estimation of response spectra and peak … · spectra as a function of earthquake magnitude, the...
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ESTIMATION OF RESPONSE SPECTRA AND PEAK ACCELERATIONS FROM
WESTERN NORTH AMERICAN EARTHQUAKES: AN INTERIM REPORT
By
David M. Boore, William B. Joyner, and Thomas E. Fumal
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
Open-File Report 93-509
This report is preliminary and has
not been reviewed for conformity with
U.S. Geological Survey editorial standards
or with the North American Stratigraphic Code.
Any use of trade, firm, or product names is
for descriptive purposes and does not imply
endorsement by the U.S. Government.
ABSTRACT
We have derived equations for predicting the larger horizontal and the random hori
zontal component of peak acceleration and of 2-, 5-, 10-, and 20- percent-damped pseudo-
velocity response spectra for 46 periods ranging from 0.1 to 2.0 sec. The equations were
obtained by fitting a functional form to empirical data using a two-stage regression method.
271 two-component recordings from 20 earthquakes were used to develop the equations for
peak acceleration, and 112 two-component recordings from 14 earthquakes were used for
the response spectral equations. The data included a subset of those used in earlier studies
by us (Joyner and Boore, 1981, 1982), augmented by data from three recent earthquakes
with magnitudes close to 7: 1989 Loma Prieta, 1992 Petrolia, and 1992 Landers. Be
sides the addition of new data, this study differs from our previous work in several ways:
records at distances equal to and greater than the distance to the first record triggered by
the 5 wave were not included (this resulted in eliminating 56 records from our previous
data set for peak horizontal acceleration and 19 records from our previous data set for
response spectra; in addition, 7 records providing peak acceleration values were removed
for a variety of other reasons), we used weighted regression in the second stage of the two-
stage regression, equations were evaluated at many more periods than previously and for
four values of damping, and the smoothing of the regression coefficients over period was
done by computer rather than by eye. In addition, we changed the way in which geologic
conditions beneath the site are classified. Our previous studies used a binary rock/soil
classification. In anticipation of future building code classifications, we now divide site
geology into four classes, depending on the average shear-wave velocity in the upper 30m.
Site class A includes sites where the average shear-wave velocity is greater than 750 m/s;
site class B sites where the velocity is between 360 and 750 m/s; site class C sites where
the velocity is between 180 and 360 m/s; and site class D sites where the velocity is less
than 180 m/s (site class D class was poorly represented in the data set and has not been
included in the analysis).
Compared to the predictions from our previous equations, the new results have a lower
variance and show differences between site classes at all periods, not just at periods longer
than about 0.3 sec. At distances within a few tens of kilometers the motions for our new
class B and class C are similar to those for our old rock class and soil class respectively;
the motions for our new class A are lower than any of our previous predictions. At large
distances the new equations predict larger motions, larger at 80 km by a factor of two or
more.
INTRODUCTION
In earlier studies (Joyner and Boore, 1981; Joyner and Boore, 1982; and Joyner and
Boore, 1988) we presented equations for peak horizontal acceleration, velocity, and response
spectra as a function of earthquake magnitude, the distance from the earthquake source,
and the type of geologic material underlying the site. These equations were based on
data obtained through 1980, and they used a binary classification ("rock" and "soil") for
the geologic materials. Many more data have been collected since 1980. In particular,
three earthquakes in California (1989 Loma Prieta, 1992 Petrolia, and 1992 Landers) have
provided data for a range of magnitude and distance, critical for engineering design, which
was poorly represented in our previous work. Furthermore, it is likely that future editions
of national building codes will use at least a four-fold classification of site geology, based
on average shear velocity to a depth of about 30 m. Our long-term goal is to develop
prediction equations incorporating all of the data recorded since our earlier work and to
reprocess all of the data for the sake of uniformity and to extend the period range covered
by the equations. We decided, however, that an interim report would be useful at this
time. Most of the post-1980 data that we are not including in this interim study are for
magnitudes and distances sampled relatively well in our previous studies, and we expect
that the results of our final study will not change greatly from those in this interim report.
In this report we give only brief discussions of those matters that were explained in
our previous reports; we concentrate instead on topics that are new in this study.
DATA
Ground Motion Data
The set of data to be used in the regression was chosen from the data used in our
previous studies combined with recordings of the 1989 Loma Prieta, the 1992 Petrolia, and
the 1992 Landers earthquakes. Most of the data were collected by the California Division
of Mines and Geology's Strong-Motion Instrumention Program and the U.S. Geological
Survey's National Strong-Motion Program.
As in our previous studies, we used values for peak acceleration scaled directly from
accelerograms, rather than the processed, instrument-corrected values.. We did this to
avoid bias in the peak values (e.g., Fig. 5 in Boore and Joyner, 1982) from the sparsely
sampled older data. This bias is not such a problem with the more densely sampled recent
data. With a few exceptions we used response spectra as provided by relevant agencies; the
exceptions are the data collected by Southern California Edison Company and by S. Hough
of the U.S. Geological Survey, for which we computed response spectra ourselves. (We use
the notation psv for response spectra, and all uses of the term "response spectra" refer
to pseudo-velocity response spectra, computed by multiplying the relative displacement
spectra by the factor 2?r/T, where T is the undamped natural period of the oscillator
[the psv provided by the U.S. Geological Survey for the Loma Prieta earthquake used the
damped period, but in the worst case (20 percent damping) this amounts to a difference
in response spectra of only 2 percent].)
As we did previously, to avoid bias due to soil-structure interaction, we did not use data
from structures three stories or higher, from dam abutments, or from the base of bridge
columns. In addition, we include no more than 1 station with the same site condition
within a circle of radius 1 km. In such cases, we generally chose the station with the
lowest database code number and excluded the others. The radius of 1 km is a somewhat
arbitrary choice.
When a strong-motion instrument is triggered by the S wave, the strongest motion
may be missed. In this study, unlike previous studies, we made a systematic effort to
exclude records from instruments triggered by the S wave.
A strong-motion data set will be biased by any circumstance that causes low values of
ground motion to be excluded because they are low, as happens when the ground motion
is too weak to trigger the strong-motion instrument, when the ground motion is so weak
that an instrument triggers on the S wave, or when records are not digitized because their
amplitude is low. To avoid a bias toward larger values, we impose a distance cutoff for
each earthquake, beyond which we ignore any data available for that earthquake. This
cutoff should logically be a function of geologic condition and trigger level of the recording
instrument. We have ignored geologic condition in the determination of cutoff distance in
this report, but we have partially considered the effect of trigger level by distinguishing
between those stations employing a trigger sensitive to horizontal motion and those that
were triggered on the vertical component of motion. Potentially, every earthquake could
have two cutoff distances, depending on the type of trigger used in the recorder. In fact,
this was only necessary for the 1971 San Fernando earthquake, which occurred during the
time of transition between older instruments that trigger on horizontal motion and newer
instruments that employ vertical triggers. For peak acceleration, the cutoff distance is
equal to the lesser of the distance to the first record triggered by the S wave and the
closest distance to an operational nontriggered instrument. For response spectra we chose
to presume that amplitude is a factor in deciding which records are digitized, and we set
the cutoff distance to the lesser of the distance to the first digitized record triggered by the
S wave, the distance to the closest non-digitized recording, and the closest distance to an
operational nontriggered instrument. The cutoff distances are given in Table 1. In Table 1,
the greater-than sign indicates that the cutoff distance is at an unknown distance greater
than that indicated. For the Landers earthquake the digitizing of the analog records is in
the early stages, and few records from digital instruments have been released. It is likely
that the cutoff distance for response spectra for the 1992 Landers earthquake will increase
in the future.
In our previous studies we ignored the possible bias introduced by including records
triggered by the S wave. Using the cutoff distances shown in Table 1 resulted in the elimi
nation of 56 records from the peak acceleration data and 19 records from the peak velocity
data set, a significant fraction of the data used in our previous studies. In addition, 7
records were deleted because information was available only for one horizontal component,
because the record was obtained on a dam abutment, or because available information
indicated that the site was underlain by muskeg or peat. Table 2 contains a listing of the
records used in the previous study that were eliminated from the current analysis.
