Baltimore
Integrated Environmental Management
Project
Phase II Report
Underground Storage Tanks Study
Regulatory Integration Division
Office of Policy Analysis
Office of Policy, Planning, and Evaluation
U.S. Environmental Protection Agency
1987
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Baltimore
Integrated Environmental Management Project
Phase II Report:
Underground Storage Tanks Study
Prepared by:
Emery T. Cleaves, Maryland Geological Survey
Thomas M. Gherlein, ICF Incorporated
Donna McCready, Sobotka & Company, Inc.
Patricia Overmeyer, Sobotka & Company, Inc.
Hope Pillsbury, Environmental Protection Agency
Catherine S. Tunis, Environmental Protection Agency
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PREFACE
This report was prepared under the auspices of the Baltimore Integrated
Environmental Management Project (IEMP). The Baltimore IEMP is a
collaborative effort of the State of Maryland, Anne Arundel and Baltimore
Counties, the City of Baltimore and the U.S. Environmental Protection Agency.
The Environmental Protection Agency (EPA) initiated the project as part of its
pursuit of new approaches to environmental management and policy. The purpose
of the IEMP is to use an integrated approach to identify and assess
environmental issues that concern managers, to set priorities for action among
these issues, and to analyze appropriate approaches to manage these problems.
The Baltimore IEMP represents the second of four geographic projects that
EPA initiated across the country. The Baltimore area was chosen, not because
it has a significant toxics problem, but because EPA and local officials
wanted to explore better ways to identify, assess, and manage the human health
risks of environmental pollutants in the area. Other IEMPs include
Philadelphia, Santa Clara County, and Denver.
The decision-making structure of the Baltimore IEMP consisted of two
committees, which also served as the means for State and local participation:
the Management'Committee and the Technical Advisory Committee. The Management
Committee, with members representing Baltimore City, Baltimore County, Anne
Arundel County, and the State, managed the IEMP and set its overall policy
directions. The Technical Advisory Committee, composed of technical managers
from the City of Baltimore, the two counties, the State, as well as
representatives from the Regional Planning Council and the academic community,
recommended issues to study, advised the Management Committee on the technical
and scientific aspects of the project, and oversaw and commented on all EPA
and consultant work. EPA provide administrative, technical, and analytical
support.
The Baltimore IEMP examined five environmental issues: air toxics,
Baltimore Harbor, indoor air pollution, lead paint abatement, and potential
contamination of groundwater from underground tanks. For further information
on these reports or other IEMP studies contact the Regulatory Integration
Division, the Office of Policy Analysis (PM-220) in the Office of Policy,
Planning, and Evaluation, U.S. Environmental Protection Agency, Washington,
D.C. 20460.
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ACKNOWLEDGMENTS
Numerous individuals contributed their time and effort to the preparation
of this report. They are:
Members of the Underground Storage Tank Work Group
Dr. Emery T. Cleaves (Chair), Deputy Director, Maryland Geological Survey,
Baltimore, MD
Bernard Bigham, Federal Program Coordinator, Waste Management Administration,
Maryland Department of the Environment, Baltimore, MD
N. Singh Dhillon, P.E., Director, Division of Environmental Health, Anne
Arundel County Department of Health, Annapolis, MD
John Hobner, Registered Sanitarian, Water Quality Section, Baltimore County
Department of Environmental, Protection and Resource Management, Towson, MD
Thomas Kusterer, Environmental Planner, Planning and Analysis unit, Maryland
Department of the Environment, Baltimore, MD
Edmond G. Otton, Hydrogeologist and President, E.G.. Otton & Associates,
Consultants, Towson, MD
William Sieger, Oil Control Division, Waste Management Administration,
Maryland Department of the Environment, Baltimore, MD
Colin Thacker, Office of the Director, Baltimore County Department of
Environmental Protection and Resource Management, Towson, MD
Othniel Thompson, Sanitarian VII, Science and Health Advisory Group, Maryland
Department of the Environment, Baltimore, MD
Edwin C. Weber, Chief, Oil Control Division, Waste Management Administration,
Maryland Department of the Environment, Baltimore, MD
Members of the Baltimore IEMP Management Committee
J. James Dieter, Special Assistant to the Administrator, Department of
Environmental Protection and Resource Management, Baltimore County
Max Eisenberg, Assistant Secretary for Toxics, Environmental Science, and
Health, Department of the Environment, State of Maryland
Robert Perciasepe, Assistant Director, Department of Planning, City of
Baltimore
Claude Vannoy, Assistant to the County Executive for Land Use, Anne Arundel
County
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Members of the Baltimore IEMP Technical Advisory Committee
Jared L. Cohon, Vice Provost for Research, and Professor of Geography and
Environmental Engineering, Johns Hopkins University (Chair, Technical Advisory
Committee)
Don Andrew, Administrator, Engineering & Enforcement Programs, Office of
Environmental Programs
Philip Clayton, Manager, Cooperative Clean Water Program, Regional Planning
Council
Emery Cleaves, Deputy Director, Maryland Geological Survey
Ralph Cullison, Baltimore City Department of Public Works, City of Baltimore
N. Singh Dhillon, Director, Environmental Health, Anne Arundel County Health
Department
Thomas Ervin, Environmental Planner, Anne Arundel County Department of
Planning and Zoning
Katherine Farrell, MD. , MPH; Chief, Division of Environmental Disease Control,
Office of Environmental Programs
David Filbert, Director, Division of Air Pollution Control, Baltimore County
Department of Environmental Protection and Resource Management
Frank Hoot, Assistant Commissioner, Environmental Health, Baltimore City
Health Department
Samuel Martin, Consultant, Vice Chair of TAC (represented Regional Planning
Council during Phase I)
Janice Outen, Supervisor of Water Quality, Baltimore County Department of
Environmental Protection and Resource Management
Colin Thacker, Office of the Director, Baltimore County Department of
Environmental Protection and Resource Management
William Wolinski, Water Quality Coordinator, Baltimore City Water Quality
Management Office
Staff of U.S. Environmental Protection Agency
Daniel Beardsley, Director, Regulatory Integration Division
Arthur Koines, Chief, Geographic Studies Branch
John B. Chamberlin, Site Director, Baltimore IEMP
Catherine S. Tunis, Policy Analyst, IEMP
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We would like to make a special acknowledgment of the contributions of
Hope Pillsbury in the development and guidance of this project.
The following individuals from consulting firms provided assistance on
this specific study:
Thomas Gherlein, ICF Incorporated
Donna McCready, Sobotka & Company, Inc.
Patricia Overmeyer, Sobotka & Company, Inc.
F.E. (Wes) Westerfield, Regional Planning Council
Jacob Wind, American Management Systems
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TABLE OF CONTENTS
Page
PREFACE . i
ACKNOWLEDGMENTS ii
TABLE OF CONTENTS " v
LIST OF EXHIBITS vii
EXECUTIVE SUMMARY viii
I. INTRODUCTION 1
I.A. Integrated Environmental Management Projects ......... 1
I.B. The Baltimore IEMP Study 1
I.C. Results of the Phase I Priority-Setting Process 4
I.D. Priority-Setting for Improved UST Management ... 6
II. THE UST SCREENING METHODOLOGY 8
II.A. Overview of the Problem 8
I I.B. Overview of the Approach 8
II. C. Individual Measures of Vulnerability . 9
II.C.l. Hydrogeologic Settings ... , , 9
II.C.2. Selecting Zip Codes" as Basic Geographic Units .... 12
II.C.3. UST Location and Density ..... 15
II.C.4. Population Density of Groundwater Users 15
II.D. Identifying and Collecting Data " ..... 16
II.E. UST Screening Analysis Map Overlays 18
III. APPLICATION OF THE UST SCREENING METHODOLOGY TO THE BALTIMORE
IEMP STUDY AREA AND GUIDANCE FOR ITS APPLICATION ELSEWHERE 20
III.A. Overview of the Baltimore Study Area . 20
III.A.1. Geography 20
III.A.2. Climate 20
III.A.3. Hydrogeology 20
III.B. Development of Groundwater Pollution Potential Maps 21
III.B.1. Hydrogeologic Settings in Anne Arundel County ... 21
III.B.2. DRASTIC Parameters for Anne Arundel County ..... 24
III.B.3. Map of Groundwater Pollution Potential
in Anne Arundel County 31
III.B.4. Hydrogeologic Settings of Baltimore
County (and Baltimore City) 31
III.B.5. DRASTIC Parameters for Baltimore County 36
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TABLE OF CONTENTS
Zlge
I1I.B.6, Map of Groundwater Pollution Potential In
Baltimore County 43
I1I.B.7. Guidance for Future Application of DRASTIC 43
III .C. Collecting Water Well Data 47
III.C.1. General Approach .... ...... 47
1II.C.2, Guidance for Collecting Well Data 50
III.D. Collecting Underground Storage Tank Data 51
III.D.l. General Approach .................. 51
III .D. 2 . Guidance for Collecting UST Data 51
III.E. Map Overlays: Well and UST Densities and Groundwater
Pollution Potential 52
III. E. 1. General Approach 52
III.E.2. Guidance for Future Application of the Methodology . 52
IV. STUDY FINDINGS AND CONCLUSIONS 54
IV.A. UST Screening Methodology: General Findings ......... 54
IV.B, Analytical Findings in the Baltimore Study Area 55
IV.C. Assumptions of the Analysis 57
V. PLANNED AND POTENTIAL USES OF THE UST SCREENING METHODOLOGY ..... 59
VI. ALTERNATIVE APPROACHES TO ASSESSING VULNERABILITY FROM LEAKING USTs . 61
FOOTNOTES 62
APPENDIX A: UNDERGROUND STORAGE TANK WORK GROUP MEMBERS A-l
APPENDIX B: WELL AND UST DATA B-l
APPENDIX C: SOFTWARE AND HARDWARE REQUIREMENTS FOR SCREENING ANALYSIS . C-l
APPENDIX D: SENSITIVITY ANALYSIS OF DRASTIC D-l
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LIST OF EXHIBITS
EXHIBIT I.1: Baltimore IEMP Study Area ..... 3
EXHIBIT 1.2; Relative Ranking of Potential Sources of Groundwater
Contamination 5
Exhibit IX.1 DRASTIC Parameter Weights, Ranges, and Ratings 11
EXHIBIT II.2: Zip Code Map of Anne Arundel County 13
EXHIBIT II.3: Zip Code Map of Baltimore County and Baltimore City ... 14
EXHIBIT III.l: Hydrogeologic Settings in Anne Arundel County 22
EXHIBIT III.2: Depth to Groundwater in Anne Arundel County ....... 25
EXHIBIT III.3: Net Recharge in Anne Arundel County 26
EXHIBIT III.4: Aquifer Media in Anne Arundel County . . 28
EXHIBIT III.5; Soil Media in Anne Arundel County ...... 29
EXHIBIT III.6: Topography in Anne Arundel County 30
EXHIBIT III.7: Impact of the Vadose Zone in Anne Arundel County .... 32
EXHIBIT III.8; Hydraulic Conductivity in Anne Arundel County . 33
EXHIBIT III.9: DRASTIC Scores for Sedimentary Rock Settings ...... 34
EXHIBIT III.10: Hydrogeologic Settings in Baltimore County ....... 35
EXHIBIT III.11: Depth to Groundwater in Baltimore County 37
EXHIBIT III.12: Net Recharge in Baltimore County 38
EXHIBIT III.13: Aquifer Media in Baltimore County 40
EXHIBIT III.14: Soil Media in Baltimore County ... 41
EXHIBIT III.15: Topography in Baltimore County .... 42
EXHIBIT III.16: Impact of the Vadose Zone in Baltimore County ...... 44
EXHIBIT III.17: Hydraulic Conductivity in Baltimore County 45
EXHIBIT III.18: DRASTIC Scores in Crystalline Rock Settings of
Baltimore County 46
Exhibit III.19: Distribution of Groundwater Usage and USTs in
Anne Arundel and Baltimore Counties . * 49
Exhibit III. 20: Automated Address-Matching Results, by Groups of
Well Permits 50
EXHIBIT IV.1: Relative Ranking of Hydrogeologic Settings by
DRASTIC Scores 55
Map Pocket I. UST Screening Methodology Map Overlays of Anne Arundel County
Map Pocket II. UST Screening Methodology Map Overlays of Baltimore County
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EXECUTIVE SUMMARY
This report presents the results of the Underground Storage Tanks (UST)
Study undertaken as part of EPA's Baltimore Integrated Environmental
Management Project (IEMP). The UST study represents one of five Phase II
studies of the Baltimore area conducted to address environmental issues of
particular concern. As a result of Maryland requirements that UST owners test
their tanks and report leaks, 8,500 tanks were tested and 720 were found to be
leaking. This 720 was part of 1,100 UST leaks reported in fiscal year (FY)
1987, a 78 percent increase in leak reports from IT 1986. The UST screening
methodology developed in this project enables environmental planners and oil
pollution enforcement officials to assess the relative vulnerability of areas
within the study area to groundwater contamination from leaking USTs; it does
not attempt to assess human health risks from exposures. Participants in the
IEMP UST study recommend that environmental officials at state, regional, and
local levels target their resources to evaluate and combat leaking USTs more
efficiently.
The UST screening methodology measures three separate factors that taken
together determine the relative vulnerability of an area: hydrogeologic
setting, groundwater use, and UST density.
o Hydrogeologic vulnerability is assessed using DRASTIC, a
standardized system developed by the National Water Well Association
with EPA support to evaluate groundwater pollution potential using
hydrogeologic settings.
o Groundwater use is assessed by determining the density of
populations using groundwater as a source of drinking water per
square mile within zip code areas.
o UST density is measured as the number of USTs per square mile within
specific zip code areas.
Each measure is geographically displayed on computer-generated maps at a
scale of 1:62,500 as well as the smaller size included in this report. These
maps are printed on transparent mylar, so that they can be laid over each
other to highlight interactions between the three indicators of vulnerability.
As applied to the Baltimore IEMP study area, the methodology reveals a
number of areas exhibiting relatively high vulnerability. Anne Arundel County
is shown to be more vulnerable than Baltimore County. Two factors contribute
to this. First, in Anne Arundel County, most people rely on public or
privately owned wells as their source of drinking water, whereas in Baltimore
County, most people obtain their drinking water from the Baltimore City water
system, which is derived from surface water. Second, the hydrogeology of Anne
Arundel County is relatively more susceptible to contamination. Much of the
northern portion of Anne Arundel County overlies vulnerable groundwater and
exhibits both high groundwater use and UST density. Within Baltimore County,
areas overlying the Cockeysville Marble formation exhibited the highest
vulnerability due to the pollution potential of the formation.
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The UST screening methodology allows officials to analyze the three
individual factors contributing to the vulnerability of a region, and evaluate
the interaction of these factors on maps. The State of Maryland plans to
apply the methodology to each of its counties. The IEMP participants plan to
use the UST screening methodology to set priorities for UST leak investigation
and cleanup, to review proposed development, to educate UST users and
developers, and to supplement related studies. The availability and accuracy
of data will strongly influence the time and effort involved and the accuracy
of the analysis. Jurisdictions may wish to evaluate and revise their UST and
groundwater data reporting to facilitate updates of the screening products.
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I. INTRODUCTION
I.A. Integrated Environmental Management Projects
This report describes a study of underground storage tanks (USTs) in the
greater Baltimore area. In this study, we developed a methodology that can
help state and local officials set priorities for UST management. We applied
this methodology in the study area and identified those areas most vulnerable
to groundwater contamination from leaking USTs,
The study was conducted as part of the Baltimore Integrated Environmental
Management Project (IEMP), The Environmental Protection Agency (EPA)
initiated the project as part of its pursuit of new approaches to
environmental management and policy. The purpose of the IEMP is to use an
integrated approach to identify and assess environmental issues that concern
¦managers, to set priorities for action among these issues, and to analyze
•appropriate approaches to manage these problems.
EPA adopted the concept of integrated environmental management as a
potential solution to the shortcomings of the traditional approaches for
pollution control. The traditional approach of focusing on one pollutant or
class of pollutants within each medium at a time may result in environmental
programs and regulations characterized by inefficient use of resources.
Grounded in the concepts of risk assessment and risk management, the IEMP uses
estimates of risk, that is, the probability of adverse effects, as a common
measure for comparing and setting priorities among environmental issues that
involve different pollutants, sources, and exposure pathways and that may
affect human health, ecosystems, and resources. The need for setting
priorities is prompted by the realization in the past ten years that hundreds
of chemicals present in our environment pose some risk of causing cancer or
other adverse health effects. Comparing the risks to help set priorities
allows environmental managers to focus limited resources in a manner that will
achieve the greatest public benefit -- the greatest reduction in risk for a
given cost of control. The projects are also intended to involve all local
responsible parties and agencies in actually managing and coordinating the
projects, ensuring that issues of greatest local concern are adequately
addressed. The Baltimore IEMP was particularly successful in this regard.
The IEMP projects are divided into two phases. In the first, project
managers establish the decision-making structures of the project, identify key
environmental issues and set priorities among them. Risk is but one of the
criteria used in ranking issues; the others include analytical feasibility,
relevance to EPA, state and local program objectives, and the potential for
effective response. In the second, the IEMP studies the priority issues in
greater detail and analyses strategies for their control or resolution.
I.B. The Baltimore IEMP Study
The Baltimore.IEMP is a cooperative effort involving the governments of
the State of Maryland, the City of Baltimore, Baltimore County, Anne Arundel
County, and EPA. The Baltimore area was chosen, not because it has a
significant toxics problem, but because EPA and local officials wanted to
explore better ways to identify, assess, and manage the human health risks of
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environmental pollutants In the area. It represents the second of four,
full-scale geographic projects that EPA has initiated to date across the
country.
The Baltimore IEMP study area covers Baltimore City, which includes the
Port of Baltimore, and Baltimore and Anne Arundel counties (see Exhibit 1.1).
It extends from the Pennsylvania border on the north, to south of Washington,
DC, and borders on the Chesapeake Bay on the southeast.
The decision-making structure of the IEMP consisted of two committees,
which also represented the vehicles for State and local participation: the
Management Committee (MC) and the Technical Advisory Committee (TAC). The MC,
with members representing Baltimore City, Baltimore County, Anne Arundel
County, and the State, managed the IEMP and set its overall policy directions.
The TAC, composed of technical managers from the City of Baltimore, the two
counties, the State, as well as representatives from the Maryland Regional
Planning Council and the academic community, recommended issues to study,
advised the MC on the technical and scientific aspects of the project, and
oversaw and commented on all EPA and consultant work. EPA provided
administrative, technical, and analytical support. In phase II, special work
groups with members from both the TAC and representatives from industry,
public interest groups, government, and academia were organized around each
priority issue. They provided greater specialized expertise in examining the
issues. The Underground Storage Tank work group members are listed in
Appendix A.
Five topics were chosen for further examination in phase II of the
Baltimore IEMP. They were:
1) Multimedia metals. The goal was to develop
cost-effective techniques for lead paint removal and
dust abatement.
2) Indoor air pollution. The goal was to develop the
information necessary to support possible programs to
reduce exposures to indoor air pollution and to
¦ support the expansion of local government capability
to respond to inquiries concerning indoor air
pollution.
3) Air toxics. The goal was to estimate ambient air
concentrations of selected air toxics, analyze
associated risks, and develop control strategies for
reducing these risks.
4) Baltimore Harbor. The goal was to define current and
future uses of the Harbor's waters and identify
actions, additional research, and institutional
arrangements necessary to help environmental
decision-makers improve water quality and habitat in
the Harbor to achieve the desired uses.
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EXHIBIT 1.1: Baltimore IEMP Study Area
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5) Underground storage tanks. The goal was to develop a strategy
for identifying which groundwater resources are at greatest
potential risk if underground tanks leak.
