Beyond Water Surface Profiles: A New Iterative Methodology for 2D Model Calibration in Rivers Using Velocity Data from Multiple Cross-Sections

Observed longitudinal water-surface profiles are commonly used to calibrate river hydrodynamic models, relying on assumptions of lateral uniformity in water surface elevation and velocity distribution. While suitable for 1D models, this approach has limitations in regard to 2D model calibration. When 2D flow measurements are available, a more robust quantitative evaluation is necessary to assess model accuracy. This study introduces a novel methodology to improve 2D model calibration and evaluate performance. High-resolution bathymetric and hydrodynamic data collected with a multibeam echosounder (MBES) and acoustic Doppler current profiler (ADCP) were aligned to compare observed and simulated flow velocities at matching spatial locations. Statistical metrics, including relative mean absolute error and root-mean-square error, were employed to assess hydrodynamic modeling. The methodology was tested using MBES and ADCP measurements alongside TELEMAC-2D simulations of a dynamic neck cutoff on the White River, Arkansas, USA. This approach provides a 2D calibration process, enhancing model accuracy and informing parameter selection, such as channel boundary roughness and downstream boundary water surface elevation.