The aim of this document is to * outline the information management process for inundation modelling projects using ANUGA * outline the general process adopted by Geoscience Australia in modelling inundation using ANUGA * allow a future user to understand (a) how the input and output data has been stored (b) how the input data has been checked and/or manipulated before use (c) how the model has been checked for appropriateness

The aim of this document is to: * outline the general process adopted by Geoscience Australia in modelling tsunami inundation for a range of projects conducted in collaboration with Australian and State Government emergency management agencies * allow discoverability of all data used to generate the products for the collaborative projects as well as internal activities.

It is with great interest that we read the paper by Mueller (2015) who proposes that the majority of small pockmarks with diameters less than about 10 m on the northwest shelf of Australia may be of biotic origin, created by the fish Epinephelus, the Grouper. This hypothesis is based on a spatial association between pockmarks and Epinephelus at a number of sites on the northwest shelf and elsewhere around Australia, and on recent work undertaken on the habitats and observed behaviours of grouper fish in the Gulf of Mexico who excavate sediment from pre-existing solution cavities (Coleman et al., 2010; Wall et al., 2011). However, we contend that critical details have not been taken into account as part of Mueller's (2015) hypothesis, and additional consideration of existing geologic, geomorphic, sedimentologic and geochemical information is required. To make the science more robust, here we present a more comprehensive overview of the information available.

The Galilee Basin Hydrogeological Model is a numerical groundwater flow model of the Galilee subregion in Queensland, an area of approximately 300,000 square kilometres. The model encompasses the entire geological Galilee Basin as well as parts of the overlying Eromanga Basin and surficial Cenozoic sediments. The model includes aquifers that form part of the Great Artesian Basin (specifically those aquifers in the Eromanga Basin), a hydrogeological system of national significance (see Evans et al 2018). The development of the Galilee Basin Hydrogeological Model represented an ambitious, first-pass attempt to better understand potential regional-scale cumulative groundwater impacts of seven proposed coal mines in the Galilee Basin (as known circa 2014, see Lewis et al. 2014 for details). This work was commissioned as part of the bioregional assessment for the Galilee subregion (https://www.bioregionalassessments.gov.au/assessments/galilee-subregion). Geoscience Australia has made the flow model and associated datasets available to support further academic or research investigations within the region. Importantly though, due to a number of limitations and assumptions (outlined in the final model report, Turvey et al., 2015), the model is not suitable for decision-making in relation to water resource planning or management. Further, the model was not developed to predict potential groundwater impacts of any individual mining operations, but provides a regional cumulative development perspective. The groundwater model and associated report were produced by HydroSimulations under short-term contract to Geoscience Australia in 2015. The report is referenced in several products released as part of the bioregional assessment (BA) for the Galilee subregion. However, due to the size, complexity and limitations of this model, this model was not used as the primary groundwater modelling input for the Galilee BA. Further detail about the key modelling limitations and why it was unsuitable for use in the Galilee BA are outlined in the BA Groundwater modelling report (Peeters et al., 2018). References Evans T, Kellett J, Ransley T, Harris-Pascal C, Radke B, Cassel R, Karim F, Hostetler S, Galinec V, Dehelean A, Caruana L and Kilgour P (2018) Observations analysis, statistical analysis and interpolation for the Galilee subregion. Product 2.1-2.2 for the Galilee subregion from the Lake Eyre Basin Bioregional Assessment. Department of the Environment and Energy, Bureau of Meteorology, CSIRO and Geoscience Australia, Australia. http://data.bioregionalassessments.gov.au/product/LEB/GAL/2.1-2.2. Lewis S, Cassel R and Galinec V (2014) Coal and coal seam gas resource assessment for the Galilee subregion. Product 1.2 for the Galilee subregion from the Lake Eyre Basin Bioregional Assessment. Department of the Environment, Bureau of Meteorology, CSIRO and Geoscience Australia, Australia. https://www.bioregionalassessments.gov.au/assessments/12-resource-assessment-galilee-subregion. Peeters L, Ransley T, Turnadge C, Kellett J, Harris-Pascal C, Kilgour P and Evans T (2018) Groundwater numerical modelling for the Galilee subregion. Product 2.6.2 for the Galilee subregion from the Lake Eyre Basin Bioregional Assessment. Department of the Environment and Energy, Bureau of Meteorology, CSIRO and Geoscience Australia, Australia. http://data.bioregionalassessments.gov.au/product/LEB/GAL/2.6.2. Turvey C, Skorulis A, Minchin W, Merrick NP and Merrick DP (2015) Galilee Basin hydrogeological model Milestone 3 report for Geoscience Australia. Prepared by Heritage Computing Pty Ltd trading as Hydrosimulations. Document dated 16 November 2015. http://www.bioregionalassessments.gov.au/sites/default/files/galilee-basin-hydrological-model-pdf.pdf. <b>The model is available on request from clientservices@ga.gov.au - Quote eCat# 146155</b>

