In cooperation with Tufts University 

Surface-Wave Site Characterization at 52 StrongMotion Recording Stations Affected by the Parkfield, 

California, M6.0 Earthquake of 28 September 2004 

By Eric M. Thompson, Robert E. Kayen, Brad Carkin, and Hajime Tanaka 

Open-File Report 2010-1168

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. Department of the Interior 

KEN SALAZAR, Secretary 

U.S. Geological Survey 

Marcia McNutt, Director 

U.S. Geological Survey, Reston, Virginia 2010 

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Suggested citation: 

Thompson, Eric M., Kayen, Robert E., Carkin, Brad, and Tanaka, Hajime, 2010, Surface-wave site 

characterization at 52 strong-motion recording stations affected by the Parkfield, California, M6.0 

earthquake of 28 September 2004, U.S. Geological Survey Open-File Report 2010-1168, 117 p.

[http://pubs.usgs.gov/of/2010/1168/]. 

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endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report. 
iii

Contents 

Abstract.............................................................................................................................................................................. 1

Introduction ....................................................................................................................................................................... 1

Study Area ......................................................................................................................................................................... 2

Field Methods.................................................................................................................................................................... 3

Inversion Methods ........................................................................................................................................................... 5

Results................................................................................................................................................................................ 5

Comparison to Invasive Velocity Profiles ................................................................................................................. 7

Discussion ......................................................................................................................................................................... 8

Resources.......................................................................................................................................................................... 9

Acknowledgments............................................................................................................................................................ 9

References Cited ............................................................................................................................................................ 12 

Appendix A ...................................................................................................................................................................... 14 

Figures 

1. Vicinity map of the Parkfield sites with geology (Jennings, 1958). ..................................................................... 2 

2. ‘Velociraptor’ Surface wave shaker trailer testing Parkfield Earthquake sites, Cholame, Calif..................... 4 

3. Comparison of the two different spectral analysis of surface waves interpretations to the surfacesource downhole-receiver (SSDR) VS profiles at sites (a) 814VIN, (b) 815CHO, (c) 840RFU, 

and (c) 841KFU..................................................................................................................................................... 8 

Tables 

1. Geologic units shown in figure 1, modified from Jennings (1958). ...................................................................... 3 

2. Summary information for the 52 Spectral Analysis of Surface-Waves surveys at strong-motion 

stations. ................................................................................................................................................................ 6 

3. Correspondence between SASW IDs and previously published downhole profiles. ...................................... 8 
Surface-Wave Site Characterization at 52 StrongMotion Recording Stations Affected by the Parkfield, 

California, M6.0 Earthquake of 28 September 2004 

By Eric M. Thompson1, Robert E. Kayen2, Brad Carkin2 and Hajime Tanaka1

Abstract 

We present one-dimensional shear-wave velocity (VS) profiles at 52 strong-motion sites that 

recorded the 28 September 2004 Magnitude 6.0 Parkfield, Calif., earthquake. We estimate the VS

profiles with the Spectral Analysis of Surface-Waves (SASW) method. The SASW method is a 

noninvasive method that indirectly estimates the VS at depth from variations in the Rayleigh wave 

phase velocity at the surface. To address the uncertainty associated with these measurements, we 

compare the SASW profiles to surface-source downhole-receiver (SSDR) profiles at four sites. 

Three of the four SSDR sites are in close agreement with the adjacent SASW site, while the SASW 

profile is considerably slower than the SSDR profile at one site. 

Introduction 

The goal of this project is to measure the shear-wave velocity (VS) profile of the nearsurface materials at strong-motion stations that recorded the 28 September 2004 Magnitude (M) 6.0 

Parkfield earthquake. The Parkfield section of the San Andreas Fault is densely instrumented with 

strong-motion stations because moderate magnitude earthquakes have ruptured at regular intervals 

at approximately the same location on the fault (Bakun and Lindh, 1985). Thus, the hope was to 

record numerous ground motions at short epicentral distances, where few records had previously 

been obtained (Shakal and others, 2006). Although the Parkfield earthquake occurred years later 

than expected, the extensive instrumentation eventually provided a spatially dense suite of 

recordings at very small distances from the fault. The large variability of the intensity of the 

shaking at these sites is striking, and is a complex function of finite fault source process, path 

effects, and local site conditions (Harris and Arrowsmith, 2006). 

