Topography. 30 metre Digital Elevation Model (DEM). This layer was merged, clipped and reprojected by CeRDI (Federation University Australia). Elevation data originally sourced from Geoscience Australia's Elevation Information System (ELVIS).

The National Digital Elevation Model (DEM) 1 Second Hydrologically Enforced product, derived from the National DEM SRTM 1 Second and National Watercourses, lakes and Reservoirs.

Topography. 30 metre Digital Elevation Model (DEM). This layer was merged, clipped and reprojected by CeRDI (Federation University Australia). A coloured-relief map was generated and rendered as an RGB GeoTIFF. Elevation data originally sourced from Geoscience Australia's Elevation Information System (ELVIS).

The National Digital Elevation Model (DEM) 1 Second Hydrologically Enforced product, derived from the National DEM SRTM 1 Second and National Watercourses, lakes and Reservoirs.

Filled DEM, Lake Victoria Region, raster, 2000 Reference Information and Units: GCS: WGS 1984 EPSG:102024 (Lambert Conformal Conic Africa) Pixel Size: ~30 meters File Naming Convention: LV_DEM_30_m_hydro Data Origin: SRTM GL1: NASA Shuttle Radar Topography Mission Global 1 arc second V003 Sensor: SRTM Data Description: NASA Shuttle Radar Topography Mission (SRTM) datasets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. The purpose of SRTM was to generate a near-global digital elevation model (DEM) of the Earth using radar interferometry. SRTM was a primary component of the payload on the Space Shuttle Endeavour during its STS-99 mission. Endeavour launched February 11, 2000 and flew for 11 days. SRTM collected data in swaths, which extend from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km). These swaths are ~225 km wide, and consisted of all land between 60° North (N) and 56° South (S) latitude. This accounts for about 80% of Earth’s total landmass. More information can be found in the metadata pdf

The Gippsland Lakes are a large coastal lagoon system in Victoria with major settlements on their shores and a potential inundation area of over 700sq km. A digital elevation model (DEM) of the Gippsland Lakes was developed in 2002 to support flood level estimation. The ANUDEM program, produced by the Centre for Resource and Environmental Studies at the Australian National University was used to produce the DEM from a comprehensive range of data sources including digitised contours from aerial photogrammetry and survey data from local authorities . The Gippsland Lakes DEM provides a digital description of the terrain surface lying below 5 metres on the Australian Height Datum (AHD), including the bathymetry of the lakes, and gives continuous elevation values over the entire study domain. The DEM provides a useful tool for extracting cross-sections of model input, computing storage volumes for confined areas and displaying computed flood extents. The DEM has been developed for use in modeling high flow events and should not be used to assess inundations patterns under low flow conditions.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

DEPI originally engaged GHD to develop seamless 3D aquifer surfaces for the Victorian Aquifer Framework (VAF). The seamless mapping of aquifers across the state provides the fundamental framework for groundwater resource management, underpins development of a revised management structure for Victoria (the Secure Allocation Future Entitlement project funded by the National Water Commission) and contributes to the data needs of the Bureau of Meteorology National Groundwater Information System (NGIS).

The original dataset was produced by GHD in 2012 using (in part) data provided by Southern Rural Water Corporation and Goulburn-Murray Water Corporation. It has been subsequently amended by Hocking et al and SKM in 2013.

