IDENTIFYING BUILDING SITES IN SUMMIT COUNTY, COLORADO: GEOGRAPHY, GEOLOGY, AND GIS
A Thesis
Presented in Partial Fulfillment for
The Degree Masters of Science in
The Graduate School of The Ohio State University
By
Kelly Ann Barrett
*******
The Ohio State University 2009
Master’s Examination Committee:
Dr. Douglas E. Pride, Adviser Approved by
Dr. Franklin Schwartz ______Adviser Dr. E. Scott Bair Geological Science Graduate Program
i ii ABSTRACT
A Geographic Information System (GIS) was developed to identify future home
and business sites in Summit County, Colorado, one of the fastest growing regions in the
country. The permanent population is projected to be 31,500 by 2010, an increase of 25
percent from 2000 (Colorado Department of Local Affairs Demography Section). Also,
in the winter the population of the county may increase to 150,000 or more during peak ski weekends (Summit County Planning Department, 2003). The county will continue
development to accommodate the growing population and tourists that flock to ski resorts and other vacation facilities in this very popular and accessible region.
The GIS developed here includes data for: land ownership, topography (slope and aspect), bedrock and surficial geology, soil types, presence and orientation of bedrock lineaments, locations of water wells, culture (cities, roads, emergency facilities, etc.), and city and county zoning regulations. By incorporating and correlating features of all of these, it was possible to identify areas within Summit County that can accommodate increases in permanent population and the surges that characterize the tourist industry in Colorado.
Because of its location in the high country of Colorado, about 80 percent of the county (496 sq mi of a total 620 sq mi) is administered by the U.S. Forest Service and the
U.S. Bureau of Land Management. However, the GIS developed here identified almost
ii 13 percent of the county that is suitable for development – a number that could change
subject to the ruling of the county or town planning commission. Twelve areas that range in size from 1.6 to 3.5 sq mi (4 to 9 sq km) were highlighted initially, and three of these were selected for follow-up evaluation: two near the town of Breckenridge (3.3 and 3.5 sq mi), and one near the town of Frisco (3.1 sq mi). The techniques developed in the GIS are directly applicable to the remaining nine of the twelve areas, and anywhere in the world where data and requirements are similar.
iii ACKNOWLEDGMENTS
It would not have been possible to complete this study without the support of my family, friends, and professors. I thank Dr. Pride for the support, guidance, and ideas that he contributed this study. His enthusiasm aided in making this thesis possible.
I wish to thank my committee members, Dr. Frank Schwartz and Dr. E. Scott
Bair, for their help throughout this process. I also want to thank Dr. Berry Lyons for his initial guidance in this process.
I thank the colleagues that gave me advice at the Ohio Department of Natural
Resources Division of Water concerning GIS. Wayne Jones, Paul Spahr, and Mike
Angle provided suggestions and fixes throughout the study.
The State of Ohio Union Education Trust has provided my tuition for the final year of my master’s reach, which has allowed me to finish this study while working fulltime. The Friends of Orton provided the ability to purchase the U.S. Geological
Survey digital orthographic quarter quadrangles and Colorado Water Resources water well data used in this study.
Finally, I thank my parents, my brothers, and my friends for their encouragement to finish this study.
iv VITA
December, 1981……………………………. Born – Salem, OH
2000 – 2004…………………………………B.S. Geology Denison University, Granville, OH
2004 – 2007…………………………………Student Intern Ohio Department of Natural Resources, Division of Water
2007 – Present……………………………….Geologist Ohio Department of Natural Resources Division of Mineral Resources Management
v
PUBLICATIONS
1. Spahr, P.N., Jones, W., Barrett, K.A., Angle, M.P., and Raab, J.M., 2007. Using GIS to Create and Analyze Potentiometric-Surface Maps. Soller, D.R., ed., Digital Mapping Techniques ’06 – Workshop Proceedings, Columbus, Ohio, June 11-14, 2006: U.S. Geological Survey Open-File Report 2007-1285, 217p. (Also available online at http://pubs.usgs.gov/of/2007/1285/.)
2. Wayne, J. and Barrett, K., 2007. Building a Water Well Database for GIS analysis. Soller, D.R., ed., Digital Mapping Techniques ’06 – Workshop Proceedings, Columbus, Ohio, June 11-14, 2006: U.S. Geological Survey Open-File Report 2007- 1285, 217p. (Also available online at http://pubs.usgs.gov/of/2007/1285/.)
3. Wayne, J., Barrett, K., M. Angle, and J. Raab, 2007. The Relationship between Land Use, Ground Water Flow and Non-Point Source Contamination in the Upper Mad River Watershed. Ohio Department of Natural Resources, Division of Water, Water Resources Section. 117p.
FIELDS OF STUDY
Major fields: Geological science
vi
TABLE OF CONTENTS
Page Abstract ...... ii
Acknowledgments...... iv
Vita ...... v
List of Tables ...... x
List of Figures ...... xii
Introduction ...... 1
1.1 Purpose and Importance of Study ...... 1
1.2 Location ...... 2
1.3 Demographics ...... 6
1.4 Climate ...... 9
1.5 Physical Geography ...... 9
1.6 Geologic Setting ...... 10
1.7 Hydrology ...... 11
1.8 Water Supply and Water Quality Concerns and Previous Work ...... 15
Part 1 of Analysis ...... 18
2.1 Introduction ...... 18
2.2 Description of Jason Miller’s Work ...... 18
2.3 Methods Used in This Study ...... 26
2.4 Slope and Aspect ...... 27
vii 2.5 Land Ownership and Zoning ...... 40
2.6 Proximity...... 52
2.7 Map Algebra: Adding Data ...... 63
2.8 Results: Final Addition Product ...... 67
2.9 Possible Variations to the Final Addition Product ...... 69
2.10 Selecting Areas for Detailed Study ...... 70
2.11 Results ...... 91
2.12 Conclusion ...... 93
Part 2 of Analysis ...... 95
3.1 Introduction ...... 95
3.2 Data Collection ...... 95
3.3 Data Preparation for Analysis ...... 101
3.4 Results and Analysis ...... 107
3.4.1 Geology ...... 107
3.4.2 Lineaments ...... 115
3.4.3 Soil ...... 127
3.4.4 Water Well Data ...... 135
3.5 Data Comparisons: Part Two Data ...... 141
3.5.1 Lineaments and Geology ...... 141
3.5.2 Water Wells and Geology ...... 155
3.6 Data Comparisons: All Data ...... 160
3.6.1 Geology and Slope Angle ...... 160
3.6.2 Geology and the Final Suitability Addition Map ...... 165
viii 3.6.3 Zoning and Water Well Locations ...... 169
3.7 Conclusions ...... 177
3.7.1 Area 5 ...... 177
3.7.2 Area 7 ...... 179
3.7.3 Area 10 ...... 181
Conclusions & Future Work ...... 183
4.1 Future Work ...... 184
APPENDIX A ...... 187
APPENDIX B ...... 193
List of References ...... 201
ix LIST OF TABLES
Table Page
Table 1.1 Historic, Estimated, and Projected Population in Summit County ...... 7
Table 1.2 Historic and Estimated Population of Summit County Towns ...... 8
Table 2.1 Data Sources for Miller, 2005 ...... 20
Table 2.2 Ratings Applied to Data in Miller, 2005 ...... 20
Table 2.3 Town and Summit County Codes Consulted for Development Guidelines ..... 27
Table 2.4 Slope Guidelines for Building Construction from Town and County Codes ... 31
Table 2.5 Slope Guidelines for Road Construction from Town and County Codes ...... 32
Table 2.6 Suitability Values Assigned to Slopes for Building Construction ...... 35
Table 2.7 Suitability Values Assigned to Slopes for Road Construction ...... 35
Table 2.8 Initial Aspect Angle Ranges Created with Surface Analysis ...... 38
Table 2.9 Suitability Values Assigned to Aspect Angle Ranges ...... 38
Table 2.10 Land Ownership in Summit County ...... 43
Table 2.11 Suitability Values Assigned to Land Ownership ...... 43
Table 2.12 Zoning Codes from the Summit County Land Use & Development Code .... 44
Table 2.13 Extent of Each Zoning Code in Summit County ...... 46
Table 2.14 Population Density in Towns and Summit County ...... 49
Table 2.15 Suitability Values Assigned to Summit County Zoning ...... 50
Table 2.16 Suitability Values Assigned to City Buffers ...... 54
x Table 2.17 Fire Station Service Areas in Summit County ...... 54
Table 2.18 Suitability Values Assigned to Fire Station Buffers ...... 57
Table 2.19 Suitability Values Assigned to Ski Area Buffers ...... 57
Table 2.20 Suitability Values Assigned to Highways, Routes, and Local Roads Buffers 61
Table 2.21 Areas of Existing Development ...... 72
Table 2.22 Extent, Closest Three Towns, and Adjacent Ski Area to 12 Areas ...... 84
Table 2.23 Data Availability for 12 Areas of Close Study ...... 85
Table 2.24 Zoning Extents for 12 Areas ...... 90
Table 3.1 Frisco Geologic Quadrangle Units in Area 5 ...... 111
Table 3.2 Frisco Geologic Quadrangle Units in Area 7 ...... 113
Table 3.3 Frisco Geologic Quadrangle Units in Area 10 ...... 115
Table 3.4 Count of Lineaments Identified ...... 117
Table 3.5 Soil Types Present in Each Area of Close Study ...... 129
Table 3.6 Soil Extents in Areas of Close Study ...... 131
Table 3.7 Well Uses in Areas of Close Study and Buffers ...... 137
Table B.1 More Detailed Description of Summit County Zoning Codes ...... 194
Table B.2 Coordinates for Corners of the Town of Montezuma ...... 196
Table B.3 Summit County Fire Stations Address and Geocoded Coordinates ...... 197
Table B.4 Summit County and Loveland Ski Areas Addresses and Geocoded Coordinates
...... 198
Table B.5 Colorado Geologic Map Units in southern Summit County (Tweto, 1979) .. 199
Table B.6 Frisco Geologic Quadrangle Units (Kellogg, Bartos, and Williams, 2002) .. 200
xi
LIST OF FIGURES
Figure Page
Figure 1.1 Location of Summit County in Colorado ...... 3
Figure 1.2 Ski Resorts and Reservoirs of Summit County ...... 4
Figure 1.3 Towns of Summit County ...... 5
Figure 1.4 Major Streams and Bodies of Water in Summit County ...... 13
Figure 2.1 Aspect Diagram ...... 21
Figure 2.2 Most Suitable Areas According to Miller, 2005...... 24
Figure 2.3 Best Regions for Development According to Miller, 2005...... 25
Figure 2.4 Topographic Maps at Summit County ...... 29
Figure 2.5 DEM Boundaries Before and After Mosaicking ...... 30
Figure 2.6 Reclassified Structure and Road Slope According to Suitability ...... 36
Figure 2.7 Aspect for Summit County as Created with Surface Analyst ...... 37
Figure 2.8 Suitability Values Assigned to Aspect ...... 39
Figure 2.9 Land Ownership in Summit County ...... 41
Figure 2.10 Summit County Zoning (Generalized from Summit County G.I.S. Zoning) 45
Figure 2.11 Suitability Values Assigned to Zoning ...... 51
Figure 2.12 Values Assigned to Suitability Buffers around Summit County towns ...... 55
Figure 2.13 Fire Station Buffers ...... 58
Figure 2.14 Ski Area Buffers ...... 59
xii Figure 2.15 Highway, Routes, and Local Roads Buffers ...... 62
Figure 2.16 Map Algebra ...... 65
Figure 2.17 Final Addition Map ...... 68
Figure 2.18 Designating Areas of Existing Development ...... 73
Figure 2.19 Areas of Existing Development ...... 74
Figure 2.20 Interval Map of Suitability Values ...... 77
Figure 2.21 Area Filter to Find Best Suitable Areas for Development ...... 78
Figure 2.22 Areas Eliminated from Consideration ...... 79
Figure 2.23 Areas of Close Study ...... 83
Figure 2.24 Zoning for Areas 1, 2, and 3 ...... 86
Figure 2.25 Zoning for Areas 4, 5, and 6 ...... 87
Figure 2.26 Zoning for Areas 7, 8, and 9 ...... 88
Figure 2.27 Zoning for Areas 10, 11 and 12 ...... 89
Figure 2.28 Selected Areas of Close Study ...... 92
Figure 2.29 Suitability Values in Relation to Existing Development ...... 94
Figure 3.1 Extent of Available Geologic Data ...... 98
Figure 3.2 Extent of Available Soil Data ...... 99
Figure 3.3 Example of DEM and Hillshade ...... 100
Figure 3.4 DOQQ Used in Lineament Analysis ...... 102
Figure 3.5 Hillshade Maps Used in Lineament Analysis ...... 103
Figure 3.6 Water Well Locations ...... 106
Figure 3.7 Frisco Geologic Quadrangle at Area 5 ...... 110
Figure 3.8 Frisco Geologic Quadrangle at Area 7 ...... 112
xiii Figure 3.9 Frisco Geologic Quadrangle at Area 10 ...... 114
Figure 3.10 Regional Lineaments Identified in DOQQ Imagery ...... 118
Figure 3.11 Area 7 Lineaments Identified from DOQQ Imagery ...... 119
Figure 3.12 Area 10 Lineaments Identified from DOQQ Imagery ...... 120
Figure 3.13 Area 5 Lineaments Identified from DOQQ Imagery ...... 121
Figure 3.14 Regional Lineaments Identified from Hillshade Maps ...... 122
Figure 3.15 Area 5 Lineaments Identified from Hillshade Maps ...... 123
Figure 3.16 Area 7 Lineaments Identified from Hillshade Maps ...... 125
Figure 3.17 Area 10 Lineaments Identified from Hillshade Maps ...... 126
Figure 3.18 Glacially-Derived Soils at Areas of Interest ...... 130
Figure 3.19 Soil Data at Area 5 ...... 132
Figure 3.20 Soil Data at Area 7 ...... 133
Figure 3.21 Soil Data at Area 10 ...... 134
Figure 3.22 Water Well Locations within One Kilometer of Area 5 ...... 138
Figure 3.23 Water Well Locations within One Kilometer of Area 7 ...... 139
Figure 3.24 Water Well Locations within One Kilometer of Area 10 ...... 140
Figure 3.25 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle ...... 144
Figure 3.26 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle Quaternary
Units ...... 145
Figure 3.27 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle Tertiary and
Proterozoic Units ...... 146
Figure 3.28 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle ...... 147
xiv Figure 3.29 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle Quaternary
Units ...... 148
Figure 3.30 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle Tertiary and
Proterozoic Units ...... 149
Figure 3.31 Area 7 DOQQ Lineaments and Frisco Geologic Quadrangle ...... 150
Figure 3.32 Area 7 DOQQ Lineaments and Frisco Geologic Quadrangle Quaternary
Units ...... 151
Figure 3.33 Area 7 Hillshade Lineaments and Frisco Geologic Quadrangle ...... 152
Figure 3.34 Area 10 DOQQ Lineaments and Frisco Geologic Quadrangle ...... 153
Figure 3.35 Area 10 Hillshade Lineaments and Frisco Geologic Quadrangle ...... 154
Figure 3.36 Frisco Geologic Quadrangle and Water Well Locations at Area 5 ...... 157
Figure 3.37 Frisco Geologic Quadrangle and Water Well Locations at Area 7 ...... 158
Figure 3.38 Frisco Geologic Quadrangle and Water Well Locations at Area 10 ...... 159
Figure 3.39 Frisco Geologic Quadrangle and Slope Data at Area 5 ...... 162
Figure 3.40 Frisco Geologic Quadrangle and Slope Data at Area 7 ...... 163
Figure 3.41 Frisco Geologic Quadrangle and Slope Data at Area 10 ...... 164
Figure 3.42 Frisco Quadrangle Frisco and Suitability at Area 5 ...... 166
Figure 3.43 Frisco Quadrangle Frisco and Suitability at Area 7 ...... 167
Figure 3.44 Frisco Quadrangle Frisco and Suitability at Area 10 ...... 168
Figure 3.45 Water Well Locations and Summit County Zoning at Area 5 ...... 171
Figure 3.46 Water Well Uses and Summit County Zoning at the Blue River ...... 172
Figure 3.47 Water Well Locations and Summit County Zoning at Area 7 ...... 173
Figure 3.48 Water Well Locations and Summit County Zoning at Area10 ...... 174
xv Figure 3.49 Water Well Locations in Subdivisions North of Area 10 ...... 175
Figure 3.50 Water Well Locations and Summit County Zoning ...... 176
Figure 3.51 Regions Best for Development in Area 5 ...... 178
Figure 3.52 Regions Best for Development in Area 7 ...... 180
Figure 3.53 Regions Best for Development in Area 10 ...... 182
Figure 4.1 Example of Additional Data ...... 186
xvi
CHAPTER 1
INTRODUCTION
Spatial analysis in locations with high population growth rates is becoming increasingly crucial as physical and human limits are tested. Constraints now include
economic and government limitations in addition to physical limitations such as geologic
hazards and adequate water supply. Land-use planning now entails integration and
analysis of data types to determine where future development should occur. This is accomplished with the use of Geographic Information Systems (GIS), which not only display applicable data, but also allow for the manipulation and analysis of such data.
Infrastructure for transportation, development, and emergency services can be overlain with the topography, geology, soil type, and the locations of streams to make decisions as to where best site development as the population grows.
1.1 Purpose and Importance of Study
This study was performed to create a land-use planning model within a GIS to
determine where best to place future development. GIS allows for the assessment of data
types that range from zoning and land ownership characteristics to bedrock geology.
Generally, zoning, land ownership, and other cultural and land-use designations are
1 considered separately from environmental concerns such as geology, soils, and water
availability. However, all of these are needed to make planning decisions. The purpose of this study was to incorporate data pertinent to traditional land use planning and
environmental data into a GIS to evaluate the suitability of the Summit County region for
future development. This study will provide a framework or “base line” for similar
studies elsewhere. Summit County was selected for study, because there are many
physical constraints for development in addition to county and federal government
limitations. It is one of the fastest growing counties in the United States, and,
importantly, adequate data are available for analysis.
