Wildfires are one of the major natural hazards facing the Australian continent. Chen (2004) rated wildfires as the third largest cause of building damage in Australia during the 20th Century. Most of this damage was due to a few extreme wildfire events. For a vast country like Australia with its sparse network of weather observation sites and short temporal length of records, it is important to employ a range of modelling techniques that involve both observed and modelled data in order to produce fire hazard and risk information/products with utility. This presentation details the use of statistical and deterministic modelling of both observations and synthetic climate model output (downscaled gridded reanalysis information) in the development of extreme fire weather potential maps. Fire danger indices such as the McArthur Fire Forest Danger Index (FFDI) are widely used by fire management agencies to assess fire weather conditions and issue public warnings. FFDI is regularly calculated at weather stations using measurements of weather variables and fuel information. As it has been shown that relatively few extreme events cause most of the impacts, the ability to derive the spatial distribution of the return period of extreme FFDI values contributes important information to the understanding of how potential risk is distributed across the continent. The long-term spatial tendency FFDI has been assessed by calculating the return period of its extreme values from point-based observational data. The frequency and intensity as well as the spatial distribution of FFDI extremes were obtained by applying an advanced spatial interpolation algorithm to the recording stations' measurements. As an illustration maps of 50 and 100-year return-period (RP) of FFDI under current climate conditions are presented (based on both observations and reanalysis climate model output). MODSIM 2013 Conference

The National Exposure Information System (NEXIS) project is an initiative of Geoscience Australia in response to the Australian Government's research priority of safeguarding Australian communities from natural hazards, critical infrastructure failures and policy development. The governmental priority urges the implementation of a 'nationally consistent system of data collection, research and analysis to ensure a sound knowledge-base on natural disasters and disaster mitigation'. The infrastructure exposure definition and development framework suitable for multi hazards and climate change impact analysis is highly complex. NEXIS aims to meet the challenge by collecting, collating and maintaining nationally consistent exposure information at the individual building level. This requires detailed spatial analysis and the integration of available demographic, structural and statistical data for various sectors. The system integrates data from several national spatial databases, such as the Geocoded National Address File, the Property Cadastre, Australian Bureau of Statistics (ABS) census data, and building data from Australian state governments. It also includes post disaster survey information and data from several infrastructure agencies and local government bodies. NEXIS provides a representative assessment of asset exposure to several hazard models which can be aggregated to an appropriate level from State to mesh block level for the required application. By integrating the information with the decision-support tools of alert systems and early warning, it can enable the rapid forecasting of the impacts due to various hazards (infrastructure damage and casualties). Currently it is being used for tactical response for emergency managers and strategic policy and planning development. In addition to enabling research in Geoscience Australia's risk and impact analysis projects, it supports several government initiatives across the departments and national committees.

A model to assess severe wind hazard using climate-simulated wind speeds has been recently completed at Geoscience Australia. The model can calculate return period of wind speeds over a given region considering current as well as future climate conditions. The winds extracted from the climate simulations are winds at 10m height over open terrain. In hazard studies it is important however, to refer the wind speeds to the characteristics of the given location in order to calculate the actual severe wind hazard at the regional level. This is achieved by multiplying the generic wind hazard by a number of wind multipliers. One of those multipliers is wind direction. The wind direction multiplier recognises the prevailing direction of the strongest winds and affects the wind hazard accordingly. Lower wind hazard would correspond to the direction of low wind speeds. In practical applications engineers calculate the wind load in structures by multiplying the design wind speeds recommended by the Australian/NZ standards for wind loading in structures (AS/NZS 1170.2:2010) by some generic multipliers also given in the standards. The multipliers have been developed considering a number of Bureau of Meteorology (BoM) weather recording stations at particular locations in Australia; this method cannot capture the actual regional characteristics in such a vast country like Australia. In this paper we propose a new methodology for calculation of wind direction multipliers based on wind speeds and direction extracted from climate simulations. Our method allows a more realistic assessment of the wind direction multiplier at a particular region.

This paper discusses two of the key inputs used to produce the draft National Earthquake Hazard Map for Australia: 1) the earthquake catalogue and 2) the ground-motion prediction equations (GMPEs). The composite catalogue used draws upon information from three key catalogues for Australian and regional earthquakes; a catalogue of Australian earthquakes provided by Gary Gibson, Geoscience Australia's QUAKES, and the International Seismological Centre. A complex logic is then applied to select preferred location and magnitude of earthquakes depending on spatial and temporal criteria. Because disparate local magnitude equations were used throughout Australia, we performed first order magnitude corrections to standardise magnitude estimates to be consistent with the attenuation factors defined by contemporary local magnitude ML formulae. While most earthquake magnitudes do not change significantly, our methodology can result in reductions of up to one magnitude unit in certain cases. Subsequent ML-MW (moment magnitude) corrections were applied. The catalogue was declustered using a magnitude dependent spatio-temporal filter. Previously identified blasts were removed and a time-of-day filter was developed to further deblast the catalogue. Secondly, a suite of candidate GMPEs were systematically tested against 5% damped response spectra recorded from Australian earthquakes in eastern and Western Australia, respectively. Since many GMPEs are developed for earthquakes larger than approximately MW 5.0, much of the data recorded in Australia is below the magnitude threshold prescribed by these equations. Nevertheless, where necessary, we extrapolate these equations to lower magnitudes to test the general applicability of the GMPEs for different source zones across Australia. The relative weights of the GMPEs for the draft national hazard model were initially determined objectively by the authors using these analyses as a basis. Final GMPE weights will be assigned through consultation with key stakeholders through the AEES.

