AN EVALUATION OF DIGITAL ELEVATION MODELS AND GEOTECHNICAL PROPERTIES OF THE GLACIAL DEPOSITS IN FRANKLIN COUNTY, OHIO, USING A GEOGRAPHIC INFORMATION SYSTEM

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

By

Jeffrey K. Bates, M.S.

*****

The Ohio State University 2007

Dissertation Committee:

Dr. Lawrence A. Krissek, Adviser Approved by Dr. E. Scott Bair

Dr. Garry D. McKenzie ______Dr. Thomas G. Naymik Adviser Graduate Program in Geological Sciences

ABSTRACT

The importance of unconsolidated deposits is reflected in the extensive use of these materials in Franklin County, Ohio. This study organizes geologic and geotechnical data in a geographic information system (GIS) to better understand the nature of the unconsolidated materials in this area. These data are then utilized to update the bedrock topography maps, evaluate the relationship between the geotechnical data and the diamictons, and to refine the interpretation of the surficial geology of the study area.

It was found that discrepancies are common between the surface elevation of geologic borings and the current surface elevation, represented by a digital elevation model (DEM) constructed in this study. It was also shown that there are considerable differences in the surface representation between the DEMs constructed here and DEMs obtained from the USGS. Elevation differences between the DEMs and the surface elevations of geologic borings were confirmed by performing global positioning system surveys at several boring locations. This study concludes that the USGS DEMs do not always accurately represent the current surface in this area, primarily because of land surface modifications by humans. Accurate DEMs are important to surficial mapping, as these efforts often rely on this surface representation for the correct vertical placement of subsurface data. The utilization of DEMs for other purposes is also explored here, showing that the outcome of a particular application can be affected by the DEM utilized. ii The updated bedrock topography maps are used to compare the bedrock drainage patterns, slopes, and aspect to some of the unconsolidated sediments. An evaluation of

the geotechnical data is made to assess whether geotechnical properties of the diamictons

show consistent variations with depth, and to determine if differences exist between

diamictons found on carbonate and clastic bedrock. Standard penetration test values,

Atterberg limits, and texture are found to differ somewhat for the diamictons above the

different bedrock types, possibly attributed to different source materials for the tills. The

diamicton properties in this area suggest they should be re-interpreted as deformation till.

Geotechnical data from certain borings also imply that lacustrine deposits are present in

several locations in northern Franklin County.

iii

Dedicated to my family

iv

ACKNOWLEDGMENTS

I first wish to thank my adviser, Dr. Larry Krissek, for his suggestions on selecting a research topic, his many hours devoted to this project, and especially for accepting me as one of his graduate students. This project progressed because of his encouragement and support.

Thank you also to my committee members, Drs. E. Scott Bair, Garry McKenzie, and Thomas Naymik. Their encouragement and suggestions were essential to the completion of the research.

Much appreciation goes to my employer, Columbus State Community College, who provided me with a job, allowed me to utilize their computers and GPS equipment, and provided financial support during my time at Ohio State.

I would like to express my gratitude to many of the employees at the Ohio

Department of Natural Resources. Mike Angle and Paul Spahr, of the Division of Water, provided me with encouragement and information that helped in piecing together this project. Several members of the Ohio Geological Survey also greatly assisted me in this research. Jim McDonald provided me with much of the GIS data used in the figures.

Mac Swinford provided me with access to ODNR facilities, personnel and data. Rick

Pavey gave me many suggestions on the use of GIS for surficial mapping. Scott

Brockman, formerly with ODNR, was an endless source of information relative to the v glacial geology of Ohio. I am especially indebted to Rick and Scott for greatly increasing

my knowledge of glacial geology.

Bob Mergel, of the Civil Engineering Technology program at Columbus State,

helped greatly in the GPS portion of the project by providing several days in the field, operation of the equipment, and post-processing of the data. His friendship and many hours donated to this project will always be appreciated.

Several employees of Franklin County, Ohio assisted me in the project, but the most important is Tony Stuart. He provided me with access to the data that allowed me to piece together the base map for this project.

Several people assisted me in the GIS portion of this project. Among those who put up with my many technical questions are Mike Rock, currently with the city of

Albuquerque, and Annie Parsons, with the GIS program at Columbus State.

Thank you to my family, for instilling faith and for providing words of encouragement in pursuing this degree.

I am indebted to my children, Abbie, Ryan, and Emily, who allowed their dad to be gone while he worked on this project.

The most important thank you goes to my wife Suzie. Her endless patience, love, and support allowed me to complete this project and the degree. I will forever be grateful to her.

vi

VITA

11 October 1968...... Born, Toledo, OH

1991...... B.A., Geology, University at Buffalo, SUNY, Buffalo, NY

Summer 1991...... Geology Field Camp Teaching Assistant, University at Buffalo, SUNY

1991-1993 ...... Graduate Teaching Assistant, Bowling Green State University Bowling Green, OH

Summer 1993...... Intern, Ohio Department of Natural Resources, Geologic Survey Lake Erie Section, Sandusky, OH

1994...... M.S., Geology, Bowling Green State University, Bowling Green, OH

1993-1995 ...... Geologist, Metcalf & Eddy, Inc., Columbus, OH

1995-Present ...... Faculty, Columbus State Community College, Columbus, OH

PUBLICATION

Bates, J.K., Evans, J.E., 1996. Evaluation of wellhead protection area delineation methods, applied to the municipal well field at Elmore, Ottawa County, Ohio. Ohio Journal of Science, 96, 13-22.

FIELDS OF STUDY

Major Field: Geological Sciences

vii

TABLE OF CONTENTS Page Abstract...... ii Dedication...... iv Acknowledgments...... v Vita...... vii List of Tables ...... xi List of Figures...... xiii

Chapters:

1. Introduction...... 1

1.1 Overview of the Study ...... 1 1.2 Description of the Study Area...... 3 1.3 Geology of the Study Area ...... 7

2. Review of Previous Studies ...... 9

2.1 Quaternary Period Glaciation in North America ...... 9 2.2 Glacial Geology of Ohio...... 11 2.3 Geology of Franklin County ...... 16 2.3.1 Historical Perspective...... 16 2.3.2 Unconsolidated Deposits...... 23 2.3.3 Ancient Drainage/Bedrock Topography...... 30 2.3.4 Bedrock Geology...... 35 2.4 Geographic Information Systems and Mapping of Unconsolidated Deposits.39 2.5 Geologic Databases...... 40

3. Methods...... 44

3.1 Introduction...... 44 3.2 Generating the Base Map...... 47 3.2.1 Sources of Surface Elevation Data ...... 48 3.2.2 Computer Methods Used to Generate Digital Elevation Models .....50 3.3 Obtaining Geologic Data ...... 51 3.4 Geologic Database ...... 55 3.4.1 Computer Database Production ...... 55 3.4.2 Locating the Drill Borings ...... 59 viii 3.5 Comparison of Boring Elevations to Surface Elevations ...... 63 3.5.1 Methods Used to Compare Surface Elevations and DEMs ...... 63 3.5.2 Use of Global Positioning Systems to Field Check Surface Elevation ...... 65 3.5.3 Examples of Digital Elevation Model Application...... 72 3.6 Modifications of Existing Bedrock Topography Maps ...... 76 3.6.1 Analysis of Bedrock Drainage Patterns ...... 79 3.6.2 Analysis of Bedrock Topography Map...... 79 3.6.3 Examination of Bedrock Topography Effects on Glacial Deposition ...... 80 3.7 Analysis of Surficial Deposits and Geotechnical Properties ...... 81

4. Results...... 88

4.1 Introduction...... 88 4.2 Description of Base Geographic Information System and Database for Study Area...... 89 4.2.1 Establishing a Digital Base Map...... 89 4.2.2 Digital Database and Boring Log Format...... 89 4.2.3 Geologic Data Sources...... 90 4.3 Surface Digital Elevation Models...... 91 4.4 Evaluation of Surface Elevations...... 92 4.4.1 Comparison of Boring Elevations to Digital Elevation Models ...... 93 4.4.2 Comparison of Digital Elevation Models ...... 99 4.4.3 Results of Global Positioning System Surveys to Investigate the Accuracy of Boring Elevations and Digital Elevation Models...... 106 4.4.3.1 Accuracy of GPS Survey Locations ...... 106 4.4.3.2 Comparison of Elevations from the GPS Survey and Boring Records ...... 110 4.4.3.3 Comparison of Elevations from the Global Positioning System Survey, Borings Records, and Digital Elevation Models113 4.4.4 Digital Elevation Model Applications ...... 118 4.4.4.1 The Placement of Boring Elevations in Subsurface Mapping ...... 118 4.4.4.2 Mapping of Flood Zones...... 121 4.4.4.3 Surface Water Modeling...... 124 4.5 Modifications to the Bedrock Topography Map...... 129 4.5.1 Data Used to Modify the Bedrock Topography Maps...... 129 4.5.2 Bedrock Drainage Patterns...... 136 4.5.3 Comparison of Bedrock Slopes to Bedrock Lithology...... 139 4.5.4 Comparison of Surficial Material Thickness to Bedrock Aspect ...143 4.6 Evaluation of Geotechnical Data ...... 146 4.6.1 Comparison of Standard Penetration Test to Gravel Content and to Depth in the Diamictons ...... 153 4.6.2 Comparison of Atterberg Limits...... 158 ix 4.6.3 Comparisons of Grain Size Data...... 162 4.6.4 Candidates for Lacustrine Deposits ...... 165

5. Discussion...... 169

5.1 General Discussion...... 169 5.2 Establishing a Geographic Information System for Geologic Mapping...... 170 5.2.1 Use of Digital Resources and the Generation of Geologic Databases ...... 170 5.2.2 Importance of Digital Elevation Model Accuracy...... 171 5.3 Geotechnical Data in the Unconsolidated Deposits...... 175 5.4 Geologic Interpretation ...... 180 5.4.1 Bedrock Topography...... 180 5.4.2 Glacial and Non-Glacial Geomorphology ...... 182 5.4.3 Lacustrine Deposits...... 190 5.5 Conclusions...... 191

6. Conclusions...... 193

6.1 Study Conclusions ...... 193

Bibliography ...... 196

LIST OF APPENDICES

Appendix Page

A Boring Log Data ...... 209

x

LIST OF TABLES

Table Page

2.1 Comparison of central Ohio till and till ages from three different reports ...... 15

2.2 Bedrock stratigraphy of Franklin County and immediate surrounding area...... 37

3.1 Description of GPS survey locations with location details...... 67

4.1 Statistical values (in meters) for the difference between boring elevation and DEM elevation at the boring...... 98

4.2 Horizontal distance between each boring location on the GIS and the GPS survey location for that boring...... 109

4.3 Elevations and difference in elevation for the 20 borings and GPS surveys...... 112

4.4 GPS station elevations, and differences in elevation for the twenty borings and DEM pixels containing the boring...... 115

4.5 Summary of patterns in the comparison of elevations from the GPS survey, starting boring elevation, and various DEMs ...... 117

4.6 Average difference between the elevation taken from the pixel of the DEMs and the boring elevation, and between the elevation taken from the pixel of the DEMs and GPS survey elevations...... 117

4.7 Root-mean-square-error for each DEM, using the GPS elevation as the true elevation value ...... 118

4.8 Comparison of the hydrologic parameters delineated in ArcSWAT runs using two different DEMs ...... 126

4.9 Average watershed hydrologic parameters from HRUs to the streams between ArcSWAT runs using the kriging DEM and the USGS DEM...... 126

4.10 Average watershed loadings from HRUs to the streams between ArcSWAT runs using the kriging DEM and the USGS DEM...... 127 xi

4.11 Comparison of the output for the two ArcSWAT model runs for one particular watershed ...... 127

4.12 Bedrock slope calculations for the various types of bedrock in Franklin County142

4.13 Comparison of the bedrock slope aspect (north- and south-facing) to unconsolidated material thickness ...... 145

4.14 Average values and standard deviations for the grain-size abundances for the samples taken above the clastic bedrock area...... 165

4.15 Average values and standard deviations for the grain-size abundances for the samples taken above the carbonate bedrock area ...... 165

5.1 Summary of the suitability of DEMs for different scales of utilization, based on the data source(s) and data abundance (number of data points/pixel)...... 175

xii

LIST OF FIGURES

Figure Page

1.1 Location and geographic features of Franklin County, Ohio ...... 4

1.2 Surface elevation of Franklin County...... 6

1.3 Surface Quaternary geology of Franklin County...... 8

2.1 Glacial lobes of the Lake Erie region during the Wisconsinan glaciation...... 14

2.2 Surficial geology map of the Columbus Quadrangle...... 18

2.3 End moraines referred to in this report ...... 22

2.4 Cross section of the stream cut at Rocky Fork Creek in Gahanna...... 26

2.5 Teays Drainage System in Ohio ...... 31

2.6 (a) Preglacial Teays/Groveport River drainage (b) Deep Stage/Illinoian drainage32

2.7 Bedrock topography of Franklin County ...... 34

2.8 Bedrock geology of Franklin County ...... 38

3.1 Flow chart showing how this study proceeds, from data collection to interpretation phases...... 46

3.2 Example of spot elevation data obtained from the Franklin County digital files ..49

3.3 Flow chart of the process used to generate the USGS DEMs for the Ohio Elevation Dataset...... 50

3.4 Example of an ODOT structure boring log used in this study...... 53

3.5 Example of geotechnical log used in this study...... 55

3.6 Boring information form created in Microsoft Access for an individual record, showing the fields used in this study...... 57 xiii

3.7 Boring log form created to incorporate geologic and geotechnical information at depth...... 58

3.8 The sketch on the left is from an ODOT Structure Foundation Plan sheet, with the arrows showing the location of the geotechnical borings for this site...... 61

3.9 Locations of the borings in the database...... 62

3.10 Digital elevation model showing the location of borings ...... 64

3.11 Boring locations surveyed with GPS ...... 69

3.12 Typical setup of global positioning system receiver and controller ...... 71

3.13 Example of GPS survey location ...... 71

3.14 A portion of the Flood Insurance Rate Map for a primarily residential area of Grove City, Ohio...... 75

3.15 Sketch showing the modified bedrock topography contours...... 78

3.16 Location and depth of the borings used to evaluate the geotechnical properties of the diamictons ...... 84

4.1 Surface topography as generated using the minimum curvature method, utilizing the Franklin County spot elevation data ...... 92

4.2 Histogram showing the difference in elevation of the top of boring and the pixel containing it for the DEM generated in this study using kriging...... 96

4.3 Histogram showing the difference in elevation of the top of boring and the pixel containing it for the DEM generated in this study using minimum curvature...... 97

4.4 Histogram showing the difference in elevation of the top of boring and the pixel containing it for the USGS 1 arc second DEM...... 97

4.5 Histogram showing the difference in elevation of the top of boring and the pixel containing it for the USGS 1/3 arc second DEM...... 98

4.6 Close up of the DEM generated using kriging...... 99

4.7 Difference in elevations from the DEM generated in this study using kriging and the 1/3 arc second USGS DEM ...... 103

xiv 4.8 Areas with a difference in elevation greater than 3 m between the DEM generated in this study using kriging and the 1/3 arc second USGS DEM...... 104

4.9 A portion of Franklin County showing the difference in elevation between the DEM generated in this study using kriging and the 1/3 arc second USGS DEM105

4.10 Sketch of two geologic borings, as represented by the surface elevation at the time of drilling ...... 120

4.11 The differences between the 100-year Special Flood Hazard Area designated by FEMA and the 100-year flood area if the same flood stages were mapped on a DEM constructed in this study...... 123

4.12 The watersheds delineated in ArcSWAT comparing the results from the DEM generated using kriging and the DEM obtained from the USGS...... 128

4.13 The borings that penetrated bedrock in this study, and their difference in bedrock elevation from the ODNR bedrock topography map...... 132

4.14 The borings that did not penetrate bedrock in this study, but have a bottom elevation below the bedrock surface elevation from the ODNR bedrock topography map ...... 133

4.15 Close up showing the bedrock topography contours ...... 134

4.16 Bedrock topography after corrections were made to the ODNR bedrock contours, and the pixel size was reduced to 30 m...... 135

4.17 Bedrock topography with drainage patterns (red lines) as generated using the Spatial Analyst tools in ArcGIS...... 138

4.18 Map showing the slopes on the bedrock surface ...... 141

4.19 Close up of the northwestern corner of the county (a) and the northeastern corner of the county (b)...... 143

4.20 Profile of geologic boring logs along the north-south transect found in the carbonate bedrock area ...... 149

4.21 Profile of geologic boring logs along the west-east transect found in the primarily clastic bedrock area...... 151

4.22 Scatter plot comparing standard penetration test value N to percent gravel for the diamictons in both the carbonate and clastic bedrock areas ...... 155

xv 4.23 Composite depth profile of average gravel content (weight %, represented by circles) and standard penetrometer test value ...... 156

4.24 Composite depth profile of average gravel content (weight %, represented by circles) and standard penetrometer test value ...... 157

4.25 Composite depth profile of plasticity index (represented by triangles) and liquid limit (represented by diamonds) for diamictons found in the clastic bedrock region ...... 160

4.26 Composite depth profile of plasticity index (represented by triangles) and liquid limit (represented by diamonds) for diamictons found in the carbonate bedrock region ...... 161

4.27 Ternary diagram showing gravel, sand and silt/clay abundances for diamictons found in the clastic bedrock region...... 163

4.28 Ternary diagram showing gravel, sand and silt/clay abundances for diamictons found in the carbonate bedrock region...... 163

4.29 Ternary diagram showing sand, silt and clay contents for diamictons found in the clastic bedrock region ...... 164

4.30 Ternary diagram showing sand, silt and clay contents for diamictons found in the carbonate bedrock region...... 164

4.31 Location of the four groups of borings that contain significant fine-grained deposits with characteristics different than the surrounding tills...... 167

4.32 Ternary diagram showing sand, silt and clay contents for those deposits interpreted as lacustrine in origin...... 167

4.33 Borings with lacustrine deposits at their base, found in east-west trending depressions in the bedrock topography...... 168

5.1 Close up of DEM developed in this study showing current stream channels along with other possible channels ...... 183

xvi

CHAPTER 1

INTRODUCTION

1.1 Overview of the Study

The importance of surficial deposits to society is reflected in the use of these materials in Franklin County, Ohio. The glacial and alluvial sediments form the aquifer framework from which much of the population and many industries obtain their water.

There is an extensive highway infrastructure built on these deposits, and much of

Columbus is developed on tens of meters of unconsolidated materials. Gravel, sand, and clay are removed for use as building materials and aggregate. The environmental, engineering and economic implications of these extensive deposits are many.

The unconsolidated materials of this region will continue to be important as the population of the greater Columbus area grows. With increasing development of the aquifers, there must also be proper management and protection of groundwater resources.

Although the engineering properties of these materials have been characterized for many years, this information has not been synthesized in a readily available form. The lack of comprehensive sources of information on these deposits has caused incorrect project planning, resulted in the failure of foundations, and is sometimes the reason for costly project overruns. Having more detailed maps and a better understanding of the 1 distribution of these unconsolidated deposits will assist in the evaluation for land use by

scientists, engineers and land use planners.

The glacial deposits of Ohio have been mapped on a broad scale (Pavey et al.,

1999) and the general glacial stratigraphy of Franklin County was described (Schmidt

and Goldthwait, 1958), but the resolution of these maps is not sufficient for certain

purposes. Ground-water reports for this area provide a higher level of stratigraphic detail

(Cunningham et al., 1996), but are limited primarily to municipal well fields. Maps of

unconsolidated deposits with a higher degree of resolution provide a level of detail that is

not only useful practically, but assists in the interpretation of the subsurface geomorphology and depositional history of the glacial deposits. This mapping is currently made possible with the use of large amounts of available subsurface data and by using recent advances in technology, such as geographic information systems (GIS) and computer programs in the study of the unconsolidated deposits.

The goals of this study are 1) to advance the understanding of the geologic and geotechnical nature of the unconsolidated materials of Franklin County by organizing the available data in a geographic information system (GIS), and 2) to use this tool in the applied analysis of these deposits. The specific objectives of this study are to:

1. develop a methodology using a GIS to assist public agencies in the compiling of

available subsurface data that will be used in the mapping of unconsolidated

deposits;

2. evaluate the accuracy of available digital elevation models that are often used as a

base in the three-dimensional mapping of the surficial materials;

2 3. refine the interpretation of the glacial geology and sedimentology of the study

area by evaluating the unconsolidated deposits; and

4. determine the relation between available geotechnical data and the distribution of

unconsolidated materials.

1.2 Description of the Study Area

Franklin County is in central Ohio and is the location of the state capital,

Columbus (Figure 1.1). The U.S. Census reported that in the year 2000 Franklin County

had a population of 1,068,978, making it the second most populous county in Ohio, and the city of Columbus had a population of 711,470, making it the most populous city in

Ohio. The population of Franklin County and the surrounding metropolitan area continues to grow, following the trend of land development that has persisted for over a century. The economy of Franklin County is diverse, with substantial business bases in agriculture, manufacturing, finance, insurance, transportation, government and education.

Franklin County occupies 1,409 square kilometers (544 square miles), with the highest elevation of 345 meters (1132 feet) in the northeastern corner, and the lowest elevation of

204 meters (670 feet) at the location where the Scioto River exits the county to the south.

There are a total of 7,255 kilometers (4,508 miles) of roads in the county.

3

Figure 1.1: Location and geographic features of Franklin County, Ohio. 4 Franklin County lies within the Till Plains Section of the Central Lowland

Province, with areas in the following four physiographic regions: the Central Ohio

Clayey Till Plain on the extreme northwest edge, the Darby Plain to the west, the

Columbus Lowland in the center of the county, and the Galion Glaciated Low Plateau in the northeast corner (Brockman, 1998). The topography ranges from flat to gently rolling, with only a few locations of steep terrain. The relief is a result of glacial deposition, stream erosion and relatively minor bedrock features such as an escarpment of Mississippian bedrock in the northeast portion of the county. Figure 1.2 shows the surface elevation as constructed from data used in the Shaded Elevation Map of Ohio

(Powers et al., 2002).

The principal stream in Franklin County is the Scioto River. The Big Darby

Creek, Olentangy River, Alum Creek and Big Walnut Creek are the other major streams in the county, generally draining to the south and eventually joining the Scioto. Surface water is the primary source of water for Columbus and other municipalities in the county, and approximately 85 percent of the water supplied by Columbus comes from three reservoirs located in northern Franklin County and southern Delaware County. The remainder of the water supply for the county comes from aquifers, with the majority of ground-water for Columbus obtained from the South Well Field. The aquifers in the southern part of Franklin County primarily formed from glacial outwash, with the wells obtaining water from the underlying bedrock and through infiltration of water from the streams adjacent to the wells.

5

Figure 1.2: Surface elevation of Franklin County. Data provided by the Ohio Division of Geological Survey.

6 1.3 Geology of the Study Area

The surficial geology of Franklin County consists of Quaternary deposits that are

glacial and alluvial in origin, with bedrock consisting of shale, sandstone, limestone and

dolomite that are Paleozoic in age. The unconsolidated materials range in thickness from

less than one meter to more than 80 meters. The majority of the surface glacial deposits

in Franklin County are characterized as late Wisconsinan silty loam till, forming ground

moraine (Figure 1.3, Pavey et al., 1999). Within the ground moraine, some areas are

mapped as having high concentrations of surface boulders. End moraine is found near the Franklin County/Delaware County boundary, formed of a silty clay till. End moraine is also found at the northeast and southwest corners of the county. Kames, kame terraces and eskers have also been mapped within Franklin County. Alluvium is found adjacent to the Olentangy River and Alum Creek, as well as along the lower stretch of the Scioto

River. Valley train deposits are also mapped in areas next to the major rivers, with the majority of this outwash found near the confluence of the Scioto and Olentangy Rivers

(Pavey et al., 1999).

7

Figure 1.3: Surface Quaternary geology of Franklin County (modified from Pavey et al., 1999).

8

CHAPTER 2

REVIEW OF PREVIOUS STUDIES

2.1 Quaternary Period Glaciation in North America

During the past 1.6 m.y. ice sheets have repeatedly covered much of present-day

Canada and the northern United States. The continental glacier(s) that once covered parts

of Ohio are referred to as the Laurentide Ice Sheet, with the ice origins probably centered

somewhere near present-day Hudson Bay. During glacial maxima the Laurentide Ice

Sheet is believed to have covered ~13,000,000 km2 and have approached thicknesses of

around 3,000 meters (Dyke et al., 2002). The character of the Quaternary glaciers and the nature of the diverse glacial deposits left behind by the multiple ice sheets have been keenly studied for over a century. For many years, establishment of the distribution of the glacial deposits dominated the research, but in recent decades our techniques in the study of these deposits have been advanced by improved dating techniques, use of geophysical methods, improved understanding of glacier mechanics, and an enhanced ability to reconstruct paleoclimates through modeling and proxies (Mickelson and

Colgan, 2004).

Oxygen-isotope records from ocean sediments show that glacial stages during the latter portion of the Pleistocene Epoch occurred approximately every 100,000 years; prior 9 to ~900,000 years before present glacial maxima were approximately every 40,000 years

(Clark, 1992). It is believed that there were at least four, and likely eight or more, major

continental glaciations in North America during the Pleistocene (Mickelson and Colgan,

2004), with evidence of ice sheet advances into various areas of the present-day U.S. over

twelve separate times (Richmond and Fullerton, 1986). The chronology of these

glaciations has been developed from multiple sources of evidence, including

paleomagnetic polarity data, volcanic ash beds, paleosols, and relative-dating techniques.

Although the timing of glacial advance and the resulting depositional stratigraphy can be

correlated regionally (Fullerton, 1986), the chronology of the advances in different ice

sheets and even glacial lobes generally differs due to variations in ice sheet evolution and

changes in climate (Lowell et al., 1999: Dyke et al., 2002).

Glaciations prior to the Late Middle Pleistocene were once referred to as the

Kansan and the Nebraskan, but those terms have been abandoned and the preferred

nomenclature for these deposits in Ohio is Pre-Illinoian, referring to any glaciations that

occurred during the Middle Middle Pleistocene or Early Pleistocene (Richmond and

Fullerton, 1986; Johnston et al., 1997). The glacial period that occurred during the Late

Middle Pleistocene (approximate period of 300 to 130 ka) is referred to as the Illinois or

Illinoian. The most recent glaciations that occurred during the Late Pleistocene in North

America are referred to as Wisconsin or Wisconsinan, and are divided into early (79 ka -

65 ka), middle (65 ka - 35 ka) and late Wisconsinan glaciations (35 ka - 10 ka)

(Richmond and Fullerton, 1986). The final Laurentide ice sheet began to develop around

27-30 ka and the glacial maximum occurred sometime between 19-21 ka (Dyke et al.,

2002). 10 2.2 Glacial Geology of Ohio

Pre-Illinoian glacial deposits are found in the extreme southwestern corner of the state, and were previously identified as Kansan deposits. These deposits include materials that are interpreted as lacustrine, ground moraine, and glacial outwash. The lacustrine deposits are mostly identified as the Minford Clay or Silt, formed in pre-

Illinoian ice-dammed lakes (Goldthwait, 1991; Pavey et al., 1999), and correlated using paleomagnetic data to around the change from the Early Pleistocene to the Middle

Pleistocene (Bonnett et al., 1991). The glacial moraine and glacial outwash deposits have not been directly correlated to a particular time period because of a lack of chronological constraints, and thus are simply categorized as Pre-Illinoian.

The Wisconsinan and Illinoian episodes of the ice sheet advance into Ohio are much better known through the many studies on the interpretation of Quaternary history.

The interglacial time period between these ice advances is known as the Sangamonian

Stage, Episode or Interglaciation. Many of the studies in Ohio on the Sangamonian

concentrate on the various aspects of soil development, including the examination of

paleosols and modern soil development on Illinoian deposits. Illinoian glacial deposits

are exposed at the surface along an ice margin that extends from northeast to southwest

Ohio. During the Illinoian the ice sheet extended further south than the glaciers during

the Wisconsinan, as demonstrated by the mapping of the respective deposits.

It was once speculated that an Early or Middle Wisconsinan glaciation occurred in

Ohio (Forsyth, 1965; Dreimanis and Goldthwait, 1973; Gooding, 1975; and most recently

Goldthwait, 1992), but the current consensus considers it unlikely that glaciers advanced into Ohio during these times. In their proposed classification and nomenclature for late 11 Quaternary glaciations, Johnson et al. (1997) consider the Early Wisconsinan ice to have

been restricted to the northern parts of the Great Lakes region. Most find it unlikely that

a Middle Wisconsinan ice sheet extended as far south as Ohio. Fullerton (1986) points

out that evidence for Middle Wisconsinan-age glacial deposits in the midwestern U.S. is

questionable because of the deficiency of well-documented chronostratigraphic units.

Johnson et al. (1997) do not establish a subepisode name for a Middle Wisconsinan

glaciation in the southern and western Great Lakes area because of a lack of glacial

deposits with that age. Instead the Middle Wisconsinan ice sheet likely was restricted to

the Lake Ontario basin (Richmond and Fullerton, 1986), covering most of the present-day

province of Quebec (Andrews, 1987). A record of Middle Wisconsinan glaciation was

once believed to exist in northern Ohio in the form of the Millbrook Till, evidenced by a

buried paleosol, but Dreimanis and Goldthwait (1973) later suggested that this till

belongs to the Early Wisconsinan. More recently Szabo (1992) and Szabo and Totten

(1995) consider the Millbrook, Gahanna and Chesterville tills as being Illinoian in age, because of thermoluminescence dates of greater than 100 ka assigned to overlying loess deposits. The Millbrook Till has been correlated with other deposits mapped as Illinoian and is identified as such on the Quaternary Geology of Ohio map (Pavey et al., 1999).

The Late Wisconsinan glacier that entered Ohio is separated into the Ontario-Erie

Lobe in the northeast and the Huron-Erie Lobe in the remainder of the state (Figure 2.1).

The Huron-Erie Lobe is separated into the Killbuck, Scioto and Miami Sublobes, with the

ice division occurring from topographic flow pattern separation. There were several

expansions and retreats of the Late Wisconsinan ice sheets in Ohio, with both Mickelson

et al. (1983) and Fullerton (1986) suggesting at least seven Late Wisconsinan advances of 12 the Scioto Sublobe between 21-15.5 ka. Although there are problems with correlating the various tills across Ohio, there are well-studied distinctions between the different tills of this sublobe, suggesting several ice sheet advances (Table 2.1). Dreimanis and

Goldthwait (1973) record several different “sets” of 14C dates marking the advance of the glacier, and more recently Lowell et al. (1999) identify at least two expansions at the southern limit of the Scioto Sublobe, based on radiocarbon dates. The final major ice sheet expansion reached central Ohio around 15 ka, and retreated from this area during the next few millennia (Figure 2.1) (Fullerton, 1986; Lowell, 1995).

13 (a)

(b)

Figure 2.1: Glacial lobes of the Lake Erie region during the Wisconsinan glaciation. (a) Glaciation during the glacial maximum (21,000-20,000 yr BP). (b) Glaciation during a major glacial readvance (15,500 yr BP) (Fullerton, 1986).

14 Lobe Navarre Millbrook Millbrook Gahanna Unnamed Hayesville Hayesville Chesterville Chesterville Northampton Eastern Scioto

Age Late Illinoian Wisconsinan Hiram Butler”) 2 units) Navarre Killbuck (multiple) Mogadore SublobeTill Millbrook and (multiple till units) till units) (multiple one or more “Pre- units and possibly Butler (at least two Butler (at least two Hayesville (at least (at Hayesville “Upper” “Lower” “Upper” “Lower” units) “Lake” Scioto Boston Tymochtee Tymochtee five till units) Sublobe Till Powell (at least 2 least two till units) till units) least two unnamed (three to Darby Jelloway and other and Jelloway Caesar Fork or Gahanna (at Rainsboro and Rocky

Time 17,400 16,000 14,400 14,800 17,400 20,400 20,400 22,000 65,000 75,000 15,000 15,700 (yr BP) BP) (yr Interval 132,000 302,000 Approx. Approx. Pre-Illinoian Butler Pre-Illinoian Powell Esboro London Wabash Glendon Defiance St. John’s Broadway Inner Cuba Outer Cuba Bloomingburg Buried Wilmington Reesville & Logan Elm Till Moraine Lake Darby Darby Upper Lower Lower Caesar Caesar (Darby I) (Darby II) (Caesar I) (Caesar II) Tymochtee Tymochtee Mickleson et al., 1983 – Scioto Sublobe Fullerton, 1986 Szabo and Totten, 1995

16,700 14,800 15,500 Unnamed 17,200 18,100 Upper 19,000 Unnamed 20,000 21,000 Boston Vandervoort & Mt. Olive “Middle” Position 16,100 & in yr BP) in yr (advance Ice-Margin

15 reports. three different till ages from Ohio till and central of Comparison Table 2.1: 2.3 Geology of Franklin County

2.3.1 Historical Perspective

The mapping of the unconsolidated deposits in Franklin County has a long history. Upon the first organization of the Geological Survey of the State of Ohio in

1837, an investigation of the geology of selected areas was made by principal geologist

William Williams Mather and his assistants. The First Annual Report (Mather, 1838a) described the clays, peat and soils of Ohio, with little mention of their possible origins, although some scientists had already identified ice as a possible mechanism for these deposits (White, 1973). In the Second Annual Report (Mather, 1838b), geologic assistants alluded to the possible formation of these Asuperficial materials@, with J. N.

Foster describing deposits found in parts of Licking, Franklin and Muskingum Counties.

This report identified Aformations@ of alluvium and peat, as well as deposits of the

ATertiary@ with descriptions of mastodon bones and granite boulders.

Some of the earliest detailed work was performed during the latter part of the 19th

Century and early part of the 20th Century by the United States Geological Survey

(USGS), most significantly by Frank Leverett. It is believed that he was the first to use subsurface records in detail, mapping many of the glacial deposits of the Midwest

(White, 1973). Leverett’s contributions to the identification of specific deposits led to a much greater understanding of their spatial distribution, with much of his classification nomenclature still being used today. His identification and description of deposits within the Scioto Lobe were very accurate, especially considering that there was no ability at the time to provide absolute dates.

16 An improvement utilized by Leverett and others was the advent of topographic maps. These aided glacial mapping by allowing geologists to better view spatial features, while also providing a mapping platform which greatly improved cartographic detail.

Many of the maps showing end moraines were refined in the early decades of the 20th

Century, leading to an improved understanding of the advance and retreat of the ice sheets. Also of benefit during this period was the use of aerial photography, which allowed even greater levels of detail in surface glacial mapping (White, 1973).

The first detailed mapping of the surface glacial deposits in Franklin County was published in 1911 by the Ohio Geological Survey, in a report titled the Geology of the

Columbus Quadrangle (Stauffer et al., 1911). This was one of the few 30-minute quadrangle maps during this time that delineated the surficial geology with a high level of detail (Figure 2.2). Progress in mapping these deposits continued into the 1950s and throughout the following decades. Of significant importance was the development of radiocarbon dating, which for the first time provided geologists with a tool to determine absolute ages for many glacial deposits (Forsyth, 1961). This advancement led to the refinement of many existing maps, and confirmed the hypothesis of multiple glaciations as evidenced by the varying deposits found in Ohio (Goldthwait, 1992).

17

Figure 2.2: Surficial geology map of the Columbus Quadrangle (from Stauffer et al., 1911).

18 Mapping the glacial deposits of many Ohio counties was performed during the

decades following the 1950s in more detail by George White, Richard Goldthwait, their

students, and many state-employed geologists. During this time there was a closer

evaluation of buried deposits, mostly due to the advent of exploratory drilling techniques.

Many reports were published by the Ohio Department of Natural Resources, sometimes

describing the glacial geology of a specific county, while descriptions of the glacial

deposits were also often incorporated within general geology or water resource reports

for specific counties. One such report is the Ohio Department of Natural Resources

bulletin titled The Ground-Water Resources of Franklin County, Ohio (Schmidt and

Goldthwait, 1958). This was published in response to the rapid growth that was

occurring in Ohio’s capital. This report is important because it was among the first to

map the unconsolidated materials below those at the surface, principally the distribution

of the sand and gravel deposits. Incorporated into the report is a section by Richard

Goldthwait describing the character and distribution of the glacial and alluvial deposits.

Included in the report is a map showing the uppermost alluvial and glacial deposits of the

county. Little has changed when this map is compared to the Quaternary Geology of

Ohio map (Pavey et al., 1999).

In 1961 the Glacial Map of Ohio was published (Goldthwait et al., 1961),

compiling the detailed work of investigators from the previous decades. Work continued

through the rest of the 20th Century, mostly by Ohio Geological Survey employees and

graduate students. The more recent publication, Quaternary Geology of Ohio (Pavey et al., 1999), updated and refined the work compiled by Goldthwait and others in the

19 Glacial Map of Ohio. The 1999 map shows the principal unconsolidated deposits at the surface, and describes the general physical characteristics of these materials (Figure 1.3).

The most detailed geologic studies in Franklin County have been for the purpose of investigating ground-water resources, and especially examined the coarse-grained deposits in the southern part of Franklin County. Some mention of the hydrogeologic resources was made in Stauffer et al. (1911) but these comments are only of a cursory nature. The first comprehensive report was the previously mentioned ODNR Division of

Water Bulletin, The Ground-Water Resources of Franklin County, Ohio (Schmidt and

Goldthwait, 1958). This publication was the first to incorporate detailed descriptions of the hydrogeologic properties of the surficial materials and the bedrock, providing a township-by-township breakdown of available ground water resources. More recent reports by ODNR have included the Ground Water Resources of Franklin County map

(Schmidt, 1993) and Ground Water Pollution Potential of Franklin County (Angle,

1995).

The majority of the recent studies investigate various aspects of the South Well

Field, including those studies identifying the available yield of this area (Ranney Water

Systems, 1968; Ranney Water Systems, 1970; Stilson & Associates, 1976). The USGS has worked in cooperation with the City of Columbus to provide detailed simulations of ground water flow at the South Well Field. Several Water-Resources Investigations

Reports have been published, including some that examine the water quality in relationship to the surface water/ground water system (de Roche and Razam, 1981; de

Roche, 1985; Childress et al., 1991). Other reports investigate and model the

20 hydrogeology of the site (Cunningham et al., 1996), with an expansion of this model to estimate the various contributions to recharge for this aquifer system (Schalk, 1996).

Among the most comprehensive private consulting reports on the geology and hydrogeology of the South Well Field is that submitted to the City of Columbus in 1988 by Bennett & Williams, Inc. The report’s geologic interpretation incorporates much of the speculative thinking by the authors in respect to the origin of the coarse grained deposits. For the purpose of aquifer delineation the report identifies four separate sand

and gravel stratigraphic units in the area of the South Well Field.

The surficial geology of areas in Franklin County has been further refined by

graduate students as thesis projects, significantly contributing to the understanding of the

glacial processes that formed the deposits. Often times this work provides subsurface

detail, improving the correlation between glacial deposits. Weatherington (1978)

described assorted characteristics of the surficial geology of Blendon and Plain

Townships. Paris (1985) described the stratigraphy and formation of the Powell Moraine,

which is on the northern edge of Franklin County (Figure 2.3). Both Stowe (1979) and

Cunningham (1992) performed detailed investigations of the hydrogeology of the Scioto

River Valley in south-central Franklin County. Stowe included cross sections from

several transects through the southern part of the county, and incorporated his

interpretation of the depositional sequence of the unconsolidated deposits. Cunningham

performed a comprehensive ground water simulation of the South Well Field through

several models and improved the understanding of its geologic framework, as well as the

understanding of surface water/ground water interaction.

21 y a B w r o a d

P J o o w e l l h n s New Albany t o w n

L o n d o n

Figure 2.3: End moraines referred to in this report (modified from the ODNR Glacial Map of Ohio, 2001, names taken from Goldthwait et al., 1965).

22 2.3.2 Unconsolidated Deposits

The unconsolidated deposits in Franklin County include both glacial and alluvial

deposits, with the glacial deposits being interpreted as subglacial, ice-marginal, glaciofluvial and glaciolacustrine in origin. The Quaternary Geology of Ohio map

(Pavey et al., 1999) shows the distribution of various glacial deposits, describes their

texture, and for the moraines, identifies their till association. The tills are described as

ground and end moraine, primarily differentiated by their topographic expression and difference in texture. The end moraines are identified by a ridge of glacial deposits, and mark a time of ice stagnation. Ground moraine generally lacks any well-defined surface expression, and is the till that is deposited beneath an advancing glacier or left behind as the glacier melts. Also found along the eastern half of the county are surfaces with a hummocky appearance, interpreted as kames and eskers. Of critical importance to the ground water resources are the valley-train deposits, interpreted mostly as glacial outwash that sometimes exceeds 75 meters in thickness.