1.2 Location
Summit County lies in central Colorado 60 miles west of Denver in the Colorado
Rocky Mountains (Figure 1.1). It covers approximately 1,600 square kilometers (620
square miles) and varies in elevation from 7,947 feet (above mean sea level) at Green
Mountain Reservoir to 14,270 feet at Gray’s Peak. The economy of Summit County
currently is dominated by tourism with facilities for skiing, boating, and other
recreational activities (Figure 1.2). It is home to four large and popular ski resorts:
Arapaho, Breckenridge, Copper Mountain, and Keystone. Most of the permanent
population lives near the ski resorts and in the towns of Blue River, Breckenridge, Dillon,
Frisco, Montezuma, and Silverthorne (Figure 1.3). Almost all of Summit County lies
within the Arapahoe National Forest, part of which is the Eagles Nest Wilderness Area.
2
Figure 1.1 Location of Summit County in Colorado
3
Figure 1.2 Ski Resorts and Reservoirs of Summit County
4
Figure 1.3 Towns of Summit County
5 1.3 Demographics
Summit County is one of the fastest growing counties in the United States. The
permanent population increased from 2,665 in 1970 to 23,548 in 2000 (Colorado State
Demographic Office, 2007) (Table 1.1). The largest increase was from 1990 to 2000
when the population grew almost 83 percent. Growth has slowed since 2000, but it is
expected to continue its climb according to U.S. Census Bureau and Colorado
Demographic Office population projections. If current trends continue, the population is
projected to reach 53,840 by 2035 (Colorado State Demographic Office, 2007). The
most recent estimate of the permanent population in Summit County was 26,547 in 2007
(U.S. Census Bureau, 2008). However, during peak ski weekends the population can
increase to nearly 150,000, more than five times the current estimated permanent
population (Summit County Planning Department, 2003).
Census data and population estimates also are available for the towns in Summit
County (Table 1.2). Silverthorne has the highest population estimate of 3,733 and
Montezuma the lowest of 42 (U.S. Census Bureau, 2007). Significant population also is
present in and around the Keystone, Copper Mountain, and Breckenridge ski areas (U.S.
Census Bureau, 2000). Towns in Summit County have a total population of 10,685,
which is more than 40 percent of the total population in the county.
6
US Census Population Estimated Population Projected Population 1870 to 2000 2000 to 2007 2010 to 2035 Year Population Percent Year Population Percent Year Population Percent Change Increase Increase 1870 258 2000 23,548 2010* 31,498 33.8 1880 5,459 2016 2001 26,355 11.9 2015 35,888 13.9 1890 1,906 -65 2002 26,798 1.7 2020 40,646 13.3 1990 2,744 44 2003 27,114 1.2 2025 45,425 11.8 1910 2,033 -26 2004 27,443 1.2 2030 49,866 9.8 1920 1,724 -15 2005 27,507 0.2 2035 53,840 8.0 1930 987 -43 2006 27,964 1.7 1940 1,754 78 2007 28,789 3.0 1950 1,135 -35 1960 2,037 79 1970 2,665 31 1980 8,848 232 1990 12,881 46 2000 23,548 83
Table 1.1 Historic, Estimated, and Projected Population in Summit County
7
Town Populations 1880 through 2006 Year Blue Breckenridge Dillon Frisco Montezuma Silverthorne River 1880 1,657 48 1890 714 133 100 106 1900 976 143 40 1910 834 134 81 134 1920 796 126 69 1930 436 92 18 38 1940 381 161 60 59 1950 296 191 87 48 1960 393 814 316 17 1970 8 548 182 471 6 400 1980 230 818 337 1,221 17 989 1990 440 1,285 553 1,601 60 1,768 2000 685 2,408 802 2,443 42 3,196 2001 685 2,970 802 2,608 43 3,540 2002 709 3,112 803 2,621 43 3,625 2003 730 3,199 801 2,631 44 3,709 2004 743 3,296 819 2,697 46 3,806 2005 745 3,359 811 2,703 48 3,840 2006 752 3,439 818 2,742 49 3,956
Table 1.2 Historic and Estimated Population of Summit County Towns
8 1.4 Climate
The climate of Summit County is controlled by the Rocky Mountains and the
land-locked conditions of the mid-latitude interior of North America (Doesken et al.,
2003). The steep changes in elevation create great differences in local climate with
significant changes in temperature, humidity, precipitation, and wind. Humidity
generally is low, and temperatures cool. Average high temperatures are between 70 and
90 degrees Fahrenheit at lower elevations and between 50 and 70 degrees Fahrenheit at
higher elevations (Doesken et al., 2003 and High Plains Regional Climate Center, 2008).
The majority of precipitation occurs in the winter and the amount increases with elevation (Doesken et al., 2003). Thunderstorms occur during the summer months when moisture-laden air from the Gulf of Mexico circulates through the region. Record at the
Dillon Weather Station indicate that average snowfall totals range from 15.2 inches in
November to 22.1 inches in March, which correspond to the peak of ski season (Great
Plains Regional Climate Center, 2008). Most of the snow melts in May and June, and this is the main source of water for the streams, lakes, and reservoirs in Summit County
(Doesken et al., 2003).
1.5 Physical Geography
Summit County is set in the Rocky Mountains. The Colorado Front Range lies
east of Breckenridge, and smaller ranges, the Tenmile and Gore Ranges, compose the
western portion of the county. The latter together comprise the larger Park Range. The
Tenmile Range lies west of the towns of Breckenridge and Blue River, and the Gore
9 Range is the eastern county boundary. The Continental Divide forms the eastern and southeastern boundaries of Summit County, and it is the drainage divide between the
Colorado River to the west, and the Arkansas and South Platte River basins to the east.
1.6 Geologic Setting
The bedrock geology of Summit County is comprised of Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, and Tertiary intrusions.
Metasedimentary rocks were intruded by granite, pegmatite and aplite, and they were then folded multiple times during the Precambrian (Lovering, 1935). Proterozoic units are mostly granodiorite and quartz monzonite that are exposed along the mountain ranges in Summit County. Along the Williams Range Thrust, Proterozoic granite, gneiss, and schist occur uncomformably over dipping Paleozoic units, as erosion wears away the ancestral Front Range (Robinson, Warner, and Wahlstrom, 1974). Mesozoic sedimentary units were deposited when the mid-continent was covered by broad seas, especially during the Cretaceous period. Mesozoic bedrock is much more extensive at the surface than the Paleozoic bedrock in the Summit County region. The uplift of the modern Front
Range began during the Laramide orogeny, a period of significant deformation from about 70 to 50 Ma. During this time Proterozoic crystalline units were thrust over
Paleozoic and Mesozoic sedimentary rock along at the Williams Range thrust, Tertiary sills and dikes intruded the region, and compressive faulting occurred (Kellogg, Bartos, and Williams, 2002). The Front Range was the site of widespread glaciation during Early and Late Pleistocene when valleys were deepened by rivers swollen with glacial
10 meltwater (Lovering, 1935). Streams erode exposed bedrock and glacial deposits and, alluvium and colluvium continue to be deposited in and along river valleys with the thickest of such deposits forming along the Blue River (Kellogg, Bartos, Williams, 2002).
Linear features that indicate a variety of features including faults, joint sets, rock foliation, drainage networks, and rock contacts are present throughout Summit County
(Steele, 1986). These features vary in scale from regional lineaments as long as 10 kilometers (six miles) to localized lineaments 100 meters or less in length. The smaller and often less obvious lineaments are visible in high resolution photography. In Summit
County, lineaments can be either single features or a composite of several closely-spaced features in a variety of material (Flyod, 1987).
Deposits of gold, silver, and sulfides of lead, zinc, silver, arsenic, antimony, molybdenum, copper, bismuth, and their supergene alteration products have been mined in Summit County (Lovering, 1935). Important mining districts in the county included the Breckenridge, Montezuma-Argentine, and the surface portion of the Climax molybdenum deposit (Conaway 1999 and Vinciguerra 2003). Mining has ceased in these areas, but many prospects and mining claims still are present in the southern portion of the county, and tailings piles, tailings ponds, and shafts are present along the large stream valleys, especially the Blue River, French Gulch, Swan River, and Tenmile Creek.
1.7 Hydrology
Summit County lies entirely within the Colorado River basin, and the three largest stream basins of the Blue River, Snake River, and Tenmile Creek comprise part of the
11 headwaters of the Colorado River (Figure 1.4). The rivers all flow into Dillon Reservoir, and only the Blue River continues north through the Green Mountain Reservoir to the
Colorado River. The Blue River begins in southern-most Summit County, flows north to the Dillon Reservoir at the Blue River Arm, and continues north through central Summit
County. The Snake River flows from the east and enters the Dillon Reservoir at the
Snake River Arm, and Tenmile Creek flows from the southwest to the Dillon Reservoir at
Giberson Bay.
Dillon Reservoir and the Green Mountain Reservoir are the largest bodies of water in Summit County. Dillon Reservoir is at the center of the county with an average capacity of 254,000 acre-feet (Denver Water 2008). Water is pumped from Dillon
Reservoir eastward through the Harold D. Roberts Tunnel to Denver. It supplies approximately 25 percent of the drinking water to Denver. The Green Mountain
Reservoir in northern Summit County is part of the US Bureau of Reclamation Colorado
– Big Thompson project, which takes water from the Blue River for irrigation, drinking, and power generation. The reservoir has a total capacity of 153,600 acre-feet (US Bureau of Reclamation, 2008). A much smaller reservoir, the Goose Pasture Tarn, provides drinking water to the town of Breckenridge. The Tarn is located in northern Blue River, and it has a maximum capacity of the tarn is 770 acre-feet (Elliot et al., 2006). All of these reservoirs are along the Blue River.
12
Figure 1.4 Major Streams and Bodies of Water in Summit County
13 Three types of groundwater aquifers are present in Summit County: Quaternary
alluvial deposits, Mesozoic sedimentary bedrock, and fractured Tertiary volcanic and
Proterozoic crystalline bedrock. Quaternary deposits occur along the large stream valleys
with the thickest and most extensive material in the Blue River valley. These valley
deposits are composed of a variety of materials from boulders to clay, and they range
greatly in thickness.
Sedimentary rock aquifers include Mesozoic carbonate units in the Eagle Basin in
the very southwest corner of the county and in Dakota-Cheyenne sandstones and Carlilie
Limestone beneath the Blue River valley (Topper et al., 2003). Eagle Basin ends west of
the Gore Range in a mountainous and unpopulated area of Summit County. The Dakota-
Cheyenne aquifer beneath many of the towns in Summit County is composed of thick
Jurassic and upper Cretaceous sandstone, shale, and mudstone layers. The Fort Hays
Limestone of the Niobrara Formation and the Dakota and Entrada sandstones are high
yielding units in the Dakota-Cheyenne aquifer that occur in Summit County according to
the Ground Water Atlas of Colorado (Topper et al., 2003).
The crystalline Proterozoic and Tertiary volcanic aquifers are grouped together
because of their proximity and similar hydrological properties. These units have no
primary porosity and exhibit significant transmissivity along zones of fracturing. Steeply
dipping fractures could create flow conduits plus significant storage capacity especially
where the rock exhibits horizontal fracturing (Topper et al., 2003). These units generally are present in the southern half of Summit County.
14
1.8 Water Supply and Water Quality Concerns and Previous Work
As of 2003, Summit County relied on surface water resources for approximately
90 percent of its water (Topper et al., 2003). These sources include the two large
reservoirs and the tributary streams, all of which are subject to drought. The last major
drought in Colorado occurred as recently as 2002 and 2003, during which time severe
drawdown was recorded in reservoirs. Streamflow was recorded at its lowest levels since
records have been kept (Hydrosphere, 2003). During this drought, Denver Water had to
draw large quantities of water from Dillon Reservoir to supplement its other supplies.
The water level at Green Mountain Reservoir was at a low, which compromised the
structural integrity of the south side of the reservoir and prevented full use of the reservoir supply. As a result of the low streamflow and reservoir levels, Summit County enacted temporary water restrictions, which may become a regular occurrence as the population of the county continues to grow.
Water quality also can be a major concern in regions such as southern Summit
County, where population is increasing, geology is variable, and there has been mining activity. Water has the potential to leach minerals from shafts and tunnels and from mineralized bedrock and then transport the lechate into streams and reservoirs of the county. The leachate sorbs onto clays and other alluvial particles at the normal pH values in streams of the region, and these are deposited with stream sediments in reservoir and ponds of the region. Conaway (1999) examined hydroxide precipitates in the Snake
River drainage basin, and he determined that significant quantities of metals were being transported to Dillon Reservoir from the Montezuma and Argentine mining districts, but
15 that they still remain as hydroxide precipitates at the current water chemistry. However,
a significant drop in pH or some other change in water chemistry could bring the metals back into solution. Vinciguerra (2003) analyzed surface and groundwater samples in the
Blue River drainage system to determine metal contaminant concentrations at high- and
low-flow conditions in the upper Blue River drainage basin. There were several
measurements of cadmium above US EPA Maximum Contaminant Level (MCL) in the
Swan River tributary of the Blue River, but no other metals exceeded MCLs.
Vinciguerra’s work showed that the upper Blue River drainage basin is relatively
unaffected by mine waters, because of dilution by the large quantities of water that flush
the system during snow melt (Vinciguerra, 2003). Analysis of sediment in Dillon
Reservoir also reveal that concentrations of copper, iron, lithium, nickel, scandium, titanium, and vanadium have been decreasing over time, which may be related directly to the decline in mining activity in the Blue River, Snake River, and Tenmile Creek drainage basins (Greve et al., 2001).
Increased levels of hydrocarbons and phosphorus were detected in Summit
County water during the 1970s and 1980s, which corresponds to the period when population also increased (Greve et al., 2001 and Lemonds and McCray, 2003).
Concentrations of phosphorus increased in Dillon Reservoir, but the source is not well understood (Lemonds and McCray, 2003). A watershed-scale, Soil and Water
Assessment (SWAT) model results showed that runoff sediments likely are the primary source of phosphorus (Lemonds and McCray, 2003). Greve et al. (2001) found that the highest concentrations of hydrocarbons occur in the Tenmile Creek arm of Dillon
16 Reservoir, which is the only major river to run through a town, Frisco, which is located
where the creek enters the reservoir.
Several studies have been undertaken to examine factors such as metal
contamination and land use when trying to determine how Summit County can
accommodate its anticipated population growth. In a collaborative effort to decrease
phosphorus concentrations in the Dillon Reservoir, the GIS-based Watershed Analysis
Risk Management Framework (WARMF) was used to determine sources and transport routes of phosphorus in Summit County (Community Services, 2007). Topography, land
use, wastewater treatment system infrastructure, and other applicable data were
incorporated into this GIS to help water resource managers determine which wastewater
infrastructure features would minimize the amount of phosphorous entering the water
system and prevent eutrophification from occurring.
Miller (2005) incorporated zoning, land ownership, topography, and the locations
of roads and towns into a GIS to determine where to site future development. Except for
topography, these data considered development in terms of guidelines put into place by
the Summit County planning commission. Erdmann and Dean (2000) created a GIS-
based analysis to examine where to put future populations in Grand County to the north of Summit County based on land use, topography, proximity to surface water and public land, and socio-economic factors such as population density and property values.
Whereas the latter study includes more data types than land-use studies typically do, it does not include bedrock or surface geology, water well data, and other data types such as the presence and density of lineaments that are parts of this study.
17
CHAPTER 2
PART 1 OF ANALYSIS
2.1 Introduction
Work for this study was performed in two parts. This chapter entails the first, in
which topography, location, and land ownership and zoning GIS data were analyzed to determine where to place future development in Summit County. Population is projected
to increase within the county, and where to accommodate this growth will become a
challenge due to physical and civil limitations. The area is mountainous, and much of
Summit County is under the jurisdiction of the National Forest Service, both of which
will affect future development. Analysis of GIS data has identified 12 areas where
development can occur. Several small areas were selected from this group for
hydrological and geological analysis, and this constitutes the second part of the present study.
2.2 Description of Jason Miller’s Work
Miller (2005) analyzed GIS data to identify regions where anticipated population
growth might be accommodated in southern Summit County. Data used in his study
included geology, slope, aspect, land ownership, zoning, and the locations of roads and
18 towns (Table 2.1). The process entailed downloading and buying GIS data, reclassifying
these data based on suitability for future development, and combining the data to reveal
overall suitability. High-summed values identified the most suitable land for development.
Slope and aspect files for southern Summit County were created from U.S.
Geological Survey 1:24,000 digital elevation models (DEMs). Slope is a degree or grade measure of the steepness of topography. Aspect is the compass direction a slope faces and is measured in degrees. Zero and 360 degrees both designate north, and south is 180 degrees (Figure 2.1). Both slope and aspect vary greatly in the study area, because the terrain is mountainous. Miller highlighted areas with slopes of less than 10 degrees, because construction is permitted only on such slopes (Table 2.2). In the northern hemisphere south-facing slopes generally are preferred for development, because they are sunlit longer than north-facing slopes. This distinction is important in mountainous areas where winters are colder and snowfall is often heavy (Ahrens, 2000). Miller identified aspects between 125 and 225 degrees (southeast to southwest) as the most suitable for development, and he assigned positive values to these aspects. Aspects within 15 degrees of south-facing slopes were ranked highest. Southeast- and southwest-facing slopes, 125
to 155 degrees and 195 to 225 degrees, were ranked lower, because these slopes are less
desirable but still receive significant sunlight. All other aspects were eliminated from further consideration.
19 Data Source Aspect U.S. Geological Survey 1:24,000 Digital Elevation Model (DEM)
Geology Digitized Geological Map of Colorado (Tweto, 1979)
Land Owner Colorado Department of Transportation & Summit County G.I.S
Roads Colorado Department of Transportation
Slope U.S. Geological Survey 1:24,000 DEM
Towns Colorado Department of Transportation
Zoning Summit County G.I.S.
