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).

This dataset contains the 2010 Offshore Petroleum Acreage Release Areas. The regular release of offshore acreage is a key part of the Australian Government's strategy to encourage investment in petroleum exploration. The 2010 release consits of 31 areas in 5 sedimentary basins.

Increases in natural disasters worldwide are presenting new challenges for natural hazard risk research. Natural disasters are more likely than ever to have global impact in a world where catastrophic risk is shared across national and international boundaries and between the public and private sector. Climate change is the popular scapegoat for the increase in disasters; but exponential growth in human population and assets as well as increased exposure of populations in coastal areas and megacities are equally to blame. Interest in natural hazard risk is widespread among the public, in all levels of government, in international relations and across the private sector. This presentation explores how these issues and interests are manifest in the evolution of natural hazards risk research, including the role of geoscientists in this process. 30 years ago, natural hazard research was narrowly confined to the development of hazard maps, which were used primarily for input to building codes and the design of major infrastructure or critical facilities. Today, solutions require multi-hazard information and the development of a wide range of analyses about the exposure and vulnerability of communities. Further, it is not enough to just quantify the problem; results also require solutions in the form of options for mitigating the risk. These new demands require inter-disciplinary teams of hazard scientists, engineers, economists, social scientists, mathematicians, geographers and more. The development of solutions also requires the involvement of a wider range of stakeholders and clients in order to ensure that products are fit for purpose. The drivers for better natural hazard risk information are now evident in Australia in the form of significant new national policies. The new National Security policy issued in 2008 recognises that natural hazards can pose catastrophic risk for Australia. In 2009, the Australian Agency for International Development issued a Disaster Reduction Policy as a foundation of its capacity building programs overseas; natural hazards are a key element of this policy, which has resulted in significant investments in natural hazard risk research in the region. Geoscientists have a major role to play in meeting the demand for information on natural disasters and in assessing natural hazard risk. First of all, there is greater demand for information to describe the processes that lead to natural hazard events. This includes better understanding of the causes and probabilities of these events, as well as descriptions of events in a physical and spatial context. Hazard or risk models based solely on statistical methods are no longer sufficient. Natural hazard science is moving to physically-based models which are driven by an understanding of Earth dynamics, with increased computing power and improved simulation tools critical to this evolution. In terms of climate change hazards, there is an increasing demand for earth scientists to contribute to our understanding of the potential increases in coastal erosion, storm surge, riverine flooding, and sea-level rise, all of which require fundamental geological and geophysical input.

Understanding marine biodiversity has received much attention from an ecological and conservation management perspective. For this purpose, scientific marine surveys are necessary and often conducted by a multidisciplinary team. In particular, the data collected can come from multiple sources inheriting a particular aspect of each discipline that requires reasonable integration for the purpose of modelling biodiversity. This talk gives an overview of some strategies investigated in the Marine Biodiversity Research Hub project funded by the Commonwealth Environment Research Facilities Program to reconcile these differences.

Close up map of Submarine Cables and southern protection zone around Clovelly / Tamarama, Sydney. For internal use by ACMA. Included in this version (July 2010) is the Telstra Endeavour Cable. This map developed from previous map GeoCat 65415 (September 2007). Upated in July 2010 with the Telstra Endeavour Cable. For internal use of ACMA. Not for sale or public distribution.

This map shows the boundary of the security regulated port for the purpose of the Maritime Transport & Office Security Act 2003. 1 sheet (Colour) May 2010 Not for sale or public distribution Contract Manager LOSAMBA project, PMD

Seismic interval velocities derived from stacking velocities can provide some clues to determination of rock lithology. This concept has been applied to understand the divergent dipping reflector (DDR) and seaward dipping reflector (SDR) packages over the Wallaby Plateau and Wallaby Saddle that were imaged on the 2008/2009 seismic survey GA310 contracted by Geoscience Australia. Root mean square velocities (Vrms) used to calculate interval velocities (Vint) were derived from long cable data. Vrms were picked on traces after pre-stack time migration, and the 4th order normal move-out (NMO) correction was implemented. Therefore, distortions to interval velocities due to insufficient curvature of NMO curve at short offsets, structural dip and ray bending due to stratification are assumed to be largely suppressed. Consequently Vrms velocities are assumed to approximate average velocities.

An extensive AEM survey recently commissioned by Geoscience Australia involved the use of two separate SkyTEM helicopter airborne electromagnetic (AEM) systems collecting data simultaneously. In order to ensure data consistency between the two systems, we follow the Danish example (conceived by the hydrogeophysics group from Aarhus University) of using a hover test site to calibrate the AEM data to a known reference. Since 2001, Denmark has employed a national test site for all electromagnetic (EM) instruments that are used there, including the SkyTEM system. The Lyngby test-site is recognised as a well-understood site with a well-described layered-earth structure of 5 layers. The accepted electrical structure model of the site acts as the reference model, and all instruments are brought to it in order to produce consistent results from all EM systems. Using a ground-based time-domain electromagnetic (TEM) system which has been calibrated at the Lyngby test site, we take EM measurements at a site selected here in Australia. With sufficient information of the instrument, we produce a layered-earth model that becomes the reference model for the two AEM systems used in the survey. We then bring the SkyTEM systems to the hover site and take soundings at multiple altitudes. From the hover test data and the ground based model, we calculate an optimal time shift and amplitude scale factor to ensure that both systems are able reproduce the accepted reference model. Conductivity sections produced with and without calibration factors show noticeably different profiles.

The coastal zone is arguably the most difficult geographical region to capture as data because of its dynamic nature. Yet, coastal geomorphology is fundamental data required in studies of the potential impacts of climate change. Anthropogenic and natural structural features are commonly mapped individually, with their inherent specific purposes and constraints, and subsequently overlain to provide map products. This coastal geomorphic mapping project centered on a major coastal metropolitan area between Lake Illawarra and Newcastle, NSW, has in contrast classified both anthropogenic and natural geomorphological features within the one dataset to improve inundation modelling. Desktop mapping was undertaken using the Australian National Coastal Geomorphic (Polygon) Classification being developed by Geoscience Australia and supported by the Department of Climate Change. Polygons were identified from 50cm and 1m aerial imagery. These data were utilized in parallel with previous maps including for example 1:25K Quaternary surface geology, acid sulphate soil risk maps as well as 1:100K bedrock geology polygon maps. Polygons were created to capture data from the inner shelf/subtidal zone to the 10 m contour and include fluvial environments because of the probability of marine inundation of freshwater zones. Field validation was done as each desktop mapping section was near completion. This map has innovatively incorporated anthropogenic structures as geomorphological features because we are concerned with the present and future geomorphic function rather than the past. Upon completion it will form part of the National Coastal Geomorphic Map of Australia, also being developed by Geoscience Australia and utilized in conjunction with Smartline.

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