Near the northern border of Sumatra, the right-lateral
strike–slip Sumatran fault zone splits into two branches and extends into
the offshore, as revealed by seismic sounding surveys. However, due to its
strike–slip faulting characteristics, the Sumatran fault zone's activity is
rarely believed to cause tsunami hazards in this region. According to two
reprocessed reflection seismic profiles, the extended Sumatran fault zone is
strongly associated with chaotic facies, indicating that large submarine
landslides have been triggered. Coastal steep slopes and new subsurface
characteristics of submarine landslide deposits were mapped using recently
acquired high-resolution shallow bathymetry data. Slope stability analysis
revealed some targets with steep morphology to be close to failure. In an
extreme hypothetical case, an earthquake of Mw 7 or more occurred, and
the strong ground shaking triggered a submarine landslide off the northern
shore of Sumatra. Based on a simulation of tsunami wave propagation in
shallow water, the results of this study indicate that a potential tsunami hazard
from several submarine landslide sources triggered by the strike–slip fault
system can generate a tsunami as high as 4–8 m at several locations along
the northern coast of Aceh. The landslide tsunami hazard assessment and
early warning systems in this study area can be improved on the basis of
this proposed scenario.
Introduction
The most distinct tectonic feature of Sumatra (Fig. 1a) is a strike–slip
fault called the Sumatran fault zone (SFZ) with a length of approximately
1900 km that stretches from Sunda Strait to Banda Aceh (Sieh and Natawidjaja, 2000). Numerous large
earthquakes have occurred along this long fault zone, the largest with a
magnitude of 7.7 that occurred in 1892 at Angkola segment and a significant
event with magnitude of 7.4 that occurred in 1943 at Sumani segment of SFZ (Sieh and Natawidjaja, 2000). Near the
northern tip of Sumatra (Aceh Province), the SFZ divides into two branches:
the Aceh and Seulimeum faults (Fig. 1b). These faults cross the northern end
of Sumatra Island and extend into the Andaman Sea (Fernández-Blanco
et al., 2016; Ghosal et al., 2012; Sieh and Natawidjaja, 2000). The most
recent earthquake at the Seulimeum fault was recorded on 2 April 1964, with
Mw 7, and it caused severe damage at Krueng Raya (Sieh and Natawidjaja, 2000). After the 2004
Sumatra–Andaman earthquake and tsunami, the source rupture region was
studied intensively; in particular, research has focused on the western side
of the island and areas near the epicenter. By contrast, the inland SFZ has
rarely been studied. The absence of high-resolution geophysical data at
these segments has resulted in limited knowledge about the seismic
activities of these two extensions and the corresponding risk of hazards.
(a) Tectonics of the Sumatra subduction zone
(Berglar et al., 2017). (b) Structure of the SFZ
at northern Sumatra according to the interpretation of Fernández-Blanco et al. (2016). Recorded earthquake epicenters (color dots) and focal mechanisms
were collected from the Badan Meteorologi, Klimatologi dan Geofisika (BMKG)
of Indonesia and from the CMT global catalog (http://www.globalcmt.org/, last access: 26 July 2022),
respectively.
Analysis of the Mw 7.0 Haiti earthquake on 12 January 2010 revealed
that an earthquake with strike–slip faulting can produce a significant
tsunami. Typically, a strike–slip fault movement is not associated with
uplift of the sea floor or tsunami generation. However, a combination of
other factors can trigger a tsunami. For the Haiti earthquake, the tsunami
waves seem to have been caused by coastal failure landslides (Poupardin et al., 2020 and references therein).
Satellite images and ground photos reveal changes in the coastline following
the earthquake (Hornbach et al., 2010). The Haiti
earthquake is not unique. On 28 September 2018, a large tsunami hit the city
of Palu following the Mw 7.5 Sulawesi earthquake in Indonesia. This
event also occurred along a strike–slip fault. A tsunami of that size is
unlikely to have been generated through earthquake rupturing alone. The
tsunami is thought to have been caused by underwater and subaerial
landslides triggered by the earthquake (Gusman et al., 2019). The complex
bathymetry of the Palu Bay may have also contributed to the generation of
the tsunami (Socquet et al., 2019). Another evaluation of
strike–slip earthquakes that have caused tsunamis is the Mw 7.6, 1999 Izmit
earthquake, where slumping resulted from the gravitative instability of
active gliding masses as the source of tsunami generation are observed as
the chaotic deposit in the basin of the Sea of Marmara (Gasperini et
al., 2022; Zitter et al., 2012). Heidarzadeh et al. (2017)
showed potential tsunami hazards from strike–slip events by analyzing the
tsunami from the Mw 7.8 strike–slip earthquake in the Wharton Basin. Other
well-known tsunamis, such as the 1998 Papua New Guinea abnormal tsunami (Heinrich
et al., 2001; Kawata et al., 1999; Tappin et al., 1999) was also induced by
earthquake-triggered submarine landslides, while the 22 December 2018
tsunami at Sunda Strait caused by a flank collapse of the Anak Krakatau
volcano (Heidarzadeh
et al., 2020; Muhari et al., 2019; Patton et al., 2018; Syamsidik et al.,
2020), which is a good example of a volcano-triggered tsunami
(Ye et al., 2020). The recent mega earthquake such as
the 2004 Mw 9.2 Indian Ocean tsunami and the 2011 Mw 9.0 Tohoku
earthquake may also include the submarine landslide as part of the tsunami
source beside the major thrust fault movement, as the evidence of submarine
landslide was observed for both earthquakes (Sibuet
et al., 2007; Song et al., 2005; Tappin et al., 2014).
An earthquake with a strike–slip fault rupture could also trigger a
landslide and induce a tsunami offshore of northern Sumatra. In this study,
to investigate the potential tsunami hazard at the northern tip of Sumatra,
seismic reflection data were used to identify evidence of past submarine
landslides. We collected detailed shallow bathymetric data of the area
beyond the coast. This high-resolution bathymetric data were used to
identify the fault traces and to evaluate the possibility of slope failure
along the continental slope. The possibility of a submarine landslide
triggered by earthquake shaking was examined through an analysis of the
continental slope stability, and a tsunami caused by the combination of the
earthquake and the resulting submarine landslide was simulated. The results
indicated the characteristics of a potential landslide-induced tsunami and
its potential damage. The predicted ground motion as a possible validation
on strong ground shaking that could induce the submarine landslide is discussed
in the discussion section. A possible tsunami early warning plan for hazard
reduction is also discussed in this paper.
Tectonic setting of the northern SFZ
The oblique subduction of the Australian plate below the Sunda plate is
compensated by right-lateral strike–slip faulting at the Sunda plate along
Sumatra (McCaffrey, 1992). Tectonic processes in the present-day
Sumatra region are controlled by three major fault systems: the megathrust
fault along the Sunda Trench (reverse fault), the Mentawai fault
(right-lateral strike–slip) (Barber
and Milsom et al., 2005; Berglar et al., 2017; Moore et al., 1980) and the
SFZ (right-lateral strike–slip) (Fig. 1a). The fault trace of the SFZ is
associated with a series of valleys along the mountain chain
(Sieh and Natawidjaja, 2000). The linkage of
the SFZ from south to north is not smooth; the fault divides into several
segments (Newcomb and McCann, 1987;
Sieh and Natawidjaja, 2000). The SFZ segmentation also results in the
segmentation of earthquakes and serves as a rupture barrier, decreasing
earthquake magnitudes (Barber and
Milsom et al., 2005; Sieh and Natawidjaja, 2000).
