E n g in e e r R e s e a rc h a n d Development Center

ERDC TR-01-7

Groundwater Flow and Contaminant Transport Modeling Near the Peele Dixie Well Field

Engineer Research and Development Center

Including Florida Petroleum Reprocessors Superfund Site, Ft. Lauderdale and Davie, Broward County, Florida M. Eileen Glynn, Stacy E. Howington, William L. Murphy, Jackie P. Hallberg, Mansour Zakikhani, Robert S. Maier, and Benita A. Abraham

Approved for public release; distribution is unlimited.

August 2001

The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. The findings of this report are not to be construed as an official Department of the Army position, unless so designated by other authorized documents.

PRINTED ON RECYCLED PAPER

ERDC TR-01-7 August 2001

Groundwater Flow and Contaminant Transport Modeling Near the Peele Dixie Well Field Including Florida Petroleum Reprocessors Superfund Site, Ft. Lauderdale and Davie, Broward County, Florida by

M. Eileen Glynn, William L. Murphy, Benita A. Abraham Geotechnical and Structures Laboratory U.S. Army Engineer Research and Development Center 3909 Halls Ferry Road Vicksburg, MS 39180-6199 Stacy E. Howington, Jackie P. Hallberg Coastal and Hydraulics Laboratory U.S. Army Engineer Research and Development Center 3909 Halls Ferry Road Vicksburg, MS 39180-6199 Mansour Zakikhani Environmental Laboratory U.S. Army Engineer Research and Development Center 3909 Halls Ferry Road Vicksburg, MS 39180-6199 Robert S. Maier Army High Performance Computing Research Center 1100 Washington Avenue South Minneapolis, MN 55415

Final report Approved for public release; distribution is unlimited

Prepared for

U.S. Environmental Protection Agency, Region IV 61 Forsyth Street, SW Atlanta, GA 30303-3104

Part I: The Conceptual Model, Flow Model, and Initial Transport Model This report documents two modeling efforts. The two pieces are being published within the same document to avoid the need to duplicate much of the discussion of the conceptualization and data sources. A compact disk is enclosed with this report that provides the pertinent data and numerical model files developed in these modeling efforts. The goals of the individual efforts were: •

Part 1. Build a hydrogeological conceptual model and a numerical groundwater flow model of the site. Use these tools to gain an understanding of the flow patterns, both historical and present, near the Peele Dixie Well Field. With this improved understanding, evaluate the plausibility of the EPA’s conceptual model of contaminant origins and perform a screening level plume-containment pumping scheme.

•

Part II. Use the calibrated flow model from Part I to drive reactive transport simulations and assess the relative merit of several remedial alternatives.

Contents Preface .............................................................................................................. vii Acronyms .........................................................................................................

ix

Conversion Factors, Non-SI to SI Units of Measurement................................ xii 1—Introduction ................................................................................................

1

Objective and Scope .................................................................................. Model Area Background............................................................................ Model Domain ...........................................................................................

2 2 3

2—Previous Studies .........................................................................................

4

South Florida Water Management District, Broward County Model, 1992 ......................................................................................................... James M. Montgomery Model, 1992......................................................... James M. Montgomery Model, 1986......................................................... Camp Dresser & McKee Model, 1980a and 1980b ...................................

4 5 6 7

3—Hydrologic Setting .....................................................................................

8

Site Climate................................................................................................ Physiography ............................................................................................. Surface Drainage System Features ............................................................ Regional drainage system ..................................................................... Water Conservation Area 2B................................................................ Local drainage systems......................................................................... Old Plantation Water Control District .................................................. Broward County Water Control District............................................... Local surface water bodies ................................................................... Regional and Local Groundwater Flow.....................................................

8 8 9 9 9 9 10 10 11 11

4—WES/ERDC Hydrogeologic Conceptual Model ........................................

13

Summary of Modeling Efforts ................................................................... Summary of Previous Hydrogeological Investigations ............................. Hydrogeology of Model Area.................................................................... Selection of Model Layers ......................................................................... Selection of Hydraulic Conductivities for WES/ERDC Model.................

13 13 15 18 22

iii

iv

5—Data Collection for Numerical Model Input...............................................

35

Pumping Data from Municipalities within the Model Domain ................. Smaller utilities pumping data .............................................................. Peele Dixie pumping data..................................................................... Data management and estimation of monthly flow rates for each PD well ............................................................................................... Other Groundwater Users in the Model Domain ....................................... Stage Data .................................................................................................. SFWMD project canals......................................................................... Water conservation data ....................................................................... Well Observation Data............................................................................... Shallow Aquifer Hydraulic Measurements................................................

35 35 36 37 39 39 39 40 40 42

6—WES/ERDC Numerical Model...................................................................

44

Model Selection ......................................................................................... Computational Domain.............................................................................. Grid Development...................................................................................... Initial Hydrogeologic Parameters .............................................................. Hydraulic conductivity ......................................................................... Anisotrophy ratio.................................................................................. Storage coefficients .............................................................................. Boundary Conditions ................................................................................. Canals and rivers .................................................................................. General head boundaries....................................................................... Lakes..................................................................................................... Recharge ............................................................................................... ET from the water table ........................................................................

44 45 45 46 46 46 46 47 47 48 48 48 49

7—Calibrating the WES/ERDC Model............................................................

51

Calibration Protocol................................................................................... Matching the Net Recharge ....................................................................... Comparison to Observation Head Data. .................................................... Calibrated Model Parameters.....................................................................

51 51 52 54

8—Sensitivity Analysis....................................................................................

55

9—Long-Term Simulation ...............................................................................

58

Exploratory Constituent Transport Simulations ........................................ Screening Level Containment Analysis.....................................................

59 61

10—Summary of Site Conceptualization, Flow Modeling, and Initial Transport Simulation ............................................................................

62

Results of Flow Modeling and Initial Transport Modeling ....................... Conclusions and Model Limitations .......................................................... Test data................................................................................................ Unsaturated effects ...............................................................................

63 64 64 64

Uncalibrated transport modeling .......................................................... Methods to Improve Model Certainty........................................................

65 65

References ........................................................................................................

66

Figures 1-64 Appendix A: Groundwater Users in WES/ERDC Model Domain.................. A1 Appendix B: Pump Rates of Small Utilities.................................................... B1 Appendix C: 1984 and 1989 Daily Percent Flow from South Well Field ...... C1 Appendix D: Weekly Peele Dixie Pump Schedule and Estimated Pump Rates ................................................................................ D1 Appendix E: Monthly Average Peele Dixie Pump Rates and Estimated Annual Totals ............................................................................ E1 Appendix F: Monthly Average Stage for Structures and Daily Hydrographs .............................................................................. F1 Appendix G: Monthly Average Stage for WCA2B ........................................ G1 Appendix H: Well Construction Data and Calibration Wells ......................... H1

List of Tables

Table 1.

Approximate Ranges of Hydraulic Conductivity of Materials that Comprise the Surficial Aquifer System of Broward County (Fish 1988) .......................................................................

16

Table 2.

Sources and Elevations of WES/ERDC Model Layers ................

19

Table 3.

Sources, Transmissivities (T), and Hydraulic Conductivities (K) for WES/ERDC Model Layers...............................................

23

Additional Data on Sources of Transmissivities for Layers 3 and 4..............................................................................................

25

Aquifer Hydraulic Properties Determined from Pumping Tests (Fish 1988) ..........................................................................

26

Aquifer Hydraulic Properties Determined in Other Tests Reported (Fish 1988) ....................................................................

27

Table 7.

Data for Large Supply Wells in Broward County (Fish 1988).....

28

Table 8.

Hydraulic Conductivities Determined from Slug Tests (Fish 1988)....................................................................................

31

Aquifer Test Results in Peele Dixie Well Field (CDM 1980a) ....

32

Table 4. Table 5. Table 6.

Table 9.

v

Table 10.

vi

Peele Dixie Production Well Construction Details (CDM 1980a)................................................................................

33

Table 11.

Example of Peele Dixie Pumping Data ........................................

36

Table 12.

Source of Stage Data from SFWMD and USGS ..........................

41

Table 13.

Shallow Slug Test Results ............................................................

43

Table 14.

Initial Hydrogeologic Properties...................................................

46

Table 15.

Experimental Versus Model ET....................................................

52

Table 16.

Statistical Fit to the Observed Head Data .....................................

52

Table 17.

Summary of Sensitivity Calculations............................................

57

Table 18.

Comparison of Long-Term Simulation to Observation Snapshots ......................................................................................

58

Preface to Part I This report describes the development of a three-dimensional geohydrologic conceptual and numerical model of the Peele Dixie well field, Fort Lauderdale, Broward County, Florida. All pertinent data used in the development of this model are discussed in the text and provided on compact disc. The data collection and management was an extensive effort and required the assistance of various Federal, state, and local agencies. The following organizations graciously contributed to the development of this study: U.S. Geological Survey, Water Resource Division, Miami, FL; South Florida Water Management District, West Palm Beach, Florida; Broward County/Florida Department of Natural Resource Protection, Fort Lauderdale; Water Utilities for the Florida cities of Sunrise, Plantation, Ferncrest, Davie, and Fort Lauderdale, Broward County Water Control District; and Old Plantation Water Control District. This report was a combined project effort by members of the staff of the Geotechnical and Structures Laboratory (GSL), the Coastal and Hydraulics Laboratory (CHL), and Environmental laboratory (EL), U.S. Army Engineer Research and Development Center (ERDC), Vicksburg, MS. The geotechnical and data portion of this report was written by Ms. M. Eileen Glynn and Mr. William L. Murphy, Geosciences and Structures Division (GSD), within GSL under the supervision of Dr. Robert Hall, Chief, GSD. Ms. Benita Abraham (GSD) contributed significantly to data management. The numerical modeling was conducted and appropriate text was written by Dr. Stacy E. Howington and Ms. Jackie P. Hallberg, Hydro-Science Division (HSD) within CHL, under the supervision of Dr. William Martin, Chief, HSD. Dr. Michael O’Connor was Director, GSL, and Dr. Thomas W. Richardson was Acting Director, CHL, during the period of report publication. The work was conducted for the U.S. Environmental Protection Agency (USEPA, Region IV) through the U.S. Army Engineer District (USAED), Jacksonville, Project Management Office. The project was monitored by project managers by Mr. Brad Jackson (USEPA) and Mr. Stan Kinmonth (USAED). This report was reviewed by Dr. John F. Peters and Mr. Earl Edris, GSD, and Dr. Jeffrey Holland, CHL.

vii

At the time of publication, Dr. James R. Houston was Director of ERDC and COL John W. Morris III, EN, was Commander and Executive Director.

The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products.

viii

Acronyms (k)

hydraulic conductivity

(T)

transmissivity

AC

Acting Chief

ADAPS

Automated Data Processing System, USGS

bls

below ground surface

BCWCD

Broward County Water Control District

C-11

South New River Canal

C-12

Plantation Road Canal

CDM

Camp Dresser & McKee

CHL

Coastal and Hydraulics Laboratory, WES

DBHYDRO

SFWMD Hydrometerologic Database

DBKEY

Database key in DBHYDRO

DW

monitoring wells installed by JMM for City of Fort Lauderdale

EPA

Environmental Protection Agency

ERDC

Engineer Research and Development Center

ET

evapotranspiration

FLCC

Fort Lauderdale Country Club

Fm

formation

FPR

Florida Petroleum Reprocessors

G

USGS Series Observation Wells

G-54

Salinity Control Structure on NNRC (Sewell Lock)

GHB

‘general head’ boundary

GSD

Geosciences and Structures Division

GSL

Geotechnical and Structures Laboratory

GMS

Department of Defense Groundwater Modeling System

ix

x

GWSI

Groundwater Inventory System, USGS

HELP

Hydrologic Evaluation Landfill Performance

JMM

James M. Montgomery (Montgomery and Watson)

MODFLOW

USGS numerical code (McDonald and Harbaugh 1984)

MOR

Monthly Operating Reports

msl

mean sea level

MT3D

Mass Transport 3-Dimensional numerical code (Zheng 1991)

NGVD

National Geodetic Vertical Datum

NNRC

North New River Canal

OPWCD

Old Plantation Water Control District

PD

Peele Dixie

Ppt

precipitation

PRP

Possible Responsible Party

PW

Peele Dixie pumping well

QWDATA

Quality of Water Database, USGS

RDB

Relational Database, USGS

S-13

Salinity Control Structure on C-11

S-33

Salinity Control Structure on C-12

SFWMD

South Florida Water Management District

SNRC

South New River Canal

TQ

total flow

TVOC

Total Volatile Organic Compound

USACE

United States Army Corps of Engineers

USEPA

United States Environmental Protection Agency

USGS

United States Geological Survey

VOC

Volatile Organic Compound

WCA

Water Conservation Area

WCA2B

Water Conservation Area 2B

WES

Waterways Experiment Station

WRD

Water Resources Division, USGS

WRPD

Water Resource Planning Division, SFWMD

Units ft

feet

ft/d

feet per day

gpd

gallons per day

gpd/ft

gallons per day per foot

gpm

gallons per minute (unless specified as gallons per month)

gpm/ft

gallons per minute per foot

in.

inches

mg

million gallons

mgd

million gallons per day

mgm

million gallons per month

mgy

million gallons per year

ppm

parts per million

ppb

parts per billion

xi

Conversion Factors, Non-SI to SI Units of Measurement Non-SI units of measurement used in this report can be converted to SI units as follows: Multiply Acres cubic feet cubic feet per day degrees degrees Fahrenheit feet feet per day gallon gallons per day gallons per day per foot gallons per minute per foot Inches mile parts per billion parts per million square miles square feet square feet per day

xii

By 43,560 0.02832 28.32 0.01745 (F-32) 5/9 0.3048 0.0003528 3.785 3.785 12.42 12.42 2.54 1.609 1.0 1.0 2.590 0.0929 0.0929

To Obtain square feet cubic meters liters per day radians degrees Centigrade meters centimeters per second liter liters per day liters per day per meter liters per minute per meter centimeters kilometer micrograms per liter milligrams per liter square kilometers square meters square meters per day

1

Introduction

The United States Environmental Protection Agency (USEPA), Region IV, Atlanta, GA, retained the U.S. Army Engineer Waterways Experiment Station (WES)/Research and Development Center (ERDC) to develop a numerical groundwater model of the Peele Dixie (PD) well field for the purpose of evaluating the empirical conceptual model developed by Bechtel Environmental, Inc., Oakridge, TN (Bechtel 1995). The model also would be used to conduct groundwater remediation feasibility studies. The PD well field (developed in the Biscayne aquifer) is a source of public drinking water for the City of Fort Lauderdale, Broward County, Florida, and surrounding unincorporated areas. The Biscayne aquifer has been designated as a sole source aquifer for Broward County. In 1986, volatile organic compounds (VOC) in excess of the maximum concentration level allowed by Federal and State Drinking Water Standards were discovered in supply well PD-18. Concentrations as high as 457 parts per billion (ppb) total VOCs were documented as occurring in the well field (Well PD-18, 12 January 1987) (James M. Montgomery (JMM) 1992). Bechtel (1997) concluded that the most likely source of the contamination was the Florida Petroleum Reprocessors (FPR) site, located approximately 1 mile from the southern end of the well field. Bechtel’s investigation included a series of soil and water analyses during 1994 through 1997. Concentrations as high as 475,300 ppb total VOCs were documented as occurring in shallow soils at FPR (Bechtel 1997). The empirical conceptual model (Bechtel 1997) shows the VOCs entering the groundwater at the FPR site, migrating downward into the high permeability zones of the Biscayne aquifer, dispersing, and moving northward under the influence of the PD pumping wells. The Possible Responsible Party(s) (PRPs) believe that the North New River Canal (NNRC), which is between the PD well field and the FPR site (Figure 1), is not only a surface water divide but also a groundwater divide that would intercept any contamination from the FPR site. The USEPA elected to develop a numerical groundwater flow model to observe historical flow patterns in the vicinities of the well field, canal, and the FPR site. The model also would be used to develop hydraulic remedial schemes, such as pump and treat or plume containment. In addition, the hydraulic model would support the development of a contaminant fate and transport models for evaluation of such processes as pump and treat, and natural attenuation.

Chapter 1 Introduction

1

Objective and Scope This study involved five major objectives. The first objective was to collect data for the development of a representative, nonbiased, hydrogeologic conceptual model of the PD well field (Biscayne aquifer) and surrounding area, including the FPR superfund site. The second objective was to develop a numerical model from the hydrogeologic model, to hindcast and forecast hydrologic stresses on the surficial aquifer system. The third objective was to calibrate the numerical model using water table observations and to conduct sensitivity analyses to develop confidence in the accuracy of the model. The fourth objective was to produce a long-term (19-year, January 1978 through December 1996) transient simulation to include the time period during which the FPR facility actively reprocessed fuels (1978 to 1992). The 19-year simulation was conducted to examine historical flow patterns throughout the model domain and specifically within the Biscayne aquifer. The fifth objective consisted of developing a screening-level estimate of the amount of pumping required to provide hydraulic containment around the plume. Existing sources of data were used to develop a hydrogeologic conceptual model of an area encompassing the area analyzed with the numerical model. Nineteen years of historical hydrologic data such as precipitation, canal stages, and pumping rates from utilities were collected to conduct a long-term transient simulation. Groundwater flow directions were observed during the long-term simulation. An exploratory transport model was constructed to examine flow patterns in more detail and provide an initial look at contaminant migration patterns. A screening-level analysis was completed to estimate pumping requirements for plume containment.

Model Area Background The WES/ERDC model area is in southeastern Florida, eastern Broward County, as shown in Figures 2 and 3. Palm Beach and Dade Counties border Broward County on the north and south, respectively. The Everglades cover western Broward County and the groundwater elevations are above ground surface or extremely shallow year round. Eastern Broward County (south and east of water conservation area 2B (WCA2B) has been drained for urban development and much of the groundwater table is 5 to 10 ft below land surface (bls). The water table is present in the surficial materials, which are moderately permeable sands and noncontiguous oolitic limestone. The surficial aquifer in Broward County consists of the moderately permeable Pamlico sands and Miami oolite, the highly permeable sandy (sometimes cavernous) limestone of the Biscayne aquifer, and the less permeable sandy limestone and clayey sand of the Tamiami formation (Fish 1988). The base of the surficial aquifer coincides with the top of the Hawthorn Formation. The Biscayne aquifer is defined hydraulically as those materials of the surficial aquifer system having greater than 1,000 ft per day horizontal hydraulic conductivities (Fish 1988). ERDC used this definition as a guideline in developing the WES/ERDC conceptual model, which is illustrated in general by Figure 4. The Biscayne follows lithologic units in 2


general but is not limited to their boundaries. The development of the conceptual model is described in detail in Chapter 4 of this report. The Biscayne aquifer is recharged by local rainfall and discharge waters from Lake Okeechobee and Water Conservation Areas (WCA) 1, 2, and 3. These WCAs cover the entire western two thirds of Broward County. Discharges from Lake Okeechobee are controlled by the South Florida Water Management District (SFWMD) and are related to irrigation demands, seasonal changes, protection against flooding, and groundwater levels (Cooper and Roy 1991). The Biscayne is one of the most productive aquifers in the United States and has been designated as a sole source of drinking water for Broward County. Despite its high productivity and past reliability as a drinking water source to Broward County, urbanization of the area has put increasing demands on the aquifer. The aquifer is in constant threat of contamination by urban activities because of its close connection with the ground surface. In addition, saltwater intrusion has been a concern for decades because of the proximity of the public well fields to the coast and the rapidly increasing population since the 1970’s. Thus, the aquifer is continuously being monitored for contamination (chemical and salt water) and evaluated for greater production. Subsequently, there has been a great deal of information collected in this area, making this study a long and arduous one. For example, four previous groundwater models have included the PD well field in the analyses. These studies are briefly discussed in the following chapter of this report.

Model Domain The model domain (Figure 1) encompasses approximately 30 square miles; with its center (the intersection of Peters Road and the Florida Turnpike) located approximately 6 miles to the west of the Atlantic Ocean in Broward County, Florida (Figure 3). The PD well field is just east of the Florida Turnpike and is divided into north and south fields by Peters Road. The WES/ERDC model boundaries are defined on three sides by canals or rivers; on the north by the Plantation Road Canal (C-12), on the south by the South New River Canal (C-11), and on the east by the North and South Forks of the New River. The western boundary has been set along a straight line, nearly coincident with Pine Island Road. The northwest corner of the model boundary is approximately 45 miles southeast of Lake Okeechobee and approximately 4 miles from the WCA2B, a major water basin of the Everglades (Figure 2). The FPR site is approximately 1-1/4 mile north of the southern model boundary (C-11) and approximately 1 mile south of the PD well field. There are a total of 26 PD wells as illustrated by Figures 5 and 6. The north field contains wells 1 through 10 and 24 through 26. The south field contains wells 11 through 23. No information was found to indicate whether or not well number 1 has ever been operative.


