PhD position – Improving the Reliability of Streamflow and Water Level Forecasting using Artificial Intelligence Techniques

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Project title: Improving the Reliability of Streamflow and Water Level Forecasting using Artificial Intelligence Techniques

This research proposes investigation and use of artificial intelligence techniques to develop robust predictive methodology for streamflow and water level based on currently collected time-series data. The project will also look at developing or refining an information management system that facilitates collection and management of the time-series data specifically for robust prediction. Research will include a comprehensive sensitivity analysis to compare current Snowy Hydro methods with the newly developed methods, and to validate and increase confidence in the proposed technique(s).

It is expected the research student would spend periods of time at Snowy Hydro offices and field sites to ensure a sound understanding of both the physical hydrologic systems and also the associated monitoring and information systems Snowy Hydro rely on and use. Time will also be spent to understand
the current predictive models that Snowy Hydro use so that appropriate comparison can be made to the new methods and techniques developed.

Industry partner and student host: Snowy Hydro Limited