At the northern corner of Sumatra, the SFZ divides into two branches named
the Aceh and Seulimeum faults. Both faults have been reported to extend
northerly into the Andaman Sea floor (Fernández-Blanco
et al., 2016; Ghosal et al., 2012; Sieh and Natawidjaja, 2000). A recent
detailed investigation of the Aceh and Seulimeum fault geometries revealed a
complex fault system for both faults (Fernández-Blanco et al.,
2016). The complex fault system at these fault segments are also reflected
trough diverse rupture modes of the recorded earthquake focal mechanism
(Fig. 1b), which includes oblique right-lateral strike–slip, with a
complicated nodal plane. The Aceh fault has fold train features that evolve
as splay contractional structures of the overall strike–slip system. The
Seulimeum fault divides into two branches, and a long valley is formed at
the northern end (Fig. 1b). The two Seulimeum fault traces were identified
by Fernández-Blanco et al. (2016) as “Set A” and “Set B”; here, we refer to them as Seulimeum fault 1 (S1) and Seulimeum fault 2 (S2), respectively; the traces are indicated in
Fig. 1b. In the region between the Aceh and Seulimeum faults, no fault trace
indicating interactions between these two main branches of the SFZ was
observed. However, because no geophysical data are available in this area,
the existence of a fault trace buried by deep sediment cannot be ruled out.
The slip rates along the Aceh and Seulimeum faults have not been reported.
However, an offset of approximately 20 to 21 km in the nearby segment of the
SFZ in the Aceh region has been observed within the past several million
years (Sieh and Natawidjaja, 2000), and the
Banda Aceh embayment extrudes to the northwest at a rate of 5±2 mm yr-1 (Genrich et al., 2000). Both observations
indicate the activity of the Aceh and Seulimeum faults.
Collected data and analysis methodsSingle-channel seismic reflection data
From 1991 to 1992, single-channel seismic (SCS) reflection data have been
collected along the western margin of Sumatra (Malod and Kemal, 1996). These collected
data include five seismic profiles offshore north of Aceh. In this study, we
selected two profiles that cross the Seulimeum faults (i.e., SUMII-32 and
SUMII-33; Fig. 1b) for further analysis. These data were originally recorded
on paper prints. Those paper recordings were scanned and converted to
digital images. All seismic traces were digitized and converted into the
SEG-Y format for reprocessing. In the absence of any velocity information,
these data were migrated using a water velocity of 1500 m s-1 to remove
the effects of seafloor scattering. Due to digital conversion, the original
seismic data has uneven trace amplitude with low-frequency noise artifacts
clearly seen on some parts of the profile, so the main purpose of
reprocessing is to attenuate those noises, while some post-stack image
enhancement methods were also applied to further improve the seismic image.
The processing detail is as follows: after SEG-Y input, a low-cut filter
(4–8 Hz) was applied to attenuate the low frequency artifact. To remove the
noise outside the data range, seafloor mute and bottom trace mute were
picked and applied, followed by amplitude balancing and signal enhancement
in both frequency domain (FXDECON) and FK domain (FKPOWER). After that,
post-stack predictive gap deconvolution was applied to remove the
reverberation and compress the wavelet. Finally, seafloor mute and bottom
trace mute were reapplied before SEG-Y output. The reprocessed seismic
profiles are presented in Figs. 2 and 3. The seismic profile SUMII-32
crosses over the northward extension of fault S2 (Fig. 1b). This profile is
a short (26.5 km) seismic profile close to the coast. On this profile, the
location of fault S2 is clearly visible in the seismic section. This fault
trace depicts a near-vertical fault plane with a positive flower structure,
indicating fault activity (Fig. 2b). A subsidence sequence marked by
fan-shaped sediments is visible in the northeast section of the profile
(Fig. 2c) and may indicate an extension regime of the back-arc basin. Figure 3 presents the seismic reflection SUMII-33, which is located parallel to the
northern coast of Banda Aceh and perpendicular to faults S1 and S2 (Fig. 1b); the figure depicts a system of shear faults that dip to the southwest
and normal to the northeast on the western part of the profile (Fig. 3b).
All of the faults are close to the surface and have a surface obstruction.
These traces indicate recent activity in this shear fault system (Fig. 3).
Seismic sections of SUMII-32 that have been collected from 1991 to
1992 by Malod and Kemal (1996). This
dataset is digitized from paper recordings that were scanned and converted
to digital images. All seismic traces were digitized and converted into the
SEG-Y format for reprocessing. Please see Sect. 3.1 for detailed
processing of this dataset. (a) The reprocess uninterpreted seismic profile
with direction, shot point (SP) and offset (in meters) presented at the top
of the profile. (b) Possible location of the Seulimeum fault. (c) Fan-shaped
sediments.
Same as Fig. 2 but for SUMII-33. (a) The reprocess uninterpreted
seismic profile with direction, shot point (SP) and offset (in meters)
presented at the top of the profile. (b) Possible compression. (c) Mass
transport deposits.
Community-based bathymetric survey data
The community-based bathymetric survey (CBBS) data used in this study
comprise fishing boat track records from GPS sounders with data logging
devices. The data include the date, time, depth, sea surface temperature
(SST), boat speed, heading and geographical position (Haridhi et al.,
2016; Rizal et al., 2013). Data were collected from 45 local fishing boats
in the northern Sumatra area, which had installed sounder equipment due to
participation in a project supported by the Asian Development Bank (ADB) as
an effort to rehabilitate the traditional fishing community after the mega
earthquake and tsunami disaster on 26 December 2004 (Wilson and
Linkie, 2012). The CBBS data collection was from June 2007 to May 2009 (23 months). A total of 6 170 648 data points from 922 data sets were collected.
The collected fishing boat tracks were employed to construct
high-spatial-density bathymetry with 20×20 m2 grid spacing.
To unite the bathymetric features and land features, topographic data from
the Badan Informasi Geospasial of Indonesia (i.e., both provided topographic
data names DEMNAS and bathymetric data names BATNAS with 0.27 arcsec and
6 arcsec grid resolution, respectively) were used (BIG, 2018).
BATNAS was resampled to match the grid resolution of CBBS bathymetry,
whereas the original data resolution of DEMNAS was used. The reconstructed
topography is presented in Fig. 4. The white dashed line in Fig. 4 indicates
the boundary location of CBBS and BATNAS datasets with different resolution
properties. The map covers the northern corner of Sumatra Island and the two
branches of the SFZ (Aceh and Seulimeum faults), as indicated in Fig. 1b.
Figure 5 presents a three-dimensional (3D) topographic view of bathymetry at
locations near the continental slope, as indicated in Fig. 4.
Topographic map of the northern tip of Aceh province. Figure 5 in
a closeup of the trapezoidal box viewed from the northeast to southwest.
The Banda Aceh coast near the shallow water area of Fig. 4 is extruded
toward the northeast by a potential shear fault system between the Aceh and
S1 faults. Tectonic movement along the main fault system may induce the
movement of these shear faults, as indicated by the contour pattern of these
shear faults with the southwest–northeast orientation (Fig. 4). The contour
line has a step over at the west side of the shear fault, and the edge
portion of these shear faults has an increased risk of collapse during an
earthquake. Four shear faults (f1, f2, f3 and f4 in Fig. 4) with
left-lateral slips can be identified in conjunction to the right-lateral
slip movement of the main fault system. A distinct difference in water depth
is observed off the northern shore of Sumatra. Some identified scarps
located at the slope close to f1 and f2 can be clearly observed, and the
location of a possible historical landslide is marked along f3 (Fig. 5). At
least one mound-shaped submarine landscape is located on the plain at
approximately 2226 m from the slope close to f2 (Fig. 5). The
highest-resolution CBBS bathymetry is limited for shallow water areas;
however, these shear faults can be identified in the seismic reflection line
SUMII-33 (Fig. 3), and they extend continuously northward from the shallow
waters. An interpretation of both the SCS seismic profile in Fig. 3b and the
shallow bathymetry in Fig. 4 reveals that these four shear faults (f1, f2,
f3 and f4 in Fig. 4) accompanied by normal slips have a negative flower
structure.
3D topographic view of the northeastern shore and waters of Banda
Aceh. The slope heights along f1 and f2 as well as the mound height and
length are indicated. Colors enhance significant features along the
continental slope.
Slope stability analysis and input parameter assessment
An analysis was performed based on the assumption that earthquake-induced
shaking may trigger submarine landslides on the unstable continental slope.
