Technical Publication 92-02

A Three-Dimensional Finite DifferenceGroundwater Flow Model of the

Surficial Aquifer in Martin County, Florida

March 1992

Technical Publication 92-02

A THREE-DIMENSIONAL FINITE DIFFERENCEGROUNDWATER FLOW MODEL OF THE

SURFICIAL AQUIFER IN MARTIN COUNTY, FLORIDA

by

Karin Adams, P.G.

March 1992

This publication was produced at an annual costof $900.00 pr $1.80 per copy to inform the public.500 292 Produced on recycled paper.

DRE Inventory Control #310

Hydrogeology DivisionDepartment of Research and Evaluation

South Florida Water Management DistrictWest Palm Beach, Florida

EXECUTIVE SUMMARY

This study was undertaken as part of the SouthFlorida Water Management District's Water SupplyPlanning initiative. One of the water supplyplanning directives in the initiative is to "developand maintain resource monitoring networks andapplied research programs (such as forecastingmodels) required to predict the quantity and qualityof water available for reasonable-beneficial uses"(SFWMD, 1991). The model will be used within theSFWMD by the Planning Department in thedevelopment of the Upper East Coast Water SupplyPlan and by the Regulation Department toimplement the water use criteria and policies of theDistrict. The Water Supply Plan includes aprojection of future water demand, identification ofwater sources and methods to meet this demand on aregional scale and an analysis of impacts associatedwith these alternate methods.

New regulatory criteria from water supplyplans and the Draft Water Supply Policy Documentwill be incorporated into the District's Basis ofReview for Consumptive Use Permits. The modelswill also be used for impact analysis in the District'swater use regulatory function and on the local scaleby governments and consultants. This model is notconsidered to be an unchanging final product. Asnew data and technologies are available, it will beupgraded and improved. Future plans include theintegration of surface water and water qualityelements, Geographic Information Systems (GIS)applications, and the ability to "zoom" in on specificmodel areas for more detailed local modeling.

Martin County, Florida is underlain by twoaquifer systems: the Surficial Aquifer System andthe deeper Floridan Aquifer System. Informationfrom a ground water assessment completed by theSouth Florida Water Management District in 1990was used to develop a regional three-dimensionalground water flow model. This model focused on theSurficial Aquifer System while a separate model wasdeveloped for the Floridan Aquifer System and isdocumented separately.

For modeling purposes, the Surficial AquiferSystem in Martin County was divided into threelayers representing different lithologic types: 1) finesand, silt, and organics, 2) shell, sand andlimestone/sandstone with little or no fines, and 3)sand, shell, silt and poorly consolidated, micriticlimestone. The second layer is moderately

productive and most ground water is withdrawnfrom this interval. Productivity in the remainder ofthe Surficial Aquifer System is low.

The Ground Water Flow ModelThe Martin County Surficial Aquifer System

model was developed using the U.S. GeologicalSurvey modular three-dimensional finite-differenceground water flow model code, commonly known asMODFLOW. This code was used because it allows adetailed evaluation of ground water flow, is availablein the public domain, is compatible with mostcomputer systems, and contains many featureswhich make it easy to use and modify. MODFLOWsimulates ground water levels and flow using datadescribing the aquifers, such as hydraulicconductivity, transmissivity, leakance, and storage.Stress on the aquifers (e.g., recharge, evapo-transpiration, well withdrawals, and interactionswith surface water bodies) can also be simulatedwith the model.

The horizontal model grid is composed of 59rows and 109 columns. A uniform size of 2,000 by2,000 feet was used, except for five columns of cellson the western edge of the model. These columnsincrease in width as they extend westward six milesinto Okeechobee County.

Recharge to the Surficial Aquifer SystemRainfall provides approximately 95 percent of

the total annual aquifer recharge in the study areaunder present conditions. An additional four percentrepresents recharge coming primarily from groundwater flow into the study area from boundaries, andthe final one percent is leakage from rivers.

Discharge/Water Use from the Surficial AquiferSvste m

Evapotranspiration accounts for approximately70 percent of the outflow from the model area underpresent conditions. Leakage to canals in the studyarea accounts for an additional 19 percent of thelosses. Well withdrawals account for an additionalnine percent, and the remaining losses are flow out ofthe model along boundaries.

Well withdrawals for agriculture, publicsupply, and domestic self-supply were determined byvarious means. Agricultural ground waterwithdrawal information for the calibration periodwas obtained primarily from water use permits

issued by the District. The permits suppliedinformation on crop types, acreages, irrigationpractices, and wells. Additional information, whennecessary, was obtained directly from theagricultural operators. This information was used toestimate monthly water use during the calibrationperiod. Actual pumpage records were used whenavailable. Data on public supply water use, asreported to the District and to the FloridaDepartment of Environmental Regulation, also wasused in the model. Domestic self-supply wasestimated based on land use types and irrigation useassumptions.

Calibration/Sensitivity TestingThe model was calibrated by adjusting aquifer

parameters within prescribed limits to matchcomputed water levels with monthly observed waterlevels in monitor wells for the period January 1989through December 1989. The calibration criteriarequired that modeled water levels be within one footof the observed water levels for at least nine of thetwelve months modeled, and this criteria was met infifty-three percent of the wells. For an additionaltwenty-nine percent of the observation wells used,calibration criteria was not met because oflimitations in reporting model levels. The modelvalue used to verify calibration represents the waterlevel at the center of each 2,000 x 2,000 foot cell.Because of the gradient across the cell and thelocation of the observation well in the cell, the wellmay not be at the same water level as the level in thecenter of the cell. However, comparing model valuesin adjacent cells confirms that the gradient is correctand, therefore, the model does calibrate to the well.Since a majority of the wells verify calibration of themodel, there is a high degree of confidence in themodel.

To ensure the best possible accuracy forevaluative or predictive purposes, it is important totest the model's sensitivity to the estimatedparameters. The model was fairly insensitive tochanges in hydraulic parameters, but changes ininputs to the recharge and evapotranspirationpackages significantly affected calibration in allthree layers of the model.

RecommendationsThe most important recharge and discharge

sources in the model are rainfall andevapotranspiration; the accuracy of the modeldepends on the accuracy of the input data for these

two sources. As currently designed, the modelprovides a simplification of the actual complexprocesses involved in determining how much rainfallactually reaches the aquifer and how much water isremoved from the aquifer by evapotranspiration.Work in these areas is needed to improve modelaccuracy.

Domestic self supply and irrigation are largeusers of water in Martin County. In order to enhancethe accuracy and reliability of the model for resourceavailability determinations, improvements in theestimation of domestic self-supply use could be madewith better information on exactly where utilityboundaries are located and which houses in utilityareas use private water for irrigation.

Public water supply utilities that use multiplewells need to record raw water pumpage from eachwell. Because of differences in pump capacity andthe operating schedule of each well, total wellfieldpumpage is of limited value in generating modelinput necessary for determining wellfield impacts.This information is especially important when"zooming" in on an area.

Based on the model budget, discharge to surfacewater bodies represents a significant loss from theaquifer. Input data, including canal constructiondetails and stage levels, are limited and estimationerrors could result in inaccurate seepage amountsinto or out of the canals. Efforts should be made inthe permitting process to obtain and include thisdata in future surface water management permits.Stage recorders in major grove canals would providevaluable information on water levels to set inriver/drain cells in future modeling efforts.

The model should be used in the evaluation ofwater use permit applications. Where a finer scale orsite-specific model is required, the regional modelcould be used to provide the boundary conditions.The model should continue to be refined and updatedwhenever additional information becomes available.

Availability of Model for UseElectronic copies of model data sets are

available upon request from the HydrogeologyDivision. If, in using the model, users include new ormore detailed data that results in a bettercalibration, they are encouraged to share that datawith the District. Refinement of the model is acontinuous, ongoing process.

TABLE OF CONTENTS

EXECUTIVE SUMMARY ............................................... ..... . iLISTOFFIGURESLIST OF TABLES ................... ......... ................................ viiACKNOWLEDGEMENTS ....... .. ........................................ viiiABSTRACT . -..................... ................ ........................... ix

INTRODUCTION ....... . ........ 1INTRODUCTION ................................................................ 1

Purpose and Scope ............... ................................ 1Location of Study Area ......................... .. ..............................Topography and Physiography ....................... ....................... 1Previous Investigations ..................................................... 5Hydrogeology of the Surficial Aquifer System ...................................... 5

MODEL DESCRIPTION .................................. ....................... 11

Overview .................................... ................. ...... 11Discretization ...................................................... 11Boundary Conditions ........... ............ ............................ 15Hydraulic Characteristics ............................................... ........................ 17

Transmissivity/Hydraulic Conductivity ...................................... 17Layer O ne ..................... ......... ....... . .... ...... 20Layer Two ...... ................... ................. 20Layer Three ........................ . ..................... 20

Storage and Specific Yield ......................... ....... 20Vertical Conductivity ................... ................................. 20

Surface Water Interactions ................ . ................................ 22Recharge ............................................................ 25Evapotranspiration .................... .................................. 27Ground W ater Use ............................................................... 33

A gricu ltu ra l ...................................... ........ .... ...... 33Public Water Supply .................................. .............. 35Domestic Self Supply .................................... ......... .. 35Other Ground Water Uses ................... .............................. 41

CALIBRATION ................................ ..... ................ .. 42

Transient Calibration ..................... ............................... 42M ethod ............ ............... ............ .................. .... 42Results .......... ................................................. 50

Steady State Calibration ........ ......................... ................ ........ 54Method ....................................... 54Results ............. . .............................. ............ 54

Budget and Flows ..................................................... 62Layer One ...................................... .................. 62Layer Two ...................................................... 62Layer Three ...................... .......... ......................... 62

SENSITIVITY TESTING S.......................................................... 3

Layer OneLayer Two ....................... 73Layer Three - - ..... 73Model Boundariese . ................ ......................................... 7M odel Boundaries ... * .............. 76Climatologic and Starting Head Effects . . ......... . 76

QUALITY ASSURANCE/QUALITY CONTROL PROCEDURE 78

S.......................... ... .... ........ ............. .. 79

CONCLUSIONS AND RECOMMENDATIONS S......................................... 80

REFERENCES

APPENDIX A: Maps and Table of Data Used for Vertical Discretization .................. 85APPENDIX B: Maps of Hydraulic Parameters

......- ................ ... 10 5APPENDIX C: General Head, River and Drain Input Data ..... 115......... .. .. .... .... . 1 1 5APPENDIX D: Recharge Methods, Rainfall Station Map and Table,

Recharge and ET Coefficients S--.......................... ........... 131APPENDIX E: Water Use Data, Public and Agricultural.........153 ............. ......... 153APPENDIX F: Computed and Observed Hydrographs Representing ....... .....Monitor Wells, 1989. 189

LIST OF FIGURES

Figure Page

1 Location of Study Area .................... .................................. 2

2 Study Area Including Reduced Threshold Areas .................................... 3

3 Topography and General Soils Maps of Martin County .............................. 4

4 Generalized Hlydrogeologic Cross Section ..................................... 6

5 Locations of Aquifer Performance Tests in Model .................................. 9

6 Model Grid ...... .. ................................. .... . ..... ... 13

7 Lithologic Types and Corresponding Model Layers ................................. 14

8 General Head Boundary Conceptualization ...................................... 16

9 Cell Types, Layer1 .................... .............. ........ ...... 18

10 Cell Types, Layers 2 and3 ..................................................... 19

11 Cells Containing River and Drain Reaches ................ ...................... 23

12 River and Drain Conceptualization ............................................... 24

13 Land Use Types in Study Area .................................................... 26

14 Cells with Modifications to Recharge Array ................ ..................... 28

15 Net Recharge, Steady State ................................... .... 29

16 Ratio of Net Recharge to Total Rainfall, Steady State .............................. 30

17 Conceptualization of Capillary Fringe and ET Extinction Depth Determination ....... 31

18 Cells Containing Agricultural or Industrial Wells, Layer 1 .......................... 36

19 Cells Containing Agricultural or Industrial Wells, Layer 2 .......................... 37

20 Cells Containing Public Water Supply Utility Wells ................................ 38

21 Urban Land Use Cells Served by Large/Small/No Utility ............................ 39

22 Observation W ells, Layer 1 ................ ... .................................... 43

23 Observation Wells, Layer 2 ............... .................................. 44

LIST OF FIGURES (Continued)

Figure Page

24 Observation Wells, Layer 2 (Tequesta/Jupiter Area) ................................. 45

25 Observation Wells, Layer3 .............. .... ................ ................ 46

26 Starting Heads, Layer 1 ........................................................ 47

27 Starting Heads, Layers 2 and 3 ................................................ 48

28 Average Difference Between Observed and Computed Water Levels, Layer 1 .......... 51

29 Average Difference Between Observed and Computed Water Levels, Layer 2 .......... 52

30 Average Difference Between Observed and Computed Water Levels, Layer 3 .......... 53

31 Computed Water Levels in Layer 1, Steady State ............................... 55

32 Computer Water Levels in Layer 2, Steady State .................................. 56

33 Computed Water Levels in Layer 3, Steady State .................................. 57

34a-d Steady-State Calibration Residuals from Average Measured Water Levels ......... 58-61

35 Magnitude and Direction of Horizontal Flow in Layer 1, Steady State ................. 63

36 Volumetric Budget, Layer 1, Steady State ....................................... 64

37 Magnitude and Direction of Horizontal Flow in Layer 2, Steady State ................. 65

38 Magnitude of Vertical Flow Between Layer 1 and Layer 2, Steady State ............... 66

39 Volumetric Budget, Layer 2, Steady State .......................................... 67

40 Magnitude and Direction of Horizontal Flow in Layer 3, Steady State ................. 68

41 Magnitude of Vertical Flow Between Layer 2 and Layer 3, Steady State ............... 69

42 Volumetric Budget, Layer 3, Steady State ...................................... 70

43 Volumetric Budget for Entire Model, Transient .................................... 71

LIST OF TABLES

TablePage

1 Aquifer Performance Test Data Used in Model 72 Packages in MODFLOW Used in the Martin County Model ... ......... 12

3 Soil Types and Corresponding Vertical Hydraulic Conductivity andCapillary Fringe Height ................................................. 21

4 Supplemental Irrigation Water Rates Used to Calculate Irrigation of Grass ........... 345 Domestic Self-Supply Estimate Parameters ........... 40

6 Transient Calibration Results ... 50

7 Steady-State Calibration Results ............... 54

8 Volumetric Budget, 1989 Conditions ........... 72

9 Sensitivity Responses to Changes in ConductivityTfransmissivity, Storage, and VCONT 74

10 Sensitivity Responses to Changes in Stress ................... .. 75

ACKNOWLEDGEMENTS

This project was carried out under the direction of Scott Burns, formerly theDirector of the Hydrogeology Division and currently Director of the Water UseDivision. I would like to thank him for giving me the opportunity to undertake thiseffort. Keith Smith, Acting Director of the Hydrogeology Division, also provideddirection and editorial comments.

The author wishes to acknowledge the peer review committee, whose commentsgreatly improved the quality of this report:

Leslie Wedderburn, Dept. of Research and Evaluation, SFWMDWilliam Scott Burns, Water Use Division, SFWMDPaul Millar, Local Government Assistance, SFWMDTom Tessier, Geraghty and MillerLinda Horne, Martin County Utilities DepartmentRick Nevulis, CH2MHill, DeerfieldGary Russell, USGS, StuartPete Anderson, Geotrans, Inc., Virginia

The author also wishes to thank Emily Hopkins for her prompt and valuableeditorial comments.

Jorge Restrepo provided numerous insights into the model as well as severalvery useful pre and post processing programs for which I am very grateful. I alsoappreciate all the suggestions I received from my fellow hydrogeologists as I discussedproblems I encountered. Especially helpful were the observations and challengespresented by Mary Jo Shine as she evaluated the model, which improved it in severalareas.

Gratitude is expressed to Barbara Dickey for her immediate attention andassistance to all problems involving the computer, especially in writing programs tomake my job easier. Also to Diane Bello, Janet Wise and Dave Demonstranti forcreating wonderful graphics and patiently accepting the tedious modifications.Finally, to Hedy Marshall for her expediency during the compilation of the text andher patience during the editorial phase of this project.

ABSTRACT

In Martin County, Florida, the Surficial Aquifer System is the primary groundwater supply source. The Surficial Aquifer System is comprised of a moderatelyproductive zone of sand, shell, and limestone/sandstone intervals overlain andunderlain by less productive layers of mainly sand and silt. A three-dimensionalground water flow model of the Surficial Aquifer System was developed using the U.S.Geological Survey modular finite-difference ground water flow model code(MODFLOW). The model consists of three layers representing three lithologic zones.Horizontal discretization was accomplished using a grid comprised of 59 rows and 109columns, with a grid spacing of 2,000 feet. Initial aquifer parameters were obtainedfrom various agency and consultant reports. A transient calibration was performed fora one-year period (1989) by comparing simulated water levels with observed waterlevels from an extensive monitoring network. Sensitivity analyses showed that waterlevels in all layers of the Surficial Aquifer System are sensitive to changes in rechargeand the evapotranspiration surface. Work is needed in these two areas to improvemodel accuracy.

INTRODUCTION

PURPOSE AND SCOPE

This study was undertaken as part of the SouthFlorida Water Management District's program todevelop regional comprehensive water supply plansand support regulatory decisions of the agency.These plans will be based on quantitativeassessments of the available water resourcescombined with estimates of future water usedemands. Evaluation of existing water supplyproblem areas, identification of potential problemareas, and development of management guidelineswill be integral parts of a water supply plan.

The purpose of this study was to develop acountywide three-dimensional ground water flowmodel of the Surficial Aquifer System in MartinCounty. Specific uses of this model will be to developand evaluate the ground water elements of the watersupply plan for the Martin County area and toevaluate the impact of future ground water uses onexisting users as part of the regulatory process. Themodel will also be used to evaluate short-termdrought management scenarios during declaredwater shortages.

This report represents one in a series of ongoingstudies to characterize the ground water resource ofMartin County. Development of the ground waterflow model is documented in this report. The modelwill be continually refined and updated as it is usedin the regulatory and planning processes, and asmore data become available. Electronic copies ofmodel data sets are available upon request from theHydrogeology Division. The modeling work waspreceded by extensive field work to define the extentand occurrence of major aquifer systems, regionalground water flow patterns, water-quality trends,and a preliminary assessment of the futuredevelopment potential of the ground water resourcesof Martin County. The results of the field work willbe described in a SFWMD Technical Publication tobe released in 1992,

LOCATION OF STUDY AREA

Martin County is located in southeasternpeninsular Florida, east of Lake Okeechobee (Figure1). It is bounded on the east by the Atlantic Oceanand to the west by Lake Okeechobee and OkeechobeeCounty. To the north and south, it is bordered by St.Lucie and Palm Beach Counties, respectively. The

county is 35 miles from east to west and 16 milesfrom north to south. The study area includes most ofMartin County, a six-mile buffer area into adjacentOkeechobee County, and five miles into northernPalm Beach County. A buffer zone was not extendedinto St. Lucie County because model developmentwas coordinated with a similar modeling effort in St.Lucie County (Padgett, in press) with the intent ofeventually combining the two models. The JensenBeach peninsula, north of the St. Lucie Inlet andwithin the political boundaries of Martin County, isactually part of the St. Lucie County ground waterflow regime. Therefore, it is included in the St. LucieSurficial Aquifer System model rather than theMartin County model. The modeled area liesgenerally within Townships 40 through 43 South,and Ranges 36 through 43 East, and encompassesapproximately 720 square miles, 550 of which are inMartin County (Figure 2).

TOPOGRAPHY AND PHYSIOGRAPHY

Martin County lies within the Atlantic CoastLowlands (White, 1970) and includes the EasternValley, the Osceola Plain and the Evergladesphysiographic regions. Each region has similartopography or relief, or a certain soil type if common.The topography (based on USGS quadrangle maps)and soil types (after McCollum, 1981) in MartinCounty are illustrated in Figure 3. Most of MartinCounty lies within the Eastern Valley, which is abroad, flat relict beach ridge plain. In the centralportion of the county, between the Osceola Plain andGreen Ridge (see Figure 2), this is evidenced by theclosely spaced system of subparallel ridges andswales oriented parallel with the present Atlanticbeach (White, 1970). Elevations in the EasternValley range from 15 to 30 feet above mean sea level.The Osceola Plain ends in a narrow terrace in MartinCounty and appears to have been a narrow peninsulaor series of islands and shoals at one time. It isapproximately two miles wide in Martin County andhas an elevation of 30 to 50 feet above mean sealevel. Located adjacent to Lake Okeechobee in thesouthwest corner of the county, is the Evergladesregion which is flat and covered by organic soilsformed by the growth and decay of sawgrass.Elevations in the Everglades range from 15 to 20 feetabove sea level.

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PREVIOUS INVESTIGATIONS

The hydrogeology of southeastern Florida wasgenerally examined by Parker (1955). A detailedinvestigation of the water resources of MartinCounty was performed by Lichtler (1960). The waterresources of the county were revisited by Earle(1975) and Miller (1978) also within this sameplanning area. Stodghill and Stewart (1984) usedsurface DC resistivity surveys to delineate thehydrostratigraphic zones of the coastal ridge aquiferin Martin County. Nealon and others (1987)provided a regional analysis of water availabilityand water resource planning recommendations. Anumber of authors have also provided information onthe county's aquifers, but on a site-specific basis.

MacVicar and others (1984) examined theground water flow of the Surficial Aquifer System inMartin, St. Lucie and eastern Okeechobee counties(Upper East Coast Planning Area) using the SouthFlorida Water Management Model. Nealon andothers (1987), refined the grid spacing of the UpperEast Coast South Florida Water Management Modelto simulate hydrogeologic conditions in MartinCounty and a portion of St. Lucie County.Three-dimensional ground water flow models havebeen developed and published for Palm BeachCounty (Shine, et al., 1990) and for the Jensen BeachPeninsula (Hopkins, 1991). Models for the St. LucieCounty Surficial Aquifer System and for theFloridan Aquifer System underlying Martin, St.Lucie, and portions of Okeechobee, Indian River andPalm Beach Counties have been developed anddocumentation is currently underway.

HYDROGEOLOGY OF THE SURFICIALAQUIFER SYSTEM

A brief summary of the hydrogeology whichsupports the model development follows. Readerswishing a more detailed discussion of thehydrogeology of the Martin County area are referredto Adams (in press). Hydrostratigraphicnomenclature used in this report is consistent withguidelines set forth by the Southeastern GeologicalSociety Committee on Florida Hydrostratigraphy(SGSCFH,1986).

Martin County is underlain by two aquifersystems: the Surficial Aquifer System and theFloridan Aquifer System. The model developed forthis study was limited to the Surficial AquiferSystem (Figure 4). The Floridan Aquifer System,being modeled separately, is not discussed in thisreport, but will be the subject of a forthcomingpublication (Lukasiewicz, in press).

The Surficial Aquifer System consists of thewater table aquifer and hydraulically connectedunits above the top of the first occurrence of laterallyextensive and vertically persistent beds of muchlower permeability (SGSCFII, 1986). In MartinCounty, the Surficial Aquifer System is unconfinedto semi-confined and is comprised of threehydrogeologic zones: the surficial sands, the primarywater-producing zone, and a less permeable zoneoverlying the confining bed. The surficial sands areshallow and may not be completely saturatedthroughout the year. The primary water-producingzone consists of sand, shell, and relatively thin bedsor lenses of sandstone/limestone. The less permeablezone is delineated as a sand, silt, shell and softmicritic limestone portion of the TamiamiFormation.

Generally, the surficial sands range inthickness between 20 to 40 feet. These sands havelow to medium permeability and may produce smallquantities of water (Lichtler, 1960). These sandsrange in size from very fine to coarse with fine grainbeing prevalent. Also included in this zone is organicmaterial including "hardpan" units and interbeddedlenses of sandy clay and silt.

The major producing zone ranges in thicknessfrom 20 to 250 feet, averaging approximately 130 to150 feet. The producing zone is capable of providingrelatively large quantities of water depending onaquifer characteristics. Transmissivity is the termrelated to the water-transmitting capacity of theaquifer at a site. Values of transmissivity for 53 sitesin Martin and adjacent counties, were collected fromvarious agencies and consultant reports. Of the 53tests, 37 were used to generate input data sets for themodel (see Table 1 and Figure 5 which includes onlythose tests that were used), while the remainingtests were not used due to questionable data or lackof documentation. In general, transmissivity valuescountywide are around 4,000 ft2 /day (30,000 gpd/ft)but increase to the east and south, withtransmissivity values of over 13,000 ft2 /day (100,000gpd/ft) at the Martin/Palm Beach County line alongthe coast. The permeable limestone and sandstonestrata are more prevalent towards the east (Lichtler,1960) and the thickness of this zone is greater in thisarea. However, in the Stuart area, located in thenortheast part of the model, transmissivities remainaround 4,000 to 6,700 ft2 /day (30,000-50,000 gpd/ft).This lower transmissivity, when compared to theother coastal area values in the model area, may bedue to the higher clay percentage within the aquiferin this area (Miller, 1978).

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The less permeable zone found below the mainproducing zone is significant in its ability to storewater and release it to the producing zone if needed.Wells completed in this zone do not often yield usefulquantities of water as the presence of silts andfine-grained, poorly consolidated limestones reducesits transmissivity. The base of this zone was definedas that point where the percentage clay contentbecame significant enough to essentially prevent therelease of water to wells or the producing zone.

MODEL DESCRIPTION

OVERVIEW

In this study, the U. S. Geological Surveymodular three-dimensional finite-difference groundwater flow model code (McDonald and Harbaugh,1988), commonly known as MODFLOW, was used.This model code was selected for the followingreasons:

1. It is available in the public domain,

2. It is compatible with most computers with onlyminor modification,

3. The modular structure of the code and itsexcellent documentation allow easy modifi-cation of the code and the addition of newmodules for specialty applications,

4. MODFLOW allows great flexibility of data filestructure and management; this facilitates theemployment of and interaction with othersoftware for data manipulation,

5. The cell-by-cell flow feature of the code can beused to:

A. Evaluate in detail flow and head changesassociated with various withdrawalscenarios, and

B. Generate boundary conditions forhigher-resolution models within theregional flow model, and

6. It can be coupled with currently available non-density dependent solute transport models.

The hydrologic properties or conditions whichthe model can represent include:

* The aquifer properties of hydraulic conductivityor transmissivity, storage capacity, and verticalconductance.

* Initial water level conditions.* Recharge.* Evapotranspiration (ET).* Rivers and drains. Rivers can both drain and

recharge the aquifer, depending on therelationship of river and aquifer heads; drainsdo not recharge.

* Wells, as either discharge or recharge.

Three iterative solution schemes are available forsolving the finite difference equations governingflow in porous media: slice-successive overrelaxation (SSOR), strongly implicit procedure (SIP),and the preconditioned conjugate gradient (PCG)method (Kuiper, 1987). The SIP method was used inthis study and after adjusting the accelerationparameter down to 0.5, it worked well. SSOR is thebetter solution method for some strongly layeredconditions. However, it is not as direct as SIP,therefore, it generally requires more time to arriveat a solution. Table 2 summarizes the modules andtheir application to the Martin County model.

DISCRETIZATION

Discretization is the process of breaking up acontinuous system into a set of discrete cells definedby a system of rows in a horizontal plane andcolumns in a vertical plane, to represent the systemnumerically. The study area was discretized into ahorizontal grid comprised of 2,000 ft2 cells,assembled into a grid of 59 rows and 109 columns(Figure 6). The westernmost five columns of cellswere expanded into Okeechobee County as shown inFigure 4 to provide a buffer zone.

