Prepared in Cooperation with the 

New Jersey Department of Environmental Protection

Simulated Effects of Alternative Withdrawal Strategies on 

Groundwater Flow in the Unconfined Kirkwood-Cohansey 

Aquifer System, the Rio Grande Water-Bearing Zone, and 

the Atlantic City 800-Foot Sand in the Great Egg Harbor 

and Mullica River Basins, New Jersey

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Scenario year

Annual 2005

1999 2000 2001 2002 2003 2004 2005 2006

Year

Water-level altitude, in feet above NGVD 29

Million gallons per day

Wading River

Well at Mullica River campsite

Scientific Investigations Report 2012–5187

U.S. Department of the Interior

U.S. Geological Survey
C.

B.

D.

A.

E.

Cover:

A. Hand pump well at Mullica River Campsite. (Photograph by W. Jones, U.S. Geological Survey)

B. Hydrograph of simulated and observed water levels at well 010180 (Oceanville) in the Atlantic City 800-foot 

 sand, southeastern New Jersey, 1999–2006.

C. Map showing annual groundwater withdrawals from the Atlantic City 800-foot sand, southeastern 

 New Jersey, 2005.

D. Final available water, simulated base-flow depletion, monthly remaining available water, and base-flow 

 deficit under the Full Allocation scenario for Hydrologic Unit Code 02040301160, southeastern New Jersey.

E. Wading River, New Jersey (Photograph by W. Jones, U.S. Geological Survey)
Simulated Effects of Alternative 

Withdrawal Strategies on Groundwater 

Flow in the Unconfined KirkwoodCohansey Aquifer System, the Rio Grande 

Water-Bearing Zone, and the Atlantic City 

800-Foot Sand in the Great Egg Harbor and 

Mullica River Basins, New Jersey

By Daryll A. Pope, Glen B. Carleton, Debra E. Buxton, Richard L. Walker, 

Jennifer L. Shourds, and Pamela A. Reilly

Prepared in cooperation with the 

New Jersey Department of Environmental Protection

Scientific Investigations Report 2012–5187

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

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Any use of trade, product, or firm names 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.

Suggested citation:

Pope, D.A., Carleton, G.B., Buxton, D.E., Walker, R.L., Shourds, J.L., and Reilly, P.A., 2012, Simulated effects of 

alternative withdrawal strategies on groundwater flow in the unconfined Kirkwood-Cohansey aquifer system, the 

Rio Grande water-bearing zone, and the Atlantic City 800-foot sand in the Great Egg Harbor and Mullica River Basins, 

New Jersey: U.S. Geological Survey Scientific Investigations Report 2012–5187, 139 p.
iii

Acknowledgments

Several individuals at the New Jersey Department of Environmental Protection (NJDEP) 

provided assistance and guidance for this project. Special thanks are extended to Robert Kecskes for his help in planning the project. Thanks are also extended to Steven Domber and Jeffrey 

Hoffman for their assistance in determining an approach to quantify criteria for base-flow depletion in the simulation of various scenarios. Thanks also go to Richard Grabowski for providing 

the 2050-demand data used in the scenarios and to Diane Zalaskus and Jennifer Myers for their 

assistance with the full-allocation data used in the model.

Contents

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

Introduction.....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................5

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

Well-Numbering System .....................................................................................................................5

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

Hydrogeologic Framework..................................................................................................................7

Kirkwood-Cohansey Aquifer System........................................................................................7

Confining Unit Overlying the Atlantic City 800-Foot Sand ...................................................11

Rio Grande Water-Bearing Zone ............................................................................................11

Atlantic City 800-Foot Sand ......................................................................................................11

Hydrogeologic Properties .................................................................................................................17

Water-Use Data ..................................................................................................................................17

Base Flow.............................................................................................................................................21

Recharge..............................................................................................................................................26

Groundwater Flow Model...........................................................................................................................27

Spatial Discretization and Layering.................................................................................................27

Temporal Discretization.....................................................................................................................29

Hydrologic Boundaries ......................................................................................................................29

Recharge.....................................................................................................................................29

Surface-Water Features...........................................................................................................29

Groundwater Withdrawals.......................................................................................................32

Lateral and Vertical Flow Boundaries....................................................................................32

Revisions to RASA Model................................................................................................32

Boundary Specification ..................................................................................................34

Model Calibration................................................................................................................................34

Model Parameters ....................................................................................................................35

Hydraulic Properties ........................................................................................................35

Recharge............................................................................................................................37

Surface-Water Features..................................................................................................41
iv

Model Calibration Data.............................................................................................................41

Hydraulic Head Observations.........................................................................................41

Base-Flow Observations .................................................................................................41

Calibration to Water-Level Observations ..............................................................................43

Kirkwood-Cohansey Aquifer System.............................................................................43

Atlantic City 800-Foot Sand .............................................................................................43

Calibration to Base-Flow Values.............................................................................................50

Sensitivity Analysis.............................................................................................................................50

Flow Budgets.......................................................................................................................................57

Limitations of the Model ....................................................................................................................59

Simulation and Results of Withdrawal Scenarios..................................................................................61

Approach..............................................................................................................................................61

Water Use for Scenarios ..................................................................................................................64

Base-Flow Depletion Criteria............................................................................................................65

No-Withdrawal Scenario ..................................................................................................................67

Basic Scenarios..................................................................................................................................67

Average ......................................................................................................................................73

Full Allocation ............................................................................................................................73

2050 Demand...............................................................................................................................75

Adjusted Scenarios ............................................................................................................................78

Tier 1 Adjustments.....................................................................................................................79

Tier 2 Adjustments.....................................................................................................................79

Tier 3 Adjustments.....................................................................................................................84

Summary of Base-Flow Deficit Reduction and Elimination with Scenario 

Adjustments ..................................................................................................................86

Summary of Final Deficits.........................................................................................................87

Summary and Conclusions.........................................................................................................................89

References Cited..........................................................................................................................................92

Appendix 1. Simulated base flow, base-flow depletion, available water, and deficits under 

Average, Full Allocation, and 2050 Demand scenarios by Hydrologic Unit Code 11 

subbasins in southeastern New Jersey...................................................................................124

Appendix 2. Results of simulations of Average, Full Allocation, and 2050 Demand scenarios–

basic scenarios–from the Great Egg-Mullica Model. (Excel spreadsheet available 

online at http://pubs.usgs.gov/sir/2012/5187/ ) .......................................................................139

Appendix 3. Results of simulations of Average, Full Allocation, and 2050 Demand scenarios 

with Tier 1–3 adjustments from the Great Egg-Mullica Model. (Excel spreadsheet 

available online at http://pubs.usgs.gov/sir/2012/5187/ ) .......................................................139
v

Figures

1. Map showing location of model grid and active model area of the Great EggMullica model, southeastern New Jersey ...............................................................................3

2. Generalized hydrogeologic section, southeastern New Jersey ..........................................4

3. Map showing location of precipitation stations and watersheds, southeastern 

New Jersey....................................................................................................................................6

4. Map showing structure contours of the top of the Kirkwood-Cohansey leaky 

confining unit, southeastern New Jersey ................................................................................9

5. Map showing structure contours of the bottom of the Kirkwood-Cohansey leaky 

confining unit, southeastern New Jersey ..............................................................................10

6. Map showing structure contours of the bottom of the lower sand, KirkwoodCohansey aquifer system, southeastern New Jersey..........................................................12

7. Map showing structure contours of the top of the Rio Grande water-bearing zone, 

southeastern New Jersey.........................................................................................................13

8. Map showing structure contours of the bottom of the Rio Grande water-bearing 

zone, southeastern New Jersey ..............................................................................................14

9. Map showing structure contours of the top of the Atlantic City 800-foot sand, 

southeastern New Jersey.........................................................................................................15

10. Map showing structure contours of the bottom of the Atlantic City 800-foot sand, 

southeastern New Jersey.........................................................................................................16

11. Map showing horizontal hydraulic conductivities at sites of aquifer-test wells and 

well-acceptance test wells in the area of the active model grid, Great Egg-Mullica 

model, southeastern New Jersey............................................................................................19

12. Graph showing groundwater withdrawals, by aquifer, in the Great Egg Harbor and 

Mullica River Basins, southeastern New Jersey,1998–2005...............................................20

13. Graph showing groundwater withdrawals, by use category, in the Great Egg 

Harbor and Mullica River Basins, southeastern New Jersey, 1998–2005 ........................20

14. Graph showing average, minimum, and maximum monthly groundwater withdrawals in the Great Egg Harbor and Mullica River Basins, southeastern 

New Jersey, 1998–2005 .............................................................................................................21

15. Graph showing average monthly groundwater withdrawals, by use category, in 

the Great Egg Harbor and Mullica River Basins, southeastern New Jersey, 

1998–2005 .....................................................................................................................................21

16. Map showing groundwater withdrawals from the Kirkwood-Cohansey aquifer 

system, southeastern New Jersey: A, annual 2005, B, February 2005, and 

C, July 2005 ..................................................................................................................................22

17. Map showing groundwater withdrawals from the Atlantic City 800-foot sand, 

southeastern New Jersey: A, annual 2005, B, February 2005, and C, July 2005 ..............23

18. Map showing subbasins of streamgaging and low-flow partial-record stations 

used in model calibration, southeastern New Jersey..........................................................24

19. Map showing areas of equal cell size in the model grid, specified-flux lateral 

model-boundary cells, and river and wetlands cells of the Great Egg-Mullica 

model, southeastern New Jersey............................................................................................28

20. Map showing distribution of estimated recharge and location of recharge zones, 

southeastern New Jersey.........................................................................................................30

21. Map showing distribution of estimated recharge used in the Great Egg-Mullica 

model for A, 2001 and B, 2005, southeastern New Jersey...................................................31
vi

22. Map showing model cells assigned to freshwater rivers, lakes, ponds, and wetlands in the Great Egg-Mullica model, southeastern New Jersey ....................................33

23. Conceptual diagram of the Kirkwood-Cohansey aquifer system, southeastern 

New Jersey, showing model layers, zone numbers, and hydraulic conductivity 

parameter names........................................................................................................................38

24. Map showing vertical hydraulic conductivity for the confining unit overlying the 

Kirkwood Formation, southeastern New Jersey...................................................................39

25. Map showing horizontal hydraulic conductivity zones for the Atlantic City 800-foot 

sand, southeastern New Jersey ..............................................................................................40

26. Map showing locations of wells with measured water levels, southeastern 

New Jersey, May 2005 and September 2006 .........................................................................42

27. Map showing simulated and measured water-level contours and residuals in the 

Kirkwood-Cohansey aquifer system, southeastern New Jersey, spring 2005.................44

28. Map showing simulated and measured water-level contours and residuals in the 

Kirkwood-Cohansey aquifer system, southeastern New Jersey, fall 2006.......................45

29. Graphs showing simulated and observed water levels for the Kirkwood-Cohansey 

aquifer system and the Atlantic City 800-foot sand, southeastern New Jersey in 

A, spring 2005 and B, fall 2006 ..................................................................................................46

30. Graphs showing residuals of water levels for A, Kirkwood-Cohansey aquifer 

system and B, Atlantic City 800-foot sand, southeastern New Jersey, 2005 

and 2006........................................................................................................................................47

31. Graphs showing hydrographs of simulated and observed water levels in selected 

wells updip in the Kirkwood-Cohansey aquifer system, southeastern New Jersey, 

1999–2006 .....................................................................................................................................48

32. Graphs showing hydrographs of simulated and observed water levels in selected 

wells downdip in the Kirkwood-Cohansey aquifer system and Atlantic City 800-foot 

sand, southeastern New Jersey, 1999–2006..........................................................................49

33. Map showing simulated potentiometric surface of the Atlantic City 800-foot sand 

and water-level residuals, southeastern New Jersey, spring 2005...................................51

34. Map showing simulated potentiometric surface of the Atlantic City 800-foot sand 

and water-level residuals, southeastern New Jersey, fall 2006.........................................52

35. Graphs showing hydrographs of simulated and observed base flows at selected 

streamgaging stations, southeastern New Jersey, 1999–2006...........................................53

36. Graphs showing hydrographs of simulated and observed base flows at selected 

updip low-flow partial-record stations, southeastern New Jersey, 1999–2006...............54

37. Graph showing hydrographs of simulated and observed base flows at selected 

downdip low-flow partial-record stations, southeastern New Jersey, 1999–2006 .........55

38. Graphs showing A, composite scaled sensitivities of model parameters and 

B, normalized group composite scaled sensitivities for the Great Egg–Mullica 

model ............................................................................................................................................57

39. Graphs showing simulated flow budgets for the A, unconfined Kirkwood-Cohansey 

aquifer system and B, Atlantic City 800-foot sand, southeastern New Jersey, 

spring 2005 and fall 2006............................................................................................................58

40. Graphs showing simulated transient flow budgets for the A, unconfined KirkwoodCohansey aquifer sytem and B, Atlantic City 800-foot sand, southeastern 

New Jersey, 1999–2006 .............................................................................................................60

41. Map showing location of Hydrologic Unit Code 11 (HUC11) subbasins, southeastern 

New Jersey..................................................................................................................................62

42. Graphs showing monthly mean streamflow and total monthly precipitation at 

selected sites, southeastern New Jersey, for selected periods from 1957 to 2002 ........63
vii

43. Graph showing simulated groundwater withdrawals in the Great Egg and Mullica 

River Basins, southeastern New Jersey, by permit series, for the Average 

1998–2008, Full Allocation, and 2050 Demand scenarios .....................................................65

44. Graphs showing simulated base flow, base-flow depletion, available water, and 

base-flow deficits under Average, Full Allocation, and 2050 Demand scenarios for 

an example Hydrologic Unit Code 11 subbasin, southeastern New Jersey....................72

45. Maps showing simulated maximum annual base-flow deficits for Hydrologic Unit 

Code 11 subbasins in southeastern New Jersey under A, Average, B, 

Full Allocation, and C, 2050 Demand scenarios, under basic conditions..........................76

46. Maps showing simulated potentiometric surfaces and simulated water-level 

decreases for the Atlantic City 800-foot sand, southeastern New Jersey, under 

Average, Full Allocation, and 2050 Demand scenarios, under basic conditions, 

in April and September of scenario year 9.............................................................................77

47. Maps showing simulated maximum annual base-flow deficits for Hydrologic 

Unit Code 11 subbasins in southeastern New Jersey under A, Average, B, 

Full Allocation, and C, 2050 Demand scenarios with Tier 2 adjustments ..........................81

48. Maps showing potentiometric surfaces and simulated water-level changes for the 

Atlantic City 800-foot sand, southeastern New Jersey, under Average, Full 

Allocation, and 2050 Demand scenarios, with Tier 2 adjustments in April and 

September of scenario year 9 ..................................................................................................83

49. Maps showing average reductions in groundwater withdrawals required to 

eliminate or minimize deficits in Hydrologic Unit Code 11 subbasins, southeastern 

New Jersey, under A, Average, B, Full Allocation, and C, 2050 Demand scenarios 

with Tier 3 adjustments..............................................................................................................85

50. Graphs showing simulated base-flow deficits under A, Average, B, Full Allocation, 

and C, 2050 Demand scenarios with basic, Tier 1, Tier 2, and Tier 3 adjustments for 

the entire study area and updip, mixed, and downdip subbasins, southeastern 

New Jersey..................................................................................................................................87

51. Maps showing simulated maximum annual base-flow deficits for Hydrologic Unit 

Code 11 subbasins in southeastern New Jersey, under A, Average, B, Full 

Allocation, and C, 2050 Demand scenarios with Tier 3 adjustments .................................88
viii

Tables

1. Geologic and hydrogeologic units, southeastern New Jersey ............................................8

2. Horizontal hydraulic conductivity from aquifer tests in the New Jersey Department 

of Environmental Protection Hydroparameters database for southeastern 

New Jersey..................................................................................................................................18

3. Horizontal hydraulic conductivity estimated from specific-capacity data, KirkwoodCohansey aquifer system, Atlantic City 800-foot sand, and Rio Grande waterbearing zone, southeastern New Jersey................................................................................95

4. Groundwater withdrawals from major aquifers in southeastern New Jersey, 2005 

and 1998–2005 .............................................................................................................................18

5. Percentage of groundwater withdrawals from major aquifers, by use, in southeastern New Jersey, 2005.........................................................................................................20

6. MOVE.1 correlation data for low-flow partial-record stations, southeastern 

New Jersey................................................................................................................................102

7. Statistics for streamgaging and low-flow partial-record stations, southeastern 

New Jersey..................................................................................................................................25

8. Final parameters for the calibrated Great Egg-Mullica model ...........................................36

9. Simulated and observed groundwater levels and residuals, southeastern 

New Jersey, May 2005 and September 2006 .......................................................................111

10. Statistics for residuals at wells with long-term hydrographs, southeastern 

New Jersey..................................................................................................................................50

11. Statistics for base-flow residuals at surface-water stations, southeastern 

New Jersey..................................................................................................................................56

12. Scenarios simulated using the Great Egg-Mullica model ...................................................61

13. Scenario years and recharge per year used for simulations with the Great 

Egg-Mullica model......................................................................................................................64

14. Projected withdrawals, by permit type, for selected Hydrologic Unit Code 11 

subbasins, southeastern New Jersey.....................................................................................66

15. Hydrologic Unit Code 11 subbasins and index stations used to transfer monthly 

flow statistics, southeastern New Jersey..............................................................................68

16. Monthly base-flow depletion criteria and associated data for Hydrologic Unit 

Code 11 subbasins, southeastern New Jersey .....................................................................69

17. Simulated monthly base-flow deficits from basic scenarios in the Great EggMullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J......................117

18. Simulated annual and total base-flow deficits from basic scenarios using the 

Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern 

New Jersey..................................................................................................................................74

19. Simulated maximum annual base-flow deficit and scenario year in which the 

deficit occurred using the Great Egg-Mullica model, by Hydrologic Unit Code 11, 

in southeastern New Jersey.....................................................................................................75

20. Simulated deficits from basic scenarios and three-tier adjustment approaches for 

the Great Egg-Mullica model and percentage of total deficit reduction in 

Hydrologic Unit Code 11 subbasins, southeastern New Jersey.........................................80
ix

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L)

gallon (gal) 0.003785 cubic meter (m3) 

million gallons (Mgal) 3,785 cubic meter (m3)

cubic foot (ft3) 0.02832 cubic meter (m3) 

Flow rate

foot per minute (ft/min) 0.3048 meter per minute (m/min)

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

foot per year (ft/yr) 0.3048 meter per year (m/yr)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

cubic foot per day (ft3/d) 0.02832 cubic meter per day (m3/d)

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

gallon per day (gal/d) 0.003785 cubic meter per day (m3/d)

million gallons per day (Mgal/d) 0.04381 cubic meter per second (m3/s)

Mass

ounce, avoirdupois (oz) 28.35 gram (g) 

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

Specific capacity

gallon per minute per foot 

[(gal/min)/ft)]

0.2070 liter per second per meter [(L/s)/m]

Hydraulic conductivity

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

Hydraulic gradient

foot per mile (ft/mi) 0.1894 meter per kilometer (m/km)

Transmissivity*

foot squared per day (ft2/d) 0.09290 meter squared per day (m2/d)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 

(NGVD 29).

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

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

*Transmissivity: The standard unit for transmissivity is cubic foot per day per square foot times 

foot of aquifer thickness [(ft3/d)/ft2]ft. In this report, the mathematically reduced form, foot 

squared per day (ft2/d), is used for convenience.

Simulated Effects of Alternative Withdrawal Strategies on 

Groundwater Flow in the Unconfined Kirkwood-Cohansey 

Aquifer System, the Rio Grande Water-Bearing Zone, and 

the Atlantic City 800-Foot Sand in the Great Egg Harbor 

and Mullica River Basins, New Jersey

By Daryll A. Pope, Glen B. Carleton, Debra E. Buxton, Richard L. Walker, Jennifer L. Shourds, and 

Pamela A. Reilly

Abstract

Groundwater is essential for water supply and plays 

a critical role in maintaining the environmental health of 

freshwater and estuarine ecosystems in the Atlantic Coastal 

basins of New Jersey. The unconfined Kirkwood-Cohansey 

aquifer system and the confined Atlantic City 800-foot sand 

are major sources of groundwater in the area, and each faces 

different water-supply concerns. The U.S. Geological Survey 

(USGS), in cooperation with the New Jersey Department of 

Environmental Protection (NJDEP), conducted a study to 

simulate the effects of withdrawals in the Kirkwood-Cohansey 

aquifer system, the Atlantic City 800-foot sand, and the Rio 

Grande water-bearing zone and to evaluate potential scenarios. The study area encompasses Atlantic County and parts 

of Burlington, Camden, Gloucester, Ocean, Cape May, and 

Cumberland Counties. The major hydrogeologic units affecting water supply in the study area are the surficial KirkwoodCohansey aquifer system, a thick diatomaceous clay confining 

unit in the upper part of Kirkwood Formation; the Rio Grande 

water-bearing zone; and the Atlantic City 800-foot sand of the 

Kirkwood Formation. 

Hydrogeologic data from 18 aquifer tests and specific 

capacity data from 230 wells were analyzed to provide horizontal hydraulic conductivity of the aquifers. Groundwater 

withdrawals are greatest from the Kirkwood-Cohansey aquifer 

system, and 65 percent of the water is used for public supply. Groundwater withdrawals from the Atlantic City 800-

foot sand are about half those from the Kirkwood-Cohansey 

aquifer system. Ninety-five percent of the withdrawals from 

the Atlantic City 800-foot sand is used for public supply. Data 

from six streamgaging stations and 51 low-flow partial record 

sites were used to estimate base flow in the area. Base flow 

ranges from 60 to 92 percent of streamflow.

A groundwater flow model of the Kirkwood-Cohansey 

aquifer system, the Rio Grande water-bearing zone, and the 

Atlantic City 800-foot sand was developed and calibrated 

using water-level data from 148 wells and base-flow data from 

22 gaging or low-flow partial record stations. The KirkwoodCohansey aquifer system within the Great Egg Harbor River 

and the Mullica River Basins was simulated on a monthly 

basis from 1998 through 2006. An existing regional model of 

the New Jersey Coastal Plain was revised to provide boundary conditions for the Great Egg Harbor and Mullica River 

Basin model (referred to as the Great Egg-Mullica model). In 

the Great Egg-Mullica model, monthly groundwater recharge 

rates used in the model ranged from 10–15 inches per year in 

2001 to 20–25 inches per year in 2005. The mean-absolute 

error for 10 of the 14 long-term hydrographs used in model 

calibration was less than 5 ft. Groundwater flow budgets for 

the Great Egg-Mullica model calibration periods, May 2005 

and September 2006, and for the entire model calibration 

period 1998 to 2006, showed that nearly 70 percent of the 

water entering the Atlantic City 800-foot sand came from the 

horizontal connection with the Kirkwood-Cohansey aquifer 

system in updip areas. 

The groundwater flow model was used to simulate scenarios under three possible conditions: average 1998 to 2006 

withdrawals (Average scenario), full-allocation withdrawals (Full Allocation scenario), and projected 2050-demand 

withdrawals (2050 Demand scenario). Withdrawals in the 

Full Allocation scenario are nearly twice the withdrawals 

from the Average scenario, primarily because of the potential 

for large agricultural withdrawals if all allocations are used. 

Withdrawals for the 2050 Demand scenario are about 50 

percent greater than those for the Average scenario, primarily 

due to expected increases in withdrawals for public supply. 

Monthly base-flow depletion criteria were determined using 

the Low-Flow Margin method, currently under consideration 

by NJDEP, to estimate available water on an annual basis at 

the Hydrologic Unit Code 11 (HUC11) level and to determine 

whether a water-supply deficit exists. Simulations of various 
2 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

groundwater-withdrawal scenarios were made using the calibrated model, and results were compared with baseline conditions (no withdrawals) to determine where and when base-flow 

deficits may be occurring and may be expected to occur in the 

future. Scenarios were simulated to assess base-flow depletion that could occur from different groundwater-withdrawal 

situations. In the Average scenario, deficits occurred in 7 of the 

14 subbasins. In the Full Allocation scenario, deficits occurred 

in 11 of the subbasins. In the 2050 Demand scenario, deficits 

occurred in 9 of the 14 subbasins. The largest deficits occurred 

in the Absecon Creek subbasin because the base-flow depletion criteria for this subbasin is small due to the surface-water 

diversions that are already occurring there and because existing groundwater withdrawals in the subbasin have resulted in 

base-flow depletion under current (1998–2006) conditions. 

Three adjusted scenarios, variations of the Average, Full 

Allocation, and 2050 Demand scenarios, were simulated; 

for the adjusted scenarios, the withdrawals were modified in 

stages with the intent to successively eliminate or minimize 

the base-flow deficits. Modifications included shifting withdrawals to a deeper part of the Kirkwood-Cohansey aquifer 

system, implementing seasonal conjunctive use of shallow 

and deep aquifers, and specifying reductions in withdrawals 

within a HUC11 subbasin in deficit. The adjusted scenarios are 

intended to show the relative effectiveness of each of the three 

approaches in reducing the deficits. Most of the deficits under 

the Average, Full Allocation, and 2050 Demand scenarios 

were eliminated by reductions in withdrawals or allocations. 

Shifting withdrawals to a deeper part of the KirkwoodCohansey aquifer system or seasonal conjunctive use did not 

eliminate deficits for any subbasin. Reductions in withdrawals 

accounted for more than 95 percent of the total reduction of 

deficits in all but one subbasin.

Introduction

Groundwater is an essential water supply and plays a 

critical role in maintaining the environmental health of freshwater and estuarine ecosystems in the Atlantic Coastal Basins 

of New Jersey (fig. 1). The unconfined Kirkwood-Cohansey 

aquifer system and the confined Atlantic City 800-foot sand 

are major sources of groundwater in the area. The unconfined 

and confined aquifer systems face different water-supply concerns in an area where water demand is on the rise. Increasing 

groundwater withdrawals from the unconfined KirkwoodCohansey aquifer system is a major concern because of the 

potential for streamflow depletion and the resulting ecological 

effects on aquatic habitats, wetlands, and vernal ponds. The 

Pinelands ecosystem, which includes the Pinelands area, is 

intensely dependent on the Kirkwood-Cohansey aquifer system to maintain streamflow during dry periods, as the groundwater system generally supplies 60 to 80 percent of annual 

streamflow as base flow. Groundwater withdrawals can reduce 

groundwater inflow to wetlands and vernal ponds and can 

decrease base flow to streams. In the confined Atlantic City 

800-foot sand aquifer a major concern is that water levels have 

been steadily declining for many years and were more than 

80 feet (ft) below National Geodetic Vertical Datum of 1929 

(NGVD 29) during all of 2003. Most of the groundwater withdrawn from the Atlantic City 800-foot sand ultimately comes 

from the Kirkwood-Cohansey aquifer system. In updip areas 

where the confining unit overlying the Atlantic City 800-foot 

sand is not present there is a lateral connection between the 

two aquifers (fig. 2). Water flows from the overlying unconfined aquifer through the confining unit to the Atlantic City 

800-foot sand. Although the effects of withdrawals from the 

Atlantic City 800-foot sand on streamflow and water levels in 

the Kirkwood-Cohansey aquifer system are much less than the 

effects of withdrawals directly from the unconfined aquifer, 

there is still the potential for severe effects on the unconfined 

aquifer system, especially near the updip limit of the Atlantic 

City 800-foot sand. A groundwater flow model of the Great 

Egg Harbor and Mullica River Basins was developed to simulate the effects of withdrawals from the Kirkwood-Cohansey 

aquifer system and the Atlantic City 800-foot sand on the 

unconfined aquifer and on streamflow in the subbasins. 

Additional concerns associated with declining water 

levels in the Atlantic City 800-foot sand are saltwater movement in the aquifer and land subsidence in Atlantic County. 

South of the study area in Cape May County, saltwater intrusion in the Atlantic City 800-foot sand is an issue where the 

250-milligram per liter (mg/L) isochlor is located onshore. In 

the Atlantic City area, water with a chloride concentration of 

250 mg/L is located more than 5 miles offshore (dePaul and 

others, 2009), but a cone of depression in the Atlantic City 

800-foot sand is causing landward movement of the saltwater. 

Declining water levels in the Atlantic City 800-foot sand have 

also contributed to land subsidence of nearly 1 inch from 1980 

through 2007, as measured at a site in Atlantic County (unpublished data on file at the U.S. Geological Survey, New Jersey 

Water Science Center in West Trenton, N.J.). If water levels 

in the Atlantic City 800-foot sand continue to decline, the rate 

of saltwater movement and land subsidence may continue to 

increase. The groundwater model developed in this study will 

provide estimates of the decline in water levels in the Atlantic 

City 800-foot sand resulting from various scenarios, which 

resource managers can then use to evaluate future saltwater 

intrusion or subsidence that may result from the declines.

When adopted, the Pinelands Comprehensive Management Plan established nine land-use management areas, one 

being Regional Growth Areas (RGAs) where most future 

residential growth would occur (Pinelands Comprehensive 

Management Plan, N.J.A.C.7:50-5.28). Eleven RGAs were 

established in the Mullica and Great Egg Harbor Basins that 

allow for housing densities of 2.0 to 3.5 houses per acre. Any 

future growth in these RGAs will increase water use, and the 

demand for water ideally will be satisfied in ways that do not 

severely affect the unconfined and confined aquifers.

The U.S. Geological Survey (USGS), in cooperation 

with the New Jersey Department of Environmental Protection 
Introduction 

3

"

" "

"

"

"

"

"

"

"

"

"

"

" ATLANTIC OCEAN

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

Atlantic City

Pleasantville

Somers Point

Ocean City

Mays Landing

Egg Harbor

 City

Hammonton

Buena

Woodbine

CUMBERLAND

GLOUCESTER

CAPE MAY

Base from U.S.Geological Survey digital line graph files, 1:24,000

PENNSYLVANIA

EXPLANATION

Camden

Fort Dix

Toms River

Glassboro

Vineland

0 5 10 15 MILES

0 5 10 15 20 25 KILOMETERS

40°39°

30' 

75° 74°30' 74°

Pinelands Management AreaExtent of model gridBoundary of Great Egg-Mullica model area representing the KirkwoodCohansey aquifer systemUpdip extent of the Atlantic City 800-foot sand (From Zapecza, 1989)Line of section

0 10 MILES

0 10 KILOMETERS

74° 75°

41°40°39°

NEW

JERSEY

A

A′

A

A′

A′ A

Figure 1. Location of model grid and active model area of the Great Egg-Mullica model, southeastern New Jersey. (Section is shown in figure 2)
4 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Confining unit overlying the Atlantic City

800-foot sand, upper confining unit

Confining unit overlying the Atlantic City 800-foot sand, lower confining unit

Rio

Grande water-bearing zone

1,000

100200300400500600700800900

NGVD 1929

200100

Kirkwood-Cohansey aquifer system Kirkwood-Cohansey aquifer system, upper sand

Approximate water table

Kirkwood-Cohansey aquifer system, leaky confining unit

Atlantic City

800-foot sand, lower sand

Atlantic City 800-foot sand, upper sand

Atlantic City 800-foot sand, confining unit

Kirkwood-Cohansey aquifer system, lower sand

Coastline

(1)

(3)

(4)

(6)

(5)

(7)

(8)

(9)

(2)

EXPLANATION

Model layer number (6)

Layers 4-6

Compasite confining unit

44,00 FEET 0 8,800 17,600 26,400 35,200

0 13,410 METERS 2,682 5,364 8,046 10,728

FEET

A

A′

NORTHWEST SOUTHEAST

Figure 2. Generalized hydrogeologic section, southeastern New Jersey. (Line of section shown in figure 1)
Hydrogeology 5

(NJDEP), conducted a study to examine the likely effects of 

withdrawals from the Kirkwood-Cohansey aquifer system, the 

Rio Grande water-bearing zone, and the Atlantic City 800-foot 

sand on streamflow and groundwater supply. The study area 

covers the drainage areas of the Mullica and Great Egg Harbor 

Rivers in the Coastal Plain of New Jersey (fig. 3) and includes 

Atlantic County and parts of Burlington, Camden, Gloucester, 

Ocean, Cape May, and Cumberland Counties.

Purpose and Scope

This report documents the development and application of a groundwater flow model for the Great Egg Harbor 

and Mullica River Basins in the Atlantic Coastal Plain of 

New Jersey. The aquifers in the study area are the unconfined 

Kirkwood-Cohansey aquifer system, the confined Rio Grande 

water-bearing zone, and the confined Atlantic City 800-foot 

sand. Groundwater withdrawal data and estimated recharge 

for the period 1998 to 2006 were used to calibrate the flow 

model. Recharge for the period from 1998 to 2006 was used 

to simulate future water-use scenarios. A regional model of 

the confined Coastal Plain aquifers in New Jersey was updated 

to provide boundary conditions for the Great Egg Harbor and 

Mullica River model (hereafter referred to as the Great EggMullica model). 

Results of the Great Egg-Mullica model were used to 

evaluate the effects of current groundwater withdrawals on the 

system. The effects of potential future groundwater withdrawals were assessed by simulating Full Allocation (maximum 

permitted withdrawals) and projected 2050 Demand scenarios. 

The effects on aquifer water levels and on base-flow depletion 

of streams also were evaluated.

Base-flow depletion criteria were determined for 14 

Hydrologic Unit Code 11 (HUC11) subbasins within the study 

area. Scenarios were simulated in which current and future 

withdrawals were modified in stages in order to meet the baseflow depletion criteria without creating substantial declines 

in the potentiometric surface of the confined Atlantic City 

800-foot sand. Results of the modified scenarios are discussed. 

Previous Investigations

Numerous reports describe the hydrogeologic framework 

and the freshwater flow system in the New Jersey Coastal 

Plain. Zapecza (1989) defines 15 regional hydrologic units 

of the Coastal Plain, describing the subsurface occurrence 

and configuration of the aquifers and confining units. Martin 

(1998) compiled an extensive list of previous investigations 

and simulated the freshwater flow system using a numerical 

groundwater flow model for the USGS Regional Aquifer-System Analysis (RASA). Mullikin (Lloyd Mullikin, New Jersey 

Departement of Environmental Protection, written commun., 

1989) used lithologic logs, cores, and drill cuttings from boreholes and geophysical data to examine the hydrostratigraphy 

of the Kirkwood Formation and its relation to adjoining units. 

Work by Sugarman (2001) describes the hydrostratigraphy of the Kirkwood Formation and Cohansey Formation, 

principally using geophysical logs compiled by Mullikin. Pope 

and Gordon (1999) simulated the New Jersey Coastal Plain 

groundwater flow system using a quasi-three-dimensional 

finite-difference computer model that showed the location 

and movement of the freshwater-saltwater interface in nine 

aquifers and eight confining units. The Coastal Plain RASA 

model was updated by Voronin (2004) using a rediscretization 

of model parameters to a finer cell size, a spatially variable 

recharge rate, and updated groundwater withdrawal data. 

A groundwater model and the hydrogeology of the 

Atlantic City 800-foot sand are described in McCauley and 

others (2001). Pope (2006) used RASA model simulations to 

assess the effects of increased groundwater withdrawals from 

the Atlantic City 800-foot sand and the unconfined KirkwoodCohansey aquifer system on water levels in the Atlantic City 

800-foot sand in the New Jersey Coastal Plain. This study 

highlighted the need for a model of both the Kirkwood-Cohansey aquifer system and the Atlantic City 800-foot sand to 

address water-supply issues in the area. Studies of the surficial 

aquifer systems in the Great Egg Harbor and Mullica River 

Basins (Johnson and Watt, 1996; Watt and Johnson, 1992) 

provide information on the hydrogeology, water levels, water 

quality, surface water, and a water budget of the KirkwoodCohansey aquifer system. 

Lacombe and Carlton (2002) discuss the hydrogeologic 

framework, availability of freshwater supplies, and saltwater intrusion in Cape May County, N.J. Lacombe and others 

(2009) describe the simulation of water-supply scenarios 

for Cape May County. Walker and others (2008) prepared 

a detailed hydrogeologic framework for each of three small 

(less than 85 square miles (mi2)) study areas in the New 

Jersey Pinelands to be used for the groundwater flow models developed for the Kirkwood-Cohansey aquifer system in 

those areas. Hydrologic conditions in these study areas during 

2004–06 were also assessed (Walker and others, 2011) 

Well-Numbering System

The well-numbering system used in this report has been 

used by the USGS in New Jersey since 1978. The well number 

consists of a county code number and a sequence number 

assigned to the well in the county. County code numbers used 

in this report are 01, Atlantic; 05, Burlington; 07, Camden; 09, 

Cape May; and 15, Gloucester. For example, well 01-578 is 

the 578th well inventoried in Atlantic County. 

Hydrogeology

The hydrogeology of the Kirkwood-Cohansey aquifer 

system, the Rio Grande water-bearing zone, and the Atlantic 

City 800-foot sand was assembled from published reports, 

existing data, and data collected as part of this study. The 
6 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Mays

Landing Atlantic City

Airport

Hammonton 

groundwater 

recharge facility

Winslow groundwater recharge 

facility

Mays

Landing

EXPLANATION

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

75° 74°40' 74°20'

Base from U.S.Geological Survey digital 

line graph files, 1:24,000

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

GLOUCESTER

39°

40' 

ATLANTIC OCEAN

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Tuckahoe River

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system 

Hydrologic Unit Code 11 watershed 

within the Great Egg River Basin

Hydrologic Unit Code 11 watershed 

within the Great Mullica River Basin

Groundwater recharge facility and name

Precipitation station and name 

Figure 3. Location of precipitation stations and watersheds, southeastern New Jersey.
Hydrogeology 7

following sections discuss the study area hydrogeologic 

framework, aquifer properties, water-use data, stream base 

flow, and groundwater recharge used in the groundwater flow 

model of the study area. 

Hydrogeologic Framework

The hydrogeologic framework of the entire Coastal Plain 

is described by Zapecza (1989). The New Jersey Coastal Plain 

is composed of a series of seaward dipping wedges of sediment of alternating sand or gravel and clay units. Generally, 

units composed predominantly of sand and gravel compose 

the aquifers of the Coastal Plain, whereas those composed 

predominantly of silt and clay compose the confining units. 

Figure 2 is a generalized hydrogeologic section that runs 

from Camden County, through Atlantic City, N.J., and shows 

the vertical extent of the Coastal Plain aquifers and confining 

units that are addressed in this report. These primary hydrogeologic units of the Great Egg Harbor and Mullica River 

Basins are listed in table 1 in relation to time stratigraphic 

geologic units.

The major hydrogeologic units affecting water supply 

in the study area are described below from shallow to deep. 

The surficial Kirkwood-Cohansey aquifer system is underlain by a thick diatomaceous clay confining unit in the upper 

part of Kirkwood Formation. Within this clay lies the Rio 

Grande water-bearing zone. The Atlantic City 800-foot sand 

is composed of upper and lower sand units. A leaky confining bed separates the sand layers. A composite confining unit 

(Zapecza, 1989) forms the basal clay beneath the Atlantic City 

800-foot sand and the semi-confined or unconfined KirkwoodCohansey aquifer system. The Piney Point aquifer lies directly 

below this clay, but in the Atlantic County area the aquifer 

is not used for water supply because of its depth and the 

presence of saltwater in some areas. Because the composite 

confining unit is relatively impermeable in the study area, it is 

represented as a lower boundary in the model. 

The hydrogeologic framework was revised for this study 

from a regional representation of the New Jersey Coastal Plain 

aquifer system described by Martin (1998). The purpose of 

the revisions was to improve the conceptual model of the flow 

system using additional work that has been done. A clay layer 

within the Kirkwood-Cohansey aquifer system may function 

locally as a confining unit in eastern Atlantic County. The 

Rio Grande water-bearing zone is modeled explicitly in the 

RASA model. The updip limit of the confining unit overlying 

the Atlantic City 800-foot sand was extended farther updip to 

investigate the connection between the Kirkwood-Cohansey 

aquifer system and the Atlantic City 800-foot sand in updip 

areas during model calibration. A thin confining unit within 

the Atlantic City 800-foot sand separates the Atlantic City 

800-foot sand into upper and lower sand units.

Kirkwood-Cohansey Aquifer System

The Kirkwood-Cohansey aquifer system is present 

throughout the entire study area. The aquifer system consists primarily of gravel, sand, silt, and clay sediments of the 

Cohansey and Kirkwood Formations, both of Miocene age. In 

some areas, younger sediments of Holocene, Pleistocene, or 

Miocene age may overlie the Cohansey Formation. In these 

areas, the younger sediments although shown as undifferentiated in table 1 are considered to be part of the aquifer system. 

The Kirkwood-Cohansey aquifer system thickens toward the 

coast to a depth of about 300 ft at the top of the confining unit 

overlying the Atlantic City 800-foot sand (fig.2) 

The Kirkwood-Cohansey aquifer system is generally 

considered to be unconfined; however, discontinuous clays are 

common, especially in sediments of the Cohansey Formation 

(Walker and others, 2008). Data from boreholes that penetrate 

the aquifer system in the eastern part of the study area indicate 

that sediments trend toward finer textures with depth. In the 

western part of the study area, the Kirkwood-Cohansey aquifer 

system includes the lower sand of the Kirkwood Formation, 

the lateral updip equivalent of the Atlantic City 800-foot sand. 

The deeper sediments also tend to be finer with depth, forming 

a gradational contact with the basal composite confining unit. 

Results of a study to investigate hydrologic and ecological 

conditions in the Pinelands, known as the Kirkwood-Cohansey 

Project, include detailed hydrogeologic framework models of 

the Kirkwood-Cohansey aquifer system in three small subbasins in the New Jersey Pinelands (Walker and others, 2008). 

Data and interpretations from that investigation were used 

in the development of the hydrogeologic framework for this 

study. The study included collection of borehole and geophysical data in three subbasins. 

Clay layers within the Kirkwood-Cohansey aquifer system are commonly of variable extent, and few can be traced 

over distances of miles using geophysical logs and borehole 

data. Walker and others (2008) identified an extensive but 

leaky confining layer in the deeper part of the KirkwoodCohansey aquifer system that lies above the principal waterbearing sands in the lower part of this aquifer system in the 

vicinity of Pomona, New Jersey.

The current study used the data accumulated during the 

Kirkwood-Cohansey Project, combined with data from additional geophysical logs and boring logs collected as part of 

this study, to address data gaps in the hydrogeologic framework. Additional interpretative work in the study area defined 

the position of an extensive leaky confining unit within the 

Kirkwood-Cohansey aquifer system that could have regional 

importance. This leaky confining unit divides the KirkwoodCohansey aquifer system in the downdip areas into upper and 

lower sands. The structure contours of the top and bottom of 

this clay, referred to herein as the “Kirkwood-Cohansey leaky 

confining unit,” are shown in figures 4 and 5, respectively. 

The lower sand of the Kirkwood-Cohansey aquifer 

lies immediately beneath the leaky confining unit described 

above. The bottom of this sand lies directly on the top of the 
8 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 1. Geologic and hydrogeologic units, southeastern New Jersey.

ERA System Series Geologic unit1 Hydrogeologic unit2 Cenozoic

Quaternary

Holocene Swamp, salt marsh and 

beach deposits, dune fields

Undifferentiated

Pleistocene

Colluvium-alluvium

Cape May Formation

Tertiary

Miocene

Bridgeton Formation Kirkwood-Cohansey aquifer system, upper sand

Cohansey Formation Kirkwood-Cohansey leaky confining unit

Kirkwood-Cohansey aquifer system, lower sand

Kirkwood Formation

Confining unit overlying the Atlantic City 800-foot sand

Upper confining unit

Rio Grande water-bearing zone

Lower confining unit

Atlantic City 800-foot sand

Upper sand

Confining unit

Lower sand

Composite confining unit3

Oligocene Piney 

Formation

Piney Point aquifer

Eocene

Shark River 

Formation

Manasquan Formation

1

 Nomenclature from Owens and others, 1998; Newell and others, 2000.

2

 Nomenclature from Zapecza, 1989; and Lloyd Mullikin (New Jersey Geological Survey, written commun., 2001).

3

 Includes older geologic units not shown in the table.
Hydrogeology 9

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

ATLANTIC OCEAN

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

-200

-150

-100

-50

0

!

!

! !

! !

! !

! !

! ! !

!

! ! !

! ! !

! !

! !

!

!

!

!

! !

!

!!

!!!

!

!

9

9

14

-6

-26

-78 -24 -17

-17 -21 -27 -20

-77

-49

-84 -40

-40

-38

-38

-38

-76 -98

-97 -78

-36 -10 -94

-98 -31 -38

-119

-113 -134 -102

-148

-100

-220 -100

EXPLANATION

75° 74°40' 74°20'

Base from U.S.Geological Survey digital 

line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

EXTENT OF KIRKWOOD-COHANSEY

LEAKY CONFINING UNIT

!

STRUCTURE CONTOUR—Shows altitude of top of the 

Kirkwood-Cohansey leaky confining unit, in feet. Datum is 

National Geodetic Vertical Datum of 1929. Interval is 50 feet

WELL USED TO INTERPRET HYDROGEOLOGIC 

FRAMEWORK—Number is altitude of top of the KirkwoodCohansey leaky confining unit, in feet. Datum is National 

Geodetic Vertical Datum of 1929

14

0

Beneath the Beneath land ocean

Figure 4. Structure contours of the top of the Kirkwood-Cohansey leaky confining unit, southeastern New Jersey.
10 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

-300

-250

-200

-150

-100

-50

!

!

! !

! !

! !

! !

! ! !

!

! ! !

! !

!

!

!

!

!

!

! !

!

!!

!!!

!

!

-84

-80

-78

-89

-100

-203

-34

-38

-117 -60 -61

-64

-58

-57

-89

-146

-196

-38

-196 -164

-335

-200 -165

-64

-116

-106 -193

-193 -228

-266

-101

-185

-196 -194

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line 

graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

EXTENT OF KIRKWOOD-COHANSEY

LEAKY CONFINING UNIT

!

STRUCTURE CONTOUR—Shows altitude of bottom of the 

Kirkwood-Cohansey leaky confining unit, in feet. Datum is 

National Geodetic Vertical Datum of 1929. Interval is 50 feet

WELL USED TO INTERPRET HYDROGEOLOGIC 

FRAMEWORK—Number is altitude of bottom of the KirkwoodCohansey leaky confining unit, in feet. Datum is National 

Geodetic Vertical Datum of 1929

-34

0

Beneath the Beneath land

ocean

Figure 5. Structure contours of the bottom of the Kirkwood-Cohansey leaky confining unit, southeastern New Jersey.
Hydrogeology 11

diatomaceous clay, the basal confining unit of the KirkwoodCohansey aquifer in the eastern part of the study area. A 

structure contour map of the bottom of the lower sand aquifer 

is shown in figure 6. 

Confining Unit Overlying the Atlantic City 

800-Foot Sand

The basal confining unit of the Kirkwood-Cohansey aquifer system over much of the southeastern part of the study area 

is the thick diatomaceous clay (fig. 2) that forms an extensive 

confining unit in the upper part of the Kirkwood Formation 

(Zapecza, 1989). The approximate updip extent of this confining unit (fig. 7) is present only in subcrop, and available data 

indicate either an abrupt change from sand to clay or a truncation of the clay (Zapecza, 1989). From the approximate updip 

edge, the diatomaceous clay thickens to as much as 350 ft in 

the vicinity of Atlantic City (Zapecza, 1989, pl. 22), confining the lower sands of the Kirkwood Formation beneath it; the 

lower sands comprise the Rio Grande water-bearing zone and 

the Atlantic City 800-foot sand. 

