Citation
A Three-Dimensional Finite Difference Ground Water Flow Model of the Surficial Acquifer in Martin County, Florida

Material Information

Title:
A Three-Dimensional Finite Difference Ground Water Flow Model of the Surficial Acquifer in Martin County, Florida
Creator:
Adams, Karin M
Publisher:
Hydrogeology Division, Dept. of Research and Evaluation, South Florida Water Management District ( West Palm Beach, Fla )
Publication Date:
Language:
English
Physical Description:
220 pages : illustrations, maps ; 28 cm.

Subjects

Subjects / Keywords:
Martin County (Fla.)
Floridan Aquifer
Groundwater ( lcsh )
Groundwater flow -- Mathematical models ( lcsh )
Hydrologic models ( lcsh )

Notes

General Note:
(Bibliography) Includes bibliographical references (pages 82-83).
General Note:
(Statement of Responsibility) by Karin Adams.
General Note:
"March 1992."
General Note:
"DRE Inventory Control #310."
General Note:
Technical Publication 92-02

Record Information

Source Institution:
Florida International University
Holding Location:
South Florida Water Management District
Rights Management:
Please contact the owning institution for licensing and permissions. It is the users responsibility to ensure use does not violate any third party rights.
Resource Identifier:
FI12090308
(OCoLC)41398122

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Technical publication ;

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Technical Publication 92-02 A Three-Dimensional Finite Difference Groundwater Flow Model of the Surficial Aquifer in Martin County, Florida March 1992

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Technical Publication 92-02 A THREE-DIMENSIONAL FINITE DIFFERENCE GROUNDWATER FLOW MODEL OF THE SURFICIAL AQUIFER IN MARTIN COUNTY, FLORIDA by Karin Adams, P.G. March 1992 This publication was produced at an annual cost of $900.00 pr $1.80 per copy to inform the public. 500 292 Produced on recycled paper. DRE Inventory Control #310 Hydrogeology Division Department of Research and Evaluation South Florida Water Management District West Palm Beach, Florida

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EXECUTIVE SUMMARY This study was undertaken as part of the South Florida Water Management District's Water Supply Planning initiative. One of the water supply planning directives in the initiative is to "develop and maintain resource monitoring networks and applied research programs (such as forecasting models) required to predict the quantity and quality of water available for reasonable-beneficial uses" (SFWMD, 1991). The model will be used within the SFWMD by the Planning Department in the development of the Upper East Coast Water Supply Plan and by the Regulation Department to implement the water use criteria and policies of the District. The Water Supply Plan includes a projection of future water demand, identification of water sources and methods to meet this demand on a regional scale and an analysis of impacts associated with these alternate methods. New regulatory criteria from water supply plans and the Draft Water Supply Policy Document will be incorporated into the District's Basis of Review for Consumptive Use Permits. The models will also be used for impact analysis in the District's water use regulatory function and on the local scale by governments and consultants. This model is not considered to be an unchanging final product. As new data and technologies are available, it will be upgraded and improved. Future plans include the integration of surface water and water quality elements, Geographic Information Systems (GIS) applications, and the ability to "zoom" in on specific model areas for more detailed local modeling. Martin County, Florida is underlain by two aquifer systems: the Surficial Aquifer System and the deeper Floridan Aquifer System. Information from a ground water assessment completed by the South Florida Water Management District in 1990 was used to develop a regional three-dimensional ground water flow model. This model focused on the Surficial Aquifer System while a separate model was developed for the Floridan Aquifer System and is documented separately. For modeling purposes, the Surficial Aquifer System in Martin County was divided into three layers representing different lithologic types: 1) fine sand, silt, and organics, 2) shell, sand and limestone/sandstone with little or no fines, and 3) sand, shell, silt and poorly consolidated, micritic limestone. The second layer is moderately productive and most ground water is withdrawn from this interval. Productivity in the remainder of the Surficial Aquifer System is low. The Ground Water Flow Model The Martin County Surficial Aquifer System model was developed using the U.S. Geological Survey modular three-dimensional finite-difference ground water flow model code, commonly known as MODFLOW. This code was used because it allows a detailed evaluation of ground water flow, is available in the public domain, is compatible with most computer systems, and contains many features which make it easy to use and modify. MODFLOW simulates ground water levels and flow using data describing the aquifers, such as hydraulic conductivity, transmissivity, leakance, and storage. Stress on the aquifers (e.g., recharge, evapotranspiration, well withdrawals, and interactions with surface water bodies) can also be simulated with the model. The horizontal model grid is composed of 59 rows and 109 columns. A uniform size of 2,000 by 2,000 feet was used, except for five columns of cells on the western edge of the model. These columns increase in width as they extend westward six miles into Okeechobee County. Recharge to the Surficial Aquifer System Rainfall provides approximately 95 percent of the total annual aquifer recharge in the study area under present conditions. An additional four percent represents recharge coming primarily from ground water flow into the study area from boundaries, and the final one percent is leakage from rivers. Discharge/Water Use from the Surficial Aquifer Svste m Evapotranspiration accounts for approximately 70 percent of the outflow from the model area under present conditions. Leakage to canals in the study area accounts for an additional 19 percent of the losses. Well withdrawals account for an additional nine percent, and the remaining losses are flow out of the model along boundaries. Well withdrawals for agriculture, public supply, and domestic self-supply were determined by various means. Agricultural ground water withdrawal information for the calibration period was obtained primarily from water use permits

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issued by the District. The permits supplied information on crop types, acreages, irrigation practices, and wells. Additional information, when necessary, was obtained directly from the agricultural operators. This information was used to estimate monthly water use during the calibration period. Actual pumpage records were used when available. Data on public supply water use, as reported to the District and to the Florida Department of Environmental Regulation, also was used in the model. Domestic self-supply was estimated based on land use types and irrigation use assumptions. Calibration/Sensitivity Testing The model was calibrated by adjusting aquifer parameters within prescribed limits to match computed water levels with monthly observed water levels in monitor wells for the period January 1989 through December 1989. The calibration criteria required that modeled water levels be within one foot of the observed water levels for at least nine of the twelve months modeled, and this criteria was met in fifty-three percent of the wells. For an additional twenty-nine percent of the observation wells used, calibration criteria was not met because of limitations in reporting model levels. The model value used to verify calibration represents the water level at the center of each 2,000 x 2,000 foot cell. Because of the gradient across the cell and the location of the observation well in the cell, the well may not be at the same water level as the level in the center of the cell. However, comparing model values in adjacent cells confirms that the gradient is correct and, therefore, the model does calibrate to the well. Since a majority of the wells verify calibration of the model, there is a high degree of confidence in the model. To ensure the best possible accuracy for evaluative or predictive purposes, it is important to test the model's sensitivity to the estimated parameters. The model was fairly insensitive to changes in hydraulic parameters, but changes in inputs to the recharge and evapotranspiration packages significantly affected calibration in all three layers of the model. Recommendations The most important recharge and discharge sources in the model are rainfall and evapotranspiration; the accuracy of the model depends on the accuracy of the input data for these two sources. As currently designed, the model provides a simplification of the actual complex processes involved in determining how much rainfall actually reaches the aquifer and how much water is removed from the aquifer by evapotranspiration. Work in these areas is needed to improve model accuracy. Domestic self supply and irrigation are large users of water in Martin County. In order to enhance the accuracy and reliability of the model for resource availability determinations, improvements in the estimation of domestic self-supply use could be made with better information on exactly where utility boundaries are located and which houses in utility areas use private water for irrigation. Public water supply utilities that use multiple wells need to record raw water pumpage from each well. Because of differences in pump capacity and the operating schedule of each well, total wellfield pumpage is of limited value in generating model input necessary for determining wellfield impacts. This information is especially important when "zooming" in on an area. Based on the model budget, discharge to surface water bodies represents a significant loss from the aquifer. Input data, including canal construction details and stage levels, are limited and estimation errors could result in inaccurate seepage amounts into or out of the canals. Efforts should be made in the permitting process to obtain and include this data in future surface water management permits. Stage recorders in major grove canals would provide valuable information on water levels to set in river/drain cells in future modeling efforts. The model should be used in the evaluation of water use permit applications. Where a finer scale or site-specific model is required, the regional model could be used to provide the boundary conditions. The model should continue to be refined and updated whenever additional information becomes available. Availability of Model for Use Electronic copies of model data sets are available upon request from the Hydrogeology Division. If, in using the model, users include new or more detailed data that results in a better calibration, they are encouraged to share that data with the District. Refinement of the model is a continuous, ongoing process.

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TABLE OF CONTENTS EXECUTIVE SUMMARY ............................................... ..... .i LISTOFFIGURES LIST OF TABLES ................... ......... ................................ vii ACKNOWLEDGEMENTS ....... .. ........................................ viii ABSTRACT .-..................... ................ ........................... ix INTRODUCTION ....... ......... 1 INTRODUCTION ................................................................ 1 Purpose and Scope ............... ................................ 1 Location of Study Area ......................... .. .............................. Topography and Physiography ....................... ....................... 1 Previous Investigations ..................................................... 5 Hydrogeology of the Surficial Aquifer System ...................................... 5 MODEL DESCRIPTION .................................. ....................... 11 Overview .................................... ................. ...... 11 Discretization ...................................................... 11 Boundary Conditions ........... ............ ............................ 15 Hydraulic Characteristics ............................................... ........................ 17 Transmissivity/Hydraulic Conductivity ...................................... 17 Layer O ne ..................... ......... ....... ..... ...... 20 Layer Two ...... ................... ................. 20 Layer Three ........................ ...................... 20 Storage and Specific Yield ......................... ....... 20 Vertical Conductivity ................... ................................. 20 Surface Water Interactions ................ ................................. 22 Recharge ............................................................ 25 Evapotranspiration .................... .................................. 27 Ground W ater Use ............................................................... 33 A gricu ltu ra l ...................................... ........ .... ...... 33 Public Water Supply .................................. .............. 35 Domestic Self Supply .................................... ......... .. 35 Other Ground Water Uses ................... .............................. 41 CALIBRATION ................................ ..... ................ ..42 Transient Calibration ..................... ............................... 42 M ethod ............ ............... ............ .................. .... 42 Results .......... ................................................. 50 Steady State Calibration ........ ......................... ................ ........ 54 Method ....................................... 54 Results ............. ............................... ............ 54 Budget and Flows ..................................................... 62 Layer One ...................................... .................. 62 Layer Two ......................................................62 Layer Three ...................... .......... ......................... 62

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SENSITIVITY TESTING S.......................................................... 3 Layer One Layer Two ....................... 73 Layer Three --..... 73 Model Boundariese ................. ......................................... 7 M odel Boundaries ... ..............76 Climatologic 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 .................. 85 APPENDIX B: Maps of Hydraulic Parameters ...................... ... 10 5 APPENDIX C: General Head, River and Drain Input Data ..... 115 ......... .. .. .... .... .1 1 5 APPENDIX D: Recharge Methods, Rainfall Station Map and Table, Recharge and ET Coefficients S--.......................... ........... 131 APPENDIX E: Water Use Data, Public and Agricultural.........153 ............. ......... 153 APPENDIX F: Computed and Observed Hydrographs Representing ....... ..... Monitor Wells, 1989. 189

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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

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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

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LIST OF TABLES Table Page 1 Aquifer Performance Test Data Used in Model 7 2 Packages in MODFLOW Used in the Martin County Model ... ......... 12 3 Soil Types and Corresponding Vertical Hydraulic Conductivity and Capillary Fringe Height ................................................. 21 4 Supplemental Irrigation Water Rates Used to Calculate Irrigation of Grass ........... 34 5 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

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ACKNOWLEDGEMENTS This project was carried out under the direction of Scott Burns, formerly the Director of the Hydrogeology Division and currently Director of the Water Use Division. I would like to thank him for giving me the opportunity to undertake this effort. Keith Smith, Acting Director of the Hydrogeology Division, also provided direction and editorial comments. The author wishes to acknowledge the peer review committee, whose comments greatly improved the quality of this report: Leslie Wedderburn, Dept. of Research and Evaluation, SFWMD William Scott Burns, Water Use Division, SFWMD Paul Millar, Local Government Assistance, SFWMD Tom Tessier, Geraghty and Miller Linda Horne, Martin County Utilities Department Rick Nevulis, CH2MHill, Deerfield Gary Russell, USGS, Stuart Pete Anderson, Geotrans, Inc., Virginia The author also wishes to thank Emily Hopkins for her prompt and valuable editorial comments. Jorge Restrepo provided numerous insights into the model as well as several very useful pre and post processing programs for which I am very grateful. I also appreciate all the suggestions I received from my fellow hydrogeologists as I discussed problems I encountered. Especially helpful were the observations and challenges presented by Mary Jo Shine as she evaluated the model, which improved it in several areas. Gratitude is expressed to Barbara Dickey for her immediate attention and assistance to all problems involving the computer, especially in writing programs to make my job easier. Also to Diane Bello, Janet Wise and Dave Demonstranti for creating wonderful graphics and patiently accepting the tedious modifications. Finally, to Hedy Marshall for her expediency during the compilation of the text and her patience during the editorial phase of this project.

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ABSTRACT In Martin County, Florida, the Surficial Aquifer System is the primary ground water supply source. The Surficial Aquifer System is comprised of a moderately productive zone of sand, shell, and limestone/sandstone intervals overlain and underlain by less productive layers of mainly sand and silt. A three-dimensional ground 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 109 columns, with a grid spacing of 2,000 feet. Initial aquifer parameters were obtained from various agency and consultant reports. A transient calibration was performed for a one-year period (1989) by comparing simulated water levels with observed water levels from an extensive monitoring network. Sensitivity analyses showed that water levels in all layers of the Surficial Aquifer System are sensitive to changes in recharge and the evapotranspiration surface. Work is needed in these two areas to improve model accuracy.

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INTRODUCTION PURPOSE AND SCOPE This study was undertaken as part of the South Florida Water Management District's program to develop regional comprehensive water supply plans and support regulatory decisions of the agency. These plans will be based on quantitative assessments of the available water resources combined with estimates of future water use demands. Evaluation of existing water supply problem areas, identification of potential problem areas, and development of management guidelines will be integral parts of a water supply plan. The purpose of this study was to develop a countywide three-dimensional ground water flow model of the Surficial Aquifer System in Martin County. Specific uses of this model will be to develop and evaluate the ground water elements of the water supply plan for the Martin County area and to evaluate the impact of future ground water uses on existing users as part of the regulatory process. The model will also be used to evaluate short-term drought management scenarios during declared water shortages. This report represents one in a series of ongoing studies to characterize the ground water resource of Martin County. Development of the ground water flow model is documented in this report. The model will be continually refined and updated as it is used in the regulatory and planning processes, and as more data become available. Electronic copies of model data sets are available upon request from the Hydrogeology Division. The modeling work was preceded by extensive field work to define the extent and occurrence of major aquifer systems, regional ground water flow patterns, water-quality trends, and a preliminary assessment of the future development potential of the ground water resources of Martin County. The results of the field work will be described in a SFWMD Technical Publication to be released in 1992, LOCATION OF STUDY AREA Martin County is located in southeastern peninsular Florida, east of Lake Okeechobee (Figure 1). It is bounded on the east by the Atlantic Ocean and to the west by Lake Okeechobee and Okeechobee County. 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 miles from north to south. The study area includes most of Martin County, a six-mile buffer area into adjacent Okeechobee County, and five miles into northern Palm Beach County. A buffer zone was not extended into St. Lucie County because model development was coordinated with a similar modeling effort in St. Lucie County (Padgett, in press) with the intent of eventually combining the two models. The Jensen Beach peninsula, north of the St. Lucie Inlet and within the political boundaries of Martin County, is actually part of the St. Lucie County ground water flow regime. Therefore, it is included in the St. Lucie Surficial Aquifer System model rather than the Martin County model. The modeled area lies generally within Townships 40 through 43 South, and Ranges 36 through 43 East, and encompasses approximately 720 square miles, 550 of which are in Martin County (Figure 2). TOPOGRAPHY AND PHYSIOGRAPHY Martin County lies within the Atlantic Coast Lowlands (White, 1970) and includes the Eastern Valley, the Osceola Plain and the Everglades physiographic regions. Each region has similar topography or relief, or a certain soil type if common. The topography (based on USGS quadrangle maps) and soil types (after McCollum, 1981) in Martin County are illustrated in Figure 3. Most of Martin County lies within the Eastern Valley, which is a broad, flat relict beach ridge plain. In the central portion of the county, between the Osceola Plain and Green Ridge (see Figure 2), this is evidenced by the closely spaced system of subparallel ridges and swales oriented parallel with the present Atlantic beach (White, 1970). Elevations in the Eastern Valley range from 15 to 30 feet above mean sea level. The Osceola Plain ends in a narrow terrace in Martin County and appears to have been a narrow peninsula or series of islands and shoals at one time. It is approximately two miles wide in Martin County and has an elevation of 30 to 50 feet above mean sea level. Located adjacent to Lake Okeechobee in the southwest corner of the county, is the Everglades region which is flat and covered by organic soils formed by the growth and decay of sawgrass. Elevations in the Everglades range from 15 to 20 feet above sea level.

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A TL A N T I C OCEAN PERC Sn RT NAPLES BOCA RATON FORT LAU ERDALE HIAN.! LOCATION OF ODIERI.ZED HYDROOEOLOOIC CROSS SECION Location of Study Area FIGURE 1.

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LEGE ND SSols of the LO R;dges od Knolls II 511 of he Sloughs and Fresh Water M4rshne SSoils of the Fklw.ood Soils of the Sand RIdges and Coastal Islands SSils o tM Tad i Swams Topography and General Soils Maps of Martin County FIGURE 3.

