Simulations of Ground-Water Flow 

and Residence Time near 

Woodbury, Connecticut

By J. Jeffrey Starn and Craig J. Brown

National Water-Quality Assessment Program

Transport of Anthropogenic and Natural Contaminants (TANC) 

to Public-Supply Wells

Scientific Investigations Report 2007–5210

U.S. Department of the Interior

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

DIRK KEMPTHORNE, Secretary

U.S. Geological Survey

Mark D. Myers, Director

U.S. Geological Survey, Reston, Virginia: 2007

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Suggested citation:

Starn, J.J., and Brown, C.J., 2007, Simulations of ground-water flow and residence time near Woodbury, Connecticut: 

U.S. Geological Survey Scientific Investigations Report 2007–5210, 45 p.
iii

Foreword

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

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

management of water, biological, energy, and mineral resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical to ensuring long-term availability of water that is safe 

for drinking and recreation and is suitable for industry, irrigation, and fish and wildlife. Population 

growth and increasing demands for water make the availability of that water, now measured in 

terms of quantity and quality, even more essential to the long-term sustainability of our communities 

and ecosystems.

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to 

support national, regional, State, and local information needs and decisions related to water-quality 

management and policy (http://water.usgs.gov/nawqa). The NAWQA Program is designed to answer: 

What is the condition of our Nation’s streams and ground water? How are conditions changing 

over time? How do natural features and human activities affect the quality of streams and ground 

water, and where are those effects most pronounced? By combining information on water chemistry, physical characteristics, stream habitat, and aquatic life, the NAWQA Program aims to provide 

science-based insights for current and emerging water issues and priorities. From 1991–2001, the 

NAWQA Program completed interdisciplinary assessments and established a baseline understanding 

of water-quality conditions in 51 of the Nation’s river basins and aquifers, referred to as Study Units 

(http://water.usgs.gov/nawqa/studyu.html).

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

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

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

monitored for more than a decade, and filling critical gaps in characterizing the quality of surface 

water and ground water. For example, increased emphasis has been placed on assessing the quality 

of source water and finished water associated with many of the Nation’s largest community water 

systems. During the second decade, NAWQA is addressing five national priority topics that build 

an understanding of how natural features and human activities affect water quality, and establish 

links between sources of contaminants, the transport of those contaminants through the hydrologic 

system, and the potential effects of contaminants on humans and aquatic ecosystems. Included are 

topics on the fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream ecosystems, effects of nutrient enrichment on aquatic ecosystems, 

and transport of contaminants to public-supply wells. These topical studies are conducted in those 

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

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

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

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

and effective water-resource management and strategies that protect and restore water quality. We 

hope this NAWQA publication will provide you with insights and information to meet your needs, 

and will foster increased citizen awareness and involvement in the protection and restoration of our 

Nation’s waters. 

The USGS recognizes that a national assessment by a single program cannot address all waterresource issues of interest. External coordination at all levels is critical for cost-effective management, regulation, and conservation of our Nation’s water resources. The NAWQA Program, therefore, 

depends on advice and information from other agencies—Federal, State, regional, interstate, Tribal, 

and local—as well as nongovernmental organizations, industry, academia, and other stakeholder 

groups. Your assistance and suggestions are greatly appreciated.

 Robert M. Hirsch

 Associate Director for Water

v

Contents

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

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

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

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

Previous Investigations........................................................................................................................5

Study Methods ......................................................................................................................................5

Design of Monitoring Well Network .........................................................................................5

Development and Application of Simulation Models ............................................................5

Geohydrologic Setting...................................................................................................................................5

Geology...................................................................................................................................................5

Bedrock .........................................................................................................................................9

Glacial Deposits ...........................................................................................................................9

Hydrology .............................................................................................................................................11

Sources of Ground Water.........................................................................................................12

Ground-Water Flow...................................................................................................................13

Water Use ...................................................................................................................................13

Geohydrologic Units...........................................................................................................................13

Simulations of Ground-Water Flow and Residence Time .....................................................................16

Large-Area Simulation of Ground-Water Flow..............................................................................16

Small-Area Simulation of Ground-Water Flow ..............................................................................16

Model Characteristics ..............................................................................................................16

Model Domain and Grid-Cell Dimensions.....................................................................16

Boundary Conditions and Model Stresses...................................................................18

Model Hydraulic Parameters, Observations, and Observation Weights.................18

Estimation of Model Parameters.............................................................................................20

Simulated Water Budget ..........................................................................................................23

Simulation of Ground-Water Residence Time................................................................................27

Residence Time of Water in Monitoring Wells .....................................................................27

Residence Time of Water in PSW-1........................................................................................27

Residence Time, Land Cover, and Water Quality..................................................................30

Model Uncertainties and Limitations ..............................................................................................40

Summary and Conclusions.........................................................................................................................43

Acknowledgments.......................................................................................................................................43

References Cited..........................................................................................................................................44
vi

Figures

1–5. Maps showing—

1. Location of large-area simulation and small-area simulation models .......................4

2. Land cover and public-supply wells in 2002....................................................................6

3. Locations of all observation and monitoring wells used in this study........................7

4. Locations of monitoring wells installed for this study...................................................8

5. Bedrock contours and surficial geology........................................................................10

6. Cross section showing geohydrologic units..........................................................................11

7–8. Graphs showing—

7. Monthly and smoothed water-level altitude in observation well WY1.....................12

8. Withdrawals from well PSW-1 and water-level altitude in well WY1, 

1997 to 2002.........................................................................................................................14

9. Map showing the domain of the SAS model, recharge rates, and public-supply 

wells..............................................................................................................................................17

10. Graphs showing weighted simulated residuals, weighted observed water levels 

and streamflow, weighted simulated water levels and streamflow, and unweighted 

observed and simulated water levels for the small-area simulation model.....................22

11. Diagram showing water budget for the small-area simulation ..........................................25

12–13. Maps showing—

12. Simulated losing stream reaches in the small-area simulation model ....................26

13. Contributing recharge area to well PSW-1 and ground-water residence time......29

14–21. Graphs showing—

14. Cumulative frequency distribution and frequency distribution of simulated 

residence times..................................................................................................................31

15. Relation of residence time, land use, and source of water for PSW-1 ....................34

16. Relation of residence time, land use, and source of water for cluster of 

shallow, medium, and deep wells WY71, WY70, and WY69........................................35

17. Relation of residence time, land use, and source of water for cluster of 

shallow, medium, and deep wells WY74, WY73, and WY72........................................36

18. Relation of residence time, land use, and source of water for cluster of 

shallow and deep wells WY76 and WY75......................................................................37

19. Simulated and predicted trend in concentration of nitrate in PSW-1 ......................38

20. Simulated and predicted trend in concentration of dissolved solids in PSW-1......39

21. Number of septic systems in the contributing recharge area to well PSW-1.........40

22–23. Maps showing—

22. Probabilistic contributing recharge area to well PSW-1 for the small-area 

simulation model................................................................................................................41

23. Probabilistic contributing recharge area and land parcels for the small-area 

simulation model................................................................................................................42
vii

Tables

1. Simulated pumping rates based on reported water withdrawals at public-supply 

wells in Woodbury, Connecticut ..............................................................................................13

2. Specified values of hydraulic properties and definition of parameters for the 

small-area simulation model.....................................................................................................15

3. Estimated optimal parameter values for the small-area simulation model ......................21

4. Statistics of residuals (observed minus simulated values) for the small-area 

simulation model.........................................................................................................................21

5. Simulated water budget for the small-area simulation........................................................24

6. Tritium/helium age and simulated residence time at monitoring wells in the 

small-area simulation model.....................................................................................................28

7. Selected characteristics of the contributing recharge area to well PSW-1....................32

8. Relation of land-cover and land-use categories as used in this report............................32

9. Percentage of backward-tracked particles started from monitoring well screens 

by land-use category for the small-area simulation model.................................................33

10. Median concentrations of selected constituents used to represent various 

land uses ......................................................................................................................................38
viii

Conversion Factors, Abbreviations, and Datums

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

Area

square kilometer (km2) 247.1 acre

hectare (ha) 2.471 acre

hectare (ha) 0.003861 square mile (mi2

)

Volume

cubic meter (m3) 264.2 gallon (gal)

Flow rate

meter per day (m/d) 3.281 foot per day (ft/d)

centimeter per year (cm/yr) 0.3937 inch per year (in./yr)

cubic meter per second per square 

kilometer [(m3/s)/km2]

91.49 cubic foot per second per square mile 

[(ft3/s)/mi2]

cubic meter per day (m3/d) 35.31 cubic foot per day (ft3/d)

cubic meter per day (m3/d) 264.2 gallon per day (gal/d)

gallon per minute (gal/min) 0.06309 liter per second (L/s)

Load

gram per day (g/d) 0.002204 pounds per day (lbs/d)

Hydraulic conductivity

meter per day (m/d) 3.281 foot per day (ft/d)

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

(NAVD 88).

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

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

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

or micrograms per liter (μg/L).
Abstract

Water withdrawn for public use from glacial stratified 

deposits in Woodbury, Connecticut, is a mixture of water 

from different source areas, each having a characteristic 

water-quality signature. The physical processes leading to this 

mixture were explored using a numerical model to simulate 

steady-state ground-water source areas and residence times 

for a public water-supply well (PSW-1) in Woodbury. Upland 

areas contribute water to the well that is primarily from undeveloped and agricultural land. Valley bottoms contribute water 

to the well that is primarily from developed land. From 1985 

to 2002, 6 percent of the contributing recharge area to the well 

changed from agricultural and undeveloped to developed land. 

The pattern of recharge areas and land use causes stratification 

of ground water by residence time and by characteristic water 

quality, which is related to land use. As land use changes with 

time, the water-quality signature of developed land moves 

deeper into the aquifer. Predicted nitrate concentrations 

decreased from 1985 to 1995 because of the conversion from 

agricultural land to developed land, but then began to increase 

after 1995 because of the conversion of undeveloped land to 

developed land. Total dissolved solids concentrations, on the 

other hand, increased from 1985 to 2002 because agriculture 

is associated with lower total dissolved solids concentrations 

than is developed land. 

About 40 percent of the water withdrawn from PSW-1 

originated as upland recharge before flowing through glacial 

deposits in the valley. About 44 percent of the water originated 

as recharge in either fluvial deposits (mean residence time 

7 years) or deltaic deposits (mean residence time 4 years). 

About 16 percent of the water originated as recharge through 

storm drains with ground-water discharge (often known as 

“dry wells”). The residence time for water that originated as 

recharge in dry wells is 2 to 4 years, and the mean residence 

time is 3 years. Dry wells are a fast pathway for water to 

enter the aquifer and provide a significant amount of water to 

PSW-1; therefore, PSW-1 is more susceptible to contamination in runoff from the commercial area, which enters the dry 

wells, than to recharge elsewhere in the area.

Water withdrawn from a well is a mixture of waters with 

different residence times, and a single residence time does 

not fully characterize the susceptibility of the well to recent 

contamination. The mean simulated flow-weighted residence 

time in PSW-1 is 6 years, which compares reasonably well 

with the apparent residence time measured using tritium/

helium data of 6 and 7 years (samples for age dating were 

collected twice from this well). There are at least two modes 

to the distribution of ages, one mode with residence times less 

than 5 years and one mode with residence times greater than 

5 years. About 34 percent of the ground-water in PSW-1 is 

younger than 5 years and 56 percent of the water is from 5 to 

9 years. 

The estimated nitrate loading rate from a singlefamily septic system is 18 grams per day. If each household 

in the contributing recharge area contributes nitrate at that 

loading rate to the well PSW-1, each additional septic system in the contributing recharge area is responsible for a 

0.045-milligram-per-liter increase in nitrate at PSW-1 at the 

current pumping rate. 

Uncertainty in the predicted contributing recharge area 

can be propagated through the analysis using a Monte Carlo 

technique. There is a greater degree of certainty in the delineation of the recharge area near the well, and as one moves 

from the well toward the recharge areas, the uncertainty in the 

model increases. The area that possibly contributes water to 

the well using the Monte Carlo model is much larger than the 

recharge area delineated using the optimal parameter estimates. Within the probabilistic recharge area, the number of 

septic systems could be twice the number initially estimated.

Introduction

Aquifers in Connecticut are a valuable natural resource 

and a major source of public drinking water. Reliance on 

ground water is expected to increase because opportunities to 

develop new surface-water supplies are diminishing due to the 

rising cost of land and increasing development (Connecticut 

General Assembly, 2005). In Connecticut, about 11 percent 

of the public water supply is from ground water; this, combined with the fact that almost all self-supplied water is from 

residential wells, means that a total of 32 percent of the state’s 

drinking-water supply is from ground water. In addition, many 

Simulations of Ground-Water Flow and Residence Time 

near Woodbury, Connecticut

By J. Jeffrey Starn and Craig J. Brown
2 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

schools, small businesses, churches, restaurants, and camps 

rely on ground water (about 165,000 people; sum of transient 

and non-transient non-community water systems; Connecticut 

Department of Public Health, 2007a). 

Although population growth in Connecticut has been 

slow in the past decade, the changing distribution of people 

has implications for the quality of ground water. Connecticut’s 

population grew from 3.3 million in 1990 to 3.4 million in 

2000 (Connecticut State Comptroller, 2007). This 3.6-percent 

population gain was the fourth lowest among all states; 

however, the modest gain was not uniformly distributed. The 

current trend in Connecticut is toward decreasing population 

in cities and increasing population in more recently developed 

areas. For example, the projected growth rate for 2005 to 2015 

for suburban areas is twice that for urban areas (University 

of Connecticut, 2007a). The state’s five largest cities had an 

overall population decline of 5.5 percent in 2002, whereas 

58 towns with an average population of 11,000 grew by more 

than 10 percent during the last decade (Connecticut State 

Comptroller, 2007). Rural and suburban areas are less likely to 

be served by large public-water suppliers and are more likely 

to rely on small water suppliers or on self-supplied water, both 

of which are more likely to use ground water as the source of 

drinking water. 

As a result of the redistributed population, the land cover 

of the state is changing. From 1985 to 2002, high-density 

development, such as building, parking lots, and roads, 

increased by 4.9 ha per day while forest cover decreased by 

7.3 ha per day (University of Connecticut, 2007b). Developed 

land expanded by 308 km2 and forest land decreased by 

440 km2 during that time period. Developed land increased 

by 15 percent from 1985 to 2002, roughly twice the rate of 

population increase. The density of new development is lower 

than in the past so more land per person is required (University 

of Connecticut, 2007b). In 2002, 56 percent of the state was 

forested and 19 percent was developed.