Table 2.1 Data Sources for Miller, 2005
Data Categories Value Aspect 30 degrees of the azimuth (155 to 195 degrees) 2 30 to 60 degrees of the azimuth (125 to 155 & 195 to 225) 1 Everything Else 0 Land Many Variety* Classification PUD & Open Space Higher* (Zoning) Mining 0 Natural Resources 0 Industrial 0 Special Use 0 Agricultural 0 Proximity to 0 to 0.5 mile 3 roads 0.51 to 1 mile 2 & towns 1.01 to 2 miles 1 Beyond 2 0 Slope Less than 10 degrees Value* Greater than 10 degrees 0 *Specific value(s) not listed in Miller (2005)
Table 2.2 Ratings Applied to Data in Miller, 2005 20
Figure 2.1 Aspect Diagram
(Modified from ESRI ArcMap North Arrow in ESRI ArcGIS Version 9.2, 2006)
21 The Summit County Government Information Systems (G.I.S.) Department
supplied zoning information and part of the land ownership data that was used by Miller.
He assigned high values to areas where moderate development is encouraged and
removed from further consideration those areas where development is not permitted
(Table 2.2). He also examined data from both the Summit County G.I.S. Department and the Colorado Department of Transportation (CDOT) to determine if Summit County had annexed land from the National Forest in the past. National Forest land covers 80 percent of Summit County and is zoned as natural resource, which carries the zoning stipulation that there will be no development beyond existing structures. Despite this, Miller found that the county had acquired control of several small areas from the National Forest
Service. These areas were used for development, and thus, show that when space becomes a limitation for future development, the county may have an option to obtain land from the Federal Government (Summit County Planning Development 2006).
Miller incorporated several development guidelines from the Summit County
Development Code into his GIS to remove hazardous locations and to highlight desirable locations for permanent population growth. The Summit County Planning Commission restricts development in areas with a high risk of landslides, and accordingly, areas of steep slope underlain by geologic units that are prone to collapse were removed from consideration. In addition, the Planning Commission strongly encourages construction close to existing roads and towns in order to limit the impact of development and to preserve the natural character of the county. To incorporate this guideline, Miller created buffers around roads and towns and eliminated areas beyond the buffers from further consideration.
22 Once the data were in hand, Miller ranked attribute categories for development suitability. A category from each data type was selected, and individual attributes were assigned numeric values according to its suitability for development. For example, zoning types were ranked, and high suitability values were assigned to residential and commercial development, and low values to agricultural, mining, and backcountry categories. This process is called reclassification and is performed with the Reclassify
Tool in ArcGIS (Appendix A).
Following reclassification, the data were combined in ArcGIS with the Raster
Calculator. This feature sums the assigned values for all data layers to create a single data layer. Each cell in this layer is the sum of all suitability values at that location. The end product reveals the best and worst areas for development on one map (Figure 2.2).
Miller compared the final map product with Google Maps to check if development had occurred between 2004 and 2005 in areas corresponding to high values.
He removed these areas from future consideration to more accurately depict areas for future development. Most areas deemed favorable by Miller (2005) were near existing towns in central and south-central Summit County. Finally, areas of likely growth over the next 10 years and 20 years were highlighted, and these areas extend largely from existing towns and population centers, and existing state and Federal highways (Figure
2.3).
23 N
!,
!,
!, !, , Ski Area Water Major Road
Brown areas are best for development.
Figure 2.2 Most Suitable Areas According to Miller, 2005.
24 Purple: National Forest Zoning Magenta: Other Zoning
Town Boundary Water Major Road
Figure 2.3 Best Regions for Development According to Miller, 2005.
25 2.3 Methods Used in This Study
The results of Miller’s work show where future development may be possible
based on the data he used. Additional data layers were used in the current study to build
upon Miller’s work to more fully develop a plan for future development. Additional data
layers include proximity to fire stations, ski resorts, three classes of roads, soil types,
bedrock geology, and hydrologic data.
The Summit County Development Code and Master Plan were consulted for rules
and guidelines on development. These documents address development in terms of
topography, zoning, and proximity to existing development. Based on existing
guidelines, aspect, slope, land ownership, zoning, and proximity to towns, roads, fire stations, and ski resorts data were added to the GIS database. The towns of Blue River,
Breckenridge, Dillon, Frisco, and Silverthorne also have development codes, and these also were consulted for guidelines on acceptable slopes angles (Table 2.3). The Summit
County documents were used for development guidelines in almost all cases, because the towns together comprise less that three percent of the county.
26 Area Code Legislative Body Blue River Blue River Ordinances Planning and Zoning Commission
Breckenridge Breckenridge Development Code Planning Commission
Dillon Dillon Municipal Code Planning and Zoning Commission
Frisco Frisco Town Code Community Development Department
Montezuma None Available NA
Silverthorne Silverthorne Town Code Community Development Planning Department
Summit County Land Use & Development Code Planning Department
Table 2.3 Town and Summit County Codes Consulted for Development Guidelines
Within ArcGIS the data were reclassified to show how the county would rate different areas for development based on the county and towns development codes and the Summit County Master Plan. A value of 10 represents the best location for development, and a value of one represents the least favorable. Areas where development is not permitted by the development codes were removed from consideration.
2.4 Slope and Aspect
Slope and aspect data layers were created in ArcGIS from DEMs. DEM data were downloaded in Spatial Data Transfer Standard file format (STDS) at no cost from the GeoCommunity GIS Data Depot. STDS is a U.S. Geological Survey proprietary
27 format that contains compressed DEM data. The files were decompressed and converted
into raster format for analysis in ArcGIS (Appendix A).
Summit County encompasses all or part of 23 USGS topographic quadrangles
(Figure 2.4). Each DEM covers exactly the same area as the topographic quadrangle with
the same name. A single DEM for Summit County was created in ArcGIS with the
Mosaic Tool, which connects the edges of the DEMs and calculates mean elevations to
eliminate possible seams (Figure 2.5) (Appendix A). Slope and aspect files were created
from this single DEM using the Surface Analysis tool in ArcGIS.
The development codes for Summit County and the towns of Blue River,
Breckenridge, Dillon, Frisco, and Silverthorne were consulted to determine what slopes
angles were considered acceptable for construction (Tables 2.4 and 2.5). Miller had
contacted the Summit County government and professionals at the Northwest Colorado
Council of Governments for guidelines on slope construction (2005). All of the sources
give different slope restrictions for building and road construction. For buildings, slopes
generally range from zero to 15 percent, with nothing permitted above 30 percent. The
recommended maximum slope for road construction is six percent, with very limited
construction allowed between six and 10 percent. No road construction is permitted on
slopes of more than ten percent. Concerns associated with construction above recommended grades include the ability of emergency equipment to traverse roads with steep slopes and the ability for construction equipment to work safely. Deterioration of the natural character of the county and risk of slumps and landslides also are factors in restricting development on very steep slopes. High grades are permitted only in areas where logging has occurred and structures had been built in the past.
28
Figure 2.4 Topographic Maps at Summit County
29
Figure 2.5 DEM Boundaries Before and After Mosaicking
30 Locality Slope Guideline Blue River No conditions on slopes up to 15% Above 15% requires special consideration
Breckenridge No development over 30% Steep slopes (>15%) require special consideration
Dillon No slope guidelines
Frisco Limited development above 15% Above 15% requires special consideration
Silverthorne Above 15% requires special consideration
Summit County No development over 30%
Other Source Slope Guideline Miller, 2005* Max of 15 degrees * Summit County GIS and professionals at the Northwest Colorado Council of Governments
Table 2.4 Slope Guidelines for Building Construction from Town and County Codes
31
Locality Slope Guideline Blue River 8% grade maximum
Breckenridge No grade specified
Dillon No grade specified
Frisco 5% grade maximum for roads 10% maximum for driveways
Silverthorne No grade specified
Summit County 6% grade maximum for most roads 10% grade maximum for low-use roads
Other Source Slope Guideline Miller, 2005* 10 degree maximum * Summit County GIS and professionals at the Northwest Colorado Council of Governments
Table 2.5 Slope Guidelines for Road Construction from Town and County Codes
32 Two slope data layers were created in this study: one for property development and one for roads. The files then were reclassified to assign suitability values based on the county and town development code guidelines (Tables 2.6 and 2.7). Property slopes greater than 30 percent and road slopes greater than 10 percent were assigned values of zero, and property slopes between 0 and 10 percent and road slopes between zero and six percent were assigned values of 10. Property slopes between 10 to 30 percent and road slopes between six to 10 percent were assigned values between one and ten based on slope angles for which town and county planning commissions readily or rarely permit construction.
The reclassified maps show that much of Summit County is unsuitable for road or property development (Figure 2.6), and much less land is favorable for road construction than for construction of homes and other buildings. Eighty-six percent of the county is unsuitable for road construction, but more than 46 percent of the county is favorable for homes and other buildings.
The Surface Analysis Tool in ArcGIS was used to create an aspect data layer, with values from 0 to 360 degrees (Figure 2.1). A default value of -1 is automatically assigned to flat areas that “face” the sky and receive sunlight from all angles. Aspect initially was displayed with colors representing degrees in ranges set by ArcGIS Surface
Analysis (Figure 2.7) (Table 2.8).
The Summit County Development Code recommends that building construction occur on south facing slopes, but it does not designate the aspect degrees of these slopes.
Also, there are no restrictions on development. “Premium” housing, winter housing, and most other development is recommended on south facing slopes. “Affordable”
33 employee housing, ski slopes, and summer oriented businesses may consider other aspects to save money and/or to limit exposure to sunlight (Summit County Planning
Department 2003). Based on development code recommendations the highest values were assigned to south-facing slopes between 160 to 200 degrees; a moderate value of six was assigned to southeast and southwest-facing slopes (140 to 160 and 200 to 220); and values of 3, 2, and 1 were assigned to east-, north-, and west-facing slopes (0 to 140 and
220 to 360) (Figure 2.8) (Table 2.9). A value of ten was also assigned to areas designated flat by the Surface Analysis Tool.
34
Slope (Degrees) Slope (% grade) Suitability Value
0 to 5.71 0 to 10 10
5.72 to 8.53 10 to 15 8
8.54 to 11.31 15 to 20 2
11.31 to 16.70 20 to 30 1
>16.70 >30 0
Table 2.6 Suitability Values Assigned to Slopes for Building Construction
Slope (Degrees) Slope (% grade) Suitability Value
0 to 3.43 0 to 6 10
3.44 to 4.57 6 to 8 3
4.58 to 5.71 8 to 10 1
>5.71 >10 0
Table 2.7 Suitability Values Assigned to Slopes for Road Construction
35
Figure 2.6 Reclassified Structure and Road Slope According to Suitability
36
Figure 2.7 Aspect for Summit County as Created with Surface Analyst
37
Orientation Degrees Flat -1 North 0 to 22.5 Northeast 22.5 to 67.5 East 67.5 to 112.5 Southeast 112.5 to 157.5 South 157.5 to 202.5 Southwest 202.5 to 247.5 West 247.5 to 292.5 Northwest 292.5 to 337.5 North 337.5 to 360
Table 2.8 Initial Aspect Angle Ranges Created with Surface Analysis
Range (degrees) Orientation Suitability Value 0 to 80 North to Almost East 1 80 to 120 Almost East to East Southeast 2 120 to 140 East Southeast to Almost Southeast 3 140 to 160 Almost Southeast to South Southeast 6 160 to 200 South 10 200 to 220 South Southwest to Southwest 6 220 to 240 Southwest to West Southwest 3 240 to 280 West Southwest to West 2 280 to 360 Almost west to North 1 -1 Flat 10
Table 2.9 Suitability Values Assigned to Aspect Angle Ranges
38
Figure 2.8 Suitability Values Assigned to Aspect
39 2.5 Land Ownership and Zoning
Data for land ownership and zoning were purchased from the Summit County
Government G.I.S. Department. The ownership file includes six classifications: private, town, county, state, National Forest, and Federal Bureau of Land Management (BLM)
(Figure 2.9) (Table 2.10). Eighty percent of the county is Federally administered, and more than 18 percent is privately owned. The remaining two percent is controlled by town, county, and state governments. Most of the privately owned land is in the large river valleys and close to major roads with many small areas of private ownership in the eastern half of the county. These areas have the fewest stipulations on construction and land use, and thus, privately owned land is the most desirable locations for future development. Most town-owned land is within the town boundaries of Blue River,
Breckenridge, Dillon, Frisco, Montezuma, and Silverthorne. None of the town-owned area occurs north of the town of Silverthorne. Most of the land owned by Summit
County is near or adjacent to privately owned land in the southern portion of the county.
The White River National Forest covers most of Summit County and includes areas that exhibit variable topography and little or no existing development. Land administered by the Forest Service and the Bureau of Land Management is the least desirable, because these agencies exercise control (Summit County Development Code). These constraints on development mean that it may be difficult to develop on Federal land in Summit
County once private, town, county, and state owned land is occupied.
40
Figure 2.9 Land Ownership in Summit County
41 Land ownership data were reclassified in ArcGIS to incorporate land ownership factors into the overall GIS database. Privately-owned land was assigned a value of 10, and a value of one was assigned to federally administered land (Table 2.11). The remaining land was assigned values below ten, with town and county controlled land receiving values of eight and six and areas owned by the State of Colorado receiving a value of three. No area was assigned a value of zero, because land ownership of any kind does not eliminate the possibility of future development. For example, town and county governments may exchange or purchase land from the Federal government, and this option may be an important component of future population growth in the County
(Summit County Development Code).
The Summit County Development Code describes all of the zoning codes in the county. The conditions permitted in each zoning code are described, and an abbreviation is designated for every code. Zoning codes vary by land use, lot size, housing type and density, ownership, and urban setting. The zoning data obtained from the Summit
County Government G.I.S. Department contain 31 zoning codes (Figure 2.10) (Table
2.12) (Appendix B). The Natural Resources (NR-2) zoning code is applied to land owned by the Federal government and stipulates that it remain as close to its natural state as possible. NR-2 land covers 78 percent of the county (Table 2.13). Development also is not permitted in the Industrial (I-1), Mining (M-1), Special Use (SU-1), and Open Space
(OS) zoning codes, which comprise over two percent of the county. According the
Summit County Development Code, these areas may suit light industrial businesses and community needs such as parks and preserves, but they cannot be used for housing or
42 associated commercial use. These areas plus NR-2 land compose over 80 percent of
Summit County.
Land Ownership Level of Area Percent of Government sq mi sq km Summit County Bureau of Land Management Federal 3.5 9.1 0.6 National Forest Federal 492.3 1275.0 79.5 State Owned State 0.7 1.8 0.1 Summit County County 6.7 17.3 1.1 Town Owned Town 3.2 8.3 0.5 Private None 112.8 292.2 18.2 Total 619.19 1603.7
Table 2.10 Land Ownership in Summit County
Land Owner Level of Government Suitability Value Bureau of Land Management Federal 1 National Forest Federal 1 State Owned State 3 Summit County County 6 Town Owned Town 8 Private/Non-Federal Government None 10
Table 2.11 Suitability Values Assigned to Land Ownership
43
Zoning Title Code Description Agriculture A-1 Agriculture and ranching Business B-1 Retail, service, and commercial business Business B-2 Same as B-2 Backcountry Zone BC Very limited low impact development; Conditions not favorable Industrial I-1 Light industrial Mining M-1 Mining operations Natural Resources NR-2 Currently or was federal or state land; Public outdoor recreation use Open Space OS Undeveloped Planned Unit Development PUD Innovative development Single Family Residential R-1 Housing Single Family Residential R-2 Housing Single Family Residential R-3 Housing Single Family Residential R-4 Housing Single Family Residential R-6 Housing Duplex Residential Single Family Residential with plan R-6 w/plan Housing Residential R-25 Housing Rural Community RC-5000 Housing in rural areas Rural Community RC-40000 Rural communities Rural Estate RE Housing Residential Mountain Estates RME Housing Residential with Plan R-P Housing Rural Residential RU Rural housing Special Use SU-1 Community use Blue River Town Breckenridge Town Dillon Town Zoning determined Frisco Town by town government Montezuma Town Silverthorne Town
Table 2.12 Zoning Codes from the Summit County Land Use & Development Code
44
Figure 2.10 Summit County Zoning (Generalized from Summit County G.I.S. Zoning)
45
Zoning Code Area Percent of County Residential Code sq mi sq km A-1 73.52 190.42 11.88 x B-1 0.031 0.08 0.00 B-3 0.05 0.13 0.01 I-1 0.02 0.044 0.00 M-1 15.04 38.95 2.43 NR-2 485.69 1257.94 78.47 PUD 10.40 26.94 1.68 x RE 0.044 0.114 0.01 x R-M 0.005 0.013 0.00 x RME 0.65 1.68 0.10 x R-P 1.02 2.64 0.16 x RU 0.064 0.17 0.01 x R-1 2.07 5.36 0.33 x R-2 2.38 6.16 0.38 x R-3 0.08 0.20 0.01 x R-4 0.61 1.58 0.10 x R-6 0.19 0.49 0.03 x R-25 0.28 0.73 0.05 x RC-5000 0.081 0.21 0.01 x RC-40000 0.055 0.14 0.01 x SU-1 0.10 0.026 0.00 R6 w/plan 0.34 0.88 0.05 x BC 10.89 28.21 1.76 x OSZD 0.38 0.98 0.06 Town 15.07 39.02 2.43 x Total 619.053 1603.107
Table 2.13 Extent of Each Zoning Code in Summit County
46 Several zoning codes are exclusively residential. Of the 31 codes used, 17 address housing density near towns and in rural areas. The number of dwellings range from one to six dwellings per acre. Several of the codes do not stipulate housing density, and in such cases the Summit County Planning Commission determines the appropriate density. Housing density codes in rural areas exhibit a much larger range. For example, in Agricultural (A-1) and Backcountry (BC) areas, only one dwelling is permitted per 20 acres, but Rural Communities (RC-5000 and RD-40000) may contain many single family dwellings per acre if permitted by the planning commission. Planned Urban
Development (PUD) is the only residential zoning code that is applied in urban and rural areas. This code does not limit housing density in areas that may range from ranches to ski resorts. PUD code area covers about two percent of Summit County.