There is uncertainty about the updip extent and character of the confining unit overlying the Atlantic City 800-foot 

sand. This uncertainty has limited the understanding of the 

extent to which the Atlantic City 800-foot sand is connected 

vertically to the generally unconfined Kirkwood-Cohansey 

aquifer system, which appears to transition into a single 

Kirkwood-Cohansey aquifer beyond the updip limit of the 

clay. Although the diatomaceous clay thins toward the west, 

there is apparently little evidence indicating a gradual pinching out of the clay west of the updip extent approximated by 

Zapecza (1989, pl. 22). Reasonable assumptions by previous 

investigators indicate that the absence of this clay to the west 

may be a result of an abrupt erosional truncation or simply a 

lateral change in lithology. Mullikin (Lloyd Mullikin, New 

Jersey Department of Environmental Protection, written commun., 1989) interpreted electrical resistivity soundings in an 

effort to determine the depth of the confining unit overlying 

the Atlantic City 800-foot sand and concluded that the clay 

may extend farther updip than that approximated by Zapecza 

(1989). Sugarman (2001) also makes a similar assertion using 

the data compiled by Mullikin (Lloyd Mullikin, New Jersey 

Department of Environmental Protection, written commun., 

1989). For the groundwater flow model, the framework was 

used as described by Mullikin, including a zone of vertical 

hydraulic conductivity in this area so that the confinement 

of the Kirkwood Formation sediments could be tested during model calibration. In the calibrated model, the Kirkwood 

Formation sediments are simulated as unconfined.

Rio Grande Water-Bearing Zone

The Rio Grande water-bearing zone is a thin aquifer 

located within the confining unit that overlies the Atlantic 

City 800-foot sand (Zapecza, 1989, pl. 5). Zapecza (1989) 

describes the Rio Grande water-bearing zone but does not 

define its geometry. The Rio Grande water-bearing zone 

extends throughout the southeastern half of the study area. In 

general, the thickness increases in the downdip direction from 

northwest to southeast. The thickness ranges from 0 to almost 

140 ft with most areas being less than 50 ft thick. The updip 

extent of the aquifer pinches out into the surrounding diatomaceous clay unit. 

The framework of the Rio Grande water-bearing zone 

was developed using information from approximately 150 

geologic and geophysical well logs. Many of the logs had been 

used in previous work conducted by Lacombe and Carlton 

(2002), Sugarman (2001), Mullikin (Lloyd Mullikin, New 

Jersey Department of Environmental Protection, written commun., 2006), and Zapecza (O.S. Zapecza, U.S. Geological Survey, written commun., 2006). For the purpose of this study, the 

log information was analyzed to differentiate where the Rio 

Grande water-bearing zone is present. The structure contours 

of the top and bottom of the Rio Grande water-bearing zone 

are shown in figures 7 and 8, respectively.

Atlantic City 800-Foot Sand

The Atlantic City 800-foot sand is the principal watersupply aquifer in coastal Atlantic and Cape May Counties. 

In the study area, the aquifer has been subdivided into upper 

and lower sands separated by a thin confining unit. The basal 

clay is the thick composite confining unit, the top of which is 

the basal clay layer of the Kirkwood Formation. The aquifer 

is well defined in coastal areas because of the many watersupply and test wells drilled there. Maps showing the structure 

contours of the top and bottom of the Atlantic City 800-foot 

sand as described by Mullikin (Lloyd Mullikin, New Jersey 

Department of Environmental Protection, written commun., 

2006) are shown in figures 9 and 10, respectively.

The updip extent of the Atlantic City 800-foot sand is 

not well defined with regard to its hydraulic connection to the 

generally semi-confined or unconfined Kirkwood-Cohansey 

aquifer system. Sugarman (2001) indicates that sediments of 

the Atlantic City 800-foot sand and the Kirkwood-Cohansey 

aquifer system are difficult to differentiate where the diatomaceous clay confining unit is absent to the west. Zapecza 

(1989), however, describes the lithologic differences between 

sediments of the Atlantic City 800-foot sand beneath the clay 

(medium- to coarse-grained sand containing considerable shell 

material) and sediments of the generally unconfined parts of 

Kirkwood Formation (fine to medium sand) where it is unconfined, indicating a distinct sediment character in each area. 

Zapecza (1989) approximates the updip extent of the diatomaceous clay subcrop and the Atlantic City 800-foot sand based 

on lithology and confirms the approximate extent using water 

levels in the lower part of the Kirkwood Formation west of the 

limit of the confining bed where it is part of the largely unconfined Kirkwood-Cohansey aquifer system. Martin (1998) represents the lower sands of the Kirkwood Formation as laterally 

continuous with the lower sands of the Kirkwood-Cohansey 
12 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC GLOUCESTER

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

-50

-100

-150

-200

0

-250

-300

-350

-400

!

! !

! !

! !

! !

! ! !

!

! ! !

!

!

!

!

!

!

! !

!

!!

!

!

!

-174

-270 -151 -341

-287

-172

-93

-264.4

-113

-236

-326

-98

-348

-431

-314

-314

-133

-156

-162 -128

-201

-194 -312

-351

-344 -368

-314

-204

-153

-314

75° 74°40' 74°20'

Base from U.S.Geological Survey digital 

line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Updip extent of the lower sand, 

Kirkwood-Cohansey aquifer system

!

STRUCTURE CONTOUR—Shows altitude of bottom of the 

lower sand, Kirkwood-Cohansey aquifer, in feet. Datum is 

National Geodetic Vertical Datum of 1929. Interval is 50 feet

WELL USED TO INTERPRET HYDROGEOLOGIC 

FRAMEWORK—Number is altitude of bottom of the lower 

sand, Kirkwood-Cohansey aquifer, in feet. Datum is National 

Geodetic Vertical Datum of 1929

-93

0

Figure 6. Structure contours of the bottom of the lower sand, Kirkwood-Cohansey aquifer system, southeastern New Jersey.
Hydrogeology 13

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

-700

-600

-500

-400

-300

-200

-100

!

!

!

!

!

!

!

!

!

!

!

! ! !

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

-145

-215

-490

-410 -480

-492

-380

-505

-245

-375

-190

-264

-142

-395

-292

-315

-260

-283

-297

-257 -300 -475

-495

-256

-310

-415

-253

-410

-490

-485

-500

-470

-175 -590

-715

-450

-530

-485

-525

-410 -477

-348

-525

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Area of transition between the Rio Grande 

water-bearing zone and the confining unit 

overlying the Atlantic City 800-foot sand

Updip extent of the Atlantic City 800-foot sand !

(From Zapecza, 1989)

STRUCTURE CONTOUR—Shows altitude of top of 

the Rio Grande water-bearing zone, in feet. Datum 

is National Geodetic Vertical Datum of 1929. 

Interval is 100 feet

WELL USED TO INTERPRET HYDROGEOLOGIC 

FRAMEWORK—Number is altitude of top of the 

Rio Grande water-bearing zone, in feet. Datum 

is National Geodetic Vertical Datum of 1929.

-100

-215

Figure 7. Structure contours of the top of the Rio Grande water-bearing zone, southeastern New Jersey.
14 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Area of transition between the Rio Grande 

water-bearing zone and the confining unit 

overlying the Atlantic City 800-foot sand

Updip extent of the Atlantic City 800-foot sand !

(From Zapecza, 1989)

STRUCTURE CONTOUR—Shows altitude of bottom 

of the Rio Grande water-bearing zone, in feet. Datum 

is National Geodetic Vertical Datum of 1929. 

Interval is 100 feet

WELL USED TO INTERPRET HYDROGEOLOGIC 

FRAMEWORK—Number is altitude of bottom of 

the Rio Grande water-bearing zone, in feet. Datum 

is National Geodetic Vertical Datum of 1929.

-100

-286

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Harbor River

Batsto River

Wading

River

Mullica River

Tuckahoe River

ATLANTIC OCEAN -800

-700

-600

-500

-400

-300

-200

-100

-698

-711

-746

-625

-690

-573

-593

-635

-300

-395

-230

-180

-200

-544

-450 -520

-520

-400

-530

-395

-100

-130

-286

-204

-423

-332

-340

-310

-309

-310

-460

-415

-308

-515

-545

-525

-545

-515

-240

-305

-360

-500 -565

-520

-440

-377

-548

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Figure 8. Structure contours of the bottom of the Rio Grande water-bearing zone, southeastern New Jersey.
Hydrogeology 15

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Har bor River

Batsto River

Wading

River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

-900

-800

-700

-600

-500

-400

-300

-200

-100

0

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Area of semi-confining zone for the 

confining unit overlying the Kirkwood 

Formation

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989)

STRUCTURE CONTOUR—Shows altitude of top 

of the Atlantic City 800-foot sand, in feet. Datum 

is National Geodetic Vertical Datum of 1929. 

Interval is 100 feet

-100

Figure 9. Structure contours of the top of the Atlantic City 800-foot sand, southeastern New Jersey. (model layer 7)
16 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

GLOUCESTER ATLANTIC

Great Egg

H arbor River

Batsto River

Wading

River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

-1100

-1000

-900

-800

-700

-600

-500

-400

-300

-200

-100

-50

0

50

100

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Area of semi-confining zone for the 

confining unit overlying the Kirkwood 

Formation

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989)

STRUCTURE CONTOUR—Shows altitude of bottom 

of the Atlantic City 800-foot sand, in feet. Datum is 

National Geodetic Vertical Datum of 1929. 

Interval is 100 feet

-100

Figure 10. Structure contours of the bottom of the Atlantic City 800-foot sand, southeastern New Jersey. (model layer 9)
Hydrogeology 17

aquifer system updip from the diatomaceous clay. It is reasonable to conclude that the sediment textures of the Atlantic 

City 800-foot sand may grade to permeable sediments west 

of the approximate extent of the diatomaceous clay subcrop 

(Zapecza, 1989), where the aquifer has been referred to as 

part of the unconfined Kirkwood-Cohansey aquifer. Because 

of the limited data in the transition area, the effectiveness of 

the lateral hydraulic connection between the Atlantic City 

800-foot sand and the Kirkwood-Cohansey aquifer system 

near the approximate updip limit of the confining unit remains 

unknown. 

For this study, the model framework includes a transition zone that effectively extends the confining unit overlying the Atlantic City 800-foot sand updip from the position 

approximated by Zapecza (1989), which bridges the gap of 

hydrogeologic uncertainty about the extent and character of 

this clay posed by the various investigators cited above. This 

transition zone is an area of lateral change in the lithology and 

vertical hydraulic conductivity, and it represents a transition 

from confining bed to aquifer. The lateral connection between 

the Atlantic City 800-foot sand and the Kirkwood-Cohansey 

aquifer system is represented as a zone of transition based on 

an assumed lateral hydraulic connection as represented by 

Martin (1998).

Hydrogeologic Properties

Data to characterize the hydraulic properties were 

obtained from the NJDEP hydroparameters database (New 

Jersey Department of Environmental Protection, 2002a) and 

from specific capacity data from public supply wells. Horizontal hydraulic conductivity data from 18 aquifer tests conducted 

in the area were used. Fourteen of these tests were conducted 

in the Kirkwood-Cohansey aquifer system, and four were 

conducted in the Atlantic City 800-foot sand. Hydraulic conductivity data for wells associated with these tests are shown 

in table 2.

Because aquifer test data for the study are sparse, the 

hydraulic conductivity dataset was augmented with specific capacity data from well-acceptance tests conducted on 

large-capacity wells. Specific capacity is a measure of the 

productivity of a well and is calculated as the pumping rate 

divided by the resulting drawdown after the well is pumped 

at the same rate for some period of time (Freeze and Cherry, 

1979). Reported specific-capacity data and ancillary information (well diameter, pumping rate and duration, drawdown, 

and screen length) for wells in the study area were retrieved 

from the USGS National Water Information System (NWIS) 

database to estimate hydraulic conductivity. The transmissivity 

was estimated using the Theis equation, as described in Heath 

(1983). An estimate of storage coefficient is needed to apply 

the Theis equation. For the unconfined Kirkwood-Cohansey 

aquifer system, the storage coefficient is approximately 

equal to specific yield and a value of 0.15 was assumed. This 

value is consistent with the range of specific yield values for 

unconfined aquifers presented by Freeze and Cherry (1979) 

and with that for the Kirkwood-Cohansey aquifer system 

presented by Rhodehamel (1973). Heath (1983) indicates that 

the transmissivity estimated from specific capacity be applied 

to the screened interval of the aquifer. Horizontal hydraulic 

conductivity is calculated for the screened interval of the 

wells by dividing the calculated transmissivity by the length 

of the screened interval. In order to obtain estimates that are 

most representative of the aquifer near the well screen (and 

less influenced by well construction), estimates were made 

for about 250 wells that were pumped at a rate of at least 

200 gallons per minute (gal/min) for at least 4 hours. Horizontal hydraulic conductivities estimated using specific-capacity 

data are listed in table 3 (at end of report).

The distribution of horizontal hydraulic conductivity values in the Kirkwood-Cohansey aquifer system and the Atlantic 

City 800-foot sand are shown in figure 11. For sites in close 

proximity, estimates of hydraulic conductivity determined 

using well-acceptance specific-capacity data and estimates 

derived from aquifer test results are generally comparable 

for the Kirkwood-Cohansey aquifer system. Therefore, it is 

reasonable to use the well-acceptance test estimates where 

aquifer test data are not available, thus allowing for a much 

larger set of wells and a better spatial distribution of horizontal 

hydraulic conductivity. 

Water-Use Data

Water use varies from year to year because of population 

changes, the resulting increased demand, and variable climatic 

conditions. Water use also varies seasonally because public 

supply withdrawals and especially irrigation withdrawals are 

greater during the summer months. The population growth in 

the study area, especially just outside the Pinelands Management Area has put increased demand on the aquifers supplying 

the withdrawals.

Groundwater withdrawals reported by permitted users 

to the NJDEP provide information that allows the NJDEP to 

manage the State’s water resources effectively. Withdrawals 

are reported quarterly by permitted high-volume public supply 

and industrial water users. Withdrawals are reported annually by agricultural and low-volume users. The USGS verifies 

the data following routine quality-assurance checks, including comparison of reported annual and monthly withdrawals 

with the withdrawals permitted by the NJDEP for each permit 

and comparison of annual withdrawals with yearly average 

withdrawals for each well. Additional quality-assurance procedures for the agricultural withdrawal data were used for this 

study because of the large volumes of agricultural withdrawals within the study area. Paper copies of the agricultural data 

were collected from NJDEP and checked against the electronic 

data for the period 1998 to 2005. Withdrawal data that were 

missing, and for which copies of original paper submissions 

were unavailable, were estimated. The estimated value was the 

withdrawal value reported for the most recent preceding year.
18 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 2. Horizontal hydraulic conductivity from aquifer tests in the New Jersey Department of Environmental Protection 

Hydroparameters database for southeastern New Jersey.

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; ft/d, feet per day; gal/min, gallons per minute; NJDEP,

New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Test date

Pumping 

rate 

(gal/min)

Test length, 

hours

Hydraulic 

conductivity 

(ft/d)

010156 -- 121CKKD 56 01/16/1990 400 73 52

010220 -- 121CKKD 169 10/18/1993 1,024 76 110

010689 3600013216 121CKKD 180 05/04/1990 680 119 191

010696 -- 121CKKD 180 02/21/1984 0 72 50

010958 -- 121CKKD 180 05/21/1990 1,808 72 190

011301 3600015053 121CKKD 102 01/20/1992 135 72 216

011448 3600022614 121CKKD 144 03/24/1999 307 72 196

011519 3600024082 121CKKD 170 07/26/2000 412 73 38

070671 -- 121CKKD 144 07/02/1974 503 8 107

070829 3100037164 121CKKD 72 09/27/1991 324 72 118

070901 3100043595 121CKKD 150 07/24/1994 1,120 72 160

070905 3100032361 121CKKD 100 01/29/1990 925 26 198

070936 -- 121CKKD 85 06/20/1994 425 72 75

090381 3600012777 121CKKD 98 -- 170 72 160

010990 3600016110 122KRKDL 657 10/27/1992 1,150 70 64

010991 3600016201 122KRKDL 647 11/17/1992 1,295 72 122

011974 3600024432 122KRKDL 665 01/26/2001 1,400 72 57

090481 -- 122KRKDL 743 10/05/1993 1,400 72 107

Withdrawal data for the Kirkwood-Cohansey aquifer 

system, the Atlantic City 800-foot sand, and the Rio Grande 

water-bearing zone in the study area are used as input for 

simulating pumping stress in the groundwater flow model. 

The average withdrawals by aquifer for 1998 to 2005 and 

total withdrawals by aquifer for 2005 are shown in table 4. 

Withdrawals from the Kirkwood-Cohansey aquifer system are 

about twice those from the deeper Atlantic City 800-foot sand. 

Withdrawals from the Rio Grande water-bearing zone are 

relatively minor. Groundwater withdrawals from each aquifer 

for 1998 to 2005 are shown in figure 12. The withdrawals 

from the Atlantic City 800-foot sand were fairly constant over 

the study period. Withdrawals from the Kirkwood Cohansey 

aquifer system were more variable. The greatest withdrawals 

were made in 2001; most of the withdrawals came from the 

Kirkwood-Cohansey aquifer system. The least withdrawals 

were made in 2000, when withdrawals from the KirkwoodCohansey aquifer system were the lowest of the 8-year period.

The distribution of withdrawals, by use category, is 

shown in figure 13. Withdrawals, by aquifer, water-use 

category, and percentage, for 2005 only are listed in table 5. 

Groundwater withdrawals reported for the study area are 

primarily used for public supply and irrigation. Domestic use 

is not reported to the NJDEP, and domestic withdrawals in 

the study area tend to be from the shallow aquifers. Domestic 

use is primarily non-consumptive, so that most of the water is 

returned to the shallow aquifer. Withdrawals from the Kirkwood-Cohansey aquifer system in 2005 were used primarily 

for public supply with about 29 percent used for irrigation 

(table 5). In contrast, about 95 percent of the withdrawals from 

the Atlantic City 800-foot sand were used for public supply. 

Withdrawals from the Rio Grande water-bearing zone were 

Table 4. Groundwater withdrawals from major aquifers in

southeastern New Jersey, 2005 and 1998–2005.

Aquifer

Time period

Withdrawals

(millions of gallons per year)

2005 Average 

(1998–2005)

Kirkwood-Cohansey aquifer system 15,767 14,742

Rio Grande water-bearing zone 65 71

Atlantic City 800-foot sand 7,597 7,200

Total 23,429
Hydrogeology 19

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

 

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

( Less than 100

( 100 - 299.99

( 300 - 999.99

(Greater than 1,000

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Kirkwood-Cohansey aquifer system

Atlantic City 800-foot sand

AQUIFER TEST 

!

HORIZONTAL HYDRAULIC WELL-ACCEPTANCE TEST

CONDUCTIVITY, IN FEET PER DAY

Less than 100

100 - 300

!

!

Kirkwood-Cohansey aquifer system

Rio Grande water-bearing zone

Atlantic City 800-foot sand

HORIZONTAL HYDRAULIC 

CONDUCTIVITY, IN FEET PER DAY

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

!P

!P

P

P

ATLANTIC OCEAN

Figure 11. Horizontal hydraulic conductivities at sites of aquifer-test wells and well-acceptance test wells in the area of the active 

model grid, Great Egg-Mullica model, southeastern New Jersey.
20 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

0

5,000

10,000

15,000

20,000

25,000

30,000

1998 1999 2000 2001 2002 2003 2004 2005 

Groundwater withdrawals, in million gallons per year 

Year

Kirkwood-Cohansey aquifer system

Rio Grande water-bearing zone

Atlantic City 800-foot sand

EXPLANATION

Figure 12. Groundwater withdrawals, by aquifer, in the Great 

Egg Harbor and Mullica River Basins, southeastern New Jersey, 

1998–2005.

used exclusively for public supply. For the most part, the 

distribution of withdrawals by water-use category remained 

relatively stable from 1998 to 2005 (fig. 13). Withdrawals for 

public supply and other uses remained fairly constant.

The monthly average withdrawals for 1998 to 2005, as 

well as the monthly minimum and monthly maximum, are 

shown in figure 14. Seasonal variations in withdrawals in the 

study area are apparent. Withdrawals in the summer months 

(June through August) can be more than twice the withdrawals 

in the winter months (December through February). Also, the 

variability in withdrawals (difference between maximum and 

minimum withdrawals) is greater in the summer. The average 

monthly withdrawals for 1998 to 2005, by water-use category, 

are shown in figure 15. In the summer months, when usage 

is higher, more water is required for irrigation and for public 

supply.

Withdrawals from the Kirkwood-Cohansey aquifer system, by use category, for all of 2005, February 2005, and July 

2005 are shown in figure 16. For the entire year, most publicsupply withdrawals occurred near Pleasantville and along the 

Camden-Gloucester County border in the northwestern part 

of the study area. Most of the irrigation withdrawals occurred 

in the northern half of the study area near Hammonton. 

0

5,000

10,000

15,000

20,000

25,000

30,000

1998 1999 2000 2001 2002 2003 2004 2005 

Groundwater withdrawals, in million gallons per year 

Year

EXPLANATION

Public supply

Irrigation 

Industrial 

Other 

Figure 13. Groundwater withdrawals, by use category, in the 

Great Egg Harbor and Mullica River Basins, southeastern New 

Jersey, 1998–2005.

Withdrawals for industrial and other uses occurred primarily 

in central Atlantic, and southeastern Camden, and Gloucester 

Counties. In February 2005, most of the large withdrawals 

were for public supply. The distribution of withdrawals for 

industrial and other uses in February 2005 is similar to that of 

annual 2005 withdrawals. Fewer wells were used for irrigation 

in February 2005 than annually in 2005. The usage pattern 

in July 2005 is similar to the pattern for the 2005 annual 

withdrawals.

Withdrawals from the Atlantic City 800-foot sand, by 

use category, for all of 2005, February 2005, and July 2005 

are shown in figure 17. Withdrawals from the Atlantic City 

800-foot sand, by season, did not vary as much as those 

Table 5. Percentage of groundwater withdrawals from major 

aquifers, by use, in southeastern New Jersey, 2005.

[All values are in percent]

KirkwoodCohansey 

aquifer 

system

Rio Grande 

water-bearing 

zone

Atlantic City 

800-foot sand 

Public Supply 64 100 95

Irrigation 29 0 0

Industrial 2 0 0

Other 5 0 5
Hydrogeology 21

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

Jan 

Feb 

Mar 

Apr 

May 

June 

July 

Aug 

Sep 

Oct 

Nov Dec 

Groundwater withdrawals, in million gallons per month 

Month 

Minimum 

Average 

Maximum 

EXPLANATION

Figure 14. Average, minimum, and maximum monthly ground

water withdrawals in the Great Egg Harbor and Mullica River 

Basins, southeastern New Jersey, 1998–2005.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Jan 

Feb 

Mar 

Apr 

May 

June 

July 

Aug 

Sep 

Oct 

Nov Dec 

Month 

Average monthly groundwater withdrawals, in million of gallons per month

EXPLANATION

Public supply

Irrigation 

Industrial 

Other 

Figure 15. Average monthly groundwater withdrawals, by use 

category, in the Great Egg Harbor and Mullica River Basins, 

southeastern New Jersey, 1998–2005.

withdrawals from the Kirkwood-Cohansey aquifer system. 

Overall, withdrawal rates were lower during February than 

during the entire year, and some wells near Pleasantville, N.J., 

were not used during February.

Base Flow

Base flow is the groundwater contribution to the total 

flow of a stream. Monthly base-flow data are needed to calibrate the groundwater flow model. This is important because 

one of the main uses of the flow model will be to predict 

changes in base flow resulting from changes in groundwater 

withdrawals. Where possible, base-flow data from the six 

streamgaging stations within the study area were used for 

model calibration. However, to get a more complete distribution of base flow for calibration purposes (especially in 

downdip areas), base flow was estimated for 51 low-flow 

partial-record sites within the study area. Locations of the 

streamgaging stations and low-flow partial-record basins are 

shown in figure 18. These are sites where discrete measurements were made during low-flow conditions over a period 

of several years. These discrete data can then be used with 

data from nearby long-term streamgaging stations to estimate statistics for the low-flow stations. Monthly base flows 

for January 1992 to September 2006 were estimated for 12 

streamgaging stations (6 within the study area and 6 nearby 

stations) with continuous records using the streamflow partioning program PART (Rutledge, 1998). Base-flow estimates 

for the streamgaging stations with continuous records of 

instantaneous streamflow were used to estimate low-flow 

statistics for 51 low-flow partial-record stations. The Maintenance of Variance Extension Type 1 (MOVE1) program 

was used to estimate the low-flow statistics at partial-record 

stations (Hirsch, 1982). Three or more streamgaging stations 

with similar hydrologic characteristics were used as index stations for each partial-record station. Watson and others (2005) 

describe how the low-flow partial-record correlations were 

done for a statewide analysis of common streamflow statistics. 

The index stations used in that analysis were those used for 

this study. The same analyses were used in this study as were 

used by Watson and others (2005) to estimate base flow at the 

partial-record stations. Daily mean flows at the index stations 

were correlated with instantaneous base-flow measurements at 

the partial-record stations to produce monthly estimated base 

flows at the partial-record stations. The correlations between 

flows at the index stations and the low-flow partial-record 

stations were used to estimate monthly base flows and direct 

runoff at the 51 low-flow sites. The correlation statistics used 

to estimate base flow are listed in table 6 (at end of report).

The base-flow values were used as model calibration 

targets for each subbasin. Average direct runoff for the study 

area was used to estimate recharge. Summary statistics for the 

streamgaging and low-flow partial-record stations are shown 

in table 7. The values for the streamgaging stations were 

determined from the long-term data and from the hydrograph 
22 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

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EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989)

PERMITTED WITHDRAWAL WELLS

Public supply

Industrial

Other

WITHDRAWALS, IN MILLION GALLONS PER DAY

( Less than 0.1

( 0.1 - 0.49

( 0.5 - 0.99

( Greater than or equal to 1.0

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 15 KILOMETERS

Irrigation

A B

C

39°

20' 

75° 74°40' 74°20’

39°

40' 

Figure 16. Groundwater withdrawals from the Kirkwood-Cohansey aquifer system, southeastern New Jersey: A, annual 2005, B, 

February 2005, and C, July 2005.
Hydrogeology 23

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

July 2005

39°

20' 

75° 74°40' 74°20’

39°

40' 

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Mays Landing

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Pleasantville

Atlantic City

Egg Harbor 

City

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February 2005

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20' 

75° 74°40' 74°20’

39°

40' 

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Mays Landing

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Point

Pleasantville

Atlantic City

Egg Harbor 

City

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Annual 2005

39°

20' 

75° 74°40' 74°20’

39°

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EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989)

PERMITTED WITHDRAWAL WELLS

Public Supply

Industrial

Other

WITHDRAWALS, IN MILLION GALLONS PER DAY

( Less than 0.1

( 0.1 - 0.49

( 0.5 - 0.99

( Greater than or equal to 1.0

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 15 KILOMETERS

A B

C

Figure 17. Groundwater withdrawals from the Atlantic City 800-foot sand, southeastern New Jersey: A, annual 2005, B, February 2005, 

and C, July 2005.
24 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Great Egg Har bor River

Batsto River

Wading

River

Mullica River

Tuckahoe River

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

ATLANTIC OCEAN

01411170

01409815

01409411

01409730

01409406

01411220

01411140

01411200

01409416

01410225

01410215

01411305

01410200

01409575

01411302

01411250

01410000

01409500

01411000

01409400

01411300

01410150

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Wetlands

Streamgaging station used in model calibration. 

Number is station number of the surface-water 

site at the downstream end of the basin

Low-flow partial-record station used in model 

calibration. Number is station number

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989) 01411000

01411170

Figure 18. Subbasins of streamgaging and low-flow partial-record stations used in model calibration, southeastern New Jersey.
Hydrogeology 25

Table 7. Statistics for streamgaging and low-flow partial-record stations, southeastern New Jersey.—Continued 

[Type: G, gaging station; LF, low-flow partial-record station, percentage of base flow is caluclated using 1998–2006 mean annual streamflow (not shown) and 

1998–2006 base flow; 7Q10, 7-day-10 year flow; ft3/s, cubic feet per second]

Station 

number Station name

Drainage 

area, 

square 

miles

Type 

Mean 

annual 

streamflow

(ft3

/s)

7Q10 

streamflow

(ft3

/s)

1998–2006 

base flow

(ft3

/s)

Base flow, 

percent of 

streamflow

Mean 

annual 

streamflow 

per square 

mile 

(ft3

/s)

01408500 Toms River near Toms River 123 G 216 66 174 84 1.8

01409400 Mullica River near Batsto 46.7 G 105 15 88 87 2.2

01409500 Batsto River at Batsto 67.8 G 122 40 96 90 1.8

01409810 West Branch Wading River near Jenkins 84.1 G 140 26 113 79 1.7

01410000 Oswego River at Harrisville 72.5 G 86 21 65 84 1.2

01410150 East Branch Bass River near New Gretna 8.11 G 17 6.4 15 88 2.1

01411000 Great Egg Harbor River at Folsom 57.1 G 85 22 72 89 1.5

01411300 Tuckahoe River at Head of River 30.8 G 43 7.2 32 84 1.4

01411500 Maurice River at Norma 112 G 163 38 142 92 1.5

01409375 Mullica River near Atco 3.22 LF 3.7 0.1 2.2 73 1.1

01409387 Mullica River at outlet of Atsion Lk at Atsion 26.7 LF 45 7 33 82 1.7

01409390 Mullica R at Atsion 33.1 LF 55 8.2 43 86 1.7

01409395 Mullica R tr near Atsion 4.1 LF 18 1 13 81 4.4

01409401 Hays Mill Creek at Atco 3.8 LF 3.1 0.8 2.6 90 0.8

01409403 Wildcat Branch at Chesilhurst 1.03 LF 26 6.8 21 88 25.2

01409404 Sleeper Branch at US Route 206 near Atsion 18.2 LF 7.8 0.3 3.4 62 0.4

01409405 Clark B at US Rt 206 near Atsion 7.12 LF 25 5.7 20 87 3.5

01409406 Sleeper Branch at Batsto 36.2 LF 9 0.8 6.5 82 0.2

01409407 Pump B near Blue Anchor 6.2 LF 2.1 0.3 1.6 84 0.3

01409408 Pump Branch near Waterford Works 9.78 LF 12 4.1 10 91 1.2

01409409 Blue Anchor Brook near Blue Anchor 3.01 LF 23 7.3 20 91 7.6

01409410 Albertson Brook near Hammonton 19.3 LF 23 7.2 19 90 1.2

01409411 Nescochague Creek at Pleasant Mills 43.7 LF 68 15 55 87 1.6

01409416 Hammonton Creek at Wescoatville 9.57 LF 16 3.1 13 87 1.7

01409450 Springers Brook near Indian Mills 12.6 LF 15 1.5 8.9 81 1.2

01409460 Springers Brook near Atsion 21.2 LF 27 1 17 77 1.3

01409500 Batsto River at Batsto 67.8 LF 117 36 101 90 1.7

01409575 Landing C at Phila Ave at Egg Harbor City 4.86 LF 6.9 1.5 5.4 86 1.4

01409730 West Branch Wading River near Chatsworth 44.8 LF 49 7.5 35 83 1.1

01409780 Tulpehocken Creek near Jenkins 21.8 LF 25 3.9 19 83 1.1

01409800 West Branch Wading River near Harrisville 83.9 LF 182 28 126 82 2.2

01409815 West Branch Wading River at Maxwell 85.9 LF 130 30 103 88 1.5

01409970 Oswego River at Oswego Lake 61.4 LF 54 13 42 86 0.9

01410200 West Branch Bass River near New Gretna 6.54 LF 14 3.8 11 92 2.1

01410215 Clarks Mill Stream at Port Republic 8.61 LF 12 3 9.9 90 1.4

01410225 Morses Mill Stream at Port Republic 8.25 LF 9.3 1.6 6.7 86 1.1

01410775 Great Egg Harbor River at Berlin 1.88 LF 0.8 0.1 0.7 87 0.4

01410784 Great Egg Harbor R near Sicklerville 15.1 LF 11 1.5 8.2 85 0.7

01410787 Great Egg Harbor R tr at Sicklerville 1.64 LF 0.2 0 0.1 50 0.1
26 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 7. Statistics for streamgaging and low-flow partial-record stations, southeastern New Jersey.—Continued 

[Type: G, gaging station; LF, low-flow partial-record station, percentage of base flow is caluclated using 1998–2006 mean annual streamflow (not shown) and 

1998–2006 base flow; 7Q10, 7-day-10 year flow; ft3/s, cubic feet per second]

Station 

number Station name

Drainage 

area, 

square 

miles

Type 

Mean 

annual 

streamflow

(ft3

/s)

7Q10 

streamflow

(ft3

/s)

1998–2006 

base flow

(ft3

/s)

Base flow, 

percent of 

streamflow

Mean 

annual 

streamflow 

per square 

mile 

(ft3

/s)

01410800

01410803

01410810

01410820

01410855

01410865

01411020

01411035

01411040

01411042

01411047

01411053

01411110

01411140

01411170

01411196

01411200

01411220

01411250

01411299

01411302

01411305

Fourmile Branch near Williamstown 

Fourmile Branch at Winslow Crossing 

Fourmile Branch at New Brooklyn 

Great Egg Harbor River near Blue Anchor 

Squankum B ab Sewage Plant at Williamstown 

Squankum B at Malaga Rd near Williamstown 

Penny Pot Stream near Folsom 

Hospitality Branch at Blue Bell Road near Cecil 

Hospitality Branch near Cecil 

Whitehall Branch near Cecil 

Whitehall Branch below Victory Lakes near Cecil 

Hospitality Branch at Berryland 

Great Egg Harbor River at Weymouth 

Deep Run at Weymouth 

Great Egg Harbor R at Mays Landing 

Babcock Creek near Mays Landing 

Babcock Creek at Mays Landing 

South River near Belcoville 

English Creek near Scullville 

Tarkiln Brook near Head of River 

Mill Creek near Steelmantown 

Mill Branch near Northfield 

5.34

6.22

7.74

37.3

1.5

3.02

5.35

4.51

8.3

2.21

4.6

20

154

20

205

16.3

20

20.4

3.8

7.4

3.82

7.47

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

LF

3.2

5.8

10

52

0.7

1.9

5.4

4.2

12

2.8

6

33

225

33

419

15

23

32

5.1

6.8

4

8.5

0.6

1.5

2.4

13

0.1

0

0.4

0.4

2.4

0.2

0.4

5.3

56

6.1

48

3.1

2.5

6.1

1.6

0.4

0.1

2.6

2.7

4.7

8.6

44

0.5

1.3

3.2

3.2

9.7

2

4.3

27

191

26

305

12

17

25

4.3

4.5

2

7.3

90

89

91

90

83

76

78

86

88

83

83

87

90

87

84

86

81

86

90

78

67

91

0.6

0.9

1.3

1.4

0.5

0.6

1

0.9

1.4

1.3

1.3

1.6

1.5

1.6

2

0.9

1.2

1.6

1.3

0.9

1

1.1

separation program. The values for the partial-record stations 

were estimated using low-flow correlation. 

Recharge

Natural recharge consists of rainfall and snow melt that 

infiltrates the ground and replenishes water in the aquifer. The 

rate of recharge can fluctuate on a daily basis. Recharge was 

estimated on a monthly basis using the water-budget approach 

used for the Toms River Basin, located in the Coastal Plain 

north of the study area (Nicholson and Watt, 1997). This 

indirect approach for estimating recharge is a common method 

used to account for all water that reaches the land surface as 

precipitation. The following equation, adapted from Nicholson 

and Watt (1997), was used for this study:

R P Q ET SM , (1) dr = – – – ∆

where

R is recharge, in inches;

 P is precipitation, in inches; 

Qdr is direct runoff (determined through 

hydrograph-separation techniques), 

in inches; 

ET is evapotranspiration (determined by the 

Thornthwaite method), in inches; and

 ∆SM is change in soil-moisture storage, in inches.

When soil moisture is less than the maximum soil-moisture capacity, then a soil-moisture deficit occurs. Recharge will 

take place only when the deficit is alleviated. In the calculation 

of monthly recharge, the recharge rate could be underestimated when the sum of total monthly evapotranspiration and 
Groundwater Flow Model 27

the soil-moisture deficit exceeds total monthly precipitation, 

especially during summer months. To compensate for this situation, recharge must be estimated on a daily basis to account 

for separate storm events that could produce high rates of 

infiltration that exceed the sum of evapotranspiration and the 

soil-moisture deficit for that same period. For the transient 

simulations, daily recharge was calculated and totaled for 

each month from January 1998 through December 2006. An 

initial soil-moisture deficit of zero was assumed for January 

1998, and an initial maximum daily soil-moisture deficit of 

1.5 inches was assumed. However, during model calibration 

this value was reduced to 0.75 inch to produce a better match 

to base-flow estimates. Daily precipitation data from the Mays 

Landing, N.J., weather station were used with supplemental 

data from the Atlantic City Airport weather station when data 

from Mays Landing were not available. Daily evapotranspiration was interpolated from monthly estimated potential 

evapotranspiration determined by Watt and Johnson (1992) at 

Hammonton, N.J. The soil-moisture deficit for the entire study 

area was calculated using the daily potential evapotranspiration from Hammonton and the precipitation from Mays Landing with supplemental data from the Atlantic City Airport. The 

water-budget equation was modified to include the soil-moisture deficit as shown in the following equation:

R S m (m n ) MD(m n Q

n

d m

P m n ET dr = [[ , )

( )

( ) ]

=

∑ − − − −

1

1 ( ) ] , , m , (2)

where

Rm is recharge for month m, in inches;

d(m) is number of days in month m;

P(m,n) is precipitation on day n in month m, 

in inches; 

ET(m,n) is evapotranspiration on day n in month m, 

in inches; 

SMD(m,n-1) is soil-moisture deficit from the day preceding 

day n in month m, in inches; and

Qdr(m) is direct runoff for month m, in inches.

The combined Great Egg Harbor and Mullica River 

Basins were divided into four areas to estimate direct runoff. 

The areas were determined by major stream drainage area, 

surface-water discharge station locations, and distribution of 

average annual direct runoff at streamgaging and low-flow 

partial-record sites. An average value of direct runoff was 

calculated for each area. For each area, monthly recharge was 

calculated from the monthly soil-moisture deficit and the average direct runoff. To determine a monthly recharge factor, the 

monthly recharge rates for the four areas were averaged. From 

this, an average recharge rate for 1998 to 2006 was calculated. 

This process allowed calculation of a monthly recharge factor (monthly rate/average monthly rate) that was used in the 

groundwater flow model to adjust recharge over time.

Groundwater Flow Model

The objective for the groundwater flow model was to 

represent the water levels and flow in the Kirkwood-Cohansey 

aquifer system, the Rio Grande water-bearing zone, and the 

Atlantic City 800-foot sand with sufficient accuracy and 

resolution to facilitate an analysis of the regional flow system. 

The model is calibrated to water-level and base-flow data for 

the period from 1998 to 2006. The model was used to predict probable hydrologic changes that result from changes in 

groundwater withdrawals under various conditions. Model 

results will be used to identify subbasins where base-flow 

depletion exceeds criteria that were defined during the study. 

Several approaches were used in a defined order to attempt to 

eliminate deficits in the subbasins. The model code used was 

the USGS modular model (MODFLOW-2000) by Harbaugh 

and others (2000). 

The boundary of the model is shown in figures 1 and 19. 

The Kirkwood-Cohansey aquifer system was simulated within 

the drainage basins of the Great Egg Harbor River and the 

Mullica River so that base-flow and recharge data for the 

large basins could be used in model calibration. Also, because 

the Kirkwood-Cohansey aquifer system is connected to the 

Atlantic City 800-foot sand in updip parts of the basins, this 

area needed to be simulated to represent the flow between the 

Atlantic City 800-foot sand and the unconfined KirkwoodCohansey aquifer system updip. The confined aquifers were 

simulated over a larger area so that the boundary conditions 

were distant from the main area of interest. Boundary flows 

for the confined aquifers were obtained from a modified version of the New Jersey RASA model (Voronin, 2004).

Spatial Discretization and Layering

The finite-difference model grid limits and grid spacing 

are shown in figure 19. The areas with different grid spacing are shown in different colors. The model consists of 276 

rows, 288 columns, and 9 layers. Grid-cell dimensions in the 

onshore part of the model are 880 x 880 or 880 x 1,100 ft. This 

discretization was used to adequately represent surface-water 

features in the model. Grid-cell dimensions are larger in offshore areas. Grid alignment and spacing were selected so that 

the model grid fits within the RASA model (Voronin, 2004) 

such that boundary conditions for the confined Atlantic City 

800-foot sand could easily be imported. The specified-flux 

boundaries from the RASA model for the confined aquifers 

are also shown in figure 19. In addition, the map shows the 

model cells where streams, freshwater wetlands, and saltwater 

wetlands are represented as boundaries. 

The model vertical discretization uses nine layers. The 

model layers are shown in the generalized section in figure 2. 

In the updip part of the model, all nine layers are used to 

represent the Kirkwood-Cohansey aquifer system. Layer 1 

was assigned a thickness of 50 ft. The estimated top of the 

Kirkwood-Cohansey aquifer system was used to represent 
28 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Area of river or freshwater-wetlands cells

Area of saltwater-wetlands cells

Flux boundary

AREA OF EQUAL MODEL CELL SIZE

Cell is 880 feet by 880 feet

Cell is 1,100 feet by 880 feet

Cell is 1,320 feet by 880 feet

Cell is 1,980 feet by 880 feet

0 5 10 15 MILES

0 5 10 15 20 KILOMETERS

Woodbine

74°

39°

40' 

39°20' 74°

75°

39°

20' 

39°40' 75° 40°

40°

ATLANTIC OCEAN

Base from U.S.Geological Survey digital line graph files, 1:24,000

Figure 19. Areas of equal cell size in the model grid, specified-flux lateral model-boundary cells, and river and wetlands cells of the 

Great Egg-Mullica model, southeastern New Jersey.
Groundwater Flow Model 29

the top of layer 7. In this updip area, layers 4 to 6 and layer 

8 were arbitrarily assigned 1-foot thicknesses in the model. 

Layers 2 to 3, 7, and 9 were subdivided to create equal layer 

thicknesses for the model. Vertical hydraulic conductivities 

in this area are high; vertical flow in the area is not impeded, 

so the aquifer functions as a single unit. For the flow model, 

the altitudes of the top and bottom of layer 1 and the altitudes 

of the bottom of layers 2 through 9 were used as model input. 

MODFLOW-2000 calculates the thickness used in the flow 

model from these altitudes.

In downdip parts, the Kirkwood-Cohansey aquifer system, including the leaky confining unit within the system, was 

modeled using layers 1 to 3. In offshore areas and saltwater 

wetland areas, layer 1 is a constant-head boundary representing the Atlantic Ocean at sea level. The confining unit overlying the Atlantic City 800-foot sand, where present, is represented by layers 4 to 6. Where the Rio Grande water-bearing 

zone is present, it is represented by a variable thickness in 

model layer 5, based on the structural contours of the top and 

bottom of the layer, previously described. Finally, the Atlantic 

City 800-foot sand is represented by the downdip parts of layers 7 to 9. The confining unit within the Atlantic City 800-foot 

sand is represented by layer 8. 

Temporal Discretization

The simulation period for model calibration was January 

1998 through September 2006. A total of 130 monthly stress 

periods was used. The calibration period was represented in 

stress periods 26 through 130. Stress period 1 was simulated 

as steady state to represent average annual 1998 conditions 

as initial conditions for the model. Stress periods 2 to 25 

were transient stress periods that repeated the 1998 cycle of 

monthly withdrawals two times. This process allows a transition period from the steady-state 1998 period (stress period 1) 

to the transient period used for model calibration in January 

1998 (stress period 26). This strategy ensures that the conditions simulated at the beginning of the calibration period are 

realistic.

Hydrologic Boundaries

Hydrologic boundaries were used to represent the locations and quantity of flow into and out of the model. For the 

unconfined aquifer, these boundaries represent lateral and 

vertical flow, recharge, surface-water features, and groundwater withdrawals. For the confined aquifers, the boundaries represent lateral and vertical flow and groundwater withdrawals. 

Recharge

The recharge boundary represented in the model varies 

spatially and temporally. The formulation of this variability 

is described below. The spatial distribution of average annual 

recharge was obtained from the New Jersey Geological Survey 

recharge map. The methodology used to estimate recharge 

for this map is documented in Charles and others (1993) and 

was later made available in a geographic information system 

dataset (New Jersey Department of Environmental Protection, 2002b). A map of the average-annual recharge distribution for the study area is shown in figure 20. Average-annual 

recharge was 10 to 15 inches per year over much of the study 

area. Less recharge (0–10 inches per year) occurred near 

streams or wetlands. The greatest average-annual recharge 

rates (15–20 inches per year) occurred in upland areas in the 

northeastern part of the study area. The recharge in the model 

was assigned to variable-head cells in the top layer of the 

model, which represents the shallowest part of the Kirkwood 

Cohansey aquifer system. 

Monthly recharge was estimated using a soil-water 

balance, as described in an earlier section of this report. An 

average monthly recharge rate for the study area was calculated from the monthly recharge for the period 1998 to 2006. 

A monthly recharge factor was calculated using the monthly 

recharge rate for each month during this period divided by 

the average monthly recharge rate for the simulation period. 

The factor was applied to each model stress period using 

time-varying parameters (instances) in the recharge package. 

Changes to the overall recharge rate were handled by creating 

the four areal zones shown in figure 20 and three zones (not 

shown), representing stream features or wetland areas.

The resultant total recharge distribution for the years 

2001 and 2005 is shown in figure 21. Recharge distribution was calculated by summing the monthly recharge rates 

for each of the 2 years. Dry conditions in 2001 resulted in 

recharge of about 10 to 15 inches per year throughout much 

of the study area. Wetter conditions in 2005 resulted in large 

areas with recharge rates ranging from 20 to 25 inches per 

year. Recharge was specified in the model using the Recharge 

package (RCH) of MODFLOW-2000.

Artificial recharge to the Kirkwood-Cohansey aquifer 

system from land-application recharge basins of wastewatertreatment plants was also simulated. Two wastewater-treatment plants within the study area apply wastewater to the land 

surface. One wastewater-treatment plant is in Hammonton, 

and the other is in Winslow Township. Data on monthly 

discharges from the treatment plants into the recharge basins 

were used. The discharges were simulated in the model using 

the Well package (WEL), and the recharge from the basins 

was applied to model layer 1. All of the recharge water was 

assumed to enter the groundwater system; evapotranspiration 

from the recharge basins was assumed to be negligible.