Scoops3D, a computer program for evaluating the slope stability throughout a
digital landscape represented by a digital elevation model, was selected for
the analysis (Reid et al., 2015). The program calculates the slope stability
through limit-equilibrium methods, which estimate the shear resistance on
the trial surface of a potential failure mass in 2D (vertical slices) and 3D
(vertical columns) (Duncan,
1996; Reid et al., 2015). Scoops3D computes a factor of safety (FS) for a
given trial surface by using the moment equilibrium. In all
limit-equilibrium methods, the FS is defined as the ratio of the average shear
resistance (strength) to the shear stress required to maintain a limiting
equilibrium along a predefined trial surface. In Scoops3D, Bishop's
simplified method can be used to determine the normal force acting on the
slip surface by first computing the force equilibrium in the vertical
direction on the base of each slice (Bishop, 1955). This method has been
demonstrated to calculate FS accurately (Reid et
al., 2015). Typically, FS > 1 is considered as representing
stability, and FS ≤ 1 represents instability.
Following the evaluation of the seismic profile and shallow bathymetry, the
continental slope edges were found to be associated with the structure of
the active fault; an example is presented in Fig. 5. Earthquake shaking is a
critical factor for generating horizontal and vertical ground motion. This
vibration causes both shear and normal stresses in the sediment. Horizontal
acceleration has the highest contribution to the shear stress and can drive
sediment failure near continental slope edges (Hampton et al., 1996). To represent the effects
of ground acceleration from an earthquake, Scoop3D models typically assume
that earthquake loading is uniform (Reid et al.,
2015); this assumption was also used in this study. However, in the absence
of any supporting information other than detailed CBBS shallow bathymetric
grid, other data such as the subsurface condition (i.e., cohesion and
internal friction) were assumed in accordance with the findings of
Dugan and Flemings (2002). Lee and Edwards (1986) examined the seismic
active offshore margins of California and southern Alaska and suggested that
pseudostatic acceleration between 0.13 and 0.14 g (gravity) corresponds to
the transition from stable to failed sediment; that is, such acceleration
causes sediment failure. Thus, we selected 0.14 g as the earthquake loading
in Scoop3D. The detailed parameters used in the Scoop3D slope stability
analysis are summarized in Table 1. Locations with low identified FS values
that are collocated with or close to a fault were candidates for slide
locations in the tsunami generation model.
Slope stability analysis parameters.
Topography resolution (m) Horizontal Minimum Maximum 20 -907566 Subsurface condition MaterialGroundwaterEarthquakepropertiesconfigurationloadingMaterial properties Angle ofHomogeneousNone0.14Cohesioninternal friction (∘)Weight0 kPa2617.5 kN m-3Stability analysis Limit-equilibrium method Search method Bishop's simplified limit equilibrium Box Simulation of tsunami wave propagation from earthquake and landslide sources
The Cornell multi-grid coupled tsunami model (COMCOT) (Liu et al., 1995; Wang, 2009) is a computer
program applied for performing tsunami simulations. It simultaneously
calculates the tsunami wave propagation and the inundation at coastal zones.
In this study, the nonlinear shallow water equation was used to construct
COMCOT. COMCOT can calculate the tsunami propagation from earthquake
sources, submarine landslides and both phenomena. As described by
Wang and Liu (2006), COMCOT has been widely used to model
tsunamis generated by earthquakes and the mega earthquake and tsunami on
26 December 2004. To construct earthquake-source tsunami simulation input
parameters, we used the magnitude scaling relationship of
Wells and Coppersmith (1994) to convert the magnitude into the
strike–slip fault area (RA) of an earthquake. Based on this relationship, we
defined the RA, the subsurface rupture length (RL) and the rupture width
(RW) from the moment (M0) of a given earthquake. To calculate the
average displacement (D‾) across the fault surface, we used the
seismic moment equation of Hanks and Kanamori (1979).
COMCOT can also be used to simulate tsunamis caused by landslides (Heidarzadeh and Satake,
2015; Liu et al., 1995; Wang, 2009). In this study, we set the 1st
layer grid with 0.25 min resolution, and grid size ratio of three to the
first layer or about 154 m grid being applied to the second layer that
both actives for the tsunami simulation. In the landslide-generated tsunami
simulation, an underwater slide of a rigid body along a particular downslope
path is considered a tsunami source (Watts et al.,
2003). Typically, modeling the time evolution of an actual landslide with
seafloor changes requires substantial computations involving the detailed
knowledge of local marine geological features and the landslide's triggering
mechanism. Therefore, the model in this study used the rigid body movement
as the source of submarine landslide are far from reality and could be
overestimate the actual conditions. To use COMCOT to model a landslide
source, input parameters including the landslide mass position (c), length
(l), width (w), thickness (h) and the slope angle along its sliding path
(ϕ) must be defined. In this study, Manning's relative roughness n was
set to 0.02 in accordance with the assumption that the continental shelf
sediments were primarily composed of mud and silt (Lee and Edwards, 1986).
Analysis and resultsEvidence of paleo-landslides
As presented in Fig. 1b, the seismic reflection SUMII-33 (Fig. 3) is a long
profile located in the sea between Sumatra Island and Weh Island, and it is
nearly perpendicular to the extending fault traces of S1 and S2. In the
western part of SUMII-33, chaotic facies at 17.5–20 km along the profile are
clearly visible (Fig. 3b), and its location is at the northward extension of
the four-shear fault zone, as identified by CBBS bathymetry (Figs. 4 and 5).
The thickness of this chaotic facies is approximately 0.2 s two-way-time
(TWT). If we assume that the seismic wave velocity of marine sediment is
approximately 2000 m s-1, the thickness of this chaotic facies is
approximately 400 m. In the eastern part of SUMII-33, large chaotic facies
are observed (interpreted as mass transport deposit (MTD) facies) and is
marked by the yellow dashed line in Fig. 3c. Similar thin-layer chaotic
facies are also observed on the near coastal line of the short seismic
profile SUMII-32 (Figs. 1b and 2). The chaotic facies are observed at the
slope of the SUMII-32 profile and may be related to the downslope turbidity
or gravity flow. A fan-shaped sediment is clearly observable on the abyssal
plain near the continental slope edge and may indicate an extensional regime
of the back-arc basin (Fig. 2c). Some similar chaotic facies below these
fan-shaped sediment sequences at a distance of 12 500 m and 2.4 s TWT are
difficult to distinguish because the reflector amplitudes are too low,
limiting our capability to interpret the profile (Fig. 2c). Furthermore, on
this seismic profile, the S2 fault has a positive flower structure,
indicating fault activity (Fig. 2b). These observations imply that a
submarine landslide previously occurred in this area and could be triggered
by a fault rupture. However, the precise landslide site along the S1 and S2
faults is difficult to identify due to the low resolution of the obtained
seafloor morphology data, as it is outside the height resolution CBBS
bathymetric data coverage (Fig. 4). The low-resolution bathymetry data of
the seismic survey area limited the identification of any evidence of scarp-
or mound-type structures for the evaluation of possible submarine landslide
sites.
Stability evaluation of seafloor morphology
The CBBS shallow bathymetric map (Figs. 4 and 5) has the highest-resolution
seafloor morphology in comparison to any other available bathymetric data
set for shallow water in this region. The average angles along the
continental shelf, continental slope and abyssal plain calculated by
Scoop3D are between 0 to 5∘, 6 to
30∘, and 0 to 15∘, respectively (Fig. 6a).
The abyssal plain typically has a low slope angle; however, some areas of
the plain have substantially larger slope angles of 10–30∘, as calculated by Scoop3D (marked as green circles in Fig. 6a). These unusual high slope angles may correspond to the location of
topographic high or low points; these morphological features are either
submarine mountain or deeper portions of the abyssal plain. However, these
unusual high slope angles were detected at regions of the plain with sparse
data; thus, the slope angle results may be unreliable. More reliable slope
analysis results were obtained from regions within the CBBS survey area;
only these results were used in the following analysis.
Regional slope distribution, slope stability analysis, location of
the submarine landslide sources for the tsunami simulation scenarios and
the location of near-coast cross sections. (a) Map of slope angles. (b) FS
from the slope stability analysis; red indicates higher likelihood of
failure. (c) Submarine landslide locations and their corresponding numbers;
tsunami simulation scenarios are in Table 2.
