ii

SIGNATURE PAGE

THESIS: MAPPING SITE RESPONSE ON CAL POLY POMONA

CAMPUS USING SPECTRAL RATIO ANALYSIS

AUTHOR: King Yin Kennis Ho

DATE SUBMITTED: Summer 2015

Geological Sciences Department

Dr. Jascha Polet _________________________________________

Thesis Committee Chair Geological Sciences

Dr. Nick Van Buer _________________________________________ Geological Sciences

Ernest Roumelis PG, EG _________________________________________ Geological Sciences

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ACKNOWLEDGMENTS

I would like to express my deep gratitude to Professor Jascha Polet, my research

mentor throughout the years of undergraduate and graduate, for her patient guidance,

enthusiastic encouragement and useful critiques of this thesis research. I would like to

thanks my parents for continuous support and encouragement. My sincere thanks go for

my mentor student: Nicole Gage. My grateful thanks are also extended to my peers, Terry

Cheiffetz, Kevin Chantrapornlert, Raymond Ng, Julie Leiva, Michael Vadman, Dandan

Zhang, Mikey Herrman. Last but not the least, I would like to give special thanks to Rachel

Hatch and Rosa Nguyen for helping me to go through the time in the graduate room.

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ABSTRACT

Site characteristics have a significant influence on earthquake hazard. To better

understand site response differences on a small scale, as well as the seismic hazard of the

area, we developed site response parameter maps of the Cal Poly Pomona campus.

We applied the Horizontal-to-Vertical Spectral Ratio (HVSR) technique, which is

an empirical method that can be employed in an urban environment with no environmental

impact. We installed broadband seismometers throughout the Cal Poly Pomona campus,

with a total number of 46 sites. The sites are spaced approximately 50 to 150 meters apart

and about two hours of waveforms were recorded at each site. The Geopsy software was

used to produce measurements of fundamental frequency and minimum site amplification

factor. The reliability and quality of these measurements were assessed using criteria from

the Site Effects Assessment Using Ambient Excitations (SESAME) guidelines.

Significant variability in both amplification and fundamental frequency is seen

across campus. Our measurements show some correlation with surface geologic units. Sites

on the alluvial deposits generally have a high minimum amplification of 4, whereas

amplification is around 2 at the hillside sites. The variation in resonance frequency on the

Southeast side of campus may be interpreted as indicating the existence of a shallowly

dipping (less than 5 degrees) impedance contrast at about 100 meters depth, likely between

alluvial deposits and bedrock. Given the measured resonance frequency of around 1 Hz,

buildings located on the alluvium that are between 6-15 stories in height could experience

soil-structure resonance.

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TABLE OF CONTENTS

Signature Page............................................................................................................... ii

Acknowledgements ....................................................................................................... iii

Abstract ......................................................................................................................... iv List of Tables ................................................................................................................ vii

List of Figures ............................................................................................................... viii

Chapter One: Introduction ............................................................................................ 1

Chapter Two: Region of Interest................................................................................... 6

Chapter Three: Methodology ........................................................................................ 15 Chapter Four: Equipment & Software .......................................................................... 26

Equipment ........................................................................................................ 26

Software ........................................................................................................... 29

Choice of Experiment Parameters..................................................................... 39

Chapter Five: Results & Interpretation ......................................................................... 50 Data Analysis ................................................................................................... 50

Site Characteristics Classification......................................................... 55

Comparison with Surface Geology ....................................................... 81

Lateral Variations in Peak Amplitude & Peak Frequency ................... 86

Interpretation of Peak Amplitude ............................................. 89 Interpretation of Peak Frequency ............................................. 90

Estimated Site Response at CLA Building ........................................... 96

vi

Future Work ..........................................................................................100

Chapter Six: Conclusions..............................................................................................101

References .....................................................................................................................102 Appendix A: Standard Deviation and Number of Windows Selected for Different

Window Lengths ....................................................................................108

Appendix B: Change of Standard Deviation and Number of Windows Selected Over Time ...............................................................................................109

Appendix C: Standard Deviation of Peak Frequency and Peak Amplitude for Different Parameter Sets Used to Select Windows..................................115

Appendix D: All Reliable H/V Curves, Grouped According Characteristics .............119

Appendix E: Results of Evaluation of the SESAME Criteria for a Clear Peak for All Reliable H/V Curves ...................................................................129

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LIST OF TABLES

Table 1 Approximate relationship between building height and natural period ...... 5

Table 2 Different parameter sets for selecting waveforms ...................................... 47

Table 3 Reference shear wave velocity around San Gabriel Valley ........................ 94

viii

LIST OF FIGURES

Figure 1 Simple illustration of site amplification...................................................... 1

Figure 2 ShakeMap of the Northridge earthquake .................................................... 2

Figure 3 Collapse of Freeway I-10 in Santa Monica................................................. 3 Figure 4 Map of 1985 “Mexico City” Earthquake .................................................... 4

Figure 5 Tectonic setting of the Cal Poly Pomona campus ...................................... 7

Figure 6 Closer look at tectonic setting around the Cal Poly Pomona campus ........ 7

Figure 7 Detailed map of the Cal Poly Pomona campus........................................... 9

Figure 8 Earthquakes from the past 45 years within 15 km of the campus .............. 10 Figure 9 Geologic map of the Cal Poly Pomona campus.......................................... 11

Figure 10 Liquefaction and landslide hazard map of the Cal Poly Pomona campus .. 12

Figure 11 ShakeMap of the Chino Hills earthquake, 2008 ........................................ 14

Figure 12 A simple seismogram of noise .................................................................... 16

Figure 13 Comparison of ambient vibration and earthquake based measurements of fundamental frequency (top) and amplification (bottom) ...................... 18

Figure 14 Simple diagram of ground motions used to illustrate H/V method ............ 20

Figure 15 Simple diagram of HVSR method .............................................................. 22 Figure 16 Simple H/V curve ....................................................................................... 23

Figure 17 K-factor versus distance from coastline...................................................... 25

Figure 18 Picture of seismometer and its connections ............................................... 26

Figure 19 Equipment used........................................................................................... 27

Figure 20 H/V Toolbox first tab, General................................................................... 30

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Figure 21 H/V Toolbox first tab, Raw signal .............................................................. 31

Figure 22 H/V Toolbox second tab, Processing ......................................................... 32

Figure 23 H/V Toolbox third tab, Output.................................................................... 33 Figure 24 H/V Toolbox, dropdown menu ................................................................... 34

Figure 25 An example of auto selected windows........................................................ 35

Figure 26 An example of selected data windows after calculation of the spectral ratio

curve. ......................................................................................................... 37

Figure 27 An ideal example of an H/V curve.............................................................. 38

Figure 28 Criteria for a reliable H/V curve and criteria for a clear H/V peak ............ 39

Figure 29 Three selected locations for pre-experiment ............................................... 41

Figure 30 H/V curve for station KGH ......................................................................... 42 Figure 31 H/V curve for station FMG ........................................................................ 43

Figure 32 H/V curve for station MBX ........................................................................ 44

Figure 33 Comparison of window selection between day- and night-time at station

FMG. ......................................................................................................... 45

Figure 34 Comparison of window selection between day- and night-time at station

KGH ........................................................................................................... 46 Figure 35 Comparison of window selection between day- and night-time at station

MBX............................................................................................................ 46

Figure 36 Comparison of windows selected for different parameter sets for station FMG. ............................................................................................... 48

Figure 37 Comparison of windows selected for different parameter sets for station KGH. ............................................................................................... 48

Figure 38 Comparison of windows selected for different parameter sets for station MBX ................................................................................................ 49

Figure 39 Google Earth map of Cal Poly Pomona campus with all reliable H/V

curves .......................................................................................................... 52

x

Figure 40 Peak amplitude for the Cal Poly Pomona campus overlaid on geological map ............................................................................................ 53

Figure 41 Peak frequency for the Cal Poly Pomona campus overlaid on

geological map ............................................................................................ 53 Figure 42 K-factors for the Cal Poly Pomona campus overlaid on seismic

hazard map .................................................................................................. 54

Figure 43 Selected windows for Site-44’s seismogram .............................................. 55 Figure 44 H/V graph for Site-44 ................................................................................. 55

Figure 45 Settings for H/V calculation for Site-44 ..................................................... 56

Figure 46 Selected windows for Site-30’s seismogram .............................................. 59

Figure 47 H/V graph for Site-30 ................................................................................. 59

Figure 48 Settings for H/V calculation for Site-30 ..................................................... 60 Figure 49 Selected windows for Site-33’s seismogram .............................................. 63




Figure 53 H/V graph for Site-34 ................................................................................. 69 Figure 54 Settings for H/V calculation for Site-34 ..................................................... 70




Figure 58 H/V Rotate results for Site-13..................................................................... 77 Figure 59 Selected windows for Site-2’s seismogram ................................................ 78

Figure 60 H/V graph for Site-2 ................................................................................... 78

Figure 61 Settings for H/V calculation for Site-2 ....................................................... 79

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Figure 62 Total site distribution of groups for the entire campus ............................... 82

Figure 63 Site classification for geologic unit sand alluvial deposits (Qyfa) ............. 83

Figure 64 Site classification for geologic unit silt alluvial deposits (Qyfs) ................ 83

Figure 65 Site classification for geologic unit clay alluvial deposits (Qyfc). ............. 84

Figure 66 Site classification for geologic unit La Vida Member (Tpl) ....................... 85 Figure 67 Site classification for geologic unit Topanga Formation (Ttc) ................... 85

Figure 68 Peak amplitude versus peak frequency graph for measurements from all

reliable curves ............................................................................................. 87 Figure 69 Peak amplitude versus peak frequency for different colored groups. ......... 88

Figure 70 Peak amplitude versus peak frequency graph with only Group Yellow

and Green. ................................................................................................... 88 Figure 71 Peak amplitude of the spectra ratio curves for all campus sites, overlain

on a topographic map .................................................................................. 90

Figure 72 Topographic profile across the Cal Poly Pomona campus on Google Earth ............................................................................................................ 91

Figure 73 Geological map overlaid on Google Earth map showing topographic profile along the red line ............................................................................. 91

Figure 74 Estimated depth to interface on topographic map....................................... 92

Figure 75 Estimated dip of interface using 314 m/s as shear wave velocity............... 94

Figure 76 Estimated dip of interface using 502 m/s as shear wave velocity............... 95 Figure 77 A dipping structure could be caused by deformation due to the San Jose

thrust fault on campus ................................................................................. 96

Figure 78 Picture of the CLA building........................................................................ 97 Figure 79 Location of the CLA building (dark outline) on fault map from

Geocon ........................................................................................................ 97

Figure 80 Stations around the CLA building .............................................................. 98

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Figure 81 H/V curve of Site-50 ................................................................................... 98

Figure 82 Location of the replacement building with yellow dot indicating the closest seismometer site ........................................................................ 99

Figure 83 H/V curve for Site-33..................................................................................100

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CHAPTER ONE

INTRODUCTION

Throughout history, earthquakes have caused much destruction to urbanized areas,

and have been responsible for the loss of many lives and major economic damages. Surface

ground motion is one of the contributing factors that can affect the level of damage

experienced during an earthquake. Various types of surface layers can influence ground

motion due to differences in soil hardness and thickness. In general, soft soil sites tend to

have lower shear wave velocities and to amplify ground motions relative to hard rock sites

(Figure 1).

