Journal of Natural Disaster Science, Volume 23, Number 1, 2001, pp35-51

Strong Motion Simulation for the Philippines Based on Seismic Hazard Assessment
Ribelito F. TORREGOSA**Graduate student, Department of Civil Engineering, Gifu University, Japan
Masata SUGITO****Professor, Department of Civil Engineering, Gifu University, Japan
Nobuoto NOJIMA******Assoc. Professor, Department of Civil Engineering, Gifu University, Japan(Received for 8 Nov., 2000 and in revised from 26 Jul., 2001)

ABSTRACT
A simulation technique for strong ground motion based on seismic hazard analysis for the Philippines that incorporates both historical earthquakes and active faults is presented. The database for historical earthquake occurrences from 1907 to 1998, provided by the Philippine Institute of Volcanology and Seismology (PHIVOLCS) wasused. Philippine active faults identified from various geotectonic studies of the country were compiled. Seismic
source zoning for the Philippines was based on the occurrence rates of historical earthquakes. A polygonal sourcearea model was used to represent seismic source zones. Estimation formulas for peak ground acceleration (Amax)
and effective ground acceleration (Ae), used with the JMA scale of seismic intensity, were developed from 118
components of selected strong ground motion records for engineering foundation levels in Japan. Expected
ground motion parameters corresponding to both rare events of 475 years recurrence (10% in 50 years) and occasional events of 100 years recurrence (39% in 50 years) in the Philippines were determined. Hazard-consistentmagnitudes and hypo-central distances from different source zones for the three major Philippine cities, Manila,
Cebu, and Davao, were obtained probabilistically, and their respective acceleration, velocity, and displacement
time histories simulated.

1. INTRODUCTION
The Philippines is located in one of the most seismically
active regions of Asia. Many destructive earthquakes haveoccurred in various parts of the country. One of the most notable
was the 1990 Central Luzon earthquake with a magnitude of
MS=7. 6. The Philippine trench, formed by subduction of thewestern edge of the Philippine plate under the Eurasia plate, is oneof the country’s major seismic generators. Other major seismic
generators are the Philippine fault and Manila trench, which roughly parallel the Philippine trench. These three major faults havehigh slip rates of more than 6. 5 cm per year. Many other faults
have been traced in the country, but details are unavailable because
many are located on the sea bottom.
Past seismic hazard studies for the Philippines, based on historical earthquakes, were made by Acharya et al. (1979), Villaraza(1991) and Molas and Yamazaki (1994). Acharya (1980a) used
active fault data to study the seismic hazard in the Philippines, but
no published report has incorporated both historical earthquakes
and active faults. Through the seismic monitoring agency(PHIVOLCS), the Philippine government is now reviewing active
Philippine faults. Currently there are about 34 seismological stations distributed throughout the islands of the Philippines. Most ofthem were installed in the 1990s after the destructive 1990 Central
Luzon earthquake. Up to now, no major ground motion records

have been obtained.
Past probabilistic seismic hazard studies for the Philippines
were concerned only with maximum ground motion intensity, suchas peak ground acceleration (Amax). Peak ground acceleration (Amax)
for different levels of exceedance probabilities for all areas of thecountry have been studied. Although the seismic hazard for thecountry is high, other ground motion parameters, such as peakground velocity (Vmax) and the response spectra for different levelsof exceedance probabilities have not been studied. A method forgenerating strong ground motions by means of seismic hazard
analysis is presented. Scenario earthquakes were simulated for thecountry’s major cities because of their vulnerability to earthquake
damage.
Major parts of this study are: a) a probabilistic seismic hazard
analysis of the Philippines based on both historical earthquakes
and active faults, b) determination of expected peak ground motion
parameters for earthquake events with 475 and 100 years recurrences, and c) simulation of ground motion time histories for thethree major cities of the Philippines based on seismic hazards.
2. EARTHQUAKE DATA IN THE PHILIPPINES
2.1 Historical earthquake occurrence data
This information was obtained from the Philippine Institute ofVolcanology and Seismology (PHIVOLCS). Data for 5969 histor-

KEY WORDS: Philippines, strong motion simulation, seismic hazard, historical earthquakes