The Rapid Inventory Collection System (RICS) is a vehicular data collection system (image and GPS) used for building/infrastructure damage and inventory assessment. The system consists of Ethernet cameras attached to a tripod mounted on a motor vehicle, a GPS receiver and software written in C++. The RICS data was used by the 2009 Victorian Bushfires Royal Commission for the impact assessment (field survey) which quantified the extent and severity of the damage caused by the fire-storm.

Geoscience Australia is currently undertaking the process to update the Australian National Earthquake Hazard Map using modern methods and an extended, more complete catalogue of Australian earthquakes. This map is a key component of Australia's earthquake loading code. The characterisation of strong ground-shaking using Ground-Motion Prediction Equations (GMPEs) underpins any earthquake hazard assessment. Recently there have been many advances in ground-motion modelling for active tectonic regions. However, the challenge for Australia - as it is for other stable continental regions - is that there are very few ground-motion recordings from large-magnitude earthquakes with which to develop empirically-based GMPEs. Consequently, there is a need to consider other numerical techniques to develop GMPEs in the absence of recorded data. Recently published Australian-specific GMPEs, which employ these numerical techniques, are now available and these will be integrated into Geoscience Australia's future hazard outputs. <p> This paper addresses several fundamental aspects related to ground-motion in Australia that are necessary to consider in the update of the National Earthquake Hazard Map, including: 1) a summary of recent advances in ground-motion modelling in Australia; 2) a comparison of Australian GMPEs against those commonly used in other stable continental regions; and 3) the impact of updated attenuation factors on local magnitudes in Australia. Specific regional and temporal aspects of magnitude calculation techniques across Australia and its affects on the earthquake catalogue will also be addressed. </p>

Power point presentation given to a meeting of earthquake hazard model stakeholders, in Sydney on July 22nd 2008.

In order to calibrate earthquake loss models for the U.S. Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER) system, two databases have been developed: an Atlas of ShakeMaps and a catalog of human population exposures to moderate to strong ground shaking (EXPO-CAT). The full ShakeMap Atlas currently contains over 5,600 earthquakes from January 1973 through December 2007, with almost 500 of these maps constrained by instrumental ground motions, macroseismic intensity data, community internet intensity observations, and published earthquake rupture models. The catalog of human exposures is derived using current PAGER methodologies. Exposure to discrete levels of shaking intensity is obtained by merging Atlas ShakeMaps with a global population database. Combining this population exposure dataset with historical earthquake loss data provides a useful resource for calibrating loss methodologies against a systematically-derived set of ShakeMap hazard outputs. Two applications of EXPO-CAT are illustrated: i) a simple objective ranking of country vulnerability to earthquakes, and; ii) the influence of time-of-day on earthquake mortality. In general, we observe that countries in similar geographic regions with similar construction practices tend to cluster spatially in terms of relative vulnerability. We find only limited quantitative evidence to suggest that time-of-day is a significant factor in earthquake mortality. Finally, we combine all the Atlas ShakeMaps to produce a global map of the peak ground acceleration (PGA) observed in the past 35 years, and compare this composite ShakeMap with existing global hazard models. In general, these analyses suggest that existing global and regional hazard maps tend to overestimate hazard.

The National Exposure Information System (NEXIS) is a capability developed by Geoscience Australia, an agency within the portfolio of the federal Department of Resources, Energy and Tourism. NEXIS is a nationally consistent database of building assets, essential infrastructure, economic activity and demographic information. All these community elements are at risk to natural hazards and will be exposed to the unavoidable, long term influences of climate change. The system collects and collates a broad range of information for research and policy development in Australia, including that associated with climate change adaptation. The development of NEXIS has been undertaken in parallel to ongoing national assessments of climate change risk for hazards such as storm surge, severe wind, bushfire and extreme temperature NEXIS employs a largely statistical approach to developing a national definition of exposure using a number of existing databases maintained by others. These include the Geocoded National Address File (GNAF), the Property Cadastre, the Business Registry, and census datasets from the Australian Bureau of Statistics. Costing modules developed by quantity surveyors have also been incorporated to provide estimates of building replacement costs across Australia. State Government departments have supplied data on local building information in Tasmania and South Australia. The Census of Land Use and Employment (CLUE) has also been made available by local government for comprehensive information about land use, employment and economic activity across the entire Greater Melbourne area.

11-5519 Metropolitan Manilla (Philippines). Philippine GIS data-sets should arrive from the source on the 15th of July, 2011. GAV will process the data, and produce a short movie. The movie will reveal the 17 town halls of the greater metro Manilla; and outline the fault line, as well as earthquake affected areas, flood affected areas and cyclone affected areas. This movie is for the Philippine Govt. via Ausaide, and will include photographs of Philippine nationals assisting in disaster reduction work. The aquired data-sets will be stored on the GA data store, where access can be gained through communication with Luke Peel - GEMD National Geographic Information Section, Geoscience australia.