Optimising seasonal decisions for environmental water use. This project will develop a tool to optimise the use of environmental water, drawing on seasonal forecasts of streamflow and water price, and predicted ecological responses to changing flows. This tool will strengthen the effectiveness of the government organisations responsible for managing Australia's environmental water reserves.
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
A new-generation flood forecasting system using observations from space. Floods are dangerous and expensive, costing Australia more than any other cause of natural disaster. This project will use satellite measurements of soil moisture and rainfall along with computer models to improve the Bureau of Meteorology’s predictions of floods in rivers. Better flood forecasts will reduce costs and save lives.
Smart management of disinfectant in chloraminated water-supply systems. Smart management of disinfectant in chloraminated water-supply systems. This project aims to develop an adaptive, real-time control system for managing disinfectant residuals in chloraminated water supply systems. While chloramine delivers microbiologically safe drinking water in warmer climates and in long distribution systems, it is largely unpredictable, costs water utilities millions of dollars annually, and has uncertai ....Smart management of disinfectant in chloraminated water-supply systems. Smart management of disinfectant in chloraminated water-supply systems. This project aims to develop an adaptive, real-time control system for managing disinfectant residuals in chloraminated water supply systems. While chloramine delivers microbiologically safe drinking water in warmer climates and in long distribution systems, it is largely unpredictable, costs water utilities millions of dollars annually, and has uncertain benefits. This project’s control system will be guided by quantitative models formulated from multi-pronged, fundamental experiments. The project will quantify microbial chloramine decay and determine mechanisms to increase predictability. The project will develop and demonstrate a real-time control technology which delivered microbiologically safe, cost-efficient drinking water to people in warmer climates, despite warming climate and increasing population.Read moreRead less