The VS profiles presented in this report are useful for studies of the local site conditions on 

the ground motions recorded at short epicentral distances in Parkfield. Recordings from the 1983 

M6.5 Coalinga earthquake indicate that the site effects are highly variable at the Parkfield stations 

(Liu and others, 2006). 

We use the Spectral Analysis of Surface Waves (SASW) method to measure the VS profile. 

SASW is an inexpensive and efficient means for noninvasively estimating the subsurface VS. Prior 

to the development of noninvasive surface-wave methods for estimating VS, shear-wave travel 

times were measured inside cased boreholes or penetration tests, which are both relatively costly by 

comparison (see Boore and Thompson (2007) for further discussion of downhole methods). Static 

penetration tests tend not to be very useful as they routinely cannot reach the depths required for 

seismic site response analysis because the soil becomes too stiff to penetrate. 

 

1

 Department of Civil and Environmental Engineering, Tufts University, Medford, MA 

2

 Coastal and Marine Geology, U.S. Geological Survey, Menlo Park, Calif. 
2

Study Area 

The Parkfield study area (fig. 1) is located astride the San Andreas Fault in the Central 

Coast Range of California. At 52 strong-motion stations, we conducted SASW surveys to estimate 

the VS profile. The northwest boundary of our study area is approximately Vineyard Canyon Road 

at 36° north and 120.5° west (VIN sites on figure 1). The southeast corner of our study area is in 

the vicinity of Jack Canyon and Red Hills, south of Cholame, at 35.6° and -120.2° (CHO sites in 

figure 1). Clusters of test sites were centered along the Vineyard Canyon corridor (VIN sites on 

figure 1), the USGS Parkfield Dense Seismograph Array (UPSAR) sites (UPS sites), along the San 

Andreas Fault zone (FZ sites), the Gold Hill corridor (GH sites), Stone Canyon corridor (SC sites), 

and Cholame (CHO sites). 

Figure 1. Vicinity map of the Parkfield sites with geology (Jennings, 1958).

A web-based map can be found at http://gdcmaps.cee.tufts.edu/parkfield/ where the 

data can also be downloaded. The data are also available as part of this report at 

http://pubs.usgs.gov/of/2010/1168/parkfieldSASW.zip
3

Table 1. Geologic units shown in figure 1, modified from Jennings (1958). 

Symbol Description Epoch Period Era

Qal Alluvium

Qf Fan Deposits Recent

Qt Nonmarine terrace deposits PleistoceneRecent

Quaternary

QP Plio-pleistocene nonmarine PliocenePleistocene - - - - - - - - -

Pc Undivided Pliocene nonmarine

Pu Upper Pliocene marine

Pml Middle and/or lower Pliocene 

nonmarine

Pliocene

Mc Undivided Miocene nonmarine

Mu Upper Miocene marine

Mv(r) Miocene volcanic (rhyolite)

Mm Middle Miocene marine

Ml Lower Miocene marine

Miocene

Oc Oligocene nonmarine Oligocene

E Eocene marine

Ev Eocene volcanic Eocene

Tertiary

Cenozoic

K Undivided Cretaceous marine Undivided

Ku Upper Cretaceous marine Upper

Kl Lower Cretaceous marine Lower

KJfv Franciscan volcanic and metavolcanic

Cretaceous

KJf Franciscan Formation 

gr Mesozoic granitic rocks

Upper Jurassic to Upper 

Cretaceous

bi Mesozoic basic intrusive rocks Upper

ub Mesozoic ultrabasic intrusive rocks Jurassic

Mesozoic

ls Pre-Cretaceous metamorphic rocks 

(limestone or dolomite) Pre-Cretaceous

Field Methods 

Active source SASW testing typically profiles the upper 10s of meters of the ground (for 

