000
represents latitude 42° 10' 05" north of the equator.
-163000.0000
represents latitude 16° 30' 00" south of the equator.
+400114.0135
represents latitude 40° 01' 14.0135" north of the equator.
Throughout this document, well(s) means: wells, springs or other ground water locations.
U.S. EPA, Office of Information Resources Management, Information Resources Management
Policy Manual - Locational Data, April 8, 1991.
10 Ibid.
-7-
-------
GEOGRAPHIC DESCRIPTOR
3. LONGITUDE
DEFINITION: A coordinate representation that indicates a location on the surface
of the earth using the prime meridian (Greenwich, England) as the
longitude origin, reported in degrees ( D ), minutes ( M), seconds ( S ),
and fractions of a second in decimal format (if fractions of a second
are available). A "+" (plus) symbol represents longitudes east of the
prime meridian. A "-" (minus) symbol represents longitudes west of
the prime meridian.
DISCUSSION: The purpose of this element is to provide a standardized locational
coordinate that will assist data users in geographically locating a well.
(For an illustration of Longitude, see Figure 1.) Due to an increasing
need for precise, reliable locational coordinates and the emergence of
sophisticated geographic information system (GIS) databases, latitude
and longitude have become the national standards for locational
information. Therefore, to promote consistency in the collection and
reporting of locational information, data providers are required to use
these national locational standards.
EPA has specified these formatting requirements in its policy on
locational data.11 Longitude coordinates must be expressed in
decimal format that allow possible precision to the ten-thousandths of
seconds and be preceded by either a "+" (plus) or a "-" (minus)
symbol to represent wells east or west of the prime meridian
(Greenwich, England), respectively. Longitude will be reported in this
format: +/-DDDMMSS.SSSS.12
The following examples provide some samples of the data convention
for this element. These examples are consistent with the format
outlined in EPA's locational data policy.
EXAMPLES:
-0930407.0000
represents longitude 093° 04' 07" west of the prime meridian.
+0480520.500
represents longitude 048° 05' 20.5" east of the prime meridian.
-1220322.0325
represents longitude 122° 03' 22.0325" west of the prime meridian.
11
12
Ibid.
Ibid.
-9-
-------
Longitude
LONGITUDE
Figure 1
Diagram to Illustrate Latitude and Longitude
42' 06" 106° 35' 00"
Weii A J-
+ 5,085 FT
5,iOOfi
+ 5,300 ft
+ 5,500 ft
+ 5,700 ft
Explanation:
WeiiB J-
+ 5,602 ft
+ 5,500 ft Topographic contours, Land surface altitude (ft)
above datum.
Contour interval: 200 ft.
Datum: NGVDof 1929
t
N
Topographic map view illustrating location of wells (Latitude and Longitude),
their relation to land surface altitude and the reference datum (NGVD 1929)
32? 40' 01'
LATITUDE
38' 06"
-10-
-------
GEOGRAPHIC DESCRIPTOR
4. METHOD USED TO DETERMINE LATITUDE AND LONGITUDE
DEFINITION: The procedure used to determine the Latitude and Longitude
coordinates (Technology of Method Used), the standard used for three
dimensional and horizontal positioning (Reference Datum), the
method used for map interpolation (Scale of Map), and the date on
which the coordinates were determined (Date). Latitude always
precedes longitude.
DISCUSSION: In order for Method Used To Determine Latitude and Longitude to
be most meaningful to secondary users, data must be collected and
documented so that there is sufficient information to independently
reproduce the same locational coordinates.
Standard documentation of "method" is done best by representing the
method as a code and having qualifying data elements for datum and
map scale. In addition! EPA has adopted Global Positing System as
the technology of choice for collecting locational data.13 Each of the
components to achieve sufficient data collection and documentation
for this data element is discussed below
(1) Technology of Method Used: is the method used to determine the
latitude/longitude coordinates of the well (i.e., address matching, map
interpolation, Loran-C, Global Positioning System (GPS), etc.). Data
users may choose to check coordinates determined through
conversions from other systems since there is a chance for substantial
error if the data provider did not make the proper conversion.
It is likely that the method used will be an essential qualifier used to
search lists and create subsets of coordinates in automated data bases.
For this reason, it is essential to ensure consistency in this data field
and establish a definitive list of the valid values for the field. Method
codes are presented below:
Latitude/Longitude Method Codes:
SUR-GPS = surveyed using differential-mode global positioning
system (GPS). This mode uses two receivers where
one is set at a known point. Data are processed
relative to a known point over time. With this mode,
U.S. EPA, Office of Research and Development Locational Data Policy Implementation
Guidance - Global Positioning Systems Technology And Its Application in Environmental Programs -
GPS Primer. EPA/600/R-92/036, February, 1992.
-11-
-------
Method Used To Determine Latitude and Longitude
NAV-GPS
SUR-C
MAP
LORAN-C =
ADDMAT =
PHOTO-GM =
SPCSCONV =
TSRCONV =
UTMCONV =
PHOTORAW =
RMTSEN
ZIP
UNKNOWN =
very high orders of accuracy can be achieved.
Survey quality GPS equipment used in
compliance with standards and specifications
defined by the Federal Geodetic Control
Committee can easily achieve sub-meter
positional accuracies with respect to the
National Geodetic Reference System.14
Navigational-type GPS units used in differential-
mode can typically achieve accuracies in the 1 to
4 meter range.
navigation-quality GPS. Surveyed using
absolute-mode global positioning system. This
mode uses a single receiver and determines a
location with respect to several satellites, not
from a known point. This mode is several
degrees of magnitude (approximately 100
meters) less accurate than differential-mode.
cadastral survey. Surveyed using conventional
methods from a previously established global
positioning system or triangulation control point.
digital or manual interpolation from a map or
photo.
Loran-C navigation device or radiotriangulation.
address-matched to a sub-portion of a street
block.
aerial photography
conversion from state plane coordinate system
conversion from township-section-range (etc.)
system
conversion from Universal Transverse Mercator
(UTM) coordinates
digital or manual raw photo extraction
remote sensing
zip code centroid
method unknown
The National Geodetic Reference System is the name given to all Geodetic Control contained
in the National Geodetic Survey data base including horizontal and vertical control, gravity data,
astronomic data and satellite data.
-12-
-------
Method Used To Determine Latitude and Longitude
(2) Reference Datum: The national reference datum for latitude and
longitude is a national standard for three dimensional and horizontal
positioning established by the U.S. National Geodetic Survey. In general,
a datum is a mathematical equation used to describe the earth's surface.
There are in existence several national reference datum systems. Nearly
all of EPA's data is in NAD27. Providers of latitude and longitude data
need to specify the reference datum their coordinates are based on in order
for others to accurately interpret the data. If the reference datum is not
available, data providers should specify that this information is not
available.
The current datum is the North American Datum of 1983 (NAD 83). This
system was completed in July 1986, and adopted by Federal Register Notice
Volume 54, No. 113, June 14, 1989, Docket No. 89-14076. It combines and
replaces several local datums including the North American Datum of 1927
(NAD 27), Old Hawaiian Datum, Puerto Rico Datum, St. Paul Island
Datum, St. George Island Datum and St. Lawrence Island Datum.
NAD 83 is based on an earth model (ellipsoid or spheroid) known as
Geodetic Reference System of 1980 (GRS 80), which is functionally
equivalent to the World Geodetic System of 1984 (WGS 84) developed by
the U.S. Department of Defense for its global positioning system. A
number of U.S. trust territories, including Guam, American Samoa, and
Wake, have not been added to NAD 83 at this time. All coordinate
information for these islands should be given in the local datum.
Reference Datum should be in the format BB where BB is the year of the
datum. The following are U.S. National Geodetic Survey codes for the
National Reference Datum for Latitude and Longitude:
83 = North American Datum of 1983 (NAD 83)
27 = North American Datum of 1927 (NAD 27)
05 = World Geodetic System of 1984 (WGS 84)
10 = World Geodetic System of 1972 (WGS 72)
15 = Old Hawaiian Datum
20 = Puerto Rico Datum
25 = St. Paul Island Datum
30 = St. George Island Datum
35 = St. Lawrence Island Datum
40 = Guam 1963
45 = Wake-Emwetok 1960
50 = Midway Astro 1961
55 = American Samoa Datum
60 = Johnson Island 1961
00 = Reference Datum not specified
-13-
-------
Method Used To Determine Latitude and Longitude
(3) Scale of Map: indicates the scale of the map used to determine
the latitude and longitude coordinates of the well or spring. If map
interpolation is the method used to determine latitude/longitude
coordinates, the data element for scale should be the "X" value of the
1:X ratio. For example if the scale is 1:24,000 (i.e., one inch on a
map is equal to 24,000 on the ground), the value of the scale is
"24,000". If map interpolation is not the method used to determine
latitude/longitude, then the data element value for scale is NOT
APPLICABLE. If the scale of the map used is unknown, then the
data element value for scale is UNKNOWN. The following codes are
established to ensure consistency and establish a definitive list of the
valid values for the method codes.
Scale
7.5'x 7.5'(1:20,000)
7.5'x 15'(1:20,000)
7.5'x 7.5'(1:24,000)
7.5'x 15'(1:24,000)
7.5'x 7.5'(1:25,000)
7.5'x 15'(1:25,000)
15'x 15'(1:62,500)
7.5'x 20 (1:63,360)
7.5' x 36' (1:63,350)
1:15,840
1:20,000
1:24,000
Not Applicable
Unknown
Data Element Value
20,000
20,000
24,000
24,000
25,000
25,000
62,500
63,360
63,350
15,840
20,000
24,000
NOT APPLICABLE
UNKNOWN
(4) Latitude/Longitude Date the Latitude/Longitude Date is the
date on which the data provider determined the latitude and longitude
coordinates. This date is important because it can provide additional
information on the accuracy of the latitude and longitude coordinates.
Due to technological advances in cartography and locational
positioning systems, data users also may want to use this information
to update old latitude and longitude values, especially if they need
very precise location information.
-14-
-------
Method Used To Determine Latitude and Longitude
The Latitude/Longitude Date format is based on Federal Information
Processing Standard (FIPS) Publication 4-115, which sets the standard
for date representation for all Agencies of the Federal Government
as yyyymmdd where y = year, m = month, and d = day.
The following examples suggest three means of expressing a data
convention for this element.
EXAMPLES: MAP
83
24,000
19860305
represents the Latitude/Longitude Method is digitally interpolated
from a map or photo (MAP); the reference datum is based on the
North American Datum of 1983 (83); the scale of the map is 1:24,000
for which the data element value is equal to 24,000 (24,000); and the
Date on which the coordinate was determined is March 5, 1986
(19860305).
NAV-GPS
27
NOT APPLICABLE
19811204
represents the Latitude/Longitude Method is surveyed using absolute-
mode global positioning system (NAV-GPS); the reference datum is
based on the North American Datum of 1927 (27); the scale of the
map is not applicable (NOT APPLICABLE); and the date on which
the coordinate was determined is December 4, 1981 (19811204).
SUR-GPS/83/NOT APPLICABLE/1980
represents the Latitude/Longitude Method is surveyed using
differential-mode global positioning system (SUR-GPS); the reference
datum is North American Datum of 1983 (83); the scale of the map
is not applicable (NOT APPLICABLE); and the date on which the
coordinate was determined is in the year 1980 (1980).
US Department of Commerce, National Bureau of Standards. Representation for Calendar
Date and Ordinal Date for Information Interchange. Federal Information Processing Standards (FIPS)
Publication 4-1, January 27, 1988.
-15-
-------
GEOGRAPHIC DESCRIPTOR
5. DESCRIPTION OF ENTITY
DEFINITION: A textual description of the entity to which the latitude and longitude
coordinate refers.
DISCUSSION: Latitude/longitude coordinates are often collected to represent an
entity but are actually a particular point or portion within the entity.
Secondary users need to know exactly what the latitude/longitude
coordinates define.
Throughout this document, the term "wells" is used to mean wells,
springs or other ground water locations. Although there are certain
data elements that clearly only pertain to wells (e.g., Depth To Well
At Completion and Screened/Open Interval). The data elements in
this document can be used as a tool to collect, use and share
information on ground water locations such as springs and boreholes.
Therefore, as required by the EPA Locational Data Policy, a
description of the entity (exact place where the coordinates are
collected) must be indicated.
The format of the description data element is a free-format, text field.
There should be, however, two components documented for
"Description Of Entity":
Whether the coordinate describes a point, line, or area.
The specific and exact description of the point, line or area that
the latitude/longitude coordinate is of and not a general
description of what the latitude/longitude represents. For
example, the description should indicate that the
latitude/longitude is of a specific well site within a well field
rather than of the well field in general.
It is very important that data collectors be consistent in their use of
the description field. The exact place used to represent the location
of the entity should be selected when planning the data collection
process.
-17-
-------
Description of Entity
The following examples suggest ways of expressing this data element.
EXAMPLES: Spring - The lat/long coordinate of spring X at the point
where it flows into surface water Y.
Well - The latitude/longitude coordinate is the point where
the well is located within a well field. The well
identifier is ALD98060001.*
*See data element number 11, Well Identifier, for explanation of well identification.
