The melioidosis agent Burkholderia pseudomallei in the anthropogenic environment of northern Australia. This project will analyse environmental factors contributing to the persistence of the soil bacterium and melioidosis agent, Burkholderia pseudomallei in the anthropogenic environment. This will increase understanding of the consequences of land use manipulations upon these bacteria and will suggest remediation measures to reduce the risk of exposure.
Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection ....Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection in water-quality data and generating predictions of sediment and nutrient concentrations throughout river networks in near-real time. This will represent a fundamental increase in scientific knowledge, which will be immediately useful in the domains of aquatic science, environmental monitoring, and statistics.Read moreRead less
Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rath ....Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rather than concentrating on individual sites. It intends to underpin a new predictive capacity including response to land use and management changes and climatic variations based on long-term data sets, as well as a water quality prediction capability. It is intended that the models developed will jointly model a range of inter-related water quality parameters.Read moreRead less
Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuo ....Portable and field-deployable analytical platforms for water monitoring. This project sets out to tackle one of the costliest and most challenging environmental problems, namely, nutrient pollution in water systems. At present, nutrient pollutant monitoring is predominantly carried out using an antiquated manual approach with numerous shortcomings, inadequate to achieve truly effective water quality management. The in-situ analyser developed and deployed within this project will provide continuous real-time observations and will allow users to remotely monitor water quality; alerting them to pollutant levels, enabling immediate action to be taken to prevent environmental damage. The system is low-cost, facilitating mass adoption, yet delivers an analytical performance comparable to leading laboratory analysers. Read moreRead less