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 plants (WTP) take in source waters then remove 95-99% of blue-green algae (cyanobacteria) cells and the toxins they produce. During this removal process waste sludge is generated and transferred from clarifier tanks in the treatment plant to lagoons. It was thought that confinement in the sludge killed the cyanobacteria, but this research found that when algal blooms have generated very high cell numbers, viable, toxin-producing cyanobacteria are retained in the sludge and can release toxins into the clarifier supernatant. It was concluded that timely removal to lagoons will avoid problems, and it is recommended that risk assessment for recycling lagoon supernatant back to the head of the WTP should incorporate extended times of 3 to 4 weeks after the end of algal blooms, to ensure cyanobacterial cell death and toxin degradation.

Cyanobacterial blooms in surface waters are a source of cells, taste and odour compounds, and a range of toxins. This research optimised treatment processes for the removal and control of cyanobacteria and their metabolites from a range of source waters. It was concluded that pre-chlorination is not advisable when cyanobacteria are present, but that in some situation’s potassium permanganate is a viable alternative. Although all three tested coagulants; ferric chloride, aluminium chlorohydrate and aluminium sulphate (alum) removed 90 to 95% of cells, alum at pH 6.3 was the most cost-effective. Maintaining pH > 6 reduced cell lysis and metabolite release. Since cyanobacteria in sludge remained viable for 2-3 weeks it was recommended that sludge detention in the clarifiers should be minimised.