The link between land use and the quality of shallow 

ground water has been well documented (Grady, 1994; Grady 

and Mullaney, 1998). In particular, there are differences in 

water quality in shallow ground water beneath undeveloped 

areas, tilled and untilled agricultural areas, sewered and 

unsewered residential areas, and commercial and industrial 

areas (Grady, 1994). Contaminants have been detected in 

52 percent of all public drinking-water sources in Connecticut, 

but the Maximum Contaminant Levels (MCLs) for drinking water established by the U.S. Environmental Protection 

Agency are rarely exceeded (with the exception of microbiological contaminants). Although less attention has been paid to 

the relation between microbiological contamination and land 

cover, a total of 454 MCL violations were issued to publicwater systems during calendar year 2005, of which 393 were 

for microbiological contamination. Nitrate was the prevalent 

non-microbiological contaminant detected in public-supply 

wells. The MCL for nitrate is 10 mg/L (reported as nitrogen 

concentration). Samples from 36 percent of all community 

water systems contained nitrate concentrations from 1 to 

10 mg/L in 2005. Eight percent of systems had detections 

of volatile organic compounds (VOCs) in 2005. The most 

commonly detected VOCs in 2005 were methyl tert-butyl 

ether (MTBE) and trichloroethylene (TCE) (Connecticut 

Department of Public Health, 2007b). Other contaminants 

that were found above their MCL in 2005 include net grossalpha radiation, radium 226, radium 228, uranium, chloride, 

total haloacetic acids, and total trihalomethanes (Connecticut 

Department of Public Health, 2007c). Some of these same 

contaminants (nitrate, VOCs, and trihalomethanes) in shallow 

ground water are related to land use (Grady, 1994). 

There is a cost of treatment and remediation associated 

with high levels of organic contaminants in ground water. 

For example, removal of tetrachloroethylene from ground 

water to levels below the MCL can cost from $11 to $73 per 

household per year for medium-sized water systems (Connecticut Department of Public Health, 2007c), and the cost 

per household would be higher for smaller systems. In 2005, 

293 systems in 149 towns had public-supply wells in which 

organic contaminants were detected that were either below 

the MCL or for which there was no MCL. Sixty-seven public 

drinking-water systems in the state in 2005 were treating their 

water to remove organic contaminants. After this treatment, 

all 67 suppliers provided drinking water that meets all legal 

standards (Connecticut Department of Public Health, 2007c). 

Of the organic chemicals detected in Connecticut’s public 

drinking-water supplies, benzene, bromodichloromethane, 

carbon tetrachloride, chloroethane, chloroform, 1,2-dichloroethane, dichloromethane, 1,2-dichloropropane, naphthalene, 

and TCE are considered known or probable carcinogens, and 

1,1-dichloroethane, p-dichlorobenzene, MTBE, 1,1,2-trichloroethane are considered possible human carcinogens (Connecticut Department of Public Health, 2007c).

Connecticut has a comprehensive and coordinated 

system of land-use regulation that includes provisions to 

protect public-drinking water in wells that tap glacial stratified 

deposits. The provisions, administered by the Connecticut 

Departments of Public Health (DPH) and Environmental 

Protection (DEP), identify vulnerable ground water and 

protect ground-water supplies. A source-water assessment, 

conducted by the Connecticut Department of Public Health 

in 2003, revealed that 20 percent of public-supply wells that 

serve more than 1,000 people ranked as highly susceptible to 

contamination. These wells were considered susceptible in 

part because they are in an area of moderate to high density of 

potential contaminant sources, are in an area of high-density 

development, and have a previous history of the detection 

of contaminants (Connecticut Department of Public Health, 

2007b). Sixty percent of the potential contaminant sources 

that were identified in the assessment involve fuel storage or 

automotive-related activity. 

One way to mitigate the effects of contamination is 

to protect the source of the water. In Connecticut, the DEP 

manages the Aquifer Protection Program. Preliminary 

aquifer-protection areas have been delineated at all 122 

active community well fields. Final aquifer-protection 
Introduction 3

mapping, conducted using techniques similar to those used 

in this study, is complete at 27 well fields, with an additional 

64 delineations underway as of March 2007 (Connecticut 

Department of Environmental Protection, 2007). Land use will 

be regulated within the aquifer-protection areas. Regulated 

activities include businesses that use hazardous materials, 

pesticides, and petroleum products. These businesses include 

some manufacturing industries, chemical wholesale storage 

facilities, gasoline stations, automobile service stations, dry 

cleaners, and furniture strippers (Connecticut Department of 

Environmental Protection, 2007). 

In 2001, the U.S. Geological Survey’s National WaterQuality Assessment (NAWQA) Program began an intensive 

study to assess the vulnerability of public-supply wells to 

contamination from a variety of compounds (Eberts and 

others, 2005). This study, referred to as the TANC study—

for Transport of Anthropogenic and Natural Contaminants—

builds on previous NAWQA studies from 1991 to 2001 that 

found low levels of multiple contaminants in about 90 percent 

of samples from shallow ground-water-monitoring wells in 

urban areas across the Nation. One goal of the TANC study is 

to synthesize and compare data and simulation results among 

TANC study areas in Woodbury, Connecticut; Modesto, 

California; Tampa, Florida; and York, Nebraska. To perform 

this analysis across multiple scales, the TANC study design 

called for development of nested simulation models of groundwater flow. A Large-Area Simulation (LAS) model of groundwater flow in the aquifer in the Pomperaug River drainage 

basin (Lyford and others, 2007) was developed to estimate 

areas contributing recharge and ground-water residence times 

to many public water-supply wells over a 128-km2 area in the 

Pomperaug River Basin, Connecticut (fig. 1). A Small-Area 

Simulation (SAS) model within the LAS boundaries is a more 

detailed model (fig. 1).

Purpose and Scope

This report documents the SAS model in the TANC study 

at Woodbury, Connecticut. The results presented here will be 

the basis for comparing this study area with other TANC study 

areas; those areas and study results will be reported elsewhere. 

This report describes (1) the approaches used to refine the 

LAS model developed by Lyford and others (2007), (2) apparent ground-water residence times using the tritium/helium 

method, (3) construction and calibration of the SAS model 

used to simulate ground-water residence time, and (4) results 

from the SAS model and a comparison of the measured and 

simulated ground-water residence times. Details of the water 

quality in the study area will be discussed in a separate report 

(C.J. Brown, U.S. Geological Survey, written commun., 2007).

The study area discussed in this report is the estimated 

contributing recharge area to one public water-supply well 

(referred to herein as well PSW-1). In order to minimize the 

effects of the model boundaries on the conclusions drawn from 

the SAS model, ground-water flow was simulated in an area 

larger than the contributing recharge area. This area is referred 

to herein as the SAS area. Data collection was focused on a 

smaller area within the SAS area in and around the contributing recharge area to well PSW-1. 

Description of Study Area

The SAS area is in the Connecticut, Housatonic, 

and Thames River Basins NAWQA Study Unit (fig. 1). 

Characteristics of the aquifer system selected for this study are 

similar to those of many other valley-fill-aquifer systems in 

the Eastern Hills and Valley Fills region, defined and described 

by Randall (2001), which encompasses much of southern New 

England, northern New Jersey, and eastern New York. 

The SAS area covers about 15 km2 of the Pomperaug 

River Basin in the west-central Connecticut towns of Woodbury and Southbury. The major river valley trends north-south 

and is bounded on the east and west by till-covered bedrock 

uplands drained by numerous perennial streams. Streams in 

upland areas are oriented mostly from east to west on the eastern side and northwest to southeast on the northern and western sides. Ponds have been constructed on several tributary 

streams. Altitudes range from about 30 m near the confluence 

of the Pomperaug River with the Housatonic River to about 

280 m at places on the basin divide. 

Precipitation in the Pomperaug River Watershed averages 

about 117 cm/yr (Randall, 1996). Basin runoff measured in 

the Pomperaug River at Southbury, Connecticut, has averaged 

60 cm/yr from 1933 to 2001 (Morrison and others, 2006). The 

balance of about 57 cm/yr is lost mainly to evapotranspiration 

or is transferred out of the basin for use as drinking water in 

other basins.

Changes in land use alter the quality and availability of 

water, so it is useful to have some understanding of how land 

use and population have changed in the past. This is especially 

true for ground water, which can have a long residence time 

in the environment, thus carrying the imprint of past land 

use. The population of Woodbury was 2,150 people in 1850 

and 2,564 in 1950, an increase of 41 people per decade 

(U.S. Census Bureau, 2007a). From 1950 to 1990, the population grew steadily to 8,131 people, an average increase of 

1,390 people per decade. From 1990 to 2000, the rate of population growth decreased to about 1,065 people per decade. The 

rate of growth for Woodbury is projected to decrease slightly 

from 2000 to 2020 (Connecticut Office of Policy and Management, 2007). 

Land use in the Pomperaug River Watershed has changed 

over the past 50 years from primarily undeveloped or agricultural lands to residential, commercial, and light-industrial 

areas. An 1822 map of the study area shows that the SAS area 

was then predominantly agricultural or undeveloped, with 

two churches, one saw mill, one fulling mill (for processing 

cloth), a grist mill, and a small number of houses. A 1934 

aerial photograph shows that the valley bottom in the SAS area 

was predominantly agricultural. Uplands were a mixture of 
4 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Southbury

Woodbury

Oxford

Watertown

Roxbury

Bethlehem

Middlebury

Morris

Washington

Newtown

Thomaston

Naugatuck

Waterbury

Litchfield

Beacon Falls

Bridgewater

73°15' 73°10' 73°05'

41°40'

41°35'

41°30'

41°25'

Small-Area Simulation area

Large-Area Simulation area

EXPLANATION

MAINE

NEW

HAMPSHIRE

VERMONT

NEW YORK

MASSACHUSETTS

CONNECTICUT RI

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000 

Projection: State Plane Feet Zone 3526

Boundary of the National Water-Quality

Assessment’s Connecticut, Housatonic, and 

Thames River Basins Study Unit

Housatonic River

Pomperaug River

MILES

KILOMETERS

0 1 2 3 4

0 1 2 3 4

Figure 1. Location of large-area simulation and small-area simulation models, Woodbury, Connecticut.
Geohydrologic Setting 5

wooded and partially cleared land that may have been pasture. 

From 1985 to 2002, Woodbury lost about 196 ha of deciduous forest (out of a town area of 9,510 ha) to development 

and land clearing (which may be a precursor to development; 

University of Connecticut, 2003). In 2002, the SAS area was 

more developed than the rest of the town (16 and 10 percent, 

respectively; fig. 2), but the patterns of land use were similar 

(commercial development primarily in the valley, residential 

primarily in the uplands). Only 12 percent of the SAS area was 

used by agriculture (fig. 2). 

Currently (2006), residential areas are unsewered and 

are characterized by low- to medium-density housing (Lyford 

and others, 2007). Agricultural lands are mostly in the upland 

areas. Industrial uses are limited and include small, modern, 

high-tech industries. Upland areas are largely forested with 

scattered residences on 0.4 ha or larger lots. Most water for 

public supply is obtained from wells completed in valley fill, 

although four condominium complexes in the uplands obtain 

water from wells completed in bedrock. Numerous residents 

in the valley and uplands obtain water from private wells for 

domestic uses, including lawn irrigation. Most of the water 

pumped from wells is used within the SAS area. Wastewater 

is returned to the ground through private septic systems and 

on-site treatment facilities. 

Previous Investigations

Ground-water conditions in the Pomperaug River Watershed have been described by Meinzer and Stearns (1929), 

Mazzaferro (1986a), Mazzaferro (1986b), Grady and Weaver 

(1988), Starn and others (2000), and Lyford and others (2007). 

In addition, the surficial geology has been described by Pessl 

(1970), and much work that has been done on the bedrock 

geology is summarized by Burton and others (2005). The work 

by Lyford and others (2007) describes the LAS model that is 

the basis for the SAS model in this report. 

Study Methods

The SAS model of ground-water flow was constructed 

and calibrated using data from a monitoring-well network that 

was installed for this study. Advective particle tracking was 

used to estimate contributing recharge areas to monitoring 

wells and water-supply wells and to estimate the distribution 

of apparent ground-water residence time.

Design of Monitoring Well Network

The design, installation, and sampling of the monitoringwell network (figs. 3 and 4) will be described in detail in a 

separate report (C.J. Brown, U.S. Geological Survey, written commun., 2007). Selection of monitoring well locations 

(except for wells WY35 and PSW-1, which existed prior to 

this study) was based on a preliminary simulation model, the 

goal of which was to identify a ground-water-flow path in the 

contributing recharge area to PSW-1 (figs. 3 and 4). Subsequent uncertainty analysis showed that there was a good probability that the source area to PSW-1 included an area off the 

chosen flow path. Additional wells were drilled to include the 

off-flow-path areas. In most locations, a nest of two to three 

wells was installed so that different levels within the aquifer 

could be monitored and sampled. At some locations, bedrock 

wells were drilled to characterize the contribution of flow from 

bedrock to the water produced from well PSW-1. 

Development and Application of 

Simulation Models

Steady-state ground-water flow was simulated using the 

computer program MODFLOW-2000 (Harbaugh and others, 

2000; Hill and others, 2000), which uses a finite-difference 

method to simulate three-dimensional ground-water flow 

through a porous medium. MODFLOW-2000 uses a non-linear 

regression technique to estimate parameter values that result in 

the best match between observed and simulated values. This 

model, when combined with boundary and initial conditions, 

describes three-dimensional ground-water flow in a heterogeneous and anisotropic medium, provided that the principal 

axes of hydraulic conductivity are aligned with the coordinate 

directions. Source-water areas and ground-water residence 

times were delineated using the particle-tracking computer 

program MODPATH (Pollack, 1994). 

Geohydrologic Setting

The ground-water-flow system in the glaciated Northeast 

is composed primarily of two materials: bedrock and glacial 

deposits. Although there are large variations of hydrologic 

properties within each material, the greatest difference with 

regard to ground-water flow is between them. Ground-water 

flow in bedrock takes place in fractures in the rock, and flow 

in the glacial deposits is through the pore spaces between 

mineral grains. 

Geology

Bedrock underlies the entire study area and is one of 

three types: crystalline rock (primarily gneiss and schist), 

basalt, or sedimentary rock (primarily arkose and shale). 

Glacial deposits overlie bedrock everywhere except locally 

where bedrock crops out at the surface. Glacial deposits are 

either till or glacial stratified deposits.
6 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 2. Land cover and public-supply wells in 2002 in part of Woodbury, Connecticut.

73°13' 73°12' 73°11'

41° 32'

41° 31'

Land cover from Center for Land Use Education and 

Research, The University of Connecticut, December 2003

0 0.5 1 KILOMETER

0 0.5 1 MILE

EXPLANATION

2002 Land cover

Developed

Turf and grass

Other grasses and agriculture

Deciduous forest

Coniferous forest

Water

Forested wetland

Non-forested wetland

Barren

Public-supply well

UPLANDS

UPLANDS

VALLEY

VALLEY

UPLANDS

UPLANDS
Geohydrologic Setting 7

Figure 3. Locations of all observation and monitoring wells used in this study, Woodbury, Connecticut.

