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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
Adaptive Agents Simulation of Freshwater Ecosystems: Artificial Intelligence Framework to Discover and Forecast Emergent Ecosystem Structures and Behaviours in Response to Environmental Changes. The project aims at intelligent adaptive agent models for lakes and rivers in order to improve understanding and proactive management of these highly complex ecosystems. Little is known about species succession in freshwater ecosystems in response to local and global environmental changes. Evolutionary a ....Adaptive Agents Simulation of Freshwater Ecosystems: Artificial Intelligence Framework to Discover and Forecast Emergent Ecosystem Structures and Behaviours in Response to Environmental Changes. The project aims at intelligent adaptive agent models for lakes and rivers in order to improve understanding and proactive management of these highly complex ecosystems. Little is known about species succession in freshwater ecosystems in response to local and global environmental changes. Evolutionary algorithms embodied in differential equations, neural networks and rules allow adaptive agents to simulate emergent structures and behaviours of algae and zooplankton communities interacting by competition and predation. The agents are trained and tested by ecological time-series of twelve lakes and rivers, and validated for the Mediterranean Myponga Reservoir, South Australia, and the temperate Burrinjuck Reservoir, NSW.Read moreRead less
New Techniques for Artificial Neural Network Modelling in Hydrology. In recent years, artificial neural networks (ANNs) have demonstrated the potential to provide improved predictions when compared with the more traditional hydrological modelling techniques in a number of areas. These include the prediction of rainfall, streamflow and water quality parameters. However, one of the major difficulties associated with the application of ANNs is the lack of an established methodology for their design ....New Techniques for Artificial Neural Network Modelling in Hydrology. In recent years, artificial neural networks (ANNs) have demonstrated the potential to provide improved predictions when compared with the more traditional hydrological modelling techniques in a number of areas. These include the prediction of rainfall, streamflow and water quality parameters. However, one of the major difficulties associated with the application of ANNs is the lack of an established methodology for their design and implementation. This research will develop new methods for constructing ANN models and test them on a number of case studies so that the full potential and genuine utility of ANNs for solving hydrological problems can be assessed.Read moreRead less