To perform a realistic 3D inversion of gravity data covering a significant proportion of the surface of the Earth, it is necessary to take into account the curvature of the Earth. We have developed an algorithm for inverting gravity data in spherical coordinates and have demonstrated this using data covering the continental mass of Australia and surrounding ocean areas. The density structures evident in the crust and uppermost mantle of the resultant 3D inversion model are in broad agreement with knowledge of the geological features for the region and with variations in the depth to the Moho that are present in the AusMoho model.

During 2009-11 Geoscience Australia completed a petroleum prospectivity study of the offshore northern Perth Basin as part of the Australian Government's Offshore Energy Security Program. A significant component of the program was the acquisition of a regional 2D reflection seismic and potential field survey GA-310 in 2008/09. Basement in the northern Perth Basin is deep and generally not resolved in the reflection seismic data. This study models the observed gravity in 2.5D along two southwest trending dip-direction reflection seismic transects across WA11-18 to provide insight into the likely sediment thickness and basement topography. Three cases and ten models are examined according to assumptions about possible target depth to basement, and assumptions about Moho depth

Ross C Brodie Murray Richardson AEM system target resolvability analysis using a Monte Carlo inversion algorithm A reversible-jump Markov chain Monte Carlo inversion is used to generate an ensemble of millions of models that fit the forward response of a geoelectric target. Statistical properties of the ensemble are then used to assess the resolving power of the AEM system. Key words: Monte Carlo, AEM, inversion, resolvability.

Geoscience Australia's Risk & Impact Analysis Group has developed a statistical model of wind hazard utilising the Generalised Pareto Distribution (GPD). The model calculates the return period of severe winds based on daily maximum wind gust observations. The model utilises an automated procedure to partition the data into the hazard constituents (thunderstorms, synoptic winds, tornadoes, etc) based on the World Meteorological Observation Codes 3-hourly coded observations. This observational data set records the archived and present weather at the station site. The model fits the GPD to the station data (daily maximum wind gust) by automating the selection of the appropriate threshold above which data is included in the extreme value distribution. This threshold <em>u</em> is selected as the maximum of all feasible return period values obtained by fitting the GPD. Published comparative findings, including same region results, demonstrate the model can produce similar results in a more efficient, fully computational way. Confidence intervals for return periods are calculated automatically to allow wind analysts to distinguish regions of greater reliability.

Despite growing concerns about potential enhancement of global warming and slope failure by methane produced by gas hydrate dissociation, much uncertainty surrounds estimates of gas hydrate reservoir sizes, as well as methane fluxes and oxidation rates at the sea floor. For cold seep sediments of the eastern Mediterranean Sea, depth-dependent methane concentrations and rates of anaerobic oxidation of methane (AOM) are constrained by modeling the measured pore-water sulfate profile. The calculated dissolved methane distribution and flux are sensitive to the advective flow velocity, which is estimated from the depth distributions of conservative pore-water constituents (Na, B). Near-complete anaerobic oxidation of the upward methane flux is supported by the depth distributions of indicative biomarkers, and the carbon isotopic compositions of organic matter and dissolved inorganic carbon. Pore-water and solid-phase data are consistent with a narrow depth interval of AOM, 14-18 cm below the sediment-water interface. Based on an isotopic mass balance, the biomass of the microbial population carrying out oxidation of methane coupled to sulfate reduction at the given methane flux represents about 20% of the total organic carbon, which is a significant pool of in situ formed organic matter. Model results indicate that the asymptotic methane concentration is reached a few meters below the sediment surface. The predicted asymptotic concentration is close to the in situ saturation value with respect to gas hydrate, suggesting that the rate of shallow gas hydrate formation is controlled by the ascending methane flux. The proposed model approach can be used to predict the formation of gas hydrate, and to quantify methane fluxes plus transformation rates in surface sediments where fluid advection is an important transport mechanism.

Increasing the knowledge of ocean current patterns in Torres Strait region is of direct interest to indigenous communities and industries such as fisheries and shipping that operate in the region. Ocean circulation in Torres Strait influences nearly all aspects of the ecosystem, including sediment transport and turbidity patterns, primary production in the water column and bottom sediments, and recruitment patterns for organisms with pelagic phases in their life cycles. This study is the first attempt to describe the water circulation and transport patterns across Torres Strait and adjacent gulfs and seas, on time scales from hours to years. It has also provided a framework for an embedded model describing sediment transport processes (described in Margvelashvili and Saint-Cast, 2006). The circulation model incorporated realistic atmospheric and oceanographic forcing, including winds, waves, tides, and large-scale regional circulation taken from global model outputs. Simulations covered a hindcast period of eight years, allowing the tidal, seasonal, and interannual flow characteristics to be investigated. Results demonstrated that instantaneous current patterns were strongly dominated by the barotropic tide and its spring-neap cycle. However, longer-term transport through Torres Strait was mainly controlled by seasonal winds, which switch from north-westerly monsoon winds in summer to south-easterly trades in winter. Model results were shown to be relatively insensitive to internal model parameters. However, model performance was strongly dependent on the quality of the forcing fields. For example, the prediction of low-frequency inner-shelf currents was improved substantially when temperature and salinity forcing based on the average seasonal climatologies was replaced by that from global model outputs. Uncertainties in the tidal component of the forcing also limited model skill, particularly predictions to the west of Cape York which were strongly dependent on the sealevels imposed along the open boundary in Gulf of Carpentaria.