In addition, the risk analysis conducted in Phase I on trihalomethanes, which
result from the disinfection of drinking water through chlorination, was to
provide the reference point for risk identified in the air toxics study.
I.C. Results of the Phase I Priority-Setting Process
The major task in phase I was to identify environmental issues of concern
in the study area and to set priorities among them for further study and
development of control strategies in phase II. The Baltimore IEMP set
priorities on the basis of available information, supplemented by data from a
brief ambient monitoring effort conducted by EPA. [Please see Chapter IV of
Baltimore Integrated Environmental Management Project: Phase I Report, May
1987 (hereafter referred to as the Phase I report) for a detailed account of
the priority-setting process in the first phase of the IEMP.]
The selection of Underground Storage Tanks as an issue for Phase II study
resulted from an extended environmental decision-making process by the TAC and
MG of the Baltimore IEMP. {See Phase I Report, expecially Chapters IV, VI,
and VIII.) This process is summarized below.
First, the TAC members defined the geographic boundaries of the study.
Second, the TAC identified thirty-two potentially important environmental
issues, drawing heavily upon the members' experience and knowledge of
potential problems. Third, the committee agreed on the use of three separate
measures of environmental degradation to evaluate the severity or significance
of the thirty-two issues. These measures -- human health risk, ecological
impact, and groundwater resource impact -- also would define a set of three
categories into which each of the thirty-two issues would be placed.
The TAC established the Groundwater Resources Subcommittee to formulate a
methodology for setting priorities among groundwater issues. This
Subcommittee was chaired by a representative of the Maryland Geological
Survey, and included one representative from Anne Arundel County, one from
Baltimore County, and one from EPA. The Subcommittee was asked to identify
and rank the environmental issues that posed the greatest potential impact on
groundwater resources, and to recommend no more than three issues for further
study.
The Subcommittee developed an index consisting of two components,
pollution impact and economic impact. They used the index to evaluate and
rank different sources of groundwater contamination. This ranking is shown in
Exhibit 1.2. (See Phase I Report. Chapter VI, for a complete description of
the indexing process.)
The Subcommittee eventually decided to recommend only two issues for
study in Phase II -- underground storage tanks and multimedia metals. There
was agreement among all Subcommittee members that they were among the most
important issues in each geographic region of the study area.
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EXHIBIT 1.2: Relative Ranking* of Potential Sources of Groundwater
Contamination
Underground storage tanks
Multi-media metals
Benzene
Pesticides/herbicides
Pollution from farming
Landfills
Septic tanks
Chromium in Harbor
Surface Impoundments
Acid rain
Sanitary sewers
Road salting
Feedlots
* The highest ranked issue is listed first, and the lowest is listed last.
Source: Baltimore Integrated Environmental Management Project: Phase I
Report, May 1, 1987.
USTs were thought to be particularly important by the Subcommittee
members for these reasons:
o the large number of underground storage tanks;
o the existence of known contamination incidents;
o the potential for future incidents;
o the size of the population using groundwater near the
units; and
o expected high values for the three types of cost that
could be incurred: prevention of contamination,
treatment of contamination, and provision of an
alternate water supply.
In addition, the State of Maryland's recent regulations (Code of Maryland
Regulations, 08.05.04) required testing of underground storage tanks for
leaks. This led Subcommittee members to believe that there would be
substantial increase in the number of reports of leaking USTs, and response to
these reports could strain inspection and oil pollution enforcement resources.
The TAC developed a set of secondary criteria to evaluate all of the
proposed Phase II issues and to choose those issues for further study. The
TAC recommended underground storage tanks for detailed Phase II study. The MC
approved this recommendation.
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The goals of the work plan developed for underground storage tanks were:
o Set priorities for UST inspection and enforcement in
the study area. Identify those areas where
underground storage tank leaks which are most likely
to damage groundwater resources.
o Provide a methodology, or tool, that can be readily
applied by State and local officials, both in the
study area and elsewhere, to help set priorities for
managing underground storage tanks.
The UST Phase II study would evaluate the potential risks to groundwater
resources from USTs in different parts of the study area, and thus enable
officials to target their resources more effectively. The study does not
attempt to assess human health risks from exposures. The methodology
developed can be used by other jurisdictions to set priorities for their own
UST management.
I.D. Priority-Setting for Improved UST Management
The UST screening methodology was developed to assist environmental
enforcement officials set priorities for responding to potential leaks from
USTs. The need for a priority-setting methodology in the Baltimore area is
highlighted by several factors:
1. State and/or local officials respond to and
investigate every report of an UST leak to protect
the groundwater resource and well water quality;
2. as a result of recent Maryland regulations, the
number of reports of UST leaks has increased
significantly in the last year; and
3. the personnel and resources available to enforcement
agencies for response have not increased
proportionately.
State and local officials thought that it was important to develop a
decision tool to enable them to respond to the potentially most serious UST
leaks first.
The State of Maryland regulations for controlling oil pollution from USTs
(Code of Maryland Regulations, 08.05.04) set standards for UST construction,
installation, corrosion protection, monitoring, tightness testing, and
reporting of leaks.
The regulations require tightness testing on:
1. all tanks which have been buried 15 years or longer,
or are of unknown age, by January 28, 1987, and these
must be retested every five years thereafter;
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2. all tanks which show inventory variations of more
than 1/2 of 1 percent of inventory over 30 days time;
and
3, all new tank installations.
All tanks found to be leaking (defined as more than or equal to .05
gallons/hour loss) must be reported. Of the estimated 8,500 USTs tested in
Maryland, 720 were found to be leaking. This was part of a total of 1,100 UST
leak reports in fiscal year (FY) 1987, a 78 percent increase over FY 1986 (The
Maryland Oil Disaster Containment, Clean-up and Contingency Fund 15th Annual
Report, Fiscal Year 1987, Maryland Department of Natural Resources, Water
Resources Administration, Oil Control Division).
The Maryland Waste Management Administration currently has seven
inspectors responding to leak reports in the State (an increase of one
inspector since FY 86). Baltimore County and Anne Arundel Country each has
two to three individuals who respond to possible UST contamination of drinking
water wells as a part of their jobs. The resources available to respond to
leak reports will limit the ability of State, county, and local officials to
address all leaks expeditiously, as well as perform their other permitting,
inspection, and enforcement activities.
The development of the UST screening methodology allows officials at all
levels of government to focus their inspection and response resources on those
incidents most likely to result in serious damages. This may involve focusing
State resources on the most vulnerable counties, or it may involve county and
regional governments allocating their resources to those areas at greatest
risk from leaking USTs. The methodology developed here is intended to support
these resource allocation decisions.
In this analysis, we only considered gasoline USTs, and did not attempt
to assess the potential impacts of USTs containing other chemicals. We also
did not consider USTs located on farms.
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II. THE UST SCREENING METHODOLOGY
This chapter describes the UST screening methodology developed for
ranking the vulnerability of areas to leaking USTs. First, we present an
overview of the problem. Next, we present an overview of the general approach
and the development of UST screening analysis maps using a computerized
geographic information management system. Then we present the three measures
of vulnerability -- hydrogeologic settings, UST density, and groundwater use
-- as well as alternatives considered. Next we discuss issues concerning the
identification and collection of data for quantifying these three measures of
vulnerability. We conclude the chapter with a description of how map overlays
are created.
II.A. Overview of the Problem
Groundwater in the Baltimore Region supplies agricultural, industrial,
commercial, and residential uses, and its discharge to streams and rivers is
crucial to sustaining surface water ecosystems. Most of Anne Arundel County
depends upon groundwater, and significant parts of suburban Baltimore County
depend on groundwater supplies. Contamination of groundwater, and its
prevention, has become a vital environmental issue nationwide, and is a focus
of State and local concern.
In order to evaluate the problem of groundwater vulnerability to
contamination, it is necessary to recognize that the resource is not uniformly
distributed throughout the study area. Some rocks and sediments are good
water-bearing strata, and others are not. Various physical and chemical
factors affect both the availability and the vulnerability to pollution of the
groundwater, a few of which include type of sediment (sand or clay),
mineralogy of clay minerals, and porosity and permeability of the sediment or
rock. Despite a large body of theory and research on hydrogeology, the fate
and transport of contaminants traveling in groundwater is often unclear. We
used a system called DRASTIC to evaluate the vulnerability of an hydrogeologic
system to groundwater contamination.
Sources of pollution are numerous - examples include landfills, road
salting, septic tanks, and non-point sources. We chose the number of USTs
present as a surrogate for the degree of pollution threat. Because pollution
affects people using the resource, we chose the number of persons dependent on
water wells as a surrogate for population impacts.
Our study focuses on a methodology for evaluating resource impact rather
that human health effects. We have assumed that once water is identified as
contaminated, it will either be avoided or treated.
II.B. Overview of the Approach
The Baltimore IEMP UST screening approach identifies areas vulnerable to
leaking USTs by quantifying and integrating three factors: hydrogeologic
setting, UST density, and population served by groundwater. Using a
computerized mapping system, we developed maps of an area that depict the
relative potential for impact from each factor and plotted them on transparent
materials. We then evaluated the overall vulnerability of areas within the
study area by overlaying the UST and groundwater use maps on the hydrogeologic
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setting map.
A computerized geographic information management system allows maps to be
drawn at various scales. For the Baltimore IEMP study, full-scale (1:62,500)
maps were created for use by the Maryland, Anne Arundel County, Baltimore
County, and Baltimore City governments. These maps provide environmental
officials with a useful tool for setting priorities within their
jurisdictions. In addition to the full-scale maps, a computerized system
allows report-sized maps to be produced which depict the same information as
the large maps. These maps can be reproduced easily and used by numerous
analysts and officials. Report-sized maps are provided in the map pockets at
the end of this report.
A benefit of developing separate component maps is that they can be used
and updated individually as well as together. This approach provides a great
deal of flexibility in determining which component (i.e., UST density,
groundwater usage, or hydrogeologic vulnerability) plays the predominant role
in defining the vulnerability of an area and also allows component maps to be
used for different types of analysis. In some cases, environmental officials
may be concerned with all areas exhibiting a high hydrogeologic vulnerability,
while in other cases, the density of USTs within a location may be the factor
of greatest interest. Furthermore, this approach will allow other components,
not previously considered, to be easily incorported into an analysis.
The UST screening approach focuses on potential impacts on the
groundwater resource; it does not attempt to assess human health risks from
exposures.
We considered a number of geographic information management mapping
packages for use in this study. Some required a mainframe computer due to the
software's large memory demands. However, other software packages are
available for personal computer use; we selected a commercially available
software package designed to run on a personal computer for this study.
Appendix B discusses hardware and software options more fully.
II.C. Individual Measures of Vulnerability
This section presents our methodology for evaluating our three component
measures of vulnerability: hydrogeologic setting, UST density, and population
served by groundwater. Each measure is described separately along with a
discussion of possible alternatives.
II.C.l. Hydrogeologic Settings
Many factors may affect the way in which contaminants released from an
UST move in groundwater to a well. The hydrogeology of an area is a primary
factor in determining the potential impact of leaking USTs upon wells. In
developing the screening methodology, we characterized hydrogeologic potential
for groundwater contamination as indicated by natural variability inherent in
the land.
We selected a method developed by the National Water Well Association
(NWWA) under the sponsorship of the U.S. EPA Robert S. Kerr Laboratory in Ada,
Oklahoma, called DRASTIC^-, to systematically evaluate the pollution potential
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of hydrogeologic settings within regional groundwater systems.
DRASTIC was developed with the guidance of groundwater experts
representing federal and state agencies, the Canadian government, and private
consultants to help environmental managers make screening level evaluations of
the relative vulnerability of a hydrogeologic setting to contamination.
DRASTIC allows users with a basic understanding of hydrogeology to score a
region for pollution potential. Depending upon the availability of
hydrogeologic information and the expertise of the user, it may take less than
one week to develop DRASTIC scores for one or two counties. We selected
DRASTIC for this study because its intended use is consistent with the
objectives of our UST screening analysis.
The approach quantifies the relative pollution potential of a
hydrogeologic setting by analyzing seven hydrogeologic parameters that form
the acronym, DRASTIC: Depth to groundwater, net Recharge, Aquifer media, Soil
media, Topography, Jmpact of the vadose zone, and hydraulic Conductivity. A
hydrogeologic setting is defined as a mappable unit with common hydrogeologic
characteristics and, therefore, common vulnerability to contamination. A
hydrogeologic setting in DRASTIC must be greater than 100 acres in areal
extent, as the method is considered inappropriate for smaller areas. DRASTIC
is designed to be used as a screening tool and should not used to replace
on-site inspections, or as a site assessment methodology. It provides a basis
for comparative evaluation of pollution potential of areas within a larger
region, but does not provide an absolute assessment of groundwater
vulnerability.
DRASTIC is a numerical ranking system that enables one to rank the
vulnerability of different settings through its system of weights, ranges, and
ratings for each of the seven parameters. Each parameter has a weight ranging
from 1 to 5 that designates its relative importance to the overall
vulnerability of a setting. The weights are set by DRASTIC, and should not be
changed, with 1 as the least important and 5 as the most important. For
example, Depth to Water Table is a relatively important parameter with a
weight of 5, while Topography is least important with a weight of 1, Each
DRASTIC parameter is divided into either ranges or significant media types
that have an impact on pollution potential. For example, Hydraulic
Conductivity has six ranges from 1 gallon/day/ft^ to over 2000
gallons/day/ft^. A numerical rating is then assigned to each range by the
user; the rating determines the relative importance of each range with respect
to pollution potential. The ratings are assigned based on the assessment of
the user as to which classification or range an area falls into, and the
ratings for those classifications or ranges as provided by DRASTIC. Higher
ratings indicate higher vulnerability. For example, the Soil Media range
corresponding to "gravel" receives a rating of 10, while the range
corresponding to "clay loam" receives a rating of 3. Exhibit II.1 displays
the weights, ranges, and ratings associated with each of the seven DRASTIC
parameters.
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Exhibit II.1 DRASTIC Parameter Heights, Ranges, and Ratings
Depth to Water
(feet)
Aquifer Media
Range
Rating
Range
RatinR
TVpical Rating
0-5
10
Massive Shale
1-3
2
5-10
9
Metamorphic/Igneous
2-5
3
18-30
7
Weathered Metamorphic/Igneous
3-5
4
30-50
5
Thin Bedded Sandstone,
50-75
3
Limestone, Shale Sequences
5-9
5
75-100
2
Massive Sandstone
4-9
5
100+
1
Massive Limestone
4-9
5
Sand and Gravel (Till)
4-9
8
Weight: 5
Agricultural Weight: 5
Basa:.:.
2-10
9
Karst Limestone
9-10
10
Ranges and Ratings for
Net Recharge
Weight: 3
Agricultural Weight: 3
Net Recharge (inches)
Ranges and Ratings for Soil Media
Range
Rating
Soil Media
0-2
1
2-4
3
Range
Rating
4-7
5
7-10
8
Thin or Absent
10
10+
9
Gravel
10
Sand
9
Weight: 4
Agricultural Weight: 4
Feat
8
Shrinking and/or Aggregated Clay
7
Ranges and Ratings for Topography
Topography (percent slope)
Sandy Loam
Loan
Silty Loam
Clay Loam
Muck
Range
Rating
Honshxinking and Nonaggregated Clay 1
0-2
10
Weight: 2 Agricultural Weight: 5
2-6
9
5-10
5
12-18
3
Ranges and Ratings for Imoact of Vadose Zone Media
18+
1
Range
Weight: 1
Agricultural Height: 3
Rating
Typical Rating
Ranges and Ratings for Hydraulic
Conductivity
Hydraulic Conductivity
(GFD/ft )
Range
Rating
1-300
1
100-300
2
300-700
4
700-1,000
6
1,000-2,000
8
2,000+
10
Slit/Clay
1-2 1
Shale
2-5 3
Limestone
2-7 6
Sandstone
4-8 6
Bedded Limestone, Sandstone,
Shale
4-8 6
Sand and Gravel with Significant
Silt and Clay
4-8 6
Metamorphic/Igneous
2-8 4
Sand and Gravel
6-9 8
Basalt
2-10 9
Karst Limestone
8-10 10
Weight: 5
Agricultural Weight
Weight: 3
Agricultural Weight: 2
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In order to develop a DRASTIC index for a given setting, the user
determines the proper rating for each of the seven DRASTIC parameters, and
multiplies each rating by its corresponding weight; all weighted ratings are
summed to get a score representative of the relative pollution potential:
DrDw + RrRw + ArAw + SrSw + TrTw + Irlw + CrCw - Pollution Potential
where: r - rating
w — weight
DRASTIC maps of the Baltimore study area were developed by calculating DRASTIC
indices for each of the major hydrogeologic settings in the area.
II,C.2, Selecting Zip Codes as Basic Geographic Units
The UST methodology uses zip code areas as the smallest geographic unit
for defining UST and groundwater-dependent population density distributions.
The hydrogeologic vulnerability ranking follows the natural boundaries of
hydrogeologic settings within the study area. Zip codes and hydrogeologic
settings both vary greatly in size. In areas of great variability, the size
of geographic areas may have a significant impact on the results and utility
of the screening analysis; smaller units will allow finer distinctions to be
made. The unit selected depends upon the scale of the study, the availability
of data for different units, and the costs of data collection. Generally, the
UST screening analysis will provide more detailed results with smaller units,
as finer distinctions can be drawn across the entire study. However, it may
be difficult or expensive to obtain data at a fine scale. In this study, we
chose zip codes as the basic geographic unit as a compromise between the
usefulness and feasibility of the options considered.
Zip code boundaries are useful for several reasons. First, location
information on documents such as State permits or well records often include
zip codes, making it relatively easy to obtain and collate data for the
analysis. Zip codes are relatively small, and their boundaries often follow
county boundaries making it easy to integrate zip code maps and other
geographic maps of an area. Exhibits II.2 and II.3 show the zip codes in the
study area.
Drawbacks associated with using zip code boundaries include the fact that
some hydrogeologic units are considerably smaller than a zip code area and
others are considerably larger, and zip code sizes may vary greatly. In
particular, zip code sizes tend to be larger in rural areas, where groundwater
use may be higher. This may provide less detail in the areas of most concern.
Differences in UST and well distributions within these areas cannot be readily
discerned. Wells and USTs may be evenly distributed in a zip code, or the
wells may be concentrated in one portion of a zip code, and USTs in another.
In addition, zip code boundaries may be changed by the Postal Service from
time to time, compromising the accuracy of the boundaries used as well as the
data.
One alternative would be to map the actual locations of wells and USTs in
the geographic information management system. If this were done, precise
interactions between wells and USTs could theoretically be analyzed, although
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EXHIBIT II. 2
Zip Code Map of Anne Arundel County
21090
21076
81144
20707
21113
no ia
31403'
30711
-------
EXHIBIT II.3: Zip Code Map of Baltimore County and Baltimore City
21093
21120
21111
tl 182
210 SI
"ewaCra
%
21136
21087
21093
21117
204 ^ 1 *1118
21234
21162
81133
21183
21207
21* 21111
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it might be difficult to effectively display the data on maps. The primary
drawback to such an approach would be the additional time and expense of data
collection, since it .might be .difficult to obtain latitude and longitude
information for many USTs and wells. States and regional authorities might
have adequate well inventory and location data, and UST locations could be
generated by a physical inventory, but the time and cost may prohibit such a
napping effort. It must also be considered that DRASTIC may not provide a
comparable level of detail.
II.C.3. UST Location and Density
The UST screening methodology indicates the potential for groundwater
contamination by depicting the potential interactions between USTs, wells, and
hydrogeologic settings in specific areas. The density of USTs (number of USTs
per square mile) within each zip code is one of the three basic measures of
vulnerability used.
