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Business cases promoting the introduction of digital water metering (DWM) have, to date, focused on a limited number of benefits, especially water savings, metering costs, occupational health and safety (OHS), and deferral of capital works. An earlier study by the authors catalogued 75 possible benefits and developed a taxonomy based on a literature review, interviews and water industry reports. The objective of the present study was to elicit the opinions of Australian water industry experts on the benefits, then use the opinions to form probability distributions which, in future work, could be used to model the value of DWM benefits. The study findings have implications for researchers and practitioners seeking to accurately and stochastically model the benefits of DWM transformation programmes. Thematic analyses on the open ended responses scaled likelihood and estimated value of benefits into comparable units. We found 82% support for the benefits of DWM with only 6% disagreement and 12% non-commital, the savings value of cost of water benefits were predominately expected to range between 5% and 10% and much higher in some individual situations, while charges/operational costs benefits were predominately expected to range between 45% and 100%, and, moreover, we indicated how a risk-based range of project benefit could potentially be calculated. Opportunities for further investigations were identified.

Digital or intelligent water meters are being rolled out globally as a crucial component in improving urban water management. This is because of their ability to frequently send water consumption information electronically and later utilise the information to generate insights or provide feedback to consumers. Recent advances in machine learning (ML) and data analytic (DA) technologies have provided the opportunity to more effectively utilise the vast amount of data generated by these meters. Several studies have been conducted to promote water conservation by analysing the data generated by digital meters and providing feedback to consumers and water utilities. The purpose of this review was to inform scholars and practitioners about the contributions and limitations of ML and DA techniques by critically analysing the relevant literature. We categorised studies into five main themes: (1) water demand forecasting; (2) socioeconomic analysis; (3) behaviour analysis; (4) water event categorisation; and (5) water-use feedback. The review identified significant research gaps in terms of the adoption of advanced ML and DA techniques, which could potentially lead to water savings and more efficient demand management. We concluded that further investigations are required into highly personalised feedback systems, such as recommender systems, to promote water-conscious behaviour. In addition, advanced data management solutions, effective user profiles, and the clustering of consumers based on their profiles require more attention to promote water-conscious behaviours.

Collaboration between government agencies and communities for sustainable water governance in remote Indigenous communities is espoused as a means to contribute to more equitable, robust, and long-term decision-making and to ensure that water services contribute to broader considerations of physical, social, and economic prosperity. In Australia, the uptake of collaborative water governance in remote Aboriginal and Torres Strait Island contexts has been slow and few examples exist from which to inform policy and practice. This study identifies barriers to uptake of collaborative sustainable water governance, drawing from qualitative interviews with water practitioners working in remote Indigenous Australia and analysis of key project documentation. Thematic analysis revealed discrete barriers across five key categories: (1) governance arrangements, (2) economic and financial, (3) capacity and skills, (4) data and information, and (5) cultural values and norms, with many barriers identified, unique to the remote Indigenous Australian context. The paper provides insights into how to address these barriers strategically to create transformative and sustainable change for Indigenous communities. The results contribute to the greater body of knowledge on sustainable and collaborative water governance, and they are of relevance for broader water management, policy, and research.

In recent years, titanium dioxide (TiO2) has increasingly been used as an inorganic ultraviolet (UV) filter for sun protection. However, nano-TiO2 may also pose risks to the health of humans and the environment. Thus, to adequately assess its potential adverse effects, a comprehensive understanding of the behaviour and fate of TiO2 in different environments is crucial. Advances in analytical and modelling methods continue to improve researchers’ ability to quantify and determine the state of nano-TiO2 in various environments. However, due to the complexity of environmental and nanoparticle factors and their interplay, this remains a challenging and poorly resolved feat. This paper aims to provide a focused summary of key particle and environmental characteristics that influence the behaviour and fate of sunscreen-derived TiO2 in swimming pool water and natural aquatic environments and to review the current state-of-the-art of single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) approaches to detect and characterise TiO2 nanoparticles in aqueous media. Furthermore, it critically analyses the capability of existing fate and transport models to predict environmental TiO2 levels. Four particle and environmental key factors that govern the fate and behaviour of TiO2 in aqueous environments are identified. A comparison of SP-ICP-MS studies reveals that it remains challenging to detect and characterise engineered TiO2 nanoparticles in various matrices and highlights the need for the development of new SP-ICP-MS pre-treatment and analysis approaches. This review shows that modelling studies are an essential addition to experimental studies, but they still lack in spatial and temporal resolution and mostly exclude surface transformation processes. Finally, this study identifies the use of Bayesian Network-based models as an underexplored but promising modelling tool to overcome data uncertainties and incorporates interconnected variables.

A comprehensive review was conducted to assess the current state of monitoring approaches for primary faecal indicator bacteria (FIB) E. coli and enterococci. Approaches were identified and examined in relation to their accuracy, ability to provide continuous data and instantaneous detection results, cost, environmental awareness regarding necessary reagent release or other pollution sources, in situ monitoring capability, and portability. Findings showed that several methods are precise and sophisticated but cannot be performed in real-time or remotely. This is mainly due to their laboratory testing requirements, such as lengthy sample preparations, the requirement for expensive reagents, and fluorescent tags. This study determined that portable fluorescence sensing, combined with advanced modelling methods to compensate readings for environmental interferences and false positives, can lay the foundations for a hybrid FIB sensing approach, allowing remote field deployment of a fleet of networked FIB sensors that can collect high-frequency data in near real-time. Such sensors will support proactive responses to sudden harmful faecal contamination events. A method is proposed to enable the development of the visioned FIB monitoring tool.

