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Hydrostratigraphy and groundwater migration within surficial deposits at the North Lakes Wetland, Hillsborough County, Florida
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LaRoche, Jason J
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Permeameter
Grain-size
Floridan
Leakance
Recharge
Dissertations, Academic -- Geology -- Masters -- USF   ( lcsh )
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bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

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ABSTRACT: A wetland in west-central Florida was studied to characterize the local hydrostratigraphic configuration of surficial deposits overlying more-permeable limestones and conceptualize groundwater recharge. Eight continuous cores were drilled through the surficial deposits and partially into the underlying limestone. A total of 111 samples were extracted from the cores for laboratory sediment analyses and testing. The surficial deposits are roughly eight meters thick and made up of upper and lower clean-sand hydrostratigraphic layers (S1 and S3, respectively) separated by a low-permeability layer of clayey sand (S2). Also, a discontinuous low-permeability layer of clayey sand (S4) lies between S3 and the top of limestone. Equivalent hydraulic conductivity values for the S2 and S4 clayey layers (0.01 and 0.1 m/day respectively) are significantly less than those of the S1 and S3 sand layers (2 and 1 m/day respectively).Significant confinement between the surficial and Upper Floridan aquifers by means of a laterally extensive dense-clay unit immediately above the limestone is consistently reported elsewhere in the region, but was not encountered within the wetland. Partial confinement is apparently the result of low-permeability layers within the surficial deposits alone. Results of ground-penetrating radar and vertical head difference measurements suggest the presence of buried sinkhole features which perforate the low-permeability S2 layer and create preferred pathways for flow or karst drains. Comparison of results between laboratory sediment testing and a site-scale aquifer performance test (APT) suggest that the primary mechanism for drainage during the APT was by vertical percolation through the S2 layer while flow through karst drains was minimized. In this case, calculated leakances based on laboratory sediment testing are most accurate in approximation of effective leakance.It is predicted that as water table stages rise within the wetland, effective leakance will increase as flow toward karst drains becomes the more dominant mechanism for drainage. As a result, calculated leakances based on direct laboratory sediment testing are a decreasingly accurate approximation of effective leakance.
Thesis:
Thesis (M.S.)--University of South Florida, 2007.
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Includes bibliographical references.
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by Jason J. LaRoche.
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Hydrostratigraphy and Groundwater Migration within Surficial Deposits at the North Lakes Wetland, Hillsborough County, Florida by Jason J. LaRoche A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science Department of Geology College of Arts and Sciences University of South Florida Major Professor: Mark T. Stewart, Ph.D. H. Leonard Vacher, Ph.D. Mark Rains, Ph.D. Date of Approval: June 27, 2007 Keywords: permeameter, grain-size, Floridan, leakance, recharge Copyright 2007, Jason J. LaRoche

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ACKNOWLEDGEMENTS Equipment and materials for this research project were provided in part through a contract with the Southwest Florida Water Management District (SWFWMD) and in part by the Department of Geology at the Univ ersity of South Florida (USF). Technical expertise and help with field work were provided by Donald Thompson (SWFWMD), project supervisor Christian Langevin, and classmates Carl Albury and W. Barclay Shoemaker. Without the help and support of these friends this research would not have been possible. I thank the faculty and staff of the Department of Geology at USF for providing me with an enjoyably challenging and rewarding educational experience. Special thanks are given to Dr. Christian Langevin for the invitation to participate in the North Lakes investigation and especially to Dr. Mark Stewart for his guidance and patience towards conclusion of this research. Most importantly I would like to thank my wife Rebecca, parents Paul and Constance, and brothers David, Michael, and Timothy LaRoche for their constant encouragement and support in this endeavor.

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i TABLE OF CONTENTS LIST OF TABLES..............................................................................................................iii LIST OF FIGURES...........................................................................................................iv ABSTRACT....................................................................................................................... v INTRODUCTION...............................................................................................................1 Background...........................................................................................................1 Purpose.................................................................................................................2 Specific Objectives................................................................................................2 STUDY AREA...................................................................................................................4 Location.................................................................................................................4 Physiography.........................................................................................................4 Climate and Hydrology..........................................................................................7 Geologic and Hydrogeologic Setting.....................................................................7 General......................................................................................................7 Regional....................................................................................................8 Local........................................................................................................12 PREVIOUS WORK.........................................................................................................13 Hydraulic Conductivity.........................................................................................13 Aquifer Heterogeneity/Anisotropy........................................................................14 Leakance.............................................................................................................16 METHODS......................................................................................................................18 Drilling and Sampling...........................................................................................18 Grain-size Analyses............................................................................................20 Permeameter Testing..........................................................................................20 Geophysical Methods..........................................................................................21 RESULTS........................................................................................................................ 23 Laboratory Analyses............................................................................................23 Hydrostratigraphy................................................................................................28 S1............................................................................................................28

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ii S2............................................................................................................29 S3............................................................................................................29 S4............................................................................................................30 Tampa Limestone....................................................................................31 Geophysical Logs................................................................................................32 DISCUSSION..................................................................................................................35 Delineation of Hydrostratigraphic Layers.............................................................35 Geophysical Logs................................................................................................38 Vertical Head Differences....................................................................................39 Equivalent Hydraulic Conductivity.......................................................................42 Leakance.............................................................................................................43 Stage-Dependent Effective Leakance.................................................................47 Leakage Estimations...........................................................................................50 Regional Outlook.................................................................................................53 CONCLUSIONS..............................................................................................................56 REFERENCES CITED....................................................................................................60 APPENDICES Appendix A Grain-size Distribution Analysis Procedures...................................65 Appendix B Permeameter Testing Procedures..................................................71 Appendix C Geophysical Logs from Completed Monitor Wells..........................74 Appendix D Grain-size Distribution Frequency Plots..........................................84 Appendix E Results of Grain-size Distribution Analyses..................................184 Appendix F Permeameter Testing Data...........................................................187 Appendix G Results of Permeameter Testing..................................................190 Appendix H Hydrogeologic Stratigraphic Columns for Cored Sites..................194 Appendix I Isopach Maps of Hydrostratigraphic Layers...................................202 Appendix J Contour Maps of Vertical Head Differences..................................206

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iii LIST OF TABLES Table 1 Monitor-well construction specifications for lithologic sampling wells......18 Table 2 Summary of textural and hydraulic parameters within lithostratigraphic layers (S1 through S4).............................................................................26 Table 3 Vertical head differences.........................................................................40 Table 4 Calculated composite hydraulic conductivities and leakances from permeameter-derived K values................................................................44

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iv LIST OF FIGURES Figure 1 Location of North Lakes wetland and the Section 21 well field..................5 Figure 2 Study Area with lithologic sampling locations and surface-visible karst features......................................................................................................6 Figure 3 Physiographic provinces, study areas, and hydrogeologically similar region after Parker (1992)..........................................................................9 Figure 4 Ternary plot of sand, silt, and clay percentages for all samples grouped by lithostratigraphic layer.........................................................................25 Figure 5 North-south stratigraphic cross-section of study area.............................33 Figure 6 East-west stratigraphic cross-section of study area................................33 Figure 7 Scatterplot of permeameter-derived log K values versus elevation and boxplots of log K values grouped by hydrostratigraphic layer.................37 Figure 8 Probability plot of log K with 95 percent normal confidence intervals......37 Figure 9 Contour map of laboratory-derived calculated leakances........................46 Figure 10 Cross-section with water table elevations from March and October........49

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v Hydrostratigraphy and Groundwater Migration within Surficial Deposits at the North Lakes Wetland, Hillsborough County, Florida Jason J. LaRoche ABSTRACT A wetland in west-central Florida was studied to characterize the local hydrostratigraphic configuration of surficial deposits overlying more-permeable limestones and conceptualize groundwater recharge. Eight continuous cores were drilled through the surficial deposits and partially into the underlying limestone. A total of 111 samples were extracted from the cores for laboratory sediment analyses and testing. The surficial deposits are roughly eight meters thick and made up of upper and lower clean-sand hydrostratigraphic layers (S1 and S3, respectively) separated by a lowpermeability layer of clayey sand (S2). Also, a discontinuous low-permeability layer of clayey sand (S4) lies between S3 and the top of limestone. Equivalent hydraulic conductivity values for the S2 and S4 clayey layers (0.01 and 0.1 m/day respectively) are significantly less than those of the S1 and S3 sand layers (2 and 1 m/day respectively). Significant confinement between the surficial and Upper Floridan aquifers by means of a laterally extensive dense-clay unit immediately above the limestone is consistently reported elsewhere in the region, but was not encountered within the wetland. Partial confinement is apparently the result of low-permeability layers within the surficial deposits alone. Results of ground-penetrating radar and vertical head difference measurements suggest the presence of buried sinkhole features which perforate the low-permeability S2 layer and create preferred pathways for flow or karst drains.

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vi Comparison of results between laboratory sediment testing and a site-scale aquifer performance test (APT) suggest that the primary mechanism for drainage during the APT was by vertical percolation through the S2 layer while flow through karst drains was minimized. In this case, calculated leakances based on laboratory sediment testing are most accurate in approximation of effective leakance. It is predicted that as water table stages rise within the wetland, effective leakance will increase as flow toward karst drains becomes the more dominant mechanism for drainage. As a result, calculated leakances based on direct laboratory sediment testing are a decreasingly accurate approximation of effective leakance.

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1 INTRODUCTION Background This report is based partially on data collected during an investigation conducted by graduate students from the Hydrogeology Laborat ory of the Geology Department at the University of South Florida (USF). The titl e of that study is The Development of a Conceptual Hydrogeologic Model from Field and Laboratory Data of the North Lakes Wetland, Phase II Results (Langevin et al., 1998). For convenience, the 1998 report is referred to throughout this thesis as the North Lakes report. The North Lakes report was prepared by USF under contract as part of a long-term investigation by the Southwest Florida Water Management District (SWFWMD) in conjunction with Hillsborough County. The purpose of the investigation was to examine methods of returning reclaimed water to original sources of heavy withdrawal in northwest Hillsborough and northeast Pinellas Counties. The North Lakes wetland has experienced serious declines in water level due to belowaverage rainfall and over pumping from nearby well fields. The North Lakes report was the second phase of a site-specific research project that focused on determining the feasibility of using reclaimed, highly-treated wastewater to artificially re-hydrate the stressed North Lakes wetland in an effort to supplement natural recharge to the Floridan aquifer in the area. One recommendation of the Phase I report was to conduct an extensive field investigation to develop a conceptual model of the hydrogeology at the site (Phase II). The conceptual model was later used to produce predictive groundwater flow and solute transport models of the flow system and make recommendations on how to proceed with the re-hydration process (Phase III). Development of the conceptual model required a detailed evaluation of the hydrogeologic framework of the groundwater-flow system as well as the hydraulic parameters that control recharge to the Upper Floridan aquifer.

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2 Purpose The purpose of this thesis consists of three primary objectives. The first is to delineate boundaries and characterize the hydrostratigraphy of the unconsolidated surficial deposits overlying more-permeable limestones of the Upper Floridan aquifer at the North Lakes wetland using laboratory sediment characterization and statistical techniques. Means of characterization include lithologic coring and descriptions, statistical grain-size distribution analyses, and both constant and falling-head soil permeameter testing. The second goal is to calculate equivalent values of vertical hydraulic conductivity (KVeq) and leakance for low-permeability hydrostratigraphic layers to compare with effective leakance estimates derived from aquifer performance testing. The third goal is to evaluate the hydrostratigraphic and hydrologic information gathered from this study and the original North Lakes investigation to locally conceptualize groundwater migration and recharge within the wetland. Examined data ty pes include water-level elevations at the time of the study, aquifer-performance testing, lithologic descriptions, laboratorysediment analyses, and geophysical logging. Specific Objectives Complete a detailed examination and description of all cores. Perform complete wet and dry sieve/settling tube grain-size distribution analyses on 111 sediment samples from eight cored sites collected at the North Lakes wetland. Qualitatively define the lithostratigraphic layering of the surficial deposits based on sample descriptions and statistical soil parameters determined from grain-size distribution analyses (ie. median and effective grain size, sorting coefficient, and porosity). Perform permeameter testing on all samples to directly measure values of hydraulic conductivity using a constant or falling-head apparatus and statistically delineate the hydrostratigraphic framework of the surficial deposits. Calculate equivalent vertical hydraulic conductivity (KVeq) values for each of the hydrostratigraphic layers utilizing a re lationship between layered heterogeneity and anisotropy after Fetter (1994). Calculate leakance coefficients at each cored location, and compare to effective leakance values generated from results of the site-scale Upper Floridan aquifer performance test (APT).

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3 Utilize results from both this study and the original North Lakes investigation to locally assess mechanisms controlling surficial groundwater migration and recharge within the wetland and evaluate regional significances.

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4 STUDY AREA Location The North Lakes Wetland is a cypress wetland located at the North Lakes Park approximately one mile east of Dale Mabry Highway in Northwest Hillsborough County, Florida (Figure 1). The wetland is approximately 65,000 m2 or 6.5 hectares (16 acres) in area and is located within the perimeter of the North Lakes County Park (Figure 2). The wetland lies in the NE of the NE of Section 27, Township 27S, and Range 18E within the Sulfur Springs topographic quadrangle. Differentially corrected GPS coordinates for the FMW-2 monitor well located near the center of the project area are 28o 06 30.94 N latitude and 82o 29 12.73 W longitude at a surface elevation of approximately 55 feet (16 m) above the National Geodetic Vertical Datum of 1929 (NGVD). The nine Upper Floridan and 30 surficial aquifer monitor wells at the wetland have been included into the SWFWMD ROMP network, and the site is designated as ROMP 65 North Lakes in the ROMP file located at SWFWMD. The well site is located in the Northwest Hillsborough Political Basin of the SWFWMD. Physiography The North Lakes wetland is located near the southern end of the North Gulf Coastal Lowlands physiographic province, a part of the Mid-Peninsular zone of the Florida peninsula (White, 1970). The wetland is roughly 4 kilometers (2.5 miles) due west of the western edge of the Zephyrhills Gap, which is the southernmost drainage outlet from the Western Central Florida Valley Province. The Zephyrhills Gap encompasses much of the Hillsborough River drainage basin and is characterized as an erosional basin with a thin sand and clay layer overlying many kars t features, resulting in many sinkholes and springs. Poorly-drained swamps and mars hes support cypress and wetland vegetation (Kelley, 1988).

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5 352000 352500 353000 353500 354000 354500 3109600 3110100 3110600 3111100 3111600 00.751.5 0.375 Kilometers 00.51 0.25 Miles Locator Map Section 21 Wellfield North Lakes WetlandB r u s h y C r e e kI n t e r c e pt o rC a n a lDale Mabry HWYLake Heather Figure 1. Location of North Lakes wetland and the Section 21 well field.

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6 353700353750353800353850353900353950354000354050354100UTM East (m) 3109800 3109850 3109900 3109950 3110000 3110050 3110100 3110150 3110200 3110250 3110300 3110350 3110400 UTM North (m) Split-spoon site Vibracoresite SITE 5 (FMW-5) SITE 1 (MW-1) SITE 2 (FMW-2) SITE 3 (MW-5) SITE 4 (FMW-4) SITE 6 (VC-1) SITE 7 (VC-2) SITE 8 (VC-3) SITE 9 (VC-4) North Lakes wetland boundary (berm) North PondI n t e r c e p t o r C a n a ltennis court reclaimed water storage tanks park center retention pond wetland neighborhoodbermweir 1 2 3 4 5 Location of karst features visible at land surface 0100 50Meters FMW-6 Figure 2. Study area with lithologic sampling locations and surface-visible karst features.

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7 Climate and Hydrology The climate of Hillsborough County is described as humid sub-tropical with high mean annual rainfall and temperatures. Kelley (1988) states that rainfall in the county varies both seasonally and annually in the county with the wet season running generally May through October. Annual rainfall in Hillsborough County averages 129 centimeters (50.8 inches). Recharge to the surficial aquifer in the region occurs primarily through infiltration of rainfall and inflow from lakes and ponds. Losses result from evapotranspiration and leakage to the Upper Floridan aquifer below. Locally, surfacewater drainage of the wetland has been altered through the construction of an interceptor canal, weir, North Pond, and a berm (Figure 2). The interceptor canal runs along the northern edge of the wetland and continues westward past a weir to Lake Heather and eventually connects with Brushy Creek on the west side of Dale Mabry Highway. The canal was constructed in 1960 with the intent of controlling potential flooding from the wetland to nearby residential areas. The canal may inadvertently have contributed to lowering of surficial groundwater levels in the wetland by providing an artificial route of discharge for surface water. In an effort to offset dehydration of the wetland attributed to heavy groundwater withdrawals in the region, a weir was constructed to dam westward-flowing water along the canal from the east and induce flooding in the wetland and a one-meter high berm was constructed around the rest of the wetland to prevent flooding of the park and other surrounding areas. The plan was unsuccessful due to low surface water flows from the east. Ironically, during wet seasons, excess water from Lake Heather which backs up in the canal is essentially blocked from entering the wetland by the weir. The interceptor canal remained completely dry east of the weir during the entire course of this investigation. Geologic and Hydrogeologic Setting General The geology of Hillsborough County is generally described as Pliocene to Recent age undifferentiated clastic sequences of medium to fine-grained quartz sands, with varying amounts of silt, clay, shell, and marl ranging in thickness from about 3 to 27 m (10 to 90 ft) overlying Tertiary carbonates and clay s deposited during higher stands of sea level (Kelley, 1988). The Tertiary carbonates, mainly limestones and dolostones containing

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8 significant marine fossils and fragments, make up the principal Floridan aquifer in central Florida (Miller, 1986). The Southeastern Geological Society's ad hoc Committee on Florida Hydrostratigraphic Unit Definition (SEGS, 1986) defines and describes three principal hydrostratigraphic units within Florida: the surficial aquifer system; the intermediate aquifer system or confining unit; and the Floridan aquifer system The surficial aquifer system is described as the unconsolidated to poorly indurated clastic permeable unit that is contiguous with land surface and is most often unconfined. Lower-permeability beds within this system may cause semi-confined or locally confined conditions in deeper portions of the system. The intermediate aquifer system or confining unit coincides with the top of laterally extensive and vertically persistent beds of much lower permeability that act to impede the exchange of water between the overlying surficial and the underlying Floridan aquifer systems. The term intermediate confining unit is applied when the unit is primarily confining sediments with little or no intermittent permeable beds as do occur in some southern areas (SEGS, 1986). The top of the Floridan aquifer system typica lly occurs where vertically persistent permeable carbonate rocks of the Floridan aquifer replace the low-permeability clastic layers of the intermediate aquifer system (SEGS, 1986). Geologic cross-sections (Kelley, 1988) show that in the northern half of Hillsborough County, the Miocene Tampa Limestone Member of the Arcadia Formation and the Oligocene Suwannee Limestone typically represents the uppermost geologic uni ts of the Upper Floridan aquifer. Throughout the west-central region of peninsular Florida, the Floridan aquifer is divided into the Upper and Lower Floridan aquifers which are separated by the Middle Confining Unit, a low porosity dolostone with intergranular anhydrite (Miller, 1986). Regional The North Lakes wetland is centrally located within a region identified by Parker (1992) as hydrogeologically similar with respect to characteristics of the surficial aquifer and upper confining unit of the Floridan aquifer (Figure 3). This region includes northern Hillsborough and Pinellas Counties, and all of Pasco County, but excludes the

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9 B R O O K S V I L L E R I D G EP O L K U P L A N D W E S T E R N V A L L E Y S O U T H E R N G U L F C O A S T A L L O W L A N D SN O R T H E R N G U L F C O A S T A L L O W L A N D SAlafia RiverP i t h l a c h a s c o t e e R i v e r H i l l s b o r o u g h R i v e rMANATEE CO. HILLSBOROUGH CO. PASCO CO. HERNANDO CO.POLK CO.PINELLAS CO. 0510 2.5Miles 0816 4KilometersEXPLANATION: North Lakes Study Area Parker (1992) Study Area Major Wellfields Physiographic Provinces After White (1970) Region HydrogeologicallySimilar to Study Areas after Parker (1992)Section 21 Wellfield Figure 3. Physiographic provinces, study areas, and hydrogeologically similar region after Parker (1992).

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10 Brooksville Ridge and the Gulf Coastal Lowlands north of the Pithlachascotee River. Parker addresses three main hydrostratigraphic units in this region: the surficial aquifer, a leaky upper confining unit, and the Floridan aquifer. Hydrogeologic isopach maps developed by Ryder (1985) for west-central Flor ida show this region to coincide with the area where the Upper Floridan aquifer is overlain by less-permeable beds of the intermediate confining unit (ICU) but north of the approximate limit where the intermediate confining unit contains intermittent permeable deposits that make up the intermediate aquifer system (IAS). Leakance and storativity values determined from aquifer performance tests at the Section 21 well field roughly a mile from the study area suggest moderately confined conditions (SWFWMD, 2000). North of the Pithlachascotee, the permeable limestones of the Upper Floridan aquifer tend to crop out at or near land surface while the intermediate confining unit essentially pinches out, leaving the Upper Floridan aquifer generally unconfined (Ryder, 1985). North of the Alafia River, which runs east to west across the center of Hillsborough County, clayey sands and clays between the surficial sands and limestones of the Upper Floridan are likely weathering remnants of the Miocene-age Peace River Formation (Kelley, 1988). Isopach maps by Scott (1988), however, show that the Peace River Formation is absent in the northwestern portion of Hillsborough and thickens to the south. Although the northwestern portion of Hillsborough is outside the mapped extent of the Peace River Formation and its Bone Vall ey Member, it is possible that Peace River or other Hawthorn Group sediments at one time occurred in the study area and have been eroded away. Scott (1988) shows the current areal extent of the Bone Valley Formation to cover the eastern one-third of Hillsborough County and notes that outside this area, individual beds can occur scattered and inter-fingered within Peace River Formation sediments. Throughout a roughly 15-square-mile study area in northwest Hillsborough, which also encompasses the North Lakes wetland, Sinclair (1974) indicates the presence of a dense, plastic, greenish-gray clay averaging 1.2 meters (4 feet) thick that directly overlies the Tampa Limestone throughout his study area in northwest Hillsborough. Sinclair (1974) presents strong evidence including high gamma radiation counts, crenulated bedding planes due to slumping, and the occurrence of fresh chert to suggest

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11 this dense clay is a weathered residuum of the Tampa Limestone. Carr and Alverson (1959) originally used similarities in sand and clay ratios to suggest that the dense clay was a weathering residuum of the underlying Tampa Limestone. They also attributed the high gamma radiation counts of the dense plastic clay unit to uranium-rich minerals concentrated by dissolution of the Tampa Limestone. Another suggested source for this concentration is through leaching of younger, phosphate-enriched Hawthorn Group sediments (i.e., Bone Valley Member of t he Peace River Formation) that may at one time have been present in this region. Sinclair (1974) states the surficial aquifer in northwestern Hillsborough County is made up of an upper fine sand unit overlying laye rs of clayey sand and sandy clay that gradationally decrease in permeability to a dense clay at depth, creating confinement between the surficial and the Floridan aquifer below. This hydrostratigraphic scheme of surficial deposits is similar to that described by Parker (1992), with the exception that Parker shows the dense-clay confining materials within his study area to be highly irregular and much more leaky due to persistent perforations by columns of sandy sediments filling ancient sinkholes. Sinclair (1974) reports that although recharge in this region occurs more rapidly through breaches of confinement, sinkholes occupy a small percentage of the total area of the region and therefore leakage across the confinement, although slower, probably contributes most of the total recharge to the Floridan. He does note that variations in thickness of clay and depth to the limestone surface are so great over short distances (ranges from zero to over six meters in Northwest Hillsboruough) that very close spacing of test holes would be necessary to actually delineate a pattern, and active sinkholes may exist that have not developed any surface expression. The wetland is located in a geologic region referred to as a covered-karst terrane characterized by high karstification of the limestone surface, frequently creating sinkholes that perforate confinement with sand-filled columns that influence the behavior of groundwater flow (Langevin et. al., 1998). Pa rker (1992) estimates that sinkhole-filling sand columns increase the average leakance and function as drains through which much of the recharge to the Floridan aquifer occurs. Stewart and Parker (as cited in Langevin et al., 1998) speculated that as much as 90 percent of the recharge to the

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12 Floridan aquifer may occur through sinkholes. Parker (1992) estimates the conduits represent an average of one to two percent of the total area of the leaky-confining unit throughout this region but can also be highly variable on a local scale based on the degree of karstification. The 9-hectare (22-acre) area of Parker's study is located on the University of South Florida ca mpus approximately 8.2 kilometers (5.1 miles) southeast of the North Lakes wetland. Local Hydrostratigraphic thickness data obtained from SWFWMD suggest that the surficial aquifer is approximately 8-10 m (28-30 ft) thick within the perimeter of the North Lakes Wetland (Langevin and Stewart, 1996). This agrees with the original data analysis of split-spoon core samples taken at North Lakes that show siliciclastic/limestone contacts ranging from approximately 8 to 10 meters below land surface. Also, generalized geologic cross-sections across Hillsborough County suggest surficial sands near the wetland directly overlie either Miocene-age limestones of the Arcadia Formation (Tampa Member) or Oligocene-age Suwannee Limestone (Kelley, 1988). Initial visual inspection of cores from the surficial deposits at the wetland lithology reveal four distinct and apparently homogeneous layers of sand with varying amounts of silt and clay overlying the top of the Tampa Limestone. No dense clay was observed between the surficial and Floridan aquifers. Five sinkholes are visible at land surface within the perimeter of the North Lakes wetland (Figure 2). An early test of the ground-penetrating radar equipment also revealed the presence of a buried sinkhole or sand column just outside the wetland perimeter. The surface-visible sinkholes appear to cluster somewhat in an east to west band across the central portion of the wetland. An earlier photolinear analysis was conducted by Langevin and Stewart (1996). Photolinears are linear features observed on aerial photographs that can sometimes be indicitive of subsurface features in underlying limestone such as fracture traces. The analysis suggested that the North Lakes wetland could be located at the intersection of two photolinears but their hydraulic significance was not further determined.

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13 PREVIOUS WORK Hydraulic Conductivity Hydraulic conductivity (K) is the capacity of a material to transmit fluid. It was first established as the constant of proportionality in the equation for Darcy's Law describing the movement of water through a porous medium. Later, Hubbert (as cited in Fetter, 1994) showed that this coefficient was a function of both the character of the porous medium as well as that of the fluid that passes through it. He accomplished this by experimentally varying the fluid density, vi scosity, and grain-size of the medium. The relationship he found between these properties and Darcys proportionality constant is expressed as g k g Cd K 2 where C is another dimensionless constant of proportionality, d is the mean grain diameter of the sand, represents the fluid density (water), is the viscosity of the fluid, and g is the gravitational acceleration. The terms g/ characterize the properties of the fluid while Cd2 is a function of the porous medium alone and is referred to as the intrinsic permeability, k. The constant C is influenced by other media properties that affect flow, apart from the mean grain diameter. These include the distribution of grain sizes, a shape factor of the grains, and the porosity, which is an integrated measure of the packing arrangement of the soil grains (Freeze and Cherry, 1979). It is obvious that the permeability in a rock or sediment would be influenced by changes in porosity, grain size, grain shape, and degree of sorting. In general, coarse sediments are more permeable than fine sediments because of the large open pores that are interconnected. Masch and Denny (1966) concluded that permeability values increase with increasing values of the d50 or median grain-size diameter of a sample distribution. Sands and gravel therefore have high permeabilit y values. Clays however are typically quite impermeable despite having high porosities. Pore throat diameters in clays are

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14 usually very small as is the degree to which the pores are interconnected, both of which inhibit flow (Davis, 1992). Numerous tests have shown that the porosity of natural materials increases with the decrease of the uniformity coefficient = d10/d60 (Vukovic et al., 1992). Istomina (1957, as cited in Vukovic et.al., 1992) was the first to establish the interrelationship between porosity and the uniformity coefficient that is further substantiated by results from other author s who experimented with similar sands. However, significant deviation was reported in the case of materials comprising clayey fractions. Poor sorting as indicated by either an increased uniformity coefficient (Fetter, 1994) or by an increased standard deviation in grain-size distribution of a sample (Davis, 1992) will tend to lower permeability because of the reduction of pore space as smaller grains fill voids between larger fragments. As stated earlier, hydraulic conductivity can be measured directly with a variety of different methods, including permeameters, slug tests, tracer studies, and aquifer performance tests. Davis (1969) concluded t hat hydraulic conductivity is a parameter that can vary by over 13 orders of magnitude for a wide range of geologic materials. Tests using these methods have been performed in the wetland at North Lakes and have produced data for the surficial as well as the Floridian aquifer at the site. Aquifer Heterogeneity/Anisotropy When trying to determine the overall hydrogeologic response of an aquifer, it is important to first consider the nature of the aquifer properties that exist within individual units as well as how they relate to the rest of the system as a whole. If the hydraulic conductivity K of a particular unit is independent of its position within the unit, the unit is said to be homogeneous. If K is dependent upon its position within the unit, it is considered heterogeneous. Also, if K is independent of the direction in which it is measured, the unit is said to be isotropic. If K varies based on the direction it is measured within a unit, it is considered anisotropic. In some cases, a hydrologic system may exhibit what is called layered heterogeneity in which smaller, individually homogeneous units of varying permeabilities are vertically stacked. In this type of layered configuration, it has been shown that there is a relationship between layered heterogeneity and anisotropy that allows the computation of the equivalent vertical and horizontal conductivities for the entire sequence. When

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15 considered as a whole, a system comprised of several individually homogeneous layers (layered heterogeneity) behaves as a singl e homogeneous, anisotropic layer (Freeze and Cherry, 1979). Freeze and Cherry (1979) describe how this relationship is used to evaluate an equivalent vertical or horizontal K value by first considering vertical flow across the layering. Because the specific discharge perpendicular to the layers, v, is constant across the entire system, it must also be constant across each layer within the system. If we Iet h1 represent the head loss across the first layer, and h2 across the second, and so on, then the total head loss across all layers is h = h1+ h2++ hn. In the same way, let d represent the total thickness of the system where d = d1+d2++dn. KVn will represent the vertical hydraulic conductivity for each respective layer. From this and Darcy's Law: d h K A Q v d h K d h K d h K d h K vVeq n n Vn V V 2 2 2 1 1 1 where KVeq represents the equivalent vertical hydraulic conductivity across the entire system of layers. Solving for KVeq and replacing h leaves: n Veqh h h vd h vd K 2 1 Vn n V VK vd K vd K vd vd 2 2 1 1 or n i Vi i VeqK d d K1 Now considering flow parallel to layering, the discharge Q through a unit thickness is the sum of the discharges through the layers. h represents the head loss over a horizontal distance l. Specific discharge v would be: n i Heq i Hil h K l h d d K v1

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16 or n i i Hi Heqd d K K1 where KVeq and KHeq now represent the equivalent vertical and horizontal hydraulic conductivities respectively for the entir e system of layered homogeneous and isotropic units described earlier (layered heterogeneity) that are hydraulically equivalent to those of a single homogeneous but anisotropic formation. It is not uncommon for layered heterogeneous formations to exhibit anisotropy ratios (KV/KH) on the order of 10-2 or smaller (Freeze and Cherry, 1979). Leakance As discussed earlier, the prevailing hydrologic conceptualization of this region consists of unconsolidated surficial deposits separated by a clay layer from underlying permeable limestone. The assumption that the confining units above and below confined aquifer systems are completely impermeable (aquiclude) is rarely true. More often than not, adjacent low-permeability units can both store and slowly transmit water from one aquifer to another making it a leaky confining unit (aquitard). In a thesis by Parker (1992), several leakance-related terms were defined. These definitions were applied in this thesis and are as follows: leakage Flow of water through a confining unit. The rate of leakage or leakage flux may be expressed as a volume of water per time unit through a specified area. leakance A measure of the resistance to leakage through a confining unit bounding an aquifer; the vertical hydraulic conductivity divided by the thickness, KV'/b', dimensions (length/time)/length or time-1. Leakance is defined assuming vertical leakage through a horizontal confining unit. The average leakance may be dominated by perforations or fractures through the confining layer. effective leakance The resistance to leakage through a confining unit considering the horizontal and vertical components of the flow paths from the source aquifer to the receiving aquifer. The term is applied when the value of the effective leakance may differ from the value calculated assuming only vertical flow, and when the value may vary with changing hydrologic conditions.

