Seismic Imaging of the Hayward Fault Near the California

Home , Hayward Fault Zone, Warren Hall

SEISMIC IMAGING OF THE HAYWARD FAULT NEAR THE CALIFORNIA

STATE UNIVERSITY AT EAST BAY HAYWARD CAMPUS

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A University Thesis Presented to the Faculty

California State University, East Bay

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In Partial Fulfillment

of the Requirements for the Degree

Master of Science in Geology

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Collin Quesenberry

May 2019

Abstract

The Hayward Fault (HF) is an active, right-lateral, strike-slip fault that strikes ~325° through the eastern San Francisco Bay Area (East Bay) from Milpitas to Point Pinole,

California. The more broadly defined Hayward Fault Zone (HFZ) includes the HF and lesser subparallel faults, which structurally separate major lithologies in the East Bay.

The dominant lithologies west of the HFZ are metamorphosed sedimentary and igneous rocks, whereas clastic sedimentary and igneous rocks dominate areas to the east. The core of the HFZ is a 1- to 3-km-wide terrane, dominated by ophiolite rocks and oriented along the eastern side of the HF, which I refer to as the San Leandro Block (SLB).

The western margin of the SLB, specifically the active trace of the HF, is the focus of my research. I collaborate with the California State University at East Bay

(CSUEB) and the United States Geological Survey (USGS) Earthquake Science Center at

Menlo Park, California. Our work advances the goal of using seismic velocities to interpret a three-dimensional structural model of the HFZ. This study continues efforts by the CSUEB and USGS to evaluate the near surface structure of the SLB on and around the CSUEB Hayward campus. We use seismic refraction methods, which are especially adept at identifying the high-angle fault zones and complexly deformed geologic materials that characterize the SLB.

I analyze P-wave and S-wave velocity data (VP and VS) from two nearly coincident seismic refraction surveys that we conducted across the active trace of the HF, in 2013 and 2017 respectively. The 2013 dataset consists of low-resolution VP and VS data from ten 4.5-Hz three-component seismographs (vertical, horizontal-transverse, and

horizontal-longitudinal), spaced at ~30-m-intervals perpendicular to the HF. The 2017 dataset consists of high-resolution VP data from sixty-three 4.5-Hz vertical-component geophones along a seismic profile that was similar to the 2013 seismic profile. I use seismic refraction analyses to produce cross-sectional models of VP, VS, VP/VS ratios, and Poisson’s ratios for the 2013 data and the 2017 data.

I correlate these results with the known seismic characteristics of geologic materials, and previous geologic mapping, to interpret the geometry of geologic materials and fault segments in the near surface. Refraction tomography models show that VP/VS ratios > 2.0 and Poisson’s ratios > 0.3 generally coincide with VP > 2.0 km/s and VS > 0.7 km/s, which we expect as the seismic expression of bedrock. These relationships, when compared to geologic mapping, indicate that the HF separates highly weathered gabbro and/or basalt to the east from alluvium to the west. Based on the velocity models and geologic mapping, the active HF likely dips ~75° toward the northeast at the study area.

At least two splay faults, one ~50-m-west of the HF and another ~150-m-east of the HF, further separate the lithologies at the study area. The eastern splay is likely a west- dipping fault that places basalt structurally above gabbro, whereas the western splay is likely an east-dipping fault that places basalt structurally above alluvial sediments. There is no mapped evidence for the western splay; however, a study by Catchings et al. (2006) has shown that there are many buried faults within the sediments west of the HF. A buried fault ~50-m-west of the active trace of the HF would increase the seismic hazard for the businesses and residences that are adjacent to the western end of the study area.

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SEISMIC IMAGING OF THE HAYWARD FAULT NEAR THE CALIFORNIA

STATE UNIVERSITY AT EAST BAY HAYWARD CAMPUS

Collin Quesenberry

Acknowledgements

Thank-you, Dr. Luther Strayer and Dr. Jean Moran, for the guidance you gave toward focusing my research and academic interests during my time in the CSUEB Earth and Environmental Sciences Graduate Program. Thank-you, Dr. Rufus Catchings, Ms.

Joanne Chan, and Mr. Mark Goldman, for the opportunities you gave to me as mentors at the USGS Earthquake Science Center. Thank-you, my fellow graduate students Adrian

McEvilly and Ian Richardson, for the close assistance you gave as I conducted my research and completed this thesis. I want to extend my thanks to all the volunteers who assisted me in bringing my research to fruition.

Table of Contents

Abstract ……………………………………………………………………… ii

Signatures ……………………………………………………………………… iv

Acknowledgements ……………………………………………………………… v

Lists of Figures and Appendices ……………………………………………… vii

Introduction ……………………………………………………………………… 1 Tectonic Setting ……………………………………………………… 1 Tectonic Framework ……………………………………………………… 6 San Leandro Block ……………………………………………………… 9 Background and Purpose ……………………………………………… 12 Study Area ……………………………………………………………… 13

Seismic Methods ……………………………………………………………… 18 Seismic Waves ……………………………………………………… 18 Seismic Surveying Techniques ……………………………………… 20 Seismic Data Processing ……………………………………………… 24

Data Acquisition ……………………………………………………………… 26 Seismic Surveys ……………………………………………………… 26 Data Overview ……………………………………………………… 36

Data Analyses ……………………………………………………………… 37 Seismic Refraction Analysis …………………………………………… 37 Multi-channel Analysis of Surface Waves ……………………………… 41 VP/VS ratios and Poisson’s ratios ……………………………………… 44

Results ……………………………………………………………………… 48 VP models ……………………………………………………………… 48 VS and MASW models ……………………………………………… 50 VP/VS ratio and Poisson’s ratio models ……………………………… 52 Interpretations ……………………………………………………… 56

Discussion ……………………………………………………………………… 65

Conclusion ……………………………………………………………………… 71

References ……………………………………………………………………… 74

Appendices ……………………………………………………………………… 85

List of Figures

Figure 1: Important faults of the central San Francisco Bay Area ……………… 2

Figure 2: The Hayward Fault Zone ……………………………………………… 3

Figure 3: Geologic overview of the central East Bay Area ……………………… 8

Figure 4: The San Leandro Block ……………………………………………… 11

Figure 5: Location of the Carlos Bee study area ……………………………… 14

Figure 6: Three versions of fault positions across the study area ……………… 16

Figure 7: Geology of the study area based on Graymer (2000) ……………… 17

Figure 8: Geology of the study area based on Jennings et al (2010) …………… 18

Figure 9: Snell’s Law for seismic waves ……………………………………… 20

Figure 10: Seismic wave propagation for a refraction survey ……………… 21

Figure 11: Cross-sectional diagram of a geophone ……………………………… 22

Figure 12: Example shot gather ……………………………………………… 23

Figure 13: Diagram of shot gather trends ……………………………… 23

Figure 14: Seismic profiles for 2013 and 2017 ……………………………… 27

Figure 15: Operation of a hand auger ……………………………………… 29

Figure 16: Preparation of a real-time kinematic GPS device ……………… 30

Figure 17: Example geophone station in the seismic profile ……………… 31

Figure 18: Geode seismograph station ……………………………………… 32

Figure 19: View of the field headquarters ……………………………………… 33

Figure 20: Operational view of the survey monitoring software ……………… 34

Figure 21: Betsy Seisgun™ emplacements ……………………………………… 35

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Figure 22: Preparation of an explosive charge emplacement ……………… 35

Figure 23: Example shot gather for an explosive charge source ……………… 36

Figure 24: Example shot gather data for a Betsy Seisgun™ shot ……………… 37

Figure 25: Example first arrival trend for a Betsy Seisgun™ shot ……………… 38

Figure 26: Travel path coverage model for 2017 ……………………………… 39

Figure 27: P-wave model for 2017 (P17) ……………………………………… 40

Figure 28: P-wave model for 2013 (P13) ……………………………………… 41

Figure 29: Example MASW processing steps ……………………………… 42

Figure 30: MASW model for 2017 (M17) ……………………………………… 43

Figure 31: S-wave models for 2013 ……………………………………… 44

Figure 32: VP/VS ratio and Poisson’s ratio models for 2017 ……………… 45

Figure 33: VP/VS ratio models for 2013 ……………………………………… 46

Figure 34: Poisson’s ratio models for 2013 ……………………………………… 47

Figure 35: VP structures of P17 ……………………………………………… 49

Figure 36: VP structures of P13 ……………………………………………… 49

Figure 37: VS structures of 2013 VS models ……………………………… 51

Figure 38: VS structures of M17 ……………………………………………… 52

Figure 39: VP/VS ratio and Poisson’s ratio anomalies for 2017 ……………… 53

Figure 40: VP/VS ratio anomalies for 2013 ……………………………………… 54

Figure 41: Poisson’s ratio anomalies for 2013 ……………………………… 55

Figure 42: Interpretations of P17 and P13 ……………………………………… 58

Figure 43: Interpretations of M17 ……………………………………………… 60

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Figure 44: Interpretations of 2013 VS models ……………………………… 61

Figure 45: Interpretations of 2017 VP/VS ratio and Poisson’s ratio models …… 63

Figure 46: Interpretations of 2013 VP/VS ratio models ……………………… 64

Figure 47: Interpretations of 2013 Poisson’s ratio models ……………………… 65

Figure 48: Simplified geologic cross-section ……………………………… 71

List of Appendices

Appendix 1: Glossary of acronyms ……………………………………… 85

Appendix 2: Equipment used for the 2017 survey ……………………………… 86

Appendix 3: Geophone stations for the 2017 survey ……………………… 87

Introduction

Tectonic Setting

The Hayward Fault (HF) is an active, right-lateral, strike-slip fault that strikes

~325° through the eastern San Francisco Bay Area (East Bay) (Figure 1). The HF extends along the western margin of the East Bay Hills, from near Milpitas in the south to San

Pablo Bay near Point Pinole in the north (Lienkaemper, 1992; Graymer et al., 1995A).