3

2

Previous Studies

Four major groundwater studies that included the PD well field in the analysis were performed prior to the current study. Each of these studies developed numerical groundwater models and were performed by the SFWMD (Restrepo, Bevier, and Butler 1992) and two private consulting firms: Montgomery and Watson, formerly known as James M. Montgomery & Associates (JMM) (1986 and 1992), and Camp Dresser & McKee (CDM) (1980a). The SFWMD study was conducted for numerous reasons but predominantly for regional water resource management purposes. The JMM 1992 model was specifically developed to examine the continued use of the PD well field while providing capture and treatment of the contaminated water. The JMM 1986 model was developed as a result of the 1970 to 1971 and 1980 to 1981 droughts, when city and county officials and utilities determined that a county-wide water supply plan was needed to assure long-term water supply needs (JMM 1986). The CDM (1980a) study, “Dixie Well Field Stress Analysis,” was conducted as a requirement by the SFWMD to evaluate the likelihood of saltwater intrusion into the PD well field. All four groundwater studies were evaluated, and relevant data were included into the WES/ERDC groundwater model.

South Florida Water Management District, Broward County Model, 1992 The SFWMD report, “A Three-Dimensional Finite Difference Groundwater Flow Model of the Surficial Aquifer System, Broward County, Florida” (Restrepo, Bevier, and Butler 1992), was perhaps the most complete of the four previous studies and the most widely accepted by the groundwater community of southeast Florida. Therefore, WES/ERDC considered its general concept of Broward County’s surficial aquifer system (Figure 4) and other aquifer parameters as valid. The SFWMD (Restrepo, Bevier, and Butler 1992) model encompasses all of eastern Broward County and parts of Palm Beach and Dade Counties, which are directly to the north and south of Broward County. The total model area (shown in Figure 2) is approximately 960 square miles, as compared to the WES/ERDC model area, which is approximately 30 square miles. The model was calibrated for two time periods, January 1983 through December 1985 and January 1989 through December 1989. Both calibration periods simulated steady-state and 4

Chapter 2 Previous Studies

transient conditions. Stress periods for the simulations were 1 month. The numerical model code selected was the United States Geological Survey (USGS) MODFLOW (McDonald and Harbaugh 1984) code. The objectives were to: a. Evaluate short-term drought management. b. Estimate potential regional impacts of proposed new groundwater uses, etc. c. Conceptualize regional effects of constructing new canals or changing the operating rules in existing canals. The SFWMD model grid was made up of 67,000 cells, or 100 rows by 134 columns by 5 layers. Each cell had the dimensions of 1,000 ft in the eastwest direction by 2,000 ft in the north-south direction. The SFWMD model relied on Fish’s (1988) hydrogeologic interpretation of the surficial aquifer, previous aquifer investigations, and their own aquifer tests to delineate model layers and define their characteristics. WES/ERDC used the SFWMD model layers as a guide and refined their delineation with site specific data collected subsequent to the SFWMD (Restrepo, Bevier, and Butler 1992) report. The SFWMD model report listed all of the sources and sinks, as of 1992 that were related to the aquifer in eastern Broward County. The listing was immediately useful to the WES/ERDC study. Each groundwater and surface water user (rated at greater than 100,000 gallons per day (gpd)) was listed by SFWMD, in addition to permit information such as well construction, pump capacity, annual allocation, etc. The groundwater users present in the WES/ERDC model domain are listed in Appendix A. Finally, WES/ERDC could not use the SFWMD numerical model alone to simulate the groundwater regime for the current study because (a) the grid resolution was too coarse for detailed analyses at the well field, (b) data were available from SFWMD for only 1 year (1989), and (c) the model area was too large with regard to data management. However, comparisons were made of simulated heads, extracted from the SFWMD 1989 transient calibration runs (Giddings 1997a) in grid cells to corresponding WES/ERDC general head boundaries. The WES/ERDC model boundary conditions and the above comparisons are described in Chapter 7. The SFWMD model has been revised by SFWMD and is now in the review process.1

James M. Montgomery Model, 1992 The objectives of the JMM (1992) study, sponsored by the City of Fort Lauderdale, were to examine the nature and extent of the well field contamination and provide recommendations for groundwater treatment. JMM (1992) installed 1

Personal Communication, 2000, Jeff Giddings, South Florida Water Management District Personnel, West Palm Beach, Florida. Chapter 2 Previous Studies

5

three zone test wells (one in the north field and two in the south field) where testing for contaminated water was conducted in 20-ft intervals. From these tests it was determined that the bulk of contamination was at 60 and 140 ft bls, although contamination was found throughout the subsurface. Consequently, 5 shallow and 17 deep monitoring wells (DW series) were constructed to depths of 60 ft and 140 ft bls, respectively. The geologic logs for these wells were not available to WES/ERDC or to Bechtel for the current study. However, Bechtel recorded water level measurements taken at these wells and made these available to WES. The results of the JMM (1992) field investigation indicated that the contamination plume was migrating from the south well field toward the north well field (JMM 1992), even though actions were taken to decrease migration (the south wells were not used from 1987 to 1992, except for wells 11, 12, 13, 20, and 21). They also concluded that by 1992, the northern limits of the plume were approximately at Peters Road. The southern limit of the plume (Figure 1) was not identified by the JMM study or any subsequent study. Locations of DW wells are presented in Figure 6. The numerical model produced by JMM (1992) was a one-layer model with a total area slightly smaller than the WES/ERDC model domain. The numerical code selected was the USGS MODFLOW (McDonald and Harbaugh 1984) code, and aquifer characteristics were taken from previous studies. The purpose of the model was to simulate viable remediation scenarios. One scenario was to create a groundwater mound between the two well fields, but this idea was rejected after the discovery of an existing hydrocarbon recovery project at Peters Road. As a compromise, the JMM (1992) report recommended pump and treat remediation in the southern well field to prevent contamination from being pulled further north (JMM 1992). Hence, wells PD-17 and PD-18 of the southern well field with the highest contaminant concentrations (Figure 5) are currently being pumped, with the volatiles removed through air stripping. The north field is still operating normally but at a decreased rate.

James M. Montgomery Model, 1986 This study was sponsored by the SFWMD after a series of droughts, 19701971 and 1980-1981, prompted officials to consider long-range planning for raw water supplies to Broward County. This study estimated the effects of constructing new centralized well fields versus increased pumping of existing well fields, for the purpose of meeting the water supply demands of the year 2020. They used two computer codes, (a) the Prickett and Lonnquist (1971) model and (b) the USGS MODFLOW (McDonald and Harbaugh 1984) model, to estimate wellhead protection zones and groundwater table drawdown, respectively. The JMM (1986) model area was approximately 400 square miles and included the eastern one third of Broward County (an area over 10 times the size of the WES/ERDC model area). They conducted aquifer tests at various sites, which were used in the development of the WES/ERDC model transmissivity fields. Trends in the regional transmissivity developed by JMM (1986) were similar to WES/ERDC model trends. Aquifer tests and transmissivity fields are discussed

6


in Chapter 4, paragraph “Selection of Hydraulic Conductivities for WES/ERDC Model.”

Camp Dresser & McKee Model, (CDM 1980a and 1980b) The Camp Dresser & Mckee (CDM 1980a) PD study was conducted by the consulting firm Ross Saarinen, Bolton & Wilder, a CDM associate firm. Although the final study report, “Dixie Well Field Stress Analysis,” was written by Ross Saarinen, Bolton & Wilder, the work will be herein referred to as the CDM model study (1980a). The CDM study (1980a) was conducted for the City of Fort Lauderdale, by order of the SFWMD, to determine the threat of saltwater intrusion within the PD well field because of its proximity to the uncontrolled tidal reaches of the NNRC (Figure 1). The SFWMD was concerned that pumping might induce saltwater flow into the well field during extended periods of low rainfall and decreased freshwater flow in the canal below the salinity control structure Sewell Lock (also referred to as G-54 and illustrated in Figure 1). The CDM study (1980a) objective was to investigate hydrologic conditions that would lead to well field failure by saltwater intrusion. CDM conducted aquifer tests, which were evaluated and incorporated into the WES/ERDC hydrogeologic conceptual model. These data are discussed in Chapter 4, paragraph entitled “Selection of Hydraulic Conductivities for WES/ERDC Model.” The numerical code selected by CDM was a modified Prickett-Lonnquist (1971) code. The model was calibrated against a long-term average water table calculated from USGS water table measurements during 1975 to 1977. The numerical model was a quasi-two-dimensional (2-D) groundwater flow model in a two-layered system. The surficial aquifer system was modeled, such that the Pamlico sand was the upper layer and the Miami oolite and Biscayne aquifer comprised the lower layer of the system. Model boundaries were modeled as no flow, which eliminates the possibility of groundwater underflow from outside the modeled area. The model area was slightly smaller than the WES/ERDC model domain. The CDM Peele Dixie analysis concluded that only under extreme drought conditions would the surface water from the canal reach the well field, hence the threat of saltwater intrusion from the canal was negligible. Likewise, the WES/ERDC model’s 19-year simulation confirmed that the NNRC, beneath the control structure G-54, was always a gaining stream. CDM conducted a similar study in Fort Lauderdale’s Prospect well field, just north of the PD well field. The study, entitled “Prospect Well Field Impact Analysis” (CDM 1980b), included specific capacity tests and recharge measurements to the water table in the Prospect well field. These data were used to calibrate recharge and for development of transmissivity fields for the WES/ERDC model. These procedures are described in later chapters of this report.


7

3

Hydrologic Setting

Site Climate The climate in Fort Lauderdale is considered to be tropical to subtropical with mild winters and long, warm, and humid summers. The average annual temperature is 75 EF, and the average annual rainfall is 60 in. Rainfall occurs during all seasons, but on average, nearly 65 percent of the annual rainfall occurs during the rainy season (June through October). The remaining 35 percent of the annual rainfall occurs during the drier months of November through May (Pendleton, Dollar, and Law 1976). During the period of evaluation (January 1978 to December 1996), the years 1988 and 1989 were drier than average, and the years 1994 and 1995 were wetter than average.

Physiography The study area is within Eastern Broward County, Florida, including some portions of Fort Lauderdale, Florida (Figure 2). Broward County is made up of four physiographic features typical of coastal southeastern Florida. These are from west to east; the Everglades, the Sandy Flatlands, the Atlantic Coastal Ridge, and the Coastal Marshes. Under natural (predevelopment) conditions, most of the county (which is covered by Everglades and Sandy Flatlands) was inundated with water for all or part of the year. The Sandy Flatlands are very low-lying, and natural drainage of this area is slow because the groundwater gradient is almost flat (Parker, Ferguson, and Love 1955). The Atlantic Coastal Ridge (hardly discernible as a ridge) is approximately 5 miles in width at Fort Lauderdale (Fish 1988) and forms the highest ground in the county of up to 22 ft above mean sea level (msl). It historically controlled the drainage overflow from Lake Okeechobee to the south, except for a few natural breaches (rivers) to the east. The WES/ERDC model boundaries generally lie within the Atlantic Coastal Ridge and the Sandy Flatlands. From regional maps (Parker, Ferguson, and Love 1955; Fish 1988; and Pendleton, Dollar, and Law 1976), it was estimated that the eastern portion of the model domain lies on the Atlantic Ridge, and the western portion of the model area lies on the Sandy Flatlands. The contact between these two land features is difficult to discern because of the changes in land by urbanization. However, the PD well field is the highest land topographically and is 8

Chapter 3 Hydrologic Setting

presumed to be on the Coastal Ridge. The land west of the Florida Turnpike appears closer to the water table and is probably part of the Flatlands. The soils on the Coastal Ridge and the Flatlands are fine- to medium-grained sands and have vertical permeabilities ranging from 12 to 40 ft per day (Pendleton, Dollar, and Law 1976). These were classified as Immokalee–Pompano Urban Series by the U.S. Soil Conservation Service (Pendleton, Dollar, and Law 1976).

Surface Drainage System Features Regional drainage system Southeastern Florida has a network of drainage systems, which control the flow of surface water from Lake Okeechobee and the Everglades to the Atlantic Ocean. The primary drainage systems were designed and built by the U.S. Army Corps of Engineers (USACE) and are managed by the SFWMD. Secondary drainage systems are maintained by local water control districts, but the SFWMD and the USACE maintain the final authority over water control practices. This system was designed under the Central and Southern Florida Project for Flood Control and other Purposes Project to provide flood protection, water control, and agricultural and municipal water supply for south Florida (Cooper and Lane 1987). Project features include canals, levees, saltwater control structures, and six water conservation areas of the Everglades. These surface water structures are referred to as Project Canals, Project Levees, etc. In general, the Project Canals are used to drain their respective basins, prevent flooding, convey excess water from Lake Okeechobee and WCA(s), supply water to their respective basins during periods of low natural flow, and maintain groundwater table elevations to prevent saltwater intrusion into local groundwater. Water Conservation Area 2B Water Conservation Area 2B (Figure 2) is the closest WCA in proximity to the WES/ERDC model area, and its stage data were used as the source for the western general head boundary. Its purpose in the regional drainage system is to (a) provide viable wetland, (b) recharge regional groundwater (the Biscayne aquifer), (c) supply water to adjacent basins in Broward County, (d) receive and store regulatory discharges from WCA2A (north of WCA2B), and (e) prevent water accumulating in the Everglades from overflowing into urban and agricultural lands in eastern Broward County (Cooper and Roy 1991). The WCA2B occupies an area of 43.8 square miles and is a significant source of recharge to the Biscayne aquifer. Its design stage is 10 ft above msl, but the stage can exceed 11 ft. When water level exceeds 11 ft msl, the excess is discharged to the NNRC and ultimately to the Atlantic Ocean.


9

Local drainage systems Three Project Canals and Structures are located within the WES/ERDC model area, in addition to two local drainage systems (Figure 7). These canals are (from north to south) the Plantation Road Canal (C-12), the NNRC, and the South New River Canal (SNRC) (C-11). The C-12 and C-11 canals are coincident with the north and south model boundaries. Because of the proximity to the Atlantic Coast, each Project Canal has its own salinity control structure. These structures prevent brackish water from moving upstream and also maintain a specified head of fresh water on the upstream side. These structures are maintained by the SFWMD and are referred to as: the S-33 on the C-12; the G-54 (Sewell Lock) on the NNRC; and S-13 on the C-11. The salinity control structure locations are presented in Figure 1. The optimum headwater elevations (el)1 above msl for these structures, as defined by SFWMD (Cooper and Lane 1987) are: 3.5 ft for S-33; 3.5 - 4.5 ft for G-54; and 1.6 ft for S-13. These optimum levels were also observed as average levels during the 19-year (1978 -1996) period of investigation. The optimum tailwater elevations were not given in the above reference, but average tailwater elevations observed were approximately 1 ft (msl), for all three structures, throughout the 19-year period of study. The water levels on the upstream side of the structures are regulated by the SFWMD. The tailwater for each structure fluctuates with the tide and is also dependent on upstream discharges. The smaller secondary water drainage systems in the model area are maintained by the local water control districts: Old Plantation Water Control District (OPWCD) and the Broward County Water Control District (BCWCD). These secondary canals provide drainage, flood protection, and maintain groundwater levels in their District. Old Plantation Water Control District The OPWCD maintains a series of secondary canals that are located in the northwest quadrant of the model area (Figure 7). The OPWCD canals are north of the NNRC, west of the Florida Turnpike, and continue north of the C-12 canal. The OPWCD canals in the WES/ERDC model area are maintained at a level slightly lower than the NNRC (Mr. H.C. O’Quinn, Superintendent of OPWCD, personal communication). Generally, the OPWCD canals are approximately 0.1 ft below the NNRC. The OPWCD canals can drain during high-water periods into the NNRC by gravity. However, water levels are normally maintained at approximately 3.8 to 4.4 ft above msl and controlled by floodgates. The depths of these canals are approximately 10 ft, while the widths are typically 50 to 75 ft.

1

All elevations (el) cited herein are in feet referenced to the National Geodetic Vertical Datum (NGVD) of 1929.

10


Broward County Water Control District Similarly, the BCWCD maintains secondary canals in the southwest quadrant of the model area. These canals are located to the south of the NNRC, to the west of the Florida Turnpike, and continue south of the C-11 canal. The water level in the BCWCD canals in the WES/ERDC model area is maintained by the S-13 structure, and subsequently by the SFWMD. However, the daily maintenance (clearing of vegetation, etc.) of these canals is under the jurisdiction of the BCWCD. The BCWCD canals drain by gravity into the SNRC. There are no floodgates controlling the water elevation in the BCWCD canals. Consequently, the water level elevation is approximately the same as the headwater at S-13 (1.6 ft msl) or slightly higher in the northern portions of these canals.1 Depths of these canals are typically 5 ft, and widths are typically 30 ft. Figure 7 was developed from four 1983 USGS 7-1/2-min quadrangle maps and shows only general boundaries of local canals. Delineation of canals used in the WES/ERDC numerical model area were digitized from a 1995 USGS orthophoto-quadrangle map used as the base map (Figure 1) for the model area. Local surface water bodies Lakes and small canals are prevalent in the western half of the model area. These lakes are locally referred to as rock pits, because of the practice of dredging sand and limestone from them for urban fill. Because of the high price of real estate, some of the older pits are being filled in to create more space for mobile home parks and other developments. These lakes have continually changed shape and size, depending on whether they were being filled or excavated, over the past 20 years. A total of seven lakes were included in the numerical model, and their perimeters have been modeled after the base map (Figure 1). They occur at the intersection of the Florida Turnpike and I-595. Illustrations in Chapter 7, “Calibrating the WES/ERDC model,” present specific water bodies discretized in the WES/ERDC numerical model. Their depths were estimated from conversations with the SFWMD, Planning Division personnel.2

Regional and Local Groundwater Flow The regional unconfined groundwater flow is predominantly from the Everglades toward the south and southeast but is very sensitive to local pumping gradients and canal drainage systems. Figures 8 and 9 illustrate average water table conditions for the years 1974 to 1982, divided into wet and dry seasons, respectively. These maps suggest that pumping from municipal well fields in the Biscayne Aquifer (such as the Fort Lauderdale Peele Dixie) significantly distort the surficial groundwater flow patterns during both seasons. When examining older water table maps from 1940 to 1950 (CDM 1980a), the gradient was almost 1

Personal Communication, 1997, J. Aucamp, BCWCD Superintendent, Florida. Personal Communication, 1997, Jeff Giddings, South Florida Water Management District Personnel, West Palm Beach, Florida. 2


11

a constant throughout the model area, from northwest to southeast. However, as drainage systems were constructed and well fields increased their extraction, a definite modification of the gradient developed. Fish (1988) states that the natural groundwater flow in Broward County is closely related to the water table and piezometric levels in the unconfined Biscayne are almost identical to the local groundwater table. However, because of considerable stratification and local permeability variation of the aquifer, the aquifer may exhibit semiconfined behavior when stressed (Fish 1988). Sherwood, McCoy, and Galliher (1973) describe the Biscayne as a semiconfined aquifer because of this variation in permeability from stratification: Water-level and aquifer-test data indicate that the Biscayne aquifer exhibits different characteristics under static conditions (nonpumping) than under pumping conditions. Under static conditions, the water level in a shallow well will be at the same elevation as the water level in an adjacent deep well, suggesting that the entire aquifer is under unconfined conditions. However, when the deep (100-150 ft), highly permeable zones of the aquifer are pumped, water levels in deep wells as much as 1,000 ft away show an immediate rapid decline and the levels in shallow wells much closer to the pumping wells show no immediate effect. Thus, in aquifer tests of short duration (less than 24 hr) the zone in which the supply wells are developed reacts as a confined aquifer overlain and partly confined by a leaky roof of less permeable beds. The Biscayne Aquifer in the PD well field has a variation in permeability (CDM 1980a) as described above and probably exhibits semiconfined behavior during changes in pumping schedules.

12


4

WES/ERDC Hydrogeologic Conceptual Model

Summary of Modeling Efforts WES/ERDC selected the hydrogeological layers for its MODFLOW analysis from evaluation of data within the PD/FPR area of investigation and from other previous investigations of the hydrogeology of the Fort Lauderdale and Broward County area. The SFWMD three-dimensional (3-D) flow model (Restrepo, Bevier, and Butler 1992) of the surficial aquifer system of Broward County adopted Fish’s (1988) hydrogeological model of the surficial aquifer as the basis for delineating layers, with supplementary information from well data obtained subsequently. Fish (1988) produced a detailed analysis of available subsurface hydrogeological data for Broward County and provided vertical cross sections showing the delineation of aquifer zones based on hydraulic conductivities and transmissivities derived from aquifer tests and laboratory analyses of samples. Fish used the earlier geological evaluation of Causaras (1985), who provided a base of geological cross sections on which Fish superposed his color-coded aquifer zones. Causaras constructed geological sections from boring logs of deep wells emplaced by the USGS in Broward County. A map showing the locations of the wells used by Causaras in the geological interpretations (ovals) and cross sections (dashed lines) is provided in Figure 10. Figure 6 is a map of production and monitoring wells in the PD/FPR study area.

