Michigan Department of Environmental Quality 

Hydrogeology and Simulation of Regional 

Ground-Water-Level Declines in 

Monroe County, Michigan 

Water-Resources Investigations Report 03-4312
	

U.S. Department of the Interior 

U.S. Gelogical Survey 
Hydrogeology and Simulation of Regional 

Ground-Water-Level Declines in 

Monroe County, Michigan 

By Howard W. Reeves, Kirsten V. Wright, and J. R. Nicholas 

In cooperation with the Michigan Department of Environmental Quality 

Water-Resources Investigations Report 03-4312 

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. DEPARTMENT OF THE INTERIOR 

Gale A. Norton, Secretary 

U.S. GEOLOGICAL SURVEY 

Charles G. Groat, Director 

U.S. Geological Survey, Lansing, Michigan: 2004 

For sale by U.S. Geological Survey, Information Services
	

Box 25286, Denver Federal Center
	

Denver, CO 80225
	

For more information about the USGS and its products:
	

Telephone:1-888-ASK-USGS
	

World Wide Web: http://www.usgs.gov/
	

Any use of trade, product, or firm names in this publication is for descriptive purposes only 

and does not imply endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted materials contained within this report. 
Contents Page 

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

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

 Purpose and scope...............................................................................................................................................2

 Description of the study area ..............................................................................................................................2

 Previous studies ..................................................................................................................................................2
	

Acknowledgment ................................................................................................................................................2
	

Hydrogeology ..........................................................................................................................................................5

 Glacial deposits...................................................................................................................................................5

 Hydraulic properties.......................................................................................................................................5
	

Water-level changes .......................................................................................................................................7

 Recharge ........................................................................................................................................................7

 Discharge .......................................................................................................................................................9

 Bedrock aquifer...................................................................................................................................................9

 Hydraulic properties.....................................................................................................................................12
	

Water-level changes .....................................................................................................................................15

 Leakage........................................................................................................................................................22

 Discharge .....................................................................................................................................................24
	

Water use................................................................................................................................................................24

 Public, self-supplied, and industrial water use..................................................................................................26
	

Agricultural irrigation .......................................................................................................................................26

 Golf-course irrigation........................................................................................................................................26

 Quarry dewatering ............................................................................................................................................26
	

Simulation of ground-water flow...........................................................................................................................28

 Numerical model...............................................................................................................................................28

 Map projection and units used ..........................................................................................................................33

 Relation between numerical and conceptual models........................................................................................33
	

Time periods simulated.....................................................................................................................................35

 Model calibration..............................................................................................................................................35

 Exploration of ground-water-level declines......................................................................................................48

 Ground-water capture ..................................................................................................................................48

 2001 simulations ..........................................................................................................................................49

 Sensitivity to imposed boundaries...............................................................................................................56

 Sensitivity to bedrock hydrogeologic parameters........................................................................................57
	

Water-level declines .....................................................................................................................................57

 Model limitations..............................................................................................................................................65
	

Summary and conclusions .....................................................................................................................................68
	

References cited.....................................................................................................................................................69
	

Appendix A. Water-level data .............................................................................................................................A-1
	

Appendix B. Monroe County statistics summary...............................................................................................B-1
	

Appendix C. WelLogic analysis..........................................................................................................................C-1
	

iii
 
Figures Page 

1-4. Maps showing:

 1. Study area in Monroe County and surrounding counties in Michigan and Ohio ...........................................3

 2. U.S. Geological Survey streamflow-gaging stations and monitoring wells in 

 Monroe County, Michigan..............................................................................................................................4

 3. Generalized glacial deposit map for study area, modified from Ferrand and Bell (1982) 

and Ohio Department of Natural Resources (2000b) .....................................................................................6

 4. Estimated log(Kveff) for Monroe County, Michigan, based on thickness and lithology of 

 units reported in the WelLogic database. Shaded areas are glacial deposits mapped by 

Ferrand and Bell (1982)..................................................................................................................................8

 5. Graph showing yearly difference in annual precipitation from long-term average at the 

 Monroe County Waterworks Monroe County, Michigan, 1970-2002 ..........................................................10
	

6-8. Maps showing:

 6. Bedrock units for Monroe County, Michigan and regional bedrock setting from 

Milstein (1987), Indiana Geological Survey (2002), Ohio Department of 

Natural Resources (2000a)............................................................................................................................ 11

 7. Potentiometric surface for bedrock aquifer, 1993, for Monroe County, Michigan, 

(from Nicholas and others 1996) .................................................................................................................13

 8. Time sequence of wells open to the bedrock aquifer showing confined (water level at least 

 one foot above top of bedrock) or unconfined (water level at least one foot below top of 

 bedrock) conditions, Monroe County, Michigan, 1960 to 2002 (data from 

WelLogic database).......................................................................................................................................14
	

9, 10. Graphs showing:

 9. Hydrograph for U.S. Geological Survey observation well GLTO which is open to the 

 bedrock aquifer, Monroe County, Michigan, 1978-2003. The change in amplitude of 

 yearly response indicates a change from locally confined to locally unconfined conditions .......................16

 10. Trend in reported depth to ground water for Exeter Township, Monroe County, Michigan, 

 data from the WelLogic database. Note the general decline in water level

 from 1990 to 2002.........................................................................................................................................18
	

11-14. Maps showing: 

11. Estimated and observed ground-water-level declines, Monroe County, Michigan, 1991-2001...................19

 12. Potentiometric surface for bedrock aquifer, 1988-1991, developed from WelLogic 

 ground-water-level records and loess function, Monroe County, Michigan.................................................20

 13. Estimated difference in potentiometric surface in bedrock aquifer in Monroe County, 

 Michigan based on WelLogic ground-water levels and loess function. ((a) (1988-1991) - 

(1964-1967) surfaces and (b) (2000-2003) - (1964-1967) surfaces.)...........................................................21
	

iv
 
 Figures--Continued Page

 14. Estimated effective vertical hydraulic conductivity and estimated change in potentiometric 

 surface from WelLogic data base and loess function (2000-2003) - (1967-1964). Area of small 

 change corresponds to area where the effective vertical hydraulic conductivity is greatest, 

 Monroe County, Michigan..........................................................................................................................23
	

15-18. Graphs showing: 

15. Hydrograph of Lake Erie from the CO-OPS National Water Level Observation Network 

 (NWLON) database at Fermi Power Station (station number 9063090), Monroe County, 

Michigan. Lake Erie level was both above and below long-term average between 

1991-2001 when ground-water levels were observed to decline................................................................25

 16. Reported London Quarry discharge and computed flow at the N.B. Amos Palmer Drain 

 streamflow-gaging station, Monroe County, Michigan. Also shown are precipitation values 

 recorded at the Dundee Farms weather station (Michigan Automated Weather Network, 

Michigan State University) ........................................................................................................................29

 17. Reported discharge from London Quarry and computed discharge at the N.B. Amos 

 Palmer Drain gage, Monroe County, Michigan..........................................................................................30

 18. Reported quarry discharges, Monroe County, Michigan, 2002-2003. Values where gaged 

 by U.S. Geological Survey at streams receiving discharge in July, 2003 also are shown..........................31
	

19-22. Maps showing:

 19. Model area and boundary conditions in the study area, Monroe County, Michigan and 

surrounding area..........................................................................................................................................32

 20. Map of major ground-water withdrawals within the study area, Monroe County, 

Michigan and surrounding area ..................................................................................................................36

 21. Simulated hydraulic heads for 1991 trial for study area Monroe County, Michigan 

and surrounding area...................................................................................................................................41

 22. Distribution of residuals (observed - simulated) for water levels in the study area 

 (Monroe County, Michigan and surrounding area) for 1991 final parameters ...........................................42

 23. Simulated and observed hydraulic heads for bedrock aquifer wells in the study area 

 (Monroe County, Michigan and surrounding area). U.S. Geological Survey G wells 

and data from Breen and Dumouchelle (1990) are distinguished from 

WelLogic water-well values.......................................................................................................................43

 24. Map showing simulated predevelopment hydraulic heads for the study area (Monroe County, 

Michigan and surrounding area) using calibrated values determined using 1991 simulation 

and constrained by predevelopment conditions..........................................................................................44
	

25, 26. Graphs showing:

 25. Weighted residuals and weighted simulated values for the model of the study area (Monroe 

County Michigan and surrounding area). Residuals are reasonably scattered positive and 

 negative and they do not show definite trends as the weighted simulated value changes..........................46

 26. Composite-scaled sensitivities for all parameters used to define the model of study area 

 (Monroe County, Michigan and surrounding area).....................................................................................47
	 v
Figures--Continued Page 

29-31. Maps showing: 

27. Simulated potential flux direction between glacial deposits and bedrock aquifer for the study 

 area (Monroe County, Michigan and surrounding area) under predevelopment conditions .....................50

 28. Simulated potential flux direction between glacial deposits and bedrock aquifer for the 

 study area (Monroe County, Michigan and surrounding area) under 1991 conditions ..............................51

 29. 2001 steady-state simulated hydraulic heads using 1991 calibrated parameters of the 

 study area (Monroe County, Michigan and surrounding area) ..................................................................52 

30. Difference between simulated hydraulic heads, 1991-2001 for the study area (Monroe 

 County, Michigan and surrounding area)...................................................................................................53

 31. Simulated effect on 2001 hydraulic heads because of a 3.28-foot lowering of the water 

 table in the glacial deposits across the study area (Monroe County, Michigan and 

surrounding area) .......................................................................................................................................58
	

32-35. Graphs showing:

 32. Change in hydraulic head for 2001 simulation at (a) G2 and (b) G7 from varying model 

parameters..................................................................................................................................................59

 33. Change in flux from 2001 calibrated simulations because of changes in leakage from the 

 glacial deposits in the study area for the (a) Lacustrine Clay, (b) Lacustrine Sand and 

(c) Moraine.................................................................................................................................................60

 34. Change in hydraulic head for 1991 simulation at (a) G2, (b) G7, (c) G13 from varying 

model parameters.......................................................................................................................................61

 34a. Change in hydraulic head for 1991 simulation at (d) G33, and (e) GLTO from varying 

model parameters......................................................................................................................................62

 35. Drawdown near Hanson Quarry and radius of influence line....................................................................63
	

36-37. Maps showing:

 36. Simulated recovery from 2001 conditions if quarry discharges are removed for the study 

 area (Monroe County, Michigan and surrounding area)............................................................................66

 37. Simulated recovery for study area (Monroe County, Michigan and surrounding area) 

 under 2001 steady-state conditions if London Quarry discharge is removed............................................67
	

vi
 
Tables Page

 1. Self-supplied fresh ground-water use in Monroe County, Michigan.........................................................27 

2. Community public-water supplies in study area, January 2003 ................................................................27 

3. Reported self-supplied industrial and quarry ground-water use in the Ohio portion of the 

study area ...................................................................................................................................................27

 4. Estimated agricultural irrigation ground-water use in Monroe County, Michigan....................................27 

5. Time periods simulated in the ground-water flow model of the Monroe County 

regional study.............................................................................................................................................37 

6. Parameters used in numerical model with parameter type and final calibrated values .............................38 

7. Quarry and spring discharges used in calibration of 1991 regional model of the study area 

 and final simulated flows ...........................................................................................................................45

 8. Fluxes from calibrated models and assessment of changes from virgin rates of recharge 

 and discharge for the study area.................................................................................................................49

 9. Simulated and reported quarry discharges for the 2001 steady-state simulation.......................................54 

10. Simulation results from 2001 steady-state simulation with observed 2001 values 

and residuals for U.S. Geological Survey monitoring wells in the study area ..........................................55 

 11. Fluxes from calibrated model and 2001 simulation summarizing ground-water capture..........................56
	

vii
 
________________________________________________________________________________ 

___________________________________________________________________________________________ 

CONVERSION FACTORS, ABBREVIATIONS, AND DATUM 

Multiply By To Obtain 

foot (ft) 0.3048 meter 

mile (mi) 1610 meters 

square mile (mi2) 2.590 square kilometer 

acre 4046.9 square meter 

cubic foot per second (ft3/s) 0.02832 cubic meter per second 

million gallon per day (Mgal/d) 0.04382 cubic meter per second 

foot per day (ft/d) 0.3048 meter per day 

foot per second (ft/s) 0.3048 meter per second 

square foot per day (ft2/d) 0.09290 square meter per day 

inch per year (in/yr) 0.0254 meter per year 

Abbreviations 

DNR Department of Natural Resources 

MDEQ Michigan Department of Environmental Quality 

NLCD National Land Coverage Database 

NPDES National Pollutant Discharge Elimination System 

RASA Regional Aquifer-System Analysis 

USGS U.S. Geological Survey 

Datum 

Vertical coordinate information is referenced to the North Geodetic Vertical Datum of 1929 (NGVD 29). 

Horizontal coordinate information from various sources was projected into the Michigan Georef 

Coordinate system and referenced to the North American Datum of 1983 (NAD 83). 

viii
 
Hydrogeology and Simulation of Regional Ground-WaterLevel Declines in Monroe County, Michigan 

By Howard W. Reeves, Kirsten V. Wright, and J. R. Nicholas 

ABSTRACT 

Observed ground-water-level declines from 1991 to 

2003 in northern Monroe County, Michigan, are 

consistent with increased ground-water demands in the 

region. In 1991, the estimated ground-water use in the 

county was 20 million gallons per day, and 80 percent of 

this total was from quarry dewatering. In 2001, the estimated ground-water use in the county was 30 million gallons per day, and 75 percent of this total was from quarry 

dewatering. 

Prior to approximately 1990, the ground-water demands 

were met by capturing natural discharge from the area and 

by inducing leakage through glacial deposits that cover 

the bedrock aquifer. Increased ground-water demand after 

1990 led to declines in ground-water level as the system 

moves toward a new steady-state. Much of the available 

natural discharge from the bedrock aquifer had been captured by the 1991 conditions, and the response to additional withdrawals resulted in the observed widespread decline 

in water levels. 

The causes of the observed declines were explored 

through the use of a regional ground-water-flow model. 

The model area includes portions of Lenawee, Monroe, 

Washtenaw, and Wayne Counties in Michigan, and portions 

of Fulton, Henry, and Lucas Counties in Ohio. Factors, 

including lowered water-table elevations because of below 

average precipitation during the time period 

(1991 - 2001) and reduction in water supply to the bedrock 

aquifer because of land-use changes, were found to affect 

the regional system, but these factors did not explain the 

regional decline. Potential ground-water capture for the 

bedrock aquifer in Monroe County is limited by the low 

hydraulic conductivity of the overlying glacial deposits and 

shales and the presence of dense saline water within the 

bedrock as it dips into the Michigan Basin to the west and 

north of the county. Hydrogeologic features of the bedrock 

and the overlying glacial deposits were included in the 

model design. An important step of characterizing the bedrock aquifer was the determination of inputs and outputs 

of water—leakage from glacial deposits and flows across 

model boundaries. The imposed demands on the groundwater system create additional discharge from the bedrock 

aquifer, and this discharge is documented by records and 

estimates of water use including: residential and industrial 

use, irrigation, and quarry dewatering. 

Hydrologic characterization of Monroe County and surrounding areas was used to determine the model boundaries and inputs within the ground-water model. 

MODFLOW-2000 was the computer model used to simulate ground-water flow. Predevelopment, 1991, and 2001 

conditions were simulated with the model. The predevelopment model did not include modern water use and 

was compared to information from early settlement of the 

county. The 1991 steady-state model included modern 

demands on the ground-water system and was based on a 

significant amount of data collected for this and previous 

studies. The predevelopment and 1991 simulations were 

used to calibrate the numerical model. The simulation of 

2001 conditions was based on recent data and explored the 

potential ground-water levels if the current conditions persist. Model results indicate that the ground-water level will 

stabilize in the county near current levels if the demands 

imposed during 2001 are held constant. 

INTRODUCTION 

In January 2002, the U.S. Geological Survey (USGS) 

published a report of hydrologic data documenting widespread ground-water-level declines in Monroe County, 

Michigan from 1991 to 2001 (Nicholas and others, 2002). 

Many of the 34 USGS monitoring wells in the county had 

declines ranging from 10 to 20 ft during this time period. 

Long-term ground-water-level declines result from a 

decrease in recharge, an increase in discharge by either 

natural or induced processes, or a combination of the two. 

Additional hydrologic data presented by Nicholas and others (2002), including precipitation, Lake Erie levels, and 

base flow to streams, did not show a systematic change 

consistent with a decrease in recharge. Ground-water use, 

however, increased appreciably from 1991 to 2001. 

In March 2002, USGS and Michigan Department of 

Environmental Quality (MDEQ) entered into a cooperative agreement to study the hydrogeology and determine 

the cause or causes of the widespread ground-water-level 

declines in Monroe County. USGS and MDEQ agreed 

that the primary investigative tool should be a computer 

model—a numerical model of ground-water flow—suitable 

for evaluating changes in recharge and discharge and the 

effects of these changes on ground-water levels in Monroe 

County. 

1
	
PURPOSE AND SCOPE 

The purpose of this report is to investigate probable causes of ground-water-level declines in Monroe 

County, Michigan. The report focuses on the conceptual 

and numerical models of ground-water flow, including 

assumptions, model calibration, model simulations, and 

model limitations. Field data, both collected for this study 

and previously presented by Nicholas and others (2002), 

also are presented and analyzed to describe the hydrogeologic system. Potential reasons for the observed decline in 

ground-water levels are offered based on analysis of the 

field data and simulation results. 

Description of the Study Area 

The study area focuses on Monroe County in southeastern Michigan. The ground-water system, however, is 

regional, and the study area includes portions of Lake Erie 

to the east, Wayne and Washtenaw Counties to the north, 

Lenawee County to the west, and Lucas, Fulton, and 

Henry Counties, Ohio to the south (fig. 1). 

Monroe County is relatively flat. The land-surface 

altitude ranges from 572 ft above NGVD 29 at Lake Erie 

to 740 ft in the northwestern corner of the county. Most 

of the study area is similar topographically to Monroe 

County; glacial moraines in the western part of the study 

area result in higher relief than the rest of the area. The 

land area of Monroe County is 550 mi2; the study area 

is approximately 3,000 mi2. The population of Monroe 

County in 2000 was 145,950 (U.S. Census Bureau, 2001). 

Major rivers in the study area include the Detroit River, 

Huron River, River Raisin, Swan Creek, Stony Creek, and 

the Maumee River in Ohio. The Detroit and Maumee Rivers are considered the northeastern and southern borders 

of the study area, respectively. Historically, much of the 

study area was wetlands. These wetlands were drained 

through the installation of drainage tiles and tile drains 

in the 1800’s to allow for agriculture, and there still are 

many drainage ditches and tile systems in the area. 

Previous Studies 

Historical studies that relate to this work were published by Sherzer (1900), Leverett (1915), Mazola (1970), 

Twenter (1975), and Allen (1977). Geologic maps showing glacial and bedrock stratigraphy in Michigan were developed by Farrand and Bell (1982) and Milstein (1987). 

These maps are used as base information for the Michigan 

portion of the study area. The Ohio Department of Natural 

Resources (2000a, 2000b) developed unconsolidated and 

bedrock aquifer maps that are used as base information 

for the Ohio portion of the study area. Breen (1989, 1991) 

provides recent ground-water information for northwestern Ohio. 

Nicholas and others (1996) present a USGS study of 

the ground-water resources of Monroe County. Most 

of the monitoring wells used in the present study were 

installed as part of the previous USGS study. Nicholas 

and others (1996) provide the baseline ground-water-level 

data used for determining subsequent ground-water-level 

declines in Monroe County. They also provide water-quality information and a water-use summary for the county. 

Nicholas and others (2002) document the ground-water-level declines in the county from 1991 to 2001 using 

water levels measured in 34 monitoring wells by the 

U.S. Geological Survey (USGS) and the Monroe County 

Health Department (fig. 2). 

Two USGS Regional Aquifer-System Analysis (RASA) 

projects provide the regional context for the simulation 

of ground-water flow described in this report. Westjohn 

and Weaver (1998) present the hydrogeologic framework 

for the Michigan Basin RASA. The Midwestern Basins 

and Arches RASA (Bugliosi, 1999) provides additional 

regional information especially relevant to the study area 

boundaries. The ground-water-flow model developed for 

the Midwestern Basins and Arches RASA overlaps slightly with the study area described here; however, the scale 

of that RASA study is too large to be used directly in the 

analysis of the observed ground-water-level declines in 

Monroe County. 

Acknowledgments 

The authors thank Elgar Brown and Brant Fisher from 

MDEQ for their technical support during this project. 

USGS Lansing Field Office staff, including Brian Heissenberger, Tom Morgan, and Daniel Obenauer, installed 

and maintained field equipment and monitored groundwater levels. USGS Network Operations staff, Rose 

McGowan and Suzanne Crowley, managed the databases 

used for water-level and water-quality data. Sharon 

Baltusis, Rose McGowan, and Michele Morenz provided 

important assistance in report preparation. Allen Shapiro, USGS, and Steven Wright, University of Michigan, 

helped with the instrumentation of wells near London Aggregates to monitor water levels after the quarry stopped 

pumping and provided additional assistance on this study 

aspect. The cooperation of Suzanne Hanf from SE Johnson and the personnel at London Aggregates for allowing instrument installation and equipment maintenance 

at their facility is appreciated. Jeff Stoll from Hanson 

Aggregates Midwest provided observation-well data. 

Water-level data collected by the Monroe County Health 

Department from 1993 to 2001 was invaluable for this 

study. The algebraic multigrid solver used in the 

2
	
 

 

!



 





!


	6 
6
6

&20-)2

!.1)*",2)

)#0"*2"0

)*",

3,%&&

-,0-&

&2&01#30(



 -*&%-












 		

0 10 20 MILES 

0 10 20 KILOMETERS 

	6

	6

	6


"1&'0-+&-*-()$"*304&5

	/3"%0",(*&1

  2





3%5"0&"


!

Figure 1. Study area in Monroe County and surrounding counties in Michigan and Ohio. 

3
	
 

 

	7

	7	












	

 















$ 

















	  

 

  

 









 






	





 









!





"



 #



# 

!

	

	 







	

	


	

0 2 4 MILES 

0 2 4 KILOMETERS 




7	

7
7	
7

 

! %

&3)*20.!)0-0+,'&-425)6

	14&(2&/+-)3

$ 

!!"% #  

!!"% #!

Figure 2. U.S. Geological Survey streamflow-gaging stations and monitoring 

wells in Monroe County, Michigan. 

4
	
link-AMG package for MODFLOW-2000 (Mehl and Hill, 

2001) was developed by the German National Research 

Center for Information Technology (GMD). 

HYDROGEOLOGY 

Understanding the hydrogeology of the bedrock 

aquifer is necessary for simulation of ground-water flow 

and investigation of water-level declines. The bedrock 

aquifer provides most of the ground-water resources in 

Monroe County, and the ground-water-level declines are 

in this aquifer. The bedrock aquifer is composed of several rock units dominated by dolomite and limestone with 

small amounts of sandstone. Glacial deposits overlie the 

bedrock aquifer in most of Monroe County and the study 

area. In Monroe County, the glacial deposits yield only 

small to moderate quantities of water to wells. In the 

at any location can be determined only by site-specific 

5 

geologic or geotechnical investigation. 

Hydraulic properties 

Despite the heterogeneity of the glacial deposits, some 

general statements regarding expected hydraulic properties can be made. The capacity of a hydrogeologic unit to 

transmit water is described by the hydraulic conductivity. 

