Active tear faulting in Hsinchu, Taiwan: A potential threat to Taiwan’s
, Wei-Hau Wang
, Chien-Hsin Chang
, Strong Wen
, Wei-Jer Wu
Department of Earth and Environmental Sciences, National Chung Cheng University, Chia-Yi, Taiwan
Seismological Observation Center of the Central Weather Bureau, Taipei, Taiwan
National Center for Research on Earthquake Engineering, Taipei, Taiwan
Received 22 November 2014
Received in revised form 27 February 2015
Accepted 11 March 2015
Available online 19 March 2015
Two unusual earthquake swarms struck Hsinchu County in northern Taiwan, near the Hsinchu Science
and Industrial Park (HSIP), in 2012 and 2014. In this study, we analyze the focal mechanisms and conduct
stress inversion for these swarms and three earthquake clusters located between them. Our results show
that both swarms were dominated by right-lateral strike-slip events along a prominent lineation in NW
direction. These earthquake ruptures may occur along two previously unrecognized tear faults as they
were clearly associated with structural bends in the area. In between, NNE–NE-striking, high-angle
reverse-faulting events with left-lateral strike-slip motions were dominant. The faults associated with
these events may have originated as horse blocks in a strike-slip duplex bounded by the two tear faults
that later rotated clockwise, resulting in bookshelf faulting. Our results suggest the Hsinchu Science and
Industrial Park could be under threat of these two nearby tear faults. As the Hsinchu Science and
Industrial Park creates about 36% of Taiwan’s total trade surplus, our ﬁndings urge innovative thinking
for hazard mitigation in Hsinchu County to reduce the potential impact on Taiwan’s economy.
Ó2015 Elsevier Ltd. All rights reserved.
Earthquake swarms are special types of seismicity that do not
follow mainshock–aftershock sequences or obey Omori’s law
(Hainzl, 2003). Earthquake swarms are often associated with vol-
canic activity due to the movement of magma at depths (Aoki
et al., 1999; Hayashi and Morita, 2003; Roman and Cashman,
2006). However, non-volcanic earthquake swarms have also been
found at plate boundaries (Tryggvason, 1973) or in the interior of
plates (Lopes et al., 2010; Fischer et al., 2014). A variety of mecha-
nisms have been proposed for the generation of non-volcanic
earthquake swarms, which include intrusion of ﬂuid into a fault
zone (Hainzl, 2004), earthquake triggering by aseismic creep or
remote earthquakes (Husen et al., 2004; Prejean et al., 2004;
West et al., 2005; Lohman and McGuire, 2007), and stress release
before a mainshock (Gao and Crampin, 2004). Because earthquake
swarms sometimes act as precursors before the occurrence of a
strong earthquake or volcanic eruption (Ramos et al., 1999;
Holtkamp and Brudzinski, 2011; Paudyal et al., 2011; Umakoshi
et al., 2011), studying the characteristics of earthquake swarms is
an important task for seismologists to gain better insight into tem-
poral variations in the stress ﬁeld and hopefully reduce potential
disasters. In this study, we investigate two unusual, non-volcanic
earthquake swarms that struck Hsinchu County (HCC) in northern
Taiwan in June 2012 and February 2014 (Fig. 1). The objectives of
this study are to understand why the earthquake swarms occurred
at these two particular locations and to determine their tectonic
The heavily populated Hsinchu City (HC) is located on the
Western Coastal Plain a few kilometers away from the toe of the
Taiwan mountain belt, and is considered to be the center of
Taiwan’s high-tech industry because the Hsinchu Science and
Industrial Park (HSIP) is established there (Fig. 1). The HSIP is
one of the world’s most signiﬁcant centers for semiconductor
manufacturing, especially wafers. The annual production value of
the HSIP is ca. 34 billion US dollars that is nearly 36% of Taiwan’s
total trade surplus, which makes it important not only for the
national economy but also for the global semiconductor supply.
