Seismic hazard modelling is a multi-disciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such seismic hazard models consist of a probabilistic framework that models the flow of uncertainty across a complex system; typically, this includes at least two model-components developed from earth science: seismic source models, and ground motion prediction models. Although there is no scientific prescription for the length of the forecasting time-window, the most common probabilistic seismic hazard analyses (PSHA hereafter) consider forecasting probabilities of ground shaking in time windows of 30 to 50 years. These types of models are the target of this review paper. Although the core methods and assumptions of such a modelling have largely remained unchanged since they were first developed more than 50 years ago, we will review the most recent initiatives which are facing the difficult task of meeting both the increasingly sophisticated demands of society and keeping pace with advances in our scientific understanding. A need for more accurate and precise hazard forecasting must be balanced with increased quantification of uncertainty and new challenges such as moving from time-independent hazard to forecasts that are time-dependent and specific to the time-period of interest. Meeting these challenges requires the development of science-driven models which integrate at best all information available, the adoption of proper mathematical frameworks to quantify the different types of uncertainties in the source and ground motion components of the hazard model, and the development of a proper testing phase of the hazard model to quantify the consistency and skill of the hazard model. We review the state-of-the-art of the national seismic hazard modeling, and how the most innovative approaches try to address future challenges.

In 2017 Queensland Fire and Emergency Services (QFES) completed the State Natural Hazard Risk Assessment which evaluated the risks presented by seven in-scope natural hazards. The risks presented by earthquakes were evaluated as part of this assessment in broad terms. The assessment highlighted a number of key vulnerabilities and risks presented by earthquakes to the communities of Queensland requiring further analysis. As QFES matures the Queensland Emergency Risk Management Framework (QERMF) by working with Local and District Disaster Management Groups (LDMGs/DDMGs), opportunities have arisen whereby QFES, in collaboration with relevant Federal and State Government and industry partners, are in a position to provide State-level support to LDMGs and DDMGs, through the development of in-depth risk assessments. The State Natural Hazard Risk Assessment 2017 and the State Disaster Management Plan 2018 note that the QERMF, as the endorsed methodology for the assessment of disaster related risk, is intended to: • Provide consistent guidance in understanding disaster risk that acts as a conduit for publicly available risk information. This approach assists in establishing and implementing a framework for collaboration and sharing of information in disaster risk management, including risk informed disaster risk reduction strategies and plans. • Encourage holistic risk assessments that provide an understanding of the many different dimensions of disaster risk (hazards, exposures, vulnerabilities, capability and capacities). The assessments include diverse types of direct and indirect impacts of disaster, such as physical, social, economic, environmental and institutional. The assessment and its intended audience This risk assessment was developed using the QERMF to undertake a scenario-based analysis of Queensland’s earthquake risk. It is intended to complement and support LDMGs and DDMGs in the completion of their risk-based disaster management plans. The development of the State Earthquake Risk Assessment 2018 was supported by Geoscience Australia (GA) through the provision of expert advice, relevant spatial datasets and the development of the scenarios used through this assessment. Input has been sought from GA to help contextualise the findings of the National Seismic Hazard Assessment 2018 for Queensland. Consultation with the University of Queensland has been sought to provide the ‘Queensland Context’, capitalising on the 80-year history of earthquake research and study undertaken by the university. A robust scientific basis enhances the assessment and enables disaster management groups to inform their local level planning. Overall, the assessment and associated report seeks to complement and build upon existing Local and District earthquake risk assessments by providing updated and validated information relating to the changes in understanding Queensland’s earthquake potential.