Figure 1. Simple illustration of site amplification. Earthquake

waves propagate from lower left corner to ground surface with one seismometer on a hard rock site and one seismometer on a soft soil site showing ground motion (Ammon, 2001).

The 1994 Northridge earthquake is a key example of the effects of site amplification

in Southern California. Figure 2 shows the ShakeMap for the Northridge earthquake, where

the shaking intensity level is indicated in different colors, with warmer colors representing

higher levels of shaking. The city of Santa Monica, as shown by the white dot in Figure 2,

especially suffered heavy shaking, while other areas at similar distances from the epicenter

2

experienced much smaller ground motions. Moreover, the collapsed Interstate 10 highway

(Figure 3) was built on top of a drained wetland, which experienced amplified ground

shaking. Results from Boore et al. (2003) show that the ground motions in the collapsed

Interstate-10 highway area, which was 2.3 kilometers away from the epicenter, were a

factor of 1.2 to 1.6 higher than in the surrounding area.

Figure 2. ShakeMap of the Northridge earthquake (USGS, 1997). Red lines outline faults in the region. The black star shows the epicenter.

Colors represent the intensity, with red the highest intensity, and white the

3

lowest. Black dots show the main cities. White dot indicates Santa Monica.

Figure 3. Collapse of Freeway I-10 in Santa Monica (U.S. Department of Transportation, 2002).

The damage level may also be associated with a combination of building height and

shallow subsurface velocity structure. When earthquakes occur, columns of ground

materials may vibrate stronger in a certain frequency range. Buildings may also vibrate at

a higher amplitude in a certain frequency range. When both frequencies are similar, soil

structure resonance will occur and the potential damage to the building will be increased.

The magnitude 8.0 “Mexico City” earthquake on September 19, 1985 is another

example of increased earthquake damage due to site response. The epicenter of this

earthquake was located 300 kilometers Southeast of Mexico City (Figure 4), but

considerable damage was still sustained in the capital of Mexico. Normally, ground

motions due to seismic waves are significantly attenuated at large distances and are of

relatively small amplitude. However, the center of Mexico City is located on a dry lakebed,

Lake Texcoco, where the soil resonance has similar frequency as the surface waves from

the offshore earthquake at this location, namely 0.5 Hz (2 seconds period). Many buildings

that were between eight stories and eighteen stories in height collapsed during this

4

earthquake. These buildings also had a 0.5 to 1 Hz natural frequency (see Table 1). Both

the soil and some of the buildings therefore experienced resonance, which led to major

damage in Mexico City (Flores, 1987). As this example shows, determining site

amplification and fundamental frequencies can help mitigate seismic hazard.

Figure 4. Map of 1985 “Mexico City” Earthquake with cities that experienced violent

shaking denoted with red dots. Note that the earthquake occurred along the coast, with Mexico City located 300 kilometers inland (“Mexico City earthquake of 1985”, n.d.).

5

Table 1

Approximate Relationship Between Building Height And Natural Period

(MCEER, 2010).

To completely understand the soil structure of a site, it is necessary to drill and

retrieve soil core samples. Depending on the depth and drilling area, this can be expensive

and can cause permanent damage to the environment. Another option to consider is the use

of geophysical methods, which are a cost-effective and non-intrusive approach for site

investigations. Traditional geophysics commonly employs the refraction or the reflection

method to determine the seismic velocity structure of a site. These methods require a

significant amount of equipment and personnel. For a more efficient approach, we use

records of ground motion of noise to measure site response parameters.

The main goal of this thesis is to enhance our understanding of the seismic response

of the area of the campus of California State Polytechnic University, Pomona. We therefore

carried out numerous experiments to determine site response parameters at many locations

across campus and created maps to show the lateral variation of these parameters.

6

CHAPTER TWO

REGION OF INTEREST

Our region of interest for this research is a university campus in Southern

California. The campus, known as California State Polytechnic University, Pomona, will

henceforth be referred to as Cal Poly Pomona. Several previous studies have been carried

out within this area. GeoCon (2001) performed borehole borings, trenching, and gamma-

ray spectrometer surveys on the campus. Oliver (2010) applied the refraction microtremor

technique to estimate shallow S-wave velocity profiles at several sites on campus. Pazos

(2011) and Potter (2011) generated gravity profiles across traces of the San Jose Fault

through the campus. Figure 5 shows the tectonic setting of the campus. Cal Poly Pomona

is located on the West side of the freeway intersection of the I-10 and 57 (as shown by the

blue dot on Figure 5). To the North are the Indian Hill Fault and San Gabriel Mountains.

Located to the South are the Puente Hills, with the Whittier Fault to the Southwest. To the

West is the San Gabriel Basin. The campus is located on top of the San Jose Fault (Figure

6), which has a shallow to moderate dip to the North and the campus is within 40 kilometers

South of the San Andreas Fault Zone.

7

Figure 5. Tectonic setting of the Cal Poly Pomona campus. Grey color indicates

area of higher elevation, such as hills and mountains. Exposed faults are shown in dark black lines, covered faults with dotted lines. Dashed lines with numbers

show the location of freeways. The extent of drainages is indicated with dash-dot lines. The campus is shown as a blue dot (adapted from Yeats, 2004).

Figure 6. Closer look at tectonic setting around the Cal Poly Pomona campus. White lines

indicate folding. Dotted lines show the location of buried faults. Black-white line indicates the suggested San Jose Fault trace line (Yeats, 2004).

8

To develop a better understanding of the local area, Figure 6 provides a closer look

at the tectonic setting. On the Southeast side of campus is Elephant Hill and the Chino

Basin (located in the Southeast corner of Figure 6), while the rest of the area is more hilly.

To the West, there are a few synclines and anticlines. The figure also shows a simplified

fault trace of the San Jose Fault.

Figure 7 is a detailed campus map, also showing the 10 Freeway to the North. This

figure shows the San Jose Fault trace as determined by GeoCon (2001) and color coded by

Pazos (2011). The red line is the trace of the San Jose Fault, which intersects the complete

campus. According to GeoCon (2001), the San Jose Fault is a regional listric thrust fault

with two shallowly to moderately North-dipping thrust faults in the central campus and it

merges to the Southwest with a secondary fault steeply dipping to the South. Based on

findings from the Southern California Earthquake Center (SCEC), the San Jose Fault was

involved in two recent earthquakes: the 1988 and the 1990 Upland earthquakes. Hauksson

(1991) determined that the 1988 earthquake had a magnitude of 4.7, with minor damage in

the area closest to the epicenter. The 1990 earthquake had a magnitude of 5.4 and caused

minor injuries to thirty-eight people and considerable damage near the epicenter (Person,

1990). These two earthquakes have shown that the San Jose Fault should be considered an

active fault. In addition to the San Jose Fault, there exist numerous other faults that are

capable of producing strong ground motions on the Cal Poly Pomona campus.

9

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10

Figure 8. Earthquakes from the past 45 years within 15 km of the campus. White circles represent earthquakes located by USGS. Black circle indicates the location of the Cal Poly

Pomona campus. The size of circles represents the earthquake magnitudes. Red lines represent faults and their names (explained in main text) in black. White lines indicate

roads (USGS, 2015).

Figure 8 shows a map of the local seismicity generated by the USGS tool located

at Search Earthquake Archives (USGS, 2015), for the past 45 years within 15 kilometers

of Cal Poly Pomona. Within this timeframe, this area has had a total of 218 earthquakes

with 37 earthquakes having a magnitude higher than 3, with 7 magnitude 4+ earthquakes

and 1 magnitude 5+ earthquake. Most of the earthquakes are less than 15 kilometers deep,

which is considered shallow. In addition to the San Jose Fault (SJF) that across the campus,

11

this figure also shows several regional active faults surrounding the Cal Poly Pomona

campus. To the North of the campus, there are the Sierra Madre Fault (SMF) zone and the

Indian Hill Fault (IHF). To the Southwest is the Elsinore Fault zone (Whittier section, WF)

and to the Southeast are the Central Avenue Fault (CAF) and Elsinore Fault zone (Chino

section, CF). All these faults can cause significant ground motions on the Cal Poly Pomona

campus. Therefore, it is important to understand the local site characteristics of the campus.

Figure 9. Geologic map of the Cal Poly Pomona campus. Qyf-alluvial fan and valley

deposits; a=sand, s=silt, c=clay. Tpl-platy siltstone interbedded with sandstone, conglomerate, limestone and tuff. Tpy-platy siltstone with interbeds of sandstone, limestone and marl. Ttc-pebbly sandstone and conglomerate. Black lines indicate the

location of contacts between units; a solid black line shows an accurately located contact and a dashed line shows an approximately located or inferred contact. Grey color indicates

buildings and freeways. Thick black and white line indicates roads (adapted from Tan, 1997).

To have a better understanding of the site characteristics, we need to gather more

background information on the study area. Figure 9 shows the surface geology map of the

greater campus area. The San Jose Creek runs along the right side of South Campus Drive

12

in an area of alluvial sand deposits (Qyfa). Most campus buildings are built on top of silt

and clay alluvial deposits (Qyfs and Qyfc) at the center of the figure. The Southwest side

of campus is built on siltstone, whereas the Northwest side of campus is mainly built on

top of sandstone and conglomerate. The underlying topography map in Figure 9 indicates

flatter land on the East side of the campus, and hills to the North and West.

