Alternatives to traditional supplies of water are being investigated by the water industry, with the intention of treating the water to a level allowing its use in various applications. An industry ongoing challenge is the differentiation of various faecal pollution sources in water bodies. This project applies some recent advances in analytical microbiology to target Melbourne stormwater and waterways, with the objectives of characterising the extent of faecal contamination, and distinguishing the impact of human sourced contamination from that originating from animals.
A framework using Microbial Source Tracking ( MST) methods, able to identify pollution of human and animal origin was described in a Round 5 Smart Water Fund project led by the same project team. The outputs of these MST methods are quantitative, and a framework for their interpretation was described in the previous work. Further data is highly desirable so as to better validate the existing methods. The primary aim of this project was to investigate a small set of linked sites with repeated sampling (two events), so as to result in a more statistically rigorous validation of the existing methods.
The sampling and analysis sections of this project included a sanitary survey of the sample sites, examination of the cross reactivity of fish faecal material, sampling events, avian-specific marker analysis and a data report detailing the site and laboratory analysis. Several water quality parameters were monitored at sites on and around Olinda Creek, including MST parameters indicative of human- and animal-sourced contamination.
The amount of faecal contamination, as determined by faecal indicator bacteria, was relatively light. Animal sources were regarded as predominant in the resultant waterway, with correlation demonstrated between the concentration of the ABM marker and faecal indicator bacteria. No correlation was demonstrated between the human-specific marker and indicators.
This project has advanced the MST capability through further validation with repeat sampling of sites with varying degrees and sources of contamination, comparison with the results achieved in the original Smart Water MST study, and proposing the approach to the interpretation of results.
It is recommended that the relationship between MST results and other water quality parameters be further statistically examined. Should positive relationships be able to be demonstrated, this could allow a tiered approach to sampling and examination, increasing the cost-effectiveness of MST monitoring.