However, this high-tech industry is extremely vulnerable to
earthquakes. The earthquake hazard of HCC is expected to be
low, owing to its relatively low seismicity and convergence rate
1367-9120/Ó2015 Elsevier Ltd. All rights reserved.
Corresponding author at: Department of Earth and Environmental Sciences,
National Chung Cheng University, 168 University Road, Min-Hsiung Township,
Chiayi County 62102, Taiwan. Tel.: +886 5 27 20411; fax: +886 5 272 0807.
E-mail addresses: email@example.com (Y.-L. Yeh), firstname.lastname@example.org
(W.-H. Wang), email@example.com (C.-H. Chang), firstname.lastname@example.org
(S. Wen), email@example.com (W.-J. Wu).
Journal of Asian Earth Sciences 106 (2015) 229–237
Contents lists available at ScienceDirect
Journal of Asian Earth Sciences
journal homepage: www.elsevier.com/locate/jseaes
Fig. 1. Earthquake swarms and geological map of the study area (after the Central Geological Survey, MOEA, 2000). The solid magenta lines indicate the fault traces. The light
blue solid squares indicate the location of Hsinchu City (HC), the Hsinchu Science and Industrial Park (HSIP). The spatial distributions of the 2012 (denoted by S1) and 2014
(denoted by S2) earthquake swarms are indicated by solid black circles. The major shock of each swarm is indicated by a solid red star. (For interpretation of the references to
color in this ﬁgure legend, the reader is referred to the web version of this article.)
230 Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237
compared with areas located farther south in Taiwan (Rau et al.,
2008; Hsu et al., 2009). Nevertheless, a magnitude 7.1 earthquake
with a focal depth of 5 km struck the Hsinchu–Taichung area in
1935, causing extensive damage and killing 3279 people (Lin
et al., 2013). Then, in 2012 and 2014, two earthquake swarms
occurred. In particular, the 2014 earthquake swarm was very close
to HC. These earthquake swarms emphasize the importance of
assessing the potential earthquake threat in this area because pre-
vious studies have proposed that an aperiodic earthquake swarm
can serve as a precursor to a larger mainshock (Singh et al.,
1982; Shanker et al., 2010).
To better understand the characteristics of these swarm earth-
quakes, in this research we examine the temporal variations of
seismic activity and analyze the corresponding b-values of these
two earthquake swarms. We also investigate the focal mechanisms
of events with local magnitudes greater than 3 for both swarms
using P-wave ﬁrst-motion polarities recorded by the Central
Weather Bureau Seismic Network (CWBSN), the Taiwan Strong
Fig. 2. The conﬁguration of seismic networks used in this study, including the CWBSN (solid triangles), the TSMIP (inverted triangles), and broadband stations (circles).
Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237 231
Motion Integrated Project (TSMIP) (Shin et al., 2003), and broad-
band seismic networks. Fig. 2 shows the conﬁguration of these
seismic networks. Next, we use ‘‘FPFIT’’ software (Reasenberg
and Oppenheimer, 1985) to obtain the optimal fault plane solu-
tions. In addition, we conduct stress inversion to gain deeper
insight into the regional stress ﬁeld and possible fault orientations,
as well as the relative fault motions for the two earthquake swarms
and earthquake clusters located between them. With these ﬁnd-
ings, we discuss the implications of regional seismotectonics and
assess the potential earthquake threat in this area.
2. Geological setting and the 2012 & 2014 earthquake swarms in
the Hsinchu area
Geographically, our study area covers the Western Foothills
(WF) and Coastal Plain (CP). The major rock formation in the WF
in our study area is composed mainly of Miocene sedimentary
rocks in the low hills and Oligocene to Eocene formations in the
hinterland, while the CP to the west is mainly covered by
Holocene alluvial deposits with some Plio-Plestocene molasse.
Five major faults are in the vicinity of HC according to geological
Fig. 3. (a) Daily histogram of the seismic activity of the S1 earthquake swarm from June 1 to 30, 2012, (b) b-value estimated for all the events occurred in June, 2012, and (c) b-
value on June 13, 2012. The black solid line denotes the best ﬁtting line. ‘‘S.D.’’ represents standard deviation.