Dataset History

A number of key input datasets were sourced as part of the process to derive the 3D aquifer surfaces. These datasets included: The DEPI State-wide Stratigraphic Database (SSD); The National Groundwater Information System (NGIS) database containing groundwater borehole location information as well as lithological and stratigraphic information; Raster layers previously produced for Southern Rural Water (SRW) by SKM and GHD in 2009; The crystalline basement surface provided by the former Department of Primary Industries (DPI); Outcrop 1:250,000 scale geological mapping compiled by the former Geological Survey of Victoria, DPI; A state-wide 100m Digital Elevation Model (DEM) based on the DEPI 20m DEM. This was used to represent the natural surface; Data generated using DEPI's state-wide ecoMarkets groundwater modelling package to assist with the definition of key layers of the major Cainozoic aquifers; Latrobe Valley Coal Model which was used to provide a framework for the hydro-stratigraphy of the wet Gippsland Basin; Rasters of the top elevation of the major aquifer systems covering the Kiewa, Ovens, Goulburn-Broken and Loddon and Campaspe catchments; Data extracted from the Basin in a Box, the Murray Basin Hydrological Map Series and the Murray-Darling Basin Groundwater Status 1990-2000: Summary Report; Airborne magnetic data publicly available from raster data published by the former Geological Survey of Victoria, DPI. Once the input data had been compiled, the VAF 3D surfaces were developed by lfollowing a number of key steps, summarised below: (1) Contours as polylines and aquifer extents as polygons were extracted from previous mapping surfaces; (2) Outcrop points attributed with values from the DEM were created; (3) Based on the state-wide stratigraphic database, the contours and extents were refined or created; (4) A top elevation raster was interpolated using contours, outcrop points and bore data then replacing outcrop areas with the DEM; (5) The aquifer thickness was then checked in GIS by comparing layers against each other and assessing for cross-overs and negative thickness; (6) The input data was then revised and bore data, contours, and aquifer extents modified as required due to errors in the thickness; (7) If there were subsequent issues identified such as overlaps between aquifers, mismatches between bores and resulting layers, then the process was revised by returning to Step (3); (8) If the layers were matching well, then extent points were created to smooth layers at the edges; (9) A top elevation raster was generated again using contours, outcrop points, extent points and bore data; (10) The aquifer thickness was checked again, and if significant issues were identified, then the process returned back to Step (3) for further iteration; (11) Further modifications were applied to remove negative thicknesses and to provide minimum thickness of overburden; (12) Top and bottom elevation rasters were then generated at 100m pixel resolution to form the final dataset. In generating each of the layers, a number of Quality Assurance (QA) measures were implemented at various stages of the process. These included a topologic review, a hydrogeological review and an external reveiw by Spatial Vision. The original dataset was published in May 2012 and subsequent revisions have been conducted by Hocking et al and SKM in 2013.

Dataset Citation

Victorian Department of Environment and Primary Industries (2014) Victorian Aquifer Framework - Water Table. Bioregional Assessment Source Dataset. Viewed 11 July 2016, http://data.bioregionalassessments.gov.au/dataset/663871a0-0444-4be4-bd2b-6741e114036e.

This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Coastal Services Center's Sea Level Rise and Coastal Flooding Impacts Viewer. The DEM includes the 'best available' lidar data known to exist at the time of DEM creation that meets project specifications for those counties within the boundary of the Corpus Christi TX Weather Forecast Office (WFO), as defined by the NOAA National Weather Service. The counties within this boundary are: Kleberg, Nueces, San Patricio, Aransas, Refugio, Victoria, and Calhoun.For all counties, except for Kleberg, the DEM is derived from LiDAR data sets collected for the Texas Water Development Board (TWDB) in 2005 and 2006 with a point density of 1.4 m GSD. The LiDAR data for Kleberg County is based on the US Geological Survey (USGS) National Elevation Dataset (NED) 1/9 arc-second elevation data. Hydrographic breaklines used in the creation of the DEM were delineated using LiDAR intensity imagery generated from the data sets. Hydrography for Kleberg County is based on the National Hydrography Dataset (NHD) and the National Wetlands Inventory (NWI). The DEM is hydro flattened such that water elevations are less than or equal to 0 meters.The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 10 meters.The DEM includes the best available lidar data known to exist at the time of DEM creation for the coastal areas of Victoria, Calhoun, Aransas, Refugio, San Patricio, Nueces, and Kleberg counties.

A polygonal dataset of mapped landforms in the Victorian Mallee. The dataset was created from the disaggregation of land systems originally defined by Rowan and Downes (1963). The disaggregation primarily involved an analysis of a 10 metre grid Digital Elevation Model (DEM) provided by the Department of Sustainability and Environment. The analysis included the use of the UPNESS index from the Fuzzy Landscape Analysis GIS (FLAG) model, Multi-resolution Valley Bottom Flatness (MrVBF) index, DEM derivative surfaces (such as slope, curvature, aspect and relative elevation) in combination with expert opinion, field observations and other supplementary datasets (such as aerial imagery, radiometrics, vegetation and GMU). The dataset was created in a staged approach through 4 project phases. The project was sponsored by the Mallee Catchment Management Authority with funding from the Federal government's Caring for our Country initiative. The final project report, "Disaggregation of landform components within land systems of the Mallee", and the Rowan and Downes (1963) report , "A study of the land of north-western Victoria", should be referred to when analysing or utilising this dataset. The landform component mapping was supplemented and refined during a "Wind erosion susceptibility mapping" project conducted in 2011. Details of changes are included in the associated project report (refer to that metadata record).