There is a recognized association between the bedrock surface and the glacial deposits in Franklin County. Along the northeastern corner of the county lies the

Allegheny Escarpment, consisting of more resistant Devonian and Mississippian clastic rocks. This feature certainly was a major factor in restricting Pleistocene glaciations due to its relatively higher elevation in Ohio, and the areas of the county underlain by the

most resistant sandstones (Cuyahoga Formation and the Berea Sandstone) have some of

the thinnest glacial deposits. The glacial till above the Berea Sandstone averages only 6

meters thick, and thicknesses less than 3 meter are common (Angle, 1995). It has been

noted that, along the Allegheny Escarpment, tills often contain sediment that is similar to 23 the texture and mineralogy to the underlying sandstone, probably due to more effective

subglacial erosion over bedrock highs (Szabo and Angle, 1983). Much of the central to

southeastern corner of the county is underlain by the Bedford, Ohio and Olentangy

Shales, which generally are softer than the rocks to the east and west. This reduced

strength allowed greater erosion by various processes, so that these areas generally are

lower in elevation.

The youngest till in Franklin County is that found at the Powell Moraine, which

resulted from the glacial retreat ~15 ka. The uppermost deposit in this end moraine is

probably the Hayesville (or Powell) Till, a silty clay deposit superimposed on an older

end moraine composed of the Darby Till (Table 2.1) The lower till is differentiated from

the upper till at this moraine on the basis of texture and carbonate content (Paris, 1985).

The till that dominates the rest of the county is interpreted as the Darby Till from the

earlier Late Wisconsinan ice advance (Pavey et al., 1999). This silty loam surface cover

forms the ground moraine and end moraines in the area, including the Johnstown, New

Albany and London Moraines (Figure 2.3). The Darby Till probably originated from ice

movement coming from the northwest as evidenced by striations on carbonate bedrock

surfaces in and outside the county. Other evidence for a local flow of ice from the

northwest to the southeast includes the preponderance of dolomite pebbles (a common

bedrock northwest of Franklin County) in the Darby Till, even in areas with other types

of bedrock within Franklin County. In southern and western areas of the county this till

is sandier and covers some of the ice-marginal features, and is interpreted as an ablation till (McLoda and Parkinson, 1977; Angle, 1995).

24 Older Wisconsinan tills have been recognized in the other parts of the county and

have been correlated to tills south and east of the county (Wolf et al., 1962;

Weatherington, 1978; Frolking and Szabo, 1998; Lloyd, 1998). What is interpreted as

the Caesar Till can be found at several locales in the eastern part of the county and is

often differentiated into more than one layer (Weatherington, 1978; Frolking and Szabo,

1998). At a stratigraphic section along Rocky Fork Creek in Gahanna, Taylor and Faure

(1982) separated what is now interpreted as Caesar Till into two subunits based on

discontinuities, differences in pebble lithology and variation in mineralogy. The Boston

Till is recognized as the oldest Wisconsinan till in Franklin County and is interpreted to

have been transported in from the northeast because of the rock fragments found in the

deposit (Bennett & Williams, 1988).

The oldest glacial deposits in Franklin County are exposed in a stream cut in

Gahanna, and form a till commonly referred to as the Gahanna or Rocky Fork Till

(Figure 2.4). Goldthwait attributed this till to an early Wisconsinan glaciation

(Goldthwait et al., 1965; Dreimanis and Goldthwait, 1973; Goldthwait, 1992) because of

a 14C date of more than 37 ka in an overlying gravel deposit. Others as far back as 1911

(Stauffer et al., 1911) attributed this till to the Illinoian glaciation, with Szabo and Totten

(1995) ascribing it to pre-Wisconsinan glaciations based on regional glacial stratigraphy,

and a thermoluminescence age for loess overlying correlated tills. A sand and gravel deposit overlies the Gahanna Till at Rocky Fork Creek, and was once correlated by

Goldthwait to the Lockborne Gravels, which are found in southeastern Franklin County.

He originally interpreted this sand and gravel unit as glacial outwash from the early

Wisconsinan glaciation, but later recognized that it cannot be correlated to the Lockborne 25 Gravels (Goldthwait, 1992). The till overlying the sand and gravel in this stream cut has been correlated to the Caesar Till (Weatherington, 1978; Frolking and Szabo, 1998). The uppermost till at the Rocky Fork stream cut is believed to be the Darby Till, deposited during the final late Wisconsinan glaciation in this area.

Figure 2.4: Cross section of the stream cut at Rocky Fork Creek in Gahanna. The Gahanna Till (1) is likely Illinoian in age, the Lockbourne Outwash (2) is probably post- Illinoian in age, the Middle Blue Till (3) has been correlated to the Caesar Till, and the Brown Till (4) has been correlated to the Darby Till. (Interpretation from Frolking and Szabo, 1998, figure taken from Goldthwait, 1992)

The ice marginal landforms found in Franklin County include kames, kame

terraces, eskers, and outwash deposits. Kames form in glaciofluvial environments, and

the term is used to describe features that form from sand and gravel deposited within a

channel or depression in the ice. As the ice melts the sediment remains, often forming

mounds or ridges that are characterized by a hummocky surface. Although kames are

usually stratified, the beds are often tilted and contorted, with post-secondary structures

such as faults and folds forming as the material slumps or flows to the ground surface.

26 The most noteworthy of the kames in Franklin County is commonly referred to as

Spangler Hill, located south of Interstate 270 and east of U.S. Route 23. Stauffer et al.

(1911) described this as “the finest kames to be found in the area…consist(ing) of some

twenty or more gravel hills ranging in height from a few feet up to sixty or seventy.”

Stauffer also noted that, because of the extent of the kame at Spangler Hill, there must

have been a substantial amount of glacial drainage in this area, and there is evidence that

the water drained out of a channel on the east side of this area (Schmidt and Goldthwait,

1958). Bennett & Williams (1988) report that these sand and gravel deposits are easily

distinguished from the surrounding Lockbourne sands and gravels mostly because of the

scarcity of shale and sandstone fragments in the kames. Another significant kame in this

part of the county is found west of Groveport (Pavey et al., 1999). Schmidt and

Goldthwait (1958) interpreted this feature as an esker, noting a thin clayey till cover with

evidence of a paleosol beneath this thin veneer. This paleosol suggests that this coarse-

grained deposit was exposed for a period of time before the final glaciation in this area.

Kame terraces form between the ice margin and a topographic high such as a

bedrock escarpment or lateral moraine, with the meltwater deposits accumulating in this

area. When the ice melts the remaining sediments are deposited on the underlying slope,

forming a terrace with an often irregular morphology. It is not certain that kame terraces are found in the county, although it is possible that some coarse-grained deposits found

along the Berea Escarpment on the east side of Big Walnut Creek are small kame

terraces. More recent interpretations have a “beaded” esker extending from north of

Gahanna to several miles south of Reynoldsburg (Figure 1.3; Pavey et al., 1999). Eskers

are deposited in subglacial (or sometimes englacial or supraglacial) glaciofluvial 27 channels. It is believed that the deposits result from channel blockage, with the resulting

deposition occurring just upstream of the obstruction, but the mechanisms that create an

esker are probably more complicated than a simple damming effect (Bennett and Glasser,

1996). Eskers usually exist as sinuous ridges, with relatively steep slopes, consist of

poorly sorted sands and gravels, and sometimes are covered by a thin till. The alignment

of short eskers in Franklin County either suggest that an initial long esker was

subsequently broken by erosion, or indicate that these eskers formed within a single

channel system, but were deposited in segments due to blockage that progressed upstream and to the north.

Bedrock topography of Franklin County controlled much of the deposition of the

extensive sands and gravels by glacial meltwater. While some bedrock valleys were

filled with till, several valleys contain significant glacial outwash deposits, some with thicknesses that exceed 75 meters. The thickest glacial outwash deposits are loosely

associated with the Scioto River, Olentangy River, and Big Walnut Creek from central to

southern Franklin County. However, sand and gravel deposits can be found somewhere above the bedrock in almost every valley developed on clastic bedrock (Angle, 1995).

The correlation between the coarse-grained deposits and bedrock topography in central

Ohio was well established by several authors in the mid-20th Century (Stout et al., 1943;

Schmidt and Goldthwait, 1958; Norris, 1959). Norris (1959) explained this pattern of

outwash materials in portions of Franklin County, attributing the deposition in the lower,

softer shale terrain because the meltwaters were confined by more resistant bedrock.

Much of the glacial outwash that occupies the near subsurface of the three major

stream valleys in Franklin County has been described as the Worthington Outwash 28 (Stauffer et al., 1911; Schmidt and Goldthwait, 1958; and Bennett & Williams, 1988).

The thickness of this outwash varies throughout the area, but incorporates the major

glacial outwash from the Wisconsinan glaciers. The thick sand and gravel deposits

underlying the Worthington Outwash in southern and southeastern Franklin County are

commonly referred to as the Lockbourne Outwash or Lockbourne Sands and Gravels. In

the area of the South Well Field, Bennett & Williams (1988) note the possibility of three

periods of deposition, with two significant coarse-grained lithologic units within the

Lockbourne. Several interpretations have been offered for the origin of the Lockbourne

Sand and Gravel; all of these include a sediment source to the east of Franklin County.

This is because sandstone clasts are common in the Lockbourne deposits and sandstone is

characteristic of the bedrock east of Franklin County (Bennett & Williams, 1988;

Weatherington-Rice et al., 1988). Weatherington-Rice et al. (1988) interpret this deposit

as post-Illinoian fluvial or glaciofluvial in origin. Although the so-called Lockbourne

Outwash at the Rocky Fork Cut in Gahanna (Figure 2.4) has not been correlated

stratigraphically with the Lockbourne in southern Franklin County, Goldthwait (1992)

noted that the Lockbourne at Rocky Fork contains sandstone that is likely from an eastern

source. The Lockbourne overlies the Gahanna Till at the Rocky Fork Cut, with the

Gahanna Till now being interpreted as Illinoian (Szabo and Totten, 1995). Bennett &

Williams (1988) also identify a separate fine-grained sand deposit restricted to the lowest

of the three coarse-grained deposits described at a quarry off of State Route 104. They

tentatively name this the Shadeville Outwash, interpreting it as a late Illinoian fluvial ice-

margin deposit.

29 Lacustrine deposits can be found in some areas within the county. Schmidt and

Goldthwait (1958) interpreted the well sorted fine sand within some of the deepest

bedrock valleys as having been deposited by “quiet waters” during the Illinoian. They noted fine sand and silt deposits in the deeply buried valleys in Washington, Plain and

Jefferson Townships at depths ranging from 1 to 67 meters below present ground surface.

Also described in Schmidt and Goldthwait (1958) is a lake clay deposit found in a ravine north of Worthington, and the map of alluvial and glacial deposits in the 1958 ground water report shows a small area of lake beds in northern Clinton Township; both of these

are interpreted as glacial lacustrine in origin. Upland organic soils and gyttja have been

identified at and near the offices of the Ohio Department of Natural Resources complex

on Morse Road, and compaction of these deposits caused damage to structures built on

these materials (McKenzie et al., 2002). These laminated and organic-rich materials are

likely post-glacial lacustrine deposits, but 14C dating produced an unexpectedly old age of

28 ka, predating the late Wisconsinan glaciation (Brockman, 2006). A thin deposit (~1

m) interpreted as a lacustrine sequence is found under the surface till at Bill Moose Run,

Ohio Schools for the Deaf and Blind (Haefner, 1999). Wood found in this lake bed

material also produced a 14C date of approximately 28 ka (Brockman, 2006). Bennett &

Williams (1988) make reference to laminated silt and clay deposits found in several areas

of Franklin County, interpreting these as Minford Silt. However, these have not been

correlated to the Minford Silt found in southern Ohio.

2.3.3 Ancient Drainage/Bedrock Topography

The influence of bedrock topography on the deposition of the various

unconsolidated deposits is well documented for central Ohio. Many of the studies began 30 with the recognition of an ancient drainage system, as evidenced by the bedrock topography mapped in Stout and others (1943) in the seminal Ohio Geological Survey

Bulletin Geology of Water in Ohio. The ancient drainage channels are commonly referred to as the Teays Bedrock Valley System, with flow that once extended from southern Ohio generally to the northwest (Figure 2.5). These ancient drainage channels are interpreted to extend from Chillicothe to the northwest to Madison County, where the primary channel then took a more westerly route (Norris and Spicer, 1958). South of

Columbus a tributary of the Teays System is interpreted to have drained to the west

(sometimes referred to as the Groveport River). The headwaters of this tributary are thought to have been located in Wayne County (Figure 2.5). Several minor tributaries in present-day Franklin County are believed to have flowed generally to the south, and eventually drained into the Groveport River.

Figure 2.5: Teays Drainage System in Ohio (from Angle, 1995, modified from Stout et al., 1943). 31 The Teays System drainage is interpreted to have changed course sometime during the early Pleistocene, probably due to the influence of a glacial boundary sometime around 700 ka (Goldthwait, 1991). Ice dammed the bedrock valleys, resulting in extensive lakes often referred to as Lake Tight. Evidence from rhythmites with reversed magnetic polarity (commonly referred to as Minford Silt or Clay) matches the timing of a pre-Illinois glaciation of ~0.79 to 0.88 m.y. ago (Bonnett et al., 1991). The

Teays System continued to change later in the Pleistocene, starting when the Illinoian glaciations acted as a major erosional mechanism, altering the unconsolidated deposits but also changing the bedrock valleys. Figure 2.6 shows the inferred changes from the pre-glacial Teays System/Groveport River drainage to the Deep Stage/Illinoian Drainage

(Angle, 1995; Schmidt and Goldthwait, 1958). Water from the melting ice sheet would have caused additional stream bed erosion and deposition.

(a) (b)

Figure 2.6: (a) Preglacial Teays/Groveport River drainage. (b) Deep Stage/Illinoian drainage. (from Angle, 1995, modified from Schmidt and Goldthwait, 1958).

32 The current bedrock topography is mentioned in several studies, especially

ground water reports (Stout et al., 1943; Schmidt and Goldthwait, 1958; Norris, 1959).

Many of these reconstructions were based on data from drilling reports. Norris (1959) noted that the bedrock drainage pattern in the eastern half of the county, which is dominated by shales and other clastic rocks, shows a dendritic pattern with wide U- shaped valleys, while the western side mostly consists of limestone and dolomite, and shows more trellis-like drainage patterns with more narrow V-shaped valleys. More recently the Ohio Division of Geological Survey (2003b) published the Shaded Bedrock

Topography Map of Ohio. This is a compilation of data from across the state, with

Figure 2.7 showing the bedrock topography for Franklin County constructed from the data used in this report.

33

Figure 2.7: Bedrock topography of Franklin County. Data provided by the Ohio Division of Geological Survey.

34 2.3.4 Bedrock Geology

The subcrops and outcrops of Paleozoic bedrock in Franklin County generally

trend north-south, with western areas of bedrock consisting of Silurian carbonates, the

central, southeastern and portions of the western area of the county consisting of

Devonian carbonates and shale, and the northeastern corner consisting mostly of

Devonian and Mississippian limestone, sandstone and shale (Table 2.2 and Figure 2.8).

The Silurian bedrock is the Salina Group undifferentiated, which is primarily dolomite

that formed in shallow marine environments. Overlying the Silurian rocks is the

Devonian Columbus Limestone, which varies in composition from more fossiliferous and calcareous in the upper two-thirds to a brown dolomite in the bottom one-third (Swinford et al., 2000). Above the Columbus Limestone is the Delaware Limestone, which is a relatively dense, argillaceous, and cherty limestone of limited thickness. Overlying this is the Olentangy Shale, a laminated clayey shale that is relatively soft; its lower portion contains limestone nodules. The Ohio Shale overlies the Olentangy Shale, and is a very thick (over 100 m) carbonaceous shale formed in a marine basin with limited circulation.

The Ohio Shale is the exposed bedrock through much of the central part of the county

(Figure 2.8). Above the Ohio Shale is the Bedford Shale, which was recently identified as Devonian (Pashin and Ettensohn, 1995). The Bedford Shale grades upward from a clayey lower zone to a more silt-rich upper zone, and has been interpreted as a prodelta deposit (Coats, 1988; Pashin and Ettensohn, 1995). The Bedford transitions into the overlying Berea Sandstone, a light, very-fine grained sandstone with thicknesses of approximately 10 meters. The Berea also coarsens upwards, recording continued changes in the delta- front depositional environment. Above the Berea is the Sunbury 35 Shale, a carbonaceous shale that is interpreted to have formed in a stagnant basin affected

by sea level rise (Coats, 1988). The uppermost Mississippian deposits in this area are the generally undivided Cuyahoga and Logan formations, consisting of interbedded fossiliferous limestone, brown sandstone, and gray to brown shale.

36

) a

y Formations Description Age M ( Period

Maxville: Gray fossiliferous limestone, weathers to light gray to tan, massive to nodular bedding. Logan: Brown sandstone, weathers light brown to Mississippian undivided reddish brown, thin to thick bedded, planar to (Maxville Limestone, Logan lenticular bedding. Formation, Cuyahoga formation Cuyahoga: Gray to brown shale interbedded with undivided) (Mu) minor sandstone and siltstone grading to massive 359-318 sandstone, weathers to light gray to light brown, Mississippian Mississippian thin to thick bedded, planar to lenticular bedding. Black to brownish-black carbonaceous shale, Sunbury Shale (Ms) Sunbury- very thin laminae. Berea- Very fine-grained light greenish gray sandstone, Berea Sandstone (Mb) Bedford weathers to shades of yellow brown, thin to thick Undivided bedded, planar to lenticular to cross-bedded. (Msbd) Gray, green, red and brown shale, siltstone beds Bedford Shale (Mbd) in upper ¼ of unit, laminated to medium bedded. Ohio- Brownish black to greenish gray carbonaceous Ohio Shale (Doh) Olentangy shale with carbonate/siderite concretions, Shale laminated to thin bedded, fissile parting. Undivided Greenish gray to medium gray clayey shale with Olentangy Shale (Dol) 416-359

Devonian Devonian (Do) limestone nodules, laminated to thin bedding. Gray to brown argillaceous, cherty, carbonaceous Delaware Limestone (Dd) limestone, thin to massive bedding. Gray to brown fossiliferous limestone and dolomite, weathers brown, massive bedding, Columbus Limestone (Dc) upper 2/3 fossiliferous limestone, lower 1/3 brown dolomite. Gray and brown dolomite, thin bedding, Salina undifferentiated (Ssu) argillaceous partings. Olive gray to yellowish brown dolomite with Tymochtee Dolomite (St) brownish-black to gray shale laminae, thin to massive bedding. Olive gray to yellow brown argillaceous dolomite, Greenfield Dolomite (Sg) thin to massive bedding.

Silurian White to medium gray dolomite, medium to 443-416 Lockport Dolomite (Sl) massive bedding, fossiliferous, vuggy porosity, finely to coarsely crystalline nature. Gray to olive green, yellow and reddish gray Sub-Lockport undifferentiated (Ssl) dolomite, limestone and shale, laminated to thick bedding.

Table 2.2: Bedrock stratigraphy of Franklin County and immediate surrounding area. The symbols used on the 7.5-minute bedrock-geology maps are in parenthesis (based on Swinford et al., 2000, and Ohio Division of Geological Survey, 2004).

37

Figure 2.8: Bedrock geology of Franklin County. Data provided by the Ohio Division of Geological Survey.

38 2.4 Geographic Information Systems and Mapping of Unconsolidated Deposits

Currently there are efforts by several geological agencies to improve the quality

of surficial mapping in the Midwest. The Central Great Lakes Geologic Mapping

Coalition was formed in the late 1990s by the state surveys of Ohio, Indiana, Illinois and

Michigan, along with the USGS. It is recognized that less than 2 percent of this glaciated

region has been mapped in Asufficient detail@, yet 15 percent of the population of the U.S.

lives in this region (Berg et al., 2000). There are initiatives to map in detail important

areas within these states, beginning with urban areas and regions with significant

environmental concerns. In this process maps will be constructed in a digital format,

with derivative maps (such as significant groundwater zones or horizons of geotechnical significance) also extracted. This process will utilize innovative methods to obtain useful data for constructing the maps, such as the use of geophysical techniques. Stack-maps of the surficial deposits are being constructed in all four states, but production is primarily in the form of hand-drafted stack maps that are converted into digital forms. Polygons of identifiable “stacks” of material are delineated, and then transferred into a two- dimensional form, mostly using the software ArcGIS. These maps will be useful in the evaluation of geologic hazards and for planning and development, and will increase our understanding of the hydrology of an area. The maps produced by these efforts should also help refine our understanding of the glacial processes that formed these valuable deposits. The Illinois State Geological Survey has made progress in their surficial mapping by modeling the three-dimensional subsurface using software such as Dynamic

Graphic’s Earth Vision, which performs interpolation and provides a three-dimensional image of the deposits (Soller et al., 1998; Abert et al., 2000). 39 The use of digital techniques to improve the study of glacial geology and geomorphology is becoming more common. More than 10 years ago Vitek et al. (1996) commented on the antiquated methods used for mapping geomorphology, arguing that digital techniques must be incorporated into this field. Brown et al. (1998) used digital elevation models to assist in the classification of glaciated landscapes in Michigan, with moderate success in the use of automated methods to demarcate particular landforms based on several different geomorphic measures. Allan (2000) used a GIS to assist in determining the genesis of glacial features found north of the Broadway Moraine.

Leverington et al. (2002) reconstructed late Quaternary landscapes using a GIS method that subtracts interpolated isobase surfaces from modern elevations, thereby generating paleo-topographic maps.

2.5 Geologic Databases

The expansion of geologic databases in digital forms has coincided with increased use of computers and, more recently GISs. In recent years geological databases integrated with a GIS have been used for traditional geologic mapping (Bain and Giles,

1997; Colman-Sadd et al., 1997), engineering purposes (Toll and Oliver, 1995; Nathanail and Rosenbaum, 1998), ground-water management (Brodie, 1999) and general evaluation of the environment (Zhang et al., 1999). Many of these projects centered on the creation of thematic maps (Power et al., 1995; Laxton and Becken, 1996) and furthered their project through the application of geostatistics (Rosenbaum and Nathanail, 1996;

Nathanail and Rosenbaum, 1998).

The use of databases for geological purposes is unusual in that the types of data that are collected and processed can be quite different from those data for which 40 databases are often designed and analyzed (Rasmussen, 1995). Geological systems and the study of earth processes are ever-changing, so that old data often are useful in the reexamination and reinterpretation of current topics (Rasmussen, 1995). Database design is especially important in GIS development, as the design involves establishing a series of steps that will ultimately produce a geodatabase structure that organizes a geologic system (Zeiler, 1999). Rasmussen (1995) outlined the database approach to properly design the geological database so that it is useful to the greatest number of people. This involves two primary principles: 1) the database must contain information that models reality, and 2) it must have a flexible query system to make the information accessible.

Following these principles the database can then be built to incorporate information about entities and their relationships, and contain attributes or properties for the data.

Inherent in most database management systems (DBMS) is the storage structure and the establishment of links within that structure. The data that are being stored can be broken down into elements that can be connected in several ways. The smallest data unit is the field, which is identified by a field name. An example of a field name used in drilling logs is “ground surface elevation”, whereas the field for a particular drilling location would be a specific value. A collection of fields is known as a record, which for geologic purposes might incorporate all of the fields and associated information collected at a particular location.

Problems in designing geological databases primarily revolve around two sets of issues (Rasmussen, 1995). The first is the improper use of data modeling techniques, where the database does not correctly classify or represent differences in geologic features. These data may be subjective or open to interpretation, which is implicit 41 especially in the collection of geologic data in the field. Also problematic is that these

data modeling techniques often need to satisfy the conflicting objectives of describing reality and having a data structure that is implementable in a DBMS. The second set of

problems is related to the DBMS itself. Most DBMS are not designed for geological

data, but rather to contain simple fields with numeric or brief text data. It is common for

some quantitative geologic data to take these forms, whereas lengthy or subjective

descriptions may be necessary but are cumbersome in many DBMS. Database

management systems also require processing and recovery of data, and geologic

databases require that the database form allows for these activities over long periods of

time and are available a large number of users. This mandates that the digital form

allows DBMS updates and the digital forms can be accessed by various versions of the

program(s) that are used (Rasmussen, 1995). Some of these DBMS issues have been

resolved to some extent with the need of databases to be compatible with GIS systems, as

the development of these systems often requires data modeling of non-numeric or

subjectively described features.

An additional problem in establishing geologic DBMS is the handling of data

within the subsurface, requiring the addition of a third dimension. These spatial data

often are of variable quality and not quantitative, ranging from numerical information to

generalized descriptions (Rosenbaum and Nathanail, 1996). If these data are to be

utilized in a GIS, one goal should be to produce quantitative data, because quantitative

data are compiled more readily in a database. Much of the quantitative data obtained

from subsurface investigations results from geotechnical testing of samples. But one

must question the usefulness of quantitative data in the characterization of the subsurface. 42 Traditionally, geologists utilize qualitative information to interpret the geology of an

area; although some investigations produce quantitative data, the majority of shallow

subsurface drilling and sampling activities produces qualitative information. In addition,

there are many occasions when qualitative data are useful, including for engineering

purposes (Rosenbaum and Nathanail, 1996).

Geologic maps are two-dimensional tools that often show verified features or an

interpretation of the three-dimensional surface or subsurface geology (Bain and Giles,

1997). Most geologists agree, however, that traditional geological maps are often deficient in portraying the three-dimensional subsurface (Laxton and Becken, 1996). It is common that information used in the creation of geologic maps is from subsurface sources, such as drilling logs or geophysical data, but the data from this third dimension often are not easily converted into well-organized or easily usable digital database forms.

The difficulty arises from the fact that a geologist can synthesize the data into three- dimensional forms, but a computer needs fully coordinated 3D data to produce a 3D model (Giles and Bain, 1995). Bain and Giles (1997) address this issue by proposing a model for the collection of data, based on the principal components of most geologic maps and the common segments found within each of these components.

43

CHAPTER 3

METHODS

3.1 Introduction

This study begins with the goal of establishing a system to improve the spatial accuracy of surficial maps. This is accomplished by generating a highly accurate digital base map, incorporating the precise locations of bridges, roads and other features that

allow the location of geologic borings to be established with a higher level of accuracy

than is usually achieved in these efforts. Another potential improvement to mapping the vertical distribution of geologic data is to establish a digital elevation model (DEM) of the surface that is more accurate than those that are readily available, such as those produced by the USGS. These DEMs are evaluated for their accuracy, based on both existing elevation data and data obtained in the field. The DEMs are then assessed by demonstrating that differences in the elevation values affect their impact in practical ways.

Databases established here are constructed primarily from geotechnical borings, and the base map is used to determine the horizontal coordinates with a high level of precision. The database is connected to the base map to create a GIS that allows for the easy access to geologic and geotechnical data. This information is used to revise the 44 existing bedrock topography map, and this revised map is then used to facilitate a

comparison of particular characteristics of the bedrock topography to glacial and lacustrine depositional models. Geotechnical properties are also assessed to determine if differences in tills are related to the type of underlying bedrock. A flow chart of how this investigation proceeds is shown in Figure 3.1.

45

Collection of subsurface geotechnical data

Construct boring and Generation of base Evaluate accuracy of subsurface databases maps and DEMs DEMs

Create GIS of geologic Assess impact of DEM and geotechnical data accuracy

Modify existing bedrock Compare geotechnical topography map properties

Assess relationship of Evaluate unconsolidated bedrock topography to depositional processes glacial deposition

Figure 3.1: Flow chart showing how this study proceeds, from data collection to interpretation phases.

46 3.2 Generating the Base Map

Because the use of GIS has become so widespread, there are multiple sources of

information to assist in the establishment of a base map for geologic mapping purposes.

The primary concerns with generating a base map in this study are 1) the level of

accuracy needed to properly locate the geotechnical borings and 2) the establishment of

an adequate surface topography map. Most of the locations of available ODOT

geotechnical borings are not surveyed in using a standard x-, y-coordinate system, but are described using a station and offset system; the station is identified as a measurement in feet along a road’s center line from a known point and the offset is the distance measured right or left of that station. Engineering figures and report profile sheets show these locations, but a problem arises because most base maps do not show features in enough detail to measure off those features in the GIS. Surface features, such as roads and streams, are accessible in a digital format and easily imported into a GIS, but they are often represented with a single line in a GIS.

The Franklin County Auditor’s office maintains a computer-aided drafting and design (CADD) system that adheres to ODOT CADD Standards. The CADD system contains layers of data such as road center lines, the boundaries of bodies of water, and surveying data. The Franklin County CADD system is broken down into over 2000 smaller files to minimize the enormous data size of the system, with each file referred to as a “facet”. The facets are gridded units of geographically-stored information that are referenced in state plane coordinates, with each facet covering a 2,500 ft (762 m) by

2,500 ft square portion of Franklin County. The facets contain over 30 CADD layers containing a variety of geographically-referenced data commonly used for construction 47 purposes. The digitally compressed CADD files were obtained from the Auditor’s office,

and each facet file was uncompressed using the program AutoCAD®. Only certain

elements believed to be important for this study, such as roads, water, spot elevations,

and surface contours, were extracted and retained. The individual facets were then

connected together in AutoCAD® as one county map, with a final data file size of several

gigabytes. The separate elements were saved as individual files to minimize the data

sizes, and were then imported into ArcGIS, the GIS software package that is used for the

majority of the GIS operations for this study. A geodatabase was generated in ArcGIS

for the various layers to ease the transition between CADD and the GIS.

3.2.1 Sources of Surface Elevation Data

The surface elevation data used to generate digital elevation models for this study

were taken from the Franklin County Auditor’s GIS files described above. These data

originate from an aerial survey in 2000, where orthophotography was used to establish

spot elevations, calculated using triangulation based on a total of 360 control points that

were established by the Franklin County Engineer’s office. A total of 739,068 spot elevations were contained in the file, with elevations based on National Geodetic Vertical

Datum (NGVD) 1929 using the Ohio State Plane Coordinate System, South Zone for horizontal control (Figure 3.2).

48

Figure 3.2: Example of spot elevation data obtained from the Franklin County digital files (elevation data shown in ft above msl, at the intersection of Interstate 270 and State Route 23 on the north end of the county.)

United States Digital Elevation Models for areas including Franklin County were downloaded from the National Elevation Dataset (available at http://ned.usgs.gov). Files containing large scale DEMs based on the 1;24,000 scale topography quads are readily available through the Seamless Data Distribution System. According to the USGS, the vertical accuracy of NED data is +/- 7 to 15 m, based on the sources used to manufacture the DEM, which are primarily existing topographic maps and aerial photos. For the Ohio elevation dataset the existing hypsography, in the form of digital line graphs of the original quadrangle elevation contours, were used to create DEMs by using the ArcInfo

49 (Figure 3.3). For this area of Ohio the DEMs are based on 10 foot contour intervals,

which equates to DEM Level 2 data production. Information on the generation of the

NED and specifically the Ohio Elevation Dataset is found at

http://seamless.usgs.gov/website/seamless/faq/ned_faq.asp.

Existing USGS Hypsography Converted to DEMs 7.5-min. converted to using the quadrangle digital line TOPOGRID

hypsography graphs (DLG) command in ArcInfo

Figure 3.3: Flow chart of the process used to generate the USGS DEMs for the Ohio Elevation Dataset (http://seamless.usgs.gov/website/seamless/faq/ned_faq.asp).

Files with two different data formats were downloaded from the USGS website:

NED 1 arc second and NED 1/3 arc second. These files use North American Vertical

Datum (NAVD) 1988 for vertical control and the North American Datum (NAD) 1983

for horizontal control, and are provided to the user in geographic projection. The NED 1

arc second files have a pixel size of approximately 30 m by 30 m, and the NED 1/3 arc

second files provide a pixel size of approximately 10 m by 10 m. The 1 arc second files

were imported into ArcGIS and merged into a single file using the Mosaic function in

Spatial Analyst, and were matched with the proper projection for the base maps. The

same processing steps were applied separately to the 1/3 arc second data files.

3.2.2 Computer Methods Used to Generate Digital Elevation Models

Multiple methods were attempted to manufacture DEMs based on the spot

elevation data obtained from the Franklin County Auditors database. Difficulties were

encountered due to the limitations of using a desktop personal computer to perform 50 interpolation methods on such a large number of spot elevations. Multiple attempts at

interpolation using a variety of techniques in both the contouring program Surfer® and

3D Analyst in ArcGIS were not fruitful; repeated contouring attempts using kriging and other methods were run for periods of over ten hours on a desktop PC but could not be completed due to processing limitations of the computer. Several efforts to interpolate over partial areas of the county and then merge the files together also proved to be too taxing for the processing or memory capability of the computer. Ultimately, two methods to interpolate the spot elevation data into a raster DEM were successful; both used a pixel size of 30 m by 30 m, which is a common configuration for readily available

USGS DEMs. The first successful approach used the minimum curvature method in

Surfer®, which is an inexact interpolation method that uses a least square regression model to fit the data, and then creates a set of residual data values which are interpolated using the minimum curvature algorithm. Default values in the program were utilized, with no anisotropy and no tensions for outside data. The second successful interpolation method used ordinary kriging with a spherical semivariogram model in the Raster

Interpolation function in ArcGIS’s 3D Analyst. The spot elevation data were successfully kriged using a more robust dual-processor desktop computer (two 3.72 GHz processors), with 3 gigabytes of RAM. It will be explained later how the DEMs generated in this study were compared to the USGS DEMs in terms of accuracy.

3.3 Obtaining Geologic Data

There is no shortage of geologic data on the surficial materials in Franklin

County. There are thousands of drilling reports (well logs) on file at the ODNR, on which drillers describe the major subsurface zones they find during the drilling of wells. 51 The reports of many subsurface environmental investigations are on file at the Ohio

Environmental Protection Agency and the Ohio Bureau of Underground Storage

Regulations. A multitude of geotechnical investigations have been performed in this

county for both private and public projects. Because much of these data is low quality

(primarily well logs), not tied to any spatial reference, and not housed in a central

repository, most of these data sources were not used in this study. Instead, this project

mostly is based on drill borings with higher-quality geotechnical data, which will be used

to interpret various properties of the subsurface materials. The sources of subsurface data

for this project are primarily state and local governmental agencies, as well as any reports

with high-quality geotechnical data that were available to the author. A total of 945

geologic logs were entered in the initial database. Most all of the borings had surveyed

vertical elevations, but few had x- and y-coordinates that tied them horizontally to a

standard spatial reference. Ultimately locations for 934 borings were identified in State

Plane Coordinates (eastings representing the x-coordinates and northings representing the

y-coordinates) using a method described later in this report.

The main source of data is the Ohio Department of Transportation (ODOT), which has on file many reports that contain geotechnical data used for roadway construction purposes. Some of these reports were obtained by the author through

ODOT’s central repository, but most were made available through ODNR, which had obtained these reports during their surficial-mapping efforts. The primary sources of data used in this project are ODOT structure borings (commonly referred to as bridge borings) that date as far back as the late 1950s; most were drilled during the 1960s and the 1970s, however. These provide details about the unconsolidated materials at regular, but 52 discontinuous intervals, with selected unconsolidated samples being analyzed for geotechnical properties such as standard penetrometer, grain size distribution, and

Atterberg limits (Figure 3.4). These borings often extend down several meters or to bedrock, and are distributed along major transportation routes in Franklin County.

ODOT also has roadway plans that show geotechnical data for soil and rock borings taken at regular intervals along the proposed location of a roadway. Large numbers of these borings have been drilled, but they often only penetrate one to three meters into the earth and contain more limited geotechnical data than the bridge borings. Although data from some of these shallow borings were used in this investigation, the author chose not to explore them further because of the time needed to obtain each report and the limited data they provide.

Figure 3.4: Example of of an ODOT structure boring log used in this study. 53 Additional geotechnical data were obtained from various sources made available

through ODNR and through contacts made with various offices and organizations around

the county. The Solid Waste Authority of Central Ohio made their drilling logs and

technical data available for the current Franklin County Sanitary Landfill, located in the

southwestern corner of the county. The 54 boring logs came from the drilling of

monitoring wells and from geotechnical reports utilized in landfill expansion projects.

Although some of the landfill borings were shallow, many were drilled to a depth of more

than 15 meters and a few were drilled to a depth of more than 60 meters. Another major

source of geologic logs was City of Columbus Engineering reports, taken primarily from

two sewer interceptor projects. The Upper Scioto West Sewer Interceptor Project

extends north-south just west of the Scioto River, and data for 114 borings were obtained

from these reports. The Big Walnut Sewer Interceptor Project is located in the south- central part of Franklin County, and 45 boring logs were obtained from these reports.

Boring logs were also obtained from various environmental and geotechnical investigations that were available in the ODNR files for their surficial studies. Figure 3.5

shows an example of a typical geotechnical log containing information used in this study.

54 Figure 3.5: Example of geotechnical log used in this study. This drilling log was obtained from a subsurface study for a sewer.

3.4 Geologic Database

3.4.1 Computer Database Production

A database of the soil borings was generated in Microsoft Access using a

selection of fields that include most types of geologic information used in geotechnical

borings. The fields include a unique identifier (based on the county, information source, project and boring identifier), the source of information, the project, a description of the

location, surface elevation at the site of the boring, boring depth, depth to bedrock (if

reached), type of bedrock, location coordinates (added later in Ohio State Plane

Coordinate System, South Zone), location method and the USGS 7.5 Minute Quadrangle

map it is within. The grain size class system was also included, as different classification

systems have been used for different projects (e.g. ODOT uses a modification of the

AASHTO system while many of the other geotechnical investigations use the USCS 55 grain-size classification). A boring information form was created to expedite adding data

to individual records (Figure 3.6). English units of measurement are used in the database,

because these are the only units used on the boring logs included in this study. The

elevations of many of the borings were determined using NGVD 1929, so those that were drilled before NAVD 88 was commonly used were converted to this vertical datum using

the U.S. Army Corps of Engineers coordinate conversion program Corpscon6 (available

at http://crunch.tec.army.mil/software/corpscon/corpscon.html). At the end of the

database form is a location for the geotechnical data table file, which is hyperlinked to the

log created in this study for each boring.

56

Figure 3.6: Boring information form created in Microsoft Access for an individual record, showing the fields used in this study. All measurements are in feet.

57 The geologic database was extended into the third dimension by transferring the available boring logs and data into a format that can be adapted to any geologic or geotechnical boring. For each location, a form was created in Microsoft Excel where data from that boring could be entered at particular intervals; the header on that form duplicated some of the identification information found in the boring database. The information includes the geologic description, sample type, sample recovery, standard penetrometer blow counts, the soil classification system and classification, the grain size distribution, percent moisture, Atterberg limits and any additional relevant information regarding this boring (Figure 3.7). Once the file for a boring was completed in Excel, it was converted to a portable document format (.pdf) which reduced the data file size to approximately half of the Excel file size.

Figure 3.7: Boring log form created to incorporate geologic and geotechnical information at depth.

58 3.4.2 Locating the Drill Borings

A total of 934 of the 945 boring locations were identified, either through surveying data or through a sketch or figure showing the boring location on a project plan. Because only 10 percent of the boring locations had surveying data associated with them, the remainder had to be located using another system. The majority of the remaining borings were from ODOT sources, which include a boring location diagram and/or boring profile sheet, as well as information regarding the ODOT station and offset.

Approximately 33 percent of the ODOT boring logs obtained at ODNR or through

ODOT’s central repository had a copy of the plans that include the location of the boring, while 57 percent had either been located on a map contained within a geotechnical report or been positioned on a USGS 7.5 Minute Quadrangle Map by ODNR staff, with no readily available boring location diagram or report profile sheet. The coordinates for the remaining borings were identified from the GIS files that contain the Franklin County roadways, including the road edges, bridge structure outlines and road centerlines. Most of the readily available GIS files represent roads as single lines, so that the additional road structure outlines made it possible to obtain a more precise location. X- and y- coordinates were obtained for each boring from these locations. The ODOT borings contain station and offset information and the remaining geotechnical borings are identified on report maps, so that a boring’s location in the GIS was obtained using the measuring tool in ArcGIS by taking distances from road edges and centerlines (Figure

3.8). A point representing the boring was inserted in the GIS and moved until it closely matched the location on a boring sketch or map, and/or station and offset information specified by ODOT. Once the borings were located in the GIS, the Ohio State Plane 59 Coordinate System, South Zone coordinates were entered into the boring database

(Figure 3.9).

It is believed that this digital locating approach improves the accuracy of the boring location in the GIS over those located using the typical method of positioning the boring location on a paper copy of the USGS quadrangle map. This improved accuracy is likely to be by a minimum of a few meters, but in some cases by tens of meters or more.