An exact location for the active trace of the HF has been determined by combining field evidence from earthquake ruptures, geomorphic features, cross-fault trenching, fault creep, and damage to manmade structures (Lienkaemper, 1992). Seismological research suggests that the HF cuts through the entire crust (Parsons, 1998), and with a steep dip of

~70° toward the northeast (Waldhauser & Ellsworth, 2002; Williams et al., 2005).

The broadly defined Hayward Fault Zone (HFZ) includes the active trace of the

HF and related subsidiary faults that are within ~10 kilometers (km) of the HF (Graymer et al., 1995A; Wakabayashi, 1999; Graymer et al., 2002) (Figure 2). The southern terminus of the HFZ originates as a restraining step-over from the Calaveras Fault near

Mission Peak Regional Preserve (Graymer et al., 2002; Manaker et al., 2005;

Wakabayashi, 2007). Parsons et al. (2003) interprets the northern terminus of the HFZ as a releasing step-over to the Rodgers Creek Fault; however, high-resolution seismic reflection images, magnetic and gravitational anomalies, and observed seismicity by Watt et al. (2016) now indicate that the HF and the Rodgers Creek Fault are structurally continuous in the near surface.

Point Pinole → Area of Figure 2

San Francisco Oakland

Livermore Hayward

Fremont

Milpitas

Legend Major Bay Area Faults San Andreas (active) Hayward (active) North Calaveras (active)

Minor Bay Area Faults Holocene aged (potentially active) 30 km Quaternary aged (not active)

Figure 1: Important faults of the central San Francisco Bay Area (USGS, 2006)

Moraga Fault

Piedmont Miller Creek Fault Reverse Fault Chabot Fault

Ashland Fault Palomares Fault

Step-over from Calaveras Fault to Hayward Fault

Legend Hayward Fault (active) Holocene aged faults (potentially active) Quaternary aged faults (not active) North

30 km

Figure 2: Faults in the East Bay that constitute the HFZ (USGS, 2006) See an overview of important subsidiary faults on Page 4

Important subsidiary faults within the HFZ include the Moraga Fault (MF), Miller

Creek Fault (MCF), Palomares Fault (PF), Chabot Fault (CF), Piedmont Reverse Fault

(PRF), and the Ashland Fault (AF). The MF, MCF, and PF are east-verging high-angle reverse faults trending 2-7 km east of and subparallel to the HF, together defining the eastern boundary of the HFZ (Graymer et al., 1995A). The CF has been mapped as a normal fault with two subparallel strands, emerging as a step-over from the HF, north of

Fremont, which trends up to 2 km east of and subparallel to the HF and terminates back to the HF in Oakland (Graymer et al., 1995A; Graymer, 2000). However, right-lateral offset of gravels between the HF and CF indicate the CF is actually an oblique right- lateral fault (Graymer et al., 1995B). The PRF is a west-verging high-angle reverse fault that splays 1-2 km to the west from and parallel to the HF through eastern Oakland

(Graymer et al., 1995A; Catchings et al., 2017). The AF is a west-verging oblique thrust fault that branches ~1 km to the west from the HF and forms an eyelid pattern through

Ashland (Rubin, 2011). The structural relationships among faults in the HFZ indicate that the East Bay Hills have significant internal deformation.

The HFZ began forming ~12 Million years ago (Ma) and has facilitated up to

~100 km of right-lateral offset in the East Bay (Graymer et al., 2002); on average, the right-lateral offset rate of the HFZ has increased to ~10 millimeters per year (mm/yr) since 6 Ma. Of that accumulating HFZ offset, ~9 mm/year of right-lateral slip transfers to the HF from the Calaveras Fault (Wakabayashi et al., 2004); a similar right-lateral slip rate of ~9 mm/year represents the strain accommodated between the HF and the Rodgers

Creek Fault. Offset of the Quaternary-aged gravels between the HF and CF indicates that

the CF has 23-50 km of accumulated right-lateral slip along it for the Quaternary period, whereas the HF may have as little as ~3 km of accumulated right-lateral slip for the same period (Graymer et al., 1995B). Offset of the Berkeley Hills Volcanics (Figure 3) indicates the MF-MCF-PF zone has up to 75 km of accumulated slip since ~9 Ma

(Graymer et al., 2002). In particular, the offset estimated by Graymer et al. (1995B) implies the active HF is likely quite young among faults within the HFZ.

The active trace of the HF exhibits aseismic creep, by which offset slowly accumulates at and near the surface between earthquakes, and coseismic slip, by which offset rapidly accumulates during earthquakes. Creep rates vary along the HF, and range in magnitude from ~3 mm/yr in Oakland to ~10 mm/yr in Fremont (Lienkaemper et al.,

2001). Creep distribution, when compared to slip rates based on Global Positioning

System (GPS) data, Interferometric Synthetic Aperture Radar data, and repetitive small- magnitude earthquake data, indicates the HF is accumulating a slip deficit equal to a 6.8 moment-magnitude (M6.8) earthquake every 100 years (Schmidt et al., 2005). Structural continuity from the HF to the Rodgers Creek Fault implies either of these faults could produce an earthquake as large as M7.4 (Watt et al., 2016). The sole documented historic

HF earthquake occurred on October 21, 1868 (Lawson, 1908), for which most intensity estimates infer magnitudes ranging from M6.5 to M7.0 (Hough & Martin, 2015). San

Leandro is the estimated epicenter for the 1868 HF Earthquake (Bakun, 1999).

Paleoseismic trenching provides evidence for earthquake recurrence intervals on the HF (Lienkaemper et al., 1999, 2010). The earthquake interval on the northern HF has been broadly constrained between 270-years and 710-years for the last ~2000 years

(Lienkaemper et al., 1999), whereas the recurrence interval on the southern HF has been estimated to be 161 ± 65 years for the last ~1900 years (Lienkaemper et al., 2010).

Relationships between the previously discussed characteristics of the HF allow us to investigate areas that we expect will produce the next large HF earthquake. The estimated epicenter of the 1868 HF earthquake is on the ~30-km-long segment of the central HF with the lowest recorded creep rates (Lienkaemper et al., 2012). Reduced creep rates on the southern HF, following the M6.9 1989 Loma Prieta Earthquake, imply variations in stress load in that area (Lienkaemper et al., 2001), whereas creep rates along the central HF indicate locking or retarding at seismogenic depths along a segment up to

50-km-long (Simpson et al., 2001; Evans et al., 2012; Lienkaemper et al., 2012). The distribution of HFZ earthquake hypocenters support the notion that there are several locked patches within the HF seismogenic zone (Waldhauser & Ellsworth, 2002), due possibly to accumulation of shear stresses at seismogenic depths, along high-friction lithologies (Evans et al., 2012) that may control the magnitude and recurrence of HF earthquakes (Lienkaemper et al., 2012).

Tectonic Framework

The HFZ is a structural boundary separating two of the major lithotectonic groups of the Bay Area (Figure 3). (1) Franciscan Complex lithologies are dominant to the west of the HFZ and Great Valley Sequence lithologies are dominant to the east of the HFZ

(Fuis, 1998; Graymer, 2000; and Elder, 2013). The Franciscan Complex consists of thrusted metamorphic terranes, principally derived from clastic marine sediments and mafic igneous rocks, metamorphosed through a high-pressure low-temperature regime;

Franciscan lithologies represent a west-vergent accretionary wedge, originally metamorphosed during a period of ocean-to-continent subduction, initiated as early as

~200 Ma and subsequently exhumed since ~100 Ma (Wakabayashi, 1999). Thrusting of

Franciscan lithologies placed increasingly older Franciscan Complex terranes in structurally higher and eastern positions (Elder, 2013). (2) The Great Valley Sequence is a Jurassic- to Cretaceous-aged series of alternating submarine fan deposits that represent a forearc basin, which formed to the east of and coeval to the Franciscan subduction zone

(Ingersoll, 1978; Godfrey & Klemperer, 1998). Great Valley Sequence lithologies in the

East Bay form a structure of alternating synclines and anticlines with generally northwest to southeast trending fold axes (Graymer, 2000).

Berkeley Hills Volcanics

Oakland

Livermore Hayward

Area of Figure 4 Fremont

Legend Active Trace Hayward Fault

Hayward Fault Zone

Water North Quaternary

Alluvium and mud 20 km Cenozoic/Mesozoic

Great Valley Sequence Tertiary volcanic rocks Mesozoic Franciscan Complex

Coast Range Ophiolite

Figure 3: Geologic overview of the central East Bay

The core of the HFZ is a distinct lithotectonic terrane dominated by the Coast

Range Ophiolite (CRO), which is a segment of Jurassic-aged ocean crust that principally consists of peridotite, gabbro, diabase, and basalt (Graymer, 2000); the CRO is structurally separate from the Franciscan Complex and the Great Valley Sequence. In addition to mapped CRO lithologies are scattered outcrops of quartz keratophyre

(partially metamorphosed rhyolite), and basal sediments of the Great Valley Sequence that are mostly between the east and west strands of the CF (Graymer et al., 1995A;

Graymer, 2000). A comprehensive tectonic model by Shervais et al. (2004) incorporates the guiding principles of competing tectonic models by Godfrey and Klemperer (1998) to propose a multiple-stage tectonic evolution of the Franciscan subduction zone as a likely mechanism for deforming the CRO into observed outcrop patterns. The San Leandro

Block, in the central East Bay, is likely composed of CRO bedrock and overlain by minor slices of basal Great Valley Sequence sediments.