As presented in Figs. 4 and 5, two river mouths are the input source of
sediment along this continental shelf; they are located on the Banda Aceh
plain (see Figs. 4 and 5, text label: Aceh and Lamnyong rivers). These thick
sediments may provide support for extending the continental shelf. The shape
of the continental shelf is further modified by the activity of the shear
faults (e.g., f1 to f4 in this area) below the shelf. The spatial
instability of the seafloor can be further evaluated using the FS index
(Reid et al., 2015). Submarine landslides may occur
in regions with low FS values. The slope stability analysis results of
Scoop3D are presented in Fig. 6b. Areas with anomalously low FS values ≤ 2 are located at the continental slope offshore of Banda Aceh. The regions
with low FS values and collocated with the four shear faults (f1 to f4) were
identified as locations for further tsunami simulations (marked as locations
4 to 7 in Fig. 6c). The sediment deposited above the area of the shear
faults across the continental slope may increase the scale of landslides
during earthquake shaking. Two other sites with FS values and collocated
with the faults (S1 and S2) were also identified as possible submarine
landslide locations, and they are marked as locations 1 and 3 in Fig. 6c.
Another area with changes in the FS value near the coast is located offshore
north of Krueng Raya; the FS drastically changes from 4 to 2 within a
distance of 2 km. This location is also a submarine landslide location for
the tsunami simulation (location 2 in Fig. 6c). Figure 6b presents that the
FS values along the continental slope (marked by a solid white circle) are
stable and high. This location was identified as a previously failed section
of the continental slope along f3; this failure can be clearly observed in
Fig. 5. This phenomenon further confirms our interpretation of the chaotic
facies in Fig. 2b.
An area with a much lower FS value located at the continental slope east of
Aceh Islands (marked as a white dashed line in Fig. 6b) is also a reasonable
landslide location for the tsunami simulation. However, this area is
approximately 2.3 km east of the Aceh fault (the main SFZ segment), has a
nearby large river system as a sediment deposit source, and no indication of
chaotic facies on the seismic profile near to this location (Fig. 3);
therefore, submarine landslides generating tsunamis are unlikely to occur
here despite the low FS value at this location. However, this location was
still used as a submarine landslide source for the tsunami simulation
(location 8 in Fig. 6c). These evaluated marine sites (locations 1 to 8 in
Fig. 6c) are the possible locations of submarine landslides that are
simulated in the tsunami scenarios described in the following section.
Tsunami model
To simulate a tsunami with an earthquake source, we must first distinguish
the earthquake sources using a fault model.
Genrich et al. (2000) suggested that the locking
depth of the Aceh and Seulimeum faults does not exceed 15 km. The lengths of
the Aceh and Seulimeum faults on land are up to 200 and 120 km, respectively
(Sieh and Natawidjaja, 2000); however,
geophysical data are insufficient to reveal the details of their extensions
to the northern offshore of Aceh. McCaffrey (1992) suggested
that an earthquake of Mw 7.5 or less is the largest possible event in
the SFZ. The findings of Sieh and Natawidjaja (2000), who summarized available earthquake records, agree with this
evaluation; accordingly, the maximum magnitude of an earthquake event was
set as Mw 7 in this study. This earthquake could occur at any location
along the faults, but we chose an epicenter location near the coast for our
scenarios (star symbol in Fig. 6c). The magnitude, RA, RL, RW, M0,
D‾ and focal mechanism of the proposed earthquake are summarized in
Table 2. The earthquake focal mechanism in terms of the strike (θ),
dip (δ) and slip (λ) were averaged from the Global CMT
catalog (http://www.globalcmt.org/, last access: 26 July 2022; Dziewonski et al., 1981; Ekström
et al., 2012).
∗ The submarine landslide locations (scenario number 1–8) are shown
in Fig. 6c.
As presented in Fig. 6c and Table 2, two earthquakes were considered in the
tsunami simulation. COMCOT was used to compute the tsunami wavefields
induced by both strike–slip earthquakes of Mw 7 in the studied region,
and tsunami waves with an amplitude of 0.3–0.5 m were generated in the
entire coastal region. Thus, the tsunami hazard of a Mw 7 strike–slip
earthquake in this area (with epicentral distances less than 30 km) is
correspond to the first degree of warning or on the alert level
(Badan Metereologi Klimatologi dan Geofisika, 2012). Therefore,
earthquakes generate strong ground motion, which triggers submarine
landslides, but the tsunami hazard is due to the submarine landslide only.
Typically, tsunamis triggered by submarine landslides have run-ups near the
landslide location but have limited far-reaching effects.
The size of paleo-submarine landslides below the northern waters offshore of
Sumatra in the tsunami simulation was estimated from seismic reflection
data. The input parameters of COMCOT for submarine landslide sources were
based on the collected information on regional active faults, the regional
maximum earthquake magnitude and the seafloor stability (Reid et al.,
2015), and the parameters are listed in Table 2. A hypothetical submarine
landslide with a length of 600 m and a width of 300 m (length–width ratio
of 50 %) was considered in this study. The COMCOT tsunami model indicated
that this submarine landslide with the aforementioned size and ratio could
generate a tsunami with a wave height comparable to that in actual records,
such as that of the recent Palu tsunami event studied by Gusman et al. (2019).
The computed spatial distribution of initial tsunami wave heights from eight
submarine landslide sources (listed in Table 2) is presented in Fig. 7
computed along a perpendicular direction to the coast. All scenarios had
depression waves toward shallow water, with subsidence ranging between 1.5
and 8.5 m; leading elevated waves propagated toward deep water, with rise
ranging between 1.5 and 9 m. The largest initial wave height was that in
scenario 4, whereas the smallest was in scenario 1. However, scenario 3 had
reversed polarity of the initial tsunami wave height compared with the other
scenarios (Fig. 7). These deviations could be due to the landslide location
with respect to other morphological features, and the submarine landslide
parameters were critical for generating the initial tsunami wavefields.
Initial tsunami wave heights for the eight submarine landslide
scenarios with the X axis is towards offshore to the right.
After evaluation of all the simulated tsunami scenarios, scenarios 4 and 7
are included in the discussion (other scenarios are presented in the
Supplement). Figure 8 displays snapshots of simulated tsunami
propagation for a submarine landslide at location 4 (Fig. 6c). The
simulation reveals that a continental slope landslide at this location can
generate a tsunami as high as 4 m; at several sites of the coast, the
maximum amplitude of a tsunami wave can reach 8 m. These sites are located
southwest of Weh Island (KW, Fig. 6c) – the closest coast to the landslide
source. The propagation speed of the computed tsunami is affected by the
water depth. The time evolution of a tsunami wave between 10 and 40 min
after the submarine landslide indicates higher speeds to the north of the
source (north offshore of Krueng Raya); however, the amplitude is lower than
that of waves with a lower speed propagating in the west–southwest
direction and approaching the north shore of Banda Aceh. The snapshots in
Fig. 8 also indicate that the frequency of tsunami waves changes when the
wave front reaches the shallow water near the northern coast of Banda Aceh.
The tsunami wave reaches the entire north coast of Aceh, west coast of Aceh
Islands, and south coast of Weh Island in the first 10 min. The
high-frequency wave is distributed throughout the shallow coastal waters
within 40 min.
Snapshots of a tsunami wave from a submarine landslide source at
location 4 of Fig. 6c at propagation times of (a) 2 min, (b) 10 min, (c) 20 min and (d) 40 min.
Images of the simulated tsunami wave from a submarine landslide at location
7 (Fig. 6c) are presented in Fig. 9. Several islands surround the submarine
landslide source. The tsunami wavefields reveal that the maximum tsunami
wave high is approximately 2 m along the coast of Banda Aceh and
approximately 3.5 m along the southwestern coast of Weh Island. This
landslide-generated tsunami wave is blocked and propagates with a low speed
in the northwestern direction. The propagation wavefield is unblocked in the
northeastern direction, and the tsunami wave has a higher amplitude of
approximately 3.5 m in the southwestern coast of Weh Island (KW, Fig. 6c)
and approximately 2.5 m along the eastern coast of Aceh Islands (LB and LN,
Fig. 6c). Furthermore, the tsunami fully sweeps the northern coast of Banda
Aceh and the surrounding islands within 10 min after the submarine
landslide.
