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Traces of past landslides were found on the seabed of Palabuhanratu Bay, West Java. This landslide is thought to have generated a tsunami, but has never been investigated before. This bay is located around the western part of the Cimandiri Fault which is an active horizontal fault with a length of 100 km. Therefore, it is necessary to study the potential impact of a tsunami in the Palabuhanratu Bay area caused by a combination of local earthquakes and underwater landslides around the bay. Evidence of past landslides was revealed through side-scan sonar data from the underwater research vessel Baruna Jaya IV in Palabuhanratu Bay, Indonesia, in 2020. The data from this survey provides evidence of debris flows (historical landslide data) at the survey site. We simulated 29 tsunami scenarios from combined landslide earthquake sources by solving shallow water nonlinear equations numerically. Tsunami sources from earthquakes are classified into three types, e.g., land faults, sea faults, and combinations of land and sea faults. While the source of the tsunami from the landslide is divided by volume. Combination of the earthquake magnitudes range from M6.80 to M7.85, and the landslide volume ranged from 3.06 × 105 m3 to 2.5 × 108 m3. This study concludes that in our scenario, the M8.12 type T7 earthquake generates the largest tsunami in the study area, followed by the T6L5 scenario with M7.85 from the Cimandiri Fault and landslide with a total volume of 2.5 × 108 m3. [ABSTRACT FROM AUTHOR]

An unusual devastating tsunami occurred on September 28, 2018 after a strike‐slip faulting earthquake in Sulawesi, Indonesia. The induced tsunami struck Palu city with ∼4‐m flow depth. We performed two analyses to investigate the source of the tsunami. We first conducted the teleseismic source inversion and obtained the overall slip distribution of the strike‐slip fault. Our tsunami simulation from the coseismic deformation of the seismically estimated strike‐slip faulting produced a tsunami comparable to the leading part of the observation at Pantoloan. In order to reconstruct the detailed slip distribution on the fault plane, we then jointly utilized the tsunami waveform and Synthetic Aperture Radar (SAR) data. Because of the lack of SAR data in the bay, the tsunami data is necessary to constrain the offshore slip distribution, which directly induces the tsunami. The inverted source model shows a strike‐slip fault which consists of three segments extending from the epicenter to the south of 1.4°S with two bends and two asperities around Palu city. The joint inversion model accurately reconstructs the observed surface displacements and the leading part of the tsunami waveform. Our result exhibits the significant contribution of the strike‐slip faulting to the tsunami, but it also suggests additional tsunami sources, such as landslides, for the high inundations near Palu bay. The result also indicates that regional devastating tsunamis can be generated by an onshore strike‐slip fault with localized large dip slip. Plain Language Summary: The Palu, Indonesia, earthquake of September 28, 2018 produced tsunami flooding and damage in Palu city. Because of its strike‐slip mechanism, which is typically not efficient to produce tsunamis, multiple submarine landslides have been speculated as a tsunami source. We found that the fault model estimated by teleseismic waves (recorded globally outside Indonesia) can reproduce the tsunami recorded at the Pantoloan station in Palu bay. This indicates that the source of tsunami recoded at Pantoloan is mostly the fault motion due to the earthquake. We then combined the displacements measured by Synthetic Aperture Radar images and the Pantoloan tsunami waveform to estimate the detailed slip distribution on the fault. The slip model shows a strike‐slip fault with two large slip areas located near Palu city between two bends. This model well reproduces the Pantoloan tsunami but fails to fully reproduce the inundations in Palu city, suggesting that additional tsunami sources, such as landslides, should be responsible for the large inundations in Palu city. Our result suggests that a strike‐slip fault can induce a devastating local tsunami. Key Points: Two analyses utilizing teleseismic, Synthetic Aperture Radar, and tsunami data retrieve an earthquake source model that explains the observed tsunamiA strike‐slip fault with localized large dip slip of the 2018 Palu earthquake induced the devastating regional tsunamiOnshore strike‐slip faults should also be regarded as a potential source of tsunamis for regional areas [ABSTRACT FROM AUTHOR]

In the subduction zone off the west coast of central Sumatra, two great earthquakes, the 2007 great Bengkulu earthquake (Mw 8.4) and the 2010 Mentawai tsunami earthquake (Mw 7.8), occurred along the plate interface. Although the moment magnitude of the 2010 earthquake was much smaller than that of the 2007 earthquake, the tsunami heights resulting from the former 2010 earthquake were higher than those resulting from the latter 2007 earthquake, indicating that tsunami heights are difficult to forecast. An advanced method for determining appropriate source models that can explain the tsunami heights along coastal areas is needed for tsunami warning purposes. In this study, fault parameters were estimated from the W-phase inversion, and fault length and width were calculated from suitable scaling relations between those and the magnitude for the 2007 and 2010 earthquakes. Tsunami numerical simulations were conducted using various slip amounts or corresponding rigidities. The best slip amount or corresponding rigidity was selected by comparing the measured and computed tsunami heights. For the 2007 Bengkulu earthquake, the measured tsunami heights are well explained using a rigidity of 3.0 × 1010 Nm−2 (7.59-m slip amount). For the 2010 Mentawai tsunami earthquake, the measured tsunami heights are well explained using a rigidity of 1.5 × 1010 Nm−2 (8.17-m slip amount). From those results, we determined the depth-dependent rigidity relation for Central Sumatra to estimate appropriate source models in our tsunami height forecasting method. [ABSTRACT FROM AUTHOR]

We estimate the fault model of the 2 September 2009 Tasikmalaya intraslab earthquake based on the GPS data available in western Java, Indonesia. The focal mechanism of the earthquake was used to help construct two possible fault models: a west-dipping fault with a strike of 160.8° and an east-dipping fault with a strike of 34.0°. In this study, vertical information from GPS data is crucial for constructing the top depth of the fault. The subsidence information from GPS data located near the epicenter suggests that the earthquake involved a deeper fault model. While the amount of the moment release of the east-dipping fault (Model dipE) is equivalent to Mw 6.9, the moment release of the west-dipping fault (Model dipW) is equivalent to Mw 6.8. The GPS data inversion indicates that Model dipW produces a better fit than Model dipE. The tsunami simulation indicates that the tsunami height generated by the east-dipping fault is smaller than that generated by the west-dipping fault, implying that the maximum tsunami height of the latter is closer to agreement with the reported one. Unlike Model dipE, the stress transfer analysis of Model dipW indicates that most of the aftershocks were located in the region where ΔCFF is positive, suggesting positive stress from the ruptured triggered aftershocks. The combined analysis of GPS data, tsunami simulation, and stress transfer suggests that the fault ruptured during the 2009 earthquake was dipping westward with a steep dip angle. • GPS data, tsunami simulation, and stress transfer for analysing crustal deformation related to earthquake occurrences. • The 2009 Tasikmalaya intraslab earthquake ruptured at a west-dipping fault. • Positive stress from the mainshock triggering the aftershocks explain by the at a west-dipping fault. [ABSTRACT FROM AUTHOR]