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PREVIOUS INVESTIGATIONS The hydrogeology of southeastern Florida was generally examined by Parker (1955). A detailed investigation of the water resources of Martin County was performed by Lichtler (1960). The water resources of the county were revisited by Earle (1975) and Miller (1978) also within this same planning area. Stodghill and Stewart (1984) used surface DC resistivity surveys to delineate the hydrostratigraphic zones of the coastal ridge aquifer in Martin County. Nealon and others (1987) provided a regional analysis of water availability and water resource planning recommendations. A number of authors have also provided information on the county's aquifers, but on a site-specific basis. MacVicar and others (1984) examined the ground water flow of the Surficial Aquifer System in Martin, St. Lucie and eastern Okeechobee counties (Upper East Coast Planning Area) using the South Florida Water Management Model. Nealon and others (1987), refined the grid spacing of the Upper East Coast South Florida Water Management Model to simulate hydrogeologic conditions in Martin County and a portion of St. Lucie County. Three-dimensional ground water flow models have been developed and published for Palm Beach County (Shine, et al., 1990) and for the Jensen Beach Peninsula (Hopkins, 1991). Models for the St. Lucie County Surficial Aquifer System and for the Floridan Aquifer System underlying Martin, St. Lucie, and portions of Okeechobee, Indian River and Palm Beach Counties have been developed and documentation is currently underway. HYDROGEOLOGY OF THE SURFICIAL AQUIFER SYSTEM A brief summary of the hydrogeology which supports the model development follows. Readers wishing a more detailed discussion of the hydrogeology of the Martin County area are referred to Adams (in press). Hydrostratigraphic nomenclature used in this report is consistent with guidelines set forth by the Southeastern Geological Society Committee on Florida Hydrostratigraphy (SGSCFH,1986). Martin County is underlain by two aquifer systems: the Surficial Aquifer System and the Floridan Aquifer System. The model developed for this study was limited to the Surficial Aquifer System (Figure 4). The Floridan Aquifer System, being modeled separately, is not discussed in this report, but will be the subject of a forthcoming publication (Lukasiewicz, in press). The Surficial Aquifer System consists of the water table aquifer and hydraulically connected units above the top of the first occurrence of laterally extensive and vertically persistent beds of much lower permeability (SGSCFII, 1986). In Martin County, the Surficial Aquifer System is unconfined to semi-confined and is comprised of three hydrogeologic zones: the surficial sands, the primary water-producing zone, and a less permeable zone overlying the confining bed. The surficial sands are shallow and may not be completely saturated throughout the year. The primary water-producing zone consists of sand, shell, and relatively thin beds or lenses of sandstone/limestone. The less permeable zone is delineated as a sand, silt, shell and soft micritic limestone portion of the Tamiami Formation. Generally, the surficial sands range in thickness between 20 to 40 feet. These sands have low to medium permeability and may produce small quantities of water (Lichtler, 1960). These sands range in size from very fine to coarse with fine grain being prevalent. Also included in this zone is organic material including "hardpan" units and interbedded lenses of sandy clay and silt. The major producing zone ranges in thickness from 20 to 250 feet, averaging approximately 130 to 150 feet. The producing zone is capable of providing relatively large quantities of water depending on aquifer characteristics. Transmissivity is the term related to the water-transmitting capacity of the aquifer at a site. Values of transmissivity for 53 sites in Martin and adjacent counties, were collected from various agencies and consultant reports. Of the 53 tests, 37 were used to generate input data sets for the model (see Table 1 and Figure 5 which includes only those tests that were used), while the remaining tests were not used due to questionable data or lack of documentation. In general, transmissivity values countywide are around 4,000 ft2/day (30,000 gpd/ft) but increase to the east and south, with transmissivity values of over 13,000 ft2/day (100,000 gpd/ft) at the Martin/Palm Beach County line along the coast. The permeable limestone and sandstone strata are more prevalent towards the east (Lichtler, 1960) and the thickness of this zone is greater in this area. However, in the Stuart area, located in the northeast part of the model, transmissivities remain around 4,000 to 6,700 ft2/day (30,000-50,000 gpd/ft). This lower transmissivity, when compared to the other coastal area values in the model area, may be due to the higher clay percentage within the aquifer in this area (Miller, 1978).

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Q Q Q o a cl 04 eel V V 7 C"S C C7 ci R1 Lw tw = 4. ET14 CO 0 x 0 d .n sv r5 d v .. a 4 .r cv LO e Ir o 0 0 0 c o ca o a o b 6 a r Q E~-+ W C d N en GxV w r] N N w X0 N m G.i U q .6 m a ca m m 00 t; 00 cp m .0 N co q C r W r co m y n Cr! m in m dV cm LO C14 N m G7 q x p Q N co CD, o d O N F a 0 O + a d c rO1 To a ry z a C o F 's x z V1 H 'r N v LC] 00 GV Cfl N N U.) N y N N b' d N m cn IV M 06 0 to (20 N N N N M C9 N M M u7 L N d c o 0 0 co m t8 t 0 0 m c o 0 o a m us o 0 co co b N C C) C 00 O O O O W ?, "" N w O O = U"4 UC3 CD w..,w Lo N+ N N W x W [+7 iA 1A QM -4 t+ 45 m M w p 00 d9 ch O 00 00 z rn m as o~o a; oD, a o, m as V" coo, C; R, Z Q N O O O d' OD t0 O p O O M G O O p O M CI} C d O LO ul d s[3 O +--i O iL O 10 O F G sp c d u] "c N G a0 C O IV N M [ CD [ 81 Cy co m O co co N cv m .O oo r+ N d' 00 iG of GS 1n iG 'd" tt7 N CG C+ G7 OD a0 a0 a0 trr tcfl m co t N N r N t~ N a '" v a a a 1 L e a b v rcq tr C 0 0 ai o co a o 0. 0. E Oa Gq f 9 q. x 0. *N IPA 00 O m In Q' d' O BLS !7 Ifd U r 0 6 3 a a w w d a G a 61 m O 11 x

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1.040.000 1.020,000 1.000;000 950.000 960.000 940.=0 920.000 n 1 2 40 S 2 4 IAY a T 41 S T735 00CM 000G*I on' -n 2 -I -u Q r% no .W.t 000"ox0"a. DW'Wo"1 000'095 ooo*m 00010*9

PAGE 21

The less permeable zone found below the main producing zone is significant in its ability to store water and release it to the producing zone if needed. Wells completed in this zone do not often yield useful quantities of water as the presence of silts and fine-grained, poorly consolidated limestones reduces its transmissivity. The base of this zone was defined as that point where the percentage clay content became significant enough to essentially prevent the release of water to wells or the producing zone.

PAGE 22

MODEL DESCRIPTION OVERVIEW In this study, the U. S. Geological Survey modular three-dimensional finite-difference ground water flow model code (McDonald and Harbaugh, 1988), commonly known as MODFLOW, was used. This model code was selected for the following reasons: 1. It is available in the public domain, 2. It is compatible with most computers with only minor modification, 3. The modular structure of the code and its excellent documentation allow easy modification of the code and the addition of new modules for specialty applications, 4. MODFLOW allows great flexibility of data file structure and management; this facilitates the employment of and interaction with other software for data manipulation, 5. The cell-by-cell flow feature of the code can be used to: A. Evaluate in detail flow and head changes associated with various withdrawal scenarios, and B. Generate boundary conditions for higher-resolution models within the regional flow model, and 6. It can be coupled with currently available nondensity dependent solute transport models. The hydrologic properties or conditions which the model can represent include: The aquifer properties of hydraulic conductivity or transmissivity, storage capacity, and vertical conductance. Initial water level conditions. Recharge. Evapotranspiration (ET). Rivers and drains. Rivers can both drain and recharge the aquifer, depending on the relationship of river and aquifer heads; drains do not recharge. Wells, as either discharge or recharge. Three iterative solution schemes are available for solving the finite difference equations governing flow in porous media: slice-successive over relaxation (SSOR), strongly implicit procedure (SIP), and the preconditioned conjugate gradient (PCG) method (Kuiper, 1987). The SIP method was used in this study and after adjusting the acceleration parameter down to 0.5, it worked well. SSOR is the better solution method for some strongly layered conditions. However, it is not as direct as SIP, therefore, it generally requires more time to arrive at a solution. Table 2 summarizes the modules and their application to the Martin County model. DISCRETIZATION Discretization is the process of breaking up a continuous system into a set of discrete cells defined by a system of rows in a horizontal plane and columns in a vertical plane, to represent the system numerically. The study area was discretized into a horizontal grid comprised of 2,000 ft2 cells, assembled into a grid of 59 rows and 109 columns (Figure 6). The westernmost five columns of cells were expanded into Okeechobee County as shown in Figure 4 to provide a buffer zone. The Martin County model contains three layers (Figure 7). The layers were determined by lithology from 224 wells. Locations, information source and breakdown into model layers for each well used in this study, as well as structure contour maps, can be found in Appendix A. Layer one, beginning at land surface, consists of fine sand, silt and organics; layer two is made up of sand, shell, and mostly thin layers of limestone/sandstone with little or no fines; and layer three is similar to layer two but contains silt/clay and the limestone is generally soft and micritic: In coastal areas, there are some minor confining units which define additional layers; however, they pinch out quickly to the west and were not considered significant on a regional scale. The surficial sands, generally in the eastern portion of the county, contain one or more "hardpan" units (layers of low permeability composed primarily of fine sand and organic material) within a few feet of land surface. In the Hopkins (1991) study of the Jensen Beach Peninsula, the hardpan, where present, was found to vary greatly in thickness and depth over very small distances. It was assumed that this variability would occur throughout the county;

PAGE 23

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 Used FLOW 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, Intrarecharge or drain the aquifer coastal, salt/brackish Loxadepending on the head hatchee, C18, St. Lucie River, gradient between the river controlled drainage district and the aquifer. canals in Jupiter wellfield area. RECHARGE Simulates recharge to the Used with measured precipiaquifer from infiltration of tation: a pre-processor program precipitation, calculates losses to interception/ evaporation and runoff. WELL Simulates a source/sink to Used to represent discharge from the aquifer that is not public water supply, domestic self affected by heads in the supply, and irrigation water use. aquifer. DRAIN Simulates discharge from the Used to represent all drainage aquifer to drains, district canals with unmaintained water levels, all grove canals, ranch canals, upstream St. Lucie River & Forks, upstream Loxahatchee River & Forks. EVAPOSimulates evapotranspirUsed modified Blaney-Criddle TRANSPIRATION ation where the source of calculation: coefficients estimawater 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, St rate proportional to the head Lucie & Jupiter Inlets, FP&L difference between the Reservoir. source/sink and the aquifer. STRONGLY IMPLICIT Solves the model's finite Used PROCEDURE difference equations using (SIP) the Strongly Implicit Procedure. OBSERVATION Generates a file of computed Used to generate comparative NODES water levels for selected hydrographs and calibration model cells. agreement.

PAGE 24

1,040.000 1.020.000 1.0001000 960.000 960.000 -940.000 920A00 IS O 9 G O O r O G I O 4 O N h 6 O O c' n 8 c N g A 1365 1 T 395 7405 T415 p o Si R O O S kkk J y O O 4 T W OO 0 y r 5 J MM ti 0 h W O f 4 o o b +O R 4 O C O r Y W W n WrO 0 U eY J r O 0 N III I --en W W A n 0 0 -1 VT OF' tlWtl "1 n Y 'LJ OY -a a e o a 5 90 1 5 61C 1 i S 00 1 5 to O r O b r O h O r pOp m O v O d r n V 0 0 qC O g g aS 000'040'1 000'OZO'L D001000% 000'098 000'096 000'0 6 OVIO s a, -a Q W W

PAGE 25

General Lithology Lithology General Hydraulic Schematic Characteristics Model Layer very fine to : medium quartz low permeability sand with silty ...low permeability intervals,organics -calcite cemented sand to sand, shell and thin limestone interval to well cemented sandy biogenic limestone sand,shell,silt and moderate to poorly -. cemented micritic limestone moderate permeability 2 low permeability olive green ----_ very low base no sandy silt/clay --.--permeability flow boundary Lithologic Types and Corresponding Model Layers and moderate---1 .I FIGURE 7.

PAGE 26

therefore, these units were not specifically included in the model. Layer one thickness values ranged from 15 feet to 75 feet, layer two thickness from 20 feet to 262 feet and layer three thickness from 15 feet to 139 feet. BOUNDARY CONDITIONS The function of boundaries is to impose tn effects of the external regional flow System on th modeled area. Several types of boundary condition are available in MODFLOW including prescribe head and prescribed flux. Constant head boundaries where the head at the boundary remains constant fo the model duration, are one example of a prescribei head boundary. Prescribed flux boundaries are use( when there is a flux which changes with time at thi outer edges of the boundaries. No-flow boundaries are a type of prescribed flux boundary where the flow regime is such that flow across the boundary is not expected to occur. In head-dependent flux boundaries, the flux is dependent on the head in the cell and the head assigned to the external source. Head-dependent fluxes in MODFLOW include general head boundaries, rivers, drains and evapotranspiration. With prescribed head, another type of head-dependent flux boundary, the flux can be as large as needed. A no-flow boundary is implicit along the outer edges and bottom layer of the model. The general head boundary package was used to generate head-dependent flux and prescribed head boundaries. According to McDonald and Harbaugh (1988), a general head boundary consists of a water source outside the model area which supplies or removes water to a model cell at a rate proportional to the head difference between the source and the cell. A horizontal conductance term is also included in the general head flow calculation and its value is initially based on the length, width, sediment thickness and horizontal hydraulic conductivity of the cell (see Figure 8). A dimensionless calibration factor is included when necessary. The Atlantic Ocean borders the entire eastern edge of the model, and Lake Okeechobee borders most of the western edge. These two large water bodies provide a constant source of water which can be considered a head dependent flow boundary. Measured water levels in Lake Okeechobee varied from 11.31 to 14.27 feet NGVD in 1989 and the Atlantic Ocean varied from a low of -0.07 feet NGVD in June to a high of 1.35 feet NGVD in October. The general head package was used to represent these boundaries because of its flexibility to vary heads. In layer one, the boundary cells are in direct contact with the ocean or lake. Accordingly, horizontal conductance values were set large enough to provide an unlimited source/sink of water, thereby acting as a prescribed head boundary. Conductances for these prescribed head cells were calculated using the following formula (see Figure 8 for conceptualization).: KLW *mulitiplier M is where K = layer one hydraulic conductivity (ft/day) r L= layer thickness d W= width of column S M= 1 multiplier= 2,000 (used as a calibration parameter) As previously discussed, flow between the general head and the cell containing it is controlled by the conductance term and head differences. Layers two and three represent fully saturated aquifers and were assumed not to be in direct contact with the ocean and lake; therefore, conductances were calculated based on the transmissivity of the cell. General head conductances were calculated using the following formula (see Figure 8 for conceptualization): TW M (2) where T= transmissivity W= width of cell containing general head and adjoining active cell face M= distance from edge of cell adjacent to water source and center of cell The C-23 canal and the St. Lucie River and Inlet are assumed to act as ground water divides along the northern edge of the model and are, therefore, used as boundaries. In a strict sense, the C-23 canal is not a true divide since it vertically penetrates only a small part of the aquifer. However, observed water levels indicate that the canal is acting as a divide under current non-stressed conditions. Significant stress on the aquifer near the C-23 canal could cause flow under the canal; the model's boundary should be adjusted accordingly if such stresses occur or must be simulated. The C-23 canal is represented by river cells in layer one and by general head cells in layers two and three (those cells directly beneath the 0-23 canal) (see Figure 8). The genera] head cells were used to simulate conditions

PAGE 27

Aa $" $" a i i i a9 I ,a s v I I I I v I I E \\x' I I V .T. C v O O 9 # G r O p C J O v S w pGp O O C7 m r a 3 b n 7 :y w An F3 o Y O N 11 fl X -' E r $ .i d ; 0 c CL f7 U T J Y c O g ou z a v a a m C rj U O C 7 V C 7 O m m O O as v a m r 0 L m c m C9 d C o S 0 0 c L m 7

PAGE 28

outside the model, therefore, head values were matched to water levels on the other side of C-23 in St. Lucie County. Conductances of the general heads are equal to the transmissivity of the cell. The C-23 canal runs most of the length of the northern model boundary except for the six westernmost miles of the Martin/St. Lucie border, and the six miles in the Okeechobee County portion of the north model boundary. There are no specific hydraulic boundaries along this northwest corner of the model. However, water level contour maps indicate that flow is occurring either in or out of the model along this boundary. There is a relict beach ridge just west of the western end of the C-23 canal which causes a ground water gradient into the Martin model. Using statistically generated water level maps, head values along the boundaries were approximated and these approximations were input as general heads. The approximated head value for each cell was used for all three layers and for all stress periods. Further refinements could be made in this area if more data were available. General head conductances for layers two and three were calculated using equation 2, and conductances for layer one, west of the C-23 canal, were calculated as follows: KL W M (3) where K= hydraulic conductivity of cell (ft/day) L= length of face along general head cell and adjoining active cell W = layer one thickness minus five feet M= distance between outside source water level and center of general head cell The five feet subtracted from the layer one thickness number represents a countywide average unsaturated zone thickness. The southern boundary of the model was based on a need to extend far enough into Palm Beach County to insure validity of the model at the Martin/Palm Beach county line. The boundary was located midway between the cones of influence of the Town of Jupiter and Seacoast Utilities wellfields. The southwest portion of the model boundary includes the Corbett Wildlife Management Area where water levels are flat for great distances. Some areas along the boundary do meet the no-flow definition, however, in order to simplify the boundary file by making cell types the same, all southern boundary cells contain a general head source/sink. Using statistically generated water level maps, head values along these boundaries were estimated, and these estimations were input as general heads. The estimated head value fur each cell was used for all three layers and for all stress periods. Constant head cells could also have been used, however, constant head cells do not provide the conductance term which can be used to calibrate the simulated sources and sinks outside the model boundaries. Equation 3 was used for layer one and equation 2 was used for layers two and three to calculate the general head conductance term. Locations of the various boundaries can be found in Figures 9 and 10. HYDRAULIC CHARACTERISTICS The Surficial Aquifer System is heterogeneous and anisotropic as a result of its widely varied composition. The system is composed of sand or sand/shell layers with intermixed thin to fairly continuous limestone/sandstone beds. Hydraulic conductivities in the system estimated from pumping tests range from 25 to 180 ft/day with an average value of 50 ft/day. The system was divided into three hydraulic conductivity zones for modeling purposes: a low permeability zone representing the uppermost fine sand/silt lithology; a zone of intermediate permeability representing the production zone tapped by most wells; and another low permeability zone representing the remainder of the system. Transmissivity/Hydraulic Conductivity MODFLOW requires that each layer of a model be classified as either confined, unconfined or some combination of the two. All three layers of the model are part of an unconfined system, however, MODFLOW only allows one layer be designated as unconfined. For this reason, layer one was defined as unconfined, layer two was defined as confined/ unconfined and layer three was designated as confined (since the entire thickness of layer three will always be completely saturated). These designations determine how heads are calculated in each layer. In an unconfined layer, transmissivity is continually recalculated as a function of hydraulic conductivity and the saturated thickness of the layer. Storage is determined from specific yield. Under the confined/unconfined designation, it is assumed that the majority of the layer will remain saturated throughout the simulation, so transmissivity is not continually recalculated. This layer type requires the input of both a specific yield and a storage coefficient, so that the appropriate storage factor may be used depending on if it is confined or unconfined. In the confined designation,