San Leandro Block

We define the San Leandro Block (SLB), sensu stricto, as the distinct ~1- to 3- km-wide (east-west) terrane that is bound between the western HF and the eastern CF, and that extends for ~25-30 km (north-south) between Berkeley and Fremont (Figure 4).

The principal bedrock lithologies of the SLB are basalt, gabbro, quartz keratophyre, sandstone, and serpentinite (Graymer, 2000). Interpretations of seismic, magnetic, and gravity surveys, in concert with geologic mapping, suggest that the SLB is mostly comprised of gabbro, has significant internal faulting, may extend to depths ≥ 6 km, and may dip 75-80° toward the northeast (Ponce et al., 2003). Most faults within the SLB are

either subparallel or diagonal to the HF, with strikes that range from ~290°-310°. Fault- bound blocks of the Great Valley Sequence within the SLB occur mostly between the west and east strands of the CF (Graymer et al., 1995A; Graymer, 2000). The west- vergent AF places SLB lithologies directly over Quaternary-aged sediments that otherwise unconformably overlie the HF (Graymer, 2000; Rubin, 2011). The western margin of the SLB correlates with the dominant HF seismicity pattern (Ponce et al.,

2003), the 1868 HF earthquake ruptures (Hough and Martin, 2015), and the locked section of the HF (Lienkaemper et al., 2012). These relationships indicate seismogenic stress accumulates along the western margin of the SLB, thereby suggesting that it is a potential source of future large-magnitude HF earthquakes.

Berkeley

Oakland

San Leandro

Hayward

Fremont

Legend Active Trace Hayward Fault Core Hayward Fault Zone

Water Quaternary North Alluvium and mud Cenozoic/Mesozoic 10 km Great Valley Sequence Tertiary volcanic rocks Mesozoic Franciscan Complex Coast Range Ophiolite Figure 4: Geologic overview of the San Leandro Block

Background and Purpose

The highly urbanized setting of the East Bay impedes the study of small-scale and near-surface structures in the SLB. However, researchers from the United States

Geological Survey (USGS) Earthquake Science Center at Menlo Park, California have applied seismic methods to image near-surface structures in similar geologic settings to the SLB (Catchings et al., 2002, 2006, 2014, 2017). As part of their focused research, the

USGS has collaborated with researchers from the California State University at East Bay

(CSUEB) in order to develop a three-dimensional seismic velocity model of the East Bay

(Catchings et al., 2015; Abimbola, 2016; McEvilly, 2018).

In 2013, the USGS and CSUEB collaborated on the East Bay Seismic Experiment

(EBSE), which used the implosion of Warren Hall, at the CSUEB Hayward campus, as the principal seismic energy source (Catchings et al., 2015). They deployed multiple seismograph arrays throughout the central East Bay, including 300 seismographs emplaced in a radial array within a ~2.5-km-radius of Warren Hall. In addition to the large radial seismograph array, they also deployed two small arrays of twelve and ten 3- component seismographs, respectively, across the HF on undeveloped study areas. The primary goal of EBSE was to determine the nature and extent of ground shaking across the HFZ during the collapse of Warren Hall.

USGS and CSUEB researchers continued to collaborate on small-scale high- resolution seismic refraction surveys lead by CSUEB graduate students. (1) The results of three seismic refraction profiles, conducted in 2016 at the proposed site of the CSUEB

Pioneer Heights student-housing complex, were compared with results from three

coincident paleoseismic trenches (Abimbola, 2016); those spatial comparisons showed that seismic refraction methods are appropriate for identifying distinct faults within the upper ~50 m of the near surface. (2) The results of a seismic refraction survey, conducted in 2015 across a CSUEB parking lot, demonstrated that seismic refraction methods are appropriate for seismically imaging faults in study areas that do not have cross-fault trenching data (McEvilly, 2018).

This study continues the efforts of USGS and CSUEB research and presents high- resolution seismic refraction tomography images across the active trace of the HF. The goal is to identify the location and geometry of the HF in the near surface, and the splays adjacent to it, by evaluating cross-fault seismic velocities and velocity ratios.

Study Area

For this study, we evaluate seismic data acquired during (1) a 2013 seismic survey and (2) a 2017 seismic survey. The 2017 seismic profile is sub-parallel to the 2013 seismic profile. The study area is an undeveloped parcel of land that is located within 500 m of the Carlos Bee Boulevard and Mission Boulevard intersection (Figure 5) in the City of Hayward, and the site is ~1 km northwest from the CSUEB Hayward campus. The

City of Hayward owns this property, and it is a right-of-way between Carlos Bee

Boulevard, utility power lines, businesses, and residences (Alameda County, 2018).

50 km

Oakland North

San Francisco Hayward Livermore

Fremont

50 0 m

North

Figure 5: Location of the Carlos Bee Study Area – APN 445-200-12-1 – in the City of Hayward and within 500 m of the Carlos Bee Blvd-Mission Blvd intersection

Three mapped interpretations of the position of the HF, including positions from two geologic maps, indicate the probable surface structure of the HFZ in the study area.

Each of the three interpretations, when projected together on the same Google Earth datum, indicates a slightly different position for the HF within the study area (Figure 6).

(1) Lienkaemper (1992) places the HF along a west-facing slope. (2) Graymer (2000) places the HF ~20 m west of and parallel to the position interpreted by Lienkaemper

(1992). (3) Jennings et al., (2010) places the HF ~30 m west of and parallel to the position interpreted by Lienkaemper (1992). The geologic maps each show slightly different interpretations of the bedrock structure at the study area (Figures 7 and 8).

Graymer (2000) identifies two splay faults separating slivers of basalt, gabbro, and clastic sediments to the northeast of the HF; whereas Jennings et al. (2010) identify a single splay fault separating basalt and gabbro in the same area.

Legend

Carlos Bee study area 100 m

Active Trace Hayward Fault (Lienkaemper, 1992) North

Active Trace Hayward Fault and splays (Graymer, 2000)

Active Trace Hayward Fault and splay (Jennings et al., 2010)

Figure 6: Possible locations for mapped faults across the study area

Legend

Hayward Fault and splays Carlos Bee study area Quaternary alluvium and mud North Cretaceous-Jurassic clastic sediments Jurassic pillow basalt 100 m Jurassic gabbro

Figure 7: Geology of the study area, based on the geologic map by Graymer (2000)

Legend Hayward Fault and splays Carlos Bee Study Area Quaternary alluvium and mud North Jurassic gabbro or basalt Jurassic gabbro or serpentinite 100 m

Figure 8: Geology of the study area, based on the geologic map by Jennings et al. (2010)

Seismic Methods

Seismic Waves

Seismic studies involve the measurement and interpretation of seismic waves, which represent four categories of elastic deformation (Burger et al., 2006; Reynolds,

2011). (1) Primary waves (P-waves) and (2) Secondary waves (S-waves) propagate through the full thickness of a material, where P-waves describe compressional

deformation and S-waves describe shear deformation. P-wave velocity (VP) is a function of material incompressibility (K), rigidity (μ), and density (ρ) (Equation 1); S-wave velocity (VS) is a function of μ and ρ (Equation 2). (3) Rayleigh waves (R-waves) and (4)

Love waves (L-waves) propagate along the ground surface, where R-waves describe retrograde elliptical deformation and L-waves describe lateral deformation. Surface waves propagate with a dispersion of wavelengths that result in many simultaneous velocities for both R-waves (VR) and L-waves (VL); however, VR and VL are inferable as functions of VP and VS, respectively (Haskell, 1953; Park et al., 1999). Seismic waves travel at differing velocities through various geologic materials, whereby velocities usually increase with material density and confining pressure (i.e. decreased volume)

(Woeber et al., 1963; Christensen & Mooney, 1995; Kennett et al., 1995).

Seismic wave velocity equations:

4μ 1/2 1) P-wave: VP = [(K + /3) / ρ]

1/2 2) S-wave: VS = [μ / ρ]

Snell’s Law mathematically explains how the velocity and travel path of a seismic wave changes as it propagates through lithologies of varying densities (Figure 9). A seismic wave incident upon a lithologic boundary will split into a reflected phase that travels back toward the ground surface, and a refracted phase that transmits across the lithologic boundary. Snell’s law relates the velocity of a seismic wave to the angle of its travel path and allows us to describe how seismic waves propagate through materials with differing physical properties.

Snell’s Law:

Sin(i) = Sin(t) Vi Vt

∴

Sin(i) = Vi Sin(t) Vt

Figure 9: Principles of Snell’s Law (modified from Burger et al., 2006; Reynolds, 2011)

(1) An incident P-wave (iP) splits into a reflected P-wave (rP) and a refracted

(transmitted) P-wave (tP), and the seismic energy imparted upon the lithologic

boundary generates a reflected S-wave (rS) and transmitted S-wave (tS), where the seismic waves travel with higher velocities through the lower lithology that has a

higher density (V2 > V1; ρ2 > ρ1). (2) Snell’s law describes the trigonometric relationships between any incidence angle

(i), any transmission angle (t), and the respective seismic wave velocities (Vi , Vt).