example, the upper 30 meters (m) that is needed to compute the widely used site parameter VS30, 

defined as 30 m divided by the shear-wave travel time to 30 m depth) by using drop weights or 

harmonic sources. Deeper shear-wave profiles require longer wavelengths that normally cannot be 

collected unless a large drop weight such as massive construction machinery is used to produce an 

ultra-low frequency wave field. For example, Kayen and others (2004) profiled the shear-wave 

structure of both sides of the Denali Fault by using a 49-ton Caterpillar D9N dozer as an active 

source. Drop weights and heavy track-mounted machinery are useful tools for generating surface 

waves where the ground and landowners will support their presence. The two major drawbacks to 

this approach are that (1) these devices tend to be damaging to the ground surface, and (2) many 

sites of scientific importance are not easily accessible with such equipment. 

The SASW method used by the USGS Coastal and Marine Geology Team is a new 

technique that uses a parallel array of mass shakers. This method allows for profiling to depths up 

to several hundred meters without the use of massive drop weights or heavy track-mounted 
4

machinery. In this method, we substitute an array of many ultra-low frequency electro-mechanical 

shakers for what would traditionally be a large Vibroseis truck. Surface waves are generated with 

an array of up to eight APS Dynamics Model 400 shaker and amplifier units, powered by two 

generators and controlled by a spectral analyzer (fig. 2). 

The shakers have a long-stroke capable of cycling as low as 1 Hertz (Hz), well below the 

normal cut-off frequency of a Vibroseis truck at 7 Hz. The output signal from the spectral analyzer 

is split into a parallel circuit and sent to the separate amplifiers. The amplifiers power the shakers to 

produce a coherent phase continuous harmonic-wave that vertically loads the ground. Most of this 

energy result produces Rayleigh surface waves. 

Figure 2. ‘Velociraptor’ Surface wave shaker trailer testing Parkfield Earthquake sites, Cholame, 

Calif. 

For a given frequency, the cross power spectra and phase-angle between the outboard and 

reference seismometers are computed. The SASW procedure steps through a suite of frequencies, 

from which phase computations are made. This method, termed swept-sine surface wave testing, 

sweeps across a range of low frequencies (1-200 Hz) in order to capture the variability of the 

Rayleigh-wave phase velocity. The shaking equipment is mounted inside a large trailer that 

includes cable reels to connect up to four seismometers, a low frequency spectrum analyzer, 4 to 8 

computer-controlled continuous harmonic-wave sources (shakers) and their amplifiers, cables, and 

two 4.5 kilowatt (kW) generators. 

In order to construct an empirical dispersion profile for the site, several different receiver 

spacings are used to capture the high, medium, and low frequency ranges. The wavelengths (λ) are 

computed by relating the seismometer spacing (d) and the phase angle (φ), from the cross-power 

spectra between the seismometers: 
5

. (1) 

The Rayleigh-wave phase velocity, Vr, is computed as the product of the frequency (ƒ) and 

wavelength(λ): 

. (2) 

Inversion Methods 

The VS profiles presented in this paper are computed by using the Fortran routines of 

SWAMI (Lai and Rix, 1998). The dispersive characteristic of Rayleigh-wave propagation is what 

allows us to infer the VS at depth based on measurements at the free surface. The forward problem 

computes the Rayleigh-wave phase velocity (VR) from laterally constant layers of an infinite 

halfspace. The Lai and Rix (1998) code employs the algorithm developed by Hisada (1994) to 

solve the forward problem by using the method of reflection and transmission coefficients. 

