BENCHMARK PALU
Indonesia's complex geological setting demands modeling for multi-source tsunami events, as landslides may occur alongside seismic activity or volcanic eruptions. Comprehensive modeling that considers these overlapping hazards is essential for accurate hazard assessment.
In this study, by performing geological field surveys and mapping, we provide an expert-based susceptibility analysis of tsunamigenic landslides, using the 2018 Palu tsunami in Palu Bay as a benchmark. We identify key geological indicators-such as slope geometry, sediment composition, and fault proximity-that signal a region's potential for tsunamigenic landslides. The results are validated through ring shear test experiments to better understand the dynamic strength behavior of coastal and submarine sediments in Palu Bay, which are closely linked to landslide initiation mechanisms. This case study not only enhances our understanding of the local geohazard conditions but also serves as a valuable reference for applying similar analyses in other tsunami-prone regions across Indonesia. By leveraging the methodologies and findings from the Palu case, disaster risk assessments in areas with comparable geological settings can be significantly improved.
The tsunami numerical model can be used to simulate the potential tsunami generated by submarine landslides or other non-seismic sources. Observations such as bathymetric surveys and seismic data can help reveal surface and subsurface features of the seafloor, allowing for the estimation of the landslide material volume. The assessment of submarine landslide volume can also be conducted using seismic waves recorded by passive sensors such as broadband and short-period seismometers. The energy derived from surface waves observed on seismograms can provide insight into the seismic wave energy corresponding to the landslide material volume. This information can then be validated using facilities such as a tsunami flume. All of this-numerical modeling, validation, and laboratory experiments-can contribute significantly to the development of an early warning system for non-seismic tsunami events.
seismic data can help reveal surface and subsurface features of the seafloor, allowing for the estimation of the landslide material volume. The assessment of submarine landslide volume can also be conducted using seismic waves recorded by passive sensors such as broadband and short-period seismometers. The energy derived from surface waves observed on seismograms can provide insight into the seismic wave energy corresponding to the landslide material volume. This information can then be validated using facilities such as a tsunami flume. All of this-numerical modeling, validation, and laboratory experiments-can contribute significantly to the development of an early warning system for non-seismic tsunami events.