This hydraulic property may vary over many orders of 

magnitude, and the capacity of the unit to transmit water 

increases as the conductivity increases. The deposits in 

Monroe County are dominated by glaciolacustrine sand 

and clay (fig. 3). Both of these deposits are expected to 

have low hydraulic conductivity, although the glaciolacustrine sands may be able to transmit water better 

than the clays. The glacial deposits that should have the 

highest hydraulic conductivity in the study area are coarse 

moraine deposits in the northwestern and western por- northwestern part of the study area, the glacial deposits tions of the study area. These deposits are predominately may yield more water than other parts of the area and sand and may contain gravel layers. The glacial deposits provide drinking-water sources for most domestic wells. are important to this study because they exchange water In this study, the glacial deposits are considered primar- with the underlying bedrock aquifer. ily with respect to how much water they transmit to or The effective vertical hydraulic conductivity of glacial receive from the bedrock aquifer. The hydrogeologic deposits was estimated using information from digital features of the glacial deposits and bedrock aquifers are water-well logs compiled by the MDEQ in the elec- discussed below. tronic water-well-log database referred to as WelLogic 

(Michigan Department of Environmental Quality, 2003). 

Glacial Deposits Water-well drillers are required to log every well drilled 

in the State, and many drillers use the WelLogic system 

Glacial deposits in the study area include unconsolidat- to enter well-log information. WelLogic defines a set of 

ed silt, clay, and gravel deposited in landforms known as descriptions for the material types (lithologies) encounmoraines; clay-rich glacial till; and glaciolacustrine sand tered during drilling. The lithologies reported on many 

and clay (fig. 3). The glacial deposits locally may act older logs also have been converted to a standard set of 

as aquifers where hydrogeologic properties allow them descriptions by MDEQ and entered into the database. The 

to store and transmit usable quantities of ground water. water-well logs in the database contain information reClay-rich deposits often adequately store water, however, garding the location and date drilled, construction details, 

they typically limit the movement of ground water and static water level, and the lithologic description of the 

are considered confining layers in the study area. In this boring as reported by the driller. There were 8,759 waterstudy, individual glacial aquifers are not identified or well logs in the WelLogic database for Monroe County in 

simulated. May 2003. Note that these are not all of the well records 

Only the upper portion of the glacial deposits are for the county, some areas have not had many new wells 

depicted in figure 3 (Farrand and Bell, 1982). These drilled or have had only a few older well logs converted 

deposits, however, have considerable three-dimensional to the database, and, therefore, have few entries in the 

complexity. Typically, the bedrock surface is covered WelLogic system. 

by clay-rich glacial till (Mozola, 1970), and the till is To estimate the effective vertical hydraulic conduccovered by the deposits shown in figure 3. Thus, where tivity, the thicknesses of sand, gravel, and clay were 

lacustrine sand deposits are shown, these deposits may identified for each water-well log in Monroe, Lenawee, 

be relatively thin compared to the underlying clay-rich Washtenaw, and Wayne Counties where the well reached 

till and separated from the bedrock. Glacial deposits are the bedrock aquifer. Only lithologies are identified on the 

absent in the study area in small areas where rivers have well logs, and material tests were not performed to deterexposed the bedrock near Lake Erie or where the glacial mine the vertical hydraulic conductivity of each lithology. 

deposits have been removed to expose the bedrock for 

quarrying or construction. The detailed glacial geology 
 

 

	6

	6

	6


2/(%$"))%5







!



!








	 
6
6


"0%&/,*%,),'(#")2/3%5

	.2"$/"+')%0

,$%)"/%"







 



))23(")

6

0 10 20 MILES 

0 10 20 KILOMETERS 

,*-)%4

"#201/(+%)"5

"#201/(+%"+$

,/"(+%


!

Figure 3. Generalized glacial deposit map for study area, modified from Ferrand and Bell (1982) and 

Ohio Department of Natural Resources (2000b). 

6
	
---------

Therefore, representative vertical hydraulic conductivities 

(Fetter, 2001) were assumed for the following lithologic 

classes: gravel = 3 x 10-3 ft/s, sand = 3 x 10-6 ft/s, and 

clay = 3 x 10-10 ft/s. The effective vertical hydraulic conductivity, Kv

eff, for the lithologic sequence described in 

each water-well log was calculated as 

eff b K = --------------------- v n

b , m

 Kv m m = 1

where bm is the thickness of lithologic layer m, and n

is the total number of lithologic layers for a given well 

(Fetter, 2001). Because the vertical hydraulic conductivity 

of each layer is assigned in this study, and not measured 

directly, the distribution of effective vertical hydraulic 

conductivities is indicative of relative values and not of 

absolute values in specific locations. The distribution of 

effective vertical hydraulic conductivity (fig. 4) indicates 

that the movement of water through glacial deposits is 

limited over most of Monroe County and that the area 

with greatest potential to transmit water is in the southcentral part of the county. Comparison of figures 3 and 4 

shows that even areas mapped as having glaciolacustrine 

sand at the surface may have a sufficient thickness of 

underlying clay to restrict vertical flow. 

Water-level changes 

Water levels in glacial deposits are important, as they 

affect the amount of water exchanged between the glacial 

deposits and the bedrock aquifer. If the water level in the 

glacial deposits is higher than that in the bedrock aquifer, 

then there is a hydraulic potential for water to flow from 

the glacial deposits to the bedrock. Most wells in the glacial deposits are not screened across the water table, and, 

therefore, because of the potential for vertical gradients 

within the glacial deposits, there are few available direct 

measurements of the level of the water table in the study 

area. The water-table surface, however, is commonly 

assumed to be shaped similar to the land surface (Fetter, 

2001). In areas with tile-drain systems, the water table 

is near the land surface. The water table is at the same 

elevation as streams, lakes, and wetlands, and generally 

at a slightly higher elevation between these surface-water 

features. In the study area, perched water in the glacial 

deposits is common (Nicholas and others, 1996). Perched 

ground water is ground water that is above the water 

table and separated from the water table by an unsaturated zone. Perched ground water typically occurs in sand 

deposits that are underlain by clay, but they also may be 

present in any glacial deposit where the water level in 

the bedrock aquifer is below the glacial deposit/bedrock 

interface. 

One USGS monitoring well, G-10, is completed in glacial deposits (fig. A10). This well is screened just above 

the contact between the glacial deposits and the bedrock 

aquifer at a depth of 107 ft. The depth to water in this well 

was 16 ft in 1991 and 20 ft in 2003. This decline in water 

level is less than the decline observed in nearby bedrock 

monitoring wells. 

To assess water levels in the glacial deposits, information from the WelLogic database was used. The WelLogic 

database includes water levels in wells reported as “static 

water level” by drillers following completion of a new 

well. Driscoll (1986) defines “static water level” as “... 

the level at which water stands in a well or unconfined 

aquifer when no water is being removed from the aquifer 

[through the well in question] either by pumping or free 

flow.” The use of “static” may be misleading, because 

the water level in wells is rarely static. As discussed later 

in this report, the “static water level” changed over time 

in the study area. The term ground-water level is used 

herein to refer to the reported static water level in the 

database. 

Statistical procedures used to evaluate the ground-water levels reported in the WelLogic database are described 

in appendix C. These procedures were applied to groundwater levels in wells screened in glacial deposits in 

Monroe, Washtenaw, and Wayne Counties. Results of the 

statistical analysis did not indicate any systematic declines 

in ground-water levels in wells screened to the glacial 

deposits. However, few well logs for glacial-deposit wells 

are available for Monroe or Wayne Counties. Therefore, 

little data are available to support the conclusion that 

ground-water levels in the glacial deposits underlying 

these counties have not declined. 

Recharge 

Water infiltrating into the ground-water system from 

surficial sources is referred to as recharge. In the study 

area, some recharge to the water table in the glacial 

deposits comes from losing reaches of streams, but most 

comes from precipitation that infiltrates below the root 

zone. Holtschlag (1996) estimated recharge to the water 

table for the Lower Peninsula of Michigan; estimated 

recharge values for the study area range from 4 to 6 in/yr. 

The procedure used to estimate recharge used statistical 

analysis of base-flow measurements from streams. Because the glacial deposits have low hydraulic conductivities in much of the study area, this base flow is assumed 

to primarily reflect the discharge of water from the glacial 

deposits to the streams. Examining the base-flow characteristics of streams in the study area may reveal changes 

in the recharge to the system. 

The USGS program RORA implements the Rorabaugh 

model to estimate ground-water recharge from stream hydrographs (Rutledge, 1998; Rutledge, 2000). The yearly 

7
	
	3

3	3
3	3



	3	

0 2 4 MILES 

0 2 4 KILOMETERS 

"/%&.,*%,),'(#")0.1%2
 

	-0"$."+')%/
 

 


 




 




!






!
! !  
 !

( 3 34+%/0 2(15%-40 	
 

 2(%4( 24+%/ 	%/'-( 3 34+%/0 2(15%-40 	
 

 2(%4( 24+%/ 	%/'-( 3 34+%/0 2(15%-40 
 

 2(%4( 24+%/ 
 

Keff Figure 4. Estimated log( ) for Monroe County, Michigan, based on thickness and lithology v

of units reported in the WelLogic database. Shaded areas are glacial deposits mapped by Ferrand 

and Bell (1982). 

8
	
recharge in the River Raisin Basin and the Otter Creek 

Basin was examined using hydrographs from the USGS 

streamflow-gaging stations at the River Raisin near 

Monroe (U.S. Geological Survey Site 04176500) and 

Otter Creek near LaSalle (U.S. Geological Survey Site 

04176605) (fig. 2). The estimated recharge to River Raisin and Otter Creek between 1990 and 2001 did not show 

a consistent downward trend. Base flow in Otter Creek 

was near its long-term average of 7.4 in/year for 8 years 

during the period. Base flow in River Raisin varied more 

than in Otter Creek. River Raisin base-flow values were 

below the basin long-term average of 7.5 in/year for 6 of 

the years during this period. The base flow was above average for the final 2 years of the period (2000-2001) and 

did not show a consistent downward trend. As another 

indication of streamflow, Nicholas and others (2002) 

showed that the 7-day low-flow values for the River 

Raisin station at Manchester, Michigan did not indicate a 

consistent downward trend. 

Precipitation is the source of most of the recharge 

to the glacial deposits. The deviation from the annual 

average of 31.5 in/year for precipitation values from the 

Midwestern Regional Climate Center for the Monroe 

County Waterworks (station 205558) were used for this 

analysis (fig. 5). The annual differences and the difference 

for the period between October of one year and March of 

the next year are shown. Most recharge to the water table 

occurs during the period from October to March. From 

1990 until 2002, the average precipitation from October 

to March tended to be below the long-term average. Average precipitation was above the long-term average during 

1990-93, 1997, and 2001, and below the long-term average during 1994-96 and 1998-2000. 

Discharge 

Tile-drain systems, together with streams, lakes, and 

wetlands are areas of discharge from the glacial deposits. 

Tile-drain systems are common in current and former 

agricultural areas throughout the study area, because the 

water table is near the land surface. Historically, much 

of the study area had extensive wetlands including the 

Point Mouillee marshes and the Black Swamp (Robbins 

and others, 1994). Locally, domestic wells discharge 

small quantities of water from the glacial deposits. The 

base-flow estimates indicate that ground-water discharge 

to streams has not changed systematically over the past 

decade. None of the indicators of hydrologic changes in 

the glacial deposits — water levels, precipitation, or base 

flow — show systematic downward trends. 

Bedrock Aquifer 

The bedrock aquifer in the study area occurs in Silurian-Devonian carbonate rocks. In ascending order, and 

from oldest to youngest, the aquifer is composed of the 

Salina Group, the Bass Islands Dolomite, the Detroit 

River Group, which was subdivided into the Sylvania 

Sandstone and Detroit River Dolomite by Mozola (1970), 

and the Dundee Formation (fig. 6). The Traverse Group, 

a sequence of shale, sandstone, and dolomite, overlies 

the Dundee Formation and generally is not considered 

an aquifer. The characteristics of these units are given by 

Mozola (1970) and summarized by Nicholas and others 

(1996). Breen and Dumouchelle (1991) summarize the 

bedrock sequence in northwestern Ohio. They note that 

these formations grade from one lithology to the next and 

that contacts are difficult to identify. Intermediate weathering surfaces are not apparent in cores or in exposed 

faces such as quarries (D.B. Westjohn, U.S. Geological 

Survey, oral commun., 2003). Although the hydraulic 

properties of the individual bedrock units may be different, there is no evidence of extensive confining beds 

among the bedrock units composing the bedrock aquifer. 

Therefore, the entire bedrock sequence was considered to 

constitute a single heterogeneous bedrock aquifer. 

The upper contact of the bedrock aquifer in the northwest portion of the study area consists of shale units, 

including the Antrim Shale and the extensive Coldwater 

Shale (fig. 6). These shales are important in that they have 

very low hydraulic conductivities that appear to prevent 

post-glacial recharge water from flowing to the SilurianDevonian carbonates from above (Westjohn and Weaver, 

1998; McIntosh and others, 2002; J.C. McIntosh, University of Michigan, oral commun., 2003). The Coldwater 

Shale was used as the lateral hydraulic boundary for the 

bedrock aquifers in the Michigan Basin RASA (Hoaglund 

and others, 2002). Glacial deposits, discussed previously, 

are the remainder of the upper boundary of the bedrock 

aquifer in this study. The lower boundary of the bedrock 

aquifer is assumed to be the Salina C-shale, which is part 

of the Salina Group (D.B. Westjohn, U.S. Geological Survey, written commun. 2002), and no evidence of upward 

flow from aquifers underlying the Salina Group has been 

presented in the literature. 

The boundary to ground-water flow along the western 

border of the study area is saline water. Fresh ground 

water within the study area is bounded by brackish and 

saline water. The density difference between the fresh 

and saline water is assumed to limit migration of the 

freshwater. The Midwestern Basins and Arches RASA 

used the salinity boundary as the northern lateral boundary (Bugliosi, 1999). Monroe County is in a relatively 

limited area where the total dissolved solids concentration in the bedrock aquifer is low enough that the ground 

water is potable. 

Lake Erie provides a hydraulic boundary to groundwater flow. Under natural conditions, the lake is a discharge area for ground-water-flow from the bedrock 

9
	


	



	



	



**/(0#,%#

!.+ #,.+,!&

-.').#"0(/#*#+,)+,#)+*.&-)'--'*%(+*%.#,)

0#,%#/-#"$+,)+*.&(10(/#


 
 
 

 
 
 
 
 

 
 

 

 

 


 

  







Figure 5. Graph showing yearly difference in annual precipitation from long-term average at the 

Monroe County Waterworks Monroe County, Michigan, 1970-2002. 

 10
	



	0

0	0
0	0 

	0	

," #+)'")&)$% &-+."/ 	*-!+($&",



	


!

$#'




	#!$#"!



	

	

	



Salina Group 

Bass Islands Group 

&#!
""""  Sylvania Sandstone 

#!% Detroit River Group 

Dundee Limestone 

#!#%!#% Traverse Group 

	!$ $!

 !##$!

Figure 6. Bedrock units for Monroe County, Michigan and regional bedrock setting from 

Milstein (1987), Indiana Geological Survey (2002), Ohio Department of Natural Resources (2000a). 

11
	
aquifer. Historically, water levels in the bedrock aquifer 

were above lake level along the Lake Erie shoreline in 

Monroe County. Bedrock water levels along most of the 

shoreline in the county ranged from slightly above lake 

level to tens of feet below lake level during the entire 

study period from 1991 through 2003. Water levels in 

the bedrock aquifer are expected to approach lake level at 

some distance eastward beneath Lake Erie. 

Regionally, the bedrock aquifer is thought to be recharged predominantly in south-central Ohio and Indiana. 

From the recharge area, ground water moves northward 

until it meets saline water in the Michigan Basin and then 

discharges either to surface-water features in Indiana and 

northern Ohio or to Lake Erie (Bugliosi, 1999, fig. 15). 

Larger rivers, including the Maumee and Detroit Rivers, 

form internal boundaries to ground-water flow within the 

regional framework. Ground-water discharge in Lucas 

County, Ohio is towards the Maumee River and Lake Erie 

(Breen and Dumouchelle, 1991; R. Sheets, U.S. Geological Survey, written commun., 2002). There is no evidence 

for ground water in the bedrock aquifer crossing the Maumee River in Lucas County or the Detroit River. Based on 

this regional view, ground water in the bedrock aquifer is 

expected to move from west to east in Monroe County. A 

potentiometric surface for the bedrock aquifer for 1993 

illustrates this movement (fig. 7). 

Hydraulic properties 

Ground-water flow in the bedrock aquifer is predominately through secondary openings consisting of fractures. Most of these fractures are along bedding-plane 

partings (Nicholas and others, 1996). Because of its 

location in the Michigan Basin, the bedding planes dip to 

the northwest in the study area. This dip coincides with a 

strike direction of southwest to northeast. Frequently, the 

fractures have been enlarged by dissolution of the bedrock. Some of the dissolution features are large enough to 

be considered karst (Sherzer, 1900) and may affect local 

flow patterns. This condition is especially true in southwestern Monroe County. Indications of the magnitude 

and distribution of hydraulic properties of the bedrock 

aquifer are given by aquifer tests, storage properties 

resulting from confined or unconfined conditions, and the 

barometric efficiency of monitoring wells. 

Analysis of an aquifer test performed in the Petersburg 

game area using wells GLTO, G-22, G-24, and G-25, 

which are open to the Detroit River Dolomite, gave an 

estimated transmissivity of 1,000 - 1,300 ft2/day and 

storativity of 0.00008 - 0.0001 (Nicholas and others, 

1996). Test results also indicated a heterogeneous reponse 

at the monitoring wells. A more limited test performed 

near the London Aggregates quarry in London Township 

gave similar results (S.J. Wright, University of Michigan, 

written commun., 2003). Nicholas and others (1996) cite 

a test performed in Bedford Township that resulted in a 

slightly higher transmissivity than the Petersburg Game 

Area test (3,800 ft2/day). These values were used as 

initial estimates in the calibration of the numerical model 

described in this report. 

Slug-test results reported by Nicholas and others 

(1996) demonstrate the potential range and variability in 

hydraulic properties resulting from the fractured nature of 

the bedrock aquifer. The estimated transmissivity values 

determined from the slug-test analysis are questionable 

because the water level in the wells responded quickly 

to the applied slug and oscillations were recorded for 

many wells hampering the analysis. Importantly for this 

study, however, spatial patterns in transmissivity are not 

indicated in the reported results. For example, consider 

the reported transmissivities determined for monitoring 

wells G-29 and G-30 (fig. 2). These wells are 2 mi apart. 

Each well is completed in the Bass Islands Dolomite, and 

the top of both boreholes is approximately at the same 

elevation. Well G-30 has 119 ft of open borehole and well 

G-29 has 33 ft of open borehole. The reported transmissivities are 10 ft2/day for G-30 and 3,400 ft2/day for 

G-29. The longer borehole, G-30, evidently did not intersect as conductive of a fracture system as did the shorter 

borehole, G-29. 

Unconfined and confined aquifers respond differently 

to pumping or other imposed stresses. For confined 

aquifers, the response time to changes in an imposed 

stress is governed by the compressibility of water and the 

compressibility of the aquifer material (aquifer storativity). For unconfined aquifers, ground water drains from 

the pore space or fracture (specific yield). The storativity of a confined aquifer typically is orders of magnitude 

smaller than the specific yield of an unconfined aquifer, 

and aquifers under confined conditions respond much 

faster than unconfined aquifers to the same disturbance 

(Theis, 1940). As discussed previously, the bedrock 

aquifer in the study area is overlain by confining units 

composed of either shale or glacial deposits. Water levels 

in the bedrock aquifer may be below the contact between 

the glacial deposit and bedrock aquifer. In this situation, 

the aquifer is under unconfined conditions. A sequence of 

maps of Monroe County illustrating the development of 

unconfined areas in the bedrock aquifer is shown in figure 

8. These areas were determined by comparing the groundwater levels reported in the WelLogic database to the 

elevation of the top of the bedrock in the same borehole. 

There is scatter in the points because of local heterogeneity and errors inherent in the database, but the unconfined 

areas have expanded over time as the water level in the 

bedrock aquifer has declined. 

The water-level record for the Petersburg deep 

 12
	
>


11

13 12

22

LTO

28 30

17



	

















630

640

650

660

	>
	>		>
	>

	



14 15

2

23

29

31

32

33

18

'7+,631#!+303-/)'0!96:+=


59'*6'2-0+7



27

24

""" "# !.3;7'08/89*+

	







>

%"


!


" !

3 5

7 4

1 8

9 6

16

21 19

25

26 20

	




3263+

3,;'8+60+:+0'29'6=

	'7.+*;.+6+

'4463</1'8+0=03)'8+*328396/28+6:'0,++8

'891/77+'0+:+0

3928=

 #$" $663;/2*/)'8+7
 

*/6+)8/323,-6392*;'8+6,03;/,8.+'59,/+6
 

;'7/738634/)'2*.313-+2+397;/8.6+74+)8
 

8386'271/77/:/8=
 

$" 6+,/<8.+0+88+6
 28 83291(+6
 

# &)8/:+/2



Figure 7. Potentiometric surface for bedrock aquifer, 1993, for Monroe County, Michigan, 

(from Nicholas and others 1996). 

13
	


 

 






	

	


'&$"
$!$ !(&)*

%(&#!' 





	 
	

	
 

	
 



Figure 8. Time sequence of wells open to the bedrock aquifer showing confined (water level at least 

one foot above top of bedrock) or unconfined (water level at least one foot below top of bedrock) 

conditions, Monroe County, Michigan, 1960 to 2002 (data fromWelLogic database). 

 14
	
monitoring well (fig. 9), designated as GLTO (fig. 2), 

suggests that the aquifer in the area around this well has 

transitioned from confined to unconfined conditions. In 

the early part of the record, seasonal changes in the water 

level were on the order of 5 ft. The water level in the well 

declined about 12 ft from 1993 to 2001. Seasonal waterlevel changes since 1999 are less than 1 ft. Before 1999, 

aquifer yield resulted from the compressibility of the 

aquifer material and the compressibility of water (storativity). After 1999, aquifer yield results from dewatering fractures in the system (specific yield). 

Barometric effects on water levels in wells in Monroe 

County were noticed by early settlers, and the response 

of water levels in monitoring wells to barometric changes 

may give insight concerning the hydraulic properties of 

the bedrock. Sherzer (1900) reported increased water 

levels and artesian flow described by residents. There 

were reports of faster flow or sediment in the water 

before storms, associated with a decrease in barometric 

pressure and a rise in water level. Precipitates in the wells 

may have been loosened by higher water velocities and 

introduced into the water in residents’ wells. One well in 

Berlin Township that had been plugged by sand suddenly 

unclogged just before a storm. The well released water 

and sand “with such noise as to be heard some little distance” (Sherzer, 1900). 

The values of barometric efficiency for 12 wells in 

Monroe County were calculated using Clark’s method 

(Davis and Rasmussen, 1993) and seasonal variation and 

lithologic effects were evaluated. High and low values 

of barometric efficiency occurred in both areas mapped 

as having lacustrine sand and areas with lacustrine clay 

(fig. 3). Aquifers under unconfined conditions should 

have low or no barometric efficiency because air in the 

pore space should rapidly equilibrate with changes in 

atmospheric pressure. Barometric efficiencies, however, 

do not appear to correspond to confined and unconfined 

areas within the study area. This lack of correspondence 

indicates that the glacial deposits may have a low enough 

air diffusivity to allow wells open to both confined and 

unconfined areas of the bedrock aquifer to respond to 

barometric changes. Also, the bedrock surface topography 

may be locally variable, resulting in isolated unconfined 

areas that respond differently to barometric changes than 

does an extensive unconfined aquifer. The barometric 

efficiency correlated better with bedrock unit. Higher 

efficiency values were calculated for wells in the Detroit 

River Group and the Sylvania Sandstone, whereas lower 

values were calculated for monitoring wells in the Bass 

Islands Dolomite and Salina Group. 

Water-level changes 

Nicholas and others (2002) summarize the ground-water levels recorded from 1991 to fall 2001. The records 

for the monitoring wells through September 2003 are 

given in appendix A. Ground-water levels dropped in 

many of the monitored wells from 1991 to 2001. Water 

levels in 11 monitoring wells declined more than 10 ft, 

and the water level in 6 wells declined more than 20 ft. 