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WY39

WY33

WY1

WY36

WY34

WY40

WY40

BR48

BR47

BR1

BR3

BR22

BR20

BR24

BR23

BR25

BR29 BR28

BR33

BR31

BR36

BR414

BR37

BR387

BR403

BR426

BR388

BR423

BR415

BR53

BR52

BR57 BR61

BR209

BR67

BR62

BR62

BR32

BR43

BR215

BR285

BR368

BR371

BR385

BR372

BR320

BR386

BR214

BR328

BR39

BR318

BR369

BR342

BR323

BR319

BR322

BR321

BR367

BR366

PSW-4

PSW-3

PSW-5

PSW-1

PSW-2

PSW-1

WY97

WY96

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

Pomperaug River

41° 32'

41° 31'

73°13' 73°12' 73°11'

0 0.5 1 KILOMETER

0 0.5 1 MILE

Location of observed hydraulic head or streamflow

Public-supply well,

and number

Outline of area shown

in figure 4 !

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#

Group 1 wells (labeled on figure 4)

Group 2 monitoring wells, and number

Group 3 monitoring wells, and number

Streamflow measurement

EXPLANATION

South Brook
8 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 4. Locations of monitoring wells installed for this study, Woodbury, Connecticut.

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WY89

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WY94

WY93

WY69

WY99

WY97

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WY81

WY83

WY85

WY86

WY84

WY87

WY35 WY100

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WY80

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WY70

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WY102

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WY34

BR1

BR3

BR33

BR53

BR37

BR61

BR39

BR366

73°12'40" 73°12'20" 73°12'00" 73°11'40"

41° 31'40"

41° 31'20"

WY40

BR62

PSW-1

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

PSW-3

PSW-4

PSW-1

WY89

Pomperaug

River

Location of observed hydraulic head or streamflow Public-supply well,

and number !

!

!

#

Group 1 wells, and number 

Group 2 monitoring wells, and number

Group 3 monitoring wells, and number

Streamflow measurement

EXPLANATION

South

Brook

0 0.5 1 KILOMETER

0 0.5 1 MILE
Geohydrologic Setting 9

Bedrock

Geologic mapping by Burton (2006) identified bedrock 

in the SAS area of two distinct ages: early Paleozoic and 

Mesozoic. Early Paleozoic rocks are present primarily in the 

uplands on the eastern side of the SAS area and consist of 

schist and gneiss of the Taine Mountain Formation and Waterbury Gneiss. The Mesozoic and Paleozoic rocks are separated 

by a fault that runs generally north-south and passes between 

wells WY86 and WY87. Paleozoic rocks close to the fault are 

highly fractured, but the degree of fracturing likely decreases 

away from the fault. These fractures are nearly vertical and 

tend to parallel the fault. The Mesozoic Orenaug Basalt underlies most of the Pomperaug River valley in the study area. 

Fractures in the Orenaug Basalt tend to be mineralized with 

calcite, which decreases their permeability; however, at least 

five near-vertical, north-south faults in the Orenaug Basalt 

may increase its permeability. Another basalt unit, the South 

Brook Basalt, is highly fractured and may be more permeable than the surrounding rocks. Mesozoic rocks also include 

fractured arkose and shale. 

Starn and Stone (2005) identified three types of 

bedrock fractures in Connecticut. The first type—vertical 

fractures—provides the pathways for ground-water flow 

vertically into deeper fractures. The second type of fractures 

comprise nearly horizontal stress-relief fractures that generally 

diminish in number and aperture with depth. Ground water can 

potentially flow in any direction in this type of fracture. The 

third type of fractures cross-cuts vertical fractures and may 

connect them, but generally is not as laterally continuous as 

layer-parallel fractures. 

The bedrock surface in the SAS area is characterized 

by two low areas separated by a buried ridge (figs. 5 and 6) 

of what probably is a resistant layer in the Orenaug Basalt 

(Burton and others, 2005). Orenaug Basalt is exposed in the 

streambed of the Pomperaug River and at several hillside 

locations near the village of Pomperaug. The buried ridge 

itself is bounded by north-south trending faults. This buried 

ridge probably provided sufficient resistance to the flow of 

glacial ice so that the retreating ice margin remained at this 

position for some time. The low area on the bedrock surface to 

the northwest of the buried ridge is underlain by easily eroded 

sedimentary rock. The low area on the bedrock surface to the 

southeast of the buried ridge is underlain, at least in part, by 

easily eroded sedimentary rock and basalt. Faulting also could 

contribute to the low bedrock altitude in this area. 

Glacial Deposits

Two major types of glacial deposits are in the SAS area: 

till and glacial stratified deposits. The differences in composition and distribution of these two types stem from their mode 

of deposition. Till was deposited directly by glacial ice; is 

generally nonlayered and nonsorted; and contains a wide range 

of grain sizes from clay to large boulders. Glacial stratified 

deposits were laid down by glacial meltwater and are composed of well to poorly sorted layers of sediment including 

gravel, sand, silt, and clay. Till blankets the bedrock surface in 

most places in the uplands and commonly is present beneath 

glacial stratified deposits in valleys. Glacier meltwater was 

concentrated in valleys as the ice margin retreated; therefore, 

glacial stratified deposits occur predominantly in valleys. 

Till deposited by glacier ice is a nonlayered, nonsorted silty sand or clayey silt-sand mixture containing 5 to 

40 percent pebbles, cobbles, and boulders (Melvin and others, 

1992). Till deposits in the SAS area include several types: 

(1) compact till of subglacial origin of Illinoian age that is 

the predominant material in glacially smoothed hills known 

as “drumlins,” (2) compact to loose sandy late Wisconsinanage till that overlies the lower till in drumlins; and (3) a loose 

sandy, surface till of late-Wisconsinan glacial ablation (melt) 

origin (Stone and others, 2005). Drumlin till is moderately to 

very compact and probably has a lower hydraulic conductivity 

than the overlying sandy till because of compaction beneath 

the glacial ice. It commonly is finer grained and less stony 

than the sandy till. The compact till in drumlins is as much as 

51 m thick in the SAS area and is generally covered by a thin 

(less than 4–5 m thick) veneer of sandy till (Stone and others, 

2005). The lower part of the sandy till is compact due to its 

deposition beneath glacial ice. Compact sandy till commonly 

is found on north-facing slopes of bedrock hills where it may 

be as much as 10 m thick. The upper part of the sandy till is 

non-compact, loose, bouldery surface till that forms a thin 

(less than 2 m thick) discontinuous veneer overlying compact 

sandy till and bedrock.

The laboratory-determined hydraulic conductivity of 

till has a strong relation to grain size (Stephenson and others, 

1988, p. 306), particularly to the clay content. Hydraulic 

conductivities are uniformly low above a threshold content 

of 15 to 20 percent clay. The clay content of sandy lateWisconsinan tills in southern New England ranges from less 

than 1 percent to 7 percent, whereas the content of clay-sized 

particles in drumlin till ranges from 11 to 38 percent (Melvin 

and others, 1992). 

The distribution of glacial stratified deposits in the 

SAS area fits general models of glacial sedimentation in 

southern New England described by Stone and others (2005) 

and by Randall (2001). Glacial stratified deposits consist of 

overlapping deposits (morphosequences) that begin at an icemargin position and grade to the water levels in a glacial lake 

or pond downstream from the ice. Morphosequences in the 

SAS area include collapsed ice-marginal material deposited 

in kame terraces (Pessl, 1970), and, on the basis of drilling 

done as part of this study, these deposits overlie compact till. 

Deltaic deposits in the center of the valley are remnants of 

an ice-marginal delta or subaqueous fan that was deposited 

in glacial Lake Pomperaug. The delta or fan is referred to 

herein as a delta for simplicity. Deltaic deposits consist of 

well-sorted, layered, non-collapsed coarse and medium sand 

(Pessl, 1970). Collapsed ice-marginal fluvial deposits in 

the delta extend to the northeast, where they are overlain by 

deltaic deposits of a younger morphosequence. The surface 
10 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

190

180

200

170

200

160

Geohydrologic units

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000 

Projection: State Plane Feet Zone 3526

Geology modified from Stone and others (2005); 

Pessl (1970); and Rodgers and others (1985)

Lake-bottom deposits

Marsh or swamp

Deltaic deposits

Deltaic over 

fluvial deposits

Fluvial deposits

Fluvial deposits 

over compact till

Non-compact till

Compact till

Altitude of top of bedrock—contour

interval, 10 feet

Line of geologic section (see

figure 6)

Fault

A A’

Altitude of topography—contour

interval, 50 feet

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PSW-1

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A

73°13' 73°12' 73°11'

41° 32'

41° 31'

0 0.5 1 KILOMETER

0 0.5 1 MILE

EXPLANATION

Figure 5. Bedrock contours and surficial geology, Woodbury, Connecticut.
Geohydrologic Setting 11

of the younger deposits is at a higher altitude than the surface 

south of the delta, indicating that these surfaces were graded to 

different lake levels (fig. 6). The delta was mined for sand and 

gravel sometime between 1970 and 1985 and no longer exists 

as a landform, but the lower stratigraphic section of the delta 

still remains. Fine-grained lake-bottom sediments are present 

in the northwestern part of the SAS area. 

Hydrology

As discussed previously, the Pomperaug River Watershed 

receives an average of 117 cm/yr of precipitation. About 

57 cm/yr of that precipitation is lost to evaporation or is used 

by plants, and about 60 cm/yr is runoff that discharges to the 

Pomperaug River. The runoff component is a combination of 

direct surface runoff and ground-water recharge. The path of 

ground-water flow between recharge and discharge areas is 

influenced by the geologic material, the altitude and spacing 

of streams and ponds, and by the pattern of water use. 

If water levels in a given area are relatively constant 

over a long period, the flow of water into an area is balanced 

by the flow of water out of the area. Water levels in well 

WY1 (in the SAS area) have been measured monthly since 

1945 (fig. 7). Water levels in this well respond primarily to 

seasonal fluctuations in recharge caused by annual cycles of 

evapotranspiration. Smoothed water levels in WY1 show the 

effect of the multi-year drought in the 1960s and of a shorter 

drought in 2001 and 2002. Water levels may have increased 

slightly since 1985, but more data are needed to see if this is a 

persistent trend or a short-term phenomenon. 

Figure 6. Geohydrologic units, Woodbury, Connecticut.

Pomperaug River

Fine lake-bottom deposits

Deltaic deposits

Fluvial deposits 

BedrockBend in section

Bend in section

NOTE: This section is schematic and is not a measured geologic section. 

Approximate line of section is shown on Figure 5. 

BEDROCK

RIDGE OF

RESISTANT

BASALT

KFINE

KFINE

KDELT

KDELT

KFLUV

A A’

PSW-1

EXPLANATION
12 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Sources of Ground Water

Sources of ground water are spatially and temporally 

variable throughout the SAS area. The sources of recharge 

include precipitation that infiltrates into the ground and flows 

through the unsaturated zone to the water table (referred to 

as “recharge”), streamflow that infiltrates the streambed, and 

ground water that flows into the SAS area from adjacent areas. 

Runoff from a commercial area flows into drains that directly 

recharge ground water (“dry wells”). 

The spatial distribution of recharge depends on surficial 

geology (till or glacial stratified deposits), land-surface slope, 

precipitation amount and rate, the areal coverage of impervious surfaces and poorly drained soils (Natural Resources 

Conservation Service Class D soils), and actual evapotranspiration (D.M. Bjerklie, U.S. Geological Survey, written commun., 2007). Precipitation amount, precipitation intensity, and 

evapotranspiration also influence temporal differences in the 

rate of recharge. Generally, there is more recharge in spring 

and fall than in summer and winter, but the SAS model uses 

only annual-average recharge as input. The rates of recharge 

are discussed in the section on model boundaries and stresses.

The conceptual model of recharge in the SAS model is 

different from that used by Lyford and others (2007), who 

based their estimates of recharge on two factors: type of 

glacial deposit (glacial stratified deposits or till) and landsurface slope. Slope was considered conceptually, not quantitatively, in dividing the amount of predicted recharge into areal 

subunits. In this method, all runoff is either direct runoff to 

surface water or recharge to ground water. In addition to these 

two components, water can move as shallow subsurface flow 

(D.M. Bjerklie, U.S. Geological Survey, written commun., 

2007). Shallow subsurface flow is water that moves laterally 

on top of a low permeability layer, such as in till on top of 

bedrock or on top of a hardpan soil layer, but it may not represent recharge to the water table that would be available to a 

water-supply well. For this reason, the recharge estimated by a 

method that accounts for shallow subsurface flow is lower than 

that estimated by Lyford and others (2007) (D.M. Bjerklie, 

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

Figure 7. Monthly and smoothed water-level altitude in observation well WY1, Woodbury, 

Connecticut.

1945

72

74

76

78

WATER-LEVEL ALTITUDE,

 IN METERS ABOVE NAVD 88

1955 1965 1975 1985 1995 2005

Measurements are made monthly except during periods of drought, 

when measurements are more frequent. Points are water-level measurements,

and line represents smoothed water levels to show general trend.

Vertical lines indicate the period from which model calibration data are taken.

EXPLANATION

Data reading well WY1

Smoothed data well WY1
Geohydrologic Setting 13

Ground-Water Flow

Ground water in the uplands flows through glacial till 

and (or) bedrock. The water moves through pore spaces 

between material grains in the till and flows laterally to glacial 

stratified deposits, to streams in till, and downward into 

fractures in the bedrock. Flow through fractures in the bedrock 

discharges laterally or upward into glacial stratified deposits in 

the valley and also directly to surface water where bedrock is 

exposed. Some ground water in fractures discharges to public 

water-supply wells and private residential wells. 

Ground water in the valley flows through glacial till, 

bedrock, and glacial stratified deposits. Flow generally is 

upward from bedrock to glacial stratified deposits, passing 

through till where till is present beneath glacial stratified 

deposits. Water in the glacial stratified deposits is from 

precipitation, from losing reaches of streams, and from 

subsurface flow through till and (or) bedrock fractures. 

Ground water discharges to the Pomperaug River, to ponds 

formed in abandoned gravel quarries south of the study area, 

and to public water-supply well PSW-1. 

Water Use

Water use constitutes about 4 percent of the total runoff 

in the SAS area. Ground water is withdrawn for human use 

through five public-supply wells and many residential wells 

(fig. 2). The largest withdrawal from the glacial stratified 

deposits from 1997 to 2001 was 391.7 m3/d (72 gal/min) 

at public water-supply well PSW-1 (table 1). The water is 

supplied to customers in the Pomperaug valley. Withdrawals 

from PSW-1 showed an increase in summer over winter 

and a slight increasing trend from 1997 to 2001 (fig. 8). 