The surface-wave inversion problem is an “ill-posed” inverse problem. The term “ill-posed” 

(in relation to inverse problems) is credited to the French mathematician Hadamard who defined 

mathematical problems to be “well-posed” if a solution exists, the solution is unique, and the 

solution is stable (Zhdanov, 2002). According to Hadamard, only “well-posed” problems are 

physically meaningful. Subsequently, methods have been developed for solving ill-posed problems, 

termed regularization methods. 

The Levenberg-Marquardt method, also called damped least squares, is one example of a 

regularization method. These and other techniques, such as artificial neural networks and genetic 

algorithms, are discussed by Santamarina and Fratta (1998). Luke and Calderón-Marcías (2007) use 

the simulated annealing stochastic inversion technique because it is better at searching through the 

parameter space. One cost of these stochastic methods is that they often require many more 

iterations, and so they are much more computationally intensive. 

The parameters of the forward problem can be chosen such that the difference between the 

observation (here, the empirical dispersion curve) and the output of the forward problem are 

minimized. Such a constraint is insufficient for ill-posed problems because many solutions will fit 

the data equally well and some of these solutions will be physically unrealistic. The most common 

approach is to seek a parsimonious solution, such that model simplicity is maximized as the misfit 

to the data is minimized. 

The inversion method that Lai and Rix (1998) apply to this problem was termed “Occam’s 

inversion” by Constable and others (1987). This method attempts to constrain the inversion 

solution space by selecting the smoothest solution from a suite of solutions that all exhibit a 

sufficient goodness-of-fit to the observed data, as indicated by a threshold root mean square (RMS) 

error. 

Results 

We provide two different inversion solutions at each site to emphasize the nonunique nature 

of the solution. We typically vary assumptions about the layer thicknesses and the threshold RMS 

error that determines if the inversion has converged. This process generally yields the two solutions 

where the smoothness or complexity of the profile is significantly different. The decision as to 

whether or not the more complex model is warranted by the fit of the theoretical dispersion curve 

(TDC) to the empirical dispersion curve (EDC) is subjective. 
6

Table 2 summarizes results and provides the SASW site ID, the latitude and longitude of 

the SASW test, the corresponding strong-motion station ID, the latitude and longitude of the target 

strong-motion station, the VS30 and Z1.0 computed from the two different SASW models (Z1.0 is the 

minimum depth where the velocity is greater than 1.0 kilometer per second (km/sec)). It was 

impossible for us to identify the specific UPSAR stations in the field. We collected two profiles in 

the vicinity of the UPSAR array but have not indicated a station ID for these because of the 

uncertainty of the location of the UPSAR stations. 

Table 2. Summary information for the 52 Spectral Analysis of Surface-Waves surveys at strongmotion stations. The geographic coordinates are given for the location of the surveys as well as the 

published location of the stations. VS30 and Z1.0 are given for the two different Spectral Analysis of 

Surface-Waves models (M1 and M2). 

SASW Strongmotion station VS30, m/sec Z1.0, m

ID Lat. Lon. ID Lat. Lon. Description M1 M2 M1 M2

807PAR 35.8985 -120.4329 36138 35.9000 -120.4330 Fault Zone 12 261 272

808PAR 35.8986 -120.4325 36531 35.8980 -120.4310 1-story School Bldg 270 271

809CHO 35.7328 -120.2894 36228 35.7330 -120.2900 Cholame 02WA 174 173

810CHO 35.7430 -120.2753 36452 35.7430 -120.2750 Cholame 01E 233 225

811TUR 35.8779 -120.3599 36529 35.8780 -120.3580 Turkey Flat - No 1(Rock) 907 926