36

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

Fig. 1

Sites of historical earthquakes (1907-1998)

ical earthquakes (Lanuza, 1999) recorded since 1907 were used.
Locations of main shocks with surface wave magnitudes of MS>5.0 are shown in Fig. 1.
Because the collected earthquake records are incomplete for
MS < 6.0, the years of complete records for different magnitude
ranges had to be determined. The yearly occurrences of earthquakes for MS > 4.0 were analyzed. The incompleteness of historical earthquake information can be grouped into the three magnitude ranges. These are; MS > 6.0, 4.5 < MS < 5.9, and 4.0 < MS <4.4. The yearly occurrences of earthquakes for these three magnitude ranges are plotted in Fig. 2, from which the period in which
complete records of historical earthquakes in the Philippines are
assumed to be:1) MS > 6.0 records are complete from 1907 – 1998
2) 4.5 < MS < 5.9 records are complete from 1962 – 1998
3) 4.0 < MS < 4.4 records are complete from 1975 – 1998
The period with complete records of lower magnitude earthquakes is too short. In order to maximize the use of all the historical earthquake occurrences, corrections were made to quantities ofeach magnitude since 1907 for which there are no complete
records. These corrections (Katayama, 1982) were added to thequantity of each data taking into consideration the incompletenessof the records.
Assuming that the occurrence of an earthquake with the given
magnitude, i, is random and independent of past events, the occurrence rate, vi , is:nvi = t iiFig. 2Yearly occurrences of earthquakes by magnitude

k

k

i=j

i=j i

n
v =Σ vi =Σ t i
Letting T be the reference period,kv = 1・Σ（ ni・ T
ti ）
T i=j

(3)

T
ti is the correction factor for different magnitude ranges taking

into consideration the reference time period, T, and the time ofcomplete recording, ti. Here, the reference time period T, is 92
years (from 1907 - 1998). The correction factors are computed asfollows:(1)1) For MS > 6.0;

Where ni is the number of earthquakes of magnitude i, and ti is theperiod of complete observation. The average occurrence rate, v,
from magnitude, j to k, is written:(2)

T = 92 =1.0
ti922) For 4.5 < MS < 5.9;

T = 92 =2.48
ti
37

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

3) For MS < 4.4;

T = 92 = 1.0
ti92

Table 1.

Seismic source zone properties

The total numbers of occurrences within the above specified magnitude ranges were multiplied by the correction factors.
2.2 Seismic source zones
A significant factor in seismic hazard analysis is the divisionof seismic source zones, in which seismic activity can be treated ashomogenous. Rast and Saegesser (1980) showed the effects ofvarying the seismic source zones. They pointed out that variationin seismic source zoning accounts for as much as half the difference in the results and that the other half is due to different
assumptions, such as the upper bounds on magnitude and otherfactors. Seismic source zoning therefore must be done systematically, the seismic characteristics of each individual source zone
consequently being homogenous. To ensure that the designatedseismic source zones used in the hazard analysis had homogenous
seismic characteristics, the occurrence rates of earthquakes for theentire country were calculated. The spatial moving averagemethod was used to determine the occurrence rates of earthquakes
at individual points in the country. In that procedure, the occurrence rate at a point is determined by dividing the number ofoccurrences within a 100km radius by the area of a circle with a
100km radius to obtain the average number of occurrences per
square kilometer at the point. The result is then divided by the
number of years covered by our data to obtain the occurrences per

Fig. 4
Fig. 3

Seismic source zones

Philippine active faults (Acharya, 1980a; Knittel, et al, 1988;
Barrier, et al, 1991; Sajona, et al, 1993)

37

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R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

square kilometer per year. In this paper, the number of occurrences per square kilometer per year per point is called the occurrence rate. Occurrence rates of all the points in the Philippines for
MS > 4.0 were calculated using the above procedure. Polygons
were drawn enclosing adjacent areas with nearly uniform occurrence rates. Each polygon was designated a single seismic source
zone, for which uniform random occurrences of earthquakes are
assumed. Totally, 27 source zones were designated by thismethod. These source zones and the occurrence rates are shown in
Fig. 3. Linear regression analysis was done to obtain the b-valueof each seismic source zone. The properties of each zone (occurrence rate, b-value, maximum magnitudes, and area) are given in
Table 1. No seismic source zone was assigned to the western portion of the Philippines which historically has had very few, widely
scattered earthquakes.
2.3 Active fault data
Fifty-nine active faults were compiled from the previous
Table 2.

