Evidence based disaster management enables decision makers to manage more effectively because it yields a better informed understanding of the situation. When based on evidence, the decision making process delivers more rational, credible and objective disaster management decisions, rather than those influenced by panic. The translation of fundamental data into information and knowledge is critical for decision makers to act and implement the decisions. The evidence from appropriate information helps both tactical and strategic responses to minimise impacts on community and promote recovery. The information requirements of such a system are quite comprehensive in order to estimate the direct and indirect losses; the short and long term social and economic resilience. Disasters may be of rapid onset in nature like earthquakes, tsunamis and blast. Others are slow onset such those associated with gradual climate change. Climate change has become a real challenge for all nations and the early adaptors will reduce risk from threats such as increased strength of tropical cyclones, storm surge inundations, floods and the spread of disease vectors. The Australian Government has recognised the threats and prioritised adaptation as an opportunity to enhance the nation's existing infrastructure and thereby reduce risk. A thorough understanding of the exposure under current and future climate projections is fundamental to this process of future capacity building. The nation's exposure to these increased natural hazards includes all sectors from communities to businesses, services, lifeline utilities and infrastructure. The development of a 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 multi-hazard impacts.

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.

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.

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 report presents a framework for assessng in quantitative terms the cost of the weather related hazards of severe wind, flood inundation, storm surge, bushfire and hail. It has been developed with reference to the risk assessment approaches used by the insurance and catastrophic loss modelling industry. For each hazard the specific data inputs to each component of the impacts framework are summarised as a list of implementation needs. Finally, the report identifies areas where impact models are immature or not readily available in the public domain.

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.

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.

This is a short and informative 3.3 minute movie for the Engineering, Economics and Exposure Project - NEXIS Development for DCCEE - late 2010. It is a promotional movie that demonstrates NEXIS capabilities, and explains how NEXIS will be benefitial to the NEXIS stakeholder. This movie may also go onto the web, where it's purpose is to convince the public that NEXIS is a worthwhile investment in Australia's future.

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 sensitivity of the Jaiswal and Wald (Earthq. Spectra, 2010) empirical earthquake fatality model is evaluated relative to the model space for a suite of macroseismic intensity prediction methods. The relative difference between intensity prediction methods is shown through the use of self-organizing maps to visualize high-dimensional ground shaking data in a two-dimensional space. Among all the macroseismic intensity prediction methods evaluated, there is significant variability in the resulting loss estimates for an earthquake of given source parameters with losses being most sensitive to those intensity models that predict high near-source ground shaking. Because the empirical fatality models evaluated herein are based on a consistent suite of ground-motion model inputs, application of the fatality models with other intensity prediction methods may result in undesirable outcomes. Consequently, it is recommend that empirical loss models be calibrated directly with hazard inputs used in the proposed loss assessment methodology.