232 Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237
and geophysical surveys (Fig. 1). These faults are the Dohuanping
Fault (DHPF), Hsinchen Fault (HCNF), Dapindi-Peipu Fault (DPD-
PPF), Chiudong Fault (CDF), and Shihtan Fault (STF). The STF was
associated with the great Hsinchu–Taichung earthquake of 1935.
It is worth noting that the DPD-PPF, denoted by the thick black line
in Fig. 1, represents a prominent geological boundary between the
WF and the CP. The light blue squares depict the locations of HC
and the HSIP. The two earthquake swarms that occurred in 2012
(denoted by S1) and 2014 (denoted by S2) are depicted in Fig. 1;
the largest events in each swarm are indicated by a red star.
Both swarms exhibited a distinct NW lineation that was sub-
parallel to the Touchien River. The 2012 earthquake swarm was
located in Genshih Township; the magnitudes of the swarm
earthquakes ranged from 2.9 to 4.6 with focal depths of 9.5 to
11.7 km. The 2014 earthquake swarm occurred in Hengshan
Township. This earthquake swarm consisted of events with M
ranging from 1.0 to 3.4 and focal depths of 6.6 to 11.8 km.
Fig. 3a illustrates the daily variations of seismic activity for 2012
earthquake swarm. A temporal burst of earthquakes with 78 events
occurred on June 13, 2012 clearly outnumbered the seismic activity
on the other days in June. The bell-shaped distribution of earth-
quake events with time agrees well with the ‘‘Type III’’ (swarm)
time histogram deﬁned by Mogi (1963). We also calculated the
corresponding b-values by employing the software package ZMAP
(Wiemer, 2001). Fig. 3b depicts that the b-value for all the earth-
quakes occurred in June, 2012 was 0.74. However, on June 13,
2012, the b-value increased to 2.05 ± 0.07 (Fig. 3c), a typical value
for ﬂuid-driven earthquake swarms (e.g., Jakobsdóttir et al., 2008;
Bachmann et al., 2012). This ﬁnding implies that the 2012 earth-
quake swarm may result from a short-lived ﬂuid pulse. As for the
S2 earthquake swarm, it lasted for three days (from February 5 to
7, 2014) with comparable daily events ranging from 8 to 12
(Fig. 4a). Other than these days and February 11, this area was seis-
mically quiescent. The b-value for S2 swarm earthquakes is esti-
mated to be 0.68 ± 0.1 (Fig. 4b). This b-value is much smaller than
that for S1 earthquake swarm on June 13, 2012 and does not deviate
much from the b-values observed in active tectonic regions, which
is in the range of 0.5–1.5 and often close to 1. Low b-value earth-
quake swarms have been reported in continental rift zones (Seht
et al., 2008) and along high-stressed faults (Farrel et al., 2009).
Fig. 4. (a) Daily histogram of the seismic activity of the S2 earthquake swarm from February 1 to 29, 2014, (b) b-value for the events occurred from February 5 to 7, 2014. The
black solid line denotes the best ﬁtting line. ‘‘S.D.’’ represents standard deviation.
Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237 233
The physics behind the low b-value for the S2 swarm, however, still
needs further investigations. Nevertheless, the distinct difference in
b-values for S1 and S2 swarms reﬂects the strength of the fault zone
medium and/or the state of stress in these two areas could be quite
3. Seismicity, focal mechanism, and stress inversion
Fig. 5 depicts the seismicity in HCC over the period from 1991
to 2014. These earthquakes were located by the Central Weather
Bureau using a 3D velocity structure derived by Wu et al. (2007).
Based on the spatial distribution of the seismicity, we divided
the study area into ﬁve sub-areas (indicated by solid white
quadrangles). Sub-areas A1 and A2 are the regions where earth-
quake swarms S1 and S2 occurred. In between these swarms,
three earthquake clusters occurred in sub-areas C1, C2, and C3.