To calculate the density of USTs within each zip code, we divided the
number of USTs by the surface area of the zip code. In cases where zip code
areas are extremely small (such as the case where a single large building has
been assigned a separate zip code), we assigned USTs to an adjacent zip code.
This sacrificed some detail, but allowed us to present UST density more easily
on maps.
After we calculated UST densities within each zip code, we divided the
zip codes within each county into three categories corresponding to high,
medium, and low UST density. This facilitated making relatively broad
distinctions concerning the potential for impacts in specific zip codes. With
the UST density distribution grouped into three categories, we can more
readily correlate UST densities with groundwater use and hydrogeologic*
settings in order to highlight areas vulnerable to leaking USTs. The approach
followed in the UST screening methodology involved creating distributions such
that equal numbers of zip codes within the counties are placed in each of the
three categories (i.e., low, medium, and high). The data were arrayed into
categories for each county individually; thus, the range of data in each
category is different for Baltimore and Anne Arundel county. After
considering some alternatives, we chose this method of displaying the data
because we thought that this array would be most useful to the jurisdictions
in the study area. Other configurations of the data are possible, such as
division of the data into high, medium and low categories on a state-wide
basis. A complete listing of the UST density used for each zip code in the
study area, as well as the groundwater-dependent population density for each
zip code, is provided in Appendix B.
II.C.4. Population Density of Groundwater Users
The screening methodology utilizes well locations and information on
groundwater use as a surrogate for the groundwater-dependent populations that
may be affected by leaking USTs. From data on the number of private and
public wells within the study area and estimates of the number of persons per
household and pumpage data, we calculated the population that is dependent on
groundwater.
For private wells, the analysis relies on Bureau of Census and State of
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Maryland estimates of the average number of persons per household in order to
determine the average number of persons (users) per private well. For public
wells, we determined the numbers of users at each well based upon State well
permit records. We summed the number of users of private and public well
water to calculate the total number of groundwater users per zip code. We
calculated the population density of groundwater users per square mile within
each zip code by dividing the estimated population served by the area of the
zip code.
In assigning users to specific zip codes, we assigned users to the zip
code in which the well is located, rather than the zip code in which the users
may be located. This ensures that the importance of the groundwater provided
by a well is fully reflected on the maps.
We assigned the distribution of groundwater use by zip code in each
county to the high, medium, or low category, following the same approach used
in calculating UST densities by zip code. Again, we placed equal numbers of
zip codes within each county in each of the three categories. If we had |
divided the zip codes into three categories across the entire study area, more
of Baltimore County's zip codes would exhibit low well use density, while Anne
Arundel County would have a higher proportion in the high category.
Alternatives to this approach again focused on using geographic
boundaries other than zip codes as the basis of the screening approach, which
is discussed in Section II.C.2.
II.D. Identifying and Collecting Data
Conducting an UST screening analysis requires the collection of
significant amounts of data on the hydrogeology, groundwater use, and number
of USTs in the region. Since the quality of data will determine the accuracy
and usefulness of the results, the identification and collection of data play
major roles in the application of this methodology.
The availability of hydrogeologic data will vary across states and to
some extent within states. Many states have geologic surveys that map the
groundwater resources, mineral resources, and geology of portions or all of
the state. These sources provide detailed information for development of
DRASTIC ratings. U.S. Geological Survey and state geological studies and
reports provide fundamental information needed in developing a DRASTIC rating.
If hydrogeologic reports specific to a study area do not exist, the DRASTIC
report provides general ratings for over one hundred hydrogeologic settings
across the United States which can be applied to the appropriate areas.
Because these ratings are quite general, they should be evaluated by
experienced professional geologists or hydrogeologists familiar with the
specific features of the area being studied.
While a number of data sources can be identified providing both well and
UST information, this information will not always be of high quality, and the
data may not exist in terms of zip codes. Major sources of available data
include the U.S. Census Bureau, and other Federal, State and local government
agencies. In some cases, data can be purchased from firms that specialize in
collecting and categorizing census data and household and business statistics.
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The Bureau of the Census estimates the number of households served by
public and private groundwater wells by Standard Metropolitan Statistical
Areas (SMSAs) and by census tracts. We found in this study that these data do
not necessarily provide sufficient accuracy because of the large variation in
the size of the census tracts in the Baltimore study area. (Census tracts
exhibited much more size variation than zip codes.) The data available from
State and local government agencies (such as the state environmental agency or
the state public works department) may have more detailed and more
geographically specific UST and well information. However, many State and
local governments do not have permitting and notification data computerized.
Data for this study on the number of wells were obtained from well permit
records that had been compiled by the State Department of Health and Mental
Hygiene. These data required much additional manipulation to be put into a
useable format.
Data collection for USTs was relatively straightforward due to the
availability of data from the EPA Region III UST Notification Survey. The
Hazardous and Solid Waste Amendments (HSWA) of 1984 required States to collect
this UST data, and most states have complied. The data were collected by EPA
Regional Offices for those states like Maryland, which did not participate.
EPA Region III is now providing the data to Maryland. The only difficulty was
that the data were formatted by a proprietary software package which was not
initially available to the project. Once arrangements were made for
reformatting the UST data, it took about two days to sort the data by zip code
and to calculate UST densities.
The Bureau of the Census also collects information on the number of
business establishments by Standard Industrial Classification (SIC) code
located in each SMSA and in each census tract. Service stations have a unique
four-digit SIC code, and therefore can be identified using Census data. By
making an assumption regarding the average number of USTs at service stations
in the study area, it is possible to estimate the number of service station
USTs in a region using available Census data. However, if UST location
information is estimated using Census data, the user must keep in mind that
business establishments other than service stations may maintain USTs (e.g.,
rental car agencies, airports, delivery agencies, and auto dealerships). In
considering other business establishments, an estimate must be made regarding
the average number of USTs at each type of establishment and the proportion of
all establishments that actually have USTs.
Another major consideration concerns the format and quality of the data.
The data should be in a format that can be easily integrated onto the
computerized mapping system. Often, data compiled by state agencies will be
stored on mainframe computers, and will be available on tape or as computer
printouts. The large number of wells in many parts of the country, such as in
the Baltimore study, area, make it necessary to obtain the information on
computer tape. In many cases, it will be necessary to arrange to have the
tape outputs transferred onto a floppy disk in order to use the data on a
personal computer system.
In most cases, the user will not receive the data already aggregated into
the geographic units being analyzed in the study. It may be necessary to use a
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statistical package to sort the information by this unit (e.g. , zip code) in
order to tabulate the number of USTs or wells in each unit within the study
area.
II.E. UST Screening Analysis Map Overlays
The UST screening methodology uses a computerized mapping system to
develop maps that display the density of groundwater use, UST density, and
hydrogeologic vulnerability within the study area. By producing these maps on
mylar and overlaying them upon the county base map, potential interactions
between groundwater use patterns and the presence of USTs in areas with
differing hydrogeologic vulnerability can be observed.
In integrating the measures of vulnerability, the separate maps must
first be developed. In this study, we used a personal computer-based data
management and geographic information system to generate and display relevant
boundaries and to visually display the relative ranking of the various
measures of vulnerability. Appendix C outlines the basic hardware and
software requirements for a personal or desktop computer management system.
It provides an overview of possible systems that are available at relatively
low costs, but does not provide an exhaustive list of system possibilities or
recommend a particular system. The best system for any particular agency
depends on the resources available, including any currently owned computer
resources, and the priority the agency wishes to attribute to an UST or
groundwater vulnerability screening analysis.
We used purchased files displaying zip code boundaries within the study
area to develop the UST and groundwater use density maps. After generating
distributions of high, medium, and low for each county, we assigned a value to
each zip code to enable the computer system to draw the proper patterns. For
example, the high-density areas have the most lines per inch, while the low-
density areas have the least. Zip codes for which data were unavailable were
left blank. The UST density map lines run from northeast to southwest, while
the groundwater use map lines run from northwest to southeast. When
overlayed, the density of cross-hatching, together with the underlying DRASTIC
rating, indicates the vulnerability of the zip code. Alternatively, each part
of the distribution can be shaded using different patterns, depending upon the
needs of the user.
Given access to digitizing software, the computer management system can
be used to define new boundaries for the analysis. Digitizing software allows
geographic boundaries to be entered into a computer data base as strings of
coordinates. In this study, we used a digitizer to computerize the
hydrogeologic setting boundaries of Anne Arundel and Baltimore Counties and
Baltimore City, which were developed for quantifying hydrogeologic pollution
potential. One of the benefits of using digitizing equipment is the
capability it provides for defining new geographic units within which analysis
can be conducted.
One of the primary benefits of using a computerized data base and
geographic analysis system is that maps can be printed at various scales.
With the proper hardware, full-scale maps (e.g., 1:62,500 scale) can be
printed for use by environmental officials. Large maps provide officials with
benefits associated with their scale, such as allowing individual locations of
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greater concern to be indicated on the map. In addition, full-scale maps can
be overlayed onto full-scale county maps that highlight roads and other
important cultural features, allowing the user to consider other potential
impacts with the screening analysis.
The computer-based system also enables each individual vulnerability
measure to be updated, revised, and printed out separately at little
additional cost. Once the system has been developed, the costs associated
with printing additional maps will be based primarily on the costs of the
materials and the time to print them.
Once the individual maps have been created, the high to low vulnerability
areas within the region can be identified. The relative importance of each of
the three maps on this final estimate of vulnerability will depend upon the
user's orientation. If the primary issue involves the identification of
problem USTs in regions with a low UST density and high groundwater use, the
user may wish to focus enforcement resources on these few USTs; given high
groundwater use patterns, the potential for a leaking UST to affect a well
would be high. Conversely, in areas with a high density of USTs and a low
density of well use, enforcement authorities may not be as concerned given the
lower likelihood that a single UST will actually affect a well. Clearly,
areas with high well and UST densities will pose the greatest potential
problems in all but the least hydrogeologically vulnerable areas.
If an agency is primarily concerned with protecting wells, it may wish to
highlight wells for inspection in areas with a high population density of
groundwater users and a high density of USTs, since they will exhibit a high
potential for contamination. Additionally, the overall pollution potential of
the aquifer as defined with DRASTIC will greatly influence groundwater
vulnerability. The extent to which officials evaluate the significance of
wells and USTs located in regions of high groundwater vulnerability versus
those located in regions of low groundwater vulnerability will vary with the
priorities of the user.
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III. APPLICATION OF THE UST SCREENING METHODOLOGY TO THE BALTIMORE IEMP STUDY
AREA AND GUIDANCE FOR ITS APPLICATION ELSEWHERE
In this chapter, the UST screening methodology is applied to the
Baltimore IEMP study area. First is an overview of the geography, climate,
and hydrogeology of the area. Next, we describe how we assessed the potential
for groundwater pollution by applying DRASTIC to create pollution potential
maps of Baltimore County (including Baltimore City) and Anne Arundel County. _
We then discuss data collection for USTs and populations dependent on
groundwater. In the final section, we discuss integration of individual map
overlays. For each section, we provide resource estimates (equipment,
personnel, time, and costs) and discuss potential problems that may confront
future users of this screening methodology.
Ill.A. Overview of the Baltimore Study Area
III.A.1. Geography
The Baltimore IEMP study area covers Baltimore County, Anne Arundel
County, and Baltimore City (see Exhibit 1.1, page 3). Baltimore City, with a
population of about 700,000 people, is located in the center of the study
area.
Anne Arundel County includes an area of 417 square miles of land and 41
square miles of water, extending from the City of Baltimore in the north, to
within 15 miles of Washington, D.C. in the south,^ Annapolis, the capital of
Maryland, is located in the east central part of the county. Major rivers in
Anne Arundel include the Patuxent River (forming the County's western
boundary) and the Patapsco (forming parts of its northern boundary). The
county also borders on the Chesapeake Bay to the east.
Baltimore County has a land area of 610 square miles, extending from
Baltimore City in the south to the Pennsylvania border in the north. The
county borders to the southeast on the Chesapeake Bay, the nation's largest
estuary.
Ill.A.2. Climate
The climate in the Baltimore IEMP study area is humid and temperate with
a mean annual temperature of 56°F and an average annual precipitation of about
44 inches,^ The net recharge to aquifers in the region represents
approximately 25% of the average precipitation, or about 8-11 inches per year.
Ill.A.3. Hydrogeology
The study area is characterized by two major physiographic provinces: the
Piedmont and the Atlantic Coastal Plain provinces. The dividing line between
these two provinces, known as the Fall Line, divides Baltimore in half,
running from the southwest corner of the city through its northeast corner.
Anne Arundel County lies entirely within the Atlantic Coastal Plain province,
and Baltimore County lies in both provinces.
The Piedmont province is composed of crystalline rocks of Precambrian or
early Paleozoic age, chiefly schist, gneiss, phyllite, gabbro, quartzite, and
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marble.^ A mantle of weathered material, known as regolith or saprolite,
overlies the crystalline rock. The saprolite serves as a storage zone for the
water in the crystalline rock, which supplies groundwater primarily through
fractures and joints.
The Atlantic Coastal Plain region underlying Anne Arundel and parts of
Baltimore County is composed of a wedge-shaped mass of unconsolidated
sediments of Cretaceous, Tertiary, and Quaternary age, approximately 50 feet
thick in the northwestern part of the Anne Arundel County and increasing to
about 2,000 feet thick in the southeastern part of the county.^ This region
contains some of the most productive aquifers in the state.
III.B. Development of Groundwater Pollution Potential Maps
Groundwater pollution potential maps are the key element in the screening
methodology. These maps portray the variability of groundwater pollution
potential of the water table aquifer as it exists on the landscape.
We applied the DRASTIC approach for mapping hydrogeologic vulnerability
to both Anne Arundel and Baltimore Counties (Baltimore City is included in the
Baltimore County DRASTIC map). The key element of DRASTIC centers on
identifying " and defining hydrogeologic settings. As described in Chapter
II.C.l, DRASTIC assigns ratings to seven hydrogeologic parameters for each
setting, and weights them according to their relative contribution to
pollution potential.
A definition of each hydrogeologic setting and a description of the
DRASTIC rating assigned to each of the seven parameters in both counties
follows below. To illustrate the DRASTIC approach, base maps for each separate
parameter, along with the final DRASTIC pollution potential map of each county
are shown.
III.B.l. Hydrogeologic Settings in Anne Arundel County
Anne Arundel County, located in the Atlantic Coastal Plain physiographic
province, is underlain by unconsolidated coastal plain sediments with a
thickness of 50 feet in the northwest section of the county, increasing to
about 2,000 feet in the southeastern part of the county. The sediments
contain three major aquifer units: the Potomac Group, Magothy, and Aquia
formations, which dip gently to the southeast at a rate of 30-80 ft/mile.^
Altogether, 12 geologic formations are shown on the Anne Arundel County
Geologic Map;^ however, some units have similar hydrogeologic characteristics
and were combined into a single hydrogeologic setting for this study. The
unconsolidated deposits are stratifie.d layers of sand, gravel, silt, and clay;
the sand and gravel strata constitute the major water-bearing rocks.®
We defined and mapped seven hydrogeologic settings comprised of
unconsolidated sediments in Anne Arundel County. (See Exhibit III.l, Units A,
B, D, E, F, G, H.) We produced this exhibit, and the other maps presented in
this chapter, by editing and printing the data files created when we digitized
the hydrogeologic units in each county. An additional sedimentary unit is
found in Baltimore (Unit C). For convenience, all eight are defined in the
following paragraphs. Each setting is named after the most areally extensive
21 -
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EXHIBIT HI-1: Hydrogeologic Settings in Anne Arundel County
jmt macs, ax tm
wtmmiasic
sxim
fasumnt Foanatlczt
Arundel Clay
Potcme Gtwp
Calvwrt Faremtion
tfmauth Foaimtian
Marlboro Clay
Aquia Fomatltxi
164-175
102-113
160
116-131
13?
109
131-145
LEGEND FOR SETTINGS
A Patuxent Formation
B Arundel Clay
D Potomac Group
E Calvert Formation
F Monmouth Formation
G Marlboro Clay
H Aquia Formation
22
-------
geologic unit which occurs within its boundary, and is identified with a
letter code.
Patuxent Setting (A): Named for the Patuxent formation in Baltimore
County, where it is a prolific source of groundwater, this setting consists
predominantly of sand and gravel, with subordinate silt and clay. In
Baltimore County/City it includes: Patuxent formation (sand facies); upland
gravels; alluvial terrace gravels; artificial fill. In Anne Arundel County it
includes: Brandywine formation; Patuxent River Terraces; Terrace Deposits;
artificial fill.
Arundel Clav Setting (B"): . Named for the Arundel Clay in Baltimore
County, this setting includes the clay facies of each of the following
formations: Arundel formation, Patuxent formation, Patapsco Formation and
Talbot formation in Baltimore County, and Potomac Groups silt-clay facies in
Anne Arundel County. The formations are made up of clay-silt and subordinate
fine to medium-grained muddy sand; the silt-clay materials are generally
massive and thick-bedded, compact and tough.
Patapsco Setting (Q: This setting consists mostly of well-bedded
medium- to fine-grained sands. This setting includes the sand facies of the
Patapsco formation, the Talbot formation and the alluvium. It occurs in
Baltimore County/City but not, in Anne Arundel County.
Potomac Setting (D*)The sand-gravel facies component of the Potomac
group is a productive aquifer. It is characterized by interbedded quartz
sand, pebbly sand, gravel, and subordinate silt-clay; the sand is fine to
coarse-grained, poorly-sorted to well-sorted, and clean to very muddy. This
setting serves as a major source of drinking water in Anne Arundel County.
Calvert Setting CE"): Named for the Calvert formation, the setting
combines the Calvert, Nanjemoy and Talbot formations because of their
hydrogeologic similarities, which are generally characterized as clayey sands.
The Calvert formation consists chiefly of fine-grained sand, silt, and
diatomaceous silt; the Nanjemoy consists of glauconitic fine to medium-grained
sand, silt, and silty clay. The Talbot formation is a very fine to
fine-grained sand aquifer.
Monmouth Setting fF'): In this setting two similar formations, the
Monmouth and Matawan formations, are combined. The setting consists of very
fine to fine-grained sand which is poorly to moderately well-sorted with
micaceous clayey silt. This setting is generally not considered a productive
aquifer.
Marlboro Clav Setting (G): The Marlboro clay occurs in three relatively
small areas within Anne Arundel County, and is characterized as a plastic
clay. Despite is small areal extent, it has been included as a separate
setting for this study in order to illustrate the vulnerability associated
with a true clay unit.
Aquia Setting CHI : This setting groups two highly productive aquifer
formations, the Magothy and Aquia formations. The Aquia formation supplies
groundwater for most of the area in Anne Arundel County south of Annapolis,
outcropping extensively in the central portion of the county. The Aquia
23 -
-------
formation consists of glauconitic sand, and clean to moderately-clayey and
calcareous sandstone; the sands are well-sorted with medium grained sands
dominating, but fine and coarse-grained sands also appearing in places. The
sands of the Magothy formation form a productive aquifer serving as the
primary source of groundwater for the City of Annapolis. The aquifer is
characterized by fine to coarse-grained sand interstratified with silt and
clay, with subordinate pebbly sand or gravel.
III.B.2. DRASTIC Parameters for Anne Arundel County
This section describes the seven DRASTIC parameters and the ratings we
assigned to them for each of the hydrogeologic settings in Anne Arundel
County. Section III.B.5 describes the parameters and their ratings for
Baltimore County. A separate parameter map accompanies each discussion in
order to display the variability of each parameter across the county. The
letter associated with the acronym "DRASTIC" follows each parameter name in
parenthesis for additional clarity. We assigned these ratings based on the
assessments of a senior geologist familiar with the hydrogeology of Maryland,
a mid-level environmental engineer, and a junior geologist.