reports of Acharya (1980a), Knittel (1988), Barrier, et al. (1991),
and Sajona et al. (1993), (Fig. 4). Their fault parameters are given
in Table 2.
To incorporate the effect of active faults in the seismic hazard
evaluation, the parameters of maximum credible earthquake(MCE) and recurrence MCE time are indispensable. Slemmons(1978) determined the percent of fault rupture to total fault length
during a maximum earthquake for strike-slip faults longer than 280
kilometers. Because the active faults in the Philippines are of thestrike-slip type, his fault-rupture relation was used. Slemmons'relationship between total fault length, L, and percentage rupture,λ, during maximum earthquake is
λ= 15.76 + 0.012・L(4)
where:
λ= percentage of rupture (i.e., ruptured length × 100%)
total fault length
L = fault length in km

Philippine active fault parameters

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

This relationship was used for faults longer than 280 kilometers.
Rupture lengths during maximum events for faults with lengths of
50 to 280 kilometers are assumed to be half the total length as in
Mualchin (1996). All the active faults included in this study are
more than 50 kilometers long. Other possible scenarios of fault
ruptures, such as smaller events with higher annual occurrence frequencies, are neglected. Acharya (1980b) studied the relationshipbetween magnitude and fault rupture in Philippine earthquakes.
That relationship is
MS = 1.79・Log10RF+3.5
where:
RF = fault rupture length (λL) in kilometers
MS = magnitude (surface wave)(5)

3.1 A brief overview of the theory (Kameda and Nojima,
1988)
Seismic hazard analysis deals with probabilistic models ofearthquake occurrences. Identifying the exact location of futureearthquakes is very difficult at this stage. In dealing with seismic
hazards, it is acceptable to assume that earthquakes occur randomly both in size and location within a source zone. This assumption
is modeled by the Poisson process. In the Poisson model, the only
parameter is the mean rate of earthquake occurrence. For seismic
hazards from fault sources, the Poisson model can be used with the
maximum credible earthquake magnitude determined deterministically from the fault length and the expected recurrence period.
The annual probability that the random earthquake intensity,
Γ, at a specific site will exceed the value, γ, assuming the Poissonprocess, is
n

k=1

k=1

(6)

in which n is the number of potential earthquake sources in theregion of a site, vk the earthquake occurrence rate in source k withupper and lower boundary magnitudes of muk and mlk, and qk (γ)
the probability that the random earthquake intensity, G, will
exceed the given intensity, γ, given that an earthquake occurs insource k.
muk

ruk

lk

lk

q k (γ) =∫m ∫r P(Γ>γm, r) fMK (m) fRK (r) dmdr

(

(8)

)

The hazard curve is obtained by calculating p0 from Eq. (6) for
various values of δγ, allowing determination of the value γ0 (p0)of the intensity parameter corresponding to a specified p0.
Let x represent any ground motion parameter being discussed.
Assume that it is represented as a function of earthquake magnitude, m, and distance r.
(9)The conditional mean of x for source k, given that Γ >γ0(p0) is

3. PROBABILISTIC SEISMIC HAZARD ANALYSISn

P(Γ>γm,r )= P(U・γE (m, r ) >γ)γ=P U>γE (m, r )x =φ(m,r)

The maximum credible earthquake magnitude of each active
Philippine fault was determined by substituting the rupture lengthin Eq. (5). The recurrence times of expected maximum magnitudes were determined by Slemmons (1978) method.

p 0 =1−exp｛−Σ vk qk (γ) ｝=~Σvk qk (γ)

39

xk(p0)=E［xΓ>γ0(p0)∩Ek ］=∫M∫Rφ(m,r)fM,RΓ>γ (p )(m,r)drdm
0 0
γ(p )
= 1 ∫M∫Rφ(m,r)P(U> 0 0 ) fMK(m)fRK(r)drdm
qk (γ0)γE (m,r)(10)

in which Ek represents the earthquake that occurs in source k, andfM,R│Γ>γ0(p0)(m,r) the conditional joint probability density function of the magnitude and distance, given that Γ>γ0(p0). When all
potential earthquake sources are considered, the conditional meanof x isnx(p0)=

xk(p0)vk qk(γ0)Σ
k=1nvk qk(γ0)Σk=1
nx(p0)=γ(p )vkΣ
φ(m,r)P (U> 0 0 ) fMk(m)fRk(r)drdm
M∫
R
k=1 ∫
γ(m,r)
E

n

γ(p )