The recent deployment of fluorescent dissolved organic matter (fDOM) probes in dam catchments and drinking water treatment plants (DWTP) for water quality monitoring purposes has resulted in the production of a large amount of data that requires scientific evaluation. This study introduces a comprehensive, transferable methodological framework for scientists and water professionals to model fluorescence site-specific quenching on fDOM probe readings caused by temperature, suspended particles, and the inner filter effect (IFE) and applies it to an Australian subtropical reservoir. The findings revealed that quenching due to turbidity and IFE effects were best predicted by threshold autoregressive models. Raw fDOM probe measurements were validated as being more reliable if they were systematically compensated using the proposed procedure. The developed fDOM compensation procedure must consider the instrument features (i.e., wavelength broadband and responsiveness) and site-specific conditions (i.e., DOM characteristics and suspended particles). A finding of particular interest was that the compensated normalized fDOM readings had a high correlation with the low (&lt, 500 Da) molecular weight fraction of the DOM, which is more recalcitrant to removal by coagulation. As a consequence, there is potential to use compensated fDOM probe readings to provide real-time, in situ information on DOM properties in freshwater systems, which will enable water treatment plant operators to optimize the coagulation process.

Digital water meters can take Australian water utilities into the world of internet of things (IoT) and big data analytics. The potential is there for them to build more efficient processes, to enable new products and services to be offered, to defer expensive capital works, and for water conservation to be achieved. However, utilities are not mounting business cases with sufficient benefits to cover the project and operational costs. This study undertakes a literature review and interviews of industry experts in the search for unreported benefits that might be considered for inclusion in business cases. It identifies seventy-five possible benefits of which fifty-seven are classified as benefiting the water utility and forty are classified as benefiting customers (twenty-two benefit both). Many benefits may be difficult to monetize. Benefits to customers may have a small monetary benefit to the water utility but provide a significant benefit to customer satisfaction scores. However, for utilities to achieve these potential benefits, eight change enablers were identified as being required in their systems, processes, and resources. Of the seventy-five benefits, approximately half might be considered previously unreported. Finally, a taxonomy is presented into which the benefits are classified, and the enabling business changes for them to be realized are identified. Water utilities might consider the taxonomy, the benefits, and the changes required to enable the benefits when developing their business cases.

A good understanding of the physical processes of lakes or reservoirs, especially of those providing drinking water to residents, plays a vital role in water management. In this study, the water circulation and mixing processes occurring in the shallow, subtropical Tingalpa Reservoir in Australia have been investigated. Bathymetrical, meteorological, chemical and physical data collected from field measurements, laboratory analysis of water sampling and an in-situ Vertical Profile System (VPS) were analysed. Based on the high-frequency VPS dataset, a 1D model was developed to provide information for vertical transport and mixing processes. The results show that persistent high air temperature and stable reservoir water depth lead to a prolonged thermal stratification. Analysis indicates that heavy rainfalls have a significant impact on water quality when the dam level is low. The peak value of Dissolved Organic Carbon (DOC) concentration occurred in the wet season, while the specific UV absorbance (SUVA) value decreased when solar radiation increased from spring to summer. The study aims to provide a comprehensive approach for understanding and modelling the water mixing processes in similar lakes with high-frequency data from VPS&rsquo, s or other monitoring systems.

This paper reviews the drivers, development and global deployment of intelligent water metering in the urban context. Recognising that intelligent metering (or smart metering) has the potential to revolutionise customer engagement and management of urban water by utilities, this paper provides a summary of the knowledge-base for researchers and industry practitioners to ensure that the technology fosters sustainable urban water management. To date, roll-outs of intelligent metering have been driven by the desire for increased data regarding time of use and end-use (such as use by shower, toilet, garden, etc.) as well as by the ability of the technology to reduce labour costs for meter reading. Technology development in the water sector generally lags that seen in the electricity sector. In the coming decade, the deployment of intelligent water metering will transition from being predominantly "pilot or demonstration scale" with the occasional city-wide roll-out, to broader mainstream implementation. This means that issues which have hitherto received little focus must now be addressed, namely: the role of real-time data in customer engagement and demand management; data ownership, sharing and privacy; technical data management and infrastructure security, utility workforce skills; and costs and benefits of implementation. © 2013 by the authors.

Fit-for-purpose potable source substitution of appropriate water end uses with rainwater or recycled water is often essential to maintain water security in growing urban regions. This paper provides the results of a detailed supply-demand forecasting review of a unique tri-supply (i.e., potable, A+ recycled and rain water sources reticulated to household) urban water scheme located in Queensland, Australia. Despite the numerous benefits of this scheme, system efficiency (e.g., reduced demand levels, water treatment, low chemical and energy use) and economic viability (i.e., capital and operating costs per kL of supply) aspects need to be considered against derived potable water savings. The review underpinned the design of a framework to enhance the schemes supply-demand balance and reduce the unit cost of alternative source supplies. Detailed scenario and sensitivity analysis identified the possibility of a refined scheme design, whereby the A+ recycled water supply would be reticulated to the cold water input tap to the washing machine, and the rain tank that originally supplied this end use be removed from future constructed households. The refined scheme design enhances the present recycled plant utilisation rate and reduces the cost to home owners when building their dwelling due to the removed requirement to install a rain tank to indoor end uses, such actions reduce the overall unit cost of the scheme.

© 2010 by the authors. Smart metering technology for residential buildings is being trialed and rolled out by water utilities to assist with improved urban water management in a future affected by climate change. The technology can provide near real-time monitoring of where water is used in the home, disaggregated by end-use (shower, toilet, clothes washing, garden irrigation, etc.). This paper explores questions regarding the degree of information detail required to assist utilities in targeting demand management programs and informing customers of their usage patterns, whilst ensuring privacy concerns of residents are upheld.