Summary of Previous Hydrogeological Investigations The general succession of aquifers and aquicludes in the Fort Lauderdale area is shown in Figure 11, prepared as a consensus of earlier geological investigations in the southeast Florida area (JMM 1986). The surficial aquifer, primarily the Biscayne, is hydraulically separated from the deeper Floridan aquifer by the 500-ft-thick Floridan aquiclude, primarily the Hawthorn formation. The Floridan aquifer begins at a depth of approximately 750 to 800 ft. Three USGS investigators published extensive treatises on the geology and groundwater hydrology of south Florida, with emphasis on the Broward County

Chapter 4 WES/ERDC Hydrogeologic Conceptual Model

13

area. Observations made by them and pertinent to the selection of the WES/ERDC model layers are summarized in this section. Parker, Ferguson, and Love (1955) characterized the surficial and Biscayne aquifers in Dade and Broward Counties in Water Resources of Southeastern Florida, USGS Water Supply Paper 1255. Parker, Ferguson, and Love (1955) described the Biscayne aquifer as consisting of Miocene (Tertiary) to Pleistoceneaged sediments. The sedimentary units are, from oldest to youngest, the uppermost part of the Tamiami formation, the Fort Thompson and Anastasia formations, the Key Largo limestone, and the Pamlico sand. Parker’s delineation of the Biscayne aquifer is broader than that of later investigators, who subsequently restricted the Biscayne to the highly permeable materials within the surficial aquifer system in Broward County. He emphasized that “The boundaries of the Biscayne aquifer seldom follow formational boundaries, but cut across according to the geohydrological properties” (Parker, Ferguson, and Love 1955). He noted that the aquifer materials are sufficiently indurated such that most wells are open-hole, or rock-wall installations, not requiring screens [most of the Peele Dixie production wells are open-hole]. Parker, Ferguson, and Love (1955) also noted that, “...deep sand-filled channels cut entirely through the Miami oolite into the underlying Fort Thompson [or Anastasia] formation.” The deep section of Pamlico sand, with missing Miami oolite, north of the New River Canal in the vicinity of the PD wells may be attributable to one of these channels. A vertical profile of the aquifer formations near Fort Lauderdale is illustrated by Figure 12 (Parker, Ferguson, and Love 1955). The profile extends west to east along the NNRC and transects the WES/ERDC model area. The PD/FPR area lies approximately between well G513 (located at the intersection of the NNRC and the Florida Turnpike) and Florida Hwy 7 on the profile. The western boundary of the WES/ERDC model is approximately 3 miles west of well G513. The profile is representative of the aquifer formations encountered in the modeling area. It shows the transition of the Fort Thompson formation in the west to the Anastasia formation in the east, the occurrence of the Miami oolite overlain by the Pamlico sand at the surface, and the contact with the Tamiami formation. The profile also shows the Fort Thompson/Anastasia formations, major units of the highly permeable Biscayne aquifer, thickening to the east. Parker, Ferguson, and Love (1955) emphasize that only the upper 15 ft or so of the Tamiami, which is a “solution-riddled” limestone, is highly permeable. Much of the rest of the formation was considered part of the Floridan aquiclude. Fish modified Parker’s delineation of the Tamiami, as discussed below. Causaras provided detailed logs of 27 deep wells, installed throughout Broward County by the USGS, and described the geological subsurface of the county in the Geology of the Surficial Aquifer System Broward County, Florida, USGS Water Resources Investigations Report 84-4068. Causaras (1985) prepared eight detailed stratigraphic profiles encompassing all of Broward County with emphasis on the eastern half of the county including the PD/FPR model area. Causaras describes the surficial aquifer as being about 400 ft thick near the coast and thinning inland to about 160 ft. There are numerous facies changes in an east-west direction. Limestone predominates in the western half of the county; sands, sandstone, and sandy limestones are prevalent in the east. 14


Fish (1988), in cooperation with the SFWMD, expanded the work of Causaras by conducting an extensive analysis of existing and new groundwater hydrological data in Broward County, using Causaras’ logs and profiles as a base. The USGS conducted aquifer testing throughout Broward County from 1981 through 1984. Fish conducted 22 pumping tests in 11 of the deep wells of Causaras, some in more than one interval, to obtain hydraulic properties (Fish 1988). Fish also compiled data from previously available tests by others in Broward County and estimated hydraulic conductivity and transmissivity from specific capacity data of many commercial and municipal wells in the county (Fish 1988). He provided a diagrammatic profile of the subsurface extending from the west side of Broward County to the sea (Figure 13). The profile covers a much greater distance than that of Parker, Ferguson, and Love (1955) shown in Figure 12. Fish’s profile shows the thickening of the surficial and Biscayne aquifers to the east, the relative positions and occurrences of formations, and the eastward transition from Fort Thompson to Anastasia formation (Fish 1988). The WES/ERDC model area has been added to the profile to show its position relative to the underlying units. Concerning the delineation of the aquifer, Fish stated that because clastic (particulate or fragmental) sediments predominate in Broward County, (with much interfingering of sands and limestones) it is more difficult to distinguish the Biscayne aquifer in Broward than in Dade County (Fish 1988). Fish relied on variations of hydraulic properties within the formations to delineate the Biscayne aquifer (Fish 1988). The Biscayne is characterized by the presence of highly permeable limestone or calcareous sandstone in the Fort Thompson, Anastasia, or Key Largo formations (the Key Largo was not identified by Fish in the WES/ERDC model area). The Biscayne includes the Tamiami formation if at least 10 ft of it has a hydraulic conductivity of greater than 1,000 ft/day (Fish 1988). Fish stated that the solution-riddled limestone and sandstone of the Biscayne have hydraulic conductivities often exceeding 10,000 ft/day (Fish 1988). He defined the base of the surficial aquifer system as the tight clays and silts, lime muds, or dense, noncavernous limestones having hydraulic conductivities of less than 0.1 ft/day (Fish 1988). In the WES/ERDC model area, the base is typically coincident with the top of the Hawthorn formation (Figure 13). Fish devised a classification of aquifer layers based on ranges of hydraulic conductivities compiled from well test data (Table 1). His classification was the basis for the selection of the 3-D finite difference model layers for the SFWMD (Restrepo, Bevier, and Butler 1992) and WES/ERDC models.

Hydrogeology of Model Area Ongoing investigations by Bechtel provided detailed information on the subsurface geology of the PD well fields and the area south of the NNRC between the Florida’s Turnpike and SW 40th Ave, as shown in Figure 6. Figure 14 is a vertical geologic profile, section AA’, extending south to north through selected


15

Table 1 Approximate Ranges of Hydraulic Conductivity of Materials that Comprise the Surficial Aquifer System of Broward County (after Fish 1988) Horizontal Hydraulic Conductivity (Permeability) Qualitative Range Permeability ft/day Very high

High

Moderate

Low

Very low to practically impermeable

16

$ 1,000

100-1,000

10-100

0.1-10

# 0.1

Materials - Lithology and Porosity

Geologic Formations

Solution-riddled limestone, commonly shelly or sandy. Calcareous sandstone, may be shelly

Qf, Qa

Coralline limestone, reefal, very porous

Qk

Gray, shelly limestone, locally sandy, relatively soft

Tt

Limestone or calcareous sandstone interbedded with sand, or with sand partially filling cavities Coarse shell sand and quartz sand

Qa, Tt, Qf

Dense, charcoal gray to tan limestone with some solution channels, usually shelly or sandy Very fine to medium, relatively clean quartz sand

Ttu

Fine to medium quartz and carbonate sand

Tt

Cream-colored limestone with minor channels

Qf, Qa

Tan, cream, or greenish limestone, locally containing shell sand Calcareous sandstone and sand

Tt

Slightly clayey or sandy, gray limestone

Tt

Oolitic limestone

Qm

Very fine to medium sand with some clay, silt, or lime mud, locally shelly Soft gray or buff limestone with silt and fine sand

Tt, Qf, Qa

Dense, calcareous sandstone

Tt

Light-green, fine-grained foraminiferal limestone with very fine quartz sand Dense, hard limestone with very small cavities or channels; approximately equal mixtures of sand, shell fragments, and lime mud. Green clay or silt; locally with very fine sand

Tt

Sandy, shelly lime mud

Tt

Very dense, hard limestone with no apparent solution cavities or fractures

Qf

Qa, Tt

Tt

Qp, Qa, Tt

Tt, Qa

Tt

Qf Th, Tth, Tt1, Ttu


borings in the area. Figure 6 shows the location of section AA’. The EPA-series of logs is comprised of Bechtel’s monitoring well borings, most of which were logged from cuttings. Split spoon samples, taken every 5 ft, improved the logging of boring EPA-SB01. The boring labeled Peele Dixie Pumping Well (PW)-18 represents a PD production well located in the south well field, for which only the total depth and approximate location of the production zone are known. Well G515 is a USGS well emplaced prior to 1955 in the north well field and logged by the USGS. From the descriptions of the soils and rocks encountered in the monitoring well borings, it was possible to identify formations underlying the study area. The Pamlico sand extends from the surface to a depth of 10 to 15 ft in the area south of the North New River Canal and Butterfly Lake. The sand is underlain immediately by 20 to 40 ft of oolitic limestone presumed by WES/ERDC to be the Miami oolite. North of the North New River Canal and Butterfly Lake, however, the Miami oolite is missing and has been replaced by a deep section of Pamlico sand. The absence of Miami oolite north of the canal is probably a result of removal by one of the deep sand-filled channels that, according to Parker, Ferguson, and Love (1955), formerly ran from the vicinity of Lake Okeechobee to the sea, as mentioned in an earlier section. The top of the sandy limestone and calcareous sandstone, identified as the Anastasia formation in Figure 14, delimits the top of the highly permeable Biscayne aquifer. A hard and often vuggy limestone, encountered at an elevation of about 110 ft, is descriptive of the upper portion of the Tamiami formation. Most of the deep (D-series) monitoring wells of Bechtel were screened in the limestone identified by WES/ERDC as upper Tamiami. WES/ERDC identified the four geologic units described in the preceding paragraphs in the PD study area from information and descriptions provided by various sources (Fish 1988; Causaras 1985; and Parker, Ferguson, and Love 1955). Assigning formational or other time-stratigraphic names to subsurface materials in the Broward County area is difficult because of the variable lithologies present vertically and laterally, as noted in the accounts of these and other hydrogeologists. Indeed, formational designations change with time with the addition of new data and further studies. Bechtel (1997) recognized two geologic units (the Fort Thompson and the Key Largo formations) in their PD study area borings in addition to the four units identified by WES/ERDC. The Fort Thompson is stratigraphically equivalent to the Anastasia and the Key Largo to the uppermost Anastasia. Bechtel’s (1997) interpretation of the subsurface to include the presence of the Fort Thompson and Key Largo in the PD study area does not affect the delineation of the model layers and the assigned ranges of hydraulic properties proposed by WES/ERDC for its groundwater flow model. Therefore, the slight difference in identifications by Bechtel (1997) and WES/ERDC of formations present beneath the study area is insignificant. Figure 14 shows the lithologies underlying the study area are consistent with the broader, county-wide geologic descriptions presented in the literature. Later sections in this report discuss the model layer thicknesses and hydraulic properties assigned to the local study area. Chapter 4 WES/ERDC Hydrogeologic Conceptual Model

17

Selection of Model Layers Fish identified the five aquifer zones by applying a logarithmic range of hydraulic conductivities to the subsurface materials depicted by Causaras (Figures 15 and 16 are greatly reduced from their original sizes). Fish derived the ranges of conductivity from aquifer test results as explained above. He delineated the zone of highest conductivity as dark blue, which included all material with hydraulic conductivity greater than or equal to 1,000 ft/day. A light blue zone included conductivities from 100 to 1,000 ft/day. A dark green zone included conductivities from 10 to 100 ft/day. A light green zone included conductivities from 0.1 to 10 ft/day. A yellow zone represented hydraulic conductivities less than or equal to 0.1 ft/day. In addition to the well hydraulic data, other information used to delineate zones of hydraulic conductivity by Fish (1988) were: a. Flow rates obtained while drilling the test holes. b. Inferences of hydrology from inspection of samples. c. Published tables of hydraulic conductivity versus grain size and sorting. Fish considered the dark blue zone of highest conductivities as representative of the Biscayne aquifer, the most productive zone of the surficial aquifer system. The top and bottom of the highly conductive zone (dark blue) formed the top and bottom, of SFWMD’s (Restrepo, Bevier, and Butler 1992) model layers 3 and 4, respectively. SFWMD (Restrepo, Bevier, and Butler 1992) used the lowest conductivity zone, less than or equal to 0.1 ft/day (yellow), as the base of its model layer 5 and applied hydraulic conductivities of 0.1 to 1,000 ft/day (green through light blue of Fish) to its layers 2 and 5. Fish (1988) delineated subsurface hydrological boundaries on the basis of hydraulic properties, not on lithologic or stratigraphic characteristics. Formational boundaries and hydraulic boundaries are not necessarily the same. The WES/ERDC model adopted layers similar to those of the SFWMD (Restrepo, Bevier, and Butler 1992) model, but consulted Fish’s (1988) original data to delineate tops and bottoms and areal distribution. Table 2 presents the data sources and layer elevations selected by WES/ERDC for its model. WES/ERDC contoured the surfaces and thicknesses of the model layers for an area beyond that of the actual model boundaries to circumvent “edge effect” problems when contouring and to take advantage of the greater number of data points available in the larger area. Referring to Figure 9 and Table 2, the area considered in contouring the model layers was delimited by USGS well G-2312 in the northwest, G-2344 in the northeast, G-2317 in the southwest, and G-2328 in the southeast. A map of all borings and wells supplying data points for layer elevations is presented as Figure 17. Bechtel (1994, 1995, 1996) placed and logged several borings in the PD well field and FPR area from 1994 to the present. Although the Pamlico sand and Miami oolite are mappable lithologic units in many of the Bechtel borings, they 18


Table 2 Sources and Elevations of Top and Bottom Layers of WES/ERDC Model NAD27 X (Easting), ft 759,950.5

NAD27 Y (Northing), ft 638,948.1

Well Number EPA-02D

Elev top of layer 3, ft 1 NGVD (and source) -43 (Bechtel log)

Elev bot. of layer 4, ft 1 NGVD (and source) 1 -160 (boring G-2345)

759,356.6

639,935.2

EPA-04D

-43 (Bechtel log and Section AA’)

-160

1

NA

758,977.6

637,003.1

EPA-06D

-31.5 (Bechtel log)

-160

1

NA

757,431

635,499

EPA-14D

-45 (Bechtel log and EPA-16D)

-160

1

NA

757,860

634,300.6

EPA-15D

-42 (Bechtel log)

-160

1

NA

757,020.9

636,267.9

EPA-16D

-42.8 (Bechtel log and Section BB’)

-160

1

NA

759,466.6

634,484.1

EPA-18D

-41.5 (Bechtel log)

-160

1

NA

738,000

631,600

TreeTops test well

-35 (JMM, 1986, log)

NA

NA

744,600

607,250

S Fla State Hosp

-31 (JMM, 1986, log)

NA

NA

775,357

663,896

Mills Pond Pk

-70 (SFWMD Tab A-1, p 48)

NA

NA

754,800

645,200

Heritage Pk

-70 (SFWMD, 3 Tab A-1)

NA

NA

713,743

652,942

Markham Pk

-32 (SFWMD Tab A-1)

-87 (SFWMD Tab A-1)

-107 (SFWMD Tab A-1)

682,659

627,759

G-2311

-11 (SFWMD and Fish Sec FF’)

-62 (SFWMD and Fish Sec FF’)

-183 (SFWMD and Fish sec FF’)

676,930

689,524

G-2312

NA

NA

-202 (Fish Sec BB’)

692,129

590,142

G-2317

-10 (Fish Sec DD’)



715,768

590,456

G-2318




671,408

658,809

G-2319

-21 (Fish Sec CC’)



707,798

652,812

G-2321


-81 (SFWMD and Fish Sec CC’)


739,564

644,396

G-2322

-52 (SFWMD and Fish Sec CC’)



747,494

597,190

G-2327

-44 (SFWMD and Fish Sec GG’)

-120 (SFWMD and Fish Sec GG’)

-265 (Fish Sec GG’)

Elev bot. of layer 5, ft 1 NGVD (and source) 2 NA

(Continued) 1

The -160-ft elevation of the base of the highly permeable layer (layers 3 and 4) in the FPR/PD area was selected on the basis of the Fish (1988) boring log G-2345, and the consistently flat occurrence of the Tamiami formation contact in the study area. 2 Datum not encountered in this boring. 3 Note that the top of layer 3 from this source disagrees with Fish (1988), his Section CC’ near G-2345.


19

Table 2 (Concluded) NAD27 X (Easting), ft 777,579

NAD27 Y (Northing), ft 602,321

Well Number G-2328

Elev bot. of layer 4, ft 1 NGVD (and source) -142 (SFWMD and Fish Sec DD’) NA

Elev bot. of layer 5, ft 1 NGVD (and source) -280 (Fish Sec GG’)

G-2341

Elev top of layer 3, ft 1 NGVD (and source) -36 (Fish Sec DD’, top of Key Largo) NA

729,658

689,372

760,435

690,055

G-2342




788,186

693,768

G-2344

-45 (SFWMD and Fish Sec BB’)


759,331

646,935

G-2345


-122 (Compromise: SFWMD and Fish Sec 4 BB’) -160 (Fish Sec GG’)

779,357

637,570

G-2347

753,412

622,062

-34 (SFWMD and Fish Sec CC’) -48 (Fish Sections)

-330 (Fish Sec CC’, arbitrary top of Th) -282 (Fish GG’)

760,000

668,495



758,844

647,248

half-way point South (between G-2327 and G-2345) half-way point -60 (Fish Sec GG’) North (between G2345 and G-2342) PW-06

-140 (SFWMD and Fish Sec CC’) -160 (Fish Sec GG’ and p. 52)


-297 (Fish GG’)

-182 (CDM log)

4

High conductivity strata exist below this depth in Fish (1988), Section BB’, but are separated by lower conductivity strata. SFWMD selected -112 as the base.

are indistinguishable hydraulically, according to Fish (1988). Hydraulic conductivity and transmissivity values from aquifer tests and ranges of values supplied by Fish (1988) (Table 1 herein) indicate a “moderate hydraulic conductivity” (10 to 100 ft/day) for both the Pamlico sand and the Miami oolite. Both of these lithologic units lie within the range of hydraulic conductivities assigned to layer 2 of the SFWMD (Restrepo, Bevier, and Butler 1992) and WES/ERDC models, and thus were not distinguished as separate hydraulic model layers based on lithology. However, to better delineate the surface water bodies and increase resolution in the numerical model, this hydraulic layer was discretized into WES/ERDC model layers 1 and 2. Hence, the top of layer 1 was defined at ground level, and the top of layer 2 was assigned a constant elevation of -15 ft NGVD. Many of the Bechtel borings penetrated much of the surficial/Biscayne aquifer with maximum depths of about 100 to 200 ft. Bechtel supplied WES/ERDC copies of their boring logs. WES/ERDC attempted to incorporate subsurface information provided in the Bechtel logs in the immediate PD/FPR area. WES/ERDC interpreted the top of the calcareous sandstone/sandy limestone unit (the Anastasia Fm) as the equivalent of the top of the highly permeable zone of the surficial aquifer recognized by Fish and by SFWMD. WES/ERDC included the top several feet of the Tamiami Formation in the highly permeable zone, in accordance with the work of Fish (1988) and Parker, Ferguson, and Love (1955). The WES/ERDC team selected logged picks of the top of the Anastasia formation (sandy limestone or calcareous sandstone) from seven of the Bechtel

20


borings (Table 2) as input to the WES/ERDC model for the top of layer 3. Logs of the City of Fort Lauderdale’s DW series of monitoring wells located north of the NNRC, and of the Peele Dixie production wells (the PW series), were not available during the limited time available for this study. Borings nearest the Peele Dixie/ FPR area other than Bechtel borings were several old USGS wells and the Heritage Park well (Figure 17) of the SFWMD (Restrepo, Bevier, and Butler 1992) model. The Heritage Park well provided a top of the highly permeable zone (WES/ERDC model layer 3) of -70 ft NGVD. After careful consideration of all hydraulic properties of the highly permeable zone (discussed in the next section), WES/ERDC eventually assigned a constant thickness of 55 ft to layer 3 to distinguish the decrease in permeability in the shallow zone of the Biscayne aquifer. The old USGS wells, described by Parker, Ferguson, and Love (1955), were logged in insufficient detail or were too inconsistent to provide confident picks of layer tops and bottoms. The old USGS wells did recognize a “very permeable limestone” at -98 to -114 ft el in well G515, at -115 to -123 ft in well G513 on the NNRC just west of the Florida’s Turnpike, and at -120 to -167 ft in well G516 on Broward Road about 1 mile northwest of the well field. These elevations corresponded to the upper part of the Tamiami formation in the area. WES/ERDC assigned an elevation of -160 ft to the base of layer 4 in the model area because of an observation by Fish (1988). Fish noted that the base of the highly permeable zone (WES/ERDC model layers 3 and 4, Fish’s dark blue zone) is about 150 to 200 ft deep several miles inland, in the vicinity of the southern half of Section GG’ and the eastern portion of Section CC’ (see Figure 10 for locations of sections, and Figures 15 and 16 for profiles GG and CC). The base of the highly permeable zone is typically shallower over much of Broward County. Well G-2345 (Figure 15) is within the Peele Dixie north well field (Figure 10). The dark blue, highly permeable zone extends to between 180 and 185 ft on Section GG’ in the vicinity of G-2345. However, Fish (1988) noted that the lithologies depicted between wells G-2345 and G-2327 to the south probably range from very high to very low hydraulic conductivity. Therefore, WES/ERDC selected a representative depth of -160 ft for the base of the zone in the vicinity of well G-2345 and for those Bechtel wells from which other layer picks were made (Table 2). Bechtel wells generally did not penetrate the entire thickness of the Tamiami permeable zone. WES/ERDC also added two additional data points located approximately halfway between well G-2345 and the wells immediately north and south of it to better represent the extent of the deep zone (last two points in Table 2) for contouring purposes. The resulting higher transmissivities (aquifer thickness times hydraulic conductivity) calculated for the area by the numerical model should more accurately reflect flow in the model area. Peele Dixie north field production well PW-6, located near USGS well G-2345, draws water from a 7-ft open hole at 182- to 189-ft depth (approximately -175- to -182-ft el). WES/ERDC assigned an elevation of -182 ft to the base of layer 4, at the site of PW-6 to accommodate the deep zone. The bottom of WES/ERDC model layer 5 is the base of the surficial aquifer system, which was defined by Fish (1988) as that material having hydraulic conductivities of less than 0.1 ft/day, the yellow zone of Fish’s hydrogeological Chapter 4 WES/ERDC Hydrogeologic Conceptual Model

21

profiles. On that basis, WES/ERDC selected the bottom of layer 5 from the Fish profiles in the area of interest. In general, the yellow zone is commonly near the top of the Hawthorn formation. In one case, that of the Markham Park well (Figure 17), the elevation of the base of SFWMD’s model layer 5 was selected from their Table A-1. Maps showing the geometry and distribution of the top of layer 3, the base of layers 4, the thickness of layers 3 and 4 (high-permeability zone), the base of layer 5, and the thickness of layer 5, are attached as Figures 18 through 22, respectively.