(11)

vk
Σ
P(U> 0 0 ) fMk(m)fRk(r)drdm
M∫
R
k=1 ∫
γ(m,r)
E

The conditional mean of the magnitude, mk (p0), and that of the
distance from the seismic source zone k, rk (p0), respectively are
given by Eqs. (12) and (13), and are referred to as the hazard-consistent magnitude and distance (Kameda and Nojima, 1988):
γ0(p0)m (p0 )=

∫M∫R m・P(U>γE (m,r) ) fMk(m)fRk(r)drdm∫M∫R P(U>

γ0(p0)
f (m)fRk(r)drdm
γE (m,r) ) Mk(12)

γ0(p0)

rk (p0 )=∫M∫R r・P(U >γE (m,r) ) fMk(m) fRk(r)drdm
γ0(p0)∫M∫R P(U>γE (m,r) ) fMk(m) fRk(r)drdm

(13)

(7)

in which fMk (r) is the probability density function of magnitude min source k, fRk (r) the probability density function of distance r(upper and lower value= ruk, rlk ) in source k, and P(Γ>γ｜m,r ) the
probability of (Γ>γ) for a given m and r. When uncertainty inthe attenuation formula of peak ground motion is involved, theattenuation rule Γ=γE (m,r) is given by Γ=U・γE (m,r), in which
U is the lognormal variate representing attenuation uncertainty
with a median of 1. 0 and coefficient of variation δγ.
This gives

3.2 Seismic hazards from fault sources
The expected maximum earthquake magnitude and shortest
distance from the site to the fault were assumed to be the parameters that would cause the fault to produce a seismic hazard. The
expected maximum earthquake magnitude from active fault MkF,
obtained deterministically, is discussed in section 2.3. To obtainthe seismic hazard caused by a fault, the qk (γ) given in Eq. 7 ismodified to:
qkF (γ)=P(Г>γMkF,RkF )

(14)

40

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

in which MkF is the expected maximum magnitude for fault k, andRkF the shortest distance from fault k to the site:
P (Γ>γMkF,RkF)=P (U >γ)γE (MkF, RkF )(15)

Let x represent the ground motion parameter due to the maximum
earthquake magnitude from fault k. It is a function of MkF and RkF;
xkF =ψ(MkF,RkF )(16)

The ground motion parameter, xkF, for fault k, given that Γ> γ0 (p0)isxkF (p0)=E[xkF Γ>γ0 (p0)∩EK]=

1
qkF(γ0)ψ(MkF,RkF )P ( U>

γ0(p0))γE (MkF, RkF )(17)

When all potential fault sources are considered, the conditionalmean of xkF isnF

x F(p0 )=xkF(p0)・vkF・qkF(γ0)
Σ
k=1
nF

vkF・qkF(γ0)Σ
k=1
γ0(p0)nF=

ψ(MFk ,RkF )・vkF・P (U >)
ΣγE(MkF, RkF )k=1
nF

γ0(p0)
vk F・P (U >Σ)
k=1
γE (MkF, RkF )(18)

in which vkF is the occurrence rate per year of MkF. Combining theeffects of both the historical earthquakes and nF number of active
faults, the conditional mean of x(p0) isnx( p0 ) =vk
Σ∫M∫Rφ(m,r)P(Γ>γ0(p0))fMk(m)fRk(r)drdm+
k=1
n

vk
Σ
∫M∫RP(Γ>γ0(p0))fMk(m)fRk(r)drdm+
k=1
nF

vkFψ(M F,R F)・P(Γ>γ(p ))
Σ
k
k
0 0
k=1
nF

vkF・P(Γ>γ(p ))

Σ

k=1

0

0

Fig. 5(19)