PAGE 29

1.04.000 1.020.00 1.00000 90.000 9 60.000 MA 4000 T355 739S T405 a 0 T 41 S P 920.000 Q a 0 n Z$ n g F0 '3d N 6C 1 C$ 3d o a 5 Oy S L I 000'010'1 0OW ZQL D001 QO'1 000 096 0000% 00'16 ooz 000'OZ6

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1~G~n~na~ I fl((~~fl T~8S I T40S T36S ~ ~ ~ ~ T3S T0741 S I I I O S d O 7 O 7 3 S, V O O s' e 5 V 0 3) 1 i i OQQIOpQ'I OOUO6SOL O00OOQL 000,09 0001096 000'01.6 -____ S____ -K 1 S orJ S bf S L# L W Q W Q W M W 0 n 1.04Q 000 1 020 000 t OC -960,000 960.000 940,000 020.Od k IC C n G 0 (N WE h Y J 7 C m 'G r_ N 'IA 'V a 6 V-1 -c 7

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transmissivity and storage coefficients are kept constant for the entire simulation. Layer One. MO)FLOW calculates the transmissivity of unconfined aquifers by multiplying the hydraulic conductivity by the saturated thickness of the aquifer. Initial saturated thickness is calculated from the starting head and aquifer bottom data, both of which are required input for an unconfined aquifer. Head changes throughout the simulation result in changes in the calculated transmissivity in an unconfined aquifer. When the simulated head in a cell drops to a level at or below the aquifer bottom elevation, the transmissivity of the cell becomes zero, resulting in the cell "going dry" and becoming inactive for the remainder of the simulation. Little data exist on the hydraulic conductivity of zone 1 (layer one) of the Surficial Aquifer System in Martin County. Originally a single hydraulic conductivity value of 20 feet per day was chosen. When a soils map with differing values of vertical hydraulic conductance was created for another package in MODFLOW, the distribution and range of values seemed reasonable for use as a layer one hydraulic conductivity array. Table 3 lists the various soil types in the model area and the conductivity used for each type. Values range from 3 feet/day in sloughs and river beds to 47 ft/day along the coastal dunes, with a large portion of the county being 12 ft/day. A weighted conductivity value based on the percent of each soil type in the cell was calculated. A contour plot of the conductivity array can be found in Appendix B. There are conceptual problems with this method since soil profiles are generally very shallow and the permeability values reported indicate the rate of downward flow rather than horizontal flow. However, the hydraulic conductivity values that were calculated were in a reasonable range for layer one. According to various hydrogeology texts (Driscoll, 1986; Todd, 1980), hydraulic conductivity in fine to silty sands, similar to layer one in Martin County, ranges from 0.03 to 32 feet/day. The model calibration improved when the soil conductivity array was substituted for the single value. Clay and hardpan layers, which are present, were not discretized into separate layers because of their discontinuous nature but are taken into account in the lower hydraulic conductivity values. Layer Two. The transmissivity grid for layer two was developed by a two-step process. Transmissivity values obtained from numerous pump tests throughout the study area were divided by production zone thickness to obtain hydraulic conductivities. These values were then regiunalized using a kriging interpolation technique which estimates a value for each cell based on the existing information available, and the resulting array was multiplied by another regionalized array of layer thickness values from numerous drilling logs. The resulting array has a range of transmissivity from 440 ft2/day to 26,572 ft2/day See Appendix B for a contour plot of transmissivity. The two-step process was preferred over just regionalizing pump test transmissivities because knowledge of aquifer thickness, which varies significantly, yielded a more accurate regional transmissivity array. Layer Three. No aquifer performance tests specific to layer three were found. Therefore, the transmissivity array for this layer was created by multiplying the layer three thickness array by a constant hydraulic conductance of 20 feet/day. This resulted in transmissivity values between 200 ft2/day to 5,560 ft2/day. After sensitivity runs, better calibration in the area generally east of the Florida Turnpike was made by doubling the transmissivity value. However, in the Tequesta area, the originally calculated tranismissivity calibrated better and was preserved. Contour plots of transmissivity arrays can be found in Appendix B. Storage and Specific Yield A single value of 9.0 X 10-4 was used for storage for layers two and three, based on the average value of pump tests performed in the study area. Repeated model runs at various storage values showed it to be relatively insensitive within the range reported from the pump tests. Specific yield is that percentage of the total volume of water in a saturated rock that will drain by gravity and thus be available to wells. Johnson (1967) compiled specific yield values based on laboratory analysis for elastic sediments ranging from clay to coarse gravel. His findings showed specific yields for sandy clay to coarse sand ranged from 0.03 to 0.35 percent. Specific yield for layer one was set at 0.2 which represents the average value for the mostly fine sediments that comprise layer one. Subsequent testing of different values from 0.18 to 0.22 showed the model to be fairly insensitive within the range tested. Vertical Conductivity There is little information on the vertical hydraulic conductivity of the Surficial Aquifer System in the study area. Todd (1980) states that the

PAGE 32

TABLE 3. SOIL TYPES AND CORRESPONDING VERTICAL HYDRAULIC CONDUCTIVITY AND CAPILLARY FRINGE HEIGHT Value Used in Model Capillary Soil Type Conductivity F i (ft/month) Fringe Height ft/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

PAGE 33

anisotropy ratio for horizontal to vertical conductivity usually falls between 2 and 10 for alluvial deposits but may range upwards of 100 if clay is present. Vertical flow in the model is a function of the vertical leakance (Veont), the cell area and the head difference between layers. Values of Vcont were obtained by using the MODFLOW calculation for vertically adjacent geohydrologic units 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 ratio of 0.1 was assumed for all zones in the aquifer. In the Jensen Beach Peninsula model (Hopkins, 1991), repeated calibration runs resulted in vertical conductance values of approximately a quarter of those estimated using the 0.1 anisotropy figure between layers one and two, apparently due to vertical impedance to flow caused by fine sands and clay layers at the base of layer one. This situation also occurs within this model area and calibration runs indicated a minor improvement in isolated areas in the eastern portion of the county with a lower anisotropy ratio. However, it was difficult to delineate and justify the lower anisotropy areas. Additional research and further refinements to the model on this subject should be addressed in future versions of the model. Clay lenses, which are present, but not well defined in the aquifer, were not represented explicitly in the model since their discontinuous nature gives them a local rather than regional influence. SURFACE WATER INTERACTIONS Canals, rivers and lakes were represented in the model using either the drain, river or general head boundary packages. The general head boundary package was used to represent water bodies along the model boundaries, as previously discussed in the boundary condition section. It was also used to represent the Florida Power and Light (FP&L) reservoir. The river package was used to represent all other controlled canals and those canals with frequent water level data. Uncontrolled canals were represented as drains. The location of river and drain cells in the model can be found in Figure 11. Appendix C summarizes the widths, control structure elevations, bottom elevations and multipliers used for the river and drain reaches. The river package represents each river/canal reach as a source of water outside the aquifer with a conductance to the aquifer based on river/canal length, width or wetted perimeter, sediment thickness and sediment hydraulic conductivity within each model cell. Flow between the river and the aquifer is determined by the head difference existing between the river reach and the model cell containing it and is proportional to the conductance. Heads in the river reaches are set to the river/canal maintained level or measured water level collected by the SFWMD and the USGS. Flow direction may be either from the river reaches to the aquifer or vice versa, depending on the direction of the head gradient. Thus, river cells may serve as either a source or sink of water with respect to the aquifer with both flow volume and direction varying according to the head gradients. The drain package simulates flow in one direction only, from the aquifer to the drain, while both the general head and river packages simulate flow either into or out of the aquifer. The drain conductances are calculated in the same manner as the river and general head conductances. Flow into the drains occurs when the simulated aquifer head is greater than the specified drain elevation. The flow is proportional to the conductance and the difference between the aquifer head and the drain elevation. When the elevation of the drain is greater than the aquifer head, no flow occurs. Drains were used in the model to represent canals where water levels are not maintained at specified heads. The drain elevations were usually set to the control structure elevation. If the structure elevation was lower than the canal bottom elevation or there was no control structure, the canal bottom elevation was used for the drain elevation (see Figure 12). The conductance term is used to represent the stream-aquifer interconnection, which is affected by streambed material. River and drain conductances for a cell were obtained by the following calculation and are illustrated in Figure 12; KL W, multiplier 1' (5) where W = width of reach L= length of reach K= layer one conductivity The 1 foot value represents canal bed thickness. The multiplier was used as a calibrating tool since streambed material data are extremely limited, and was determined from numerous model runs. For river reaches, the multiplier ranged from 0.001 to 0.01, with the Intracoastal and tidal rivers generally

PAGE 34

1 0000 9 vv0 006 qw= 4 m 920.000 TI415 1405 0 ,. o r N 41 b r w ac0rorgI 00009 00O0to aao'o0 I -Am T395 r S950 '1 3. 1020 000 600.088 000'096 I: C 0 C Ou w U. 6OV" Owl=

PAGE 35

Drain Elevation Determination I "" .... Canal Bottom Used Control Structure "Used for Drain Elevation for Drain Elevation Control Structure River/Drain K L W Conductance M Le of Bed Thickness River/Drain Width River and Drain Conceptualization vtty or Dea Materoal r ........................... ........................................' '''' i c FIGURE 12.

PAGE 36

requiring a multiplier of 0.001. The drain reach multipliers ranged from 0.001 to 0.1, with most grove canals requiring a multiplier of 0.01. The length of river and drain reaches was measured from USGS topographic maps, overlain with the model grid. The width of river reaches was determined from USGS maps, permit maps, canal survey maps or "as-built" drawings by the Corps of Engineers. When available, the same sources were used for drain reaches, however, widths for most grove canals were estimated based on discussions with the land owners or their engineering consultant. The Florida Power & Light reservoir is a large water body within the modeled area with stages that fluctuate within a small range. It is an above-ground reservoir; therefore, there is some lithologic restriction to flow between the reservoir and the underlying water table. The general head package was used to simulate the reservoir. Conductance terms were calculated in the same manner as those for river bottom conductances (Equation 5). The multiplier was varied until modeled leakage values were similar to values reported by FP&L. The FP&L reservoir calibrated conductance calculation is as follows: KL W.00o 2' (6) where, K= layer one horizontal conductivity for that cell L= row length W= column width hydraulic RECHARGE Rainfall recharges the Surficial Aquifer System over its entire area. Average annual rainfall ranges from 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 through October. Average rainfall during the dry season, November through April, is approximately 12 to 16 inches. Wet and dry season durations may vary from year to year. For the modeled time period, annual rainfall (amounts observed in any consecutive 12-month period) steadily declined from normal to record below-normal amounts from August 1988 until August 1989 after which it moderated but stayed below normal well into 1990 (Trimble, et al., 1990). For 1989, average annual rainfall from stations in the study area was 44 inches, ranging from 24 to 57 inches for individual stations. Wet seast,n rainfall ranged from 12 to 43 inches, averaging 31 inches and dry season rainfall amounts ranged from 9 to 21 inches, averaging 14 inches. Rainfall events in south Florida are often localized, particularly in the summer months when convective thunderstorms are common. Frequently, these events are very intense and of short duration. In winter months, however, frontal systems and occasional tropical depressions (hurricanes) provide more evenly distributed rainfall over the study area. Because of the variable nature of most rain events. there are an inadequate number of rain stations to provide a completely accurate distribution of rainfall. Daily rainfall data collected from 41 stations were used in creating the recharge arrays. Appendix D includes information on each station as well as a station location map. Recharge is calculated as a function of interception, depression storage loss, and surface drainage. The following summarizes the preprocessing steps taken to create the recharge arrays: 1) assembled daily rainfall totals from numerous stations throughout the study area collected by federal 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 and summed for each month as depression storage; 3) the monthly depression storage is subtracted from the monthly total rainfall and the remaining recharge was contoured using the inverse distance method to determine a value for each model cell; 4) the resulting arrays were further reduced to remove interception water based on land use type, runoff to surface drainage based on slope, and hydraulic conductivity of the soil (see Figure 13 for land use types in the model area; the calculations for interception and runoff can be found in Appendix D); 5) added to the final recharge arrays was 50 percent of the irrigation water withdrawn by flood irrigated agricultural operations in the appropriate cells.

PAGE 37

_ __~_

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For a detailed discussion of the recharge calculations, please refer to Appendix D. The flood irrigation recharge figure is based on assumptions made in the SFWMD Water Use Permit Information Manual (SFWMD, 1985) that in flood irrigated projects 50 percent of the water applied is used by the crop. To be consistent, all irrigation projects that are not 100 percent efficient should return some water as recharge to the first layer of the model. Due to current limitations, it was too difficult to calculate the contribution to each model cell for each irrigation project; therefore, only the flood irrigated projects were included. Figure 14 illustrates the model cells to which irrigation recharge was added. The net recharge, after all subtractions from rainfall have been made, for a single steady state month is shown in Figure 15. Because of the number of variables involved in determining what portion of rainfall would actually recharge the aquifer, the ratio of rainfall to recharge varies widely throughout the county (Figure 16). However, a check of the ratio for broad land use types in the month with the least (February) and most (August) rainfall in 1989 provides some information. In February, the average calculated rainfall/recharge ratio for urban areas was 41 percent; for agricultural areas, 43 percent; for forested areas, 51 percent; and for wetland areas, 48 percent. In August, the ratios were 53 percent for urban, 59 percent for agricultural, 62 percent for forested and 62 percent of rainfall for wetlands. As mentioned previously, these are averages and the ratio for any given cell and land use type ranges from zero to 98 percent of rainfall based on the many variables included in the determination. The recharge term used in MODFLOW represents water that actually reaches the aquifer. In areas where there is a significant unsaturated zone above the water table, the above recharge calculations become inaccurate. An additional portion of the calculated recharge never reaches the aquifer because of the large soil storage capacity in the unsaturated zone. Dune area plants will satisfy their water needs from the soil water and never use water from the aquifer itself. Therefore, in cells where there was 16 to 20 feet of unsaturated soil, recharge to the aquifer was reduced by half, and in cells with unsaturated zones of 20 feet or more, recharge was reduced to zero, which improved calibration. The recharge reduction figures, based on thickness of the unsaturated zone, were not based on specific scientific data, but on calibration results. A scientific approach for more exact determination of the recharge prevented from reaching the aquifer by a significant unsaturated zone above should be examined. Figure 14 illustrates the model cells in which recharge was altered. EVAPOTRANSPIRATION Evapotranspiration (ET), water loss through evaporation and plant transpiration, is the largest mechanism for ground water loss from the system. ET is a complicated process controlled primarily by weather, vegetation, soils, and water availability. There are numerous methods available to estimate ET using different combinations of factors. The modified Blaney-Criddle method was used in this model to estimate the potential evapotranspiration rate. The modified Blaney-Criddle method is based on the principle that ET is proportional to the product of day length percentage and mean air temperature and incorporates crop type as it relates to the ET estimate for grass (Jensen, 1980). Water loss from the saturated ground water regime through direct evaporation and through transpiration from the saturated zone by plants is simulated in the model by the Evapotranspiration (ET) Package of MODFLOW. The following assumptions are applied (McDonald and Harbaugh, 1988): 1) When the water table is at or above a specified elevation, termed "ET surface", ET loss from the water table occurs at a specified maximum rate. 2) When the water table elevation drops below a specified value, termed the "extinction depth" or "root zone", ET from the water table ceases. 3) ET from the aquifer varies linearly between the above limits. The evapotranspiration from the unsaturated zone is not considered at this point but modifications to the code are currently under development at SFWMD. The ET surface elevation is represented in the model by the average land surface elevation in each cell minus the capillary zone height for that cell (see Figure 17 for conceptualization), Land surface values were taken from USGS 7.5 minute topographic quadrangle maps. Because of the model cell sizes, there is only one elevation for each 2,000 by 2,000 foot area and it represents the average elevation within that cell. In most areas, there was