Figure 10. Liquefaction and landslide hazard map of the Cal Poly Pomona campus. Green – Liquefaction hazard areas. Blue – Landslide hazard areas. Black - Surface buildings and roads (adapted from Davis, 1999).

Earthquakes can also cause liquefaction and landslides. Figure 10 shows a hazard

map of campus with the shaking inputs based on a 10% probability of exceedance in 50

years. A green color is used for potential liquefaction hazard areas, which underlie most of

the campus. The hills to the Northwest show potential hazard for earthquake induced

landslides.

13

We use the ShakeMap of the Chino Hills earthquake in 2008 as a reference for the

level of shaking produced by a magnitude 5.5 earthquake in the local area (Figure 11). The

measured intensity for the closest station to the epicenter is about intensity VI, which is

approximately the same intensity measured by the station (21 kilometers away from

epicenter) that is closest to Cal Poly Pomona. Although there are numerous earthquakes in

the local area, most of them are aftershocks with low magnitude. Only one Southern

California Seismic Network station was located on campus and this instrument was only

active for a few years. Therefore, earthquake based data is not sufficient for studies of site

characteristics at Cal Poly Pomona campus, since the few available waveforms are not

adequate for such a study. Cal Poly Pomona will experience high frequency, short wave

length, ground motion if a local earthquake occurs, such as on the San Jose Fault. On the

other hand, the campus will experience low frequency, long wave length, ground motion

from any earthquake that occurs at regional distances on faults such as the San Andreas.

Numerous faults surround the Cal Poly Pomona campus at both local and regional

distances. Therefore, we will focus on a broadband frequency range for this research,

covering a large spectrum of possible ground motion frequencies.

14

Figure 11. ShakeMap of the Chino Hills earthquake, 2008, colored according to shaking intensity. Red star indicates epicenter. Black dots show the location of major cities. Purple

dot shows the Cal Poly Pomona campus (adapted from USGS, 2008).

15

CHAPTER THREE

METHODOLOGY

The best way to understand subsurface geology is through applying invasive site

assessment techniques such as drilling and trenching. Although Geocon (2001) obtained

geologic borehole data from the Cal Poly Pomona campus, these boreholes only reached

about 80 feet (25 meters) in maximum depth below the surface. Borehole geology has a

great impact on the environment and involves other logistical issues that are associated

with drilling in developed urban areas. An alternative to this approach is to use a passive

geophysical method such as the Standard Spectral Ratio (SSR) approach (Abbott, 2006).

This method uses data recorded by seismometers and determines the site response

differences between a soft soil site and a reference site, usually located on hard rock

material. This method requires active seismicity with large earthquakes to be able to carry

out its data analysis. For a site like the Cal Poly Pomona campus that has experienced little

to no strong ground motion and has not been well instrumented, this method is not

appropriate. Instead we chose to apply another passive method that is based on the use of

background noise, called the Horizontal-to-Vertical Spectral Ratio (HVSR) approach. This

is an empirical method that was first applied by Nogoshi and Igarashi (1970, 1971) to

determine site response parameters such as fundamental frequency and site amplification.

This well-established method is based on a computation of the ratio of horizontal ground

motion over vertical motion. Numerous studies have been conducted successfully (Lacave,

1999 and references therein) using HVSR and have compared its results to those obtained

by other geophysical methods. In general, this method is capable of determining accurate

estimates of resonant fundamental frequency and may provide a lower bound of the

16

amplification factor of a site. Based on these two parameters, we can also estimate the

minimum depth to the first significant subsurface impedance contrast. An additional

parameter, the k-factor, may also be derived and used as an estimate for the susceptibility

to damage from liquefaction. To help mitigate earthquake effects, we can determine these

site response parameters, so that they can be taken into account when designing and

constructing buildings.

The HVSR method analyzes ambient noise from vertical and horizontal ground

motion to determine site characteristics. Ambient noise is also referred to as microtremor.

It is a low amplitude background vibration that is caused by local movement such as people

walking, wind blowing, and car movement. Figure 12 shows an example of microtremor

recorded on a seismogram. The figure shows random background noise in 3 different

orthogonal directions, vertical (Z), north-south (N), and east-west (E).

Figure 12. A simple seismogram of noise recorded with ground motion amplitude in three directions on the y-axis and time on the x-axis.

17

A European project called Site EffectS assessment using AMbient Excitations

(SESAME) conducted extensive research on the application of the HVSR method

(SESAME, 2004). One of their projects compared the results of microtremor based HVSR

versus earthquake based SSR at different sites. Figure 13 (top) shows a comparison of the

fundamental frequencies and Figure 13 (bottom) shows that of the amplification. In Figure

13 (top), most of the data plots on a straight line, showing a linear relationship between the

fundamental frequency determined using the two methods. Thus, this result of the

SESAME project suggests that the fundamental frequency measured from ambient noise

corresponds well with the actual site response. The bottom diagram shows ground motion

amplification measured by ambient vibrations plotted against ground motion amplification

determined from earthquake data. Most of the data plot below the 1-to-1 ratio line,

suggesting that amplification measured from ambient vibrations can be considered to be a

lower bound on the site response amplification due to earthquakes. However, most of the

data points do plot close to the 1-to-1 ratio line. In this thesis project, we will therefore

assume that the HVSR peak frequency provides an estimate of the site’s fundamental

frequency and the HVSR peak amplitude may be considered to represent a lower bound of

the true site amplification factor.

18

Figure 13. Comparison of ambient vibration and earthquake based measurements of fundamental frequency (top) and amplification (bottom).

Y-axis shows results obtained by the HVSR method; x-axis show those of the SSR method (SESAME, 2004).

19

The HVSR method is empirical and was originally developed using observations

from earthquakes in Japan. Several theoretical explanations have been developed to try to

address why the HVSR method works (e.g. Jerez et al., 2004 and Fäh, 2001). In general,

most researchers (e.g. Lane Jr, 2008) use ground motion predictions based on a 1-D model

with a homogeneous soft soil layer overlying hard rock, as shown in Figure 14. We here

describe the explanation from Lermo and Chavez-Garcia (1994) and originally from

Nakamura (1989). They assume the microtremor originates from a local source and that

the microtremor mainly consists of Rayleigh waves. As we are interested in how much a

surficial soft layer can amplify ground motion compared to bedrock, Equation 1 shows our

desired result: the ratio of the surface horizontal movement to the bedrock horizontal

movement. But, the horizontal movement of bedrock is difficult to determine and SE

includes a source effect. To compensate SE for the source spectrum, a modified site effect

spectral ratio SM with the relative vertical motion (Equation 2) is computed as shown in

Equation-3. Then, we assume that bedrock doesn’t amplify the horizontal movement as

shown in Equation 4. Substituting Equation 4 into Equation 3, we obtain Equation 5, the

horizontal movement divided by the vertical movement, which is the basic for the HVSR

method.

20

Figure 14. Simple diagram of ground motions used to illustrate H/V method.

Z-Thickness of first layer. VS-Vertical movement of surface. HS-Horizontal movement of surface. VB-Vertical movement of base rock. HB-Horizontal movement of base rock (from

Nakamura, 1989).

Equation 1. Ideal equation to calculate site effect.

Equation 2. Site vertical motion relative to bedrock.

Equation 3. Modified site effect equation to compensate for any source effect.

21

Equation 4. Assumption that there is no horizontal amplification on bedrock.

Equation 5. Equation for HVSR.

Figure 15 illustrates that the horizontal ground motion is generally larger than the

vertical ground motion in soft soil, while both motions are similar at a hard rock site. The

right side of the figure shows that by dividing the horizontal movement by the vertical

movement, a standout peak is generated.

22

Figure 15. Simple diagram of HVSR method. H is horizontal motion. V is vertical motion. Blue arrows indicate motion on hard rock site. Red arrows indicate motion on soft soil

layer. Fo is the fundamental frequency (Nakamura, 2008).

This method produces an H/V curve as shown in Figure 16. We mainly focus on

two parameters that may be measured from this curve: the peak spectral ratio frequency

(f0) and the peak amplitude (A0). These two values can be interpreted in the context of the

fundamental frequency and amplification factor. We will explain these two values in more

depth in a later section.

23

Figure 16. Simple H/V curve. f0 denotes the frequency of the highest peak. A0 is the

amplitude of the highest peak.

Once we have a peak frequency and an estimate of the local shallow shear wave

velocity, we can calculate the minimum depth to the impedance contrast using

Equation 6.

hmin ≈ 𝑉𝑠𝑠𝑢𝑟𝑓

4𝑓0

Equation 6. hmin is the minimum depth to the impedance contrast. Vssurf is the top soft soil layer shear wave velocity. f0 is the fundamental frequency (SESAME, 2004).

In addition to the two most frequently used HVSR parameters, a derived

liquefaction parameter, the k-factor (Equation 7), involves the fundamental frequency and

site amplification factor and was used by Nakamura (1996) to estimate the potential for

damage by earthquake liquefaction. This parameter was developed using an empirical

approach that is based on observations from the 1989 Loma Prieta Earthquake in the San

24

Francisco Bay area. Liquefaction is failure of soil strength. When an earthquake happens,

shaking causes the water pressure inside saturated soil to increase, which decreases the

strength of the soil, causing buildings on the surface to sink.

k=𝐴02

𝑓0

Equation 7. Equation for the k-factor, k. A0 is the site amplification. f0 is fundamental frequency (Nakamura, 1996).

As shown in Figure 17, in the Loma Prieta earthquake the reclaimed land area

suffered severe damage and the k-value calculated for sites in this region had the highest

value. The seaside area was also damaged by liquefaction and sites there had a k-factor

higher than 20. As the distance from the coastline increases, both the amount of damage

and the k-factor decrease. In the hillside area, where there was no damage, the k-value had

decreased to 5 and below. The author concluded that when k is greater than 20, liquefaction

is likely to occur when strong ground motions are experienced. Therefore, we also

calculated the k-factor (Equation 7) and compared our results to existing liquefaction maps.

25

Figure 17. K-factor versus distance from the coastline. Y-axis shows the value of the k-factor and the x-axis shows the distance from the coastline. Each dot is a measured value from a site (Nakamura, 1996).