The Martin County model contains three layers(Figure 7). The layers were determined by lithologyfrom 224 wells. Locations, information source andbreakdown into model layers for each well used inthis study, as well as structure contour maps, can befound in Appendix A. Layer one, beginning at landsurface, consists of fine sand, silt and organics; layertwo is made up of sand, shell, and mostly thin layersof limestone/sandstone with little or no fines; andlayer three is similar to layer two but containssilt/clay and the limestone is generally soft andmicritic: In coastal areas, there are some minorconfining units which define additional layers;however, they pinch out quickly to the west and werenot considered significant on a regional scale. Thesurficial sands, generally in the eastern portion ofthe county, contain one or more "hardpan" units(layers of low permeability composed primarily offine sand and organic material) within a few feet ofland surface. In the Hopkins (1991) study of theJensen Beach Peninsula, the hardpan, wherepresent, was found to vary greatly in thickness anddepth over very small distances. It was assumed thatthis variability would occur throughout the county;

TABLE 2.PACKAGES IN MODFLOW USED IN THE MARTIN COUNTY MODEL

MODFLOW PACKAGE FUNCTION USE IN MODEL

BASIC Model Administration Used

BLOCK CENTERED Computation of conductance UsedFLOW and storage components of

finite-difference equations.

RIVER Simulates effects of river Used to represent C23, C44, L8,leakage. Rivers may L47, L63, L64, L65, C59, Intra-recharge or drain the aquifer coastal, salt/brackish Loxa-depending on the head hatchee, C18, St. Lucie River,gradient between the river controlled drainage districtand the aquifer. canals in Jupiter wellfield area.

RECHARGE Simulates recharge to the Used with measured precipi-aquifer from infiltration of tation: a pre-processor programprecipitation, calculates losses to interception/

evaporation and runoff.

WELL Simulates a source/sink to Used to represent discharge fromthe aquifer that is not public water supply, domestic selfaffected by heads in the supply, and irrigation water use.aquifer.

DRAIN Simulates discharge from the Used to represent all drainageaquifer to drains, district canals with unmain-

tained water levels, all grovecanals, ranch canals, upstreamSt. Lucie River & Forks,upstream Loxahatchee River &Forks.

EVAPO- Simulates evapotranspir- Used modified Blaney-CriddleTRANSPIRATION ation where the source of calculation: coefficients estima-

water is the saturated porous ted by land use types.medium.

GENERAL HEAD Simulates a source/sink of Used along all model boundaries,BOUNDARY water providing recharge/ and to represent Lake

discharge to the aquifer at a Okeechobee, Atlantic Ocean, Strate proportional to the head Lucie & Jupiter Inlets, FP&Ldifference between the Reservoir.source/sink and the aquifer.

STRONGLY IMPLICIT Solves the model's finite UsedPROCEDURE difference equations using

(SIP) the Strongly ImplicitProcedure.

OBSERVATION Generates a file of computed Used to generate comparativeNODES water levels for selected hydrographs and calibration

model cells. agreement.

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medium quartz low permeabilitysand with silty . . . low permeability

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limestone intervalto well cemented

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Lithologic Types and Corresponding Model Layers

and moderate---- 1 .I

FIGURE 7.

therefore, these units were not specifically includedin the model. Layer one thickness values rangedfrom 15 feet to 75 feet, layer two thickness from 20feet to 262 feet and layer three thickness from 15 feetto 139 feet.

BOUNDARY CONDITIONS

The function of boundaries is to impose tneffects of the external regional flow System on thmodeled area. Several types of boundary conditionare available in MODFLOW including prescribehead and prescribed flux. Constant head boundarieswhere the head at the boundary remains constant fothe model duration, are one example of a prescribeihead boundary. Prescribed flux boundaries are use(when there is a flux which changes with time at thiouter edges of the boundaries. No-flow boundariesare a type of prescribed flux boundary where the flowregime is such that flow across the boundary is notexpected to occur. In head-dependent fluxboundaries, the flux is dependent on the head in thecell and the head assigned to the external source.Head-dependent fluxes in MODFLOW includegeneral head boundaries, rivers, drains andevapotranspiration. With prescribed head, anothertype of head-dependent flux boundary, the flux canbe as large as needed. A no-flow boundary is implicitalong the outer edges and bottom layer of the model.

The general head boundary package was usedto generate head-dependent flux and prescribed headboundaries. According to McDonald and Harbaugh(1988), a general head boundary consists of a watersource outside the model area which supplies orremoves water to a model cell at a rate proportionalto the head difference between the source and thecell. A horizontal conductance term is also includedin the general head flow calculation and its value isinitially based on the length, width, sedimentthickness and horizontal hydraulic conductivity ofthe cell (see Figure 8). A dimensionless calibrationfactor is included when necessary.

The Atlantic Ocean borders the entire easternedge of the model, and Lake Okeechobee bordersmost of the western edge. These two large waterbodies provide a constant source of water which canbe considered a head dependent flow boundary.Measured water levels in Lake Okeechobee variedfrom 11.31 to 14.27 feet NGVD in 1989 and theAtlantic Ocean varied from a low of -0.07 feet NGVDin June to a high of 1.35 feet NGVD in October. Thegeneral head package was used to represent theseboundaries because of its flexibility to vary heads. Inlayer one, the boundary cells are in direct contactwith the ocean or lake. Accordingly, horizontal

conductance values were set large enough to providean unlimited source/sink of water, thereby acting asa prescribed head boundary. Conductances for theseprescribed head cells were calculated using thefollowing formula (see Figure 8 forconceptualization).:

KLW *mulitiplierM

is where

, K = layer one hydraulic conductivity (ft/day)r L= layer thicknessd W= width of column

S M= 1multiplier= 2,000 (used as a calibration

parameter)

As previously discussed, flow between thegeneral head and the cell containing it is controlledby the conductance term and head differences.Layers two and three represent fully saturatedaquifers and were assumed not to be in direct contactwith the ocean and lake; therefore, conductanceswere calculated based on the transmissivity of thecell. General head conductances were calculatedusing the following formula (see Figure 8 forconceptualization):

TW

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where

T= transmissivityW= width of cell containing general head and

adjoining active cell faceM= distance from edge of cell adjacent towater source and center of cell

The C-23 canal and the St. Lucie River andInlet are assumed to act as ground water dividesalong the northern edge of the model and are,therefore, used as boundaries. In a strict sense, theC-23 canal is not a true divide since it verticallypenetrates only a small part of the aquifer. However,observed water levels indicate that the canal isacting as a divide under current non-stressedconditions. Significant stress on the aquifer near theC-23 canal could cause flow under the canal; themodel's boundary should be adjusted accordingly ifsuch stresses occur or must be simulated. The C-23canal is represented by river cells in layer one and bygeneral head cells in layers two and three (those cellsdirectly beneath the 0-23 canal) (see Figure 8). Thegenera] head cells were used to simulate conditions

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outside the model, therefore, head values werematched to water levels on the other side of C-23 inSt. Lucie County. Conductances of the general headsare equal to the transmissivity of the cell. The C-23canal runs most of the length of the northern modelboundary except for the six westernmost miles of theMartin/St. Lucie border, and the six miles in theOkeechobee County portion of the north modelboundary. There are no specific hydraulicboundaries along this northwest corner of the model.However, water level contour maps indicate thatflow is occurring either in or out of the model alongthis boundary. There is a relict beach ridge just westof the western end of the C-23 canal which causes aground water gradient into the Martin model. Usingstatistically generated water level maps, head valuesalong the boundaries were approximated and theseapproximations were input as general heads. Theapproximated head value for each cell was used forall three layers and for all stress periods. Furtherrefinements could be made in this area if more datawere available. General head conductances forlayers two and three were calculated using equation2, and conductances for layer one, west of the C-23canal, were calculated as follows:

KL WM (3)

where

K= hydraulic conductivity of cell (ft/day)L= length of face along general head cell and

adjoining active cellW = layer one thickness minus five feetM= distance between outside source water

level and center of general head cell

The five feet subtracted from the layer one thicknessnumber represents a countywide averageunsaturated zone thickness.

The southern boundary of the model was basedon a need to extend far enough into Palm BeachCounty to insure validity of the model at theMartin/Palm Beach county line. The boundary waslocated midway between the cones of influence of theTown of Jupiter and Seacoast Utilities wellfields.The southwest portion of the model boundaryincludes the Corbett Wildlife Management Areawhere water levels are flat for great distances. Someareas along the boundary do meet the no-flowdefinition, however, in order to simplify theboundary file by making cell types the same, allsouthern boundary cells contain a general headsource/sink. Using statistically generated waterlevel maps, head values along these boundaries were

estimated, and these estimations were input asgeneral heads. The estimated head value fur eachcell was used for all three layers and for all stressperiods. Constant head cells could also have beenused, however, constant head cells do not provide theconductance term which can be used to calibrate thesimulated sources and sinks outside the modelboundaries. Equation 3 was used for layer one andequation 2 was used for layers two and three tocalculate the general head conductance term.Locations of the various boundaries can be found inFigures 9 and 10.

HYDRAULIC CHARACTERISTICS

The Surficial Aquifer System is heterogeneousand anisotropic as a result of its widely variedcomposition. The system is composed of sand orsand/shell layers with intermixed thin to fairlycontinuous limestone/sandstone beds. Hydraulicconductivities in the system estimated from pumpingtests range from 25 to 180 ft/day with an averagevalue of 50 ft/day.

The system was divided into three hydraulicconductivity zones for modeling purposes: a lowpermeability zone representing the uppermost finesand/silt lithology; a zone of intermediatepermeability representing the production zonetapped by most wells; and another low permeabilityzone representing the remainder of the system.

Transmissivity/Hydraulic Conductivity

MODFLOW requires that each layer of a modelbe classified as either confined, unconfined or somecombination of the two. All three layers of the modelare part of an unconfined system, however,MODFLOW only allows one layer be designated asunconfined. For this reason, layer one was defined asunconfined, layer two was defined as confined/unconfined and layer three was designated asconfined (since the entire thickness of layer threewill always be completely saturated). Thesedesignations determine how heads are calculated ineach layer. In an unconfined layer, transmissivity iscontinually recalculated as a function of hydraulicconductivity and the saturated thickness of thelayer. Storage is determined from specific yield.Under the confined/unconfined designation, it isassumed that the majority of the layer will remainsaturated throughout the simulation, sotransmissivity is not continually recalculated. Thislayer type requires the input of both a specific yieldand a storage coefficient, so that the appropriatestorage factor may be used depending on if it isconfined or unconfined. In the confined designation,

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transmissivity and storage coefficients are keptconstant for the entire simulation.

Layer One. MO)FLOW calculates thetransmissivity of unconfined aquifers by multiplyingthe hydraulic conductivity by the saturatedthickness of the aquifer. Initial saturated thicknessis calculated from the starting head and aquiferbottom data, both of which are required input for anunconfined aquifer. Head changes throughout thesimulation result in changes in the calculatedtransmissivity in an unconfined aquifer. When thesimulated head in a cell drops to a level at or belowthe aquifer bottom elevation, the transmissivity ofthe cell becomes zero, resulting in the cell "goingdry" and becoming inactive for the remainder of thesimulation.

Little data exist on the hydraulic conductivityof zone 1 (layer one) of the Surficial Aquifer Systemin Martin County. Originally a single hydraulicconductivity value of 20 feet per day was chosen.When a soils map with differing values of verticalhydraulic conductance was created for anotherpackage in MODFLOW, the distribution and rangeof values seemed reasonable for use as a layer onehydraulic conductivity array. Table 3 lists thevarious soil types in the model area and theconductivity used for each type. Values range from 3feet/day in sloughs and river beds to 47 ft/day alongthe coastal dunes, with a large portion of the countybeing 12 ft/day. A weighted conductivity value basedon the percent of each soil type in the cell wascalculated. A contour plot of the conductivity arraycan be found in Appendix B.

There are conceptual problems with thismethod since soil profiles are generally very shallowand the permeability values reported indicate therate of downward flow rather than horizontal flow.However, the hydraulic conductivity values thatwere calculated were in a reasonable range for layerone. According to various hydrogeology texts(Driscoll, 1986; Todd, 1980), hydraulic conductivityin fine to silty sands, similar to layer one in MartinCounty, ranges from 0.03 to 32 feet/day. The modelcalibration improved when the soil conductivityarray was substituted for the single value. Clay andhardpan layers, which are present, were notdiscretized into separate layers because of theirdiscontinuous nature but are taken into account inthe lower hydraulic conductivity values.

Layer Two. The transmissivity grid for layertwo was developed by a two-step process.Transmissivity values obtained from numerouspump tests throughout the study area were divided

by production zone thickness to obtain hydraulicconductivities. These values were then regiunalizedusing a kriging interpolation technique whichestimates a value for each cell based on the existinginformation available, and the resulting array wasmultiplied by another regionalized array of layerthickness values from numerous drilling logs. Theresulting array has a range of transmissivity from440 ft2/day to 26,572 ft2/day See Appendix B for acontour plot of transmissivity. The two-step processwas preferred over just regionalizing pump testtransmissivities because knowledge of aquiferthickness, which varies significantly, yielded a moreaccurate regional transmissivity array.

Layer Three. No aquifer performance testsspecific to layer three were found. Therefore, thetransmissivity array for this layer was created bymultiplying the layer three thickness array by aconstant hydraulic conductance of 20 feet/day. Thisresulted in transmissivity values between 200ft2/day to 5,560 ft 2/day. After sensitivity runs, bettercalibration in the area generally east of the FloridaTurnpike was made by doubling the transmissivityvalue. However, in the Tequesta area, the originallycalculated tranismissivity calibrated better and waspreserved. Contour plots of transmissivity arrayscan be found in Appendix B.

Storage and Specific Yield

A single value of 9.0 X 10-4 was used for storagefor layers two and three, based on the average valueof pump tests performed in the study area. Repeatedmodel runs at various storage values showed it to berelatively insensitive within the range reported fromthe pump tests.

Specific yield is that percentage of the totalvolume of water in a saturated rock that will drainby gravity and thus be available to wells. Johnson(1967) compiled specific yield values based onlaboratory analysis for elastic sediments rangingfrom clay to coarse gravel. His findings showedspecific yields for sandy clay to coarse sand rangedfrom 0.03 to 0.35 percent. Specific yield for layer onewas set at 0.2 which represents the average value forthe mostly fine sediments that comprise layer one.Subsequent testing of different values from 0.18 to0.22 showed the model to be fairly insensitive withinthe range tested.

Vertical Conductivity

There is little information on the verticalhydraulic conductivity of the Surficial AquiferSystem in the study area. Todd (1980) states that the

TABLE 3. SOIL TYPES AND CORRESPONDING VERTICAL HYDRAULICCONDUCTIVITY AND CAPILLARY FRINGE HEIGHT

Value Used in Model CapillarySoil Type Conductivity F i

(ft/month) Fringe Heightft/month ft/day (feet)

Basinger > 1,200 1,400 46.7 1.0

Basinger-Ft. Drum Valkaria 360-> 1,200 1,400 46.7 1.0

Bessie-Okeelanta Var-Terra Ceia Var 120-1,200 360 12 1.0

Chobee-Gator 12-120 360 12 3.0

Floridana-Jupiter-Hilolo 12-1,200 360 12 1.0

Immokalee-Pompano > 380 390 13 1.0

Myakka-Basinger > 380 390 13 1.0

Myakka-Immokalee-Basinger 360-> 1,200 600 20 1.0

Nettles 60 60 2 1.0

Okeelanta-Canova Var Floridana 120-360 360 12 1.0

Okeelanta-Delray-Pompano > 380 390 13 1.0

Pahokee 360-1,200 780 26 1.0

Palm Beach-Canaveral-Beaches >1,200 1,400 47 1.0

Palm Beach-Urban Land-Canaveral >1,200 1,400 47 1.0

Pompano-Charlotte-Delray > 380 390 13 1.0

Pomello-Immokalee 360 360 12 1.0

Pineda-Riviera 360 360 12 1.0

Pineda-Riviera-Boca 360 360 12 1.0

Paola-St. Lucie > 1,200 1,400 47 1.0

Ri viera 360 360 12 1.0

Riviera-Boca 360 360 12 1.0

Salerno-Jonathan-Hobe 420-900 660 22 1.0

St. Lucie-Urban Land-Paola >1,200 1,400 47 1.0

Torry 36-120 78 3 3.0

Terra Ceia 360-1,200 780 26 1.0

Waveland-Lawnwood Basinger 12-> 1,200 800 27 1.0

Winder-Riviera 360-480 360 12 2.0

Wabasso-Riviera-Oldsmar 360 360 12 1.0

Winder-Tequesta 360-480 360 12 1.0

Wabasso-Winder 360 360 12 1.0

anisotropy ratio for horizontal to verticalconductivity usually falls between 2 and 10 foralluvial deposits but may range upwards of 100 ifclay is present. Vertical flow in the model is afunction of the vertical leakance (Veont), the cellarea and the head difference between layers. Valuesof Vcont were obtained by using the MODFLOWcalculation for vertically adjacent geohydrologicunits which is as follows:

1

Thickness of upper layer/2 . Thickness of lower layerl2

(Hydr. K upper layer) * .1 (Hydr. K lower layer)* .1

For this model, a kvertical/khorizontal anisotropy ratioof 0.1 was assumed for all zones in the aquifer. In theJensen Beach Peninsula model (Hopkins, 1991),repeated calibration runs resulted in verticalconductance values of approximately a quarter ofthose estimated using the 0.1 anisotropy figurebetween layers one and two, apparently due tovertical impedance to flow caused by fine sands andclay layers at the base of layer one. This situationalso occurs within this model area and calibrationruns indicated a minor improvement in isolatedareas in the eastern portion of the county with alower anisotropy ratio. However, it was difficult todelineate and justify the lower anisotropy areas.Additional research and further refinements to themodel on this subject should be addressed in futureversions of the model. Clay lenses, which arepresent, but not well defined in the aquifer, were notrepresented explicitly in the model since theirdiscontinuous nature gives them a local rather thanregional influence.

SURFACE WATER INTERACTIONS

Canals, rivers and lakes were represented in themodel using either the drain, river or general headboundary packages. The general head boundarypackage was used to represent water bodies alongthe model boundaries, as previously discussed in theboundary condition section. It was also used torepresent the Florida Power and Light (FP&L)reservoir. The river package was used to representall other controlled canals and those canals withfrequent water level data. Uncontrolled canals wererepresented as drains. The location of river anddrain cells in the model can be found in Figure 11.Appendix C summarizes the widths, controlstructure elevations, bottom elevations andmultipliers used for the river and drain reaches.

The river package represents each river/canalreach as a source of water outside the aquifer with aconductance to the aquifer based on river/canal

length, width or wetted perimeter, sedimentthickness and sediment hydraulic conductivitywithin each model cell. Flow between the river andthe aquifer is determined by the head differenceexisting between the river reach and the model cellcontaining it and is proportional to the conductance.Heads in the river reaches are set to the river/canalmaintained level or measured water level collectedby the SFWMD and the USGS. Flow direction maybe either from the river reaches to the aquifer or viceversa, depending on the direction of the headgradient. Thus, river cells may serve as either asource or sink of water with respect to the aquiferwith both flow volume and direction varyingaccording to the head gradients.

The drain package simulates flow in onedirection only, from the aquifer to the drain, whileboth the general head and river packages simulateflow either into or out of the aquifer. The drainconductances are calculated in the same manner asthe river and general head conductances. Flow intothe drains occurs when the simulated aquifer head is

greater than the specified drain elevation. The flowis proportional to the conductance and the differencebetween the aquifer head and the drain elevation.When the elevation of the drain is greater than theaquifer head, no flow occurs. Drains were used in themodel to represent canals where water levels are notmaintained at specified heads. The drain elevationswere usually set to the control structure elevation. Ifthe structure elevation was lower than the canalbottom elevation or there was no control structure,the canal bottom elevation was used for the drainelevation (see Figure 12).

The conductance term is used to represent thestream-aquifer interconnection, which is affected bystreambed material. River and drain conductancesfor a cell were obtained by the following calculationand are illustrated in Figure 12;

KL W, multiplier1' (5)

where

W = width of reachL= length of reachK= layer one conductivity

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requiring a multiplier of 0.001. The drain reachmultipliers ranged from 0.001 to 0.1, with most grovecanals requiring a multiplier of 0.01.

The length of river and drain reaches wasmeasured from USGS topographic maps, overlainwith the model grid. The width of river reaches wasdetermined from USGS maps, permit maps, canalsurvey maps or "as-built" drawings by the Corps ofEngineers. When available, the same sources wereused for drain reaches, however, widths for mostgrove canals were estimated based on discussionswith the land owners or their engineeringconsultant.

The Florida Power & Light reservoir is a largewater body within the modeled area with stages thatfluctuate within a small range. It is an above-groundreservoir; therefore, there is some lithologicrestriction to flow between the reservoir and theunderlying water table. The general head packagewas used to simulate the reservoir. Conductanceterms were calculated in the same manner as thosefor river bottom conductances (Equation 5). Themultiplier was varied until modeled leakage valueswere similar to values reported by FP&L. The FP&Lreservoir calibrated conductance calculation is asfollows:

KL W.0 0o2' (6)

where,

K= layer one horizontalconductivity for that cell

L= row lengthW= column width

hydraulic

RECHARGE

Rainfall recharges the Surficial Aquifer Systemover its entire area. Average annual rainfall rangesfrom 50 to 60 inches in the study area (MacVicar,1983). Most of this rain, 38 to 44 inches on average,falls during the wet season from May throughOctober. Average rainfall during the dry season,November through April, is approximately 12 to 16inches. Wet and dry season durations may vary fromyear to year.

For the modeled time period, annual rainfall(amounts observed in any consecutive 12-monthperiod) steadily declined from normal to recordbelow-normal amounts from August 1988 untilAugust 1989 after which it moderated but stayedbelow normal well into 1990 (Trimble, et al., 1990).

For 1989, average annual rainfall from stations inthe study area was 44 inches, ranging from 24 to 57inches for individual stations. Wet seast,n rainfallranged from 12 to 43 inches, averaging 31 inches anddry season rainfall amounts ranged from 9 to 21inches, averaging 14 inches.

Rainfall events in south Florida are oftenlocalized, particularly in the summer months whenconvective thunderstorms are common. Frequently,these events are very intense and of short duration.In winter months, however, frontal systems andoccasional tropical depressions (hurricanes) providemore evenly distributed rainfall over the study area.Because of the variable nature of most rain events.there are an inadequate number of rain stations toprovide a completely accurate distribution ofrainfall. Daily rainfall data collected from 41stations were used in creating the recharge arrays.Appendix D includes information on each station aswell as a station location map.

Recharge is calculated as a function ofinterception, depression storage loss, and surfacedrainage.

The following summarizes the preprocessingsteps taken to create the recharge arrays:

1) assembled daily rainfall totals from numerousstations throughout the study area collected byfederal and state agencies, grove operators,utility operators and golf courses;

2) assuming one precipitation event per rainy day,0.11 inches from that event was removed andsummed for each month as depression storage;

3) the monthly depression storage is subtractedfrom the monthly total rainfall and theremaining recharge was contoured using theinverse distance method to determine a valuefor each model cell;

4) the resulting arrays were further reduced toremove interception water based on land usetype, runoff to surface drainage based on slope,and hydraulic conductivity of the soil (seeFigure 13 for land use types in the model area;the calculations for interception and runoff canbe found in Appendix D);

5) added to the final recharge arrays was 50percent of the irrigation water withdrawn byflood irrigated agricultural operations in theappropriate cells.

_ __~_

For a detailed discussion of the rechargecalculations, please refer to Appendix D.

The flood irrigation recharge figure is based onassumptions made in the SFWMD Water Use PermitInformation Manual (SFWMD, 1985) that in floodirrigated projects 50 percent of the water applied isused by the crop. To be consistent, all irrigationprojects that are not 100 percent efficient shouldreturn some water as recharge to the first layer ofthe model. Due to current limitations, it was toodifficult to calculate the contribution to each modelcell for each irrigation project; therefore, only theflood irrigated projects were included. Figure 14illustrates the model cells to which irrigationrecharge was added.

The net recharge, after all subtractions fromrainfall have been made, for a single steady statemonth is shown in Figure 15. Because of the numberof variables involved in determining what portion ofrainfall would actually recharge the aquifer, theratio of rainfall to recharge varies widely throughoutthe county (Figure 16). However, a check of the ratiofor broad land use types in the month with the least(February) and most (August) rainfall in 1989provides some information. In February, theaverage calculated rainfall/recharge ratio for urbanareas was 41 percent; for agricultural areas, 43percent; for forested areas, 51 percent; and forwetland areas, 48 percent. In August, the ratioswere 53 percent for urban, 59 percent foragricultural, 62 percent for forested and 62 percent ofrainfall for wetlands. As mentioned previously,these are averages and the ratio for any given celland land use type ranges from zero to 98 percent ofrainfall based on the many variables included in thedetermination.

The recharge term used in MODFLOWrepresents water that actually reaches the aquifer.In areas where there is a significant unsaturatedzone above the water table, the above rechargecalculations become inaccurate. An additionalportion of the calculated recharge never reaches theaquifer because of the large soil storage capacity inthe unsaturated zone. Dune area plants will satisfytheir water needs from the soil water and never usewater from the aquifer itself. Therefore, in cellswhere there was 16 to 20 feet of unsaturated soil,recharge to the aquifer was reduced by half, and incells with unsaturated zones of 20 feet or more,recharge was reduced to zero, which improvedcalibration. The recharge reduction figures, basedon thickness of the unsaturated zone, were not basedon specific scientific data, but on calibration results.A scientific approach for more exact determination of

the recharge prevented from reaching the aquifer bya significant unsaturated zone above should beexamined. Figure 14 illustrates the model cells inwhich recharge was altered.

EVAPOTRANSPIRATION

Evapotranspiration (ET), water loss throughevaporation and plant transpiration, is the largestmechanism for ground water loss from the system.ET is a complicated process controlled primarily byweather, vegetation, soils, and water availability.There are numerous methods available to estimateET using different combinations of factors. Themodified Blaney-Criddle method was used in thismodel to estimate the potential evapotranspirationrate.

The modified Blaney-Criddle method is basedon the principle that ET is proportional to theproduct of day length percentage and mean airtemperature and incorporates crop type as it relatesto the ET estimate for grass (Jensen, 1980).

Water loss from the saturated ground waterregime through direct evaporation and throughtranspiration from the saturated zone by plants issimulated in the model by the Evapotranspiration(ET) Package of MODFLOW. The followingassumptions are applied (McDonald and Harbaugh,1988):

1) When the water table is at or above a specifiedelevation, termed "ET surface", ET loss fromthe water table occurs at a specified maximumrate.

2) When the water table elevation drops below aspecified value, termed the "extinction depth"or "root zone", ET from the water table ceases.

3) ET from the aquifer varies linearly between theabove limits.

The evapotranspiration from the unsaturated zone isnot considered at this point but modifications to thecode are currently under development at SFWMD.

The ET surface elevation is represented in themodel by the average land surface elevation in eachcell minus the capillary zone height for that cell (seeFigure 17 for conceptualization), Land surfacevalues were taken from USGS 7.5 minutetopographic quadrangle maps. Because of the modelcell sizes, there is only one elevation for each 2,000by 2,000 foot area and it represents the averageelevation within that cell. In most areas, there was

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only a one or two foot difference in elevation within acell. However, in some areas, the elevations changedas much as 20 feet within a cell and the averagevalue will not represent conditions throughout theentire cell. The consequences of land surfaceaveraging is discussed in the calibration section.The ET surface was then altered ±2.5 feet forspecific cells during the calibration process.

