Raw source water contains parts of plants, blue-green algae and their toxins, and many other types of organic matter. Identifying the types and amounts of organic matter helps treatment plant operators make informed decisions about the most efficient and cost-effective methods for treating and removing unwanted substances from source waters. The problem is that many of the tests for identifying organic compounds can take hours to days to deliver results. This research developed a test that gives information immediately. It uses three commercially available fluorescent probes that each emit fluorescent light at a specific wavelength. Certain compounds within organic matter, such as proteins, “reflect” the fluorescent light, but at different wavelengths which can be detected by the probes. These patterns of “reflected” fluorescence were related to traditional tests for organic compounds. This on-line fluorescence monitoring was then trialled at real-world treatment plants. The patterns gave reliable information about broad categories of organic compounds and there was a linear correlation between dissolved organic carbon and fluorescent intensity in both raw and treated waters. This research has provided a valuable addition to the suite of tools available for producing safe, high quality drinking water.

Although a cluster of customer complaints can identify specific water quality issues such as a dirty water event, it is more difficult to understand the extent of general customer satisfaction with water quality and taste. The Final Report for this project includes four printable water quality Factsheets for the general public which explain tastes and odours, fluoridation, and disinfection. The Report also includes the protocols and texts for two customer engagement techniques: Blind Taste Testing and Systematic Taste Testing; as well as a comprehensive customer survey instrument to assess perceptions of drinking water quality. These can be downloaded to electronic mobile devices and used to direct face to face customer engagement with the tastes and odours of different types of potable water. The scoresheet links to a rating spreadsheet that collates results and generates graphical representations of customer acceptance of water sample taste. These tools have been used to assess customer satisfaction with water quality at large events including National Water Quality week or Utility information days.

Although water utilities recognise the value of online instruments that provide real-time monitoring capability, there are problems with visualising and interpreting datasets, and with distinguishing between data resulting from real-world changes in treatment plant operating conditions, for example changed turbidity or flow, and instrument failure. There are also challenges around instrument installation and operation. This project developed tools to support data visualisation and interpretation by building a prototype visualisation platform for analysing complex online UV spectral data in conjunction with weather and lab data (see Factsheet 2 ‘Development of an online platform’). To improve differentiation between instrument failure and real-world data a Bayesian Belief Network model was developed to analyse patterns and variations within datasets. Real operational, high turbidity data was used to demonstrate that this model could accurately identify different causes for the readings which included filter ripening, backwash and other causes (see Factsheet 3 ‘Improving decision making in water plant operability through Bayesian Belief networks’). Strategies for instrument installation and operation were illustrated through case studies.

The aim of this project was to examine the utility of ultra-violet (UV) spectroscopy as a real-time water quality monitoring system. Two case studies were conducted. One assessed stormwater and showed that the UV system could detect that the first flush contained chemicals used as surrogates for water quality whereas later flows contained bacterial and biological markers. From this it was concluded that the sources of bacteria and chemicals were probably physically separated until they were mixed during surface runoff. In the second case study, the UV measurement equipment was set up in a groundwater filtration plant. It proved possible to accurately characterise water quality changes and assist operational decision-making.