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Hypocenter relocation of the aftershocks of the Mw 7.5 Palu earthquake (September 28, 2018) and swarm earthquakes of Mamasa, Sulawesi, Indonesia, using the BMKG network data

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On September 28, 2018, the Mw 7.5 earthquake occurred in Palu, Central Sulawesi, Indonesia. This earthquake produced strong tremors, landslides, liquefaction and a tsunami and caused thousands of fatalities and damaged houses and infrastructure. We have relocated 386 of the 554 Palu aftershocks by using the double-difference relocation method (hypoDD) from September 28 to November 22, 2018. The aftershock pattern is consistent with the crustal deformation in the area and generally shows that the events have a NW–SE trending of ~ 200 km in length and ~ 50 km in width. Most of the aftershocks are located to the east of the Palu-Koro Fault Line. Since November 2, 2018, there have been hundreds of swarm earthquakes in the area of Mamasa, West Sulawesi, which is about 230 km south of the city of Palu. Some of these earthquakes were felt, and houses were even damaged. We have relocated 535 of the 556 swarm earthquakes having a magnitude of M 2 to M 5.4. Our results show that the seismicity pattern has a dip that becomes shallower to the west (dipping at a ~ 45° angle) and extends from north to south for a length of ~ 50 km. We also conducted a focal mechanism analysis to estimate the type of fault slip for selected events of an M > 4.5 magnitude. Most of the solutions of the focal mechanism analysis show a normal fault type. This swarm earthquake probably corresponds to the activity of the fault in the local area.
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Supendietal. Geosci. Lett. (2019) 6:18
https://doi.org/10.1186/s40562-019-0148-9
RESEARCH LETTER
Hypocenter relocation oftheaftershocks
oftheMw 7.5 Palu earthquake (September
28, 2018) andswarm earthquakes ofMamasa,
Sulawesi, Indonesia, using theBMKG network
data
Pepen Supendi1,2,4*, Andri Dian Nugraha3,4, Sri Widiyantoro3,4, Chalid Idham Abdullah5, Nanang T. Puspito3,4,
Kadek Hendrawan Palgunadi6, D. Daryono7 and Samsul Hadi Wiyono7
Abstract
On September 28, 2018, the Mw 7.5 earthquake occurred in Palu, Central Sulawesi, Indonesia. This earthquake
produced strong tremors, landslides, liquefaction and a tsunami and caused thousands of fatalities and damaged
houses and infrastructure. We have relocated 386 of the 554 Palu aftershocks by using the double-difference relo-
cation method (hypoDD) from September 28 to November 22, 2018. The aftershock pattern is consistent with the
crustal deformation in the area and generally shows that the events have a NW–SE trending of ~ 200 km in length
and ~ 50 km in width. Most of the aftershocks are located to the east of the Palu-Koro Fault Line. Since November 2,
2018, there have been hundreds of swarm earthquakes in the area of Mamasa, West Sulawesi, which is about 230 km
south of the city of Palu. Some of these earthquakes were felt, and houses were even damaged. We have relocated
535 of the 556 swarm earthquakes having a magnitude of M 2 to M 5.4. Our results show that the seismicity pattern
has a dip that becomes shallower to the west (dipping at a ~ 45° angle) and extends from north to south for a length
of ~ 50 km. We also conducted a focal mechanism analysis to estimate the type of fault slip for selected events of an
M > 4.5 magnitude. Most of the solutions of the focal mechanism analysis show a normal fault type. This swarm earth-
quake probably corresponds to the activity of the fault in the local area.
Keywords: Aftershocks, Palu, Swarm earthquakes, Mamasa, Double-difference
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Introduction
On September 28, 2018, an Mw 7.5 devastating earth-
quake and tsunami affected the city of Palu in Central
Sulawesi, Indonesia. As of November 22, 2018, the Indo-
nesian Agency for Meteorology, Climatology, and Geo-
physics (BMKG) has recorded 554 aftershocks in this
area with a significant number of events having a mag-
nitude 3 with the use of a dense regional seismic net-
work. According to the BMKG catalog, the mainshock
occurred at 10:02:44 UTC and the epicenter was located
at 0.18° S; 119.85° E with a depth of 10km depth (Fig.1).
About 12min after the mainshock, a sequence of after-
shocks continued occurring until the final date that these
data were downloaded, which was November 23, 2018,
but even after that aftershocks still occurred. e shake
map from BMKG and the community reports indicate
that the earthquake was rated VII to VIII on the Modified
Open Access
*Correspondence: pepen_geophysics@yahoo.com
1 Geophysical Engineering Study Program, Faculty of Mining
and Petroleum Engineering, Institut Teknologi Bandung, Bandung 40132,
Indonesia
Full list of author information is available at the end of the article
Page 2 of 11
Supendietal. Geosci. Lett. (2019) 6:18
Mercalli Intensity (MMI) scale in Palu and the surround-
ing area.
According to the National Disaster Management
Authority (NDMA) report (http://bnpb.go.id/en), the
tsunami and liquefaction caused more than 4000 fatali-
ties. e geological map made by Watkinson (2011)
shows that the city of Palu consists of Holocene sedimen-
tary rock. Pramono etal. (2017) used the multichannel
analysis of surface waves (MASW) method to conclude
that the city of Palu and its surrounding area consist of
alluvium and soft soil. us, the damage caused by the
earthquake and the liquefaction was massive in the Palu
area. Gusman etal. (2019) showed that the tsunami was
caused by a combination of sudden ground and seafloor
changes due to the earthquake, along with landslides, and
a high tide at the time of the event.
e earthquake was generated by the strike-slip fault-
ing of the Palu-Koro Fault (Bao et al. 2019; Socquet
etal. 2019). e Palu-Koro Fault has a slip rate of about
42 mm/year, which was estimated by Global Position-
ing System (GPS) and slip rate modeling (Socquet etal.