Capillary rise is a function of soil grain size andcan vary from 0.38 centimeters in a coarse gravel to 3meters in clay (Fetter, 1980). Noting the sandy,clayey soils in the modeled area, it was assumed thata significant volume of water would be lost by ET inthe capillary fringe. Since MODFLOW does notaddress ET that occurs when the water table dropsbelow the root zone, capillary fringe ET wasapproximated by reducing the original ET surface(land surface) by an amount equal to the capillaryfringe height. The height (Table 3) was determinedby soil type, and an array of capillary fringe heightswas created. To be physically accurate, the capillaryzone height should be added to the water table level,however, since the water table changes with time,this raising of the available water level would needto be incorporated in the MODFLOW program. Asimplifying assumption was adopted for calculationpurposes by moving the ET "window" down by anamount equal to the capillary zone height.

Where water bodies were present, the freewater surface evapotranspiration rate was used. Forall other areas, the maximum ET rate was estimatedusing the modified Blaney-Criddle equation. Thebasic form of the equation is:

P tU=kk mm

to100

where,U is the crop ET for a given month, in inchesper day from layer 1,k is a consumptive use coefficient which variesaccording to the crop, type and growth stage,kt is a climatic coefficient which is related tothe mean air temperature;kt = .0173t - .314, where t is Fahrenheit

temperature,Pm is the percent of daytime hours of the yearwhich occurred during the month,tm is the mean temperature for the month, indegrees Fahrenheit.

The consumptive use coefficient is defined:

where,kc is a coefficient reflecting the growth state ofthe crop (Table D-4, Appendix D), andkf is a coefficient reflecting the fraction of landsurface which is covered with a specific type ofvegetation (also Table D-4) it varies between0.1 and 1.0.

Temperature data was used from stations inStuart, Jupiter and Indiantown. Crop coefficients(ke) were either taken directly from or inferred fromvalues presented in SFWMD's Permit InformationManual Volume III (SFWMD, 1985). Values of kf forurban land uses were determined by examination ofsurface water permit data for ratios of pervious toimpervious area.

Extinction depth physically represents thedepth to which the roots of plants extend below landsurface and is determined in MODFLOW as thedepth of the water table below the ET surfaceelevation beyond which evapotranspiration ceases.Extinction depths in the model are related to landuse and are based on estimated root depth for variouskinds of vegetation supplied by the District'sPlanning Department (Teets, 1990, personalcommunication). A table with values used can befound in Appendix D.

The MODFLOW evapotranspiration packageremoves water from the aquifer up to the maximumET rate specified. If the aquifer head is below theroot zone extinction depth, the model does notremove any ET. In groves, for example, drainagecanals are designed to keep the root zone drained.Consequently, the model does not remove any waterfrom the aquifer to ET in most grove canals. This is avalid approximation since the water removed byevapotranspiration in a grove is mostly provided bydrip irrigation rather than from the aquifer itself. Indune areas also, the aquifer head is significantlylower than the root zone extinction depth, so no ETwater is removed from the aquifer. However, asdiscussed above in the recharge section, these duneplants do transpire using recharge water retained assoil moisture which then never reaches the aquifer.These are all examples of situations which precludethe use of reported evaporation data withoutsignificant alteration. It becomes apparent thatMODFLOW currently is not capable of a fullaccounting of all recharge and evapotranspirationtaking place and users should be aware of the

k =k * k

limitations and adjustments that should be made toinput data sets.

GROUND WATER USE

Water use figures for the model weredetermined using data from water use permits issuedby the SFWMD. Individual water use permits arerequired if the average daily water use equals orexceeds 100,000 gallons per day (gpd). An individualwater use permit is also required of smaller uses(average daily use exceeding 10,000 gpd) in ReducedThreshold Areas (RTA). The Stuart and LighthousePoint (north of Palm City) areas are designatedRTA's (Figure 2). The SFWMD also issues generalwater use permits to all uses less than 100,000gallons per day, with the exception of single familyhomes, duplexes, and water used strictly forfire-fighting (SFWMD, 1985).

General water use permits were included in thedetermination of water use for the model because thetotal amount covered in general permits could besignificant considering the hydraulic conductivity ofthe aquifer. All legal uses of water, no matter howsmall, are important from a management standpointbecause they are protected by the District's water userules from adverse impacts caused by other waterusers. Therefore, impacts to the smaller users canaffect larger users, requiring reduced withdrawals ormitigation of the adverse impacts. This can be ofcritical importance during the management ofcompeting uses.

The permits were used to determinewithdrawal facilities, water use type, project size andproject location. The permit allocation was not usedin the model, as it does not necessarily equal theactual use. For example, in public water supplypermits, the allocation covers a ten year periodduring which pumpage increases gradually withincreasing population. In agricultural areas, somefacilities and planted acreage may be proposed andnot installed during the model period. Therefore,wherever possible, actual use was input to the model,and all estimated uses were based only on existingfacilities and planted acreage.

Agricultural

Agricultural water use accounts for 27 percentof the ground water well withdrawals in the model.This category includes all farming, golf, recreational,landscaping and nursery uses. Records of waterwithdrawn for agricultural uses are submitted to theSFWMD for a small percentage of the projects.Where these records were available, the informationwas input directly into the model. Where sufficient

information was not available, irrigation applicationrates were estimated. The irrigation waterrequirements of different crops was estimated usinga method described by the U.S. Soil ConservationService (USDA, 1970). This method uses themodified Blaney-Criddle formula to estimate thewater requirements of various crops. Crop type, soiltype, air temperature, daylight hours, effectiverainfall, and irrigation system efficiency are used tocalculate the irrigation requirements of differentcrops found throughout the modeled area.

Data on all agricultural water uses withindividual and general water use permits wasassembled into a spreadsheet. This informationincluded crop types, acreage, irrigation system data,well information, and soil types. Precipitation datafrom the closest station (Stuart, Indiantown orJupiter) was used to determine effective rainfall.The irrigation requirements for each permitted usewere estimated for each month of the calibrationperiod (January 1989 through December 1989). Themonthly irrigation requirement for each permitteduse was distributed among the permitted withdrawalfacilities in proportion to their pump capacities.Individual wells were then assigned to the propermodel cell.

Fourteen landscape irrigation permits thatreport pumpage to the SFWMD were compared to themodified Blaney-Criddle estimates for each project.On average, Blaney-Criddle overestimatedirrigation requirements in April through August andunderestimated in October through March,estimating only half of what was actually beingpumped by users in January and February. TheBlaney-Criddle supplemental crop requirementswere adjusted according to these findings (Table 4)and these adjusted requirements were used for alllandscape irrigation uses where actual pumpage wasnot available.

Several crop types were either not included oronly reported pumpages were used, rather thanBlaney-Criddle estimates. Withdrawals fromsurface water sources were not considered. Pastureallocations were not included because they aregenerally irrigated from surface water sources andsince runoff water is usually held in pasture ditchesby control structures, supplemental water is rarelyneeded. The Blaney-Criddle formula is difficult touse for nursery irrigation requirements, therefore,all nurseries were contacted and actual irrigationpractices were used to estimate withdrawals. Theone large citrus grove in Martin County which usessurficial aquifer water for irrigation maintainspumpage records, which were incorporated in the

TABLE 4. SUPPLEMENTAL IRRIGATION WATER RATES USED TO CALCULATEIRRIGATION OF GRASS (Inches/Month)

STUART

Soil#* Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

.4 2.40 2.54 4.15 2.52 3.50 3.38 3.83 2.55 3.01 3.27 2 98 2.14

8 2.09 2.25 3.85 2.38 3.26 3.00 3.47 2.33 2.43 2.41 2.79 1.95

1.5 1.64 1.84 3.43 2.18 2.93 2.45 2.95 2.01 1.58 1.19 2.53 1.65

JUPITER

Soil#* Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

.4 1.71 2.75 4.08 2.64 3.22 3.47 3.90 2.45 3.07 2.03 2.55 2.38

.8 1.25 2.46 3.75 2.52 2.97 3.13 3.58 2.22 2.47 0.97 2.30 2.16

1.5 0.59 2.03 3.30 2.34 2.61 2.63 3.11 1.89 1.62 0.50 1.95 1.84

INDIANTOWN

ADJUSTMENT FACTOR - 1989 records from 14-19 permits.

Calculation: Supplemental irrigation rate * irrigated acres/irrigated system efficiency*Soil # maps for each county in the SFWMD can be found in Permit Information Manual Volume III

model. Almost all other groves primarily use surfacewater with Floridan Aquifer augmentation in a fewgroves. All small vegetable growers were alsocontacted and actual irrigation practices were usedto estimate irrigation withdrawals. For uses notcurrently permitted by the SFWM D but visible onUSGS quad maps, the owners were contacted forfacility information which was then incorporatedinto the model.

Agricultural water use data is presented inAppendix E. Figures 18 and 19 show the distributionof cells with well withdrawals for layers one and two,respectively. Layer three did not contain any wellwithdrawals.

Pu blic Supply

Public water supply (PWS) withdrawalsaccount for 24 percent of the total modeled groundwater well withdrawals. Ground water withdrawalsfor PWS were obtained from pumpage informationroutinely furnished to the Florida Department ofEnvironmental Regulation (FDER) by the waterutilities. These reports provide total raw waterpumpage for the entire wellfield. Since manywellfields in Martin County are distributed overseveral model cells, individual well discharges wereused whenever possible. If there were multiple wellsin a wellfield and individual well pumpages were notavailable, total pumpage was divided among thewells based on the individual well capacities ofroutinely active wells. Model cells containing publicsupply withdrawals are shown in Figure 20. Thelocation of PWS wells used in the model, along withinformation on withdrawals, can be found inAppendix E.

Domestic Self-Supply

Domestic self supply accounts for 45 percent ofmodeled ground water well withdrawals. Thiswithdrawal type covers all non-potable (outdoor) andpotable (indoor) water use not supplied by a utility.While potable uses are fairly well documented, thereis a lack of data in the area of non-potable water use,because the majority of non-potable water is selfsupplied and pumpage records are not maintainedfor the majority of private wells being used forirrigation (Opalat, 1985). In developing an urbanwater demand model for Martin County, Opalat,1985, describes a method of determining residentialnon-potable demand. The methodology involvesdeveloping figures for each land use type taking intoconsideration allowable unit density, percentage ofunits having automatic irrigation systems, andirrigation application rates and frequency. Model

cells containing urban land use types, and thereforehaving the potential for domestic self-supplywithdrawals, are shown in Figure 21. Table 5summarizes the assumptions made for each urbanland use type. Land use information collected in1986-1988 was used and no adjustments for partialbuildout were made.

Once the locations of different urban land usetypes were determined, the areas were furthersubdivided into large utility supplied, small utilitysupplied and self supplied (Figure 21). Types ofwater use were broken into three categories:irrigation by automatic sprinkler system, irrigationby hand watering (garden hose), and indoor wateruse. In areas where water is utility supplied, anyhand watering was assumed to come from the utilitywater.

Model results indicate that potable demandbreaks down to 32 percent from large utilities, threepercent from small utilities and 64 percent selfsupplied. A figure of 120 gallons per capita per daywas used in the potable demand estimates. Thisfigure is based on water use information published inthe 1983 City/County Data Book (USDC, 1983).

It was assumed that all non-potable water usenot supplied by a utility came from ground waterwells rather than canals. This assumption is basedon the fact that there are very few fresh water canalsin urban areas of Martin County and coastal PalmBeach County. The Jupiter Farms area in PalmBeach County does have a fresh water canal systembut all the houses have wells for drinking water so itwas assumed that irrigation water would also comefrom these wells. In addition, the lots are large inJupiter Farms and houses may be a considerabledistance from the canals.

The irrigation figures resulting from the landuse method then were compared to irrigationdemand using the modified Blaney-Criddlecalculation for the same acreage of grass. The landuse method estimated water use to be 1.6 times whatBlaney-Criddle determined to be necessary.However, as discussed earlier in the agriculturalwater use section, reported figures for grassirrigation indicate that Blaney-Criddle is notentirely accurate. Reported actual use on an annualbasis for large-scale landscape irrigation was foundto be an average of 1.3 times what Blaney-Criddlecalculated. This would indicate that the land usemethod of determining self-supply is acceptable.

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TABLE 5. DOMESTIC SELF-SUPPLY ESTIMATE PARAMETERS

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Acres Irrig .5

Sprinkl Units .5

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D.U./Acre .35

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Assumptions:Drinking water -

120 gpcd (1983 City/County Data Book)

Irrigation rate -Sprinkler systems: 3/8" per acre X 3 times/week X 4 weeks per month

Hand watering: 1/4" per acre X 3 times/week X 4 weeks per month

All sprinkler systems use private wells

Formulas:Drinking water:

Acres of land use type * capita per acre * 3600 gpc/m)

Irrigation:Sprinkler sytems: Acres of land use type * # of dwelling units * % of units withsprinklers * acres irrigated per unit * 135762 gallons/acre/month

Hand watering: Acres of land use type * # of dwelling units * (1 - % of units withsprinkler systems) * .5 * acres irrigated per unit * 67881 gal/acre/month

Other Ground Water Uses

Most of the other uses of ground water inMartin County are either industrial ormining-dewatering. The mining-dewatering usesare usually short-term uses which generally requireon-site impoundment of withdrawn water. The onlyconsumptive use in these operations is water lost toevaporation, which is insignificant for a regionalmodel with a coarse grid. Therefore,mining-dewatering uses were not simulated in themodel

There are several industrial use of groundwater in Martin County, including Florida Powerand Light, Pratt and Whitney, and LoxahatcheeRiver Environmental Control District. Permittedindustrial ground water use in Martin County totals136 million gallons per month, or four percent of allmodeled ground water well withdrawals.

CALIBRATION

Calibration is accomplished by comparing theresponse of the actual physical system withmathematical models calculated response to thesame conditions. If they agree, the model is assumedto be calibrated. If not, various parameters in themathematical model are altered until the model is inreasonable agreement with the physical system.

The Martin County model was calibrated toboth steady state and transient conditions. Initialsteady state runs served to make the firstadjustments to the aquifer parameters used in themodel. Once the model was able to run withouterrors, the adjusted aquifer parameter data sets thenwere used in the transient calibration runs, wherethey were refined further. After some refinement,the data sets from the transient calibration wereused in the steady state model, and sensitivityanalysis runs were made. Information from theseruns was input back into the transient model andfurther refinements were made. Finally, the steadystate model was re-run using the data sets from thelatest transient calibration to obtain a final steadystate run.

The calibration period was January 1989through December 1989. This period was chosenbecause it is the most recent period represented byample water level observations. Locations of themonitor wells in each layer used in the calibrationprocess are shown in Figures 22 through 25. Thestrongly implicit procedure (SIP) was the solutionmethod used in the calibration process. Overall, itresulted in a stable solution in an average of 13iterations. The number of iterations was near theinitially set limit of 50 until the "prescribed head"cells, with their large conductance values, wereapplied to the Lake Okeechobee and Atlantic Oceanlayer one boundaries.

TRANSIENT CALIBRATION

Method

Following the initial steady state calibrationrun, a series of transient runs were made to calibratethe model to observed water levels. The transientruns comprised 12 stress periods of one month each.Each stress period contained four time steps.

Starting heads in each layer were calculatedfrom water level data obtained from USGS monitor

wells in January 1989, the first month water leveldata were collected from a new expanded MartinCounty network. These data, along with surfacewater stage data for the same time period, wereregionalized using a kriging interpolation technique,which estimated a head value for every cell based onthe available data. Further refinements to thesearrays were made during calibration runs. Figures26 and 27 are contour plots of the starting headarrays.

The intent was to calibrate so that agreementbetween observed water levels in monitor wells andsimulated water levels in the cells which representthe location of those wells were within one foot ofeach other and that the seasonal water levelfluctuation pattern would be imitated by the model.

Hydrographs comparing observed andsimulated water levels in cells that correspond to thelocations of water level monitor wells weregenerated. These were used to aid in interpretationof the numerous model runs, particularly how thesimulated water levels changed over time inresponse to varying stresses. These hydrographs arepresented in Appendix F.

Agreement of simulated water levels withobserved water levels can be affected by thefollowing conditions:

1. MODFLOW simulates well withdrawals from acell as a single stress located at the node, orcenter of the cell. In reality, the arearepresented by a cell may contain manypumping wells. This situation is commonthroughout the Martin County model, due tothe size of the cells. Combining all the wellwithdrawals located within a cell and locatingthe total withdrawal at the center of the cell isnot a completely accurate simulation. Inaddition, the computed head in a cell representsthe average water level over a model cell. Ifactual levels vary significantly across the cell,monitor well levels may not closely match thecomputed levels. In areas of higher groundwater gradients, such as those caused byintensive well withdrawals or where wells arelocated near surface water bodies causingstrong natural gradients, water levelsthroughout a cell can vary significantly fromthe average. Cell-wide averaging effects are

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evident in comparing observed and computedlevels in the cells containing monitor wells inall the major wellfields.

2. The model was run using one month stressperiods, consequently the model water levelsreflect the average effect of stresses thatoccurred throughout the month. However, amonitor well will reflect the most recent eventsaffecting water levels around the well (canalstage changes, well withdrawals, rainfallevents) just before the water level reading wastaken. Also, monitor well readings wereusually collected near the end of the month butcould have been take anytime in the latter halfof the month. These situations can cause somediscrepancy between the model and observationwell levels used to check calibration.

3. Most of the rainfall in the study area occurs asintense short term events over relatively smallareas. In many cases, ground water levelsrespond almost immediately to these events. Alocal rainstorm during any of the measuringperiods could result in water level increases inselected wells reflecting a local phenomenarather than a regional trend. Also, some of theobservation wells are located a significantdistance from a rainfall station, so an intenserainfall event causing water level fluctuationsat a given well may not be represented in therainfall data.

4, Inspection of aerial photography reveals thatMartin County has a large network of canals,ranging in width from several feet to hundredsof feet. Only canals with some data on depths,configurations and control elevations wereincluded in the model. In general, these weregrove canals, some pasture canals and theSFWMD canals. This omits many smallerroadside drainage systems. An observationwell near a canal not included in the modelcould then indicate the model is not accurate inthat area. And, as mentioned before, if themonitor well is in the same cell as the canalreach, cell-wide averaging effects cansometimes make it impossible to calibrate themodel to the observation well water level.

Because all the layers of the model are basicallyunder atmospheric conditions and there are nosignificant confining units between layers, modeledwater levels in the three layers were generally thesame by the end of each one month stress period.Any changes in the evapotranspiration, recharge orriver/drain packages affected all three layers

similarly Therefore, calibration discussions will notaddress individual layers, but the model as a whole.

Most of the calibration changes were made inone of three areas; 1) river/drain conductance, 2)starting head levels, and/or 3) evapotranspirationsurface. After the initial runs, two observed versusmodeled hydrograph patterns became apparent.Either the model initial value was much higher orlower than the observation well and the well wasnever able to recover from that poor starting point, orthe initial level was accurate but as the modelprogressed the modeled water level became too high,starting to come down by the end of the calibrationperiod. In the former situation, adjustments to thestarting head file usually corrected the problemwhich was probably caused by the statisticalinterpolation program used to create the file.

In the latter situation, water seemed to"mound" during the summer rainy months.Adjustments to rainfall were attempted but were notparticularly successful. Eventually it was discoveredthat adjustments in the evapotranspiration (ET)surface would correct the problem. If the ET surfaceis lowered, the ET extinction point is then deeper andthe ET rate becomes larger at the same depth whichresults in more ET which removes the water thatwas "mounding". The opposite situation can beaffected by raising the ET surface to correctsituations where the modeled level is too low.Changes of one or two feet were usually sufficient tocause the model to calibrate. This method, whileeffective, is tedious and can only be changed andverified on a local level. In cells without a monitorwell, which is the majority of cells, this fine tuning isnot possible.

The ET surface was based on land surfaceelevations which were determined from USGStopographic quadrangles which were overlain withthe model grid. Although some grid cells hadelevation changes of 20 feet or more, it was necessaryto average the elevation for model input. Theelevation contour lines are at five foot intervals,generally leaving a ±2.5 feet range for adjustmentwhen calibrating the ET surface of the model. In theareas where elevations change rapidly, the modelwould be more accurate with a smaller cell size. Inwetlands areas, modeled water levels were too lowand using the above method would have resulted inan evapotranspiration surface well above landsurface. Therefore, coefficients used in creating themaximum evapotranspiration rate array werealtered until the resulting array, when used in themodel, led to calibration with observed water levels.

The other parameter which measurablyaffected water levels was river and drainconductances. There are many wells, in the modeledarea, near large surface water sources. The modelwas run several times using different river and drainconductance multipliers and checking calibration ofnearby wells. Reaches which calibrated well atcertain multipliers were noted and finally the riverand drain files were modified to reflect the bestmultiplier for each reach. The Loxahatchee Riverchanges from drain reaches upstream to riverreaches in the brackish/tidal areas. Theconductances are significantly different between theriver and drain sections. The model documentation(McDonald & Harbaugh, 1988) states that theconductance term is best used as a calibrationparameter and does not necessarily reflect a naturalcondition. Apparently, because of the way the modelhandles flow in and/or out of river versus drainreaches, the conductance values that resulted in agood calibration are different for the two types.

Results

Agreement of one foot or less between observedwater levels and simulated water levels in cellswhich represent the location of those wells, for atleast 75 percent of the stress periods was thecalibration criteria. For this model that means thatfor nine out of the twelve months, modeled waterlevels had to be within a foot of the observed level.

The wells were broken into three calibrationcategories: 1) wells that met the calibration criteria,2) wells that did not meet the criteria but the reasonfor being outside the range is explainable, and 3)wells that did not meet criteria, indicating an area of

the model that needs further refinement. Table 6presents the current status of observation wells usedin the transient model calibration.

Wells categorized as "explainable" did not meetcalibration criteria but other influences, such asthose previously discussed, prevented a betterapparent calibration. In layer one, wells M-1046,M-1083, and M-1265 may be affected by ETparameters; wells M-1262, M-1263, and M-1270 maybe affected by drain cells; and wells M-1048, M-1081,M-1232, M-1256, M-1269, M-1274, PB-1520, PipersLanding well 9A, and PB-927 have no obviousstarting point from which to seek a bettercalibration. In layer two, wells M-1086 (ETproblems), M-1085 (grove drain), M-1010, M-1049,M-1161, M-1253, PB-720, T-4 (Tequesta) and U(Jupiter) did not meet the calibration criteria andprobably indicate areas where more work is neededon the model. Non-calibrated wells in layer three areM-1088, M-1096, M-1236, M-1238, M-1230, M-1235,and Pipers Landing wells 6, 8, 9, 10 and 40B3.

Figures 28 through 30 depict the averagedifference between observed and modeled waterlevels over the entire transient calibration period foreach monitor well. This map gives a generalindication of model calibration; however, if the modelwater level is much higher than observed during onestress period and then equally too low at anothertime, they would, of course, cancel themselves out,resulting in a small average difference. But if a wellor group of wells is consistently high or low, thiswould show up and give guidance on which areasneed work.

Table 6: Transient Calibration Results

Layer one Layer two Layer three Total

# % # % # % # %

Calibrated 42 58 49 51 11 44 102 53

Explainable 15 21 38 40 3 12 56 29

Not Calibrated 15 21 9 8 11 44 35 18

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STEADY STATE CALIBRATION

Method"Steady state" can be viewed as an average

condition achieved over a long period of time, andassumes that no major changes in stress rates occurduring that time. When the stresses that driveground water flow change very slowly in timerelative to the rate of change within the aquifersystem, steady state assumptions are justified. Inmany cases, however, the steady state condition ishypothetical due to the artificially rapid changesapplied to the aquifer system. A pre-developmentcondition for Martin County was present earlier inthis century, but little or no data exists that could beused to reproduce it. At the present time, the aquifersystem is in a dynamic transient process, but on amonthly basis behaves in a "quasi-steady-state"manner.

Ideally, the steady state runs would have beencalibrated using predevelopment data wherebydisturbances to the steady state condition would notexist. Average values of recharge, evapo-transpiration, pumpage, and surface water stageelevations were used, calculated from the monthlyvalues for 1989. January 1989 water levels wereused for the starting head array. The model was runfor one stress period broken into twelve 30-day timesteps. The resulting modeled water levels (Figures31, 32 and 33) represent an average 1989 conditionand are best used for sensitivity analysis anddifferences between predictive scenarios rather thanto determine specific water level information for agiven time period.

Results

The steady state calibrations were based on theassumption that the ground water levels during the

calibration period were fluctuating around a steadystate condition as a result of seasonal variations inrainfall, pumpage, evapotranspiration and canallevels. Further, the average measured ground waterlevels during the period were assumed toapproximate steady state levels under average 1989conditions. Thus, the steady state calibrations weremade based on comparison of simulated water levelsunder 1989 recharge/discharge conditions versus themeasured water levels in surveyed wells during thecalibration period. A well was considered calibratedif the modeled water level fell within the minimumto maximum water level range for that well or nomore than 0.1 feet outside the range for thecalibration period. Figures 34a-d illustrate thedifferences between the simulated steady state waterlevels and the average measured water levels inthese wells during the calibration period.Differences between the average measured levelsand the minimum and maximum measured levelsare shown in the same figures.

The wells were broken into three calibrationcategories: 1) wells that met the calibration criteria,2) wells that did not meet the criteria but the reasonfor being outside the range is explainable, and 3)wells that did not meet criteria indicating an area ofthe model that needs further refinement. There is adiscussion in the transient calibration section on thedifferent situations that can influence model resultsand make an observation well appear uncalibrated.Table 7 gives the breakdown of the calibrationresults for the steady state model.

Most of the uncalibrated wells which indicate areasneeding work, also fell into the same category in thetransient calibration results. The following wells inlayer one did not meet calibration criteria, indicatingareas needing further model refinement: M-1081,

Table 7: Steady State Calibration Results

Layer one Layer two Layer three Total

# % # % # % # %

Calibrated 48 67 51 53 17 68 116 60

Explainable 19 26 39 41 5 20 63 33

Not Calibrated 5 7 6 6 3 12 14 7

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M- 1232, LOX. R4, PB-1520 and PB-927. In layer twothe uncalibrated wells are M-1010, M-1055, M-1161M-1253, PB-720 and T-4 (Tequesta). For layer threethey are wells M-1235 and Pipers Landing wellsand 10.

Budget and Flows

Layer One Figure 35 shows the direction andmagnitude of simulated horizontal flow in layer one.Each arrow represents the flow from an individualcell. The majority of the larger flow vectors areassociated with intensive ground water use orinteractions with surface water bodies. The flowvectors north of Indiantown represent flow from atopographic high (the Osceola Plain), steeplydeclining and then intercepting grove canals whichmaintain water levels lower than land surface. Flow

vectors are not shown in the Okeechobee portion ofthe model due to graphic problems associated withexpanded grid cells.

An analysis of the volumetric budget for layerone is shown in Figure 36. The majority of flow intothis layer (86 percent) is derived from recharge(rainfall), 10 percent is upward leakage from layertwo, one percent is river leakage, and three percentis from the general and "prescribed" head cells,representing flow from outside the model, mainlyfrom St. Lucie and Okeechobee counties and LakeOkeechobee. Of the total flow out of layer one, 63percent is to evapotranspiration, 19 percent isleakage to layer two, less than one percent isagricultural well pumpage, six percent is riverleakage, 11 percent is into drains and the remainingone percent is flow to the general and "prescribed"head cells, representing flow out of the modeled area,mainly to the Atlantic Ocean and Palm BeachCounty.