812CHO 35.8180 -120.3792 36415 35.8180 -120.3780 Gold Hill 1W 214 216

813CHO 35.7072 -120.3163 36412 35.7070 -120.3160 Cholame 04AW 283 288

814VIN 35.9220 -120.5348 36176 35.9220 -120.5340 Vineyard Cyn 3W 309 311

815CHO 35.6963 -120.3288 36227 35.6970 -120.3280 Cholame 05W 237 226 100

816CHO 35.7521 -120.2657 36230 35.7520 -120.2620 Cholame 02E 523 510

817EAD 35.8952 -120.4229 EFU 35.8942 -120.4212 Eades 384 388

818PAR 35.9266 -120.4570 FZ16 35.9270 -120.4560 Fault Zone 16 378 384 30 40

819VIN 35.9731 -120.4671 36177 35.9730 -120.4670 Vineyard Cyn 2E 468 465

820CHO 35.8701 -120.4051 36431 35.8710 -120.4040 Fault Zone 07 297 290

821TUR 35.8767 -120.3826 36449 35.8780 -120.3810 Fault Zone 08 309 295 45 68

822PAR 35.9080 -120.4595 36456 35.9080 -120.4580 Fault Zone 14 246 258

823PAR 35.9211 -120.4813 36445 35.9210 -120.4810 Fault Zone 15 310 308 100 90

824VCY 35.9399 -120.4247 DFU 35.9392 -120.4245 Donna Lee 666 657 20 20

825VCN 35.9573 -120.4831 36455 35.9570 -120.4810 Vineyard Cyn 1E 381 373

826FZ 35.8955 -120.3989 36453 35.8960 -120.3980 Fault Zone 11 545 542 60 80

827SAF 35.9741 -120.5521 SAFOD Drill Site 387 387

828VIN 35.8829 -120.5629 36440 35.8850 -120.5650 Vineyard Cyn 5W 320 321

829VIN 35.9033 -120.5513 36446 35.9050 -120.5510 Vineyard Cyn 4W 386 386 90 80

830CHO 35.7671 -120.2488 36450 35.7700 -120.2470 Cholame 03E 396 397

831VIN 35.9336 -120.4974 36448 35.9340 -120.4970 Vineyard Cyn 1W 284 286

832UPS 35.8214 -120.5059 35.8210 -120.5070 UPSAR 358 363

833UPS 35.8248 -120.5011 35.8238 -120.5033 UPSAR 419 417

834FZ 35.8791 -120.4461 36443 35.8790 -120.4450 Fault Zone 09 372 363 130 120

835CHO 35.6842 -120.3418 36451 35.6840 -120.3420 Cholame 06W 252 253

836TUR 35.8824 -120.3510 36520 35.8820 -120.3500 Turkey Flat - No 2 489 467 40 40