Snapshots of a tsunami wave from a submarine landslide source at
location 7 of Fig. 6c at propagation times of (a) 2 min, (b) 10 min, (c) 20 min and (d) 40 min.
The computed initial tsunami wavefields of all scenarios (Fig. 7) reveal
that the induced tsunami waves will extend and hit the coasts of nearby
islands. The computed maximum tsunami wave amplitudes at eight coastal sites
were obtained for all submarine landslide scenarios (Fig. 6c). Statistical
analysis of the distribution of the tsunami wave height at the eight
selected sites is presented in Fig. 10 as a box-and-whisker plot (Massart et
al., 2005). Landslide sources located at the northeastern coast of Banda
Aceh (i.e., scenarios 1 to 5) generate higher tsunami waves that hit the
entire northern coast of Aceh compared with tsunamis with sources located at
the northwestern coast of Banda Aceh (i.e., scenarios 6 to 8), which only
affect the northern coast of Banda Aceh, the eastern coast of Aceh Islands
and the southwestern coast of Weh Island. However, the tsunami wave
generated has nonsignificant effects on the eastern coast of Banda Aceh
(Krueng Raya). The tsunami in scenario 4 had the greatest tsunami hazard of
all analyzed scenarios.
Box and whisker plots (Massart et al., 2005) of the maximum
tsunami wave amplitude along the selected coastlines of Fig. 6c. The “+”
sign indicates the extreme values, while the solid red and dashed blue lines
indicate the median and mean, respectively. The title of each plot indicates
the cross-section location, the x axis is shown for the landslide scenarios
indicated in Table 2, while the y axis indicates the tsunami wave height
shown in meters.
Discussion
Tsunamis induced by giant megathrust earthquakes, such as the 2004
Sumatra–Andaman earthquake or the 2011 Tohoku earthquake in Japan, and
their mechanisms have been investigated (Araki
et al., 2006; Liu and Zhao, 2018; Romano et al., 2014; Sibuet et al., 2007;
Tsuji et al., 2011; Wang and Liu, 2006). These disastrous tsunamis were
induced by a significant co-seismic deformation due to sudden, vertical
seafloor movement in the entire source area. Typically, earthquakes due to
strike–slip fault movement are not associated with significant uplift of the
seafloor or with tsunami generation. In this study, the tsunami wavefield
from a strike–slip earthquake with source parameters listed in Table 2 was
computed. Consistent with previous reports, our results indicate that
vertical seafloor movement is limited, and the induced tsunami wave is less
than 0.5 m throughout the coastal regions in the study area, and the
contribution of the earthquake to tsunami generation will resulted on first
degree of warning or on the alert level (Badan Metereologi
Klimatologi dan Geofisika, 2012). However, the source rupture of a
strike–slip fault (Table 2) dominates the generation of ground motion
through its horizonal components and its shaking of the seafloor sediment.
To verify the calculated ground motion induced by the fault, we followed the
evaluation procedure of Phung et al. (2020) to predict ground motion by
using four global ground motion prediction equations (GMPEs), which were
developed for the global application as a part of the NGA-West2 project:
[ASK14], [BSSA14], [CB14], [CY14] (Abrahamson
et al., 2014; Boore et al., 2014; Campbell and Bozorgnia, 2014; Chiou and
Youngs, 2014). The predicted ground motion is presented in Fig. 11. The
predicted ground acceleration is greater than 0.4 g for epicentral distances
less than 30 km. The eight landslide sites in Fig. 6c considered in this
paper are all 30 km from both simulated earthquakes, and the induced ground
acceleration exceeds the pseudo-static acceleration threshold (0.14 g) for
triggering submarine landslides (Lee and
Edwards, 1986).
Median response spectra predicted by the global candidate GMPEs
for vertical strike–slip earthquakes with VS30=310 m s-1 at selected epicentral distances (RX). Sa named as an abbreviation of
spectral acceleration.
According to computations conducted using the aforementioned proposed global
GMPE models, the predicted ground motion of a Mw 7 strike–slip fault
can exceed the pseudostatic acceleration threshold of 0.14 g for epicentral
distances greater than 70 km (Fig. 11). Thus, a Mw 7 earthquake
occurring on land may trigger a submarine landslide and may induce a large
tsunami. However, a submarine landslide-induced tsunami can be triggered by
nearby small-magnitude offshore events. Furthermore, multiple submarine
landslides can be triggered by one event at failure sites on the continental
slope, enhancing tsunami hazards. The 2018 Palu earthquake is a real example
of this phenomenon (Gusman
et al., 2019; Heidarzadeh et al., 2019).
Numerous examples have been presented, indicating that submarine landslides
can be triggered by earthquakes. To evaluate the submarine
landslide-induced tsunami hazard, detailed examination of the occurrence of
large earthquakes is necessary. Following the 2004 mega earthquake and
tsunami, the seismic activity in northern Sumatra was low (Fig. 1b). The
absence of earthquakes in the northern SFZ (i.e., at the Aceh and Seulimeum
faults) indicates that this region is vulnerable to future earthquakes with
a large magnitude (McCloskey et al., 2005; Nalbant
et al., 2005). According to historical reports, a large event in 1936
(Mw 7.1–7.3) (Newcomb and McCann,
1987; Sieh and Natawidjaja, 2000) seriously damaged the city of Banda Aceh.
Harbitz et al. (2014) reported on historical tsunamis in Southeast Asia and
described a much older event close to northern Sumatra. In 1837, this
Mw 7.3 event caused substantial damage at Banda Aceh and moderate
damage at more distant coastal areas, such as Penang Island (Malaysia) and
Teluk Ayer (Singapore) (Harbitz et
al., 2014; NCEI, 2019). However, source locations were not identified for
either historical event. To capture this uncertainty in possible source
locations, two strike–slip earthquakes with a magnitude as high as that of
these historical events were simulated in offshore areas, and eight
potential submarine landslide sites were considered in this study (Fig. 6c).
To mitigate tsunami threats from landslide sources, numerical modeling is a
key method for both understanding the landslides and predicting
landslide-induced tsunamis (Harbitz et al., 2014;
Masson et al., 2006). Modeling results indicated that response times in the
northern tip of the Sumatra are less than 10 min for all evaluated
scenarios. Due to the mechanism discrepancies of submarine landslides, the
established Indonesian Tsunami Early Warning System (INATEWS), which was
constructed to provide warnings for tsunamis induced by earthquakes further
away, has limited capability to monitor submarine landslide-induced
tsunamis. Therefore, a new tsunami hazard mitigation and early warning
system for tsunamis caused by landslides should be developed; this is
crucial due to the evidence for a large MTD deposit with a clear sequence
exposed in the seismic section. Although the escape buildings constructed
during the rehabilitation and reconstruction following the 2004 disaster and
some more of such building recently built by the government (Syamsidik, personal
communication, 26 October 2021) are ready for use, these buildings are still insufficient to
accommodate the need for settlements from damaged coastal areas. This lack
of refuge is another issue that must be overcome to successfully manage a
submarine landslide tsunami event. One of the most crucial actions to reduce
the significant damage and victims is to enhance better preparedness and
awareness of tsunami disaster. Although on the northern coast of Aceh the
tsunami preparedness in Aceh is at a good level (Syamsidik et al.,
2021), it is important to enhance the preparedness and awareness of a group
community such as schools, disabilities and others, while opportunities to
enhance the involvement of local institutions could be increased in the activities related to
disaster risk reduction.