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Texas Central digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Calhoun, Jackson, Matagorda, and Victoria Counties. The DEM was produced from the following lidar data sets: 1. 2018 TNRIS Lidar: Upper Coastal Lidar 2. 2018 Matagorda Bay TX Lidar 3. 2018 Texas - South Texas Lidar The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Texas South 1 digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Calhoun, Jackson, Matagorda, and Victoria Counties. The DEM was produced from the following lidar data sets: 1. 2017 25 County AL Lidar 2. 2014 Mobile County, AL Lidar 3. 2014 NRCS/USGS/NPS Choctaw and Washington Co., AL Lidar The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

20m resolution bathymetry and 5m contour intervals derived from 20m resolution bathymetry for nearshore Victorian Coast, LiDAR-derived bathymetry plus small area of multibeam-derived bathymetry on Westernport Bay.

This dataset covers the Victorian coast, generally extending to the 20m depth contour. This dataset is based on information acquired between November 2008 and April 2009 to support the Victorian Governments Future Coasts Project.

Coastline of Victoria based primarily on zero metre (0m) contour dataset from the Vicmap Elevation Coastal DEM and Contours product derived using LIDAR and reviewing this dataset against the most recent and highest resolution aerial photography available in the DSE CIP image repository. Where LIDAR contours were absent or of poor quality, the coastline was digitised from recent API. For MGA Zone 54, zero contour was largely incomplete, and 0.5m contour was used due to the absence of a satisfactory 0m contour. Where no LIDAR and photography was available, Framework was used (including for internal state boundaries).

A terrain surface dataset that represents the height value of all natural and built features of the surface of the city. Each pixel within the image contains an elevation value in accordance with the Australian Height Datum (AHD).

The data has been captured in May 2018 as GeoTiff files, and covers the entire municipality.

A KML tile index file can be found in the attachments to indicate the location of each tile, along with a sample image.

Capture Information:

Capture Pixel Resolution: 0.1 metres

Limitations:

Whilst every effort is made to provide the data as accurate as possible, the content may not be free from errors, omissions or defects.Preview:Download:A zip file containing all relevant files representing the Digital Surface ModelDownload Digital Surface Model data (12.0GB)

This GIS data package contains airborne electromagnetic (AEM) datasets and interpreted data products for the Lindsay-Wallpolla and Lake Victoria-Darling Anabranch survey area, as part of the River Murray Corridor (RMC) Salinity Mapping and Interpretation Project. The RMC project was undertaken between 2006 and 2010 to provide information on a range of salinity and land management issues along a 450 kilometre reach of the Murray River from the South Australian border to Gunbower, northwest of Echuca in Victoria. The Lindsay-Wallpolla survey area extends from the South Australian border to approximately 10 kilometres west of Mildura, incorporating Lake Victoria and the lower reaches of the Darling and Darling Anabranch river systems. This metadata briefly describes the contents of the data package. The user guide included in the package contains more detailed information about the individual datasets and available technical reports. The main components in the package are: AEM data and images derived from a holistic inversion of the RMC RESOLVE AEM survey; a composite digital elevation model (DEM); a range of interpreted data products designed to map key elements of the hydrogeological system and salinity hazard; and a series of ESRI ArcGIS map documents. The AEM data component consists of grids and images of modelled conductivity data derived from a holistic inversion of the RMC RESOLVE AEM survey. They include: layer conductivity grids below ground surface; depth slice grids representing the average conductivity of various regular depth intervals below ground surface; floodplain slice grids representing the average conductivity of various depth intervals relative to the elevation above or below a surface that approximates the River Murray floodplain; watertable slice grids representing the average conductivity of various intervals relative to the elevation above or below the regional watertable; and AEM cross sections of conductivity versus depth along each of the flight lines. The holistic inversion AEM data are derived from the 'River Murray Corridor RESOLVE AEM Survey, VIC & NSW, 2007 Final Data (P1141)', available as GA product (GeoCat #67212). The DEM data component consists of a 10 metre resolution composite DEM for the River Murray Corridor AEM Survey area, derived from airborne light detection and ranging (LiDAR) surveys, AEM surveys and the shuttle radar topography mission (SRTM) survey. The interpreted data component is organised into product themes to address salinity and land management questions and to map key elements of the hydrogeological system and salinity hazards. An ArcGIS map document is included for each product theme. The products include: Blanchetown Clay; conductive soils; flush zones; groundwater conductivity; strategic extents and reliability; near surface conductive zones; near surface resistive zones; Parilla Sands; Quaternary alluvium; recharge; salt store; surface salt; vegetation health; and Woorinen Formation. The RMC project was funded through the National Action Plan for Salinity and Water Quality, with additional funding from the Lower Murray Catchment Management Authority (CMA), Mallee CMA, Goulburn-Murray Water and the Murray-Darling Basin Authority. The project was administered by the Australian Government Department of Agriculture, Fisheries and Forestry through the Bureau of Rural Sciences, now known as the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES). Geoscience Australia (GA) were contracted to provide geophysical services to manage the AEM system selection and data acquisition, and to process and calibrate the AEM data. The AEM survey was flown by Fugro Airborne Geophysical Services in 2007 using the helicopter-borne RESOLVE frequency domain system. The Cooperative Research Centre for Landscape Environments and Mineral Exploration was sub-contracted through GA to manage the interpretation and reporting component of the RMC project.

