The Asia-Pacific region is home to well over half the world's population and is also the focus of some of earth's most intense geological activity. It is no surprise therefore that geological hazards, in particular earthquake and volcano hazards, make the Asia-Pacific region the scene of som e of the worlds most lethal natural disasters. While this is evident form a perusal of historical data relating to natural disasters, it is not clear how well such historical data can be used as a guide for high -impact events that might be expected in the future. This uncertainty is due to (1) how poorly extreme geological events having long recurrence intervals are represented in the relatively short historical record, and (2) the failure of the historical record to account for recent demographic trends, in particular the explosive growth of population in the Asia -Pacific region and its rapid urbanisation during the 20 th century. We present here two novel techniques for assessing the potential impacts of volcanic and earthquake events on human population in the Asia Pacific region. For volcanic risk, we have calculated the frequency of large eruptions, aggregated for the countries of the Asia -Pacific region, using data provided by the Smithsonian Institution's Global Volcanism Program. These eruption frequ encies have been combined with an analysis of population data for the region to estimate the average number of people who might be affected, in the broad sense of death, injury or loss of essential services, by a major volcanic eruption. For earthquake, risk, we have considered that the potential future high -impact events will be driven by the probability that an earthquake might occur in or adjacent to one of the many megacities of the Asia -Pacific region. Earthquake probabilities near megacities are cal culated from catalogue data, and these are combined with a rough criterion for damage based on earthquake ground motion, to asses potentially affected populations. We present preliminary results of these analyses, which suggest the potential for earthquakes and volcanoes in the Asia-Pacific region to cause future `mega-disasters', for which affected populations may be much larger than the numbers indicated by the historical record.

A key recommendation of the Council of Australian Governments review into natural disaster management arrangements in Australia is that a five-year national program of systematic and rigorous disaster risk assessments be developed and implemented. This process requires the construction of national databases and standardised methods and models that allow objective comparison of risks between regions and across hazards. A significant component of this process is the completion and delivery of a series of national earthquake risk assessments. The need for an improved understanding of earthquake ground shaking in Australia was recognised following the 1989 Newcastle earthquake, which resulted in 13 fatalities and A$4.5 billion in estimated losses. An enhanced capability to anticipate the impacts of such events will facilitate improved earthquake disaster mitigation and planning for Australian communities, and influence the development of relevant engineering codes and standards. To achieve this it is necessary to model earthquake events, the mechanisms by which earthquake energy dissipates, and the potential influence of variation in geological materials on the ground shaking. At present, national scale earthquake hazard products for Australia do not included the effect of regolith site response on ground shaking, and as such may provide inconsistent or inaccurate estimates of ground shaking in some areas. The development of the National Regolith Site Classification Map represents a significant advance in our ability to model the potential influence of near-surface geological materials on earthquake ground shaking, and therefore to assess earthquake hazard and risk in Australia. The National Regolith Site Classification Map presented here has been developed through the application of a pre-existing methodology which has been modified to suit Australian conditions. The changes include the development and application of an innovative method to account for weathering in bedrock geological units. To the extent that the data permits, site classification takes into account the age and physical properties of the geological materials and relates them to key geophysical parameters that most accurately represent the behaviour of these materials under the influence of earthquake ground motion. The compilation of data at both national and regional scales has led to the development of a multi-resolution tool that provides more detailed information in and around the major population centres. This same variation in spatial resolution does, however, make map sheet edge mismatches unavoidable. The National Regolith Site Classification Map provides a tool for estimating the regolith site response to ground shaking at any location in Australia. This product has potential implications for revision of earthquake-related Standards and Building Codes in Australia, particularly regarding the criteria used to classify sites according to ground shaking potential. When implemented within Geoscience Australia's National Earthquake Risk Model (EQRM) the National Regolith Site Classification Map and associated amplification factors represent fundamental components of the most rigorous available method for assessing earthquake risk in Australia.

