Author(s): Hendrik Jongbloed; Bart Vermeulen; Antonius J. F. Hoitink

Linked Author(s): Bart Vermeulen

Keywords: No Keywords

Abstract: Flow velocities in river, channel or estuarine environments are often estimated using moving-boat Acoustic Doppler Current Profiler sensors. Usually, obtained raw data are projected and processed on a pre-defined computational mesh. For every ADCP velocity profile, the measured flow velocity is solved from the radial beam velocities to directly obtain Cartesian velocity vector data. This approach suffers from spatial homogeneity assumptions: To estimate flow velocities, the acoustic beams from the transducer diverge. Hence, the larger the distance from the instrument, the larger the assumption of spatial flow homogeneity becomes. For ship-mounted ADCP measurements, the resulting performance is worst near the bed, where the velocity gradients are largest and the spatial homogeneity assumption is least justifiable. An improved method of meshbased velocity estimation was presented recently (Vermeulen et al., 2014). Rather than solving for flow velocities for each ADCP profile measurement and thereafter projecting them on the computational mesh, flow velocities are solved per mesh cell by collecting all radial velocity measurements in that cell. Thereafter, the flow velocity is solved for per computational cell, based on all radial velocity measurements within that cell performed at different times. This approach however requires assumptions on temporal homogeneity: temporal variations should be small compared to spatial variations (Moradi et al., 2019). Thus, there is a tradeoff between assumptions on spatial and temporal homogeneity. The temporal homogeneity assumption holds for inland riverine systems, were temporal variations are typically small. For tidal systems however, temporal variations play a more prominent role. Therefore, the novel method cannot directly be applied to ADCP processing in tidal systems. In the present work, we present a fitting procedure that to a large degree circumvents both the spatial and temporal homogeneity assumptions in tidal environments. It extends the novel method (Vermeulen et al. 2014) to reduce the dependence on the spatial homogeneity assumption, and uses available information on tidal motion to reduce the problem of temporal homogeneity.

DOI:

Year: 2022