Because of the relatively low sampling rate of the older data (unevenly sampled, but
usually interpolated to 50 samples/s), the response spectra are not well determined at
periods less than 0.1 s. At longer periods, low signal to noise and filter cutoffs employed
in the processing limit the generally useful band to periods less than about 2 to 4 s (we
hope to extend this range in the future by reprocessing the data). We have used response
spectra for periods between a maximum range of 0.1 and 2 s.
The recording of the 1992 Petrolia earthquake at the Cape Mendocino station provided
only lower bounds for the peak acceleration, and therefore the recording was not used for
peak acceleration. According to numerical experiments mentioned by Shakal et al. (1992a),
the high-frequency character of the acceleration trace associated with the peak motion
makes the displacement and velocity records insensitive to the actual value of the peak
motion. For this reason, we have used response spectra determined from the recording for
periods greater than 0.1 sec in our analysis.
Predictor Variables
As before, we use moment magnitude as the measure of earthquake size and a dis
tance equal to the closest horizontal distance from the station to the point on the earth's
surface that lies directly above the rupture. We estimated the moment magnitudes and
the areas of the rupture surface from a literature review of various published studies for
each earthquake.
Unlike the earlier studies, we use a site classification scheme based on the shear velocity
averaged over the upper 30m. This scheme, shown in Table 3, has been proposed by Roger
Borcherdt and Thomas Fumal and is now being considered for use in the 1994 edition
of the National Earthquake Hazard Reduction Program's recommended code provisions.
When available, we used measurements from boreholes at the strong-motion sites. In most
cases such measurements were not available, and then we estimated the site classifications
by analogy with borehole measurements in similar geologic materials; the type of geologic
materials underlying each site was obtained from site visits, consultation with geologists
familiar with the area, and various geologic maps (in particular, the 1:250,000 scale maps
published by the California Division of Mines and Geology; see also Fumal, 1991, who
used more detailed maps). Although we expect that some of the site classifications will
change as more data become available, we do not anticipate any significant changes in the
regression coefficients as a result of such changes. Of the four site classes listed in Table 3,
class D was poorly represented in the data set and has not been included in the analysis.
The earthquake-station pairs and the corresponding predictor variables are given in
Tables 4 and 5 for peak acceleration and response spectra, respectively. The information
in Tables 4 and 5 is sorted by date, site class, and distance, in that order. The site class is
given in the column labeled G. In addition, Table 4 contains the peak acceleration values
(space does not allow a comparable listing of response spectral values). In both tables
a borehole number is given if the site classification is based on a nearby borehole. The
borehole information is contained in Table 6. The distribution in magnitude and distance
space is shown in Figure 1, where the data used previously (but not wiinowed out of the
current data set) and the data from the three recent earthquakes are plotted with different
symbols. It is clear that the recent data fill an important gap in the previous data set. It
should also be noted that very few data are available for distances beyond about 80 km.
METHOD
The coefficients in the equations for predicting ground motion were determined using
a weighted, two-stage regression procedure (Joyner and Boore, 1993). In the first stage,
the distance dependence was determined along with a set of amplitude factors, one for each
earthquake. In the second stage, the amplitude factors were regressed against magnitude
to determine the magnitude dependence. The second-stage regression used a weighting
matrix with zero off-diagonal terms (equation (34) in Joyner and Boore, 1993); the value
of at was determined by finding the value that satisfies (or the non-negative value that
most nearly satisfies) equation (33) in Joyner and Boore (1993).
We fit the following functional form to the data:
logy = bi + 62 (M - 6) + 63 (M - 6)2 + 64 r + 65 logr + b6 GB + b7 Gc + er + ee , (1)
where
r = (d2 +h2 )( 1 M. (2)
In this equation Y is the ground motion parameter (in cm/s for response spectra and g
for peak acceleration); the predictor variables are magnitude (M), distance (d, in km),
and site classification (G# = 1 for class B and zero otherwise; GC 1 for class C and
zero otherwise); er is an independent random variable that takes on a specific value for
each record; and ee is an independent variable that takes on a specific value for each
earthquake. The coefficients to be determined are 61 through 67, fo, and the variance of ee
and er (a2 and <r2 , respectively). The earthquake-to-earthquake component of variability is
represented by cr 2 , and all other components of variability are represented by <r2 . Note that
h is a fictitious depth that is determined by the regression. We present sets of equations
for predicting both the larger of the two horizontal components and a randomly-oriented
horizontal component of ground motion. To derive equations for the randomly-oriented
component, we used the geometric mean of the two horizontal-component amplitudes for Y
in equation (1) rather than choosing one of the horizontal components randomly. This will
give the correct regression coefficients, but the variance of er determined by the regression
program will be reduced below that expected for the prediction of a random component
of ground motion. To account for this, we computed the variance (cr;?) of the horizontal
components from the following formula:
- nrecs -
(3)
where Yij is the zth component from the jth recording and the sum is taken over all records
for which both horizontal components were available. The few records that did not have
both horizontal components were not included in the sum, although the one available
component was used in the regression to determine the coefficients in equation (1)). The
variance d^ is then given by
4 = °l + °l, (4)
where a\ is the variance from the first stage of our two-stage regression. The overall
variance is given by combining the individual variances:
^+^e2 - (5)
RESULTS
Equation (1) was fit to the data period-by-period at the 46 periods between 0.1 and 2.0
s for which the response spectral values had been computed. These periods are distributed
in a generally logarithmic manner over the interval. The data and regression fit for the
second stage of the regression analysis are shown in Figure 2, for the random horizontal
component of peak acceleration and 5-percent damped response spectra; plots for the other
values of damping and for the larger of the horizontal components are similar and are not
included in this report.
Plots of the coefficients versus period showed them to have fluctuations that lead
to somewhat jagged spectra at a fixed distance and magnitude; the amplitude of the
8
fluctuations is comparable to the uncertainty in the estimated coefficients. Because we
wish our equations to produce smooth response spectra, we have smoothed the coefficients
over period. After some experimentation with various smoothing schemes, we adopted
the least-squares fit of a cubic polynomial as the best representation of the smoothed
coefficients. The unsmoothed and smoothed coefficients for the 5-percent damped response
spectra for the random horizontal component are shown in Figure 3; figures for the other
dampings and for the larger horizontal component are collected at the end of the report
in a multipart figure labeled Al.
Comparisons of response spectra computed from the unsmoothed and the smoothed
regression coefficients are given in Figures 4, 5, and 6 for combinations of magnitudes, site
classes, and distances. These figures illustrate the jaggedness that motivated our smoothing
of the coefficients and also demonstrates the effectiveness of the smoothing procedure.
The smoothed coefficients for the random horizontal component and the larger hori
zontal component are given in Table 7 and 8, respectively. Each table contains four parts,
corresponding to dampings of 2, 5, 10, and 20 percent. Note in the column headings for
the tables that the uncertainties cr\, crc , crr , &e, a^d 0iog y are represented by 51, SC, SR,
SE, and SLOGY', respectively. The coefficients for predicting peak acceleration are given
in Table 9.
Based on the magnitude and distance distribution shown in Figure 1, we stipulate
that our equations not be used to predict motions at distances greater than 100 km or
magnitudes less than 5.0 or greater than 7.7.
Several columns in Tables 7 and 8 have zero entries, for the following reasons. We
initially fixed 65 at -1, but this led to values of the coefficient 64 greater than 0. Positive
values of 64 lead to unreasonable behavior at large distances. For this reason we set 64 = 0.0
and solved for the geometrical-spreading surrogate, 65. The "SC" column represents the
variance due to the difference in amplitude of the two horizontal components of motion at a
site; it obviously has no meaning when peak motions from the larger horizontal component
is being considered, and therefore the "SC" entries in Table 8 are set to zero.
Plots of selected ground motions against distance computed from the coefficients in
Tables 7b and 9 are shown in Figure 7.
RESIDUALS
An important step in a regression analysis is a study of the residual of the data about
the regression fits. We have already shown one such comparison (Figure 2), in which no
systematic departures from the assumed model can be seen. We have plotted residuals of
the logarithms of ground motion against distance for different site and magnitude classes,
and we again we see no systematic differences between the data and the predictions (Figure
8).
