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  • The tragic events of the Indian Ocean tsunami on 26 December 2004 highlighted shortcomings in the alert and response systems for tsunami threats to Western Australia's (WA) coastal communities. To improve community awareness and understanding of tsunami hazard and potential impact for Western Australia, the Fire and Emergency Services Authority of WA (FESA) established a collaborative partnership with GA in which science and emergency management expertise was applied to identified communities.

  • The term "Smartline" refers to a GIS line map format which can allow rapid capture of diverse coastal data into a single consistently classified map, which in turn can be readily analysed for many purposes. This format has been used to create a detailed nationally-consistent coastal geomorphic map of Australia, which is currently being used for the National Coastal Vulnerability Assessment (NCVA) as part of the underpinning information for understanding the vulnerability to sea level rise and other climate change influenced hazards such as storm surge. The utility of the Smartline format results from application of a number of key principles. A hierarchical form- and fabric-based (rather than morpho-dynamic) geomorphic classification is used to classify coastal landforms in shore-parallel tidal zones relating to but not necessarily co-incident with the GIS line itself. Together with the use of broad but geomorphically-meaningful classes, this allows Smartline to readily import coastal data from a diversity of differently-classified prior sources into one consistent map. The resulting map can be as spatially detailed as the available data sources allow, and can be used in at least two key ways: Firstly, Smartline can work as a source of consistently classified information which has been distilled out of a diversity of data sources and presented in a simple format from which required information can be rapidly extracted using queries. Given the practical difficulty many coastal planners and managers face in accessing and using the vast amount of primary coastal data now available in Australia, Smartline can provide the means to assimilate and synthesise all this data into more usable forms.

  • Imagine you are an incident controller sitting in front of a computer screen that is showing you where a fire that's just started is likely to head. Not just that, but also what houses and other structures in the fire's path are likely to burn, and even the number and type of people living in the area - children, adults, elderly. In addition imagine that you can quantify the uncertainty in both the fire weather and also the state of the vegetation so as to deliver a range of simulations relating to the expected firespread which allow the incident controller to address 'what if' scenarios. Think of the advantages of such a program in making speedy, accurate decisions about where best to send fire trucks and fire-suppression aircraft; in being able to issue timely, locality-specific warning messages; in judging whether this fire will become so bad that it might warrant recommending not only an early, orderly evacuation of communities in its way, but also identifying the least risky roads for people to get to safety. A computer program that will not only be able to help with all this and more in a fire, but will also be capable of use at any time in identifying what structures, streets and communities would be at risk should a fire occur, enabling those at risk to undertake remedial work around their properties in advance to make them better fire-ready. This will be achieved by building up a library of possible / credible fire impact scenarios based on the knowledge of observed (historical) severe fire weather conditions as well as vegetation information (fuel type/amount/moisture).

  • The 2002 report to the Council of Australian Governments (COAG) <i>Natural disasters in Australia: Reforming mitigation, relief and recovery arrangements</i> advocated a 'fundamental shift in focus towards cost-effective, evidence-based disaster mitigation'. The report stated that in Australia there was a 'lack of independent and comprehensive systematic natural disaster risk assessments, and natural disaster data and analysis'. One key solution proposed to address this gap in our knowledge is outlined in Reform Commitment 1 in the report: <i>Develop and implement a five-year national programme of systematic and rigorous disaster risk assessments</i>. This framework is designed to improve our collective knowledge about natural hazard risk in Australia to support emergency risk management and natural hazard mitigation. The natural hazards covered are those defined in the report to COAG: bushfire, earthquake, flood, storm, cyclone, storm surge, landslide, tsunami, meteorite strike and tornado. Many events have demonstrated that the importance of natural hazards does not lie simply in the generation and passage of events such as severe storms or floods, but in the wide-reaching and profound impacts that these events can have on communities. Risk 1 is defined as: A concept to describe the likelihood of harmful consequences arising from the interaction of hazards, communities and the environment. This framework focuses on risk assessment for sudden onset natural hazards to underpin natural hazard risk management and natural hazard mitigation. The framework does not focus on risk management or mitigation, although its outcomes support and benefit these. The framework covers the following risks arising from natural hazards: financial, socio-economic, casualty, political and environmental risk. Each of these risks contributes to the overall impacts of natural hazards on communities . This framework is aimed foremost at those who seek an improved evidence base for risk management of natural hazards, in all levels of government. The framework is also intended for risk assessment practitioners, researchers and information managers. The primary driver of the framework is the need to develop an improved evidence base for effective risk management decisions on natural hazards. Developing this improved evidence base will also deliver on COAG Reform Commitment 1. Other key drivers include: - Cooperative approaches across all levels of government to managing natural hazards; - A consistent approach to natural hazard risk assessment; - Risk management for cross-jurisdictional and catastrophic disasters; - The potential impacts of climate change from possible changes in the frequency or severity of weather related natural hazards; - Increasing exposure of populations to natural hazards through demographic change and increases in personal assets.

  • 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. In this study, regional return period wind gust hazard (10 metre height over open terrain) is determined using a new methodology developed by Geoscience Australia over the past 3 years. The methodology developed for severe wind hazard (3-second peak gust) involves a combination of 3 models: - A Statistical Model (ie. data-based model) to quantify wind hazard using extreme value distributions. - A Monte Carlo method to calculate severe wind hazard produced by gust wind speeds using results from the Statistical Model. The method generates synthetic wind gust speeds by doing a numerical convolution of mean wind speeds and gust factors. - A high-resolution regional climate model (RCM) which produces gridded hourly 'maximum time-step mean- wind speed and direction fields. Area-averaged measurements from the RCM are 'corrected' for point measurement exposure by calibration with existing measurements. To assess model accuracy severe wind hazard return period levels (50, 100, 200, 500, 1000 and 2000 years) were determined for a number of locations where a long observation record is available. Comparisons are made between observational and RCM-generated return period of gust speeds; and also with the Australian/New Zealand wind loading standards (AS/NZS 1170.2, 2002).

