Plutonium (Pu) interactions in the environment are highly complex. Site-specific variables play an integral role in determining the chemical and physical form of Pu, and its migration, bioavailability, and immobility. This paper aims to identify the key variables that can be used to highlight regions of radioecological sensitivity and guide remediation strategies in Australia. Plutonium is present in the Australian environment as a result of global fallout and the British nuclear testing program of 1952 – 1958 in central and west Australia (Maralinga and Monte Bello islands). We report the first systematic measurements of 239+240Pu and 238Pu activity concentrations in distal (≥1,000 km from test sites) catchment outlet sediments from Queensland, Australia. The average 239+240Pu activity concentration was 0.29 mBq.g -1 (n = 73 samples) with a maximum of 4.88 mBq.g -1. 238Pu/239+240Pu isotope ratios identified a large range (0.02 – 0.29 (RSD: 74%)) which is congruent with the heterogeneous nuclear material used for the British nuclear testing programme at Maralinga and Montebello Islands. The use of a modified PCA relying on non-linear distance correlation (dCorr) provided broader insight into the impact of environmental variables on the transport and migration of Pu in this soil system. Primary key environmental indicators of Pu presence were determined to be actinide/lanthanide/heavier transition metals, elevation, electrical conductivity (EC), CaO, SiO2, SO3, landform, geomorphology, land use, and climate explaining 81.7% of the variance of the system. Overall this highlighted that trace level Pu accumulations are associated with the coarse, refractive components of Australian soils, and are more likely regulated by the climate of the region and overall soil type. <b>Citation:</b> Megan Cook, Patrice de Caritat, Ross Kleinschmidt, Joёl Brugger, Vanessa NL. Wong, Future migration: Key environmental indicators of Pu accumulation in terrestrial sediments of Queensland, Australia,<i> Journal of Environmental Radioactivity</i>, Volumes 223–224, 2020, 106398,ISSN 0265-931X, https://doi.org/10.1016/j.jenvrad.2020.106398

This Carpentaria 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 Carpentaria Basin is a vast intra-cratonic sedimentary basin situated on and offshore in north-eastern Australia, covering around 550,000 square kilometres across Queensland and the Northern Territory. It comprises predominantly sandstone-rich rock units deposited during sea level highs from the Late Jurassic to Mid Cretaceous. The basin overlies a heterogeneous Proterozoic basement and is separated from contemporaneous sedimentary structures by basement highs and inliers. Four main depocentres within the larger Carpentaria Basin form four major sub-basins: the Western Gulf Sub-basin, Staaten Sub-basin, Weipa Sub-basin, and Boomara Sub-basin. While the basin is extensive and continuous in Queensland, it becomes more heterogeneous and discontinuous in the Northern Territory. Remnants of the basin's stratigraphy, referred to as the Dunmarra Basin, are found along the Northern Territory coast and inland. The depositional history commenced during the Jurassic with down warping near Cape York Peninsula, resulting in the Helby beds and Albany Pass beds' concurrent deposition. The basin experienced marine transgressions during the Cretaceous, with the Gilbert River Formation widespread and the Wallumbilla Formation occurring during sea level highs. The Carpentaria Basin's strata are relatively undeformed and unmetamorphosed. The Northern Territory sequence displays slightly different stratigraphy, limited to the height of the Aptian marine transgression above the Georgina Basin. The Walker River Formation and Yirrkala Formation represent key units in this area, outcropping as tablelands and mesas largely unaffected by tectonism.

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

This animation shows how groundwater sampling is conducted. It is part of a series of Field Activity Technique Engagement Animations. The target audience are the communities that are impacted by GA's data acquisition activities. There is no sound or voice over. The 2D animation includes a simplified view of what groundwater sampling equipment looks like, what the equipment measures and how scientists use the data.

This animation shows how Surface Magnetic Resonance (SMR) Surveys are conducted. It is part of a series of Field Activity Technique Engagement Animations. The target audience are the communities that are impacted by GA's data acquisition activities. There is no sound or voice over. The 2D animation includes a simplified view of what SMR equipment looks like, what the equipment measures and how scientists use the data.