The towns of Blue River, Breckenridge, Dillon, Frisco, Montezuma, and
Silverthorne have developed their own zoning codes, which are similar in most respects to the Summit County Development Code. The Summit County G.I.S. Department designates areas as towns to indicate town control over zoning. To compare these areas with the other Summit County zoning codes, the population density of each town and the county were determined by dividing population by area (Table 2.14) (US Census Bureau
2007). Frisco has the greatest population density (1,436 people per square mile), and
Dillon has the lowest population density (328 people per square mile). To compare with this with the zoning code population densities, the population of Frisco is less than 3 people per acre despite having the greatest population density in Summit County. If three people live in each dwelling, a total of 18 people could occupy an acre, and this is eight times larger than the density of Frisco, the town with the greatest density per acre in the
47 county. Using just these numbers, all of the towns in Summit County can accommodate
significant future development.
In an effort to preserve the natural character of Summit County the Planning
Commission encourages future development in and around existing development
(Summit County Development Code). The towns currently encompass much of the
development in the county. As such, towns were assigned a highest rank of 10, because
they include existing development and the potential for more considerate future growth.
The above data were crucial in determining suitability values for each zoning
code in the GIS being built in this study. Zoning codes designated as residential and
commercial with small lot sizes, high housing density, and local ownership were assigned
values ranging from 6 to 10, whereas zoning codes with rural, industrial, agricultural, and
conservation uses, large lot sizes, low housing density, and State and Federal government
ownership were assigned values from 1 to 4, or they were removed entirely. Areas
where development currently is not permitted under any circumstances were assigned a
value of zero (Table 2.15). The latter include areas such as Mining (M-1), Industrial (I-
1), Natural Resources (NR-2), Open Space (OS), and Special Use (SU-1). Values of 10 were assigned to Planned Unit Development (PUD), Business (B-1 and B-2), Residential
(R-25), Rural Community (RC-5000), Rural Mountain Estates (RME), Residential with
Plan (RP), and existing towns.
Data layers with reclassified zoning codes reveal that much of the county cannot
be developed within the existing zoning designations. Most of Summit County is
represented by zero or a low value (Figure 2.12). However, the current zoning codes are
not absolute, and the Summit County Planning Commission may need to change these to
48 accommodate future development. Also, the county may try to exchange or purchase land from the Federal government to accommodate growth. Thus, the current zoning codes in the county in the final analysis may be more guidelines than law.
Area Population Density (People per Square Mile) Geographic Area (sq mi) 2000 2001 2002 2003 2004 2005 Blue River 2.25 314 306 332 338 351 362 Breckenridge 5.42 446 472 484 485 489 494 Dillon 2.29 351 348 344 345 340 338 Frisco 1.75 1383 1370 1375 1393 1385 1382 Montezuma 0.079 532 544 544 544 532 532 Silverthorne 3.31 975 1044 1065 1088 1086 1091 Summit County 608 39 40 41 41 41 41
Table 2.14 Population Density in Towns and Summit County
49
Zoning Title Code Suitability Value Agriculture A-1 1 Business B-1 10 Business B-2 10 Backcountry Zone BC 1 Industrial I-1 0 Mining M-1 0 Natural Resources NR-2 0 Open Space OS 0 Planned Unit Development PUD 8 Single Family Residential R-1 4 Single Family Residential R-2 5 Single Family Residential R-3 6 Single Family Residential R-4 7 Single Family Residential/Duplex Residential R-6 9 Single Family Residential with plan R-6 w/plan 9 Residential R-25 10 Rural Community RC-5000 10 Rural Community RC-40000 4 Rural Estate RE 3 Residential Mountain Estates RME 10 Residential with Plan R-P 10 Rural Residential RU 2 Special Use SU-1 0 Town Town 10
Table 2.15 Suitability Values Assigned to Summit County Zoning
50
Figure 2.11 Suitability Values Assigned to Zoning
51 2.6 Proximity
The Summit County Development Code emphasizes that future development should occur in close proximity to existing towns and fire stations. Proximity to the existing road infrastructure and to ski resorts also is an important consideration. Buffers were created in ArcGIS around each of the above features based on available guidelines in the Development Code. The buffers vary between data layers according to the guidelines and with respect to existing development and topography.
The Summit County Code does not recommend particular distances from existing towns, but most development has occurred within ten kilometers of towns with the densest nearest to the towns. Using this information as a guide, five, two-kilometer buffers were created around each of the towns.
Most of the useful town data came from the Colorado Department of
Transportation (CDOT) cities GIS data layer for Summit County. Polygons in this layer outline Blue River, Breckenridge, Dillon, Frisco, and Silverthorne. Montezuma was not included despite its classification as a town in the 2000 US Census, because it currently has a permanent population of only 42. However, at the peak of the Colorado silver boom the population of Montezuma was nearly 1000, and thus, it may be able to support many times the current population in the future (RealEstateColorado.com). For this reason, Montezuma was added to the CDOT cities GIS data (Appendix B).
Buffers around the towns were generated with the Buffer Wizard in ArcGIS. The
Wizard creates any number of buffers at designated distances from items in a designated data layer. Five buffers at two kilometers intervals were created around town boundaries
52 in Summit County. Beyond these town buffers, an additional 15 buffers were created to cover the entire County. This was necessary, because ArcGIS designates all area beyond the buffers as ‘NoData’. This creates a problem when data layers are summed, because
‘NoData’ areas will not be included in the sum map. The town buffers were reclassified with the closest buffer assigned a value of ten, and the furthest buffer was assigned a value of one (Figure 2.12) (Table 2.16). The additional buffers were assigned a value zero.
The Summit County Development Code states that no major development can occur more than three kilometers from a fire station. The Code does allow cabins and small houses in areas zoned Backcounty where the terrain is very steep, and over time development has occurred adjacent to roads that extend beyond the three kilometer distance. Thus, the three kilometer radius will apply principally to future development.
Summit County currently is home to six fire stations, of which five are fully staffed (Table 2.17). The Lake Dillon Fire-Rescue Station at Silverthorne is a volunteer station that is not staffed 24 hours a day. The station locations were geocoded to create a fire stations data layer. Geocoding entails finding the addresses of fire houses and then determining the latitude and longitude of the addresses. The addresses of all fire stations were determined from Google Maps and entered into TravelGIS.com, a free geocoding website based on the coordinate system used in Google Maps (Appendix B). The latitude and longitude were entered into an Excel spreadsheet and imported into ArcMap as a point file of fire stations in Summit County.
53
Distance from Town Range (km) Suitability Value
0 to 2 10
2 to 4 8
4 to 6 4
6 to 8 2
8 to 10 1
All Other Buffers 0
No Data No Data
Table 2.16 Suitability Values Assigned to City Buffers
Fire Station Service Area(s) Frisco Dillon Areas in and around Keystone, Montezuma, Keystone Dillon, Silverthorne, Frisco, and Heeney Silverthorne Copper Mountain Copper Mountain Area
Red, White and Blue Breckenridge and Blue River
Table 2.17 Fire Station Service Areas in Summit County
54
Figure 2.12 Values Assigned to Suitability Buffers around Summit County towns
55 Two buffers were created around each station location. The zero to three
kilometer distance buffer was assigned a value of 10, and the three to six kilometer buffer
was assigned a value of three (Figure 2.13) (Table 2.18). The close buffer corresponds to
areas where major development is permitted, and the three to six kilometer buffer
encompasses most of the existing development that does not fall within the close buffer.
Thirteen additional buffers were created to cover Summit County, and these were
assigned a value of zero.
There are no specific guidelines for development near ski areas in Summit
County. However, these areas generally are in or adjacent to towns and include
considerable existing development. During ski season the population of Summit County
increases to perhaps four times the permanent population (Miller, 2005). Proximity to ski
areas was included in the GIS to help evaluate the potential for development in Summit
County. There are four large ski areas: Arapahoe Basin, Breckenridge, Copper
Mountain, and Keystone. In addition, the Loveland Basin ski area is located just west of
Summit County in Clear Creek County. The address of each ski area was found on
Google Maps and geocoded, and the coordinates were imported into ArcGIS (Appendix
B). Twenty-four buffers of two kilometers each were generated around each of the ski areas, but only the inner five were assigned values (Figure 2.14) (Table 2.19). The five
encompass distances that skiers might have to travel from nearby towns and regions of
residential zoning in Summit County. The closest buffer was assigned a value of 10, and the remaining four the values of 8, 6, 4, and 1. All other buffers were assigned a value of zero.
56
Range (km) Suitability Value
0 to 3 10
3 to 6 3
All Other Buffers 0
No Data No Data
Table 2.18 Suitability Values Assigned to Fire Station Buffers
Range (km) Suitability Value
0 to 2 10
2 to 4 8
4 to 6 6
6 to 8 4
8 to 10 1
All Other Buffers 0
No Data No Data
Table 2.19 Suitability Values Assigned to Ski Area Buffers
57
Figure 2.13 Fire Station Buffers
58
Figure 2.14 Ski Area Buffers
59 In addition to slope, traffic volume and road grade are used to determine where to
build roads and which class of road to build. The Summit County Development Code
and the Colorado Division of Transportation (CDOT) rank roads by number and width of
lanes, number of intersections, and a variety of other construction guidelines. Higher
class roads have more lanes and support heavier vehicles. Development generally is
permitted close to the higher rank roads, and this is where most lower class roads are
located. Preexisting roads are important at all levels, because these roads are present in
areas where past development occurred and where it likely will continue in the future.
The CDOT GIS data includes data layers for each of the three classes of roads
that are present in Summit County: highways, routes, and local roads (Figure 2.15)
(Table 2.20). One kilometer wide buffers were created around the three classes of roads
in the county: seven buffers around highways, five buffers around routes, and four
around local roads were ranked. A total of 17 buffers of one kilometer each were created
to cover Summit County in the highways and routes buffer layers. Local roads required
only 12 buffers to cover Summit County. In all three cases, a value of 10 was assigned to
the innermost buffer, and the furthest ranked buffer was assigned a value of one. The
other five buffers around highways were assigned values of 8, 6, 4, 3, and 2, the other
buffers around routes assigned values of 8, 4, and 2, and the other two local roads buffers assigned values of 7 and 4. All other buffers were assigned a value of zero to ensure correct addition when combining the layers.
60
Highways Range (km) Suitability Values 0 to 1 10 1 to 2 8 2 to 3 6 3 to 4 4 4 to 5 3 5 to 6 2 6 to 7 1 All Other Buffers 0 No Data No Data
Routes Range (km) Suitability Values 0 to 1 10 1 to 2 8 2 to 3 4 3 to 4 2 4 to 5 1 All Other Buffers 0 No Data No Data
Local Roads Range (km) Suitability Values 0 to 1 10 1 to 2 7 2 to 3 4 3 to 4 1 All Other Buffers 0 No Data No Data
Table 2.20 Suitability Values Assigned to Highways, Routes, and Local Roads Buffers
61
Figure 2.15 Highway, Routes, and Local Roads Buffers 62 2.7 Map Algebra: Adding Data
Map algebra is the process of adding, subtracting, or performing other arithmetic
on data layers. All of the data layers were summed to graphically show the suitability for development in Summit County on a single map. The suitability values assigned during reclassification are also summed to produce the single map.
To produce such a map, the data layers must be in the same map projection, they must all be in raster file format, and they must cover exactly the same geographical area.
If the projection and area extent of all the data layers do not overlap, the cells of the raster files will not line up correctly, and the sum value of each will not be accurate. Also, areas not rated in all raster files will be excluded (Figure 2.16a and 2.16b). The following manipulations were performed to generate a correct resultant map. GIS data from CDOT were projected in North American NAD 1983 UTM Zone 13N, which was used as the default coordinate system and datum for all data in the GIS. Data projected in any other coordinate system were re-projected with the Project Tool in Arc Toolbox
(Appendix A). Several of the data layers, including land ownership, zoning, and proximity buffers were created in Feature File format and converted into raster files with
Convert in the Spatial Analyst Toolbar (Appendix A). Lastly, all files were clipped exactly to the boundary of Summit County.
The data layers were added with Raster Calculator in the ArcGIS Spatial Analyst
Toolbar (Appendix A). This tool works like a handheld calculator, in which the data layer names are entered like numbers, and plus signs are put between the names. The raster files of each data type were added in small groups before all the groups were
63 combined. With each addition, the sums of several cells were checked to ensure that the files lined up correctly and that default averaging or other unwanted statistical operations were occurring. Also, the resulting values from each addition were checked for validity.
For example, if two rasters were added with a maximum value of 10 each, no value greater than 20 should result from the addition. Aspect and slope data, land ownership and zoning data, and proximity buffer data were added to create one sum file.
64
Continued
Figure 2.16 Map Algebra
65 Figure 2.16 Continued
66 2.8 Results: Final Addition Product
The final addition product identifies areas in Summit County that are best for development based on reclassified values assigned to the various data types (Figure 2.17).
In general, the best areas in the central part of the county, and lower value areas occur along county boundaries. Between the two are regions that are not the best but where development may occur at some point in the future. The latter region contains slopes that
may not face south, and which are some distance from roads and towns. Development
can still occur here, but these regions contain places where lower income-type housing
could be sited.
67
Figure 2.17 Final Addition Map
68 2.9 Possible Variations to the Final Addition Product
The final map product is based on data that includes development codes for
Summit County and the towns of Blue River, Breckenridge, Dillon, Frisco, and
Silverthorne. The codes were followed as closely as possible; however, they do contain exceptions. For example, Summit County zoning codes for Residential (R-25), Rural
Community (RC-5000), and Residential with plan (R-P) do not contain housing or lot density maximums. Developers can petition for changes to zoning codes like Planned
Unit Development (PUD) to change housing and lot density limits. These petitions to adjust limits and to accommodate greater density can be submitted to the Summit County
Planning Commission, but there is no guarantee that such petitions will be approved.
Also, the Summit County Planning Commission may rezone parts of the County as the permanent population grows. This sometimes occurs in areas that currently are zoned
Natural Resources (NR-2) and are adjacent to existing development. The Federal
Government sells, trades, or transfers land with private owners or with other government agencies. Values assigned to the Final map product in this study adhered to the most current versions of development codes and did not take into account possible exceptions or anticipated changes in development codes and.
During the decision-making process, values were assigned and ranges of data selected even for situations where strict town and county guidelines do not currently exist. According to the Summit County Development Code, major development is allowed only within three kilometers of fire stations. Also, zoning codes control housing densities. However, limits or ranking were not listed for other data types in the
69 Development Code. For example, no specific distance is listed for proximity of major
development to towns and to ski areas. These distances in the current study were determined through trial and error, which entailed creating buffers with various radii and
numbers of intervals around the different points of interest. The buffers used here were
chosen based the presence of existing development around towns and ski areas, the
presence of existing roads, and in the opinion of the author, what best fits various town
and county development codes.
2.10 Selecting Areas for Detailed Study
Several small sites where development is most favored for growth based on the
criteria being elevated here were selected for the final summary map for detailed study.
Analysis of topographic and urban planning data revealed a spectrum of land suitability
in Summit County that ranges from very favorable to unfavorable. Sites for follow-up
evaluation were selected from areas on the map that were rated moderately or very
favorable for development. These “postage stamps” are areas where developers, scientists, and government officials can perhaps agree that development can occur. Other
criteria used to select the areas were lack of current development or reservoirs and
sufficient area for major development. Areas of existing development and reservoirs and
of low suitability values and insufficient size were highlighted in ArcGIS and removed from consideration. To do this, the Areas to Remove data layer was created in
ArcCatalog. Polygons were drawn over areas to be eliminated, and each was labeled to
70 designate types of existing development, reservoirs, low suitability, or insufficient size
(Table 2.21).
Areas of existing development were delineated from USGS Digital Orthophoto
Quarter Quadrangle (DOQQ) aerial photographs, and from satellite images and road maps on Google Earth and Yahoo Maps. The DOQQs are black-and-white photographs that can be viewed in ArcGIS at scales ranging from 1:40,000 to 1:3,000. They were examined at large scales to identify small structures and to determine the type of development with which they are associated (Figure 2.18). For the southern half of
Summit County, DOQQs were purchased from USGS EarthExplorer. These images are quarter quadrangle size with high resolution and contrast. For the northern half of the county, the DOQQs were downloaded from the USGS Seamless website. These vary in size and generally are lower resolution and contrast, which made identification of development more difficult. Small structures were especially difficult to find, and maps and images from Google Earth and Yahoo Maps had to be used to confirm development in the northern half of the county.
DOQQs were imported into ArcGIS for viewing, and polygons were drawn over areas of existing development in the Areas to Remove data layer (Figure 2.19). The maps and images from Google Earth and Yahoo Maps also were consulted to identify development in areas not included in the DOQQs and to identify areas that had been developed since the DOQQ photography was taken. For example, areas designated for recreational use around Dillon Reservoir do not appear on the DOQQ, but they are clearly delineated on Google Earth and Yahoo Maps. For this study, the types of development were generalized to seven categories to make the final map easier to read.
71 Polygons covering areas of existing development make up approximately eight percent of
Summit County, and about half of this area is designated either as town or ski area.
Area of Development Includes Agriculture Farmsteads, crop fields Fire Station Too Far Area beyond 6 mile fire station buffer Low Value Area Final Additional Product Low Value (0 to 24) Major Road Highways Recreation Golf courses, recreational areas Residential Homes and subdivisions around towns Ski Area Breckenridge, Copper Mountain, Silverthorne Too Small Areas less than 2.25 square kilometers Too Steep Slopes assigned zero value in Part 1 Town Blue River, Breckenridge, Dillon, Frisco, Montezuma, Silverthorne Water Lakes, ponds, and reservoirs
Table 2.21 Areas of Existing Development
72
Figure 2.18 Designating Areas of Existing Development
73
Figure 2.19 Areas of Existing Development
74 Lakes, ponds, and reservoirs were identified from the DOQQs, from the Lakes shapefile downloads from CDOT, and from the maps and images in Google Earth and
Yahoo Maps. Several man-made ponds are also visible in small groupings near towns that likely are on golf courses. Development of golf course subdivisions could occur near these ponds. Many small natural lakes are present in the northwestern part of the county, but much of this area has steep slopes and is far from existing towns and roads. Thus, the lakes probably will not be the focus of future development. Green Mountain Reservoir and Dillon Reservoir are by far the largest reservoirs in Summit County. The Summit
County Planning Commission does not permit construction to replace reservoirs, lakes, and ponds, but it occasionally allows development around such features.
