Wildfires are one of the major natural hazards facing the Australian continent. Chen (2004) rated wildfires as the third largest cause of building damage in Australia during the 20th Century. Most of this damage was due to a few extreme wildfire events. For a vast country like Australia with its sparse network of weather observation sites and short temporal length of records, it is important to employ a range of modelling techniques that involve both observed and modelled data in order to produce fire hazard and risk information/products with utility. This presentation details the use of statistical and deterministic modelling of both observations and synthetic climate model output (downscaled gridded reanalysis information) in the development of extreme fire weather potential maps. Fire danger indices such as the McArthur Fire Forest Danger Index (FFDI) are widely used by fire management agencies to assess fire weather conditions and issue public warnings. FFDI is regularly calculated at weather stations using measurements of weather variables and fuel information. As it has been shown that relatively few extreme events cause most of the impacts, the ability to derive the spatial distribution of the return period of extreme FFDI values contributes important information to the understanding of how potential risk is distributed across the continent. The long-term spatial tendency FFDI has been assessed by calculating the return period of its extreme values from point-based observational data. The frequency and intensity as well as the spatial distribution of FFDI extremes were obtained by applying an advanced spatial interpolation algorithm to the recording stations' measurements. As an illustration maps of 50 and 100-year return-period (RP) of FFDI under current climate conditions are presented (based on both observations and reanalysis climate model output). MODSIM 2013 Conference

This report provides background information about the Ginninderra controlled release Experiment 2 including a description of the environmental and weather conditions during the experiment, the groundwater levels and a brief description of all the monitoring techniques that were trialled during the experiment. Release of CO2 began 26 October 2012 at 2:25 PM and stopped 21 December 2012 at 1:30 PM. The total CO2 release rate during Experiment 2 was 218 kg/d CO2. The aim of the second Ginninderra controlled release was to artificially simulate the leakage of CO2 along a line source, to represent leakage along a fault. Multiple methods and techniques were then trialled in order to assess their abilities to: - detect that a leak was present - pinpoint the location of the leak - identify the strength of the leak - monitor how the CO2 behaves in the sub-surface - assess the effects it may have on plant health Several monitoring and assessment techniques were trialled for their effectiveness to quantify and qualify the CO2 that was release. This experiment had a focus on plant health indicators to assess the aims listed above, in order to evaluate the effectiveness of monitoring plant health and the use of geophysical methods to identify that a CO2 leak may be present. The methods are described in this report and include: - soil gas - airborne hyperspectral surveys - plant health (PhenoMobile) - soil CO2 flux - electromagnetic (EM-31) - electromagnetic (EM-38) - ground penetrating radar (GPR) This report is a reference guide to describe the Ginninderra Experiment 2 details. Only methods are described in this report with the results of the study published in conference papers and future journal articles.

Changes in microbial diversity and population structure occur as a result of increased nutrient loads and knowledge of microbial community composition may be a useful tool for assessing water quality in coastal ecosystems. However, the ability to understand how microbial communities and individual species respond to increased nutrient loads is limited by the paucity of community-level microbial data. The microbial community composition in the water column and sediments was measured across tropical tidal creeks and the relationship with increased nutrient loads assessed by comparing sewage-impacted and non-impacted sites. Diversity-function relationships were examined with a focus on denitrification and the presence of pathogens typically associated with sewage effluent tested. Significant relationships were found between the microbial community composition and nutrient loads. Species richness, diversity and evenness in the water column all increased in response to increased nutrient loads, but there was no clear pattern in microbial community diversity in the sediments. Water column bacteria also reflected lower levels of denitrification at the sewage-impacted sites. The genetic diversity of pathogens indicated that more analysis would be required to verify their status as pathogens, and to develop tests for monitoring. This study highlights how microbial communities respond to sewage nutrients in a tropical estuary. Estuarine, Coastal and Shelf Science