-18-
-------
GEOGRAPHIC DESCRIPTOR
6. ACCURACY OF LATITUDE AND LONGITUDE MEASUREMENT
DEFINITION: The quantitative measurement of the amount of deviation from true
value present in a measurement (estimate of error). It describes the
correctness of a measurement.
DISCUSSION: The distance represented by a degree of latitude remains constant
throughout the world whereas the distance represented by a degree
of longitude varies from the poles to the equator. For example, the
number of meters on the ground represented by a 1.0 second accuracy
for longitude at the equator (0 degrees latitude) would be larger than
± 1 second accuracy at the poles (90 degrees latitude). Additionally,
±1.0 second of accuracy for latitude and for longitude is similar only
at the equator. The issue of requiring a particular level of
latitude/longitude accuracy has been addressed by the EPA
Locational Accuracy Task Force (LATF). The Task Force has
recommended an accuracy goal of 25 meters.16 At a minimum, values
for latitude and longitude should always be complete to the second
and in accordance with the 25 meter accuracy goal. However, data
systems should be capable of handling latitude data to the full length
of the format (i.e., either + or - DDMMSS.SSSS) to accommodate
more precise measurements likely in the future. Likewise, data
systems should also be capable of handling longitude data to the full
length of the format (i.e., either + or - DDDMMSS.SSSS) to
accommodate more precise measurements likely in the future.
It is important to keep in mind that the accuracy limit was established
as a goal and not a standard because the achievement of maximum
locational data accuracy is necessarily technology-based (i.e., the
quality of locational data should be as good as the most practicable
data collection technology). Currently technology constraints may
limit the accuracy of locational data to 25-100 meters. However, the
technology to produce highly accurate locational coordinates is
improving rapidly. Techniques for map digitization, address matching,
and global positioning are becoming more feasible every day.
Therefore, the LATF recommendation is to have the best available
technology applied to collection of locational data.
U.S. EPA, Office of Administration and Resources Management, Locational Data Policy
Implementation Guidance - Guide To The Policy, March 1992.
-19-
-------
Accuracy of Latitude and Longitude Measurement
Global Positioning System (GPS) technology has been determined to
be an effective way of producing accurate locational data. When the
constellation of satellites upon which this technology depends is fully
deployed in 1992, means for collecting accurate locational data will be
available. At that time, accuracies of 10 meters or better will be
achievable with a high degree of confidence and precision. Note that
accuracy is not the same as precision. Precision is a quantification of
the range of variation normally present in a measurement technique
(i.e., precision describes the likelihood of the same values being
repeated in another measurement).
To be fully descriptive, coordinate pairs require two accuracy
measurements; one for latitude and one for longitude. Due to the
additional burden on data storage, however, the EPA requires in the
Locational Data Policy (LDP)17 that only the lowest accuracy
measurement be recorded, regardless of whether it is for longitude or
for latitude. With such an arrangement, the user community will
know that both coordinates are at least as accurate as the reported
value.
Accuracy is to be presented as a range within which there is
confidence that the true latitude/longitude value falls. The format for
presentation of accuracy is: ±X units where units are degrees,
minutes, seconds, or decimal fractions of a second. Accuracy should
be presented to one decimal place smaller than the units in which the
latitude/longitude coordinates are reported. Therefore, if coordinates
are presented in whole-tenths-of- seconds, it is because they have been
"rounded up" from some value in hundredths-of-seconds, and the
accuracy is described as the range, in hundredths of seconds. In
general, to meet the 25 meter goal, accuracy should be determined
within fractions of a second.
17
U .S. EPA Office of Information Resources Management, Information Resources Management
Policy Manual - Locational Data Policy, April 8, 1991.
-20-
-------
Accuracy of Latitude and Longitude Measurement
EXAMPLES: The following examples suggest ways of expressing this data element.
+ 432430.3
±0.05
Represents a latitude value of + 43°24'30.3" (+432430.3) which is the
least accurate of the latitude/longitude coordinates, for this example.
This value has an accuracy range of ± five one-hundredths of a
second (± 0.05) assuming that the latitude /longitude coordinates
have been reported to the tenths of seconds.
-1295720.8
±.03
Represents a longitude value of -129°57'20.8" (-1295720.8) which is the
least accurate of the latitude/longitude coordinates, for this example.
This value has an accuracy range of ± three one-hundredths of a
second (± 0.03) assuming that the latitude/longitude coordinates have
been reported to the tenths of seconds.
-21-
-------
GEOGRAPHIC DESCRIPTOR
7. ALTITUDE
DEFINITION: The vertical distance from the National Reference Datum for Altitude
to the land surface or other measuring point in feet or meters. If the
measuring point is above the National Reference Datum for Altitude
a "+" (plus) sign shall precede the reported altitude value. If the
measuring point is below the National Reference Datum for Altitude
a "-" (minus) sign shall precede the reported altitude value.
DISCUSSION: The purpose of this element is to provide a vertical reference for use
in well construction and monitoring activities at wells, springs, or
other ground water locations (for an illustration of Altitude, see
Figure 2). Altitude is commonly referred to as elevation.
Measuring Point: the measuring point is the point at the well which
is used as a reference for making vertical measurements. The
following list presents the measuring points most commonly used by
agencies and suggested associated codes:
A = airline
C = top of well casing
K = Kelly Bushing
L = land or ground surface
U = underground surface (e.g., caves)
The following examples suggest ways to express a data convention for
this element. Meters is the preferred unit of measurement within
EPA systems.
EXAMPLES: L
+00100
M
represents the measuring point is the land or ground surface (L); and
the altitude of the measuring point, as well as the altitude of the land
surface, is 100 (+00100) meters (M) above the National Reference
Datum for Altitude.
C/-5.25F
represents the measuring point is the top of the well casing (C); and
the altitude of the measuring point is 5.25 (-5.25) feet (F) below the
National Reference Datum for Altitude.
-23-
-------
Altitude
Figure 2
Alt stud a of Land Surface
Above Reference Datum
(5,085 ft.)
^ _ ,
Filter Park f ^
1 \\
(
* From Figure 1 (Well A)
^ Altitude of Measuring
^7 *
Point (MR) Above
Reference Datum
f* naa ft >
^
x-^
^ Drive Pipe
Casino
^ Water Level
Water Table
Screened
Interval
)
Cross Section of a Screened Water Well Located Above Sea Level
-24-
-------
GEOGRAPHIC DESCRIPTOR
8. METHOD USED TO DETERMINE ALTITUDE
DEFINITION: The method used to determine the altitude value (Altitude Method),
the National Reference Datum on which the altitude measurement is
based (National Reference Datum for Altitude) and the date the
measurement was taken (Altitude Date).
DISCUSSION: The purpose of this element is to provide users with qualitative
information to assess the accuracy of the altitude value. The
definition consists of the following three components: (1) Altitude
Method, (2) National Reference Datum for Altitude and (3) Altitude
Date. Each of these components is discussed below.
(1) Altitude Method: the Altitude Method is the method the data
provider used to determine the altitude value. A description of the
method used provides some indication of the accuracy of the altitude
value. For example, data users may choose to place more confidence
in an altitude determined from using an absolute-mode global
positioning system rather than in an altitude manually interpolated
from a map or photo. In addition, data users may want to check an
altitude interpolated from a map or photo since a chance for gross
error exists if the data provider did not make a correct interpolation.
Data providers or managers also may want to add codes to this
element that provide a more explicit determination of the accuracy of
the altitude value (e.g., ± 0.5 meters or ± 50 feet).
The following presents descriptions of Altitude Methods and
suggested codes:
Altitude Method Codes:
A = surveyed using differential-mode global positioning system. This
mode uses two receivers in which one receiver is set at a known
point. Data are processed relative to a known point over time.
If proper modeling is used, global positioning system heights can
generally be determined to a precision of approximately 0.1
meters.
B = surveyed using absolute-mode global positioning system. This
mode uses a single receiver and determines a location with
respect to several satellites, not from a known point. This mode
is less accurate than the differential-mode.
-25-
-------
Method Used to Determine Altitude
C = surveyed from a benchmark using conventional survey methods.
A benchmark has a known altitude based on a National
Reference Datum. Examples of benchmarks include a disc in
the ground, a chiseled square in a headwall, a nail in a post, etc.
D = digitally interpolated from a map or photo.
E = manually interpolated from a map or photo.
(2) National Reference Datum for Altitude the National Reference
Datum for Altitude is a national standard for vertical control
established by the National Geodetic Survey. The two National
Reference Data for Altitude are the National Geodetic Vertical
Datum of 1929 (NGVD 29) and the North American Vertical Datum
of 1988 (NAVD 88). The name "NGVD 29" is a synonym for the "Sea
Level Datum of 1929 and was adopted by the National Geodetic
Survey in May 1976. The actual datum, however, remained the same.
Although based on the observed heights of sea level at a number of
tide gauges, the datum is not mean sea level. The National Geodetic
Survey is in the process of completing the newer NAVD 88. Data
providers need to use an appropriate code for specifying the National
Reference Datum that they used as the benchmark for the altitude
determination. If the National Reference Datum for Altitude is not
available, data providers should specify that this information is not
available.
The following are suggested codes for the National Reference Datum
for Altitude:
National Reference Datum for Altitude Codes:
29 = National Geodetic Vertical Datum of 1929
88 = North American Vertical Datum of 1988
00 = National Reference Datum for Altitude is not available
(3) Altitude Date the Altitude Date is the date on which the data
provider determines the altitude. This date is important because it
can provide additional information on the accuracy of the altitude
value. Due to technological advances in determining altitude, data
users also may use the Altitude Date to identify altitude values they
would like to update, especially if they need precise locational
information.
-26-
-------
Method Used to Determine Altitude
Altitude Date format is based on Federal Information Processing
Standard (FIPS) Publication 4-118, which sets the standard for date
representation for all Agencies of the Federal government as
yyyymmdd, where y = year, m = month, and d = day. The following
examples suggest various ways for expressing a data convention for
this element.
EXAMPLES: B
88
19811204
represents the Altitude Method is surveyed using absolute-mode
global positioning system (B); the National Reference Datum for
Altitude is the North American Vertical Datum of 1988 (88); and the
Altitude Date is December 4, 1981 (19811204).
D
29
1986
represents the Altitude Method is digitally interpolated from a map
or photo (D); the National Reference Datum for Altitude is the
National Geodetic Vertical Datum of 1929 (29); and the Altitude
Date is the year 1986 (1986).
1R
US Department of Commerce, National Bureau of Standards, Representation for Calendar
Date and Ordinal Date for Information Interchange, Federal Information Processing Standards (FIPS)
Publication 4-1, January 27, 1988.
-27-
-------
GEOGRAPHIC DESCRIPTOR
9. STATE FIPS CODE
DEFINITION: A Federal Information Processing Standard (FIPS) alphabetic or
numeric code to indicate the location of the state (or its equivalent
such as territory or province) in which the well is located.
DISCUSSION: The purpose of this element is to identify the state, territory, foreign
country, dependency or special sovereignty in which a well is located.
This code is especially important to identify data by state when those
data are contained in a multi-state data base.
State FIPS Codes are an accepted national convention for identifying
states or their equivalents. FIPS Codes for states and outlying areas
of the U.S. are expressed as two-digit numeric or alpha codes. Given
the wide use of State FIPS Codes, data providers are required to use
this data standard to specify the state (or its equivalent) in which a
well is situated.
A complete list of State FIPS Codes can be found in the following
publication:
U.S. Department of Commerce, Codes for the Identification of the
State, the District of Columbia and the Outlying Areas of the United
States, and Associated Areas. Federal Information Processing
Standards (FIPS) Publication 5-2, National Bureau of Standards,
Washington, D. C, May 28, 1987.
-29-
-------
State FIPS Code
The following are examples of the data convention for State FIPS
Codes. The most common preference is the alphabetic code.
EXAMPLES: MI
represents the alphabetic State FIPS Code for the State of Michigan.
26
represents the numeric State FIPS Code for the State of Michigan.
OK
represents the alphabetic State FIPS Code for the State of Oklahoma.
40
represents the numeric State FIPS Code for the State of Oklahoma.
AS
represents the alphabetic State FIPS Code for the U.S. sovereignty of
American Samoa.
60
represents the numeric State FIPS Code for the U.S. sovereignty of
American Samoa.
-30-
-------
GEOGRAPHIC DESCRIPTOR
10. COUNTY FIPS CODE
DEFINITION: A Federal Information Processing Standard (FIPS) numeric code to
indicate the location of the county (or county equivalent) in which a
well is located.
DISCUSSION: This information will allow data users to easily organize and present
ground water quality and other data at the county level. It is
particularly important for counties with the same names located in
different States.
County FIPS Codes are an accepted national standard for identifying
counties or their equivalents. County FIPS Codes are expressed as
three-digit numeric codes and are available for all counties, or their
equivalents, of the 50 states, the District of Columbia, and U.S.
possessions. Given the wide use of County FIPS Codes, data
providers are required to use this data standard to specify the county
or its equivalent in which a well is located.
