Water reservoirs and lakes are gaining popularity for recreation activities as populations increase and green spaces become in high demand. However, these activities may cause contamination to critical water resources. This study investigates the impact of recreational activities on the presence and concentration of polycyclic aromatic hydrocarbons (PAHs) and ultraviolet (UV) filters in drinking water reservoirs in Southeast Queensland, Australia. Polydimethylsiloxane passive samplers were used to monitor 14 lakes over a 3-year period, focusing on seasonal variations and the influence of recreational activities such as petrol-powered boating and swimming. A total of 15 PAHs and six UV filters were detected, with chrysene (97%) and octyl salicylate (34%) being the most prevalent PAH and UV filter, respectively. Polycyclic aromatic hydrocarbon levels were statistically significantly higher in lakes permitting petrol-powered boating, especially during summer (p = 0.005 to 0.05). Lake Maroon and Lake Moogerah were the only sites that showed significantly higher PAH levels in summer (3.9 ± 1.1 and 4.0 ± 1.2 ng L-1, respectively) than winter (1.6 ± 0.61 and 1.5 ± 0.84, respectively). Ultraviolet filters were generally detected in higher levels in lakes allowing swimming, with Lake Moogerah and Lake Sommerset measuring UV filter concentrations of 20 ± 4.1 and 20 ± 11 ng L-1 in summer, respectively. Other lakes that do not permit swimming, such as Lake Maroon and Lake Samsonvale, also exhibited elevated UV filter levels, suggesting illegal swimming. These findings highlight the complexity of PAH and UV filter presence, influenced by multiple factors including lake size, recreational activity type, and seasonal variations. The levels of individual PAHs and UV filters in this study were below established freshwater guidelines. However, when considering their bioaccumulation potential and mixture toxicity, mitigating the impact of these substances on our environment and the organisms within it should be of priority.

The nuisance raphidophyte Gonyostomum semen (Ehrenberg) Diesing blooms in lakes and is known to produce a mucilage which can cause human skin irritation. Parameters such as water temperature, iron and high dissolved organic matter loads are shown to be important drivers in temperate regions. However, the causes of blooms in warmer latitudes are less well understood. Over a 6 mo study period, we used field monitoring and a nutrient addition experiment within a water reservoir to examine the role of nutrients in promoting G. semen growth. Early in the study, an inflow event delivered nutrients which increased dissolved inorganic nitrogen (DIN) concentrations 2-fold and filterable reactive phosphorus (FRP = phosphate) 4-fold. This event shifted the phytoplankton community from a mixed community to one dominated by G. semen. Two months after the inflow event, the effect of nutrients in promoting G. semen was confirmed with a nutrient addition experiment. Total biovolumes of this species across the study were strongly predicted by FRP and nitrate + nitrite concentrations. G. semen biovolumes also decreased as ratios of total nitrogen (TN):total phosphorus (TP) and DIN:FRP increased, highlighting the importance of P inputs. The stable isotope tracer 15 N-nitrate was also used to trace N through the G. semen-dominated phytoplankton community. The tracer rapidly cycled through the G. semen-dominated phytoplankton community in 1-2 d, settled and remineralized, providing an ongoing source of DIN for maintaining blooms. Overall, the results highlight the importance of FRP, and to a lesser extent nitrate, in promoting blooms of this nuisance species.

A major stormwater harvesting scheme is being investigated at Aura (McAlister et al 2017 and Figure 1). This scheme could see 2 GL/yr of urban stormwater being harvested and used to augment the nearby Ewen Maddock Dam, owned and operated by Seqwater. This paper describes an innovative and transparent riskbased approach that was developed to assess potential water quality, environmental and public health issues associated with the scheme and implemented for the first time in the region. Previous and ongoing technical investigations being conducted to inform this process are also described.

The Mudgeeraba drinking water treatment plant, in Southeast Queensland, Australia, can withdraw raw water from two different reservoirs: the smaller Little Nerang dam (LND) by gravity, and the larger Advancetown Lake, through the use of pumps. Selecting the optimal intake is based on water quality and operators' experience; however, there is potential to optimise this process. In this study, a comprehensive hybrid (data-driven, chemical, and mathematical) intake optimisation model was developed, which firstly predicts the chemicals dosages, and then the total (chemicals and pumping) costs based on the water quality at different depths of the two reservoirs, thus identifying the cheapest option. A second data-driven, probabilistic model then forecasts the volume of the smaller LND 6 weeks ahead in order to minimise the depletion and spill risks. This is important in case the first model identifies this reservoir as the optimal intake solution, but this could lead in the long term to depletion and full reliance on the electricity-dependent Advancetown Lake. Both models were validated and proved to be accurate, and with the potential for substantial monetary savings for the water utility.