Seismic hazards corresponding to a moderate annual exceedance
probability (p0), are dominated by the contribution from historicalearthquakes, whereas those for a very low annual exceedance
probability is dominated by the contribution from fault sources.
The historical earthquake data used coveres earthquakes from 1907
to 1998. Historical earthquakes associated with the rupture ofactive faults, other than the 1990 Central Luzon earthquake, are
not included. Maximum credible earthquake magnitudes from
active faults show a minimum recurrence interval of several hundred years. Historical events covered by the data are assumed not
to be associated with this known active faults.
3.3 Attenuation formula for rock surface ground motions
Sugito et al. (2000) developed a database of modified strong
motion records for engineering foundation levels with shear wave
velocities of 500-600 m/sec using the major Japanese strong
motion records. These records obtained on deposit sites were converted to the equivalent free rock level surface motion by the modified equivalent linearization method for the response analysis oflayered ground, the FDEL, developed by Sugito (1995). Fig. 5
shows the scattergrams of the database for 118 components of rocksurface ground motion time histories that was used for regression
analysis in order to develop the attenuation formula for rock surface ground motion.
Based on this database, linear regression analysis was performed to formulate the attenuation formula for peak ground acceleration (Amax) and effective ground acceleration (Ae). Herein, theground motion parameter, Ae, used in the JMA Seismic Intensity
scale, IJMA, is dealt with. Parameter Ae, called 'effective acceleration', is obtained from filtered acceleration time histories. The
JMA seismic intensity IJMA is scaled in
IJMA = 2・log10 Ae +0.94
where:IJMA = seismic intensity (JMA scale)
Ae = effective peak acceleration(20)

According to the definition of Ae by the JMA, its effective acceleration is determined from the vector synthesis of three orthogonalcomponents of ground acceleration time histories obtained fromthe three components of the filtered acceleration time histories.
Here only Ae determined from a single component of the time history is dealt with, because the dataset for rock surface groundmotion does not include vertical component time histories.

Scattergrams of the modified rock-surface strong motion dataset

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

The database is in JMA magnitude scale, MJ, therefore theempirical formula for converting MJ to MS, proposed by Hayashi
and Abe (1984) and given in Eq. (21) is used.

Table 3.

MS = 1.27・MJ -1.83

41

(21)

Linear regression analysis was performed on the dataset given
in Table 3 to formulate the attenuation formula for rock surface

Datasets of modified rock-surface strong motion records from Japanese earthquakes

42

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

ground motion. The resulting relationships for rock surface peakground acceleration (Amax) and the effective ground acceleration(Ae) attenuation with the coefficients of variation are given in
Table 4. The dataset used to formulate rock level ground motion

Table 3.

attenuation relationships has the minimum hypo-central distance of
20 kilometers. Fig. 5 shows the attenuation curves for magnitudes
MS=8.0, 7.0, 6.0, and 5.0.

Datasets of modified rock-surface strong motion records from Japanese earthquakes (continued)

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

3.4 Seismic hazard analysis of the Philippines
A seismic hazard analysis that incorporated the effects of bothactive faults and historical earthquakes was made for the entire
land area of the country. Totally, 123,727 points were analyzed;
equivalent to a grid size of 1.4 kilometers. The historical earthquake information included only those data for focal depths of lessthan 100 kilometers. The average focal depth of historical earthquakes with magnitudes greater than MS=5.0 is 25.4 kilometers.
When historical earthquakes are categorized as land and sea
events, the respective average focal depths become 21.7 and 27.0
km. Most of the deeper events were located under the sea far fromthe main islands. Assuming a uniform depth equal to the averagevalue of the total underestimates the hazard because most inland
events have focal depths that are less than the average for all thedata. In the analysis, a conservative assumption of a 20 kilometer
focal depth was used to calculate the seismic hazards. The expected earthquake peak ground motion parameters for occasional (100year recurrence period) and rare (475- year recurrence period)
events for all the land areas of the country were calculated. Figs. 6
and 7, respectively show the expected peak ground accelerations
Table 4.

