Seasonal rainfall forecasting using large scale climate drivers: an artificial intelligence approach

As Australia is exposed to severe droughts and floods, seasonal rainfall forecasting is crucial for water resources management, food production and mitigating flood risks. The main focus of this thesis is the development of a non-linear rainfall forecast model for Victoria, Australia using antecedent large-scale climate predictors. The forecast results in this study were superior to that of the official forecast model used in Australia. The study proposes the use of Artificial Intelligence approach as an alternative tool for seasonal rainfall forecasting in Australia as they require minimal inputs, less development time and are less complex compared to dynamic models.