As part of long-term monitoring of Cryptosporidium in water catchments serving Western Australia, New South Wales (Sydney) and Queensland, Australia, we characterised Cryptosporidium in a total of 5774 faecal samples from 17 known host species and 7 unknown bird samples, in 11 water catchment areas over a period of 30 months (July 2013 to December 2015). All samples were initially screened for Cryptosporidium spp. at the 18S rRNA locus using a quantitative PCR (qPCR). Positives samples were then typed by sequence analysis of an 825 bp fragment of the 18S gene and subtyped at the glycoprotein 60 (gp60) locus (832 bp). The overall prevalence of Cryptosporidium across the various hosts sampled was 18.3% (1054/5774; 95% CI, 17.3-19.3). Of these, 873 samples produced clean Sanger sequencing chromatograms, and the remaining 181 samples, which initially produced chromatograms suggesting the presence of multiple different sequences, were re-analysed by Next- Generation Sequencing (NGS) to resolve the presence of Cryptosporidium and the species composition of potential mixed infections. The overall prevalence of confirmed mixed infection was 1.7% (98/5774), and in the remaining 83 samples, NGS only detected one species of Cryptosporidium. Of the 17 Cryptosporidium species and four genotypes detected (Sanger sequencing combined with NGS), 13 are capable of infecting humans; C. parvum, C. hominis, C. ubiquitum, C. cuniculus, C. meleagridis, C. canis, C. felis, C. muris, C. suis, C. scrofarum, C. bovis, C. erinacei and C. fayeri. Oocyst numbers per gram of faeces (g-1) were also determined using qPCR, with medians varying from 6021-61,064 across the three states. The significant findings were the detection of C. hominis in cattle and kangaroo faeces and the high prevalence of C. parvum in cattle. In addition, two novel C. fayeri subtypes (IVaA11G3T1 and IVgA10G1T1R1) and one novel C. meleagridis subtype (IIIeA18G2R1) were identified. This is also the first report of C. erinacei in Australia. Future work to monitor the prevalence of Cryptosporidium species and subtypes in animals in these catchments is warranted.

An early warning scheme is proposed that runs ensembles of inferential models for predicting the cyanobacterial population dynamics and cyanotoxin concentrations in drinking water reservoirs on a diel basis driven by in situ sonde water quality data. When the 10- to 30-day-ahead predicted concentrations of cyanobacteria cells or cyanotoxins exceed pre-defined limit values, an early warning automatically activates an action plan considering in-lake control, e.g. intermittent mixing and ad hoc water treatment in water works, respectively. Case studies of the sub-tropical Lake Wivenhoe (Australia) and the Mediterranean Vaal Reservoir (South Africa) demonstrate that ensembles of inferential models developed by the hybrid evolutionary algorithm HEA are capable of up to 30 days forecasts of cyanobacteria and cyanotoxins using data collected in situ. The resulting models for Dolicospermum circinale displayed validity for up to 10 days ahead, whilst concentrations of Cylindrospermopsis raciborskii and microcystins were successfully predicted up to 30 days ahead. Implementing the proposed scheme for drinking water reservoirs enhances current water quality monitoring practices by solely utilising in situ monitoring data, in addition to cyanobacteria and cyanotoxin measurements. Access to routinely measured cyanotoxin data allows for development of models that predict explicitly cyanotoxin concentrations that avoid to inadvertently model and predict non-toxic cyanobacterial strains.

This paper proposes a novel multi-objective hybrid evolutionary algorithm (MOHEA) that allows spatially-explicit modelling of local outbreaks and dispersal of population density. The MOHEA was tested for modelling at once two cyanobacteria populations at one lake site, same population in two different lakes and same population at three different sites of one lake. All experiments with MOHEA utilized water quality time-series and abundances of Anabaena and Cylindrospermopsis monitored in the sub-tropical Lakes Wivenhoe and Somerset in Queensland (Australia) from 1999 to 2010. Results have demonstrated the capacity of MOHEA to determine generic rules that: (1) reveal crucial thresholds for outbreaks of cyanobacteria blooms, and (2) perform spatially-explicit forecasting of timing and magnitudes 7-day-ahead of bloom events. (C) 2016 Elsevier B.V. All rights reserved.

