Catchment outlet sediments (0-10 cm depth, sieved to <2 mm) collected at a very low density over most of the Australian continent have been analysed using the Mobile Metal Ion (MMI®) partial extraction technique. Of the 54 elements analysed, eight are generally regarded as essential nutrients for plant growth: Ca, Cu, Fe, K, Mg, Mn, P and Zn. For these, 'bioavailability', defined here as the ratio of the partial digest concentration to the total concentration, has been investigated. This estimation of 'bioavailability' gives results comparable with standard agricultural measurements. Average 'bioavailability' ranges from 15.0% for Ca to 0.1% for Fe. Smoothed (kriged) colour contour maps for continental Australia have been produced for these eight nutrients and interpreted in terms of lithology (e.g., presence of carbonates in the MMI® Ca map), mineralization (e.g., well known and possibly less known mineral districts in the Cu, P and Zn maps), environmental processes (e.g., salinity in K map, weathering and acid generation in Fe map) and agricultural practices (e.g., application of fertilizers in P and Zn maps). This first application of a partial extraction technique at the scale of a continent has yielded meaningful, coherent and interpretable results.

Inland sulfidic soils have recently formed throughout wetlands of the Murray River floodplain associated with increased salinity and river regulation (Lamontagne et al., 2006). Sulfides have the potential to cause widespread environmental degradation both within sulfidic soils and down stream depending on the amount of carbonate available to neutralise acidity (Dent, 1986). Sulfate reduction is facilitated by organic carbon decomposition, however, little is known about the sources of sedimentary organic carbon and carbonate or the process of sulfide accumulation within inland sulfidic wetlands. This investigation uses stable isotopes from organic carbon (13C and 15N), inorganic sulfur (34S) and carbonate (13C and 18O) to elucidate the sources and cycling of sulfur and carbon within sulfidic soils of the Loveday Disposal Basin.

Published estimates for heavy metal emissions from the copper-nickel industry on the Kola Peninsula are re-examined in the light of: a) Official emission figures for 1994, b) Modelled emissions based on dry and wet deposition estimates based on data from snow and rain samples collected in 1994 and c) Chemical data on the composition of the ores. The modelled emissions, official emission figures and chemical data are mutually compatible for Ni, Cu and Co and show that previously published figures underestimated the emissions of the major elements, Ni and Cu (though within the same order of magnitude) and overestimated the emissions of As, Pb, Sb and Zn by up to several orders of magnitude, in some cases exceeding the calculated total input to the plants. Published estimates have neglected information on the nature and chemistry of the ores processed in metallurgical industries in the Noril-sk area of Siberia and the Urals. Revised emission estimates for 1994, using knowledge of the chemistry of the ores, are proposed: taken with published information on total emissions up to 2000 these data give an indication of emission levels in more recent years.

Geoscience Australia and CO2CRC have constructed a greenhouse gas controlled release facility to simulate surface emissions of CO2 (and other greenhouse gases) from the soil into the atmosphere under controlled conditions. The facility is located at an experimental agricultural station maintained by CSIRO Plant Industry at Ginninderra, Canberra. The design of the facility is modelled on the ZERT controlled release facility in Montana. The facility is equipped with a 2.5 tonne liquid CO2 storage vessel, vaporiser and mass flow controller unit with a capacity for 6 individual metered CO2 gas streams (up to 600 kg/d capacity in total). Injection of CO2 into the soil is via a 120m long slotted HDPE pipe installed horizontally 2m underground. This is equipped with a packer system to partition the well into six CO2 injection chambers. The site is characterised by the presence of deep red and yellow podsolic soils with the subsoil containing mainly kaolinite and subdominant illite. Injection is above the water table. The choice of well orientation based upon the effects of various factors such as topography, wind direction, soil properties and ground water depth will be discussed. An above ground release experiment was conducted from July - October 2010 leading to the development of an atmospheric tomography technique for quantifying and locating CO2 emissions1. An overview of monitoring experiments conducted during the first subsurface release (January-March 2012), including application of the atmospheric tomography technique, soil flux surveys, microbiological surveys, and tracer studies, will be presented. Additional CO2 release experiments are planned for late 2012 and 2013. Poster presented at 11th Annual Conference on Carbon Capture Utilization & Sequestration, April 30 - May 3, 2012, Pittsburgh, Pennsylvania

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.