DISCUSSION AND CONCLUSIONS
How do the new equations compare to our previous equations? Because of the differ
ence in site classification, we cannot make a direct comparison. Predicted psv from old
and new equations are shown in Figure 9 as a function of period for two magnitudes, with
different curves for the various site classes for distances of 0 and 20 km. In general, at
these distances the new site class A has lower motions than we would have predicted for
rock sites; the motions from the new site class C are similar to those from the old soil class
and the motions for the new site class B are similar to those for the old rock class. We
found that many of our previously-designated rock sites fell into the B class, and therefore
at first glance it is not surprising that the old rock and new class B predictions are similar.
On the other hand, our old soil class was made up of a combination of B and C sites,
and therefore Figure 9 suggests that the average ground motion from our new equations
and new site classes, for a specific collection of sites, would be lower than from our old
equations and site classes. Note also that the difference between the various site classes
persists to low periods, unlike our previous finding.
The new equations give higher values than the old equations at large distances. At 80
km the new equations give values for the average of site classes B and C that are a factor
of two or more greater than the values given by the old equations for soil (Figure 10).
To understand better the reasons for the higher values at large distances we performed a
series of analyses of the old data set. The results show that using weighted regression for
the second stage of the analysis, winnowing the data set on the basis of the distance cutoff
table, assigning new site classes to the older data, and including the new data from the
three recent earthquakes all contributed to increasing the values for large distances.
10
Although not shown in the figure, the variance of the ground motions has been reduced
in our new results. This is shown in Table 10 for 5 percent damped psv at periods of 0.3
and 1.0 s. A series of analyses of the old data set shows that the primary cause of the
reduction in variance is the winnowing of the data set. The use of weighted regression for
the second stage also contributed to the reduction in variance.
Although this is not the place for an extended discussion of the variations in the coef
ficients and their possible physical interpretation, we point out that a number of trends are
similar to those found in our previous work: with increasing T, the magnitude dependence
increases, as do the site factors and the variance. The coefficient h generally decreases
with increasing period.
ACKNOWLEDGMENTS
We wish to thank Sue Hough and Dennis Ostrom for recordings of the Landers earth
quake, and Norm Abrahamson, Allin Cornell, and Robin McGuire for discussions about
regression analysis of strong-motion data. We also thank Ken Lajoie, Patty McCrory, Bob
McLaughlin, Dan Ponti, and John Tinsley for discussions about geologic materials, and
April Converse, Bob Darragh, Ed Etheridge, and Peter Mork for help with the data set.
Julian Bommer helped us with the initial formulation of the database structure. Chuck
Mueller provided a useful review of the paper. This work was partially supported by the
U.S. Nuclear Regulatory Agency.
11
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15
Tabl
e la.
Cutoff distances
for
peak a
cceleration
EQ#
YEAR NAME
CUTOFFDIST (km)
8 19
40 Im
peri
al Va
lley
>
12.0
18
19
52 Ke
rn C
ount
y 14
8.0
32 19
57 Daly
City
>
8.0
50 19
66 P
arkf
ield
63
.6
58 19
68 B
orrego M
t.
105.
064
19
70 Lytle
Creek
13.0
65 19
71 San
Fern
ando
72 19
72 Bear Va
lley
76 1972 Sitka
79 19
72 M
anag
ua84
19
73 P
t. Mu
gu97 19
74 Hoi li
ster
>
109
1975 Or
ovil
le
137
1978
Santa Barbara
> 144
1979
St. El
ias
>14
6 19
79 C
oyot
e La
ke14
7 19
79 Imperial Va
lley
153
1980
Li
verm
ore
Vall
ey!
>154
1980
Livermore
Valley2
>15
5 19
80 Horse
Canyon
328
1989
Loma P
rieta
349
1992
Petrolia
352
1992
Landers
119.
9
20.2 for
H tr
igge
r, > 60.7 f
or V
tr
igge
r31.0
145.
0 >
5.0
50.0
> 17
.0
8.0
> 14
.0
> 25
.443.0
64.0
40.
48.
47.
80.
45.
Table
1b.
Cutoff distance d
istances used f
or re
spon
se s
pect
ra
EQ#
YEAR
NA
ME
CUTOFFDIST (km)
8 19
40 Im
peri
al Va
lley
18
1952 Ke
rn C
ounty
32 19
57 D
aly
City
50 19
66 P
arkf
ield
58
19
68 B
orrego M
t.64
19
70 Lytle
Creek
65 19
71 San
Fern
ando
76
1972 Sitka
79 19
72 M
anagua
144
1979
St.
Elias
146
1979
Coy
ote
Lake
147
1979
Im
peri
al Va
lley
328
1989
Loma Prieta
349
1992 Petrolia
352
1992 Landers
> 12
.014
8.0
> 8.
063.6
105.
013
.020
.2 for
H tr
igge
r; > 60.7 f
or V
tr
igge
r 14
5.0
> 5.
0 >
25.4
43.0
64.0
68.7
45.3
65.4
CUTO
FFDS
.OFR
7-
15-9
3 3:
49p
Page 1
of
1
Tabl
e 2a.
Records
from
previous
work eliminated from t
he c
urre
nt
regr
essi
on a
nalysis
of peak ac
cele
rati
on.
DATE
EART
HQUA
KEDI
ST ST
ATIO
NLAT.
LONG.
21-Jul-52
Kern C
ount
y 21-Jul-52
Kern C
ount
y
21-J
ul-5
2 Kern C
ount
y 21-Jul-52
Kern Co
unty
21-Jul-52
Kern C
ount
y 21-Jul-52
Kern C
ount
y
7.40 14
8.0
San
Luis
Obi
spo
35.285 12
0.66
07.40 3
59.0 H
awthorne,
NV
38.5
50 11
8.63
0
7.40 15
6.0
Colton:
SCE
Subs
tn.
34.0
60 11
7.32
07.40 2
24.0 Bi
shop
37
.360
11
8.39
67.40 2
93.0 H
ollister C
ity
Hall
36
.850
12
1.40
07.40 3
70.0 E
l Centro A
rray S
ta 9
32
.794
11
5.54
9
28-Jun-66
Park
fiel
d 28-Jun-66 Park
fiel
d 28
-Jun
-66
Park
fiel
d
6.10
63.6 S
an L
uis
Obis
po6.10 10
5.0
Taft
6.10 11
2.0
Buena
Vista
Pumping
28-Jun-66
Park
fiel
d 6.10 12
3.0
Hollister
City H
all
35.285 12
0.66
035
.150
11
9.46
035
.160
11
9.35
0
36.8
50 12
1.40
0
9-Apr-68 B
orrego M
ount 6.60 14
1.0
Devi
l Canyon
34.2
00 11
7.33
09-Apr-68 B
orrego M
ount 6.60 2
00.0 P
asad
ena
- Ol
d Se
ism
Lab
34.1
50 11
8.17
0
9-Apr-68 B
orre
go M
ount 6.60 10
5.0
Pern's D
am
33.843 11
7.18
89-Apr-68 B
orre
go M
ount 6.60 12
2.0
San On
ofre
33
.370
11
7.56
09-Apr-68 B
orrego M
ount 6.60 14
7.0
Ceda
r Springs
- Pu
mp H
ouse
34.3
10 11
7.30
09-Apr-68 B
orre
go M
ount 6.60 19
7.0
Pasa
dena
- At
hena
eum
34.1
40 11
8.12
09-Apr-68 B
orrego M
ount 6.60 2
03.0 P
earblossom:
Pumping
Plan
t 34
.510
11
7.92
0
9-Ap
r-68
Bor
rego
Mount 6.60 13
0.0
Colton:
SCE
Subs
tn.
34.0
60 11
7.32
09-Apr-68 B
orrego M
ount 6.60 18
7.0
Long
Be
ach
- Te
rmin
al Is
land
33.
770
118.
230
9-Ap
r-68
Bor
rego
Mount 6.60 2
11.0 Hollywood
Stor
age
Bldg
PE
Lo 3
4.09
0 11
8.34
0
2-Oct-69 S
anta Rosa,
C 5.60
2-Oct-69 S
anta Rosa,
C 5.70
62.0 S
an P
ablo
62.0 S
an P
ablo
37.9
80 12
2.34
037
.980
12
2.34
0
12-S
ep-7
0 Lytle
Creek
12-Sep-70
Lytle
Creek
12-Sep-70
Lytle
Creek
12-Sep-70
Lytle
Creek
5.30
19
.0 C
edar S
prings
- Miller C
anyo 3
4.28
0 11
7.33
0 5.