Manganese monitoring and removal is essential for water utilities in order to avoid supplying discoloured water to consumers. Traditional manganese monitoring in water reservoirs consists of costly and time-consuming manual lake samplings and laboratory analysis. However, vertical profiling systems can automatically collect and remotely transfer a range of physical parameters that affect the manganese cycle. In this study, a manganese prediction model was developed, based on the profiler's historical data and weather forecasts. The model effectively forecasted seven-day ahead manganese concentrations in the epilimnion of Advancetown Lake (Queensland, Australia). The manganese forecasting model was then operationalised into an automatically updated decision support system with a user-friendly graphical interface that is easily accessible and interpretable by water treatment plant operators. The developed tool resulted in a reduction in traditional expensive monitoring while ensuring proactive water treatment management.

Studies on endocrine disruption in Australia have mainly focused on wastewater effluents. Limited knowledge exists regarding the relative contribution of different potential sources of endocrine active compounds (EACs) to the aquatic environment (e.g., pesticide run-off, animal farming operations, urban stormwater, industrial inputs). In this study, 73 river sites across mainland Australia were sampled quarterly for 1 year. Concentrations of 14 known EACs including natural and synthetic hormones and industrial compounds were quantified by chemical analysis. EACs were detected in 88 % of samples (250 of 285) with limits of quantification (LOQ) ranging from 0.05 to 20 ng/l. Bisphenol A (BPA; LOQ = 20 ng/l) was the most frequently detected EAC (66 %) and its predicted no-effect concentration (PNEC) was exceeded 24 times. The most common hormone was estrone, detected in 28 % of samples (LOQ = 1 ng/l), and the PNEC was also exceeded 24 times. 17α-Ethinylestradiol (LOQ = 0.05 ng/l) was detected in 10 % of samples at concentrations ranging from 0.05 to 0.17 ng/l. It was detected in many samples with no wastewater influence, and the PNEC was exceeded 13 times. In parallel to the chemical analysis, endocrine activity was assessed using a battery of CALUX bioassays. Estrogenic activity was detected in 19 % (53 of 285) of samples (LOQ = 0.1 ng/l 17β-estradiol equivalent; EEQ). Seven samples exhibited estrogenic activity (1–6.5 ng/l EEQ) greater than the PNEC for 17β-estradiol. Anti-progestagenic activity was detected in 16 % of samples (LOQ = 8 ng/l mifepristone equivalents; MifEQ), but the causative compounds are unknown. With several compounds and endocrine activity exceeding PNEC values, there is potential risk to the Australian freshwater ecosystems.

The University of Queensland, The National Research Centre for Environmental Toxicology (Entox), 39 Kessels Rd., Coopers Plains QLD 4108, Australia. k.sarit@uq.edu.au Griffith University, School of Environment, Nathan QLD 4111, Australia. SEQWater, PO Box 16146, City East QLD 4002, Australia. Queensland Health Forensic and Scientific Services, Coopers Plains QLD 4108, Australia. NIOZ Royal Netherlands Institute for Sea Research, P.O. Box 59, 1790 AB Texel, The Netherlands.

A batch test approach was used to assess the in situ attenuation by natural reservoir systems of selected disinfection by‐products (DBPs). The aim was to determine which natural attenuation processes (volatilisation, photolysis and biodegradation) dominated for selected trihalomethanes (THMs) and N‐nitrosodimethylamine (NDMA), common DBPs present in reclaimed water which could be used to potentially augment drinking water supplies. Attenuation rates for THMs were found to be all very similar, with half‐lives ranging from 1.5–1.6 days for open batch tests. The dominant attenuation mechanisms for THMs were volatilisation with hydrolysis and biodegradation of potentially minor importance. NDMA had a half‐life of 3.5–4.3 days for vials exposed to light. The most important attenuation mechanism for NDMA was photolysis with volatilisation and biodegradation of minor importance. The results indicate that the selected DBPs could be effectively attenuated by a natural reservoir system such as a surface water reservoir.

Trace organic contaminant (TrOC) studies in Australia have, to date, focused on wastewater effluents, leaving a knowledge gap of their occurrence and risk in freshwater environments. This study measured 42 TrOCs including industrial compounds, pesticides, and pharmaceuticals and personal care products by liquid chromatography tandem mass spectrometry at 73 river sites across Australia quarterly for 1 yr. Trace organic contaminants were found in 92% of samples, with a median of three compounds detected per sample (maximum 18). The five most commonly detected TrOCs were the pharmaceuticals salicylic acid (82%, maximum = 1530 ng/L), paracetamol (also known as acetaminophen; 45%, maximum = 7150 ng/L), and carbamazepine (27%, maximum = 682 ng/L), caffeine (65%, maximum = 3770 ng/L), and the flame retardant (2-chloroethyl) phosphate (44%, maximum = 184 ng/L). Pesticides were detected in 28% of the samples. To determine the risk posed by the detected TrOCs to the aquatic environment, hazard quotients were calculated by dividing the maximum concentration detected for each compound by the predicted no-effect concentrations. Three of the 42 compounds monitored (the pharmaceuticals carbamazepine and sulfamethoxazole and the herbicide simazine) had a hazard quotient >1, suggesting that they may be causing adverse effects at the most polluted sites. A further 10 compounds had hazard quotients >0.1, indicating a potential risk; these included four pharmaceuticals, three personal care products, and three pesticides. Most compounds had hazard quotients significantly <0.1. The number of TrOCs measured in this study was limited and further investigations are required to fully assess the risk posed by complex mixtures of TrOCs on exposed biota.