2006). Daryono (2016) suggested that this fault includes
active faults with a slip rate of around 30–40mm yearly
and can potentially generate a co-seismic slip. As a result,
seismic hazard along Palu-Koro Fault segment in the
vicinity of a highly populated area is also increasing.
Interestingly, a month after the mainshock, a swarm
earthquake occurred in Mamasa, which is ~ 230 km to
the south of Palu (Fig.1). As of November 22, 2018, the
BMKG has recorded 556 events with a magnitude of
M > 2. ese were located in the area at an average depth
of 10km. Unfortunately, some of the earthquakes caused
damage to several houses and economic loss. However,
the source of these swarm earthquakes is still unclear:
whether they occurred due to known activity at currently
dormant volcanoes or a static triggering as a result of the
devastating Palu earthquake. erefore, this study aims
to relocate the aftershocks of the Palu earthquake and the
swarm earthquakes to obtain more precise hypocenter
locations, as well as to conduct a focal mechanism analy-
sis to estimate the fault type in the Mamasa area.
Fig. 1 Map of the study area. The red star depicts the Mw 7.5 mainshock; the green inverted triangles are the BMKG seismic station used in this
study; blue traces represent the Palu-Koro Fault; and red traces correspond to the other major crustal faults in the region extracted from Irsyam et al.
(2017). The black boxes show the map regions of Figs. 2, 3, 4, 5, 6, 8 and 9
Page 3 of 11
Supendietal. Geosci. Lett. (2019) 6:18
Data andmethod
e arrival time data used in this study were obtained
from September 28 to November 22, 2018, at BMKG
seismic stations in Sulawesi and Borneo (Fig. 1). Dur-
ing this period, there were 554 aftershocks from the Palu
earthquake and 556 swarm earthquakes from Mamasa,
constituting 5608 and 2649 P- and S-wave arrival times,
respectively. e velocity model from IASPEI91 (Kennett
and Engdahl 1991) was used for the initial hypocenter
determination of the BMKG catalog, using the Seis-
ComP3 program (GFZ).
We used the HypoDD program (Waldhauser 2001) to
perform the double-difference method (Waldhauser and
Ellsworth 2000) for relocating the aftershock hypocent-
ers. e method assumes that if there are two earth-
quakes with a hypocentral distance smaller than the
distance from the hypocenters to the station, then the
ray paths of these two earthquakes to the station can be
assumed to be the same and therefore, propagate through
the same medium. is method has been successful in
relocating earthquakes in Indonesia using the BMKG
network data with some prominent tectonic interpreta-
tions: for example, in Sumatra (Nugraha et al. 2018a),
West Java (Supendi etal. 2018a), Sulawesi (Ismullah etal.
2017; Supendi etal. 2018b) and Molucca (Utama etal.
2015; Nugraha etal. 2018b).
We applied a statistical resampling approach “boot-
strap” method (Efron 1982; Billings 1994; Shearer 1997)
to assess the reliability of the error estimates. For the final
hypocenters, we replaced the final residuals with samples
drawn with replacements from the observed residual dis-
tribution and relocated all events with these bootstrap
sample data and unit weights to determine the shift in
location with the resampled data vector. We applied
Gaussian noise to the data with a standard deviation
0.1s. e process was then repeated 1000 times.
For selected events in the Mamasa earthquakes, we
used the ISOLA package (Sokos and Zahradnik 2008)
to perform moment tensor inversions from at least four
BMKG seismic stations (see inverted green triangles in
Fig.1). e observed waveforms were preprocessed using
a high-pass filter with a corner frequency of 0.075Hz to
0.15Hz. For hypocenter relocation and focal mechanism
determination, we used the 1-D seismic velocity model
AK135 (Kennett etal. 1995).
Results anddiscussion
We have relocated 386 aftershocks from the Palu earth-
quake (Fig. 2). We first compared the relocated after-
shocks with the initial locations (Fig. 3). e relocated
hypocenters were then plotted in the vertical cross sec-
tion and show a northwest–southeast trending (Fig.3).
e relocated hypocenters exhibit an improvement in
clustering both horizontally and vertically, as shown in
Fig. 3. Relative location errors for the 386 aftershocks
along the Palu-Koro Fault are shown in Fig. 4. Relative
horizontal and vertical error ellipses are shown to be at
the 95% confidence level. Ellipses are computed from the
major axes of the horizontal and vertical projection of
the 95% confidence ellipsoids obtained from a bootstrap
analysis of the final double-difference vector. e distri-
bution of the major and minor axes of the horizontal and
vertical projections of the ellipsoids for the Palu after-
shocks is shown in Fig.7a. Average mislocations horizon-
tally and vertically are generally less than 2km, and the
maximum dislocation is less than 13km (Table1).
e distribution of aftershocks extended from the
north to the south of the mainshock (Fig.2). e location
of the aftershocks is consistent with the crustal deforma-
tion data in the area. e Geospatial Information Author-
ity of Japan (GSI) applied interferometric analysis using
ALOS-2/PALSAR-2 data to show that crustal deforma-
tion occurred in the part of the island (https ://www.gsi.
go.jp). Based on the vertical cross section in parallel to
the fault (cross section A), the aftershocks were mostly
located less than a depth of 20km, which stay within the
seismogenic zone, whereas the trend shown by the hypo-
center in the northern part (close to the Mw 7.5 main-
shock) is shallower than in the southern part. Based on
the distribution of relocated aftershocks, it can be seen
that the events have a NW–SE trending about ~ 200km
in length and ~ 50km in width.