In this study, scenarios of submarine landslides triggered by a strike–slip
fault earthquake, which would induce significant landslide tsunamis, have
been demonstrated and quantitatively evaluated. Similar tectonic and
environmental situations can be observed in other regions around the world,
and our identified scenarios may also be relevant in these regions. However,
the compounded tsunami and earthquake hazard in this submarine strike–slip
fault system is still largely neglected in standard seismic hazard
assessments.
Conclusions
A scenario of a submarine landslide in the northern waters offshore Sumatra
triggered by a strike–slip fault system was proposed. The strike–slip fault
movement in the marine environment was demonstrated to trigger a significant
landslide on an unstable continental slope, inducing a tsunami; the effects
were quantitatively evaluated. Evidence of a large MTD deposit was also
observed in the northern offshore area. The northern tip of Sumatra has a
high tsunami risk. This type of tsunami can be triggered by a Mw 7
earthquake occurring on land or by a nearby small-magnitude offshore event.
Furthermore, multiple submarine landslides can be triggered by a single
event, enhancing the tsunami hazard. Similar tectonic and environmental
situations can be observed in other regions around the world, and our
identified scenarios may also be relevant in these regions. According to all
scenarios evaluated in this study, near the coast, the warning time for the
landslide tsunami would be less than 10 min. The established Indonesian
Tsunami Early Warning System constructed to provide warnings for far
earthquake-induced tsunamis has limited capability to monitor submarine
landslide–induced tsunamis. Further landslide tsunami hazard assessments
and improvements in the early warning system in this area could be achieved
by using the proposed scenarios in this study.
Code availability
The COMCOT version 1.7 used in this research is currently not an open-source model but is available from the corresponding author upon reasonable request. GMT 5.4 is available at https://github.com/GenericMappingTools/gmt/releases/tag/5.4.5 (last access: 26 July 2022). Scoop3D is available at 10.3133/tm14A1.
Data availability
The data used in this study could be requested from the corresponding authors.
The supplement related to this article is available online at: https://doi.org/10.5194/nhess-23-507-2023-supplement.
Author contributions
HAH and BSH initiated the original idea and conceptualized the research. FK,
CSLee, CSLiu and AM performed the processing and analysis on the
single-channel seismic reflection data. HAH, CRW, SR, SP, IF and IS
performed the processing and analysis on the community-based bathymetric
survey data. HAH and VBP performed the slope stability analysis and ground
motion prediction with input from BSH and WKL. HAH and IF performed the
tsunami modeling with input from TRW and BSH. All co-authors contributed to
the interpretation of the results and to the article writing led by HAH
and BSH.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
The Body of Rehabilitation and Reconstruction Nanggroe Aceh Darussalam and
Nias coordinated the CBBS project with funding from the ADB (grant number
0002-INO Earthquake and Tsunami Emergency Support Project). Haekal A. Haridhi
would like to thank the Taiwan International Graduate Program (TIGP),
Academia Sinica and National Central University for sponsoring his Ph.D
study. We thank Tedi Yudistira for his effort to digitize the SUMI and
SUMII single-channel seismic reflection data and Ifremer for access to this
dataset, allowing us to fully use the results. We thank Yu-Ting Kuo at
the Institute of Earth Science, Academia Sinica and Danny Chan at the
Institute of Geoscience, National Taiwan Ocean University, for their
assistance in producing some of the figures. We thank Syamsidik at the
Tsunami and Disaster Mitigation Research Center, Universitas Syiah Kuala, for
their support and discussion. We thank the Panglima Laot, fishermen of Lhok
Krueng Aceh, the CBBS team (A. Syukri, A. Bonar, P. Dwi, F. Arif, P. Safrizal, B. Nazaruddin, S. Anjar, U. Maria, M. Siska, N. Suraiya, D. Putra, M. Aris and Zariansyah) and the Network of Aquaculture Centers in Asia-Pacific
for their cooperation, efforts and support during the CBBS data collection.
The Generic Mapping Tools software package was used to draw map figures
(Wessel and Smith, 1991). Thanks for the English edited by
Wallace Academic Editing. Additionally, we sincerely thank the two anonymous reviewers and editor Maria Ana Baptista for their constructive suggestions that have significantly improved the quality of this paper.
Financial support
This research has been supported by the Institute for Information Industry, Ministry of Science and Technology, Taiwan (grant nos. MOST 108-2116-M-001-010-MY3, MOST 108-2116-M-001-010-MY3 and MOST 109-2119-M-001-011). This study was also funded by the Ministry of Education and Culture of the Republic of Indoneia under the Resaerch Center of Universitas Syiah Kuala within the H-Index Scheme (grant no. 169/UN11/SPK/PNBP/2021).
Review statement
This paper was edited by Maria Ana Baptista and reviewed by two anonymous referees.
ReferencesAbrahamson, N. A., Silva, W. J., and Kamai, R.: Summary of the ASK14 ground
motion relation for active crustal regions, Earthq. Spectra, 30,
1025–1055, 10.1193/070913EQS198M, 2014.Araki, E., Shinohara, M., Obana, K., Yamada, T., Kaneda, Y., Kanazawa, T.,
and Suyehiro, K.: Aftershock distribution of the 26 December 2004
Sumatra-Andaman earthquake from ocean bottom seismographic observation,
Earth, Planets Sp., 58, 113–119, 10.1186/bf03353367, 2006.
Badan Metereologi Klimatologi dan Geofisika: Pedoman Pelayanan Peringatan Dini Tsunami InaTEWS Edisi kedua, BMKG, Jakarta, 158 pp., 2012.Barber, A. J. and Milsom, J. S. (Eds): Sumatra: geology, resources and
tectonic evolution, Geological Society of London, Oxford, 1–304, 10.1144/GSL.MEM.2005.031, 2005.Berglar, K., Gaedicke, C., Ladage, S., and Thöle, H.: The Mentawai
forearc sliver off Sumatra: A model for a strike-slip duplex at a regional
scale, Tectonophysics, 710–711, 225–231, 10.1016/j.tecto.2016.09.014,
2017.BIG: DEMNAS – Seamless Digital Elevation Model (DEM) dan Batimetri Nasional, Badan Inf. Geospasial, https://tanahair.indonesia.go.id/demnas/#/ (last access: 26 July 2022), 2018.Bishop, A. W.: The use of the slip circle in the stability analysis of slopes, Geotechnique, 5, 7–17, 10.1680/geot.1955.5.1.7, 1955.Boore, D. M., Stewart, J. P., Seyhan, E., and Atkinson, G. M.: NGA-West2
equations for predicting PGA, PGV, and 5 % damped PSA for shallow crustal
earthquakes, Earthq. Spectra, 30, 1057–1085, 10.1193/070113EQS184M,
2014.Campbell, K. W. and Bozorgnia, Y.: NGA-West2 ground motion model for the
average horizontal components of PGA, PGV, and 5 % damped linear
acceleration response spectra, Earthq. Spectra, 30, 1087–1114,
10.1193/062913EQS175M, 2014.Chiou, B. S. J. and Youngs, R. R.: Update of the Chiou and Youngs NGA model
for the average horizontal component of peak ground motion and response
spectra, Earthq. Spectra, 30, 1117–1153, 10.1193/072813EQS219M,
2014.Dugan, B. and Flemings, P. B.: Fluid flow and stability of the US
continental slope offshore New Jersey from the Pleistocene to the present,
Geofluids, 2, 137–146, 10.1046/j.1468-8123.2002.00032.x, 2002.Duncan, J. M.: State of the art: limit equilibrium and finite-element
analysis of slopes, J. Geotech. Eng., 122, 577–596,
10.1061/(asce)0733-9410(1996)122:7(577), 1996.
