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. Appeared online in Front. Earth Sci., 29 April 2021

In November, 2018 a workshop of experts sponsored by UNESCO’s Intergovernmental Oceanographic Commission was convened in Wellington, New Zealand. The meeting was organized by Working Group (WG) 1 of the Pacific Tsunami Warning System (PTWS). The meeting brought together fourteen experts from various disciplines and four different countries (New Zealand, Australia, USA and French Polynesia) and four observers from Pacific Island countries (Tonga, Fiji), with the objective of understanding the tsunami hazard posed by the Tonga-Kermadec trench, evaluating the current state of seismic and tsunami instrumentation in the region and assessing the level of readiness of at-risk populations. The meeting took place in the “Beehive” Annex to New Zealand’s Parliament building nearby the offices of the Ministry of Civil Defence and Emergency Management. The meeting was co-chaired by Mrs. Sarah-Jayne McCurrach (New Zealand) from the Ministry of Civil Defence and Emergency Management and Dr. Diego Arcas (USA) from NOAA’s Pacific Marine Environmental Laboratory. As one of the meeting objectives, the experts used their state-of-the-science knowledge of local tectonics to identify some of the potential, worst-case seismic scenarios for the Tonga-Kermadec trench. These scenarios were ranked as low, medium and high probability events by the same experts. While other non-seismic tsunamigenic scenarios were acknowledged, the level of uncertainty in the region, associated with the lack of instrumentation prevented the experts from identifying worse case scenarios for non-seismic sources. The present report synthesizes some of the findings of, and presents the seismic sources identified by the experts to pose the largest tsunami risk to nearby coastlines. In addition, workshop participants discussed existing gaps in scientific knowledge of local tectonics, including seismic and tsunami instrumentation of the trench and current level of tsunami readiness for at-risk populations, including real-time tsunami warnings. The results and conclusions of the meeting are presented in this report and some recommendations are summarized in the final section.

Offshore Probabilistic Tsunami Hazard Assessments (offshore PTHAs) provide large-scale analyses of earthquake-tsunami frequencies and uncertainties in the deep ocean, but do not provide high-resolution onshore tsunami hazard information as required for many risk-management applications. To understand the implications of an onshore PTHA for the onshore hazard at any site, in principle the tsunami inundation should be simulated locally for every scenario in the offshore PTHA. In practice this is rarely feasible due to the computational expense of inundation models, and the large number of scenarios in offshore PTHAs. Monte-Carlo methods offer a practical and rigorous alternative for approximating the onshore hazard, using a random subset of scenarios. The resulting Monte-Carlo errors can be quantified and controlled, enabling high-resolution onshore PTHAs to be implemented at a fraction of the computational cost. This study develops novel Monte-Carlo sampling approaches for offshore-to-onshore PTHA. Modelled offshore PTHA wave heights are used to preferentially sample scenarios that have large offshore waves near an onshore site of interest. By appropriately weighting the scenarios, the Monte-Carlo errors are reduced without introducing any bias. The techniques are applied to a high-resolution onshore PTHA for the island of Tongatapu in Tonga. In this region, the new approaches lead to efficiency improvements equivalent to using 4-18 times more random scenarios, as compared with stratified-sampling by magnitude, which is commonly used for onshore PTHA. The greatest efficiency improvements are for rare, large tsunamis, and for calculations that represent epistemic uncertainties in the tsunami hazard. To facilitate the control of Monte-Carlo errors in practical applications, this study also provides analytical techniques for estimating the errors both before and after inundation simulations are conducted. Before inundation simulation, this enables a proposed Monte-Carlo sampling scheme to be checked, and potentially improved, at minimal computational cost. After inundation simulation, it enables the remaining Monte-Carlo errors to be quantified at onshore sites, without additional inundation simulations. In combination these techniques enable offshore PTHAs to be rigorously transformed into onshore PTHAs, with full characterisation of epistemic uncertainties, while controlling Monte-Carlo errors. Appeared online in Geophysical Journal International 11 April 2022.