## 6 Conclusions  
Field measurements were carried out during a flood season on a sand-bed river with high sediment transport (bedload and suspended load), when transport stages were between 11 and 16. A SonTek M9-ADCP was employed for different purposes during the field campaign: (a) measure discharges at the main cross-section; (b) perform moving-bed tests at six verticals along the cross-section; and (c) simultaneously map bathymetry and flow velocities throughout the 1.0-km length of the study reach. Bedload sediment transport rates were estimated using the following four approaches: (1) physical sampling, using the Helley-Smith mechanical trap; (2) moving-bed tests with ADCP (bottom tracking feature); (3) dune tracking, based on a modified ISSDOTv2 method; and (4) five empirical equations ([PERSON] [17]; [PERSON] [18]; [PERSON] [19]; [PERSON] and [PERSON] [20]; [PERSON] [21]). Results were consistent, with discrepancy ratios between 0.5 and 2, except for the HS measurements that underestimated the bedload transport. Data collected with ADCP may be used for purposes other than those used in the present work. [PERSON] et al. [56], for instance, employed dense observations of depths and flow velocities acquired from an ADCP to calibrate and validate a hydrodynamic model implemented for a braided river. In this regard, the data collected at the Taquari River were also used in three-dimensional hydrosedimentological modeling with Delft3D software [25], the results of which are presented in the author's thesis [57]. The simultaneously collected and spatially distributed depths and flow velocities are extremely useful for mapping hydrodynamic and sedimentological behaviors and increasing our understanding of local physical processes. The application of these data-points with empirical formulations, such as Van Rijn [21], allows the analysis of bedload transport distribution throughout the monitored area, overcoming the limitations inherent to cross-section averaged estimates. