FIRE-DST is the largest of the projects within the extended Bushfire Cooperative Research Centre (BCRC). It is addressing the sub-theme of evaluating risk by developing a framework and computational methodology for evaluating the impacts and risks of extreme fire events on regional and peri-urban populations (infrastructure and people) applicable to the Australian region. The research is considering three case studies of recent extreme fires employing an ensemble approach (sensitivity analysis) which varies the meteorology, vegetation and ignition in an effort to estimate fire risk to the case-study fire area and adjacent region. Outcomes from recent extreme fires have demonstrated a need for a tool to assess future bushfire impacts and risk on regional and peri-urban communities. Such a tool would illustrate (map) bushfire impact and risk across the urban fringe and will also enable fire and land management authorities to develop and assess the effect of appropriate fire risk treatment options at local, regional and national levels. The tool would also characterise vegetation, extreme fire weather, firespread, smoke production and dispersion, and estimate the consequences of extreme fires on communities. As well as being validated using conditions pertaining at the time of the case study events, the tool will be used to explore alternative scenarios reflecting the sensitivity in ignition, fuel load and state, meteorology and fire spread, as well as alternative suppression strategies. Results from these scenario analyses and associated reports and papers will be communicated via the project website and through structured workshops.

Stochastic finite-fault ground-motion prediction equations (GMPEs) are developed for the stable continental region of southeastern Australia (SEA). The models are applicable for horizontal-component ground motions for earthquakes 4.0 <= MW <= 7.5 and 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 (BSSA, 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, BSSA, 2007), the SEA GMPEs estimate lower ground-motions than ENA models at larger distances. 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, Eastern North American 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.

The Australian Bureau of Meteorology (BoM) have been recording peak gust wind speed observations in the Australian region for over 70 years. The current wind loading code and the performance of our infrastructure is based primarily on the Dines anemometer interpretation of the peak gust wind speed. Australian building codes through the Australia/New Zealand Wind Actions Standard [1] as well as the wind engineering community in general rely to a significant extent on these peak gust wind speed observations. In the mid-1980's the Australian Bureau of Meteorology (BoM) commenced a program to replace the aging pressure tube Dines anemometer with the Synchrotac and Almos cup anemometers. Only six Dines anemometers remain in operation, mainly as backup or for high-speed measurement. During the anemometer replacement procedure, many localities had more than one type of anemometer operating, recording extreme events. The passage of Cyclone Vance through Exmouth in 1999 saw Dines and Almos anemometers, separated by 25 metres, recording peak gusts of 144 and 122 knots respectively [2]. A weak cyclone that passed through Townsville in April 2000 recorded a peak gust of 70 knots on the Dines and 59 knots on the Almos anemometer [3]. These systematic differences raise concerns about the consistency and utility of the peak gust wind speed database.

Macroseismic shaking intensity is a fundamental parameter for the development, calibration, and use in a variety of hazard maps as well as in empirical (direct) and semi-empirical (indirect) earthquake shaking loss methodologies. Macroseismic data also quantify damage from past and present events and facilitate communicating ground motion levels in terms of human experiences and incurred losses. The aim of this report is to summarize and recommend 'best practices' for the use of macroseismic intensity in conjunction with hazard maps (particularly ShakeMaps) and as input to associated loss models. The continued reliance on macroseismic intensity data dictates that ground motion prediction equations (GMPEs) alone are not always sufficient for estimating or constraining shaking hazards. Relations that allow direct estimation of intensity given an earthquake magnitude and distance, and those that convert ground motions to intensity (and vice versa) are required. Forward estimation of macroseismic intensities take two primary forms: 1) direct intensity prediction equations (IPEs), and 2) ground-motion-to-intensity conversion equations (GMICE). In addition, one can potentially better constrain historical ground motions at particular sites by employing intensity-to-ground-motion conversion equations (IGMCEs), though such equations are rare. Both the Global Earthquake Model (GEM) and Global ShakeMap (GSM) require advice and optimization in the state-of-the-art use of ground motion and intensity data. We provide background on the issues relating ground motions to intensities, directly predicting intensities, and offer insight into their uses.

The Bushfire CRC initiated in 2011 the project 'Fire & Impact Risk Evaluation - Decision Support Tool (F.I.R.E.-D.S.T)' involving Geoscience Australia, CSIRO, Bureau of Meteorology and University of Melbourne. The project is the largest of the Bushfire CRC's suite of projects and conducts research into the multiple aspects required for the computer simulation of bushfire impact and risk on the peri-urban and urban interface. This paper will provide an overview of the research directions for the project and our research progress. In particular we will summarise our progress in: - The development of a Bushfire Risk Assessment Framework, - The inclusion of detailed building information to improve exposure, - The inclusion of human factors and wind damage in determining building vulnerability to bushfires, - The new Bureau of Meteorology ACCESS Numerical Weather Prediction (NWP) system to provide high temporal and spatial resolution meteorology for input into the PHOENIX Rapidfire fire spread simulation model, - The development of very-high resolution local wind modifiers, - The changes made to the PHOENIX fire simulation system, - The development of an bushfire impact/damage subsystem, - The integration of the exposure, vulnerability, fire spread and impact systems to produce a cohesive research tool, and - Initial research on convection column and smoke plume dynamics. The team examined the effectiveness of this research by analysing numerous simulation scenarios. This paper will display the effectiveness of the research progress by providing one example of the comparison between the 2009 Black Saturday

Poster describing the FIRE-DST project (GA contribution) focising on the developments in 2011/12 FY with respect to the Bushfire Risk Assessment Framework (BRAF) and the computational framework.

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 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.

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.

As part of the Climate Futures for Tasmania project (CFT) Geoscience Australia's Risk and Impact Analysis Group (RIAG) is conducting a severe wind hazard assessment for Tasmania under current climate conditions as well as two future climate scenarios. The assessment uses climate-simulated data generated by a high resolution regional model. A poster presented to this workshop shows the main results of the project [1]; a brief description of the methodology developed for the project is discussed in a paper also presented to this workshop [2]. In this paper three possible sources of error in the calculation of the severe wind hazard (using the methodology discussed in [2]) will be examined and recommendations on ways to improve the model results will be provided.