60

Figure 3.8: The sketch on the left is from an ODOT Structure Foundation Plan sheet, with the arrows showing the location of the geotechnical borings for this site. The sketch on the right is from the road files obtained through the Franklin County Auditor and imported into GIS, with the red lines showing how the same roads are represented in most readily available GIS downloads (the bridge is from the intersection of Interstate 270 and State Route 23 on the north end of the county.) The boring location was inserted as a point in the GIS, and moved until it matched the plan sheets, maps, or other available location data.

61

Figure 3.9: Locations of the borings in the database.

62 3.5 Comparison of Boring Elevations to Surface Elevations

3.5.1 Methods Used to Compare Surface Elevations and DEMs

It became apparent during this project that many of the surface elevations

identified on the boring reports are significantly different from the corresponding surface

elevation on the DEMs, especially for the DEMs generated in this project. These

differences were calculated by subtracting the starting boring elevation obtained from the

boring report from the elevation of the pixel that contains it in the DEM. This was done

for the DEMs constructed using the minimum curvature and kriging interpolation

methods in this study, and from the elevation of the pixel that contains the boring in the 1

arc second and 1/3 arc second DEMs obtained from the USGS (Figure 3.10). Histograms

were created to show the differences between these elevations, and the average

difference, the standard deviation, and the variance were calculated for each of the four

DEMs. The starting boring elevations used to calculate these differences were corrected

to NAVD 88, the Franklin County aerial survey data is in NGVD 29, and the USGS

DEMs are in NAVD 88. The difference in elevations between the NGVD 29 and NAVD

88 datums is not deemed to be a concern, as the previous conversions of the boring

elevations resulted in an average change of approximately 0.2 m.

63

Figure 3.10: Digital elevation model showing the location of borings, with an expansion of detail showing two boring locations and the pixel representing a particular elevation that contains that boring. The pixels are 30 m by 30 m.

It also became evident that the DEMs constructed from the Franklin County aerial survey were different from the USGS DEMs, which are often used as a surface base map for surficial mapping efforts. The differences between the two DEMS were evaluated by subtracting the DEMs interpolated using kriging from the USGS 1/3 arc second DEM.

This was accomplished by using the Spatial Analyst tools in ArcGIS, with the resulting raster showing the elevation difference between the two DEMs.

One of the most common methods used to evaluate accuracy in a DEM or in a topographic map is to determine the root-mean-square-error (RMSE), which is the standard deviation of difference between the elevations (such as spot elevations or those taken from contour lines) and the corresponding pixel elevation on the DEM (Carlisle,

2005; Aguilar et al, 2006; Ziadat, 2007). The RMSE is defined as (USGS, 1998):

(z − z ) 2 RMSE = ∑ i t n where: zi = interpolated DEM elevation of a test point

zt = true elevation of a test point 64 n = number of test points.

There is an increased value of RMSE with decreased vertical accuracy. For this

evaluation the RMSE is calculated for both the DEM generated using kriging and the

USGS 1/3 arc second DEM, representing zi, and zt is the “true” elevation from five

percent of the over 700,000 spot elevation data points (n=36,953). The locations used

were randomly selected (through a tool in ArcGIS) from the Franklin County data set, and were well distributed as recommended by the USGS Standards for Digital Elevation

Models (1998). The elevations were adjusted in the program Corpscon6 so that the vertical datum would be consistent in this comparison. The RMSE is usually utilized to provide an evaluation of the vertical accuracy of a DEM’s interpolation, but here it is also used to evaluate the accuracy of the USGS DEM as compared to the best surface elevation data available for this area.

3.5.2 Use of Global Positioning Systems to Field Check Surface Elevations

The current surface elevations for twenty of the borings were surveyed using a differential global positioning system (GPS). The purposes of the survey were 1) to assess which DEM is more accurate in its representation of current surface elevation, and

2) to confirm the differences between the starting elevation taken from the boring report and the boring location elevations taken from the DEMs (the two DEMs constructed in this project and the two USGS DEMs at different resolutions). Another reason for the

GPS survey was to provide an additional tool for determining which DEMs evaluated in this study most accurately represent the surface elevations for Franklin County.

Ultimately the goal of these comparisons was to assess the likely reasons for the large differences in surface elevations. The locations for the field survey were primarily 65 selected because of a high-level of disagreement between the boring elevation and the

DEMs. More specifically, the locations were chosen based on several criteria: 1) the pixel of at least one of the DEMs has an elevation difference greater than 3 meters from the surface elevation of the boring, whether the DEM elevation difference varies either positively or negatively (there is an attempt to evaluate both cases), 2) the borings provide geographical distribution across Franklin County, 3) the borings have a diversity of locations (they include bridge locations over highways, streams and railroads), 4) the accessibility of the boring’s location, and 5) the ability to safely obtain a spot elevation from the location (many of the borings are at locations where a highway now exists and offsets from the actual boring locations were sometimes necessary.) The GPS survey/boring locations are described in Table 3.1, and their geographic distribution is shown in Figure 3.11.

66

GPS Survey Boring ID Description of Location Station Relocated Jones Rd bridge over I-70, southeast 1 ODOT-FRA-70-0261-a corner of bridge, near top of south bridge abutment, near bench mark KK11, boring B-1. Relocated Jones Rd bridge over I-70, northeast 2 ODOT-FRA-70-0261-b corner of bridge, near top of north bridge abutment boring B-9. Roberts Rd bridge over I-270, northwest corner of bridge, near top of west bridge abutment, 3 ODOT-FRA-270-0205-a boring B-1, boring location moved approximately 25 feet to the west for safety purposes. Near Griggs Dam, on the ridge between Griggs Reservoir and limestone quarry, uphill from sewer 4 USWIS FRA-BTB-1 cleanout, difficult to locate exact location of boring, between borings ATB-18 & BTB-1. Culvert under Stringtown Road, south & ODOT-FRA-Stringtown Rd- 5 downhill of street, west of Republican Run, Republican Run-a boring B-1. State Route 317 (London-Groveport Rd) bridge over Big Walnut Creek, downhill and next to 6 ODOT-FRA-317-0037-b west bridge abutment, boring B-2, near bench mark K38(reset). State Route 317 (London-Groveport Rd) bridge 7 ODOT-FRA-317-0037-a over Big Walnut Creek, south of the middle of the bridge, in floodplain, boring B-1. County Road 122 (intersection of Alum Creek Dr 8 ODOT-FRA-122-Big Walnut Creek-a and Bixby Rd) bridge over Big Walnut Creek, just west of south bridge abutment, boring T.H.1. Gender Rd bridge over Penn-Central Railroad, ODOT-FRA-Gender Rd-Penn Central 9 southeast corner of bridge, boring B-1. RR-a

Gender Rd bridge over Penn-Central Railroad, ODOT-FRA-Gender Rd-Penn Central 10 northwest corner of bridge, boring B-8. RR-b

Table 3.1: Description of GPS survey locations with location details. (continued)

67 Table 3.1 continued

GPS Survey Boring ID Description of Location Station Williams Rd bridge over I-270, southwest end of bridge, boring B-1, GPS survey moved approx. 11 ODOT-FRA-270-1634-a 50 ft to the west at the end of the bridge due to inaccessible location of boring. Williams Rd bridge over I-270, southeast end of bridge, boring B-7, GPS survey moved 12 ODOT-FRA-270-1634-b approximately 50 ft to the east at the end of the bridge for safety purposes. State Route 62 over Big Walnut Creek, in Gahanna, northwest end of bridge boring B-1, 13 ODOT-FRA-62-2284-a 11.2 ft from bridge deck to base of bridge, 13.6 ft from bridge deck to ground near stream. McCutcheon Rd over I-270, northwest end of bridge, boring B-1, GPS survey moved approx. 14 ODOT-FRA-270-2525-a 35 ft to the west at the end of the bridge due to inaccessible location of boring, 24.9 ft from bridge deck to ground. McCutcheon Rd over I-270, southeast end of bridge, boring B-10, GPS survey moved 15 ODOT-FRA-270-2525-b approximately 65 ft to the east at the end of the bridge for safety purposes, approx. 27 ft from bridge deck to ground. State Route 3 over Alum Creek, northwest corner 16 ODOT-FRA-3-40.780-b of bridge, boring B-2.

Cooper Rd. bridge over I-270, southeast corner of bridge, boring B-3, GPS survey moved 17 ODOT-FRA-270-1922-a approximately 80 ft to the south at the end of the bridge due to inaccessible and unsafe location of boring, 23.9 ft from bridge deck to ground. Cooper Rd. bridge over I-270, northwest corner of bridge, GPS survey moved approximately 80 ft 18 ODOT-FRA-270-1922-b to the north at the end of the bridge due to inaccessible and unsafe location of boring, 22.7 ft from bridge deck to ground. State Route 161 westbound bridge over Blacklick 19 ODOT-FRA-161-2280-a Creek, northwest corner of bridge, boring B-1.

State Route 161 eastbound bridge over Blacklick 20 ODOT-FRA-161-2280-b Creek, northeast corner of bridge, boring B-2, 18.8 ft from bridge deck to ground next to stream.

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Figure 3.11: Boring locations surveyed with GPS.

69 The surface elevations and coordinates of the boring locations were determined during two separate static GPS field survey events. The first event surveyed eight boring locations using a Trimble 4600 LS single-frequency individual receiver GPS survey unit in conjunction with a Trimble TSC1 handheld data logger survey controller. The second survey evaluated twelve boring locations using a Trimble 5800 dual-frequency individual receiver GPS survey unit, along with a Trimble TSC2 handheld controller for data collection (Figure 3.12). The location of each boring for the GPS surveys was determined in the field by using detailed boring location diagrams that were printed from the GIS, and by using distances from known landmarks, primarily the bridge structures

(Figure 3.13). In the first survey event locations were field checked by using uncorrected x- and y-coordinates to see if the selected location was close to the boring coordinates determined using the GIS. The collected static data were post-processed using Trimble

Geomatics Office software and referenced to ODOT’s Continuously Operating Reference

Station (CORS) located in Franklin County (CORS identification COLB). The data collected in the first set of GPS surveys were corrected to CORS to determine surface elevation to approximately the nearest 0.1 m, and the x- and y-coordinates to the nearest

0.5 m. The data collected in the second set of GPS surveys were also corrected to CORS to determine surface elevation to approximately the nearest 0.01 m, and the x- and y- coordinates to the nearest 0.1 m.

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Figure 3.12: Typical setup of global positioning system receiver and controller.

Figure 3.13: Example of GPS survey location (at end of bridge abutment on Jones Road over Interstate 70).

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Franklin County Engineer benchmarks with known elevations are located on

some of the bridges and were used to check the accuracy of the first, and less accurate,

GPS survey. Bench mark KK11, located near GPS survey number 1, has an elevation of

292.45 m msl; from the GPS survey the elevation at the soil boring location is 292.15 m

msl. Because the surface elevation at the boring location was measured (using a tape

measure) as 0.31 m below the bench mark, this produces an error of about 0.01 to 0.02 m.

Bench mark K38 is located near GPS survey 6 with an elevation of 217.66 m msl, and the

elevation of the soil boring location from the GPS survey is 215.53 m msl. The vertical

measurement from the GPS survey location to bench mark K38 was 1.88 m, therefore

measuring down from the bench mark to the soil boring location the elevation is 215.78 m msl or a difference of less than 0.3 m. Errors in the GPS observations from the first survey range from 0.01 m to about 0.3 m, thereby confirming the GPS surveys’ accuracy.

The RMSE is also calculated for the DEMs using the elevation data collected

from the GPS survey as the true elevation of a test point (zt). This will assist in

determining which DEM has the best vertical accuracy.

3.5.3 Examples of Digital Elevation Model Applications

Digital elevation models in a raster format are used for a variety of applications,

and the degree of accuracy in the surface elevation representation may have implications

on those applications. The DEM comparison in this study was intended to evaluate their

use in the mapping of surficial deposits, but DEMs are also utilized in other geologic applications, for construction purposes, and in a variety of environmental models.

Inaccuracies in a DEM could lead to erroneous calculations in an application. This portion of the study will make a comparison between applications using the DEM 72

constructed with ordinary kriging (it had the lowest RMSE values and is therefore

considered the most accurate) and where appropriate, the same application using a USGS

DEM. This will evaluate how the use of a DEM can impact a particular application, and

how the accuracy of that DEM can affect the outcome.

The first DEM application example was performed by placing the top of a few geologic borings at the surface elevations represented by the kriging DEM and the USGS

1 arc second DEM. A comparison of these results to the boring’s proper vertical

placement based on the surveyed elevation will show how particular geologic units can

be represented improperly if merely “hung” from a surface elevation taken from a DEM.

A second example of DEM influence was performed to determine if the 100-year

flood zone, as mapped by the Federal Emergency Management Agency (FEMA),

matched the flood area designation based on the DEM constructed in this study using the

ordinary kriging method. A Flood Insurance Rate Map (FIRM) was obtained from

FEMA for a primarily residential area of Grove City, a suburb of Columbus located in

southwestern Franklin County (Figure 3.14). The map was randomly selected from a

series of FIRMs available for Grove City. It was then confirmed that this area of the

FIRM contained many spot elevations used in the construction of the DEM using kriging,

so it is expected that this DEM is an accurate representation of the current surface of this

area. Only a portion of this FIRM was evaluated, assessing the 100-year flood Special

Flood Hazard Areas (SFHA) surrounding West Water Run, an eastward-flowing tributary

of Grove City Creek.

A digital version of the FIRM was obtained from FEMA, containing ArcGIS files

of the flood zone designations. The 100-year flood stages for the stream (represented on 73

Figure 3.14 by squiggly lines crossing the stream, labeled with the stage elevation in ft above msl) used to designate the SFHA were taken from the paper version of the FIRM, and plotted on the GIS. The flood stages and SFHA designation were visually compared with the elevations represented by contours on the USGS 7.5-minute quadrangle topographic map, and also compared with the surface representation from the USGS 1/3 arc second DEM. This confirmed that current SFHA designations were likely based upon the available USGS information. The same 100-year flood SFHA was then re-mapped using the elevations represented on the kriging DEM. A visual comparison is shown between the SFHA from the FIRM and the SFHA based on the kriging DEM.

A third example to evaluate the DEM impact was to conduct watershed modeling, comparing the results using the DEM generated by kriging in this study with a DEM obtained from the USGS. The model that was used is the Soil and Water Assessment

Tool (SWAT), a watershed model developed to assess the impact of land management practices on surface water quality (Arnold et al., 1998). Current releases of this model have the ability to incorporate DEMs into the delineation of watersheds and into particular runoff characteristics of a basin. This study uses the ArcSWAT graphical user interface to facilitate the modeling sessions. The only variation between two modeling sessions was the use of the different DEMs. This allowed for an equivalent comparison between modeling results.

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Figure 3.14: A portion of the Flood Insurance Rate Map for a primarily residential area of Grove City, Ohio. The shaded area represents the FEMA designation of the 100-year Special Flood Hazard Area (Zone X generally represents areas within or outside of the 500 year flood level, and are not used in this study). The 100-year flood stages as a water elevation above stream level are generally designated perpendicular to channel orientation, and represented by a wiggly line with an elevation in ft above msl. 75

3.6 Modification of Existing Bedrock Topography Maps

The Ohio bedrock topography map was published in 2003, and is available in

both paper and GIS formats from the Ohio Division of Geological Survey (ODNR,

2003a). The GIS digital data include the data points used to generate the topography, the

bedrock topography contours, and the grid (raster image) formatted at the 1:500,000-

scale. The bedrock-topography contour lines were originally drawn by hand at the

1:24,000-scale for most of the 788 quadrangles in the state, using data from water well logs (drilling reports), oil and gas wells, bedrock exposures, and a variety of other sources. The contour lines and data points were entered into the GIS through digitizing

and scanning the paper maps. The raster image was generated by compiling the bedrock-

topography contour lines into a grid surface, with a pixel size of 60 m by 60 m.

The ODNR bedrock topography digital data files were added into this study’s

GIS, and the database was queried for the borings that hit bedrock. Two hundred ninety-

three of the 934 located borings were identified as having penetrated bedrock. The

elevation of bedrock for each of these borings was subtracted from the elevation of its

grid pixel in the ODNR bedrock topography data file using an added ArcGIS extension

(Hawth’s Analysis Tools, available at http://www.spatialecology.com/htools/index.php).

The resulting differences indicated discrepancies between the bedrock elevations within the borings and the bedrock elevations shown on the ODNR digital bedrock topography map. For borings that did not hit bedrock, the bottom elevation of the boring was subtracted from its bedrock topography grid pixel elevation using the same analysis tools to determine if the ODNR bedrock map was inaccurate in its elevations at these boring locations. A total of 39 borings had bottom elevations that were deeper than the top of 76

bedrock on the ODNR bedrock topography map, identifying locations where the bedrock topography was inaccurate.

The bedrock elevation data from the borings used in this study and the borings

with a depth that exceeded the bedrock elevation were plotted along with the ODNR

bedrock topography data points and contours. The digital bedrock topography contours

were then modified to correct for the bedrock elevations encountered in the geologic

borings used in this study, and the contours also were modified for the areas where the

digital bedrock map showed an elevation above the bottom of the borings that did not hit

bedrock (Figure 3.15). The adjusted contours and bedrock elevations were used to create a new bedrock topography map in a DEM for the study area. After trying several methods to transform the contours and point data to a raster format, the DEM generation was completed by using the TopoGrid function in Map Algebra, with a pixel size of 30 m by 30 m to provide for better resolution of the study area. The TopoGrid function uses an interpolation method specifically designed for the creation of hydrologically correct

DEMs, which eliminated the “steps” and flat surfaces that were generated using other geostatistical methods such as kriging. The TopoGrid function is based on the

ANUDEM program, which uses an iterative finite-difference interpolation technique

(Hutchinson 1988, 1989). Although this interpolation method is designed for the field of hydrology, the smoother surfaces generated using this function produced a DEM that is probably more representative of the true surface. A comparison of the bedrock

topography map generated using this method to the ODNR bedrock topography map indicates that this is the same method used by ODNR in the creation of their bedrock topography map. 77

Figure 3.15: Sketch showing the modified bedrock topography contours. The small, green diamond symbols represent the data points used in the original ODNR bedrock topography contours, and the larger, red circle symbols identify the borings used in this study that hit bedrock, along with the bedrock elevation. The thin, red lines are the original ODNR bedrock topography contours, and the thick, black lines are the modified bedrock topography contours. All elevations are in feet above mean sea level.

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3.6.1 Analysis of Bedrock Drainage Patterns

The bedrock topography was analyzed using a series of functions in the Spatial

Analyst tools. These ArcGIS tools typically are used in surface hydrology analysis to

evaluate stream networks by establishing watershed basins and drainage divides based on surface elevation, but provided an easy method to evaluate the bedrock topography surface for Franklin County. This information can provide some insight into ancient drainage patterns that eroded the bedrock surface. The bedrock topography raster was first evaluated using the Flow Direction tool, which determines the steepest direction from each pixel to its downslope neighbor. Then any sinks (depressions) in the bedrock surface were identified in a separate raster using the Sink tool, which outlines low points where the channels are disconnected but are likely within the same area of internal drainage. The Flow Direction raster was then evaluated using the Flow Accumulation tool, which sums the number of upgradient pixels that drain to that particular pixel, resulting in a raster showing areas of flow accumulation across a surface. This network of drainage was then converted into a line vector shapefile by evaluating the major flow accumulation areas and locations of sinks on the surface. The final map shows the hypothetical drainage of the bedrock topography if the unconsolidated deposits did not exist.

3.6.2 Analysis of Bedrock Topography Map

To determine the relation between bedrock topography and other variables, the slopes of the corrected bedrock topography map were determined by creating a slope map using the 3D Analyst Extension in ArcGIS. This function calculates the maximum change of elevation between each pixel and the surrounding eight pixels, with the output 79

value selected to be in degrees. This function produces a continuous raster showing local

differences in slope.

To determine if there is a relation between bedrock slope and type of bedrock, the

bedrock slope raster was clipped for each polygon of bedrock. The raster statistics were

identified in the Layer Properties, including the slope minimum, maximum, mean and

standard deviation.

3.6.3 Examination of Bedrock Topography Effects on Glacial Deposition

Bedrock topography and slope orientation have an effect on glacial

erosion/deposition processes, and resulting deposit thicknesses (Boulton, 1982; Coates,

1982; Bennett and Glasser, 1996; Evans et al., 2006). Bedrock slope orientation was

compared to the thickness of the unconsolidated deposits to determine if a relation exists

for this area. This was analyzed for the western portion of the county, which has a

relatively uniform bedrock lithology (primarily Silurian and Devonian carbonates), fewer

deep bedrock valleys, and more consistency in the thickness of the glacial tills. The GIS

was utilized to create a surficial thickness map by subtracting the bedrock topography

map from the surface topography map generated using kriging. A slope aspect map was

generated from the bedrock topography map in ArcGIS using the Spatial Analyst tools,

where the resulting values of the output raster are the compass direction of the slope orientation. Three separate, but overlapping, areas in the western region of the county were analyzed: one area that includes much of this region, incorporating areas of significant surficial thickness (average thickness exceeding 35 m); a second area that minimizes data in any deep bedrock valleys (approximate average surficial thickness of

28 m), and a third smaller area in the northwest corner of the county where there are 80

thinner unconsolidated materials (approximate average surficial thickness of 8 m). A set

of randomly sampled points was generated for each of the three areas. A query was performed for the randomly sampled points to obtain the aspect value for the bedrock in degrees and for the surficial thickness at that location. The randomly sampled points

with slopes facing north (a compass direction of 315 to 45 degrees) and the randomly

sampled points on south-facing slopes (a compass direction of 135 to 225 degrees) were

pulled from the database. The average thickness of the surficial materials was extracted

from the surficial thickness map and compared for the north- versus south-facing slopes.

This was done for each of the three areas with different average surficial thicknesses.

3.7 Analysis of Surficial Deposits and Geotechnical Properties

The physical and geotechnical properties of glacial till depend on a variety of

factors, but among the most important are the sediment source and particle size

(Dreimanis, 1976; Milligan, 1976). A till can contain components of the up-glacier

substrata, the intra-glacial geologic materials, and the subglacial bedrock (Menzies and

Shilts, 2002). In some situations the local bedrock can greatly impact the texture and

mineralogy of a till, especially near bedrock highs (Szabo and Angle, 1983). The

subglacial bedrock can also affect several till depositional processes (Evans et al., 2006).

The textural and engineering properties of different types of glacial deposits in Ohio have

been evaluated previously (Steiger et al., 1971; Sun, 1975), but the use of GIS in this

study facilitates a more extensive comparison of typical geotechnical data to the

diamictons in Franklin County. This study also attempts to determine whether

geotechnical properties vary due to the differences in bedrock lithology. This project

considers standard penetrometer data, Atterberg limits and grain sizes in the glacial 81

deposits found in central Ohio, and evaluates the usefulness of this geotechnical data in surficial deposit mapping efforts.

The assorted sediments were deposited in a variety of depositional environments, and this study concentrates on those materials interpreted here to be glacial tills. An evaluation of the unconsolidated materials across the whole county is limited for several reasons: 1) the distribution of borings is not uniform, 2) not all borings in the database contain engineering data, 3) the thicknesses of the unconsolidated materials found in the borings range from less than one meter to over sixty meters, and 4) many of the borings do not extend through the full depth of the unconsolidated deposits (approximately 30 percent of the borings are drilled to or past bedrock).

This analysis focuses on sediments in borings that form two transects across the county (Figure 3.16), and considers tills found in an area of carbonate bedrock separately from those tills found on an area of clastic bedrock. One transect extends along the northern end of the county, containing ODOT borings drilled for various structure projects along Interstate 270 and State Route 161. This transect goes across various types of bedrock, covering an area with a change in bedrock elevation of over 100 meters, and a difference in surface elevation of 80 meters. The second transect crosses the first, but trends north to south in the northwest part of the county; it contains ODOT structure borings drilled along Interstate 270. This transect covers a more uniform bedrock lithology (mostly Devonian carbonates), less bedrock topography (difference in elevation of 45 meters, but mostly due to one major bedrock valley in the area) and generally less surface topography (difference in elevation from the highest to lowest boring of 18 m).

This analysis includes a total of 106 borings with an average boring depth (within the 82

surficial deposits) of 13 m. Most of the data is taken from borings with a minimum total diamicton thickness of 8 m. Some borings were drilled to or very near to bedrock (31

borings), while others, according to ODNR data, penetrated less than one-fifth of the total

thickness of the surficial materials. All of the samples that were analyzed from this group

of borings were collected using a split-spoon sampler, a device commonly utilized in

geotechnical investigations.

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Figure 3.16: Location and depth of the borings used to evaluate the geotechnical properties of the diamictons. The base map is the bedrock topography.

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The engineering data evaluated for this study are mostly from the diamictons, recognized by their poorly sorted texture and identified by a silt and clay matrix that contains sand and gravel components. In this study the diamictons are defined as those that contain 40 percent or more silt and clay, but also have at least 20 percent sand and gravel to avoid those samples that may have been deposited in a lacustrine environment.

Because sampling is sometimes problematic in coarse-grained materials, some of the information includes data taken from the boring logs, such as the location and thickness of gravelly zones noted by the driller.

The first parameter that was evaluated is commonly referred to as the Standard

Penetration Test (SPT). This method of sampling originated over 100 years ago and for several decades has been standardized as ASTM method D1586, a technique most recently revised in 1999. This method uses a 2-inch outside-diameter split spoon sampler

(usually 18 to 24 inches in length) that is driven into the unconsolidated material by dropping a 140 pound weight (referred to as a hammer) 30 inches onto the drill, thus advancing the sampler by multiple drops (or “blows”) of the hammer. The number of blows that it takes to drive the sampler every six inches is recorded. In more recent years the blow count for the first six inches is discarded, and the blow counts for the next two six-inch intervals are combined to form the SPT blow count value, referred to as the “N” value. The N value is then equated to a particular soil density or hardness condition

(typically used for any material that primarily consists of clay, silt or sand) and is often used by engineers to calculate the bearing capacity of that soil. Most of the borings along these transects were obtained prior to the mid-1970s, when only the first two sets of blow counts were recorded and used. For this reason the N value data for most of the borings 85

consist of the first and second six inch intervals in those conditions where the split spoon

sampler was only driven one foot.

A comparison was made by plotting the N value and percentage of gravel on a

scatterplot, with the purpose of determining if there is a correlation between these two

parameters. Additional plots were made showing a composite profile of N values and

percent gravel with respect to depth, to determine if there is a consistent trend in these

values in the subsurface.

Atterberg limits are performed on the portion of the soil sample that passes

through the 425 µm (No. 40) sieve, which corresponds to a grain-size classification of fine sand and smaller in the Unified Soil Classification System (USCS). The limits are used to establish the moisture content at which the material is in a liquid or plastic state.

These values are usually determined by ODOT when the sample is at least 20 percent silt and/or clay, thus most of the diamictons have had the liquid and plastic limits analyzed.

The Atterberg limits for samples from the two transects were compared to determine if there is a difference between the liquid limit and the plasticity index for those glacial tills found on the carbonate bedrock and those on clastic bedrock. This comparison mostly shows whether there is a significant difference in the proportion or types of clays found in the tills from one bedrock area versus the other. A composite profile of the liquid limits and plasticity indexes with respect to depth was made for the samples found in each bedrock region.

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The texture of the diamictons in the two different bedrock areas was compared primarily using ternary plots of the gravel/sand/silt and clay and the sand/silt/clay fractions. These plots were generated to include grain size data from the diamictons as well as other sediment types, including those that appear to be lacustrine deposits.

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CHAPTER 4

RESULTS

4.1 Introduction

Modern geologic maps typically are constructed using computers, and this study outlines a methodology for proceeding in the digital mapping of unconsolidated deposits.

This study also investigates the accuracy of digital elevation models (DEM), showing that they sometimes represent the surface inaccurately. These errors may affect DEM use as a base for surficial mapping, as well as affecting their value for other purposes.

Readily available DEMs, as well as those constructed in this study, contain some inherent inaccuracies and should be evaluated before being used. This study shows that DEM inaccuracies in some areas of Franklin County can stem from changes in the surface due to human activity, and that DEMs often misrepresent the surface near streams.

The type of bedrock and bedrock topography can be important to the formation of surficial deposits. This study modified the existing digital bedrock topography map for

Franklin County, and performed an assessment of the effects of the bedrock surface on the development of the unconsolidated materials. An evaluation was performed of the available geotechnical data for the glacial tills, assessing whether differences exist for the deposits found above areas of different bedrock. 88

4.2 Description of Base Geographic Information System and Database for Study Area

4.2.1 Establishing a Digital Base Map

Establishing an accurate base map is understandably important for cartographic

and spatial information purposes, and this study shows that it is important in the precise

mapping of surficial deposits as well as for various other applications. Establishing an

accurate base map for a heavily populated county, such as Franklin County, is not

problematic because of the digital resources that are available for property and

engineering uses. Counties and municipalities with fewer resources often do not have the

benefit of readily available GIS or CADD systems, but as organizations move away from

paper and allocate more resources towards digital applications these systems will become

more common. Having these maps in digital forms improves the accuracy and ability to

modify future mapping of unconsolidated deposits.

The borings are located much more accurately in this study by establishing a detailed base map that allows the user to measure away from structures such as highways

and bridges. The ODNR surficial maps that are being generated at the 1:100,000-scale

may not benefit from this improved accuracy, but if these maps are converted into three-

dimensional digital formats on a county-by-county or larger scale, there is some

advantage to establishing the base map in a digital format rather than plotting borings on

paper topographic maps as is currently the practice.

4.2.2 Digital Database and Boring Log Format

The creation of the basic geologic database for the borings in digital format

provides a flexible platform that can be utilized for any geologic log, and can be applied to either a large or small level of data. Microsoft Access database provides a cost- 89

effective tool that is both commonly available and easily imported into a GIS. Additional fields can be added for other applications, and the hyperlink to the boring log can be in any digital format (e.g. it may be more time- and cost-effective to have most existing geologic logs scanned into a digital format rather than have the data reentered into a new form.)

The use of Microsoft Excel also provides a convenient platform for generating geologic logs. There are many other programs available to perform this task, but since the majority of desktop computers have Excel the logs can be formatted and entered at most computer stations, and the files can be opened by just about anyone if converted to

.pdf format. As more data is made available via the Internet, the user will be able to easily upload these forms. Digital data space is not an issue, as the total of 945 borings generated less than 65 megabytes of data in the Microsoft Excel format and less than 15 megabytes of data in pdf format. Entering the geologic data was among the most time consuming tasks, but that task can be sped up by requiring that users within an organization enter information into the geologic database as the information is obtained.

4.2.3 Geologic Data Sources

This author only explored data sources that were considered to have good quality geotechnical data and were readily accessible. Much of the work visiting the ODOT repository and searching through boxes for geotechnical logs was performed by ODNR staff and interns. In the future, similar data acquisition will be expedited once all of the

ODOT plans and drawings are converted to digital form. Some visits by this author to government offices resulted in no or only a few geologic logs, while other contacts resulted in multiple logs. ODNR drilling reports were not used because of their 90

subjective nature, but in more rural locations these may be the only data the geologist has available for subsurface mapping. Ohio EPA and Ohio BUSTR files contain a wealth of geologic data in the form of soil sample logs and drilling logs for monitoring wells, but obtaining the reports and locating the borings would be a very time consuming task, so the only ones used in this project were those available in the files at ODNR.

4.3 Surface Digital Elevation Models

The surface DEMs generated in this study provide a base map with the most current elevation data available to the author. An examination of the DEMs shows significant detail of the surface topography, to the level that human-generated features such as major roads and the Franklin County Sanitary Landfill are easily observable

(Figure 4.1). The DEMs generated in this study using ordinary kriging and minimum curvature are at a resolution similar to the DEMs most commonly available to the public by the USGS, allowing for comparisons to be made. The DEMs generated in this study were also deemed manageable in terms of data size, and accurate due to the high concentration of elevation data used to construct the DEMs (approximately 2.5 spot elevations per pixel.) Some errors are likely because spot elevation data from the

Franklin County aerial survey are not distributed regularly and some small areas (some exceeding 100 m across in size) do not contain any spot elevations. Other areas not sampled include most bodies of water. Reservoirs such as Julian Griggs (found along the

Scioto River) and Hoover (partially located in the northeastern corner of the county) show up as relatively flat areas with little topography, as the surfaces created over those areas are based on surrounding data.

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8

Figure 4.1: Surface topography as generated using the minimum curvature method, utilizing the Franklin County spot elevation data. Vertical exaggeration (15x) and shading enhance the visualization of natural and human-made features. Scale is in feet (eastings and northings from the Ohio State Plane system).

4.4 Evaluation of Surface Elevations

This portion of the study compares the surface elevations found on the boring reports, the elevations represented on the DEMs constructed in this study, the elevations represented by USGS DEMs, and ground elevations obtained from a field survey using a high-resolution GPS. The differences in surface elevations will help to determine the accuracy of the DEMs constructed using ordinary kriging and the minimum curvature methods, and the accuracy of the 1/3 arc second and the 1 arc second DEMs, obtained from the USGS. The DEMs are then utilized in some practical applications, showing how their surface representation differences can affect the results of those applications.

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4.4.1 Comparison of Boring Elevations to Digital Elevation Models

The mapping of subsurface geology often relies on having a particular surface elevation, from which depths within a boring can be subtracted. This study shows that the surface elevation obtained from a DEM may differ significantly from the surface elevation determined directly at the time of drilling that boring. If a boring’s subsurface geologic data is “hung” from the surface of a map or DEM that is not representative of the boring’s true starting elevation, then the subsurface mapping will be inaccurate. This may be especially true in the mapping of surficial deposits. Some of the unconsolidated lithologies in central Ohio are only one or a few meters thick; if they are mapped using borings whose surface elevations are wrong by several meters, that particular lithology may be placed at the wrong elevation.

The current surface elevation (either the true elevation or those taken from DEMs or maps) could be different from the surface elevation recorded at the time of drilling for several reasons. One possible reason is inaccurate survey elevations, either those elevations surveyed at the time of drilling or the spot elevations used to generate maps

such as DEMs. This is an unlikely source of error, however, because the surveying done

at the time of drilling and the aerial surveys that produce spot elevations follow standards

to minimize errors. A second possible reason for the differences in elevations is utilizing

a DEM to obtain the surface elevation of a point. An inherent problem is that a DEM pixel represents a single elevation across a three-dimensional surface. In areas of greater slopes that pixel is less likely to accurately represent the surface at any single point in that area. This effect is a likely source of the differences in elevations found in this study, as will be demonstrated. A third reason the map or DEM may not represent the original 93

boring elevation is that the surface may have changed over time; this could be due to natural changes or anthropogenic modifications. This study shows that surface modification is another likely source of the differences between a surface boring elevation and the elevation of the pixel in the DEM that contains that boring.

There are significant differences between the original boring elevations and those elevations taken from the pixels of the DEMs that contain the borings for all four DEMs considered in this study: the DEMs generated in this study using ordinary kriging and minimum curvature, as well as the 1 and 1/3 arc second USGS DEMs. Differences between the original boring elevation and that derived from the DEM constructed using kriging show a broad distribution of values, but illustrate that the majority of the starting boring elevations are below the elevation of the DEM pixel containing that boring

(Figure 4.2). A similar pattern is identified when boring elevations are compared to elevations from the DEM constructed using minimum curvature (Figure 4.3). The histograms of elevation differences relative to the USGS DEMs show a similar range of values, but both histograms have distributions generally symmetric about zero and have narrower distributions when compared to the histograms for DEMs constructed in this study (Figures 4.4 and 4.5). The average difference in elevation relative to the kriging

DEM is ±2.33 m, and the average difference relative to the minimum curvature DEM is

±2.44 m (Table 4.1). The average difference relative to the USGS 1 arc second DEM is

±1.45 m, and the average difference relative to the USGS 1/3 arc second DEM is ±1.42 m. Over one-half of the boring elevations have a difference of less than 1 m when compared to the USGS DEMs, and approximately 12 percent have elevation differences greater than 3 m. About 40 percent of the boring elevations have a difference of less than 94

1 m when compared to the DEMs constructed in this study, and approximately 30 percent

of the borings have an elevation difference of 3 m or greater. The standard deviations

and variances for the elevation differences relative to the DEMs constructed in this study

are higher than those relative to the USGS DEMs (Table 4.1).

Elevation differences relative to the kriging and minimum curvature DEMs have similar statistics; differences relative to the higher and lower resolution USGS DEMs have similar statistics, and both USGS DEMs produce significantly lower differences than the differences relative to the kriging and minimum curvatures DEMs. These results may have implications for efforts to establish an accurate base map for large-scale geologic mapping because the detailed delineation of the upper boundaries of deposits could greatly vary. The differences in the elevation of the top of boring relative to the elevation from the base DEM are significant in the mapping of surficial deposits in central Ohio. Although the average thickness of unconsolidated material is approximately 35 m in Franklin County (as calculated in the GIS constructed in this study), an error of ±1.4 m or greater is large relative to an unconsolidated thickness of 3 m or less, which can be found in many areas. These locations with thin surficial deposits are primarily in the northern half of the county, and in locations of higher bedrock topography.

A closer inspection of many of the borings and the pixels that contain those borings, constructed using the spot elevation data, demonstrates that what shows up as mounds on the DEMs are usually locations of bridge overpasses (Figure 4.6). This is the likely reason why the elevation differences relative to the DEMs constructed in this study tend to be negative. These areas of higher elevations, which represent the mounding of 95

materials at bridge overpasses, are absent on the USGS DEMs, indicating that the source data for the USGS DEMs was collected before much of the highway construction activity in central Ohio. This demonstrates that if the starting elevation of a geologic boring is not known and it was drilled prior to significant land modification in an area, it is probably preferable to “hang” the borings from the currently available USGS DEMs.

This suggestion may change if the USGS revises its DEMs to reflect the current surface elevations for an area.

Histogram of Difference in Elevation Boring minus DEM (Franklin Co. Data - Kriging)

250

216

200

159

150

Frequency 100 92 94

66 60 57

50 38 30 22 24 16 17 13 13 0004 2 4 4 2 00001 00 0 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Elevation Difference (meters)

Figure 4.2: Histogram showing the difference in elevation of the top of boring and the pixel containing it for the DEM generated in this study using kriging.

96

Histogram of Difference in Elevation Boring minus DEM (Franklin Co. Data - Minimum Curvature)

250

212

200

165

150

115

Frequency 100

70 74

44 50 39 35 33 26 27 25 11 15 6 9 10 6 0 3 1 4 2 0 1 0001 0 0 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Elevation Difference (meters)

Figure 4.3: Histogram showing the difference in elevation of the top of boring and the pixel containing it for the DEM generated in this study using minimum curvature.

Histogram of Difference in Elevation Boring minus DEM (USGS 1 arc sec resolution, 30m)

250 238 232

200

150 138 126

Frequency 100

43 50 37 22 26 24 16 5 9 9 00000002 4 1 00002 00 0 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Elevation Difference (meters)

Figure 4.4: Histogram showing the difference in elevation of the top of boring and the pixel containing it for the USGS 1 arc second DEM. 97

Histogram of Difference in Elevation Boring minus DEM (USGS 1/3 arc sec resolution, 10m)

249 250 240

200

150

122 115

Frequency 100

48 50 45 28 15 17 18 17 6 5 00000000 4 3 00002 00 0 -15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Elevation Difference (meters)

Figure 4.5: Histogram showing the difference in elevation of the top of boring and the pixel containing it for the USGS 1/3 arc second DEM.

Ordinary Minimum USGS DEM USGS DEM Kriging DEM Curvature DEM 1 arc second 1/3 arc second Mean -1.28 -1.37 0.24 0.18 Mean of the 2.33 2.44 1.45 1.42 Absolute Value Standard 3.00 3.24 2.09 2.06 Deviation Variance 8.97 10.48 4.35 4.26

Table 4.1: Statistical values (in meters) for the difference between boring elevation and DEM elevation at the boring (n=934).

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Figure 4.6: Close up of the DEM generated using kriging, with boring locations along the west side of Interstate 270. Higher elevations are shown by the darker spots around the borings, representing the mounds for highway overpasses.

4.4.2 Comparison of Digital Elevation Models

The accuracy of four different DEMs was evaluated primarily for their use in the stack mapping of surficial deposits, but DEMs are used for many other purposes. For examples, DEMs commonly are used to interpret geomorphology and examine terrain

(Brown et al., 1998). Digital elevation models are often used in surface hydrology applications, such as flood routing and contaminant transport models. Digital elevation models also are used in various soils applications, such as soil series mapping and erosion modeling. Land development and mining utilize DEMs to calculate cut and fill volumes, and to determine final grading. An understanding of the accuracy of readily available

99

DEMs, such as those produced by the USGS and those constructed from elevation data,

will improve their utilization.