We have relocated 535 of the 556 swarm earthquakes
in Mamasa with a magnitude of M 2 to M 5.4 (Fig.5). e
events that had previously been held fixed at 10km could
now be relocated/resolved (Fig.5). Our results show that
the earthquake swarms probably correspond to the activ-
ity of the local fault in the area, indicated by the fact that
the seismicity pattern has a dip that becomes shallower
toward the west (dipping at a ~ 45° angle) and extends
from north to south with a length of ~ 50 km (Fig. 8b).
Relative location errors for the 535 swarm earthquakes
in Mamasa are shown in Fig.6. e distribution of the
major and minor axes of the horizontal and vertical pro-
jections of these ellipsoids for the events is shown in
Fig.7b. e spatial distribution of relative error agrees
with the relocated seismicity pattern. is confirms that
the seismic swarm sequence has a dip with a 45° angle.
Average mislocations horizontally and vertically are less
than 1.1km, and the maximum dislocation is less than
9km (Table2).
We also conducted a focal mechanism analysis to esti-
mate the type of fault slip for selected events with a mag-
nitude of M > 4.5 (Fig. 8a). Most of the focal mechanism
solutions show the normal fault type. We plotted a spa-
tiotemporal distribution of the aftershocks right after
Page 4 of 11
Supendietal. Geosci. Lett. (2019) 6:18
the Mw 7.5 mainshock and the swarm earthquakes in
Mamasa (Fig.9).
As noted from the spatiotemporal distribution of
the relocated seismicity, the swarm earthquakes in
the Mamasa area are not related to the devastating
Palu earthquake. Figure 9 indicates that the Mamasa
swarm earthquakes occurred approximately 30 days
after the larger magnitude (M > 3) aftershocks had
stopped. Furthermore, it seems very unlikely that a
direct dynamic triggering would respond from such a
large distance (~ 230km) (O’Malley etal. 2018) and the
timing is beyond the timescale of the dynamic stress
transfer. e evidence of a large earthquake triggering
other earthquake sequences only occurs at a magnitude
of M > 8 and is very rare (Johnson et al. 2015). How-
ever, the static stress triggering may have contributed
Fig. 2 Map view for relocated events of the Palu aftershocks; red-to-blue circles represent the epicenters of earthquakes as a function of the focal
depths. Red star illustrates the epicenter of the mainshock, red beach ball diagram denotes the global centroid moment tensor (gCMT) solution,
blue traces correspond to the Palu-Koro Fault and red traces represent other major crustal faults in the region extracted from Irsyam et al. (2017)
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Supendietal. Geosci. Lett. (2019) 6:18
Fig. 3 Vertical cross section of the aftershocks parallel to the fault before relocation (left panel); after relocation (right panel), 386 events,
respectively. The red star represents the Mw 7.5 mainshock, and the blue line depicts the Palu-Koro Fault
Page 6 of 11
Supendietal. Geosci. Lett. (2019) 6:18
to the stress accumulation at the Mamasa earthquake
sequence. erefore, a more rigorous study of static
stress change, incorporating the area of the Mamasa
earthquake sequence, needs to be performed.
Conclusions
We have conducted hypocenter relocations of the
aftershocks of the Mw 7.5 earthquake in Palu since the
September 28, 2018 event. Our results show that the
aftershocks were located to the east of the Palu-Koro
Fig. 4 a Map view of relative location errors for the 386 aftershocks along the Palu-Koro Fault Zone; b depth view along latitude; and c depth view
along longitude. Relative horizontal and vertical error ellipses are shown at the 95% confidence level. Ellipses are computed from the major axes of
the horizontal and vertical projection of the 95% confidence ellipsoids obtained from a bootstrap analysis of the final double-difference vector
Table 1 Horizontal (DX, DY) andvertical (DZ) deviation shift withGaussian noise (0.1s) forthePalu aftershocks
DX [km] DY [km] DZ [km]
Mean Max Mean Max Mean Max
Relocated noise (0.1 s) 1.80 12.43 1.18 8.61 0.61 3.88
Page 7 of 11
Supendietal. Geosci. Lett. (2019) 6:18
Fig. 5 Map of 535 relocated swarm earthquakes in Mamasa, West Sulawesi; for (left panel) the initial location of the BMKG catalogue; (right panel)
after relocation using the double-difference method used in this study
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Supendietal. Geosci. Lett. (2019) 6:18
Fig. 6 a Map view of relative location errors for the 535 earthquakes in Mamasa; b depth view along latitude; c depth view along longitude.