Depth to Groundwater (D): As described earlier, the Coastal sediments in
Anne Arundel County form a multi-layered system of aquifers, with the lowest
aquifer units outcropping further north in the county. Although wells may
often penetrate the surficial aquifer in order to pump from one of the lower,
confined units, we assumed that the pollution potential of a geographic
location will be based upon the characteristics of the surficial aquifer.
Although well users may not always drink from the aquifer outcropping in their
area, contamination occurring in the surficial aquifer could contaminate a
drinking water supply through a well bore-hole or by a pinching out of the
aquitard between members. Depth to the water table varied in the county from
a minimum of about 5 feet to a maximum of about 50 feet. The DRASTIC rating
thus varied from 5 to 9 within the county (Exhibit III.2)
Net Recharge (R): Of the approximately 44 inches of annual precipitation
in Anne Arundel County, about one quarter represents groundwater recharge.^
This value was applied to Anne Arundel County based upon review by members of
the Maryland Geologic Survey. A revised DRASTIC rating of 9 was assigned to
Anne Arundel County, corresponding to the value for greater than 10" per year
net recharge (Exhibit III.3).
Aquifer Media (A): The aquifer media in Anne Arundel County are
characterized by unconsolidated sediments, ranging from sand and gravel to
silty clays. Because a number of the various unconsolidated sediments found
in Anne Arundel County are not represented in the DRASTIC system, a revised
table of Aquifer Media ratings has been prepared for use in this study
(personal communication, E.T. Cleaves, Maryland Geological Survey).
- 24 -
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EXHIBIT III.2: Depth to Groundwater
in Anne Arundel
County
ME AH9CEL COKIY
DEPTH TO 3CUCWAIER: Height
H&3KKSXJ3GIC
SHTUG
cue
MICE
(feet)
BAXSEKS)
Patuass: Fonmtloti
A
5-30
9,7*
35-*5
AcmU. Ojtf
B
5-30
9,7*
35-45
Potxnac Group
D
10-30
7
35
Ciivtrt FoncBtlm
E
10-50
7,5*
25-35
Hin'uffh.
P
10-30
7
35
ffaxlboro day
G
5-10
9
*5
Aquia Fozaetlcrx
H
10-50
7,5*
25-35
« Two casing* arm aaalpmd twnimi depth to groundwater
mrlms signl ftr«tXy across the fct5"dro»eolcsLc smtins-
LEGEND
Rating Depth to Groundwater
9 5-10 feet
7 10-30 feet
5 30-50 feet
- 25 -
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EXHIBIT III.3: Net Recharge In Acme Arundel County
ANNE JffiUOEL COUNTY
NET RECHARGE; Weight - 4
HffiBXBCLOSIC
SETTHC
RAXDC SCORE
ALL UNITS
LEGEND
Rating Net Recharge
9 10+ inches/year
- 26 -
-------
Aquifer Media in the Coastal Plain Settings
Unconsolidated
Sediment Type Rating
Gravel 9
Sand 6
Clayey/silty sand 4
Silt 3
Clay/silt 2
Clay 1
This type of fine tuning is recommended by the DRASTIC authors in
situations where local conditions differ from these described in the DRASTIC
report. The scores for each setting are depicted in Exhibit III.4.
Soil Media (S1): Values for this factor are based on the Soil Survey of
Anne Arundel county (1973).10 xhe settings with silty clay subsoil were
assigned a DRASTIC rating of 3. Silty clay loam subsoils were assigned a
rating of 4 and the settings with sandy loam were given a rating of 6 (Exhibit
III.5). The table below describes the soil associations and textures
corresponding to each setting in Anne Arundel County.
Soil Media in Anne Arundel County
Setting Soil Association (and Texture) Rating
A Beltsville-Chillum-Sassafras: (silt 4
(loam to sandy clay loam subsoil)
B Lenoir-Beltsville: (silt loam subsoil) 4
Mattapox-Barclay-Othello: (silty
clay loam subsoil)
C Sassafras-Woodstown-Fallingston: 3
(sandy clay loam)
Mattapox-Barclay-Othello: (silt-
silty clay)
D Evesboro-Rumford-Sassafras: (sandy 6
loam)
E Marr-Westphalia-Sassafras: (sandy 6
loam subsoil)
F,H Monmouth-Collington: (sandy clay 3
loam subsoil)
Tonography (T): The topography of Anne Arundel County is relatively flat
and uniform except along the coves and embayments along Chesapeake Bay, and
where tributaries join major streams. Most of the county has land surface
slope of about 2 to 6 percent corresponding to a DRASTIC rating of 9. Part of
the county, however, has land surface slopes of 6 to 12 percent, corresponding
to a DRASTIC rating of 5 (Exhibit III.6).
Impact of the Vadose Zone (I): The Impact of the Vadose Zone category
parallels the Aquifer Media category, as many of the materials forming the
saturated zone of the aquifer also compose major portions of the unsaturated
zone. Again, ratings for the surficial aquifer in each area were developed.
- 27 -
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EXHIBIT III.4: Aquifer Media in Anne Arundel County
8
ANNE AJ5JNDH. OXHTY
AQUIFER MEDIA: Weight - 3
HHHX2EL0GIC
SETTDC
axe
Aquifer
Media
RATHE SGCRE
Psttunent Formation
Arundel Clay
Potonac Groins
Calvert Formation
ffcroouth Fonstlczi
Marlboro Clay
Aqula Fonmtian
A Sandl & Gravel
B Clay/j Lit
0 Sand & Grawl
E Clayey sand
F Flue sand
G Clay
S Sand
2*
6
a
12
13
3
18
LEGEND
8
Rating Aquifer Media
8 Sand & gravel
7 Sand & gravel
6 Sand
5 Fine sand
4 Clayey sand
2 Clay/silt
1 Clay
V
- 28 -
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EXHIBIT III.5: Soil Media in Anne Arundel County
6
ah® jusatm. comt
SOU: Usight - 2
BSSCGECLOCIC
SETTSC
occe
Soil
Typ«
&
RATDC SOCRE
Pacuxera: Fonmtim A Slier Lam * 8
Acuidel day 8 Sllty Loam * 8
ftxoac Gcof) D Saidy Loam 6 12
Calvert Fonnultzi S Sandy Loam 6 12
HxBBuch Format 1m F Clajr Loan 3 6
Marlboro Clay C Silt? Loam 4 8
Aquia Format 1m B day Loan 3 6
LEGEND
Ratinq Soil Type
6
4
3
Sandy loam
Silty loam
Clay loam
6
29 -
-------
EXHIBIT III.6: Topography in Anne Arundel County
ANNE mXB. CECHTY
KKCRAPHY: Height - 1
BSXraijQGIC
SEnnc
OCXS
RANGE
(X Slope)
KAIBC(S)
SOME
Paaocenc Format ion
A
0-6
10,9*
9-10
Arundel CLtf
B
0-6
10,9*
9-10
Patinas Grtxp
0
2-6
9
9
Calvert Foasscijan
E
0-2, 6-12
10,5*
5-10
Hamcnth Fonmtion
?
2-6
9
9
Marlboro Clay
G
2-6
9
9
Aquia Founafim
a
2-12
9,5*
5-9
* An ratings in assigned b
eeause the X
slope varies
algniflrantly across the hydxuROologlc setting.
10
10
LEGEND
Ratinq % Slope
10
9
5
0
2
6
2
6
12
- 30 -
-------
Ratings for the Coastal Plain deposits may be expected to vary from 1 (clay)
to 9 (sand and gravel). The rating for each setting is shown on Exhibit
III.7.
Hydraulic Conductivity (O: The hydraulic conductivity of each formation
in Anne Arundel County was estimated using the DRASTIC report or data from
Mack.H The ratings for the Coastal Plain unconsolidated settings ranged from
a low of 1 for clay to a high of 4 for sands (Exhibit III.8).
III.B.3. Map of Groundwater Pollution Potential in Anne Arundel County
A DRASTIC score for each hydrogeologic setting in Anne Arundel County was
compiled from the seven DRASTIC parameters (Exhibit III.9). This exhibit
provides both the individual scores for each parameter and the overall DRASTIC
rating for each setting. These scores, combined with the map of hydrogeologic
settings, create a map of "Groundwater Pollution Potential, Anne Arundel
County" (this map has been placed in the Anne Arundel map overlay pocket at
the end of the report along with the UST and well use maps). The setting with
the highest groundwater pollution potential is the Patuxent setting with a
score of 164-175; the lowest pollution potential is in the Arundel and
Marlboro Clay settings with scores of 102-113 and 109 respectively.
III.B.4. Hydrogeologic Settings of Baltimore County (and Baltimore City)
The hydrogeology of Baltimore County is more varied than Anne Arundel
County, as both crystalline rocks and unconsolidated sediments are present.
Baltimore County straddles two physiographic provinces: the Piedmont Province
and the Atlantic Coastal Plain Province. The geologic map of Baltimore County
maps over 25 separate geologic units within the region. ^ Many of these
units, although of geologic consequence, are similar in hydrogeologic
characteristics and for purposes of this study have been lumped together.
Altogether nine hydrogeologic settings have been mapped in Baltimore
County (Exhibit III.10). Three hydrogeologic settings consisting of
unconsolidated sediments occur in Baltimore County: Patuxent, Arundel Clay,
and Patapsco (which were described above for Anne Arundel County). The other
six hydrogeologic settings are crystalline rock settings, which are numbered
with Roman numerals in order to distinguish them from the sedimentary units.
Cockevsville Marble Setting (I): This setting includes the Cockeysville
Marble formation and the Hydes Marble member. The Cockeysville Marble is a
crystalline marble ranging from coarsely crystalline calcite to a fine-grained
dense dolomite. It is the best source of groundwater in the Piedmont part of
the county.
Mount Washington Amphibolite Setting (11): This setting includes the
Mount Washington Amphibolite, the Holofield Layered Ultra-Mafite, the
Sweathouse Amphibolite member of the Oella formation, the Raspeburg
Amphibolite, the Bradshaw Amphibolite, the Perry Hall Gneiss, and serpentinite
at Bare Hills.
Baltimore Gneiss Setting (III'): This setting includes the Baltimore
Gneiss, the Setters Quartzite, the Franklinville Gneiss, the Slaughterhouse
Gneiss, the Woodstock Granite, the Ellicott City Granite, the Sykesville
- 31 -
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EXHIBIT III.7:
Impact of the Vadose Zone in Anne Arundel County
AWE MM2L cowry
amcr at the vjdose zcks; - s
HBECGHMSSG
SE3TUC
Pacunent Fosnatlm
Arxrdcl Clay
Potnsnc Gc«f>
Cilvert PomKlai
MbraouEh Foraatioo
Mirlfaoro Clay
Aqula Fozmation
LEGEND
Rating
4
1
CCDE
A
B
D
I
P
0
H
Vadose Zone
MsdU HAHJGfS) SOCKS
Sand L gxstvel
Clay
Gawelly ml
CLaycy Kmd
SmxI
CUjr
Sand
Vadose Zone Media
Sand S gravel
Gravel1y sand
Sand
Clayey sand
Clay
- 32 -
-------
EXHIBIT III.8: Hydraulic Conductivity in Anne Arundel County
m(Ł AKIH5EL CONry
BHRMiLIC axwcnvrcf: Might - 3
HHSDGEOjCEIC
SUHCE
SETTUC
axe
(gpd/ftA2)
tWXBC(S)
SCORE
htonc Fsasscian
A
300-700
*
12
Anndal Chef
8
1-100
1
3
Pocrzmc Qsqup
0
300-700
*
12
Cilvert Foacoclm
S
100-300
2
6
Mrmnirh Fonmrfm
F
100-300
2
6
Marlboro dxy
C
1-100
1
3
Aquls FoaKLm
H
100-300
2
6
LEGEND
Rating Hydraulic Conductivity
300 - 700 gpd/ftŁ
100 - 300 gpd/ftj
1 - 100 gpd/ft*
V
- 33 -
-------
EXHIBIT III.9 DRASTIC SCORES FOR SEDIMENTARY ROCK SETTINGS
Setting
A. Fatuxent
B. Arundel
C. Patapaco
D. Potomac
E. Calvert
P, Monmouth
G. Marlboro Clay
B. Aquia
Total
Score
162-175
ISO
Depth to
Groundwater
35-45
102-113 35-45
146-157 35-45
35
116-131 25
137 32
109 45
131, 145 25
Not
Becharsa
36
36
36
36
36
36
36
36
Aquifer
Jfeflla
24
6
18
21
12
15
3
18
Soil
Media
B
6
12
12
6
8
6
Topography
7-10
9-10
9-10
9
5-10
9
9
5-9
Impact oŁ
Yadose Zona
40
30
35
20
30
5
35
Hydraulic
Conduct IvitY
12
12
12
6
6
3
6
-------
EXHIBIT III.10: Hydrogeologic Settings in Baltimore County
111
IV
III
III
&
LEGEND FOR SETTINGS
I Cockeysville Marble
II Mount Washington Amphibolite
III Baltimore Gneiss
IV Loch Raven Schist
V Serpentinite
VI Prettyboy Schist
A Patuxent Formation
B Arundel Clay
C Patapsco Formation
IV
III
w>«
.III
0
BALTIMORE QQKTY/CITY
KYHUGEOLiOGIC
setting
Batttasra &ieiss
Loch Omen Schist
Serpmtinfte
Pm tyfcoy Schist
PatxMnt Formation
AnidtrcUy
Pstjpsoo Formtlin
OCDE
TOM.
SOCK
I
147
11
TO
III
107-121
IV
1CB-116
V
103
VI
107-117
A
144-175
B
102-113
C
146-157
III
- 35 -
-------
formation (Gneiss member), and the James Run formation (Relay Gneiss member
and Carroll Gneiss member). The unit includes rocks ranging from heavily
banded granitoid biotite gneiss to a thinly banded "ribbon" gneiss to a fine
to medium-grained biotite muscovite-plagioclase quartz schist to a
fine-grained felspathic gneiss. These units are not as productive a source of
groundwater as either the marble or the Loch Raven Schist.
Loch Raven Schist Setting (IV): This setting includes the Loch Raven
Schist and the Oella formation. These formations are located in the central
portion of Baltimore County. They are relatively poor sources of groundwater,
with uniformly low transmissivities. Schists of this setting are medium- to
coarse-grained.
Serpentinite Setting (V): This setting comprises a rock called
"serpentinite". The rock occurs in two main masses in Baltimore County, one
at Soldiers Delight and the other at Bare Hills. The setting is unusual
because of its lack of saprolite, thin soil cover, and low permeability. Only
the Soldiers Delight area on the western side of the County is areally large
enough to be evaluated with DRASTIC.
Prettvbov Schist Setting (VI): In this formation we have lumped together
several similar formations: the Prettyboy Schist, the Sykesville formations,
the Pleasant Grove Schist, and the Piney Run formation. Schists of this group
are fine grained, low metamorphic grade minerals and have low water renovation
characteristics.
III.B.5. DRASTIC Parameters for Baltimore County
Depth to Groundwater (D): Exhibit III.11 shows the distribution of
groundwater depths in Baltimore County. As can be seen on the map, the
DRASTIC rating ranges from 5 to 9, corresponding to groundwater table depths
from 5 to 50 feet.
Net Recharge (R): The sediments outcropping in Baltimore County are
assigned the same value of 10+ inches per year of net recharge as those units
in Anne Arundel County (resulting in a DRASTIC rating of 10). Net recharge in
the Piedmont sections of the county has been estimated at 8-10 inches per
year.This corresponds to a DRASTIC rating of 8. The distribution of
DRASTIC ratings for net recharge is illustrated in Exhibit III.12. This is an
arbitrary decision based on contrasting information available from groundwater
reports about the area.
Aquifer Media (A): Baltimore County is characterized by both crystalline
rock and sedimentary hydrogeologic settings. The sediment settings consist of
—sand and gravel aquifers, with varying amounts of interspersed silt and clay.
The Piedmont settings consist primarily of metamorphic and igneous rock
overlain by weathered rock and saprolite. Groundwater is available through
fractures within the crystalline bedrock, while the saprolite serves as a
storage zone. Because the DRASTIC ratings for Aquifer Media do not adequately
represent the hydrogeologic settings in Anne Arundel and Baltimore Counties, a
revised table has been prepared for this study. The revised ratings for the
unconsolidated formations are shown on page 27; the crystalline rock ratings
are given below.
36 -
-------
EXHIBIT III.11; Depth to Groundwater in Baltimore County
smjikke ourrr/cm
mm TO GRCUNOtMBt; Uel^it - 5
fflnUGEOjOGlC
SETTING
CockwsMlle Karble
Nt Utah AifiilMlte
Mttagre freiss
lod> Raven Schist
Serpentinite
Prett>fcoy Schist
PUmBt Fcrratfcn
Arundel Kay
PflttpiCO Fo notion
MNGE
GCDE
(feet)
RATIWKS)
SORE
I
10-30
7
S
II
30-58
5
25
tu
10-50
7.V
25-35
IV
10-50
7.5*
25-35
V
30-50
5
25
w
10-50
7,5*
25-$
A
5-30
9,7*
36-45
B
5-30
9,7*
9,7*
35-45
C
5-30
35-45
* Tm ratfngt an assiywd because deprt to grauxl«tcr
wrf« •iTriffeaxly acpos* the tvfregeolcgic settirs.
v>
&
LEGENO
Rating Depth to Groundwater
9
7
S - 10 feet
10 - 30 feet
30 - 50 feet
37
-------
EXHIBIT III.12: Net Recharge in Baltimore County
BALTIMORE QDUfTT/CITT
NErRECHARGE: Ueitflt = 4
HYDROGEOLOGIC
SETTING
RANGE
{ir/yr>
RATING
SCORE
Codceysvi I le Marble
I
8-10
8
32
Ht Uash Mffiibolite
II
8-10
a
32
Baltimore Qreiss
III
8-10
8
32
Loch Rbmti Schist
IV
8-10
8
32
Serpent inite
V
8-10
8
32
Prettybcy Schist
VI
8-10
8
32
Patueent Formation
A
10»
9
36
ArutM Clay
B
10*
9
36
PvUpaco Formation
C
10»
9
36
a
LEGENO
Eating Net Recharge
9 10+ inches/year
8 8-10 inches/year
38
-------
I
AQUIFER MEDIA IN THE PIEDMONT PROVINCE OF BALTIMORE COUNTY
Setting
I. Cockeysville
II. Mt. Washington
III. Baltimore Gneiss
IV. Loch Raven Schist
V. Serpentinite
VI. Prettyboy Schist
Crystalline Rock Type
Saprolite, silty sand to sand
Amphibolite: saprolite,
clay to silty clay, including various
amphibolites and mafic gneiss
Saprolite, silty
clayey sands
Saprolite and
medium to coarse-grained crystalline
Fractured crystalline rock
Saprolite, clayey silt,
and fine-grained schists
Rating
6
2
4
4
1
3
Exhibit III.13 illustrates the aquifer media ratings of the hydrogeologic
settings within the county.
Soil Media (S'): Ratings for soil media are based on the Soil Survey of
Baltimore county (1976).The soil in Baltimore county ranges from heavy
clay found in the sediment areas (DRASTIC rating of 3) to aggregated clay with
a DRASTIC rating of 7 found in the crystalline rock areas. In general, the
soils found in Baltimore county are highly varied, as can be seen by examining
Exhibit III.14, which illustrates the DRASTIC Soil Media Map for Baltimore
County. The hydrogeologic settings and their associated soil types are given
below.