30
21.0 D
evil
Canyon
34.2
00 11
7.33
0
5.30
13
.0 W
rightwood
5.30
22.0 C
edar
Springs
- Pu
mp H
ouse
12-Sep-70
Lytle
Creek
5.30
29.0 C
olton: SCE
Subs
tn.
34.3
60 11
7.63
034
.310
11
7.30
0
34.0
60 11
7.32
0
9-Fe
b-71
San
Fernando
9-Feb-71 San
Fernando
9-Fe
b-71
San
Fernando
9-Fe
b-71
San
Fernando
9-Fe
b-71
9-
Feb-
71
9-Fe
b-71
9-
Feb-
71
9-Feb-71
9-Fe
b-71
9-
Feb-
71
San
Fern
ando
San
Fern
ando
San
Fernando
San
Fernando
San
Fern
ando
San
Fern
ando
San
Fernando
9-Fe
b-71
San
Fernando
9-Fe
b-71
Sa
n Fe
rnan
do9-
Feb-
71 San
Fernando
6.60
20.2 Lake H
ughe
s St
a 9
34.6
10 11
8.56
06.60
21.1 Gr
iffi
th P
ark
Obse
rvat
ory
34.1
18 11
8.29
96.60
21.9 P
asadena
- Ol
d Se
ism
Lab
34.1
50 11
8.17
06.60
87.0 C
edar S
prings
- Miller Canyo
34.2
80 11
7.33
0
6.60
23.4
Lake H
ughes
Sta
1 34.674 11
8.43
06.60
24.2
Castaic
34.5
60 11
8.66
06.60
28.6 P
almd
ale:
Fi
re S
tation
34.5
78 118.113
6.60
37.4 Pearblossom: Pumping
Plan
t 34
.510
11
7.92
06.60
64.0 Fort Tejon
34.8
70 11
8.90
06.60
66.0 Ed
mons
ton
Pump
ing
34.9
40 11
8.83
06.60
88.0 C
edar S
prings
- Pump H
ouse
34.3
10 11
7.30
0
6.60
24.6 Hollywood
Stor
age
Bldg
PE
Lo 3
4.09
0 11
8.34
06.60
46.7
Oso P
umping Pl
ant
34.8
08 11
8.72
06.60
56.9 P
alos V
erdes
Estates
33.8
01 11
8.38
7PA
JBOU
T.OF
R 7-16-93
11:43a
Page
1 of
2
9-Feb-71
9-Fe
b-71
9-Fe
b-71
9-Feb-71
24-Feb-72
30-Jul-72
30-J
ul-7
2
21-Feb-73
1-Aug-75
1-Au
g-75
1-Aug-75
1-Au
g-75
28-Feb-79
6-Aug-79
6-Au
g-79
£
6-Au
g-79
03
15-Oct-79
24-Jan-80
27-Jan-80
25-Feb-80
25-F
eb-8
025-Feb-80
San
Fernando
San
Fernando
San
Fernando
San
Fernando
Bear V
alle
y
Sitka
Sitka
Poin
t Mu
gu
Orov
il le
Orovi
I le
Oroville
Orovi lie
St.
Elias
Coyo
te L
ake
Coyo
te La
keCo
yote
Lak
e
Impe
rial
Va
il
Livermore
Val
Livermore
Val
Horse
Canyon
Horse
Canyon
Horse
Canyon
6.60
6.60
6.60
6.60
5.30
7.70
7.70
5.60
6.00
6.00
6.00
6.00
7.60
5.80
5.80
5.80
6.50
5.80
5.50
5.30
5.30
5.30
61.4
62.
82.
91.
0 0 0
31.0
300.
145. 50. 8. 32.
31.
30.
40. 1. 23.
38.
64.
10.
11.
53.
47.
49.
0 0 0 0 0 0 0 0 6 4 9 0 8 1 1 7 2
Long
Beach
- Te
rmin
al Island 3
3Po
rt Hu
enem
eWh
eele
r Ridge
Col ton: SC
E Substn.
Hoi li
ster
Ci
ty H
all
Yaku
tat,
Al
aska
Juneau
Jensen Filter Pl
ant
Oroville
Paradise
Chico
Mary
svi lie
Mund
ay C
reek,
Alas
ka
Coyote Lake D
am
Corr
al ito
sCa
pito
l a
Yuma
Delta
Pump
ing
Plan
t
Delta
Pump
ing
Plan
t
Whitewater Cyn
Fun Va
lley
Caba
zon
34 35 34 36 59 58 34 39 39 39 39 60 37 37
.770
.145
.030
.060
.850
.510
.382
.312
.550
.727
.717
.149
.023
.118
.046
36.974
32 37 37 33 33 33
.730
.800
.800
.989
.925
.918
118.
119.
118.
117.
121.
139.
134.
118.
121.
121.
121.
121.
141.
121.
121.
121.
114.
121.
121.
116.
116.
116.
230
206
990
320
400
670
642
496
500
681
815
577
966
550
803
952
700
620
620
655
389
782
PAJB
OUT
.OFR
7-
16-9
3 11
:43a
Page
2 o
f 2
Tabl
e 2b
.
DATE
28-Jun-66
28-Jun-66
12-Sep-70
12-Sep-70
H
9-Feb-71
VD
9-Fe
b-71
9-Fe
b-71
9-Feb-71
9-Fe
b-71
9-Feb-71
9-Fe
b-71
9-Feb-71
9-Feb-71
9-Fe
b-71
9-Fe
b-71
9-Feb-71
9-Feb-71
9-Fe
b-71
9-Fe
b-71
Records
from
regression o
f
EART
HQUA
KE
Park
fiel
dPa
rkfi
eld
Lytl
e Creek
Lytle
Creek
San
San
San
San
San
San
San
San
San
San
San
San
San
San
San
Fern
ando
Fern
ando
Fernando
Fernando
Fernando
Fernando
Fernando
Fernando
Fernando
Fern
ando
Fernando
Fernando
Fernando
Fernando
Fern
ando
prev
ious
work e
limi
nate
d from t
he c
urre
nt
response s
pect
ra.
M 6.10
6.10
5.30
5.30
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
6.60
DIST
63 105 19 13 20 21 21 23 24 28 37 64 66 24 46 56 61 62 82
.6 .0 .0 .0 .2 .1 .9 .4 .2 .6 .4 .0 .0 .6 .7 .9 .4 .0 .0
STATION
San
Luis
Obi
spo
Taft
Cedar
Springs
- Miller Canyo
Weight wood
Lake
Hughes St
a 9
Grif
fith
Park O
bser
vato
ryPa
sade
na
- Ol
d Seism
Lab
Lake Hughes St
a 1
Castaic
Palmdale:
Fire
Station
Pearblossom: Pumping
Plan
tFo
rt Te
jon
Edmo
nsto
n Pumping
Hollywood
Storage
Bldg P
E Lo
Oso
Pump
ing
Plan
tPalos
Verd
es Estates
Long B
each
- Te
rmin
al Island
Port
Hu
enem
eWh
eele
r Ri
dge
LAT.
35.285
35.150
34.280
34.360
34.610
34.1
1834.150
34.674
34.560
34.5
7834.510
34.870
34.940
34.090
34.8
0833
.801
33.770
34.145
35.030
LONG
.
120.
119.
117.
117.
118.
118.
118.
118.
118.
118.
117.
118.
118.
118.
118.
118.
660
460
330
630
560
299
170
430
660
113
920
900
830
340
720
387
118.
230
119.206
118.
990
PVJB
OU
T.O
FR
7-1
6-9
3
11:3
6aPa
ge 1
o
f 1
Table
3. Definition o
f si
te c
lass
SITE
CLASS
RANG
E OF
SH
EAR
VELO
CITI
ES*
A gr
eate
r th
an 7
50 m
/sB
360
m/s
to 7
50 m
/sC
180
m/s
to 3
60 m
/sD
less t
han
180
m/s
Shea
r velocity i
s av
erag
ed o
ver
the
upper
30 m
.
