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  • 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.

  • 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.

  • This report describes the results of an extended national field spectroscopy campaign designed to validate the Landsat 8 and Sentinel 2 Analysis Ready Data (ARD) surface reflectance (SR) products generated by Digital Earth Australia. Field spectral data from 55 overpass coincident field campaigns have been processed to match the ARD surface reflectances. The results suggest the Landsat 8 SR is validated to within 10%, the Sentinel 2A SR is validated to within 6.5% and Sentinel 2B is validated to within 6.8% . Overall combined Sentinel 2A and 2B are validated within 6.6% and the SR for all three ARD products are validated to within 7.7%.

  • 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

  • Our knowledge of life at the Antarctic sea-bed has increased in the past decades with increasing ship-based surveys and monitoring sites, new technologies and data sharing. However, seafloor habitats and their communities exhibit high spatial variability and heterogeneity that limits our ability to assess the state of the Southern Ocean benthos on larger scales. The seafloor communities that inhabit the Antarctic shelf are often diversity hotspots. These habitats are important in the generation of ‘blue carbon’ and habitat for commercial fish species, for this reason we focus on these habitats. Many Southern Ocean seafloor habitats and their communities seem to be especially vulnerable to certain drivers of change including increasing ocean temperatures, iceberg scour, sea-ice melt, ocean acidification, fishing pressures, pollution and non-indigenous species. Some of the most vulnerable areas include those experiencing rapid regional warming and increased iceberg-scouring e.g. the West Antarctic Peninsula; where human activities and environmental conditions increase the potential for the establishment of non-indigenous species e.g. sub-Antarctic islands and tourist destinations and areas with fishing activities e.g. around South Georgia, Heard and MacDonald Islands. Vulnerable species include calcifying species susceptible to increasing ocean acidity as well as slow-growing habitat forming species that can be damaged by fishing gears e.g. sponges, bryozoan and coral species. Management regimes can protect seafloor habitats and key species from fishing activities but only if they consider specific traits, such as longevity, food availability, their physiological adaptation and rare or common occurrences. Ecosystem-based management practices and long-term protected areas may be the most effective in the preservation of vulnerable seafloor habitats. However, action is needed to reduce carbon emissions to limit the impact of increasing ocean temperatures and ocean acidification. We focus on outlining seafloor responses to drivers of change observed to date and projections for the future. We discuss the need for action to preserve seafloor habitats under climate change and fishing pressures. <b>Citation:</b> Brasier MJ, Barnes D, Bax N, Brandt A, Christianson AB, Constable AJ, Downey R, Figuerola B, Griffiths H, Gutt J, Lockhart S, Morley SA, Post AL, Van de Putte A, Saeedi H, Stark JS, Sumner M and Waller CL (2021) Responses of Southern Ocean Seafloor Habitats and Communities to Global and Local Drivers of Change. <i>Front. Mar. Sci.</i> 8:622721. doi: 10.3389/fmars.2021.622721

  • This animation shows how Magnetotelluric (MT) 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 magnetotelluric (MT) stations and equipment looks like what the equipment measures and how the survey works.

  • Presentation to Australian Research Council (ARC) Training Centre for Data Analytics in Resources and Environment (DARE) Symposium (17 February 2023, University of Sydney) demonstrating use of uncertainty in hydrogeophysical applications as part of the Upper Darling River Floodplain EFTF project.

  • <div>The groundwater and surface water systems associated with the Upper Darling River Floodplain (UDF) in arid northwest New South Wales form part of the Murray-Darling Basin drainage system, which hosts 40% of Australia’s agricultural production. Increasing water use demands and a changing regional climate are affecting hydrological systems, and consequently impacting the quality and quantity of water availability to communities, industries and the environment.</div><div>As part of the Australian Government’s Exploring for the Future program, the UDF project is working in collaboration with State partners to collect and integrate new data and information with existing hydrogeological knowledge. The goal is to provide analyses and products that assist water managers to increase water security in the region, with a focus on groundwater resources. </div><div>As part of this project we are assessing the occurrence of, and geological controls on, potable water resources within the Darling Alluvium (DA), which comprises unconsolidated sediments (<140 m thick) associated with the modern and paleo-Darling River. The DA’s relationship to the underlying Eromanga, Surat (Great Artesian Basin) and Murray basins is also important, particularly in the context of potential groundwater sources or sinks, and connection between low and high quality groundwater resources. At least one major fault system is known to influence groundwater flow paths and control groundwater-surface water interaction.</div><div>Data collection across the project area has commenced, with an airborne electromagnetic (AEM) survey already complete, and new geophysical, hydrochemical and hydrodynamic data being acquired. Preliminary interpretation of the new AEM data in conjunction with existing geological and hydrogeological information has already revealed the major paths and geometries of the paleo-Darling River, given important insights into potential fault controls on groundwater flow paths, and shown variation in the thickness, distribution and character of the DA, which has direct implications for groundwater–surface water connectivity.</div><div><br></div>

  • The Exploring for the Future program Virtual Roadshow was held on 7 July and 14-17 July 2020. The Minerals session of the roadshow was held on 14 July 2020 and consisted of the following presentations: Introduction - Richard Blewett Preamble - Karol Kzarnota Surface & Basins or Cover - Marie-Aude Bonnardot Crust - Kathryn Waltenberg Mantle - Marcus Haynes Zinc on the edge: New insights into sediment-hosted base metals mineral system - David Huston Scale reduction targeting for Iron-Oxide-Copper-Gold in Tennant Creek and Mt Isa - Anthony Schofield and Andrew Clark Economic Fairways and Wrap-up - Karol Czarnota

  • This Murray 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 Murray Basin, a significant sedimentary basin in Australia, displays varying sediment thickness across its expanse, with the thickest layers concentrated in its central regions. The basin's geological evolution is characterised by distinct depositional phases. During the Paleocene to Eocene Renmark Group phase, sedimentary deposits encompass fluvial sands at the base, transitioning into paralic carbonaceous clay and lignite layers. These sediments indicate the shift from riverine to shallow marine environments, dating back to the Paleocene and Eocene periods. The Oligocene to Middle Miocene period encompasses the Ettrick Formation and Murray Group Limestone. The former includes marl, and the latter displays glauconitic grey-green marl and bryozoal limestone, revealing prevailing marine conditions during the Oligocene to Middle Miocene. In the Late Miocene to Early Pliocene Bookpurnong Formation, marine shelly dark grey clay and silt, previously known as the Bookpurnong Beds, coexist with Pliocene fluvial to marginal marine quartz sands (Loxton Sands), marking the transition back to terrestrial and nearshore marine settings. During the Late Pliocene to Pleistocene, the Blanchetown Clay, a substantial unit within Lake Bungunnia, signifies lacustrine phases. Overlying ferricretes in the central/eastern basin and the Norwest Bend Formation's oyster coquinas in the western region, the clay exhibits variable coloration and laminations. Lastly, the Pleistocene to Holocene phase witnesses river-induced reworking and erosion of underlying sediments, giving rise to the Shepparton and Coonambidgal formations. In the western Murray Basin, Cenozoic sedimentary rocks are relatively thin, typically measuring under 200-300 meters. The Renmark Trough area presents a maximum thickness of 600 meters.