Growing concern about the environmental impact of ionizable and polar organic chemicals such as pesticides, pharmaceuticals and personal care products has lead to the inclusion of some in legislative and regulatory frameworks. It is expected that future monitoring requirements for these chemicals in aquatic environments will increase, along with the need for low cost monitoring and risk assessment strategies. In this study the uptake of 13 neutral and 6 ionizable pesticides, pharmaceuticals and personal care products by modified POCIS (with Strata™-X sorbent) and Chemcatchers™ (SDB-RPS or SDB-XC) was investigated under controlled conditions at pH = 6.5 for 26 days. The modified POCIS and Chemcatcher™ (SDB-RPS) samplers exhibited similar performance with the uptake of the majority of the 19 chemicals of interest categorised as linear over the 26 day deployment. Only a few ionized herbicides (picloram and dicamba) and triclosan showed negligible accumulation. Chemcatcher™ with SDB-XC sorbent performed relatively poorly with only carbamazepine having a linear accumulation profile, and 8 compounds showing no measurable accumulation. Differences in the uptake behavior of chemicals were not easily explained by their physico-chemical properties, strengthening the requirement for detailed calibration data. PES membranes accumulated significant amount of some compounds (i.e. triclosan and diuron), even after extended deployment (i.e. 26 days). At present there is no way to predict which compounds will demonstrate this behavior. Increasing membrane pore size from 0.2 to 0.45 μm for Chemcatcher™ (SBD-RPS) caused an average increase in Rs of 24%.

Little Nerang Dam (LND, Figure 1a) is a subtropical, warm monomictic, freshwater reservoir, located approximately 80 km south of Brisbane, Australia. LND has a surface area of 0.44 km2 and full supply capacity of 6,465 ML. Maximum water depth is 36.2 m (avg. 14.8 m). Mixing processes that drive water exchange between the epilimnion, metalimnion and hypolimnion in LND are primarily determined by the wind, inflow and outflow. Due to periodicity of the wind forcing, water movement in LND typically follows a distinct diurnal cycle. This cycle is interrupted by storm events that can dominate mixing processes in the reservoir for short (1-5 days) periods. For water resource management applications an understanding of underlying physical processes that drive mixing, as well as their interactions within a water reservoir, are necessary for effective water quality management (Ji, 2008). Field monitoring from 2 – 8 February 2011 was conducted in LND during highly stratified conditions (Lake Number, LN > 150) to increase understanding of mixing processes in LND, when wind forcing is the main energy supplier and no major inflows and/or outflows are present...

Introduction Sub-tropical water supply reservoirs are under increasing pressure from population driven demand for water resources, transformation and degradation of terrestrial catchments, climate variability and associated increased frequency and severity of extreme weather events (both drought and flood cycles). To mitigate the potential negative impacts of these pressures water resource managers often adopt a monitoring-modelling-management (M-M-M) approach to improve the information on which decisions are based. An overview of the application of a M-M-M approach to address extreme drought in a large sub-tropical water supply reservoir is provided to highlight some challenges and opportunities that the M-M-M approach presents. The study focused on Lake Wivenhoe (27.394022 °S, 152.609334 °E), a sub-tropical, warm monomictic, freshwater reservoir, located 40 km west of Brisbane, Australia. The Lake’s surface area and storage capacity are approximately 10,940 hectares and 1,165,000 Ml respectively at full water supply capcity with an additional 1,450,000 Ml of flood storage. Maximum and average depths are 50 m and 10 m respectively at full water supply capacity. The main catchment inflow is from the 5,438 km2 Upper Brisbane Catchment. The Lake also receives significant inflows via releases from Somerset Dam (located immediately upstream of Lake Wivenhoe on the Stanley River system) and the Splityard Creek hydro-power station (a pumped storage hydroelectric facility that drives both inflows and outflows). Average rainfall and evaporation are approximately 940 mm y-1 and 1,872 mm y-1 respectively [Seqwater, 2005]. The extent of groundwater interactions with the Lake is largely unexplored...