The product consists of 8,800 line kilometres of time‐domain airborne electromagnetic (AEM) geophysical data acquired over the far north part of South Australia known as the Musgrave Province. This product release includes: a) the measured AEM point located data, b) electrical conductivity depth images derived from the dataset, and c) the acquisition and processing report. The data were acquired using the airborne SkyTEM312 Dual Moment 275Hz/25Hz electromagnetic and magnetic system, which covered a survey area of ~14,000 km2, which includes the standard 1:250 000 map sheets of SG52-12 (Woodroffe), SG52-16 (Lindsay), SG53-09 (Alberga) and SG53-13 (Everard). The survey lines where oriented N-S and flown at 2km, 500m and 250m line spacing. A locality diagram for the survey is shown in Figure 1. This survey was funded by the Government of South Australia, as part of the Plan for Accelerating Exploration (PACE) Copper Initiative, through the Department of the Premier and Cabinet, (DPC) and the Goyder Institute of Water Research. Geoscience Australia managed the survey as part of a National Collaborative Framework project agreement with SA. The principal objective of this project was to capture a baseline geoscientific dataset to provide further information on the geological context and setting of the area for mineral systems as well as potential for groundwater resources, of the central part of the South Australian Musgrave Province. Geoscience Australia contracted SkyTEM (Australia) Pty. Ltd. to acquire SkyTEM312 electromagnetic data, between September and October 2016. The data were processed and inverted by SkyTEM using the AarhusInv inversion program (Auken et al., 2015) and the Aarhus Workbench Laterally Constrained Inversion (LCI) algorithm (Auken et al. 2005; Auken et al. 2002). The LCI code was run in multi-layer, smooth-model mode. In this mode the layer thicknesses are kept fixed and the data are inverted only for the resistivity of each layer. For this survey a 30 layer model was used. The thickness of the topmost layer was set to 2 m and the depth to the top of the bottommost (half-space) layer was set to 600 m. The layer thicknesses increase logarithmically with depth. The thicknesses and depths to the top of each layer are given in Table 1. The regional AEM survey data can be used to inform the distribution of cover sequences, and at a reconnaissance scale, trends in regolith thickness and variability, variations in bedrock conductivity, and conductivity values of key bedrock (lithology related) conductive units under cover. The data will also assist in assessing groundwater resource potential and the extent of palaeovalley systems known to exist in the Musgrave Province. A considerable area of the survey data has a small amplitude response due to resistive ground. It very soon becomes evident that lack of signal translates to erratic non-monotonic decays, quite opposite to the smooth transitional exponential decays that occur in conductive ground. Some sections of the data have been flown over what appears to be chargeable ground, hence contain what potentially can be identified as an Induced Polarization effect (airborne IP—AIP). For decades these decay sign changes, which characterize AIP, have not been accounted for in conventional AEM data processing and modelling (Viezzoli et al., 2017). Instead they have mostly been regarded as noise, calibration or levelling issues and are dealt with by smoothing, culling or applying DC shifts to the data. Not accounting for these effects is notable on the contractor’s conductivity-depth sections, where data can’t be modelled to fit the data hence large areas of blank-space have been used to substitute the conductivity structure. The selection of the survey area was undertaken through a consultative process involving the CSIRO, GOYDER Institute, Geological Survey of South Australia and the exploration companies currently active in the region (including industry survey partner PepinNini Minerals Ltd). The data will be available from Geoscience Australia’s web site free of charge. It will also be available through the South Australian Government’s SARIG website at https://map.sarig.sa.gov.au. The data will feed into the precompetitive exploration workflow developed and executed by the Geological Survey of South Australia (GSSA) and inform a new suite of value-added products directed at the exploration community.

Exploring for the Future (EFTF) is a four-year geoscience data and information collection programme that aims to better understand on a regional scale the potential mineral, energy and groundwater resources concealed under cover in northern Australia and parts of South Australia. This factsheet explains one of the activities being undertaken to collect this data and information.

The Minister for Resources and Northern Australia, Senator the Hon Matthew Canavan, formally released the 2016 offshore areas for petroleum exploration on insert date here. The 28 areas are located on the North West Shelf in the Bonaparte, Browse, Roebuck, offshore Canning and Northern Carnarvon basins (Figure 1). Competitive work-program bidding for exploration permits will apply, except for three selected areas which are released under the cash-bidding scheme. These are located in the inboard part of the Northern Carnarvon Basin, where existing hydrocarbon discoveries are currently in production and where complete coverage of 3D-seismic data exists.

Geoscience Australia Flight Line Diagrams Catalogue Archive

The data covers an area of approximately 8500 sq km in the Darling river catchment area, located between Bourke, NSW and Wilcannia, NSW. A set of seamless products were produced including hydro-flattened bare earth DEMs, DSMs, Canopy Height Models (CHM) and Foliage Cover Models (FCM). The outputs of the project are compliant with National ICSM LiDAR Product Specifications and the NEDF.

