An acoustic travel time method for continuous velocity monitoring in shallow tidal streams

Abstract

[1] Long-term variations of streamflow in a tidal channel were measured using a Fluvial Acoustic Tomography (FAT) system through one transmission path. FAT is an innovative acoustic technology that utilizes the time-of-travel method to determine velocity between two points from multiple ray paths that traverse the entire cross-section of stream. Due to high spatial variability of flow distribution stationary ADCP measurements were not likely to yield true section-averaged flow velocity and moving-boat ADCP method was therefore used to provide reference data. As such, two short-term moving boat ADCP campaigns were carried out by the authors. In the first campaign, a couple of acoustic stations were added to the FAT system in order to resolve flow angularity in addition to the mean velocity. Comparing the FAT results with corresponding ADCP section-averaged flow direction and velocity indicated remarkable consistency. Second campaign was designed to capture the influence of salt wedge intrusion on the sound propagation pattern. It was found that FAT velocity measurements bias high if acoustic stations lay inside the cooler freshwater layer. Ray-tracing hindcasts suggest that installing acoustic stations inside the salt wedge may significantly improve function of output of the system. Comparing salinities evaluated from long-term FAT travel time records with nodal salinity measurements provided by conductivity-temperature sensors reveals the potential ability of FAT in measuring salt flux.

Characteristics of Tidal Discharge and Phase Difference at a Tidal Channel Junction Investigated Using the Fluvial Acoustic Tomography System

“…The relative difference of discharges estimated from ADCP measurements and FATS are mostly ranged from ∼0.4% to ∼10%, as shown in Table 3, Table 4, and Table 5. The results are consistent with those of previous works, where the relative differences between FATS and ADCP estimates range from 1% to 10% [12][13][14]. Moreover, we can evaluate how closely the FATS estimates match the ADCP results using the equation of root mean square error (RMSE):…”

“…To obtain the discharge (Q), the cross-sectional averaged velocity is multiplied by cross-sectional area (A 0 ), which varies in time and corresponds to water level fluctuation. For detailed information about the FATS measurement method and its reliability, readers can refer to previous studies [11][12][13][14].…”

Application of acoustic tomography to reconstruct the horizontal flow velocity field in a shallow river

“…To assess the flow velocity and direction estimated from inverse analysis, the velocity components were compared to the depth‐averaged ADCP direct measurements and the unmeasured parts which were approximated by the power law. Because the ADCP positions do not overlap with any of the computational grid nodes, the inverse distance weighting method [ Razaz et al ., ] was used to generate velocity time‐series from the four nearby nodes of computational domain that surround each particular ADCP coordinate. Graphs in Figures and allow qualitative comparisons between the tomographically derived velocities and the nodal ADCP direct readings.…”

“…By incorporating two crossing ray paths, Razaz et al . [] demonstrated that, in a shallow estuary, the mean current speed and direction derived from FAT reports compare favorably with those obtained using a moving‐boat ADCP. In both studies, the deviation of FAT results from the reference method did not exceed ±10%.…”

High‐frequency streamflow acquisition and bed level/flow angle estimates in a mountainous river using shallow‐water acoustic tomography

“…The cross‐path configuration is essential to resolve the flow angle θ (Sloat and Gain, ). In the previous study, the flow angle was measured by moving‐boat ADCP measurements (Kawanisi , et al , , Razaz , et al , ). A cross‐path configuration was also used for 19 h (Kawanisi , et al , ).…”