This report deals with an investigation of the electrical resistivities of a variety of wet surface soils, gravels and sands. The work may be regarded as preliminary to an investigation by Mr. R.F. Thyer into the detection of electrically resistive bodies buried in wet soils at shallow depths. It was required to determine the range over which the resistivities of surface soils vary, and also the changes that may be expected in any one type of soil between measurements made within any 1 foot of each other. Measurements were made in four localities, three being in the bed or on the banks of the Molonglo River, where the surface materials are sand, gravel, silts, and in some places, clay. The fourth locality was near the head of Sullivan's Creek, where the soil is a heavy black clay.

The Atlas of Australian Soils (Northcote et al, 1960-68) was compiled by CSIRO in the 1960's to provide a consistent national description of Australia's soils. It comprises a series of ten maps and associated explanatory notes, compiled by K.H. Northcote and others. The maps are published at a scale of 1:2,000,000, but the original compilation was at scales from 1:250,000 to 1:500,000. Mapped units in the Atlas are soil landscapes, usually comprising a number of soil types. The explanatory notes include descriptions of soils landscapes and component soils. Soil classification for the Atlas is based on the Factual Key. This dataset has been modified to show only soil types. For more information go to http://www.asris.csiro.au/themes/Atlas.html

pH is one of the more fundamental soil properties governing nutrient availability, metal mobility, elemental toxicity, microbial activity and plant growth. The field pH of topsoil (0-10 cm depth) and subsoil (~60-80 cm depth) was measured on floodplain soils collected near the outlet of 1186 catchments covering over 6 M km2 or ~80% of Australia. Field pH duplicate data, obtained at 124 randomly selected sites, indicates a precision of 0.5 pH unit (or 7%) and mapped pH patterns are consistent and meaningful. The median topsoil pH is 6.5, while the subsoil pH has a median pH of 7 but is strongly bimodal (6-6.5 and 8-8.5). In most cases (64%) the topsoil and subsoil pH values are similar, whilst, among the sites exhibiting a pH contrast, those with more acidic topsoils are more common (28%) than those with more alkaline topsoils (7%). The distribution of soil pH at the national scale indicates the strong controls exerted by precipitation and ensuing leaching (e.g., low pH along the coastal fringe, high pH in the dry centre), aridity (e.g., high pH where calcrete is common in the regolith), vegetation (e.g., low pH reflecting abundant soil organic matter), and subsurface lithology (e.g., high pH over limestone bedrock). The new data, together with existing soil pH datasets, can support regional-scale decision-making relating to agricultural, environmental, infrastructural and mineral exploration decisions.

Analytical data for 10 major oxides (Al2O3, CaO, Fe2O3, K2O, MgO, MnO, Na2O, P2O5, SiO2 and TiO2), 16 total trace elements (As, Ba, Ce, Co, Cr, Ga, Nb, Ni, Pb, Rb, Sr, Th, V, Y, Zn and Zr), 14 aqua regia extractable elements (Ag, As, Bi, Cd, Ce, Co, Cs, Cu, Fe, La, Li, Mn, Mo and Pb), Loss On Ignition (LOI) and pH from >3500 soil samples from two continents (Australia and Europe) are presented and compared to (1) the composition of the upper crust, (2) published world soil average values, and (3) data from other continental-scale soil surveys. It is demonstrated that average upper continental crust values do not provide reliable estimates for natural concentrations of elements in soils. For many elements there exist substantial differences between published world soil averages and the median concentrations observed on two continents. Direct comparison with other continental datasets is hampered by the fact that often mean, instead of the statistically more correct median, is reported. Using a database of the worldwide distribution of lithological units, it can be demonstrated that lithology is a poor predictor of soil chemistry. Climate-related processes such as glaciation and weathering are strong modifiers of the geochemical signature inherited from bedrock during pedogenesis. To overcome existing shortcomings of predicted global or world soil geochemical reference values, we propose Preliminary Empirical Global Soil reference values based on analytical results of a representative number of soil samples from two continents (PEGS2).

