Volcanic ash represents a serious hazard to communities living in the vicinity of active volcanoes in developing countries like Indonesia. Geoscience Australia, the Australia-Indonesia Facility for Disaster Reduction (AIFDR) and the Indonesian Centre for Volcanology and Geohazard Mitigation (CVGHM) have adapted an existing open source volcanic ash dispersion model for use in Indonesia. The core model is the widely used volcanic ash dispersion model FALL3D. A python wrapper has been developed, which simplifies the use of FALL3D for those with little or no background in computational modelling. An application example is described here for Gunung Ciremai in West Java, Indonesia. Scenarios were run using eruptive parameters within the acceptable range of possible future events for this volcano, granulometry as determined through field studies and a meteorological dataset that represented a complete range of possible wind conditions expected during the dry and rainy seasons for the region. Implications for varying degrees of hazard associated with volcanic ash ground loading on nearby communities for dry versus rainy season wind conditions is discussed. Communities located on the western side of Gunung Ciremai are highly susceptible to volcanic ash ground loading regardless of the season whereas communities on the eastern side are found to be more susceptible during the rainy season months than during the dry. This is attributed to prevailing wind conditions during the rainy season that include a strong easterly component. These hazard maps can be used for hazard and impact analysis and can help focus mitigation efforts on communities most at risk.

Severe wind has major impacts on exposed human settlements and infrastructure, while climate change is expected to increase the severe wind hazard in many regions of Australia. The Risk and Impact Analysis Group (RIAG) in Geoscience Australia (GA) has developed a series of techniques to analyse the impact of severe wind imposed on the residential buildings under current and future climate. The process includes four components: hazard, exposure, vulnerability and risk. Severe wind hazard represents site specific wind speed values for different return periods (e.g. 500-year, 2000-year return periods), which may be derived by the wind loading standard (AS/NZS 1170.2), or be a result of modelling for current or future climates. GA has developed a National Exposure Information System (NEXIS), a repository of spatial and structural information of infrastructure exposed and vulnerable to natural hazards. NEXIS has also been extended to consider the number of future residential structures by utilising simple spatial relationships. Using an expert evaluation process, GA has developed a series of fragility curves which relate wind speed to the expected level of damage to residential buildings (measured as a percentage of the total replacement cost) in specific regions in Australia. These curves include consideration of factors such as building location, age, roof material, wall material, and so on. Given a certain intensity of severe wind imposed on a certain type of residential building in a specific region, the physical impact to a community can be determined in terms of the economic loss and casualties. By applying above concepts and procedures, based on sample data from the selected cities, we have integrated these three components (hazard, residential buildings exposure and vulnerability) within a computational framework to derive severe wind risk under both current climate and for a range of climate scenarios. These processes will be utilised for the assessment of climate change adaptation strategies concerning structural wind loading.

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The term "Smartline" refers to a GIS line map format which can allow rapid capture of diverse coastal data into a single consistently classified map, which in turn can be readily analysed for many purposes. This format has been used to create a detailed nationally-consistent coastal geomorphic map of Australia, which is currently being used for the National Coastal Vulnerability Assessment (NCVA) as part of the underpinning information for understanding the vulnerability to sea level rise and other climate change influenced hazards such as storm surge. The utility of the Smartline format results from application of a number of key principles. A hierarchical form- and fabric-based (rather than morpho-dynamic) geomorphic classification is used to classify coastal landforms in shore-parallel tidal zones relating to but not necessarily co-incident with the GIS line itself. Together with the use of broad but geomorphically-meaningful classes, this allows Smartline to readily import coastal data from a diversity of differently-classified prior sources into one consistent map. The resulting map can be as spatially detailed as the available data sources allow, and can be used in at least two key ways: Firstly, Smartline can work as a source of consistently classified information which has been distilled out of a diversity of data sources and presented in a simple format from which required information can be rapidly extracted using queries. Given the practical difficulty many coastal planners and managers face in accessing and using the vast amount of primary coastal data now available in Australia, Smartline can provide the means to assimilate and synthesise all this data into more usable forms.

