Public land polygons derived from LCC recommendations. This layer contains the line and polygon features depicting the Land Conservation Council (LCC) Final Recommendations as per the 1988 Statewide Assessment published map at 1:500 000. The Mallee Study Area was subsequently updated in 1991.

The Victorian Coastal Cliff Assessment - Instability Areas (ASCCIE) is a digital dataset consisting of multiple spatial layer outputs from modelled erosion scenarios. The dataset is recommended for use at the statewide / regional scale along the Victorian coastline. Application of the data should be guided by the accompanying Victorian Coastal Cliff Assessment technical reports and expert advice. The product is not suitable for individual property scale assessments. Consolidated shorelines, which include soil and rock cliffs, are not able to rebuild following periods of erosion but rather are subject to a one-way process of degradation. ASCCIEs typically have two components: • Toe Erosion A gradual retreat of the cliff toe caused by weathering, marine and bio-erosion processes. This retreat will be affected by global process such as sea level rise and potentially increased soil moisture. Future cliff toe position based on historical erosion rates with a factor applied to allow for the effect of future sea level rise. • Cliff Instability Episodic instability events are predominately due to a change in loading or material properties of the cliff or yielding along a geological structure. In soft cliffs, instability causes the cliff slope to flatten to a slope under which it is “stable” (geo-mechanically). Soil cliff slope instabilities are influenced by processes that erode and destabilise the cliff toe, including marine processes, weathering and biological erosion or change the stress within the cliff slope. Most of the hard cliffs are stable at very steep angles. Instability events may range from small-scale instabilities (block or rock falls) or discontinuities, to cliff slope instability cause by large-scale and deep-seated mass movement. The latter mode of failure in hard cliffs is rare. The product is an update to the Victorian Coastal Cliff Assessment, Stage 1. Included datasets for Stage 2a supersede the Stage 1 outputs. The Stage 2a project report should be read in conjunction with the Stage 1 report. Application of the data should be guided by the accompanying "Victorian Coastal Cliff Assessment, Stage 2a technical report" (Tonkin & Taylor 2025) read in conjunction with the Stage 1 technical report, combined with appropriate expert advice.

Potential Groundwater Dependent Ecosystems (GDE) are ecosystems identified within the landscape as likely to be at least partly dependent on groundwater. State-wide screening analysis was performed to identify locations of potential terrestrial GDEs, including wetland areas. The GDE mapping was developed utilising satellite remote sensing data, geological data and groundwater monitoring data in a GIS overlay model. Validation of the model through field assessment has not been performed. The method has been applied for all of Victoria and is the first step in identifying potential groundwater dependent ecosystems that may be threatened by activities such as drainage and groundwater pumping. The dataset specifically covers the Port Phillip and Westernport Catchment Management Authority (CMA) area. The method used in this research is based upon the characteristics of a potential GDE containing area as one that: 1. Has access to groundwater. By definition a GDE must have access to groundwater. For GDE occurrences associated with wetlands and river systems the water table will be at surface with a zone of capillary extension. In the case of terrestrial GDE's (outside of wetlands and river systems), these are dependent on the interaction between depth to water table and the rooting depth of the vegetation community. 2. Has summer (dry period) use of water. Due to the physics of root water uptake, GDEs will use groundwater when other sources are no longer available; this is generally in summer for the Victorian climate. The ability to use groundwater during dry periods creates a contrasting growth pattern with surrounding landscapes where growth has ceased. 3. Has consistent growth patterns, vegetation that uses water all year round will have perennial growth patterns. 4. Has growth patterns similar to verified GDEs. The current mapping does not indicate the degree of groundwater dependence, only locations in the landscape of potential groundwater dependent ecosystems. This dataset does not directly support interpretation of the amount of dependence or the amount of groundwater used by the regions highlighted within the maps. Further analysis and more detailed field based data collection are required to support this. The core data used in the modelling is largely circa 1995 to 2005. It is expected that the methodology used will over estimate the extent of terrestrial GDEs. There will be locations that appear from EvapoTranspiration (ET) data to fulfil the definition of a GDE (as defined by the mapping model) that may not be using groundwater. Two prominent examples are: 1. Riparian zones along sections of rivers and creeks that have deep water tables where the stream feeds the groundwater system and the riparian vegetation is able to access this water flow, as well as any bank storage contained in the valley alluvials. 2. Forested regions that are accessing large unsaturated regolith water stores. The terrestrial GDE layer polygons are classified based on the expected depth to groundwater (ie shallow <5 m or deep >5 m). Additional landscape attributes are also assigned to each mappnig polygon. In 2011-2012 a species tolerance model was developed by Arthur Rylah Institute, collaborating with DPI, to model landscapes with ability to support GDEs and to provide a relative measure of sensitivity of those ecosystems to changes in groundwater availability and quality. Rev 1 of the GDE mapping incorporates species tolerance model attributes for each potential GDE polygon and attributes for interpreted depth to groundwater. Separate datasets and associated metadata records have been created for GDE species tolerance.

