The Surface Hydrology Points (Regional) dataset provides a set of related features classes to be used as the basis of the production of consistent hydrological information. This dataset contains a geometric representation of major hydrographic point elements - both natural and artificial. This dataset is the best available data supplied by Jurisdictions and aggregated by Geoscience Australia it is intended for defining hydrological features.

This service has been created specifically for display in the National Map and the symbology displayed may not suit other mapping applications. Information included within the service includes the polygon/area locations for surface hydrology, including natural and man-made features such as water courses (including directional flow paths), lakes, dams and other water bodies and marine themes. The data is sourced from Geoscience Australia 250K Topographic data and Surface Hydrology data. The service contains layer scale dependencies.

We present a multifaceted hydrogeological investigation of the McBride and Nulla basalt provinces in the Upper Burdekin region, north Queensland. The project aims to better understand their key groundwater system processes to inform future development and water management decisions. This work, carried out as part of the Exploring for the Future Upper Burdekin Groundwater Project, has shown that basalt aquifers in each province are typically unconfined where monitored. Groundwater recharge is widespread but highly variable, largely occurring within the boundaries of the basalt provinces. Groundwater salinity based on electrical conductivity is <1000 μS/cm in the McBride Basalt Province (MBP) and up to 2000 μS/cm in the Nulla Basalt Province (NBP). Groundwater levels have been declining since 2011 (following major flooding in Queensland), showing that the study period covers a small fraction of a longer-functioning dynamic groundwater system. The basalt provinces contain distinct lava flows, and the degree of hydraulic connectivity between them is unclear. Despite similarities in their rock properties, the geometry of lava emplacement leads to different groundwater flow regimes within the two basalt provinces. Radial flow away from the central high elevations towards the edges is characteristic of the MBP, while regional flow from west to east dominates the NBP. Basalt aquifers in both provinces support a range of groundwater-dependent ecosystems, such as springs, some of which sustain flow in tributaries of the Burdekin River. Where streams intersect basalt aquifers, this also results in direct groundwater discharge. Springs and perennial tributaries, particularly emanating from the MBP, provide important inflows to the Burdekin River, especially in the dry season. This work has highlighted that management of MBP and NBP groundwater sources is crucial for maintaining a range of environmental assets in the region and for ensuring access for existing and future users. <b>Citation:</b> Ransley, T.R., Dixon-Jain, P., Cook, S.B., Lai, E.C.S., Kilgour, P., Wallace, L., Dunn, B., Hansen, J.W.L. and Herbert, G., 2020. Hydrogeology of the McBride and Nulla basalt provinces in the Upper Burdekin region, north Queensland. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

Comprises a national satellite imagery mosaic and derived information products produced by a collaboration of CSIRO, Geoscience Australia (GA) and State and Territory Surveys, and several additional national and international collaborators. Mineral products were derived using a validated mosaic of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. <b>Value: </b>The data are used to understand distributions of and changes in surface materials and assessment of environmental, agricultural and resource potential. <b>Scope: </b>This dataset covers the continent with the intent to provide the best quality mosaic from 10+ year archive of scenes across Australia (i.e., lowest cloud/vegetation cover, high sun angle etc)

This web service delivers data from an aggregation of sources, including several Geoscience Australia databases (provinces (PROVS), mineral resources (OZMIN), energy systems (AERA, ENERGY_SYSTEMS) and water (HYDROGEOLOGY). Information is grouped based on a modified version of the Australian Bureau of Statistics (ABS) 2021 Indigenous Regions (IREG). Data covers population centres, top industries, a regional summary, groundwater resources and uses, energy production and potential across six sources and two energy storage options. Mineral production and potential covers 36 commodities that are grouped into 13 groups.

Background These are the statistics generated from the DEA Water Observations (Water Observations from Space) suite of products, which gives summaries of how often surface water was observed by the Landsat satellites for various periods (per year, per season and for the period from 1986 to the present). Water Observations Statistics (WO-STATS) provides information on how many times the Landsat satellites were able to clearly see an area, how many times those observations were wet, and what that means for the percentage of time that water was observed in the landscape. What this product offers Each dataset in this product consists of the following datasets: - Clear Count: how many times an area could be clearly seen (i.e. not affected by clouds, shadows or other satellite observation problems) - Wet Count: how many times water was detected inobservations that were clear - Water Summary: what percentage of clear observations were detected as wet (i.e. the ratio of wet to clear as a percentage) As no confidence filtering is applied to this product, it is affected by noise where misclassifications have occurred in the input water classifications, and can be difficult to interpret on its own. The confidence layer and filtered summary are contained in the Water Observations Filtered Statistics (WO-FILT-STATS) product, which provides a noise-reduced view of the all-of-time water summary. WO-STATS is available in multiple forms, depending on the length of time over which the statistics are calculated. At present the following are available: WO-STATS:statistics calculated from the full depth of time series (1986 to present) WO-STATS-ANNUAL:statistics calculated from each calendar year (1986 to present) WO-STATS-NOV-MAR:statistics calculated yearly from November to March (1986 to present) WO-STATS-APR-OCT:statistics calculated yearly from April to October (1986 to present)