Measurements for the current study showed additional 

declines in water levels in most of the wells. Two wells, 

G-1 and G-2 (fig. 2), recently were dry indicating water 

levels below the bottom of the well. Well G-3, which is 

nearby and measured at 15-minute increments, exhibited 

a periodic pumping signature. Some of the wells (G-11, 

G-19, G-20, G-27 and G-28) had seasonal fluctuations 

on the order of 10 ft, with G-28 the most extreme. Some 

wells (G-4, G-5, G-6, G-7, G-8, G-10, G-17 and G-22 

through G-26) showed little seasonal variation during the 

recent study period, which may be due to locally unconfined conditions in the bedrock aquifer. Ten wells (G-5, 

G-7, G-8, G-9, G-11, G-13, G-14, G-17, G-18, G-19) had 

water-level recoveries during 2002 and 2003. Some of 

these recoveries can be matched to seasonal variations. 

The general downward trend of water levels since 1991 

can be seen in all the wells except for G-10 and G-18. 

The monitoring well G-10 is the only monitoring well 

screened to the glacial deposits. All of the other wells are 

open to the bedrock aquifer. 

Ground-water levels in bedrock monitoring wells from 

four landfills were obtained from MDEQ and also are 

given in appendix A. Near the Monroe County line to the 

north, ground-water levels at Carleton Farms decreased 

approximately 15 ft between early 1995 and late 2001, 

and levels at Matlin Road Landfill decreased about 5 ft 

between 1996 and 2002. This decline in ground-water 

level is consistent with USGS well G-4, which declined 

about 10 ft over the same time period. The ground-water 

level at Jefferson Smurfit, near the city of Monroe, did not 

change from early 1999 to early 2002. This water-level 

record is consistent with the record from G-16, which is 

located northeast of the landfill nearly parallel with the 

Lake Erie shoreline. Rockwood Landfill is located within 

a mile of the Thompson and Rockwood Quarries, and 

ground-water levels are clearly affected by dewatering 

at these quarries (fig. A37). Landfill records from 1980 

precede quarry operations and water levels were similar 

across the landfill. More recent measurements show a 

decrease in water levels on the south side of the landfill, 

from 60 to 80 ft below the levels on the north side. 

The statistical significance of trends in water levels 

from 1991 through 2001 for the USGS monitoring well 

data was determined by using the methods described by 

15
	
	

	

	

	

	

	






 , *+-*" ) , *+-*"& 
* -&& *!$ %(.'+#$)

(,


   	    
  

Figure 9. Hydrograph for U.S. Geological Survey observation well GLTO which is open to the 

bedrock aquifer, Monroe County, Michigan, 1978-2003. The change in amplitude of yearly 

response indicates a change from locally confined to locally unconfined conditions. 

 16
	
Kendall (1955) and by the Sen slope (Gilbert, 1987). Kendall’s test was developed to determine if two series were 

correlated or not based on the ranking of the series. The 

test is summarized by the value referred to as the Kendall 

τ. The Kendall τ ranges from 1 for a strictly increasing series to -1 for a strictly decreasing series. A τ value 

of zero indicates no trend in the data. The test does not 

depend on the absolute value of the observations, and it 

is not affected by missing observations or changes in the 

frequency of observation of the time series. The analysis 

was performed using the statistical program S-Plus 2000 

(MathSoft, 2000) and the S-Plus USGS library function 

“kensen” on both water-level time series and streamflow 

hydrographs. Details of the analysis are presented in appendix B, and a summary of the analysis follows. 

The largest magnitude for the Sen slope for a waterlevel record was -8.7 ft/year at well G-17. Note that this 

well is less than 500 ft from a quarry that was deepened 

and increased ground-water withdrawals during the study 

period. At this distance, the water level is directly under 

the influence of the quarry depth, and this large decline 

is not indicative of declines throughout the county. Most 

wells had declines that can be grouped into three clusters. 

Wells in the northeastern part of the county (G-1 through 

4), wells (G-12 through 15, G-19, G-20, G-29, G-31), 

and wells near Petersburg (G-21 through 28) had slopes 

between -1 and -2 ft/year. Wells in the northern part of the 

county (G-5 through 9, G-11) had slopes between 

-2 and -4.5 ft/year. The remaining wells (G-10, G-16, 

G-18 through 20, G-30, G-32, G33) showed little decline. 

Well G-10 does not follow the pattern in the northeastern 

portion of the county, but this is the only monitoring well 

completed in the glacial deposits overlying the bedrock 

aquifer. Well G-13 shows the only positive trend over 

the time period. The p-value for this well (0.16), however, indicates little statistical likelihood of a trend at this 

well. The only other well with a high p-value (0.13) is 

G-18. The remainder of the wells have p-values that are 

extremely small, and the statistical likelihood of no trend 

in these wells is less than 1 percent. 

The water-well logs in the WelLogic database also 

were examined to determine if water-level trends in the 

bedrock aquifer are present. Despite the uneven coverage 

across the county, examination of the reported ground-water levels from the digitized logs may indicate trends and 

patterns of ground-water levels in the area. The groundwater levels from the water-well logs are subject to errors, 

including errors in determination of land-surface elevation 

at the well from topographic maps, water-level measurement error, and incomplete recovery of the water level in 

the well after disturbance during well drilling and development. These errors are assumed to be scattered around 

the true water level randomly, and, therefore, they are not 

assumed to impose a systematic bias to the analysis. An 

estimate of the mean ground-water level can be determined if a large number of well logs is included in the 

analysis. The water-well logs in the WelLogic data base 

were examined, and 7,229 logs for the bedrock aquifer 

had the date of drilling and other information to determine 

the ground-water level. 

The analysis of WelLogic records described in appendix C was performed for the bedrock wells in Monroe 

County. This analysis grouped wells by township and date 

to discern changes in the ground-water level. The boxand-whisker diagrams were developed by grouping wells 

into 2-year groups by the drilling date. The mean, median, 

lower and upper quartiles, and outliers were determined 

for each group that had more than 10 wells. Mean values 

for all groups are connected by a dotted line on the plots. 

Groups with less than 10 wells drilled during a 2-year 

period are plotted using open circles for individual wells 

and solid circles at the means. Examination of the figures 

in appendix C reveals appreciable scatter for the depth-towater for each 2-year group in each township. The boxes 

enclose data values between the lower quartile and upper 

quartile. These boxes tend to enclose a range up to 30 ft. 

The whiskers show the spread of the data by extending to 

either the maximum data value or the upper quartile 

+ 1.5*(upper quartile-lower quartile) and to the minimum 

data value or the lower quartile - 1.5*(upper quartile 

and lower quartile). In the latter cases, the whiskers help 

highlight outliers in the data set. For most townships, the 

variation in the mean is less than the scatter of the groups. 

Despite this scatter, general trends are evident in the plots. 

Little change in the mean ground-water level is indicated 

for six townships. Townships where the depth to water 

increased (mean ground-water level declined) include 

Ash, Berlin, Dundee, Exeter, Frenchtown, London, Milan, 

Monroe, and Summerfield. For example, the mean 

ground-water levels decline in Exeter Township was 

approximately 25 ft (fig. 10). Estimated mean groundwater-level declines using the WelLogic database and the 

declines observed in the USGS monitoring wells generally agree (fig. 11). The townships that show the largest 

declines are consistent with the USGS monitoring wells. 

In the southern townships, the USGS wells have shown 

either no decline or smaller declines and the WelLogic 

interpretation agrees. 

The spatial distribution of ground-water levels reported 

in the WelLogic database was examined further. Fouryear groups of wells were plotted (figs. 12-13). A smooth 

surface was fit to the reported ground-water levels using 

the S-Plus 2000 loess function (Mathsoft, 2000). The 

loess surface fits a local trend surface to the data by using 

a weighted least-squares technique with greater weight 

given to data near the interpolation point (Venables and 

17
	
 

DEPTH TO WATER, IN FEET BELOW LAND SURFACE 

0

 20

 40

 60

 80
­

100
­

Lower Quartile

 Median 

Upper Quartile 

Outlier 

Minimum value or [Lower Quartile1.5* (Upper Quartile-Lower Quartile)] 

Mean, dotted line connects the mean values 

Maximum value or [Upper Quartile + 

1.5* (Upper Quartile-Lower Quartile)] 

Individual well for groups with less than 10 wells during 2-year period 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 

Figure 10. Trend in reported depth to ground water for Exeter Township, 

Monroe County, Michigan, data from the WelLogic database. Note 

the general decline in water level from 1990 to 2002. 

 18
	

;









	








	;


	;	
	;

	;


;



 



 %!


! 


 



'5+ ,420" +2/2-.)'/ 748+:


37'*4'1-/+5



$! 

 # !$

 "

  





"

%!

 !!"$!#

!$+/2-.)'1'/:5.5



157,,.).+16'6' "!&

 #"$!#!

	" +2/2-.)'/ 748+:2(5+48'6.219+//5

Figure 11. Estimated and observed ground-water-level declines, Monroe County, 

Michigan, 1991-2001. 

19
	

9














	




















	9
	9		9
	9

MONROE





 


9



 


! 

'4* +31/" *1.1,-('. 637*8


26')3'0,.*4

%!



!$$

"!!"!!!

 " !!$!

 "! 105163-05*37'.-4+**5

'56/-4#
 

"!&

Figure 12. Potentiometric surface for bedrock aquifer, 1988-1991, developed from WelLogic 

ground-water-level records and loess function, Monroe County, Michigan. 

20
	

:


:

	

:
:







































 
	
 	


				
	







#


$"#

MONROE

MONROE


	


	

	:

	:

(5+ ,420%#+2/2-.)(/ #748+9

	
37(*4(1-/+5

& $

#$$"

 $$$" #%""

!%"216274.16+48(/.5	,++6 

"%$'

Figure 13. Estimated difference in potentiometric surface in bedrock aquifer in Monroe County, 

Michigan based on WelLogic ground-water levels and loess function. ((a) (1988-1991) - (1964-1967) 

surfaces and (b) (2000-2003) - (1964-1967) surfaces.) 

21
	
Ripley, 1994). The distribution of water levels was fit using the well location. With these two independent variables, the loess surface essentially is a weighted-quadratic 

fit to the data. The fitted surface and observation points 

for the 1987-90 grouping is shown in figure 12. Note the 

general agreement between the loess surface and the interpreted potentiometric surface from Nicholas and others 

(1996) shown in figure 7. 

The difference in the fitted surfaces between the 

1988-91 grouping and the 1964-67 grouping is shown in 

figure 13(a). Little change in the mean ground-water level 

is shown. Zero changes are contoured over large parts of 

the county. Thus, the estimated change between these 

two time groupings is less than 10 ft. In contrast, large 

changes in ground-water levels are calculated using the 

2000-03 grouping and the 1964-67 grouping (fig. 13(b)). 

In the northern portion of the county, 20-ft declines in 

water levels are contoured. The observed declines in the 

USGS monitoring wells also are plotted (fig. 13(b)). The 

contours indicate that the pattern of water-level changes 

produced with the WelLogic records are consistent with 

observed declines in water levels in the USGS monitoring 

wells. Exceptions to these results include G-17, which is 

close to an active quarry and not indicative of the regional 

decline, and G-1 which is now dry and, thus, not yielding 

a representative value for the local decline. The surface 

seems to overestimate the decline in the extreme northeast 

portion of the county and may overestimate the decline 

near G-16 where there are not many wells in the WelLogic database to control how the surface is contoured. 

The ground-water-level patterns described above appear to relate to the expected pattern of vertical hydraulic 

conductivity of the glacial deposits. Superimposing the 

effective vertical hydraulic conductivity map and the 

apparent change in ground-water level shows that the 

area identified with the highest potential to allow vertical flow is in the region where ground-water levels have 

not declined substantially since 1991 (fig. 14). Regions 

with large change in ground-water level tend to have low 

potential for vertical flow based on the WelLogic lithologies. Note that the relation between the effective vertical 

hydraulic conductivity and the area of ground-water-level 

decline may be coincidental. The pattern of pumping in the region also is important, and the region with 

lower declines may simply correspond to a region where 

ground-water use has not increased as much as it has in 

the northern townships of the county. 

USGS monitoring wells and the mean surface computed from the WelLogic records are consistent. Analysis 

of the time-series data from each set of wells indicates 

water-level declines up to 20 ft in the northern portion of 

Monroe County. Analysis of the WelLogic trends indicate 

fairly constant ground-water levels until the mid 1990s, 

when declines are evident in townships in northern Monroe County. The ground-water levels for monitoring wells 

in the bedrock aquifer reported from four landfills in the 

northeastern portion of the county also are consistent with 

levels observed in the USGS monitoring wells. 

Leakage 

Not all of the water that recharges the water table 

moves through the glacial deposits to the bedrock aquifer. 

The amount of water that reaches the bedrock aquifer 

depends on both the vertical hydraulic conductivity of 

the glacial deposits and the difference between the water 

level in the glacial deposits and the water level in the 

bedrock aquifer. Ground water only will flow from the 

glacial deposits to the bedrock aquifer if the water level 

in the glacial deposit is higher than that in the bedrock 

aquifer. For the bedrock, the term leakage is used to describe the supply of water flowing to the bedrock aquifer 

instead of recharge, because water from the surface must 

move through the overlying glacial deposits. Leakage also 

can be out of the bedrock aquifer to the overlying glacial 

deposits. Leakage to the bedrock aquifer has not been 

measured directly in the study area, but inferences regarding leakage can be deduced from water-level patterns and 

water quality. 

Leakage to the bedrock aquifer is highest in areas 

where the water level in the glacial deposits is higher than 

that in the bedrock aquifer and in areas where the glacial 

deposits have higher vertical hydraulic conductivity than 

other areas. The moraine west of Monroe County appears 

to be a potential recharge area, however, much of the 

moraine lies on top of confining units composed of the 

Coldwater and Antrim Shales. Therefore, leakage to the 

bedrock aquifer in the study area is assumed to be through 

glacial deposits east of the Antrim Shale subcrop (fig. 6). 

Ground-water chemistry can be used to identify leakage areas. Evaluation of the water-quality data summarized by Nicholas and others (1996) indicates that 

gypsum controls the major ion chemistry of the bedrock 

ground water in Monroe County. Geochemically, anhydrite (CaSO4) acts like gypsum (CaSO4*H20), and these 

minerals only are absent in the formations below the 

Dundee Formation, indicating that gypsum saturation of 

the ground water occurs within these bedrock units. Spatial analysis of the data indicates higher saturation with 

respect to gypsum in water samples from wells under or 

near the lacustrine clay, and lower saturation with respect 

to gypsum in water samples from wells under or near the 

lacustrine sand areas (fig. 4). The pattern of lower saturation indicates that the sand units allow more leakage into 

the bedrock. 

 22
	

:




























	:

	 
	:	
	:

	:

MONROE


	


:




!


" !

'5*+420#!*2/2,.('/!748*9


37')4'1,/*5

%"

	 !"" """ 
 

!#  # 216274.16*48'/.5+**6
 

 !""$ "& ##"$"&
 

" &
 

*556-'124*37'/62	

 #"& 4*'6*46-'1	'1)/*556-'124*37'/62	

4*'6*46-'1	'1)/*556-'124*37'/62

4*'6*46-'1

Figure 14. Estimated effective vertical hydraulic conductivity and estimated change in 

potentiometric surface from WelLogic data base and loess function (2000-2003) -

(1967-1964) Monroe County, Michigan. Area of small change corresponds to area where 

the effective vertical hydraulic conductivity is greatest. 

23
	
Another indicator of recharge is tritium content. Tritium concentrations above background in ground water 

indicates post-1953 recharge (Fetter, 2001). There is no 

clear relation between the geologic bedrock unit or the 

overlying glacial geology and the tritium values reported 

by Nicholas and others (1996). Water from 13 of 26 bedrock wells sampled for tritium indicated pre-bomb levels. 

The remaining 13 wells had elevated levels indicating 

some post-1953 recharge. 

The water-chemistry results indicate only a small 

amount of leakage to the bedrock aquifer through the 

overlying glacial deposits. If extensive leakage were occurring, the ground water in the bedrock aquifer would 

be expected to have elevated tritium concentrations. The 

water also would be expected to be less saturated with 

respect to gypsum. 

Discharge 

Discharge from the bedrock aquifer is either natural 

or induced by human activities. Natural discharge occurs to Lake Erie, at springs, and in major streams. In 

areas where the potentiometric surface in the bedrock is 

higher than the water table in the glacial deposits, ground 

water will flow from the bedrock to the glacial deposits. 

Discharge caused by human activities is discussed in the 

“Water Use” section later in this report. 

Historically, flowing wells were present in much of 

eastern Monroe County. In these areas, ground water 

would have flowed naturally from the bedrock to the glacial deposits. Earlier reports describing these wells were 

summarized by Allen (1977). Sherzer (1900) includes a 

photograph from 1899 of a flowing well near Otter Creek, 

2.5 mi from LaSalle. The owner placed an 8-in pipe on the 

well, and it was reported to yield “... a very rapid stream 

two feet broad and four inches deep flowing from the 

well to Otter Creek” (Sherzer, 1900). The water level in 

flowing wells were reported to be from slightly above land 

surface to 20 ft above land surface near Lake Erie. Sherzer 

(1900) also reported that wells would interfere with each 

other and that, “wells which formerly flowed in the southern part of Erie township, back three miles from the lake, 

have now ceased although the water rises near the surface.” He also noted that a deep well in the city of Monroe 

caused so much interference with other wells that it had to 

be plugged. The change from confined to unconfined conditions over portions of the county and the current absence 

of flowing wells indicates that natural discharge to the glacial deposits from the bedrock aquifer has decreased since 

1900, and the decrease continues through 2001 as more of 

the bedrock aquifer becomes unconfined. 

Lake Erie levels were examined to determine if there 

was a relation between the declining ground-water levels 

in the bedrock aquifer and the observed lake level. Lake 

Erie levels fluctuated from 1991 through 2002. A hydrograph of Lake Erie levels from the CO-OPS National 

Water Level Observation Network (NWLON) database at 

the Fermi Power Station (Station number 9063090) (National Oceanic and Atmospheric Administration, 2003) is 

shown in figure 15. The long-term mean Lake Erie levels 

for February and June also are shown (U.S. Army Corps 

of Engineers, 2003). Lake level was from 1 to 2 ft above 

the long-term average in 1997-98, and from 1 to 2 ft below the long-term average in 2001-02. The most important 

feature of this dataset for this study is that although the 

level of Lake Erie varied over the course of the study, the 

levels did not show a consistent downward trend. This 

lack of consistent trend indicates that the discharge to 

Lake Erie did not consistently increase for the time period 

leading to regional ground-water declines. 

Great Sulphur Spring, in Erie Marsh near the Lake 

Erie shoreline in the southern part of Monroe County, is a 

discharge point for ground-water flow from the underlying 

bedrock aquifer. The spring was sampled in September 

2003. The specific conductance was 2,590 microsiemens 

per centimeter at 25 degrees Celsius (μS/cm), and the 

flow rate from the spring during this period was approximately 5.2 ft3/s. Any historical variation in its discharge 

would have been controlled by the water-level difference 

between the aquifer and the surrounding surface water that 

coincides with Lake Erie levels. Ground-water levels at 

G-33, which is nearby (see fig. 2), have been steady and 

Lake Erie levels have not dropped consistently. Therefore, 

ground-water discharge at Great Sulfur Spring should not 

have changed appreciably during the study period. Smaller springs may be present in the area, and their discharge 

would be controlled by this water-level difference. 

WATER USE 

Various data sources were used to estimate water use 

in the region. Agricultural irrigation and domestic selfsupplied estimates were obtained through the USGS 

Water-Use Program that is performed in cooperation with 

MDEQ (U.S. Geological Survey, 2003; C.L. Luukkonen, 

U.S. Geological Survey, written commun., 2003), the U.S. 

Department of Agriculture (1999), and the U.S. Department of Commerce (1987). Industrial-use data were obtained through MDEQ following the MichiganWater Use 

Reporting Program that is mandated under the authority of 

Part 327, Great Lakes Preservation, Natural Resources and 

Environmental Protection Act, 1994 PA 451, as amended. 

Water users who have the capacity to withdraw over an 

average of 100,000 gallons (378,500 liters) per day over 

any 30-day period are required to register with the MDEQ 

and to report their water-use information on an annual 

basis. Quarry discharge was estimated from NPDES permits and associated reported discharges through MDEQ 

 24
	
	



	

	

	

	

	

		

	





	

	
 "!), ).%('#+")& -") #"

	


 $%.&" '%"-"%*

,'"%('#+")& -") #"

	




 
 
 

 
 

 

 

 


 

  

Figure 15. Hydrograph of Lake Erie from the CO-OPS National Water Level Observation 

Network (NWLON) database at Fermi Power Station (station number 9063090), Monroe County, 

Michigan. Lake Erie level was both above and below long-term average between 1991-2001 

when ground-water levels were observed to decline. 

 25
	
and checked by field measurements. Comparing groundwater-use estimates from 1991 to 2000 shows an overall 

increase. The ground-water withdrawal for all recorded 

users for Monroe County in 1991 was approximately 

20 Mgal/d, and was nearly 30 Mgal/d in 2001. The percentage of the total for public supply, self supplied, industrial, 

irrigation, and quarry dewatering remained about the same 

for each user. 

Public, Self-Supplied, and Industrial 

Water Use 

Individual domestic wells are important in Monroe 

County. The self-supplied water use estimates were made 

using census figures to estimate the number of people in 

the county who are not on public-water supply (table 1). 

The estimated number of self-supplied users was multiplied 

by 86 gallons per day, which is the average daily use per 

person (U.S. Geological Survey, 2003). 

Most public supplies for communities in Monroe 

County rely on surface water. Historically, Carleton used 

approximately 0.1 Mgal/d of ground water. Petersburg and 

Flat Rock Village currently use approximately this amount 

(table 2). Use information for self-supplied industries and 

quarries in the study area from Ohio is summarized in table 

3 (J. Remic, Ohio Department of Natural Resources, written communication, 2002). 

Agricultural Irrigation 

Agricultural irrigation is an important water use in 

the study area. Estimated irrigated farmland for Monroe 

County, Michigan, in 1982 was 1,952 acres; in 1987 it was 

2,181 acres; in 1992 it was 2,385 acres; and in 1997 it was 

5,047 acres (U.S. Department of Commerce, 1987; U.S. 

Department of Agriculture, 1999). Much of the irrigation, 

however, is attributed to surface-water sources (Nicholas 

and others, 1996; 2002). Ground-water irrigation estimates 

are given in table 4 (R. Van Til, Michigan Department 

of Environmental Quality, written commun., 2003). The 

values are given as an average daily withdrawal for each 

year. Because the irrigation season is much shorter than a 

calendar year, the actual pumping rates are higher than the 

values given in table 4 during the irrigation season and zero 

during the rest of the year. 

Land-use maps were used to estimate the distribution of 

this irrigation across Monroe County. The distribution of 

row crops is widespread. Not all of the row crops farmed 

in the county are irrigated, but this distribution was used to 

simulate the general irrigation demand. The irrigation use 

from the bedrock aquifer estimated by MDEQ for Monroe 

County was divided by the acreage farmed to estimate an 

average demand that was applied to the entire agricultural 

area. 

Golf-Course Irrigation 

Golf-course irrigation is a visible water use in the study 

area. Some golf courses have registered with MDEQ as 

having the capacity to withdraw 100,000 gal/d for a 30-day 

period. Other courses in the area provided ground-water 

use estimates to USGS. The remaining courses are assumed to use limited amounts of ground water. To estimate an upper bound on golf course ground-water use, 

the remaining 12 courses were estimated to use between 

the median value of the other courses (0.012 Mgal/d) and 

the average value for the other courses (0.03 Mgal/d). 

