HaorFloodAlert: Advanced Machine Learning Ensemble Predicts Floods in Bangladesh's Haor Wetlands

Researchers have developed HaorFloodAlert, a machine learning ensemble designed to forecast flash floods in Bangladesh's haor wetlands, where traditional flood prediction methods fall short. Current systems, which focus on riverine floods, do not account for the unique backwater dynamics of the flat basins. The ensemble model forecasts 72-hour flood probabilities for the Sunamganj Haor, covering approximately 8,000 km². By addressing seasonal influences, the model improved accuracy by 6.9 percentage points, achieving 89.6 percent accuracy and 87.5 percent recall in real-world tests. The system integrates an upstream Barak River Sentinel-1 SAR proxy for additional lead time and includes a calibrated estimator for potential damage to the boro rice harvest.