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 using the OpenQuake software developed by the Global Earthquake Model Foundation (Pagani et al. 2014). 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 more 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 southwestern part of mainland PNG. In comparison with the seismic zonation map in the current design standard, it can be noted that the spatial distribution of seismic hazard 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. <b>Citation:</b> Ghasemi, H., Cummins, P., Weatherill, G. <i>et al.</i> Seismotectonic model and probabilistic seismic hazard assessment for Papua New Guinea. <i>Bull Earthquake Eng, </i><b>18</b>, 6571–6605 (2020). https://doi.org/10.1007/s10518-020-00966-1

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.

Heterogeneous distribution of slip during megathrust earthquakes has been shown to significantly affect the spatial distribution of tsunami height in both numerical studies and field observations. This means that tsunami hazard maps generated using uniform slip distributions in their tsunami source models may underestimate tsunami inundation in some locations compared with real events of the same magnitude in the same location. In order to more completely define areas that may be inundated during a tsunami it is important to consider how different possible distributions of slip will impact different parts of the coastline. We generate tsunami inundation maps for the Mentawai Islands, West Sumatra, Indonesia, from a composite suite of possible source models that are consistent with current knowledge of the source region. First, a suite of earthquake source models with randomly distributed slip along the Mentawai Segment of the Sunda Subduction Zone is generated using a k-2 rupture model. From this suite we select source models that generate vertical deformation consistent with that observed in coral palaeogeodetic records of previous ruptures of the Mentawai Segment in 1797 and 1833, minus deformation observed in the 2007 Bengkulu earthquake sequence. Tsunami inundation is then modelled using high resolution elevation data for selected source models and the results compiled to generate a maximum tsunami inundation zone. This method allows us to constrain the slip distribution beneath the Mentawai Islands, where coral palaeogeodetic data is available, while allowing for greater variation in the slip distribution away from the islands, in particular near the trench where large slip events can generate very large tsunami. This method also allows us to consider high slip events on deeper portions of the megathrust between the Mentawai Islands and the Sumatran Mainland, which give greater tsunami inundation on the eastern part of the Mentawai Islands and the west coast of Sumatra compared with near-trench event. By accounting for uncertainty in slip distribution, the resulting hazard maps give a more complete picture of the areas that may be inundated compared with hazard maps derived from a single 'worst case' source model. These maps allow for more robust tsunami evacuation plans to be developed to support immediate community evacuation in response to strong or long-lasting earthquake ground shaking. From the American Geophysical Union Fall Meeting Abstracts

The Government of Indonesia has committed to deploying a network of 500 strong-motion sensors throughout the nation. The data from these sensors have the potential to provide critical near-real-time information on the level of ground shaking and potential impact from Indonesian earthquakes near communities. We describe the implementation of real-time ‘ShakeMaps’ within Indonesia's Agency of Meteorology, Climatology and Geophysics (BMKG). These ShakeMaps are intended to underpin real-time earthquake situational awareness tools. The use of the new strong-motion network is demonstrated for two recent earthquakes in northern Sumatra: the 2 July 2013 Mw 6.1 Bener Meriah, Sumatra and the 10 October 2013 Mw 5.4 Aceh Besar earthquakes. The former earthquake resulted in 35 fatalities, with a further 2400 reported injuries. The recently integrated ShakeMap system automatically generated shaking estimates calibrated by BMKG's strong-motion network within 7 min of the Bener Meriah earthquake's origin, which assisted the emergency response efforts. Recorded ground motions are generally consistent with theoretical models. However, more analysis is required to fully characterize the attenuation of strong ground motion in Indonesia.

