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.

This metadata relates to the ANUGA hydrodynamic modelling results for Busselton, south-west Western Australia. The results consist of inundation extent and peak momentum gridded spatial data for each of the ten modelling scenarios. The scenarios are based on Tropical Cyclone (TC) Alby that impacted Western Australia in 1978 and the combination of TC Alby with a track and time shift, sea-level rise and riverine flood scenarios. The inundation extent defines grid cells that were identified as wet within each of the modelling scenarios. The momentum results define the maximum momentum value recorded for each inundated grid cell within each modelling scenario. Refer to the professional opinion (Coastal inundation modelling for Busselton, Western Australia, under current and future climate) for details of the project.

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.

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.

Manila is one of the world's megacities, and the Greater Metro Manila Area is prone to natural disasters. These events may have devestating consequences for individuals, communities, buildings, infrastructure and economic development. Understanding the risk is essential for implementing Disaster Risk Reduction programs. In partnership with AusAID, Geoscience Australia is providing technical leadership for risk analysis projects in the Asia-Pacific Region. In the Philippines, Geoscience Australia is engaging with Government of the Philippines agencies to deliver the "Enhancing Risk Analysis Capacities for Flood, Tropical Cyclone Severe Wind and Earthquake in the Greater Metro Manila Area" Project.

Stochastic finite-fault ground-motion prediction equations (GMPEs) are developed for the stable continental region of southeastern Australia (SEA). The models are based on reinterpreted source and attenuation parameters for small-to-moderate magnitude local earthquakes and a dataset augmented with ground-motion records from recent significant earthquakes. The models are applicable to horizontal-component ground-motions for earthquakes 4.0 <= MW <= 7.5 and at distances less than 400 km. The models are calibrated with updated source and attenuation parameters derived from SEA ground-motion data. Careful analysis of well-constrained earthquake stress parameters indicates a dependence on hypocentral depth. It is speculated that this is the effect of an increasing crustal stress profile with depth. However, rather than a continuous increase, the change in stress parameter appears to indicate a discrete step near 10 km depth. Average stress parameters for SEA earthquakes shallower and deeper than 10 km are estimated to be 23 MPa and 50 MPa, respectively. These stress parameters are consequently input into the stochastic ground-motion simulations for the development of two discrete GMPEs for shallow and deep events. The GMPEs developed estimate response spectral accelerations comparable to the Atkinson and Boore (2006) GMPE for eastern North America (ENA) at short rupture distances (less than approximately 100 km). However, owing to higher attenuation observed in the SEA crust (Allen and Atkinson, 2007), the SEA GMPEs estimate lower ground-motions than ENA models at larger distances. A correlation between measured VS30 and ?0 was developed from the limited data available to determine the average site condition to which the GMPEs are applicable. Assuming the correlation holds, a VS30 of approximately 820 m/s is obtained assuming an average path-independent diminution term ?0 of 0.006 s from SEA seismic stations. Consequently, the GMPE presented herein can be assumed to be appropriate for rock sites of B to BC site class in the National Earthquake Hazards Reduction Program (NEHRP, 2003) site classification scheme. The response spectral models are validated against moderate-magnitude (4.0 <= MW <= 5.3) earthquakes from eastern Australia. Overall the SEA GMPEs show low median residuals across the full range of period and distance. In contrast, ENA models tend to overestimate response spectra at larger distances. Because of these differences, the present analysis justifies the need to develop Australian-specific GMPEs where ground-motion hazard from a distant seismic source may become important.

This document describes a structure for exchanging information to assist discovery and retrieval/transfer of flood information, including GIS flood mapping data. The draft class model represents metadata, data and summary information that supports the goals of the National Flood Risk Information Project (NFRIP) to improve the quality, consistency and accessibility of flood information. This document describes the data model that will be used to create an application schema.

This document is intended to provide a record of the participants, program, and discussions held at the Fire Weather and Risk Workshop, held at Peppers Craigieburn in Bowral, from 1st -4th September 2011. The workshop was attended by 77 delegates and was sponsored by the ACT Emergency Services Agency, Geoscience Australia, the Bureau of Meteorology, and the Federal Attorney Generals Department. These proceedings include the: - workshop program - executive summary by the workshop organizers - presentation abstracts (optional) - summaries of presentations and discussions (compiled at the workshop by the session chairs and scribes) - survey of participants- expectations of the workshop (received prior to the workshop) - results of a post-workshop evaluation - list of participants. This document also includes an invited journalistic-styled article by science journalist, Nick Goldie (Senior Deputy Captain, Colinton Rural Fire Brigade, NSW RFS) which provided an independent view on the activities that occurred over the three days.

The datasets created to produce the emergency mapping support products which contributed to fulfilling GA's arrangements in supporting the outcomes sought by the Australian Government during disaster events.

This report describes the 2018 Probabilistic Tsunami Hazard Assessment for Australia (henceforth PTHA18). The PTHA18 estimates the frequency with which tsunamis of any given size occur in deep waters around the Australian coastline. To do this it simulates hundreds of thousands of possible tsunami scenarios from key earthquake sources in the Pacific and Indian Oceans, and models the frequency with which these occur. To justify the PTHA18 methodologies a significant fraction of the report is devoted to testing the tsunami scenarios against historical observations, and comparing the modelled earthquake rates against alternative estimates. Although these test provide significant justification for the PTHA18 results, there remain large uncertainties in “how often” tsunamis occur at many sites. This is due to fundamental limitations in present-day scientific knowledge of how often large earthquakes occur.