Polygons were drawn over the water features described above in the Areas to
Remove data layer. Lakes and ponds were grouped as lake, and Dillon and Green
Mountain Reservoirs were labeled reservoir. These polygons were added to the data layer containing the areas of possible development. All of bodies of water compose approximately two percent of Summit County.
Suitability values were split into three ranges of values, high, medium, and low, to highlight where these occur on the final map. In ArcGIS different data classifications can be selected according to what feature of the data is to be emphasized. In this study, a natural-breaks scheme was selected, because this classification method emphasized the difference between intervals of values (Krygier and Wood, 2005). Simply dividing the data into evenly divided groups would not do this. Low values range from 0 to 24, moderate values from 25 to 50, and high values from 51 to 100. This map reveals that most of the eastern and western parts of Summit County are not favored for development,
75 and polygons were drawn over these areas and over any other areas of value 24 and
below (Figure 2.20). All of these polygons were labeled low value area in the Areas to
Remove data layer.
Areas smaller than 2.25 square kilometers (0.87 square miles) were considered
too small for significant development and thus, too small for further analysis. Squares
and rectangles 2.25 square kilometers in area were created in ArcGIS to place over the
Areas to Remove data layer (Figure 2.21). Polygons were drawn over any 2.25 square
kilometer area that included low suitability values and 50 percent existing development
or more than 25 percent reservoir areas. These polygons were added to the Areas to
Remove.
Over 891 square kilometers of Summit County was removed from consideration
(Figure 2.22). This is more than 55 percent of the county and much of this area is zoned
Natural Resources (NR-2). One large area along the major river valleys remain as the
most suitable for development. Almost 35 percent of Summit County still lies within these regions, and this area is too large to be considered a “postage stamp”. Thus, small areas that range from 2.25 to 10 square kilometers were identified as areas that might be of special interested to realtors and developers.
76
Figure 2.20 Interval Map of Suitability Values
77
Figure 2.21 Area Filter to Find Best Suitable Areas for Development
78
Figure 2.22 Areas Eliminated from Consideration
79 Areas with slopes greater than 30 per cent grade and more than six kilometers from existing fire stations were also removed from consideration. These areas had been assigned a value of zero when the final map product data layers were reclassified.
However, these areas also may have been assigned high suitability values in other data
layers, which could have resulted in a moderate suitability value in the final map product
after all the reclassified data layers were summed. Polygons were drawn over these
areas, and they were designated either Too Steep or Fire Station Too Far in the Areas to
Remove data layer. Another 24 percent of Summit County was removed from further
consideration. The northern portion was removed completely as were large areas of
steep slope in the southern portion of the county.
Twelve locations ranging in area from four to nine square kilometers were
identified as suitable for development in southern Summit County (Figure 2.23) (Table
2.22). All are close to towns, fire stations, and ski resorts. Together, the 12 comprise
approximately 78 square kilometers (30 square miles), which is five percent of Summit
County.
Three of the 12 areas were selected for detailed analysis: Areas 5, 7, and 10.
Selection criteria included availability of GIS data, zoning variability, and location of
areas with respect to the others and existing development. Data available for further
analysis include two USGS Geologic Quadrangles, a digitized portion of the Geologic
Map of Colorado by Tweto, DEMs, and DOQQs (Table 2.23). As expected, all 12 areas
lie within the digitized Geologic Map of Colorado, but only the areas of Dillon and Frisco
quadrangles have the USGS geologic quadrangle data. All but one area are within the
80 available DEMs and DOQQs. The Summit County Area Soil Survey covers only central
Summit County.
A relative scale ranging from zero to eight was created to represent the available data coverage in each of the areas. Zero represents no data availability and four is complete data coverage for all the data except the USGS geological quadrangles. Values assigned to geologic data from the USGS geological quadrangles were doubled, because they are higher resolution and more detailed than data from the digitized Geologic Map of Colorado. Thus, zero still represents no data availability and eight is complete data coverage. Areas 5 and 6 exhibit the highest sum values and Area 8 the lowest sum (Table
2.23). Area 7 was the only areas to be covered completely by the Summit County Area
Soil Survey, and Areas 5, 6, and 12 were the only areas covered completely by the USGS geologic quadrangles.
All 12 of the areas were examined for zoning variability to avoid selecting areas that contained the same zoning codes. This was done to select differing areas for further analysis. The zoning for each area was clipped from the complete Summit County zoning coverage to calculate the percent area of each zoning code within an area (Figures
2.24, 2.25, 2.28, and 2.29) (Table 2.24). Most locations are 80 percent or more Natural
Resources (NR-2), which, coincidentally, is the only code present in all 12 locations. Of the 12, only Area 7 contains significant area that is classified under two zoning codes:
Backcountry (BC) and Natural Resources (NR-2). Agriculture (A-1) and Planned Unit
Development (PUD) are present in nine of the twelve areas, and PUD is significantly present in several of the locations. For example, Area 1 is 13 percent Agriculture (A-1);
Area 5 is 20 percent Planned Unit Development (PUD); and Area 4 is 13 percent Planned
81 Unit Development (PUD). All other codes together cover less than four percent in any one area.
Thirteen percent of Area 4 and twenty percent of Area 5 are zoned Planned Urban
Development (PUD), which not only favors development, but also can support higher density development. Area 7 differs significantly from the other areas, because approximately 48 percent is zoned Backcountry (BC) and 47 percent Natural Resources
(NR-2). Area 5 contains the largest area, 20 percent, that is zoned for major development. Areas 3, 9, and 11 contain the least area that can be developed.
The location of each area with respect to the other areas and existing development was also considered (Figure 2.23) (Table 2.22). Distances from each area to the three closest towns were measured. Areas 1, 3, 7, and 9 include small sections of town zoning:
Areas 2 and 6 are adjacent to Breckenridge, and Area 12 is adjacent to Frisco. Area 10 is closest to three towns, Frisco, Silverthorne, and Frisco, and Area 8 is the furthest from all towns with the closest, Breckenridge, almost 7 miles away. Areas 2, 5, 6, and 12 are adjacent and located between Frisco and Breckenridge. Areas 2, 5, 6, and 7 are located close to Breckenridge; areas 1 and 4 are close to Dillon; and areas 9, 10, and 11 are located close to Frisco.
82
Figure 2.23 Areas of Close Study
83
Area Extent (sq km) Closest Three Towns Distance Adjacent Ski Area 1 5.29 Dillon Included Keystone Silverthorne 3.27 Frisco 4.99 2 6.47 Breckenridge Adjacent Breckenridge Blue River 4.01 Frisco 6.67 3 5.18 Blue River Included Breckenridge Breckenridge Included Frisco 11.7 4 5.19 Dillon 1.23 Keystone Frisco 2.13 Silverthorne 3.74 5 8.54 Breckenridge 0.241 None Frisco 2.67 Blue River 6 6 7.24 Breckenridge Adjacent None Frisco 0.0339 Dillon 4.98 7 9.12 Breckenridge Included None Blue River 2.91 Frisco 7.1 8 5.15 Breckenridge 6.95 Copper Mountain Frisco 6.46 Blue River 10.6 9 6.82 Silverthorne Included None Dillon 3.97 Frisco 6.01 10 7.97 Frisco 0.165 None Silverthorne 0.819 Dillon 1.22 11 7.60 Silverthorne 0.0753 None Dillon 1.65 Frisco 2.67 12 4.83 Frisco Adjacent None Breckenridge 3 Silverthorne 5.72 Sum 79.40 (km)
Table 2.22 Extent, Closest Three Towns, and Adjacent Ski Area to 12 Areas 84
Data Availability Area Frisco Digitized Soil DOQQ DEM Geologic Tweto Survey Imagery Hillshade Quadrangle Geology 1 H C M C C 2 P C P C C 3 C P C C 4 M C M C C 5 A C H C C 6 C C H C C 7 P C C C C 8 C M C 9 M C P C C 10 M C M C C 11 M C H C C 12 C C P C C Value Assigned Area Frisco Digitized Soil DOQQ DEM Total Geologic Tweto Survey Imagery Hillshade Quadrangle Geology 1 4 4 3 4 4 19 2 2 4 1 4 4 15 3 0 4 1 4 4 13 4 6 4 3 4 4 21 5 8 4 2 4 4 22 6 8 4 2 4 4 22 7 2 4 4 4 4 18 8 0 4 0 3 4 11 9 6 4 1 4 4 19 10 6 4 3 4 4 21 11 6 4 2 4 4 20 12 8 4 1 4 4 21 Area Covered Value C Complete 4 M Most 3 H Half 2 P Partial 1
Table 2.23 Data Availability for 12 Areas of Close Study 85
Figure 2.24 Zoning for Areas 1, 2, and 3 86
Figure 2.25 Zoning for Areas 4, 5, and 6 87
Figure 2.26 Zoning for Areas 7, 8, and 9 88
Figure 2.27 Zoning for Areas 10, 11 and 12 89 Zoning Area % of Zoning Area % of Code (sq km) Area Code (sq m) Area 1 A-1 0.66 12.90 7 A-1 0.43 4.45 NR-2 4.10 79.70 BC 4.50 47.30 PUD 0.32 6.10 NR-2 4.56 48.00 R-2 0.054 1.04 Town 0.02 0.20 RE 0.0097 0.19 8 A-1 0.45 8.62 Town 0.0055 0.11 NR-2 4.45 86.10 2 A-1 0.20 3.05 PUD 0.27 5.27 BC 0.04 0.61 9 A-1 0.45 6.66 NR-2 6.10 93.30 NR-2 6.30 92.30 PUD 0.031 0.47 OSZD 0.017 0.24 R-1 0.057 0.88 R-P 0.045 0.66 R-2 0.61 0.93 Town 0.0084 0.12 RE 0.0099 0.15 10 NR-2 7.46 92.90 RME 0.037 0.57 PUD 0.57 7.12 3 A-1 0.28 5.50 11 NR-2 7.04 97.10 NR-2 4.76 92.10 OSZD 0.0022 0.03 PUD 0.0013 0.02 R-2 0.0090 0.12 R-1 0.079 1.52 R-3 0.081 1.12 RME 0.018 0.35 R-P 0.12 1.67 RU 0.014 0.29 12 A-1 0.073 2.02 Town 0.013 0.20 NR-2 3.34 91.80 4 NR-2 4.49 87.10 PUD 0.13 3.46 PUD 0.66 12.90 R-2 0.010 2.74 5 A-1 0.00021 0.00 NR-2 6.84 80.40 PUD 1.67 19.60 6 A-1 0.17 2.36 NR-2 6.87 94.30 PUD 0.15 2.13 R-1 0.029 0.39 R-2 0.048 0.65 RME 0.0094 0.13
Table 2.24 Zoning Extents for 12 Areas
90 2.11 Results
Areas 5, 7, and 10 were chosen for followed-up detailed analysis (Figure 2.28).
Area 5 was selected, because it contains the largest amount of Planned Unit Development that can accommodate high density development. In addition, there are more geologic and soil data available the area in comparison to the other areas, and it contains the most land that already is zoned favorable for major development. The greatest variability in zoning exists in Area 7, which also is the only area that is less than 80 percent Natural
Resources. Area 7 also is the only area that is covered completely by the Summit County
Area Soil Survey. Area 10 is close to the Dillon Reservoir, and it is less than two miles from Frisco, Silverthorne, and Dillon. It also contains significant Planned Unit
Development, and almost as much data are available as for Areas 5 and 6.
The remaining areas of the original 12 were eliminated from consideration at this time. Areas 2, 5, 6, and 12 all are located close to one another and lie between Frisco and
Breckenridge, and only one (Area 5) was selected for demonstration purposes. Areas 3 and 8 contain the least available data. In addition, Area 8 is the furthest from existing towns. Areas 3, 9, and 11 contain the least area zoned favorable for development, and
Areas 1 and 4 are close to other areas that have been selected for detailed study although they are attractive for development.
91
Figure 2.28 Selected Areas of Close Study 92 2.12 Conclusion
Topography, land ownership, county zoning, and proximity to roads, towns, and
ski resorts have been used to identify the part of Summit County that is best suited for
future development. These areas exhibit the highest values in the final map product.
Many areas of existing development coincide with the areas deemed favorable in this study, which validates the process followed here to identify such areas (Figure 2.29).
Initially, twelve areas were determined to be most suitable for future development. These areas are located in the southern portion of the county and comprise a total of 18 square kilometers, eight percent of the county. Of these, three areas were chosen for detailed analysis, Areas 5, 7, and 10
According to the final addition map product for Area 5, the areas assigned the zoning code PUD, and stream valleys with shallow slopes represent the most suitable areas for development. The most suitable areas occur in the western portion and close to the town Breckenridge in Area 7. In Area 10, areas assigned zoning code PUD, close to the towns of Frisco and Silverthorne, and land with shallow slopes were rated most
suitable for development. The geology and hydrology of these three areas will be
examined in the following chapter.
93
Figure 2.29 Suitability Values in Relation to Existing Development
94
CHAPTER 3
PART 2 OF ANALYSIS
3.1 Introduction
Bedrock geology, soil data, locations and number of lineaments, and water well
data were analyzed to refine conditions for development in Areas 5, 7, and 10 of the final
suitability map for Summit County. The data were not ranked, because county and town
codes contain few development guidelines with respect to geology, soils, and hydrology.
Attribute descriptions and literature were consulted to determine how to evaluate each data type with respect to development. After this evaluation was completed for each data type, maps were created to compare two data types to form additional conclusions to make the final decisions where to site future development in each of the three areas.
3.2 Data Collection
Creating data layers for bedrock geology, soil types, and water well locations is
very time intensive, because it often involves, digitizing paper maps, and processing the
data to make it compatible for use in ArcGIS. The bedrock geology for Summit County is available in two digital forms: U.S. Geological Survey 1:24,000 geologic quadrangles
for the Frisco and Dillon quadrangles, and a partially digitized Geological Map of
95 Colorado by Tweto (1979) (Figure 3.1). At least part of each of the areas of close study
is within the Frisco Quadrangle. Area 5 lies completely within the Frisco Quadrangle,
but much of Area 7 and a small portion of Area 10 are not covered. The Frisco
Quadrangle and its informational pamphlet were downloaded from the USGS Online
Publication Warehouse (2005). The portion of the Geologic Map of Colorado by Tweto
that covers southern Summit County was digitized by the USGS, and although no
geology key was included, the descriptions of lithologies are available on the USGS website. This map has much lower resolution than the Frisco geologic quadrangle map, because it is at a much smaller scale.
The Summit County Area Soil Survey is the only such survey in Summit County that can be downloaded through the National Resource Conservation Service (NRCS). It covers the Blue River valley and Dillon Reservoir as well as the larger towns in the
County (Figure 3.2). Soil descriptions, compositional tables, and supplementary information were imported into a Microsoft Access database, which then was used to produce reports by soil type. These reports include information that was used to evaluate soil conditions in areas of possible development.
Lineaments were identified on hillshade maps and in geographically-referenced aerial photographs. Hillshade maps represent topography as shaded relief surfaces that are illuminated by a simulated light source (Figure 3.3). These maps are generated in
ArcGIS with the Surface Analysis Tool, which uses digital elevation data, usually from a
DEM to simulate topography. The geographically-referenced aerial photographs are orthographic quarter quadrangle (DOQQ) aerial photographs that were used in the first part of this study to identify areas of existing development. These DOQQs were
96 purchased and downloaded from the USGS EarthExplorer website, and the Windows
Command Prompt was used to assign geographic coordinates to each image. After identification, high-resolution, color imagery from Google Maps was used to check the lineaments, in particular to remove manmade linear features.
Water well data are available by county from the Colorado Division of Water
Resources. These data document the location, permit number, well use, and the name of each well, plus yield, total depth of well, depth to static water level, and available permitting information for each well. The data also include geographic coordinates, which can be imported into the GIS.
97
Figure 3.1 Extent of Available Geologic Data
98
Figure 3.2 Extent of Available Soil Data
99
Figure 3.3 Example of DEM and Hillshade 100 3.3 Data Preparation for Analysis
Rock-type and soils data were imported into ArcGIS and clipped to the three
areas selected for close study. The Summit County Area Soil Survey data lacks an
attribute category for soil type. Instead, each polygon representing a soil is designated by
a code that corresponds to a soil type in the Access database. An Excel spreadsheet that matched soil types with the codes was imported into ArcGIS, and a Join Function was
performed to link these in the attribute table. The amended soil survey data then were
clipped to fit each of the study areas. The soil survey covers all of Area 7 and portions of
Areas 5 and 10.
Lineaments were identified based on the method used by Steele (1986), who
examined aerial photography and satellite imagery as well as topographic maps to
identify natural linear features that probably represent faults and other major rock
fractures. In the present study, large, regional lineaments and smaller linear features in
the areas of close study were digitized in ArcGIS from DOQQ and hillshade maps. The areas of close study are located within ten DOQQs (Figure 3.4). Hillshade maps have lower resolution than DOQQs and thus, regional lineaments can be seen only when hillshade maps are viewed at small scales. The hillshade maps of the Boreas Pass,
Breckenridge, Copper Mountain, Frisco, Keystone, and Vail Pass quadrangles were selected for study and mosaicked together to best delineate regional lineaments (Figure
3.5). This combined region includes Areas 5, 7, and 10, and it is the smallest scale at which lineaments can be confidently identified.
101
Figure 3.4 DOQQ Used in Lineament Analysis
102
Figure 3.5 Hillshade Maps Used in Lineament Analysis
103 Eight lineament shapefiles were created in ArcCatalog to record lineaments from
the DOQQ and hillshade maps: one for regional lineaments from the DOQQs, one per
area for local lineaments from the DOQQs (three total), one for regional lineaments from
the hillshades, and one per area for local lineaments from the hillshades (three total).
These eight files were imported into ArcGIS with the DOQQs, the hillshades, and the
outlines of Areas 5, 7, and 10.
