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.

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 document describes a structure for exchanging information to assist discovery and retrieval/transfer of flood information, including GIS flood mapping data. The draft class model represents metadata, data and summary information that supports the goals of the National Flood Risk Information Project (NFRIP) to improve the quality, consistency and accessibility of flood information. This document describes the data model that will be used to create an application schema.

This record has been created for Sales to be able to invoice data requests that occur from downloading of data from the National Elevation Data Framework (NEDF) Web Portal. The Portal was set up in 2010 and data more than 400MB needs to be downloaded from the holding pen on the NEDF server and copied onto media and sent to the requester. Each data request will come with metadata and the appropriate data licence.

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.

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

The AusHydro database provides a seamless surface hydrography layer for Australia at a nominal scale of 1:250,000. It consists of lines, points and polygons representing natural and man-made features such as water courses, lakes, dams and other water bodies. The natural water course layer consists of a linear network with a consistent topology of links and nodes that provide directional flow paths through the network for hydrological analysis. This network was used to produce the National 9 second Digital Elevation Model (DEM) of Australia (http://www.ga.gov.au/nmd/products/digidat/dem_9s.jsp). Surface Hydrology Dataset is an amalgamation of two primary datasets. The first is the hydrographic component of the GEODATA TOPO 250K Series 3 product released by Geoscience Australia in 2006 . The Series 3 dataset contains the following hydrographic features: canal lines, locks, rapid lines, spillways, waterfall points, bores, canal areas, flats, lakes, pondage areas, rapid areas, reservoirs, springs, watercourse areas, waterholes, water points, marine hazard areas, marine hazard points and foreshore flats.It also provides information on naming, hierarchy and perenniality. The dataset also contains Cultural and Transport features that may intersect with hydrography features. These include: Railway Tunnels, Rail Crossings, Railway Bridges, Road Tunnels, Road Bridges, Road Crossings, Water Pipelines. Refer to the GEODATA TOPO 250K Series 3 User Guide http://www.ga.gov.au/image_cache/GA8349.pdf for additonal information The second primary dataset is based on the GEODATA TOPO-250K Series 1 water course lines completed by Geoscience Australia in 1994, which has been supplemented by additional line work captured by the Australian National University during the production of the 9 second DEM to improve the representation of surface water flow. This natural watercourse dataset consists of directional flow paths and provides a direct link to the flow paths derived from the DEM. There are approximately 700,000 more line segments in this version of the data. AusHydro 1.0 uses the natural watercourse geometry from the ANU-enhanced Series 1 data, and the attributes (names, perenniality and hierarchy) associated with Series 3 to produce a fully attributed data set with topologically correct flow paths. The attributes from Series 3 were attached using spatial queries to identify common features between the 2 datasets. Additional semi-automated and manual editing was then undertaken to ensure consistent attribution along the entire network. WatercourseLines includes a unique identifier for each line segment (AusHydro-ID) which will be used to maintain the dataset, and to incorporate higher resolution datasets in the future. The AusHydro-ID will be linked to the ANUDEM-Derived (raster) streams through a common segment identifier, and ultimately to a set of National Catchments and Reporting Units (NCRU). Purpose Surface Hydrology Dataset is the reconciliation of the hydrological features in the two data sets to produce a single authoritative national stream network and water body data set suitable for hydrological analysis at national scales. It uses the natural watercourse geometry from the ANU-enhanced Series 1 data, and the attributes (names, perenniality and hierarchy) associated with Series 3 to produce a fully attributed data set with topologically correct flow paths.

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 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 Environmental Arttibutes Database is a set of lookup tables supplying attributes describing the natural and anthropogenic characteristics of the stream and catchment environment that was developed by the Australian National University (ANU) in 2011. The data is supplied as part of the supplementary Geofabric products which is associated with the 9 second DEM derived streams and the National Catchment Boundaries based on 250k scale stream network. Please consult the spreadsheet below for details of the attributes and their source data.