Abstract: Land Surface Temperature (Ts) is an important boundary condition in many land surface modelling schemes. It is also important in other application areas such as, hydrology, urban environmental monitoring, agriculture, ecological and bushfire monitoring. Many studies have shown that it is possible to retrieve Ts on a global scale using thermal infrared data from satellites. Development of standard methodologies that generate Ts products routinely would be of broad benefit to the application of remote sensing data in areas such as hydrology and urban monitoring. AVHRR and MODIS datasets are routinely used to deliver Ts products. However, these data have 1km spatial resolution, which is too coarse to detect the detailed variation of land surface change of concern in many applications, especially in heterogeneous areas. Higher resolution thermal data from Landsat is a possible option in such cases. To derive Ts, two scientific problems need to be resolved: to remove the atmospheric effects and derive surface brightness temperature (TB) and to separate the emissivity and Ts effects in the surface brightness temperature (TB). To derive TB, for single thermal band sensors such as, Landsat 5, 7 and (due to a faulty dual-band thermal instrument) on Landsat-8, the split window methods, such as those used for NOAAAVHRR data (Becker & Li, 1990), and the day/night pairs of thermal infrared data in several bands, as used for MODIS (Wan et al., 2002) are not available for correcting atmospheric effects. The retrieval of surface brightness temperature TB from Landsat data therefore needs more care, as the accuracy of the TB retrieval depends critically on the ancillary data, such as atmospheric water vapour data (precipitable water). In this paper, a feasible operational method to remove the atmospheric effects and retrieve surface brightness temperature from Landsat data is presented. The method uses the MODTRAN 5 radiative transfer model and global atmospheric profile data sets, such as NASA MERRA (The Modern Era Retrospective-Analysis for Research and Applications) atmospheric profiles, NOAA NCEP (National Center for Environmental Prediction) reanalysis product and ECMWF (The European Centre for Medium-Range Weather Forecasts) to correct for the atmospheric effects. The results derived from the global atmospheric profiles are assessed against the TB product estimated by using (accurate) ground based radiosonde data (balloon data). The results from this study have found: The global data sets NCEP1, NCEP2, MERRA and ECMWF can all generally give satisfactory TB products and can meet the levels of accuracy demanded by many practitioners, such as 1º K. Among global data sets, ECMWF data set performs best. The root mean square difference (RMSD) for the 9 days and 3 test sites are all within 0.4º K when compared with the TB products estimated using ground radiosonde measurements.

A video for the launch of new Great Barrier Reef bathymetry data on 30 November 2017.

The Clarence-Moreton and the Surat basins in Queensland and northern New South Wales contain the coal-bearing sedimentary sequences of the Jurassic Walloon Coal Measures, composed of up to approximately 600 m of mudstone, siltstone, sandstone and coal. In recent years, the intensification of exploration for coal seam gas (CSG) resources within both basins has led to concerns that the depressurisation associated with future resource development may cause adverse impacts on water resources in adjacent aquifers. In order to identify the most suitable tracers to study groundwater recharge and flow patterns within the Walloon Coal Measures and their degree of connectivity with over- or underlying formations, samples were collected from the Walloon Coal Measures and adjacent aquifers in the northern Clarence-Moreton Basin and eastern Surat Basin, and analysed for a wide range of hydrochemical and isotopic parameters. Parameters that were analysed include major ion chemistry, -13C-DIC, -18O, 87Sr/86Sr, Rare Earth Elements (REE), 14C, -2H and -13C of CH4 as well as concentrations of dissolved gases (including methane). Dissolved methane concentrations range from below the reporting limit (10 µg/L) to approximately 50 mg/L in groundwaters of the Walloon Coal Measures. However, the high degree of spatial variability of methane concentrations highlights the general complexity of recharge and groundwater flow processes, especially in the Laidley Sub-Basin of the Clarence-Moreton Basin, where numerous volcanic cones penetrate the Walloon Coal Measures and may form pathways for preferential recharge to the Walloon Coal Measures. Interestingly, dissolved methane was also measured in other sedimentary bedrock units and in alluvial aquifers in areas where no previous CSG exploration or development has occurred, highlighting the natural presence of methane in different aquifers. Radiocarbon ages of Walloon Coal Measure groundwaters are also highly variable, ranging from approximately 2000 yrs BP to >40000 yrs BP. While groundwaters sampled in close proximity to the east and west of the Great Dividing Range are mostly young, suggesting that recharge to the Walloon Coal Measures through the basalts of the Great Dividing Range occurs here, there are otherwise no clearly discernable spatial patterns and no strong correlations with depth or distance along inferred flow paths in the Clarence-Moreton Basin. In contrast to this strong spatial variability of methane concentrations and groundwater ages, REE and 87Sr/86Sr isotope ratios of Walloon Coal Measures groundwaters appear to be very uniform and clearly distinct from groundwaters contained in other bedrock units. This difference is attributed to the different source material of the Walloon Coal Measures (mostly basalts in comparison to other bedrock units which are mostly composed of mineralogical more variable Paleozoic basement rocks of the New England Orogen). This study suggests that REE and 87Sr/86Sr ratios may be a suitable tracer to study hydraulic connectivity of the Walloon Coal Measures with over- or underlying aquifers. In addition, this study also highlights the need to conduct detailed water chemistry and isotope baseline studies prior to the development of coal seam gas resources in order to differentiate between natural background values of methane and potential impacts of coal seam gas development.