Numerous experiments have used the HVSR method. Panou et al. (2005) and

Konno and Ohmachi (1998) both show good correlation of both fundamental frequency

and amplification with the thickness of the top soil layer. Konno and Ohmachi (1998) and

Huang and Teng (1999) also show that H/V ratio data agrees with measurements based on

earthquake data. Parolai et al. (2002), Fairchild (2013) and Lane (2008) confirm that the

HVSR approach works well in areas that have a significant impedance contrast between

the sediment layers and underlying bedrock. However, Castellaro and Mulargia (2009)

concluded that the low frequency results are weather dependent and not accurate. Delgado

et al. (2000) argue that HVSR is not an appropriate method to use in areas where there is

no strong impedance contrast at depth or where the shear wave velocity changes irregularly

with depth.

26

CHAPTER FOUR

EQUIPMENT AND SOFTWARE

Equipment

We used seismometers manufactured by Guralp, model CMG-6TD as shown in

Figure 18. It is a broadband, force-feedback instrument measuring ground motions in three

directions: vertical (Z), north-south (N), and east-west (E). The sampling rate is 0.01

second (100 Hz). It includes a Global Positioning System (GPS) unit that can synchronize

its time and location using satellites.

Figure 18. Picture of seismometer and its connections. Left figure shows a simple diagram

of equipment set up. Right photo shows the actual size of the seismometer.

27

Figure 19. Equipment: top row, from left to right: hard drive, laptop computer, GPS unit, seismometer, marine battery, data extraction cable, computer data cable, GPS cable, battery

cable, and breakout box cable.

Setting up the experiment is straightforward and can easily be done by one person.

We installed seismometers throughout the Cal Poly Pomona campus following the

guidelines suggested by SESAME:

In Situ Soil-sensor Coupling

A thin cover of asphalt or concrete does not affect H/V results in the main

frequency band of interest

It is not recommended to put the seismometer on grass since the blowing wind

can lead to perturbed results below 1 Hz

Avoid setting the sensor on superficial layers of "soft" soils, such as mud,

plowed soil, or artificial covers like synthetic sport covering

28

Avoid recording on water saturated soils, for example after heavy rain

Avoid recording on superficial cohesionless gravel, as the sensor will not be

correctly coupled to the ground resulting in strongly perturbed curves

Sensor Setting

The sensor should be set up on the ground horizontally as recommended by the

manufacturer

Do not put any load on the sensor

Recording near structures may influence the results: movements of the

structures due to the wind may introduce strong low frequency perturbations in

the ground

Avoid measuring above underground structures such as car parks, pipes, sewer

lids, etc., these structures may significantly alter the amplitude of the vertical

motion

Weather Conditions

Avoid measurements during windy days

Measurements during heavy rain should be avoided, while slight rain has no

noticeable influence on H/V results

Extreme temperatures should be treated with care

Disturbances

All kinds of short-duration local sources (footsteps, car, train, etc) can disturb the

results

o Fast highway traffic influences H/V ratios if they are within 15-20 meters

o Slow inner city traffic influences H/V ratios when they are much closer

29

Avoid measurements near monochromatic sources like: construction machines,

industrial machines, pumps, etc.

The recording team should not keep its car engine running during recording

Software

We use the Geopsy software program (http://www.geopsy.org/) to generate the

spectral ratio curves. We will illustrate our workflow and choice of input parameters by

describing the use of this software on the waveform data from one of our sites. First, we

input the 3 component seismograms. Then, we set our parameters in the H/V Toolbox.

When we open the H/V toolbox, as shown in Figure 20, the first tab will show, Time.

Within this tab, we can narrow the data to a certain time period for analysis in Global Time

Range. We can also set the length of each window for H/V analysis in Time Windows.

30

Figure 20. H/V Toolbox first tab, General.

Within a sub-tab of Time, Raw Signal (Figure 21), we can control what kind of

waveform we want to use for analysis. As we mentioned in a previous section, HVSR uses

ambient noise. Therefore, we set the parameters to help us select waveforms that are low

amplitude background noise and also eliminate large sudden peaks. Detailed explanations

on what parameters we use for Raw Signal will be discussed in the Pre-experiment section.

31

Figure 21. H/V Toolbox first tab, Raw signal.

The second tab is Processing (Figure 22), which controls how Geopsy processes

data and combines the horizontal components, N-S and E-W, into one component. For this

section, we use the default setting.

32

Figure 22. H/V Toolbox second tab, Processing.

The third tab is the Output (Figure 23), which controls the frequency range,

appearance, and the output folder. We chose a broadband frequency sampling range

between 0.1 Hz and 20 Hz.

33

Figure 23. H/V Toolbox third tab, Output.

Once we set the parameters, we return to the Time tab and then click on the

dropdown menu marked with Select in the lower right corner and choose Auto as shown in

Figure 24.

34

Figure 24. H/V Toolbox, dropdown menu.

This will generate a set of pre-selected windows on the seismograms in a green

color as shown in Figure 25. From this step, we can add or remove any of these windows

manually to prepare for H/V data processing. After that, we click Start and the software

runs the H/V calculation.

35

Fig

ure

25. A

n ex

ample

of

auto

sel

ecte

d w

indow

s.

36

The program then colors the selected windows as in Figure 26. Each colored

window undergoes the H/V calculation and is used to generate an H/V curve. Then, all the

H/V curves are plotted together as shown in Figure 27. The black colored H/V curve is the

average of all colored H/V curves, while the dashed black lines indicate the standard

deviation. The vertical grey bar shows the auto-selected peak, which is the highest

amplitude peak. Figure 27 shows an ideal situation where there is a single clear peak. Based

on this figure, the frequency of the peak (f0) is about 1.074 Hz with standard deviation of

0.137 and the peak amplitude (A0) is about 4.515 with a standard deviation of about 1.209.

We can then use the criteria list shown in Figure 28 to determine whether this H/V curve

is reliable and its H/V peak is clear. The criteria for the reliability of the H/V curve verify

that there are enough windows selected for the targeted frequency with low standard

deviation. The criteria for a clear H/V peak check that the peak stands out from the

background H/V curve with small standard deviation and fulfills thresholds of peak

frequency and peak amplitude. If both sets of criteria are met, we consider, based on the

empirical results shown in Figure 13, the peak frequency as an estimate of the fundamental

frequency of the site and the peak amplitude as the lower bound on the site amplification.

37

Fig

ure

26. A

n ex

ample

of

sele

cted

dat

a w

indow

s af

ter

calc

ulat

ion

of

the

spec

tral

rat

io

curv

e.

38

Figure 27. An ideal example of an H/V curve. X-axis indicates frequency (in Hz). Y- axis indicates spectral ratio amplitude. Each colored line is an H/V curve in each

selected window of the same color. Solid black line indicates the average H/V curve. Dotted lines represent the standard deviation of the H/V curve. Grey bars indicate the

selected peak frequency and its standard deviation.

39

Figure 28. Criteria for a reliable H/V curve and criteria for a clear H/V peak (SESAME, 2004).

Choice of Experiment Parameters

As we mentioned in the REGION OF INTEREST chapter, Cal Poly Pomona will

experience different frequencies of ground motion depending on the distance to the

earthquake rupture and the magnitude of the event. Therefore, we are interested in the site

response over a broadband frequency range from 0.1 Hz to 20 Hz. For an H/V curve to be

considered reliable, we need at least ten full cycles of the targeted frequency as shown by

Equation 8 (SESAME, 2003).

Window Length = 1 / frequency *10

Equation 8. Appropriate minimum window length.

40

If the targeted frequency is 20 Hz, one cycle is 0.05 seconds. Ten cycles will give

us 0.5 seconds as window length. If the targeted frequency is 0.1 Hz, one cycle is 10

seconds and ten cycles will give us 100 seconds. Therefore, we use a 100 second window

length to cover our frequency range of interest. An additional benefit of a longer window

length is that it generates measurements with a lower standard deviation as shown in

Appendix A.

The standard deviation of our measurements can also be affected by the number of

windows. Geopsy uses Equation 9 to calculate the standard deviation of the H/V curve.

Equation 9. Equation used in the Geopsy software to compute σH/V, the standard deviation

of the H/V curve. nwindows is number of windows selected (SESAME, 2003).

We initially collected waveform data at a few sites to empirically estimate the time

when the standard deviation would stabilize and no longer decrease significantly with time.

In general, about one hour of seismometer data was needed for a stable standard deviation

of peak frequency, while there was no clear correlation between the standard deviation of

the peak amplitude and the duration of the available data. The results of these tests are

shown in Appendix B. To guarantee that we had sufficient data for our analysis, we decided

to have at least 2 to 3 hours recording time at each site.

We installed three seismometers in three different locations for three months as a

preliminary experiment. These sites were used as our references for this thesis project. The

locations are shown in Figure 29.

41

Figure 29. Three selected locations for pre-experiment. Map generated with Google Earth.

The results of our preliminary experiment are shown in Figure 30 to Figure 32 and

each figure was based on the analysis of a one full day (24 hours) of waveform data.

The H/V curve for station KGH (Figure 30) shows a peak frequency at 0.387 Hz with

standard deviation of 0.073 and a peak amplitude at 2.375 +- 1.289. The H/V curve for

station FMG (Figure 31) shows a peak frequency at 1.075 Hz with standard deviation of

0.132 and a peak amplitude at 4.637 with a standard deviation of 1.205. The H/V curve for

station MBX (Figure 32) shows two small peaks. The first peak frequency is at 0.165 Hz

with standard deviation of 0.035, with a peak amplitude of 2.019 and a standard deviation

of 1.419. The second peak frequency is at 0.494 Hz with a standard deviation of 0.075. Its

associated amplitude is 2.121 with a standard deviation of 1.238. This initial analysis gave

us a general idea of the site characteristics on the Cal Poly Pomona campus.

42

Figure 30. H/V curve for station KGH. Peak frequency at 0.387 Hz with standard deviation of 0.0731. A peak amplitude at 2.375 with standard deviation of 1.289.

Graph lines, colors and axes as described for Figure 27.

43

Figure 31. H/V curve for station FMG. Peak frequency at 1.075 Hz with standard deviation of 0.132. A peak amplitude at 4.637 with standard deviation of 1.205.

Graph lines, colors and axes as described for Figure 27.