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only a one or two foot difference in elevation within a cell. However, in some areas, the elevations changed as much as 20 feet within a cell and the average value will not represent conditions throughout the entire cell. The consequences of land surface averaging is discussed in the calibration section. The ET surface was then altered 2.5 feet for specific cells during the calibration process. Capillary rise is a function of soil grain size and can vary from 0.38 centimeters in a coarse gravel to 3 meters in clay (Fetter, 1980). Noting the sandy, clayey soils in the modeled area, it was assumed that a significant volume of water would be lost by ET in the capillary fringe. Since MODFLOW does not address ET that occurs when the water table drops below the root zone, capillary fringe ET was approximated by reducing the original ET surface (land surface) by an amount equal to the capillary fringe height. The height (Table 3) was determined by soil type, and an array of capillary fringe heights was created. To be physically accurate, the capillary zone 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 need to be incorporated in the MODFLOW program. A simplifying assumption was adopted for calculation purposes by moving the ET "window" down by an amount equal to the capillary zone height. Where water bodies were present, the free water surface evapotranspiration rate was used. For all other areas, the maximum ET rate was estimated using the modified Blaney-Criddle equation. The basic form of the equation is: P t U=kk mm to100 where, U is the crop ET for a given month, in inches per day from layer 1, k is a consumptive use coefficient which varies according to the crop, type and growth stage, kt is a climatic coefficient which is related to the mean air temperature; kt = .0173t -.314, where t is Fahrenheit temperature, Pm is the percent of daytime hours of the year which occurred during the month, tm is the mean temperature for the month, in degrees Fahrenheit. The consumptive use coefficient is defined: where, kc is a coefficient reflecting the growth state of the crop (Table D-4, Appendix D), and kf is a coefficient reflecting the fraction of land surface which is covered with a specific type of vegetation (also Table D-4) it varies between 0.1 and 1.0. Temperature data was used from stations in Stuart, Jupiter and Indiantown. Crop coefficients (ke) were either taken directly from or inferred from values presented in SFWMD's Permit Information Manual Volume III (SFWMD, 1985). Values of kf for urban land uses were determined by examination of surface water permit data for ratios of pervious to impervious area. Extinction depth physically represents the depth to which the roots of plants extend below land surface and is determined in MODFLOW as the depth of the water table below the ET surface elevation beyond which evapotranspiration ceases. Extinction depths in the model are related to land use and are based on estimated root depth for various kinds of vegetation supplied by the District's Planning Department (Teets, 1990, personal communication). A table with values used can be found in Appendix D. The MODFLOW evapotranspiration package removes water from the aquifer up to the maximum ET rate specified. If the aquifer head is below the root zone extinction depth, the model does not remove any ET. In groves, for example, drainage canals are designed to keep the root zone drained. Consequently, the model does not remove any water from the aquifer to ET in most grove canals. This is a valid approximation since the water removed by evapotranspiration in a grove is mostly provided by drip irrigation rather than from the aquifer itself. In dune areas also, the aquifer head is significantly lower than the root zone extinction depth, so no ET water is removed from the aquifer. However, as discussed above in the recharge section, these dune plants do transpire using recharge water retained as soil moisture which then never reaches the aquifer. These are all examples of situations which preclude the use of reported evaporation data without significant alteration. It becomes apparent that MODFLOW currently is not capable of a full accounting of all recharge and evapotranspiration taking place and users should be aware of the k =k k

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limitations and adjustments that should be made to input data sets. GROUND WATER USE Water use figures for the model were determined using data from water use permits issued by the SFWMD. Individual water use permits are required if the average daily water use equals or exceeds 100,000 gallons per day (gpd). An individual water use permit is also required of smaller uses (average daily use exceeding 10,000 gpd) in Reduced Threshold Areas (RTA). The Stuart and Lighthouse Point (north of Palm City) areas are designated RTA's (Figure 2). The SFWMD also issues general water use permits to all uses less than 100,000 gallons per day, with the exception of single family homes, duplexes, and water used strictly for fire-fighting (SFWMD, 1985). General water use permits were included in the determination of water use for the model because the total amount covered in general permits could be significant considering the hydraulic conductivity of the aquifer. All legal uses of water, no matter how small, are important from a management standpoint because they are protected by the District's water use rules from adverse impacts caused by other water users. Therefore, impacts to the smaller users can affect larger users, requiring reduced withdrawals or mitigation of the adverse impacts. This can be of critical importance during the management of competing uses. The permits were used to determine withdrawal facilities, water use type, project size and project location. The permit allocation was not used in the model, as it does not necessarily equal the actual use. For example, in public water supply permits, the allocation covers a ten year period during which pumpage increases gradually with increasing population. In agricultural areas, some facilities and planted acreage may be proposed and not installed during the model period. Therefore, wherever possible, actual use was input to the model, and all estimated uses were based only on existing facilities and planted acreage. Agricultural Agricultural water use accounts for 27 percent of the ground water well withdrawals in the model. This category includes all farming, golf, recreational, landscaping and nursery uses. Records of water withdrawn for agricultural uses are submitted to the SFWMD for a small percentage of the projects. Where these records were available, the information was input directly into the model. Where sufficient information was not available, irrigation application rates were estimated. The irrigation water requirements of different crops was estimated using a method described by the U.S. Soil Conservation Service (USDA, 1970). This method uses the modified Blaney-Criddle formula to estimate the water requirements of various crops. Crop type, soil type, air temperature, daylight hours, effective rainfall, and irrigation system efficiency are used to calculate the irrigation requirements of different crops found throughout the modeled area. Data on all agricultural water uses with individual and general water use permits was assembled into a spreadsheet. This information included crop types, acreage, irrigation system data, well information, and soil types. Precipitation data from the closest station (Stuart, Indiantown or Jupiter) was used to determine effective rainfall. The irrigation requirements for each permitted use were estimated for each month of the calibration period (January 1989 through December 1989). The monthly irrigation requirement for each permitted use was distributed among the permitted withdrawal facilities in proportion to their pump capacities. Individual wells were then assigned to the proper model cell. Fourteen landscape irrigation permits that report pumpage to the SFWMD were compared to the modified Blaney-Criddle estimates for each project. On average, Blaney-Criddle overestimated irrigation requirements in April through August and underestimated in October through March, estimating only half of what was actually being pumped by users in January and February. The Blaney-Criddle supplemental crop requirements were adjusted according to these findings (Table 4) and these adjusted requirements were used for all landscape irrigation uses where actual pumpage was not available. Several crop types were either not included or only reported pumpages were used, rather than Blaney-Criddle estimates. Withdrawals from surface water sources were not considered. Pasture allocations were not included because they are generally irrigated from surface water sources and since runoff water is usually held in pasture ditches by control structures, supplemental water is rarely needed. The Blaney-Criddle formula is difficult to use for nursery irrigation requirements, therefore, all nurseries were contacted and actual irrigation practices were used to estimate withdrawals. The one large citrus grove in Martin County which uses surficial aquifer water for irrigation maintains pumpage records, which were incorporated in the

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TABLE 4. SUPPLEMENTAL IRRIGATION WATER RATES USED TO CALCULATE IRRIGATION 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

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model. Almost all other groves primarily use surface water with Floridan Aquifer augmentation in a few groves. All small vegetable growers were also contacted and actual irrigation practices were used to estimate irrigation withdrawals. For uses not currently permitted by the SFWM D but visible on USGS quad maps, the owners were contacted for facility information which was then incorporated into the model. Agricultural water use data is presented in Appendix E. Figures 18 and 19 show the distribution of cells with well withdrawals for layers one and two, respectively. Layer three did not contain any well withdrawals. Pu blic Supply Public water supply (PWS) withdrawals account for 24 percent of the total modeled ground water well withdrawals. Ground water withdrawals for PWS were obtained from pumpage information routinely furnished to the Florida Department of Environmental Regulation (FDER) by the water utilities. These reports provide total raw water pumpage for the entire wellfield. Since many wellfields in Martin County are distributed over several model cells, individual well discharges were used whenever possible. If there were multiple wells in a wellfield and individual well pumpages were not available, total pumpage was divided among the wells based on the individual well capacities of routinely active wells. Model cells containing public supply withdrawals are shown in Figure 20. The location of PWS wells used in the model, along with information on withdrawals, can be found in Appendix E. Domestic Self-Supply Domestic self supply accounts for 45 percent of modeled ground water well withdrawals. This withdrawal type covers all non-potable (outdoor) and potable (indoor) water use not supplied by a utility. While potable uses are fairly well documented, there is a lack of data in the area of non-potable water use, because the majority of non-potable water is self supplied and pumpage records are not maintained for the majority of private wells being used for irrigation (Opalat, 1985). In developing an urban water demand model for Martin County, Opalat, 1985, describes a method of determining residential non-potable demand. The methodology involves developing figures for each land use type taking into consideration allowable unit density, percentage of units having automatic irrigation systems, and irrigation application rates and frequency. Model cells containing urban land use types, and therefore having the potential for domestic self-supply withdrawals, are shown in Figure 21. Table 5 summarizes the assumptions made for each urban land use type. Land use information collected in 1986-1988 was used and no adjustments for partial buildout were made. Once the locations of different urban land use types were determined, the areas were further subdivided into large utility supplied, small utility supplied and self supplied (Figure 21). Types of water use were broken into three categories: irrigation by automatic sprinkler system, irrigation by hand watering (garden hose), and indoor water use. In areas where water is utility supplied, any hand watering was assumed to come from the utility water. Model results indicate that potable demand breaks down to 32 percent from large utilities, three percent from small utilities and 64 percent self supplied. A figure of 120 gallons per capita per day was used in the potable demand estimates. This figure is based on water use information published in the 1983 City/County Data Book (USDC, 1983). It was assumed that all non-potable water use not supplied by a utility came from ground water wells rather than canals. This assumption is based on the fact that there are very few fresh water canals in urban areas of Martin County and coastal Palm Beach County. The Jupiter Farms area in Palm Beach County does have a fresh water canal system but all the houses have wells for drinking water so it was assumed that irrigation water would also come from these wells. In addition, the lots are large in Jupiter Farms and houses may be a considerable distance from the canals. The irrigation figures resulting from the land use method then were compared to irrigation demand using the modified Blaney-Criddle calculation for the same acreage of grass. The land use method estimated water use to be 1.6 times what Blaney-Criddle determined to be necessary. However, as discussed earlier in the agricultural water use section, reported figures for grass irrigation indicate that Blaney-Criddle is not entirely accurate. Reported actual use on an annual basis for large-scale landscape irrigation was found to be an average of 1.3 times what Blaney-Criddle calculated. This would indicate that the land use method of determining self-supply is acceptable.

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TABLE 5. DOMESTIC SELF-SUPPLY ESTIMATE PARAMETERS Land Use Type Single Low Acres Irrig .5 Sprinkl Units .5 Capita/Acre .84 D.U./Acre .35 Single Med .23 .75 8.4 3.5 Single High .11 .50 19.2 8 Multi-family Mobile Homes .03 .02 .75 .25 36 19.2 15 8 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 with sprinklers acres irrigated per unit 135762 gallons/acre/month Hand watering: Acres of land use type # of dwelling units (1 -% of units with sprinkler systems) .5 acres irrigated per unit 67881 gal/acre/month

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Other Ground Water Uses Most of the other uses of ground water in Martin County are either industrial or mining-dewatering. The mining-dewatering uses are usually short-term uses which generally require on-site impoundment of withdrawn water. The only consumptive use in these operations is water lost to evaporation, which is insignificant for a regional model with a coarse grid. Therefore, mining-dewatering uses were not simulated in the model There are several industrial use of ground water in Martin County, including Florida Power and Light, Pratt and Whitney, and Loxahatchee River Environmental Control District. Permitted industrial ground water use in Martin County totals 136 million gallons per month, or four percent of all modeled ground water well withdrawals.

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CALIBRATION Calibration is accomplished by comparing the response of the actual physical system with mathematical models calculated response to the same conditions. If they agree, the model is assumed to be calibrated. If not, various parameters in the mathematical model are altered until the model is in reasonable agreement with the physical system. The Martin County model was calibrated to both steady state and transient conditions. Initial steady state runs served to make the first adjustments to the aquifer parameters used in the model. Once the model was able to run without errors, the adjusted aquifer parameter data sets then were used in the transient calibration runs, where they were refined further. After some refinement, the data sets from the transient calibration were used in the steady state model, and sensitivity analysis runs were made. Information from these runs was input back into the transient model and further refinements were made. Finally, the steady state model was re-run using the data sets from the latest transient calibration to obtain a final steady state run. The calibration period was January 1989 through December 1989. This period was chosen because it is the most recent period represented by ample water level observations. Locations of the monitor wells in each layer used in the calibration process are shown in Figures 22 through 25. The strongly implicit procedure (SIP) was the solution method used in the calibration process. Overall, it resulted in a stable solution in an average of 13 iterations. The number of iterations was near the initially set limit of 50 until the "prescribed head" cells, with their large conductance values, were applied to the Lake Okeechobee and Atlantic Ocean layer one boundaries. TRANSIENT CALIBRATION Method Following the initial steady state calibration run, a series of transient runs were made to calibrate the model to observed water levels. The transient runs comprised 12 stress periods of one month each. Each stress period contained four time steps. Starting heads in each layer were calculated from water level data obtained from USGS monitor wells in January 1989, the first month water level data were collected from a new expanded Martin County network. These data, along with surface water stage data for the same time period, were regionalized using a kriging interpolation technique, which estimated a head value for every cell based on the available data. Further refinements to these arrays were made during calibration runs. Figures 26 and 27 are contour plots of the starting head arrays. The intent was to calibrate so that agreement between observed water levels in monitor wells and simulated water levels in the cells which represent the location of those wells were within one foot of each other and that the seasonal water level fluctuation pattern would be imitated by the model. Hydrographs comparing observed and simulated water levels in cells that correspond to the locations of water level monitor wells were generated. These were used to aid in interpretation of the numerous model runs, particularly how the simulated water levels changed over time in response to varying stresses. These hydrographs are presented in Appendix F. Agreement of simulated water levels with observed water levels can be affected by the following conditions: 1. MODFLOW simulates well withdrawals from a cell as a single stress located at the node, or center of the cell. In reality, the area represented by a cell may contain many pumping wells. This situation is common throughout the Martin County model, due to the size of the cells. Combining all the well withdrawals located within a cell and locating the total withdrawal at the center of the cell is not a completely accurate simulation. In addition, the computed head in a cell represents the average water level over a model cell. If actual levels vary significantly across the cell, monitor well levels may not closely match the computed levels. In areas of higher ground water gradients, such as those caused by intensive well withdrawals or where wells are located near surface water bodies causing strong natural gradients, water levels throughout a cell can vary significantly from the average. Cell-wide averaging effects are

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evident in comparing observed and computed levels in the cells containing monitor wells in all the major wellfields. 2. The model was run using one month stress periods, consequently the model water levels reflect the average effect of stresses that occurred throughout the month. However, a monitor well will reflect the most recent events affecting water levels around the well (canal stage changes, well withdrawals, rainfall events) just before the water level reading was taken. Also, monitor well readings were usually collected near the end of the month but could have been take anytime in the latter half of the month. These situations can cause some discrepancy between the model and observation well levels used to check calibration. 3. Most of the rainfall in the study area occurs as intense short term events over relatively small areas. In many cases, ground water levels respond almost immediately to these events. A local rainstorm during any of the measuring periods could result in water level increases in selected wells reflecting a local phenomena rather than a regional trend. Also, some of the observation wells are located a significant distance from a rainfall station, so an intense rainfall event causing water level fluctuations at a given well may not be represented in the rainfall data. 4, Inspection of aerial photography reveals that Martin County has a large network of canals, ranging in width from several feet to hundreds of feet. Only canals with some data on depths, configurations and control elevations were included in the model. In general, these were grove canals, some pasture canals and the SFWMD canals. This omits many smaller roadside drainage systems. An observation well near a canal not included in the model could then indicate the model is not accurate in that area. And, as mentioned before, if the monitor well is in the same cell as the canal reach, cell-wide averaging effects can sometimes make it impossible to calibrate the model to the observation well water level. Because all the layers of the model are basically under atmospheric conditions and there are no significant confining units between layers, modeled water levels in the three layers were generally the same by the end of each one month stress period. Any changes in the evapotranspiration, recharge or river/drain packages affected all three layers similarly Therefore, calibration discussions will not address individual layers, but the model as a whole. Most of the calibration changes were made in one of three areas; 1) river/drain conductance, 2) starting head levels, and/or 3) evapotranspiration surface. After the initial runs, two observed versus modeled hydrograph patterns became apparent. Either the model initial value was much higher or lower than the observation well and the well was never able to recover from that poor starting point, or the initial level was accurate but as the model progressed the modeled water level became too high, starting to come down by the end of the calibration period. In the former situation, adjustments to the starting head file usually corrected the problem which was probably caused by the statistical interpolation 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 not particularly successful. Eventually it was discovered that adjustments in the evapotranspiration (ET) surface would correct the problem. If the ET surface is lowered, the ET extinction point is then deeper and the ET rate becomes larger at the same depth which results in more ET which removes the water that was "mounding". The opposite situation can be affected by raising the ET surface to correct situations where the modeled level is too low. Changes of one or two feet were usually sufficient to cause the model to calibrate. This method, while effective, is tedious and can only be changed and verified on a local level. In cells without a monitor well, which is the majority of cells, this fine tuning is not possible. The ET surface was based on land surface elevations which were determined from USGS topographic quadrangles which were overlain with the model grid. Although some grid cells had elevation changes of 20 feet or more, it was necessary to average the elevation for model input. The elevation contour lines are at five foot intervals, generally leaving a 2.5 feet range for adjustment when calibrating the ET surface of the model. In the areas where elevations change rapidly, the model would be more accurate with a smaller cell size. In wetlands areas, modeled water levels were too low and using the above method would have resulted in an evapotranspiration surface well above land surface. Therefore, coefficients used in creating the maximum evapotranspiration rate array were altered until the resulting array, when used in the model, led to calibration with observed water levels.