The differences in elevation of the DEM generated in this study using kriging and

the 1/3 arc second USGS DEM are shown in Figure 4.7. The kriging DEM was chosen

because it was deemed more accurate due to a lower RMSE value than that of the

minimum curvature DEM, and the 1/3 arc second USGS DEM was chosen rather than the

1 arc second USGS DEM because of the higher resolution. This map shows the elevation

differences across the raster, including minor values in the lighter shading. Differences

range from -44.6 to 41.9 m. Figure 4.8 shows only those pixels with an elevation difference less than -3 or greater than 3 m. The average elevation of the kriging DEM is

0.32 m higher than the average elevation of the 1/3 arc second USGS DEM, with a

standard deviation of 1.77 m. A close-up of a portion of the northern part of the county is

shown in Figure 4.9 to show some of the differences in elevation relative to roads and

waterways.

Many areas with large elevation differences are found at two types of locations:

those where humans have altered the ground surface, and those near bodies of water.

Among the more apparent features are those along major transportation routes, with certain overpasses and highways evident on the maps (Figure 4.9). This again shows that the USGS DEM does not incorporate all of the surface changes that occurred due to highway construction activity in central Ohio. Large and small streams also are areas subject to errors in one DEM or the other (Figure 4.9). Positive values are more typical along streams, suggesting some consistency to the cause of the differences, but it is not determined here if the kriging DEM or the USGS DEM better represents areas along 100

waterways. Reservoirs are also areas that show large differences in elevation from one

DEM to the other. Hoover Reservoir, in the northeastern part of the county, and Julian

Griggs Reservoir, along the northern part of the Scioto River, have among the largest positive values. The current elevation as calculated by the kriging method shows these reservoirs as relatively flat surfaces, created from spot elevation data on the shores of the reservoir. The USGS DEM still shows these areas to be valleys; it is apparent that this

DEM has not been changed for this area since the Scioto River and Big Walnut Creek were dammed (in 1925 and 1955, respectively) to create the reservoirs, with the elevations representing the valleys beneath the water surface. Active and inactive limestone quarries and gravel pits within the county are also apparent on Figure 4.7.

When this map is compared to other available maps showing quarries and pits, many of the large negative and positive values on Figure 4.7 closely align with these features.

The spot elevation data used to generate the DEMs in this study often show deep depressions where rock or unconsolidated materials have been mined and higher elevations where rock or aggregate has been piled up. The changes in the land surface at quarries and pits are not represented on the USGS DEM.

Some areas with elevation differences shown on the maps occur where no spot elevation data is available. Some of these areas, which are tens to even a few hundreds of meters across, produce zones in the kriging DEM that are probably not properly represented due to a lack of elevation data. A closer inspection shows that some of these areas that lack spot elevation data appear as small ravines and gullies on the USGS DEM, and are often found in the vicinity of streams where there is greater topography. If these

101

locations were not properly reconciled it would likely cause systematic errors in the final

DEMs constructed for the county.

An additional way to evaluate the accuracy of the DEMs is by calculating the

RMSE of the DEM-derived elevations compared to spot elevations. This comparison

used the kriging DEM because its greater accuracy and used the 1/3 arc second USGS

DEM because of the higher resolution. The RMSE evaluation utilized five percent of the

spot elevation data obtained from the county. The RMSE for the kriging DEM is 0.14 m,

and 1.64 m for the USGS 1/3 arc second DEM. The lower RMSE value for the kriging

DEM is not surprising considering it was generated using spot elevation data. The

RMSE value for the USGS 1/3 arc second DEM almost aligns with what the USGS

Standards for Digital Elevation Models (1998) considers to be a Level 2 DEM classification. The standards state that an RMSE of one-half the contour interval is the maximum permitted for Level 2 DEMs. The contour interval for the majority of the

USGS 7.5-minute quadrangle maps representing Franklin County is 10 ft (3 m), making the RMSE of 1.64 m slightly greater than what is permitted by the USGS standards for

Level 2 classification.

102

Figure 4.7: Difference in elevations from the DEM generated in this study using kriging and the 1/3 arc second USGS DEM.

103

Figure 4.8: Areas with a difference in elevation greater than 3 m between the DEM generated in this study using kriging and the 1/3 arc second USGS DEM.

104

Figure 4.9: A portion of Franklin County showing the difference in elevation between the DEM generated in this study using kriging and the 1/3 arc second USGS DEM, emphasizing those areas with a difference in elevation of greater than 3 meters. This area is on the north end of Franklin County, where Interstate 270 and State Route 23 intersect. Some cut and fill activities are apparent around the I-270 and S.R. 315 interchange, likely accounting for the lack of modifications to the USGS DEMs after development. Many positive values are found along small streams. Many of the positive and negative values found north of I-270 are locations with few spot elevation data points, likely showing areas of errors in the kriging DEM constructed in this study.

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4.4.3 Results of Global Positioning System Surveys to Investigate the Accuracy of

Boring Elevations and Digital Elevation Models

There were several purposes for performing the GPS survey: 1) to determine the reason(s) for the differences in the surface elevation of a DEM compared to the starting elevation of the borings, 2) to evaluate which DEM best represents the starting elevation for the borings used in this study, and 3) to determine which type of DEM (USGS or those constructed in this study) was more accurate in representing the current surface elevation. The data here assist in explaining the likely causes of differences between the starting boring elevation and the elevations derived from DEMs, showing that there are often consistent differences depending on whether the boring is located near a highway or railroad bridge overpass, or if the boring is located near a stream. Although the USGS

DEMs generally provide a better starting elevation for the borings, this evaluation also shows that the DEMs constructed in this study are generally a more accurate representation of the current surface than the USGS DEMs. One method used to compare the four DEMs is calculating the RMSE for each relative to the elevations determined in the GPS survey. This calculation uses the GPS survey elevation as the

“true” elevation, and compares it to the elevation of the DEM pixel that contains the GPS survey point. Ultimately these comparisons will assist those mapping surficial deposits by identifying likely sources of discrepancies between the boring surface elevations and a

DEM’s surface elevation representation.

4.4.3.1 Accuracy of GPS Survey Locations

The accuracy of the GPS survey locations was evaluated by determining the horizontal distance from the boring on the GIS and the GPS survey for that boring. This 106

was evaluated because of difficulties on setting up and taking a GPS measurement at

some of the boring locations. The boring locations in the field were mostly determined

by identifying the boring location on the GIS, printing the diagram of the location and nearby features, and measuring off of physical objects, such as the edge of a bridge, to identify the survey location. At eight of the 20 GPS survey locations, it was not feasible to set up the GPS equipment at the spot where the boring was drilled because of traffic hazards, steep slopes, and physical obstructions. In these cases the survey was completed by offsetting from the boring location and either: 1) surveying a location at the same elevation as the current surface of the boring location, or 2) surveying at the bridge abutment and physically measuring with a tape measure horizontally and then vertically to the boring location.

Horizontal distances between the boring x- and y-coordinates taken from the GIS and the coordinates obtained from the GPS survey are shown in Table 4.2. The GPS survey stations were generally accurate when accessibility to the reported boring location was not a concern, and provided the current surface elevation at or very close to the

original boring locations. The twelve borings that could be surveyed directly were offset

by 6 m or less from their GIS-generated coordinates, and on average were 2.8 m away

from the boring coordinates obtained from the GIS. The differences between the GPS

survey location and the boring location for these twelve stations are considered minor for

the purposes here, which is specifically to evaluate the current surface elevation at the

location of the boring. The GPS survey data for these twelve borings are considered

adequate for the purpose of evaluating the current surface elevation because the

107

differences in surface elevation over these small lateral distances were generally minor at the survey sites.

The eight borings that were measured using offsets were moved horizontally by

an average of 20.1 m (Table 4.2). Although this value appears large, the final GPS

survey data taken from the offset survey locations are still useful. This is because

measures were taken in the field to obtain an accurate surface elevation at the original

location of the boring by physically measuring horizontally and/or vertically from the

GPS survey location. The GPS survey was performed with relatively high vertical and

horizontal accuracy, and although elevation control was lost in some cases where survey

points were moved, an error in the elevation of 0.1 or even 0.5 m is relatively small

compared to the large elevation differences of several meters observed between the

surface elevation recorded on the boring logs and the surface elevation represented on the

DEMs.

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x, y coordinates taken x, y coordinates from GPS from GIS (ft) GPS survey (ft) Difference Survey Boring ID between Station Easting Northing Easting Northing GIS and GPS (m)

1 ODOT-FRA-70-0261-a 1772315.6 721627.2 1772320.9 721609.4 5.7

2 ODOT-FRA-70-0261-b 1772246.1 721909.3 1772242.7 721915.1 2.0

3 ODOT-FRA-270-0205-a 1795192.6 729988.9 1795166.8 729992.0 7.9

4 USWIS FRA-BTB-1 1801760.1 734652.3 1801747.5 734557.2 29.3

ODOT-FRA-Stringtown Rd- 5 1811125.1 684673.7 1811127.4 684674.0 0.7 Republican Run a

6 ODOT-FRA-317-0037-b 1829992.5 667967.3 1829983.7 667967.7 2.7

7 ODOT-FRA-317-0037-a 1830139.5 667890.4 1830136.7 667888.9 0.9

ODOT-FRA-122-Big Walnut 8 1845348.6 676277.5 1845356.2 676295.7 6.0 Creek-a ODOT-FRA-Gender Rd-Penn 9 1877726.7 697881.7 1877719.8 697872.6 3.5 Central RR-a ODOT-FRA-Gender Rd-Penn 10 1877670.1 698031.5 1877674.9 698037.2 2.3 Central RR-b

11 ODOT-FRA-270-1634-a 1852860.4 688115.6 1852810.7 688140.4 16.9

12 ODOT-FRA-270-1634-b 1853133.5 688116.2 1853185.0 688110.2 15.8

13 ODOT-FRA-62-2284-a 1861936.6 735585.5 1861935.6 735592.7 2.2

14 ODOT-FRA-270-2525-a 1855498.0 740799.4 1855433.9 740803.2 19.6

15 ODOT-FRA-270-2525-b 1855651.1 740746.1 1855716.7 740753.1 20.1

16 ODOT-FRA-3-40.780-b 1849396.0 762148.2 1849401.9 762155.7 2.9

17 ODOT-FRA-270-1922-a 1845530.6 766376.9 1845566.7 766297.3 26.6

18 ODOT-FRA-270-1922-b 1845391.9 766585.0 1845359.9 766658.9 24.6

19 ODOT-FRA-161-2280-a 1888820.3 757909.0 1888812.4 757912.1 2.6

20 ODOT-FRA-161-2280-b 1888945.1 757808.6 1888942.2 757813.5 1.7

Table 4.2: Horizontal distance between each boring location on the GIS and the GPS survey location for that boring.

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4.4.3.2 Comparison of Elevations from the GPS Survey and Boring Records

The differences between the surface elevations at the boring locations determined

by the GPS survey and the original surface elevations of the borings are shown in Table

4.3. Fourteen of the GPS survey elevations were higher than the original boring surface

elevations, being on average 6.1 m higher. The remaining six GPS survey elevations

were on average 4.8 m lower than the original boring surface elevations. The differences

between these elevations are interpreted to be from changes to the land surface either due

to construction or due to the proximity of a boring to a stream. The reason for the

difference observed at one location could not be ascertained.

Eleven of the 20 borings have a current surface elevation, measured during the

GPS survey, that is different from the original boring surface elevation due to changes in

the ground surface during bridge or roadway construction. At seven of these 11

locations, the GPS survey elevation is higher than the original elevation of the boring

location (GPS survey stations 1, 2, 3, 9, 10, 11, and 12); this change is interpreted to be

caused by overpasses constructed over the boring location by the mounding of earth.

These seven locations have an average difference of 8.2 m, but the elevation difference is

in excess of 10 m at GPS survey station 11. At four of the 11 borings where elevation

differences are attributed to construction (GPS survey stations 14, 15, 17 and 18), GPS survey elevations are lower than the original surveyed elevation of the boring, with an

average value of -6.1 m. The source of these elevation differences appears to be that the

highway beneath a bridge overpass was excavated into the ground. This demonstrates

that the original boring elevation was above the current surface elevation for these

locations. 110

Eight GPS survey stations (5, 6, 7, 8, 13, 16, 19 and 20) are adjacent to streams,

with some GPS survey surface elevations higher than the boring surface elevations (five

of the stations) and some lower than the boring surface elevations (three of the stations)

(Table 4.3). The average absolute value of the elevation difference is ±3.4 m for these

eight stations. There may be multiple reasons for the differences between the GPS

survey elevations and the original boring elevations near streams. The bridge structures

that are built over streams often have abutments resting on earth, along with concrete

structures that have been built upon the banks. Some of the GPS surveys from stations

next to streams were located on these bridge structures. Some elevation error near a

stream location may also be due to an inexact GPS station location on a slope, or due to the addition or removal of earth during the construction of the bridge.

The difference in GPS and boring survey data elevation at one location (GPS survey station 4) was not explainable using either of the two causes discussed previously.

This boring and GPS survey location differed from the others in two ways; it is the only

GPS survey not performed at an ODOT boring and the actual boring location was more uncertain. The likely location of the boring did not match the boring location map in its engineering report, so that the large difference in elevation (5.1 m) for this location may be due to an inaccurate boring location obtained from the GIS or an inaccurate GPS station location setup in the field. Another possible reason for the difference in elevation is because steep slopes are present on both sides of the survey location (the station is on a

ridge between Griggs Reservoir and a limestone quarry), so that a small horizontal error in location will produce a large elevation error.

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Top of Boring Elevations Original GPS Elev. Original Elevation Boring ID Boring minus Cor. Boring from GPS Station Corrected Boring

GPS Survey (m, NGVD29) (m, NAVD 88) (m, NAVD 88) Elev. (m) 1 ODOT-FRA-70-0261-a 284.6 284.4 292.2 7.8

2 ODOT-FRA-70-0261-b 285.2 285.0 291.9 6.9

3 ODOT-FRA-270-0205-a 263.6 263.4 271.2 7.8

4 USWIS FRA-BTB-1 243.3 243.1 248.2 5.1

ODOT-FRA-Stringtown 5 Rd-Republican Run a 237.6 237.4 238.9 1.5

6 ODOT-FRA-317-0037-b 209.8 209.6 215.5 5.9

7 ODOT-FRA-317-0037-a 209.2 209.0 212.7 3.7

ODOT-FRA-122-Big 8 226.0 225.8 224.6 -1.2 Walnut Creek-a ODOT-FRA-Gender Rd- 9 Penn Central RR-a 240.9 240.7 249.3 8.5 ODOT-FRA-Gender Rd- 10 Penn Central RR-b 240.5 240.3 249.3 9.0

11 ODOT-FRA-270-1634-a 220.1 219.9 230.2 10.3

12 ODOT-FRA-270-1634-b 223.2 223.0 230.4 7.4

13 ODOT-FRA-62-2284-a 242.5 242.3 239.1 -3.1

14 ODOT-FRA-270-2525-a 256.2 256.0 251.9 -4.2

15 ODOT-FRA-270-2525-b 256.6 256.5 250.6 -5.8

16 ODOT-FRA-3-40.780-b 240.5 240.3 243.7 3.4

17 ODOT-FRA-270-1922-a 256.2 256.1 248.7 -7.3

18 ODOT-FRA-270-1922-b 256.0 255.8 249.0 -6.9

19 ODOT-FRA-161-2280-a 322.0 322.0 326.6 4.5

20 ODOT-FRA-161-2280-b 322.7 322.7 326.8 4.1

Table 4.3: Elevations and difference in elevation for the 20 borings and GPS surveys.

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4.4.3.3 Comparison of Elevations from the Global Positioning System Survey, Boring

Records, and Digital Elevation Models

This comparison of the GPS survey elevations to the DEM and original boring

elevations shows a variety of patterns (data in Table 4.4, and a summary of the patterns in

Table 4.5). The average of the absolute values of the differences between the elevation

of the pixel of the four DEMs and the boring elevation, and the average differences

between the elevations of the pixel of the four DEMs and the GPS survey elevation are

shown in Table 4.6.

In general, data from the GPS surveys show that the DEMs constructed in this

study are more accurate in their representation of the current surface elevations than the

USGS DEMs at those locations where bridge overpasses were constructed over the

boring location by the mounding of earth, and at those locations where excavation into

the earth occurred for the construction of a highway (Table 4.5). For the same locations, the USGS DEMs represent the original boring surface elevations more accurately than the DEMs constructed in this study do. (One exception, a boring that follows this pattern but is not associated with roadway or bridge construction, is GPS station 4.) Two GPS surveys did not follow any pattern when compared to the DEMs; they were at locations where both excavation and bridge abutment construction appear to have occurred near the borings.

Survey locations near streams exhibit a variety of patterns. In some cases, GPS survey elevations or boring elevations are similar to the various DEM elevations; in other cases, the GPS survey or boring elevations are quite different from the DEM-derived elevations. Overall, these data show that a DEM is likely to be less accurate near 113

streams. The possible reasons for this include the problem of using a DEM to represent the greater topography that is likely near a stream, or possible changes that have occurred at the surface from stream erosion, sediment deposition or changes during bridge construction over the stream. Regardless of its cause, an important result is that errors in the surface elevations are more likely for surficial mapping near streams..

The RMSE is calculated to evaluate the vertical accuracy of the DEMs (Table

4.7). This was calculated using the GPS survey elevation as the “true” elevation, and the elevation of the pixel containing that GPS survey station as the DEM elevation. Overall, the DEMs produced in this study are more accurate than the USGS DEMs, with the DEM constructed using the ordinary kriging method as the most accurate. As shown in Table

4.4, though, the USGS DEMs are as accurate as, or more accurate than, the DEMs constructed in this study in some settings.

114

Elevation of Cell from DEMs (m, NAVD 88) (Difference from original boring, m) (Difference from GPS survey, m) Boring ID

Station Ordinary Minimum USGS 30 m USGS 10 m

GPS Survey GPS Survey Kriging Curvature DEM DEM 291.8 291.5 286.3 286.3 ODOT-FRA- 1 (+7.4) (+7.1) (+2.0) (+2.0) 70-0261-a (-0.3) (-0.6) (-5.8) (-5.8) 291.4 292.3 286.9 287.3 ODOT-FRA- 2 (+6.4) (+7.3) (+1.9) (+2.3) 70-0261-b (-0.5) (+0.4) (-5.0) (-4.6) 271.4 271.6 265.0 265.0 ODOT-FRA- 3 (+8.0) (+8.2) (+1.6) (+1.6) 270-0205-a (+0.2) (+0.4) (-6.2) (-6.2) 248.1 249.5 241.5 238.6 USWIS FRA- 4 (+5.0) (+6.4) (-1.6) (-4.5) BTB-1 (-0.1) (+1.3) (-6.7) (-9.6) ODOT-FRA- 240.6 240.6 238.7 239.3 Stringtown 5 (+3.2) (+3.2) (+1.3) (+1.9) Rd-Republican (+1.8) (+1.8) (-0.2) (+0.5) Run-a 215.4 216.7 215.1 215.7 ODOT-FRA- 6 (+5.7) (+7.1) (+5.5) (+6.0) 317-0037-b (-0.2) (+1.2) (-0.4) (+0.2) 213.3 212.4 212.8 213.0 ODOT-FRA- 7 (+4.3) (+3.4) (+3.8) (+4.0) 317-0037-a (+0.6) (-0.3) (+0.2) (+0.3) ODOT-FRA- 224.1 225.1 220.7 218.8 122-Big 8 (-1.7) (-0.8) (-5.1) (-7.0) Walnut Creek- (-0.5) (+0.4) (-3.9) (-5.9) a ODOT-FRA- 247.2 249.4 240.9 240.6 Gender Rd- 9 (+6.4) (+8.7) (+0.1) (-0.1) Penn Central (-2.1) (+0.1) (-8.4) (-8.7) RR-a ODOT-FRA- 244.3 249.4 240.6 240.6 Gender Rd- 10 (+4.0) (+9.1) (+0.3) (+0.3) Penn Central (-5.0) (+0.2) (-8.7) (-8.7) RR-b

Table 4.4: GPS station elevations, and differences in elevation for the twenty borings and DEM pixels containing the boring. (continued)

115

Table 4.4: continued

Elevation of Cell from DEMs (m, NAVD 88) (Difference from original boring, m) (Difference from GPS survey, m) Boring ID

Station Ordinary Minimum USGS 30 m USGS 10 m

GPS Survey GPS Survey Kriging Curvature DEM DEM 229.3 228.2 222.3 222.3 ODOT-FRA- 11 (+9.4) (+8.3) (+2.4) (+2.4) 270-1634-a (-0.9) (-2.0) (-7.9) (-7.9) 227.7 230.5 222.3 222.3 ODOT-FRA- 12 (+4.6) (+7.4) (-0.7) (-0.7) 270-1634-b (-2.7) (+0.1) (-8.1) (-8.1) 240.2 240.1 237.2 238.0 ODOT-FRA- 13 (-2.1) (-2.2) (-5.1) (-4.3) 62-2284-a (+1.0) (+0.9) (-1.9) (-1.2) 252.6 252.2 255.8 255.8 ODOT-FRA- 14 (-3.4) (-3.8) (-0.2) (-0.2) 270-2525-a (+0.7) (+0.4) (+4.0) (+4.0) 252.7 251.3 255.8 255.8 ODOT-FRA- 15 (-3.8) (-5.2) (-0.6) (-0.6) 270-2525-b (+2.0) (+0.6) (+5.2) (+5.2) 243.7 244.1 241.5 241.1 ODOT-FRA- 16 (+3.4) (+3.7) (+1.2) (+0.8) 3-40.780-b (0.0) (+0.4) (-2.2) (-2.6) 250.4 252.6 251.1 249.0 ODOT-FRA- 17 (-5.7) (-3.5) (-4.9) (-7.1) 270-1922-a (+1.7) (+3.8) (+2.4) (+0.3) 252.1 256.2 249.0 250.9 ODOT-FRA- 18 (-3.7) (+0.4) (-6.8) (-4.9) 270-1922-b (+3.1) (+7.3) (+0.1) (+2.0) 325.3 326.8 322.3 322.4 ODOT-FRA- 19 (+3.3) (+4.8) (+0.3) (+0.4) 161-2280-a (-1.3) (+0.2) (-4.2) (-4.1) 327.4 327.7 322.3 322.3 ODOT-FRA- 20 (+4.6) (+5.0) (-0.4) (-0.4) 161-2280-b (+0.5) (+0.9) (-4.5) (-4.5)

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Description of Pattern and Interpretation GPS Survey Stations GPS survey elevation better represented by kriging and minimum curvature DEMs, boring elevations better represented by USGS DEMs 1, 2, 3, 4, 9, 10, 11 and 12 Survey locations with the mounding of earth for bridge overpasses (with the exception of station 4)

GPS survey elevation better represented by kriging and minimum curvature DEMs, boring elevations better represented by 14 and 15 USGS DEMs Survey locations with the excavation into the earth for highway construction GPS survey elevations and boring elevations that are either well-represented or not well-represented by the various 5, 6, 7, 8, 13, 16, 19 and 20 DEMs (various relationships exist) Survey locations next to streams GPS survey and boring elevations not fitting any pattern Survey location probably affected by 17 and 18 excavation into the earth and bridge construction

Table 4.5: Summary of patterns in the comparison of elevations from the GPS survey, starting boring elevation, and various DEMs.

Ordinary Minimum USGS 1 USGS 1/3 Kriging Curvature arc second arc second DEM DEM DEM DEM Average difference from boring elevation ±4.8 ±5.3 ±2.3 ±2.6 (absolute value in m) Average difference from GPS survey ±1.3 ±1.2 ±4.3 ±4.5 (absolute value in m)

Table 4.6: Average difference between the elevation taken from the pixel of the DEMs and the boring elevation, and between the elevation taken from the pixel of the DEMs and GPS survey elevations (n=20).

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Ordinary Minimum USGS 1 USGS 1/3 Kriging Curvature arc second arc second DEM DEM DEM DEM RMSE (m) 1.8 2.0 5.1 5.4

Table 4.7: Root-mean-square-error for each DEM, using the GPS elevation as the true elevation value (n=20).

4.4.4 Digital Elevation Model Applications

The previous comparisons show that DEMs can be inaccurate in their

representation of the actual surface elevations. These inaccuracies could produce errors in an application that relies on a DEM to adequately represent the surface. The importance of DEM accuracy is shown here by evaluating DEM use in several applications.

4.4.4.1 The Placement of Boring Elevations in Subsurface Mapping

Geologic borings are the primary source of information for several of ODNR’s digital mapping efforts, including the map establishing Ohio’s bedrock topography, as well as the ongoing surficial mapping program. In both of these subsurface mapping efforts, the data from geologic borings are often “hung” from a surface elevation that is taken from USGS DEMs. This study has established that the surface elevation represented by such a DEM can be inaccurate. If the starting elevation of a boring is assumed to be the elevation of the pixel representing the surface, then this error will be

carried down through its geologic representation of the subsurface. Figure 4.10 shows that if the surface elevations of two borings were taken from DEMs, the unconsolidated deposits and bedrock surface would have an incorrect vertical placement, and the bedrock topography orientation would incorrectly mapped. The original elevations of the borings 118

utilized in this study were determined by surveying, but many of the ODNR mapping projects rely on well logs from locations that have not been surveyed.

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Figure 4.10: Sketch of two geologic borings, as represented by the surface elevation at the time of drilling, and how they would be represented if placed vertically according to a DEM elevation. Particular unconsolidated deposits or the bedrock surface may be off vertically by several meters if placement is solely based upon DEM surface elevations.

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4.4.4.2 Mapping of Flood Zones

The Federal Emergency Management Agency is responsible for making and

updating flood hazard maps for those areas involved in the National Flood Insurance

Program. The flood hazard maps generally define the Special Flood Hazard Areas

(SFHAs), primarily designating those areas with a 1 percent annual chance of flooding.

These are commonly referred to as 100-year flood zones, and are used to determine who

participates in the flood insurance program.

The SFHAs are generally created by first predicting the flood (generally defined

as a time period when the stream flows outside of its banks) frequency for a particular

year of a stream based on historical streamflow data, and then calculating the likelihood

of a particular flood frequency to rise to a particular stage. The stage designation at that

stream location for an event with a 1 percent annual chance of occurring is then used to

map the areas adjacent to the stream that will be inundated during the predicted flood

event. The mapping of the SFHA is historically performed using the elevations represented on topographic maps, but there are several efforts by FEMA to modernize

and update their flood maps using digital techniques.

A visual comparison of the flood stages taken from the Flood Insurance Rate Map

(FIRM) to the elevations represented by contours on the USGS 7.5-minute quadrangle

topographic map and to elevations represented on the USGS 1/3 arc second DEM

confirmed that they closely matched the FEMA SFHA designation. This matching of the

flood stage to the USGS elevation data was not surprising since the traditional mapping

of SFHAs has been on USGS maps.

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This study was designed to determine if the 100-year flood SFHA as designated

on FEMA’s maps would remain the same if mapped on the DEM constructed in this

study using the ordinary kriging method. There was no attempt to comprehensively

evaluate the SFHA for all of Grove City, or for all of West Water Run. The purpose was

not to submit a revision for FEMAs flood hazard map, but rather to identify areas where the current SFHA was mapped based on elevations that may not be accurate.

The comparison between the FIRMs 100-year flood SFHA and the 100-year flood

SFHA based on the elevations represented on the kriging DEM is shown in Figure 4.11.

The area of the modified 100-year flood zone increases by approximately 170 percent when mapped on the DEM generated in this study. Some small portions of the SFHA designated on the FEMA FIRM are reduced in size from the currently mapped areas, but most of the 100-year flood zone as mapped on the kriging DEM is significantly expanded. This evaluation suggests that the current SFHA delineation is inaccurate because topographic maps were used that did not accurately represent the surface at the time of the mapping of the 100-year flood zone. There is also the possibility that the 100- year flood zone has changed because of the lowering of the ground surface during construction in this area, and this lowering is reflected in the kriging DEM. Although the

actual reason why the current 100-year flood zone delineation appears inaccurate is not

determined here, if the modified 100-year flood zones are accurate, this would

considerably change who qualifies for flood insurance in this area.

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Figure 4.11: The differences between the 100-year Special Flood Hazard Area designated by FEMA (black line), and the 100-year flood area if the same flood stages were mapped on a DEM constructed in this study (red line).

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4.4.4.3 Surface Water Modeling

Watershed models are an important tool for estimating approximate non-point source pollutant contributions to a stream. The Soil and Water Assessment Tool (SWAT) is a stream basin model that was developed by the USDA to assess the impact of land management practices on surface water quality (Arnold et al., 1998). The SWAT model utilizes spatial factors such as soil type, land use, and slope to calculate hydrologic parameters, and ultimately to determine stream loading of a variety of common non-point pollutants.

This study compares how the different DEMs for this area can produce different results in a surface water model. The evaluation uses the ArcSWAT ArcGIS extension for SWAT, which provides a graphical user interface for the model (Winchell et al.,

2007). The SWAT model was run twice: once using the Franklin County DEM generated by kriging, and once using the USGS 1/3 arc second DEM. All other parameters in the two modeling sessions remained the same to facilitate a comparison of the results.

The first step in the model is the delineation of watersheds using the DEM. This procedure utilizes some of the hydrologic tools available in ArcGIS, which relies on the elevation data in the DEM. The result is the delineation of subwatersheds and stream networks for a given area. The program then creates hydrologic response units (HRUs) based on soil types, land uses, and slopes calculated from the DEM. The HRU analysis provides the spatial distribution of surface properties within the watershed, ultimately providing the parameters needed for runoff and other hydrologic calculations. The

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simulation in this study used precipitation data from 2003, with all results calculated for

this one-year period. The same default values were used in both model runs.

The comparison of the ArcSWAT runs using the two different DEMs is shown in

Tables 4.8 through 4.10. More watersheds were delineated for the kriging DEM than for

the USGS DEM. Overall, there was little overlap between the watersheds delineated

using the two different DEMs (Figure 4.12). Some watershed borders created from the

kriging DEM are adjacent to human-constructed features, such as highways and the

sanitary landfill, creating hydrologic divides. The average slope and the number of

HRUs calculated for each DEM are also different (Table 4.8). Some differences are

noticed when comparing the average watershed hydrologic parameters, with the

ArcSWAT model using the kriging DEM having a higher lateral flow contribution,

higher ground water discharge, and a higher percolation rate (Table 4.9). Small

differences are noticiable when comparing some of the average watershed loadings of

sediment and NO3 (Table 4.10).

An additional comparison was made for one particular subwatershed to determine

if the two DEM model runs produced different results for this one defined basin. The

subwatershed to be evaluated was selected by visual inspection, showing that the basin was of a similar shape and size for both DEM model watershed delineations. Values from the subwatershed delineation and resulting non-point pollutant output calculation are shown in Table 4.11. In general, the results show that the calculated slope values are different, and that the non-point pollutant outputs can be different solely based on which

DEM is used in the watershed model. Because SWAT is used by governmental agencies to establish point and non-point discharge policies, such as in calculations of total 125

maximum daily loads, this evaluation shows that the model outcome may be affected

solely by the use of a particular DEM.

Number of Watershed in Average Slope Number of Watersheds Area (km2) (%) HRUs Delineated Kriging 1327.1 166 1.9 593 DEM USGS 1332.7 154 1.7 529 DEM

Table 4.8: Comparison of the hydrologic parameters delineated in ArcSWAT runs using two different DEMs.

Ground Surface Lateral Flow Percolation Water Runoff Contribution Rate Discharge (mm) (mm) (mm) (mm) Kriging 198 0.2 8.3 13 DEM USGS 200 0.1 6.4 11 DEM

Table 4.9: Average watershed hydrologic parameters from HRUs to the streams between ArcSWAT runs using the kriging DEM and the USGS DEM.

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NO Lateral Sediment NO Surface 3 NO 3 Flow 3 Yield Discharge Percolation Contribution (tons/ha) (kg/ha) (kg/ha) (kg/ha) Kriging 6.7 1.4 0.02 1.7 DEM USGS 6.4 1.4 0.02 1.2 DEM

Table 4.10: Average watershed loadings from HRUs to the streams between ArcSWAT runs using the kriging DEM and the USGS DEM.

Watershed Slope Values Sediment Sediment NH4 in Area (% in slope Output Conc. Output (km2) category) (tons) (mg/L) (kg) <1 27.4 1-3 41.7 Kriging 6.77 3-5 10.6 511 628 123 DEM 5-7 5.5 >7 14.8 <1 28.8 1-3 36.4 USGS 6.76 3-5 13.4 532 538 116 DEM 5-7 7.1 >7 14.3

Table 4.11: Comparison of the output for the two ArcSWAT model runs for one particular watershed.

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Figure 4.12: The watersheds delineated in ArcSWAT comparing the results from the DEM generated using kriging and the DEM obtained from the USGS.

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4.5 Modifications to the Bedrock Topography Map

4.5.1 Data Used to Modify the Bedrock Topography Map

Bedrock topography is important in the deposition of unconsolidated materials in an area, as the bedrock surface can greatly affect the depositional and erosional processes acting in an area. An understanding of bedrock topography is also important for various practical applications, such as building foundation investigations, ground water exploration, and mining. The bedrock topography maps developed by ODNR are based on a compilation of data from a variety of sources, primarily water-well logs found on

ODNR drilling reports. The bedrock topography maps were constructed by digitizing the various sources of bedrock data into a GIS, and gridding that data into a DEM (Ohio

Division of Geological Survey, 2003a). If a particular water-well penetrated bedrock, that bedrock elevation was determined by taking the well surface elevation from a USGS

DEM or topographic map, and subtracting down to the reported depth of bedrock. While this system works well to construct the bedrock topography for certain map scales, inaccuracies are inherent when utilizing these data to construct more detailed representations of the bedrock topography.

The accuracy of Franklin County’s bedrock topography was improved by using data from those borings in the database from this study that penetrated bedrock, few of which were incorporated into the ODNR map. Because the borings utilized in this study have accurate locations and surface elevations, the bedrock elevations at those borings that penetrated bedrock are accurate.

A total of 293 of the located borings penetrate bedrock. For these borings, the measured bedrock elevation averages 2.47 m different from the elevation derived from 129

the bedrock topography DEM generated by ODNR; the mean of the absolute values of

the elevation differences is 5.70 m. The elevation differences ranged from -17.4 to 29.8

m, with a standard deviation of 8.34 m. These values show that significant differences

exist between the ODNR bedrock topography map and the actual bedrock elevations.

Figure 4.13 shows the borings that identify the top of bedrock on their logs, as well as the differences in elevations between the ODNR bedrock topography map and the boring reports. The majority of the borings that reached bedrock are found in the northern half of the county, where the surficial sediments are thinner. The primary exception is in southwestern Franklin County where six borings at the Franklin County

Sanitary Landfill were drilled beyond 40 m and into bedrock (average depth to bedrock for these borings is 45 m). Thirty-nine percent of the borings that reached bedrock are from the Upper Scioto Sewer Interceptor project, comprising almost all of the borings from that project. The remainder of the borings are from ODOT structure and soil investigations, confirming that these are a valuable source of bedrock elevations. These data were then used to modify the existing ODNR bedrock topography map.

A query was performed in the GIS to find those borings utilized in this study that

do not report reaching bedrock (i.e. they were not drilled deep enough), but that should have reached bedrock according to the ODNR bedrock topography map. This query identified those areas where the ODNR bedrock topography map shows a higher bedrock elevation than exists. Thirty-nine borings have a bottom elevation below the bedrock surface on the ODNR bedrock topography map, but did not penetrate bedrock (Figure

4.14). The average difference is -19.0 m and one boring at the Franklin County Sanitary

Landfill has a bedrock elevation that is 91.1 m different from that shown on the ODNR 130

bedrock topography map. Thirty-six of the borings in this category were from ODOT geotechnical reports. The data from these borings were also used to revise the bedrock topography map for Franklin County.

The data identifying differences from the ODNR bedrock topography map were digitally plotted along with the available ODNR data, and the bedrock topography contours were modified to fit the revised data set (Figure 4.15). The modified contours were then used to grid the data using the TopoGrid function in ArcGIS. The resulting modified bedrock topography map in the form of a DEM is shown in Figure 4.16. When compared to the details in the original ODNR bedrock topography map (Figure 2.7), the following changes are evident: 1) the bedrock topography shows greater relief in southwestern Franklin County, near the existing sanitary landfill, due to the addition of accurate bedrock elevations at a significant depth; 2) the bedrock is significantly higher in certain areas of central Franklin County than is shown on the ODNR bedrock topography (several areas on the ODNR map had the bedrock surface 20 m or more below the bedrock elevations in borings); and 3) bedrock elevation data from the borings along the Upper Scioto Sewer Interceptor project (in the northern part of the county, west of the Scioto River) provide a more detailed map of the area along the west side of the bedrock valley, showing greater relief in the carbonate bedrock of this area.

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Figure 4.13: The borings that penetrated bedrock in this study, and their difference in bedrock elevation from the ODNR bedrock topography map.

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Figure 4.14: The borings that did not penetrate bedrock in this study, but have a bottom elevation below the bedrock surface elevation from the ODNR bedrock topography map.

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Figure 4.15: Close up (near the Franklin County Sanitary Landfill) showing the bedrock topography contours (brown lines), the ODNR data used to generate the bedrock topography contours (green data points) and how the data used to change the contours are represented in study. The borings that penetrated bedrock in this study and have an elevation higher than that shown on the ODNR map are represented by red circles, and the borings that have a bedrock elevation lower than the ODNR map are represented by green circles. The borings that did not penetrate bedrock in this study, but have a bottom elevation above the bedrock surface elevation from the ODNR bedrock topography map, are represented by blue circles.

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Figure 4.16: Bedrock topography after corrections were made to the ODNR bedrock contours, and the pixel size was reduced to 30 m.

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4.5.2 Bedrock Drainage Patterns

The bedrock drainage patterns that are defined by the ArcGIS hydrology tools provide a detailed picture of erosional surfaces cut into the bedrock (Figure 4.17). The major drainage channels generally follow the Deep Stage/Illinoisan drainage described in

Schmidt and Goldthwait (1958; Figure 2.5), but show many subtle deviations from these larger drainage paths. The most deeply incised bedrock valleys are generally contained within the clastic bedrock region, especially in the central and southeastern portions of the county where the Ohio and Olentangy shales are found (Figure 2.8). As noted by

Schmidt and Goldthwait (1958) and Norris (1959), the deeper and broader U-shaped valleys are found in the area of clastic bedrock. A more trellis-like drainage pattern with shorter, but more numerous, tributaries is found in the carbonate bedrock in the western half of the county, as well as in many of the more resistant clastic rocks in the northeastern corner of the county.

The multiple drainage systems identified by Schimdt and Goldthwait (1958) are evident here, and as they concluded, the systems probably did not all function at the same time. Some modern drainage patterns in the northern end of the county, especially the upper reaches of the Scioto and Olentangy rivers, follow the bedrock drainage, indicating that the modern streams are either following channels that are pre-glacial or are incising into the existing bedrock surface at these locales (Schmidt and Goldthwait, 1958). Most of the other modern stream channels follow paths that are separate from the bedrock valleys, indicating that a new flow path was occupied after glacial deposition. A third relationship between the substrate and the current stream valley is evident in the southwestern corner of the county, where Big Darby Creek closely follows the bedrock 136

channels in this area. However, this drainage cuts through moderately thick unconsolidated deposits (generally over 30 m thick), indicating a post-glacial origin, with significant erosion, for this stream and its tributaries.

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Figure 4.17: Bedrock topography with drainage patterns (red lines) as generated using the Spatial Analyst tools in ArcGIS. Modern streams are superimposed over the graphic in blue.

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4.5.3 Comparison of Bedrock Slopes to Bedrock Lithology

The slope of the bedrock surface was calculated for each pixel by calculating the

change in elevation from its neighbors. The map of the slope of the bedrock surface is

shown in Figure 4.18, and shows that many of the bedrock drainages are contained within

areas of steep bedrock topography, indicating that drainage closely corresponds to

erosional surfaces. The area of less-resistant clastic bedrock found in the central to

southeastern part of the county has relatively broad, flat valley surfaces bordered by long

slopes into the uplands. The same clastic bedrock found in the northern areas of the county has more abundant and narrower valleys. The bedrock drainage on the generally more resistant bedrock (primarily found in the western and northeastern parts of the county) also tends to be contained within smaller areas, with shorter, steeper slopes.