A complete list of County FIPS Codes can be found in the following
publication:
U.S. Department of Commerce. Counties and Equivalent Entities of
the United States, its Possessions, and Associated Areas. Federal
Information Processing Standards (FIPS) Publication 6-4, National
Institute of Standards and Technology, Washington, D. C., August 31,
1990.
The following are examples of the data convention for County FIPS
Code.
EXAMPLES: 085
represents Sioux County in the State of North Dakota.
137
represents Putnam County in the State of Ohio.
073
represents Kingfisher County in the State of Oklahoma.
-31-
-------
WELL DESCRIPTORS
-33-
-------
WELL DESCRIPTOR
11. WELL IDENTIFIER
DEFINITION: A unique well identifier assigned by the responsible organization.
DISCUSSION: The purpose of this element is to (1) provide a means of uniquely
identifying each well (or spring or other ground water location) and
(2) provide a means of linking all data associated with each well. If
there are multiple wells (casings) in a single borehole (frequently used
for monitoring ground water at different depths), then each well
(casing) should have its own Well Identifier. Also, if there are
multiple completions of a single well, then data base managers may
choose to assign a unique Well Identifier to each well completion.
A variety of conventions exist for uniquely identifying wells. In fact,
most states have developed their own well identification systems. As
such, data providers may report Well Identifiers using these existing
systems or in any format that they feel is most appropriate for their
circumstances. The only requirements are that the Well Identifier
must (1) be associated with a particular known well; (2) be unique;
and (3) follow and incorporate EPA's Facility Identification Data
Standard if the well is part of a facility regulated by EPA19. In
addition, each individual well at an EPA site should have a unique
identifier (e.g., well 01, well 02, well 03, etc.). The code for the EPA
Facility Identification Data Standard is 12 digits in length, beginning
with the two digit alphanumeric State FIPS code and followed by a
ten digit arbitrary number that is assigned by EPA's Facilities Index
System (FINDS).
A variety of well identification systems exist. For purposes of
elaborating on this element, the examples below suggest several ways
of expressing a data convention for this element. The use of latitude
and longitude in well identification systems results from the
convention used by the U.S. Geological Survey. However, the use of
latitude and longitude in the Well Identifier in no way suggests that
data users should use the Well Identifier for purposes of well location
information.
U.S. EPA, EPA Order - Facility Identification Data Standard, Information, Management and
Services Division, April 9, 1990.
-35-
-------
Well Identifier
Use of the Well Identifier for purposes of well location information
must be avoided as the original latitude and longitude coordinates
may be revised over time using more precise locational methods while
the Well Identifier may not change. The use of latitude and longitude
is just one means of developing a unique number for the Well
Identifier and data users should not interpret any other information
from it.
The following examples show various ways to express a data
convention for this data element.
EXAMPLES: ALD980600001
represents a Well Identifier based on EPA's Facilities Index System
(FINDS) for a facility located in Alabama. The identifier consists of
the State FIPS code for the facility (AL) and a ten-digit number
randomly generated by FINDS (D980600001) representing well #1 at
the facility.
+300510
-0750407
03
represents a Well Identifier based on an estimate of the well's
location at a latitude of 30°05'10" (+300510) and a longitude of
-075°04'07" (-0750407) and is the third well that is present at the
same latitude/longitude location (03).
11S/17E
22dcal7
represents a Well Identifier located in township 11 south (1 IS), range
17 east (17E), section 22 (22), quarter section d (d), quarter-quarter
section c (c), quarter-quarter-quarter section a (a), and the 17th
sequentially numbered well within quarter-quarter section c (17).
014-1035-55432SD890EC33Y6
represents a Well Identifier based on the three-digit County FIPS
code (014), a four-digit submitting agency code (1035), and a 16-digit
alphanumeric well code (55432SD890EC33Y6).
62-000498
represents a Well Identifier based on a state formulated two-digit
county code (62), and the 498th sequentially numbered well in that
county (000498).
-36-
-------
WELL DESCRIPTOR
12. WELL USE
DEFINITION: The principal current use of the well, or if the well is not currently in
use, then the original or principal purpose for its construction.
DISCUSSION: The purpose of this element is to assist data users in distinguishing
between the various uses of wells. Knowing the use of a well is
particularly important when data users interpret ground water quality
data. For example, a data user may be very concerned if a sample
taken from a public water supply well violates maximum contaminant
levels (MCLs) for certain constituents. Alternatively, if the same
sample was taken from a remedial action monitoring well at a
Superfund site rather than a public water supply well, the data user
may not be as immediately concerned.
Wells have many different uses that will vary depending on several
factors such as geographic location and the structure of the regional
economy. For example, agricultural states may have a need to include
a number of specific well uses in their data base (e.g., irrigation wells,
livestock wells, irrigation return flow wells, agricultural drainage wells)
that a regional authority whose jurisdiction is dominated by heavy
industry would probably not include in their data base. Because of
the varying needs of different data bases, no one list of well uses is
likely to be sufficient. Therefore, provided below are a few lists of
well uses for consideration. The lists vary by the type and level of
detail of the well uses. These lists are provided merely to suggest
possible examples of well use lists. Data providers or data users
should modify these lists to meet their needs.
List 1 contains very broad categories of well uses with a description
of more specific uses associated with that category.
List 1
Withdrawal of Water includes public water supply wells, community
water supply wells, industrial water supply
wells, irrigation wells, etc.
-37-
-------
Well Use
List 1 (continued)
Monitoring includes RCRA monitoring wells, Superfund
monitoring wells, observation wells,
piezometer wells, test wells, etc.
Disposal includes deep injection wells and shallow
injection wells.
Unknown the well use is unknown.
List 2 presents more specific well uses that includes wells that are
primarily in a region dominated by agricultural communities and open
range land.
List 2
Public Water Supply Wells
Community Water Supply Wells
Non-community Water Supply Wells
Irrigation Wells
Livestock Watering Wells
Irrigation Return Flow Wells (Class V Injection Wells)
Agricultural Drainage Wells (Class V Injection Wells)
Other Class V Injection Wells
Class II Injection Wells (Salt water disposal wells, enhanced oil
recovery wells, and hydrocarbon storage wells)20
Class III Injection Wells (Salt and sulfur extraction wells and in situ
leaching wells)20
Class IV Injection Wells (Hazardous and radioactive wastewater
disposal wells located in or above underground sources of
drinking water (USDWs))20
Geophysical Wells
Geothermal Wells
Oil and Gas Wells
Unknown
20 For more information on describing injection wells and their classifications, see: U.S.
Environmental Protection Agency and the Underground Injection Practices Council, Injection Wells - An
Introduction to Their Use. Operation and Regulation, (undated).
-38-
-------
Well Use
List 3 presents a broader list of well uses that may be necessary for
large data bases such as State data bases.
List3
Public Water Supply Wells
Community Supply Wells
Non-community Supply Wells
Industrial Supply Wells
Recharge Wells
Irrigation Wells
RCRA Monitoring Wells
Superfund Monitoring Wells
Recovery Wells
Remediation Wells
Piezometer Wells
Class I Injection Wells (Hazardous, nonhazardous and municipal
wastewater disposal wells located below USDWs)21
Class II Injection Wells (Salt water disposal wells, enhanced oil
recovery wells and hydrocarbon storage wells)21
Class III Injection Wells (Salt and sulfur extraction wells and in situ
leaching wells)21
Class IV Injection Wells (Hazardous and radioactive wastewater
disposal wells located in or above underground sources of
drinking water (USDWs))21
Class V Injection Wells (Injection wells not covered under the first
four classes of injection wells)21
Geophysical Wells
Geothermal Wells
Oil and Gas Wells
Unknown
21 For more information on describing injection wells and their classifications, see: U.S.
Environmental Protection Agency and the Underground Injection Practices Council, Injection Wells -An
Introduction to Their Use. Operation and Regulation, (undated).
-39-
-------
Well Use
The naming convention for each well type shall be the choice of
the data providers. The following examples suggest a few means of
expressing a data convention for this element.
EXAMPLES: A
represents a Public Water Supply Well.
01
represents a Public Water Supply Well.
PWS
represents a Public Water Supply Well.
-40-
-------
WELL DESCRIPTOR
13. TYPE OF LOG
DEFINITION: The type of record-keeping log(s) available for a well.
DISCUSSION: The purpose of this element is to provide data users with information
on the types of logs that are available for a given well. Data users
can use this information for a number of purposes. For example,
knowing the types of logs available will help users decide whether
examining the logs is worthwhile to them.
There may be a number of different logs that have been completed
for a given well. For example, some well logs such as electrical logs
and radioactive logs are often completed together at the same well.
As a result, this element will be a repeating field.
Below is a list of common ground water well logs and one means of
defining codes for each log type. The list includes general families of
well logs (e.g., radioactive logs) as well as more specific log types (e.g.,
video logs). This list is provided to present examples of different
types of record-keeping logs. Data managers or data providers may
modify this list as they wish and present it as a look-up table. For
example, data managers may want to provide more specific types of
radioactive logs such as gamma-gamma logs and gamma-ray logs. The
only requirements are that data managers provide a means for
indicating, in a logical manner, the types of logs available for ground
water wells, and that they reference these logs in a consistent way.
Examples of different types of logs include the following:
A = Acoustic - a graphical representation of the transit of an
acoustical pulse through a length of material.
C = Caliper - a graphical record of the diameter of an uncased
borehole at various depths.
D = Driller's - a description of the material penetrated during
drilling, prepared by the drilling crew.
E = Electrical - a graphical representation of the resistivity to
the flow of electric current or electrical potentials
(voltages) through subsurface geologic formations.
-41-
-------
Type of Log
G = Geologist's/Engineer's - a record prepared by a geologist
or engineer that presents a description of the lithology of
each formation penetrated by the well (e.g., sand, shale).
R = Radioactive - a graphical representation of the natural,
induced, or isotope injection radioactivity of subsurface
geologic formations.
T = Temperature - a continuous record of temperature in the
borehole taken at various depths.
U = Unknown.
V = Video - a video tape record of the features of a well
created by lowering a video camera into the well.
The following examples suggest two means of expressing a data
convention for this element.
EXAMPLES: A
represents an acoustic log.
G
represents a geologist's log.
-42-
-------
WELL DESCRIPTOR
14. DEPTH OF WELL AT COMPLETION
DEFINITION: The depth of the completed well below the land surface or other
measuring point, in feet or meters.
DISCUSSION: The purpose of this element is to provide well construction data that
are useful in interpreting water quality data. The depth of the well
at completion may indicate whether the well fully penetrates the
aquifer. The measuring point used as a reference point to determine
the depth of the well at completion is specified under the Altitude
data element. If the measuring point is not level (e.g., the plastic well
casing was cut unevenly), the measurement is usually taken from the
lowest point on the measuring point. Because there are different
margins of error associated with the various devices used to measure
the depth of a well, data base managers may consider requesting that
data providers indicate the measurement devices used. Note that this
element is not referring necessarily to the depth of the original
wellbore. In addition, note that this element is not applicable to
springs. (For illustrations of Depth of Well at Completion, see
Figures 3 and 4.)
The following examples suggest ways of expressing a data convention
for this element. Meters is the preferred unit of measurement within
EPA systems.
EXAMPLES:
050
M
represents the well is completed to a depth of 50 (050) meters (M)
below the measuring point (defined under the Altitude element).
100
F
represents the well is completed to a depth of 100 (100) feet (F)
below the measuring point (defined under the Altitude element).
-43-
-------
Depth of Well at Completion
Figure 3
Diagram to Illustrate Depth of Well atCoiriDietion
Land surface (5,085 ft.)*
Measuring Point (MP)
(5,088 ft.)
Drive Pipe
Casing
Water Level
Water Table
Filter Pack
Screen
Total Drilled Depth
From Measuring Point (39 ft.;
From figure 1 (Well A)
Screened
Interval
Total Depth of Completed
Well From Measuring
Point (36 ft.)
Cross Section of a screened Water Well
-44-
-------
Depth of Well at Completion
Figure 4
Diagram to Illustrate Depth of Well at Comoletion
Total Depth of
Completed Well
from Measuring
Point (20 ft.)
Altitude of MP (5,605 ft.)*
LarjdSurface (5,602 ft.)'
Conductor
Pipe
Cement Grout
Depth to
Water from
MP is 15 ft
Open Hole
Explanation:
Depth to water table from land surface is 12 ft.
Depth to water table from measuring point is 15 ft.
Drilled depth is 20 ft.
*From Figure 1 (Well B)
Cross Section of an Open Hole Water Well
-45-
-------
WELL DESCRIPTOR
15. SCREENED/OPEN INTERVAL
DEFINITION: The depth below the measuring point to the top and bottom of the
open section in a well reported as an interval in feet or meters. The
open section may be a well screen, perforated casing or open hole.
DISCUSSION: The purpose of this element is to report the depth of the
hydrogeologic interval from which ground water is drawn. Recording
this interval is also important in the event that the screened or
perforated casing requires maintenance. The first value in this
interval is the depth below the measuring point to the top of the open
section. The measuring point is recorded under the Altitude data
element. The second value in this interval is the depth below the
measuring point to the bottom of the open section. The open section
may be a well screen, open hole, or perforated casing. (For an
illustration of Screened/Open Interval, see Figure 5.). Finally, since
some wellbores may have multiple completions, and each well
completion may have multiple screened, perforated, or open sections,
this data element may be a repeating field. Note that this element is
not applicable to springs.