Seismic Surveying Techniques During an active-source seismic survey, an energy source generates seismic waves that propagate through the subsurface, and an array of geophones detects the seismic waves at the surface (Figure 10). Examples of common energy sources used for seismic surveying include sledgehammer strikes, accelerated weight drops, hydraulic vibrators, explosive charges, and sonic generators. Geophones detect seismic waves by converting the mechanical oscillations of an internal coil into an electrical signal that

relays to a seismograph (Figure 11). Vertical-component geophones optimally detect P- waves and R-waves, whereas horizontal-component geophones optimally detect S-waves and L-waves. (Burger et al., 2006; Reynolds, 2011)

Figure 10: Principles of a simple P-wave survey (Burger et al., 2006; Reynolds, 2011) (1) A sledgehammer strike generates the seismic waves, and then vertical-component geophones detect the P-wave and R-wave arrivals. (2) The geophones detect the portion of the P-wave that travels only through the uppermost lithology as a direct wave. (3) Seismic energy traveling along the lithologic boundary generates critically refracted

head waves (hP). The critically refracted head waves, having transmitted through a denser lithology, will eventually arrive at the surface before the direct wave arrivals. (4) The geophones detect the R-waves as dispersed arrivals, and the sound of the sledgehammer strike as an airwave arrival.

Figure 11: Simplified diagram of the components in a common geophone (Modified from Burger et al., 2006)

Seismic shot gathers display the seismic wave arrivals recorded from a geophone array, as a time-distance plot, where vertical signal traces correspond to each geophone station (Figure 12). On time-distance plots, refracted waves (including head waves) have linear slopes originating from the source (shot) position and after the origin (trigger) time.

Reflected arrivals have concave-down hyperbolic slopes originating after the trigger time, and always after first arrivals. Direct arrivals, surface-wave arrivals, and airwave arrivals all have linear slopes originating from the shot position at the trigger time. Shot gathers display direct waves and critically refracted head waves as the first arrivals. We process our data by measuring the first arrivals on each shot gather (Hole, 1992).

Figure 12: An example shot gather with vertical signal traces, corresponding to the positions of geophones in an array (in meters), and showing the arrival of seismic waves through time (in milliseconds); shaded peaks indicating negative amplitude

Figure 13: A diagram of common arrival patterns discernible on a typical shot gather; the cross-over point is the slope inflection in the first arrival pattern, beyond which the refracted wave arrives before the direct wave (Modified from Burger et al., 2006; Reynolds, 2011)

Seismic Data Processing

The two principal analyses that we use for processing seismic data are seismic reflection imaging and seismic refraction tomography. Reflection analyses are ideal for relatively simple geologic settings, with horizontally oriented lithologies (Ashcroft,

2011). For vertically oriented lithologies or structures, which we expected at the study area, refraction analyses are more appropriate (Hole et al., 2001; Catchings et al., 2014).

Refraction methods use measured first arrivals on shot gathers to model seismic wave velocities (White, 1989; Hole, 1992). Two-dimensional refraction surveys (see Figure 10) yield depth-distance models of seismic velocity. We can use seismic refraction data to produce tomography models of VP and/or VS, depending on the sources and geophones used to record the seismic wave arrivals.

Seismic refraction tomography is a modelling method that uses multiple measures of travel times for a given distance and depth range. We can develop two- and three- dimensional refraction tomography models with the appropriate data. For my study, I use the two-dimensional refraction tomography algorithm developed by Hole (1992), which applies an inversion to my measured first arrival travel times from multiple shot gathers in order to model subsurface seismic velocities.

We can compare VP and VS by calculating the VP/VS ratio and Poisson’s ratio.

The comparisons of seismic velocities and their ratios are useful in assessing mineral composition, density, groundwater saturation, and fault zone shearing (Christensen, 1996;

Gercek, 2007; Catchings et al., 2014; Yu et al., 2016). Among other properties, mineral composition influences the elastic wave propagation within rocks. Generally, VP and VS

increase with density in the subsurface. VP increases when groundwater saturation is > 90

%, but VS decreases slightly in the same range of saturation. Shearing, produced by the faulting process, can cause both VP and VS to decrease across fault zones, but there is usually more of a decrease in VS than VP. In particular, the combination of groundwater saturation and fault-zone shearing can cause apparent VP and VS to be misrepresentative of subsurface materials relative to their unsaturated and unfaulted states. Catchings et al.

(2014) have shown that VP/VS ratios within shallow-depth saturated fault zones are particularly high, usually > 5.0. Poisson’s ratio (Equation 3) quantifies the extent that materials deform perpendicular to the direction of seismic wave propagation, and is a unitless value that ranges from 0.2 to 0.5 for most geologic materials. Poisson’s ratios are usually higher in mafic rocks and saturated fault zones (Christensen, 1996; Catchings et al., 2014). Poisson’s ratios support interpretations of VP/VS ratios by indicating where mineral composition, groundwater saturation, and/or fault zone shearing strongly affects the seismic expression of a study area.

Vp 2 Vp 2 3) Poisson’s ratio: ν = [( /Vs) – 2] / [2( /Vs) – 2]

For studies where only P-wave data are available, we can use R-waves to estimate

VS by using the Multi-channel Analysis of Surface Waves (MASW) method of Park et al.

(1999). Hayashi and Suzuki (2004) developed a version of the MASW method that uses

Common Mid-Point Cross Correlation to stack multiple shot gathers and develop a series of dispersion curves along a seismic profile. The MASW method uses the fundamental mode of R-wave dispersion to infer one-dimensional VS models (Park et al., 1999; Xia et al., 2000). We use the two-dimensional MASW method to infer two-dimensional Vs

models that often feature where sediments overlay bedrock, and sometimes near-vertical fracture zones (Park et al., 1999; Miller et al., 1999).

Data Acquisition

Seismic Survey

For this study, CSUEB and USGS researchers collected data from two seismic refraction surveys (Figure 14). (1) We collected a high-resolution P-wave data set during a seismic refraction survey at the Carlos Bee study area in November of 2017 (CB17).

The CB17 survey consisted of 63 vertical-component geophones that detected 63 shots

(seismic sources), and three Geometrics™ Geode 24-channel digital seismographs that recorded the data. (2) For this study, I compared models derived from the CB17 survey with an adjacent, low-resolution P- and S-wave seismic refraction survey conducted by the USGS across the active trace of the HF in 2013 (CB13). The CB13 survey consisted of ten 3-component seismographs (vertical, horizontal-transverse, and horizontal- longitudinal) that recorded data from four shots. The CSUEB Department of Earth and

Environmental Sciences and the USGS supplied equipment for both the CB13 and the

CB17 surveys (Appendix 2).

Legend Carlos Bee study area

CB13 seismic profile 100 m North CB17 seismic profile

Figure1. 14 : Comparison of two survey paths across the Carlos Bee study area

For the CB17 survey, an initial preparation day took place in four principal steps.

(1) We surveyed the geometry of the seismic profile using a 100 m surveying tape and

Brunton pocket transits. (2) We used hand augers to place shot points at 5 m intervals to

~30-cm-depth continuously along the seismic profile, and (3) used hand augers to place

~2-m-deep explosive charges at three locations along the seismic profile (Figure 15). (4)

We used a Real-Time Kinematic GPS to record the coordinates and elevation of each shot position (Figure 16, Appendix 3).

Seismic data acquisition took place in five principal steps. (1) We deployed sixty- three 4.5-Hz vertical-component geophones (spaced at 5 m intervals) ~0.5 m north of each shot location. (2) The geophones connected to multi-channel seismographs

(Geometrics™ Geode) by three 24-channel refraction cables (Figure 17); due to the limited space of the survey line, we used only 63 of the available 72 take-out connections on the refraction cables, resulting in a 310-m-long seismic profile. (3) We connected the refraction cables to a Panasonic Toughbook laptop computer to manage survey parameters and view seismic wave arrivals (Figures 19 and 20). (4) We generated shots using Betsy Seisguns™ every 5 m (horizontally offset 1 m from each geophone) along the 310-m-long seismic profile (Figure 21); and (5) generated an explosive charge at meters 10, 220, and 300 along the seismic profile (Figure 22) in order to generate seismic signals with high signal-to-noise ratios. The three Geode seismographs recorded our seismic data.

In 2018, we returned to the study area and deployed another seismic profile with a geometry equivalent to that deployed for CB17. Instead of vertically emplaced explosive sources, we deployed a two-sided steel shear block and used an eight-pound sledgehammer to generate S-waves. Our goal was to collect an S-wave data set with the same resolution as the CB17 P-wave data set. Upon review of our data, we determined that the data was incorrectly stacked, and thus the recorded S-wave arrivals were not appropriate for our seismic refraction analyses. Rather than presenting an overview of the

2018 data, I instead applied the MASW method to the CB17 P-wave data set.

Figure 15: Example of a 2-m hand auger being used to excavate the borehole for an explosive charge; volunteer graduate students Joseph “Alec” McConnell (center), Adrian McEvilly (left), and Niket Kundariya (right) took turns operating this hand auger; a common experience for most of the 63 boreholes was difficulty in excavation due to wet clay in the topsoil; we used fine-grained sand to fill in the packing space above the charge in the borehole prior to detonation

Figure 16: Set-up of the Global Positioning System base station; volunteer graduate students Niket Kundariya (left), Alec McConnell (center), and Ian Richardson (right), prepare to record the coordinates of the seismic profile geometry; the base station is the reference used to record the position of each geophone station in a consistent offset and with minimized error

Refraction cable Power cable

Geophone take-out

Deployed geophone

Figure 17: Example of a geophone station within the seismic profile

Figure 18: Example of a Geometrics™ Geode 24-channel digital seismograph (yellow box), refraction cable (yellow cable in black spool), and power cable (black cable in orange spool) at the eastern end of the seismic profile

Figure 19: Field headquarters, with laptop computer (center) set up for data collection

Figure 20: Example view of the Geometrics™ multiple geode operating software on the Panasonic Toughbook, where the left viewing window displays real-time seismic data, and the right viewing window displays an instantaneous data record for a source trigger

Figure 21: Deployment of two (of the three we used) Betsy Seisguns™

Figure 22: Dr. Rufus Catchings (top left), Dr. Luther Strayer (bottom left), Mr. Coyn Criley (bottom right), and Ms. Carolyn Stieben (top right) prepare an explosive charge

Data Overview

The explosive charges generated higher amplitude seismic waves than those generated by the Betsy Seisgun™, such that the explosive charges produced strong seismic wave arrivals across the full 310-m-long seismic profile (Figure 23), whereas the

Betsy Seisgun™ sources produced less energetic seismic arrivals (Figure 24). The Geode seismographs recorded no data at geophone station 40 (155 m), due to a malfunctioning take-out; thus, I did not include the corresponding geophone trace in my analyses.