We analyzed the source mechanisms in these ﬁve sub-areas
using the following two approaches: (i) determination of the
focal mechanisms using P-wave ﬁrst-motion polarities for events
with magnitudes greater than 3, and (ii) performing stress inver-
sion. We discuss details of the procedures in the following
3.1. Focal mechanisms obtained from P-wave polarities
We collected the P-wave ﬁrst-motion polarity readings (P-read-
ings) from seismic events with M
values greater than 3 (denoted
by red solid circles, Fig. 5) to avoid the ambiguity of P-readings
from small events. To obtain reliable focal mechanisms, we
selected events with more than ten P-readings to ensure good sta-
tion coverage. We employed the widely used ‘‘FPFIT’’ method to
determine the fault-plane solutions for the selected events. The
results are shown in Fig. 5.
Interestingly, the focal mechanisms indicated by the red focal
spheres for the largest events in the two earthquake swarms are
remarkably similar, i.e., right-lateral strike-slip motion on a NW-
striking fault plane sub-parallel to the lineation of the swarm seis-
micity. The largest shock in S1 had a fault-plane solution with
strike 125°, dip 75°and rake 162°, and the largest event in S2
had source parameters of strike 124°, dip 81°and rake 173°.In
fact, most events in sub-areas A1 and A2 were NW-trending
strike-slip faulting. Only one exception exhibited reverse faulting
in the sub-area A1 with the fault strike perpendicular to the
direction of regional compression. This event may have been trig-
gered by the surrounding strike-slip faulting, which caused a
reverse rupture in the thrust belt.
Fig. 5. The seismicity and focal mechanisms in HCC between 1991 and 2014. The study area is divided into ﬁve sub-areas: A1, A2, C1, C2, and C3 (each area is enclosed by a
solid white quadrangle). The stars represent the largest events in the 2012 and 2014 swarms. The focal mechanisms shown in the ﬁgure were obtained using P-wave
polarities for events with M
greater than 3 (denoted by solid red circles) in our study area. Note that most events were strike-slip faulting. The red focal spheres represent the
largest events in the 2012 and 2014 swarms, which were very similar. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web
version of this article.)
234 Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237
More interestingly, sub-area C3, which almost aligned with the
S1 lineation, was also dominated by NW strike-slip faulting analo-
gous to that observed in sub-area A1. This ﬁnding implies that the
2012 earthquake swarm and the earthquake cluster in sub-area C3
may belong to the same fault system despite a clear seismic gap
between them. In contrast, high-angle reverse faulting with left-
lateral slip motion was the dominant focal mechanism in the
sub-areas C1 and C2. In addition, normal faulting mechanisms
were found in sub-area C2. We interpreted this normal faulting
as secondary ruptures in a wrench fault system.
3.2. Stress inversion
To obtain an extensive view of the source mechanism in each
sub-area, we conducted stress inversion based on the method
derived by Robinson and McGinty (2000). This method incorpo-
rates the Coulomb failure criterion and employs composite P-wave
polarities from all earthquakes in a particular region to derive the
optimal stress ﬁeld and preferred fault orientation in that area.
Fig. 6 illustrates the stress directions and optimal fault ori-
entations derived from the stress inversions for each sub-area
and the entire study area. As we expected in sub-areas A1, A2,
was in the NNW direction and
was in the WSW
direction (for sub-area C3, it was in the ENE direction), correspond-
ing to the optimal focal mechanism of NW-striking right-lateral
strike-slip faulting. This fault strike closely coincided with the
lineation of both earthquake swarms shown in Fig. 1. The results
further conﬁrm earlier ﬁndings presented in the previous section.
However, the stress regimes in sub-areas C1 and C2 show that
was in the SSE direction and
was in the W–WNW direction.
The preferred fault orientations in these two sub-areas were
dominated by NNE–NE-striking high-angle reverse faulting with
left-lateral strike-slip motion. The optimal stress ﬁeld derived for
the entire study area indicates that the
axes were sub-
horizontal and oriented at 148°and 56°azimuths, respectively.