837CHO 35.7151 -120.3041 36411 35.7171 -120.3050 Cholame 04W 439 410

838CHO 35.6369 -120.3998 36229 35.6360 -120.4030 Cholame 12W 359 363

839CHO 35.7239 -120.2970 36410 35.7260 -120.2960 Cholame 03W 241 231

840RFU 35.6199 -120.2570 RFU 35.6244 -120.2535 Red Hills 240 239

841KFU 35.7153 -120.2056 KFU 35.7125 -120.2025 Jack Canyon 603 576 20 30

842FFU 35.9108 -120.4873 FFU 35.9111 -120.4855 Froelich 234 227 70

843MFU 35.9564 -120.4959 MFU 35.9576 -120.4956 Middle Mountain 398 417 70 50

844JFU 35.9390 -120.4309 JFU 35.9397 -120.4319 Joaquin Canyon 379 406

845VIN 35.9268 -120.5100 36447 35.9270 -120.5090 Vineyard Cyn 2W 439 442

846UPS 35.8277 -120.5001 35.8276 -120.5002 UPSAR10 342 336
7

847WFU 35.8145 -120.5118 WFU 35.8145 -120.5111 Work Range 447 474

848FZ 35.8586 -120.4214 36454 35.8590 -120.4200 Fault Zone 06 267 284

849FZ 35.8360 -120.3958 36414 35.8360 -120.3950 Fault Zone 04 221 219

850FZ 35.8019 -120.3450 36408 35.8030 -120.3340 Fault Zone 03 206 212

851SC 35.8331 -120.2713 36437 35.8330 -120.2700 Stone Corral 3E 606 565 15 20

852SC 35.8105 -120.2831 36422 35.8100 -120.2820 Stone Corral 2E 566 586

853SC 35.7878 -120.2948 36419 35.7880 -120.2940 Stone Corral 1E 261 261

854GH 35.7958 -120.4120 36420 35.7960 -120.4110 Gold Hill 3W 511 457

855GH 35.8113 -120.3922 36416 35.8120 -120.3910 Gold Hill 2W 290 297

856FZ 35.7581 -120.3075 36407 35.7580 -120.3070 Fault Zone 01 178 180

857GH 35.8695 -120.3346 36439 35.8700 -120.3340 Gold Hill 3E 442 451 30 45

858GH 35.8428 -120.3485 36421 35.8430 -120.3480 Gold Hill 2E 361 346

859GFU 35.8324 -120.3477 GFU 35.8331 -120.3464 Gold Hill 583 558 10 20

Appendix A includes plots of the two model profiles and the EDCs and TDCs for each site. 

These figures also can be found on the interactive map associated with this report. Additionally, 

two SASW velocity models and the observed dispersion data can be downloaded from the map at 

http://gdcmaps.cee.tufts.edu/parkfield/ where the data can also be downloaded. The data are also 

available as part of this report at http://pubs.usgs.gov/of/2010/1168/parkfieldSASW.zip. Appendix 

A also includes the site photos and a vicinity map for each site. Where possible, we have indicated 

the location of the strong-motion station in the site photographs and vicinity maps to assess the 

distance between the SASW survey and the strong-motion station. 

Note that the vertical lines on the EDC curves indicate the degree of scatter in the 

composite dispersion curve (the combination of the dispersion curves from the different receiver 

spacings). These bars indicate sites where the scatter in the composite dispersion curve is large, 

which would indicate that the measurement is less certain. However, care must be taken when 

interpreting these bars as an estimate of the uncertainty of the measurement. Lai and others (2005) 

assumed that the error of a phase velocity measurement is proportional to the phase velocity and we 

follow this assumption in the inversion process when the model error must be estimated to 

determine if the solution has converged. If the vertical bars are interpreted as estimates of the 

uncertainty, then the opposite conclusion is reached in many cases: the error would appear to be 

inversely proportional to phase velocity. This is because there is less redundancy of observations 

(that is overlap of the wavelengths from different receiver spacings) at the longer wavelengths, 

which are associated with larger phase velocities, thus there is generally less scatter in the 

composite dispersion curve higher phase velocities. This should not be interpreted as evidence that 

the longer wavelength measurements are more accurate than the shorter wavelength measurements. 

Comparison to Invasive Velocity Profiles 

Four of the sites where we measured the spectral analysis of surface waves (SASW) shear 

wave velocity,(VS) profiles were previously characterized by the surface- source downholereceiver (SSDR) method: 814VIN, 815CHO, 840RFU, and 841KFU. Additionally, site 836TUR is 

located at the Turkey Flat Valley Center site where many previous velocity investigations have 

been performed (see Kwok and others, 2008 for the comparison of the SASW profile to the 

numerous downhole profiles). The previous SSDR profiles were published in various USGS OFRs 

and compiled by Boore (2003). Table 3 gives the correspondence of the SASW site IDs with the 

USGS OFRs that originally published the downhole profiles. Figure 3 compares the SASW profiles 

with the downhole profiles at these four sites. 
8

Table 3. Correspondence between SASW IDs and previously published downhole profiles. 

SASW ID USGS OFR Hole Code Name

814VIN Gibbs and others (1990) 205 Vineyard Canyon

815CHO Fumal and others (1982) 197 Cockrums Garage

840RFU Gibbs and others (1990) 203 Red Hills

841KFU Gibbs and others (1990) 202 Jack Canyon

Discussion 

Sites 819VIN and 837CHO illustrate the effect of the smoothing parameter. At site 

819CHO, model 1 is nearly monotonically increasing while model 2 has a velocity inversion (that 

is low velocity layer) between 40 to 60 m depth. The inclusion of this low-velocity layer improves 

Figure 3.Figure 3. Comparison of the two different spectral analysis of surface waves interpretations to the 

surface- source downhole-receiver (SSDR) VS profiles at sites (a) 814VIN, (b) 815CHO, (c) 840RFU, 

and (c) 841KFU.

