Sediment measurement data are essential for sediment transport analysis and therefore highly important in overall river planning. Extant sediment measurement methods consume considerable manpower and time and are limited by factors including economic reasons and worker risks. This study primarily aimed to predict the changes in SSC (Suspended Sediment Concentration) and turbidity by examining the change in color in underwater images. While maintaining a constant flow in a channel, the turbidity and concentration were measured under different SSC. Multiple regression models were developed using turbidity measurement results, and they exhibited high explanatory powers (adjusted R² > 0.91). Furthermore, upon verification using the verification dataset of the experimental results, an excellent predictive power (RMSE ≈ 0.4 NTU) was demonstrated. The model with the highest predictive power, which was inclusive of red and green bands and showed no underlying multicollinearity was used to predict turbidity. Finally, the turbidity and suspended sediment concentration relationship determined from the experimental results was used to estimate the sediment concentration from the color changes in the underwater images. The concentrations that were predicted by the model showed satisfactory results, compared to the measurements (RMSE ≈ 21 ppm). This study indicated the feasibility of continuous SSC monitoring using underwater images as a new measurement method.

Bed shear stress is a critical parameter in riverine environments, directly influencing sediment transport, erosion, deposition, and flow dynamics. However, direct measurement of bed shear stress in natural rivers is nearly impossible, and estimating bed shear stress by extrapolating the Reynolds stress profile, though known for accuracy, faces practical limitations due to the challenges of measuring turbulence in natural rivers. As alternatives, indirect methods, such as global bed shear stress estimation based on bed slope and hydraulic radius (assuming uniform flow) and local bed shear stress estimation through regression of velocity profiles using the log law, have been employed. The estimation of local bed shear stress using the log law has primarily been derived from laboratory flow conditions due to the limitations in observing detailed turbulence in field conditions. Consequently, the applicability of the log-law method under field conditions has not been sufficiently evaluated. This study aims to assess local bed shear stress using the log law through a dedicated field experiment in a specific river condition, comparing it with methods utilizing the Reynolds stress profile. The experiment was conducted in a straight river channel with a width of approximately 6.5 m, a depth of 0.61 m, and a mean flow velocity of 0.56 m/s. A total of 197 points of regularly distributed velocity and turbulence data for the given cross-section were acquired using micro-acoustic Doppler velocimeter measurements with a duration of 90 s. We found that the log-law method overestimated local bed shear stress by an overall factor of 2.3 compared to the method using Reynolds stress profiles. Thus, the experimental results conclusively indicate that local bed shear stress estimated from the log law in natural river conditions could be overestimated. However, additional research is needed under more diverse flow and geometric conditions to develop a correction formula for applying the log law in estimating local bed shear stress.

The present study was conducted to re-estimate the factors needed for the velocity-area method previously provided by ISO through precise actual scale experiments in order to verify the appropriateness of the errors of the individual factors presented by ISO 748 and ISO 1088. For this, a steady-state flow of a flow velocity of approximately 1 m/s, 7 m wide, and 1 m deep, was maintained in the mild slope channel located at the River Experiment Center (Andong) of the Korea Institute of Construction Technology. Under this condition, the objective was to measure the flow velocity very precisely with respect to the space by using a micro-ADV having a high accuracy of flow velocity measurement. The water depth was precisely measured before the generation of the flow by using Total Station. The ISO regulations and the results of the present experiment were applied to three different conditions. The uncertainty assessed by applying the results of the present experiment exceeded twice that of the uncertainty estimated by applying the uncertainty factors provided by ISO. The uncertainty of the lateral gap between measurement lines and the number of measurement points in the depth direction was dependent on the scale of rivers. However, ISO may have presented the uncertainty factors analyzed from the data obtained from a wide range of river scales. Therefore, the discharge estimated by the velocity-area method may be dependent on the scale of rivers. The errors of the individual factors of the velocity-area method derived from the present study may be applied to the estimation of the uncertainty of the discharge calculated by the velocity-area method in small rivers.