Our results suggest that the optimal focal mechanism in the study
area favored right-lateral strike-slip faulting along NW-striking
We have demonstrated that the 2012 and 2014 earthquake
swarms were caused by right-lateral strike-slip faulting and, as
shown in Figs. 5 and 6, the two NW-trending earthquake swarms
are perpendicular to the DPD-PPF, where distinct structural bends
are found. Our ﬁndings suggest that both swarms resulted from
ruptures along two previously overlooked NW-striking tear faults.
Earthquake swarms associated with tear faulting have also been
found in the Corinth Rift, Greece (Pacchiani and Lyon-Caen,
2010) and in the Gulf of Aquaba along the Dead Sea transform fault
(El-Isa et al., 1984). As the 2014 earthquake swarms extended over
a length of approximately 20 km, which is comparable to the
rupture length of the Tuntzuchiao fault during the great 1935
earthquake (Huang and Yeh, 1992), the potential threat due to
the movement of these two tear faults could be signiﬁcant.
Fig. 6. Map showing the principal stress directions and preferred fault plane in each individual sub-area. The great circles on either side of the diagram show the stress
orientations, where the plus signs denote individual re-samples that deﬁne the 95% conﬁdence limits for
, and the open circles for
. The overall optimal orientations of
are indicated by solid red and green circles. The trend and plunge of the principal stress vectors are labeled below the great circles. The focal spheres on the top and
bottom of the diagram show the optimal focal mechanisms for each sub-area and the entire study area. The strike (S), dip (D), and rake (R) of the preferred fault plane and slip
are labeled above each focal sphere. The blue focal sphere represents the optimal fault plane solution of the entire study area. (For interpretation of the references to color in
this ﬁgure legend, the reader is referred to the web version of this article.)
Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237 235
In addition, our results show that the major rupture type in
between these two tear faults is high-angle reverse faulting
accompanied by left-lateral strike-slip motion. The nature of
high-angle faults bounded by two tear faults implies that the
high-angle reverse faults may have originated as horses of a
strike-slip duplex, a common feature observed in many wrench
fault systems (Woodcock and Fischer, 1986; Jensen et al., 2011;
Nadim and Konon, 2012). Aside from that, two possible mecha-
nisms may be responsible for the left-lateral motion along these
high-angle faults. First, the oblique convergence with respect to
NNE-striking faults in sub-area C1 may result in such a relative
fault slip. However, this mechanism can hardly apply to the
faults in sub-area C2 because the optimal fault plane (striking
NE) in C2 derived from stress inversion is almost perpendicular
to the direction of the regional compression (in a NW direc-
tion). Alternatively, as we prefer, the earthquake clusters in
sub-areas C1 and C2 might reﬂect clockwise rotation of fault
blocks in these sub-areas due to right-lateral simple shear
between the two tear faults. The southward increase in
convergence velocity in our study area provides strong support
for this hypothesis (Rau et al., 2008). Such a scenario of book-
shelf faulting, as illustrated in Fig. 7, has been observed in vari-
ous tectonic regimes around the world (Mandl, 1987;
Tapponnier et al., 1990; La Femina et al., 2002; Green et al.,
As an earthquake swarm may sometimes lead up to a large
earthquake event (e.g., Srivastava and Dube, 1996; Evision and
Rhoades, 1999; Sharma et al., 2013), especially when the swarm
does not follow past patterns, the previously unseen earthquake
swarms in HCC can be of major concern despite their small magni-
tude. In addition, because the rupture of the 2014 earthquake
swarm is adjacent to the highly populated areas of HC and the
HSIP, the potential seismic threat is high. It is a matter of urgency
that more efforts are made to prepare for the potential seismic risk
and set up an appropriate earthquake early warning system in this
In summary, in this study, we discovered two previously unrec-
ognized tear faults located in Hsinchu County by analyzing the
focal mechanisms and stress ﬁelds of the 2012 and 2014 earth-
quake swarms. The tear faults correlated well with the bends of
the Dapindi-Peipu fault and geological formations. In addition,
we observed two NNE–NE-trending earthquake clusters between
these two tear faults. These earthquake clusters are likely asso-
ciated with reverse faulting with left-lateral strike-slip motions.
