From 1995 to 2000 information from the federal and state governments was compiled for Comprehensive Regional Assessments (CRA), which formed the basis for Regional Forest Agreements (RFA) that identified areas for conservation to meet targets agreed by the Commonwealth Government with the United Nations. These 3 CDs were created as part of GA's contribution to the Tasmania CRA. CD1 contains final versions of all data coverages and shapefiles used in the project, and final versions of documents provided for publishing. CD2 contains Published Graphics files in ArcInfo (.gra), postscript (.ps) and Web ready (.gif) formats. CD3 contains all Geophysical Images and Landsat data.

A question and answer style brochure on geological storage of carbon dioxide. Questions addressed include: - What is geological storage? - Why do we need to store carbon dioxide? - How can you store anything in solid rock? - Could the carbon dioxide contaminate the fresh water supply? - Could a hydrocarbon seal leak? - Are there any geological storage projects in Australia?

From 1995 to 2000 information from the federal and state governments was compiled for Comprehensive Regional Assessments (CRA), which formed the basis for Regional Forest Agreements (RFA) that identified areas for conservation to meet targets agreed by the Commonwealth Government with the United Nations. These 3 CDs were created as part of GA's contribution to the SW Western Australia CRA. CD1 contains final versions of all data coverages, images and shapefiles used in the project. CD2 contains the final CRA report, Executive Summary, and associated maps and figures in Arcinfo (.gra), postscript (.ps) and Web ready (.gif) formats. CD3 contains the final Minerals Assessment report and associated maps and figures in Arcinfo, postscript and Web ready formats.

This project was conducted by Geoscience Australia in collaboration with the Water Science Branch of the Department of Water, Western Australia, to acquire baseline information supporting the condition assessment for Hardy Inlet. The project contributes to the Estuarine Resource Condition Indicators project funded by the Strategic Reserve of the National Action Plan for Salinity and Water Quality / National Heritage Trust and forms part of the Resource Condition Monitoring endorsed under the State (Western Australia) Natural Resource Management framework. Two surveys were undertaken in Hardy Inlet in September 2007 and April 2008 with the aim to develop an understanding of the historical environmental changes and current nutrient and sediment conditions for the purpose of developing sediment indicators to characterise estuary condition.

A seabed mapping survey over a series of carbonate banks, intervening channels and surrounding sediment plains on the Van Diemen Rise in the eastern Joseph Bonaparte Gulf was completed under a Memorandum of Understanding between Geoscience Australia and the Australian Institute of Marine Sciences. The survey obtained detailed geological (sedimentological, geochemical, geophysical) and biological data (macro-benthic and infaunal diversity, community structure) for the banks, channels and plains to establish the late-Quaternary evolution of the region and investigate relationships between the physical environment and associated biota for biodiversity prediction. The survey also permits the biodiversity of benthos of the Van Diemen Rise to be put into a biogeographic context of the Arafura-Timor Sea and wider northern Australian marine region. Four study areas were investigated across the outer to inner shelf. Multibeam sonar data provide 100 per cent coverage of the seabed for each study area and are supplemented with geological and biological samples collected from 63 stations. In a novel approach, geochemical data collected at the stations provide an assessment of sediment and water quality for surrogacy research. Oceanographic data collected at four stations on the Van Diemen Rise will provide an understanding of the wave, tide and ocean currents as well as insights into sediment transport. A total of 1,154 square kilometres of multibeam sonar data and 340 line-km of shallow (<100 mbsf) sub-bottom profiles were collected.

In 2008, the performance of 14 statistical and mathematical methods for spatial interpolation was compared using samples of seabed mud content across the Australian Exclusive Economic Zone (AEEZ), which indicated that machine learning methods are generally among the most accurate methods. In this study, we further test the performance of machine learning methods in combination with ordinary kriging (OK) and inverse distance squared (IDS). We aim to identify the most accurate methods for spatial interpolation of seabed mud content in three regions (i.e., N, NE and SW) in AEEZ using samples extracted from Geoscience Australia's Marine Samples Database (MARS). The performance of 18 methods (machine learning methods and their combinations with OK or IDS) is compared using a simulation experiment. The prediction accuracy changes with the methods, inclusion and exclusion of slope, search window size, model averaging and the study region. The combination of RF and OK (RFOK) and the combination of RF and IDS (RFIDS) are, on average, more accurate than the other methods based on the prediction accuracy and visual examination of prediction maps in all three regions when slope is included and when their searching widow size is 12 and 7, respectively. Averaging the predictions of these two most accurate methods could be an alternative for spatial interpolation. The methods identified in this study reduce the prediction error by up to 19% and their predictions depict the transitional zones between geomorphic features in comparison with the control. This study confirmed the effectiveness of combining machine learning methods with OK or IDS and produced an alternative source of methods for spatial interpolation. Procedures employed in this study for selecting the most accurate prediction methods provide guidance for future studies.

