The Upper Burdekin Chloride Mass Balance Recharge web service depicts the recharge rates have been estimated at borehole locations in the Nulla and McBride basalt provinces. Using rainfall rates, rainfall chemistry and groundwater chemistry, the recharge rates have been estimated through the Chloride Mass Balance approach.

This report presents key results of groundwater barometric response function development and interpretation from the Upper Burdekin Groundwater Project in North Queensland, conducted 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 Upper Burdekin Groundwater Project is a collaborative study between Geoscience Australia and the Queensland Government. It focuses on basalt groundwater resources in two geographically separate areas: the Nulla Basalt Province (NBP) in the south and the McBride Basalt Province (MBP) in the north. The NBP and MBP basalt aquifers are heterogeneous, fractured, vesicular systems. This report assesses how water levels in monitoring bores in the NBP and MBP respond to barometric pressure changes to evaluate the degree of formation confinement. The main process used to evaluate water level response to barometric pressure in this study is based on barometric efficiency (BE). The BE of a formation is calculated by dividing the change in monitoring bore water level by the causative barometric pressure change. Both parameters are expressed in the same units, so BE will typically be some fraction between zero and one. BE is not necessarily constant over time; the way BE changes following a theoretical step change in barometric pressure can be described using a barometric response function (BRF). BRFs were calculated in the time domain and plotted as BE against time lag for interpretation. The BRF shape was used to assess the degree of formation confinement. Although there is some uncertainty due to monitoring bore construction issues (including long effective screens) and potentially air or gas trapped in the saturated zone, all BRFs in the current project are interpreted to indicate unconfined conditions. This finding is supported by the identification of recharge at many monitoring bores through hydrograph analysis in other EFTF project components. We conclude that formations are likely to be unconfined at many project monitoring bores assessed in this study.

Geoscience Australia, in collaboration with state government agencies, has been collecting magnetotelluric (MT) data as part of the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) for several years. This program aims to map the electrical resistivity of the rock layers, at depths from ten kilometres to hundreds of kilometres, across the entire continent. AusLAMP sites are each about 55 km apart from each other. Locations are chosen in consultation with landholders and other stakeholders to minimise impacts and avoid disturbance.MT data is collected using sensors that record naturally occurring variations of the Earth’s magnetic and electric fields. The equipment does not produce or transmit and signals. After four to six weeks the equipment is retrieved and the site restored to its original condition.

In 2017, Queensland Fire and Emergency Services (QFES) completed the State Natural Hazard Risk Assessment which evaluated the risks presented to Queensland by seven in-scope natural hazards. This publication can be found at www.disaster.qld.gov.au. The risks presented by tsunami were not evaluated as part of this assessment as there were State and Commonwealth projects underway at the time that would better inform the understanding of the hazard. These have since been completed and now underpin this guide. Following the release of the State Natural Hazard Risk Assessment and through consultation with stakeholders at all levels of Queensland’s Disaster Management Arrangements, the need for consistent information regarding Queensland’s risk from tsunami impact and inundation was identified. Accordingly, this Tsunami Guide for Queensland was developed, with support from Geoscience Australia and the Department of Environment and Science’s Coastal Impacts Unit (CIU), through a consultative process which also helped contextualise the findings of Geoscience Australia’s Probabilistic Tsunami Hazard Assessment 2018 (PTHA18) for Queensland.