Fig. 643

for the 100- and 475-year recurrence periods.
The strong motion records in Japan, used to formulate theattenuation relationships, are earthquake intensity records based on
the JMA scale. The attenuation relationship for effective groundaccelerations, given in Eq. 23 was used. As ground accelerations
are related to earthquake intensities, Eq. 20 was used to convert theeffective ground accelerations to the equivalent JMA seismic
intensity. The expected seismic intensities on the JMA scale forthe 100- and 475-year recurrence periods are shown in Figs. 8 and
9. A graphical correlation of the JMA and MMI intensity scales isshown in Fig. 10.
Locations of the three major Philippine cities: Manila, Cebu,
and Davao are shown in Fig. 3. Islands shown without color on
the map (an indication of seismic hazard) belong to aseismic areas
where no analysis was done. Results show that the eastern
Philippines has the highest seismic hazard. These sites are locatedin zones with a high occurrence rate due to movement of thePhilippine plate whose western edge runs along the eastern side of
the Philippines. Zones 14 and 16 mainly contributed to the maximum seismic hazard in and around the areas. The expected peak

Attenuation formula for rock surface ground motion

100-year-recurrence peak ground acceleration map (historical earthquakes and active faults)

44

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

Fig. 7475-year-recurrence peak ground acceleration map (historical earthquakes and active faults)

Fig. 8100-year-recurrence JMA Seismic Intensity map (historical earthquakes and active faults)

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

ground acceleration for the 100-year recurrence period has a maximum value of 257 gal and that for the 475-year recurrence period
468 gal. The expected seismic intensities on the JMA scale for the
100- and 475-year recurrence periods respectively have the maximum values of 4.9 (VIII in MMI) and 5.5 (IX in MMI). All the
maximum values are located inside zone 14. No analysis wasmade of the western most side of the Philippines where there havebeen few and scattered historical earthquakes.
The 100-year recurrence peak ground acceleration map compiled for this study is compared with the results of Molas andYamazaki (1994). In both studies, relatively high seismic hazards
are present for eastern Mindanao Island. There are slight differences in the results for the seismic hazards of Luzon. From Molas

Fig. 9Fig. 10and Yamazaki’s 100-year recurrence peak ground acceleration
map, areas surrounding Baguio City, which experienced a destructive earthquake in 1990, have an Amax of 200 gal or more, whereas
other Central Luzon areas and the Metro Manila area have an Amaxof less than 100 gal. Clusters of high peak ground accelerations ofas much as 600 gal also were found in their study. In our study, auniform 100-year recurrence peak ground acceleration ranging
from 180 – 199 gal is expected in Baguio City, Central Luzon
island, and Metro Manila. The maximum inland 100-year peakground acceleration is only 250 gal. One factor contributing to thedifferences in the results of the two studies is the different sourcezones used. The analysis done by Molas and Yamazaki (1994), theseismic hazard was calculated by treating a circular area with a

475-year-recurrence JMA Seismic Intensity map (historical earthquakes and active faults)

Graphical correlation between the Modified Mercalli(MMI) and JMA intensity scales (ATC-13, 1985)

45

Fig. 11Comparison of peak ground acceleration attenuation with
distance

46

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

radius of 250 km around the site as the seismogenic zone. In our
analysis, the seismogenic source zones were fixed prior to making
the hazard analysis. Another factor is the difference in the attenuation relationships used in the studies. The attenuation formula forpeak ground acceleration that they used was reported by
Fukushima and Tanaka (1991). A comparison of the peak groundacceleration attenuation relationships used in our and Molas andYamazaki’s studies is shown in Fig. 11.
4. HAZARD-CONSISTENT STRONG MOTION TIMEHISTORIES FOR THE MAJOR PHILIPPINE CITIES
4.1 Strong motion prediction on a rock surface
Sugito, et al. (2000) developed a strong motion prediction
model based on 118 components of a modified rock surface strong
motion dataset obtained from Japanese accelerograms (Table 3).
Their simulation model was developed for motion on stiff groundwith a shear wave velocity of v s=500~600 m/sec. This stiff
ground is called a "free rock surface". In their model, by use of agiven magnitude and hypo-central distance, strong motion time
history can be simulated. In that strong motion prediction model,
the earthquake acceleration with non-stationary frequency content
isand hypo-central distance, R. Estimation formulas for the parameters which were modeled as a function of earthquake magnitudeand hypo-central distance, as well as for the frequency f, are given
in Table 5. Ground motion time history with non-stationary frequency contents can be simulated for a given earthquake magnitude and hypo-central distance. Simulated rock surface groundmotions for two combinations of magnitude and hypo-central distance are shown in Fig. 12. The ground motion duration clearly is
longer for case (a), and is a typical characteristic of ground motion
time history.
4.2