The National Geochemical Survey of Australia (NGSA) project (www.ga.gov.au/ngsa) was part of Geoscience Australia's Onshore Energy Security Program 2006-2011 and was carried out in collaboration with the geological surveys of all States and the Northern Territory. It delivered (1) Australia's first national geochemical atlas, (2) an underpinning geochemical database, and (3) a series of reports. Catchment outlet sediments (similar to floodplain sediments in most cases) were sampled in 1186 catchments covering ~80% of the country (average sample density 1 sample per 5500 km2). Samples were collected at 2 depths each sieved to 2 grain size fractions. Chemical analyses carried out on the samples fall into 3 main categories: (1) total (using mainly XRF and total digestion ICP-MS), (2) aqua regia, and (3) Mobile Metal Ion® (MMI) element contents. The MMI analyses were conducted on the surface (0-10 cm) samples sieved to <2 mm, in one single batch, by ICP-MS. Concentrations of 54 elements (Ag, Al, As, Au, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Er, Eu, Fe, Ga, Gd, Hg, K, La, Li, Mg, Mn, Mo, Nb, Nd, Ni, P, Pb, Pd, Pr, Pt, Rb, Sb, Sc, Se, Sm, Sn, Sr, Ta, Tb, Te, Th, Ti, Tl, U, V, W, Y, Yb, Zn and Zr) were determined. Maps and quality assessment of these data are presented in reports available from the project website. Preliminary interpretations of the MMI dataset suggest that it potentially has significant value in geological, mineral exploration and agronomic (e.g., bioavailability) applications.

pH is one of the more fundamental soil properties governing nutrient availability, metal mobility, elemental toxicity, microbial activity and plant growth. The field pH of topsoil (0-10 cm depth) and subsoil (~60-80 cm depth) was measured on floodplain soils collected near the outlet of 1186 catchments covering over 6 M km2 or ~80% of Australia. Field pH duplicate data, obtained at 124 randomly selected sites, indicates a precision of 0.5 pH unit (or 7%) and mapped pH patterns are consistent and meaningful. The median topsoil pH is 6.5, while the subsoil pH has a median pH of 7 but is strongly bimodal (6-6.5 and 8-8.5). In most cases (64%) the topsoil and subsoil pH values are similar, whilst, among the sites exhibiting a pH contrast, those with more acidic topsoils are more common (28%) than those with more alkaline topsoils (7%). The distribution of soil pH at the national scale indicates the strong controls exerted by precipitation and ensuing leaching (e.g., low pH along the coastal fringe, high pH in the dry centre), aridity (e.g., high pH where calcrete is common in the regolith), vegetation (e.g., low pH reflecting abundant soil organic matter), and subsurface lithology (e.g., high pH over limestone bedrock). The new data, together with existing soil pH datasets, can support regional-scale decision-making relating to agricultural, environmental, infrastructural and mineral exploration decisions.

A short animation of an atmospheric simulation of methane emissions from a coal mine (produced using TAPM) compared to actual methane concentrations detected by the Atmospheric Monitoring Station, Arcturus in Central Queensland. It illustrates the effectiveness of both the detection and simulation techniques in the monitoring of atmospheric methane emissions. The animation shows a moving trace of both the simulated and actual recorded emissions data, along with windspeed and direction indicators. Some data provided by CSIRO Marine and Atmospheric Research.

The National Geochemical Survey of Australia (NGSA) project (www.ga.gov.au/ngsa) was part of Geoscience Australia's Onshore Energy Security Program 2006-2011 and was carried out in collaboration with the geological surveys of all States and the Northern Territory. It delivered (1) Australia's first national geochemical atlas, (2) an underpinning geochemical database, and (3) a series of reports. Catchment outlet sediments (similar to floodplain sediments in most cases) were sampled in 1186 catchments covering ~80% of the country (average sample density 1 sample per 5500 km2). Samples were collected at 2 depths each sieved to 2 grain size fractions. Chemical analyses carried out on the samples fall into 3 main categories: (1) total (using mainly XRF and total digestion ICP-MS), (2) aqua regia, and (3) Mobile Metal Ion® element contents. Results to date indicate a common spatial coincidence of elevated commodity element concentrations near areas of known mineralisation, for instance of U, Au and REEs. The survey data also identifies areas with elevated concentrations of energy and ore-related elements away from known deposits or occurrences, information which may be useful to the exploration industry. Comparison with airborne radiometric data indicates reasonable correlations between ground and airborne concentrations of K, U and Th. The phenomenon of disequilibrium in the radioactive decay chain of U does lead to some insights about leaching and accumulation of the more mobile daughter products (e.g., Rn, Ra). A continental-scale correction factor for airborne gamma-ray U surveys applicable to depositional areas is being developed.