This increase in withdrawals is due to a small increase 

in population and to increasing water use by the existing 

population of Woodbury. Four other public-supply wells 

(PSW-2 through PSW-5) serve condominiums and apartments 

and withdrew a total of 233.9 m3/d (43 gal/min) from bedrock 

(Lyford and others, 2007). 

No data are available on actual residential water use, but 

a rough estimate can be made. The number of residences in the 

SAS area is estimated to be 517, the average number of people 

per household in Woodbury is 2.68 (U.S. Census Bureau, 

2007b), and the average water use per person in Connecticut 

is 0.28 m3/d (Hutson and others, 2005). On the basis of these 

values, the total residential water use in the SAS area is 

388 m3/d. The distribution of houses is fairly even in the 

uplands, so there is no area of concentrated pumping. An 

estimated 20 percent of water pumped is lost to evaporation 

(Solley and others, 1998), and 80 percent of the water pumped 

in the SAS area is returned to the ground through septic 

systems. The net effect of domestic wells is to redistribute 

water from bedrock fractures to shallow soils. More of the 

water in the shallow zone evaporates or flows to local streams 

than would be the case if the water remained in the bedrock. 

For comparison to the water-use figures, the annual average 

runoff in the Pomperaug River Watershed is 0.0189 m3/s/km2

(Morrison and others, 2006), so over the 15-km2 area of the 

SAS area, the average annual runoff is 24,500 m3/d.

Geohydrologic Units

Seven geohydrologic units were defined for input to the 

SAS model on the basis of data from monitoring wells drilled 

for this project (fig. 5; table 2). These data were interpreted 

in the context of previous published work in the area and by 

J.R. Stone (U.S. Geological Survey, oral communs., 2005 and 

2006). The altitude of bedrock (fig. 5) was subtracted from the 

altitude of land surface to obtain the thickness of the glacial 

deposits, which was then used to define layer boundaries in 

the SAS model, as discussed below. The geohydrologic units 

are identified in the model by a series capital letters chosen for 

mnemonic purposes. 

Glacial till in the SAS area is represented by the KTCOM 

and KTNON (table 2) geohydrologic units. KTCOM (fig. 5) 

consists of compact drumlin till and compact surface till and 

may be overlain by KFLUV at the valley margins. KTNON 

consists of loose (noncompact) surface till. 

The glacial stratified deposits in the SAS area are represented by the KFLUV, KDELT, and KFINE geohydrologic 

units (table 2). At the valley margins, KFLUV consists of 

collapsed, ice-marginal fluvial sequences that overlie KTCOM 

(fig. 5). In this area, the layer boundary between KFLUV 

and KTCOM was assumed to be at a depth equal to one-third 

of the total thickness of the glacial deposits. In the center of 

the valley, KFLUV consists of collapsed ice-marginal fluvial deposits throughout the entire saturated thickness of the 

glacial stratified deposits. The contact between fluvial deposits 

and the underlying deltaic deposits marked the water level in 

glacial Lake Pomperaug at an altitude of 76.2 m (Pessl, 1970), 

and the map-view contact between KFLUV and KDELT units 

(fig. 5) was estimated to be close to the 76.2-m land-surface 

contour, unless local data indicated otherwise (J.R. Stone, 

U.S. Geological Survey, oral commun., 2006). 

Table 1. Simulated pumping rates based on reported water 

withdrawals at public-supply wells in Woodbury, Connecticut.

[Data from Lyford and others (2007)]

Well Pumping rate, 

in cubic meters per day

PSW-1 391.7

PSW-2 97.7

PSW-3 45.5

PSW-4 45.3

PSW-5 45.4
14 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 8. Withdrawals from well PSW-1 and water-level altitude in well WY1, 1997 

to 2001, Woodbury, Connecticut.

1997 1998 1999 2000 2001

70

72

74

76

78

80

Water level in well WY1

1997 1998 1999 2000 2001 0

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WATER USE, IN CUBIC

 METERS PER DAY

Water use in well PSW-1

WATER-LEVEL ALTITUDE,

 IN METERS ABOVE NAVD 88

YEAR

Well out of service
Geohydrologic Setting 15

KDELT consists of two deltaic sequences having different surface altitudes (fig. 6). In between these areas, KDELT 

overlies KFLUV (fig. 5), and the layer boundary is assumed 

to be at a depth equal to two-thirds of the total thickness of 

the glacial deposits. This zone was delineated on the basis 

of hydraulic-head data, which show that hydraulic heads in 

some deep wells (KFLUV) are lower than hydraulic heads in 

shallow wells at the same location (KDELT). One way for this 

situation to arise is for there to be more permeable deposits 

deeper in the glacial stratified deposits. 

KFINE consists of a fine-grained sequence of silts and 

clays deposited in glacial Lake Pomperaug. These deposits are 

north of the buried bedrock ridge that separates thick glacial 

stratified deposits north of the study area from thick glacial 

stratified deposits in the study area. 

The bedrock in the SAS model is divided into two units 

as was done in the LAS (Lyford and others, 2007). KMESO 

represents Mesozoic bedrock, and KXLN represents Paleozoic 

bedrock. There are differences from the LAS: (1) the boundary between Paleozoic and Mesozoic rock changed slightly on 

the basis of analysis of rock samples collected in wells drilled 

for this study (wells WY86 and WY87), and (2) the Mesozoic 

bedrock in the study area is now known to be primarily basalt, 

as opposed to arkose, which had been reported in the LAS 

(Burton and others, 2005). 

Table 2. Specified values of hydraulic properties and definition of parameters for the small-area simulation model, Woodbury, 

Connecticut.

[“Estimated” means that the parameter value was not specified but was estimated (estimated values shown in table 3); m/d, meters per day; DQ, indicates 

dimensionless quantity]

Parameter 

name Parameter description Units

Value from 

modified 

large-area 

simulation

Parameter values and ranges 

from Lyford and others (2007)

Values used 

in large-area 

simulation

Range of 

reasonable 

values

KTCOM Hydraulic conductivity of compact till m/d Estimated 0.12 0.003 to 0.3

KTNON Hydraulic conductivity of non-compact till m/d 0.3 .09 .03 to 3

KFLUV Hydraulic conductivity of fluvial deposits m/d Estimated 5.7 to 6.3 3 to 52

KDELT Hydraulic conductivity of deltaic deposits m/d Estimated 5.7 to 6.3 3 to 52

KFINE Hydraulic conductivity of lake-bottom deposits m/d 2.3 2.8 3 to 52

KMESO Hydraulic conductivity of Mesozoic bedrock m/d Estimated 0.09 0.03 to 1.5

KXLN Hydraulic conductivity of Paleozoic bedrock m/d Estimated .03 .003 to .3

KVTILL Ratio of horizontal to vertical hydraulic conductivity in all till DQ 1 1 1 to 10

KVGSD Ratio of horizontal to vertical hydraulic conductivity in all glacial 

stratified deposits

DQ 1 1 1 to 10

KVROCK Ratio of horizontal to vertical hydraulic conductivity in all bedrock DQ 1 1 1 to 10

KPOMP Hydraulic conductivity of Pomperaug River streambed deposits m/d 0.3 0.3 0.1 to 3

KTRIB Hydraulic conductivity of tributary streambed deposits m/d Estimated .3 .1 to 3

PTT Porosity of compact till DQ .1 .08 .25

PTILL Porosity of non-compact till DQ .1 .035 .20 to .35

PGSD Porosity of glacial stratified deposits DQ .3 .35 .30 to .45

PBR Porosity of bedrock DQ .001 .02 .005 to .02
16 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Simulations of Ground-Water Flow and 

Residence Time

The construction, calibration, and results of the steadystate SAS model are described in this section. A steady-state 

model is one in which ground-water flow between cells does 

not change with time. In this case, the steady-state SAS model 

represents average annual conditions, as discussed in the 

following paragraphs. In order to represent different types of 

aquifer materials, the model uses parameter zones, that is, the 

modeled area is divided into large units in which each hydraulic property of the subsurface is considered to be represented 

by a single characteristic value. The use of parameter zones 

allows parameter values to be estimated with a small amount 

of data, but in reality, properties vary within each zone. The 

initial SAS model used boundary conditions and aquifer-property estimates from a modified version of the LAS model. 

Large-Area Simulation of Ground-Water Flow

The LAS model was used to estimate ground-water-flow 

rates across external boundaries into the SAS area. The layer 

thickness, recharge, and parameter estimates were modified 

from the original LAS model described by Lyford and others 

(2007), in order to make layers correspond between the LAS 

and SAS models and to incorporate information that became 

available after the LAS model was completed. 

Changes in layer thickness in the LAS model were necessary because that model represented a combination of glacial 

stratified deposits and bedrock in a single 45.7-m thick layer; 

therefore, aquifer properties in the LAS model are a combination of properties of bedrock and glacial deposits. More detail 

was needed for the SAS model because the glacial deposits 

vary in thickness and are less than 30 m thick. In the modified 

LAS model, the upper layer was subdivided into three layers, 

and the lower LAS layer, which represents only bedrock, was 

left as one layer. 

The LAS model also was modified by using a more 

detailed representation of ground-water recharge (D.M. Bjerklie, U.S. Geological Survey, written commun., 2007). The 

average annual recharge was used so that the modified LAS 

model would be compatible with the SAS model. The use of 

average annual recharge is discussed in the section on model 

boundaries and stresses.

Other minor changes were made in the modified LAS 

model, such as replacing the altitude of the top of the upper 

layer with more accurate values interpolated from 1:24,000 

topographic map contours. Another change was that a more 

accurate estimate of bedrock altitude was calculated and used 

in the model. This was done by subtracting the interpolated 

values of the thickness of the glacial deposits (Mazzaferro, 

1986a), which were modified slightly to include new data 

collected for this project, from land-surface altitude. For these 

reasons, the upper model layers in the modified LAS model 

represent more homogeneous materials than did the single 

layer in the original LAS model.

The different layering changed the geohydrologic unit 

definition, and an accurate estimate of ground-water flow 

could be obtained only by re-estimating model parameters. 

The re-estimation was done using the parameter-estimation 

capability available in MODFLOW-2000 and the same set of 

calibration data that was used in the LAS calibration. These 

modifications resulted in slightly different aquifer property 

estimates than those used in the LAS model (table 2).

Small-Area Simulation of Ground-Water Flow

The purpose of the SAS model was to provide detailed 

estimates of steady-state ground-water-flow rates and ages in 

the source area to monitoring wells and to water-supply well 

PSW-1. The results of the model simulations include estimates 

of aquifer properties, simulated hydraulic heads and streamflow, water budget, ground-water-flow paths, and groundwater residence times.

Model Characteristics

Steady-state ground-water flow in the study area is 

simulated by a model constructed of a grid of square cells. 

The flow of water into and out of each cell is simulated by 

the model. In the SAS model, the Hydrogeologic Unit Flow 

module in MODFLOW-2000 was used (Anderman and Hill, 

2000). This module allows aquifer properties to be specified 

independently of the model grid, and geohydrologic units do 

not need to be in a continuous layer. The aquifer-property 

boundaries correspond to the geohydrologic units discussed 

previously in this report. Input parameters for these units are 

adjusted until the simulation reproduces observed values as 

closely as possible.

Model Domain and Grid-Cell Dimensions

The model domain of the SAS model is the area within 

the external boundaries of the model (fig. 9) that includes all 

areas that could contribute water to well PSW-1 under various 

scenarios of pumping rates, taking into account the uncertainty 

in hydrologic and aquifer properties. The external boundaries were selected to be particle tracks from the original LAS 

model. Particle tracks trace a path line of flow across which 

there is no flow of water; therefore, the external boundaries of the SAS model initially were specified to be no-flow 

boundaries. In the course of re-estimating aquifer properties 

in the modified LAS model, some simulated flow crossed the 

SAS model’s external boundaries. The simulated flow from 

the modified LAS model was specified as a fixed flow rate for 

each model cell on the external boundaries of the SAS model. 

The top of the uppermost model layer is the water table, 

but the position of the water table was observed at only a few 

locations; therefore, the initial top of the upper model layer 
Simulations of Ground-Water Flow and Residence Time 17

PSW-1

PSW-4

PSW-3

PSW-5

PSW-2

Average annual recharge rate,

in meters per day

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

PSW-1

0.00009

EXPLANATION

Commercial area with dry wells

External flow

Quarry pond

River or stream

0.0005

0.00128

0.00096

0.00092

0.00076

0.00072 0.0004

0.00147

0.0005

0.00139

0.00068

0.00078

0.00133

0.00108

0.00135

0.00094

0 0.5 1 KILOMETER

0 0.5 1 MILE

Public-supply well,

and number

Model cells

41° 32'

41° 31'

73°13' 73°12' 73°11'

0.00058

Figure 9. The domain of the SAS model, recharge rates, and public-supply wells, Woodbury, Connecticut.
18 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

was taken to be land surface or the simulated water table, 

whichever was lower. The top altitude was continually refined 

by replacing the top altitude with the water-table altitude 

determined from a model run. This process was run iteratively 

until a stable water-table position was reached. In this way, 

vertical resistance assigned to model layers takes account of 

only the saturated part of the subsurface. The lower boundary of the model is a no-flow boundary placed at the depth at 

which flow through fractures is assumed to be negligible 

(61 m below the base of the glacial deposits). 

In the SAS model grid, there are 241 rows, 322 columns, 

and 7 layers. Active grid cells in the SAS model cover 15 km2. 

The grid has the same orientation as the LAS model grid (the 

y-axis is rotated 10 degrees clockwise from north). The model 

was initially calibrated at a 61-by-61-m grid-cell size. After an 

acceptable model was obtained through calibration, the grid 

cell size was refined to 15.2-by-15.2 m. The upper six model 

layers were a uniform 3 m thick, and the lowest model layer 

was 61 m thick. 

Boundary Conditions and Model Stresses

Ground-water flow is specified at the external boundaries of the SAS model, except for quarry ponds, which are 

represented by head-dependent flow boundaries. The eastern 

boundary has a specified flow rate equal to zero (no flow) 

because this is a watershed boundary, and ground-water flow 

across the boundary is assumed to be minimal. Ground-water 

flow across the other lateral boundaries was accounted for by 

taking the flow rate across cell faces in the modified LAS, 

and converting them to a flow per unit length multiplied by 

the length of the cell in the SAS model. Flow across lateral 

boundaries was simulated in MODFLOW-2000 using the Flow 

and Head Boundary (FHB) package. 

The boundary condition for the top of the model is a 

specified flow rate equal to average annual recharge from 

1998 to 2004 (fig. 9), as determined using a rainfall-runoff 

model (D.M. Bjerklie, U.S. Geological Survey, written commun., 2007). The use of an annual average value dampens the 

influence of variability among years. Also, recharge during 

this time period is compatible with the hydraulic-head measurements used for parameter estimation (see next section). 