SITE
CLSS
.OFR
7-
11-9
3 4:24
p Pa
ge 1
of 1
Table
4.
DATE
19-May-40
21-J
ul-5
2 21
-Jul
-52
21-J
ul-5
2
21-J
ul-5
2
22-M
ar-5
7
28-J
un-6
6 28
-Jun
-66
28-J
un-6
6 28
-Jun
-66
28-J
un-6
6
9-Apr-68
9-Fe
b-71
9-
Feb-
71
to
9-Fe
b-71
M
9-Feb-71
30-J
ul-7
2
23-D
ec-7
2
21-F
eb-7
3
28-N
ov-7
4
28-N
ov-7
4 28
-Nov
-74
28-N
ov-7
4
13-Aug-78
13-Aug-78
13-A
ug-7
8
28-F
eb-7
9
6-Au
g-79
6-Aug-79
6-Au
g-79
Records
used th
e de
velo
pmen
t of
th
e equations
for
peak a
ccel
erat
ion.
EART
HQUA
KE
M DIST ST
ATIO
N LAT.
LONG
.
Impe
rial
Va
il
Kern C
ount
y Kern C
ount
y Kern C
ount
y
Kern C
ount
y
Daly C
ity
Park
fiel
d Pa
rkfi
eld
Park
fiel
d Pa
rkfi
eld
Park
fiel
d
Borrego
Mount
San
Fern
ando
San
Fernando
San
Fernando
San
Fernando
Sitk
a
Managua
Poin
t Mu
gu
Hoi li
ster
Hollist'er
Hoi li
ster
Hoi li
ster
Sant
a Ba
rbar
a Sa
nta
Barb
ara
Sant
a Ba
rbar
a
St.
Elias
Coyote L
ake
Coyote Lake
Coyote L
ake
7.00
7.40
7.40
7.40
7.40
5.30
6.10
6.10
6.10
6.10
6.10
6.60
6.60
6.60
6.60
6.60
7.70
6.20
5.60
5.20
5.20
5.20
5.20
5.10
5.10
5.10
7.60
5.80
5.80
5.80
12.0
42.0
85.0
109.
0
107.
0
8.0
16.1
17
.3 6.6
9.3
13.0
45.0
17.0
25
.7
60.7
19.6
45.0 5.0
16.0
17.0 8.0
10.0
10.0 0.0
11.0
14
.0
25.4 9.1
1.2
17.9
El Ce
ntro
Array S
ta 9
Taft
Sa
nta
Barbara
Pasa
dena
- At
hena
eum
Hollywood
Stor
age
Bldg PE Lo
San
Fran.: Go
lden
Gate
Park
Cholame-Shandon: Temblor
Park
fiel
d: Ch
olam
e 12U
Park
fiel
d: Ch
olam
e 2
Park
fiel
d: Ch
olam
e 5U
Park
fiel
d: Ch
olam
e 8W
El Centro A
rray S
ta 9
Lake H
ughes
Sta
12
Pasa
dena
- At
hena
eum
Urig
htwo
od
Lake H
ughes
Sta
4
Sitka
Mana
gua:
ES
SO R
efin
ery
Port
Hueneme
Hoi li
ster
- Sago V
ault
San
Juan B
auti
sta
Gavi
lon
College
Geol
Bldg
Hoi li
ster
City H
all
Santa
Barbara
UCSB
: Ph
ysic
al Pl
ant
Goleta Substation
Icy
Bay
Gilroy A
rray
1
Gilroy A
rray 6
San
Juan B
auti
sta
32.7
94
35.1
50
34.420
34.140
34.0
90
37.770
35.710
35.6
39
35.733
35.6
97
35.6
71
32.794
34.570
34.140
34.3
60
34.6
50
57.060
12.1
45
34.145
36.765
36.8
46
36.973
36.8
50
34.4
20
34.422
34.4
70
59.968
36.973
37.0
26
36.8
46
115.549
119.
460
119.
700
118.
120
118.
340
122.
480
120.
170
120.
404
120.288
120.
328
120.
359
115.549
118.
560
118.
120
117.
630
118.
478
135.
320
86.3
22
119.206
121.446
121.536
121.
568
121.
400
119.
700
119.
851
119.
890
141.
643
121.
572
121.
484
121.536
G HO
LE PA_H1
PA_H
2
C B B B C A B B C C C C B B B C A C C A B B C B B B B A B B
107
201 96
92 63 173
200
228
197
198
107 86
92
88 71 96 192
196
.359
.196
.135
.054
.062
.127
.411
.072
.509
.4
67
.279
.142
.374
.114
.057
.200
.110
.390
.130
.011
.120
.1
40
.170
.210
.3
90
.280
.160
.127
.419
.1
10
.224
.177
.090
.048
.044
.105
.282
.066
.403
.276
.061
.288
.103
.047
.159
.090
.330
.080
.008
.050
.100
.100
.100
.240
.240
.110
.100
.344
.090
REFERENCE
CIT:
EERL 76-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76-02
CIT: EE
RL 76-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76
-02
CIT: EE
RL 76-02
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28-Jun-92
Land
ers
28-J
un-9
2 La
nder
s7.
30 11
5.3
Prado
Dam
7.30
117
.6 P
omon
a33
.888
117.640
C 34.056 117.748
C.0
90.050
.080
.070
USGS
: CD
MG:
OFR
93-x
xx
OSMS
92-
07
PGAT
BL.O
FR
7-12-93
10:0
3pPa
ge 6 o
f 6
Expanded R
eferences
for
Table
4:
Shor
tRef
LongRef
to
CDMG:
OSMS 89
-06
CDMG:
OSMS 92-05
CDMG:
OSMS 9
2-07
CDMG:
OSMS 92
-09
CDMG
: OSMS PR
22
CDMG:
OSMS PR
26
CD
MG:
OSMS
PR
28
CI
T: EE
RL 76
-02
NCEL:
Lew2
SCE
USDC
: US
EQ72
USGS+CDMG
USGS:
A Brady
Circ
. 713
Circ
. 71
7-A
Circ
. 818-A
Circ
. 85
4-B
Circ
. 854-C
Circ.
914
OFR
79-1654
USGS
: US
GS:
USGS:
USGS
: US
GS:
USGS:
USGS:
USGS:
USGS
: US
GS:
USGS
: US
GS:
USGS
:
OFR
79-3
85
OFR
89-5
68
OFR
93-x
xx
PP 1254
Porc
ella
.
Shakal et al.
(1989)
Shakal et al.
(1992a)
Calif. Div. Mi
nes
and
Geol
ogy
(1992)
Shakal et al.
(1992b)
Port
er (1978)
MeJu
nkin
and
Ragsdale
(1980a)
MeJu
nkin
and
Ragsdale
(1980b)
Calif. In
st.
of Te
chno
logy
(1976)
T. K. Lew
(1990)
S. Ca
l. Ed
ison
mem
oran
dom
date
d Ju
ly 3
0, 19
92,
from
T.
A. Kelly
U. S.
De
pt.
of Commerce (1
974)
PGA
H1 fr
om U
SGS: Circ.
914;
the
othe
rs are
from C
DMG:
OSMS
PR
28.
horTz. fr
om U
SGS: OFR
79-1654; ve
rt,
scal
ed b
y R. L.
Po
rcel
laA.
G.
Br
ady
(U.S.
Geological Survey,
written
commun., 1977)
U.S.
Ge
olog
ical
Su
rvey
(1974)
U.S.
Ge
olog
ical
Su
rvey
(1
975)
U.S. Geological Su
rvey
(1
979)
U.S. Geological Su
rvey
(1980a)
U.S.
Ge
olog
ical
Su
rvey
(1980b)
U.S. Ge
olog
ical
Su
rvey
(1981)
Porc
ella
an
d Ma
tthi
esen
(1979)
PGA
H1 provided b
y R. L.
Po
rcel
la (w
ritt
en c
ommun.); ot
her
valu
es in
Por
cell
a et al
. (1
979)
Ma ley
et
al.
(1989)
Ethe
redg
e et
al.
(199
3)Br
une
et al.
(1982)
R. L.
Po
rcel
la (U.S.
Geological Survey,
written
commun,
various
years)
PGAF
OOT.
