A series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with enhanced capabilities including 3D visualisation, and online analysis tools. The User Guide Video complements the help menu in the portal. The User guide is broken into a series of topics 1. Introduction 2. Toolbar 3. Map layers 4. Multiple Layers 5. Background Layers and Sharing 6. 3D Layers 7. Tools 8. Custom Layers The step by step guides were produced by James Cropper.

The values and distribution patterns of the strontium (Sr) isotope ratio 87Sr/86Sr in Earth surface materials is of use in the geological, environmental and social sciences. Ultimately, the 87Sr/86Sr ratio of any mineral or biological material reflects its value in the rock that is the parent material to the local soil and everything that lives in and on it. In Australia, there are few large-scale surveys of 87Sr/86Sr available, and here we report on a new, low-density dataset using 112 catchment outlet (floodplain) sediment samples covering 529,000 km2 of inland southeastern Australia (South Australia, New South Wales, Victoria). The coarse (<2 mm) fraction of bottom sediment samples (depth ~0.6-0.8 m) from the National Geochemical Survey of Australia were fully digested before Sr separation by chromatography and 87Sr/86Sr determination by multicollector-inductively coupled plasma-mass spectrometry. The results show a wide range of 87Sr/86Sr values from a minimum of 0.7089 to a maximum of 0.7511 (range 0.0422). The median 87Sr/86Sr (± robust standard deviation) is 0.7199 (± 0.0112), and the mean (± standard deviation) is 0.7220 (± 0.0106). The spatial patterns of the Sr isoscape observed are described and attributed to various geological sources and processes. Of note are the elevated (radiogenic) values (≥~0.7270; top quartile) contributed by (1) the Palaeozoic sedimentary country rock and (mostly felsic) igneous intrusions of the Lachlan geological region to the east of the study area; (2) the Palaeoproterozoic metamorphic rocks of the central Broken Hill region; both these sources contribute fluvial sediments into the study area; and (3) the Proterozoic to Palaeozoic rocks of the Kanmantoo, Adelaide, Gawler and Painter geological regions to the west of the area; these sources contribute radiogenic material to the region mostly by aeolian processes. Regions of low 87Sr/86Sr (≤~0.7130; bottom quartile) belong mainly to (1) a few central Murray Basin catchments; (2) some Darling Basin catchments in the northeast; and (3) a few Eromanga geological region-influenced catchments in the northwest of the study area. The new spatial dataset is publicly available through the Geoscience Australia portal (https://portal.ga.gov.au/restore/cd686f2d-c87b-41b8-8c4b-ca8af531ae7e).

As part of the Great Artesian Basin (GAB) Project a pilot study was conducted in the northern Surat Basin, Queensland, to test the ability of existing and new geoscientific data and technologies to further improve our understanding of hydrogeological systems within the GAB, in order to support responsible management of basin water resources. This report presents selected examples from the preliminary interpretation of modelled airborne electromagnetic (AEM) data acquired as part of this pilot study. The examples are selected to highlight key observations from the AEM with potential relevance to groundwater recharge and connectivity. Previous investigations in the northern Surat Basin have suggested that diffuse groundwater recharge rates are generally low (in the order of only a few millimetres per year) across large areas of the GAB intake beds—outcropping geological units which represent a pathway for rainfall to enter the aquifers—and that, within key aquifer units, recharge rates and volumes can be heterogeneous. Spatial variability in AEM conductivity responses is identified across different parts of the northern Surat Basin, including within the key Hutton Sandstone aquifer. Consistent with findings from other studies, this variability is interpreted as potential lithological heterogeneity, which may contribute to reduced volumes of groundwater entering the deeper aquifer. The influence of geological structure on aquifer geometry is also examined. Larger structural zones are seen to influence both pre- and post-depositional architecture, including the presence, thickness and dip of hydrogeological units (or parts thereof). Folds and faults within the Surat Basin sequences are, in places, seen as potential groundwater divides which may contribute to compartmentalisation of aquifers. Discrete faults have the potential to influence inter-aquifer connectivity. The examples presented here demonstrate the utility of AEM models, in conjunction with other appropriate geophysical and geological data, for characterising potential recharge areas and pathways within the main GAB aquifer units, by helping to better define aquifer geometry, lithological heterogeneity and possible structural controls. Such assessments have the potential to further improve our understanding of groundwater recharge and flow path variability at local to regional scales. Acquisition of broader AEM data coverage across groundwater recharge areas, along with complementary geophysical, geological and hydrogeological data, would further assist in quantifying recharge variability, facilitating revised water balance estimates for the basin and thereby supporting GAB water resource management and policy decision-making.

To set out how Geoscience Australia will meet its vision for the Exploring for the Future program, we have summarised the ways our scientific activities, outputs and intended outcomes and impacts are linked, using the Impact Pathway diagram.

