Gaining insights into mine waste dumps to avoid environmental legacies. The project aims to develop new methods for identifying pollution source hotspots and pathways inside mine waste rock dumps. This addresses the national need for effective management of Acid and Metalliferous Drainage (AMD), which is now a critical consideration in the viability of new mines and in confronting pollution legacies of old mines. The research will develop and test innovative methods of geophysical and geochemica ....Gaining insights into mine waste dumps to avoid environmental legacies. The project aims to develop new methods for identifying pollution source hotspots and pathways inside mine waste rock dumps. This addresses the national need for effective management of Acid and Metalliferous Drainage (AMD), which is now a critical consideration in the viability of new mines and in confronting pollution legacies of old mines. The research will develop and test innovative methods of geophysical and geochemical analysis and their integration that provide 3-dimensional mapping of key physical and chemical features of the dump. Expected outcomes include greater confidence in the ability of the mining industry to manage its AMD liability. Read moreRead less
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