Dziewonski, A. M., Chou, T.-A., and Woodhouse, J. H.: Determination of
earthquake source parameters from waveform data for studies of global and
regional seismicity, J. Geophys. Res., 86, 2825–2852, 1981.Ekström, G., Nettles, M., and Dziewonski, A. M.: The global CMT project
2004–2010: Centroid-moment tensors, Phys. Earth Planet. Inter.,
200–201, 1–9, 10.1016/j.pepi.2012.04.002, 2012.Fernández-Blanco, D., Philippon, M., and von Hagke, C.: Structure and
kinematics of the Sumatran Fault System in North Sumatra (Indonesia),
Tectonophysics, 693, 453–464, 10.1016/j.tecto.2016.04.050, 2016.Gasperini, L., Zaniboni, F., Armigliato, A., Tinti, S., Pagnoni, G., Sinan,
M., Marco, Ö., and Francesca, L.: Tsunami potential source in the eastern
Sea of Marmara (NW Turkey), along the North Anatolian Fault system,
Landslides, (June), 10.1007/s10346-022-01929-0, 2022.Genrich, J. F., Bock, Y., McCaffrey, R., Prawirodirdjo, L., Stevens, C. W.,
Puntodewo, S. S. O., Subarya, C., and Wdowinski, S.: Distribution of slip at
the northern Sumatra fault system, J. Geophys. Res., 105, 28327–28341,
10.1029/2000JB900158, 2000.Ghosal, D., Singh, S. C., Chauhan, A. P. S., and Hananto, N. D.: New insights
on the offshore extension of the Great Sumatran fault, NW Sumatra, from
marine geophysical studies, Geochemistry, Geophys. Geosystems, 13, Q0AF06,
10.1029/2012GC004122, 2012.Gusman, A. R., Supendi, P., Nugraha, A. D., Power, W., Latief, H., Sunendar,
H., Widiyantoro, S., Daryono, Wiyono, S. H., Hakim, A., Muhari, A., Wang,
X., Burbidge, D., Palgunadi, K., Hamling, I., and Daryono, M. R.: Source
model for the tsunami inside Palu Bay following the 2018 Palu earthquake,
Indonesia, Geophys. Res. Lett., 46, 8721–8730,
10.1029/2019gl082717, 2019.Hampton, M. A., Lee, H. J., and Locat, J.: Submarine landslides, Rev.
Geophys., 34, 33–59, 10.1029/95RG03287, 1996.Hanks, T. C. and Kanamori, H.: A moment magnitude scale, J. Geophys. Res.,
84, 2348–2350, 10.1029/JB084iB05p02348, 1979.Harbitz, C. B., Løvholt, F., and Bungum, H.: Submarine landslide tsunamis:
How extreme and how likely?, Nat. Hazards, 72, 1341–1374,
10.1007/s11069-013-0681-3, 2014.Haridhi, H. A., Nanda, M., Wilson, C. R., and Rizal, S.: Preliminary study of
the sea surface temperature (SST) at fishing ground locations based on the
net deployment of traditional purse-seine boats in the northern waters of
Aceh – A community-based data collection approach, Reg. Stud. Mar. Sci.,
8, 114–121, 10.1016/j.rsma.2016.10.002, 2016.Heidarzadeh, M. and Satake, K.: Source properties of the 1998 July 17 Papua
New Guinea tsunami based on tide gauge records, Geophys. J. Int., 202,
361–369, 10.1093/gji/ggv145, 2015.Heidarzadeh, M., Harada, T., Satake, K., Ishibe, T., and Takagawa, T.:
Tsunamis from strike-slip earthquakes in the Wharton Basin, northeast Indian
Ocean: March 2016 Mw7.8 event and its relationship with the April 2012 Mw
8.6 event, Geophys. J. Int., 211, 1601–1612, 10.1093/gji/ggx395,
2017.Heidarzadeh, M., Muhari, A., and Wijanarto, A. B.: Insights on the Source of
the 28 September 2018 Sulawesi Tsunami, Indonesia Based on Spectral Analyses
and Numerical Simulations, Pure Appl. Geophys., 176, 25–43,
10.1007/s00024-018-2065-9, 2019.Heidarzadeh, M., Ishibe, T., Sandanbata, O., Muhari, A., and Wijanarto, A.
B.: Numerical modeling of the subaerial landslide source of the 22 December
2018 Anak Krakatoa volcanic tsunami, Indonesia, Ocean Eng., 195, 106733,
10.1016/j.oceaneng.2019.106733, 2020.Heinrich, P. H., Piatanesi, A., and Hébert, H.: Numerical modelling of
tsunami generation and propagation from submarine slumps: The 1998 Papua New
Guinea event, Geophys. J. Int., 145, 97–111,
10.1111/j.1365-246X.2001.00336.x, 2001.Hornbach, M. J., Braudy, N., Briggs, R. W., Cormier, M. H., Davis, M. B.,
Diebold, J. B., Dieudonne, N., Douilly, R., Frohlich, C., Gulick, S. P. S.,
Johnson, H. E., Mann, P., McHugh, C., Ryan-Mishkin, K., Prentice, C. S.,
Seeber, L., Sorlien, C. C., Steckler, M. S., Symithe, S. J., Taylor, F. W.,
and Templeton, J.: High tsunami frequency as a result of combined
strike-slip faulting and coastal landslides, Nat. Geosci., 3, 783–788,
10.1038/ngeo975, 2010.Kawata, Y., Benson, B. C., Borrero, J. C., Borrero, J. L., Daoies, H. L.,
Lange, W. P., Imamura, F., Letz, H., Nott, J., and Synolakis, C. E.: Tsunami
in papua New Guinea was as intense as first thought, Eos (Washington DC),
80, 101–105, 10.1029/99EO00065, 1999.
Lee, J. H. and Edwards, D.: Regional method to assess offshore slope stability,
J. Geothechnical Eng., 112, 489–509,
doi:doi.org/10.1061/(ASCE)0733-9410(1986)112:5(489), 1986.Liu, P. L.-F., Cho, Y.-S., Briggs, M. J., Kanoglu, U., and Synolakis, C. E.:
Runup of solitary waves on a circular island, J. Fluid Mech., 302, 259–285,
10.1017/S0022112095004095, 1995.Liu, X. and Zhao, D.: Upper and lower plate controls on the great 2011
Tohoku-oki earthquake, Sci. Adv., 4, eaat4396, 10.1126/sciadv.aat4396, 2018.Malod, J. A. and Kemal, B. M.: The Sumatra margin: oblique subduction and
lateral displacement of the accretionary prism, Geol. Soc. London, Spec.
Publ., 106, 19–28, 10.1144/GSL.SP.1996.106.01.03, 1996.
Massart, D. L., Smeyers-Verbeke, J., Capron, X., and Schlesier, K.: Visual presentation of data by means of box plots, LC-GC Eur., 18, 215–218, 2005.Masson, D. G., Harbitz, C. B., Wynn, R. B., Pedersen, G., and Løvholt, F.:
Submarine landslides: processes, triggers and hazard prediction, Philos.
Trans. R. Soc. A, 364, 2009–2039, 10.1098/rsta.2006.1810, 2006.McCaffrey, R.: Oblique plate convergence, slip vectors, and forearc
deformation, J. Geophys. Res., 97, 8905–8915, 10.1029/92JB00483,
1992.McCloskey, J., Nalbant, S. S., and Steacy, S.: Earthquake risk from
co-seismic stress, Nature, 434, 291, 10.1038/434291a, 2005.
Moore, G. F., Curray, J. R., Moore, D. G., and Karig, D. E.: Variations in
geologic structure along the Sunda fore arc, Northeastern Indian Ocean, in:
In The Tectonic and Geologic Evolution of Southeast Asian Seas and Islands, edited by:
Hayes, D. E., 23, 145–160, 1980.Muhari, A., Heidarzadeh, M., Susmoro, H., Nugroho, H. D., Kriswati, E.,
Supartoyo, S., Wijanarto, A. B., Imamura, F., and Arikawa, T.: The December
2018 Anak Krakatau volcano tsunami as inferred from post-tsunami field
surveys and spectral analysis, Pure Appl. Geophys.,
176, 1–15,
10.1007/s00024-019-02358-2, 2019.Nalbant, S. S., Steacy, S., Sieh, K., Natawidjaja, D., and McCloskey, J.:
Earthquake risk on the Sunda trench, Nature, 435, 756–757,
10.1038/nature435755a, 2005.Newcomb, K. R. and McCann, W. R.: Seismic history and seismotectonics of the
Sunda Arc, J. Geophys. Res., 92, 421–439, 10.1029/JB092iB01p00421,
1987.