The DOQQs were viewed at scales ranging from 1:71,000 for the full quadrangles
to 1:40,600 for quarter quadrangle. Local lineaments found in the DOQQ imagery were
drawn for the three areas of detailed study. All of Area 5 was visible at 1:24,000, and
sections could even be examined at a scale of 1:4,700. All of Area 7 was visible at
1:21,400, and lineaments were found at a scale as small as 1:3,336. Area 10 was
completely visible at 1:20,728, and areas were clear up to a maximum scale of 1:4,000.
Lineaments identified using this method were cross-checked with the high resolution
imagery available on Google Maps, the purpose being to remove manmade features.
Hillshade maps were created in ArcGIS using the Surface Analysis Toolbar in the
Spatial Analyst Extension. DEMs of the six selected quadrangles were mosaicked to
create one continuous surface. The Surface Analysis Tool uses continuous DEMs to
create hillshade maps from designated sun azimuth and illumination altitude above the
horizon. Several hillshades with different altitudes were created to identify which would
consistently reveal the most lineaments. After trying altitudes of 20, 30, 40, and 50
degrees, the ArcGIS default value of 30 degrees was determined to be the best altitude for
the present study. Eight hillshade maps were created, each with a different illumination
104 direction corresponding to an azimuth of one cardinal direction or a direction that bisects the cardinal directions (Figure 2.1).
To identify regional lineaments, the hillshade maps were viewed at scales ranging from 1:150,100 to 1:74,800. The smaller scale (1:150,000) corresponds to the view at which the entire composite hillshade was visible, and the largest scale (1:74,800) is the view at which approximately one quadrangle was visible. Local lineaments were identified at scales greater than 1:74,800.
The presence of lineaments was confirmed in hillshade maps of at least two azimuths. Graphical errors that can be mistaken for N-S or E-W lineaments may be incorporated into hillshades when they are created. However, errors such as these generally exist as long lines of different shade from the surrounding pixels only at one azimuth of the eight possible hillshades, which makes them easy to identify. Linear features were checked in at least two hillshade maps to avoid such errors.
Initially, the Summit County water well data contained 6,745 records. As used in this study, the well data contain permit number, well use(s), well depth, water level, yield, and geographic coordinates. Some editing of the original data was required to remove records from which key data are missing, e.g., permit number and geographic coordinates, which eliminated 283 records. The edited files where imported into ArcGIS
using the Add XY Data tool to create a shapefile of water well locations (Figure 3.6).
105
Figure 3.6 Water Well Locations
106 Areas selected for close examination, by their nature contain few water wells, and thus, wells that lie within one kilometer of the parameter were included in the analysis.
Two buffers, each 0.5 kilometer wide were created around the three areas. Records for wells within the buffers were exported from ArcGIS for analysis in Microsoft Excel, which also identified and removed wells with identical geographic coordinates.
Duplicate coordinates represent well updates, duplicate records, or groups of wells set close together. From the initial 637 well records exported from ArcGIS for the three areas and the corresponding buffers, 589 remained in the areas of close study after outdated and duplicate records were deleted.
3.4 Results and Analysis
3.4.1 Geology
The geology in the areas of close study varies greatly between the Geologic Map of Colorado and the Frisco Geologic Quadrangle. The difference is most apparent in
Area 5, for which data for the entire area are available in both maps. In all three areas
Frisco Geologic Quadrangle contains at least twice as many geologic units as the
Geologic Map of Colorado map. This is especially true for small areas of Quaternary deposits. The description of units in the pamphlet that accompanies the Frisco Geologic
Quadrangle addresses characteristics that are useful when units are being considered for development (Kellogg et al, 2002). For example, alluvium (Qal) forms in modern floodplains, and thus, it may flood during periods of increased precipitation or snow melt.
Young landslide deposits (Qls) show signs of slow creep, deeply weathered diamicton
107 (QTd) and bouldery gravel of the Mesa Cortina unit (QTgm) weathers to expansive soils that could damage building foundations. In addition, wetland deposits (Qw) officially are designated off-limits to development in the Summit County Development Code. The
Geologic Map of Colorado lacks this type of information, and thus, it was not used to evaluate areas for development.
Units from the Frisco Geologic Quadrangle were compared with aquifer maps in the Groundwater Atlas of Colorado to identify which units may be aquifers in the three areas of interest. Aquifer units in the Frisco Geologic Quadrangle include the Niobrara
Formation (Kn), Dakota sandstone (Kd), Entrara sandstone (Je), and the Morrison
Formation (Jm), which are high-yielding units within the Dakota-Cheyenne Aquifer of central Colorado (Topper et al, 2003). All of these units flank the Blue River valley, which also contain significant Quaternary deposits.
The Frisco Geologic Quadrangle shows 5.1 sq km (60 percent) of Area 5 to be
Quaternary material, generally along the Blue River Valley (Figure 3.7) (Table 3.1).
Mesozoic units in the eastern half of the Area are part of the Dakota-Cheyenne aquifer that is designated as an important aquifer unit in the Ground Water Atlas of Colorado
(Topper et al, 2003). Alluvium (Qal) and gravel diamicton (QTd) that cover 28 percent of Area 5 are unsuitable for development, but these units also are areas where water can easily infiltrate the underlying aquifers.
According to the Frisco Geologic Quadrangle almost 2 sq km of Area 7 is underlain by Mesozoic sedimentary formations (Figure 3.8) (Table 3.2). One square
kilometer is underlain by the aquifer units Niobrara Formation (Kn), Benton Shale (Kb),
Dakota Sandstone (Kd), and Morrison Formation (Jm). Almost 0.85 square kilometer
108 (30 percent) of this portion of Area 7 is the lower Pierre Shale (Kpl), which is not a source of potable water. Quaternary deposits cover 0.7 square kilometers of Area 7 as
Pleistocene to Pliocene bouldery gravel of the Gold Run unit (QTgg).
All 7.8 sq km of Area 10 were mapped as Quaternary deposits in the Frisco
Quadrangle (Figure 3.9) (Table 3.3). Gravel of the Mesa Cortina (QTgm) and younger landslide deposits (Qls) each cover about a third of Area 10. Together along with alluvium (Qal), wetland deposits (Qw), and gravel diamicton (QTd) these units eliminate more than 6.4 sq km or 80 percent of Area 10 from consideration for development – leaving only 1.4 of the 7.8 square kilometers as suitable.
109
Figure 3.7 Frisco Geologic Quadrangle at Area 5
110
Area Label Description (sq km) % Qal Alluvium (Holocene) 0.017 0.20 Qc Colluvium (Holocene and upper Pleistocene) 1.21 14.22 Qac Alluvium and colluvium, undivided 0.54 6.37 (Holocene and upper Pleistocene) Qtp Till of Pinedale glaciation (upper Pleistocene) 0.37 4.35 Qtb Bull Lake till, undifferentiated (middle Pleistocene) 0.0056 0.07 QTd Diamicton (middle Pleistocene to Pliocene?) 2.43 28.61 QTgg Gravel of Gold Run (Pleistocene to Pliocene?) 0.79 9.29 Tqp Quartz monzonite porphyry (Eocene) and 0.023 0.27 Pierre Shale (Upper Cretaceous) Kd Dakota Sandstone (Lower Cretaceous) 0.99 11.59 Jm Morrison Formation (Upper Jurassic) 0.47 5.49 Je Entrada Sandstone (Middle Jurassic) 0.12 1.40 TrPcm Chinle (Upper Triassic) and Maroon Formations 0.28 3.25 (Lower Permian to Middle Pennsylvanian) Xgg Granite gneiss 0.92 10.79 Xgd Granodiorite 0.0051 0.06 Xhpg Amphibolite and hornblende-plagioclase gneiss 0.28 3.29 Xbg Biotite gneiss 0.063 0.74 w Water 0.0019 0.02 Total Area 8.5
Table 3.1 Frisco Geologic Quadrangle Units in Area 5
111
Figure 3.8 Frisco Geologic Quadrangle at Area 7
112
Area Label Description (sq km) % Qal Alluvium (Holocene) 0.0010 0.04 QTgg Gravel of Gold Run (Pleistocene to Pliocene) 0.69 24.35 Tqp Quartz monzonite porphyry (Eocene) and 0.17 6.08 Pierre Shale (Upper Cretaceous), undivided Tmp Hornblende-biotite Monzonite Porphyry (Eocene) 0.0092 0.32 Kpl Lower Shale Member 0.85 29.92 Kn Niobrara Formation (Upper Cretaceous) 0.25 8.80 Kb Benton Shale (Upper Cretaceous) 0.48 16.71 Kd Dakota Sandstone (Lower Cretaceous) 0.17 5.89 Jm Morrison Formation (Upper Jurassic) 0.22 7.88 Total Area 2.84
Table 3.2 Frisco Geologic Quadrangle Units in Area 7
113
Figure 3.9 Frisco Geologic Quadrangle at Area 10
114
Area Label Description (sq km) % Qal Alluvium (Holocene) 0.13 1.69 Qw Wetlands 0.017 0.22 Qac Alluvium and colluvium, undivided 0.41 5.22 (Holocene and upper Pleistocene) Qls Younger landslide deposits 2.52 32.39 (Holocene and upper Pleistocene) Qg Terrace gravel (Holocene to middle Pleistocene) 0.11 1.35 Qtp Till of Pinedale glaciation (upper Pleistocene) 0.42 5.36 Qtb Bull Lake till, undifferentiated (middle Pleistocene) 0.39 5.07 QTd Diamicton (middle Pleistocene to Pliocene?) 1.2 14.98 QTgm Gravel of Mesa Cortina ('Buffalo placers') 2.6 33.08 (Middle Pleistocene to Pliocene?) w Water 0.049 0.64 Total Area 7.77
Table 3.3 Frisco Geologic Quadrangle Units in Area 10
3.4.2 Lineaments
Initially, more than 200 regional linear features were identified in the DOQQ imagery (Figure 3.10) (Table 3.4). Most were found when viewing the DOQQs at the scale 1:40,600. Regional lineaments range from 0.7 to 10 kilometers in length. The greatest number was found in Area 7 (176) and the least in Area 10 (127) (Figures 3.11 and 3.12). One-hundred-thirty-three lineaments were found in Area 5 (Figure 3.13). In all areas, lineaments generally were identified in regions of tree cover, along stream valleys, and where stark changes in shading occur. In addition to existing development, tree cover and shallow slopes often conceal lineaments in all three of the areas selected for detailed analysis.
115 Thirty-five of the smaller (local) lineaments that were identified in DOQQ
imagery were shown to be man-made in high resolution Google Map satellite imagery of the region. Five linear features that correspond to small, unpaved roads and agricultural
fields and fences also were removed in Area 5, and twenty-five lineaments were removed
from Area 7 that correspond to unpaved roads. Five man-made linear features were
found in Area 10 that correspond to boundaries of cleared fields.
A total of 315 regional lineaments were identified in the hillshade maps (Figure
3.14) (Table 3.4). They range from 0.8 to 10 kilometers in length, and most were found
when the landscape was illuminated from the northwest (315 degrees). (Table 3.4) Fifty
lineaments were found in Area 5 in hillshades that were illuminated from the north,
northwest, and northeast (Figure 3.15). Most of the lineaments correspond to streams and
river valleys in the northern half of the area where the topographic relief is greatest.
116
Lineaments Identified in DOQQ Maps Regional Area 5 Area 7 Area 10 Initial Total 200 133 176 127 Man Made 0 5 25 5 Final Total 200 128 151 122
Lineaments Identified in Hillshade Maps Direction Regional Area 5 Area 7 Area 10 North 11 14 13 9 Northeast 29 12 10 14 East 17 7 16 12 Southeast 20 0 12 0 South 22 1 6 4 Southwest 56 0 7 5 West 24 5 23 9 Northwest 136 11 12 12 Total 315 50 99 65
Table 3.4 Count of Lineaments Identified
117
Figure 3.10 Regional Lineaments Identified in DOQQ Imagery
118
Figure 3.11 Area 7 Lineaments Identified from DOQQ Imagery
119
Figure 3.12 Area 10 Lineaments Identified from DOQQ Imagery
120
Figure 3.13 Area 5 Lineaments Identified from DOQQ Imagery
121
Figure 3.14 Regional Lineaments Identified from Hillshade Maps
122
Figure 3.15 Area 5 Lineaments Identified from Hillshade Maps
123 Ninety-nine lineaments were identified in Area 7 (Figure 3.16). Most are in the
hillshade illuminated from the west. In regions with moderate slopes, the high resolution
Frisco DEM reveals the most lineaments in Area 7. A total of 65 local lineaments were
found in Area 10 (Figure 3.17). Most were identified in the hillshade illuminated from the northeast. Lineaments were difficult to spot in the northern half of Area 10, because a
subdivision with its access roads obscure natural detail. Generally, lineaments are
present throughout Area 10 with the greatest frequency near the southern boundary, close
to the Dillon Reservoir, Interstate 70, and the town of Silverthorne.
124
Figure 3.16 Area 7 Lineaments Identified from Hillshade Maps
125
Figure 3.17 Area 10 Lineaments Identified from Hillshade Maps
126 3.4.3 Soil
The Summit County Area Soil Survey includes 17 soil types, of which 12 are
present in the areas of close study (Table 3.5). More than half of the soil in all of the
areas is Frisco-Peeler Complex, which is a well-drained, glacially-derived soil (Figure
3.18). In general, most of the soils in the three areas are well-drained and do not flood.
However, floodplain soils typically are poorly drained, and by their nature are subject to
flooding. According to the soil survey reports, flooding also is common in areas of
Cumlic Cryaquolls and Histic Cryaquolls soils, which is a limiting factor for home and small business construction (Soil Survey Staff, 2007). In addition, the reports indicate that floodplain soils are hydric soils, because they flood during the growing season long
to enough to create anaerobic conditions. The presence of these soils is an indicator of
wetlands, which the Summit County Development Code specifies should be preserved or
restored where feasible (Summit County Planning Commission). Clay-rich exhibit moderate to high shrink-swell potential, which can cause structural damage to roads and buildings (Berry et al, 2002). Thus, Cimarron loam, Muggins sandy loam, Youga loam, and Yovimpa clay loam soils are to be avoided.
Soil data are available for 2.5 square kilometers in the east-central part of Area 5
(Figure 3.19) (Table 3.6). Seven soil types and one man-made unit (mine dumps) are present over 1.8 sq km (72 percent) of Area 5 that is covered with Frisco-Peeler Complex soils. Two square kilometers of the region is not covered by Cumulic Cryaquolls, Histic
Cryqauolls, and Youga Loam soils, of which can perhaps be developed.
127 The Summit County Area Soil Survey covers the entire nine square kilometers of
Area 7 (Figure 3.20) (Table 3.6). Six soil types and one-made unit (mine dumps) are
present. Almost 85 percent (7.8 sq km) of the soils in Area 7 are glacially-derived, and
there are no restrictions on development. Soils to avoid within Area 7 include Histic
Cryaquolls, Muggins sandy loam, and Yovimpa, which together with several mine dumps
eliminate more than one sq km of Area 7 from further consideration.
About 5.5 sq km of Area 10 are covered by the soil survey (Figure 3.21). Seven
soil types are present with almost 60 percent (3.2 sq km) is Frisco-Peeler Complex (Table
3.6). Collectively, potentially hazardous soils cover 1.9 sq km of Area 10 for the regions
where soil data are available, which leaves 3.6 square kilometers potentially available to develop.
128
Map Unit Parent Material Area 5 7 10 Cimarron loam Alluvium x Cumulic Cryaquolls Wetland x Frisco-Peeler complex Glacial drift x x x Grenadier gravelly loam Glacial drift x x Handran gravelly loam Glacial drift x Histic Cryaquolls Wetland x x x Leavitt loam Alluvium x Alluvium and/or glacial Muggins sandy loam drift x x Rock outcrop-Cryoborolls complex Slope alluvium x x Youga loam Glacial drift x x Youga loam, thick surface Glacial drift x Yovimpa clay loam Weathered shale/slate x Water N/A x Mine dumps N/A x x
Table 3.5 Soil Types Present in Each Area of Close Study
129
Figure 3.18 Glacially-Derived Soils at Areas of Interest 130 Area 5 Soil Name Area (sq km) % Cumulic Cryaquolls 0.087 3.45 Frisco-Peeler Complex 1.82 72.11 Handran Gravelly Loam 0.033 1.30 Histic Cryaquolls 3.28 12.99 Leavitt Loam 0.17 6.64 Youga Loam 0.0000010 0.00 Youga Loam 0.79 3.11 Mine dumps 0.010 0.40 Total Area 2.52 Area of Area 5 8.54
Area 7 Soil Name Area (sq km) % Frisco-Peeler Complex 7.2 78.93 Grenadier Gravelly Loam 5.03 5.54 Histic Cryaquolls 0.18 2.03 Muggins Sandy Loam 0.43 4.69 Rock Outcrop-Cryoborolls Complex 0.35 3.83 Yovimpa Clay Loam 0.033 0.37 Mine dumps 0.42 4.62 Total Area 9.08 Area of Area 7 9.12
Area 10 Soil Name Area (sq km) % Cimarron Loam 0.50 9.12 Frisco-Peeler Complex 3.2 58.24 Grenadier Gravelly Loam 0.42 7.64 Histic Cryaquolls 0.29 5.18 Muggins Sandy Loam 3.70 6.70 Youga Loam 5.39 9.77 Youga Loam, Thick Surface 0.17 3.14 Water 0.012 0.22 Total Area 5.51 Area of Area 10 7.97
Table 3.6 Soil Extents in Areas of Close Study
131
Figure 3.19 Soil Data at Area 5
132
Figure 3.20 Soil Data at Area 7
133
Figure 3.21 Soil Data at Area 10
134 3.4.4 Water Well Data
The majority of water wells in Summit County are located in and along the large
river valleys. Of the 589 well records selected for evaluation within the county, only 30
occur in Areas 5, 7, and 10. However, there are 559 wells within one kilometer of the
three areas, and 75 percent (419) of these are designated for either household or domestic
use. Of the remaining wells in the one-kilometer buffer, 143 are monitoring wells.
