Image-based measurements of surface flow velocity, turbulence, and depth distribution during sediment replenishment implementation in the Naka River, Japan.

Image-based methods for surface velocity measurements are notable due to the monitoring requirements during flood events. This method is a low-cost and secure approach that has already been commonly utilized to monitor and quantify flood events. This study applied image-based velocimetry below a Japanese dam in the Naka River basin to record the evolution of flow and sediment movement near a sediment replenishment (SR) site. SR is a typical technique of sediment management that requires high flow to erode the emplaced sediment. Consequently, in the field, three significant flow patterns, including surface flow velocity, discharge, and water depth were monitored over long periods during various flushing hydrographs to investigate SR dynamics. Hence, Large-scale particle image velocimetry (LSPIV) and Space-time image velocimetry (STIV) were utilized to accurately estimate the surface velocity distribution during two recent flood events in 2021. The flow discharge was computed based on the area velocity method at different flood magnitudes. The corresponding water depth was calculated by combining the surface velocity and dissipation rate of the turbulent kinetic energy (TKE). Finally, the results illustrated that image-based approaches are suitable for flow pattern monitoring during high-erosion periods of placed sediment. TKE utilization is a relevant approach to quantify the water depth and investigate the impacts of bed topography on the developed flow fields. This nonintrusive method with simple devices and inexpensive placement can be adopted to record flow and sediment erosion for SR purposes. • Utilizing Image-based approach to measure flow patterns during sediment replenishment implementation. • Collecting data by a PTZ camera with solar panel and 4G internet. • Performance of LSPIV and STIV approaches to calculate flow velocity and discharge at various stages of flood. • Water depth estimation based on distribution of surface flow velocity using turbulent structure. [ABSTRACT FROM AUTHOR]