Large tsunami occur infrequently but can be extremely destructive to human life and the built environment. Management of these risks requires an understanding of the possible sizes of future tsunami, and the probability that they will occur over some time interval of interest. Herein we present a globally extensive probabilistic assessment of tsunami runup hazards, considering only earthquake sources as these have been responsible for about 80% of destructive tsunami globally. The global scale of the analysis prevents us from exploiting detailed site specific data (e.g. high-resolution elevation data, tsunami observations), and because of this we do not suggest the analysis is appropriate for local decision making. However, consistent global analyses are useful to inform international disaster risk reduction initiatives, and can also serve as a reference and potential source of boundary conditions for regional and local tsunami hazard assessments. A global synthetic catalogue of 17000 tsunamigenic earthquake events is developed with magnitudes ranging from 7.5 to 9.6. The geometry of the earthquake sources accounts for the detailed three-dimensional shape of subduction interfaces, when the latter is well constrained. The rate of earthquake events is modelled such that on each earthquake source zone, the earthquakes follow a Gutenberg-Richter magnitude-frequency distribution, and the time-integrated earthquake slip balances the seismic moment release rate inferred from the convergence of neighbouring tectonic plates. Tsunami propagation from each earthquake is modelled globally, and runup height is estimated roughly by combining the global model with heuristic treatments of nearshore tsunami amplification. We evaluate the accuracy of this approach by comparing runup observations from four globally significant historical tsunami with model scenarios having the same earthquake magnitude and location (i.e. without event-specific calibration). Around 50% of runup observations are within a factor of two of the model predictions. The dominant source of uncertainty in the modelled runup seems related to limitations in the earthquake source representation, with limitations due to the global runup methodology being a significant but secondary issue. These uncertainties are modelled statistically, and integrated into the hazard computations. In most locations, the modelled tsunami runup exceedance rate is sensitive to assumptions about the maximum possible earthquake magnitude on nearby earthquake source zones, and the fraction of plate convergence accommodated by non-seismic processes. We model the uncertainties of these (typically) poorly constrained processes using a logic-tree. For any site and chosen exceedance rate, this allows the mean runup (integrated over all logic tree branches) to be estimated, and associated runup confidence intervals to be derived. As well as highlighting the uncertainties in tsunami hazard, the analysis suggests relatively high hazard around most of the Pacific Rim, especially on the east coast of Japan and the west coast of South America, and relatively low hazard around most of the Atlantic outside of the Caribbean. Runup hazards on the east and west coast of Australia are relatively poorly constrained, because there are large uncertainties in the maximum magnitude earthquake which could occur on key source zones in the eastern Indian Ocean and western Pacific.

The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by UNISDR and GFDRR. We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models and the use of aleatory variability and epistemic uncertainty, and preliminary results for a global hazard assessment which is an update of that included in UNIDSDR GAR15.

Exploring for the Future (EFTF) is a four-year geoscience data and information collection programme that aims to better understand on a regional scale the potential mineral, energy and groundwater resources that are concealed under cover in northern Australia and parts of South Australia. This factsheet explains one of the activities being undertaken to collect this data and information.

Exploring for the Future (EFTF) is a four-year geoscience data and information collection programme that aims to better understand on a regional scale the potential mineral, energy and groundwater resources concealed under cover in northern Australia and parts of South Australia. This factsheet explains one of the activities being undertaken to collect this data and information.

The ACT Elevation Acquisition 2015 is a highly accurate airborne LiDAR dataset, to be used to accurately model the impacts of climate change, disaster management, water security, environmental management, urban planning and infrastructure design. The full dataset covers the entire state of the ACT with a density of 4 pulses per square metre, and the Canberra's City Center at 8 pulses per square metre. LiDAR is classified to ICSM specification Level 3 (for ground) and delivered as LAS v1.4 in both ellipsoidal and othormetric formats. In addition, full waveform datasets have been provided for a small region within the 8 pulses per square metre area of interest. The outputs of the project are compliant with National ICSM LiDAR Product Specifications and the NEDF. The classification scheme is as follows: Unclassified (1), Ground (2), low vegetation (0-0.3m : 3), medium vegetation (0.3-2m : 4), high vegetation (>2m : 5), buildings (6), low noise (7), water (9), bridge (17), and high noise (18). The full waveform LiDAR dataset provides up to 7 returns per pulse depending upon the complexity of the features on the ground. This dataset defines the classified Australian Height Datum (AHD) LiDAR dataset for the full ACT region minus Canberra's City Center at 4 pulses per square metre.