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.

The combination of anthropogenic activity and climate variability has resulted in changes to hydrologic regimes across the globe. Changes in water availability impact on vegetation structure and function, particularly in semi-arid landscapes. Riparian and floodplain vegetation communities are sensitive to changes to surface-water and groundwater availability in these water-limited landscapes. Remote-sensing multi-temporal methods can be used to detect changes in vegetation at a regional to local scale. In this study, a `best-available pixel' approach was used to represent dry-season, woody-vegetation-canopy characteristics inferred from Normalised Difference Vegetation Index (NDVI). This paper describes a method in which Landsat 5 TM and Landsat 7 ETM+ data from 1987 to 2011 were processed using object-based image-analysis techniques to generate annual minimum NDVI values for vegetation communities in the Lower-Darling floodplain The changes detected in riparian and floodplain canopies over time can then be integrated with other spatial data to identify water-source dependence and infer a relationship between changes to the hydrologic characteristics of specific water sources and vegetation dynamics.

This service provides Australian surface hydrology, including natural and man-made features such as water courses (including directional flow paths), lakes, dams and other water bodies. The information was derived from the Surface Hydrology database, with a nominal scale of 1:250,000. The National Basins and Catchments are a national topographic representation of drainage areas across the landscape. Each basin is made up of a number of catchments depending on the features of the landscape. This service shows the relationship between catchments and basins. The service contains layer scale dependencies.

Mean monthly and mean annual rainfall grids. The grids show the rainfall values across Australia in the form of two-dimensional array data. The mean data are based on the standard 30-year period 1961-1990. Gridded data were generated using the ANU (Australian National University) 3-D Spline (surface fitting algorithm). The resolution of the data is 0.025 degrees ( approximately 2.5km) - as part of the 3-D analysis process a 0.025 degree resolution digital elevation model (DEM) was used. Approximately 6000 stations were used in the analysis over Australia. All input station data underwent a high degree of quality control before analysis, and conform to WMO (World Meteorological Organisation) standards for data quality.

Subtitle: Behind the Scenes of Geofabric Version 3 Pilot & the Future of Geospatial Surface Water Information The Bureau of Meteorology's Australian Hydrological Geospatial Fabric (Geofabric) was established in 2008 as the spatial information database to support water accounting and resource assessment mandated under the Water Act 2007. Foundation layers for Geofabric versions 1 and 2 were developed from 1:250K streamline data and the 9 second resolution national DEM. The uses of the Geofabric data have expanded to new disciplines and have resulted in increased demand for finer national resolution. Version 3 of the Geofabric is now under development in a collaborative project between Geoscience Australia, CSIRO, Australian National University (ANU) and the Bureau of Meteorology. The foundation inputs for Geofabric version 3 are based on the integrated national surface hydrology dataset which uses the best available scale data from the jurisdictions and the 1 second resolution SRTM DEM. This significant enhancement presents both challenges and opportunities. This presentation at the Surveying & Spatial Sciences Institute (SSSI) ACT Region conference on 16 August 2013 aims to show the work being undertaken in the pilot areas of the Namoi and Murrumbidgee River Regions.

Mean monthly and mean annual maximum, minimum & mean temperature grids. The grids show the temperature values across Australia in the form of two-dimensional array data. The mean data are based on the standard 30-year period 1961-1990. Gridded data were generated using the ANU (Australian National University) 3-D Spline (surface fitting algorithm). As part of the 3-D analysis process a 0.025 degree resolution digital elevation model (DEM) was used. The grid point resolution of the data is 0.025 degrees (approximately 2.5km). Approximately 600 stations were used in the analysis over Australia. All input station data underwent a high degree of quality control before analysis, and conform to WMO (World Meteorological Organisation) standards for data quality.

This service provides Australian surface hydrology, including natural and man-made features such as water courses (including directional flow paths), lakes, dams and other water bodies. The information was derived from the Surface Hydrology database, with a nominal scale of 1:250,000. The service contains layer scale dependencies.

The purpose of this paper is to investigate and quantify the accuracy with which hydrological signals in the Murray-Darling Basin, southeast Australia can be estimated from GRACE. We assessed the extent to which the Earth's major geophysical processes contaminate the gravitational signals in the Basin. Eighteen of the world's largest geophysical processes which generate major gravitational signals (e.g. melting of the Greenland icesheet, hydrology in the Amazon Basin) were simulated and the proportion of the simulated signal detected in the Murray - Darling Basin was calculated. The sum of the cumulative effects revealed a maximum of ~4 mm (equivalent water height) of spurious signal was detected within the Murray - Darling Basin; a magnitude smaller than the uncertainty of the basin-scale estimates of changes in total water storage. Thus, GRACE products can be used to monitor broad scale hydrologic trends and variability in the Murray-Darling Basin without the need to account for contamination of the estimates from external geophysical sources.

Contains a medium scale vector representation of the topography of Australia. The data include the following themes: Hydrography - drainage networks including watercourses, lakes, wetlands, bores and offshore features; Infrastructure - constructed features to support road, rail and air transportation as well as built-up areas, localities and homesteads. Utilities, pipelines, fences and powerlines are also included; Relief - features depicting the terrain of the earth including 50 metre contours, spot heights, sand dunes, craters and cliffs; Vegetation - depicting forested areas, orchards, mangroves, pine plantations and rainforests; and Reserved Areas - areas reserved for special purposes including nature conservation reserves, aboriginal reserves, prohibited areas and water supply reserves.

The 1 second Shuttle Radar Topographic Mission (SRTM) derived smoothed Digital Elevation Model (DEM-S) Version 1.0 is a 1 arc second (~30m) gridded smoothed version of the DEM (ANZCW0703013355). The DEM-S represents ground surface topography, excluding vegetation features, and has been smoothed to reduce noise and improve the representation of surface shape. The dataset was derived from the 1 second Digital Elevation Model Version 1.0 (DSM; ANZCW0703013336) by an adaptive smoothing process that applies more smoothing in flatter areas than hilly areas, and more smoothing in noisier areas than in less noisy areas. This DEM-S supports calculation of local terrain shape attributes such as slope, aspect and curvatures that could not be reliably derived from the unsmoothed DEM because of noise. A full description of the methods is in progress (Gallant et al., in prep) and in the User Guide (Geoscience Australia & CSIRO, 2010).