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 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.

Floodplain vegetation can be degraded from both too much and too little water due to regulation. Over-regulation and increased use of groundwater in these landscapes can exacerbate the effects related to natural climate variability. Prolonged flooding of woody plants has been found to induce a number of physiological disturbances such as early stomatal closure and inhibition of photosynthesis. However drought conditions can also result in leaf biomass reduction and sapwood area decline. Depending on the species, different inundation and drought tolerances are observed. This paper focuses specifically on differing lake level management practices in order to assess associated environmental impacts. In western NSW, two Eucalyptus species, River Red Gum (E. camaldulensis) and Black Box (E. largiflorens) have well documented tolerances and both are located on the fringes of lakes in the Menindee Lakes Storage Water scheme. Flows to these lakes have been controlled since 1960 and lake levels monitored since 1979. Pre-regulation aerial photos indicate a significant change to the distribution of lake-floor and fringing vegetation in response to increased inundation frequency and duration. In addition, by coupling historic lake water-level data with a Landsat satellite imagery, spatial and temporal vegetation response to different water regimes has been observed. Two flood events specifically investigated are the 2010/11 and 1990 floods. Results from this analysis provide historic examples of vegetation response to lake regulation including whether recorded inundation duration and frequency resulted in positive or negative impacts, the time delay till affects become evident, duration of observed response and general recovery/reversal times. These findings can be used to inform ongoing water management decisions.

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.

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.

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.

The 9 second DEM derived streams are a a fully connected and directed stream network produced in rastor and vector fomats by Australian National University. This product is the raster format, for the the vector product please refer to the Bureau of Meterology's Geofabric Website (http://www.bom.gov.au/water/geofabric/index.shtml). It is built upon the representation of surface drainage patterns provided by the GEODATA national 9 second Digital Elevation Model (DEM) Version 3 (ANU Fenner School of Environment and Society and Geoscience Australia, 2008).

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.

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 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.