On the potential for megathrust earthquakes and tsunamis off the southern coast of West Java and southeast Sumatra, Indonesia

High seismicity rates in and around West Java and Sumatra occur as a result of the Indo-Australian plate converging with and subducting beneath the Sunda plate. Large megathrust events associated with this process likely pose a major earthquake and tsunami hazard to the surrounding community, but further effort is required to help understand both the likelihood and frequency of such events. With this in mind, we exploit catalog seismic data sourced from the Agency for Meteorology, Climatology, and Geophysics (BMKG) of Indonesia and the International Seismological Centre (ISC) for the period April 2009 through to July 2020, in order to conduct earthquake hypocenter relocation using a teleseismic double-difference method. Our results reveal a large seismic gap to the south of West Java and southeast Sumatra, which is in agreement with a previous GPS study that finds the region to be a potential future source of megathrust earthquakes. To investigate this further, tsunami modeling was conducted in the region for two scenarios based on the estimated seismicity gaps and the existence of a backthrust fault. We show that the maximum tsunami height could be up to 34 m along the west coast of southernmost Sumatra and along the south coast of Java near the Ujung Kulon Peninsula. This estimate is comparable with the maximum tsunami height predicted by a previous study of southern Java in which earthquake sources were derived from the inversion of GPS data. However, the present study extends the analysis to southeast Sumatra and demonstrates that estimating rupture from seismic gaps can lead to reliable tsunami hazard assessment in the absence of GPS data.publishedVersio

Coupled, Physics-Based Modeling Reveals Earthquake Displacements are Critical to the 2018 Palu, Sulawesi Tsunami

The September 2018, Mw 7.5 Sulawesi earthquake occurring on the Palu-Koro strike-slip fault system was followed by an unexpected localized tsunami. We show that direct earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay. To this end, we use a physics-based, coupled earthquake–tsunami modeling framework tightly constrained by observations. The model combines rupture dynamics, seismic wave propagation, tsunami propagation and inundation. The earthquake scenario, featuring sustained supershear rupture propagation, matches key observed earthquake characteristics, including the moment magnitude, rupture duration, fault plane solution, teleseismic waveforms and inferred horizontal ground displacements. The remote stress regime reflecting regional transtension applied in the model produces a combination of up to 6 m left-lateral slip and up to 2 m normal slip on the straight fault segment dipping 65∘ East beneath Palu Bay. The time-dependent, 3D seafloor displacements are translated into bathymetry perturbations with a mean vertical offset of 1.5 m across the submarine fault segment. This sources a tsunami with wave amplitudes and periods that match those measured at the Pantoloan wave gauge and inundation that reproduces observations from field surveys. We conclude that a source related to earthquake displacements is probable and that landsliding may not have been the primary source of the tsunami. These results have important implications for submarine strike-slip fault systems worldwide. Physics-based modeling offers rapid response specifically in tectonic settings that are currently underrepresented in operational tsunami hazard assessment

Insights on the source of the 28 September 2018 Sulawesi tsunami, Indonesia based on spectral analyses and numerical simulations

The 28 September 2018 Sulawesi tsunami has been a puzzle because extreme deadly tsunami waves were generated following an Mw 7.5 strike-slip earthquake, while such earthquakes are not usually considered to produce large tsunamis. Here, we obtained, processed and analyzed two sea level records of the tsunami in the near-field (Pantoloan located inside the Palu Bay) and far-field (Mamuju located outside the Palu Bay) and conducted numerical simulations to shed light on the tsunami source. The two tide gauges recorded maximum tsunami trough-to-crest heights of 380 and 24 cm, respectively, with respective dominating wave periods of 3.6-4.4 and 10 min, and respective high-energy wave duration of 5.5 and [14 h. The two observed waveforms were significantly different with wave amplitude and period ratios of *16 and *3, respectively. We infer tsunamigenic source dimen19 sions of 3.4–4.1 km and 32.5 km, for inside and outside of the Palu Bay, respectively. Our numerical simulations fairly well repro21 duced both tsunami observations in Pantoloan and Mamuju; except for the arrival time in Mamuju. However, it was incapable of reproducing the maximum reported coastal amplitudes of 6–11 m. It is possible that these two sources are different parts of the same tectonic source. A bay oscillation mode of *85 min was revealed for the Palu Bay through numerical modeling. Actual sea surface disturbances and landslide-generated waves were captured by two video recordings from inside the Palu Bay shortly after the earthquake. It is possible that a large submarine landslide contributed to and intensified the Sulawesi tsunami. We identify the southern part of the Palu Bay, around the latitude of -0.82o S, as the most likely location of a potential landslide based on our backward tsunami ray tracing analysis. However, marine geological data from the Palu Bay are required to confirm such hypothesis

Examination of three practical run-up models for assessing tsunami impact on highly populated areas

This paper describes the examination of three practical tsunami run-up models that can be used to assess the tsunami impact on human beings in densely populated areas. The first of the examined models applies a uniform bottom roughness coefficient throughout the study area. The second uses a very detailed topographic data set that includes the building height information integrated on a Digital Elevation Model (DEM); and the third model utilizes different bottom roughness coefficients, depending on the type of land use and on the percentage of building occupancy on each grid cell. These models were compared with each other by taking the one with the most detailed topographic data (which is the second) as reference. The analysis was performed with the aim of identifying how specific features of high resolution topographic data can influence the tsunami run-up characteristics. Further, we promote a method to be used when very detailed topographic data is unavailable and discuss the related limitations. To this purpose we demonstrate that the effect of buildings on the tsunami flow can be well modeled by using an equivalent roughness coefficient if the topographic data has no information of building height. The results from the models have been utilized to quantify the tsunami impact by using the tsunami casualty algorithm. The models have been applied in Padang city, Indonesia, which is one of the areas with the highest potential of tsunami risk in the world