Surface-Water Features

Surface-water features simulated in the model are 

freshwater wetlands, rivers, streams, lakes, ponds, saltwater 

wetlands, the ocean, and bays. These features are represented 

as boundaries using either the River package (RIV) or the 

Drain package (DRN), or as Constant Head cells (for saltwater 

wetlands or ocean cells). The USGS National Hydrography 
30 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Zone 4

Zone 1

Zone 2

Zone 3

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Boundary of 

recharge zone

Wetlands

ESTIMATED RECHARGE, IN INCHES PER YEAR

(From New Jersey Department of Environmental Protection, 2002b)

0 - 5

>5 - 10

>10 - 15

>15 - 20

EXPLANATION

Charles and others (1993); NJGS Digital Geodata Series, DGS 02-3

(>, greater than)

Great Egg Harbor River

Batsto River

Wading River

Mullica River

Tuckahoe River

ATLANTIC OCEAN

Figure 20. Distribution of estimated recharge and location of recharge zones, southeastern New Jersey.
Groundwater Flow Model 31

Great E gg

Harbor River

Batsto River

Wading

River

Mullica River

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

75° 74°40' 74°20'

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

GLOUCESTER

39°

40' 

39°

20' 

Tuckahoe River

Zone 4

Zone 1

Zone 2

Zone 3

A

B

Great Egg

Harbor River

Batsto River

Wading

River

Mullic a River

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

GLOUCESTER

39°

40' 

39°

20' 

Tuckahoe River

Zone 4

Zone 1

Zone 2

Zone 3

EXPLANATION

Boundary of recharge zones

ESTIMATED RECHARGE, IN INCHES PER YEAR

Less than 10

> 10 - 15

> 15 - 20

0 5 10 MILES

0 10 KILOMETERS

(>, greater than)

EXPLANATION

Boundary of recharge zones

ESTIMATED RECHARGE, IN INCHES PER YEAR

Less than 10

> 10 - 15

> 15 - 20

> 20 - 25

> 25 - 30

(>, greater than)

0 5 10 MILES

0 10 KILOMETERS

ATLANTIC OCEAN

ATLANTIC OCEAN

Figure 21. Distribution of estimated recharge used in 

the Great Egg-Mullica model for A, 2001 and B, 2005, 

southeastern New Jersey.
32 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Dataset (NHD) and the location of saltwater wetlands, as 

delineated on 1:24,000 contour maps, were used to assign the 

type of features simulated. Digital Elevation Model (DEM) 

data were used as a starting point to assign an altitude to these 

features. 

Saltwater wetlands along the coast were simulated as 

constant head cells in layer 1 because these are tidal wetlands 

and the stage of the wetlands changes on a time scale much 

shorter than the 1-month stress periods used in the model. 

A stage of 0.0 ft was used for these constant head cells. The 

limit of these wetlands areas was delineated using the contact 

between the land (green areas) and the wetlands (white areas) 

along the coast or bay areas as shown on coastal topographic 

maps. Wetlands or river features above this limit line were represented using either the River or Drain package. The Atlantic 

Ocean and bays were also represented as constant heads cells 

in layer 1 with a constant head value of 0.0 to represent sea 

level. 

Freshwater surface-water features were derived from the 

NHD. Data were extracted from the NHD and processed to 

assemble the model input for the freshwater features. Areal 

rivers were extracted from the NHD and used to assign some 

of the River package cells in the model. The area of the river 

feature in each model cell was used as input to the River package. Lakes or pond features were extracted from the NHD and 

were used to create input to the DRN package to model the 

lakes. Cranberry bogs are included in this dataset and were 

modeled using the DRN package. Ponds or lakes, which were 

disconnected from other surface-water features, were removed 

from the model. Canals and ditches in coastal areas where 

saltwater wetlands were to be modeled were removed from the 

model. The area of lake, pond, or wetland in each model cell 

was used to prepare input to the DRN package. Linear stream 

features were modeled as either rivers or drains, depending on the position within the watershed. Streamflows from 

first-order streams were simulated using the DRN package to 

avoid unrealistic boundary flows into the model from losing 

sections in the upstream areas because of the steep gradients 

in these areas and because it is reasonable to assume that these 

upstream reaches will be gaining reaches. The remaining 

linear stream features were modeled using the RIV package. 

In either case, the area for the feature was determined by using 

the length of the stream within each model cell and a stream 

width of 5 ft, which is a reasonable estimate for the study area. 

Altitudes of the stage of the river, stream, pond or wetland were initially assigned using the best available DEM data, 

which were obtained from the National Elevation Dataset. For 

the study area, 30-meter DEMs were the best available for 

all areas, except in Burlington County where more detailed 

Light Detecting and Ranging ( LiDAR) data were available. 

Linear features were converted to points spaced 10 meters 

(3.281 ft) apart, and altitudes were obtained for these points. 

The minimum altitude of points within a model cell for each 

feature was used as the initial stage value for that cell. For 

areal features, zonal statistics were used to obtain the lowest altitude within the polygon area of the feature. During 

model calibration, the model flow budget showed areas with 

unreasonable flow from losing stream segments. To correct 

this problem, stages were revised to ensure that stream stage 

always decreased downstream. Estimated stages for the River 

and Drain packages were held constant throughout the model 

simulation period. The river bottom was assumed to be 3 ft 

below the stage in all rivers and drains. Cells assigned to 

freshwater rivers, lakes/ponds, and wetlands used in the model 

are shown in figure 22.

Groundwater Withdrawals

Groundwater withdrawals for the model were obtained 

from the water-use data described earlier in the report. The 

Well package (WEL) was used to represent withdrawals in 

the model. Each withdrawal was associated with a particular 

model layer (or layers) by using the location of the well screen 

of each well. In cases where a well screen crossed model 

layers, the withdrawals were distributed based on the percentage of the well screen located within each model layer. This 

strategy implicitly assumes that the hydraulic conductivity 

does not vary vertically within the aquifer, which was the case 

in the calibrated model. The month with the largest number 

of wells in the model was August 2005. There are 807 wells 

in the model for this stress period with 728 wells are in the 

Kirkwood-Cohansey aquifer, 2 are in the Rio Grande waterbearing zone, and 77 in the Atlantic City 800-foot sand. 

Lateral and Vertical Flow Boundaries

The Great Egg Harbor and Mullica River Basins overlie the Kirkwood-Cohansey aquifer system in southern New 

Jersey. For the unconfined part of the model, lateral no-flow 

boundaries were used because the main area of interest is 

downdip in Atlantic County and near the updip limit of the 

Atlantic City 800-foot sand, which are both distant from the 

basin boundaries. The Atlantic City 800-foot sand, however, 

is definitely part of a regional confined aquifer. The regional 

RASA model was used to provide lateral boundary flows to 

the confined Atlantic City 800-foot sand. In this section, revisions to the RASA model (Voronin, 2004) to incorporate the 

Rio Grande water-bearing zone and to update water-use data 

are described, followed by the boundary specifications for the 

Great Egg–Mullica model.

Revisions to RASA Model

As part of this study, the finite-difference numerical flow 

model developed for the USGS RASA program to simulate 

groundwater flow in the New Jersey Coastal Plain was revised 

by adding the Rio Grande water-bearing zone and recalibrating the model. The model results from this revision serve 

as initial boundary conditions for the sub-regional Great 

Egg–Mullica model which nests within the RASA model. 

The model was recalibrated by matching simulated heads 

to 2003 observed heads. This process included studying the 
Groundwater Flow Model 33

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

Great Egg Harb or River

Batsto River

Wading River

Mullica River

Tuckahoe River

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

STREAMBED VERTICAL HYDRAULIC 

CONDUCTIVITY, IN FEET PER DAY

0.02

1

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

River

FRESHWATER CELL

Lake/Pond Wetlands

ATLANTIC OCEAN

Figure 22. Model cells assigned to freshwater rivers, lakes, ponds, and wetlands in the Great Egg-Mullica model, southeastern 

New Jersey.
34 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

distribution of the residuals and interpreted potentiometric 

contours in the Kirkwood-Cohansey aquifer system, Rio 

Grande water-bearing zone, Atlantic City 800-foot sand, and 

the Piney Point aquifer.

Previous RASA models (Martin, 1998; Voronin, 2004) 

incorporated the Rio Grande water-bearing zone into the 

Atlantic City 800-foot sand. Collectively, the combined unit 

was referred to as the confined Kirkwood aquifer. The goal of 

adding the Rio Grande water-bearing zone to the RASA model 

was to separate, and better define, the Kirkwood-Cohansey 

aquifer system, Rio Grande water-bearing zone, and the Atlantic City 800-foot sand. The Rio Grande water-bearing zone 

was added to the model as layer 3, which increased the number of model layers from 10 to 11. The previously described 

Rio Grande water-bearing zone framework was used to define 

the layer with its overlying and underlying clays. 

This RASA model assumes that flow is completely horizontal within the aquifers and vertical through the confining 

units (Voronin, 2004). For steady-state calibration, a range of 

horizontal hydraulic conductivities from 25 ft per day (ft/d) 

to 75 ft/d was tested to calculate the transmissivity of the Rio 

Grande water-bearing zone. In the final model, a horizontal 

hydraulic conductivity of 50 ft/d was used in calculating transmissivity. During recalibration, it became evident that heads 

needed to be higher in the updip area of the Rio Grande waterbearing zone where the thickness of the layer decreases and 

the layer transitions from confined to semi-confined. Therefore, two zones were created. The vertical hydraulic conductivity could be adjusted separately in each zone, and a range of 

vertical hydraulic conductivities from 0.4 ft/d to 10 ft/d were 

tested. The final model used a vertical hydraulic conductivity 

of 5 ft/d in zone 1 and 1 ft/d to define the clay above the Rio 

Grande water-bearing zone. This same two-zone concept was 

applied to define the clay below the Rio Grande water-bearing 

zone. The final model used a vertical hydraulic conductivity of 

1 ft/d in zone 1 and 0.5 ft/d in zone 2 for this confining unit.

The transient run of the revised RASA model simulated 

conditions from January 1968 to September 2006 with 29 

stress periods and 10 time steps within each stress period. The 

last 8 stress periods cover the simulation period for the Great 

Egg-Mullica flow model. Stress periods 1 through 21 are the 

same as those used in the original RASA model, which covered the period from January 2, 1968, to December 31, 1998 

(Voronin, 2004). Stress periods 22 through 26 cover the period 

from January 1, 1999, to December 31, 2003 (M.K. Watt, U.S. 

Geological Survey, written commun., 2007). Stress periods 

27, 28, and 29 were added to bring the model up to 2006 with 

each stress period representing a calendar year. Withdrawal 

data from 2003 were used for stress periods 27 to 29 to simulate conditions in 2004 through 2006. The simulated heads 

from stress period 26, time step 10, representing 2003, were 

compared to 2003 observed heads in the Kirkwood-Cohansey 

aquifer system, Rio Grande water-bearing zone, Atlantic City 

800-foot sand, and Piney Point aquifer.

Boundary Specification 

For the Great Egg–Mullica model, the lateral flow boundary for the Kirkwood-Cohansey aquifer system is a no-flow 

boundary at the physical boundaries of the Great Egg Harbor 

and Mullica River Basins. Because the main area of focus for 

the study is the Atlantic County area, this is an appropriate 

boundary. For the confined Atlantic City 800-foot sand, the 

lateral boundaries to the north and south, and offshore to the 

east, are specified flows that were imported from the revised 

RASA model. The locations of these boundary flow cells are 

shown in figure 19. The boundary flow cells are present only 

where the Atlantic City 800-foot sand is modeled as confined. 

The lower boundary for the model is a specified-flow boundary, incorporating vertical flows from the New Jersey RASA 

model into the confined and unconfined parts of the model. 

Boundary flows were simulated using the Flow and Head 

Dependent Boundary package (FHB) of MODFLOW. 

Model Calibration

Simulated water levels and base flows were compared 

to observed values to calibrate the Great Egg-Mullica model. 

A total of 32 parameters was used in the model, and values of 

these parameters were adjusted to obtain a fit to hydrologic 

observations. Model calibration was accomplished by initially 

using UCODE-2005 (Poeter and others, 2005) to calculate 

parameter sensitivities using initial estimates of parameters. 

Final calibration was accomplished using the UCODE-2005 

parameter sensitivities and manual adjustment of parameters. During calibration, parameters representing horizontal 

hydraulic conductivity, vertical hydraulic conductivity of 

confining units, recharge, riverbed hydraulic conductivity and 

storage were adjusted to fit observed heads and base flows. 

Synoptic measurements of groundwater levels in fall 1998, fall 

2003, spring 2005, and fall 2006 were used to increase spatial 

coverage of observations for water-level calibration targets 

for the Kirkwood-Cohansey aquifer system and the Atlantic City 800-foot sand. In addition, water-level hydrographs 

for 14 wells and base-flow hydrographs for 22 streamgages 

were used as calibration targets throughout the entire model 

calibration period. The calibration period for the model was 

1998 to 2006. However, because base flow was still responding to initial conditions during 1998, hydrographs of base flow 

and water levels are shown only for 1999 to 2006. Data from 

the 1998 synoptic survey were used to calibrate the Atlantic 

City 800-foot sand because otherwise the model calibration 

period coincided with only one (2003) of the confined aquifer 

synoptic surveys of the Coastal Plain aquifer in New Jersey. 

The goal of model calibration was to match the simulated and 

observed water levels to within plus or minus 5 ft and to match 

simulated and observed base flow as much as possible during 

the summer months. 
Groundwater Flow Model 35

Model Parameters 

The parameters and values used in the model for the 

Layer Property Flow package (LPF), RIV package, DRN 

package, and RCH package are shown in table 8. Seven 

parameter sub-groups were used to represent horizontal 

hydraulic conductivity, eight for vertical hydraulic conductivity, eight for riverbed hydraulic conductivities in the RIV 

and DRN packages, seven for recharge, and two for storage. 

Uniform values for a parameter type were used whenever 

possible to get a good model fit. In many cases, several zones 

were created for a single parameter type to allow for spatial 

variability of various model parameters should they be needed 

during calibration; however, a single value was often used for 

adjacent zones.

Hydraulic Properties

Figure 23 shows a conceptual diagram of the model 

layers that coincide with the section shown in figure 2 along 

line A-Aꞌ (fig.1). The diagram shows the zones within each 

layer that were used to delineate the parameters for the LPF 

in MODFLOW. The number of the zone is shown in bold, 

followed by the names of the parameters for horizontal and 

vertical hydraulic conductivity in the zone. In the following 

discussion, different parts of the flow system and the main 

model parameter controlling flow for the area are described 

using these zones. For units that are primarily aquifers, the 

parameter is the horizontal hydraulic conductivity. For units 

that are primarily confining units, the parameter is the vertical 

hydraulic conductivity. 

The Kirkwood-Cohansey aquifer system was represented 

in parts of all model layers and is shown in shades of yellow 

in figure 23. The vertical red line in layers 4 to 9 corresponds 

to the updip limit of the Atlantic City 800-foot sand that is 

shown in figure 1 and many subsequent figures. In all areas to 

the left of this line (fig. 23) and in zones 24, 25, and 34, the 

Kirkwood-Cohansey aquifer system is modeled as a uniform aquifer system using the parameters cnsy-k1 and KW-k

for horizontal hydraulic conductivity. Different zones were 

established to allow representation of the horizontal hydraulic conductivity of the Kirkwood portion of the aquifer in 

the updip parts of layers 7 to 9 (KW-k). In the eastern part of 

the modeled area, the leaky-confining unit in the KirkwoodCohansey aquifer system is represented in zones 20 and 22 

using the parameter kvcnsyclay for vertical hydraulic conductivity. Constant head cells representing the Atlantic Ocean 

and bays are in zone 12. Zones 10, 12, 30, and 32 represent 

the Kirkwood-Cohansey aquifer system in this area. Different 

zones were created to allow for different horizontal hydraulic conductivity values for the Kirkwood-Cohansey aquifer 

system in these downdip areas (cnsy-k2 and cnsy-k3). In the 

updip part of the model, layers that represent confining units 

or the Rio Grande water-bearing zone in downdip parts of the 

model are simulated as 1 foot thick (layers 2, 4, 5, 6, and 8), 

and the vertical hydraulic conductivity value used (kv-vertcon) 

is large enough that vertical flow between the model layers is 

not substantially limited. 

The horizontal hydraulic conductivity of the KirkwoodCohansey aquifer system (cnsy-k1, cnsy-k2, and cnsy-k3) was 

simulated with a uniform value of 60 ft/d. During calibration, 

different values for zones in the updip and downdip areas, and 

for shallow and deep parts of the aquifer system, were tested, 

but these different values were not needed. The hydraulic 

conductivity values were generally lower than those estimated from well acceptance tests, but using a higher hydraulic 

conductivity value did not produce a good match to observed 

heads and base flows. This same value of horizontal hydraulic 

conductivity was also used for the Kirkwood Formation part 

of the Kirkwood-Cohansey aquifer system in layers 4 to 9 

where the aquifer is unconfined (KW-k). Where the KirkwoodCohansey aquifer system is unconfined (zones 21, 31, 41, 

51, 61, 71, and 81), the vertical hydraulic conductivity of the 

aquifer (kv-vertcon) is 0.5 ft/d. This parameter value allows 

vertical connection between all model units in this area. The 

vertical hydraulic conductivity of the leaky confining unit 

in the Kirkwood-Cohansey aquifer system (kvcnsyclay) is 

0.05 ft/d.

The confining unit overlying the Atlantic City 800-foot 

sand is represented in layers 4 to 6 by zones 43, 53, 63, 40, 

and 60. The area of the confining unit that is updip from the 

extent of the Rio Grande water-bearing zone is represented in 

zones 43, 53, and 63 (this area is shown in figure 7 as the area 

of transition). The vertical hydraulic conductivity of this zone 

is controlled by a single parameter (kv-riosemi) that effectively 

separates the overlying Kirkwood-Cohansey aquifer system 

from the Atlantic City 800-foot sand. The Rio Grande waterbearing zone is represented by zone 50 using the parameter 

rio-k for horizontal hydraulic conductivity with a value of 

50 ft/d. The confining unit above and below the Rio Grande 

water-bearing zone is controlled by two parameters (kvdclay-u

and kvdclay-l) for vertical hydraulic conductivity. The vertical hydraulic conductivity of the confining unit overlying the 

Atlantic City 800-foot sand (kvdclay-u and kvdclay-l) was 

1x10-5 ft/d. Zones 46, 56, and 66 represent the area designated 

as the semi-confining zone for the confining unit overlying 

the Kirkwood Formation and are represented by the vertical hydraulic conductivity parameter kv800semi. The area in 

which these zones occur is just updip from the limit of the 

Atlantic City 800-foot sand, as designated by Zapecza (1989), 

and is shown in figures 9 and 10 as shaded in light green. 

These zones were included to test the model sensitivity to the 

vertical hydraulic conductivity of the confining unit in this 

area. An initially low value of vertical hydraulic conductivity 

was used to test the confinement of the deeper aquifer units in 

this area. However, in the final model calibration, the vertical 

hydraulic conductivity (kv800semi) used in this zone to best 

match observed heads in the Atlantic City 800-foot sand was 

the same as that used throughout the Kirkwood-Cohansey 

aquifer system, which was 0.5 ft/d. This relatively high value 

of vertical hydraulic conductivity results in the representation 

of the updip limit of the Atlantic City 800-foot sand as being 
36 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 8. Final parameters for the calibrated Great Egg-Mullica model.

[NJGS, New Jersey Department of Environmental Protection, Geological Survey; NHD, U.S. Geological Survey National Hydrography Dataset; n/a, not 

applicable]

Parameter

type

Parameter 

description

Parameter 

name

Value Unit

Figure reference 

for parameter 

location

Model 

layer

Composite 

scaled 

sensitivity

Horizontal

hydraulic

conductivity

Cohansey sand, updip cnsy-k1 60 feet/day Fig. 23, zones 15, 21,

25, 24, 31, 34, 41, 51, 

and 61

1-6 92.5

Cohansey sand, downdip cnsy-k2 60 feet/day Fig. 23, zones 10 

and 12

1 32.9

Cohansey sand in semi-confined zone,

downdip

cnsy-k3 60 feet/day Fig. 23, zones 30 

and 32

3 35.8

Confining units cu-k 1 feet/day Fig. 23, zones 20, 22,

40, 43, 53, 60, 63, 

and 80

2, 4-6, 8 33.4

Rio Grande water-bearing zone rio-k 50 feet/day Fig. 23, zone 50 5 24.6

Unconfined Kirkwood Formation KW-k 60 feet/day Fig. 23, zones 46, 56, 

66, 71, 75, 76, 81, 86,

95, 94 and 96. Fig 24 

green zone.

4-9 229

Atlantic City 800-foot sand ac800k 50 feet/day Fig. 23, zones 70 and 

90. Fig 24 gold zone.

7, 9 1,161

Vertical

hydraulic

conductivity 

Kirkwood-Cohansey leaky 

confining unit

kvcnsclay 0.05 feet/day Fig. 23, zones 20 and 

22. Fig.4

2 18.8

Semi-confining zone for the confining

unit overlying Atlantic City 800-foot 

sand 

kv800semi 0.5 feet/day Fig. 23, zones 46, 56, 

and 66. Fig. 9 green 

shaded area

4-6 15.4

Vertical connection between aquifers kv-vertcon 0.5 feet/day 2-8 2.6

Area of transition between the 

Rio Grande water-bearing zone 

and the confining unit overlying 

the Atlantic City 800-foot sand

kv-riosemi 1.00E-5 feet/day Fig. 23 zones 43,53, 

and 63. Fig. 7, gold 

zone

4-6 11.2

Upper part of the confining unit 

overlying Atlantic City 800-foot sand 

kvdclay-u 1.00E-5 feet/day Fig. 23, zone 40 4 15.9

Lower part of the confining unit 

overlying Atlantic City 800-foot sand 

kvdclay-l 1.00E-5 feet/day Fig. 23, zone 60 6 21.8

Semi-confining unit within the 

Atlantic City 800-foot sand

kv800clay 9.8 feet/day Fig. 23, zone 80, 86 8 0.75

Vertical hydraulic conductivity of 

aquifer material

aquifer 1.00E+1 feet/day All aquifer units 1-3, 

5, 7-9

39.5

River-bed

hydraulic

conductivity 

Drains in the Oswego River Basin, updip drnk1 0.02 feet/day Fig. 22, green zone 1 26.3

Drains, downdip drnk2 1 feet/day Fig. 22, pink zone 1 15.3

Drains in the Great Egg Harbor River

Basin, updip

drnk3 0.02 feet/day Fig. 22, green zone 1 12.4

Drains in the Mullica River Basin,

updip

drnk4 0.02 feet/day Fig. 22, green zone 1 55.6

Rivers in the Oswego River Basin,

updip

rivk1 0.02 feet/day Fig. 22, green zone 1 0.99

Rivers, downdip rivk2 1 feet/day Fig. 22, pink zone 1 10.2

Drains in the Great Egg Harbor 

River Basin, updip

rivk3 0.02 feet/day Fig. 22, green zone 1 0.48

Drains in the Mullica River Basin, updip rivk4 0.02 feet/day Fig. 22, green zone 1 17.2
Groundwater Flow Model 37

Table 8. Final parameters for the calibrated Great Egg-Mullica model.

[NJGS, New Jersey Department of Environmental Protection, Geological Survey; NHD, U.S. Geological Survey National Hydrography Dataset; n/a, not 

applicable]

Parameter

type

Parameter 

description

Parameter 

name

Value Unit

Figure reference 

for parameter 

location

Model 

layer

Composite 

scaled 

sensitivity

Recharge

factor

Recharge in zone 1 rechz1 1.25 dimensionlessFig. 20, zone 1 1 71.6

Recharge in zone 2 rechz2 1.5 dimensionlessFig. 20, zone 2 1 24.5

Recharge in zone 3 rechz3 1.5 dimensionlessFig. 20, zone 3 1 95.4

Recharge in zone 6 rechz4 1.5 dimensionlessFig. 20, zone 4 1 136

Recharge in area delineated as 

wetlands in NJGS recharge dataset 

but not in the NHD

rechz5 1.5 dimensionlessWetlands in NHD 1 44.8

Recharge in areas delineated as 

wetlands in the National Hydrologic 

Dataset (NHD)

rechz6 1 dimensionlessWelands in NJGS 

recharge dataset 

but not in NHD

1 10.9

Recharge in river or drain cells rechz7 0 dimensionlessRiver or drain cells 1 n/a

Storage Specific Yield SY 0.15 dimensionless

All active cells 1 33.4

Specific Storage SS 4.00E-6 1/foot All active cells 1-9 69.8

was 0.15. Model layer 1 was simulated as a convertible unit in 

MODFLOW. Layers 2 to 9 were simulated as confined units; 

the transmissivity was calculated as the hydraulic conductivity 

times the thickness of the layer. 

Recharge

Recharge was simulated using the Recharge package 

(RCH) in MODFLOW-2000. A recharge multiplier was used 

to adjust the New Jersey Geological Survey GSR32 recharge 

number and the monthly recharge factor for each of seven 

model parameters (fig. 20). Parameters rechz1 through rechz4

were used for the main recharge rate in the four areal zones. 

A recharge factor of 1.5 was used for zones 2 to 4 (parameters rechz2, rechz3, and rechz4). A factor of 1.25 was used 

in zone 1 (parameter rechz1). In addition to the four areal 

zones, three zones near stream features or wetlands were 

assigned different recharge factors. All cells representing rivers or drains were assigned a recharge value of zero (parameter rechz7). Areas that were delineated as wetlands in the NHD 

were assigned recharge (parameter rechz6) but with a recharge 

factor of 1.0. Areas that were wetlands in the New Jersey 

Geological Survey recharge dataset but were not wetlands in 

the NHD (parameter rechz5) were assigned a recharge factor 

of 1.5.

the same as that identified by Zapecza (1989) and used in the 

RASA model. The final vertical hydraulic conductivity of the 

units overlying the Kirkwood Formation in layers 4 to 6 is 

shown in figure 24. 

The Atlantic City 800-foot sand is modeled in layers 7 

to 9 and is represented using zones 70, 80, and 90. Layer 7 

represents the upper part of the aquifer (zone 70); layer 8, the 

thin confining unit (zone 80); and layer 9, the lower part of the 

aquifer (zone 90). The horizontal hydraulic conductivity of 

the Atlantic City 800-foot sand in layers 7 and 9 (ac800k) was 

50 ft/d. During calibration, a larger value of horizontal hydraulic conductivity was tested for the Atlantic City 800-foot sand, 

but the lower value was needed to match the observed cones 

of depression. The horizontal hydraulic conductivity of the 

Kirkwood Formation part of the Kirkwood-Cohansey aquifer 

system and the Atlantic City 800-foot sand in layers 7 to 9 is 

shown in figure 25. The vertical hydraulic conductivity of the 

confining unit separating the two aquifer units (kv800clay) 

was 9.8 ft/d.

Some uniform parameters were used to represent vertical 

hydraulic conductivity of the aquifers and the storage terms. 

The vertical hydraulic conductivity value for most aquifer 

units (aquifer) was 10 ft/d. The specific storage of the confined 

aquifers and confining units (SS) was 4 x10-6 ft-1 as determined 

during model calibration. Several models of the Coastal Plain 

aquifers in New Jersey have used similar low specific storage values (Voronin, 2004). The specific yield used for the 

unconfined Kirkwood-Cohansey aquifer system in layer 1 (SY) 
38 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Layer

1 15 cnsy-k1, aquifer 10 cnsy-k2, aquifer 12 cnsy-k2, aquifer

2 21 cnsy-k1, kv-vertcon 25 cnsy-k1, aquifer 24 cnsy-k1, aquifer 20 cu-k, kvcnsyclay 22 cu-k, kvcnsyclay

3 31 cnsy-k1, kv-vertcon 34 cnsy-k1, aquifer 30 cnsy-k3, aquifer 32 cnsy-k3, aquifer

4 41 cnsy-k1, kv-vertcon 46

K

W-k, kv800semi

43

cu-k, kv-riosemi

40

cu-k, kvdclay-u

5 51 cnsy-k1, kv-vertcon 56

K

W-k, kv800semi

53

cu-k, kv-riosemi

50

rio-k, aquifer

6 61 cnsy-k1, kv-vertcon 66

K

W-k, kv800semi

63

cu-k, kv-riosemi

60

cu-k, kvdclay-l

7 71

K

W-k, kv-vertcon

75

K

W-k, aquifer

76

K

W-k, aquifer

70

ac800-k, aquifer

8 81

K

W-k, kv-vertcon

86

K

W-k, kv-800clay

80

cu-k, kv-800clay

9 95

K

W-k, aquifer

94

K

W-k, aquifer

96

K

W-k, aquifer

90

ac800-k, aquifer

Figure 23. Conceptual diagram of the Kirkwood-Cohansey aquifer system, southeastern New Jersey, showing model layers, zone numbers, and hydraulic conductivity parameter names. (Names are defined in table 8)
Groundwater Flow Model 39

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the Kirkwood-Cohansey 

aquifer system

0.00001

VERTICAL HYDRAULIC CONDUCTIVITY, IN FEET PER DAY

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

0.5

ATLANTIC OCEAN

Figure 24. Vertical hydraulic conductivity for the confining unit overlying the Kirkwood Formation, southeastern New Jersey.
40 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

EXPLANATION

Boundary of Great Egg-Mullica model 

area representing the Kirkwood-Cohansey 

aquifer system

50

HORIZONTAL HYDRAULIC CONDUCTIVITY, IN FEET PER DAY

60

ATLANTIC OCEAN

Figure 25. Horizontal hydraulic conductivity zones for the Atlantic City 800-foot sand, southeastern New Jersey.
Groundwater Flow Model 41

Surface-Water Features

Eight zoned parameters were used in the model for 

riverbed vertical hydraulic conductivity for the RIV and DRN 

packages. One set of four zones was used to simulate hydraulic conductivity for the DRN package, and four zones were 

used for the RIV package. Three zones (1, 3 ,4) were created 

for the three major river basins (Oswego, Great Egg Harbor, and Mullica Rivers Basins, respectively) in updip areas 

(parameters drnk1, drnk3, drnk4, rivk1, rivk3, and rivk4). A 

fourth zone (2) was created to include all areas downdip from 

the limit of the confining unit overlying the Atlantic City 

800-foot sand (parameters drnk2 and rivk2). This fourth zone 

was created during calibration to aid in matching heads and 

base flow in downdip areas. 

Initial values of 0.2 ft/d for riverbed vertical hydraulic 

conductivity were obtained from a previous model of the 

Mullica River (Harbaugh and Tilly, 1984). The final calibrated 

values for the updip zones were all 0.02 ft/d. During calibration, this value did not produce a good fit with heads and base 

flow in downgradient areas. A zone was created for surfacewater features in this downdip area that coincides with the 

updip limit of the Atlantic City 800-foot sand because this area 

contains subbasins characterized by high base flow (zone 4). 

A riverbed vertical hydraulic conductivity value of 1 ft/d was 

used in this zone. The calibrated values of streambed hydraulic 

conductivity are shown in figure 22. The values of streambed 

conductance within each zone were the same for both the RIV 

and DRN packages in the final calibration.

Model Calibration Data

A variety of data was collected or assembled in order to 

calibrate the groundwater flow model. Data used to calibrate 

the model include synoptic water levels, long-term water levels, and monthly estimates of base flow.

Synoptic water levels used to calibrate the groundwater 

flow model were collected for the study during 2005 and 2006. 

Data were collected in May 2005 to represent high water-level 

and streamflow conditions that occur in the spring. Data collected in September 2006 are representative of late summer 

conditions when water levels and streamflows are typically at 

the lowest levels of the year. Water levels were measured in 

113 wells in the Kirkwood-Cohansey aquifer system, 2 wells 

in the Rio Grande water-bearing zone, and 33 wells in the 

Atlantic City 800-foot sand. The locations of these wells and 

identifiers are shown in figure 26. Water-level data are shown 

in table 9 (at end of report). These data provided two areally 

extensive datasets for use in model calibration. Low-flow measurements were made at 48 sites in May 2005 and 

September 2006. 

Hydraulic Head Observations

In addition to the water levels measured in 2005 and 

2006 as part of this study, other water-level data from the 

USGS NWIS database were used to calibrate the groundwater flow model. These data include water levels measured 

in 1998 and 2003 (Lacombe and Rosman, 2001; dePaul 

and others, 2009) in wells in the USGS New Jersey Coastal 

Plain Synoptic Water-Level Network that are completed in 

the Atlantic City 800-foot sand and long-term water levels 

measured in wells in the New Jersey Water-Level Monitoring Network. All water levels were assigned weights based 

on the accuracy of the land-surface altitude at the site. Some 

wells have relatively accurate land-surface altitudes determined by leveling, whereas others have less accurate values 

interpreted from digital elevation maps or from topographic 

maps. Using the altitude accuracy is appropriate to determine 

the weights because the measurement error at all the wells is 

relatively consistent and small compared to the measurement 

uncertainty in the land-surface altitude. The error statistic for 

heads used in UCODE-2005 is a standard deviation calculated 

using a 90-percent confidence interval. The weighted water 

levels were used to calculate the composite scaled sensitivity 

of the model-simulated heads to changes in each of the model 

parameters.

Daily water levels in 14 wells in the USGS New Jersey 

Water-Level Monitoring Network were used to create monthly 

hydrographs for use in model calibration. The monthly hydrographs were made by using the water level on the 15th day of 

each month during the model calibration period. The locations of these wells are shown in figure 26. Contours of water 

levels from previous studies were used to evaluate the general 

direction and slope of the simulated water levels. Contours of 

measured water levels in the Atlantic City 800-foot sand from 

the New Jersey Coastal Plain Synoptic Water-Level Network 

in 1998 and 2003 were used to visually compare the simulated 

and observed potentiometric surfaces. For the water-table 

aquifer, contours from surficial aquifer studies done by the 

USGS in the Mullica and Great Egg Harbor River Basins were 

used to show the general flow direction in the aquifer. The 

water-level contour map for the Mullica River Basin (Johnson 

and Watt, 1996) is based on water-level data collected during 

1991. The contour map of the Great Egg Harbor River Basin 

(Watt and Johnson, 1992) is based on water-level data collected in 1989. In general, these contour maps agree well at 

the shared boundary between the subbasins; there are some 

small differences that are not relevant at the scale of this study, 

however.

Base-Flow Observations

Base-flow data from 22 sites in the area (fig. 18) were 

used to create the base-flow hydrographs used to calibrate 

the model. Base-flow separation, described earlier, was used 

to directly estimate base flow at the six streamgaging stations. For the remaining 16 low-flow partial-record stations, 

base flow at nearby index sites and the MOVE.1 correlations 

established for these sites were used to estimate base flow. The 

observed base flow is for the total subbasin and includes flow 

in streams simulated by model cells that represent both rivers 
42 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

GLOUCESTER ATLANTIC

 

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

NON-NETWORK WELL WITH MAY 2005 OR 

SEPTEMBER 2006 WATER LEVEL. NUMBER IS 

U.S. GEOLOGICAL SURVEY WELL IDENTIFIER 

!

!

EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Area of semi-confining zone for the confining unit 

overlying the Kirkwood Formation

Updip extent of the Atlantic City 800-foot 

sand (From Zapecza, 1989)

NETWORK WELL WITH WATER-LEVEL 

DATA FOR 1998 TO 2006. NUMBER IS U.S. 

GEOLOGICAL SURVEY WELL IDENTIFIER

Kirkwood-Cohansey aquifer system

Atlantic City 800-foot sand

Kirkwood-Cohansey aquifer system

Rio Grande water-bearing zone

Atlantic City 800-foot sand

!

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

!

!

!

!

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!

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! 011404

011402

011400

011234 011197

010953

010930 010919

010899

010885

010864

010851

010757

010751

010750

010747

010744

010742

010740

010726

010724 010721

010720

010719

010712 010717

010699

010689

010603

010486,010464

010466

010465

291062

290789

151281

151207

151149

150753

090460

090382

090381

090348

090325 090145

071129

071128

071125

071092 071091

070845

070840

070835

070712

070681

070501

070479

070459

070452

070451

070432

070431

070430

051504

051501

051139

051138

051136

051131

051126

051119

051107

051104

051103

051102

051098

050613 050609 050608

050512

050482

050455

050454

050452

050418 050451

050417

050404

011670

011667,011652

011638,011639 011630

011627

011624 011622

011565

011506

011505

090186

011275

010778

010754

010725

010219

090519

090149

011455

011256

011252

011220

011218

010990

010967

010889

010704

010683

010650

010648

010637

010600

010593

010369

010117

010039

010037

090461

090459 090185 090148 090124

090116

090109

011456

010256

151213

050684

050630

050628

050570

050409

050408

010776 010775

010706

090481

090144

011476

010180

010703

010702

010578

011504

011671,011631,011629

011625,011623

011500,011499,011498

ATLANTIC OCEAN

Figure 26. Locations of wells with measured water levels, southeastern New Jersey, May 2005 and September 2006.
Groundwater Flow Model 43

and drains. A good match between simulated and observed 

base flows during the summer months was achieved for most 

basins.

Calibration to Water-Level Observations

Maps and hydrographs of water levels were used to calibrate the groundwater model. Maps show the simulated potentiometric surface and residuals at observed wells. The residuals are the simulated head minus the observed head at the well. 

Most of the simulated water levels in all aquifers are within 

5 ft of the observed water level. In the Kirkwood-Cohansey 

aquifer system, 69 percent are within 5 ft, and 89 percent are 

within 10 ft. In the Atlantic City 800-foot sand, 53 percent are 

within 5 ft, and 79 percent are within 10 ft.

Kirkwood-Cohansey Aquifer System

The model of the Kirkwood-Cohansey aquifer system 

was calibrated by comparing water-level data collected during spring 2005 and fall 2006 with simulated water levels. 

The model also was evaluated by qualitatively comparing 

simulated water-level contours for the Mullica and Great Egg 

Harbor River Basins calculated for the spring 2005 and the 

fall 2006 with previously mapped water-table contours for 

the same time period. The simulated water-table contours and 

residuals (simulated minus observed heads) for the Kirkwood-Cohansey aquifer system in spring 2005 are shown in 

figure 27. The simulated contours and residuals for the Kirkwood-Cohansey aquifer system in fall 2006 are shown in figure 28. The shapes of the simulated contours for spring 2005 

and fall 2006 closely follow the water-table maps created for 

the Mullica and Great Egg Harbor River Basins surficial aquifer studies (Watt and Johnson, 1992; Johnson and Watt, 1996). 

The simulated and observed groundwater levels and the residuals for spring 2005 and fall 2006 are listed in table 9. The 

locations of these wells, labeled with USGS well numbers, 

are shown in figure 26. Throughout most of the study area, the 

simulated water levels are within +/- 5 ft of the observed water 

levels. The largest and most frequent occurrence of residuals 

of more than +/- 5 ft is in the area northwest of Pleasantville 

along the divide between the Mullica and Great Egg Harbor 

River Basins. Residuals of up to 38 ft occurred in this area. 

For most of these large residuals, the simulated head is much 

lower than the observed head. However, at other nearby wells, 

the simulated heads are either greater than the measured heads 

or within +/- 5 ft. The water-use maps in figure 16 show large 

withdrawals occurring in this area, especially in the summer. 

In this area, the regional representation does not match local 

conditions exactly.

Graphs of the simulated and observed heads in both 

the Kirkwood-Cohansey aquifer system and the Atlantic 

City 800-foot sand in spring 2005 and fall 2006 are shown 

in figure 29A. The heads in the Kirkwood-Cohansey aquifer 

system (shown in blue) generally plotted along the 1:1 line 

in figure 29A. The heads above the line are those in the area 

northwest of Pleasantville (discussed above). The distribution 

of the residuals for the Kirkwood-Cohansey aquifer system 

in spring 2005 and fall 2006 is shown in figure 30A. The distribution of residuals does not indicate any spatial bias in the 

simulated heads.

Hydrographs for wells in the Kirkwood-Cohansey aquifer 

system are shown in figures 31 and 32. Figure 31 shows 

hydrographs for wells in the updip areas of the KirkwoodCohansey aquifer system. Figure 32 shows hydrographs for 

wells in the downdip areas. Wells in the Kirkwood-Cohansey 

aquifer system are labeled CKKD, and wells in the Atlantic 

City 800-foot sand are labeled AC800. The simulated heads 

match the observed seasonal water levels fairly well. One goal 

of calibration was to match both the magnitude and seasonal 

variation of the observed heads. Most of the simulated heads 

are within 5 ft of the observed heads. Simulated water levels 

at the Mount Obs well (050570) are low and do not match the 

observed levels or seasonal variations as well as simulated 

water levels match observed water levels for most other wells. 

Three sets of these hydrographs are for well nests in different 

model layers at or near the same locations. At the Atsion well 

nest (050409 and 050408), simulated water levels are close 

to the observed water levels, especially at the shallow well. 

At the Penn SF nest (050628 and 050630; fig. 31), simulated 

water levels for the shallow well are up to 10 ft higher than 

observed water levels, whereas simulated water levels for the 

deep well are much closer to observed levels. At the Pomona 

nest (010776 and 010775; fig. 32), simulated water levels at 

the shallow well are as much as 15 ft lower than the observed 

water levels, whereas simulated water levels for the intermediate well match the observed water levels fairly well. Well 

010775 (intermediate) is in the area where the leaky confining 

unit in the Kirkwood-Cohansey aquifer system is present, but 

both of the wells at the Pomona nest are screened above the 

leaky confining unit. Statistics for the residuals for these wells 

are listed in table 10. The absolute value of the mean error at 

six of the nine long-term wells in the Kirkwood-Cohansey 

aquifer system is less than 5 ft. The Mount Obs well (050570), 

the Penn SF shallow well (050628), and the Pomona shallow 

well (010776) have mean errors with absolute values greater 

than 5 ft, but the seasonal trends match fairly well. This is 

considered acceptable because other wells in the area matched 

magnitude and trends quite well and this area was not the 

focus of the scenarios.

Atlantic City 800-Foot Sand

Maps of potentiometric surface and residuals for the 

Atlantic City 800-foot sand in spring 2005 and fall 2006 are 

shown in figures 33 and 34, respectively. Graphs of simulated and observed heads are shown in figure 29B. Simulated 

and observed water levels in spring 2005 match well, and 

the heads plot along 1:1 line in figure 29B. Some observed 

heads in fall 2006 generally plot high along the 1:1 line in 

figure 29B. These wells are shown in figure 34 in areas along 

the coast near and north of Ocean City where simulated water 
44 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

GLOUCESTER ATLANTIC

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

EXPLANATION

Boundary of Great Egg-Mullica model area representing the KirkwoodCohansey aquifer system

SIMULATED WATER-TABLE CONTOUR—Shows altitude of simulated water 

level. Interval is 20 feet. Datum is National Geodetic Vertical Datum of 1929

MEASURED WATER-TABLE CONTOUR—Shows altitude of measured water 

level. Interval is 20 feet. Datum is National Geodetic Vertical Datum of 1929

RESIDUAL IN LAYER 1 RESIDUAL IN LAYER 3

Less than -5

-5 − 5

Greater than 5

#* Less than -5

#* -5 − 5

#* Greater than 5

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

40

60

80

40

20

60

140

100

120

100

140

120

100

100

80

40

60

20

120

100

140

160

100

20

20

160

60

60

0

40

20

60

80

100

120

140

160

0

140

120

0

40

0

0

0 0

0

20

100

140

0

0

60

0

20

100

0

0

40

60

140

80

120

0

100

0

0

60

60

40

20

80

80

60

60

60

40 40

60

80

80

100

120

60

40

40

20

20

40

40

20

40

20

40

60

80

#*

#*

#* #* #* #*

#*

#*

#*

#*

#*

#* #*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#* #* #*

#*

#*

#*

#*

#*

3

-1

1.1

0.7

2.9

3.2

3.4

1.6

1.1

2.9

2.2

2.8

-2.6

-1.9

-0.6

-2.9

-0.6

-1.7

-1.3 -0.4

-4.1

-2.9

-6

-9

-5.4

-6.2

-7.1

-7.2

-7.6

-6.5

-7.6

-8.1 -6.2

-11.2

-11.2

-29.3

-14.1

-11.6

-5.2

-7.7

-37.7

-10.5

-11.5

-22.3

-33.1

4

1 1

-1

-4

1.6

3.1

0.9

3.9

0.9

3.7

1.3

4.7

0.6 0.5 3.6

3.6

0.1

2.3

1.6

1.4

1.5

0.3

3.3

0.3

2.7

0.4

2.8

-0.7

-3.8

-1.9

-0.5

-2.7

-3.9

-4.2

-1.1 -4.3

-0.8

-3.1

-0.2

-2.8

-0.5

-2.2

-0.7

-0.6

-0.7 -0.6

-3.1

-4.2

-2.4 -3.1

-2.9

-3.9

-3.9

-0.4

-3.6

7

22

7.9

5.8

5.8

6.4

14.4

9.6

6.2 5.4

9.4

7.7

13.4

4.1

-2.7

-2.1

2.9

0.2

ATLANTIC OCEAN

Figure 27. Simulated and measured water-level contours and residuals in the Kirkwood-Cohansey aquifer system, southeastern 

New Jersey, spring 2005.
Groundwater Flow Model 45

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

 

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

EXPLANATION

Boundary of Great Egg-Mullica model area representing the KirkwoodCohansey aquifer system

SIMULATED WATER-TABLE CONTOUR—Shows altitude of simulated water 

level. Interval is 20 feet. Datum is National Geodetic Vertical Datum of 1929

MEASURED WATER-TABLE CONTOUR—Shows altitude of measured water 

level. Interval is 20 feet. Datum is National Geodetic Vertical Datum of 1929

RESIDUAL IN LAYER 1 RESIDUAL IN LAYER 3

Less than -5

-5 − 5

Greater than 5

#* Less than -5

#* -5 − 5

#* Greater than 5 40

60

80

40

20

60

140

100

120

100

140

120

100

100

80

40

60

20

120

140

160

100

20

20

160

60

60

0

40

20

60

100

120

140

0

120

0

40

0

0

0 0

0

20

100

140

0

0

60

0

20

100

0

0

140

0

100

0

0

60

40

20

80

80

60

60

60

40 40

60

80

80

100

120

40

40

20

20

40

40

20

40

20

40

60

80

160

60 40

20

#*

#*

#* #* #* #*

#*

#*

#*

#*

#* #*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#*

#* #* *#

#*

#*

#*

#*

#*

#*

3.7

-2.2

1.1

1.4

1.4

3.2

2

2.2

2.2

1.5

3.6

3.2

-3.6

-1.9

-0.7

-1

-0.8

-1.7

-1.8 -1.6

-6.4

-3.1

-5.9

-9.9

-4.1

-6.4

-8.7

-5.8

-7.5

-7.6

-5.9 -5.2

-11.3

-10.9

-27.3

-13.5

-10.5

-4.4

-7.3

-35.7

-5.6

-9.2

-20.3

-31.6

3.8

0.1 0.2

-2.3

-1.7

0.3

2.8

0.5

2.7

0.9

5.4

1.9

1.5

0.3

2.1

3.2

1.5

3

2.3

1.6

4.9

0.7

2.4

-3.4

2.5

-3.5

-1.7

-4.2

-2.2

-3.3

-4.3

0.5 -3.5

-1.7

-1.8

-3.9

-2.4

-3.3

-0.6

-1.4

-1.5 -1.3

-2.8

-2.2

-2.4

-3.9

-3.2

-3.2 -0.9

-3.2

5.4

12.4

8.1

6.4

1.8

10.5

8.7

6.4 3.2

9.6

-27

12.9

-2.3

0.9

1.8 -1.5

ATLANTIC OCEAN

Figure 28. Simulated and measured water-level contours and residuals in the Kirkwood-Cohansey aquifer system, southeastern 

New Jersey, fall 2006.
46 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

-50

200

150

100

50

0

-50

-150 -100 0 50 100 150

Simulated water level, in feet

B. Fall 2006

-100

-150

200

Kirkwood-Cohansey aquifer 

system

Atlantic City 800-foot sand 

1-1 line

EXPLANATION 0

0

200

150

100

50

-50

-100

-100 -50 50 100 150 200

A. Spring 2005

Observed water level, in feet

Figure 29. Simulated and observed water levels for the Kirkwood-Cohansey aquifer system and the Atlantic City 800-foot sand, 

southeastern New Jersey in A, spring 2005 and B, fall 2006.
Groundwater Flow Model 47

< -15 -15 − -10 -10 − -5 -5 − 0 0 − 5 5 − 10 10 − 15 > 15

100

90

80

70

60

50

40

30

20

10

0

Residuals, in feet

Number of residuals

35

30

25

20

15

10

5

0

Number of residuals

< -15 -15 − -10 -10 − -5 -5 − 0 0 − 5 5 − 10 10 − 15 > 15

Residuals, in feet

A. Kirkwood-Cohansey aquifer system

B. Atlantic City 800-foot sand

Figure 30. Residuals of water levels for A, Kirkwood-Cohansey aquifer system and B, Atlantic City 800-foot sand, southeastern New 

Jersey, 2005 and 2006. (<, less than; >, greater than)

levels are as much as 10 ft lower than observed heads. For 

spring 2005, these water levels match fairly well. A close 

match between simulated and observed water levels in this 

area is one of the main reasons that the calibrated vertical 

hydraulic conductivity of the Atlantic City 800-foot sand is 

low. Hydrographs of wells in the Atlantic City 800-foot sand 

are shown in figure 32. The largest residuals are for the Burke 

Ave Obs well (010702), which is located near the area of 

simulated low heads in fall 2006. In well 010702, simulated 

heads are higher than observed heads, but simulated water 

levels at many wells located south of this location are lower 

than observed water levels. Well 010703 is located near 

wells 010775 and 010776 in the Kirkwood-Cohansey aquifer 

system. Mean errors for residuals for the wells with longterm hydrographs and completed in the Atlantic City 800-foot 

sand are shown in table 10. The mean errors are reasonable 

especially given the seasonal water-level fluctuations at these 

wells. The histogram of residuals in the Atlantic City 800-foot 

sand in spring 2005 and fall 2006 is shown in figure 30B. 