With these values, the range for the maximum golf course 

ground-water use is 0.62 - 0.84 Mgal/d, and the annualized 

average reported ground-water use for golf courses is 

0.48 Mgal/d. 

Quarry Dewatering 

Quarries have operated in the study area for decades. 

Aggregate (dolomite and limestone) quarries typically 

dewater the rock to provide access for the quarrying equipment and workers. The water pumped from the bedrock 

aquifer is either used in other processes at or near the 

quarry site, or it is discharged to surface water. 

From 1985 to 2000, the estimated quarry dewatering 

has represented approximately 75 percent of the groundwater use in the study area. The amount of water pumped 

from the bedrock aquifer by quarries is estimated from 

reported discharges regulated by facility NPDES permits. 

Historically, some quarry operators accurately measured 

discharge, whereas others reported a discharge value that 

appears to be related to the permitted limit or pump capacity. Examination of the most recent records indicates that 

most quarries now measure discharge. The annualized 

average total reported discharge for quarries in Monroe 

County and nearby quarries in Wayne County in 1991 was 

approximately 17 Mgal/d. The reported discharge increased 

to approximately 23 Mgal/d in 2001 and ranged between 

20 and 27 Mgal/d during 2001-02. In December 2002, one 

of the largest quarries stopped discharging and the total 

decreased by approximately 8 Mgal/d. 

The largest ground-water discharge in 2001 in Monroe 

County, Michigan was reported for London Aggregates 

in London Township. To provide a confirmation of the 

reported values, a streamflow-gaging station was established on the North Branch (N.B.) of the Amos Palmer 

Drain downstream from the quarry (fig. 2). This drain 

received discharge from the quarry. Like many drains in 

the area, this drain dries out or has very little flow during 

the summer, except after large storms, without the quarry 

discharge. During 2002, the reported values from London 

Aggregates and discharges estimated from stage-discharge 

relations developed for the N.B. Amos Palmer Drain 

 26
	
	
*0+79440.*)+6*7-,6392);&8*697*.23263*3928<.(-.,&2

$,&0)1.00.32,&003274*6)&<%

#*&6	 3490&8.323278.1&8*)78.1&8*)*6(&4.8&6&2,*78.1&8*

7*0+79440.*)4*6(&4.8&97*:&09*,&003274*6)&<97*6&2,*

,6392);&8*697*,&00327,&0)&<,&0)

8-397&2)74*6)&<

	
  
 
 	
 


	  
 
 	
 


	
 
 
  	
 


  
  	
 

	
31192.8<49'0.(;&8*679440.*7.2789)<&6*&&29&6<


$,&0)1.00.32,&003274*6)&<238&:&.0&'0*%

&(.0.8<3490&8.32*6(&4.8&97*6&2,*".8-)6&;&06&2,*

7*6:*),&003274*6)&<,&0)

*22*883'.0*31*&6/   	
 


0&83(/!.00&,*   	
 
	

*8*67'96, 	
	 	
 	

832*<6&.074&681*287  	 	
 	

"-.8*-397*92.(.4&0"&8*6<78*1    

	
*4368*)7*0+79440.*).2)9786.&0&2)59&66< 	
78.1&8*)&,6.(90896&0.66.,&8.32

,6392);&8*697*.28-*-.34368.323+8-*789)<&6*& ,6392);&8*697*.23263*3928<.(-.,&2

$,&0)1.00.32,&003274*6)&<% $,&0)1.00.32,&003274*6)&<%

#*&6 78.1&8*),6392);&8*6 &(.0.8< 7*,&0) 97*,&0)

	 


	
 

.030*)3*+.2*6< 

&91**0&28 

	  *&;&<&2)&2)6&:*0 

	  <0:&2.& 



 


	 

27
	
Station using methods described by Rantz and others 

(1982) were consistent (figs. 16 and 17). The reported 

quarry discharge generally is the stream discharge during 

storm events and generally higher than the stream discharge between storm events. Given the potential water 

loss because of evaporation and seepage, and the potential 

for additional water at the N.B. Amos Palmer Drain station from the surrounding fields, the reported discharge 

values appropriately represent the rate of water pumped 

by the quarry. 

In July 2003, discharge measurements were made on 

streams receiving discharge from the Sylvania, Stone-Co 

Ottawa Lake, Stone-Co Maybee, and Hanson Quarries. 

Three of the four discharge measurements were consistent 

with reported discharge values (fig. 18), but the discharge 

measurement for the Sylvania quarry was lower than the 

typical reported discharge. Examination of the recent 

discharge records indicates that the reported values for 

2002-2003 are reasonably accurate. 

SIMULATION OF GROUND- WATER FLOW 

The bedrock aquifer is modeled as a layered heterogeneous system. The complex heterogeneity implied 

by the slug-test results, however, is not considered in 

this regional model. Barometric efficiency analysis and 

preliminary modeling results indicate that the individual 

units of the bedrock aquifer should be modeled as separate 

units to allow for a variation in aquifer properties between 

units. The nature of flow in the fractured rock system 

suggests that anisotropy may be important in defining the 

flow regime. 

As discussed previously, the ground water in the bedrock aquifer is under confined conditions for parts of the 

study area. In other areas, however, ground-water levels 

are below the glacial deposit/bedrock interface, and the 

bedrock aquifer is under unconfined conditions. The difference in aquifer response on a regional basis to changes 

in confinement of the aquifer is considered in the model. 

The area of the model is approximately 3,000 mi2 

(fig. 19). Ground water does not flow into or out of the 

bedrock aquifer across the western salinity boundary, the 

Detroit River, and the Maumee River. The interaction 

between these rivers and the bedrock aquifer, however, is 

considered in the model. There is not a natural hydraulic 

boundary for the southwestern portion of the model area. 

This boundary was established to be far enough away 

from the main area of interest, Monroe County, to minimize the effect of the boundary on simulation results. The 

value assigned to the southwestern boundary was adjusted 

during model calibration to be consistent with the regional 

flow in the ground-water system described by Bugliosi 

(1999). A boundary in Lake Erie was established at a 

distance from Monroe County to lessen its direct impact 

on the simulation results, and the value of this boundary was set to the average lake level for each time period 

simulated. No flow is allowed through the bottom of the 

bedrock aquifer through the Salina C-Shale. Where the 

bedrock aquifer is confined by the Coldwater and Antrim 

Shales, no flow is allowed. Leakage between the bedrock 

aquifer and the glacial deposits is simulated. 

The major ground-water withdrawals simulated are 

quarry dewatering; self-supplied domestic, municipal and 

industrial use; and agricultural and golf-course irrigation. 

Water may exit or enter the bedrock aquifer as leakage 

to or from the overlying glacial deposits. Water also may 

enter or exit the model area through the constant-head 

boundaries in Lake Erie and in the southwestern edge of 

the domain. Based on the regional flow analysis (Bugliosi, 

1999), water enters the domain across the southwestern 

boundary and exits at Lake Erie. 

Numerical Model 

The equation describing ground-water flow cannot be 

solved analytically for the layered, irregular, and heterogeneous domain required for this regional study. Therefore, 

a numerical model that approximates this equation was 

used. MODFLOW-2000 (Harbaugh and others, 2000) 

was the computer code used to generate the numerical 

model of ground-water flow in the Monroe County region. 

Argus ONE and the Argus-ONE MODFLOW interface 

was used to generate the model grid and prepare the input 

files (Argus Holdings Limited, 2002; Winston, 2000). The 

ArcView and ArcMap Geographic Information Systems 

(ESRI, 2002a and ESRI, 2002b) also were used to generate information for the model input and to visualize model 

output. The numerical model requires specification of the 

geometry of the model domain, the boundary conditions, 

and parameters specifying the hydraulic conductivities, 

volumetric fluxes, and specific storage. 

A finite-difference method is used in MODFLOW-2000 

to approximate the equation that describes ground-water 

flow. The program allows the aquifer to convert between 

confined and unconfined conditions, and it has the capacity to simulate the other processes and boundary conditions 

required for the Monroe County regional model. The 

major limitation of the model for this application is that 

flow in the bedrock aquifer is dominated by flow through 

individual fractures, whereas flow through an equivalent 

porous media is assumed in the model simulation. This 

simulation of a fractured system as an equivalent porous 

media is typical of regional models (Anderson and Woessner, 1992; National Research Council, 1990), and at the 

scale of this model, this assumption should not hamper 

 28
	


	



	



	














	






     


&(+ %&#** $'" $%/&# '

('"('- **/" $%/*#)(*,#". %-#

*#!$)$, ,$(' ,-'"## *&+

- **/)-&)+*#&(.#"



Figure 16. Reported London Quarry discharge and computed flow at the N.B. Amos Palmer Drain 

streamflow-gaging station, Monroe County, Michigan. Also shown are precipitation values recorded
­

at the Dundee Farms weather station (Michigan Automated Weather Network, 

Michigan State University). 

29
	

 


















	




     
 


	
	




Figure 17. Reported discharge from London Quarry and computed discharge at the N.B. Amos 

Palmer Drain gage, Monroe County, Michigan. 

 30
	










	













!

22"5"

6+4"-)" "6#&& "-1.-

&/2 $2 &$ "- "0$( "6 3-&

 

!

.-%.-''0&'"2&1

2.-&$."6#&&

.+$),

"-1.-''0&'"2&1

6+4"-)")-&0"+1

2.-&$.22"5""*&

.$*5..%3"006

(.,/1.-$3++63"006

&"130&%3"006

Figure 18. Reported quarry discharges, Monroe County, Michigan, 2002-2003. Values also are shown 

where gaged by U.S. Geological Survey at streams receiving discharge in July, 2003 . 

31
	

9




 	9		9


9	


9	








#


!

!

!

!
#






%2()1/-(/,/*+&%,415(7


04%'1%.*,(2










	














"



!
#

!
#!

 
#




#



8 
$









	







	



	





























"




"
#

!
#


!
!
11/6

+.'+&%3(2'+1(&3+/./)),/6

Figure 19. Model area and boundary conditions in the study area, Monroe County, Michigan 

and surrounding area. 

 32
	
the application of the model or the evaluation of the results. For site-specific evaluation, however, the fractured 

nature of the aquifer becomes important and field observations may deviate substantially from the simulation 

results. 

Map Projection and Units Used 

Michigan georef coordinates (Berry and Bormanis, 

1970) were used as base coordinates for the model. Meters are used in this projection to define the map position, 

and Standard International units were used for the entire 

model. The simulation results have been converted to 

English units for this report to conform to standard usage 

in the area. 

Relation Between Numerical and 

Conceptual Models 

The conceptual model is the basis of the numerical 

model. The finite-difference approximation used in MODFLOW-2000 requires that the model area be subdivided 

into a regular grid of cells. For this application, the grid 

is composed of 10 layers, 297 rows, and 194 columns of 

finite difference cells. Cells outside the study area, and 

cells in layers eastward of the subcrop, are designated as 

inactive cells and are not used in the computation of water 

levels. There are approximately 400,000 active cells in the 

finite-difference grid. The grid is oriented with the strike 

of the bedrock units to anticipate anisotropy aligned with 

the strike (Nicholas and others, 1996). The grid is nonuniform. Because of the large withdrawals by quarries 

in the region, and the desire to evaluate the effects of all 

withdrawals on the ground-water system, the grid was refined to approximately 400 by 400 ft in quarries that were 

active in either 1991 or 2001. The largest model cells 

were approximately 6,500 by 6,500 ft in areas furthest 

away from Monroe County. The required input for the 

model are described in this section, but the specific values 

used in the model are difficult to present in the report. 

Model input data arrays are available by request from the 

Michigan District office. 

Each bedrock unit is modeled as two numerical layers of equal thickness. The bedrock units dip from their 

subcrop northwest into the Michigan Basin. A generalized 

cross section through the model extending from Lake Erie 

through northwestern Monroe County into the Michigan Basin is shown on figure 19. The subcrop of each 

unit, and the entire Dundee formation, is bounded above 

by glacial material to the east and shales in the western 

portion of the study area. The lower boundary is a noflow boundary. The northern, western, and southeastern 

boundaries of the model are also represented as no-flow 

boundaries. No flow was allowed across the outer boundary of the cells along the Detroit and Maumee Rivers. The 

upper cells for the numerical model along these rivers 

were modeled using the MODFLOW River Package, as 

discussed below. These rivers appear to act as regional 

hydraulic boundaries, but the vertical gradients near the 

rivers are not known. With this choice of boundary condition, the simulation considers the interaction between 

bedrock ground-water and the Maumee and Detroit Rivers. Constant-head boundaries were used for the remaining model boundaries (fig. 19). 

Confined and unconfined conditions were considered 

in the designation of the MODFLOW layer types for each 

bedrock unit. The layer-property flow package (Harbaugh 

and others, 2000) was used to define the geometry and 

designations of the numerical layers. For each bedrock 

unit, both numerical layers were specified to be convertible layers. In convertible layers, if the water level for 

a cell falls below the top of the cell, then the saturated 

thickness of the cell is computed and used in the approximation. Under transient conditions, the storativity of the 

cell in this case is replaced by its specific yield. If the 

water level in the cell falls below the bottom of the cell, 

the cell is removed from the calculation for an iteration. 

These cells can be re-wet during the iterative solution process if surrounding cells have a water level greater than 

3.28 ft above the bottom of the cell. The value of 3.28 ft 

was set during model calibration. 

 Leakage from the overlying glacial deposits is simulated using the general-head boundary package (Harbaugh 

and others, 2000). This package adds or removes water 

from the finite-difference cell based on the hydraulic 

conductance (hydraulic conductivity multiplied by the 

area available for flow, divided by boundary thickness) 

and the difference in water levels between the cell and 

the general-head boundary. As the water level decreases 

in the bedrock aquifer, the potential for leakage from the 

glacial deposits increases. In the field, once the bedrock 

aquifer becomes unconfined, the leakage from the glacial 

deposits will become independent of the water level in 

the bedrock aquifer. Downward leakage from the glacial 

deposits to the bedrock aquifer should become a function of the hydraulic properties of the glacial deposits 

and the perched water level within the glacial deposits. 

Complicating this process, capillary behavior also will 

change the response of the system as the bedrock aquifer 

becomes unconfined. The effects of capillarity, however, 

cannot be quantified without site-specific testing regarding the geometry, size, and distribution of fractures in the 

bedrock. Because of the uncertainties associated with 

quantifying flux across this boundary and the anticipated 

importance of this boundary to the regional model, a 

conservative choice that maximizes the potential leakage 

through the glacial deposits was made for this boundary. 

33
	
The general-head boundary increases the flux from the 

glacial deposits to the bedrock aquifer as the water level 

in the bedrock aquifer declines. This choice may moderate the local effect of high-capacity pumping by allowing 

increased leakage compared to the field situation. This 

boundary condition was applied in the subcrop of each 

bedrock unit. Conductance values were defined by designating a MODFLOW parameter to the different glacial 

lithologies shown in figure 3. In Monroe County, where 

a sufficient number of WelLogic logs were available for 

hydrogeologic analysis, the glacial lithology parameter 

was scaled by the effective vertical hydraulic conductivity discussed earlier and shown in figure 4. The individual 

well-log estimates were averaged in the preprocessing 

software to generate a value for each finite-difference cell. 

This scaling allows the variability shown in figure 4 to 

be represented in the model. The Coldwater and Antrim 

Shales are expected to restrict leakage, and the hydraulic 

conductance through the Coldwater and Antrim Shales 

was set to zero in the model. 

The general-head boundary was not assigned to a small 

zone around each quarry to prevent unrealistic values of 

leakage from being computed as the water level declined 

in cells designated as quarry cells. This zone may represent the disturbed area around the quarry where glacial 

materials are reworked after exposing the rock or the zone 

where the quarry operations essentially de-water adjacent 

glacial deposits. 

The value of the boundary head was estimated by intersecting the elevation contours and stream reach information from the available 1:100,000 USGS digital line 

graphics (DLG) from the model area. The intersections 

approximate the average elevation of the water surface 

at streams and rivers. The water table is at this elevation 

at the streams and rivers. The water table is actually at a 

higher elevation between the rivers and streams, but for 

the regional model scale, this approximation is considered 

satisfactory. For cells under Lake Erie, the appropriate 

lake level from figure 15 was used. The sensitivity of the 

model to changes in water-table elevation is considered 

in this report, because it is important in the leakage to or 

from the bedrock aquifer. 

Larger streams and rivers in the model area may affect 

ground-water levels and flow paths in the bedrock aquifer. 

The river package (Harbaugh and others, 2000) was used 

to simulate this effect. For the rivers, the exchange of 

water between the aquifer and river was estimated as the 

product of the river bed hydraulic conductance and the 

difference between the water level in the finite-difference 

cell below the river and the river stage. The river stage 

was estimated by intersecting the river with topographic 

contours as described previously. The conductance was 

set using a MODFLOW parameter and includes the 

thickness of the glacial deposits separating the river from 

the bedrock aquifer. In this way, the river has less effect 

on the bedrock aquifer when separated by thick glacial 

deposits and more effect where the glacial deposits are 

thinner. 

Agricultural and domestic water-use demands were 

modeled as averaged values across the study area. 

Domestic use often is neglected for regional studies, 

because much of the water pumped by homeowner wells 

is returned to the ground-water system through septic 

tanks or the return flow associated with watering gardens 

and lawns. For the most conservative model simulation 

in terms of the effect on the bedrock aquifer system, the 

estimated domestic use was removed from the bedrock. 

Return flow was assumed into the overlying glacial material where it is available to recharge the bedrock through 

leakage as described previously. Average values were 

estimated using data from Monroe County and applied to 

the entire study area, in the case of domestic supply, and 

to the rowcrop land use from the National Land Coverage 

Database (NLCD), in the case of agricultural use. Because 

the row crop coverage is not uniform across the region, 

the 30 m NLCD data were aggregated into 600 m by 

600 m cells. The percentage of 30 m pixels in the larger 

block that were designated as rowcrops was determined. 

The average irrigation rate for the rowcrops was multiplied by this percentage so that areas entirely covered 

by rowcrops were subject to the average demand, and 

those areas with less crops were subject to less demand. 

Model areas overlying shale are assumed to get water 

from glacial deposits and these irrigation demands were 

not imposed on the region of the model domain overlain 

by shale. Few wells are expected to be drilled through the 

shale into the carbonate aquifers. The average demands 

were modeled using negative values in the MODFLOW 

recharge package. The demands are input as length per 

time and multiplied by the area of the finite-difference cell 

to obtain the volume of water removed from the cell. 

Pumpage from golf courses, municipal supply, and 

industrial wells were modeled as point stresses using the 

MODFLOW well package. The well package requires the 

pumping rate and location of the well. The Argus ONE 

MODFLOW preprocessor apportions pumping from different numerical layers based on the transmissivity of the 

layers, if the well spans multiple numerical layers. Three 

major wells were identified on the potentiometric-surface 

map of Lucas County, Ohio by Breen (1989). The pumping rates at these wells, however, were not provided. To 

simulate the effect of these wells on the regional groundwater system, the MODFLOW drain package was used. A 

drain was specified at the appropriate finite-difference cell 

and the mapped ground-water level in the well was used 

to specify the drain elevation. 

 34
	
Quarries were simulated using the MODFLOW drain 

package. The model requires the elevation of the drain 

and the hydraulic conductance between the drain and the 

aquifer. To simulate a quarry, the conductance was set 

to 328 ft/d so that the water level in the finite-difference 

cells adjacent to the quarry would be very close to the 

level of the quarry. The elevation of the drain was set to 

the elevation of the quarry sump. This information was 

available for some quarries and estimated for the others. 

The discharge rates reported by the quarry operators were 

for model calibration. All of these imposed withdrawals 

are illustrated in figure 20. 

Time Periods Simulated 

The model time periods simulated, the stresses on the 

system for each time period, and the calibration targets 

for each time period are summarized in table 5. Three 

time periods were considered: predevelopment (approximately 1900), developed (1991), and recent (2001). 

Each period was simulated under steady-state conditions. 

The purpose of the steady-state 2001 simulation was to 

examine the long-term ground-water levels in the region 

given 2001 conditions. Field observations imply that the 

ground-water system, although showing some seasonal 

variation, may have been at a cyclic steady state until the 

late 1980s or early 1990s. 

Model Calibration 

In model calibration, input values are sought that 

minimize the difference between the simulation and field 

observations. Two types of observations were used in the 

calibration: water levels and fluxes. Use of flux observations greatly improves model calibration compared 

to using water levels only. For this reason, the reported 

quarry fluxes were used in the calibration procedure and 

were not imposed on the model as other demands, such as 

wells. The model must be calibrated, because site-specific 

measurements of aquifer properties, such as hydraulic 

conductivity, may not be appropriate at the scale of the 

regional model. Other values, such as leakage between 

the glacial deposits and bedrock aquifer, have not been 

measured directly. In the MODFLOW-2000 calibration 

procedure, parameters are established to define various 

hydraulic properties of the model (Hill and others, 2000). 

For this application, parameters were set up for each 

geologic unit, for each glacial lithology with a generalhead boundary conductance, for river bed conductance, 

and for the specified constant-head for the southwestern 

boundary. 

For the southwestern boundary, the parameter for the 

constant-head boundary fixed the value near the Maumee 

River to the river elevation. For the remainder of the 

boundary, a factor multiplying the difference between 

the river elevation and the calculated water-table height 

was sought. The product of the parameter and the difference between the river elevation and the calculated 

water-table height was added to the river elevation for the 

entire boundary. Therefore, the constant-head boundary 

always specifies the river elevation on the eastern end of 

the boundary and allows the head specified for the rest of 

the boundary to increase more where the glacial deposits 

are thick and less where they are thin. A value of this 

parameter of one gives a constant-head boundary fixed to 

the estimated water-table height. 

During calibration, many parameters were found to 

have low sensitivity or appeared to lack sufficient observations to yield reasonable results using inverse procedures. The values for these parameters were fixed at best 

estimates and the remaining parameters were used in the 

inverse procedure. The values of the fixed parameters 

were varied to try and yield the most reasonable and best 

calibrated model. As stated, the 1991 scenario was used 

for calibration. The set of calibrated parameter values 

also was checked using predevelopment simulations to 

provide an additional model constraint. The parameters 

used to define the model and the final calibrated values 

for each parameter are summarized in table 6. 

To check the model at the calibration targets, simulated water levels in the uppermost active rock layer were 

compared against water levels from the USGS monitoring wells in Monroe County, WelLogic ground-water 

elevations, and water levels reported by Breen (1989) 

and Breen and Dumouchelle (1991). The observed values were treated as steady-state heads and values were 

estimated for the USGS monitoring wells to account for 

observed seasonal changes during the early portion of 

the time series. The observations were weighted differently in the inverse procedure. Water levels from the 

USGS monitoring wells (G wells) were assumed to be as 

accurate as the contour interval on the topographic maps 

used to estimate the elevation of the well head. Measurement or any other error for these wells is assumed to be 

small compared to the elevation error. The uncertainty in 

a USGS topographic map is quantified by the statement 

that 90 percent of the elevations are within one-half the 

contour spacing of the true value. The 90-percent 

confidence interval is 1.6, if the error follows a Gaussian distribution. The standard deviation, entered as the 

observation weight to the parameter-estimation process, 

is the value of the contour interval divided by twice the 

confidence interval. This computation yields a water-level 

observation weighting value of 3 ft for the simulation. 

Because the WelLogic data may have greater error in 

35
	
	=

= 
=

=

	=


=




" 

"!

%

#

# !#

#%





&44*)

 *&;&<

&<'**

32)32

30(.1

&2732

 <0:&2.&

!-314732

 <0:&2.& 3(/;33)

88&;&/

 .'0*<

"  .0.(&3



6&2(*7832*

	 

	! 

&7*+631" *303,.(&0 96:*<

	59&)6&2,0*7

$!

"%

"% 

3)*0&6*&





" !"
 

" !#
 

# ""


 

 ! 
 