Recharge to the model was modified in the commercial area, 

where all surface runoff flows into storm drains (dry wells). In 

this area, recharge was set to the annual rainfall over the commercial area. This approach slightly overestimates recharge 

from the commercial area, because some water evaporates 

before reaching the dry wells. 

The boundary condition for the bottom of the model is 

a specified flow rate equal to zero, because at some depth, 

ground-water flow in fractures in bedrock is minimal. Alternative versions of the model were run with the base of the 

model at 500 ft below the base of the glacial deposits, and the 

model was found to be not sensitive to the depth of the lower 

model boundary.

Surface-water head-dependent-flow-rate boundaries are 

of two types. Streams are simulated using the Stream (STR) 

package in MODFLOW-2000, as was done in the LAS model 

(Lyford and others, 2007). Ponds near the Pomperaug River 

are simulated using the General-Head Boundary (GHB) 

package in MODFLOW-2000. The conductance term for this 

boundary is calculated using a hydraulic conductivity that is 

equal to that used for the Pomperaug River, so there is virtually no difference between how ponds are simulated and how 

the Pomperaug River is simulated. The different packages 

available in MODFLOW-2000 were used simply to allow for 

water budgets to be calculated separately for quarry ponds and 

for the river and tributary streams. 

Pumping wells are simulated in the SAS model at the 

same locations and withdrawal rates as in the LAS (table 1) 

(Lyford and others, 2007). Wells were simulated using the 

Multi-Node Well (MNW) package (Halford and Hanson, 

2002). The MNW package enables wells to span multiple 

layers, and the model calculates the amount of total well 

pumpage assigned to each model layer.

Model Hydraulic Parameters, Observations, and 

Observation Weights

The hydraulic-property parameters in the SAS model 

are the nine horizontal hydraulic conductivities of five glacial 

geohydrologic units, two bedrock geohydrologic units, and the 

streambeds of the Pomperaug River and of tributary streams. 

The values of the parameters were taken either from the LAS 

or were estimated in the SAS model using the parameter-estimation capability of MODFLOW-2000. The values of some of 

these nine parameters could be estimated because the calibration data contained sufficient information about the parameter 

(table 2), but other parameter values could not be estimated 

because either the model was not sensitive to the parameter 

or the calibration data contained insufficient information 

about that parameter. Values for parameters that could not be 

estimated were not changed from the modified LAS values 

(table 2). The ratio of horizontal to vertical hydraulic conductivity also could not be estimated with the data available. 

Other model parameters were estimated while the ratio was 

held at fixed values between 1 and 10, and the best model was 

obtained with a value of 1. A value of 1 also was determined 

to produce the best fit to observed values in the LAS model 

study (Lyford and others, 2007).

Although not required for the flow simulation, effective porosity values are required for the advective particle 

tracking that is used to calculate residence times. The SAS 

model uses four porosity groups (identified in the model by 

the capital letters in parentheses): glacial stratified deposits 

(PGSD), non-compact surface till (PT), compact till (PTT), 

and bedrock (PBR) (table 2). The range of porosities assigned 

to glacial sediments is from 0.20 (till) to 0.45 (glacial stratified deposits), a maximum to minimum ratio equal to 2.5. The 

range of porosities assigned to bedrock is from 0.005 to 0.02, 

a maximum to minimum ratio equal to 4.0 (Lyford and others, 
Simulations of Ground-Water Flow and Residence Time 19

2007). The simulated residence time is proportional to the 

porosity, so porosity variation in glacial deposits has less effect 

on residence time than variation in bedrock. Residence time of 

water in wells completed in glacial deposits will be sensitive 

to a combination of porosity in bedrock and glacial deposits 

because some water may flow through bedrock before entering 

the glacial stratified deposits. 

Parameters were estimated in the SAS model using three 

types of observed data (“observations”). The primary type 

of observation is hydraulic head. In the 34 wells drilled for 

this study (Group 1 wells; figs. 3 and 4), either monthly or 

continuous water-level measurements were available. In both 

cases, the average water level from March 1, 2004 through 

February 28, 2005 was used in parameter estimation. This 

period was chosen because it had the most water-level measurements available. In addition, this period roughly represents 

average conditions, in part because precipitation in the period 

was at the 58th percentile for annual total precipitation for all 

years from 1950 to 2005. Although some variability in water 

levels is seasonal (fig. 8), levels increased slightly from 1985 

to 2005 at WY1 (fig. 7) and a possible short-term rise occurred 

from 1998 to 2005. If this trend is real, SAS model results are 

more representative of conditions in the last 20 years than they 

are of conditions longer ago, when average water levels might 

have been lower. 

Hydraulic-head observations in wells from two other 

sources (fig. 3) were used in parameter estimation—water 

levels in wells used in the LAS model (from Mazzaferro, 

1986b) (Group 2 wells) and water levels in domestic wells 

measured at the time of well completion (Group 3 wells; 

from Burton, 2006). Group 2 also includes two wells (WY96 

and WY97) that were drilled for this study but were not 

surveyed to the same accuracy as Group 1 wells. The latter 

two groups of hydraulic-head data are less accurate than those 

measured for this study, but they are important in areas where 

data are sparse. 

The second type of observation is streamflow gain 

and (or) loss. In order to constrain leakage from tributary 

streams, streamflow was gaged at two locations on South 

Brook. South Brook was identified as a possible source of 

water in the LAS model (Lyford and others, 2007). The difference between the two measurements represents the rate 

of water gained or lost from the stream. The median of five 

measurements made during low flow periods in 2003 and 2004 

was used in parameter estimation. The third type of observation used is ground-water age. Hydraulic conductivity values 

were determined first using parameter estimation, then porosities were adjusted manually to achieve a good fit between 

tritium/helium age estimates and simulated residence times. 

If observation data used in parameter estimation have 

different units (hydraulic head in meters and flow in cubic 

meters per second, for example) or the data have different 

measurement errors, the data can be weighted to emphasize 

more reliable or more accurate values while allowing all values to be included in the regression. A method for calculating 

weights (Hill, 1998) was followed initially in the SAS model. 

MODFLOW-2000 requires the user to specify one of the 

following: the standard deviation, variance, or coefficient of 

variation for each observation. Weights used in the regression 

are calculated internally in MODFLOW-2000 from the userspecified value, and are the inverse of the variance. Weights 

on observations were subsequently changed within reasonable 

ranges during parameter estimation to achieve an approximately normal probability distribution of residuals. 

Hydraulic heads measured in Group 1 wells are assumed 

to be within 0.003 m of their true value. Reference point 

altitudes were surveyed to within 0.0003 m, and water levels 

were measured to within 0.003 m. To relate the measurement 

to a normal probability distribution, a 95-percent confidence 

interval was used. Weights were assigned on the basis of the 

statement that 95 percent of all measurements are within 

0.003 m of the true value. The initial standard deviation 

from which weights were calculated is 0.00155 m, and the 

final value is 0.0762 m. This large increase in the estimated 

standard deviation could reflect variation of hydraulic 

conductivity, which affects hydraulic head, within parameter 

zones. In other words, variation of hydraulic head within 

a parameter zone is affected by sources of error other than 

purely measurement error, on which the initial standard 

deviation was based. 

Observed hydraulic heads in Group 2 wells are assumed 

to be within 1.5 m of their true value because the reference 

points were estimated from a topographic map having a 10-ft 

(3.048-m) contour interval. A 90-percent confidence interval 

was assumed for these wells. The initial and final standard 

deviation from which weights were calculated is 0.924 m. 

Observed hydraulic heads in the Group 3 wells are assumed to 

be within 4.5 m of their true value. Their reference points were 

estimated from the same topographic map as were Group 2, 

but the locations were less certain and the terrain was steeper, 

so that the reference points are more uncertain. In addition, 

these hydraulic heads were not measured at the same time and 

may not have completely stabilized after drilling. A 90-percent 

confidence interval was assumed for these wells. The initial 

standard deviation from which weights were calculated is 

2.77 m and the final value is 3.11 m.

The difference between streamflow measured at two 

locations on South Brook (fig. 4) also was used as an observation. The median measured difference in streamflow was a 

loss of 0.0017 m3/s on July 7, 2004. The error of the individual 

measurements was assumed to be 10 percent, and the total 

variance was calculated by adding the measurement variances. 

The initial and final coefficients of variation (standard deviation divided by the mean) from which weights were calculated 

was 0.94 (dimensionless). Because the standard deviation 

and the mean are almost equal, there is a large amount of 

uncertainty in the streamflow data, and the weight assigned 

is two orders of magnitude lower than the weight assigned to 

hydraulic-head observations. Even so, streamflow loss was 

used in the final parameter estimation because it does improve 

the model fit slightly. 
20 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Estimation of Model Parameters

In order to have confidence in model simulation 

results, the model should produce reasonable parameter 

values; hydraulic heads, streamflow, and ground-water 

residence times that are close to observed data; and residuals 

that are normally distributed and uncorrelated. In this study, 

the parameter values that were estimated are reasonable 

when compared with previous estimates (tables 2 and 3). The 

standard error of the regression is 1.85 m, but the regressionbased calibration minimizes the sum of squares of weighted 

residuals, and the observations have different weights, so a 

simple measure like the standard error of the regression is not 

straightforward to interpret; therefore, other aspects of model 

fit will be discussed. 

The parameter estimation should produce weighted 

residuals (observed minus simulated values) that are small and 

unbiased, as indicated by a random distribution of weighted 

residuals. Also, both the sum and the mean of residuals will be 

close to zero. In the SAS model, there are more observations 

of hydraulic head than other types of observations; therefore, 

unweighted head residuals offer the most intuitive qualitative 

assessment of model fit. 

Weighted model residuals range from -4.8 to 5.2 m 

(table 4). The mean weighted residual is 0.30 m, and there are 

four dry wells in the simulation. Group 1 weighted residuals 

also ranged from -4.8 to 5.2 m (the minimum and maximum 

for all data were in Group 1), and the mean was 0.012 m, indicating a good fit between observations and simulated values. 

The mean absolute residual is 1.80 m for the Group 1 wells 

and is an indication of how far weighted simulated heads are 

from weighted observed heads. The sum of weighted residuals for Group 1 was 0.44 m, indicating that there is little bias 

in the model. Weighted model residuals also can be analyzed 

graphically to detect potential problems with the regression 

(fig. 10A). Residuals are distributed approximately randomly 

when plotted against simulated values, although shallow and 

deep pairs of wells (WY77/WY78 and WY96/WY97) tend 

to have residuals of equal magnitude but opposite sign. This 

probably means that some geologic feature is not represented 

in the model, as discussed in the following paragraph. Most 

weighted residuals tend to lie on a line having a 1:1 slope 

when plotted against observed values (fig. 10B). 

Unweighted water-level residuals range from -15 to 

45 m (table 4; fig. 10C). The mean unweighted residual is 

2.9 m, and there are four dry wells in the simulation. The 

extreme values for unweighted residuals are at Group 3 wells 

(table 4). The location and reference altitudes for these wells is 

less certain than for other wells, so there is less weight placed 

on these data. For the 34 hydraulic-head observations in 

Group 1 wells, the unweighted residuals ranged from -1.2 

to 1.3 m, and the mean was 0.0030 m, indicating a good 

fit between observations and simulated values. The mean 

absolute residual is 0.46 m for the Group 1 wells and is an 

indication of how far simulated heads are from observed 

heads. The sum of unweighted residuals for the Group 1 wells 

was 0.11 m, indicating that there is little bias in the model.

Although the Group 1 residuals are small and indicative 

of a good model fit, their pattern does reveal some aspects of 

the model with respect to the position of geologic contacts 

that could be improved. Residuals from the area where 

KDELT overlies KFLUV are too high in the upper, deltaic 

deposits and too low in the lower, fluvial deposits. Also, 

the absolute magnitude of these residuals is higher than 

elsewhere. This model, which uses the superposition of these 

two geohydrologic units to help explain the head differences 

between shallow and deep intervals in the glacial stratified 

deposits has less bias and “splits the difference” better 

than models that do not include this feature. Other models 

were constructed to simulate this feature, for example by 

introducing a confining layer between the shallow and deep 

parts of the glacial stratified deposits, but these models did not 

have a geologic basis and did not remove the bias in residuals. 

Perhaps the absolute magnitude of residuals in this area could 

be lowered by moving the position of the glacial stratified 

deposits/till contact, but no geologic evidence supported this, 

and it was not clear that this would improve the model.

The observed value of streamflow loss, 147 m3/d, was 

the same as the simulated value, 147 m3/d, although the 

uncertainty in the measurements was almost as large as the 

difference in the streamflow measurements. Thus, the weight 

on this observation was small and the observation did not 

affect the regression to the same extent as the observed values 

of hydraulic head. 

In the SAS model, the correlation coefficient of weighted 

residuals against a normal probability plotting position is 

0.972, but the critical value at the 5-percent significance level 

is 0.975, which would lead to the rejection of the assumption 

of normality. However, a regression produces residuals that are 

correlated for observed values that are close to one another. An 

overprediction at one location is likely to produce an overprediction at a nearby location. Residuals can be plotted against 

randomly generated residuals that have the same degree of 

correlation as expected from the model to see if the assumption of normality of residuals can be accepted (Cooley and 

Naff, 1990). The SAS model did produce residuals that are 

normally distributed based on this type of analysis.

After the hydraulic parameters were estimated, porosities 

were varied systematically in order to achieve the best fit 

between simulated residence times and measured tritium/

helium age dates. The range of reasonable porosity values is 

small (table 2), and porosity in the glacial stratified deposits 

that is in the contributing recharge area to PSW-1 probably 

varies in an even smaller range than that given in table 2 

(values in table 2 are for many types of glacial stratified 

deposits in many locations). Porosity for the glacial stratified 

deposits in the contributing recharge area is probably in the 

range 0.20 to 0.35, or a decrease and increase of 3 percent 

and 17 percent, respectively, from the porosity used in the 

SAS model (0.30). Residence times are a linear function of 

porosity, so the residence times for water that recharges the 
Simulations of Ground-Water Flow and Residence Time 21

Table 4. Statistics of residuals (observed minus simulated values) for the small-area simulation model, Woodbury, Connecticut.

[All residuals in meters]

Statistic All wells Group 1 Group 2 Group 3

Number of water levels 97 34 8 51

Number of dry wells 4 0 0 4

Weighted water-level residuals

Minimum water-level residual -4.8 -4.8 -1.7 -1.5

Mean water-level residual .30 .012 .073 .52

Median water-level residual .28 .46 .22 .067

Maximum water-level residual 5.2 5.2 1.7 4.4

Standard deviation of water-level residual 1.8 2.4 1.3 1.3

Sum of water-level residuals 28 .44 .57 27

Mean absolute residual 1 1.80 1.00 1

Unweighted water-level residuals

Minimum water-level residual -15 -1.2 -5.2 -15

Mean water-level residual 2.9 .0030 .22 5.2

Median water-level residual .19 .12 .67 .67

Maximum water-level residual 45 1.3 5.2 45

Standard deviation of water-level residual 10.4 .6 3.8 14

Sum of water-level residuals 274 .11 1.7 272

Mean absolute residual 6 .46 3.0 10

Table 3. Estimated optimal parameter values for the small-area simulation model, Woodbury, 

Connecticut.