Building on newly acquired airborne electromagnetic and seismic reflection data during the Exploring for the Future (EFTF) program, Geoscience Australia (GA) generated a cover model across the Northern Territory and Queensland, in the Tennant Creek – Mount Isa (TISA) area (Figure 1; between 13.5 and 24.5⁰ S of latitude and 131.5 and 145⁰ E of longitude) (Bonnardot et al., 2020). The cover model provides depth estimates to chronostratigraphic layers, including: Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic. The depth estimates are based on the interpretation, compilation and integration of borehole, solid geology, reflection seismic, and airborne electromagnetic data, as well as depth to magnetic source estimates. These depth estimates in metres below the surface (relative to the Australian Height Datum) are consistently stored as points in the Estimates of Geophysical and Geological Surfaces (EGGS) database (Matthews et al., 2020). The data points compiled in this data package were extracted from the EGGS database. Preferred depth estimates were selected to ensure regional data consistency and aid the gridding. Two sets of cover depth surfaces (Bonnardot et al., 2020) were generated using different approaches to map megasequence boundaries associated with the Era unconformities: 1) Standard interpolation using a minimum-curvature gridding algorithm that provides minimum misfit where data points exist, and 2) Machine learning approach (Uncover-ML, Wilford et al., 2020) that allows to learn about relationships between datasets and therefore can provide better depth estimates in areas of sparse data points distribution and assess uncertainties. This data package includes the depth estimates data points compiled and used for gridding each surface, for the Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic (Figure 1). To provide indicative trends between the depth data points, regional interpolated depth surface grids are also provided for the Base Cenozoic, Base Mesozoic, Base Paleozoic and Base Neoproterozoic. The grids were generated with a standard interpolation algorithm, i.e. minimum-curvature interpolation method. Refined gridding method will be necessary to take into account uncertainties between the various datasets and variable distances between the points. These surfaces provide a framework to assess the depth and possible spatial extent of resources, including basin-hosted mineral resources, basement-hosted mineral resources, hydrocarbons and groundwater, as well as an input to economic models of the viability of potential resource development.

This service provides Estimates of Geological and Geophysical Surfaces (EGGS). The data comes from cover thickness models based on magnetic, airborne electromagnetic and borehole measurements of the depth of stratigraphic and chronostratigraphic surfaces and boundaries.

This dataset includes point estimates of groundwater recharge in mm/year. Recharge rates have been estimated at monitoring bore locations in the basaltic aquifers of the Nulla and McBride basalt provinces. Recharge estimates have been calculated using the “chloride mass balance” method. The chloride mass balance process assumes that the chloride ion is a conservative tracer in precipitation, evapotranspiration, recharge and runoff; and that all the chloride is from rainfall, instead of for example halite saturation or dissolution processes. So the volumetric water balance and the flux of chloride balance must both be true. Assuming that runoff and evapotranspiration are negligible (so approximated by zero), the equation is simplified: Water balance P=ET+R+Q Water balance multiplied by chloride concentrations (chloridefluxbalance) P∙Cl_ppt=ET∙Cl_ET+R∙Cl_gw+Q∙Cl_riv | ΔCl_reac≈0 Assumptions to simplify equation P∙Cl_ppt=R∙Cl_gw | Q≈0 & ET≈0 Rearranging for recharge rate (unknown) R=P∙(Cl_ppt)/(Cl_gw ) | Q≈0 & ET≈0 Where P = precipitation rate; ET = evapotranspiration rate; R = recharge rate; Q = runoff to streams; Clppt = concentration of Cl in precipitation; ClET = concentration of chloride in evapotranspiration; Clgw = concentration of Cl in groundwater; Clriv = concentration of chloride in river runoff; ΔClreac = change in chloride concentrations from reactions.