 ""  #

Figure 20. Map of major ground-water withdrawals within the study area, Monroe County, 

Michigan and surrounding area. 

36
	
Table 5. Time periods simulated in the ground-water flow model of the Monroe County regional study 

Model feature Predevelopment Developed Recent 

Time simulation Steady-state Steady-state Steady-state 

General-head 

boundary stress 

Drained, crossing of surface 

water features for small 

drains and contours 

used to fix stress 

Drained, crossing of surface 

water features for small 

drains and contours used 

to fix stress 

Same as developed 

simulation 

Lake Erie level = 571.7 feet 

above NGVD 29 

Lake Erie level = 571.7 feet 

above NGVD 29 

Lake Erie level = 569.7 feet 

above NGVD 29 

Lateral boundaries As described in text Same as predevelopment Same as predevelopment 

Domestic wells None Wells from Well Logic database 

with estimated demand 

Wells from Well Logic data 

base includes Developed 

condition and additional wells 

Irrigation wells None 

Estimated irrigation stress 

imposed for cells with 

rowcrop land-use coverage. 

Estimated irrigation stress 

imposed for cells with rowcrop 

land-use coverage. 

Industrial wells None As noted in table 3 As noted in table 3 

Quarry dewatering None Reported values used in 

model calibration 

Simulation results compared 

to reported values 

Calibration Target

 head

 flux 

Pattern of flowing wells and 

general magnitude of heads 

Checked flux from 

Sulfur Spring 

WelLogic ground- water levels, 

U.S. Geological Survey 

monitoring wells 

Sulfur Spring and quarry 

dewatering estimates 

Not calibrated - values compared 

to U.S. Geological Survey 

monitoring wells and WelLogic 

values to test mechanisms for 

observed declines 

37
	
0+!

Table 6./*"1"/020"!&++2*"/& )*,!")4&1%-/*"1"/16-"+!#&+) )&/1"!3)2"0/*"1"/0"),41%"

!,2)")&+"&+1%"1)"/"#&5"!!2/&+$-/*"1"/"01&*1&,++!4"/"*+2))6!'201"!

/*"1"/6-" )2"

&+#""1-"/!6

,/&+" "+"/)%"!,2+!/6 ,+!2 1+ "# 1,/  %&03)2"&0*2)1&-)&"!

6/",# "))+!!&3&!"!

61%& (+"00,#$) &)

!"-,0&101,6&")!/".2&/"!

 ,+!2 1+ "

"1/,&1&3"/ 6"/-/,-"/16#),4%6!/2)&  ,+!2 1&3&16 
	

000)+!0 6"/-/,-"/16#),4%6!/2)&  ,+!2 1&3&16 

6)3+& 6"/-/,-"/16#),4%6!/2)&  ,+!2 1&3&16 

)&+ 6"/-/,-"/16#),4%6!/2)&  ,+!2 1&3&16 

))23&) "+"/)%"!,2+!/6 ,+!2 1+ " 




2/&"!))"6 "+"/)%"!,2+!/6 ,+!2 1+ " 


,*-)"5 "+"/)%"!,2+!/6 ,+!2 1+ " 


/&")(""! "+"/)%"!,2+!/6 ,+!2 1+ " 	


 201/&+" )6 "+"/)%"!,2+!/6 ,+!2 1+ " 	


%&03)2"&0*2)1&-)&"!

6/",# "))+!!&3&!"!6

1%& (+"00,#$) &)!"-,0&101,

6&")!/".2&/"! ,+!2 1+ "

%&03)2"&0*2)1&-)&"!

6/",# "))+!!&3&!"!6

1%& (+"00,#$) &)!"-,0&101,

6&")!/".2&/"! ,+!2 1+ "

%&03)2"&0*2)1&-)&"!

6/",# "))+!!&3&!"!6

1%& (+"00,#$) &)!"-,0&101,

6&")!/".2&/"! ,+!2 1+ "

%&03)2"&0*2)1&-)&"!

6/",# "))+!!&3&!"!6

1%& (+"00,#$) &)!"-,0&101,

6&")!/".2&/"! ,+!2 1+ "

%&03)2"&0*2)1&-)&"!6/"

,# "))+!!&3&!"!61%& (+"00

,#$) &)!"-,0&101,6&")!/".2&/"!

 ,+!2 1+ "%"/""),$& 

0"!"##" 1&3"3"/1& ) ,+!2 1+ "0

/"3&))"1%&0-/*"1"/)0,&0

0 )"!6+&+1"/-,)1"!"##" 1&3"

3"/1& ) ,+!2 /+ "!&3&!"!6


	&+/"0*--"!0) 201/&+"

 38
	
 

Table 6. Parameters used in numerical model with parameter type and final calibrated values--Continued
­

Parameter Type Value 

(in feet per day) 

Lacustrine sand 

Not mapped 

Anisotropy 

Drain 

Southwest head 

River bed 

Detroit River 

Maumee River 

Dundee 

General-head boundary conductance 

General-head boundary conductance 

Horizontal anisotropy 

Drain conductance 

Constant head boundary head 

Riverbed conductance 

Riverbed conductance 

Riverbed conductance 

Layer-property flow hydraulic conductivity 

0.0013 ft/d 

0.003 ft/d 

1.0 

330. day-1 

0.9

 0.03 ft/d 

3.3 ft/d 

3.3 ft/d 

3.3 ft/d 

This value is multiplied 

by area of cell and divided 

by thickness of glacial 

deposits to yield required 

conductance. Where 

WelLogic-based effective 

vertical conductances are 

available, this parameter

 also is scaled by an 

interpolated effective 

vertical conducrance 

divided by 8.64E-02 in 

areas mapped as lacustrine 

sand

This value is multiplied by area of 

cell and divided by thickness of 

glacial deposits to yield required 

conductance 

Horizontal (x-y) anisotropy, 

aligned along rows that 

follow the general strike 

of bedrock units 

Multiplied by area of cell 

contributing to quarry flow 

Factor used to set 

constant-head boundary, 

a value of 1.0 sets the 

boundary to approximate 

water-table elevation 

Multiplied by length of 

river in a cell to yield 

required river bed 

conductance 

Multiplied by length of 

river in a cell to yield 

required river bed 

conductance 

Multiplied by length of 

river in a cell to yield 

required river bed 

conductance 

39
	
the estimated elevation or measurement of ground-water 

level, an 80-percent confidence interval was assumed. The 

standard deviation used for these observations was 

4 ft. The water-level values tabulated by Breen and Dumouchelle (1991) were treated in the same manner as the 

G wells and assigned a weight of 3 ft. 

The simulated hydraulic-head distribution (fig. 21) 

agrees with the expected distribution shown in figure 7. 

There is a component of flow from northwest of Monroe 

County and an area of elevated water levels because of 

leakage through the portion of the glacial moraine that 

lies east of the Coldwater and Antrim Shales. The regional 

flow is from the southwest, then east towards Lake Erie. 

This flow follows the regional pattern given by Bugliosi 

(1999). Areas of local drawdown are noted near the active 

quarries. 

One check on the model calibration is the spatial 

distribution of residuals, the differences between the observed and simulated values. The unweighted water-level 

residuals for the calibrated model are shown in figure 22. 

Positive and negative residuals tend to be scattered across 

the model area. Points of closer agreement (+/- 5 ft) also 

are scattered across the model area. There is an overestimation in the simulation of the water levels in southeastern Monroe County. This overestimation and points with 

good agreement occur in the same geologic unit and this 

fit was accepted. There are less data from Lucas County, 

Ohio, and some pumping in this area may not be simulated as the hydraulic head in this area was consistently 

overestimated during the calibration process. 

A direct comparison between the observed water level 

and simulated water level, which is the computed hydraulic head at the monitoring well, for the final calibrated 

trial is shown in figure 23. Note that the residuals follow the 1:1 correspondence line. The maximum underprediction of the model was 35 ft, and the maximum 

overprediction of the model was 29 ft. These largest two 

mismatches resulted from comparison of simulated water 

levels to values reported in the WelLogic database. Many 

of the residuals fall within 1 ft of the target water level. 

The water level was overpredicted at 78 observations 

and underpredicted at 96 observations. For this simulation, the mean weighted residual for water level was 0.74 

ft, and the mean residual (unweighted) for water level 

was 0.88 ft. These values indicate that the model slightly 

underpredicts the water levels. The root-mean-square 

error of water-level residuals was approximately 10 ft. 

The observations from the USGS monitoring wells were 

given higher weight than the WelLogic values during 

the inversion procedure, and, in general, the simulation 

matches the G wells better. The most notable mismatches 

with the G well monitoring targets are large underestimations of head, greater than 15 ft, at G29 and G30. Both of 

these monitoring wells are in the karst area in southwestern Monroe County. The water levels in these monitoring 

wells tends to fluctuate more than other wells in the study 

area, making estimation of a steady-state observation 

difficult. In addition, the regional model generalizes the 

ground-water flow in karst areas. 

The calibrated parameters were used to simulate the 

hydraulic-head distribution under predevelopment conditions. For this simulation, the quarries, and domestic 

and agricultural withdrawals were removed. Under these 

conditions, the model simulated water exchange with 

rivers, Lake Erie, and the glacial deposits. The simulated 

predevelopment water levels are shown in figure 24. 

This plot compares well to the regional patterns given 

by Bugliosi (1999) and the predevelopment conditions 

given by Nicholas and others (1996). Comparison of the 

water levels to ground elevation reveals that the hydraulic 

heads simulated are consistent with the flowing wells in 

the region summarized by Allen (1977). Heads in parts of 

Monroe County are as high as 20 ft above land surface, 

which is the value reported by Sherzer (1900). 

In addition to calibrating to the observed hydraulic 

heads, reported quarry discharges were used in the parameter-estimation procedure. Discharges reported for the 

quarries were compared to simulated drain fluxes. These 

observations were weighted using an estimated scaled coefficient of variation for the observation. For flows where 

some values were reported and where the values did not 

vary widely, a scaled coefficient of variation of 

10 percent was used. For other quarries, a scaled coefficient of variation of 20 percent was used. Various 

weighting values for the drain flows were used during the 

calibration process and had little effect on the final calibrated values for the parameters. The quarry discharges 

used in the 1991 calibration and the simulated flow from 

the model are summarized in table 7. 

The model tends to underestimate most quarry and 

spring flows. This underestimation is especially true for 

the Sulfur Spring and Francestone calibration targets. 

The error at Sulfur Spring may be a result of the regional 

nature of the ground-water-flow model. Spring flow may 

result from local heterogeneities that are not captured in 

the simulation. The larger flow at Holcim quarry, however, is simulated reasonably well. The inherent uncertainty 

in quarry discharge and sump elevation used to set the 

drain elevations in the model, and the resolution possible 

with the scale of the regional model, make these calibration targets more uncertain. The reported discharges are in 

a reasonable range for the study area and accepted in the 

calibration. 

Another flux constraint checked in the calibration was 

the discharge to the Detroit River. Gillespie and Dumouchelle (1989) used geophysical techniques to estimate 

the thickness of glacial deposits and sediments for Great 

Lakes connecting channels. Using estimated hydraulic 

 40
	

;


 	;		;


;	


;	

!

$"

$#

!(

&

&"#&

&(







 

 


 

 

	 






 

	


 
 





 	



	










 	






"

#!"

)6,-531$",303./*)0"859,:


48)+5)2.0,6

'#

 $###$!"$#

(!$"327385/27,59)0/6

-,,7)781/2%

3+,0)5,)





$!(

Figure 21. Simulated hydraulic heads for 1991 trial for study area (Monroe County, Michigan 

and surrounding area). 

41
	

;

 ;;


;

	;

 

#" #!

 '

%

%!"%

%'





( 6+,531#! +303-/)(0!859+:

	
48(* 5(2-0+6



	
!

	
" !

&"





# ' 3*+0(5+(

!" #" !#!
 

! $!#"
 

 %" $!		"
 

+667.(235+48(073	

 

5+(7+57.(2	
(2*0+667.(235+48(073

 

5+(7+57.(2
(2*0+667.(235+48(073

 

5+(7+57.(2
 (2*0+667.(235+48(073	

 

5+(7+57.(2	

 

Figure 22. Distribution of residuals (observed - simulated) for water levels in the study area 

(Monroe County, Michigan and surrounding area) for 1991 final parameters. 

42
	






	












( ##'

 #%!"( ##'

& $( ##'


"$ 

   	    




Figure 23. Simulated and observed hydraulic heads for bedrock aquifer wells in the study area 

(Monroe County, Michigan and surrounding area). Data from U.S. Geological Survey G wells and data 

from Breen and Dumouchelle (1990) are distinguished from WelLogic. 

43
	
	:


	 
:
:

	:

	:

 

#!

#"

 '

%

%!"%

%'










 

 

 

	 

 








 	


 


 

 	

 	
















!

" !

(5+,420#!+2/2-.)(/!748+9

	37(*4(1-/+5

&"

#""# !#"

 $"' #!

216274.16+48(/.5,++6(670.5

$

2*+/(4+(





# '

Figure 24. Simulated predevelopment hydraulic heads for the study area (Monroe County, 

Michigan and surrounding area) using calibrated values determined using 1991 simulation 

and constrained by predevelopment conditions. 

44
	
Table 7.2//5+"0-/'+%"'0!&/%#020#"'+!)' /1',+,$		/#%',+)*,"#),$1"5/#+"$'+)

0'*2)1#"$),40

%)"*'))',+%)),+0-#/"5+,13') )#+#%1'3#3)2#0'+"'!1#41#//#*,3#"$/,*.2'$#/

2//5,/01'*1#", 0#/3#""'0!&/%#'*2)1#""'0!&/%##0'"2), 0#/3#"
 

0-/'+%%)"%)"0'*2)1#"%)"
 

,)!'*


,!(4,,"	

1,+#!,114(#
	

/+!#01,+#	


2)$2/-/'+%


#45

5)3+'2!0,			


2//5,+/##+-	

conductivities and an estimated upward gradient of 0.01, 

discharge values were estimated. For the Detroit River, 

these values ranged from 0.6 Mgal/d near Lake St. Clair 

to 20 Mgal/d near Lake Erie where the river and shipping 

channel reach the bedrock aquifer. Simulated discharge to 

the Detroit River is 1 Mgal/d. This value is in the reasonable range estimated by Gillespie and Dumouchelle (1989). 

The thickness of the glacial deposits in the model cells at 

the Detroit River may be too large leading to an underestimate of flux. On the scale of the model cells used, however, 

the values used were appropriate. More accurate discharge 

values would require additional grid refinement near the 

river and better input data regarding the thickness of the 

glacial deposits near and under the river, the hydraulic conductivity of these materials, and the actual vertical gradient 

at the river. 

The model residuals were checked for correlation and 

trends to guard against a biased result despite adequate 

mean-error statistics. Plotting the weighted residual against 

the weighted simulation value tests for bias in the simulation (fig. 25). The weighted residuals for the WelLogic 

observations are distributed with both positive and negative 

values and show no apparent trend as the weighted simulation value is changed. The G wells and observations from 

Breen and Dumouchelle (1991) have slightly more positive 

residuals indicating that the model overestimates the head, 

but there is not a trend with the weighted simulation value. 

Simulated quarry fluxes, as discussed, tend to underestimate 

the observed discharges. In general, simulation results are not 

biased toward high or low observed values. 

The composite-scaled sensitivity for all of the parameters, 

computed using the calibrated values for the parameters, are 

shown in figure 26. Note that the five parameters used in the 

final parameter-estimation simulation have among the highest composite-scaled sensitivities. The lacustrine clay, lacustrine sand, horizontal anisotropy, and southwest constant-head 

boundary parameters have similar magnitudes for the composite-scaled sensitivity, but during the calibration process these 

parameters tended to be unstable and prevented convergence 

of the parameter estimation. The instability may be caused 

by a lack of observations for some parameters, change in the 

sensitivity as the parameter values change, or correlation with 

other parameters in the ground-water system when too many 

parameters are chosen for parameter estimation. Effects on 

the simulation results of varying the parameters with larger 

composite-scaled sensitivity values were tested in a sensitivity 

analysis performed with the model. Changes in the low-sensitivity parameters should not appreciably affect the simulation 

results and sensitivity analysis was not performed on these 

parameters. 

45
	




















% $

 "


#!

#!$

       	 
 



Figure 25. Weighted residuals and weighted simulated values for the model of the study area 

(Monroe County, Michigan and surrounding area). Residuals are reasonably scattered positive 

and negative, and they do not show definite trends as the weighted simulated value changes. 

 46
	

















	


($*()+)!%'($*()*!$*!&%

)!$+#*!&%)

($*(),(!$%+##/+(!%

#!(*!&%

&&)$##

*&)%

&&)$##

*&)%

##+,!#

	+(!,##/


&$'#.

(!#"

+)*(!%#/

+)*(!%)%

&(!%

&*$''

*(&!*!,(

	)))#%)

/#,%!

#!%

+%

(*!#

&(!0&%*#

+((!)

* ((!,()

*(&!*!,(

+$!,(

&+* -)*




%(# /(+#!&%+*% &(!0&%*# /(+#!&%+*!,!*/ %!)&*(&'/ /(+#!&%+*%




Figure 26. Composite-scaled sensitivities for all parameters used to define the model of study area 

(Monroe County, Michigan and surrounding area). 

47
	
The correlation matrix estimated for the five parameters used in the parameter-estimation procedures is 

 

    

  
  	
 	

 
    



     

 	
    	

 	 

  	 

This matrix indicates that the parameters used in the 

estimation process are not excessively correlated, because the off-diagonal values in the matrix are not close 

to unity. If parameters are correlated, parameters may 

have to be combined, or more constraints added to the 

model to help provide a unique set of calibrated values. 

A water budget for each simulation is reported in 

MODFLOW-2000. This budget will be used to investigate causes of ground-water-level declines. For the 1991 

and predevelopment simulations, the error in the water 

budget was 0.5 percent or less. Large errors in the water 

budget may indicate inconsistencies in the ground-water 

model, too few iterations in the iterative solver used by 

the numerical model, or potential problems with simulated water flux across model boundaries. The lack of error 

in the simulations does not guarantee a consistent model, 

but it is another indicator of satisfactory model performance. The water-budget values will not be presented 

for the predictive simulations or sensitivity simulations 

presented in the next sections, but the mass-balance error 

consistently was 1.0 percent or less for all simulations. 

Exploration of Ground-Water-Level 

Declines 

Ground-water capture 

The numerical model was used to investigate the observed ground-water-level declines in the Monroe County area. The evaluation is discussed following the classic 

series of papers by Theis (1940), Bredehoeft and others 

(1982), and Bredehoeft (2002) that explores the source 

of water to wells and the “water budget myth.” This series of papers explains that there is a concomitant decline 

in water level as withdrawal from an aquifer is increased 

by pumping — any pumping of water causes a removal 

of water from storage. Achievement of a new steadystate water level only is possible when the hydraulic 

gradients caused by the pumping either induce increased 

recharge to the ground-water system, decreased natural discharge from the ground-water system, or produce a 

combination of increased recharge and decreased discharge. 

It is the change in recharge, discharge, or both, which may 

be termed “capture”, that allows the system to reach a new 

steady-state, not the virgin recharge or discharge rates for 

the system. Bredehoeft and others (1982) refer to a focus 

on the relation between imposed pumping and the virgin 

recharge rate as the “water budget myth.” In this section, 

the induced changes in the capture of the bedrock aquifer 

in response to the change in withdrawals from predevelopment to 1991 and then to 2001 will be explored to help with 

the analysis of the observed water-level declines. Pertinent 

fluxes for the calibration simulations are presented in table 

8. Information from the exploratory 2001 simulations will 

be presented in this same form. 

The fluxes summarized demonstrate the factors required 

to achieve steady-state water levels with the 1991 demands 

imposed on the ground-water system. The flux from the 

ground-water use simulated for the entire model area is 

approximately 10 Mgal/d greater than the use estimated 

for Monroe County. The difference is due to quarries and 

pumping in Ohio and Wayne County, Michigan, and to the 

additional domestic and agricultural use across the study 

area outside of Monroe County. Capture is the total change 

in the flux across head-dependent boundaries, general-head 

boundaries, and the flux to rivers. Because these are steadystate simulations, this capture must equal the flux from the 

demands on the system. The increase in flux across constant 

head boundaries is a combination of an increase in virgin 

recharge of 1.1 Mgal/d and a decrease in natural discharge 

across the boundary in Lake Erie of 1.0 Mgal/d. In the same 

manner, water exchange with the glacial deposits and Lake 

Erie changes by both an increase in leakage to the bedrock 

aquifer (in) and a decrease in leakage from the bedrock 

aquifer (out). The flux to rivers also is important in this 

simulation. The change in discharge from the bedrock aquifer to the rivers is approximately 8.5 Mgal/d. This decrease 

might be questioned if the earlier discussion of base flow 

and the discussion that base flow may not reflect the condition of the bedrock aquifer is recalled. The major fluxes 

from the bedrock aquifer in the simulation, however, are to 

the Maumee and Detroit Rivers, and this small change in 

discharge may not be evident compared to the river discharge. The discharge in the Maumee River at Waterville, 

Ohio (USGS Station 04198500) ranged from 300 to 13,000 

Mgal/d in 2000, and the average discharge of the Detroit 

River is approximately 120,000 Mgal/d (Holtschlag and 

Koschik, 2003). 

The spatial distribution of fluxes from the general-head 

boundaries for the predevelopment and 1991 calibration 

simulations are shown in figures 27 and 28. In these figures, the change in leakage between the glacial deposits and 

the bedrock aquifer in Monroe County is clear. Under pre-

 48
	
Table 8.(14"/#.+) (&.0"!)+!"(/*!//"//)"*0+# %*$"/#.+)2&.$&*.0"/+#." %.$"*!

!&/ %.$"#+.0%"/01!5."

((#(14"/&*)&((&+*$((+*/,".!5*"$0&2"2(1"/&*!& 0"30"..")+2"!#.+)"!.+ '-1&#".

(14 .+// (140+-1..&"/

$"*".(%"! 1(#1.,.&*$

+1*!.&"/ &*!1/0.&(*!

(14 .+// ("'$"0+ (140+.&2"./ )1*& &,(3"((/

 +*/0*0%"! #.+)$( &( &..&$0&+**!

+1*!.&"/ !",+/&0/*! +)"/0& 1/"

'".&"

* 	
 	
 	 

."!"2"(+,)"*0 10  
 	 


"0   	
 


* 	
 

 
 

		(&.0"! 10   	 



"0 

 
 	 



%*$"#.+)2&.$&*.0" 
	 
	
  


development conditions (fig. 27), the bedrock is losing 

water to the glacial deposits over much of the study area 

and nearly half of Monroe County. In the 1991 simulation (fig. 28), the bedrock is gaining water over most of 

the study area and almost all of Monroe County. The 

localized leakage from the moraine northwest of Monroe County is evident in both simulations. The pumping 

demands imposed by the 1991 simulation are balanced 

by capture resulting from a virtual elimination of the 

natural discharge from the bedrock to the glacial deposits under predevelopment conditions and an increase in 

the recharge to the bedrock by leakage from the glacial 

deposits in the western portion of the study area. 

2001 simulations 

Simulations were done to determine the causes of 

ground-water-level declines by imposing the estimated 

2001 demands described in this report on the model with 

the 1991 calibrated parameters. The transient stresses 

from 1991 to 2001 were not used in model calibration, 

because the conditions used for such calibration simulations would predetermine the causes of the simulated 

ground-water-declines. For example, if the model were 

calibrated using these transient stresses, and the general-head boundary were assumed not to change, then a 

calibrated 2001 model would indicate that the observed declines could be attributed only to increased demands. The 

effect of below-average precipitation on the water level in 

the glacial deposits is difficult to assess. Therefore, the best 

option for exploring water-level declines was to run simulations using the calibrated model based on 1991 and predevelopment conditions, and to perform sensitivity analysis to 

illustrate the range of reasonable solutions. 

