- Project No 1145
- Project Name Bushfire Recovery for Resilience – bushfire modelling as an enabling decision support tool
- Lead Organisation WaterNSW
- Research Lead Alluvium
- Main Researcher Dr Petter Nyman
- Completion Year 2026
The 2019-20 bushfire season in Australia was unprecedented in its extent, duration, intensity and impact on the natural environment and human livelihoods. The combination of catastrophic fire followed by heavy rainfall mobilised significant ash and sediment loads into receiving waterways and source water supply reservoirs. This created various treatment challenges for water suppliers across the country due to a range of potential contaminants that may be present in the burned material.
What if our (water quality) predictive capabilities post-bushfires could be enhanced by having nationally consistent, but regionally bespoke modelling approaches that can be integrated into the national hydrological modelling platform, SOURCE?
To support fire management, preparation and response efforts, water suppliers require predictive tools to understand the potential water quality impacts of specific burn scenarios. Given the unpredictable nature of bushfires, and the logistical difficulties of post-event sampling, catchment modelling offers the most practicable means of quantifying fire-related contaminant mobilisation at the landscape scale. Modelled estimates of sediment, nutrients and metal export would strengthen the evidence base available to guide strategic planning, catchment fire management, risk assessment and incident response. This would ultimately improve the capacity for utilities to maintain a safe and secure water supply following future bushfire events.
This project will combine learnings and catchment data from the past bushfires across the nation and create modelling tool(s) with options for localised parameterisation and approaches. Existing modelling tools already being used by different utilities provide an excellent starting point to work towards integration opportunities into utilities’ inhouse models, ideally via the SOURCE platform.