Located within an intraplate setting, continental Australia has a relatively low rate of seismicity compared with its surrounding plate boundary regions. However, the plate boundaries to the north and east of Australia host significant earthquakes that can impact Australia. Large plate boundary earthquakes have historically generated damaging ground shaking in northern Australia, including Darwin. Large submarine earthquakes have historically generated tsunami impacting the coastline of Australia. Previous studies of tsunami hazard in Australia have focussed on the threat from major subduction zones such as the Sunda and Kermadec Arcs. Although still subject to uncertainty, our understanding of the location, geometry and convergence rates of these subduction zones is established by global tectonic models. Conversely, actively deforming regions in central and eastern Indonesia, the Papua New Guinea region and the Macquarie Ridge region are less well defined, with deformation being more continuous and less easily partitioned onto discrete known structures. A number of recently published geological, geodetic and seismological studies are providing new insights into present-day active tectonics of these regions, providing a basis for updating earthquake source models for earthquake and tsunami hazard assessment. This report details updates to earthquake source models in active tectonic regions along the Australian plate boundary, with a primary focus on regions to the north of Australia, and a subsidiary focus on the Puyesgur-Macquarie Ridge-Hjort plate boundary south of New Zealand. The motivation for updating these source models is threefold: 1. To update regional source models for the 2018 revision of the Australian probabilistic tsunami hazard assessment (PTHA18); 2. To update regional source models for the 2018 revision of the Australian national seismic hazard assessment (NSHA18); and 3. To provide an updated database of earthquake source models for tsunami hazard assessment in central and eastern Indonesia, in support of work funded through the Department of Foreign Affairs and Trade (DFAT) DMInnovation program.

In 2018, Geoscience Australia updated and released the Probabilistic Tsunami Hazard Assessment (PTHA), which outlines the tsunami hazard for all of Australia and its offshore territories.

This study tests three models for generating stochastic earthquake-tsunami scenarios on subduction zones by comparison with deep ocean observations from 18 tsunamis in 2006-2016. It focusses on the capacity of uncalibrated models to generate a realistic distribution of hypothetical tsunamis, assuming the earthquake location, magnitude and subduction interface geometry are approximately known, while details of the rupture area and slip distribution are unknown. <p>Modelling problems like this arise in tsunami hazard assessment, and when using historical and paleo-tsunami observations to study pre-instrumental earthquakes. Tsunamis show significant variability depending on their parent earthquake's properties, and it is important that this is realistically represented in stochastic tsunami scenarios. To clarify which aspects of earthquake variability should be represented, three scenario generation approaches with increasing complexity are tested: a simple fixed-area-uniform-slip model with earthquake area and slip deterministically related to moment magnitude; a variable-area-uniform-slip model which accounts for earthquake area variability; and a heterogeneous-slip model which accounts for both earthquake area variability and slip heterogeneity. The models are tested using deep-ocean tsunami time-series from 18 events (2006-2016) with moment magnitude $M_{w} > 7.7$. <p>For each model and each observed event a `corresponding family of model scenarios' is generated which includes random scenarios with earthquake location and magnitude similar to the observation, with no additional calibration. For an ideal model (which perfectly characterises the variability of tsunamis) the 18 observed events should appear like a random sample of size 18, created by taking one draw from each of the 18 `corresponding family of model scenarios'. This idea facilitates the development of statistical approaches to test the models. <p>Firstly a goodness-of-fit criterion is developed to identify random scenarios `most similar' to the observed tsunamis, and assess the capacity of different models to produce good-fitting scenarios. Both the heterogeneous-slip and variable-area-uniform-slip models show similar capacity to generate tsunamis similar to observations, while the fixed-area-uniform-slip model performs much more poorly in some cases. Secondly the observed tsunami stage ranges are tested for consistency with the null hypothesis that they were randomly generated by the model. The null hypothesis cannot be rejected for the heterogeneous-slip model, whereas both uniform-slip models exhibit a statistically significant tendency to produce small tsunamis too often. <p>Finally the statistical properties of random earthquake scenarios are compared against those earthquake scenarios that best fit the observations. For the variable-area-uniform-slip models the best-fitting model scenarios have higher slip on average than the random scenarios, highlighting biases in this model. Such biases are not evident in the heterogeneous-slip model. The techniques developed in this study can be applied to test random tsunami scenario generation techniques, identify and partially correct their biases, and provide better justification for their use in applications.

In the early hours of 23 May 1960, an earthquake and tsunami struck Chile. There were no morning television shows and newspapers had already been printed for the day. Tsunami warning systems for Australia did not exist and there were no tools nor knowledge to help Australia prepare. Thankfully, we live in different times.