To determine if increased demands, both quarry dewatering and other uses, could produce the observed declines, 

the calibrated model was run using 2001 conditions as described in table 5. Note that the elevation of the water table 

in the glacial deposits, the general-head boundary value, 

was not changed. The simulated steady-state water levels 

under 2001 conditions are given in figure 29. A small area 

of elevated water levels to the northwest of Monroe County 

is evident in the figure, and there is additional drawdown 

across the modeled area compared to the 1991 simulation. 

The simulated decline in water level is more easily recognized when the 1991 simulated water levels are subtracted 

from the 2001 simulated heads (fig. 30). Negative values in 

figure 30 indicate a decline in water level. Note the 

similarity between the simulated change map and the 

change map estimated from WelLogic ground-water levels 

49
	

 

	4

	




	4 
4
4

	 

	4

 "

  

  






 
 

	  0 10 20 MILES 	4

" 0 10 20 KILOMETERS 


#0&'/-+&-*-()$#*1/2&3 
 
 
 

	.1#%/#,(*&0
 



! -%&*#/&#

 !




 !





 
 


"
 


"

Figure 27. Simulated potential flux direction between glacial deposits and bedrock aquifer for the 

study area (Monroe County, Michigan and surrounding area) under predevelopment conditions. 

 50
	

	5 
5
5

	 

	5

!
#

!

!

	5


! 



	











	5# 0 10 20 MILES 

	 

0 10 20 KILOMETERS 

$1'(0.,'.+.)*%$+203'4

	/2$&0$-)+'1


 ! 
!



!
"








!
"










!


 #


"



.&'+$0'$







#

Figure 28. Simulated potential flux direction between glacial deposits and bedrock aquifer for 

the study area (Monroe County, Michigan and surrounding area) under 1991 conditions. 

 51
	
 

 

	9


	9 
9
9

	9

	9



" 

"!

&

$

$ !$

$&








 



 


 

 

 

	


 



 	


 


 

 	






 





	








0 10 20 MILES 

0 10 20 KILOMETERS 

'4*+31/" *1.1,-('. 637*8

	26')3'0,.*4

%!

"!!!"

 "!&" 

105163-05*37'.-4+**5'56/-4#

"&

1)*.'3*'





Figure 29. 2001 steady-state simulated hydraulic heads using 1991 calibrated parameters of the 

study area (Monroe County, Michigan and surrounding area). 

52
	
 

 


9


9 
9
9


9

	9



" 

"!

&

$

$ !$ $&









 












	



0 10 20 MILES 

0 10 20 KILOMETERS 

'4*+31/" *1.1,-('. 637*8

	
26')3'0,.*4

%!

 "!$

 "!		
	&" 

105163-05*37'.-4	+**5

 !!$

$!# "!&



	

		

"&

1)*.'3*'





Figure 30. Difference between simulated hydraulic heads, 1991-2001 for the 

study area (Monroe County, Michigan and surrounding area). 

53
	
Table 9. !#+"*$(&%(*'+((-!) ()%()"*'+((!)(%#* 
	

)*-)**)!#+"*!%$%(* )*+-(

"#!""!%$""%$)&(-

+((- &%(*

!) (

"

!#+"*,"+

"

!($

"

%"!#

$)%$

%$%$

-",$!




























(fig. 13b). The -10-ft contour from the WelLogic analysis also is shown on figure 30. Both the simulation and 

the WelLogic analysis show approximately 

10 ft of decline across the middle of Monroe County, 

small declines in the southern townships in Monroe 

County, and larger declines in the northern townships. 

The area of 20 ft or more of decline in the north-central 

portion of the county is smaller in the simulation than in 

the WelLogic analysis (fig. 13b). The simulation results 

appear to slightly underestimate the observed regional 

water-level decline. 

Selected quarry discharges estimated in the 2001 

steady-state simulation are summarized in table 9. The 

simulation slightly overestimates discharge at Hanson 

and Holcim quarries and underestimates discharges at 

London Aggregates and Sylvania quarries. Some of the 

difference may be attributed to heterogeneities in the 

bedrock aquifer that are not simulated in the regional 

model. Changes in the unit hydraulic conductivity affect 

discharge at all of these quarries and improving the fit 

to discharge from one quarry would be expected to degrade the fit at the others. Some of the differences also 

may be attributed to inaccuracies in model estimates for 

the area or depth of these quarries. 

A similar analysis for other water withdrawals is not 

necessary because they are input directly as demands 

into the ground-water model. The simulated domestic, 

municipal, and irrigation demands match those outlined 

in the “Water use” section of this report. Any uncertainty related to the ground-water system response to these 

flows would be related to the uncertainty in the water-use 

estimates. As in the 1991 simulations, the total flux in the 

2001 simulations is approximately 10 Mgal/d greater than 

that estimated for Monroe County. The total increment in 

withdrawal from the system is consistent with the estimated 

increase in withdrawal based on available water-use information. 

A more detailed examination of the results reveals that 

the estimated steady-state heads tend to be higher than the 

observed values in 2001, especially in the northwest and 

north-central portion of the county. This information for 

the USGS monitoring wells is summarized in table 10. Note 

that simulated water levels in monitoring wells G-22, G-23, 

G-24, G-25, and GLTO match, but some wells, including 

G-7, G-8, and G-9, overestimate the water level. Sensitivity 

analysis can help explore to what extent other factors affect 

the water levels and can reveal the reasonable range of 

declines expected because of the inherent uncertainty in the 

model parameter values. 

The 2001 simulation is for steady-state conditions, 

therefore, the simulation provides an estimate of the ultimate capture, if conditions were held to 2001 values. The 

increased demands are balanced by increased flux across 

the general-head boundary (table 11). In the 2001 simulation, nearly all of the additional water withdrawn from the 

system is provided by leakage through general-head boundaries and interaction with rivers. Recall that the use of the 

general-head-boundary package to simulate the leakage 

 54
	
Table 10#%+$*#'&()+$*) ('%)*.)**)#%+$*#'&-#*"')(,

,$+)&()#+$) '('$'!#$+(,.%'&#*'(#&!-$$)#&*")*+.(

)(,-*( #%+$*-*( )#+$

'&#*'(#&!-$$ $,$ $,$ )(,

*', *', #%+$*

  *

  	 

 
 
 


	   


 	 


 	

 
  

 	 		 



  
 


   

  

 


  

 



   

	 
  


 	 

 

  
	
 	

 
  

 
 
 


  	 



   

   

   

	   


   

   

  	 

 	  


	 
  

   

55
	
Table 11. Fluxes from calibrated model and 2001 simulation summarizing ground-water capture.
­

[All fluxes in million gallons per day, negative values indicate water removed from bedrock aquifer]
­

"+.(%))

$("

"+.(%)) %+$( )

%$)*$* "!*%

 " "&%) *) "+.*%

%+$( ) $!(  ( ,()

"+.(%))

'+(( ))+"+(

)&( $ $+)*( "

$#+$  &"

-"") (( * %$

$%#)* +)

$  

 
 

+*   
  	" (*

* 
	 

	  

$(%#, ( $(* 	 	
 	 



 $(%#(* 	 
 

from the glacial deposits to the bedrock aquifer maximizes this flux as the bedrock aquifer model layer becomes unconfined. Because this general-head-boundary 

flux is the key factor balancing the increase in demand 

in 2001, this choice of numerical representation of the 

boundary is a potential cause of the overestimation of 

head in the simulation. In the 2001 simulation, the flux 

out to Lake Erie through the general-head boundaries 

representing the lakebed is reduced to slightly less than 

1 Mgal/d. Because the hydraulic-head gradients do 

not change appreciably at the Lake Erie or southwest 

constant-head boundaries between the 1991 and 2001 

simulations, the flux across the model boundaries only 

changes by 0.7 Mgal/d. 

Sensitivity to imposed boundaries 

Sensitivity analysis examining the uncertainty inherent in the model and the effect of changes in different 

model inputs to the simulated hydraulic head was used 

to ascertain whether the observed heads are consistent 

with the 2001 steady-state model results or if other 

processes affect water levels. Three model boundaries 

were examined to determine how each can contribute 

to the observed ground-water declines, and to illustrate 

how each affects ground-water capture in the study 

area. The boundaries examined were the level of Lake Erie 

on the eastern boundary, the constant-head boundary on the 

southwest border of the model area, and the general-head 

boundary used to simulate the glacial deposits. 

As discussed previously, the level of Lake Erie changed 

between 1991 and 2001. To examine how much of the observed ground-water decline could be attributed to a change 

in lake level, the 1991 calibration simulation was run again 

using the 2001 level of Lake Erie. The change in lake level 

was -1.7 ft. The steady-state simulation maximizes the effect of changing the lake level by neglecting any time lag 

in the response of the bedrock aquifer to changes in lake 

level. The maximum simulated change at a USGS monitoring well location was 0.8 ft at G16. The change in the fluxes 

across the boundaries because of this change were less than 

0.5 Mgal/d. More water exited the system through leakage to Lake Erie, but, at the same time, slightly less water 

entered the system in areas where the ground-water level 

is below lake level. The simulation results indicate that 

changes in lake level minimally effect the observed groundwater declines in Monroe County. 

Changes in the constant-head on the southwestern 

boundary of the modeled area affect the computed flux 

across the boundary, but if the remaining model parameters 

of the simulation are held constant, these changes did not 

greatly affect the simulated heads at the USGS monitoring 

 56
	
wells in Monroe County. The boundary head was kept 

to a small range consistent with the regional pattern 

suggested by Bugliosi (1999), and extreme changes 

would be expected to have a greater effect on fluxes. 

The potential effect of decreased precipitation or infiltration leading to a decrease in the ground-water level 

in the glacial deposits was tested through a simulation 

using the 2001 conditions, but with the water level 

in the glacial deposits simulated by the general-head 

boundary reduced by 3.3 ft. This simulation examines 

the combined effect of changing water-table elevation 

and imposed demands. Changing leakage through the 

glacial deposits by changing the water-table elevation, 

as might be expected during drought periods, affects 

areas where there is leakage to the bedrock (fig. 31). 

The difference between the two 2001 steady-state solutions is shown. Negative values result from the lowered 

water-table elevation in the general-head boundary 

package. Mass balances reported by the simulations 

yield a loss of approximately 1.6 Mgal/d in leakage to 

the bedrock because of the lowering of the water table. 

The results indicate that ground-water-level declines 

would be more evident in southern Monroe County 

if a decrease in leakage, because of low precipitation, 

caused the regional decline. This simulated distribution 

of declines does not match the WelLogic analysis or the 

water levels measured in the USGS monitoring wells. 

The hydraulic conductance of the glacial deposits 

also controls the leakage between the glacial deposits 

and the bedrock aquifer. The calibrated model parameters prescribing the hydraulic conductance for the 

general-head boundary condition for the lacustrine clay, 

lacustrine sand, and moraine units were varied for the 

2001 simulation. For each sensitivity simulation, all of 

the remaining parameters were fixed at the calibrated 

1991 values, and the 2001 Lake Erie level was used. In 

general, increasing the conductance increases the heads 

for the modeled area. The response at monitoring wells 

G-7 and G-2 is shown in figure 32. Water levels in 

both of these monitoring wells were more sensitive to 

changes in the lacustrine clay parameter. The simulated 

heads did not respond as much when the conductances 

were lowered compared to when the conductance was 

increased. Increasing the conductance by an order of 

magnitude for the moraine parameter increased the 

head at G-7 by 12 ft, and decreasing the conductance 

by an order of magnitude caused a decrease in water 

level at G-7 of 6 ft. As the amount of water entering 

the system through the general-head boundary was 

decreased, the hydraulic heads in the bedrock aquifer 

lowered, and the flux through the drain cells representing the quarries decreased. 

Ground-water capture in the system responds as 

anticipated (fig. 33). As the hydraulic conductance of the 

glacial deposits is increased, the water level in the bedrock 

aquifer tends to increase. This water-level increase causes 

an increase in quarry flux and a rise in the overall imposed 

demand of the ground-water system. The increased flux 

across the general-head boundary balances this increase 

in demand. The change in flux across the constant-head 

boundaries is small for these sensitivity simulations. The 

fluxes from the rivers and imposed demands are able to readjust to changes in the general-head boundary flux. As the 

flux through the general-head boundary is more restricted, 

quarry flows decrease and the system reaches steady state 

without as large of an adjustment to the overall fluxes or 

heads. The changes shown in figure 33 are with respect to 

the results of the 2001 steady-state simulation using the 

calibrated parameters. 

Sensitivity to bedrock hydrogeologic 

parameters 

The remaining model parameters examined were the 

hydraulic conductivities of the Detroit River, Sylvania, Bass 

Islands, and Salina units and the horizontal anisotropy ratio 

used for the simulations. The sensitivity to these parameters 

was assessed by examining the change in the 1991 steadystate simulation compared to the calibrated results. Similar 

analysis on the 2001 simulation shows similar trends. The 

most important feature of this portion of the sensitivity 

analysis is the range of head simulated by the model as the 

parameters are varied. The sensitivity to hydraulic conductivity parameter changes at monitoring wells G-2, G-7, G13, G-33, and GLTO are shown in figure 34 and 34a. Note 

that the model responds differently in different locations to 

changes in hydraulic conductivity of the bedrock units. For 

example, a change in the hydraulic conductivity of the Salina unit causes an increase in hydraulic head at G-33 of 6 

ft and a decrease at G-7 of 10 ft. For a factor-of-five change 

in all of these parameters, the resulting change in simulated 

hydraulic head is on the order of 10 ft. 

Water-level declines 

The WelLogic analysis and USGS monitoring-well data 

reveal regional ground-water-level declines, and model 

results and sensitivity analysis can be used to identify 

potential causes of these observed declines. In terms of 

the ground-water capture discussion, the declines may 

be caused by increased pumping or natural discharge, by 

decreased recharge to the ground-water system or by a combination of these factors. Effects of changes in natural discharge and recharge due to leakage changes were explored 

previously in the discussion of sensitivity analysis. 

57
	
 

 


6


6	 	6		6


6	


6	



 

 

#

!

!!

!#








































	




0 10 20 MILES 

0 10 20 KILOMETERS 

$1'(0., '.+.)*%$+304'5



/3$&0$-)+'1

"

	   

# !!



#	.-2.30*-2'04$+*1(''2

 #

.&'+$0'$





Figure 31. Simulated effect on 2001 hydraulic heads because of a 3.28-foot lowering of the 

water table in the glacial deposits across the study area (Monroe County, Michigan 

and surrounding area). 

58
	


 












 




	

	



 



 












 



 

	
 

	

 





 



  
 





 

)'(&"$!#*

)'(&"$!'$ 

%&"$!



)'(&"$!#*

)'(&"$!'$ 

%&"$!



  
 






Figure 32. Change in hydraulic head for 2001 simulation at (a) G2, (b) G7, 

from varying model parameters. 

59
	



	







	






,+/0"+0'&"%

&+&.")'&"%

(1&.

*-,/&%%&*"+%/


	

"


 









!

  










  










  










Figure 33. Change in flux from 2001 calibrated simulations because 

of changes in leakage from the glacial deposits in the study area for 

the (a) Lacustrine Clay, (b) Lacustrine Sand and (c) Moraine. 




	







	







 









!

,+/0"+0'&"%

&+&.")'&"%

(1&.

*-,/&%%&*"+%/


	

#




	







	







 









!

,+/0"+0'&"%

&+&.")'&"%

(1&.

*-,/&%%&*"+%/



	

$ $

 60
	
	


	



















	

"*(&#*#+"(

)))$%!)

,$+%#

$#%

&(#-&%*$%#)&*(&',

		







  






  
 





 

  
 





 

Figure 34. Change in hydraulic head for 1991 simulation at (a) G2, (b) G7, 

(c) G13 from varying model parameters. 

	


	



















	

	






"*(&#*#+"(

)))$%!)

,$+%#

$#%

&(#-&%*$%#)&*(&',

		



	


	



















	

	


"*(&#*#+"(

)))$%!)

,$+%#

$#%

&(#-&%*$%#)&*(&',

		







61
	
	


	



















	

	






 (&$!(!) &

'''"#'

*")#!

"!#

$&!+$#("#!'$(&$%*

		



  






  






	


	























 (&$!(!) &

'''"#'

*")#!

"!#

$&!+$#("#!'$(&$%*

		



Figure 34a. Change in hydraulic head for 1991 simulation at (d) G33, (e) GLTO, 

from varying model parameters. 

 62
	












	













 




 $& " %

&# %

#( " %

  " %

  " %

'!)	

 $& " %


&# %

&# %

#( " %

)

Figure 35. Drawdown near Hanson Quarry and radius of influence line. 

63
	
The simulation results indicate that the effect of Lake 

Erie levels on a regional decline in ground-water levels 

appears to be small. Low rainfall or drought may affect 

the ground-water system by lowering the water-table 

elevation in the glacial deposits. The effect of this 

lowered water table, however, should result in greater 

changes in the water levels in south-central Monroe 

County. Neither the USGS monitoring well data or the 

analysis of the WelLogic ground-water-level information support a lowered water table in the glacial deposits 

as the mechanism leading to widespread bedrock aquifer 

water-level declines. In addition, geochemical analysis 

of the system indicates that the ground water in the bedrock aquifer is not recharged to a great extent by recent 

rainfall indicating that short-term changes in rainfall 

would not produce the observed declines. 

Simulation results indicate that the effect of reducing the hydraulic conductance of glacial deposits and 

thereby reducing the leakage to the bedrock aquifer is 

greater than the effect of changing Lake Erie level or the 

decreased water-table elevation in the glacial deposits. A 

decrease in the hydraulic conductance of glacial deposits 

may be a result of land-use change. This effect, however, is smaller than the observed regional declines and 

may be ascertained through the sensitivity results that 

examined the conductances of the general-head boundary. An order of magnitude reduction in the capacity of 

the glacial deposits designated as moraines to transmit 

water to the bedrock aquifer decreased the general-head 

boundary flux by 5 Mgal/d or less and resulted in a 

change in water level of 6 ft at monitoring well G-7 and 

3 ft at G-2 (fig. 32). The decline at GLTO also was 3 ft. 

Land-use change as a contributing factor to the observed 

declines cannot be discounted by the simulation results; 

however, the simulation results do not support this factor 

as the sole cause for the observed ground-water declines. 

Simulation results indicate that the effect of increased 

ground-water withdrawals on a regional decline in 

ground-water levels is significant. The area of declines 

is the northern portion of Monroe County based on the 

WelLogic analysis and USGS monitoring wells (fig. 

13b). Based on the simulation results, the increase in 

total ground-water use can explain most of the observed 

ground-water-level decline. As discussed previously, 

the majority of the ground-water use in the region is for 

quarry dewatering. The numerical model can be used to 

illustrate the relative effects of increased quarry dewatering, irrigation, and self-supplied domestic, municipal, 

and industrial use. 

The relative effect of increased self-supplied domestic, municipal, and industrial use, and agricultural and 

golf-course irrigation can be illustrated by considering 

the results of a simulation where the simulated quarries 

from 1991 are used with the remaining conditions for the 

2001 simulation. The maximum decline in simulated water 

level at a USGS monitoring well was 3.2 ft at G-29. The 

average simulated drawdown for all of the USGS monitoring wells from the 1991 simulation was 1.6 ft. The increased withdrawals for self-supplied domestic, municipal, 

and industrial use, agricultural irrigation, and golf-course 

irrigation contribute to the regional decline, but do not 

explain much of it. Note that increased pumping for any of 

these uses potentially can have a large site-specific effect. 

For example, the continuous record of water level for monitoring well G-3 (fig. A3) indicates local pumping. The measured water level decreases rapidly and then recovers more 

slowly to its previous elevation consistent with a nearby 

well intermittently pumping from the bedrock aquifer. 

The effect of quarry dewatering can be considered 

through two analyses. The first is classic dewatering analysis. Simulation results (fig. 29, for example), clearly show 

localized drawdown in the vicinity of active quarries. These 

“cones of depression” are superimposed on the regional 

hydraulic surface. To illustrate the cone of depression from 

an active quarry in more detail, monitoring-well data from 

USGS well G-17 and observation wells operated by Hanson 

Aggregates (J. Stoll, Hanson Aggregates, written commun., 

2002) are shown in a distance-drawdown curve (fig. 35). 

From this analysis, the hypothetical “radius of influence” 

for a well is estimated by extending a straight-line through 

the data until it intersects the axis of zero drawdown. 

Implicit in this analysis is that the drawdowns plotted on 

the figure all result only from the dewatering at the facility. 

This assumption may be violated for the wells furthest from 

the quarry as they may show regional declines. Violation of 

the assumption, however, will increase the radius of influence for the quarry and does not change the conclusion of 

this evaluation. For this quarry, the distance at which little 

impact on nearby water levels is expected is on the order of 

1 mi. This analysis, however, does not account for regional 

effects or assess the capture of the ground-water system. 

On the regional scale, the relation between the radius 

of influence and regional effect must be evaluated. Alley 

and Schefter (1987) and Alley and others (1999) discuss 

the “egg carton” and “bathtub” conceptual models to frame 

the discussion of water-level declines and ground-water 

management for the High Plains aquifer. These conceptual models are useful analogies for Monroe County. The 

“bathtub” model proposes that any withdrawal from the 

ground-water system lowers the water level for the entire 

system instantaneously. Thus, any pumping in the aquifer is immediately noticed throughout the ground-water 

system. Resistance to ground-water flow, however, makes 

this an inappropriate model for water management. Pumping ground water can induce local drawdowns such as the 

cone of depression shown in figure 29, and ground-water 

 64
	
withdrawals do not instantaneously and uniformly lower 

regional water levels from the point of the withdrawal to 

the hydraulic boundaries of the system. The inadequacy of 

the “bathtub” model leads to the conceptual model of an 

“egg carton”, where individuals are not seriously effected 

by nearby pumps because of the local nature of the cone of 

depression. Alley and Schefter (1987) demonstrate that the 

“egg carton” model also is not appropriate for water management for the High Plains aquifer. The cumulative effects 

of many wells interact to generate regional drawdowns. The 

actual situation lies between these two extreme analogies: 

pumping leads to both localized drawdown and contributes 

to regional effects (Alley and others, 1999). The situation 

in Monroe County is similar to the High Plains aquifer 

analysis in that large-scale withdrawals at quarries cause 

both local cones of depression and contribute to the regional 

decline. 

Dewatering at individual quarries creates small cones of 

depression, approximately 1 mi in radius, but the withdrawals are part of the overall demand causing the observed 

regional decline. The depth of dewatering is controlled by 

the elevation of the quarry sumps in the vicinity of the quarries and by proximity to sources of ground-water capture in 

the remainder of the area. Simulation results and sensitivity analysis suggest that if regional demands were held to 

2001 levels, water levels would stabilize near the observed 

elevation. Note that London Aggregates in London Township, Monroe County stopped pumping in December 2003 

under a consent agreement with the U.S. Environmental 

Protection Agency (PIRGIM v. Wolcottville, 2002; United 

States v. Wolcottville, 2002). At the time of the shutdown, 

this quarry was the largest single ground-water user in 

Monroe County based on reported discharges from 8 to 10 

Mgal/d. The observed water level at monitoring well G-7 

recovered approximately 10 ft in September 2003. The 

model underestimated the withdrawal from this quarry, but 

simulation without pumping at London Aggregates 

shows some regional recovery under steady-state conditions 

(fig. 36). This simulation again illustrates both the local nature of the cone of depression caused by a large withdrawal 

and the regional effect of large withdrawals on the system. 

The greatest recovery shown in the figure is at the quarry 

as expected, and much of the recovery occurs within a mile 

of the quarry. This is the recovery of the short-range cone 

of depression. More regional recovery also is predicted, 

however, for steady-state conditions. Recovery between 1 

and 6 ft is predicted outside the cone-of-depression, and this 

recovery reflects the regional effect of quarry dewatering. 