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17 stage-dependent effective leakance A direct relationship between the stage of the water table in the source aquifer and the value of the effective leakance. The relationship causes the effective leakance to vary depending upon the prevailing hydrologic conditions, from a maximum at the high water-table stage to a minimum at the low stage. apparent leakance the estimate of leakance determined from an aquifer performance test. The apparent leakance is a function of the total leakage into the aquifer induced by the cone of depression that results from the pumping stress. When it can be assumed that the aquifer is bounded below by an impermeable confining layer, then the apparent leakance determined from the test is the effective leakance of the upper confining unit within the area affected by the test. If the aquifer system has the characteristics which cause stagedependent effective leakance, then the apparent leakance will be a value within the range of the effective leakance. Parker (1992) concluded that stage-dependent effective leakance is a cause of seasonal variation in the rate of recharge to the Floridan aquifer and should be considered when interpreting aquifer performance tests.

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18 METHODS Drilling and Sampling Monitor wells were constructed at locations throughout the wetland. Several wells were grouped in nests to delineate the hydraulic gradient between the surficial and Upper Floridan aquifers. Each well nest includes both shallow and deep surficial monitors alongside an Upper Floridan monitor well. Lithologic samples for laboratory analyses were obtained from continuous split-spoon cores collected from land surface to the base of the unconsolidated surficial deposits during monitor well construction (Table 1) by contracted drillers at monitor well sites 1 through 5 (Figure 2) around the perimeter of the wetland, and from vibracores collected within the interior of the wetland at sites 6 through 8 (Figure 2). Table 1: Monitor-well construction specifications for lithologic sampling wells [elev. (m), elevation in meters NGVD] Open Open Site No. Well Type Casing Ground Interval Interval Screen (Well ID) Top Bottom Length elev. (m)elev. (m)elev. (m) elev. (m) (m) 1 (MW-1) 2" Deep Surficial Monitor Well 16.76 15.86 9.46 7.94 1.52 2 (FMW-2) 12" UFA Monitor Well 16.19 15.85 -12.5 -61.9 49.4 3 (MW-5) 2" Deep Surficial Observation Well 16.73 15.84 9.75 8.22 1.52 4 (FMW-4) 6" UFA Monitor Well 16.50 15.43 -12.0 -15.7 3.7 5 (FMW-5) 4" UFA Monitor Well 16.39 15.48 -11.5 -18.8 7.3 With the split-spoon method, a two-inch by two-foot split-spoon sampler was driven into the ground. The spoon is advanced with a 140-pound slide hammer attached to a cathead. The spoon is then retrieved, and the spoon is broken open for sample retrieval. Samples are described in the field and placed in core boxes for archiving and transport. Continuous samples are collected using the split-spoon until the water table is

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19 encountered. At that time, a 2 -inch inside diameter (ID) hollow-stem auger is advanced to the water table. Fresh water is pumped into the bore of the hollow stem auger to remove drill cuttings introduced while drilling. Once the cuttings are flushed, the split spoon is placed in the hollow-stem auger attached to N-type drill pipe and advanced to the bottom of the borehole. The drill pipe and assembly is then advanced 2 feet using a slide hammer, tripped out of the augers, and a sample is retrieved. This process is continued until consolidated bedrock is encountered and the sampling device reaches refusal. Some continuous cores of surficial deposits were collected using the vibracore method at sites in the interior of the wetland where no UFA monitor wells were constructed. Vibracoring was especially useful in providing an undisturbed sample of the shallow surficial aquifer deposits in wooded areas of the wetland that were inaccessible to drill rigs. The 3-inch vibracoring apparatus used for this study was loaned from the sedimentology laboratory at the University of South Florida. A report by Thompson et. al. (1991) provides information on the operation, extraction, transport, and processing of vibracored samples. The vibracore technique involves the driving of 3-inch diameter aluminum pipe into the ground by attaching the pipe to a vibrating steel boot. The boot is vibrated by rotation of eccentric weights in the gearbox. The vibration of the pipe enables it to penetrate the sediments while core is captured inside. A winch and steel tripod are then used to extract the pipe. One of the vibracoring attempts (Site 9, VC-4) met early refusal resulting in a very shallow and suspect core recovery. This core was removed from the study. The boxed cores were transported to a sedimentary geology laboratory for processing and analyses. The lithology and stratification of the cores were examined and described in detail prior to extraction of samples for laboratory analyses. Representative samples (0.1 m) were extracted from each apparent lithologic unit differentiated during examination of the cores. Samples derived from split-spoon coring during well construction were named after each respecti ve monitor well followed by a letter (MW1-a, MW1-b, etc.). Similarly, samples that originated from vibracoring are denoted as VC1-a, VC1-b, etc.

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20 Grain-size Analyses In unconsolidated materials, hydraulic conductivity is highly dependent upon the size and shape of the component grains and their degree of sorting. The determination of grain-size distribution parameters for a given sample can be used to help characterize the geologic and hydrogeologic nature of the sediment. Results from grain-size analyses are in the form of grain-size distribution curves from which statistical parameters of the distribution can be determined such as the effective and median grain size. In this study, grain-size analyses were completed on the split-spoon samples of surficial deposits retrieved by the contract driller at or next to monitor well locations. In addition, grain-size analyses were run on vibracore samples from three sites. A total of 111 samples were analyzed from eight sites (Figure 2). A step-by-step description of all standard procedures applied during grain-size analyses for this study is presented in Appendix A. A Fortran program, MVASKF, provided as part of a water resources publication (Vukovic et. al., 1992), was very helpful in processing the large quantity of grain-size distribution data. The program computed grain-size statistical parameters based on inputs of raw grain-size distribution data. The program outputs also provided hydraulic conductivity and porosity estimates by applying ten of the more commonly used empirical formulas for estimating K from grain-size distributions that are discussed in detail in the Vukovic publication. Permeameter Testing Direct measurements of hydraulic conductivi ty for the 111 samples were measured in the laboratory using both constant and falling-head permeameters. In a constant-head permeameter test, a sediment sample is enclosed between two porous plates in a cylindrical tube, and a constant-head differential is set up across the sample. The head gradient across the sample forces water to flow through the porous matrix and the volumetric flow rate is measured. This measured discharge rate is then used to calculate a value of K for the sample using a form of Darcy's Law. In a falling-head permeameter test, a sediment sample is en closed in the same type of sample chamber

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21 but a water-filled tube is attached to one end of the permeameter and the change in head with time is measured as water drains from the tube through the sample chamber. This rate is used to calculate K for the sample. A constant-head permeameter is used for loose unconsolidated sediments such as sand or gravel as opposed to a falling-head permeameter, which is best suited for sedim ents that are more cohesive or clayey (ASTM, 1972). Klute (1965a, as cited in Freeze and Cherry, 1979) notes that the constant-head system is better suited for samples with values of hydraulic conductivity greater than approximately 0.1 m/day (0.3 ft/day) where as a falling-head system is better suited for samples of lower conductivity. In order to obtain more representative permeam eter results, it is desirable to collect undisturbed samples. Samples collected for both permeameter testing and grain-size analyses for this study were collected from CME drill rig split-spoon cores and therefore were mostly un-disturbed during extraction. When sediments are repacked into the sample chamber, they are typically assumed to only approximate the value of hydraulic conductivity for undisturbed materials. Fetter (1994) states that values of hydraulic conductivity for repacked sediments depend on the density to which the samples are compacted. A step-by-step description of the standard laboratory procedures applied during permeameter testing for this study is presented in Appendix B. Geophysical Methods Borehole geophysical logs were completed as part of the original North Lakes investigation in all Floridan and selected deep surficial monitor wells. An electromagnetic induction multi-tool equipped with a passive gamma tool was used to measure the bulk conductivity/resistivity as well as the natural gamma radiation of the formation as a qualitative indicator of lithology. Electromagnetic (EM) methods work by inducing an electric current through formation materials immediately surrounding a well bore and are well suited for locating relatively conductive materials such as clays and resistive materials such as sand or limestone. EM induction tools measure the bulk conductivity of the formation surrounding the borehole and will operate through PVC casing and in air, water, or mud-filled wells. Gamma radiation is emitted by radioactive isotopes found in some geologic materials, principally 40K, and can be useful in locating materials such as phosphates, organics, and many clay minerals. Two geophysical logging suites were run at each monitor well nest (sampling sites 1 through 5). One

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22 suite was run in the deep surficial monitor that spans most the length of the unconsolidated surficial deposits while a second suite was run in the Upper Floridan monitor roughly 20 meters into the top of limestone. Appendix C contains the geophysical log suites run at sites 1 through 5. Ground-penetrating radar (GPR) was used within the wetland in an attempt to identify subsurface features such as buried sand-filled columns caused by sinkholes. GPR works by transmitting electromagnetic energy in to the ground that typically reflects back to a receiver in association with variations in sediment types. Over 30 GPR transects were run along straight paths cleared within the wetland. Every 25 cm, the transmitter and receiver antennas were placed on the ground spaced one meter apart and a radar pulse was initiated. Stacking the results of each pulse reduces the effect of background noise but also slows the survey process. Stacking each pulse 128 times resulted in low background noise at an efficient survey rate. One limitation of the GPR method is that the energy signal cannot penetrate far into sediments with high values of electrical conductivity such as clay or groundwater.

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23 RESULTS Initial lithologic inspection of the cores suggest that the unconsolidated surficial deposits overlying the limestones of the Upper Floridan Aquifer can be divided into four apparent lithostratigraphic layers named in this study S1 through S4. Upper and lower clean sands (S1 and S3 respectively) were separated by a clayey sand to sandy clay (S2). Discontinuous clayey sand (S4) below the S3 sand was found at four of the eight sampling sites. After thorough examination and description, thinner lithologic beds (generally 0.5-0.6 m thick) were identified that sub-divide these layers based on more subtle differences in texture, consolidation, color, or composition. Representative samples (111 samples, 0.1 m thick) were extracted from each observed lithologic bed for laboratory grain-size distribution analysis and permeameter testing. Laboratory Analyses Plots of cumulative frequency curves and frequency histograms from grain-size distribution analyses for each of the samples are presented in Appendix D. Typical cumulative frequency curves for clean sands, such as MW1-a (Appendix D), begin with 100 percent finer grain-size diameter of very coarse sand at -1 phi units or 2 mm. The bulk of the sample, represented by the steepest part of the curve, falls in the +2 to +4 phi size range (250-62 m) or fine to very fine sand. +4 phi (62 m) represents the upper limit of silt and clay-sized particles (mud) based on the Wentworth grain-size classification scale (re-printed in Davis, 1992). The percentages of mud in these samples are mostly at or less than five percent. Some curves, however, as shown in sample FMW2-h (Appendix D), contain higher clay and silt fractions. The mud content of these samples is typically between 10 and 20 percent. The sample curves do not reach ten percent finer within the minimum grain-size detection limits of the hydrometer (these curves must reach ten percent finer at some point smaller than +9.5 phi units). This signifies that more than ten percent of the sample is made up of clay-size particles. The value of d10 (effective grain size) for this type of curve was assumed as the smallest

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24 grain-size diameter detected of +9.5 phi units or 2 m, which is within the upper limit of clay-size particles. Certain statistical sediment parameters can be read straight from the cumulative frequency plots but instead, a public-domain software Fortran program (Vukovic et. al., 1992) enabled quick computation of these parameters for each sample from input files of cumulative percent finer versus grain-size diameter. Calculated parameters included median grain size, effective grain size, and uniformity coefficient. The median grain size represents the grain size diameter in the middle of the distribution or the grain size of the 50th percentile or d50 (Davis, 1992). In other words, the grain size where 50 percent of the sample mass is finer. The 10th percentile or d10 of a sample is commonly, but not always referred to as the effective grain size. The uniformity coefficient or Cu is a measure of the degree of sorting in a sample distribution and is the ratio of d60/d10 (Fetter, 1994). A sample with a uniformity coefficient less than 4 is considered well sorted while a coefficient more than 6 is considered poorly sorted (Fetter, 1994). Porosity, n, can be approximated using an em pirical relationship by Istomina (1957 as cited in Vukovic et.al., 1992) based on the uniformity coefficient. The results of the laboratory grain-size distribution analyses for all samples are summarized in Appendix E. The table in Appendix E provides sample and lithologic bed depths as well as five statistical soil parameters calculated for each sample. Data collected during laboratory permeameter testing for all samples grouped by site are presented in Appendix F. Included are the laboratory measurements recorded during each test depending on the test type (constant or falling-head design). The results of the laboratory permeameter analyses for all samples are presented in Appendix G. The table provides sample and lithologic bed depths as well as the permeameter-measured K and log K values for each sample. The geometric means of K for each of the layers show that the S1 and S3 sand layers are roughly two orders of magnitude greater than those of S2 and S4 clayey sand layers. The geometric mean of K for the S1 and S3 layers are both 2 m/day while the geometric mean of K for the S2 and S4 layers are 0.01 and 0.04 m/day respectively.

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25 A ternary plot showing the sand, silt, and clay percentages of all samples (Figure 4) illustrates that the surficial deposits are primar ily comprised of mostly similar sands with varying amounts of silt and clay. The S1 and S3 layers both range between 90 and100 percent sand content with less than 10 percent silt and clay. Both the S2 and S4 layers, however, range mostly between 80 and 90 percent sand, 0 and 10 percent silt, and 10 to 20 percent clay. Also, hand-drawn contour s of permeameter-derived K are sketched on the diagram. Expectedly, the contours show that K decreases with increasing silt and clay content. % silt % sand % clay 90 10 90 80 20 80 70 30 70 60 40 60 50 50 50 40 60 40 30 70 30 20 80 20 10 90 10 0.1 S1 S2 S3 S4 1 .1 .01 .001 K contour Figure 4. Ternary plot of sand, silt, and clay percentages for all samples grouped by lithostratigraphic layer.

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26 Summary statistics for laboratory analyses results (Table 2) show percentile-based measures of center (median) and variability (interquartile range). A percentile represents the percent of a data set less than or equal to a particular observation. Percentile measures are resistant estimators in that they are not strongly affected by outliers (Helsel and Gilroy, 2006). Outliers tend to dominate the equations for more traditional measures of center and variability such as mean, variance, and standard deviation. These measures are more appropriate with measures of mass and Table 2: Summary of textural and hydraulic parameters within litho-stratigraphic layers (S1 through S4) [mm, millimeters; m/day, meters per day] effective uniformity median estimated grain size coefficient grain size porosity d10 d60 d60/d10 d50 n K (mm) (mm) (mm) (m/day) S1 25th percentile (d25) 0.1 0.1 1 0.1 0.4 1 75th percentile (d75) 0.1 0.1 2 0.1 0.5 3 interquartile range (d75 d25) 0.01 0.01 0.2 0.01 0.01 2 median (d50) 0.1 0.1 2 0.1 0.5 2a S2 25th percentile (d25) 0.001 0.1 81 0.1 0.3 0.003 75th percentile (d75) 0.001 0.1 93 0.1 0.3 0.04 interquartile range (d75 d25) 0.0001 0.01 11 0.01 0.01 0.04 median (d50) 0.001 0.1 88 0.1 0.3 0.01a S3 25th percentile (d25) 0.1 0.2 2 0.1 0.4 1 75th percentile (d75) 0.1 0.2 2 0.2 0.4 3 interquartile range (d75 d25) 0.03 0.02 1 0.02 0.02 2 median (d50) 0.1 0.2 2 0.1 0.4 2a S4 25th percentile (d25) 0.001 0.1 7 0.1 0.3 0.02 75th percentile (d75) 0.01 0.1 106 0.1 0.3 0.2 interquartile range (d75 d25) 0.01 0.01 99 0.05 0.1 0.1 median (d50) 0.003 0.1 60 0.1 0.3 0.04a a = calculated value of K is the geometric mean rather than median value

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27 volume, when it makes sense to sum up individual estimates. Percentile measures on the other hand, are more appropriate when searching for the most typical value of a dataset with minimal effect of data outliers. Both textural and hydraulic parameter interquartile ranges for samples within the same layer are small relative to quartile values for the same parameter, suggesting homogeneity within individual layers (Table 2). Sediment parameters show more variability between adjacent layers. Medians of textural parameters which are associated with the middle of the grain size distributions (d50 and d60) remain nearly identical from one layer to the next, which primarily correspond to the more abundant, sand-size portion of the samples. Medians of effective grain sizes (d10) however, which correspond more with the silt and clay fractions of the sample, show distinct statistical differences between adjacent layers. Median values of effective grain size are two orders of magnitude smaller in the S2 and S4 layers (0.001 and 0.003 mm respectively) than in S1 and S3 (both 0.1 mm). Median values of uniformity coefficient (Cu = d60/d10) or sorting, are similar between S1 and S3 just as they are between S2 and S4 (Table 2). The uniformity coefficient for the clean sands associated with S1 and S3 both have a median value of 2 (Cu < 4 is considered well sorted), whereas the median values of Cu for the poorly sorted clayey sands of S2 and S4 are 88 and 60 respectively, meaning the pairs differ from each other by more than an order of magnitude. Comparison of percentiles for effective grain size and sorting between S2 and S4, show that the silt and clay-size fraction of the S2 layer is higher than in S4. As with effective grain sizes, the geometric mean values of K from permeameter testing also show two-order-of-magnitude decreases between well-sorted sands of S1 and S3 (2 m/day) and poorly-sorted clayey sands of S2 and S4 (.01 and .04 m/day respectively). The geometric means were calculated in Table 2 in place of the median values because hydraulic conductivities within a given uni t typically exhibit lognormal distributions (Fetter, 1994). If the logs of data are normally distributed, the geometric mean is a good representation of a typical value of K for a particular hydrologic unit (Helsel and Gilroy, 2006).

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28 Table 2 and Figure 4 show that relatively sma ll increases in silt and clay content as evidenced by decreases in effective grain size of otherwise similar sands, can have substantial effects on permeability. Bear (1972) states that particle-size distribution has a significant effect on the porosity of sediments as smaller particles occupy more of the space formed between larger particles. It is apparent from the table that the main factor controlling the textural differences between samples from different layers is primarily a function of the silt and clay content. Sand compositions within all layers are similar, but the layers differ primarily with respect to the abundance of fine-grained particles. Fetter (1994) states that K values frequently vary by more than two orders of magnitude within the same hydrogeologic unit. K variation within the S1 layer ranges from a minimum value of 0.2 m/day, to a maximum value of 7 m/day, by more than an order of magnitude or by a factor of 35. The K variation within the S2 layer ranges from 0.0001 to 0.4 m/day, by more than 3 orders of magnitude or by a factor of 4000. The K variation between these two layers, however, ranges from 0.0001 to 7 m/day, or by a factor of 70,000. Domenico and Schwartz (1998) states that if the K variation within a layer is much smaller than the conductivity differences between layers, it can be assumed that each layer is homogeneous and isotropic. Hydrostratigraphy The following provides summarized hydrostratigraphic characterizations for each layer in the order they were encountered from land surface. Detailed diagrams of the conceptual hydrogeology developed for each of the eight individual core locations are presented in Appendix H. Isopach maps of each hydrostratigraphic layer are presented in Appendix I. Contour lines in all of the isopach maps are clipped to exclude contouring outside of areas where actual data points exist. S1 The S1 layer is a clean, well-sorted, light gray to yellowish-orange, fine to very finegrained quartz sand (Wentworth classification, median diameter 0.062 to 0.250 mm). The silt and clay content for this layer ranges from 0.6 to 7 percent (Appendix D). The median values of median grain size, effective grain size (diameter corresponding to the 10% line on the grain-size distribution curve or d10), uniformity coefficient (sorting), and

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29 porosity from grain-size distribution analyses for all S1 samples are 0.1 mm, 0.1 mm, 2, and 50% respectively (Table 2). A uniformity coefficient less than 4 is considered well sorted (Fetter, 1994). The geometric mean of K values from permeameter analyses for all S1 samples is 2 m/day. The S1 layer is the uppermost hydrostratigraphic layer of the surficial deposits. S1 ranges from 2.29 to 2.74 m thick and averages 2.70 m (Appendix I.1). S1 is thinnest in the west and tends to thicken to the east, northeast, and southeast. S2 The S2 layer is a relatively thick and laterally continuous sequence of poorly sorted, greenish-gray to light brown, silty/clayey, ve ry fine-grained sand regularly containing thin beds of clay (Wentworth classification, median diameter < 0.125 mm) that separates the upper and lower clean sands of the surficial deposits (S1 and S3 respectively). Silt and clay content for this layer ranges from 10 to 31 percent (Appendix D). Silty/clayey sand was used to describe deposits that are chiefly sand but contain enough clay and silt to have a significant effect on permeability. The median values of median grain-size, effective grain size, uniformity coefficient (sorting), and porosity from grain-size distribution analyses for all S2 samples are 0.1 mm, 0.001 mm, 88, and 30% respectively (Table 2). A uniformity coefficient greater than 6 is considered poorly sorted (Fetter, 1994). The geometric mean of K values from permeameter analyses for all S2 samples is 0.01 m/day. The S2 layer ranges from 2.44 to 3.36 m thick and averages 2.93 m (Appendix I.2). Unlike S1, S2 is thinnest in the northeast portion of the study area (2.44 m) and generally thickens to the southwest. The thickest point (3.36 m) was cored at Site 2 in the center of the study area. S3 The S3 layer is a predominantly clean, well-sorted, yellowish-orange to white, fine to very fine-grained quartz sand with occa s ional inter-bedded lenses (approximately 0.3 m thick) of silty sand. The silt and clay content for this layer ranges from 1 to 14 percent (Appendix D). The median values of median grain size, effective grain size, uniformity

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30 coefficient (sorting), and porosity from grain-size distribution analyses for all S3 samples are 0.1 mm, 0.1 mm, 2, and 40% respectively (Table 2). The geometric mean of K values from permeameter analyses for all S3 samples is 2 m/day. The S3 layer ranges from 1.83 to 4.57 m thick and averages 2.23 m (Appendix I.3). S3 directly overlies the Tampa Limestone where S4 is not encountered. Similar to S1, S3 is thickest in the northeast portion of the site and thins to the southwest. S4 The S4 layer is a laterally discontinuou s sequence of poorly sorted, light brown to gray, silty, very fine-grained sand (Wentworth classification, median diameter < 0.125 mm). Silt and clay content for this layer is highly variable ranging from 5 to 58 percent in some samples (Appendix D). Thin, greenish-gray lenses of clay were found in the layer at some sites. Small limestone fragments (1-2 mm) were occasionally found near the base of S4. The median values of median grain size, effective grain size, uniformity coefficient (sorting), and porosity from grain-size distribution analyses for all S4 samples are 0.1 mm, 0.003 mm, 60, and 30% respectively (Table 2). The geometric mean of K values from permeameter analyses for all S4 samples is 0.05 m/day. The S4 layer ranges from 0.92 to 2.06 m thick and averages 1.26 m (Appendix I.4). The S4 layer of the surficial deposits was only encountered at four of the eight core locations (Sites 1, 2, 5, and 7) in the northeastern portion of the study area. It appears thickest in the center of the study area (Site 2) and is discontinuous in the south and west portion of the wetland. Apparent cavities were encountered during the split-spoon sampling just above the base of the surficial deposits. Based on the cores, it appears the cavities are at least partially filled with black, organic-rich clay and lim estone fragments with some white calcareous clay. It is unclear if the white calcareous clays were in the organic-rich clay cavities or below. Due to the soft, fluid texture of the material, advancement of the sampling chamber may have mixed the sample, not preserving the position or thickness of the two clays relative to each other. Sinclair ( 1974) observed similar organic-rich, black clays

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31 infilling cavities near the limestone surface at several drilling locations in his investigation. Tampa Limestone The Miocene-aged Tampa Limestone Member of the Arcadia Formation (Hawthorn Group) is the consolidated bedrock that underlies the surficial deposits at the North Lakes study area. The Tampa Limestone Member from drill cuttings at the site is primarily composed of sandy fossiliferous limestone with minor amounts of clay, dolomite, and phosphatic sand. Fossil molds and fragments were common throughout, including mollusks and the benthic foraminifera Sorites The abundance of Sorites decreases near the base of the Tampa Member. The limestone surface appears to slope downward from the southwest to the northeast (Figure 5). The Tampa Limestone is first encountered at an average depth of 9 to 10 m below land surface and continues to an average depth of 27 m below land surface. The thickness is roughly 19-20 m to the contact with the underlying Oligocene-age Suwannee Limestone Formation. The surface of the Tampa Limestone consists of highly weathered limestone and calcareous white clay mixed with we athered limestone fragments. The weathered surface appears relatively thin in split-spooned cores (approximately 0.05 m thick). The sampling device was advanced to refusal as far as possible into the limestone contact. It is possible that limestone fragments or chert fragments could have blocked sampler penetration prematurely, prior to seating on more consolidated material. The actual thickness for the white calcareous clay is not certain as cutting returns were poor in the upper portions of the limestone. Softer clays can potentially be washed out making it difficult to capture in borehole cutting returns. However, based on drill rig responses and driller's comments, the clay is thought to be less than 1 foot (0.3 meters) or so thick. The unconsolidated calcareous clays overlying co mpetent limestone in Parker's (1992) study are significantly thicker (2-2.5 m) and described as the parent and supporting material for the overlying residual dense clay. The calcareous clay was also reported to lack the competence to support fractures or voids. As a result, it was included as part of the overall confinement with the dense clay.

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32 Several secondary porosity features were noted during exploratory drilling within the upper portion of the Tampa Limestone at North Lakes. Dissolution cavities and/or fracture features were reported based on cuttings samples and regular losses of drilling fluid circulation during mud-rotary drilling. These dissolution features may result from concentrated drainage from above through preferred pathways in the weathered limestone that enlarge over time in the poor to moderately indurated limestone surface. Parker (1992) reported the upper surface of the Tampa Limestone in his study area to be highly irregular and deeply incised by fissures, grikes, and pipes from meters to tens of meters in depth. North-south and east-west stratigraphic cross-sectional diagrams of the study area (Figures 5 and 6) as gleaned from laboratory results of this study show that the S2 layer is generally uniform but thins slightly in the northern and eastern portions of the wetland. The S4 layer above the limestone dips both north and east and is absent at sites 3 and 4 at the southern and western edges of the wetland. S4 was thickest at site 2 in the central portion of the wetland. Geophysical Logs Natural gamma and electromagnetic (EM) conductivity/resistivity geophysical logs were run in all of the Upper Floridan and selected deep surficial monitor wells for the original North Lakes study to supplement interpreta tion of the hydrologic and hydraulic data. Appendix C contains the geophysical log suites run at Sites 1 through 5 in both the deep surficial and Upper Floridan monitor wells. Each site has one suite run in the deep surficial monitor to focus in on the surficial deposits and another suite run in the Upper Floridan monitor that penetrates well into the top of limestone. Within the surficial deposits, intervals of increased EM conductivity coincide with moderate natural gamma increases within t he clayey sands and sandy clays of the S2 layer at Sites 1 through 3 (Appendix C.1 and C.3). Sites 4 and 5 (Appendix C.4 and C.5) however show little change in gamma respons e to increased EM conductivity. Resistive peaks appear to correlate to the clean sands of the S3 layer when penetrated in the completed monitor wells. Because of the length of the tool, conductivity and resistivity measurements could not be made at depths less than three meters. In the Upper

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33 3109800 3109850 3109900 3109950 3110000 3110050 3110100 3110150 3110200 3110250 3110300 3110350 3110400UTM North (meters) 20 15 5 0 -5 -10 -15 -20 -25 -30Elevation ( meters NGVD)10 SITE 3 -61.9 SITE 2SITE 5 N S1 S2 S3 S4 Undifferentiated Surficial Sands and Clays Tampa Limestone Suwannee Limestone Figure 5. North-south stratigraphic cross-section of study area. 353700 353750 353800 353850 353900 353950 354000 354050 354100 354150 354200 354250 354300UTM East (meters)Elevation (meters NGVD)SITE 4 -61.9 SITE 2 SITE 1 Undiff. Surf. S ands and Clays N 20 15 5 0 -5 -10 -15 -20 -25 -30 10 Suwannee Limestone Tampa Limestone S1 S2 S3 S4 Figure 6. East-west stratigraphic cross-section of study area.

