Growing populations and climate change place increased pressures on our water supplies. Stormwater harvesting and reuse offers a potential option to augment traditional water resources. Before it can be utilised within a given context, however, its safety must be established. This project developed a Bayesian Belief Network (BBN) model representing pathogen sources and treatment barriers within a proposed stormwater harvesting scheme. The BBN can utilise a range of data sources and be constantly updated to assist managers to engage effectively with stakeholders and identify the most appropriate combination of risk management strategies available to them.

Honours Thesis completed by Dean Albert Mensinga in October 2019.

Lakes and reservoirs are essential for water supply for humans and agriculture, and have an important role in flow regulation, biodiversity, and streamflow below dams. Australia has been subject in recent decades to severe drought which has heightened the importance of reservoirs for human populations and highlighted the need for careful management of water levels to maintain continuity of supply. Climate change is likely to exacerbate water shortages, with extended periods of drought, interspersed with more discrete and intense rainfall, leading to challenges for storing water in reservoirs and potentially affecting the quality of water.

In this project, Griffith University researchers examined the water quality risks from low and variable water levels in dams and reservoirs in Eastern Australia.

Fish, frogs, and other aquatic animals sometimes show signs of ‘endocrine disruption’; aberrant changes to their hormone or reproductive systems that are thought to be caused by chemicals in the water they inhabit. Very few of these chemicals have been identified, and this prevents the use of classical chemistry-based analytical methods. The other problem is that the levels of hormone-like chemicals which have endocrine-disrupting biological effects tend to be so low that standard methods cannot detect them. This research developed a suite of biological tests sensitive enough to detect very low levels of chemicals associated with certain types of endocrine disruption. These tests were used to examine wastewater, surface water and drinking water collected from Australia, South Africa and four European countries. The water samples were also subjected to standard chemical analysis, and the datasets compared. It was concluded that some wastewater and surface water samples contained compounds that interacted with components of the estrogen, progesterone, androgen and mineralocorticoid hormone systems, but none of the biological tests detected endocrine disrupting activity in drinking water.

Burkholderia pseudomallei is a bacteria that is widespread in SE Asia and northern Australia, where there are an average of 16 cases per 100,000 people. This research found that water samples collected in and around Cairns from June to September did NOT contain Burkholderia pseudomallei and led to the conclusion that the risk of infection is much lower than in Darwin or Townsville.

The ADWG has methods for predicting risks to water quality, but these were not developed for managing extreme climate-change driven weather events such as bushfires or floods. This research developed a risk assessment tool for managing water-related health risks associated with extreme weather events. Real-world datasets and experience of water cloudiness (turbidity), colour and blue-green algae were used to create and validate environmental models which were developed further by applying Baysian network and System Dynamics concepts. This iteration of the model was not constrained by, and did not reflect existing risk profiles, but was judged to be flexible enough to provide a realistic representation of future hazards arising from extreme weather events.

The ADWGs include methods and strategies for calculating all types of risks to water quality but lack guidance for managing extreme weather events. This research completed a number of activities which included the collection and analysis of 10 Australian extreme weather events and listed transferrable, real-world lessons and experiences. Two hypothetical scenarios based on extreme flood, and on bushfire combined with significant rainfall, were designed then ‘managed’ by diverse water utility personnel and health regulators. This activity also generated a list of key lessons. Optimal methods for calculating short-term Exposure Trigger Values for hazardous compounds were identified. Outcomes from all the project activities were processed and collated into a practical instruction guide to support Australian water utilities in their management of extreme weather events.

Blue-green algae (cyanobacteria) reduce water quality especially when they bloom and form high numbers of cells which produce toxins, and taste and odour compounds. Most cyanobacteria photosynthesise and tend to grow and float at depths which optimise their exposure to sunlight, but an increase in unexplained occurrences of taste and odour compounds in reservoirs, and a bloom of benthic (bottom-living) cyanobacteria, forced the closure of a water supply. This research examined the role that bottom-living benthic cyanobacteria play in the production of toxins or taste and odour compounds. Seven DNA-based PCR tests were developed to identify benthic species of cyanobacteria and their capacity for producing toxins. A taste and odour compound, and two toxins were found in winter and spring in an SA reservoir, whereas a different taste and odour compound and toxin assemblage were found in summer and autumn in a reservoir in NSW. These results will help water suppliers to anticipate and manage future aesthetic or toxin issues related to benthic cyanobacteria.

Water utilities lack the information they need to implement risk-based adaptation and planning strategies that incorporate climate change. This research addresses this problem by modelling the effects of climate change on reservoirs in three climate zones: temperate, humid tropical and Mediterranean. By integrating different modelling approaches it was concluded that increased temperatures will increase water stratification; the differences in water temperature that occur with depth. This is important because the duration and type of stratification affects the storage and release of substances from reservoir floors and this in turn affects blue-green algal blooms and water quality. The integrated modelling approach developed in this project can be applied to the management of contaminants running off the catchments and for future risk assessment. This information will also support the development of business cases for targeted catchment interventions.

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.