This dataset was created for the National Geochemical Survey of Australia (NGSA) to help determine the location of target sites for sampling catchment outlet sediments in the lower reach of defined river catchments. Each polygon represents a surface drainage catchment derived from a national scale 9 second (approximately 250 m) resolution digital elevation model. Catchments were extracted from an unpublished, interim version of a nested catchment framework with an optimal catchment area of 5000 km2. Only catchments from the Australian mainland and Tasmania were included. In order to generate catchments approaching the optimal area, catchments with an area of less than 1000 km2 were excluded from the dataset, while other small catchments were amalgamated, and catchments much larger than 5000 km2 were split.

A fundamental component of soils is its mineralogy which is a key driver/indicator of important soil properties/processes such as soil pH (acidity), metal availability (e.g. Al, K, Fe, Si, Ca, Mg) and water content/permeability/runoff. However, soil mineralogy is not routinely measured as part of current soil mapping programs at the paddock-, catchment- or continental-scales mainly because currently deployed measurement technologies are not able to deliver soil mineralogy directly, though remote radiometric and microwave sensing technologies do provide useful soil information. In contrast, mineralogy is now being efficiently delivered to the Australian minerals exploration industry through a new generation of field, airborne and spaceborne hyperspectral technologies (www.hyvista.com; nvcl.csiro.au/). This mineral information includes two of the three major soil mineral components, namely: clays (e.g. kaolinite, illite, smectite); and iron/aluminium oxyhydroxides (e.g. hematite. goethite, gibbsite), with specific information being delivered on their composition, abundances and physicochemistries (disorder and chemistry). The third dominant soil mineral component, quartz, is also spectrally measurable but has diagnostic features at wavelengths longer than current "operational" hyperspectral systems. These hyperspectral technologies thus provide an excellent opportunity to transfer mineral mapping capabilities being developed for the minerals industry into the soil mapping application, especially for establishing baseline inventories of soil mineral composition and providing a possible mechanism for quantitative monitoring of change in soil properties related to its mineralogy (e.g. pH, soil loss, water effects, metal activities and possibly soil carbon and salinity). This opportunity is explored using results from a collaborative geological remote sensing project between the CSIRO, the Geological Survey of Queensland and Geoscience Australia (www.em.csiro.au/NGMM, www.nrw.qld.gov.au/science/geoscience/projects/hyperspectral.html) which involves the collection and processing of 25,000 km2 of airborne HyMap imagery (~300 flight-lines at 5m pixel resolution and totalling >1 Terabyte of raw data) from across Queensland, including areas covered by airborne radiometrics and published geology at 1:100 000 scale around the Mount Isa region. The processed hyperspectral data show that lateritic materials in the Tick Hill area comprise relatively abundant iron oxides and kaolinite (poorly ordered) whereas the radiometrics shows these areas as being relatively high Th and U counts. This kaolinite is presumably developed in response to more acid conditions and/or better (downward percolating) drainage. The hyperspectral data also maps extensive areas of Al-smectite (montmorillonite) associated with the weathering of carbonate (calcite and dolomite) parent rocks or as "pedogenic" occurrences in alluvium/colluvium, with the latter sometimes associated with abundant opaline silica (also mapped using the hyperspectral data). These Al-rich smectites are formed in more alkaline conditions where there is sufficient Ca or Mg and water at the near surface and typically show in the radiometric as being poor in K and Th. Muscovite (water-poor, K-bearing white mica) is mapped over exposed parent rocks whereas illite (water-rich, K-bearing white mica) is typically mapped in weathered materials, including many soils and dried lake beds where there is sufficient available K. The radiometric data typically shows these areas as being K-rich. Note that the accuracy of the hyperspectral clay mineral maps was also validated by field sampling and associated laboratory spectral and X-Ray diffraction analyses.