  • The short historical record of tropical cyclone activity in the Australian region is insufficient for estimating return period wind speeds at long return periods (greater than 100 years). Utilising the auto-correlated nature of tropical cyclone behaviour (forward speed and direction, intensity and size), Geoscience Australia has developed a statistical-parametric model of tropical cyclone behaviour to generate synthetic event sets that are statistically similar to the historical record. The track model is auto-regressive, with lag-1 auto-regression used for forward speed and bearing, and lag-2 auto-regression applied to the intensity and size characteristics. Applying a parametric wind field and a linear boundary layer model to the synthetic tropical cyclone tracks allows users to generate synthetic wind swaths, and in turn fit extreme value distributions to evaluate return period wind speeds spatially. The model has been applied to evaluate severe wind hazard across Australia and neighbouring regions. In conjunction with statistical models of synoptic (mid-latitude storms) and thunderstorm wind hazard, we have been able to generate a national assessment of severe wind hazard, which is comparable to existing wind loading design standards. Using tropical cyclone-like vortex tracks directly detected from regional climate models, it is also possible to project cyclonic wind hazard into future climate conditions, accounting for both changes in frequency and intensity of tropical cyclones.

  • Cyclone Tracy is the only tropical cyclone to have devastated a major Australian population centre. Following the disaster (December 1974), the Australian Government implemented significantly improved building standards aimed at reducing the impact of a similar event in future. Geoscience Australia has developed models of severe wind risk for the Australian continent which utilise impact modelling, where we separately assess hazard, exposure and vulnerability in order to evaluate impact/damage. As often occurs in extreme natural disasters, meteorological instrumentation failed prior to the maximum wind gusts being recorded, so the spatial extent of the peak wind gusts were inferred from models constrained by estimates of the observed maximum peak wind gust. For this study, we utilise the wind vulnerability relationships determined in recent years for similar circa 1974 structures, and our knowledge of the type and specific location of structures at the time, to make the link between hazard and impact/damage. This spatial damage estimation (site specific values) is compared with the observed 1974 post-event survey damage in an effort to validate the model. As a result of Cyclone Tracy and the subsequent evacuation of 75% of the population, much more attention was given to building codes and other social aspects of disaster planning (i.e. tree planting). The likelihood of another severe cyclone impacting Darwin is real and on past experience likely within the next few decades. The study utilises both the exposure and vulnerability for 1974 and present-day residential building inventories, to evaluate the resulting effectiveness of the improved building codes. This provides a comparative impact assessment of the scenario were Cyclone Tracy to occur in the current cyclone season and evaluates the reduced vulnerability of the present building stock (compared to 1974). The study also assesses the effect that improved building standards have had on the Darwin community.

  • We report on an assessment of severe wind hazard across the Australian continent, and severe wind risk to residential houses (quantified in terms of annualised loss). A computational framework has been developed to quantify both the wind hazard and risk due to severe winds, based on innovative modelling techniques and application of the National Exposure Information System (NEXIS). A combination of tropical cyclone, synoptic and thunderstorm wind hazard estimates is used to provide a revised estimate of the severe wind hazard across Australia. The hazard modelling utilises both 'current-climate information and also simulations forced by IPCC SRES climate change scenarios, which have been employed to determine how the wind hazard will be influenced by climate change. We have also undertaken a national assessment of localised wind speed modifiers including topography, terrain and the built environment (shielding). It is important to account for these effects in assessment of risk as it is the local wind speed that causes damage to structures. The effects of the wind speed modifiers are incorporated through a statistical modification of the regional wind speed. The results from this current climate hazard assessment are compared with the hazard based on the existing understanding as specified in the Australian/New Zealand Wind Loading Standard (AS/NZS 1170.2, 2002). Our analysis has identified regions where the design wind speed depicted in AS/NZS 1170.2 is significantly lower than 'new' hazard analysis. These are regions requiring more immediate attention regarding the development of adaptation options including consideration by the wind loading standards committee for detailed study in the context of the minimum design standards in the current building code regulations.

  • Disaster management is most effective when it is based on evidence. Evidence-based disaster management means that decision makers are better informed, and the decision making process delivers more rational, credible and objective disaster management outcomes. To achieve this, fundamental data needs to be translated into information and knowledge, before it can be put to use by the decision makers as policy, planning and implementation. Disaster can come in all forms: rapid and destructive like earthquakes and tsunamis, or gradual and destructive like drought and climate change. Tactical and strategic responses need to be based on the appropriate information to minimise impacts on the community and promote subsequent recovery. This implies a comprehensive supply of information, in order to establish the direct and indirect losses, and to establish short and long term social and economic resilience. The development of the National Exposure Information System (NEXIS) is a significant national project being undertaken by Geoscience Australia (GA). NEXIS collects, collates, manages and provides the information required to assess multi-hazard impacts. Exposure information may be defined as a suite of information relevant to all those involved in a natural disaster, including the victims, the emergency services, and the policy and planning instrumentalities.

  • This presentation will provide an overview of some of the work currently being undertaken at Geoscience Australia GA) as part of the National Coastal Vulnerability Assessment (NCVA), funded by the Department of Climate Change (DCC). The presentation will summarise the methodology applied, and highlight the issues, including the limitations and data gaps.