Relative horizontal and vertical error ellipses are shown at the 95% confidence level. Ellipses are computed from the major axes of the horizontal
and vertical projection of the 95% confidence ellipsoids obtained from a bootstrap analysis of the final double-difference vector
Fig. 7 Histograms of lateral and vertical relative location errors of double-difference solutions for a the Palu aftershocks; b the Mamasa swarm
earthquakes. Errors are computed from the major axes of the horizontal and vertical projection of the 95% confidence ellipsoids obtained from a
bootstrap analysis of the final double-difference vector based on 1000 samples with replacement
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Supendietal. Geosci. Lett. (2019) 6:18
Table 2 Horizontal (DX, DY) andvertical (DZ) deviation shift withGaussian noise (0.1s) fortheMamasa sequence
DX [km] DY [km] DZ [km]
Mean Max Mean Max Mean Max
Relocated noise (0.1 s) 0.87 8.22 1.03 2.35 0.78 1.77
Fig. 8 a Focal mechanism solution for selected events (M > 4.5) Mamasa swarm earthquakes; b cross section A after relocation; dashed blue line is
the first-order interpretation of dipping fault, cross section location in Fig. 4
Page 10 of 11
Supendietal. Geosci. Lett. (2019) 6:18
Fault Line, and these results are consistent with the
deformation data of the area. e relocated swarm
earthquakes in Mamasa most likely correspond to the
activity of the local fault (dipping at a ~ 45° angle) and
extend from north to south for a length of ~ 50km.
Supplementary information
Supplementary information accompanies this paper at https ://doi.
org/10.1186/s4056 2-019-0148-9.
Additional le1. The relocated earthquake catalog for aftershocks of
the Mw 7.5 Palu earthquake and swarm earthquakes of Mamasa from Sep-
tember 28 to November 22, 2018.
Fig. 9 Map view of spatiotemporal distribution of relocated Palu aftershocks and the Mamasa swarm earthquakes. Colored dots depict the
sequence number of events (days) relative to the Mw 7.5 Palu earthquake (September 28, 2018, to November 22, 2018)
Page 11 of 11
Supendietal. Geosci. Lett. (2019) 6:18
Acknowledgements
We are grateful to the Indonesian Agency for Meteorology, Climatology, and
Geophysics (BMKG) for access to their earthquake data which were used in
this study. All figures were made using Generic Mapping Tools (Wessel and
Smith 1998). We thank James D. P. Moore for constructive comments, which
helped us improve the manuscript considerably.
Authors’ contributions
PS, ADN, SW, CIA, NTP, KHP, DD, SHW conceived the study. PS, ADN, SW, KHP
contributed to the writing of the manuscript. All authors contributed to
the preparation of the manuscript. All authors read and approved the final
manuscript.
Funding
This study was supported in part by the Indonesian Directorate General of
Higher Education (DIKTI) research funding 2018–2019, awarded to S.W., and
research funding from the Institut Teknologi Bandung (ITB) 2018, awarded to
A.D.N.
Availability of data and materials
The relocated earthquake catalog data are available in Additional file 1.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Geophysical Engineering Study Program, Faculty of Mining and Petroleum
Engineering, Institut Teknologi Bandung, Bandung 40132, Indonesia. 2 Agency
for Meteorology, Climatology, and Geophysics (BMKG), Bandung 40161, Indo-
nesia. 3 Global Geophysics Research Group, Faculty of Mining and Petroleum
Engineering, Institut Teknologi Bandung, Bandung 40132, Indonesia. 4 Center
for Earthquake Science and Technology, Institut Teknologi Bandung, Band-
ung 40132, Indonesia. 5 Geodynamic and Sedimentology Research Group,
Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Band-
ung 40132, Indonesia. 6 Physical Science and Engineering, King Abdullah Uni-
versity of Science and Technology, Thuwal, Saudi Arabia. 7 Agency for Meteor-
ology, Climatology, and Geophysics (BMKG), Jakarta 10610, Indonesia.
Received: 20 August 2019 Accepted: 3 December 2019
References
Bao H, Ampuero J-P, Meng L, Fielding EJ, Liang C, Milliner CWD, Fen T, Huang H
(2019) Early and persistent supershear rupture of the 2018 magnitude 7.5
Palu earthquake. Nat Geosci 12:200–205. https ://doi.org/10.1038/s4156
1-018-0297-z
Billings SD (1994) Simulated annealing for earthquake location. Geophys J Int
118:680–692. https ://doi.org/10.1111/j.1365-246X.1994.tb039 93.x
Daryono MR (2016) Paleoseismology tropis Indonesia (dengan studi kasus di
Sesar Sumatra, Sesar Palukoro-Matano, dan Sesar Lembang). Phd thesis,
Institut Teknologi Bandung (in Indonesia)
Efron B (1982) The Jackknife, the bootstrap and other resampling plans.
Society for Industrial and Applied Mathematics, Philadelphia. https ://doi.
org/10.1137/1.97816 11970 319
Gusman AR, Supendi P, Nugraha AD, Power W, Latief H, Sunendar H, Widiyan-
toro S, Daryono, Wiyono SH, Hakim A, Muhari A, Wang X, Burbidge D,
Palgunadi K, Hamling I, Daryono MD (2019) Source model for the tsunami
inside Palu Bay following the 2018 Palu earthquake, Indonesia. Geophys
Res Lett. https ://doi.org/10.1029/2019G L0827 17
Irsyam M, Widiyantoro S, Natawidjaya DH, Meilano I, Rudyanto A, Hidayati S,
Triyoso W, Hanifa NR, Djarwadi D, Faizal L, Sunarjito (2017) Peta sumber
dan bahaya gempa Indonesia tahun 2017. Pusat Penelitian dan Pengem-
bangan Perumahan dan Permukiman, Kementerian Pekerjaan Umum
dan Perumahan Rakyat (in Indonesian)
Ismullah MF, Nugraha AD, Ramdhan M, Wandono (2017) Precise hypocenter
determination around Palu Koro fault: a preliminary results. In: IOP confer-
ence series: earth and environmental science, pp 012056
Johnson CW, Bürgmann R, Pollitz FF (2015) Rare dynamic triggering of remote
M 5.5 earthquakes from global catalog analysis. J Geophys Res Solid
Earth 120:1748–1761. https ://doi.org/10.1002/2014J B0117 88
Kennett BLN, Engdahl ER (1991) Traveltimes for global earthquake loca-
tion and phase identification. Geophys J Int 105:429–465. https ://doi.