0 ↓ 100 ↓ Distance [m] 200 ↓ 300 ↓ 1550 >

1700 >

Time [ms] Time

2000 >

2200 >

Figure 23: Example of a shot gather recorded from an explosive charge shot

Distance [m] 0 ↓ 100 ↓ 200 ↓ 300 ↓

100 >

Time [ms]Time

500 >

Figure 24: Example of a shot gather recorded from a Betsy Seisgun™ shot.

Data Analysis

Seismic Refraction Analysis

I used Promax™ seismic processing software to process the data from the CB13 and CB17 surveys. (1) An inspection of signal quality and propagation indicated traces without identifiable first arrivals, for which I replaced weak traces with a zero-value trace. (2) Combining the data from each geode produced a shot gather ratio for each shot.

(3) I inserted the seismic profile geometry by including the latitude, longitude, and elevation for each shot and geophone. (4) Before measuring first arrivals, I applied a 30-

60-90-120 Hz band-pass filter to the data. (5) I measured the first arrivals (Figure 25) from each of the 10 shot gathers from the CB13 survey and the 63 shot gathers from the

CB17 survey. For the CB17 data, the first arrivals for the more-energetic explosive charge shots guided my progress through the less-energetic Betsy Seisgun™ shots.

Figure 25: Example first arrival pattern, where the dashed red lines show the first arrivals that coincide with the Betsy Seisgun™ shot at 220 m

The USGS used a time- and position-checking script to evaluate the seismic reciprocity of the first arrival measurements for shot and geophone pairs. In theory, the calculated travel path from a source at Position A to a geophone at position B should be the same as when the source is at position B and the geophone is at position A. The reciprocity evaluation is an important form of quality control that strongly assures accuracy in first-break measurements.

We used the code of Hole (1992) to develop two-dimensional velocity models based on the measured first arrivals. We used the Generic Mapping Tools software to view the models as contoured distance-depth plots and with optimal color schemes

(Figures 26, 27, 28, and 29).

Figure 26: Example ray convergence model for the CB17 survey, extending from the southwest (SW) end to the northeast (NE) end of the seismic profile, which displays the number of calculated travel paths coinciding within each 5-m-by-5-m grid unit

Figure 27: VP model for the CB17 survey (P17)

Figure 28: VP model for the CB13 survey (P13)

Figure 29: Transverse-component (top) and longitudinal-component (bottom) VS models for the CB13 survey (TS13 and LS13)

Multi-channel Analysis of Surface Waves (MASW)

I used the SeisImager™ software package to process the CB17 R-wave arrivals for MASW and infer VS along the CB17 seismic profile. SeisImager™ includes a module for basic data analyses (Pickwin™), seismic refraction processing (Plotrefa™), surface wave analysis (WaveEq™) , and graphic display (GeoPlot™). A combination of MASW functions in Pickwin™, WaveEq™, and GeoPlot™ constitute the Surface Wave Analysis

Wizard™ (SeisImager, 2009). I used Pickwin™ to: (1) import the CB17 data files as a group file list and specify the survey geometry of the seismic array, (2) apply the

CMPCC method to the geophone traces and convert the stacked CMPCC data records from time domain plots into phase velocity plots, and (3) manually select the fundamental mode of dispersion for each phase velocity plot (Figure 30). The frequencies of fundamental modes of dispersion generally did not exceed ~25 Hz. I next used

WaveEq™ to: (1) upload the 63 dispersion curves, and (2) perform a 20-iteration VS inversion with a 10-layer and 30-m-deep starting model. Finally, I used GeoPlot™ to: (1) upload the final two-dimensional VS model, and (2) incorporate the topographic profile

(Figure 31). With guidance from colleagues at the USGS, we imported the MASW result in the Generic Mapping Tools software in order to view the final MASW model in a graphical style consistent with the other models.

A Phase velocity [m/s] 500 ↓ 1000 ↓ 1500 ↓ 2000 ↓

0,0 .

↓

Frequency[Hz]

↓ B Frequency [Hz]

10 ↓ 20 ↓ 30 ↓ 40 ↓ 50 ↓

2000

↓

]

1500

↓

1000

↓

500

↓ Phase velocity [m/s Phasevelocity

Figure 30: A) example phase-velocity plot at 0 m; B) selected dispersion curve

Figure 31: MASW model for the CB17 survey (M17)

VP/VS and Poisson’s Ratios

We calculated VP/VS and Poisson’s ratios from the CB17 velocity models (Figure

32). For comparison, we also calculated the VP/VS and Poisson’s ratios from the CB13 velocity models (Figures 33 and 34).

Figure 32: VP/VS ratio (top) and Poisson’s ratio (bottom) models for the CB17 survey

(PS17 and PR17)

Figure 33: Transverse-component (top) and longitudinal-component (bottom) VP/VS models for the CB13 survey (TPS and LPS)

Figure 34: Transverse-component (top) and longitudinal-component (bottom) Poisson’s ratio models for CB13 (TPR and LPR)

Results

VP Tomography

I suggest three important observations for the VP models of the CB17 and CB13 seismic profiles, referred to here as P17 and P13 respectively (Figures 35 and 36). (1) For

P17 and P13 there are significant differences in overall VP structure. For the P17 model,

VP contours < 1500 m/s are nearly parallel to the terrain profile, whereas VP contours >

1500 m/s differ from the topography and all higher VP have a similar structure. For P13, the VP contours are more evenly spaced and the central area exhibits VP contours with steeper slopes than for the same area of P17. (2) P17 and P13 each exhibit a distinct high velocity zone (HVZ), where the notable VP structure is a concentration of contours >

3000 m/s. For P17, the HVZ peaks near 160 m distance and 0 m elevation, whereas for

P13, the HVZ peaks in the eastern 150 m. (3) P17 and P13 each exhibit distinct low velocity zones (LVZ), where the notable VP structure is a decrease in contour spacing for contours < 2500 m/s. For P17, the principal LVZ extends through the eastern 200 m, whereas for P13, the principal LVZ extends through the western 100 m.

Figure 35: Noted VP structures for P17; a dashed oval indicates the HVZ; the double-

dotted ovals indicate the principal widely-spaced VP contour zones; the highlighted

path is the 1500 m/s Vp contour

Figure 36: noted VP structures for P13; the dashed oval indicates the principle HVZ and the dotted oval indicates the principle LVZ

VS and MASW Models

I suggest three important observations for the transverse- and longitudinal- component VS structures of the 2013 models, referred to here as TS13 and LS13 respectively, and for the VS structures of the 2017 MASW model, referred to here as M17

(Figures 37 and 38). (1) TS13 and LS13 each have similar VS structures, with a dominant

LVZ in the western area and a dominant HVZ in the eastern area. Each LVZ exhibits a trough-like structure, defined by steep contours with VS magnitudes ≤ 2000 m/s; each

HVZ includes high gradients of contours with VS ≥ 2000 m/s. (2) VS magnitudes in M17 are comparable to those of TS13 and LS13, and with VS contours similar in structure to those of P17. (3) M17 exhibits consistently increasing VS across the entire distance of the seismic profile below ~20-m-depth, and subtle VS structures in the upper ~20 m. The subtly of M17 may be caused by the modeling of VS from R-waves of the CB17 data set, such that M17 infers a VS structure similar to the upper ~20 m of P17; furthermore, the reliability of M17 is low, due to the effects that the steep topography along the seismic profile has on the precision of MASW modeling.

Figure 37: Comparison of VS structures between TS13 (top) and LS13 (bottom); the dashed oval indicates each HVZ; the dotted oval indicates each LVZ

Figure 38: noted velocity structures for M17; the dotted ovals indicate each LVZ; the dashed ovals indicate each HVZ

VP/VS Ratio and Poisson Ratio Models

I highlight two important observations among the CB17 VP/VS and Poisson’s ratio models (PS17 and PR17) (Figure 39), and the transverse- and longitudinal-components of the CB13 VP/VS ratio models (TPS13 and LPS13) (Figure 40) and Poisson’s ratio models

(TPR13 and LPR13) (Figure 41). (1) The magnitudes of PS17 and PR17 high value zones

(HVZ) are higher than corresponding HVZ of the CB13 models. PS17 peaks at ~3.4, whereas TPS13 and LPS13 peak at ~2.1; PR17 peaks at ~0.45, whereas TPR13 and

LPR13 peak at ~0.33. (2) The overall structure of the CB17 models is significantly different from the CB13 models. CB17 anomalies exhibit HVZ that are nearly coincident to the LVZs of M17, whereas CB13 anomalies most resemble TS13 and LS13.