Most of the residuals fall within the +/- 5-foot range, and the 

distribution of residuals does not indicate any systematic bias 

in simulated heads. 
48 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Water-level altitude, in feet above NGVD 29

50

48

46

44

42

40

38

36

34

32

30

50

48

46

44

42

40

38

36

34

32

30

65

63

61

59

57

55

53

51

49

47

45

100

98

96

94

92

90

88

86

84

82

80

130

128

126

124

122

120

118

116

114

112

110

55

53

51

49

47

45

43

41

39

37

35

80

78

76

74

72

70

68

66

64

62

60

85

83

81

79

77

75

73

71

69

67

65

1999 2000 2001 2002 2003 2004 2005 2006 1999 2000 2001 2002 2003 2004 2005 2006

050409 Atsion Shallow, CKKD 050684 Butler Place 2 Obs, CKKD

050408 Atsion Deep, CKKD 050570 Mount Obs, CKKD

151213 UND06, CKKD 050630 Penn SF Deep, CKKD

010256 Scholler, CKKD 050628 Penn SF Shallow, CKKD

EXPLANATION

Observed water level

Simulated water level

Figure 31. Hydrographs of simulated and observed water levels in selected wells updip in the Kirkwood-Cohansey aquifer system, 

southeastern New Jersey, 1999–2006.
Groundwater Flow Model 49

Water-level altitude, in feet above or below NGVD of 1929

-15

-20

-25

-30

-35

-40

-45

-50

-55

-60

-65

25

20

15

10

5

0

10

5

0

-5

-10

-15

-25

-30

-35

-45

-55

-65

-70

-75

-70

-75

-80

-85

-90

-95

-100

-105

-110

-115

-120

-40

-45

-50

-55

-60

-65

-70

-75

-80

-85

-90

010180 Oceanville, AC800 010703 Pomona Deep, AC800

010776 Pomona Shallow, CKKD 010702 Burk Ave Obs, AC800

010775 Pomona Intermediate, CKKD 010578 Jobs Point, AC800

EXPLANATION

Observed water level

Simulated water level

-40

-50

-60

1999 2000 2001 2002 2003 2004 2005 2006 1999 2000 2001 2002 2003 2004 2005 2006

Figure 32. Hydrographs of simulated and observed water levels in selected wells downdip in the Kirkwood-Cohansey aquifer system 

and Atlantic City 800-foot sand, southeastern New Jersey, 1999–2006.
50 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 10. Statistics for residuals at wells with long-term 

hydrographs, southeastern New Jersey.

[USGS, US Geological Survey, Aquifer: 122KRKDL, Atlantic City 

800-foot sand; 121CKKD, Kirkwood-Cohansey aquifer system; RMS, 

Root mean square error]

USGS 

well 

number

Aquifer

Number 

of observations

Mean 

error

Mean 

absolute 

error

RMS

010180 122KRKDL 102 -0.7 2.7 3.2

010578 122KRKDL 104 -0.9 3.5 4.1

010702 122KRKDL 62 7.8 8.3 10.3

010703 122KRKDL 100 4.2 4.7 5.9

Average 2.6 4.8 5.9

010256 121CKKD 105 0.7 1 1.2

010775 121CKKD 43 -2.8 5.3 6.6

010776 121CKKD 63 -12 12 12.1

050408 121CKKD 45 -3.5 3.5 3.6

050409 121CKKD 56 -0.5 0.8 0.9

050570 121CKKD 71 -7.9 7.9 8.1

050628 121CKKD 68 -7.7 7.7 7.8

050630 121CKKD 76 -2.2 2.2 2.4

050684 121CKKD 81 -0.8 1.2 1.5

151213 121CKKD 103 -4 4 4.1

Average -4.1 4.6 4.8

Calibration to Base-Flow Values

Hydrographs of simulated base flows were compared to 

hydrographs of observed base flows at streamgaging stations 

and at low-flow partial-record stations. Simulated base-flow 

values were calculated for each stress period from 1998 

to 2006 by adding the simulated values from the RIV and 

DRN packages model output. Hydrographs of simulated and 

observed base flows are shown in figures 35 to 37. The subbasins in which the streamgaging stations are located are shown 

in figure 18. Statistics for the monthly residuals for the subbasins with base-flow hydrographs shown in figures 35 to 37 are 

listed in table 11. The mean error and mean absolute error give 

an indication of the mean differences between the simulated 

and observed base flows. The root mean square (RMS) error is 

the square root of the average of the squared differences. The 

largest RMS errors are associated with the large streamflows 

that occur in the large subbasins. A 10-percent difference in a 

large subbasin will result in a larger RMS error than a 10-percent difference in a small subbasin. For subbasins where winter base flow is high, the matching of simulated and observed 

base-flow hydrographs was focused on the lower base-flow 

part of the hydrograph so that the model was best calibrated 

to low-flow conditions in the summer. Base-flow hydrographs 

for the six streamgaging stations within the study area are 

shown in figure 35. Streamgaging stations used for calibrating 

simulated base flows are located in the updip part of the study 

area because the large streams in the downdip part are tidal. 

Observed base flows in the updip part of the modeled area are 

considered to be the best data for use in calibration. Note that 

the hydrograph at the Batsto at Batsto streamgage (01409500) 

extends only through 2004 because the streamgage was discontinued. Base-flow hydrographs for the updip subbasins are 

shown in figure 36. Most of the simulated and observed hydrographs match fairly well and have moderate to small RMS 

errors. The hydrograph for station 01411170 (fig. 36; table 11) 

has the highest RMS error of all stations. This high RMS error 

is primarily due to high observed base flow during the winters 

of 2003 to 2006 that occurred in several subbasins in the 

study area, but the RMS stands out in this subbasin because 

of the larger flows and residuals. Base-flow hydrographs for 

the downdip subbasins are shown in figure 37. Because, in 

general, these are small subbasins with small flows, the RMS 

values are also small. 

In general, the simulated base flows match the observed 

base flows in all 22 hydrographs fairly well. Complicated 

surface-water drainage systems result in some observed baseflow values that are anomalous and were not simulated in the 

model. The observed base flows in Sleeper Branch at Batsto 

(01409406) are lower than would be expected on the basis of 

the size of the subbasin, whereas observed base flows at the 

Mullica near Batsto station (01409400) are slightly higher than 

would be expected. This difference is due to diversion ditches 

that contribute substantial flow from the Sleeper Branch into 

the Mullica River Basin (U.S. Geological Survey, 2007). 

The hydrographs for the Batsto at Batsto station (01409500) 

match well, whereas the simulated hydrograph for Mullica 

near Batsto 01409400 is low, and the simulated hydrograph 

for Sleeper Branch (01409406) is high. Instead of attempting 

to match simulated and observed base flows at each subbasin, 

which would require more zones for parameters in the model, 

relatively uniform values for parameters were used throughout 

the model. Hydrographs at adjacent subbasins were calibrated 

to obtain the best overall fit for the area. During calibration, 

matching the fit at the six streamgaging stations was given 

priority over matching the fit at the low-flow partial-record 

stations. The model calibration using the base-flow hydrographs was most influenced by the streambed vertical hydraulic conductivities and recharge. 

Sensitivity Analysis

A sensitivity analysis was conducted on the calibrated 

model to evaluate the relative effects of the various parameters. The sensitivity of hydraulic heads and streamflow to 

the model parameters was calculated using the parameterestimation software UCODE-2005 (Poeter and others, 2005). 

Composite scaled sensitivities (CSS) were calculated for all 

31 parameters using observed heads from 1998, 2003, 2005, 

and 2006; the observed heads from the monthly hydrographs 

for the New Jersey Water-level Monitoring Network sites; 
Groundwater Flow Model 51

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

1

0.8

3.9

0.8

2.8

0.4

0.5

1.6

0.3

1.6

3.8

3.5

0.8

1.6

3.7

4.4

0.4

-2.4

-0.4

-0.7

-3.4

-1.4

-0.6

-7.1 -7.4

-33.8

16

7.7

12.2 0

-10

-20

-30

-40

10

20

-50

30

-60

40

50

-70

60

40

30

10

50

20

3.3

0.8 10.5

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Updip extent of the Atlantic City 800-foot sand

(From Zapecza, 1989)

SIMULATED POTENTIOMETRIC SURFACE—Shows 

altitude at which water level would have stood in 

tightly cased wells. Interval is 10 feet. Datum is 

National Geodetic Vertical Datum of 1929

RESIDUAL 

Less than -5

-5 − 5

Greater than 5

40

EXPLANATION

ATLANTIC 

OCEAN

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

Figure 33. Simulated potentiometric surface of the Atlantic City 800-foot sand and water-level residuals, southeastern New Jersey, 

spring 2005.
52 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

0

-10

-20

-30

-40

-50

10

20

30

-60

-70

-80

-90

40

50

-100

-80

10

20

40

30

-90

0

0.3

-2.4

-3.2

-0.3

-4.4

-1.1 -2.3

-0.6

-10.1

-7.1

-5.3

-5.5

-8.2

-10.2

-10.8

7.6

5.8

7.2

5.2

5.1

16.6

17.3

-10.1

-10.8

18.5

-43

-7.4

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

Updip extent of the Atlantic City 800-foot sand

(From Zapecza, 1989)

SIMULATED POTENTIOMETRIC SURFACE—Shows 

altitude at which water level would have stood in 

tightly cased wells. Interval is 10 feet. Datum is 

National Geodetic Vertical Datum of 1929

RESIDUAL 

Less than -5

-5 − 5

Greater than 5

40

EXPLANATION

ATLANTIC OCEAN

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

Figure 34. Simulated potentiometric surface of the Atlantic City 800-foot sand and water-level residuals, southeastern New Jersey, 

fall 2006.
Groundwater Flow Model 53

Base flow, in cubic feet per second

250

225

200

175

150

125

100

75

50

25

0

100

90

80

70

60

50

40

30

20

10

0

01409400 Mullica near Batsto 01409500 Batso at Batsto

01411000 Great Egg at Folsom 01410150 Esat Branch Bass River

01411300 Tuckahoe River 01410000 Oswego River as Harrisville

EXPLANATION

Observed base flow

Simulated base flow

1999 2000 2001 2002 2003 2004 2005 2006 1999 2000 2001 2002 2003 2004 2005 2006

250

225

200

175

150

125

100

75

50

25

0

250

225

200

175

150

125

100

75

50

25

0

250

225

200

175

150

125

100

75

50

25

0

250

225

200

175

150

125

100

75

50

25

0

1999 2000 2001 2002 2003 2004

Figure 35. Hydrographs of simulated and observed base flows at selected streamgaging stations, southeastern New Jersey, 

1999–2006.
54 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Base flow, in cubic feet per second

100

90

80

70

60

50

40

30

20

10

0

140

120

100

80

60

40

20

0

50

45

40

35

30

25

20

15

10

5

0

1,200

1,100

1,000

900

800

700

600

500

300

100

0

140

120

100

80

60

40

20

0

270

245

220

195

170

145

120

95

70

45

20

50

45

40

35

30

25

20

15

10

5

0

100

90

80

70

60

50

40

30

20

10

0

1999 2000 2001 2002 2003 2004 2005 2006 1999 2000 2001 2002 2003 2004 2005 2006

01409406 Sleeper Branch at Batsto 01409730 West Branch Wading, nr Chatsworth

01409411 Nescochague Creek at Pleasant Mills 01409815 West Branch Wading, at Maxwell

01411170 Great Egg Harbor at Mays Landing 01411140 Deep Run at Weymouth

01409416 Hammonton Creek at Wescoatville 01410200 West Branch Bass, nr New Gretna

EXPLANATION

Observed base flow

Simulated base flow

400

200

Figure 36. Hydrographs of simulated and observed base flows at selected updip low-flow partial-record stations, southeastern 

New Jersey, 1999–2006.
Groundwater Flow Model 55

Base flow, in cubic feet per second

50

45

40

35

30

25

20

15

10

5

0

100

90

80

70

60

40

20

0

100

90

80

70

60

50

40

30

20

10

0

50

45

40

35

30

25

20

15

5

0

50

45

40

30

20

10

5

0

50

45

40

35

30

25

20

15

10

5

0

50

45

40

35

30

25

20

15

10

5

0

50

45

40

35

30

25

20

15

10

5

0

1999 2000 2001 2002 2003 2004 2005 2006 1999 2000 2001 2002 2003 2004 2005 2006

01409575 Landing Creek 01410215 Clarks Mill Stream

01411200 Babcok Creek at Mays Landing 01410225 Morses Mill Stream

01411302 Mill Creek nr Steelmantown 01411250 English Creek nr Scullville

01411220 South River nr Belcoville 01411305 Mill Branch nr Northfield

EXPLANATION

Observed base flow

Simulated base flow

10

35

25

15

50

30

10

Figure 37. Hydrographs of simulated and observed base flows at selected downdip low-flow partial-record stations, southeastern 

New Jersey, 1999–2006.
56 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 11. Statistics for base-flow residuals at surface-water stations, southeastern New Jersey.

[ft3/s, cubic foot per second; Type: GS, gaging station; LF, low-flow partial-record station; RMS, Root mean square error]

Station

number Station name Type

Drainage area, 

in square 

miles

Mean 

error

(ft3

/s)

Mean 

absolute 

error

(ft3

/s)

RMS

(ft3

/s)

01409400 Mullica River near Batsto NJ GS 46.7 -51.3 52.2 69.7

01409406 Sleeper Branch at Batsto NJ LF 36.2 17.3 17.3 18.2

01409411 Nescochague Creek at Pleasant Mills NJ LF 43.7 -24.1 25.6 33.7

01409416 Hammonton Creek at Wescoatville NJ LF 9.57 -7.2 7.3 8.9

01409500 Batsto River at Batsto NJ GS 67.8 -32.5 35.0 47.1

01409575 Landing C at Phila Ave at Egg Harbor City NJ LF 4.86 -5.2 5.2 5.8

01409730 West Branch Wading River near Chatsworth NJ LF 44.8 4.9 15.3 19.5

01409815 West Branch Wading River at Maxwell NJ LF 85.9 -24.7 34.0 46.4

01410000 Oswego River at Harrisville NJ GS 72.5 -2.4 16.2 22.5

01410150 East Branch Bass River near New Gretna NJ GS 8.11 -0.8 3.2 4.6

01410200 West Branch Bass River near New Gretna NJ LF 6.54 -5.2 5.3 6.3

01410215 Clarks Mill Stream at Port Republic NJ LF 8.61 -8.1 8.2 9.3

01410225 Morses Mill Stream at Port Republic NJ LF 8.25 -1.7 3.9 5.1

01411000 Great Egg Harbor River at Folsom NJ GS 57.1 -28.4 30.9 38.4

01411140 Deep Run at Weymouth NJ LF 20 -8.2 10.0 13.9

01411170 Great Egg Harbor R at Mays Landing NJ LF 205 -185.6 206.3 290.3

01411200 Babcock Creek at Mays Landing NJ LF 20 -9.8 11.3 15.6

01411220 South River near Belcoville NJ LF 20.4 -13.8 13.9 18.1

01411250 English Creek near Scullville NJ LF 3.8 -2.1 2.3 2.6

01411300 Tuckahoe River at Head of River NJ GS 30.8 -13.2 14.3 21.4

01411302 Mill Creek near Steelmantown NJ LF 3.82 -3.6 3.6 6.7

01411305 Mill Branch near Northfield NJ LF 7.47 -3.8 4.5 5.2

Average -18.0 23.4 31.5

and the observed base flows from the monthly hydrographs. 

The composite scaled sensitivities are shown in figure 38A. 

These CSS values show, overall, how sensitive all the observations in the model are to changes in each of the parameters. 

The parameters with the largest CSS values are the horizontal 

hydraulic conductivities for the Atlantic City 800-foot sand 

(ac800k) and the deep part of the unconfined KirkwoodCohansey aquifer system (KW-k). The next four most sensitive parameters are a mixture of vertical/horizontal hydraulic 

conductivities for the Kirkwood-Cohansey aquifer system 

(cnsy-k1) and recharge in three of the four areal recharge 

zones (rechz4, rechz3, and rechz1). The hydraulic conductivity of the Kirkwood-Cohansey aquifer system downdip 

(cnsy-k2 and cnsy-k3) and the recharge in the southern part of 

the study area (rechz2) are less sensitive than the other parameters of the same type. Normalized group composite scaled 

sensitivities for observation groups show the relative sensitivities of each parameter to the different types of observation 

data (Kirkwood-Cohansey water levels, Atlantic City 800-foot 

sand water levels, or base-flow observations) (fig. 38B). Figure 38B shows normalized group composite scaled sensitivities. The normalized CSS for each group of observations is the 

CSS for the group squared, times the number of observations 

for the group, divided by the total number of observations. 

When the group CSS values are normalized in this way, the 

total of the CSS values for the three groups (Kirkwood-Cohansey water levels, Atlantic City 800-foot sand water levels, and 

base-flow observations) equals the CSS values for the entire 
Groundwater Flow Model 57

100

90

80

70

60

50

40

30

20

10

0

1,200

1,000

800

600

400

200

0

B. Normalized group composite scaled sensitivity

A. Composite scaled sensitivity ac800k KW-k rechz4 rechz3 cnsy-k1 rechz1ss drnk4 rechz5 aquifer

cnsy-k3

SY

cu-k

cnsy-k2

drnk1

rio-k

rechz2

kvdclay-l

kvcnsyclay

rivk4

kvdclay-u

kv800semi

drnk2drnk3

kv-riosemi

rechz6

rivk2

kv-vertcon

rivk1

kv800clay

rivk3

Normalized group composite scaled 

sensitivity, in percent

Composite scaled sensitivity

Parameters

ac800k

KW-k

rechz4rechz3

cnsy-k1

rechz1

ss

drnk4

rechz5

aquifer

cnsy-k3

SY

cu-k

cnsy-k2

drnk1

rio-k

rechz2

kvdclay-l

kvcnsyclay

rivk4

kvdclay-u

kv800semi

drnk2drnk3

kv-riosemi

rechz6

rivk2

kv-vertcon

rivk1

kv800clay

rivk3

Kirkwood-Cohansey aquifer 

system, observed water levels

Atlantic City 800-foot sand, 

observed water levels

Observed base flow

EXPLANATION

Figure 38. A, composite scaled sensitivities of model parameters and B, normalized group composite scaled sensitivities for the Great 

Egg–Mullica model. (Parameters are defined in table 8)

set of observations. The parameters ac800k, SS, kv-riosemi,

rio-k, cu-k, kvdclay-l, kvdclay-u, and kv800clay are almost 

completely controlled by observed heads in the Atlantic City 

800-foot sand. Parameters that are at least 50 percent influenced by the observed heads in the unconfined aquifer are 

rechz4, drnk1, SY, cnsy-k3, rivk1, rivk3, and rechz1. Twentyfour of the 31 parameters are affected more by observed heads 

in the confined aquifers than by observed heads in the unconfined system. This is probably due to the updip connection 

between the two major aquifers and the fact that the source 

of most of the water to the Atlantic City 800-foot sand is the 

updip part of the Kirkwood-Cohansey aquifer system.

Flow Budgets

Groundwater flow budgets were created for spring 2005 

and fall 2006 and for the entire model calibration period 1998 

to 2006. Budgets are shown for the confined Atlantic City 

800-foot sand and for the entire Kirkwood-Cohansey aquifer 

system. The flow budgets for spring 2005 and fall 2006 used 

for model calibration are shown in figure 39. These graphs 

are used for comparison of the contributions from different parts of the groundwater flow system during the spring 

and fall. Note that scales for the budgets for the unconfined 

and confined aquifer system are different. Much more water 
58 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

0

3,000,000

2,000,000

1,000,000

-1,000,000

-2,000,000

-3,000,000

-4,000,000

Wells

Boundary flows

Updip

Overlying

Storage

B. Atlantic City 800-foot sand

Flow, in cubic feet per day

0

200,000,000

150,000,000

100,000,000

50,000,000

-50,000,000

-100,000,000

-150,000,000

Recharge

Wells

Rivers

Bay and ocean

Storage

Drains

Atlantic City 800-foot sand

Unconfined Kirkwood

A. Unconfined Kirkwood-Cohansey aquifer system

Spring 05 Fall 06

EXPLANATION

Spring 05 Fall 06

EXPLANATION

Figure 39. Simulated flow budgets for the A, unconfined Kirkwood-Cohansey aquifer system and B, Atlantic City 800-foot sand, 

southeastern New Jersey, spring 2005 and fall 2006.
Groundwater Flow Model 59

moves through the unconfined aquifer system than through 

the Atlantic City 800-foot sand. The flow component Atlantic 

City 800-foot sand in the Kirkwood-Cohansey aquifer system 

budget is equivalent to the sum of the flow components Updip 

and Overlying in the Atlantic City 800-foot sand budget. The 

Atlantic City 800-foot sand component represents flow from 

the unconfined Kirkwood-Cohansey aquifer to the confined 

Atlantic City 800-foot sand and is a minor part of the flow 

budget for the unconfined aquifer. However, the components 

Updip and Overlying in the Atlantic City 800-foot sand budget 

represent most of the flow into the confined aquifer. The major 

input to the flow budget for the Kirkwood-Cohansey aquifer system is the Recharge component. Most of the recharge 

received is discharged to Drains or Rivers components. The 

net discharge to the Wells component is relatively small. The 

flows into and out of constant heads represent flow to or from 

constant head cells representing the Bay and (or) Ocean components in the model. The Unconfined Kirkwood component 

represents flow from the shallow Kirkwood-Cohansey aquifer 

system into the deep layers 7 to 9 that represent the Kirkwood 

Formation. Most of the water that moves into the Kirkwood 

Formation then flows back to the upper model layers. A small 

portion of the water that flows into the Kirkwood Formation 

goes to the confined Atlantic City 800-foot sand. Recharge is 

greater in May 2005 than in September 2006, and the flow to 

the sink components (flow less than zero) is also reduced in 

the fall. The major input into the Atlantic City 800-foot sand is 

flow from the unconfined Kirkwood-Cohansey aquifer system 

updip (Updip component). The Boundary Flows component 

represents boundary flows into the confined aquifer from 

both lateral and vertical flow boundaries. This is a substantial 

source of water to the aquifer in the study area. The major outflow from the confined aquifer is discharge to pumped wells. 

Withdrawals from the aquifer are greater in the fall than in the 

spring to meet higher water demands. The flow from the updip 

unconfined aquifer is also greater in the fall.

The simulated-transient flow budgets for 1999 to 2006 

are shown in figure 40. These graphs show the transient 

effects of the major components of the flow system, including 

changes in storage during the calibration period. In the Kirkwood-Cohansey aquifer system, recharge varied monthly and 

was greatest in the winter to early spring. Flow out to drains 

also was highest at these times (fig. 40A). Water is released 

into the aquifer from storage in the summer when recharge is 

low, and water goes into storage from the aquifer in the summer. In the Atlantic City 800-foot sand, withdrawals (Wells) 

are seasonal and are greatest in the summer and fall (fig. 40B). 

Flow released from storage also was greatest in the summer. 

Flow into storage occurred in the winter. Flow into the aquifer 

from updip and overlying parts of the Kirkwood-Cohansey 

aquifer system varied slightly throughout the year but did not 

change as quickly as the storage. 

Limitations of the Model

Before the results of the groundwater flow model can 

be used effectively, it is important to understand the model 

limitations. The accuracy of the model is limited because of 

the simplification of components of the aquifer system, spatial 

and temporal discretization, and assumptions inherent in the 

governing equations used in the model. Model accuracy is also 

limited by the number of model layers, accuracy of boundary 

conditions, accuracy of model input data, distribution of zoned 

parameters, and parameter sensitivity. Although a model may 

be calibrated to the available data, the particular values for the 

simulated parameters may not form a unique representation of 

the system.

The purpose of the Great Egg-Mullica model is to represent the groundwater flow system in the Great Egg Harbor 

and Mullica River Basins in the Kirkwood-Cohansey aquifer 

system and the Atlantic City 800-foot sand and to represent 

the interaction between the two flow systems. Therefore, a 

regional scale was used for the model. The size of the model 

grid cells is adequate for a regional representation of streams, 

but the model is not intended to simulate detailed groundwater/surface-water interactions. Additionally, a generalized 

hydrogeologic framework was used to represent the system. 

Some clay units that may be local confining units and may 

locally affect the groundwater flow system were not included. 

The boundaries of the model were selected to be distant 

from the main area of interest in Atlantic County and from the 

area where the confined Atlantic City 800-foot sand connects 

with the unconfined Kirkwood-Cohansey aquifer system. The 

assumption that the groundwater flow boundaries coincide 

with the surface-water boundaries of the Great Egg Harbor 

and Mullica River Basins is appropriate given the main area 

of interest. However, care is needed when using the model 

results for areas near the updip boundaries of the subbasins, 

even though the heads were simulated reasonably well in these 

areas. The boundaries for the confined Atlantic City 800-foot 

sand were taken from the New Jersey RASA model, so some 

limitations of that model affect the simulation of the boundaries of this model. Because the RASA model was temporally 

discretized at an annual scale, the boundary flows into the 

Great Egg-Mullica model may not be representative of actual 

seasonal changes in these flows. Boundary flows into the 

model may be smaller than actual flows during the summer 

months because the RASA model uses annual withdrawals that 

are smaller than the heavy summer withdrawals in the area. 

This may be the reason simulation of the cone of depression 

south of Atlantic City in the Atlantic City 800-foot sand was 

difficult. Because the RASA model does not include saltwater intrusion and the saltwater was not simulated in the Great 

Egg-Mullica model, the downdip boundary of the Atlantic 

City 800-foot sand offshore is uncertain. For the simulation 

of future scenarios, it was assumed that land use and climatic 

conditions remain the same as those during the model calibration period. 
60 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Jan-99

July-99

Jan-00

July-00

Jan-01

July-01

Jan-02

July-02

Jan-03

July-03

Jan-04

July-04

Jan-05

July-05

Jan-06

July-06

3,000,000

2,000,000

1,000,000

0

-1,000,000

-2,000,000

-3,000,000

-6,000,000

-4,000,000

-5,000,000

Atlantic City 800-foot sand

Storage

Updip

Overlying

Specified Flows

Wells

EXPLANATION

4.00E+08

3.00E+08

2.00E+08

1.00E+08

0.00E+00

-1.00E+08

-2.00E+08

-3.00E+08

Unconfined Kirkwood-Cohansey aquifer system

Flow, in cubic feet per day

Recharge

Storage

Drains

EXPLANATION

Figure 40. Simulated transient flow budgets for the A, unconfined Kirkwood-Cohansey aquifer system and B, Atlantic City 800-foot 

sand, southeastern New Jersey, 1999–2006.
Simulation and Results of Withdrawal Scenarios 61

Simulation and Results of Withdrawal 

Scenarios

Simulations of base-flow depletion were conducted for 

several scenarios and results were compared with base-flow 

depletion criteria characterized as part of this study to determine where and when base-flow deficits may be occurring or 

may be expected to occur in the future. Results of the simulations were evaluated using Hydrologic Unit Code 11 (HUC11) 

subbasins delineated within the study area.

The locations of the HUC11 subbasins are shown in 

figure 41. The first 6-digits of the HUC designate the region, 

major river, and accounting unit, and are the same (020403) 

for all HUCs in the study area. The next two digits represent a 

subdivision of the accounting unit; 01 represents the Mullica 

River Basin, and 02 represents the Great Egg Harbor River 

Basin. The last three digits represent the watershed. The interaction between HUC11 subbasins and the underlying Atlantic 

City-800-foot sand is shown in figure 41 as updip, mixed, 

and downdip. The red line on the map in figure 41 shows the 

extent of the confining unit overlying the Atlantic City 800-

foot sand. Subbasins through which this red line passes are 

designated as “mixed.” The unconfined Kirkwood-Cohansey 

aquifer system underlies parts of some subbasins, and where 

the Atlantic City 800-foot sand is present, parts of subbasins 

are underlain by confined and unconfined aquifers. The subbasins in the northern part of the study area are designated 

“updip,” and they are entirely underlain by the unconfined 

Kirkwood-Cohansey aquifer system. In the eastern part of 

the study area subbasins are designated “downdip.” These 

subbasins are underlain by the shallow flow system within 

the Kirkwood-Cohansey aquifer system. These designations 

were made based on the results of the scenario simulations and 

represent where the model behaved in a similar manner. The 

interaction between the Kirkwood-Cohansey aquifer system 

and the confined Atlantic City 800-foot sand beneath the 

mixed subbasins is an important finding of these simulations. 

The terms “updip,” “downdip,” and “mixed” are used throughout this section to discuss the simulation results.

Approach

Seven scenarios were simulated to assess base-flow 

depletion that could occur from different groundwater withdrawal situations (table 12). Scenario 1 represents conditions 

from 1998 to 2006 if there were no groundwater withdrawals. 

Scenarios 2 to 4 represent average 1998–2006 withdrawals, full-allocation withdrawals, and withdrawals projected 

for 2050 demand. These scenarios are intended to identify 

subbasins where deficits may already be occurring or where 

deficits may occur under future conditions; these scenarios 

are referred to as the basic scenarios. The final three scenarios 

(5–7) are variations of the Average, Full Allocation, and 2050 

Demand scenarios for which the withdrawals were modified 

sequentially to represent management strategies that attempt 

Table 12. Scenarios simulated using the Great Egg-Mullica 

model.

Scenario

1 No withdrawals

Basic—current and future conditions

2 Average

3 Full Allocation

4 2050 Demand

Adjusted—withdrawals adjusted to eliminate deficits

5 Adjusted Average

6 Adjusted Full Allocation

7 Adjusted 2050 Demand

to eliminate the base-flow deficits. For scenarios 2 to 7, the 

base-flow depletion was compared with monthly criteria determined by NJDEP. Base-flow depletion was calculated for each 

scenario by subtracting the base flow for each HUC11 subbasin from the base flow that would have occurred during the 

simulation period had there been no groundwater withdrawals. 

HUC11 subbasins and time periods when the base-flow depletion is greater than the monthly available water are considered 

to be in deficit.

Simulation of the final three scenarios (5–7) is an attempt 

to resolve deficits by sequentially simulating three alternative 

management approaches; these scenarios are referred to as the 

adjusted scenarios. The three approaches are designated as: 

Tier 1, moving withdrawals to the deeper part of the Kirkwood-Cohansey aquifer; Tier 2, all changes from Tier 1 and 

shifting demand seasonally between shallow and deep aquifers 

for any subbasins still in deficit (seasonal-conjunctive use); 

and Tier 3, all changes from Tier 1 and Tier 2 plus reduction 

of withdrawals for any subbasins still in deficit. Simulations 

of these approaches provide a conceptual understanding of the 

management benefits these approaches could achieve.

Monthly simulations from 1998 to 2006 were used for 

the scenarios. This time span includes a generally dry period 

from 1999 to 2002 and a wetter period from 2003 to 2006. The 

dry period from 1999 to 2002 produced streamflows comparable to those that occurred during the 1960s drought, which 

generally is considered to be the drought of record for New 

Jersey, even though the precipitation was less during the 1960s 

drought. Monthly mean streamflows at streamgaging stations 

Mullica River near Batsto (01409400) and Great Egg Harbor 

River at Folsom (01408000), and total monthly precipitation at 

the Atlantic City Airport, for the 4-year periods 1963 to 1966 

and 1999 to 2002 are shown in figure 42. The total precipitation at Atlantic City Airport during the two 4-year periods 

1963 to 1966 and 1999 to 2002 were 148.5 inches and 157 

inches, respectively. However, the monthly mean streamflows 
62 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City

Pleasantville

Somers

Point

Ocean City

Mays Landing

Egg Harbor City

Hammonton

Buena

Woodbine

CAPE MAY

CUMBERLAND

CAMDEN

BURLINGTON

OCEAN

ATLANTIC

GLOUCESTER

75° 74°40' 74°20'

Base from U.S.Geological Survey digital line graph files, 1:24,000

39°

40' 

0 5 10 MILES

0 5 10 15 KILOMETERS

39°

20' 

02040302010

02040301210

02040302050

02040302040

02040301160

02040301170

02040302070

02040301200

02040301190

02040301180

02040302030

02040302060

02040301150

02040302020

EXPLANATION

Boundary of Great Egg-Mullica model area representing the Kirkwood-Cohansey aquifer system

HYDROLOGIC UNIT CODE 11 SUBBASIN

Updip

Mixed

Downdip

Updip extent of the Atlantic City 800-foot sand 

(From Zapecza, 1989)

ATLANTIC 

OCEAN

Great Egg Har bor River

Batsto River

Wading River

Mullica River

Tuckahoe River

Figure 41. Location of Hydrologic Unit Code 11 (HUC11) subbasins, southeastern New Jersey.
Simulation and Results of Withdrawal Scenarios 63

0

20

40

60

80

100

120

140

160

180

Mullica River near Batsto 

Period of record average 1957−2002 

Average 1963−66 

Average 1999−2002 

Period of record minimum

0

20

40

60

80

100

120

140

Monthly mean flow, in cubic feet per second

Great Egg Harbor River at Folsom 

Period of record average 1925−2002 

Average 1963−66 

Average 1999−2002 

Period of record minimum

0

5

10

15

20

25

Total monthly precipitation, in inches

Month 

Atlantic City Airport monthly precipitation 

Total 1963−66 

Total 1999−2002

EXPLANATION

EXPLANATION

EXPLANATION

July

Aug

Set

Oct

NovDec

May

June

Jan

Feb

Mar

Apr

Figure 42. Monthly mean streamflow and total monthly precipitation at selected sites, southeastern New Jersey, for selected periods 

from 1957 to 2002.

at the two streamgaging stations for the two drought periods 

are similar. Late summer and fall streamflows during 2001–02 

were lower than those during any year in the 1960s drought. 

The period from 1998 to 2006 represented a strong drought 

period for the simulation scenarios, which also used groundwater-recharge and water-use datasets that were created for 

model calibration. For discussion of the scenarios, the years 

1998 to 2006 will be referred to as scenarios years 1 to 9. The 

scenario year and the year of recharge are shown in table 13. 

Recharge for each year and the ratio of the recharge per year 

to the largest recharge (2006) are also shown.

Because groundwater withdrawals from the AtlanticCity 800-foot sand differ for each scenario, flows across the 

model boundaries change, so the RASA model was used to 

provide boundary conditions for the Great Egg-Mullica model. 

The RASA model was run using no withdrawal conditions, 

average 1998–2006 conditions, full-allocation conditions, and 

2050 demand conditions for the wells within this study area 
64 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 13. Scenario years and recharge per year used for 

simulations with the Great Egg-Mullica model.

[Mgal/d, million gallons per day]

Scenario 

year

Recharge 

year

Recharge

(Mgal/d)

Recharge 

ratio

1 1998 7,914 0.65

2 1999 10,204 0.83

3 2000 8,248 0.67

4 2001 7,425 0.61

5 2002 12,135 0.99

6 2003 11,076 0.91

7 2004 9,218 0.75

8 2005 12,233 1

9 2006 10,750 0.88

to match the conditions used in the Great Egg-Mullica model 

simulations. The RASA model provided fluxes in the Atlantic 

City 800-foot sand to the Great Egg-Mullica model. The simulations representing Tier 2 (seasonal-conjunctive use) used the 

same boundary conditions as the respective basic scenarios. 

The total annual withdrawals used for the RASA model did 

not change even though the timing of the withdrawals from the 

Atlantic City 800-foot sand changed because the RASA model 

is represented using annual stress periods.

Water Use for Scenarios 

The calibrated Great Egg Harbor-Mullica model was 

used to evaluate possible future conditions under several different withdrawal scenarios and groundwater-management 

approaches. The effects of recent groundwater withdrawals 

on groundwater flow were simulated using the average annual 

1998 to 2006 withdrawals. The long-term effects of groundwater withdrawals on water supply under full-allocation conditions were simulated to evaluate recent groundwater-management policies. Groundwater withdrawals under projected 

2050 demand withdrawals were simulated to evaluate possible 

future groundwater conditions. In order to perform these 

simulations, estimates of groundwater withdrawals at existing 

sources were needed. A simplifying assumption was made that 

future withdrawals would occur at the same locations as existing withdrawals.

The NJDEP Bureau of Water Allocation manages waterallocation permits for users in New Jersey. Public supply 

and commercial/industrial permits (5,000 and 2,000 series 

permits) allow the withdrawal of more than 100,000 gallons 

per day. Diversion limits of 3.1 million gallons per month 

(Mgal/mo) (up to 37.2 million gallons per year (Mgal/yr)) are 

assigned for users who have the capacity to divert in excess 

of 100,000 gallons per day (gal/d) but divert less than that 

quantity, which is based on monthly average use, under the 

10000W series water-use registrations. Permits and registrations also are designated for agricultural users (Ag permits). 

Limits are specified for all water-allocation permits, which 

may include more than one source (wells or surface-water 

intakes). In some cases, allocation limits are assigned for a 

group of sources within a permit. In order to simulate the Full 

Allocation scenario, estimates of full-allocation withdrawal 

rates at individual sources were needed.

Water-allocation data, including withdrawal limits and 

usage, were supplied by NJDEP. Annual limits were used 

where they were available. If only monthly limits were available, annual limits were estimated from the monthly limits. 

For most permits this was done by multiplying the monthly 

limit times 12. However, for agricultural permits this was not 

appropriate because withdrawals are made seasonally. Annual 

limits for simulation of full-allocation conditions for agricultural permits were estimated using the monthly limit times a 

representative growing season of 3.5 months, based on discussions with NJDEP. 

Water demand for the year 2050 for each allocation 

permit was estimated using several different methods depending on the series of the water-allocation permit. Projected 

withdrawals for 2050 for each public supply permit (5,000 

series) were estimated by the NJDEP using population data 

from the New Jersey Metropolitan Planning Organization 

(MPO) municipal population projection data for the drinkingwater service areas of the purveyors (Richard Grabowski, 

New Jersey Department of Environmental Protection, written 

commun., 2007). Water-demand projections are based on the 

population growth and withdrawals during 2001–02. Projected 2050 demands for 2,000 and 10,000 series permits were 

estimated using annual increases in withdrawals of 1.4 and 

1.8 percent of 1998–2006 average withdrawal rates, respectively. The NJDEP estimated the 2050 demand for agricultural 

permits to hold constant at the 1998–2006 average level. This 

estimate was based on two trends that are expected to continue 

and create opposite effects on agricultural irrigation, resulting 

in little net change in irrigation withdrawals. First, the amount 

of agricultural land is expected to decrease as development 

continues. Second, however, the percentage of agricultural 

land that is irrigated is expected to increase and produce more 

high value crops.

Withdrawals for each well or diversion within the permits were estimated in order to simulate the Full Allocation 

and 2050 Demand scenarios. The distribution of withdrawals for each scenario was estimated using the distribution 

of withdrawals for each permit and using recent (2003–05) 

data. Withdrawals for the year 2005 were used, if available. 

If data for 2005 were not available, data from 2003 or 2004 

were used. These withdrawal data were used to calculate the 

percentage of withdrawals at each individual well or diversion 

listed within the permit. This percentage was multiplied by 

the full-allocation or 2050-demand withdrawal rate for each 

permit to estimate future withdrawals. 

Because the data for the Average 1998–2006, Full 

Allocation, and 2050 Demand scenarios were provided as 
Simulation and Results of Withdrawal Scenarios 65

annual totals, the monthly distribution of withdrawals also was 

estimated using recent withdrawal patterns. NJDEP provided 

monthly withdrawal percentages for each well or diversion 

calculated from withdrawal data for 1990 to 1999 from the 

New Jersey Water-Transfer Data System (NJWaTr) database (New Jersey Department of Environmental Protection, 

2010). More recent withdrawal data were used to estimate the 

monthly withdrawal percentages for sources that were not in 

use in the 1990s. These monthly percentages were then used 

with the annual data to estimate the monthly withdrawals for 

each scenario.

that the withdrawals are more than 50 percent of the total 

for all permit types for the subbasin and highlights the 

predominant use by permit type. Several downdip or mixed 

subbasins are dominated by public supply withdrawals 

(02040301200, 02040302020, 02040302050, 02040302060, 

and 02040302070). Several updip subbasins or mixed subbasins are dominated by non-cranberry agricultural withdrawals (02040301150, 02040301160, 02040301170, 

and 02040302040). Withdrawals from updip subbasins 

02040301180 and 02040301190 are completely or almost 

completely for cranberry use. 

Base-Flow Depletion Criteria

In order to evaluate scenario results, monthly base-flow 

depletion criteria were needed for each of the 14 HUC11 

subbasins in the study area. Simulated base-flow depletion for 

each scenario was compared to criteria to determine subbasins 

and time periods where deficits occurred. The approach used 

to determine the monthly base-flow depletion criteria was 

based on the Low-Flow Margin (LFM) method developed 

by NJDEP to estimate available water on an annual basis at 

the HUC11 level for the New Jersey Water Supply Plan. The 

NJDEP developed the LFM method to estimate the volume of 

water available in a water-table aquifer for use within a subbasin during ecologically critical flow periods. This method 

is being used as part of the NJDEP draft of the most recent 

version of the New Jersey Water Supply Plan (SWSP) (Jeffrey 

Hoffman, New Jersey Department of Environmental Protection, written commun., 2012). For the method, it was assumed 

that some percentage of streamflow can be removed without 

affecting stream ecology. The method defines the available 

water as a percentage of the difference between normal dry 

season streamflow and drought streamflow. 

The September median flow represents flows typical for 

September, which are frequently the lowest flows of the year 

in New Jersey. The 7-day, 10-year (7Q10) flow represents 

drought flows. In this report, the low-flow margin is defined 

as the difference between the September median flow and 

the 7Q10 flow. The NJDEP defines available water as some 

percentage of this margin. If the entire margin were used 

for depletive and consumptive purposes, typical flows during summer months would decline to flows observed during 

droughts. However, according to the rationale of the LFM 

method, removing only a percentage of this margin would 

provide streamflows that could still support aquatic ecosystem 

health. 

The NJDEP used the results of detailed studies and a 

comparison to subbasins with known water-availability issues 

to determine the percentage of the low-flow margin that can 

be lost to depletive/consumptive use without creating adverse 

effects. The Hydroecological Integrity Assessment Process 

(also known as eco-flow goals) (Kennen and others, 2007; 

Hoffman and Rancan, 2009) was used to estimate the volume 

of water available for use in 10 subbasins throughout New 

0

5,000

10,000

15,000

20,000

25,000

30,000

10,000

series

registrations

Commercial/

industrial

Publlic supply Agricultural Agricultural

cranberry

Simulated groundwater withdrawals, in million gallons per year

Permit series

Average 1998−2006

Full Allocation

2050 Demand

EXPLANATION

Figure 43. Simulated groundwater withdrawals in the Great Egg 

and Mullica River Basins, southeastern New Jersey, by permit 

series, for the Average 1998–2008, Full Allocation, and 

2050 Demand scenarios.

Groundwater-withdrawal totals for the three scenarios, by 

permit series, are shown in figure 43. Commercial/industrial 

uses and public supply uses have much higher withdrawals 

under the Full Allocation and 2050 Demand scenarios than 

under the Average scenario (1998–2006). Public supply use is 

the only category for which the 2050 demand is greater than 

the full-allocation demand. Agricultural withdrawals under 

full-allocation conditions are several times larger than withdrawals under average conditions.

Groundwater withdrawals from the unconfined aquifer 

in Average, Full Allocation, and 2050 Demand scenarios 

are listed, by use category, in table 14. Bold values indicate 
66 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 14. Projected withdrawals, by permit type, for selected Hydrologic Unit Code 11 subbasins, southeastern New Jersey. 

[HUC11, Hydrologic Unit Code 11; all withdrawals in millions of gallons per year; values in bold are more than 50 percent of total withdrawals]

HUC11

number Scenario Public supply

Commercial/

industrial

Agricultural 

non-cranberry

Agricultural 

cranberry 10,000 series Total

02040301150 Average 0 61 110 57 0 227

02040301150 Full Allocation 0 129 519 151 0 798

02040301150 2050 Demand 0 113 110 57 0 280

02040301160 Average 478 144 659 70 65 1,417

02040301160 Full Allocation 725 1,585 3,963 151 260 6,684

02040301160 2050 Demand 719 270 659 70 146 1,864

02040301170 Average 159 0 602 18 21 800

02040301170 Full Allocation 217 0 2,541 185 86 3,029

02040301170 2050 Demand 253 0 602 18 48 921

02040301180 Average 0 0 0 72 0 72

02040301180 Full Allocation 0 0 0 330 0 330

02040301180 2050 Demand 0 0 0 72 0 72

02040301190 Average 0 0 4 1,027 6 1,036

02040301190 Full Allocation 0 0 15 1,786 25 1,826

02040301190 2050 Demand 0 0 4 1,027 12 1,043

02040301200 Average 534 254 12 0 15 816

02040301200 Full Allocation 866 753 326 0 62 2,007

02040301200 2050 Demand 953 475 12 0 34 1,475

02040301210 Average 0 22 0 0 0 22

02040301210 Full Allocation 0 31 0 0 0 31

02040301210 2050 Demand 0 42 0 0 0 42

02040302010 Average 0 94 0 0 0 94

02040302010 Full Allocation 0 97 0 0 0 97

02040302010 2050 Demand 0 175 0 0 0 175

02040302020 Average 4,017 142 0 0 17 4,176

02040302020 Full Allocation 6,395 582 0 0 53 7,030

02040302020 2050 Demand 4,567 265 0 0 37 4,869

02040302030 Average 1,533 0 388 0 18 1,938

02040302030 Full Allocation 2,243 0 1,697 0 97 4,036

02040302030 2050 Demand 2,620 0 388 0 41 3,048

02040302040 Average 188 41 1,257 0 47 1,533

02040302040 Full Allocation 324 158 4,557 0 152 5,191

02040302040 2050 Demand 370 77 1,257 0 105 1,809

02040302050 Average 297 94 84 0 51 526

02040302050 Full Allocation 587 269 316 0 123 1,295

02040302050 2050 Demand 920 190 84 0 113 1,307

02040302060 Average 1,667 92 5 0 50 1,815

02040302060 Full Allocation 2,594 148 77 0 133 2,952

02040302060 2050 Demand 2,910 172 5 0 112 3,200

02040302070 Average 105 15 9 0 3 133

02040302070 Full Allocation 250 326 29 0 5 609

02040302070 2050 Demand 180 29 9 0 7 225
Simulation and Results of Withdrawal Scenarios 67

Jersey. The percentages of the low-flow margin available 

ranged from 10 to 34 with an average of 24. For the purposes 

of this analysis, the water available for depletive/consumptive 

use is defined as 25 percent of the low-flow margin. 