The following examples suggest two means of expressing a data
convention for this element. Meters are the preferred unit of
measurement within EPA systems.
EXAMPLES: 22.0
25.5
M
represents a screened/open interval whereby the depth from the
measuring point (defined under the Altitude element) to the top of
the open section is 22 (22.0) meters (M) and the depth from the
measuring point to the bottom of the open section is 25.5 (25.5)
meters.
00075.5
00079
F
represents a screened/perforated interval whereby the depth from the
measuring point (defined under the Altitude element) to the top of
the open section is 75.5 (00075.5) feet (F) and the depth from the
measuring point to the bottom of the open section is 79 (00079) feet.
-47-
-------
Screened/Open Interval
Figure 5
Diagram to Illustrate Screened/Oneri Interval
Measuring Point (MP)
(5,088 ft.
Land surface (5,085 ft.)
Water Level
Water Table
Screened/Open
Interval
Total Drilled Depth
From Measuring Point (110 ft)
* From Figure 1 (Well A)
Cross Section of a Screened Water Well
-48-
-------
SAMPLE DESCRIPTORS
-49-
-------
SAMPLE DESCRIPTOR
16. SAMPLE IDENTIFIER
DEFINITION: A unique number for each water quality sample collected at a well
(Sample Control Number) which references the date (Sample Date),
the depth at which each sample is taken reported in feet or meters
(Sample Depth) and the time the sample is taken (Sample Time).
DISCUSSION: The purpose of this element is to provide critical supporting
documentation for each water quality sample. The supporting
documentation for the water quality samples include the following
four components: (1) Sample Control Number, (2) Sample Date,
(3) Sample Depth and (4) Sample Time. Each of these components
is discussed below.
(1) Sample Control Number: the Sample Control Number is a unique
number or series of codes that the data provider must assign to each
sample collected at a well. The purpose of this Control Number is to
provide a means of identifying the sample and linking it to
corresponding water quality data for a particular well. Provisions may
need to be made to account for the possibility that laboratories may
split one sample into a number of different samples. If a sample is
split, the newly created samples must be assigned unique Sample
Control Numbers.
(2) Sample Date: the data provider also must record the date that
water quality samples are taken. The Sample Date is necessary for
tracking trends in ground water quality over time. The format for
Sample Date is based on the Federal Information Processing Standard
(FIPS) for date (i.e., yyyymmdd)22.
(3) Sample Depth: The Sample Depth indicates the depth in the
aquifer or aquifers (in case of multiple saturated zones) with respect
to the measuring point (recorded under the Altitude data element)
from which the water quality sample was taken and the units of
measure used to report this measurement. Sample depth information
can be referenced to hydrogeologic information which can help data
users analyze water quality. Meters is the preferred unit of measure
within EPA systems.
22
U S Department of Commerce, National Bureau of Standards, Representation for Calendar
Date and Ordinal Date for Information Interchange. Federal Information Processing Standards (FIPS)
Publication 4-1, January 27, 1988.
-51-
-------
Sample Identifier
(4) Sample Time: The data provider must record the time each water
quality sample is taken. The time must indicate a.m. or p.m. (either
explicitly or through the use of the 24-hour clock) and the time zone.
The time a sample was taken is an important piece of information.
For example, two samples taken at the same well, at the same depth,
on the same day but at different times may show a difference in the
water quality analysis results. Data providers will need to consider
normalizing the recorded time to account for differences between
standard time and day-light savings time.
The following examples suggest a few means of expressing a data
convention for this element. Each component of the Sample
Identifier has its own "field" and as such data base managers may
decompose the components to make any necessary corrections to their
database, if needed.
EXAMPLES: 00101
19820430
026.5
M
1635
EDT
represents the unique Sample Control Number (00101), the Sample
Date is April 30, 1982 (19820430), the Sample Depth is 26.5 (026.5)
meters (M) and the Sample Time is 1635 (1635) eastern daylight time
(EDT).
100262
19821204
1635EST
65F
represents the unique Sample Control Number (100262), the Sample
Date is December 4, 1982 (19821204), the Sample Time is 4:35 p.m.,
eastern standard time (1635EST) and the Sample Depth is 65 (65)
feet (F).
100262A
19821204
1635EST
65F
represents the unique Sample Control Number (100262A) that is a
split sample from the sample identified directly above. The Sample
Date is December 4, 1982 (19821204), the Sample Time is 4:35 p.m.,
eastern standard time (1635EST) and the Sample Depth is 65 (65)
feet (F).
-52-
-------
SAMPLE DESCRIPTOR
17. DEPTH TO WATER
DEFINITION: The vertical distance between the measuring point and the water
surface level at a well, corrected to land surface, where the measuring
point is not the land surface. This distance should be reported in feet
or meters (Measurement Depth), along with the date and time the
measurement was taken (Measurement Date and Measurement Time).
DISCUSSION: The purpose of this element is to provide and track depth to water
measurements that are necessary for the construction of
potentiometric surface maps. The depth measurement must be
corrected to the land surface when constructing the potentiometric
maps. For an illustration of Depth to Water, see Figure 6. Since
officials may take more than one depth to water measurement at a
well, the field for this element will be a repeating field. Note that this
element is not applicable to springs. The definition consists of the
following three components: (1) Measurement Depth,
(2) Measurement Date and (3) Measurement Time. Each component
is described below.
(1) Measurement Depth: the Measurement Depth is typically the
static water level obtained by measuring the distance between the
measuring point to the water surface in a particular aquifer before the
well is purged. This distance is corrected to the land surface. Static
water level measurements, however, are not always possible especially
at public water supply wells. The measuring point used as a reference
point for this measurement is specified under the Altitude data
element. If the measuring point is not level (e.g., the plastic well
casing was cut unevenly), the measurement is usually taken from the
lowest point on the measuring point. In most cases, the water surface
will be below the measuring point, therefore, the depth to water
measurement will be taken from below the measuring point.
However, there are cases when the water surface will be above the
measuring point (e.g., flowing artesian wells). To differentiate depth
to water measurements in this case, the standard convention is to
precede the depth to water value with a "-" (minus) sign if the water
surface level is above the measuring point. Data providers will also
need to specify the units of measure used to report the Measurement
Depth value. EPA prefers the use of meters. Because there are
different margins of error associated with various devices used to
measure the depth to water, data base managers may consider
requesting that data providers indicate the measurement devices used.
-53-
-------
Depth to Water
Figure 6
Diagram to Illustrate Depth to Water
Altitude of Measuring Point (MP)
/ (5,088 ft.)
4
"3ft,
1
*
f
Depth To Water
(25 ft.)
i
F
S
--^—
/
r
liter Pack
(
(
k.
f
^-»*
**7*^
—
<-"-•
J.
Attitude of Land Surface
(5,085ft.)*
^. Water Level
Water Table
^
Screened
Interval
^ Total Drilled Depth
From Measuring Point (39 ft.)
Explanation: Depth to water table from land surface is 22 ft.
Depth to water table from measuring point is 25 ft.
•From Rgure 1 (well A)
••Distance between measuring point and land surface is 3ft.
Cross Section of a screened Water Well
-54-
-------
Depth to Water
(2) Measurement Date: the Measurement Date is the date that the
depth to water measurement was taken. This component is necessary
since officials will take several depth to water measurements over
time and will need to relate each measurement to when it was taken.
The format for Measurement Date is based on the Federal
Information Processing Standard (FIPS) for date (i.e., yyyymmdd)23.
(3) Measurement Time: Officials may occasionally take more than
one depth to water measurement in the same day. In this case, the
time at which the measurements were taken must be recorded to
differentiate the depth to water measurements. Data providers will
need to consider normalizing the recorded time in their time zone to
account for differences between standard time and day-light savings
time. The time must indicate a.m. or p.m. (either explicitly or through
the use of the 24-hour clock) and the time zone. Since officials may
take more than one depth to water measurement at a well, the field
for this element will be a repeating field.
The following examples suggest two means of expressing a data
convention for this element. Meters is the preferred unit of
measurement for EPA systems.
EXAMPLES: -000.25
M
19821204
04:35P
EDT
represents the Measurement Depth is 0.25 (-000.25) meters (M) above
the measuring point, the Measurement Date is December 4, 1982
(19821204) and the Measurement Time is 4:35 (04:35) p.m. (P),
eastern daylight time (EDT).
00125.F
19831230
1635
EST
represents the Measurement Depth is 125 (00125) feet (F) below the
measuring point, the Measurement Date is December 30, 1983
(19831230) and the Measurement Time is 4:35 p.m. (1635), eastern
standard time (EST).
US Department of Commerce, National Bureau of Standards, Representation for Calendar
Date and Ordinal Date for Information Interchange, Federal Information Processing Standards (FIPS)
Publication 4-1. January 27, 1988.
-55-
-------
SAMPLE DESCRIPTOR
18. CONSTITUENT OR PARAMETER MEASURED
DEFINITION: Measurement of a physical, chemical or biological component. The
physical, chemical or biological components are referred to as
constituents or parameters.
DISCUSSION: The purpose of this element is to provide a means of identifying the
constituents or parameters that data providers measure in ground
water samples. Constituent or parameter codes developed for U.S.
EPA's data Storage and Retrieval system (STORE!) are widely used
by the U.S. EPA, U.S. Geological Survey, States and other agencies
and organizations. However, States may have or prefer to use other
constituent or parameter codes such as Chemical Abstract Service
Registry Numbers (CAS Numbers). Data providers should use the
constituent or parameter codes that they feel best meet their needs
and note the source of the parameter codes. The following list
presents suggested abbreviations for parameter code sources:
S = STORET parameter codes
C = CAS number
O = other
If data providers would like to use STORET Parameter Codes, a
current online file of STORET codes can be obtained from the U.S.
EPA Client Services Branch (1-800-424-9067 or 1-703-883-8861).
The following examples suggest two means of expressing a data
convention for this element.
EXAMPLES:
39180
S
represents the STORET parameter code (S) for trichloroethylene
(whole water sample (39180).
79016
C
represents the CAS Number (C) for trichloroethylene (79016). Note:
A CAS Number can have several STORET parameter codes.
-57-
-------
SAMPLE DESCRIPTOR
19. CONCENTRATION/VALUE
DEFINITION: The analytical results value, the units of measure used (Analytical
Concentration/Value) and the analytical method applied (Analytical
Method) to samples collected.
DISCUSSION: The purpose of this element is to record the concentration or values
of the parameters measured showing units of measurement and
analytical methods used. The definition consists of the following two
components: (1) Analytical Concentration/Value and (2) Analytical
Method. Each component is described below.
(1) Analytical Concentration/Value: the Analytical
Concentration/Value is the concentration or value of a particular
ground water quality parameter obtained from laboratory and/or field
analyses. Data providers may need to express Analytical
Concentrations/Values in scientific notation. Data providers will need
to specify the units of measure used to report the Analytical
Concentration/Value. Since data providers are likely to have
Analytical Concentrations/Values for multiple parameters, this
element may be a repeating field.
(2) Analytical Method: the Analytical Method is the method of
analysis applied to determine the Analytical Concentration/Value for
a particular ground water quality parameter. Reference to the
specific analytical method should include information on the minimum
detection limit of that method and the units of measurement used.
This element may be a repeating field. A comprehensive listing of
analytical method codes and descriptions of the methods is available
from the following publications:
U.S. EPA "Environmental Monitoring Methods Index (List of Lists -
Catalog of Analytes and Methods)," Office of Water Regulations and
Standards, September, 1990; and
U.S. EPA, "Test Methods for Evaluating Solid Waste," Office of Solid
Waste and Emergency Response, SW-846, November 1986.
-59-
-------
Concentration/Value
The following examples suggest two means of expressing a data
convention for this element.
EXAMPLES: 00002.07E-03
8080
represents the Analytical Concentration/Value is 2.07 x 10~3
(00002.07E-03) measured in units of micrograms per liter (/xg/1); the
analytical method is EPA Analytical Method 8080 ~ gas
chromatographic analytical method for various organochlorine
pesticides and PCB's (8080). This method specifies the minimum
detection limit of the method and the units of measure for various
types of organochlorine pesticides and PCB's (e.g., the minimum
detection limit of this method for the pesticide Heptachlor is 0.003
Mg/1).
00004 Mg/1/8240
represents the Analytical Concentration/Value is 4 (00004) measured
in units of micrograms per liter (p. g/1); the analytical method is EPA
Analytical Method 8240 — gas chromatography/mass spectrometry for
volatile organic compounds (8240). This method specifies the
minimum detection limit of the method and the unit of measure (e.g.,
the minimum detection limit of this method for 1,1,1-trichloroethane
is 5 M g/1).
-60-
-------
SAMPLE DESCRIPTOR
20. ANALYTICAL RESULTS QUALIFIER
DEFINITION: Qualifying information that will assist in the interpretation of the
concentration/value, such as whether the value is below the detectable
limit or if the constituents (parameters) of interest are present but
cannot be quantified.
