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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.

Water utilities undertake long term planning for water source security, often with forecast cycles of 20–30 years. Whilst this planning is generally involved with investigations of source water abstraction security and the need to build dams or to increase the recharge rate of groundwater aquifers, planning for water efficiency gains occurs at annual intervals. Most water utilities in Australia are heavily engaged in water efficiency initiatives with rebate schemes for domestic water-efficient devices being ubiquitous across the industry. Wide Bay Water Corporation (WBWC) also engages in these activities but is increasingly interested in the concept of Time of Use Tariffs (TOUTs) to target high water users in order to reduce their demand on the system. In 2006, WBWC introduced smart metering technology across the city which captures hourly use data. Interrogation of this data has led to the ability to identify water use patterns for every domestic and commercial water customer and to design specific interventions to encourage water efficiency, such as a TOUT for domestic customers. A TOUT has been developed that imposes a penalty on all individual consumption greater than 600 L in any hourly interval of any day in the year. The tariff was designed to reduce both the annual peak hour and peak day demand. The ability to reduce both of these infrastructure design parameters may have the potential to deliver substantial savings in infrastructure planning and deployment. This paper details the design process of this tariff, examines the infrastructure savings potential derived by network modelling and explores the regulatory framework hurdles to be overcome in order to implement such tariffs in the water industry.