Eight water wells are present in the east-central part of Area 5, where water is utilized generally for household, monitoring, and livestock (Figure 3.22) (Table 3.7).
Four wells for which information is available average 21 gallons per minute (gpm), total well depths range from 64 to 275 feet, and the static water levels ranged from 20 to 100
feet. There are no wells in the western and northern parts of Area 5 or within one
kilometer of the north or west boundaries of the Area. However, in the other directions,
63 wells are located within one kilometer of the boundary of Area 5, in the direction of
Breckenridge.
Fifteen water wells are present in Area 7, of which all are for domestic and
household use, and two also provide water for livestock (Figure 3.23) (Table 3.7). The
mean yield for six is eight gpm, and total well depths and static water levels range widely
from 36 to 260 feet and from 28 to 128 feet, respectively. A large number of wells are
present within one kilometer to the north, west, and southwest, toward and into the city of
Breckenridge. There are 110 wells in the 0 to 0.5 kilometer buffer, 70 percent of which
are for domestic and household use, and the outer buffer contains more than twice the
wells in the inner buffer. Of 228 wells in this outer buffer, 90 percent are for domestic
135 and household use (Table 3.7). Yield, well depth, and static water level information is available for 184 of these wells. The average yield of buffer wells is six gpm, well depths range from 20 to 665 feet from the surface, and static water levels range, from 4 to
400 feet below the surface.
Only seven water wells are present in Area 10, located near the south and east boundaries of the Area (Figure 3.24). Six of the seven are for domestic and household use, and the remaining well is for crop irrigation (Table 3.7). The average yield is 16.7 gpm, total well depths range from 55 to 93 feet from the surface, and the static water levels range from 10 to 30 feet below the surface. An additional 158 wells lie within one kilometer of Area 10, most in a subdivision immediately northeast of Area 10 near
Silverthorne and to the south in the direction of Frisco. Eighty of the wells are for monitoring, but 56 are for domestic and household use (Table 3.7). The remaining wells in Area 10 are for irrigation, geothermal energy production, livestock, and snowmaking.
Ten municipal wells for the town of Frisco also are located within the one kilometer buffer for Area 10. The average yield within the one kilometer buffer is 10 gpm, ranging to 200 gpm, well depths range from 14 to 396 feet, and the static water level ranges from
10 to 110 feet below the surface.
136
Area 5 Use Within Area 0 to 0.5 km 0.5 to 1 km Commercial 1 3 Domestic 2 14 5 Domestic & Irrigation 1 Domestic & Livestock 1 2 Household 1 24 1 Monitoring 4 5 5 Municipal 1 1 Total Wells 8 48 15
Area 7 Use Within Area 0 to 0.5 km 0.5 to 1 km Commercial 1 2 Domestic 4 10 30 Domestic & Livestock 3 1 1 Household 8 66 171 Household & Livestock 1 4 Industrial 1 Monitoring 30 20 Total 15 110 228
Area 10 Use Within Area 0 to 0.5 km 0.5 to 1 km Commercial 1 2 Domestic 4 2 29 Domestic & Commercial 1 Geothermal 1 Household 1 24 Irrigation 1 4 Livestock 1 Monitoring 29 54 Municipal 8 Snowmaking 2 Total 6 37 121
Table 3.7 Well Uses in Areas of Close Study and Buffers
137
Figure 3.22 Water Well Locations within One Kilometer of Area 5
138
Figure 3.23 Water Well Locations within One Kilometer of Area 7
139
Figure 3.24 Water Well Locations within One Kilometer of Area 10
140 3.5 Data Comparisons: Part Two Data
Geologic and hydrologic data layers were overlain in ArcGIS to formulate
conclusions about suitability for building in the areas of detailed study. A symbology for
each layer was developed to highlight attributes suitable for development and to remove
unsuitable areas from consideration. In the current study, comparisons of lineaments and
geology, and geology and water well locations were performed for each area.
3.5.1 Lineaments and Geology
The Frisco Geologic Quadrangle was overlain with lineaments identified in the
hillshade maps and in DOQQ imagery to highlight areas with potential for potable water.
The combinations of lineaments and geologic units with high primary porosity, e.g., unconsolidated deposits and sedimentary bedrock; and lineaments that cut geologic units
exhibiting high secondary porosity, e.g., fractured crystalline rocks, identify regions
within the areas of close study where water is likely to flow within bedrock or where it
may be stored (Topper et al., 2003). Lineaments that underlie unconsolidated Quaternary
material or cut Mesozoic and Paleozoic sedimentary bedrock, and those that transect
highly fractured Proterozoic crystalline and Tertiary intrusive bedrock highlight areas
with significant potential for potable water in Summit County. Three types of maps were
created for each area of close study: lineaments and geology, lineaments and Quaternary
units, and lineaments and Tertiary and Proterozoic units. One set of maps was created for
lineaments identified in the DOQQ imagery and another for lineaments identified in
141 hillshade maps. In all, six maps were created for Areas 5, three for Area 7, and two for
Area 10, based on geologic units present in each area.
Lineaments identified in the DOQQ imagery cut or underlie every unit in Area 5
(Figure 3.25). Dense clusters of lineaments are present in the southeast part of the area,
where they underlay the bouldery gravel of Gold Run (QTgg), and cut Mesozoic Entrada sandstone (Je), and the Chinle and Maroon Formations (TrPcm). Seventy-eight of the mapped lineaments underlay Quaternary deposits with 63 intersecting either colluvium or diamicton (Figure 3.26). Diamicton typically exhibits shrink-swell properties, and thus, it likely will present hazardous conditions to development. Of the 24 lineaments that transect Mesozoic units, 15 cut potential aquifers (Dakota and Entrada sandstones). Two
lineaments cut Tertiary intrusive bedrock, and 16 cut Proterozoic units, both of which are
potential sources of potable water because of their brittle behavior during deformation
(Figure 3.27).
A smaller number of lineaments (50) were identified in the hillshade maps of
Area 5, although they generally are longer than those identified in DOQQ imagery
(Figure 3.28). Thirty-one hillshade lineaments transect Quaternary units with almost half
of those in terrace gravels (Qc) (Figure 3.29). Ten lineaments cut Mesozoic units, several
intersect Tertiary quartz monzonite porphyry (Tqp), and nine cut the Proterozoic bedrock
(Figure 3.30). Six lineaments intersect diamicton (QTd), and landslide deposits (Qls),
both of which are not suitable for development.
Only the northwest part of Area 7 is covered by the Frisco Geologic Quadrangle
(Figure 3.31). Sixty-two of the lineaments identified in DOQQ imagery occur within the
area of the quadrangle, of which 46 are in Mesozoic units. Fifteen lineaments occur in
142 the Niobrara (Kn) and Dakota (Kd) sandstones, which are good potential aquifers, but 23
occur in the lower shale member of the Pierre Shale (Kpl), which very likely will not yield potable water. Fifteen lineaments occur in a dense cluster beneath the bouldery gravel of Gold Run (QTgg) (Figure 3.32).
Fewer lineaments were identified in the hillshade maps than in the DOQQs for
Area 7, and they generally are longer with the longest being almost four kilometers
(Figure 3.33). Of the 47 lineaments in the area covered by of the Frisco Geologic
Quadrangle, most (36) cut Mesozoic units, including the aquifer units Niobrara sandstone
(Kn) and Dakota sandstone (Kd).
Most of Area 10 falls within the Frisco Geologic Quadrangle. Lineaments vary in length from 0.13 to almost 3 kilometers (Figure 3.34). Of the 121 lineaments identified in
DOQQ imagery, 100 underlie geologic units that likely will not be developed: 41 in
Quaternary landslide deposits (Qls), 49 in the bouldery gravel of the Mesa Cortina
(QTgm), nine in diamicton (QTd), and one in floodplain alluvium (Qal). All of the
Quaternary units in Area 10 typically have high rates of recharge, and thus, may be ideal
localities to site water wells even if development cannot occur in most of it.
Of the 64 lineaments identified in hillshade maps in Area 10, 52 underlay
Quaternary landslide deposits (Qls), tills of the Pinedale glaciation (Qtp), and the
bouldery gravel of the Mesa Cortina (QTgm) (Figure 3.35). The tills of the Pinedale
glaciation might be appropriate for development, and they are located along the eastern
boundary of the Area near interstate 70 between the towns of Frisco and Silverthorne.
143
Figure 3.25 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle
144
Figure 3.26 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle Quaternary Units
145
Figure 3.27 Area 5 DOQQ Lineaments and Frisco Geologic Quadrangle Tertiary and Proterozoic Units
146
Figure 3.28 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle 147
Figure 3.29 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle Quaternary Units 148
Figure 3.30 Area 5 Hillshade Lineaments and Frisco Geologic Quadrangle Tertiary and Proterozoic Units 149
Figure 3.31 Area 7 DOQQ Lineaments and Frisco Geologic Quadrangle
150
Figure 3.32 Area 7 DOQQ Lineaments and Frisco Geologic Quadrangle Quaternary Units
151
Figure 3.33 Area 7 Hillshade Lineaments and Frisco Geologic Quadrangle
152
Figure 3.34 Area 10 DOQQ Lineaments and Frisco Geologic Quadrangle
153
Figure 3.35 Area 10 Hillshade Lineaments and Frisco Geologic Quadrangle
154 3.5.2 Water Wells and Geology
Geologic units were recorded where water wells in Area 5 and within the one
kilometer buffer were drilled (Figure 3.36). The eight wells in Area 5 penetrate
Proterozoic, Tertiary, and Quaternary units, and three are in the Chinle and Maroon
Formations undivided (TrPcm). The deepest well is in Proterozoic biotite gneiss (Xbg).
There is no distinct pattern between well use and geologic formation in Area 5.
However, of the 63 wells in the one kilometer buffer, 46 are in Quaternary units, and
nearly all are located in the southeast part of the buffer toward of the town of
Breckenridge. Thirty-nine wells are in alluvium (Qal) and in boulder gravel of Mesa
Cortina (QTgg). Also, water flows down valleys through Quaternary material and toward
the Blue River, which provides additional recharge capacity during the late spring and
summer as the snow pack melts. Of the 15 wells currently set in alluvium, 12 are used
for household or domestic purposes, and the other three for monitoring purposes. Seven
of the wells in dredge tailings along the Blue River valley north of Breckenridge are
monitoring wells. All household and domestic wells within the one kilometer buffer
around Area 5 are either in Quaternary units or in Proterozoic bedrock. In summary,
large areas of Area 5 and its surrounding buffer probably contain significant potable
water.
Only a small portion of Area 7 lies within the Frisco Geologic Quadrangle, and
information on geologic units is available for only six wells in the Area (Figure 3.37).
They are in the Niobrara Formation (Kn), Benton Shale (Kb), and Morrison Formation
(Jm), all of which are Mesozoic units. Of the 338 wells within the one kilometer buffer
155 around Area 7, the underlying geology is known for only 72. Forty-one are in the lower
shale member of the Mesozoic Pierre Shale (Kpl), near the eastern border of the Frisco
Quadrangle; 18 are in Quaternary units; and the remaining are in either Tertiary quartz monzonite porphyry (Tqp) or dredge tailings. Wells within the buffer average 13 gpm yield, which is adequate for household use, and a dense cluster of wells in one region suggests that additional wells can perhaps be drilled there.
Six wells in Area 10 were drilled into Quaternary material with five of the six in landslide deposits (Figure 3.38). The other well is in the boulder gravel of Mesa Cortina
(QTgm), and it is the only well used for crop irrigation. The six wells all are relatively shallow, the deepest being 92 feet, and they yield from 15 to 40 gpm. The wells are in the southeastern part of the Area, but those within the one kilometer buffer are to the north, east, and south. There are 158 wells in the one kilometer buffer, almost all of which are in Quaternary units: 96 in Pinedale glacial till (Qtp) and 35 in Pinedale outwash material (Figure 3.45). Eighty-two of the wells are used for monitoring, and 61 are used for household and domestic use. In addition, ninety-seven wells have been drilled within the town limits of Frisco in Pinedale outwash deposits and in glacial till between the Dillon Reservoir and Interstate 70.
156
Figure 3.36 Frisco Geologic Quadrangle and Water Well Locations at Area 5
157
Figure 3.37 Frisco Geologic Quadrangle and Water Well Locations at Area 7
158
Figure 3.38 Frisco Geologic Quadrangle and Water Well Locations at Area 10
159 3.6 Data Comparisons: All Data
Maps were created to compare data from Chapters 2 and 3 to compare geology
and slope angle, geology and the final suitability addition map values for development, and well locations and zoning.
3.6.1 Geology and Slope Angle
All three of the areas of close study contain variable slopes. In Chapter 2, slope
was rated 0, 1, 2, 8, 11, 13, and 20, with shallow slopes assigned values of 11, 13, and 20;
moderate slopes a value of 8; and steep slopes values of 0, 1, and 2. The later slopes
cannot or should not be developed. Geologic units underlying areas of shallow slopes are used to highlight regions where development can occur.
Large regions of shallow slope in the central and northern parts of Area 5 are underlain by colluvium (Qc), Dakota Sandstone (Kd), Morrison Formation (Jm), granitic gneiss (Xgg), and amphibolites and hornblende plagioclase gneiss (Xhpg) (Figure 3.39).
Areas of shallow slope also exist along stream valleys on Quaternary alluvium deposits
(Qac).
There are few shallow slopes in Area 7 (Figure 3.40). Geologic units that underlay these include bouldery gravel of Gold Run (QTgg), quartz monzonite porphyry
(Tqp), the lower Pierre shale (Kpl), the Dakota Sandstone (Kd), and the Morrison
Formation (Jm). Regions with moderate slopes are underlain by bouldery gravel of Gold
Run, Benton Shale (Kb), and Dakota Sandstone, all of which can accommodate development.
160 Approximately 2.0 sq km of Area 10 contains slopes with ratings of 11, 13 and 20
(Figure 3.41). However, except for small areas on till of the Bull Lake and Pinedale glaciations, and terrace gravel (Qg) in the eastern part of the Area, much of the low slope region is not suitable for development.
161
Figure 3.39 Frisco Geologic Quadrangle and Slope Data at Area 5
162
Figure 3.40 Frisco Geologic Quadrangle and Slope Data at Area 7
163
Figure 3.41 Frisco Geologic Quadrangle and Slope Data at Area 10
164 3.6.2 Geology and the Final Suitability Addition Map
Suitability values from the final addition map (Figure 2.20) were divided into
three intervals: low, medium, and high, the divisions used in Chapter 2. Areas of
moderate suitability are shaded in the following figures, and high suitability areas are
translucent to clearly display the underlying geologic units.
Suitability for development in Area 5 is either medium or high throughout (Figure
3.42). Regions of high suitability are in the eastern and southern portions of the Area,
and they are underlain by colluvium (Qc), diamicton (QTd), and bouldery gravel of Gold
Run (QTgg), plus several minor units. The western part of Area 5 is moderately suitable
for development in the direction of the Ten Mile Mountain Range. Geologic units there
are diamicton, and large areas of Pinedale till (Qtp), plus granitic gneiss (Xgg) and
amphibolite and horneblende-plagioclase gneiss (Xhpg).
The portion of Area 7 that is covered by the Frisco Quadrangle Geologic map coincides with regions for which there are high suitability values for development (Figure
3.43). Most of the geologic units there are Mesozoic, and all are suitable for
development.
The central and eastern parts of Area 10 are highly suitable for development, and
the western portion also exhibits moderate values (Figure 3.44). However, most of Area
10 is not suitable for development, where it is underlain by diamicton (QTd), till of the
Pinedale glaciation (Qtp), till of the Bull Lake glaciation (Qtb), younger landslide
deposits (Qls), and alluvium deposits (Qac).
165
Figure 3.42 Frisco Quadrangle Frisco and Suitability at Area 5
166
Figure 3.43 Frisco Quadrangle Frisco and Suitability at Area 7
167
Figure 3.44 Frisco Quadrangle Frisco and Suitability at Area 10
168 3.6.3 Zoning and Water Well Locations
All eight of the water wells in Area 5 are within area zoned Planned Unit
Development (PUD), and correspond to the only development in the area: the Red Tail
Ranch (Figure 3.45). Almost half of the 63 wells within one kilometer of Area 5 are in
residential R-4 zoning, and 50 of the 63 are in zoning classified for residential use. All
seven monitoring wells in the one kilometer buffer are located to the east in A-1 zoning
along the Blue River and near dredge tailings (Figure 3.46).
There are few water wells in Area 7, because to date there has not been significant residential development there (Figure 3.47). Fifteen wells are used in the Area for household or domestic use, three of which are also used for livestock. Of the 338 wells in the one kilometer buffer surround Area 7, 227 are in zoning designated for residential development. The density of wells increases within the region of PUD zoning to the north, in residential zoned regions to the southwest (R-1 and R-2), and in agriculture zoning (A-1) to the south, near Breckenridge.
The six water wells that are sited in Area 10 are in a PUD zoned area, and they are used for domestic purposes (Figure 3.48). Of the 158 wells in the one kilometer buffer around Area 10, 145 are in residential zoning. Area 10 is near the towns of Frisco and Silverthorne as well as I-70, and these factors alone make it attractive for development, providing land can be leased or transferred from the National Forest
Service. There already are several housing subdivisions within a distance of one kilometer to the north of Area 10 (Figure 3.49).
169 Most existing water wells in Summit County are in the large river valleys where
towns and residential buildings are located, which corresponds to agriculture, planned unit development, residential, and town zoning (Figure 3.50). This trend can be expected to continue as new areas of construction naturally will require water for irrigation, household use, and domestic and livestock drinking water.