DISCUSSION: The purpose of this element is to provide clarifying and/or supporting
analytical results information. The analytical results qualifier,
together with the analytical method recorded under the
concentration/value element and the quality assurance information
(see element 19~Quality Assurance Indicator) will help the data
user to determine the reliability and usefulness of the analytical
results data.
Different agencies and programs use various methods to present
analytical results qualifiers. Some examples of analytical-results
qualifiers are provided below:
ADL = Above Detection Limits
A suitable concentration exists for analysis and it is above the
detection limit of the analytical method.
BDL = Below Detection Limits
The concentration of the constituent (parameter) in the sample did
not exceed the lower detection limit in force at the time the analysis
was performed. Concentration/Value, if present, is at best an
approximate value.
BQL = Below Quantitation Limits
Concentration of the constituent or parameter was below the limit of
analytical quantitation. Concentration/Value, if present, is at best an
approximate value.
FPS = Failed Preliminary Screening
A preliminary screening of the sample for the subject parameter was
conducted. The result of the screening indicated that determining the
concentration of the parameter would not be useful.
-61-
-------
Analytical Results Qualifier
NSA = Sample Not Suitable for Analysis
The sample was not suitable for analysis, i.e., there was not a
sufficient quantity of the sample to conduct an analysis, there was an
accident in the field or laboratory that rendered the sample unsuitable
for analysis, or the sample was not preserved properly.
PNQ = Present But Not Quantified
The subject parameter was present in the sample but no quantifiable
result could be determined.
If "above detection limit," "below detection limit" and "below
quantitation limit" are included as analytical results qualifiers, then
the data provider should also provide the values of those limits.
Knowing the detection and quantitation limits is important for three
reasons: (1) detection and quantitation limits can improve over time;
(2) detection limits will vary depending on the analytical method used
and the laboratory performing the analysis; and (3) knowing a
concentration/value was below the detection and/or quantitation limit
provides little information unless the actual limits are specified.
The following examples suggest three ways to express a data
convention for this element.
EXAMPLES: BDL
1
represents there was not a sufficient concentration of the constituent
(parameter) in the sample to exceed the lower detection limit in force
at the time the analysis was performed (1 microgram per liter (jj. g/1)).
Concentration/Value, if present, is at best an approximate value.
ADL
represents there is a suitable concentration for analysis and it is above
the detection limit of the analytical method.
BQL
2
represents the concentration of the parameter was below the limit of
analytical quantitation (2 micrograms per liter (/ig/1))-
Concentration/Value, if present, is at best an approximate value.
-62-
-------
SAMPLE DESCRIPTOR
21. QUALITY ASSURANCE INDICATOR
DEFINITION: The quality assurance of the field protocol plan and laboratory quality
assurance/quality control (QA/QC) procedures.
DISCUSSION: The purpose of this element is to provide a means of reporting the
level of reliability attached to the sample data. This element includes
information on the degree of sophistication of both the field protocol
plan and the laboratory QA/QC procedures in effect at the time of
sampling. The following presents a suggested means of defining codes
for the field protocol plan and laboratory QA/QC procedures:
Field Protocol Plan Codes:
A = Resource Conservation and Recovery Act (RCRA) Field
QA/QC Program which includes (1) a reference to
accepted sampling techniques, (2) procedures for
documenting field actions contrary to the QA project plan,
(3) documentation of pre-field activities (i.e., equipment
calibrations and container preparation), field activities, and
post-field activities (i.e., sample shipment and receipt, and
team debriefing), (4) documentation of field measurement
quality control data and (5) generation of quality control
samples (i.e., trip and equipment blanks).
B = A detailed field sampling and preservation protocol plan
that was developed by a certified laboratory or
organization and approved by the responsible regulatory
authority. Standard procedures and internal checks also
exist.
C = A detailed field sampling and preservation protocol plan
that contains standard procedures and internal checks but
has not been approved by the responsible organization
(State, EPA).
D = No detailed field sampling protocol plan exists.
U = Field sampling protocol information is unknown.
-63-
-------
Quality Assurance Indicator
Laboratory QA/QC Procedures Codes:
1 = The laboratory is certified by a state for all parameters
reported or has had a state or EPA approved QA/QC
evaluation within the last two years with a satisfactory
rating.
2 = Work conducted by an EPA Contract Laboratory Program
lab.
3 = Laboratory has a detailed QA/QC plan with standard
procedures and internal checks. Neither the state nor EPA
has verified or evaluated the procedures, but the objectives
of the plan have been reported as being met.
4 = Laboratory has a detailed QA/QC plan with standard
procedures and internal checks, however, neither the state
nor EPA has evaluated or verified the procedures.
5 = No detailed laboratory QA/QC plan exists.
6 = Laboratory QA/QC information is unknown.
The suggested codes for the field protocol plan and the laboratory
QA/QC procedures provide a hierarchy of plans and procedures that
range from the most to the least sophisticated. The RCRA field
QA/QC program is at the top of the field protocol plan hierarchy
since protocols used to enforce RCRA requirements are the most
exacting. The following examples suggest ways of expressing a data
convention for this element.
-64-
-------
Quality Assurance Indicator
EXAMPLES: A
3
represents use of RCRA Field QA/QC Program guidelines (A) and
use of a detailed laboratory QA/QC plan with standard procedures
and internal checks, however, neither the State nor EPA has verified
or evaluated the procedures, but the objectives of the plan have been
reported as being met (3).
C5
represents use of a detailed field sampling and preservation protocol
plan that contains standard procedures and internal checks but has
not been approved by the responsible organization (C) and no
detailed laboratory QA/QC Procedures exist (5).
-65-
-------
APPENDICES
-67-
-------
APPENDIX A
Key Issues Involved in the Implementation of the Minimum Set of
Data Elements for Ground Water Quality
The Minimum Set of Data Elements for Ground Water Quality (MSDE) does not
address issues related to actually designing or implementing a ground water quality data
base. For example, the MSDE does not identify computer hardware specifications or
logical design requirements. Instead the MSDE focuses on identifying and defining a list
of data elements that, at a minimum, should be included in a ground water quality data
base. EPA, however, has included this appendix that discusses key issues involved in the
implementation of the MSDE.
This appendix identifies and describes a few fundamental data base design and
implementation issues that some data base managers may find useful in developing or
modifying a data base. Data base managers are likely to be well aware of these issues
and may have already incorporated them into their data bases. By no means is this
discussion of key implementation issues exhaustive. The purpose of this appendix is to
identify and briefly discuss fundamental data base implementation issues that data base
managers may want to consider. For more information, officials should contact the
information systems specialists in their agency or department.
This appendix focuses on the following key MSDE implementation issues:
Consistency in expressing data;
Linking related data; and
Storing data fields separately.
Consistency in Expressing Data
Designing data bases to consistently define parallel information contained in
different elements is important. For example, several elements in the MSDE record
depth information that require the unit of measurement to be identified (i.e., either feet
or meters). Data bases should consistently use the same unit of measurement ~ either
feet or meters ~ for all relevant data elements. EPA uses meters, which is becoming
standard practice. If data are not expressed consistently, data base managers will need
to develop conversion programs to make the data uniform. Such conversion programs
can be complex and may fail to convert all data, resulting in errors.
Units of measure is just one example of the need to express data consistently.
Other examples include the use of alphabetical and numerical representations for data
and the number of spaces allowed after a decimal. Prescribing formats for each data
element is not an objective of this document except where EPA policy or Federal
standards specify formats (e.g., latitude and longitude). Therefore, it is the role of the
-69-
-------
Appendix A
data base developer and/or data base manager to consider ensuring, to the extent
practicable, that data are expressed consistently.
Database developers and managers have an important incentive to ensure such
consistency. Consistent data results in a data base that uses storage space efficiently and
requires less maintenance. It should also lead to easier database enhancements that
may be implemented in the future such as upgrading the complexity of the reports the
data base is able to generate. These advantages ultimately save often scarce program
dollars, making efforts to ensure data consistency a wise investment.
Linking Related Data
A critical factor in the design of any data base is deciding how to link data that are
distinct but related. For one data record, each data element in the MSDE represents a
distinct piece of information, but all are related by the fact that they represent attributes
of the same well (e.g., the altitude, depth to water, and concentration/value of a
constituent are all attributes of the same well). In order to save storage space and
improve the efficiency of the data base, data base developers can group similar data
elements into what are known as "entity" files. An entity can be defined as an object or
event that is of concern to your data base. The following list identifies the three entities
related to the MSDE:
(1) Wells and other ground water locations;
(2) Samples; and
(3) Analytical results.
Each data element in the MSDE can be grouped under one of these three entities
and helps to define the attributes of that entity. For example, the general, geographic
and well descriptors (elements 1 through 13) describe the attributes of a well (i.e., the
well entity). Element 14 — Sample Identifier ~ and element 15 — Depth to Water ~
describe the attributes of a sample (i.e., the sample entity). And elements 16 through 19
describe the attributes of each sample analysis (i.e., the analytical results entity).
One entity relates to the next entity in what is referred to as a one-to-many
relationship. That is, each well will have several samples that are taken from it,
therefore there is a one-to-many relationship between wells and samples. Similarly, each
sample will likely be analyzed for several constituents, therefore, there is a one-to-many
relationship between samples and analytical results.
A less efficient way of linking all the data elements together is to repeat the well
entity attributes and the sample entity attributes for each analytical result recorded. For
example, if a well sample is analyzed for fifty separate constituents, then each of those
fifty records would have to repeat all of the well entity and sample entity elements (i.e.,
elements 1 through 15). This method of linking data would result in a great deal of data
-70-
-------
Appendix A
repetition and, therefore, would not maximize the data storage capabilities of the data
base.
In contrast, the most efficient way for database developers to link all the data
elements together and avoid repeating data is to group the MSDE elements that define
each entity into three separate entity files. Using the example from above, creating the
three separate entity files will allow the storage of the fifty different analytical results
without repeating the well and sample entity elements. Data from each entity file is
linked to the corresponding data in other entity files by what is known as "primary keys."
A primary key is a unique identifier created for each record in an entity file that is
repeated for corresponding records in the other entity files thereby enabling the linking
of these related data elements. To be more specific, primary keys allow information
from each analytical result to be linked to its proper sample and each sample to be
linked to its well to allow you to reconstruct all the data for a single well. The MSDE
would need two primary keys to link the three entity files. Element 9 ~ Well identifier -
- can be used as the primary key to link the elements in the well entity file with the
elements in the sample entity file. Element 14— Sample Identifier, or more specifically,
the Sample Control Number under this element ~ can be used as the primary key to link
the elements under the sample entity file with the elements under the analytical results
entity file. See Figure 7 for an illustration of linking related data in this manner.
Storing Data Fields Separately
Data elements that contain two or more values representing distinct pieces of
information can be stored separately in different fields to increase the flexibility of a
data base. Separating data fields will make it easier for data base users to use the data
and for data base managers to correct any data errors. These benefits are particularly
apparent when a primary key contains data values in addition to a unique identifier.
Because primary keys are critical to linking data, any error in a data value that is part of
a primary key should be easy to correct.
An example of this issue is element 14 ~ Sample Identifier. The Sample identifier
is comprised of the date, time, and depth the sample was taken in addition to the unique
sample control number. Storing sample date, sample time, sample depth, and sample
control number separately makes it easy to correct errors and will result in minimal
impact to tracking the sample and linking data. On the other hand, if sample date, time,
depth, and control number were stored in one composite field, then a subsequent data
correction would result in a new sample identification number that could lead to
confusion in tracking the sample and linking its related data.
Another example of an MSDE data element that contains two values is element 13
~ Screened/Open interval. This data element consists of (1) depth below the measuring
point to the top of the open section and (2) depth below the measuring point to the
bottom of the open section. Data base managers may choose to store these values in
separate fields as is suggested in the example for this element.
-71-
-------
Appendix A
Figure 7.
Diagram to Illustrate Linking Related Data
Well
Entity
File
primary
key
^ -^
(Well
Identifier)
Samples
Entity
File
primary
key
<^
^
(Sample
Identifier)
Analytical
Results
Entity
File
1. Data Sources
2. Latitude
3. Longitude
4. Method Used to
Det. Lat./Long.
5. Altitude
6. Method Used to
Det. Altitude
7. State FIPS Code
8. County FIPS Code
9. Well Identifier
10. Well Use
11. Type of Log
12. Depth of Well
at Completion
13. Screened/Open
Interval
9. Well Identifier
14. Sample Identifier
15. Depth to Water
4. Sample Identifier
16. Constituent or
Parameter Used
17. Concentration/Value
18. Analytical Results
Qualifier
19. Quality Assurance
Indicator
-72-
-------
Appendix A
Conclusion
The MSDE does not address issues involved in the implementation of the data set.
Data base developers, however will need to consider many such issues including:
Consistency in expressing data;
Linking related data; and
Storing data fields separately.
Considering these issues early in the planning process will help ensure that the data base
stores data efficiently, data can be corrected easily, and the data base can accommodate
future enhancements.
