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KNOU-Flood: Advancing global streamflow forecasting with lead-aware probabilistic machine learning
Global streamflow forecasting supports flood preparedness, yet data-driven models trained on reanalysis lose skill when driven by operational forecasts, increasingly so with lead time. AIFL addresses this shift with a two-stage transfer-learning recipe and a deterministic LSTM, but it feeds one fore
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