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34 Floridan monitor wells, strong gamma responses were recorded just below the limestone contact at all five sites. Sites 1 and 3 (Appendix C.6 and C.8) each have a second gamma spike roughly five meters below the top of limestone. Gamma peaks at thelimestone contact and below correspond very closely to increases in EM conductivity at all five sites. Gamma increases associated with the clayey S2 layer within the surficial deposits are much less pronounced relative to responses at or below the limestone contacts. Only 22 of the 30 GPR transects run in the wetland were successful. Since the radar signal cannot penetrate far into sediments with higher values of electrical conductivity, the radar response becomes attenuated at depth below the clean S1 sands within higher conductivity silt and clay material of the S2 layer. When a sinkhole-induced sand column with no surface expression is encountered, it is recorded by the GPR as an increase in the penetration depth where columns of S1 sands have ravelled into underlying secondary openings in the carbonate rocks. This settling process of mostly permeable sand overburden into developing cavities is termed "piping" (Tihansky, 1999). Thirteen of these buried sinkhole features were located along six of the 22 successful GPR transects.

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35 DISCUSSION Delineation of Hydrostratigraphic Layers Seaber (1988) states that a hydrostratigraphic uni t is a body of rock or soil of significant lateral extent, distinguished and characterized by its porosity and permeability. A hydrostratigraphic "unit" refers to a laterally continuous regional aquifer or aquitard. A hydrostratigraphic layer on the other hand, for the purposes of this study, refers to a section of rock or sediments that can be correlated across the study area with hydraulic characteristics that distinguish it from overlying and underlying units. The grouping of thinner lithologic beds into thicker hydrostratigraphic layers S1 through S4 was based on permeameter-determined K values sampled from each bed. Beds were assigned to particular hydrostratigraphic layers based on the direction their log-K values fell from the mean-log K value for all samples (Appendix G). Those samples with log-K values greater than the mean-log K were assigned to either the S1 or S3 layers. Samples were assigned to S2 and S4 layers if log-K values were less than the mean-log K. This method was applied to the permeameter-determined values of K because they are direct measurements of sample permeability as opposed to K values empirically estimated from grain-size distributions. In almost all cases, the hydrostratigraphic picks based on measured hydraulic properties (permeameter) were identical to lithostratigraphic picks chosen based on lithologic inspection and sediment texture characteristics alone. In three sample instances (FMW5-g, VC1-a, and VC3-f), beds were included in the S2 layer despite having a positive deviation from the mean. The reasoning for these exceptions is that not placing these lithologic beds in these layers produces unlikely vertical shifts in elevation of correlated layers. Also, the K values for these samples fall in close proximity to the mean, in other words they are just shy of having a negative deviation. Two samples (FMW5-org, and VC1-a) that were included

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36 in S1 despite negative deviation from the m ean are explained by the fact that these samples were collected directly from land surface which included high organic matter and leaf debris that affected grain-size distribution analyses and subsequent K estimation. It should be noted that all these exceptions were tested both ways and shown to have no significant effect on calculated leakances at those locations (ie. leakances were re-calculated with samples assigned to original layer choices for comparison). When sample values of log K are plotted versus elevation (scatterplot, Figure 7), the strong division of samples along the mean value of log K in alternating layers is evident. Samples from vertically adjacent layers consistently group on opposite sides of the mean-K value. The boxplot of log K plotted by individual layer (Figure 7) illustrates sample distribution characteristics for continuous data such as center, spread, skewness, symmetry, and outliers. The median which represents the center of the data (50th percentile, depicted as horizontal line across box) falls near the middle of the range in all four layers showing strong symmetry about the center with no outliers aside from the two land surface samples in S1 mentioned earlier (depicted as two asterisks on S1 boxplots). Symmetric data in boxplots typica lly signify a normal distribution. The fact that these are transformed (log) values of K that are strongly symmetric supports that K is log-normally distributed within each hydrostratigraphic layer, which is typical for single hydrogeologic units (Fetter, 1994). Another plot used to judge normality is the probability plot. The probability plot of log K (Figure 8) depicts how well data from individual layers follow a specific distribution. Data that plots as a straight line on a probability chart illustrates the normality of a distribution. Since the log K values for each layer plot as nearly straight lines, the individual layers demonstrate lognormal distributions of K. The pl ot also illustrates the similarity between the S1 and S3 sand layers as well as their disparity from the S2 and S4 layers. Summary statistics presented on the probability plot include results of the AndersonDarling normality test. A P-value >= 0.05 is considered a normal distribution. All four layers meet the criteria for normality using this test. The P-value for all S1 samples (0.057) is near this limit, but increases to 0.090 if you exclude the two outliers from this layer explained earlier. Also, it should be noted that the criteria for normality is not met

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37 log KElevation in meters 1 0 -1 -2 -3 -4 16 14 12 10 8 6 S1 S2 S3 S4C2 Layerlog K S4 S3 S2 S1 0 -2 -4 Mean = -0.5648 Figure 7. Scatterplot of permeameter-derived log K values versus elevation and boxplots of log K values grouped by hydrostratigraphic layer. log KPercent 2 1 0 -1 -2 -3 -4 -5 99 95 90 80 70 60 50 40 30 20 10 5 1 0.28400.3458350.7150.057 -2.0870.9131310.3220.514 0.25790.4342290.2070.854 -1.3630.613980.2880.523 MeanStDevNADP S1 S2 S3 S4C2 Figure 8. Probability plot of log K with 95 percent normal confidence intervals.

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38 when using untransformed or non-log values of K. These plots support the idea that the combined hydrostratigraphic layers (S1 through S4) represent a single, layered heterogeneous unit comprised of four vertically stacked, individually homogeneous layers of distinct textural and hydraulic properties. Geophysical Logs Larger peaks of gamma radiation were encountered below the limestone contact relative to that of the clastic S2 layer. In general, increased gamma responses that correlate with spikes in conductivity are associated with increases in clay content. Radioactivity as measured by the gamma tool may also reflect increases in organic or phosphatic mineral content of the deposits. Both phosphate and organics were identified as accessory minerals in the lithologic descriptions within the Tampa Limestone. Although conductivity increases do coincide with the highest gamma responses near the limestone contact at all five sites, clayey materials noted several meters further below the contact in the lithologic logs show increased EM conductivity kicks, but more subdued gamma responses at four of the five sites (1, 2, 4, and 5). This suggests that the increased gamma responses nearest the limestone contact may be the result of nonclay radioactive materials such as phosphate or organics. Sinclair (1974) made note of anomalous logs where both organic-rich clays and in one case, 20 feet of dense clay were penetrated with no appreciable gamma response demonstrating that natural gamma alone is not always a reliable indicator of lithology. A theory as to the source of increased natural gamma responses below the limestone contact within the wetland may be linked to secondary phosphate leached from previously overlying Hawthorn Group deposit s. Logs from Sinclair (1974) showed natural gamma responses in the dense clay immediately overlying the limestone throughout the region to be very high relative to overlying surficial sands and clays as well as underlying limestones. Carr and Alverson (1959) theorized that the source of these significant increases may be associated with concentration of secondary phosphatic material originally leached into the Tampa Limestone from younger, phosphate-rich Hawthorn Group units now eroded away. Scott (1988) suggests that Hawthorn Group sediments at one time blanketed much of west-central Florida. Subsequent dissolution of that limestone could then concentrate these materials in the remaining weathered residuum of dense clay. Since the dense-clay residuum is absent

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39 at the wetland, the increased gamma responses within the upper portion of the Tampa Limestone may represent leachate materials of Hawthorn origin not concentrated by dissolution of the limestone. The highest gamma responses within the upper Tampa limestone at the wetland were not as pronounced as those within the regional dense clays of Sinclair (1974) The results of ground-penetrating radar confirm the existence of numerous buried, sandfilled sinkholes within the wetland that perforate low-permeability layers below the S1 sands with no present surface manifestation. Perforations appear as vertical pipes of raveling S1 sands through underlying layers. Although several transect lines were run across the wetland, lines were spaced roughly 100 meters apart leaving a significant amount of un-surveyed area between transect lines. The identification of 13 apparent buried sinkholes from just 22 transect lines suggests that the frequency of occurrence is substantial. Several more transect lines would be required to establish the true density of buried sinkholes within the wetland. Although cores were not drilled in any of the established sinkholes visible at land surface, but their presence attests that the S2 low-permeability layer is perforated in several locations by sinkhole-filled columns of higher-permeability sands of the S1 layer. Surface-expressed sinkholes are found clustered in the center portion of the wetland (Figure 2). Since the surficial deposits are comprised of sand and clayey sand rather than a dense-clay confining unit above the limestone, the sinkholes that have developed within the wetland are likely of the cover-subsidence type. Cover-subsidence sinkholes are typically shallow, small diameter depre ssions that develop gradually (Sinclair, 1985) as are the visible sinkholes within the wetland. These sinkholes occur where the cover material is mostly incohesive and permeable, and individual sand grains move downward to replace grains that have moved downward to occupy space formerly held by newly dissolved lim estone (Sinclair, 1985). Vertical Head Differences Vertical head differences between the surficial deposits and the Upper Floridan aquifer within the wetland indicate a recharging system where groundwater flows downward from the surficial aquifer to the Upper Floridan aquifer. Hydrographs presented in the original North Lakes investigation reveal that head differences between the surficial

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40 deposits and the Upper Floridan aquifer during the year of study (1997) were near minimum and maximum levels in March and Oct ober respectively. The water levels on 3/3/97 and 10/3/97 were selected to represent instances of minimum and maximum head differences for the year. Vertical head differences were consistently greater across the S2 low-permeability layer than across S4 (Table 3). The A columns in Table 3 represent the average head differences between S1 and S3 units (across S2) while B columns represent the average head difference between S3 and the Upper Floridan aquifer (across S4). Column C represents the total head difference between the surficial deposits and the Upper Floridan aquifer and is the sum of the A and B columns. Table 3: Vertical Head Differences [m, meters] 3-Mar-1997 3-Oct-1997 1997 AVERAGE COLUMN COLUMN COLUMN A B C A B C A B C (A + B) (A + B) (A + B) Site Total Total Total No. S1 S3 S3 UFA SURFICIAL S1 S3S3 UFA SURFICIAL S1 S3 S3 UFA SURFICIAL (m) (m) (m) (m) (m) (m) (m) (m) (m) 1 0.17 0.61 0.78 0.32 0. 55 0.87 0.18 0.57 0.75 2 0.25 0.31 0.56 0.30 0. 58 0.88 0.25 0.30 0.55 3 1.45 0.03 1.48 1.32 0. 02 1.34 1.41 0.03 1.44 4 0.02 0.20 0.22 0.90 0. 59 1.49 0.29 0.34 0.63 5 0.29 0.06 0.35 1.22 0. 26 1.48 0.41 0.11 0.52 average 0.44 0.24 0.68 0. 81 0.40 1.21 0.51 0.27 0.78 Within the wetland, the total potentiometric head differences between the surficial and the Upper Floridan from 12/1/96 to 12/31/97 averaged 0.78 meters (2.56 feet) during the year of study (Table 3). Also, averaged vertical head differences between the upper (S1) and lower (S3) surficial deposits (0.51m) were greater than those between the lower surficial deposits (S3) and the Floridan aquifer (0.27 m) by nearly a factor of two. This suggests that during the year of investigation, roughly 65 percent of the total head difference between the surficial and the Upper Floridan occurred across S2 while only 35 percent occurred between S3 and the Upper Floridan or across the S4 layer. These percentages remain nearly identical regardless of high or low water-level stage (3/3/97

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41 and 10/3/97, Table 3). However, the magnitudes of the head differences are roughly double at the higher water-level stage (10/3/97) than at low stage (3/3/97). Contour maps illustrate vertical head differences between permeable units across the study area at both high and low water-level stages and are presented in Appendix J. Contour lines in all of the maps are clipped to exclude contouring outside of areas where actual data points exist. Comparisons of the head-difference maps between S1 and S3 (across S2) show distinct pattern differences between low (3/3/97, Appendix J.1) and high (10/3/97, Appendix J.2) water-level stages. During low or dry conditions, the headdifference pattern somewhat resembles the isopach pattern of the S2 low-permeability layer (Appendix I.2) in that the head differences decline from the southwest to the northeast within the wetland just as S2 slightly thins slightly from southwest to northeast. However, at high water-level stages, the smallest head differences are clustered in the central portion of the wetland (Appendix J.2). This area coincides with the area of the wetland where most surface-expressed sinkholes are located (Figure 2). This suggests that the influence of buried sinkholes or ka rst drains has increased with higher water table stage. Parker (1992) found that the head differences across the leaky confining unit within his study area were small at a poi nt where the clay units are perforated by a sinkhole, and are about five times greater at a point where the clay units are intact. Comparisons of the head-difference maps between S3 and the UFA (across S4) show that head-difference patterns also vary between low (3/3/97, Appendix J.3) and high (10/3/97, Appendix J.4) water-level stages. Both patterns resemble the isopach pattern of the S4 low-permeability layer (Appendix I.4) but with differing magnitudes. During low or dry conditions (Appendix J.3), head-difference values are highest in the same area where the S4 layer is thickest in the east-central portion of the wetland and decreases to the west. Head differences are near zero in the northeast and southwest. At higher water-level stage (Appendix J.4), the head-difference pattern more resembles the isopach pattern of S4 in that the head difference is near zero in the south end of the wetland (Site 3) but is greater in the northeast (Site 5). It appears that the lowpermeability materials of the S4 layer slow downward-percolating water causing semiperched conditions where S4 exists.

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42 Equivalent Hydraulic Conductivity Equivalent horizontal and vertical hydraulic conductivities (KHeq and KVeq) were computed for each of the hydrostratigraphic layers (S1 through S4) at each of the eight sampling locations (Table 4) using formulas after Fetter (1994): n i i Hi Heqd d K K1 and n i Vi i VeqK d d K1, where KHeq and KVeq represent equivalent values of horizontal and vertical hydraulic conductivity respectively. The above formula for composite KVeq of a system of several homogeneous layers is the weighted (by bed thickness) harmonic mean of the K values. It is clear from the position of KV in the formula that beds with lower K values (less permeable) are the dominant factor controlling the value of KVeq. Geometric means were used to compute parameter averages within each layer presented in Table 4. Values of KHeq are very similar to those of KVeq within the S1 and S3 sand layers at different sites (Table 4). Values of KVeq vary by roughly an order-of-magnitude less than KHeq within the S2 clayey sand and by less than an order-of-magnitude within the S4 layer. This suggests that sediments within individual layers are mostly homogeneous and isotropic. It should be noted, however, that laboratory permeability measurements were performed on re-packed sediments and therefore could obscure differences in the directionality of hydraulic conductivity. The values of KVeq for the S2 low-permeability layer range from 0.001 to 0.01 m/day with a geometric mean of 0.01 m/day (Table 4). The same values for the discontinuous S4 layer were larger, ranging from 0.02 to 0.2 m/day with a geometric mean of 0.1 m/day. The geometric mean of KVeq values for the S2 layer is nearly two orders-of-magnitude less than the geometric mean of KVeq for the S1 sand layer (2 m/day).

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43 Leakance Although the Upper confining unit is apparently absent at the wetland, results of a sitescale aquifer performance test (APT) for the original North Lakes investigation (Langevin et al., 1998) suggest that the Upper Floridan aquifer is at least partially confined. Storativity values estimated from the drawdown curves ranged from 0.0002 to 0.003 and averaged 0.001, which is considered very leaky. Late-time data from the drawdown curves in all observation wells during the site-scale APT revealed significant leaky contributions from above. The leaky confinement therefore must originate from either low-permeability zones within the Tampa Limestone or from low-permeability layers within the surficial deposits, or a combination of the two. It was not possible to directly measure hy draulic parameters for the upper portion of consolidated limestones to determine if those properties may contribute to the overall confinement. To deal with this issue, it was decided to initially make the assumption that all leaky confinement was the result of low-permeability layers within the unconsolidated surficial deposits above the Tampa Limestones and disregard the possibility of lowpermeability zones that may exist within the upper portion of the Tampa Limestone. Leakances were therefore calculated solely on the laboratory-measured properties of the surficial deposits alone. The results of Upper Floridan aquifer performance testing, however, include the effects associated with all leakage from above within the area of pumping influence. Comparison of APT-derived or effective leakances to laboratoryderived or calculated leakances for the surficial deposits should indirectly reveal the validity of the original assumption. The Hantush analytical method (1960) was used to estimate leakance values from the APT results (Table 4). APT-derived or effe ctive leakance values ranged from 0.001 to 0.04 days-1 with a geometric mean of 0.003 days-1. The highest leakance value of 0.04 was recorded from an Upper Floridan observation well (FMW-6, Figure 2) very near the APT production well (FMW-2). FMW-6 was drilled as a tracer test observation well only, long after lithologic cores were extracted for laboratory analysis. Notes taken during installation of this observation well, however, show several large intervals of lost circulation and poor recovery of cuttings. It is possible this site intersects a belowsurface karst feature that breaches low-permeability sediments in that location.

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44 Table 4: Calculated composite hydraulic conductivitie s and leakances from permeameter-derived K values [m, meters; m/day, meters per day; day1 1/days] Equivalent Vertical CALCULATED APT Equivalent Horizontal Equivalent Vert ical Hydraulic Conductivity Leakance Leakance thickness Hydraulic Conductivity Hydr aulic Conductivity of low K layers L L b KHeq KVeq KVeq' or KV'/b' or KV'/b' Drilling (m) (m/day) (m/day) (m/day) (day-1) (day-1) site S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4 S2, S3, and S4 S2, S3, and S4 1 (MW1) 2.74 2.75 3.65 0.92 2 0.03 5 0.031 0.0032 0.1 0.01 0.001 0.004 2 (FMW2) 2.43 3.36 2.13 2.06 3 0.03 2 0.1 3 0.0041 0.04 0.01 0.001 0.04* 3 (MW5) 2.74 3.05 1.83 3 0.01 1 2 0.0031 0.004 0.001 0.001 4 (FMW4) 2.29 3.20 2.13 3 0. 022 2 0.012 0.01 0.003 0.003 5 (FMW5) 2.74 2.44 4.57 0.92 2 0.2 2 0.2 1 0.021 0.2 0.1 0.01 0.01 6 (VC1) 2.74 3.06 1.01 2 0. 2 6 1 0.011 0.01 0.003 7 (VC2) 3.33 2.40 1.17 1.14 3 0.0042 0.1 2 0.0011 0.02 0.002 0.001 0.001** 8 (VC3) 2.59 3.20 1.35 2 0. 1 5 2 0.014 0.01 0.002 Geom. mean 2 0.033 0.1 2 0.011 0.1 0.01 0.002 0.003 Arith. mean 2.70 2.93 2.23 1.26 1) Equivalent hydraulic conductivities (KHeq, KVeq) for each hydrostratigraphic unit (S1-S4) are the weighted arithmetic and harmonic means, respectively, of K for all lithostratigraphic beds within that unit 2) Leakance is calculated using the relationship of KV'/b', where KV' and b' represent the total vertical hy draulic conductivity and thickness of confinement at each respective location 3) = APT leakance values actually from observation well (FMW6) appro ximately 24 meters north of FMW2 4) ** = APT leakance values actually from observation well (FMW7) approxi mately 125 meters southwest of VC2

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45 Leakance is defined as the ratio of the vertical hydraulic conductivity of a confining unit (KV') divided by the confining unit's thickness (b') in dimensional units of L/T/L or just T-1. In order to calculate values of leakance from laboratory-measured permeabilities at each of the eight sampling locations, estimates of the total vertical hydraulic conductivity of confinement (KV') are needed at each location. Since no dense-clay layer above the limestone was found, the S2 and the S4 layer were assumed to be the only significant impediment to vertical movement of water within the surficial deposits. Regardless of its hydraulic properties, the S3 layer was included as part of the overall leaky confinement based on its position between two confining layers at sites where S4 was encountered. Therefore, the source of leaky confinement is assumed to be the S2 layer alone when the S4 layer is not encountered and the combination of the S2, S3, and S4 layers when S4 exists. To note, no significant differences to the calculated leakances occurred whether or not S3 and S4 are included as part of the confinement in the leakance calculation as opposed to assuming S2 as the sole source of confinement. The equation is dominated by KV of the lower-permeability S2 layer. For four of the eight sampling locations where S2 was the only confinement encountered, the total vertical conductivity of confinement (KV') is simply the equivalent vertical hydraulic conductivity (KVeq) of the S2 layer. The KV' at the three locations where S4 was encountered was determined by re-applying the equivalent vertical hydraulic conductivity equation (weighted harmonic mean) to the equivalent KVeq values for S2, S3, and S4 at each location to generate an equivalent KVeq' for the combination of these layers (Table 4). Leakances were then computed by dividing KVeq' by the total thickness of the layers (b') at each of the sites. The range of laboratory-derived or calculated leakance values spans roughly one orderof-magnitude. The spatial distribution of leakance (Figure 9) generally follows the geometry of the low-permeability layers in that leakance is highest in the northeast portion of the study area where S2 and S4 are thin (Appendices I.2 and I.4). Calculated leakances are lowest in the east central portion of the wetland where S4 occurs, as well as the southern portion where S2 is thickest (Appendices I.2 and I.4). Contour lines in Figure 9 are clipped to exclude contouring of areas beyond actual data points. It should be stressed that these calculated leakance values are only representative of vertical

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46 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.001 0.001 0.001 0.003 0.010 0.003 0.001 0.002 0.0005 0.002 0.003 0.006UTM NORTH (meters)UTM EAST (meters) Figure 9. Contour map of laboratory-derived calculated leakances in days-1 percolation through confinement and do not account for additional contributions from karst drains that may perforate low-permeability layers creating preferred conduits for flow.

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47 The calculated leakances ranged from 0.001 to 0.01 days-1 with a geometric mean of 0.002 days-1 (Table 4). This geometric mean is nearly identical to the geometric mean of leakances from the site-scale APT (0.003 days-1). The APT-derived or effective leakances also reflect the influence of any ka rst drains that create accelerated pathways for leakage during pumping. In a site-by-site comparison, the calculated leakances wereall very similar to corresponding effective leakances from the Floridan observation wells (Table 4). The calculated values of leakance at two of the sites (Sites 3 and 5) are identical to the effective leakance values. The close similarity of geometric means bet ween the calculated and effective leakances strongly supports the suggestion that there are no significant low-permeability zones in the upper portion of the Tampa Limestone that contribute to confinement of the UFA. Otherwise, the APT-derived effective leakances which are influenced by all confinement within the cone of depression would presumably be lower than the calculated estimates, which only account for low-permeability sediments within the surficial deposits. If the calculated leakances are accurate, any low-permeability beds at or below the limestone surface provide poor confinement to the UFA. Stage-Dependent Effective Leakance Parker (1992) introduced a direct relationship between the stage of the water table and the rate of leakage from the surficial to the Upper Floridan aquifer that exists in regions that are hydrogeologically similar to t he area of his study. The relationship he presented, "stage-dependent effective leakance", states that for a given downward head differential, there is a greater rate of l eakage at high stages of the overlying surficial aquifer than at lower stages. This is the result of increasing potential for horizontal flow in more permeable sediments above low-permeability units toward sand-filled drains that breach the units. The characteristics he describes include a leaky-confining-unit surface that is undulating and perforated by sinkhole-filling sediment columns of higher permeability than the rest of the unit, surficial aquifer sediments that decrease in permeability with depth, and a water table that fluctuates within that zone of decreasing permeability. The term "effective leakance" is used to distinguish from the normal definition of leakance, which only considers vertical flow that percolates through the confining

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48 sediments. Effective leakance considers additional leakage that can occur through breaches in confinement as a result of horizontal flow towards sinkholes that act as preferred drains. The capability for horizontal flow towards these karst-developed drains is increased during higher water table stages when the saturated thickness is greater in the higher permeability sediments, hence "stage-dependent leakance". Comparison of vertical head-difference contour maps across S2 confinement at high and low water table stage support that visible as well as buried sinkholes clustered in the central portion of the wetland breach the S2 layer. If sinkhole-filling sand columns consisting of S1 material breach S2, K values within the columns could be up to 2 orders of magnitude higher than the surrounding S2 layer based on laboratory measured permeabilities from S1 (Table 4). Sand columns such as these would create preferred hydraulic drains for water above S2 when hydrologic conditions permit. In March of 1997, after prolonged drought conditions, water table elevations in the wetland were at or very near the surface of the S2 low-permeability layer (Figure 10). The water level height above the top of the S2 layer in shallow surficial wells screened in the S1 layer averaged only 0.14 meters NGVD. Water levels at Sites 2 and 4 (Figure 2) were slightly below the top of S2. Vertical head gradients across the S2 layer at this time were at a minimum. As a result, water was contained mostly within, rather than above the low-permeability materials of S2. The karst drains were thus starved of water as the amount of lateral flow in the S1 sands was minimized, influencing water to propagate primarily by vertical percolation through the low-permeability S2 layer. In this case, the rate of leakage is predominately a function of the hydraulic properties of the S2 layer materials. Evidence for this can be seen in the vertical headdifference pattern across the S2 layer on 3/3/97 (Appendix J.1). The head-difference pattern mimics the isopach pattern of the S2 layer (Appendix I.2) in that head differences are mostly flat but gradually decline from the southwest where S2 is thickest, to the northeast where S2 is thinnest. This pattern is expected if leakage is dominated by vertical percolation through the low-permeability sediments. Results of the site-scale APT conducted in March of 1997 further support that leakage at this time occurs mostly as vertical percolation through the S2 layer. Calculated leakances based on results of permeameter te sting were nearly identical to effective

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49 20 15 5Elevation ( meters NGVD)10 SITE 3 SITE 2 SITE 5 S1 S2 S3 S4 S4 S3 S2 S1 S1 S2 S3 Water table elevation March 3, 1997 Water table elevation October 3, 1997 Figure 10. Cross-section with water table elevations from March and October leakances resulting from analyses of the APT data (geometric means of 0.002 days-1 and 0.003 days-1 respectively, Table 4). The effective leakances account for all water contributions regardless of flow path including both vertical percolation through S2 as well as flow through karst drains. Since water levels were low at the time of the APT, horizontal flow toward karst drains was minimal to non-existent, leaving the APT-derived effective leakance predominantly controlled by vertical percolation alone. In this case, the calculated and the effective leakances represent specific values of leakance within the range of effective leakance that can occur as hydrologic conditions vary. Both values likely represent low to minimum va lues of leakance since only the vertical component of flow is mostly active. In October of 1997, water levels had significantly increased as a result of artificial flooding of the wetland in August for surficial tracer testing and the onset of unusual late season rains associated with "El Nino" weather patterns (Figure 10). During this period, the height of water above the top of S2 averaged 2.25 meters NGVD or 2.11 meters (6.92 feet) higher than in March. The increased height of water within the more

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50 permeable S1 sands increases the potential for lateral flow toward karst drains. Evidence for this is seen in the head-difference pattern across S2 in October of 1997 (Appendix J.2). The lowest head differences are now located in the central portion of the wetland in the same vicinity of the wetland where three out of the five surface-visible sinkholes are located (Figure 2). It appears that as water levels rise above lowpermeability sediments within the more permeable sands, lateral flow toward karst drains becomes the path of least hydraulic resistance, while the potential for flow to percolate through the lower permeability sediments becomes more resistive by comparison. The dominant factor controlling the rate of leakage across S2 is no longer the hydraulic properties of the S2 layer, but the permeabilities and locations of sandfilled karst drains. If a large-scale APT were conducted during elevated water-level stages, it is anticipated that the effective leakances derived from that APT would no longer match calculated values derived from the laboratory analyses, but instead be higher as the influence of karst drains grows. In other words, the laboratory-derived calculated leakances remain unchanged and a decreasingly accurate approximation of effective leakance as the influence of stage-dependency increases. Leakage Estimations In the North Lakes report, estimations of the leakage (recharge) to the Upper Floridan aquifer within the wetland were calculated by multiplying total head differences between the surficial and Upper Floridan aquifers over the course of a year by the average value of leakance obtained through analysis of the aquifer performance test and the area of the wetland. A graph in that report illustrates the temporal variability of leakage due to changing vertical head differences as water levels fluctuated throughout the year. As expected, leakage peaked soon after artificial surficial flooding (during surficial tracer tests) and after the onset of uncharacteristically heavy late season rainfall creating maximum head gradients between the surficial and the Upper Floridan. As Upper Floridan water levels gradually increased near the end of the wet season, recharge declined in conjunction with reduced vertical head gradients between the two aquifers. Multiplying the average of the total surficial head differences for the entire year (0.78 meters, Table 3) by the APT-derived arithmetic mean leakance (0.009 days-1) and the total area of the bermed wetland (65,000 m2), the average leakage to the Upper Floridan aquifer for the year as reported in the North Lakes study is 456 m3/day. Using instead