-73-
-------
APPENDIX B
List of Workgroup Members
These are the workgroup members involved with assisting in refining the element
names and developing definitions for the data elements.
STATES
Sonja Massey
Department of Environmental
Management
Montgomery, Alabama
Bill Ashton
Alaska Department of Environmental
Conservation
Anchorage, Alaska
Wayne Hood
Arizona Department of Environmental
Quality
Phoenix, Arizona
Ralph Desmarais
Water Division
Little Rock, Arkansas
Darlene E. Ruiz
State of California Water Resources
Control Board
Sacramento, California
Heather Stone
Regional Water Quality Control Board
Monterey Park, California
Scot Davies
Colorado Department of Health
Denver, Colorado
Dan Meade
Department of Environmental Protection
Hartford, Connecticut
Mike Apgar
Department of Natural Resources &
Environmental Control
Dover, Delaware
Philip J. Cherry
Delaware Department of Natural
Resources & Environmental Control
Dover, Delaware
Richard Budell
Bureau of Pesticides
Tallahassee, Florida
Rodney DeHan
Bureau of Drinking Water and Ground
Water Resources
Tallahassee, Florida
William McLemore
Georgia Geologic Survey
Atlanta, Georgia
Dan Chang
Hawaii Department of Health
Honolulu, Hawaii
Gerry Winter
Department of Health and Welfare
Boise, Idaho
Bob Clarke
Illinois Environmental Protection Agency
Springfield, Illinois
-75-
-------
Appendix C
Kenneth Hlinka
Illinois State Water Survey
Champaign, Illinois
Marty Risch
Department of Environmental
Management
Indianapolis, Indiana
Rick Kelley
Iowa Department of Natural Resources
Des Moines, Iowa
Vic Robbins
Kansas Department of Health &
Environment
Topeka, Kansas
Bill Bryson
Kansas Corporation Commission
Topeka, Kansas
Bill Yarnell
Department for Environmental
Protection
Frankfort, Kentucky
Laurie Peacock
Ground Water Protection Division
Baton Rouge, Louisiana
Paul Dutram
State Planning Office
Augusta, Maine
Mike Griffen
Hazardous & Solid Waste Management
Administration
Baltimore, Maryland
David Terry
Division for Water Supply
Boston, Massachusetts
Mike Beaulac
Department of Natural Resources
Lansing, Michigan
Tom Segall
Department of Natural Resources
Lansing Michigan
Robert Bixby
St. Cloud State University
St. Cloud, Minnesota
Debra Menk
Water Resources Center
Mankato, Minnesota
Susan Schreifels
Minnesota Pollution Control Agency
St. Paul, Minnesota
Charlie Smith
Ground-Water Quality Branch
Jackson, Mississippi
John Finley
Department of Natural Resources
Jefferson City, Missouri
Gary Gingery
Montana Department of Agriculture
Helena, Montana
Dick Ehrman
Nebraska Department of Environmental
Control
Lincoln, Nebraska
Jim Cooper
Bureau of Water Quality Planning
Carson City, Nevada
Paul Currier
Department of Environmental Services
Concord, New Hampshire
-76-
-------
Appendix C
Dan Van Abs
Department of Environmental Protection
Trenton, New Jersey
Stuart Castle
Ground Water Bureau
Santa Fe, New Mexico
Natalie Keller
New Mexico Environmental
Improvement Division
Santa Fe, New Mexico
Fred VanAlstyne
Department of Environmental
Conservation
Albany, New York
Carl Bailey
Department of Environmental Health
and Natural Resources
Raleigh, North Carolina
Kris Roberts
North Dakota State Department of
Health
Bismark, North Dakota
Mike Baker
Ohio Environmental Protection Agency
Columbus, Ohio
Larry Edmison
Department of Pollution Control
Oklahoma City, Oklahoma
Richard Kepler
Oregon Department of Environmental
Quality
Portland, Oregon
Joe Lee
Bureau of Community Environmental
Control
Harrisburg, Pennsylvania
Susan B. Kiernan
Rhode Island Department of
Environmental Management
Providence, Rhode Island
Michael Muthig
Bureau of Solid & Hazardous Waste
Management
Columbia, South Carolina
Tom Donn
Department of Health and
Environmental Control
Columbia, South Carolina
Barbara Nielsen
South Dakota Department of Water and
Natural Resources
Pierre, South Dakota
Pat Turri
Bureau of Environment
Nashville, Tennessee
Bill Klemt
Texas Water Commission
Austin, Texas
Jerry Mullican
Texas Railroad Commission
Austin, Texas
Bill Damery
Utah Department of Health
Salt Lake City, Utah
David Butterfield
Department of Environmental
Conservation
Waterbury, Vermont
Winslow LaDue
Vermont Department of Health
Burlington, Vermont
-77-
-------
Appendix C
Fred Cunningham
Virginia State Water Control Board
Richmond, Virginia
Ginny Stern
Washington Department of Ecology
Lacey, Washington
Patrick V. Campbell
West Virginia Department of Natural
Resources
Charleston, West Virginia
Gary LeMasters
Wisconsin Department of Agriculture
Madison, Wisconsin
Randell Clark
Wisconsin Department of Natural
Resources
Madison, Wisconsin
Jake Strohman
Department of Environmental Quality
Cheyenne, Wyoming
FEDERAL AGENCIES
Department of Agriculture
Jim Hyland
Soil Conservation Service
Washington, D.C.
Dennis Erinakes
National Water Quality Technology
Development Staff
Fort Worth, Texas
Department of Commerce
David Doyle
National Geodetic Survey, NOAA
Rockville, Maryland
Department of Defense
Ming Tseng
U.S. Army Corps of Engineers
Washington, D.C.
Edmund Miller
Environmental Engineering
Alexandria, Virginia
John Edkins
Naval Energy and Environmental
Support Activity
Port Hueneme, California
Department of Housing and Urban
Development
Truman Goins
Office of Environment and Energy
Washington, D.C.
Department of Interior
Claud Baker
Geological Survey
Lawrence, Kansas
Darwin Knochenmus
Geological Survey
Baton Rouge, Louisiana
Robert Laney
Geological Survey
Reston, Virginia
Jayne May
Geological Survey
Oklahoma City, Oklahoma
John McLean
Geological Survey
Lakewood, Colorado
-78-
-------
Appendix C
Paul Summers
Bureau of Land Management
Denver, Colorado
Kip Gjerde
Bureau of Reclamation
Billings, Montana
Lynn Johnson
Bureau of Reclamation
Denver, Colorado
Douglas Growitz
Office of Surface Mining
Reclamation and Enforcement
Washington, D.C.
EPA REGIONS
Dave Delaney
Region I
Office of Ground-Water
Boston, Massachusetts
Richard Bloch
Region II
Office of Ground-Water
New York, New York
Stu Kerzner
Region III
Philadelphia, Pennsylvania
Peter Schaul
Region III
Superfund Programs Branch
Philadelphia, Pennsylvania
Phyllis Mann
Region IV
Office of Integrated Environmental
Analysis
Atlanta, Georgia
Robert Olive
Region IV
Atlanta, Georgia
Bill Melville
Region V
Chicago, Illinois
James Harris
Region VI
Dallas, Texas
Dan Harris
Region VII
Kansas City, Kansas
Randy Brown
Region VIII
Denver, Colorado
Tom Aalto
Region VIII
Denver, Colorado
Steve Ihnen
Region IX
Office of Ground-Water
San Francisco, California
Matt Gubitosa
Region X
Geographic Information Systems Section
Seattle, Washington
EPA HEADQUARTERS
Office of Air and Radiation
Kathy Kaufman
Air Quality Management Division
Washington, D.C.
-79-
-------
Appendix C
Office of Information Resources
Management
Steve Hufford
Information Management and Services
Division
Washington, D.C.
Phil Lindenstruth
Systems Development Center
McLean, Virginia
Walter Shackelford
Research Triangle Park, North Carolina
National Enforcement Investigations
Center
Steven Sisk
Denver Federal Center
Denver, Colorado
Office of Pesticides and Toxic
Substances
Paul Tobin
Office of Toxic Substances
Washington, D.C.
David Wells
Office of Pesticide Programs
Washington, D.C.
Office of Policy Planning and Evaluation
Cindy Dyballa
Office of Policy Analysis
Washington, D.C.
Office of Research and Develpment
Jane Denne
Environmental Monitoring Systems
Laboratory
Las Vegas, Nevada
Office of Solid Waste and Emergency
Response
Jim Brown
Office of Solid Waste
Washington, D.C.
Jennifer Haley
Office of Emergency and Remedial
Response
Washington, D.C.
Mary Lou Melley
Office of Program Management and
Technology
Washington, D.C.
Rick Otis
Policy Analysis and External Affairs
Washington, D.C.
Office of Water
Wendy Blake Coleman
Resource Management Administration
Office
Washington, D.C.
Roger Anzzolin
Office of Drinking Water
Washington, D.C.
Bob Thronson
Office of Water Regulations and
Standards
Washington, D.C.
ALTERNATES AND INTERESTED
PARTIES
Cindy Warner
EPA Office of Water Regulations and
Standards
Washington, D.C.
-80-
-------
Appendix C
Stallings Howell
EPA, Region IV
Office of Ground-Water
Atlanta, Georgia
Erlece Allen
EPA, Region VI
Office of Ground Water
Dallas, Texas
Pat Costello
EPA, Region VII
Office of Ground Water
Kansas City, Kansas
Bill Pedicino
EPA, Region VII
WSTM/RCRA
Kansas City, Kansas
Donald Gipe
EPA, National Enforcement
Investigations Center
Denver, Colorado
Lee Lenfest, Jr.
U.S. Geological Survey
Reston, Virginia
Kenneth J. Lanfear
U.S. Geological Survey
Reston, Virginia
Bill Wilber
U.S. Geological Survey
Reston, Virginia
Tom Yorke
U.S. Geological Survey
Reston, Virginia
Terry Thompson
U.S. Geological Survey
Reston, Virginia
-81-
-------
BIBLIOGRAPHIES
-83-
-------
BIBLIOGRAPHY A
Bibliography of Key References
Aller, Linda, Bennett, Truman W., Hackett, Glen, Petty, Rebecca J., Lehr, Jay H.,
Sedoris, Helen, and Denne, Jane E., Handbook of Suggested Practices for the Design
and Installation of Ground Water Monitoring Wells. U.S. EPA Environmental
Monitoring Systems Laboratory, September 26, 1989.
Arizona Department of Environmental Quality, Ground Water Quality Data Base
Systems Definition Document May 19, 1989, 51 pp.
Baker, Jr., C. H., and D. G. Foulk, National Water Data Storage and Retrieval System
rWATSTOREV Instructions for Preparation and Submission of Ground Water Data.
USGS Open File Report 75-589-IV, 1975 (Revised 1980).
Battelle Memorial Institute, Pacific Northwest Laboratories, Procedures for Ground
Water Investigations. September, 1989.
Childress, C. J., Chancy, T. H., Myers, D., Norris, J. M., and J. Hren, U.S. Geological
Survey Water-Quality Data Collection Activities in Colorado and Ohio: Phase II-
Evaluation of 1984 Field and Laboratory Quality-Assurance Practices. Open File Report
87-33, 1987, 70 pp.
Collins, C. A., Ground Water Data in the Baker County-Northern Malheur County Area.
Oregon. USGS Open-File Report 79-695, 1979, 28 pp.
Crouch, M. S., "Tidally Induced Water Level Fluctuations as a Measure of Diffusivity in
a Confined Aquifer- A Graphical Method," Proceeding of the FOCUS Conference on
Southeastern Ground Water Issues. Tampa, FL, October 6-8, 1986, pp. 231-286.
Dictionary of Scientific and Technical Terms. Ed. Sybil P. Parker, McGraw-Hill Book
Company, Fourth Edition, 1989.
District of Columbia, Department of Consumer and Regulatory Affairs, Housing and
Environmental Regulation Administration, Letter to EPA, April 5, 1989, 3 pp.
Federal Interagency Coordinating Committee on Digital Cartography, Federal
Geographic Exchange Format: A Standard Format for the Exchange of Spatial Data
Among Federal Agencies. Final Draft Version 01.08, December 15, 1986, 52 pp.
Ferrigno, C. F., A Data-Management System for Detailed Areal Interpretative Data.
USGS Water Investigations Report 86-4091, 1986, 103 pp.
-85-
-------
Bibliography A
Florida Department of Environmental Regulation, Letter to EPA, Enclosure: "GWIS-
MWI Data Dictionary Draft," April 21, 1989, 55 pp.
Freethey, G. W., Models. Data Available, and Data Requirements for Estimating the
Effects of Injecting Saltwater Into Disposal Wells in the Greater Altamont-Bluebell Oil
and Gas Field. Northern Uinta Basin. Utah. USGS Open-File Report 88-475, 1988, 30
pp.
Gandl, L. A., and J. A. Fleniken, "The Use of Limited Geophysical Log Data to
Delineate and Characterize Disposal and Confining Zones," Proceedings of the FOCUS
Conference on Southeastern Ground Water Issues. Tampa, FL, October 6-8, 1986, pp.
304-311.
