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  • 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.

  • 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 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.

  • 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.

  • 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.

  • Natural Hazards and Earth Systems Science

  • 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.

  • Probabilistic earthquake hazard maps were prepared for the Fiji Islands. Damage has been caused by Fiji earthquakes around 1850, in 1884, 1902, 1919, 1932 (twice), 1953 and 1979. No previous assessment had produced a comprehensive description of the earthquake hazard in Fiji and the present study was initiated in 1990 when the author was attached to the Mineral Resources Department, Fiji. Collection and analysis of data continued at MRD until 1992 and the study was completed at the Australian Geological Survey Organisation in 1993-1997. The aim of the study was to produce probabilistic earthquake hazard maps which can be used in the National Building Code for Fiji, for design of special structures, for planning, for emergency management and for risk management. Few, if any, similar studies have been undertaken in the seismically active Southwest Pacific.

  • Historical reports of earthquake effects from the period 1681 to 1877 in Java, Bali and Nusa Tenggara are used to independently test ground motion predictions in Indonesia’s 2010 national probabilistic seismic hazard assessment (PSHA). Assuming that strong ground motion occurrence follows a Poisson distribution, we cannot reject Indonesia’s current PSHA for key cities in Java at 95% confidence. However, the results do suggest that seismic hazard may be underestimated for the megacity Jakarta. Ground motion simulations for individual large damaging events are used to identify plausible source mechanisms, providing insights into the major sources of earthquake hazard in the region and possible maximum magnitudes for these sources. The results demonstrate that large intraslab earthquakes have been responsible for major earthquake disasters in Java, including a ~Mw 7.5 intraslab earthquake near Jakarta in 1699 and a ~Mw 7.8 event in 1867 in Central Java. The results also highlight the potential for large earthquakes to occur on the Flores Thrust. We require an earthquake with Mw 8.4 on the Flores Thrust to reproduce tsunami observation from Sulawesi and Sumbawa in 1820. Furthermore, large shallow earthquakes (Mw > 6) have occurred in regions where active faults have not been mapped identifying the need for further research to identify and characterize these faults for future seismic hazard assessments. <b>Citation:</b> Jonathan Griffin, Ngoc Nguyen, Phil Cummins, Athanasius Cipta; Historical Earthquakes of the Eastern Sunda Arc: Source Mechanisms and Intensity‐Based Testing of Indonesia’s National Seismic Hazard Assessment. <i>Bulletin of the Seismological Society of America </i>2018; 109 (1): 43–65. doi: https://doi.org/10.1785/0120180085

  • The present study reports on recent developments of the Indonesia Tsunami Early Warning System (InaTEWS), especially with respect to the tsunami modeling components used in that system. It is a dual system: firstly, InaTEWS operates a high-resolution scenario database pre-computed with the finite element model TsunAWI; running in parallel, the system also contains a supra real-time modeling component based on the GPU-parallelized linear long-wave model easyWave capable of dealing with events outside the database coverage. The evolution of the tsunami scenario database over time is covered in the first sections. Starting from the mere coverage of the Sunda Arc region, the current state contains scenarios in 15 fault zones. The study is augmented by an investigation of warning products used for early warning like the estimated wave height (EWH) and the estimated time of arrival (ETA). These quantities are determined by easyWave and TsunAWI with model specific approaches. Since the numerical setup of the models is very different, the extent of variations in warning products is investigated for a number of scenarios, where both pure database scenarios and applications to real events are considered.