OFR
7-13-93
6:43p
Page 1
of
1
Tabl
e 5.
DATE
19-M
ay-4
0
21-Jul-52
21-J
ul-5
221-Jul-52
21-Jul-52
22-Mar-57
28-J
un-6
628
-Jun
-66
28-J
un-6
628
-Jun
-66
28-J
un-6
6
9-Ap
r-68
9-Feb-71
to
9-Fe
b-71
00
9-Fe
b-71
9-Feb-71
30-J
ul-7
2
23-Dec-72
28-F
eb-7
9
6-Aug-79
6-Aug-79
6-Aug-79
6-Aug-79
6-Au
g-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-Oct-79
15-O
ct-7
9
Records
used in
EART
HQUA
KE
M
Imperial Va
il
Kern C
ount
yKe
rn C
ount
yKern C
ount
y
Kern C
ount
y
Daly C
ity
Parkfield
Park
fiel
d
Parkfield
Park
fiel
dPa
rkfi
eld
Borr
ego
Mount
San
Fern
ando
San
Fernando
San
Fernando
San
Fernando
Sitka
Managua
St.
Elias
Coyote L
ake
Coyote Lake
Coyo
te L
ake
Coyote Lake
Coyote Lake
Imperial Va
ilIm
peri
al Va
il
Impe
rial
Va
ilIm
peri
al Va
ilIm
peri
al Va
ilIm
peri
al Va
ilImperial Va
ilImperial Va
ilIm
peri
al Va
ilImperial Va
il
7 7 7 7 7 5 6 6 6 6 6 6 6 6 6
the
deve
lopm
ent
of th
e equations
for
resp
onse
spectra.
DIST STATION
LAT.
LONG
. G
.00
.40
.40
.40
.40
.30
.10
.10
.10
.10
.10
.60
.60
.60
.60
6.60
7 6 7 5 5 5 5 5 6 6 6 6
.70
.20
.60
.80
.80
.80
.80
.80
.50
.50
.50
.50
6.50
6 6 6 6 6
.50
.50
.50
.50
.50
12.0
42.0
85.0
109.
0
107.
0
8.0
16.1
17.3 6.6
9.3
13.0
45.0
17.0
25.7
60.7
19.6
45.0 5.0
25.4 9.1
1.2
3.7
5.3
7.4
14.0
26.0 .6 1.3
2.6
3.8
4.0
5.1
6.8
7.5
El Centro A
rray S
ta 9
Taft
Santa
Barb
ara
Pasadena
- At
hena
eum
Hollywood
Storage
Bldg P
E Lo
San
Fran.: Golden G
ate
Park
Cholame-Shandon: Temblor
Park
fiel
d: Cholame
12W
Park
fiel
d: Ch
olam
e 2
Park
fiel
d: Ch
olam
e 5W
Park
fiel
d: Cholame
8W
El Ce
ntro
Array S
ta 9
Lake H
ughes
Sta
12Pasadena
- At
hena
eum
Wrig
htwo
od
Lake H
ughes
Sta
4
Sitka
Mana
gua:
ESSO R
efinery
Icy Bay
Gi Iro
y Array
1
Gilroy Array 6
Gilr
oy Array 4
Gilroy Array 3
Gilr
oy Array 2
Parachute
Test
Site
Supe
rsti
tion
Mtn
El Ce
ntro
Arr
ay S
ta 7
El Centro A
rray S
ta 6
Bonds
Corner
El Ce
ntro
Array S
ta 8
El Ce
ntro
Array Sta 5
El Centro:
Differential Arra
El Centro A
rray S
ta 4
Holtville
32.7
94
35.1
5034
.420
34.1
40
34.0
90
37.7
70
35.7
1035
.639
35.7
3335
.697
35.6
71
32.7
94
34.5
7034
.140
34.360
34.6
50
57.0
60
12.1
45
59.9
68
36.9
73
37.0
26
37.005
36.9
8736
.982
32.9
2932
.955
32.8
2932
.839
32.6
9332
.810
32.8
5532
.796
32.8
6432.812
115
119
119
118
118
122
120
120
120
120
120
115
118
118
117.5
49
.460
.700
.120
.340
.480
.170
.404
.288
.328
.359
.549
.560
.120
.630
118.
478
135 86 141
121
121
121
121
121
115
115
115
115
115
115
115
115
115
115
.320
.322
.643
.572
.484
.522
.536
.556
.699
.823
.504
.487
.338
.530
.466
.535
.432
.377
C B B B C A B B C C C C B B B C A C B A B C C C B B C C C C C C C C
HOLE 107
201 96 92 63 173
200
228
197
198
107 86 92 88 71 192
196
195
194
193
116
105
104 97 106
103
112
102 99
SOURCE
n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n n nPS
VTB
L.O
FR
7-1
2-9
3
10:0
4pPa
ge 1
of
3
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30
Foot
note
s fo
r Table
5:
CODE
RE
FERE
NCE
c Re
spon
se s
pectra from t
he C
alif
orni
a Strong-Motion
Instrumentation
Prog
ram.
g Re
spon
se spectra
computed f
rom
digital
unco
nnec
ted
accelerati
on
time
series
recorded on
te
mpor
any
deployments
of GEOS
instruments; data pr
ovid
ed b
y S.
Hough.
n Response s
pectra from t
apes d
istr
ibut
ed b
y th
e World Da
ta C
enter
Afor
Solid
Eart
h Ge
ophy
sics
, National Ge
ophy
sica
l Data Center,
Boulder,
Colo
rado
; primary
data providers
ane
the
U.S.
Ge
olog
ical
Su
rvey
and
the
California St
rong
-Mot
ion
Inst
rume
ntat
ion
Prog
ram.
s Re
spon
se spectra
computed from d
igital unconnected
acce
lera
tion
ti
me s
enies
pnovided b
y De
nnis
Ost
nom
of th
e Southenn C
alif
orni
a Edison C
ompa
ny.
u Response s
pectna fnom U
. S.
Geological Su
nvey
computen
files,
pn
ovid
ed
by P
. Mo
nk.
PSVFOOT.OFR
7-11
-93
5:43p
Page
1 of
1
o>
I
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V-CMSON-N.N-N.N.OOOOOOOO
32
*
142
143
144
145
146
147
150
158
164
170
173
182
190
192
193
194
195
196
197
198
200
201
208
Anderson Dam
Cala
vera
s Re
serv
oir
Bear V
alle
y #12
(Wil
liam
s Ranch)
Bear
Val
ley
#5 (Call en
s Ranch)
Bear
Val
ley
#10
(Web
b Ranch)
Hoi li
ster
Ai
rpor
tJohn M
uir
Scho
ol (A
PEEL
#2
E ?)
Cal
State
Hay w
ard
Pulgas Tu
nnel
(A
PEEL
#7
?)
Brid
ge wa
y Pa
rkPrayer boo
k Cr
oss
KGEI
(A
PEEL
#1)
Audubon
Scho
olGa
vilo
n Water
Tank (G
ilro
y #1)
Mission
Trails M
otel (G
ilro
y #2)
Gilroy S
ewag
e Tr
tmnt
(Gilroy
#3)
San
Ysid
ro S
choo
l (Gilroy
#4)
Canada Ro
ad (G
ilro
y #6)
Cockrum's
Garage (C
hola
me-S
hndn
5)
Shan
don
Pump
Station (C
hola
me 8
)Temblor
IILincoln
Scho
ol (Taft)
Keen
wi Id
37 37 36 36 36 36 37 37 37 37 37 37 37 36 36
.164
.453
.664
.673
.531
.889
.656
.657
.486
.529
.774
.544
.568
.974
.981
36.9
8637
.000
37 35 35 35 35 33
.027
.696
.671
.708
.149
.714
121
121
121
121
121
121
122
122
122
122
122
122
122
121
121
121
121
121
120
120
120
119
116
.631
.807
.249
.195
.144
.411
.084
.060
.314
.253
.477
.235
.258
.572
.554
.536
.521
.485
.328
.358
.171
.456
.711
506
482
330
391
311
218
276
522
435
134
732
115
133
1415 309
306
223
714
278
260
509
429
811
tt extrapolated 0
.7m
tt extrapolated 4
.4m
no t
t ex
trap
olat
ion
tt extrapolated 0
.4m
tt extrapolated 11
mtt extrapolated 1.2m
tt extrapolated 2
.5m
tt ex
trap
olat
ed 10
.7m
no t
t ex
trap
olat
ion
no t
t extrapolation
tt extrapolated 0
.4m
tt extrapolated 2
.5m;
no t
t extrapolation
tt extrapolated 1.7m
tt extrapolated 2
.3m
no tt
ex
trap
olat
ion
hole is
391
m N2
12E
of
basi
s fo
r ex
trap
olat
ion
not
well
the
coords above
J.F. Gibbs,
J.F. Gi
bbs,
J.F. Gi
bbs,
J.F. Gi
bbs,
J.F. Gibbs,
J.F. Gibbs,
Gibbs
et al
Gibb
s et
al
Gibb
s et
al
Gibbs
et al
Gibbs
et a
IGi
bbs
et al
Gibbs
et al
Fuma
l et
al
Fuma
l et
al
Fumal
et a
IFumal
et al
Fuma
l et
al
Fuma
l et al
Fumal
et al
Fuma
l et
a
IFu
mal
et a
IFl
etch
er et
written
comm
.written
comm.