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The other parameter which measurably affected water levels was river and drain conductances. There are many wells, in the modeled area, near large surface water sources. The model was run several times using different river and drain conductance multipliers and checking calibration of nearby wells. Reaches which calibrated well at certain multipliers were noted and finally the river and drain files were modified to reflect the best multiplier for each reach. The Loxahatchee River changes from drain reaches upstream to river reaches in the brackish/tidal areas. The conductances are significantly different between the river and drain sections. The model documentation (McDonald & Harbaugh, 1988) states that the conductance term is best used as a calibration parameter and does not necessarily reflect a natural condition. Apparently, because of the way the model handles flow in and/or out of river versus drain reaches, the conductance values that resulted in a good calibration are different for the two types. Results Agreement of one foot or less between observed water levels and simulated water levels in cells which represent the location of those wells, for at least 75 percent of the stress periods was the calibration criteria. For this model that means that for nine out of the twelve months, modeled water levels had to be within a foot of the observed level. The wells were broken into three calibration categories: 1) wells that met the calibration criteria, 2) wells that did not meet the criteria but the reason for 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 6 presents the current status of observation wells used in the transient model calibration. Wells categorized as "explainable" did not meet calibration criteria but other influences, such as those previously discussed, prevented a better apparent calibration. In layer one, wells M-1046, M-1083, and M-1265 may be affected by ET parameters; wells M-1262, M-1263, and M-1270 may be affected by drain cells; and wells M-1048, M-1081, M-1232, M-1256, M-1269, M-1274, PB-1520, Pipers Landing well 9A, and PB-927 have no obvious starting point from which to seek a better calibration. In layer two, wells M-1086 (ET problems), 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 and probably indicate areas where more work is needed on the model. Non-calibrated wells in layer three are M-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 average difference between observed and modeled water levels over the entire transient calibration period for each monitor well. This map gives a general indication of model calibration; however, if the model water level is much higher than observed during one stress period and then equally too low at another time, they would, of course, cancel themselves out, resulting in a small average difference. But if a well or group of wells is consistently high or low, this would show up and give guidance on which areas need 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 #= number of observation wells %= percentage of observation wells in the respective layer

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t.O4Q,000 1,020.000 1 OQ0C 90.000 9M. 000 9 90oo 133 7395 T403 1 415 000p0%' ooo-620-L D00'WO' 0W0096S 0 96 oo 920.000 o N w 0 R W 2 CCn

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f3n5 Z LJ O m w 7 Ld ix i LL) Ow Z LJ Ln aQp J ZLa7 p(AQ2 S K 1 5651 5 n1

PAGE 65

STEADY STATE CALIBRATION Method "Steady state" can be viewed as an average condition achieved over a long period of time, and assumes that no major changes in stress rates occur during that time. When the stresses that drive ground water flow change very slowly in time relative to the rate of change within the aquifer system, steady state assumptions are justified. In many cases, however, the steady state condition is hypothetical due to the artificially rapid changes applied to the aquifer system. A pre-development condition for Martin County was present earlier in this century, but little or no data exists that could be used to reproduce it. At the present time, the aquifer system is in a dynamic transient process, but on a monthly basis behaves in a "quasi-steady-state" manner. Ideally, the steady state runs would have been calibrated using predevelopment data whereby disturbances to the steady state condition would not exist. Average values of recharge, evapotranspiration, pumpage, and surface water stage elevations were used, calculated from the monthly values for 1989. January 1989 water levels were used for the starting head array. The model was run for one stress period broken into twelve 30-day time steps. The resulting modeled water levels (Figures 31, 32 and 33) represent an average 1989 condition and are best used for sensitivity analysis and differences between predictive scenarios rather than to determine specific water level information for a given time period. Results The steady state calibrations were based on the assumption that the ground water levels during the calibration period were fluctuating around a steady state condition as a result of seasonal variations in rainfall, pumpage, evapotranspiration and canal levels. Further, the average measured ground water levels during the period were assumed to approximate steady state levels under average 1989 conditions. Thus, the steady state calibrations were made based on comparison of simulated water levels under 1989 recharge/discharge conditions versus the measured water levels in surveyed wells during the calibration period. A well was considered calibrated if the modeled water level fell within the minimum to maximum water level range for that well or no more than 0.1 feet outside the range for the calibration period. Figures 34a-d illustrate the differences between the simulated steady state water levels and the average measured water levels in these wells during the calibration period. Differences between the average measured levels and the minimum and maximum measured levels are shown in the same figures. The wells were broken into three calibration categories: 1) wells that met the calibration criteria, 2) wells that did not meet the criteria but the reason for being outside the range is explainable, and 3) wells that did not meet criteria indicating an area of the model that needs further refinement. There is a discussion in the transient calibration section on the different situations that can influence model results and make an observation well appear uncalibrated. Table 7 gives the breakdown of the calibration results for the steady state model. Most of the uncalibrated wells which indicate areas needing work, also fell into the same category in the transient calibration results. The following wells in layer one did not meet calibration criteria, indicating areas 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 # = number of observation wells %= percentage of observation wells in the respective layer

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W j r d, 3 c a =' o Lwj U? sn.s 000'M'I 000'kOl OOD'000'L 0001026 000'0% 1640.400 1.0]0.000 1.DMOOD 960.000 960.000 940 00 276.060 T36S T 39s 7 40S T 41 S S 9 oe $ c rc 0 h O W G' I a I WFF O O u a u u n o a n 6 O R OOO'W6 00010L6

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1000!m 00p'OYO'i 000'OZO'1 IA40.OW 1.omom i ommo 960000 "0000 640A00 920000 i T30S i T 39s i T405 T 41 s 8 m r O 0 m r u e 0: Q S ri r W ^ O N r 4 K O u o r ¢ C W h N OI' O 9 s 5 d .Fi 00 W6 !1 P J m d afrOr U Z 50 1 000'000'& 000'088 000'098

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LEGEND T Range of Measured Wat rL eaI Simulated Steady Cir. I ... FIGURE 34a. Steady-State Calibration Residuals from Average Measured Water Levels

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LEGEND I Range of Measured Water L.ols SSlimulated Steady State Leel OBSERVATION WELL FIGURE 34b. Steady-State Calibration Residuals from Average Measured Water Levels 4.00 3.50 3.00 2.50 2.00 i.00 0.50 0 -0.50 -1.00 -1.50 -2.00 -2.50 -100 -300 -2.50 -2.00 4.00 3.50 3.00 2.50 2.00 .50 1.00 0 -0.50 -1.00 -1.50 -2.00 -2.50 -100 -300 -2.50 -2.00

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OBSERVATION ELL FIGURE 34c. Steady-State Calibration Residuals from Average Measured Water Levels 60 4.00 3.50 3.00 2.SO 2.00 1.50 1.00 0.50 0 -0.50 -1.00 -1.50 -2.00 -2.50 -100 -350 -300 -250 7.50 7.00 4.50 4.00 5.50 5.00 4.50 4.00 3.50 3.00 2.50 2.00 1.50 0.50 0 -1.00 -1.10 -2.00 -2.50 -100 -13.50 -100 -2.tC

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550 5.00 4.50 400 3r 2.50 2.00 o 0 S-1.00 S-1.50 -100 -2.50 -2.DD 600 3.60 4.50 4.00 IO 100 250 2.00 -1.50 100 -2.50 -2-0 -G50 -1.00 -1.50 -20 -2.50 -2.00 OBSERVATION WELL FIGURE 34d. Steady-State Calibration Residuals from Average Measured Water Levels 61 in

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M1232, LOX. R4, PB-1520 and PB-927. In layer two the uncalibrated wells are M-1010, M-1055, M-1161 M-1253, PB-720 and T-4 (Tequesta). For layer three they are wells M-1235 and Pipers Landing wells and 10. Budget and Flows Layer One Figure 35 shows the direction and magnitude of simulated horizontal flow in layer one. Each arrow represents the flow from an individual cell. The majority of the larger flow vectors are associated with intensive ground water use or interactions with surface water bodies. The flow vectors north of Indiantown represent flow from a topographic high (the Osceola Plain), steeply declining and then intercepting grove canals which maintain water levels lower than land surface. Flow vectors are not shown in the Okeechobee portion of the model due to graphic problems associated with expanded grid cells. An analysis of the volumetric budget for layer one is shown in Figure 36. The majority of flow into this layer (86 percent) is derived from recharge (rainfall), 10 percent is upward leakage from layer two, one percent is river leakage, and three percent is from the general and "prescribed" head cells, representing flow from outside the model, mainly from St. Lucie and Okeechobee counties and Lake Okeechobee. Of the total flow out of layer one, 63 percent is to evapotranspiration, 19 percent is leakage to layer two, less than one percent is agricultural well pumpage, six percent is river leakage, 11 percent is into drains and the remaining one percent is flow to the general and "prescribed" head cells, representing flow out of the modeled area, mainly to the Atlantic Ocean and Palm Beach County. Layer Two Figure 37 shows the magnitude and direction of simulated horizontal flow in layer two. Most of the larger flow vectors are associated with intensive ground water use, for example the Jupiter and Hobe Sound wellfields. Figure 38 is a representation of the simulated vertical flow between layer two and the overlying layer. Upward flow 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 for layer two. Approximately 82 percent of the total inflow to this layer is recharge from layer one, 16 percent is inflow from layer three, two percent is from the general head cells, and one percent is recharge (rainfall) in cells where the model determined that the vertically adjacent cell in layer one was inactive. The flow from the general head cells represents flow into the modeled area from all boundaries. Of the total outflows, 45 percent is upward leakage to the water table aquifer, 37 percent is to wells, 16 percent is downward leakage to layer three, and two percent is to the general head cells. Layer Three Figure 40 shows the magnitude and direction of simulated horizontal flow in layer three. The larger flow vectors are associated with intensive ground water withdrawals associated with the Jupiter and Hobe Sound wellfields. Figure 41 illustrates the simulated leakage between layers two and three. Most of the flow is upward to recharge layer two and large upward flow vectors indicated intensive withdrawals from layer two, for example in Jupiter. The volumetric budget for layer three is illustrated in Figure 42. Almost all of the inflow to layer three (97 percent) is recharge from above. The remaining three percent comes from the general head cells. Of the total outflow, 95 percent is upward leakage to layer two and five percent is to general head cells. A combined steady state volumetric budget for all of the modeled area is presented in Figure 43 and Table 8. Total inflow consists of 95 percent recharge (rainfall), four percent flow from general head boundaries (flow from outside the modeled area), and one percent from river leakage. Total outflow consists of 70 percent evapotranspiration, nine percent to wells, one percent to general head boundaries (flow out of the modeled area), and 19 percent discharge to surface water bodies (12 percent to drains and seven percent to rivers).

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1 -.I aooo i sot A s t t ooo'oa6 0O0'0h0'L 0O0'0LdL OWb W'L woogB 000'096 OO0'O" -No "C ooo 960 000 2440= 920,000 T39S I 939E T4OS 1 141 S G7 a 0 z o U II o o rrkk C V LL F+ I 4 Z n C C I sat

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1 -000 1 020 000 t 000.000 960.000 000.0" 960.000 944000 920 000 1 T 41 S T38S 1 T39S T 40 S 1 O alely aG ,c sv. .." "11 f1 rrY a. i C r f".. /v x e. n f// -NQI 1. 1l sal el.b --. Y' '1 J Lr' f U } 69 aS ... ,174 /at f4 .o IA I "dr frrr, 1, '" CJ 338 L C I F ,I, Eve.V fl 4 T r l a 6 W i h d C LLJ I 9 t" 4 C ooo"o s + k 2OY I 12c I sacs 000'Of0"t 000.&O't DOO 000'l 000646

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I -oxx 1 2D .OM A 0p SOrl y S If 1 9 000096 000'0.6 a0a'aa1 000'01r0't 000'OZO't Dxa'=% 00x'046 1.000.000 SG0.000 960.000 040J= T !6 S 7 34 S r4as' 1 41 S L r 00 aao o 11 .W9 o" .P' Oa )J O o a D O Oo --4 wp e aCo o Via, ...e -.tee ..... a -..,.: .... ...fie :xx, .... '::. ." ...5 f. n m W C Y Q J W W C I i

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o o 0 o Ul) o N -I -o 0 0 m C a L o L 0 a. 1O 2o v a c 0 .5 C c 0 LO N

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1.640.000 1.020,000 ~ a~c S.0 6.0 4&0 2.0 7385 131 1405 14153 d' R 6 g 4 CN § O C I ~ f IW. tOS £9 S liL 000'01r0t 000O0L' 000'001 000'066 000'Dfl 000'0/ 000'O&5 68 w ft ft ft W ft HI 1.000.000 SM.= 9W.000 Swim 920,000 a ft ft 4 a r q 9 r 'c N F n -d Y) 4.' W 0 a) 0. U.) 0n 0L 'U 4V+ ca L a0 Wl 0D _W 0L

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C: Q _J a a ++ to a.. n r u'E M L IQJ J N L J C 41 C7 43 co 3 0 L d 0 C C 69

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v a. c v a 0 0 0M 0 0 0 0 -o 0 0 C 0 0 C c m -i -7 01 -a a, ti C

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I \ I I X X X 0 0 I I I I I I r 0 r 0 -o a v 0 IIa 04 0 a voc c 0.2 0 0 0 -o a IA C 0 C1 0 0 a' LU W. D) L9 n7q r M t

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TABLE 8. VOLUMETRIC BUDGET FOR ENTIRE MODEL, 1989 CONDITIONS RATE (Million Gallons/day) RATE (Acre-Feet/day) Storage Constant Head Wells Drains Recharge ET River Leakage Head Dept. Bounds Total In OUT Storage Constant Head Wells Drains Recharge ET River Leakage Head Dept. Bounds Total Out IN-OUT 183 0 0 0 1020 0 13.7 52.8 1270 562 0 0 0 3130 0 42 162 3898 219 0 98.7 129 0 726 77.6 27.8 1273 -2.93 672 0 303 396 0 2228 238 85 3907 -8.99

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SENSITIVITY TESTING The model was tested to check its sensitivity to changes in aquifer parameters and stresses. Using the steady state model, aquifer parameters were tested by altering the following parameters: Layer one conductivity and river and drain bed conductance, Vcont between layers one and two, layer two transmissivity, Veont between layers two and three, and layer three transmissivity. The sensitivity of the model to these parameters was tested by doubling, then halving each parameter, one at a time. In addition, the Vcont terms and river and drain conductances were also reduced and increased by an order of magnitude. Using the transient model, specific yield in layer one was doubled and halved and storage in layers two and three were each increased and decreased by one order of magnitude. It was assumed that testing this range of values would bracket the range of uncertainty for each parameter. Head changes in each layer were examined to determine the relative sensitivity. The results of these tests are presented in Table 9. The model was also tested, using the steady state version, for its sensitivity to the following climatological factors: recharge, maximum evapotranspiration rate, and evapotranspiration surface. Recharge and ET rates were increased and decreased by 10 percent, and the ET surface was raised and lowered by one and two feet. The wells were turned off for one scenario to see the overall effect of withdrawals. Using the transient model, starting head was increased and decreased by 2 feet and results after one stress period (one month) were analyzed. It was assumed that testing this range of values for the various stresses would bracket the range of uncertainty. Results of these sensitivity tests are presented in Table 10. LAYER ONE Generally, simulated water levels in layer 1 were not sensitive to changes in aquifer parameters. Changes in hydraulic conductivity in layer one, on average, had no effect with a maximum increase of a foot and maximum decrease of 0.71 feet. Doubling and halving the Vcont between layers one and two also had no effect but reducing it by an order of magnitude raised water levels by an average of 0.08 feet. An attempt to increase by Veont an order of magnitude was unsuccessful as the model failed to converge. In layer two, the magnitude of the effect was similar but the direction was opposite with water levels decreasing an average of u. 4 feet when the Vcont was reduced by an order of magnitude. Reactions in layer three were similar to those in layer two. Reducing specific yield by half led to a 0.12 foot average reduction in water levels while doubling it had no effect, on average. Since the maximum increase and decrease resulting from specific yield changes was over two feet, this parameter could affect calibration in some areas. These maximum and minimum values occurred in the Jupiter agricultural area north of Indiantown Road. The largest effects are usually seen in areas with the largest stress. This area has significant withdrawals and since the irrigation is by flood method, the recharge to the aquifer is also high. Therefore, changes in specific yield and storage have the greatest effect in this area. As expected, increases in river and drain conductances resulted in lowering water levels in layer one, and average results in layers two and three were identical but the maximum change in water levels was slightly less in layer two and further diminished in layer three. A decrease in river and drain conductances led to a slight average increase in water levels, and layers two and three showed similar average changes. Of all the sensitivity runs made, changes in river and drain conductances had the largest maximum increase or decrease depending on the scenario. A decrease of almost twenty feet occurred in the Jupiter area when river and drain conductances were increased by an order of magnitude. The Jupiter area is the area of highest stress in the model, so the effect of changes is largest here also. The average value gives a better indication of the overall effect on the model, since most areas are not as significantly stressed. LAYER 2 Simulated heads in layer 2 show only minor effects from changes in aquifer parameters. Average heads in layer two increased 0.01 feet when transmissivity was doubled and decreased 0.05 feet when transmissivity was cut in half. A maximum increase of almost six feet and a decrease of seven feet indicates that calibration in local areas could be significantly affected by transmissivity values. These maximum increases and decreases occurred in the area of the Jupiter wellfield. Changes in Vcont between layers two and three caused little or no average changes in water level in all three layers.