Selection of Hydraulic Conductivities for WES/ERDC Model WES/ERDC estimated the distribution of hydraulic conductivity in the highly permeable zone (layers 3 and 4 of the WES/ERDC model) using published data from aquifer tests in eastern Broward County. Data for layers 2 and 5 were limited, but available test results were considered in deriving a hydraulic conductivity value for those layers. Figure 23 shows the locations of the test wells with respect to the model area. Table 3 and Table 4 summarized the test data. WES/ ERDC reviewed the original source of the data where possible. Data sources included Fish (1988), CDM (1980a,b), JMM (1986), Tarver (1964), and Sherwood (1959). Fish provided four tables of aquifer properties. Table 5 (Fish 1988) presents data from tests conducted in the USGS wells. The table identifies the interval tested, the type of test conducted, the geologic formation involved, an estimate of the aquifer interval affected by the test, the calculated transmissivity, and the derived hydraulic conductivity. WES/ERDC used the data from four of the tests shown in this table for its model layers 3 and 4 (wells G-2317J, -2319D, -2321J, and -2322F, and two of the tests for layer 5 (wells 2312K and 2342B). The four tests applied to model layers 3 and 4 were either specific capacity or step drawdown tests. Fish stated that for these tests, “the length of open hole or screen intake of the well is a reasonable estimate of the thickness of the aquifer that contributes most of the flow to the well, if the aquifer has ... greater horizontal [hydraulic conductivity, k] than vertical [k] ... and if the open interval is relatively long.” Table 6 (Fish 1988) presents aquifer data from selected tests conducted in wells by others, with correspondingly less information concerning the nature of the tests and the test intervals. WES/ERDC used these values for transmissivities for the Pompano Beach, Prospect Field Fiveash, and Prospect Executive Airport sites, after consulting the original sources (Tarver 1964, Sherwood 1959, and CDM 1980b, respectively). Test intervals for the three sites were within WES/ERDC layers 3 and 4. Table 7 (Fish 1988) is part of an extensive list of well data for large supply wells in Broward County, for which specific capacities were available. Fish 22



23

692,129 671,408 707,798 739,564 738,000 747,230 755,456 770,367 789,057 773,274 765,886

G-2319D

G-2321J

G-2322F

Treetops Park

Pembroke Pines

N Lauderdale

Tradewinds Park

Pompano Beach

Prospect exec. airport

Prospect 5-ash

760,304

Dania C

PW-03

3

2

648,420

623,830

653,053

633,563

677,467

676,202

699,529

703,445

685,178

611,424

631,600

644,396

652,812

658,809

590,142

Northing, ft, NAD 27

Reported T, sq ft/day

Derived k, ft/day

3

110-125

100-110

74-118

125-140

82 to 99

110 to 130

approx 120 to 140

Not given

152,000

95,000

470,000

110,000

260,000

330,000

200,000

361,000

141,600

512,000

approx 105-130

103-115

895,000

3

600,000

870,000

430,000

710,000

103-128

69-117

60-88

31-49

40-61

1,086

863

5,465

1,028

3,376

4,286

2,667

2,694

1,221

4,452

8,774

8,823

18,913

22,631

16,136

Sources for WES Model Layers 3 and 4

Test Interval, depth, ft

Sources: Fish 1988; JMM 1988; CDM 1980b. Letter at end of well number designates the test zone. Production interval for Pembroke Pines Treatment Plant No. 2, Well No. 5, from Fish 1988, Table 2.

778,078

Plantation 11

1

751,935 752,458

Davie 4

G-2317J

2

Well

Easting, ft, NAD 27

CDM

Fish

Fish

Fish

CDM, in Fish

Sherwood, in Fish

Tarver, in Fish

JMM test

JMM test

JMM test

JMM test

Fish test

Fish test

Fish test

Fish test

1

Source of T

140

110

86

107

77

77

75

134

116

115

102

68

46

19

44

Thickness of Aquifer Used to Derive k , ft

Table 3 Sources and Transmissivities (T) and Hydraulic Conductivities (k) for WES/ERDC Model Layers

(Continued)

CDM

WES/ERDC

WES/ERDC

WES/ERDC

WES/ERDC

WES/ERDC

WES/ERDC

JMM

JMM

JMM

JMM

WES/ERDC

WES/ERDC

Fish

WES/ERDC

Source of Thickness Value

24


Easting, ft, NAD 27

758,844

757,909

758,158

758,492

760,200

760,027

760,393

759,282

759,235

758,855

757,573

676,930

760,435

747,494

747,494

Well

PW-06

PW-07

PW-08

PW-09

PW-15

PW-16

PW-19

PW-20

PW-21

PW-23

PW-25

G-2312K

G-2342B

G-2327A

G-2327B

Table 3 (Concluded)

597,190

597,190

690,055

689,524

647,675

641,979

643,415

644,348

641,059

642,438

643,131

649,082

648,696

646,661

647,248

Northing, ft, NAD 27

Reported T, sq ft/day

Derived k, ft/day

154,000

80,000

109,000

134,000

262,000

246,000

398,000

209,000

140,000

68,000

171,000

1,100

571

778

957

1,871

1,757

2,843

1,493

1,000

486

1,221

1,500

75 (Fish)

39.5-42.2

NA

27 (Fish)

Sources for WES/ERDC Model Layer 2 23.5-26.5 NA 44 (Fish)

170-190

Sources for WES/ERDC Model Layer 5 40-62 9,000 300 (Fish)

89-115

87-114

87-114

89-114

110-125

110-125

110-125

110-125

89-104

110-125

181-189

Sources for WES/ERDC Model Layers 3 and 4

Test Interval, depth, ft

Fish slug test in Pamlico Fish slug test in Pamlico

Fish test

Fish test, partial penetr

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

1

Source of T

3

3 ft

20

30 ?

140

140

140

140

140

140

140

140

140

140

140

Thickness of Aquifer Used to Derive k , ft

Fish

Fish

Fish

Fish

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

CDM

Source of Thickness Value

Table 4 Additional Data on Sources of Transmissivities (T) for Layers 3 and 4 Source of T Fish (1988) test

Well Number G-2317J

Fish (1988) test

G-2319D

Fish (1988) test

G-2321J

Fish (1988) test

G-2322F

Fish (1988) estimate

Davie No. 4 municipal well

Fish (1988) estimate Fish (1988) estimate

Plantation No. 11 municipal well Dania C municipal well

JMM (1986) test

Treetops Park test well

JMM (1986) test

Pembroke Pines test well

JMM (1986) test

North Lauderdale test well

JMM (1986) test

Tradewinds Park test well

Tarver, USGS (1964) test

Pompano Beach municipal well Prospect Executive Airport municipal wells

Sherwood, USGS (1959) test CDM (1980) test CDM (1980) tests

Prospect well field (Fiveash) municipal wells Dixie well field municipal wells (several)


Test Type and Analytical Method Step drawdown, Jacob and Bierschenk Step drawdown, Jacob and Bierschenk Step drawdown, Jacob and Bierschenk Step drawdown, Jacob and Bierschenk T estimate from specific capacity T estimate from specific capacity T estimate from specific capacity Drawdown/recovery, Boulton delayed yield Drawdown/recovery, Boulton delayed yield Drawdown/recovery, Boulton delayed yield Drawdown/recovery, Boulton delayed yield Drawdown, Theis and Cooper/Jacob Drawdown, multiple pumping wells; Cooper/Hantush leakyaquifer Drawdown/recovery, Neuman anisotropic, delayed yield T estimated from specific capacity

Comments Single-well test. T is estimated from specific capacity (Same as above) (Same as above) (Same as above) T = 270 Q/s T = 270 Q/s T = 270 Q/s Multiple-well test. Multiple-well test. Multiple-well test. Multiple-well test. Multiple-well test. Multiple pumping and observation wells. Multiple-well test. Corrected for partial penetration Analysis of Walton (1970), corrected for partial penetration. 12 wells analyzed.

25

Table 5 Aquifer Hydraulic Properties Determined from Pumping Tests (after Fish 1988)

26


Table 6 Aquifer Hydraulic Properties Determined in Other Tests (after Fish 1988)


27

Table 7 Data for Large Supply Wells in Broward County (after Fish 1988)

(Continued)

28


Table 7 (Concluded)


29

estimated transmissivities for the production zones using the relationship between transmissivity (T) and specific capacity (Q/s) derived for Broward County from the Theis nonequilibrium equation. The Theis equation modified for determining T from specific capacity, is T = (W (u )/4π )Q / s

(1)

where W(u) = Theis’ well function of u Q = discharge of a pumping well s = drawdown at Q Fish (1988) determined that for local Broward County hydrogeology, the representative value of W(u)/4B is about 270. Therefore, for the Broward County area, T = 270 Q/ s, T in ft 2/day, Q / s in gallons per minute ( gpm) / ft drawdown

(2)

WES/ERDC used the data for three of the wells in Table 7 (Dania No. 8, Davie No. 4, and Plantation No. 11) for its model layers 3 and 4. Fish (1988) cautioned that Virtually all the supply wells [evaluated in Broward County] are open to only part, often less than 25 percent, of the highly... permeable materials in the Biscayne aquifer. Therefore, the transmissivity of the aquifer should be greater than the estimated value. He further stated that methods commonly used to correct for partial penetration were applied to three sites in Broward County but produced results that were Many times greater than values estimated directly from the specific capacity... and are considered unreasonably high... Correction methods are often hard to apply in Broward County because of the difficulty in determining the thickness of the highly permeable zone of the aquifer... and the methods assume homogeneous aquifer materials, whereas in detail the very highly permeable zone is heterogeneous,...ranging from sand to limestone with large cavities. A representative transmissivity at a given site is considered to be in the range of one to perhaps three times the value calculated from the highest specific capacity. Fish is explaining that, given the heterogeneity and great thickness of the aquifer, it is difficult to precisely quantify the transmissivity from tests in wells that only partially penetrate the aquifer. He therefore reports in Table 7 an uncorrected estimate of T from specific capacities of pumping wells. Table 8, also from Fish (1988) provided estimates of hydraulic conductivity from slug tests in short test intervals in the USGS G-series of wells. WES/ERDC 30


Table 8 Hydraulic Conductivities Determined From Slug Tests (after Fish 1988) USGS Well Number G-2327A

Latitude 255820

Longitude 0801448

G-2327B

255820

G-2329A

SN 01

Approximate Interval Tested, ft-bls 23.5-26.5

Geologic Formation Qp

0801448

02

39.5-42.2

Qp

261014

0805122

02

17-20

Qf

Fine sand with lime mud

G-2329B

261014

0805122

03

36-40

Tt

Mixed lime mud, shell fragments, quartz sand

G-2338H

260532

0805036

09

68.2-2.70

Tt

Very fine sand, silt and clay

Lithology Fine to medium sand, minor lime mud, moderately sorted Fine sand, minor lime mud, moderately sorted

Hydraulic Conductivit y ft/day 44 27 16 .16 0.061

Qp – Pamlico Sand, Qf – Ft. Thompson, Tt- Tamiami, bls = below land surface

used the data from two of the slug tests for estimates of hydraulic conductivity in model layer 2, the Pamlico sand, and Miami oolite (Tables 3 and 4). JMM (1986) evaluated several sites in eastern Broward County for future water supplies. They conducted aquifer tests in six wells and provided calculated transmissivities and estimated hydraulic conductivities. WES/ERDC used the data from four of the tests as input to its model layers 3 and 4 (Tables 3 and 4). The test wells were Pembroke Pines, Tree Tops Park, North Lauderdale, and Tradewinds Park (Figure 23 and Tables 3 and 4). Figure 24 is from the JMM (1986) Report providing their calculated and derived aquifer properties. Data for the Florida State Hospital test site, southern Broward County, were not used because the test had to be performed in a less permeable part of the aquifer after the target zone caved. The Winston Park site is out of the area of evaluation. The Tree Tops Park test was conducted in the open zone of a 16-in.-diam well at approximately -98- to -123-ft el, in the Tamiami limestone. The test intervals for the other wells were not provided by JMM (1986), but Fish’s (1988) Table 2 provided the well production intervals for the Pembroke and North Lauderdale wells. JMM (1986) estimated the hydraulic conductivities from the calculated transmissivities by dividing T by aquifer thicknesses ranging from 102 to 132 ft. CDM (1980a) conducted tests in the Biscayne aquifer of the PD well field. CDM performed specific capacity recovery tests in 12 production wells in the field and estimated transmissivity using the following relationship of Walton (1970): Q/ s =

T 264 log (Tt / 2693 rw2 S ) − 65.5)


(CDM 1980a)

(3)

31

where T = transmissivity in gpd/ft S = storage coefficient

rw = nominal well radius, ft t = time after pumping stopped, minutes Q/s = specific capacity, gpm/ft Analytical results for the 12 tested wells are presented in Table 9 and well specifics such as test intervals are given in Table 10. CDM (1980a) also adjusted the estimated transmissivities for partial penetration using a relationship between the specific capacity of a partially penetrating well to that of a fully penetrating well and an assumed aquifer thickness of 140 ft (CDM 1980a) (see Fish’s (1988) statement concerning correction for partial penetration discussed previously). Fish also estimated transmissivities for the PD wells (Table 7). One value of T reported by CDM (1980a), that of 5.08 × 106 gpd/ft for PW-07, was much too high for the reported specific capacity of 284 gpm/ft (Table 9). WES/ERDC could not resolve the discrepancy because the original test results were not available. The estimated T’s of Fish are lower than those of CDM (1980a), probably because of the difference in the relationships used to derive T and the fact that Fish’s reported values of T were apparently not corrected for partial penetration. Fish stated that representative transmissivities should be one to three times his estimated value. WES/ERDC adopted the transmissivity values calculated by CDM (1980a) for the 12 Peele Dixie production wells tested. Transmissivities ranged from 80,000 ft2/ day in well PW-23 to 398,000 ft2/day in well PW-15 (Tables 3 and 4). Six wells were open to the aquifer at 110- to 125-ft depths (in layer 4), five at approximately 89- to 115-ft depths (in layer 3), and one at 181- to 189-ft depth (in layer 4). All of the Peele Dixie wells are in the Biscayne aquifer, layers 3 and 4 of the groundwater flow model. Table 9 Aquifer Test Results in Peele Dixie Well Field (CDM 1980a) Production Well Number

Recovery Specific Capacity, gpm/ft

Adjusted Specific Capacity, gpm/ft

3

159.6

636

1.14 × 10

6

6

269.3

718

1.28 × 10

6

7

105.7

284

5.08 × 10

6

8

151.6

586

1.05 × 10

6

9

322.8

872

1.56 × 10

6

15

651.0

1,667

2.98 × 10

6

16

409.6

1,031

1.84 × 10

6

19

433.7

1,099

1.96 × 10

6

20

306.2

559

1.00 × 10

6

21

155.5

458

8.18 × 10

5

23

128.9

336

6.00 × 10

5

25

185.7

646

1.15 × 10

6

1.32 × 10

6

Average

32

Estimated Transmissivity, gpd/ft


Table 10 Peele Dixie Production Well Construction Details (after CDM 1980a) Inside Diameter in.

Drilled, year

Well Capacity gpm

Well No.

Depth, ft

Cased, ft

Open Hole ft

2

125

110

15

12

1926

600

3

125

110

15

12

1926

600

4

125

110

15

12

1926

600

5

99

87

12

12

1971

600

6

189

181

7

12

1971

600

7

125

110

15

12

1940

600

8

104

89

15

12

1971

600

9

125

110

15

12

1945

600

10

148

82

66

12

1945

600

11

126

110

16

10

1926

600

12

126

110

16

12

1926

600

13

125

110

15

12

1947

400

14

125

110

15

12

1947

400

15

125

110

15

12

1947

400

16

125

110

15

12

1947

400

17

125

110

15

12

1947

400

18

125

110

15

12

1947

400

19

125

110

15

12

1947

400

20

114

89

25

10

1952

500

21

114

87

27

10

1952

500

22

115

89

26

10

1952

500

23

114

87

27

10

1952

500

24

115

89

26

10

1952

500

25

115

89

26

10

1952

500

26

114

89

25

10

1952

500

WES/ERDC constructed maps of the contoured T and k data of Tables 3 and 4, model layers 3 and 4 (the highly permeable Biscayne aquifer). The numerical flow model package extracts a subset of the grid file produced in the contouring process when the grid file is imported into the model. The subset grid is bounded by the model’s geographical limits. The contour maps of T and k for the gridded area are presented in Figures 25 through 28. The flow model imports only the subset outlined by the model limits, shown in halftone in Figures 25 through 28. Within the model area, hydraulic data from CDM’s (1980a) aquifer tests in the Peele Dixie production wells (PW series) were segregated on the basis of shallow and deep wells, because tests in the five shallow wells produced hydraulic conductivities only about 40 percent as high, on average, as tests in the seven deep wells (Tables 3 and 4). The difference in hydraulic conductivity indicated that the shallow zone (model layer 3, generally 89- to 115-ft depth) is less permeable than the deep zone (model layer 4, generally 110- to 125-ft depth).


33

The flow model can accommodate local (cell by cell) variations in hydraulic properties to take advantage of the information provided by all of the tests. However, when the above data were contoured for layer 3, very low conductivities (150 ft/day) were calculated, because of a lack of test data in the East. Hence, WES/ERDC elected to truncate the conductivity field in layer 3 to create a more representative field according to the available data and knowledge of the site. Therefore, the conductivity field of layer 3 was truncated to a constant conductivity of 800 ft/day (Figure 28) beginning at the 800 ft/day dashed contour line to the eastern boundary of the model. The 800 ft/day value was considered to be a rough average of the lowest three conductivity values calculated in the shallow zone of the Biscayne (Table 3). The conductivity field of layer 4 was not modified. At the time of this study, there were not enough tests of the materials in layers 2 and 5 to construct an areal distribution (contours) of hydraulic conductivities in eastern Broward County or the immediate study area. WES/ERDC selected reasonable values of k from Tables 1, 3, and 4, of 50 ft/day for layer 2, which includes the Pamlico sand and Miami oolite, and 75 ft/day for layer 5, which includes the materials below the highly permeable zone to the base of the aquifer, mostly the middle to lower Tamiami formation. The Miami oolite can readily be mapped from numerous borings penetrating it in the immediate well field and area of investigation. However, limited test data for the unit suggests that it is not hydraulically different from the Pamlico sand and other lower permeability sediments below it. Accordingly, WES/ERDC could not justify creating a separate hydraulic conductivity layer for the Miami oolite within the model.

