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.

<div>The Australian Bureau of Meteorology (BoM), Geoscience Australia (GA) and the Pacific Community (SPC) work together on the Australian Aid funded Pacific Sea Level and Geodetic Monitoring Project (PSLGMP). The project is focused on determining the long-term variation in sea level through observation and analysis of changes in the height of the land (using Global Navigation Satellite System (GNSS) data) and changes in the sea level (using tide gauges managed and operated by the BoM. It is the role of GA and SPC to provide information about ‘absolute’ movement of the tide gauge (managed by BoM) using GNSS to continuously monitor land motion and using levelling (SPC) to measure the height difference between the tide gauge and GNSS pillar every 18 months. </div><br><div>Land movement caused by earthquakes, subsidence and surface uplift have an important effect on sea level observations at tide gauges. For example, a tide gauge connected to a pier which is subsiding at a rate of 5 mm per year would be observed as a rate of 5 mm per year of sea level rise at the tide gauge. Because of this, it is important to measure, and account for, the movement of land when measuring ‘absolute’ sea level variation - the change in the sea level relative to the centre of the Earth. Relative sea level variation on the other hand is measured relative to local buildings and landmass around the coastline.</div><div>Geoscience Australia’s work enables more accurate 'absolute' sea level estimates by providing observations of land motion which can be accounted for by BoM when analysing the tide gauge data.</div><div><br></div>

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.

Hot emissions of mainly sulphur dioxide and carbon dioxide took place from a mound in Koranga open cut, near Wau, following a landslide at the end of May, 1967. Rocks of the Holocene volcano, Koranga, are exposed in the open cut. The emissions lasted about three months, and ceased on 13 August after another landslide removed the active mound. During the period of activity, recorded temperatures ranged up to 680°C; no anomalous seismic or tilt phenomena were recorded. The cause of the activity is not known, but it is thought that the high temperatures and gases may have been the result of the spontaneous combustion of reactive sulphides and carbonaceous material present in the altered rocks of Koranga volcano.

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 Australian Bureau of Meteorology (BoM), Geoscience Australia (GA) and the Pacific Community (SPC) work together on the Australian Aid funded Pacific Sea Level and Geodetic Monitoring Project (PSLGMP). The project is focused on determining the long-term variation in sea level through observation and analysis of changes in the height of the land (using Global Navigation Satellite System (GNSS) data) and changes in the sea level (using tide gauges managed and operated by the BoM. It is the role of GA and SPC to provide information about ‘absolute’ movement of the tide gauge (managed by BoM) using GNSS to continuously monitor land motion and using levelling (SPC) to measure the height difference between the tide gauge and GNSS pillar every 18 months. Land movement caused by earthquakes, subsidence and surface uplift have an important effect on sea level observations at tide gauges. For example, a tide gauge connected to a pier which is subsiding at a rate of 5 mm per year would be observed as a rate of 5 mm per year of sea level rise at the tide gauge. Because of this, it is important to measure, and account for, the movement of land when measuring ‘absolute’ sea level variation - the change in the sea level relative to the centre of the Earth. Relative sea level variation on the other hand is measured relative to local buildings and landmass around the coastline. Geoscience Australia’s work enables more accurate 'absolute' sea level estimates by providing observations of land motion which can be accounted for by BoM when analysing the tide gauge data. This report provides the results of the GNSS monitoring survey & high precision level survey completed between the Sea Level Fine Resolution Acoustic Measuring Equipment (SEAFRAME) tide gauge and the GNSS Continuously Operation Reference Station (CORS) in Pohnpei, FSM from 16th to 27th October 2018. It also provides an updated ellipsoidal height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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.