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Cliff Risk Score - Short Term - now to 2040

Created 05/05/2025

Updated 05/05/2025

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The Cliff_RiskScore_ShortTerm_to_2040 dataset evaluates the likelihood and consequence of cliff instability to support risk management in areas with coastal cliffs. This includes the classification of risk across the determined timeframes and climate change scenarios. The dataset provides a second-pass, regional assessment providing a top-down coastal compartment view of risk which. The outputs of second-pass risk assessments can be used to support discussion among stakeholders regarding coastal erosion and instability risks, broader climate change risks and the development of adaptation pathways within Victoria’s coastal compartments. However, it should be noted that this assessment has been undertaken at a high level (regional/state-wide scale) and is not appropriate for local scale planning. The data from this assessment may be superseded by local scale and site-specific assessments undertaken by a suitably qualified and experienced practitioner. The assessment is based on available data, tools and understanding of coastal processes. Further information is contained in the study report "Victorian Coastal Cliff Assessment - Stage 2 Risk Assessment", Tonkin and Taylor, September 2023.

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Additional Info

Field Value
Title Cliff Risk Score - Short Term - now to 2040
Language English
Licence Creative Commons Attribution 3.0 Australia
Landing Page https://devweb.dga.links.com.au/data/dataset/b1c51769-ef89-4b0e-84f9-eae7295b9ea5
Remote Last Updated 03/04/2025
Contact Point
Department of Energy, Environment and Climate Action
test@email.loc
Reference Period 29/02/2024
Geospatial Coverage http://www.ga.gov.au/place-names/PlaceDetails.jsp?submit1=GA7
Data Portal data.gov.au

Data Source

This dataset was originally found on Victoria Government "Cliff Risk Score - Short Term - now to 2040". Please visit the source to access the original metadata of the dataset:
https://discover.data.vic.gov.au/dataset/cliff-risk-score-short-term-now-to-2040

Original dataset
Dataset copies

No duplicate datasets found.