44

Figure 32. H/V curve for station MBX. First peak frequency at 0.165 Hz with standard frequency of 0.035. An amplitude of 2.019 with standard deviation of

1.419. Second peak frequency at 0.494 Hz with standard deviation of 0.075. Its associated amplitude is 2.121 with standard deviation of 1.238. Graph lines, colors

and axes as described for Figure 27.

To determine the best time of day for the experiments, we compared the difference

between results obtained for waveforms recorded during the daytime and nighttime. Figure

33 to Figure 35 show the number of windows selected for analysis at each site. We chose

one week of data and compared the three stations. Daytime is considered to be 07:00 to

19:00 and nighttime is considered from 19:00 to 07:00 the next day. We used the parameter

45

set suggested by SESAME: STA: 1, LTA: 30, Min STA/LTA: 0.3, and Max STA/LTA:

2.0 with 100 seconds window length. These three data sets do not shown a correlation

between number of windows selected in weekday and number of windows selected in

weekend. For the data for station FMG (Figure 33), a similar number of windows was

selected between daytime and nighttime. For the data for station KGH (Figure 34), a very

small number of windows was selected during the nighttime. For the data for station MBX

(Figure 35), generally a higher number of windows was selected during the daytime and a

very small number of windows was selected in the night. We could explain these numbers

by an increase in the ambient noise needed for this analysis during the daytime. Since it is

important to have sufficient windows selected for analysis for the relatively short

deployment time, we decided to install the seismometers during the daytime.

Figure 33. Comparison of window selection between day- and night-time at station FMG.

Red squares indicate weekend.

0

50

100

150

200

250

300

350

400

Nu

mb

ers

of

win

do

ws

sele

cte

d

Date

FMG_Day

FMG_Night

46

Figure 34. Comparison of window selection between day- and night-time at station KGH. Red squares indicate weekend.

Figure 35. Comparison of window selection between day- and night-time at station MBX.

Red squares indicate weekend.

0

50

100

150

200

250

3-Oct 4-Oct 5-Oct 6-Oct 7-Oct 8-Oct 9-Oct 10-Oct

Nu

mb

er

of

win

do

ws

sele

cte

d

Date

KGH_Day

KGH_Night

0

50

100

150

200

250

300

350

400

3-Oct 4-Oct 5-Oct 6-Oct 7-Oct 8-Oct 9-Oct 10-Oct

Nu

mb

er

of

win

do

ws

sele

cte

d

Date

MBX_Day

MBX_Night

47

We also tested different parameter sets for window selection: the default parameters

from Geopsy, Project SESAME, Set-C, Set-B, and Set-A are shown in Table 2, all with a

100 seconds window length. We picked two days of waveform data for our three initial test

stations and applied each parameter set to the same dates for comparison. As shown in

Figure 36 to Figure 38, Set-C and the Geopsy parameter set led to a higher number of

windows selected and Set-C has the highest number. Therefore, we choose parameter Set-

C: STA: 1, LTA: 15, Min STA/LAT: 0.2, Max STA/LTA: 2.5, as the main parameter set

for our noise window selection. On a side note, Appendix C shows that the different sets

of parameters did not have a significant influence on the standard deviation of either peak

frequency or peak amplitude.

Table 2

Different Parameter Sets Tested For Waveform Selection.

STA LTA MinSTA/LTA MaxSTA/LTA

Geopsy 1 30 0.2 2.5

Sesame 1 25 0.5 2

C 1 15 0.2 2.5

B 1 30 0.3 2

A 1 20 0.5 2.2

48

Figure 36. Comparison of windows selected for different parameter sets for station FMG.

Figure 37. Comparison of windows selected for different parameter sets for

station KGH.

0

50

100

150

200

250

300

350

400

Geopsy Sesame C B A

Nu

mb

er

of

Win

do

ws

Parameter Sets

10-Nov

22-Nov

0

50

100

150

200

250

300

350

400

Geopsy Sesame C B A

Nu

mb

er o

f Win

do

ws

Parameter Sets

19-Oct

18-Oct

49

Figure 38. Comparison of windows selected for different parameter sets for station MBX.

0

50

100

150

200

250

300

350

400

Geopsy Sesame C B A

Nu

mb

er

of

Win

do

ws

Parameter Sets

10-Nov

28-Oct

50

CHAPTER FIVE

RESULTS AND INTERPRETATION

Data Analysis

We collected broadband waveform data from 46 sites located across the Cal Poly

Pomona campus with the sites spaced about 50 to 150 meters apart as shown in Figure 39.

This figure also shows the 34 graphs that were determined to be reliable H/V curves using

the SESAME guidelines. Larger versions of all H/V graphs from this figure are shown in

Appendix D and the associated list of criteria for a clear H/V peak are shown in Appendix

E. Based on these graphs, we generated a peak amplitude map (Figure 40) and a peak

frequency map (Figure 41) overlaid on the geological map from Tan (1997). We also

generated a k-factor map (Figure 42) based on calculations of this factor at each site from

the peak amplitude and frequency values, overlaid on the seismic hazard map from Davis

(1999). We will discuss the peak amplitude and peak frequency results in more detail later

in this chapter.

From Figure 42, it is clear that the seismic hazard map considers the entire campus

as having a high risk of earthquake induced liquefaction. From a comparison with the

geological map, it is obvious that this hazard map is mostly based on the geological units

and not on a detailed analysis of the area. Most of the k-factors that we determined are less

than 20, which indicates a low susceptibility to liquefaction. Only 3 sites have a k-factor

higher than 20 and 2 of these sites are located on bedrock. Therefore, the k-factor map

shows no correlation with the seismic hazard map. Mucciarelli (2011) also did a study on

the k-factor using the HVSR method. He concluded that there was no clear correlation

between the k-factor and the occurrence of liquefaction in the 2011 Christchurch

earthquake.

51

Based on a comparison of the general characteristics of the measured H/V curves

that are considered reliable based on the criteria from SESAME, we divided them into 5

color groups: Green, Yellow, Blue, Red, and Black. H/V graphs in Green indicate a clear

one peak case with an f0 of about 0.9 Hz and a value of A0 of about 4. Yellow indicates a

one peak case with f0 of 0.6 Hz and A0 about 3. Red indicates a reliable H/V curve with no

clear peak. Blue indicates a reliable curve with multiple unclear low frequency low

amplitude peaks. The other cases (2 in total) are grouped in Black. We picked one H/V

graph from each color group as a representative example. For each of these selected graphs

we describe the criteria (Figure 28) as a reference to determine the reliability and the clarity.

52

Fig

ure

39

. G

oogl

e E

arth

map

of

Cal

Poly

Pom

ona

cam

pus

with

all

relia

ble

H/V

cur

ves.

Bla

ck d

ots

ind

icat

e th

e si

tes

for

whi

ch t

he

H/V

cur

ves

that

wer

e det

erm

ined

to b

e un

relia

ble

. G

raphs

with

a g

reen

out

line

indic

ate

a cl

ear

H/V

pea

k c

ase

with

f0 a

bo

ut 0

.9 H

z

and A

0 a

bout

4.

A y

ello

w o

utlin

e in

dic

ates

a o

ne p

eak c

ase

with

f0 o

f 0.6

Hz

and A

0 a

bout

3.

A r

ed o

utlin

e in

dic

ates

a r

elia

ble

H/V

cu

rve

with

no c

lear

pea

k.

Gra

phs

with

a b

lue

out

line

indic

ate

curv

es w

ith m

ultip

le l

ow

fre

que

ncy

and l

ow

am

plit

ude

pea

ks.

All

oth

er

case

s ar

e sh

ow

n w

ith a

bla

ck o

utlin

e. G

reen

pin

s re

pre

sent

site

s fo

r w

hich

3 m

ont

hs o

f dat

a w

as c

olle

cted

. B

lue

pin

s re

pre

sen

t th

e lo

catio

ns

of

ReM

i ex

per

imen

ts.

53

Figure 40. Peak amplitude for the Cal Poly Pomona campus overlaid on geological map. Circles show site locations for which reliable curves were determined, with color showing

peak amplitude. Geological units as indicated in Figure 9.

Figure 41. Peak frequency for the Cal Poly Pomona campus overlaid on geological map. Triangles show site locations for which reliable curves were determined, with color showing peak frequency. Grey triangles indicate sites with peaks that were determined to

not be clear. Geological units as indicated in Figure 9.

54

Figure 42. K-factors for the Cal Poly Pomona campus overlaid on seismic hazard map (Figure 10). Red symbols indicate k-factors larger than 20. Yellow symbols indicate k-

factors between 15 to 20. Green symbols indicate k-factors less than 15.

55

Site Characteristics Classification

Green.

Figure 43. Selected windows for Site-44’s seismogram.

Figure 44. H/V graph for Site-44. Colors, lines and axes as in Figure 27.

56

Figure 45. Settings for H/V calculation for Site-44.

Site-44 f0 = 0.910 ± 0.084 Hz A0 = 4.486 ± 1.206

Criteria for a reliable H/V curve:

i) f0 > 10 / Iw

0.910 > 10 / 100

0.910 > 0.10

True

57

ii) nc (f0) > 200

Iw * nw * f0 > 200

100 * 16 * 0.910 > 200

1456 > 200

True

iii) σA (f) < 2 for 0.5f0 < f < 2f0 if f0 > 0.5 Hz

0.084 < 2 for 0.455 < f < 1.820

True

Therefore, this is a reliable H/V curve

Criteria for a clear H/V peak:

i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [0.910 / 4, 0.910] AH/V(f-) < 4.486 / 2

f- [0.228, 0.910] AH/V(f-) < 2.243

True

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [0.910, 4*0.910] AH/V(f+) < 4.486 / 2

f+ [0.910, 3.640] AH/V(f+) < 2.243

True

iii) A0 > 2

4.486 > 2

True

58

iv) Fpeak [AH/V (f) ± σA(f)] = f0 ± 5%

[0.894, 0.901] = [0.865, 0.956]

True

v) σf < ε(f0)

0.084 < ε(0.910)

0.084 < 0.15 * f0

0.084 < 0.15 * 0.910

0.084 < 0.137

True

vi) σA(f0) < θ (f0)

1.206 < θ (0.910)

1.206 < 2

True

This H/V peak fulfilled 6 out of 6 criteria and is therefore considered to be a clear

peak. It has a peak frequency of 0.910 with standard deviation of 0.084 and a peak

amplitude of 4.486 with standard deviation of 1.206.

