Two major marine surveys off northern Papua New Guinea (PNG) earlier this year now suggest, when survivors' reports are taken into account, that last summer's disastrous tsunami there was caused by a sediment slump 25 km offshore. The slump was probably the result of seabed shaking from an earthquake. Not only was a sediment slump, or submarine landslide, responsible for the tsunami, according to the data, but the magnitude and wave‐height distribution of the tsunami along the coast were the result of focusing by local seabed morphology. The conclusions are based on new off‐shore bathymetry, remote operated vehicle (ROV) dive investigations, the time delay between the source earthquake and when the tsunami struck, computer simulation models, and earthquake aftershock distribution. The most critical evidence is in survivors' accounts of the timing of the tsunami relative to the initially felt earthquake and aftershock [see Davies, 1998a].

Tsunamis are unpredictable and infrequent but potentially large impact natural disasters. To prepare, mitigate and prevent losses from tsunamis, probabilistic hazard and risk analysis methods have been developed and have proved useful. However, large gaps and uncertainties still exist and many steps in the assessment methods lack information, theoretical foundation, or commonly accepted methods. Moreover, applied methods have very different levels of maturity, from already advanced probabilistic tsunami hazard analysis for earthquake sources, to less mature probabilistic risk analysis. In this review we give an overview of the current state of probabilistic tsunami hazard and risk analysis. Identifying research gaps, we offer suggestions for future research directions. An extensive literature list allows for branching into diverse aspects of this scientific approach.

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The Mw 7.5 earthquake that struck Central Sulawesi, Indonesia, on September 28, 2018, was rapidly followed by coastal landslides and destructive tsunami waves within Palu Bay. Here, we present new tsunami modeling that supports a dual source mechanism from the supershear strike-slip earthquake and coastal landslides. Up until now the tsunami mechanism: earthquake, coastal landslides, or a combination of both, has remained controversial, because published research has been inconclusive; with some studies explaining most observations from the earthquake and others the landslides. Major challenges are the numerous different earthquake source models used in tsunami modeling, and that landslide mechanisms have been hypothetical. Here, we simulate tsunami generation using three published earthquake models, alone and in combination with seven coastal landslides identified in earlier work and confirmed by field and bathymetric evidence which, from video evidence, produced significant waves. To generate and propagate the tsunamis, we use a combination of two wave models, the 3D non-hydrostatic model NHWAVE and the 2D Boussinesq model FUNWAVE-TVD. Both models are nonlinear and address the physics of wave frequency dispersion critical in modeling tsunamis from landslides, which here, in NHWAVE are modeled as granular material. Our combined, earthquake and coastal landslide, simulations recreate all observed tsunami runups, except those in the southeast of Palu Bay where they were most elevated (10.5 m), as well as observations made in video recordings and at the Pantoloan Port tide gauge located within Palu Bay. With regard to the timing of tsunami impact on the coast, results from the dual landslide/earthquake sources, particularly those using the supershear earthquake models are in good agreement with reconstructed time series at most locations. Our new work shows that an additional tsunami mechanism is also necessary to explain the elevated tsunami observations in the southeast of Palu Bay. Using partial information from bathymetric surveys in this area we show that an additional, submarine landslide here, when simulated with the other coastal slides, and the supershear earthquake mechanism better explains the observations. This supports the need for future marine geology work in this area.

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We use satellite imagery to investigate the shoreline changes associated with volcanic activity in 2018–2019 at Anak Krakatau, Indonesia, spanning a major lateral collapse and period of regrowth through explosive activity. The shoreline changes have been analyzed and validated through the adaptation of an existing methodology based on Sentinel-2 multispectral imagery and developed on Google Earth Engine. This work tests the results of this method in a highly dynamic volcanic environment and validates them with manually digitized shorelines. The analysis shows that the size of the Anak Krakatau Island increased from 2.84 km2 to 3.19 km2 during 15 May 2018–1 November 2019 despite the loss of area in the 22 December 2018 lateral collapse. The lateral collapse reduced the island area to ~1.5 km2 but this was followed by a rapid increase in area in the first two months of 2019, reaching up to 3.27 km2. This was followed by a period of little change as volcanic activity declined and then by a net decrease from May 2019 to 1 November 2019 that resulted from erosion on the SW side of the island. This history of post-collapse eruptive regrowth and coastal erosion derived from the shoreline changes illuminates the potential for satellite-based automated shoreline mapping to provide databases for monitoring remote island volcanoes.