As part of its response to the Indian Ocean tsunami of 26 December 2004, the Australian Government funded the establishment of the Australian Tsunami Warning System (ATWS). The ATWS has three objectives: (i) provide a comprehensive warning system for Australia, (ii) contribute to international efforts to establish an Indian Ocean Tsunami Warning System, and (iii) facilitate tsunami warnings in the Pacific Ocean. The ATWS has been issuing warnings for Australia since July 2006, and in 2007 started sharing advisories with other warning centres. It expects to begin issuing advisories directly to other countries during 2009. To be successful, an end-to-end warning system must develop mitigation strategies to prepare communities for tsunami. Mitigation strategies include taking steps to minimise the impact of a tsunami, eg., avoiding building in the likely inundation zone and building sea walls when this can't be avoided, and response procedures, such as evacuations, when an event occurs. The warning system must monitor for tsunami and issue warnings; and it must implement response strategies when a tsunami approaches the coastline and a recovery phase afterwards (Figure 1). In Australia, responsibility for these phases is shared by Commonwealth, State/Territory and Local Governments. Etc ...

We have developed a Building Fire Impact Model to evaluate the probability that a building located in a peri-urban region of a community is affected/destroyed by a forest fire. The methodology is based on a well-known mathematical technique called Event Tree (ET) modeling, which is a useful graphical way of representing the dependency of events. The tree nodes are the event itself, and the branches are formed with the probability of the event happening. If the event can be represented by a discrete random variable, the number of possible realisations of the event and their corresponding probability of occurring, conditional on the realisations of the previous event, is given by the branches. As the probability of each event is displayed conditional on the occurrence of events that precede it in the tree, the joint probability of the simultaneous occurrence of events that constitute a path is found by multiplication (Hasofer et al., 2007). BFIM contains a basic implementation of the main elements of bushfire characteristics, house vulnerability and human intervention. In the first pass of the BFIM model, the characteristics of the bushfire in the neighboring region to the house is considered as well as the characteristics of the house and the occupants of the house. In the second pass, the number of embers impacting on the house is adjusted for human intervention and wind damage. In the third pass, the model examines house by house conditions to determine what houses have been burnt and their impact on neighboring houses. To illustrate the model application, a community involved in the 2009 Victorian bushfires has been studied and the event post-disaster impact assessment is utilized to validate the model outcomes. MODSIM 2013 Conference

Geoscience Australia (GA) is currently undertaking the process to update the Australian National Earthquake Hazard Map using modern methods and an extended 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. We have recently seen 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, we need to consider other numerical techniques to develop these models in the absence of these data. Recently published Australian-specific GMPEs which employ these numerical techniques are now available and these will be integrated into GA's future hazard outputs. 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 of ground-motion modelling in Australia; 2) a comparison of Australian GMPEs against those commonly used in other stable continental regions; 3) a comparison of new GMPEs against their intensity-based counterparts used in the previous hazard map; and 4) the impact of updated attenuation factors on local magnitudes in southeastern Australia. Specific regional and temporal aspects of magnitude calculation techniques across Australia and its affects on the earthquake catalogue will also be addressed.

The Australian National Coastal Vulnerability Assessment (NCVA) has been commissioned by the Federal Government (Department of Climate Change) to assess the risk to coastal communities from climate related hazards. The first-pass national assessment includes an evaluation of the exposure of infrastructure (residential and commercial buildings as well as roads and major infrastructure such as ports and airports) to sea-level rise and storm surge. In addition to an understanding of the 'number by type' and 'replacement value' of infrastructure at risk from inundation posed by the current climate, we have also examined the change in risk of inundation under a range of future climate scenarios (up to the end of the 21st century). The understanding of coastal vulnerability and risk is derived from a number of factors, including: the frequency and intensity of the hazard(s); community exposure and the relationship with stressors; vulnerability related to socio-economic factors; impacts that result from the interaction of those components; and capacity of communities, particularly vulnerable communities and groups, to plan, prepare, respond and recover from these impacts. These factors and resulting impacts from hazard events are often complex and often poorly known, but such complexity and uncertainty is not an excuse for inaction. Given these limitations, the NCVA has been undertaken using the best information available to understand the risk to coastal areas on a national scale, and to prioritise areas that will require more detailed assessment.