[All units are meters per day]

Parameter name Parameter description Optimal parameter value

KTCOM Hydraulic conductivity of compact till 0.0099

KFLUV Hydraulic conductivity of fluvial deposits 18

KDELT Hydraulic conductivity of deltaic deposits 6.2

KMESO Hydraulic conductivity of Mesozoic bedrock .14

KXLN Hydraulic conductivity of Paleozoic bedrock .035

KTRIB Hydraulic conductivity of tributary streambed deposits .039
22 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 10. Weighted simulated residuals, weighted observed water levels and 

streamflow, weighted simulated water levels and streamflow, and unweighted 

observed and simulated water levels for the small-area simulation model, 

Woodbury, Connecticut.

0 200 800 1,000 1,200 1,400

-20

-15

-10

-5

0

5

10

15

20

WEIGHTED SIMULATED RESIDUAL (DIMENSIONLESS)

NO DATA

WY81

WY86

WY77

WY78

WY97

WY96

0 200 800 1,000 1,200 1,400

WEIGHTED SIMULATED WATER LEVELS AND 

STREAMFLOW (DIMENSIONLESS)

0

200

800

1,000

1,200

1,400

WEIGHTED OBSERVED WATER LEVELS 

AND STREAMFLOW (DIMENSIONLESS)

NO DATA

Group 2

and 3 wells

Group 1 wells and

streamflow

A

B
Simulations of Ground-Water Flow and Residence Time 23

glacial stratified deposits could be expected to vary by 

-33 percent to +14 percent of the reported values. Water that 

recharges the uplands follows paths that include both types of 

till as well as bedrock, and the residence time is a function of 

the porosity and the amount of time spent in all those units, so 

no generalization is possible. Residence times did not match 

well for bedrock wells, as discussed later in this report, but 

the final porosity used for bedrock (0.001) was reasonable 

based on published values, and resulted in the best overall 

match for all wells. An attempt to match residence times in 

bedrock wells resulted in a much poorer match for other wells. 

The final porosities reported in table 2 produced the best fit 

between measured and observed residence times for all wells.

The use of the SAS model developed and described 

here is deemed acceptable for the purposes of this study. The 

model generally produces unbiased and optimal estimates of 

the most important model parameters. The hydraulic heads, 

streamflows, and parameter values estimated using the model 

are within reasonable ranges. Simulated residence times 

show the same magnitude and trends with depth as measured 

residence times, except for bedrock for reasons that are 

discussed in the next section.

Simulated Water Budget

The simulated water budget is similar to that produced 

by Lyford and others (2007) in that the dominant source of 

water in the uplands is recharge from precipitation, whereas 

recharge from precipitation accounts for only about one-third 

of the total flow in the glacial stratified deposits. In both the 

LAS and SAS models, contributions of ground water from 

uplands to the glacial stratified deposits are significant. The 

Pomperaug River is the main discharge area, but some ground 

water flows into tributary reaches as well. Tributaries can gain 

or lose ground water, depending on the local relation of stream 

stage and ground-water level. A more detailed description 

of the simulated water budget provides some insight into the 

relation of upland and glacial stratified deposits parts of the 

ground-water flow system (table 5). 

60 70 80 90 100

UNWEIGHTED SIMULATED GROUP 1 WATER LEVELS, IN METERS 

60

70

80

90

100

UNWEIGHTED OBSERVED GROUP 1 WATER

 LEVELS, IN METERS

C

Figure 10. Weighted simulated residuals, weighted observed water levels and 

streamflow, weighted simulated water levels and streamflow, and unweighted 

observed and simulated water levels for the small-area simulation model, Woodbury, 

Connecticut.—Continued
24 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Table 5. Simulated water budget for the small-area simulation, Woodbury, Connecticut.

[--, not applicable; budgets do not always sum to 100 percent because of rounding; negative flow is out of unit; positive flow is into unit; m3/d, cubic meters per 

day]

Component of water budget and MODFLOW module 

(in parentheses)

Water in, 

in m3/d

Water in, 

in percent

Water out, 

in m3/d

Water out, 

in percent

Net flow, 

in m3/d

FLOWS IN AND OUT OF MODEL

Entire simulated area

Multi-node wells (MNW) -- -- 626 4 -626

General Head-Dependent Boundaries (GHB), 

representing quarry ponds

251 2 1,280 8 -1,029

Recharge from precipitation on land surface (RCH) 11,600 70 -- -- 11,600

Specified Flows (FHB), representing flows across 

external boundaries

3,960 24 560 3 3,400

Stream Leakage (STR) 793 5 14,100 85 -13,307

Valley (Glacial stratified deposits)

Multi-node wells (MNW) -- -- 392 3 -392

General Head-Dependent Boundaries (GHB), 

representing quarry ponds

252 2 1,280 8 -1,030

Recharge from precipitation on land surface (RCH) 5,070 32 -- -- 5,070

Specified Flows (FHB), flow across external boundaries 2,920 19 210 1 2,710

Stream Leakage (STR) 781 5 11,500 74 -10,700

Uplands (1Upper 18 meters of till and bedrock)

Multi-node wells (MNW) -- -- 128 2 -128

Recharge from precipitation on land surface (RCH) 6,480 77 -- -- 6,480

Specified Flows (FHB), flow across external boundaries 411 5 166 2 245

Stream Leakage (STR) 12.4 -- 2,580 31 -2,570

Uplands (1Bedrock deeper than 18 meters)

Multi-node wells (MNW) -- -- 106 2 -106

Specified Flows (FHB), flow across external boundaries 625 9 184 3 441

FLOWS BETWEEN UNITS IN MODEL

Valley (Glacial stratified deposits)

Upper 18 meters of till and bedrock 1,330 8 203 1 1,130

Bedrock deeper than 18 meters 5,300 34 2,041 13 3,260

Uplands (1Upper 18 meters of till and bedrock)

Glacial stratified deposits 203 2 1,330 16 -1,130

Bedrock deeper than 18 meters 1,330 16 4,250 50 -2,920

Uplands (1Bedrock deeper than 18 meters)

Glacial stratified deposits 2,040 30 5,300 77 -3,260

Upper 18 meters of till and bedrock 4,250 61 1,330 19 2,920

1 Depths measured from water table.
Simulations of Ground-Water Flow and Residence Time 25

Recharge to the water table in upland areas is dominated 

by precipitation (table 5). Discharge from the upper 18 m of 

till and bedrock in the uplands is to bedrock deeper than 18 m 

(50 percent), streams (31 percent), and glacial stratified deposits (16 percent). Minor amounts (3 percent) of upland ground 

water flows to wells and external model boundaries. Bedrock 

greater than 18 m deep receives water from till, glacial stratified deposits, and external boundaries. Most water from deep 

bedrock discharges upward into glacial stratified deposits, 

with minor amounts to till and wells. 

The glacial stratified deposits receive ground water 

through recharge from precipitation (32 percent), upward flow 

from bedrock (34 percent), and flow across external boundaries (19 percent), as well as minor amounts from streams, 

till, and quarry ponds (fig. 11). Although net percentages (as 

presented above) give an overall water budget, losing stream 

reaches account for 5 percent of the flow into the glacial 

stratified deposits. Most of the streamflow loss occurs in the 

lower reach of South Brook in the study area (fig. 12). Losing 

reaches of streams are common in the New England glacialaquifer setting. Evidence that South Brook loses water to the 

aquifer was observed on August 26, 2005, when the stream 

went dry over the predicted losing reach because of a lack of 

rainfall. Water was flowing in South Brook above and below 

this reach. The dry wells in the commercial area (fig. 9) also 

are a source of recharge to the glacial stratified deposits (about 

80 m3, or 1.6 percent of the natural recharge from precipitation 

to the glacial stratified deposits). Most of the ground water 

in the glacial stratified deposits discharges to the Pomperaug 

River (74 percent) and quarry ponds (8 percent). Water in 

the quarry ponds eventually discharges back into the Pomperaug River south of the study area. Only about 3 percent of 

the ground water in the glacial stratified deposits is used for 

public-water supply. 

Figure 11. Water budget for the small-area simulation, Woodbury, Connecticut.

Quarry ponds, 1,030

Well, 392

Streamflow, 10,700

Precipitation, 5,070

Streamflow, 2,570

Boundaries, 2,710

Precipitation, 6,480Boundaries, 245

Wells, 128

BEDROCK

GLACIAL STRATIFIED DEPOSITS GLACIAL TILL AND BEDROCK

BEDROCK

GLACIAL STRATIFIED DEPOSITS GLACIAL TILL AND BEDROCK

3,260

2,920

1,130

3,260

2,920

1,130

Wells, 106

Boundaries, 441

DEPTH BELOW LAND SURFACE

0 meters

18 meters

61 meters

All water-budget components are net flow and are in cubic meters per day.
26 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

Pomperaug

River

South Brook

41° 32'

41° 31'

73°13' 73°12' 73°11' 73°10 '

0 0.5 1 KILOMETER

0 0.5 1 MILE

Losing stream reach

Boundary of Small-Area Simulation area 

EXPLANATION

Figure 12. Simulated losing stream reaches in the small-area simulation model, Woodbury, Connecticut.
Simulations of Ground-Water Flow and Residence Time 27

Simulation of Ground-Water Residence Time

The particle-tracking program MODPATH (Pollock, 

1994) was used to simulate ground-water residence time, 

which was in turn used to relate natural and anthropogenic 

factors to water quality. Land use is related to shallow groundwater quality (Grady, 1994); for any given land use in a 

contributing recharge area to a well, an associated set of waterquality characteristics moves with the ground water toward the 

well. If land use changes, a new characteristic water quality develops that also moves toward the well. The residence 

time is related to the time it takes for that new water-quality 

characteristic to be detected in a water sample from the well. 

Residence time also can be used in the analysis of chemical 

processes that depend on contact time between the water and 

the solid matrix through which the water flows.

Residence Time of Water in Monitoring Wells

Residence times and contributing recharge area were 

simulated for monitoring wells in order to refine understanding of the relation between land use and water quality. Well 

PSW-1 integrates water quality from a large area containing a 

variety of land uses and geohydrologic units, but monitoring 

wells, which are pumped only when being sampled, have a 

smaller contributing recharge area and therefore are affected 

by fewer land uses. 

Residence times were simulated for monitoring wells by 

reverse particle tracking using the SAS model. The reason for 

using reverse particle tracking is that water is not normally 

pumped from monitoring wells, so ground-water-flow paths 

do not converge on the well, and only a limited number of 

particles pass forward through the well. The best way to 

ensure that particles pass through the well is to “start” them 

at the well and track them back to their source area. 

Concentrations of tritium and helium-3 were measured in 

samples from selected wells and converted to residence times 

for comparison with simulated ground-water residence times. 

Details of tritium/helium dating procedures are summarized in 

Schlosser and others (1988) and Solomon and Cook (1999). 

Measured and simulated residence times generally are similar 

(table 6). Simulated residence times at monitoring wells 

ranged from less than 0.1 years to 10.7 years. As expected, 

water from deeper wells generally had longer simulated residence times. In some medium-depth and deep wells (WY70, 

WY73, WY75, and WY102), the simulated residence times 

are shorter than the measured values. This could be because of 

error either in the configuration of flow paths predicted by the 

model or in the simulated porosity distribution. In some cases, 

a slight change in the value of hydraulic conductivity causes 

shifts in the flow paths to shallower or deeper zones, thus 

changing the simulated residence time at a fixed depth in a 

monitoring well. The measured residence time for the sample 

from bedrock well WY87 (9.9 years) is longer than simulated 

(2.6 years). The measured residence time can be long for at 

least two reasons: the actual flow path can be longer than the 

simulated flow path because of tortuous paths through a fracture network (fracture networks are not explicitly included in 

the simulation); or, the sample is a mixture of water of a short 

residence time (through a permeable fracture) and water of a 

long residence time (from dead-end fractures or from fractures 

so small that Darcy’s Law does not apply). The simulated 

residence times in bedrock tend to be short because of the low 

bulk-rock porosity, based on previous studies (table 2), that is 

used in the advective particle tracking.

Residence Time of Water in PSW-1

Residence times were simulated for PSW-1 by forward 

particle tracking using the SAS model. Forward tracking 

allows particles to be tagged with a recharge volume based on 

where the particle starts, and flow-weighted residence times 

at the supply well can be calculated. Flow-weighted residence 

time is more important for the public-supply well than for the 

monitoring wells because as water is pumped from the publicsupply well, residence times are mixed in the well in proportion to the flow rate over each interval in the well screen. 

The contributing recharge area to PSW-1 shows the effect 

of geology on ground-water-flow direction and residence time 

(fig. 13). Within the glacial stratified deposits, the contributing 

recharge area is relatively narrow. The longest residence time 

and greatest spread of flow paths is in the upland area. About 

40 percent of the water withdrawn from PSW-1 originated as 

upland recharge before flowing through the glacial stratified 

deposits. The mean residence time for water recharged in the 

uplands is 7.8 years. About 44 percent of the water withdrawn 

from PSW-1 originated as recharge in either KFLUV (mean 

residence time 6.9 years) or KDELT (mean residence time 

4 years). About 16 percent of the water withdrawn from 

PSW-1 comes from dry wells in the commercial area. The 

residence time for water that is recharged through dry wells 

ranges from 1.6 to 3.8 years, and the mean residence time is 

2.5 years. Dry wells are a fast pathway for water to enter the 

aquifer and provide a significant amount of water to PSW-1; 

therefore, PSW-1 is more susceptible to contamination in runoff from the commercial area, which enters the dry wells, than 

to recharge elsewhere in the SAS area. 

Ground-water residence time has been used as a surrogate 

measure of an aquifer’s susceptibility to contamination (Eberts 

and others, 2005), and wells producing water with short 

residence times commonly are judged to be more susceptible 

to surface contamination than wells producing water with 

long residence times. If the susceptibility is calculated using 

age tracers that reflect a flow-weighted average of residence 

times in the aquifer, the full range of residence times in the 

water is not revealed. Water withdrawn from a well is a 

mixture of waters with different residence times, and a single 

residence time does not fully characterize the susceptibility 

of the well to recent contamination. The mean simulated 

flow-weighted residence time from PSW-1 is 5.9 years, which 

compares reasonably well with the residence time measured 
28 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Table 6. Tritium/helium age and simulated residence time at monitoring wells in the small-area simulation model, Woodbury, 

Connecticut.