59

Yellow.



60


Site-30 f0 = 0.763 ± 0.145 Hz A0 = 3.356 ± 1.154


i) f0 > 10 / Iw

0.763 > 10 / 100

0.763 > 0.10

True

61

ii) nc (f0) > 200

Iw * nw * f0 > 200

100 * 26 * 0.763 > 200

1984 > 200

True


1.154 < 2 for 0.382 < f < 1.526

True

This is a reliable H/V curve.


i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [0.763 / 4, 0.763] AH/V(f-) < 3.356 / 2

f- [0.191, 0.763] AH/V(f-) < 1.678

True

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [0.763, 4*0.763] AH/V(f+) < 3.356 / 2

f+ [0.763, 3.052] AH/V(f+) < 1.678

True

iii) A0 > 2

3.356 > 2

True

62


[0.725, 0.767] = [0.725, 0.801]

True

v) σf < ε(f0)

0.145 < ε(0.763)

0.145 < 0.15 * f0

0.145 < 0.15 * 0.763

0.145 < 0.114

False

vi) σA(f0) < θ (f0)

1.154 < θ (0.763)

1.154 < 2.0

True

This is considered a reliable H/V curve and a clear H/V peak as it fulfilled 5 out of

6 criteria. It has a peak frequency of 0.763 Hz with standard deviation of 0.145 and a peak

amplitude of 3.356 with standard deviation of 1.154.

63

Blue.



64


Site-33 f0 = 0.169 ± 0.045 Hz A0 = 2.023 ± 1.425


i) f0 > 10 / Iw

0.169 > 10 / 100

0.169 > 0.10

True

65

ii) nc (f0) > 200

Iw * nw * f0 > 200

100 * 96 * 0.169 > 200

1622 > 200

True

iii) σA (f) < 3 for 0.5f0 < f < 2f0 if f0 < 0.5 Hz

1.425 < 3 for 0.085 < f < 0.338

True

This is a reliable H/V curve.

First peak of the H/V curve:


i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [0.169 / 4, 0.169] AH/V(f-) < 2.023 / 2

f- [0.042, 0.169] AH/V(f-) < 1.012

False

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [0.169, 4*0.169] AH/V(f+) < 2.023 / 2

f+ [0.169, 0.676] AH/V(f+) < 1.012

False

iii) A0 > 2

2.023 > 2

True

66


[0.183, 0.179] = [0.161, 0.177]

False

v) σf < ε(f0)

0.045 < ε(0.169)

0.045 < 0.25 * f0

0.045 < 0.25 * 0.169

0.045 < 0.042

False

vi) σA(f0) < θ (f0)

1.425 < θ (0.169)

1.425 < 3.0

True

2 out of 6 criteria fulfilled. This peak is not a clear peak.

Second peak of the H/V curve:

f1 = 0.487 ± 0.072 Hz A1 = 2.153 ± 1.240


i) f0 > 10 / Iw

0.487 > 10 / 100

0.487 > 0.10

True

67

ii) nc (f0) > 200

Iw * nw * f0 > 200

100 * 96 * 0.487 > 200

4675 > 200

True


1.240< 3 for 0.244 < f < 0.974

True

A reliable H/V curve


i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [0.487 / 4, 0.487] AH/V(f-) < 2.153 / 2

f- [0.122, 0.487] AH/V(f-) < 1.077

False

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [0.487, 4*0.487] AH/V(f+) < 2.153 / 2

f+ [0.487, 1.948] AH/V(f+) < 1.077

False

iii) A0 > 2

2.153 > 2

True

68


[0.497, 0.528] = [0.463, 0.511]

False

v) σf < ε(f0)

0.072 < ε(0.487)

0.072 < 0.20 * f0

0.072 < 0.20 * 0.487

0.072 < 0.097

True

vi) σA(f0) < θ (f0)

1.240 < θ (0.487)

1.240 < 2.5

True

3 out of 6 fulfilled and it is not considered to be a clear peak.

Although both of the peaks are considered not clear, the H/V curve is reliable and

the surrounding H/V graphs show similar characteristics.

69

Black, Site-34.



70


Site-34 f0 = 0.370 ± 0.074 Hz A0 = 3.570 ± 1.519


i) f0 > 10 / Iw

0.370 > 10 / 100

0.370 > 0.10

True

71

ii) nc (f0) > 200

Iw * nw * f0 > 200

100 * 11 * 0.370 > 200

407 > 200

True


1.519 < 3 for 0.185 < f < 0.740

True

This is considered a reliable H/V curve.


i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [0.370 / 4, 0.370] AH/V(f-) < 3.570 / 2

f- [0.093, 0.370] AH/V(f-) < 1.785

True

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [0.370, 4*0.370] AH/V(f+) < 3.570 / 2

f+ [0.370, 1.480] AH/V(f+) < 1.785

True

iii) A0 > 2

3.570 > 2

True

72


[0.342, 0.359] = [0.352, 0.389]

False

v) σf < ε(f0)

0.074 < ε(0.370)

0.074 < 0.20 * f0

0.074 < 0.20 * 0.370

0.074 = 0.074

True / False

vi) σA(f0) < θ (f0)

1.519 < θ (0.370)

1.425 < 2.5

True

This peak is on the threshold of the criteria. As it is a one peak case with similar

amplitude as the H/V curves from the surrounding sites, we consider this a strong peak.

However, it has a peak frequency of 0.37 Hz, which is different from the Green and Yellow

groups, which have a peak frequency of 0.6 Hz with similar amplitude. Therefore we

cannot classify this site into either of these groups.

73

Black, Site-13.



74


Site-13 f0 = 1.433 ± 0.130 Hz A0 = 2.745 ± 1.245


vii) f0 > 10 / Iw

1.433 > 10 / 50

1.433 > 0.2

True

75

viii) nc (f0) > 200

Iw * nw * f0 > 200

50 * 15 * 1.433 > 200

1074 > 200

True

ix) σA (f) < 2 for 0.5f0 < f < 2f0 if f0 > 0.5 Hz

0.130 < 2 for 0.717 < f < 2.866

True



x) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [1.433 / 4, 1.433] AH/V(f-) < 2.745 / 2

f- [0.358, 1.433] AH/V(f-) < 1.373

True

xi) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [1.433, 4*1.433] AH/V(f+) < 2.745 / 2

f+ [1.433, 5.732] AH/V(f+) < 1.373

True

xii) A0 > 2

2.745 > 2

True

76

xiii) Fpeak [AH/V (f) ± σA(f)] = f0 ± 5%

[1.442, 1.456] = [1.361, 1.505]

True

xiv) σf < ε(f0)

0.130 < ε(1.433)

0.130 < 0.10 * f0

0.130 < 0.10 * 1.433

0.130 = 0.143

True

xv) σA(f0) < θ (f0)

1.519 < θ (1.433)

1.245 < 1.78

True

This H/V curve is reliable and the peak is clear, since 6 out of 6 criteria are met. It

is grouped in Black because it has a peak frequency of 1.4 Hz, which is the highest

frequency of all the data that we analyzed for campus. The data for this site was recorded

while there was a garbage truck operating within 5 meters. In order to determine if this

unusual signal may have been produced by mechanical noise from the truck, we use a

function in Geopsy called H/V rotate to determine the direction of the wave energy. If the

peak is in fact due to this mechanical noise, the origin of its energy should indicate the

direction to this truck.

77

Figure 58. H/V Rotate results for Site-13.

From Figure 58, the main amplitude for the signal of 1.5 Hz, is coming from 0

degrees to 30 degrees and from 100 degrees to 180 degrees, which is in Southeast and

Northwest direction. It is different than the location of the truck that is located to the

Southwest to the seismometer. Therefore, the origin of this unusual peak is still unclear,

and further analysis and data collection are needed.

78

Red.



79


Site-2 f0 = 1.496 ± 0.174 Hz A0 = 1.998 ± 1.222


i) f0 > 10 / Iw

1.496 > 10 / 50

1.496 > 0.2

True

80

ii) nc (f0) > 200

Iw * nw * f0 > 200

50 * 36 * 1.496 > 200

2693 > 200

True


0.174 < 2 for 0.748 < f < 2.992

True



i) f- [ f0 / 4, f0 ] AH/V(f-) < A0 / 2

f- [1.496 / 4, 1.496] AH/V(f-) < 1.998 / 2

f- [0.374, 1.496] AH/V(f-) < 0.999

False

ii) f+ [ f0, 4f0 ] AH/V(f+) < A0 / 2

f+ [1.496, 4*1.496] AH/V(f+) < 1.998 / 2

f+ [1.496, 5.984] AH/V(f+) < 0.999

False

iii) A0 > 2

1.998 > 2

False

81


[1.470, 1.392] = [1.421, 1.571]

False

v) σf < ε(f0)

0.174 < ε(1.496)

0.174 < 0.10 * f0

0.174 < 0.10 * 1.496

0.174 < 0.150

False

vi) σA(f0) < θ (f0)

1.222 < θ (1.496)

1.222 < 1.78

True

This is a considered a reliable H/V curve and not a clear peak.

Comparison with Surface Geology

We divided the sites based on their surface geologic unit and their color group.

Figure 62 shows the distribution of all the spectral ratio parameters on Cal Poly Pomona

campus. The site characteristics mainly fall into Green and Blue categories.

82

Figure 62. Total site distribution of groups for the entire campus.

Geologic unit Qyfa shows a good correlation with the Green group (Figure 63),

which was defined as having a single peak frequency of about 0.9 Hz with a peak amplitude

over 4. With an estimated shear wave velocity of 314 meters per second (we will explain

this choice in the following section) and using Equation 6, we have an estimated minimum

depth to a significant impedance contrast of 80 meters, which likely represents an interface

between the soft alluvial layer and the underlying hard bedrock.

0

2

4

6

8

10

12

14

Green Yellow Blue Red Black

# o

f S

ite

Group

83

Figure 63. Site classification for geologic unit sand alluvial deposits (Qyfa).

Figure 64. Site classification for geologic unit silt alluvial deposits (Qyfs).

A few of the sites located on the geologic unit Qyfs were classified as Group Green

and Red, and one site as Blue (Figure 64). There is therefore no strong correlation between

sites located on this geologic unit with one certain type of spectral parameters.