Recently, continental-scale geochemical surveys of Europe and Australia were completed. Thanks to having exchanged internal project standards prior to analysing the samples, we can demonstrate direct comparability between these datasets for 10 major oxides (Al2O3, CaO, Fe2O3, K2O, MgO, MnO, Na2O, P2O5, SiO2 and TiO2), 16 total trace elements (As, Ba, Ce, Co, Cr, Ga, Nb, Ni, Pb, Rb, Sr, Th, V, Y, Zn and Zr), 14 aqua regia extracted elements (Ag, As, Bi, Cd, Ce, Co, Cs, Cu, Fe, La, Li, Mn, Mo and Pb), Loss On Ignition (LOI) and pH. It is useful to compare these new datasets, covering 12 million km2, with compositional estimates from other continents, the upper continental crust and, indeed, published average world soil values. Comparison with other continental datasets is hampered by differences in sampling strategies (media, depth, etc.), sample preparation (esp. sieving), sample analysis (total vs partial analysis), and data reporting (means vs medians). Overall, it appears that different continents have distinct geochemical characteristics. Using upper continental crust concentrations to estimate 'average' global soil compositions is over-simplistic and unwarranted. We propose a set of Preliminary Empirical Global Soil reference values from 2 continental-scale geochemical surveys (PEGS2) based on the median values measured for Europe and Australia, for the elements listed above. These empirical values can be significantly different to previous (theoretical) world soil values. For instance PEGS2 values are systematically lower in Al2O3, CaO, Fe2O3, P2O5, Ba and Sr than previous estimates.

We describe a model to predict soil-regolith thickness in a 128,000 ha study area in the central Mt Lofty Ranges in South Australia. The term soil-regolith includes the A, B, and C soil horizons to the lower boundary of the highly weathered bedrock zone (R horizon). The thickness of the soil-regolith has a major control on water holding capacity for plant growth and movement of water through the landscape, and as such, it is important in hydropedological modelling and in evaluating land suitability, e.g. for forestry and agriculture. Thickness estimates also have direct application in mineral exploration and seismic risk assessment. Geology and landscape evolution within the area is complex, reflecting the variable nature of bedrock materials, and the partial preservation of deeply weathered profiles as a consequence of weathering processes dating to the Cenozoic, or possibly older. These characteristics, together with strong climatic gradients across the area, make the study area an ideal location to understand the environmental and landscape evolution controls on weathering depth. The area also features weathered landscape analogues to many parts of southern Australia. We use a digital soil mapping piecewise linear decision tree approach to develop the model to predict soil-regolith thickness. This model is based on relationships established between 714 soil-regolith thickness measurements and 28 environmental covariates (e.g. rainfall, slope, gamma-ray spectrometry). The results establish a correlation R2 of 0.64, based on a 75:25% training:test data split. These results are encouraging, and are a significant advance over soil depth mapping by traditional soil-landscape mapping methods.

A weathering intensity index (WII) over the Australian continent has been developed at 100 m resolution using regression models based on airborne gamma-ray spectrometry imagery and the Shuttle Radar Topography Mission (SRTM) elevation data. Airborne gamma-ray spectrometry measures the concentration of three radioelements - potassium (K), thorium (Th) and uranium (U) at the Earth's surface. The total gamma-ray flux (dose) is also calculated based on the weighted additions of the three radioelements. Regolith accounts for over 85% of the Australian land area and has a major influence in determining the composition of surface materials and in controlling hydrological and geomorphological processes. The weathering intensity prediction is based on the integration of two regression models. The first uses relief over landscapes with low gamma-ray emissions and the second incorporates radioelement distributions and relief. The application of a stepwise forward multiple regression for the second model generated a weathering intensity index equation of: WII = 6.751 + -0.851*K + -1.319* Relief + 2.682 * Th/K + -2.590 * Dose. The WII has been developed for erosional landscapes but also has the potential to inform on deposition processes and materials. The WII correlates well with site based geochemical indices and existing regolith mapping. Interpretation of the WII from regional to local scales and its application in providing more reliable and spatially explicit information on regolith properties is described.

The Northern Australian Development Committee nominated the region of the Ord and Victoria rivers to be surveyed by the Northern Australian Regional Survey, when the Barkly Region had been completed. The immediate objectives of the Survey are "to accurately record the nature of the country, to establish a sound basis upon which the production possibilities of the Region may be appraised and to make general recommendations concerning development and further investigations." It was decided that the region should include the Army Four Mile Map Sheets of Delamere, Victoria River Downs, Wave Hill, Birrundudu, Limbunya, Waterloo, Auvergne, Port Keats, Medusa Banks, Cambridge Gulf, Lissadell, Dixon Range, and Gordon Downs, and that the field work would be commenced during the 1949 dry season. The techniques and methods used to complete this survey work are noted. The stratigraphy, pedology, and economic geology of the area are described in some detail.