Figure 39: Comparisons between PS17 (top) and PR17 (bottom), where the dashed ovals indicate the distinct HVZs

Figure 40: noted comparisons between TPS13 (top) and LPS13 (bottom); the dashed ovals indicate each HVZ; the dotted ovals indicate each LVZ

Figure 41: noted comparisons between TPR13 (top) and LPR13 (bottom); the dashed ovals indicate each HVZ; the dotted ovals indicate each LVZ

Interpretation

I interpret comparisons of P17 with P13 to infer the dip of faults (Figure 42). (1)

A Google Earth satellite map, overlain by the mapped surface positions of faults

(Lienkaemper, 1992; Graymer, 2000; Jennings et al., 2010) and the orientation of the seismic profile, indicates where the seismic profile crossed those faults (see Figure 6).

Based on the west-facing slope that is the geomorphic expression of the HF, the surface position of the HF projected from Lienkaemper (1992) fits poorly to our evidenced near- surface position of the HF. The two nearly coincident surface positions of the HF, projected from Graymer (2000) and Jennings et al. (2010), fit better to our evidenced near-surface position of the HF. (2) Both P17 and P13 exhibit LVZs and/or widely spaced contours that suggest the seismic expression of the HF. Such structures are consistent with expectations of the HF, as P-wave LVZs (in excess of 2500 m/s) typically infer fault zones (Catchings et al., 2002, 2006, 2014, 2017). Based on the positions of contour minima, and in accordance with geophysical interpretations (Waldhauser &

Ellsworth, 2002; Ponce et al, 2003), the HF dips through a core zone at dip angles ranging from 50-80° toward the northeast. By connecting the location of the lowest VP value, ~10-m-west of the HF position from Graymer (2000), to the location of the widest contour spacing, ~40-m-below that same HF position, I interpret that the HF may dip

~55° toward the northeast.

The LVZs and widely spaced contours of P17 and P13 also suggest the dip of the mapped splay faults by Graymer (2000) and Jennings et al. (2010) (Figure 42). The mapped surface positions of faults east of the HF do not correspond to distinct contour

patterns at depth. Furthermore, the HVZ of P13 is more eastern than the HVZ of P17; thus, the dip of the splay faults is indeterminate for the VP models. Two different possible interpretations for the position of mapped faults are as follows: (1) the HF and at least one splay bound the core of the HVZ, whereas (2) splay faults flank the HVZ and the HF cuts through the HVZ west of the peak VP magnitude.

Further interpretations require examination of the lithology of the fault-bound

HFZ in P17 by relating its VP structure to the theoretical VP of ultramafic rocks mapped at the surface (Figure 42). The ultramafic rocks at the study area (gabbro and basalt) have theoretical VP values ranging between ~4000 m/s and ~6000 m/s (Woeber et al., 1963;

Kahraman, 2007). The HVZ of P17 has a peak VP of ~4200 m/s, which may confirm gabbro and/or basalt in that area. The closely spaced VP contours of P17 between the

HVZ and the 1500 m/s contour may represent fractured gabbro/basalt. Due to a lack of outcrops along the seismic profile, it is not clear how deep the topsoil extends; however,

CB17 borehole excavations show that the top soil is at least ~2 m deep in three places.

HF (Jennings et al., 2010) Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992) Gabbro/Serpentinite

Alluvium

HF (Jennings et al., 2010) HF (Graymer, 2000) Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Lienkaemper, 1992)

Alluvium

Gabbro/Basalt

Figure 42: Interpretations for P17 (top) and P13 (bottom); arrows indicate the location of mapped geologic structures; labels of known lithologies are below their mapped locations; the dashed line is my suggested dip of the HF for P17; dotted polygons indicate the possible location of other faults for P17; I project my interpretations from P17 onto P13 for comparison

I compare my VP interpretations of P17 and P13 to VS interpretations of M17,

TS13, and LS13 (Figures 43 and 44). (1) The M17 VS contours are generally parallel to the terrain profile, which is most similar to P17. However, the VS models should not be similar to the VP models, as VP and VS expressions of the near surface are known to be different (Abimbola, 2016; Catchings et al., 2017; Chan, 2018; McEvilly, 2018). (2) The

TS13 and LS13 models show a pronounced LVZ in the western area that is nearly coincident to the LVZ in P13. The LVZs may suggest the HF, as a high-angle S-wave

LVZ commonly represents other Bay Area fault zones (Catchings et al., 2014, 2017). The contour patterns of M17 are poorly resolved below ~20-m-depth, and as a result, I cannot accurately interpret zones for possible fault dips (Figure 43). (3) The patterns of LVZs and widely spaced contours indicate alternative dips for the two mapped splay faults. The contour patterns of TS13 indicate that the two mapped splays constrain the eastern HVZ

(e.g. gabbro), and then the HF and the western mapped splay constrain another HVZ (e.g. basalt) – as I suggest for P17. However, the contour patterns of LS13 suggest that the HF and the western splay may dip toward each other west of the principal HVZ. (4) The contour minima through the LS13 LVZ are below the mapped positions of the HF, but in

TS13 the minima are ~100 m further to the west. Thus, the HF dip interpretation may be more realistic in LS13 than in TS13, or TS13 may represent another nearly vertical fault to the west of the HF. The TS13 LVZ is nearly coincident to the widely spaced contours of the P13 LVZ and to one subtle M17 LVZ. These nearly coincident LVZs support the existence of an unmapped fault ~50 m to the west of the HF.

Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992)

Alluvium

Figure 43: Interpretations for M17; arrows indicate the surface expression of mapped geologic structures; dotted polygons indicate zones through which those structures may dip; the dashed line is the dip of the HF from Figure 42, projected here for comparison; labels of known lithologies are below their mapped locations

Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992)

Alluvium

Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992)

Alluvium

Figure 44: Interpretations for TS13 (top) and LS13 (bottom); arrows indicate the surface expression of mapped geologic structures; dotted polygons indicate zones through which those structures may dip; labels of known lithologies are below their mapped locations; the dashed line is the dip of the HF from Figure 42, projected here for comparison

VP/VS ratio and Poisson’s ratio models broaden the interpretations made for the preceding models (Figures 45, 46, and 47). (1) The ~55° easterly dip for the HF from P17 fits poorly with the VP/VS ratio and Poisson’s ratio models. The CB17 models (PS17 and

PR17) indicate a dip of ~70° toward the southwest, whereas the CB13 transverse models

(TPS13 and TPR13) and longitudinal models (LPS13 and LPR13) indicate a dip of ~75° toward the northeast. (2) The possible dips for the eastern mapped splay fit well with all

VP/VS ratio and Poisson’s ratio models, which indicate a dip of ~70° toward the southwest. Furthermore, all VP/VS ratio and Poisson’s ratio models indicate the actual surface position of the eastern splay is likely ~15-20 m east of its mapped position. (3)

PS17 and PR17 exhibit strong anomalies at the location of other nearly coincident anomalies, which corroborate the presence at least one western splay fault. A dip of ~65-

70° toward the northeast for the western splay compares reasonably well to the anomalies in LPS13 and LPR13, but compares poorly to the anomalies in TPS13 and TPR13. (4)

VP/VS ratios and Poisson’s ratios generally fall within the expected ranges for basalt, gabbro, and serpentinite (Christensen, 1996; Gercek, 2007); however, the HVZ of PS17 and PR17 generally exceed the expected values of the bedrock lithologies in their theoretically unsaturated states. However, previous USGS and CSUEB research has consistently shown that water-saturated sediments have VP/VS ratios of ≥ 3 and Poisson’s ratios > 0.4 (Catchings et al., 2014, 2017; Abimbola, 2016; McEvilly, 2018). Based on the seismic velocities that correlate to the interpreted anomalies, the HVZs of PS17 and

PR17 likely indicate where saturated sediments may overlay bedrock.

HF (Jennings et al., 2010) Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992)

Alluvium

Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992)

Alluvium

Figure 45: Interpretations for PS17 (top) and PR17 (bottom); arrows indicate the surface expression of mapped geologic structures; the dashed lines are my suggested dips for faults; labels of known lithologies are below their mapped locations

HF (Jennings et al., 2010) Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992) Gabbro/ Serpentinite Alluvium

Figure 46: Interpretations for TPS13 (top) and LPS13 (bottom); arrows indicate the surface expression of mapped geologic structures; the dashed lines are my suggested dips for faults; labels of known lithologies are below their mapped locations

HF (Jennings et al., 2010) Contact/splay fault (Graymer, 2000; Jennings et al., 2010) HF (Graymer, 2000) HF (Lienkaemper, 1992) Gabbro/ Serpentinite Alluvium

Figure 47: Interpretations for TPR13 (top) and LPR13 (bottom); arrows indicate the surface expression of mapped geologic structures; the dashed lines are my suggested dips for faults; labels of known lithologies are below their mapped locations

Discussion

Based on the VP and VS models, I present alternative interpretations for structures in the active HFZ. (1) At least three different faults separate the bedrock lithologies into distinct blocks, or (2) the active HFZ has a shallow splay structure that is ~200 m wide at the surface that includes at least two principal splay faults adjacent to the active trace of the HF. Observations of aseismic creep (Lienkaemper, 1992, 2012) indicate one trace of a

splayed HF would be the active (creeping) trace of the HF. My interpretation of the HF surface position, as fitted to the topography and the velocity models, may indicate that either (1) Lienkaemper’s (1992) suggested HF surface position is incorrect, or (2) the projection of that position on the Google Earth datum is inaccurate. In order to enhance my competing interpretations, I require an evaluation of the reliability of the CB13 and

CB17 velocity models.

