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 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.

Four data formats are available for download, three vector (e00, mif, shp) and one raster (ecw).

Mean monthly and mean annual areal actual, areal potential and point potential evapotranspiration grids. The grids show the evapotranspiration 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 grid point resolution of the data is 0.1 degrees ( approximately 10km). As part of the 3-D analysis process a 0.1 degree resolution digital elevation model (DEM) was used. Approximately 700 stations were used in the analysis, and all input station data underwent a high degree of quality control before analysis, and conform to WMO (World Meteorological Organisation) standards for data quality. Areal Actual ET is the ET that actually takes place, under the condition of existing water supply, from an area so large that the effects of any upwind boundary transitions are negligible and local variations are integrated to an areal average. Areal Potential ET is the ET that would take place, under the condition of unlimited water supply, from an area so large that the effects of any upwind boundary transitions are negligible and local variations are integrated to an areal average. Point Potential ET is the ET that would take place, under the condition of unlimited water supply, from an area so small that the local ET effects do not alter local airmass properties. It is assumed that latent and sensible heat transfers within the height of measurement are through convection only. The above definitions are based on those given by Morton (1983), but we have used the term areal potential ET for Mortons wet-environment ET and the term point potential ET for Mortons potential ET. Morton, F.I. (1983). Operational estimates of areal evapotranspiration and their significance to the science and practice of hydrology. Journal of Hydrology, 66: 1-76.

This paper presents the application of a neural network methodology to historical time series of GPS data from the global GPS network, based on terrestrial water storage information. Hydrology signals at the global GPS sites are important for including water loading corrections in GPS data processing. However, it is quite common that a correct global water storage model may not be available for this purpose, due to lack of science data. It is therefore mostly assumed that water mass redistribution is one of the potential contributors to the seasonal variations in GPS station position results, particularly, in the vertical direction. Presently, the IERS Special Bureau for Hydrology (SBH) has archived continental water storage data from some of the latest model developments. Examples include the monthly (GRACE, NOAA CPC, NCEP/NCAR CDAS-1) and daily (NCEP/NCAR and ECMWF reanalyses) solutions. It is valuable to study the relationship between these solutions and long-term geodetic results, especially as the water storage models continue to be refined. Using neural networks offers an effective approach to correlate the non-linear input of hydrology signals and output of geodetic results by recognizing the historic patterns between them. In this study, a neural network model is developed to enable the prediction of GPS height residuals based on the input of NOAA CPC hydrology data. The model is applied to eight global GPS sites with satisfactory results.

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.

Shows the boundaries of the Australian basins as defined by the Agriculture and Resource Management Council of Australia and New Zealand (ARMCANZ). This data shows boundary and attribute information for 12 divisions, 77 regions and 245 basins. It also contains, for each basin, information relating to its individual basin/region/division name and number. State borders are also included in the data. Data for Division XIII Distant Islands Division is not included. These basins are the primary building block for the collection of national hydrologic data and the assessment of water resources. Data are suitable for GIS applications. Free online download. Available in ArcView Shapefile and MapInfo mid/mif. Product Specifications Coverage: Australia Currency: June 1997 Coordinates: Geographical Datum: AGD66 Format: ArcInfo Export, ArcView Shapefile and MapInfo mid/mif Medium: Free online and CD-ROM (fee applies)

This dataset was created for the National Geochemical Survey of Australia (NGSA) to help determine the location of target sites for sampling catchment outlet sediments in the lower reach of defined river catchments. Each polygon represents a surface drainage catchment derived from a national scale 9 second (approximately 250 m) resolution digital elevation model. Catchments were extracted from an unpublished, interim version of a nested catchment framework with an optimal catchment area of 5000 km2. Only catchments from the Australian mainland and Tasmania were included. In order to generate catchments approaching the optimal area, catchments with an area of less than 1000 km2 were excluded from the dataset, while other small catchments were amalgamated, and catchments much larger than 5000 km2 were split.

This specification describes the aggregation of jurisdictional data that is maintained by Geoscience Australia. Currently this data is made up of a mixture of scale ranging from 1:25,000 to 1:250,000 across the continent.