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.

Soil mapping at the local- (paddock), to continental-scale, may be improved through remote hyperspectral imaging of surface mineralogy. This opportunity is demonstrated for the semiarid Tick Hill test site (20 km2) near Mount Isa in western Queensland, which is part of a larger Queensland government initiative involving the public delivery of 25,000 km2 of processed airborne hyperspectral mineral maps at 4.5 m pixel resolution to the mineral exploration industry. Some of the "soil" mineral maps for the Tick Hill area include the abundances and/or physicochemistries (chemical composition and crystal disorder) of dioctahedral clays (kaolin, illite-muscovite and Al smectite, both montmorillonite and beidellite), ferric/ferrous minerals (hematite/goethite, Fe2+-bearing silicates/carbonates) and hydrated silica (opal) as well as "soil" water (bound and unbound) and green and dry (cellulose/lignin) vegetation. Validation of these hyperspectral mineral products is based on field sampling and laboratory analyses (spectral reflectance, X-ray diffraction, scanning electron microscope and electron backscatter). The mineral maps show more detailed information regards the surface composition compared with the published soil and geology (1:100,000 scale) maps and airborne radiometric imagery (collected at 200 m line spacing). This mineral information can be used to improve the published mapping but also has the potential to provide quantitative information suitable for soil modeling/monitoring.

Several quality control measures were taken during the project. These included: - Central provision of sampling equipment and sample bags to all field teams - Randomised sample identification scheme so that samples were presented to the laboratories in a sequence unrelated to the order in which they were collected (as much as practically feasible) - Prevention of contamination in the field and in the lab - Prevention of sample mix-up in the field and in the lab - Field duplicates: every 10th site, a field duplicate sample was collected to help quantify total (sampling + analytical) precision (not identified as such to the lab) - Certified Reference Materials (CRMs) TILL-1, TILL-2 (Natural Resources Canada) were run with every batch on GA's XRF & ICP-MS to help quantify analytical precision and bias - Laboratory duplicates (splits), internal project standards (MRIS, WRIS, ORIS, MRIS2, WRIS2), exchanged project standards (GEMAS-Ap, GEMAS-Gr from EuroGeoSurveys; SoNE-1 from United States Geological Survey), and international CRMs (TILL-1, TILL-3, LKSD-1, STSD-3 from Natural Resources Canada) were covertly inserted in the analytical suites for in-house and external analyses to help quantify analytical precision and bias (not identified as such to the lab) - Internal project standard (GRIS) for pH 1:5, EC 1:5 and grain size measurements (not identified as such to the lab) In addition to the above measures, the analytical labs applied their own QA/QC procedures, including running CRMs and/or internal standards, replicating digests and/or analysis, and analysis of blanks. The present report uses some of the above data to quantitatively assess the quality of the NGSA data, which allows a quality statement to be made about the NGSA data.

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.

This report deals with the problem of detecting electrically resistive bodies of small size buried at shallow depths in wet soils. Detection was attempted by means of measurements made on the surface of the soil using the electrical resistivity method. The present report can be regarded as an extension of an earlier one (No. 1943/64B). The purpose of the new tests was twofold. Firstly it was proposed to make tests of 'normal' resistivity effects using a constant electrode arrangement and measuring the resistivity at closely spaced points on water saturated soils. The second part of the testing programme was contingent on the first part proving that under saturated conditions soil resistivities were sufficiently constant to warrent an attempt being made at detection. If this condition of constancy existed, it was proposed to extend the work of the tests, reviewed in the previous report, to actual field conditions. This has been done and the present report deals with the results obtained.

