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    Total magnetic intensity (TMI) data measures variations in the intensity of the Earth's magnetic field caused by the contrasting content of rock-forming minerals in the Earth crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The data are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. These line dataset from the Murrindal, Vic, 1996 VIMP Survey (GSV3060) survey were acquired in 1995 by the VIC Government, and consisted of 15589 line-kilometres of data at 200m line spacing and 80m terrain clearance. To constrain long wavelengths in the data, an independent data set, the Australia-wide Airborne Geophysical Survey (AWAGS) airborne magnetic data, was used to control the base levels of the survey data. This survey data is essentially levelled to AWAGS.

  • We collected 38 groundwater and two surface water samples in the semi-arid Lake Woods region of the Northern Territory to better understand the hydrogeochemistry of this system, which straddles the Wiso, Tennant Creek and Georgina geological regions. Lake Woods is presently a losing waterbody feeding the underlying groundwater system. The main aquifers comprise mainly carbonate (limestone and dolostone), siliciclastic (sandstone and siltstone) and evaporitic units. The water composition was determined in terms of bulk properties (pH, electrical conductivity, temperature, dissolved oxygen, redox potential), 40 major, minor and trace elements as well as six isotopes (δ18Owater, δ2Hwater, δ13CDIC, δ34SSO4=, δ18OSO4=, 87Sr/86Sr). The groundwater is recharged through infiltration in the catchment from monsoonal rainfall (annual average rainfall ~600 mm) and runoff. It evolves geochemically mainly through evapotranspiration and water–mineral interaction (dissolution of carbonates, silicates, and to a lesser extent sulfates). The two surface waters (one from the main creek feeding the lake, the other from the lake itself) are extraordinarily enriched in 18O and 2H isotopes (δ18O of +10.9 and +16.4 ‰ VSMOW, and δ2H of +41 and +93 ‰ VSMOW, respectively), which is interpreted to reflect evaporation during the dry season (annual average evaporation ~3000 mm) under low humidity conditions (annual average relative humidity ~40 %). This interpretation is supported by modelling results. The potassium (K) relative enrichment (K/Cl mass ratio over 50 times that of sea water) is similar to that observed in salt-lake systems worldwide that are prospective for potash resources. Potassium enrichment is believed to derive partly from dust during atmospheric transport/deposition, but mostly from weathering of K-silicates in the aquifer materials (and possibly underlying formations). Further studies of Australian salt-lake systems are required to reach evidence-based conclusions on their mineral potential for potash, lithium, boron and other low-temperature mineral system commodities such as uranium. <b>Citation:</b> P. de Caritat, E. N. Bastrakov, S. Jaireth, P. M. English, J. D. A. Clarke, T. P. Mernagh, A. S. Wygralak, H. E. Dulfer & J. Trafford (2019) Groundwater geochemistry, hydrogeology and potash mineral potential of the Lake Woods region, Northern Territory, Australia, <i>Australian Journal of Earth Sciences</i>, 66:3, 411-430, DOI: 10.1080/08120099.2018.1543208

  • Geochemical surveys deliver fundamental data, information and knowledge about the concentration and spatial distribution of chemical elements, isotopes and compounds in the natural environment. Typically near-surface sampling media, such as soil, sediment, outcropping rocks and stream or groundwater, are used. The application of such datasets to fields such as mineral exploration, environmental management, and geomedicine has been widely documented. In this presentation I reflect on a sabbatical experience with the Australian Federal Police (AFP) in 2017-2018 that allowed me to extend the interpretation of geochemical survey data beyond these established applications. In particular, with my collaborators we explore ways in which geochemical survey data and maps can be used to indicate the provenance of an evidentiary sample collected at a crime scene or obtained for instance from items belonging to a suspect intercepted at border entry. Because soils are extremely diverse mineralogically, geochemically and biologically, it should theoretically be possible to exclude very large swathes of territory (>90%) from further provenancing investigation using soil data. In a collaboration between Geoscience Australia (GA), the AFP and the University of Canberra (UC), a recent geochemical survey of the urban/suburban Canberra region in southeastern Australia is being used as a testbed for developing different approaches to forensic applications of geochemical surveys. A predictive soil provenancing method at the national scale was also developed and tested for application where no actual detailed, fit-for-purpose geochemical survey data exist. Over the next few years, GA, AFP and UC are collaborating with Flinders University to add biome data from soil and soil-derived dust to further improve the provenancing technique. This Abstract was presented at the 2021 Goldschmidt Conference (https://conf.goldschmidt.info/goldschmidt/2021/meetingapp.cgi)