written
comm
.written
comm
.written
comm
.written
comm
..
(1976)
. (1976)
. (1976)
. (1977)
. (1977)
. (1977)
. (1977)
. (1
982a
).
(198
2a)
. (1
982a
).
(198
2a)
. (1
982a
).
(198
2a)
. (1982a)
. (1982a)
. (1982a)
al.
(1990);
Aster
and
Shea
rer
(199la,
209
210
211
212
213
214
W
216
W
217
219
220
221
224
225
228
Note:
Mont
erey
Belm
ont
Sago S
outh (H
oi lister
Hill
s)Piedmont Jr
. Hi
gh Sc
hool
San
Francisco, Rincon H
ill
San
Francisco, Pa
cifi
c Heights
San
Fran
cisc
o, Di
amon
d Heights
Poin
t Bo
nita
Capi
tola
So.
San
Fran
cisc
o, Sierra Point
Agnews Ho
spital
Mission
San
Jose
Santa
Cruz
Park
fiel
d #2
AVGVEL = 30
m divided
by t
he t
rave
l
36 37 36 37 37 37 37 37 36 37 37 37 37 35
time
.597
.512
.753
.823
.786
.790
.740
.820
.974
.674
.397
.530
.001
.733
121
122
121
122
122
122
122
122
121
122
121
121
122
120
to 3
0m;
.897
.308
.396
.233
.391
.429
.433
.520
.952
.388
.952
.919
.060
.288
769
645
1224
1154
1429
1034
1875 484
1071 270
405
698
194
units
are
extrpltd 10.4m
to b
ottom
(nee
d 10.4m
of slower 9
21 m/s
no t
t ex
trap
olat
ion
a ra
nge
of velocities
given, co
rres
p. to
71
and
31 ms
ecextrpltd 4.9
m top, 4m bo
ttom
(nd
4.9m
of 250m/s for
750m
extrpltd 2
.7 m t
o su
rfno tt ex
trap
olat
ion
, 5.
5m t
o dpth (nd 2.
7m o
f 16
5m/s
used
shallow v
el.
to f
ill
in g
ap from 1
0m t
o 14
m, so
Av
tt ex
trap
olat
ed 2
m to
surface
(nee
d 2m
of
84m/
s to
give
tt extrapolated 1.
8m t
o su
rfac
e (n
eed
73m/
s to
reduce
att
ex
trpl
td 4
m to
sur
fno t
t ex
trap
olat
ion
no t
t ex
trap
olat
ion
tt ex
trap
olat
ed 16m
to
(nee
d 4m o
f 23
3 m/s
to lo
wer
avg
depth
(need
over
20,000
m/s
to g
tt based
on v
eloc
ity
vrs
depth
plot
m/s.
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
EPRI/CUREE
1993
1993
1993
1993
1993
1993
1991
b)
R. E.
Wa
rric
k, written
comm.
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41
Tabl
e 9.
Co
efficients o
f equations
for
the
rand
om a
nd larger h
orizontal
comp
onents o
f pe
ak a
ccel
erat
ion
(in
g; distance in k
m).
Comp
onen
tB1
B2B3
B4B5
B6B7
S1SC
SRSE
SLOGY
torandom
-.105
larg
er
-.038
.229
.216
0.0
0.0
0.0
-.778
0.0
-.77
7.162
.158
.251
5.57
.254
5.48
.186
.193
.098
.000
.210
.193
.093
.068
.230
.205
The
equations
are
to b
e us
ed f
or 5
.0 <
= M
<= 7
.7 a
nd d
<=
100.
0 km
.
RLPA.TBL
7-19-93
12:21p
Page
1 of
1
Table
10.
Comparison o
f uncertainies
in the
old
and
new
regr
essi
on
resu
lts.
T(sec)
SLOGY-OLD
SLOGY-NEW
....
..
..........
....
....
..0.
3 0.28
0.23
1.0
0.34
0.27
SIGM
A.TB
L 7-
13-9
3 6:19p
Page
1 of 1
8 -
0 -o 7- 4
0) CO
c 6-0E o^
5 -
8 _i
0
"§ 7 ""cO) CO
4 cc 6 -0
0**
5 -
Peak Acceleration o o
*- A A AAtA A4M
oo <D) o oooaDoaiSifiaD&S
°O O OOD
O O O OO dDZD <ODO
O O OOQIDOOO Q O OO (QD
OQ. O
o old dataA new data
, , , , , ,| , , , , , , ,,| r i i . . ,.| ii
Response Spectra o o
(2) A A AAA^AA 00 A M M
<QDO O O O O O ©OGDDOGDUDCD
°0 O OOD
O O O OO
O
o old dataA new data
10° 10 1 102
Closest Distance (km)
Figure 1. The distribution of the data in magnitude and distance space (each point represents a recording). The data points labeled old data are the ones that were also used in previous studies. The top frame is for the peak acceleration data set and the bottom is for the response spectral data set.
44
P 0
-1
Acceleration
. . I .... I .... I ..
M8
P 2 o _
P 2
T = 0.2 s
M
T = 0.3s
8
M
o -
Figure 2a. The data and regression for the second stage of the analysis, for peak acceleration and 5 percent damped response spectra at selected periods.
45
P 2
1
3
P 2
, I ..,,,.......
T = 0.75 s
T = 0.5 s
OQ
T = 1.0s
P 2
T = 1.5s T = 2.0s
8 8
M M
Figure 2b. The data and regression for the second stage of the analysis, for peak acceleration and 5 percent damped response spectra at selected periods.
46
Random component, 5 percent PSV
2.4
^ 2CO
1.6
-0.1
-0.2
0.4
0.2
0.6 l-rr^r
CM 0.4
0.2
-0.6
infij -0.8
-1
0.6
0.4
0.2
0.1 0.2 1 2
Period (sec)
0.1 0.2 1 2
Period (sec)
Figure 3a. The unsmoothed and smoothed coefficients (light and heavy lines, respec tively) for the 5 percent damped response spectra of the random horizontal component.
47
Random component, 5 percent PSV
10
8
6
4
oCO
0.16
0.12
0.08
0.1 0.2 1 2
Period (sec)
0.24
CO 0.2
0.16
0.16
to 0.08
0
0.1 0.2 1 2
Period (sec)
Figure 3b. The unsmoothed and smoothed coefficients (light and heavy lines, respec tively) for the 5 percent damped response spectra of the random horizontal component.
48
5 PCT DAMPING M=7.5 D=01000
100
CO
io
CO Q_
10
c
B
10.1
I I I I I I I I I I I I
1 PERIOD (S)
10
Figure 4. 5 percent damped, random component response spectra for magnitude 7.5 at 0 km distance, predicted from the unsmoothed and smoothed regression coefficients. The three sets of curves are for site classes A, B, and C.
49
5 PCT DAMPING D=0 S=C1000
100
CO
io
10
T I I I I I L
M 7.5
M 6.5
M 5.5
1 0.1 1
PERIOD (S)10
Figure 5. 5 percent damped, random component response spectra for site class C at 0 km distance, predicted from the unsmoothed and smoothed regression coefficients. The three sets of curves are for magnitudes 5.5, 6.5, and 7.5.