(a) (b)

(c) (d)
9

the fit to the EDC. Here, we feel that the more complex model may be warranted. In contrast, the 

more complex solution at 837CHO is less justified by the EDC and it is our opinion that the 

smoother solution would be appropriate for any analysis. 

Resources 

We have used the SWAMI Fortran routines that are freely available at 

http://geosystems.ce.gatech.edu/soil_dynamics/research/surfacewavesanalysis/ (distributed under 

the terms of the GNU General Public License). 

The EDC data and our interpreted velocity profiles are available from the website for this 

report. One text file for each site contains both types of data along with the site meta information in 

the header. 

Acknowledgments 

This work is supported through a Cooperative Research and Development Agreement 

(CRADA) with the Pacific Gas and Electric Company (PG&E) in cooperation with the U.S. 

Geological Survey (USGS). Andrew Snyder was instrumental in negotiating site access on 

privately held lands and directing us to the location of the strong-motion stations. We thank Dave 

Boore for pointing out that the downhole velocity data area available at some of the same stations 

where we conducted SASW surveys. Eugene Morgan assisted with the field measurements at some 

of sites. 

References Cited 

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Science, v. 229, p. 619–624. 

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logging—Summary and reanalysis of previously published data and analysis of unpublished 

data: U.S. Geological Survey Open-File Report 03-191, 14 p. 

Boore, D. M., and Thompson, E. M., 2007, On using surface-source downhole-receiver logging to 

determine seismic slownesses: Soil Dynamics and Earthquake Engineering, v. 27, p. 971–

985. 

Constable, S.C., Parker, R.L., and Constable, G.G., 1987, Occam's Inversion—A practical 

algorithm for generating smooth models from electromagnetic sounding data: Geophysics, 

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Fumal, T.E., Gibbs, J.F., and Roth, E.F., 1982, In-situ measurements of seismic velocity at 10 

strong motion accelerograph stations in central California: U.S. Geological Survey OpenFile Report 82-407, 76 p. 

Gibbs, J.F., Roth, E.F., Fumal, T.E., Jasek, N.A., and Emslie, M.A., 1990, Seismic velocities from 

borehole measurements at four locations along a fifty-kilometer section of the San Andreas 

fault near Parkfield, California: U.S. Geological Survey Open-File Report 90-248, 35 p. 

Harris, R.A., and Arrowsmith, J. R., 2006, Introduction to the special issue on the 2004 Parkfield 

earthquake and the Parkfield earthquake prediction experiment: Bull. Seism. Soc. Am., v. 

96, p. S1–S10. 

Hisada, Y., 1994, An efficient method for computing Green’s functions for a layered half-space 

with sources and receivers at close depths: Bull. Seism. Soc. Am., v. 84, p. 1,456-1,472. 
10

Jennings, C. W., 1958, Geologic atlas of California, San Luis Obispo sheet: Calif. Div. Mines Geol. 

Geologic Atlas Map GAM 018, scale 1:250,000. 

Kayen, R., Thompson, E., Minasian, D., Moss, R.E.S., Collins, B.D., Sitar, N., Dreger, D., Carver, 

G., 2004, Geotechnical reconnaissance of the November 3, 2002 M7.9 Denali Fault 

earthquake: Earthquake Spectra, v. 20, p. 639-667. 

Kwok, A.O.L., Stewart, J.P., and Hashash, Y.M.A., 2008, Nonlinear ground-response analysis of 

Turkey flat shallow stiff-soil site to strong ground motion: Bull. Seism. Soc. Am., v. 98, p. 