The Great Artesian Basin (GAB) covers one fifth of Australia and is the largest groundwater ‘basin’ on the continent. Groundwater from the GAB is a vital resource for pastoral, agricultural and extractive industries, underpinning at least $12.8 billion in economic activity annually, as well as providing town water supplies and supporting environmental and cultural values. The Australian Government, through the National Water Infrastructure Development Fund – Expansion, commissioned Geoscience Australia to undertake the project ‘Assessing the Status of Groundwater in the Great Artesian Basin’. A key deliverable of this project is a water balance (for 2019) encompassing the main aquifers of the GAB. To facilitate this outcome, a range of tools and techniques to assist in the development of improved hydrogeological conceptualisations of the GAB have been developed and assessed. This report presents the results of investigations from a pilot study area in the northern Surat Basin, Queensland, with components of the work extending into the wider GAB. The results demonstrate that the application of existing and new geoscientific data and technologies has the potential to further improve our understanding of the GAB hydrogeological system thus supporting the responsible management of basin water resources. Groundwater recharge potential within the GAB intake beds has been investigated using techniques that consider variations in physical and environmental characteristics. Empirical modelling assessing deep drainage as a recharge proxy suggests that, with isolated exceptions, diffuse recharge potential is generally low across most of the study area. The spatial variability in recharge potential can assist in the interpretation and/or interpolation of estimates derived from other techniques, such as chloride mass balance. The results of machine learning modelling suggest that further work is needed to better constrain uncertainty in input and training datasets, and in the development of robust translations of outputs to hydrogeologically meaningful products. The chloride mass balance (CMB) method remains the most appropriate tool for estimating long-term mean gross recharge to GAB aquifers in the northern Surat Basin. New upscaling methods provide significant improvements for mapping regional scale groundwater recharge rates and quantifying uncertainties associated with these estimates. Application of multiple techniques to the assessment of groundwater flow and recharge processes is necessary to complement CMB recharge estimates, and reduce associated uncertainty. Analysis of groundwater environmental tracers are recommended for constraining CMB recharge rates. Integrated geological assessments using airborne electromagnetic data in conjunction with other geophysical and geological data (e.g., reflection seismic, wells) are effective at characterising aquifer architecture to better understand geometry, flow pathways and structural controls relevant to recharge and connectivity at local to regional scales. Significant effort has gone into updating the regional geological framework at the whole-of-GAB scale, combining legacy and new data with recent knowledge to revise the hydrogeological conceptualisation of the GAB. This assists in constraining interpretations of regional depositional architecture and lithological heterogeneity within hydrogeological units, particularly those properties that influence groundwater storage and flux. Assessment of lateral and vertical heterogeneity of hydraulic properties within and between aquifers and aquitards in the northern Surat Basin has refined our understanding of potential groundwater connectivity and compartmentalisation. This study provides an improved hydrogeological framework to support revised water balance estimates for the GAB, and insights into potential recharge variability that may impact those input components. Targeted examples from the northern Surat Basin demonstrate the application of the techniques and tools employed, including methods to reduce uncertainty. The outcomes of this work underpin a revised hydrogeological conceptualisation for the GAB, a standardised basis for establishing future investigations, and a framework for more informed water management decision-making.

This brief report updates the ‘Two-part Seabed Geomorphology classification scheme’ of Dove et al. (2016) and presents a new glossary (Part 1) of Seabed Morphology features. This Morphology glossary is intended to provide marine scientists with an accurate and robust way to characterise the seabed. Each glossary entry includes a feature definition and a representative schematic diagram to support clear and consistent classification. Feature terms and definitions are primarily drawn from the IHO guide for undersea feature names, which are herein modified and augmented with additional terms to ensure the final feature catalogue and glossary encompasses the diversity of morphologies observed at the seabed, while also minimising duplication and/or ambiguity. This updated classification system and new glossary are the result of a collaboration between marine geoscientists from marine mapping programmes/networks in Norway (MAREANO), Ireland (INFOMAR), UK (MAREMAP), and Australia (Geoscience Australia) (MIM-GA). A subsequent report will present the (Part 2) Geomorphology feature glossary. <b>Citation:</b> Dove, Dayton, Nanson, Rachel, Bjarnadóttir, Lilja R., Guinan, Janine, Gafeira, Joana, Post, Alix, Dolan, Margaret F.J., Stewart, Heather, Arosio, Riccardo, & Scott, Gill. (2020). <i>A two-part Seabed Geomorphology classification scheme (v.2); Part 1: Morphology Features Glossary.</i> Zenodo. https://doi.org/10.5281/zenodo.4071939

