No abstract available

Identification of groundwater-dependent (terrestrial) vegetation, and assessment of the relative importance of different water sources to vegetation dynamics commonly involves detailed ecophysiological studies over a number of seasons or years. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Consequently, quicker, more regional mapping approaches have been developed. These new approaches utilise advances in computation geoscience, and remote sensing and airborne geophysical technologies. This study, undertaken in the semi-arid Darling River Floodplain in N.S.W., Australia, combines Landsat Normalised Difference Vegetation Index (NDVI) time series data with hydrogeological, hydrogeochemical and hydrogeophysical data to assess the relative importance of hydrological processes and groundwater characteristics. The first stage in the study combined high-resolution vegetation structural mapping derived from LiDAR data (Canopy Digital Elevation Model and Foliage Projected Cover), with 23 years of Landsat time-series data. Statistical summaries of Normalised Difference Vegetation Index values were generated for each spatially continuous vegetation structural class for each Landsat scene (e.g. stand of closed forest). This has enabled long-term temporal changes in vegetation condition to be assessed against different water regimes (drought, local rainfall, river bank full, overbank flow, and lake filling), and groundwater dependent vegetation to be identified. The second stage involved integration with airborne electromagnetics (AEM), hydrogeology and hydrogeochemistry. This has shown that the deeper (>25m), semi-confined aquifer is only rarely important to vegetation dynamics, with the shallow unconfined aquifer and river lateral bank recharge zones being of greater importance.

Geoscience Australia (GA) has recently completed two regional-scale Airborne Electromagnetic (AEM) surveys: one in the Paterson Region, WA; and the other in the Pine Creek region, NT. These surveys provide AEM data at line spacings of 200 m to 6 km covering an area greater than 110 000 km2. The surveys were designed to promote more detailed investigations by the mineral exploration industry. An inherent risk in using AEM surveys is that the depth of penetration of the primary electromagnetic field is highly variable. Although forward modelling is undertaken before the AEM campaign, the depth to which we can reliably invert the AEM signal to generate conductivity models is not known until after the survey is flown. In order to estimate the penetration depth of the AEM surveys, we calculate the depth of investigation (DOI) based on the GA layered-earth inversion algorithm, which is influenced by both conductivity measurements and reference model assumptions. We define the DOI as the maximum depth at which the inversion is influenced more by the conductivity data than the reference model. We present the DOI as a 2D grid across both the Paterson and Pine Creek AEM surveys. Labelled the 'AEM go-map', the DOI grid helps to promote AEM exploration by decreasing risk when industry undertakes follow-up surveys within these regions.

Presentation to minerals industry representatives at the Geological Survey of Western Australia, 4 May 2010.

Presentation to minerals industry representatives at the Geological Survey of Western Australia, 4 May 2010.

Airborne Electromagnetic data were acquired by Geoscience Australia in areas considered to have potential for uranium or thorium mineralisation under the Australian Government's Onshore Energy Security Program (OESP). The surveys have been managed and interpreted by Geoscience Australia's Airborne Electromagnetic Acquisition and Interpretation project. Government of South Australia Department for Manufacturing, Innovation, Trade, Resources and Energy (DMITRE), formerly the Department of Primary Industries and Resources South Australia (PIRSA), which changed name in October 2011 purchased infill. Three survey areas were recognised in the Frome AEM survey area and Cariewerloo traverses. Industry paid for infill - all of this data has now been released to the public domain and is available at the GA website. In contrast to industry style deposit scale investigations, these surveys are designed to reveal new geological information at regional scale. The Frome airborne electromagnetic data were acquired at line spacing's of between one and five kilometres, a total of 32 317 line km and covers an area of 95 450 km squared. The outcomes of the Frome AEM survey include mapping of subsurface geological features that are associated with unconformity-related, sandstone-hosted and palaeovalley-hosted uranium mineralisation. The data are also capable of interpretation for other commodities including metals and potable water as well as for landscape evolution studies. The improved understanding of the regional geology resulting from the Pine Creek survey results will be of considerable benefit to mining and mineral exploration companies. This Data Package is for Archive to the internal area of the CDS and contains all data, grids, images, mxd, shape files, documentation, licenses, agreements, interpretations and scripts used to create the Frome deliverables. At the projects completion (2012) all directories are required to be moved off the NAS. The reason to keep all the files is that more work is to be done on this data in the 2012-2015 period and these files may be needed in this future work.

In 2008-2009 Geoscience Australia, contracted Fugro Airborne Surveys and Geotech Airborne, to respectively acquire TEMPEST and VTEM airborne electromagnetic (AEM) data with broad line spacings covering more than 71 000 km² in the Pine Creek region, Northern Territory. The Pine Creek survey (Figure 1) is the second regional AEM survey funded by the Onshore Energy Security Program (OESP) at Geoscience Australia. Geoscience Australia funded the flying of 19 500 line km, subscriber companies funded 10 400 line km. The 5 000 m line spacing provide regional information with 1 666 m, 555 m and closer line spacing providing detail for mineral systems analysis and deposit scale mapping. One of the main survey objectives was to reduce exploration risk and encourage exploration in the region by mapping, under cover, in areas where gravity and magnetics are quiet. Geological targets included detecting: conductive unites within the Pine Creek Orogen (PCO) sequence; Kombolgie Sandstone / PCO unconformity; Tolmer Group/ Finniss River Group unconformity. Geoscience Australia undertook conductivity logging (Figure 2) in the Pine Creek region. Conductivity logs were processed and as input into forward models, ground truth AEM results and for geological interpretations. To facilitate interpretation, subsurface electrical conductivity predictions using a layered earth inversion (sample by sample) algorithm developed by Geoscience Australia (GA-LEI) were derived from the AEM survey data. Conductivity characterisation of large regional units using the AEM data show: the Rum Jungle Complex is a consistently resistive area with an average conductivity value of less than 2 m/S; the Mt Partridge Group has a conductivity value up to 100 m/S; the Kombolgie Sandstone has a conductivity range of less than 2 m/S in more areas. Detecting conductivity contrasts in areas with known uranium prospectivity aids in a mineral systems analysis and geological interpretation of uranium deposits.

A brief summary fo the highlights of the Paterson AEM survey and planned future work of Geoscience Australia's Airborne EM Project.

Under the Community Stream Sampling and Salinity Mapping Project, the Australian Government through the Department of Agriculture, Fisheries and Forestry and the Department of Environment and Heritage, acting through Bureau of Rural Sciences, funded an airborne electromagnetic (AEM) survey to provide information in relation to land use questions in selected areas along the River Murray Corridor (RMC). The proposed study areas and major land use issues were identified by the RMC Reference Group at its inception meeting on 26th July, 2006. This report has been prepared to facilitate recommendations on the Lindsay-Walppolla study area. The work was developed in consultation with the RMC Technical Working Group (TWG) to provide a basis for the RMC Reference Group and other stake holders to understand the value and application of AEM data to the study area. This understanding, combined with the Reference Group's assessment of the final results and taking in account policy and land management issues, will enable the Reference Group to make recommendations to the Australian Government. The report is based on an assessment the application of AEM to the Reference Group's land management issues as specified by the TWG at its meeting on 16th August 2006 and out of session.

Ross C Brodie Murray Richardson AEM system target resolvability analysis using a Monte Carlo inversion algorithm A reversible-jump Markov chain Monte Carlo inversion is used to generate an ensemble of millions of models that fit the forward response of a geoelectric target. Statistical properties of the ensemble are then used to assess the resolving power of the AEM system. Key words: Monte Carlo, AEM, inversion, resolvability.