Flow Velocity Distribution in Rivers through Image-Based Technique Calibrated by ADCP Measurements

Abstract

In the context of climate change, the knowledge of flow discharge is of crucial importance. Flow discharge is not a direct measurement but is estimated on the basis of information of flow velocity and cross-sectional flow area. Thus, accurate flow velocity measurements are critical for defining early warning systems for flood management and for quick decision-making for emergency actions. In recent years, the acoustic Doppler current profiler (ADCP) has been especially used to measure flow velocity profiles and the flow discharge, in natural and man-made waterways[1]. During flood events, because of continuously changing in flow velocities, water depths, and high sediment concentrations, conditions is not safe for measurement operator. As consequence, in high flow conditions, measurement equipment’s like current meters and/or more advanced instruments such as ADCP cannot be used. For this reason, especially in the last decade, alternative approach based on image processing techniques has been increasingly used to obtain the distribution of the surface velocity, from which the flow discharge might be estimated. Several software tools have been also implemented for the image-based technique application, enabling researchers and practitioners to derive flow velocity data with high spatial and temporal resolution [2,3]. In comparison to the traditional measurement methods, the image-based technique presents the advantage to be nonintrusive allowing the safe estimation of surface velocity distribution also during floods. One of challenges in the application of image techniques is determining the error in estimating surface velocity, whose quantification depends on many factors characterizing not only the measurement conditions but also the processing method used.