Conditioning Season-ahead Global Flood Forecasting on Large-scale Climate Indices

Globally, flood catastrophes lead all natural hazards regarding impacts on society, causing billions of dollars of damages each year. While short-term forecasts emphasize immediate emergency actions, longer-range forecasts, on the order of months to seasons, can complement short-term forecasts by focusing on disaster preparedness. In this study, prospects of season-ahead flood prediction are investigated globally by examining inter-annual climate variability on seasonal maximum floods, particularly how large-scale climate indices (e.g. ENSO, PDO, AMO) influence discharge and flood severity. Prediction models are constructed using PCR-GLOBWB simulations and season-ahead single or multiple large-scale climate indices, and validated with GRDC discharge. Skillful prediction can lead to season-ahead flood probabilities, flood extent, estimated damages, and eventual integration into early warning systems for informed advanced planning and management. This is especially attractive for areas with limited observations and/or little capacity to develop early warning flood systems.