In 1994, the United Nations Regional Cartographic Conference for Asia and the Pacific resolved to establish a Permanent Committee comprising of national surveying and mapping agencies to address the concept of establishing a common geographic information infrastructure for the region. This resolution subsequently led to the establishment of the Permanent Committee for GIS Infrastructure for the Asia and Pacific (PCGIAP). One of the goals of the PCGIAP was to establish and maintain a precise understanding of the relationship between permanent geodetic stations across the region. To this end, campaign-style geodetic-GPS observations, coordinated by Geoscience Australia, have been undertaken throughout the region since 1997. In this presentation, we discuss the development of an Asia Pacific regional reference frame based on the PCGIAP GPS campaign data, which now includes data from 417 non-IGS GPS stations and provides long term crustal deformation estimates for over 200 GPS stations throughout the region. We overview and evaluate: our combination strategy with particular emphasis on the alignment of the solution onto the International Terrestrial Reference Frame (ITRF); the sensitivity of the solution to reference frame site selection; the treatment of regional co-seismic and post-seismic deformation; and the Asia-Pacific contribution to the International Association of Geodesy (IAG) Working Group on "Regional Dense Velocity Fields". The level of consistency of the coordinate estimates with respect to ITRF2005 is 6, 5, 15 mm, in the east, north and up components, respectively, while the velocity estimates are consistent at 2, 2, 6 mm/yr in the east, north and up components, respectively.

The development of the Indian Ocean Tsunami Warning and mitigation System (IOTWS) has occurred rapidly over the past few years and there are now a number of centres that perform tsunami modelling within the Indian Ocean, both for risk assessment and for the provision of forecasts and warnings. The aim of this work is to determine to what extent event-specific tsunami forecasts from different numerical forecast systems differ. This will have implications for the inter-operability of the IOTWS. Forecasts from eight separate tsunami forecast systems are considered. Eight hypothetical earthquake scenarios within the Indian Ocean and ten output points at a range of depths were defined. Each forecast centre provided, where possible, time series of sea-level elevation for each of the scenarios at each location. Comparison of the resulting time series shows that the main details of the tsunami forecast, such as arrival times and characteristics of the leading waves are similar. However, there is considerable variability in the value of the maximum amplitude (hmax) for each event and on average, the standard deviation of hmax is approximately 70% of the mean. This variability is likely due to differences in the implementations of the forecast systems, such as different numerical models, specification of initial conditions, bathymetry datasets, etc. The results suggest that it is possible that tsunami forecasts and advisories from different centres for a particular event may conflict with each other. This represents the range of uncertainty that exists in the real-time situation.

In many areas of the world, vegetation dynamics in semi-arid floodplain environments have been seriously impacted by increased river regulation and groundwater use. In this study, the condition of two of Australia's iconic riparian and floodplain vegetation elements, River Red Gums (Eucalyptus camaldulensis) and Black Box (E. largiflorens) are examined in relation to differing hydraulic regimes. With increases in regulation along Murray-Darling Basin rivers, flood volume, seasonality and frequency have changed which has in turn affected the condition and distribution of vegetation. Rather than undertaking a field based assessment of tree health in response to current water regimes, this paper documents a remote sensing study that assessed historic response of vegetation to a range of different climatic and hydraulic regimes at a floodplain scale. This methodology innovatively 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 (e.g. stand of closed forest) for each Landsat scene. Consequently long-term temporal change in vegetation condition was assessed against different water regimes (drought, local rainfall, river bank full, overbank flow, and lake filling). Results provide insight into vegetation response to different water sources and overall water availability. Additionally, some inferences can be made about lag times associated with vegetation response and the duration of the response once water availability has declined (e.g. after floodwaters recede). This methodology should enable water managers to better assess the adequacy of environmental flows.