The LFM method was modified for this study to determine monthly base-flow depletion limits that would be 

allowable under an application of the LFM method. This 

modification was necessary to guide simulation of a seasonalconjunctive approach for the use of the shallow unconfined 

aquifer, along with a deeper confined aquifer, as an alternative. 

Seasonal-conjunctive use would take advantage of the higher 

streamflows during winter months and allow withdrawal of 

additional groundwater from the unconfined aquifer, thus 

requiring lower rates of withdrawals from the confined aquifer 

during this time. Withdrawals from the confined aquifer 

could then be increased by the same amount during the summer months, along with a decrease in withdrawals from the 

unconfined aquifer. This results in no net annual change in 

withdrawals from either aquifer. This approach requires that 

monthly water-availability limits be established so that more 

water can be withdrawn in the winter months when the difference between the median flow and the low flow is greater, and 

therefore, more water is available.

To determine monthly water-availability limits, the LFM 

method was applied on a monthly basis to the 14 HUC11 

subbasins in the Great Egg Harbor and Mullica River Basins 

study area. Streamflow data from streamgaging stations or 

low-flow partial-record stations in or near the HUC11 subbasins were used to estimate the statistics for the HUC11 

subbasins. Monthly medians and monthly 7Q10 statistics 

were calculated for continuous-streamgaging stations with 

20 years of record and low-flow partial-record stations with 

five or more measurements. These statistics were calculated 

for the period of record through water year 20091. Monthly 

statistics at stations were transferred to the HUC11 subbasins 

using the same techniques used in the Water Capacity Analysis 

prepared by the USGS for the New Jersey Water Supply Plan. 

If the drainage area for a streamgaging station corresponded 

closely to a HUC11 subbasin, the statistics were transferred 

by adjusting the values by the ratio of drainage area to the 

HUC11 area. If multiple stations were located within a HUC11 

subbasin, the statistics for the stations were summed, and the 

drainage areas were summed. The values were adjusted by 

the ratio of the summed drainage area to the HUC11 area. 

In one subbasin, 02040302040, the flows from the upstream 

HUC11 (02040302030) were subtracted from the streamflows 

calculated from index stations in order to get an estimate 

for the downstream HUC11. The HUC11 subbasins and the 

index stations that were used to transfer the flows are shown 

in table 15. In all but one subbasin, HUC 02040302040, the 

same index stations that were used in the SWSP for each of 

the HUC11 subbasins were used here. For HUC 02040302040, 

the average of streamflows at index stations 01411110 and 

1

 A water year is the 12-month period from October 1 to September 30; it is 

designated by the year in which it ends. 

01411140 was used instead of streamflow at index station 

01411170, which was used in the Water Capacity Analysis, 

because the values estimated using station 01411170 were low 

compared to those of other HUC11 subbasins when adjusted 

by drainage area.

Once the monthly statistics were calculated for the 

HUC11 subbasins, the LFM method was applied. The monthly 

low-flow margin is the difference between the monthly median 

flow and the monthly 7Q10 flow. For this analysis, the lowflow margin available water was calculated as 25 percent of 

the LFM method, unless this value exceeded 50 percent of the 

monthly 7Q10, in which case it was set to 50 percent of the 

monthly 7Q10. In the implementation of the LFM method for 

the New Jersey Water Supply Plan, the low-flow margin available water was reduced in each HUC11 by existing consumptive uses of groundwater and surface water within the subbasin 

to determine the base-flow criteria. Because the groundwater 

withdrawals are being directly included in the groundwater 

flow model, they are not removed from the available water 

calculation. However, surface-water consumptive use within 

the subbasins needs to be accounted for. Average surface-water 

diversions for 1998 to 2006 were calculated and subtracted 

from the LFM available water to determine the monthly baseflow depletion criteria for each HUC11 subbasin. The HUC11 

monthly streamflow statistics, the calculations of LFM, and 

the monthly base-flow depletion criteria are listed in table 16. 

Surface-water diversions during June to November in subbasin 

02040302020 were larger than the low-flow margin available 

water for the subbasin.

No-Withdrawal Scenario

The no-withdrawal scenario represents conditions that 

would have occurred during 1998–2006 if there had been no 

groundwater withdrawals. This scenario is used as the baseline 

for comparison with the other scenarios. Base-flow depletion 

for each of the remaining scenarios is calculated as the base 

flow simulated for the no-withdrawal scenario minus the base 

flow simulated for a particular scenario.

Basic Scenarios

The basic scenarios simulate a 9-year hypothetical period 

during which recharge is equivalent to that estimated for 1998 

to 2006 and the withdrawals for each year represent average, 

full-allocation, and 2050 demand conditions. The withdrawals 

used represent hypothetical conditions instead of the actual 

withdrawals. In each of these scenarios, the same cycle of 

withdrawals is applied during each year of the simulation 

period. The withdrawals vary by month, using the percentage distribution of average withdrawals by month from the 

NJDEP. These scenarios represent conditions that would have 

occurred if the withdrawals for the scenario had occurred during the 1998–2006 period. 
68 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 15. Hydrologic Unit Code 11 subbasins and index stations used to transfer monthly flow statistics, southeastern New Jersey. [HUC11, Hydrologic Unit Code 11; GSP, Garden State Parkway; --, no data] HUC11 number Basin name Basin Drainage area (square miles) Station 1 Station 2 Station 3 Station 4 Drainage area ratio 02040301150 Batsto River Mullica 67.85 01409500 -- -- -- 0.995 02040301160 Mullica River (above Batsto River) Mullica 127.25 01409400 01409406 01409411 -- 1.009 02040301170 Mullica River (Turtle Ck to Basto River) Mullica 109.93 01409416 01409575 -- -- 7.663 02040301180 Oswego River Mullica 72.51 01410000 -- -- -- 1.001 02040301190 West Branch Wading River Mullica 87.03 01409810 -- -- -- 1.037 02040301200 Mullica River (GSP bridge to Turtle Ck) Mullica 95.65 01410150 01410200 01410215 01410225 3.062 02040301210 Great Bay / Mullica R (below GSP bridge) Mullica 21.72 01409300 01410225 01410500 -- 0.703 02040302010 Reeds Bay / Absecon Bay & tribs Great Egg Harbor 14.81 01410225 01410500 01411305 -- 0.442 02040302020 Absecon Creek Great Egg Harbor 26.42 01410215 01411305 -- -- 1.641 02040302030 Great Egg Harbor R (above HospitalityBr) Great Egg Harbor 71.01 01411000 -- -- -- 1.247 02040302040a Great Egg Harbor R (Lk Lenape to HospBr) Great Egg Harbor 133.40 01411140 -- -- -- 10.2 02040302040b Great Egg Harbor R (Lk Lenape to HospBr) Great Egg Harbor 133.40 01411110 -- -- -- 1.32 02040302040c Great Egg Harbor R (Lk Lenape to HospBr) Great Egg Harbor 133.40 01411170 -- -- -- 0.100 02040302050 Great Egg Harbor R (below Lake Lenape) Great Egg Harbor 142.08 01411200 01411220 01411250 -- 3.221 02040302060 Patcong Creek/Great Egg Harbor Bay Great Egg Harbor 42.68 01411305 -- -- -- 5.689 02040302070 Tuckahoe River Great Egg Harbor 102.14 01411300 -- -- -- 3.320
Simulation and Results of Withdrawal Scenarios 69

Table 16. Monthly base-flow depletion criteria and associated data for Hydrologic Unit Code 11 subbasins, southeastern New Jersey.—Continued[HUC11, Hydrologic Unit Code 11; SW, surface water]

HUC11 

number Statistic Monthly base-flow, in million gallons per day Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

Mullica River Basin

02040301150 Median1 78.82 83.71 93.81 84.36 76.52 57.48 47.45 46.81 44.04 47.26 60.31 68.22

7Q102 43.98 48.79 53.93 49.29 42.63 34.5 29.81 26.41 26.67 29.55 35.49 38.32LFM3 34.84 34.92 39.88 35.07 33.89 22.98 17.64 20.4 17.37 17.71 24.82 29.9LFM available water4 8.71 8.73 9.97 8.77 8.47 5.74 4.41 5.1 4.34 4.43 6.2 7.48

Average SW diversions5 0 0 0.01 0.03 1.16 2.14 1.62 1.98 1.52 0.05 0 0

Base-flow criteria6 8.71 8.73 9.96 8.74 7.31 3.6 2.79 3.12 2.82 4.38 6.2 7.48

02040301160 Median 129.96 134.34 150.96 137.73 106.69 72.67 56.84 51.66 47.94 58.75 82.05 108.07

7Q10 57.38 64.83 67.78 62.97 53.25 35.12 27.39 21.76 19.95 25.37 34.07 44.75LFM 72.58 69.51 83.18 74.76 53.44 37.55 29.45 29.9 27.99 33.38 47.98 63.32LFM available water 18.14 17.38 20.8 18.69 13.36 9.39 7.36 7.48 7 8.34 12 15.83Average SW diversions 0 0 0.01 0.1 0.29 0.35 0.5 0.34 0.16 0.07 0.03 0Base-flow criteria 18.14 17.38 20.79 18.59 13.07 9.04 6.86 7.14 6.84 8.27 11.97 15.83

02040301170 Median 113.39 118.97 135.77 125.73 102.66 71.6 56.91 54.1 49.95 57.8 78.44 94.99

7Q10 53.45 60 65.55 61.05 49.57 35.56 28.28 23.75 23.17 28.01 37.47 44.17LFM 59.94 58.97 70.22 64.68 53.09 36.04 28.63 30.35 26.78 29.79 40.97 50.82LFM available water 14.98 14.74 17.56 16.17 13.27 9.01 7.16 7.59 6.7 7.45 10.24 12.7Average SW diversions 0 0 0 0.03 0.24 0.52 0.81 0.58 0.32 0.02 0.01 0Base-flow criteria 14.98 14.74 17.56 16.14 13.03 8.49 6.35 7.01 6.38 7.43 10.23 12.7

02040301180 Median 56.62 58.56 65.68 62.12 51.57 38.12 33 32.87 30.22 34.16 43.93 46.33

7Q10 28.7 32.35 32.98 30.73 25.85 20.49 17.64 16.12 15.45 17.81 23.03 23.74LFM 27.92 26.21 32.7 31.39 25.72 17.63 15.36 16.75 14.77 16.35 20.9 22.59LFM available water 6.98 6.55 8.18 7.85 6.43 4.41 3.84 4.19 3.69 4.09 5.22 5.65Average SW diversions 0 0 0.02 0.02 0.04 0.11 0.1 0.11 0.01 0.01 0.01 0.01Base-flow criteria 6.98 6.55 8.16 7.83 6.39 4.3 3.74 4.08 3.68 4.08 5.21 5.64

02040301190 Median 98.3 101.65 104.73 113.04 85.24 54.34 42.08 43.75 38.47 53.87 60.71 62.85

7Q10 48.31 56.28 54.51 50.15 38.02 26.57 22.17 19.04 19.41 27.31 32.89 32.2LFM 49.99 45.37 50.22 62.89 47.22 27.77 19.91 24.71 19.06 26.56 27.82 30.65LFM available water 12.5 11.34 12.56 15.72 11.8 6.94 4.98 6.18 4.76 6.64 6.96 7.66Average SW diversions 0 0 0 0.01 1.55 0.75 0.82 0.71 0.03 0.02 0.01 0Base-flow criteria 12.5 11.34 12.56 15.71 10.25 6.19 4.16 5.47 4.73 6.62 6.95 7.66
70 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 16. Monthly base-flow depletion criteria and associated data for Hydrologic Unit Code 11 subbasins, southeastern New Jersey.—Continued [HUC11, Hydrologic Unit Code 11; SW, surface water] HUC11 number Statistic Monthly base-flow, in million gallons per day Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec 02040301200 Median 132.35 133.14 144.45 139.44 116.16 85.11 70.76 65.1 59.81 73.49 91.91 111.38 7Q10 65.77 73.86 74.18 70.03 61.9 47.9 42.1 34.59 33.41 37.28 48.43 62.64 LFM 66.58 59.28 70.27 69.41 54.26 37.21 28.66 30.51 26.4 36.21 43.48 48.74 LFM available water 16.64 14.82 17.57 17.35 13.56 9.3 7.16 7.63 6.6 9.05 10.87 12.18 Average SW diversions 0 0 0 0 0.12 0.03 0.02 0.01 0 0 0 0 Base-flow criteria 16.64 14.82 17.57 17.35 13.44 9.27 7.14 7.62 6.6 9.05 10.87 12.18 02040301210 Median 20.43 20.51 23.33 22.57 18.36 12.45 8.75 7.87 7.06 10.44 13.42 17.29 7Q10 7.74 8.23 9.58 7.84 5.49 3.69 3.15 2.3 2.17 2.42 3.84 6.26 LFM 12.69 12.28 13.75 14.73 12.87 8.76 5.6 5.57 4.89 8.02 9.58 11.03 LFM available water 3.17 3.07 3.44 3.68 2.74 1.84 1.4 1.15 1.08 1.21 1.92 2.76 Average SW diversions 0 0 0 0 0 0 0 0 0 0 0 0 Base-flow criteria 3.17 3.07 3.44 3.68 2.74 1.84 1.4 1.15 1.08 1.21 1.92 2.76 Great Egg Harbor River Basin 02040302010 Median 14.14 14.23 16.12 15.71 12.9 8.96 6.47 5.86 5.31 7.48 9.49 12.06 7Q10 5.76 6.12 7.11 5.99 4.34 3.05 2.6 1.99 1.92 2.15 3.19 4.8 LFM 8.38 8.11 9.01 9.72 8.56 5.91 3.87 3.87 3.39 5.33 6.3 7.26 LFM available water 2.1 2.03 2.25 2.43 2.14 1.48 0.97 0.97 0.85 1.08 1.58 1.82 Average SW diversions 0 0 0.02 0.05 0.06 0.06 0.04 0.04 0.13 0.02 0.01 0 Base-flow criteria 2.1 2.03 2.23 2.38 2.08 1.42 0.93 0.93 0.72 1.06 1.57 1.82 02040302020 Median 23.77 24.78 27.66 26.06 22.05 16.33 13.46 12.76 12.01 13.54 17.49 20.67 7Q10 12.94 14.16 15.45 14.61 12.24 9.26 7.53 6.45 6.38 7.52 9.68 11.21 LFM 10.83 10.62 12.21 11.45 9.81 7.07 5.93 6.31 5.63 6.02 7.81 9.46 LFM available water 2.71 2.66 3.05 2.86 2.45 1.77 1.48 1.58 1.41 1.5 1.95 2.36 Average SW diversions 1.41 1.14 1.2 1.02 1.49 2.57 3.38 3.2 2.37 2.23 2.03 1.8 Base-flow criteria 1.3 1.52 1.85 1.84 0.96 0 0 0 0 0 0 0.56

02040302030 Median 73.43 76.65 86.89 79.88 67.22 48.2 40.06 37.56 35.78 40.71 54.72 65.04

7Q10 39.73 43 48.7 45.61 36.83 27.02 21.08 17.7 18.46 21.87 29.73 34.88LFM 33.7 33.65 38.19 34.27 30.39 21.18 18.98 19.86 17.32 18.84 24.99 30.16LFM available water 8.42 8.41 9.55 8.57 7.6 5.3 4.74 4.96 4.33 4.71 6.25 7.54Average SW diversions 0 0 0 0.01 0.14 0.26 0.18 0.27 0.17 0.04 0 0Base-flow criteria 8.42 8.41 9.55 8.56 7.46 5.04 4.56 4.69 4.16 4.67 6.25 7.54
Simulation and Results of Withdrawal Scenarios 71

Table 16. Monthly base-flow depletion criteria and associated data for Hydrologic Unit Code 11 subbasins, southeastern New Jersey.—Continued[HUC11, Hydrologic Unit Code 11; SW, surface water]

HUC11 

number Statistic Monthly base-flow, in million gallons per day Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

02040302040 Median 173.975 182.21 207.975 195.97 159.615 112.52 89.935 85.315 78.63 90.125 121.155 145.735

7Q10 82.94 92.89 102.055 96.045 76.82 55.855 44.08 37.105 36.155 43.765 58.485 69.22

determined using average of data from 01411110 and 01411140

LFM 91.04 89.32 105.92 99.93 82.8 56.67 45.86 48.21 42.47 46.36 62.67 76.51LFM available water 22.76 22.33 26.48 24.98 20.7 14.17 11.46 12.05 10.62 11.59 15.67 19.13Average SW diversions 0 0.01 0.06 0.36 0.4 0.59 0.79 0.72 0.58 0.34 0.27 0.29Base-flow criteria 22.76 22.32 26.42 24.62 20.3 13.58 10.67 11.33 10.04 11.25 15.4 18.84

02040302050 Median 119.76 126.67 147.61 134.11 106.78 71 55.1 51.72 47.57 55.63 78.51 98.45

7Q10 51.75 58.7 65.38 60.3 47.77 33.22 25.82 21.35 20.81 25.45 34.75 42.11LFM 68.01 67.97 82.23 73.81 59.01 37.78 29.28 30.37 26.76 30.18 43.76 56.34LFM available water 17 16.99 20.56 18.45 14.75 9.44 7.32 7.59 6.69 7.54 10.94 14.08Average SW diversions 0.05 0.05 0.28 0.58 0.64 0.76 0.9 1 0.76 0.34 0.64 0.07Base-flow criteria 16.95 16.94 20.28 17.87 14.11 8.68 6.42 6.59 5.93 7.2 10.3 14.01

02040302060 Median 35.4 36.79 40.58 39.85 34.03 26.15 21.82 20.83 19.58 21.68 26.93 30.95

7Q10 20.48 22.26 24.17 23.31 19.57 15.38 12.65 11.08 10.96 12.81 16.2 18.25LFM 14.92 14.53 16.41 16.54 14.46 10.77 9.17 9.75 8.62 8.87 10.73 12.7LFM available water 3.73 3.63 4.1 4.14 3.62 2.69 2.29 2.44 2.16 2.22 2.68 3.18Average SW diversions 0 0 0 0.13 0.19 0.22 0.32 0.34 0.23 0.06 0 0Base-flow criteria 3.73 3.63 4.1 4.01 3.43 2.47 1.97 2.1 1.93 2.16 2.68 3.18

02040302070 Median 91.84 97.65 107.94 119.1 90.77 62.45 44.86 39.91 36.06 44.42 58.8 71.45

7Q10 42.23 48.51 51.4 50.63 43.66 29.62 21.95 17.66 15.74 22.11 32.41 37.05LFM 49.61 49.14 56.54 68.47 47.11 32.83 22.91 22.25 20.32 22.31 26.39 34.4LFM available water 12.4 12.28 14.14 17.12 11.78 8.21 5.73 5.56 5.08 5.58 6.6 8.6Average SW diversions 0.48 0.61 0.71 0.8 1.11 1.26 1.18 1.14 1.11 1.02 0.83 0.74Base-flow criteria 11.92 11.67 13.43 16.32 10.67 6.95 4.55 4.42 3.97 4.56 5.77 7.86

1Median Monthly median streamflow.27Q10 7-Day, 10-Year streamflow.3LFM Monthly low-flow margin (LFM) is the monthly median minus the monthly 7Q10.4LFM available water The LFM available water is 25 percent of the monthly LFM, unless this value exceeds 50 percent of the monthly 7Q10. If so, the LFM available water is set to 50 percent of the 

monthly 7Q10.

5Average SW diversion Average monthly surface-water diversions for the basin for 2003–06. Values in Italics have been corrected using cranberry withdrawal consumptive use estimates for the growing 

and nongrowing seasons. These only occur in the Mullica River Basin.

6Base-flow criteria Base-flow depletion criteria that will be used to evaluate groundwater flow model scenario results, calculated as the LFM available water minus the average surface-water 

diversions. Values in bold indicate the average monthly surface-water diversions are greater than the LFM available water.
72 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Average Baseline base flow Base flow EXPLANATION Baseline base flow Base flow EXPLANATION Baseline base flow Base flow EXPLANATION Final available Base-flow depletion EXPLANATION Final available Base-flow depletion EXPLANATION Final available Base-flow depletion EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

0

755025

125100

-5

50

201510

50

201510

Simulated base flow, in million 

gallons per day 

0

755025

125100

-5

50

201510

50

201510

0

755025

125100

-5

50

201510

50

201510

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

Full Allocation 2050 Demand 

Figure 44. Simulated base flow, base-flow depletion, available water, and base-flow deficits under Average, Full Allocation, and 2050 Demand scenarios for an example Hydrologic Unit Code 11 subbasin, southeastern New Jersey.
Simulation and Results of Withdrawal Scenarios 73

An example graph of base flow, base-flow depletion, 

monthly available water and base-flow deficits for the Average, Full Allocation, and 2050 Demand scenarios is shown in 

figure 44 for the HUC11 subbasin representing the lower part 

of the Mullica River (02040301200) (Graphs for all 14 of the 

HUC11 subbasins are included in Appendix 1.) For each scenario, the top graph shows the base flow under no withdrawal 

conditions and the base flow for the scenario conditions. The 

middle graph shows the monthly base-flow depletion and the 

available water for the subbasin. In the Full allocation and 

2050 Demand scenarios, the base-flow depletion during the 

summer months is often larger than the low-flow margin available water. This results in a base-flow deficit condition. The 

base-flow deficits, remaining available water, and the monthly 

base-flow criteria are shown in the bottom graph. Deficits are 

show in the green bars and are negative values. The remaining 

available water is shown in the blue bars. The data used to create these graphs are shown in tabular form in Appendix 2. 

The monthly base-flow deficits for each subbasin, by 

scenario, for each scenario year are listed in table 17 (at end 

of report). If no deficits occurred for a scenario for a subbasin 

in a given year, that year is not listed. Months shaded in gray 

in the table are those designated as summer months (June 

through November) for the seasonal-conjunctive use scenario. 

The monthly base-flow deficits for the Average scenario are 

shown first for all subbasins, followed by the Full Allocation 

and 2050 Demand scenarios. The annual deficit and the total 

deficit for each subbasin are listed in table 18. The maximum 

annual base-flow deficit for each subbasin and the scenario 

year in which it occurred are shown in table 19. The maximum annual deficits for the Average, Full Allocation, and 

2050 Demand scenarios are shown in maps in figure 45. The 

maximum annual base-flow deficits in many of the subbasins 

occur in either scenario years 5 or 6. In general, scenario years 

4 and 5 were dry years in the study area. The budget for the 

Kirkwood-Cohansey aquifer system from the calibrated model 

shows that the recharge applied for 2001 to 2002 (scenario 

years 4 to 5) was low (fig. 40). Therefore, base flow in the 

subbasins was lower during this time period so more base-flow 

depletion was simulated. 

The deficits are larger under the Full Allocation scenario 

because the full-allocation limits for agricultural wells (which 

are all completed within the Kirkwood-Cohansey aquifer 

system) are much larger than the limits under average annual 

conditions. Any increases in deficits from average annual to 

2050 demand conditions are due to withdrawals from nonagricultural wells because the agricultural 2050 demand 

numbers were held constant at the average annual withdrawal 

amount.

The simulated water levels under the Average scenario 

and water-level decreases under the Full Allocation and 

2050 Demand scenarios in the Atlantic City 800-foot sand are 

shown in figure 46. The maps show water levels and waterlevel decreases in April and September of scenario year 9 for 

all three scenarios. 

Average 

Average conditions were simulated using average annual 

water-use data for the period 1998 to 2006. This simulation 

represents current conditions in the study area. Maximum 

annual base-flow deficits resulting from the Average scenario 

are shown in figure 45. Small deficits (less than 1.5 Mgal/yr) 

were simulated for subbasins 02040301190, 02040301180, 

02040301170, and 02040302040. These deficits occur in 

scenario years 5, 6 or 7 (tables 17 and 18). Except for monthly 

deficits that occur in December in subbasin 02040301190, 

the deficits all occurred during the period defined as summer 

(June-November) for the simulations. Deficits for subbasin 

02040302030 are somewhat larger than for other subbasins 

but also occur during the summer months. Withdrawals from 

subbasin 02040302030 under average conditions are much 

greater than in the rest of the updip subbasins; most of these 

withdrawals are for public supply (table 12). Deficits from the 

two downdip subbasins (02040302020 and 02040302060) are 

also larger and occur throughout the year (although the winter 

deficits from subbasin 02040302060 are smaller than the summer deficits). Subbasin 02040302020 (Absecon Creek) shows 

deficits because the LFM available water for the subbasin is 

relatively low (table 16; after the surface-water diversions are 

subtracted from the LFM available water, the base flow is even 

lower, and during some months base flow is 0 (no depletion 

allowed). The base-flow depletion simulated in this subbasin is 

about 10 million gallons per day (Mgal/d), which is the largest 

volume simulated for any of the subbasins. Withdrawals from 

the unconfined aquifer in this subbasin are more than double 

the withdrawals for any other subbasin.

Simulated heads in the Atlantic City 800-foot sand under 

average conditions are shown in figure 46. Heads at the center 

of the cone of depression are more than 80 ft below NGVD 29 

in April of scenario year 9 (when withdrawals are low) and are 

more than 100 ft below land surface in September in scenario 

year 9 (at the end of the summer withdrawal period). The 

simulated heads from the Average scenario were used to estimate the effects of increased withdrawals on heads in the Full 

Allocation and 2050 Demand scenarios (fig. 46).

Full Allocation 

Simulation of the Full Allocation scenario was made 

using the projected full-allocation withdrawals discussed 

previously. This simulation represents conditions that would 

occur if all wells were pumping at their full-allocation rate. 

The distribution of these withdrawal increases for agricultural 

and public supply use has a large effect on the increases in 

deficits in this scenario. As shown in figure 43, the agricultural withdrawals (which are exclusively from the unconfined 

Kirkwood-Cohansey aquifer system) in this scenario are 

much larger than in the Average scenario. The large agricultural withdrawals caused increased deficits in the subbasins. The increases in public supply withdrawals (fig. 43) 

occur in the Atlantic City 800-foot sand, as well as the 
74 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 18. Simulated annual and total base-flow deficits from basic scenarios using the Great Egg-Mullica model for Hydrologic Unit 

Code 11 subbasins, southeastern New Jersey.

[HUC11, Hydrologic Unit Code 11; Deficits are in millions of gallons per year; --, no data]

HUC11 number

Scenario year

1 2 3 4 5 6 7 8 9 Total

Average

02040301170 -- 0.12 -- -- 0.75 -- -- -- 1.34 2.21

02040301180 -- 0.64 0.51 0.43 1.12 0.64 0.45 0.71 1.12 5.62

02040301190 -- -- -- -- 0.25 -- -- -- -- 0.25

02040302020 110.31 117.67 112.84 111.02 118.86 121.43 113.61 119.01 116.3 1,041.05

02040302030 1.76 5.96 4.49 4.56 6.39 7.3 5.17 6.36 7.46 49.45

02040302040 -- -- -- -- 0.12 -- -- -- 0.05 0.17

02040302060 12.38 14.82 13.44 12.93 15.36 17.04 13.76 15.51 15.36 130.6

Full Allocation

02040301150 -- 0.76 0.49 0.25 0.73 1.72 0.04 0.32 1.8 6.11

02040301160 35.53 52.29 45.17 42.7 64.91 60.39 49.13 57.66 60.57 468.35

02040301170 33.13 50.45 41.22 38.21 59.1 55.44 42.04 47.39 51.31 418.29

02040301180 12.19 15.76 14.02 13.25 18.13 15.55 14.57 14.98 15.7 134.15

02040301190 -- 2.12 0.93 0.47 7.76 2.62 1.77 3.59 4.24 23.5

02040301200 3.16 9.2 7.79 7.21 15.36 13.15 7.69 9.96 14.45 87.97

02040302020 163.31 179.05 171.13 168.05 180.06 198.61 181.01 192.66 186.42 1,620.3

02040302030 79.65 97.58 86.8 83.86 97.52 109.58 88.49 99.69 94.49 837.66

02040302040 14.04 42.66 29.78 27.37 70.97 71.1 38.27 55.22 67.95 417.36

02040302050 -- 2.61 2.16 1.56 4.47 5.8 0.84 2.46 5.53 25.43

02040302060 43.15 47.54 45.2 44.08 48.94 50.95 45.74 48.61 46.62 420.83

2050 Demand

02040301170 2.08 7.17 5.58 4.87 10.76 8.19 5.24 6.33 10.08 60.3

02040301180 5.11 8.09 7.35 7.07 10.95 9.5 8.23 8.89 9.56 74.75

02040301190 -- -- -- -- 0.45 -- -- -- -- 0.45

02040301200 0.05 3.42 3.02 1.9 4.78 4.21 1.69 2.62 6.07 27.76

02040302020 131.39 141.31 135.5 133.26 142.22 149.05 137.76 144.55 140.92 1,255.96

02040302030 21.57 31.4 26.05 23.95 32.12 33.22 28.42 30.87 31.74 259.34

02040302040 -- 1.92 0.24 -- 7.06 2.27 -- 2.73 6.3 20.52

02040302050 -- 2.76 2.49 1.64 3.44 5.82 1.05 2.82 5.64 25.66

02040302060 43.6 48.16 45.45 44.13 48.93 50.7 45.9 48.85 47.23 422.95

Kirkwood-Cohansey aquifer system. The increases in public 

supply withdrawals from the unconfined Kirkwood-Cohansey 

aquifer system occur mainly in the downdip subbasins. In the 

Atlantic City 800-foot sand, public supply withdrawals are 

about 3,300 Mgal/d greater than in the Average scenario.

Maximum annual base-flow deficits for the Full Allocation scenario are shown in figure 45. The only subbasins 

that are not in deficit are 02040301210, 02040302010, and 

02040302070, located downdip near the coast. These subbasins are not in deficit because there are small or no agricultural withdrawals and public supply withdrawals are 

small. Deficits in the mixed subbasins, and in many of the 

updip subbasins, are much larger than those for the Average scenario (tables 18 and 19) because of the large unused 

agricultural allocations. Deficits for three updip undeveloped 

subbasins in the northern part of the study area (02040301150, 

02040301180, and 02040301190) increased from average 

conditions but not as much as for downdip and mixed subbasins because unused agricultural allocations from the subbasins are relatively small. Deficits in subbasins 02040302020 

and 02040302060 increased because of the unused allocations 

for public supply. Most maximum annual deficits occur in 
Simulation and Results of Withdrawal Scenarios 75

Table 19. Simulated maximum annual base-flow deficit and scenario year in which the deficit occurred using the Great Egg-Mullica 

model, by Hydrologic Unit Code 11, in southeastern New Jersey.

[HUC11, Hydrologic Unit Code 11; Mgal/yr, millions of gallons per year; Max, maximum; --, no data]

Average Full Allocation 2050 Demand

HUC11

number 

Basin

subbasin

Max 

annual 

deficit, 

Mgal/yr

Scenario

year

Max 

annual 

deficit, 

Mgal/yr

Scenario

year

Max 

annual 

deficit, 

Mgal/yr

Scenario

year

02040301150 Batsto River -- -- 1.8 9 -- --

02040301160 Mullica River (1) -- -- 64.9 5 -- --

02040301170 Mullica River (2) 1.3 9 59.1 5 10.8 5

02040301180 Oswego River 1.1 5 18.1 5 11.0 5

02040301190 West Branch Wading River 0.3 5 7.8 5 0.5 5

02040301200 Mullica River (3) -- -- 15.4 5 6.1 9

02040301210 Great Bay/Mullica River -- -- -- -- -- --

02040302010 Reeds Bay/Absecon Bay -- -- -- -- -- --

02040302020 Absecon Creek 121.4 6 198.6 6 149.1 6

02040302030 Great Egg Harbor River (1) 7.5 9 109.6 6 33.2 6

02040302040 Great Egg Harbor River (2) 0.1 5 71.1 6 7.1 5

02040302050 Great Egg Harbor River (3) -- -- 5.8 6 5.8 6

02040302060 Patcong Creek 17.0 6 51.0 6 50.7 6

02040302070 Tuckahoe River -- -- -- -- -- --

scenario years 5 or 6 (all subbasins except 02040301150). 

Deficits occur throughout the year in subbasins 02040302020, 

02040302030, and 02040302060. Deficits in subbasin 

02040302030 occur only in summer months under the Average 

scenario. 

Simulated heads in the Atlantic City 800-foot sand under 

the Full Allocation scenario are shown in figure 46. Simulated 

heads at the center of the cone of depression were more than 

120 ft below NGVD 29 in April of scenario year 9 (when 

withdrawals are less) and are more than 150 ft below NGVD 

29 in September of scenario year 9 (at the end of the summer 

withdrawal period). An increase in withdrawals to full-allocation levels would cause the heads in the Atlantic City 800-foot 

sand to drop from levels during average conditions by as much 

as 60 ft in April of scenario year 9 and by as much as 70 ft in 

September of scenario year 9. The potential declines in the 

potentiometric surface of the Atlantic City 800-foot sand may 

increase the possibility of saltwater intrusion in the aquifer. 

The water levels are much lower in the Full Allocation scenario than in the Average scenario, and the gradients from the 

center of the cone of depression towards the east (where the 

saltwater is) are steeper.

The increased base-flow deficits and declining water 

levels in the Atlantic City 800-foot sand in the Full Allocation 

scenario could potentially result from existing water-management policies. However, for this simulation, it was assumed 

that the increased withdrawals for full allocation would 

occur at existing well locations. Although this is a reasonable 

assumption, some increases are likely to occur at new wells. In 

that case, the declines in water levels would not be as large as 

simulated in this scenario. 

2050 Demand

The 2050 demand conditions were simulated using the 

projected 2050 demand water-use data discussed previously. 

The biggest change in this scenario from the Full Allocation 

scenario is in the projected withdrawals for public supply and 

agricultural use. As discussed in the section on water-use data 

for scenarios, the 2050 demand for agricultural use is held 

constant at the average 1998 to 2006 levels (fig. 43). This is 

a substantial reduction in withdrawals from the KirkwoodCohansey aquifer system compared to withdrawals in the Full 

Allocation scenario. Because of this difference, deficits in subbasins with large agricultural withdrawals are much smaller 

than deficits in the Full Allocation scenario because of this 

difference. Public supply demand in 2050 is about 700 Mgal/d 

lower for the Kirkwood-Cohansey aquifer system than in the 

Full Allocation scenario. Public supply withdrawals decreased 

from Full Allocation levels by about 1,800 Mgal/d in subbasin 

02040302020. This decrease is partially offset by increases of 

about 300 Mgal/d each from subbasins 02040302030 (updip), 

02040302050 (mixed), and 02040302060 (downdip). In the 

Atlantic City 800-foot sand, public supply withdrawals are 

about 600 Mgal/d greater than in the Full Allocation scenario 

and about 4,000 Mgal/d greater than in the Average scenario.
76 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

2050 Demand

"

39°

20' 

75° 74°40' 74°20’

39°

40' 

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Full Allocation

"

39°

20' 

75° 74°40' 74°20’

39°

40' 

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Average

"

39°

20' 

75° 74°40' 74°20’

39°

40' 

A B

C

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 15 KILOMETERS

EXPLANATION

SIMULATED MAXIMUM ANNUAL BASE-FLOW 

DEFICIT, IN MILLION GALLONS PER YEAR

> 0 - 20

> 20 - 80

> 80 - 120

> 120 - 200

Updip extent of the Atlantic City 800-

foot sand (From Zapecza, 1989)

Upper number is basin number, middle 

number is maximum annual deficit, and

bottom number is the scenario year in 

which the maximum deficit occurred

02040301170

10.76

5

(>, greater than)

02040301160

02040302070

02040302050

5.82

6

02040301170

10.76

5

02040301150

02040301210

02040302040

7.06

5

02040301200

6.07

9

02040301190

0.45

5

02040301180

10.95

5

02040302030

33.22

6

02040302060

50.7

6

02040302010

02040302020

149.05

6

02040302050

5.8

6

02040301160

64.91

5

02040301170

59.1

5

02040301210

02040302040

71.1

6

02040301200

15.36

5

02040301190

7.76

5

02040301180

18.13

5

02040302030

109.58

6

02040302060

50.95

6

02040301150

1.8

9

02040302010

02040302020

198.61

02040302050 6

02040301160

02040302070

02040301170

1.34

9

02040301150

02040301210

02040301200

02040302040

0.12

5

02040301190

0.25

5

02040301180

1.12

02040302030 5

7.46

9

02040302060

17.04

6

02040302010

02040302020

121.43

6

02040302070

Figure 45. Simulated maximum annual base-flow deficits for Hydrologic Unit Code 11 subbasins in southeastern New Jersey under A, 

Average, B, Full Allocation, and C, 2050 Demand scenarios, under basic conditions.
Simulation and Results of Withdrawal Scenarios 77

0

-20

-30

-40

-10

-50

-60 -70

-80

-90

10

20

30

-100

-110

-120

40

50

0

2030

0

-20

-10

-30

-40

-50

-60

-70

-80

10

-90

20

30

-100

-110

40

50

-120

0

20

10

30

40

0

-10

-20

-30

-40

10

-50

20

30

-60

-70

50 40

-80

50

30

40

20

10

40

0

-20

-30 -40

-50

-10

-60

-70

-80

-90

10

20

-100

30

-110

-120

-130

-140

-150

40

-160

20

0 40

0

-20

-10

-30

-40 -50

-60

-70

-80

-90

10

20

30

-110

-120

-100

-130

-140

40

-150

30

0 10

0

-10

-20

-30

-40

-50

10

20

30

-60

-70

-80

-90

40

50

-100

10

30

20

-130 39° 20' 

74°40' 74°20’

39°

40' 

74°40' 74°20’ 74°40' 74°20’

39°

40' 

39°

20' 

Base from U.S.Geological Survey digital line graph files, 1:24,000

EXPLANATION

< 10> 10 - 20> 20 - 30> 30 - 40Boundary of Great EggMullica model area representing the KirkwoodCohansey aquifer systemUpdip extent of the Atlantic City 800-foot sand (From Zapecza, 1989)SIMULATED POTENTIOMETRIC SURFACE—Shows altitude at which water level would have stood in tightly cased wells. Interval is 10 feet. Datum is National Geodetic Vertical Datum of 1929

> 40 - 50> 50 - 60> 60 - 70

April of scenario year 9September of scenario year 9

Average annual Full Allocation 2050 Demand 

SIMULATED WATER-LEVEL 

30

DECREASE, IN FEET

0 5 10 MILES0 5 10 15 KILOMETERS

(<, less than, >, greater than)

Figure 46. Simulated potentiometric surfaces and simulated water-level decreases for the Atlantic City 800-foot sand, southeastern New Jersey, under Average, Full Allocation, and 2050 Demand scenarios, under basic conditions, in April and September of scenario year 9.
78 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Base-flow deficits resulting from the 2050 Demand 

scenario are shown in figure 45. In addition to the three 

subbasins that were not in deficit during the Full Allocation 

scenario (02040301210, 02040302010, and 02040302070), 

subbasins 02040301150 and 02040301160 located updip in the 

Mullica River Basin are no longer in deficit. Deficits in many 

of the updip and mixed subbasins are much lower because, 

in the 2050 Demand scenario, agricultural withdrawals are 

decreased compared to those in the Full Allocation scenario. 

Deficits are also lower in subbasin 02040302020 because 

public supply withdrawals are decreased compared to those 

in the Full Allocation scenario. Deficits in the mixed or some 

updip subbasins (02040301180 and 02040301190) under the 

2050 Demand scenario are larger than those under the Average scenario because of the effects of increased public supply 

withdrawals from the confined Atlantic City 800-foot sand on 

the unconfined part of the aquifer. Deficits occur throughout 

the year in subbasins 02040302020 and 02040302060. In subbasin 02040302030, deficits occur through most of the winter 

months. The deficits in the remaining subbasins that have 

deficits occur in the summer (with the exception of December 

deficits in subbasin 02040301180) (table 17).

Simulated heads in the Atlantic City 800-foot sand under 

2050 demand conditions are shown in figure 46. Heads at the 

center of the cone are more than 140 ft below NGVD 29 in 

April of scenario year 9 (when withdrawals are lower) and are 

more than 160 ft below NGVD 29 in September of scenario 

year 9 (at the end of the summer withdrawal period). These 

heads are about 10 to 20 ft lower than simulated in the Full 

Allocation scenario in both April and September. The shaded 

areas showing water-level change from the Average scenario 

are larger at the center of the cones in the 2050 Demand scenario than in the Full Allocation scenario, and the areas where 

declines are more than 40 ft in the spring and 50 ft in the fall 

are much larger. 

In the Atlantic City 800-foot sand, the simulated heads 

are lowest for the 2050 Demand scenario because withdrawals for public supply use are larger than for other use types 

(fig. 16), and public supply withdrawals for the 2050 Demand 

scenario are slightly larger than for the Full Allocation scenario. Water-level declines from average conditions to future 

demand conditions are as much as 60 ft at the center of the 

cone of depression. The declines are greatest near the center of the cone and towards the ocean. The declines become 

smaller upgradient in the system towards the area where the 

Atlantic City 800-foot sand and the Kirkwood-Cohansey 

aquifer system are hydraulically connected because (1) those 

areas are farther away from the largest withdrawals and (2) the 

Kirkwood-Cohansey aquifer system provides additional water 

to the Atlantic City 800-foot sand near the updip limit of the 

Atlantic City 800-foot sand.

The increased base-flow deficits and declining water 

levels in the Atlantic City 800-foot sand in this scenario are 

those that would result from the expected 2050 demand. However, for this simulation, it was assumed that the increased 

withdrawals to satisfy the 2050 demand conditions would 

occur at existing well locations. Although this is a reasonable 

assumption, some of the increases are likely to occur at new 

wells. Increased withdrawals from new wells would result in 

somewhat less decline in heads at the center of the cones of 

depression and a more dispersed decline in heads throughout 

the Atlantic City 800-foot sand.

Adjusted Scenarios

Once the basic scenarios (Average, Full Allocation, and 

2050 Demand scenarios) were simulated and subbasins with 

months having base-flow deficits were identified, simulated 

withdrawals were modified in stages with the intent to progressively eliminate the deficits. Simulated withdrawals were 

altered under each of the three demand conditions of average, 

full allocation, and 2050 demand only in those subbasins that 

experienced deficits under a particular withdrawal condition. 

Of the 14 subbasins, 7 had deficits in the Average scenario, 11 

had deficits in the Full Allocation scenario, and 9 had deficits 

in the 2050 Demand scenario.

A series of simulations was formulated to test a hypothetical approach for eliminating the deficits. This strategy was 

developed as part of this study to show several potential ways 

the base-flow deficits could be reduced and to allow comparison of the effectiveness of various parts of the strategy. 

There may be other strategies that could be used to eliminate 

the base-flow deficits. These simulations were done to help 

the New Jersey Departmental Projection evaluate potential 

strategies. No plan is currently in place to implement these 

strategies.

The strategy was implemented using a three-tier 

approach. Tier 1 represents changes to the depths of the 

withdrawal wells in the Kirkwood-Cohansey aquifer system 

downdip. Tier 2 starts with the Tier 1 changes, and then shifts 

the withdrawals between the Kirkwood-Cohansey aquifer 

system and the Atlantic City 800-foot sand seasonally for 

any subbasins still in deficit after Tier 1. Lastly, Tier 3 starts 

with changes made in Tier 1 and Tier 2 and then reduces the 

magnitude of withdrawals for any subbasins still in deficit 

after Tier 2.

In the southeastern part of the study area, the unconfined 

Kirkwood-Cohansey aquifer system (overlying the Rio Grande 

water-bearing zone and the Atlantic City 800-foot sand) 

contains a shallow clay that creates an upper and lower unit 

within the aquifer. For subbasins with deficits within the area 

where this clay exists, simulated withdrawals from existing 

wells open to the shallowest, unconfined part of the Kirkwood-Cohansey aquifer system would be moved to the deeper, 

semi-confined part of the Kirkwood-Cohansey aquifer system. 

These changes are referred to as Tier 1 adjustments. For any 

subbasins that still have deficits and that are at least partly 

underlain by the Atlantic City 800-foot sand, seasonal-conjunctive use of the Kirkwood-Cohansey aquifer system (winter 

use) and the confined Atlantic City 800-foot sand (summer 

use) was implemented. These changes are referred to as Tier 2 

adjustments. Third, for any subbasins that have deficits that 
Simulation and Results of Withdrawal Scenarios 79

were not resolved by the first two adjustments, withdrawals or 

allocation limits from the Kirkwood-Cohansey aquifer system 

would be incrementally reduced basin-wide until there was no 

deficit. These changes are referred to as Tier 3 adjustments.

Tier 1 Adjustments

In order to reduce the stress from withdrawals on the 

water-table aquifer, which results in a reduction of base flow, 

simulated withdrawals were first shifted from the unconfined 

to the semi-confined Kirkwood-Cohansey aquifer system 

(model layer 1 to model layer 3)— the Tier 1 adjustments. 

The use of this approach was possible only in the downdip 

subbasins where the Kirkwood-Cohansey leaky confining unit 

is present (see fig. 4). The subbasins with at least one well 

for which withdrawals could be shifted to the deeper part of 

the aquifer and for which deficits were simulated under any 

conditions are 02040301170, 02040302020, 02040302050, 

and 02040302060. 

The changes in base flow resulting from Tier 1 adjustments were small. The percentages of the deficit resolved 

by this approach and the other two approaches are shown 

in table 20. No base-flow deficits were resolved using this 

change alone, and improvements were observed in only a few 

subbasins. The biggest change was for subbasin 02040302060 

located downdip, in which the Tier 1 adjustments ultimately 

accounted for 6 and 3 percent of the deficit reduction in the 

Average and 2050 Demand scenarios, respectively. The 

deficits in the Full Allocation scenario actually increased 

in this subbasin (and in several other subbasins) using this 

approach. This increase may be due to water moving to the 

deeper part of the aquifer in adjacent subbasins, which caused 

head declines in the subbasin with increased withdrawals. The 

effects of Tier 1 adjustments in other subbasins can be seen in 

subbasins 02040301150 and 02040301190, which are located 

updip; only slight reductions in deficits occurred in these 

subbasins when this change was implemented in downdip 

subbasins. 