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Changes in storage had no effect on average, with a maximum increase of 0.13 feet when storage was increased by an order of magnitude; this increase occurred in the Jupiter agricultural area near I-95 and north of Indiantown Road. LAYER 3 Doubling and halving transmissivity in layer three resulted in almost no change in average water levels in layer three. Average effects in layer one and two were less than 0.2 feet, with a maximum rise in head of almost 4 feet when transmissivity was doubled and an maximum decrease in head of approximately 3 feet when transmissivity was reduced to half Once again, the maximum increase and decrease occurred in the Jupiter wellfield area as a result of the large stresses in the area. MODEL BOUNDARIES The heads and conductances in the general heads were varied to determine their contribution at model boundaries (see Table 10 for results). At the Atlantic Ocean and Lake Okeechobee boundaries, because of the prescribed head condition, when prescribed head levels were increased or decreased by two feet, water levels in the cell containing the prescribed head also changed by the same amount. Along Lake Okeechobee, the cell adjacent to the prescribed head cell showed only a 0.1 foot change. However, along the ocean boundary, up to six cells west of the boundary were affected by the prescribed head level change. By the third or fourth cell west, the change was only 0.1 or 0.2 feet. The magnitude and distance of these effects was larger near coastal wellfields. Changes in the general head cells in layers two and three were similar to those in layer one. With an increase in prescribed head water level, flow increased into the model through the prescribed heads. There was no change in head as a result of reducing or increasing conductance by one order of magnitude. Flow rates out of the prescribed heads decreased only slightly with decreasing conductance and vice-versa. Flow rates were an order of magnitude less in layers two and three with an order of magnitude decrease in conductance. Similarly, increasing conductance in the general head boundary cells in layers two and three increased flow rates by approximately an order of magnitude. Along the north model boundary, a two foot increase in general heads resulted in heads that were 0.8 feet higher in the boundary cells in all three layers. In boundary cells containing or directly beneath rivers, aquifer head levels increased up to 0.3 feet. The largest changes occurred near large gradients (Osceola Plain edges, S97 control structure). The change was 0.1 foot or less by the adjacent cell (Row 2). Reviewing flow rates into and out of the general head, the increased head reduced the rate of loss from the aquifer into the general heads or increased the rate into the aquifer from the general head, depending on the initial flow condition. Decreasing general heads by two feet reduced heads in the cell by one foot and 0.3 feet in the boundary cells containing rivers. Decreasing conductance by one order of magnitude reduced water levels by 0.7 feet in general head boundary cells and boundary cells containing drains. Water levels changed 0.1 foot or less in boundary cells containing rivers. The changes were insignificant in the adjacent cells in row two. Increasing conductance lowered water levels in the general head boundary cells by 1.1 feet. Changes in boundary 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 by row three. In boundary cells containing drains, however, water levels were one foot higher and by row four they were 0.1 feet higher than the initial heads. Effects of conductance changes were similar in all layers. Along the south model boundary, the results of general head changes were similar in all three layers. When general head levels were increased by two feet, water levels in the boundary cells increased. In the area east of the Turnpike, near the Jupiter wellfield and nearby agricultural operations, water levels in the boundary cells were 1.26 feet higher in layer one and 1.33 feet higher in layers two and three. Water levels were affected up to six cells north of the boundary (Row 54). West of the Turnpike, water levels were 0.8 feet higher in the boundary cells but in the adjacent cells (Row 58), water levels were only 0.1 feet higher. Increases in flow rates out of the general head cells were less than one order of magnitude. Decreasing the general head water levels by two feet resulted in equal but opposite changes from the two foot head increase. An order of magnitude increase and decrease in general head conductance had variable results. West of the Turnpike, changes due to decreased conductance ranged from + 0.5 feet to -0.4 feet with an average of -0.1 feet; while east of the Turnpike, changes ranged from -6.2 feet to + 1.5 feet with the largest declines near 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 the Turnpike, changes ranged from +2.8 feet to -1.2 feet with the higher increases near large ground water

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withdrawals, and water levels were affected as much as five cells to the north (Row 54). CLIMATOLOGICAL AND STARTING HEAD EFFECTS Changes in these parameters (recharge, ET, starting head) showed some of the largest average changes in water levels in the model. Increasing and decreasing recharge by 20 percent resulted in a half foot increase and decrease in water levels, respectively. The maximum increase of 4 feet and decrease of 5.6 feet occurred in the Stuart area. Increasing the ET rate by 20 percent reduced water levels an average of 0.22 feet while decreasing the ET rate increased water levels by 0.33 feet on average. The maximum changes occurred in the area of the Florida Power and Light Reservoir. Increasing the extinction depth, which effectively increases the water available for ET, led to decreases in water levels of 0.76 feet. An attempt to reduce the extinction depth, adjusting so the minimum depth was zero feet, made the model unstable and it would not converge. Changes in the ET surface led to some of the most significant effects on average water levels. Increasing the ET surface by two feet, effectively moving it further away from the ground water source, led to an average water level increase of 1.48 feet. Decreasing the ET surface had the opposite effect, with a 1.55 foot decrease in water levels, on average. Starting head was another parameter that was increased and decreased by two feet using the transient simulation with very similar average results to ET surface changes. Raising and lowering the starting head is very similar to raising and lowering the ET surface and both should have similar effects. However, the model will attempt to equilibrate the water levels, moving them up or down based on the regional gradient. In lower transmissivity aquifers, model adjustments to equilibrate are slow and may not occur within the modeled time period. Therefore, starting head values should be as accurate as possible so calibration 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 occurred in the Jupiter wellfield and was almost 18 feet, which is consistent with wellfield drawdown data. The overall average water level increase was only 0.37 feet, which reflects the fact that in the majority of the county, well use is small to none.

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QUALITY ASSURANCE / QUALITY CONTROL PROCEDURE The South Florida Water Management District developed a quality assurance/quality control (QA/QC) procedure pertaining to ground water flow models as they progressed from the development stage to use by the Planning Department. The process involves a series of iterations between the model developer and the end user in the Planning Department as well as a peer review team selected for each model. Each model is evaluated in terms of: a) acceptability and b) impacts of deficiencies on application of the model. Acceptability is divided into three categories: 1) meets all standards of completeness and accuracy, 2) meets main standards, but enhancements are necessary to improve the overall accuracy of the model, and 3) does not meet standards and the model is not ready for use. All parameters that did not meet standards were corrected as a first priority. Parameters needing enhancements were prioritized into those that should be upgraded before the models are used to minimize future problems and those items which can be continually enhanced even while the model is in use. The QA/QC checklist is divided in two parts; a conceptualization section and a data sets section. The conceptualization section is a narrative discussion of the methodology and assumptions used in creating the data sets. It covers such topics as boundary conditions, time and space discretization, recharge and evapotranspiration calculations, water use data sources and assumptions, aquifer parameters, creation of parameters for rivers and drains, and calibration criteria. This discussion was intended to familiarize the user with all assumptions used in creating the model to make them aware of situations which may affect results. The data set checklist includes all data sets used in the model and verifies that there are no data anomalies. Data were checked both graphically and numerically. Three-dimensional plots of all arrays were created to point out errant data points. Contour plots were compared with data points used to create them to make sure they were accurate. The minimum and maximum value for each plot was determined and checked for reasonableness. Numeric arrays were printed and checked visually, especially at boundaries. River, drain and general head cell values were also printed spatially and checked for reasonableness and consistency between cells. All well locations were verified both in row,column and planar coordinate formats. Modeled pumpage was compared to permitted allocations for reasonableness. The volumetric budget was also checked to determine if anything was out of proportion. Several data corrections were made and changes in conceptualization at boundaries and in recharge and evapotranspiration sections resulted in model modifications. Finally, agreement was reached and checklists from the peer review panel were approved with no unacceptable sections and several sections identified as acceptable under current conditions with future enhancements necessary.

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RESULTS 1. The most important source of recharge to the Surficial Aquifer System in Martin County is rainfall. Approximately 95 percent of the recharge in the study area was provided by rainfall. The remaining five percent came from ground water flow 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 well withdrawals (nine percent), ground water flow out of the modeled area (one percent), and discharge to surface water bodies (19 percent). 3. Forty-five percent of the total ground water well withdrawals in the model area come from domestic self-supply use. Agricultural irrigation accounted for 27 percent of the ground water well withdrawals and public water supply withdrawals accounted for 24 percent. The remaining four percent comes from industrial uses. 4. The largest impacts in layer one, based on flow volumes, occur in the Port Salerno area, where domestic self-supply use is high, and at the edge of the Osceola Plain in Indiantown, where ground water elevations decrease rapidly and are further reduced by grove drainage. In layer two, flow is greatest around the Hobe Sound and Jupiter wellfields. Flow is also greatest around the Jupiter and Hobe Sound wellfields in layer three as well as between layers two and three.

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CONCLUSIONS AND RECOMMENDATIONS 1. Discharge to surface water bodies accounted for 19 percent of losses from the ground water system. Currently, the accuracy of this number cannot be verified but surface water models are being developed and results from this may result in modifications to the ground water model. One potential for error comes from defining the "wetted perimeter" of a canal. Data on widths and depths of canals is sparse, especially for the many grove and roadside drainage canals. Also, these same canals have no records on stage levels and often, not even information on control structure elevations. This makes it difficult, if not impossible, to accurately represent the drainage and recharge potential of these surface water bodies. During the regulation process, every effort should be made to include pertinent control elevation and canal construction data in the permits. Information concerning ditches, lakes, canals, wetlands, etc. in future surface water permits as well as one foot topographic data obtained during permit review could be of benefit in model calibration. Stage recorders in some of the major grove canals would produce invaluable data for use in the ground and surface water models. 2. Currently, the model is not sensitive/accurate enough to be used in surface water permitting to determine exact control elevations or to set wetland elevations. However, ground water levels in the model can be checked against existing permits and new proposed control elevations and any discrepancies reported to the model developer to aid in improved model calibration. Refinements in grid size and elevation data would make this a useful tool for surface water permitting to evaluate existing and future impacts due to surface water management systems. 3. The model in its present configuration (92 acres per cell) is not accurate in assessing ground water withdrawal impacts on a small scale, due to the regional nature of the model grid. As a result, small scale impacts on adjacent users or small wetland areas may be overlooked due to cell-wide averaging. Improved grid resolution and use of one foot topographic data is needed to better assess these small scale impacts. The SFWMD is currently working on software to make it possible to "zoom in" on an area of the regional model and extract data to create a submodel with finer grid resolution. This should improve site-specific evaluations. 4. With 95 percent of water to the model coming from the recharge package and 70 percent of the losses removed by the evapotranspiration package, the accuracy of the model is dependent on the accuracy of these two packages. During model calibration it became very obvious that these packages do not allow the user to accurately imitate the intricacies of these processes because they deal only with direct effects on the saturated aquifer. Therefore, pre-processing of inputs to these packages is necessary to meet the assumptions the model makes of this data. Areas needing work include accounting for irrigation water, investigating areas where ground water is significantly below land surface (dunes), and effects of canals which lower the water table below the ET extinction depth and the effects of each of these situations effects on recharge and evapotranspiration rates. 5. One portion of the evapotranspiration package is ET surface. It is usually set to land surface. Detailed land surface data on a large scale is not available. Where water level data were available for confirmation, changes of even one foot in ET surface affected calibration results. This illustrates the need for detailed information. However, cell size is also an important factor. In areas with rapid elevation changes, smaller cells and more detailed data should result in improved calibration of the model. 6. Although ground water withdrawals account for only nine percent of the modeled outflow, the impact of these withdrawals was the impetus for developing the model. Because domestic self-supply is such a large and widespread type of water use, parameters used in reaching this estimate need refining to increase the accuracy and reliability of the model. Specifically, better information on where all domestic use is self-supplied (i.e. pockets not yet on utilities), the location of private wells in utility areas and/or homes which use utility water for irrigation is needed.

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Agricultural irrigation accounted for 27 percent of the ground water well withdrawals in Martin County. However, data on actual amounts withdrawn are limited. Actual water use data would increase confidence in the calibration of the model, particularly in areas of heavy ground water use. In addition, accurate projections of future agricultural water use will be necessary for the development of a water supply plan for the area including Martin County. Most public supply utilities do not record flow from individual wells in their wellfields. Some do keep track of hours pumped per well but point out that well capacity is dependent on the number of wells pumping at a given time, which changes often. Individual flow meters would provide accurate withdrawals for input into the model. The model was difficult to calibrate within the specified constraints in several localized areas, especially the Martin Downs/Palm City area. Probable reasons are cell-wide averaging or uncertainty in aquifer parameters or stress rates. Future revisions to the model should be concentrated in these areas to improve the confidence level of the model.

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REFERENCES Adams, K. In Press. Ground Water Resource Assessments of Martin County. South Florida Water Management District Technical Publication 92-***, West Palm Beach, Florida. Bower, R.F., K. M. Adams, and J. I. Restrepo. 1990. A Three Dimensional Finite Difference Ground Water Flow Model of Lee County, Florida. South Florida Water Management District Technical Publication 90-1. Cooper, R. M. and R. Santee. 1988. An Atlas of Martin County Surface Water Management Basins. South Florida Water Management District Technical Memorandum. South Florida Water Management District, West Palm Beach, Florida. Cooper, R. M. and J. Lane. 1988. An Atlas of Eastern Palm Beach County Surface Water Management Basins. South Florida Water Management District Technical Memorandum. South Florida Water Management 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 Water Resource Investigation of Martin County, Florida: U. S. Geological Survey Open File Report FL-75-521, Tallahassee, Florida. Fetter, C. W. 1980. Applied Hydrogeology. Charles E. Merrill Company. Hopkins, E. 1991. A Water Resource Analysis of the Jensen Beach Peninsula, Martin County, Florida. South Florida Water Management District Technical Publication 91-03, West Palm Beach, Florida. Jensen, M. E. 1981. Design and Operation of Farm Irrigation Systems. American Society of Agricultural Engineers, St. Joseph, Michigan. Johnson, A. I. 1967. Specific Yield -Compilation of Specific Yields for Various Materials. U. S. Geological Survey Water-Supply Paper 1662-D. Kuiper, L. K. 1987. Computer Program for Solving Ground Water Flow Equations by the Preconditioned Conjugate Gradient Method. U.S. Geological Survey, Water Resources Investigations Report 87-4091. Lichtler, W. F. 1960. Geology and Ground-Water Resources of Martin County, Florida: Florida Geol. Survey Report of Investigations No. 23. Lukasiewicz, J. In Press. A Three-Dimensional Finite-Difference Ground Water Flow Model of the Floridan Aquifer System in Martin, St. Lucie and Eastern Okeechobee Counties, Florida. South Florida Water Management District Technical Publication 92-***, West Palm Beach, Florida. MacVicar, T. K. 1983. Rainfall Averages and Selected Extremes for Central and South Florida. South Florida Water Management District Technical Publication 83-2. MacVicar, T. K., T. Van Lent and A. Castro. 1984. South Florida Water Management Model Documentation Report: South Florida Water Management 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 Survey of Palm Beach County Area, Florida. U.S. Department of Agriculture, Soil Conservation Service, Florida. McCollum, S. H. and O. E. Cruz, Sr. 1981. Soil Survey of Martin County Area, Florida. U.S. Department of Agriculture, Soil Conservation Service, Florida. McDonald, M. G. and A. W. Harbaugh. 1988. A Modular Three-Dimensional Finite-Difference Ground-Water Flow Model. Techniques of Water-Resources Investigations of the United States Geological Survey, Book 6, Chapter Al. Miller, R, A. 1978. Water Resources Setting, Martin County: U. S. Geological Survey, Water Resources Investigation 77-68. Morris, F. W. 1986. Bathymetry of the St. Lucie Estuary. South Florida Water Management District Technical Publication 86-4. South Florida Water Management District, West Palm Beach, Florida. Nealon, D., G. Shih, S. Trost, S. Opalat, A. Fan and B. Adams. 1987. Martin County Water Resource Assessment. South Florida Water Management District, West Palm Beach, Florida.

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Opalat, S. 1985. Urban Water Demand Estimates for Martin County: 1983 Existing and Committed, and Buildout. South Florida Water Management District Technical Memorandum, West Palm Beach, Florida. Padgett, D). In Press. A Three-Dimensional FiniteDifference Ground Water Flow Model of the Surficial Aquifer in St. Lucie County, Florida. South Florida Water Management District Technical Publication 92-***, 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 Of Eastern Palm Beach County, Florida. South Florida Water Management District Technical Publication No. 88-4. Southeastern Geological Society Committee on Florida Hydrostratigraphic Units Definition. 1986. Hydrogeological Units of Florida. Florida Geological Survey 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 Florida Water Management District, West Palm Beach, Florida. Stodghill, A. M. and M. T. Stewart. 1984. Resistivity Investigation of the Coastal Ridge Aquifer Hydrostratigraphy, Martin County, Florida: South Florida Water Management District, West Palm Beach, Florida. Todd, K. D. 1980. Groundwater Hydrology. John Wiley & 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 Special Report, West Palm Beach, Florida. United States Department of Agriculture, Soil Conservation Service. 1970. Irrigation Water Requirements. 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. A Dun-Donnelley Publisher, New York. White, William A. 1970. The Geomorphology of the Florida Peninsula: Florida Geological Survey, Geological Bulletin No. 51, 164 pp.