This grid dataset is an estimation of the relative surface potential for recharge within the Nulla Basalt Province. This process combined numerous factors together as to highlight the areas likely to have higher potential for recharge to occur. Soil permeability and surface geology are the primary inputs. Vegetation and slope were excluded from consideration, as these were considered to add too much complexity. Furthermore, this model does not include rainfall intensity – although this is known to vary spatially through average rainfall grids, this model is a depiction of the ground ability for recharge to occur should a significant rainfall event occur in each location. The relative surface potential recharge presented is estimated through a combination of soil and geological factors, weighting regions that are considered likely to have greater potential for recharge (e.g. younger basalts, vent-proximal facies, and highly permeable soils). Near-surface permeability of soil layers has been considered as a quantified input to the ability for water to infiltrate soil strata. It was hypothesised that locations proximal to volcanic vents would be preferential recharge sites, due to deeply penetrative columnar jointing. This suggestion is based on observations in South Iceland, where fully-penetrating columnar joint sets are more prevalent in proximal facies compared to distal facies in South Iceland (Bergh & Sigvaldson 1991). To incorporate this concept, preferential recharge sites are assumed to be within the polygons of vent-proximal facies as derived from detailed geological mapping datasets. Remaining geology has been categorised to provide higher potential recharge through younger lava flows. As such, a ranking between geological units has been used to provide the variation in potential recharge estimates. <b>Reference</b> Bergh, S. G., & Sigvaldason, G. E. (1991). Pleistocene mass-flow deposits of basaltic hyaloclastite on a shallow submarine shelf, South Iceland. Bulletin of Volcanology, 53(8), 597-611. doi:10.1007/bf00493688

Geoscience Australia’s Exploring for the Future (EFTF) program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia’s geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia’s transition to a low emissions economy, strong resources and agriculture sectors, and economic opportunities and social benefits for Australia’s regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government. Further detail is available at http://www.ga.gov.au/eftf. The National Groundwater Systems (NGS) project, is part of the Australian Government’s Exploring for the Future (EFTF) program, led by Geoscience Australia (https://www.eftf.ga.gov.au/national-groundwater-systems), to improve understanding of Australia’s groundwater resources to better support responsible groundwater management and secure groundwater resources into the future. The project is developing new national data coverages to constrain groundwater systems, develop a new map of Australian groundwater systems and improve data standards and workflows of groundwater assessment to populate a consistent data discovery tool and web-based mapping portal to visualise, analyse and download hydrogeological information. While our hydrogeological conceptual understanding of Australian groundwater systems continues to grow in each State and Territory jurisdiction, in addition to legacy data and knowledge from the 1970s, new information provided by recent studies in various parts of Australia highlights the level of geological complexity and spatial variability in stratigraphic and hydrostratigraphic units across the continent. We recognise the need to standardise individual datasets, such as the location and elevation of boreholes recorded in different datasets from various sources, as well as the depth and nomenclature variations of stratigraphic picks interpreted across jurisdictions to map such geological complexity in a consistent, continent-wide stratigraphic framework that can support effective long-term management of water resources and integrated resource assessments. This stratigraphic units data compilation at a continental scale forms a single point of truth for basic borehole data including 47 data sources with 1 802 798 formation picks filtered to 1 001 851 unique preferred records from 171 367 boreholes. This data compilation provides a framework to interpret various borehole datasets consistently, and can then be used in a 3D domain as an input to improve the 3D aquifer geometry and the lateral variation and connectivity in hydrostratigraphic units across Australia. The reliability of each data source is weighted to use preferentially the most confident interpretation. Stratigraphic units are standardised to the Australian Stratigraphic Units Database (ASUD) nomenclature (https://asud.ga.gov.au/search-stratigraphic-units) and assigned the corresponding ASUD code to update the information more efficiently when needed. This dataset will need to be updated as information grows and is being revised over time. This dataset provides: 1. ABSUC_v1 Australian stratigraphic unit compilation dataset (ABSUC) 2. ABSUC_v1_TOP A subset of preferred top picks from the ABSUC_v1 dataset 3. ABSUC_v1_BASE A subset of preferred base picks from the ABSUC_v1 dataset 4. ABSUC_BOREHOLE_v1 ABSUC Borehole collar dataset 5. ASUD_2023 A subset of the Australia Stratigraphic Units Database (ASUD) This consistent stratigraphic units compilation has been used to refine the Great Artesian Basin geological and hydrogeological surfaces in this region and will support the mapping of other regional groundwater systems and other resources across the continent. It can also be used to map regional geology consistently for integrated resource assessments.