In June 2012 Geoscience Australia was commissioned by Commonwealth Scientific and Industrial Research Organisation (CSIRO) to undertake detailed wind hazard assessments for 14 Pacific Island countries and East Timor as part of the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program. PACCSAP program follows on from work Geoscience Australia did for the Pacific Climate Change Science Program (PCCSP) looking at CMIP3 generation of climate models. The objective of this study is to improve scientific knowledge by examining past climate trends and variability to provide regional and national climate projections. This document presents results from current and future climate projections of severe wind hazard from tropical cyclones for the 15 PACCSAP partner countries describing the data and methods used for the analysis. The severe wind hazard was estimated for current (1981 to 2000) and future (2081 to 2100) climate scenarios. Tropical-cyclone like vortices from climate simulations conducted by CSIRO using six Coupled Model Intercomparison Project phase 5 (CMIP5) models (BCC-CSM1.1, NorESM1-M, CSIRO-Mk3.6, IPSL-CM5A, MRI-CGM3 and GFDL-ESM2M) as well as the International Best Track Archive for Climate Stewardship were used as input to the Geoscience Australia's Tropical Cyclone Risk Model to generate return period wind speeds for the 15 PACCSAP partner countries. The Tropical Cyclone Risk Model is a statistical-parametric model of tropical cyclone behaviour, enabling users to generate synthetic records of tropical cyclones representing many thousands of years of activity. The 500-year return period wind speed is analysed and discussed into more details in this report, since it is used as a benchmark for the design loads on residential buildings. Results indicate that there is not a consistent spatial trend for the changes in 500-year cyclonic wind speed return period when CMIP5 models are compared individually. BCC-CSM1M and IPSL-CM5A presented an increase in the annual TC frequency for East Timor, northern hemisphere and southern hemisphere. On the other hand, NorESM1M showed a decrease in the annual TC frequency for the same areas. The other three models showed a mixed of increase and decrease in their annual TC frequency. When CMIP5 models were analysed by partner county capitals for the 500-year cyclonic wind speed return period, IPSL-CM5A and GFDL-ESM2M models presented an increase in the cyclonic wind speed intensity for almost all capitals analysed with exception of Funafuti (GFDL-ESM2M), which presented a decrease of 0.7% and Honiara (IPSL-CM5A) with a decrease of 1.6%. The tropical cyclone annual frequency ensemble mean indicates an increase in the tropical cyclone frequency within all three regions considered in this study. When looking at individual capitals, a slight increase in the 500-year return period cyclonic wind speed ensemble mean varying between 0.8% (Port Vila) to 9.1% (Majuro) is noticed. A decline around 2.4% on average in the 500-year return period cyclonic wind speed ensemble mean is observed in Dili, Suva, Nukualofa and Ngerulmud. The ensemble spatial relative change did not show any particular consistency for the 500-year cyclonic wind speed. Areas where Marshall Islands and Niue are located presented an increase in the 500-year cyclonic wind speed while a decrease is observed in areas around South of Vanuatu, East of Solomon Islands, South of Fiji and some areas in Tonga. The information from the evaluation of severe wind hazard from tropical cyclones, together with other PACCSAP program outputs, will be used to build partner country capacity to effectively adapt and plan for the future and overcome challenges from climate change.

Tsunami hazard maps are generated for the Mentawai Islands, West Sumatra, Indonesia, to support evacuation and disaster response planning. A random heterogeneous slip generator is used to forward model a suite of earthquake rupture scenarios on the Mentawai Segment of the Sunda Subduction Zone. A total of 1000 rupture models that fit constraints provided by coral and geodetic records of coseismic vertical deformation from great earthquakes in 1797, 1833 and 2007 are used to model inundation and define a maximum inundation zone that envelopes all of these scenarios. Results are compared with single scenario hazard assessments developed by experts and agreed through scientific consensus building processes to assess the additional value of modelling a suite of scenarios to obtain a more robust estimate of potential inundated areas by incorporating uncertainty in the earthquake source. The model presented here, like all tsunami hazard assessments, is based on assumptions about the characteristics of future events based on past events, however by sampling a range of plausible outcomes we gain a more robust estimate of which areas may be inundated during a tsunami within the bounds of our assumptions.

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

As part of the 2018 Tropical Cyclone Hazard Assessment (TCHA), we compiled the geospatial raster dataset that can be accessible to internal and external users via ArcGIS online and can be integrated for building additional geoprocessing applications. This web service gives more stable and easy access to data and interactive maps. With having separate geospatial layers for each recurrence interval- i.e. 5 through 10000 years, users can toggle between the layers and evaluate the changes in wind speed (km/hr) and potential areas at risk on the fly.

<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

<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