The predicted recovery if quarry withdrawals are 

removed and the remaining 2001 stresses applied to the 

model is illustrated in figure 37. The recovery contours 

show more than 10 ft of recovery in water levels for most of 

the model area. Recoveries greater than 30 ft are simulated 

in parts of Monroe County. In the simulations of water-level 

recovery, the hydraulic properties of the bedrock aquifer are 

assumed to have not changed because of dewatering conditions. Because without quarries the withdrawals are less 

than the calibrated 1991 values, the model simulates water 

levels above 1991 levels in parts of the model area. As 

noted above, however, the ground-water-capture analysis 

must consider all ground-water use. If other uses increase, 

the ground-water level will decline again, until sufficient 

capture is produced by the ground-water system to balance 

the new demands. 

Model Limitations 

There are limitations to the model and analysis presented 

herein. As discussed previously, despite the widespread use 

of analysis techniques based on flow through porous media 

for fractured rock systems, local flow conditions in the 

ground-water system will be affected by fractures and conditions may be locally different than the averaged condition 

simulated with the regional model. In the same way, local 

heterogeneities in hydrogeologic properties of the bedrock 

deposits and in the bedrock/glacial interface could not be 

considered in the regional model. Finally, karst features 

in southwestern Monroe County are not simulated by the 

model. The effect of karst features on the regional system 

was not assessed other than to note that the model produces 

results consistent with observed values in the remainder of 

Monroe County. 

The simulated ground-water capture depends on the 

ground-water demands placed on the system. Errors in water-use estimates will affect the results and major changes 

in water-use estimates would necessitate recalibration of the 

model. 

The configuration of the moraine/bedrock aquifer boundary is not well known. Large-scale maps were used to create 

the basemap for the model, and the area where moraine or 

more conductive deposits overlie the Dundee Formation to 

the west and northwest of Monroe County could be different than used in the simulation. The effect of a smaller 

recharge area to the regional system was illustrated with 

the sensitivity analysis by decreasing the conductance of 

the moraine general-head boundary parameter. A larger 

recharge area could provide more water to help the system 

achieve steady-state. The larger recharge area may be less 

sensitive to land-use changes, because these changes affect 

the local scale and the influence would be buffered by a 

larger unchanged area. 

Leakage between the glacial deposits and bedrock aquifer is an important factor in the regional water budget. The 

model simplifies the system by treating the glacial deposits 

as a boundary condition to the bedrock aquifer. The flux 

also is potentially maximized by the use of the general-head 

boundary that increases the flux as water levels decline in 

65
	
 

 

.

	. 	.	.

.

.








 









 



























 





	




0 10 20 MILES 

0 10 20 KILOMETERS 








 



 










('+(,)%'+#)-!&%*$##+

("#&!)#!









 

Figure 36. Simulated recovery from 2001 conditions if quarry discharges are removed for 

the study area (Monroe County, Michigan and surrounding area). 

66
	
 

 

.

	. 	.	.

.

.








 









 












	











	

0 10 20 MILES 

0 10 20 KILOMETERS 








 



 








 


('+(,)%'+#)-!&%*$##+

("#&!)#!









 

Figure 37. Simulated recovery for study area (Monroe County, Michigan and surrounding area) 

under 2001 steady-state conditions if London Quarry discharge is removed. 

67
	
the bedrock aquifer regardless of whether this unit is locally confined or unconfined. A more rigorous approach 

would be to explicitly simulate water flow in the glacial 

deposits. This approach also could include a transient 

analysis so time-varying conditions in both the bedrock 

aquifer and glacial deposits could be considered. 

A consistent model was sought by using predevelopment and 1991 conditions to constrain model performance. An improved simulation may result if 1991 to 

2003 information is used to develop a transient model. 

This simulation could help estimate the time to reach a 

new steady-state condition given changes in the imposed 

demands. This simulation may not improve the ability 

to identify the causes of ground-water declines beyond 

the steady-state models, but it would provide additional 

insight into aquifer properties and could produce a more 

well-calibrated model. 

SUMMARY AND CONCLUSIONS 

The U.S. Geological Survey (USGS), in cooperation 

with the Michigan Department of Environmental Quality 

(MDEQ), began a study in 2002 to study the hydrogeology and identify the cause or causes of observed widespread ground-water-level declines in the bedrock aquifer in Monroe County, Michigan. The study area focuses 

on Monroe County, but includes portions of neighboring 

counties in Michigan and Ohio. Previous reports provide 

necessary background regarding water use, water chemistry, and hydrogeology. The present report analyzes the 

hydrologic data in more detail than previous work and 

uses a numerical ground-water-flow model to investigate 

the causes of ground-water-level declines. 

The main focus of the study is the bedrock aquifer 

composed of five Silurian-Devonian bedrock units. 

These rocks are fractured, exhibit karst features in some 

areas, and are locally heterogeneous with respect to 

hydrogeologic properties. The overlying glacial deposits 

are important in that they control leakage to the bedrock 

aquifer, and leakage is important to the response of the 

bedrock ground-water system to changes in pumping. In 

addition to the 32 bedrock monitoring wells and 1 glacial 

monitoring well installed for an earlier study, the MDEQ 

WelLogic database of water-well logs was used extensively in this study to both estimate hydrogeologic properties of the glacial deposits and to document water-level 

changes. The USGS monitoring wells were monitored 

from 1991 through 2003 and provide documentation of 

the water-level declines in the bedrock aquifer across the 

county. 

Ground-water levels declined in many of the monitoring wells from 1991 to 2001. Water levels in 11 monitoring wells declined more than 10 ft, and the water level in 6 

wells declined more than 20 ft. The general downward trend 

of water levels since 1991 is evident for all but 2 wells, one 

of which is completed in glacial deposits. Water levels in 10 

wells, all in northern Monroe County, increased in 2003, 

and some of this increase can be attributed to seasonal fluctuations in water levels. 

Estimated ground-water use in Monroe County increased 

from approximately 20 Mgal/d in 1991 to nearly 30 Mgal/d 

in 2001. The percentage of the total used for public supply, 

self supplied, industrial, irrigation, and quarry dewatering in 

1991 and 2001 is about the same. The major ground-water 

use is attributed to quarry dewatering. In 1991, 80 percent 

of the total was from quarry dewatering. In 2001, 75 percent of the total was from quarry dewatering. 

The conceptual model of the study area uses an equivalent porous media approach to simulate ground-water flow 

in the bedrock aquifer. The bedrock aquifer is simulated as 

10 layers—2 layers for each geologic unit. Glacial deposits 

are not simulated explicitly. Rather, these units are simulated as an upper boundary condition to the bedrock aquifer. 

The bedrock aquifer can both receive water from the 

overlying glacial deposits and transmit water to the glacial 

deposits. Shale units overlying the bedrock aquifer in the 

west and northwestern portions of the study area are considered to be no-flow upper boundaries for the model. The 

lower boundary condition for the bedrock aquifer also is a 

no-flow boundary. Lateral boundaries were no-flow across 

the Detroit and Maumee Rivers and the western boundary 

of the study area, where the ground water in the bedrock is 

saline. Flow to the Maumee and Detroit Rivers, however, 

is simulated in the model. The remaining lateral boundaries are constant-head boundaries in Lake Erie and on the 

southwestern model boundary. Discharge from the bedrock 

aquifer includes leakage to the overlying glacial deposits. 

In addition, quarry dewatering; self-supplied domestic, 

municipal, and industrial water use; and irrigation water use 

were simulated in the model. 

Simulation results indicate that regional declines in 

ground-water levels are caused by increased ground-water 

demands. Results indicate that a simulated lower level of 

Lake Erie has little effect on regional ground-water levels. 

Similarly, results indicate that a simulated decreased leakage from the glacial deposits to the bedrock aquifer, consistent with land-use changes, does not explain the observed 

declines in regional ground-water levels in the bedrock 

aquifer. 

The largest ground-water withdrawal in the region was 

quarry dewatering operations. Increases in other uses contribute to the observed decline, but cannot account for the 

total observed regional decline. Dewatering at individual 

quarries creates limited cones of depression, approximately 

1 mi in radius, but the withdrawals are part of the overall 

 68
	
regional demand causing the observed decline. The 

depth of dewatering is controlled by the elevation of 

the quarry sumps in the vicinity of the quarries and by 

proximity to sources of ground-water capture in the 

remainder of the area. 

Application of model results is limited by the assumptions inherent in numerical models of ground-water flow. The assumption of porous media flow in the 

model limits its application in local areas where heterogeneities in hydrogeologic properties dominate the 

response of ground-water levels to stresses. Leakage 

between glacial deposits and the underlying bedrock 

aquifer is an important factor in the model simulations 

and is simplified in the numerical ground-water-flow 

model. Whereas regional patterns of leakage are sufficiently accurate for simulation purposes, direct measurements of leakage and glacial deposit conductances 

are necessary to calculate leakage in local areas. 

Ground-water capture controls the magnitude of 

water-level declines when new demands are introduced 

to the ground-water system. Simulation results were 

used to illustrate ground-water capture for the regional 

model. Prior to 1991, ground-water demands appear to 

have been balanced by interception of natural discharge from the bedrock aquifer to the glacial deposits 

in eastern Monroe County. At some time, demands in 

the region exceeded the amount of water that could be 

readily captured from natural discharge, and groundwater levels declined. Observations from 1991 until 

2003 document this regional decline. Simulation 

results indicate, if demands were held constant to 2001 

levels, the decline would stop when the combination of 

decreased discharge and additional recharge balances 

the demand. Limits to future ground-water withdrawals in the region should be assessed on a regional basis 

because analysis relying on local drawdown does not 

consider regional effects. Decisions regarding future 

ground-water development also must be made with recognition that dispersed withdrawals, while not creating 

large local drawdowns, still affect the regional groundwater system. 

REFERENCES CITED 

Allen, W.B., 1977, Flowing wells in Michigan, 

1974: Michigan Geological Survey Water 

Information Series Report 2, 27 p. 

Alley, W.M. and Schefter, J.E., 1987, External

 effects of irrigators’ pumping decisions, High

 Plains Aquifer: Water Resources Research, 

 v. 28, no. 7, p. 1123-1130. 

Alley, W.M., Reilly, T. M., and Franke, O.L., 1999, 

Sustainability of ground-water resources: U.S. 

 Geological Survey Circular 1186, 79 p. 

Anderson, M. P. and Woessner, W. W., 1992, 

Applied groundwater modeling - Simulation of 

flow and advective transport: San Diego, Calif., 

Academic Press, 381 p. 

Argus Holdings Limited, 2002, Argus-ONE (Open 

Numerical Environments): Herzelia, Israel, 

Computer Software. 

Berry, R.M., and Bormanis, V., 1970, Plane 

coordinate survey system for the Great Lakes based 

on the Hotine Skew Orthomorphic Projection: U.S. 

 Lake Survey Miscellaneous Paper, p. 70-4: Detroit, 

 Michigan, U.S. Lake Survey District, U.S. Army 

Corps of Engineers, 16 p. 

Blumer, S.P., Nurnberger, F.V., Hamilton, D.A., 

 and Sorrell, R.C., 1991, Michigan floods and

 droughts, in National Water Summary 1988-1989: 

U.S. Geological Survey Water-Supply Paper 2375, 

p. 335-344. 

Bredehoeft, J.D., Papadopulos, S.S., and Cooper 

 H.H., Jr., 1982, The water-budget myth: Scientific

 Basis of Water Resources Management, Studies in 

 Geophysics, Washington, D.C., National Academy 

Press, p. 51-57. 

Bredehoeft, J.D., 2002, The water budget myth

 revisited: Why hydrologists model: Ground Water, 

 v. 30, no. 4, p. 340-345. 

Breen, K.J., 1989, Potentiometric-surface map 

of the carbonate aquifer in Silurian and Devonian 

 rocks, Lucas, Sandusky, and Wood Counties, 

northwestern Ohio, July 1986: U.S. Geological 

 Survey Water-Resources Investigations Report 

88-4144, 1 sheet, scale 1:126,720. 

Breen, K.J., and Dumouchelle, D.H., 1991, 

Geohydrology and quality of water in aquifers in 

 Lucas, Sandusky, and Wood Counties, 

northwestern Ohio: U.S. Geological Survey WaterResources Investigations Report 91-4024, 234 p. 

Bugliosi, E.F., 1999, The midwestern basins and 

arches regional aquifer system in parts of Indiana, 

Ohio, Michigan, and Illinois - Summary: U.S. 

Geological Survey Professional Paper 1423-A, 46 p. 

69
	
Davis, D.R., and Rasmussen, T.C., 1993, A

 comparison of linear regression with Clark’s Method

 for estimating barometric efficiency of confined 

aquifers: Water Resources Research, v. 29, no. 6, p. 

1849-1854. 

Driscoll, F.G., 1986, Groundwater and wells, 

second edition: St. Paul, Minnesota, Johnson 

Division, 1089 p. 

ESRI, 2002a, ArcView GIS 3.3: Redlands, Calif., 

Computer Software. 

ESRI, 2002b, ArcMap 8.2: Redlands, Calif., 

Computer Software. 

Farrand, W.R., and Bell, D.L., 1982, 

 Quaternary Geology of Southern Michigan: Ann 

Arbor, Michigan, Department of Geological 

Sciences, University of Michigan, scale 1:500,000 

(electronic version available through State of 

Michigan, Center for Geographic Information, 

 http://www.michigan.gov/cgi). 

Fetter, C.W., 2001, Applied hydrogeology, fourth 

 edition: Upper Saddle River, New Jersey, 

Prentice-Hall, 598 p. 

Gilbert, R.O., 1987, Statistical methods for 

 environmental pollution monitoring: New York, 

Van Nostrand Reinhold Company, 320 p. 

Gillespie, J.L., and Dumouchelle, D.H., 1989, 

Ground-water flow and quality near the upper Great 

Lakes connecting channels, Michigan: U.S. 

 Geological Survey Water-Resources Investigations 

Report 88-4232, 82 p. 

Harbaugh, A.W., Banta, E.R., Hill, M.C., and 

 McDonald, M.G., 2000, MODFLOW-2000, the

 U.S. Geological Survey modular ground-water 

model - User guide to modularization concepts 

 and the ground-water flow process: U.S. 

Geological Survey Open-File Report 00-92, 

121 p.
	

Hill, M.C., Banta, E.R., Harbaugh, A.W., and 

Anderman, E.R., 2000, MODFLOW-2000, the 

U.S. Geological Survey modular ground-water 

model - User guide to the observation, 

 sensitivity, and parameter-estimation processes 

and three post-processing programs: U.S. 

Geological Survey Open-File Report 00-184, 209 p.
	

Hoaglund, J.R., III, Huffman, G.C., and 

Grannemann, N.G., 2002, Michigan Basin 

 regional ground water flow discharge to three 

 Great Lakes: Ground Water, v. 40, no. 4, 

p. 390-406. 

Holtschlag, D.J., 1996, A generalized estimate of 

 ground-water-recharge rates in the lower 

peninsula of Michigan: U.S. Geological Survey 

Open-File Report 96-593, 37 p. 

Holtschlag, D.J.and Koschik, J.A., 2003, An 

 acoustic doppler current profiler survey of flow 

 velocities in Detroit River, a Connecting 

Channel of the Great Lakes: U.S. Geological 

Survey Open-File Report 03-219, date posted: 

August 12, 2003, at URL http://

 mi.water.usgs.gov/pubs/OF/OF03-219/

 index.php 

Indiana Geological Survey, 2002, BEDROCK_

 GEOL_MM48_IN: Bedrock geology of Indiana 

 (1:500,000 polygon shapefile) accessed June 11, 

 2003, at URL http://igs.indiana.edu/arcims/

 statewide/download.html#Geology 

Kendall, M.G., 1955, Rank correlation methods 

 (2nd ed.): London, Charles Griffin and Company, 

Ltd., 196 p. 

Leverett, F., and Taylor, F.B., 1915, The 

Pleistocene of Indiana and Michigan and the history

 of the Great Lakes: U.S. Geological Survey 

Monograph, 53, 529 p. 

McIntosh, J.C., Walter, L.M., and Martini, A.M., 

 2002, Pleistocene recharge to midcontinent basins:

 Effects of salinity structure and microbial gas 

generation: Geochemica et Cosmochimica Acta,

 v. 66, no. 10, p. 1681-1780. 

MathSoft, 2000, S-Plus 2000: now maintained 

 by Insightful Corporation, Seattle, Washington, 

Computer Software. 

Mehl, S.W., and Hill, M.C., 2001, MODFLOW-

 2000, The U.S. Geological Survey modular groundwater model - User guide to the link-AMG (LMG) 

package for solving matrix equations using an 

algebraic multigrid solver: U.S. Geological Survey

 Open-File Report 01-77, 33 p. 

 70
	
Michigan Department of Environmental Quality, 

 2003, WelLogic, Statewide Ground Water 

Database (SGWD): Lansing, Michigan, Michigan 

 Department of Environmental Quality, 

(continuously updated), last accessed May 16, 2003, 

at URL http://www.mcgi.state.mi.us/mgdl

 ?rel=thext&action=thmname&cid=2&cat=Drinking

 +Water+Wells 

Milstein, R.L., comp., 1987, Bedrock geology of 

 southern Michigan: Michigan Geological Survey, 

scale 1:500,000 (electronic version available

 through State of Michigan, Center for Geographic 

 Information, http://www.michigan.gov/cgi). 

Mozola, A.J., 1970, Geology for environmental

 planning in Monroe County, Michigan: Michigan 

Department of Natural Resources, Report of 

Investigation 13, 34 p. 

National Oceanic and Atmospheric Administration 

(NOAA), 2003, Center for Operational 

Oceanographic Products and Services (CO-OPS), 

 National Water Level Observation Network 

(NWLON) database (continuously updated), 

Fermi Power Plant Station 9063090: Chesapeake, 

Virginia, NOAA 

National Ocean Service, last accessed October 24, 

 2003, at URL http://co-ops.nos.noaa.gov/data_

 retrieve.shtml?input_code=100111111vgl 

National Research Council, 1990, Ground water 

 models - Scientific and regulatory applications: 

Washington, D.C., National Academy Press, 303 p. 

Nicholas, J.R., Blumer, S.P., and McGowan, R.M., 

2002, Comparison of hydrologic data from Monroe 

 County, Michigan, 1991-2001: U.S. Geological 

Survey Open-File Report 01-498, 44 p. 

Nicholas, J.R., Rowe, G.L., and Brannen, J.R., 1996, 

 Hydrology, water quality, and effects of drought in 

 Monroe County, Michigan: U.S. Geological Survey 

Open-File Report 94-4161, 169 p. 

Ohio Department of Natural Resources, 2000a, 

 Digital Bedrock Aquifer Map: Ohio Department of 

 Natural Resources, Division of Water, accessed 

May 16, 2002, at URL http://www.dnr.state.oh.us/

 water/samp/default.htm 

Ohio Department of Natural Resources, 2000b, 

 Digital Unconsolidated Aquifer Map: Ohio 

Department of Natural Resources, Division 

 of Water, accessed September 20, 2002 at 

 http://www.dnr.state.oh.us/water/samp/default.htm 

Parkhurst, D.L., and Appelo, C.A.J., 1999, User’s 

 guide to PHREEQC (version2)- A computer 

program for speciation, batch-reaction, onedimensional transport, and inverse geochemical 

calculations: U.S. Geological Survey WaterResources Investigations Report 99-4259, 312 p. 

PIRGIM Public Interest Lobby, William Tobler, 

Wendy Tobler, Billie Borso, and Robert Morawski 

 v. Wolcottville Sand and Gravel Corporation

 d/b/a London Aggregates, 2002, Civ. No. 98-73730 

 DT, (U.S. District Court, Eastern District of 

Michigan, Southern Division). 

Rantz, S.E. and others, 1982, Measurement and 

 computation of streamflow: U.S. Geological 

 SurveyWater-Supply Paper 2175, 631 p. 

Robbins, E.I., Rybicki, R.A., Hockey, D., Fuller, 

 J.A., Indrick, S.S., 1994, Wetlands of modern and 

 ancestral lakes Erie and St. Clair, Michigan, Ohio, 

 Indiana, Pennsylvania, and New York, U.S.A., and 

Ontario, Canada: U.S. Geological Survey 

Miscellaneous Investigations Series I-2451, 

1 sheet, scale 1:500,000. 

Rutledge, A.T., 1998, Computer programs for 

 describing the recession of ground-water discharge

 and for estimating mean ground-water recharge 

 and discharge from streamflow records - update: 

U.S. Geological Survey Water-Resources 

Investigations Report 98-4148, 43 p.
	

Rutledge, A.T., 2000, Considerations for use of the 

 RORA program to estimate ground-water recharge

 from streamflow records: U.S. Geological Survey

 Open-File Report 00-156, 44 p. 

Sherzer, W.H., 1900, Geological report on Monroe 

 County, Michigan: Geological Survey of Michigan,

 v. VII, part I. 

Theis, C.V., 1940, The source of water derived from

 wells: Civil Engineering, v. 10, no. 5, p. 277-280. 

Twenter, F.R., 1975, Southeastern Michigan 

 water-resources study: U.S. Geological Survey 

71
	
 Open-File Report, 143 p.
	

United States v. Wolcottville Sand and Gravel 

 Corporation d/b/a London Aggregates, 2002, 

 Civ. no. 98-74192, (U.S. District Court, Eastern 

District of Michigan, Southern Division). 

U.S. Army Corps of Engineers, 2003, Great Lakes 

 historic data: Detroit, Michigan, U.S. Army Corps

 of Engineers, Detroit District, accessed October 

 24, 2003, at URL http://www.lre.usace.army.mjl/

 index.cfm?chn_id=1438 

U.S. Census Bureau, 2001, Census 2000 Summary

 File 1, Michigan: U.S. Census Bureau. 

U.S. Department of Agriculture, 1999, Census of 

Agriculture, Volume 1. Geographic Area Studies, 

Part 22, Michigan, State and County Data: 

 National Agriculture Statistics Service AC97-A-22. 

U.S. Department of Commerce, 1987, Census of 

Agriculture, Volume 1. Geographic Area Studies, 

Part 22, Michigan, State and County Data: 

 Bureau of the Census AC87-A-22. 

U.S. Geological Survey, 2003, Water use in the 

United States, accessed February 18, 2003 at 

 http://water.usgs.gov/watuse/ 

Venables, W.N., and Ripley, B.D., 1994, Modern 

applied statistics with S-Plus: New York, 

 Springer-Verlag, 462 p. 

Westjohn, D.B., and Weaver, T.L., 1998, 

Hydrologic framework of the Michigan Basin 

regional aquifer system: U.S. Geological Survey 

Professional Paper 1418, 47 p. 

Winston, R.B., 2000, Graphical User Interface for 

 MODFLOW, Version 4: U.S. Geological Survey

 Open-File Report 00-315, 34 p. 

 72
Appendix A 

Water-Level Data 

Ground-water wells originally drilled in 1991 for the study done by Nicholas and 

others (1996) were monitored by the U.S. Geological Survey (USGS) through August 

1993. Measurements were taken by Monroe County from this time until August 2001 

when USGS began monitoring for the present study until September 2003. Eleven of the 

33 wells were electronically monitored at 15-minute increments during this study, and 

21 of the wells were manually measured at approximately 6-week intervals. One well, 

G31, was unavailable for measurement during this study. Well GLTO (figure 13) located 

in Petersburg State Game Area has a record dating back to 1978, and water levels from 

this well were used in the study. 

U.S. Geological Survey Observation Wells 

G-01 Point Mouillee, Berlin Township 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

550 

545 

540 

535 

530 

525 

520 

515 

510 

No data 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County Bottom of Well 525.35 ft 

Figure A1. Ground-water levels for well G-1 Berlin Township, Monroe County, 

Michigan. 

A-1 
600 

G-02 Berlin Township Park, Berlin Township 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

575 

570 

565 

560 

555 

550 

545 

540 

535 

No data 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County Bottom of Well 540.41 ft 

Figure A2. Ground-water levels for well G-2 Berlin Township, Monroe County, 

Michigan. 