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51 the geometric mean of the APT-derived leakances (0.003 days-1) returns a leakage of 152 m3/day. Doing the same calculation but using the geometric mean of permeameterderived calculated leakances from this study (0.002 days-1) yields a leakage value of 101 m3/day, roughly 4.5 times less than the original reported estimate in the North Lakes study. All of these leakage values differ sharply from an independent estimate of wetland leakage to the Floridan aquifer reported in the North Lakes study of 2000 m3/day based on the results of surficial aquifer tracer testing within a portion of the wetland. This value was obtained by multiplying an average velocity estimated from the tracer test (10 cm/day) by the area of the wetland (65000 m2) and an average porosity estimate of the surficial aquifer (0.3). This leakage value, which corresponds to the time when the wetland was artificially flooded, is over 13 times greater than the estimate from the North Lakes APT analysis (152 m3/day) and nearly 20 times greater than the laboratory-based estimate in this study (101 m3/day). It was reported in the North Lakes study that the discrepancy between recharge estimates of the tracer tests versus those of the APT was attributed to either a false assumption that the average downward velocity of the wetland was measured with the surficial tracer test or that the average leakance value at the site is higher than 0.009 day-1 (Langevin et. al., 1998). Based on the findings of this study, it seems that neither of these explanations is fully accurate. The large discrepancy between leakage estimates can be explained by the circumstances under which the tests were performed rather than flawed results. The surficial aquifer tracer test was executed by flooding the wetland during a time of suppressed Upper Floridan head levels, thereby further increasing the driving mechanism for leakage by significantly incr easing the vertical head gradient. Revisiting the data from the North Lakes report, a conservative estimate of the head difference between flood stage and water levels in the Upper Floridan after the onset of flooding is close to 2.3 meters. Using this flooded head difference of 2.3 meters and re-calculating leakage using the effective and calculated leak ances of this study, leakage estimates jump to 449 m3/day and 299 m3/day respectively. These values are significantly higher but still much less than the 2000 m3/day estimate based on the results of the surficial aquifer tracer test, which is expected since the effective and calculated leakances do not

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52 include effects of karst drains. The large discrepancy between high and low-stage leakage estimates strongly supports the theory that leakances are stage-dependent and that the effects of karst drains have substantial impact to leakage rates as hydrologic conditions change. Parker (1992) estimates the leakage rate within his study area is 0.025 m3/day per square meter of clay layer perforation, which multiplied by the area of the study area equals 2250 m3/day. He also estimates the leakage rate is 0.000025 m3/day per square meter of intact clay layer, which returns a value of 2.25 m3/day for the study area. Parker (1992) also found that the head differences across the leaky confining unit within his study area were small in locations where the clay units are perforated by a sinkhole, and about five times greater at a point where clay units are intact. At North Lakes, shallow surficial observation wells were installed within two of the largest visible sinkholes. Both of these wells were coupled with a second shallow well drilled just outside the perimeter of the sinkhole for monitoring purposes during the site-scale APT. Strangely, although the lowest vertical head differentials across the S2 lowpermeability layer at North Lakes occur mostly in the central portion of the wetland where most visible sinkholes were clustered, data recorded during the site-scale APT reveals that water levels dropped faster in wells outside, rather than wells inside the sinkholes. One explanation for this occurrence might be related to the accumulation of organic and mineral fines within the sand-filled sinkholes. Based on observations within his study, Parker (1992) suggests that although collapse of a sediment column into a cavity may introduce sands that create preferred pathways for movement of water, the throats of these drains may, over time, become choked with accumulated finer-grained materials by the process of illuviation. Surface sediments in the bottoms of large sinks at North Lakes were visibly very muddy and organic-rich. It is conceivable that progressive accumulation of finer-grained particles within the pore space of larger sand particles could considerably reduce porosity and permeability of the displaced sands within the drain throat. This was demonstrated earlier in the results of grain-size distribution analyses, where relatively small increases in silt and clay content of otherwise clean sands resulted in substantial decreases in measured permeability. If this scenario is correct, the KV of the sinkhole may become less than surrounding

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53 sediments where the S2 layer is still intact. Through time, vertical percolation through the adjacent S2 layer could become the path of least resistance while the potential for flow through the sinkhole becomes resistive by comparison. Regional Outlook Based on the lithology of the cores, the unconsolidated surficial deposits at North Lakes appear to directly overlie the weathered Tam pa Limestone while the dense clay of the Upper Confining Unit reported in both the thesis by Parker (1992) at the USF campus and the Sinclair study (1974) at the Section 21 well field appears absent beneath this wetland. This concurs with Sinclair's geologic logs of two test wells in the area southeast of the Section 21 well field which reflect relatively shallow limestone that is directly overlain by the surficial sands. The North Lakes wetland lies just northwest of these test wells, between the test wells and the Section 21 well field. Undisturbed stratification in the clayey sand layers suggests that deposition of the surficial deposits occurred after the period of weathering and dissolution of the underlying limestone which produced the dense-clay residuum. Sinclair (1974) suggested the sands and interbedded sands overlying the limestone and weathering residuum to be reworked sediments deposited by a transgressive sea. The North Lakes wetland lies within the limits of a region described by Parker (1992, Figure 3) that is hydrogeologically similar. However, the leaky-confining unit in Parker's study is a dense, plastic carbonate residuum clay with a sand content of around 20 to 30 percent. It is roughly 2.5 meters thick and immediately overlies the limestone surface. Surficial aquifer sediments above this unit gr adually decrease in permeability with depth. The S2 low-permeability layer at North Lakes however, is comprised of silty/clayey finegrained sand with a clay content between 10 and 20 percent (Appendix D) that is also approximately 2.5 meters thick (Table 4). The gradation between the more permeable S1 sands and the lower permeability S2 layer is sharper however, and S2 is separated from the limestone surface by additional clasti c sediment layers S3 and S4 (Figure 6). The same formulas and methods used in this study to calculate values of equivalent vertical hydraulic conductivity (termed com posite coefficient of vertical permeability by Sinclair), leakance (leakage factor), and leakage (recharge) were applied to the results of laboratory permeability tests on surficial aquifer samples from Sinclair's (1974) study

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54 as well as results of slug testing in the study by Parker (1992). Results of both studies found the typical lithostratigraphy to be comprised of high permeability surficial sands underlain by gradationally less permeable beds of sand with clay, followed by relatively impermeable dense clay immediately above the limestone. However, Parker (1992) found that sinkhole-filling sand columns perforate the dense-clay unit and estimates they represent one to two percent of the total area of the leaky-confining unit of the region. He also demonstrates that the values of KV for the sand columns are much greater than that of the adjacent dense clay and have a large effect on the calculated average leakance. Parker (1992) estimated leakance at a point where the dense-clay confinement is in tact to be 0.00005 days-1 while leakance within a sinkhole-filling sediment column was over four orders of magnitude larger at 0.25 days-1. Assuming an areal density of columns of two percent, Parker calculated an average leakance for the region of 0.005 days-1. This estimate is two orders of magnitude larger than the calculated leakance of Sinclair (1974) of 0.00005 days-1, which is based on dense-clay thicknesses with no consideration of sinkhole effects. Parker's estimate is considerably dependent upon the assumed areal density of columns. Substituting a 0.2 percent areal density returns a value of 0.00055 days-1. Parker adds that the true areal density of columns within the region is highly variable and difficult to verify due to dependency upon local conditions and degrees of karstification. The potentiometric surface contour map of the surficial and Upper Floridan presented by Sinclair (1974) reveals a depression in the water table overlying a cone of depression in the Upper Floridan that is centered in the southeast corner of the Section 21 well field where several large capacity pumping wells are clustered. He attributes the UFA cone to heavy well field pumping and the water table depression to increased leakage induced by higher head differences as a result of the pumping. On Sinclair's map, the UFA cone of depression centered in the well field also extends out over the location of the North Lakes wetland, where no production wells exist. Also, a depression in the water table appears to center over the wetland creating a double-bull's-eye or kidney-shaped feature in the water-table surface that extends between the well field and the wetland. Sinclair's logs collected southeast of the Section 21 well field (test wells 58 and 59 about mile

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55 southeast and about 1mile SSE of the North Lakes wetland, respectively) show a shallow top of limestone directly overlain by surficial sands and clayey sands. Both Tihansky (1999) and Sinclair (1982) have documented the effects of past aggressive pumping on groundwater declines and sinkhole development near the Section 21 well field. In 1964, a year after pumping began and within a month after the rate was nearly tripled, groundwater levels were lowered more than 10 feet and 64 new sinkholes had developed within a one mile radius of the well field (Tihansky, 1999). A well in the southeast corner of the well field was pumping almost double the rate of the other production wells and a majority of the 64 sinkholes were clustered just south and east of the well field property. Neighboring areas witnessed significant declines in lake levels and wetland dewatering (Tihansky, 1999). The pumping rate of that well was subsequently reduced by about 50 percent (Sinclair, 1982). Sinclair (1974) reported that although recharge in this region occurs faster through breaches in of confinement, sinkholes occupy a small percentage of the total area of the region and therefore leakage across the confinement, although slower, probably contributes most of the recharge to the Floridan. Parker (1992) disagrees with this assessment and confirmed through geophysical methods the existence of prevalent sinkholes, mostly with no surface expression that actually provide the dominant pathways for recharge in the region. The North Lakes wetland, however, is an example of a localized 'hydraulic sink' where accelerated recharge to the Upper Floridan occurs as a result of discontinuous confinement between surficial deposits and underlying limestone in the form of dense clay above t he limestone found elsewhere in the region. Also, the confining abilities of low-permeability sediment layers that occur within surficial deposits of the wetland are lessened by perforations at several locations where surface and buried sinkholes perforate low-permeability layers. The frequency, volume, distribution, and recharge capabilities of similar 'hydraulic sinks' throughout the region are unknown. If these 'sinks' are a regionally prevalent occurrence, collective recharge from these 'sinks' could potentially be responsible for a considerable portion of the total recharge in the region as opposed to leakage through confinement.

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56 CONCLUSIONS The hydrostratigraphic configuration of the surficial deposits at the North Lakes wetland varies significantly with respect to the common configuration of surficial aquifer deposits throughout northwest Hillsborough County. Sinclair (1974) states: "In northwest Hillsborough County surficial sand of relatively high permeability and large storage capacity is underlain by layers of sand and clay of less permeability and storage capacity. Underlying these units is a rela tively impermeable clay which overlies the permeable limestone of the Floridan Aquifer and is the most important factor in retarding the downward movement of water from the surficial aquifer to the Floridan Aquifer." At North Lakes, a 'layer-cake', vertical stacking of alternating high and low-permeability layers within the unconsolidated surficial deposits (S1 through S4) creates a vertically heterogeneous overburden within which individual hydrostratigraphic layers are mostly homogeneous in nature. Each layer is characterized by distinct textural and hydraulic characteristics based on the results of detailed laboratory grain-size distribution and permeameter analyses. Upper and lower clean sands (S1 and S3 respectively) are separated by a clayey sand to sandy clay (S 2). Discontinuous clayey sand (S4) below the S3 sand was found at four of eight cored sites at North Lakes. S1 and S3 are similar in their hydrogeologic properties but differ signi ficantly from those of S2 and S4. The geometric mean of equivalent vertical hydraulic conductivity (KVeq) values for the S2 layer (0.01 m/day) is over two orders of magnitude less than that of S1 (2 m/day). This hydrostratigraphic framework differs from ot hers described in the region where surficial sediments exhibit downward fining of sediment grains and decreasing permeability with depth. Most importantly, the dense clay that typically forms the Upper Confining Unit of the Floridan aquifer in this region is discontinuous or absent beneath this wetland. Despite the apparent lack of dense-clay confinement above the top of limestone, analyses of a sitescale APT reflects that the Upper Floridan aquifer is at least partially confined. The partial confinement appears signi ficantly leaky as evidenced by middle to

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57 late-stage water contributions during pumping. Therefore, the leaky confinement must originate from either low-permeability zones within the Tampa Limestone, lowpermeability layers within the surficial deposits, or a combination of the two. Vertical head differences between the surficial deposits and the Upper Floridan aquifer indicate a recharging system. Higher vertical head differences across S2 than S4, and that S4 was encountered at only half of the cored locations, suggests that S2 layer represents the primary source of partial confinement to the Upper Floridan aquifer. The results of ground penetrating radar confirm the existence of sinkhole-induced, sand-filled columns that perforate underlying low-permeability layers within the wetland with no surface expression. The occurrence of 13 buried sinkhole features identified from just 22 transect lines suggests that the true occurrence of these sub-surface features is substantial. Contour-map patterns of vertical head differences across the S2 layer at both high and low water-level stages suggest that the karst features provide a significant mechanism for drainage aside from vertical percolation through the S2 layer. Leakances calculated from results of permeameter testing of cores within the lowpermeability hydrostratigraphic layers were highest in the northeastern portion of the wetland where the S2 layer appears thinnest, and lowest in the central and southern parts of the wetland where S4 is encountered and S2 appears thickest. The geometric mean of these calculated leakances (0.002 day-1) is nearly identical to the geometric mean of the APT-derived or effective leakanc es obtained from individual monitor wells during the Upper Floridan aquifer APT (0.003 day-1). Since the calculated leakances only account for low-permeability layers within the surficial deposits, the similarity of these geometric means suggests that leaky confinement between surficial and Upper Floridan aquifers during the APT, was effectively the result of the low-permeability layers within the surficial deposits alone; otherw ise effective leakances would expectedly be smaller than the calculated values. Low-permeability zones within the Tampa Limestone, if they exist, appear to have little resistance to leakage. The laboratory-derived calculated leakances, by definition (Kv'/b'), consider only vertical components of flow by means of percolation through the horizontal, leaky confining unit. The APT-derived or effective leakance, however, accounts for the total contribution of

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58 water from above induced by pumping regardless of actual pathways. This includes water contributions as the result of both vertical percolation through the low-permeability layer, as well as contributions that occu r by way of horizontal movement above S2 towards karst drains that perforate the low-permeability layer. The close match of geometric means for calculated versus effect ive leakances suggests that leakage during the site-scale APT occurred primarily as vertical percolation through S2; otherwise effective leakances would expectedly be greater than the calculated values. This is further supported by the fact that vertical head differences across the S2 layer just prior to the test appear to mimic the isopach pattern of the S2 layer. This pattern would be expected if the primary mechanism for drainage were through vertical percolation, not through more preferred karst drains. Hydrologic conditions present at the time of the APT do not exclude the possibility that effective leakance at the wetland is also stage dependent. Prevailing drought conditions at the onset of the APT (3/3/97) resulted in depressed water table levels, at or very near the top of the low-permeability S2 layer. This diminishes lateral flow in the S1 sands above S2 toward more preferred karst drains in favor of vertical percolation through the S2 layer as the primary mechanism for drainage. It is thus theorized that the hydrologic conditions present at the time of the APT allowed accurate assessment of effective leakance by means of laboratory-derived ca lculated values because the mechanism for drainage was mostly limited to vertical percolation through the S2 layer. This would minimize measured effective leakance, and optimize the calculated leakance as a predictor of effective leakance. It is expected that as water table stages rise in the wetland, effective leakance increases as lateral flow in the S1 sands towards karst drains becomes more feasible. This is supported in that later the same year (10/3/97) during higher water table stages, vertical head differences across the S2 layer no longer mimic the isopach pattern of the S2 layer. Instead, the smallest head differences were now focused in the central portion of the wetland, which coincides with the area of most surface-visible sinkholes. This suggests that the mechanism for drainage shifts with increases in water table stage or stage dependency. As such, calculated leakances based on direct laboratory sediment testing are increasingly a less reliable approximation of effective leakance as water levels rise.

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59 A leakage rate can be estimated for the area within the wetland at the time of the APT by multiplying the geometric mean of effective leakances derived from the APT by the average total surficial head difference at the time of the APT and the area of the wetland yielding a value of 152 m3/day. This estimate is similar to the same computation using instead the geometric mean of permeameter-derived calculated leakances yielding a value of 101 m3/day. Based on conditions present at the time, these estimates likely represent low-range values within a range of potential leakage rates associated with water table variations. These leakage estimates differ considerably from that of an earlier surficial tracer test in the wetland, which resulted in a value of 2000 m3/day. If the tracer results are accurate, this value further supports the idea of stage-dependent influences. The tracer test was conducted by artificially flooding the wetland while water levels in the surficial and Upper Floridan were relatively depressed, which could create an abnormally large driving potential for downward flow. The wetland at North Lakes appears to represent a localized 'hydraulic sink' of accelerated recharge to the Upper Floridan aquifer due to discontinuity of the regionally extensive dense clays found between uncons olidated surficial deposits and underlying porous limestones. Downward propagation of groundwater through the surficial deposits is still however impeded by low-permeability cl ayey sand layers that occur within the surficial deposits. Evidence suggests that the degree of this restriction fluctuates with varying hydrologic conditions. The confining abilities of the low-permeability deposits within the wetland are lessened by perforations at several locations where surface and sub-surface sinkholes occur. If 'sinks' such as this wetland are a regionally prevalent occurrence, collective recharge from these 'sinks' could be responsible for a considerable portion of the total recharge in the region as opposed to leakage through confinement. Generating reasonably accurate estimates of recharge on a regional scale using methods of this study would require a high density of sampling and testing locations to adequately characterize the frequency, distribution, and hydraulic parameters of similar localized 'sinks' in the area of interest. Assessment of hydrologic conditions would also be critical in identifying potential for leakance stage-dependancy as a result of perforations to confinement. Not doing so could lead to misleading characterizations and inaccurate predictions of recharge.

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60 REFERENCES CITED American Society for Testing and Materi als 1972. ASTM Designation: D 2434-68 (Reapproved 1974), Permeability of Granul ar Soils (Constant Head), 7 p. American Society for Testing and Mate rials 1990. ASTM Designation: D 422-63 (Reapproved 1990), Standard Test Method for Particle-Size Analysis of Soils, 7 p. Bear, J., 1972, Dynamics of Fluids in Porous Media: New York, American Elsevier Co., 764 p. Butler, J.J., 1998, The Design, Performanc e, and Analysis of Slug Tests: Boca Raton, Florida, Lewis Publishers, 252 p. Carr, W.J., and Alverson, D.C., 1959, Strati graphy of middle Tertiary rocks in part of west-central Florida: U.S. Geological Survey Bulletin 1092, 111 p. Davis, R.A. Jr., 1992, D epositional Systems: Englewood Cliffs, New Jersey, Prentice Hall, 604 p. Davis, S.D., 1969, Porosity and pe rmeability of natural materials, in Flow Through Porous Media, edited by De Wi est, R.J.M.: Academic Press, New York, pp. 53-89 Domenico, P.A., and Schwartz, F.W., 1998, Physical and Chemical Hydrogeology: New York, John Wiley and Sons, 506 p. Fetter, C. W., 1994, Appl ied Hydrogeology: Englewood Cliffs, New Jersey, Prentice Hall, 691 p.

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61 Freeze, R.A., and Cherry, J.A., 1979, Groundwater: Englewood Cliffs, New Jersey, Prentice Hall, 604 p. Helsel, D.R. and Gilroy, E.J., 2006, Applied Environmental Statistics: unpublished manuscrip t (course guide). Kelley, G. Michael et. al., 1988, Ground-wate r Resource Availability Inventory: Hillsborough County, Florida, So uthwest Florida Water Management District, 203 p. Langevin C.D. and M.T.Stewart, 1996, No rth Lakes Wetland Project Phase I Report: Tampa, University of South Florida, 73 p. Langevin, C.D., D.Thompson, J.J. LaRoche ., C. Albury, W.B. Shoemaker and M.T. Stewart, 1998, Development of a Conceptual Hydrologic Model from Field and Laboratory Data, Phase II Results of North lakes Wetland Project Hillsborough County, Fl orida: Tampa, Universi ty of South Florida, 72 p. Miller, J.A., 1986, Hydrologic framework of the Floridan aquifer system in Florida and in parts of Georgia, South Ca rolina, and Alabama: United States Geological Survey Profe ssional Paper 1403-B, 91p. Masch, F.D. and K.J. Denny, 1966, Grain size distribution and its effect on the permeability of unconsolidated sands: Water Resources Research, v. 2, no. 4, pp. 665-667. Parker, J.W., 1992, Surficial Aquifer Hy drogeology in a Covered Karst Terrane: Unpublished M.S. thesis, Tampa, Univ ersity of South Florida, 227 p. Ryder, P.D., 1985, Hydrology of the Fl oridan aquifer system in west-central Florida: U.S. Geological Survey Prof essional Paper 1403-F, 63 p., 1 pl. Scott, T.M., 1988, The Lithostratigraphy of the Hawthorn Group (Miocene) of Florida: Florida Geological Su rvey Bulletin 59, 148 p.

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62 Seaber, P.R., 1988, Hydrostr atigraphic units, In Back, W., J.S. Rosenshein, and P.R. Seaber, (Eds.), Hydrogeology: B oulder, Colorado, Geological Society pf America, The Geology of Nort h America, v. O-2, pp. 9-14. Sinclair, W.C., 1974, Hydrogeologic characte ristics of the surficial aquifer in northwest Hillsborough C ounty, Florida: Florida Bureau of Geology Information Circular 86, 98 p. Sinclair, W.C., 1982, Sinkhole devel opment resulting from ground-water withdrawal in the Tampa Bay area, Fl orida: U.S. Geological Survey Water-Resources Investigations 81-50, 19 p. Sinclair, W.C., 1985, Sinkhole type, devel opment, and distributi on in Florida: U.S. Geological Survey Map Series 110. Southeastern Geological Society, 1986, Hy drogeologic units of Florida: Florida Bureau of Geology Specia l Publication 28, 9 p. Summers, W.K., and P.A. Weber, 1984, The re lationship of grain-size distribution and hydraulic conductivity-an alternat e approach: Groundwater, v. 22, no. 4, pp. 474-475. Thompson, T. A., C.S. Miller, P.K. Do ss, L.D.P. Thompson, and S.J. Baedke, 1991, Land-based vibracoring and vibr acore analysis: tips, tricks, and traps: Indiana Geological Survey Occasional Paper 58, 13 p. Tihansky, A.B., 1999, Sinkholes, west-central Florida, in Galloway, Devin, Jones, D.R., Ingebritsen, S.E., eds., Land subs idence in the United States: U.S. Geological Survey Circular 1182, p. 121-140. Vacher, H.L., Jones, G.W. and Stebnisky, R.J., 1992, Heterogeneity of the surficial aquifer system in west c entral Florida: Tallahassee, Florida Geological Survey Special Publication 36, pp. 93-99. Vukovic, Milan and Soro, Andjelko, 1992, Determination of hydraulic conductivity of porous media from grain-size composition: Water Resources Publications, Littleton, Colorado, 83 p.

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63 White, W.A., 1970, The geomorphology of the Florida Penins ula: Tallahassee, Florida Geological Survey Geol ogical Bulletin 51, 164 p., 7 pl.

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64 APPENDICES

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Appendix A. Grain-size Distibution Analysis Procedures 65 Sediments are classified based on the size (diameter) of the individual grains ranging from less than a micrometer to millimeters in diameter. Determination of grain size is measured by passing the grains through several sieves that separate grains into narrow size classes and/or by allowing them to settle through a column of fluid, usually water. The rate at which the particles settle in the tube after vigorous agitation of the water is a function of the size, shape, and density of the grains. Grain-size analyses were conducted on the samples using the procedure specified in the standard test method for particle-size analysis (ASTM, 1990). The method includes the procedure for determining the composite correction factor associated with experimental uncertainty. The factor corrects for the error attributed to instrument uncertainty as well as the variation of conditions in the testing environment during the hydrometer portion of the analysis. Also a correction is made on each sample regarding the mass amount of sample that is attributed to hygroscopic moisture or water held in the interstitial spaces between grains. The procedure first includes the air-drying of sample before analysis, followed by soaking of the sample in a sodium hexametaphosphate solution for a 16-hour period to allow for dispersion of any soil aggregates that may exist between particles. Immediately after dispersion, the soil-water slurry is transferred to a sedimentation cylinder where it is churned for one minute before starting the settling-tube portion of the test. Fluid density readings are taken at 2, 5, 15, 30, 60, 250, and 1440 minute intervals using an ASTM 152H air-filled glass hydrometer. The height that the hydrometer stem is elevated above the surface of the slurry is determined by the amount of particles that remain in suspension around it. The density of the slurry at that time is then read off the demarcated hydrometer stem at the slurry surface. The percentage of soil remaining in suspension is a function of the soil-water slurry and is calculated at each interval. The diameter of the particle corresponding to the percentage indicated by a reading is then calculated according to Stoke's Law for sedimentation of particles in suspension. After the final reading, the samples are wet sieved through a 3.74 (75 m) mesh to separate the silt-clay fraction from the sand-size fraction. The retained sand-sized sample mass is weighed, oven-dried to remove all hygroscopic moisture (interstitial water retained on grain surfaces), then reweighed to determine the hygroscopic moisture mass and the hygroscopic moisture ratio which is the ratio of the oven-dried sample mass to the initial

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Appendix A (Continued) 66 air-dried sample mass used in the grain-size distribution computations (Figure A.1). A final, dry sieve analysis is then performed on the retained mass to classify the sand size or larger particles by passing the sedim ents through a series of sieves using a mechanical sieve shaker. Once the samples have been shaken for at least ten minutes, the masses retained on each sieve are removed, measured, and recorded on data worksheets (Figure A.2). Grain-size distribution analyses data was processed according to the guidelines stipulated in the ASTM methodology (ASTM, 1990). The method results in percentages of sample mass that coincide with grain-size diameters measured on the phi scale where: d2log where d is the grain-size diameter in mm. This notation simplifies statistical calculations and graphical representation of results. Results may be plotted as frequency histograms or cumulative frequency curves. Since the distribution of grain sizes in a sediment population typically follows a log-normal distribution (Davis, 1992), plots of percent by weight versus phi grain size frequency curves best visualize the characteristic bell-shape curve. Frequency curves of cumulative percent finer by weight (percentiles) are more practical in determining statistical parameters because percentiles can be read straight from the graph. Both types of frequency curves were generated for each of the samples (Appendix D). Statistical soil parameters were calculated from the grain-size distributions. These parameters include median grain size, effectiv e grain size, and uniformity coefficient. The median grain size represents the grain size diameter in the middle of the distribution or the grain size of the 50th percentile or d50 (Davis, 1992). In other words, the grain size where 50 percent of the sample mass is finer. The 10th percentile or d10 of a sample is commonly, but not always, referred to as the effective grain size. The uniformity coefficient or Cu is a measure of the degree of sorting in a sample distribution and is the ratio of d60/d10 (Fetter, 1994). A sample with a uniformity coefficient less than 4 is

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Appendix A (Continued) 67 Figure A.1. Example of hygroscopic moisture laboratory worksheet.

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Appendix A (Continued) 68 Figure A.2. Example of grain-size distribution analysis laboratory worksheet.

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Appendix A (Continued) 69 considered well sorted while a coefficient more than 6 is considered poorly sorted (Fetter, 1994). Porosity, n, can be approximated using an empirical relationship by Istomina (1957 as cited in Vukovic et.al., 1992) based on the uniformity coefficient: 83 0 1 255 0 n where is the symbol used by Istomina for uniformity coefficient or d60/d10. Other statistical parameters generally used to describe grain size distribution include the mean and standard deviation (also referred to as sorting value). According to Folk (1974 as cited in Davis, 1992), the mean grain size of a sediment tends to reflect characteristics of the transporting media prior to deposition while sorting reflects processes that occur after deposition. A public-domain software Fortran program (Vukovic et. al., 1992) allows quick computation of these values for each sample from input files of cumulative percent finer versus grain-size diameter (Figure A.3). Complications occurred with the software when calculating de for formulas with de = d10. Some samples contained clay fractions greater than 10 percent of the sample mass and therefore were unable to generate a d10 value from the curve (there is no d10 grain size if the smallest particles, clay, make up more than 10 percent of the total mass). Values of d10 for these particular samples were approximated from the distribution curve to estimate uniformity coefficient. The program also calculates porosity (n) using the formula introduced earlier.

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Appendix A (Continued) 70 Mw1-a (0-2') NUMBER OF DIVISIONS OF THE GRAIN-SIZE CURVE 1 CASE 1 17 FRACTIONS D A T A E N T R Y NUMBER OF FRACTIONS ON GRAIN-SIZE COMPOSITION CURVE -17, POROSITY n = .45 *) *) Warning Porosity n computed on the basis of Eq.(53) PERCENT (%) GRAIN DIAMETER D(mm) 1.28 .0014 1.74 .0034 1.89 .0069 1.99 .0097 2.24 .0138 2.24 .0238 3.24 .0375 5.86 .0750 10.91 .0900 66.30 .1250 88.94 .1800 97.73 .2500 98.45 .3550 98.95 .5000 99.17 .7100 99.40 1.0000 99.59 1.4000 99.73 2.0000 EFFECTIVE GRAIN DIAMETERS D10 = .0871(mm) D17 = .0933 (mm) D20 =.0950 (mm) DKRUE = .091 (mm), DKOZ = .085 (mm), DZUN = .087 (mm), DZAM = .089 (mm) D60 = .1204 (mm) ETA = 1.38 D50 = .11 H Y D R A U L I C C O N D U C T I V I T Y (m/s) at 15 deg. C ================================================================ AFTER HAZEN K = .114E-03 AFTER SLICHTER K = .480E-04 AFTER TERZAGHI K = .849E-04 *(0.73 1.27) AFTER BEYER K = .868E-04 AFTER SAUERBREI K = .865E-04 AFTER KRUEGERR K = .536E-04 AFTER KOZENY K = .159E-03 AFTER ZUNKER K = .685E-04 *(0.45 1.55) AFTER ZAMARINU K = .642E-04 AFTER USBR K = .161E-04 Figure A.3. Example of the MVASKF program output reports.

