This metadata relates to the ANUGA hydrodynamic modelling results for Busselton, south-west Western Australia. The results consist of inundation extent and peak momentum gridded spatial data for each of the ten modelling scenarios. The scenarios are based on Tropical Cyclone (TC) Alby that impacted Western Australia in 1978 and the combination of TC Alby with a track and time shift, sea-level rise and riverine flood scenarios. The inundation extent defines grid cells that were identified as wet within each of the modelling scenarios. The momentum results define the maximum momentum value recorded for each inundated grid cell within each modelling scenario. Refer to the professional opinion (Coastal inundation modelling for Busselton, Western Australia, under current and future climate) for details of the project.

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

40 years atmospheric reanalysis for Australia region. http://www.ecmwf.int/products/data/archive/descriptions/e4/index.html

This service provides Estimates of Geological and Geophysical Surfaces (EGGS). The data comes from cover thickness models based on magnetic, airborne electromagnetic and borehole measurements of the depth of stratigraphic and chronostratigraphic surfaces and boundaries.

X3D Model and Visualisation of the Hydrostratigraphic System in the Hodgson and Kings Creek Sub-Catchments

Demand for critical raw materials is expected to accelerate over the next few decades due to continued population growth and the shifting consumption patterns of the global economy. Sedimentary basins are important sources for critical raw materials and new discoveries of sediment–hosted Mississippi Valley–type (MVT) and/or clastic–dominated (CD) Zn–Pb deposits are likely required to mitigate future supply chain disruptions for Zn, Pb, Ag, Cd, Ga, Ge, Sb, and In. Herein we integrate public geoscience datasets using a discrete global grid to system to model the mineral potential for MVT and CD deposits across Canada, the United States of America, and Australia. Statistical analysis of the model results demonstrates that surface–wave tomography and derivative products from satellite gravity datasets can be used to map the most favourable paleo–tectonic settings of MVT and CD deposits inboard of orogenic belts and at the rifted edges of cratonic lithosphere, respectively. Basin development at pre–existing crustal boundaries was likely important for maintaining the low geothermal–gradients that are favourable for metal transport and generating the crustal fluid pathways that were reactivated during ore–formation, as suggested by the statistical association of both sediment–hosted mineral deposit types with the edges of upward–continued gravity and long–wavelength magnetic anomalies. Multivariate statistical analysis demonstrates that the most prospective combination of these geophysical datasets varies for each geological region and deposit type. We further demonstrate that maximum and minimum geological ages, coupled with Phanerozoic paleogeographic reconstructions, represent mappable proxies for the availability of oxidized, brine–generating regions that are the most likely source of ore–forming fluids (e.g., low– to mid–latitude carbonate platforms and evaporites). Ore deposition was likely controlled by interaction between oxidized, low–temperature brines and sulfidic and/or carbonaceous rocks, which, in some cases, can be mapped at the exposed surface or identified using the available rock descriptions. Baseline weights–of–evidence models are based on regional geophysics and are the least impacted by missing surface information but yield relatively poor results, as demonstrated by the low area–under–the–curve (AUC) for the spatially independent test set on the success–rate plot (AUC = 0.787 for MVT and AUC = 0.870 for CD). Model performance can be improved by: (1) using advanced methods that were trained and validated during a series of semi–automated machine learning competitions; and/or (2) incorporating geological and geophysical datasets that are proxies for each component of the mineral system. The best–performing gradient boosting machine models yield higher AUC for the test set (AUC = 0.983 for MVT and AUC = 0.991 for CD) and reduce the search space by >94%. The model results highlight the potential benefits of mapping sediment–hosted mineral systems at continental scale to improve mineral exploration targeting for critical raw materials.

This study brings together a wide range of datasets to provide a comprehensive assessment of the Pandurra Formation sedimentology and geochemistry in 3D. Sedimentology and geochemistry datasets generated this study are combined with pre-existing data to generate a 3D interpretation of the Pandurra Formation and improve understanding of how the Pandurra formation as we see it to today was deposited and subsequently post-depositionally mineralised.

This service provides Estimates of Geological and Geophysical Surfaces (EGGS). The data comes from cover thickness models based on magnetic, airborne electromagnetic and borehole measurements of the depth of stratigraphic and chronostratigraphic surfaces and boundaries.

<div>The Hastings River 5m Digital Elevation Model (DEM) is generated from all relevant data available on the Elvis - Elevation and Depth - Foundation Spatial Data (Elvis) platform with a resolution of 5 Metres or higher. Source datasets with a resolution higher than 5m have been resampled to 5m.</div><div>This elevation model is generated from a total of 1238 datasets sourced from multiple providers including State and Territory Governments. The capture dates for input data range from 2009/10/30 - 2018/07/15. See Table 1 below for further information.</div><div>The area covers the land mass of the Hastings River drainage basin as defined by the Bureau of Meteorology Geofabric. Near shore bathymetry data has also been included in the final raster.</div>

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