G-03 Evergreen Cemetery, Ash Township 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 595 

590 

585 

580 

575 

570 

565 

560 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A3. Ground-water levels for well G-3 Ash Township, Monroe County, 

Michigan. 

A-2 
G-04 Carleton Cemetery, Ash Township 

570 

575 

580 

585 

590 

595 

600 

605 

610 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A4. Ground-water levels for well G-4 Ash Township, Monroe County, 

Michigan. 

G-05 Colf Road, Exeter Township 

620
 

615
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 610 

605 

600 

595 

590 

585 

580 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A5. Ground-water levels for well G-5 Exeter Township, Monroe County, 

Michigan. 

A-3 
G-06 Doty Road, Exeter Township 

580 

585 

590 

595 

600 

605 

610 

615 

620 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS
 Monroe County 

Figure A6. Ground-water levels for well G-6 Exeter Township, Monroe County, 

Michigan. 

G-07 London Township Hall, London Township 

620
 

615
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

585 

590 

595 

600 

605 

610 

No data 

580
 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A7. Ground-water levels for well G-7 London Township, Monroe County, 

Michigan. 

A-4
 
G-08 London Township Cemetery, London Township 

575 

580 

585 

590 

595 

600 

605 

610 

615 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY:
 USGS Monroe County 

Figure A8. Ground-water levels for well G-8 London Township, Monroe County, 

Michigan. 

G-09 Couper Road, Milan Township 

620
 

615
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

585 

590 

595 

600 

605 

610 

No data 

580
 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A9. Ground-water levels for well G-9 Milan Township, Monroe County, 

Michigan. 

A-5
 
G-10 Rice Cemetery, Milan Township 

670 

675 

680 

685 

690 

695 

700 

705 

710 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY:
 USGS Monroe County 

Figure A10. Ground-water levels for well G-10 Milan Township, Monroe County, 

Michigan. 

G-11 Maple Grove Cemetery, Dundee Township 

630
 

625
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

595 

600 

605 

610 

615 

620 

No data 

590
 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A11. Ground-water levels for well G-11 Dundee Township, Monroe County, 

Michigan. 

A-6
 
G-12 Oak Grove Cemetery, Dundee Township 

610 

615 

620 

625 

630 

635 

640 

645 

650 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS
 Monroe County 

Figure A12. Ground-water levels for well G-12 Dundee Township, Monroe County, 

Michigan. 

G-13 Rath Cemetery, Raisinville Township 

650
 

645
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

615 

620 

625 

630 

635 

640 

No data 

610
 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS 

Figure A13. Ground-water levels for well G-13 Raisinville Township, Monroe County, 

Michigan. 

A-7
 
G-14 McIntyre Cemetery, Raisinville Township 

590 

595 

600 

605 

610 

615 

620 

625 

630 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A14. Ground-water levels for well G-14 Raisinville Township, Monroe County, 

Michigan. 

G-15 Frenchtown Fire Station, Frenchtown Township 

610
 

605
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 600 

595 

590 

585 

580 

575 

570 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A15. Ground-water levels for well G-15 Frenchtown Township, Monroe County, 

Michigan. 

A-8 
G-16 Frenchtown Township Park, Frenchtown Township 

560 

565 

570 

575 

580 

585 

590 

595 

600 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A16. Ground-water levels for well G-16 Frenchtown Township, Monroe County, 

Michigan. 

Note the change G-17 Monroe Township Hall, Monroe Township
 in vertical scale 

610
 

600
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 590 

580 

570 

560 

550 

540 

530 

520 

510 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A17. Ground-water levels for well G-17 Monroe Township, Monroe County, 

Michigan. 

A-9 
G-18 LaSalle Township Cemetery, LaSalle Township 

570 

575 

580 

585 

590 

595 

600 

605 

610 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A18. Ground-water levels for well G-18 LaSalle Township, Monroe County, 

Michigan. 

G-19 Ida Township Hall, Ida Township 

650
 

645
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 640 

635 

630 

625 

620 

615 

610 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A19. Ground-water levels for well G-19 Ida Township, Monroe County, 

Michigan. 

A-10 
G-20 Lulu Road Cemetery, Ida Township 

610 

615 

620 

625 

630 

635 

640 

645 

650 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY:
 USGS Monroe County 

Figure A20. Ground-water levels for well G-20 Ida Township, Monroe County, 

Michigan. 

G-21 Pleasantview Cemetery, Summerfield Township 

640
 

635
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

605 

610 

615 

620 

625 

630 

No data 

600
 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A21. Ground-water levels for well G-21 Summerfield Township, Monroe County, 

Michigan. 

A-11
 
G-22 Petersburg Game Area, Summerfield Township 

615 

620 

625 

630 

635 

640 

645 

650 

655 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A22. Ground-water levels for well G-22 Summerfield Township, Monroe County, 

Michigan. 

G-23 Petersburg Game Area, Summerfield Township 

655
 

650
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 645 

640 

635 

630 

625 

620 

615 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A23. Ground-water levels for well G-23 Summerfield Township, Monroe County, 

Michigan. 

A-12 
G-24 Petersburg Game Area, Summerfield Township 

615 

620 

625 

630 

635 

640 

645 

650 

655 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A24. Ground-water levels for well G-24 Summerfield Township, Monroe County, 

Michigan. 

G-25 Petersburg Game Area, Summerfield Township 

655
 

650
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 645 

640 

635 

630 

625 

620 

615 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A25. Ground-water levels for well G-25 Summerfield Township, Monroe County, 

Michigan. 

A-13 
G-26 Ida Center Road, Summerfield Township 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

650 

645 

640 

635 

630 

625 

620 

615 

610 

WATER LEVEL MEASURED BY: USGS Monroe County Observer 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A26. Ground-water levels for well G-26 Summerfield Township, Monroe County, 

Michigan. 

G-27 Todd Road, Summerfield Township 

650
 

645
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

640 

635 

630 

625 

620 

615 

610 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A27. Ground-water levels for well G-27 Summerfield Township, Monroe County, 

Michigan. 

A-14 
655 

Note the change G-28 Lakeview Cemetery, Whiteford Township 

in vertical scale 

670
 

665
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

660 

655 

650 

645 

640 

635 

630 

625 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A28. Ground-water levels for well G-28 Whiteford Township, Monroe County, 

Michigan. 

G-29 Whiteford Union Cemetery, Bedford 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 650 

645 

640 

635 

630 

625 

620 

615 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A29. Ground-water levels for well G-29 Whiteford Township, Monroe County, 

Michigan. 

A-15 
G-30 Parmelee Park, Bedford Township 

630 

635 

640 

645 

650 

655 

660 

665 

670 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS
 Monroe County 

Figure A30. Ground-water levels for well G-30 Bedford Township, Monroe County, 

Michigan. 

G-31 Bedford Township Park, Bedford Township 

650
 

645
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

615 

620 

625 

630 

635 

640 

No data 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003
 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A31. Ground-water levels for well G-31 Bedford Township, Monroe County, 

Michigan. 

A-16
 

610 
G-32 Telegraph Road, Erie Township 

580 

585 

590 

595 

600 

605 

610 

615 

620 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

WATER LEVEL MEASURED BY: USGS Monroe County 

Figure A32. Ground-water levels for well G-32 Erie Township, Monroe County, 

Michigan. 

G-33 Erie Township Park, Erie Township 

590
 

585
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 580 

575 

570 

565 

560 

555 

550 

WATER LEVEL MEASURED BY: USGS Monroe County 

1991 1992 1993 1995 1996 1997 1999 2000 2001 2003 

Figure A33. Ground-water levels for well G-33 Erie Township, Monroe County, 

Michigan. 

A-17 
Landfill records from MDEQ 

Water-level measurements from landfill observation wells were obtained from the 

Michigan Department of Environmental Quality. Water-levels in bedrock wells were 

available from four landfills: Carlton Farms, Matlin Road, Rockwood Landfill, and Jefferson Smurfit. Rockwood Landfill records from 1980 predate the two nearby quarries, 

and the influence of the quarries can be seen in more recent measurements. Other landfills appear to match local trends observed in USGS observation wells (Carleton Farms 

and Matlin Road with G4 and Jefferson Smurfit with G16). 

A-18 
605 

Carleton Farms Landfill, Sumpter Township, Wayne County 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 600 

595 

590 

585 

580 

MW-09 

MW-16 

MW-28 

MW-29 

Well identifier 

1994 1995 1997 1998 1999 2001 2002 

Figure A34. Ground-water levels for observation wells at Carleton Farms Landfill, 

Monroe County, Michigan. 

Matlin Landfill, Ash Township 

591 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 

590 

589 

588 

587 

586 

585 

584 

1996 1997 1998 1999 2000 2001 2001 

MW-1 

MW-2 

MW-3 

MW-4R 

MW-5 

MW-6 

MW-7 

MW-10 

Well identifier 

Figure A35. Ground-water levels for observation wells at Matlin Landfill, 

Monroe County, Michigan. 

A-19 
584 

Jefferson Smurfit Landfill, Monroe Township 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 582 

580 

578 

576 

574 

572 

570 

1999 2000 2001 2002 

A02D 

A03D 

A04D 

A05U 

A06D 

A07U 

Well identifier 

Figure A36. Ground-water levels for observation wells at Jefferson Smurfit Landfill, 

Monroe County, Michigan. 

Rockwood Landfill, Berlin Township 

600
 

580
 

WATER LEVEL, IN FEET ABOVE SEA LEVEL 560 

540 

520 

500 

480 

460 

440 

420 

400 

1980 1983 1985 1988 1991 1994 1996 1999 2002 2005 

MW-102 MW-103 MW-104 MW-105 

MW-106 MW-107 MW-108 MW-109 

MW-110 MW-111 MW-112 MW-113 

MW-114S MW-115 MW-116 MW-117 

MW-118 MW-119 MW-120 MW-121 

P-2 P-3 P-1 P-4 

P-6 P-8 P-10 P-14 

P-16 P-18 P-20 1988 

Well identifier 

Figure A37. Ground-water levels for observation wells at Rockwood Landfill, 

Monroe County, Michigan. 

A- 20 
Appendix B 

Monroe County Statistics Summary 

Data Used 

Ground-water-level data summarized by Nicholas and others (2002) were used in this analysis. 

These data are presented in Appendix A of this report. All of the wells except G10 are open to the bedrock 

aquifer. G10 extends to 110 feet below the ground surface and is screened to glacial deposits approximately four feet above the glacial deposit/bedrock contact. 

Daily mean discharge, monthly mean discharge, annual means, and seven-day average low flow 

data for the River Raisin at three gaging stations were used in an analysis of surface-water trends. The 

sites and periods of record are: near Monroe in Monroe County (1937-2001), near Adrian in Lenawee 

County (1953 - 2001), near Manchester in Washtenaw County (1970-2001), and Otter Creek near LaSalle 

in Monroe County (1987-2001). 

Methods 

The index developed by Kendall to describe correlation is now referred to as the Kendall τ and is 

computed by determining examining the differences between every possible pair of observations in chronological order. If the difference between a pair is positive, Nc is incremented by one. If the difference 

is negative Nd is incremented by one. The total number of pairs is n(n-1)/2. τ is defined as, 

N – N

τ = ---------c

------------d----- n n( – 1) ⁄ 2

If the observations are monotonically increasing, then Nc will be equal to the total number of pairs 

and τ will be 1. If the observations are monotonically decreasing, τ will be -1. The algorithm used in SPLUS (Mathsoft, 2000) also allows for tied values. This rank test indicates where a positive (τ close to 1) 

or negative (τ close to -1) trend is present in the observations. A τ close to zero implies no trend is indicated by the data. In addition to the Kendall τ, the statistical significance of the trend is determined. For 

values of n larger than 40, τ has a normal distribution, and this property allows the critical level (p-value) 

to be determined for a statistical evaluation of the null hypothesis of the test that there is no trend supported. Large p-values imply that the null hypothesis cannot be rejected. 

The magnitude of the trend was computed using the Sen slope procedure. In this method, the slope 

for every pair in the ranked series is obtained, 

o – o i′ i Q = ---------------∀i′ > i 

t – t i′ i 

Where oi and ti are the values of the observation and the observation time at i. If there is only one 

observation per time period, which is the case for the data used in this study, then this evaluation yields 

n(n-1)/2 values of Q. These values are then put in rank order, and the Sen estimator of the slope is the 

median value of the ranked list. The results of this analysis are summarized in Table B-1. 

B-1 
The largest magnitude for the Sen slope for a water-level record was -8.7 ft/year at well G-17. Note 

that this well is less than 500 ft from a quarry that was deepened and increased ground-water withdrawals 

during the study period. At this distance, the water level is directly under the influence of the quarry 

depth, and this large decline is not indicative of declines throughout the county. Most wells had declines 

that can be grouped into three clusters. Wells in the northeastern part of the county (G-1 through 4), wells 

(G-12 through 15, G-19, G-20, G-29, G-31), and wells near Petersburg (G-21 through 28) had slopes 

between -1 and -2 ft/year. Wells in the northern part of the county (G-5 through 9, G-11) had slopes 

between -2 and -4.5 ft/year. The remaining wells (G-10, G-16, G-18 through 20, G-30, G-32, G33) 

showed little decline. Well G-10 does not follow the pattern in the northeastern portion of the county, 

but this is the only monitoring well completed in the glacial deposits overlying the bedrock aquifer. Well 

G-13 shows the only positive trend over the time period. The p-value for this well (0.16), however, indicates little statistical likelihood of a trend at this well. The only other well with a high p-value (0.13) is 

G-18. The remainder of the wells have p-values that are extremely small, and the statistical likelihood 

of no trend in these wells is less than 1 percent. 

The same statistical procedures were used to evaluate the potential for trends in the mean daily discharge values from 1991 through 2001 for the River Raisin near Monroe, Manchester, and Adrian, and 

Otter Creek near Lasalle. Two analyses were performed. The first used the mean daily discharge values 

for the gaging stations with time, and the second normalized the daily discharge values by the drainage 

area associated with each station. These analyses showed a statistically significant downward trends in 

the mean daily discharge for each station. The trend in mean daily discharge, when normalized by the 

annual mean discharge is approximately 3 percent decline per year. When normalized by the drainage 

area, the trends for the three stations on the River Raisin are fairly close in magnitude implying that any 

changes in River discharge cannot be solely attributed to activities within Monroe County downstream 

of the Adrian and Manchester gages. These results are summarized in Table B-2. The approach was 

repeated using the average monthly discharge values for the period of record for each station. The results 

of this analysis indicate a slightly positive, but statistically significant, trend at each station on the River 

Raisin. Changes in land use over the period of record may have caused these trends. 

The time-series analysis for surface water support the conclusions made by Nicholas and others 

(2002) that stream discharge numbers do not show the same systematic and sigificant decline as noted in 

ground-water levels. Examination of the variation of stream discharge over the period of record reveals 

that stream discharge was much lower during the drought period in the 1960s than during for the past ten 

to fifteen years. These findings indicate that baseflow to streams is dominated by flow from the overlying glacial material and not from the bedrock aquifer. 

B-2 
Table B-1. Results of trend analysis for ground-water levels in U.S. Geological Survey monitoring wells in 

Monroe County, Michigan, 1991-2001 [ft/yr, feet per year] 

Monitoring well Kendall τ p-value Sen slope 

(ft/yr) 

G-1 -0.786 9.90E-02 -1.38 

G-2 - .454 2.50E-09 - .888 

G-3 - .726 6.00E-26 -1.37 

G-4 - .748 2.00E-27 - .833 

G-5 - .91 2.00E-36 -3. 

G-6 - .992 1.00E-38 -1.72 

G-7 - .876 7.00E-19 -4.5 

G-8 - .928 1.20E-39 -3.1 

G-9 - .759 5.70E-12 -3.7 

G-10 - .55 1.60E-14 - .4 

G-11 - .74 1.54E-22 -2.95 

G-12 - .806 1.00E-30 -1.7 

G-13 .21 1.60E-01 .96 

G-14 - .44 2.70E-10 - .86 

G-15 - .49 7.30E-13 - .8 

G-16 - .423 8.00E-09 - .4 

G-17 - .82 1.00E-21 -8.7 

G-18 - .106 1.26E-01 -0.05 

G-19 - .29 2.00E-05 - .52 

G-20 - .27 7.90E-05 -0.6 

G-21 - .538 3.80E-07 -1.87 

G-22 - .74 7.00E-25 -1.4 

G-23 - .76 2.70E-26 -1.37 

G-24 - .77 2.90E-24 -1.36 

G-25 - .72 1.70E-21 -1.36 

G-26 - .51 4.00E-27 -1.07 

G-27 - .34 8.00E-06 -0.91 

G-28 - .18 9.00E-03 -1.11 

G-29 - .38 4.90E-08 -.7 

G-30 - .46 6.00E-11 - .46 

G-31 - .38 8.20E-05 -1.6 

G-32 - .31 8.10E-06 -.48 

G-33 - .35 5.00E-06 - .35 

GLTO - .54 4.20E-28 - .62 

B-3 
Table B-2. Surface-water flow statistical trends, 1991 - 2001
 

[cfs/year, cubic feet per second per year; ft/sec/year, feet per second per year]
 

Site Kendall τ Slope Slope/Annual Mean 

River Raisin near Monroe 

- 0.086 -17. cfs/year -0.023 1/year 

River Raisin near 

Manchester 

- .104 -3.3 cfs/year - .031 1/year 

River Raisin near Adrian - .084 -8.6 cfs/year - .025 1/year 

Otter Creek - .134 -1.3 cfs/year - .028 1/year 

River Raisin near Monroe normalized by drainage area 

- .086 -6. E-10 ft/sec/year 

River Raisin near 

Manchester normalized 

by drainage area 

- .104 -9. E-10 ft/sec/year 

River Raisin near Adrian 

normalized by drainage 

area 

- .084 -7. e-10 ft/sec/year 

B-4 
Appendix C 

WelLogic Analysis 

The box-and-whisker diagrams in this appendix were developed by grouping wells 

from the WelLogic database (Michigan Department of Natural Resources, 2003) into 

two-year groups by the date the well was drilled. The mean, median, lower and upper 

quartiles, and outliers were determined for each group with more than ten wells. The dotted line on the figure connects the mean values. Groups with less than ten wells drilled 

during a four-year period are plotted using open circles for individual wells and solid circles at the means. Examination of the figures reveals significant scatter for the depth to 

water for each group of four years in each township. The boxes enclose data values 

between the lower quartile and upper quartile. These boxes tend to enclose a range of 

several feet. The whiskers show the spread of the data by extending to either the maximum data value or the upper quartile + 1.5*(upper quartile-lower quartile) and to the 

minimum data value or the lower quartile - 1.5*(upper quartile and lower quartile). In the 

latter cases, the whiskers help highlight outliers in the data set. The outliers are shown 

on the plots using asterisks. For most of the townships, the variation in the mean is generally less than the scatter of the groups. Despite this scatter, general trends are evident 

in the plots. The appendix includes time series for wells open to the bedrock aquifer in 

Monroe County, Michigan and for wells screened in glacial deposits in Washtenaw 

County, Michigan. 

C-1 
Figure C1. Bedrock aquifer ground-water levels reported in WelLogic database for

 Ash Township, Monroe County, Michigan. 

Figure C2. Bedrock aquifer ground-water levels reported in WelLogic database for 

Bedford Township, Monroe County, Michigan. 

C-2 
Figure C3. Bedrock aquifer ground-water levels reported in WelLogic database for 

Berlin Township, Monroe County, Michigan. 

Figure C4. Bedrock aquifer ground-water levels reported in WelLogic database for 

Dundee Township, Monroe County, Michigan. 

C-3 
Figure C5. Bedrock aquifer ground-water levels reported in WelLogic database for 

Erie Township, Monroe County, Michigan. 

Figure C6. Bedrock aquifer ground-water levels reported in WelLogic database for 

Exeter Township, Monroe County, Michigan. 

C-4 
Figure C7. Bedrock aquifer ground-water levels reported in WelLogic database for 

Frenchtown Township, Monroe County, Michigan. 

Figure C8. Bedrock aquifer ground-water levels reported in WelLogic database for 

Ida Township, Monroe County, Michigan. 

C-5 
Figure C9. Bedrock aquifer ground-water levels reported in WelLogic database for 

Lasalle Township, Monroe County, Michigan. 

Figure C10. Bedrock aquifer ground-water levels reported in WelLogic database for 

London Township, Monroe County, Michigan. 

C-6 
Figure C11. Bedrock aquifer ground-water levels reported in WelLogic database for 

Milan Township, Monroe County, Michigan. 

Figure C12. Bedrock aquifer ground-water levels reported in WelLogic database for 

Monroe Township, Monroe County, Michigan. 

C-7 
Figure C13. Bedrock aquifer ground-water levels reported in WelLogic database for 

Raisinville Township, Monroe County, Michigan. 

Figure C14. Bedrock aquifer ground-water levels reported in WelLogic database for 

Summerfield Township, Monroe County, Michigan. 

C-8 
Figure C15. Bedrock aquifer ground-water levels reported in WelLogic database for 

Whiteford Township, Monroe County, Michigan. 

C-9
 
Figure C16. Glacial deposit ground-water levels reported in WelLogic database for 

Ann Arbor Township, Washtenaw County, Michigan. 

Figure C17. Glacial deposit ground-water levels reported in WelLogic database for 

Augusta Township, Washtenaw County, Michigan. 

C-10 
Figure C18. Glacial deposit ground-water levels reported in WelLogic database for 

Bridgewater Township, Washtenaw County, Michigan. 

Figure C19. Glacial deposit ground-water levels reported in WelLogic database for 

Dexter Township, Washtenaw County, Michigan. 

C-11 
Figure C20. Glacial deposit ground-water levels reported in WelLogic database for 

Freedom Township, Washtenaw County, Michigan. 

Figure C21. Glacial deposit ground-water levels reported in WelLogic database for 

Lima Township, Washtenaw County, Michigan. 

C-12 
Figure C22. Glacial deposit ground-water levels reported in WelLogic database for 

Lodi Township, Washtenaw County, Michigan. 

Figure C23. Glacial deposit ground-water levels reported in WelLogic database for 

Lyndon Township, Washtenaw County, Michigan. 

C-13 
Figure C24. Glacial deposit ground-water levels reported in WelLogic database for 

Manchester Township, Washtenaw County, Michigan. 

Figure C25. Glacial deposit ground-water levels reported in WelLogic database for 

Northfield Township, Washtenaw County, Michigan. 

C-14 
Figure C26. Glacial deposit ground-water levels reported in WelLogic database for

 Pittsfield Township, Washtenaw County, Michigan. 

Figure C27. Glacial deposit ground-water levels reported in WelLogic database for 

Salem Township, Washtenaw County, Michigan. 

C-15 
Figure C28. Glacial deposit ground-water levels reported in WelLogic database for 

Saline Township, Washtenaw County, Michigan. 

Figure C29. Glacial deposit ground-water levels reported in WelLogic database for 

Scio Township, Washtenaw County, Michigan. 

C-16 
Figure C30. Glacial deposit ground-water levels reported in WelLogic database for

 Sharon Township, Washtenaw County, Michigan. 

Figure C31. Glacial deposit ground-water levels reported in WelLogic database for 

Superior Township, Washtenaw County, Michigan. 

C-17 
Figure C32. Glacial deposit ground-water levels reported in WelLogic database for 

Sylvan Township, Washtenaw County, Michigan. 

Figure C33. Glacial deposit ground-water levels reported in WelLogic database for

 Webster Township, Washtenaw County, Michigan. 

C-18 
Figure C34. Glacial deposit ground-water levels reported in WelLogic database for 

York Township, Washtenaw County, Michigan. 

Figure C35. Glacial deposit ground-water levels reported in WelLogic database for 

Ypsilanti Township, Washtenaw County, Michigan. 

C-19