org/10.1111/j.1365-246X.1991.tb067 24.x
Kennett BLN, Engdahl ER, Buland R (1995) Constraints on seismic velocities
in the earth from traveltimes. Geophys J Int 122:108–124. https ://doi.
org/10.1111/j.1365-246X.1995.tb035 40.x
Nugraha AD, Supendi P, Widiyantoro S, Daryono, Wiyono SH (2018a) Earth-
quake swarm analysis around Bekancan area, North Sumatra, Indonesia
using the BMKG network data: Time periods of February 29, 2015 to
July 10, 2017. In: AIP conference proceedings, pp 020092. https ://doi.
org/10.1063/1.50473 77
Nugraha AD, Supendi P, Widiyantoro S, Daryono, Wiyono SH (2018b) Hypo-
center relocation of earthquake swarm around Jailolo volcano, North
Molucca, Indonesia using the BMKG network data: time periods of
September 27-October 10, 2017. In: AIP conference proceedings. https ://
doi.org/10.1063/1.50473 78
O’Malley RT, Mondal D, Goldfinger C, Behrenfeld MJ (2018) Evidence of sys-
tematic triggering at teleseismic distances following large earthquakes.
Sci Rep 8:11611. https ://doi.org/10.1038/s4159 8-018-30019 -2
Pramono S, Prakoso W, Rahayu A, Cummins P, Rahayu A, Rudyanto A, Syukur F,
Sofian (2017) Investigation of subsurface characteristics by using a Vs30
parameter and a combination of the Hvsr and Spac methods for micro-
tremor arrays. Int J Technol 8:983. https ://doi.org/10.14716 /ijtec h.v8i6.682
Shearer PM (1997) Improving local earthquake locations using the L1 norm
and waveform cross correlation: application to the Whittier Narrows,
California, aftershock sequence. J Geophys Res 102:8269–8283. https ://
doi.org/10.1029/96JB0 3228
Socquet A, Simons W, Vigny C, McCaffrey R, Subarya C, Sarsito D, Ambrosius
B, Spakman W (2006) Microblock rotations and fault coupling in SE Asia
triple junction (Sulawesi, Indonesia) from GPS and earthquake slip vector
data. J Geophys Res. https ://doi.org/10.1029/2005J B0039 63
Socquet A, Hollingsworth J, Pathier E, Bouchon M (2019) Evidence of supers-
hear during the 2018 magnitude 7.5 Palu earthquake from space geod-
esy. Nat Geosci 12:192–199. https ://doi.org/10.1038/s4156 1-018-0296-0
Sokos EN, Zahradnik J (2008) ISOLA a Fortran code and a Matlab GUI to
perform multiple-point source inversion of seismic data. Comput Geosci
34:967–977. https ://doi.org/10.1016/j.cageo .2007.07.005
Supendi P, Nugraha AD, Puspito NT, Widiyantoro S, Daryono, Wiyono SH
(2018a) Identification of active faults in West Java, Indonesia, based on
earthquake hypocenter determination, relocation, and focal mechanism
analysis. Geosci Lett. https ://doi.org/10.1186/s4056 2-018-0130-y
Supendi P, Nugraha AD, Widiyantoro S (2018b) Hypocenter relocation of the
aftershocks of the Poso, Sulawesi (Mw 6.6, May 29, 2017) event using the
BMKG network data. In: AIP conference proceedings, pp 020076. https ://
doi.org/10.1063/1.50473 61
Utama MRJ, Nugraha AD, Puspito NT (2015) Seismicity studies at Moluccas
area based on the result of hypocenter relocation using HypoDD. In: AIP
conference proceedings, pp 030022. https ://doi.org/10.1063/1.49150 30
Waldhauser F (2001) hypoDD-A program to compute double-difference
hypocenter locations, USGS open file report 2001-113
Waldhauser F, Ellsworth WL (2000) A double-difference earthquake location
algorithm: method and application to the northern Hayward Fault, Cali-
fornia. Bull Seismol Soc Am 90:1353–1368. https ://doi.org/10.1785/01200
00006
Watkinson IM (2011) Ductile flow in the metamorphic rocks of central
Sulawesi. Geol Soc Lond Spec Publ 355:157–176. https ://doi.org/10.1144/
SP355 .8
Wessel P, Smith WHF (1998) New, improved version of generic mapping
tools released. Eos Trans Am Geophys Union 79:579. https ://doi.
org/10.1029/98EO0 0426
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The Arxan Volcanic Group is one of the largest active volcanic fields in China. Its last eruption occurred ∼2000 years ago, but it still has a potential of eruption in the future. The spatial distribution and migration channel of its magmatic reservoirs are still unclear. Here we precisely locate microearthquakes and study the detailed 3-D velocity structure of the volcanic area using a large number of high-quality P and S wave arrival-time data recorded at 227 portable seismometers. A swarm of microearthquakes (M<1.5) related to magmatic activity were recorded, which lasted about 4 days during 13-16 September 2020. Our tomographic results show that 12 Arxan volcanoes share the same magmatic system. The melt fraction of a magma chamber below the Tianchi volcano at ~0-8 km depths is estimated to be ~6.1-8.6% from the seismic velocity reductions. Our results indicate that the Arxan magmatic system is still active at present.
