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                <gco:CharacterString>Borehole data is one of the key sources of information for conducting groundwater projects. This borehole data is composed of two primary components: construction (location, elevation, bore construction) and hydrogeologic (lithology, stratigraphy, aquifer, water level and chemistry) information.
Since the development of recommended National reporting guidelines in Australia for registering boreholes, the completeness of borehole data has improved. Unfortunately, legacy borehole data is often incomplete, missing key pieces of information. A key legacy data gap is attributing aquifers to water sources in boreholes. Incomplete aquifer attribution information places limitations on the assessment of borehole data.

Borehole aquifer attribution has historically been a time-consuming manual task requiring an investigator with the required level of knowledge to assess each bore. This manual task is influenced by numerous factors including the number and spatial distribution of boreholes, complexity of groundwater systems and geographical extent of the assessment area. Advancements in computing hardware, software and scripting environments offer the opportunity to automate this process.

Tools for automating borehole aquifer attribution have been developed using python script or FME (Feature Manipulation Engine) workflows. While these workflows follow the same general processing flow approach, they are customised to their respective assessment areas limiting broader application. To use these tools in other geographical areas would require customisation for each instance. Geoscience Australia have developed a prototype tool to standardise and streamline this process and deliver a consistent, repeatable method for attributing aquifers to borehole data to support groundwater projects under the Resourcing Australia’s Prosperity initiative.

Presented at the 52nd Congress of International Association of Hydrogeologists (IAH2025)</gco:CharacterString>
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