Within this general distribution of bedrock slopes, however, are differences in the average slope for similar lithologies (Table 4.12). The average slopes on the Delaware and Columbus limestones are 1.46 and 1.56 degrees respectively, similar to the average slope on the differentiated Ohio and Olentangy shales (1.68 and 1.65 degrees respectively). The Salina Group Undifferentiated is primarily composed of carbonates, but has an average slope of 2.20 degrees, which is more similar to the slopes on the

Mississippian Undivided, the Sunbury Shale, and the Berea Sandstone (2.06, 2.58 and

2.28 degrees, respectively) than to the slopes on the Columbus and Delaware limestones.

On average, the steepest slopes are found in those areas with Bedford Shale as bedrock

(4.06 degrees), which define the margin of the Berea Escarpment in the northeastern portion of the county. The largest standard deviation for the slope is also found in the

Bedford Shale (Table 4.12). 139

These data do not explain why similar lithologies produce different slope values, but it is clear that when comparing the maps of bedrock formations, bedrock drainage and the slope of the bedrock surface, channels preferentially eroded certain lithologies, producing greater slopes in these bedrock valleys. For example, the Salina Group

Undifferentiated contains more bedrock drainage channels and has steeper slopes than the overlying Columbus and Delaware limestones (Figure 4.19 a). In a similar way, in the northeastern portion of Franklin County Mississippian bedrock outlines the bedrock drainage patterns, with the drainage channels found on underlying Ohio Shale (Figure

4.19 b).

Some of these slope values are likely to be artifacts of the original ODNR construction of the bedrock topography map. The area of the Ohio and Olentangy shales

(Figure 2.8) may have the shallowest slopes because data are very sparse in this area, so there is less control on the bedrock topography. Few borings or wells penetrate into

bedrock in this area, whereas the areas with thinner unconsolidated materials have more

data. In the latter case, the true complexity of the bedrock surface is represented more

accurately, and identifies small areas with steeper slopes. Much of the well-defined

bedrock elevation data is in the upland areas and more easily mapped because of the

thinner mantle of unconsolidated deposits.

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Figure 4.18: The calculated slopes on the bedrock surface.

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Slope Values (in degrees) for Type of Bedrock in Franklin County, Ohio

Standard Formations Minimum Maximum Mean Deviation Mississippian Undivided (Maxville 0.001 20.3 2.06 2.17 Limestone, Logan Fm, Cuyahoga Fm)

Sunbury Shale 0.0002 20.3 2.58 2.87

Berea Sandstone 0.005 18.9 2.28 2.52

Bedford Shale 0.0006 20.0 4.06 3.49

Sunbury-Berea-Bedford Undivided 0.004 13.3 2.29 2.07

Ohio Shale 0.0008 15.9 1.68 1.72

Olentangy Shale 0.002 13.3 1.65 1.84

Ohio-Olentangy Shale Undivided 0.0003 11.9 0.90 1.03

Delaware Limestone 0.002 11.0 1.46 1.52

Columbus Limestone 0.0002 14.0 1.56 1.55

Salina Undifferentiated 0.001 13.0 2.20 1.96

Table 4.12: Bedrock slope calculations for the various types of bedrock in Franklin County.

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(a) (b)

Figure 4.19: Close up of the northwestern corner of the county (a) and the northeastern corner of the county (b), showing the bedrock drainage patterns superimposed over the bedrock lithology. The drainage patterns and steepest bedrock slopes are generally close to the margin of where one formation changes to another, following a drainage channel evolution of downcutting into bedrock.

4.5.4 Comparison of Surficial Material Thickness to Bedrock Aspect

The thickness of the unconsolidated materials was compared to the orientation of the bedrock topography (only the north- or south-facing aspects) to evaluate whether glacial deposition is generally greater on the stoss side (north) or the lee side (south) of the bedrock surfaces. The implication is that depositional processes may vary on the up- glacier versus down-glacier side of a static surface, such as the carbonate bedrock found on the western part of the county. Boulton (1982) demonstrated that the subglacial stresses and resulting deposits will vary for static and residual bedforms based on the up- and down-glacier aspects of those surfaces. Analysis by Boulton, along with others

(Evans et al., 2006), concludes that under subglacial processes the lee-side will generally accumulate more sediment than the stoss-side, and that this accumulation will be lessened 143

as the subglacial bed is smoothed by deposited till. The presence of “shadow hills” was demonstrated by Coates (1982); these formed as a result of southward glacier movement, which eroded more from slopes with a north-facing aspect and deposited more on slopes with a south-facing aspect. Coates described this depositional pattern on bedrock hills that are generally 100 to 200 m high, and have till thicknesses on their south-facing slopes that are ~5 times the till thicknesses on their north-facing slopes. This analysis determines if a similar surficial thickness difference is found on north- and south-facing bedrock slopes that are only on the scale of tens of meters high.

Unconsolidated deposit thicknesses were compared to bedrock aspect only for the western part of Franklin County, which is composed primarily of Silurian and Devonian carbonates. This area was selected for analysis based on the similarity of bedrock lithology across the area, with these carbonates being relatively rigid subglacial beds.

Randomly sampled data points were generated using Hawth’s Analysis Tools for ArcGIS for three overlapping areas to compare the north- and south-facing aspects for a range of deposit thicknesses. Based on the random data points, the average thickness for the area defined as having relatively thin deposits was 8.1 m, the average thickness for the area defined as having thin to moderately thick deposits was 27.8 m, and the average thickness for the area defined as having a range of thin to very thick deposits was 36.5 m.

The thickness of surficial material was compared to bedrock aspect, and showed that unconsolidated materials consistently are thicker on south-facing slopes than on the north-facing slopes (Table 4.13). This difference in thickness is slightly more pronounced in areas with thinner unconsolidated materials (less than 10 m thick) than in areas where the unconsolidated material is a few tens of meters thick. This is indicated 144

by the ratio of the difference in thicknesses for the north- and south-facing aspects to the average thickness for each average thickness category (Table 4.13). There are rather large standard deviations for the thickness data, because the average unconsolidated material thickness varies to such a great extent in this portion of Franklin County. This example of till thickness disparity in Franklin County clearly does not approach the disparity of till thickness found by Coates (1982), but does suggest that the till accumulation patterns here follow the demonstration of Boulton (1982) that the down- glacier side of a rigid bed (south-facing for this example) will accumulate more sediment than the up-glacier side of a rigid bed. For an area of less bedrock relief, such as in central Ohio, the small differences in up-ice and down-ice sediment thickness imply that an overall smoothing of the ground surface occurs during glacial deposition.

Shallow Shallow to Medium Shallow to Deep Surficial Material Surficial Material Surficial Material

Thickness Thickness Thickness (Ave. = 8.14 m) (Ave. = 27.82 m) (Ave. = 36.52 m) North South North South North South Facing Facing Facing Facing Facing Facing n = 83 n = 78 n = 705 n = 741 n = 191 n = 192 Average 7.8 8.5 26.9 28.7 35.4 37.7 Thickness (m) Standard 5.2 5.9 14.8 14.8 15.0 14.6 Deviation (m) Ratio of Diff. of Ave Thickness to 0.65 m/8.14 m = 0.080 1.80 m/27.82 m = 0.065 2.31 m/36.52 m = 0.063 Average of Both

Table 4.13: Comparison of the bedrock slope aspect (north- and south-facing) to unconsolidated material thickness, for the area composed of primarily Devonian and Silurian carbonate bedrock in western Franklin County.

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4.6 Evaluation of Geotechnical Data

The primary source of glacigenic sediments is material derived from the

substratum of the glacier (Brodzikowski and van Loon, 1991). Till is often made up of reworked sediments that existed at the surface prior to glaciation, but till is also known to incorporate significant proportions of materials derived from local bedrock. The proportion of the till consisting of local materials can be in the tens of percent, especially when sand (Gross and Moran, 1971) or pebbles are included (Dreimanis, 1976). Till components derived from local bedrock can account for the bimodal or multi-modal grain-size distribution, primarily due to the contribution of larger clasts, but also from the fine-grained matrix that often results from the grinding of these bedrock materials

(Dreimanis and Vagners, 1971; Bennett and Glasser, 1996). Szabo and Angle (1983) demonstrated that bedrock materials glacially transported only a few kilometers can be crushed, significantly affecting the physical properties of a till. The soils that formed from tills in Franklin County are known to have different textures and lime contents, and the delineation between the two major tills is loosely based on whether the underlying sedimentary bedrock is carbonate or clastic in origin (McLoda and Parkinson, 1977).

This portion of the study evaluates whether geotechnical properties of tills in

Franklin County vary based on whether the till overlies the Silurian/Devonian carbonate bedrock or the Devonian/Mississippian (primarily) clastic bedrock. Profiles of geologic boring logs have been constructed for two transects (Figure 3.16): one running north to south in the area with carbonate bedrock (Figure 4.20), and one running west to east in the area with primarily clastic bedrock (Figure 4.21).

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The surface topography for the north-south transect varies little when compared to

the east-west transect. There is less than 20 m of surface relief for the north-south

transect, crossing only a minor stream valley near Big Run. There is a significant

bedrock valley near the center of this transect, but relatively little bedrock topography

north and south of this valley.

Four borings at the northern end of the north-south transect contain significant

clay deposits; the clay overlies bedrock in two borings, and the clay overlies a gravelly zone in the other two borings. Above the clay in all four borings is a diamicton of varying thickness, and two borings have a gravelly zone at the top. The stratigraphic sequence recovered in borings to the south is relatively consistent and dominated by diamictons, although one or more gravelly zones may be present. The gravel zones consist of a mixture of gravel (usually 40 percent or more gravel) with varying amounts of sand, silt and clay. Some borings contain a sandy zone, which is usually only a meter or two thick (with no stratigraphically consistent location), but is eight meters thick in one of the borings. Near the south end of the transect, five borings have lower surface elevations, reflecting their proximity to Big Run. Some of these borings also contain more coarse-grained deposits than the surrounding borings. Although the coarse-grained material is interbedded within the diamictons in several cases, the bedrock elevations do not indicate a significant older valley at these locations.

Along the east-west transect of borings, the surface topography shows the locations of major stream valleys, including the Scioto and Olentangy rivers, and Alum and Big Walnut creeks. There is relatively little surface topography near Blacklick Creek on the eastern end of this transect. The greatest change in surface elevation occurs at the 147

Berea Escarpment, and elevations generally continue to rise to the eastern edge of the

county, where surface elevations exceed 320 m msl. The bedrock topography along this

transect generally matches the locations of the major streams; bedrock valleys are found

underlying or adjacent to the five major streams. The deepest bedrock valleys on the

north end of the county are found near Alum and Blacklick creeks, where bedrock is the

Devonian shales.

The surficial deposits in the east-west transect vary markedly in thickness, with

the unconsolidated materials ranging from a few meters to over 80 m thick (Figure 4.21).

Some of the diamictons recovered in the borings are consistent through twenty meters,

whereas others are punctuated by gravel zones in the borings. Abundant gravel and sand in a set of borings located near Alum Creek (Penn RR a, SR3 a and b) and a set of borings near Big Walnut Creek (Sunbury a and b, Big Walnut a and b) are interbedded with diamictons. This stratigraphy indicates that these deposits are not simply modern

(post-Wisconsinan) stream deposits, but instead show intervals of coarse-grained

deposition between periods of glacial advance. Four sets of borings along the east-west

transect encounter fine-grained deposits that primarily consist of either silt or clay; these

are differentiated from diamictons because their silt and clay contents exceed 80 percent,

and because they lack gravel. Three of the four sets of these fine-grained deposits are

found in small east-west oriented bedrock valleys.

148

North South

North South

Figure 4.20: Profile of geologic boring logs along the north-south transect found in the carbonate bedrock area. Each partial profile connects with the partial profile that follows. (continued) 149

Figure 4.20 continued

North South

150

West East

West East

Figure 4.21: Profile of geologic boring logs along the west-east transect found in the primarily clastic bedrock area. Each partial profile connects with the partial profile that follows. Note that the elevations change from section to section. (continued)

151

Figure 4.21 continued West East

West East Berea Escarpment

152

4.6.1 Comparison of Standard Penetration Test to Gravel Content and to Depth in the

Diamictons

The standard penetrometer test (SPT) is the most common geotechnical test

performed in the field, and is generally used to evaluate the relative density of an

unconsolidated material. This test is performed by advancing a split-spoon sampler by dropping a weight onto a drill rod connected to the sampler. The number of drops of the

hammer needed to drive the sampler a fixed distance is correlated to a particular density

or hardness of materials described as clays, silts or sands (the use of this test is not

encouraged in gravels). A comparison is made here to determine if there is a correlation

between the standard penetrometer test value (N) and diamicton properties. The first

comparison is made between values of N and the proportion of gravel in the diamictons

to see if there is a correlation. The second comparison is made to determine if there is a

relation between N value and depth within the diamictons found in the north-south and

east-west transects as described in the previous section.

The initial evaluation of standard penetration test N values and gravel content

shows no relationship between these two parameters (Figure 4.22). The proportion of

gravel in the samples interpreted as tills ranges from 0 to ~40 percent, but there is a wide

range of N values for the various proportions of gravel. The inconsistency between these

two variables is evident even though the other grain-size components remain relatively

consistent; the amount of sand is fairly uniform for these samples (usually 15 to 30

percent) and the silt and clay contents are relatively uniform (defined here for a diamicton

as having at least 40 percent silt and clay).

153

Standard penetrometer testing is performed in materials that are primarily sand- sized or smaller. If the sampler is advanced into sediment containing gravel, the N values can be very inaccurate due to the edge of the sampler hitting the clasts (Zekkos et al.,

2004; McCarthy, 2007). The ODOT grain-size data available for these borings does not identify the grain size of the gravel fraction, so the effect of a fine versus coarse gravel component cannot be evaluated; however, such an effect is possible because a broad distribution of gravel sizes has been reported for diamictons (Dreimanis and Vagners,

1971; Milligan, 1976). In an engineering context, this evaluation demonstrates that the gravel content of the diamictons in Franklin County does not have a predictable effect on their SPT N values.

A second evaluation was made to determine if the SPT N values and the gravel abundances vary downsection in some predictable way, as well as to determine any differences for the diamictons from the two bedrock areas. The composite depth profiles of the N data and percent gravel data were constructed for the two separate transects

(Figure 4.23 and 4.24). In both profiles the gravel content remains fairly constant at ~20 percent (average of 19.5 percent for the carbonate area and 19.3 percent for the clastic area), although the upper 2.5 meters of diamicton on the clastic bedrock generally contain less gravel. The composite depth profiles of N are also similar for the two bedrock areas, although the average N value for the carbonate bedrock area is somewhat higher (39.5) than the average value for the clastic bedrock area (34.2). Both profiles exhibit increasing N with depth, but the increase occurs over a shorter depth range for the carbonate bedrock area than for the clastic bedrock area. Most borings do not achieve an

N value above 30 (generally classified as “dense” or “hard” in most correlations between 154

soils and SPT; McCarthy, 2007) until a depth of 5 m in the clastic bedrock area; however,

samples with N>30 are common below 2 m on the carbonate bedrock. An explanation

for the higher N values in the diamictons found in the carbonate bedrock area is the

possibility of greater proportions of carbonate cements. Both profiles show a relatively

consistent N value below a depth of 10 m. Engineering calculations based on N values

are sometimes corrected for depth, due to the fact that the blow count is often higher for a

given soil density due to overburden and lateral pressures; however, these corrections are

restricted to materials dominated by sand (Zekkos et al, 2004; McCarthy, 2007).

50

40

30

R2 = 0.0003 % Gravel % 20

10

0 0 1020304050 N

Figure 4.22: Scatter plot comparing standard penetration test value N to percent gravel for the diamictons in both the carbonate and clastic bedrock areas. The square of the correlation equals 0.0003, indicating an insignificant relationship.

155

Composite for Clastic Bedrock Area N-value or % Gravel 0.0 50.0 0.0

Number of values for sample depth 5.0 (depth at middle of sample interval in m) - n 0.9 = 13 1.7 = 26 2.4 = 19 3.2 = 21 4.0 = 13 4.7 = 19 10.0 5.5 = 17 6.2 = 17 7.0 = 8 7.8 = 20 9.3 = 22 10.1 = 6 Depth (m) 10.8 = 19 12.3 = 15 15.0 13.9 = 16 15.4 = 16 16.9 = 10 ≥18.4 = 6

20.0

25.0

Figure 4.23: Composite depth profile of average gravel content (weight percent, represented by circles) and standard penetrometer test value (N, represented by squares) for diamictons found in the clastic bedrock region.

156

Composite for Carbonate Bedrock Area N-value or % Gravel 0.0 50.0 0.0

Number of values for sample depth 5.0 (depth at middle of sample interval in m) - n 0.9 = 8 1.7 = 23 2.4 = 16 3.2 = 23 4.0 = 19 4.7 = 21 10.0 5.5 = 19 6.2 = 19 7.0 = 11 7.8 = 21 9.3 = 25 10.1&10.8 = 24 Depth (m) 12.3 = 23 13.9 = 4 15.0 15.4 = 4 16.9 = 5 ≥18.4 = 3

20.0

25.0

Figure 4.24: Composite depth profile of average gravel content (weight percent, represented by circles) and standard penetrometer test value (N, represented by squares) for diamictons found in the carbonate bedrock region.

157

4.6.2 Comparison of Atterberg Limits

Atterberg limits are often used in the engineering classification of soils. The

liquid limit identifies the percent moisture at which the fine-grained fraction (primarily silt and clay) of a sample is between the liquid and plastic state. The plastic limit identifies the percent moisture at which the fine-grained fraction of a sample is between the plastic and semi-solid state. The plasticity index is the difference between the plastic limit and liquid limit, identifying the range of moisture content at which the soil is in a plastic state. The plasticity index value and liquid limit value are used in both the USCS and AASHTO systems of classifying soils. These values are useful in that they reflect certain engineering attributes of a soil, often providing an indication of the physical properties of the clay minerals found in that soil.

In general, the plasticity index and liquid limit values for the samples taken from above the clastic bedrock areas and the carbonate bedrock areas are not considerably different. On average, the plasticity index and liquid limit for the samples taken from the clastic bedrock region are 9.2 and 25.5, with standard deviations of 6.2 and 7.4 respectively (n = 428). The mean plasticity index and liquid limit for the samples taken from the carbonate bedrock region are 7.4 and 23.0, with standard deviations of 3.8 and

3.1 respectively (n = 371). Larger differences are found in the samples taken close to the surface for these two areas, however. The composite depth profiles for the Atterberg limits from the diamictons in the clastic and carbonate bedrock regions are shown in

Figures 4.25 and 4.26. The two profiles exhibit a similar pattern, with plasticity indexes and liquid limits decreasing down hole, but this decrease is slightly more pronounced in the area of clastic bedrock. The Atterberg limits are relatively uniform below 3 m depth 158

for the clastic bedrock area and below 2 m depth for the carbonate bedrock area; and there are few noticeable differences between the two profiles below 5 m depth. Some variations in the depth profiles are found at intervals with fewer samples (n ≤ 2), such as at 20 m in the clastic bedrock profile and 12 m in the carbonate bedrock profile.

159

Clastic Bedrock

Plasticity Index or Liquid Limit 0 1020304050607080 0

5

10 Depth (m)

15

20

25

Figure 4.25: Composite depth profile of plasticity index (represented by triangles) and liquid limit (represented by diamonds) for diamictons found in the clastic bedrock region.

160

Carbonate Bedrock

Plasticity Index or Liquid Limit 0 1020304050607080 0

5

10 Depth (m)

15

20

25

Figure 4.26: Composite depth profile of plasticity index (represented by triangles) and liquid limit (represented by diamonds) for diamictons found in the carbonate bedrock region.

161

4.6.3 Comparisons of Grain Size Data

Diamicton textures were compared to determine if there is a difference between

the samples taken above the clastic bedrock and the samples taken above the carbonate

bedrock. Ternary plots showing the relative abundances of gravel/sand/silt & clay and

sand/silt/clay for the diamicton samples from the two bedrock areas are shown in Figures

4.27 through 4.30. The definition of a diamicton for this study as having at least forty

percent clay and silt excludes data within a certain area of the gravel/sand/silt and clay

plot (Figures 4.27 and 4.28). The average values and standard deviations for the grain-

size abundances in these samples are shown in Tables 4.14 and 4.15.

There are only small differences in the textures of the diamictons from the two

bedrock regions. The samples from the diamictons above the clastic bedrock generally

have slightly higher sand contents and slightly lower silt contents than the samples from

the carbonate bedrock area. The sand/silt/clay ternary diagram for diamictons from the

clastic bedrock region generally shows samples with more sand and clay, and the samples

from the carbonate bedrock are slightly enriched in silt (Figures 4.29 and 4.30). This trend toward higher clay content in diamictons from the clastic bedrock area helps to explain the slightly higher liquid limits and plasticity index for samples from this area.

162

0 1

0.2 0.8

y la 0.4 0.6 S C a & n t d il S

0.6 0.4

0.8 0.2

1 0

0 0.2 0.4 0.6 0.8 1 Gravel

Figure 4.27: Ternary diagram showing gravel, sand and silt/clay abundances for diamictons found in the clastic bedrock region (n=418).

0 1

0.2 0.8

y la 0.4 0.6 S C a & n t d il S

0.6 0.4

0.8 0.2

1 0

0 0.2 0.4 0.6 0.8 1 Gravel

Figure 4.28: Ternary diagram showing gravel, sand and silt/clay abundances for diamictons found in the carbonate bedrock region (n=370).

163

0 1

0.2 0.8

0.4 0.6 y S la i lt C

0.6 0.4

0.8 0.2

1 0

00.20.40.60.81 Sand

Figure 4.29: Ternary diagram showing sand, silt and clay contents for diamictons found in the clastic bedrock region (n=418).

0 1

0.2 0.8

0.4 0.6 y S la i lt C

0.6 0.4

0.8 0.2

1 0

00.20.40.60.81 Sand

Figure 4.30: Ternary diagram showing sand, silt and clay contents for diamictons found in the carbonate bedrock region (n=370).

164

Gravel Sand Silt Clay Silt & Clay

Average 20.3 23.8 31.1 25.1 56.1 Abundance (%) Standard 10.7 6.4 7.9 7.5 9.2 Deviation (%)

Table 4.14: Average values and standard deviations for the grain-size abundances for the samples taken above the clastic bedrock area.

Gravel Sand Silt Clay Silt & Clay

Average 20.4 21.4 33.6 24.6 58.2 Abundance (%) Standard 11.2 5.5 7.3 7.3 10.3 Deviation (%)

Table 4.15: Average values and standard deviations for the grain-size abundances for the samples taken above the carbonate bedrock area.

4.6.4 Candidates for Lacustrine Deposits

Four separate locations in the northern end of Franklin County have sets of borings that contain significant fine-grained deposits with characteristics different than those of the surrounding diamictons (Figure 4.31, with corresponding sets of borings shown on Figure 4.33). These fine-grained deposits are not included in the analyses described previously because they have properties not typical of glacial tills in this area.

Their differentiation from the diamictons is based on the following: a lack of gravel, minor proportions of sand, the deposit consists primarily of silt and clay (total abundance of at least 60 percent), at least one boring in the cluster penetrated 4 m or more of fine-

grained deposits, and the samples exhibit geotechnical properties that are significantly

different from those of the surrounding diamictons (Atterberg limits that are higher for

165

the clays and low to non-plastic for the silts, and SPT N values that are typically lower in

the clays than in the surrounding diamictons).

The ternary plot of the sand/silt/clay contents in these fine-grained samples is

shown in Figure 4.32. These data show two locations enriched in clay (the two locations

to the west), whereas the other two locations have deposits that primarily consist of silt.

All locations show a range of sand contents, but most have a sand content of less than 20

percent. At three of the locations, the fine-grained deposits are at or very close to the

bedrock surface. Two locations from the western half of the county have clay-rich

intervals more than 5 m thick, lying directly above gravelly zones (a few meters thick),

which lie in turn on bedrock (Figure 4.21). The other two locations are from the northeastern part of the county, with sediments that consist primarily of silt. Three of the four fine-grained deposits are found in small bedrock valleys that are oriented east-west

(Figure 4.33). All of these fine-grained deposits are covered by diamictons, and were formed prior to the advance of the last ice sheet in this area. Based on their properties and distribution, these deposits are interpreted as lacustrine, possibly having a proglacial origin in ice-dammed small valleys.

166

" / , *

Figure 4:31: Location of the four groups of borings that contain significant fine-grained deposits with characteristics different than the surrounding tills.

0 1

0.2 0.8

0.4 0.6 y S la i lt C

0.6 0.4

0.8 0.2

1 0

0 0.2 0.4 0.6 0.8 1 Sand

Figure 4.32: Ternary diagram showing sand, silt and clay contents for those deposits interpreted as lacustrine in origin. The different symbols correspond to sample locations shown in Figure 4.31.

167

Figure 4.33: Borings with lacustrine deposits at their base, found in east-west trending depressions in the bedrock topography. (Darker shading shows lower bedrock elevations).

168

CHAPTER 5

DISCUSSION OF RESULTS

5.1 General Discussion

This study emphasizes the importance of high quality data in digital geologic mapping, including the establishment of an accurate base map for locating data. It is also important to utilize a DEM that is correct to a level adequate for that particular mapping effort. The unconsolidated deposits within central Ohio vary to such a degree that short horizontal distances can result in significant differences in the subsurface materials. The vertical accuracy of the map should also be good enough to not introduce errors into the mapping of surficial materials since lithologies that are important in the subsurface may be thin enough that inaccurate starting elevations for borings can offset the depth interval of that lithology by more than its thickness. The DEMs used for this purpose should incorporate elevation data that are current, as human activity can produce surface elevations that are significantly different from the elevations on commonly used DEMs.

Those using data from older geologic borings, such as ODOT structure borings, should be aware that current surface elevations may not apply.

Bedrock topography DEMs should also be modified when additional data become available. State-produced bedrock surface DEMs are good for establishing the general

169

topography, but are not generated to be accurate at a site-specific level, as is

demonstrated by the inaccurate elevations identified in this study.

The interpretation of the glacial history of an area involves the complex

evaluation of many geologic data sources, ultimately attempting to piece together

erosional and depositional processes that occurred in the past. Although the geotechnical

borings utilized in this study do not identify important features such as sedimentary

structures and subtle depositional transitions identifiable on a facies level, they do

provide good-quality data about sediment texture, as well as identifying other properties

that may assist in understanding the deposition of these materials.

5.2 Establishing a Geographic Information System for Geologic Mapping

5.2.1 Use of Digital Resources and the Generation of Geologic Databases

This project establishes a simple, accessible and flexible database system for the

mapping of unconsolidated materials that can be transferred into any GIS or made

available via the Internet. The Ohio Division of Geological Survey 1:100,000 scale

surficial geology maps are currently being produced with plans for this information to be

made available in both paper and digital forms. Portions of the state mapping projects are

complete, and one map (Surficial Geology of the Ohio portions of the Cincinnati and

Falmouth 30x60 Minute Quadrangles) has been officially released. A pilot project by the

Survey is also underway to develop methods and techniques to produce detailed three-

dimensional surficial-geology maps for a high-priority area, with the pilot project

utilizing GIS to establish the glacial geology of the Milan 7.5 minute Quadrangle

(http://www.dnr.state.oh.us/geosurvey/staff/mapgrp/milan.htm). The methods introduced in this investigation are consistent with the Survey’s project objective of “three- 170

dimensional digital compilation of field, borehole, and other existing data for the project

areas.” The author will provide the GIS and database to the Ohio Division of Geological

Survey to assist them in creating more accurate and detailed bedrock and surficial maps for Franklin County. It is also my intent to disseminate the GIS and database generated in this study by duplicating CDs of the data, and providing them to interested parties.

5.2.2 Importance of Digital Elevation Model Accuracy

DEMs in a raster format are common due to their simplicity and because of the

ease with which algorithms can convert available data into a grid. Raster-format DEMs

are generated at many different map scales with a variety of pixel resolutions, and are

ultimately utilized for a variety of purposes. DEMs serve the purpose of representing a

three-dimensional surface, but having a level two-dimensional pixel representing this

surface can result in significant inaccuracies, especially in areas of greater slopes. The

causes of errors in a DEM are numerous, and include inaccurate source data, human

errors from incorrect sampling and interpolation, errors that occur from particular

mathematical models, and systematic errors from modeling (USGS, 1998; Shi et al.,

2005).

This study underscores the importance of using an accurate raster DEM as a base

for geologic mapping, but DEMs are also commonly utilized in surface hydrology

applications, terrain analysis, construction site preparation, and a range of environmental

models. Their accuracy is paramount to a variety of applications, but problems in their

use arise for several different reasons. The type of algorithm used in constructing a DEM

has an impact on its utilization as demonstrated for spatial analysis (Shi et al., 2005),

hydrologic modeling (Zhou and Liu, 2002; Vazquez and Feyen, 2007) and volume 171

calculations in construction (Yanalak and Baykal, 2003). The source data used in

generating a DEM can have an impact on the estimation of soil parameters (Venteris and

Slater, 2005) and the DEM resolution can greatly impact the terrain analysis of soils

(Smith et al, 2006).

Other common concerns in the use of DEMs stem from faulty slope calculations derived from the DEM. Zhou and Liu (2004), and Raaflaub and Collins (2006) showed that gridded DEMs often generate errors in topographic parameters, such as slope and aspect. Ziadat (2007) showed that topographic contours, a common source of data in the construction of DEMs, can ultimately be the source of errors in slopes derived from those

DEMs. Haugerud and Greenberg (1998) described the importance of slope values to the visualization of surfaces, but pointed out that the USGS standards for DEMs have no specifications on the quality of this important value. They also stated that 30 m raster

DEMs are usually adequate for surface visualization at map scales of 1:100,000 or smaller but may not be adequate for maps of a larger scale due to problems with the slopes derived from a raster of this size.

In this study, DEMs are investigated as a base map for three-dimensional mapping of surficial deposits. Because of the heterogeneities inherent in glacially- deposited sediment, relatively thin deposits can be offset by an incorrect starting elevation for a boring or by a DEM surface that is not accurate. This study demonstrates that inconsistencies in and between a DEM and borings elevations should be reconciled before that data is used. Differences between the DEMs obtained from the USGS, the

DEMs generated using available data, and field investigation of actual elevations demonstrate the importance of confirming the true boring elevation when data from that 172

boring is used for geologic mapping, especially where it is likely that the earth’s surface has changed in that area. It is recommended that one or more sources of data be investigated when establishing past and current surface elevations in mapping efforts.

This study clearly indicates that numerous and accurate elevation data should be incorporated into larger scale mapping efforts whenever such data are available. This study generated raster DEMs with a 30 m pixel size, partially because that size replicates most available USGS DEMs, but also because of the computational difficulties encountered when attempting to perform algorithms with such a large number of elevation values on a desktop computer. Although the RMSE is low for the kriging DEM constructed during this study, the generation of a DEM with pixel resolution smaller than

30 m is recommended in those cases where adequate data and computational ability are available.

Although some USGS DEMs with a 10 m pixel are being made available, these generally are not more accurate (Haugerud and Greenberg, 1998); this conclusion is confirmed in this study by comparing the boring elevation data, the GPS survey, and the

1/3 arc second DEM. The USGS National Elevation Dataset is constantly being improved and revisions are still being made to the 7.5-minute topographic maps (Moore,

2000), but it is apparent that many of the DEMs contain out-of-date data. As better elevation data become available, those data should be used to establish a more accurate

DEM for surficial mapping projects. The updated DEM will then be available for other uses, as well.

Table 5.1 is based on experience gained in this study, and summarizes the characteristics of DEMs that are appropriate for usage at different scales in a setting such 173

as central Ohio. This summary shows that the data source(s) and data abundance affect the DEM representation of the surface, and thereby influence the level of detail for which the DEM is appropriate. Table 5.1 only applies to areas with significant and ongoing human activity, because surface elevations will not change significantly in other areas.

In an area such as Franklin County, with a relatively high population density and continued development, it is likely that DEMs are used for many purposes other than mapping. The City of Columbus is expected to spend over $2 billion within the next 40 years to correct a variety of stormwater and sanitary wastewater problems that have resulted in non-compliance with the Clean Water Act, and hydrologic analysis will be necessary in the design of modified and new sewers. Road and bridge construction and residential and commercial development continue in many parts of the county, and site preparation and cut-and-fill activities often rely on having good local surface data.

Concerns with local surface water quality, stemming from sediment and other non-point pollution runoff, also necessitates environmental modeling of the watersheds, and accurate DEMs and slopes derived from the DEMs are important parameters in these models. Although Franklin County makes their contour maps available in CADD, having readily available, detailed DEMs will improve the accuracy of a variety of calculations that rely on surface data.

174

Data Source(s) Data Abundance Most Suitable For: Outdated USGS ≥ 0 / pixel Statewide topographic maps 0-1 / pixel Statewide to countywide Updated USGS Countywide to township- topographic maps >1 / pixel scale 0-1 / pixel Statewide to countywide Spot elevations Countywide to township- ± USGS topographic maps >1 / pixel scale 0-1 / pixel Statewide to countywide Point surveys >1 / pixel Countywide to township- ± spot elevations (pixel size > 10 m x 10 m) scale ± USGS topographic maps >1 / pixel Township-scale to site- (pixel size ≤ 10 m x 10 m) specific

Table 5.1: Summary of the suitability of DEMs for different scales of utilization, based on the data source(s) and data abundance (number of data points/pixel).

5.3 Geotechnical Data in the Unconsolidated Deposits

The primary purpose of characterizing the geotechnical properties of the diamictons is to assess whether any spatial relationships are apparent and to determine if particular properties could be associated with bedrock type. This study does not try to definitively link particular geotechnical values to certain types of tills. Certain relationships are revealed, but the data also demonstrate that the variability of glacial tills is expressed in the geotechnical properties.

Because the SPT is the most common geotechnical evaluation performed on unconsolidated materials, this information should be considered in establishing a general understanding of diamicton densities. SPT N values are subject to a number of uncertainties that can ultimately pose problems with bearing capacity and shear strength calculations (McCarthy, 2007), with most of the problems arising from incorrect field

175

procedures (Zekkos et al., 2004). None of these uncertainties are deemed to be a problem here as this evaluation of the data is more subjective in its attempt to obtain a general understanding of soil densities within the tills and how the density might be linked to glacial depositional processes.

There is an attempt here to observe trends in the SPT-N values relative to gravel content and depth. One might expect that increasing N values would correlate to a greater proportion of gravel, as has been identified as a concern when obtaining the blow count values. This is not the case for the tills in this area; the SPT values of these diamictons appear to be independent of the gravel content in these matrix-dominated deposits. The composite profiles show a lower N and lower gravel values in the upper 2 m of the diamictons, but also show consistent proportions of gravel beyond 3 m and generally consistent N values below a depth of 8 m for diamictons in the carbonate bedrock region and below a depth of 10 m for diamictons in the clastic bedrock region.

The trend of increasing material density with depth observed in the composite profiles is reflected in many of the borings containing diamictons of a consistent texture. Because the proportion of gravel does not change downward, other possible causes for the downward increase in N values should be assessed.

Standard penetrometer test values often are corrected with respect to depth for materials classified as sands, accounting for factors such as effective stress and pore pressures in the presence of water. These adjustments generally result in increased N values within the upper few meters and decreased N values at depth (McCarthy, 2007).

Corrections are also made for sandy materials with conditions of partial saturation, with the modification resulting in greater density values due to effects from cohesion 176

(McCarthy, 2007). These modifications with depth are usually not made on silts and

clays because of their cohesive nature and more regular pore pressures, although some

suggest that adjustments should be made for overburden pressure in deep conditions

(Sivrikaya and Togrol, 2006). This study generally shows increasing N values with

depth, a trend that is common due to greater pressures with depth (McCarthy, 2007), but

cannot conclude that this trend is caused by overburden pressure because effective stress

data are lacking. Because adjustments accounting for effective stresses are often not

made in diamictons and no information for overburden pressures is available, the possibility exists that the trend of increasing N with depth is a result of changing glacial depositional processes.

Standard penetrometer test density values have not been linked to the mode of glacial deposition on a large scale, but this evaluation attempts to draw some inferences based on glacial processes. A potential reason for the changing N values with depth may be a transition in the glacial depositional processes being represented in the diamictons.

Sediments deposited at the base of a glacier tend to have higher basal density, especially if pore water is driven out of the sediments by glacial loading (Boulton, 1982; Boulton et al., 2001; Menzies and Shilts, 2002). Tills that are deposited under greater basal stresses will usually have greater consolidation and density; lodgement tills usually are highly consolidated as compared to melt-out or ablation tills (Boulton, 1976; Dreimanis, 1988).

The Darby Till in this area has been interpreted as an ablation till, and the N values are

generally lower near the surface, which may indicate the lower stress conditions found

from a thinner ice sheet or upon active melting. If the Darby Till is truly an ablational

till, the lower concentration of gravel generally found near the surface may indicate that it 177

is a subglacial melt-out till, rather than a supraglacial melt-out till. The latter usually has

a coarser texture, whereas subglacial melt-out till generally is indistinguishable from

lodgement or deformation tills and contains a wide range of particle sizes. Although

diamicton density generally increases with depth and down boring profiles of N values generally are similar for adjacent borings, N values vary significantly in detail. This variability challenges a common perception that tills are deposited as sheets with a certain degree of uniformity, something current research contradicts (Kjær et al., 2003).

The difference in Atterberg limits between the diamictons in the carbonate and clastic regions probably reflects the differences in source material. The slightly lower liquid limit and plasticity index for the carbonate region is most likely due to the lower

amount of clay and greater amounts of silt. The values for the clastic region show

increases probably due to the slightly greater proportion of clay. The clastic region has

much higher standard deviations possibly because of differences in shale versus

sandstone as source materials of the tills; the standard deviations for the diamictons in the

carbonate area indicate homogeneity in the source material as the dolomite and limestone

are likely limited in their contribution to the silt and clay fraction of the tills. The higher

liquid limits and plasticity indexes near the surface are either a consequence of greater

weathering of parent materials, resulting in higher proportions of clay, or a different

depositional process occurring nearer to the surface. The bedrock-derived components

that form much of the tills in the clastic region may contain more materials from the

dominantly shale bedrock, and weathered to particular clays that have higher Atterberg

values. Particular clay mineralogies and Atterberg limits have been correlated (Sun,

1975; Schmitz et al, 2004). Because there is some noticeable difference in the values 178

between the two bedrock regions, the difference is likely caused by a difference in till

source materials. A difference in bedrock as a source material has been demonstrated to

be an important factor in the clay mineralogy composition of glacial tills of Ohio and elsewhere (Wilding et al., 1971; Volpi and Szabo, 1988; Peuraniemi et al., 1997).

The plots of texture show that the one significant variable in these deposits is the proportion of gravel. Other studies also conclude that the tills in this area have a

consistent matrix with different amounts of gravel, with the clasts varying in both

composition and size (May & Dreimanis, 1976; Dreimanis, 1988). Although the average proportion of gravel is relatively consistent in the till profiles, the overall gravel

component remains somewhat variable from boring to boring. This suggests that a

variety of glacial erosional and depositional processes were active during formation of

these materials.

The tertiary plots that remove the gravel component show small differences in the

average texture of the diamictons found in the two bedrock areas, but a great amount of

local variation is present. Because there is so much spread between data points there is

also the possibility that some of the diamictons that are included in this plot are not true

tills, but are matrix-supported deposits deposited by other glacially associated processes, such as those acting in small lakes. Some differentiation between the tills in the two areas is not unexpected, as the Soil Survey of Franklin County, Ohio (McLoda and

Parkinson, 1977) mentions differences between the till matrix and till clasts for the northeastern third and the southwestern two-thirds of the county. Entrainment of local bedrock material and incorporation into the till is well documented (Szabo and Angle,

1983; Alley et al., 1997), and the tills found in Franklin County are no exception. 179

5.4 Geologic Interpretation

5.4.1 Bedrock Topography

The existing ODNR bedrock topography maps present well-constructed surfaces,

but should be revised as additional data becomes available. One of the primary

limitations of the ODNR maps is the DEM resolution, and it is recommended that

county-specific maps that are released electronically should be at a smaller resolution,

and that a system be available to update them based on new and more accurate data. The

inaccuracies discovered here in the ODNR maps are likely due to the fact that water well

logs are the major source of ODNR’s data. Such logs remain the primary data source

when mapping the bedrock topography of Franklin County and many other counties,

because these logs are so numerous and have excellent spatial distribution. Errors stemming from surface elevations read from topographic maps and bedrock elevations

that cannot easily be confirmed may have led to inaccurate contour intervals derived from

these data. The borings utilized here show enough variation from the ODNR-produced

map to emphasize that reliable sources of bedrock elevations must be incorporated into

future large-scale maps to improve their accuracy.