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APPENDIX A MAPS AND TABLE OF DATA USED FOR VERTICAL DISCRETIZATION

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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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1.040,000 1.020,000 tOGOODO 980.000 960.000 940,000 920,000 T 38SI T3 I TI0SI T4 0 Uu LOLnNJO o0 CN p Nc ON" 6* -NVN If 0 -N C-N 0-= lC "r 0 7 4 o > w DJ. 0 n1 I u f 0 c CP oLn.* Mari acoc C~B 00f 04Cf oo

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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 Elev East 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

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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 Elev East 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

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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 Elev East 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

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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 Elev East 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

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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 Elev East 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

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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 I Layer 2 Layer 3 Elev. 1 2 3 Elev Elev Elev East 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

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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 Elev East 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 _= ----_

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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 42-45 Gee & Jenson Martin Downs 46-53 Perrson Drilling Corp St. Lucie Falls 54-56 CH2MHill Stuart So. Wellfld 57,58 Gee & Jenson Banyan Bay 59,60 USGS Hobe Sound/Unpublished 61 USGS J.D.S. Park/Unpublished 62 Geraghty & Miller Woodside 63 USGS Tequesta/Unpublished 64 CH2MHill Pipers Landing 65 Geraghty & Miller GDC-Martin Co. 66-70 Geraghty & Miller Stuart Y & CC 71 Geraghty & Miller Harbour Ridge 72 Geraghty & Miller River Bend Pk 73 USGS 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 92 Ray 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

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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 FileRpt 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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1.040 040 [ 020 400 1.000.000 960A00 960.000 940A00 MAN acs I45 T40s f415 V J Vi+ O 4A w Ql Y ^ i a LU t7 LL 9'W z + fi O n w z d n gy N 4 h w pp O O W C 8 C L 9 U 10 g .W O o re W n JIE 0 o 8 7 n" 1 {f i P w O r r WF d r K W Q O W 0 +f g 6 -, r W w a o a m S W 000'6t0'1 400'OZO'l 040'000'1 000'088 ow"O" 000'06 0001026 'i

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PAGE 112

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APPENDIX B MAPS OF HYDRAULIC PARAMETERS

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LIST OF FIGURES -APPENDIX B Figure Page B-1 Vertical Soil Conductance (Layer 1 Hydraulic Conductivity) ..... 109 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 B-5 Vertical Conductance (VCONT) Between Layers 2 and 3 ........ 113

PAGE 115

1.040.000 1.020.000 1.000.000 980.000 960.000 940.000 920.00E r 38 s S St .1 7t39 S T40S T4 S So 60 S Lt 1 0000v0L 000020 L1 0001001 000QQ9S 0001096 0000t6 o00"Z i S 0 1 S ns >a a

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}FT 39 S S St

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g m h d a n O 4 r S 0 H n Sh sm c' m c w o' W M Q O f P n Or n w n x 56£L I 56£1 SCO 1 I S L41 0 gS x 640'OhQ% 000'0Z0'L OW1b00'1 000'488 000'046 000'01$ 446 M G fp N L m J 4J a a m F z 0 u d V V 0 u u a 1,P1 W W 113 1.040.000 020,000 WOO.000 9rA0.0p4 986,000 940,000 926,004 T 385 T795 T465 141 5 W Y d 4 Y W W m W n rc S a 9 r mCl F O f r S h r a 'd 0 O d 0

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APPENDIX C GENERAL HEAD, RIVER AND DRAIN INPUT DATA

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LIST OF FIGURESAPPENDIX C Figure Page CLocation of Drain Structures ........... ......... ........... 119 C-2 Location of River Stage Stations ........................... 125 LIST OF TABLES -APPENDIX C Table Page C-1 Parameters Used to Describe Canals in Drain Package .......... 120 C-2 Structure Elevation Data Used in Drain Package ............... 124 C-3 Parameters Used to Describe Canals/Rivers in River Package .... 126 C-4 Stage Data Used in River Package ............................ 128 C-5 Data Used in General Head Cells ........................... 130

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I04O0 1.020.000 1.00ft000 960.000 960.000 940,000 920.000 rigS T1395 r 40 S T 41 S Liii 5 Sail 5641 SLVt oOOvtrt 600.,0I 000'00L 000orns owO 0004 000OI 9

PAGE 123

U a .a V4mJ + 6 N Vi N N Nl b > V) C4 ul Ln CA cm u wi vn CA y Zn v) eQe 6 Q. a fxT E 5 8 E :OUG. 4 } E H F to co 'o^ V3 Q* in Ga CL. PL Q a Q Q a Q Q 3 A 8. .S. S. LM ;n Qn U Un W y ( vs vs a. U V5 Q Q Q Q rn y $ $ '" 0 0 o g g g o $ a o 0 0 '" o 'C. C G C O G C p p O O C C Cl G O 6 O O re r .e i o $ 8 g o a a o o r Y o n o 0 C, kn a n N O O O .-i .y u7 00 l9 r+ wl op L, C4 4 0 o o r. o a o o N o 0 0 o a o k1l ON 10 c r n J z. N z 3 A Lo) En 0.i y 00 O 6. u o CA RY. O cL aC c y d Cg a A poQ Q a Q tpQp pp _.a U V] ur W w a. P. VI j v V u W p, u -.v .fir an G G Q 7 s! C a 3 u u r a V = U w W Q Q yQ y lu U U t p3 U U U .T. ? 9 fr7 7 q U fly o m V3 rn z a U rn CC m Q s. O ron

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.3 q O O y =a pp a a a = U W W W L L Y..1 va a LQ W La W W a a O o o o va fA vs n u V2 0 cn cn V) a. o. a. U V r, M U v Ca U -C -C O a as o o o A 8 8 -q U s My My E3 -' 6 + CL Or" 0 0 0 0 0 0 0 0 0 ; ; ; 0 ; A A F AA y A Q E+ A Q O Q Q E-' E-+ Fr F Q rr cn cn Q va v, vs rn r p ] Q Q q q q Q A V 0 0 _S."'{ O O O O 8 8 O O O O O p p O O O O O O C7 O O C O O O C C Q p O C C C O O b C G G% fA h r pp M ^ p E: o o a r1 0 0 0 a o o o o r o o ao 0 0 r + Ik 5oC o > 3 si h IL. Q o C7 C7 C7 L7 U a c 93. Cw C6 C6 Z x G C7 V C7 C7 L7 F F RY F 53 74 v a C L R C f0 V v a 0 -v a c L Q av V W J m H

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L V Ly K O O V O q b 9 b .b b 'C G 3 3 R m S Q Q en cn c+t sn Vy M M ., M M M .. rn CA in r, Q o" 6 -m Z Z I.n .Lo W C6 t. 3 3 g. S 3 IL O .. [ F F F F can .vpi rpn vi -:: Q p O O Q p p O O O O O O O O O O O O O Q O O Q O O O O O G G C C C O O C O O O O G O O V w z 'a pp of N %n O W N N O tit iN N (4 N N N N N N O p a z 0 m r r r N o v, en o 0 0 0 0 ao 00 n _.W 00 G + fV N + Q U S zn w z Z z z z z ., cn rA v, p Q rn ris v v. m cn rn rn e+g cL' r N .., ,, + x x x a a x x x + + + + + + M r 'i w p n .a h O Z CA v a S .a S a A Q Q Q Q Q D A Q Q QU Q e {5 L C E .4 -j s s C V! M tri Vl W) co) 01 G/l Gn V] M 0 Vi rA > x x x x x x z x x= x x x x a a v a c O L{S C u a V iA 0 a G C ".0 a V W m

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3 F9 EpE2 E2 Cn CA En col) co CO) 61) U U C7 C7 t7 C7 U .V1 fn V] V7 Vf Gn to u u u 0u z CL. d. 0. V lls [n V] Vl V) -. Vt c/S Vi VI VJ in m V} Cn VJ V1 V) [n V1 v: w GW7 :: 0 0 0 V CPK G L o 0 0 0 o t7 t 0 0 o O D .,s3 u u u u u d p L .A I lw f0 Y V a D V d L V H Q C 10 4W .a CJ H N "Q C r &C 0 u u eu J m H

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Structure Elevation Data Used in Drain Package STRUCTURE (WEIR) NAME LOX.CYPR SIR@TURNP SIR@C18 EPB2A EPB2B EPB2C EPB2D SALCTRL PKCOM P&W1 P&W2 M1Q MIP M10 M1N M1L MI1K L2K LL .2I iRGWPC 3RGCSS 3RGS1CN }RGS1S RGS2 LLLAP1 PILLMID LLAP2 16 16 WEIR ELEV (NGVD) 1.54 13 wet 14 dry 10.5 8 9 11 11 6.01 21 20 23.5 23.5 22.5 22.5 24.5 25 26.4 23.5 25 25 18 12.8 19.4 19 13.9 15.96 STRUCTURE WEIR (WEIR) ELEV NAME (NGVD) INDIANTWN 16 WEST END 16 C(C-44) 15.8 D(C-44) 15.8 E(C-44) 15.8 HSL KITCH 13 CRK 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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w w LtJQ -Sw w 0 Ii C SKi S 6C I S L~

PAGE 129

z O E U E, m. p' rn f i T f F U U a J J J i i r z i o co A 7 4 t u H V5 Q a o v L G QC G V a L V 4J to N L 4) W ED L m C. V W ..J m a v a ;4 Ac Ca .1 i 7 N 7 CA a

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y. 'v s Gi a: O w G 0 S 0 M m w U 0 0 0 (V a a c Q N C ,o U as U 0 c a 0 N 3 h6 3 U 0 c 0 g 0 a U ao .a 0 0 O O a c V m 0 Q 7 0 vl 0 N W J aw .i m w 0 6 0 o a M F, O 0 e cc 00 O o z a Q ti Q L lb w cj Q CC fx v "a "a. L .yC a 9 7 u o r a a F 0 U v r a u a cic c a LA i. i V v LO% a 0 a, W w-0 a E O aU V J

PAGE 131

F pC p '7 e o h e v, M v+ V e h M1 a .r ( Q1 h .., pppp C .M h h M1 N ry M h h .+ Q1 D 11'1 N 4+ N ." M1 { G n r. (V CV eV O+ O+ Q O +-i A N O O G e+1 O m O C n M Q O N Q N e'e5 Q vi w M n C GO N f Nr N C .Nr cr, .Ch-"i C O fl [V O C O .e-"i .e-"i Q C Q_ b C? b O 3 ne r t .+ b r N N CA C b O M Q .,y.O m N N .Nr .N O w a ONi C C .+ t+1 C G + ,' + s O (r en co T ['+ r+ en 00 C% en NS h h .+ o h h } -.a 'D nj o0 D fe5 .r 06 a0 .+ h N1 ao N O oa "r h a ti 00 fJ rr O N d 4 G .i ( 1 44 .i G .+ ri N G fV p" N rn ao ono 00 n ao T l'V eN+1. i ti o0 vmi, O n .r; G oD N N .i O n~i r -r .Qi C C7 N N e O O O .e-i .~i O C .a B o r. i, c O r } o ., ., ro M R'i .r rg c 3 0+ o N a rs N SV r+ .-+ .erg .N N p, r+ .ti lb : 4 vnj. M .-sD ,nN N C+ w %0 O Q e[ + IN W Ln ., Rtwy-. Q M1 T e-i w w. q .: OQ O'+ OQ 4; .+ C C C CVN O fV C O rr .r 'r N N .r .w .+ .r .r in Cr' 'D C h Q N r+ .r ,". O+ h h M Q+ G rr Q h N r N M C1 n rr er; O 8 =: C [ CI iV f3 O+ O+ O C d ri lV O O O .-+ O iS O :.. ^ 00 1N M co v i vNi b M 4 ['+ N N C4 O ffi vI ON O O 'r O, N O O O O O O [+ 00 o l+ 30 7 N M o h + N N G h M w v1 O h e ,r3 M h c's o h .. h 1O in n o e M1 o M1 n r" ,-+ C O M1 N N .r .fir .Q-i O G .-i CV lV C G C4 eq Np N M .fir N f/I b M1O, h f~r'i 0 0 tM 1 Ve+1i :. C !+ N rn O .T+ G G C ... O O O O G O 'T co Q+ vi [* .M1r ,O-i ehry t +1 .M-i N N (71 O a N ,nn h b O n Q O T e C r'I C Os C O *+ '+ c i O O O O fV O C Li3 K a a z a cs x a s AA a, "' o 0 0

PAGE 132

p { i' 'Y M h M r~ 1 Vr'i .M O 0 N N .+ Vi O N N'i hl H5 + .. .C Q p C G C. C4 r3 C ao r-! C a ,-i v r3 A tG c d o .. a A Na, a n O" O G J. N D O N ,r n fV C 'n pp >0 p n O R vl O %n yr C [*7 (r N p' GY. OL n a r c O x O 4 d 0 o v M fH o o A ti Q A Q v c+i tv C C r q o n c i rr o A Q O O A. '" vai n N aNO on w vMi. ?r }" y' 4 o 0 0 o o A n A R en r+ vi v. -o n 7 i Y i" "" oo M v, oo e r. e+s ors p dr OC OG N n t o R o ci d to ri '" Q n Q Q Q v c v .. e N N Q Q Q Qi O v] C a .nD Q+ 4 C + rMi O N N + NCr f+'I + i-a N v'7 F7 O r "D o q o c o cS r3 ri c c r A A *" o v C4 e a v e a + p arG o+ a o o Q O G M !h M 0 Q Q Q s o q c o o r; o; d o; c q In M N h n T + O 1" .r N 1n s o Q o 0 0 N r3 a o O% p 4 a o Q N o v ." b m Q v Q o a. A C 4 ca w cm w Q.) rA to

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N L C C N O V LU m H 3 s U_ 1"r 3 a .o a pG v r .Q .C .r DWI w .+ Cq i 4 .61 3 0 fl .r r+ .d k C s L g W s aka -a

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APPENDIX D RECHARGE METHODS, RAINFALL STATION MAP AND TABLE, RECHARGE AND ET COEFFICIENTS

PAGE 135

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

PAGE 136

RECHARGE The average recharge depth in a model cell resulting from precipitation, Rp, can be computed using the mass balance equation as: R, = P, -Qd -ET, -ET, (1) where P, 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 a MODFLOW package), and ET, is the average evapotranspiration depth from the unsaturated zone (not calculated by the evapotranspiration package in MODFLOW). ET, is the average evapotranspiration depth from the saturated zone (calculated by the evapotranspiration package in MODFLOW). The evapotranspiration from the unsaturated zone, Er, was not considered in this model. In areas where there is a significant unsaturated zone above the water table, however, the recharge calculations may become inaccurate 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 approximated from the total monthly precipitation depth over the cell, Pt, as: N P. = MAX{KJ'P -( M Kd(n), 0} (2) n=1 where 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 objects until it returns to the atmosphere through evaporation (Bower, et al., 1990). The quantity of water intercepted depends upon the storm character, the season of the year, and the species, age, and density of the prevailing plants 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 KI assigned to a model cell represented the weighted average of the I values for all land use types within the cell. 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 trapped in 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

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for each precipitation event. The model depression storage loss, K, was calculated as: Kd = KIa {MAX{[1 -SQR(K/Km)], 0}} (3) where Kd" 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 is assumed 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 single precipitation event, and a value of (KiK.) = 1, a highly pervious area, implies a Ki = 0. Rainfall of less than the 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 -storage capacity is usually reached early in a storm event. This implies that a larger fraction of rainfall is intercepted in 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 tables of 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 47 feet/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 net precipitation depth, P,, and the net infiltration (Bower, et al., 1990). Then net average depth of water lost to 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 drainage into a canal or into a surface water body. Factor KI takes into account the effector of drainage systems which may recharge the unsaturated zone of the aquifer. The value of K, is a function of the average hydraulic conductivity and the average slope of the land surface. It has a value of 1 if there if no drainage into the unsaturated zone, and has a value of 0 when rainfall completely recharges the unsaturated zone. Model values for K, varied between .1 and .3. Table D-3 lists land use codes and the K, value assigned for each code. The value 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.

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T 3 S 5 t .1

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TABLE D-1: Rainfall Station Descriptions Map State Plane Coordinates No. 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

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TABLE D-1: Rainfall Station Descriptions (Continued) Map State Plane Coordinates No. 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

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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:

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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:

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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:

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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, and gravel pits) (BS) Spoil areas (BL) Levees Documentation of major codes from "LAND USE, COVER AND FORMS CLASSIFICATION SYSTEM, A TECHNICAL MANUAL", Department of Transportation, State Topographic Office Remote Sensing Center, Kuyper, Becker and Shopmyer, February 1981 TABLE D-2:

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Coefficients Used in Recharge Preprocessing Land Use 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 Ka Ki .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 Land Use 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:

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Coefficients Used in Recharge Preprocessing (Continued) Land Ki Ks Ka Use 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 Ka Use 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:

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Crop Coefficients/Land Use Type Coefficients/Percent Coverage Land Covered Month Use % 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:

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

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

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

PAGE 151

1.040S00 1 .Q20.OOC ?SOa~ CR0 IWI CR0 WI OM% r 40S 41 5 Q: 0> H-azf cr) CD o (fA L -I 5f i k S 1 5 4 SLt I 00A 10 000I W O L 000'000' QQQ'396 Oon rrO'On irmom 5 T 39S I" 7 -0T 38 1,040.000 1.020,000 limo00 9M.000 960 000 9#0,000

PAGE 152

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APPENDIX E WATER USE DATA, PUBLIC AND AGRICULTURAL

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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 Pumpages in 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 Comparison of Modelled to Permitted Pumpage ............................ 186

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T35 O C) z
PAGE 156

TABLE E-1-A: Description of Public Supply Utility Wells Used in Model (Community Systems) WELL INDEX 4300041 4300053 STUART UTILITY NAME IND LANTOWN 2 3 4 5 6 7 8 9 10 11 12 13 15 16 22 23 24 25 26 27 28 29 WELL NAME 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 PUMP CAPAC. (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 PLANE COORDINATES 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 PUMPAGE METHODOLOGY 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

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TABLE E-1-A: Description of Public Supply Utility Wells Used in Model (Community Systems) (Continued) WELL UTILITY WELL PUMP ROW COL STATE PLANE PUMPAGE INDEX NAME NAME CAPAC. COORDINATES MEIHODOLOGY AND (GPM) CALCULATIONS X 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 .194 VISTA 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

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TABLE E-1-A: Description of Public Supply Utility Wells Used in Model (Community Systems) (Continued) WELL INDEX 4300169 4300173 4300277 4300342 5000010 JUPITER UTILITY NAME MARTIN DOWNS PIPER'S LANDING DEPT. OF CORRECT. FISHERMAN'S COVE 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 WELL NAME 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 PUMP CAPAC. (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 PLANE COORDINATES 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 PUMPAGE METHODOLOGY 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

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TABLE E-1-A: Description of Public Supply Utility Wells Used in Model (Community Systems) (Continued) UTILITY NAME TEQUESTA PRATT & WHITNEY PB PK OF COMM WELL NAME 24 25 26 27 7R 8R 18 19 20 23 2 3 4 7 8 1 2 =r PUMP CAPAC. (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 PLANE COORDINATES 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 PUMPAGE METHODOLOGY AND CALCULATIONS (MT = Monthly Tolal) FLOW METERS MT .37 MT .37 MT .19 MT .04 MT .04 FLOW METERS WELL INDEX 5000046 5000501 5001528

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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 N East 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

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TABLE E-1-B: Description of Public Supply Utility Wells Used in Model (Non-Community Systems) (Continued) Model Model Populaton Sae Plane Coordlnaltes Utility ]Name Map # 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

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

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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 1647 3.647 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 am 4000 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 0.00 amono 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 3.2o 1521 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 ace ao 0000 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 am 0.777 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 2.415 2415 4171 4708 Q 182 4.809 0 142 3.068 0.142 0.142 4165 3439 3.439 3.439 1439 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 4000 amo 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 108 4.148 3.916 3371 1.882 0.000 L886 aLmU &000 182. 3411 4760 533 16149 13569 6960 &472 2237 1237 2237 .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