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Appendix B. Permeameter Testing Procedures 71 The guidelines used for permeameter analyses were based on those specified in the standard test method for permeability of granular soils published by the American Society for Testing and Materials (ASTM, 1972). Minor variations were made to the procedure for sample preparation such as the use of a manual rather than mechanical tamping device for compaction of soil in the sample chamber. This method describes the determination of the coefficient of permeability using a constant-head apparatus for laminar flow of water through granular soils under constant-head conditions and is limited to disturbed granular soils containing not more than 10% soil passing the No. 200 (75 um) sieve (ie. clay-size). A falling-head permeameter testing apparatus was designed for more cohesive samples containing more than 10% soil passing the no. 200 sieve or clay based on the design described by Freeze and Cherry (1979). An example of the data worksheets used during laboratory testing of samples during constant and falling-head permeameter analyses for all 111 samples is shown in figure B.1. The specific procedures and design for both types of tests are as follows: Constant-head test For non-cohesive, disturbed granular sediments (<10% passing the No. 200 sieve), a funnel with overflow provides a supply of water maintaining a constant head that moves water through a sediment chamber at some lower height (smaller head) at a steady rate. By recording the sample volume of water V that drains from the permeameter over some time t, the hydraulic conductivity of the soil can be calculated by a variation of Darcy's law that relates the hydraulic conductivity K to the volume of water discharging in time t (Q), the length of the sample L, the cross-sectional area A, and the hydraulic gradient across the sample dh where: ) ( ( ) ( )) ( ( ) (1 2 1 2h h At VL h h A QL K where Q = V/t h2h1 = change in head across the sample h1 = h at the funnel aperature h2 = head at the discharge spout of the sample chamber

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Appendix B (Continued) 72 Figure B.1. Example of permeameter testing laboratory worksheet.

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Appendix B (Continued) 73 L = length of the sample = 7.4 cm A = cross-sectional area of the sample chamber = 11.4 cm T = time in seconds Falling-Head test For cohesive, disturbed granular sediments (>10% passing the No. 200 sieve), a fallinghead Tygon flexible tube is attached to the permeameter. The initial water level above the outlet in the falling-head tube, h0 is measured. After some time t, the new water level, h, is again noted. The inside diameter of the falling-head tube, dt, the length of the sample, L, and the diameter of the sample, dc, must also be measured. Using a variation of the constant-head equation along with the conservation of mass, the fallinghead equation can be expressed as: ) ln( ) (0 2 2h h t d L d Kc t where: dt = diameter of the tube = 1.2 cm L = length of the sample = 7.4 cm dc = sample diameter = 3.81 cm

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Appendix C. Geophysical Logs from Completed Monitor Wells 74 Appendix C.1. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 1 – deep surficial monitor well (MW1).

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Appendix C (Continued) 75 Appendix C.2. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 2 – deep surficial monitor well (MW3).

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Appendix C (Continued) 76 Appendix C.3. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 3 – deep surficial monitor well (MW5).

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Appendix C (Continued) 77 Appendix C.4. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 4 – deep surficial monitor well (MW7).

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Appendix C (Continued) 78 Appendix C.5. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 5 – deep surficial monitor well (MW9).

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Appendix C (Continued) 79 Appendix C.6. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 1 – deep surficial monitor well (FMW1).

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Appendix C (Continued) 80 Appendix C.7. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 2 – deep surficial monitor well (FMW2).

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Appendix C (Continued) 81 Appendix C.8. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 3 – deep surficial monitor well (FMW3).

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Appendix C (Continued) 82 Appendix C.9. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 4 – deep surficial monitor well (FMW4).

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Appendix C (Continued) 83 Appendix C.10. Geophysical Logs (Natural Gamma, Conductivity, Resistivity) at Site 5 – deep surficial monitor well (FMW5).

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Appendix D. Grain-size Distribution Frequency Plots 84 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-a 0.0-0.3 m0.1-0.2 m cumulative D(mm)phi% finer% 0.0029.41.280.46clay 0.0048.11.740.15 0.0077.11.890.10 0.0106.61.990.25silt 0.0156.12.240.00 0.0255.32.241.00 0.0404.73.242.61 0.0753.75.865.06 0.093.510.9155.39 0.1253.066.3022.64 0.182.588.948.80 0.252.097.730.71 0.3551.598.450.50sand 0.51.098.950.22 0.710.599.170.23 10.099.400.19 1.4-0.599.590.14 2-1.099.730.27 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

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Appendix D (Continued) 85 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-b 0.30-1.22 m0.8-0.9 m cumulative D(mm)phi% finer% 0.0029.41.170.31clay 0.0048.11.490.25 0.0077.11.740.25 0.0106.61.990.25silt 0.0156.12.240.50 0.0255.32.740.00 0.0404.72.742.65 0.0753.75.394.65 0.093.510.0447.36 0.1253.057.4032.43 0.182.589.848.54 0.252.098.380.88 0.3551.599.260.51sand 0.51.099.770.16 0.710.599.930.04 10.099.970.02 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 86 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-c 1.22-1.83 m1.5-1.6 m cumulative D(mm)phi% finer% 0.0029.40.050.05clay 0.0048.10.100.50 0.0077.10.600.10 0.0106.60.700.15silt 0.0156.10.850.50 0.0255.31.360.25 0.0404.61.613.63 0.0753.75.243.82 0.093.59.0646.60 0.1253.055.6634.46 0.182.590.128.53 0.252.098.650.73 0.3551.599.390.40sand 0.51.099.790.11 0.710.599.900.04 10.099.940.03 1.4-0.599.970.01 2-1.099.980.02 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 87 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-d 1.83-2.43 m2.1-2.2 m cumulative D(mm)phi% finer% 0.0019.42.510.71clay 0.0048.13.220.90 0.0077.14.130.10 0.0106.64.230.75silt 0.0146.14.980.50 0.0255.35.480.50 0.0394.75.982.56 0.0753.78.553.21 0.093.511.7645.72 0.1253.057.4731.77 0.182.589.249.18 0.252.098.420.95 0.3551.599.370.46sand 0.51.099.830.11 0.710.599.940.04 10.099.980.01 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 88 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-e 2.43-2.74 m2.5-2.6 m cumulative D(mm)phi% finer% 0.0019.44.400.60clay 0.0048.25.000.73 0.0077.15.730.25 0.0106.65.980.25silt 0.0146.16.230.25 0.0255.36.480.50 0.0394.76.992.58 0.0753.79.573.41 0.093.512.9844.37 0.1253.057.3531.50 0.182.588.869.67 0.252.098.530.95 0.3551.599.480.42sand 0.51.099.900.08 0.710.599.980.02 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 89 North Lakes WetlandGrain-Size Distribution lithos. layersample depth Sample: MW1-f 2.74-3.05 m2.8-2.9 m cumulative D(mm)phi% finer% 0.0019.515.490.85clay 0.0038.316.340.20 0.0077.216.530.20 0.0096.716.740.25silt 0.0136.216.990.64 0.0235.417.630.00 0.0374.817.633.99 0.0753.721.627.33 0.093.528.9644.99 0.1253.073.9518.23 0.182.592.176.88 0.252.099.050.61 0.3551.599.660.28sand 0.51.099.940.06 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 90 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-g 3.05-3.66 m3.4-3.5 m cumulative D(mm)phi% finer% 0.0019.514.530.87clay 0.0038.215.400.37 0.0077.215.780.40 0.0106.716.180.39silt 0.0136.216.570.25 0.0235.416.820.00 0.0374.816.822.96 0.0753.719.786.26 0.093.526.0444.90 0.1253.070.9420.49 0.182.591.437.51 0.252.098.940.65 0.3551.599.590.35sand 0.51.099.940.06 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 91 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-h 3.66-4.27 m3.9-4.0 m cumulative D(mm)phi% finer% 0.0019.515.760.60clay 0.0038.316.360.00 0.0077.216.360.39 0.0096.716.750.00silt 0.0136.216.750.15 0.0235.416.910.10 0.0374.817.015.43 0.0753.722.447.63 0.093.530.0747.99 0.1253.078.0613.81 0.182.591.877.10 0.252.098.960.61 0.3551.599.570.36sand 0.51.099.930.06 0.710.599.990.01 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 92 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-i 4.27-5.33 m4.7-4.8 m cumulative D(mm)phi% finer% 0.0019.513.160.47clay 0.0038.213.640.27 0.0077.213.910.00 0.0106.713.910.04silt 0.0146.213.950.10 0.0245.414.050.26 0.0374.714.305.24 0.0753.719.547.30 0.093.526.8444.17 0.1253.071.0119.88 0.182.590.897.76 0.252.098.650.89 0.3551.599.540.38sand 0.51.099.920.08 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 93 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-j 5.33-5.49 m5.35-5.45 m cumulative D(mm)phi% finer% 0.0019.516.520.85clay 0.0038.317.360.79 0.0077.218.150.04 0.0096.718.190.10silt 0.0136.218.290.77 0.0235.519.060.51 0.0364.819.579.66 0.0753.729.239.33 0.093.538.5742.38 0.1253.080.9510.84 0.182.591.796.59 0.252.098.380.91 0.3551.599.290.49sand 0.51.099.790.12 0.710.599.910.04 10.099.950.03 1.4-0.599.980.02 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 94 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-aa 5.49-6.10 m5.8-5.9 m cumulative D(mm)phi% finer% 0.0019.41.540.03clay 0.0048.11.580.27 0.0077.11.850.00 0.0106.61.850.11silt 0.0146.11.960.16 0.0255.32.120.00 0.0404.72.121.52 0.0753.73.642.76 0.093.56.3927.94 0.1253.034.3430.63 0.182.564.9718.85 0.252.083.8110.92 0.3551.594.733.94sand 0.51.098.671.07 0.710.599.740.21 10.099.950.04 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

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Appendix D (Continued) 95 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-bb 6.10-6.71 m6.4-6.5 m cumulative D(mm)phi% finer% 0.0019.40.740.03clay 0.0048.10.770.00 0.0077.10.770.83 0.0106.61.600.00silt 0.0156.11.600.00 0.0255.31.600.28 0.0404.71.882.92 0.0753.74.804.33 0.093.59.1326.23 0.1253.035.3636.12 0.182.571.4816.92 0.252.088.418.31 0.3551.596.712.59sand 0.51.099.300.59 0.710.599.890.09 10.099.980.02 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 96 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-cc 6.71-7.31 m7.0-7.1 m cumulative D(mm)phi% finer% 0.0019.40.850.03clay 0.0048.10.890.17 0.0077.11.060.00 0.0106.61.060.00silt 0.0156.11.060.00 0.0255.31.060.00 0.0404.61.061.30 0.0753.72.353.14 0.093.55.4924.72 0.1253.030.2135.01 0.182.565.2218.08 0.252.083.3010.98 0.3551.594.294.12sand 0.51.098.401.28 0.710.599.690.23 10.099.920.08 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 97 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-dd 7.31-7.62 m7.4-7.5 m cumulative D(mm)phi% finer% 0.0019.40.160.23clay 0.0048.10.390.00 0.0077.10.390.00 0.0106.60.390.00silt 0.0156.10.390.00 0.0255.30.390.00 0.0404.60.390.57 0.0753.70.960.76 0.093.51.729.29 0.1253.011.0116.42 0.182.527.4332.63 0.252.060.0632.19 0.3551.592.256.67sand 0.51.098.920.94 0.710.599.860.10 10.099.960.04 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 98 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-ee 7.62-8.53 m8.0-8.1 m cumulative D(mm)phi% finer% 0.0019.43.720.08clay 0.0048.23.800.03 0.0077.13.830.25 0.0106.64.080.00silt 0.0146.14.080.10 0.0255.34.180.00 0.0394.74.188.44 0.0753.712.620.67 0.093.513.2912.99 0.1253.026.2912.96 0.182.539.2534.52 0.252.073.7719.44 0.3551.593.215.79sand 0.51.099.000.89 0.710.599.890.10 10.099.990.01 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 99 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-ff 8.53-9.14 m8.7-8.8 m cumulative D(mm)phi% finer% 0.0019.47.190.13clay 0.0038.27.320.00 0.0077.27.320.00 0.0106.77.320.14silt 0.0146.27.460.00 0.0245.47.460.00 0.0394.77.464.24 0.0753.711.700.83 0.093.512.5314.12 0.1253.026.6524.00 0.182.550.6522.83 0.252.073.4817.08 0.3551.590.566.79sand 0.51.097.341.73 0.710.599.070.37 10.099.440.15 1.4-0.599.590.14 2-1.099.740.26 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 100 North Lakes WetlandGrain-Size Distribution lithos. layersample 9.14-9.75 m9.4-9.5 m Sample: MW1-gg cumulative D(mm)phi% finer% 0.0019.47.202.21clay 0.0038.29.400.41 0.0077.29.821.07 0.0106.710.881.18silt 0.0146.212.070.89 0.0245.412.952.66 0.0374.815.627.51 0.0753.723.123.24 0.093.526.3720.85 0.1253.047.2227.35 0.182.574.5711.95 0.252.086.526.20 0.3551.592.722.50sand 0.51.095.221.35 0.710.596.570.83 10.097.400.56 1.4-0.597.950.46 2-1.098.411.59 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 101 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW1-hh 9.75-10.06 m9.85-9.95 m cumulative D(mm)phi% finer% 0.0019.42.403.23clay 0.0048.15.636.51 0.0077.112.140.29 0.0106.612.432.89silt 0.0146.115.3322.14 0.0245.437.476.51 0.0374.843.9814.28 0.0753.758.265.01 0.093.563.2711.40 0.1253.074.676.92 0.182.581.597.29 0.252.088.894.89 0.3551.593.782.66sand 0.51.096.441.77 0.710.598.210.81 10.099.020.38 1.4-0.599.390.26 2-1.099.650.35 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 110

Appendix D (Continued) 102 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-a 0.0-0.3 m0.1-0.2 m cumulative D(mm)phi% finer% 0.0019.41.450.33clay 0.0048.11.780.03 0.0077.11.810.10 0.0106.61.910.00silt 0.0146.11.910.75 0.0255.32.660.00 0.0394.72.661.75 0.0753.74.413.41 0.093.57.8238.92 0.1253.046.7342.19 0.182.588.938.38 0.252.097.301.96 0.3551.599.270.46sand 0.51.099.730.15 0.710.599.880.06 10.099.940.02 1.4-0.599.960.02 2-1.099.980.02 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 111

Appendix D (Continued) 103 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-b 0.3-1.22 m0.7-0.8 m cumulative D(mm)phi% finer% 0.0019.41.650.50clay 0.0048.22.150.27 0.0077.12.420.25 0.0106.62.670.00silt 0.0146.12.670.15 0.0255.32.820.00 0.0394.72.822.16 0.0753.74.983.54 0.093.58.5239.26 0.1253.047.7842.42 0.182.590.207.75 0.252.097.951.65 0.3551.599.600.31sand 0.51.099.910.07 0.710.599.980.02 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 112

Appendix D (Continued) 104 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-c 1.22-1.83 m1.5-1.6 m cumulative D(mm)phi% finer% 0.0019.40.770.12clay 0.0048.10.880.09 0.0077.10.970.20 0.0106.61.170.00silt 0.0146.11.170.35 0.0255.31.520.15 0.0394.71.672.96 0.0753.74.643.12 0.093.57.7640.03 0.1253.047.7942.61 0.182.590.397.73 0.252.098.121.48 0.3551.599.610.30sand 0.51.099.910.07 0.710.599.980.01 10.099.990.00 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 113

Appendix D (Continued) 105 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-d 1.83-2.43 m2.1-2.2 m cumulative D(mm)phi% finer% 0.0019.41.450.73clay 0.0048.22.180.36 0.0077.12.550.00 0.0106.62.550.46silt 0.0146.13.010.12 0.0255.33.120.12 0.0394.73.240.02 0.0753.73.263.26 0.093.56.5147.15 0.1253.053.6636.14 0.182.589.808.22 0.252.098.031.52 0.3551.599.550.33sand 0.51.099.880.08 0.710.599.970.02 10.099.990.01 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 114

Appendix D (Continued) 106 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-e 2.43-3.05 m2.7-2.8 m cumulative D(mm)phi% finer% 0.0019.510.771.12clay 0.0038.211.890.02 0.0077.211.910.44 0.0106.712.360.00silt 0.0146.212.360.29 0.0245.412.640.29 0.0384.712.935.23 0.0753.718.165.75 0.093.523.9138.58 0.1253.062.4929.67 0.182.592.166.18 0.252.098.341.29 0.3551.599.630.27sand 0.51.099.910.06 0.710.599.970.01 10.099.980.00 1.4-0.599.980.00 2-1.099.980.02 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 115

Appendix D (Continued) 107 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-f 3.05-3.66 m3.2-3.3 m cumulative D(mm)phi% finer% 0.0019.511.800.72clay 0.0038.212.510.74 0.0077.213.250.57 0.0106.713.820.28silt 0.0146.214.110.34 0.0235.414.450.38 0.0374.814.833.03 0.0753.717.856.83 0.093.524.6937.70 0.1253.062.3828.65 0.182.591.036.94 0.252.097.971.58 0.3551.599.550.37sand 0.51.099.920.07 0.710.599.990.01 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 116

Appendix D (Continued) 108 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-g 3.66-4.27 m3.9-4.0 m cumulative D(mm)phi% finer% 0.0019.511.931.38clay 0.0038.213.301.37 0.0077.214.680.74 0.0106.715.420.90silt 0.0136.216.320.28 0.0235.416.600.57 0.0374.817.175.40 0.0753.722.577.77 0.093.530.3437.52 0.1253.067.8623.98 0.182.591.846.21 0.252.098.051.49 0.3551.599.550.36sand 0.51.099.910.08 0.710.599.990.01 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 117

Appendix D (Continued) 109 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-h 4.27-5.27 m4.7-4.8 m cumulative D(mm)phi% finer% 0.0019.510.361.24clay 0.0038.211.601.26 0.0077.212.871.04 0.0106.713.911.06silt 0.0146.214.971.11 0.0235.416.080.56 0.0374.816.644.42 0.0753.721.067.30 0.093.528.3636.31 0.1253.064.6726.12 0.182.590.796.86 0.252.097.651.81 0.3551.599.450.41sand 0.51.099.870.11 0.710.599.980.02 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 118

Appendix D (Continued) 110 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-aa 5.27-5.79 m5.4-5.5 m cumulative D(mm)phi% finer% 0.0019.516.700.84clay 0.0038.317.540.34 0.0077.217.880.54 0.0096.718.410.11silt 0.0136.218.520.00 0.0235.418.520.43 0.0364.818.9511.59 0.0753.730.547.77 0.093.538.3146.66 0.1253.084.9711.80 0.182.596.772.67 0.252.099.430.47 0.3551.599.900.09sand 0.51.099.990.01 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 119

Appendix D (Continued) 111 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-bb 5.79-6.71 m6.2-6.3 m cumulative D(mm)phi% finer% 0.0019.41.870.00clay 0.0048.11.870.29 0.0077.12.160.10 0.0106.62.260.10silt 0.0146.12.370.05 0.0255.32.420.00 0.0404.72.4210.93 0.0753.713.353.77 0.093.517.1225.68 0.1253.042.8033.88 0.182.576.6813.51 0.252.090.196.99 0.3551.597.182.11sand 0.51.099.290.54 0.710.599.820.11 10.099.940.03 1.4-0.599.970.03 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 120

Appendix D (Continued) 112 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-cc 6.71-7.31 m6.9-7.0 m cumulative D(mm)phi% finer% 0.0019.46.780.23clay 0.0038.27.010.41 0.0077.17.420.00 0.0106.67.420.00silt 0.0146.17.420.00 0.0245.47.420.16 0.0394.77.586.09 0.0753.713.682.07 0.093.515.7516.57 0.1253.032.3217.60 0.182.549.9118.03 0.252.067.9519.96 0.3551.587.919.36sand 0.51.097.262.33 0.710.599.590.31 10.099.900.06 1.4-0.599.970.03 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 121

Appendix D (Continued) 113 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-dd 7.31-7.92 m7.5-7.6 m cumulative D(mm)phi% finer% 0.0019.46.090.08clay 0.0038.26.170.42 0.0077.16.590.15 0.0106.66.730.00silt 0.0146.16.730.11 0.0245.46.840.00 0.0394.76.846.03 0.0753.712.871.98 0.093.514.8537.14 0.1253.051.9933.54 0.182.585.537.73 0.252.093.264.45 0.3551.597.711.66sand 0.51.099.370.52 0.710.599.890.08 10.099.970.02 1.4-0.599.990.00 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 122

Appendix D (Continued) 114 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-ee 7.92-8.53 m8.4-8.5 m cumulative D(mm)phi% finer% 0.0019.49.350.52clay 0.0038.29.870.43 0.0077.210.300.17 0.0106.710.470.11silt 0.0146.210.580.17 0.0245.410.750.39 0.0384.711.143.16 0.0753.714.301.19 0.093.515.4935.54 0.1253.051.0335.57 0.182.586.608.43 0.252.095.033.28 0.3551.598.311.21sand 0.51.099.520.35 0.710.599.870.06 10.099.920.00 1.4-0.599.920.01 2-1.099.930.07 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 123

Appendix D (Continued) 115 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-x 8.53-8.84 m8.6-8.7 m cumulative D(mm)phi% finer% 0.0019.511.580.35clay 0.0038.211.930.00 0.0077.211.930.21 0.0106.712.140.48silt 0.0146.212.610.42 0.0245.413.040.11 0.0374.713.143.01 0.0753.716.161.90 0.093.518.0633.90 0.1253.051.9532.80 0.182.584.759.22 0.252.093.973.75 0.3551.597.721.48sand 0.51.099.200.43 0.710.599.630.08 10.099.710.05 1.4-0.599.770.04 2-1.099.810.19 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 124

Appendix D (Continued) 116 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-ff 8.84-9.14 m8.9-9.0 m cumulative D(mm)phi% finer% 0.0019.519.972.75clay 0.0038.322.732.70 0.0077.325.431.64 0.0096.827.081.45silt 0.0136.328.522.43 0.0225.530.961.32 0.0344.932.2716.25 0.0753.748.533.84 0.093.552.3718.04 0.1253.070.4114.79 0.182.585.205.46 0.252.090.663.09 0.3551.593.751.97sand 0.51.095.721.53 0.710.597.251.07 10.098.320.46 1.4-0.598.780.41 2-1.099.180.82 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 125

Appendix D (Continued) 117 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-gg 9.91-9.98 m9.91-9.98 m cumulative D(mm)phi% finer% 0.0019.525.593.32clay 0.0038.328.922.68 0.0067.331.591.89 0.0096.833.481.53silt 0.0126.335.011.82 0.0215.636.841.21 0.0344.938.059.36 0.0753.747.412.06 0.093.549.4717.07 0.1253.066.5517.56 0.182.584.106.18 0.252.090.283.45 0.3551.593.742.00sand 0.51.095.741.55 0.710.597.290.92 10.098.210.45 1.4-0.598.650.38 2-1.099.030.97 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 126

Appendix D (Continued) 118 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW2-xx 8.84-9.91 m9.5-9.6 m cumulative D(mm)phi% finer% 0.0019.524.553.67clay 0.0038.228.223.17 0.0077.231.391.05 0.0106.732.441.58silt 0.0146.234.021.58 0.0235.435.602.37 0.0374.837.9713.77 0.0753.751.742.68 0.093.554.4214.76 0.1253.069.1814.68 0.182.583.876.24 0.252.090.113.21 0.3551.593.321.47sand 0.51.094.790.84 0.710.595.630.39 10.096.030.24 1.4-0.596.260.26 2-1.096.533.47 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 127

Appendix D (Continued) 119 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-a 0.3-0.61 m0.4-0.5 m cumulative D(mm)phi% finer% 0.0029.40.130.15clay 0.0048.10.280.01 0.0077.10.300.07 0.0106.60.370.02silt 0.0156.10.390.10 0.0255.30.490.12 0.0404.60.611.84 0.0753.72.454.17 0.093.56.6346.68 0.1253.053.3035.85 0.182.589.158.04 0.252.097.192.12 0.3551.599.310.53sand 0.51.099.840.12 0.710.599.960.01 10.099.970.02 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 128

Appendix D (Continued) 120 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-b 0.61-1.52 m1.2-1.3 cumulative D(mm)phi% finer% 0.0019.41.140.18clay 0.0048.11.310.24 0.0077.11.550.17 0.0106.61.720.00silt 0.0146.11.720.27 0.0255.31.990.00 0.0404.71.992.17 0.0753.74.164.13 0.093.58.3045.05 0.1253.053.3437.24 0.182.590.587.33 0.252.097.911.50 0.3551.599.410.36sand 0.51.099.770.11 0.710.599.880.05 10.099.930.03 1.4-0.599.960.02 2-1.099.980.02 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 129

Appendix D (Continued) 121 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-c 1.52-2.44 m1.9-2.0 m cumulative D(mm)phi% finer% 0.0029.40.230.30clay 0.0048.10.530.44 0.0077.10.970.25 0.0106.61.220.00silt 0.0156.11.220.12 0.0255.31.340.20 0.0404.71.542.09 0.0753.73.633.86 0.093.57.5044.00 0.1253.051.5039.66 0.182.591.166.93 0.252.098.091.44 0.3551.599.530.32sand 0.51.099.850.10 0.710.599.950.02 10.099.970.02 1.4-0.599.990.00 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 130

Appendix D (Continued) 122 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-d 2.44-2.59 m2.45-2.55 m cumulative D(mm)phi% finer% 0.0019.40.490.25clay 0.0048.10.730.09 0.0077.10.820.15 0.0106.60.970.50silt 0.0156.11.470.78 0.0255.32.250.10 0.0404.72.353.36 0.0753.75.714.38 0.093.510.0945.69 0.1253.055.7834.48 0.182.590.266.51 0.252.096.771.36 0.3551.598.130.33sand 0.51.098.470.15 0.710.598.620.11 10.098.730.14 1.4-0.598.870.23 2-1.099.100.90 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 131

Appendix D (Continued) 123 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-e 2.59-2.74 m2.2.6-2.7 m cumulative D(mm)phi% finer% 0.0019.41.360.20clay 0.0048.11.570.02 0.0077.11.580.02 0.0106.61.600.22silt 0.0146.11.820.20 0.0255.32.020.20 0.0404.72.222.33 0.0753.74.555.76 0.093.510.3154.06 0.1253.064.3727.74 0.182.592.116.11 0.252.098.221.34 0.3551.599.560.29sand 0.51.099.850.10 0.710.599.950.03 10.099.980.01 1.4-0.599.990.00 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 132

Appendix D (Continued) 124 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-f 2.74-3.05 m2.8-2.9 m cumulative D(mm)phi% finer% 0.0019.512.840.69clay 0.0038.213.530.03 0.0077.213.560.48 0.0106.714.040.25silt 0.0136.214.290.15 0.0235.414.440.00 0.0374.814.443.36 0.0753.717.806.73 0.093.524.5343.49 0.1253.068.0226.58 0.182.594.604.23 0.252.098.830.80 0.3551.599.640.23sand 0.51.099.870.12 0.710.599.990.01 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 133

Appendix D (Continued) 125 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-g 3.05-3.2 m3.05-3.15 m cumulative D(mm)phi% finer% 0.0019.45.680.36clay 0.0038.26.040.02 0.0077.16.060.09 0.0106.66.150.15silt 0.0146.16.300.15 0.0245.46.450.15 0.0394.76.603.51 0.0753.710.118.25 0.093.518.3757.05 0.1253.075.4220.26 0.182.595.683.47 0.252.099.150.70 0.3551.599.850.13sand 0.51.099.980.02 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 134

Appendix D (Continued) 126 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-h 3.20-4.88 m4.1-4.2 m cumulative D(mm)phi% finer% 0.0019.516.080.21clay 0.0038.316.290.11 0.0077.216.400.00 0.0096.716.400.02silt 0.0136.216.420.12 0.0235.416.540.00 0.0364.816.543.43 0.0753.719.978.40 0.093.528.3749.52 0.1253.077.8917.26 0.182.595.154.26 0.252.099.410.53 0.3551.599.940.05sand 0.51.099.990.01 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 135

Appendix D (Continued) 127 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-i 4.88-5.72 m5.2-5.3 m cumulative D(mm)phi% finer% 0.0019.515.240.31clay 0.0038.315.550.53 0.0077.216.090.10 0.0096.716.190.35silt 0.0136.216.540.07 0.0235.416.610.30 0.0364.816.916.19 0.0753.723.107.99 0.093.531.0940.47 0.1253.071.5622.48 0.182.594.044.12 0.252.098.161.28 0.3551.599.440.37sand 0.51.099.810.13 0.710.599.940.04 10.099.980.01 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 136

Appendix D (Continued) 128 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-j 5.79-6.40 m6.0-6.1 m cumulative D(mm)phi% finer% 0.0019.43.670.03clay 0.0048.23.700.15 0.0077.13.850.20 0.0106.64.050.22silt 0.0146.14.270.15 0.0255.34.410.00 0.0394.74.411.79 0.0753.76.213.04 0.093.59.2536.45 0.1253.045.7028.06 0.182.573.7515.12 0.252.088.877.07 0.3551.595.942.79sand 0.51.098.731.01 0.710.599.740.21 10.099.950.05 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 137

