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.

A compilation of short animations, describing the key processes involved in tsunami generation.

Coastal communities in Australia are particularly exposed to disasters resulting from the coincidence of severe wind damage, storm surge, coastal flooding and shoreline erosion during cyclones and extra-tropical storms. Because the climatic drivers of these events are stronger during or across specific years (e.g. during La Nina periods), they can repeatedly impact the coast over periods of weeks, months or up to a few years. The consequences of individual events are therefore exacerbated with little or no opportunity for recovery of natural systems or communities. This poster summarises the objectives, approach and methodology for this storm surge project. A contribution to the Bushfire and Natural Hazards CRC.

The 2018 Probabilistic Tsunami Hazard Assessmetn (PTHA18) outputs are can be accessed following the README instructions here: https://github.com/GeoscienceAustralia/ptha/tree/master/ptha_access

This Geoscience Australia Record contains technical data and input files that, when used with the Global Earthquake Model’s (GEM’s) OpenQuake-engine probabilistic seismic hazard analysis software (Pagani et al., 2014), will enable end users to explore and reproduce the 2018 National Seismic Hazard Assessment (NSHA18) of Australia (Allen et al., 2018a). This report describes the NSHA18 input data only and does not discuss the scientific rationale behind the model development. These details are provided in Allen et al. (2018a) and references therein.

A community Safety Capbility Flyer was produced to showcase the work undertaken in the Community Safety Value Stream. The flyer includes an introduction to the Community Safety Value Stream, case studies of the work Geoscience Australia does in this space and information on how to engage with Geoscience Australia via the products, tools, models and applications that are produced. This flyer is intended for use a conferences and where promotional material would beneficial to showcase the work undertaken at Geoscience Australia such as the Floodplain Management Association Conference on 19-22 May 2015.

Geoscience Australia is currently drafting a new National Earthquake Hazard Map of Australia using modern methods and models. Among other applications, the map is a key component of Australia's earthquake loading code AS1170.4. In this paper we provide a brief history of national earthquake hazard maps in Australia, with a focus on the map used in AS1170.4, and provide an overview of the proposed changes for the new map. The revision takes advantage of the significant improvements in both the data sets and models used for earthquake hazard assessment in Australia since the original maps were produced. These include: - An additional 20+ years of earthquake observations - Improved methods of declustering earthquake catalogues and calculating earthquake recurrence - Ground motion prediction equations (i.e. attenuation equations) based on observed strong motions instead of intensity - Revised earthquake source zones - Improved maximum magnitude earthquake estimates based on palaeoseismology - The use of open source software for undertaking probabilistic seismic hazard assessment which promotes testability and repeatability The following papers in this session will address in more detail the changes to the earthquake catalogue, earthquake recurrence and ground motion prediction equations proposed for use in the draft map. The draft hazard maps themselves are presented in the final paper.

This paper presents a model to assess bushfire hazard in south-eastern Australia. The model utilises climate model simulations instead of observational data. Bushfire hazard is assessed by calculating return periods of the McArthur Forest Fires Danger Index (FFDI). The return periods of the FFDI are calculated by fitting an extreme value distribution to the tail of the FFDI data. The results have been compared against a spatial distribution of bushfire hazard obtained by interpolation of FFDI calculated at a number of recording stations in Australia. The results show that climate simulations produce a similar pattern of bushfire hazard than the interpolated observations but the simulated values tend to be up to 60% lower than the observations. This study shows that the major source of error in the simulations is the values of wind speed. Observational wind speed is recorded at a point-based station whilst climate simulated wind speed is averaged over a grid cell. On the other hand FFDI calculation is very sensitive to wind speed and hence to improve the calculation of FFDI using climate simulations it is necessary to correct the bias observed in the simulations. A statistically-based procedure to correct the simulation bias has been developed in this project. Bias-corrected calculation of FFDI shows that the major bushfire hazard in south-eastern Australia is in the western parts of SA and NSW; and in south-western Tasmania.

A probabilistic tsunami hazard assessement (PTHA) was developed for the island of Tongatapu, All modelled tsunamis were initiated by hypothetical thrust earthquakes on the nearby Kermadec-Tonga subduction zone. We provide raster outputs containing the inundation depth with an estimated 10% and 2% chance of being exceeded in 50 years, as well as the code used to perform the analysis [both available here: https://github.com/GeoscienceAustralia/ptha/tree/master/misc/probabilistic_inundation_tonga2020].

The service contains the Australian Coastal Geomorphology Landform Subtype Classifications, used to support a national coastal risk assessment. It describes the location and extent of landform subtypes identifiable at scales between 1:25,000 and 1:10,000. It also provides further detail to the Landform Type, with particular reference to feature stability (e.g. dune types) and mobility (e.g. channel types).