The Philippine Institute of Volcanology and Seismology (PHIVOLCS) and Geoscience Australia (GA) have developed a long-term partnership in order to better understand and reduce the risks associated with earthquake hazards in the Philippines. The Project discussed herein was supported by the Australian Agency for International Development (AusAID). Specifically, this partnership was designed to enhance the exposure and damage estimation capabilities of the Rapid Earthquake Damage Assessment System (REDAS), which has been designed and built by PHIVOLCS. Prior to the commencement of this Project, REDAS had the capability to model a range of potential earthquake hazards including ground shaking, tsunami inundation, liquefaction and landslides, as well as providing information about elements at risk (e.g., schools, bridges, etc.) from the aforementioned hazards. The current Project enhances the exposure and vulnerability modules in REDAS and enable it to estimate building damage and fatalities resulting from scenario earthquakes, and to provide critical information to first-responders on the likely impacts of an earthquake in near real-time. To investigate this emergent capability within PHIVOLCS, we have chosen the pilot community of Iloilo City, Western Visayas. A large component of this project has been the compilation of datasets to develop building exposure models, and subsequently, developing methodologies to make these datasets useful for natural hazard impact assessments. Collection of the exposure data was undertaken at two levels: national and local. The national exposure dataset was gathered from the Philippines National Statistics Office (NSO) and comprises basic information on wall type, roof type, and floor area for residential buildings. The NSO census dataset also comprises crucial information on the population distribution throughout the Philippines. The local exposure dataset gathered from the Iloilo City Assessors Office includes slightly more detailed information on the building type for all buildings (residential, commercial, government, etc.) and appears to provide more accurate information on the floor area. However, the local Iloilo City dataset does not provide any information on the number of people that occupy these buildings. Consequently, in order for the local data to be useful for our purposes, we must merge the population data from the NSO with the local Assessors Office data. Subsequent validation if the Iloilo City exposure database has been conducted through targeted foot-based building inventory surveys and has allowed us to generate statistical models to approximate the distribution of engineering structural systems aggregated at a barangay level using simple wall and roof-type information from the NSO census data. We present a comparison of the national and local exposure data and discuss how information assembled from the Iloilo City pilot study - and future study areas where detailed exposure assessments are conducted - could be extended to describe the distribution of building stock in other regions of the Philippines using only the first-order national-scale NSO data. We present exposure information gathered for Iloilo City at barangay level in a format that can be readily imported to REDAS for estimating earthquake impact.

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.

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.

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.

Large research initiatives such as the Global Earthquake Model (GEM) or the Seismic HAzard haRmonization in Europe (SHARE) projects concentrate a great collaborative effort for defining a global standard for seismic hazard estimations. In this context, there is an increasing need for identifying ground motion prediction equations (GMPEs) that can be applied at both global and regional scale. With increasing amounts of strong motion records which are now available worldwide, observational data can provide a valuable resource to tackle this question. Using the global dataset of Allen and Wald (2009), we evaluate the ability of fifteen GMPEs for active shallow crustal regions to predict ground-motion in California, Japan, Europe and Middle East, Italy and Turkey. Adopting the approach of Scherbaum et al. (2009), we rank these GMPEs according to their likelihood of having generated the data. In particular, we estimate how strongly data support or reject the models with respect to the state of non-informativeness defined by a uniform weighting. Such rankings derived from this particular global dataset enable us to determine conditions in terms of magnitudes and distances under which a model could be applied in its main region of derivation but also in other regions. In the ranking process, we particularly focus on the influence of the distribution of the testing dataset compared to the GMPE's native dataset. One of the results of this study is that some non-indigenous models present a high degree of consistency with the data from a target region. Two models in particular demonstrated a strong power of geographically wide applicability in different geographic regions with respect to the testing dataset: the models of Akkar and Bommer (2010) and Chiou et al. (2010).

11-5413 The Probabilistic Volcanic Ash - Hazard Map movie describes how you construct a probabilistic hazard map for volcanic ash, using an example scenario from GA's volcanic ash modelling work in West Java, Indonesia. The target audience is other govt. agencies both national and international, and the general public. The 3.3 minute movie uses 3D Max animations and 2D affects, has narration and production music. The narration will also be done in Bahasa Indonesian, at a later date.

The National Exposure Information System (NEXIS) is a capability developed by Geoscience Australia, an agency within the portfolio of the federal Department of Resources, Energy and Tourism. NEXIS is a nationally consistent database of building assets, essential infrastructure, economic activity and demographic information. All these community elements are at risk to natural hazards and will be exposed to the unavoidable, long term influences of climate change. The system collects and collates a broad range of information for research and policy development in Australia, including that associated with climate change adaptation. The development of NEXIS has been undertaken in parallel to ongoing national assessments of climate change risk for hazards such as storm surge, severe wind, bushfire and extreme temperature NEXIS employs a largely statistical approach to developing a national definition of exposure using a number of existing databases maintained by others. These include the Geocoded National Address File (GNAF), the Property Cadastre, the Business Registry, and census datasets from the Australian Bureau of Statistics. Costing modules developed by quantity surveyors have also been incorporated to provide estimates of building replacement costs across Australia. State Government departments have supplied data on local building information in Tasmania and South Australia. The Census of Land Use and Employment (CLUE) has also been made available by local government for comprehensive information about land use, employment and economic activity across the entire Greater Melbourne area.

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.

Crucial elements for assessing earthquake risk are exposure and vulnerability. In assessing earthquake risk to the Australian built environment we need to know what is exposed to earthquake ground motion and also how vulnerable the exposed infrastructure is to the severity of shaking. While central business district (CBD) buildings make up a relatively small proportion of Australia's built environment their function and the business activity they support is vital to Australia's economy. This paper describes an ongoing effort by the Australian Government to undertake engineering and architectural surveys of buildings within state capital CBDs. With funding from the Attorney-General's Department Geoscience Australia has recently completed a survey of the Melbourne CBD and will complete surveys of the Sydney, Adelaide and Brisbane CBDs this financial year. Survey teams comprise a structural engineer and a GIS operator who populates survey fields on a handheld computer. Approximately 90 survey data fields are incorporated in the template to enable capture of the variety in building features. The fields cover building characteristics that are understood to influence earthquake vulnerability. A summary of the survey activity undertaken to date is presented here along with some examples of the type of data that is being collected.

Note: A more recent version of this product is available. This dataset contains spatial locations in point format as a representation of Electricity Transmission Substations in Australia. For government use only. Access through negotiation with Geoscience Australia