Models of seabed sediment mobilisation by waves and currents over Australia's continental shelf environment are used to examine whether disturbance regimes exist in the context of the intermediate disturbance hypothesis (IDH). Our study shows that it is feasible to model the frequency and magnitude of seabed disturbance in relation to the dominant energy source (wave-dominated shelf, tide-dominated shelf or tropical cyclone dominated shelf). Areas are mapped where the recurrence interval of disturbance events is comparable to the rate of ecological succession, which meets criteria defined for a disturbance regime. We focus our attention on high-energy, patch-clearing events defined as exceeding the Shields (bed shear stress) parameter value of 0.25. Using known rates of ecological succession for different substrate types (gravel, sand, mud), predictions are made of the spatial distribution of a dimensionless ecological disturbance index (ED), given as: ED = FA (ES/RI), where ES is the ecological succession rate for different substrates, RI is the recurrence interval of disturbance events and FA is the fraction of the frame of reference (surface area) disturbed. Maps for the Australian continental shelf show small patches of ED-seafloor distributed around the continent, on both the inner and outer shelf. The patterns are different for wave-dominated (patches on the outer shelf trending parallel to the coast), tide-dominated (patches crossing the middle-shelf trending normal to the coast) and cyclone-dominated (large oval-shaped patches crossing all depths). Only a small portion of the shelf (perhaps ~10%) is characterised by a disturbance regime as defined here. To our knowledge, this is the first time such an analysis has been attempted for any continental shelf on the earth.

A key component of Geoscience Australia's marine program involves developing products that contain spatial information about the seabed for Australia's marine jurisdiction. This spatial information is derived from sparse or unevenly distributed samples collected over a number of years using many different sampling methods. Spatial interpolation methods are used for generating spatially continuous information from the point samples. These methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Machine learning methods, like random forest (RF) and support vector machine (SVM), have proven to be among the most accurate methods in disciplines such as bioinformatics and terrestrial ecology. However, they have been rarely previously applied to the spatial interpolation of environmental variables using point samples. To improve the accuracy of spatial interpolations to better represent the seabed environment for a variety of applications, including prediction of biodiversity and surrogacy research, Geoscience Australia has conducted two simulation experiments to compare the performance of 14 mathematical and statistical methods to predict seabed mud content for three regions (i.e., Southwest, North, Northeast) of Australia's marine jurisdiction Since 2008. This study confirms the effectiveness of applying machine learning methods to spatial data interpolation, especially in combination with OK or IDS, and also confirms the effectiveness of averaging the predictions of these combined methods. Moreover, an alternative source of methods for spatial interpolation of both marine and terrestrial environmental properties using point survey samples has been identified, with associated improvements in accuracy over commonly used methods.

Australian Daily Wind Data as produced by the Bureau of Meteorology. Dataset contains: Mean daily wind speed; Daily maximum wind gust; Daily wind run from instruments at a height below 3 metre; Daily wind run from instruments at a height above 3 metre; plus additional supporting information.

A major concern for regulators and the public with geological storage of CO2 is the potential for the migration of CO2 via a leaky fault or well into potable groundwater supplies. Given sufficient CO2, an immediate effect on groundwater would be a decrease in pH which could lead to accelerated weathering, an increase in alkalinity, release of major and minor ions and heavy metals (particularly Pd, Ni and Cr) as well as CO2 mobilisation of trace organic contaminants. These scenarios potentially occur in a high CO2 leakage event, therefore detection of a small leak, although barely perceptible, could provide an important early warning for a subsequent and more substantial impact. Different approaches are required for the detection and quantification of these low level leaks and are the subject of this paper. A 3 year groundwater survey was recently completed in the Surat Basin, which provided comprehensive water and isotopic analysis of groundwaters together with their exsolved gases. The gases were analysed for composition, -13CCO2, -13CCH4 and -2HCH4. Methane is prevalent in the major Surat Basin aquifers (e.g. Mooga, Gubberamunda and Hutton sandstones) and is invariably associated with a bacterial (methanogenic) carbonate reduction source, evident from its isotopic signature ('13CCH4 ~ -70', '2HCH4 ~ -220'). In addition to methane and low levels of CO2, trace ethane is common. Two neighbouring wells, however, were quite different to the other 85 wells surveyed. Their exsolved gases contained comparatively high ethane, but also C1-C6 hydrocarbons in addition to methane. Methane isotope systematics were significantly different from other groundwater wells completed in the same formation. The -13C of the CO2 was similar to the surrounding groundwater wells, but the relative proportion of CO2 in the gas was significantly higher. Combined, these characteristics are consistent with hydrocarbon biodegradation. There was little difference in the groundwater chemistry for these wells compared to the regional baseline. The study provides a useful analogue study for detection, at various scales, of a leaky well associated with a geological storage site. Compositional and isotopic analysis of exsolved gases from groundwater samples could be used to demonstrate non-equilibrium conditions and intrusion of exogenic CO2. Abstract for the 2013 International Association of Hydrologist Congress, Perth