Layer Two Figure 37 shows the magnitudeand direction of simulated horizontal flow in layertwo. Most of the larger flow vectors are associatedwith intensive ground water use, for example theJupiter and Hobe Sound wellfields. Figure 38 is arepresentation of the simulated vertical flowbetween layer two and the overlying layer. Upwardflow into layer one is generally to river or drain cells.

, The largest downward flow from layer one is, associated with well withdrawals in layer two.

9 Figure 39 illustrates the volumetric budget forlayer two. Approximately 82 percent of the totalinflow to this layer is recharge from layer one, 16percent is inflow from layer three, two percent isfrom the general head cells, and one percent isrecharge (rainfall) in cells where the modeldetermined that the vertically adjacent cell in layerone was inactive. The flow from the general headcells represents flow into the modeled area from allboundaries. Of the total outflows, 45 percent isupward leakage to the water table aquifer, 37percent is to wells, 16 percent is downward leakageto layer three, and two percent is to the general headcells.

Layer Three Figure 40 shows the magnitudeand direction of simulated horizontal flow in layerthree. The larger flow vectors are associated withintensive ground water withdrawals associated withthe Jupiter and Hobe Sound wellfields. Figure 41illustrates the simulated leakage between layers twoand three. Most of the flow is upward to rechargelayer two and large upward flow vectors indicatedintensive withdrawals from layer two, for example inJupiter.

The volumetric budget for layer three isillustrated in Figure 42. Almost all of the inflow tolayer three (97 percent) is recharge from above. Theremaining three percent comes from the generalhead cells. Of the total outflow, 95 percent is upwardleakage to layer two and five percent is to generalhead cells.

A combined steady state volumetric budget forall of the modeled area is presented in Figure 43 andTable 8. Total inflow consists of 95 percent recharge(rainfall), four percent flow from general headboundaries (flow from outside the modeled area), andone percent from river leakage. Total outflowconsists of 70 percent evapotranspiration, ninepercent to wells, one percent to general headboundaries (flow out of the modeled area), and 19percent discharge to surface water bodies (12 percentto drains and seven percent to rivers).

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RATE(Million Gallons/day)

RATE(Acre-Feet/day)

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OUT

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SENSITIVITY TESTING

The model was tested to check its sensitivity tochanges in aquifer parameters and stresses. Usingthe steady state model, aquifer parameters weretested by altering the following parameters: Layerone conductivity and river and drain bedconductance, Vcont between layers one and two,layer two transmissivity, Veont between layers twoand three, and layer three transmissivity. Thesensitivity of the model to these parameters wastested by doubling, then halving each parameter, oneat a time. In addition, the Vcont terms and river anddrain conductances were also reduced and increasedby an order of magnitude. Using the transientmodel, specific yield in layer one was doubled andhalved and storage in layers two and three were eachincreased and decreased by one order of magnitude.It was assumed that testing this range of valueswould bracket the range of uncertainty for eachparameter. Head changes in each layer wereexamined to determine the relative sensitivity. Theresults of these tests are presented in Table 9.

The model was also tested, using the steadystate version, for its sensitivity to the followingclimatological factors: recharge, maximumevapotranspiration rate, and evapotranspirationsurface. Recharge and ET rates were increased anddecreased by 10 percent, and the ET surface wasraised and lowered by one and two feet. The wellswere turned off for one scenario to see the overalleffect of withdrawals. Using the transient model,starting head was increased and decreased by 2 feetand results after one stress period (one month) wereanalyzed. It was assumed that testing this range ofvalues for the various stresses would bracket therange of uncertainty. Results of these sensitivitytests are presented in Table 10.

LAYER ONE

Generally, simulated water levels in layer 1were not sensitive to changes in aquifer parameters.Changes in hydraulic conductivity in layer one, onaverage, had no effect with a maximum increase of afoot and maximum decrease of 0.71 feet. Doublingand halving the Vcont between layers one and twoalso had no effect but reducing it by an order ofmagnitude raised water levels by an average of 0.08feet. An attempt to increase by Veont an order ofmagnitude was unsuccessful as the model failed toconverge. In layer two, the magnitude of the effectwas similar but the direction was opposite with

water levels decreasing an average of u. 4 feet whenthe Vcont was reduced by an order of magnitude.Reactions in layer three were similar to those inlayer two. Reducing specific yield by half led to a0.12 foot average reduction in water levels whiledoubling it had no effect, on average. Since themaximum increase and decrease resulting fromspecific yield changes was over two feet, thisparameter could affect calibration in some areas.These maximum and minimum values occurred inthe Jupiter agricultural area north of IndiantownRoad. The largest effects are usually seen in areaswith the largest stress. This area has significantwithdrawals and since the irrigation is by floodmethod, the recharge to the aquifer is also high.Therefore, changes in specific yield and storage havethe greatest effect in this area.

As expected, increases in river and drainconductances resulted in lowering water levels inlayer one, and average results in layers two andthree were identical but the maximum change inwater levels was slightly less in layer two andfurther diminished in layer three. A decrease inriver and drain conductances led to a slight averageincrease in water levels, and layers two and threeshowed similar average changes. Of all thesensitivity runs made, changes in river and drainconductances had the largest maximum increase ordecrease depending on the scenario. A decrease ofalmost twenty feet occurred in the Jupiter area whenriver and drain conductances were increased by anorder of magnitude. The Jupiter area is the area ofhighest stress in the model, so the effect of changes islargest here also. The average value gives a betterindication of the overall effect on the model, sincemost areas are not as significantly stressed.

LAYER 2

Simulated heads in layer 2 show only minoreffects from changes in aquifer parameters. Averageheads in layer two increased 0.01 feet whentransmissivity was doubled and decreased 0.05 feetwhen transmissivity was cut in half. A maximumincrease of almost six feet and a decrease of sevenfeet indicates that calibration in local areas could besignificantly affected by transmissivity values.These maximum increases and decreases occurred inthe area of the Jupiter wellfield. Changes in Vcontbetween layers two and three caused little or noaverage changes in water level in all three layers.

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Changes in storage had no effect on average, with amaximum increase of 0.13 feet when storage wasincreased by an order of magnitude; this increaseoccurred in the Jupiter agricultural area near I-95and north of Indiantown Road.

LAYER 3

Doubling and halving transmissivity in layerthree resulted in almost no change in average waterlevels in layer three. Average effects in layer oneand two were less than 0.2 feet, with a maximum risein head of almost 4 feet when transmissivity wasdoubled and an maximum decrease in head ofapproximately 3 feet when transmissivity wasreduced to half Once again, the maximum increaseand decrease occurred in the Jupiter wellfield area asa result of the large stresses in the area.

MODEL BOUNDARIES

The heads and conductances in the generalheads were varied to determine their contribution atmodel boundaries (see Table 10 for results). At theAtlantic Ocean and Lake Okeechobee boundaries,because of the prescribed head condition, whenprescribed head levels were increased or decreasedby two feet, water levels in the cell containing theprescribed head also changed by the same amount.Along Lake Okeechobee, the cell adjacent to theprescribed head cell showed only a 0.1 foot change.However, along the ocean boundary, up to six cellswest of the boundary were affected by the prescribedhead level change. By the third or fourth cell west,the change was only 0.1 or 0.2 feet. The magnitudeand distance of these effects was larger near coastalwellfields. Changes in the general head cells inlayers two and three were similar to those in layerone. With an increase in prescribed head waterlevel, flow increased into the model through theprescribed heads. There was no change in head as aresult of reducing or increasing conductance by oneorder of magnitude. Flow rates out of the prescribedheads decreased only slightly with decreasingconductance and vice-versa. Flow rates were anorder of magnitude less in layers two and three withan order of magnitude decrease in conductance.Similarly, increasing conductance in the generalhead boundary cells in layers two and threeincreased flow rates by approximately an order ofmagnitude.

Along the north model boundary, a two footincrease in general heads resulted in heads that were0.8 feet higher in the boundary cells in all threelayers. In boundary cells containing or directlybeneath rivers, aquifer head levels increased up to

0.3 feet. The largest changes occurred near largegradients (Osceola Plain edges, S97 controlstructure). The change was 0.1 foot or less by theadjacent cell (Row 2). Reviewing flow rates into andout of the general head, the increased head reducedthe rate of loss from the aquifer into the generalheads or increased the rate into the aquifer from thegeneral head, depending on the initial flowcondition. Decreasing general heads by two feetreduced heads in the cell by one foot and 0.3 feet inthe boundary cells containing rivers. Decreasingconductance by one order of magnitude reducedwater levels by 0.7 feet in general head boundarycells and boundary cells containing drains. Waterlevels changed 0.1 foot or less in boundary cellscontaining rivers. The changes were insignificant inthe adjacent cells in row two. Increasingconductance lowered water levels in the generalhead boundary cells by 1.1 feet. Changes inboundary cells containing rivers varied from + 0.6 to-1.5 feet and averaged +.12 feet. In row two,changes were down to -0.3 feet and were -0.1 feet byrow three. In boundary cells containing drains,however, water levels were one foot higher and byrow four they were 0.1 feet higher than the initialheads. Effects of conductance changes were similarin all layers.

Along the south model boundary, the resultsof general head changes were similar in all threelayers. When general head levels were increased bytwo feet, water levels in the boundary cellsincreased. In the area east of the Turnpike, near theJupiter wellfield and nearby agricultural operations,water levels in the boundary cells were 1.26 feethigher in layer one and 1.33 feet higher in layers twoand three. Water levels were affected up to six cellsnorth of the boundary (Row 54). West of theTurnpike, water levels were 0.8 feet higher in theboundary cells but in the adjacent cells (Row 58),water levels were only 0.1 feet higher. Increases inflow rates out of the general head cells were less thanone order of magnitude. Decreasing the generalhead water levels by two feet resulted in equal butopposite changes from the two foot head increase. Anorder of magnitude increase and decrease in generalhead conductance had variable results. West of theTurnpike, changes due to decreased conductanceranged from + 0.5 feet to -0.4 feet with an average of-0.1 feet; while east of the Turnpike, changes rangedfrom -6.2 feet to + 1.5 feet with the largest declinesnear pumpages. With increased conductances,changes west of the Turnpike ranged from -1.0 to+0.8 with an average increase of + 0.2. East of theTurnpike, changes ranged from +2.8 feet to -1.2 feetwith the higher increases near large ground water

withdrawals, and water levels were affected as muchas five cells to the north (Row 54).

CLIMATOLOGICAL AND STARTING HEADEFFECTS

Changes in these parameters (recharge, ET,starting head) showed some of the largest averagechanges in water levels in the model. Increasing anddecreasing recharge by 20 percent resulted in a halffoot increase and decrease in water levels,respectively. The maximum increase of 4 feet anddecrease of 5.6 feet occurred in the Stuart area.Increasing the ET rate by 20 percent reduced waterlevels an average of 0.22 feet while decreasing theET rate increased water levels by 0.33 feet onaverage. The maximum changes occurred in thearea of the Florida Power and Light Reservoir.Increasing the extinction depth, which effectivelyincreases the water available for ET, led to decreasesin water levels of 0.76 feet. An attempt to reduce theextinction depth, adjusting so the minimum depthwas zero feet, made the model unstable and it wouldnot converge. Changes in the ET surface led to someof the most significant effects on average waterlevels. Increasing the ET surface by two feet,effectively moving it further away from the groundwater source, led to an average water level increase

of 1.48 feet. Decreasing the ET surface had theopposite effect, with a 1.55 foot decrease in waterlevels, on average.

Starting head was another parameter thatwas increased and decreased by two feet using thetransient simulation with very similar averageresults to ET surface changes. Raising and loweringthe starting head is very similar to raising andlowering the ET surface and both should havesimilar effects. However, the model will attempt toequilibrate the water levels, moving them up ordown based on the regional gradient. In lowertransmissivity aquifers, model adjustments toequilibrate are slow and may not occur within themodeled time period. Therefore, starting headvalues should be as accurate as possible socalibration is not affected.

As a check of the effect of wells on the system,they were turned off for one sensitivity run.Predictably, the largest rise in water levels occurredin the Jupiter wellfield and was almost 18 feet,which is consistent with wellfield drawdown data.The overall average water level increase was only0.37 feet, which reflects the fact that in the majorityof the county, well use is small to none.

QUALITY ASSURANCE / QUALITY CONTROL PROCEDURE

The South Florida Water Management Districtdeveloped a quality assurance/quality control(QA/QC) procedure pertaining to ground water flowmodels as they progressed from the developmentstage to use by the Planning Department. Theprocess involves a series of iterations between themodel developer and the end user in the PlanningDepartment as well as a peer review team selectedfor each model.

Each model is evaluated in terms of: a)acceptability and b) impacts of deficiencies onapplication of the model. Acceptability is dividedinto three categories: 1) meets all standards ofcompleteness and accuracy, 2) meets mainstandards, but enhancements are necessary toimprove the overall accuracy of the model, and 3)does not meet standards and the model is not readyfor use. All parameters that did not meet standardswere corrected as a first priority. Parametersneeding enhancements were prioritized into thosethat should be upgraded before the models are usedto minimize future problems and those items whichcan be continually enhanced even while the model isin use.

The QA/QC checklist is divided in two parts; aconceptualization section and a data sets section.The conceptualization section is a narrativediscussion of the methodology and assumptions usedin creating the data sets. It covers such topics asboundary conditions, time and space discretization,recharge and evapotranspiration calculations, wateruse data sources and assumptions, aquifer

parameters, creation of parameters for rivers anddrains, and calibration criteria. This discussion wasintended to familiarize the user with all assumptionsused in creating the model to make them aware ofsituations which may affect results. The data setchecklist includes all data sets used in the model andverifies that there are no data anomalies. Data werechecked both graphically and numerically.Three-dimensional plots of all arrays were created topoint out errant data points. Contour plots werecompared with data points used to create them tomake sure they were accurate. The minimum andmaximum value for each plot was determined andchecked for reasonableness. Numeric arrays wereprinted and checked visually, especially atboundaries. River, drain and general head cellvalues were also printed spatially and checked forreasonableness and consistency between cells. Allwell locations were verified both in row,column andplanar coordinate formats. Modeled pumpage wascompared to permitted allocations forreasonableness. The volumetric budget was alsochecked to determine if anything was out ofproportion.

Several data corrections were made andchanges in conceptualization at boundaries and inrecharge and evapotranspiration sections resulted inmodel modifications. Finally, agreement wasreached and checklists from the peer review panelwere approved with no unacceptable sections andseveral sections identified as acceptable undercurrent conditions with future enhancementsnecessary.

RESULTS

1. The most important source of recharge to the Surficial Aquifer System in MartinCounty is rainfall. Approximately 95 percent of the recharge in the study areawas provided by rainfall. The remaining five percent came from ground waterflow into the modeled area (four percent) and river leakage (one percent).

2. Evapotranspiration accounts for the majority of outflow from the modeled area(approximately 70 percent). The remaining outflow is comprised of wellwithdrawals (nine percent), ground water flow out of the modeled area (onepercent), and discharge to surface water bodies (19 percent).

3. Forty-five percent of the total ground water well withdrawals in the model areacome from domestic self-supply use. Agricultural irrigation accounted for 27percent of the ground water well withdrawals and public water supplywithdrawals accounted for 24 percent. The remaining four percent comes fromindustrial uses.

4. The largest impacts in layer one, based on flow volumes, occur in the Port Salernoarea, where domestic self-supply use is high, and at the edge of the Osceola Plainin Indiantown, where ground water elevations decrease rapidly and are furtherreduced by grove drainage. In layer two, flow is greatest around the Hobe Soundand Jupiter wellfields. Flow is also greatest around the Jupiter and Hobe Soundwellfields in layer three as well as between layers two and three.

CONCLUSIONS AND RECOMMENDATIONS

1. Discharge to surface water bodies accountedfor 19 percent of losses from the ground watersystem. Currently, the accuracy of thisnumber cannot be verified but surface watermodels are being developed and results fromthis may result in modifications to the groundwater model. One potential for error comesfrom defining the "wetted perimeter" of acanal. Data on widths and depths of canals issparse, especially for the many grove androadside drainage canals. Also, these samecanals have no records on stage levels andoften, not even information on controlstructure elevations. This makes it difficult, ifnot impossible, to accurately represent thedrainage and recharge potential of thesesurface water bodies. During the regulationprocess, every effort should be made to includepertinent control elevation and canalconstruction data in the permits. Informationconcerning ditches, lakes, canals, wetlands,etc. in future surface water permits as well asone foot topographic data obtained duringpermit review could be of benefit in modelcalibration. Stage recorders in some of themajor grove canals would produce invaluabledata for use in the ground and surface watermodels.

2. Currently, the model is not sensitive/accurateenough to be used in surface water permittingto determine exact control elevations or to setwetland elevations. However, ground waterlevels in the model can be checked againstexisting permits and new proposed controlelevations and any discrepancies reported tothe model developer to aid in improved modelcalibration. Refinements in grid size andelevation data would make this a useful toolfor surface water permitting to evaluateexisting and future impacts due to surfacewater management systems.

3. The model in its present configuration (92acres per cell) is not accurate in assessingground water withdrawal impacts on a smallscale, due to the regional nature of the modelgrid. As a result, small scale impacts onadjacent users or small wetland areas may beoverlooked due to cell-wide averaging.Improved grid resolution and use of one foottopographic data is needed to better assessthese small scale impacts. The SFWMD is

currently working on software to make itpossible to "zoom in" on an area of the regionalmodel and extract data to create a submodelwith finer grid resolution. This shouldimprove site-specific evaluations.

4. With 95 percent of water to the model comingfrom the recharge package and 70 percent ofthe losses removed by the evapotranspirationpackage, the accuracy of the model isdependent on the accuracy of these twopackages. During model calibration it becamevery obvious that these packages do not allowthe user to accurately imitate the intricaciesof these processes because they deal only withdirect effects on the saturated aquifer.Therefore, pre-processing of inputs to thesepackages is necessary to meet the assumptionsthe model makes of this data. Areas needingwork include accounting for irrigation water,investigating areas where ground water issignificantly below land surface (dunes), andeffects of canals which lower the water tablebelow the ET extinction depth and the effectsof each of these situations effects on rechargeand evapotranspiration rates.

5. One portion of the evapotranspiration packageis ET surface. It is usually set to land surface.Detailed land surface data on a large scale isnot available. Where water level data wereavailable for confirmation, changes of evenone foot in ET surface affected calibrationresults. This illustrates the need for detailedinformation. However, cell size is also animportant factor. In areas with rapidelevation changes, smaller cells and moredetailed data should result in improvedcalibration of the model.

6. Although ground water withdrawals accountfor only nine percent of the modeled outflow,the impact of these withdrawals was theimpetus for developing the model. Becausedomestic self-supply is such a large andwidespread type of water use, parameters usedin reaching this estimate need refining toincrease the accuracy and reliability of themodel. Specifically, better information onwhere all domestic use is self-supplied (i.e.pockets not yet on utilities), the location ofprivate wells in utility areas and/or homeswhich use utility water for irrigation isneeded.

Agricultural irrigation accounted for 27percent of the ground water well withdrawalsin Martin County. However, data on actualamounts withdrawn are limited. Actual wateruse data would increase confidence in thecalibration of the model, particularly in areasof heavy ground water use. In addition,accurate projections of future agriculturalwater use will be necessary for thedevelopment of a water supply plan for thearea including Martin County. Most publicsupply utilities do not record flow fromindividual wells in their wellfields. Some dokeep track of hours pumped per well but pointout that well capacity is dependent on the

number of wells pumping at a given time,which changes often. Individual flow meterswould provide accurate withdrawals for inputinto the model.

The model was difficult to calibrate within thespecified constraints in several localizedareas, especially the Martin Downs/Palm Cityarea. Probable reasons are cell-wideaveraging or uncertainty in aquiferparameters or stress rates. Future revisionsto the model should be concentrated in theseareas to improve the confidence level of themodel.

REFERENCES

Adams, K. In Press. Ground Water ResourceAssessments of Martin County. South Florida WaterManagement District Technical Publication 92-***,West Palm Beach, Florida.

Bower, R.F., K. M. Adams, and J. I. Restrepo. 1990.A Three Dimensional Finite Difference GroundWater Flow Model of Lee County, Florida. SouthFlorida Water Management District TechnicalPublication 90-1.

Cooper, R. M. and R. Santee. 1988. An Atlas ofMartin County Surface Water Management Basins.South Florida Water Management District TechnicalMemorandum. South Florida Water ManagementDistrict, West Palm Beach, Florida.

Cooper, R. M. and J. Lane. 1988. An Atlas of EasternPalm Beach County Surface Water ManagementBasins. South Florida Water Management DistrictTechnical Memorandum. South Florida WaterManagement District, West Palm Beach, Florida.

Driscoll, F. G. 1986. Groundwater and Wells.Johnson Filtration Systems, St. Paul, Minnesota.

Earle, J. E. 1975. Progress Report on the WaterResource Investigation of Martin County, Florida:U. S. Geological Survey Open File Report FL-75-521,Tallahassee, Florida.

Fetter, C. W. 1980. Applied Hydrogeology. CharlesE. Merrill Company.

Hopkins, E. 1991. A Water Resource Analysis of theJensen Beach Peninsula, Martin County, Florida.South Florida Water Management District TechnicalPublication 91-03, West Palm Beach, Florida.

Jensen, M. E. 1981. Design and Operation of FarmIrrigation Systems. American Society ofAgricultural Engineers, St. Joseph, Michigan.

Johnson, A. I. 1967. Specific Yield - Compilation ofSpecific Yields for Various Materials. U. S.Geological Survey Water-Supply Paper 1662-D.

Kuiper, L. K. 1987. Computer Program for SolvingGround Water Flow Equations by the PreconditionedConjugate Gradient Method. U.S. GeologicalSurvey, Water Resources Investigations Report87-4091.

Lichtler, W. F. 1960. Geology and Ground-WaterResources of Martin County, Florida: Florida Geol.Survey Report of Investigations No. 23.

Lukasiewicz, J. In Press. A Three-DimensionalFinite-Difference Ground Water Flow Model of theFloridan Aquifer System in Martin, St. Lucie andEastern Okeechobee Counties, Florida. SouthFlorida Water Management District TechnicalPublication 92-***, West Palm Beach, Florida.

MacVicar, T. K. 1983. Rainfall Averages andSelected Extremes for Central and South Florida.South Florida Water Management District TechnicalPublication 83-2.

MacVicar, T. K., T. Van Lent and A. Castro. 1984.South Florida Water Management ModelDocumentation Report: South Florida WaterManagement District, Technical Publication 84-3,West Palm Beach, Florida.

McCollum, S. H. and O. E. Cruz, L. Stem, W.Wittstruck, R. Ford and F. Watts. 1978. Soil Surveyof Palm Beach County Area, Florida. U.S.Department of Agriculture, Soil ConservationService, Florida.

McCollum, S. H. and O. E. Cruz, Sr. 1981. SoilSurvey of Martin County Area, Florida. U.S.Department of Agriculture, Soil ConservationService, Florida.

McDonald, M. G. and A. W. Harbaugh. 1988. AModular Three-Dimensional Finite-DifferenceGround-Water Flow Model. Techniques ofWater-Resources Investigations of the United StatesGeological Survey, Book 6, Chapter Al.

Miller, R, A. 1978. Water Resources Setting, MartinCounty: U. S. Geological Survey, Water ResourcesInvestigation 77-68.

Morris, F. W. 1986. Bathymetry of the St. LucieEstuary. South Florida Water Management DistrictTechnical Publication 86-4. South Florida WaterManagement District, West Palm Beach, Florida.

Nealon, D., G. Shih, S. Trost, S. Opalat, A. Fan andB. Adams. 1987. Martin County Water ResourceAssessment. South Florida Water ManagementDistrict, West Palm Beach, Florida.

Opalat, S. 1985. Urban Water Demand Estimates forMartin County: 1983 Existing and Committed, andBuildout. South Florida Water Management DistrictTechnical Memorandum, West Palm Beach, Florida.

Padgett, D). In Press. A Three-Dimensional Finite-Difference Ground Water Flow Model of the SurficialAquifer in St. Lucie County, Florida. South FloridaWater Management District Technical Publication92-***, West Palm Beach, Florida.

Parker, G. G., G. E. Ferguson, S. K. Love, and others.1955. Water Resource of Southeastern Florida. U. S.Geological Survey Water Supply Paper No. 1255.

Shine, M. J., D. G. J. Padgett, and W. M. Barfknecht.1989. Ground Water Resource Assessment OfEastern Palm Beach County, Florida. South FloridaWater Management District Technical PublicationNo. 88-4.

Southeastern Geological Society Committee onFlorida Hydrostratigraphic Units Definition. 1986.Hydrogeological Units of Florida. Florida GeologicalSurvey Special Publication No. 28.

South Florida Water Management District. 1985.Management of Water Use Permitting Information,Volume III.

South Florida Water Management District. 1991.Draft Water Supply Policy Document. South FloridaWater Management District, West Palm Beach,Florida.

Stodghill, A. M. and M. T. Stewart. 1984.Resistivity Investigation of the Coastal RidgeAquifer Hydrostratigraphy, Martin County, Florida:South Florida Water Management District, WestPalm Beach, Florida.

Todd, K. D. 1980. Groundwater Hydrology. JohnWiley & Sons, New York.

Trimble, P. J., J. A. Marban, M. Molina, S. P.Sculley. 1990. Analysis of the 1989-1990 Drought.South Florida Water Management District SpecialReport, West Palm Beach, Florida.

United States Department of Agriculture, SoilConservation Service. 1970. Irrigation WaterRequirements. Technical Release No. 21.

United States Department of Commerce. 1983. U. S.Bureau of the Census County and City Data Book,1983. U. S. Government Printing Office,Washington, D.C..

Viessman, W., J. W. Knapp, G. L. Lewis, and T. E.Harbaugh. 1977. Introduction to Hydrology. ADun-Donnelley Publisher, New York.

White, William A. 1970. The Geomorphology of theFlorida Peninsula: Florida Geological Survey,Geological Bulletin No. 51, 164 pp.

APPENDIX A

MAPS AND TABLE OF DATA USED

FOR VERTICAL DISCRETIZATION

LIST OF FIGURES - APPENDIX A

Figure

A-1

A-2

A-3

A-4

A-5

A-6

A-7

Page

........... 89

........... 99

.......... 100

.......... 101

.......... 102

.......... 103

.......... 104

LIST OF TABLES - APPENDIX A

Page

Lithologic Well Data ................................................ 90

Source ofLithologic Data ................ ....................... 97

Locations of Lithologic Control Wells ................

Thickness of Layer 1 ....................... .......

Bottom of Layer 1 ...........................

Thickness of Layer 2 ............................

Bottom of Layer 2 .. ............................

Thickness of Layer 3 ............................

Bottom of Layer 3 ...... .... ...................