Although the concept of using the deeper part of the 

Kirkwood-Cohansey aquifer system where the clay layer is 

present has merit on a local scale, the approach did not result 

in elimination of base-flow deficits. The semi-confining unit 

within the Kirkwood-Cohansey aquifer system may limit 

the effects on wetland water levels locally, but at the HUC11 

subbasin scale, the withdrawals from the deeper part of the 

aquifer still affect streamflow and contribute to base-flow 

depletion. The base flow, base-flow depletion, remaining available water in aquifer, and deficits for the adjusted scenarios are 

described in tabular form in Appendix 3.

Tier 2 Adjustments

For subbasins overlying both the unconfined KirkwoodCohansey aquifer system and the confined Atlantic City 

800-foot sand, seasonal-conjunctive use of the unconfined 

and confined aquifers was implemented as Tier 2 adjustments 

to eliminate deficits. Tier 2 adjustments incorporate Tier 1 

adjustments. Shifting withdrawals from the unconfined aquifer 

to the confined aquifer during periods of deficit (during the 

summer) would reduce the strain on the water-table aquifer. 

To balance the effects on the confined Atlantic City 800-foot 

sand, the same volume of withdrawals was shifted from the 

confined aquifer to the unconfined aquifer during times of 

high flows (winter/spring). The monthly deficits that occurred 

in downdip subbasins were examined, and it was determined 

that the summer period for shifting withdrawals would be June 

through November, and the winter period would be December 

through May.

Wells that withdraw water from the unconfined Kirkwood-Cohansey aquifer system (model layers 1 or 3) were 

identified; these wells are in areas underlain by the Atlantic 

City 800-foot sand. For each of these wells, a hypothetical well at the same location and open to the Atlantic City 

800-foot sand was used to simulate the summer withdrawals 

shifted to the confined aquifer. For each well with withdrawals from the Atlantic City 800-foot sand, a hypothetical well at 

the same location and open to the Kirkwood-Cohansey aquifer 

system was used to simulate the winter withdrawals, which 

were shifted to the shallow aquifer. There are six HUC11 

subbasins in the study area with wells that could be used for 

seasonal-conjunctive use and that have simulated deficits 

under at least one withdrawal condition—02040301170, 

02040301200, 02040302020, 02040302040, 02040302050, 

and 02040302060. 

The concept of seasonal-conjunctive use in this study 

refers to shifting withdrawals seasonally but maintaining the 

same net withdrawals from each aquifer so that the scenario 

does not result in increased water-level declines in the Atlantic 

City 800-foot sand or increased base-flow deficits. In each 

subbasin for which seasonal-conjunctive use was an option, 

the withdrawals from the Kirkwood-Cohansey aquifer system 

do not match exactly the withdrawals from the Atlantic City 

800-foot sand. If unconfined aquifer withdrawals were greater 

than Atlantic City 800-foot sand withdrawals and all unconfined summer withdrawals for the six subbasins were shifted 

to the confined aquifer, there would not be the same amount 

of water available when winter withdrawals were shifted back 

to the unconfined aquifer, and a net annual increase in withdrawals from the Atlantic City 800-foot sand would result. 

Similarly, if withdrawals from the Atlantic City 800-foot sand 

exceed those from the unconfined Kirkwood Cohansey aquifer 

system, shifting all withdrawals from the confined aquifer to 

the unconfined aquifer in the winter would increase the stress 

on the unconfined aquifer.

The maximum annual deficits simulated for each condition using Tier 1 and 2 adjustments (wherever possible, 

withdrawals shifted from model layer 1 to model layer 3, followed by seasonal-conjunctive use) is shown in figure 47. The 

percentage of the deficit that was resolved with seasonal-conjunctive use (Tier 2) for each subbasin is shown in table 20. In 

addition to the potential reduction or elimination of base-flow 

deficits, the effect of this approach on water levels in the 
80 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 20. Simulated deficits from basic scenarios and three-tier adjustment approaches for the Great Egg-Mullica model and 

percentage of total deficit reduction in Hydrologic Unit Code 11 subbasins, southeastern New Jersey.

[HUC11, Hydrologic Unit Code 11; Deficits are in millions of gallons;*, deficits were increased; **, deficits were improved but were made worse by seasonalconjunctive use]

HUC11

number

Basic scenarios

deficit

Deficit Total deficit reduction, percent

Tier 1 Tier 2 Tier 3 Tier 1 Tier 2 Tier 3

Average

Average basic

02040301150 0 0 0 0

02040301160 0 0 0 0

02040301170 2.21 2.67 5.76 0 * * 100

02040301180 5.62 6.18 28.61 18.94 * * 100

02040301190 0.25 0.25 0.26 0 0 * 100

02040301200 0 0 0 0

02040301210 0 0 0 0

02040302010 0 0 0 0

02040302020 1,041.05 1,040.49 1,017.16 63.34 0 2 98

02040302030 49.45 49.52 49.07 0 * 1 99

02040302040 0.17 0.19 2.26 0 * * 100

02040302050 0 0 0 0

02040302060 130.6 123.09 18.35 0 6 80 14

02040302070 0 0 0 0

Full Allocation

Full Allocation basic

02040301150 6.11 6.07 6.16 0 ** * 100

02040301160 468.35 467.87 456.88 0 0 2 98

02040301170 418.29 419.24 499.32 34.79 * * 100

02040301180 134.15 134.26 263.23 162.75 * * 100

02040301190 23.5 23.36 24.54 0 ** * 100

02040301200 87.97 98.65 136.93 0.27 * * 100

02040301210 0 0 0 0

02040302010 0 0 0 0

02040302020 1,620.3 1,698.63 1,620.32 84.55 * 5 95

02040302030 837.66 837.39 835.06 0 0 0 100

02040302040 417.36 417.62 590.05 0 * * 100

02040302050 25.43 29.66 36.07 0 * * 100

02040302060 420.83 428.41 256.52 0 * 40 60

02040302070 0 0 0 0

2050 Demand

2050 Demand basic

02040301150 0 0 0 0

02040301160 0 0 0 0

02040301170 60.3 61.52 94.87 14.24 * * 100

02040301180 74.75 74.97 157.01 141.06 * * 100

02040301190 0.45 0.45 0.49 0 0 * 100

02040301200 27.76 28.17 58.59 0.31 * * 100

02040301210 0 0 0 0

02040302010 0 0 0 0

02040302020 1,255.96 1,255.57 1,245.09 85.86 0 1 99

02040302030 259.34 259.4 259.43 0 * * 100

02040302040 20.52 20.69 54.92 0 * * 100

02040302050 25.66 27.05 25.36 0 * 6 94

02040302060 422.95 409.37 259.78 0 3 35 61

02040302070 0 0 0 0
Simulation and Results of Withdrawal Scenarios 81

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

2050 Demand

"

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Full Allocation

"

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Average

"

A B

C

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 15 KILOMETERS

EXPLANATION

SIMULATED MAXIMUM ANNUAL BASE-FLOW 

DEFICIT, IN MILLION GALLONS PER YEAR

> 0 - 20

> 20 - 80

> 80 - 120

> 120 - 200

Updip extent of the Atlantic City 800-

foot sand (From Zapecza, 1989)

Upper number is basin number, middle 

number is maximum annual deficit, and

bottom number is the scenario year in 

which the maximum deficit occurred

02040301170

16.19

5

(>, greater than)

02040301160

02040302050

6.1

6

02040301170

16.19

5

02040301150

02040301210

02040302040

14.88

5

02040301200

9.59

5

02040301190

0.49

5 02040301180

23.1

2

02040302030

33.23

6

02040302060

31.8

6

02040302010

02040302020

147.27

6

02040302070

02040302050

02040301160

02040301170

1.81

5

02040301150

02040301210

02040301200

02040302040

1.06

5

02040301190

0.26

5

02040301180

4.61

2

02040302030

7.43

9

02040302060

2.94

6

02040302010

02040302020

118.36

6

02040302070

02040302050

7.72

6

02040301160

63.21

5

02040301170

68.89

2

02040301210

02040302040

88.89

6

02040301200

22.75

5

02040301190

8.04

5

02040301180

38.42

2 02040302030

109.06

6

02040302060

31.68

6

02040301150

1.79

9

02040302010

02040302020

197.68

6

02040302070

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

Figure 47. Simulated maximum annual base-flow deficits for Hydrologic Unit Code 11 subbasins in southeastern New Jersey under A, 

Average, B, Full Allocation, and C, 2050 Demand scenarios with Tier 2 adjustments.
82 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Atlantic City 800-foot sand is important. Figure 48 shows the 

simulated heads and water-level changes from the basic conditions for each of the three basic scenarios in April of scenario 

year 9 and September of scenario year 9; the seasonal effects 

of seasonal-conjunctive use withdrawals from the Atlantic 

City 800-foot sand can be seen. The top three maps show the 

simulated heads in April of scenario year 9 with up to 20 ft of 

recovery from the basic scenarios near the center of the cone 

of depression in the Atlantic City 800-foot sand. The recovery 

is greatest near the center of the cone because that is where 

most withdrawals were made and, under Tier 2 adjustments, 

were moved to the shallow aquifer during the winter months. 

In areas away from the cone, a decline of as much as 20 ft 

from the basic scenario levels still occurred. The bottom three 

maps show the simulated heads and water-level changes from 

basic conditions in the Atlantic City 800-foot sand in September of scenario year 9 and the effects of increased summer 

withdrawals. Simulated heads declined as much as 70 ft from 

the basic scenarios during September because of the increased 

summer withdrawals. 

Seasonal-conjunctive use (Tier 2) reduced base-flow 

deficits in only one downdip subbasin (02040302060) where 

it accounted for 35 percent to 80 percent of the total deficit 

reduction in that subbasin (table 20). Minor improvements 

were also seen in subbasin 02040302020 (1 to 5 percent of 

total deficit reduction), but the adjustment was not nearly 

as successful as in subbasin 02040302060. As discussed 

previously, deficits could not be eliminated in subbasin 

02040302020 in the summer months through adjustment of 

groundwater withdrawals because the base-flow depletion 

limit for this subbasin of zero is due to the Average scenario 

surface-water withdrawals. In mixed subbasins where deficits 

were present (02040302040, 02040302050, 02040301170, and 

02040301200), seasonal-conjunctive use actually increased the 

deficits under at least one scenario. Increased deficits are the 

result of the declining heads during summer in the KirkwoodCohansey aquifer system and base-flow depletion caused by 

increased summer withdrawals from the Atlantic City 800-foot 

sand within the mixed subbasins or downdip subbasins. This 

result is important because it shows that withdrawals from the 

confined aquifer have an effect on base flow in the subbasins 

updip from the limit of the confining unit overlying the Atlantic City 800-foot sand. The deficits in subbasin 02040301200 

increased substantially under the Full Allocation and 2050 

Demand scenarios. In updip subbasins the results were mixed. 

In general, deficits increased or decreased slightly as a result 

of seasonal-conjunctive use in the these subbasins. However, 

deficits in subbasin 02040301180 increased greatly as a result 

of seasonal-conjunctive use. The deficits nearly doubled in 

the Full Allocation and 2050 Demand scenarios. This deficit 

increase is again due to the increased withdrawals from the 

Atlantic City 800-foot sand in other subbasins during the 

summer months. The increased deficits occurred in two ways. 

First, deficits that occurred from June through December 

under basic conditions increased. Second, deficits occurred 

during all 12 months of the year in this subbasin. 

Under average conditions, seasonal-conjunctive use 

reduced the deficits in several downdip subbasins but 

increased deficits in mixed subbasins and some updip subbasins (including large effects on subbasin 02040301180). Simulated groundwater levels in the Atlantic City 800-foot sand 

recovered in the spring of scenario year 9 by 10 to 20 ft in 

most areas of the cone of depression and recovered up to 20 ft 

in some areas near the center of the cone (fig. 48). Water levels 

decreased slightly in areas away from the center of the cone of 

depression. Heads near the center of the cone of depression in 

the late summer for the conjunctive-use simulation were more 

than 40 ft lower than the heads from the Average scenario 

basic simulation, as illustrated in the September of scenario 

year 9 map in figure 48.

Seasonal-conjunctive use (Tier 2) under the Full Allocation scenario improved base-flow deficits in subbasin 

02040302060 and to a lesser degree in subbasin 02040302020. 

Base-flow deficits in mixed or updip subbasins increased, 

particularly in subbasins 02040301170, 02040301180, 

02040301200, and 02040302040. Recovery of water levels 

in the Atlantic City 800-foot sand are seen near the center of 

the cone of depression, but declines of 10 to 20 ft occurred in 

areas away from the center of the cone of depression (fig.48). 

Water levels declined in September of scenario year 9 more 

than 50 ft from those resulting from the basic Full Allocation 

scenario, and heads in the Atlantic City 800-foot sand declined 

to more than 190 ft below NGVD 29 in the center of the cone 

of depression. 

Under the 2050 Demand scenario, seasonal-conjunctive 

use worked best in subbasin 02040301160. As under the 

Average and Full Allocation scenarios, deficits increased 

in mixed and some updip subbasins (particularly in subbasins 02040301170, 02040301180, 02040301200, and 

02040302040). The deficits in the mixed subbasins are not 

as large as those from the Full Allocation scenario (because 

the agricultural full-allocation limits are not in use) but are 

substantially larger than the deficits from the Average scenario. This result is due to the effect of withdrawals from the 

Atlantic City 800-foot sand on these subbasins. Head recovery 

in the spring and head decline in the summer in the Atlantic 

City 800-foot sand are both greater under the 2050 Demand 

scenario than under the Full Allocation scenario because of 

the greater withdrawals from the Atlantic City 800-foot sand 

by public supply wells. Heads in September of scenario year 9 

declined as much as 70 ft from basic 2050 demand conditions 

to more than 190 ft below NGVD 29 because of seasonalconjunctive use.

Seasonal-conjunctive use worked well in one downdip 

subbasin, but it caused substantial increases in the deficits in 

mixed and some updip subbasins because of the decreased 

heads in the Atlantic City 800-foot sand in the summer. Heads 

in the Atlantic City 800-foot sand recovered up to 20 ft during the spring but declined as much as 70 ft by the end of 

the summer, and heads reached levels of more than 190 ft 

below NGVD 29. Given the increased deficits in the mixed 

subbasins and the head declines in the Atlantic City 800-foot 
Simulation and Results of Withdrawal Scenarios 83 Figure 48. Potentiometric surfaces and simulated water-level changes for the Atlantic City 800-foot sand, southeastern New Jersey, under Average, Full Allocation, and 2050 Demand scenarios, with Tier 2 adjustments in April and September of scenario year 9.

0

-20

-60

40

20

20

40

40

-40

0

0

-20

-60

-80

-100

20

40

0

20

40

-40

-20

0

-20

-60

-80

-100

20

-120

40

0

20

40

-40

-40

0

-20

-60

-40

40

-100

-120

20

40

40

20

0

-40

-60

-20

-80

-100

20

-120

-160

40

-180

0

20

0

-40

-60

-20

-80

-100

20

-120

-140

-160

40

-180

0

20

-80

-140

-60

39°

20' 

74°40' 74°20’

39°

40' 

74°40' 74°20’ 74°40' 74°20’

39°

40' 

39°

20' 

Base from U.S.Geological Survey digital line graph files, 1:24,000

April of scenario year 9September of scenario year 9

Average annual Full Allocation 2050 Demand 

0 5 10 MILES0 5 10 15 KILOMETERS

EXPLANATION

0 - 10> 10 - 20> 20 - 30> 30 - 40> 40 - 50> 50 - 60> 60 - 70Boundary of Great EggMullica model area representing the KirkwoodCohansey aquifer systemUpdip extent of the Atlantic City 800-foot sand (From Zapecza, 1989)SIMULATED POTENTIOMETRIC SURFACE—Shows altitude at which water level would have stood in tightly cased wells. Interval is 20 feet. Datum is National Geodetic Vertical Datum of 1929

20

SIMULATED WATER-LEVEL 

CHANGE, IN FEET

(>, greater than)

INCREASE DECREASE

>10 - 20

0 - 10
84 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

sand, seasonal-conjunctive use would not solve the base-flow 

deficits if applied throughout the study area. However, results 

for subbasin 02040302060 are promising, and seasonalconjunctive use may prove an effective tool to manage deficits 

in this subbasin. The effectiveness of the approach in reducing deficits may be even greater and could result in smaller 

head declines in the confined aquifer if seasonal-conjunctive 

use was not occurring concurrently in the adjacent subbasin 02040302020, for which substantial withdrawals were 

shifted to the Atlantic City 800-foot sand in the summer. A 

limited application of seasonal-conjunctive use in subbasin 

02040302060 could produce better results.

Tier 3 Adjustments

Base-flow deficits simulated using existing wells and 

average (1998–2006), full-allocation, or 2050 demand withdrawal rates were not eliminated by shifting withdrawals from 

the shallow to the semi-confined Kirkwood-Cohansey aquifer 

system (Tier 1) or through seasonal-conjunctive use of the 

Atlantic City 800-foot sand (Tier 2) in any HUC11 subbasin. 

Therefore, a third alternative was simulated in which Kirkwood-Cohansey aquifer system withdrawals were reduced on 

a subbasin-by-subbasin basis until all deficits were eliminated 

or minimized. The reduction in withdrawals could represent 

shifting the water supply to a different source or reducing 

water use. Simulation of this alternative does not imply that 

the NJDEP will be implementing these reductions in withdrawals but was used to understand the magnitude in changes 

in withdrawals that would be needed to eliminate the deficits. 

These adjustments are referred to as Tier 3 adjustments. These 

adjustments are in addition to those made for Tier 1 and Tier 2.

Withdrawals were reduced in all wells in the KirkwoodCohansey aquifer system within each subbasin that had a 

deficit after implementation of Tier 1 and Tier 2 adjustments. 

Preliminary simulations in which withdrawals were reduced 

in increments of 10 percent in all subbasins in deficit were 

used to determine the approximate percentage of reduction necessary to eliminate deficits. Because of interactions 

between subbasins, reductions were adjusted (in 10-percent 

increments) for each subbasin until deficits were eliminated 

or withdrawals were reduced to zero. In some cases, deficits 

could not be eliminated even when withdrawals from the shallow Kirkwood-Cohansey aquifer system within the subbasin 

were eliminated. This is due to the effects of withdrawals from 

the shallow aquifer in other HUC11 subbasins or the effects of 

withdrawals from the Atlantic City 800-foot sand withdrawals 

in other subbasins. No attempt was made to eliminate deficits 

in one subbasin by reducing withdrawals in adjacent subbasins 

or by reducing withdrawals from the Atlantic City 800-foot 

sand downdip from the subbasins.

The reductions in groundwater withdrawals necessary 

to eliminate base-flow deficits for streams in the Average, 

Full Allocation, and 2050 Demand scenarios are shown in 

figure 49. Elimination of withdrawals from the unconfined 

aquifer (100-percent reduction) did not eliminate the deficit in 

subbasin 02040302020 because the base-flow depletion limit 

for this subbasin in summer is zero as a result of the surfacewater withdrawals and diversions in that subbasin. All but one 

of the other subbasins where reductions did not eliminate the 

deficits are mixed subbasins located along the updip limit of 

the confined Atlantic City 800-foot sand. Basin 02040301180 

was the only updip subbasin where 100-percent reductions did 

not eliminate the base-flow deficit. This subbasin is affected 

by withdrawals from the Atlantic City 800-foot sand. 

For most subbasins, the deficits were eliminated by 

reducing withdrawals from the unconfined aquifer until the 

annual deficit total was zero (no deficit occurred in any month 

of any simulated year). In most cases, the decrease in deficit 

was essentially proportional to increases in the percentage of 

groundwater-withdrawal reduction. That is, reductions in withdrawals were increased in increments of 10 percent until the 

deficit was eliminated, and the reduction of deficits followed 

in equal increments until the deficit was eliminated. In a few 

cases, however, the reduction of withdrawals only partially 

eliminated the deficit. For subbasin 02040302020, a base-flow 

deficit remained because of surface-water withdrawals in this 

subbasin. For other subbasins, including 02040301170 and 

02040301180, the deficit was caused primarily by withdrawals from the confined Atlantic City 800-foot sand in downdip subbasins and not by withdrawals within the subbasins. 

Therefore, even with a 100-percent reduction of unconfined 

aquifer withdrawals (all of the withdrawals in 02040301180), 

these two subbasins remained in deficit under the Full Allocation scenario. 

In several subbasins, including 02040301200 and 

02040302050, reductions in deficits were asymptotic to 

zero with a linear reduction in withdrawals. That is, initial 

10-percent reductions in withdrawals substantially reduced 

the base-flow deficit, but further 10-percent reductions had 

less and less effect on deficits. For subbasin 02040301200, 

the deficit in the Full Allocation scenario was reduced substantially from 137 Mgal/d after an 80-percent reduction in 

withdrawals, but the deficit was only reduced to 0.8 Mgal/d 

and 0.2 Mgal/d after a 90- or 100-percent reduction of withdrawals, respectively. Similarly, in subbasin 02040302050, a 

deficit of 36 Mgal/d was reduced to 2.2 Mgal/d with a 30-percent reduction, but deficits were reduced to 0.7 Mgal/d and 

0.3 Mgal/d with 40- and 60-percent reductions in withdrawals, 

respectively. The deficit was eliminated completely in this case 

but only with an 80-percent reduction in withdrawals. This 

behavior may result from withdrawals from the Atlantic City 

800-foot sand in downdip parts of the subbasin or in adjacent 

subbasins.

Under average conditions, reductions in groundwater 

withdrawals were needed to eliminate deficits in three updip 

subbasins, two mixed subbasins, and two downdip subbasins. 

Complete reductions in withdrawals were necessary in subbasins 02040301180 (updip) and 02040302020 (downdip). 

Reductions of 40 percent from current withdrawals were 

required in subbasin 02040302030 (updip) because of existing withdrawals for public supply and agriculture. Reductions 
Simulation and Results of Withdrawal Scenarios 85

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

2050 Demand

"

A B

C

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Full Allocation

"

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Average

"

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

AVERAGE REDUCTION IN WITHDRAWALS 

0

1 - 20

>20 - 40

>40 - 60

>60- 80

>80 - 99

100

Boundary of Great Egg-Mullica model 

area representing the KirkwoodCohansey aquifer system

Updip extent of the Atlantic City 800-foot 

sand (From Zapecza, 1989)

(>, greater than)

80

80

20

100

60

70

100

100

100

20 70

10

40

20

100

100

80

70

100

50

100

70

60

10

100

100

100

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

Figure 49. Average reductions in groundwater withdrawals required to eliminate or minimize deficits in Hydrologic Unit Code 11 

subbasins, southeastern New Jersey, under A, Average, B, Full Allocation, and C, 2050 Demand scenarios with Tier 3 adjustments.
86 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

in withdrawals from mixed subbasins 02040301170 and 

02040302040 (70 and 20 percent, respectively) were needed 

because of the withdrawals already occurring in the subbasins and because of withdrawals for seasonal-conjunctive 

use from the Atlantic City 800-foot sand downdip. Subbasin 

02040302060 located downdip required 20-percent reductions 

in withdrawals to eliminate base-flow deficits. 

In the Full Allocation scenario, reductions in withdrawals were needed in five updip subbasins, four mixed subbasins, and two downdip subbasins. The large base-flow deficit 

in subbasin 02040301160 in the Full Allocation scenario 

was caused by the substantial withdrawals for agricultural 

use. Basin-wide reductions in withdrawals of 70 percent 

were necessary to eliminate the base-flow deficits. Allocated 

withdrawals for agricultural use caused a similar (but less 

severe) increase in deficits; a basin-wide 10-percent reduction in withdrawals was required to eliminate the deficit. In 

updip subbasins 02040301190 and 02040302030, the deficits 

increased in the Full Allocation scenario, and additional reductions in withdrawals were needed to eliminate the deficits. 

Deficits in mixed subbasins 02040301200 and 02040302040 

increased in the Full Allocation scenario, and reductions in 

withdrawals greater than 10 percent (from average conditions) 

were required to eliminate the deficits. In the mixed subbasins, 

the increased deficits were due to a combination of increased 

withdrawals within the subbasin and seasonal-conjunctive use 

withdrawals from the Atlantic City 800-foot sand. Increased 

public supply withdrawals caused increased deficits (from 

average conditions) in downdip subbasin 02040302060; additional reductions in withdrawals were needed to eliminate the 

deficit. 

Under the 2050 Demand scenario, reductions in withdrawals were needed in three updip subbasins, four mixed 

subbasins, and two downdip subbasins. Withdrawals from the 

unconfined aquifer in this scenario were generally less than 

those under the Full Allocation scenario because the agricultural withdrawals remained at average 1998–2006 levels. In 

some subbasins, public supply withdrawals under the 2050 

Demand scenario were substantially increased, such that the 

total withdrawals within the subbasin were greater than those 

in the Full Allocation scenario. The same four mixed subbasins that were in deficit under the Full Allocation scenario 

required substantial reductions (even though the agricultural withdrawals remained at 1998–2006 rates) because of 

increased public supply withdrawals from the Atlantic City 

800-foot sand downdip. 

Summary of Base-Flow Deficit Reduction and 

Elimination with Scenario Adjustments

In general, most of the deficits under the Average, Full 

Allocation, and 2050 Demand scenarios were eliminated by 

reductions in withdrawals. The percentage of deficit reduction accomplished using Average, Full Allocation, and 2050 

Demand scenarios in each subbasin is shown in table 20. 

Reductions in withdrawals accounted for more than 95 percent 

of the total reduction of deficits in all subbasins, except for 

subbasin 02040302060. Moving withdrawals from the shallow 

to the deep Kirkwood-Cohansey aquifer system was most successful in this subbasin, but it still accounted for a maximum 

of only 6 percent of the reduction in the deficit (under average 

conditions). Seasonal-conjunctive use was successful in this 

subbasin; 35 to 80 percent of the base-flow deficit reduction 

for the three scenarios was achieved by seasonal-conjunctive 

use. Because seasonal-conjunctive use resulted in 80 percent 

of the deficit reduction, reduction in withdrawals would only 

need to provide 14 percent of the deficit reduction.

The effects of the three adjustment approaches on eliminating deficits depended on whether the subbasin was updip, 

mixed, or downdip. The sums of the deficits, grouped by 

subbasin type, for the average conditions, and adjusted Tier 1, 

Tier 2, and Tier 3 conditions are shown in figure 50. Under 

average conditions, most of the deficits occurred in downdip 

areas and were reduced somewhat by moving withdrawals 

from the shallow to the deep Kirkwood-Cohansey aquifer 

system (layer 1 to 3; Tier 1) or by seasonal-conjunctive use 

(Tier 2), but deficits were eliminated or minimized only by 

reductions to withdrawals (Tier 3). In the Full Allocation 

scenario, deficits increased in updip and mixed subbasins 

with implementation of seasonal-conjunctive use because of 

increased withdrawals from the Atlantic City 800-foot sand. In 

downdip subbasins, Tier 1 adjustments increased the deficits 

slightly, but Tier 2 adjustments ultimately reduced the deficits 

to less than the initial deficits. Deficits in the Full Allocation 

scenario were reduced primarily by reductions in withdrawals 

(Tier 3). In the 2050 Demand scenario, seasonal-conjunctive 

use (Tier 2) increased deficits in updip and mixed subbasins 

and reduced deficits in the downdip subbasins. For all of the 

subbasins combined, the deficits remained similar and were 

ultimately reduced or minimized through reductions in withdrawals (Tier 3).

Seasonal-conjunctive use (Tier 2) did not eliminate 

deficits for any subbasin (elimination of deficits was expected) 

and made deficits worse in the mixed subbasins; however, 

the manner in which the adjustments were simulated affected 

these results. With an attempt to eliminate deficits in all subbasins at the same time, there were substantial effects on other 

downdip subbasins and on the mixed subbasins because of 

the increased withdrawals from the Atlantic City 800-foot 

sand during the summer months in the seasonal-conjunctive 

use approach. The biggest effect was that in attempting to 

reduce deficits in subbasin 02040302020, increased deficits 

occurred in adjacent subbasins. The large volume of withdrawals moved from the Kirkwood-Cohansey aquifer system to the 

Atlantic City 800-foot sand in this subbasin had a great effect 

on neighboring downdip subbasins, as well as on mixed and 

updip subbasins. Effects on mixed and updip subbasins would 

be less severe, and water-level decline in the Atlantic City 

800-foot sand would be less, if withdrawals from subbasin 

02040302020 were not moved from the Kirkwood-Cohansey 

aquifer system to the Atlantic City 800-foot sand in the 

summer. 
Simulation and Results of Withdrawal Scenarios 87

EXPLANATION

Basic

Tier 1

Tier 2

Tier 3

ADJUSTMENT

A. Average B. Full Allocation C. 2050 Demand

5,000

4,000

3,000

2,000

1,000

0

5,000

4,000

3,000

2,000

1,000

0

5,000

4,000

3,000

2,000

1,000

0

Updip Mixed Downdip All Updip Mixed Downdip All Updip Mixed Downdip All

Base-flow deficit, in million gallons

Subbasins Subbasins Subbasins

Figure 50. Simulated base-flow deficits under A, Average, B, Full Allocation, and C, 2050 Demand scenarios with basic, Tier 1, Tier 2, 

and Tier 3 adjustments for the entire study area and updip, mixed, and downdip subbasins, southeastern New Jersey.

Reductions in withdrawals needed to eliminate deficits (Tier 3) were large. In some cases, however, reductions 

may have been larger than necessary because of the way 

the simulations were developed and adjusted. Because the 

seasonal-conjunctive-use adjustment (Tier 2) was applied 

first, increased deficits in mixed and updip subbasins resulted, 

which were then decreased by subsequent reductions in 

withdrawals (Tier 3). Similarly, an attempt to reduce deficits 

in subbasin 02040302020 caused a larger effect on base-flow 

deficits in mixed and updip subbasins and on water-level 

declines in the Atlantic City 800-foot sand than would have 

occurred if there had been no attempt to reduce deficits in this 

subbasin. (Deficits could not be eliminated in this subbasin.)

The purpose of the adjustments to scenarios was to 

illustrate several approaches that could be used to reduce baseflow deficits in the study area. These adjustments, however, 

are not the only means by which deficits could be reduced or 

eliminated. Also, these adjustments are not intended to represent any current management plan but are simply intended 

to illustrate the effects of the different approaches. Simulating reductions of withdrawals is not intended to imply that 

this approach is part of any plan for the Kirkwood-Cohansey 

aquifer system. The results of these simulations are presented 

merely to show the magnitudes of withdrawal reductions that 

would be needed to reduce or eliminate base-flow deficits. 

The results of these adjustments could be used in formulating water-management plans by showing a range of possible 

strategies and relative effectiveness. 

Summary of Final Deficits

The final adjusted conditions are the results of the Tier 3 

simulations. The maximum annual deficit and the simulation 

year in which it occurred for each HUC11 subbasin are shown 

in figure 51. For all basic scenarios, subbasin 02040302020 

was in deficit under adjusted conditions because of the zero 

base-flow depletion criterion for that subbasin in some summer months. The remaining subbasins in deficit are those 

mixed or updip subbasins discussed previously that were 

affected by declining heads in the summer in the Atlantic City 

800-foot sand that resulted from seasonal-conjunctive use. As 

discussed previously, some of these deficits might be eliminated if seasonal-conjunctive use was simulated differently or 
88 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

2050 Demand

"

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Full Allocation

"

"

"

"

"

"

" "

"

Buena

Woodbine

Hammonton

Ocean City

Mays Landing

Somers 

Point

Pleasantville

Atlantic City

Egg Harbor 

City

"

Average

"

A B

C

Base from U.S.Geological Survey 

digital line graph files, 1:24,000

0 5 10 MILES

0 5 10 KILOMETERS

EXPLANATION

SIMULATED MAXIMUM ANNUAL BASE-FLOW 

DEFICIT, IN MILLION GALLONS PER YEAR

> 0 - 20

> 20 - 80

Updip extent of the Atlantic City 800-

foot sand (From Zapecza, 1989)

Upper number is basin number, middle 

number is maximum annual deficit, and

bottom number is the scenario year in 

which the maximum deficit occurred

02040301170

7.48

5

(>, greater than)

02040302050

02040302040

02040301160

02040302070

02040301190

02040301170

3.86

5

02040301150

02040301210

02040302030

02040302060

02040301200

0.31

2

02040301180

21.32

2

02040302010

02040302020

10.21

6

02040302050

02040302040

02040301160

02040301170

02040302070

02040301150 02040301190

02040301210

02040301200

02040302030

02040302060

02040301180

3.5

2

02040302010

02040302020

7.58

6 02040302050

02040302040

02040301160

02040302070

02040301190

02040301170

7.48

5

02040301150

02040301210

02040302030

02040302060

02040301200

0.27

2

02040301180

25.57

2

02040302010

02040302020

9.98

6

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

39°

20' 

75° 74°40' 74°20’

39°

40' 

Figure 51. Simulated maximum annual base-flow deficits for Hydrologic Unit Code 11 subbasins in southeastern New Jersey, under A, 

Average, B, Full Allocation, and C, 2050 Demand scenarios with Tier 3 adjustments.
Summary and Conclusions 89

was not used as an alternative. Adjusting the base-flow depletion criteria by changing the percentage of the low-flow margin available for use would also result in different deficits for 

the scenarios. Analysis of basins where deficits are simulated 

as occurring under Average conditions could be investigated to 

see if signs of impact of base-flow depletion are visible.

Summary and Conclusions

Groundwater is an essential component of the water supply and plays a critical role in maintaining the environmental 

health of freshwater and estuarine ecosystems in the Atlantic 

Coastal basins of New Jersey. The unconfined KirkwoodCohansey aquifer system and the confined Atlantic City 

800-foot sand are major sources of groundwater in the area, 

and each is subject to different water-supply concerns in an 

area where future water demand is on the rise. The U.S. Geological Survey (USGS), in cooperation with the New Jersey 

Department of Environmental Protection (NJDEP), conducted 

a study to simulate the effects of withdrawals in both aquifers, as well as the Rio Grande water-bearing zone. The study 

area encompasses Atlantic County and parts of Burlington, 

Camden, Gloucester, Ocean, Cape May, and Cumberland 

Counties. Recent groundwater withdrawals have created cones 

of depression in the Atlantic City 800-foot sand and caused 

base-flow depletion in streams in some subbasins.

The major hydrogeologic units affecting water supply in 

the study area are the surficial Kirkwood-Cohansey aquifer 

system, a thick diatomaceous clay confining unit in the upper 

part of Kirkwood Formation; the Rio Grande water-bearingzone; and the Atlantic City 800-foot sand of the Kirkwood 

Formation. The hydrogeology of the three aquifers was 

assembled from published reports, available data, and data 

collected as part of this study. The hydrogeologic framework 

was revised from a more regional representation of the New 

Jersey Coastal Plain aquifer system to include a clay-rich zone 

identified in the southeastern part of the study area within the 

Kirkwood-Cohansey aquifer system in the model. The Rio 

Grande water-bearing zone was also included as a separate 

layer in the model. 

The Kirkwood-Cohansey aquifer system is present 

throughout the entire study area. The aquifer system consists primarily of gravel, sand, silt, and clay sediments of the 

Cohansey and Kirkwood Formations. The Kirkwood-Cohansey aquifer system is generally considered to be unconfined; 

however, discontinuous clays are common, especially in 

sediments of the Cohansey Formation. Many of the clay units 

within the generally unconfined Kirkwood-Cohansey aquifer system are of variable extent. The Kirkwood-Cohansey 

aquifer system is underlain by a confining unit in the downdip 

areas. There has been uncertainty about the updip extent and 

character of the confining unit. This uncertainty has limited 

the understanding of how effectively the Atlantic City 800-

foot sand is connected vertically to the generally unconfined 

Kirkwood-Cohansey aquifer system, which appears to transition into a single aquifer beyond the updip edge of the clay. 

The Rio Grande water-bearing zone is a thin aquifer in the 

southeastern half of the study area and is present within the 

major confining unit overlying the Atlantic City 800-foot sand.

Hydrogeologic data needed to prepare the groundwater 

flow model were collected or assembled during the study. 

Horizontal hydraulic-conductivity data from 18 aquifer tests 

conducted in the area were used. Estimates of specific capacity at public supply wells were used to supplement these 

data. Withdrawal data for the Kirkwood-Cohansey aquifer 

system, the Atlantic City 800-foot sand, and the Rio Grande 

water-bearing zone in the study area were used as input to the 

groundwater flow model. Withdrawals from the KirkwoodCohansey aquifer system were about twice those from the 

deeper Atlantic City 800-foot sand aquifer. Withdrawals from 

the Rio Grande water-bearing zone were relatively minor. 

Groundwater withdrawals were primarily used for public supply and irrigation. Seasonal variations in withdrawals in the 

summer months (June through August) were sometimes more 

than twice the withdrawals in the winter months (December 

through February). Also, the variability in withdrawals was 

greater in the summer. Base flow is the groundwater contribution to the total flow of a stream. Monthly base flow was estimated for 12 streamgaging stations with continuous records. 

Low-flow statistics at partial-record stations were estimated 

using data from the 12 streamgaging stations. The correlation 

of streamflows between the index stations and the low-flow 

partial-record stations was used to estimate monthly base flow 

and direct runoff at 51 low-flow partial-record stations. The 

base-flow values were used as model calibration targets for 

each subbasin. The direct runoff estimated using base-flow 

separation was in turn used to estimate average direct runoff 

for the study area for use in estimation of recharge. Recharge 

was estimated on a monthly basis using a water-budget 

approach. 

The groundwater flow model is a representation of the 

heads and groundwater flow in the Kirkwood-Cohansey 

aquifer system, the Rio Grande water-bearing zone, and the 

Atlantic City 800-foot sand with sufficient accuracy and 

resolution to facilitate an analysis of the regional flow system. 

The Kirkwood-Cohansey aquifer system within the drainage 

areas of the Great Egg Harbor River and the Mullica River 

was modeled. The confined aquifers were modeled over a 

larger area so that the boundary conditions were distant from 

the main area of interest. Boundary flows for the confined 

aquifer were obtained by modifying the New Jersey Regional 

Aquifer-System Analysis (RASA) model and simulating the 

same conditions over a larger area. Grid spacing in the onshore 

part of the model is 880 x 880 or 880 x 1,100 ft on a side to 

adequately represent surface-water features in the model. Grid 

spacing is larger in offshore areas. Grid alignment and spacing were selected so that the model grid fits within the RASA 

model and boundary conditions for the confined Atlantic City 

800-foot sand could be attained easily. The simulation period 
90 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

for model calibration is January 1999 through September 

2006. 

Hydrologic boundaries were used to represent the locations and quantity of flow into and out of the model. Recharge 

used in the model is based on three factors—spatial variation based on a New Jersey Geological Survey recharge map, 

temporal variation based on monthly recharge estimated from 

base-flow data, and model calibration zones. Recharge was 

simulated using the Recharge package of MODFLOW. Artificial recharge to the Kirkwood-Cohansey aquifer system from 

land-application recharge basins of two wastewater-treatment 

plants in the study area was also simulated. Surface-water 

features represented in the model are freshwater wetlands, 

rivers, streams, lakes or ponds, saltwater wetlands, the ocean, 

and bays. These features are simulated using either the River 

or Drain package or as constant head cells (for saltwater wetlands or ocean cells). Freshwater surface-water features were 

derived from the National Hydrography Dataset. Altitudes of 

the stages of the river, stream, pond, or wetland were initially 

assigned using the best available Digital Elevation Model 

data, which were obtained from the National Elevation Dataset. Subsequently, stream stages were revised to ensure that 

downstream stages were lower than upstream stages to correct 

problems with simulated heads near surface-water features. 

Groundwater withdrawals were simulated using the Well package in MODFLOW. The lateral flow boundary for the surficial 

aquifer is a no-flow boundary at the basin boundaries of the 

Great Egg Harbor and Mullica River Basins. For the confined 

Atlantic City 800-foot sand, the lateral boundaries to the north 

and south, and offshore, are flows from the revised New Jersey 

RASA model. The lower boundary for the model is a flow 

boundary incorporating vertical flows from the revised New 

Jersey RASA model into the unconfined and confined parts of 

the Great Egg Harbor and Mullica River model. 

Simulated water levels, base flow, and hydraulic gradients were compared to observed values to calibrate the 

groundwater flow model. A total of 32 parameters was used to 

adjust model values to obtain a fit to the observed values. During calibration, parameters representing horizontal hydraulic 

conductivity, vertical hydraulic conductivity of confining 

units, recharge, streambed conductance, and storage were 

adjusted to fit head and base-flow observations. Seven parameters were used to represent horizontal hydraulic conductivity, 

eight to represent vertical hydraulic conductivity, and eight to 

represent the streambed hydraulic conductivities for modeled 

rivers and drains. Seven parameters were used for recharge, 

and two were used for storage.

A variety of data were collected or assembled in order 

to calibrate the groundwater flow model—synoptic water 

levels, long-term water levels, monthly estimates of base flow, 

and vertical head gradients. Synoptic data used to calibrate 

the groundwater flow model were collected during 2005 and 

2006. Data collected in May 2005 represent high water-level 

and streamflow conditions during spring. Data collected in 

September 2006 represent late summer conditions when water 

levels and streamflow typically are at the lowest levels of the 

year. In addition to the water levels measured in 2005 and 

2006 as part of this study, other water-level data from wells 

completed in the Atlantic City 800-foot sand and included in 

the New Jersey Coastal Plain Synoptic Water-Level Network 

in 1998 and 2003 were used in this study. Daily water-level 

data from 14 wells in the U.S. Geological Survey New Jersey 

Water-Level Monitoring Network were used to create monthly 

hydrographs for use in model calibration. Base-flow data from 

22 sites in the area were used to create base-flow hydrographs. 

Simulated base flows in the River and Drain packages of the 

model were calibrated to the base-flow hydrographs generated 

for the study area. 

The shapes of the simulated contours for spring 2005 and 

fall 2006 in the Kirkwood-Cohansey aquifer system closely 

follow those of the water-table maps created for previous studies of the surficial aquifer in the Mullica and Great Egg Harbor 

River Basins. Throughout most of the study area, the simulated water levels were within +/- 5 ft of the observed water 

levels. The largest and most frequent occurrence of residuals 

(simulated minus observed values) of more than 5 ft was for 

the area northwest of Pleasantville, N.J., along the divide 

between the Mullica and Great Egg Harbor River Basins. Most 

of these large residuals occurred when the simulated head was 

much lower than the observed head. Hydrographs of wells in 

the Kirkwood-Cohansey aquifer system show that simulated 

heads match the observed seasonal changes fairly well. Most 

of the simulated heads are within 5 ft of the observed heads. 

In the Atlantic City 800-foot sand, simulated water levels 

match observed water levels well, except for an area along 

the coast near and north of Ocean City, N.J., where simulated 

water levels were as much as 10 ft lower than observed water 

levels. Most of the residuals fall within +/- 5 ft. Calibration 

of simulated base-flow values to observed values was accomplished by using visual comparison of hydrographs. Base-flow 

hydrographs for the six streamgaging stations are considered 

the best observed base-flow data for use in calibration. Most 

of the simulated and observed hydrographs match fairly well 

and have moderate to small root mean square errors. Parameter values that most affected the calibration of the base-flow 

hydrographs are the streambed conductance values for the 

River and Drain packages and the multiplier for recharge. 

The sensitivity of simulated hydraulic heads to the model 

parameters was calculated using UCODE-2005. Composite 

scaled sensitivities (CSS) were calculated for 31 parameters 

using the observed heads from 1998, 2003, 2005, and 2006 

and the data from the monthly hydrographs for the water-level 

network sites. The parameters with the largest CSS values are 

the horizontal hydraulic conductivities for the Atlantic City 

800-foot sand and the deep part of the unconfined KirkwoodCohansey aquifer system. 

Groundwater flow budgets were created for the Great 

Egg Harbor and Mullica River model calibration periods— 

May 2005, September 2006, and 1998 to 2006, the entire 

9-year model calibration period. Flow budgets for the model 

calibration periods 2005 and 2006 allow comparison of the 
Summary and Conclusions 91

contributions from different parts of the flow system during 

the spring and fall. 

Much more water moves through the unconfined Kirkwood-Cohansey aquifer system than through the Atlantic 

City 800-foot sand. The major input to the flow budget for 

the Kirkwood-Cohansey aquifer system is recharge. Most of 

the recharge received is then discharged to drains or rivers. 

The term representing flow from the unconfined KirkwoodCohansey aquifer system to the confined Atlantic City 800-

foot sand is a minor part of the flow budget for the unconfined 

aquifer, but it is the major source of water for the Atlantic 

City 800-foot sand. Flows into the confined aquifer from 

lateral and vertical flow boundaries were a substantial source 

of water to the aquifer. The major outflow from the confined 

aquifer was discharge to pumped wells. The flow budget for 

1999 to 2006 shows the transient effects of the major components of the flow system during the calibration period. In the 

Kirkwood-Cohansey aquifer system, recharge varies monthly 

and was greatest in winter to early spring. Flow out to drains 

was also greatest at these times. In the Atlantic City 800-foot 

sand, withdrawals were seasonal and greatest in the summer 

and fall. Flow into this aquifer from storage also was greatest 

in the summer. Flow from the Atlantic City 800-foot sand into 

storage occurred in winter. 

Simulations of various scenarios were run using the calibrated model to compare simulated base-flow depletion with 

base-flow depletion criteria to determine, as part of this study, 

where and when base-flow deficits could occur or be expected 

to occur in the future. Results of the simulations were analyzed using Hydrologic Unit Code 11 (HUC11) subbasins 

delineated within the study area. The 14 HUC11 subbasins 

were categorized as updip, mixed, or downdip for analysis. 

Subbasins that span the updip limit line for the confining unit 

overlying the Atlantic City 800-foot sand were designated 

“mixed.” Parts of these subbasins overlie the unconfined aquifer, and parts overlie both confined and unconfined aquifers. 

The interaction of the Kirkwood-Cohansey aquifer system and 

the confined Atlantic City 800-foot sand in the mixed subbasins is an important finding from these simulations. 

Six scenarios—three basic and three adjusted—were 

simulated to assess base-flow depletion that could occur 

in different groundwater-withdrawal situations. Simulated 

base-flow depletion was compared to monthly criteria determined by NJDEP. Base-flow depletion was calculated for each 

scenario by subtracting the base flow for each HUC11 subbasin from the base flow that would have occurred during the 

simulation period had there been no groundwater withdrawals. 

The basic scenarios represent average 1998–2006 withdrawals, full-allocation withdrawals, and projected 2050 demand 

withdrawals. These basic scenarios were intended to identify 

subbasins where deficits may be occurring currently (2012) or 

where they may occur under future conditions. The adjusted 

scenarios simulate variations of the Average, Full Allocation, and 2050 Demand scenarios in which the withdrawals 

were modified in an attempt to eliminate or reduce base-flow 

deficits. This adjustment was done by moving withdrawals to 

a deeper aquifer, by seasonal-conjunctive use of shallow and 

deep aquifers, or by reductions in withdrawals from a HUC11 

subbasin in deficit. The results of the simulations are considered to be conceptual evaluations, showing only what the 

adjustments might achieve.