The faults themselves may have originated as horses in a strike-slip
duplex and later rotated clockwise to accommodate the right-
lateral shear motion of the two tear faults. As a result, bookshelf
faulting accompanied by left-lateral motion was observed. As this
complex wrench fault system has not been identiﬁed in previous
studies, the potential seismic hazard in the Hsinchu area may be
underestimated. This is especially true for the area along the
Touchien River where the 2014 earthquake swarm occurred.
Because the swarm events were in very close proximity to the
highly populated areas of Hsinchu City and the Hsinchu Science
and Industrial Park, we therefore urge that early warning systems
be set up and additional effort be placed on seismic mitigation
strategies for strong earthquakes in Hsinchu County to reduce
potential seismic risk.
Fig. 7. Schematic diagram illustrating the kinematics of bookshelf faulting.
236 Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237
The authors would like to thank the Central Weather Bureau,
Taiwan for providing us the earthquake catalog. We also thank
Ching-Yi Chiang for assistance with the artwork. We are indebted
to an anonymous reviewer for the constructive comments and sug-
gestions. This work was supported by the Ministry of Science and
Technology (MOST), Taiwan under Grant 103-2116-M-194 -009.
Aoki, Y., Segall, P., Kato, T., Cervelli, P., Shimada, S., 1999. Imaging magma transport
during the 1997 seismic swarm off the Izu peninsula, Japan. Science 286, 927–
Bachmann, C.E., Wiemer, S., Goert-Allmann, B.P., Wossner, J., 2012. Inﬂuence of
pore-pressure on the event-size distribution of induced earthquakes. Geophys.
Res. Lett. 39, L09302. http://dx.doi.org/10.1029/2012GL051480.
Central Geological Survey, MOEA, 2000. Taiwan Geological Map.
El-Isa, Z.H., Merghelani, H.M., Bazzari, M.A., 1984. The Gulf of Aqaba earthquake
swarm of 1983 January–April. Geophys. J. Roy. Astron. Soc. 78, 711–722.
Evision, F.F., Rhoades, D.A., 1999. The precursory earthquake swarm and the
inferred percursory quarm. NZ J. Geol. Geophys. 42, 229–236.
Farrel, J., Husen, S., Smith, R.B., 2009. Earthquake swarm and b-value
characterization of the Yellowstone volcano-tectonic system. J. Volcanol.
Geoth. Res. 188, 260–276.
Fischer, T., Horálek, J., Hrubcova, P., Vavryc
ˇuk, V., Bräuer, K., Kämpf, H., 2014. Intra-
continent earthquake swarms in West-Bohemia and Vogtland: a review.
Tectonophysics 611, 1–27.
Gao, Y., Crampin, S., 2004. Observations of stress relaxation before earthquakes.
Geophys. J. Int. 157, 578–582.
Green, R.G., White, R.S., Greenﬁeld, T., 2013. Motion in the north Iceland volcanic
rift zone accommodated by bookshelf faulting. Nat. Geosci. 7, 29–33.
Hainzl, S., 2003. Self-organization of earthquake swarms. J. Geodyn. 35, 157–172.
Hainzl, S., 2004. Seismicity patterns of earthquake swarms due to ﬂuid intrusion
and stress triggering. Geophys. J. Int. 159, 1090–1096.
Hayashi, Y., Morita, Y., 2003. An image of a magma intrusion process inferred from
precise hypocentral migrations of the earthquake swarm east of the Izu
peninsula. Geophys. J. Int. 153, 159–174.
Holtkamp, S.G., Brudzinski, M.R., 2011. Earthquake swarms in circum-Paciﬁc
subduction zones. Earth Planet. Sci. Lett. 306, 215–225.