Table

A-1

A-2

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TABLE A-1: Lithologic Well Data

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# Coordinates Surface Layer Layer Layer Layer 1 Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

I M1229 776748 962488 10 22 99 30 -12 -111 -141

2 M1230 786233 964674 8 25 109 0 -16 -125

3 M1231 748150 954250 22 15 115 40 7 -108 -148

4 M1235 750277 985847 17 38 24 88 -21 -45 -133

5 M1236 721553 996890 25 18 67 45 7 -60 -105

6 M1237 684311 996504 27 15 83 52 12 -71 -123

7 M1238 684246 1010943 27 15 44 67 12 -32 -99

8 M1239 725834 991057 23 15 47 65 8 -39 -104

9 M1240 668568 1043894 30 15 36 80 15 -21 -101

10 M1241 695767 982723 35 17 86 53 18 -68 -121

11 M1242 679626 972350 26 37 28 101 -11 -39 -140

12 M1246 716250 1043800 22 18 112 21 4 -108 -129

13 M1248 697980 1044050 31 39 43 75 -8 -51 -126

14 M1250 655300 1013870 45 46 64 41 -1 -65 -106

15 M1251 619000 1016650 31 23 27 88 8 -19 -107

16 SCD2 670000 1044150 30 15 42 71 15 -27 -98

17 M1252 646150 980450 25 18 44 83 7 -37 -120

18 M1253 749150 1014400 17 40 95 15 -23 -118 -133

19 M1254 751850 1059150 15 40 90 38 -24 -114 -152

20 CAULKINS 704550 996900 27 15 60 70 12 -48 -118

21 C-23 641000 1043900 26 20 90 10 6 -84 -94

22 L-65 614400 1008600 20 20 40 60 0 -40 -100

23 SR76 745300 1028000 10 40 120 20 -30 -150 -170

24 SITEA 748200 1042100 10 38 47 46 -28 -75 -121

25 SITEH-A 759150 1031200 10 42 68 16 -32 -100 -116

26 SITEH-C 759000 1031000 10 55 -45

27 SITE[ 744300 1028750 10 26 100 21 -16 -116 -137

28 MF20 628260 1026880 32 23 21 97 9 -12 -109

29 CB-12 636350 980800 23 38 -15

30 CBll 629250 980750 25 33 -8

31 CB9 628600 984500 22 27 71 -5 -76

TABLE A-1: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# Coordinates Surface Layer Layer Layer Layer 1 Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

32 CB8 626750 990600 22 23 -1

33 CB7 626000 995200 22 23 67 -1 -68

34 CB13 631300 993550 25 22 70 3 -67

35 CB6 631100 995900 26 25 65 1 -64

36 CB5 635900 995800 27 23 53 48 4 -49 -97

37 CB4 636350 989950 26 22 75 4 -71

38 CB3 640900 989200 27 26 76 48 I -75 -123

39 CB2 636300 986000 23 20 80 3 -77

40 CBIO 639200 985800 23 20 82 43 3 -79 -122

41 CB1 641850 983000 24 15 84 35 9 -75 -110

42 MG1 766000 1022400 15 25 115 -10 -125

43 MG2 766350 1022500 20 30 115 -10 -125

44 MG4 767100 1023300 20 42 103 -22 -125

45 MG5 767500 1023500 20 35 105 -15 -120

46 MD-4D 720150 1038700 5 15 80 45 -10 -90 -135

47 MD-3D 723550 1033000 18 20 85 40 -2 -87 -127

48 OW-1D 721850 1036350 18 20 65 50 -2 -67 -117

49 MD-SD 731900 1032500 13 30 60 50 -17 -77 -127

50 MD-6D 725350 1038100 11 15 75 60 -4 -79 -139

51 MD-1D 736300 1036400 7 50 65 20 -43 -108 -128

52 MD-5S 737550 1036400 5 50 40 30 -45 -85 -115

53 MD-2D 737300 1032500 7 50 30 15 -43 -73 -88

54 SLF1 729400 1004500 20 22 54 49 -2 -56 -105

55 SLF2 729950 1004150 20 22 37 -2 -39

56 SLF3 730200 1005000 20 23 45 59 -3 -48 -107

57 STTPW-1 749250 1029350 15 32 108 -17 -125

58 STOW-2 749700 1029400 15 40 100 -25 -125

59 BBOW-1D 744400 1021850 3 30 100 30 -27 -127 -157

60 BBOW-4D 741900 1021950 10 60 -50

61 HS32W 779850 996200 30 40 85 85 -10 -95 -180

62 M1093 789300 972900 7 35 -28

63 WOODOBS 733850 1041450 10 41 -31

TABLE A-1: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# Coordinates Surface Layer Layer Layer Layer I Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

64 TEQPK 795900 960400 25 26 -1

65 PL4 737350 1023500 12 35 45 -23 -68

66 GDC1 716000 1034250 20 28 72 -8 -80

67 GDC2 716000 1044000 20 35 69 46 -15 -84 -130

68 GDC4 716300 1039300 20 20 30 0 -30

69 GDC5 705800 1033950 25 20 22 114 5 -17 -131

70 GDC8 703300 1044100 25 20 62 52 5 -57 -109

71 INTOBS 756900 1026250 15 50 -35

72 HR2 726750 1045400 11 48 52 40 -37 -89 -129

73 JURBI 758600 946750 15 20 105 -5 -110

74 PB597 797500 958100 21 15 50 6 -44

75 PB639 775952 946225 16 40 92 86 -24 -116 -202

76 PB640 750140 948888 19 22 98 55 -3 -101 -156

77 PB649 712491 948777 26 24 31 2 -29

78 PB650 668304 954126 7 21 101 71 -14 -115 -186

79 PB651 626285 935296 22 22 68 120 0 -68 -188

80 PB681 795146 958274 12 15 201 -3 -204

81 PB1546 750247 946263 20 18 75 63 2 -73 -136

82 PB1613 694180 935863 26 15 76 70 11 -65 -135

83 PB1614 713305 948882 27 27 23 99 0 -23 -122

84 TEQRDI 793100 956600 10 30 110 -20 -130

85 TEQD2-5 796500 959600 20 33 -13

86 TEQD1-3 796200 955900 15 35 0 -20

87 TEQD1-4 795900 958500 16 36 0 -20

88 TEQD1-2 795400 955300 10 45 0 -35

90 93836 587700 1036000 20 25 23 -5 -28

92 Pioneer 133 605000 1032000 25 40 44 -15 -59

93 TurnDairy 645000 1026000 35 50 -15

94 StuartWest 701000 1030000 30 20 40 10 -30

95 PaImCty23 725000 1026000 20 25 -5

96 113937 631000 1006000 25 30 -5

97 CAULK1 658300 985600 35 20 80 80 15 -65 -145

TABLE A-1: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# Coordinates Surface Layer Layer Lyer Layer Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVI NGVD NGVD

98 CAULK4 700000 986000 27 30 110 30 -3 -113 -143

99 Burg&Div33 715000 984000 24 20 4

100 193941 735000 994000 20 30 95 -10 -105

101 PeroFarm2 761000 988000 15 20 -5

104 Burg&Div31 735000 982000 20 20 40 80 0 -40 -120

105 H.S.Water 783249 988032 35 35 0

106 H.S.Assoc 781000 992000 24 40 -16

107 JBReedPk 783000 990000 25 30 -5

108 Bridge&Flor 775000 982000 10 20 80 -10 -90

109 HYD10 771700 1012600 20 30 -10

110 Ju.RivDr. 781000 960000 10 30 -20

111 PBPkCommS 739000 934000 24 15 83 9 -74

112 CVII-5 657600 960200 27 15 70 100 12 -58 -158

113 CV11-4 657600 969000 27 15 90 60 12 -78 -138

114 CVI-5 668100 954400 24 15 90 80 9 -81 -161

115 CVI-4 668100 959200 24 20 55 105 4 -51 -156

116 Dunklin-Ind 677000 974000 30 52 -22

117 IND3R 672764 976408 35 60 57 -25 -82

118 Burg&Div 94 713000 972000 24 15 30 95 9 -21 -116

119 Becker 1240 763000 972000 15 20 -5

120 Teq. 264042 789000 956000 8 20 82 -12 -94

121 BECKB30-1 748100 970200 19 15 4

122 BECKB30-2 748100 973500 19 15 4

123 HYD1A 776025 1005343 25 23 2

124 JU13 783667 943147 13 40 110 -27 -137

125 JU14 784500 943150 13 40 88 -27 -115

126 JU15 784300 938100 14 35 0 -21

127 JU18 786700 938100 14 45 80 -31 -111

128 GMRB1 768600 946800 15 40 85 -25 -110

129 GMRB3 768600 943500 15 15 130 0 -130

130 GMCE1 778500 937800 16 50 80 -34 -114

131 GMCE2 774400 938000 16 30 140 -14 -154

TABLE A-1: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# Coordinates Surface Layer Layer Layer Layer I Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

132 GMCE3 770200 938100 16 20 110 -4 -114

133 M1012 710814 1028439 24 20 80 40 4 -76 -116

134 M1013 737462 1028182 12 30 90 50 -18 -108 -158

135 M1014 781628 990500 25 30 130 70 -5 -135 -205

136 M1015 758234 985896 15 15 120 60 0 -120 -180

137 M1016 739757 991136 19 15 80 60 4 -76 -136

138 M1017 757938 1018511 15 30 130 30 -15 -145 -175

139 M1018 738937 1007691 12 20 80 50 -8 -88 -138

140 M1019 712020 987348 25 15 90 50 10 -80 -130

141 M1020 675904 975362 20 80 40 50 -60 -100 -150

142 M41021 663212 1028322 31 15 30 110 16 -14 -124

143 M1022 694916 1028461 30 20 50 80 10 -40 -120

145 M1030 745997 1050852 15 40 55 15 -25 -80 -95

146 M1038 794316 960388 13 20 -7

147 M1039 796398 960302 25 35 -10

148 M1040 644262 997757 30 15 90 70 15 -75 -145

149 M1041 604957 1026919 28 30 70 100 -2 -72 -172

150 M1042 641351 1029048 36 40 120 10 -4 -124 -134

151 M1043 752207 1054021 11 61 59 90 -50 -109 -199

153 M1050 734858 1041193 5 37 118 10 -32 -150 -160

154 M1051 739244 1032332 5 55 82 -50 -132

155 M1052 763889 1020468 8 50 47 20 -42 -89 -109

156 M1053 769739 1023838 5 15 172 0 -10 -182 -182

157 M1070 792971 971386 21 27 208 -6 -214

158 M1075 745223 984301 19 35 51 -16 -67

159 M1085 668259 964930 24 18 72 6 -66

160 M1088 639304 967144 24 15 72 58 9 -63 -121

161 M1089 700363 1004455 27 15 64 12 -52

162 M1091 750043 1038860 12 43 112 27 -31 -143 -170

163 M1095 791774 974407 30 20 10

164 M1096 735291 965764 22 24 40 82 -2 -42 -124

165 M1097 776898 1007224 10 20 -10

TABLE A-i: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom BottomCoordinates Surface Layer Layer Layer Layer I Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

167 M623 744500 1041000 10 45 -35

168 M841 744500 1031000 15 55 113 42 -40 -153 -195

169 JURO1 782200 945700 13 40 100 60 -27 -127 -187

170 PBPkCom 736400 935200 24 12 12

171 SW-1 749789 1050875 5 60 50 -55 -105

172 MPLCLUB 738500 1001800 15 50 85 20 -35 -120 -140

173 M1181 747400 1031150 15 41 -26

174 M1189 747550 1033700 15 40 -25

175 EVANS 628000 1062900 27 15 110 20 12 -98 -118

176 REDTOP 582000 1046000 25 30 58 15 -5 -63 -78

177 KINGSBAY 576000 1047000 20 40 25 -20 -45

178 W5405 599650 1017200 17 22 78 59 -5 -83 -142

179 W14754 647750 983800 28 20 60 82 8 -52 -134

180 W15817 612500 1000100 15 30 88 11 -15 -103 -114

181 BTW-1 652354 991086 33 20 60 84 13 -47 -131

182 BTW-2 652258 977089 23 40 25 54 -17 -42 -96

183 BTW-3 643646 995507 31 31 44 83 0 -44 -127

184 BTW-4 652283 984402 31 30 50 85 1 -49 -134

185 ALLAPAPT 685200 1032100 30 15 32 108 15 -17 -125

186 JDSPAPT 771850 979525 12 30 90 102 -18 -108 -210

187 MONREVE 728050 986500 22 15 64 50 7 -57 -107

188 MOBIL 750900 1003700 13 60 60 50 -47 -107 -157

189 PALMAR 722320 963020 24 25 65 -1 -66

190 EVANS 635000 1036000 30 45 45 70 -15 -60 -130

192 MF3 766873 1047651 6 60 10 75 -54 -64 -139

193 SLF-23 672337 1049363 30 21 9

194 MF-4 772700 1037000 9 15 190 60 -6 -196 -256

195 PB-1607 768207 926382 18 35 99 35 -17 -116 -151

196 PB-1550 731213 918686 23 36 104 13 -13 -117 -130

197 HSP83-1 767400 969600 14 25 102 -11 -113

198 HSP83-2 766150 975400 14 15 94 -1 -95

199 HSP83-3 764850 979450 14 30 130 -16 -146

TABLE A-i: Lithologic Well Data (Continued)

Map Well Name State Plane Land Model Model Model Bottom Bottom Bottom# .Coordinates Surface Layer Layer Layer Layer 1 Layer 2 Layer 3

Elev. 1 2 3 Elev Elev ElevEast North Thick Thick Thick NGVD NGVD NGVD

200 HSP83-4 757400 978000 15 15 116 0 -116

201 HSP83-5 754600 983600 15 15 140 0 -140

202 HSP89-15 763800 967500 15 15 77 0 -77

203 HSP89-16 765000 968900 15 15 85 0 -85

204 HSP89-17 763700 970300 15 26 69 -11 -80

205 HSP89-18 765500 971350 14 21 94 55 -7 -101 -156

206 HSP89-19 763700 972850 14 15 130 -1 -131

207 HSP89-20 763800 975100 14 20 110 -6 -116

208 HSP89-21 766050 967500 12 28 52 -16 -68

209 HSP89-22 760450 975600 10 15 -5

210 STLCH5 659808 1044364 26 15 18 11 -7

211 TC21-44 746700 1036400 15 45 100 -30 -130

212 PB708 807905 921812 18 25 100 -7 -107

213 PB709 807899 922619 17 24 151 -7 -158

214 PB830 694365 915669 22 15 40 112 7 -33 -145

216 PB1109 730861 916765 23 29 125 -6 -131

217 PB1099 768387 926585 18 27 93 49 -9 -102 -151

218 HSMW4DL 781000 989000 40 30 131 71 10 -121 -192

220 HSMW2D 782750 989500 30 37 57 -7 -64

221 HSSW4 782900 988600 35 44 71 -9 -80

222 HSSW3 785000 988800 40 44 71 -4 -75

223 HSSW1 785400 989400 7 20 61 -13 -74

224 GMSC2 794900 927500 13 36 -23

225 GMSC8 770000 917200 18 35 155 36 -17 -172 -208

226 GMSC11 779000 931800 18 50 72 22 -32 -104 -126

227 GMSC20 799500 918300 10 34 108 98 -24 -132 -230

228 GMSC22 795200 932800 10 23 225 130 -13 -238 -368

229 GMSC25 792400 938000 8 33 176 90 -25 -201 -291

230 GMSC31 768800 932800 18 39 24 -21

231 GMSC33 791900 916800 14 40 125 -26 -151

232 MPLWOOD 785750 939200 14 50 95 115 -36 -131 -246

233 GMJLTW2 795300 939500 6 53 102 -47 -149_ _ _ _- = - - - - _

TABLE A-2: Source of Lithologic Data

Somurce Development/Report Map Number

SFWMD Unpublished 1-23,82,83,185-188,210

Geraghty & Miller City of Stuart 24-27

SFWMD Tech Pub 84-2 28

FP&L Martin Power Plant 29-41

Gee & Jenson Miles Grant 42-45Gee & Jenson Martin Downs 46-53

Perrson Drilling Corp St. Lucie Falls 54-56

CH2MHill Stuart So. Wellfld 57,58

Gee & Jenson Banyan Bay 59,60USGS Hobe Sound/Unpublished 61

USGS J.D.S. Park/Unpublished 62

Geraghty & Miller Woodside 63USGS Tequesta/Unpublished 64

CH2MHill Pipers Landing 65Geraghty & Miller GDC-Martin Co. 66-70Geraghty & Miller Stuart Y & CC 71Geraghty & Miller Harbour Ridge 72Geraghty & Miller River Bend Pk 73USGS Open File Rpt 76-713 74-80

USGS Unpublished 81,195,196

Gee & Jenson Tequesa 84-88

Ray Domer, Driller Okeechobee 90

Frank DeCarlo, Driller Pioneer Estates 92Ray Domer, Driller Turnpike Dairy 93

Martin Co. Well Drilling Stuart West 94

BJ. McCullers, Driller Palm City 95

Dan Barrett, Driller Indiantown 96

Steve Ordway, Driller Caulkins Indiantown 97,98

D. Spencer, Driller Burg & Divosta 99,104,118

Steve Ordway, Driller 100

Steve Ordway, Driller Pero Farms 101

D. Spencer, Driller Burg & Divosta 104

A.E.C.O.A., CI2MHill Hobe Sound 105

TABLE A-2: Source of Lithologic Data (Continued)

Somrce DevelopmentReport Map Number

Steve Ordway, Driller Hobe Sound 106

Gordon Beams, Driller Hobe Sound 107

Steve Ordway, Driller Hobe Sound 108

Steve Ordway, Driller Hydratech 109

Donald Barrett, Driller Tequesta 110

David Webb, Driller PB Pk of Commerce 111

Steve Ordway, Driller Caulkins Venture 11 112-115

Ray Domer, Driller Dunklin Mem. Camp 116

David Webb, Driller Indiantown 117

D. Spencer, Driller Burg & Divosta 118

Steve Ordway, Driller Becker Groves 119

Kenneth Morgan, Driller Tequesta 120

Steve Ordway, Driller Becker Groves 121,122

Steve Ordway, Driller Becker Groves 122

G. Bobo & Assoc Hydratech 123

Geraghty & Miller Jupiter 124-127,169

Geraghty & Miller River Bend Pk 128,129

Geraghty & Miller PB Country Estates 130-132

USGS Open File- Rpt 79-1543 133-165

USGS RI 23 167,168

? PB Pk of Commerce 170

Dames & Moore Michigan Players Club 172

USGS Letter to City of Stuart 11/13/86 173,174

Ray Domer, Driller Evans Prop./Bluefield 175,190

Ray Domer, Driller Red Top Dairy 176

David Webb, Driller Kings Bay 177

FL B.O.G. FBOG Database 178-180

Bechtel FP&L Coal GassiL 181-184

Dames & Moore PalMar WCD 189

SFWMD Tech Pub 80-5 192-194

Geraghty & Miller Hobe Sound Plantation 197-209

Enviropact Serv 211

USGS Open File Rpt 76-713 212-214

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MAPS OF HYDRAULIC PARAMETERS

LIST OF FIGURES - APPENDIX B

Figure Page

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B-2 Layer 2 Transmissivity ...................................... 110

B-3 Layer 3 Transmissivity (with multiplier) .................... 111

B-4 Vertical Conductance (VCONT) Between Layers 1 and 2 ........ 112

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GENERAL HEAD, RIVER AND DRAIN

INPUT DATA

LIST OF FIGURES- APPENDIX C

Figure Page

C- Location of Drain Structures ........... ......... ........... 119C-2 Location of River Stage Stations ........................... 125

LIST OF TABLES - APPENDIX C

Table Page

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STRUCTURE(WEIR)NAME

LOX.CYPR

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23.5

22.5

22.5

24.5

25

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19.4

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INDIANTWN 16

WEST END 16

C(C-44) 15.8

D(C-44) 15.8

E(C-44) 15.8

HSL KITCH 13CRK

LOX.HOBE 2.17

HSL II 15

HSL L49 15

HSL SFORK 11

S97D 0.27 (7.79)

S80D 0.27 (0.32)

MDSW7-BES 0.27 (2.42)

MDSW10 0.27 (4.19)

MDSW11 0.27 (12.38)

MDSW12 0.27 (6.66)

MDSW3-DAN 0.27 (1)

SLR-HARB 0.27

SLR-CARD 0.27

LOX.TPK 0.44 (2.75)

LOXTRAP 0.44 (0.66)

LOX.VAUGH 0.38

C23 21.48

TABLE C-2:

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APPENDIX D

RECHARGE METHODS,RAINFALL STATION MAP AND TABLE,

RECHARGE AND ET COEFFICIENTS

APPENDIX D

Page

Recharge Calculations .................................................. 135

LIST OF FIGURES - APPENDIX D

Figure Page

D-1 Locations of Rainfall Stations ............................... 137

D-2 Evapotranspiration Surface ................................ 150

LIST OF TABLES - APPENDIX D

Table Page

D-1 Rainfall Station Descriptions ............................. 138

D-2 S.F.W.M.D. Land Use and Land Cover Classification Code ....... 140

D-3 Coefficients Used in Recharge Preprocessing ............. ..... 144

D-4 Crop Coefficients/Land Use Type Coefficients/Percent Coverage . 146

D-5 Extinction Depths Used in ET Preprocessing ................. 151

RECHARGE

The average recharge depth in a model cell resulting from precipitation, Rp, can be computed usingthe mass balance equation as:

R, = P, - Qd - ET, - ET, (1)

whereP, is the average net precipitation depth over the cell not lost to interception or depressional storage,

Qd is the average depth of water lost to surface drainage (not otherwise simulated using aMODFLOW package), and

ET, is the average evapotranspiration depth from the unsaturated zone (not calculated by theevapotranspiration package in MODFLOW).

ET, is the average evapotranspiration depth from the saturated zone (calculated by theevapotranspiration package in MODFLOW).

The evapotranspiration from the unsaturated zone, Er, was not considered in this model. In areas wherethere is a significant unsaturated zone above the water table, however, the recharge calculations may becomeinaccurate without considering ET. This limitation will be resolved in the complete recharge package(currently under development).

Net Precipitation: The average monthly net precipitation depth, Pn, for a cell can be approximatedfrom the total monthly precipitation depth over the cell, Pt, as:

NP. = MAX{KJ'P - ( M Kd(n), 0} (2)

n=1where

KI in the interception coefficient,

Kd(n) is the daily depression storage loss due to evaporation, and

n is the number of days in the month.

Interception is that portion of gross precipitation which wets and adheres to above ground objectsuntil it returns to the atmosphere through evaporation (Bower, et al., 1990). The quantity of water intercepteddepends upon the storm character, the season of the year, and the species, age, and density of the prevailingplants and trees. The total interception by an individual plant is directly related to the amount of foliage.For non-urban land uses, extreme values of Ki can be defined as (Viessman, et al., 1977):

1.00 for clear bare ground surface (0% interception)

0.75 for dense closed forest (25% interception).

Values for R in urban areas ranged from 1.00 to 0.50, depending upon the land use type. The value of KIassigned to a model cell represented the weighted average of the I values for all land use types within thecell. Table D-3 lists land use types and corresponding values for K.

Precipitation that reaches the ground surface may infiltrate, flow over the surface, or become trappedin numerous small depressions. The depression-storage loss for impervious drainage areas varies from 0.05",on a slope of 2.5%, up to 0.11", on a slope of 1% (Bower, et al., 1990). The upper limit of 0.11" was assumed

for each precipitation event. The model depression storage loss, K, was calculated as:

Kd = KIa {MAX{[1 -SQR(K/Km)], 0}} (3)

whereKd" is the sum of maximum depression storage losses for the stress period computed on a daily basis(an upper limit of 0.11 was assumed for each day),

K is the hydraulic conductivity of the soil layer, and

Km is a calibration factor. It is defined as the value of hydraulic conductivity at which infiltration isassumed to be nearly instantaneously related to the potential evaporation rate.

A value of (K/IK) = 0, signifying an impervious drainage area, implies a value of K, = 0.11" per singleprecipitation event, and a value of (KiK.) = 1, a highly pervious area, implies a Ki = 0. Rainfall of less thanthe critical daily precipitation depth Kd evaporates and creates neither infiltration nor runoff drainage.

Only one precipitation event per rainy day of at least 0.11" was assumed. Interception - storagecapacity is usually reached early in a storm event. This implies that a larger fraction of rainfall is interceptedin depressions during numerous small storms that during infrequent severe storms (Bower, et al, 1990).

The value of soil hydraulic conductivity, K, in a model cell was estimated by examination of the tablesof saturated vertical permeability for applicable soil types found in Soil Conservation Service soil survey books(McCollum, et al., 1981 and McCollum, et al., 1978). Soil permeability values ranged from 2 feet/day to 47feet/day throughout the modeled area. The instantaneous hydraulic conductivity, Km, was set at 47 ft/day

Surface Drainage: The surface drainage depth is defined as the difference between the netprecipitation depth, P,, and the net infiltration (Bower, et al., 1990). Then net average depth of water lostto surface drainage, Qd,, can be estimated by:

Qd = (KYj(K)(Ph) (4)

where

K is a coefficient relating the potential for runoff to surface drainage, and

K, is a coefficient relating the potential for aquifer recharge from surface drainage.

K, varies between 0 and 1, depending on the potential of the land use type to have surface drainageinto a canal or into a surface water body. Factor KI takes into account the effector of drainage systems whichmay recharge the unsaturated zone of the aquifer. The value of K, is a function of the average hydraulicconductivity and the average slope of the land surface. It has a value of 1 if there if no drainage into theunsaturated zone, and has a value of 0 when rainfall completely recharges the unsaturated zone. Model valuesfor K, varied between .1 and .3. Table D-3 lists land use codes and the K, value assigned for each code. Thevalue for Ka was uniformly set to 0.1 and was defined as:

K = Kx(1-K/J. ) (5)

where

K" is the maximum value that K, may take (less than or equal to 1), and

K is the maximum soil hydraulic conductivity in the study area.

T 3 S

5 t .1

TABLE D-1: Rainfall Station Descriptions

Map State Plane CoordinatesNo. Rainrall Station Source

East North

1 631328 939000 North Unit SFWMD

2 726776 934919 Pratt & Whitney SFWMD

3 785001 946690 Simms Creek SFWMD

4 772612 972256 Kitchings Creek SFWMD

5 739724 1058288 No Mt Co Water Plant SFWMD

6 743790 1042559 Stuart 1N USWB

7 610177 1000579 S-135 SFWMD

8 624749 963968 S-308 USWB

9 732597 1010079 S-80 USWB

10 564645 1044001 S-133 SFWMD

11 673871 1049370 BlueGoose SFWMD

12 768500 1023500 Miles Grant Miles Grant Utility

13 673050 976400 Indiantown Indiantown Utility

14 784500 988400 Hobe Sound Hobe Sound Utility

15 775600 1006300 Hydratech Hydratech Utility

16 795900 958350 Tequesta Tequesta Utility

17 724500 1031500 Martin Downs Martin Downs Utility

18 643900 986400 FPL1 Florida Power & Light

19 640550 976000 FPL2

20 633800 970500 FPL3

21 630900 974400 FPL4

22 629450 983300 FPL5

23 628900 987500 FPL6

24 627250 995700 FPL7

25 641000 996000 FLP8

26 761510 1015140 Mt Co Dixie Park Martin County Utility

27 724900 1049900 Harbour Ridge Harbour Ridge Utility

28 737700 1022400 Pipers Landing Pipers Landing Utility

29 755500 993500 HSL B14 Hobe St. Lucie Conservancy District

30 748000 975500 HSL B12

31 761000 972500 HSL B13

32 796200 941200 Jonathan's Landing Jonathans Landing Golf Maintenance

TABLE D-1: Rainfall Station Descriptions (Continued)

Map State Plane CoordinatesNo. Rainfall Station Source

East North

33 758300 963000 Old Trail (West) Old Trail Golf Maintenance

34 760700 959800 Old Trail (East) Old Trail Golf Maintenance

35 763400 935800 SIRWCD South Indian River Water Control Dist.