SOIL MEDIA IN THE PIEDMONT PROVINCE OF BALTIMORE COUNTY
Setting Soil Association and Textures Rating
I. Cockeysville Marble Baltimore-Conestoga-Hagerstown 3
(clay loam to clay)
II. Mt. Washington Chrome-Watcheeng 7
Amphibolite (silty clay; montmorillonite a major
clay mineral)
III. Baltimore Gneiss Chester-Glenelg; Manor-Glenelg 5
(loam)
IV. Lock Raven Schist Chester-Glenelg; Manor-Glenelg 5
(loam)
V. Serpentinite Thin or absent 10
VI. Prettyboy Schist Manor-Glenelg; Chester-Glenelg 4
(silty-clay loam)
Topography (T): A topographic map of Baltimore County was overlayed with
the Geologic map of Baltimore County in order to make generalizations about
the topography of the county and related to the settings. In general, the
county was within a 2-6% slope range corresponding to a DRASTIC rating of 9.
Some areas were more hilly and had a slope of 6-12% and therefore a DRASTIC
rating of 5. Locally, slopes exceeded 12% along major streams, but they have
been subsumed within the 6-12% slope category for this exercise (Exhibit
III.15).
- 39 -
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EXHIBIT III.13: Aquifer Media in Baltimore County
BN.TMJE WfTY/CITY
MUIFBt »IA: Ueitfit > 3
HTDfiOGBDLOGIC
SETTING
Aquifer
Media
RATING SORE
Cockeysville Marble
Ht Wash Anphibolite
Baltimore Oieiss
Loch Raven Schist
Serpentinite
Prettyfcoy Schist
PatiMmt Format ion
Anrdel Clay
Patapeco Formation
I Silty sand to sand* 6 18
II City to silty clay* 2 6
II! Silty clayey sand» 4 12
IV Clay/send/ loon 4 12
V Massive shale** 1 3
VI Clayey silt* 3 9
A Sard 4 gravel 8 24
B Clay/silt 2 6
C Sand 6 18
* This descibes saprolite of varying caipxiticn.
** The DRASTIC category 'neesive shale* best describes
the aqjifer media of the Serpentinite hjck-cgeologic
setting.
2 6
LEGEND
bating Aquifer Media
3 Sediment: sand & gravel
6 Saprolita: stlty sand to sand>
Sediment: sand
4 Saprolite: silty clayey sands
3 Saprolite: clayey silt
2 Saprolite: clay to silty clay
Sediment: clay/silt
1 Massive shale**
•* the DRASTIC category 'missive shale' best describes
die aquifer media of the Serpent inita and Arundel Clay
hsuircgeologle settings.
- 40
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EXHIBIT III.14: Soil Media in Baltimore County
BALTIMORE COUNTY/CITY
SOIL: weight = 2
HYDROGBOLOSIC
SETTING OCDE
SOU
TV!®
RATING SCORE
Cocfceysville Marble
Mt Uash Anphibolite
Baltimore Q-eiss
Loch Raven schist
Serpent inite
Prettytooy Schist
Pstutent Format icn
Anrriel Clay
PsUpaco Fonratiai
I Clay Loot
II Silty/ctay*
III Loan
IV
V
VI
A
B
C
Loan
Thin or ateent
Si Ity Loon
Si Ity Loon
Si Ity Loot
Clay Loot
3
7
5
S
10
4
4
4
3
6
14
10
10
20
8
8
8
6
* Si Ity clay with clay mineral sentnnrH Unite
(a shrinking clay).
10
9
3,
LEGEND
Rating Soil Type
10
7
5
4
3
Thirt to absent
SI 1ty clay with clay
mineral montmorillonite
(a shrinking clay) ,
Loam
SiIty loam
Clay loam
41 -
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EXHIBIT III.15: topography In Baltimore County
MLTUBRE OUnT/CITY
TCRXIWW: Msitfit » 1
HYDHQGBOLOGIC RANGE
SETTING CUE (X slope) RATING(S) SORE
Cocteysville Marble I 2-6 9 9
Wt Ubeh M^ibolite It 2-6 9 9
Baltimre freiss III 2-12 9,5* 5-9
Loch mien Schist IV 2-12 9,5* 5-9
5erp«r*inlt# V 6-12 S 5
Prettytay SdliSt VI 6-12 5 5
Pstuint Formation A 0-6 10,9* 9-10
Afwfet Clay 8 0-6 10,9* 9-10
Patqpeoo Fornoticn C 0-6 10,9* 9-10
* Tmo ratlntP «re aesiyed because the X slope varies
sisnificantly across the hy^ttsgnloglc setting.
LEGEND
- 42 -
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Impact of the Vadose Zone (I): For the crystalline rock, unlike the
discussion in the DRASTIC report, the primary concern is the combination of
path length and tortuosity as impacted by grain size, sorting and packing,
sorption, consumptive sorption, and fracturing. Considering these factors and
that the primary media are more like silt/clay and sand/gravel with consider-
able silt and clay, ratings for each setting given in Exhibit III.16 are more
representative of actual conditions than those given in DRASTIC. These
ratings blend professional judgment based upon the thickness of the saprolite
and the jointing, fracturing, and porosity of the bedrock.
Hydraulic Conductivity (CI: The values for hydraulic conductivity for
Baltimore County were taken from Nutter and Otton (1969).-'--' All of the
crystalline units except for the Cockeysville Marble had hydraulic
conductivities in the range of 1-100 gpd/ft , which correspond to a DRASTIC
rating of 1. The Cockeysville Marble had a hydraulic conductivity in the
range of 300-700 gpd/ft^, with a corresponding DRASTIC rating of 4 (Exhibit
III.17).
III.B.6. Map of Groundwater Pollution Potential in Baltimore County
A DRASTIC score for each hydrogeologic setting in Baltimore County was
compiled from the seven DRASTIC parameters (Exhibit III.18). This table gives
the combined total score for each setting. These scores combined with the map
of hydrogeologic settings create a map of "Groundwater Pollution Potential,
Baltimore County and Baltimore City" (see the Baltimore County/City map
overlays pocket at the back of the report, which contains this map and the UST
and well use maps). The setting with the highest potential for groundwater
pollution is the Patuxent Setting with a score of 164-175 (note that this
setting occurs in both Anne Arundel and Baltimore Counties and is the highest
rated in both); the setting with the lowest pollution potential is the
Serpentinite Setting with a score of 103.
III.B.7. Guidance for Future Application of DRASTIC
Determining the hydrogeologic vulnerability depends upon the time and
personnel resources available, the availability of data, and the desired level
of detail for the maps. As stated previously, the DRASTIC report provides
ratings for each hydrogeologic setting within the 15 groundwater regions
within the United States. If specific data pertaining to a county or state
are not available, these ratings can be used to evaluate the hydrogeologic
vulnerability of the relevant area.
During the development of DRASTIC scores for individual hydrogeologic
settings, we found that the DRASTIC ranges pertaining to several of the
hydrogeologic parameters did not include types occurring in the Baltimore
study area. For example, the aquifer media types provided by DRASTIC did not
provide fine enough detail to allow the various unconsolidated and crystalline
rock formations to be adequately differentiated. Consequently, we developed
revised ratings to better describe the range of aquifer media in the study
area. This kind of fine-tuning and revision may be necessary in other
applications, and should be conducted by an experienced geologist or
hydrogeologist familiar with the area of interest.
- 43 -
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EXHIBIT III.16: Impact of the Vadose Zone in Baltimore County
BALTIMORE COJHTY/CITT
HOC? OF THE VKXEE 20E: « 5
mwamoGic
SETTING
CCDE
Vadose Zone
Media
RATIMKS) SCORE
CnckeysviUe Marble
Ht Mash flrrphibol f te
Baltimore Qteiss
Loch Racn Schist
Serpentinite
Prettvtoy SAist
?atLKErtt Formtfen
Artrriel CI 3/
Patspsco Forneticn
t Silty sand to send? 7 5
II Clay to si Ity clay* 4 20
III Silty clayey sand* 4 2D
IV Clay/said/ loan 3 15
V Massive shale?"* 3 15
VI Clayey silt* 5 25
A SandSgravel 8 40
B Clay/silt 1 5
C Sand 6 30
* This desclbes safrotite of varying ecnpositiaw
** The DRASTIC category 'massive shale' best dsicribet
the vadose zene media of the Serpmtinite
frydrogecLogic setting.
8
8
Ratings for crystalline rock
settings are a blend of professional
judgement, based upon thickness of
saprolite, renovation capacity of
saprollte, jointing, fracturing and
porosity of bedrock,
. 44
'S
8
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EXHIBIT III.17: Hydraulic Conductivity In Baltimore County
BALTIMORE COKTY/C1TY
msRKiic cnarrivjTT: wM^it ¦ 3
WDBOGBMEIC
SETT IMG
CockrysviLte Marble
Ht Mash Aiphibotite
Baltimore Qieiss
Loch Raven Schist
Serpent inite
Prett^fcoy Schist
Pat!*ent Format icrt
Arundel CIaf
farmtim
OfflE
RANGE
(gpVft~2)
RATIMG(S)
sons
1
300-700
4
12
II
1-1®
1
3
in
1-100
%
3
IV
1-100
1
3
V
1-100
%
3
VI
1-100
1
3
*
300-700
4
12
a
1-100
1
3
c
300-TO
4
12
4 (O 4
LEGEND
Rating Hydraulic Conductivity
4 300 - 700 gpd/ft2
1 1 - 100 gpd/ft^
4 r\A
1^ 1 ^ "
45
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EXHIBIT III.18 DRASTIC SCORES IN CRYSTALLINE ROCK SETTINGS Of BALTIMORE COUNTY
Total Depth to Net Aquifer Soil Impact of Hydraulic
Set t ina Score Groundwater Recharae Med ia Media Topography Vaaose Zone Conductivi ty
I. CockeysviI Ie 147 35 32 IB 6 9 35 12
II. Mt . Washington 109 25 32 6 14 9 20 3
Amphi bo 1i t•
III. Baltimore 107-121 25-35 32 12 10 5-9 20 3
One i ss
IV. lock Raven Schist 102-116 25-35 32 12 10 5-9 15 3
V. Serpentinite 103 25 32 3 20 5 15 3
VI. Prettyftoy Schist 107-117 25-35 32 9 B 5 25 3
0V
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While the DRASTIC methodology was developed for use by relatively junior
hydrogeologists, the experience from this application suggests that
experienced technical professionals should play a significant role in ranking
hydrogeologic vulnerability. The DRASTIC system represents common
hydrogeologic conditions observed nationally, and does not provide ratings for
all media types that may be encountered. Experienced technical professionals
can provide important insights on how to score areas not addressed in the
DRASTIC system.
The time and resources required for scoring an area with DRASTIC will
depend upon the size of the area and the level of detail desired. A rough
scoring of the two counties considered in this report required less than one
calendar week (100 person-hours) to complete, which should be representative
of most applications. The scoring was performed by one senior level
geologist, a mid-level environmental engineer, and a junior level geologist.
Once the initial scoring was completed, considerable effort at fine-tuning the
approach consumed additional time. Again, the additional effort in fine-
tuning the approach will depend upon the experience of the participants, the
complexity of the areas, and the level of detail desired.
III.C, Collecting Water Well Data
III.C.I. General Approach
In collecting data on water wells (used here as a surrogate for
populations dependent on groundwater), we based the data requirements upon the
need to identify data that quantified groundwater use and the number of USTs,
and which could be aggregated by zip code and manipulated by the computer
software we used to analyze and display it. As discussed in Section II.C.2,
we collected both well and UST locational information by zip code. This
choice was made in part due to the availability of computer software able to
analyze geographic information at this level, and in part due to the
availability of data in this format. We would have preferred to use a smaller
and more uniformly sized unit than zip codes, or to map data points
individually, but compromised due to time and resource limitations.
The Maryland Department of Health and Mental Hygiene provided data on
water well locations from its computerized records of water well permits in
the State. These records contain well locations (by Maryland grid coordinates
and street address of well owner), use type (domestic, municipal, or
industrial), well depths, and distance to the nearest town. The records
provided information on well location, and information to estimate the number
of people served by each well. The location information for many of the
records was either missing or incomplete. In general, the data for Anne
Arundel County was found to be less reliable than that for Baltimore, mostly
due to street name changes. The Maryland grid coordinates for the older
records were too general to be useful. It was also discovered that
individuals filing for permits apparently interpreted the term "nearest town"
differently. Most of the records correspond to well permits received after
1978 and probably correspond to operating wells; some of the well records,
however, were received prior to 1970 and some of these wells may no longer be
in operation. Although these records were incomplete, they were the best
information available on well placement and use.
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Because the well records were so incomplete, researchers at the Baltimore
Regional Planning Council (RPC), used a software package to assign well owner
street addresses to five digit zip codes. Because many of the well owner
addresses could not be computer matched with zip codes, and because it was
discovered that the well owner address was not always the address for the well
itself, the RPC undertook the task of manually matching "addresses with zip
codes and double checking matches to ensure, whenever possible, that the well
was assigned to the zip code in which it was actually located. More than 90
percent of the well records were assigned to zip codes. The data were sorted
by zip code to provide the numbers of wells per zip code in both Anne Arundel
and Baltimore Counties. The data on private wells were verified by comparing
it with maps showing the distribution of municipal water to residents, and
other less complete sources of well data, and making adjustments where
appropriate.
In order to analyze potential impacts on private and municipal well
systems, we translated the well information into numbers of people served by
wells. For private wells, we assumed one well per household. We assumed that
2.58 persons/household are served by wells in Baltimore County and 2.83
persons/household in Anne Arundel County.^ We obtained estimates of the
number of users for the public wells from telephone conversations with
employees of appropriate public works departments and by using the Master
Water and Sewer plan (Anne Arundel County). We considered all persons using a
public well supply to be in the same zip code as the well because pollution of
the well directly impacts their water use. Appendix B provides the tables of
well data which are used in this report.
After the number of well users within each zip code was determined, we
calculated the well use densities for each zip code by dividing the number of
users by the surface area of the zip code, to provide the number of well users
per square mile. Each zip code was ranked and assigned to three categories --
low, medium, and high density -- for convenience in displaying the densities
on maps.
Three density categories were chosen for several reasons. The first is
that three is enough to delineate between the densities without cluttering up
a map with regions of a finer gradation. By dividing the data into three
equal distributions, an equal number of low, medium, and high density zip
codes are found within each county. Exhibit III.19 displays the numerical
values for the distribution of well usage and UST densities in both Anne
Arundel and Baltimore Counties. Maps displaying the geographic distribution
of well use density categories are provided in the map overlay pockets at the
back of the report for Anne. Arundel and Baltimore Counties. An alternative
approach to assigning density categories would be to inspect the data for
clear break points between observed densities, and defining ranges
accordingly. No matter how the density categories are defined, it is
important that the ranges be stated so that users may interpret the maps
accordingly.
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Exhibit III.19
Distribution of Groundwater Usage and USTs in
Anne Arundel and Baltimore Counties
Anne Arundel County
Number of
USTs t>er Square Mile Zip Codes"
Low: 0-2 12
Medium: 3-6 11
High: 7-49 10
Baltimore County
Number of
USTs per Square Mile Zip Codes
Low: 0-1.98 19
Medium: 2-5.2 18
High: 5.3-37.1 19
Population Served by
Number of
Wells per Square Mile
Zip Codes
Low: 6-1078
12
Medium: 1644-4465
11
High: 5037-20059
10
Population Served by
Number of
Wells oer Square Mile
Zip Codes
Low: 0
29
Medium: 4-81
15
High: 85-630
14
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Ill.C.2 . Guidance for Collecting Well Data
Collecting data on groundwater use within an area can be a difficult
undertaking depending upon the accuracy of the data available. In the first
stages of the Baltimore IEMF UST project, we originally used data from the
1985 Census of the United States to quantify both groundwater use and
locations of USTs. We identified numerous problems with the accuracy of the
data, however, and decided to examine alternative sources. Thus, we obtained
the data on private and public wells from the State of Maryland Department of
Health and Mental Hygiene.
As described previously, the State of Maryland provided compiled records
of well permits for private wells on computer tape. The Baltimore RPC
assigned the locations of wells to zip codes. The cost for this data analysis
was approximately $2,400,
Quality control analysis highlighted several problems. In some zip codes,
the data suggested more private wells than households, while in others, the
percentage of households served appeared to be too low. Additionally, some
zip codes located in Baltimore City (which is served entirely by public water)
showed private well populations. Cases where there were more wells than
households or wells in areas served by public water occurred because well
records do not identify whether wells are active or inactive. Because the
well records in Maryland date from the late 1940's, some of the wells may not
actually be in service.
The RPC conducted a computer match on well permits with known well owner
addresses. The RPC found that its automated address-matching technology was
successful about one-half as often as it normally is in assigning well permits
with owner street addresses to zip codes. Their results are summarized in the
following table.
Exhibit
Permits
III. 20: Automated Address-Matching Results, by Groups of Well
Permits Issued
Category
Total:
No Address
No Match
Matched
Before Jan 1970 Since Jan 1970
24,976
9,083
10,895
4,998
39,236
6,435
12,325
20,478
All Permits
Issued
64,212
15,518
23,220
25,476
Missing (or unrecognizable) address information was found to be more
prevalent than normal. Additionally, well location records with readable
addresses failed to match the present-day street system in the three political
subdivisions at unusually high rates.
Although disappointing, these results were not total surprises. They
reflect the overall geographic distribution of wells, limitations in automated
address-matching technology, and the history of development in the Baltimore
metropolitan area. The results do not imply poor record-keeping practices by
- 50 -
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the Department of Health and Mental Hygiene; rather, they reflect the fact
that historical data may often not be complete, accurate, or in a useable
format,
Note, for example, the differences before and after 1970. More than 1/3
of the well permits issued prior to 1970 had no street address for the well's
owners, or, had entries that could not be recognized as "city" style street
addresses, because house-numbering didn't exist in the rural parts of
Baltimore County until 1970, more or less, and not until nearly 1980 in Anne
Arundel County.
We overcame some of the data discrepancies using updated maps showing the
distribution of public water supplies. Using these maps, we were able to
estimate the percentage of households served by private wells. We also
compared the RFC-treated data with other reliable, but less complete, sources
of well data, then made adjustments where appropriate.
Depending upon the availability of data, it could take from two weeks to
two months to identify populations served by groundwater by zip code within a
given study area. Some states or counties may have readily accessible and
usable data that will make this data collection relatively straightforward.
In other cases, such as in this study, it may be necessary to manipulate large
amounts of data, which can add time and expense to the study.
Ill.D. Collecting Underground Storage Tank Data
III.D.l. General Approach
We obtained UST data from the EPA Region III office in Philadelphia.
Region III provided a computer file containing information on number of USTs
in both Anne Arundel and Baltimore Counties. These data were sorted by zip
code and the total number of USTs per square mile in each zip code was
calculated,
In order to integrate the well and UST information, we calculated UST
densities for each zip code in a procedure similar to that followed for wells.
The number of USTs in each zip code was divided by the surface area of the zip
code in order to generate a value for the number of USTs per square mile. We
created a distribution of UST densities corresponding to low density, medium
density, and high density with 1/3 of the zip codes in each of the categories
(see Appendix B), We printed maps of both Anne Arundel and Baltimore Counties
displaying the distribution of USTs by zip code (see the map overlay pockets
at the end of the report).
II1.D.2. Guidance for Collecting UST Data
Data collection for USTs was relatively straightforward due to the
availability of data from the EPA Region III UST Notification survey. The
Hazardous and Solid Waste Amendments (HSWA) of 1984 required States to collect
this UST data, and most states have complied. These data were collected by
EPA Regional Offices for those states, like Maryland, that did not
participate. EPA Region III is now providing these data to Maryland. The
only difficulty was that the data were formatted by a proprietary software
51 -
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package which was not initially available to the project. Once arrangements
were made to reformat the UST data, it took about two days to sort the data by
zip code and calculate UST densities.