Hsu, Y.-J., Yu, S.-B., Simons, M., Kuo, L.-C., Chen, H.-Y., 2009. Interseismic crustal
deformation in the Taiwan plate boundary zone revealed by GPS observations,
seismicity, and earthquake focal mechanisms. Tectonophysics 479, 4–18.
Huang, B.-S., Yeh, Y.T., 1992. Source geometry and slip distribution of the April 21,
1935, Hsinchu–Taichung, Taiwan earthquake. Tectonophysics 210, 77–90.
Husen, S., Taylor, R., Smith, R.B., Healser, H., 2004. Changes in geyser eruption
behavior and remotely triggered seismicity in Yellowstone National Park
produced by the 2002 M 7.9 Denali fault earthquake, Alaska. Geology 32,
Jakobsdóttir, S.S., Roberts, M.J., Guðmundsson, G.B., Geirsson, H., Slunga, R., 2008.
Earthquake swarms at upptyppingar north-east Iceland: a sign of magma
intrusion? Stud. Geophys. Geod. 52, 513–528.
Jensen, E., Cembrano, J., Faulkner, D., Veloso, E., Arancibia, G., 2011. Development of
a self-similar strike-slip duplex system in the Atacama Fault system, Chile. J.
Struc. Geol. 33, 1611–1626.
La Femina, P.C., Dixon, T.H., Strauch, W., 2002. Bookshelf faulting in Nicaragua.
Geology 30, 751–754.
Lin, D.-H., Chen, K.H., Rau, R.-J., Hu, J.-C., 2013. The role of a hidden fault in stress
triggering: stress interactions within the 1935 Mw 7.1 Hsinchu–Taichung
earthquake sequence in central Taiwan. Tectonophysics 601, 37–52.
Lohman, R.B., McGuire, J.J., 2007. Earthquake swarms driven by aseismic creep in
the Salton Trough, California. J. Geophys. Res., 112 http://dx.doi.org/10.1029/
Lopes, A.E.V., Assumpcao, M., do Nascimento, A.F., Ferreira, J.M., Menezes, E.A.S.,
Barbosa, J.R., 2010. Intraplate earthquake swarm in Belo Jardim, NE Brazil:
reactivation of a major Neoproterozoic shear zone (Pernambuco Lineament).
Geophys. J. Int. 180, 1303–1312.
Mandl, G., 1987. Tectonic deformation by rotation parallel faults: the ‘‘bookshelf’’
mechanism. Tectonophysics 141, 277–316.
Mogi, K., 1963. Some discussions on aftershocks, foreshocks and earthquake
swarms – the fracture of a semi-inﬁnite body caused by an inner stress origin
and its relation to the earthquake phenomena (3). Bulletine of Earthquake
Research, Institute University Tokyo 41, 615–658.
Nadim, A., Konon, A., 2012. Strike-slip faulting in the central part of the Sanandaj-
Sirjan Zone, Zagros Orogen, Iran. J. Struct. Geol. 40, 2–16.
Pacchiani, F., Lyon-Caen, H., 2010. Geometry and spatio-temporal evolution of the
2001 Agios Ioanis earthquake swarm (Corinth Rift, Greece). Geophys. J. Int. 180,
Paudyal, H., Shanker, D., Singh, H.N., 2011. Characteristics of earthquake sequence
in northern Himalayan region of South Central Tibet-Precursor search and
location of potential area of future earthquake. J. Asian Earth Sci. 41, 459–466.
Prejean, S.G., Hill, D.P., Brodsky, E.E., Hough, S.E., Johnston, M.J.S., Malone, S.D.,
Oppenheimer, D.H., Pitt, A.M., Richards-Dinger, K.B., 2004. Remotely Triggered
Seismicity on the United States West Coast following the Mw 7.9 Denali Fault
Earthquake. Bull. Seismol. Soc. Am. 94, S348–S359.
Ramos, E., Hamburger, M.W., Pavlis, G.L., Laguerta, E.P., 1999. The low-frequency
earthquake swarms at Mount Pinatubo, Philippines: implication for magma
dynamics. J. Volcanol. Geoth. Res. 92, 295–320.