36 679250 997800 Troup Ind. WCD 801 Coca-Cola Groves - Indiantown

37 679300 1003000 Troup Ind. WCD 803

38 679300 1008500 Troup Ind. WCD 805

39 687500 984900 Troup Ind. WCD 814

40 689750 993900 Troup Ind. WCD 817

41 690100 1001900 Troup Ind. WCD 820

42 689750 978800 Robinson Blk 1 Indian Sun Groves

43 689700 974200 Robinson Blk 8

44 690300 972050 Robinson Blk 12

45 689050 975300 Robinson Blk 21

46 685600 975400 Robinson Blk 27

47 683400 975600 Robinson Blk 30

48 680750 972100 Chastain Blk 1 Indian Sun Groves

49 684500 973400 Chastain Blk 6

50 684400 970700 Chastain BIk 8

51 688000 970800 Chastain Blk 11

52 687100 968800 Chastain Bik 13

53 691900 969900 Chastain BIk 17

54 689700 967400 Chastain BIk 19

55 691000 964800 Chastain Blk 21

56 684300 987300 CircleT Blk 2 Indian Sun Groves

57 682200 987300 CircleT Blk 9

58 678200 987300 CircleT Blk 21

59 674600 989550 CircleT Blk 35

60 678200 989550 CircleT Blk 48

61 681800 989550 CircleT Blk 55

62 705456 1034067 Martin Co. Landfill Martin County Solid Waste Facility

S.F.W.M.D. Land Use and Land Cover Classification Code

LEVEL 1I LEVEL II LEVEL II

(U) Urban and built-up land

(UR) Residential

(URSL) Single-family, Low Density (under 2 D.U./grossacrej(URSM) Single-family, Medium Density (2 to 5 D.U./gross acre)(URSH) Single-family, High Density (over 5 D. U./gross acre)(URMF) Multi-family building(URMH) Mobile homes

(UC) Commercial and Services

(UCPL) Parking lot(UCSC) Shoppingcenter(UCSS) Sales and services(UCCEj Cultural and Entertainment(UCMCI Marine commercial (Marinas)(UCHM) Hotel-Motel

(UI) Industrial

(UIJK) Junkyard(UILT) Other light industrial(UIHV) Other heavy industrial

(US) Institutional

(USED) Educational(USMD) Medical(USRL) Religious(USMF) Military(USCF) Correctional(USGF) Governmental (other than military or correctional)(USSS) Social services (Elks, Moose, Eagles)

(UT) Transportation

(UTAP) Airports(UTAG) Small grass airports(UTRR) Railroad yards and terminals(UTPF) Port facilities(UTEP) Electrical power facilities(UTTL) Major transmission lines(UTHW) Major highway and rights-of-way(UTWS) Water supply plants(UTSP) Sewerage treatment plants(UTSW) Solid waste disposal

TABLE D-2:

S.F.W.M.D. Land Use and Land Cover Classification Code (Continued)

(UTRS) Antennaarrays(UTOG) Oil and gas storage

tUO) Open and others

(UORC) Recreational facilities(UOGC) Golfcourses(UOPK) Parks(UOCM) Cemeteries(UORV) Recreational vehicle parks(UOUD) Open under development(UOUN) Open and undeveloped within

urban area

(A) Agriculture

(AC) Cropland

(ACSC) Sugar cane(ACTC) Truck crops(ACRF) Rice fields

(AP) Pasture

(APIM) Improved pasture(APUN) Unimproved pasture

(AM) Groves, Ornamentals, Nurseries, Tropical fruits

(AMCT) Citrus(AMTF) Tropical fruits(AMSF) Sod farms(AMOR) Ornamentals

(AF) Confined feeding operations

(AFFL) Cattle feed lots(AFDF) Dairy farms(AFFF) Fish farms(AFHT) Horse training and stables(AFPY) Poultry

(R) Rangeland

(RG) Grassland

(RS) Scrub and brushland

(RSPP) Palmetto prairies(RSSB) Brushland

(F) Forested uplands

TABLE D-2:

S.F.W.M.D. Land Use and Land Cover Classification Code (Continued)

(FE) Coniferous

(FEPF) Pine flatwoods(FESP) Sand pine scrub(FECF) Commercial forest (pinej

(FO) Non-coniferous

(FOAP) Australian pine(FOBP) Brazilian pepper(FOPA) Palms(FOSO) Scrub oak(FOOK) Oak(FOCF) Commercial forest

(FM) Mixed forested

(FMTW) Temperate hardwoods(FMCM) Cabbage palms/Melaleuca(FMCO) Cabbage palms/Oaks(FMPM) Pine/Melaleuca(FMPO) Pine/Oak(FMTH) Tropical hammocks(FMOF) Old fields forested(FMCD) Coastaldunes(FMPC) Pine/Cabbage palms

(W) Wetlands

(WF) Forested fresh

(WFCM) Cypress/Melaleuca(WFCY) Cypress(WFWL) Willow(WFME) Melaleuca(WFSB) Scrub and brushland(WFMX) Mixed forested

(WN) Non-forested fresh

(WNSG) Sawgrass(WNCT) Cattail(WNBR) Bullrush(WNWC) Wire cordgrass(WNAG) Mixed aquatic grass(WNWL) Sloughs

(WS) Forested salt

(WSRM) Red mangrove(WSBW) Black and White mangrove

(WM) Non-forested salt

TABLE D-2:

S.F.W.M.D. Land Use and Land Cover Classification Code (Continued)

(WX) Mixed forested and non-forested fresh

(WXPP) Pine and wet prairies(WXCP) Cypress domes and wet prairies(WXHM) Hardwood marsh

(H) Water

(B) Barren land

(BB) Beaches(BP) Extractive

(strip mines, quarries, andgravel pits)

(BS) Spoil areas(BL) Levees

* Documentation of major codes from "LAND USE, COVER AND FORMS CLASSIFICATIONSYSTEM, A TECHNICAL MANUAL", Department of Transportation, State Topographic OfficeRemote Sensing Center, Kuyper, Becker and Shopmyer, February 1981

TABLE D-2:

Coefficients Used in Recharge Preprocessing

LandUse

U

UR

URSL

URSM

URSH

URMF

URMH

UC

UCPL

UCSC

UCSS

UCCE

UCMC

UCHM

UI

UIJK

UILT

UIHV

US

USED

USMD

USRL

USMF

USCF

USGF

USSS

UT

UTAP

UTAG .70

Ks KaKi

.75

.70

.80

.75

.70

.65

.60

.50

.50

.50

.50

.60

.50

.50

.50

.50

.50

.50

.50

.60

.50

.50

.50

.50

.50

.50

.60

.60

.10

.10

.10

.10

.10

.10

.10

.30

.30

.30

.30

.20

.20

.20

.30

.30

.20

.30

.20

.20

.30

.20

.20

.20

.20

.20

.20

.20

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

LandUse

AMOR

AF

AFFL

AFDF

AFFF

AFHT

AFPY

R

RG

RS

RSPP

RSSB

F

FE

FEPF

FESP

FECP

FO

FOAP

FOBP

FOPA

FOSO

FOOK

FOCF

FM

FMTW

FMCM

FMCO

FMPM .85

Ki

.70

.90

.90

.90

.90

.90

.90

.75

1.00

.80

.75

.80

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

.85

Ks

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

Ka

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

.10

TABLE D-3:

Coefficients Used in Recharge Preprocessing (Continued)

Land Ki Ks KaUse

UTRR .60 .10 .10

UTPF .60 .20 .10

UTEP .60 .10 .10

UTTL .60 .10 .10

UTHW .60 .10 .10

UTWS .60 .10 .10

UTSP .60 .20 .10

UTSW .60 .10 .10

UTRS .60 .10 .10

UTOG .60 .20 .10

UO .98 .10 .10

UORC .90 .10 .10

UOGC .75 .10 .10

UOPK .90 .10 .10

UOCM .90 .10 .10

UORV .80 .20 .10

UOUD .98 .10 .10

UOUN .75 .10 .10

A .80 .10 .10

AC .95 .10 .10

ACSC .83 .10 .10

ACTC .95 .10 .10

ACRF .86 .10 .10

AP .83 .10 .10

APIM .83 .10 .10

APUN .83 .10 .10

AM .85 .10 .10

AMCT .85 .10 .10

AMTF .85 .10 .10

AMSF .90 .10 .10

Land Ki Ks KaUse

FMPO .85 .10 .10

FMTH .85 .10 .10

FMOF .85 .10 .10

FMCD .85 .10 .10

FMPC .85 .10 .10

W .90 .10 .10

WF .85 .10 .10

WFCM .85 .10 .10

WFCY .85 .10 .10

WFWL .85 .10 .10

WFME .87 .10 .10

WFSB .80 .10 .10

WFMX .80 .10 .10

WN .90 .10 .10

WNSG .90 .10 .10

WNCT .90 .10 .10

WNBR .90 .10 .10

WNWC .90 .10 .10

WNAG .90 .10 .10

WNWL .90 .10 .10

WS .85 .10 .10

WSRM .85 .10 .10

WSBW .85 .10 .10

WM .90 .10 .10

WX .90 .10 .10

WXPP .90 .10 .10

WXCP .90 .10 .10

WXHM .90 .10 .10

H 1.00 .10 .10

TABLE D-3:

Crop Coefficients/Land Use Type Coefficients/Percent Coverage

Land Covered MonthUse

% 1 2 3 4 5 6 7 8 9 10 11 12

U .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UR .48 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

URSL .67 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

URSM .53 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

URSH .45 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

URMF .33 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

URMH .40 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UC .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCPL .25 .8.8 080 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCSC .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCSS .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCCE .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCMC .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UCHM .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UI .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UIJK .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UILT .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UIHV .05 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

US .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USED .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USMD .60 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USRL .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USMF .60 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USCF .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USGF .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

USSS .70 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UT .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTAP .10 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

TABLE D-4:

TABLE D-4: Crop Coefficients/Land Use Type Coefficients/Percent Coverage(Continued)

Land Covered MonthUse

% 1 2 3 4 5 6 7 8 9 10 11 12

UTAG .20 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTRR .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTPF .05 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTEP .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTTL .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTHW .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTWS .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTSP .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTSW .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTRS .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UTOG .50 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UO .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UORC .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UOGC .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UOPK .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UOCM .90 .80 .80.80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UORV .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UOUD .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

UOUN .90 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80 .80

AC .90 .41 .44 .63 .67 .64 .69 .72 .71 .72 .86 .74 .64

ACSC .90 .39 .30 .53 .61 .70 .79 .79 .84 .73 .88 .72 .69

ACTC .85 .44 .71 .82 .78 .53 .49 .57 .44 .71 .82 .78 .53

ACRF .. 90 .39 .30 .53 .61 .70 .79 .79 .84 .73 .88 .72 .69

AP .90 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

APIM .90 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

APUN .90 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AM .85 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AMCT .85 .63 .66 .68 .70 .71 .71 .71 .71 .7 .68 .67 .64

AMTF .85 .27 .42 .58 .70 .78 .81 .77 .71 .63 .54 .43 .3

AMSF .90 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

TABLE D-4: Crop Coefficients/Land Use Type Coefficients/Percent Coverage(Continued)

Land Covered MonthUse Use % 1 2 3 4 5 6 7 8 9 10 11 12

AMOR .85 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AF .76 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AFFL .75 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AFDF .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AFFF .75 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AFHT .75 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

AFPY .75 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

R 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

RG 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

RS 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

RSPP 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

RSSB 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

F .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FE .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FEPF .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FESP .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FECF .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FO .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOAP .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOBP .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOPA .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOSO .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOOK .. 80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FOCF .80 .61 .71 .91 1.06 1.13 1.15 1.15 1.14 1.08 .98 .84 .69

FM .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

FMTW .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMCM .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMCO .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMPM .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMPO .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

TABLE D-4: Crop Coefficients/Land Use Type Coefficients/Percent Coverage(Continued

Land Covered MonthUse

% 1 2 3 4 5 6 7 8 9 10 11 12

FMTH .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMOF .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMCD .80 .49 .57 .73 .87 .67 .92 .92 .91 .87 .79 .67 .55

FMPC .80 .49 .57 .73 .85 .67 .92 .92 .91 .87 .79 .67 .55

W .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WF .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WFCM .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WFCY .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WFWL .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WFME .80 .73 .84 .99 1.14 1.24 1.30 1.28 1.22 1.14 1.05 .90 .75

WFSB .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WFMX .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WN .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNSG .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNCT .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNBR .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNWC .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNAG .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WNWL .80 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

WS .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WSRM .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WSBW .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WM .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WX .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WXPP .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WXCP .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

WXHM .80 .62 .71 .76 .97 1.05 1.11 1.09 1.04 .97 .89 .77 .64

H 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55

B 1.0 .49 .57 .73 .85 .90 .92 .92 .91 .87 .79 .67 .55_ _ -- - - - - a - - =I

149

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APPENDIX E

WATER USE DATA,

PUBLIC AND AGRICULTURAL

LIST OF FIGURES - APPENDIX E

Figure Page

E-1 Location of Public Water Supply Utilities ...................... 157

LIST OF TABLES - APPENDIX E

Table Page

E-1-A Description of Public Supply Utility Wells Used in Model(Community Systems) .................................... 158

E-1-B Description of Public Supply Utility Wells Used in Model(Non-Community Systems) ................................ 162

E-2 Public Water Supply Utility Pumpage Data .................... 165

E-3 Comparison of Actual Reported Pumpages to Permitted Pumpagesin Public Water Supply Wellfields ......................... 171

E-4-A Non-Potable Well Locations and Pumpages Used in Model(Individual Water Use Permits) ............................ 172

E-4-B Non-Potable Well Locations and Pumpages Used in Model(General Water Use Permits) ................................ 183

E-5 Non-Potable Water Use Permits in Model Area and Comparisonof Modelled to Permitted Pumpage ............................ 186

T35

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C)z

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Sg I S50*1

0.

a

a-

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J-

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S t A

157

TABLE E-1-A: Description of Public Supply Utility Wells Used in Model(Community Systems)

WELLINDEX

4300041

4300053 STUART

UTILITYNAME

IND LANTOWN

2

3

4

5

6

7

8

9

10

11

12

13

15

16

22

23

24

25

26

27

28

29

WELLNAME

1

2

3

4

5

6

7

180

180

140

140

140

140

160

160

180

180

180

180

180

180

180

240

240

240

450

440

520

480

PUMPCAPAC.(GPM)

425

150

135

100

200

180

260

4

4

4

4

4

4

4

4

4

4

4

5

5

5

7

6

5

6

8

9

8

8

ROW

35

35

35

35

34

34

34

78

78

78

78

78

78

79

79

79

79

79

79

79

79

80

79

78

78

79

79

79

78

STATE PLANECOORDINATES

COL

41

41

41

41

40

40

40

X

673149

672809

672611

672238

671830

671568

671283

746577

746643

747093

746800

747677

747250

747800

748280

748650

748283

748990

749733

748296

748716

749113

750936

748503

747677

747850

749640

748386

749056

747536

748626

PUMPAGEMETHODOLOGY AND

CALCULATIONS(MT = Monthly Total)

MT * .293

MT * .103

MT * .093

MT * .069

MT * .138

MT * .124

MT * .179

Y

976576

976797

976588

976679

977061

977312

977530

1038761

1038450

1038788

1038100

1038778

1038100

1037800

1038831

1038395

1037615

1037618

1037625

1036721

1035421

1035098

1032628

1034918

1035211

1034508

1029408

1028789

1030768

1030012

1029729

PUMP HOURS *CAPACITY

I I I I

i

TABLE E-1-A: Description of Public Supply Utility Wells Used in Model(Community Systems) (Continued)

WELL UTILITY WELL PUMP ROW COL STATE PLANE PUMPAGEINDEX NAME NAME CAPAC. COORDINATES MEIHODOLOGY AND

(GPM) CALCULATIONSX Y (MT = Monthly Total)

4300066 HYDRATECH 2 100 20 92 775676 1006562 MT * .09

3 100 20 92 775520 1006464 MT ' .09

6 100 20 92 775537 1006625 MT * .09

4A 250 20 92 775388 1006330 MT * .23

1A 275 20 93 776015 1005426 MT * .25

2A 275 20 93 776197 1005356 MT * .25

SC 100 25 95 780750 996200 MT

4300076 HOBE SOUND 3 500 29 96 783605 988850 MT * .10

5 500 29 97 784022 988747 MT * .10

6 500 29 97 784223 988402 MT * .10

7 500 29 96 783837 988582 MT * .10

8 500 29 96 783486 988574 MT * .10

9 500 29 96 783227 988685 MT * .10

10 450 29 96 783332 988971 MT * .10

11 500 28 96 783679 989199 MT " .10

12 500 29 96 782788 988067 MT * .10

13 500 29 96 782951 987751 MT * .10

4300086 MILES GRANT 1 215 12 88 766016 1022268 PUMP HOURS "CAPACITY

2 280 12 88 66379 1022402

3 160 12 88 766917 1022600

4 225 11 88 767095 1023246

5 170 11 88 767490 1023410

6 215 11 88 767647 1023781

4300089 MARTIN CO. 2 218 15 85 761200 1015950 MT * .194VISTA SALERNO

4 225 15 85 760150 1015800 MT * .20

3 290 15 85 761512 1015146 MT * .258

6 220 16 85 760547 1014996 MT * .196

5 170 15 84 758522 1015004 MT * .151

1A 10 83 757283 1026133 MT * .50

7B 10 83 756894 1026440 MT * .50

4300164 ST. LUCIE FALLS 1 250 21 69 729415 1004482 MT * 50

2 125 21 69 729767 1004139 MT * .50

TABLE E-1-A: Description of Public Supply Utility Wells Used in Model(Community Systems) (Continued)

WELLINDEX

4300169

4300173

4300277

4300342

5000010 JUPITER

UTILITYNAME

MARTIN DOWNS

PIPER'S LANDING

DEPT. OFCORRECT.

FISHERMAN'S COVE

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

WELLNAME

1

2

4

1

2

3

4

1

2

250

200

200

200

240

300

300

350

350

300

700

700

500

250

650

550

350

395

360

560

590

PUMPCAPAC.(GPM)

700

600

140

149

149

149

149

250

250

50

50

50

50

51

51

51

51

51

51

51

51

51

54

54

54

54

52

53

54

54

ROW

6

5

11

2

2

2

2

10

10

STATE PLANECOORDINATES

COL

66

67

73

38

38

38

38

77

77

95

95

95

9

96

95

95

95

95

95

95

96

96

97

97

97

98

98

97

95

96

96

97

X

722755

725427

737289

667191

667123

666775

666334

745252

745380

782450

782100

782350

782050

782600

781600

781500

781600

781500

781600

781450

782500

783550

784400

784200

785162

786000

787000

784350

781900

782985

782073

784278

PUMPAGEMETHODOLOGY AND

CALCULATIONS(MT = Monthly Total)

MT * .50

MT * .50

MT

MT * .25

MT * .25

MT * .25

MT " .25

MT * .50

MT * .50

y

1034591

1036453

1023301

1042246

1042506

1042465

1042317

1026661

1026312

946080

946056

945673

945859

945663

943511

943698

944177

944354

944700

943927

943400

943400

943281

938025

937992

938000

938000

942200

940000

937886

937938

935158

FLOW METER

TABLE E-1-A: Description of Public Supply Utility Wells Used in Model(Community Systems) (Continued)

UTILITYNAME

TEQUESTA

PRATT & WHITNEY

PB PK OF COMM

WELLNAME

24

25

26

27

7R

8R

18

19

20

23

2

3

4

7

8

1

2=r

PUMPCAPAC.(GPM)

820

590

340

480

750

750

200

200

200

1250

250

250

150

250

250

ROW

57

57

57

56

56

45

45

43

43

43

44

56

56

56

56

56

55

55

COL

97

96

96

96

102

103

102

102

102

102

68

68

69

69

69

73

73

STATE PLANECOORDINATES

784250

782826

782315

782509

781300

795500

796400

795000

794900

794700

795600

727550

727900

728250

728000

728500

736400

737500

932297

932699

932665

934536

934941

955425

955500

959800

960200

960700

958600

933800

933800

933800

933400

933400

935200

935200

PUMPAGEMETHODOLOGY AND

CALCULATIONS(MT = Monthly Tolal)

FLOW METERS

MT * .37

MT .37

MT * .19

MT .04

MT * .04

FLOW METERS

WELLINDEX

5000046

5000501

5001528

TABLE E-1-B: Description of Public Supply Utility Wells Used in Model(Non-Community Systems)

Model Model Population State Plan Coordinates

Map #tility N Row Column Served East NEast North

Palm Beach County (norlh of Donald Ross Road)

10 S & S Rentals (Sierra Sq) 50 88 25 767585 946953

11 Sunshine Tree School 59 96 25 782596 927923

12 Tri-Gas 53 66 25 723095 940783

13 Valmaron Country Store 52 86 25 762967 942000

14 West Jupiter Campground 49 78 25 747800 947800

Martin County (not Including Jensen Peninsula)

15 Ackels MHP 21 72 275 735500 1004000

16 Airport Bus. Park 5 80 124 750434 1033914

17 Angle Inn MHP 24 94 108 779000 997000

18 Anton's Plaza 12 85 25 761077 1022065

19 Armellini Truck 8 68 25 726796 1029333

21 Camp Welaka 41 98 200 782884 964852

22 Canoe Creek 3 68 310 727549 1040243

23 Casa Roma Rest. 10 81 25 753700 1025452

24 Caulkins Indiantown 31 35 65 660940 986004

25 Circle K-Kanner 6 76 25 742850 1033950

26 Coral Gardens Shp. Ctr. 11 82 74 754100 1024650

27 Country Place Rest 6 78 25 747500 1034000

28 Crestwood Condo 17 76 40 742800 1011760

31 Evergreen Club 2 66 100 723500 1042054

32 Fairmont Estates 14 76 128 743000 1017100

33 Farms Store 11 82 40 754250 1024447

34 First Assembly of God 7 73 88 737535 1031110

35 Fuirst Nat'l Bank/l'rust 7 73 25 737400 1032300

37 Florida Fisheries 7 62 25 714700 1031088

39 Fa Run 4 71 732000 1039000

40 Fraternal Order of Eagles 17 76 25 742900 1012200

42 Greentree MHP 19 74 186 739744 1007702

43 Heritage Square 9 73 25 736200 1028500

44 Hidden Harbor MHP 11 84 380 759252 1024982

45 Hobe Sound Bible College 26 96 315 783321 993231

TABLE E-1-B: Description of Public Supply Utility Wells Used in Model(Non-Community Systems) (Continued)

Model Model Populaton Sae Plane CoordlnaltesUtility ]NameMap # Row Column Served North

46 Hobe Sound MHP 26 94 318 779200 994000

47 Hobe Village MHP 26 95 140 781500 994000

48 Indianwood GolfCC 32 39 25 669531 981600

49 Interstate Ind. Park 8 67 100 724897 1029827

50 J & S Fish Camp 23 10 70 611100 999600

52 JDSP-Pine Grove 37 101 75 792500 971800

53 JDSP-River Area 40 94 25 778500 966800

54 J/T Church of Christ 38 101 444 793705 969876

56 Lakeside Village MHP 25 94 200 779000 995500

57 La Ruche Rest. 25 94 125 779350 995900

58 LI'l Saints-Golden Gate 8 81 100 753497 1030401

59 Martin Co. Min. Security 3 38 100 667593 1039144

60 Meyer Mobile Est. 13 81 170 753858 1020808

61 Midnight Farms Store 9 67 25 724001 1028509

62 Monterey Marine 17 73 30 736921 1012425

63 Monterey Motel 6 75 48 741600 1033500

64 Natalie Estates MHP 12 81 310 753740 1022500

65 New Life Ch of Christ 8 72 585 735500 1030000

66 Nichols Sanitation 29 93 65 776500 988200

67 Old Trail-Clubhouse 43 84 400 759844 960055

68 Old Trail-Golf Maint. Bldg 43 84 25 758500 960800

69 Old Trail-Sales Tr. 43 84 25 758500 959700

70 Open Gate Trailer Park 12 81 55 753833 1022000

72 Palm City Elem. 9 72 750 735550 1028500

73 Palm City Plaza 8 73 737800 1029600

74 Palms Motel 26 95 90 780065 993511

76 Pinelake Gardem 16 86 25 762500 1014207

77 Pines MHP 7 80 120 750133 1032548

78 Port Salerno Groc. 12 85 200 760178 1022450

82 River Landing 13 73 417 737600 1020300

83 Riverland MHP 8 76 420 743000 1030200

84 Rogers Quarters/Booker Pk 34 38 343 667700 977540

85 Ronny's Mobil Ranch 13 77 156 744500 1019500

TABLE E-1-B: Description of Public Supply Utility Wells Used in Model(Non-Community Systems) (Continued)

Model Model Popuation State Plane CoordinatesMap Utlity Name Row Colman Served East North

86 Salerno Tr. Pk (Old) 13 84 60 759100 1019500

87 Salerno Tr. Pk (New) 13 84 140 759500 1020468

89 Scottry's-Stuart 7 80 71 750176 1031893

90 Sea Breeze Mobile Man. 25 94 250 779500 995400

91 Seabridge Builders 17 88 30 766400 1012750

92 Soundings Y&CC 24 95 210 781000 998000

93 South End Improv. 37 101 158 793691 971896

94 South Fork Homeowners 18 76 400 743083 1009432

95 South Fork HS 24 76 1800 743152 997921

96 South River Condo 11 77 200 745525 1024900

97 St. Lucie Mob Vill, 33 50 550 691600 979650

98 St. Lucie Settlement 16 75 40 740200 1013400

99 STOP Camp (JDSP) 33 99 28 788206 980036

100 Stuart Aviation Ctr. 6 81 50 753779 1033430

101 Tannah Keeta Camp 40 95 200 780259 965036

102 Ted 'Iist Tank&Tummy 15 76 50 743044 1015096

104 Towering Pines MH 21 72 68 735800 1004700

106 Treasure Cove 21 94 58 778664 1004000

108 win Rivers MHP 18 90 60 769506 1009600

109 Tylander Systems 29 92 30 775500 987300

110 Vacation Park 26 94 177 779800 993050

112 Willoughby Creek Townhouses 7 83 35 756400 1032400

113 Willoughby Golf 9 79 749500 1028800

114 Woodbridge Mobile Vill 26 94 189 779500 995000

115 Woodside Subdiv. 2 71 25 734135 1041189

TABLE E-2: Public Water Supply Utility Pumpage Data

1989 PUMPAGE IN MILLION GALLONS PER MONTH

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT I NOV I DEC jAVG

Community Systems (Large Utilities)

5.965

2097

1.893

1405

2810

36452

3.644

1

2

3

4

5

6

7

INDIANTOWN 5.824

2047

1849

L372

2.743

2465

3.558

5.706

2006

1811

L344

2687

2415

1486

3.618

5.006

4.040

3.647

3.29

3.647

16473.647

3.793

3.620

1630

4000

1630

L630

.000

2859

3940

5.999

5.647

7.469

14320

&587

6.720

7.342

6.215

2.303

2303

4396

2.465

1465

1465

6299

6B47

6795

1.600

2876

4151

am

4884

am4000

1224

a000

alO

3.749

4.414

5.041

5.041

5.041

5.041

5.041

3407

5.199

7.727

7.266

7.450

4000

12676

9369

5380

2800

1800

2800

7.155

7.778

5.977

2101

L897

L407

2815

2529

3651

0.00amono

4609

amo

3.617

4000

40.000

4239

3.959

1753

3.753

13753

3.753

1753

3201

4775

(20B

6485

7.127

acO

IQ931

7.257

7887

2717

1717

2,717

6944

7.548

5.607

L971

1.780

1.321

2641

2373

3426

4.052

&000

1835

0.000

3.298

3 843

1.594

1.594

1.594

1.594

2262

1896

5.5

.568

7.389

11.551

6099

(649

2.500

.500

2500

4389

6945

5902

2075

L873

1.390

2.780

249%

3.606

1830

oam

3.2o1521

1431

2877

1757

L757

1.757

L757

L757

2771

3.602

5.885

6954

d789

12.260

9931

4519

2444

1444

21444

6789

5.259

L849

1669

L2i8

32477

2.226

3.213

0.000

1963

aces

1024

aceao0000

2840

3.374

1065

1.065

1065

3.065

1065

2.706

4203

5.564

6.474

12115

1L420

S .25

9.290

2760

2760

Z760

7.054

7.668

5.389

194

L710

1269

2538

2281

3.292

I 168

1958

L.452

2905

2.610

3.768

5.226

L837

L659

L231

2.461

2212

3193

3.876

am

3.571

am

1405

0000

1836

3.225

1642

L642

1.642

L642

3.137

1566

6815

3.484

7018

14771

5.807

10730

1547

2547

d510

7.076

7.316

2.572

2.322

1723

3.446

1096

4.469

anao

4007

000

13577

0000

1627

408B

&944

.944

Q944

0.944

0.944

4.49

5.863

7.817

7580

11871

13.170

7.60

14%9

1498

6383

6.93

5.928

1396

2792

2509

3.621

.793

4.258

0.777

1133

1793

am0.777

1611

13.434

2438

1126

2438

2.438

1.620

2978

4.155

6.617

5. 67

4879

14280

1L931

7.273

605

9.781

2529

2529

2.29

6464

7026

2415

2.4152415

4171

4708

Q 182

4.809

0 142

3.068

0.142

0.142

4165

3439

3.439

3.4391439

3.439

L1246

3.945

4421

7.596

5.910

6671

7.40

11940

7.931

6757

STUART

ftYDRATECH

1.051

4160

1618

3.938

1618

1618

4.218

4,228

4.103

187

4.103

2728

1120

'334

4.524

5.660

14257

.274

7.668

amooo

3.167

4000amo

am

4238

13420

2401

2.401

2401

2401

21406

4184

6708

5.534

7217

14542

12025

7.162

6043

11547

2.665

2665

2.665

4811

1.403

4572

3.921

1906

1084.148

3.916

3371

1.882

0.000

L886aLmU

&000

182.