[--, no tritium/helium analysis or residence time not simulated; blank line separates clusters of wells; vertical well-screen position: Deep wells are 

screened in the lower third of glacial deposits; middle wells are screened in the middle third of glacial deposits; shallow wells are screened in the upper 

third of glacial deposits; bedrock means well is screened in bedrock]

Well name Tritium/helium age, 

in years

Simulated residence time, in years Vertical well-screen position Minimum Average Maximum

PSW-1 5.5–6.6 -- 5.9 -- Deep

WY69 5.8 5.6 6.3 8.3 Deep

WY70 4.9 1.3 1.4 1.5 Middle

WY71 1.8 -- -- -- Shallow

WY72 8.4 7.4 8.5 8.9 Deep

WY73 4.0 2.6 2.8 2.9 Middle

WY74 .7 -- -- -- Shallow

WY75 10.0 5.9 6.2 6.6 Deep

WY76 .9 -- -- -- Shallow

WY77 -- .6 .7 .8 Deep

WY78 -- -- -- -- Shallow

WY79 -- 1.2 1.3 1.5 Shallow

WY80 -- .5 .5 .5 Deep

WY81 -- .3 .4 .4 Shallow

WY82 -- 2.3 4.3 6.7 Deep

WY83 -- .2 .4 .5 Middle

WY84 3.4 3.3 4.6 6.2 Deep

WY85 -- .8 .8 .8 Shallow

WY86 -- 3.1 3.2 3.3 Bedrock

WY87 9.9 2.6 2.6 2.6 Bedrock

WY88 -- .1 .3 .5 Deep

WY89 -- .6 .7 .8 Deep

WY90 -- .3 .4 .4 Deep

WY91 -- 7.7 8.4 9.1 Middle

WY92 -- 1.6 2.0 2.4 Shallow

WY93 -- 5.5 5.5 5.6 Deep

WY94 -- .3 1.2 2.5 Middle

WY95 -- .5 .5 .6 Shallow

WY96 -- -- -- -- Middle

WY97 -- 2.8 3.0 3.3 Bedrock

WY98 -- .3 .4 .4 Deep

WY99 -- 0.0 .1 .1 Middle

WY100 4.9 10.0 10.4 10.7 Middle

WY101 5.4 6.7 7.5 9.4 Deep

WY102 5.6 .4 .6 .9 Shallow

WY106 -- 5.9 5.9 5.9 Bedrock
Simulations of Ground-Water Flow and Residence Time 29

Figure 13. Contributing recharge area to well PSW-1 and ground-water residence time, Woodbury, Connecticut.

PSW-4

PSW-3

PSW-5

PSW-1

PSW-2

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

41° 32'

41° 31'

73°13' 73°12' 73°11' 73°10 '

0 0.5 1 KILOMETER

0 0.5 1 MILE

Public-supply well and number

Simulated residence time, in years

Contributing area to PSW-1

Boundary of Small-Area Simulation area 

EXPLANATION

PSW-1

0.1 to 1.0

greater than 1.0 to 5.0

greater than 5.0 to 10.0

greater than 10.0 to 30.0

Pomperaug

River

South Brook
30 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

using tritium/helium data of 5.5 and 6.6 years (samples for 

age dating were collected twice from this well). Although the 

observed and simulated residence times are similar, ground 

water pumped from PSW-1 contains a range of residence 

times (figs. 13 and 14 combined). Of the water pumped from 

this well, 10 percent is less than 1.9 years old, and 10 percent 

is more than 9 years old (table 7). The residence times are 

shortest (about 1 year) in KFLUV near PSW-1. There are at 

least two modes to the distribution of ages, one mode with 

residence times less than 5 years and one mode with residence 

times greater than 5 years. About 34 percent of the groundwater in PSW-1 is younger than 5 years and 56 percent of the 

water is between 5 and 9 years (fig. 14).

Residence Time, Land Cover, and Water Quality

Particle tracking was used to relate land use/land cover 

and residence time in the contributing recharge area to the 

water quality in well PSW-1. Each of many particles represents a parcel of water whose chemical quality is determined 

in part by the land use/land cover in the area of recharge. Each 

parcel of water reaches PSW-1 after its characteristic residence 

time, where it mixes with water of different residence times 

and quality. 

Several potential sources of contamination in the contributing recharge area to PSW-1 can be related to land use. 

The most common source of contaminants to the ground 

water in unsewered residential areas is septic systems, which 

receive domestic waste, wastewater, and discarded household 

chemicals (Grady, 1994). Other potential contaminants include 

lawn and garden chemicals, wastes from domestic animals, 

and leaky fuel tanks. Concentrations of many water-quality 

constituents, such as chloride, dissolved solids, and nitrate, are 

significantly higher in residential areas than in undeveloped 

areas; however, ground-water quality in residential areas is 

highly variable. Grady (1994) found similar concentrations 

of these water-quality constituents in sewered and unsewered 

residential areas. The reasons include leaky sewer lines and 

the heavy use of lawn fertilizer in densely populated sewered areas. The use of road de-icing chemicals affects water 

quality in developed areas as well as in undeveloped areas, 

to the extent that roads are present in the undeveloped areas. 

Impervious surfaces, such as those in the commercial areas in 

the study area, also are sources of contaminants to the ground 

water where runoff enters the aquifer through dry wells. Contaminants come from materials that accumulate on impervious surfaces, including detritus, litter, and dust that contain 

chemicals from parking lot seal coat; motor vehicle emissions; 

road wear; decaying vegetation and animal waste; litter and 

garbage; de-icing chemicals; leaks and spills from vehicles; 

and rainfall (Grady, 1994). 

Land-cover changes in Connecticut over the past 

two decades are documented in a series of satellite images 

(University of Connecticut, 2003) from 1985, 1990, 1995, 

and 2002. Land cover, when interpreted from satellite images, 

does not indicate what the land is used for, so land cover 

and land use are different but related concepts (table 8). The 

available geographic data are for land cover, and the available 

water-quality data are for land use. The “developed” landcover category includes residential, commercial, institutional, 

and industrial land, transportation and infrastructure 

easements, golf courses, parks, and cemeteries. Areas of turf 

and grass also are considered developed because they are often 

associated with residential land. 

Developed land in the SAS area is primarily a mixture 

of low-to-medium density residential areas, commercial areas, 

and transportation easements. Undeveloped land includes 

deciduous and coniferous forest, water, wetlands, quarries, 

utility rights-of-way, and low-density residential areas that 

have a tree cover. Water that recharged in developed land is 

the dominant ground water at shallow depths (table 9 and 

figs. 15–18). Water deeper in the aquifer tends to be a mixture 

of water that recharged in the uplands in undeveloped, developed, and agricultural land cover.

Land cover is not static, as discussed in the Introduction 

of this report, and changes in land cover complicate the 

relation between the residence time and chemical quality of 

ground water (figs. 15–18). From 1985 to 2002, developed 

land in the contributing recharge area to PSW-1 increased 

from 28 to 34 percent of the contributing recharge area, 

a process illustrated by the conversion of green and red 

symbols to black symbols between the left and right graphs 

on figures 15 to 18. Because of different rates in recharge in 

the contributing recharge area, the percentage of recharge to 

PSW-1 from developed land increased from 38 percent in 

1985 to 45 percent in 2002. The percentage of agricultural 

land in the contributing recharge area was relatively constant 

from 1985 to 2002, about 25 percent, and the percentage of 

water from agricultural land in PSW-1 was about 20 percent. 

Residence time indicates when water from a particular 

land use reaches PSW-1. Vertical profiles of shallow groundwater residence time generally show an increase of residence 

time with depth (figs. 15–18). Deeper in the aquifer, where the 

source of water is primarily the uplands, the profiles generally 

show a more uniform residence time with depth. Deviations 

from the general patterns are the result of different flow paths 

intersecting a well screen, and age inversions in wells (older 

water over younger water) can occur (figs. 15–18). Sampling 

water from any well yields a mixture of water recharged 

beneath different land covers and of different ages. In general, 

water is stratified by residence time and by land cover.

Historical concentrations can be reconstructed and 

projected into the future using information on land-cover 

changes and residence-time distributions. Examples are given 

here for nitrate and dissolved solids. Nitrate concentrations 

are highest in ground water beneath agricultural land, intermediate in developed areas, and lowest in undeveloped areas 

(table 10), and as land is developed, nitrate concentrations 

in shallow ground water can change. The conversion of 

agricultural land to developed land can cause a decrease in 

nitrate concentrations, whereas the conversion of undeveloped land to developed land can result in an increase. The 
Simulations of Ground-Water Flow and Residence Time 31

Figure 14. Cumulative frequency distribution and frequency distribution of simulated residence 

times, Woodbury, Connecticut.

5 10 15 20

0

20

40

60

80

100

CUMULATIVE RECHARGE, IN PERCENT

Mean flow-weighted residence 

time is 5.9 years

RESIDENCE TIME, IN YEARS

0

5

10

15

20

25

PERCENTAGE OF RECHARGE

 IN EACH AGE CATEGORY

0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

A

B
32 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

concentration of dissolved solids is a widely used indicator 

of overall water quality, and the median concentration of 

dissolved solids in ground water from developed areas is twice 

that in water from undeveloped areas (table 10). As land is 

developed, the concentration of dissolved solids in shallow 

ground water is likely to increase.

The changes in land cover in the contributing recharge 

area to PSW-1 are small, and the predicted changes in water 

quality are smaller than what can be measured reliably, but 

the following approach nonetheless illustrates the effect of 

changes in land cover on the quality of public-drinking water. 

Simulated concentrations of nitrate in water from PSW-1 

decreased (though almost indistinguishably on fig. 19) from 

1985 to 1995 because of the conversion of agricultural land 

to developed land, but then began to increase after 1995, also 

almost imperceptibly, because of the conversion of undeveloped land to developed land (fig. 19; gray line). A similar but 

slightly more pronounced effect can be shown by using the 

median nitrate concentrations reported by Grady (1994) for 

commercial land (fig. 19; red line). This provides a reasonable 

lower and upper bound on nitrate concentrations, because the 

contributing recharge area to well PSW-1 is mixed commercial 

and residential land. Concentrations of dissolved solids, on the 

other hand, increase over the entire period (fig. 20) as undeveloped and agricultural land is developed. Concentrations of 

other water-quality constituents such as chloride, alkalinity, 

and sulfate show patterns similar to those for dissolved solids. 

The nitrate concentrations (Grady and Mullaney, 1998) 

assigned to general land-cover categories are not representative of individual sources of contamination. To extrapolate the 

contribution of nitrate from individual septic systems in the 

contributing recharge area, nitrate loading for each household 

was calculated. First, the nitrate load at PSW-1 was calculated. 

PSW-1 pumps 391.7 m3/d, and the mean nitrate concentration 

measured during this study was 1.9 mg/L (C.J. Brown, U.S. 

Geological Survey, written commun., 2007), yielding a nitrate 

load of 744 g/d. If, in the worst case, septic systems were the 

only source of nitrate, each of the approximately 42 septic systems in the contributing recharge area contributes about 18 g/d 

of nitrate. Next, the average rate at which water flows through 

a septic system was calculated. Each household discharges 

about 0.60 m3/d to their septic system, based on a household 

water use of 0.28 cubic meters per person per day (Hutson and 

others, 2005), 2.68 people/household (U.S. Census Bureau, 

2007b), and a factor of 0.80 to account for consumptive losses, 

such as evaporation (Solley and others, 1998). The average 

concentration of nitrate needed to supply 18 g/d of nitrate at 

this flow rate is 30 mg/L, which is higher than that in samples 

from wells that are downgradient of septic-system drain fields 

(17 mg/L at WY90 and 19 mg/L at WY85). The calculated 

concentration is higher than the measured concentrations for 

two possible reasons: some of the nitrate load in PSW-1 is not 

from septic sources (which is likely, in part), or that the measured concentrations of nitrate are not representative of shallow ground water downgradient from septic systems. Water 

Table 8. Relation of land-cover and land-use categories as 

used in this report, Woodbury, Connecticut.

Land cover Land use

Developed Urban

Turf and grasses Urban

Other grasses and agriculture Agriculture

Deciduous forest Undeveloped

Coniferous forest Undeveloped

Forested wetland Undeveloped

Non-forested wetland Undeveloped

Barren Undeveloped

Table 7. Selected characteristics of the contributing recharge area to well PSW-1, Woodbury, Connecticut.

Percentile 

or mean

Residence time of water, 

in years

Flow path length, 

in kilometers

Velocity of water, 

in meters per day

Residence time of water 

in glacial deposits, 

in years

Residence time of water 

in bedrock, 

in years

10th 1.93 0.34 0.02 1.30 0.00

25th 3.77 .51 .03 2.37 .00

50th 6.21 .98 .03 3.88 .46

75th 7.91 1.45 .04 5.91 3.11

90th 8.98 1.75 .05 7.31 4.91

Mean 5.91 1.01 .03 4.20 1.71
Simulations of Ground-Water Flow and Residence Time 33

Table 9. Percentage of backward-tracked particles started from monitoring well screens by land-use category for the 

small-area simulation model, Woodbury, Connecticut.

[--, simulated position of well screen is dry; blank line separates clusters of wells; vertical well-screen position: Deep wells are screened in the 

lower third of glacial deposits; middle wells are screened in the middle third of glacial deposits; shallow wells are screened in the upper third of 

glacial deposits; bedrock means well is screened in bedrock]

Well name Percentage of particles by land use Vertical well-screen position Developed Agriculture Undeveloped

WY69 90 0 10 Deep

WY70 100 0 0 Middle

WY71 -- -- -- Shallow

WY72 20 0 80 Deep

WY73 100 0 0 Middle

WY74 -- -- -- Shallow

WY75 100 0 0 Deep

WY76 -- -- -- Shallow

WY77 100 0 0 Deep

WY78 -- -- -- Shallow

WY79 100 0 0 Shallow

WY80 10 0 90 Deep

WY81 100 0 0 Shallow

WY82 60 30 10 Deep

WY83 100 0 0 Middle

WY84 90 0 10 Deep

WY85 100 0 0 Shallow

WY86 100 0 0 Bedrock

WY87 0 0 100 Bedrock

WY88 -- -- 40 Deep

WY89 0 0 100 Deep

WY90 0 0 100 Deep

WY91 80 0 20 Middle

WY92 100 0 0 Shallow

WY93 0 0 100 Deep

WY94 0 0 100 Middle

WY95 100 0 0 Shallow

WY96 -- -- -- Middle

WY97 100 0 0 Bedrock

WY98 80 0 20 Deep

WY99 100 0 0 Middle

WY100 100 0 0 Middle

WY101 80 0 20 Deep

WY102 0 30 70 Shallow

WY106 0 0 100 Bedrock
34 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 15. Relation of residence time, land use, and source of water for 

PSW-1, Woodbury, Connecticut.

