Bedload velocity and backscattering strength from mobile sediment bed: A laboratory investigation comparing bistatic versus monostatic acoustic configuration

Despite the many advantages of using active ultrasound sonars, recent studies have shown that the specific acoustic geometry, signal-processing configuration, and complex surface-volume scattering process at the riverbed introduce several uncertainties in bedload estimation. This study presents a comparison of bedload velocity and bottom echo intensity measurements performed by monostatic and bistatic active ultrasound systems. The monostatic configuration is widely applied in the field to measure the apparent velocity at the riverbed with an acoustic current Doppler profiler (ADCP). Two laboratory investigations were conducted in two different hydraulic facilities deploying ADCP Stream Pro, monostatic and bistatic acoustic velocity profilers, manufactured by Ubertone. The bistatic instruments provided more accurate bedload velocity measurements and helped in understanding the acoustic sampling of the monastic systems. The bistatic profiles succeeded in measuring a profile over the active bedload layer, and the monostatic instruments resulted in different bedload velocity estimations depending on the acoustic resolution and sampling. The echo intensity increased in the cells measured within the active bedload layer with respect to the cell measuring the water column above. The cells that sampled the immobile bed surface beneath the bedload layer showed a reduction of the echo intensity compared with the cells above. The acoustic sampling, which combines the measurement volume geometry and internal processing, seems crucial for more accurate outputs. Future research about the use of monostatic instruments in the field should aim to define the best possible setting for the acoustic parameters at a given bedload condition that may be tuned by evaluating the backscattering at the river bottom together with the apparent bedload velocity

Bedload transport analysis using image processing techniques

Bedload transport is an important factor to describe the hydromorphological processes of fluvial systems. However, conventional bedload sampling methods have large uncertainty, making it harder to understand this notoriously complex phenomenon. In this study, a novel, image-based approach, the Video-based Bedload Tracker (VBT), is implemented to quantify gravel bedload transport by combining two different techniques: Statistical Background Model and Large-Scale Particle Image Velocimetry. For testing purposes, we use underwater videos, captured in a laboratory flume, with future field adaptation as an overall goal. VBT offers a full statistics of the individual velocity and grainsize data for the moving particles. The paper introduces the testing of the method which requires minimal preprocessing (a simple and quick 2D Gaussian filter) to retrieve and calculate bedload transport rate. A detailed sensitivity analysis is also carried out to introduce the parameters of the method, during which it was found that by simply relying on literature and the visual evaluation of the resulting segmented videos, it is simple to set them to the correct values. Practical aspects of the applicability of VBT in the field are also discussed and a statistical filter, accounting for the suspended sediment and air bubbles, is provided

Laboratory monitoring of bedload transport rates using hydro-acoustic techniques (ADCP)

This study aims to develop a surrogate methodology for quantification of the bedload transport in riverine environments by using acoustic devices. Bedload transport experiments were performed in laboratory conditions to test the capabilities of the acoustic current Doppler profilers (ADCP) to quantify the bedload velocity, concentration, and active layer thickness. Two ADCPs working at four frequencies (0.5MHz, 1MHz, 3MHz M9, by Sontek, and 2MHz StreamPro, by RDI) were deployed at the same time. Simultaneously, the bedload transport was monitored by high-speed cameras, and continuous bedload transport rate measurements were conducted at the end of the measurement section. The apparent bedload velocity was analyzed and compared with the velocity from the imagery data and the transport rates measured by the bedload trap. Besides the apparent bedload velocity, the ADCPs also registered the backscattered (BS) signal from the sediment bed, which appeared to be sensitive to the change of the bedload transport conditions and the type of the sediment particles. The results confirmed the capability of these acoustic instruments to measure the bedload velocity by demonstrating a strong correlation with the physical transport measurements and the velocities from the imagery data. The apparent velocities measured by the 3 MHz and 1 MHz demonstrated similar results; the 2 MHz measurements led to lower values with 2-4.5 times magnitude difference comparing with the spatially normalized image velocity. The corrected BS signal documented a clear correlation with the apparent bedload velocity, more precisely with the change of the bedload transport condition. The variation between the results from the two instruments is assigned to the different acoustic geometry of the instruments, internal processing, and availability of the instrument related parameters needed for correction of the backscattered signal. Future tests should aim towards a better understanding of the internal processing of the signal and extensive analysis of BS strength sensitivity towards a wide range of sediment types and hydraulic conditions

Laboratory investigation of the apparent bedload velocity measured by ADCPs under different transport conditions

Several studies have investigated the use of the bottom tracking (BT) mode of acoustic Doppler current profilers (ADCPs) for evaluating bedload transport. The raw apparent bedload velocity is usually noisy and contains erroneous data. This study investigates how bedload dynamics influence acoustic processes occurring at riverbeds (i.e., volume and roughness scattering). The accuracy of ADCP apparent bedload velocity measurements is analyzed in two sets of laboratory experiments using two ADCPs working at different frequencies [2 MHz RDI StreamPro (RDI Teledyne Marine, Cypress, Texas) and 3 MHz SonTek M9 (Sontek/Xylem, San Diego)], with a variety of sediment materials and different hydraulic conditions. Simultaneously, the velocity and surface concentration of the mobile sediments are measured using high-resolution cameras. Despiking and filtering are applied to the raw data, and the temporal average of the apparent bedload velocity is spatially normalized. The percentage of filtered erroneous velocity data from the ADCP time series demonstrates a strong correlation with the surface concentration of mobile particles. Velocities measured with the M9 matched the particle velocities measured by image velocimetry better than those measured with the StreamPro, which appeared to underestimate the bedload velocity by a factor of 2\u20134. This suggests that instruments with different acoustic frequency yield a different interpretation of the apparent velocity; instruments with lower acoustic frequency and larger acoustic sampling length are more affected by the fixed surface beneath the layer of moving particles. These results bear out the notion that filtered apparent bedload velocity can be used to estimate the spatial velocity of bedloads, but its dependence on a set of acoustic properties must be further investigated

Acoustic sampling effects on bedload quantification using acoustic Doppler current profilers

This paper provides an evaluation of a hydro-acoustic technique for efficient quantification of the bedload transport in riverine environments. Stationary bedload measurements were conducted simultaneously at different study sites, using three different acoustic Doppler current profilers (ADCP) working at four different frequencies. The raw apparent bedload velocities were de-spiked and filtered in a streamwise direction. Then, functional correlations were observed between the magnitudes of the apparent velocities and the bedload transport rates measured by the conventional bedload sampler. Each ADCP yielded different results because of the different frequency backscatter sensitivity and acoustic penetration in the active bedload layer. In addition to the frequency, other acoustic parameters such as the percentage of the filtered data, transducers width, beam opening angle, beam-grazing angle and the pulse length, contributed to the acoustic bedload sampling. The influence of these parameters is examined, and recommendations are given for the performance and limitations of each instrument