## 1 Introduction  
Bedload sediment transport in rivers can interfere with hydro-morphodynamic processes, such as bed erosion/deposition, sandbank formation and changes in flow capacity. When these processes become excessive and out of balance, they might affect economic activities, such as waterway navigation, harbor installation and operation, hydroelectric power generation and water supply. It is important to understand the hydro sedimentological behavior, quantifying bedload transport, in order to establish an effective management of sediments and water resources [1]. Several bedload sampling techniques are cited in the literature. Conventional sampling procedures are based on mechanical traps deployed on the river bottom to collect sediment samples at different positions along a cross-section, during a certain time interval [2]. However, these techniques present limited spatial and temporal resolutions and high uncertainties [3]. Conventional sampling is technically difficult, time-consuming, expensive and dangerous during floods. These constraints are even more relevant in rivers with dunes and high sediment transport, as the position of the sampler on the river bottom and the heterogeneous bedload transport affect the measurements [4, 5]. Surrogate technologies, such as acoustic Doppler current profilers (ADCP), provide faster and safer measurements with better resolution [6, 7, 8]. ADCPs were initially developed with the aim of computing water velocities and discharges. However, recent research indicates the ADCP's potential to estimate bedload rates through a feature called bottom tracking (BT) [8; 9; 10]. Bottom tracking consists of sending acoustic pulses from slanted ADCP beams that reflect on the river bottom and return to the sensor. The Doppler shift in the frequency of the return pulse is related to the boat's velocity (when the instrument is mounted on a moving boat). In rivers with a moving-bed (i.e., sediment particles in motion near the bottom), static measurements (named moving-bed tests) allow for computing spatially averaged bed particle velocities. Thereafter, bedload transport rates can be estimated from the product between moving-bed velocities, thickness of the bedload layer and sediment concentration in the bedload layer. This method is herein referred to as ADCP-BT. Bedload may consist of fine (clays, silts and sand) to coarse (gravels and cobbles) sediment particles. The entrainment and transport of gravel beds are normally more intermittent than sand beds, due to their larger and typically less sorted particle size, providing a more spatially and temporally heterogeneous transport. Nevertheless, the supposed more homogeneous transport in sand-bed rivers tends to be restricted and local due to the transport of bed material as bedforms (ripples and dunes), which increases the spatial-temporal heterogeneity of bedload rates [11]. Additionally, to the application of ADCPs to estimate moving-bed velocities and hence bedload transport rates, the instrument with activated HydroSurveyor capabilities (in the case of SonTek M9-ADCP model) allows the collection of synchronized data of bathymetry and flow velocities, where not only the vertical beam, but also four slanted beams are used to obtain depth information. After detailed and consecutive surveys along a river reach, it is possible to analyze longitudinal bathymetric profiles, and map aggradation and degradation areas. This approach is known as dune tracking, since it evaluates dune migration rates, and has been successfully employed to estimate bedload transport [5; 12; 13]. [PERSON] et al. [14] developed a method using the dune tracking approach, which was named ISSDOTv2 (Integrated Section Surface Difference Over Time, Version 2). This method computes bedload based on the difference in time-sequenced three-dimensional bathymetric data. Scour volumes calculated from the difference plots of bed level are related to the average bedload transport due to the dune's movement.