Accurate coastal wave and hydrodynamic modelling relies on quality bathymetric input. Many national scale modelling studies, hindcast and forecast products, have, or are currently using a 2009 digital elevation model (DEM), which does not include recently available bathymetric surveys and is now out of date. There are immediate needs for an updated national product, preceding the delivery of the AusSeabed program’s Global Multi-Resolution Topography for Australian coastal and ocean models. There are also challenges in stitching coarse resolution DEMs, which are often too shallow where they meet high-resolution information (e.g. LiDAR surveys) and require supervised/manual modifications (e.g. NSW, Perth, and Portland VIC bathymetries). This report updates the 2009 topography and bathymetry with a selection of nearshore surveys and demonstrates where the 2009 dataset and nearshore bathymetries do not matchup. Lineage: All of the datasets listed in Table 1 (see supporting files) were used in previous CSIRO internal projects or download from online data portals and processed using QGIS and R’s ‘raster’ package. The Perth LiDAR surveys were provided as points and gridded in R using raster::rasterFromXYZ(). The Macquarie Harbour contour lines were regridded in QGIS using the TIN interpolator. Each dataset was mapped with an accompanying Type Identifier (TID) following the conventions of the GEBCO dataset. The mapping went through several iterations, at each iteration the blending was checked for inconstancy, i.e., where the GA250m DEM was too shallow when it met the high-resolution LiDAR surveys. QGIS v3.16.4 was used to draw masks over inconstant blending and GA250 values falling within the mask and between two depths were assigned NA (no-data). LiDAR datasets were projected to +proj=longlat +datum=WGS84 +no_defs using raster::projectRaster(), resampled to the GA250 grid using raster::resample() and then merged with raster::merge(). Nearest neighbour resampling was performed for all datasets except for GEBCO ~500m product, which used the bilinear method. The order of the mapping overlay is sequential from TID = 1 being the base, through to 107, where 0 is the gap filled values.

Permissions are required for all code and internal datasets (Contact Julian OGrady).

The Statewide Marine Habitat Map 2023 was developed by DEECA applying novel machine learning methods that model and predict habitat distributions as well as a mosaic of former mapping products (listed below). The Statewide map represents 24 marine and coastal habitats complexes at Level 3, Victoria's Combined Biotope Classification Scheme (CBiCS) described by Edmunds and Flynn (2015, 2018; 2021). The final map comprises of 83% its area from predictive modelling, with the remaining 17% of area from synthesised existing habitat maps.

Predictive Model: A total of 32,998 habitat survey sites (ground-truth records) were used within the model, along with 28 environmental properties mapped at a 10m resolution (including a Digital Elevation Model DEM (VCDEM2021), computed benthic terrain characteristics (toolkit: Walbridge et al. 2018), Chlorophyl a (IMOS 2000a), Sea Surface Temperature SST (IMOS 2000a), Net Primary Productivity NPP (IMOS 2000b), Sediments (Geoscience Australia; Li et al. 2011a,b,c), waves (Liu et al. 2022). To predict the distribution of habitats across Victorian waters the powerful and flexible Random Forest machine learning algorithm was applied. Random Forest is an ensemble model using bagging as the ensemble method and decision trees as the individual model (Breiman 2001). The modelling produced an accuracy (Out-of-bag) of 89%.