The aim of this document is to * outline the general process adopted by Geoscience Australia in modelling storm surge inundation for projects conducted in collaboration with Australian and State Government planning agencies * allow discoverability of all data used to generate the products for the collaborative projects as well as internal activities

As part of Geoscience Australia’s Exploring for the Future Program, Broadband and Audio Magnetotelluric (MT) data were acquired at 131 stations in the East Tennant region, Northern Territory, in 2019. This survey aimed to characterise major crustal structures, to map cover thickness to assist in stratigraphic drill targeting, and to help understand mineral potential in the region. The data package was released in December 2019 (http://dx.doi.org/10.26186/5df80d8615367) and the 3D resistivity model was released in March 2020 (https://pid.geoscience.gov.au/dataset/ga/135011). We applied a probabilistic approach to inverting high-frequency MT data for cover thickness estimation using the 1D Rj-McMCMT code, newly developed in Geoscience Australia. The inversion employs multiple Markov chains in parallel to generate an ensemble of millions of resistivity models that adequately fit the data given the assigned noise levels. The algorithm uses trans-dimensional Markov chain Monte Carlo techniques to solve for a probabilistic resistivity-depth model. Once the ensemble of models is generated, its statistics are analysed to assess the posterior probability distribution of the resistivity at any particular depth, as well as the number of layers and the depths of the interfaces. This stochastic approach gives a thorough exploration of the model space and a more robust estimation of uncertainty than deterministic methods allow. This release package includes the results of probabilistic inversion of Audio Magnetotelluric data at the 131 stations. They can be used to estimate cover thickness for drill site planning, and to map the base of geological basins in the region. Model data files are large, but can be made available on request to clientservices@ga.gov.au.

Communities and their economic activity rely heavily on critical infrastructure. Utility infrastructure facilities are usually comprised of a range of interconnected components characterised by varying degrees of operational criticality and vulnerability to earthquake ground motion. The severity of damage to these components in an earthquake has complex implications for post-event functionality, repair cost and recovery timeframe of facilities. This paper describes how an integration of physical component vulnerability, associated component functionality and a system model of the facility have been used to understand the seismic vulnerability and mitigation opportunities associated with a thermal power station. System behaviour of the facility has been analysed using a network model to evaluate facility performance and to assess component criticality. An application has been developed that integrates these elements in a Monte Carlo simulation that enables the outcomes of a broad set of events to be assessed, and is used to develop facility level fragility models. Finally, the benefits of this approach to the process of assessment of vulnerability of legacy assets and identification of mitigation opportunities are demonstrated.

The purpose of this study is to determine the potential of tsunami inundation from historical and potential submarine mass failures of the NSW coast based on the findings from the October 2006 Continental Slope Survey conducted by GA. The learnings from this study are intended for use by the Australian Tsunami Warning Project and NSW emergency managers.

The project modelled the tsunami inundation to selected sites in South East Tasmania based on a Mw 8.7 earthquake on the Puysegur Trench occurring at Mean Sea Level. As yet, there is no knowledge of the return period for this event. The project was done in collaboration with Tasmania State Emergency Services as part of a broader project that investigated tsunami history through palaeotsunami investigations. The intent was to build the capability of staff within Tasmania Government to undertake the modelling themselves. Formal modelling of the tsunami inundation occurred through national project funding.

The depth to Proterozoic basement surface was constructed in order to delineate the thickness of Phanerozoic and more recent cover material. The "basement" refers to the Neoproterozoic and older rocks underlying the Canning Basin. The 3D surface was constructed using GoCad software and constrained by drill-hole data, Euler depth solutions and forward modelling using magnetic data, and interpreted depths from three seismic lines crossing the Waukalycarly Embayment. The depth to basement surface should be used as a guide. With the exception of the drill-hole data, there are uncertainties involved in estimating the depths based on the magnetic methods (Euler depth solutions and forward modelling), as well as the seismic data.