3411

4760

533

16149

13569

6960

&472

2237

12372237

.217

5.718

2

4

6

7

8

9

10

11

12

13

Is

16

22

23

24

25

27

28

29

30

2

3

6

4A

1A

1

TABLE E-2: Public Water Supply Utility Pumpage Data (Continued)

UrILTYNAME

IEOUESTA

P.ATI A WHrrNEy

1B PK OF COMM

28

7Rit

19

20

23

2

3

4

7

8

1

1989 PUMPAGE IN MILLION GALLONS PER MONTHor

MAP

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

JAN

.487

0

&799

4.323

5.306

6066

11.321

755

&862

25.082

113.164

1.377

&185

14298

9442

.465

112405

13328

20.887

1&683

21.918

24817

21309

13.999

23095

9.832

16839

0

4328

03

1.571

3d92

1L259

11.2591L259

5.78

1.217

L217

x166

15.842

0

0299

0

L471

38085

1.a11

10811

5.552

1169

L169

Q459

FEB

5.415

0

6587

308

2.662

10855

&IS4&.154

11624

10669

22172

12.062

0

12841

12509

9.775

816

11556

14534

M474

17.364

20607

19093

11424

2L.623

MAl

0.833

0

1.8

6009

4.21

6548

2836

2698

2,968

1&927

17.152

0

10.392

125

9.808

x693

11.837

15.762

221199

14945

22308

25.292

20628

13674

22066

1x457

1599

0

4030.03

1.027

33.92

12.018

12010

&171

1.299

1.299

A592

9.712

8376

L163

x209

L246

32.617

12.520

12.520

6429

1.354

1354

APR

1375

0

1.831

1.65

.933

768

7.49

2.6%

24.24

1616

0

12.721

10.434

1109

.184

12.56

12.339

21.324

15.744

22.164

24.221

1&683

12087

21582

3.628

15.38

0.326

.1

34946

12994

11994

673

1.405L-40

MAA

0.732

0

1.947

8.38

8.105

7.721

11.486

11.SIS

11045

24.437

17.415

4143

13.389

12.95

7.969

2-831

12779

15.05

21175

1&.741

2L912

25.823

19.753

2.429

24.29

16971

24856

1.46

04559

2.036

19.814

12.562

12562

&451

1.358

1.35892

1792

JUN

1.319

0

L696

6371

.463

5.243

9251

9669

9.65

23.402

14383

9956

13.274

11.309

11.515

2.526

13585

15.415

21462

17.797

2L994

25012

19169

10.386

23.962

677

24481

2.762

1538

2.668

0

11.078

11070

5.685

1197

1197

1297

JUL

0.552

0

0.734

4.088

3.13

259

7.697

6153

5.959

21L787

11I71

&935

12855

11499

11.739

0.944

14.264

16.576

18

15.267

21.094

23.824

19.573

11464

24406

13.1241

3936

4.212

.795LTP5

3.539

17.939

11.222

1 L222

S.763

1.213

L213

AUG

1307

0

L661

4.7

L612

4912

5.158

4321

&076

23.957

14.029

9.692

12948

11409

11 914

a445

14403

16015

0.371

16.6 8

21.909

24.13

16991

11.241

22.105

1269

3.80

1791

1892

1716

2@.22:5

10869

5.581

1.175

1175

SEP

L075

0

1.703

5 007

7.518

6942

9.626

8547

8818

17.663

17.651

9933

12636

928B

1L446

0307

14206

14483

0

1.318

22,11

22.599

17.657

1L013

20163

5.51

9.203

4851

0

5.062

15.404

1x408

3345

L125

1.16$1656

OCT

0.881

0

1.111

5.406

.494

5.266

8248

9.041

.435

20.x591

14.39

9814

11.598

&8501

11703

0.861

13381

15.957

0

16714

21493

20.615

17.357

11.699

22.853

NOV

3.563

0

3.054

4.227

4484

514

12293

10.4891xo9911.056

2d.336

15.719

9084

11.762

7.733

11119

1612

13.89

15.291

x098

16-W

2203

2143

1&827

1115

21872

13.854

4.002

3.453

0.002&002

4188

17156

14356

1&356

5.318

1.120

1120

1.076

DEC

0.504

0

Q55409544

11,079

12.617

932

13.177

12.615

10.908

17.268

14.876

5,456

10057

&612

9.672

x668

9.057

10.731

6852

146504

21.83

22.109

16.216

12.137

19.301

6375

13.964

3.3

189

0083

3.178

11612

11275Iam

134275

5.276

1.111

111

12073

7.631

2130

0514

2576

22388

11364ILS

11364

5.835',33

1.229

L229

AVG

2.8710B70000

2623

5.361

5.295

5.932

8.911

&393

1262

21655

14.848

5.699

14.888

10.716

11516

x946

11807

14.790

12.754

14773

2L2

23.542

1&688

12142

22.443

TABLE E-2: Public Water Supply Utility Pumpage Data (Continued)

WELLTEL L989 PUMPAGE IN MILLION GALLONS PER MONTHUTILITYNAME or

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC AVG

2 0.454 0626 4247 0.407 0 0 0 0 0 0 0 0 4145

Non-Community Systems (Small Utilities) * = Utility outside of model boundary

S S Rentals (Sierra Sq) 10 0 0 0 &004 4017 4015 0021 0.019 40007 0.06 023 4902 0012

Sunshine Tree School 11 41016 04017 4039 1042 0.055 .402 04022 Q028 4028 0.03 4027 0.022 4029

Tri-Gas 12 4007 00 41007 006 401 4006 0,007 0.006 006 1009 4007 1006 4007

Valmaro Country Store 13 0.027 027 4021 0.042 1047 40053 40042 as029 025 40041 0.024 0.1 0.034

Wet Jupiter Campground 14 &0279 4367 4272 40309 .293 40.267 0.241 0.187 4317 0.319 0.367 04487 0.309

Ackhe MHP 15 4807 1 02 0.945 0.693 753 4585 04628 525 40624 4654 40746 40757 4732

AirpO Bus Park 16 (061 4052 4158 40136 0.107 0.169 4288 40103 40009 1078 40.113 04076 40119

An(le [o MHP 17 1022 04744 0.428 0.879 1.985 1.748 L926 2366 1903 1.59 1306 L445

Amon's Plaza 18 40026 0.031 0.024 4027

Armeini Truck 19 405 4115 04097 04006 4038 0.6 04106 4065 0.097 .079

Blue Heron MHP 1 20 41136 4126 4121 4099 400 0.058 001 0.072 4068 405 40.86 0.109 4091

Camp Welaka 21 0191 0.41215 177 01668 0199 0.189 0295 4173 4173 40154 4184 0.097 4185

Canoe Cr ee 22 1861 2178 2213 2.398 .964 3.038 2945 239 2274 205 2538 2441

Caa Roma Rmt. 23 4017 4017 0018 0.011 001 01 0.002 4014 4013 4012 013 41012

Caulkim lndianran 24 41131 04329 4227 2 0 432 4294 04028 0048 4089 0.07 4207 40555 04211

Cide K-Kanner 25 0.004 4004 4003 .008 0.009 4007 0.002 4.003 1.005

Cal Garden sip. Crr. 26 40027 0.023 a003 0.028 n028 0023 02 0.03 4026 ao049 0037 412 400 0

Country Place Rest. 27 4005 4004 4oo 4005 &003 400 4007 &oo8 0o 4009 10.00 oe 1006

Crmood Condo 28 0416 Q12 0.114 4135 0159 0.0 4068 4086 0.106 4147 40186 0.124

De Ja Vu 29 40016 O O9 4011 4014 .012 015 400 4008 41006 401 4006 0.011 0011

Estuary @ N.River Shore * 30 1.872 2024 2246 2649 3.007 357 3.574 3.417 2.811 2.959 3059 2907 2824

Euegreen Club 31 4066 4053 405 4062 1062 408 005 41037 0&5 4045 4047 4091 4052

Fairmont Etates 32 0.301 .28 314 0271 0.263 4233 4235 40247 0.26 0279 0.326 037 4282

Farm sm 33 &007 1 400 ar7 4007 0.006 4o006 r007 n007 06 a006 00s 4005 0006

First AMcby of God 34 0.012 4019 41014 4014 4.02 1012 40012 4017 4 027 .416 0.027 4.055 021

Firt Nal Bank/Trust 35 07 aI 4031 0.026 . 02 4 s005 .007 40012 0014 0.018 4013 4012 0.016

Fberman's He' 36 1.352 .327 1.319 1375 L627 L4I 1522 1.415 1.315 L249 L294 1109 1365

Florid Fhbeis 37 10 03 4024 402 0.017 4017 4018 4014 40014 04014 012 0.001 0014 0.016

PP&L (In Uri Ue] 38 12972 13.30 14.317 12603 1L971 20154 21$14 15.128 1324 22.058 23088 24845 17.107

FaxRun 39 1.076 172 L163 L279 L428 1.374 .123 1.04 1004 L.5 1123 1166 L175

Fraernal Order of es Et 40 411 OM 007 05 o1011 0ae6 4 00 .007 .oe &o007

Garden Vill.. 41 445 4413 1487 4 471 667 0&639 41489 1458 441 0518 &631 096 0.505

Greetree MHP 42 41165 024 403 0.262 0.211 173 4156 413 G15 0.229 0.279 0308 0.209

Heritae Square 43 4097 a099 128 4134 4062 045 0.052 4062 40066 402 0.46 4.045 4

Hidden Harbor MHP 44 1.31 1322 1369 1311 1.342 1256 219 1.226 1.115 1.231 L316 L452 L289

Hoe Smmd Bible Cdole 45 2274 L69 1886 L524 2148 1708 1308 L46 1944 1424 1.715 L481 1753

TABLE E-2: Public Water Supply Utility Pumpage Data (Continued)

UTILITYNAME

HOBE SOUND

MILES GRANT

MARTIN CO,VISTA SALERNO

sT. LUCIE FALLS

MARTIN DOWNS

PIPERS 1ANDING

DEF3IF OP CORRECT.

FISHERMAN'S COVE

UPIlER

WEL

orMAP

2A

SC

3

5

6

7

8

9

10

11

12

13

1

2

3

4

6

2

4

3

6

S

1A

7B

2

2

4

1

2

3

4

1

2

2

1989 PUMPAGE IN MILLTON GALLONS PER MONTH

JAN

3%96

1.612

&BIB

6818

6818

6.818

6818

6818

6818

6818

0

024

0013

1.257L257

1933

6986

7.202

9.290

7.058

S.437

5.338

L87

1.877

1671

7.671

1.939

1939

1.939

2300

2300

1652

.638

FEB

6215

L250

7.239

7.239

7.239

7.239

7.239

7.239

7.239

7.239

7.239

7.239

0068

0.063

0

L744

1.318

2.134

6184

6375

8&224

6248

4.813

6300

6300

1.817

.1508

7.5oB

3,783

L739

L739

1739

.231

1.231

0331

435

MA

6.708

1.497

5.307

5.307

5.307

5.307

5.307

5.307

5.307

5.307

5307

5.307

8161

035

0

2.545

1.557

L442

7.061

7.279

9390

7.133

5.496

6020

6020

L869

1869

&434

&434

3.6

L813

1.813

1.813

1462

2462

2414

1379

APR

6.847

1.360

5.166

5.166

5.166

5.166

5.166

5.166

5.166

5.166

5.166

5.166

0.761

0.318

0

1.322

1.373

L406

6790

700

9030

6860

5.285

6022

60822

7.964

7.964

1.719

L.719

1719

1719

2342

,342

272

2.895 |

MA

7778

0.789

8240

&240

12*

&240

8240

&240

8240

8.240

&240

8240

0.278

0.164

1.216

1877

0947

7.117

7.338

9466

7.191

6593

6593

2070

2070

&028

&028

1233

1.901

1.901

1.83L409

4.OF

JUN

7548

1912

8310

&310

&310

8310

8310

&310

8310

&310

.310

8310

0

0

2832

0618

0517

1559

7.039

7.256

9360

7.111

5.478

6458

6458

2056

2.056

7.672

7.672

3.199

1913

L913

L913

L913

2439

±439

2.27

JUL

6945

1.209

5.153

5.153

5.153

5.15

5.153

5.153

5.153

5.153

5.153

5.153

0369

aOBc

"1159

1.544

4529

8724

6572

6775

1740

6640

5.115

6308

6308

L1811

1.811

7039

7.089

2699

LOS1.860

L860

2249

1249

0923

AUG

6789

2.532

&731

&731

.731

1731

&731

&731

&731

&731

&731

&731

a395

1334

636

029

1.09

1.443

6578

6781

&748

6646

5.120

3521

5.J22

L254

L254

6857

6857

.349

2006

2.006

L006

2006

2223

L983

2079

SEP

7.668

1.683

10.646

10.646

10646

11646

10646

21646

11646I0646

14646

0317

£324

1.072

1274

1848

2058

4426

6625

8546

6492

5.002

6756

6756

L223

7.143

7.143

2512

1.958

L958

1958

1.958

2153

2.153

L941

2027

OCT

1076

2.630

7.170

7.170

7.170

7.170

7.170

7.170

7.170

7170

7.170

7,170

1.315

0.966

1.865

&725

0.952

7.033

7250

9353

7.106

5.474

4052

1.372

1372

7.923

7.924

3.136

1223

2223

2223

1223

2.250

B25083

±803

NOV

7.403

2.421

7.433

7.433

7.433

7.433

7433

7433

7.433

7.433

7.433

7.433

0.836

0.486

4662

1.021

8211

1.811

7.100

7247

9.349

7.102

5.471

6424

6424

L614

.614

&549

8549

3.236

2577

2.577

1577

2577

2.233

2.233

3.578

6935

DEC

6938

1389

6565

6565

6565

6565

6565

6565

6565

655

665

656515063

(.53

1.392

1836

0

0

7.034

7251

9.354

7106

5.475

6401

,401

1546

&786

&786

3.65

2487

2487

2487

2487

1267

1737

0895

AVG

7.026

1774

7.231

7.231

7.231

7.231

7.231

7.231

7.231

7.231

7.231

7231

1464

0744

1.522

0942

1.286

6.821

7.312

9.071

6891

5.309

6183

6183

1.707

7.02

3.233

10112011

1011

1304

1304

1.803

2358

19119 PUMPAGE IN MILLION GALLONS PER MONTH

1

TABLE E-2: Public Water Supply Utility Pumpage Data (Continued)

WELLL 1989 PUMPAGE IN MILLION GALLONS PER MONTH

UTILITYNAME

MAP JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC AVG

Hobe Sound MHP 46 1.343 L266 1.228 L516 2353 2072 1.55 1.757 2.095 1.525 1.636 L243 1.632

Hobe Village MHP 47 2206 1.979 2.306 3.259 3.557 3.499 2986 2.431 2.967 2611 2.702 2.256 2732

Indiawood GolflCC 48 0.042 0.038 0.39 0041 0.34 0.073 0.037 0.039 0049 0.05 0024 017 0.041

Inerstate Ind. Part 49 0.068 0.07 0.134 0.077 009 0.076 0106 0.099 0.122 0134 0.09 0.109 0.09

7 & S Fih Camp 50 0026 0.039 0.019 (0.14 0.024 0.019 0M9 0.0 4009 Q01 0.0 0.008 0,016

Jemn Vlape Plaza * 51 0.127 0177 0.2 0.194 0.282 0.242 0281 0269 0.355 0.227 0311 0.242

JDSP-Pine Grove 52 0.275 0273 0233 0193 0.282 208 0.158 .152 0168 0.75 0147 .143 0.201

JDSP-River Ara 53 232 195 0228 0277 0.293 0.274 236 0.196 0234 4162 0181 199 .226

3/iTChtab ofChrdt 54 0 0 0.28 0201 0364 00345 0176 0177 0.255 4113 0.123 0103 &170

Lakeside Village MHP 56 L569 L032 0.825 1389 L348 0.79 0.4 0578 L12 0.71 0.703 0.619 0935

La Ruch Res. 57 0.34 0.049 0.34 0.038 0.027 0.019 0.016 0.021 0 0.021 0.33 .028 0.027

Lii Saint-Golden Gate 58 005 0038 0.037 0.042 0.54 0.053 0.054 0061 10044 0O51 0.015 0046

Martin Ca Mit Scurity 59 0432 0.391 0.609 0.458 0341 L05 2419 0538 0428 0554 0.58 0.8se 0.716

Meyer Mobile Est. 60 0.425 4413 0442 0357 0.391 0.515 0382 0348 0.479 0.563 0.444 0.496 0438

Midnight Farms Ster 61 40029 0.028 0058 0044 0.45 00.4 0.037 t039 0.037 0.052 0.031 0028 .4

Mai n Marine 62 0013 0.016 0.021 0.022 0.03 0032 0.024 0.036 0. 1 0.024 0.r

Monterer Motel 63 028 0.022 4025 0015 (O1 £013 0.016 0017 0.017 0.02 0017 0.018 0.019

Natalie Estates MHP 64 12186 L236 LOll 0.68 0953 881 &736 0658 06452 0.841 9 0as819 .895

New irfe Ci of Criyt 65 0.009 0.06 0015 011 0ao00 am 4007 .O 0.009 0.009

Nichos Saniraton, 66 0.047 0.0 0609 &.073 0.024 a022 a063 00

Old TailClubbos 67 0124 0125 40128 01 0099 0097 0.141 0.09 .093 0144 028 0.165 0.126

Od Trail- Maint. Bldg 68 0.199 0.055 039 0a9 0.04 0054 0.065 06 40.059 0068 .1 0.1 0.070

Old Trail-Ssle Tr. 69 0.003 o0.01 0.003 015 a 0. 003 0 a am 0.003 003 0.0 0.003 0004

Open Gate Traier Park 70 0035 0042 0.043 4.034 4033 0.038 1033 0.07 003 &0.6 032 04 0.036

Palm Cirde MHP " 71 0.38 0422 0.312 256 0.214 202 0.199 4199 223 0256 0.343 &0271

Pal City Ek 72 0.193 0.145 0118 0.246 4169 .058 0.33 0073 40193 0.127 40279 0.122 0155

Pam City Pt. 73 0.046 o0045 049 00SS 053 0.047 0.05 007 00on s0.062 054 042 0.054

Pasr Motel 74 5al5 0221 0233 0192 0.24 10,185 8 QM 211 (252 0.191 0an 019 4205

Pine Gruve Comm. Cr 75 0.052 04 0.043 034 031 4022 0.t6 01103 02 0.043 0.037 046 0.037

Pnelake Garden 76 2.713 2695 2806 1035 168 385 1867 239 2527 2709 2566 2195 2.814

Pi MHP 77 02 04212 0.178 0202 0231 0.127 4018 .2 019 40102 013 0&148 0.178

Pet Sem Groc. 78 0.021 002 024 0.028 023

Rio Colmer Cr * 79 0.031 GO18 0021 0.02 0.011 0.01 0.009 0022 1016 Q014 1017

RioTrar Part * 80 0146 010A5 1155 0132 a0l6 0072 0061 a0.08 09 0.12 0135 0.163 123

Ri C * 81 0.823 868 (1964 828 072. 0596 0604 0.461 0.48 091 1744 1841 1710

er Landing 82 0.841 03851 L042 1199 L79 1.597 348 1.077 0943 L206 L237 1.381 1.09

Riverb MHP 83 0.992 .019 0945 0851 ass85 076 054 0.52 4416 .587 073 0767 0.750

Roa Ouarens/ookerPk 84 0119 0074 0148 0.101 0.132 0.122 0149 0112 0.145 0.06 0.94 117

TABLE E-2: Public Water Supply Utility Pumpage Data (Continued)

1989 PUMPAGE IN MILLION GALLONS PER MONTHUTILITY

NAME or

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC AVG

Ronoy's Mobil Ranch 85 0.391 0.331 0.286 0.237 0.237 0.26 0.185 0.156 0.167 0.195 0252 0.26 .246

Salerno Tr. Pk (Old) 86 0.10B 0158 0.073 0.045 025 0.017 .013 8031 0.021 0.05 0.03 0.046 &049

Salerno Tr. Pk (New) 87 0.288 0.31 0.321 0.2 0.121 0.1 0.122 0.091 0.072 .094 0141 156 0.166

Sandy's MHP 88 0.049 0 58 0.057 0,052 0.159 0.243 0.226 0.177 0.128

Souyt-St~ art 89 0.031 0.028 40041 0.039 0.o26 40019 0.024 .033 0.9 0.018 0.011 0.022 0.029

Sea Breeze Mobile Man. 90 1806 1372 L207 L743 2674 2.549 L734 L477 L902 L486 L466 L024 1.720

Sabridge Builders 91 0.009 0014 0.014 0.022 .018 0.069 0.065 0.03 0.057 0.018 00B a061 0.037

Soundings YACC 92 3.863 1757 3.827 3623 4.626 (595 3.886 4165 4336 4.047 4.185 3.543 4.038

South End impov. 93 2972 2211 LS92 2416 1169 3.362 L915 2707 2714 1206 2623 .491 2.448

South Fork Howem esmn 94 0902 0.761 0.963 0.948 0.855 0.813 0.605 4649 0.641 0.775 .867 0452 0.80

South Fork HS 95 0.922 0.735 1154 0.674 4766 0.076 a97 L08 2.146 L49 L345 0.448 01965

South River Condo 96 2648 2601 2713 2426 214 1098 2171 2209 L905 2206 2.418 2464 2333

SLt Lame Mob ViL 97 2621 2358 268 2425 2873 L816 2964 2921 2.629 2587

St. Luie Settlement 9 0.38 0.358 0279 0.297 0.276 0.267 0.288 0326 0.243 0.234 Q307 4309 0297

SIP camp (3DSP) 99 4037 0036 .043 a5 04121 0.15 0141 096 096 0.07or 0.05 0.01a

Stuart Avition Ca. 100 0.06 0.015 0.03 0.116 0.096 0.034 0.013 0.019 0.02 0017 0.016 016 0038

Tannish Kets Camp 101 0013 001 0.001 0 0 0 0.047 031 0.018 011 03 0.019 0.013

Ted IRit Tank&Tummy 102 48 0.057 05a2 043 050

Tmering Pines MHP 104 0.131 R0.09 0118 .128 0096 0.10 009 0.069 4063 4075 0.096 4097 096

Treasure Cove 106 2.92 2816 281 288 4363 1731 29.2 1083 3787 3.234 3.684 2575 3.237

Tropical Aes MHP * 107 2384 1011 2579 2749 1784 3523 3.112 2.929 1046 228 2.281 L783 2.788

Tiin Riven MHP 108 0.121 0.118 0.12 ar7 044 0.044 0.035 0. 4002 a0.6 077 0097 0.073

Tylander Systems 109 0a004 ao007 004 0.017 0.004 a004 a

Vasuon Park 110 0.355 m0.3 064 0.408 344 0344 02 a.2 0.313 246 0313

Vi'a Del Lapg * ll 168 3355 2.56 2001 2099 2263 2195 2.125 244 2293 2501

Willoughby Creek To bouses 112 0.078 4067 0.079 0.060 .07 071 ao3 0.073 0.073 086 o09 0.076

Willughby Golf 113 0 0 0 0 0 0.015 a082 0022 165 0.131 0.2 0121 .09

Woodbridge Mobile Vill 114 .764 0.582 0.68 0715 1019 0.835 x713 4731 0.8 0.617 67 40576 0.734

Waoodide Subdiv. 115 0631 1653 613 465 &037

Yankee Trader 116 .144 0.123 0.10 0.113 0.122 131 0.132 0.126 all 0.18 092 0.72 .116

Comparison of Actual Reported Pumpages to Permitted Pumpagesin Public Water Supply Wellfields

Individual Water Use PermitsPermit # Permittee

430004143000534300066430007643000864300089430016443001694300173430027743003425000010500004650005015001528

INDIANTOWNSTUARTHYDRATECHHOBE SOUNDMILES GRANTMARTIN CO. V.SALERNOST. LUCIE FALLSMARTIN DOWNSPIPER'S LANDINGDEPT. OF CORRECT.FISHERMAN'S COVEJUPITERTEQUESTAPRATT & WHITNEYPB PK OF COMM

General Water Use Permits

85-5 AckeLs MHP87-174 Angle Inn MHP79-189 Canoe Creek85-45 Evergreen Club85-15 First Nat'l Bank/Trust83-55 Indianwood Golf/CC84-98 J & S Fish Camp87-81 J/T Church of Christ

82-407 Martin Co. Min. Security88-255 Monterey Marine

B8-5 New Life Ch of Christ87-243 Nichols Sanitation86-168 OLd Trail-Golf Maint. Bldg84-216 Palm City Elem.80-142 Pinelake Gardens

43-00497 Pines MHP88-339 Port Salerno Groc.85-109 Rio Coemmerc. Ctr *83-110 River Landing79-211 Soundings Y&CC84-111 South End improv.79-194 South Fork HS80-157 South River Condo88-396 St. Lucie Mob VilL.86-214 STOP Camp (JDSP)87-272 Stuart Aviation Ctr.