NCEI: The National Center for Environmental Information tsunami run-up database, NOAA, doi:doi:10.7289/V5PN93H7, 2019.Patton, J. R., Stein, R., and Sevilgen, V.: Sunda Strait tsunami launched by
sudden collapse of Krakatau volcano into the sea Cause: Earthquake,
Landslide, or Volcanic Eruption?, Temblor,
10.32858/temblor.001, 2018.Phung, V. B., Loh, C. H., Chao, S. H., Chiou, B. S. J., and Huang, B. S.: Ground motion prediction equation for crustal earthquakes in Taiwan, Earthq. Spectra, 36, 2129–2164, 10.1177/8755293020919415, 2020.Poupardin, A., Calais, E., Heinrich, P., Hébert, H., Rodriguez, M., Leroy, S., Aochi, H., and Douilly, R.: Deep submarine landslide contribution to the 2010 Haiti earthquake tsunami, Nat. Hazards Earth Syst. Sci., 20, 2055–2065, 10.5194/nhess-20-2055-2020, 2020.
Reid, M. E., Christian, S. B., Brien, D. L., and Henderson, S. T.: Scoops3D
– Software to analyze three-dimensional slope stability throughout a
digital landscape: U.S. Geological Survey techniques and methods, in: Book
14, Chapter. A1, p. 218., 2015.
Rizal, S., Haridhi, H. A., Wilson, C. R., Hasan, A., and Setiawan, I.:
Community collection of ocean current data: An example from Northern Aceh
Province, Indonesia, SPC Tradit. Mar. Resour. Manag. Knowl. Inf. Bull., 31,
3–11, 2013.Romano, F., Trasatti, E., Lorito, S., Piromallo, C., Piatanesi, A., Ito, Y.,
Zhao, D., Hirata, K., Lanucara, P., and Cocco, M.: Structural control on the
Tohoku earthquake rupture process investigated by 3D FEM, tsunami and
geodetic data, Sci. Rep., 4, 5631, 10.1038/srep05631, 2014.Sibuet, J. C., Rangin, C., Le Pichon, X., Singh, S., Cattaneo, A.,
Graindorge, D., Klingelhoefer, F., Lin, J.-Y., Malod, J., Maury, T.,
Schneider, J.-L., Sultan, N., Umber, M., and Yamaguchi, H.: 26th December
2004 great Sumatra-Andaman earthquake: Co-seismic and post-seismic motions
in northern Sumatra, Earth Planet. Sci. Lett., 263, 88–103,
10.1016/j.epsl.2007.09.005, 2007.Sieh, K. and Natawidjaja, D.: Neotectonics of the Sumatran fault, Indonesia,
J. Geophys. Res., 105, 28295–28326, 10.1029/2000JB900120, 2000.Socquet, A., Hollingsworth, J., Pathier, E., and Bouchon, M.: Evidence of
supershear during the 2018 magnitude 7.5 Palu earthquake from space geodesy,
Nat. Geosci., 12, 192–199, 10.1038/s41561-018-0296-0, 2019.Song, Y. T., Ji, C., Fu, L. L., Zlotnicki, V., Shum, C. K., Yi, Y., and
Hjorleifsdottir, V.: The 26 December 2004 tsunami source estimated from
satellite radar altimetry and seismic waves, Geophys. Res. Lett., 32,
1–5, 10.1029/2005GL023683, 2005.Syamsidik, Benazir, Luthfi, M., Suppasri, A., and Comfort, L. K.: The 22 December 2018 Mount Anak Krakatau volcanogenic tsunami on Sunda Strait coasts, Indonesia: tsunami and damage characteristics, Nat. Hazards Earth Syst. Sci., 20, 549–565, 10.5194/nhess-20-549-2020, 2020.Syamsidik, Oktari, R. S., Nugroho, A., Fahmi, M., Suppasri, A., Munadi, K.,
and Amra, R.: Fifteen years of the 2004 Indian Ocean Tsunami in
Aceh-Indonesia: Mitigation, preparedness and challenges for a long-term
disaster recovery process, Int. J. Disaster Risk Reduct., 54,
102052, 10.1016/j.ijdrr.2021.102052, 2021.Tappin, D. R., Matsumoto, T., Watts, P., Satake, K., McMurtry, G. M.,
Matsuyama, M., Lafoy, Y., Tsuji, Y., Kanamatsu, T., Lus, W., Iwabuchi, Y.,
Yeh, H., Matsumotu, Y., Nakamura, M., Mahoi, M., Hill, P., Crook, K., Anton,
L., and Walsh, J. P.: Sediment slump likely caused 1998 Papua New Guinea
tsunami, Eos, Trans. Am. Geophys. Union, 80, 329–344,
10.1029/99EO00241, 1999.Tappin, D. R., Grilli, S. T., Harris, J. C., Geller, R. J., Masterlark, T.,
Kirby, J. T., Shi, F., Ma, G., Thingbaijam, K. K. S., and Mai, P. M.: Did a
submarine landslide contribute to the 2011 Tohoku tsunami?, Mar. Geol., 357,
344–361, 10.1016/j.margeo.2014.09.043, 2014.Tsuji, Y., Satake, K., Ishibe, T., Kusumoto, S., Harada, T., Nishiyama, A.,
Kim, H. Y., Ueno, T., Murotani, S., Oki, S., Sugimoto, M., Tomari, J.,
Heidarzadeh, M., Watada, S., Imai, K., Choi, B. H., Yoon, S. B., Bae, J. S.,
Kim, K. O., and Kim, H. W.: Field Surveys of Tsunami Heights from the 2011
off the Pacific Coast of Tohoku, Japan Earthquake, Bull. Earthq. Res. Institute, Univ. Tokyo, 86, 29–279,
http://www.eri.u-tokyo.ac.jp/BERI/pdf/IHO86301.pdf (last access: 26 July 2022), 2011 [in Japanese with English
abstract].Wang, X.: User manual for COMCOT version 1.7,
https://pdfs.semanticscholar.org/401d/e93588d6c28d0c3984044ad1f95b75dadab0.pdf (last access: 26 July 2022),
2009.Wang, X. and Liu, P. L.-F.: An analysis of 2004 Sumatra earthquake fault
plane mechanisms and Indian Ocean tsunami, J. Hydraul. Res., 44,
147–154, 10.1080/00221686.2006.9521671, 2006.Watts, P., Grilli, S. T., Kirby, J. T., Fryer, G. J., and Tappin, D. R.: Landslide tsunami case studies using a Boussinesq model and a fully nonlinear tsunami generation model, Nat. Hazards Earth Syst. Sci., 3, 391–402, 10.5194/nhess-3-391-2003, 2003.
Wells, D. L. and Coppersmith, K. J.: New empirical relationships among
magnitude, rupture length, rupture width, rupture area, and surface
displacement, Bull. Seismol. Soc. Am., 84, 974–1002, 1994.Wessel, P. and Smith, W. H. F.: Free software helps map and display data,
Eos, Trans. Am. Geophys. Union, 72, 441–448, 10.1029/90EO00319,
1991.Wilson, C. and Linkie, M.: The Panglima Laot of Aceh: a case study in
large-scale community-based marine management after the 2004 Indian Ocean
tsunami, Oryx, 46, 495–500, 10.1017/S0030605312000191, 2012.
Ye, L., Kanamori, H., Rivera, L., Lay, T., Zhou, Y., Sianipar, D., and
Satake, K.: The 22 December 2018 tsunami from flank collapse of Anak
Krakatau volcano during eruption, Sci. Adv., 6, 0–8,
10.1126/sciadv.aaz1377, 2020.Zitter, T. A. C., Grall, C., Henry, P., Özeren, M. S., Çagatay, M.
N., Şengör, A. M. C., Gasperini, L., de Lépinay, B. M., and
Géli, L.: Distribution, morphology and triggers of submarine mass
wasting in the Sea of Marmara, Mar. Geol., 329–331, 58–74,
10.1016/j.margeo.2012.09.002, 2012.