Map Synthesis: A mosaic of former mapping products that provided higher resolution mapping by aerial imagery, field observations and high-resolution modelling were integrated into the map, classifying habitat according to the CBICS habitat classification scheme at level 3. Assessed and synthesised maps and citations include: Corangamite Coast Marine Habitat December 2009 (ANZVI0803005530); East Gippsland Marine Habitats November 2009 (ANZVI0803003974); Discovery Bay Marine National Park habitat mapping 2006 (ANZVI0803004053); Portland Coastal Habitats (ANZVI0803004236) ; Corner Inlet Mapping Marine National Park North and South 2004 (ANZVI0803004051) ; Merri Marine Sanctuary 2004 (ANZVI0803004058); Western Port Bay Biotope Mapping Fathom Pacific (2016) CBiCS-Mapping. Central Victoria Coastal Habitats (ANZVI0803004135); Mallacoota Coastal Habitats (ANZVI0803004235); Western Port Rhodolite (ANZVI0803005430) & Western Port Biogenic Reefs; Port Phillip Bay Habitat Map 2021 (ANZVI0803009278); Saltmarsh and Mangrove Habitats; DELWP 2021 Statewide Marine Habitat Map 2021 (ANZVI0803009286) and relevant citations: Ball (1999), Ball et al. (2010). Ball & Blake (2007a), Ball & Blake (2007b), Blake and Ball (2001), Blake et al. (2013), Boon et al. (2011), Cohen et al (2000), Deakin Marine Mapping (Zavalas, R et al. 2018), DELWP (1994), Edmunds &Flynn (2015), Fathom Pacific (2020), Ford et al (2016), GeoHab Victoria Estuaries Geomorphology (2010), Ierodiaconou 2007, Ierodiaconou et al. 2018, Mazor et al. (2021), Monk et al. (2011), Poore (1992), Roob and Ball (1997), Victoria Department of Transport (1999), Young et al. 2022, Zavalas, R et al. 2018.

Applications: The Statewide Marine Habitat Map 2023 provides broad habitat complexes across the state and provides greater knowledge of the ecological diversity across Victoria¿s waters. The map should be used at broad scales of >25 m, and where information of larger habitat complexes is needed. This work can support the management of large-scale habitats, their condition, marine spatial planning, strategic management prospect (SMP), FeAST risk assessments, and other broad scale applications to support management decisions across Victoria. The habitat model and resulting map provides an updated broad-scale habitat map across Victoria¿s state waters and provides a baseline for future data to build upon.

The Bass Strait Digital Elevation Model (DEM) is a compilation of all available bathymetry data for the area of seabed between the coastlines of Victoria and northern Tasmania, extending approximately 460 km from west of King Island to east of Flinders Island. The Bass Strait is bounded by a continental slope incised with numerous canyons, including the prominent Bass Canyon on the eastern side. The region encompasses islands and exposed rocks, drowned paleo-shorelines and dunefields, fringed by a rugged coastline. Bathymetry mapping of the seafloor is vital for the protection of Bass Strait, allowing for safe navigation of shipping, improved environmental management and resource development. Australian Hydrographic Office-supplied ENC tile spot depths were used to develop the general bathymetry variation across the entire region. Shallow- and deep-water multibeam survey data reveal the complexity of the seafloor for the continental shelf and adjacent canyons which incise the western and eastern sides of Bass Strait. Airborne LiDAR bathymetry acquired by the Australian Hydrographic Office cover most of the northern Tasmanian nearshore and coast, with some coverage gaps supplemented by Landsat-8 satellite derived bathymetry data. The Geoscience Australia-developed Intertidal Elevation Model DEM improves the source data over the intertidal zone. Highly accurate photogrammetry coastline data developed for the Tasmania, Victoria and New South Wales coastlines, and Near Surface Feature data representing shoal features observable in aerial imagery, were used to improve the land/water interface of the numerous island and rock features. All source bathymetry data were extensively edited as 3D point clouds to remove noise, given a consistent WGS84 horizontal datum, and where possible, an approximate MSL vertical datum.

This dataset is not to be used for navigational purposes.