170
Figure 3.45 Water Well Locations and Summit County Zoning at Area 5
171
Figure 3.46 Water Well Uses and Summit County Zoning at the Blue River
172
Figure 3.47 Water Well Locations and Summit County Zoning at Area 7
173
Figure 3.48 Water Well Locations and Summit County Zoning at Area10
174
Figure 3.49 Water Well Locations in Subdivisions North of Area 10
175
Figure 3.50 Water Well Locations and Summit County Zoning
176 3.7 Conclusions
3.7.1 Area 5
Seventy-two percent of Area 5 was deemed suitable for development. Of the 178
lineaments identified throughout the area, 107 are associated with potential aquifers: 18
correspond to the Dakota and Entrada sandstones, 64 to permeable Quaternary units, and
25 to fractured Proterozoic bedrock. In addition, many of the potential aquifer units lie in
shallow slopes, and they are cut by east-west trending valleys that provide access where
roads in existing developments could be extended into large areas of shallow slope and
suitable geology.
Soil data and surficial and bedrock geology effectively removes 34 percent (2.9 sq km) of Area 5 from consideration for development, but lineament and water well data
suggest that adequate water will be available if the remaining 5.6 square kilometers are
developed (Figure 3.51). The few water wells that are present within Area 5 on a private
ranch were drilled in Quaternary deposits, in Tertiary intrusive bedrock, and in
Proterozoic gneisses. The variety of units that currently support water wells within Area
5 and the one kilometer buffer indicate that new wells and well fields likely can be drilled
into several aquifer units, which is particularly true where the aquifer units are intersected
by bedrock lineaments.
177
Figure 3.51 Regions Best for Development in Area 5 178 3.7.2 Area 7
Evaluation of Area 7 was limited to the northwest, which is part of the Frisco
Geologic Quadrangle. These data cover only 2.8 square kilometers of Area 7, although
the soil survey data covers all of the Area. Of this, 2 square kilometers are underlain by
units that can be expected to produce potable water. These units include Quaternary deposits, Tertiary intrusive bedrock, and Mesozoic sedimentary bedrock.
Of the 275 lineaments identified in and near Area 7, 109 lie within the region covered by the Frisco Geologic Quadrangle, and all but four cut or underlay potential aquifers in Quaternary, Tertiary, and Mesozoic units. Only six water wells have been drilled in Area 7, and these all are in Mesozoic aquifer units. The 72 wells that lie within the one kilometer buffer also are in potential Quaternary, Tertiary, and Mesozoic aquifer units.
Only 12 percent of Area 7 is overlain by soils that are not suitable for development, but the zoning in Area 7 does not particularly suit development (Figure
3.52). Most of the Area originally was designated Backcountry and Natural Resources, but, several small regions to the west of Area 7 and east of Breckenridge already contain development, which may signify that it will be possible in Area 7 if the county can change current zoning conditions.
179
Figure 3.52 Regions Best for Development in Area 7
180 3.7.3 Area 10
About 20 percent (1.6 sq km) of Area 10 is underlain by geologic units that are suitable for development (Figure 3.53). Of the 185 lineaments identified in and partially within Area 10, 180 are within the area covered by the Frisco Geologic Quadrangle.
Forty-six underlie potential Quaternary aquifer units along the eastern boundary of the
Area. The greatest densities of water wells are in the towns Dillon, Frisco, and
Silverthorne. More than half of the 164 water wells in Area 10 are used for monitoring purposes in and near these three towns. Most of the wells were drilled into Pinedale outwash deposits and till, but 11 also are in units that have been deemed herein as unsuitable for development, including alluvium, younger landslide deposits, and boulder gravel of the Mesa Cortina.
181
Figure 3.53 Regions Best for Development in Area 10
182
CHAPTER 4
CONCLUSIONS & FUTURE WORK
A Geographic Information System (GIS) that includes data on slope angle, aspect,
zoning and land ownership information, and proximity to cities and areas of interest has
highlighted 208 sq km (81 sq mi) of Summit County that maybe suitable for
development. Twelve locations that range in area from four to nine square kilometers
have been identified as particularly favorable for development in the County. Three of
these areas were selected for follow-up evaluation to demonstrate the high resolution effectiveness of the GIS, and to identify areas where development can readily begin.
Bedrock and surface geology, and soil and water supply data are not addressed in the Summit County Development Code. High resolution geologic data and lineament occurrences in the Frisco 7.5 minute Geologic Quadrangle and in the Summit County
Area soil survey, together with water well data were used in the three areas as the basis for identifying potential building sites.
As might be expected in areas where topography and geology are extremely variable, the suitability for development varies greatly from area to area. Area 5 lies immediately northwest of the town of Breckenridge, and it contains the largest area identified as suitable for development. The Area encompasses the Red Tail Ranch,
183 which is an operating entity of 1.7 sq km (Figure 3.58). The northwest corner of Area 7 also is covered by the Frisco Quadrangle, and overall, more than 8 sq km has been identified as suitable for development. Twenty percent (1.6 sq km) of Area 10, which is situated close to the towns of Dillon, Frisco, and Silverthorne as well as to Interstate 70 probably is suitable for development.
4.1 Future Work
The GIS developed in this study can be applied anywhere in the world where data are available. Whereas this study concentrated on identifying areas that are best suited to accommodate population growth in Summit County, the GIS can be used in other ways.
For example, areas for businesses (grocery stories, service industries, etc.) that support population growth can be identified, and ski resorts and golf courses, even town sites can be identified given appropriate guidelines. The high cost of living in Summit County limits the availability of affordable housing for support staff that are employed by the county itself, and by businesses associated with skiing and tourism. Currently, affordable housing in the County is limited to trailer parks and small homes and duplexes, and employees often cannot find even these accommodations. Instead, they are forced to commute to Summit County from surrounding counties (RRC Associates and Rees
Consulting, 2007). The GIS defined above can also be used to solve this problem.
Slopes facing east, west, and even north might be excellent places to site affordable housing and still conform to requirements in the Summit County Development Code.
184 Such sites could be close to ski areas, even if they do not abut existing roads and
emergency facilities.
Data sources that might be used to refine the model developed here include the
USGS Central Colorado Assessment Project (Kellogg and Klein, 2007), which aims to
conduct water, mineral, geologic hazard, and climate analyses while revising existing 30’
x 60’ geologic quadrangles in central Colorado. As of September 2008, the project had
produced an updated Geologic Map of the Denver West 30’ x 60’ Quadrangle that
includes part of eastern Summit County. On a larger scale and directly pertinent to
Summit County, water and sediment sample locations in theses by Conaway (OSU, 1999)
and Vinciguerra (OSU, 2003) can be imported easily into the GIS (Figure 4.1).
As a practical insight, all of the twelve areas deemed appropriate for development in this study should be field inspected prior to any planed development. For example, every DEM used in this study has a pixel resolution of 100 square meters (10 by 10 meters), and at this resolution, slopes may be quite irregular despite what is displayed in
the DEMs. Information such as this could be especially important to land-use planners.
185
Figure 4.1 Example of Additional Data
186
APPENDIX A
G.I.S. GLOSSARY AND PROCESSES
187 Add XY points
This is located in the Tools menu. It allows for database files (ex. DBF or Excel
Spreadsheets) with geographic coordinates to be imported into ArcGIS. The proper
geographic coordinates are usually designated as X and as Y. For example, latitude is X
and longitude is Y. A projection is also assigned to the imported data, and ArcGIS
displays the points based on that reference in a temporary event file. The event file can
be exported as a shapefile, which can be edited and analyzed.
Buffer Wizard
This Wizard allows for easy creation of a buffer. The distance and number of
buffers is designated around a selected file. If buffers overlap, options in the buffer wizard allow boundaries of buffers with identical values to be dissolved within an
otherwise continuous buffer.
Clipping a raster to a nonrectangular polygon
There is no tool for clipping a raster to a nonrectangular polygon like the border
of Summit County. Thus, this clip is performed with the Raster Calculator in conjunction
with settings in the Spatial Analyst toolbar Options. In Options, the file extent is set to the polygon of desired extent like Summit County. The file to be clipped is entered in the Raster Calculator, and when run, the Raster Calculator clips the raster to the extent of the designated polygon.
188 Data types
In GIS there are two basic ways data is represented: vector and raster. Points,
lines, and polygons represent vector data. Vector data is discontinuous. Examples of
data in this format include locations of cities and towns, population, and zoning tracts.
Raster or grid data represent a continuous surface. Temperature, elevation, and slope are
examples of raster data. Sometimes raster data are aerial photographs that have been
assigned geographic coordinates like digital orthographic quarter quadrangles.
Digital Elevation Models
Digital elevation Models or DEMs are available for download from either the
USGS or GeoComm for no charge. Many USGS data layers available are downloaded in
their proprietary Spatial Data Transfer Standard file format (SDTS) including DEMs.
The full ArcInfo package is required to decompress these files. The ArcInfo Arc
Toolbox contains the ‘Import from SDTS’ command. This command will decompress
and convert the SDTS file into a DEM raster for use in ArcGIS.
Features to Rasters
This tool is located in the Spatial Analyst Toolbar under Convert. This is one of
several ways to convert a feature file like a shapefile to a raster file.
189 Import from SDTS Tool
This is located in the Data Management Arc Toolbox XX. It converts spatial data
transfer standard, SDTS, files into a raster file for use in ArcGIS. The ArcInfo license is
required for use of this tool.
Identifying Coordinate System
There are two methods to identify the coordinate system for data if it is listed as
Unknown. The first method is to check the accompanying files for projections if the data were downloaded. Coverage files in particular usually retain in what projection the data were created. This method is the easier of the two, but it requires the full ArcInfo license, which was not available in the department computer lab.
The second method is detailed in the ArcGIS Desktop Help under the heading
‘Defining a shapefile’s coordinate system’. First the probable coordinate systems have to be determined by consulting maps that have state plane and UTM zone boundaries. For example, Summit County data would either be in State Plane Colorado Central Zone or
UTM Zone 13. The data is then displayed in ArcGIS and reference systems data fields are added to compare the locations of both. The unknown data file was also compared with other files with designated datums to match coordinates at the same location. This is important because there is a 200 foot difference between NAD 1927 and NAD 1983.
190 Join
This links the attributes of a file with those of another or a database. This is not a
permanent link unless data are exported as a new file.
Mosaic tool
This tool is used to combine segmented raster files into one continuous raster such
as adjacent DEMs or digital aerial photographs. It is located in the raster tools in the
Data Management Arc Toolbox.
Project Tool
This tool is located in the Data Management Arc Toolbox under Projections and
Transformations. This is used to change the projection or to assign a projection if the coordinate system is indicated as unknown. The coordinate system has to be identified before assigning a projection with this tool to ensure that the correct one is used. (See
Identifying Coordinate System) A data layer can be reprojected with this tool only if the projection is known.
191 Raster Calculator (Adding data)
Raster Calculator is located in the Spatial Analyst toolbar. Mathematical operations or SQL statements are entered and creates a new raster. The raster data has to be in an appropriate format according to how the user wants to evaluate it. Thus, for this project, the data was reclassified to values that could be combined with other rasters to produce a meaningful result of the highest values corresponding to the best areas of development and lowest values to the worst or unacceptable areas.
Reclassify
The Spatial Analyst and 3D Analyst toolbars in ArcMap contain this command. It
allows for values to be assigned to particular attributes of a raster or grid file. In the
context of this work, higher values were assigned to attributes favorable for development
and lower values or zero to attributes least or not favorable for development. Attributes
reclassified in this project include distances, zoning codes, slopes, aspects, and land
owner.
Surface Analyst
Surface Analyst evaluates surface data found in datasets like DEMs to produce
aspect, slope, hillshade maps.
192
APPENDIX B
DATA CREATED FOR STUDY
193
Zoning Title Code Description Agriculture A-1 Agriculture and ranching 1 dwelling per 20 acres Business B-1 Retail, service, and commercial business Coordination and clustering of business development encouraged Discourage strip malls Encourage low scale, low impact areas (Except in areas near major ski resorts) Business B-2 Same as B-1 Backcountry Zone BC Undeveloped character of Upper Blue Basin Very limited low impact development consistent with historical development Services (water, sewage, etc) not provided Conditions often not favorable for development Industrial I-1 Light industrial compatible with existing zoning Mining M-1 Mining operations Natural Resources NR-2 Currently or formerly federal and state land Prevent coming under county rule Use for public outdoor recreation Designation until rezoning should land be legally obtained by county Open Space OS Protect and preserve undeveloped state Predominately undeveloped Planned Unit PUD Innovative development compatible with setting Development Mixture of use and housing types 6 dwellings per acre with more upon approval Single Family R-1 1 dwelling per acre, 1 dwelling per lot Residential Adjacent to urban growth centers Single Family R-2 2 dwellings per acre, 1 dwelling per lot Residential Adjacent to urban growth centers Access to central sewage Single Family R-3 3 dwellings per acre, 1 dwelling per lot Residential Adjacent or within urban growth centers Access to central sewage and water
Continued
Table B.1 More Detailed Description of Summit County Zoning Codes 194 Table B.1 Continued
Zoning Title Code Description Single Family R-4 4 dwellings per acre, 1 dwelling per lot Residential Adjacent or within urban growth centers Access to central sewage, water, and utilities Single Family R-6 Single family homes and duplexes Residential/ 6 units per acre, 2 dwellings per lot Duplex Adjacent or within urban growth centers Residential Access to central sewage, water, and utilities Single Family R-6 Same as R-6 Residential w/plan Plan for greater housing density Residential R-25 Residential zoning Plan for greater housing density RC- Rural Community 5000 Single family residential neighborhoods Unincorporated communities More intense development (village-like) RC- Rural Community 40000 1 dwelling per acre, 1 dwelling per lot Rural unincorporated communities Recreational orientation Rural Estate RE Transition between urban centers and rural areas 1 dwelling per 2 acres to 1 dwelling per < 5 acres Lots of at least 2 acres Residential RME No description provided Mountain Estates Residential with Plan R-P Dwelling density to be determined Rural Residential RU Maintain rural character Low density residential development 1 dwelling per 5 acres to 1 dwelling per < 20 acres 1 dwelling per 5 acres in cluster subdivisions Special Use SU-1 Community use (recreational, cemetery, etc) Density determined by site Blue River Town Zoning determined by town government Breckenridge Dillon Frisco Montezuma Silverthorne 195
Corner Longitude Latitude 1 39.5815 -105.8713 2 39.5816 -105.8702 3 39.5833 -105.8700 4 39.5834 -105.8691 5 39.5846 -105.8688 6 39.5849 -105.8661 7 39.5794 -105.8654 8 39.5784 -105.8679 9 39.5795 -105.8683 10 39.5787 -105.8689
Table B.2 Coordinates for Corners of the Town of Montezuma
196
Fire Station Address Lake Dillon Fire-Rescue Station 2 Frisco 301 South 8th Ave Lake Dillon Fire-Rescue Station 8 Dillon 225 Lake Dillon Dr Lake Dillon Fire-Rescue Station 11 Keystone 22393 US Highway 6 Lake Dillon Fire-Rescue Station 10 Silverthorne 401 Blue River Parkway Copper Mountain Fire Department 513 Copper Road Red, White and Blue Fire Department 316 North Main St
Fire Station Town Zip Code Lake Dillon Fire-Rescue Station 2 Frisco Frisco 80443 Lake Dillon Fire-Rescue Station 8 Dillon Dillon 80435 Lake Dillon Fire-Rescue Station 11 Keystone Keystone 80435 Lake Dillon Fire-Rescue Station 10 Silverthorne Silverthorne 80498 Copper Mountain Fire Department Frisco 80443 Red, White and Blue Fire Department Breckenridge 80435
Fire Station Latitude Longitude Lake Dillon Fire-Rescue Station 2 Frisco 39.574108 -106.091898 Lake Dillon Fire-Rescue Station 8 Dillon 39.630375 -106.046096 Lake Dillon Fire-Rescue Station 11 Keystone 39.607425 -105.962778 Lake Dillon Fire-Rescue Station 10 Silverthorne 39.632454 -106.07448 Copper Mountain Fire Department 39.502088 -106.151664 Red, White and Blue Fire Department 39.484959 -106.046156
Table B.3 Summit County Fire Stations Address and Geocoded Coordinates
197
Name Address Arapahoe Basin 23836 US Highway 6, CO 80435 Breckenridge 1801 Ski Hill Rd, Breckenridge, CO 80424 Copper Mountain 940 N Ten Mile Dr, Frisco, CO 80435, USA Keystone 21996 US Highway 6, Keystone, CO, 80435 Loveland 3877 US Highway 6, Georgetown, CO 80444
Name Latitude Longitude Arapahoe Basin 39.653939 -105.876039 Breckenridge 39.482705 -106.067619 Copper Mountain 39.588417 -106.093816 Keystone 39.605849 -105.975406 Loveland 39.69135 -105.87955
Table B.4 Summit County and Loveland Ski Areas Addresses and Geocoded Coordinates
198
Symbol Name Qg Pinedale and Bull Lake Gravel and Alluvium Qd Glacial Drift of the Pinedale and Bull Lake Glaciations Qdo Older Glacial Drift (Pre-Bull Lake Age) Td Dry Union Formation TKi Laramide Intrusive Rocks Kp Pierre Shale, Undivided Kc Colorado Group KJdm Dakota and Morrison Formations IPm Minturn Formation and other mid Pennsylvanian Age Units Xb Biotitic Gneiss, Schist and Migmatite Xfh Felsic and Hornblendic Gneisses, Separate or Interlayered
Table B.5 Colorado Geologic Map Units in southern Summit County (Tweto, 1979)
199
Symbol Name Qal Alluvium Qw Wetlands Qc Colluvium Qac Alluvium & Colluvium, undivided Qls Younger landslide deposits Qg Terrace gravel Qtp Till of Pinedale glaciation Qtb Bull Lake till, undifferentiated QTd Diamicton QTgm Gravel of Mesa Cortina QTgg Gravel of Gold Run Tqp Quartz monzonite porphyry & Pierre Shale Tmp Hornblende-biotite Monzonite Porphyry Kpl Lower Shale Member Kn Niobrara Formation Kb Benton Shale Kd Dakota Sandstone Jm Morrison Formation Je Entrada Sandstone TrPcm Chinle and Maroon Formations, undivided Xgg Granite gneiss Xgd Granodiotrite Xhpg Amphibolite and hornblende-plagioclase gneiss Xbg Biotite gneiss w Water
Table B.6 Frisco Geologic Quadrangle Units (Kellogg, Bartos, and Williams, 2002)
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