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.

The Philippine Institute of Volcanology and Seismology (PHIVOLCS) and Geoscience Australia (GA) have developed a long-term partnership in order to better understand and reduce the risks associated with earthquake hazards in the Philippines. The Project discussed herein was supported by the Australian Agency for International Development (AusAID). Specifically, this partnership was designed to enhance the exposure and damage estimation capabilities of the Rapid Earthquake Damage Assessment System (REDAS), which has been designed and built by PHIVOLCS. Prior to the commencement of this Project, REDAS had the capability to model a range of potential earthquake hazards including ground shaking, tsunami inundation, liquefaction and landslides, as well as providing information about elements at risk (e.g., schools, bridges, etc.) from the aforementioned hazards. The current Project enhances the exposure and vulnerability modules in REDAS and enable it to estimate building damage and fatalities resulting from scenario earthquakes, and to provide critical information to first-responders on the likely impacts of an earthquake in near real-time. To investigate this emergent capability within PHIVOLCS, we have chosen the pilot community of Iloilo City, Western Visayas. A large component of this project has been the compilation of datasets to develop building exposure models, and subsequently, developing methodologies to make these datasets useful for natural hazard impact assessments. Collection of the exposure data was undertaken at two levels: national and local. The national exposure dataset was gathered from the Philippines National Statistics Office (NSO) and comprises basic information on wall type, roof type, and floor area for residential buildings. The NSO census dataset also comprises crucial information on the population distribution throughout the Philippines. The local exposure dataset gathered from the Iloilo City Assessors Office includes slightly more detailed information on the building type for all buildings (residential, commercial, government, etc.) and appears to provide more accurate information on the floor area. However, the local Iloilo City dataset does not provide any information on the number of people that occupy these buildings. Consequently, in order for the local data to be useful for our purposes, we must merge the population data from the NSO with the local Assessors Office data. Subsequent validation if the Iloilo City exposure database has been conducted through targeted foot-based building inventory surveys and has allowed us to generate statistical models to approximate the distribution of engineering structural systems aggregated at a barangay level using simple wall and roof-type information from the NSO census data. We present a comparison of the national and local exposure data and discuss how information assembled from the Iloilo City pilot study - and future study areas where detailed exposure assessments are conducted - could be extended to describe the distribution of building stock in other regions of the Philippines using only the first-order national-scale NSO data. We present exposure information gathered for Iloilo City at barangay level in a format that can be readily imported to REDAS for estimating earthquake impact.

<div>On January 15, 2022, an ongoing eruption at the Hunga volcano generated a large explosion which resulted in a globally observed tsunami and atmospheric pressure wave. This paper presents time series observations of the event from Australia including 503 mean sea level pressure (MSLP) sensors and 111 tide gauges. Data is provided in its original format, which varies between data providers, and a post-processed format with consistent file structure and time-zone. High-pass filtered variants of the data are also provided to facilitate study of the pressure wave and tsunami. For a minority of tide gauges the raw sea level data cannot be provided, due to licence restrictions, but high-pass filtered data is always provided. The data provides an important historical record of the Hunga volcano pressure wave and tsunami in Australia. It will be useful for research in atmospheric and ocean waves associated with large volcanic eruptions. <b>Citation:</b> Davies, G., Wilson, K., Hague, B. et al. Australian atmospheric pressure and sea level data during the 2022 Hunga-Tonga Hunga-Ha’apai volcano tsunami. <i>Sci Data</i> <b>11</b>, 114 (2024). https://doi.org/10.1038/s41597-024-02949-2

