Riverine Flood Forecasting Using Advanced Deep Learning Approaches
Analysis of riverine flood forecasting models revealed that PatchTST outperformed the other models during moderate‐flow regimes while falling behind during extreme flooding events, and sensitivity analysis results indicated that PatchTST was slightly more sensitive to the selected training data features.