The initial data collection efforts relied upon data from the 1985 Census,
the accuracy of which was questioned by members of the UST Work Group. In
future applications, users should take care to check data carefully to ensure
their usefulness and accuracy for the intended goals of the study. It is
recommended for quality control purposes that one zip code area (or more) be
physically inventoried (by driving the roads within the zip code and mapping
the occurence of every gas station and UST located on other properties). For
example, a physical survey for USTs in the Cockeysville 7.5-minute quadrangle
(a 50 square mile area in central Baltimore County), took two people one
working day. By way of contrast, a well inventory for a county like Baltimore
could be expected to take one person two to eight months, depending upon the
existence of prior well inventories (Emery T. Cleaves, Maryland Geological
Survey, personal communication).
III.E. Map Overlays: Well and UST Densities and Groundwater Pollution
Potential
III.E.l. General Approach
The maps of groundwater pollution potential, well usage density, and UST
density are laid over each other to identify the relative risk of groundwater
contamination from possible; UST leaks. (See the Anne Arundel County and
Baltimore County/City map overlay pockets at the end of the report). The map
overlays are the primary product of the Baltimore IMP screening analysis in
that they provide an indication of geographic areas where potential impacts
are greatest. Based upon these overlays, state and county environmental
planners can identify those areas where tank and well use is high, and/or
where the groundwater is especially vulnerable, in order to focus inspection
and enforcement resources on the most vulnerable areas.
III.E.2. Guidance for Future Application of the Methodology
Appendix C describes the computer hardware and software we used to
generate map overlays which integrate the three measures of vulnerability.
The resource requirements for this aspect of the study will depend primarily
upon the amount and types of computer equipment within the organization
conducting the screening analysis. While this work does not require staff
with advanced computer programming skills, it does require persons possessing
a working familiarity with computer applications.
Some difficulty arose in digitizing the map boundaries for hydrogeologic
settings. Only a few software packages are designed to support the creation
of boundary files through digitizing map information on personal computers.
While the mapping software relied upon in the study had the capability to
digitize new geographic boundaries, numerous difficulties were encountered in
carrying out this portion of the study. In general, these experiences
highlighted the importance of obtaining a well-tested digitizing software
package before undertaking this section of the analysis. Future applications
will benefit from rapid advances in computerized graphics technology taking
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place.
The resources required for developing map overlays will depend upon the
type of products desired. In this study, we developed four sets of full scale
maps (1/62,500) printed on mylar to facilitate their use as overlays by Anne
Arundel County, Baltimore County, and Baltimore City officials. The cost for
mylar and pens to print these maps may be $100 to $500 for four sets of maps.
Thus, these maps should be test plotted on paper to be sure they are correct
before plotting on mylar. The costs for printing report-sized maps, like
those presented here, however, is considerably less given the appropriate
computer hardware (see Appendix C).
The time required for developing the three maps varies depending upon the
system used and the ease of access to the system. Several months were
required to develop the final maps of groundwater pollution potential for this
study, although we believe that much of this time resulted from the
exploratory nature of the project and time needed to coordinate between
agencies and consultants in different cities. With experience, and proper
computer hardware and software, one person-month is a reasonable estimate.
It is possible to develop a map in which we aggregate the three measures
of vulnerability. We chose not to do this because we would lose detail if we
aggregated the factors into fewer composite categories. And we would lose the
capability to evaluate each measure individually as well as together with the
other measures. It is also possible to create one composite map of the three
measures retaining the level of detail we now have, but it would be
prohibitively expensive to do this on the computer, and we would again lose
the capability to view each measure individually.
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IV. STUDY FINDINGS AND CONCLUSIONS
IV.A. UST Screening Methodology: General Findings
The UST screening methodology developed for the Baltimore IEMP identifies
areas vulnerable'to leaking UST's by quantifying and integrating hydrogeologic
settings, UST density, and population served by groundwater. The keys to the
methodology are:
(1) The use of maps to identify and display the geographic distribution
and variability of the three major factors (settings, UST's, and
populations dependent on groundwater).
(2) The use of DRASTIC to identify and evaluate mappable units with
common hydrogeologic characteristics and common vulnerability to
contamination.
(3) The potential groundwater resource impact is determined by the
location of the counties, USTs, and drinking water wells relative to
the "natural" hydrogeologic settings.
The UST screening methodology provides a useful tool for assisting State,
county, and local environmental officials to focus inspection and enforcement
resources on areas within their jurisdiction exhibiting the greatest
vulnerability to leaking USTs. The strength of the methodology lies in its
map overlays, which allow environmental officials to exercise their judgment
on which locations are most vulnerable. While the methodology does not
integrate the three measures of vulnerability into one overall score, the maps
allow officials to analyze three major factors contributing to the
vulnerability of a region, and evaluate the interaction of these factors on
maps.
A successful application of the methodology depends upon the accuracy of
data used to quantify groundwater pollution potential, UST density, and
well-dependent population density. Before undertaking an UST screening
analysis in future applications, the data format to be used in the analysis
should be determined. In the application to the Baltimore area, well and UST
data were aggregated to the zip code level. While the participants in this
study believe the analysis will provide a useful tool, many stated a
preference for using individual geographic coordinates for each well and UST,
or finding a more uniformly sized and smaller base geographic unit. Decisions
on data format will affect both the utility of the map overlays and the
resources required to develop them.
It is difficult to estimate the amount of time that would be necessary for
other states, counties, or localities to undertake an UST screening analysis.
The UST screening methodology evolved simultaneously with its application to
the Baltimore area and, therefore, required more time and resources than will
be necessary in future applications. Data collection will often consume the
most resources during applications. Groundwater pollution potential maps may
be developed with DRASTIC in less than one person-week if at least one
experienced hydrogeologist contributes to their development. Well and UST
data collection may require from two person-weeks to two person-months,
depending upon the data's accuracy, availability, and format.
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Because of the importance of data availability, accuracy, and format,
jurisdictions may wish to evaluate their current UST and groundwater data
reporting. If the needed variables are not currently collected, or if these
data are not reasonably complete and in a useable format, jurisdictions may
wish to revise their reporting requirements in order to facilitate efficient
updates and improve the accuracy of these screening products.
IV.B. Analytical Findings in the Baltimore Study Area
The UST screening analysis allows a number of conclusions to be drawn
concerning the potential for groundwater contamination from USTs in the
Baltimore IEMP study area. The DRASTIC scores for the hydrogeologic settings
reveal the relative vulnerability of the settings to groundwater
contamination. In general, hydrogeologic settings in sedimentary rocks are
relatively more vulnerable to groundwater pollution than those in crystalline
rock settings in the study area. The ranking of the settings is shown in
Exhibit IV.1. Because Anne Arundel County is underlain by sedimentary rocks,
groundwater pollution of the water table aquifer there is a much greater
potential problem than in Baltimore County, which is mostly underlain by
crystalline rock settings. The contrasting relative vulnerability between
sedimentary and crystalline settings reflects the geologic and hydrogeologic
contrast between the Coastal Plain and Piedmont Physiographic Provinces in
Maryland.
EXHIBIT IV.1 Relative Ranking of Hydrogeologic Settings by DRASTIC Scores
Rank*
Setting
Settine Type
DRASTIC
Score
Median
Score
1
A.
Patuxent Formation
Sedimentary
164-175
169.5
2
D.
Potomac Group
Sedimentary
160
160
3
C.
Patapsco Formation
Sedimentary
146-157
151.5
4
I.
Cockeysville Marble
Crystalline
147
147
5
H.
Aquia Formation
Sedimentary
131-145
138
6
F.
Monmouth Formation
Sedimentary
137
137
7
E.
Calvert Formation
Sedimentary
116-131
123.5
8
III.
Baltimore Gneiss
Crystalline
107-121
114
9
VI.
Prettyboy Schist
Crystalline
107-117
112
10,11,12
G.
Marlboro Clay
Sedimentary
109
109
10,11,12
II.
Mt. Wash. Amphibolite
Crystalline
109
109
10,11,12
IV.
Loch Raven Schist
Crystalline
102-116
109
13
B.
Arundel Clay
Sedimentary
102-113
107.5
14
V.
Serpentinite
Crystalline
103
103
* The setting with the highest potential for groundwater pollution
is ranked
first; the lowest is ranked last.
The hydrogeologic settings in the region received DRASTIC scores ranging
from a low score of 102 to a high score of 175. The Patuxent setting, located
in both Anne Arundel and Baltimore Counties, was found to be the most
55 -
-------
vulnerable setting, with a score ranging from 164 to 175. The Potomac
setting, found only in Anne Arundel County, had nearly the same pollution
potential, with a DRASTIC score of 160. Several crystalline rock settings
exhibit low pollution potential, with DRASTIC scores between 100 and 119: Mt.
Washington Araphibolite, Loch Raven Schist, Prettyboy Schist, and the
Serpentinite. The Arundel Clay, found in both counties, also exhibits a low
pollution potential with a DRASTIC score of 102-113.
The density of USTs within the study area ranges from 0 to 49 USTs per
square mile and the distribution is relatively similar in both counties. The
highest density of USTs is generally found in Baltimore City and near
Annapolis, the most concentrated population, centers in the study area.
Because the distribution of USTs does not vary as widely as either groundwater
use or hydrogeologic vulnerability, this study suggests that the other two
measures of vulnerability will be more critical to the targeting of resources
in the Baltimore IEMP study area.
Groundwater use is significantly greater in Anne Arundel County than in
Baltimore County. The high well use category in Anne Arundel County ranges
from 5,037 to 20,569 users per square mile, compared to that of Baltimore
County, which ranges from 85 to 630 users per square mile (Appendix B).
Baltimore City falls into the low well use category because surface water
supplies are used for drinking water.
The map overlays reveal a number of areas within Anne Arundel County where
zip codes with high densities of wells and USTs are located in vulnerable
hydrogeologic settings. The Glen Burnie area, situated in the Potomac
setting, is one of the most vulnerable areas within Anne Arundel County due to
its high well usage and UST density. Generally, most of the northern portion
of the County is within one of the two highest groundwater vulnerability
categories (except for those areas overlying the Arundel Clay setting), and
has high well use and medium to high UST density.
The South River Neck area near Annapolis overlies the Aquia Setting
(DRASTIC score of 131-145), and has both high well usage and UST density,
making it a relatively vulnerable area in the County. The western edge of
Anne Arundel County borders on the Patuxent River, and overlies the vulnerable
Patuxent setting. While well and UST densities vary along this border from
low to high, the vulnerability of the groundwater in this area indicates a
potential for damages from USTs. Because the southern portion of the County
overlies the less vulnerable Calvert setting and exhibits lower densities of
both USTs and wells, it will not demand the same degree of attention as the
more vulnerable areas described above.
Baltimore County has fewer areas with a high vulnerability to leaking USTs
than Anne Arundel County. While the highly vulnerable Patuxent setting
outcrops in the southern portions of Baltimore County, the population in most
of these areas are not dependent on groundwater (although the high UST density
in these areas indicate the potential for resource damages). The most
vulnerable area where groundwater is used occurs in the center of the County
in the Cockeysville Marble setting. The Cockeysville setting received a
DRASTIC score of 147. Significant portions of this setting exhibit both high
UST and well densities, indicating a high vulnerability to leaking USTs.
Other than the Cockeysville Marble, the other crystalline rock settings in
- 56 -
-------
Baltimore County generally fall into the lowest pollution potential category
(DRASTIC score of 100-119), and pose relatively less threat from leaking USTs.
Baltimore City overlies portions of the Baltimore Gneiss setting, the
Patuxent setting, and the Arundel Clay setting. While the Patuxent setting is
highly vulnerable to pollution, the entire city is in the low well use
category due to the use of surface public water supplies.
DRASTIC notes that net recharge, soil, and topography are not as important
in evaluating pollution potential from USTs because of their location below
ground. As a sensitivity analysis, we calculated the DRASTIC scores omitting
these three factors and found that the relative rank of the hydrogeologic
settings changed only slightly. (See Appendix D.)
IV.C. Assumptions of the Analysis
Conclusions from this application of the UST screening methodology to the
Baltimore area must be evaluated in light of certain assumptions and
limitations inherent to the application. These factors generally relate to
each of the three measures of vulnerability examined in this approach:
hydrogeologic vulnerability, density of populations served by groundwater, and
UST density.
In developing the DRASTIC maps, we assumed that depth to groundwater in
the study area referred to the depth to groundwater in the water table
aquifer. In some cases, however, the surficial aquifer may not be a source of
drinking water; many wells in Anne Arundel County tap lower artesian aquifers
for drinking water supplies. Because of this, the vulnerability of the actual
drinking water source may not always have been rated.
These assumptions were made for two reasons. First, because gasoline USTs
release contaminants that are predominantly lighter than water and will float
on the water table, it is not likely that these contaminants will migrate
through several confining layers into lower aquifers. Second, poorly sealed
well bores may serve as conduits transporting contaminants floating on the
water table into wells, where they may contaminate the drinking water supply.
Therefore, we assumed that the potential for UST impacts at wells can be
characterized by the ability of the constituents to migrate in the surficial
aquifer toward the well.
In developing the DRASTIC maps of hydrogeologic vulnerability, we based
the division of DRASTIC scores (which ranged from 102 to 175) into separate
ranges upon suggestions from the DRASTIC report for preparing final maps.
While most of the hydrogeologic settings received a range of scores rather
than one single score, most of these ranges fell completely within the ranges
defined by a single color. For those settings with a range falling between
two categories, the unit was colored to match that of the more vulnerable
category in order to be conservative.
For both counties, the final definition of the hydrogeologic settings and
the assignment of the DRASTIC ratings were made by Dr. Emery T. Cleaves,
Maryland Geological Survey. As noted in the text, he modified some DRASTIC
factors and their ratings to better reflect regional conditions. The initial
ratings were assigned based on the assessments of a senior geologist familiar
- 57 -
-------
with the. hydrogeology of Maryland, a mid-level environmental engineer, and a
junior level geologist. It is Dr. Cleaves' opinion that an experienced
geologist knowledgeable in local hydrogeology and geology is necessary for
reasonable and timely application of the DRASTIC methodology.
We made a number of assumptions in assigning wells to zip codes from the
data supplied by the State of Maryland Department of Health and Mental Hygiene
and the counties. In some cases, it appeared that the address of a well owner
did not coincide with its actual location. As stated previously, these wells
could have been assigned to incorrect zip codes in these instances despite
significant efforts to assign wells to the correct zip code. The well data
also indicated areas where a low percentage of the population used groundwater
when it was expected that the entire population relied upon private wells. In
these cases, we used public water supply maps and other sources to identify
zip codes where no populations were served by public water, and zip codes in
these areas were changed to indicate 100% private well use.
We obtained locations and population served by public wells from the State
of Maryland Water Resources Administration, Anne Arundel County Department of
Utilities, and the Baltimore County Department of Environmental Protection and
Resource Management. Only municipal wells and those privately owned well
systems supplying the domestic needs of a residential population (such as
trailer parks and small towns) were considered. Commercial wells, such as
those serving hotels, schools, or religious, social, or military organizations
(except for military housing), were not included in .the well use information.
Because of the complexity of the Anne Arundel County municipal water
system, population served by well fields was provided by the Anne Arundel
County Master Water and Sewerage Plan (1984) or estimated from pumpage data.
All population information was for a projected 1985 population, while the
pumpage data were from 1987. Where there was insufficient information
regarding the number of people served by privately owned water systems, the
service populations were estimated from.pumpage data by assuming domestic use
of 80 gallons/person/day. Appendix B provides the data on both wells and USTs
in both counties.
EPA Region III supplied the UST data which represent the result of the
notification requirement for owners and operators of USTs. These are probably
the most complete and accurate data available on the locations and
characteristics of USTs. Because the survey relied upon submission of the
notification forms by UST owners and operators, some USTs may not have been
considered. The analysis did not consider gasoline USTs located on farms,
which often have their own gasoline storage. The analysis also considered
only gasoline USTs, and did not attempt to quantify impacts associated with
USTs containing other types of chemical products.
- 58 -
-------
V. PLANNED AND POTENTIAL USES OF THE UST SCREENING METHODOLOGY
The State and local officials involved in the IEMP thought that it was
important to develop a priority-setting tool to enable them to respond to the
most serious UST leaks first. The tool we developed may be used by state
officials for determining priority areas across the state, and by state,
county, and local officials for targeting inspection and enforcement
activities within their jurisdiction. The approach will allow officials not
ony to practice better UST management, but to also evaluate other potential
sources of groundwater contamination, and to better plan future development.
The State Waste Management Administration, the Baltimore County Department
of Environmental Protection and Resource Management, and the Anne Arundel
County Health Department have each indicated that they intend to use the UST
study's methodology to help set priorities regarding staff and resource
allocation for UST leak investigation and cleanup. (The State Waste
Management Administration has primary responsibility for investigating and
enforcing cleanup from leaking USTs under the state regulations, while the
county health and environmental departments respond to reports of oil
pollution in wells, storm drains, and excavations.) The hydrogeologic
information presented by this study for specific areas, especially soil type
and depth to groundwater, will help inspectors assess the vulnerability of a
site to groundwater damage before they specify remedial actions. Information
on UST density and well-dependent population density may help the State
determine the degree of groundwater remediation that will be required.
The State of Maryland plans to use our priority-setting methodology to
fulfill requirements for a cooperative agreement with the EPA's Office of
Underground Storage Tanks. EPA amendments to Subtitle I of the Resource
Recovery and Conservation Act (part of the Superfund Amendments and
Reauthorization Act of 1986) have established a trust fund to finance the
cleanup of petroleum releases from USTs. EPA, and States who enter into
cooperative agreements with EPA, can access this fund for cleanup when
appropriate. EPA will manage the trust fund monies in ways which will best
•protect human health and the environment. Thus, one of the requirements for
the cooperative agreement is that a state must have a priority-setting system
either in-place or under development. This screening device will enable
enforcement agencies to address the potentially most serious UST leaks first.
The State of Maryland has chosen the methodology developed in the UST Phase II
study as its requisite priority-setting management tool, and will attempt to
apply the methodology to all Maryland's counties.
Another major application of the UST Phase II screening methodology and
maps will be in reviewing proposed development. A large part of the work of
the Baltimore County Department of Environmental Protection and Resource
Management and the Anne Arundel County Health Department involves reviewing
plans for proposed residential and commercial development. The hydrogeologic
information developed in this study will help the departments to evaluate
these proposed plans, especially siting new USTs. Specific design, operating,
monitoring, or inspection requirements for USTs may differ, depending on the
vulnerability of an area due to populations dependent on groundwater or
hydrogeologic setting. The departments may negotiate with developers to
locate UST-dependent facilities on less vulnerable sites. Or, in highly
vulnerable areas, the departments may require extra tank containment, alarm
- 59 -
-------
and detection systems, above-ground tanks, or may not allow storage tanks at
all.
The UST Phase II study maps are designed to be used by planning and zoning
offices. The DRASTIC, UST, and well maps will be plotted on high transmission
film at a scale of 1:62,500 to be used as overlays on county planning maps.
These maps will allow planners to identify broad areas for further .
site-specific analysis to evaluate proposed development, landfill sites, or
other activities in light of groundwater vulnerability.
The information collected in the UST Phase II study can be used in
conjunction with other planned studies. The Anne Arundel County Department of
Planning and Zoning is planning to conduct a comprehensive survey of the
groundwater situation in the county and evaluate future uses in light of the
findings. The hydrogeologic information and the impact of USTs presented in
our study will be considered in the survey.