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On the 15th of January 2021 (local date), an MW 6.2 earthquake struck the Mamuju and Majene regions of West Sulawesi, Indonesia. This event killed more than one hundred inhabitants, leaving at least thirty thousand people displaced from their homes, and damaged almost eight thousand buildings within a radius of ∼30 km from the mainshock's epicentre location (as shown on our damage proxy map). This event was generated by an active fault that continues to the Makassar Strait Thrust (MST) offshore West Sulawesi. The hazard potential of this fault remains poorly understood. In this study, we use seismic and Global Positioning System (GPS) data to investigate the source characteristics of the mainshock. The results suggest that the mainshock partially ruptured one segment of the MST, activated a secondary fault structure, and likely brought the up-dip unruptured section of the MST segment closure to failure. Our analysis of interseismic GPS velocities indicates that the Mamuju and Majene regions have a higher crustal strain rate than other nearby regions. The results (partial rupture of the MST segment, the up-dip unruptured section of the MST, and high strain rate in the Mamuju and Majene regions) together suggest a significant seismic hazard potential in West Sulawesi, particularly in the Mamuju and Majene areas.
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A destructive earthquake (Mw 6.1) struck Pasaman, West Sumatra, Indonesia, on 25 February 2022, resulting in at least 18 deaths and damage to 1765 buildings. Our relocated foreshock, mainshock, and aftershocks and their source mechanisms reveal a previously unknown ~20 km long segment of the Sumatran Fault as a result of dextral strike-slip motion (strike N132oE and dip 72oSW) along what we have called the Kajai Fault. The inverted rupture model indicates a single, compact asperity with an approximate depth range of 2–11 km. This asperity extends ~14 km along strike, and ~9 km in the down-dip direction. The Coulomb stress change of the mainshock shows that areas to the north and south experienced an increase in stress, which is consistent with the observed aftershock pattern. The nearby Great Sumatran Fault segments (Angkola and Sumpur) experienced a significant increase in stress without any accompanying aftershocks, which likely increases the risk of them rupturing in the future.
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A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 Mw = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike‐slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake‐induced landslides. In this study we examine the tsunami potential of the co‐seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar‐derived displacement fields to estimate a 3D co‐seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co‐seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co‐seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co‐seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video‐derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co‐seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike‐slip faults in transtensional basins.
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Halmahera is an area with active tectonics, so it has a high level of seismicity. Swarm earthquakes occurred in Jailolo from November to December 2015, and then in 2017, another earthquake swarm occurred from September to October. This earthquake is characterized by an increase in the number of earthquakes in a certain period with a relatively small magnitude, without mainshocks, and occurs in volcanic areas. This research used arrival time from P and S waves recorded at Taide Digital Seismograph (TDS) which was positioned at Ternate Geophysical Station (TNTI). We used cross-section on hypocenter to see the depth distribution using GMT and determination of b-value using ZMAP code. From the results of this study, the variation in the magnitude of the earthquake swarm obtained ranged from 0.7 to 5.0 with a depth of 7.7-12 km. Our results show a b-value of aproximately 1.0 in the area near Jailolo Volcano, 1.0-1.5 in the northwest of Jailolo and 1.0-2.0 in the southeastern part of Jailolo. Based on b-value we obtained, the characteristics of the Jailolo swarm earthquake tend to be influenced by magmatic activity.
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A devastating Mw 7.5 earthquake and tsunami struck northwestern Sulawesi, Indonesia on 28 September 2018, causing over 4000 fatalities and severe damage to several areas in and around Palu City. Severe earthquake-induced soil liquefaction and landslides claimed hundreds of lives in three villages within Palu. The mainshock occurred at 18:03 local time at a depth of 10 km on a left-lateral strike-slip fault. The hypocenter was located 70 km north of Palu City and the rupture propagated south, under Palu Bay, passing on land on the west side of Palu City. The surface rupture of the earthquake has been mapped onshore along a 30 km stretch of the Palu-Koro fault. We present results of field surveys on the effects of the earthquake, tsunami and liquefaction conducted between 1–3 and 12–19 of October 2018. Seismic intensities on the Modified Mercalli Intensity (MMI) scale are reported for 375 sites and reach a maximum value of 10. We consolidate published tsunami runup heights from several field studies and discuss three possible interrelated tsunami sources to explain the variation in observed tsunami runup heights. Due to limited instrumentation, PGA and PGV values were recorded at only one of our field sites. To compensate, we use our seismic intensities and Ground Motion to Intensity Conversion Equations (GMICEs) and Ground Motion Prediction Equations (GMPEs) developed for similar tectonic regions. Our results indicate that the maximum predicted PGAs for Palu range from 1.1 g for GMICEs to 0.6 g for GMPEs.
