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

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).

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

The National Geochemical Survey of Australia (NGSA) is Australia’s first national-scale geochemical survey. It was delivered to the public on 30 June 2011, after almost five years of stakeholder engagement, strategic planning, sample collection, preparation and analysis, quality assurance/quality control, and preliminary data analytics. The project was comprehensively documented in seven initial open-file reports and six data and map sets, followed over the next decade by more than 70 well-cited scientific publications. This review compiles the body of work and knowledge that emanated from the project to-date as an indication of the impact the NGSA had over the decade 2011-2021. The geochemical fabric of Australia as never seen before has been revealed by the NGSA. This has spurred further research and stimulated the mineral exploration industry. This paper also critically looks at operational decisions taken at project time (2007-2011) that were good and perhaps – with the benefit of hindsight – not so good, with the intention of providing experiential advice for any future large-scale geochemical survey of Australia or elsewhere. Strengths of the NGSA included stakeholder engagement, holistic approach to a national survey, involvement of other geoscience agencies, collaboration on quality assurance with international partners, and targeted promotion of results. Weaknesses included gaining successful access to all parts of the nation, and management of sample processing in laboratories. <b>Citation:</b> Patrice de Caritat; The National Geochemical Survey of Australia: review and impact. <i>Geochemistry: Exploration, Environment, Analysis </i>2022;; 22 (4): geochem2022–032. doi: https://doi.org/10.1144/geochem2022-032 This article appears in multiple journals (Lyell Collection & GeoScienceWorld)