Soils are one of the key factors which limit human settlement in Australia. Few Australian soils are of good quality - most are naturally infertile. This map shows the extent of soil limitations across the country. In order to overcome problems associated with the many classifications in existence, this map classes soils according to limitations of use - in particular chemical and physical limitations. Altogether, four primary groupings are shown and these are further divided into a total of 29 mapping units. A detailed table relates these units to traditionally classified soil profiles and landforms. Product Specifications: Coverage: Australia Currency: 1976-77 Coordinates: Geographical Datum: AGD66 (GDA94 compliant at this scale) Projection: Simple Conic on two standard parallels 18S and 36S Medium: Paper, flat and folded copies

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.

The ability of thermal and shortwave infrared spectroscopy to characterise composition and textural was evaluated using both particle size separated soil samples and raw soils. Particle size analysis and separation into clay, silt and sand sized soil fractions was undertaken to examine possible relationships between quartz and clay mineral spectral signatures, and soil texture. Spectral indices, based on thermal infrared specular and volume scattering features, were found to discriminate clay mineral-rich soil from mostly coarser quartz-rich sandy soil, and to a lesser extent, from the silty quartz-rich soil. Further investigations were undertaken using spectra and information on 51 USDA and other soils within the ASTER Spectral Library to test the application of shortwave, mid- and thermal infrared spectral indices for the derivation of clay mineral, quartz and organic carbon content. A non linear correlation between quartz content and a TIR spectral index based on the 8.62 im was observed. Preliminary efforts at deriving a spectral index for the soil organic carbon content, based on 3.4 - 3.5 im fundamental H-C stretching vibration bands were also undertaken with limited results.

Our planet provides everything we need for our lives, including the food we eat. As the human population increases and expectations for lifestyle quality increases, so too do the pressures placed on our planet to provide that food. We therefore need to be better at producing food and understanding how that links to our scientific understanding of our planet. For National Science Week 2021, the Geoscience Australia public seminar (co-sponsored by the ACT Division of the Geological Society of Australia and the ACT Branch of the Australian Marine Sciences Association) will present four speakers to demonstrate how geoscience is integral to the provision of our food. Steve Hill – The Long View: Across many disciplines of geoscience and different spatial scales, geology, soils and even plate tectonics influence our food (and wine). Andrew Carroll – Finding Important Seabed Habitat (FISH): Did you know that seabed mapping data directly contributes $9 billion to the Australian economy each year and employs over 56,000 people? For the fishing and aquaculture sectors, seabed mapping is valued at $3 billion. However, only one quarter of Australia’s seabed is mapped! Learn how GA is addressing this challenge to support the rapid growth of Australia's Blue Economy. Claire Krause – Food at Scale: In a country as big and dynamic as Australia, producing food is no small task. Satellite imagery is being leveraged to map, monitor and understand Australia’s food production regions and to identify and manage challenges in the sector. Anna Riddell – From Paddock to Plate with Positioning: Have you ever wondered how your food arrives on your plate and the role that navigation satellites play? Positioning is becoming ubiquitous in everyday life and even has a part in enabling our food to be grown, harvested and transported.

Soil is a common evidence type used in forensic and intelligence operations. Where soil composition databases are lacking or inadequate, we propose to use publicly available soil attribute rasters to reduce forensic search areas. Soil attribute rasters, which have recently become widely available at high spatial resolutions, typically three arc-seconds (~90 m), are predictive models of the distribution of soil properties (with confidence limits) derived from data mining the inter-relationships between these properties and several environmental covariates. Each soil attribute raster is searched for pixels that satisfy the compositional conditions of the evidentiary soil sample (target value ± confidence limits). We show through an example that the search area for an evidentiary soil sample can be reduced to <10% of the original investigation area. This Predictive Soil Provenancing (PSP) approach is a transparent, reproducible and objective method of efficiently and effectively reducing the likely provenance area of forensic soil samples. <b>Citation:</b> de Caritat, P., Simpson, T. and Woods, B. (2019), Predictive Soil Provenancing (PSP): An Innovative Forensic Soil Provenance Analysis Tool. <i>J Forensic Sci</i>, 64: 1359-1369. https://doi.org/10.1111/1556-4029.14060