Several agencies indicated that that UST study data and maps could be
incorporated into existing or planned groundwater quality data bases or used
as an adjunct to these data bases. The Baltimore County Department of
Environmental Protection and Resource Management now has such a data base, and
the State is developing a comprehensive data base to track groundwater quality
and another to monitor ambient groundwater statewide. The State is also
planning to digitize its geographic data points, including all USTs.
The results of the UST Phase II study can be used to educate UST users,
developers, and others. The agencies involved in this study plan to use it to
educate developers, engineers, and other segments of the public. If these
individuals understand the importance of groundwater protection in vulnerable
areas, they may be more inclined to cooperate with protection strategies, and
developers may be motivated to develop environmentally sound storage practices
prior to submitting their plans for review.
The UST screening approach can be applied to the analysis of other
potential sources of groundwater contamination. For example, impacts from
municipal landfills, industrial surface impoundments and landfills, and road
salt piles depend upon the frequency of occurrence of each source, the
dependence on groundwater, and the pollution potential of the hydrogeologic
setting. Any of these potential sources of pollution could be substituted for
USTs in this analysis.
Other potential uses of the UST Phase II products vary. The state and
counties are required, under the Safe Drinking Water Act, to develop
management standards of facilities that fall into the critical protection
areas that surround public drinking water wells. The information developed by
our study could be used to evalute these critical areas and develop well-head
protection program or to help site new public wells. Various public agencies
that use USTs may install extra protection in hydrogeologically vulnerable
areas or locate USTs in less vulnerable areas. Fire departments may wish to
pay special attention to areas with high UST density to track potential leaks,
especially where leaked fuel may travel quickly, to prevent dangerous seepage
of fuel or fumes into sewers and basements.
- 60 -
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VI. ALTERNATIVE APPROACHES TO ASSESSING VULNERABILITY FROM LEAKING USTs
EPA's Office of Underground Storage Tanks (OUST) has developed an
alternative approach for assisting State administrators in setting priorities
for effectively expending their resources in the UST programs.^' The OUST
approach focuses on groundwater use within zip code areas from public and
private wells, and the likelihood that tanks within a zip code will leak based
upon their numbers and age. These two factors are quantified into two numeric
values: the Geographic Potential Impact Factor (GPIF) and the Leak Likelihood
Factor (LLF). These two values are combined to produce a numeric ranking for
each zip code considered, and taken together, a relative ranking of zip codes
can be generated.
This approach is similar to the UST screening methodology presented in
this report in that both approaches produce a relative ranking of areas of
potential vulnerability. Both approaches identifying vulnerable locations
address similar scales (State- and county-wide), and focus on zip codes as the
basic geographic unit.
The approaches differ in that the Baltimore UST screening methodology
addresses the inherent pollution potential of groundwater using the DRASTIC
methodology. The Baltimore screening approach thus integrates three compo-
nents affecting potential groundwater impacts rather than two: groundwater,
use, UST density, and hydrogeologic setting. The OUST approach will generally
require less time to develop on a regional basis but omits consideration of
the hydrogeologic environment. The IEMP methodology does not proj ect the
probability of UST leaks, but does not require the collection of UST age data.
In evaluating which methodology to use, a jurisdiction should consider the
hydrogeologic variability of an area, the financial and staff time resources
available, and the availability of hydrogeologic and UST age data, as well as
the preferences of the agencies. If an area is varied in its hydrogeology,
and there is a reasonable amount of hydrogeologic information available, the
jurisdiction may wish to use the IEMP methodology. On the other hand, if the
hydrogeology is very uniform, and age data is available, the jurisdiction may
wish to use the OUST methodology. The financial and staff resources and the
preferences of the agencies, including the use of the screening products for
other uses, will also influence the decision of which methodology to use.
- 61 -
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FOOTNOTES
1. National Water Well Association, DRASTIC: A Standardized System for
Evaluating Ground Water Pollution Potential Using Hvdrogeologic Settings.
EPA/600/2-85-018, May 1985.
2. Mack, Frederick K. , Ground Water Supplies for Industrial and Urban
Development in Anne Arundel County. . Maryland Department of Geology,
Mines, and Water Resources, 1962.
3. Ibid.
4. Dingman, R.J., and Ferguson, H.F., The Water Resources of Baltimore and
Harford Counties. Maryland Department of Geology, Mines, and Water
Resources, 1956.
5. Mack, Frederick K., op. cit.
6. Chapelle, Francis H. , "A Solute-Transport Simulation of Brackish-Water
Intrusion Near Baltimore, Maryland", Ground Water. Vol. 24:3, May-June
1986.
7. State of Maryland, Maryland Geologic Survey, Geologic Map of Anne Arundel
County. 1976.
8. Mack, Frederick K., op. cit.
9. Ibid.
10. Kirby, R.M., Matthews, E.D. 1973. Soil Survey of Anne Arundel County,
Maryland: Soil Conservation Service, U.S. Department of Agriculture,
Washington, D.C. 127 pp.
11. Mack, Frederick K., op. cit.
12. State of Maryland, Maryland Geologic Survey, Geologic Map of Baltimore
County and Citv. 1976.
13. E.G. Otton, E.T. Cleaves, Cockevsville Quadrangle. Geology. Hydrology,
and Mineral Resources Maps. Maryland Geologic Survey, 1975.
14. Reybold, N.U., III, Matthews, E.D., 1976. Soil Survey of Baltimore
County, Maryland: Soil Conservation Service, U.S. Department of
Agriculture, Washington, D.C. 149 pp.
15. Nutter, L.J. and Otton, E.G.. 1969. R.I. 10. Ground-Water Occurrence in
the Maryland Piedmont: Maryland Geological Survey, Baltimore, Maryland.
56 pp.
16. 1985 statistics used by the State of Maryland. Telephone discussion,
Cindy Powell, State of Maryland Water Resources Administration, April 29,
1987, verified May 13, 1987.
- 62 -
-------
17. Development and Application of an UST Program Targeting Methodology,
draft, prepared for Office of Underground Storage Tanks, USEPA, by Camp
Dresser & McKee, October 1, 1986. (Final report expected in early 1988)
- 63 -
-------
APPENDIX A
UNDERGROUND STORAGE TANK WORK GROUP MEMBERS
Dr. Emery T. Cleaves (Chair)
Deputy Director
Maryland Geological Survey
Baltimore, MD
Bernard Bigham
Federal Program,Coordinator
Waste Management Administration
Maryland Department of the Environment
Baltimore, MD
N. Singh Dhillon, P.E., Director
Division of Environmental Health
Anne Arundel County Department of Health
Annapolis, MD
John Hobner, Registered Sanitarian
Water Quality Section
Baltimore County Department of Environmental
Protection and Resource Management
Towson, MD
Thomas Kusterer, Environmental Planner
Planning and Analysis unit
Maryland Department of the Environment
Baltimore, MD
Edmond G. Otton, Hydrogeologist and President
E.G. Otton & Associates, Consultants
Towson, MD
William Sieger
Oil Control Division
Waste Management Administration
Maryland Department of the Environment
Baltimore, MD
Colin Thacker
Office of the Director
Baltimore County Department of Environmental
Protection and Resource Management
Towson, MD
Othniel Thompson, Sanitarian VII
Science and Health Advisory Group
Maryland Department of the Environment
Baltimore, MD
A - 1
-------
Edwin C. Weber, Chief
Oil Control Division
Waste Management Administration
Maryland Department of the Environment
Baltimore, MD
Hope Pillsbury, Analyst
Office of Solid Waste
U.S. Environmental Protection Agency
Washington, D.C.
Catherine S. Tunis, Policy Analyst
Office of Policy Analysis
U.S. Environmental Protection Agency
Washington, D.C.
A - 2
-------
APPENDIX B WELL AND UST DATA
ANNE ARUNDEL COUNTY WELL AM) UST DATA
PRIVATE POPULATION PUBLIC
POPULATION
AREA
1985
ZIP CCDE
USTs
WELLS
SERVED
WELLS [1]
SERVE)
SQ.M1LES
POP
20707
..
..
3
5203
--
..
20701
11
980
2772
0
0
6.42
2772
20711
51
510
1442
5
2575
33.66
4017
20714
--
--
1
523
--
--
20733
4
952
2693
1
30
4.09
2723
20751
34
287
811
0
0
3.51
811
20754
5
--
-•
0
0
--
--
20755
152
67
190
0
0
21.79
15421
20758
5
336
952
0
0
6.32
952
20764
10
696
1969
0
0
4.02
1969
20765
19
226
640
0
0
0.92
640
20776
7
368
1043
2
821
23.67
1864
20778
6
568
1606
2
3%
9.24
2000
20779
4
231
654
2
64
4.69
718
20794
35
--
--
1
774
--
-•
21012
28
669
1893
1
9121
9.45
17635
21032
50
2425
6862
4
2278
19.41
7639
21035
31
2064
5841
1
270
27.45
6111
21037
126
3729
10552
2
517
19.67
13022
21054
60
1578
4465
1
11
17.86
6394
21056
2
37
105
1
305
1.38
325
21061
373
1106
3130
10
84468
25.61
77687
21076
34
96
2»
3
ICES
12.68
3838
21077
5
51
144
0
0
0.18
1602
21090
76
1780
5037
0
0
6.99
10073
21108
61
908
2570
5
540
15.22
11633
21113
91
486
1375
2
14772
14.13
6483
21114
18
143
405
1
7631
5.68
14472
21122
168
7267
20565
3
128
31.48
46250
21140
2
178
503
1
504
1.18
1509
21144
28'
1483
4196
10
20521
16.28
23463
21146
74
1782
5043
2
17329
8.31
19594
21240
87
10
27
1
22185
5.46
27
21401
334
6564
18577
7
46287
33.97
41321
21402
58
25
71
0
0
1.18
5281
21403
42
1882
5325
1
. 1
8.74
22623
21404
3
--
--
0
0
--
•-
21405
1
2
6
0
0
0.75
1153
AVERAGE
58.24
1164
2947
1.92
5839
12.18 10070.38
PEDIAN
32.50
539
1209
1.00
357
8.74
3838.00
HIGH
373.00
7267
20565
10.00
81227
33.97 77687.00
LOU
1.00
0
0
0.00
0
0.18
0.00
LOW
MB)
HIGH
[1] Includes larricipal and privately owed caimunity water supplies.
(2J HH = Households
Table 1
% OF
MJM3ER HH WITH PRIVATE PUBLIC
OF HH PRIVATE USTs WELLS WELLS
1965 m WELLS PER 9Q.M PER SQ.M PER SQ.M
960
100.00%
HIGH
1.71
LOU
152.57
KB)
0.000
LOU
1419
35.90%
ffl)
1.52
LOU
15.14
LOU
0.149
(ED
962
98.90%
HIGH
0.98
LOU
232.66
HIGH
0.244
FED
287
100.00%
HIGH
9.69
HIGH
81.64
(CD
0.000
LOU
5449
1.23%
LOU
6.98
HIGH
3.07
LOU
0.000
LOW
336
100.00%
HIGH
0.79
LOW
53.23
MED
0.000
LOU
(06
100.00%
HIGH
2.49
IS)
173.07
HIGH
0.000
LOU
226
100.00%
HIGH
20.65
HIGH
245.81
HIGH
0.000
LOU
659
55.94%
0.30
LCU
15.57
LOU
0.084
MED
707
80.31%
m
0.65
LOU
61.43
NED
0.216
PED
254
91.12%
HIGH
0.85
LOU
49.29
LOU
0.426
MB)
6231
10,74%
LOU
2.96
KED
70.79
MED
0.106
MED
2699
89.82%
HIGH
2.58
MED
124.91
NED
0.206
KG)
2159
55.58%
HIGH
1.13
LOW
75.19
MB)
0.036
MB)
4601
81.0S%
HIGH
6.41
MED
189.56
HIGH
0.102
PED
2259
69.82%
3.36
t€D
88.33
MED
0.056
MED
115
32.22%
fO
1.45
LOW
26.81
LOU
0.725
PED
27451
4.03%
LOU
14.56
HIGH
43.18
LOU
0.390
1356
7.02%
LOU
2.68
f®
7.51
LOW
0.237
Iti)
566
9.01%
LOU
27.78
HIGH
283.33
HIGH
0.000
LOU
3559
50.00%
m>
10.87
HIGH
254.60
HIGH
0.000
LOU
4111
22.09%
LOW
4.01
fE)
59.66
MED
0.329
KED
2291
21.22%
LOU
6.44
WD
34.39
LOW
0.142
MS)
5114
2.80%
LOU
3.17
m>
25.18
LOU
0.176
MED
16343
44.46%
(CD
5.34
MED
230.84
HIGH
0.055
PED
533
33.36%
1.69
LOW
150.75
MED
0.847
(€D
8291
17.89%
LOU
1.72
LOU
91.12
l"ED
0.614
IB)
6924
25.74%
PB)
8.90
HIGH-
214.44
HIGH
0.241
FED
10
100.00%
HIGH
15.93
HIGH
1.75
LOU
0.183
MED
14601
44.96%
ME)
9.83
HIGH
193.23
HIGH
0.206
m
1866
1.34%
LOU
49.15
HIGH
21.19
LOU
0.000
LOU
7994
23.54%
4.81
m
215.28
HIGH
0.114
«D
407
0.49%
LOU
1.33
LOU
2.66
LOU
0.000
LOU
3990 50.02%
1866 44.46%
27451 100.00%
10 0.49%
7.06
3.17
49.15
0.30
105.92
75.19
283.33
1.75
0.18
0.11
0.85
0.00
0.5% • 22.1%
23.5% - 80.3%
81.0% - 100%
0 - 2
3 - 6
7 - 49
2 - 49
61 - 153
173 - 283
0
0 • 1
NONE
POPULATION
SERVED
BY GU
PER SQ.M
2772 »
1519 t€D
2700 m>
811 LOW
190 LOU
952 LOW
1969 MED
640 LOU
1077 LOU
1649 MED
668 LOU
2858 MED
6979 HIGH
5851 HIGH
10678 HIGH
4465 MED
326 LOU
6428 HISt
351 LOW
144 LOU
5037 HIGH
2605 PED
2421 MED
1748 l*D
20569 HIGH
931 LOU
5459 HIGH
7128 HIGH
4090 MED
19509 HIGH
71 LOW
5325 HIGH
6 LOU
3853
57*
20569
6
6 - 1078
1644 - 4465
5037 • 20569
B-l
-------
Table 2
BALTIMORE COUNTY WELL AM) UST DATA
% OF
NUMBER HH WITH
PRIVATE POPULATION PUBLIC PORJLATION AREA 1905 OF HH PRIVATE
ZIP CODE USTs WELLS SERVO) WELLS til SERVED SQ.MILES POP 1985 03 WELLS
21013
2
--
• •
0
0
..
100.00%
HIGH
21021
9
279
720
0
0
2.8
720
279
100.00%
HIGH
21022
26
0
0
0
0
0.7
1856
719
0.00%
LOW
21030
129
1533
3956
0
0
21.6
21168
8205
18.69%
HIGH
21051
20
0
0
0
0
1
245
95
0.00%
LOU
21051
5
39
100
0
0
0.6
100
39
100.00%
HIGH
21053
13
556
1434
0
0
21.9
1434
556
100.00%
HIGH
21057
15
2006
5176
0
0
16.8
5176
2006
100.00%
HIGH
21071
13
785
2026
0
0
7.8
2026
785
100.00%
HIGH
21062
1
1636
4221
0
0
6.7
4221
1636
100.00%
HIGH
21087
7
917
2367
0
0
12.2
2367
917
100.00%
HIGH
21093
55
576
1486
0
0
20.4
29057
11262
. 5.11%
MB)
21107
5
419
1082
0
0
24.5
1082
419
100.00%
HIGH
21111
3
1129
2912
0
0
34.4
2912
1129
100.00%
HIGH
21117
86
1710
4412
0
0
22.3
14730
5709
29.95%
HIGH
21120
37
3636
9380
0
0
49.6
9380
3636
100.00%
HIGH
21128
6
211
544
0
0
6.7
6090
2360
8.94%
KB)
21131
22
2636
6800
1
77
23.1
6877
2666
98.87%
HIGH
21133
66
726
1873
0
0
7.2
16162
6264
11.59%
MED
21136
79
2316
5975
0
0
56.4
27601
10698
21.65%
HIGH
21152
6
365
942
0
0
23.6
2367
917
39.78%
HIGH
21155
9
--
--
0
0
--
-•
100.00%
HIGH
21156
--
47
121
0
0
0.4
121
47
100.00%
HIGH
21161
14
789
2035
0
0
48.7
20(35
78?
100.00%
HIGH
21162
77
422
1089
0
0
15.9
21457
8317
5.07%
KB)
21163
1
252
650
0
0
17.3
3340
1295
19.47%
HIGH
21204
160
0
0
0
0
17.8
41829
16213
0.00%
LOU
21220
82
466
1203
0
0
19.8
33820
13109
3.56%
ffi)
21221
90
174
448
0
0
13.6
42464
16459
1.06%
KB)
21228
99
174
448
0
0
14.8
38727
15010
1.16%
KB)
[Totals for Baltimore Comty/City are provided on Table 2a].
[1] Includes iru-iicipal and privately cwred camtrity water sifplies.
t2] HH = Households
13] ZIP 21093 st±6unes ZIP 21022. These two ZIPs together fall into the HIGH category.
B-2
POPULATION
PRIVATE
PUBLIC
SERVB)
USTs
WELLS
WELLS
BY GU
R 9Q.M
PER SQ.M
PER SO.M
PER SQ.M
3.21
KB)
99.67
HIGH
0.00
LOU
257
HIGH
37.14
HIGH
0.00
LOU
0.00
LOU
0
LOU
5.97
HIGH
70.99
HIGH
0.00
LOW
183
HIGH
20.00
HIGH
0.00
LOU
0.00
LCU
0
LOU
8.33
HIGH
64.60
HIGH
0.00
LOW
167
HIGH
0.59
LOW
25.38
KB)
0.00
LOW
65
KB)
0.89
LOW
119.42
HIGH
0.00
LOU
308
HIGH
1.67
LOW
100.68
HIGH
0.00
LOU
260
HIGH
0.15
LOU
244.19
HIGH
0.00
LCU
630
HIGH
0.57
LOU
75.20
HIGH
0.00
LOU
194
HIGH
4.66
KB) 13]
28.24
HIGH
0.00
LCU
73
MB)
0.20
LOU
17.12
MED
0.00
LOU
44
(CD
0.09
LOU
32.81
HIGH
0.00
LOW
85
HIGH
3.86
m>
76.68
HIGH
0.00
LOU
198
HIGH
0.75
LOW
73.30
HIGH
0.00
LOU
189
HIGH
0.90
LOU
31.49
HIGH
0.00
LOU
81
t€D
0.95
LOW
114.09
HIGH
0.04
LOW
296
HIGH
9.17
HIGH
100.83
HIGH
0.00
LOW
260
HIGH
1.40
LOU
41.06
HIGH
0.00
LOU
106
HIGH
0.25
LOU
15.47
KB)
0.00
LOU
40
KB)
117.25
HIGH
o.oo
LOW
303
HIGH
0.29
LCU
16.20
MB)
0.00
LOU
42
KB)
4.84
KB)
26.54
MED
0.00
LOW
68
KB)
0.06
LOU
14.57
KB)
0.00
LOU
38
KB)
8.99
HIGH
0.00
LOW
0.00
LOU
0
LOU
4.14
WD
23.54
IB)
0.00
LOU
61
KB)
6.62
HIGH
12.77
0.00
LOU
33
KB)
6.69
HIGH
11.73
IB)
0.00
LOU
30
m
-------
Table 2a
BALTIMORE CITY WELL AM) UST DATA
NLMBER
X OF
HH WITH
PRIVATE
PUBLIC
POPULATION
SERVO)
PRIVATE POPULATION PUBLIC
POPULATION
AREA
1985
OF HH
PRIVATE
USTS
UELLS
IELLS
BY GU
> CODE
USTs
UELLS
SERVED
UELLS [1]
SERVED SQ.MILES
POP
1965 ca
IELLS
PER SQ.M
PER SQ.M
PER SQ.M
PER 9Q.M
21201
6
0
0
0
0
1.9
32735
12494
0.00%
LOU
3.16
ie>
0.00
LOU
0.00
LOU
0
LOU
21202
10
0
0
0
0
1.6
24899
9503
0.00%
LOU
6.25
HIGH
0.00
LOU
0.00
LOU
0
LOU
21205
12
0
0
0
0
2.3
21740
8296
0.00%
LOU
5.22
ffi)
0.00
LOU
0.00
LCU
0
LOU
21206
11
0
0
0
0
6.1
54366
20750
0.00%
LOU
1.80
LOU
0.00
LOU
0.00
LOU
0
LOU
21207
112
294
770
0
0
26.6
72918
27831
1.06%
fED
4.21
MB)
11.05
W)
0.00
LOU
29
21208
48
306
802
0
0
24.3
36089
13774
2.22%
to
1.96
LCU
12.59
MB)
0.00
LCM
33
ie>
21209
6
0
0
0
0
3.8
10879
4152
0.00%
LOU
1.58
LOU
0.00
LOU
0.00
LOU
0
LOU
21210
8
0
0
0
0
2.5
690?