Following the drilling of a shallow natural CO₂ reservoir at the Qinghai research site, west of Haidong, China, it was discovered that CO₂ was continuously leaking from the wellbore due to well-failure. The site has become a useful research facility in China for studying CO₂ leakage and monitoring technologies for application to geological storage sites of CO₂. During an eight day period in 2014, soil gas and soil flux surveys were conducted to characterise the distribution, magnitude and likely source of the leaking CO₂ . Two different sampling patterns were utilised during soil flux surveys. A regular sampling grid was used to spatially map out the two high-flux zones which were located 20–50 m away from the wellhead. An irregular sampling grid, with higher sampling density in the high-flux zones, allowed for more accurate mapping of the leak distribution and estimation of total field emission rate using cubic interpolation. The total CO₂ emission rate for the site was estimated at 649-1015 kgCO₂/d and there appeared to be some degree of spatial correlation between observed CO₂ fluxes and elevated surface H₂O fluxes. Sixteen soil gas wells were installed across the field to test the real-time application of Romanak et al.’s (2012) process-based approach for soil gas measurements (using ratios of major soil gas components to identify the CO₂ source) using a portable multi-gas analyser. Results clearly identified CO₂ as being derived from one exogenous source, and are consistent with gas samples collected for laboratory analysis. Carbon-13 isotopes in the centre of each leak zone (−0.21‰ and −0.22‰) indicate the underlying CO₂ is likely sourced from the thermal decomposition of marine carbonates. Surface soil mineralisation (predominantly calcite) can be used to infer prior distribution of the CO₂ hotspots and as a consequence highlighted plume migration of 20m in 11 years. The broadening of the affected area beyond the wellbore at the Qinghai research site markedly increases the area that needs surveying at sufficient density to detect a leak. This challenges the role of soil gas and soil flux in a CCS monitoring and verification program for leak detection, suggesting that these techniques may be better applied for characterising the source and emission rate of a CO₂ leak, respectively. <b>Citation:</b> I.F. Schroder, H. Zhang, C. Zhang, A.J. Feitz, The role of soil flux and soil gas monitoring in the characterisation of a CO2 surface leak: A case study in Qinghai, China, International Journal of Greenhouse Gas Control, Volume 54, Part 1, 2016, Pages 84-95, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2016.07.030.

The Surface Hydrology Lines (National) dataset presents the spatial locations of surface hydrology line features and its attributes. The dataset represents the Australia's surface hydrology at a national scale. It includes natural and man-made geographic features such as: watercourses, canals, pipelines, etc. This product presents line hydrology features with full topological connectivity and flow paths for the entire continental of Australia.

Digital elevation models (DEMs) reflect the morphology of landscape surfaces and attributes derived from these models, including slope, aspect, relief and topographic wetness index. DEMs have broad application in geomorphology, geology, hydrology, ecology and climatology. Here, we consider two important terrain attributes: topographic position index and topographic ruggedness. Topographic position index measures the topographic slope position of landforms. It compares the mean elevation of a specific neighbourhood area with the elevation value of a central cell. This is done for every cell or pixel in the DEM to derive the relative topographic position (e.g. upper, middle, lower landscape elements). Ruggedness refers to the roughness of the surface and is calculated as the standard deviation of elevations. Both these terrain attributes are scale dependent and will vary according to the size of the analysis window. Here, we generated a multiscale topographic position model over the Australian continent using a 3-second resolution (~90 m) DEM derived from the Shuttle Radar Topography Mission. The algorithm calculates topographic position scaled by the corresponding ruggedness across three spatial scales (window sizes): 0.2–8.1 km, 8.2–65.2 km and 65.6–147.6 km. The derived ternary image captures variations in topographic position across these spatial scales, giving a rich representation of nested landform features, with broad application to understanding geomorphological and hydrological processes, and mapping regolith and soils. <b>Citation:</b> Wilford, J., Basak, S. and Lindsay, J., 2020. Multiscale topographic position image of the Australian continent. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

Analysis Ready Data (ARD) are satellite data that have been pre-processed for immediate analysis with minimal user effort. The generation of Surface Reflectance (SR) from optical satellite data, involves a series of corrections to standardise the data and enable meaningful comparison of data from multiple sensors and across time. Surface reflectance data are foundational for time-series analyses and rapid generation of other information products. Field based validation of surface reflectance data is therefore critical to determine its fitness for purpose, and applicability for downstream product development. In this paper, an approach for continental scale validation of the surface reflectance data from Landsat-8 and Sentinel-2 satellites, using field-based measurements that are near-synchronous to the satellite observations over multiple sites across Australia is presented. Good practice measurement protocols governing the acquisition of field data, including field instrument calibration, sampling strategy and approach for post-collection processing and management of field spectral data are outlined. This study has been a nationally coordinated, collaborative field data collection campaign across Australia. Permanent field sites, to support validation efforts within the broader Earth Observation (EO) community for continental scale products were also identified. The approach is expected to serve as a model for coordinated ongoing validation of ARD products at continental to global scales. Presented at the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)