Daily (1981-2019), monthly (1981-2019) and monthly mean (1981-2010) surfaces of precipitation across Victoria at a spatial resolution of 9 seconds (approx. 250 m). Lineage: A) Data modelling: 1. Weather station observations collected by the Australian Bureau of Meteorology were obtained via the SILO patched point dataset (https://data.qld.gov.au/dataset/silo-patched-point-datasets-for-queensland), followed by the removal of all interpolated records. 2. Climate normals representing the 1981-2010 reference period were calculated for each weather station. A regression patching procedure (Hopkinson et al. 2012) was used to correct for biases arising due to differences in record length where possible. 3. Climate normals for each month were interpolated using trivariate splines (latitude, longitude and elevation as spline variables) using a DEM smoothed (Gaussian filter with a standard deviation of 10 and a search radius of 0.0825°, optimised using cross validation) to account for the lack of strong correlation between elevation and precipitation at short distances (Hutchinson 1998; Sharples et al. 2005). All data was interpolated using ANUSPLIN 4.4 (Hutchinson & Xu 2013). 4. Monthly surfaces were interpolated directly from monthly station records using the methods described in step 3. 5. Daily anomalies were calculated as a proportion of monthly precipitation, and interpolated with full spline dependence on latitude and longitude. 6. Interpolated anomalies (constrained to values between 0 and 1) were multiplied by monthly precipitation to obtain the final daily surfaces. B) Spatial data inputs: 1. Fenner School of Environment and Society and Geoscience Australia. 2008. GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3. C) Model performance: Accuracy assessment was conducted with leave-one-out cross validation. Mean monthly precipitation: RMSE = 7.65 mm (14.0% relative to mean) Monthly precipitation: RMSE = 13.12 mm (24.7% relative to mean) Daily precipitation: RMSE = 2.21 mm (26.3% relative to mean)

Abstract

This dataset was supplied to the Bioregional Assessment Programme by a third party and is presented here as originally supplied. Metadata was not provided and has been compiled by the Bioregional Assessment Programme based on known details at the time of acquisition.

The slope is derived from the 1" DEM SRTM global elevation data set developed under the National Elevation Data Framework undertaken by GA BoM CSIRO and ANU (Gallant et al. 2011). Slope is used to show topographic variability.

To represent slope of a surface relative to the horizontal

Purpose

Slope is used to show topographic variability.

Dataset History

Slope derived from the 1 second digital elevation model, using tools in ArcGIS software.

Dataset Citation

Victorian Department of Environment, Land, Water and Planning (2000) Slope 1second Digital Elevation Model Gippsland Clip. Bioregional Assessment Derived Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/9051bb0d-1054-42f4-b6c8-5742e40cc389.

Dataset Ancestors

• Derived From Geoscience Australia, 1 second SRTM Digital Elevation Model (DEM)

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

This is the master metadata record for the Victorian Aquifer Framework (VAF) 3D Surfaces dataset. For information on each aquifer surface, please refer to the separate metadata record.

DEPI originally engaged GHD to develop seamless 3D aquifer surfaces for the Victorian Aquifer Framework (VAF). The seamless mapping of aquifers across the state provides the fundamental framework for groundwater resource management, underpins development of a revised management structure for Victoria (the Secure Allocation Future Entitlement project funded by the National Water Commission) and contributes to the data needs of the Bureau of Meteorology National Groundwater Information System (NGIS).

The original dataset was produced by GHD in 2012 using (in part) data provided by Southern Rural Water Corporation and Goulburn-Murray Water Corporation. It has been subsequently amended by Hocking et al and SKM in 2013.

Purpose

Aquifer Name, Aquifer Code, Aquifer Number: Quaternary Aquifer QA 100 Upper Tertiary/Quaternary Basalt Aquifer UTB 101 Upper Tertiary/Quaternary Aquifer UTQA 102 Upper Tertiary/Quaternary Aquitard UTQD 103 Upper Tertiary Aquifer (marine) UTAM 104 Upper Tertiary Aquifer (fluvial) UTAF 105 Upper Tertiary Aquitard UTD 106 Upper Mid-Tertiary Aquifer UMTA 107 Upper Mid-Tertiary Aquitard UMTD 108 Lower Mid-Tertiary Aquifer LMTA 109 (Lower) Tertiary Basalts LTB 112 Lower Mid-Tertiary Aquitard LMTD 110 Lower Tertiary Basalts LTB 112 Lower Tertiary Aquifer LTA 111 Lower Tertiary Basalts LTB 112 Cretaceous and Permian Sediments CPS 113 Mesozoic and Palaeozoic Bedrock BSE 114

