On the 30th September 2009 a magnitude 7.6 earthquake struck West Sumatra in the Padang and Pariaman regions. It caused widespread damage to buildings and resulted and an estimated 1,117 fatalities. Thankfully the event was not accompanied by a tsunami that could have had additional devastating impacts and a greatly increased mortality. Under its mandate the AIFDR responded to the earthquake event with the objective of deriving an understanding of the factors that had contributed to outcome. It supported a team of Indonesian and international engineers and scientists who collected and analysed damage information that could subsequently be used for future disaster risk reduction in West Sumatra and Indonesia more broadly. The activity was jointly led by the Centre for Disaster Mitigation at the Institut Teknologi Bandung (ITB) and Geoscience Australia. This report provides a background to the region, describes the nature of the earthquake and its impacts, details the survey activity and outlines the significant outcomes that has come from it. Importantly, it makes several recommendations to assist in the regional reconstruction after the event and to guide future development in the Padang region and Indonesia more generally.

With a population of over 250 million people, Indonesia is the fourth most populous country in the world (United Nations, 2013). Indonesia also experiences more earthquakes than any other country in the world (USGS, 2015). Its borders encompass one of the most active tectonic regions on Earth including over 18 000 km of major tectonic plate boundary, more than twice that of Japan or Papua New Guinea (Bird, 2003). The potential for this tectonic activity to impact large populations has been tragically demonstrated by the 20004 Sumatra earthquake and tsunami. In order to inform earthquake risk reduction in Indonesia, a new national earthquake hazard map was developed in 2010 (Irsyam et al., 2010). In this report historical records of damaging earthquakes from the 17th to 19th centuries are used to test our current understanding of earthquake hazard in Indonesia and identify areas where further research is needed. In this report we address the following questions: - How well does our current understanding of earthquake hazard in Indonesia reflect historical activity? - Can we associate major historical earthquakes with known active faults, and are these accounted for in current assessments of earthquake hazard? - Does the current earthquake hazard map predict a frequency and intensity of shaking commensurate with the historical record? - What would the impact of these historical earthquakes be if they were to reoccur today? To help answer questions like these, this report collates historical observations of eight large earthquakes from Java, Bali and Nusa Tenggara between 1699 and 1867. These observations are then used to: - Identify plausible sources for each event; - Develop ground shaking models using the OpenQuake Engine (GEM Foundation, 2015); - Assess the validity of the current national seismic hazard map; and - Estimate fatalities were the historical events to occur today using the InaSAFE (InaSAFE.org, 2015) software.

The Greater Metro Manila Area is one of the world's megacities and is home to about 12 million people. It is located in a region at risk from earthquakes, volcanic eruptions, tropical cyclones, riverine flooding, landslides and other natural hazards. Major flooding affected the Greater Metro Manila Area in September 2009 following the passage of Typhoon Ketsana (known locally as Typhoon Ondoy). Following this event, the Australian Aid Program supported Geoscience Australia to undertake a capacity building project with its partner agencies in the Government of the Philippines. The output of this project has been a series of risk information products developed by agencies in the Collective Strengthening of Community Awareness for Natural Disasters (CSCAND) group. These products quantify the expected physical damage and economic loss to buildings caused by earthquakes, tropical cyclone severe wind and riverine flooding across the Greater Metro Manila Area. Spatial data is a key input to the development of hazard models and information on exposure, or the 'elements at risk'. The development of a spatially enabled exposure database was a crucial element in the construction of risk information products for the Greater Metro Manila Area. The database provides one central repository to host consistent information about the location, size, type, age, residential population and structural characteristics of buildings within the area of interest. Unique spatial analysis techniques were employed to quantify and record important aspects of the built environment, for inclusion in the database. The process of exposure data development within the Greater Metro Manila Area, including a new application developed by Geoscience Australia for estimating the geometric characteristics of buildings from high resolution elevation data and multi-spectral imagery, will be presented.

On 6th July 2006, an intense swarm of earthquake activity began in the Sulu Range, Central New Britain, Papua New Guinea. The earthquakes were felt almost every one to two minutes, 24 hours a day, with modified Mercalli intensities of MM1 to MM4. They were accompanied by unusual vigorous activity in the hot springs southwest of the Sulu Range. Fearing a possible eruption and tsunami, about 1000 locals were evacuated.

Probabilistic seismic hazard map of Papua New Guinea, in terms of Peak Ground Acceleration, is developed for return period of 475 years. The calculations were performed for bedrock site conditions (Vs30=760 m/s). Logic-tree framework is applied to include epistemic uncertainty in seismic source as well as ground-motion modelling processes. In this regard two source models, using area source zones and smoothed seismicity, are developed. Based on available geological and seismological data, defined seismic sources are classified into 4 different tectonic environments. For each of the tectonic regimes three Ground Motion Prediction Equations are selected and used to estimate the ground motions at a grid of sites with spacing of 0.1 degree in latitude and longitude. Results show high level of hazard in the coastal areas of Huon Peninsula and New Britain/ Bougainville regions and relatively low level of hazard in the southern part of the New Guinea highlands block. In Huon Peninsula, as shown by seismic hazard disaggregation results, high level of hazard is caused by modelled frequent moderate to large earthquakes occurring at Ramu-Markham Fault zone. On the other hand in New Britain/Bougainville region, the geometry and distance to the subduction zone along New Britain Trench mainly controls the calculated level of hazard. It is also shown that estimated level of PGAs is very sensitive to the selection of GMPEs and overall the results are closer to the results from studies using more recent ground-motion models.

