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.

Reverse osmosis (RO) is used to desalinate seawater and brackish groundwater, and to remove microscopic pathogens from treated wastewater. The salty water is pressurised on one side of the RO membrane and this is part of the process that results in water molecules passing (diffusing) through the membrane to the lower pressure solution on the other side. Salts such as sodium chloride (table salt) and calcium sulphate and calcium carbonate (scale) do not diffuse easily across the RO membrane and build up on the high-pressure side. Eventually scale deposition on the membrane prevents the diffusion of water molecules and the production of freshwater declines. This research tested four commercial and three in-house antiscalent chemicals, and additionally developed a technique to monitor scale formation and RO membrane performance in real-time. It was concluded that the antiscalent ‘PC-191T’ was best and that adding an ‘Electrical Impedance Spectroscope’ to RO systems has the potential to deliver a sensitive in-situ, real-time monitoring method capable of detecting very early scale formation, well before membrane performance declines. This will enable optimisation of membrane scale removal and improve the efficiency of freshwater production.

A survey of water utilities identified the top five challenges faced in daily operations, and technical, economic and literature reviews identified remote sensing strategies and technologies to address these five operational issues. The need for, and benefits of real-time monitoring which facilitates cost-effective and efficient responses to rapidly changing conditions, were common to all five challenges, which were: monitoring cyanobacteria and their metabolites, the effects of contamination and extreme climate-change driven events on water quality, the variation in climatological data over relatively small distances (need to increase focus, precision and produce ‘finer’ datasets for reservoir management), asset inspection and management and monitoring catchments for a variety of factors. This research evaluated and explained the solutions, strengths, weaknesses, and costs of products best suited for addressing each challenge.

The management of blue-green algae (cyanobacteria), and the toxins and taste and odour compounds they produce, have been the focus of more than 30 years of research, but there is still a need for a suite of user-friendly tools to assess and manage aesthetic and toxin risks. This project conducted an extensive literature review about the ability of six treatment paradigms to remove MIB, geosmin, saxitoxins, microcystins and cylindrospermopsin. An empirical spreadsheet-base model was then built and used to simulate ‘whole-of-plant’ removal of cells and toxic metabolites. This model performed well when tested with two years of full-scale sampling data.

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.

Water treatment plant operators remove cyanobacteria and the toxins they produce from source waters but calculating the amount of treatment needed for effective removal is difficult, particularly in bloom conditions when cyanobacterial cell numbers and toxins change quickly. Current cell counting and toxin measurement can take hours or days to complete, and the results are not available quickly enough to help treatment plant operators respond to changing conditions. There is a need for a real-time method that gives instant results. This research examined the utility of fluorometers; probes that emit light that is ‘reflected’ back at different wavelengths by living cells and other matter in the water and is detected by the fluorometer. It was found that when only one species of cyanobacteria was present, there was a good correlation between the fluorescent signal and cell number, particularly when source waters were clear and not cloudy. Cell numbers did not relate well to levels of toxins or taste and odour compounds. When fluorometers were installed in 13 water treatment plants the correlation between cyanobacteria cell numbers and fluorometer signals was validated, and this led to the conclusion that fluorometers can give early warning of blue-green algae blooms.

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.