ICF Incorporated, Sample Tracking Form, EPA National Pesticide Survey, December
1989.
KRS Enterprises, Incorporated, Letter to EPA and Letter to ICF, Enclosure: "Sample
Well Logs," August 29, 1989, 11 pp.
Laura, Delia, Virgina Water Use Data System. USGS, 1978, 215 pp.
Lindquist, R. C., Scott, T. M., Lloyd, J. M., and Arlington, D. V., "A Microcomputer Data
Base System for the Scientific Well Log Data Base of the Florida Geological Survey",
Southwestern Ground Water Symposium Proceeding. Monitor Wells and Computer
Applications to Water Resources. Florida Water Well Association, October 1986, 324 pp.
Massachusetts - Methods of Field Verification for Data Layer Points, 5 pp.
Meyer, M., "A Summary of South Dakota's Ground Water Information Resources, Data
Management Efforts, and Data Needs," EPA/SEA 2.3.1. Ground Water Quality
Management, 1. Institutional Strategy, A. 1.2.- Data Summary, January 1986, 51 pp.
Michigan Land and Water Management Division (Geological Survey Division), "Water
Well Record Location Verification Methods: A User Manual," April 1989, pp. 7-8.
Michigan - Southwestern Michigan Ground Water Survey and Monitoring Program,
Users Guide, October 1986 (extracted portions), 22 pp.
Minnesota Pollution Control Agency, Integrated Ground Water Information System
(IGWIS), Data Dictionary, Field Descriptions and Sample Component Section, 45 pp.
Minnesota - DNR Well Log Listing System, Wells Data Base, File Definition, 4 pp.
Minnesota - DNR Water Use Codes to be Used by IGWIS, 1 page.
-86-
-------
Bibliography A
Minnesota Pollution Control Agency, Integrated Ground Water Information System
(IGWIS), Facility and Station Components Sections, 144 pp.
Missouri, Sample Quality Assurance/Quality Control Information, 3 pp.
Missouri, Data Dictionary Reporter Element Report, Febuary 1, 1988.
Moses, C. O., "WATIN- A Computer Program for Generating Input Files for WATEQF,"
Ground Water. Vol. 24, No. 1, January-February, 1986, pp. 83-89.
North Carolina - Chapter 3. Header Screen Definitions, pp. 21-30.
Pennsylvania - List of Definitions used in the Bureau of Water Quality Management's
Ground Water Monitoring Programs, pp. 9-36.
State of Maine Ground Water Data Base Management System Standards, Ground Water
Standing Committee, November 1, 1988.
State of Minnesota Geological Survey Database File and Record Structure for Wells and
Well Logs.
State of Minnesota Pollution Control Agency, "Ground Water, Leachate, Spring, and
Surface Water Sample Confidence Factor Codes," June 30, 1987, 1 page.
State of Washington Department of Ecology Water Resources Program, Data Reporting
Manual for the Ground Water Management Program, October 1987.
State of Delaware Department of Natural Resources and Environmental Control, Letter
to EPA Enclosure: "Well Data Set," April 3, 1989, 6 pp.
Taylor, John K., "Quality Assurance of Chemical Measurements," Analytical Chemistry.
Vol. 53, # 14, December 1981, pp. 1588A-1596A.
Taylor, John K. and Kratochvil, Byron, "Sampling for Chemical Analysis." Analytical
Chemistry. Vol. 53, # 8, July 1981, pp. 925A-938A.
Texas, Ground Water Data System Data Dictionary. Instruction and Coding Procedures.
1989, 52 pp.
U.S. Army Toxic and Hazardous Materials Agency, USATHAMA OA Program.
Aberdeen Proving Ground, MD, Second Edition, March 1987.
-87-
-------
Bibliography A
U.S. Department of Commerce, American National Standard Codes for the
Representation of Names of Countries. Dependencies, and Areas of Special Sovereignty
for Information Interchange. Federal Information Processing Standards (FIPS)
Publication 104-1, National Bureau of Standards, U.S. Department of Commerce,
Washington, D. C., May 12, 1986. (This reference includes codes for foreign countries
other than outlying areas of the United States.) U.S. Department of Commerce, Letter
to ICF, Enclosure: "Input Formats and Specifications of the National Geodetic Survey
Data Base," Volume I: Horizontal Control Data, 1982, 2 pp.
U.S. Department of Commerce, Counties and Equivalent Entities of the United States.
its Possessions, and Associated Areas. Federal Information Processing Standards (FIPS)
Publication 6-4, National Institute of Standards and Technology, U.S. Department of
Commerce, Washington, D.C., August 31, 1990.
U.S. Department of Commerce, Codes for the Identification of the State, the District of
Columbia and the Outlying Areas of the United States, and Associated Areas. Federal
Information Processing Standards (FIPS) Publication 5-2, National Bureau of Standards,
U.S. Department of Commerce, Washington, D.C., May 28, 1987.
U.S. Department of Commerce, National Geodetic Survey, Geodetic Glossary.
September 1986, 274 pp.
U.S. EPA, CERCLIS Data Element Dictionary. March 15, 1988, 300 pp.
U.S. EPA, Data Review Workgroup, Laboratory Data Validation Functional Guidelines
For Evaluating Inorganics Analyses. July 1, 1988, p. 16.
U.S. EPA, Data Review Workgroup, Laboratory Data Validation Functional Guidelines
for Evaluating Organics Analyses. February 1988.
U.S. EPA, Office of Information Resources Management, Information Resources
Management Policy Manual - Locational Data, April 8, 1991.
U.S. EPA, "Environmental Monitoring Methods Index (List of Lists - Catalog of Analytes
and Methods)," Office of Water Regulations and Standards, September 1990.
U.S. EPA. EPA Workshop to Recommend a Minimum Data Element Set - Dictionary of
Elements, (unpublished), June 6-81988, 90 pp.
U.S. EPA, Ground Water Data Management with STORET. OGWP, EPA/440/6-87-
005, May 1987.
U.S. EPA, "Standards for the Electronic Transmission of Laboratory Measurement
Results," Information, Management and Services Division Memorandum, July 27, 1987,
52 pp.
-------
Bibliography A
U.S. EPA, EPA Order - Facility Identification Data Standard, Information, Management
and Services Division, April 9, 1990.
U.S. EPA, STORE! Seminar Documentation Storage, March 13, 1989, 115 pp.
U.S. EPA, "Test Methods for Evaluating Solid Waste, Laboratory Manual
Physical/Chemical Methods," Vols. 1A, IB, 1C; "Field Manual Physical/Chemical
Methods," Vol. 11, EPA-OSW, SW-846, Third Edition, November 1986.
U.S. EPA, ESAT Division, Region V. Guidelines for Inorganic Data Review and
Preparation of Re view Narratives: prepared by Winston K. Vijjeswarapu, Jan. 25, 1988,
p. 5.
U.S. EPA, Office of Ground Water Protection, Minimum Set of Data Elements for
Ground Water: DEFINITIONS AND FORMATS. January 4, 1990 (unpublished).
U.S. EPA, Office of Ground Water Protection, Definitions for the Minimum Set of Data
Elements for Ground Water. July 23, 1990 (unpublished).
U.S. EPA, Office of Waste Programs Enforcement. RCRA Ground Water Monitoring
Technical Enforcement Guidance Document. September 1986, 317 pp.
U.S. EPA, Region IV, Environmental Services Division, National Contract Laboratory
Program (CLP) Data Review. Standard Operating Procedures. Athens. GA, Oct 1. 1987,
Attachment 3, pp. 2-4, 6-7.
U.S. EPA, Region VII, Organic Data Review Training Course, p. 5.
U.S. EPA, Region VII, Inorganic Data Review Training Course, p. 5.
USGS, A Data-Management System for Use in Ground Water Modeling and Resource
Evaluation. Water Resources Investigations Report 84-4014, March 1984, 277 pp.
USGS, Definitions of the Components of the Water Data Sources Directory Maintained
by the National Water Data Exchange. Open-File Report 82-923, 1982, 125 pp.
USGS, Definitions of Components of Master Water Data Index Maintained by the
National Water Data Exchange (NAWDEXX Open-File Report 82-327, 1982, 268 pp.
USGS Form No. 9-1904-A, revised February 1987, and Form No. 9-1904-B, revised
February 1987.
USGS, Geophysical Well-Log Data Base for the Gulf Coast Aquifer Systems. South
Central United States. Open File Report 87-677, 1987, 213 pp.
-89-
-------
Bibliography A
USGS, Ground Water Withdrawal and Water-Level Data Used to Simulate Regional
Flow in the Major Coastal Plain Aquifers of New Jersey. Water-Resources Investigations
Report 87-4038, 1987, 120 pp.
USGS, GWSI Data Dictionary. Version 89.1, National Water Information System User's
Manual Attachment, 1989, 189 pp.
USGS, Instructions for Using the U.S. Geological Survey Data Base. USGS Open File
Report 82-568, 1982, 189 pp.
USGS, Lithogic Schedule. Form No. 9-1904-F, 2 pp.
USGS, National Water Information System User's Manual. Vol. 2, Ch. 4, Ground Water
File, May 1989, 263pp.
USGS, National Water Information System 87.1 User's Manual (Draft), Open File
Report, Volume 2, Chapter 4.
USGS, Specifications for Representation of Geographic Point Locations for Information
Interchange. Geological Survey Circular 878-B.
USGS, Techniques of Water-Resources Investigations. Aquifer Test Desire. Observations
and Data Analysis.
USGS, Water Supply Paper 2220. Basic Ground Water Hydrology. 1983, 77 pp.
Virginia State Water Control Board, Memorandum - Definitions for the MSDEGW,
April, 1989, 3 pp.
Voegli, P.T., and Hershey, L. A., "Records of Logs of Selected Wells and Test Holes, and
Chemical and Radiometric Analyses of Ground Water, Prowers County, Colorado",
Groundwater. Vol, 1-13, Colorado Water Conservation Board, 1960, p. 52.
Washington State - Ground Water Management Data Form.
Wisconsin State - Ground Water Information Network Data Dictionary.
-90-
-------
BIBLIOGRAPHY B
Bibliography of References Consulted But Not Used
Agricultural Law and Policy Institute, Farming and Groundwater: An Introduction.
(Agricultural Law and Policy Institute issues booklet, No. 1), 1988, 64 pp.
American Chemical Society, "Guidelines for Data Acquisition and Data Quality
Evaluation in Environmental Chemistry," Vol. 52, No. 14, 1980, pp. 2242-2249.
American Society of Civil Engineers, Proceedings of the Symposium Sponsored by the
Committee on Watershed Management of the Irrigation and Drainage Division of the
American Society of Civil Engineers. Denver, Colorado, April 30-May 1, 1985, 319 pp.
American Geological Institute, Dictionary of Geological Terms. Third Edition, 1984, 788
pp.
Anttila, P. W., U.S. Geological Survey Ground Water Studies in California. USGS
Water Fact Sheet, 1988, 2 pp.
Appel, C. A., Selected Reports That Include Computer Programs Produced by the U.S.
Geological Survey for Simulation of Ground Water Flow and Quality. Water-resources
investigations report 87-4271, 1988, 64 pp.
ASTM. Annual Book of ASTM Standards. Vols. 11.01 and 11.02, 1988.
ASTM, ASTM Terminology Standard D965-86a, Standard Terminology for Ground
Water, 1 page.
Bone, L. I., " Developing Guidelines for Sampling and Analysis of Ground Water,"
Hazardous and Industrial Solid Waste Testing and Disposal. Vol. 6, 1986, pp. 337-342.
Born, S. M., A Guide to Groundwater Quality Planning and Management for Local
Governments. Wisconsin Geological and Natural History Survey, 1987, 91 pp.
Brother, M. R., and J. H. Clarke, "Interpretation of Ground Water Monitoring Data~An
Integrated Systems Approach," Proceeding of the FOCUS Conference on Southeastern
Ground Water Issues. National Water Well Association. Dublin, Ohio, 1986, pp. 70-96.
Brown, D. J., "Computerized Data Bases for Ground Water Management: The
Southwest Michigan Ground Water Program," Proceedings of the NWWA FOCUS
Conference on Midwestern Ground Water Issues. National Water Well Association.
Dublin, Ohio, 1987, pp. 59-70.
-91-
-------
Bibliography B
California, "Model(26) for Monitoring Wells Ordinance: Appendix A - Definition of
Terms," 5 pp.
California Hazardous Waste Laws, "Section 2600 State Water Resources Control
Board Title 23,"5 pp.
California Environmental Hazards Assessment Program, Sampling for Pesticide Residues
in California Well Water: 1987 Update. Well Inventory Data Base, December 1, 1987,
pp. 98-120.
Combs, L. J., U.S. Geological Survey Ground Water Studies in Kansas. USGS Water
fact sheet, 1988, 2 pp.
Computer Notes: A Computer Program for Generating Input Files for WATEQF.
Currie, Lloyd A., "Limits for Qualitative Detection and Quantitative Determination:
Application to Radiochemistry," Analytical Chemistry. Vol. 40, # 3, March 1968, pp. 586-
593.
Davis, G. H., "Current Methodologies for the Collection and Dissemination of Water
Resources Data in the United States," Water Management and Development.
