Probabilistic hazard assessments are a fundamental tool for assessing the threats posed by hazards to communities and are important for underpinning evidence-based decision-making regarding risk mitigation activities. Indonesia has been the focus of intense tsunami risk mitigation efforts following the 2004 Indian Ocean tsunami, but this has been largely concentrated on the Sunda Arc with little attention to other tsunami prone areas of the country such as eastern Indonesia. We present the first nationally consistent probabilistic tsunami hazard assessment (PTHA) for Indonesia. This assessment produces time-independent forecasts of tsunami hazards at the coast using data from tsunami generated by local, regional and distant earthquake sources. The methodology is based on the established monte carlo approach to probabilistic seismic hazard assessment (PSHA) and has been adapted to tsunami. We account for sources of epistemic and aleatory uncertainty in the analysis through the use of logic trees and sampling probability density functions. For short return periods (100 years) the highest tsunami hazard is the west coast of Sumatra, south coast of Java and the north coast of Papua. For longer return periods (500–2500 years), the tsunami hazard is highest along the Sunda Arc, reflecting the larger maximum magnitudes. The annual probability of experiencing a tsunami with a height of > 0.5 m at the coast is greater than 10% for Sumatra, Java, the Sunda islands (Bali, Lombok, Flores, Sumba) and north Papua. The annual probability of experiencing a tsunami with a height of > 3.0 m, which would cause significant inundation and fatalities, is 1–10% in Sumatra, Java, Bali, Lombok and north Papua, and 0.1–1% for north Sulawesi, Seram and Flores. The results of this national-scale hazard assessment provide evidence for disaster managers to prioritise regions for risk mitigation activities and/or more detailed hazard or risk assessment.

In order to characterize the subsurface structure of the Jakarta Basin, Indonesia, a dense portable seismic broad-band network was operated by The Australian National University (ANU) and the Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG) between October 2013 and February 2014. Overall 96 locations were sampled through successive deployments of 52 seismic broad-band sensors at different parts of the city. Oceanic and anthropogenic noises were recorded as well as regional and teleseismic earthquakes. We apply regularized deconvolution to the recorded ambient noise of the vertical components of available station pairs, and over 3000 Green's functions were retrieved in total. Waveforms from interstation deconvolutions show clear arrivals of Rayleigh fundamental and higher order modes. The traveltimes that were extracted from group velocity filtering of fundamental mode Rayleigh wave arrivals, are used in a 2-stage Transdimensional Bayesian method to map shear wave structure of subsurface. The images of S wave speed show very low velocities and a thick basin covering most of the city with depths up to 1.5 km. These low seismic velocities and the thick basin beneath the city potentially cause seismic amplification during a subduction megathrust or other large earthquake close to the city of Jakarta.

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 and 2017 national probabilistic seismic hazard assessments (PSHAs). Assuming that strong ground motion occurrence follows a Poisson distribution, we cannot reject Indonesia’s current and previous PSHA for key cities in Java at 95% confidence, although the results suggest an incremental improvement in the updated PSHA. The source mechanisms of important historical earthquakes are estimated by undertaking a grid search of source parameters and using ground‐motion models (GMMs) and ground motion to intensity conversion equations (GMICEs) to forward model intensity at each intensity data point. Bayesian inference is applied to calculate the distribution of source parameters given the historical intensity data. The results demonstrate that large intraslab earthquakes have been responsible for major earthquake disasters in Java, including an $Mw∼7.4$ intraslab earthquake near Jakarta in 1699 and an $Mw∼7.8$ event in 1867 in Central Java. The results also highlight the potential for large earthquakes to occur on the Flores thrust, with a cluster of large earthquakes rupturing the Flores thrust in 1815, 1818, and 1820. The results show that large shallow crustal earthquakes (⁠$Mw>6$⁠) occurred in regions of Java where active faults have not been mapped, highlighting the need for further research to identify these faults for future seismic hazard assessments. We do not find conclusive evidence for the occurrence of large earthquakes on the Java megathrust during the time period of this study; however, because of difficulties using intensity data to discriminate between subduction intraslab and interface sources, we cannot exclude megathrust source models for the 1699 and 1867 events, and note other possible megathrust events in 1757, 1780, and 1851.

A probabilistic seismic hazard assessment that includes the effect of site amplification is undertaken for the island of Sulawesi, Indonesia. High seismic activity rates, both along fast-slipping crustal faults including the major Palu-Koro–Matano Fault System and in regions of distributed deformation, contribute to moderate–high earthquake hazard over all but the SW part of the island. Of particular concern in terms of seismic risk are the numerous cities sited on soft sedimentary basins that have formed due to movement along presently active structures and that can be expected to amplify earthquake ground motions, including the provincial capitals of Palu and Gorontalo.