Animation showing Australian Earthquakes since 1964

The Geological Survey of Western Australia, in collaboration with the Australian National University, Macquarie University, the Department of Fire and Emergency Services and Geoscience Australia has just installed the first seismometers of an array across the South West Seismic Zone of Western Australia. This region is one of the most seismically active areas of Australia having experienced over 2000 small (between ML 2 to 3) earthquakes since the year 2000. Many smaller events are also noted by the local people who often hear them coming. Yes – hear them coming – this area is known for its “noisy” earthquakes. Most of these earthquakes occur in swarms rather than main shock-aftershock sequences (Dent, 2015). This means that the region experiences a lot of small earthquakes, all much the same size and which occur in a similar area. These swarms can be active for years. The hazard associated with these seismic events is relatively small. However, in the past six decades this region has also hosted five of the nine surface rupturing earthquakes in Australia, most notably; Meckering (M 6.5) in 1968 from which there are photos of the bends in the railway lines (Fig 1a) and faulting of 2-3 m in height across the fields (Fig 1b) (Gordon and Lewis 1980; Johnston and White 2018, Clark and Edwards 2018); Calingiri (M5.9) in 1970 and Lake Muir (M5.6), which was felt by a lot of people across Western Australia just two years ago (Clark et al. 2020). Despite the high rates of seismicity, seismic monitoring in the region remains relatively sparse. To overcome this lack of instrumentation, the consortium of institutions mentioned above, came together for an ARC Linkage project to put in place a temporary network- the South West Australia Network (SWAN) - to improve the monitoring and detection capabilities in this area. This project will see a total of twenty-five broadband seismometers deployed across the Southwest of Western Australia for a period of approximately 2 years (Fig 2a and b). This temporary array will enable the detection and location of smaller-magnitude earthquakes which can be used to improve the crustal velocity models which in turn enables more accurate earthquake locations and helps the understanding of the crustal structure of this part of Australia. Better velocity models also enable better magnitude calculation methods, which improve the knowledge about recurrence of earthquakes of a certain magnitude. From a seismic hazard point of view, this data has the potential to assist in the development of improved methods for modelling how shaking intensity varies as it propagates through the earth’s crust from the earthquake source. Overall, this information will feed into an improved understanding of the earthquake hazard in the Southwest region of Western Australia. For local communities, it will provide an improved situational awareness following significant earthquakes. More broadly, the improved understanding of the seismicity of the Southwest of Western Australia will enhance emergency response capabilities, and inform building codes and mitigation initiatives, which are the best methods we have to minimise the earthquake risks to communities. Data will be released through AusPASS, the Australian Passive Seismic Server two years after the last data has been collected.

The 6th Generation Seismic Hazard Model of Canada (CanadaSHM6) provides the basis for seismic design values proposed by Natural Resources Canada for the 2020 edition of the National Building Code of Canada (NBCC 2020). This Open File includes OpenQuake compatible source model files that will generate seismic hazard values as currently being proposed. Once NBCC 2020 is finalized, this report will be superseded by a subsequent Open File, to document the final model used to generate seismic hazard values using CanadaSHM6 for NBCC 2020.

Seismic risk assessment involves the development of fragility functions to express the relationship between ground motion intensity and damage potential. In evaluating the risk associated with the building inventory in a region, it is essential to capture ‘actual’ characteristics of the buildings and group them so that ‘generic building types’ can be generated for further analysis of their damage potential. Variations in building characteristics across regions/countries largely influence the resulting fragility functions, such that building models are unsuitable to be adopted for risk assessment in any other region where a different set of building is present. In this paper, for a given building type (represented in terms of height and structural system), typical New Zealand and US building models are considered to illustrate the differences in structural model parameters and their effects on resulting fragility functions for a set of main-shocks and aftershocks. From this study, the general conclusion is that the methodology and assumptions used to derive basic capacity curve parameters have a considerable influence on fragility curves.