Appendix D (Continued) 129 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-k 6.71-7.01 m6.8-6.9 m cumulative D(mm)phi% finer% 0.0019.46.150.11clay 0.0038.26.260.10 0.0077.26.360.20 0.0106.76.560.00silt 0.0146.26.560.15 0.0245.46.710.00 0.0384.76.711.08 0.0753.77.791.28 0.093.59.0823.37 0.1253.032.4537.83 0.182.570.2817.44 0.252.087.728.44 0.3551.596.162.93sand 0.51.099.090.74 0.710.599.830.13 10.099.960.02 1.4-0.599.980.02 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 138

Appendix D (Continued) 130 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: MW5-l 7.32-7.62 m7.4-7.5 m cumulative D(mm)phi% finer% 0.0019.45.290.09clay 0.0038.25.370.20 0.0077.15.580.15 0.0106.65.730.00silt 0.0146.15.730.14 0.0245.45.870.00 0.0394.75.871.57 0.0753.77.441.78 0.093.59.2225.69 0.1253.034.9042.61 0.182.577.5213.36 0.252.090.885.35 0.3551.596.232.45sand 0.51.098.680.87 0.710.599.550.25 10.099.800.07 1.4-0.599.870.00 2-1.099.870.13 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 139

Appendix D (Continued) 131 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-a 0.3-0.61 m0.4-0.5 m cumulative D(mm)phi% finer% 0.0019.42.520.38clay 0.0048.12.910.11 0.0077.13.020.31 0.0106.63.330.20silt 0.0146.13.530.10 0.0255.33.630.10 0.0404.73.731.67 0.0753.75.403.97 0.093.59.3740.20 0.1253.049.5742.07 0.182.591.646.65 0.252.098.301.37 0.3551.599.670.25sand 0.51.099.920.06 0.710.599.980.02 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 140

Appendix D (Continued) 132 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-b 0.61-1.52 m1.0-1.1 m cumulative D(mm)phi% finer% 0.0019.41.620.48clay 0.0048.12.100.51 0.0077.12.620.01 0.0106.62.620.08silt 0.0156.12.700.00 0.0255.32.700.40 0.0404.73.101.91 0.0753.75.014.07 0.093.59.0845.49 0.1253.054.5737.14 0.182.591.716.49 0.252.098.211.30 0.3551.599.510.32sand 0.51.099.830.09 0.710.599.920.03 10.099.950.02 1.4-0.599.970.02 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 141

Appendix D (Continued) 133 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-c 1.52-1.82 m1.6-1.7 m cumulative D(mm)phi% finer% 0.0019.41.120.70clay 0.0048.11.820.17 0.0077.11.990.78 0.0106.62.770.10silt 0.0156.12.880.65 0.0255.33.530.00 0.0404.73.533.53 0.0753.77.068.59 0.093.515.6552.38 0.1253.068.0226.60 0.182.594.624.23 0.252.098.860.91 0.3551.599.770.19sand 0.51.099.960.03 0.710.599.990.01 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 142

Appendix D (Continued) 134 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-d 1.82-2.13 m1.9-2.0 m cumulative D(mm)phi% finer% 0.0019.43.730.60clay 0.0048.24.330.57 0.0077.14.900.75 0.0106.65.650.24silt 0.0146.15.890.65 0.0255.36.540.10 0.0394.76.644.38 0.0753.711.026.50 0.093.517.5249.05 0.1253.066.5728.22 0.182.594.794.29 0.252.099.090.73 0.3551.599.820.15sand 0.51.099.970.03 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 143

Appendix D (Continued) 135 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-e 2.13-2.29 m2.15-2.25 m cumulative D(mm)phi% finer% 0.0019.45.780.59clay 0.0038.26.370.10 0.0077.16.470.13 0.0106.66.600.13silt 0.0146.16.730.00 0.0255.36.730.00 0.0394.76.734.43 0.0753.711.168.59 0.093.519.7552.66 0.1253.072.4022.03 0.182.594.443.81 0.252.098.251.07 0.3551.599.320.31sand 0.51.099.630.18 0.710.599.810.12 10.099.930.05 1.4-0.599.980.02 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 144

Appendix D (Continued) 136 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-f 2.29-3.66 m3.3-3.4 m cumulative D(mm)phi% finer% 0.0019.416.580.29clay 0.0038.216.880.01 0.0077.216.890.05 0.0106.716.940.36silt 0.0146.217.300.06 0.0245.417.360.00 0.0384.717.361.80 0.0753.719.153.26 0.093.522.4223.24 0.1253.045.664.63 0.182.550.2921.81 0.252.072.1020.48 0.3551.592.596.02sand 0.51.098.611.39 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 145

Appendix D (Continued) 137 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-g 3.66-3.96 m3.7-3.8 m cumulative D(mm)phi% finer% 0.0019.513.610.19clay 0.0038.213.800.03 0.0077.213.830.00 0.0106.713.830.09silt 0.0146.213.920.00 0.0245.413.920.00 0.0374.713.923.01 0.0753.716.932.49 0.093.519.4323.92 0.1253.043.357.25 0.182.550.6023.57 0.252.074.1821.01 0.3551.595.184.24sand 0.51.099.420.51 0.710.599.930.05 10.099.980.02 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 146

Appendix D (Continued) 138 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-h 3.96-5.49 m5.1-5.2 m cumulative D(mm)phi% finer% 0.0019.59.980.15clay 0.0038.210.140.00 0.0077.210.140.00 0.0106.710.140.03silt 0.0146.210.170.16 0.0245.410.330.00 0.0384.710.336.70 0.0753.717.038.29 0.093.525.3241.52 0.1253.066.8422.96 0.182.589.806.72 0.252.096.522.57 0.3551.599.080.70sand 0.51.099.790.17 0.710.599.960.03 10.099.990.01 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 147

Appendix D (Continued) 139 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-i 5.49-5.79 m5.6-5.7 m cumulative D(mm)phi% finer% 0.0019.43.470.02clay 0.0048.13.500.23 0.0077.13.720.00 0.0106.63.730.00silt 0.0146.13.730.03 0.0255.33.760.00 0.0394.73.761.00 0.0753.74.761.84 0.093.56.6033.10 0.1253.039.7033.29 0.182.572.9915.35 0.252.088.347.72 0.3551.596.052.56sand 0.51.098.611.06 0.710.599.670.25 10.099.920.07 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 148

Appendix D (Continued) 140 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-j 5.79 -6.71 m6.2-6.3 m cumulative D(mm)phi% finer% 0.0019.42.970.22clay 0.0048.13.180.28 0.0077.13.470.25 0.0106.63.720.15silt 0.0146.13.870.00 0.0255.33.870.10 0.0394.73.971.11 0.0753.75.082.40 0.093.57.4827.08 0.1253.034.5528.34 0.182.562.8911.97 0.252.074.8611.62 0.3551.586.497.85sand 0.51.094.333.83 0.710.598.171.30 10.099.470.43 1.4-0.599.900.10 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 149

Appendix D (Continued) 141 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-k 6.71-7.32 m6.95-7.05 m cumulative D(mm)phi% finer% 0.0019.43.220.22clay 0.0048.13.440.28 0.0077.13.730.15 0.0106.63.880.10silt 0.0146.13.980.00 0.0255.33.980.00 0.0394.73.980.82 0.0753.74.791.30 0.093.56.1033.21 0.1253.039.3148.64 0.182.587.948.02 0.252.095.972.48 0.3551.598.451.09sand 0.51.099.540.31 0.710.599.850.09 10.099.940.02 1.4-0.599.960.01 2-1.099.970.03 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 150

Appendix D (Continued) 142 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: FMW4-l 7.32-7.62 m7.4-7.5 cumulative D(mm)phi% finer% 0.0019.42.870.31clay 0.0048.13.180.04 0.0077.13.210.05 0.0106.63.270.45silt 0.0146.13.720.25 0.0255.33.970.50 0.0394.74.472.41 0.0753.76.883.27 0.093.510.1534.21 0.1253.044.3639.13 0.182.583.499.74 0.252.093.234.62 0.3551.597.861.62sand 0.51.099.480.42 0.710.599.900.08 10.099.980.02 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 151

Appendix D (Continued) 143 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-a 0.3-0.91 m0.6-0.7 m cumulative D(mm)phi% finer% 0.0019.41.300.41clay 0.0048.11.710.24 0.0077.11.950.03 0.0106.61.980.10silt 0.0156.12.080.30 0.0255.32.380.00 0.0404.72.381.71 0.0753.74.093.38 0.093.57.4840.26 0.1253.047.7442.54 0.182.590.287.61 0.252.097.891.58 0.3551.599.470.40sand 0.51.099.870.10 0.710.599.970.03 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 152

Appendix D (Continued) 144 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-b 0.91-1.22 m1.0-1.1 m cumulative D(mm)phi% finer% 0.0029.40.030.05clay 0.0048.10.070.15 0.0077.10.220.34 0.0106.60.560.01silt 0.0156.10.570.00 0.0255.30.570.72 0.0404.61.292.40 0.0753.73.683.61 0.093.57.2941.76 0.1253.049.0537.38 0.182.586.438.03 0.252.094.461.61 0.3551.596.063.48sand 0.51.099.540.17 0.710.599.710.10 10.099.820.06 1.4-0.599.880.05 2-1.099.930.07 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 153

Appendix D (Continued) 145 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-c 1.22-1.52 m1.3-1.4 cumulative D(mm)phi% finer% 0.0029.40.050.19clay 0.0048.10.240.90 0.0077.11.140.56 0.0106.61.700.38silt 0.0156.12.081.33 0.0255.33.410.76 0.0394.74.176.45 0.0753.710.623.05 0.093.513.6843.29 0.1253.056.9730.40 0.182.587.369.12 0.252.096.492.40 0.3551.598.890.70sand 0.51.099.590.27 0.710.599.870.10 10.099.970.03 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 154

Appendix D (Continued) 146 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-d 1.52-1.83 m1.6-1.7 cumulative D(mm)phi% finer% 0.0029.40.030.05clay 0.0048.10.070.35 0.0077.10.430.25 0.0106.60.680.36silt 0.0156.11.040.51 0.0255.31.550.54 0.0404.72.084.10 0.0753.76.192.55 0.093.58.7432.42 0.1253.041.1642.18 0.182.583.3411.80 0.252.095.143.23 0.3551.598.370.91sand 0.51.099.280.39 0.710.599.660.16 10.099.830.07 1.4-0.599.900.06 2-1.099.960.04 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 155

Appendix D (Continued) 147 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-e 1.83-2.13 m1.9-2.0 m cumulative D(mm)phi% finer% 0.0029.40.590.63clay 0.0048.11.220.86 0.0077.12.080.87 0.0106.62.950.67silt 0.0146.13.621.44 0.0255.35.061.38 0.0394.76.445.14 0.0753.711.582.86 0.093.514.4434.87 0.1253.049.3137.04 0.182.586.3510.47 0.252.096.822.38 0.3551.599.200.54sand 0.51.099.740.18 0.710.599.930.04 10.099.970.02 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 156

Appendix D (Continued) 148 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-f 2.13-2.74 m2.5-2.6 m cumulative D(mm)phi% finer% 0.0029.40.330.39clay 0.0048.10.720.32 0.0077.11.040.61 0.0106.61.650.30silt 0.0156.11.950.43 0.0255.32.390.91 0.0404.73.305.68 0.0753.78.974.71 0.093.513.6941.95 0.1253.055.6332.12 0.182.587.767.43 0.252.095.192.16 0.3551.597.350.84sand 0.51.098.190.65 0.710.598.840.41 10.099.250.28 1.4-0.599.530.11 2-1.099.640.36 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 157

Appendix D (Continued) 149 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-g 2.74-3.96 m3.2-3.3 m cumulative D(mm)phi% finer% 0.0019.45.600.27clay 0.0038.25.870.19 0.0077.16.060.00 0.0106.66.060.10silt 0.0146.16.160.33 0.0255.36.480.30 0.0394.76.793.83 0.0753.710.616.50 0.093.517.1148.23 0.1253.065.3528.74 0.182.594.084.51 0.252.098.600.95 0.3551.599.550.26sand 0.51.099.810.09 0.710.599.900.03 10.099.930.01 1.4-0.599.940.03 2-1.099.970.03 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 158

Appendix D (Continued) 150 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-h 3.96-5.18 m5.0-5.1 m cumulative D(mm)phi% finer% 0.0019.512.330.02clay 0.0038.212.340.07 0.0077.212.410.40 0.0106.712.820.00silt 0.0146.212.820.00 0.0245.412.820.40 0.0374.713.220.13 0.0753.713.351.46 0.093.514.8232.11 0.1253.046.9348.24 0.182.595.174.56 0.252.099.730.25 0.3551.599.980.02sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 159

Appendix D (Continued) 151 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-i 6.4-7.92 m7.2-7.3 m cumulative D(mm)phi% finer% 0.0019.42.910.16clay 0.0048.13.080.12 0.0077.13.200.00 0.0106.63.200.20silt 0.0146.13.400.20 0.0255.33.600.00 0.0394.73.601.48 0.0753.75.082.30 0.093.57.3832.97 0.1253.040.3531.82 0.182.572.1716.80 0.252.088.977.71 0.3551.596.682.46sand 0.51.099.140.68 0.710.599.820.14 10.099.960.03 1.4-0.599.990.01 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 160

Appendix D (Continued) 152 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-j 7.92-8.53 m8.2-8.3 m cumulative D(mm)phi% finer% 0.0019.43.000.02clay 0.0048.13.020.02 0.0077.13.040.08 0.0106.63.110.05silt 0.0146.13.160.15 0.0255.33.310.20 0.0394.73.511.42 0.0753.74.932.32 0.093.57.2635.14 0.1253.042.3930.88 0.182.573.2716.91 0.252.090.186.71 0.3551.596.892.20sand 0.51.099.090.72 0.710.599.810.15 10.099.960.03 1.4-0.599.990.00 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 161

Appendix D (Continued) 153 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-k 8.53-9.45 m9.0-9.1 m cumulative D(mm)phi% finer% 0.0019.42.320.15clay 0.0048.12.470.17 0.0077.12.640.00 0.0106.62.640.15silt 0.0146.12.790.05 0.0255.32.840.20 0.0404.73.041.79 0.0753.74.822.58 0.093.57.4133.64 0.1253.041.0533.17 0.182.574.2215.86 0.252.090.086.80 0.3551.596.882.32sand 0.51.099.200.65 0.710.599.850.12 10.099.970.02 1.4-0.599.990.00 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 162

Appendix D (Continued) 154 North Lakes WetlandGrain-Size Distribution lithos. Layersample Sample: FMW5-l 9.75-10.67 m10.2-10.3 m cumulative D(mm)phi% finer% 0.0019.42.870.02clay 0.0048.12.890.19 0.0077.13.090.00 0.0106.63.090.05silt 0.0146.13.140.00 0.0255.33.140.00 0.0394.73.140.65 0.0753.73.791.99 0.093.55.7830.43 0.1253.036.2139.59 0.182.575.8014.08 0.252.089.886.68 0.3551.596.562.47sand 0.51.099.040.76 0.710.599.800.13 10.099.930.04 1.4-0.599.970.02 2-1.099.990.01 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 163

Appendix D (Continued) 155 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-a 0.0-0.34 m0.1-0.2 m cumulative D(mm)phi% finer% 0.0019.43.50.79clay 0.0038.24.30.32 0.0077.24.60.70 0.0106.75.30.10silt 0.0146.25.40.06 0.0245.45.50.00 0.0384.75.52.59 0.0753.78.14.10 0.0903.512.236.87 0.1253.049.042.53 0.1802.591.66.39 0.2502.098.01.57 0.3551.599.50.36sand 0.5001.099.90.12 0.7100.5100.00.00 1.0000.0100.00.00 1.400-0.5100.00.00 2.000-1.0100.00.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 164

Appendix D (Continued) 156 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-b 0.34-1.37 m0.85-0.95 m cumulative D(mm)phi% finer% 0.0019.42.460.74clay 0.0038.23.190.27 0.0077.13.470.64 0.0106.64.110.12silt 0.0146.14.230.09 0.0245.44.320.29 0.0394.74.612.02 0.0753.76.633.95 0.093.510.5836.98 0.1253.047.5644.19 0.182.591.746.51 0.252.098.261.51 0.3551.599.770.23sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 165

Appendix D (Continued) 157 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-c 1.37-2.32 m1.85-1.95 m cumulative D(mm)phi% finer% 0.0019.40.550.18clay 0.0048.20.720.71 0.0077.11.430.55 0.0106.61.970.07silt 0.0146.12.040.84 0.0255.32.880.15 0.0394.73.035.18 0.0753.78.217.98 0.093.516.1939.17 0.1253.055.3635.71 0.182.591.075.60 0.252.096.671.55 0.3551.598.210.71sand 0.51.098.930.60 0.710.599.520.36 10.099.880.12 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 166

Appendix D (Continued) 158 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-d 2.32-3.05 m2.65-2.75 m cumulative D(mm)phi% finer% 0.0019.58.760.77clay 0.0038.29.530.77 0.0077.210.301.06 0.0106.711.360.18silt 0.0146.211.541.12 0.0235.412.670.62 0.0374.813.294.71 0.0753.718.005.76 0.093.523.7631.65 0.1253.055.4135.53 0.182.590.947.06 0.252.098.001.76 0.3551.599.760.24sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 167

Appendix D (Continued) 159 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-e 3.05-3.40 m3.2-3.3 m cumulative D(mm)phi% finer% 0.0019.512.820.97clay 0.0038.213.790.48 0.0077.214.260.27 0.0096.714.530.43silt 0.0136.214.960.24 0.0235.415.200.71 0.0374.815.914.92 0.0753.720.837.62 0.093.528.4535.83 0.1253.064.2927.02 0.182.591.317.02 0.252.098.331.43 0.3551.599.760.24sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 168

Appendix D (Continued) 160 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-f 3.40-3.75 m3.54-3.64 m cumulative D(mm)phi% finer% 0.0019.512.960.81clay 0.0038.213.770.36 0.0077.214.130.28 0.0096.714.410.27silt 0.0136.214.680.39 0.0235.415.07-0.03 0.0374.815.046.39 0.0753.721.438.33 0.093.529.7643.81 0.1253.073.5721.90 0.182.595.483.57 0.252.099.050.71 0.3551.599.760.24sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 169

Appendix D (Continued) 161 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-g 3.75-4.91 m4.3-4.4 m cumulative D(mm)phi% finer% 0.0019.43.480.05clay 0.0038.23.520.28 0.0077.13.800.04 0.0106.63.84-0.03silt 0.0146.13.820.12 0.0245.43.930.03 0.0394.73.960.34 0.0753.74.302.09 0.093.56.4026.51 0.1253.032.9147.44 0.182.580.3512.21 0.252.092.565.00 0.3551.597.561.86sand 0.51.099.420.58 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 170

Appendix D (Continued) 162 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-h 4.91-5.55 m5.2-5.3 m cumulative D(mm)phi% finer% 0.0019.40.740.21clay 0.0038.20.950.06 0.0077.11.010.03 0.0106.61.040.03silt 0.0146.11.070.00 0.0255.31.070.01 0.0394.71.081.71 0.0753.72.790.81 0.093.53.605.70 0.1253.09.3022.91 0.182.532.2148.60 0.252.080.8116.40 0.3551.597.212.44sand 0.51.099.650.35 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 171

Appendix D (Continued) 163 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC1-i 5.55-5.76 m5.64-5.74 m cumulative D(mm)phi% finer% 0.0019.43.110.22clay 0.0038.23.330.61 0.0077.13.940.18 0.0106.74.130.22silt 0.0146.24.340.18 0.0245.44.520.00 0.0394.74.520.96 0.0753.75.481.79 0.093.57.2632.74 0.1253.040.0052.38 0.182.592.385.95 0.252.098.331.31 0.3551.599.640.36sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 172

Appendix D (Continued) 164 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-a 0.19-1.57 m1.0-1.1 m cumulative D(mm)phi% finer% 0.0019.42.390.50clay 0.0038.22.890.70 0.0077.23.590.60 0.0106.74.190.30silt 0.0146.24.490.10 0.0245.44.590.00 0.0384.74.591.51 0.0753.76.103.00 0.093.59.1033.10 0.1253.042.2048.50 0.182.590.707.60 0.252.098.301.30 0.3551.599.600.30sand 0.51.099.900.10 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 173

Appendix D (Continued) 165 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-b 1.57-2.94 m2.3-2.4 m cumulative D(mm)phi% finer% 0.0019.41.550.00clay 0.0038.21.550.03 0.0077.11.580.22 0.0106.61.800.30silt 0.0146.12.110.40 0.0245.42.510.15 0.0384.72.662.78 0.0753.75.445.44 0.093.510.8837.26 0.1253.048.1441.79 0.182.589.937.45 0.252.097.381.91 0.3551.599.300.50sand 0.51.099.800.20 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 174

Appendix D (Continued) 166 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-c 2.94-3.77 m3.4-3.5 m cumulative D(mm)phi% finer% 0.0019.513.450.20clay 0.0038.313.650.03 0.0077.213.680.00 0.0096.713.680.17silt 0.0136.213.850.30 0.0235.514.150.07 0.0364.814.222.85 0.0753.717.076.43 0.093.523.4932.63 0.1253.056.1235.34 0.182.591.476.53 0.252.097.991.61 0.3551.599.600.40sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 175

Appendix D (Continued) 167 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-d 3.77-3.94 m3.8-3.9 m cumulative D(mm)phi% finer% 0.0019.625.430.55clay 0.0038.425.980.50 0.0067.426.480.35 0.0096.926.830.50silt 0.0126.427.330.48 0.0215.627.810.00 0.0334.927.815.29 0.0753.733.108.45 0.093.541.5537.02 0.1253.078.5719.01 0.182.597.592.01 0.252.099.600.40 0.3551.5100.000.00sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 176

Appendix D (Continued) 168 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-e 3.94-4.40 m4.13-4.23 m cumulative D(mm)phi% finer% 0.0019.616.950.15clay 0.0038.317.100.11 0.0067.317.210.00 0.0096.817.210.39silt 0.0136.317.600.15 0.0225.517.750.45 0.0354.818.204.81 0.0753.723.027.44 0.093.530.4535.28 0.1253.065.7327.04 0.182.592.766.03 0.252.098.790.90 0.3551.599.700.10sand 0.51.099.800.10 0.710.599.900.10 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 177

Appendix D (Continued) 169 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-f 4.40-5.06 m4.55-4.65 m cumulative D(mm)phi% finer% 0.0019.617.580.02clay 0.0038.317.600.00 0.0067.317.600.20 0.0096.817.800.30silt 0.0136.318.100.15 0.0225.518.250.20 0.0354.818.454.06 0.0753.722.516.73 0.093.529.2541.41 0.1253.070.6524.22 0.182.594.873.92 0.252.098.791.01 0.3551.599.800.20sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 178

Appendix D (Continued) 170 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-g 5.06-5.73 m5.27-5.37 m cumulative D(mm)phi% finer% 0.0019.53.460.05clay 0.0038.23.510.01 0.0077.23.520.00 0.0106.73.520.10silt 0.0146.23.620.02 0.0245.43.640.05 0.0384.73.690.04 0.0753.73.731.61 0.093.55.3419.74 0.1253.025.0850.15 0.182.575.2314.30 0.252.089.537.15 0.3551.596.682.52sand 0.51.099.190.70 0.710.599.900.10 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 179

Appendix D (Continued) 171 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-h 5.73-6.09 m5.9-6.0 m cumulative D(mm)phi% finer% 0.0019.41.660.08clay 0.0038.21.740.01 0.0077.11.740.10 0.0106.61.840.05silt 0.0146.11.890.00 0.0245.41.890.00 0.0394.71.891.41 0.0753.73.303.20 0.093.56.5019.50 0.1253.026.0040.80 0.182.566.8025.80 0.252.092.606.20 0.3551.598.801.00sand 0.51.099.800.20 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 180

Appendix D (Continued) 172 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-i 6.09-6.38 m6.15-6.25 m cumulative D(mm)phi% finer% 0.0019.59.470.05clay 0.0038.29.520.15 0.0077.29.670.05 0.0106.79.720.15silt 0.0136.29.870.10 0.0235.49.970.10 0.0374.810.070.06 0.0753.710.130.90 0.093.511.0326.48 0.1253.037.5155.07 0.182.592.585.72 0.252.098.291.20 0.3551.599.500.40sand 0.51.099.900.10 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 181

Appendix D (Continued) 173 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-j 6.38-6.53 m6.38-6.48 m cumulative D(mm)phi% finer% 0.0019.617.720.48clay 0.0038.318.190.41 0.0067.318.600.20 0.0096.818.810.15silt 0.0136.318.960.51 0.0225.519.460.10 0.0354.819.560.11 0.0753.719.681.22 0.093.520.8921.91 0.1253.042.8048.38 0.182.591.186.39 0.252.097.571.62 0.3551.599.190.61sand 0.51.099.800.20 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 182

Appendix D (Continued) 174 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-k 6.53-6.75 m6.54-6.64 m cumulative D(mm)phi% finer% 0.0019.511.610.42clay 0.0038.312.030.31 0.0077.212.340.10 0.0096.712.440.00silt 0.0136.212.440.12 0.0235.412.560.02 0.0364.812.590.06 0.0753.712.651.00 0.093.513.6521.79 0.1253.035.4452.51 0.182.587.958.23 0.252.096.182.71 0.3551.598.900.90sand 0.51.099.800.20 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 183

Appendix D (Continued) 175 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC2-l 6.75-7.10 m6.85-6.95 m cumulative D(mm)phi% finer% 0.0019.54.720.02clay 0.0038.24.740.05 0.0077.24.790.10 0.0106.74.890.10silt 0.0146.24.990.00 0.0245.44.990.00 0.0384.74.990.14 0.0753.75.142.82 0.093.57.9624.97 0.1253.032.9347.94 0.182.580.8712.89 0.252.093.764.23 0.3551.597.991.41sand 0.51.099.400.50 0.710.599.900.10 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % finer by weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 184

Appendix D (Continued) 176 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-a 0.25-1.75 m1.2-1.3 m cumulative D(mm)phi% finer% 0.0019.53.110.22clay 0.0038.23.330.92 0.0077.24.250.11 0.0106.74.360.22silt 0.0146.24.590.34 0.0245.44.920.45 0.0384.75.370.58 0.0753.75.963.15 0.093.59.1034.16 0.1253.043.2648.88 0.182.592.136.52 0.252.098.651.12 0.3551.599.780.22sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 185

Appendix D (Continued) 177 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-b 2.0-2.24 m2.05-2.15 m cumulative D(mm)phi% finer% 0.0019.41.410.23clay 0.0038.21.630.23 0.0077.11.860.03 0.0106.61.900.17silt 0.0146.12.070.06 0.0245.42.130.23 0.0394.72.365.54 0.0753.77.906.09 0.093.514.0036.68 0.1253.050.6841.20 0.182.591.876.55 0.252.098.421.35 0.3551.599.770.23sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 186

Appendix D (Continued) 178 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-c 2.24-3.35 m2.5-2.6 m cumulative D(mm)phi% finer% 0.0019.619.490.22clay 0.0038.319.710.47 0.0067.320.190.11 0.0096.820.300.40silt 0.0136.320.700.35 0.0225.521.060.00 0.0354.821.066.57 0.0753.727.635.48 0.093.533.1129.57 0.1253.062.6730.48 0.182.593.155.14 0.252.098.291.48 0.3551.599.770.23sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 187

Appendix D (Continued) 179 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-d 3.35-3.93 m3.4-3.5 m cumulative D(mm)phi% finer% 0.0019.58.760.70clay 0.0038.29.461.19 0.0077.210.650.89 0.0106.711.540.72silt 0.0136.212.261.00 0.0235.413.260.80 0.0364.814.063.79 0.0753.717.857.09 0.093.524.9433.07 0.1253.058.0133.98 0.182.591.996.06 0.252.098.051.60 0.3551.599.660.34sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

PAGE 188

Appendix D (Continued) 180 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-e 3.93-4.11 m4.0-4.1 m cumulative D(mm)phi% finer% 0.0019.617.550.48clay 0.0038.318.030.15 0.0067.318.180.01 0.0096.818.190.46silt 0.0136.318.650.20 0.0225.518.850.12 0.0354.818.973.36 0.0753.722.327.25 0.093.529.5735.44 0.1253.065.0228.42 0.182.593.445.18 0.252.098.621.15 0.3551.599.770.23sand 0.51.0100.000.00 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 82.45 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

PAGE 189

Appendix D (Continued) 181 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-f 4.11-5.01 m4.7-4.8 m cumulative D(mm)phi% finer% 0.0019.59.380.77clay 0.0038.210.150.46 0.0077.210.610.57 0.0106.711.180.21silt 0.0136.211.390.70 0.0235.412.090.23 0.0374.812.326.26 0.0753.718.586.50 0.093.525.0937.98 0.1253.063.0726.02 0.182.589.087.55 0.252.096.632.44 0.3551.599.070.70sand 0.51.099.770.23 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 90.62 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative %Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

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Appendix D (Continued) 182 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-g 5.01-5.70 m5.5-5.6 m cumulative D(mm)phi% finer% 0.0019.40.860.17clay 0.0038.21.040.06 0.0077.11.100.01 0.0106.61.110.01silt 0.0146.11.120.00 0.0245.41.120.00 0.0394.71.122.64 0.0753.73.754.34 0.093.58.0924.15 0.1253.032.2445.25 0.182.577.4914.19 0.252.091.685.98 0.3551.597.661.88sand 0.51.099.530.47 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by weight