Many earthquakes in Indonesia have caused a large number of fatalities. Disaster risk-reduction of fatalities requires a representative fatality model derived from fatality data caused by historical earthquakes in Indonesia. We develop an empirical fatality model for Indonesia by relating macroseismic intensity to fatality rate using compiled subdistrict level fatality rate data and numerically simulated ground shaking intensity for four recent damaging events. The fatality rate data are compiled by collecting population and fatality statistics of the regions impacted by the selected events. The ground shaking intensity is numerically estimated by incorporating a finite fault model of each event and local site conditions approximated by topographically-based site amplifications. The macroseismic intensity distribution of each event is generated by using ShakeMap software with a selected pair of ground motion predictive equation (GMPE) and ground motion to intensity conversion equation (GMICE). The developed fatality model is a Bayesian generalized linear model where the fatality rate is assumed to follow a mixture of a Bernoulli and a gamma distribution. The probability of zero fatality rate and the mean non-zero fatality rate is linked to a linear function of shaking intensity by the logit and the log link functions, respectively. We estimate posterior distribution of the parameters of the model based on the Hamilton Monte Carlo algorithm. For validation of the developed model we calculate fatalities of the past events from the EXPO-CAT catalog and compare the estimates with the EXPO-CAT fatality records. While the developed fatality model can provide an estimate of the range of fatalities for future events it needs on-going refinement by incorporation of additional fatality rate data from past and future events.

Through Australian Department of Foreign Affairs and Trade, Geoscience Australia has been working closely with the Government of Papua New Guinea technical agencies (Rabaul Volcano Observatory, Port Moresby Geophysical Observatory, and Engineering Geology Branch) since September 2010 to enhance their capabilities to monitor and assess natural hazards. The objective of this program is to support the Government of Papua New Guinea in developing fundamental information and practices for the effective response and management of natural hazard events in PNG. Earthquakes as natural hazards are one of the key focus points of this project, as they continue to cause loss of life and widespread damage to buildings and infrastructure in Papua New Guinea. The country’s vulnerability to earthquakes is evident from the significant socio-economic consequences of recent major events in Papua New Guinea, e.g., a magnitude 7.5 earthquake that occurred in the Hela Province of Papua New Guinea in 2018. Earthquake risk is likely to increase significantly in the years to come due to the growth in population and urbanization in Papua New Guinea. However, earthquake risk, unlike hazard, can be managed and minimized. One obvious example would be minimizing earthquake risk by constructing earthquake-resistant structures following building standards. The high level of earthquake hazard of Papua New Guinea has been long recognised and the suite of building standards released in 1982 contained provisions to impart adequate resilience to buildings based on the best understanding of seismic hazard available at that time. However, the building standards and incorporated seismic hazard assessment for Papua New Guinea has not been updated since the 1980s. The integration of modern national seismic hazard models into national building codes and practices provides the most effective way that we can reduce human casualties and economic losses from future earthquakes. This report aims at partially fulfilling this task by performing a probabilistic seismic hazard assessment to underpin a revision of the earthquake loading component of the building standards of Papua New Guinea. The updated assessment offers many important advances over its predecessor. It is based on a modern probabilistic hazard framework and considers an earthquake catalogue augmented with an additional four decades-worth of data. The revised assessment considers advances in ground-motion modelling through the use of multiple ground-motion models. Also, for the first time, the individual fault sources representing active major and microplate boundaries are implemented in the input hazard model. Furthermore, the intraslab sources are represented realistically by using the continuous slab volume to constrain the finite ruptures of such events. This would better constrain the expected levels of ground motion at any given site in Papua New Guinea. The results suggest a high level of hazard in the coastal areas of the Huon Peninsula and the New Britain–Bougainville region, and a relatively low level of hazard in the southern part of the New Guinea Highlands Block. In comparison with the seismic zonation map in the current design standard, it can be noted that the spatial distribution used for building design does not match the bedrock hazard distribution of this study. In particular, the high seismic hazard of the Huon Peninsula in the revised assessment is not captured in the current seismic zoning map, leading to a significant under-estimation of hazard in PNG’s second-largest city, Lae. It can also be shown that in many other regions and community localities in PNG the hazard is higher than that regulated for the design of buildings having a range of natural periods. Thus, the need for an updated hazard map for building design has been confirmed from the results of this study, and a revised map is developed for consideration in a revised building standard of Papua New Guinea.

Tsunami hazard modelling for Tonga shows the potential impacts of tsunami generated by a very large earthquake on the nearby Tongan Trench.

Natural Hazards and Earth Systems Science

The Papua New Guinea (PNG) region has been formed within an oblique convergence zone between the north-northeasterly moving Australian plate and the Pacific plate. The region is subject to most types of tectonic activity, including active folding, faulting and volcanic eruptions and hence is arguably one of the most seismically active regions in the world. Given its high level of seismic activity, PNG would benefit from a dense monitoring network to enhance the efficiency of the earthquake emergency response operations. A program to densify the earthquake monitoring network of PNG by utilizing low-cost sensors has been developed by Geoscience Australia in collaboration with the Department of Mineral Policy and Geohazards Management in PNG. To verify the performance, trial low-cost sensors were co-located with observatory-quality instrumentation for a period of one month in Port Moresby and Rabaul observatories. The comparisons demonstrated comparable recording results across a wide seismic frequency range. Once this proved successful, the first deployments were undertaken recently, with sensors installed in the Bialla International School, Kimbe International School and the Earth Science Division of the University of PNG. Educational institutions are ideal for the installation of these sensors as they can provide guaranteed internet and electricity, allowing for continuous monitoring of earthquakes. The data acquired by these stations will feed into the existing networks for national earthquake and volcano monitoring, thus expanding the national seismic network of PNG. This work is being undertaken as part of the Australian Aid program. Presented at the 2020 Seismological Society of America (SSA) Annual Meeting