This Record presents data collected as part of the ongoing NTGS-GA geochronological collaboration between July 2000 and June 2011 under the National Geoscience Agreement (NGA). This record presents new SHRIMP U-Pb zircon and monazite geochronological results for 18 samples from the Arunta Region, Davenport Province, Simpson Desert and Pine Creek Orogen in the Northern Territory. Five Paleoproterozoic igneous and metasedimentary samples were collected from the Eastern Arunta (ILLOGWA CREEK), and one metasedimentary sample from the eastern Casey Inlier (HALE RIVER). One igneous volcanic sample and two metasedimentary samples are from the Davenport Province (MAPSHEET) and Simpson Desert regions (HAY RIVER), respectively. Ten samples in total were collected from the Pine Creek Orogen; one igneous sample from DARWIN, the remainder being igneous and metasedimentary samples from the Nimbuwah Domain (ALLIGATOR RIVER).

Known magmatic-related uranium mineralisation is rare in Australia, despite the widespread occurrence of uranium-rich igneous rocks. Known intrusive-related mineralisation is almost entirely restricted to South Australia, while uranium mineralisation related to volcanic rocks is mostly known from northern Queensland. This apparent discrepancy suggests that Australia is under-represented in this category of uranium mineral system, and as such, the potential for future discoveries is inferred to be high. Recent work by Geoscience Australia has sought to enhance the prospectivity for a range of uranium mineral system types in Australia, including those related to magmatic rocks, by undertaking regional scale assessments of the potential for these systems. Using a similar approach, an assessment for the potential for magmatic-related uranium mineral systems has been undertaken in a systematic manner on a national scale. This has been done in a GIS environment using the fuzzy logic method, which allows for uncertainty to be captured while being relatively easy to implement. Two subcategories of magmatic-related uranium systems have been assessed: intrusive- and volcanic-related. Rather than attempting to identify specific sites of mineralisation, this investigation has focused on delineating those igneous units and events which have the highest potential for a magmatic-related uranium mineral system to operate. This allows for potentially prospective tracts to be readily identified, in which the mineral potential and uranium depositional sites may be refined using detailed local knowledge and datasets. Potentially prospective igneous rocks have been identified in all States and Territories where uranium exploration is currently permitted, including regions already known for magmatic-related uranium occurrences. Significantly, this study has identified high potential in regions which are currently not well known for magmatic-related uranium mineralisation.

Note that this Record has now been published as Record 2014/050, GeoCat number 78802

In early 2011 PRL provided Geoscience Australia with the Old Drill Hole Clearing dataset. This dataset shows the location of old drill lines cleared through the rainforest on Christmas Island. Drill lines were cleared to test the land for phosphate deposits and were cleared from the 1960Âs through to the 1970Âs, before Phosphate Resources Limited (PRL) began mining on the island. No clearing of primary rainforest has occurred under PRL. This dataset can be combined with the Pre-PRL Clearing (pre_prl_clearing.shp) data to give a realistic representation of all cleared areas on the island. The dataset can be accessed from the CIGIS CD from the following path: C:\CIGIS\environment\old_dh_clearingextent_poly.shp

Sub-sampling is a commonly used technique to reduce the amount of time and effort for investigating biological specimens of, especially, a large quantity. However, it is not immediately clear how sub-sampling may affect the estimates of biodiversity measures such as species presence/absence, richness and abundance by using such sub-sampled data. This article quantifies the effect of sub-sampling as attenuation of the species abundance distribution. Its theoretical description is derived by accounting for the random sampling scheme of finite populations and is illustrated using sub-sampled data collected by a marine survey. It shows the theory and data are in agreement. Our method can be used to set benchmarks for sub-sampling schemes since the departure from this model estimates the unexpected bias peculiar to the sub-sampling scheme adopted. This quantification also enables the effect of sub-sampling to be incorporated into further model development for biodiversity estimates.