Severe wind is one of the major natural hazards in Australia. The main contributors to economic loss in Australia are tropical cyclones, thunderstorms and sub-tropical (synoptic) storms. Geoscience Australia's Risk and Impact Analysis Group (RIAG) is developing mathematical models to study a number of natural hazards including wind hazard. This study examines synoptic wind hazard under current and future climate scenarios using RIAG's synoptic wind hazard model. This model can be used in non-cyclonic regions of Australia (Region A in the Australian-New Zealand Wind Loading Standard; AS/NZS 1170.2:2002) which are dominated by synoptic and thunderstorm winds. The methodology to study synoptic wind hazard involves a combination of three models: - a statistical model (ie. a model based on observed data) to quantify wind hazard using extreme value distributions; - a technique to extract and process wind speeds from a high-resolution regional climate model (RCM), which produces gridded hourly 'maximum time-step mean' wind speed and direction fields; and - a Monte Carlo method to generate gust wind speeds from the RCM mean winds. Gust wind speeds are generated by a numerical convolution of the modelled mean wind speed distribution and a distribution of observed 'regional' gust factor. To illustrate the methodology, wind hazard calculations under current and future climate conditions for the Australian state of Tasmania will be presented. The results show increases in synoptic wind hazard in some parts of the state especially at the end of this century.

Tropical cyclones, thunderstorms and sub-tropical storms can generate extreme winds that can cause significant economic loss. Severe wind is one of the major natural hazards in Australia. The Geoscience Australia's Risk and Impact Analysis Group (RIAG) is developing mathematical models to study a number of natural hazards including wind hazard. In this study, RIAG's wind hazard model for non-cyclonic regions of Australia (Region A in the Australian-New Zealand Wind Loading Standard; AS/NZS 1170.2(2010)) for both current and a range of projected future climate are discussed. The methodology involves a combination of 3 models: - A Statistical Model (ie. a model based on observed data) to quantify wind hazard using extreme value distributions. - A technique to extract and process wind speeds from a high-resolution regional climate model (RCM) which produces gridded hourly 'maximum time-step mean' wind speed and direction fields, and a - Monte Carlo method to generate gust wind speeds from the RCM mean winds. Gust wind speeds are generated by a numerical convolution of the mean wind speed distribution and a regional 'observed' gust factor. Wind hazard at a particular location is affected by the corresponding wind direction. In the last part of this paper a methodology to calculate wind direction multipliers over a region is presented. These multipliers are used to assess the actual wind hazard at the given location. To illustrate the methodology involved with the calculation of severe wind hazard, including the effect of wind direction, analysis over the Australian state of Tasmania will be presented (current and future climate).

The impacts of climate change, including sea level rise and the increased frequency of storm surge events, will adversely affect infrastructure in a significant number of Australian coastal communities. In order to quantify this risk, Geoscience Australia in collaboration with the Department of Climate Change and Energy Efficiency, have undertaken a first-pass national assessment which has identified the extent and value of infrastructure that are potentially vulnerable to impacts of climate change. We have utilised the best available national scale information to assess the vulnerability of Australia's coastal zone to the impacts of climate change. In addition to assessing coastal vulnerability assuming the current population, we also examined the changes in exposure under a range of future population scenarios provided by the Australian Bureau of Statistics. Continuation of the current trend for significant development in the coastal zone increases the number and value of residential buildings potentially vulnerable by 2100. We found that over 270,000 residential buildings are potentially vulnerable to the combined impacts of inundation and recession by 2100. This equates to a replacement value of approximately AUD$72 billion. Nearly 250,000 residential buildings were found to be potentially vulnerable to inundation only, which equates to AUD$64 billion. Queensland and New South Wales have the largest vulnerability (considering both value and number of buildings affected). Nationally, approximately 33,000 km of road and 1,500 km of rail infrastructure are potentially at risk by 2100. These results are influencing policy and adaptation planning decisions made by federal, state and local government.

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