This project investigates potential groundwater contamination causes, pathways and vulnerability to understand onshore gas water quality impacts for south east South Australia.

The research achieves a realistic quantification of groundwater contamination risks in gas development areas in south east South Australia, providing improved knowledge for regulators, industry and community.

Reports and papers

Groundwater contamination risks from conventional gas in the southeast SA PDF 3 MB

This study considered three plausible contamination scenarios and for each scenario, water flow and solute transport modelling estimated peak concentrations at risk receptors (i.e. nearby groundwater bores). Results showed that it is very unlikely that plausible contamination events would result in high contaminant concentrations at groundwater receptors in the vicinity of the gas development considered in this study, due to dilution rates over distance to receptor sites and solute degradation within soils and aquifers.

Final report, May 2020

Deep learning emulators for groundwater contaminant transport modelling

This research project investigates the feasibility of using deep learning emulators to improve the efficiency of groundwater computer modelling (generalised flow and contaminant transport model) based on the hydrogeology of an aquifer located in South Australia, where contamination risk from on-shore gas development needs to be assessed. Study results improve understanding of hybrid modelling and show that accurate, efficient and scalable deep learning emulators can be achieved.

Journal paper, November 2020


Groundwater contamination risks: Causal pathways and modelling analysis PDF 3 MB

Presentation to the South Australian Knowledge Transfer Session held in Brisbane via video conference in March 2020.

Presentation, March 2020

Project progress

This project is 100%  complete.

Project proposal PDF 875 KB

Project Order, July 2018

Project progress PDF 531 KB

The project outline, any variations and research progress.

Project progress, September 2020

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