Data resolution is a significant cause for noted differences between the CB13 and

CB17 velocity models. We derived CB13 velocity models using 4 shot points and 10 seismographs along a ~300-m-long seismic profile. In contrast, we derived the CB17 velocity models from 63 shots and 63 geophones on a 310-m-long seismic profile. This means that the CB17 data has significantly greater spatial resolution than the CB13 data, which results in a greater likelihood that CB17 models display near surface structures with higher precision. However, the P- and S-wave data from CB13 have allowed us to produce analyses that are slightly more diverse, which results in broader interpretations – although with lower accuracy. Furthermore, the less-resolved results of the CB13 survey represent a seismic profile that is not exactly coincident to the CB17 seismic profile.

Therefore, the higher resolution CB17 models are likely to be more realistic, whereas the lower-resolution CB13 models simply enhance the CB17 interpretations.

Another cause for the noted differences between CB13 and CB17 models may be changes in groundwater conditions between the CB13 and CB17 surveys. We acquired the CB13 dataset on August 17, 2013, during late summer, when the water table should have been deeper. The 2013 water table should have been exceptionally low due to an

extended drought in the Bay Area (Griffin & Anchukaitis, 2014; Seager et al., 2015;

DWR, 2019). We acquired the CB17 dataset on November 18, 2017, during middle autumn, when the water table should have been shallower. On November 16-17, 2017,

~5-7 cm of precipitation fell in the East Bay (CoCoRaHS, DWR, 2019), which may have caused the water table to rise at the study area. The nearest recently operating groundwater monitoring wells, within 3-8 km west of the study area, record a rise in groundwater elevation of ~0.5-2.5 m between early 2013 and late 2017 (Water Data

Library, 2019). Although there are no accessible groundwater data in the immediate vicinity of the study area, groundwater elevations likely increased significantly between

CB13 and CB17 – following the drought. Based on the known effects of groundwater on seismic refraction tomography (Mooney & Ginzburg, 1986; Catchings et al., 2006, 2014,

2017), we know that the 1500 m/s VP contour correlates with the water table. I cannot interpret the 2013 water table in P13, as there is no VP less than 1800 m/s; this observation also suggests that the resolution of CB13 data is too low to model the vadose zone accurately. However, the 1500 m/s VP contour may correlate with the water table in

CB17. Furthermore, the precipitation event immediately prior to CB17 data acquisition implies the terrain-parallel contours above the 1500 m/s VP contour may represent a generally uniform increase in saturation from the surface to the water table.

I interpret the 2017 groundwater table as having the geometry of the CB17 1500 m/s VP contour, which indicates that the groundwater table is nearly horizontal across the

HF. However, faults commonly act as barriers to groundwater flow (Caine and Forster,

1999), and thus we would expect the groundwater to collect on the uphill and

hydrologically up-gradient (eastern) side of the HF. Four interpretations may explain the unexpected geometry of the water table. (1) Groundwater infiltrating through the vadose zone, after the precipitation event that preceded the CB17 survey, did not have the time required to collect in the expected fashion. (2) A splayed structure of the HF, which correlates to stepping slopes across the study area, may cause the water table to drop in steps from east to west across the study area. (3) Subsurface conditions 1 and 2 may have interacted to result in the geometry of the water table on November 18, 2017. (4) My models may have lacked sufficient resolution to image the groundwater table accurately.

As the CB17 1500 m/s VP contour is likely the water table, the closely spaced VP contours between the water table and the HVZ should represent a lithology with relatively high porosity and permeability. Such a lithology could simply be a transition from top soil into unconsolidated sediments (e.g. alluvium) below the water table. This could be possible, as VP for saturated sediments in fault zones can be unexpectedly high, although usually < 2500 m/s (Catchings et al., 2014). Alternately, the area between the water table and the HVZ could be a shallower extension of the gabbro/basalt bedrock that we expect for the deeper HVZ. However, basalt and gabbro are rigid crystalline rocks, in which high porosity and permeability are necessary for groundwater saturation. Whereas basalt can have relatively high porosities compared to other crystalline rocks (Kahraman,

2007), gabbro generally has low porosity. A highly fractured bedrock structure, existing beyond the HF, would give the gabbro/basalt secondary porosity and that could better explain the observed transition from low to high VP below the water table; otherwise, there would be a more dramatic change in VP and VS representing such a contact between

unconsolidated sediments and rigid crystalline bedrock. Highly fractured outcrops of

SLB gabbro and serpentinite, within ~2 km of the study area, corroborate the probability of highly fractured bedrock at the study area.

Based on the boreholes we excavated during the CB17 survey, the study area has a top soil that is at least ~2 m deep in three locations along the seismic profile; however, the exact depth to the base of top soil is unknown. Previous research has shown that sediments in the San Francisco Bay area generally correlate to VP < 2000 m/s and VS <

750 m/s (Catchings et al., 2006, 2014; Abimbola, 2016), and often correlate to VP < 500 m/s and VS < 250 m/s. For the western and eastern 50-m-distance, the widely spaced VP contours < 2000 m/s likely indicate that soil and/or alluvium is deeper in those areas. In particular, the alluvium mapped in the western ~100 m is likely to be ≤ 20 m deep.

I further interpret the near surface by incorporating related geologic fieldwork. (1)

Trenching across the HFZ has revealed a variety of large- and small-scale splay faults that characterize a ≥ 30-m-wide splay structure (Lienkaemper et al., 2003; Berlogar,

2017). These findings, when compared with the upward splaying geometry of the HFZ

(Graymer et al., 1995A; Graymer, 2000; Jennings et al., 2010), suggest the faults that I interpreted from the velocity models probably connect at depth. However, my velocity models may not be accurate or extensive enough to specify a depth for connectivity between these splays. My interpretations give better support to the notion that the evidenced splays do not connect within ~30 m of the surface. (2) The interpreted surface position for the HF is coincident with the base of the west-facing slope (scarp) at the study area, which would be the geomorphic expression of the HF (Lienkaemper, 1992).

Likewise, the surface position of the eastern splay is coincident with a similar scarp. (3)

A geotechnical report encompassing the field area interprets a landslide across the eastern scarp (Earth Focus, 2018), which covers meters ~140 to ~190 along the CB17 seismic profile. The landslide is nearly coincident with a subtle HVZ in M17, and with the uppermost part of the eastern HVZ in the VP/VS ratio and Poisson’s ratio models.

Finally, a simple geologic cross-section for CB17 (Figure 48) summarizes my interpretations with a focus on CB17 models. (1) Since VP contours > 2000 m/s and VS contours < 700 m/s best express near surface structures, I summarize my interpretations of P17, M17, PS17, and PR17 by focusing on the anomalies that correspond to the indicated velocity zones. The active HFZ has at least three principle fault segments, including the active segment of the HF that has an averaged dip of ~75° toward the northeast. (2) A hummock in the terrain profile coincides with the position of the landslide determined by Earth Focus (2018). The estimated profile of this landslide, highlighted in green, has a concave-up geometry based on common landslide profiles

(Waltham, 2009). (3) The water table, highlighted in blue, has a stepped geometry, based on the 1500 m/s VP contour, where the water table steps down in elevation, from east to west, between each interpreted fault segment. (4) A contact, separating deeper and more compact bedrock from shallower and less compact bedrock or sediments, has an averaged geometry based on the P17 2000 m/s VP contour and the M17 700 m/s VS contour. I assume a near surface lithology in transition from top soil at the surface to increasingly compact bedrock. (5) Based on the P17 VP structure west of the HF, I interpret that basalt bedrock extends ~50 m west of the HF and underlies alluvium between the HF and the

western splay. Based on geologic mapping, I interpret that basalt is between the HF and the eastern splay, and gabbro is in the easternmost block of the study area.

Southwest Northeast

Hayward Fault Unnamed Fault

Unmapped Fault

Explanation Quaternary alluvium Terrain profile Landslide profile Transitional layer (soil → bedrock) Water table Jurassic basalt (bedrock) Transitional boundary

Jurassic gabbro (bedrock) Strongly evidenced fault Lesser splay fault

Figure 48: Cross-sectional model of the study area along the CB17 seismic profile, based on a summary of interpretations

Conclusion

By interpreting seismic refraction data from the CB13 and CB17 surveys, using seismic refraction tomography, MASW, VP/VS ratios, and Poisson’s ratios, I conclude that at least three faults separate the study area into distinct lithologic blocks. (1)

Quaternary alluvium characterizes the uppermost ~20 m of the block to the west of the

active trace of the HF. My estimated dip for the HF, ~75° toward the northeast, corroborates (for the near surface) those estimates by previous geophysical research

(Ponce et al., 2003; Williams et al., 2005). The mapped traces of the HF by Graymer

(2000) and Jennings et al. (2010) fit well with my interpreted position of the HF. The mapped trace of the HF by Lienkaemper (1992) is not coincident with the topographic or dominant velocity expression of the HF. The datum that I used in Google Earth is a probable cause for Lienkaemper’s (1992) inferred trace of the HF not fitting well with my models. (2) The alluvium likely buries an unmapped fault that dips ~65° toward the northeast and extends ~50 m west of the HF. VP of ~2000-3000 m/s between the unmapped fault and the HF indicates a potentially dropped-down block of bedrock is likely buried beneath the alluvium in that area. (3) Highly fractured Jurassic gabbro or basalt characterizes the block between the HF and another fault (mapped but unnamed) that dips ~65° toward the southwest and extends ~125 m east of the HF. My estimates for the dip of the splay faults are more broadly constrained than for the HF. (4) Jurassic gabbro or serpentinite characterizes the easternmost block, which is probably up-thrown in the footwall of the eastern fault. There is no significant velocity expression for the gabbro-to-sandstone contact that Graymer (2000) maps in the extreme eastern portion of the study area. My models have relatively low spatial resolution in the eastern end of the seismic profile, which lowered the precision of the seismic expression of that area.