The bedrock topography map generated in the GIS is consistent with previous

reports, but utilization of the ArcGIS tools demonstrates the presence of additional small

drainage “channels”. Characterizing all of the bedrock erosion processes and timing is

beyond the scope of this project, but the bedrock topography map and the bedrock slope

map assist in conceptualizing the evolution of the surface. The broad, deep bedrock

channels with longer “tributaries” have developed in the more easily eroded Devonian

shales, whereas the narrow, shallow channels with more numerous short “tributaries” are 180

in the more resistant bedrock. The development of the bedrock surface and depositional processes are sometimes linked, as is evident by textural components in the glacial tills and by glacial outwash that is often found in bedrock valleys. These smaller channels suggest that bedrock exposure and erosion of this surface by flowing water occurred from streams during a warmer time prior to the last glacial maximum or by glacial meltwater prior to the Wisconsinan glaciation. Glacial meltwater is among the most efficient sediment transport systems on earth and because these systems often have the ability to remove all available sediment at the bedrock surface (Alley et al, 1997) they also have the potential to erode large amounts of bedrock. Although some of the bedrock drainage is reflective of pre-glacial erosion (Schmidt and Goldthwait, 1958) an overall lowering of the bedrock surface by glacial meltwater, especially within the Devonian shales, is likely.

A visual inspection of the bedrock topography, drainage and slope maps in the southeastern part of the county shows a distinct separation of the valley identified as the

Teays Stage Groveport River from a higher erosional surface to the northwest. This separation implies that the bedrock channel evolution and subsequent deposition may have occurred in stages. This region with deep bedrock erosion contains much of the area where the Lockborne Sand and Gravel is found, which is generally found beneath glacial deposits (Bennett & Williams, 1988). Erosion to form these surfaces probably contributed material to this formation.

5.4.2 Glacial and Non-Glacial Geomorphology

The detailed DEMs of the surface topography generated in this study allow a subjective interpretation of significant surficial processes, both glacial and post-glacial.

Depositional and erosional features, such as end moraines and eroded valleys, have 181

traditionally been inferred from topographic maps, but an inspection of the DEM allows

us to easily visualize such features. The Scioto and Olentangy Rivers have eroded the

bedrock within their upper reaches in the county, and their relatively deep valleys are

apparent on this map. Denudation of the glaciated landscape is visible in the southwestern portion of the county, to a large extent in Big Darby Creek and to a lesser extent for its tributaries such as Hellbranch Run (Figure 5.1). An assessment of the DEM in this area demonstrates that the post-glacial channels have been altered over time, either from a natural migration or by humans. The Scioto Big Run appears to have once included drainage that is now part of another basin. Hellbranch Run has what are likely abandoned channels adjacent to it. In contrast, it appears that Hamilton and Clover Groff

Ditches are engineered systems, with little evidence of erosion within their upper regions.

This is not surprising as channelization is common in the U.S. (Wohl, 2005).

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Figure 5.1: Close up of DEM developed in this study showing current stream channels along with other possible channels. The topography in the area aligned upstream of the current course of the Scioto Big Run suggests that it may have once drained this area, and the Hellbranch Run has nearby erosional surfaces suggesting that it may have changed its course over time. The square-shaped object near the bottom is the Franklin County Sanitary Landfill, and a rock quarry and the interstate highway system are apparent to the west of the Scioto River.

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When visually inspecting the DEMs showing the surface topography, human activity as a geomorphic agent cannot be ignored. Features such as highways, bridge overpasses, airport runways, the currently operating landfill, and gravel pits and rock quarries are apparent (Figure 5.1), indicating that materials classifiable as anthropogenic are common. It is likely that significant additional materials have been lost from this region’s surface due to erosion, occurring from both agriculture and construction activities (Wilkinson and McElroy, 2007). The opposite is also evident, as several locations show a build-up of the surface. This subjective evaluation of changes to the surface agrees with results of other studies, which have found that humans are very efficient at moving surficial materials and bedrock (Hooke, 2000; Wilkinson, 2005).

The glacial geomorphology of this area can be explored further based on the data collected in this report. As is shown in Table 2.1 deposits of the Scioto Sublobe have been divided into multiple tills. There is a consensus that the tills near the surface in

Franklin County are Late Woodfordian, and (with the exception of the Powell Moraine) contain deposits associated with ice advances between 17.4 and 16.0 ka. Most authors have identified the diamictons at the surface as the Darby Till, which has been generally subdivided into the Upper and Lower, with deposits below that as the Caesar Till. These divisions are based primarily on chronology and geomorphology. Although five end moraines are usually associated with this glacial interval, correlation and separation of these tills remains problematic.

Few detailed studies differentiate the Darby and Caesar Tills within Franklin

County, and none cover the whole county. Some of the till separations appear subjective.

Weatherington (1978) separated the two in the northeastern portion of the county based 184

on the Darby being a “yellow clay till” and the Caesar being the lower “blue clay”; the

same differentiation has been made at the Rocky Fork exposure in Gahanna (Goldthwait,

1992). Taylor and Faure (1982) found differences in pebble lithologies in the two tills, and suggested that the Darby is ablational in nature and the Caesar is more representative of a basal or lodgement till; however the textures of the two tills in this study are similar.

Frolking and Szabo (1998) show some differences in texture between the two diamictons but the differences are generally within one standard deviation.

Studies in surrounding counties provide mixed results in attempting to distinguish between the Darby and Caesar Tills. In Ross County, Quinn and Goldthwait (1985) found no textural or compositional differences between the Darby and other tills of the southern Scioto Sublobe. Lloyd (1998) tentatively separated the Darby from the Caesar in central Madison County based on laboratory analysis and core description, although they are very similar in texture and their division is partially based on a coarse-grained layer that is not found in all borings. In Delaware County, Paris (1985) separated the

Darby from Knox Lake/Navarre Tills (sometimes viewed as Caesar equivalents) based on texture and stratigraphic observations.

No consistent differences within or between till deposits in Franklin County are identified in the geotechnical analysis of this study. This may be a consequence of the lack of fabric or detailed lithologic analysis of the deposits, but textural or geotechnical properties cannot be used to differentiate within the diamictons. The thickness of the

Darby is generally reported to range from 5 to 10 m, but this 10 m thickness was exceeded in several of the borings along the two transects. The thickness does not mean that a single till is present; instead, the geotechnical properties are either consistent 185

enough or contain enough natural variation that two tills cannot be identified. Future

studies that identify buried weathered zones or identifiable changes in properties would

provide some of the best evidence for differentiation of tills.

One of the identifiable changes found in the diamictons is that many of the

borings contain one or more significant gravelly zones. Although others have separated

the Darby and Caesar Tills based on a coarse-grained zone (Lloyd, 1998), this differentiation cannot be made based on the data here. The gravelly zones may separate tills, but many investigations of other glacial tills show that coarse-grained materials are commonly incorporated into till layers. Norris (1998) recognized that several borings drilled at the Franklin County Sanitary Landfill primarily contained till, but often included sand and/or gravel zones. He showed that these coarse-grained zones should not be considered continuous, and are a common product of the varying depositional processes that occurred during glaciation. These gravelly zones may identify times of differing glacial deposition, potentially forming during periods of ice sheet changes and greater amounts of melting. It has been observed that higher sediment loads occur in subglacial drainages during seasonal changes, and that periodic deposition of coarse- grained materials occurs during increased drainage (Alley et al., 1997; Swift et al., 2002).

As a result, the coarse-grained zones may represent climate changes that produced additional melting, or may simply result from random deposition of coarse-grained materials entrained within the ice.

The tills at the surface in central Ohio have commonly been interpreted as ablational or melt-out (sometimes these terms are differentiated, but often they are used

interchangeably), lodgement, and deformation. The Darby Till has been interpreted as an 186

ablation till, but with tills it can be difficult to establish a depositional process with any

level of certainty. Melt-out or ablation tills can consist of supra-, en- and subglacial

materials and form at the base of stagnant ice, and often have characteristics that

distinguish them from other types of tills. The upper portions of tills formed by ablation could be expected to contain more sand and/or gravel, as is the case with some supraglacial ablation tills (Brodzikowski and van Loon, 1991), or possibly less silt or clay, as is the case with some melt-out tills (Dreimanis, 1988). Neither of these conditions is found in this study; instead just the opposite relationship is evident in the gravel content. The diamictons evaluated in the geotechnical portion of the study on average contain less gravel near the surface, possibly due to a depositional mechanism but possibly because of increased weathering of these particles near the surface. Other

characteristics that are common in ablation or melt-out tills include lower densities, a thickness of no more than a few meters (unless stacked), and a hummocky surface expression (Dreimanis, 1988; Brodzikowski and van Loon, 1991). Other than lower densities found near the surface of the tills evaluated here, there is no strong evidence that all of these diamictons should be interpreted as ablation or melt-out tills. Some stronger candidates for ablational tills may be found within Franklin County, though. Brockman

(2007) reports that certain areas, such as in the ground moraine near the Big Darby

Creek, contain what appear to be tills associated with glacier ablation, as indicated by the hummocky topography characteristic of this type of deposit (Bennett and Glasser, 1996).

This area also contains a “boulder belt” (Pavey, et al., 1999), which may be a good candidate for a location containing ablation or melt-out till.

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Some of the tills found in the subsurface of this area have been interpreted as

lodgement tills, which usually form at the base of an advancing ice sheet. Lodgement

tills commonly have identifiable fabrics, are sometimes characterized by sheets of up to a

few meters thick, often contain clasts with the same lithology as the native bedrock, and have a higher density than other tills in the same region. High till density is one characteristic that may identify some of the central Ohio tills as lodgement, but other

properties typical of a lodgment till cannot be assessed here.

In recent years there has been a shift in the genetic classification of tills. Tills

came to be viewed as forming from a combination of processes, which makes them less

identifiable (Dreimanis, 1988). In this process-based classification many different types

of tills are now described as deformational (Murray, 1997). The term “deformation till” is primarily used to describe those soft sediments that are deposited at the base of a

glacier while undergoing significant shearing. Deformation till plays a major role in the

movement of an ice sheet. Some authors even question any conventional classifications

of subglacial lodgement or melt-out tills, proposing that most of these are likely some

form of deformation till (Menzies et al., 2006). Some of this reinterpretation of till

deposition is a result of experiments and observations of sediment entrainment at the base

of a glacier. One of the more recent methods used to assess tills that form from

deformable beds or those that form from glaciotectonic processes is the study of

microstructures within the till matrix, which show how the till responded to particular

stresses (Carr and Rose, 2003; Menzies et al., 2006). Not everyone is convinced that the traditional classification schemes should be abandoned (Ruszczynska-Szenajch, 2001),

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and others believe that deforming subglacial sediments are not as common as has been

reported (Piotrowski et al, 2001).

Some characteristics of deformation tills match features observed in the diamictons for Franklin County. Deformation tills are known to form in soft sediments at the base of soft-bedded glaciers (Bennett and Glasser, 1996; Iverson, 2000; Van der

Wateren, 2002; Evans et al, 2006). Deformable beds produce tills that are described as dense and consolidated, containing a diverse range of particle sizes (Bennett and Glasser,

1996). The sediments near the surface may have a reduced density due to structural changes that occur during movement (Evans et al, 2006) and also because of increased water pressures within the pores in the upper portion of the sediment bed (Benn and

Evans, 1996; Boulton et al, 2001). As an ice mass thins, the effective and basal shear stresses are reduced, causing less deformation (Menzies, 2002) and possibly resulting in

lower densities near the surface. These tills are often somewhat homogeneous from the

mixing that occurs due to glaciotectonic activity, such as folding (Alley et al, 1997).

Some deformation tills are thought to form in a melting-ice or ice-marginal phase

(Brodzikowski and van Loon, 1991), and some studies have concluded that deformation

till is the major form of till in the area of the southern Laurentide ice sheet (Alley, 1991).

Deformation tills can be stacked, and Benn and Evans (1996) describe how interbeds of

coarser materials may be found between tills, depending on the changing hydraulic

conditions at the base of the glacier. In addition the shear forces are greater near the

sediment surface, and may be a mechanism by which larger particles are comminuted,

thus resulting in less gravel at the top of the tills in Franklin County. It is also possible

that particular till surfaces were obliterated as the ice sheet advanced and deformation 189

occurred on the surface of existing till sheets. Based on the above criteria, this author

favors the interpretation of most tills in central Ohio to have a deforming till origin.

5.4.3 Lacustrine Deposits

The combination of geotechnical data and bedrock topography points to the

interpretation of certain intervals in some borings as lacustrine deposits. Glacial lakes are

generally classified according to their location relative to the ice sheet and by the source

of water and sediment (Ashley, 2002). Not enough data exists here to definitively

classify the types of lacustrine environments for these sediments or whether they are

glacial in origin at all, but some inferences can be made regarding these and associated deposits. The east-west orientation of the bedrock valleys suggests damming by topography, with the lakes possibly being fed by glacial meltwater from either ice-contact or more distal ice sources. The deposits containing mostly clay indicate a low-energy environment, whereas the silt and fine sand deposits signify a relatively higher energy environment (Teller, 1987; Ashley, 2002). The gravelly zones found beneath the clay deposits indicate either fluvial or glacial deposition prior to lake formation. The diamictons directly above the clayey deposits contain higher proportions of clay when compared to surrounding diamictons. The diamictons found above the clayey deposits interpreted as lacustrine may have been entrained in the subglacial environment, also arguing for deforming bed deposits.

If this interpretation is correct, then additional lacustrine deposits may be found in other east-west oriented bedrock valleys, especially those in the northern end of the county. Lacustrine deposits have been reported throughout the county (see section 2.3.2), so the likelihood of others is not unexpected. Identifying the chronology of the lacustrine 190

deposits from these geotechnical borings does pose a problem, however. Other deposits

in Franklin County interpreted as lacustrine include materials found both at the surface

and at significant depths, containing deposits that are likely pre-Illinoian, post-Illinoian,

and Wisconsinan in age. Because tills are found above the lacustrine deposits for these sets of borings, we know that deposition occurred prior to the last glaciation of Franklin

County, but glacially-fed lakes occur both during the advance and retreat of the ice sheet

(Ashley, 2002). Because one of the geotechnical logs contained a record of organic materials (roots) there is the potential they could be dated using radiocarbon methods. If additional cores were obtained from these deposits one could also look for stratification, such as varves, and sedimentary structures to aid in an interpretation.

Identifying lacustrine deposits in the county primarily has ramifications for development activities. If these deposits are not sufficiently mapped and documented, additional problems could arise. The geotechnical properties of these fine-grained sediments can be quite different from the properties of the diamictons, and could significantly compromise a building’s foundation, as has been discovered in other locations within the county. This geotechnical behavior also could affect many other types of projects, especially those that do not require a thorough geotechnical evaluation of the site such as is the case in residential developments.

5.5 Conclusions

The unconsolidated deposits in Franklin County result from a variety of erosional and depositional mechanisms. Accurate mapping and characterization of these materials is essential to proper land use in this developing area. The continued interpretation of the

191

glacial and post-glacial processes that formed the majority of the surficial deposits is critical to establishing an accurate framework of these materials.

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CHAPTER 6

CONCLUSIONS

6.1 Study Conclusions

• The use of digital technologies and the establishment of an accurate base map

can improve subsurface mapping efforts. The establishment of a GIS provides a

spatial database that can be amended as additional data are made available,

allowing for continuous improvements in geologic maps. In addition, this study

provides a methodology for a more accurate placement of borings on a digital

base map.

• Readily available DEMs from the USGS do not always accurately represent the

current surface elevations. Digital elevation models constructed from current

surface elevation data show considerable differences from DEMs obtained from

the USGS. The differences often come from land surface modifications by

human activities in and around urban areas. Anthropogenic activity seems to be a

significant factor in the current geomorphological development of this area.

• Individuals performing surficial mapping should make an effort to confirm the

surface elevation of geologic borings. There can be a large difference between

the surface elevations represented on a DEM and the starting boring elevation.

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The comparison of DEMs to the surface elevation of borings and to high-

resolution GPS data shows that there can be considerable differences between

surface elevation data sources.

• The accuracy of a DEM can significantly impact the utilization of that DEM for

various purposes. This study shows how the use of two DEMs representing the

same area can affect a particular outcome. The examples shown herein are

subsurface mapping, flood zone mapping, and surface water modeling.

• Well-defined bedrock topography maps are important for understanding the

geomorphology in central Ohio. The bedrock topography maps for this area

should be continuously updated as data become available. Significant changes in

the bedrock topography are found when maps are revised using additional data

sources. Some unconsolidated deposits were evidently affected by the underlying

bedrock surface.

• The geotechnical properties of the glacial tills in this area show some differences

based on whether the till is found on carbonate or clastic bedrock. Small

differences are noticed in the standard penetration test values, Atterberg limits,

and texture for samples taken from the carbonate bedrock areas versus those taken

from the clastic bedrock areas.

• There are few to no consistent variations in the geotechnical properties of the

glacial tills found across this area. The glacial depositional and erosional

processes that were at work in central Ohio were varied enough that no predicable

pattern seems evident among available data. There is no ability to differentiate

glacial tills based on the geotechnical properties evaluated here. 194

• Based on geotechnical data from certain borings, lacustrine or glacio-lacustrine

deposits appear to be present at several locations in northern Franklin County.

Four locations with small buried valleys contain borings with geotechnical

properties that show significant departures from the properties of nearby

diamictons. This differentiation is primarily based upon the high clay or high silt

content, the low sand and gravel content, and the low standard penetration values.

• The current trend of reinterpreting many diamictons as deformation till likely is

appropriate for this area of central Ohio. Particular till properties found here,

such as high densities and a diversity of particle sizes, are consistent with the

deformation till interpretation in the area where the southern Laurentide ice sheet

once resided.

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208

APPENDIX A

BORING LOG DATA

209

Corrected ID ID_No Source X_coord Y_coord Elev. (m)

1 BWSI FRA-COW1A City of Columbus Eng. Report 213.6 1829711.48 667712.71 2 BWSI FRA-COW1B City of Columbus Eng. Report 213.6 1829706.95 667709.30 3 BWSI FRA-COW2A City of Columbus Eng. Report 213.3 1829839.90 667572.49 4 BWSI FRA-COW2B City of Columbus Eng. Report 212.7 1829841.92 667564.91 5 BWSI FRA-COW3A City of Columbus Eng. Report 213.6 6 ODOT FRA-70-0080a ODOT Bridge Boring 280.1 1762668.73 722294.34 7 ODOT FRA-70-0080b ODOT Bridge Boring 278.5 1762940.75 722514.46 8 ODOT FRA-70-0138a ODOT Bridge Boring 282.0 1766071.05 722049.50 9 ODOT FRA-70-0138b ODOT Bridge Boring 282.9 1765757.74 722291.17 10 ODOT FRA-70-0261a ODOT Bridge Boring 284.4 1772315.60 721627.22 11 ODOT FRA-70-0261b ODOT Bridge Boring 285.0 1772246.12 721909.30 12 ODOT FRA-70-0329a ODOT Bridge Boring 280.0 1775870.89 721595.35 13 ODOT FRA-70-0329b ODOT Bridge Boring 280.5 1775915.93 721438.19 14 BWSI FRA-COW3B City of Columbus Eng. Report 213.5 1829726.91 667575.45 15 BWSI FRA-COW5A City of Columbus Eng. Report 214.3 1829076.89 667415.34 16 BWSI FRA-COW5B City of Columbus Eng. Report 214.2 1829074.12 667410.71 17 BWSI FRA-COW6A City of Columbus Eng. Report 213.1 1829981.68 667379.23 18 BWSI FRA-COW6B City of Columbus Eng. Report 213.1 1829979.33 667374.03 19 ODOT FRA-70-0381a ODOT Bridge Boring 283.4 1778674.20 721186.26 20 ODOT FRA-70-0381b ODOT Bridge Boring 284.0 1778592.24 721414.10 21 ODOT FRA-70-0417a ODOT Bridge Boring 281.8 1780463.40 721129.21 22 ODOT FRA-70-0417b ODOT Bridge Boring 282.3 1780618.46 721268.14 23 BWSI FRA-COW7A City of Columbus Eng. Report 212.9 1830761.95 667601.66 24 BWSI FRA-COW7B City of Columbus Eng. Report 212.9 1830762.27 667608.95 25 BWSI FRA-B-2 City of Columbus Eng. Report 215.6 1830980.00 667838.09 26 BWSI FRA-COW11S City of Columbus Eng. Report 226.8 1842960.72 667088.22 27 BWSI FRA-COW10D City of Columbus Eng. Report 226.6 1842847.51 667094.38 28 ODOT FRA-70-0525a ODOT Bridge Boring 285.0 1786285.21 720642.15 29 ODOT FRA-70-0525b ODOT Bridge Boring 284.3 1786170.99 720910.01 30 ODOT FRA-Hubbard Rd a ODOT Bridge Boring 282.3 1763089.25 713907.16 31 ODOT FRA-Hubbard Rd b ODOT Bridge Boring 281.8 1763195.15 713805.93 32 ODOT FRA-Roberts Rd a ODOT Bridge Boring 263.6 1758467.50 721956.22 33 ODOT FRA-Roberts Rd b ODOT Bridge Boring 264.2 1758655.71 722047.82 34 BWSI FRA-COW10D1 City of Columbus Eng. Report 226.7 1842870.03 667094.60 35 BWSI FRA-COW11D City of Columbus Eng. Report 226.7 1842960.68 667097.26 36 BWSI FRA-COW9D City of Columbus Eng. Report 226.4 1842692.08 667108.82 37 BWSI FRA-COW9A City of Columbus Eng. Report 226.6 1842766.25 667095.36 38 BWSI FRA-COW12 City of Columbus Eng. Report 226.2 1843370.39 667057.13 39 BWSI FRA-COW13 City of Columbus Eng. Report 227.1 1842352.59 667142.66 40 BWSI FRA-COW14 City of Columbus Eng. Report 226.2 1843684.90 667350.80 41 BWSI FRA-SSB1 City of Columbus Eng. Report 226.2 42 BWSI FRA-B12 City of Columbus Eng. Report 224.0 1841380.94 667155.52 43 ODOT FRA-Roberts Rd c ODOT Bridge Boring 265.8 1759349.54 721790.70 44 ODOT FRA-Roberts Rd d ODOT Bridge Boring 265.5 1759428.66 721788.74 210

45 ODOT FRA-270-0542a ODOT Bridge Boring 267.9 1792422.37 747454.55 46 ODOT FRA-270-0542b ODOT Bridge Boring 268.3 1792614.10 747388.03 47 ODOT FRA-270-0693a ODOT Bridge Boring 272.3 1790558.58 756655.51 48 ODOT FRA-270-0693b ODOT Bridge Boring 272.1 1790681.96 756649.35 49 ODOT FRA-270-0772a ODOT Bridge Boring 271.6 1789961.00 759335.20 50 ODOT FRA-270-0772b ODOT Bridge Boring 270.7 1790179.84 759370.83 51 ODOT FRA-270-0774a ODOT Bridge Boring 271.5 1789969.79 759437.45 52 ODOT FRA-270-0774b ODOT Bridge Boring 270.8 1790108.13 759521.20 53 ODOT FRA-270-0886a ODOT Bridge Boring 269.7 1790793.35 765098.10 54 ODOT FRA-270-0886b ODOT Bridge Boring 268.6 1791243.69 765217.16 55 BWSI FRA-B13 City of Columbus Eng. Report 225.9 1841868.92 667187.79 56 BWSI FRA-B8 City of Columbus Eng. Report 221.7 1837194.98 667512.92 57 BWSI FRA-B15 City of Columbus Eng. Report 227.1 1843851.60 667069.90 58 BWSI FRA-B16 City of Columbus Eng. Report 226.6 1843775.67 668443.10 59 BWSI FRA-B10 City of Columbus Eng. Report 224.0 1839363.99 667410.44 60 BWSI FRA-B18 City of Columbus Eng. Report 226.6 1844883.42 666943.54 61 BWSI FRA-B19 City of Columbus Eng. Report 224.8 1846160.38 666905.97 62 BWSI FRA-B20 City of Columbus Eng. Report 225.0 1847044.79 666877.51 63 BWSI FRA-SAB13B City of Columbus Eng. Report 212.2 1833246.32 663565.24 64 BWSI FRA-COW25S City of Columbus Eng. Report 212.4 1833306.29 663496.29 65 BWSI FRA-COW25D City of Columbus Eng. Report 212.4 1833310.47 663495.02 66 BWSI FRA-COW27D City of Columbus Eng. Report 211.7 1833433.37 663815.11 67 BWSI FRA-COW27S City of Columbus Eng. Report 211.8 1833435.93 663811.70 68 BWSI FRA-COW26 City of Columbus Eng. Report 218.1 1832936.90 663311.84 69 BWSI FRA-COW19D City of Columbus Eng. Report 212.8 1833845.69 664094.64 70 BWSI FRA-SAB12A City of Columbus Eng. Report 221.7 1832425.40 662713.80 71 BWSI FRA-COW22 City of Columbus Eng. Report 209.5 1834247.52 663958.46 72 BWSI FRA-COW18 City of Columbus Eng. Report 211.0 1834258.41 664111.61 73 BWSI FRA-SAB20A City of Columbus Eng. Report 212.0 1834791.36 664016.40 74 ODOT FRA-270-0914a ODOT Bridge Boring 267.4 1791771.87 766351.97 75 ODOT FRA-270-0914b ODOT Bridge Boring 267.3 1792007.52 766187.26 76 ODOT FRA-270-0919a ODOT Bridge Boring 266.8 1792138.92 766379.11 77 ODOT FRA-270-0919b ODOT Bridge Boring 264.2 1792086.49 766527.78 78 ODOT FRA-Hilliard-Cementary Rd a ODOT Bridge Boring 284.0 1785136.32 740178.10 79 BWSI FRA-SAB10A City of Columbus Eng. Report 211.8 1830847.50 661966.60 80 BWSI FRA-SAB7 City of Columbus Eng. Report 209.8 1829761.39 662500.48 81 ODOT FRA-Hilliard-Cementary Rd b ODOT Bridge Boring 284.0 1785162.69 740099.72 82 ODOT FRA-3-2501a ODOT Bridge Boring 239.5 1849431.96 761997.64 83 ODOT FRA-3-2501b ODOT Bridge Boring 240.3 1849396.01 762148.21 84 ODOT FRA-3-2356a ODOT Bridge Boring 242.3 1848443.47 754443.81 85 ODOT FRA-3-2356b ODOT Bridge Boring 243.7 1848487.32 754534.45 86 ODOT FRA-Cooke Rd a ODOT Soil/Rock Boring 262.4 1828894.64 745803.38 87 ODOT FRA-Cooke Rd b ODOT Soil/Rock Boring 256.6 1828791.43 745779.57 88 ODOT FRA-270-0205a ODOT Bridge Boring 263.4 1795192.62 729988.93 89 ODOT FRA-270-0205b ODOT Bridge Boring 264.2 1795429.44 729886.75 90 ODOT FRA-3-Hudson St a ODOT Soil/Rock Boring 259.1 1830180.68 734205.27 211

91 ODOT FRA-3-Hudson St b ODOT Soil/Rock Boring 259.2 1829981.98 734218.14 92 ODOT FRA-270-0419a ODOT Bridge Boring 265.1 1793717.00 741091.02 93 ODOT FRA-270-0419b ODOT Bridge Boring 264.7 1793896.61 741205.64 94 ODOT FRA-1-2530a ODOT Bridge Boring 270.3 1829063.74 751304.19 95 ODOT FRA-1-2530b ODOT Bridge Boring 270.3 1829145.87 751245.96 96 ODOT FRA-270-0310a ODOT Bridge Boring 265.8 1794550.67 736784.40 97 ODOT FRA-270-0310b ODOT Bridge Boring 266.5 1794341.16 737264.19 98 ODOT FRA-270-1508a ODOT Bridge Boring 269.9 1823946.03 769548.43 99 ODOT FRA-270-1508b ODOT Bridge Boring 270.9 1824052.31 769798.37 100 ODOT FRA-270-1576a ODOT Bridge Boring 281.0 1827588.82 769540.32 101 ODOT FRA-270-1576b ODOT Bridge Boring 280.7 1827721.36 769375.05 102 ODOT FRA-270-1293a ODOT Bridge Boring 264.7 1812592.12 769524.22 103 ODOT FRA-270-1293b ODOT Bridge Boring 264.8 1812774.98 769377.56 104 ODOT FRA-270-1248a ODOT Bridge Boring 271.2 1810248.15 769313.72 105 ODOT FRA-270-1248b ODOT Bridge Boring 270.9 1810356.71 769167.00 106 ODOT FRA-315-0698a ODOT Bridge Boring 223.8 1819225.52 746040.06 107 ODOT FRA-315-0698b ODOT Bridge Boring 224.0 1819520.73 746042.78 108 ODOT FRA-315-5-20a ODOT Soil/Rock Boring 0.0 109 ODOT FRA-315-5-20b ODOT Soil/Rock Boring 0.0 110 ODOT FRA-315-5-20c ODOT Soil/Rock Boring 0.0 111 ODOT FRA-315-5-20d ODOT Soil/Rock Boring 0.0 112 ODOT FRA-315-5-20e ODOT Soil/Rock Boring 0.0 113 ODOT FRA-315-5-20f ODOT Soil/Rock Boring 0.0 114 ODOT FRA-315-0570a ODOT Bridge Boring 225.2 1819962.50 739850.10 115 ODOT FRA-315-0570b ODOT Bridge Boring 225.5 1820046.55 739994.71 116 ODOT FRA-315-0570c ODOT Bridge Boring 223.1 1820408.98 740288.44 117 ODOT FRA-315-Henderson-a ODOT Bridge Boring 224.8 1819718.23 747750.39 118 ODOT FRA-315-Henderson-b ODOT Bridge Boring 227.4 1820013.90 747813.05 119 ODOT FRA-315-Ramp DH-a ODOT Bridge Boring 231.8 1818779.52 739161.12 120 ODOT FRA-315-Ramp DH-b ODOT Bridge Boring 231.8 1819000.95 739417.79 121 ODOT FRA-315-Ramp DD-a ODOT Bridge Boring 225.5 1819966.21 739808.26 122 ODOT FRA-315-Ramp DD-b ODOT Bridge Boring 225.2 1820139.70 739893.67 123 CCDR FRA-Calumet St-a City of Columbus Eng. Report 255.5 1826279.37 738272.29 124 CCDR FRA-Calumet St-b City of Columbus Eng. Report 245.8 1826332.91 738187.84 125 CCDR FRA-Calumet St-c City of Columbus Eng. Report 244.7 1826391.72 738076.24 126 CCDR FRA-Calumet St-d City of Columbus Eng. Report 253.7 1826396.24 737991.79 127 ODOT FRA-315-Bethel Rd Ext-a ODOT Soil/Rock Boring 225.1 1819590.73 751845.15 128 ODOT FRA-315-Bethel Rd Ext-b ODOT Soil/Rock Boring 224.9 1819775.99 751803.86 129 ODOT FRA-Hayden Run Rd-a ODOT Soil/Rock Boring 251.3 1797341.21 753665.54 130 ODOT FRA-Hayden Run Rd-b ODOT Soil/Rock Boring 243.5 1797956.30 753792.89 131 ODOT FRA-Hayden Run Rd-c ODOT Soil/Rock Boring 240.2 1798080.50 753754.57 132 ODOT FRA-Hayden Run Rd-d ODOT Soil/Rock Boring 232.4 1799035.84 753931.63 133 ODOT FRA-Hayden Run Rd-e ODOT Soil/Rock Boring 237.9 1798200.75 753775.71 134 ODOT FRA-Hayden Run Rd-f ODOT Soil/Rock Boring 230.2 1798400.27 753865.56 135 ODOT FRA-Hayden Run Rd-g ODOT Soil/Rock Boring 230.3 1798623.58 753882.74 136 ODOT FRA-Hayden Run Rd-h ODOT Soil/Rock Boring 230.3 1798821.78 753914.45 212

137 ODOT FRA-Hayden Run Rd-i ODOT Soil/Rock Boring 234.2 1799008.09 753913.13 138 ODOT FRA-E North Broadway-a ODOT Soil/Rock Boring 240.6 1824541.59 740330.11 139 ODOT FRA-E North Broadway-b ODOT Soil/Rock Boring 252.8 1825738.79 740290.91 140 ODOT FRA-E North Broadway-c ODOT Soil/Rock Boring 258.0 1826550.84 740265.35 141 ODOT FRA-E North Broadway-d ODOT Soil/Rock Boring 260.1 1827823.59 740229.42 142 ODOT FRA-Kenny Rd-a ODOT Soil/Rock Boring 245.2 1816393.15 737619.57 143 ODOT FRA-Kenny Rd-b ODOT Soil/Rock Boring 249.8 1815496.15 738956.72 144 ODOT FRA-Kenny Rd-c ODOT Soil/Rock Boring 252.5 1814794.64 739903.98 145 ODOT FRA-Kenny Rd-d ODOT Soil/Rock Boring 250.4 1814252.38 740894.07 146 ODOT FRA-Kenny Rd-e ODOT Soil/Rock Boring 233.0 1818797.70 731629.92 147 ODOT FRA-Kenny Rd-f ODOT Soil/Rock Boring 235.1 1818313.53 732989.54 148 ODOT FRA-Kenny Rd-g ODOT Soil/Rock Boring 236.0 1818088.41 734025.77 149 ODOT FRA-Kenny Rd-h ODOT Soil/Rock Boring 236.0 1817972.28 735231.73 150 ODOT FRA-Kenny Rd-i ODOT Soil/Rock Boring 239.1 1817282.65 736343.60 151 ODOT FRA-Kenny Rd-j ODOT Soil/Rock Boring 241.2 1817062.90 736661.17 152 ODOT FRA-Kenny Rd-k ODOT Soil/Rock Boring 245.2 1816459.91 737411.55 153 ODOT FRA-Kenny Rd-l ODOT Soil/Rock Boring 245.8 1814210.35 741541.17 154 ODOT FRA-Kenny Rd-m ODOT Soil/Rock Boring 242.7 1814231.98 741945.53 155 ODOT FRA-Kenny Rd-n ODOT Soil/Rock Boring 251.9 1814352.27 742754.97 156 ODOT FRA-Fishinger Rd-d ODOT Soil/Rock Boring 256.5 1813650.64 737751.38 157 ODOT FRA-Fishinger Rd-e ODOT Soil/Rock Boring 251.3 1814475.60 737705.18 158 ODOT FRA-Fishinger Rd-f ODOT Soil/Rock Boring 247.0 1815734.03 737522.80 159 ODOT FRA-Henderson Rd-a ODOT Soil/Rock Boring 0.0 1809866.60 748580.58 160 ODOT FRA-Henderson Rd-b ODOT Bridge Boring 246.5 1816083.60 748212.86 161 ODOT FRA-Henderson Rd-c ODOT Soil/Rock Boring 0.0 1813235.17 748305.43 162 ODOT FRA-Henderson Rd-d ODOT Soil/Rock Boring 0.0 1816192.04 748091.20 163 ODOT FRA-Henderson Rd-e ODOT Bridge Boring 247.1 1818188.85 747847.88 164 ODOT FRA-270-1013-a ODOT Bridge Boring 244.7 1796644.49 768666.54 165 ODOT FRA-270-1013-b ODOT Bridge Boring 234.7 1796863.27 768570.21 166 ODOT FRA-270-1013-c ODOT Bridge Boring 233.9 1796989.32 768709.76 167 ODOT FRA-270-1013-d ODOT Bridge Boring 233.3 1797295.43 768685.45 168 ODOT FRA-270-1013-e ODOT Bridge Boring 243.6 1797517.81 768812.40 169 ODOT FRA-270-1114-a ODOT Bridge Boring 275.1 1803063.53 768716.04 170 ODOT FRA-270-1114-b ODOT Bridge Boring 274.8 1803343.92 768631.92 171 ODOT FRA-270-0980-a ODOT Bridge Boring 254.3 1794812.90 768270.85 172 ODOT FRA-270-0233-a ODOT Bridge Boring 266.2 1795078.41 732792.38 173 ODOT FRA-270-0233-b ODOT Bridge Boring 265.9 1794943.77 733082.10 174 ODOT FRA-3-18.31-a ODOT Soil/Rock Boring 247.9 1832275.87 724538.63 175 ODOT FRA-3-18.31-b ODOT Soil/Rock Boring 248.5 1832263.82 724733.73 176 ODOT FRA-3-18.31-c ODOT Soil/Rock Boring 248.5 1832304.77 724783.11 177 ODOT FRA-3-18.31-d ODOT Soil/Rock Boring 248.5 1832319.22 724877.05 178 ODOT FRA-3-16.69-a ODOT Soil/Rock Boring 235.1 1828260.53 720097.32 179 ODOT FRA-3-16.69-b ODOT Soil/Rock Boring 235.1 1828297.86 720124.61 180 ODOT FRA-3-16.69-c ODOT Soil/Rock Boring 235.1 1828271.54 720170.08 181 ODOT FRA-3-17.06-a ODOT Soil/Rock Boring 237.7 1830339.02 719252.00 182 ODOT FRA-3-17.06-b ODOT Soil/Rock Boring 237.6 1830422.27 719149.62 213

183 ODOT FRA-3-17.06-c ODOT Soil/Rock Boring 238.3 1830555.27 718985.04 184 ODOT FRA-3-17.06-d ODOT Bridge Boring 242.9 1832912.00 715723.47 185 ODOT FRA-3-17.06-e ODOT Bridge Boring 242.9 1832940.60 715793.45 186 ODOT FRA-3-17.06-f ODOT Bridge Boring 243.0 1832868.84 716718.59 187 ODOT FRA-3-17.06-g ODOT Bridge Boring 243.1 1832900.83 716819.82 188 ODOT FRA-3-17.06-h ODOT Bridge Boring 243.0 1833033.61 716833.84 189 ODOT FRA-3-17.06-i ODOT Bridge Boring 243.1 1833156.75 716770.30 190 ODOT FRA-3-17.06-j ODOT Bridge Boring 241.6 1833054.39 715730.77 191 ODOT FRA-3-17.06-k ODOT Bridge Boring 242.0 1833032.48 715833.00 192 ODOT FRA-3-17.06-l ODOT Bridge Boring 242.0 1833216.25 715753.90 193 ODOT FRA-3-17.06-m ODOT Bridge Boring 242.0 1833152.35 715837.87 194 ODOT FRA-3-N&W RR-a ODOT Bridge Boring 237.1 1830144.79 719487.90 195 ODOT FRA-3-N&W RR-b ODOT Bridge Boring 237.4 1830233.64 719299.75 196 ODOT FRA-3-2.40-a ODOT Bridge Boring 235.2 1829593.93 719936.32 197 ODOT FRA-3-2.40-b ODOT Bridge Boring 234.1 1829838.53 719666.64 198 ODOT FRA-3-17.06-n ODOT Bridge Boring 242.9 1832790.07 717295.44 199 ODOT FRA-3-17.06-o ODOT Bridge Boring 244.8 1833117.86 717439.08 200 ODOT FRA-3-Weber Rd-a ODOT Bridge Boring 260.6 1829851.74 737646.16 201 ODOT FRA-3-Weber Rd-b ODOT Bridge Boring 260.3 1829974.86 737575.25 202 ODOT FRA-3-18.31-e ODOT Soil/Rock Boring 254.3 1832589.33 727657.72 203 ODOT FRA-Clifton Ave-a ODOT Soil/Rock Boring 231.9 1842955.84 717209.85 204 ODOT FRA-Clifton Ave-b ODOT Soil/Rock Boring 234.2 1843916.46 717336.78 205 ODOT FRA-Clifton Ave-c ODOT Soil/Rock Boring 242.1 1845752.60 717571.89 206 ODOT FRA-3-18.31-f ODOT Bridge Boring 244.9 1832866.75 722044.95 207 ODOT FRA-3-18.31-g ODOT Bridge Boring 244.9 1832665.57 722160.08 208 ODOT FRA-3-1909-a ODOT Bridge Boring 249.3 1832369.58 725027.77 209 ODOT FRA-3-1909-b ODOT Bridge Boring 249.4 1832382.26 725126.19 210 ODOT FRA-3-1909-c ODOT Bridge Boring 250.4 1832481.29 725162.42 211 ODOT FRA-3-1909-d ODOT Bridge Boring 249.8 1832469.21 725262.05 212 ODOT FRA-Fairgrounds-Swine Exhibit-a ODOT Soil/Rock Boring 249.4 1830270.30 727173.67 213 ODOT FRA-Fairgrounds-Swine Exhibit-b ODOT Soil/Rock Boring 249.4 1830145.59 727344.76 214 ODOT FRA-Fairgrounds-Swine Exhibit-c ODOT Soil/Rock Boring 249.4 1830027.27 727488.67 215 ODOT FRA-Fairgrounds-Swine Exhibit-d ODOT Soil/Rock Boring 249.4 1830267.11 727485.47 216 ODOT FRA-200-8-a ODOT Bridge Boring 220.9 1816907.46 688908.92 217 ODOT FRA-200-8-b ODOT Bridge Boring 230.7 1816761.93 689087.90 218 ODOT FRA-200-8-c ODOT Bridge Boring 212.6 1827344.29 683844.78 219 ODOT FRA-200-8-d ODOT Bridge Boring 212.6 1827243.16 683906.83 220 ODOT FRA-104-6.86-a ODOT Bridge Boring 214.7 1821295.97 693612.43 221 ODOT FRA-104-6.86-b ODOT Bridge Boring 214.5 1821252.76 693571.68 222 ODOT FRA-200-0806-a ODOT Bridge Boring 228.7 1816789.43 690201.08 223 ODOT FRA-200-0806-b ODOT Bridge Boring 229.5 1816603.16 689944.28 224 ODOT FRA-200-0822-a ODOT Bridge Boring 229.8 1817279.21 689558.73 225 ODOT FRA-200-0819-a ODOT Bridge Boring 229.2 1817319.54 689721.49 226 ODOT FRA-200-0894-a ODOT Bridge Boring 217.0 1820384.08 687278.72 227 ODOT FRA-200-0894-b ODOT Bridge Boring 217.1 1820384.08 687479.76 228 ODOT FRA-200-0902-a ODOT Bridge Boring 210.3 1820893.15 687107.28 214