50
5 PCT DAMPING M=7.5 S=C1000
CO
io
COQ_
100
10
10.1
1 I 1 I I I
I I I I I I I
1 PERIOD (S)
10
Figure 6. 5 percent damped, random component response spectra for magnitude 7.5 and site class C , predicted from the unsmoothed and smoothed regression coefficients. The five sets of curves are for distances of 0, 10, 20, 40, and 80 km.
51
ID
100 101 10s
Distance (km)
102 -
O. 101 -
I
in
10°
Site Class =
T = 0.3 sec
10°
M7.5
M6.5
M5.5
101 102
Distance (km)
10° 101 102
Distance (km)
Figure 7. Attenuation with distance of peak acceleration and response spectra for the random horizontal component.
52
T = 0.3 sec1
0.5
o ! 0.5
-1
1
0.5
0
0.5
-1
1
0.5
0
0.5
-1
1
0.5
0
0.5
_i
X
Xx ° x
' / *" * x i * * " *x °
* x *»$ U x*X&*^*t*°*
' 5 x x ° °
1
M5 x M6 o M7
0
w o
All Sites
i
X X
o " x°; . x o
0
1
M5 x M6 o M7
Site Ai
J ." /__ . . ^ x^o
r *<x xx> xo o *fc o o" x
1
M5 x M6 o M7
0
o
SiteB
X
: xxx x x X X u x x K It «»^**^**w^ ** *
^^J[ X X " ^C O ^ X ^x x Mo *( X X o
1
M5 x M6 o M7
SiteC i
0 50 100
Distance (km)
Figure 8a. Residuals (log Yobserved logVpredicted), as a function of distance for mag nitude groups and site classes.
53
T = 1.0 sec1
0.5
0 ,
-0.5
-1
1
0.5
0
-0.5
-1
1
0.5
0 ,i
-0.5
-1
1
0.5
0
-0.5
-1
C
M5* M6, «. «Vv " " ." "" ' °. M7
* X x o * ° 0*x° o
All Siteso
I 1 1 . , 1 . 1 1
M5 x x M6
* " o M7X
^ X
0o
o0
: Site A i , , , , i .
M5 x M6
** x *o" Xx °° M7
_0 Site B
i , , . . i .
: M5L K x x x x M6
: x « K o M7 _*C. -~ x . * o1 x "
Lj»V x x ox
: Site C i . . , , i ,
) 50 100
Figure 8b. Residuals (log F0 &serwed log predicted), as a function of distance for mag nitude groups and site classes.
54
5 PCT DAMPING M=6.5 D=201000
100
CO
io
CO Q_
10
1 0.1 1
PERIOD (S)
soil
rock
10Figure 9a. Comparison of random component, 5 percent damped response spectra
computed from our previous equations and our new equations for the various site classes.
55
5 PCT DAMPING M=7.5 D=01000
100
CO
io
COCL
10
1 0.1
soil
rock
1 PERIOD (S)
10
Figure 9b. Comparison of random component, 5 percent damped response spectra computed from our previous equations and our new equations for the various site classes.
56
10
(0
1010C
Distance (km)
M = 6.5 T= 1.0 sec
! X
10C 10C
Distance (km) Distance (km)
Figure lOa. Comparison of ground motions computed from our previous equations and our new equations as a function of distance for magnitudes 6.5 and 7.5 and soil site classes.
57
10
10° -
(0 (D
D_
10" -
10"
10C
Distance (km)
10C 102 10C
Distance (km) Distance (km)
Figure lOb. Comparison of ground motions computed from our previous equations and our new equations as a function of distance for magnitudes 6.5 and 7.5 and soil site classes.
58
2.4
^ 2GO
1.6
COCD
0
-0.1
-0.2
0.4
CO CQ
0
Random component, 2 percent PS V
0.6
Sl 0.4
0.2
-0.6
CD -0.8
-1
0.6
CQ0.4
0.2
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Ala. Smoothed and unsmoothed regression coefficients.
59
Random component, 2 percent PSV
10
8
6
4
o co
0.16
0.12
0.08
0.24 n-"T
0.2
0.16
0.16
co 0-08
0.1 0.2 1 2
Period (sec)
0.1 0.2 1 2
Period (sec)
Figure Alb. Smoothed and unsmoothed regression coefficients.
60
2.4
CD
1.6
CO CO
0
-0.1
-0.2
0.4
CD CQ
Random component, 10 percent PSV
0.6
' fxf^J^; "V -
SI 0.4
CO
0.2
-0.6
-0.8
-1
0.6
0.4
0.2
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Ale. Smoothed and unsmoothed regression coefficients.
61
Random component, 10 percent PSV
10
8
6
4
oCO
0.16
0.12
0.08
0.24
CO 0.2
0.16
0.16
co 0.08
0
0.1 0.2 1 2
Period (sec)
0.1 0.2 1 2
Period (sec)
Figure Aid. Smoothed and unsmoothed regression coefficients.
62
2.4
DO
1.6
COm
0
-0.1
-0.2
0.4
COas 0.2
0
Random component, 20 percent PS V
0.6
S! 0.4
0.2
-0.6
IT)ft -0.8
-1
0.6
CD0.4
0.2
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Ale. Smoothed and unsmoothed regression coefficients.
63
10
8
OCO
0.16
0.12
0.08
Random component, 20 percent PSV
0.24
CO 0.2
0.16
0.16
co 0.08
0
0.1 0.2 1 2
Period (sec)
0.1 0.2 1
Period (sec)
Figure Alf. Smoothed and unsmoothed regression coefficients.
64
2.4
,. 2CD
1.6
S
0
0.1
0.2
0.4
0.2
0
Larger component, 2 percent PS V
0.6
0.4
0.2
-0.6
m -0.8
-1
0.6
r- °'4
0.2
0
0.1 0.2 1 2 0.1 0.2 1 2
Period (sec) Period (sec)
Figure Alg. Smoothed and unsmoothed regression coefficients.
65
Larger component, 2 percent PSV
10
8
6
4
OCO
0.16
0.12
0.08
0.24 I-TTTT
to 0.2
0.16
0.16
0.08
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Alh. Smoothed and unsmoothed regression coefficients.
66
Larger component, 5 percent PS V
2.4
CD
1.6
CO CD
0
-0.1
-0.2
0.4
CD CO
0
0.1 0.2 1 2
Period (sec)
0.6
0.4
0.2
-0.6
in no CQ -U.o
-1
0.6
CO0.4
0.2
0
0.1 0.2 1 2
Period (sec)
Figure Ali. Smoothed and unsmoothed regression coefficients.
67
Larger component, 5 percent PSV
10
8
6
4
OCO
0.16
0.12
0.08
0.24 rrrrr
CO 0.2
0.16
0.16
Jo
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Alj. Smoothed and unsmoothed regression coefficients.
68
Larger component, 10 percent PSV
2.4
_ 2
1.6
CO
0
-0.1
-0.2
0.4
0.2
0
0.1 0.2 1 2
Period (sec)
0.6 n-rrr
0.4
CD
0.2
-0.6
-0.8
-1
0.6
0.4
0.2
0
0.1 0.2 1
Period (sec)
Figure Alk. Smoothed and unsmoothed regression coefficients.
69
Larger component, 10 percent PSV
10
8
6
4
oCO
0.16
0.12
0.08
0.24 I-"-"
0.2
0.16
0.16
co 0.08
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure All. Smoothed and unsmoothed regression coefficients.
70
2.4
CD
1.6
Larger component, 20 percent PS V
0.6
... .I/ . .......I
COCO
0
-0.1
-0.2
0.4
COco 0.2
0
0.4
CD
0.2
-0.6
-0.8
-1
0.6
0.4
0.2
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Aim. Smoothed and unsmoothed regression coefficients.
71
Larger component, 20 percent PSV
10
8
6
4
oCO
0.16
0.12
0.08
0.24 n-"f
CO 0.2
0.16
0.16
co 0.08
0
0.1 0.2 1 2 0.1 0.2 1
Period (sec) Period (sec)
Figure Aln. Smoothed and unsmoothed regression coefficients.
72