0

1

2

3

4

5

6

7

8


# o

f S

ite

Group

0

1

2

3

4

5

6

7

8


# o

f S

ite

Group

84

Figure 65. Site classification for geologic unit clay alluvial deposits (Qyfc).

More sites were located on geologic unit Qyfc than other geologic units, because it

is where most of the campus buildings are located. A fair number of sites were classified

as group Green and Yellow (Figure 65). Group Green was defined by a large single peak

with peak frequency of about 0.9 Hz and a peak amplitude of about 4. Group Yellow

indicates a large single peak with peak frequency of 0.7 Hz and a peak amplitude of about

3. Both geologic units, Qyfa and Qyfc, are very similar, as they are considered alluvial

deposits. The main difference is the particle size which is smaller for clay than sand.

Therefore, these measurements suggest that at about 70 meters depth, there is an interface,

separating the deeper bedrock from the top alluvial layer. However, the depth to this

interface has some lateral variability, based on the variation in the measurement of peak

frequency between different sites.

0

1

2

3

4

5

6

7

8


# o

f S

ite

Group

85

Figure 66. Site classification for geologic unit La Vida Member (Tpl).

Geologic unit Tpl shows no correlation with any defined Group, as the

classification of sites on this unit is spread over the different colored groups (Figure 66).

Figure 67. Site classification for geologic unit Topanga Formation (Ttc).

Sites on geologic unit Ttc (Figure 67) are perfectly correlated with a classification

as Group Blue. This bedrock has a particular type of H/V curve, which is low frequency

0

1

2

3

4

5

6

7

8


# o

f S

ite

Group

0

1

2

3

4

5

6

7

8


# o

f S

ite

Group

86

low amplitude unclear peak, which is expected for a hillside area that does not have a soft

layer at the surface.

Based on this analysis, we conclude that the type of surficial geologic unit that

underlies our sites has some correlation with the peak frequency and amplitude that we

measured at these sites. Geologic units Qyfa and Ttc show a near perfect correlation. For

geologic unit Qyfa our results could be interpreted as indicating a subsurface model of an

alluvial layer above bedrock, with the interface separating the two at a consistent depth.

For geologic unit Ttc our results may be interpreted as indicating a relatively homogeneous

bedrock subsurface.

Our results therefore indicate that the surface geological unit is an imperfect proxy

for seismic site response parameters, and more detailed geophysical investigations are

required on a small scale to provide more detailed information. Although the presence of

alluvial surface units suggests that a site may be susceptible to resonance, the specific

frequency and amplification of this resonance can only be determined by a targeted

geophysical study such as the spectral ratio approach used in this study.

Lateral Variations in Peak Amplitude and Peak Frequency

We generated a graph of peak amplitude versus peak frequency for all the reliable

H/V curves, shown in Figure 68. This figure indicates there is a positive correlation

between amplitude and peak frequency on Cal Poly Pomona campus. We also show these

measurements with colors based on their group colors in Figure 69. The Green group has

a near linear relationship between amplitude and peak frequency. Group Yellow has a very

specific peak frequency of about 0.6 Hz and amplitude of about 3. The Blue group has low

87

amplitude with a wide range of peak frequency. The two sites of the Black colored group

do not show a correlation. We remove Groups Black and Blue, as they do not indicate a

correlation and plot the linear fit line for the remaining measurements in Figure 70. The

figure shows an apparent near linear relationship: as the peak frequency increase, the peak

amplitude increases as well. This result is counterintuitive, since commonly a thicker layer

of alluvium is associated with a higher amplification, but lower peak frequency. To

understand the direct linear relationship of peak frequency and peak amplitude, we analyze

them separately.

Figure 68. Peak amplitude versus peak frequency graph for measurements from all

reliable curves.

y = 1.8346x + 1.8876R² = 0.333

0

1

2

3

4

5

6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Pe

ak A

mp

litu

de

Peak Frequency (Hz)

88

Figure 69. Peak amplitude versus peak frequency for different colored groups.

Figure 70. Peak amplitude versus peak frequency graph with only Group Yellow and

Green.

0

1

2

3

4

5

6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Pe

ak A

mp

litu

de

Peak Frequency (Hz)

Blue

Black

Green

Yellow

y = 2.7266x + 1.3594R² = 0.7218

0

1

2

3

4

5

6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Pe

ak A

mp

litu

de

Peak Frequency (Hz)

89

Interpretation of Peak Amplitude. For a parameter-specific analysis, we plotted

the peak amplitude and frequency for each site on maps of campus. Figure 71 shows a

general decrease in the amplitude of the spectral peak from East to West. The East side of

the campus is a mostly flat surface covered with alluvial and valley deposits. The West

side of the campus has higher elevation and the geological surface unit correspondingly

changes to bedrock. The peak amplitude across campus decreases from almost 5, high

amplitude, in the alluvial plane to about 2, low amplitude, in the hills. We can therefore

correlate the amplitude decrease with a transition to stronger surface material, as may be

expected. For the 1985 “Mexico City” earthquake, Celebi et al. (1987) determined a

maximum spectral ratio amplitude of 7-10 in the lake zone, therefore a peak spectral ratio

amplitude of 5, as we measured for several sites on the South-east side of campus,

indicates a site with a high seismic amplification. Since the amplitude of the peak in the

spectral ratio curve may be considered to be a lower bound of the true amplification, this

area of campus is thus likely to experience particularly high ground motions in the next

earthquake.

90

Figure 71. Peak amplitude of the spectra ratio curves for all campus sites, overlain on a

topographic map (USGS, 2012).

Interpretation of Peak Frequency. For further analysis of the measurements of

peak frequency, we chose sites that are located on the alluvial deposits with relatively

similar spectral characteristics. In this region, the peak frequency decreases from Southeast

to Northwest. From Figures 72 and 73, it can be seen that the surface topography dip has

little variation (approximately 0.6 degrees) in the area of the alluvial deposits, which will

therefore be considered to be a flat surface.

From Equation 6, a decreasing peak frequency could indicate an increasing depth

to a subsurface impedance contrast or a decreasing shear wave velocity. We will discuss

these two options in the next sections.

91

Figure 72. Topographic profile across the Cal Poly Pomona campus on Google Earth.

Figure 73. Geological map overlaid on Google Earth map showing topographic profile

along the red line.

92

Increasing interface depth. Measurements of varying peak frequencies on a flat

surface could indicate a dipping subsurface interface between the alluvial deposits and the

underlying bedrock layer. To estimate the dip of this possible interface, we selected stations

that are located in this region and show the depth to the estimated impedance contrast for

sites in Figure 74.

Figure 74. Estimated depth to interface on topographic map (USGS, 2012). Hexagonal

symbols indicate sites used for dip analysis. Numbers on the upper right corner indicate the estimated depth in meters calculated for a shear wave velocity of 314 m/s (CH2MHILL, 2009). Solid blue lines indicate the estimated dipping direction. Green line represents the

ReMi experiment line. Dotted blue line indicates the river stream.

As there is limited subsurface data available for Cal Poly Pomona campus,

especially for depths greater than 10 meters, we had to make a few assumptions, based on

our topographic profiles and spectral parameter measurements. We first assume this region

93

of the campus has a completely flat surface (Figures 72 and 73 indicate this is a valid

assumption) and that the structure in this area consists of a homogeneous alluvial layer

over a homogeneous bedrock layer. Then, we assume the dip direction is parallel to the

blue lines as indicated on Figure 72 with a shallower interface on the Southeast and a deeper

interface on Northwest. This dip direction is a rough estimate based on our visual

inspection of Figure 74, and a more accurate estimate could be obtained by fitting a plane

to our calculated depth measurements (see the FUTURE WORK section later in this

thesis). We use Equation 6 to give us the depth to the interface, so we can calculate the

relative depth differences between the stations. To be able to use this equation, we also

have to assume a reasonable shear wave velocity to use as input. Oliver (2010) did a pilot

study close to Station FMG (shown with a green line in Figure 74) using Refraction Micro-

Tremor (ReMi) and has an estimated Vs30 of 276 meters per second. Table 3 shows a

summary of shear wave velocity studies done by CH2MHILL (2009). As shown in Table

3, there are 4 zones in this area and only Zone 2 and Zone 3 include the Puente Formation

and Topanga Formation. To address the uncertainty, we used 1029 ft/s (314 m/s) as a lower

average shear wave velocity and 1647 ft/s (502 m/s) (highlighted in red in Table 3) as a

high average shear wave velocity for alluvium in Equation 6 to see how much the dip angle

varies depending on our choice of velocity. Figure 75 and Figure 76 show the depth to the

subsurface impedance contrast calculated from the peak frequencies and the two different

values of shear wave velocity. We used Google Earth to measure the distance between

stations and then calculate the interface depth difference along this distance using Equation

6. Finally, we calculate the dip angle using the arc tangent of the slope from the linear fit.

94

Table 3

Reference Shear Wave Velocity Around San Gabriel Valley

(CH2MHILL, 2009).

Figure 75. Estimated dip of interface using 314 m/s as shear wave velocity. Dip is

estimated to be 3.5 degrees.

y = 0.0619x + 63.579R² = 0.843

0

20

40

60

80

100

120

140

0 200 400 600 800 1000

Esti

mat

ed D

epth

(m

)

Surface Distance (m)

Line1

Line2

line3

Linear (linefit)

95

Figure 76. Estimated dip of interface using 502 m/s as shear wave velocity. Dip is estimated to be 5.7 degrees.

Using 314 meters per second for the shear wave velocity results in a dip angle of

less than 4 degrees and using 502 meters per second of shear wave velocity results in a dip

angle of less than 6 degrees. These results indicate that the specific choice of the shear

wave velocity in the alluvial layer doesn’t have a significant impact on the dip angle.

Our analysis suggest that the variation of peak frequencies in the Southeast part of

the campus may be explained by the existence of a very shallowly dipping interface,

dipping towards the Northwest, between the alluvial deposits and the bedrock below. The

direction of this dip may be explained by deformation due to the San Jose Fault to the

Northwest as shown in Figure 77.

y = 0.099x + 101.67R² = 0.8456

0

50

100

150

200

250

0 200 400 600 800 1000

Esti

mat

ed D

epth

(m

)

Surface Distance (m)

Line1

Line2

Line3

Linear (Linefit)

96

Figure 77. A dipping structure could be caused by deformation due to the San Jose thrust fault on campus (King, 1988).

