## 1 Introduction  
Sediment movement has a significant impact on river morphology and the aquatic environment. In some rivers, particularly mountainous rivers, bedload sediment transport is considerable. Bedload sediment transport is the act of particles rolling, sliding, and saltating [1, 2]. Bedload sediment transport is affected mainly by flow hydraulics (such as flow velocity, bed slope, and water depth) and river-bed characteristics [3]. This makes bedload sediment transport have the characteristics of strong intermittent movement [4, 5, 6] and high randomness [7, 8, 9]. As a result, the reliable measurement of bedload sediment movement has long been a challenge in hydraulic engineering. Basket sampling and trap measurements were originally used to examine bedload transport in the field, but neither one was able to capture the dynamic process of the mass transport in time and space [10, 11, 12]. As a result, numerous techniques have been developed for identifying bedload sediment transport, including tracers [13, 14, 15, 16], optical methods, ultrasonic topography, and acoustic approaches. Radioactive particle tracking [17, 18], radio-tracking techniques [19, 20, 21], magnetic tracer particles [22, 23, 24], painted particles [25], and the \"Smartrock\" tracer [26, 27] are all examples of tracer techniques. This approach, however, has certain drawbacks. For example, the particle size range to be detected is limited, particles in motion may burb each other, recovery rates are low [28], and certain particles may poison the aquatic environment. Furthermore, the test is costly. Using a high-definition camera, the optical approach primarily observes bedload sediment transport on the riverbed [29; 30]. [PERSON] [31; 32] applied a low-light camera and placed it about 50 cm above the ocean floor to monitor the bedload movement in order to test the effectiveness of a synchronized hydrophone operating beneath the camera to observe bedload transport. He estimated high-temporal-resolution bedload transport rates based on the video and audio signal analyses. [PERSON] et al. [4] used a Redlake Locam camera to photograph bedload transport in Duck Creek. They obtained the bedload movement pattern after processing the images. [PERSON] and [PERSON] [33; 34] measured the amount of bedload transport by using high-speed cameras. Their experimental results revealed that the measured parameters in the flume were consistent with the authors' theoretical relationships. The experimental protocol was then adapted to a flume experiment and a gravel-bed river. [PERSON] et al. [35] used underwater video to track the motion of bedload sediment in a flume. They analyzed the individual sediment particle movements as well as the distribution of the moving particle sizes by applying statistical theory and image processing techniques. In summary, although the camera method can observe bedload transport in the flow, the technique has some limitations. (1) It is only applicable to shallow rivers with little suspended content, clear river water, and large sediment particles. The camera needs important protective measures and effective lighting during the observation process. (2) The method is unable to measure the bedload transport rate in the case of a high transport rate [36]. (3) Planar video photography can only record the transport information of the surface layer, while a high-speed camera placed on the side can only record the changes in limited space [36]. Ultrasonic topography is significantly affected by the device resolution, flow conditions, and sediment concentration, which results in inaccurate measurements of bedload sediment transport, particularly in mountainous rivers. The acoustic method has the advantages of high temporal resolution and working effectively in turbidity conditions [12]. This method can also provide continuous sampling data [37]. For example, [PERSON] et al. [38] established a mathematical model to trace gravel using a customized acoustic transmitter based on the target tracing theory of underwater sonic wave analysis.