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Appendix D (Continued) 183 North Lakes WetlandGrain-Size Distribution lithos. layersample Sample: VC3-h 5.70-6.18 m6.0-6.1 m cumulative D(mm)phi% finer% 0.0019.53.140.01clay 0.0038.23.150.14 0.0077.23.290.00 0.0106.73.300.03silt 0.0146.23.330.03 0.0245.43.360.00 0.0384.73.360.92 0.0753.74.281.07 0.093.55.3528.30 0.1253.033.6557.55 0.182.591.206.66 0.252.097.861.55 0.3551.599.410.48sand 0.51.099.880.12 0.710.5100.000.00 10.0100.000.00 1.4-0.5100.000.00 2-1.0100.000.00 0 10 20 30 40 50 60 70 80 90 100 -1012345678910 Grainsize (phi)Cumulative % Finer by Weight 0 10 20 30 40 50 60 -1012345678910 Grainsize (phi)Percent by Weight

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Appendix E. Results of Laboratory Grain-size Distribution Analyses 184 [bls, below land surface; elev., elevation; m, meters; mm, millimeters] lithoeffectiveuniformitymedianestimated sample thickness stratigraphic grain sizecoefficientgrain sizeporosity IDfromtofromtoaveragefromtofromtob layer d10d60d60/d10d50n bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(mm)(mm)(mm) Mw1-a0.100.2015.7615.6615.710.000.3015.8615.560.30 S1 0.08710.12041.38230.11340.45 Mw1-b0.800.9015.0614.9615.010.301.2215.5614.640.92 S1 0.08990.12871.43160.11830.45 Mw1-c1.501.6014.3614.2614.311.221.8314.6414.030.61 S1 0.09060.13091.44480.12070.45 Mw1-d2.102.2013.7613.6613.711.832.4314.0313.430.60 S1 0.08150.12871.57910.11740.44 Mw1-e2.502.6013.3613.2613.312.432.7413.4313.120.31 S1 0.07670.12891.68060.11740.44bMw1-f2.802.9013.0612.9613.012.743.0513.1212.810.31 S2 0.00130.112987.51940.10510.26bMw1-g3.403.5012.4612.3612.413.053.6612.8112.200.61 S2 0.00130.115489.45740.10810.25bMw1-h3.904.0011.9611.8611.913.664.2712.2011.590.61 S2 0.00130.110585.65890.10150.26bMw1-i4.704.8011.1611.0611.114.275.3311.5910.531.06 S2 0.00130.115289.30230.10730.26bMw1-j5.355.4510.5110.4110.465.335.4910.5310.370.16 S2 0.00130.106382.40310.09810.26 Mw1-aa5.805.9010.069.9610.015.496.1010.379.760.61 S3 0.06820.16292.38860.15180.42 Mw1-bb6.406.509.469.369.416.106.719.769.150.61 S3 0.06010.15362.55570.14360.41 Mw1-cc7.007.108.868.768.816.717.319.158.550.60 S3 0.06620.16292.46070.15390.42 Mw1-dd7.407.508.468.368.417.317.628.558.240.31 S3 0.12140.25012.06010.22530.43 Mw1-ee8.008.107.867.767.817.628.538.247.330.91 S3 0.06080.21953.61020.20170.39 Mw1-ff8.708.807.167.067.118.539.147.336.720.61 S3 0.05470.20563.75870.17680.38bMw1-gg9.409.506.466.366.419.149.756.726.110.61 S4 0.01170.135311.56410.12940.28 Mw1-hh9.859.956.015.915.969.7510.066.115.800.31 S4 0.01180.06085.15250.04940.35 FMW2-a0.100.2015.7515.6515.700.000.3015.8515.550.3 S1 0.09170.14021.52890.12940.45 FMW2-b0.700.8015.1515.0515.100.301.2215.5514.630.92 S1 0.09110.13881.52360.12590.45 FMW2-c1.501.6014.3514.2514.301.221.8314.6314.020.61 S1 0.09170.13881.51360.12590.45 FMW2-d2.102.2013.7513.6513.701.832.4314.0213.420.6 S1 0.09220.13331.44580.12330.45bFMW2-e2.702.8013.1513.0513.102.433.0513.4212.80.62 S2 0.00130.122494.88370.11270.25bFMW2-f3.203.3012.6512.5512.603.053.6612.812.190.61 S2 0.00130.122494.88370.11270.25bFMW2-g3.904.0011.9511.8511.903.664.2712.1911.580.61 S2 0.00130.116790.46510.10810.25bFMW2-h4.704.8011.1511.0511.104.275.2711.5810.581 S2 0.00130.119892.86820.10880.25bFMW2-aa5.405.5010.4510.3510.405.275.7910.5810.060.52 S2 0.00130.104881.24030.09870.26 FMW2-bb6.206.309.659.559.605.796.7110.069.140.92 S3 0.06050.15042.48600.13400.42 FMW2-cc6.907.008.958.858.906.717.319.148.540.6 S3 0.04830.21634.47830.17800.37 FMW2-dd7.507.608.358.258.307.317.928.547.930.61 S3 0.05310.13642.56870.12410.41 FMW2-ee8.408.507.457.357.407.928.537.937.320.61 S4 0.00400.137034.25000.12500.26 FMW2-x8.608.707.257.157.208.538.847.327.010.31 S4 0.00130.1367105.96900.12330.25bFMW2-ff8.909.006.956.856.908.849.147.016.710.3 S4 0.00130.1367105.96900.08190.26 FMW2-xx9.309.406.556.456.509.149.916.715.940.77 S4 0.0670bFMW2-gg 9.919.985.945.875.919.919.985.945.870.07 S4 0.00130.110285.42640.09150.26 Fmw4-org0.100.2015.3315.2315.280.000.3015.4315.130.3 S1 Fmw4-a0.400.5015.0314.9314.980.300.6115.1314.820.31 S1 0.09050.13681.51160.12500.45 Fmw4-b1.201.3014.2314.1314.180.611.5214.8213.910.91 S1 0.09060.13181.45470.12070.45 Fmw4-c1.601.7013.8313.7313.781.521.8213.9113.610.3 S1 0.07980.11891.49000.11030.45 Fmw4-d1.902.0013.5313.4313.481.822.1313.6113.30.31 S1 0.06360.11961.88050.11030.43 lithostratigraphic bed sample depth

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Appendix E (Continued) 185 [bls, below land surface; elev., elevation; m, meters; mm, millimeters] lithoeffectiveuniformitymedianestimated sample thickness stratigraphic grain sizecoefficientgrain sizeporosity IDfromtofromtoaveragefromtofromtob layer d10d60d60/d10d50n bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(mm)(mm)(mm) Fmw4-e2.152.2513.2813.1813.232.132.2913.313.140.16 S1 0.06220.11571.86010.10880.44bFmw4-f2.402.9013.0312.5312.782.293.6613.1411.771.37 S2 0.00140.2083150.94200.17680.25bFmw4-g3.703.8011.7311.6311.683.663.9611.7711.470.3 S2 0.00130.2052159.06980.17680.25bFmw4-h5.105.2010.3310.2310.283.965.4911.479.941.53 S2 0.00150.118478.93330.10880.26 Fmw4-i5.605.709.839.739.785.495.799.949.640.3 S3 0.09310.15611.67670.13970.44 Fmw4-j6.206.309.239.139.185.796.719.648.720.92 S3 0.09280.17341.86850.15390.44 Fmw4-k6.957.058.488.388.436.717.328.728.110.61 S3 0.09350.14601.56150.13580.45 Fmw4-l7.407.508.037.937.987.327.628.117.810.3 S3 0.08930.14461.61930.13300.44 Fmw5-org0.100.2015.3815.2815.330.000.3015.4815.180.30 S1 Fmw5-a0.500.6014.9814.8814.930.300.9115.1814.570.61 S1 0.09190.13891.51140.12590.45 Fmw5-b1.001.1014.4814.3814.430.911.2214.5714.260.31 S1 0.09190.13911.51360.12670.45 Fmw5-c1.301.4014.1814.0814.131.221.5214.2613.960.30 S1 0.07010.12961.84880.11830.44 Fmw5-d1.601.7013.8813.7813.831.521.8313.9613.650.31 S1 0.09120.14711.61290.13400.44 Fmw5-e1.801.9013.6813.5813.631.832.1313.6513.350.30 S1 0.06020.13892.30730.12500.42 Fmw5-f2.502.6012.9812.8812.932.132.7413.3512.740.61 S1 0.07800.13141.68460.12070.44 Fmw5-g3.203.3012.2812.1812.232.743.9612.7411.521.22 S2 0.06680.12051.80390.11270.44bFmw5-h5.005.1010.4810.3810.433.965.1811.5210.301.22 S2 0.00130.1380106.97670.12760.25 Fmw5-x6.206.309.289.189.235.186.4010.309.081.22 S3 Fmw5-i7.207.308.288.188.236.407.929.087.561.52 S3 0.09240.15661.69480.13970.44 Fmw5-j8.208.307.287.187.237.928.537.566.950.61 S3 0.09230.15391.66740.13490.44 Fmw5-k9.009.106.486.386.438.539.456.956.030.92 S3 0.09230.15391.66740.13870.44 Fmw5-l9.509.605.985.885.939.459.756.035.730.30 S3 0.09420.15561.65180.14260.44 Fmw5-xx9.9010.005.585.485.539.7510.675.734.810.92 S4 Mw5-org0.100.2015.7415.6415.690.000.3015.8415.540.30 S1 MW5-a0.400.5015.4415.3415.390.300.6115.5515.240.31 S1 0.09220.13381.45120.12330.45 Mw5-b1.101.2014.7414.6414.690.611.5215.2314.320.91 S1 0.09110.13341.46430.12330.45 Mw5-c1.902.0013.9413.8413.891.522.4414.3213.400.92 S1 0.09170.13521.47440.12500.45 Mw5-d2.452.5513.3913.2913.342.442.5913.4013.250.15 S1 0.08970.13071.45710.12070.45 Mw5-e2.602.7013.2413.1413.192.592.7413.2513.100.15 S1 0.08910.12171.36590.11580.45bMw5-f2.802.9013.0412.9412.992.743.0513.1012.790.31 S2 0.00130.117791.24030.10880.25 Mw5-g3.103.2012.7412.6412.693.053.2012.7912.640.15 S2 0.07330.11441.56070.10880.45bMw5-h3.204.2012.6411.6412.143.204.8812.6410.961.68 S2 0.00130.111086.04650.10430.26bMw5-i5.205.3010.6410.5410.594.885.7210.9610.120.84 S2 0.00130.113888.21710.10510.26bMw5-x5.705.8010.1410.0410.095.725.7910.1210.050.07 S2 Mw5-j6.006.109.849.749.795.796.4010.059.440.61 S3 0.09060.15051.66110.13400.44 Mw5-xx6.506.609.349.249.296.406.719.449.130.31 S3 Mw5-k6.806.909.048.948.996.717.019.138.830.30 S3 0.09120.16301.78730.14870.44 Mw5-xxx7.107.208.748.648.697.017.328.838.520.31 S3 Mw5-l7.407.508.448.348.397.327.628.528.220.30 S3 0.09090.15491.70410.14360.44aVC1-a0.120.2415.5515.4315.490.000.4015.6715.270.40 S1 0.08170.13731.68050.12500.44 lithostratigraphic bed sample depth

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Appendix E (Continued) 186 [bls, below land surface; elev., elevation; m, meters; mm, millimeters] lithoeffectiveuniformitymedianestimated sample thickness stratigraphic grain sizecoefficientgrain sizeporosity IDfromtofromtoaveragefromtofromtob layer d10d60d60/d10d50n bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(mm)(mm)(mm)aVC1-b1.011.1214.6614.5514.610.401.6215.2714.051.22 S1 0.08760.13851.58110.12590.44aVC1-c2.192.3113.4813.3613.421.622.7414.0512.931.12 S1 0.07810.13111.67860.11990.44abVC1-d3.133.2512.5412.4212.482.743.6112.9312.060.86 S2 0.00520.131025.19230.11660.26abVC1-e3.783.9011.8911.7711.833.614.0212.0611.650.41 S2 0.00130.120292.46150.10880.25abVC1-f4.194.3011.4811.3711.424.024.4311.6511.240.41 S2 0.00130.112986.84620.10510.26aVC1-g5.085.2010.5910.4710.534.435.8111.249.861.37 S2 0.09410.15391.63550.14360.44aVC1-h6.156.279.529.409.465.816.569.869.110.76 S3 0.12640.21721.71840.20310.44aVC1-i 6.676.799.008.888.946.566.819.118.860.25 S3 0.09250.14371.55350.13400.45aVC2-org0.060.1715.6115.5015.560.000.2215.6715.450.22 S1aVC2-a1.131.2514.5414.4214.480.221.7815.4513.891.56 S1 0.09080.14291.57380.13400.45aVC2-b2.612.7213.0612.9513.011.783.3313.8912.341.55 S1 0.08740.13861.58580.12570.44abVC2-c3.853.9711.8211.7011.763.334.2712.3411.400.94 S2 0.00130.1301100.07690.11660.25abVC2-d4.314.4211.3611.2511.314.274.4611.4011.210.19 S2 0.00130.106081.53850.09810.26abVC2-e4.684.7910.9910.8810.934.464.9911.2110.680.52 S2 0.00130.118591.15380.10880.25abVC2-f5.165.2710.5110.4010.464.995.7310.689.940.75 S2 0.00130.114988.38460.10510.26aVC2-g5.976.089.709.599.645.736.499.949.180.76 S3 0.09730.16111.65570.14870.44aVC2-h6.686.808.998.878.936.496.909.188.770.41 S3 0.09550.16941.77380.15390.44aVC2-i6.977.088.708.598.656.907.238.778.440.33 S4 0.02720.14515.33460.13400.35abVC2-j7.237.348.448.338.387.237.408.448.270.17 S4 0.00130.1423109.46150.13300.25abVC2-k7.417.528.268.158.207.407.658.278.020.25 S4 0.00130.1482114.00000.13770.25abVC2-l 7.767.877.917.807.857.658.048.027.630.40 S4 0.09250.15361.66050.14360.44aVC3-org0.120.2315.7915.6815.740.000.2915.9115.620.29 S1aVC3-a1.391.5014.5214.4114.470.292.0215.6213.891.73 S1 0.09080.14161.55950.13400.45aVC3-x2.082.2013.8313.7113.772.022.3113.8913.600.29 S1aVC3-b2.372.4813.5413.4313.482.312.5913.6013.320.28 S1 0.07990.13581.69960.12500.44abVC3-c2.893.0013.0212.9112.962.593.8713.3212.041.28 S2 0.00130.121393.30770.10880.25abVC3-d3.934.0411.9811.8711.923.874.5412.0411.370.67 S2 0.00460.127727.76090.11660.26abVC3-e4.624.7411.2911.1711.234.544.7511.3711.160.21 S2 0.00130.119391.76920.10880.25abVC3-f5.435.5510.4810.3610.424.755.7911.1610.121.04 S2 0.00280.121743.46430.11190.26aVC3-g6.356.479.569.449.505.796.5910.129.320.80 S3 0.09240.15631.69160.14360.44aVC3-h 6.937.058.988.868.926.597.149.328.770.55 S3 0.09500.14771.55470.13770.45 1) a = Compaction correction factor applied to vibracore sample/bed depths due to based on difference between penetration and core length 2) b = Sample contains high clay fraction (> 10%), d10 estimated based on the size of the smallest clay-sized particles detectable by the hydrometer after 24 hours of settling since the start time (phi=9.6) 3) Porosity estimated from grainsize distribution using analytical relationship (Istomina, 1957 as cited in Vukovic et. al., 1 992). This method has been shown in Vukovic et.al. to decline in accuracy for materials comprising clayey f lithostratigraphic bed sample depth

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Appendix F. Permeameter Testing Data 187 [bls, below land surface; m, meters; sec, seconds; ml, milliliters; cm, centimeters; m/day, meters per day] sample constant-head testfalling-head test ID thickness startfinish tVh0h K fromtofromtoaveragefromtofromto b tV1V2V3VSSh2-h1K bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m) (sec)(ml)(ml)(ml)(ml)(cm)(m/day)(sec)(ml)(cm)(cm)(m/day) Mw1-a0.100.2015.7615.6615.710.000.3015.8615.560.30301313131393.62.6 Mw1-b0.800.9015.0614.9615.010.301.2215.5614.640.92306.36.26.26.293.61.24 Mw1-c1.501.6014.3614.2614.311.221.8314.6414.030.613010.810.710.710.793.62.14 Mw1-d2.102.2013.7613.6613.711.832.4314.0313.430.60306.26.26.26.293.61.24 Mw1-e2.502.6013.3613.2613.312.432.7413.4313.120.31302.42.42.42.493.60.48bMw1-f2.802.9013.0612.9613.012.743.0513.1212.810.314:15:0011:00:006754.857470.150.001bMw1-g3.403.5012.4612.3612.413.053.6612.8112.200.6111:24:4511:31:203950.507473.500.010bMw1-h3.904.0011.9611.8611.913.664.2712.2011.590.612:39:203:00:1512551.507472.500.010bMw1-i4.704.8011.1611.0611.114.275.3311.5910.531.0611:39:0011:53:208606.007468.000.060bMw1-j5.355.4510.5110.4110.465.335.4910.5310.370.1610:03:1011:01:1034800.207473.800.001 Mw1-aa5.805.9010.069.9610.015.496.1010.379.760.613011.711.711.711.793.62.34 Mw1-bb6.406.509.469.369.416.106.719.769.150.613021.521.421.421.493.64.27 Mw1-cc7.007.108.868.768.816.717.319.158.550.603025.025.025.025.093.64.99 Mw1-dd7.407.508.468.368.417.317.628.558.240.313084.084.083.083.093.616.58 Mw1-ee8.008.107.867.767.817.628.538.247.330.913021.521.321.321.393.64.25 Mw1-ff8.708.807.167.067.118.539.147.336.720.61304.04.04.04.093.60.80bMw1-gg9.409.506.466.366.419.149.756.726.110.611:03:301:09:453752.0074.0072.000.0500 Mw1-hh9.859.956.015.915.969.7510.066.115.800.31 FMW2-a0.100.2015.7515.6515.700.000.3015.8515.550.3303131313193.66.19 FMW2-b0.700.8015.1515.0515.100.301.2215.5514.630.923017.417.317.317.393.63.48 FMW2-c1.501.6014.3514.2514.301.221.8314.6314.020.613014.914.914.814.893.62.96 FMW2-d2.102.2013.7513.6513.701.832.4314.0213.420.63013.513.413.413.493.62.68bFMW2-e2.702.8013.1513.0513.102.433.0513.4212.80.621:17:341:20:061521.0074730.06bFMW2-f3.203.3012.6512.5512.603.053.6612.812.190.612:22:282:25:261781.0068670.05bFMW2-g3.904.0011.9511.8511.903.664.2712.1911.580.614:02:224:10:224800.5066.5660.01bFMW2-h4.704.8011.1511.0511.104.275.2711.5810.5814:10:264:14:262401.0074730.04bFMW2-aa5.405.5010.4510.3510.405.275.7910.5810.060.5212:03:2012:24:2012600.107473.90.0007 FMW2-bb6.206.309.659.559.605.796.7110.069.140.923015.615.415.415.493.63.08 FMW2-cc6.907.008.958.858.906.717.319.148.540.6307.67.47.47.493.61.48 FMW2-dd7.507.608.358.258.307.317.928.547.930.61302.22.02.02.093.60.40 FMW2-ee8.408.507.457.357.407.928.537.937.320.61301.41.21.21.293.60.24 FMW2-x8.608.707.257.157.208.538.847.327.010.31bFMW2-ff8.909.006.956.856.908.849.147.016.710.310:14:3010:39:3015001.0074730.006 FMW2-xx9.309.406.556.456.509.149.916.715.940.77bFMW2-gg9.919.985.945.875.919.919.985.945.870.07 Mw5-org0.100.2015.7415.6415.690.000.3015.8415.540.303025.525.2252593.64.99 MW5-a0.400.5015.4415.3415.390.300.6115.5515.240.313033.032.2323293.66.39 Mw5-b1.101.2014.7414.6414.690.611.5215.2314.320.913019.819.619.519.593.63.89 Mw5-c1.902.0013.9413.8413.891.522.4414.3213.400.92305.35.25.25.293.61.04 Mw5-d2.452.5513.3913.2913.342.442.5913.4013.250.153017.917.517.317.393.63.46 Mw5-e2.602.7013.2413.1413.192.592.7413.2513.100.15bMw5-f2.802.9013.0412.9412.992.743.0513.1012.790.31 Mw5-g3.103.2012.7412.6412.693.053.2012.7912.640.152:01:202:27:401580274730.0080bMw5-h3.204.2012.6411.6412.143.204.8812.6410.961.6810:51:2011:16:301510174730.0060bMw5-i5.205.3010.6410.5410.594.885.7210.9610.120.8411:48:2012:11:101370274720.0100bMw5-x5.705.8010.1410.0410.095.725.7910.1210.050.073:00:0011:00:0072000174730.0001 sample depthlithostratigraphic layer

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Appendix F (Continued) 188 [bls, below land surface; m, meters; sec, seconds; ml, milliliters; cm, centimeters; m/day, meters per day] sample constant-head testfalling-head test ID thickness startfinish tVh0h K fromtofromtoaveragefromtofromto b tV1V2V3VSSh2-h1K bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m) (sec)(ml)(ml)(ml)(ml)(cm)(m/day)(sec)(ml)(cm)(cm)(m/day) Mw5-j6.006.109.849.749.795.796.4010.059.440.61308.58.58.58.593.61.7 Mw5-xx6.506.609.349.249.296.406.719.449.130.31303.33.33.33.393.60.66 Mw5-k6.806.909.048.948.996.717.019.138.830.303011.511.511.511.593.62.3 Mw5-xxx7.107.208.748.648.697.017.328.838.520.31302.322293.60.4 Mw5-l7.407.508.448.348.397.327.628.528.220.30306.76.46.46.493.61.28 Fmw4-org0.100.2015.3315.2315.280.000.3015.4315.130.33013.813.713.713.793.62.74 Fmw4-a0.400.5015.0314.9314.980.300.6115.1314.820.313022.018.718.218.293.63.64 Fmw4-b1.201.3014.2314.1314.180.611.5214.8213.910.913027.023.0232393.64.59 Fmw4-c1.601.7013.8313.7313.781.521.8213.9113.610.3305.55.05593.61 Fmw4-d1.902.0013.5313.4313.481.822.1313.6113.30.31306.86.86.86.893.61.36 Fmw4-e2.152.2513.2813.1813.232.132.2913.313.140.16bFmw4-f2.402.9013.0312.5312.782.293.6613.1411.771.3710:03:0010:26:001380174730.006bFmw4-g3.703.8011.7311.6311.683.663.9611.7711.470.310:32:0011:29:003420174730.003bFmw4-h5.105.2010.3310.2310.283.965.4911.479.941.5312:35:5512:40:10255171700.040 Fmw4-i5.605.709.839.739.785.495.799.949.640.3305.95.85.85.893.61.16 Fmw4-j6.206.309.239.139.185.796.719.648.720.923011.411.411.211.293.62.24 Fmw4-k6.957.058.488.388.436.717.328.728.110.613017.317.217.217.293.63.44 Fmw4-l7.407.508.037.937.987.327.628.117.810.3306.46.26.26.293.61.24 Fmw5-org0.100.2015.3815.2815.330.000.3015.4815.180.30301.41.31.31.393.60.26 Fmw5-a0.500.6014.9814.8814.930.300.9115.1814.570.613016.416.416.416.493.63.28 Fmw5-b1.001.1014.4814.3814.430.911.2214.5714.260.31306.86.86.76.793.61.34 Fmw5-c1.301.4014.1814.0814.131.221.5214.2613.960.30306.86.86.76.793.61.34 Fmw5-d1.601.7013.8813.7813.831.521.8313.9613.650.31307.27.07793.61.4 Fmw5-e1.801.9013.6813.5813.631.832.1313.6513.350.30306.86.86.76.793.61.34 Fmw5-f2.502.6012.9812.8812.932.132.7413.3512.740.61306.86.86.76.793.61.34 Fmw5-g3.203.3012.2812.1812.232.743.9612.7411.521.22301.81.51.61.693.60.32bFmw5-h5.005.1010.4810.3810.433.965.1811.5210.301.222:54:003:00:45405174730.01 Fmw5-x6.206.309.289.189.235.186.4010.309.081.22301.61.51.51.593.60.3 Fmw5-i7.207.308.288.188.236.407.929.087.561.52301312.912.812.893.62.56 Fmw5-j8.208.307.287.187.237.928.537.566.950.61307.07.07793.61.4 Fmw5-k9.009.106.486.386.438.539.456.956.030.923010.610.2101093.62 Fmw5-l9.509.605.985.885.939.459.756.035.730.303:32:003:35:20200474700.18 Fmw5-xx9.9010.005.585.485.539.7510.675.734.810.92308.28.28.28.293.61.64aVC1-a0.100.2015.5715.4715.520.000.3415.6715.330.34301.81.61.21.293.60.2412:09:0012:25:369961074640.0920aVC1-b0.850.9514.8214.7214.770.341.3715.3314.301.033010.610.610.610.693.62.12aVC1-c1.851.9513.8213.7213.771.372.3214.3013.350.953010.410.0101093.62abVC1-d2.652.7513.0212.9212.972.323.0513.3512.620.7312:02:001:02:023602574690.012abVC1-e3.203.3012.4712.3712.423.053.4012.6212.270.352:46:1710:00:006948016.37457.70.002abVC1-f3.543.6412.1312.0312.083.403.7512.2711.920.3511:00:4011:42:1225321074640.036aVC1-g4.304.4011.3711.2711.323.754.9111.9210.761.16302.221.81.893.60.36aVC1-h5.205.3010.4710.3710.424.915.5510.7610.120.643055.051.0424293.68.39aVC1-i5.645.7410.039.939.985.555.7610.129.910.21301.61.41.41.493.60.28aVC2-org0.050.1515.6215.5215.570.000.1915.6715.480.193024.823.8232393.64.59aVC2-a1.001.1014.6714.5714.620.191.5715.4814.101.38306.36.26.26.293.61.24aVC2-b2.302.4013.3713.2713.321.572.9414.1012.731.373021.220.419.419.493.63.87abVC2-c3.403.5012.2712.1712.222.943.7712.7311.900.833:43:004:14:0018600.77473.30.003 sample depthlithostratigraphic layer

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Appendix F (Continued) 189 [bls, below land surface; m, meters; sec, seconds; ml, milliliters; cm, centimeters; m/day, meters per day] sample constant-head testfalling-head test ID thickness startfinish tVh0h K fromtofromtoaveragefromtofromto b tV1V2V3VSSh2-h1K bls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m) (sec)(ml)(ml)(ml)(ml)(cm)(m/day)(sec)(ml)(cm)(cm)(m/day)abVC2-d3.803.9011.8711.7711.823.773.9411.9011.730.174:54:001:15:00235260574690.0002abVC2-e4.134.2311.5411.4411.493.944.4011.7311.270.462:16:002:37:0012600.27473.80.001abVC2-f4.554.6511.1211.0211.074.405.0611.2710.610.6612:36:0011:16:452445274720.007aVC2-g5.275.3710.4010.3010.355.065.7310.619.940.67303.33.13.13.193.60.62aVC2-h5.906.009.779.679.725.736.099.949.580.363023.423.223.223.293.64.63aVC2-i6.156.259.529.429.476.096.389.589.290.29300.90.80.7N93.60.142:46:402:57:55675874660.11abVC2-j6.386.489.299.199.246.386.539.299.140.151:09:0010:15:00759604174330.007abVC2-k6.546.649.139.039.086.536.759.148.920.2211:28:3512:12:351803666600.0230abVC2-l6.856.958.828.728.776.757.108.928.570.352:54:363:21:351679474660.0430aVC3-org0.100.2015.8115.7115.760.000.2515.9115.660.253036.536.0353593.66.99aVC3-a1.201.3014.7114.6114.660.251.7515.6614.161.503010.210.210.210.293.62.04aVC3-x1.801.9014.1114.0114.061.752.0014.1613.910.25303.22.82.42.493.61.24aVC3-b2.052.1513.8613.7613.812.002.2413.9113.670.24301.81.61.51.593.61.46abVC3-c2.502.6013.4113.3113.362.243.3513.6712.561.1110:50:0011:51:003660274720.005abVC3-d3.403.5012.5112.4112.463.353.9312.5611.980.5812:26:0012:36:25625574690.071abVC3-e4.004.1011.9111.8111.863.934.1111.9811.800.183:18:0012:49:00774601174630.001abVC3-f4.704.8011.2111.1111.164.115.0111.8010.900.901:58:002:05:074271474600.3120aVC3-g5.505.6010.4110.3110.365.015.7010.9010.210.69303131313193.66.19aVC3-h6.006.109.919.819.865.706.1810.219.730.483014.213.813.613.693.62.72 1) a = Compaction correction factor applied to vibracore sample/bed depths due to based on difference between penetration and core length 2) b = Sample contains high clay fraction (> 10%), d10 estimated based on the size of the smallest clay-sized particles detectable by the hydrometer after 24 hours of settling since the start time (phi=9.6) 3) Methodologies for each type of permeameter analyses are described below: Constant-head test For non-cohesive, disurbed granular sediments (<10% soil passing the no. 200 or 75 Microm. Sieve), a funnel with overflow provi des a supply of water maintaining a constant head that moves the water through a sediment chamber at some lower height (smaller head) at a steady rate. By recording the sample volume of water V that drains from the permeameter over some time t, the hydraulic conductivity of the soil can be calculated by a variation of Darcy's law that relates the hydraulic conductivity K to the volume of water discharging in time t (Q), the length of the sample L, the cross-sectional area A, and the hydraulic gradient across the sample dh using the equation: K = -(QL)/(A(h2-h1)) = -(VL)/(At(h2-h1)) where:Q = V/t h2-h1 = change in head across the sample (h1 = h at the funnel aperature, h2 = head at the discharge spout of sample chamber) L = length of sample = 7.4 cm A = cross-sectional area of the sample chamber = 11.4 cm Falling-head test = Hydraulic conductivity measured using a falling-head permeameter apparatus (sample contains 10% or more fraction passing th e #200 sieve or <0.039 mm). A falling-head tube is attached to the permeameter. The initial water level above the outlet in the falling-head tube, h0, is measured. After some time t, the new water level, h, is again noted. The inside diameterof the falling-head tube dt, the length of the sample L, and the diameter of the sample dc must also be measured. Using a variation of the constant-head equation along with the conservation of mass, the falling-head equation can be expressed as: K = (dt 2L/dc 2t)*ln(h0/h) where:dt = diameter of tube = 1.2 cm L = length of sample = 7.4 cm dc = sample diameter = 3.81 cm sample depthlithostratigraphic layer