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This study provides an attempt to analyze the pre-eruptive seismicity events for volcano eruption forecasting. After more than 50 years of slumber, Agung volcano on Bali Island erupted explosively, starting on November 21, 2017. The eruption was preceded by almost 2 months of significant increase of recorded seismicity, herein defined as “seismic crisis.” Our study provides the first analysis of VT events using data from eight local seismic stations deployed by the Center for Volcanology and Geological Hazard Mitigation of Indonesia (CVGHM) to monitor the Agung Volcano activity. In total, 2,726 Volcano-Tectonic (VT) events, with 13,023 P waves and 11,823 S wave phases, were successfully identified between October 18 and November 30, 2017. We increased the accuracy of the hypocenter locations of these VT events using a double-difference (DD) relative relocation and a new velocity model appropriate to the subsurface geological conditions of Agung volcano. We found two types of seismicity during the recording period that represent the VT events relating to fracture network reactivation due to stress changes (during the seismic crisis) and magma intrusion (after the seismic crisis). The characteristics of each event type are discussed in terms of Vp/Vs values, phase delay times, seismic cluster shapes, and waveform similarity. We interpret that the upward migrating magma reached a barrier (probably a stiff layer) which prohibited further ascent. Consequently, magma pressurized the zone above the magma chamber and beneath the barrier, reactivated the fracture zone between Agung and Batur volcanoes, and caused the seismic crisis since September 2017. In early November 2017, the barrier was finally intruded, and magma and seismicity propagated toward the Agung summit. This reconstruction provides a better depth constraint as to the previous conceptual models and explains the long delay (∼10 weeks) between the onset of the seismic crisis and the eruption. The distinction between the fracture reactivation and magma intrusion VT events observed in this study is significant for eruption forecasting and understanding the subsurface structure of the magmatic system. Based on the results obtained in this study, we emphasize the importance of prompt analysis (location and basic seismic characteristics) of the seismic crisis preceding the Agung eruption.
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On 28 September 2018, a strike‐slip earthquake occurred in Palu, Indonesia, and was followed by a series of tsunami waves that devastated the coast of Palu Bay. The tsunami was recorded at the Pantoloan tide gauge station with a peak amplitude of ~2 m above the water level and struck at high tide. We use the Pantoloan tsunami waveform and synthetic aperture radar displacement data in a joint inversion to estimate the vertical displacement around the narrow bay. Our inversion result suggests that the middle of the bay was uplifted up to 0.8 m, while the other parts of the bay subsided by up to 1 m. However, this seafloor displacement model alone cannot fully explain the observed tsunami inundation. The observed tsunami inundation heights and extents could be reproduced by a tsunami inundation simulation with a source model that combined the estimated vertical displacement with multiple subaerial-submarine landslides.
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The speed at which an earthquake rupture propagates affects its energy balance and ground shaking impact. Dynamic models of supershear earthquakes, which are faster than the speed of shear waves, often start at subshear speed and later run faster than Eshelby’s speed. Here we present robust evidence of an early and persistent supershear rupture at the sub-Eshelby speed of the 2018 magnitude 7.5 Palu, Indonesia, earthquake. Slowness-enhanced back-projection of teleseismic data provides a sharp image of the rupture process, along a path consistent with the surface rupture trace inferred by subpixel correlation of synthetic-aperture radar and satellite optical images. The rupture propagated at a sustained velocity of 4.1 km s –1 from its initiation to its end, despite large fault bends. The persistent supershear speed is further validated by seismological evidence of far-field Rayleigh Mach waves. The unusual features of this earthquake probe the connections between the rupture dynamics and fault structure. An early supershear transition could be promoted by fault roughness near the hypocentre. Steady rupture propagation at a speed unexpected in homogeneous media could result from the presence of a low-velocity damaged fault zone. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.
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A magnitude 7.5 earthquake hit the city of Palu in Sulawesi, Indonesia on 28 September 2018 at 10:02:43 (coordinated universal time). It was followed a few minutes later by a 4–7-m-high tsunami. Palu is situated in a narrow pull-apart basin surrounded by high mountains of up to 2,000 m altitude. This morphology has been created by a releasing bend in the Palu-Koro fault, a rapidly moving left-lateral strike-slip fault. Here we present observations derived from optical and radar satellite imagery that constrain the ground surface displacements associated with the earthquake in great detail. Mapping of the main rupture and associated secondary structures shows that the slip initiated on a structurally complex and previously unknown fault to the north, extended southwards over 180 km and passed through two major releasing bends. The 30 km section of the rupture south of Palu city is extremely linear, and slightly offset from the mapped geological fault at the surface. This part of the rupture accommodates a large and smooth surface slip of 4–7 m, with no shallow slip deficit. Almost no aftershock seismicity was recorded from this section of the fault. As these characteristics are similar to those from known supershear segments, we conclude that the Palu earthquake probably ruptured this segment at supershear velocities. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.
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We determined earthquake locations through re-picking of P- and S-wave arrival times recorded by BMKG network. Earthquake locations were determined using Hypoellipse code that employs a single event determination method. We then relocated the events using hypocenter double-difference method. We also conducted focal mechanism analysis to estimate the type of fault slip. The results indicate improved hypocenter locations, where patterns of seismicity in West Java were delineated clearly. There are several clusters of earthquakes at depths ≤ 30 km, which are probably related to the Cimandiri, Lembang, and Baribis faults. In addition, there is another cluster in Garut trending southwest-northeast, which is possibly related to a local fault. Histograms of travel-time residuals depict good results, in which travel-time residuals are mostly close to zero. Source mechanism throughout the Lembang fault indicates a left-lateral strike slip in agreement with previous studies. The Cimandiri fault also shows a left-lateral slip, but in the south it shows a thrust fault mechanism. While the source mechanisms of the western part of the Baribis fault indicate a thrust fault and the cluster of events in Garut shows a right-lateral slip if they are related to a local fault.
