Python-Based HEC-RAS Controller for Coupling National Water Model with HEC-RAS for River Ice-Informed Streamflow Modeling

Accurate streamflow modeling under ice-affected conditions is critical for reliable flood prediction. This resource integrates satellite-derived ice data and meteorological inputs with HEC-RAS and the National Water Model (NWM) to capture seasonal streamflow variations. By automating the HEC-RAS setup in Python, the framework updates boundary conditions and composite channel roughness based on river ice climatology, improving the model’s adaptability to dynamic conditions. The resource performs batch runs of the unsteady 2D HEC-RAS model, pausing monthly to restart with a warm-start file. It applies monthly updates to boundary conditions via the Qmult parameter in the unsteady-flow file and adjusts Manning’s roughness values for each calibration region within the geometry files.