30

25

20

15

10

5

0

Well and identifier—position shows depth and 

measured tritium/helium age date (two samples

are plotted)

1985 Land use 2002 Land use

30

25

20

15

10

5

0

DEPTH BELOW SIMULATED WATER TABLE, IN METERS

Upland recharge, undeveloped land use

Upland recharge, agricultural land use

Upland recharge, developed land use

Valley recharge, undeveloped land use

Valley recharge, agricultural land use

Valley recharge, developed land use

PSW-1

Bedrock

AGE, IN YEARS

PSW-1

Glacial

deposits

EXPLANATION

0 3 6 9 12 0 3 6 9 12

Recharge
Simulations of Ground-Water Flow and Residence Time 35

1985 Land use 2002 Land use

WY70

WY71

DEPTH BELOW SIMULATED WATER TABLE, IN METERS

Upland recharge, undeveloped land use

Upland recharge, agricultural land use

Upland recharge, developed land use

Valley recharge, undeveloped land use

Valley recharge, agricultural land use

Valley recharge, developed land use

WY69

Glacial

deposits

Bedrock

AGE, IN YEARS

WY69

30

25

20

15

10

5

0

0 3 6 9 12 0 3 6 9 12

30

25

20

15

10

5

0

EXPLANATION

Well and identifier—position shows depth and 

measured tritium/helium age date

Recharge

Figure 16. Relation of residence time, land use, and source of water 

for cluster of shallow, medium, and deep wells WY71, WY70, and WY69, 

Woodbury, Connecticut.
36 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 17. Relation of residence time, land use, and source of water 

for cluster of shallow, medium, and deep wells WY74, WY73, and WY72, 

Woodbury, Connecticut.

1985 Land use 2002 Land use

WY73

WY74

DEPTH BELOW SIMULATED WATER TABLE, IN METERS

Upland recharge, undeveloped land use

Upland recharge, agricultural land use

Upland recharge, developed land use

Valley recharge, undeveloped land use

Valley recharge, agricultural land use

Valley recharge, developed land use

WY72

Glacial

deposits

Bedrock

WY72

AGE, IN YEARS

0 3 6 9 12 0 3 6 9 12

30

25

20

15

10

5

0

30

25

20

15

10

5

0

EXPLANATION

Well and identifier—position shows depth and 

measured tritium/helium age date

Recharge
Simulations of Ground-Water Flow and Residence Time 37

Figure 18. Relation of residence time, land use, and source of water for 

cluster of shallow and deep wells WY76 and WY75, Woodbury, Connecticut.

2002 Land use 1985 Land use

WY75

WY76

DEPTH BELOW SIMULATED WATER TABLE, IN METERS

Upland recharge, undeveloped land use

Upland recharge, agricultural land use

Upland recharge, developed land use

Valley recharge, undeveloped land use

Valley recharge, agricultural land use

Valley recharge, developed land use

WY75

Glacial

deposits

Bedrock

AGE, IN YEARS

0 3 6 9 12 0 3 6 9 12

30

25

20

15

10

5

0

30

25

20

15

10

5

0

EXPLANATION

Well and identifier—position shows depth and 

measured tritium/helium age date

Recharge
38 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Table 10. Median concentrations of selected constituents used to represent various land uses, Woodbury, Connecticut.

[All concentrations in milligrams per liter; NR, not reported]

Constituent Undeveloped Agriculture Developed Commercial

Alkalinity 10 15 16 NR

Chloride 3.1 12 29 36

Nitrate as nitrogen .14 3.8 1.1 3.4

Sulfate 48 58 104 19.5

Dissolved solids 98 162 217 241.5

Figure 19. Simulated and predicted trend in concentration of nitrate in PSW-1, 

Woodbury, Connecticut.

1985 1990 1995 2000 2005 2010

YEAR

0

1

2

3

CONCENTRATION OF NITRATE, IN MILLIGRAMS PER LITER

EXPLANATION

Measured concentration of nitrate. Data are from

United Water Company files and this study.

Simulated trend using a concentration of nitrate of 1.1 milligrams per liter

typical of ground water beneath developed land.

Simulated trend using typical loading from septic systems.

Simulated trend using a concentration of nitrate of 3.4 milligrams per liter

typical of ground water beneath commercial land.
Simulations of Ground-Water Flow and Residence Time 39

follows the general population trend (fig. 21). The population and number of septic systems remained low until about 

1950, when the rate of growth increased. The rate of increase 

may have leveled off in recent years as developable land has 

become scarcer. In recent years, septic systems have been 

added at the approximate rate of three systems every 4 years 

(fig. 21). If this rate continues in the future, nitrate concentrations can be predicted based on the individual system contribution of 0.045 mg/L nitrate (fig. 19).

The projected nitrate trends bracket most measured 

nitrate concentrations (fig. 19); however, there appears to be 

a trend in measured nitrate that is not captured by the predictions. Possible explanations include: (1) any real trend in the 

data is obscured by sampling methods and seasonal variation 

in nitrate values (for example, the concentrations of 0.9 and 

samples from glacial aquifers at other sites downgradient 

from septic-system drain fields have higher nitrate concentrations. Robertson and others (1991) measured concentrations 

of 33 and 39 mg/L of nitrate at two domestic septic-system 

sites, and Harman and others (1996) measured concentrations 

of 50 mg/L of nitrate at a school septic-system site. Although 

nitrate concentrations can be lowered through denitrification 

in an anoxic environment, the aquifer system in the SAS area 

is mostly oxic (McMahon and others, in press), and the rate of 

denitrification can be assumed to be small. If septic systems 

are assumed to be the only source of nitrate in PSW-1, each 

additional septic system in the contributing recharge area 

contributes 0.045 mg/L of nitrate to PSW-1. The number of 

houses that could have septic systems (based on land records 

in the town of Woodbury) in the contributing recharge area 

1985 1990 1995 2000 2005 2010

YEAR

150

160

170

180

190

200

CONCENTRATION OF DISSOLVED SOLIDS,

 IN MILLIGRAMS PER LITER

EXPLANATION

Measured concentration of dissolved solids. Data are from this study.

Predicted trend using a concentration of dissolved solids of 217 milligrams per liter

typical of ground water beneath urban land.

Predicted trend using a concentration of dissolved solids of 241.5 milligrams per liter

typical of ground water beneath commercial land.

Figure 20. Simulated and predicted trend in concentration of dissolved solids in PSW-1, 

Woodbury, Connecticut.
40 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

1800 1850 1900 1950 2000

YEAR

0

10

20

30

40

50

NUMBER OF SEPTIC SYSTEMS

EXPLANATION

Cumulative number of septic systems in the

area contributing recharge to well PSW-1.

Data are from town of Woodbury land records. 

Figure 21. Number of septic systems in the contributing recharge area to well PSW-1, 

Woodbury, Connecticut.

uncertainty in the estimated values. This uncertainty can be 

propagated through the contributing recharge area analysis 

using a Monte Carlo technique, as described by Starn and 

others (2000). The result of this procedure is a probabilistic 

contributing recharge area. The results show a greater degree 

of certainty in the delineation of the contributing recharge 

area near PSW-1, and, as one moves backward in time and 

space toward the recharge areas, the uncertainty in the model 

increases (the effect of uncertainty in model parameter 

estimates causes increasing uncertainty in the boundaries of 

the contributing recharge area) (fig. 22). The area that could 

possibly contribute water to PSW-1 is much larger than the 

contributing recharge area delineated in figure 13. The effect 

of this uncertainty on the reconstruction of nitrate history 

is that the 0.045 mg/L of nitrate that may be added by each 

additional septic system could include many more houses than 

were originally included in the contributing recharge area. 

Considering the probabilistic contributing recharge area in 

figure 22, the number of land parcels, and therefore, potential 

septic systems, could be double the initial estimate (fig. 23). 

3.0 shown are substantially outside the range of other values 

and may be in error), (2) there is a source of nitrate that is not 

accounted for (for example, a higher mean nitrate concentration in recharge from the multiple-residence septic systems 

that are present in the area), or (3) despite good indications 

that the model reproduces actual conditions well, small 

changes in the model could lead to simulations that predict 

disproportionate changes in water quality (for example, a large 

community septic system located just outside the contributing 

recharge area might be included in the contributing recharge 

area if the model were changed slightly). In any case, the predicted trends give reasonable estimates of nitrate concentration 

in PSW-1, and the predicted trends are small. 

Model Uncertainties and Limitations

The discussion in the previous section is based on results 

of the SAS model, which was calibrated using a nonlinear 

regression technique. The regression produces information 

about how well the model is calibrated, in other words, about 
Simulations of Ground-Water Flow and Residence Time 41

Figure 22. Probabilistic contributing recharge area to well PSW-1 for the small-area simulation model, Woodbury, Connecticut.

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

PSW-4

PSW-3

PSW-5

PSW-1

PSW-2

41° 32'

41° 31'

73°13' 73°12' 73°11' 73°10 '

Public-supply well and number

Simulated probability for contributing recharge area

Contributing area to PSW-1, as shown on figure 13

Boundary of Small-Area Simulation area 

EXPLANATION

PSW-1

0.0 to 0.2

greater than 0.2 to 0.4

greater than 0.4 to 0.6

greater than 0.6 to 0.8

Pomperaug

River

South Brook

0 0.5 1 KILOMETER

0 0.5 1 MILE
42 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

Figure 23. Probabilistic contributing recharge area and land parcels for the small-area simulation model, Woodbury, Connecticut.

Base from Connecticut Department of 

Environmental Protection, 1994, 1:24,000

Projection: State Plane Feet Zone 3526

PSW-4

PSW-3

PSW-5

PSW-1

PSW-2

41° 32'

41° 31'

73°13' 73°12' 73°11' 73°10 '

Public-supply well and number

Simulated probability for contributing recharge area

Boundary and center of land parcel

Boundary of Small-Area Simulation area 

EXPLANATION

PSW-1

0.0 to 0.2

greater than 0.2 to 0.4

greater than 0.4 to 0.6

greater than 0.6 to 0.8

Pomperaug

River

South Brook

0 0.5 1 KILOMETER

0 0.5 1 MILE
Summary and Conclusions 43

Summary and Conclusions

In 2001, the U.S. Geological Survey’s National WaterQuality Assessment (NAWQA) Program began an intensive 

study to assess the vulnerability of public-supply wells to 

contamination from a variety of compounds. As part of that 

study, a simulation model of ground-water flow in the aquifer at Woodbury, Connecticut, was constructed to estimate 

hydraulic parameters, water-budget components, and groundwater residence times. Advective particle tracking was used to 

estimate contributing recharge areas to monitoring wells and 

water-supply wells and to estimate the distribution of apparent 

ground-water residence time.

Hydraulic conductivities estimated with the model ranged 

from 6.2 to 18 meters per day (m/d) in glacial stratified deposits, 0.01 to 0.04 m/d in compact till, and 0.04 to 0.14 m/d in 

bedrock. Hydraulic conductivities that could not be estimated 

with the model were set at fixed values of 2.3 m/d in gravel 

overlying lake-bottom deposits, 0.3 m/d in loose surface till, 

and 0.3 m/d in Pomperaug River streambed material. Porosities also were set at fixed values of 0.3 in glacial stratified 

deposits, 0.1 in till, and 0.001 in bedrock. 

Recharge to the uplands is dominated by precipitation. 

Fifty percent of upland recharge flows downward to bedrock, 

31 percent to streams, and 16 percent to glacial stratified 

deposits in the valley. Recharge to glacial deposits in the 

valley is from precipitation (32 percent), upward flow from 

bedrock (34 percent), and flow across external boundaries 

(19 percent). Dry wells (storm drains that discharge to 

ground water) and losing stream reaches also are a source of 

ground water to the glacial deposits in the valley. 

Water withdrawn from a well is a mixture of waters with 

different residence times, and a single residence time does not 

fully characterize the susceptibility of the well to recent contamination. The mean simulated flow-weighted residence time 

in water from PSW-1 is 5.9 years, which compares reasonably 

well with the apparent residence time measured using tritium/

helium data of 5.5 and 6.6 years (samples for age dating 

were collected twice from this well). Water from PSW-1 is a 

mixture of water recharged in glacial stratified deposits in the 

valley that is younger than 5 years (34 percent) and water from 

the upland that is 5 to 20 years old (66 percent). 

Vertical profiles of shallow ground-water residence time 

generally show an increase of residence time with depth. 

Deeper in the aquifer, where the source of water is primarily 

the uplands, the profiles generally show a more uniform residence time with depth. Deviations from the general patterns 

are the result of different flow paths intersecting a well screen, 

and age inversions in wells (older water over younger water) 

can occur. Sampling water from any well yields a mixture of 

water recharged beneath different land covers and of different 

ages. In general, the ground water is stratified by residence 

time and by land cover.

About 16 percent of the water withdrawn from PSW-1 

comes from dry wells in a commercial area. The residence 

time for water that originated as recharge in the dry wells 

ranges from 1.6 to 3.8 years, and the mean residence time is 

2.5 years. Dry wells are a fast pathway for water to enter the 

aquifer and provide a significant amount of water to PSW-1.

Changes in land cover in the contributing recharge area 

to PSW-1 are small, and predicted changes in water quality 

are smaller than what can be measured reliably, but the 

approach illustrates the effect of changes in land cover on 

the quality of public-drinking water. For example, nitrate 

concentrations decreased from 1985 to 1995 because of the 

conversion from agricultural land to developed land, but 

then began to increase after 1995 because of the conversion 

of undeveloped land to developed land. Concentrations of 

dissolved solids, on the other hand, increase over the entire 

period as land is developed. 

One of the main sources of nitrate in the area is 

septic-tank drain fields from single- and multiple-family 

developments. The estimated nitrate loading rate from a single 

family septic system is 18 grams per day. If each household 

in the contributing recharge area to PSW-1 contributes nitrate 

at that loading rate to the well PSW-1, each additional septic 

system in the contributing recharge area is responsible for a 

0.045-milligrams per liter increase in nitrate at PSW-1. 

Uncertainty in the SAS model can be propagated through 

the contributing recharge area analysis using a Monte Carlo 

technique. There is a greater degree of certainty in the delineation of the contributing recharge area near PSW-1, and as one 

moves toward the recharge areas, the uncertainty in the model 

increases. The area that possibly contributes water to PSW-1 

is much larger than the contributing recharge area delineated 

using the optimal parameter estimates. 

Acknowledgments

This study could not have been done without the 

cooperation of the Pomperaug River Watershed Coalition, 

especially board members Larry Pond, Marc Taylor, and 

Dick Leavenworth, and Executive Directors Laurie Gianotti 

and Hunter Brawley, as well as Kevin Moran (United Water 

Company) and Ernie Coppack (Watertown Fire District). 

USGS personnel who greatly contributed to the study include 

Remo Mondazzi, David Bjerklie, and Claudia Tamayo. 

Leon Kauffman provided invaluable assistance with 

intersecting particle-tracking results with GIS coverages. 
44 Simulations of Ground-Water Flow and Residence Time near Woodbury, Connecticut

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