Robust streamflow predictions by improving the identification of hydrological model structure. This project aims to provide Australian environmental agencies, design engineers and policy-makers with robust methods that better utilise observed environmental data and process understanding to produce hydrological models with stronger scientific basis and improved operational predictive ability in gauged and ungauged catchments.
Dynamic Release Mechanisms for Phosphorus in Shallow Ponds and Lakes. Phosphorus release from submerged sediments is controlled by the physical and chemical environment. The mechanisms are well understood where thermal stratification is persistent but the behaviour during transient episodes has not been properly addressed. The aim is to study a dynamic chemical and hydraulic environment and develop a model of phosphorus release under these conditions. Algal blooms, which rely on high nutrient co ....Dynamic Release Mechanisms for Phosphorus in Shallow Ponds and Lakes. Phosphorus release from submerged sediments is controlled by the physical and chemical environment. The mechanisms are well understood where thermal stratification is persistent but the behaviour during transient episodes has not been properly addressed. The aim is to study a dynamic chemical and hydraulic environment and develop a model of phosphorus release under these conditions. Algal blooms, which rely on high nutrient concentrations, pose a significant threat to waterways yet a process-based description of phosphorus release is not yet possible. The outcome will be a verified model of phosphorus release mechanisms suitable for a range of water bodies.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
An integrated modelling approach for efficient management of irrigated landscapes. Northern Victoria's irrigators use a substantial portion of water from the Murray-Darling Basin, which is under mounting pressure to satisfy competing economic, social and environmental needs for water in the face of climate change. Up to 20 per cent of this water may be on-farm surface runoff and deep percolation, with poorly known spatial distributions. This project will provide reliable temporally and spatially ....An integrated modelling approach for efficient management of irrigated landscapes. Northern Victoria's irrigators use a substantial portion of water from the Murray-Darling Basin, which is under mounting pressure to satisfy competing economic, social and environmental needs for water in the face of climate change. Up to 20 per cent of this water may be on-farm surface runoff and deep percolation, with poorly known spatial distributions. This project will provide reliable temporally and spatially distributed information on surface runoff and deep percolation for Northern Victoria irrigation regions. This will inform decisions which improve water use efficiency, agricultural productivity and environmental values through optimisation of irrigation infrastructure and by better management of groundwater resources and salinity.Read moreRead less
Improving flow management for the control of blue-green algal blooms. Cyanobacterial (blue-green algal) blooms are a major water quality problem worldwide. They are toxic, produce odours and are estimated to cost around $200 million/year in Australia alone. Flow management is one of the most promising approaches for combating the cyanobacterial bloom problem in rivers. In this research, a new risk-based approach for quantifying the impact of flow management on cyanobacterial blooms is developed, ....Improving flow management for the control of blue-green algal blooms. Cyanobacterial (blue-green algal) blooms are a major water quality problem worldwide. They are toxic, produce odours and are estimated to cost around $200 million/year in Australia alone. Flow management is one of the most promising approaches for combating the cyanobacterial bloom problem in rivers. In this research, a new risk-based approach for quantifying the impact of flow management on cyanobacterial blooms is developed, which can be applied to rivers world wide. The utility of the approach is demonstrated for key sites in the Murray-Darling basin, providing a valuable decision support tool for river managers.Read moreRead less
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
Network-wide sewer odour and corrosion management by model predictive control. Network-wide sewer odour and corrosion management by model predictive control. This project aims to develop and demonstrate, through real-life field studies, a model predictive control approach that achieves cost-effective network-wide mitigation of hydrogen sulphide. The lack of suitable methodologies to support the control designs of chemical dosing units and sewage pumping stations makes network-wide sewer corrosio ....Network-wide sewer odour and corrosion management by model predictive control. Network-wide sewer odour and corrosion management by model predictive control. This project aims to develop and demonstrate, through real-life field studies, a model predictive control approach that achieves cost-effective network-wide mitigation of hydrogen sulphide. The lack of suitable methodologies to support the control designs of chemical dosing units and sewage pumping stations makes network-wide sewer corrosion and odour management a problem. Innovative control methodology will simultaneously manipulate chemical dosing unit(s) and selected sewage pumping station(s), based on real-time prediction of sewage flows and characteristics both at sources and across the network, to ensure optimal delivery of dosed chemicals to mitigate hydrogen sulphide.Read moreRead less
Resilience in biogeochemical pathways along a catchment-to-coast continuum. Aquatic systems have degraded more in the past 50 years than any other time in history. Global pressures are further threatening their sustainability, but their complexity makes it difficult to understand how they are responding. This project will combine numerous state-of-the-art approaches to unravel pathways that shape their response.
Traffic microsimulation of ITS implementations in CBD road networks. This research project will investigate the advantages and disadvantages of using Intelligent Transport Systems (ITS) technologies in an Australian Central Business District (CBD) environment. It is often assumed that road networks and especially high activity areas such as CBDs can benefit significantly from ITS implementations. Traditionally ITS impacts have been difficult to quantify due to difficulties in isolating network ....Traffic microsimulation of ITS implementations in CBD road networks. This research project will investigate the advantages and disadvantages of using Intelligent Transport Systems (ITS) technologies in an Australian Central Business District (CBD) environment. It is often assumed that road networks and especially high activity areas such as CBDs can benefit significantly from ITS implementations. Traditionally ITS impacts have been difficult to quantify due to difficulties in isolating network effects and limitations with traditional traffic models. The project will overcome this difficulty by using a current state of the art traffic microsimulation model in order to test various ITS scenarios in a duplicate of a real world CBD.Read moreRead less
Multiscale physics for enhanced oil recovery. The project aims to develop a multiscale mathematical and laboratory modelling methodology for combined enhanced oil recovery (EOR) and CO2 storage, and synthesise the technology for Santos’s Mulberry oilfield as a test case. The multidisciplinary team will develop advanced reservoir- and laboratory-scale mathematical models and novel laboratory methods to enhance the reliability of modern EOR and CO2 storage and increase its uptake by companies in A ....Multiscale physics for enhanced oil recovery. The project aims to develop a multiscale mathematical and laboratory modelling methodology for combined enhanced oil recovery (EOR) and CO2 storage, and synthesise the technology for Santos’s Mulberry oilfield as a test case. The multidisciplinary team will develop advanced reservoir- and laboratory-scale mathematical models and novel laboratory methods to enhance the reliability of modern EOR and CO2 storage and increase its uptake by companies in Australia and globally. The expected outcomes are a pioneering methodology with environmental benefits without additional drilling and reduction of greenhouse effect, and economic benefit to the Australian oil industry through increases in productivity.Read moreRead less