43-00498 Tannah Keeta Camp87-401 Ted Twist Tank&Tummy80-56 Tropical Acres MHP *

87-340 Tylander Systems88-311 Willoughby Golf81-107 Woodside Subdiv.88-205 Yankee Trader *87-450 S & s Rentals (Sierra Sq)82-392 Sunshine Tree School83-052 Tri-Gas82-398 Valmaron Country Store

Actual Permitted(mgm) (mgm)

242.531 3551257.504 1410358.520 752867.761 107062.769 72.63

569.857 54840.975 92187.242 61438.796 36.596.536 13455.300 60

3507.811 4927.5570.158 941.7372.241 105.578.664 147.28

Actual Permitted PermittedAvg Day Avg Day Max Day(mgd) (mgd) (mgd)

0.0241 0.0210 0.03100.0782 0.0200 0.05000.0801 0.0600 0.10000.0017 0.0005 0.10000.0005 0.0002 0.10000.0013 0.0009 0.01000.0005 ? 0.10000.0067 0.0014 0.00210.0235 0.0350 0.10000.0008 0.0020 0.00400.0003 0.0014 0.00140.0016 0.0015 0.00200.0023 0.0179 0.02930.0051 0.0114 0.01330.0925 0.0900 0.10000.0059 0.0070 0.01400.0008 0.0010 0.00200.0006 0.0008 0.00200.0398 0.0400 0.10000.1327 0.0500 0.10000.0805 0.0320 0.08000.0324 0.0700 0.10000.0767 0.0819 0.10000.0853 0.0820 0.09800.0027 0.0030 0.00600.0012 0.0009 0.00140.0004 0.0160 0.05000.0016 0.0008 0.00100.0917 0.0250 0.10000.0002 0.0003 0.00030.0016 0.0072 0.00140.0212 0.0150 0.10000.0038 0.0035 0.00500.0004 0.0009 0.00120.0009 0.0010 0.00100.0002 0.0008 0.00150.0011 0.0100 ?

Note: The General Permits listed are not a complete list of all small public supplies in the model, but onlythose that actually have SFWMD permits.

* Water Use Permits outside of model area (Jensen Beach Peninsula)** Units are in million gal ons

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TABLE E-4-B: Non-Potable Well Locations and Pumpages Used in Model(General Water Use Permits)

sati PLal Conu p1 p Papalte ia Millia Gallka per MotIalraa Ly Rw C.I

Ea North Jly am .h Ma Apr May Jm J1l Ag S-ep O Nt Dc4

79-54 755237 1940025 2 3 82 30 0.217 0230 0.376 0.228 0317 0.306 0.347 0,231 4272 0.296 0.270 0194

79-121 743250 1012120 2 17 76 90 0348 0368 0601 0.365 0507 0.490 0555 0.369 0436 0.474 0.432 0310

79-194 743269 997350 2 24 76 200 0.378 0401 0697 0.431 0590 0.543 0.628 0.422 0440 0.436 M505 0353

743269 997350 2 24 76 200 0378 0407 0697 0.431 090 0.543 0.628 0422 0440 0.436 0.5. 0.353

81-222 760069 1015915 2 15 85 30 0.028 031 0.052 0.32 044 0041 0.047 032 &033 033 0.038 026

760869 1015915 2 15 85 60 0057 0061 105 0s06 008 9 0.81 4094 4063 0066 .065 0.076 0053

760869 1015915 2 15 85 40 40.0 0.041 4070 4043 0.09 054 4063 0.042 044 0.044 0.051 4005

760869 1015915 2 15 85 30 028 0.031 0052 0.2 0.044 0041 4047 0.032 0.033 0.03 0.038 0.0,6

82-407 668168 1039164 2 3 39 25 0.076 081 0.139 0086 4118 &109 0126 0.084 088 0.87 8101 4071

83-118 697149 1031680 2 7 53 20 0061 0065 0.112 0.069 094 0.087 0101 0.067 0070 070 0.001 0056

83-122 756355 1017148 2 14 83 267 L423 1.532 2621 L620 2219 2042 2362 1.586 L654 L640 1899 1.327

84-153 771115 1014247 2 16 90 80 0.495 4524 856 &0520 4722 0.698 0790 0526 0.621 0675 0615 0.442

85-51 728342 1030450 2 8 69 20 0115 0124 0.212 0131 4180 0.166 0192 0129 0.134 0133 0.154 0.108

728342 1030450 2 8 49 400 2307 2483 4.249 2627 3.598 3.311 3.830 2572 2682 2.60 3.079 152

85-76 781439 994273 2 26 95 25 00 800oo8 0014 4009 0012 0.011 4013 0008 0 09 009 0.010 0007

85-107 781902 990126 2 28 95 200 606 0.644 La52 0639 887 0.857 4971 646 0.763 829 0.755 0342

85-192 726682 1032744 2 7 68 60 0.272 0.293 502 0.310 0425 0391 0.452 0304 0317 0.314 0364 254

85.207 728914 1031584 2 7 69 60 0.149 160 0.274 0169 4232 0.214 .247 4166 0.173 0172 0.199 0.139

85-361 761165 1024763 2 11 85 100 4067 0092 .150 0091 4127 0.122 40139 0092 0.109 0.118 0.106 0.077

86-3 736044 1035422 2 5 73 120 0.227 0.244 4418 0259 0354 0.326 377 0.253 0.264 4262 0.303 0212

86-20 749937 985$37 2 30 79 200 5.000 1000 4.000 4327 5.000 7.000 7.00 2000 2.000

86-137 723650 1034500 2 6 66 130 0.28 0.310 0530 .237 0.449 0413 0477 321 0.334 0.332 0384 0268

86148 748140 1033303 2 6 79 40 0.226 4239 0391 4091 0329 8318 0.361 240 4283 .308 0.281 4201

86-149 748395 1033248 2 6 79 40 0.087 0.092 150 0137 0.127 4122 4139 0.092 0109 0.118 0108 0077

86 171 748223 1032772 2 7 79 146 0.130 4138 0.225 0956 419 0.184 0.20 0.138 4163 0.178 0.162 0.116

86.182 731035 1031711 2 7 70 10 0.840 0904 1.547 8274 1310 L06 1.395 0936 4977 0.969 L121 0784

86-266 748768 1032894 2 7 79 90 0.261 0276 0.451 4593 0380 0367 0.416 0.277 4327 0.355 0.324 232

87.92 750746 1029171 2 8 80 150 0.565 0598 977 4301 0.24 4795 0.901 0600 0708 70 0701 504

87-110 779661 1000225 1 23 94 30 0.287 303 0496 0043 4418 0404 0458 4305 360 0391 0356 0256

87.160 721195 1024450 2 11 65 20 4038 0.041 0.070 171 0.059 4054 63 00 04042 044 044 40051 a1035

87.392 762948 1015189 2 15 86 85 0.151 0163 4279 0172 0.236 4217 .251 416 01176 0175 022 8141

762948 1015189 2 15 86 85 .151 163 0.279 8012 0236 8217 0251 a169 0.176 0175 202 4141

87-436 751465 1029891 2 8 80 80 0.07B 483 0135 0023 0114 4110 0125 0.03 00M 01097 4097 0t.70

88-27 746257 1027181 2 9 78 12 4022 9023 008 1023 0.032 . 1 0035 0.023 0,7 030 027 40019

746257 1027181 2 9 78 12 40022 4023 0.038 1.896 632 01 005 0 23 4027 0030 0.027 4019

88-89 732484 1032026 2 7 71 200 2.65 L6792 1067 1137 1597 2390 2.764 L856 1936 L90 2.222 1553

TABLE E-4-B: Non-Potable Well Locations and Pumpa es Used in Model(General Water Use Permits) (Continued)

Stare nlam CV Ca rPapa3 in M11. GallsH pe MpeaPurms Lay R. Cal a-

Eas f Nori Jas F.r Mar Apr May J>a Jal A* Sap Oel Nav D.e

88-96 727339 1033266 2 6 68 200 0.999 1.07$ 1.840 1.558 1.4341 L658 1.114 1.161 1.152 1.333 0.932

88-153 722198 1018034 2 14 66 40 0.173 0.186 0.319 0.197 0.270 0248 0.287 0.193 0.201 0.199 0.231 I1161

72219 1018034 2 14 66 10 0.043 0.047 0.080 0.049 0.067 4062 .072 0.048 0.050 0050 0.058 0.040

722198 1018034 2 14 66 10 01043 0.047 080 0049 0.067 0.062 0.072 0.048 0050 0.050 4008 040

722196 1018034 2 14 66 10 0043 0.047 0.080 049 0.067 0062 0.072 0.048 0050 0.050 0.058 0.040

88-182 778394 990993 2 24 94 25 (0017 0.018 .030 018 0.025 1024 0.028 0.018 4022 4024 0,022 0016

88357 743772 1019869 2 13 76 12 0.151 0.163 0.279 0.172 0.236 0.217 0.251 0.169 0.176 0.175 0202 0141

43-00493 753066 1041018 2 2 81 160 0.000 4000 .I000 0073 0101 0.098 0.111 0,074 4097 0.095 Q 086 40062

43-0512 751991 1041298 2 2 81 140 R,(0 1000 0000 4000 0000 &000 01042 0.028 1 033 0.36 032 0.023

79.106 780988 992076 2 27 95 25 0.062 1t100 0.148 0.096 0.117 0.126 4141 0.089 0.111 0.074 4092 04086

85-186 788550 959700 2 43 99 45 0.371 0.597 0,886 0574 0.699 0.754 0.847 0.532 01667 0441 0554 0.517

86-331 795151 967233 1 39 102 20 0087 0.139 0.207 0.134 0.163 0.176 0198 0.124 0.16 0a103 0.129 (1121

87-82 794422 969117 2 38 102 50 0.056 0.09 0 133 0.086 0.105 0.113 0.127 0.080 0.100 0066 4063 0078

43-00528 78808 961483 1 42 99 20 0.031 0.050 0074 0.048 (0.08 0.063 0.071 0.044 .056 .037 0.046 (0043

788002 961483 1 42 99 20 0031 4050 0.07r4 0.048 0058 0.063 .071 0.044 4056 .037 0.046 0.043

82-3 763019 930958 2 54 86 15 0.099 0.018 4027 0.018 0.022 0023 0026 ( 016 0.018 0.007 0.017 0016

763019 938958 2 54 86 60 0036 0.071 0.109 0.073 0.06 091 (4104 0.064 0.072 r0.02 (1067 0063

84-123 791569 941889 2 52 100 40 0.063 1125 0.190 128 151 0.159 0.181 0.113 0.125 0.049 4117 01109

791569 941889 2 2 100 40 0.063 0.125 0190 0.128 0.151 0.159 0181 0.113 0.125 0049 117 0109

84-212 06933 928293 1 $9 59 108 25 0. 4 0.067 0.102 4068 0.081 085 097 .060 0.067 0.026 10.62 409

806933 928293 1 59 106 25 0.034 007 0102 01068 0.081 0085 0097 4060 0.067 1a026 0.062 0059

84-224 726123 934573 2 56 68 200 0.059 0116 0177 (119 0.140 (147 0169 4104 .116 046I 0.108 0.102

85-48 806358 932778 2 57 108 50 0310 0.498 0.739 0.478 0 3 0628 0.706 0.444 4036 (367 0462 0431

85-301 799236 946180 2 S0 104 45 0.014 4027 0.01 07 0.032 .I034 0.09 0.024 0.027 0011 4025 0.023

85-352 783178 944935 2 51 96 150 .665 1309 1996 1.341 1.581 1.66 L05 11 1 315 0516 1224 1L150

85-353 783185 944010 2 51 96 150 0.815 L603 2444 1,642 1936M 2.040 2.333 L447 1.610 0.632 1499 L40

85-376 778542 942314 2 52 94 75 0.102 01200 I305 0.2¢ 0.242 a2 0.292 0.181 0.201 (.079 r1187 0176

777748 942342 2 52 93 75 0.102 0.200 0.305 0.205 0.242 0.255 4292 0.181 0.201 (1079 0.187 (0176

86-23 805866 932125 2 57 107 60 .038 0.074 0113 0076 0.090 0.84 0.108 0.67 4075 10029 0.069 0.065

805866 932125 2 57 107 60 40.38 0.074 0.113 0.076 4090 (1094 0.108 0067 0.073 (1029 0069 0065

80866 932125 2 57 107 60 0.38 0.074 (113 0,076 090 (1094 (100 0.067 4075 1029 4069 065

86-84 780931 946M 2 50 95 120 06 0.134 (1204 137 0.161 .(170 .194 4121 0.134 1053 0.125 0.117

780931I 946224 2 51o 95 120 0.06 4134 01204 40137 0.161 4170 0194 0121 4.134 053 0125 0117

06-200 784704 94290 2 52 97 90 0.136 40267 0407 4 01274 0323 0340 4389 4241 0.26 0.10 4250 0.235

87-450 767585 946953 2 50 88 65 1005 04009 014 (09 40.11 (011 013 0.08 0.09 (0004 .00B 04000

88261 781180 945874 2 S0 95 80 (1077 (1151 0231 4155 0.13 40193 420 0 0137 0.152 41060 0142 0.133

85441 781342 949225 2 48 95 150 0.407 01 1.222 8 1 0.968 1-020 L167 a723 I48( 0316 0749 40704

5001797 725769 938530 2 54 67 1 005 (009 0.014 009 0.011 011 0.013 006 0409 1004 0.008 G00L

TABLE E-4-B: Non-Potable Well Locations and Pumpages Used in Model(General Water Use Permits) (Continued)

S itate n C4M4 m Fumpa i. Mik Gallas per MeatLrmit lay B .r C I-

tEat N CAPt Ja 7.k Mar ApH May Jua Jul As& Se Ots N. D.c

5001896 78282- 958718 2 44 96 60 0.000 000 0 0.00 0 4525 0.565 0635 0.399 0500 0331 0.415 0388

50.0161 7802]8 943574 2 51 95 55 4o000 0.00 0 0.000 000 000 0.000 0.648 0.402 0447 0.176 0.416 0391

50-02016 784270 943582 2 51 97 45 0. 0.000 0.000 0.000 0000 0.000 0.000 0.000 0179 0.070 0167 0.156

88-133 757854 947268 2 49 83 15 L200 1200 L200 1200 1.200 L200 1.200 L200 1.200 L200 200 1.200

88-134 755577 943696 2 51 82 15 1.200 12 200 1200 1.200 200 20 1200 1.200 1.200 L200 120 L200

79-104 745652 1036225 2 55 72 20 0.060 0.060 0.060 0.6 0.060 0060 0.060 0060 0.060 0.060 06o 060

82-60 719201 502669e 2 to 59 25 0.270 0.270 0.270 0.270 0.270 270 0270 0.270 0.270 270 0270 0.270

82-161" 744859 1013079 2 16 77 4090 0.090 0.090 0090 090 090 409 0.090 0.090 090 0.090 Q090

82-233 748495 101B876 2 14 79 250 0.1( 0150 15 0 150 0150 150 0.150 S0.10 0.10 o150 0150 s150

82-242 726652 1024515 2 11 68 84 007 0.075 0.075 0075 &07 0.075 0.7 $ 0. 075 O07 40.075 0.075 075

87-253 776480 9831310 2 31 93 200 1275 L275 127 1275 1275 1.275 1.275 L75 1275 L275 1275

87-258 642073 1023092 2 11 26 200 1.824 L824 8824 4 1.8 4 124 1.824 1.824 2424 L824 L824 L824 1824

87-361' 658456 1000252 2 23 34 30 0600 &600 0600 0600 a600 0600 4600 0.600 0. 0.&600 0.0 060

87-432 745278 1028694 2 9 77 150 0300 00 0 0.300 0.300 0.300 0.300 0.0 300 0300 0.300 4300

82-354 745184 1023982 2 11 77 200 0.135 0.135 0405 0.45 0.4 0445 0.405 0.405 0405 0.135 0.t35 .135

87-176 711290 103181 2 7 60 400 0600 0.600 0600 0.600 0660 0a600 0.600 0.600 60.0 600

87448' 717178 1027984 2 9 63 30 0075 0.075 0.075 0.075 0.075 0.075 0075

8227" 751270 959680 2 43 90 100 L200 L200 1200 L200 1200 L20 1.200

Black 651000 980400 2 33 30 0.569 0.814 0.209 0.284 0.913 0.529 0.221 0.112 0.010 0062 0432 0473

ck 649200 977900 2 34 29 8L3 2.016 0.784 L715 L722 .294 538 0639 140 0.063 L785 L16232

Black 6492OD 979100 2 33 29 0.792 0.864 0.10 0828 0294 0.060 0.439 0145 0.099 0.297 0.22832"t

Bla 651050 978500 2 34 30 2.086 1.836 1.03 1722 1108 L980 0.456 0.343 0.17 0.428 L773 1817

Unless otherwise noted, all pumpages were calculated using the Blaney-Criddle Formula.

= Nursery Permit: Pumpage calculated by multiplying the "Average Day" Water Use Permit Allocation by 15 days per month.

** = Actual reported pumpage used (Groves)

TABLE E-5:

Permit UseNumber Type Owner

4300013 GLF4300017 AG4300021 AG4300031 GLF4300032 GLF4300064 GLF4300069 RECR4300132 AG4300156 LSC4300198 GLF4300261 LSC4300266 GLF4300335 AG4300368 AG4300382 LSC4300425 LSC4300434 GOL4300441 LAN4300502 LSC4300054 GLF4300091 GLF4300138 GLF4300200 AG4300202 LSC4300273 GLF4300371 GLF4300375 AG5000153 AG5000223 GLF5000237 AG5000344 AG5000547 AG5001131 LAN5001169 LAN5001203 LAN5001204 LAN5001282 LAN5001373 LAN5001391 LAN5001392 LAN5001484 LAN5001664 LAN5001842 LAN4300009 AG4300022 IND4300051 NUR4300055 COMM4300059 COMM4300057 AG4300107 NUR4300143 NUR4300144 NUR4300182 NUR4300206 AG4300242 NUR4300251 NUR4300399 NUR4300409 NUR

RodriguezAGMecca AG4300362 IND

Non-Potable Water Use Permits in Model Area and Comparisonof Modelled to Permitted Pumpage

Model Q Permitted % Diff(mgy) (mgy) ModeL/Permit

KING MOUNTAIN CONDOMONTEREY FLOWERS INC.SOUTH FLORIDA GRASSINGMARTIN CO. GOLF & C.C.

YACHT & COUNTRY CLUB, INC.MARINER SANDS COUNTRY CLUBMID RIVERS INC.S & S FLOWER FARMSMARTIN CO. SCHOOL BOARDPIPERS LANDINGRGA DEV. (CUTTER SOUND)ENVIRON. VENTURES (THE WATERFORD)J. & J. DAVIS (TARHEAL FARMS)PALM CITY SODLOBLOLLY PINES DEVELOPMENT

J. RICHARD HARRIS (CAPTAIN'S CREEK)CORNERSTONE GROUP (COBBLESTONE C.C.)MARINER SANDS PROP. OWNERSMARTIN CO. (HOLT LAW ENF. CENTER)

JUPITER HILLS CLUBRIVER BEND GOLF COURSELINKS GROUP (CYPRESS LINKS GOLF COURSE)JOHN D. & NANCY P. MARTIN (LESSEE)LITTLE CLUB CONDO ASSOC.HOSE SOUND WATER COMPANYHOSE SOUND GOLF CLUBPERO FAMILY FARMS

RESTIGOUCHE, INC (MAPLEWOOD)TEGUESTA COUNTRY CLUBJONATHAN'S LANDINGS & J FARMSAMERICAN FOODSSEA OATS OF JUNO BEACHJUPITER 1 HOMEOWNERSRADMOR CORPORATIONOCEANSIDE TERRACE HOMEOWNERSTHE RIDGE AT THE BLUFFSTHE RIVER HOMEOWNERSJUPITER BAY HOMEOWNERSLJ JUPITER VENTURE (VILLAS OF OCEAN DUKEJUPITER BEACHCOMBER CONDOPRATT & UHITNEY

MARQUETTE ELECTRONICSSUNSHINE STATE CARNATIONFLORIDA POWER & LIGHTR. N. RINKER FARMS INC.ROBERTS FISH FARM

LARRY WRIGHT'S FISH FARMHOBE-ST. LUCIE CONSERVANCYHOWE HOLDINGS INC. (FERNLEA NURSERIES)STUART FARMSSCHRAMM'S FLOWERSRICHARD G. & MARSHA HUPFELBLOODIS HAMMOCK GROVES, INCMARTIN CO. TREE GROWERSLOXAHATCHEE NURSERY OF STUART0. & E. NISSEN (SUSHINE STATE CARNATION)R. REMELIUS (CLASSIC GROWERS)No PermitNo PermitCAULKINS INDIANTOWN CITRUS CO.

S)

General Permits7900054 LSC KIMGS00O, INC.7900121 PUSI STEFFENS TOWNHOUSE7900194 PUSI MARTIN CO. (SOUTH FORK H.S.)8100222 PWSI R.C. LINDSEY (VISTA SALERNO SUBED.)8200407 PWSI MARTIN CO. STOCKADE8300118 LAN INDIANTOUN TELEPHONE CO.8300122 LAN MONTEGO COVE

-0.036-3.103

-291.243-147.919-183.803-406.955-50.410-5.161-16.521-67.390-59.462-38.871-41.687

-482.064-20.481-8.161-25.595-34.103-21.007

-421.972-100.428-27.592

-809.826-3.358

-127.696-35.358

-165.058-49.198-10.427-63.602

-1204.780-275.769

-3.914-12.272-29.321-5.929

-121.896-9.240-6.766-4.448-4.421-0.147-5.067-9.751

-243.099-6.048

-30.776-36.498

-2743.668-9.406-22.613-7.936-2.700

-17.862-6.908

-25.938-7.199-22.676

-204.075-1117.341

-0.283

-3.282-5.252-11.660-2.332-1.166-0.933

-21.920

11.1013.80

288,90229.90176.80271.20119.004.3037.9083.8061.90361.4067.40333.0098.407.90

113.3069.4019.70

160.60

134.90295.0024.3051.10133.90456.0080.77

318.9078.2092.4013.803.2330.302.00

51.6021.658.378.371.35

37.895.136.10

300.0018.1030.8036.50

4460.0020.4041.308.508.0018.4048.0038.2034.0049.30

50.00

3.6536.5036.503.6536.5036.5032.10

022

10164

104150421204480961162145211032349

107263

2027514

250263661

20154129828

38097

296236438153

3270

99160813310010062465593349714682146

1

9014326433

68

TABLE E-5:

84001538500051 LAN8500076 LAN8500107 LAN8500192 LAN8500207 LAN8500361 LAN8600003 LAN8600020 AG8600137 IRR8600148 LAN8600149 LAN8600171 LAN8600182 LAN8600266 LAN8700092 LAN8700110 LAN8700160 PWSI8700392 LAN8700436 LAN8800027 PWSI8800089 LAN8800096 LAN8800153 LAN8800182 PJSI8800357 LAN4300493 LAN4300512 LAN7900106 PUS8500186 IRR8600331 LAN8700082 LAN4300528 LAN8200398 PWIR8400123 AG8400212 AG8400224 AG8500048 AG8500301 AG8500352 AG8500353 AG8500376 AG8600023 AG8600084 AG8600200 AG8700450 PuSI8800261 AG8800441 AG5001797 PWSI5001896 AG5001961 AG5002016 AG8800133 NUR8800134 NUR7900104 PWS8200060 HUR8200161 NUR8200233 NUR8200242 NUR8700253 NUR8700258 AG8700361 NUR8700432 NUR8200354 NUR8700176 NUR8700448 NUR8800277 NURBLock28 AG

BLock32S AGBLock32N AG

BLock33 AG

SEABRIDGE ASS. (BUNKER HILL 0 HRTGE ROGE)MARTIN DOWNS (SUNSET TRACE)GTE SPRINT COMMUN. (R-2 REPEATER)MARTIN CO. (J.V. REED PARK)STARLING COURT (MARTIN DOWNS)R.H. PROPERTIES (VILLAGE CENTER)PIRATES COVEMARTIN OOWNS PUBLIC PARKSKIN POY LEE & SONSMALLARD CREEKKINGMAN ACRES CONDOKINGMAN ACRES CLUBKINGMAN ACRES VILLAGE IIAMONARCH POINT DEV. (PARCEL 35)REGENCY SQUARESHOPS OF STUART/WEDGEWOOD COMMONSWHIPPOORWILL SUBDIVISIONEPISCOPAL CHURCH OF THE ADVENTFAIRWAY GARDENSINDIAN STREET SHOPPESWATERFORD ADMIN. & SALES CTR.CHARTER CLUB AT MARTIN DOWNSIBIS POINT AT MARTIN DOWNSPENNWOCD FARMJERRY'S FOUR SEASONS MARKETMY SCHOOL LEARNING CTRMARTIN CO. ADMIN. COMPLEXFIRST NATIONAL BANK (SE OCEAN BLVD)GOLDEN CORRAL STEAK HOUSETURTLE CREEK EASTINDIAN HILLSJUPITER-TEQ. CHURCH OF CHRISTTURTLE CREEK CLUBW. T. BELLEWSUMMER WINDS OF JUPITERLOGGERHEAD PLAZAPRATT & WHITNEYOCEAN 8 THE BLUFFS SOUTHBANANA MAXCHASEWOOD NORTHCHASEWOOD OF JUPITERJUPITER PK OF COMMERCEBLUFFS SQUARE SHOPPESJUPITER HEALTH & RECRE. CENTERMAPLEWOO PARK, PHASE ISIERRA SQUAREJUPITER WESTELEMENTARY SCHOOL "A" (LIMESTONE CRK)H & B TOOLLOXAATCHEE POINTEMALLARDS COVE IILAUREL OAKSPARAMOUNT NURSERY (NORTH SITE)PARAMOUNT NURSERY (SOUT SITE)F. PASQUALINO (RESTAURANT)ADAMS NURSERYBIG PINE NURSERYELIAS LUSTIGPINDER'S NURSERYBUILD INC.TURNPIKE DAIRYISLAND PLANT NURSERIESBURKEY NURSERYD. KOUBA (THE PLANT FACTORY)D. GLUCKLER (FLOWER FARM)WATER-RITE TREE FARMJUPITER TREE FARMUnpermittedUnpermittedUnpermittedUnpermitted

Key to Use Types:AG = AgricuLturaLIND = Industrial

GLF = GolfCmE = Commercial

MUR = Nursery LA, LSC,IRR = LandscapePWSI = Public Water Supply & Irrigation

-7.484-37.320-0.117-9.190-4.197-2.293-1.313-3.498

-43.431-4.430-3.414-1.313-1.970-12.942-3.938-8.534-4.332-0.583-4.664-1.182-0.656-25.651-15.391-4.665-0.263-2.332-0.787-0.193-1.240-7.439-1.735-1.116-1.241-1.078-3.018-1.617-1.401-6.199-0.323

-15.846-19.403-4.851-2.694-3.234-3.233-0.108-1.833-9.702-0.108-3.758-2.479-0.572

-14.396-14.396-0.719-3.239-1.080-1.799-0.899

-15.298-21.884-7.198-3.600-3.508-5.998-0.525-8.398-4,627

-12.738-4.555

-16.445

36.5031.3036.5027.306.2310.202.005.1832.808.853.610.732.8125.5023.6011.407.530.331.648.761.99

32.8030.500.730.372.921.970.663.65

21.903.132.042.31

3.282.557.113.502.19

27.3032.8019.10

3.658.390.447.30

19.400.377.305.912.19

21.9021.903.65

36.5036.5036.502.92

32.8032.8021.903.65

36.5035.007.30

32.80

Non-Potable Water Use Permits in Model Area and Comparisonof Modelled to Permitted Pumpage (Continued)

APPENDIX F

COMPUTED AND OBSERVED

HYDROGRAPHS REPRESENTING

MONITOR WELLS, 1989

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