Australia has a low to moderate seismicity by world standards. However, the seismic risk is significant due to the legacy of older buildings constructed prior to the national implementation of an earthquake building standard in Australia. The 1989 Newcastle and the 2010 Kalgoorlie earthquakes are the most recent Australian earthquakes to cause significant damage to unreinforced masonry (URM) and light timber frame structures and have provided the best opportunities to examine the earthquake vulnerability of these building types. This paper describes the two above mentioned building types with a differentiation of older legacy buildings constructed prior to 1945 to the relatively newer ones constructed after 1945. Furthermore, the paper presents method to utilise the large damage and loss related data (14,000 insurance claims in Newcastle and 400 surveyed buildings in Kalgoorlie) collected from these events to develop empirical vulnerability functions. The method adopted here followed the GEM Empirical Vulnerability Assessment Guidelines which involves preparing of a loss database, selecting an appropriate intensity measure, selecting and applying a suitable statistical approach to develop vulnerability functions and the identification of optimum functions. The adopted method uses a rigorous statistical approach to quantify uncertainty in vulnerability functions and provides an optimum solution based on goodness-of-fit tests. The analysis shows that the URM structures built before 1945 are the most vulnerable to earthquake with post 1945 URM structures being the next most vulnerable. Timber structures appear to be the least vulnerable, with little difference observed in the vulnerability of timber buildings built before or after 1945. Moreover, the older structures (both URM and timber) depict exhibit more scatter in results reflecting greater variation in building vulnerability and performance during earthquakes. The analysis also highlights the importance of collecting high quality damage and loss data which is, not only a fundamental requirement for developing empirical vulnerability functions, and but is also useful in validating analytically derived vulnerability functions. The vulnerability functions developed herein are the first publically available functions for Australian URM and timber structures. They can be used for seismic risk assessment and to focus the rm a basis for development ofing retrofit strategies to reduce the existing earthquake risk.

Geoscience Australia provides 24/7 monitoring of seismic activity within Australia and the surrounding region through the National Earthquake Alerts Centre (NEAC). Recent enhancements to the earthquakes@GA web portal now allow users to view felt reports, submitted online – together with reports from other nearby respondents – using the new interactive mapping feature. Using an updated questionnaire based on the US Geological Survey’s Did You Feel It? System, Geoscience Australia now calculate Community Internet Intensities (CIIs) to support near-real-time situational awareness applications. Part of the duty seismologists’ situational awareness and decision support toolkit will be the production of real-time “ShakeMaps.” ShakeMap is a system that provides near-real-time maps of shaking intensity following significant earthquakes. The software ingests online intensity observations and spatially distributed instrumental ground-motions in near-real-time. These data are then interpolated with theoretical predictions to provide a grid of ground shaking for different intensity measure types. Combining these predictions with CIIs provides a powerful tool for rapidly evaluating the likely impact of an earthquake. This paper describes the application of the new felt reporting system and explores its utility for near-real-time ShakeMaps and the provision of situational awareness for significant Australian earthquakes.

This short video introduces liquefaction and its impact on buildings and other structures. Liquefaction is demonstrated using sand in a glass container and explains why it happens. The video contains images and short clips of liquefaction and introduces some ways engineers lessen the impact of earthquakes on buildings. The second half of the video includes instructions on how to make your own liquefaction demonstration and extend it into an inquiry activity.

Modern geodetic and seismic monitoring tools are enabling study of moderate-sized earthquake sequences in unprecedented detail. Here we use a variety of methods to examine surface deformation caused by a sequence of earthquakes near Lake Muir in Southwest Western Australia in late 2018. A shallow MW 5.3 earthquake near Lake Muir on the 16th of September 2018 was followed on the 8th of November by a MW 5.2 event in the same region. Focal mechanisms produced for the events suggest reverse and strike slip rupture, respectively. Recent improvements in the coverage and observation frequency of the Sentinel-1 Synthetic Aperture Radar (SAR) satellite in Australia allowed for the timely mapping of the surface deformation field relating to both earthquakes in unprecedented detail. Interferometric Synthetic Aperture Radar (InSAR) analysis of the events suggest that the ruptures are in part spatially coincident. Field mapping, guided by the InSAR results, revealed that the first event produced an approximately 3 km long and up to 0.5 m high west-facing surface rupture, consistent with slip on a moderately east-dipping fault. Double difference hypocentre relocation of aftershocks using data from rapidly deployed seismic instrumentation confirms an easterly dipping rupture plane for the first event. The aftershocks are predominantly located at the northern end of the rupture where the InSAR suggests vertical displacement was greatest. The November event resulted from rupture on a NE-trending strike slip fault. Anecdotal evidence from local residents suggests that the southern part of the September rupture was ‘freshened’ during the November event, consistent with InSAR results, which indicate that a NW-SE trending structural element accommodated deformation during both events. Comparison of the InSAR-derived deformation field with surface mapping and UAV-derived digital terrain models (corrected to pre-event LiDAR) revealed a surface deformation envelope consistent with the InSAR for the first event, but could not discern deformation unique to the second event.