Modelling Catchment Hydrology and Nutrient Fluxes to Forecast Cyanobacterial Blooms in In Ross River Reservoir

Co Investigator

The project focuses on developing an integrated modelling framework for forecasting cyanobacterial blooms in tropical reservoirs. It combines surface water modelling (SWAT or similar) with groundwater modelling (MODFLOW or similar) to capture the coupled dynamics of catchment hydrology, nutrient transport, and reservoir inflows. These physical models are further integrated with remote sensing datasets and machine learning approaches (e.g., Random Forest, GNN, LSTM) to identify bloom drivers and improve prediction. Additionally, sub-seasonal to seasonal (S2S) climate forecasts are incorporated to extend predictive lead times, enabling an early warning system for effective reservoir and water quality management.

20 Apr 2026 - 22 Oct 2029

N/A