This study presents a toolset designed to generate synthetic river bathymetry by leveraging the principle of maximum entropy with information from Digital Elevation Models (DEMs) as well as other relevant data from a target watershed and river network. This toolset presents a potential cost-effective and efficient solution to address the challenges associated with the acquisition of bathymetry data for large-scale river networks. To evaluate the utility of the generated cross sections, hydraulic modeling experiments are conducted comparing the generated synthetic bathymetry against actual surveyed cross-sections from selected river networks in Alabama, USA. The hydrologic modeling experiments are conducted using a Saint-Venant equation river network model (SWMM5+) and a Chezy-Manning model (AutoRoute). The output of the models using synthetic and surveyed bathymetry is then compared to evaluate the errors introduced by this synthetic bathymetry approach.