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Appendix G. Results of Permeameter Testing 190 [bls, below land surface; elev., elevation; m, meters; m/day, meters per day] # ofhydrothicknessstandardstratigraphic fromtofromtoaveragefromtofromto bK log K deviationsunit samplebls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(m/day)from mean Mw1-a0.100.2015.7615.6615.710.000.3015.8615.560.302.6E+000.4150+1 S1 Mw1-b0.800.9015.0614.9615.010.301.2215.5614.640.921.2E+000.0934+1 S1 Mw1-c1.501.6014.3614.2614.311.221.8314.6414.030.612.1E+000.3304+1 S1 Mw1-d2.102.2013.7613.6613.711.832.4314.0313.430.601.2E+000.0934+1 S1 Mw1-e2.502.6013.3613.2613.312.432.7413.4313.120.314.8E-01-0.3188+1 S1bMw1-f2.802.9013.0612.9613.012.743.0513.1212.810.315.0E-04-3.3010-3 S2bMw1-g3.403.5012.4612.3612.413.053.6612.8112.200.611.0E-02-2.0000-2 S2bMw1-h3.904.0011.9611.8611.913.664.2712.2011.590.611.0E-02-2.0000-2 S2bMw1-i4.704.8011.1611.0611.114.275.3311.5910.531.066.0E-02-1.2218-1 S2bMw1-j5.355.4510.5110.4110.465.335.4910.5310.370.165.0E-04-3.3010-3 S2 Mw1-aa5.805.9010.069.9610.015.496.1010.379.760.612.3E+000.3692+1 S3 Mw1-bb6.406.509.469.369.416.106.719.769.150.614.3E+000.6304+1 S3 Mw1-cc7.007.108.868.768.816.717.319.158.550.605.0E+000.6981+2 S3 Mw1-dd7.407.508.468.368.417.317.628.558.240.311.7E+011.2196+2 S3 Mw1-ee8.008.107.867.767.817.628.538.247.330.914.3E+000.6284+1 S3 Mw1-ff8.708.807.167.067.118.539.147.336.720.618.0E-01-0.0969+1 S3bMw1-gg9.409.506.466.366.419.149.756.726.110.615.0E-02-1.3010-1 S4 Mw1-hh9.859.956.015.915.969.7510.066.115.800.31 S4 FMW2-a0.100.2015.7515.6515.700.000.3015.8515.550.36.2E+000.7917+2 S1 FMW2-b0.700.8015.1515.0515.100.301.2215.5514.630.923.5E+000.5416+1 S1 FMW2-c1.501.6014.3514.2514.301.221.8314.6314.020.613.0E+000.4713+1 S1 FMW2-d2.102.2013.7513.6513.701.832.4314.0213.420.62.7E+000.4281+1 S1bFMW2-e2.702.8013.1513.0513.102.433.0513.4212.80.626.0E-02-1.2218-1 S2bFMW2-f3.203.3012.6512.5512.603.053.6612.812.190.615.0E-02-1.3010-1 S2bFMW2-g3.904.0011.9511.8511.903.664.2712.1911.580.611.0E-02-2.0000-2 S2bFMW2-h4.704.8011.1511.0511.104.275.2711.5810.5814.0E-02-1.3979-1 S2bFMW2-aa5.405.5010.4510.3510.405.275.7910.5810.060.527.0E-04-3.1549-2 S2 FMW2-bb6.206.309.659.559.605.796.7110.069.140.923.1E+000.4886+1 S3 FMW2-cc6.907.008.958.858.906.717.319.148.540.61.5E+000.1703+1 S3 FMW2-dd7.507.608.358.258.307.317.928.547.930.614.0E-01-0.3979+1 S3 sample depthlithostratigraphic bed

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Appendix G (Continued) 191 [bls, below land surface; elev., elevation; m, meters; m/day, meters per day] # ofhydrothicknessstandardstratigraphic fromtofromtoaveragefromtofromto bK log K deviationsunit samplebls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(m/day)from mean FMW2-ee8.408.507.457.357.407.928.537.937.320.612.4E-01-0.6198-1 S4 FMW2-x8.608.707.257.157.208.538.847.327.010.31 S4bFMW2-ff8.909.006.956.856.908.849.147.016.710.36.0E-03-2.2218-2 S4 FMW2-xx9.309.406.556.456.509.149.916.715.940.77 S4bFMW2-gg 9.919.985.945.875.919.919.985.945.870.07 S4 Fmw4-org0.100.2015.3315.2315.280.000.3015.4315.130.32.7E+000.4378+1 S1 Fmw4-a0.400.5015.0314.9314.980.300.6115.1314.820.313.6E+000.5611+1 S1 Fmw4-b1.201.3014.2314.1314.180.611.5214.8213.910.914.6E+000.6618+1 S1 Fmw4-c1.601.7013.8313.7313.781.521.8213.9113.610.31.0E+000.0000+1 S1 Fmw4-d1.902.0013.5313.4313.481.822.1313.6113.30.311.4E+000.1335+1 S1 Fmw4-e2.152.2513.2813.1813.232.132.2913.313.140.16 S1bFmw4-f2.402.9013.0312.5312.782.293.6613.1411.771.376.0E-03-2.2218-2 S2bFmw4-g3.703.8011.7311.6311.683.663.9611.7711.470.33.0E-03-2.5229-2 S2bFmw4-h5.105.2010.3310.2310.283.965.4911.479.941.534.0E-02-1.3979-1 S2 Fmw4-i5.605.709.839.739.785.495.799.949.640.31.2E+000.0645+1 S3 Fmw4-j6.206.309.239.139.185.796.719.648.720.922.2E+000.3502+1 S3 Fmw4-k6.957.058.488.388.436.717.328.728.110.613.4E+000.5366+1 S3 Fmw4-l7.407.508.037.937.987.327.628.117.810.31.2E+000.0934+1 S3 Fmw5-org0.100.2015.3815.2815.330.000.3015.4815.180.302.6E-01-0.5850-1 S1 Fmw5-a0.500.6014.9814.8814.930.300.9115.1814.570.613.3E+000.5159+1 S1 Fmw5-b1.001.1014.4814.3814.430.911.2214.5714.260.311.3E+000.1271+1 S1 Fmw5-c1.301.4014.1814.0814.131.221.5214.2613.960.301.3E+000.1271+1 S1 Fmw5-d1.601.7013.8813.7813.831.521.8313.9613.650.311.4E+000.1461+1 S1 Fmw5-e1.801.9013.6813.5813.631.832.1313.6513.350.301.3E+000.1271+1 S1 Fmw5-f2.502.6012.9812.8812.932.132.7413.3512.740.611.3E+000.1271+1 S1 Fmw5-g3.203.3012.2812.1812.232.743.9612.7411.521.223.2E-01-0.4949+1 S2bFmw5-h5.005.1010.4810.3810.433.965.1811.5210.301.221.0E-02-2.0000-2 S2 Fmw5-x6.206.309.289.189.235.186.4010.309.081.223.0E-01-0.5229+1 S3 Fmw5-i7.207.308.288.188.236.407.929.087.561.522.6E+000.4082+1 S3 Fmw5-j8.208.307.287.187.237.928.537.566.950.611.4E+000.1461+1 S3 sample depthlithostratigraphic bed

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Appendix G (Continued) 192 [bls, below land surface; elev., elevation; m, meters; m/day, meters per day] # ofhydrothicknessstandardstratigraphic fromtofromtoaveragefromtofromto bK log K deviationsunit samplebls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(m/day)from mean Fmw5-k9.009.106.486.386.438.539.456.956.030.922.0E+000.3010+1 S3 Fmw5-l9.509.605.985.885.939.459.756.035.730.301.6E+000.2148+1 S3 Fmw5-xx9.9010.005.585.485.539.7510.675.734.810.921.8E-01-0.7447-1 S4 Mw5-org0.100.2015.7415.6415.690.000.3015.8415.540.306.4E+000.8055+2 S1 MW5-a0.400.5015.4415.3415.390.300.6115.5515.240.31 S1 Mw5-b1.101.2014.7414.6414.690.611.5215.2314.320.913.9E+000.5899+1 S1 Mw5-c1.902.0013.9413.8413.891.522.4414.3213.400.921.0E+000.0170+1 S1 Mw5-d2.452.5513.3913.2913.342.442.5913.4013.250.153.5E+000.5391+1 S1 Mw5-e2.602.7013.2413.1413.192.592.7413.2513.100.15 S1bMw5-f2.802.9013.0412.9412.992.743.0513.1012.790.31 S2 Mw5-g3.103.2012.7412.6412.693.053.2012.7912.640.158.0E-03-2.0969-2 S2bMw5-h3.204.2012.6411.6412.143.204.8812.6410.961.686.0E-03-2.2218-2 S2bMw5-i5.205.3010.6410.5410.594.885.7210.9610.120.841.0E-02-2.0000-2 S2bMw5-x5.705.8010.1410.0410.095.725.7910.1210.050.071.0E-04-4.0000-3 S2 Mw5-j6.006.109.849.749.795.796.4010.059.440.611.7E+000.2304+1 S3 Mw5-xx6.506.609.349.249.296.406.719.449.130.316.6E-01-0.1805+1 S3 Mw5-k6.806.909.048.948.996.717.019.138.830.302.3E+000.3617+1 S3 Mw5-xxx7.107.208.748.648.697.017.328.838.520.314.0E-01-0.3979+1 S3 Mw5-l7.407.508.448.348.397.327.628.528.220.301.3E+000.1072+1 S3aVC1-a0.120.2415.5515.4315.490.000.4015.6715.270.402.4E-01-0.6198-1 S1aVC1-b1.011.1214.6614.5514.610.401.6215.2714.051.222.1E+000.3263+1 S1aVC1-c2.192.3113.4813.3613.421.622.7414.0512.931.122.0E+000.3010+1 S1abVC1-d3.133.2512.5412.4212.482.743.6112.9312.060.861.2E-02-1.9208-2 S2abVC1-e3.783.9011.8911.7711.833.614.0212.0611.650.412.0E-03-2.6990-2 S2abVC1-f4.194.3011.4811.3711.424.024.4311.6511.240.413.6E-02-1.4437-1 S2aVC1-g5.085.2010.5910.4710.534.435.8111.249.861.373.6E-01-0.4437+1 S2aVC1-h6.156.279.529.409.465.816.569.869.110.768.4E+000.9238+2 S3aVC1-i 6.676.799.008.888.946.566.819.118.860.252.8E-01-0.5528+1 S3aVC2-org0.060.1715.6115.5015.560.000.2215.6715.450.224.6E+000.6618+1 S1 sample depthlithostratigraphic bed

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Appendix G (Continued) 193 [bls, below land surface; elev., elevation; m, meters; m/day, meters per day] # ofhydrothicknessstandardstratigraphic fromtofromtoaveragefromtofromto bK log K deviationsunit samplebls (m)bls (m)elev. (m)elev. (m)elev. (m)bls (m)bls (m)elev. (m)elev. (m)(m)(m/day)from meanaVC2-a1.131.2514.5414.4214.480.221.7815.4513.891.561.2E+000.0934+1 S1aVC2-b2.612.7213.0612.9513.011.783.3313.8912.341.553.9E+000.5877+1 S1abVC2-c3.853.9711.8211.7011.763.334.2712.3411.400.943.0E-03-2.5229-2 S2abVC2-d4.314.4211.3611.2511.314.274.4611.4011.210.192.0E-04-3.6990-3 S2abVC2-e4.684.7910.9910.8810.934.464.9911.2110.680.521.0E-03-3.0000-2 S2abVC2-f5.165.2710.5110.4010.464.995.7310.689.940.757.0E-03-2.1549-2 S2aVC2-g5.976.089.709.599.645.736.499.949.180.766.2E-01-0.2076+1 S3aVC2-h6.686.808.998.878.936.496.909.188.770.414.6E+000.6656+1 S3aVC2-i6.977.088.708.598.656.907.238.778.440.331.4E-01-0.8539-1 S4abVC2-j7.237.348.448.338.387.237.408.448.270.177.0E-03-2.1549-2 S4abVC2-k7.417.528.268.158.207.407.658.278.020.252.3E-02-1.6383-1 S4abVC2-l 7.767.877.917.807.857.658.048.027.630.404.3E-02-1.3665-1 S4aVC3-org0.120.2315.7915.6815.740.000.2915.9115.620.297.0E+000.8445+2 S1aVC3-a1.391.5014.5214.4114.470.292.0215.6213.891.732.0E+000.3096+1 S1aVC3-x2.082.2013.8313.7113.772.022.3113.8913.600.291.2E+000.0934+1 S1aVC3-b2.372.4813.5413.4313.482.312.5913.6013.320.281.5E+000.1644+1 S1abVC3-c2.893.0013.0212.9112.962.593.8713.3212.041.285.0E-03-2.3010-2 S2abVC3-d3.934.0411.9811.8711.923.874.5412.0411.370.677.1E-02-1.1487-1 S2abVC3-e4.624.7411.2911.1711.234.544.7511.3711.160.211.0E-03-3.0000-2 S2abVC3-f5.435.5510.4810.3610.424.755.7911.1610.121.043.1E-01-0.5058+1 S2aVC3-g6.356.479.569.449.505.796.5910.129.320.806.2E+000.7917+2 S3aVC3-h 6.937.058.988.868.926.597.149.328.770.552.7E+000.4346+1 S3 geom. mean of K (S1) =1.9231 -0.5648 = mean (log K) geom. mean of K (S2) =0.0082 0.0645 = median (log K) geom. mean of K (S3) =1.8107-3-2-1+1+2 1.2476 = st. dev. (log K) geom. mean of K (S4) =0.0434 -4.3076-3.0600-1.81240.68271.9303 1) a = Compaction correction factor applied to vibracore sample/bed depths due to based on difference between penetration and core length 2) b = S amp l e con t a i ns c l ay f rac ti on > 10% d 10es ti ma t e d b ase d on th e s i ze o f th e sma ll es t c l ay-s i ze d par ti c l es d e t ec t a bl e b y th e h y d rome t er a ft er 24 h ours o f se ttli ng s i nce s t ar t standard deviations from mean sample depthlithostratigraphic bed

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Appendix H. Hydrogeologic Stratigraphic Columns for Cored Sites 194 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 1 (MW-1) LITHOLOGY 0 1 2 3 1715.86 15.56 14.03 12.20 13.12 10.53 10.37 9.76 8.24 7.33 6.72 5.80 5.75 8.55 DESCRIPTION Organic-rich, dark gray-black well-sorted, subangular Clean, light gray-yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND VERY FINE SAND Marbled, light gray-yellowish orange-white medium-sorted, subangular SILTY/CLAYEY VERY FINE SAND Greenish gray-light brown poorly-sorted, subangular SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular CLAY Greenish gray Clean, light gray-white well-sorted, subangular VERY FINE SAND VERY FINE SAND Clean, yellowish orange-white well-sorted, subangular MEDIUM-FINE SAND Clean, white well-sorted, subangular FINE SAND Clean, yellowish orange-gray well-sorted, subangular FINEVERY FINE SAND Medium gray poorly-sorted, subangular SILTY VERY FINE SAND Light brown-gray with limestone chips poorly-sorted, subangular CALCAREOUS CLAY AND LIMESTONE Organic black-dark gray clay and limestone S4 S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER TAMPA LIMESTONE MEMBER OF THE ARCADIA FORMATION UPPER FLORIDAN AQUIFER LimestoneSTRATIGRAPHY GEOLOGY HYDROLOGY LIMESTONE Sandy fossiliferous limestone with minor clay and phosphate MW1 MW2MONITOR-WELL INTERVAL Appendix H.1. Hydrogeology of site 1 (MW1).

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Appendix H (Continued) 195 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 2 (FMW-2) LITHOLOGY 0 1 2 3 1715.85 15.55 12.20 13.42 10.58 10.06 9.14 7.93 7.32 5.94 5.87 DESCRIPTION Organic-rich, grayyellowish orange well-sorted, subangular Clean, yellowish orange-light gray well-sorted, subangular VERY FINE SAND VERY FINE SAND SILTY VERY FINE SAND Light gray-light brown poorly-sorted, subangular CLAY Greenish gray-light brown Clean, yellowish orange-white well-sorted, subangular VERY FINE SAND FINE SAND Clean, yellowish orange well-sorted, subangular SILTY VERY FINE SAND Slight silt, lt. gray-yellowish orange medium-sorted, subangular SILTY VERY FINE SAND Lt. brown-gray with limestone chips poorly-sorted, subangular CALCAREOUS CLAY AND LIMESTONE Organic black-dark gray clay and limestone chips S4 S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER TAMPA LIMESTONE MEMBER OF THE ARCADIA FORMATION UPPER FLORIDAN AQUIFER Limestone LIMESTONE Sandy fossiliferous limestone with minor clay and phosphate STRATIGRAPHY GEOLOGY HYDROLOGY MW3 MW4MONITOR-WELL INTERVAL Appendix H.2. Hydrogeology of site 2 (FMW2).

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Appendix H (Continued) 196 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 3 (MW-5) LITHOLOGY 0 1 2 3 1715.84 15.69 13.40 13.10 10.12 9.44 8.22 DESCRIPTION Organic-rich, dark gray well-sorted, subangular Clean, yellowish orange-light gray well-sorted, subangular VERY FINE SAND VERY FINE SAND SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular CLAY Greenish gray-light brown Clean, light gray-white well-sorted, subangular Silty sand lenses: gray-yellowish orange medium-sorted, subangular VERY FINE SAND WITH INTERBEDDED SILTY SAND CALCAREOUS CLAY AND LIMESTONE Organic dark gray-black clay and limestone S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER TAMPA LIMESTONE MEMBER OF THE ARCADIA FORMATION UPPER FLORIDAN AQUIFER Limestone VERY FINE SAND Clean, medium gray (13.40-13.25) Clean, white (13.25-13.10) well-sorted, subangular 10.05 8.83 8.52 8.18 9.09 LIMESTONE Sandy fossiliferous limestone with minor clay and phosphate STRATIGRAPHY GEOLOGY HYDROLOGY MW5 MW6MONITOR-WELL INTERVAL Appendix H.3. Hydrogeology of site 3 (MW5).

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Appendix H (Continued) 197 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 4 (FMW-4) LITHOLOGY 0 1 2 3 1715.43 15.13 13.14 9.64 7.81 DESCRIPTION Organic-rich, dark brown-gray well-sorted, subangular Clean, yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular Clean, light gray-white and yellowish orange-white well-sorted, subangular VERY FINE SAND CALCAREOUS CLAY AND LIMESTONE Organic dark gray-black clay and limestone S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER TAMPA LIMESTONE MEMBER OF THE ARCADIA FORMATION UPPER FLORIDAN AQUIFER Limestone VERY FINE SAND Light gray-yellowish orange well-sorted, subangular 9.94 7.76 9.34 13.91 LIMESTONE VERY FINE SAND Clean, lt. gray-yellowish orange well-sorted, subangular Sandy fossiliferous limestone with minor clay and phosphate STRATIGRAPHY GEOLOGY HYDROLOGY MW7 MW8MONITOR-WELL INTERVAL Appendix H.4. Hydrogeology of site 4 (FMW4).

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Appendix H (Continued) 198 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 5 (FMW-5) LITHOLOGY 0 1 2 3 1715.48 14.57 11.52 12.74 10.60 10.30 9.08 7.56 6.95 6.03 5.73 DESCRIPTION Organic-rich, dark gray-black medium-sorted, subangular Clean, light gray-yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND VERY FINE SAND Clean, dark brown well-sorted, subangular SILTY VERY FINE SAND Mottled, light gray-light brown medium-sorted, subangular SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular Yellowish light gray-white moderate-sorted, subangular VERY FINE SAND FINEVERY FINE SAND Very clean, light gray-white well-sorted, subangular VERY FINE SAND Clean, yellowish orange-white well-sorted, subangular SILTY VERY FINE SAND Clean, med. gray well-sorted CALCAREOUS CLAY AND LIMESTONE Organic black-dark gray clay and limestone S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER TAMPA LIMESTONE MEMBER OF THE ARCADIA FORMATIONUPPER FLORIDAN AQUIFER Limestone LIMESTONE Sandy fossiliferous limestone with minor clay and phosphate 15.18 SILTY/CLAYEY VERY FINE SAND Greenish gray-light brown poorly-sorted, subangular 4.81 VERY FINE SAND Clean, light gray-white well-sorted, subangular VERY FINE SAND Light gray medium-sorted, subangular 4.77STRATIGRAPHY GEOLOGY HYDROLOGY MW9 MW10MONITOR-WELL INTERVALS4 Appendix H.5. Hydrogeology of site 5 (FMW5).

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Appendix H (Continued) 199 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 6 (VC-1) LITHOLOGY 0 1 2 3 1715.67 14.05 12.93 12.06 DESCRIPTION Organic-rich, dark gray-brown medium-sorted, subangular Clean, light gray-yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular S3 S2 S1 UNDIFF. SANDS AND CLAYS SURFICIAL AQUIFER VERY FINE SAND Organic-rich, dark brown well-sorted, subangular 11.65 9.86 8.86 15.27 SILTY VERY FINE SAND Llightgray-yellowish orange medium-sorted, subangular FINE SAND Clean, white very well-sorted, subangular VERY FINE SAND Light gray-yellowish orange medium-sorted, subangular NO SAMPLES ? Note: Vibracoredevice met refusal prior to reaching top of limestone. Deepestpenetration of sampling at elevation of 8.86 m. 9.11 STRATIGRAPHY GEOLOGY HYDROLOGY Appendix H.6. Hydrogeology of site 6 (VC1).

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Appendix H (Continued) 200 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 7 (VC-2) LITHOLOGY 0 1 2 3 1715.67 13.89 11.40 12.34 11.21 10.68 9.18 8.27 DESCRIPTION Organic-rich, dark brown-dark gray well-sorted, subangular Clean, light gray-yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND VERY FINE SAND Organic-rich, dark brown well-sorted, subangular SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular Light gray-yellowish orange moderate-sorted, subangular SILTY VERY FINE SAND FINE SAND Very clean, lt. gray-white well-sorted S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER 15.45 CLAY Greenish gray-light brown SILTY/CLAYEY VERY FINE SAND Light tan-brown poorly-sorted, subangular 8.77 SILTYVERY FINE SAND Light brown-gray medium-sorted, subangular CLAY Greenish gray 8.44 SILTYVERY FINE SAND Light gray poorly-sorted, subangular S4 NO SAMPLES ? Note: Vibracoredevice met refu sal prior to reaching top of li mestone. De epest penetration of samp ling at elevati on of 7.63 m. 9.94 8.02 7.63 SILTYVERY FINE SAND Light brown-gray poorly-sorted, subangular Light gray poorly-sorted, subangular SILTY/CLAYEY VERY FINE SAND STRATIGRAPHY GEOLOGY HYDROLOGY Appendix H.7. Hydrogeology site 7 (VC2).

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Appendix H (Continued) 201 16 14 12 15 13 11 10 9 8 7 6 5 4Elevation NGVD (m)Site 8 (VC-3) LITHOLOGY 0 1 2 3 1715.62 13.89 12.04 11.16 10.12 8.77 DESCRIPTION Organic-rich, gray well-sorted, subangular Clean, light gray-yellowish orange well-sorted, subangular VERY FINE SAND VERY FINE SAND VERY FINE SAND Organic-rich, dark brown well-sorted, subangular SILTY/CLAYEY VERY FINE SAND Light gray-light brown poorly-sorted, subangular Very clean, white well-sorted, subangular FINEVERY FINE SAND VERY FINE SAND S3 S2 S1 UNDIFFERENTIATED SANDS AND CLAYS SURFICIAL AQUIFER CLAY Greenish gray-light brown SILTY VERY FINE SAND Light gray-yellowish orange medium-sorted, subangular NO SAMPLES ? Note: Vibracoredevice met refu sal prior to reaching top of li mestone. De epest penetration of samp ling at elevati on of 8.77 m. 15.91 13.60 VERY FINE SAND Clean, light gray-white well-sorted, subangular 13.32 9.32 Clean, yellowish orange-white well-sorted, subangular 11.37 Light gray-brown poorly-sorted, subangular SILTY VERY FINE SAND STRATIGRAPHY GEOLOGY HYDROLOGY Appendix H.8. Hydrogeology of site 8 (VC3).

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Appendix I. Isopach Maps of Hydrostratigraphic Layers 202 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 2.74 2.43 2.74 2.29 2.74 2.2 2.4 2.6 2.8UTM NORTH (meters)UTM EAST (meters) Appendix I.1. Isopach map of S1 layer in meters.

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Appendix I (Continued) 203 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 2.75 3.36 3.05 3.20 2.44 2.4 2.6 2.8 3UTM NORTH (meters)UTM EAST (meters) Appendix I.2. Isopach map of S2 layer in meters.

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Appendix I (Continued) 204 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 3.65 2.13 1.83 2.13 4.57 1.5 2.5 3.5 4.5UTM NORTH (meters)UTM EAST (meters) Appendix I.3. Isopach map of S3 layer in meters.

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Appendix I (Continued) 205 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.92 2.06 0.00 0.00 0.92 1.14 0.8 1.3 1.8UTM NORTH (meters)UTM EAST (meters) Appendix I.4. Isopach map of S4 layer in meters.

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Appendix J. Contour Maps of Vertical Head Differences 206 UTM NORTH (meters)UTM EAST (meters) 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.17 0.25 1.45 0.02 0.29 0.1 0.3 0.5 0.7 0.9 1.1 1.3 Appendix J.1. Map of vertical head differences between S1 and S3 on 03/03/97 in meters.

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Appendix J (Continued) 207 UTM NORTH (meters)UTM EAST (meters) 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.32 0.30 1.32 0.90 1.22 0.3 0.5 0.7 0.9 1.1 1.3 Appendix J.2. Map of vertical head differences between S1 and S3 on 10/03/97 in meters.

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Appendix J (Continued) 208 UTM NORTH (meters)UTM EAST (meters) 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.61 0.31 0.03 0.20 0.06 0.1 0.2 0.3 0.4 0.5 Appendix J.3. Map of vertical head differences between S3 and UFA on 03/03/97 in meters.

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Appendix J (Continued) 209 UTM NORTH (meters)UTM EAST (meters) 353700353800353900354000354100 3109900 3110000 3110100 3110200 3110300 3110400 0.55 0.58 0.02 0.59 0.26 0 0.1 0.2 0.3 0.4 0.5 Appendix J.4. Map of vertical head differences between S3 and UFA on 10/03/97 in meters.


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Hydrostratigraphy and groundwater migration within surficial deposits at the North Lakes Wetland, Hillsborough County, Florida
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by Jason J. LaRoche.
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[Tampa, Fla.] :
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2007.
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ABSTRACT: A wetland in west-central Florida was studied to characterize the local hydrostratigraphic configuration of surficial deposits overlying more-permeable limestones and conceptualize groundwater recharge. Eight continuous cores were drilled through the surficial deposits and partially into the underlying limestone. A total of 111 samples were extracted from the cores for laboratory sediment analyses and testing. The surficial deposits are roughly eight meters thick and made up of upper and lower clean-sand hydrostratigraphic layers (S1 and S3, respectively) separated by a low-permeability layer of clayey sand (S2). Also, a discontinuous low-permeability layer of clayey sand (S4) lies between S3 and the top of limestone. Equivalent hydraulic conductivity values for the S2 and S4 clayey layers (0.01 and 0.1 m/day respectively) are significantly less than those of the S1 and S3 sand layers (2 and 1 m/day respectively).Significant confinement between the surficial and Upper Floridan aquifers by means of a laterally extensive dense-clay unit immediately above the limestone is consistently reported elsewhere in the region, but was not encountered within the wetland. Partial confinement is apparently the result of low-permeability layers within the surficial deposits alone. Results of ground-penetrating radar and vertical head difference measurements suggest the presence of buried sinkhole features which perforate the low-permeability S2 layer and create preferred pathways for flow or karst drains. Comparison of results between laboratory sediment testing and a site-scale aquifer performance test (APT) suggest that the primary mechanism for drainage during the APT was by vertical percolation through the S2 layer while flow through karst drains was minimized. In this case, calculated leakances based on laboratory sediment testing are most accurate in approximation of effective leakance.It is predicted that as water table stages rise within the wetland, effective leakance will increase as flow toward karst drains becomes the more dominant mechanism for drainage. As a result, calculated leakances based on direct laboratory sediment testing are a decreasingly accurate approximation of effective leakance.
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Thesis (M.S.)--University of South Florida, 2007.
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Permeameter.
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Leakance.
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Dissertations, Academic
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