HiQGA is a general purpose software package for spatial statistical inference, geophysical forward modeling, Bayesian inference and inversion (both deterministic and probabilistic). It includes readily usable geophysical forward operators for airborne electromagnetics (AEM), controlled-source electromagnetics (CSEM) and magnetotellurics (MT). Physics-independent inversion frameworks are provided for probabilistic reversible-jump Markov chain Monte Carlo (rj-MCMC) inversions, with models parametrised by Gaussian processes (Ray and Myer, 2019), as well as deterministic inversions with an "Occam inversion" framework (Constable et al., 1987). In development software for EFTF since 2020

This Carnarvon Basin dataset contains descriptive attribute information for the areas bounded by the relevant spatial groundwater feature in the associated Hydrogeology Index map. Descriptive topics are grouped into the following themes: Location and administration; Demographics; Physical geography; Surface water; Geology; Hydrogeology; Groundwater; Groundwater management and use; Environment; Land use and industry types; and Scientific stimulus. The Carnarvon Basin is a large sedimentary basin covering the western and north-western coast of Western Australia, stretching over 1,000 km from Geraldton to Karratha. It is predominantly offshore, with over 80% of the basin located in water depths of up to 4,500 m. The basin is elongated north to south and connects to the Perth Basin in the south and the offshore Canning Basin in the north-east. It is underlain by Precambrian crystalline basement rocks. The Carnarvon Basin consists of two distinct parts. The southern portion comprises onshore sub-basins with mainly Paleozoic sedimentary rocks extending up to 300 km inland, while the northern section consists of offshore sub-basins containing Mesozoic, Cenozoic, and Paleozoic sequences. The geological evolution of the Southern Carnarvon Basin was shaped by multiple extensional episodes related to the breakup of Gondwana and reactivation of Archean and Proterozoic structures. The collision between Australia and Eurasia in the Mid-Miocene caused significant fault reactivation and inversion. The onshore region experienced arid conditions, leading to the formation of calcrete, followed by alluvial and eolian deposition and continued calcareous deposition offshore. The Northern Carnarvon Basin contains up to 15,000 m of sedimentary infill, primarily composed of siliciclastic deltaic to marine sediments from the Triassic to Early Cretaceous and shelf carbonates from the Mid-Cretaceous to Cenozoic. The basin is a significant hydrocarbon province, with most of the resources found within Upper Triassic, Jurassic, and Lower Cretaceous sandstone reservoirs. The basin's development occurred during four successive periods of extension and thermal subsidence, resulting in the formation of various sub-basins and structural highs. Overall, the Carnarvon Basin is a geologically complex region with a rich sedimentary history and significant hydrocarbon resources. Exploration drilling has been ongoing since 1953, with numerous wells drilled to unlock its hydrocarbon potential.

This South Australian Gulf and Yorke Cenozoic Basins dataset contains descriptive attribute information for the areas bounded by the relevant spatial groundwater feature in the associated Hydrogeology Index map. Descriptive topics are grouped into the following themes: Location and administration; Demographics; Physical geography; Surface water; Geology; Hydrogeology; Groundwater; Groundwater management and use; Environment; Land use and industry types; and Scientific stimulus. The South Australian Gulf and Yorke Cenozoic basins consist of eleven separate basins with similar sediments. These relatively small to moderate-sized basins overlies older rocks from the Permian, Cambrian, or Precambrian periods and are often bounded by north-trending faults or basement highs. The largest basins, Torrens, Pirie, and Saint Vincent, share boundaries. The Torrens and Pirie basins are fault-bounded structural depressions linked to the Torrens Hinge Zone, while the Saint Vincent basin is a fault-bounded intra-cratonic graben. Smaller isolated basins include Carribie and Para Wurlie near the Yorke Peninsula, and Willochra and Walloway in the southern Flinders Ranges. The Barossa Basin, Hindmarsh Tiers, Myponga, and Meadows basins are in the Adelaide region. These basins resulted from tectonic movements during the Eocene Australian-Antarctic separation, with many forming in the late Oligocene. Sediment deposition occurred during the Oligocene to Holocene, with various environments influenced by marine transgressions and regressions. The well-studied Saint Vincent Basin contains diverse sediments deposited in fluvial, alluvial, deltaic, swamp, marine, littoral, beach, and colluvial settings, with over 30 major shoreline migrations. Eocene deposition formed fluvio-deltaic lignite and sand deposits, before transitioning to deeper marine settings. The Oligocene and Miocene saw limestone, calcarenite, and clay deposition, overlain by Pliocene marine sands and limestones. The uppermost sequences include interbedded Pliocene to Pleistocene limestone, sand, gravel, and clay, as well as Pleistocene clay with minor sand lenses, and Holocene to modern coastal deposits. The sediment thickness varies from less than 50 m to approximately 600 m, with the Saint Vincent Basin having the most substantial infill. Some basins were previously connected to the Saint Vincent Basin's marine depositional systems but later separated due to tectonic movements.