Strong motion simulation based on hazard-consistentearthquake parameters

Seismic hazard analysis was performed for the three biggest
cities in the Philippines: Manila, Cebu and Davao. Figure 13
shows the peak ground acceleration, Amax, hazard curves for thesecities. The hazard curves were determined by combining the contributions of the various seismogenic source zones and active
faults. Clearly, Cebu has the least Amax hazard. The peak groundacceleration hazard curves for Manila and Davao indicate that Amax
<144 gal has a higher annual occurrence probability in Davao,
whereas Amax>144 gal has a higher probability in Manila. This is
attributed to the differences in the properties of the seismogenicmx (t)=Σ√4π・Gx (t,2πfk)Δf・cos(2πfkt+φk)

(24)

k=1

Table 5.

Estimation formula for strong motion prediction model parameters (Sugito, 2000)

in which √Gx (t,2πfk) is the evolutionary power spectrum (Kameda,
1975) for time t and frequency fk,φk the independent random phaseangles distributed over 0~2π, and m the number of superposed harmonic components. The upper and lower boundary frequencies, fu
and fl, are fixed as fu = 10.03 Hz and fl = 0.13 Hz, and m and Δf are
fixed as m = 166 and Δf = 0.06 Hz. The following time-varying
function is adopted for the model of √Gx (t,2πfk) ;t- t (f )t- t (f )ppsexp(1- s ) ;t > ts( f )√Gx(t,2πf ) =αm( f ) t (f)
t (f )(25)

in which ts and tp respectively are the starting time and duration
parameter, and αm(f) is the intensity parameter which represents
the peak value of √Gx (t,2πfk). For each individual frequency, theseparameters have been scaled as a function of the magnitude, M,

Fig. 12

Simulated rock surface ground motions for two combinations of magnitude and hypo-central distanceSTRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

zone locations of the two cities. Zone 10, in which Manila is located, has both a lower occurrence rate and b-value than zone 23, in
which Davao is located, indicative that Davao has more earthquakes due to its higher occurrence rate. The maximum earthquake magnitude in zone 10 (MS=7.7), however, is higher than inzone 23 (Ms=7.4). Moreover, the b-value for zone 10 is much

lower than that for zone 23; therefore, high magnitude earthquakes
are more likely to occur in the Manila area than in Davao. The
high Amax has a higher annual occurrence probability in Manila thanin Davao, whereas the opposite is true for the low Amax. Seismic
hazard contributions from various source zones were determined,
and the seismic hazards from source zone locations shown to dominate the contributions of the three cities, contributions from outside source zones in all cases being negligible (Fig. 14). Becauseof this, it was decided to determine the hazard-consistent magnitude and hypo-central distances of these three cities based only on
their respective zone locations. Manila, Cebu, and Davao respectively are located inside zones 10, 18, and 25. Their hazard-consistent magnitudes and hazard-consistent hypo-central distances
are shown in Fig. 15. From Figs. 14 and 15, hazard-consistentmagnitudes and the hypo-central distances of these three major
Table 6.

Fig. 13

Hazard-consistent earthquake parameters

Peak ground acceleration hazard curves for Manila, Cebu, and
DavaoFig. 14

Fig. 15

47

Hazard contribution curves for the three major Philippines cities

Hazard-consistent magnitude and hypo-central distance curves for the three major Philippines cities

48

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

Fig. 16

Simulated rock surface strong motion for a 100-year-recurrence earthquake event.

STRONG MOTION SIMULATION FOR THE PHILIPPINES BASED ON SEISMIC HAZARD ASSESSMENT

Fig. 17

Simulated rock surface strong motion for a 475-year-recurrence earthquake event.