Abstract for AMSA Conference

This study of drillcore materials was carried out to assess the ability of hyperspectral methods to rapidly map the distribution of key minerals pertinent to managed aquifer recharge studies in the Darling floodplain. The study used two hyperspectral instruments: the Hylogger core scanner (using an instrument at DMITRE Minerals in Adelaide); and the Portable Infrared Mineral Analyser (PIMA). Further validation of the methods was carried out using XRD analysis of selected samples. Cores were obtained using the sonic drilling method. The Hylogger tool qualitatively mapped the distribution of clays and oxides in both the confining aquitard and key aquifers. The unconfined Coonambidgal Formation aquifer is dominated by montmorillonite, and the Blanchetown Clay aquitard by kaolinite with lesser montmorillonite. Clay mineralogy in the Calivil Formation aquifer is related to sedimentary facies, with kaolinite and lesser nontronite in muddy units, and kaolinite-dominant or smectite-dominant clays in sandy units. The two clay mineral associations were found to correlate with different hydraulic conductivity trends in the NMR data from the aquifer. These trends have been defined by the Kernel Function of Nuclear Magnetic Resonance (NMR)-derived hydraulic conductivity data. Kernel Functions (C values) of 6,200 corresponding with predominantly smectites in the screened aquifer interval, and C values of 46,000 corresponding with kaolinite in the screened aquifer intervals of two holes. This made it possible to predict the dominant clay in the screened aquifer intervals in the remaining NMR-logged holes. These predictions were tested using PIMA analysis of the clay mineralogy of addition from NMR-logged holes. Of 97 PIMA scans, 67 contained the predicted mineralogy and 27 did not, giving a success rate of 69%, providing reasonable confidence that the Kernal Function in the NRM logging can be explained by the clay mineralogy. Overall, this study demonstrates that hyperspectral logging can provide relatively rapid, semi-quantitative data on the abundance and distribution of clay and oxide mineralogy in drillcore. These data assisted with geochemical modelling and risk assessments at the Jimargil aquifer storage and recovery (ASR) site.

Nuclear Magnetic Resonance (NMR) tools have been used for decades by the oil industry to study lithological properties in consolidated sedimentary materials. Recently, slimline NMR borehole logging systems have been developed specifically for the study of near-surface (<100m) groundwater systems. In this study of unconsolidated fluvial sediments in the Darling River floodplain, data were acquired downhole every 0.5 m using a Javelin NMR tool. A total of 26 sonic cored bores were logged to a depth of ~70 m. Hydraulic conductivity (KNMR) can be estimated from the NMR measurements using the Schlumberger-Doll Research Equation: KNMR = C x -2 x T2ML2, where is the NMR porosity, T2ML is the logarithmic mean of the T2 distributions, and C is a formation factor related to tortuosity. To this end, the NMR data were classified into five hydraulic classes ranging from clay to gravely-coarse sand using the core, geophysical, mineralogical, and hyperspectral logs. Borehole slug tests were conducted to provide constraints on the K and T of the aquifers. Least-squares inversion was used to solve for the optimum C values versus the slug test derived T for the aquifer material (medium to gravely sand). Laboratory permeameter measurements helped constrain the C values of fine textured sediment. Comparisons between the geophysics derived KNMR and slug test KSlug indicated correspondence within two orders of magnitude. Investigations were also carried out to compare measurements of water content between laboratory determinations (oven drying of wet sediment at 105 oC) and that derived from NMR bore log data. A systematic decrease in ratio between the NMR total water and gravimetric water with fining of texture is observed. This is in part due to the inter-echo spacing of the NMR instrument (2.5 ms), which may be too large to detect hydroscopic moisture. Differences observed between NMR free water and gravimetric water within the sands requires further investigation, including the potential influence of iron phase coating of grains on fast relaxation responses. Overall, the borehole NMR method provides logging of near-continuous variations in K through a saturated sedimentary sequence, providing useful K estimates at increments not achievable using traditional aquifer testing, as well as K estimates for aquitard material.