Rau, R.-J., Ching, K.-E., Hu, J.-C., Lee, J.-C., 2008. Crustal deformation and block
kinematics in transition from collision to subduction: global positioning system
measurements in northern Taiwan, 1995–2005. J. Geophys. Res. 113, 1995–
Reasenberg, P., Oppenheimer, D., 1985. FPFIT, FPPLOT, and FPPAGE: FORTRAN
computer programs for calculating and displaying earthquake fault-plane
solutions. US Geol. Survey Open-File Rep., 85–739
Robinson, R., McGinty, P.J., 2000. The enigma of the Arthur’s Pass, New Zealand,
earthquake: 2. The aftershock distribution and its relation to regional and
induced stress ﬁelds. J. Geophys. Res., 105 http://dx.doi.org/10.1029/
Roman, D.C., Cashman, K.V., 2006. The origin of volcano-tectonic earthquake
swarms. Geology 34, 457–460.
Seht, M.I., Pleneﬁsch, T., Klinge, K., 2008. Earthquake swarms in continental rifts — a
comparison of selected cases in America, Africa and Europe. Tectonophysics
Shanker, D., Singh, H.N., Paudyal, H., Kumar, A., Panthi, A., Singh, V.P., 2010.
Searching for an earthquake precursor—a case study of precursory swarm as a
real seismic pattern before major shocks. Pure Appl. Geophys. 167, 655–666.
Sharma, S., Baruah, S., Sahu, O.P., Bora, P.K., Duarah, R., 2013. Low b-value prior to
the Indo-Myanmar subduction zone earthquakes and precursory swarm before
the May 1995 M 6.3 earthquake. J. Asian Earth Sci. 73, 176–183.
Shin, T.C., Tsai, Y.B., Yeh, Y.T., Liu, C.C., Wu, Y.M., 2003. Strong motion
instrumentation programs in Taiwan. In: Lee, W.H.K., Kanamori, H., Jennings,
P.C., Kisslinger, C. (Eds.), Handbook of Earthquake and Engineering Seismology.
Academic Press, pp. 1057–1062.
Singh, V.P., Singh, H.N., Singh, J., 1982. On the possibilities of premonitory swarms
for three sequences of earthquakes of Burma–Szechwan region. Tectonophysics
Srivastava, H.N., Dube, R.K., 1996. Comparison of precursory and non-precursory
swarm activity in peninsular India. Tectononphysics 265, 327–339.
Tapponnier, P., Armijo, R., Manighetti, I., Courtillot, V., 1990. Bookshelf faulting and
horizontal block rotations between overlapping rifts in southern afar. Geophys.
Res. Lett. 17, 1–4.
Tryggvason, E., 1973. Seismicity, earthquake swarms, and plate boundaries in the
Iceland region. Bull. Seismol. Soc. Am. 63, 1327–1348.
Umakoshi, K., Itasaka, N., Shimizu, H., 2011. High-frequency earthquake swarm
associated with the May 1991 dome extrusion at Unzen Volcano, Japan. J.
Volcanol. Geoth. Res. 206, 70–79.
Wiemer, S., 2001. A software package to analyze seismicity: ZMAP. Seismol. Res.
Lett. 72, 374–383.
West, M., Sanchez, J.J., McNutt, S.R., 2005. Periodically triggered seismicity at Mount
Wrangell, Alaska, after the Sumatra earthquake. Science 308, 1144–1146.
Woodcock, N.H., Fischer, M., 1986. Strike-slip duplex. J. Struct. Geol. 8, 725–735.
Wu, Y.M., Chang, C.H., Zhao, L., Shyu, J.B.H., Chen, Y.G., Sieh, K., Avouac, J.P., 2007.
Seismic tomography of Taiwan: improved constraints from a dense network of
strong motion stations. J. Geophys. Res. 112. http://dx.doi.org/10.1029/
Y.-L. Yeh et al. / Journal of Asian Earth Sciences 106 (2015) 229–237 237