49

50

R. F. TORREGOSA, M. SUGITO AND N. NOJIMA

Philippine cities for recurrence periods of 100 and 475 years were
determined (Table 6).
Results indicate that Manila has a much higher hazard-consistent magnitude than Cebu or Davao. For the recurrence period of
T=100 years, the expected magnitude for Manila is M S =6.8
(MJ=6.8), whereas for Cebu and Davao respectively it is MS=5.7(M J=5.9) and M S=6.0 (M J=6.2). For the recurrence period of
T=475 years, the expected magnitude for Manila is MS=7.1(MJ=7.0), whereas for Cebu and Davao respectively it is MS=5.9(MJ=6.1) and MS=6.5 (MJ=6.5). These hazard-consistent magnitudes depend on the properties of the zones in which the cities arelocated. Manila has a much bigger hazard-consistent magnitude
than Cebu or Davao because the b-value in zone 10 is much smaller than the values in zones 18 and 23. The b-value is not the only
factor, however. If we look at zones 18 and 23, the former has aslightly lower b-value, but Cebu has a lower expected magnitude
than Davao. This is because the maximum magnitude at zone 18 is
only 6.7, whereas in zone 23, it is 7.4. This is why Davao has ahigher expected magnitude than Cebu.
For the recurrence period of T=100 years, the expected hypocentral distance for Manila is 40.1 kilometers, whereas for Cebu it
is 32 kilometers and for Davao 30.3 kilometers. For rare eventswith the recurrence period of T=475 years, the expected hypo-central distance for Manila is 32.2 kilometers, for Cebu 28.8 kilometers and for Davao 28.9 kilometers. The importance of solving thehazard-consistent magnitude and distance is shown by the use of
these parameters to simulate strong motion time histories. Groundmotion time histories were simulated by inserting these parametersin the strong motion prediction model described in section 4.1.
On the basis of the hazard-consistent magnitude and hypocentral distance, the strong motions corresponding to 100-yearand 475-year-recurrence periods were simulated for Manila, Cebu,
and Davao. Simulated strong motions for occasional events or the
100-year recurrences for Manila, Cebu and Davao are shown in
Fig. 16. The simulated strong motions for Manila, Cebu andDavao gave respective Amax values of 190.8, 98.4, and 125.9 gal;
Vmax values of 13.4, 5.6, and 7.7 cm/sec; and Dmax values of 3.4, 0.8,
and 1.7 cm. Response spectra for different percentages of damping are shown. The ground motion intensity in Manila, based on
the Modified Mercalli Intensity scale, is VII, whereas for Cebu it is
VI and for Davao VI in MMI. For rare events corresponding to arecurrence time of 475 years, strong motions for each city also
were simulated(Fig. 17): for Manila Amax of 343.5 gal, Cebu 96.2
gal, and Davao 212.3 gal and respective Vmax values of 24.6, 11.3,
and 14.7 cm/sec; and Dmax values of 7.4, 1.7, and 2.3 cm. The
ground motion intensity for Manila is VIII MMI, and for Cebu andDavao, respectively VI and VII in MMI. The simulated strong
motions are rock surface ground motions, soil conditions not being
considered. Ground motion amplification for different soil types isbeyond the scope of this study.
5.

CONCLUSIONS

The major conclusions obtained are
1. In the systematic seismic source zoning done for thePhilippines, based on the occurrence rates of historical earthquakes, totally 27 seismic source zones were designated for seismic hazard analysis. No seismic source zones were assigned in thewestern portion of the country which is known to be aseismic.
2. In the seismic hazard analysis done for the Philippines, basedon historical earthquakes and active faults, 123,727 points wereanalyzed equivalent to a grid size of 1.4 kilometers. Results
showed that the eastern portion of the country is under muchgreater seismic hazard due to movement of the Philippine Trench.
Seismic hazard analyses also were made for the three major cities
Manila, Cebu, and Davao, and the hazard-consistent earthquake
magnitude and hypocentral distance for each city calculated.
3. Strong motion time histories based on the hazard-consistentmagnitudes and hypocentral distances corresponding to 100- and475-year recurrence periods for the three major Philippine cities
were simulated. Of these cities, the capital, Manila, has the highest
seismic hazard followed in order by Davao and Cebu. The
methodology for simulating strong ground motion based on seismic hazards can be used for the earthquake-resistant design ofstructures. Work on amplification corrections for the various geological conditions in the Philippines is in progress.
ACKNOWLEDGMENTS
We thank Mr. Yoshinori Furumoto of Gifu University forproviding the modified rock surface strong motion records.
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