This flythrough highlights shallow and mesophotic seabed environments of Elizabeth and Middleton Reefs, located within the Lord Howe Marine Park. These reefs are unique because they are the southern-most platform reefs in the world and host a diverse range of tropical, sub-tropical and temperate marine species. High-resolution multibeam bathymetry data and seafloor imagery used in this flythrough was acquired by the Marine Biodiversity Hub, during the period 31 January to 6 February 2020 on board the Australian Maritime College vessel, TV Bluefin. Participating agencies included Geoscience Australia, the Institute for Marine and Antarctic Studies (University of Tasmania), the Australian Centre for Field Robotics (University of Sydney) through their involvement with the Integrated Marine Observing System (IMOS), NSW Department of Primary Industries and Parks Australia. The specific aim of the survey was to fill knowledge gaps on the distribution, extent and structure of seabed habitats and associated sessile and mobile fauna in the lagoon and mesophotic shelves of Elizabeth (Recreational Use Zone) and Middleton (National Park Zone) Reefs, using a suite of national standard survey tools and best practice sampling procedures. Data acquisition for the project included seabed mapping using multibeam sonar (Kongsberg EM 2040C HD, 300 kHz), seabed imagery acquisition by Autonomous Underwater Vehicles (AUV Sirius and AUV Nimbus), sediment samples, and imagery of demersal fish communities by stereo-baited remote underwater videos (stereo-BRUVs). This work was undertaken by the Marine Biodiversity Hub, a collaborative partnership supported through funding from the Australian Government’s National Environmental Science Program (NESP), and Parks Australia. AUV data was sourced from Australia’s Integrated Marine Observing System (IMOS) – IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). It is operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent. This multimedia product is published with the permission of the CEO, Geoscience Australia.

This report presents key results from hydrogeological investigations in the Tennant Creek region, completed as part of Exploring for the Future (EFTF)—an eight year, $225 million Australian Government funded geoscience data and information acquisition program focused on better understanding the potential mineral, energy and groundwater resources across Australia. The EFTF Southern Stuart Corridor (SSC) Project area is located in the Northern Territory and extends in a north–south corridor from Tennant Creek to Alice Springs, encompassing four water control districts and a number of remote communities. Water allocation planning and agricultural expansion in the SSC is limited by a paucity of data and information regarding the volume and extent of groundwater resources and groundwater systems more generally. Geoscience Australia, in partnership with the Northern Territory Department of Environment and Natural Resources and Power and Water Corporation, undertook an extensive program of hydrogeological investigations in the SSC Project area between 2017 and 2019. Data acquisition included; helicopter airborne electromagnetic (AEM) and magnetic data; water bore drilling; ground-based and downhole geophysical data for mapping water content and defining geological formations; hydrochemistry for characterising groundwater systems; and landscape assessment to identify potential managed aquifer recharge (MAR) targets. This report focuses on the Tennant Creek region—part of the Barkly region of the Northern Territory. Investigations in this region utilised existing geological and geophysical data and information, which were applied in the interpretation and integration of AEM and ground-based geophysical data, as well as existing and newly acquired groundwater hydrochemical and isotope data. The AEM and borehole lithological data reveal the highly weathered (decomposed) nature of the geology, which is reflected in the hydrochemistry. These data offer revised parameters, such as lower bulk electrical conductivity values and increased potential aquifer volumes, for improved modelling of local groundwater systems. In many instances the groundwater is shown to be young and of relatively good quality (salinity generally <1000 mg/L total dissolved solids), with evidence that parts of the system are rapidly recharged by large rainfall events. The exception to this is in the Wiso Basin to the west of Tennant Creek. Here lower quality groundwater occurs extensively in the upper 100 m below ground level, but this may sit above potentially potable groundwater and that possibility should be investigated further. Faults are demonstrated to have significantly influenced the occurrence and distribution of weathered rocks and of groundwater, with implications for groundwater storage and movement. Previously unrecognised faults in the existing borefield areas should be investigated for their potential role in compartmentalising groundwater. Additionally a previously unrecognised sub-basin proximal to Tennant Creek may have potential as a groundwater resource or a target for MAR. This study has improved understanding of the quantity and character of existing groundwater resources in the region and identified a managed aquifer recharge target and potential new groundwater resources. The outcomes of the study support informed water management decisions and improved water security for communities; providing a basis for future economic investment and protection of environmental and cultural values in the Tennant Creek and broader Barkly region. Data and information related to the project are summarised in the conclusions of this report and are accessible via the EFTF portal (https://portal.ga.gov.au/).

This animation shows how passive seismic surveys Work. It is part of a series of Field Activity Technique Engagement Animations. The target audience are the communities that are impacted by our data acquisition activities. There is no sound or voice over. The 2D animation includes a simplified view of what passive seismic equipment looks like, what the equipment measures and how the survey works.