In order to evaluate simulation results, monthly baseflow depletion criteria were needed for each of the 14 HUC11 

subbasins in the study area. The approach used to determine 

the monthly base-flow-depletion criteria was based on the 

Low-Flow Margin method used by NJDEP to estimate available water on an annual basis at the HUC11 level. The method 

assumes that some percentage of streamflow can be removed 

without affecting stream ecology. For the method, available 

water is defined as a percentage of the difference between 

normal dry-season streamflow and drought streamflow. The 

September median flow represents typical flows for September, which are generally the lowest flows of the year in New 

Jersey. The 7-day, 10 year (7Q10) flow represents drought 

flows. The low-flow margin is the difference between the 

September median flow and the 7Q10 flow. The NJDEP 

defines available water as a percentage of this margin. The 

water available for depletive and consumptive use is defined 

as 25 percent of the Low-Flow Margin. The NJDEP LowFlow Margin method was modified for this study to determine 

monthly base-flow depletion limits for the Great Egg Harbor 

and Mullica River Basins. The modification was necessary in 

order to consider seasonal-conjunctive use of shallow unconfined and deeper confined sources as an alternative within the 

study area.

The simulation of the Average scenario was run using 

average annual water-use data for 1998 to 2006. In this simulation, base-flow deficits occurred during June to November. 

Simulated heads in the Atlantic City 800-foot sand under 

average conditions were more than 80 feet below National 

Geodetic Vertical Datum of 1929 in the spring and more than 

100 feet below land surface in September of scenario year 9.

The simulation of the Full Allocation scenario represents 

conditions that would occur if all wells were pumped at their 

full-allocation rate. In the Full Allocation scenario, all but 

three downdip subbasins with few agricultural withdrawals 

were in deficit. Deficits in the mixed subbasins and in many of 

the updip subbasins in the Full Allocation scenario were much 

larger than in the Average scenario because of the increased 

agricultural withdrawals. Simulated heads in the Atlantic 

City 800-foot sand near the center of the cone were more 

than 120 feet below land surface in April of scenario year 9 

and more than 150 feet below land surface in September of 

scenario year 9. 

The simulation of the 2050 Demand scenario was run 

with an agricultural-use constant at the average 1998 to 2006 

levels and using estimated 2050 demand for wells with public 

supply and other permit types. In this scenario, some updip 

subbasins in the Mullica River Basin were no longer in deficit. 

However, base-flow deficits in the mixed and updip subbasins 

were larger under the 2050 Demand scenario than under the 

Average scenario because of the effects of increased public 
92 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

supply withdrawals from the confined Atlantic City 800-foot 

sand in the unconfined part of the aquifer. Simulated heads 

in the Atlantic City 800-foot sand at the center of the cone of 

depression were more than 120 feet below NGVD 29 in April 

of scenario year 9 and were more than 160 feet below NGVD 

29 in September of scenario year 9. 

Simulation of the basic scenarios identified subbasins 

that would be in deficit under average, full-allocation, and 

2050 demand conditions. These base-flow deficits were 

addressed by using three tiers of hypothetical adjustments. 

These hypothetical adjustments are not intended to reflect 

any management policy in place or under consideration but 

simply to illustrate the relative effects of the methods. In 

Tier 1, the depths of the withdrawal wells in the KirkwoodCohansey aquifer system in downdip subbasins was changed. 

Tier 2, seasonal-conjunctive use, incorporated the results of 

Tier 1, then implemented a shift of withdrawals between the 

Kirkwood-Cohansey aquifer system and the Atlantic City 800-

foot sand, seasonally. Finally, Tier 3 incorporated the results 

of Tier 2, then reduced the magnitude of withdrawals. Tier 1 

adjustment had little effect and did not eliminate deficits in 

any subbasin. Tier 2 adjustments (seasonal-conjunctive use) 

improved base-flow deficits in only one downdip subbasin, 

reducing the deficit by 40 to 80 percent of the total base-flow 

deficit in that subbasin for the 2050 Demand, Full Allocation, 

and 1998 to 2006 Average scenarios. In mixed subbasins, 

where base-flow deficits were present, seasonal-conjunctive 

use increased the deficits. This is because of the declining 

summer heads caused by increased summer withdrawals from 

the Atlantic City 800-foot sand within the mixed subbasins or 

downdip subbasins. This finding is important because it shows 

that withdrawals from the confined aquifer have an effect on 

base flows in the subbasins located updip from the limit of 

the confining unit overlying the Atlantic City 800-foot sand. 

Heads in the Atlantic City 800-foot sand recovered by as much 

as 20 feet during the spring but declined by as much as 70 feet 

by the end of the summer, and heads in the aquifer reached 

levels of more than 190 feet below NGVD 29 in the seasonalconjuctive use approach. Given the increased deficits in the 

mixed subbasins and the head declines in the Atlantic City 

800-foot sand, seasonal-conjunctive use would not solve the 

base-flow deficits if applied throughout the study area. Finally, 

Tier 3 was simulated; withdrawals were reduced on a subbasin-by-subbasin basis until all deficits were eliminated or minimized. The reduction of withdrawals could represent shifting 

the water supply to a different source or reducing water use. 

The base-flow deficits for most subbasins were eliminated by 

reducing withdrawals from unconfined aquifers. 

Using the three-tier approach to reduce or eliminate 

base-flow deficits showed that all three adjustments were 

necessary to eliminate deficits in most subbasins. The Tier 1 

approach of moving withdrawals from the unconfined part of 

the Kirkwood-Cohansey aquifer system to the semi-confined 

part of the Kirkwood-Cohansey aquifer system did not 

substantially reduce deficits. The Tier 2 approach of seasonalconjunctive use worked well for only one downdip subbasin. 

Also, the shifting of some withdrawals to the confined Atlantic 

City 800-foot sand in the summer caused increased deficits in 

several subbasins near the limit of the confining unit overlying 

the aquifer. Most of the reductions in deficits were accomplished by reductions in withdrawals. After simulation of the 

three adjustment tiers, deficits remained in several subbasins. 

This situation occurred in subbasin 02040302020 because no 

base-flow depletion was allowed in that subbasin. Deficits 

remained in subbasins near the updip limit of the Atlantic City 

800-foot sand. These subbasins were affected by the increased 

withdrawals from the Atlantic City 800-foot sand during the 

summer in the Tier 2 approach. A change in the base-flow 

depletion criteria would also change the ratio of success in 

eliminating deficits.

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94 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

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Table 3 95

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

010013 3600000299 121CKKD 205 710 8 27 152

010015 -- 122KRKDL 831 554 4 52 62

010040 3600000057 122KRKDL 769 706 8 60 52

010041 5600000009 122KRKDL 829 700 8 93 40

010042 5600000010 122KRKDL 788 700 8 60 73

010114 3100005832 121CKKD 179 351 8 20 52

010116 -- 122KRKDL 401 750 6 52 156

010117 3200000477 122KRKDL 432 768 12 82 86

010118 3200000175 122KRKDL 406 415 8 40 48

010121 3600000271 122KRKDL 783 300 8 40 105

010135 3600000429 121CKKD 127 1,016 24 35 297

010138 3600000404 121CKKD 133 1,223 24 23 175

010150 3600000431 121CKKD 222 1,016 22 36 113

010151 3600000428 121CKKD 208 1,016 24 36 201

010154 3600000401 121CKKD 160 503 6 30 66

010160 3600000367 121CKKD 165 670 16 37 214

010172 3600000426 121CKKD 204 1,000 4 40 25

010175 3600000408 121CKKD 250 610 8 52 58

010183 3600000443 121CKKD 192 415 8 20 28

010185 3600000392 121CKKD 173 307 8 33 44

010189 3600000420 121CKKD 159 495 8 41 24

010190 3600000421 121CKKD 167 402 24 31 57

010191 3600000422 121CKKD 159 403 24 26 49

010193 3600000425 121CKKD 150 325 4 20 103

010194 3600000424 121CKKD 145 300 4 20 94

010218 3600000439 121CKKD 118 450 4 20 154

010220 2800008310 121CKKD 169 524 8 30 71

010222 3600000396 121CKKD 87 305 8 20 154

010225 3600000260 121CKKD 160 210 8 20 91

010227 3600000391 122KRKDL 347 754 8 31 73

010229 5600000023 121CKKD 243 427 24 30 52

010231 3600000290 121CKKD 151 300 8 20 115

010232 3600000399 121CKKD 151 800 8 22 82

010250 3200000474 121CKKD 157 210 12 15 202

010251 3200000473 121CKKD 142 201 12 15 144

010264 -- 121CKKD 107 200 16 10 76

010276 3100004684 121CKKD 77 480 8 15 208

010279 5100000039 121CKKD 328 675 8 52 231

010281 5100000037 121CKKD 315 700 4 60 68

010284 3100004266 121CKKD 171 600 10 30 88
96 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

010292 3100005022 121CKKD 241 1,000 8 40 494

010293 3100004872 121CKKD 252 396 8 50 45

010353 3600000315 121CKKD 71 525 8 15 120

010355 3600000286 121CKKD 252 904 8 106 17

010356 3600000284 121CKKD 262 904 8 20 125

010360 3600000041 121CKKD 165 300 24 20 71

010361 3600000042 121CKKD 165 300 24 20 71

010362 3600000368 121CKKD 146 1,000 8 50 75

010367 5600000038 122KRKDL 800 725 8 50 164

010368 5600000037 122KRKDL 805 517 8 67 78

010369 3600000402 122KRKDL 811 1,007 8 50 79

010370 3600000318 122KRKDL 801 1,000 8 50 136

010372 3600000326 122KRKDL 803 800 8 40 94

010374 -- 122KRKDL 810 770 8 50 101

010375 3600000197 122KRKDL 797 700 8 50 112

010376 3600000278 122KRKDL 791 700 8 50 89

010378 3200000529 121CKKD 176 868 5 140 40

010382 3200000623 121CKKD 154 503 7 20 57

010388 -- 121CKKD 108 200 16 11 69

010549 3600000008 121CKKD 152 620 8 30 156

010549 3600000008 121CKKD 152 620 8 30 180

010554 3600000383 121CKKD 141 302 8 25 208

010563 -- 121CKKD 109 1,100 24 61 88

010565 3600000014 122KRKDL 668 1,056 8 50 71

010568 3600000013 122KRKDL 636 1,050 8 50 125

010572 3600000405 121CKKD 105 1,012 8 30 106

010582 3600000021 121CKKD 99 1,000 8 20 133

010583 -- 121CKKD 123 450 8 40 23

010589 3600000388 121CKKD 159 1,000 8 30 74

010593 3600000372 122KRKDL 793 1,022 8 50 103

010596 5600000013 122KRKDL 810 500 8 50 54

010598 3600000371 122KRKDL 803 818 8 60 56

010600 5600000016 122KRKDL 810 750 8 60 178

010636 -- 121CKKD 53 402 72 10 259

010637 3200005113 122KRKDL 428 602 8 90 11

010657 3100005464 121CKKD 124 500 5 54 88

010660 3600001866 121CKKD 157 360 8 20 275

010680 -- 122KRKDL 835 400 8 62 40

010683 3600002091 122KRKDL 780 1,060 8 50 63
Table 3 97

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

010686 3600003110 121CKKD 172 305 8 20 154

010689 3600002433 121CKKD 180 904 8 50 125

010696 3600003934 121CKKD 180 1,205 72 50 82

010697 3600003935 121CKKD 175 1,205 72 50 66

010698 3600003936 121CKKD 179 1,205 72 50 81

010708 3600000468 121CKKD 168 411 8 40 95

010781 3600005292 121CKKD 182 1,507 8 51 71

010782 3600005296 121CKKD 180 1,705 8 50 104

010783 3600005295 121CKKD 183 1,507 8 51 76

010785 3600005293 121CKKD 184 1,507 8 51 99

010786 3600005297 121CKKD 176 1,507 8 51 79

010789 3600006288 121CKKD 242 473 24 43 95

010864 3200013099 121CKKD 160 400 4 100 17

010866 3600005809 121CKKD 151 340 8 20 259

010874 3600004463 121CKKD 135 212 24 20 54

010889 3600011871 122KRKDL 795 1,216 4 60 100

010918 3600014427 121CKKD 153 802 8 40 205

010933 3200015836 121CKKD 135 300 4 60 47

010958 3600012463 121CKKD 180 1,808 72 60 141

010967 3600013010 122KRKDL 776 1,205 48 74 74

010970 3600002070 121CKKD 200 578 72 30 59

010972 3600008845 121CKKD 156 850 72 32 189

010973 3600014415 121CKKD 185 907 5 51 109

010974 3600006629 121CKKD 150 350 4 50 127

010975 3600011999 121CKKD 150 350 4 60 41

010985 3600015426 122KRKDL 790 1,231 72 51 155

010990 3600016110 122KRKDL 657 1,150 72 156 31

010991 3600016204 122KRKDL 647 1,295 72 150 49

010993 3600007215 121CKKD 150 350 4 50 122

010995 3100007656 121CKKD 120 240 4 80 49

010996 3600013489 121CKKD 160 500 4 70 129

010997 3600009890 121CKKD 160 450 4 80 30

011005 3100029188 121CKKD 140 250 4 70 66

011007 3100029626 121CKKD 153 600 4 100 106

011010 3200000229 121CKKD 117 350 8 26 96

011024 3100028718 121CKKD 135 410 4 80 47

011247 3100020122 121CKKD 170 356 4 60 79

011252 3200020165 122KRKDL 446 730 24 104 114

011253 3600016750 122KRKDL 603 1,275 72 254 24
98 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

011255 3600019350 122KRKDL 647 1,295 72 150 49

011256 3600017667 122KRKDL 801 1,200 72 147 71

011257 3600018120 122KRKDL 619 1,800 72 90 93

011294 3600004033 121CKKD 150 350 4 40 75

011295 3100011806 121CKKD 104 210 4 74 15

011297 3600015811 121CKKD 150 250 4 90 19

011299 3500006780 121CKKD 135 500 4 100 94

011310 3500001164 121CKKD 107 268 8 26 37

011315 3100019150 121CKKD 90 300 4 20 284

011319 3500001163 121CKKD 108 200 4 26 36

011323 3600000452 121CKKD 70 500 4 30 90

011325 3600015681 121CKKD 190 500 12 50 36

011328 3200004267 121CKKD 138 280 4 90 24

011341 3200004268 121CKKD 139 310 4 90 24

011346 3600017074 121CKKD 212 1,150 72 40 80

011364 3600015680 121CKKD 190 500 12 50 36

011381 3200021134 121CKKD 120 500 4 80 113

011438 3600000303 121CKKD 182 200 8 20 235

011456 3600021156 122KRKDL 652 916 24 50 55

011460 3600020165 122KRKDL 798 938 72 118 81

011507 3600024428 122KRKDL 665 1,328 72 118 31

011508 3600024429 121CKKD 127 1,200 72 46 147

011576 3600025639 121CKKD 215 752 4 40 69

011614 3200014198 121CKKD 135 500 4 80 43

011616 3200012931 121CKKD 140 500 4 70 27

011649 3600000454 122KRKDL 621 465 8 55 98

011674 3600010221 121CKKD 225 280 6 30 53

011675 3100011576 121CKKD 97 525 4 25 85

011677 3100005469 121CKKD 124 500 5 54 88

011679 3100033895 121CKKD 155 450 4 80 86

011696 3100046647 121CKKD 130 201 4 60 124

050674 3200000688 121CKKD 179 4,447 8 70 112

050708 3200000727 121CKKD 92 200 8 15 221

050710 3200000725 121CKKD 121 315 8 15 131

050727 3200000811 121CKKD 76 850 6 24 127

051119 3200015738 121CKKD 100 450 4 80 22

051132 3200008781 121CKKD 182 4,560 8 72 205

051133 3200013974 121CKKD 161 1,016 6 31 91

051442 3200009228 121CKKD 90 520 4 20 243
Table 3 99

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

051453 3200000508 121CKKD 180 1,350 4 90 161

051463 3200009979 121CKKD 65 300 4 31 45

051469 3200003227 121CKKD 206 600 6 100 105

051470 3200003228 121CKKD 202 1,100 6 90 185

051473 3200008959 121CKKD 182 4,560 8 72 205

051474 3200019150 121CKKD 182 500 4 110 61

051641 3200024086 121CKKD 67 317 4 30 56

070226 3100001449 121CKKD 102 240 24 20 45

070456 3100005389 121CKKD 140 310 8 10 99

070468 3100005716 121CKKD 165 715 8 20 106

070470 3100000995 121CKKD 167 708 8 26 60

070471 3100000996 121CKKD 138 502 5 21 64

070481 3100006874 121CKKD 111 1,012 8 33 162

070483 -- 121CKKD 139 225 8 21 224

070490 3100005542 121CKKD 113 1,000 48 31 231

070497 3100005543 121CKKD 101 1,000 48 26 192

070499 3100004678 121CKKD 101 596 8 19 123

070501 3100005295 121CKKD 141 510 8 25 144

070505 3100003277 121CKKD 110 240 8 8 484

070603 3100016697 121CKKD 120 503 8 20 65

070686 3100003194 121CKKD 50 250 10 10 373

070691 3100024727 121CKKD 80 305 24 15 105

070694 3100026187 121CKKD 64 218 8 20 60

070698 3100026123 121CKKD 167 525 72 30 221

070708 3100022373 121CKKD 120 201 72 30 63

070736 3100005578 121CKKD 97 200 4 15 79

070809 3100038740 121CKKD 130 250 4 90 52

070814 3100021345 121CKKD 135 475 4 100 42

070831 3100037167 121CKKD 89 324 72 36 49

070899 3100047169 121CKKD 80 500 4 22 166

070900 3100047168 121CKKD 90 240 8 20 48

070901 3100051329 121CKKD 150 1,146 72 42 253

070982 3100005229 121CKKD 139 225 8 20 209

070983 3100029724 121CKKD 136 300 8 20 80

070995 3100051944 121CKKD 72 352 24 20 67

071002 3100034400 121CKKD 140 425 4 80 67

071003 3100030945 121CKKD 140 500 4 70 39

071084 3100024130 121CKKD 93 200 8 10 137

071093 3100059328 121CKKD 155 805 72 40 88
100 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

071095 3100064904 121CKKD 153 850 24 40 78

071139 3100037014 121CKKD 107 400 4 30 57

071144 3100068206 121CKKD 115 720 72 30 125

090108 3600000412 122KRKDL 843 768 24 66 70

090110 3600000373 122KRKDL 814 831 8 55 99

090117 3600000017 122KRKDL 798 700 8 52 82

090124 3600000413 122KRKDL 843 768 24 66 68

090128 5700000010 122KRKDL 870 875 10 70 158

090144 3600000451 122KRKDL 691 457 8 40 94

090145 3600000312 121CKKD 150 300 8 20 128

090146 3600000313 121CKKD 120 300 8 20 105

090147 3600000319 121CKKD 145 300 8 20 161

090148 3600000364 122KRKDL 678 300 8 30 14

090317 3500002729 121CKKD 161 805 24 23 742

090422 3600012682 121CKKD 205 540 8 60 57

090481 3600017001 122KRKDL 743 1,413 72 135 81

090482 3600020238 122KRKDL 889 800 4 160 117

090514 3600017504 122KRKDL 710 700 4 50 201

090527 3600023696 122KRKDL 795 1,001 72 130 16

110279 3500002258 121CKKD 168 750 10 60 83

111226 3500009327 121CKKD 168 205 4 30 27

150200 3100000361 121CKKD 106 805 24 37 218

150365 3100005375 121CKKD 144 412 8 34 54

150375 3100014080 121CKKD 147 805 24 29 186

151018 -- 121CKKD 140 340 72 20 204

151048 3100027529 121CKKD 144 492 24 41 51

151068 3100018471 121CKKD 135 300 8 20 235

151336 3100006606 121CKKD 144 355 4 30 121

151624 3100028145 121CKKD 118 300 4 60 90

151628 3100005732 121CKKD 167 200 6 20 51

151629 3100005733 121CKKD 167 200 6 20 51

290455 3300001051 122KRKDU 458 700 8 25 115

290462 3200000609 122KRKDL 564 752 8 44 164

290464 3200000447 122KRKDL 542 508 8 57 173

290465 3200000224 122KRKDU 329 300 8 21 84

290565 3200000479 122KRKDL 497 726 8 35 60

290597 3200005858 122KRKDL 500 1,000 24 100 44

290775 3200008715 122KRKDU 323 366 24 25 58

290927 3300017494 121CKKD 244 340 12 30 254
Table 3 101

Table 3. Horizontal hydraulic conductivity estimated from specific-capacity data, Kirkwood-Cohansey aquifer system, Atlantic City 

800-foot sand, and Rio Grande water-bearing zone, southeastern New Jersey.—Continued

[Aquifer: 121CKKD, Kirkwood-Cohansey aquifer system; 122KRKDL, Atlantic City 800-foot sand; 122KRKDU, Rio Grande water-bearing zone; ft/d, feet 

per day; gal/min, gallons per minute; NJDEP, New Jersey Department of Environmental Protection; --, no data]

U.S. Geological 

Survey well 

number

NJDEP well 

permit 

number

Aquifer

Well depth 

(feet below

land surface)

Discharge 

(gal/min)

Duration 

(hours) Drawdown

Hydraulic 

conductivity 

(ft/d)

291063 3200015207 122KRKDL 526 1,245 24 46 169

291421 3200022507 122KRKDL 516 600 72 106 72

291621 3300040378 122KRKDU 461 885 72 39 66

291730 3200025614 122KRKDL 527 1,476 24 61 156

291731 3200023935 122KRKDL 519 1,266 72 98 105
102 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued [Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in bold are used as base-flow calibration sites; ft3/s, cubic feet per second] Low-flow partial-record station number Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight 01409375 Mullica River near Atco, NJ 3.22 114 01409500 0.000 2.947 0.754 114.640 0.39 01409375 01411500 1.0E-5 2.544 0.741 146.620 0.24 01409375 01411000 2.0E-5 2.700 0.780 117.910 0.37 01409387 Mullica River at outlet of Atsion Lake, at Atsion, NJ 26.7 53 01411000 0.106 1.353 0.895 42.690 0.22 01409387 01409400 0.436 0.994 0.925 37.380 0.28 01409387 01410000 0.070 1.505 0.845 54.320 0.13 01409387 01466500 12.012 1.883 0.735 74.840 0.07 01409387 01409500 0.036 1.507 0.903 36.690 0.29 01409390 Mullica River at Atsion, NJ 33.1 25 01411000 0.094 1.419 0.968 23.286 0.29 01409390 01409500 0.020 1.680 0.963 23.854 0.28 01409390 01409400 0.528 0.988 0.988 19.064 0.43 01409395 Mullica River tributary near Atsion, NJ 4.1 11 01466500 3.697 2.082 0.696 145.235 0.22 01409395 01411000 0.003 2.012 0.770 137.579 0.24 01409395 01409400 0.016 1.548 0.879 93.076 0.54 01409401 Hays Mill Creek at Atco, NJ 3.8 87 01409500 9.94E-3 1.249 0.739 38.867 0.22 01409401 01477120 0.132 0.980 0.754 42.069 0.19 01409401 01411500 0.033 0.919 0.782 37.173 0.24 01409401 01409400 0.087 0.806 0.754 47.126 0.15 01409401 01411000 0.041 1.025 0.750 39.221 0.21 0140940200 Hays Mill Creek near Chesilhurst, NJ 7.13 98 01409400 0.574 0.638 0.788 33.524 0.27 0140940200 01411000 0.285 0.832 0.827 26.188 0.44 0140940200 01409500 0.119 0.952 0.753 31.742 0.30

0140940250 Cooper Branch near Chesilhurst, NJ 1.93 67 01411000 5.60E-6 2.859 0.653 254.870 0.360140940250 01410000 2.35E-6 3.060 0.595 403.700 0.140140940250 01409400 6.0E-5 2.148 0.581 539.540 0.080140940250 01409500 1.07E-7 3.477 0.657 234.540 0.4201409403 Wildcat Branch at Chesilhurst, NJ 1.03 19 01411000 1.71E-8 3.928 0.889 139.260 0.35
Table 6 103

Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued[Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in boldare used as base-flow calibration sites; ft3/s, cubic feet per second]

Low-flow 

partial-record 

station number

Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight

01409403 01409400 1.36E-6 2.823 0.788 370.230 0.0501409403 01466500 0.011 4.607 0.911 107.300 0.600140940310 Wildcat Branch near Chesilhurst, NJ 2.27 86 01411000 0.006 1.418 0.772 54.588 0.280140940310 01409400 0.024 1.039 0.776 60.518 0.230140940310 01409500 0.001 1.656 0.754 55.546 0.270140940310 01410000 0.005 1.479 0.752 60.587 0.230140940360 Sleeper Branch above diversion, near Atsion, NJ 16.1 77 01411000 0.355 0.966 0.949 15.696 0.500140940360 01409400 0.788 0.743 0.926 21.955 0.250140940360 01409500 0.115 1.127 0.899 22.245 0.250140940370 Sleeper Branch near Atsion, NJ 16.1 89 01409500 0.163 1.029 0.876 22.410 0.170140940370 01411500 0.313 0.835 0.927 17.531 0.270140940370 01411000 0.439 0.891 0.946 14.754 0.390140940370 01409400 0.988 0.667 0.907 21.948 0.1701409404 Sleeper Branch at Us Rt 206 near Atsion, NJ 18.2 11 01410000 7.8E-4 1.959 0.835 117.690 0.1001409404 01409400 7.4E-3 1.371 0.970 43.930 0.7201409404 01411000 8.7E-4 1.953 0.879 89.670 0.170140940480 Clark Branch near Atsion, NJ 6.42 87 01409500 7.32E-12 5.775 0.851 214.975 0.230140940480 01477120 5.82E-7 4.783 0.696 1,135.492 0.010140940480 01411500 4.73E-10 4.580 0.825 295.327 0.120140940480 01408000 3.51E-8 4.793 0.777 334.469 0.090140940480 01411000 2.62E-9 4.925 0.875 184.387 0.310140940480 01409400 1.57E-7 3.783 0.879 223.677 0.210140940480 01410000 3.73E-9 4.863 0.756 525.509 0.0401409405 Clark Branch at US Rt 206, near Atsion, NJ 7.12 11 01409400 0.430 0.857 0.961 26.747 0.2701409405 01411000 0.118 1.207 0.963 22.993 0.3701409405 01409500 0.132 1.100 0.952 23.533 0.3501409406 Sleeper Branch at Batsto, NJ 36.2 11 01409400 0.018 1.314 0.993 24.660 0.4701409406 01411000 2.7E-3 1.840 0.965 38.032 0.20
104 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued [Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in bold are used as base-flow calibration sites; ft3/s, cubic feet per second] Low-flow partial-record station number Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight 01409406 01409500 0.001 1.887 0.978 29.451 0.33 01409407 Pump Branch near Blue Anchor, NJ 6.2 18 01466500 1.053 1.918 0.896 42.480 0.61 01409407 01409400 0.036 1.079 0.719 94.120 0.12 01409407 01411000 5.7E-3 1.531 0.818 63.540 0.27 01409408 Pump Branch near Waterford Works, NJ 9.78 86 01410000 0.385 0.774 0.635 41.058 0.25 01409408 01411000 0.355 0.792 0.662 38.872 0.28 01409408 01409400 0.685 0.606 0.627 48.087 0.19 01409408 01409500 0.156 0.901 0.625 39.368 0.28 01409409 Blue Anchor Brook near Blue Anchor, NJ 3.01 23 01466500 0.292 2.370 0.973 29.560 0.56 01409409 01411000 4.2E-4 1.950 0.920 52.148 0.18 01409409 01409400 4.9E-3 1.366 0.954 43.866 0.26 0140940950 Blue Anchor Brook at Elm, NJ 4.86 122 01411000 0.007 1.424 0.802 51.879 0.36 0140940950 01409400 0.022 1.109 0.743 71.777 0.19 0140940950 01409500 1.3E-3 1.677 0.738 61.809 0.25 0140940950 01410000 0.011 1.344 0.699 69.723 0.20 0140940970 Albertson Branch near Elm, NJ 17.1 89 01411000 0.531 0.853 0.841 26.262 0.41 0140940970 01409400 1.119 0.646 0.806 32.846 0.26 0140940970 01409500 0.220 0.972 0.796 29.452 0.33 01409410 Albertson Brook near Hammonton, NJ 19.3 44 01409500 0.297 0.971 0.920 21.003 0.29 01409410 01466500 12.015 1.060 0.922 22.112 0.26 01409410 01409400 1.732 0.614 0.963 16.819 0.45 0140941050 Great Swamp Branch at Elm, NJ 2.83 75 01409400 3.0E-4 2.252 0.679 309.154 0.13

0140941050 01410000 3.72E-6 2.883 0.697 214.787 0.280140941050 01411000 3.62E-6 2.911 0.702 198.444 0.320140941050 01409500 1.32E-7 3.363 0.671 218.045 0.2701409411 Nescochague Creek at Pleasant Mills, NJ 43.7 50 01409400 1.513 0.810 0.960 22.004 0.2901409411 01411000 0.356 1.180 0.962 18.267 0.42
Table 6 105

Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued[Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in boldare used as base-flow calibration sites; ft3/s, cubic feet per second]

Low-flow 

partial-record 

station number

Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight

01409411 01409500 0.138 1.304 0.940 22.123 0.2901409416 Hammonton Creek at Wescoatville, NJ 6.57 66 01409400 0.302 0.848 0.892 35.739 0.2801409416 01409500 0.025 1.358 0.837 40.114 0.2201409416 01411500 0.023 1.281 0.828 47.570 0.1601409416 01411000 0.067 1.223 0.848 39.061 0.2301409416 01410000 0.154 1.033 0.716 55.356 0.1201409450 Springers Brook near Indian Mills, NJ 12.6 11 01410000 1.1E-3 2.206 0.914 56.262 0.1101409450 01466500 3.431 1.693 0.929 37.813 0.2501409450 01409500 0.002 1.942 0.974 23.610 0.6401409460 Springers Brook nr Atsion 21.2 27 01409500 4.0E-5 2.832 0.940 57.868 0.3601409460 01409400 6.4E-3 1.779 0.938 63.145 0.3101409460 01411000 4.8E-4 2.428 0.933 60.957 0.3301409500 Batsto River at Batsto, NJ 67.8 01409400 6.581 0.611 0.933 20.000 0.4101409500 01410000 2.743 0.860 0.801 34.500 0.1401409500 01411000 2.525 0.863 0.932 18.910 0.4601409575 Landing Creek at Philadelphia Avenue at 

Egg Harbor City, NJ

4.86 19 01408500 0.023 1.084 0.693 46.826 0.22

01409575 01466500 1.948 1.711 0.556 73.784 0.0901409575 01410000 0.060 1.086 0.819 35.878 0.3801409575 01409500 0.011 1.382 0.518 75.344 0.0901409575 01411000 0.018 1.366 0.657 66.266 0.1101409575 01409400 0.061 1.055 0.462 121.290 0.0301409575 01411500 0.039 1.006 0.521 75.033 0.0901409730 West Branch Wading River near Chatsworth, NJ 44.8 10 01409500 0.035 1.529 0.942 35.650 0.4301409730 01410000 0.094 1.387 0.948 37.543 0.3901409730 01409400 0.167 1.207 0.918 53.825 0.1901409780 Tulpehocken Creek near Jenkins, NJ 21.8 31 01409500 0.013 1.592 0.948 25.084 0.40
106 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued [Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in bold are used as base-flow calibration sites; ft3/s, cubic feet per second] Low-flow partial-record station number Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight 01409780 01411000 0.050 1.398 0.931 29.962 0.28 01409780 01409400 0.217 1.007 0.957 27.549 0.33 01409800 West Branch Wading River near Harrisville, NJ 83.9 14 01409500 0.065 1.660 0.949 31.052 0.42 01409800 01411000 0.834 1.198 0.857 49.810 0.16 01409800 01410000 0.302 1.434 0.969 31.050 0.42 01409815 West Branch Wading River at Maxwell, NJ 85.9 40 01410000 0.833 1.144 0.815 41.884 0.14 01409815 01409400 3.049 0.812 0.910 29.679 0.28 01409815 01409500 0.365 1.225 0.932 24.462 0.42 01409815 01411000 1.293 1.010 0.774 40.346 0.15 01409970 Oswego River at Oswego Lake, NJ 61.4 13 01411000 0.387 1.138 0.964 28.171 0.07 01409970 01410000 0.830 0.958 0.995 10.757 0.48 01409970 01409500 0.114 1.340 0.965 25.763 0.08 01409970 01409400 1.107 0.868 0.978 25.167 0.09 01409970 01408500 0.287 1.010 0.970 24.102 0.10 01409970 01411500 0.134 1.174 0.964 31.301 0.06 01409970 01466500 15.028 1.468 0.980 21.834 0.12 01410200 West Branch Bass River near New Gretna, NJ 6.54 12 01409400 0.657 0.633 0.927 26.769 0.26 01410200 01410000 0.133 1.049 0.947 22.623 0.36 01410200 01409500 0.100 1.030 0.942 22.128 0.38 01410215 Clarks Mill Stream at Port Republic, NJ 8.61 16 01409400 0.360 0.740 0.879 26.411 0.27 01410215 01409500 0.029 1.263 0.856 25.678 0.29 01410215 01411000 0.128 1.029 0.904 20.676 0.44

01410225 Morses Mill Stream at Port Republic, NJ 8.25 44 01409400 0.074 1.000 0.588 96.879 0.0801410225 01411000 0.015 1.438 0.717 64.938 0.1801410225 01409500 0.006 1.534 0.905 32.311 0.7401410775 Great Egg Harbor River at Berlin, NJ 1.88 26 01409400 8.4E-3 0.992 0.621 108.868 0.2901410775 01411000 2.3E-3 1.311 0.649 97.156 0.37
Table 6 107

Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued[Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in boldare used as base-flow calibration sites; ft3/s, cubic feet per second]

Low-flow 

partial-record 

station number

Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight

01410775 01411500 2.4E-3 1.131 0.612 100.284 0.3401410775 01409500 1.3E-10 4.837 0.408 15,533.890 0.0001410775 01466500 0.015 4.794 0.634 2,005.458 0.0001410775 01410000 0.000 4.357 0.395 30,442.024 0.0001410784 Great Egg Harbor River near Sicklerville, NJ 15.1 89 01409500 7.5E-3 1.572 0.853 47.749 0.2101410784 01411000 0.019 1.469 0.906 38.799 0.3201410784 01409400 0.093 1.076 0.900 43.872 0.2501410784 01464500 0.026 1.360 0.790 66.564 0.1101410784 01477120 5.9E-2 1.615 0.825 63.675 0.1201410787 Great Egg Harbor River tributary at Sicklerville, NJ 1.64 2 01411500 6.7E-5 1.900 0.796 124.190 0.1701410787 01464500 2.2E-4 1.810 0.817 126.282 0.1601410787 01477120 2.4E-3 1.729 0.929 61.449 0.6701410800 Fourmile Branch near Williamstown, NJ 5.34 11 01475000 0.092 1.674 0.804 57.260 0.3101410800 01409400 0.085 0.856 0.791 62.330 0.2601410800 01411000 0.026 1.165 0.842 48.950 0.4301410803 Fourmile Branch at Winslow Crossing, NJ 6.22 68 01411000 0.061 1.043 0.809 35.101 0.4901410803 01409500 0.019 1.209 0.776 37.283 0.4301410803 01475000 0.256 1.321 0.528 89.084 0.0801410810 Fourmile Branch at New Brooklyn, NJ 7.74 58 01409400 0.235 0.804 0.848 38.592 0.2301410810 01411000 0.096 1.051 0.897 28.444 0.4101410810 01411500 0.074 0.957 0.881 30.531 0.3601410820 Great Egg Harbor River near Blue Anchor, NJ 37.3 9 01411500 0.384 0.964 0.901 30.896 0.1401410820 01411000 0.601 0.999 0.978 13.995 0.6701410820 01409400 1.148 0.828 0.945 25.730 0.2001410855 Squankum Brook above sewage treatment plant, 

at Williamstown, NJ

1.5 28 01409400 4.5E-3 1.081 0.610 116.962 0.37

01410855 01411000 1.8E-3 1.335 0.603 98.247 0.53
108 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued [Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in bold are used as base-flow calibration sites; ft3/s, cubic feet per second] Low-flow partial-record station number Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight 01410855 01411500 7.1E-5 1.806 0.093 1,520.249 0.00 01410855 01409500 1.5E-4 1.756 0.320 224.644 0.10 01410865 Squankum Branch at Malaga Road, near Williamstown, NJ 3.02 55 01411000 3.1E-4 2.688 0.732 139.816 0.32 01410865 01409400 0.000 2.027 0.614 290.910 0.07 01410865 01411500 5.09E-6 2.512 0.822 100.771 0.61 01411020 Penny Pot Stream near Folsom, NJ 5.35 11 01475000 3.1E-4 4.093 0.354 2,494.959 0.00 01411020 01411500 6.0E-5 2.187 0.511 636.798 0.02 01411020 01409500 1.0E-4 2.280 0.785 99.803 0.84 01411020 01409400 5.8E-4 1.928 0.643 388.118 0.06 01411020 01411000 5.0E-5 2.547 0.635 325.426 0.08 01411035 Hospitality Branch at Blue Bell Road, near Cecil, NJ 4.51 91 01409500 4.8E-4 1.893 0.795 66.562 0.17 01411035 01411000 2.9E-3 1.645 0.865 52.351 0.27 01411035 01411500 1.5E-3 1.552 0.932 35.921 0.57 01411040 Hospitality Branch near Cecil, NJ 8.3 25 01411000 0.073 1.161 0.907 23.513 0.44 01411040 01411500 0.038 1.115 0.928 22.747 0.47 01411040 01409500 0.014 1.393 0.718 50.068 0.10 01411042 Whitehall Branch near Cecil, NJ 2.21 25 01409400 1.3E-3 1.674 0.594 195.175 0.07 01411042 01411500 1.0E-4 1.965 0.832 69.965 0.58 01411042 01409500 1.64E-5 2.498 0.601 144.557 0.14 01411042 01411000 2.0E-4 2.237 0.682 116.064 0.21 01411047 Whitehall Branch below Victory Lakes, near 

Cecil, NJ

4.6 54 01409500 1.7E-4 2.183 0.661 98.423 0.24

01411047 01411500 6.0E-4 1.795 0.750 84.646 0.3301411047 01409400 5.7E-3 1.483 0.613 151.188 0.1001411047 01411000 9.3E-4 1.989 0.743 84.459 0.3301411053 Hospitality Branch at Berryland, NJ 20 21 01409400 0.409 0.963 0.769 48.450 0.16
Table 6 109

Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued[Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in boldare used as base-flow calibration sites; ft3/s, cubic feet per second]

Low-flow 

partial-record 

station number

Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight

01411053 01411000 0.080 1.359 0.913 27.040 0.5301411053 01411500 0.066 1.195 0.860 35.530 0.3101411110 Great Egg Harbor River at Weymouth, NJ 154 55 01411000 2.577 1.000 0.960 18.060 0.3601411110 01409400 6.953 0.750 0.948 21.575 0.2501411110 01409500 0.875 1.168 0.893 29.536 0.1301411110 01411500 1.342 1.005 0.948 21.110 0.2601411140 Deep Run at Weymouth, NJ 20 40 01410000 0.156 1.236 0.909 28.953 0.3801411140 01411500 0.106 1.092 0.877 35.515 0.2501411140 01411000 0.121 1.251 0.917 29.497 0.3701411170 Great Egg Harbor River at Mays Landing, NJ 205 18 01411000 0.233 1.747 0.817 58.122 0.1701411170 01409500 0.058 1.875 0.895 39.529 0.3701411170 01411500 0.185 1.470 0.946 35.172 0.4601411196 Babcock Creek near Mays Landing, NJ 16.3 34 01411000 0.083 1.165 0.943 27.316 0.3001411196 01409500 0.018 1.416 0.923 30.872 0.2301411196 01411500 0.052 1.103 0.936 28.941 0.2601411196 01409400 0.303 0.845 0.912 32.772 0.2101411200 Babcock Creek at Mays Landing, NJ 20 30 01409500 1.3E-3 2.048 0.861 54.929 0.2201411200 01411000 0.021 1.570 0.931 36.676 0.5001411200 01409400 0.072 1.249 0.906 49.276 0.2801411220 South River near Belcoville, NJ 20.39 ?? 01411000 0.070 1.406 0.795 49.796 0.1501411220 01409500 0.025 1.535 0.789 43.712 0.1901411220 01411500 0.055 1.262 0.850 41.098 0.2101411220 01410000 0.185 1.125 0.869 37.249 0.2601411220 01409400 1.045 0.700 0.720 44.095 0.1901411250 English Creek near Scullville, NJ 3.8 21 01409400 0.289 0.609 0.355 66.916 0.1101411250 01411000 0.106 0.886 0.427 55.039 0.1601411250 01411500 0.096 0.764 0.630 40.187 0.30
110 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 6. MOVE.1 correlation data for low-flow partial-record stations, southeastern New Jersey.—Continued [Sites with number of measurements in bold indicate that additional data were collected for these sites as part of this project in spring 2005 and fall 2006. Sites with station number and station name in bold are used as base-flow calibration sites; ft3/s, cubic feet per second] Low-flow partial-record station number Station name Drainage area (square miles) Number of measurements Index station number Correlation slope Correlation exponent Correlation coefficient Standard error of estimate (ft3/s) Weight 01411250 01409500 0.048 0.987 0.466 48.251 0.21 01411250 01410000 0.144 0.808 0.491 45.657 0.23 01411299 Tarkiln Brook near Head of River, NJ 7.4 13 01411500 1.9E-4 2.038 0.934 49.450 0.25 01411299 01410000 5.3E-4 2.157 0.952 39.740 0.38 01411299 01411000 1.7E-3 1.841 0.943 40.660 0.37 01411302 Mill Creek near Steelmantown, NJ 3.82 13 01411300 5.0E-4 2.437 0.974 67.550 0.26 01411302 01411500 2.05E-6 2.783 0.950 60.290 0.33 01411302 01410000 8.49E-6 2.946 0.956 53.470 0.41 01411305 Mill Branch near Northfield, NJ 7.47 28 01411000 0.232 0.810 0.858 27.480 0.30 01411305 01411300 0.532 0.773 0.735 41.162 0.13 01411305 01410000 0.235 0.805 0.784 32.202 0.22 01411305 01411500 0.114 0.837 0.894 25.378 0.35
Table 9 111

Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued[NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error]

U.S. 

Geological 

Survey well 

number

NJDEP 

well permit 

number

Well use Latitude (NAD83) Longitude (NAD83)

Altitude 

of land 

surface

(NGVD29)

Aquifer

Well 

depth,

in feet

Model 

layer

May 2005 September 2006

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

010256 3200000173 Observation 393333 744425 93.19 121CKKD 275 7 56.62 58.217 1.6 54.92 57.119 2.2010464 -- Unused 394027 743957 21 121CKKD 25 1 16.06 15.454 -0.61 16.32 14.839 -1.48010465 -- Unused 394027 743957 21 121CKKD 50 1 16.11 15.454 -0.66 16.41 14.839 -1.57010466 -- Unused 394027 743957 21 121CKKD 99 7 16.17 15.753 -0.42 16.47 15.141 -1.33010486 -- Unused 394028 743957 20 121CKKD 50 1 15.42 15.493 0.07 -- -- --010603 3600001849 Observation 392304 743514 25 121CKKD 95 1 12.01 12.449 0.44 15.45 12.046 -3.4010689 3600002433 Withdrawal 392944.7 742824.1 31.17 121CKKD 180 3 8.93 7.073 -1.86 7.47 1.267 -6.2010699 3500004370 Observation 392933 744603 40 121CKKD 160 5 24.73 32.426 7.7 23.4 -3.632 -27.03010712 3500004796 Observation 392902 745050 100 121CKKD 387 9 69.65 71.832 2.18 67.21 70.815 3.61010717 3600065514 Observation 392933 743129 40 121CKKD 335 5 16.36 -5.947 -22.31 14.32 -5.937 -20.26010719 3100023946 Observation 393241 744817 68 121CKKD 38 1 47.38 44.940 -2.44 44.67 43.411 -1.26010720 3100023945 Observation 393549 745058 63 121CKKD 22 1 55.44 61.814 6.37 57.1 60.986 3.89010721 3600006133 Observation 393145 743008 31 121CKKD 26 1 19.14 16.014 -3.13 17.13 14.846 -2.28010724 3600006132 Observation 393049 743959 67 121CKKD 23 1 64.35 56.242 -8.11 60.82 54.885 -5.94010725 3200011807 Observation 393418 743536 15 121CKKD 23 1 9.19 10.773 1.58 9.09 10.569 1.48010726 3600006134 Observation 392939 742543 25 121CKKD 31 1 12.92 6.699 -6.22 11.35 6.149 -5.2010740 3600003836 Observation 393210 743715 47 121CKKD 25 1 44.32 35.306 -9.01 44.74 34.823 -9.92010742 3600005648 Observation 392606 744155 60 121CKKD 52 1 23.82 23.403 -0.42 22.7 21.835 -0.86010744 3100023886 Observation 393530 744810 75.65 121CKKD 20 1 67.15 64.054 -3.1 65.27 62.469 -2.8010747 5600000048 Observation 392552 744556 52.2 121CKKD 40 1 25.05 27.739 2.69 24.17 26.569 2.4010750 3100023857 Observation 393627 745113 90 121CKKD 38 1 69.86 72.158 2.3 67.57 70.803 3.23010751 -- Observation 393346 745055 85 121CKKD 19 1 71.82 67.595 -4.23 68.42 66.170 -2.25010754 3600005159 Observation 392640 743645 70.9 121CKKD 32 1 53.37 53.687 0.32 51.91 52.577 0.67010757 3600001216 Observation 392832.5 742835.1 42.2 121CKKD 32 1 30.79 16.669 -14.12 29 15.508 -13.49010775 -- Observation 392639 743231 38.1 121CKKD 182 3 6.18 -4.295 -10.47 0.66 -4.972 -5.63010776 -- Observation 392639 743231 38.1 121CKKD 93 1 17.61 6.419 -11.19 17.29 6.012 -11.28010778 3600005518 Observation 392344 743731 50 121CKKD 71 1 41.05 38.334 -2.72 39.7 37.485 -2.21010851 3600005058 Withdrawal 392446 744013 35 121CKKD 114 3 29.41 32.213 2.8 28.16 31.315 3.15010864 3200013099 Withdrawal 393442 744303 95 121CKKD 160 3 74.76 63.266 -11.49 71.35 62.194 -9.16
112 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued [NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error] U.S. Geological Survey well number NJDEP well permit number Well use Latitude (NAD83) Longitude (NAD83) Altitude of land surface (NGVD29) Aquifer Well depth, in feet Model layer May 2005 September 2006 Observed water- level altitude Simulated water- level altitude Residual, in feet Observed water- level altitude Simulated water- level altitude Residual, in feet 010885 3600000465 Observation 392233 744547 35 121CKKD 30 1 30.81 27.230 -3.58 30.03 26.821 -3.21 010899 3200015393 Withdrawal 393321 743352 52 121CKKD 102 3 14.75 24.145 9.4 13.6 23.214 9.61 010919 -- Withdrawal 393220 745216 85 121CKKD 26 1 78.51 79.952 1.44 75.68 78.707 3.03 010930 3600011742 Withdrawal 393150 742736 10 121CKKD 100 3 0.83 3.975 3.15 0.71 3.875 3.16 010953 3200012016 Observation 393506 744030 98.65 121CKKD 38 1 78.87 49.603 -29.27 75.57 48.223 -27.35 011197 5600000119 Withdrawal 393101.6 743338 49.54 121CKKD 100 3 49.97 45.879 -4.09 51.26 44.887 -6.37 011234 3500012532 Observation 393117 745538 113.09 121CKKD 30 1 96.33 97.850 1.52 94.45 96.785 2.33 011275 3500018902 Observation 392901 745354 101 121CKKD 25 1 91.51 87.497 -4.01 88.59 86.885 -1.7 011400 3600024011 Observation 391844 744514 7 121CKKD 14 1 4.73 7.495 2.76 4.62 7.147 2.53 011402 3200025196 Observation 394130.2 744347.9 41.99 121CKKD 12 1 39.96 43.612 3.65 40.03 42.112 2.08 011404 3100060862 Observation 393948 744642.7 69.55 121CKKD 14 1 66.61 72.456 5.85 66.26 68.008 1.75 011498 3600028385 Observation 392904.3 743333.8 55.84 121CKKD 65 1 47.71 45.592 -2.12 46.49 44.964 -1.53 011499 3600028384 Observation 392904.3 743334.1 55.12 121CKKD 165 3 47.17 44.249 -2.92 45.98 43.676 -2.3 011500 3600028386 Observation 392904.4 743334.1 55.64 121CKKD 22 1 49.75 45.628 -4.12 48.07 45.000 -3.07 011504 3200027988 Observation 394137.7 744531.8 55.66 121CKKD 160 9 53.52 52.231 -1.29 53.75 51.582 -2.17 011505 3200027990 Observation 394137.9 744531.6 55.54 121CKKD 50 1 52.79 52.168 -0.62 52.92 51.516 -1.4 011506 3200027989 Observation 394138.0 744531.4 55.53 121CKKD 92 7 53.14 52.180 -0.96 53.33 51.532 -1.8 011565 3600028859 Observation 392957.6 743408.5 54.79 121CKKD 20 1 49.42 46.540 -2.88 49.8 45.937 -3.86 011622 3600007181 Observation 392743.7 743034.1 59.91 121CKKD 30 1 39.1 27.545 -11.56 37.22 26.702 -10.52 011624 3600010894 Observation 392811.4 743329.6 51.58 121CKKD 87 1 46.37 42.469 -3.9 45.1 41.883 -3.22 011625 3600010893 Observation 392811.5 743329.1 51.9 121CKKD 17 1 46.33 42.410 -3.92 45.07 41.822 -3.25 011627 3600020934 Observation 392836.7 743542.1 68.24 121CKKD 25 1 58.13 61.395 3.27 55.87 60.761 4.89 011630 3600010906 Observation 392852.4 743443.4 69.1 121CKKD 90 1 53.94 54.148 0.21 52.31 53.955 1.65 011631 3600010903 Observation 392852.6 743444.7 68.15 121CKKD 26 1 54.07 54.349 0.28 52.37 54.148 1.78

011638 -- Observation 392929.5 743144.4 49.54 121CKKD 157 3 36.61 28.882 -7.73 35.34 28.063 -7.28011639 -- Observation 392929.5 743144.4 49.54 121CKKD 68 1 36.25 30.056 -6.19 35.61 29.180 -6.43011652 3600025387 Observation 393011.1 743206 56.79 121CKKD 121 3 36.52 31.305 -5.22 34.62 30.257 -4.36011667 -- Observation 393011.2 743206.1 56.68 121CKKD 84 1 38.05 32.600 -5.45 35.44 31.372 -4.07011671 3600010215 Observation 392923.26 743556.86 60.75 121CKKD 55 1 56.2 60.161 3.96 55.4 59.212 3.81
Table 9 113

Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued[NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error]

U.S. 