34


5

Data Collection for Numerical Model Input

Pumping Data from Municipalities within the Model Domain Pumping data were obtained from the following municipalities (water utilities); City of Fort Lauderdale, Peele Dixie (25 wells), City of Ferncrest (2 wells), City of Sunrise (Park City, 7 wells), City of Davie (System I, 4 wells), and City of Plantation (Plantation East, 10 wells). Monthly Operating Reports (MOR) were obtained from the smaller utilities (Ferncrest, Sunrise, Davie, and Plantation) which showed a daily total flow, a monthly total flow, and daily hours of operation. Also, rough estimates of pumping rates were given for the years that monthly operating reports were not provided, by Davie and Sunrise utilities. The utilities are required by the SFWMD to submit MORs each month. Peele Dixie pumping data are described in detail later in this chapter. The MORs did not provide individual flow rates per operating well but recorded combined flow being pumped to the water treatment plant from all the wells. Because WES/ERDC could not obtain data for individual wells, a single composite well, with an average location and average depth, was entered to simulate each utility, except for the Peele Dixie wells. Specific information describing individual well locations (Florida State Planar Coordinates), depths, and pump capacities was obtained from the utilities and the SFWMD (Restrepo, Bevier, and Butler 1992) report. These data are presented in Appendix A. Pumprates of small utilities are presented in Appendix B. Utility pump locations are illustrated by Figure 29. Smaller utilities pumping data WES/ERDC requested the MORs for the years 1978 to 1997 from each of the small utilities, but unfortunately, some data were not provided. Although the pumping data received were voluminous, months and years of data were missing. For the case of months missing, prior and previous months were averaged to estimate missing months. In addition, where years of data were missing, previous or post years were copied directly to the missing year. In this way, seasonal fluctuations in pumping rates were maintained. The estimates made by

Chapter 5 Data Collection for Numerical Model Input

35

WES/ERDC to pumping rates are completely documented in Appendix B and briefly discussed in the next two paragraphs. Ferncrest is the closest utility to the FPR Site, less than 1/4 mile away. The SFWMD listed this utility as having four production wells. WES/ERDC confirmed that there have been only two production wells at Ferncrest at least since 1984.1 The data collected for this plant were 82 percent complete. Only 3 years, 1978, 1979, and 1983, were missing, along with 6 months, spaced intermittently, between the years 1978 to 1996. Pumping data for the next closest utility (Davie), approximately 1/2 mile west of FPR , were 43 percent complete with 11 years missing: 1979 through 1983 and 1985 through 1990. Pumping data obtained from Sunrise (approximately 3.5 miles to the northwest of FPR) were 36 percent complete with 12 years missing: 1978 through 1983 and 1985 through 1991. The data for Plantation (approximately 3 miles northwest of FPR) were 100 percent complete. WES/ERDC considered estimation of the missing data valid, because either the monthly flow rate from the utility was very small or the utility was significantly removed from the area of interest. For example, Davie is a very small water plant with the average daily flow for the years 1978 to 1990 of 1.75 million gallons.2 WES/ERDC found that small changes in pumping at Davie did not significantly affect the flow at the FPR site and, therefore, considered it reasonable to estimate the missing data. Further, it was considered reasonable to estimate data for the Sunrise Plant, because it is significantly removed from the FPR site and small pumping changes there did not affect flow directions at the FPR site. The estimated pumping rates by WES/ERDC were checked against rough estimates provided by the plant operators, to assure relative accuracy. Data collected from the PD Water Plant is described in detail in the next paragraphs. Peele Dixie pumping data Bechtel initially requested pumping data for the PD wells from Mr. Maurice Toban, Project Engineer, City of Fort Lauderdale. Bechtel engineers did not manipulate the data in any way.3 These data were transferred from Bechtel to WES/ERDC in the original form, which was handwritten by the operators at the Peele Dixie Water Treatment Plant. The original data format was as follows in Table 11: The data consisted of the pumping schedule for each Wednesday for every week between January 1978 through June 1997. The pumping schedule included the date, which wells operated that day, the total number of wells operating, and 1

Personal Communication, 1997, Robert and Al Salerno, Superintendents at Ferncrest Utilities, Ferncrest, FL. 2 Personal Communication, 1997, Bruce Taylor, Superintendent of Operations, Davie Utilities, Davies, FL. 3 Personal Communication, 1997, Jeff Cange, Bechtel Environmental Inc. Personnel, Oakridge, TN.

36


Table 11 Example of Peele Dixie Pumping Data Date

Wells Operating

Jan 4, 1978

3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 24, 25, 26

Total Flow million gallons (mg)

Total Number of Wells

10.85 mg

13

the total flow in millions of gallons. Because of the intense labor required to retrieve pump schedules for every day during the period of interest, the Peele Dixie operators, only retrieved records for each Wednesday. The operators stated that Wednesdays were representative of an average day for its respective week, because weekends were generally lower than average usage days and Mondays were generally much higher than average usage days. Bechtel also obtained from the City of Fort Lauderdale a copy of the daily operating schedule for the year 1995. These data were also handwritten in a similar format as stated above. WES/ERDC used these specific data for the 1995 model calibration simulation. In addition, WES/ERDC obtained a small amount of daily data from the Plant Operator, Mr. Craig Canning. These data consisted of daily hours of operation for each well for the months of April, May, and October 1984 and April and May 1989. WES/ERDC also used these specific data for the 1984 and 1989 calibration simulations. See Appendix C for specific daily data. Data management and estimation of monthly flow rates for each PD well After close examination of the data and the water permit issued by the SFWMD, a strategy for calculating the monthly average flow rates for each PD well was developed. It was stated in the water permit, that the northern-most wells will be used to meet base flows. Increases in demand will be met by activating the wells in a southerly direction. Therefore, WES/ERDC distributed the total flow (TQ) among the north well field first, up to 100 percent of its capacity (of operating wells), and any remaining flow was distributed among the south wells, according to their capacities (capacities of wells are presented in Table 10). A flow chart defining the procedures for assigning pumprates to the individual PD Wells is shown in Figure 30. The procedure is described in detail in the following paragraphs. The general distribution of the total flow defined by the flow chart worked well, except for a few special cases where (a) the south wells were the only wells on or, (b) where TQ was less than 100 percent capacity of the north wells (which were operating) and south wells were also pumping. For these very few cases of the first type, where the south wells were the only wells on, the TQ was distributed among them according to capacity. In addition, for the few exceptions of the second type, 25 percent of the TQ was distributed among the south wells, or 50 percent of the south well’s capacity, which ever was less, and the remainder was distributed among the north. The OR statement had to be used, because in


37

some cases where only two south wells were operating, 25 percent of TQ would have exceeded their capacities. The 25-percent factor of TQ assigned to the south wells for the second case was derived from the specific daily data (Appendix C) obtained for the year 1984 as described above. WES/ERDC calculated that on average, 28 to 38 percent of TQ during the months of April, May, and October 1984 came from the south wells. Therefore, WES/ERDC chose a conservative number of 25 percent to assign to the south wells for these few cases. The last pumping scenario defined by the data is where TQ is greater than the capacity of all wells (north and south) operating for the day. In this case, which was ubiquitous, the total flow was distributed among all operating wells equally according to their capacity. This scenario resulted in these wells pumping over their capacities. Appendix D lists the weekly pumping schedule and the pump rates calculated per well per year of simulation. Appendix E contains the monthly average pump rates calculated per well from the weekly rates. The calculated pump rates often exceeded the capacity of the pumps. After consideration of these calculations and discussions with PD employees, WES/ERDC concluded that there were two reasons for this, (a) these pumps do not run at a fixed rate in the field and can actually pump over or under their capacities, and (b) the number of wells recorded as operating was not always accurate. The total flow rate is a separate number and is recorded on monthly operating reports, which are submitted to the SFWMD. The efficiency of each pump depends on its current maintenance, the height of the water table, and the pressure in the main waterline into the water plant. For these reasons, it is common for a pump that is rated at 600 gpm, to pump at 550 gpm on one day and 650 gpm on the next.1 Therefore, calculated pumprates from 10 to 15 percent over capacity are considered valid estimates of the actual pumprates. Calculated pump rates which were over 15-percent capacity (approximately 20 percent of the data) were probably the result of the plant operators’ forgetting to document every operating well, or possibly because a group of wells were only operating for a very short period of the day, they were simply left off the provided data sheets. Another possible source of misrepresentation in the data is simply an error in the voluminous handwritten data, which was originally provided to Bechtel from the Peele Dixie Water Plant. In conclusion, in every case that the total flow did not exceed well field capacities, the pumping rates have been biased toward the distribution of total flow from the north well field. Meaning that total flow was first distributed to the north wells at 100 percent of their operating capacities, even though they may have been pumping under capacity or for less than a 24-hr period. In addition to the pumping distribution, the total flow rate is the most important factor governing flow directions in the model, and these values were not estimated or adjusted from the original data.

1

Personal Communication, 1998, Tom Turrell, Peele Dixie Water Plant personnel, Ft. Lauderdale, FL.

38


Other Groundwater Users in the Model Domain Small groundwater users that were deemed important to the study were given a constant flow rate since detailed data were not accessible for these pumps. These included the Fort Lauderdale Country Club (FLCC), the Davie Concrete Company, and the old Broadview Park Water Company. The FLCC only recently began reporting its usage to the SFWMD as part of the permit. WES/ERDC obtained 15 months of data from FLCC. The calculated average 20 million gal per month (mgm) was used for a constant flow rate for the duration of the 19-year simulation. Davie Concrete pumping rate was estimated from conversations with company employees. They estimated how much water was needed per truck of concrete and estimated the daily number of trucks. The estimate of daily use was approximately 100,000 gpd. The Broadview Park Water Company was a very small municipal water plant and operations ceased on May 19, 1991.1 For Broadview Park, WES/ERDC used the annual groundwater allocation value of 270 million gal per year (mgy), (Restrepo, Bevier, and Butler 1992). Seven other water users were listed as inside the WES/ERDC model domain by SFWMD. Their water use allocation recorded by Restrepo, Bevier, and Butler (1992) was the combined flow from groundwater and surface water pumps. Therefore, the groundwater allocations were not easily estimated. In general, the groundwater pump capacities were very small and the locations of these users were not critical to the model results. Hence, these users were not included in the numerical calculations. See Appendix A for a list of water users in WES/ERDC Domain.

Stage Data Head and tailwater stages are recorded daily by the SFWMD at the three Project Structures S-33, G-54, and S-13, and the WCA2B (described earlier). These records are maintained by the Hydrologic Data Reporting Unit from within the SFWMD, West Palm Beach, Florida. These data are managed within the SFWMD’s DBHYDRO Database. The DBHYDRO database is described in the document, “Hydrometeorologic Monitoring Network Metadata Report,” by Stuart Van Horn (1996). The headwater is a mean daily reading while the tailwater is the average of the highest tide and lowest tide. This database is available to the public. SFWMD project canals Stage data at each salinity control structure were available from DBHYDRO for almost every day during the period of January 1978 to December 1996, with a few exceptions. For some of these exceptions (S-33 headwater for the months January 1985 to September 1986) the data were obtained from the USGS annual hydrologic data report for South Florida (USGS 1985 and 1986). 1

Personal Communication, 1997, Mr. Mike Swab, City of Broadview personnel, Broadview, FL.


39

Where data could not be found in the SFWMD or USGS databases, the missing data were estimated by taking averages of adjacent months or copying existing data from one structure to another. For example, during the periods: January 1978 through September 1982, and December 1982 through September 1984, the data from S-13_T (tailwater) were copied to structure S-33_T (tailwater). It was determined through plotting of existing data, that tailwater stages at these two structures were very similar (both are tidally influenced). This was the only period where data were copied. Individual sources of stage data are defined below. Daily hydrographs for the year 1984 are presented in Appendix F. Daily stage readings were averaged per month as input to the WES/ERDC model (Appendix F). The sources of data for each stage are represented in DBHYDRO by the Database Key (DBKEY) (see column 2 in Table 12). There are numerous sources for each stage because there are several instrument recorders at the same gauging station. These instruments are continuously being updated (or replaced) and every instrument has a unique DBKEY in DBHYDRO. This makes the SFWMD database somewhat complicated, when examining records for long periods of time. However, all sources for this study are explicitly documented in Table 12. Water conservation data Stage information was needed for the WCA2B, as input to the general head boundary for layers 2 through 5 for the north and west boundaries. WCA2B is described in the section on physiography of the study area. Daily stage information was only available in DBHYDRO for the years 1985 to 1996, therefore WES/ERDC had to search other sources for the years 1978 to 1986. WES/ERDC learned through conversation with Jeff Giddings of the SFWMD, that an instrument (gauge 2B-21) was read by the Water Resource Planning Division (WRPD, SFWMD, West Palm Beach, Florida) during the time period 1983 to 1995. These readings were collected by the WRPD for the purpose of calibrating the revised Broward County Flow Model (Restrepo, Bevier, and Butler 1992). The WRPD readings were not daily, but only one reading per month. For the remaining missing years 1978 through 1982, WES/ERDC used simulated data from the revised SFWMD model (1992). The daily stage data from gage WCA_2BY was averaged per month and combined with the monthly and simulated readings from gauge 2B_21. The complete WCA 2B input file is provided in Appendix G, where each data source has been identified.

Well Observation Data The USGS Water Resource Division (WRD), Miami, FL, has large network of observation wells in Southeast Florida which are monitored for trends in water table flow and water quality. There are four databases, Relational Database (RDB), Groundwater System Inventory (GWSI), Automated Data Processing 40


Table 12 Source of Stage Data from SFWMD and USGS Stage Name

DBKEY

Start Date

End Date

Description

G-54_H

00454

1/1/78

4/30/92

'69-'92 Mean Daily

15114

5/1/92

5/31/94

'91-'95 Mean Daily

99999

6/1/94

10/31/94

Estimated

15114

11/1/94

12/31/94

'91-'95 Mean Daily

15966

1/1/95

6/30/97

'93-'97 Mean Daily

00462-00463

1/1/78

2/28/82

'70-'92 H Tide - L Tide

00460

3/1/82

7/31/82

'69-'92 Mean Daily

00462-00463

8/1/82

9/30/83


00460

10/1/83

4/30/92

'69-'92 Mean Daily

15116

5/1/92

12/31/92

'91-'95 Mean Daily

15967

1/1/93

6/30/97

'92-'97 Mean Daily

00474

1/1/78

12/31/84

'68-'96 Mean Daily

99999

1/1/85

9/30/85

Estimated

00474

10/1/85

2/28/95

'68-'96 Mean Daily

12999

2/1/95

2/28/95

'89-'97 Mean Daily

12999

3/1/96

5/31/97

'89-'97 Mean Daily

00481-00482

1/1/78

2/28/86


03830

3/1/86

12/31/88

'85-'89 Mean Daily

00481-00482

1/1/89

8/31/89


13000

9/1/89

5/31/97

'89-'97 Mean Daily

00422

1/1/78

12/31/84

68-'95 Mean Daily

00000

1/1/85

9/30/86

USGS Mean Monthly

00422

10/1/86

4/30/95

68-'95 Mean Daily

15678

5/1/95

7/31/97

'91-'97 Mean Daily

98182

1/1/78

9/30/82

Copied from S13_T

6476-6552

10/1/82

11/30/82

82-'92 H Tide - L Tide

98182

12/1/82

9/30/84

Copied from S13_T

6476-6552

10/1/84

12/31/84

82-'92 H Tide - L Tide

00000

1/1/85

9/30/86

USGS Mean Monthly

07085

10/1/86

8/31/92

86-'92 Mean Daily

15679

9/1/92

7/31/97

'91-'97 Mean Daily

G-54_T

S-13_H

S-13_T

S-33_H

S-33_T

Database Key Legend 00000 USGS database. 99999 WES/ERDC estimated. 98182 WES/ERDC copied. 6476-6552 SFWMD DBHYDRO Low tide and High tide averaged. 00481-00482 SFWMD DBHYDRO Low tide and High tide averaged. All others SFWMD DBHDRO database keys.


41

System (ADAPS), Quality of Water Database (QWDATA), that are maintained by the WRD. The RDB lists all active wells in the USGS program. The GWSI lists all wells, active or inactive, that were ever mentioned in a USGS report. ADAPS stores and facilitates the processing of all data from continuous recorders. QWDATA stores all intermittent water quality and water level data. 1 WES/ERDC retrieved information from each of these sources. The data included: Water well readings and well construction information. There are a total of 63 USGS wells in the WES/ERDC model domain (Figure 7), which were read during the period 1978 to 1996. Two of these (G-1221 and S-329) were monitored daily for the majority of the modeling period. Also, a series of wells (G-2493, G2492, G-2491, G-2490, C-2489, G-2488, G-2487) in the Pond Apple Swamp area were monitored daily for the year 1989. The Pond Apple Swamp is present at the convergence of the South New River and North New River Canals. The remaining wells were read intermittently, sometimes more than once a month, monthly or biannually. The USGS used the biannual readings to produce water table maps for many years prior to and through 1986. WES/ERDC obtained several of these maps (1978 to 1986) to evaluate groundwater flow trends. In addition to the biannual maps, average water table maps for the wet and dry seasons during the years 1974 to 1982 (Figures 8 and 9) were also compiled by the USGS. The construction information and state planar coordinates for each USGS well are presented in Appendix H. Included in this appendix are the well information data for monitoring wells placed by Bechtel (EPA series) and the City of Fort Lauderdale (DW series). The Bechtel wells were constructed as a part of the Remedial Investigations of the PD well field and the FPR site. The DW wells were placed during the contaminant assessment study conducted by JMM (1992). Coordinates for the USGS wells were provided in geodetic coordinates (North Atlantic Datum (NAD) 1927) and were translated to Florida East State Planar Coordinates. Bechtel provided the coordinates and well construction data for the DW wells in addition to the information on the EPA wells installed by Bechtel. In some cases, WES/ERDC estimated the top of ground to determine the bottom elevation of some wells. Location of USGS wells used for calibration of the numerical model are shown in Figure 7. Wells used for each calibration period are listed in Appendix H.

Shallow Aquifer Hydraulic Measurements Numerous shallow aquifer hydraulic tests have been conducted in the shallow subsurface within the study area by owners of leaky underground storage tanks, mainly gasoline stations. Broward County Department of Natural Resource Protection requires aquifer tests as part of petroleum recovery remedial action plans. Tests were conducted at five locations by five different contractors. All of the tests, except one (7-Eleven Site, pump test) were slug tests. Each calculation 1

42

Personal Memorandum, 1997, Scott Prinos, USGS, Miami, FL. Chapter 5 Data Collection for Numerical Model Input

was made using the Bouwer and Rice equation for partially penetrating wells, except for the pump test which used the Cooper and Jacob straight line method. The derived hydraulic conductivities are presented in Table 13. The locations of these sites are illustrated by Figure 31. WES/ERDC acquired these data late in the study. Therefore, these data were used as a guideline for calibration, rather than a building block for the hydrogeologic conceptual model. However, these data values were within the range of Ks used in the conceptual model. The shallow hydrogeologic data may be a good source for additional data in future studies, especially of the pamlico sand. Table 13 Shallow Slug Test Results 1.

Test Interval, depth/ft

Derived K, ft/day

Test

Environmental Contractor

5.0-15.0

230

Slug Test

Law Envr. Inc. 1992

5.0-13

10

Slug Test

U.S. Envr Group 1992

10.0-18.0

125

Slug Test

GWL 1992

4 Wells (1992)

5.0-15.0

38

Slug Test

Applied Earth Science

3 Wells (1988)

5.0-15.0

56

Slug Test

Applied Earth Science

3 Wells (1991)

10.0-18.0

52

Slug Test

GWL 1991

2 Wells (1989)

30.0-35.0

138

Slug Test

Water Resource Inc.

5 Wells (1989)

10.0-25.0

464

Pump Test

Water Resource Inc.

Well Site Texaco Nova Plaza

Address 3690 Davie Road

3 Wells 2.

Florida

4400 SW 36th Street

Dairy Farmers 6 Wells 3.

Amerada Hess Station

4200 Peters Road

3 Wells (1992) 4.

5.

Exxon

7- Eleven

2396 S. State Road 7

4451 Davie Blvd


43

6

WES/ERDC Numerical Model

Model Selection The physical attributes of a site and the study questions dictate the choice of an appropriate numerical model. The PD well field is located in a region with mild ground surface slope and a thin and reasonably uniform unsaturated zone. The water table elevation does not change drastically with time and displays less than a 10-ft range over the model area. The material stratigraphy, described earlier, can be represented adequately with continuous, mildly sloping layers of reasonably consistent material. The stated purpose of this study was to examine flow patterns in the vicinity of the well field. Constituent transport was not to be addressed. Given these considerations, any of several groundwater models might have been chosen. The USGS’ modular three-dimensional (3-D) finite difference model MODFLOW (McDonald and Harbaugh 1984) was selected for this study, because it is relatively simple to implement and has gained regulatory acceptance through years of widespread use. MODFLOW subdivides the domain into a structured array of cells. The model solves the transient or steady-state, saturated groundwater flow equation for the piezometric head (H) in each cell within the computational grid using Equation 1, where Kxx, Kyy, and Kzz are the principal hydraulic conductivities, W is the source/sink term, and S is the storage coefficient. This saturated groundwater flow equation assumes that the grid axes are aligned with the principal directions of flow:

∂H ∂  K xx ∂x  ∂x

∂H  ∂  +  K yy ∂y   ∂y

 ∂ ∂H  ∂H  +  K zz  −W = S ∂z  ∂t   ∂z

(4)

MODFLOW’s numerical scheme approximates the equation by using finite differences on a structured grid. The head in each cell depends on the head in the six cells that share a face with that cell and on any local sources or sinks of water. This approximation process reduces the equation to a system of algebraic equations. MODFLOW solves the system of equations simultaneously using iterative methods. Because the solution is simultaneous, the size of time-steps is not limited explicitly by stability but depends only on the desired time-accuracy of

44

Chapter 6 WES/ERDC Numerical Model

the solution. MODFLOW permits the modification of boundary conditions with time, but these conditions must remain constant over each stress period.