<div>The city of Lae is Papua New Guinea (PNG)’s second largest, and is the home of PNG’s largest port. Here, a convergence rate of ~50 mm/yr between the South Bismarck Plate and the Australian Plate is accommodated across the Ramu-Markham Fault Zone (RMFZ). The active structures of the RMFZ are relatively closely spaced to the west of Lae. However, the fault zone bifurcates immediately west of the Lae urban area, with one strand continuing to the east, and a second strand trending southeast through Lae City and connecting to the Markham Trench within the Huon Gulf. </div><div>The geomorphology of the Lae region relates to the interaction between riverine (and limited marine) deposition and erosion, and range-building over low-angle thrust faults of the RMFZ. Flights of river terraces imply repeated tectonic uplift events; dating of these terraces will constrain the timing of past earthquakes and associated recurrence intervals. Terrace riser heights are typically on the order of 3 m, indicating causative earthquake events of greater than magnitude 7. </div><div>Future work will expose the most recently active fault traces in trenches to assess single event displacements, and extend the study to the RMFZ north of Nadzab Airport. These results will inform a seismic hazard and risk assessment for Lae city and surrounding region.</div> Presented at the 2023 Australian Earthquake Engineering Society (AEES) Conference

A component of the PNG-Australia Volcanological Services Support (VSS) Project funded by AusAID

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

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

Papua New Guinea (PNG) lies in a belt of intense tectonic activity that experiences high levels of seismicity. Although this seismicity poses significant risks to society, the Building Code of PNG and its underpinning seismic loading requirements have not been revised since 1982. This study aims to partially address this gap by updating the seismic zoning map on which the earthquake loading component of the building code is based. We performed a new probabilistic seismic hazard assessment for PNG. Among other enhancements, for the first time together with background sources, individual fault sources are implemented to represent active major and microplate boundaries in the region to better constrain the earthquake-rate and seismic-source models. The seismic-source model also models intraslab, Wadati-Benioff zone seismicity in a realistic way using a continuous slab volume to constrain the finite ruptures of such events. 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 building code of PNG. We will also discuss how the seismic hazard map of PNG is being used to underpin its building code, including what steps have been taken by GA together with the Government of PNG to promote uptake of the new hazard map by PNG’s earthquake engineering community.

Indonesia is located in one of the most seismically active regions in the world and often experiences damaging earthquakes. In the past the housing sector has sustained more damage and losses than other sectors due to earthquakes. This is often attributed to the fact that the most common houses in Indonesia are non-engineered, built with poor quality workmanship, poor quality materials and without resilient seismic design features. However little effort has been made to quantify how fragile these houses are, or how the fragility of these houses may vary according to location or wealth. It is not possible to derive empirical fragility functions for Indonesia due to insufficient damage data. The aim of this study is to determine whether existing earthquake fragility functions can be used for common houses in Indonesia. Scenario damage analyses were undertaken several times using different sets of fragility functions for the 2006 Yogyakarta and 2009 Padang events. The simulated damage results were then compared to the damage observed post event to determine whether an accurate damage prediction could be achieved. It was found that the common houses in Yogyakarta and Central Java vary according to age, location and wealth and can be reasonably well represented by existing fragility functions. However, the houses in Padang and surrounding West Sumatra did not vary in a predictable manner and are more fragile than anticipated. Therefore, the fragility of the most common houses in Indonesia is not uniform across the country. This has important implications for seismic damage and risk assessment undertaken in Indonesia. <b>Citation:</b> Weber, R., Cummins, P. & Edwards, M. Fragility of Indonesian houses: scenario damage analysis of the 2006 Yogyakarta and 2009 Padang earthquakes. <i>Bull Earthquake Eng</i> (2024). https://doi.org/10.1007/s10518-024-01930-z

The Assessment of Tropical Cyclone Risks in the Pacific Region project represents a collaboration between DIICCSRTE and Geoscience Australia with PCRAFI and AIR Worldwide. Building on the expertise of each organisation, the project will deliver an assessment of the financial risks to buildings, infrastructure and agriculture arising from tropical cyclones (TCs) under current and future climate regimes. This extends previous risk assessments undertaken by incorporating the influence of climate change on the hazard (TCs) into the assessment process. The output of this study is a set of peril matrices, which detail the relative change in parameters describing TC behaviour: e.g. annual mean frequency, mean maximum intensity and mean latitude of genesis. The relative changes are evaluated as the fractional change between TC behavior in current climate GCM simulations and future climate GCM simulations.