Dataset History

A number of key input datasets were sourced as part of the process to derive the 3D aquifer surfaces. These datasets included: The DEPI State-wide Stratigraphic Database (SSD); The National Groundwater Information System (NGIS) database containing groundwater borehole location information as well as lithological and stratigraphic information; Raster layers previously produced for Southern Rural Water (SRW) by SKM and GHD in 2009; The crystalline basement surface provided by the former Department of Primary Industries (DPI); Outcrop 1:250,000 scale geological mapping compiled by the former Geological Survey of Victoria, DPI; A state-wide 100m Digital Elevation Model (DEM) based on the DEPI 20m DEM. This was used to represent the natural surface; Data generated using DEPI's state-wide ecoMarkets groundwater modelling package to assist with the definition of key layers of the major Cainozoic aquifers; Latrobe Valley Coal Model which was used to provide a framework for the hydro-stratigraphy of the wet Gippsland Basin; Rasters of the top elevation of the major aquifer systems covering the Kiewa, Ovens, Goulburn-Broken and Loddon and Campaspe catchments; Data extracted from the Basin in a Box, the Murray Basin Hydrological Map Series and the Murray-Darling Basin Groundwater Status 1990-2000: Summary Report; Airborne magnetic data publicly available from raster data published by the former Geological Survey of Victoria, DPI. Once the input data had been compiled, the VAF 3D surfaces were developed by lfollowing a number of key steps, summarised below: (1) Contours as polylines and aquifer extents as polygons were extracted from previous mapping surfaces; (2) Outcrop points attributed with values from the DEM were created; (3) Based on the state-wide stratigraphic database, the contours and extents were refined or created; (4) A top elevation raster was interpolated using contours, outcrop points and bore data then replacing outcrop areas with the DEM; (5) The aquifer thickness was then checked in GIS by comparing layers against each other and assessing for cross-overs and negative thickness; (6) The input data was then revised and bore data, contours, and aquifer extents modified as required due to errors in the thickness; (7) If there were subsequent issues identified such as overlaps between aquifers, mismatches between bores and resulting layers, then the process was revised by returning to Step (3); (8) If the layers were matching well, then extent points were created to smooth layers at the edges; (9) A top elevation raster was generated again using contours, outcrop points, extent points and bore data; (10) The aquifer thickness was checked again, and if significant issues were identified, then the process returned back to Step (3) for further iteration; (11) Further modifications were applied to remove negative thicknesses and to provide minimum thickness of overburden; (12) Top and bottom elevation rasters were then generated at 100m pixel resolution to form the final dataset. In generating each of the layers, a number of Quality Assurance (QA) measures were implemented at various stages of the process. These included a topologic review, a hydrogeological review and an external reveiw by Spatial Vision. The original dataset was published in May 2012 and subsequent revisions have been conducted by Hocking et al and SKM in 2013.

Dataset Citation

Victorian Department of Environment and Primary Industries (2014) Victorian Aquifer Framework - Salinity. Bioregional Assessment Source Dataset. Viewed 29 September 2017, http://data.bioregionalassessments.gov.au/dataset/dd006fce-bef5-4377-82ae-2c5a14b50e34.

Flow Accumulation, LV Watershed, raster, 2000 Reference Information and Units: GCS: WGS 1984 Projection: EPSG:102024 (Lambert Conformal Conic Africa), Resolution: ~30 meters File Naming Convention: v2_flow_accum Data Origin: SRTM GL1: NASA Shuttle Radar Topography Mission Global 1 arc second V003 Sensor: SRTM Data Description: NASA Shuttle Radar Topography Mission (SRTM) datasets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. The purpose of SRTM was to generate a near-global digital elevation model (DEM) of the Earth using radar interferometry. SRTM was a primary component of the payload on the Space Shuttle Endeavour during its STS-99 mission. Endeavour launched February 11, 2000 and flew for 11 days. SRTM collected data in swaths, which extend from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km). These swaths are ~225 km wide, and consisted of all land between 60° North (N) and 56° South (S) latitude. This accounts for about 80% of Earth’s total landmass. More information can be found in the metadata pdf