Computational Domain The area of interest encompassed the PD well field and FPR site. Large-scale flow patterns in the area are dictated by the Water Conservation Areas (WCA) to the west and the Atlantic Ocean to the east. Ideally, the model domain should extend to these well-defined hydrologic controls, as in the SFWMD MODFLOW model (Restrepo, Bevier, and Butler 1992). However, combining this large domain size with the desired, fine spatial resolution near the PD well field and the fine temporal resolution in hydrologic stresses would produce an extremely large computational problem. Although problems of this size can be simulated, the model calibration process becomes unwieldy, and this kind of detail away from the area of interest is simply unnecessary. Accurate representation of local hydrologic stresses coupled with a good approximation of regional flow patterns is the wiser choice. Therefore, a smaller domain with model boundaries coinciding with partial hydrologic control (rivers or canals) was created. To the north and east, the model is bounded by canal C-12 and the north fork of the New River. To the south and east, the model is bounded by canal C-11 and the south fork of the New River. To the west, there were no prominent hydrologic boundaries available. The western boundary was placed sufficiently far away that uncertainties in the choice of boundary properties would not substantially affect model predictions near the well field. The model domain is approximately 5 miles from south to north and 6 miles from west to east encompassing about 30 square miles.

Grid Development To provide detail in the head distributions and flow patterns, small grid cells were desired within and near the water table depression created by the PD well field. However, this fine resolution was not needed in the western part of the domain where larger cells could be tolerated. Grid refinement points were assigned at the FPR site and within the PD well field. Cells at these refinement locations were set to 125 ft by 125 ft in plan view. Cells were permitted to become gradually larger away from the refinement points to a maximum of 600 ft on a side. The resulting grid is shown in Figure 32 with an underlying photograph of the domain. In the vertical, the computational grid contained five layers as defined in the conceptual model. The resulting grid contains 81 rows by 96 columns by five layers for a total of 38,800 computational cells. Cells to the east of the north and south forks of the New River were declared inactive. Top and bottom elevations were interpolated to the computational grid from the contours in the WES/ERDC conceptual model. MODFLOW converts these top and bottom elevations and the local conductivity to intercell transmissivities that are applied to a fixed, Cartesian computational grid. Chapter 6 WES/ERDC Numerical Model

45

Initial Hydrogeologic Parameters The model was assigned initial hydrogeologic properties with the realization that these would change during the calibration process. The initial properties are summarized by layer in Table 14. Table 14 Initial Hydrogeologic Properties Layer

Hydraulic Conductivity, ft/d

Anisotropy ratio

Primary Storage Coefficient

1

501

0.055

0.21

2

50

1

0.055

4.0e-41

3

Variable

0.15

7.0e-5

4

Variable

0.15

7.0e-5

5

75

0.052

4.0e-4

1

Spatially constant except for the borrow pits and small lakes.

Hydraulic conductivity The initial hydraulic conductivities were taken from the WES/ERDC conceptual model’s realization of the site. Conductivities for layers 3 and 4 were interpolated to the computational grid from the contoured conductivity fields. Several surface lakes and borrow pits in the model area in layers 1 and 2 were represented as highly conductive (50,000 ft/day) porous media because no inflow or outflow points from these lakes were evident. Anisotropy ratio Initial anisotropy ratios were taken from the average values determined by SFWMD’s modeling (Restrepo, Bevier, and Butler 1992). The anisotropy ratio and horizontal conductivity provide the local, vertical conductivity. This local, vertical conductivity may be coupled with the layer thicknesses to compute the interlayer vertical leakance term using the vertical conductance equation for the interface between layers k and k+1 based on the harmonic mean:

V( k ) =

1 ∆z ( k ) 2 K xx ( k ) A vh ( k )

+

∆z ( k +1)

(5)

2 K xx ( k +1) Avh ( k +1)

Storage coefficients Layer 1 was modeled as unconfined, meaning the primary storage coefficient was the specific yield. Layers 2 through 5 were modeled as confined/ unconfined. The primary storage coefficient was the confined storage coefficient, and the

46


secondary storage coefficient was the specific yield. Historically, the water table has never dropped below the elevation of the top of layer 2, meaning that this secondary storage term will not be needed. The initial storage coefficients for layers 2 through 5 also were taken from the SFWMD (Restrepo, Bevier, and Butler 1992) model report. The material representing the borrow pits and small lakes in layers 1 and 2 used a specific yield of 1.0.

Boundary Conditions MODFLOW (McDonald and Harbaugh 1984) requires that boundary conditions be prescribed on the faces of the model boundary. If no conditions are given, MODFLOW imposes a no-flow through these boundaries. Boundary conditions are also prescribed to assign local sources and sinks of water (wells, rivers, drains, recharge, and evapotranspiration (ET)). Canals and rivers In the surface layer, ‘river’ boundary conditions were defined along canal C-12 to the north, canal C-11 to the south, and by the north and south forks of the New River to the east. The many canals and rivers in the model area were represented with MODFLOW’s river package. Within each cell containing a river boundary condition, a flux (Qi) is computed based on the local head in the cell (Hi), a known head in the river (Hr), and a conductance term (Ci),

Qi = C i ( H i − H r )

(6)

The conductance term (Ci) reflects the degree of interaction between the river and the porous medium within the cell (McDonald and Harbaugh 1984). This conductance may be estimated knowing the thickness (Li), plan-view crosssectional area of the river bottom (Ab) within the cell, and approximate conductivity (Ki) of the material at the bottom of the river with the river conductance equation:

Ci =

K i Ab Li

(7)

SFWMD (Restrepo, Bevier, and Butler 1992) estimated the thickness of the bottom sediments to be roughly 1 ft and the conductivity to range from about 0.5 ft/day in the tidal reaches to about 1.25 ft/day in the freshwater canals. With a conductivity value near 1.0 ft/d and a thickness near 1.0 ft, the canal conductance was roughly the plan-view area of the water body within the cell. Because the DoD Groundwater Modeling System (GMS) (Holland 1996) interface used in this study multiplies the input conductance by the river length in the cell, the values for Ci (ft2/d) were initially estimated to be the value of the river widths (ft) for these simulations.


47

General head boundaries To the west, the model boundary along Pine Island Road was defined as a ‘general head’ boundary (GHB) condition. The GHB condition prescribes a flux based on the difference between the local head in the cell and a reference head. The reference head is normally assigned to some distant, known water body. Thus, GHB conditions permit users to include the effects of known-head bodies that are outside the model domain. The GHB flux equation is identical to that for rivers (Equation 6), with Hr being the known head at a distance (Li) from the cell to the known headwater body. The conductivity and cross-sectional area in Equation 7 become the area and conductivity of the material between the GHB and the known water body. General head boundaries were defined around the perimeter of the model in layers 2 through 5. The distant, known water bodies for these computations were the water conservation area to the northwest and the Atlantic Ocean to the east. The head in the WCA was variable with time as defined in Appendix G. The mean ocean elevation was held constant at 0.0 ft. Conductances were computed individually for each boundary segment in each layer based on an extrapolation of the conductivity and the layer thickness toward the external water body. Because the large-scale gradient is toward the east/southeast, segments along the west and north used the WCA as a reference head. Boundary segments along the south and east used the ocean as a reference head. Distances from the model boundaries to the water bodies were measured in plan view along estimated flow paths. These conductances were installed in the initial model configuration. Lakes The model area contains several large sand and rock borrow pits to the south of the PD well field. These lakes have no well-defined inlets or outlets. Therefore, these lakes were modeled as filled with porous material with very large conductivity (50,000 ft/day) and large storage coefficient (1.0). Recharge The net recharge into the groundwater system is the net flux of water inbound from precipitation. Three components diminish the precipitation flux: (a) surface runoff, (b) evapotranspiration (ET) from the unsaturated zone, and (c) ET from the water table. Because MODFLOW (McDonald and Harbaugh 1984) is a saturated-zone model, it cannot represent processes in the unsaturated zone. The HELP model (Schroeder et al. 1994), which is used to evaluate landfill cover performance, was used to capture the effects of the unsaturated-zone. The HELP model (version 3.05) predicts one-dimensional (1-D), saturated or unsaturated vertical percolation rates through one or more uniform layers. It accounts for runoff and evapotranspiration from the unsaturated zone. The flux computed by the HELP model corresponds to a net precipitation to the water table. The HELP (Schroeder et al. 1994) model accepts precipitation, solar radiation, and air temperature data, soil properties, average wind speed, and vegetation 48


properties. Temperature and precipitation data were taken from the Fort Lauderdale Airport, which is very near the site. Solar radiation data were generated by the HELP model, since these data were not available. Surface soil at the site was classified as a fine sand (Pendleton, Dollar, and Law 1976) corresponding to soil type 3 in the unified soil classification system. Because the HELP model simulation is a 1-D representation of the unsaturated zone, a single thickness must be chosen to be representative of the entire site. Near the Peele Dixie well field, there are local topographic highs, producing unsaturated zone thicknesses up to 10 or 15 ft. However, in the large majority of the domain, the unsaturated zone thickness is about 3 ft. A single layer, 4 ft thick, was chosen to represent the site for the HELP model analyses. The maximum leaf area index was chosen to be 5.0, which is appropriate for southern Florida. The evaporative depth was chosen to be 10 in., which is near the lower end of the range of values recommended for this area. The value chosen is reasonable because the model domain is largely residential and commercial and the majority of the vegetation is shallow rooted (grasses). Given the soil type, the HELP manual suggests a Soil Conservation Service runoff curve number of about 35. These parameters were used in the HELP model to simulate annual, monthly, and daily percolation rates through this layer. The HELP model results were not sensitive to changes in the leaf area index or the runoff curve number. For a reasonable range of curve numbers, very little runoff was observed. Net percolation was, however, sensitive to the choice of soil type and the evaporative depth. These net precipitation values were compared to field experiments conducted by CDM at the nearby Prospect Well Field (CDM 1980b). This comparison, given in Figure 33, shows excellent agreement between the HELP model predictions and the experimental data for comparable annual precipitation rates. The experimental data were collected by observing the short-term rise in water depth in a well following precipitation events. ET from the water table The remaining component in computing net recharge was evaporation from the water table. This component was predicted with MODFLOW’s (McDonald and Harbaugh 1984) evapotranspiration package. This package requires that three quantities be specified: (a) maximum ET surface is the water table elevation at which the maximum evaporation rate applies, (b) extinction depth is the depth beneath the maximum ET surface where the evaporation rate becomes zero, and (c) maximum ET rate. The model assumes a linear decline in the ET rate from the maximum ET surface to the extinction depth. The maximum ET rate was set to be the pan evaporation rate measured at the Fort Lauderdale Airport (0.0123 ft/day). The maximum ET surface should be the ground surface. However, using the ground surface neglects the effect of the capillary fringe (Restrepo, Bevier, and Butler 1992). For example, when the water table is within a short distance of the surface, the ground surface is virtually saturated and significant evaporation will occur. To account for the capillary fringe and the effects of local depressions, small lakes, and ditches not explicitly included in the model, the maximum ET surface was established at 2 ft below an


49

approximate ground surface, taken from surface contours on USGS maps. Estimates for the extinction depth are about 1 ft for this land use and vegetation (Restrepo, Bevier, and Butler 1992). However, it was anticipated that this value would be adjusted upward during calibration.

50


7

Calibrating the WES/ERDC Model

Calibration Protocol Calibration is the process of adjusting uncertain model inputs to provide a better match to historical observations. It is important to test a range of hydrologic conditions because different model components may dominate in dry years than in wet years. Three different hydrologic conditions were chosen for model calibration. The years chosen were 1984 (average), 1989 (dry), and 1995 (wet). These particular years were chosen because a significant number of observations were available. In each of these years, an observation ‘snapshot’ consisting of several measurements taken near the same time was available in the spring. Having many observations near the same time provided an image of the spatial distribution of heads within the model domain. Another snapshot of observation data was available in the fall for each year. Thus, the calibration process for each of the 3 years consisted of a steady-state calibration to the spring observations, followed by a transient, 6-month calibration from the spring to the fall observation snapshot. Stress periods were chosen to be 1 week long. Therefore, stage data, pumping data, and recharge data were averaged to weekly periods where available. One to three time-steps per week were used to approximately match the simulation and observation times.

Matching the Net Recharge CDM (1980b) performed experiments at the nearby Prospect well field to determine the ET from the water table. These measurements were made by longterm monitoring of the decline in the water table during dry periods. Using these observations, the extinction depth in the Peele Dixie MODFLOW (McDonald and Harbaugh 1984) model was adjusted uniformly in space. In these experiments, CDM (1980b) observed long-term evaporation from the water table in a wet, a dry, and an average water year. Table 15 summarizes their findings and the MODFLOW (McDonald and Harbaugh 1984) ET predictions over the 6-month simulations. Direct comparisons were not possible, because the simulation and experiments were made in different years. Chapter 7 Calibrating the WES/ERDC Model

51

Table 15 Experimental Versus Model ET Ppt Characteristics

CDM Observed ET Rate, in./year

CDM Observed ET rate percent annual excess ppt

MODFLOW ET from Water Table, percent excess ppt

Dry year

2.5

12.5

27.7

Average year

10.2

30.0

20.6

Wet year

10.7

20.2

26.0

The extinction depth was set to 2.5 ft to approximately match the CDM observations. From the CDM data, the net recharge from precipitation is 23.8 in. in an average water year. As a comparison, the linear regression of the HELP (Schroeder et al. 1994) data gives an annual excess precipitation of nearly 31 in. for a year with about 62 in. of rain. Removing 25 percent of this for ET from the water table gives 23.3 in./yr. Both of these estimates are somewhat higher than the 17.5 in./yr proposed by Sherwood, McCoy, and Gallagher (1973), which was a generalization of the hydrologic cycle.

Comparison to Observation Head Data The model parameters from the initial simulation were modified to achieve a better fit to the nine snapshots of observed head data (two in 1984, two in 1989, and five in 1995). The horizontal and vertical hydraulic conductivities, the storage coefficients, the canal and river conductances, and the GHB conductances were changed to improve the match to historical data. Table 16 shows the statistical fit to the observation snapshots from the calibrated model. Table 16 Statistical Fit to the Observed Head Data Mean Absolute Error, ft

Root-MeanSquare Error, ft

0.03

0.38

0.56

33

0.03

0.57

0.82

SS1

31

-0.08

0.31

0.44

Oct-89

TR2

31

-0.45

0.53

0.65

Apr-95

1

27

-0.13

0.42

0.62

TR

2

32

0.19

0.19

0.26

TR

2

35

-0.07

0.15

0.19

Aug-95

TR

2

45

0.22

0.26

0.36

Oct-95

TR2

25

-0.20

0.60

0.85

Snapshot Date

Simulation Type

Number of Observations

May-84

SS1

30

Oct-84

TR

2

May-89

May-95 Jul-95

1 2

52

SS

Mean Error ft

SS - steady-state TR - transient-state

Chapter 7 Calibrating the WES/ERDC Model

From the observation snapshots, composite error statistics were computed. Each snapshot was weighted by the number of observations it contained. With 289 observations, the composite mean error in the head simulation was less than 0.05 ft. The mean absolute error was less than 0.4 ft. The composite root-meansquare (RMS) error was 0.6 ft. When normalized by the range of heads in the observed data set (7.82 ft), the composite data fit was 7.07 percent, which is within the 10 percent normalized error established as a goal prior to the model study. Individual images and comparison graphs for these snapshots may be found from Figures 34 through 51. These plots show head contours in layer 3 and ‘whisker plots’ where observed data were given. Green bars indicate a good comparison (generally less than 0.5 ft), yellow bars indicate a marginal comparison (generally more than 0.5 ft difference, but less than 1 ft), and red bars indicate significant errors (generally larger than 1 ft). The comparisons to observed data show generally good agreement. Several of the larger errors occur in observation wells very near pumping wells. Resolving these errors poses two problems. First, if the well was pumping when the observation was made and not at the time the simulation data were extracted, the heads could be very different. Second, the head in each MODFLOW (McDonald and Harbaugh 1984) cell represents an average over the volume of that cell. In the real medium, drawdown measured near the pumping well might be substantially larger than the drawdown only 50 ft away. The simulated heads were slightly low during the dry year (1989) comparisons. Part of this was a result of the observation data collection techniques. Observations in the southeastern part of the domain in Pond Apple Swamp (Van Horn 1996) were collected as daily maximum values. The swamp is adjacent to the tidally influenced North New River. These data were collected very near the ground surface and the swamp contains many channels visible on areal photographs. Of the six observation locations in the swamp, those nearest the river showed the most significant under prediction, which is consistent with variations due to tides. As expected, the effect of these tidal fluctuations diminished with distance from the river. Of the 289 total observations contained in the nine snapshots used for calibration, none of the differences between computed and observed heads exceeded 3 ft. Two observations differed by more than 2 ft, and 23 differed by more than 1 ft. Of these ‘problem’ comparisons with differences exceeding 1 ft, the majority (18 of 23) are in the surface layer. Near the ground surface, there may be local sources or users of water that are not included in the model. Further, the transient effects of precipitation recharge would be most pronounced and difficult to capture near the surface. Additionally, local heterogeneities in the surface layer could cause some variability in adjacent head values. In the lower layers which hold the contaminants, the observations and simulations agreed well.


53

Calibrated Model Parameters In the calibrated model, canal conductances ranged from 25 feet per day (ft/d) in the small, tidally influenced canals to 200 ft/d in the large, freshwater canals (C-12, C-11, NNRC). These values are per unit length of canal. They must be multiplied by the canal length in the cell to determine conductance for input to MODFLOW (McDonald and Harbaugh 1984). Assigning slightly higher conductance in the freshwater canals than in comparably sized tidal canals, as proposed by SFWMD (Restrepo, Bevier, and Butler 1992), provided a better fit. Because the canal conductance is dictated by the biogeological composition of the material on the canal bottom, different values for fresh and saltwater canals are reasonable. GHB conductances were modified but showed little effect on the statistical fits. The final conductance values used were near those specified in the initial description. Remarkably, it was possible to get virtually the same statistical fit to the observed data using GHBs with modified conductances and a reference head from canal stages on the northern, southern, and eastern boundaries, rather than the water conservation area and the ocean. The best, composite fit to the observations was achieved with hydraulic conductivity in layers 1, 2, and 5 at 150 ft/d (except for the borrow pits in layers 1 and 2). A value of 150 ft/d was well within the range of values observed in each of these layers (Tables 3 and 13). Hydraulic conductivities in layers 3 and 4 from the conceptual model were modified nonuniformly in space. Block changes were limited to the eastern part of the domain, because very few conductivity data were available in that area. No improvement to the overall data fit was observed with these changes. Anisotropy ratios given by the SFWMD model provided the best composite fit of the values tested. With a horizontal conductivity of 150 ft/d in the upper layer and an anisotropy ratio of 0.055, the vertical conductivity is 8.25 ft/d. This conductivity is only slightly less than the vertical conductivity of the soil (12 to 40 ft/d ) identified at the site (Pendleton, Dollar, and Law 1976). Because the model boundaries did not lie on known hydraulic controls for all five layers, a comparison was performed with the larger SFWMD (Restrepo, Bevier, and Butler 1992) Broward County model. Cells were identified in the Broward County model corresponding to boundaries in the WES/ERDC model. Data from these cells were provided by SFWMD (Giddings 1997a) for each month in 1989. Figures 52 through 55 compare the SFWMD model and the WES/ERDC model along these boundaries for layers 1 and 3 for the month of June. This comparison shows that the WES/ERDC model boundaries produce heads consistent with the SFWMD model.

54


8

Sensitivity Analysis

The calibrated model represents a nonunique, approximate realization of the actual, under-sampled site. Sensitivity analysis helps distinguish between model parameters that must be reasonably accurate, and those that need not be. For the sensitivity calculations, a model very similar to the final calibrated model was accepted as the base condition. Beginning with this model, each hydrologic and geologic input parameter was systematically modified independently and the changes noted. With the GMS (Holland 1996) these modifications are made in the conceptual model of the site. Changes are then mapped to appropriate MODFLOW (McDonald and Harbaugh 1984) input files without the need to make cell-by-cell changes. The transient calibration for the average water year (1984) was chosen to examine sensitivity. Properties were modified and simulations were performed as summarized in Table 17. The results showed generally little impact on the statistical fit to the observed head data. A few of the modifications caused a reduction in the overall error compared to the calibrated model. For example, increasing the storage coefficient in layers 2 through 5 improved the data fit slightly. However, these changes caused increased error when compared to the other calibration data sets and, thus, were not retained in the conceptual model. Changes in the statistical fit to the October 1984 observed head snapshot were used as one measure of sensitivity. Standard error measures, given in the third column of Table 17, showed the largest sensitivity to changes in specific yield and recharge, moderate sensitivity to changes in hydraulic conductivity, ET extinction depth, and canal conductance, and very little sensitivity to changes in storage coefficient, anisotropy ratio, or GHB conductances. The table includes another measure of sensitivity. Changes in the volumetric contribution from the boundary and internal sources and sinks were documented. These, too, showed sensitivity to changes in specific yield and recharge. However, in contrast to the error statistics, this measure also showed sensitivity to GHB conductance and hydraulic conductivity. An important observation here is that some changes to parameters made little difference to the statistical fit but resulted in significant differences in the paths by which water enters or exits the model. For example, changing the GHB conductance has virtually no effect on the comparison to observed heads. However,

Chapter 8 Sensitivity Analysis

55

this change may alter the amount of fluid exiting through river boundaries by over 1 million ft3/d. This analysis shows that the simulated head field is not remarkably sensitive to changes in many of the model parameters. The head field is dominated by pumping and recharge, which are well quantified. This finding gives added confidence that model-predicted flow directions (which are determined largely by the spatial distribution of head) are probably not sensitive to most model properties.

