Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run‐up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

Large tsunamis occur infrequently but have the capacity to cause enormous numbers of casualties, damage to the built environment and critical infrastructure, and economic losses. A sound understanding of tsunami hazard is required to underpin management of these risks, and while tsunami hazard assessments are typically conducted at regional or local scales, globally consistent assessments are required to support international disaster risk reduction efforts, and can serve as a reference for local and regional studies. This study presents a global-scale probabilistic tsunami hazard assessment (PTHA), extending previous global-scale assessments based largely on scenario analysis. Only earthquake sources are considered, as they represent about 80% of the recorded damaging tsunami events. Globally extensive estimates of tsunami run-up height are derived at various exceedance rates, and the associated uncertainties are quantified. Epistemic uncertainties in the exceedance rates of large earthquakes often lead to large uncertainties in tsunami run-up. Deviations between modelled tsunami run-up and event observations are quantified, and found to be larger than suggested in previous studies. Accounting for these deviations in PTHA is important, as it leads to a pronounced increase in predicted tsunami run-up for a given exceedance rate.

Abstract. Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence-based decision-making regarding risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean tsunami, but this has been largely concentrated on the Sunda Arc with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment produces time-independent forecasts of tsunami hazards at the coast using data from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500-2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting the larger maximum magnitudes. The annual probability of experiencing a tsunami with a height of > 0.5 m at the coast is greater than 10 % for Sumatra, Java, the Sunda islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of > 3.0 m, which would cause significant inundation and fatalities, is 1-10 % in Sumatra, Java, Bali, Lombok and north Papua, and 0.1-1 % for north Sulawesi, Seram and Flores. The results of this national-scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

A sensitivity study is undertaken to assess the utility of different onshore digital elevation models (DEMs) for simulating the extent of tsunami inundation using case studies from two locations in Indonesia. We compare airborne IFSAR, ASTER, and SRTM against high resolution LiDAR and stereo-camera data in locations with different coastal morphologies. Tsunami inundation extents modeled with airborne IFSAR DEMs are comparable with those modeled with the higher resolution datasets and are also consistent with historical run-up data, where available. Large vertical errors and poor resolution of the coastline in the ASTER and SRTM elevation datasets cause the modeled inundation extent to be much less compared with the other datasets and observations. Therefore, ASTER and SRTM should not be used to underpin tsunami inundation models. A model mesh resolution of 25 m was sufficient for estimating the inundated area when using elevation data with high vertical accuracy in the case studies presented here. Differences in modeled inundation between digital terrain models (DTM) and digital surface models (DSM) for LiDAR and IFSAR are greater than differences between the two data types. Models using DTM may overestimate inundation while those using DSM may underestimate inundation when a constant Manning's roughness value is used. We recommend using DTM for modeling tsunami inundation extent with further work needed to resolve the scale at which surface roughness should be parameterized.

Abstract. Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence based decision making on risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean Tsunami, but this has been largely concentrated on the Sunda Arc, with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent Probabilistic Tsunami Hazard Assessment (PTHA) for Indonesia. This assessment produces time independent forecasts of tsunami hazard at the coast from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte-carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and through sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500–2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting larger maximum magnitudes along the Sunda Arc. The annual probability of experiencing a tsunami with a height at the coast of > 0.5 m is greater than 10% for Sumatra, Java, the Sunda Islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of >3.0 m, which would cause significant inundation and fatalities, is 1–10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1–1% for north Sulawesi, Seram and Flores. The results of this national scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

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A probabilistic seismic hazard assessment that includes the effect of site amplification is undertaken for the island of Sulawesi, Indonesia. High seismic activity rates, both along fast-slipping crustal faults including the major Palu-Koro–Matano Fault System and in regions of distributed deformation, contribute to moderate–high earthquake hazard over all but the SW part of the island. Of particular concern in terms of seismic risk are the numerous cities sited on soft sedimentary basins that have formed due to movement along presently active structures and that can be expected to amplify earthquake ground motions, including the provincial capitals of Palu and Gorontalo.

Probabilistic Tsunami Hazard Assessment (PTHA) often proceeds by constructing a suite of hypothetical earthquake scenarios, and modelling their tsunamis and occurrence-rates. Both tsunami and occurrence-rate models are affected by the representation of earthquake slip and rigidity, but the overall importance of these factors for far-field PTHA is unclear. We study the sensitivity of an Australia-wide PTHA to six different far-field earthquake scenario representations, including two rigidity models (constant and depth-varying) combined with three slip models: fixed-areauniform-slip (with rupture area deterministically related to magnitude); variable-area-uniform-slip; and spatially heterogeneousslip. Earthquake-tsunami scenarios are tested by comparison with DART-buoy tsunami observations, demonstrating biases in some slip models. Scenario occurrence-rates are modelled using Bayesian techniques to account for uncertainties in seismic coupling, maximum-magnitudes and Gutenberg-Richter b-values. The approach maintains reasonable consistency with the historical earthquake record and spatially variable plate convergence rates for all slip/rigidity model combinations, and facilitates partial correction of model-specific biases (identified via DART-buoy testing). The modelled magnitude exceedance-rates are tested by comparison with rates derived from long-term historical and paleoseismic data and alternative moment-conservation techniques, demonstrating the robustness of our approach. The tsunami hazard offshore of Australia is found to be insensitive to the choice of rigidity model, but significantly affected by the choice of slip model. The fixed-area-uniform-slip model produces lower hazard than the other slip models. Bias adjustment of the variable-areauniform-slip model produces a strong preference for 'compact' scenarios, which compensates for a lack of slip heterogeneity. Thus, both heterogeneous-slip and variable-area-uniform-slip models induce similar far-field tsunami hazard.