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The vertical structure of downslope velocity within sub-aqueous gravity-driven flows of (smoother) glass beads and (rougher) natural sand is investigated for both fixed roughness and erodible beds using high-resolution, MHz-frequency acoustics. The observed velocity profiles within the O(1) cm thick, O(10) cm/s flows exhibit a negative shear layer extending downward from the sediment–water interface to a velocity maximum at ∼ 9 grain diameters depth within the layer, below which the velocities decrease to near-zero values at the pre-flow bed location for fixed roughness beds and to non-zero values for mobile beds. The attenuation of sound transmitted through the moving layer is used to constrain the depth-averaged solids concentration to a value of ∼ 0.52. The observed negative shear at the interface indicates that, unlike the sub-aerial case, interfacial friction is dynamically important in gravity-driven sub-aqueous granular flows. It is shown that the observed vertical structure of velocity within the layer can be well represented by continuum viscous flow models. Solids concentration and effective viscosity are estimated from the best-fit model parameters using the Zarraga–Hill–Leighton (2000) empirical relation for suspensions of negatively buoyant particles, yielding vertically averaged values ∼ 0.57. While the sub-millimeter vertical resolution of the measurements is too coarse to provide precise estimates of the friction velocity at the interface, the model-data comparisons nevertheless indicate that the vertical structure of the downslope flow consists of a weakly stratified dense layer and a thin, dilute transition layer between the dense flow and the overlying water. [ABSTRACT FROM AUTHOR]

This paper considers the problem of accurately measuring the sediment transport over bedforms where flow evolves continuously both in time and space. For this purpose, we have developed a pulse-to-pulse coherent Doppler sonar system designed in bistatic geometry with two fan-beam transmitters symmetrically positioned on each side of a multielement receive array. The system resolves 2D velocity components within a ±20° (~0.5m by ~0.5m) swath. The software-defined radio data acquisition and control system limited us at present to eight independent receiver channels, and consequently the azimuthal resolution of the systemis 48. As a preliminary test of the sonar system, the system operation was simulated using a model developed to predict coherent sonar performance. The uncertainties with respect to the prescribed values and mean measurements in the model results were confined to 0.35 and 0.23 cm s-1, respectively, in the presence of strong shear (~150 s-1) and 50 cm s-1 horizontal flow. An important thing is that the model allowed us to test and develop the signal processing algorithms necessary to invert the multibeam sonar data. Using sand of 0.4-mm median diameter, the laboratory trials were carried out in active sediment transport conditions over dunes with 2-m wavelength and ~0.90m s-1 unidirectional flow velocities. The results presented here focus mainly on 2D velocity field and indicate an average 4% deviation from the wake law and 8% from independent observations made with the wide-band multifrequency coherent Doppler profiler (MFDop) instrument under similar flow conditions. [ABSTRACT FROM AUTHOR]

Coherent Doppler sonar is a useful tool for noninvasive measurement of ocean currents, sediment transport, and turbulence in coastal environments. Various methods have been proposed to separately address two of its inherent limitations: velocity ambiguity and measurement noise. However, in energetic turbulent flows, both factors may be present simultaneously. The presence of measurement noise complicates velocity ambiguity resolution, and conversely velocity ambiguity presents a challenge for existing noise suppression methods. A velocity estimator based on maximum a posteriori (MAP) estimation has been developed to resolve velocity ambiguity and suppress measurement noise simultaneously rather than separately. The estimator optimally combines measurements from multiple acoustic carrier frequencies and multiple transducers. Data fusion is achieved using a probabilistic approach, whereby measurements are combined numerically to derive a velocity likelihood function. The MAP velocity estimator is evaluated using a high-fidelity coherent Doppler sonar simulation of oscillating flow and data from a towing tank grid turbulence experiment where both velocity ambiguity and backscatter decorrelation were present. Time series and spectra from MAP velocity estimation are compared to those obtained with conventional Doppler signal processing. In addition to robustly resolving velocity ambiguity, the MAP velocity estimator is shown to reduce high-frequency noise in turbulence spectra. [ABSTRACT FROM AUTHOR]