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TABLE E-2: Public Water Supply Utility Pumpage Data (Continued) UrILTY NAME IEOUESTA P.ATI A WHrrNEy 1B PK OF COMM 28 7R it 19 20 23 2 3 4 7 8 1 1989 PUMPAGE IN MILLION GALLONS PER MONTH or 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 11.259 1L259 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 0 403 0.03 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 1.405 L-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 .795 LTP5 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 10.489 1xo99 11.056 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 Q554 09544 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 11275 Iam 134275 5.276 1.111 111 12073 7.631 2130 0514 2576 22388 11364 ILS 11364 5.835 ',33 1.229 L229 AVG 2.87 10B7 0000 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

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TABLE E-2: Public Water Supply Utility Pumpage Data (Continued) WELL TEL L989 PUMPAGE IN MILLION GALLONS PER MONTH UTILITY NAME 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

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TABLE E-2: Public Water Supply Utility Pumpage Data (Continued) UTILITY NAME HOBE SOUND MILES GRANT MARTIN CO, VISTA SALERNO sT. LUCIE FALLS MARTIN DOWNS PIPERS 1ANDING DEF3IF OP CORRECT. FISHERMAN'S COVE UPIlER WEL or MAP 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 1.257 L257 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 1.83 L409 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 LOS 1.860 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 11646 I0646 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 6565 15063 (.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 1011 2011 1011 1304 1304 1.803 2358 19119 PUMPAGE IN MILLION GALLONS PER MONTH 1

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TABLE E-2: Public Water Supply Utility Pumpage Data (Continued) WELL L 1989 PUMPAGE IN MILLION GALLONS PER MONTH UTILITY NAME 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 TrailMaint. 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

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TABLE E-2: Public Water Supply Utility Pumpage Data (Continued) 1989 PUMPAGE IN MILLION GALLONS PER MONTH UTILITY 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

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Comparison of Actual Reported Pumpages to Permitted Pumpages in Public Water Supply Wellfields Individual Water Use Permits Permit # Permittee 4300041 4300053 4300066 4300076 4300086 4300089 4300164 4300169 4300173 4300277 4300342 5000010 5000046 5000501 5001528 INDIANTOWN STUART HYDRATECH HOBE SOUND MILES GRANT MARTIN CO. V.SALERNO ST. LUCIE FALLS MARTIN DOWNS PIPER'S LANDING DEPT. OF CORRECT. FISHERMAN'S COVE JUPITER TEQUESTA PRATT & WHITNEY PB PK OF COMM General Water Use Permits 85-5 AckeLs MHP 87-174 Angle Inn MHP 79-189 Canoe Creek 85-45 Evergreen Club 85-15 First Nat'l Bank/Trust 83-55 Indianwood Golf/CC 84-98 J & S Fish Camp 87-81 J/T Church of Christ 82-407 Martin Co. Min. Security 88-255 Monterey Marine B8-5 New Life Ch of Christ 87-243 Nichols Sanitation 86-168 OLd Trail-Golf Maint. Bldg 84-216 Palm City Elem. 80-142 Pinelake Gardens 43-00497 Pines MHP 88-339 Port Salerno Groc. 85-109 Rio Coemmerc. Ctr 83-110 River Landing 79-211 Soundings Y&CC 84-111 South End improv. 79-194 South Fork HS 80-157 South River Condo 88-396 St. Lucie Mob VilL. 86-214 STOP Camp (JDSP) 87-272 Stuart Aviation Ctr. 43-00498 Tannah Keeta Camp 87-401 Ted Twist Tank&Tummy 80-56 Tropical Acres MHP 87-340 Tylander Systems 88-311 Willoughby Golf 81-107 Woodside Subdiv. 88-205 Yankee Trader 87-450 S & s Rentals (Sierra Sq) 82-392 Sunshine Tree School 83-052 Tri-Gas 82-398 Valmaron Country Store Actual Permitted (mgm) (mgm) 242.531 355 1257.504 1410 358.520 752 867.761 1070 62.769 72.63 569.857 548 40.975 92 187.242 614 38.796 36.5 96.536 134 55.300 60 3507.811 4927.5 570.158 941.7 372.241 105.57 8.664 147.28 Actual Permitted Permitted Avg Day Avg Day Max Day (mgd) (mgd) (mgd) 0.0241 0.0210 0.0310 0.0782 0.0200 0.0500 0.0801 0.0600 0.1000 0.0017 0.0005 0.1000 0.0005 0.0002 0.1000 0.0013 0.0009 0.0100 0.0005 ? 0.1000 0.0067 0.0014 0.0021 0.0235 0.0350 0.1000 0.0008 0.0020 0.0040 0.0003 0.0014 0.0014 0.0016 0.0015 0.0020 0.0023 0.0179 0.0293 0.0051 0.0114 0.0133 0.0925 0.0900 0.1000 0.0059 0.0070 0.0140 0.0008 0.0010 0.0020 0.0006 0.0008 0.0020 0.0398 0.0400 0.1000 0.1327 0.0500 0.1000 0.0805 0.0320 0.0800 0.0324 0.0700 0.1000 0.0767 0.0819 0.1000 0.0853 0.0820 0.0980 0.0027 0.0030 0.0060 0.0012 0.0009 0.0014 0.0004 0.0160 0.0500 0.0016 0.0008 0.0010 0.0917 0.0250 0.1000 0.0002 0.0003 0.0003 0.0016 0.0072 0.0014 0.0212 0.0150 0.1000 0.0038 0.0035 0.0050 0.0004 0.0009 0.0012 0.0009 0.0010 0.0010 0.0002 0.0008 0.0015 0.0011 0.0100 ? Note: The General Permits listed are not a complete list of all small public supplies in the model, but only those that actually have SFWMD permits. Water Use Permits outside of model area (Jensen Beach Peninsula) ** Units are in million gal ons TABLE E-3:

PAGE 170

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PAGE 171

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PAGE 173

s; C7 M d e"'n d M d Y : Cry R. d At: M A ; M FF !M y NY L a y M w7 h o0 a0 o m 3 P d vi vi od ed d eJ O P h GFO 'G .. s6 r d r r i d N N r5 r r r od N N n N O l5 r r N ad as S S W N r e+. e+: 9 A _.. .N N N N in en m N N N N N N N _QG N 4 dl Q N A N N N N NI N N N N N N N N N D N T F M en F r N ti n F n n n n r F r r r rte'M1 h r N in f v O F a0 P H ti r n r .+ r ti N N a' i! q s E P4 a 0 Ql H a 'D CL r E 7 0.0 V -ti C c oL cti. o&A J D L Y a o2 a' oac Z a DIY! M W

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PAGE 175

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PAGE 176

e I a e c .-3 3 e b h M N N O o o O O .. d d N o o e o o N d d m 0 4 e e e o e .i A ;; M o P O o o e ,7S L5: d d e4 rQrQ'' d eJ d N{ '' +^ i t o+ eqq A 3 N rya e d d A .4 c .a .4 d c1 d ti rj CO [N F r h On0 d0 M N t;t c w v m N N N N N N N N N N N N N N W M @ N N N '/': ': i n n M m p h h h [ h M1 M1 h h F n [ M1 Cfb'h r O M h H r r -. m N b N N N N en V N M e h b Z V O C M w ut M av" p1 4) r a m C r 'o av C 4A E O L a v as 0 LA J W W W O d 9 O C Z a 1 LU J m

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PAGE 178

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PAGE 179

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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 MotI alraa 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

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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 Mpea Purms Lay R. Cal aEas 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

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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 MeatL rmit lay B .r C ItEat N CAPt Ja 7.k Mar ApH May Jua Jul As& Se Ots N. D.c 5001896 78282958718 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 L162 32 Black 6492OD 979100 2 33 29 0.792 0.864 0.10 0828 0294 0.060 0.439 0145 0.099 0.297 0.228 32"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)

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TABLE E-5: Permit Use Number Type Owner 4300013 GLF 4300017 AG 4300021 AG 4300031 GLF 4300032 GLF 4300064 GLF 4300069 RECR 4300132 AG 4300156 LSC 4300198 GLF 4300261 LSC 4300266 GLF 4300335 AG 4300368 AG 4300382 LSC 4300425 LSC 4300434 GOL 4300441 LAN 4300502 LSC 4300054 GLF 4300091 GLF 4300138 GLF 4300200 AG 4300202 LSC 4300273 GLF 4300371 GLF 4300375 AG 5000153 AG 5000223 GLF 5000237 AG 5000344 AG 5000547 AG 5001131 LAN 5001169 LAN 5001203 LAN 5001204 LAN 5001282 LAN 5001373 LAN 5001391 LAN 5001392 LAN 5001484 LAN 5001664 LAN 5001842 LAN 4300009 AG 4300022 IND 4300051 NUR 4300055 COMM 4300059 COMM 4300057 AG 4300107 NUR 4300143 NUR 4300144 NUR 4300182 NUR 4300206 AG 4300242 NUR 4300251 NUR 4300399 NUR 4300409 NUR RodriguezAG Mecca AG 4300362 IND Non-Potable Water Use Permits in Model Area and Comparison of Modelled to Permitted Pumpage Model Q Permitted % Diff (mgy) (mgy) ModeL/Permit KING MOUNTAIN CONDO MONTEREY FLOWERS INC. SOUTH FLORIDA GRASSING MARTIN CO. GOLF & C.C. YACHT & COUNTRY CLUB, INC. MARINER SANDS COUNTRY CLUB MID RIVERS INC. S & S FLOWER FARMS MARTIN CO. SCHOOL BOARD PIPERS LANDING RGA DEV. (CUTTER SOUND) ENVIRON. VENTURES (THE WATERFORD) J. & J. DAVIS (TARHEAL FARMS) PALM CITY SOD LOBLOLLY PINES DEVELOPMENT J. RICHARD HARRIS (CAPTAIN'S CREEK) CORNERSTONE GROUP (COBBLESTONE C.C.) MARINER SANDS PROP. OWNERS MARTIN CO. (HOLT LAW ENF. CENTER) JUPITER HILLS CLUB RIVER BEND GOLF COURSE LINKS GROUP (CYPRESS LINKS GOLF COURSE) JOHN D. & NANCY P. MARTIN (LESSEE) LITTLE CLUB CONDO ASSOC. HOSE SOUND WATER COMPANY HOSE SOUND GOLF CLUB PERO FAMILY FARMS RESTIGOUCHE, INC (MAPLEWOOD) TEGUESTA COUNTRY CLUB JONATHAN'S LANDING S & J FARMS AMERICAN FOODS SEA OATS OF JUNO BEACH JUPITER 1 HOMEOWNERS RADMOR CORPORATION OCEANSIDE TERRACE HOMEOWNERS THE RIDGE AT THE BLUFFS THE RIVER HOMEOWNERS JUPITER BAY HOMEOWNERS LJ JUPITER VENTURE (VILLAS OF OCEAN DUKE JUPITER BEACHCOMBER CONDO PRATT & UHITNEY MARQUETTE ELECTRONICS SUNSHINE STATE CARNATION FLORIDA POWER & LIGHT R. N. RINKER FARMS INC. ROBERTS FISH FARM LARRY WRIGHT'S FISH FARM HOBE-ST. LUCIE CONSERVANCY HOWE HOLDINGS INC. (FERNLEA NURSERIES) STUART FARMS SCHRAMM'S FLOWERS RICHARD G. & MARSHA HUPFEL BLOODIS HAMMOCK GROVES, INC MARTIN CO. TREE GROWERS LOXAHATCHEE NURSERY OF STUART 0. & E. NISSEN (SUSHINE STATE CARNATION) R. REMELIUS (CLASSIC GROWERS) No Permit No Permit CAULKINS INDIANTOWN CITRUS CO. S) General Permits 7900054 LSC KIMGS00O, INC. 7900121 PUSI STEFFENS TOWNHOUSE 7900194 PUSI MARTIN CO. (SOUTH FORK H.S.) 8100222 PWSI R.C. LINDSEY (VISTA SALERNO SUBED.) 8200407 PWSI MARTIN CO. STOCKADE 8300118 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 11.10 13.80 288,90 229.90 176.80 271.20 119.00 4.30 37.90 83.80 61.90 361.40 67.40 333.00 98.40 7.90 113.30 69.40 19.70 160.60 134.90 295.00 24.30 51.10 133.90 456.00 80.77 318.90 78.20 92.40 13.80 3.23 30.30 2.00 51.60 21.65 8.37 8.37 1.35 37.89 5.13 6.10 300.00 18.10 30.80 36.50 4460.00 20.40 41.30 8.50 8.00 18.40 48.00 38.20 34.00 49.30 50.00 3.65 36.50 36.50 3.65 36.50 36.50 32.10 0 22 101 64 104 150 42 120 44 80 96 11 62 145 21 103 23 49 107 263 20 275 14 250 26 36 61 20 1541 298 28 380 97 296 236 43 81 53 327 0 99 160 81 33 100 100 62 46 55 93 34 97 14 68 21 46 1 90 14 32 64 3 3 68

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TABLE E-5: 8400153 8500051 LAN 8500076 LAN 8500107 LAN 8500192 LAN 8500207 LAN 8500361 LAN 8600003 LAN 8600020 AG 8600137 IRR 8600148 LAN 8600149 LAN 8600171 LAN 8600182 LAN 8600266 LAN 8700092 LAN 8700110 LAN 8700160 PWSI 8700392 LAN 8700436 LAN 8800027 PWSI 8800089 LAN 8800096 LAN 8800153 LAN 8800182 PJSI 8800357 LAN 4300493 LAN 4300512 LAN 7900106 PUS 8500186 IRR 8600331 LAN 8700082 LAN 4300528 LAN 8200398 PWIR 8400123 AG 8400212 AG 8400224 AG 8500048 AG 8500301 AG 8500352 AG 8500353 AG 8500376 AG 8600023 AG 8600084 AG 8600200 AG 8700450 PuSI 8800261 AG 8800441 AG 5001797 PWSI 5001896 AG 5001961 AG 5002016 AG 8800133 NUR 8800134 NUR 7900104 PWS 8200060 HUR 8200161 NUR 8200233 NUR 8200242 NUR 8700253 NUR 8700258 AG 8700361 NUR 8700432 NUR 8200354 NUR 8700176 NUR 8700448 NUR 8800277 NUR BLock28 AG BLock32S AG BLock32N 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 COVE MARTIN OOWNS PUBLIC PARKS KIN POY LEE & SONS MALLARD CREEK KINGMAN ACRES CONDO KINGMAN ACRES CLUB KINGMAN ACRES VILLAGE IIA MONARCH POINT DEV. (PARCEL 35) REGENCY SQUARE SHOPS OF STUART/WEDGEWOOD COMMONS WHIPPOORWILL SUBDIVISION EPISCOPAL CHURCH OF THE ADVENT FAIRWAY GARDENS INDIAN STREET SHOPPES WATERFORD ADMIN. & SALES CTR. CHARTER CLUB AT MARTIN DOWNS IBIS POINT AT MARTIN DOWNS PENNWOCD FARM JERRY'S FOUR SEASONS MARKET MY SCHOOL LEARNING CTR MARTIN CO. ADMIN. COMPLEX FIRST NATIONAL BANK (SE OCEAN BLVD) GOLDEN CORRAL STEAK HOUSE TURTLE CREEK EAST INDIAN HILLS JUPITER-TEQ. CHURCH OF CHRIST TURTLE CREEK CLUB W. T. BELLEW SUMMER WINDS OF JUPITER LOGGERHEAD PLAZA PRATT & WHITNEY OCEAN 8 THE BLUFFS SOUTH BANANA MAX CHASEWOOD NORTH CHASEWOOD OF JUPITER JUPITER PK OF COMMERCE BLUFFS SQUARE SHOPPES JUPITER HEALTH & RECRE. CENTER MAPLEWOO PARK, PHASE I SIERRA SQUARE JUPITER WEST ELEMENTARY SCHOOL "A" (LIMESTONE CRK) H & B TOOL LOXAATCHEE POINTE MALLARDS COVE II LAUREL OAKS PARAMOUNT NURSERY (NORTH SITE) PARAMOUNT NURSERY (SOUT SITE) F. PASQUALINO (RESTAURANT) ADAMS NURSERY BIG PINE NURSERY ELIAS LUSTIG PINDER'S NURSERY BUILD INC. TURNPIKE DAIRY ISLAND PLANT NURSERIES BURKEY NURSERY D. KOUBA (THE PLANT FACTORY) D. GLUCKLER (FLOWER FARM) WATER-RITE TREE FARM JUPITER TREE FARM Unpermitted Unpermitted Unpermitted Unpermitted Key to Use Types: AG = AgricuLturaL IND = Industrial GLF = Golf CmE = Commercial MUR = Nursery LA, LSC,IRR = Landscape PWSI = 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 36.50 31.30 36.50 27.30 6.23 10.20 2.00 5.18 32.80 8.85 3.61 0.73 2.81 25.50 23.60 11.40 7.53 0.33 1.64 8.76 1.99 32.80 30.50 0.73 0.37 2.92 1.97 0.66 3.65 21.90 3.13 2.04 2.31 3.28 2.55 7.11 3.50 2.19 27.30 32.80 19.10 3.65 8.39 0.44 7.30 19.40 0.37 7.30 5.91 2.19 21.90 21.90 3.65 36.50 36.50 36.50 2.92 32.80 32.80 21.90 3.65 36.50 35.00 7.30 32.80 Non-Potable Water Use Permits in Model Area and Comparison of Modelled to Permitted Pumpage (Continued)

PAGE 187

APPENDIX F COMPUTED AND OBSERVED HYDROGRAPHS REPRESENTING MONITOR WELLS, 1989

PAGE 188

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PAGE 190

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PAGE 191

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PAGE 192

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PAGE 193

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PAGE 194

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PAGE 196

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