Machine-Learning-Enhanced Optimization of Reservoir Sediment Routing During Flood Control Operations

This archive contains reproducible datasets, model codes, and simulation cases associated with the study "Machine-Learning-Enhanced Optimization of Reservoir Sediment Routing During Flood Control Operations."It includes: A modified dynamic programming model for reservoir operation; Surrogate models using XGBoost for sediment prediction; Four SRH-2D simulation scenarios (Gaemi, Kalmaegi, Lupit, Q25) for training ML models.The files are organized with README files for each component and are structured according to FAIR principles for data transparency and reproducibility.