229 ODOT FRA-200-0904-a ODOT Bridge Boring 210.5 1820856.98 686937.42 230 ODOT FRA-200-0951-a ODOT Bridge Boring 213.7 1822847.88 685674.24 231 ODOT FRA-200-0952-a ODOT Bridge Boring 207.7 1823099.30 685300.74 232 ODOT FRA-200-0951-b ODOT Bridge Boring 208.7 1823183.91 685436.12 233 ODOT FRA-200-0952-b ODOT Bridge Boring 210.5 1823399.07 685081.96 234 ODOT FRA-200-0976-a ODOT Bridge Boring 210.3 1823858.94 684755.24 235 ODOT FRA-200-0976-b ODOT Bridge Boring 210.6 1823936.67 684841.86 236 ODOT FRA-200-0976-c ODOT Bridge Boring 210.6 1823924.00 684763.45 237 ODOT FRA-200-0976-d ODOT Bridge Boring 210.6 1824003.78 684845.97 238 ODOT FRA-200-1041-a ODOT Bridge Boring 211.6 1827053.64 683364.67 239 ODOT FRA-200-1041-b ODOT Bridge Boring 210.7 1827186.88 683277.83 240 ODOT FRA-270-0000-a ODOT Bridge Boring 268.6 1794995.57 720447.85 241 ODOT FRA-270-0000-b ODOT Bridge Boring 268.4 1795134.80 720555.61 242 ODOT FRA-270-0000-c ODOT Bridge Boring 268.8 1795130.37 720375.13 243 ODOT FRA-270-0013-a ODOT Bridge Boring 268.1 1794914.89 719786.82 244 ODOT FRA-270-0013-b ODOT Bridge Boring 268.0 1795100.67 719715.67 245 ODOT FRA-270-0018-a ODOT Bridge Boring 269.6 1794813.73 721351.53 246 ODOT FRA-270-0018-b ODOT Bridge Boring 269.0 1795127.37 721457.89 247 ODOT FRA-270-0039-a ODOT Bridge Boring 269.7 1794793.38 718445.37 248 ODOT FRA-270-0039-b ODOT Bridge Boring 268.7 1795031.46 718387.18 249 ODOT FRA-270-0060-a ODOT Bridge Boring 267.2 1795034.66 723653.90 250 ODOT FRA-270-0060-b ODOT Bridge Boring 267.0 1795241.84 723643.94 251 ODOT FRA-270-0252-a ODOT Bridge Boring 269.5 1793919.37 707295.00 252 ODOT FRA-270-0252-b ODOT Bridge Boring 268.4 1794096.42 707171.45 253 ODOT FRA-270-0322-a ODOT Bridge Boring 267.2 1793473.42 703572.80 254 ODOT FRA-270-0322-b ODOT Bridge Boring 265.4 1793671.99 703611.65 255 ODOT FRA-270-0372-a ODOT Bridge Boring 269.4 1794553.80 701071.11 256 ODOT FRA-270-0372-b ODOT Bridge Boring 268.4 1794706.48 701351.47 257 ODOT FRA-270-0637-a ODOT Bridge Boring 253.0 1806006.79 693826.11 258 ODOT FRA-270-0637-b ODOT Bridge Boring 252.8 1806076.32 693688.75 259 ODOT FRA-270-0638-a ODOT Bridge Boring 253.1 1806165.84 694079.82 260 ODOT FRA-270-0638-b ODOT Bridge Boring 252.6 1806375.85 694191.08 261 ODOT FRA-270-0651-a ODOT Bridge Boring 250.8 1806962.80 693981.97 262 ODOT FRA-270-0651-b ODOT Bridge Boring 251.2 1806810.34 693892.56 263 ODOT FRA-270-0715-a ODOT Bridge Boring 242.3 1810164.40 693230.05 264 ODOT FRA-270-0715-b ODOT Bridge Boring 241.8 1810165.61 693067.09 265 ODOT FRA-270-0770-a ODOT Bridge Boring 234.3 1812885.30 692283.39 266 ODOT FRA-270-0770-b ODOT Bridge Boring 233.8 1813050.78 692391.54 267 ODOT FRA-315-Third Ave-a ODOT Bridge Boring 215.5 1822193.63 723052.14 268 ODOT FRA-315-Third Ave-b ODOT Bridge Boring 215.3 1822268.66 723122.45 269 ODOT FRA-315-Fifth Ave-a ODOT Bridge Boring 219.6 1821289.38 724884.46 270 ODOT FRA-315-Fifth Ave-b ODOT Bridge Boring 222.7 1821283.41 725300.56 271 ODOT FRA-315-Fifth Ave-c ODOT Bridge Boring 223.4 1821408.69 725594.37 272 ODOT FRA-315-Fifth Ave-d ODOT Bridge Boring 216.6 1821732.33 724736.81 273 ODOT FRA-315-Fifth Ave-e ODOT Bridge Boring 222.1 1821800.93 724256.57 274 ODOT FRA-315-Fifth Ave-f ODOT Bridge Boring 216.0 1821935.16 723822.57 215

275 ODOT FRA-315-Ramp A-a ODOT Bridge Boring 221.9 1822098.10 722573.13 276 ODOT FRA-315-Ramp A-b ODOT Bridge Boring 221.7 1822119.86 722902.05 277 ODOT FRA-315-0061-a ODOT Bridge Boring 222.8 1822105.91 718704.91 278 ODOT FRA-315-0061-b ODOT Bridge Boring 222.8 1822294.42 718670.72 279 ODOT FRA-3R-1470-a ODOT Bridge Boring 216.0 1823362.27 712117.24 280 ODOT FRA-3R-1470-b ODOT Bridge Boring 216.3 1823236.68 712048.17 281 ODOT FRA-3-1614-a ODOT Bridge Boring 220.6 1822303.03 719457.22 282 ODOT FRA-3-1614-b ODOT Bridge Boring 221.4 1822491.39 719529.66 283 ODOT FRA-3-1614-c ODOT Bridge Boring 221.7 1822835.70 719520.29 284 ODOT FRA-670-SR315-a ODOT Bridge Boring 218.5 1821958.76 717386.16 285 ODOT FRA-670-SR315-b ODOT Bridge Boring 221.9 1822016.36 717333.36 286 ODOT FRA-670-SR315-c ODOT Bridge Boring 216.8 1822183.41 717475.45 287 ODOT FRA-670-SR315-d ODOT Bridge Boring 217.7 1822160.37 717543.61 288 ODOT FRA-670-SR315-e ODOT Bridge Boring 214.2 1822277.50 717619.46 289 ODOT FRA-670-SR315-f ODOT Bridge Boring 213.2 1822366.78 717608.90 290 ODOT FRA-670-SR315-g ODOT Bridge Boring 213.3 1822313.98 717714.50 291 ODOT FRA-670-SR315-h ODOT Bridge Boring 218.2 1822422.46 717692.42 292 ODOT FRA-670-SR315-i ODOT Bridge Boring 216.7 1822518.47 717815.31 293 ODOT FRA-670-SR315-j ODOT Bridge Boring 218.7 1822890.01 715405.65 294 ODOT FRA-670-SR315-k ODOT Bridge Boring 209.8 1822905.75 715500.07 295 ODOT FRA-670-SR315-l ODOT Bridge Boring 214.7 1822851.80 715619.22 296 ODOT FRA-670-SR315-m ODOT Bridge Boring 214.7 1822905.75 715699.03 297 ODOT FRA-670-SR315-n ODOT Bridge Boring 215.2 1822870.90 715801.32 298 ODOT FRA-670-SR315-o ODOT Bridge Boring 214.7 1822801.21 715793.46 299 ODOT FRA-670-125-a ODOT Bridge Boring 220.9 1822253.25 718711.09 300 ODOT FRA-670-125-b ODOT Bridge Boring 220.8 1822257.89 718636.76 301 ODOT FRA-670-125-c ODOT Bridge Boring 214.4 1822153.04 718745.60 302 ODOT FRA-670-125-d ODOT Bridge Boring 214.7 1822137.78 718670.61 303 ODOT FRA-670-125-e ODOT Bridge Boring 219.0 1822317.62 718936.72 304 ODOT FRA-670-125-f ODOT Bridge Boring 218.8 1822286.43 718859.07 305 ODOT FRA-70-0678-a ODOT Bridge Boring 270.1 1794405.55 720416.31 306 ODOT FRA-70-0678-b ODOT Bridge Boring 268.9 1794314.20 720572.41 307 USWIS FRA-ATB-18 City of Columbus Eng. Report 249.0 1801813.60 734631.47 308 USWIS FRA-BTB-1 City of Columbus Eng. Report 243.3 1801760.13 734652.33 309 USWIS FRA-ATB-17 City of Columbus Eng. Report 247.2 1801135.25 734944.80 310 USWIS FRA-BTB-2 City of Columbus Eng. Report 246.3 1800775.34 735183.09 311 USWIS FRA-ATB-24 City of Columbus Eng. Report 246.1 1800687.06 735245.44 312 USWIS ATB-16 City of Columbus Eng. Report 247.6 1800486.64 735538.60 313 USWIS FRA-ATB-15 City of Columbus Eng. Report 246.6 1800142.03 736209.17 314 USWIS FRA-ATB-14 City of Columbus Eng. Report 249.6 1799960.94 736789.73 315 USWIS FRA-ATB-13 City of Columbus Eng. Report 250.4 1799823.44 737414.47 316 USWIS FRA-BTB-3 City of Columbus Eng. Report 251.6 1799782.20 737667.60 317 USWIS FRA-ATB-23 City of Columbus Eng. Report 251.5 1799774.33 737748.16 318 USWIS FRA-ATB-12A City of Columbus Eng. Report 251.6 1799746.29 738062.14 319 USWIS FRA-ATB-12 City of Columbus Eng. Report 251.9 1799711.17 738641.61 320 USWIS FRA-ATB-11 City of Columbus Eng. Report 252.2 1799690.34 739124.01 216

321 USWIS FRA-TB-2 City of Columbus Eng. Report 250.4 1799680.09 739309.85 322 USWIS FRA-ATB-10 City of Columbus Eng. Report 252.0 1799647.90 740016.63 323 USWIS FRA-TB-2A City of Columbus Eng. Report 250.4 1799644.97 740657.56 324 USWIS FRA-TB-15 City of Columbus Eng. Report 250.0 1799637.66 740809.74 325 USWIS FRA-BTB-4 City of Columbus Eng. Report 249.9 1799634.73 740875.59 326 USWIS FRA-BTB-4R City of Columbus Eng. Report 249.9 1799630.34 740964.40 327 USWIS FRA-TB-16 City of Columbus Eng. Report 248.3 1799613.06 741459.09 328 USWIS FRA-TB-17 City of Columbus Eng. Report 246.6 1799596.59 741828.67 329 USWIS FRA-ATB-2 City of Columbus Eng. Report 246.3 1799592.48 742138.98 330 USWIS FRA-TB-3 City of Columbus Eng. Report 247.0 1799589.19 742241.87 331 USWIS FRA-TB-18 City of Columbus Eng. Report 247.5 1799585.89 742342.29 332 USWIS FRA-TB-19 City of Columbus Eng. Report 248.4 1799571.08 742826.28 333 USWIS FRA-ATB-3 City of Columbus Eng. Report 249.0 1799564.49 743002.42 334 USWIS FRA-TB-20 City of Columbus Eng. Report 248.4 1799563.67 743052.63 335 USWIS FRA-ATB-4 City of Columbus Eng. Report 248.4 1799560.38 743200.79 336 USWIS FRA-TB-21 City of Columbus Eng. Report 248.4 1799556.26 743327.55 337 USWIS FRA-BTB-5 City of Columbus Eng. Report 248.4 1799555.64 743340.57 338 USWIS FRA-TB-22 City of Columbus Eng. Report 248.9 1799545.92 743697.54 339 USWIS FRA-TB-23 City of Columbus Eng. Report 248.4 1799536.04 743970.05 340 USWIS BTB-6 City of Columbus Eng. Report 249.0 1799531.93 744186.53 341 USWIS FRA-TB-24 City of Columbus Eng. Report 248.5 1799529.46 744279.54 342 USWIS FRA-TB-25 City of Columbus Eng. Report 249.4 1799512.39 744648.37 343 USWIS FRA-TB-4 City of Columbus Eng. Report 249.1 1799497.57 745019.59 344 USWIS FRA-ATB-21 City of Columbus Eng. Report 249.3 1799490.16 745179.28 345 USWIS FRA-ATB-5 City of Columbus Eng. Report 249.2 1799486.05 745254.18 346 USWIS FRA-ATB-20 City of Columbus Eng. Report 249.2 1799485.22 745274.76 347 USWIS FRA-TB-26 City of Columbus Eng. Report 248.8 1799481.11 745351.31 348 USWIS FRA-ATB-6 City of Columbus Eng. Report 247.5 1799473.70 745449.26 349 USWIS FRA-ATB-7 City of Columbus Eng. Report 248.8 1799472.05 745534.86 350 USWIS FRA-TB-27 City of Columbus Eng. Report 247.3 1799464.65 745701.95 351 USWIS FRA-TB-28 City of Columbus Eng. Report 248.4 1799422.67 746126.68 352 USWIS FRA-BTB-8 City of Columbus Eng. Report 249.1 1799329.66 746418.06 353 USWIS FRA-TB-29 City of Columbus Eng. Report 248.9 1799308.26 746481.44 354 USWIS FRA-TB-30 City of Columbus Eng. Report 249.4 1799199.60 746823.03 355 USWIS FRA-TB-31 City of Columbus Eng. Report 249.0 1799060.50 747282.33 356 USWIS FRA-BTB-9 City of Columbus Eng. Report 249.4 1799039.10 747344.06 357 USWIS FRA-TB-32 City of Columbus Eng. Report 248.5 1798940.32 747665.90 358 USWIS FRA-TB-33 City of Columbus Eng. Report 247.6 1798820.15 748100.50 359 USWIS FRA-TB-5 City of Columbus Eng. Report 246.7 1798780.64 748256.07 360 USWIS FRA-TB-34 City of Columbus Eng. Report 246.5 1798730.43 748448.68 361 USWIS FRA-BTB-10 City of Columbus Eng. Report 248.5 1798632.48 748814.14 362 USWIS FRA-TB-35 City of Columbus Eng. Report 248.3 1798607.79 748913.73 363 USWIS FRA-BTB-11 City of Columbus Eng. Report 248.0 1798490.91 749264.38 364 USWIS FRA-TB-36 City of Columbus Eng. Report 249.8 1798405.30 749417.48 365 USWIS FRA-ATB-19 City of Columbus Eng. Report 253.9 1798198.70 749787.88 366 USWIS FRA-TB-37 City of Columbus Eng. Report 250.8 1798148.49 749877.60 217

367 USWIS FRA-ATB-8 City of Columbus Eng. Report 250.7 1798096.64 749975.55 368 USWIS FRA-ATB-22 City of Columbus Eng. Report 250.9 1798055.48 750051.27 369 USWIS FRA-ATB-9 City of Columbus Eng. Report 251.0 1798021.73 750114.65 370 USWIS FRA-TB-38 City of Columbus Eng. Report 251.3 1797965.76 750218.37 371 USWIS FRA-BTB-12 City of Columbus Eng. Report 251.2 1797833.24 750462.01 372 USWIS FRA-TB-39 City of Columbus Eng. Report 251.4 1797774.80 750569.83 373 USWIS FRA-TB-6 City of Columbus Eng. Report 250.4 1797571.49 750959.17 374 USWIS FRA-BTB-13 City of Columbus Eng. Report 251.0 1797467.78 751229.97 375 USWIS FRA-TB-40 City of Columbus Eng. Report 250.8 1797457.90 751253.84 376 USWIS FRA-TB-41 City of Columbus Eng. Report 253.3 1797321.26 751623.42 377 USWIS FRA-BTB-14 City of Columbus Eng. Report 253.7 1797235.66 751968.30 378 USWIS FRA-TB-42 City of Columbus Eng. Report 253.8 1797229.08 752014.40 379 USWIS FRA-TB-43 City of Columbus Eng. Report 254.4 1797192.04 752414.43 380 USWIS FRA-TB-44 City of Columbus Eng. Report 255.3 1797150.88 752732.97 381 USWIS FRA-BTB-15 City of Columbus Eng. Report 255.7 1797125.36 752966.74 382 USWIS FRA-TB-45 City of Columbus Eng. Report 256.0 1797102.32 753159.34 383 USWIS FRA-TB-46 City of Columbus Eng. Report 255.5 1797051.28 753574.19 384 USWIS FRA-BTB-16 City of Columbus Eng. Report 255.8 1796983.79 753947.88 385 USWIS FRA-TB-47 City of Columbus Eng. Report 255.6 1796957.45 754212.93 386 USWIS FRA-TB-48 City of Columbus Eng. Report 255.5 1796928.64 754465.62 387 USWIS FRA-TB-7 City of Columbus Eng. Report 254.9 1796923.70 754533.94 388 USWIS FRA-BTB-17 City of Columbus Eng. Report 255.4 1796894.89 754907.63 389 USWIS FRA-TB-49 City of Columbus Eng. Report 254.6 1796890.78 754958.67 390 USWIS FRA-TB-50 City of Columbus Eng. Report 254.4 1796856.21 755448.42 391 USWIS FRA-TB-51 City of Columbus Eng. Report 254.9 1796843.86 755800.71 392 USWIS FRA-TB-52 City of Columbus Eng. Report 255.0 1796822.46 756185.10 393 USWIS FRA-TB-8 City of Columbus Eng. Report 254.6 1796800.23 756569.49 394 USWIS FRA-BTB-18 City of Columbus Eng. Report 254.9 1796800.23 756594.19 395 ODOT FRA-3-2201-a ODOT Bridge Boring 263.2 1829878.68 740153.75 396 ODOT FRA-3-2201-b ODOT Bridge Boring 263.4 1830066.86 740069.07 397 ODOT FRA-270-2182-a ODOT Bridge Boring 258.5 1854489.86 758761.92 398 ODOT FRA-270-2182-b ODOT Bridge Boring 258.0 1854662.51 758637.42 399 ODOT FRA-62-0149-a ODOT Bridge Boring 247.8 1858162.13 735367.75 400 ODOT FRA-62-0149-b ODOT Bridge Boring 248.1 1858258.01 735288.99 401 ODOT FRA-62-2095-a ODOT Bridge Boring 247.2 1852910.14 731295.57 402 ODOT FRA-62-2095-b ODOT Bridge Boring 247.7 1853046.61 731640.34 403 ODOT FRA-62-2142-a ODOT Bridge Boring 250.1 1854544.11 733020.32 404 ODOT FRA-62-2142-b ODOT Bridge Boring 249.5 1854569.01 732902.02 405 ODOT FRA-62-2142-c ODOT Bridge Boring 250.2 1854693.55 732702.76 406 ODOT FRA-62-2142-d ODOT Bridge Boring 249.8 1854712.23 732628.04 407 ODOT FRA-62-2142-e ODOT Bridge Boring 250.1 1854388.44 733182.22 408 ODOT FRA-62-2181-a ODOT Bridge Boring 251.9 1855917.76 734932.67 409 ODOT FRA-62-2181-b ODOT Bridge Boring 252.2 1855886.73 734787.85 410 ODOT FRA-62-2284-a ODOT Bridge Boring 242.3 1861936.59 735585.47 411 ODOT FRA-62-2284-b ODOT Bridge Boring 241.8 1862149.25 735512.26 412 ODOT FRA-161-1511-a ODOT Bridge Boring 238.8 1851015.15 758312.78 218

413 ODOT FRA-161-1511-b ODOT Bridge Boring 239.1 1851230.20 758346.40 414 ODOT FRA-161-Sunbury Rd-a ODOT Bridge Boring 255.5 1857832.03 758451.79 415 ODOT FRA-161-Sunbury Rd-b ODOT Bridge Boring 254.6 1857655.59 758420.47 416 ODOT FRA-161-Big Walnut Creek-a ODOT Bridge Boring 248.4 1858961.81 758086.21 417 ODOT FRA-161-Big Walnut Creek-b ODOT Bridge Boring 253.3 1859215.51 757928.83 418 ODOT FRA-270-1701-a ODOT Bridge Boring 280.1 1834117.35 769139.15 419 ODOT FRA-270-1701-b ODOT Bridge Boring 279.7 1834144.61 769009.76 420 ODOT FRA-270-1617-a ODOT Bridge Boring 281.4 1829616.35 769268.91 421 ODOT FRA-270-1617-b ODOT Bridge Boring 282.8 1829815.28 769405.48 422 ODOT FRA-270-1713-a ODOT Bridge Boring 277.1 1834750.04 768953.62 423 ODOT FRA-270-1713-b ODOT Bridge Boring 276.2 1835089.59 769124.44 424 ODOT FRA-270-1729-a ODOT Bridge Boring 275.3 1835596.44 768991.31 425 ODOT FRA-270-1729-b ODOT Bridge Boring 274.9 1835714.79 768912.81 426 ODOT FRA-270-1731-a ODOT Bridge Boring 275.9 1835571.87 769342.67 427 ODOT FRA-270-1731-b ODOT Bridge Boring 276.5 1835667.77 769143.94 428 ODOT FRA-270-1803-a ODOT Bridge Boring 273.3 1839254.61 768020.32 429 ODOT FRA-270-1803-b ODOT Bridge Boring 271.8 1839524.69 768133.36 430 ODOT FRA-270-1868-a ODOT Bridge Boring 264.1 1842731.02 767089.65 431 ODOT FRA-270-1868-b ODOT Bridge Boring 263.5 1842799.29 767286.21 432 ODOT FRA-270-1922-a ODOT Bridge Boring 256.1 1845530.60 766376.89 433 ODOT FRA-270-1922-b ODOT Bridge Boring 255.8 1845391.89 766584.95 434 ODOT FRA-270-1931-a ODOT Bridge Boring 242.9 1845990.10 766261.17 435 ODOT FRA-270-1931-b ODOT Bridge Boring 243.1 1846026.11 766408.60 436 ODOT FRA-270-Penn RR-a ODOT Bridge Boring 249.1 1848738.10 765718.14 437 ODOT FRA-270-SR3-a ODOT Bridge Boring 252.2 1849539.69 765488.73 438 ODOT FRA-270-SR3-b ODOT Bridge Boring 251.8 1849619.72 765284.66 439 ODOT FRA-270-2089-a ODOT Bridge Boring 259.9 1853563.29 763317.60 440 ODOT FRA-270-2089-b ODOT Bridge Boring 259.1 1853643.45 763365.61 441 ODOT FRA-270-2089-c ODOT Bridge Boring 260.1 1853760.17 763312.32 442 ODOT FRA-270-CDN Ramp A-a ODOT Soil/Rock Boring 261.1 1855484.34 749799.90 443 ODOT FRA-270-CDN Ramp A-b ODOT Soil/Rock Boring 261.7 1855442.51 749967.20 444 ODOT FRA-270-CDN Ramp A-c ODOT Soil/Rock Boring 260.9 1855531.09 750132.05 445 ODOT FRA-270-CDN Ramp A-d ODOT Soil/Rock Boring 261.2 1855420.37 750232.92 446 ODOT FRA-270-CDN Ramp B-a ODOT Soil/Rock Boring 257.6 1855873.69 747686.73 447 ODOT FRA-270-CDN Ramp B-b ODOT Soil/Rock Boring 256.2 1855864.47 747731.02 448 ODOT FRA-270-CDN Ramp B-c ODOT Soil/Rock Boring 257.3 1855851.55 747828.82 449 ODOT FRA-270-CDN Ramp B-d ODOT Soil/Rock Boring 256.3 1855840.48 747932.16 450 ODOT FRA-270-CDN Ramp B-e ODOT Soil/Rock Boring 258.1 1855840.48 748037.34 451 ODOT FRA-270-CDN Ramp B-f ODOT Soil/Rock Boring 258.8 1855831.25 748142.52 452 ODOT FRA-270-CDN Ramp B-g ODOT Soil/Rock Boring 258.3 1855806.65 748225.25 453 ODOT FRA-270-CDN Ramp B-h ODOT Soil/Rock Boring 258.3 1855782.05 748326.13 454 ODOT FRA-270-CDN Ramp B-i ODOT Soil/Rock Boring 258.3 1855764.82 748439.30 455 ODOT FRA-270-CDN Ramp B-j ODOT Soil/Rock Boring 258.7 1855745.14 748540.18 456 ODOT FRA-270-CDN Ramp B-k ODOT Soil/Rock Boring 260.6 1855725.46 748655.82 457 ODOT FRA-270-CDN Ramp B-l ODOT Soil/Rock Boring 261.3 1855725.46 748737.01 458 ODOT FRA-270-CDS-a ODOT Bridge Boring 259.6 1855516.32 749659.65 219

459 ODOT FRA-270-CDS-b ODOT Bridge Boring 260.1 1855454.81 749480.05 460 ODOT FRA-270-2525-a ODOT Bridge Boring 256.0 1855497.97 740799.42 461 ODOT FRA-270-2525-b ODOT Bridge Boring 256.5 1855651.07 740746.06 462 ODOT FRA-270-2667-a ODOT Bridge Boring 249.6 1855748.98 733383.91 463 ODOT FRA-270-2667-b ODOT Bridge Boring 249.8 1855839.38 733274.87 464 ODOT FRA-270-2667-c ODOT Bridge Boring 249.8 1855951.70 733354.87 465 ODOT FRA-270-2680-a ODOT Bridge Boring 248.7 1856040.66 732710.91 466 ODOT FRA-270-2680-b ODOT Bridge Boring 248.8 1856413.32 732766.94 467 ODOT FRA-270-2685-a ODOT Bridge Boring 249.1 1856531.84 732944.64 468 ODOT FRA-270-2685-b ODOT Bridge Boring 249.1 1856629.62 732946.22 469 ODOT FRA-270-2719-a ODOT Bridge Boring 249.1 1858018.96 731950.75 470 ODOT FRA-270-2719-b ODOT Bridge Boring 249.3 1857911.44 731705.29 471 ODOT FRA-Cleveland Ave-a ODOT Bridge Boring 250.0 1842954.07 771590.35 472 ODOT FRA-Cleveland Ave-b ODOT Bridge Boring 249.1 1843045.23 771594.29 473 ODOT FRA-Agler Rd-a ODOT Bridge Boring 249.6 1854692.79 736040.24 474 ODOT FRA-Agler Rd-b ODOT Bridge Boring 249.7 1854692.79 735997.39 475 ODOT FRA-Seventeenth Ave-a ODOT Bridge Boring 258.7 1837961.18 728762.11 476 ODOT FRA-Seventeenth Ave-b ODOT Bridge Boring 258.4 1838162.88 728688.43 477 ODOT FRA-BLE-82-Schrock Rd-a ODOT Bridge Boring 242.5 1845563.61 768975.29 478 ODOT FRA-BLE-82-Schrock Rd-b ODOT Bridge Boring 242.6 1845506.78 769024.81 479 ODOT FRA-BLE-82-Schrock Rd-c ODOT Bridge Boring 242.0 1845483.15 768962.91 480 ODOT FRA-BLE-82-Schrock Rd-d ODOT Bridge Boring 242.2 1845405.50 769031.00 481 ODOT FRA-BLE-82-Schrock Rd-e ODOT Bridge Boring 244.6 1845300.27 768978.10 482 ODOT FRA-Schrock Rd-a ODOT Bridge Boring 260.6 1856151.85 767053.25 483 ODOT FRA-Schrock Rd-b ODOT Bridge Boring 257.8 1856250.51 767029.91 484 ODOT FRA-Cooke Road-a ODOT Bridge Boring 264.9 1829004.46 745849.69 485 ODOT FRA-Cooke Road-b ODOT Bridge Boring 262.4 1828894.64 745803.38 486 ODOT FRA-Cooke Road-c ODOT Bridge Boring 259.8 1828812.60 745913.21 487 ODOT FRA-Cooke Road-d ODOT Bridge Boring 256.6 1828791.43 745779.57 488 ODOT FRA-E North Broadway-e ODOT Soil/Rock Boring 262.1 1829017.74 740244.32 489 ODOT FRA-E North Broadway-f ODOT Soil/Rock Boring 263.3 1829161.23 740234.91 490 ODOT FRA-E North Broadway-g ODOT Soil/Rock Boring 262.6 1829024.80 740136.11 491 ODOT FRA-E North Broadway-h ODOT Soil/Rock Boring 262.3 1829205.93 740103.18 492 ODOT FRA-Morse Rd-a ODOT Soil/Rock Boring 268.9 1828589.04 751378.86 493 ODOT FRA-Morse Rd-b ODOT Soil/Rock Boring 268.5 1828594.33 751246.54 494 ODOT FRA-Morse Rd-c ODOT Soil/Rock Boring 270.5 1828589.04 751329.46 495 ODOT FRA-Morse Rd-d ODOT Soil/Rock Boring 270.5 1828668.43 751315.35 496 ODOT FRA-Morse Rd-e ODOT Soil/Rock Boring 269.3 1828673.72 751378.86 497 ODOT FRA-Morse Rd-f ODOT Soil/Rock Boring 269.9 1828671.96 751244.78 498 ODOT FRA-Agler Rd-c ODOT Bridge Boring 233.1 1846285.31 738525.87 499 ODOT FRA-Agler Rd-d ODOT Bridge Boring 232.8 1846699.73 738542.65 500 ODOT FRA-Innis Rd-a ODOT Bridge Boring 234.6 1846897.92 741582.00 501 ODOT FRA-Innis Rd-b ODOT Bridge Boring 234.2 1847124.21 741310.99 502 ODOT FRA-71-3267-a ODOT Bridge Boring 276.1 1835135.71 769761.84 503 ODOT FRA-71-3267-b ODOT Bridge Boring 275.3 1835387.93 769680.99 504 ODOT FRA-3-39.590-a ODOT Bridge Boring 244.8 1848625.12 758496.80 220

505 ODOT FRA-3-39.590-b ODOT Bridge Boring 244.8 1848627.59 758529.49 506 ODOT FRA-3-40.780-a ODOT Bridge Boring 239.5 1849431.96 761997.64 507 ODOT FRA-3-40.780-b ODOT Bridge Boring 240.3 1849396.01 762148.21 508 ODOT FRA-3-40.780-c ODOT Bridge Boring 243.7 1849474.68 762145.08 509 ODOT FRA-161-1796-a ODOT Bridge Boring 296.8 1865790.60 757583.35 510 ODOT FRA-161-1796-b ODOT Bridge Boring 297.6 1865798.72 757685.69 511 ODOT FRA-161-1796-c ODOT Bridge Boring 297.7 1865802.78 757799.29 512 ODOT FRA-161-1875-a ODOT Bridge Boring 296.7 1869422.08 759211.96 513 ODOT FRA-161-1875-b ODOT Bridge Boring 296.3 1869453.43 759143.47 514 ODOT FRA-161-1875-c ODOT Bridge Boring 296.1 1869494.66 759187.43 515 ODOT FRA-161-1875-d ODOT Bridge Boring 296.0 1869480.01 759235.13 516 ODOT FRA-161-1875-e ODOT Bridge Boring 295.8 1869579.15 759196.63 517 ODOT FRA-161-1875-f ODOT Bridge Boring 295.4 1869567.91 759280.78 518 ODOT FRA-161-2051-a ODOT Bridge Boring 306.5 1878135.74 761809.05 519 ODOT FRA-161-2051-b ODOT Bridge Boring 306.8 1878101.33 762009.97 520 ODOT FRA-161-2051-c ODOT Soil/Rock Boring 303.6 1877511.16 762217.26 521 ODOT FRA-161-2051-d ODOT Soil/Rock Boring 308.9 1878660.59 762220.20 522 ODOT FRA-161-2051-e ODOT Soil/Rock Boring 307.7 1878595.91 761541.12 523 ODOT FRA-161-2051-f ODOT Soil/Rock Boring 302.0 1877390.63 761696.93 524 ODOT FRA-161-2051-g ODOT Soil/Rock Boring 303.1 1878066.17 761110.82 525 ODOT FRA-161-2051-h ODOT Soil/Rock Boring 307.6 1878169.10 762709.43 526 ODOT FRA-161-2180-a ODOT Bridge Boring 317.2 1884914.21 760681.32 527 ODOT FRA-161-2180-b ODOT Bridge Boring 317.9 1885084.43 760641.32 528 ODOT FRA-161-2250-a ODOT Bridge Boring 326.7 1887408.74 758075.42 529 ODOT FRA-161-2250-b ODOT Bridge Boring 324.1 1887432.81 758174.31 530 ODOT FRA-161-2250-c ODOT Bridge Boring 322.9 1887458.45 758258.55 531 ODOT FRA-161-2280-a ODOT Bridge Boring 322.0 1888820.28 757909.05 532 ODOT FRA-161-2280-b ODOT Bridge Boring 322.7 1888945.15 757808.59 533 ODOT FRA-270-2824-a ODOT Bridge Boring 238.9 1863451.49 731264.04 534 ODOT FRA-270-2824-b ODOT Bridge Boring 238.6 1863663.41 730961.05 535 ODOT FRA-270-2865-a ODOT Bridge Boring 244.3 1865521.62 730207.95 536 ODOT FRA-270-2865-b ODOT Bridge Boring 245.8 1865441.06 730489.93 537 ODOT FRA-605-0103-a ODOT Bridge Boring 310.7 1881087.26 763445.46 538 ODOT FRA-605-0103-b ODOT Bridge Boring 312.0 1881050.76 763472.53 539 ODOT FRA-PL111-404-a ODOT Bridge Boring 296.9 1873961.66 769192.69 540 ODOT FRA-PL111-404-b ODOT Bridge Boring 296.8 1873995.87 769219.79 541 ODOT FRA-PL111-404-c ODOT Bridge Boring 296.8 1873990.13 769280.86 542 ODOT FRA-PLA190-103-a ODOT Bridge Boring 292.4 1871449.21 762204.00 543 ODOT FRA-PLA190-103-b ODOT Bridge Boring 292.3 1871525.67 762174.44 544 ODOT FRA-PLA190-103-c ODOT Bridge Boring 292.6 1871390.74 762189.54 545 ODOT FRA-PLA190-103-d ODOT Bridge Boring 292.2 1871582.53 762192.75 546 ODOT FRA-Central College Rd-a ODOT Bridge Boring 329.4 1890307.97 763653.50 547 ODOT FRA-Central College Rd-b ODOT Bridge Boring 330.8 1890425.91 763696.50 548 ODOT FRA-Havens Rd-a ODOT Bridge Boring 296.5 1880816.38 739459.15 549 ODOT FRA-Havens Rd-b ODOT Bridge Boring 298.8 1880835.77 739490.97 550 ODOT FRA-Havens Rd-c ODOT Bridge Boring 296.1 1880950.10 739503.39 221

551 FCSLF FRA-MW-1D Franklin Co. San. Landfill Boring 264.6 1797450.10 670791.60 552 FCSLF FRA-MW-6D Franklin Co. San. Landfill Boring 263.2 1797765.50 668162.00 553 FCSLF FRA-SB-16 Franklin Co. San. Landfill Boring 264.7 1795706.00 667972.00 554 FCSLF FRA-SB-17 Franklin Co. San. Landfill Boring 265.0 1796453.00 671007.00 555 FCSLF FRA-SB-18 Franklin Co. San. Landfill Boring 263.2 1797730.00 670958.00 556 FCSLF FRA-SB-19 Franklin Co. San. Landfill Boring 260.0 1799873.00 670632.00 557 FCSLF FRA-SB-20 Franklin Co. San. Landfill Boring 260.2 1800018.00 669194.00 558 FCSLF FRA-SB-21 Franklin Co. San. Landfill Boring 259.2 1800498.00 670548.00 559 FCSLF FRA-MW-4 Franklin Co. San. Landfill Boring 261.4 1799141.00 670188.00 560 FCSLF FRA-MW-7 Franklin Co. San. Landfill Boring 261.9 1799081.00 669323.00 561 FCSLF FRA-MW-8 Franklin Co. San. Landfill Boring 265.2 1796398.00 670133.00 562 FCSLF FRA-MW-9 Franklin Co. San. Landfill Boring 264.4 1796301.00 668410.00 563 FCSLF FRA-MW-12 Franklin Co. San. Landfill Boring 258.8 1800859.00 670959.00 564 FCSLF FRA-MW-13 Franklin Co. San. Landfill Boring 258.2 1801092.00 669390.00 565 FCSLF FRA-MW-14 Franklin Co. San. Landfill Boring 266.0 1794633.00 668104.00 566 FCSLF FRA-MW-15 Franklin Co. San. Landfill Boring 266.4 1795610.00 671461.00 567 FCSLF FRA-MW-2T Franklin Co. San. Landfill Boring 262.7 1798431.29 670977.42 568 FCSLF FRA-MW-4T Franklin Co. San. Landfill Boring 261.4 1799142.27 670177.89 569 FCSLF FRA-MW-9T Franklin Co. San. Landfill Boring 264.5 1796297.58 668402.55 570 FCSLF FRA-MW-14T Franklin Co. San. Landfill Boring 265.9 1794627.15 668083.83 571 FCSLF FRA-PTW-8 Franklin Co. San. Landfill Boring 259.2 1800488.43 670516.47 572 FCSLF FRA-SB-22 Franklin Co. San. Landfill Boring 265.1 1796675.11 672387.07 573 FCSLF FRA-SB-23 Franklin Co. San. Landfill Boring 263.8 1796947.70 667627.57 574 FCSLF FRA-SB-24 Franklin Co. San. Landfill Boring 264.0 1796123.49 667515.50 575 FCSLF FRA-TB-1 Franklin Co. San. Landfill Boring 260.8 1799231.40 668744.90 576 FCSLF FRA-TB-2 Franklin Co. San. Landfill Boring 257.9 1799495.70 668855.20 577 FCSLF FRA-TB-3 Franklin Co. San. Landfill Boring 257.3 1800186.50 669182.70 578 FCSLF FRA-TB-4 Franklin Co. San. Landfill Boring 259.1 1800440.10 669325.20 579 FCSLF FRA-TB-5 Franklin Co. San. Landfill Boring 258.8 1800687.90 669544.80 580 FCSLF FRA-TB-6 Franklin Co. San. Landfill Boring 258.6 1800699.30 669841.70 581 FCSLF FRA-TB-7 Franklin Co. San. Landfill Boring 259.5 1800495.60 669994.10 582 FCSLF FRA-TB-8 Franklin Co. San. Landfill Boring 259.5 1800183.90 669981.60 583 FCSLF FRA-TB-9 Franklin Co. San. Landfill Boring 260.2 1799895.70 669918.80 584 FCSLF FRA-TB-10 Franklin Co. San. Landfill Boring 260.5 1799608.40 669856.60 585 FCSLF FRA-TB-11 Franklin Co. San. Landfill Boring 261.3 1799231.40 669744.90 586 FCSLF FRA-TB-12 Franklin Co. San. Landfill Boring 261.3 1799231.50 669428.10 587 FCSLF FRA-TB-14 Franklin Co. San. Landfill Boring 260.9 1799595.60 669644.80 588 FCSLF FRA-TB-15 Franklin Co. San. Landfill Boring 259.2 1799595.70 669244.90 589 FCSLF FRA-TB-16 Franklin Co. San. Landfill Boring 259.4 1799896.10 669545.00 590 FCSLF FRA-TB-17 Franklin Co. San. Landfill Boring 259.9 1800312.50 669769.70 591 FCSLF FRA-TB-18 Franklin Co. San. Landfill Boring 258.6 1800195.70 669444.80 592 FCSLF FRA-TB-19 Franklin Co. San. Landfill Boring 259.7 1800707.50 670145.50 593 FCSLF FRA-TB-20 Franklin Co. San. Landfill Boring 258.5 1800722.90 670434.50 594 FCSLF FRA-TB-21 Franklin Co. San. Landfill Boring 258.5 1800507.90 670629.30 595 FCSLF FRA-TB-22 Franklin Co. San. Landfill Boring 259.8 1800221.10 670659.50 596 FCSLF FRA-TB-23 Franklin Co. San. Landfill Boring 260.5 1799907.90 670700.50 222