Geological 

Survey well 

number

NJDEP 

well permit 

number

Well use Latitude (NAD83) Longitude (NAD83)

Altitude 

of land 

surface

(NGVD29)

Aquifer

Well 

depth,

in feet

Model 

layer

May 2005 September 2006

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

050404 -- Observation 394406 744126 40.88 121CKKD 35 1 36.55 36.025 -0.52 36.95 34.562 -2.39050408 -- Observation 394422 744308 47.52 121CKKD 65 7 43.79 40.848 -2.94 44.16 40.006 -4.15050409 -- Observation 394422 744308 47.13 121CKKD 17 1 41.198 40.740 -0.46 40.89 39.902 -0.99050417 -- Observation 394608 744053 48.49 121CKKD 100 9 43.36 40.743 -2.62 43.72 40.069 -3.65050418 -- Observation 394608 744053 48.52 121CKKD 46 1 43.44 40.657 -2.78 43.84 39.983 -3.86050451 -- Observation 394536 743541 64.86 121CKKD 170 1 55.75 56.367 0.62 -- -- --050452 -- Observation 394536 743541 64.86 121CKKD 21 1 55.81 56.347 0.54 -- -- --050454 -- Observation 394812 744030 66.62 121CKKD 142 9 58.36 61.230 2.87 58.6 60.047 1.45050455 -- Observation 394812 744030 66.54 121CKKD 51 7 58.36 61.235 2.88 58.55 60.051 1.5050512 -- Observation 394009 743251 42.27 121CKKD 50 1 33.2 22.037 -11.16 31.9 20.976 -10.92050570 -- Observation 394106 743622 63.24 121CKKD 25 1 51.31 43.703 -7.61 48.18 42.380 -5.8050609 -- Observation 394300 743829 62.9 121CKKD 45 1 42.9 48.671 5.77 40.49 46.932 6.44050613 -- Observation 394305 743356 41.07 121CKKD 35 1 36.99 34.821 -2.17 37.49 34.151 -3.34050628 -- Observation 394452 742818 78.78 121CKKD 12 1 77.15 69.896 -7.25 77.21 68.481 -8.73050630 -- Observation 394513 742805 104.3 121CKKD 41 1 78.04 76.116 -1.92 76.36 74.663 -1.7050684 -- Observation 395122 743016 140.82 121CKKD 170 7 121.98 121.368 -0.61 119.34 120.077 0.74

051102 -- Observation 393729 742528 23 121CKKD 18 1 17.98 18.980 1 17.98 18.113 0.13051103 -- Observation 393729 742528 23 121CKKD 60 1 17.98 18.980 1 17.96 18.113 0.15051104 3200007214 Withdrawal 394532 744324 50 121CKKD 89 1 45.71 49.326 3.62 47.93 48.248 0.32051107 3200014423 Observation 394736 744441 77 121CKKD 18 1 71.49 76.204 4.71 71.95 73.477 1.53

051119 3200015738 Withdrawal 394930 744233 105 121CKKD 100 1 85.66 100.045 14.38 84.47 94.950 10.48

051126 3200013665 Withdrawal 394251 743039 40 121CKKD 175 7 32.46 37.842 5.38 33.77 36.939 3.17051131 3200014078 Observation 394828 743219 87.6 121CKKD 22 1 82.65 82.417 -0.23 83.44 81.672 -1.77051136 3200012712 Withdrawal 395030 743253 120 121CKKD 80 1 104.47 101.364 -3.11 -- -- --051139 -- Withdrawal 393644 743017 10 121CKKD 41 1 4.74 4.072 -0.67 3.92 3.341 -0.58

051501 3200025195 Observation 394018 743246 35 121CKKD 18 1 28.96 21.359 -7.6 27.94 20.375 -7.57051504 3200025728 Observation 394640 743231 68 121CKKD 10 1 65.07 72.017 6.95 65.16 70.543 5.38070430 -- Observation 394203.1 744919.5 92.52 121CKKD 120 7 80.58 81.286 0.71 78.6 80.038 1.44070431 -- Observation 394203.2 744919.4 93.64 121CKKD 29 1 82.46 81.355 -1.11 79.59 80.095 0.5
114 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued [NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error] U.S. Geological Survey well number NJDEP well permit number Well use Latitude (NAD83) Longitude (NAD83) Altitude of land surface (NGVD29) Aquifer Well depth, in feet Model layer May 2005 September 2006 Observed water- level altitude Simulated water- level altitude Residual, in feet Observed water- level altitude Simulated water- level altitude Residual, in feet 070432 -- Observation 394224 744712 69.83 121CKKD 25 1 66.71 65.685 -1.03 67.05 64.740 -2.31 070451 -- Observation 394628 744922 122.36 121CKKD 166 9 91.11 92.177 1.07 89.61 90.533 0.92 070452 -- Observation 394628 744922 122.33 121CKKD 41 1 94.97 92.246 -2.72 92.63 90.590 -2.04 070459 3100004937 Withdrawal 393943.2 744937.2 95.8 121CKKD 180 1 90.18 89.345 -0.84 89.65 87.975 -1.67 070501 3100005295 Withdrawal 394418.5 745527.8 166.34 121CKKD 141 1 132.2 133.092 0.89 130.67 132.138 1.47 070681 3100022928 Observation 393704 745314 88 121CKKD 25 1 82.55 76.057 -6.49 82.66 75.188 -7.47 070712 3100019134 Observation 394046.4 745207.9 129.9 121CKKD 50 1 102.16 103.454 1.29 100.38 102.237 1.86 070835 3100049659 Observation 394141.8 745503.7 140 121CKKD 32 1 113.74 109.399 -4.34 111.8 108.257 -3.54 070840 3100049746 Observation 394259.7 745326.1 131 121CKKD 29 1 114.08 117.784 3.7 111.42 116.794 5.37 070845 3100049625 Observation 394747.9 745549.1 155 121CKKD 19 1 149.99 157.852 7.86 148.93 157.022 8.09 071091 3100068275 Observation 394406.6 745336.1 155.29 121CKKD 95 7 125.17 128.137 2.97 123.34 127.027 3.69 071092 3100068274 Observation 394406.8 745336.1 155.23 121CKKD 160 9 125.24 128.137 2.9 123.35 127.025 3.68 071125 3100048501 Withdrawal 393925.5 745154.3 116.14 121CKKD 80 3 96.37 97.480 1.11 94.11 96.273 2.16 071128 3100055453 Withdrawal 394541 745641.9 160.43 121CKKD 100 7 136.4 134.664 -1.74 135.48 133.745 -1.74 071129 3100061981 Withdrawal 394303.9 744941.6 90.88 121CKKD 110 7 82.52 92.146 9.63 81.75 90.461 8.71 090186 3600006189 Observation 391621 744353 14 121CKKD 22 1 10.13 5.972 -4.16 9.91 5.633 -4.28 090325 3500013059 Observation 391701 745056 55 121CKKD 124 3 32.69 36.108 3.42 32.93 34.945 2.02 090348 3500013019 Observation 391430 744847 43 121CKKD 45 1 30.26 34.179 3.92 29.77 32.441 2.67 090381 3600012777 Observation 391553 743914 30 121CKKD 98 1 8.43 9.295 0.87 7.55 8.091 0.54 090382 3600012681 Observation 391553 743914 30 121CKKD 210 3 6.95 6.301 -0.65 6.49 5.706 -0.78 090460 5600000430 Observation 391726 743809 11.18 121CKKD 35 1 4.98 1.061 -3.92 4.03 0.707 -3.32 150753 -- Withdrawal 393931 750038 140 121CKKD 130 9 123.09 136.485 13.39 121.1 134.004 12.9 151149 5100000068 Observation 393217 745753 120 121CKKD 25 1 106.49 128.495 22 103.63 116.008 12.38 151207 3100049626 Observation 393415.4 745635.1 120 121CKKD 24 1 105.72 108.793 3.07 103.94 106.697 2.76

151213 3100049658 Observation 393751.8 745512.6 97 121CKKD 15 1 92.41 88.650 -3.76 90.91 87.439 -3.47151281 3100052397 Observation 394225.5 750038.8 145 121CKKD 24 1 134.25 128.268 -5.98 133.11 127.192 -5.92

Mean error -0.96 -1.47Mean absolute error 4.36 4.36RMS 41.05 40.13
Table 9 115

Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued[NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error]

U.S. 

Geological 

Survey well 

number

NJDEP 

well permit 

number

Well use Latitude (NAD83) Longitude (NAD83)

Altitude 

of land 

surface

(NGVD29)

Aquifer

Well 

depth,

in feet

Model 

layer

May 2005 September 2006

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

Observed 

waterlevel

altitude

Simulated 

waterlevel

altitude

Residual,

in feet

010037 5600000071 Observation 392151 742458 9.54 122KRKDL 842 9 -74.58 -64.043 10.54 -106.69 -88.173 18.52010039 5600000012 Withdrawal 392329.6 742346 10 122KRKDL 788 9 -67.4 -63.620 3.78 -93.7 -93.752 -0.05

010117 3200000477 Withdrawal 393212.9 743830.5 40 122KRKDL 432 9 20.45 20.934 0.48 15.76 16.021 0.26

010369 3600000402 Withdrawal 391905.4 743125.4 10 122KRKDL 811 9 -69.76 -69.375 0.39 -103.77 -113.898 -10.13010578 3600000295 Observation 391826 743708 10 122KRKDL 680 9 -51.04 -52.436 -1.39 -75.26 -75.844 -0.58010593 3600000372 Withdrawal 392030.5 742850.7 9 122KRKDL 793 9 -76.24 -79.624 -3.38 -110.73 -128.812 -18.08010600 5600000016 Withdrawal 392045.6 742837.8 8 122KRKDL 810 9 -75.14 -74.294 0.85 -113 -115.307 -2.31010637 3200005113 Withdrawal 393213.9 743823.9 35 122KRKDL 428 9 11.63 19.360 7.73 6.56 14.134 7.57010648 3600001084 Withdrawal 392125 742603 7 122KRKDL 835 9 -71.74 -68.239 3.5 -103.3 -96.079 7.22010650 -- Test 392651 744253 21 122KRKDL 380 7 16.25 13.903 -2.35 12.52 7.212 -5.31010683 3600002091 Withdrawal 392411.2 742226.3 8 122KRKDL 780 9 -59.87 -58.285 1.58 -87.59 -91.923 -4.33010702 -- Observation 392032 743007 5 122KRKDL 755 9 -82.45 -70.210 12.24 -112.13 -113.263 -1.13010703 3600005092 Observation 392639 743231 38 122KRKDL 575 9 -36.46 -32.770 3.69 -67.9 -62.728 5.17010704 -- Observation 392343 743732 51 122KRKDL 611 9 5.46 -28.314 -33.77 -- -- --010706 3600004982 Observation 392933 743129 40 122KRKDL 535 9 -20.69 -19.119 1.57 -40.7 -34.889 5.81010889 3600011871 Withdrawal 392003.3 743009.8 8.2 122KRKDL 795 9 -73.48 -74.272 -0.79 -115.65 -123.882 -8.23010967 3600013010 Withdrawal 392456.1 742120.3 5 122KRKDL 776 9 -52.45 -51.409 1.04 -70.53 -76.053 -5.52010990 3600016110 Withdrawal 392308.2 743521.0 30 122KRKDL 657 7 -39.22 -39.885 -0.67 -71.6 -75.969 -4.37

011218 3600017655 Test 392620 743739 66 122KRKDL 610 9 -35.31 -19.330 15.98 -58.42 -41.096 17.32011220 3600017339 Test 392647 743659 65 122KRKDL 602 9 -- -- -- -61.94 -45.384 16.56011252 3200020165 Withdrawal 393211.9 743826.0 41 122KRKDL 446 9 19.04 19.436 0.4 14.49 14.186 -0.3011256 3600017667 Withdrawal 391932.6 743054.2 6 122KRKDL 801 7 -75.07 -73.508 1.56 -112.75 -123.501 -10.75011455 -- Withdrawal 392749 744259 22 122KRKDL 436 7 18.79 19.089 0.3 -- -- --011456 3600021156 Withdrawal 392450.0 743026.0 5 122KRKDL 652 9 -44.55 -44.931 -0.38 -89.01 -96.429 -7.42011476 3600016749 Observation 392749 743240 45 122KRKDL 596 9 -31.11 -26.689 4.42 -65 -59.920 5.08

090109 5600000008 Withdrawal 391535.9 743609.4 8 122KRKDL 814 9 -56.63 -64.066 -7.44 -81.28 -91.506 -10.23

090116 5600000007 Withdrawal 391637.7 743449.4 7 122KRKDL 810 9 -66.98 -66.223 0.76 -96.11 -104.887 -8.78

090124 3600000413 Withdrawal 391711.8 743338.3 8 122KRKDL 843 9 -66.73 -67.337 -0.61 -96.05 -109.146 -13.1090144 3600000451 Unused 391721.3 743805 9 122KRKDL 691 9 -59.3 -55.984 3.32 -- -- --
116 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 9. Simulated and observed groundwater levels and residuals, southeastern New Jersey, May 2005 and September 2006.—Continued [NJDEP, New Jersey Department of Environmental Protection; Simulated and observed water levels are in feet above, NGVD29, National Geodetic Vertical Datum of 1929; NAD83, North American Datum of 1983; --, no data; RMS, Root mean square error] U.S. Geological Survey well number NJDEP well permit number Well use Latitude (NAD83) Longitude (NAD83) Altitude of land surface (NGVD29) Aquifer Well depth, in feet Model layer May 2005 September 2006 Observed water- level altitude Simulated water- level altitude Residual, in feet Observed water- level altitude Simulated water- level altitude Residual, in feet 090185 3700001340 Observation 391621.4 744354.5 15 122KRKDL 655 9 -32.92 -30.124 2.8 -- -- -- 090459 3600000377 Withdrawal 391712.9 743722.6 7 122KRKDL 620 7 -54.9 -58.794 -3.89 -78.53 -81.681 -3.15 090461 3600015182 Withdrawal 391729 743812.6 8 122KRKDL 710 9 -54.97 -54.175 0.79 -76.32 -78.735 -2.42 090481 3600017001 Withdrawal 391553.5 743915.0 33 122KRKDL 743 7 -45.15 -52.279 -7.13 -66.35 -73.443 -7.09 Mean error 0.50 -1.37 Mean absolute error 4.36 7.13 RMS 60.87 79.44 090149 3700000005 Withdrawal 391815.3 744953 20 122KRKDU 290 5 18.25 -1.667 -19.92 18.13 -0.868 -19 090519 3600022762 Withdrawal 391554.2 743916 31 122KRKDU 498 5 -22.91 -8.382 14.53 -23.75 -7.808 15.94 Mean error -2.70 -1.53 Mean absolute error 17.23 17.47 RMS 303.96 307.54
Table 17 117

Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued[HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits]

HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

Average

02040301170 2 -0.1202040301170 5 -0.31 -0.4402040301170 9 -1.03 -0.3102040301180 2 -0.61 -0.0302040301180 3 -0.13 -0.3802040301180 4 -0.19 -0.2402040301180 5 -0.05 -0.62 -0.4502040301180 6 -0.13 -0.44 -0.0702040301180 7 -0.03 -0.3 -0.1202040301180 8 -0.1 -0.26 -0.3502040301180 9 -0.42 -0.54 -0.1602040301190 5 -0.25

02040302020 1 -9.6 -9.6 -10.3 -8.66 -8.81 -9.58 -9.35 -9.12 -8.61 -8.97 -9.16 -8.5502040302020 2 -11.38 -9.65 -9.62 -8.64 -8.54 -10.15 -9.52 -10.97 -10.82 -9.83 -9.11 -9.4402040302020 3 -9.49 -8.43 -9.75 -8.41 -8.55 -9.41 -10.64 -10.54 -9.82 -8.73 -9.75 -9.3202040302020 4 -9.25 -9.12 -10.01 -8.21 -8.38 -10.53 -10.48 -10.17 -9.1 -9 -8.47 -8.302040302020 5 -8.33 -7.21 -8.51 -8.59 -8.95 -10.16 -9.39 -11.19 -10.77 -11.65 -12.66 -11.4502040302020 6 -9.67 -10.22 -9.29 -8.55 -8.75 -12.39 -10.66 -10.51 -10.15 -10.22 -10.68 -10.3402040302020 7 -9.06 -8.72 -8.89 -8.82 -8.62 -9.45 -9.75 -10.28 -9.23 -10.12 -10.84 -9.8302040302020 8 -9.38 -9 -8.91 -9.21 -10.16 -10.7 -10.34 -9.8 -9.11 -11.54 -10.5 -10.3602040302020 9 -10.42 -8.12 -7.27 -7.22 -8 -10.19 -12.12 -10.84 -10.78 -10.83 -11.23 -9.2802040302030 1 -0.27 -0.66 -0.4 -0.4302040302030 2 -0.47 -0.85 -1.58 -2.11 -0.9502040302030 3 -0.07 -1.3 -1.45 -1.55 -0.1202040302030 4 -0.57 -1.4 -1.3 -1.04 -0.2502040302030 5 -0.48 -0.56 -1.58 -1.97 -1.802040302030 6 -1.24 -1.6 -1.62 -1.79 -1.0502040302030 7 -0.24 -1.14 -1.43 -1.3602040302030 8 -0.7 -1.47 -1.3 -1.34 -1.5502040302030 9 -0.54 -2.05 -1.79 -2.01 -1.07
118 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued [HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits] HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Average—Continued 02040302040 5 -0.12 02040302040 9 -0.05 02040302060 1 -0.61 -0.6 -0.38 -0.04 -0.51 -1.43 -2.01 -1.8 -1.75 -1.6 -1.08 -0.57 02040302060 2 -1.07 -0.64 -0.18 -0.04 -0.4 -1.71 -2.08 -2.43 -2.46 -1.91 -1.1 -0.8 02040302060 3 -0.59 -0.26 -0.3 -0.41 -1.39 -2.4 -2.26 -2.13 -1.56 -1.37 -0.77 02040302060 4 -0.51 -0.51 -0.34 -0.35 -1.8 -2.35 -2.12 -1.92 -1.66 -0.89 -0.48 02040302060 5 -0.22 -0.54 -1.62 -1.99 -2.54 -2.38 -2.52 -2.1 -1.45 02040302060 6 -0.7 -0.91 -0.32 -0.14 -0.59 -2.42 -2.48 -2.29 -2.28 -2.15 -1.65 -1.11 02040302060 7 -0.46 -0.42 -0.1 -0.16 -0.51 -1.42 -2.09 -2.13 -1.9 -2 -1.65 -0.92 02040302060 8 -0.46 -0.49 -0.04 -0.26 -1.02 -1.92 -2.33 -2.01 -1.87 -2.51 -1.56 -1.04 02040302060 9 -0.75 -0.31 -0.25 -1.69 -2.84 -2.31 -2.44 -2.19 -1.77 -0.81 Full Allocation 02040301150 2 -0.76 02040301150 3 -0.09 -0.4 02040301150 4 -0.14 -0.11 02040301150 5 -0.56 -0.17 02040301150 6 -1.16 -0.13 -0.43 02040301150 7 -0.04 02040301150 8 -0.32 02040301150 9 -1.08 -0.72 02040301160 1 -0.89 -5.21 -7.36 -7.02 -6.69 -5.71 -2.65 02040301160 2 -2.41 -0.53 -6.03 -7.83 -10.58 -12.11 -9.15 -3.39 -0.26 02040301160 3 -0.28 -4.72 -9.32 -10.19 -9.96 -6.53 -4.01 -0.16 02040301160 4 -6.5 -9.62 -9.64 -8.5 -6.74 -1.7 02040301160 5 -1.32 -6.28 -7.43 -10.82 -11.67 -13 -10.57 -3.82

02040301160 6 -0.2 -10.33 -10.46 -10.63 -10.89 -9.92 -6.31 -1.6502040301160 7 -4.68 -8.06 -9.6 -8.96 -9.48 -7.13 -1.2202040301160 8 -2.36 -7.25 -9.58 -9.22 -8.71 -12.49 -6.28 -1.7702040301160 9 -5.42 -12.78 -11.68 -12.36 -11.14 -7.1902040301170 1 -0.97 -1.62 -3.88 -6.16 -5.66 -5.74 -5.2 -3.15 -0.75
Table 17 119

Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued[HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits]

HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

Full Allocation—Continued

02040301170 2 -4.89 -1.86 -4.92 -6.55 -8.4 -9.95 -7.74 -3.71 -2.4302040301170 3 -0.93 -3.64 -7.81 -8.06 -8.22 -5.77 -4.42 -2.3702040301170 4 -0.62 -0.77 -5.39 -8.07 -7.55 -7.16 -5.98 -2.33 -0.3402040301170 5 -0.19 -5.14 -6.5 -8.86 -9.91 -11.56 -10.71 -6.2302040301170 6 -0.99 -1.81 -8.39 -8.64 -8.25 -8.85 -8.39 -6.38 -3.7402040301170 7 -3.47 -6.45 -7.59 -7.09 -7.75 -6.75 -2.9402040301170 8 -0.74 -5.44 -7.69 -6.76 -6.81 -10.42 -5.98 -3.5502040301170 9 -1.41 -4.16 -10.26 -8.56 -9.53 -9.09 -6.89 -1.4102040301180 1 -.35 -1.28 -1.76 -1.77 -2.53 -2.1 -1.19 -1.2102040301180 2 -0.62 -0.39 -1.48 -1.83 -2.38 -3.6 -2.78 -1.28 -1.402040301180 3 -1.19 -2.07 -2.34 -3.3 -2.33 -1.39 -1.402040301180 4 -0.02 -1.56 -2.16 -2.24 -3.02 -2.43 -0.84 -0.9802040301180 5 -0.03 -1.79 -1.99 -2.6 -3.67 -3.58 -2.47 -202040301180 6 -0.02 -1.9 -2.08 -2.21 -3.3 -2.8 -1.69 -1.5502040301180 7 -1.19 -1.81 -2.15 -3.05 -2.85 -1.93 -1.5902040301180 8 -1.55 -2.01 -2.02 -2.93 -3.26 -1.65 -1.5602040301180 9 -1.43 -2.49 -2.4 -3.5 -2.94 -1.73 -1.2102040301190 2 -0.32 -0.15 -1.47 -0.1802040301190 3 -0.35 -0.37 -0.2102040301190 4 -0.4702040301190 5 -0.79 -1.57 -0.99 -1.04 -3.3702040301190 6 -0.27 -0.42 -1.9302040301190 7 -0.21 -1.5602040301190 8 -0.17 -0.93 -2.4902040301190 9 -1.66 -0.47 -1.44 -0.67

02040301200 1 -1.21 -0.66 -1.2902040301200 2 -0.11 -1.45 -2.83 -4.03 -0.7802040301200 3 -2.59 -2.36 -2.8402040301200 4 -0.61 -2.58 -1.96 -2.0602040301200 5 -0.29 -1.41 -3.16 -4.03 -3.18 -2.75 -0.5402040301200 6 -2.96 -2.96 -2.33 -3.3 -1.33 -0.27
120 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued [HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits] HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Full Allocation—Continued 02040301200 7 -1.67 -2.28 -2.15 -1.22 -0.37 02040301200 8 -0.91 -2.48 -1.42 -1.98 -3.17 02040301200 9 -0.16 -4.48 -2.82 -4.11 -2.15 -0.73 02040302020 1 -15.08 -15.55 -17.4 -14.37 -13.56 -13.77 -12.84 -12.17 -11.41 -11.97 -12.69 -12.5 02040302020 2 -18.6 -15.8 -16.15 -14.34 -13.03 -14.88 -13.15 -15.64 -15.65 -14.21 -13.09 -14.51 02040302020 3 -15.24 -13.62 -16.57 -14.04 -13.21 -13.56 -15.34 -14.98 -13.89 -12.1 -14.34 -14.24 02040302020 4 -14.74 -15.02 -17.19 -13.68 -12.87 -15.82 -15.17 -14.36 -12.62 -12.53 -11.75 -12.3 02040302020 5 -12.7 -10.83 -13.51 -13.82 -13.46 -14.57 -12.64 -15.77 -15.43 -17.91 -20.31 -19.11 02040302020 6 -16.36 -18.2 -16.64 -15.15 -14.24 -20.55 -16.36 -15.71 -15.15 -15.91 -17.03 -17.31 02040302020 7 -15.42 -15.17 -15.7 -15.65 -14.11 -14.33 -14.28 -15.01 -13.24 -15.23 -16.98 -15.89 02040302020 8 -15.71 -15.47 -15.51 -16.24 -17.18 -17.07 -15.69 -14.35 -13.21 -18.35 -16.56 -17.32 02040302020 9 -18.03 -14.08 -12.44 -12.16 -12.54 -15.55 -18.86 -16.25 -16.47 -16.81 -18.1 -15.13 02040302030 1 -6.38 -7.79 -8.53 -6.59 -6.04 -7.64 -7.36 -6.84 -6.71 -6.3 -5.25 -4.22 02040302030 2 -10.27 -8.64 -7.48 -6.48 -5.59 -8.46 -7.83 -9.73 -10.91 -9.27 -6.43 -6.49 02040302030 3 -7.18 -5.86 -7.2 -5.89 -5.49 -7.23 -9.19 -9.46 -9.24 -7.03 -6.83 -6.2 02040302030 4 -6.53 -7.12 -7.89 -5.66 -5.17 -9.04 -9.55 -9.04 -8.06 -7.17 -4.76 -3.87 02040302030 5 -3.8 -2.59 -3.73 -5.39 -5.75 -8.29 -7.46 -9.91 -10.67 -12.96 -14.61 -12.36 02040302030 6 -8.67 -8.92 -5.93 -5.52 -6.13 -12.76 -10.99 -10.39 -10.57 -10.57 -10.03 -9.1 02040302030 7 -6.62 -5.73 -4.24 -4.79 -5.66 -7.68 -8.39 -9.15 -8.47 -9.46 -10.06 -8.24 02040302030 8 -7.08 -6.27 -4.41 -5.31 -7.53 -10.21 -10.06 -9.04 -8.55 -12.44 -9.91 -8.88 02040302030 9 -7.92 -4.65 -2.08 -2.66 -4.09 -8.35 -12.3 -11.01 -11.79 -11.8 -10.87 -6.97 02040302040 1 -0.4 -0.24 -1.5 -3.37 -2.45 -3.21 -2.8 -0.07 02040302040 2 -6.22 -1.67 -3.13 -4.13 -7.36 -10.22 -7.48 -1.56 -0.89 02040302040 3 -1.26 -6.77 -6.84 -7.43 -3.98 -2.93 -0.57 02040302040 4 -4.54 -7.04 -6 -5.43 -4.36

02040302040 5 -3.45 -4.01 -8.11 -10.13 -14.72 -18.33 -12.2202040302040 6 -1.13 -4.77 -14.1 -8.9 -7.68 -9.14 -9.94 -8.6 -6.8402040302040 7 -1.65 -4.72 -6 -5.62 -8.04 -8.41 -3.8302040302040 8 -1.71 -6.55 -7.15 -5.08 -5.35 -14.01 -8.09 -7.2802040302040 9 -5.18 -2.94 -12.97 -8.66 -11.48 -12.58 -12.52 -1.62
Table 17 121

Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued[HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits]

HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

Full Allocation—Continued

02040302050 2 -0.82 -1.7902040302050 3 -0.63 -0.7 -0.8302040302050 4 -0.89 -0.41 -0.2602040302050 5 -1.07 -1.58 -1.72 -0.102040302050 6 -1.21 -1.46 -1.04 -1.48 -0.6102040302050 7 -0.14 -0.47 -0.2302040302050 8 -0.88 -0.12 -0.19 -1.2702040302050 9 -1.92 -0.98 -1.79 -0.8402040302060 1 -3.54 -3.41 -3.29 -2.57 -2.96 -3.9 -4.4 -4.22 -4.15 -4.06 -3.63 -3.0202040302060 2 -4.44 -3.4 -3.01 -2.59 -2.8 -4.39 -4.52 -5.43 -5.34 -4.6 -3.54 -3.4802040302060 3 -3.33 -2.77 -3.17 -2.49 -2.84 -3.87 -5.27 -5.13 -4.86 -3.96 -4.09 -3.4202040302060 4 -3.22 -3.18 -3.26 -2.36 -2.74 -4.64 -5.12 -4.88 -4.43 -4.16 -3.19 -2.902040302060 5 -2.79 -2.09 -2.73 -2.67 -3.17 -4.35 -4.42 -5.72 -5.43 -5.68 -5.4 -4.4902040302060 6 -3.46 -3.85 -3.08 -2.75 -3.13 -5.73 -5.35 -5.11 -5.06 -4.94 -4.53 -3.9602040302060 7 -3.13 -3.01 -2.75 -2.84 -3.06 -3.89 -4.64 -4.97 -4.45 -4.85 -4.56 -3.5902040302060 8 -3.19 -3.11 -2.75 -3.05 -3.95 -4.75 -5.09 -4.55 -4.35 -5.61 -4.29 -3.9202040302060 9 -3.79 -2.7 -1.81 -1.82 -2.53 -4.36 -6.01 -5.2 -5.3 -5.11 -4.7 -3.29

2050 Demand

02040301170 1 -1 -0.36 -0.69 -0.0302040301170 2 -1.18 -1.88 -2.91 -1.202040301170 3 -1.94 -1.64 -1.94 -0.0602040301170 4 -2.03 -1.28 -1.28 -0.2802040301170 5 -1.22 -2.27 -2.73 -3.35 -1.1902040301170 6 -1.2 -2.09 -1.45 -2.05 -1.402040301170 7 -1.11 -1.49 -1.32 -1.3202040301170 8 -1.69 -0.78 -1.08 -2.7802040301170 9 -3.6 -1.91 -2.71 -1.8602040301180 1 -0.89 -1.3 -0.88 -1.14 -0.84 -0.0602040301180 2 -1.1 -1.38 -1.49 -2.17 -1.55 -0.23 -0.1702040301180 3 -0.84 -1.64 -1.45 -1.86 -1.1 -0.31 -0.1502040301180 4 -1.21 -1.71 -1.35 -1.61 -1.19
122 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J. Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued [HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits] HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec 2050 Demand—Continued 02040301180 5 -1.3 -1.44 -1.62 -2.18 -2.26 -1.36 -0.79 02040301180 6 -1.64 -1.74 -1.42 -1.94 -1.64 -0.71 -0.41 02040301180 7 -0.92 -1.42 -1.31 -1.67 -1.63 -0.88 -0.4 02040301180 8 -1.28 -1.65 -1.21 -1.6 -2.06 -0.67 -0.42 02040301180 9 -1.14 -2.1 -1.56 -2.14 -1.77 -0.76 -0.09 02040301190 5 -0.45 02040301200 1 -0.05 02040301200 2 -0.09 -1.04 -2.29 02040301200 3 -1.1 -0.66 -1.26 02040301200 4 -1.05 -0.29 -0.56 02040301200 5 -0.06 -1.41 -2.36 -0.95 02040301200 6 -0.79 -1.3 -0.53 -1.59 02040301200 7 -0.31 -0.63 -0.75 02040301200 8 -0.98 -0.67 -0.97 02040301200 9 -2.6 -1.03 -2.32 -0.12 02040302020 1 -11.74 -11.88 -12.89 -10.88 -10.64 -11.2 -10.81 -10.42 -9.83 -10.26 -10.6 -10.24 02040302020 2 -14.01 -12.02 -12.03 -10.86 -10.26 -11.96 -11.04 -12.76 -12.68 -11.56 -10.72 -11.41 02040302020 3 -11.67 -10.45 -12.28 -10.59 -10.33 -11.03 -12.43 -12.28 -11.45 -10.17 -11.56 -11.26 02040302020 4 -11.36 -11.38 -12.63 -10.32 -10.09 -12.55 -12.26 -11.82 -10.58 -10.46 -9.84 -9.97 02040302020 5 -9.98 -8.68 -10.47 -10.62 -10.71 -11.89 -10.81 -12.98 -12.47 -13.97 -15.46 -14.18 02040302020 6 -12.14 -12.97 -11.86 -10.94 -10.8 -15.05 -12.72 -12.41 -12.05 -12.38 -12.97 -12.76 02040302020 7 -11.3 -10.96 -11.21 -11.14 -10.62 -11.21 -11.41 -12.01 -10.75 -12.06 -13.08 -12.01 02040302020 8 -11.59 -11.24 -11.19 -11.55 -12.51 -12.92 -12.23 -11.44 -10.63 -13.84 -12.67 -12.74 02040302020 9 -12.86 -10.24 -9.16 -9.05 -9.67 -12.12 -14.37 -12.77 -12.87 -12.93 -13.52 -11.36 02040302030 1 -0.93 -0.96 -1.11 -3.69 -3.89 -3.51 -3.34 -2.69 -1.31 -0.14

02040302030 2 -2.44 -1.04 -0.99 -4.07 -4.15 -5.23 -5.88 -4.51 -2.01 -1.0802040302030 3 -0.46 -0.83 -3.43 -4.88 -5.02 -4.99 -3.21 -2.22 -1.0102040302030 4 -0.32 -0.21 -0.73 -4.21 -5 -4.79 -4.25 -3.37 -1.0702040302030 5 -1.11 -3.95 -3.76 -5.18 -5.68 -5.87 -4.4 -2.1702040302030 6 -0.35 -0.44 -1.13 -5.38 -5.52 -5.45 -5.56 -4.86 -3.09 -1.44
Table 17 123

Table 17. Simulated monthly base-flow deficits from basic scenarios in the Great Egg-Mullica model for Hydrologic Unit Code 11 subbasins, southeastern N.J.—Continued[HUC11, Hydrologic Unit Code 11; shaded cells are summer months as defined for seasonal-conjunctive use scenario; deficits are in millions of gallons per month; blank cells indicate no deficits]

HUC11 number Scenario year Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

2050 Demand—Continued

02040302030 7 -0.98 -3.79 -4.64 -5.04 -4.73 -4.61 -3.31 -1.3202040302030 8 -0.07 -1.56 -4.47 -5.21 -4.93 -4.79 -5.57 -2.9 -1.3702040302030 9 -0.6 -0.63 -4.16 -6.06 -5.64 -5.89 -4.95 -3.04 -0.7702040302040 2 -1.9202040302040 3 -0.2402040302040 5 -0.17 -1.79 -3.39 -1.7102040302040 6 -0.69 -0.22 -0.91 -0.4502040302040 8 -2.7302040302040 9 -2.9 -0.1 -2.1 -1.202040302050 2 -0.01 -0.89 -1.8602040302050 3 -0.83 -0.73 -0.9302040302050 4 -0.93 -0.44 -0.2702040302050 5 -1.19 -0.6 -1.6502040302050 6 -1.22 -1.48 -1.05 -1.49 -0.5802040302050 7 -0.19 -0.52 -0.3402040302050 8 -0.95 -0.2 -0.34 -1.3302040302050 9 -2 -0.94 -1.93 -0.7702040302060 1 -3.66 -3.54 -3.38 -2.65 -2.98 -3.86 -4.37 -4.2 -4.1 -4.07 -3.68 -3.1102040302060 2 -4.57 -3.5 -3.1 -2.67 -2.79 -4.35 -4.47 -5.41 -5.47 -4.62 -3.61 -3.602040302060 3 -3.45 -2.86 -3.22 -2.53 -2.81 -3.81 -5.22 -5.08 -4.8 -3.95 -4.19 -3.5302040302060 4 -3.31 -3.27 -3.32 -2.41 -2.69 -4.6 -5.03 -4.8 -4.35 -4.16 -3.26 -2.9302040302060 5 -2.85 -2.14 -2.85 -2.72 -3.12 -4.27 -4.35 -5.63 -5.43 -5.69 -5.41 -4.4702040302060 6 -3.48 -3.84 -3.08 -2.74 -3.13 -5.66 -5.26 -5.04 -5.01 -4.97 -4.55 -3.9402040302060 7 -3.18 -3.05 -2.8 -2.84 -3.05 -3.83 -4.57 -4.92 -4.4 -4.94 -4.63 -3.6902040302060 8 -3.26 -3.17 -2.81 -3.06 -3.95 -4.7 -5.02 -4.52 -4.31 -5.65 -4.39 -4.0102040302060 9 -3.85 -2.79 -1.91 -1.91 -2.56 -4.42 -5.99 -5.2 -5.27 -5.13 -4.78 -3.42
Appendix 1

Appendix 1. Simulated base flow, base-flow depletion, available water, and deficits under Average, Full Allocation, and 2050 

Demand scenarios by Hydrologic Unit Code 11 subbasins in southeastern New Jersey.
Appendix 1 125Figure 1-A. Hydrologic Unit Code 11 02040301150, Batsto River.

Average

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

0

755025

125100

-5

50

10

50

1510

Simulated base flow, in million 

gallons per day 

0

755025

125100

-5

50

10

50

1510

0

755025

125100

-5

50

10

50

1510

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

Full Allocation 2050 Demand 
126 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-B. Hydrologic Unit Code 11 02040301160, Mullica River. (Above Batsto River)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

30 30

200 200

0

50

200175150100

-20

0

3020

0

302010

Simulated base flow, in million 

gallons per day 

0

0

0

0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

7525

125

50

175150100

7525

125

50

175150100

7525

125

5

2515

2010

5

2515

2010

5

2515

-10

10

-20

0

3020

-10

10

-20

0

3020

-10

10
Appendix 1 127Figure 1-C. Hydrologic Unit Code 11 02040301170, Mullica River. (Turtle Creek Batsto River)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

20 20

175 175

0

75

175150125

-15

0

2015

0

2010

Simulated base flow, in million 

gallons per day 

0

0

0

0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

5025

100

75

150125

5025

100

75

150125

5025

100

5

15

10

5

15

10

5

15

-10

10

-5

5

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

-15

0

2015

-10

10

-5

5

-15

0

2015

-10

10

-5

5
128 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-D. Hydrologic Unit Code 11 02040301180, Oswego River.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

10 10

0

90807050

-5

5

10

50

10

Simulated base flow, in million 

gallons per day 

0 0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

604020

5 5

0

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

3010

908070605040302010

0

908070605040302010

-5

0

10

5

-5

0

10

5

0
Appendix 1 129Figure 1-E. Hydrologic Unit Code 11 02040301190, West Branch Wading River.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

20 20

0

150125

2015

-5

0

2010

Simulated base flow, in million 

gallons per day 

0 0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

50

100

10 10

5

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

7525

150125

50

100

7525

0

150125

50

100

7525

-5

5

2015

-5

0

2010

0

15

5 5

15 15

5

0

10

0

10

5

15
130 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-F. Hydrologic Unit Code 11 02040301200, Mullica River. (GSP bridge to Turtle Creek)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

20 20

0

125100

2015

-5

0

2010

Simulated base flow, in million 

gallons per day 

0 0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

7525

10 10

5

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

50

125100

755025

0

125100

755025

-5

5

2015

-5

0

2010

0

15

5 5

15 15

5

0

10

0

10

5

15
Appendix 1 131Figure 1-G. Hydrologic Unit Code 11 02040301210, Great Bay / Mullica River. (Below GSP bridge)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

5 5

0

10

-5

505

Simulated base flow, in million 

gallons per day 

0 0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

50

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

10

5

0

10

5

-5

5

-5

50

0

0
132 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-H. Hydrologic Unit Code 11 02040302010, Reeds Bay / Absecon By and tribs.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

5 5

0

20

-5

505

Simulated base flow, in million 

gallons per day 

0 0

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

10

0

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

2010

0

2010

-5

5

-5

50

0

0
Appendix 1 133Figure 1-I. Hydrologic Unit Code 11 02040302020, Absecon Creek.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Base-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

0

30

-25

05

25

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

10

-10

Base-flow deficitFinal available 

EXPLANATION

Base-flow deficitFinal available 

EXPLANATION

30

0

0

3010

-10

20

20

20

5

201510

0

25

5

201510

0

25

5

201510

-20

0

-15

-5

10

-25

5

-10-20

0

-15

-5

-25

5

-10-20

0

-15

-5
134 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-J. Hydrologic Unit Code 11 02040302030, Great Egg Harbor River. (Above Hospitality Branch)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Base-flow deficitFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

-20

10

0

25

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

-5

100

25

0

75

5

201510

0

25

5

201510

0

25

5

201510

-15

5

-10

0

50

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

-20

10

-5

-15

5

-10

0

-20

10

-5

-15

5

-10

0

100

25

0

7550

100

25

0

7550
Appendix 1 135Figure 1-K. Hydrologic Unit Code 11 02040302040, Great Egg Harbor River. (Lake Lenape to Hospitality Branch)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

-20

30

0

40

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

50

35251520

-10

10

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

200

75

0

175125

50

150100

25

200

75

0

175125

50

150100

25

200

75

0

175125

50

150100

25302010

0

40

5

353025201510

0

40

5

353025201510

-20

30

0

20

-10

10

-20

30

0

20

-10

10
136 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-L. Hydrologic Unit Code 11 02040302050, Great Egg Harbor River. (Below Lake Lenape)

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

Full Allocation 2050 Demand Average

25

-5

0

25

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

5

201020

0

15

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

200

75

0

175125

50

150100

25

200

75

0

175125

50

150100

25

200

75

0

175125

50

150100

2515

5

0

25201510

5

0

25201510

5

10

25

-5

5

20

0

1510

25

-5

5

20

0

1510
Appendix 1 137Figure 1-M. Hydrologic Unit Code 11 02040302060, Patcong Creek / Great Egg Harbor Bay.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Full Allocation 2050 Demand Average

-10

05

15

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

10

-5

0

Base-flow deficitFinal available 

EXPLANATION

Base-flow deficitFinal available 

EXPLANATION

30

50

25201510

5

Monthly remaining available waterBase-flow deficitFinal available 

EXPLANATION

30

50

25201510

30

50

25201510

0

1510

5

0

1510

5

-10

5

-5

0

-10

5

-5

0
138 Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.

Figure 1-N. Hydrologic Unit Code 11 02040302070, Tuckahoe River.

Baseline base flow Base flow 

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Baseline base flowBase flow

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Final availableBase-flow depletion 

EXPLANATION

Full Allocation 2050 Demand Average

20

-5

0

20

Simulated base flow, in million 

gallons per day 

Scenario year

1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2 1 3 4 5 6 7 8 9 2

Scenario year Scenario year

Million gallons per day 

0

1510

Monthly remaining available waterFinal available 

EXPLANATION

Monthly remaining available waterFinal available 

EXPLANATION

125

25

0

100

7550

5

Monthly remaining available waterFinal available 

EXPLANATION

125

25

0

100

7550

125

25

0

100

7550

10

0

2015

5

10

0

2015

5

10

5

15

20

-5

0

10

5

15

20

-5

0

10

5

15
Appendixes 2 and 3

Appendix 2. Results of simulations of Average, Full Allocation, and 2050 Demand scenarios–basic scenarios–from the 

Great Egg-Mullica Model. (Excel spreadsheet available online at http://pubs.usgs.gov/sir/2012/5187/) 

Appendix 3. Results of simulations of Average, Full Allocation, and 2050 Demand scenarios with Tier 1–3 adjustments 

from the Great Egg-Mullica Model. (Excel spreadsheet available online at http://pubs.usgs.gov/sir/2012/5187/)
Prepared by the West Trenton Publishing Service Center

For additional information, write to:

Director

U.S. Geological Survey

New Jersey Water Science Center

Mountain View Office Park

810 Bear Tavern Rd., Suite 206

West Trenton, NJ 08628

or visit our Web site at:

http://nj.usgs.gov/
Pope and others—Simulated Effects of Withdrawals on Aquifers in the Great Egg Harbor and Mullica River Basins, N.J.—Scientific Investigations Report 2012–5187