Hydrometeorological events make up or contribute to a majority of disasters in Australia and around the world. Scientists expect climate change will accelerate the frequency and intensity of these events in the future. Information on the location and characteristics of the built and social environment combined with hazard modelling and spatial analysis can facilitate the identification of buildings, people and infrastructure exposed to a particular natural hazard event. This information informs evidence based decision making and future planning to aid in the preparedness, response and recovery to severe hazard events. In Australia, the National Exposure Information System (NEXIS) is a significant national project being undertaken by Geoscience Australia (GA). In 2006 GA embarked on the development of NEXIS in response to the Council of Australian Governments (COAG) reform commitment on Australian's ability to manage natural disasters and other emergencies. The COAG commitment called for the establishment of a 'nationally consistent system of data collection, research and analysis to ensure a sound knowledge base on natural disasters and disaster mitigation' (DOTARS 2002). NEXIS database contains information on buildings, people, businesses and infrastructure and is derived from publicly available demographic, structural, economic and statistical data. Exposure profiles contain information on: building type, size, construction materials, age, replacement costs and population demographics for all residential, commercial and industrial buildings in Australia. Aggregated exposure information underpins risk assessment, emergency management, climate change adaptation, urban planning, insurance industry and research to help assist evidence based decision making. NEXIS development and operationalisation is crucial to support the decision makers and underpins community safety, emergency management and disaster risk reduction initiatives Australia This paper will discuss the development of NEXIS and its application in several national projects with the Department of Climate Change Energy and Efficiency (DCCEE) in Australia and recent national disaster impacts assessments on: Queensland tropical cyclone Yasi, Victoria bushfires and the Queensland floods.

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

Overhead transmission lines are a key element of the electrical power system for transferring bulk power from generators to communities. Lattice type transmission towers carrying conductors form the physical backbone of the power transmission system. Transmission tower safety and reliability assessment is necessary to plan for minimisation of the risk of disruption of power supply resulting from in-service tower failure. Lattice type transmission towers are constructed using angle section members and are eccentrically connected. They are regarded as one of the most difficult forms of lattice structures to analyse for dynamic loads. Analysis is difficult due to fabrication errors, inadequate joint details and material properties being hard to quantify as a combination. Proof loading and full-scale tower testing is a traditional form of design validation for lattice type towers [1]. However, loading conditions experienced in severe wind events are dynamic and relatively short term loads and this behavior is confirmed in a limited way through full scale measurements of aero-elastic models in wind tunnels [2].

Geoscience Australia (GA) began the development of the National Exposure Information System (NEXIS) in response to COAG reform Commitment 2 'establish a nationally consistent system of data collection, research and analysis to ensure a sound knowledge base on natural disasters and disaster mitigation' (COAG, 2003). It was also recognised as a priority for the development of better models and tools to allocate investment across prevention, preparedness, response and recovery (PPRR) and also to assess the impact of emergencies on the community in the Emergency Management Information Development Plan (Harper, 2006). The NEXIS underpins various activities of risk assessment modelling, critical infrastructure failures, early warning systems and several national priority initiatives. This system will provide consistent and best available information at a national scale (for example, the number and type of buildings, businesses, people, critical infrastructure, and institutions such as schools and hospitals) to understand hazard exposure, at all locations in Australia.

The Climate Futures for Tasmania (CFT) research project is the Tasmanian Government's most important source of climate change data at a local scale. The project has created fine-scale (14 kilometre) climate information for Tasmania by downscaling five global climate models (GCM-s) with two IPCC emission scenarios (A2 and B1) to generate climate information from 1961 to 2100. This new dataset is being used to interpret the impact of the changing climate on four main disciplines: General Climate, Water and Catchments, Extreme Events and Agriculture. As part of the extreme events component, Geoscience Australia is conducting severe wind hazard and risk studies in the Tasmanian region under both current and future climate conditions. In this paper we present severe wind hazard maps for Tasmania for current and future climate. The CFT fine scale climate simulations which provide high-resolution spatial detail of the wind speed (hourly maximum time-step mean wind speed used) were used. The methodology is described in an accompanying paper ('Dynamical downscaling of severe wind hazard: Methodology', in these proceedings).

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.

The tragic events of the Indian Ocean tsunami on 26 December 2004 highlighted the need for reliable and effective alert and response sysems for tsunami threat to Australian communities. Geoscience Australia has established collaborative partnerships with state and federal emergency management agencies to support better preparedness and to improve community awareness of tsunami risks.

An increase in the frequency and intensity of storms, coastal flooding, and spread of disease as a result of projected climate change and sea-level rise is likely to damage built environments and adversely affect a significant proportion of Australia's population. Understanding the assets at risk from climate change hazards is critical to the formulation of adaptation responses and early action is likely to be the most cost effective approach to managing the risk. Understanding the level of exposure of assets, such as buildings, lifeline utilities and infrastructure, under current and future climate projections is fundamental to this process. The National Exposure Information System (NEXIS) is a significant national capacity building task being undertaken by Geoscience Australia (GA). NEXIS is collecting, collating, managing and providing the exposure information required to assess climate change impacts. It provides residential, business and infrastructure exposure information derived from several fundamental datasets. NEXIS is also expanding to include institutions (such educational, health, emergency, government and community buildings) and lifeline support infrastructure exposure. It provides spatial exposure data in GIS format at a building level and is often provided to clients for an area of interest. It is also designed to predict future exposure for climate change impact analysis. NEXIS is currently sourcing more specific datasets from various data custodians including state and local governments along with private data providers. NEXIS has been utilised in various climate change impact projects undertaken by CSIRO, the Department of Climate Change (DCC), the Department of Environment, Water, Heritage and the Arts (DEWHA), and several universities. Examples of these projects will be outlined during the presentation.

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.

When considering structural design with regard to wind loading, the Australian building code through the Australia/New Zealand Wind Actions Standard (AS/NZS 1170.2, 2002) as well as the wind engineering community in general, relies to a significant extent on the peak wind gust speed observations collected over more than 60 years by the Bureau of Meteorology (BoM). The wind-loading performance of our infrastructure (resilience) is based primarily on the Dines anemometer interpretation of the peak gust wind speed. In the early 1990's BoM commenced a program to replace the aging pressure tube Dines anemometer with the Synchrotac and Almos cup anemometers. This paper presents the results of a reanalysis of the current BoM peak wind gust database for the non-cyclonic region (Region A) of AS/NZS 1170.2 (2002). We compares estimates of the 500-year RP peak wind gust hazard magnitude derived of varying observing record lengths obtained from 31 "Region A" BoM sites. Region A was considered for this initial study as record length would contain a significant number of extreme events (synoptic or thunderstorm) over decadal time scales (i.e. extremes not dominated by one or two tropical cyclone events). To isolate the issue of anemometer replacement, only wind stations located at airports (consistent exposure) and with more than 30 years of record were considered. The methodology was formulated to explore the consistency of peak wind gust measurements due to issues surrounding equipment upgrading. Comparison of results indicated that the recent period (1990-2006) appears to have a reduction in significant events (13 of 31 sites have a mean 500 year RP below the 95% confidence limit for the 500 year RP estimate using the total record). Future plans are to calibrate some existing Dines instruments in-situ in an effort to provide sufficient information to fully specify the dynamic response over the range of operating conditions