Decreasing shear wave velocity. From Figure 41, the peak frequency decreases by

about a factor of 2 on the alluvium. This difference could be related to a change of the shear

wave velocity of the material above the subsurface impedance contrast. However, it is

unlikely that a factor of 2 difference in shear wave velocity could be produced by different

types of alluvial units. Therefore, we consider the presence of a dipping interface a more

plausible explanation of the decrease in peak frequency.

Estimated Site Response at CLA Building

From all buildings on Cal Poly Pomona campus, the CLA building (Figure 78) is

listed in Priority List 1 in the CSU Seismic Report Priority Listings (2013), which means

it needs urgent attention for seismic upgrade. The CLA building, outlined in black in Figure

79, is located on a clay alluvial deposit. There are 3 stations that surround the CLA building

(Figure 80) and all have a measurement of a peak frequency of about 0.6 Hz and peak

amplitude about of 3 (Figure 81). The CLA building is about 30 meters tall on the West

wing, which is about 10 stories high. Comparing these numbers with

Table 1, the CLA building would have an estimated natural period of 1.0 second, which is

about 1 Hz. This number is close to the peak frequency we measured for the sites

surrounding the building. Therefore, if significant ground shaking were to occur due to an

97

earthquake, the resonance of the CLA building may be similar to that of the soil column

below the building and therefore the building could experience increased shaking

amplitude due to soil-structure resonance.

Figure 78. Picture of the CLA building.

Figure 79. Location of the CLA building (dark outline) on fault map from

Geocon (2001).

98

Figure 80. Stations around the CLA building. Yellow pins

indicate the location of the sites and red pin indicates the example used (Figure 81).

Figure 81. H/V curve of Site-50.

99

The proposed location of the replacement building (Figure 82) is outside of the

Alquist-Priolo Zone. The closest measured H/V curve (Figure 84) to this proposed location

has a peak frequency of 0.9 Hz and peak amplitude of 4. If the replacement building is as

high as the CLA building, similar soil-structure resonance may occur. Since the minimum

site amplification in this location is higher than at the current CLA site, the new building

may experience increased shaking.

Figure 82. Location of the replacement building with yellow dot indicating the closest seismometer site (Cal Poly Pomona, 2013).

100

Figure 83. H/V curve for Site-33.

Future Work

For future work, longer installations at sites that were identified as unreliable H/V

curves would likely produce better observations and fill in some of the gaps in the coverage.

A denser distribution of stations would allow for higher resolution site response maps. A

more accurate estimate of the dip of the subsurface interface could be obtained by fitting a

plane to the calculated depths. The resonance frequency of structures on campus may be

measured directly by installing seismometers inside those structures and then compared to

the peak frequencies for the sites that we obtained. We would propose to perform additional

ReMi experiments on campus to determine more shallow subsurface velocity profiles. A

refraction experiment may be able to directly confirm the existence of the subsurface

impedance contrast. Deeper boreholes on our sites would allow us to compare direct

measurements of soils and rocks with our measured H/V curves.

101

CHAPTER SIX

CONCLUSIONS

We developed site response parameter maps of the Cal Poly Pomona campus

through application of the Horizontal-to-Vertical Spectral Ratio (HVSR) technique.

We installed broadband seismometers throughout the Cal Poly Pomona campus,

with a total number of 46 sites, 34 of which produced reliable H/V curves. Our

measurements show significant variation in site response parameters within distances of

only 40 meters. Based on a comparison with the geological map from Tan (1997), our

results show some correlation with surface geologic units.

The spectral characteristics of the H/V curves show a linear relationship between

peak amplitude and peak frequency. As the peak frequency increases, the peak amplitude

increases. Amplification factors are generally higher on the alluvial deposits, as expected,

with a peak frequency of about 1 Hz and a peak amplitude of up to 5, which may be

considered a relatively high value. The hilly North side of the campus has a much lower

peak amplitude of 2.

The decrease in the peak frequency as measured on the alluvium from Southeast to

Northwest may be explained by the existence of a very shallowly dipping interface at about

100 m depth, dipping towards the Northwest, between the alluvial deposits and the bedrock

below. The direction of this dip may be explained by deformation due to the San Jose Fault.

The Cal Poly Pomona landmark CLA building may experience enhanced shaking

from earthquakes, since the peak frequency measured for sites around this building, about

0.6 Hz, is similar to the resonance frequency that is expected for a building of its height.

102

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108

APPENDIX A

STANDARD DEVIATION AND NUMBER OF WINDOWS SELECTED FOR

DIFFERENT WINDOW LENGTHS

We selected different days of waveform data from station FMG and applied the

H/V analysis for different window lengths on each day. In general, a greater window

length results in lower standard deviations in peak frequency and lower standard

deviations in peak amplitude.

0

0.05

0.1

0.15

0.2

0.25

1113 1114 1115 1116 1117

σof

f0

Dates (MMDD)

σ of f0 for Different Window Lengths

25s

50s

100s

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1113 1114 1115 1116 1117

σof

A0

Dates (MMDD)

σ of A0 for Different Window Lengths

25s

50s

100s

109

APPENDIX B

CHANGES OF STANDARD DEVIATION AND NUMBER OF WINDOWS

SELECTED OVER TIME

We randomly selected 5 stations to compare the standard deviation of peak frequency and the standard deviation of peak amplitude to see the changes in the

measurements with time for a given window length of 100 seconds.

0

5

10

15

20

25

30

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100 120#

of

win

do

w

Frequ

en

cy

(Hz)

Time since start of recording (minutes)

Frequency and Number of Windows Selected

Over Time-Site 7

F0

# of

Windows

Selected

110

0

5

10

15

20

25

30

0

1

2

3

4

5

6

0 20 40 60 80 100 120

# o

f w

indo

w

Am

pli

tude


Amplitude and Number of Windows Selected

Over Time-Site 7

A0

# of

Windows

Selected

0

5

10

15

20

25

30

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100 120 140

# o

f W

indow

Frequ

en

cy

(Hz)



Over Time-Site 9

f0

# of

Windows

Selected

111

0

5

10

15

20

25

30

0

1

2

3

4

5

6

0 20 40 60 80 100 120 140

# o

f W

indow

Am

pli

tude



Over Time-Site 9

A0

# of

Windows

Selected

0

5

10

15

20

25

30

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 50 100

# o

f W

indow

Frequ

en

cy

(Hz)



Over Time-Site 30

f0

# of

Windows

Selected

112

0

5

10

15

20

25

30

0

1

2

3

4

5

6

0 50 100

# o

f W

indow

Am

pli

tude



Over Time-Site 30

A0

# of Windows

Selected"

0

5

10

15

20

25

30

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 50 100 150

# o

f W

indow

Frequ

en

cy

(Hz)



Over Time-Site 36

f0

# of

Windows

Selected

113

0

5

10

15

20

25

30

0

1

2

3

4

5

6

0 20 40 60 80 100 120 140

# o

f W

indow

Am

pli

tude



Over Time-Site 36

A0

# of

Windows

Selected

0

5

10

15

20

25

30

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100

# o

f W

indow

Frequ

en

cy

(Hz)



Over Time-Site 45

f0

# of

Windows

Selected

114

0

5

10

15

20

25

30

0

1

2

3

4

5

6

0 20 40 60 80 100

# o

f w

ind

ow

Am

plit

ud

e


Amplitude and Number of Windows Selected Over Time-Site 45

A0

# of

Windows

Selected

115

APPENDIX C

STANDARD DEVIATION OF PEAK FREQUENCY AND PEAK AMPLITUDE

FOR DIFFERENT PARAMETER SETS USED TO SELECT WINDOWS

We picked stations FMG, KGH, and MBX and compare their standard deviation

of peak frequency and their standard deviation of peak amplitude for different parameter

sets used for the selection of data windows.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

Geopsy Sesame C B A

σo

f f0

Parameter Sets

σ of f0 for Different Parameter Sets

FMG_1

FMG_2

116

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Geopsy Sesame C B A

σof

A0

Parameter Sets

σ of A0 for Different Parameter Sets

FMG_1

FMG_2

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

Geopsy Sesame C B A

σof

f0

Parameter Sets


KGH_1

KGH_2

117

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Geopsy Sesame C B A

σof

A0

Parameter Sets


KGH_1

KGH_2

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

Geopsy Sesame C B A

σof

f0

Parameter Sets


MBX_1

MBX_2

118

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Geopsy Sesame C B A

σof

A0

Parameter Sets


MBX_1

MBX_2

119

APPENDIX D

ALL RELIABLE H/V CURVES

The following figures show all reliable H/V curves, grouped according to spectral

characteristics as described in the main text, with the station number shown under each

graph.

GREEN

4 9

120

10 30

32 39

42 44

121

45 47

48 53

122

Yellow

5 8

14 22

123

38 50

124

Blue

11 12

17 18

125

26 28

31 33

126

36 37

127

Black

13 34

128

Red

2 3

7 19

129

APPENDIX E

RESULTS OF EVALUATION OF SESAME CRITERIA FOR A CLEAR PEAK

FOR ALL RELIABLE H/V CURVES

This table shows the results of the evaluation of the SESAME criteria in Figure 28

(Roman numerals are used for the criterion number) for all reliable H/V curves. Station

numbers are shown in the first column. T indicates True and F indicates False.

Green I II III IV V VI

4 T F T T/F T T

9 T T T T F T

10 T T T F T T

30 T T T T F T

32 T T T T F T

39 T T T T T T

42 T T T T T T

44 T T T T T T

45 F T T F F T

47 T T T T/F F T

48 T T T T F T

53 T T T T T T

Yellow

5 F T T T F T

8 T T T T F T

14 T T T T T T

22 F T T T T T

38 F T T T T T

50 T T T T T T

Blue

11 T F T T T T

12 T F T F T T

17 F F T T T T

18 F F T F T T

26 F F F T T T

28 T T F T T T

31 F T T T T T

33 F F T T T T

36 F F T T T T

37 F T T T/F T T

Black

13 T T T T T T

34 T T T T F T

130

Red

2 F F F F F T

3 F F F F F F

7 T T T T T T

19 F F T F T T

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