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.

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.

The Philippine archipalego is tectonically complex and seismically hazardous, yet few seismic hazard assessments have provided national coverage. This paper presents an updated probabilistic seismic hazard analysis for the nation. Active shallow crustal seismicity is modeled by faults and gridded point sources accounting for spatially variable occurrence rates. Subduction interfaces are modelled with faults of complex geometry. Intraslab seismicity is modeled by ruptures filling the slab volume. Source geometries and earthquake rates are derived from seismicity catalogs, geophysical datasets, and historic-to-paleoseismic constraints on fault slip rates. The ground motion characterization includes models designed for global use, with partial constraint by residual analysis. Shallow crustal faulting near metropolitan Manila, Davao, and Cebu dominates shaking hazard. In a few places, peak ground acceleration with 10% probability of exceedance in 50 years on rock reaches 1.0 g. The results of this study may assist in calculating the design base shear in the National Structural Code of the Philippines.

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

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.

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.

<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

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<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

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.