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A reliable simulation of the manganese cycle in water supply system is essential for timely and effective manganese treatment strategies. A data-driven model estimating manganese levels in the treated water was developed through a threshold-based approach using raw water and supernatant return manganese levels. This data-driven model and a three-dimensional manganese cycle model for the source reservoir were integrated to simulate the overall manganese variations from the lake to the treated water. A decision support system based on the developed data-driven model was established to allow operators to react to situations that could result in elevated levels of manganese in the treated water. Scenario analyses were completed to examine the manganese variations in the reservoir, raw water and treated water due to different precipitations and wind conditions and to allow the identification of optimal strategies for manganese management from the reservoir to the water supply system.

A series of experiments were undertaken in order to understand and predict the dosage of powdered activated carbon required to remove taste and odour compounds in an Australian drinking water treatment plant. Competitive effects with organic matter removal by aluminium sulphate during coagulation were also quantified. Data on raw and finished water quality following jar tests, as well as chemical dosages and treatment performance, were statistically analysed, and a data-driven prediction model was developed. The developed powdered activated carbon dosage prediction model can be used by the plant operators for rapid dosage assessment and can increase the preparedness of the plant to sudden taste and odour events. It was also found that total organic carbon levels and properties greatly affect the ability of powdered activated carbon to remove taste and odour compounds; on the other hand, total organic carbon removal is not affected by high taste and odour levels, since these were still much lower than organic carbon concentrations.

Understanding and predicting Taste and Odour events is as difficult as critical for drinking water treatment plants. Following a number of events in recent years, a comprehensive statistical analysis of data from Lake Tingalpa (Queensland, Australia) was conducted. Historical manual sampling data, as well as data remotely collected by a vertical profiler, were collected; regression analysis and self-organising maps were the used to determine correlations between Taste and Odour compounds and potential input variables. Results showed that the predominant Taste and Odour compound was geosmin. Although one of the main predictors was the occurrence of cyanobacteria blooms, it was noticed that the cyanobacteria species was also critical. Additionally, water temperature, reservoir volume and oxidised nitrogen availability, were key inputs determining the occurrence and magnitude of the geosmin peak events. Based on the results of the statistical analysis, a predictive regression model was developed to provide indications on the potential occurrence, and magnitude, of peaks in geosmin concentration. Additionally, it was found that the blue green algae probe of the lake’s vertical profiler has the potential to be used as one of the inputs for an automated geosmin early warning system.

The effect of ozone on the formation, breakup and re-formation of flocs generated using ferric sulphate has been investigated using conventional jar test procedure and by continuous optical monitoring using raw water. Using a range of different dosage of coagulant, the breakage of flocs was followed at a high stirring speed, corresponding to average shear rate (G) of about 518 s(-1). Most of the breakage occurred within a few seconds of increasing the shear rate. After breakage the stirring rate was reduced to the original value of 50 rpm (G approximately equals 23 s(-1)) to allow the flocs to re-grow. It was found that only limited re-growth of flocs occurred indicating irreversibility of the floc breakup process. For preozonated samples, the re-growth of flocs occurred to a much greater extent with lower residual turbidity. The findings show that the use of preozonation (1.25 and 1.50 mg/L) provides beneficial results to both improve turbidity removal and reduce coagulant requirement. Furthermore, better re-formation of flocs is achievable.

Study region Advancetown Lake, South-East Queensland (Australia). Study focus A detailed analysis of available meteorological, physical and chemical data (mostly coming from a vertical profiler remotely collecting data every 3 h) was performed in order to understand and model the manganese cycle. A one-dimensional model to calculate manganese vertical velocities was also developed. New hydrological insights for the region The soluble manganese concentration in the hypolimnion is dominantly dependent on the dissolved oxygen level, pH and redox potential, which determine the speed of the biogeochemical reactions between different manganese oxidation states. In contrast, the manganese level in the epilimnion is mainly affected by the transport processes from the hypolimnion and thus to the strength of the thermal stratification, with high concentrations recorded solely during the winter lake circulation and wind playing only a minor role. The value of the peak concentration was found to be proportional to the amount of manganese in the hypolimnion and to the temperature of the water column at the beginning of the circulation period. In case of partial circulation only, a very high peak is espected during the next full winter turnover. This issue will increase in the future due to global warming and increased number of years with partial circulations only. These findings provide water authorities with increased manganese predictive power and thus proactive water treatment management strategies.