South-east Australian Fractured Rock Province Hydrogeological Inventory
Updated 1mo ago
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Description
A 2026 dataset from the Australian Ocean Data Network describes hydrogeological attributes for fractured rock provinces in south-east Australia. Groundwater in these fractured rock aquifers comprises about 40% of Australia's groundwater, though they account for only 10% of total extraction. The inventory groups descriptive topics into themes including location, demographics, physical geography, geology, hydrogeology, and land use.
Use Cases
Assessing groundwater availability for irrigation and town supplies based on hydrogeological attributes
Modeling groundwater flow direction influenced by fracture orientation rather than hydraulic head
Studying mineral deposit distribution in relation to lithological units like granite bodies and volcano-intrusive complexes
Analyzing the relationship between land use, industry types, and groundwater management in fractured rock regions
Strengths
Covers a significant region, the Lachlan Orogen, which contains diverse lithological units and mineral deposits
Groups descriptive information into 11 specific themes, suggesting structured attribute organization
Provides context on fractured rock aquifers, which store about 40% of Australia's groundwater
Limitations
Column-level documentation is absent; field semantics must be inferred after download
Row count is unknown, which may limit suitability assessment
The study excludes additional Orogens in the east (New England) and west (Thomson and Delamerian), limiting geographic completeness
Provenance
Source
Australian Ocean Data Network
Collection Method
Descriptive attribute information bounded by spatial groundwater features from an associated Hydrogeology Index map.
Freshness
Last updated 2026-06-23 02:09:01.122164; freshness should be verified
Geography
South-east Australia, specifically the Lachlan Orogen extending from central and eastern New South Wales to Victoria and Tasmania.
File format is PDF, which may require extraction for structured data analysis.