Proceedings of the United Nations Water Conference. Mar del Plata. Argentina. March
1977. Vol. 1, part 4, 1978, pp. 2387-2411.
DeVille, W. B., and J. A. Malloy, "Low-Cost Data Management for Protection of Ground
Water Resources: The Importance of Quality Assurance," Hazardous and Industrial
Solid Waste Testing and Disposal. Vol. 6, 1986, pp. 104-119.
Edwards, M. D., "The National Water Data Exchange (NAWDEX) and its Services,"
Proceeding of the Eleventh Biennial Conference on Ground Water. Fresno, California,
September 15-16, 1977, pp. 126-132.
Electric Power Research Institute, Sampling Guidelines for Groundwater Quality. Project
2485-1 Final Report, September, 1987.
EnviroSys, Groundwater/DMS System Overview, 1987, 9 pp.
Extract from draft USGS paper on Colorado and Ohio studies, regarding quality
assurance/quality control, January 1987.
40 CFR 262, 264, 265, 270.
-92-
-------
Bibliography B
Geological Survey, Washington, D. C., "Remote Sensing for Water Resources
Management." Water Management and Development. Proceeding of the United Nations
Water Conference. Mar del Plata. Argentina. March 1977. Vol. 1, Part 4, 1978, pp. 2413-
2429.
Gilbert, B. K., and T. J. Buchanan, Water-Data Program of the USGS. USGS Circular
863, 1982, 54 pp.
Heath, R. C., Ground Water Regions of the United States. USGS Water-Supply Paper
2242, 1984.
Hem, J. P.. Study and Interpretation of the Chemical Characteristics of Natural Water.
USGS Water-Supply Paper 1473, 2nd Edition, 1970.
Hix, G., "A Data Base Management System Approach to Ground Water Data
Management," Proceedings of the NWWA Western Regional Conference on Ground
Water Management. San Diego, CA, October 23-26. 1983, pp. 351-355.
Holcomb Research Institute Butler University, The Establishment of a Groundwater
Research Data Center for Validation of Subsurface Flow and Transport Models-Final
Report. May 1989, 227 pp.
Hothem, L. D., Goad, C. C. and B. W. Remondi, "GPS Satellite Surveying-Practical
Aspects," The Canadian Surveyor. Vol. 38, No.3, 1984, pp. 177-192.
Hutchinson, N. E.. Compiler. WATSTORE-National Water Data Storage and Retrieval
System of the USGS-User's Guide. USGS Open-File Report 75-426, 1975, 791 pp.
Interagency Advisory Committee. Subsurface-Water Flow and Solute Transport. Glossary
of Selected Terms, draft report prepared by Subsurface-Water Glossary Working Group,
Ground Water Subcommittee, February 1988, 35 pp.
Kent, R. T., and K. E. Payne, "Sampling groundwater monitoring wells; special quality
assurance and quality control considerations," ACS Professional Reference Book. 1988,
pp. 231-246.
Kirchmer, C. J., "Quality Control in Water Analysis." Environmental Science and
Technology. Vol. 17, No. 4, 1983, pp. 174a-181a.
Knecht, W. A., and M. D. Edwards. Definitions of Components of the Water Data
Sources Directory Maintained by the National Water Data Exchange. USGS Open-File
Report 79-1541, 1980, 106pp.
Langbein, W. B., and K. T. Iseri. General Introduction and Hydrologic Definitions.
USGS Water-Supply Paper 1541-A, 1960, 29 pp.
-93-
-------
Bibliography B
Leick, A., "GPS Evolving: A surveyor muses on where the fledgling technology is taking
us," American Congress on Surveying and Mapping (ACSM) Bulletin. June 16, 1989, pp.
16-17.
List of Ground Water and Ground Water Related Data Elements with Associated
Codes, 34 pp.
Liu, Annemary, Taylor, Raymond, Adney, Kent, Falling, Gary, A Quality Assurance
Program for the Analysis of Volatile Organic Chemicals. California Water Service
Company, September 25, 1989.
Lehman, S. W.. Definitions of Selected Ground Water Terms-Revisions and Conceptual
Refinements. USGS Water-supply Paper 1988, 1972, pp. 21.
Marie, J. R.. Preliminary Evaluation of the Ground Water Data Network in Indiana.
USGS Water Resources Investigations 76-24, 1976.
Meinzer, O. E., Outline of Ground Water Hydrology with Definitions. USGS Water-
Supply Paper 494, 1923, 71 pp.
Mercer, M. W., and C. O. Morgan, Storage and Retrieval of Ground Water Data at the
USGS. USGS Circular 856, 1982, 57 pp.
Mink, J. F., "Handbook-Index of Hawaii Groundwater and Resources Data," Extracted
from reports of the Water Resources Research Center, University of Hawaii, 1977.
Minnesota, Appendix C: Lithologic Codes, Appendix D: Stratigraphic codes, 6 pp.
Minnesota Pollution Control Agency, Letter to EPA, Enclosure: MPCA Master Table
Layout Report, April 7, 1989,55 pp.
Mitchell, G. F., Assessment and Compilation of Groundwater Quality Data for
Mississippi. Water Resources Research Institute, Mississippi State University, 1986, 8 pp.
National Academy of Science. Final Report on Quality Assurance to the EPA. 1988, 53
pp.
National Committee for Digital Cartographic Data Standards, Issues in Digital
Cartographic Data Standards. Report 9, May 1987, 71 pp.
North Central Region Eight State Groundwater Workshop, North Central Region Eight
State Groundwater Workshop proceedings. Ames, Iowa, 1987, 128 pp.
-94-
-------
Bibliography B
Office of the Secretary/Commerce, "Standardization of Data Elements and
Representations," 15 CFR, Part 6, Subtitle A, 1987, pp. 72-77.
Oudijk, G.. Handbook for the Identification. Location and Investigation of Pollution
Sources Affecting Ground Water: A Basic Guide for Government Personnel. Industrial
Officials and Ground Water Consultants. National Water Well Association, 1989, 185 pp.
Paulsen, S. G., Chen, C. L., Stetzenbach, K. L., and Miah, M.J., Guide to the Application
of Quality Assurance Data to Routine Survey Data Analysis. U.S. EPA Environmental
Monitoring Systems Laboratory, January, 1988.
Peralta, R. C., Development of a Combined Quantity and Quality Model for Optimal
Groundwater Management. Arkansas Water Resources Research Center, University of
Arkansas, No. 127, 1987, 20 pp.
Pfannkuch, J., Elsevier's Dictionary of Hvdrogeology. 1969, 168 pp.
Philippines (Republic) National Water Resources Council, Manual on Water Data
Standards/Republic of the Philippines. National Water Resources Council. 1976.
Pinder, G. F., "A Digital Model for Aquifer Evaluation," Techniques of Water-Resources
Investigations of the United States Geological Survey. Automated Data Processing
Commutations. Book 7, Chapter 1, 1970, 18 pp.
Quality Assurance Terms, database search by EPA, Winter 1988/1989.
Rapp, J. R., Doyel, W. W., and E. B. Chase, Geological Survey Water Data Catalog.
USGS, 1969,657pp.
Sadeh, W. Z., "Data Collection, Analysis and Instrumentation," Stochastic Approaches to
Water Resources. Vol. I, Chapter 5, 1976, pp. 5-1 to 5-27.
Scalf, M. R., McNabb, J. F., Dunlap, W. J., and R. L. Cosby, Manual of Ground Water
Quality Sampling Procedures. National Water Well Association, 1981, 93 pp.
Schuller, R. M., Gibb, J. P., and R. A. Griffin, "Recommended Sampling Procedures for
Monitoring Wells," Ground Water Monitoring Review, 1981, pp. 42-46.
Shaw, J. E., and K. A. Rodberg, "Monitoring Well Inventory Using Database
Development Software," Hydraulics and Hydrology in the Small Computer Age: Volume
L Proceedings of the Specialty Conference sponsored by the Hydraulics Division of the
American Society of Civil Engineers, Lake Buena Vista, FL, August 12-17, 1985, pp. 748-
752.
-95-
-------
Bibliography B
Smith, J. S., Steele, D. P., Malley, M. J., and M. A. Bryant, "Principles of Environmental
Sampling." ACS Professional Reference Book. 1988, pp. 255-260.
Smith, B. J., U.S. Geological Survey Ground Water Studies in Missouri. USGS Water
fact sheet, 1988. pp. 2.
STORET codes, computer printouts alphabetical order and numerical order.
SYCOM, Inc.. Federal Reporting Data System (FRDS-II) Data Element Dictionary.
report submitted to EPA, ODW, October 30, 1987, 239 pp.
The University of Kansas Space Technology Center (Kansas Applied Remote Sensing
Program), "An Inventory of State Natural Resources Information System," January 1984,
pp. 1-3.
Titelbaum, O. A., Glossary of Water Resources Terms. Federal Water Pollution Control
Administration, 1970, 39 pp.
Tselentis, G. A., "Processing of Geophysical Well Logs by Microcomputers as Applied to
the Solution of Hydrogeological Problems," Journal of Hydrology. Vol. 80, No. 3/4,
October 5, 1985, pp. 215-236.
United Nations Educational Scientific and Cultural Organization, International Glossary
of Hydrology. First Edition, WMO\OMM\BMO-No. 385, 1974, 393 pp.
U.S. Department of the Interior, Dictionary of Mining, Mineral and Related Terms.
U.S. EPA. EPA Workshop to Recommend a Minimum Set of Data Elements for Ground
Water. Workshop Findings Report, OGWP, EPA 440/6-88-005, June 1988, 23 pp.
U.S. EPA. FRDS 1.5 to FRDS II Conversion Guide. Office of Water, December 2, 1987,
23pp.
U.S. EPA. FRDS-II Data Entry Instructions. Release Number 0.04, March 15, 1988, 118
pp.
U.S. EPA. Ground Water Data Requirements Analysis for the Environmental Protection
Agency. 1987.
U.S. EPA, "Guidelines Establishing Test Procedures for the Analysis of Pollutants Under
the Clean Water Act (Proposed Rule)," Federal Register, Vol. 44, No. 233, December 3,
1979, pp. 69464-69575.
-96-
-------
Bibliography B
U.S. EPA, "Guidelines Establishing Test Procedures for the Analysis of Pollutants Under
the Clean Water Act (Final Rule)," Federal Register, Vol. 49, No. 209, October 26, 1984,
pp. 43234-43442.
U.S. EPA, "National Primary Drinking Water Regulations," 40 CFR, Section 141.2,
August 1987, pp. 526-529.
U.S. EPA, Office of Air Quality Planning and Standards. Guidance on Appying the Data
Quality Objectives Process for Ambient Air Monitoring Around Superfund Sites (Stages
LUX August, 1989.
U.S. EPA, Office of Ground Water Protection, EPA Order: Minimum Set of Data
Elements for Ground Water, September 11, 1989.
U.S. EPA. Office of Ground Water Data Base. Interim Report, December 1988.
U.S. EPA, Office of Research and Development, Draft Glossary of Quality Assurance
Related Terms. September 29, 1988, pp. 1-26.
U.S. EPA, Office of Solid Waste, RCRIS Data Element Dictionary. September 20, 1989.
U.S. EPA, Office of Water, UIC Data Element Definitions. Preliminary Draft,
September 25, 1989.
User's Guide Version 1.8 to the Electronic Knowledge Services of the National Ground
Water Information Center.
USGS, "Aquifer Codes by State/Territory," Computer Printout, June 1989.
USGS. Ground Water Hydraulics. Professional Paper 708.
USGS, Office of Water Data Coordination, "Status of the Nation's Water Quality
Information Activities," Proceeding of the Joint Meeting Advisory Committee on Water
Data for Public Use. Interagency Advisory Committee on Water Data. Department of
the Interior. Charlottesville, VA, May 19-21, 1987, 114 pp.
Van Ee, J. J., and L. G. McMillion, "Quality Assurance Guidelines for Ground Water
Investigations: The Requirements," Ground Water Contamination: Field Methods.
1988, pp. 27-34.
Van der Leeden, F., Geraghty & Miller's Groundwater Bibliography. Water Information
Center, Plainview, N. Y., 1987, 381 pp.
Walton, W. C., Analytical Groundwater Modeling: Flow and Contaminant Migration.
1988, 172 pp.
-97-
-------
Bibliography B
Warner, D. L., "Monitoring Disposal-Well Systems," EPA 680/4-75-008, July 1975, 101
pp.
Washington State - Data Reporting Manual for the Ground Water Management
Program, October 1987.
Weeks, J. B., U.S. Geological Survey Ground Water Studies in Colorado. USGS Water
fact sheet, 1988,2 pp.
White, D. E., Summary of Hvdrologic Information in the El Paso. Texas. Area, with
Emphasis on Ground Water Studies. Texas Water Development Board, 1987, 75 pp.
Yee, Johnson, J. S., and W. R. Souza, Quality of Groundwater in Idaho. USGS Water-
Supply Paper 2272, 1987, 53 pp.
•CO. U.S. Government Printing office : 1992 - 715-003/67079
-98-
------- |