331-343. 

Lai, C.G., and Rix, G. J., 1998, Simultaneous inversion of Rayleigh phase velocity and attenuation 

fornNear-surface site characterization, Report no. GIT-CEE/GEO-98-2: Georgia Institute of 

Technology, School of Civil and Environmental Engineering, Atlanta, Georgia, 258 p. 

Lai, C.G., Foti, S., and Rix, G. J., 2005, Propagation of data uncertainty in surface wave inversion: 

Journal of Environmental and Engineering Geophysics, v. 10, p. 219-228. 

Liu, P., Custodio, S., and Archuleta, R. J., 2006, Kinematic inversion of the 2004 M 6.0 Parkfield 

earthquake including an approximation to site effects: Bull. Seism. Soc. Am., v. 96, p. 

S143–S158. 

Luke, B., and Calderón-Marcías, C., 2007, Inversion of seismic surface wave data to resolve 

complex profiles: J. Geotech. and Geoenv. Eng., v. 133(2), p. 155-165. 

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civil engineering: Amer. Society of Civil Engineers, 327 p. 

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11

Appendix A: 

Site Summaries 
12

A1-2. Summary of site 807PAR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
13
14

A1-4. Summary of site 808PAR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
15
16

A1-6. Summary of site 809CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
17
18

A1-8. Summary of site 810CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
19
20

A1-10. Summary of site 811TUR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
21
22

A1-12. Summary of site 812CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
23
24

A1-14. Summary of site 813CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
25
26

A1-16. Summary of site 814VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
27
28

A1-18. Summary of site 815CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
29
30

A1-20. Summary of site 816CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
31
32

A1-22. Summary of site 817EAD. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
33
34

A1-24. Summary of site 818PAR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
35
36

A1-26. Summary of site 819VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
37
38

A1-28. Summary of site 820CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
39
40

A1-30. Summary of site 821TUR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
41
42

A1-32. Summary of site 822PAR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
43
44

A1-34. Summary of site 823PAR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
45
46

A1-36. Summary of site 824VCY. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
47
48

A1-38. Summary of site 825VCN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
49
50

A1-40. Summary of site 826FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
51
52

A1-42. Summary of site 827SAF. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
53
54

A1-44. Summary of site 828VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
55
56

A1-46. Summary of site 829VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
57
58

A1-48. Summary of site 830CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
59
60

A1-50. Summary of site 831VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
61
62

A1-52. Summary of site 832UPS. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
63
64

A1-54. Summary of site 833UPS. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
65
66

A1-56. Summary of site 834FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
67
68

A1-58. Summary of site 835CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
69
70

A1-60. Summary of site 836TUR. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
71
72

A1-62. Summary of site 837CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
73
74

A1-64. Summary of site 838CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
75
76

A1-66. Summary of site 839CHO. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
77
78

A1-68. Summary of site 840RFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
79
80

A1-70. Summary of site 841KFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
81
82

A1-72. Summary of site 842FFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
83
84

A1-74. Summary of site 843MFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
85
86

A1-76. Summary of site 844JFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
87
88

A1-78. Summary of site 845VIN. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
89
90

A1-80. Summary of site 846UPS. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
91
92

A1-82. Summary of site 847WFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
93
94

A1-41. Summary of site 848FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
95
96

A1-86. Summary of site 849FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
97
98

A1-88. Summary of site 850FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
99
100

A1-90. Summary of site 851SC. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
101

 
102
103

A1-92. Summary of site 852SC. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
104

 
105

A1-94. Summary of site 853SC. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
106
107

A1-96. Summary of site 854GH. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
108

 
109

A1-98. Summary of site 855GH. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
110
111

A1-100. Summary of site 856FZ. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
112
113

A1-102. Summary of site 857GH. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
114
115

A1-104. Summary of site 858GH. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves. 
116
117

A1-106. Summary of site 859GFU. Left panel: Vs profiles; Right panel: empirical and model 

dispersion curves.