This dataset is derived from the Melway directory and contains the map indices for the 1:15 000 Queenscliffe maps.

A map of Victorian rainfall deciles for the winter period of 2022.

This layer is part of Vicmap Elevation 10-20 Contours & Relief, a subset of Vicmap Elevation. It contains point features delineating ground type points. Includes: Mountain, Rock Terrestial and Points.

This dataset depicts the location of the Danyo, Hindmarsh, Tyrell, Avoca and Leaghur faults in the north-western Murray Basin in Victoria. The faults have been digitised from Macumber (1991) and Robson and Webb (2011). These north-south oriented faults appear to truncate or interrupt a number of cross-cutting structures in the Murray Basin. The Hindmarsh, Tyrell, Avoca and Leaghur faults all influence modern day stream flows which may be indicative of an earlier impact on the aquifer if movement has occurred regularly over the Tertiary period. The dataset was compiled by GHD to inform the report 'Potential Influences of Geological Structures on Groundwater Flow Systems' for DEPI's Secure Allocation Future Entitlements (SAFE) Project.

Projection data is described in the gridcode column of the attribute table. This number is 1000 times the actual value (retained in this form to capture significant figures through map processing). For example, "Gridcode -23599" equates to -24% (rainfall) and "Gridcode 1986" equates to 2.0 degrees Celsius (temperature). The results are from 23 climate models that were available for the IPCC Fourth Assessment Report (2007). It is assumed that that the model results give a representation of the real world response to a specific emissions scenario. The IPCC (2007) estimates of global warming are relative to the period 1980-1999. For convenience, the baseline is often called 1990. Projections are given for 2030 and 2070 but, of course, individual years can vary markedly within any climate period, so the values can be taken as representative of the decade around the single year stated, i.e. projections for 2030 are representative of 2026-2035. Natural variability (independent of greenhouse gas forcing) can cause decadal means to vary and estimates of this effect are included in the estimates of uncertainties. The projections comprise a central estimate and a range of uncertainty. The central estimate is the median – or 50th percentile - of the model results, while the uncertainty range is based on two extreme values – the 10th and 90th percentiles. 10% of values fall below the 10th percentile and 10% of values lie above the 90th percentile. Greater emphasis is given to projections from models that best simulate the present climate. The weightings are based on statistical measures of how well each model can simulate the 1975-2004 average patterns of rainfall, temperature, and sea level pressure over Australia. Subregions of Victoria are indicated. Victoria has an integrated catchment management system established under the Catchment and Land Protection Act 1994 (the CaLP Act). Under the CaLP Act, Victoria is divided into ten catchment regions, with a Catchment Management Authority (CMA) established for each region. (See: http://www.water.vic.gov.au/governance/catchment_management_authorities)

This dataset shows the area covered by the Wotjobaulk Consultation agreement.

Areas of catchments that drain directly to Victorian estuaries - i.e. not via major freshwater tributaries. This data updates the previous EST_CATCH (Deakin) layer for use in the 2021 Index of Estuarine Condition. Boundaries were determined from a digital elevation model (DEM) and were compared with DELWP boundaries for some estuaries (where DELWP data existed (i.e. in the estuary fluvial catchment layer [WATER_EST_FLUV_VSDL] available on the Victorian Spatial Data Library [January 2020]). On steep land (the Otways, east Gippsland etc) the boundaries align well. On the flatter areas there are some discrepancies between the DEM derived boundary and the DELWP derived boundary. For some catchments the DELWP boundaries are more accurate, but for others the DEM derived boundary is more accurate. Final catchment boundaries were determined by adopting the DEM derived boundary where there was good alignment with the DELWP layer and then adjusting just the contested boundaries to choose the one that appeared most accurate based on the rationale specified for each estuary below.