The seismic refraction method has two principle limitations. (1) The precision of seismic refraction interpretations is dependent on the resolution of the acquired seismic data and the accuracy of the measured first breaks. Environmental noise, power of the

seismic source, and geophone spacing affect data resolution. In our study area, urban noise limited the propagation of seismic energy, primarily generated by the Betsy

Seisgun™ source, to only ~1/3 of the seismic profile per shot. (2) The exact dip of faults or depth to bedrock cannot always be determined from VP tomography alone. Seismic studies should incorporate VP tomography, VS tomography, VP/VS ratios, and Poisson’s ratios whenever possible.

I recommend several approaches for future research in order to expand on my interpretations. (1) A high-resolution S-wave survey will allow interpretations that are more informed. (2) A P-wave survey using more than three explosive shots will allow deeper penetration of P-waves. (3) Excavating and logging at least one trench and/or deep borehole will allow better correlations among geologic structures and velocity data. (4)

Employing other geophysical methods, including gravity, magnetic, and resistivity may be cost-effective alternatives to trenching and drilling. (5) Conducting other studies, at study areas along-strike of the HF, would permit a more expansive interpretation of the

SLB. In particular, a survey on the east side of Carlos Bee Boulevard would permit an examination of the basal Great Valley Sequence lithology that Graymer (2000) has mapped in contact with gabbro. A primary goal of future work should be to confirm the existence of at least one unmapped splay fault ~50 m west of the HF. Confirmation of that fault would help to evaluate a more realistic seismic hazard for the businesses and residences that are adjacent to the western end of the study area.

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Appendix 1: Glossary of acronyms

AF – Ashland Fault; CF – Chabot Fault; CRO – Coast Range Ophiolite CB13 – Carlos Bee study area seismic survey 2013 CB17 – Carlos Bee study area seismic survey 2017 CMPCC – Common Mid-Point Cross Correlation CSUEB – California State University at East Bay EBSE – East Bay Seismic Experiment GPS – Global Positioning System HF – Hayward Fault; HFZ – Hayward Fault Zone HVZ – High Velocity Zone in seismic velocity models – High Value Zone in seismic velocity ratio or Poisson’s ratio models Hz – Hertz, international unit for frequency km – kilometer; km/s – kilometers per second; L-wave – Love-type surface wave LS13 – Longitudinal-component P-wave velocity model for CB13 LPR13 – Longitudinal-component Poisson’s ratio model for CB13 LPS13 – Longitudinal-component P-wave/S-wave ratio model for CB13 MASW – Multi-channel Analysis of Surface Waves M17 – MASW model for CB17 m – meter; m/s – meters per second; ms - millisecond mm – millimeter mm/s – millimeters per second MF – Moraga Fault; MCF – Miller Creek Fault; PF – Palomares Fault; PRF – Piedmont Reverse Fault P-wave – Primary (compressional) seismic wave P13 – P-wave velocity model for CB13; P17 – P-wave velocity model for CB17 PS17 – P-wave/S-wave ratio model for CB17 PR17 – Poisson’s ratio model for CB17 RCF – Rodgers Creek Fault; R-wave – Rayleigh-type surface wave; SLB – San Leandro Block S-wave – Secondary (shear) seismic wave TS13 – Transverse-component S-wave velocity model for CB13 TPR13 – Transverse-component Poisson’s ratio model for CB13 TPS13 – Transverse-component P-wave/S-wave ratio model for CB13 USGS – United States Geological Survey

VP – P-wave velocity; VS – S-wave velocity

VP/VS – ratio of VP to VS

Appendix 2: List of equipment used during the 2017 seismic refraction survey

From CSUEB:  100-m-long surveying tapes, Brunton Pocket Transit surveying compasses;  Real-Time Kinematic (RTK) Global Positioning System (GPS);  Marking flags, spray paint, shovels;  Sand bags for packing seismic source emplacements  72 4.5 Hz vertical-component geophones, 3 power cables, 3 refraction cables, 3 Geometrics™ Geode 24-channel digital seismographs, 3 auxiliary batteries, and a Panasonic Toughbook as the field laptop computer From USGS:  All-Terrain Vehicle (ATV) for rapid on-site movement;  Hand augers for excavating source emplacements;  3 Betsy Seisgun™ sources, explosive charge sources;  Signal trigger cables and source trigger relay to coordinate timing of source shots with data recording

Appendix 3: List of geophone stations

Station Profile Distance [m] Longitude [°] Latitude [°] Elevation [m]

1 0 122° 04' 20.02994"W 37° 39' 33.38056"N 27.341 2 5 122° 04' 19.88121"W 37° 39' 33.45473"N 27.431 3 10 122° 04' 19.71963"W 37° 39' 33.55022"N 27.531 4 15 122° 04' 19.55706"W 37° 39' 33.64579"N 27.575 5 20 122° 04' 19.38681"W 37° 39' 33.74735"N 27.638 6 25 122° 04' 19.22471"W 37° 39' 33.84333"N 27.797 7 30 122° 04' 19.06486"W 37° 39' 33.94380"N 28.084 8 35 122° 04' 18.90824"W 37° 39' 34.03278"N 28.18 9 40 122° 04' 18.73645"W 37° 39' 34.14568"N 28.527 10 45 122° 04' 18.57211"W 37° 39' 34.22264"N 28.724 11 50 122° 04' 18.41850"W 37° 39' 34.31315"N 28.993 12 55 122° 04' 18.25541"W 37° 39' 34.41291"N 29.417 13 60 122° 04' 18.08639"W 37° 39' 34.51546"N 29.947 14 65 122° 04' 17.92283"W 37° 39' 34.60094"N 30.525 15 70 122° 04' 17.75783"W 37° 39' 34.70109"N 31.309 16 75 122° 04' 17.60282"W 37° 39' 34.80378"N 32.252 17 80 122° 04' 17.44419"W 37° 39' 34.90259"N 33.423 18 85 122° 04' 17.28947"W 37° 39' 34.99820"N 34.633 19 90 122° 04' 17.13312"W 37° 39' 35.09280"N 35.891 20 95 122° 04' 16.97635"W 37° 39' 35.17918"N 37.15 21 100 122° 04' 16.81541"W 37° 39' 35.27996"N 38.875 22 105 122° 04' 16.66259"W 37° 39' 35.37238"N 40.597 23 110 122° 04' 16.49280"W 37° 39' 35.45155"N 42.413 24 115 122° 04' 16.35804"W 37° 39' 35.55891"N 44.032 25 120 122° 04' 16.19131"W 37° 39' 35.64592"N 45.598 26 125 122° 04' 16.03887"W 37° 39' 35.75025"N 46.673 27 130 122° 04' 15.85613"W 37° 39' 35.83438"N 47.574 28 135 122° 04' 15.71660"W 37° 39' 35.93768"N 48.27 29 140 122° 04' 15.55595"W 37° 39' 36.03634"N 48.948 30 145 122° 04' 15.39328"W 37° 39' 36.13704"N 49.642

31 150 122° 04' 15.22903"W 37° 39' 36.22868"N 50.233 32 155 122° 04' 15.07483"W 37° 39' 36.33336"N 50.814 33 160 122° 04' 14.91450"W 37° 39' 36.43761"N 51.361 34 165 122° 04' 14.75832"W 37° 39' 36.53539"N 51.99 35 170 122° 04' 14.59330"W 37° 39' 36.62494"N 53.333 36 175 122° 04' 14.42684"W 37° 39' 36.71671"N 54.326 37 180 122° 04' 14.26571"W 37° 39' 36.79512"N 55.427 38 185 122° 04' 14.11093"W 37° 39' 36.89363"N 56.516 39 190 122° 04' 13.95497"W 37° 39' 36.99921"N 57.263 40 195 122° 04' 13.78740"W 37° 39' 37.09235"N 57.814 41 200 122° 04' 13.63004"W 37° 39' 37.18722"N 59.119 42 205 122° 04' 13.47138"W 37° 39' 37.28840"N 60.071 43 210 122° 04' 13.30091"W 37° 39' 37.37939"N 60.572 44 215 122° 04' 13.14365"W 37° 39' 37.48582"N 60.948 45 220 122° 04' 12.98765"W 37° 39' 37.57249"N 61.215 46 225 122° 04' 12.82986"W 37° 39' 37.67768"N 62.174 47 230 122° 04' 12.66902"W 37° 39' 37.76391"N 63.964 48 235 122° 04' 12.52307"W 37° 39' 37.85259"N 65.701 49 240 122° 04' 12.36927"W 37° 39' 37.94848"N 67.091 50 245 122° 04' 12.20804"W 37° 39' 38.11355"N 67.691 51 250 122° 04' 12.04456"W 37° 39' 38.21238"N 68.79 52 255 122° 04' 11.88571"W 37° 39' 38.30141"N 70.051 53 260 122° 04' 11.74638"W 37° 39' 38.40047"N 71.245 54 265 122° 04' 11.58338"W 37° 39' 38.49800"N 72.516 55 270 122° 04' 11.42334"W 37° 39' 38.58516"N 73.59 56 275 122° 04' 11.25213"W 37° 39' 38.67670"N 74.7 57 280 122° 04' 11.08636"W 37° 39' 38.77310"N 75.458 58 285 122° 04' 10.93212"W 37° 39' 38.87440"N 76.216 59 290 122° 04' 10.77424"W 37° 39' 38.97575"N 76.924 60 295 122° 04' 10.61778"W 37° 39' 39.07202"N 77.427 61 300 122° 04' 10.44474"W 37° 39' 39.16425"N 78.025 62 305 122° 04' 10.28747"W 37° 39' 39.26635"N 78.119 63 310 122° 04' 10.12790"W 37° 39' 39.36502"N 78.448