Estimating the Average River Cross-Section Velocity by Observing Only One Surface Velocity Value and Calibrating the Entropic Parameter

The current research aims to predict the velocity distribution and discharge rates in rivers based on the entropy concept using only one surface velocity measurement. In this direction, first, the uncrewed aerial vehicle (UAV)-based image acquisition technique was applied to collect the surface velocity distribution along two European rivers, the Sajo, and the Freiberger Mulde Rivers. Seven cross sections were chosen for the analysis. At each cross section, first, the entropic parameter phi(M) was calibrated based on the maximum and mean velocity magnitudes, derived from Acoustic Doppler Current Profilers, respectively, showing a trend for all cross sections with a range of 0.6 phi(M) < 0.75. Next, the maximum surface velocity provided by the UAV was implemented as a single velocity input. Finally, the bathymetry data, herein collected by UAV, were considered as the input for the entropy approach. In this way, the entropy iterative method allowed estimating the mean flow velocity by identifying the location (dip) of maximum velocities across the river site and inferring the 2D velocity distribution. The results highlighted that the entropy approach can accurately predict the velocity distribution and discharge rates with a percentage error lower than 13%.