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 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.

With a population of over 250 million people, Indonesia is the fourth most populous country in the world (United Nations, 2013). Indonesia also experiences more earthquakes than any other country in the world (USGS, 2015). Its borders encompass one of the most active tectonic regions on Earth including over 18 000 km of major tectonic plate boundary, more than twice that of Japan or Papua New Guinea (Bird, 2003). The potential for this tectonic activity to impact large populations has been tragically demonstrated by the 20004 Sumatra earthquake and tsunami. In order to inform earthquake risk reduction in Indonesia, a new national earthquake hazard map was developed in 2010 (Irsyam et al., 2010). In this report historical records of damaging earthquakes from the 17th to 19th centuries are used to test our current understanding of earthquake hazard in Indonesia and identify areas where further research is needed. In this report we address the following questions: - How well does our current understanding of earthquake hazard in Indonesia reflect historical activity? - Can we associate major historical earthquakes with known active faults, and are these accounted for in current assessments of earthquake hazard? - Does the current earthquake hazard map predict a frequency and intensity of shaking commensurate with the historical record? - What would the impact of these historical earthquakes be if they were to reoccur today? To help answer questions like these, this report collates historical observations of eight large earthquakes from Java, Bali and Nusa Tenggara between 1699 and 1867. These observations are then used to: - Identify plausible sources for each event; - Develop ground shaking models using the OpenQuake Engine (GEM Foundation, 2015); - Assess the validity of the current national seismic hazard map; and - Estimate fatalities were the historical events to occur today using the InaSAFE (InaSAFE.org, 2015) software.

<div>Australia has been supporting 13 Pacific Island countries (PICs) to measure, record and analyse long-term sea level and land motion for over 25 years. This is known as the Pacific Sea Level and Geodetic Monitoring (PSLGM) project which is funded by Australian Aid under the Climate and Oceans Support Program in the Pacific (COSPPac). </div><div>The sea level data is collected continuously at one or two tide gauges in each of the 13 PICs. The land motion data is collected continuously at one or two Global Navigation Satellite System (GNSS) stations in each of the 13 PICs. The height difference between the tide gauges and GNSS stations is observed once every 18 months (approximately). The data is then analysed to produce sea level information-based products (e.g. tide calendars) and to inform about motion of the land (e.g. for coastal infrastructure planning). </div><div>The PSLGM project involves Australian science agencies (Bureau of Meteorology (Bureau) and Geoscience Australia (GA)) working in partnership with regional organisations (Pacific Community (SPC)), and Pacific government ministries (meteorology and land and survey departments).</div><div><br></div><div>This GA Record reports findings regarding the absolute vertical rate of movement (i.e. the rate at which the land is moving up or down with respect to the centre of the Earth) of 13 Pacific Island Countries tide gauges over the period 2003 – 2022 based on the analysis of Global Navigation Satellite System (GNSS) data and levelling data.&nbsp;&nbsp;</div><div><br></div>

<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>

<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><div><br></div><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><div>This report provides the results of the GNSS monument 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 Funafuti, Tuvalu in October of 2019. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.</div><div><br></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. 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 Nukualofa, Tonga from 7th to 19th July 2019. It also provides an updated height of the tide gauge derived from GNSS time series analysis and precise levelling observations.

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.

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.

The Greater Metro Manila Area is one of the world's megacities and is home to about 12 million people. It is located in a region at risk from earthquakes, volcanic eruptions, tropical cyclones, riverine flooding, landslides and other natural hazards. Major flooding affected the Greater Metro Manila Area in September 2009 following the passage of Typhoon Ketsana (known locally as Typhoon Ondoy). Following this event, the Australian Aid Program supported Geoscience Australia to undertake a capacity building project with its partner agencies in the Government of the Philippines. The output of this project has been a series of risk information products developed by agencies in the Collective Strengthening of Community Awareness for Natural Disasters (CSCAND) group. These products quantify the expected physical damage and economic loss to buildings caused by earthquakes, tropical cyclone severe wind and riverine flooding across the Greater Metro Manila Area. Spatial data is a key input to the development of hazard models and information on exposure, or the 'elements at risk'. The development of a spatially enabled exposure database was a crucial element in the construction of risk information products for the Greater Metro Manila Area. The database provides one central repository to host consistent information about the location, size, type, age, residential population and structural characteristics of buildings within the area of interest. Unique spatial analysis techniques were employed to quantify and record important aspects of the built environment, for inclusion in the database. The process of exposure data development within the Greater Metro Manila Area, including a new application developed by Geoscience Australia for estimating the geometric characteristics of buildings from high resolution elevation data and multi-spectral imagery, will be presented.