  • To deliver open data, government agencies must deal with legacy processes, both social and technical, that contain barriers to openness. These barriers limit the true usability of open data - how it can be used over time and in multiple contexts - and are critical to address as governments seek to expose open data. Linked Data (LD) has always been, at its core, about ensuring the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable) by focusing on the identity and relationship of entities and exposing their context to consumers of data, even if these principles have only recently been named FAIR. A fundamental component of LD is that entities are identified by sustainable URI references called Persistent Identifiers (PIDs) which retain their utility over time despite system and organisation change. This poster will show how Geoscience Australia (GA) is applying the use of LD & PIDS in a real world, production IT, setting. Long running operational processes have been incrementally advanced to deliver data from relational databases as LD. Policies, practices and tools have developed and applied to support these LD delivery. The key components are: Data transformation tools: reliant on a robust internal data schema, the Corporate Data Model, these tools export views of it as XML or CSV publicly which is then converted to RDF in another step Overarching data model: a Semantic Web ontology that outlines the types of entities delivered publicly by GA and their macro relations. To date, public entities are Datasets, Web Services, vocabulary terms and geological Samples, Sites Surveys and Stratigraphic Units. New objects will include images with multiple formats and resolutions PID service: an application that manages a series of PID redirection rules PID governance policy: the defined process to support the agency with its multiple teams and their different data sources to have consistent application of entity identification rules and ensure uniqueness across multiple systems in the same registers pyLDAPI data service tools: a Web API tool that can present LD endpoints for entities according to given ontologies Cloud infrastructure as code (infracode): Provisioning of LD data holding RDF triple stores on the public cloud following agency best practice in delivering scalable solutions. The tools used are Apache’s Jena/Fuseki triplestore and API deployed on Amazon Web Services (AWS) with scalability through AWS Elastic Load Balancer and Elastic File Store components. Further work will explore suitability of the new triple store on AWS Neptune.

  • This poster will present on the tools and their implementation for structured linked data at Geoscience Australia (GA). The datasets include: samples, sites, surveys, placenames. The goal is to have persistent identifiers and their profiles is governed through organisational policy with entities and relationships conceptualised in ontologies. Tools include the PID service, pyLDAPI https://github.com/RDFLib/pyLDAPI, and including current work to investigate the new content negotiation by profile – separate from media type, standardising these profiles and the expression of relationships to other features. Profile templates are implemented in entity specific pyLDAPI implementations with data transformed and delivered as standard formats and profiles, sourced from an internal, organisational point of truth – a common organisational data model with well-defined internal identifiers. Applications using these mechanisms to publish such open data at the feature level granularity and their relationships include the geoscience AusGIN portal (http://www.geoscience.gov.au/) and Location Index initiative (LOC-I).

  • Petascale archives of Earth observations from space (EOS) have the potential to characterise water resources at continental scales. For this data to be useful, it needs to be organised, converted from individual scenes as acquired by multiple sensors, converted into ‘analysis ready data’ and made available through high performance computing platforms. Moreover, converting this data into insights requires integration of non-EOS datasets that can provide biophysical and climatic context for EOS. Digital Earth Australia has demonstrated its ability to link EOS to rainfall and stream gauge data to provide insight into surface water dynamics during the hydrological extremes of flood and drought. This information is supporting the characterisation of groundwater resources across Australia’s north and could potentially be used to gain an understanding of the vulnerability of transport infrastructure to floods in remote, sparsely gauged regions of northern and central Australia.

  • The emerging global trend of satellite operators producing analysis ready data combined with open source tools for managing and exploiting this data are leading to more and more countries using Earth observation data to drive progress against key national and international development agendas. This paper provides examples from Australia, Mexico, Switzerland and Tanzania on how the Open Data Cube technology has been combined with analysis ready data to provide new insights and support better policy making across issues as diverse as water resource management through to urbanization and environmental-economic accounting.

  • A probabilistic tsunami hazard assessement (PTHA) was developed for the island of Tongatapu, All modelled tsunamis were initiated by hypothetical thrust earthquakes on the nearby Kermadec-Tonga subduction zone. We provide raster outputs containing the inundation depth with an estimated 10% and 2% chance of being exceeded in 50 years, as well as the code used to perform the analysis [both available here: https://github.com/GeoscienceAustralia/ptha/tree/master/misc/probabilistic_inundation_tonga2020].

  • The Exploring for the Future program is an initiative by the Australian Government dedicated to boosting investment in resource exploration in Australia. As part of the Exploring for the Future program, this study aims to improve our understanding of the petroleum resource potential of northern Australia. This data release presents newly derived chemical maturity parameters based on Fourier transform-ion cyclotron resonance-mass spectrometry (FT-ICR-MS) analysis of non-polar (polyaromatic hydrocarbons) and polar (NSO) compounds. As such, it complements optical and bulk chemical techniques. Although, only a single core extract was analysed in this study, the technique offers potential for maturity assessments in high maturity samples outside the range of other traditional chemical maturity estimates and is ideally suited to samples older than the Early Palaeozoic.