The Coorong, a shallow coastal lagoon at the mouth of the Murray River, has had a significant decline in water quality over the last 15 years because of reduced freshwater inflows. Salinity has increased throughout the lagoon and currently ranges between 60 and 190 psu depending on the proximity to the Murray Mouth and the season. Although nutrient inflow has been negligible in recent years, the lagoon is considered euthrophic. This study aimed to identify the source of nutrients and the biogeochemical processes that transform them. The key findings were: 1. Groundwater discharge is likely to be an important nutrient source 2. Nitrogen appears to be the nutrient limiting primary production 3. Decomposition of organic matter in the sediments is highly seasonal with much higher rates in the summer.

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 series of short field surveys in Jervis Bay, New South Wales, were undertaken by Geoscience Australia staff as part of the Surrogates Program in the Commonwealth Environmental Research Facilities (CERF) Marine Biodiversity Hub. The aim of the Jervis Bay field work was to collect accurately co-located physical and biological data to enable research into the utility of physical parameters as surrogates for patterns of benthic biodiversity in shallow soft-sediment habitats. In this report the survey design and sampling methods are described; selected field datasets are mapped and discussed; initial results of the laboratory analysis of seabed samples are presented; and there is a brief description of the upcoming analysis of covariance of the physical and biological datasets. The major outputs of the survey work to date are: 1. High-resolution multibeam acoustic datasets for priority areas along the open coast of Jervis Bay (Beecroft Head to Drum and Drumsticks), within the Jervis Bay National Park; and within the southern bay around Darling Road, and in the bay entrance. 2. High quality underwater video footage of benthic habitats in the Darling Road study area acquired with Geoscience Australia's shallow-water towed-video system. The video was used to characterise benthic habitat types, relief/bedform types, and biota occurrence. Characterisations were collected in real-time along bi-directional (six offshore and four alongshore) towed video transects, and were subsequently processed and mapped into three ArcGIS map layers. 3. A set of broad-scale (bay-wide) widely-spaced, co-located sediment and biotic (infauna) seabed samples from the bay's soft-sediment habitats (polychaete mounds, drift algal beds, sand flats, and sand ripple and wave habitats); 4. Sediment samples for geochemical, biogeochemical and sedimentological analyses. 5. A new acoustic doppler current profiler was successfully trialed, and is now being used to collect seabed current data in the Darling Road study area. 6. A progress report on the survey work was presented at the annual CERF Marine Biodiversity Hub's Annual Science Workshop in October 2008.

This atlas volume summarises historic geographical knowledge about Australia's soil resources and land use and complements the other environmental and resource topics in the Atlas of Australia Resource Series. The following volumes in this series are also available: <ul><li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60922">Volume 3: Atlas of Australian Resources Third Series - Agriculture (1982 (edition)</a></li> <li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60924">Volume 5: Atlas of Australian Resources Third Series - Geology and Minerals (1988 edition)</a> </li> <li><a href="https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&amp;catno=60925">Volume 6: Atlas of Australian Resources Third Series - Vegetation (1990 edition)</a></li> </ul> <strong>The following PDFs have been reproduced in A3 format, for best results please print on A3 paper (297mm x 420mm).</strong>

In this study, we conducted a simulation experiment to identify robust spatial interpolation methods using samples of seabed mud content in the Geoscience Australian Marine Samples database. Due to data noise associated with the samples, criteria are developed and applied for data quality control. Five factors that affect the accuracy of spatial interpolation were considered: 1) regions; 2) statistical methods; 3) sample densities; 4) searching neighbourhoods; and 5) sample stratification. Bathymetry, distance-to-coast and slope were used as secondary variables. Ten-fold cross-validation was used to assess the prediction accuracy measured using mean absolute error, root mean square error, relative mean absolute error (RMAE) and relative root mean square error. The effects of these factors on the prediction accuracy were analysed using generalised linear models. The prediction accuracy depends on the methods, sample density, sample stratification, search window size, data variation and the study region. No single method performed always superior in all scenarios. Three sub-methods were more accurate than the control (inverse distance squared) in the north and northeast regions respectively; and 12 sub-methods in the southwest region. A combined method, random forest and ordinary kriging (RKrf), is the most robust method based on the accuracy and the visual examination of prediction maps. This method is novel, with a relative mean absolute error (RMAE) up to 17% less than that of the control. The RMAE of the best method is 15% lower in two regions and 30% lower in the remaining region than that of the best methods in the previously published studies, further highlighting the robustness of the methods developed. The outcomes of this study can be applied to the modelling of a wide range of physical properties for improved marine biodiversity prediction. The limitations of this study are discussed. A number of suggestions are provided for further studies.

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 5 CDs were created as part of GA's contribution to the SE Queensland CRA. CD1 contains ArcView Legends and Projects, data coverages, shapefiles, all documents and reports and associated maps and figures. CD2 contains various edited versions of covers and shapefiles, original data supplied by custodians, and staff workareas. CD3 contains Landsat, Magnetics etc. images. CD4 contains DEM etc. CD5 contains integration data, miscellaneous ArcInfo grids, and ArcInfo graphic files.

This dataset contains species identifications of molluscs collected during survey SOL4934 (R.V. Solander, 27 August - 24 September, 2009). Animals were collected from the Joseph Bonaparte Gulf with a benthic sled. Specimens were lodged at Northern Territory Museum on the 8 February 2010. Species-level identifications were undertaken by Richard Willan at the Northern Territory Museum and were delivered to Geoscience Australia on the 15 March 2010. See GA Record 2010/09 for further details on survey methods and specimen acquisition. Data is presented here exactly as delivered by the taxonomist, and Geoscience Australia is unable to verify the accuracy of the taxonomic identifications.<p><p>This dataset is not to be used for navigational purposes.

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.

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?

This chapter presents a broad synthesis and overview based on the 57 case studies included in Part 2 of this book, and on questionnaires completed by the authors. The case studies covered areas of seafloor ranging from 0.15 to over 1,000,000 km2 (average of 26,600 km2) and a broad range of geomorphic feature types. The mean depths of the study areas ranged from 8 to 2,375 m, with about half of the studies on the shelf (depth <120 m) and half on the slope and at greater depths. Mapping resolution ranged from 0.1 to 170 m (mean of 13 m). There is a relatively equal distribution of studies among the four naturalness categories: near-pristine (n=17), largely unmodified (n = 16), modified (n=13) and extensively modified (n=10). In terms of threats to habitats, most authors identified fishing (n=46) as the most significant threat, followed by pollution (n=12), oil and gas development (n=7) and aggregate mining (n=7). Anthropogenic climate change was viewed as an immediate threat to benthic habitats by only three authors (n=3). Water depth was found to be the most useful surrogate for benthic communities in the most studies (n=17), followed by substrate/sediment type (n=14), acoustic backscatter (n=12), wave-current exposure (n=10), grain size (n=10), seabed rugosity (n=9) and BPI/TPI (n=8). Water properties (temperature, salinity) and seabed slope are less useful surrogates. A range of analytical methods were used to identify surrogates, with ARC GIS being by far the most popular method (23 out of 44 studies that specified a methodology).