2668
0.00%
LOU
3.20
MED
0.00
LCU
0.00
LOU
0
LOU
21211
14
0
0
0
0
2.6
20391
7783
0.00%
LOU
5.38
HIGH
0.00
LOU
0.00
LOU
0
LOU
21212
12
0
0
0
0
4.6
36356
138%
0.00%
LOU
2.61
«D
0.00
LOU
0.00
LOU
0
LOU
21213
4
0
0
0
0
4.2
44126
16842
0.00%
LOU
0.95
LOU
0.00
LOU
0.00
LOU
0
LOU
21214
6
0
0
0
0
2.6
20419
77%
0.00%
LOU
2.31
MB)
0.00
LOU
0.00
LOU
0
LCU
21215
22
0
0
0
0
6.2
74762
28535
0.00%
LOU
3.55
MB)
0.00
LCU
0.00
LOU
0
LOU
21216
9
0
0
0
0
3.2
41711
15920
0.00%
LOU
2.81
MED
0.00
LOU
0.00
LOU
0
LOU
21217
5
0
0
0
0
2.5
49625
18941
0.00%
LOU
2.00
0.00
LOU
0.00
LOU
0
LOU
21218
19
0
0
0
0
4.5
59177
22587
0.00%
LOU
4.22
MED
0.00
LOU
0.00
LOU
0
LCU
21219
58
18
47
0
0
10.6
10366
3566
0.45%
hED
5.47
HIGH
1.70
F€D
0.00
LOU
4
MB)
21222
156
43
113
0
0
12.3
71833
27417
0.16%
12.68
HIGH
3.50
MB)
o.oo
LOU
9
M3)
21223
5
0
0
0
0
2.2
47376
18082
0.00%
LOU
2.27
ffl)
0.00
LOU
0.00
LOU
0
LCM
21224
75
0
0
0
0
8.1
54757
20900
0.00%
LOU
9.26
HIGH
0.00
LOU
0.00
LOU
0
LOU
21225
98
0
0
0
0
8.7
34970
13347
0.00%
LOU
11.26
HIGH
0.00
LOU
0.00
LOU
0
LOU
21226
77
0
0
0
0
11.2
6159
2351
0.00%
LOU
6.88
HIGH
0.00
LOU
0.00
LOU
0
LOU
21227
110
0
0
0
0
25.6
43132
16463
0.00%
LOU
4.30
m
o.oo
LOU
0.00
LOU
0
LCU
21229
34
0
0
0
0
6.6
54957
20976
0.00%
LOU
5.15
MED
0.00
LOU
0.00
LOU
0
LOU
21230
33
0
0
0
0
5.4
41704
15918
0.00%
LOU
6.11
HIGH
0.00
LOU
0.00
LOU
0
LCU
21231
--
0
0
0
0
1.2
23968
9148
0.0%
LOU
0.00
LCU
0.00
LCU
0
LOU
21234
43
0
0
0
0
12.6
61207
23361
0.00%
LOU
3.41
ra
0.00
LOU
o.oo
LOU
0
LOU
21236
54
0
0
0
0
1.5
3103
1184
0.00%
LOU
36.00
HIGH
0.00
LOU
0.00
LOU
0
LOU
21237
68
0
0
0
0
10.5
20892
7974
0.00%
LOU
6.48
HIGH
0.00
LOU
0.00
LOU
0
LOU
21239
1
0
0
0
0
3.2
31724
12108
0.00%
LOU
0.31
LOU
0.00
LCU
0.00
LOU
0
LOU
BALTIMORE COUNTY/CITY TOTAL
AVERAGE
37.59
395
1019
0.02
1
MEDIAN
14.50
0
0
0.00
0
HIGH
160.00
3636
9380
1.00
77
LOU
0.00
0
0
0.00
0
11.74 23430.55 8975 26.51% 4.73 25.55 0.00 64
7.50 21030.00 7974 0.31% 3.21 0.00 0.00 0
56.40 74762.00 28535 100.00% 37.14 244.19 0.04 630
0.00 0.00 0 0.00% 0.00 0.00 0.00 0
LOW
MED
HIGH
[1] Includes ituiicipel and privately owned comuiity water sillies.
123 HH = Households
0.0%
0.2% • 39.8%
98.9% • 100%
0 - 1.98
2.0 ¦ 5.2
5.3 - 37.1
2
28
27
244
0.0 • 0.04
NONE
NONE
4
85
81
630
B-3
-------
APPENDIX C
SOFTWARE AND HARDWARE REQUIREMENTS FOR SCREENING ANALYSIS
Software
Central to the screening tool developed for the IEMP Baltimore Study is
the computer-generated maps of hydrogeologic vulnerability, UST density, and
well density. Therefore, the essential software is a micro-computer mapping
package. There are several mapping packages on the market; the "best one"
depends upon the needs of the user.
Most PC mapping packages are written to be relatively easy to use. Most
are menu driven and come with a demonstration or tutorial program. The
manuals are generally very thorough and include step-by-step directions for
first time users. The user does not have to be a highly skilled computer
programmer; most packages can be learned and used by first time computer users
in a few days. Some basic understanding of computer operation and some
knowledge of the hardware is required for initial use and installation of the
software. Many venders provide installation and technical support if the user
has difficulty with the manufacturer's installation instructions. Almost all
of the software manufacturers provide technical support for registered users
of their software over the phone.
One important mapping capability is the mapping of small geological areas.
We used zip codes as the analytical unit because it it the smallest
geographical area for which we could attain well, population, and UST data.
Many mapping software packages do not have the ability to map zip codes, or
only map zip codes for major metropolitan areas. Of course, if the user
cannot attain data by zip code, then their is no reason to limit the choice of
software packages to those only mapping zip code boundaries. Some mapping
.packages can map the U.S. by census tract, others can map the U.S. by county.
A few packages can only map state boundaries. In order to use this screening
tool at the state or local level, the smallest possible geographic area for
which data can be obtained should be used. Data availability should be the
limiting factor to the geographical unit used in the analysis, not the
boundaries contained in a software package. Data availability should be
verified first, before deciding upon specific software.
Boundary and Data File
Mapping packages generally use two types of files to create maps, boundary
files and data files. Some packages also allow the user to create and display
a text file. The boundary file contains the coordinates for the geographical
boundaries displayed on the maps (i.e., zip code boundaries or county
boundaries).
Data files contain statistical data for each geographical unit the user
wishes to display. The two files are matched by the software through the use
of a common identifier for each individual geographical unit. Boundary files
are usually supplied by the software manufacturer. A few packages allow for
user-created boundary files. Some mapping software packages allow the user to
enter new boundary files with the use of digitizing tablet or a mouse, but
C - 1
-------
most packages only map manufacturer specified boundary files. Most packages
have limited capabilities to map self-generated boundary files, such as
hydrogeologic setting boundaries.
Data files are usually generated by the user. Some packages come with
limited data files created by the manufacturer (i.e., U.S. population by
state). Data is entered into the software either by importing data created in
a spreadsheet or database package, by entering data directly from the
keyboard, or by specifying a proprietary data file provided with the software.
Some mapping packages only allow keyboard entry of data in some cases, all
data must be read from a manufacturer supplied proprietary data base. Mapping
packages that do not allow keyboard entry of data and do not allow data to be
entered using a file created in a separate spreadsheet or database package are
not recommended. These packages limit the user of data provided in files
created by the manufacturer, and do not allow for user- generated data bases.
After specifying the boundary file and data files, the user can specify
the number of data ranges and any limits to data ranges for the statistics
that are to be displayed on the map. For example, the user may specify that
the data be divided into six data ranges, the user may specify that the data
be divided into equal frequency ranges, or the user may specify the limits for
each data range (1-1000, 1001-10,000, etc.). Different shading patterns or
dot patterns are generally available to the user, so that the data range
applicable to each geographical unit mapped is denoted by a separate and
unique shading. Most packages limit the number of data ranges and shading
patterns that can be used per map. More patterns will allow the user greater
flexibility.
Printing
After boundary and data input, the next step is drawing the map on the
screen and then directing the map to an output file or to a printer or
plotter. Most packages can be used on a number of plotters. Not all packages
can be used with printers. The user must therefore choose compatible hardware
and software. The vendor or manufacturer of the software and hardware can
verify compatibility between these two components.
Other Software Considerations
Other features that may or may not be available from a mapping package are
enlarging maps, reducing maps, creating dot density maps as well as shaded
maps, adding text or labels to maps, and editing boundary files. The features
available from each package vary, so the user should inquire about the
capabilities and limitations of several packages before choosing one. We
recommend choosing a package that has reducing capabilities, and allows the
user to create text and add labels.
The cost of any software package varies by geographical area of the
country and by the vendor supplying package. Most micro-computer mapping
packages which meet the demands for the screening analysis cost between §400
and $800.
C - 2
-------
Hardware
A goal of this project was to design a management tool, or screening
analysis, that could be run on a desktop or personal computer. All the
software mentioned above runs on a personal computer, either an IBM PC or a PC
compatible. There are mapping systems available for mini or mainframe
computers. However, the focus of our analysis is for the design of a PC
program.
We recommend that the user attain an IBM XT or AT model computer or
compatible if possible. Most micro-computer mapping software will run on an
IBM PC, however it will run very slowly. The XT and AT models greatly
increase the computational speed and the drawing speed of any software
package. If the user must use an IBM PC, most software manufacturers
recommend the purchase of a math coprocessor for increased computational
speed. In fact, some mapping software requires a math coprocessor. A math
coprocessor is a simple computer chip that sits on the main board of the
computer. It is very easy to install, and costs approximately $200.
Another great advantage of using an IBM XT or AT, is the ability to store
and run the software from a harddisk. most mapping packages use four or five
floppy disks. Running the package on a PC requires a great deal of disk
swapping between program routines. Data must also be stored on a floppy disk
if a PC is used. Using an XT or AT computer allows the user to store the
program and the data on the computer's harddisk. Running the program from a
harddisk makes program and data retrieval and writing faster and much more
convenient. The user does not have to change disks every time a new routine
is envoked.
In order to make hard copies of the maps or data files created with the
mapping system, the user must have a pen plotter or a printer connected to the
computer. As mentioned in the discussion of mapping software, most mapping
software packages support a wide range of plotters, some do not support
printers. If the output device is limited to one already in use at the office
or agency, the software package must be compatible with that device. We
recommend calling the vendor or manufacturer of the software prior to
purchasing it to be sure that the output device is supported by the software.
Some software may support a given printer, but the quality, or resolution, of
the graphics may be less than satisfactory. Again, the user should check with
the vendor or manufacturer before purchasing the software. For top quality
graphics or maps, we recommend a pen plotter. Most pen plotters provide good
resolution graphics and allow the user to produce color maps. Most printers
are restricted to black and white output.
C - 3
-------
APPENDIX D
SENSITIVITY ANALYSIS OP DRASTIC
The DRASTIC report notes that net recharge, soil, and topography are "of
lesser importance for potential pollution evaluations" for USTs because of
their location below ground. The DRASTIC report does not discuss adjustment
of these factors for this lessened importance, and rather states that "weights
may not be changed for any of the DRASTIC factors... (A)ny changes will make
the system invalid." Because of this caution, we did not adjust any DRASTIC
factors for this study.
As a sensitivity analysis, we did recalculate the DRASTIC scores using
only Depth to groundwater, Aquifer media, Impact of the vadose zone, and
hydraulic Conductivity (DAIC). In comparing the rank of the hydrogeologic
settings, we found that they changed only slightly when net recharge, soil,
and topography are not considered.
Factors Considered
Drastic DAIC
Hydrogeologic Median Median
Setting Score Rank Score Rank
A
169.5
1
116
1
B
107.5
13
54
12,13
C
151.5
3
100
3,4
D
160
2
103
2
E
123.5
7
68
7
F
137
6
86
6
G
109
10,11,12
56
11
H
138
5
89
5
I
147
4
100
3,4
II
109
10,11,12
54
12,13
III
114
8
65
9
IV
109
10,11,12
60
10
V
103
14
46
14
VI
112
9
67
8
D - 1
*¦ U.S. Government Printing Office : 1988 -516-OQ2/S0039
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WELL-[»«fiM«»OT^fWUAIflQMJN(fKRBM^afl. MI)
BY ZIP ESSE. AANNBE&naBQBtYpDMNHYLAMBRYLAND
t 76.50,39.14
76.25,39.14 + NORTH t
Hydrageolagic
A Patuxent Formation
B Arundel Clay
0 Potomac Group
E Calvert Formation
F Monmouth Formation
G Marlboro Clay
H Aquia Formation
DRASTIC
Score
164=175
102-113
160
116-131
137
109
131-145
;s>
V
w
Mv\
V
\\\v
\\\\
\v
MM
,
+ 76.50,30.43
0-NO t®"d00-li9
\ V
76.25.38.43 +
|l420-139 ^ 103448355 | §05439-20569
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BY ZIP Ł#flg, AMMEMJ^WNffft.Aj^flVLANO
+ 76.50,39.14
76.25,39.14 + north t
Hydrogeologic DRASTIC
Setting Scopb_
A Patuxent Formation 164-175
B Arundel Clay 102-113
D Potoaac Group 160
E Calvert Formation 116-131
F Monmouth Formation 137
6 Marlboro Clay 109
H Aquia Formation 131-145
76.25,38.43 +
| f§dS^3-20569
+ 76.50,38.43
[~Lnq C^A|@oa4T9 ~ ^§«a®-139
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UNDEGBaOMOBABHBFRaO_lTPHBJS FUfBEWT'EAL MI)
BY ZIP &BQE. AWIilWHE16FIC)0ttBffT.YlCCWIAI:rifLAM^RVLAND
+ 76.50,39.14
76.25,39.14 + north
Hydrogeologic DRASTIC
Setting Score_
A Patuxent Formation 164-175
B Arundel Clay 102-113
D Potomac Group 160
E Calvert Formation 116-131
F Monmouth Formation 137
G Marlboro Clay 109
H Aquia Formation 131-145
+ 76.50,38.43
^ l^P-M ¦ 1^139
l3«fe-159
76.25,38.43 +
BjiB04^79
t
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+ 76.50,39.14
GROUNDWATER POLLUTION POTENTIAL
ANNE ARUNDEL COUNTY. MARYLAND
76.25,39.14 + north t
I
hM
Hydrogeologic
A Patuxent Formation
B Arundel Clay
0 Potonac Group
E Calvert Formation
F Monmouth Formation
G Marlboro Clay
H Aquia Formation
DRASTIC
_Score
164=175
102-113
160
116-131
137
109
131-145
¦..v-'v.
+ 76.50.3B.43
¦ 100-119
120-139 j 140-159
76.25,38.43 +
¦ 160-179
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WELlGOGt^CMISnBNTH'DPCILIfllTTOMtPEHSBDHSyBQ.MI)
BY ZIP tt6US^0JSETUI!DRlftian^BMfllWBRE"raifD(DIREr,p(>BWTYt'MABYLAMD
+ 7G0')j' , }o«1?"
L E,? [ Ht'
f lyrif oqcrr Ioq i c DRASTIC
Selling: Score:
I fiork<>y*,viTT«? MurfiTe 147
II Ml .Wish. Ampli i bo I i I e 103
III Bullirnofe C-nciss 107-1? I
IV Lorh R'tv>n Schisl 102— 11 F»
V S^r[¦ enf 1 rii le 103
VI Pre)Iyhoy 5chist 107-117
A Paluietil Fuinirjlion 164-17fj
B Arundel Cloy 102-115
C Pala[/ic.i> Formal ion MS— 1S7
, NORTH
. 39° 12' 4
SCORE NO ~ 0® 120-139 EQ-tJp-150 H *®-Me
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LEGEND
Hydr p?qeoIogi r. DRASTIC
Sell in-}: Score:
i forl«yjviITe Muriile 147
II Ml.Wonh.Amphibo Ii1e 100
III fi-jl I itnor 4 Gneiss 107-121
IV Lo<¦ l> Rovui Sclii5l 102-IIP
V Serpenlinile Ill J
VI Prellyboy Schist 107-117
A Paluxenf Formation 164- 17fi
0 Arundel Clay 102-113
^ 'oi»_J46— 157
I NORTH
4 7(i0r)J', 3001 ?'
scoB5iife%m"9 0^-139
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BY ZIP MARYLAND
t7ror.v, v}°'i.v
1
vS
WS/
/.
yY
II rrK
/V
7/
h
II Ut.Wish.Amphibolili
III Bo 11 i ntcj r e C-ne is?
DRASTIC
Sror e:
~~M7
109
107-171
102-UK
I(i3
107-117
1G4-175
102-113
C Palojiscu roimal ion 146-157
IV
V
VI
A
B
Lorh ftuvofi Schist
S-)t |">fi1 mil*
Pi <• M yt>(>y S'. h i s I
f'ulu*enl roimollon
Arundel Clny
NORTH
m
4 7f;0r,3' . 3^°l ?*
7F,®?0', 39° 12' 4
SCOF?5 NO BaW119 ~ ofl.#0-139
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GROUNDWATER POLLUTION POTENTIAL
BALTIMORE CITY AND BALTIMORE COUNTY, MARYLAND
47r>or,V , 35°'1.3"
11 o;.q • 3904 5 -4
LECCHti
Hydrogen logic
SelI ing:
I Cor. k«?ysvilli? Mm hi
II HI.Wash.AmphiboIiI
III Baltimore Gneiss
IV torh Rnven Sclti5f
V Ser^eoliniI*
VI Picmyhoy Srhist
A fvjlu
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1. Digitizing maps:
-Originally used MAX-PC and small ditigizei
(polygon data sets)
-For Final used GS-MAP with Calcomp digitizer
at Maryland Geological Survey with IBM-PC
2. Zip Code boundary files used for UST and
groundwater maps
3. Developing and printing maps:
-line segments to polygons
-labels in centers
-printed on HP and Calcomp, switched to ink jet
-sizing, projection
-xeroxing
4. Macintosh for producing maps:
-We used MacPaint to produce B&W maps
-Some Mac programs can produce maps in color
-Much cheaper if you don't need large maps
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