The geology and mineral prospectivity of the southern Thomson Orogen is poorly understood because the vast majority of its extent is buried beneath younger regolith and/or sedimentary rocks. To address this issue a collaborative program to drill 16 stratigraphic boreholes was proposed to collect samples of the basement geology that can be comprehensively analysed to improve the understanding of the geological evolution of this region. To reduce the uncertainty associated with intersecting the target stratigraphy at each of the borehole sites, estimates of the cover thickness were obtained by applying the geophysical techniques of refraction seismic, audio-magnetotellurics (AMT) and targeted magnetic inversion modelling (TMIM) prior to drilling. Refraction seismic was acquired at all 16 proposed borehole sites using a system with 48 single-component geophones and a propelled weight drop primary-wave source. At 14 of the sites clear basement refractors were observed in the data. At the two other sites, Nantilla 1 and Barrygowan 1, loss of signal due to seismic attenuation at far offsets meant that a clear basement refractor was not observed. With the exception of these two sites, three distinct refractors are generally observed in the data. Those with velocities ranging from 0.4 km/s to 1.5 km/s are interpreted as regolith, those ranging from 1.8 km/s to 2.4 km/s are interpreted as Eromanga Basin sediments, and those ranging from 3.9 km/s to 5.7 km/s are interpreted as metamorphic/igneous basement. Two-dimensional velocity models of the subsurface geology were then generated using the time-term inversion method, which allowed for the thickness of each layer to be estimated. Cover thickness estimates using refraction data vary widely from site to site, with the shallowest estimate being Overshot 1 (49 m - 55 m) and the deepest Adventure Way 1 (295 m - 317 m). These variations in cover thickness estimates from site to site are indicative of basement topography variations and are not error margins. Audio-magnetotelluric data was collected at ten sites by simultaneously deploying four porous pot electrodes, to collect the two orthogonal components of telluric data (Ex and Ey), and three magnetic induction coils, to collect the three components of magnetic data (Hx, Hy and Hz). For each dataset, a one-dimensional inversion model was produced, from which resistivity contrasts were identified and used to describe electrical conductivity discontinuities in the subsurface geology. In general, the models show a near-surface conductive layer with resistivity values ≤10 Ω·m overlying layers with continuously increasing resistivities with depth (up to 102-103 Ω·m). Those layers which were >10 Ω·m were interpreted as metamorphic/igneous basement rocks and were observed to occur at depths of ~100 m to ~300 m across the survey sites, except at Overshot 1 (38 m ±10%) and Barrygowan 1 (480 m ±10%). Targeted magnetic inversion modelling (TMIM) was applied to freely available, good quality, regional airborne magnetic survey data. Depth to magnetic source estimates were generated for 53 targets, with confidence ratings, using a dipping tabular source body to model targeted magnetic anomalies in the vicinity of the borehole sites. A combined depth estimate was generated using a distance and confidence weighted average from multiple depth estimates at all but two borehole sites. Only a single depth estimate was available at Adventure Way 1 while no depth estimates were generated at Eulo 1. These combined depth estimates provide cover thickness estimates at the sites as they are likely sourced from, or near, the top of basement. Of the ten proposed borehole sites with coincident AMT and refraction seismic data, five sites have overlapping cover thickness estimates. Cover thickness estimates from the TMIM overlap both the AMT and refraction data at four sites and at two sites where only the refraction depth estimates were available. 2 Estimating Cover Thickness in the Southern Thomson Orogen The cover thickness estimates presented in this report lower the risks associated with the proposed southern Thomson Orogen stratigraphic drilling program by reducing the uncertainty in intersecting the target stratigraphy at each of the borehole sites as well as allowing for better project and program planning. Successful completion of the stratigraphic drilling program in the southern Thomson Orogen will allow for each of these geophysical methods for estimating cover thickness to be benchmarked using actual cover thicknesses measured in the boreholes.