The Paterson National Geoscience Agreement project is using a number of tools to better understand the time-space evolution of the northwest Paterson Orogen in Western Australia. One of these tools, 3D Geomodeller, is an emerging technology that constructs three-dimensional (3D) volumetric models based on a range of geological information. The Paterson project is using 3D Geomodeller to build geologically-constrained 3D models for the northwest Paterson Orogen. This report documents the model building capability and benefits of 3D Geomodeller and highlights some of the geological insights gained from the model building exercise. The principal benefit of 3D Geomodeller is that it provides geoscientists with a rapid tool for testing multiple working hypotheses. The Cottesloe Syncline district was selected as the focus for a trial of the 3D Geomodeller software. The 3D model was built by members of the Paterson Project, as well as model building specialists within Geoscience Australia. The resultant Cottesloe Syncline model including two dimensional sections, maps and images was exported from 3D GeoModeller and transformed into a Virtual Reality Modelling Language (VRML), enabling a wide audience to view the model using readily available software.

The Fitzoy Estuary is one of several macrotidal estuaries in tropical northern Australia that face ecological change due to agricultural activities in their catchments. The biochemical functioning of such macrotidal estuaries is not well understood in Australia, and there is a pressing need to identify sediment, nutrient and agrochemical pathways, sinks and accumulation rates in these extremely dynamic environments. This is particularly the case in coastal northern Queensland because the impact of water quality changes in rivers resulting from vegetation clearing, changes in land-use and modern agricultural practices are the single greatest threat to the Great Barrier Reef Marine Park. This report includes: 1 Aims and Research questions 2 Study Area 3 Climate and Hydrology 4 Geology 5 Vegetation and land use 6 Methods 7 Sampling strategy 8 Water column observations and samples 9 Bottom sediment properties 10 Core and bottle incubations 11 Data analysis 12 Results 13 Discussion 14 The roll of Keppel Bay in accumulating and redirecting sediment and nutrients from the catchment 15 Sediment biogeochemistry 16 Links between primary production, biogeochemistry and sediment dynamics: A preliminary zonation for Keppel Bay 17 Conclusions

A weathering intensity index (WII) over the Australian continent has been developed at 100 m resolution using regression models based on airborne gamma-ray spectrometry imagery and the Shuttle Radar Topography Mission (SRTM) elevation data. Airborne gamma-ray spectrometry measures the concentration of three radioelements - potassium (K), thorium (Th) and uranium (U) at the Earth's surface. The total gamma-ray flux (dose) is also calculated based on the weighted additions of the three radioelements. Regolith accounts for over 85% of the Australian land area and has a major influence in determining the composition of surface materials and in controlling hydrological and geomorphological processes. The weathering intensity prediction is based on the integration of two regression models. The first uses relief over landscapes with low gamma-ray emissions and the second incorporates radioelement distributions and relief. The application of a stepwise forward multiple regression for the second model generated a weathering intensity index equation of: WII = 6.751 + -0.851*K + -1.319* Relief + 2.682 * Th/K + -2.590 * Dose. The WII has been developed for erosional landscapes but also has the potential to inform on deposition processes and materials. The WII correlates well with site based geochemical indices and existing regolith mapping. Interpretation of the WII from regional to local scales and its application in providing more reliable and spatially explicit information on regolith properties is described.

Machine learning methods, like random forest (RF), have shown their superior performance in various disciplines, but have not been previously applied to the spatial interpolation of environmental variables. In this study, we compared the performance of 23 methods, including RF, support vector machine (SVM), ordinary kriging (OK), inverse distance squared (IDS), and their combinations (i.e., RFOK, RFIDS, SVMOK and SVMIDS), using mud content samples in the southwest Australian margin. We also tested the sensitivity of the combined methods to input variables and the accuracy of averaging predictions of the most accurate methods. The accuracy of the methods was assessed using a 10-fold cross-validation. The spatial patterns of the predictions of the most accurate methods were also visually examined for their validity. This study confirmed the effectiveness of RF, especially its combination with OK or IDS, and also confirmed the sensitivity of RF and its combined methods to the input variables. Averaging the predictions of the most accurate methods showed no significant improvement in the predictive accuracy. Visual examination proved to be an essential step in assessing the spatial predictions. This study has opened an alternative source of methods for spatial interpolation of environmental properties.