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Earthquakes are part of a cycle of tectonic stress buildup and release. As fault zones near the end of this seismic cycle, tipping points may be reached whereby triggering occurs and small forces result in cascading failures. The extent of this effect on global seismicity is currently unknown. Here we present evidence of ongoing triggering of earthquakes at remote distances following large source events. The earthquakes used in this study had magnitudes ≥M5.0 and the time period analyzed following large events spans three days. Earthquake occurrences display increases over baseline rates as a function of arc distance away from the epicenters. The p-values deviate from a uniform distribution, with values for collective features commonly below 0.01. An average global forcing function of increased short term seismic risk is obtained along with an upper bound response. The highest magnitude source events trigger more events, and the average global response indicates initial increased earthquake counts followed by quiescence and recovery. Higher magnitude earthquakes also appear to be triggered more often than lower magnitude events. The region with the greatest chance of induced earthquakes following all source events is on the opposite side of the earth, within 30 degrees of the antipode.
Conference Paper
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A year after the hundreds of earthquake swarm last year (2015-2016), recent swarm activity in Jailolo, north of Maluku area, Indonesia began to reactivated. We have successfully relocated 108 out of the 130 earthquake swarm from September 27 to October 10, 2017 by using the BMKG network data through hypocenter double-difference method. The results indicate improvement in hypocenter location, where the initial earthquake focal depths fixed at a depth of 10 km has been updated. A validation through the histogram of travel-time residual depicts good relocation results, in which the residual values are mostly close to zero. The relocated hypocenters are located close to Jailolo volcano area which has focus depths of about 5 – 30 km. We analyzed of waveform of several swarm events (with largest and smallest magnitude) which are recorded by the nearest BMKG station and show has frequency range of 2 to 8 Hz. Our preliminary interpretation, these swarm events probably associated with stress change due to combination of tectonic and deep magma activity in the area.
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Palu City is an active seismic area in Indonesia due to the very active Palu-Koro fault system. The development of the city area, therefore, must consider the risks induced by the seismic activities. The risk assessment has to be supported by information on subsurface characteristics. The aim of this study is to investigate the characteristics of the subsurface of the area by considering the value of Vs30 (top 30 m shear-wave velocity). This parameter has been related to the estimation of the site's ground shaking during the occurrence of an earthquake. The measurements taken in the deep soil sediment include the microtremor array, using the spatial auto correlations (SPAC) method, as well as the site's dominant period measurement, using the horizontal-to-vertical spectral ratio (HVSR) method. All these parameters were local site parameters, which could be subsequently related to a description of the potential impact in an area near to the epicenter. The measurement of Vs30 was conducted in collaboration between the Indonesian Agency for Meteorology, Climatology, and Geophysics (Badan Meteorologi, Klimatologi, dan Geofisika) (BMKG) and the University of Indonesia (Universitas Indonesia) (UI); the overall surveys included Vs30 measurements at 44 sites, microtremor array surveys at 10 sites, and the dominant period measurements at 74 sites. The overall results indicated that there is a good correlation between Vs30 and the dominant period. In general, Palu City is predominantly a class-D site, but the northwest part of the Palu area is a class-C site.
Conference Paper
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Sulawesi area is located in complex tectonic pattern. High seismicity activity in the middle of Sulawesi is related to Palu Koro fault (PKF). In this study, we determined precise hypocenter around PKF by applying double-difference method. We attempt to investigate of the seismicity rate, geometry of the fault and distribution of focus depth around PKF. We first re-pick P-and S-wave arrival time of the PKF events to determine the initial hypocenter location using Hypoellipse method through updated 1-D seismic velocity. Later on, we relocated the earthquake event using double-difference method. Our preliminary results show the distribution of relocated events are located around PKF and have smaller residual time than the initial location. We will enhance the hypocenter location through updating of arrival time by applying waveform cross correlation method as input for double-difference relocation.
Conference Paper
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The precise hypocenter was determined location using double difference method around subduction zone in Moluccas area eastern part of Indonesia. The initial hypocenter location from MCGA data catalogue of 1,945 earthquake events. Basically the principle of double-difference algorithm assumes if the distance between two earthquake hypocenter distribution is very small compared to the distance between the station to the earthquake source, the ray path can be considered close to both earthquakes. The results show the initial earthquakes with a certain depth (fix depth 10 km) relocated and can be interpreted more reliable in term of seismicity and geological setting. The relocation of the intra slab earthquakes beneath Banda Arc are also clearly observed down to depth of about 400 km. The precise relocated hypocenter will give invaluable seismicity information for other seismological and tectonic studies especially for seismic hazard analysis in this region
Conference Paper
Earthquake swarm are common occur around active tectonic and volcanic regions. The recent activities of swarm event occurred around Bekancan area, North Sumatra Province, Indonesia for February 29, 2015 to July 10, 2017 recorded by BMKG local/regional network. This location close to Sinabung and Sibayak volcanoes, lead to our intriguing to analysis of source mechanism and location of the swarm event. We attempted to update hypocenter location of BMKG data catalogue by applying double-difference method. We have successfully relocated of 152 swarm events in the area. The relocated events appear about 10 km northeast of Sinabung volcano with focus depth of about 0 to 30 km (below sea level), however very close to Sibayak volcano area. Overall, the dominant frequency of the event from the closest station is about 2 to 9 Hz. So, our preliminary interpretation is the location of swarm events close to Sinabung and Sibanyak volcanoes in Bekancan area which probably related to stress change due to volcanic-tectonic activity.