This report presents geoscientific advice for the management of Antarctic Specially Protected Area (ASPA) No. 143, Marine Plain in the Vestfold Hills, East Antarctica. The advice is based on expert field observations and Remotely Piloted Aircraft (RPA) imagery of the ASPA as well as a review of observations and reports from previous visitors and scientific literature on human disturbance in polar environments. This report builds on an earlier report (McLennan 2017) which was written prior to any site visits by Geoscience Australia scientists. The advice addresses questions raised by the Australian Antarctic Division regarding the ASPA management plan, particularly relating to access via foot and helicopter, and the condition of two fossil sites. Key assumptions include that the rate of visitors to Marine Plain in the next decade will remain low and that the remaining faunal fossil specimens will stay in place. If there is a large increase in visitor numbers to Marine Plain or the fossil fauna are intended to be removed, further advice should be sought about the impacts to Marine Plain values.

The AEM method measures regolith and rocks' bulk subsurface electrical conductivity, typically to a depth of several hundred meters. AEM survey data is widely used in Australia for mineral exploration (i.e. mapping undercover and detection of mineralisation), groundwater assessment (i.e. hydro-stratigraphy and water quality) and natural resource management (i.e. salinity assessment). Geoscience Australia (GA) has flown Large regional AEM surveys over Northern Australia, including Queensland, Northern Territory and Western Australia. The surveys were flown nominally at 20-kilometre line spacing, using the airborne electromagnetic systems that have signed technical deeds of staging with GA to ensure they can be modelled quantitatively. Geoscience Australia commissioned the survey as part of the Exploring for the Future (EFTF) program. The EFTF program is led by Geoscience Australia (GA), in collaboration with the Geological Surveys of the Northern Territory, Queensland, South Australia and Western Australia, and is investigating the potential mineral, energy and groundwater resources in northern Australia and South Australia. We have used a machine learning modelling approach that establishes predictive relationships between the inverted flight-line modelled conductivity with a suite of national environmental and geological covariates. These covariates include terrain derivatives, gamma-ray radiometric, geological maps, climate derived surfaces and satellite imagery. Conductivity-depth values were derived from a single model using GA's deterministic 1D smooth-30-layer layered-earth-inversion algorithm. (Brodie and Richardson 2015). Three conductivity depth interval predictions are generated to interpolate the actual modelled conductivity data, which is 20km apart. These depth slices include a 0-50cm, 9-11m and 22-27m depth prediction. Each depth interval was modelled and individually optimised using the gradient boosted tree algorithm. The training cross-validation step used label clusters or groups to minimise over-fitting. Many hundreds of conductivity models are generated (i.e. ensemble modelling). Here we use the median of the models as the conductivity prediction and the upper and lower percentiles (95th and 5th) to measure model uncertainty. Grids show conductivity (S/m) in log 10 units. Reported out-of-sample r-squares for each interval in order of increasing depth are 0.74, 0.64, and 0.67. A decline in model performance with increasing depth was expected due to the decrease in suitable covariates at greater depths. Modelled conductivities seem to be consistent with the geological, regolith, geomorphological, and climate processes in the study area. The conductivity grids are at the resolution of the covariates, which have a nominal pixel size of 85 meters. Datasets in this data package include; 1. 0-50cm depth interval 0_50cm_median.tif; 0_50_upper.tif; 0_50_lower.tif 2. 9-11m depth interval 9_11m_median.tif; 9_11m_upper.tif; 9_11m_lower.tif 3. 22-27m depth interval 22_27_median.tif; 22_27_upper.tif; 22_27_lower.tif 4. Covariate shift; Cov_shift.tif (higher values = great shift in covariates) Reference: Ross C Brodie & Murray Richardson (2015) Open Source Software for 1D Airborne Electromagnetic Inversion, ASEG Extended Abstracts, 2015:1, 1-3, DOI: 10.1071/ ASEG2015ab197

Background It is important to know where water is normally present in a landscape, where water is rarely observed, and where inundation has occasionally occurred. These observations tell us where flooding has occurred in the past, and allows us to understand wetlands, water connectivity and surface-groundwater relationships. This can lead to more effective emergency management and risk assessment. This is the principal Digital Earth Australia (DEA) Water product (previously known as Water Observations from Space (WOfS)), providing the individual water observations per satellite image that are subsequently used in the following DEA Watersuite and related water bodies products: DEA Waterbodies (Landsat), DEA Water Observations Statistics (Landsat), DEA Water Observations Filtered Statistics (Landsat). This product shows where surface water was observed by the Landsat satellites on any particular day since mid 1986. These daily data layers are termed Water Observations (WOs). What this product offers DEA Water Observations provides surface water observations derived from Landsat satellite imagery for all of Australia from 1986 to present. The Water Observationsshow the extent of water in a corresponding Landsat scene, along with the degree to which the scene was obscured by clouds, shadows or where sensor problems cause parts of a scene to not be observable.