56


Table 17 Summary of Sensitivity Calculations

Property

Layers

Base Condition

Error Summary, mean error/ mean abs. error/ RMS error

Cumulative Volumes, *1,000,000 ft3 In Recharge

Rivers

Out GHBs

ET

Rivers

GHBs

+0.10 / 0.55 / 0.81

1,631

180

568

336

1,408

48

Base*0.5

+0.20 / 0.60 / 0.83

-

-40

-15

+33

-122

+4

Base*2.0

+0.04 / 0.54 / 0.81

-

+59

+11

-22

+95

-2

Base*0.5

-0.07 / 0.60 / 0.86

-

-1

-13

+11

-34

-2

Base*2.0

+0.19 / 0.59 / 0.83

-

+20

+14

-12

+34

+3

Base*0.33

+0.27 / 0.62 / 0.84

-

-47

-20

+42

-150

+6

Base*3.0

+0.02 / 0.55 / 0.81

-

+67

+14

-24

+109

-3

Base*0.33

+0.12 / 0.56 / 0.82

-

+5

+1

+1

-5

+1

Base*3.0

+0.09 / 0.55 / 0.81

-

+7

+1

-1

+1

-

Base*0.01

+0.10 / 0.55 / 0.81

-

+7

+1

-

-1

-

Base*100.

+0.02 / 0.53 / 0.80

-

-1

+1

-12

-34

-

0.1

+0.02 / 0.54 / 0.81

-

+18

-

+27

+41

+1

0.3

-0.49 / 0.68 / 0.94

-

+59

+9

+244

-184

-3

Base*0.1

+0.29 / 0.66 / 0.86

-

-39

-16

+47

-143

+6

Base*10.

-0.03 / 0.53 / 0.81

-

+55

+13

-29

+109

-3

Base*0.1

+0.08 / 0.55 / 0.81

-

+37

-179

-23

-102

-16

Base*10.

+0.12 / 0.55 / 0.81

-

-25

+295

+39

+184

+30

Base*0.67

-0.41 / 0.63 / 0.89

-369

+41

+11

-53

-238

-4

Base*1.5

+0.81 / 0.98 / 1.19

+558

-22

-16

+88

+367

+6

1.0 ft

+0.26 / 0.64 / 0.85

-

-26

-8

-170

+109

+1

4.0 ft

-0.10 / 0.52 / 0.81

-

+47

+7

+171

-109

-2

Hydraulic Conductivity

Hydraulic Conductivity

Anisotropy Factor

Anisotropy Factor

Storage Coefficient

Specific Yield

Canal Conductance

GHB Conductance

Recharge

ET Extinction Depth

1,2,5

3,4

1,2,5

3,4

2,3,4,5

1

1

All

1

1


57

9

Long-Term Simulation

The calibrated model was used to construct a long-term simulation spanning the period of 1978 through 1996. Stress periods were chosen to be 1 month each to capture the transient effects of variable pumping and recharge. Each stress period contained one time-step except those requiring two steps for midmonth comparison to the observations. The long-term simulation used the calibrated model parameters without modification. Results from the long-term simulation were compared against the observation snapshots used for the model calibration. The results are presented in Table 18. Table 18 Comparison of Long-Term Simulation to Observation Snapshots Snapshot Date

Mean Error, ft

Mean Absolute Error, ft

Root-Mean-Square Error, ft

May-84

1.38

1.40

1.50

Oct-84

-0.13

0.58

0.84

May-89

-0.50

0.53

0.66

Oct-89

-0.45

0.53

0.64

Apr-95

-0.05

0.41

0.58

May-95

0.29

0.29

0.33

Jul-95

0.03

0.23

0.27

Aug-95

0.34

0.42

0.47

Oct-95

-0.47

0.78

1.08

For several reasons, the long-term simulation results should have fit the observed heads more poorly than the shorter, calibration simulation results. Monthly stress periods in the long-term simulation required that the hydrologic stresses (pumping rates, stage data, recharge rates) be averaged over an entire month, instead of the weekly averaging used for calibration. Further, the calibration process permitted some manipulation of the recharge data for each of the steady-state simulations. Even so, the resulting fit of the long-term simulation to the observed head snapshots (Table 18) is often close to the calibration fits. The composite statistics showed a mean error of less than 0.1 ft, a mean absolute error less than 0.6 ft, and an RMS error of 0.77 ft. The composite, normalized RMS error for the long-term simulation was about 9.8 percent. However, the May 1984

58

Chapter 9 Long-Term Simulation

comparison showed the model results to be uniformly high by about 1.4 ft. This one comparison, which accounted for about 40 percent of the total error, occurred during a time of rapid change in the water table elevation. During rapid change in the water table, differences in the actual and predicted timing of these changes will appear as large errors in model-data comparison. At some locations within the domain, observations were available at many times over the 19-year period. The long-term simulations were compared to observations at several locations which offered the most data. Figures 56 through 62 give monthly-averaged observed head values and simulation results. In these figures, the observations are portrayed with the dashed line and the simulations are represented with a solid line. Comparisons are very favorable. The direction of flow between the Peele Dixie well field and the FPR site varies substantially during the 19 years of simulation. In the first several years of simulation, flow in layer 3 tends toward the northeast from FPR, but varies with season. The northeasterly direction is clear in the April 1978 flow patterns in layer 3 shown in Figure 63. Northeasterly flow was also noted during extended dry periods with high pumping (1988 and 1989). Not surprisingly, the flow direction appears to depend substantially on the amount and distribution of pumping in the Peele Dixie well field. After the pumping strategy was changed in 1986 to favor the north well field, the flow direction is generally toward the south/ southeast from FPR. Southerly flow is apparent in the October 1995 layer 3 head distribution and flow directions shown in Figure 64. Fluid was not shown to be entering the model via the North New River Canal below Sewell Lock (G-54). This portion of the river was ‘gaining’ for all conditions tested. This finding is consistent with the CDM (1980a) model results.

Exploratory Constituent Transport Simulations A constituent transport model, MT3D (Zheng 1991), was used to further explore flow patterns to the south of Peele Dixie well field. Given a working MODFLOW (McDonald and Harbaugh 1984) model of a site, the MT3D model is simple to implement because both models can use the same computational grid. MT3D accepts flux data from the flow model to predict migration and fate of soluble constituents, and the model simulates the effects of advection, dispersion, sorption, and simple reactions. Model parameters must be specified to accompany each of these processes. Several transport properties for these simulations were taken from the MT3D study by Geraghty and Miller, Inc. (Kladias 1998), built upon this same (WES/ERDC) MODFLOW simulation of the site. In their model, Geraghty and Miller used an effective porosity of 4 percent in layers 3 and 4, no dispersion, a sorption retardation factor of 2, a half-life of 5 years for decay, and a continuous source concentration of 3,000 micrograms per liter of total VOCs. With the exception of dispersion, these choices for model parameters are generally reasonable, but certainly do not reflect a ‘worst case’ for predicting maximum plume migration. Each process and parameter are described below.


59

Simulating advection requires the specification of an effective porosity to convert Darcy fluxes (MODFLOW output) into transport velocities. The effective porosity describes the fraction of the medium volume that actually conveys the constituents. In homogeneous material, the effective porosity will be slightly smaller than the volumetric porosity. However, in heterogeneous media, the majority of transport will occur through a few preferential flow paths defined by the higher conductivity material. Thus, the effective porosity for these materials should be much smaller. A value of 4 percent indicates that about 20 percent of the interconnected pore space will conduct the majority of the contaminant. To simulate dispersion in MT3D (Zheng 1991), a dispersivity parameter is required. This parameter is related to the size of the unresolved geologic features in the medium. Rule-of-thumb guidance for assigning dispersivity length in naturally heterogeneous media is one-tenth the scale of the plume (Gelhar, Welty, and Rehfeldt 1992). Therefore, with a plume size on the order of 1 mile, a dispersivity of 500 ft in the direction of flow would be appropriate. A dispersivity value of 100 ft was chosen for additional simulations. Using a larger dispersivity in this model caused undue artificial spreading in the vertical direction, an artifact of the quasi-isotropic dispersion model included in MT3D (Zheng 1991). Linear sorption may be represented with a retardation factor that simply modifies the plume’s movement and rate of growth. A sorption retardation factor of 2 indicates that the plume will move and grow half as fast as a nonsorbing plume. A retardation factor of 2 probably represents the upper end of the appropriate range of values for a site with such low organic carbon content and the given distribution of contaminants (Bechtel 1997). Decreasing the retardation factor would produce a larger, more mobile plume. Breakdown paths for VOCs are multistep reactions with multiple kinetic rates that depend on the local geochemistry. Representing this complex process with uncalibrated, first-order decay rates is a crude approximation. However, a 5-year half-life is probably a reasonable ‘average’ value for the mixture of contaminants (Howard et al. 1991). To be conservative, the slowest reaction in the path (probably the breakdown of vinyl chloride) should be used. Initial transport simulations were conducted using flow data from the 19-year MODFLOW (McDonald and Harbaugh 1984) simulation spanning 1978 through 1996. Most of the contaminant movement occurred in the more permeable material in layers 3 and 4. The simulations showed large-scale oscillation in the flow direction were attributable to wet/dry patterns in the hydrology. Early in the simulation, migration is to the east/northeast. The late 1980s and early 1990s generally saw a more southeasterly flow. However, during the dry years of 1988 and 1989, migration tended toward the north/northeast. Contaminants were introduced only at the FPR site to examine the plausibility of migration from FPR to the Peele Dixie well field. Some contaminant was captured by the North New River Canal and some passed under the canal toward the Peele Dixie well field.

60


The simulated contaminant migration patterns further supported by observations of nested well pairs in the area (Bechtel 1997). At two times in 1997, the vertical gradients were assessed in the Peele Dixie well field, near the canal, and near the FPR site. These data show a consistent, upward flow beneath the canal. These gradients are mild, but rival the small lateral gradients in the area. With comparable gradients in the horizontal and vertical directions, it is difficult to anticipate whether contaminants would continue in the highly conductive layers 3 and 4, or head to the surface for removal by the river. The difference in vertical and horizontal conductivities is offset by the shorter travel distances in the vertical than the horizontal. The simulated plumes migrated farther to the east than is indicated by the contaminant observations. However, comparison to the observed plume was difficult because the plume boundaries were not well quantified to the east or the south. Further, hydraulic conductivity in this, the eastern part of the domain, is largely uncertain and may be lower than simulated in the flow model. The conceptual model for hydraulic conductivity in layers 3 and 4 shows a significant trend decreasing from west to east. If this trend were continued to the east, instead of truncating the conductivity field at 800 ft/d, this easterly migration would be lessened.

Screening Level Containment Analysis The EPA asked for a screening-level estimate of the amount of pumping required to provide hydraulic containment around the plume. Potential extraction wells were located in the numerical model throughout the 5 ppb TVOC plume boundary. Head-gradient control locations were identified all along the 5 ppb plume contour at depths corresponding to the Biscayne aquifer. These gradientcontrol locations amount to pairs of observation points spaced about 50 to 100 ft apart in the model. The MODMAN optimization package (Greenwald 1996) was applied to determine the required extraction rates to achieve the desired head differences between the observation points in a control pair. Because this was a screening-level computation, the steady-state flow simulation for the average water year (1984) was used. For a measurable, ‘inbound’ head difference (about 0.02 ft) between the points in each gradient control pair, the flow required was approximately 4 mgd. While this is a large pumping requirement, it did not preclude the use of hydraulic containment as a potential remediation alternative.


61

10 Summary of Site Conceptualization, Flow Modeling, and Initial Transport Simulation An extensive literature search was conducted on the hydrogeological characteristics of the surficial aquifer system in Broward County and the Fort Lauderdale Area. A hydrogeologic conceptual model was developed using data from previous investigations (Bechtel 1997; Restrepo, Bevier, and Butler 1992; Fish 1988; Casaurus 1985; JMM 1986; CDM 1980a; Parker, Ferguson, and Love 1955). A five-layer hydrogeologic system was defined using data from actual aquifer tests and examination of stratigraphic logs. The five-layer system was defined over an area of 360 square miles which encompassed the much smaller numerical model area (approximately 30 square miles). The aquifer tests were conducted by previous investigators to define the high permeability zone (Biscayne aquifer) of the surficial aquifer system. The Biscayne aquifer is delineated by WES/ERDC model layers 3 and 4. The Biscayne aquifer is made up of several lithologies, which include; coarsegrained limestone, limestone with large cavities, sandy limestone, calcareous sandstone and mixtures of limestone and sandstone. All of these units can be highly permeable but are sometimes interbedded with less permeable layers. WES/ERDC defined the distribution of hydraulic conductivity in the Biscayne (layers 3 and 4) by contouring the test data from previous studies. Hydraulic conductivities decreased from west to east ranging from 8,500 ft/d to approximately 600 ft/d. The area east of the PD Well Field suffered from a lack of aquifer test data. Consequently, the conductivity field in the model was truncated to 800 ft/day, east of the Peele Dixie field. Since little information was collected by previous studies on materials shallower (WES/ERDC layers 1 and 2) and deeper (WES/ERDC layer 5) than the Biscayne, these layers were initially assigned constant conductivities of 50 ft/d and 75 ft/d, respectively. Subsequent additional data were collected (on layers 1 and 2) from Broward County (Schneider 1998) which provided a range of conductivities. The best composite fit to the observations was achieved with a hydraulic conductivity in layers 1, 2, and 5 at 150 ft/d.

62

Chapter 10 Model Summary

Available hydrologic data were collected from local and Federal agencies and utilities, and synthesized as time-series input and calibration data for the model. Specifically, local precipitation, temperature, canal stage data, water table observations, and pumping schedules were collected. Temperature and precipitation were used to generate recharge estimates to the water table, using the HELP model (Schroeder et al. 1994). These estimates compared favorably with actual field measurements described in the CDM (1980b) report. Daily canal stage and some well observations were averaged to weekly or monthly values. However, most wells were read in intervals of 1 month or greater and, therefore, were not an average value but a single measurement. Pumping data from small utilities were provided as monthly operating reports. These pumping data were estimated from existing data, where records were missing. The Peele Dixie pumping schedule was provided by the plant operators for the entire period of interest (1978 through 1996). One snapshot per week was provided, showing the total flowrate and listing of operating wells for one day. These weekly snapshots were considered by the plant operator as representative of the entire week. Using the hydrogeologic conceptualization and the available hydrologic data, a groundwater flow model was constructed to simulate head distributions in the vicinity of the Peele Dixie well field and the FPR Site. The model was calibrated using weekly time-steps to match observed head distributions for a wide range of hydrologic conditions. The calibration produced a composite normalized RMS error near 7 percent. A long-term simulation using monthly time-steps was created spanning 1978 through 1996. This simulation also showed good agreement with observed head data.

Results of Flow Modeling and Initial Transport Modeling The Biscayne aquifer displays a mild ambient gradient on the order of 1 ft/mile. Therefore, local flow direction is sensitive to changes in pumping strength or location and changes in canal stages. Early in the long-term simulation, when Peele Dixie’s south well field was operating normally (pre-1987), flow from the FPR site was often toward the northeast and the Peele Dixie well field. This pattern was also observed during very dry periods such as 1988 and 1989. After pumping from the south field was decreased drastically (post-1986), flow patterns in layers 3 and 4 at FPR tended more toward the southeast for average or wet hydrologic conditions. During the 19-year period of simulation, flow direction at FPR varied by about 140 deg in plan view, depending on the pumping rates and distribution of wells operating in the Peele Dixie well field. Transport simulations confirmed the flow results, showing contaminants traveling toward the north/northeast early in the simulation, and shifting to the southeast later in the simulation. Transport simulations showed some of the northbound contaminant being captured by the North New River Canal and some contaminant passing beneath the canals toward the well field. Transport simulations also emphasized the need for a better understanding of the hydraulic


63

conductivity field in the eastern part of the model domain and the variation in vertical permeabilities of the Biscayne Aquifer at the well field. The screening level containment analysis estimated a 4-mgd pumping rate to contain the plume.

Conclusions and Model Limitations Evaluation of the EPA Conceptual Model for Plume Migration from FPR The EPA’s conceptual model of this site suggests that contamination from FPR traveled northward, under the canal, and into the Peele Dixie wells. Given the flow patterns and plume migration patterns predicted by these simulations, this conceptual model is consistent with our understanding of the site. Contaminants released at FPR would have traveled generally north/northeasterly from 1978 to 1986 and during dry years 1988 and 1989. This transport would have occurred through high velocity, preferential flow paths in the deeper Biscayne aquifer. Some of these contaminants would have been captured by upward flow into the North New River Canal and some would have passed beneath the canal, according to model results. When the pumping strategy changed at Peele Dixie (decreased pumping from the south in 1987), the southern edge of the well field capture zone would have moved northward. The plume was split into northern and southern plumes. The northern plume would continue to be drawn northward toward the Peele Dixie wells, as documented by the Contaminant Assessment Report (JMM 1992). Part of the plume would be extracted by the North New River Canal. The southern plume would have altered course with the changing flow field and turned to the southeast. Therefore, while the model cannot identify conclusively the origin of the contamination, the model results do not refute FPR as a potential source.

Test data There was a lack of aquifer test data to the east of the well field, making conductivity estimates in that portion of the Biscayne aquifer uncertain. Model sensitivity analyses indicate that this uncertain conductivity has a pronounced effect on the easterly component of plume migration. A higher estimate of conductivity to the east permits easterly motion, while a lower conductivity to the east forces a more north-south motion of the plume. Unsaturated effects The MODFLOW (McDonald and Harbaugh 1984) model used in this study is a saturated flow model. These models treat the water table in unconfined aquifers in a simplified fashion. The HELP model (Schroeder et al. 1994) was used to estimate recharge to the groundwater. Doing this neglects the time required for 64


travel between the ground surface and the water table. Fortunately, these shortcomings probably had little impact on flow patterns at this site, because the unsaturated zone is very thin and recharge to the groundwater table is uniformly fast. Uncalibrated transport modeling The values chosen for decay, retardation, and source concentration in the transport model were taken from literature values and engineering judgment on the part of Geraghty and Miller, Inc. (Kladias 1998). Though the values were based on reasonable assumptions, the uncertainty in these values remains quite large. This parameter uncertainty translates into uncertainty in the predicted migration and fate of the contaminant plume. For this reason, model parameters should be systematically calibrated to match observed contaminant concentration data. In the absence of calibration to field data, sensitivity analyses should be performed to explore the range of potential model predictions corresponding to a reasonable range of model parameter values. Given that the parameter values chosen were not calibrated and no sensitivity analyses performed, the model predictions for plume migration should be taken as plausible, but not unique.

Methods To Improve Model Certainty To confirm or discount the plume migration scenario offered, results from the flow and transport modeling could be strengthened with additional field testing. Uncertainty in conductivity in the Biscayne aquifer in the eastern third of the domain could be addressed with additional conductivity measurements. Using a more firm conductivity field to the east would permit a more thorough examination of the direction of plume migration. In addition, interconnectivity among layers, expressed through the anisotropy ratios, would be more certain with vertical conductivity measurements. This layer interconnectivity strongly affects the amount of water exchanged between the surface canals and the Biscayne aquifer. Additional calibration data, such as tracer tests, large-scale long-term transient pump tests, and detailed geologic examination of any new wells, would help fortify the model results. Tracer tests would provide a measure of the apparent dispersion properties and the effective porosity for transport. Transient pump tests would help quantify the storage coefficients and permit examination of the interlayer connectedness. Geologic examination of new wells would increase confidence in layer thicknesses, (primarily of the Biscayne) in the area of high interest.


