A robust integrated streamflow forecasting framework for Australian water information and management agencies. This project aims to deliver an accurate and reliable seasonal streamflow forecasting system for Australian water users by developing a flexible rainfall-runoff modelling approach integrated into a Bayesian inference and prediction framework. These scientific developments aim to significantly advance the operational capabilities of the Australian Bureau of Meteorology to deliver robust ....A robust integrated streamflow forecasting framework for Australian water information and management agencies. This project aims to deliver an accurate and reliable seasonal streamflow forecasting system for Australian water users by developing a flexible rainfall-runoff modelling approach integrated into a Bayesian inference and prediction framework. These scientific developments aim to significantly advance the operational capabilities of the Australian Bureau of Meteorology to deliver robust streamflow forecasts to water agencies such as South East Queensland Water and others across Australia. Accurate predictions of future water flows are of tremendous value to urban and rural Australian communities whose economic prosperity, water security and social well-being depend on reliable estimates of water availability.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
Optimising permeable pavements with underlying reservoirs to enhance urban tree performance. This project will determine the optimal configuration of permeable pavements with underlying storage reservoirs and water delivery system to resolve the water security challenges that trees face in urban environments. This project will promote the healthy growth of urban trees and will lead to more liveable and healthier cities.