The environmental conditions which cause blue-green algae (cyanobacteria) blooms vary according to location, the climate, and other attributes of aquatic ecosystems. This variety has made it difficult to develop one broadly applicable predictive model for cyanobacterial blooms. Water utilities monitor source waters to implement cyanobacterial risk management programmes but there are no standard protocols while limited information transfer between utilities has prevented the identification of management strategies that do or do not work. This research reviewed literature about early warning systems (Almuhtaram et al., 2021) and source control strategies, conducted a survey of 35 utilities in America and Canada (74%) and Australia (Kibuye et al., 2021) and evaluated selected control strategies. These different types of information were synthesised into decision trees within an overarching guidance document. It was concluded that a 3-tier framework to detect algal blooms which monitored biological activity, then confirmed the identification of cyanobacterial genes and associated metabolites gave sufficient early warning, while multi-barrier control strategies gave field-scale efficacy and enabled timely responses.

Cyanobacteria (blue-green algae) which float in reservoirs have been studied for decades because when they bloom, the very high cell numbers cause a problem for water treatment plant (WTP) operators, who have to remove the cells, toxins, and taste and odour compounds they produce. Benthic, bottom-living cyanobacteria which also produce toxins were recently discovered in Australian reservoirs. The problem is that benthic cyanobacteria are not included in routine monitoring practices and very little is known about them. This research provided information about the incidence of benthic cyanobacteria and the toxins they produce in various catchments; identified environmental conditions that stimulate bloom formation, and investigated naturally occurring biodegradation of taste and odour compounds. It was concluded that there is a need to monitor benthic cyanobacterial mats to ascertain the risk they pose, and to obtain additional in-situ data about more benthic species, because this will support the construction of predictive models to facilitate improved management of catchment and source waters.

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.

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.

‘Microbial source tracking’ (MST) is a technique that aims to identify the animal that excreted faeces and polluted water. There are a number of ways to do this, but the problem is that no one method accurately identifies the origins of faecal pollution in environmental water samples. This research found that faeces could be stored in a freezer or a laboratory -80°C cold-store for up to a month without changing the relative numbers of the different types of bacteria in the samples of faeces. Up to seven faeces samples from different animals were mixed together and examined using 17 techniques to identify the original animals. Three of the most accurate and reliable methods used mitochondrial DNA, the analysis of a bacterial enzyme sequence (beta-glucuronidase), and specific DNA sequences form bacteria known to come from humans, horses and cows. These three types of tests were selected for inclusion in a ‘Toolbox’ from which a combination of methods will allow accurate and reliable management of faecal contaminants in source waters.

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.

Cyanobacterial blooms are a major problem for reservoir managers because of the large numbers of cells and the toxins they contain. These blue-green algae blooms have traditionally been treated with the algaecide copper sulphate, but this was expensive and unsustainable because it killed non-target species and left residual contaminants. This research examined and rejected alternatives: other copper-based algaecides, hydrogen peroxide, substances that trap cyanobacterial-growth supporting nutrients on the floor of the reservoir, and mechanical surface mixers. Laboratory experiments that tested the ability of ultrasound to prevent the photosynthetic cyanobacteria from floating at the depth that optimises light absorption were initially promising because the ultrasound reduced photosynthesis and metabolism and the blue-green algae died. Unfortunately, when an ultrasound system was deployed in a reservoir, the much larger volume of water attenuated and ‘absorbed’ the low-power ultrasound and led to the conclusion that sustainable, environmentally friendly levels of ultrasound do not provide effective control of blue-green algae. This rigorously conducted scientific study has generated useful information about methods which do not work, and resources can now be directed to promising new innovations.

This research has provided the most comprehensive account of the geographical distribution of blue-green algae (cyanobacteria), and the toxins they produce, in Australia. The blue-green algae cells were collected and stored. This collection now forms a valuable national asset which is particularly valuable for managing the complex array of factors that affect the accurate assessment of risk posed by any one algal bloom. Not all cyanobacteria produce toxins, and the identification of species and the presence of toxin is an important step in the decision-making process necessary to produce high quality, safe water. This research led to some notable conclusions; one being that a traditional method that uses cell-shape to identify algal species is unreliable, and also that the number of cyanobacterial cells does not necessarily correlate to the amount of toxin in source waters. Five laboratory tests were reviewed and it was found that tests for cylindrospermopsin were reliable, but tests for microcystin and saxitoxins differed as to the amount they measured, although they reliably identified the presence or absence of toxin. Problem cyanobacteria species are ubiquitous in Australia and if climatic events create favourable conditions, blooms can occur in unexpected locations.