65

References Aronson, D., and Howard, P. (1997). “Anaerobic biodegradation of organic chemicals in groundwater: A summary of field and laboratory studies,” Environmental Science Center, Syracuse Research Corporation, North Syracuse, NY. American Society for Testing and Materials. (1995). “Emergency standard guide for risk-based corrective action applied at petroleum release sites,” ASTM E-1739, Philadelphia, PA. Azadpour-Keeley, A., Russel, H. H., and Sewell, G. W. (1999). “Microbial processes affecting monitored natural attenuation of contaminant in the subsurface,” Issue Paper, EPA/540/S-99/001, Environmental Protection Agency Office of Research and Development, Ada, OK. Bechtel Environmental, Inc. (1998). “Remedial investigation report for Florida petroleum reprocessors site, Davis, Broward County, Florida,” Volume I, Prepared for United States Environmental Protection Agency, Washington, DC. __________. (1994). “DRAFT remedial investigation/feasibility study phase I site characterization report for the Peele Dixie Groundwater Plume Site, Fort Lauderdale, Florida,” EPA Contract Number 68-W9-0058, Oakridge, TN. __________. (1995). “Site characterization report for phase II of the remedial investigation for the Peele Dixie Groundwater Plume Site, Fort Lauderdale, Florida,” EPA Contract Number 68-W9-0058, Oakridge, TN. __________. (1996). “Site characterization report addendum for the Peele Dixie Groundwater Plume Site, Fort Lauderdale, Florida,” EPA Contract Number: 68-W9-0058, Oakridge, TN. __________. (1997). “DRAFT remedial investigation report for the Florida Petroleum Reprocessors Site, Davie Florida,” EPA Contract Number 69-W9-0058, Oakridge, TN.

66

References

Boulton, N. S. (1963). “Analysis of data from nonequilibrium pumping tests allowing for delayed yield from storage.” Proceedings Institute Civil Engineers 26, p 469-482. Bierschenk, W. H. (1963). “Determining well efficiency by multiple stepdrawdown tests,"”IASH Publications 46, 493-507. Bouwer, E. J. (1994). “Bioremediation of chlorinated solvents using alternate electron acceptors.” Handbook of bioremediation. R. D. Norris, R. E. Hinchee, R. Brown, P. L. McCarty, L. Semprini, J. T. Wilson, D. H. Kampbell, M. Reinhard, E. J. Bouwer, R. C. Borden, T. M. Vogel, J. M. Thomas, and C. H. Ward, eds., Lewis Publishers, Boca Raton, FL. Bouwer, H., and Rice, R. C. (1976). “A slug test for determining hydraulic conductivity of unconfined aquifers with completely or partially penetrating wells,” Water Resources Research 12(3), 423-428. Bradley, P. M., and Chapelle, F. H. (1997). “Kinetics of DCE and VC mineralization under methanogenic and Fe (III)-reducing conditions,” Environ. Sci. Technol. 31, 2692-2696. Callahan, M. A.; Slimak, M. W.; Gabel, N. W.; May, I. P.; Fowler, C. F.; Freed, J. R.; Jennings, P.; Durfee, R. L.; Whitemore, F. C.; Maestri, B.; Mabey, W. R.; Holts, B. R.; and Gould, C. (1979). “Water-related environmental fate of 129 priority pollutants. Vol. II, Halogenated alipatic hydrocarbons, halogenated ethers, monocyclic aromatics, phthalate esters, polycyclic aromatic hydrocarbons, nitrosamines and miscellaneous compounds,” EPA440/4-79-029b, U.S. Environmental Protection Agency, Washington, DC. Camp Dresser & McKee. (1980a). “Dixie well field stress analysis,” prepared for the City of Fort Lauderdale, Florida. __________. (1980b). “Prospect well field impact analysis,” prepared for the City of Fort Lauderdale, Florida. Causaras, Carmen R. (1985). “Geology of the surficial aquifer system, Broward County, Florida,” U.S. Geological Survey Water Resources Investigations Report 84-4068, Tallahassee. Clement, T. P., and Johnson, C. D. (1998). “Modeling natural attenuation of chlorinated solvent plumes at the Dover Air Force Base area-6 site,” Draft Report, Pacific Northwest National Laboratory, Richland, WA. Clement, T. P., and Jones, N. L. (1998). “RT3D tutorials for GMS users,” PNNL-11805, Pacific Northwest National Laboratory, Richland, WA. Clement, T. P., Hooker, B. S., and Skeen, R. S. (1996a). “Numerical modeling of biologically reactive transport near a nutrient injection well,” ASCE Journal of Environmental Engineering Division 122(9), 833-839.

References

67

Clement, T. P., Sun, Y., Hooker, B. S., and Petersen, J. N. (1998). “Modeling multi-species reactive transport in groundwater aquifers,” Groundwater Monitoring & Remediation Journal 18(2), 79-92. Cohen, R. M., and Mercer, J. W. (1993). “DNAPL site evaluation, Robert Kerr Environmental Research Laboratory, Ada, Oklahoma,” EPA/600/R-93/022, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC. Cooper, H. H., and Jacob, C. E. (1946). “A generalized graphical method for evaluating formation constants and summarizing well-field history,” Trans. Amer. Geophys. Union 27(4), 526-534. Cooper, Richard M., and Lane, Jim. (1987). “An atlas of eastern Broward County surface water management basins,” Technical Memorandum DRE-31, South Florida Water Management District, Water Resources Division, West Palm Beach, Florida. Cooper, Richard M., and Roy, Joanne. (1991). “An atlas of surface water management basins in the Everglades: The Water Conservation Areas and Everglades National Park,” Technical Memorandum DRE-300, South Florida Water Management District, Water Resources Department of Research and Evaluation, West Palm Beach, Florida. Deutsch, C. V., and Journel, A. G. (1992). GSLIB: Geostatistical Software Library and User Guide. Oxford University Press, New York. Fish, Johnnie E. (1988). “Hydrogeology, aquifer characteristics, and groundwater flow of the surficial aquifer system, Broward County, Florida,” U.S. Geological Survey Water Resources Investigations Report 87-4034, Tallahassee. Gelhar, L. W., Montoglou, A., Welty, C., and Rehfeldt, K. R. (1985). “A review of field-scale physical solute transport processes in saturated and unsaturated porous media,” Final Project Report EPRI EA-4190, Electric Power Research Institute, Palo Alto, CA. Gelhar, L. W., Welty, C., and Rehfeldt, K. R. (1992). “A critical review of data on field-scale dispersion in aquifers,” Water Resources Research 28(7), 19551974. Giddings, Jeff. (1997a). “Simulated head data from cells in the SFWMD 1992 model which correspond to WES/ERDC model boundaries,” electronic file, South Florida Water Management District personnel, West Palm Beach, Florida. __________. (1997b). “Simulated head from cells in SFWMD 1992 model at WCA2B gage 2B-21,” electronic file, South Florida Water Management District personnel, West Palm Beach, Florida.

68

References

Greenwald, R. M. (1996). “MODMAN: Management module for MODFLOW using LINDO Optimization Program,” IGWMC report FOS 76, International Groundwater Modeling Center, Colorado School of Mines, Golden, CO. Haggerty, R., and Gorelick, S.M. (1994). “Design of multiple contaminant remediation: Sensitivity to rate-limited mass transfer,” Water Resources Research 30(2), 435-446. Haag, W. R., and Mill, T. (1988). “Transformation kinetics of 1,1,1-trichloroethane to the stable product 1,1-dichloroethene,” Environ. Sci. Technol. 22, 658–663. Haire, W. J., Sonenshein, R., Lietz, C., Workman, E. (1988). “Water resources data Florida water year 1986, volume 2B, south Florida groundwater,” U.S. Geological Survey Water-Data Report FL-86-2B, Miami, FL. Haire, W. J., Sonenshein, R., Price, C. (1987). “Water resources data Florida water year 1985, volume 2B, south Florida groundwater,” U.S. Geological Survey Water-Data Report FL-85-2B, Miami, FL. Hanson, R. J., and Hiebert, K. L. Subroutine DSPLP, Sandia National Laboratory, http://netlib.org/slatec/src/dsplp.f Hantush, M. S., and Jacob, C. E. (1955). “Nonsteady radial flow in an infinite leaky aquifer.” Trans. Amer. Geophys. Union, 36, p. 95-100. Holland, Jeff. (1996). “The Department of Defense Groundwater Modeling Program: An overview.” Subsurface Fluid Flow Modeling. ASTM STP/ 288, J. D. Ritchey and J. O. Rumbaugh, ed., American Society for Testing and Materials, Philadelphia, PA. Hounslow, A. W. (1995). Water quality data analysis and interpretation. CRC Press, Boca Raton, FL. Howard, P. J., Boethling, R. S., Jarvis, W. F., Meylan, W. M., and Michalenko, E. M. (1991). Handbook of environmental degradation rates. Lewis Publishers, Inc., Chelsea, MI. Howington, Stacy E., Peters, John F., and Illangasekare, Tissa H. (1997). “Discrete network modeling for field-scale flow and transport through porous media,” Technical Report CHL-97-21, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. James M. Montgomery, Consulting Engineers, Inc. (1986). “The study of water supply and the selection of future wellfield sites in Broward County, Florida, Main Report,” in association with Dames and Moore, Plantation, FL.

References

69

James M. Montgomery, Consulting Engineers, Inc. (1992). “Contamination assessment for the continued use of the Peele Dixie well field,” Plantation, FL. Jeffers, P. M., Ward, L. M., Woytowitch, L. M., and Wolfe, N. L. (1989). “Homogeneous hydrolysis rate constants for selected chlorinated methanes, ethanes, ethenes, and propanes,” Environ. Sci. Technol. 23(8), 965–969. Johnson, C. D., Skeen, R. S., Leigh, D. P., Clement, T. P., and Sun, Y. (1998). “Modeling natural attenuation of chlorinated ethenes at a Navy site using the RT3D code,” Proceedings of WESTEC 98 conference, Water Environmental Federation, Orlando, Florida. Hantush, M. S. (1956). “Analysis of data from pumping tests in leaky aquifiers,” Trans. Amer. Geophys.Union, 37, 702-714. Kaluarachchi, J., and Morshed, J. (1995). “Critical assessment of the operatorsplitting technique in solving the advection-dispersion-reaction equation: 1. First-order reaction,” Advances in Water Resources 18 (2), 89-100. Karickhoff, S. W., Brown, D. S., and Scott, T. A. (1979). Sorption of hydrophobic pollutants on natural sediments,” Water Res.13, 241-248. Kladius, Michael P. (1998). “Historical solute transport analysis.” Attachment 1 of the review comments to the draft report entitled “A three-dimensional groundwater flow model of the Peele Dixie well field, including the Florida Petroleum Processors Superfund Site, Fort Lauderdale and Davie, Florida, by U.S. Army Engineer Waterways Experiment Station,” Arcadis Geraghty & Miller, Inc. Millersville, MD. Lu, G., Zheng, C., Clement, T. P., and Wiedenmeier, T. H. (1999). “Natural attenuation of BTEX compounds model development and field-scale application,” Ground Water 37(5), 707-717. Lyman, W. J., Reidy, P. J., and Levy, B. (1991). “Assessing UST corrective action technology-A scientific evaluation of the mobility and degradability of organic contaminants in subsurface environment,” EPA/600/2-91/053, Risk Reduction Engineering Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC. Major, D. M., Hodgins, E. W., and Butler, B. J. (1991). “Field and laboratory evidence of in situ biotransformation of tetrachlororthene to ethene and ethane at a chemical transfer facility in North Toronto.” On-site bioremediation. R. E. Hinchee and R. F. Olfenbuttel, R. F., eds, Butterworth-Heinemann, 147-171, Boston, MA. McDonald, M. G., and Harbaugh, A. W. (1984). “A modular three-dimensional finite-difference ground water flow model,” United States Geological Survey Open File Report 83-875, Washington, DC.

70

References

McDonald, M. G., and Harbaugh, A. W. (1988). “A modular three-dimensional finite-difference groundwater flow model,” Techniques in Water Resources Investigations, Book 6, Chapter A1. U.S. Geological Survey, Washington, DC. McCarty, P. L., and Semprini, L. (1994). “Ground-water treatment for chlorinated solvents,” Handbook of Bioremediation. R. D. Norris, R. E. Hinchee, R. Brown, P. L. McCarty, L. Semprini, J. T. Wilson, D. H. Kampbell, M. Reinhard, E. J. Bouwer, R. C. Borden, T. M. Vogel, J. M. Thomas, and C. H. Ward, eds., Lewis Publishers, Boca Raton, FL, 87-116. Murray, W. D., and Richardson, M. (1993). “Progress toward the biological treatment of C 1 and C 2 halogenated hydrocarbons,” Crit. Rev. Environ. Sci. Technol. 23(3), 195-217. Neuman, S. P. (1975). “Analysis of pumping test data from anisotropic unconfined aquifers considering delayed gravity response,” Water Resources Research 2, 329-342. Parker, Garald G., Ferguson, G. E., and Love, S. K. (1955). “Water resources of Southeastern Florida,” Geological Survey Water Supply Paper 1255, Washington, DC. Parsons, F., Wood, P. R., and DeMacro, J. (1984). “Transformations of tetrachloroethylene and trichloroethylene in microcosms and ground water,” J. Am. Water Assoc. 76, 56-59. Pendleton, Robert F., Dollar, Hershel D., and Law, Lloyd Jr. (1976). “Soil survey of Broward County Area, Florida,” U.S. Department of Agriculture, Soil Conservation Service, Washington, DC. Prickett, T. A., and Lonnquist, C. G. (1971). “Selected digital computer techniques for ground water resource evaluation,” Illinois State Water Survey, Bulletin 55. Prinos, Scott. (1997). “Explanation of USGS water level databases of South Florida,” USGS Water Resource Division, Miami, FL. Restrepo, Jorge I., Bevier, Cindy, and Butler, David. (1992). “A threedimensional finite difference groundwater flow model of the surficial aquifer system, Broward County, Florida,” Technical Publication 92-05, DRE 314, South Florida Water Management District, West Palm Beach, Florida. Schneider, Harvey. (1998). “Various excerpts from petroleum related remedial investigations near the FPR Site in Broward County,” Department of Natural Resource Protection, Fort Lauderdale, FL. Schnoor, J. L. (1996). Environmental modeling fate and transport of pollutants in water, air, and soil. Wiley, New York.

References

71

Schroeder, Paul R., Lloyd, C. M., Zappi, P. A., Aziz, N. M. (1994). “The hydrologic evaluation of landfill performance (HELP) model, Version 3,” EPA/600/R-94/16b, Environmental Protection Agency Report, Washington, DC. Sherwood, C. B. (1959). “Ground-water resources of the Oakland Park Area of Eastern Broward County, Florida, Report of investigations No. 20,” Florida Geological Survey, Tallahassee. Sherwood, C. B., McCoy, H. J., and Galliher, C. F. (1973). “Water resources of Broward County, Florida,” Florida Bureau of Geology report of investigations 65, 141. Suarez, M. P., and Rifai, H. S. (1999). “Biodegradation Rates for Fuel Hydrocarbons and Chlorinated Solvents in Groundwater,” Bioremediation Journal 3(4), 337-362. Sun, Y., Petersen, J. N., Clement, T. P., and Hooker, B. S. (1998). “Effects of reaction kinetics on predicted concentration profiles during subsurface bioremediation,” Journal of Contaminant Hydrology 31, 359-372. Sun, Y., and Clement, T. P. (1998). “A decomposition method for solving coupled multi-species reactive transport problems,” Transport in Porous Media Journal 1404, 1-20. Tarver, George R. (1964). “Hydrology of the biscayne aquifer in the Pompano Beach Area, Broward County, Florida, Report of investigations No. 36,” Florida Geological Survey, Tallahassee. Taylor, S.W., and Jaffe, P. R. (1990). “Substrate and biomass transport in a porous medium,” Water Resources Research 26, 2153-2159. Theis, C. V. (1935). “The relation between the lowering of the piezometric surface and the rate and duration of discharge of a well using groundwater storage.” Trans. Amer. Geophys. Union. 2, 519-524. U.S. Environmental Protection Agency. (1986). “Background document for the ground-water screening procedure to support 40 CFR Part 269 - Land Disposal,” EPA/530-SW-86-047, Washington, DC. U.S. Environmental Protection Agency. (1999). “Use of monitored natural attenuation at Superfund, RCRA corrective action, and underground storage tank sites, directive number: 9200.4-17P,” United States Environmental Protection Agency, Office of Solid Waste and Emergency Response, Washington, DC. Valocchi, A. J., and Malmstead, M. (1992). “Accuracy of operator-splitting for advection-dispersion-reaction problems,” Water Resources Research 28(5), 1471-1476.

72

References

Van Horn, Stuart. (1996). “Hydrometeorologic monitoring network metadata report,” WRE#344, South Florida Water Management District, Resource Assessment Division, West Palm Beach, Florida. Veith, G. D., Call, D. J., and Brooke, L. T. (1983). “Structure-toxicity relationship for the fathead minnow, pimephales promelas: Narcotic industrial chemicals,” Can. J. Fish Aquat. Sci. 40, 743-748. Vogel, T. M. (1994). “Natural bioremediation of chlorinated solvents.” Handbook of Bioremediation. R. D. Norris, R. E. Hinchee, R. Brown, P. L. McCarty, L. Semprini, J. T. Wilson, D. H. Kampbell, M. Reinhard, E. J. Bouwer, R. C. Borden, T. M. Vogel, J. M. Thomas, C. H. Ward, eds., Lewis Publishers, Boca Raton, FL, 201-225. Walter, A. L., Frind, E. O., Blowes, D. W., Ptacek, C. J., and Molson, J. W. (1994). “Modeling of multicomponent reactive transport in groundwater 1. Model development and evaluation,” Water Resources Research 30(11), 3137-3148. Walton, William C. (1970). Groundwater resource evaluation. McGraw-Hill, New York, 664. Weaver, J. W., Wilson, J. T., and Kampbell, D. H. (1996). “Extraction of degradation rate constants from the St. Joseph, Michigan Trichloroethene Site.” Proceedings of the symposium on natural attenuation of chlorinated organics in ground water. September 11-13, Dallas, TX. Xu, M., and Eckstein, Y. (1995). “Use of weighted least-squares method in evaluation of the relationship between dispersivity and scale,” Ground Water 33(6), 905-908. Zheng, C., MT3D. (1990). “A modular three-dimensional transport model for simulation of advection, dispersion and chemical reactions of contaminants in groundwater systems,” U.S. Environmental Protection Agency, Washington, DC. Zheng, C. (1991). MT3D: A ground-water path and travel time simulator. 2nd ed., S. S. Papadopulos & Associates, Inc., Rockville, MD. Zheng, C., and Wang, P. Patrick. (1999). “A modular three-dimensional multispecies transport model for simulation of advection, dispersion and chemical reactions of contaminants in groundwater systems,” Release DoD_3.50.A, University of Alabama, Tuscaloosa, AL.

References

73

Figure 1. WES/ERDC model area boundaries

1

Figure 2. WES/ERDC model area location

Figure 3. WES/ERDC model area, Ft. Lauderdale, Florida

Figure 4. WES/ERDC model layers and general hydrogeologic concept of the site (modified from SFWMD 1992)

Figure 5. Peele Dixie well locations and model lakes (modified from Bechtel Environmental, Inc. 1997)

Figure 6. Map of production (diamonds and other wells in the Peele Dixie/ FPR study area. Many sites are clusters: only "D" wells shown for clusters. Cross section AA' is in Figure 14.

Figure 7. USGS observation well locations used for calibration and local water district boundaries

Figure 8. Average wet season water table for 1974-1982 (USGS)

Figure 9. Average dry season water table for 1974-1982 (USGS)

Figure 10. Map of Broward County, FL area showing locations of USGS wells (ovals) and cross sections (dashed lines) of Causaras (1985) and Fish (1988)

Figure 11. General sequence of geological unit, aquifers, and aquicludes in Broward County, Florida (James M. Montgomery, 1986)

Figure 12. West to east cross section along North New River Canal from 20-mile Bend to Ft. Lauderdale (Parker 1955)

Figure 13. Schematic relationships in surficial aquifer of Broward County (Fish 1988)

Figure 14. South to north vertical geologic profile AA’ through the local modeling area, Peele Dixie well field and vicinity

Figure 15. Hydrologic cross section GG’ prepared by Fish (1988). See Figure 9 for location

Figure 16. Hydrologic cross section CC’ prepared by Fish (1988). See Figure 9 for location

Figure 17. Borings and wells supplying elevations for model layers and thickness

Figure 18. Contoured surface elevations of the top of layer 3, WES/ERDC flow model

Figure 19. Contoured surface elevations of the bottom of layer 4, WES/ERDC flow model

Figure 20. Countoured thickness of layers 3 and 4, WES/ERDC flow model

Figure 21. Contoured surface elevations of the base of layer 5, WES/ERDC flow model

Figure 22. Contoured thickness of layer 5, WES/ERDC flow model

Figure 23. Wells providing transmissivity values for WES/ERDC model layers 3 and 4, with source and value, in ft2/day (see Tables 3 and 4)

Figure 24. Aquifer test results from James M. Montgomery (1986)

Figure 25. Contoured values of transmissivities, layer 4--deep zone, PW wells: 3, 6, 9, 15, 16, and 19

Figure 26. Contoured values of transmissivities, layer 3--shallow zone, PW wells: 8, 20, 21, 23, and 25

Figure 27. Contoured values of hydraulic conductivity (k), layer 4--deep zone, PW wells: 3, 6, 9, 15, 16, and 19

Figure 28. Contoured values of hydraulic conductivity (k), layer 3--shallow zone, PW wells: 8, 20, 21, 23, and 25

Figure 29. Locations of small water utilities and FLCC

TQ> NW & SW CAP

NO

NO

SW CAP = 0

YES

YES

TQ-N W CAP