The OzCoasts web-based database and information system draws together a diverse range of data and information on Australia's coasts and its estuaries. Maps, images, reports and data can be downloaded and there are tools to assist with coastal science, monitoring, management and policy. The content is arranged into seven inter-linked modules: Search Data, Conceptual Models, Coastal Indicators, Habitat Mapping, Natural Resource Management, Landform and Stability Maps and Climate Change. The Climate Change module is the newest feature of the website and was developed in partnership with the Australian Government Department of Climate Change and Energy Efficiency. The module provides information and tools to help communicate the risks of sea-level rise and other potential impacts of climate change on coastal areas. It includes an elevation data and a modelling portal for access to existing and new elevation data and derived products, including sea level inundation maps for Perth to Mandurah, Melbourne, Sydney, Hunter and Central Coast & Brisbane and Gold Coast. The inundation footprints illustrate three sea level rise scenarios: a low (0.5m), medium (0.8m) and high (1.1m) scenario for a 2100 time period, with values based on IPCC projections (B1 and A1FI scenarios) and more recent science. OzCoasts will also soon deliver the Coastal Eutrophication Risk Assessment Tool (CERAT) for the NSW Department of Environment, Climate Change and Water, and the Australian Riverscape Classification Service (AURICL) for the Tropical Rivers and Coastal Knowledge (TRaCK) consortium. CERAT will help identify and prioritise land use planning decisions to protect and preserve the health of NSW estuaries. AURICL has a northern tropical focus, and is a dynamic and flexible system for classifying catchments and their rivers based on the similarity, or dissimilarity, of a wide range of parameters.

This research utilises metadata from GA's centralised metadata store containing the history of the equipment changes which have taken place at all GNSS stations; such as antenna or receiver swaps, firmware upgrades and removal/ alteration of antenna domes and cables. Several change detection algorithms have been implemented for automatic detection of discontinuities in the coordinate time series. Once offsets are detected, their position in time is correlated with equipment changes or earthquake occurrences nearby the station. If a correlation is found and the offset is visibly evident, the offset is introduced into a database. This information is used in the routine combination of weekly SINEX solutions using the CATREF software to produce an enhanced set of coordinates and velocities. It is shown that after cleansing the offsets in time series using this approach, the quality of the combined APREF solution is improved in terms of WRMS. By analysing time series coordinates at a few stations using CATS software, it is shown that the uncertainty of velocity estimates is improved after offsets are detected and removed from the time series.

AUSPOS, Geoscience Australia's online GPS positioning service, has now been in worldwide use since 2000 and has processed over 150,000 user data files. In 2011, the AUSPOS service was fully upgraded to use the Bernese Software as the processing engine together with more sophisticated GPS data analysis strategies, new ITRF to GDA transformations and the recently developed the AUSGEIOD09 model. In this presentation, we will briefly overview the AUSPOS2 system including the improved modelling and analysis strategies employed. Then, we will present test results for AUSPOS2 using 1, 2, 6, 12, 24 hours of data from 232 IGS2008 core stations as well stations from the Asia Pacific Reference Frame (APREF) network within mainland Australia using the IGS final, rapid and ultra rapid products, respectively. Preliminary tests using 24 hours data show that coordinate differences between AUSPOS solutions and APREF weekly solutions are within a millimetres level for all three components.

Climate change is expected to increase severe wind hazard in many regions of the Australian continent with consequences for exposed infrastructure and human populations. The objective of this paper is to provide an initial nationally consistent assessment of wind risk under current climate, utilizing the Australian/New Zealand wind loading standard (AS/NZS 1170.2, 2002) as a measure of the hazard. This work is part of the National Wind Risk Assessment (NWRA), which is a collaboration between the Australian Federal Government (Department of Climate Change and Energy Efficiency) and Geoscience Australia. It is aimed at highlighting regions of the Australian continent where there is high wind risk to residential structures under current climate, and where, if hazard increases under climate change, there will be a greater need for adaptation. This assessment is being undertaken by separately considering wind hazard, infrastructure exposure and the wind vulnerability of residential buildings. The NWRA will provide a benchmark measure of wind risk nationally (current climate), underpinned by the National Exposure Information System (NEXIS; developed by Geoscience Australia) and the wind loading standard. The methodology which determines the direct impact of severe wind on Australian communities involves the parallel development of the understanding of wind hazard, residential building exposure and the wind vulnerability of residential structures. We provide the current climate wind risk, expressed as annualized loss, based on the wind loading standard.

Floods are Australia's most expensive natural hazard with the average annual cost of floods estimated at AUD$377 million (BITRE 2008). This figure is likely to have risen following the widespread and devastating floods across eastern Australia that occurred over the summer of 2010-11. The development of tools to support the identification and analysis of flood risk is an important first step in reducing the cost of floods in the community. The Australian Government through Geoscience Australia (GA) has been leading the development of tools which assist in flood intelligence, modelling and damage assessment. An overview of three of these tools will be provided in this presentation. Note: Rest of abstract is too long for space provided.