Geoscience Australia and the CO2CRC operate a greenhouse gas controlled release facility at an experimental agricultural station maintained by CSIRO Plant Industry in Canberra, Australia. The facility is designed to simulate surface emissions of CO2 and other greenhouse gases from the soil into the atmosphere. Over 10 different near surface monitoring techniques were trialled at the Ginninderra controlled release site during 2012-2013. These included soil gas, soil CO2 flux, soil analysis, eddy covariance, CO2 laser, noble gas tracers, airborne hyperspectral, in-field phenotyping (thermal, hyperspectral and 3D imaging), and microbial soil genomics. Result highlights are presented. Different climatic conditions for the early 2012 release experiment (wet) and late 2013 release experiment (dry) resulted in markedly different sub-surface plume behaviour and surface expression of CO2. The differences between the years are attributed to changes in groundwater levels and drier conditions leading to a larger vadose zone during the 2013 experiment.

The National Exposure Information System (NEXIS) is a unique modelling capability designed by Geoscience Australia (GA) to provide comprehensive and nationally-consistent exposure information in response to the 2003 COAG commitment to cost-effective, evidence-based disaster mitigation. Since its inception, NEXIS has continually evolved to fill known information gaps by improving statistical methodologies and integrating the best publically-available data. In addition to Residential, Commercial and Industrial building exposure information, NEXIS has recently expanded to include exposure information about agricultural assets providing a wider understanding of how communities can be affected by a potential event. GA's collaboration with the Attorney General's Department (AGD) has involved the consolidation of location-based data to deliver consistent map and exposure information products. The complex information requirements emphasised the importance of having all relevant building, demographic, economic, agriculture and infrastructure information in NEXIS available in a clear and unified Exposure Report to aid decision-makers. The Exposure Report includes a situational map of the hazard footprint to provide geographic context and a listing of detailed exposure information consisting of estimates for number and potential cost of impacted buildings by use, agricultural commodities and cost, the number and social vulnerability of the affected population, and the number and lengths of infrastructure assets and institutions. Developed within an FME workbench, the tool accepts hazard footprints and other report specifics as input before providing an HTML link to the final output in approximately 5 minutes. The consolidation of data and streamlining of exposure information into a simple and uniform document has greatly assisted the AGD in timely evidence-based decision-making during the 2014-15 summer season.

ARR is a series of national guidelines and datasets fundamental to flood estimation. The work is being completed by Engineers Australia and funded by the Australian Government through the National Flood Risk Information Project at Geoscience Australia. This flyer is for promoting the revision of ARR at the Hydrology & Water Resources Symposium (HWRS 2015) in Hobart in December 2015.

The DMCii Mosaic presents a sample of imagery acquired by Geoscience Australia under CC-BY Creative Commons Attribution 3.0 Australia licence. This imagery was captured by UK2-DMC satellite between December 2011 to April 2012 and has spatial resolution of 22 metres. Spectral bands are: Band 1 NIR; Band 2 Red; Band 3 Green. The DMCii Mosaic is displayed as a Pseudo Natural Colour Image.