597 FCSLF FRA-TB-24 Franklin Co. San. Landfill Boring 260.9 1799600.70 670734.30 598 FCSLF FRA-TB-25 Franklin Co. San. Landfill Boring 260.1 1799307.90 670772.50 599 FCSLF FRA-TB-26 Franklin Co. San. Landfill Boring 260.8 1799060.10 670802.10 600 FCSLF FRA-TB-27 Franklin Co. San. Landfill Boring 261.7 1799062.70 670486.40 601 FCSLF FRA-TB-28 Franklin Co. San. Landfill Boring 261.2 1799260.00 670025.00 602 FCSLF FRA-TB-29 Franklin Co. San. Landfill Boring 260.9 1799507.90 670286.50 603 FCSLF FRA-TB-30 Franklin Co. San. Landfill Boring 260.4 1799907.90 670286.50 604 FCSLF FRA-TB-31 Franklin Co. San. Landfill Boring 260.2 1800307.90 670286.50 605 ODOT FRA-40-WB East Freeway-a ODOT Bridge Boring 237.2 1832702.46 712513.86 606 ODOT FRA-40-WB East Freeway-b ODOT Bridge Boring 238.5 1832942.75 712649.02 607 ODOT FRA-40-WB East Freeway-c ODOT Bridge Boring 238.2 1833049.45 712559.70 608 ODOT FRA-40-Hamilton Rd-a ODOT Bridge Boring 233.1 1862279.28 704551.53 609 ODOT FRA-40-Hamilton Rd-b ODOT Bridge Boring 233.7 1862212.68 704614.63 610 ODOT FRA-40-James Rd-a ODOT Bridge Boring 233.2 1851772.43 702822.56 611 ODOT FRA-40-James Rd-b ODOT Bridge Boring 233.3 1851831.26 702754.76 612 ODOT FRA-40-Ramp E-a ODOT Bridge Boring 230.7 1842925.44 711724.95 613 ODOT FRA-40-Ramp E-b ODOT Bridge Boring 231.7 1843156.78 711640.39 614 ODOT FRA-40-Ramp E-c ODOT Bridge Boring 231.7 1843185.50 711515.94 615 ODOT FRA-40-Kelton Ave-a ODOT Bridge Boring 236.0 1839834.84 711942.34 616 ODOT FRA-40-Kelton Ave-b ODOT Bridge Boring 236.2 1839826.97 711819.56 617 ODOT FRA-40-Kelton Ave-c ODOT Bridge Boring 236.2 1839818.42 711726.53 618 ODOT FRA-40-Miller Ave-a ODOT Bridge Boring 238.0 1839224.50 711753.42 619 ODOT FRA-40-Miller Ave-b ODOT Bridge Boring 238.3 1839272.72 711856.37 620 ODOT FRA-40-Miller Ave-c ODOT Bridge Boring 238.5 1839237.50 711954.87 621 ODOT FRA-40-Linwood Ave-a ODOT Bridge Boring 240.5 1837992.28 711757.26 622 ODOT FRA-40-Linwood Ave-b ODOT Bridge Boring 240.9 1837964.92 711899.99 623 ODOT FRA-40-Linwood Ave-c ODOT Bridge Boring 240.9 1838011.43 712031.33 624 ODOT FRA-40-Ohio Ave-a ODOT Bridge Boring 240.7 1836423.84 711896.65 625 ODOT FRA-40-Ohio Ave-b ODOT Bridge Boring 241.2 1836431.29 711938.14 626 ODOT FRA-40-Ohio Ave-c ODOT Bridge Boring 241.0 1836432.35 711997.18 627 ODOT FRA-40-Ohio Ave-d ODOT Bridge Boring 241.0 1836402.56 712115.80 628 ODOT FRA-40-18th St-a ODOT Bridge Boring 240.9 1834929.62 712058.68 629 ODOT FRA-40-18th St-b ODOT Bridge Boring 240.9 1834935.87 712199.23 630 ODOT FRA-40-18th St-c ODOT Bridge Boring 241.0 1834943.90 712345.13 631 ODOT FRA-40-High St-a ODOT Bridge Boring 232.9 1828702.04 711614.09 632 ODOT FRA-40-High St-b ODOT Bridge Boring 233.8 1828685.90 711738.51 633 ODOT FRA-40-High St-c ODOT Bridge Boring 234.7 1828666.53 711870.72 634 ODOT FRA-40-Grant Ave-a ODOT Bridge Boring 233.5 1831363.56 712015.37 635 ODOT FRA-40-Grant Ave-b ODOT Bridge Boring 233.4 1831337.59 712206.83 636 ODOT FRA-40-Main St-a ODOT Bridge Boring 239.0 1832988.69 713472.91 637 ODOT FRA-40-Main St-b ODOT Bridge Boring 239.4 1833283.27 713578.34 638 ODOT FRA-40-Alum Creek Dr-a ODOT Bridge Boring 228.5 1843972.33 710972.43 639 ODOT FRA-40-Alum Creek Dr-b ODOT Bridge Boring 229.6 1843961.22 710731.21 640 ODOT FRA-40-Livingston Ave-a ODOT Bridge Boring 230.9 1844058.58 710016.97 641 ODOT FRA-40-Livingston Ave-b ODOT Bridge Boring 231.2 1844180.64 709915.38 642 ODOT FRA-40-1751-a ODOT Bridge Boring 226.5 1847290.75 704246.30 223

643 ODOT FRA-40-1751-b ODOT Bridge Boring 225.6 1847542.32 704104.48 644 ODOT FRA-40-1774-a ODOT Bridge Boring 231.9 1848453.20 703969.74 645 ODOT FRA-40-1774-b ODOT Bridge Boring 231.5 1848708.66 703832.69 646 ODOT FRA-40-James Rd-c ODOT Bridge Boring 234.3 1851925.26 703914.01 647 ODOT FRA-40-James Rd-d ODOT Bridge Boring 234.0 1851913.60 703744.72 648 ODOT FRA-40-1928-a ODOT Bridge Boring 231.4 1856492.77 704606.00 649 ODOT FRA-40-1928-b ODOT Bridge Boring 231.1 1856597.88 704489.97 650 ODOT FRA-40-1996-a ODOT Bridge Boring 233.9 1859973.55 705378.15 651 ODOT FRA-40-1996-b ODOT Bridge Boring 234.2 1860063.70 705347.14 652 ODOT FRA-40-2040-a ODOT Bridge Boring 234.4 1862367.84 705733.65 653 ODOT FRA-40-2040-b ODOT Bridge Boring 233.9 1862350.26 705512.87 654 ODOT FRA-62-1976-a ODOT Bridge Boring 248.7 1847974.87 727518.88 655 ODOT FRA-62-1976-b ODOT Bridge Boring 248.9 1847987.96 727802.18 656 ODOT FRA-71-1830-a ODOT Bridge Boring 246.1 1833025.65 719793.59 657 ODOT FRA-71-1830-b ODOT Bridge Boring 245.3 1833090.93 719769.69 658 ODOT FRA-104-Ped Bridge-a ODOT Bridge Boring 228.4 1835019.14 698582.30 659 ODOT FRA-104-Ped Bridge-b ODOT Bridge Boring 228.6 1835017.34 698491.74 660 ODOT FRA-270-1562-a ODOT Bridge Boring 221.2 1850571.52 685081.24 661 ODOT FRA-270-1562-b ODOT Bridge Boring 220.9 1850815.82 685174.35 662 ODOT FRA-270-1622-a ODOT Bridge Boring 220.7 1852519.07 687557.37 663 ODOT FRA-270-1622-b ODOT Bridge Boring 220.2 1852646.90 687723.93 664 ODOT FRA-270-1634-a ODOT Bridge Boring 219.9 1852860.40 688115.64 665 ODOT FRA-270-1634-b ODOT Bridge Boring 223.0 1853133.54 688116.19 666 ODOT FRA-270-1753-a ODOT Bridge Boring 226.6 1856621.18 692999.03 667 ODOT FRA-270-1753-b ODOT Bridge Boring 226.7 1856873.80 693021.70 668 ODOT FRA-270-1815-a ODOT Bridge Boring 223.8 1858903.48 695623.12 669 ODOT FRA-270-1815-b ODOT Bridge Boring 223.2 1858877.42 695821.12 670 ODOT FRA-270-1780-a ODOT Bridge Boring 229.9 1857630.61 694323.96 671 ODOT FRA-270-1780-b ODOT Bridge Boring 229.9 1857786.23 694179.59 672 ODOT FRA-270-1874-a ODOT Bridge Boring 227.2 1861057.20 697902.78 673 ODOT FRA-270-1874-b ODOT Bridge Boring 227.5 1861220.74 698006.07 674 ODOT FRA-270-1890-a ODOT Bridge Boring 229.8 1861669.45 698377.11 675 ODOT FRA-270-1890-b ODOT Bridge Boring 230.0 1861894.21 698728.11 676 ODOT FRA-317-0069-a ODOT Bridge Boring 226.9 1861616.10 695763.40 677 ODOT FRA-317-0069-b ODOT Bridge Boring 222.8 1861639.76 695962.35 678 ODOT FRA-317-0201-a ODOT Bridge Boring 229.8 1862090.55 702920.33 679 ODOT FRA-670-Third St-a City of Columbus Eng. Report 228.3 1828644.85 718204.57 680 ODOT FRA-670-Third St-b City of Columbus Eng. Report 228.5 1828635.15 718313.43 681 ODOT FRA-670-Third St-c City of Columbus Eng. Report 227.4 1828643.77 718427.67 682 ODOT FRA-670-Third St-d City of Columbus Eng. Report 228.7 1828705.20 718414.74 683 ODOT FRA-670-Third St-e City of Columbus Eng. Report 227.7 1828618.98 718524.67 684 ODOT FRA-670-Third St-f City of Columbus Eng. Report 229.1 1828620.06 718609.81 685 ODOT FRA-670-Third St-g City of Columbus Eng. Report 229.5 1828608.20 718704.65 686 ODOT FRA-670-Third St-h City of Columbus Eng. Report 230.1 1828548.93 718772.55 687 ODOT FRA-670-Third St-i City of Columbus Eng. Report 230.2 1828600.66 718774.71 688 ODOT FRA-670-Third St-j City of Columbus Eng. Report 229.9 1828635.15 718865.24 224

689 ODOT FRA-670-3.93 Cleveland Ave-a ODOT Bridge Boring 239.4 1831315.29 721445.50 690 ODOT FRA-670-3.93 Cleveland Ave-b ODOT Bridge Boring 239.4 1831234.26 721505.44 691 ODOT FRA-670-Nelson Rd-a ODOT Bridge Boring 232.8 1844268.87 721968.14 692 ODOT FRA-670-Nelson Rd-b ODOT Bridge Boring 232.7 1844277.95 721886.91 693 ODOT FRA-670-Nelson Rd-c ODOT Bridge Boring 232.7 1844204.43 721832.90 694 ODOT FRA-670-Nelson Rd-d ODOT Bridge Boring 232.5 1844244.82 721759.84 695 ODOT FRA-670-Nelson Rd-e ODOT Bridge Boring 232.5 1844167.22 721739.87 696 ODOT FRA-670-Nelson Rd-f ODOT Bridge Boring 232.4 1844239.83 721809.76 697 ODOT FRA-670-Nelson Rd-g ODOT Bridge Boring 233.0 1844303.82 721983.57 698 ODOT FRA-670-Sunbury Rd-a ODOT Bridge Boring 239.3 1841908.62 721582.35 699 ODOT FRA-670-Sunbury Rd-b ODOT Bridge Boring 239.5 1841953.60 721666.56 700 ODOT FRA-670-Sunbury Rd-c ODOT Bridge Boring 240.3 1841902.34 721784.77 701 ODOT FRA-670-Sunbury Rd-d ODOT Bridge Boring 239.1 1842075.47 721881.01 702 ODOT FRA-670-Joyce Ave-a ODOT Bridge Boring 255.2 1837264.64 721137.29 703 ODOT FRA-670-Joyce Ave-b ODOT Bridge Boring 252.8 1837346.70 721166.93 704 ODOT FRA-670-Joyce Ave-c ODOT Bridge Boring 250.4 1837310.80 721272.92 705 ODOT FRA-670-Joyce Ave-d ODOT Bridge Boring 251.0 1837286.30 721395.45 706 ODOT FRA-670-Joyce Ave-e ODOT Bridge Boring 251.3 1837368.93 721401.71 707 ODOT FRA-670-Alum Creek-a ODOT Bridge Boring 232.5 1845852.04 724890.28 708 ODOT FRA-670-Alum Creek-b ODOT Bridge Boring 228.8 1845913.88 725111.69 709 ODOT FRA-670-Alum Creek-c ODOT Bridge Boring 228.8 1845855.79 725106.57 710 ODOT FRA-670-Alum Creek-d ODOT Bridge Boring 230.4 1845929.94 725265.11 711 ODOT FRA-670-N&W RR-a ODOT Bridge Boring 248.5 1838289.75 721547.69 712 ODOT FRA-670-N&W RR-b ODOT Bridge Boring 248.3 1838446.84 721498.26 713 ODOT FRA-670-N&W RR-c ODOT Bridge Boring 247.9 1838537.74 721422.36 714 ODOT FRA-670-N&W RR-d ODOT Bridge Boring 248.1 1838416.83 721580.34 715 ODOT FRA-670-N&W RR-e ODOT Bridge Boring 247.9 1838581.87 721601.52 716 ODOT FRA-670-N&W RR-f ODOT Bridge Boring 247.8 1838847.52 721515.03 717 ODOT FRA-670-N&W RR-g ODOT Bridge Boring 247.5 1838689.54 721646.53 718 ODOT FRA-670-N&W RR-h ODOT Bridge Boring 247.1 1838810.45 721601.52 719 ODOT FRA-670-N&W RR-i ODOT Bridge Boring 247.1 1838983.43 721527.39 720 ODOT FRA-5th Ave-Alum Creek-a ODOT Bridge Boring 234.4 1845696.51 723502.97 721 ODOT FRA-5th Ave-Alum Creek-b ODOT Bridge Boring 228.7 1845743.07 723440.90 722 ODOT FRA-5th Ave-Alum Creek-c ODOT Bridge Boring 228.7 1845805.46 723437.34 723 ODOT FRA-5th Ave-Alum Creek-d ODOT Bridge Boring 235.1 1845880.46 723485.84 724 ODOT FRA-670-St Clair Ave-a ODOT Bridge Boring 249.3 1833856.39 720925.64 725 ODOT FRA-670-St Clair Ave-b ODOT Bridge Boring 246.7 1833878.74 721193.80 726 ODOT FRA-670-St Clair Ave-c ODOT Bridge Boring 247.3 1833927.76 721186.59 727 ODOT FRA-670-St Clair Ave-d ODOT Bridge Boring 246.9 1833879.46 721343.02 728 ODOT FRA-670-St Clair Ave-e ODOT Bridge Boring 254.2 1833898.20 721474.22 729 ODOT FRA-670-St Clair Ave-f ODOT Bridge Boring 254.3 1833927.04 721463.41 730 ODOT FRA-Williams Rd-Big Walnut Creek-a ODOT Bridge Boring 217.1 1854883.35 687981.80 731 ODOT FRA-Williams Rd-Big Walnut Creek-b ODOT Bridge Boring 217.1 1855021.39 687985.48 732 ODOT FRA-Williams Rd-Alum Creek-a ODOT Bridge Boring 217.3 1851963.36 688213.81 733 ODOT FRA-Frank Rd-RR & Parsons Ave-a ODOT Bridge Boring 222.9 1831791.01 697635.17 734 ODOT FRA-Frank Rd-RR & Parsons Ave-b ODOT Bridge Boring 225.4 1832078.62 697776.44 225

735 ODOT FRA-Frank Rd-RR & Parsons Ave-c ODOT Bridge Boring 226.0 1832293.70 697772.62 736 ODOT FRA-Frank Rd-RR & Parsons Ave-d ODOT Bridge Boring 227.7 1832510.05 697944.42 737 ODOT FRA-Frank Rd-High St-a ODOT Bridge Boring 223.4 1829512.67 698324.78 738 ODOT FRA-Frank Rd-High St-b ODOT Bridge Boring 223.3 1829599.84 698183.14 739 ODOT FRA-Frank Rd-S Sixth St-a ODOT Bridge Boring 223.7 1831122.71 697745.37 740 ODOT FRA-Frank Rd-S Sixth St-b ODOT Bridge Boring 223.8 1831243.92 697779.76 741 ODOT FRA-Frank Rd-Groveport Rd-a ODOT Bridge Boring 233.5 1833117.86 698229.64 742 ODOT FRA-Frank Rd-Groveport Rd-b ODOT Bridge Boring 234.2 1833245.22 698083.59 743 ODOT FRA-Refugee Rd-Mason Run-a ODOT Bridge Boring 225.2 1858899.02 698093.40 744 ODOT FRA-Refugee Rd-Mason Run-b ODOT Bridge Boring 225.9 1858950.79 698154.67 745 ODOT FRA-17th Ave-Brentnell Ave-a ODOT Bridge Boring 245.3 1842562.56 728626.21 746 ODOT FRA-17th Ave-Brentnell Ave-b ODOT Bridge Boring 245.8 1842673.39 728446.80 747 ODOT FRA-17th Ave-Alum Creek-a ODOT Bridge Boring 235.6 1845544.10 728645.83 748 ODOT FRA-17th Ave-Alum Creek-b ODOT Bridge Boring 230.7 1845873.56 728544.51 749 ODOT FRA-17th Ave-Woodland Ave-a ODOT Bridge Boring 246.1 1841096.83 728727.20 750 ODOT FRA-17th Ave-Woodland Ave-b ODOT Bridge Boring 246.4 1841174.43 728600.51 751 ODOT FRA-33-George Creek-a ODOT Bridge Boring 227.3 1873467.79 678559.68 752 ODOT FRA-33-George Creek-b ODOT Bridge Boring 227.2 1873458.43 678414.81 753 ODOT FRA-33-Tussing Ditch-a ODOT Bridge Boring 231.6 1879706.53 675733.65 754 ODOT FRA-33-Tussing Ditch-b ODOT Bridge Boring 231.8 1879789.64 675774.05 755 ODOT FRA-33-2819-a ODOT Bridge Boring 228.2 1868612.93 681589.50 756 ODOT FRA-33-2819-b ODOT Bridge Boring 227.8 1868847.68 681651.67 757 ODOT FRA-33-2904-a ODOT Bridge Boring 228.7 1872129.16 679339.56 758 ODOT FRA-33-2904-b ODOT Bridge Boring 228.8 1872072.98 679157.41 759 ODOT FRA-33-2997-a ODOT Bridge Boring 230.8 1876418.12 677144.24 760 ODOT FRA-33-2997-b ODOT Bridge Boring 230.7 1876418.12 677144.24 761 ODOT FRA-33-3131-a ODOT Bridge Boring 233.3 1883079.57 674438.75 762 ODOT FRA-33-3131-b ODOT Bridge Boring 232.9 1883077.13 674250.82 763 ODOT FRA-Gender Rd-George Creek-a ODOT Bridge Boring 231.2 1876782.64 680682.42 764 ODOT FRA-Gender Rd-George Creek-b ODOT Bridge Boring 231.9 1876716.92 680743.20 ODOT FRA-Lithopolis Rd-Little Walnut 765 Creek-a ODOT Bridge Boring 222.5 1867632.88 671950.66 ODOT FRA-Lithopolis Rd-Little Walnut 766 Creek-b ODOT Bridge Boring 220.5 1867660.18 671849.65 ODOT FRA-Lithopolis Rd-Little Walnut 767 Creek-c ODOT Bridge Boring 222.1 1867746.77 671746.69 768 ODOT FRA-270-1375-a ODOT Bridge Boring 226.1 1841897.29 682134.73 769 ODOT FRA-270-1375-b ODOT Bridge Boring 226.1 1842089.87 682010.35 770 ODOT FRA-270-1423-a ODOT Bridge Boring 227.9 1844482.70 682050.04 771 ODOT FRA-270-1423-b ODOT Bridge Boring 227.8 1844660.27 681836.59 772 ODOT FRA-270-1465-a ODOT Bridge Boring 227.9 1846752.70 681980.12 773 ODOT FRA-270-1465-b ODOT Bridge Boring 227.4 1846928.48 682206.66 774 ODOT FRA-317-0037-a ODOT Bridge Boring 209.0 1830139.48 667890.38 775 ODOT FRA-317-0037-b ODOT Bridge Boring 209.6 1829992.46 667967.31 776 ODOT FRA-317-0718-a ODOT Bridge Boring 226.3 1856796.45 680178.08 777 ODOT FRA-317-0718-b ODOT Bridge Boring 226.8 1856758.27 680313.78 778 ODOT FRA-317-0807-a ODOT Bridge Boring 221.9 1860524.84 682686.36 779 ODOT FRA-317-0807-b ODOT Bridge Boring 222.8 1860503.22 682865.32

226

780 ODOT FRA-122-Big Walnut Creek-a ODOT Bridge Boring 225.8 1845348.56 676277.54 781 ODOT FRA-122-Big Walnut Creek-b ODOT Bridge Boring 215.6 1845437.26 676378.17 782 ODOT FRA-122-Big Walnut Creek-c ODOT Bridge Boring 217.7 1845358.80 676533.39 783 ODOT FRA-122-Big Walnut Creek-d ODOT Bridge Boring 217.5 1845446.92 676605.60 784 ODOT FRA-Reese Rd-Big Walnut Creek-a ODOT Bridge Boring 211.2 1840171.00 676555.22 ODOT FRA-Lockbourne Rd-Big Walnut 785 Creek-a ODOT Bridge Boring 217.2 1836176.98 673924.11 ODOT FRA-Lockbourne Rd-Big Walnut 786 Creek-b ODOT Bridge Boring 213.8 1836265.44 674024.40 ODOT FRA-Lockbourne Rd-Big Walnut 787 Creek-c ODOT Bridge Boring 214.2 1836210.23 674233.43 ODOT FRA-Lockbourne Rd-Big Walnut 788 Creek-d ODOT Bridge Boring 214.9 1836280.09 674278.50 ODOT FRA-Groveport Rd-Big Walnut 789 Creek-a ODOT Bridge Boring 215.1 1847238.66 680286.02 ODOT FRA-Groveport Rd-Big Walnut 790 Creek-b ODOT Bridge Boring 218.8 1847458.05 680245.72 791 ODOT FRA-16-0801-a ODOT Bridge Boring 246.9 1869109.90 720641.33 792 ODOT FRA-16-0801-b ODOT Bridge Boring 246.9 1869123.14 720746.88 793 ODOT FRA-16-1026-a ODOT Bridge Boring 269.9 1880859.32 722433.54 794 ODOT FRA-16-1026-b ODOT Bridge Boring 274.8 1880993.59 722456.16 795 ODOT FRA-33-2757-a ODOT Bridge Boring 226.9 1866012.44 684167.19 796 ODOT FRA-33-2757-b ODOT Bridge Boring 227.5 1866164.65 683963.03 797 ODOT FRA-40-2115-a ODOT Bridge Boring 229.4 1866192.99 705233.44 798 ODOT FRA-40-2115-b ODOT Bridge Boring 230.2 1866453.43 705217.81 799 ODOT FRA-70-2140-a ODOT Bridge Boring 233.7 1867308.62 704685.77 800 ODOT FRA-70-2140-b ODOT Bridge Boring 233.2 1867598.37 704922.12 801 ODOT FRA-70-2179-a ODOT Bridge Boring 235.1 1869409.47 704515.29 802 ODOT FRA-70-2179-b ODOT Bridge Boring 235.1 1869663.11 704625.76 803 ODOT FRA-70-2179-c ODOT Bridge Boring 237.1 1869569.43 704502.92 804 ODOT FRA-70-2179-d ODOT Bridge Boring 238.3 1869853.13 704663.76 805 ODOT FRA-70-2298-a ODOT Bridge Boring 240.9 1875695.98 704043.86 806 ODOT FRA-70-2298-b ODOT Bridge Boring 241.6 1875709.73 704230.98 807 ODOT FRA-317-1764-a ODOT Bridge Boring 243.3 1865234.59 727496.55 808 ODOT FRA-317-1764-b ODOT Bridge Boring 240.0 1865344.08 727704.00 809 ODOT FRA-270-1946-a ODOT Bridge Boring 227.9 1866051.86 701862.14 810 ODOT FRA-270-1946-b ODOT Bridge Boring 230.6 1866196.93 702136.79 811 ODOT FRA-270-1946-c ODOT Bridge Boring 230.6 1866271.09 702020.25 812 ODOT FRA-270-Retaining Wall-a ODOT Bridge Boring 232.6 1867473.02 703187.35 813 ODOT FRA-70-2200-a ODOT Bridge Boring 240.3 1870557.32 704388.58 814 ODOT FRA-70-2200-b ODOT Bridge Boring 237.7 1870550.50 704467.01 815 ODOT FRA-70-2200-c ODOT Bridge Boring 242.4 1870645.12 704807.14 816 ODOT FRA-270-2063-a ODOT Bridge Boring 237.0 1868789.42 704009.69 817 ODOT FRA-270-2063-b ODOT Bridge Boring 237.0 1869110.63 704010.92 818 ODOT FRA-270-3065-a ODOT Bridge Boring 247.5 1870688.46 720703.12 819 ODOT FRA-270-3065-b ODOT Bridge Boring 246.9 1870567.13 720604.22 820 ODOT FRA-270-2046-a ODOT Bridge Boring 232.3 1868072.41 703492.57 821 ODOT FRA-270-2046-b ODOT Bridge Boring 232.7 1868258.14 703536.30 822 ODOT FRA-270-3073-a ODOT Bridge Boring 247.4 1869227.67 721141.66 823 ODOT FRA-270-3073-b ODOT Bridge Boring 248.2 1869422.81 721250.02 824 ODOT FRA-270-3084-a ODOT Bridge Boring 248.9 1869474.21 720794.89 227

825 ODOT FRA-270-3084-b ODOT Bridge Boring 251.2 1869725.55 720698.05 826 ODOT FRA-270-3272-a ODOT Bridge Boring 242.3 1871782.13 712047.59 827 ODOT FRA-270-3272-b ODOT Bridge Boring 243.9 1871975.25 712069.94 828 ODOT FRA-270-3272-c ODOT Bridge Boring 244.4 1872189.12 712161.71 829 ODOT FRA-270-2982-a ODOT Bridge Boring 249.2 1868707.76 725853.84 830 ODOT FRA-270-2982-b ODOT Bridge Boring 247.8 1868446.91 725795.33 831 ODOT FRA-270-3351-a ODOT Bridge Boring 241.4 1871173.75 707953.15 832 ODOT FRA-270-3351-b ODOT Bridge Boring 241.2 1871453.55 707896.99 833 ODOT FRA-Livingston Ave-Blacklick Ck-a ODOT Bridge Boring 257.4 1884384.45 708809.96 834 ODOT FRA-Livingston Ave-Blacklick Ck-b ODOT Bridge Boring 256.8 1884527.94 708867.80 835 ODOT FRA-Gender Rd-Blacklick Ck-a ODOT Bridge Boring 234.8 1877295.84 693129.46 836 ODOT FRA-Gender Rd-Blacklick Ck-b ODOT Bridge Boring 235.7 1877371.63 693279.45 837 ODOT FRA-Gender Rd-Penn-Central RR-a ODOT Bridge Boring 240.7 1877726.79 697881.73 838 ODOT FRA-Gender Rd-Penn-Central RR-b ODOT Bridge Boring 240.3 1877670.10 698031.47 839 ODOT FRA-Refugee Rd-Blacklick Cr-a ODOT Bridge Boring 237.8 1881855.49 696386.04 840 ODOT FRA-Livingston Ave-Big Walnut Ck-a ODOT Bridge Boring 229.0 1868539.52 708128.24 841 ODOT FRA-Livingston Ave-Big Walnut Ck-b ODOT Bridge Boring 240.0 1868765.70 708058.13 842 ODOT FRA-Refugee Rd-Big Walnut Ck-a ODOT Bridge Boring 229.3 1864411.52 697689.98 843 ODOT FRA-Refugee Rd-Big Walnut Ck-b ODOT Bridge Boring 224.5 1864568.14 697672.52 844 ODOT FRA-Refugee Rd-Big Walnut Ck-c ODOT Bridge Boring 229.3 1864658.42 697702.45 845 ODOT FRA-33-Blacklick Ck-a ODOT Bridge Boring 223.7 1863156.10 686586.26 846 ODOT FRA-33-Blacklick Ck-b ODOT Bridge Boring 225.4 1863221.22 686529.28 847 ODOT FRA-33-Big Walnut Ck-a ODOT Bridge Boring 220.9 1857885.07 691674.33 848 ODOT FRA-33-Big Walnut Ck-b ODOT Bridge Boring 221.3 1858122.66 691509.81 849 ODOT FRA-33-2269-a ODOT Bridge Boring 231.0 1849537.49 702026.02 850 ODOT FRA-33-2269-b ODOT Bridge Boring 232.1 1849673.84 702084.86 851 ODOT FRA-33-2334-a ODOT Bridge Boring 225.1 1850661.27 698724.87 852 ODOT FRA-33-2334-b ODOT Bridge Boring 224.3 1850512.83 698796.77 853 ODOT FRA-33-2491-a ODOT Bridge Boring 227.7 1855669.21 693409.70 854 ODOT FRA-33-2491-b ODOT Bridge Boring 227.5 1855829.17 693565.25 855 Griffin Wheel FRA-B-1 Ohio EPA Report 226.9 1856257.70 682951.22 856 Griffin Wheel FRA-B-2 Ohio EPA Report 228.3 1855805.83 682972.74 857 Griffin Wheel FRA-B-3 Ohio EPA Report 226.7 1855327.06 682992.47 858 Griffin Wheel FRA-B-4 Ohio EPA Report 222.5 1854823.18 683037.30 859 Griffin Wheel FRA-B-5 Ohio EPA Report 227.2 1856293.56 683444.34 860 Griffin Wheel FRA-B-6 Ohio EPA Report 227.8 1855843.48 683474.82 861 Griffin Wheel FRA-B-7 Ohio EPA Report 227.9 1855348.57 683494.55 862 Griffin Wheel FRA-B-8 Ohio EPA Report 221.7 1854855.46 683512.48 863 Georgia-Pacific FRA-MW-9B Ohio EPA Report 233.4 1843720.62 693033.50 864 Georgia-Pacific FRA-BP-1 Ohio EPA Report 233.9 1844015.42 692988.31 865 Georgia-Pacific FRA-BP-2 Ohio EPA Report 234.0 1844318.82 692996.92 866 ODOT FRA-270-0279-a ODOT Bridge Boring 255.4 1793694.52 706119.99 867 ODOT FRA-270-0279-b ODOT Bridge Boring 255.9 1793832.30 706002.02 868 ODOT FRA-270-0279-c ODOT Bridge Boring 254.9 1793663.52 705971.88 869 ODOT FRA-270-0279-d ODOT Bridge Boring 257.0 1793770.30 705747.13 870 ODOT FRA-270-0279-e ODOT Bridge Boring 258.8 1793608.41 705643.80 228

871 ODOT FRA-70-760-a ODOT Bridge Boring 229.8 1810548.25 717589.89 872 ODOT FRA-70-760-b ODOT Bridge Boring 229.3 1810657.23 717698.88 873 ODOT FRA-70-760-c ODOT Bridge Boring 228.3 1810830.48 717805.06 874 ODOT FRA-70-760-d ODOT Bridge Boring 227.8 1811031.67 717894.48 875 ODOT FRA-70-760-e ODOT Bridge Boring 225.2 1811143.45 717958.75 876 ODOT FRA-70-Harrison Rd-a ODOT Bridge Boring 236.5 1809322.48 717686.29 877 ODOT FRA-70-Harrison Rd-b ODOT Bridge Boring 233.8 1809595.66 717761.02 878 ODOT FRA-70-1036-a ODOT Soil/Rock Boring 219.4 1814486.81 715091.96 879 ODOT FRA-70-1036-b ODOT Soil/Rock Boring 219.6 1814636.88 714764.12 880 ODOT FRA-70-1098-a ODOT Soil/Rock Boring 220.7 1818550.15 716867.64 881 ODOT FRA-70-1157-a ODOT Soil/Rock Boring 216.4 1821434.27 716919.02 882 ODOT FRA-71-Stringtown Rd-a ODOT Soil/Rock Boring 236.2 1815249.35 684746.52 883 ODOT FRA-71-Stringtown Rd-b ODOT Bridge Boring 236.6 1814541.48 684735.37 884 ODOT FRA-71-Stringtown Rd-c ODOT Bridge Boring 234.7 1814266.75 684717.46 885 ODOT FRA-71-Stringtown Rd-d ODOT Bridge Boring 237.4 1813990.70 684739.35 886 ODOT FRA-Alkire Rd-B&O RR-a ODOT Bridge Boring 231.0 1808730.22 698239.15 887 ODOT FRA-Alkire Rd-B&O RR-b ODOT Bridge Boring 229.0 1808956.22 698115.39 888 ODOT FRA-Frank Rd-Early Run-a ODOT Bridge Boring 225.6 1813797.69 699452.43 889 ODOT FRA-Frank Rd-Early Run-b ODOT Bridge Boring 224.5 1813841.46 699375.32 890 ODOT FRA-Frank Rd-Whims Ditch-a ODOT Bridge Boring 212.3 1821270.59 697695.95 891 ODOT FRA-Frank Rd-Whims Ditch-b ODOT Bridge Boring 212.0 1821310.96 697764.20 892 ODOT FRA-Georgesville Rd-Big Run-a ODOT Bridge Boring 248.7 1796182.79 705159.86 893 ODOT FRA-Georgesville Rd-Big Run-b ODOT Bridge Boring 251.0 1796135.99 705086.14 894 ODOT FRA-Greenlawn Ave-Scioto River-a ODOT Bridge Boring 219.8 1828012.61 706786.47 895 ODOT FRA-Greenlawn Ave-Scioto River-b ODOT Bridge Boring 220.2 1828024.82 706728.03 896 ODOT FRA-Greenlawn Ave-Scioto River-c ODOT Bridge Boring 213.5 1828072.79 706806.53 897 ODOT FRA-Greenlawn Ave-Scioto River-d ODOT Bridge Boring 213.8 1828071.05 706770.77 898 ODOT FRA-Greenlawn Ave-Scioto River-e ODOT Bridge Boring 212.0 1828119.02 706729.77 899 ODOT FRA-Greenlawn Ave-Scioto River-f ODOT Bridge Boring 211.5 1828132.98 706807.40 900 ODOT FRA-Greenlawn Ave-Scioto River-g ODOT Bridge Boring 210.4 1828204.50 706765.53 901 ODOT FRA-Greenlawn Ave-Scioto River-h ODOT Bridge Boring 209.6 1828216.71 706808.27 902 ODOT FRA-Greenlawn Ave-Scioto River-i ODOT Bridge Boring 209.6 1828312.65 706721.92 903 ODOT FRA-Greenlawn Ave-Scioto River-j ODOT Bridge Boring 209.9 1828318.76 706783.85 904 ODOT FRA-Greenlawn Ave-Scioto River-k ODOT Bridge Boring 0.0 905 ODOT FRA-Greenlawn Ave-Scioto River-l ODOT Bridge Boring 209.8 1828440.87 706794.32 906 ODOT FRA-Greenlawn Ave-Scioto River-m ODOT Bridge Boring 209.8 1828567.34 706800.42 907 ODOT FRA-Greenlawn Ave-Scioto River-n ODOT Bridge Boring 211.0 1828575.19 706723.67 908 ODOT FRA-Greenlawn Ave-Scioto River-o ODOT Bridge Boring 213.9 1828661.54 706759.43 909 ODOT FRA-Greenlawn Ave-Scioto River-p ODOT Bridge Boring 214.2 1828665.90 706799.55 910 ODOT FRA-Greenlawn Ave-Scioto River-q ODOT Bridge Boring 219.6 1828731.32 706718.43 911 ODOT FRA-Greenlawn Ave-Scioto River-r ODOT Bridge Boring 225.8 1828808.07 706803.91 912 ODOT FRA-Greenlawn Ave-Scioto River-s ODOT Bridge Boring 227.4 1828859.53 706762.04 ODOT FRA-Stringtown Rd-Republican Run- 913 a ODOT Bridge Boring 237.4 1811125.14 684673.71 ODOT FRA-Stringtown Rd-Republican Run- 914 b ODOT Bridge Boring 238.8 1811157.16 684786.28 915 ODOT FRA-Trabue Rd-Service Rd-a ODOT Bridge Boring 224.3 1806667.48 728382.63 916 ODOT FRA-Trabue Rd-Service Rd-b ODOT Bridge Boring 226.3 1806850.57 728402.48 229

917 ODOT FRA-Trabue Rd-Scioto River-a ODOT Bridge Boring 226.8 1805970.81 727943.73 918 ODOT FRA-Trabue Rd-Scioto River-b ODOT Bridge Boring 227.0 1806074.31 727945.76 919 ODOT FRA-Trabue Rd-Scioto River-c ODOT Bridge Boring 221.4 1806248.16 728112.17 USWIS FRA-TB-53 920 USWIS TB-53 City of Columbus Eng. Report 254.5 1796745.94 757028.98 921 USWIS FRA-CTB-1 City of Columbus Eng. Report 254.4 1796743.93 757061.17 922 USWIS FRA-TB-54 City of Columbus Eng. Report 254.4 1796721.80 757407.15 923 USWIS FRA-TB-55 City of Columbus Eng. Report 254.4 1796703.70 757801.40 924 USWIS FRA-CTB-2 City of Columbus Eng. Report 254.2 1796695.65 757924.10 925 USWIS FRA-TB-56 City of Columbus Eng. Report 252.2 1796643.35 758247.95 926 USWIS FRA-TB-57 City of Columbus Eng. Report 253.7 1796595.08 758445.08 927 USWIS FRA-TB-58 City of Columbus Eng. Report 252.5 1796528.70 758847.38 928 USWIS FRA-TB-59 City of Columbus Eng. Report 253.1 1796426.11 759297.96 929 USWIS FRA-CTB-3 City of Columbus Eng. Report 253.0 1796405.99 759368.36 930 USWIS FRA-CTB-4 City of Columbus Eng. Report 252.2 1796353.70 759625.83 931 USWIS FRA-TB-60 City of Columbus Eng. Report 252.3 1796365.76 759758.59 932 USWIS FRA-TB-10 City of Columbus Eng. Report 251.3 1796438.18 760418.36 933 USWIS FRA-TB-61 City of Columbus Eng. Report 251.9 1796460.31 760792.50 934 USWIS FRA-CTB-5 City of Columbus Eng. Report 249.6 1796487.13 761351.59 935 USWIS FRA-TB-62 City of Columbus Eng. Report 250.4 1796494.28 761383.77 936 USWIS FRA-TB-63 City of Columbus Eng. Report 245.3 1796589.04 761842.39 937 USWIS FRA-CTB-6 City of Columbus Eng. Report 245.8 1796613.18 761946.99 938 USWIS FRA-TB-64 City of Columbus Eng. Report 245.6 1796768.74 762325.15 939 USWIS FRA-CTB-7 City of Columbus Eng. Report 245.7 1796776.78 762357.34 940 USWIS FRA-ATB-1 City of Columbus Eng. Report 244.2 1796849.20 762539.71 941 USWIS FRA-TB-65 City of Columbus Eng. Report 245.3 1796900.15 762679.18 942 USWIS FRA-CTB-8 City of Columbus Eng. Report 245.4 1797012.80 762963.47 943 USWIS FRA-TB-66 City of Columbus Eng. Report 244.4 1797071.80 763204.85 944 USWIS FRA-TB-11 City of Columbus Eng. Report 244.0 1797072.97 763213.27 945 USWIS FRA-CTB-9 City of Columbus Eng. Report 243.8 1797071.56 763258.31

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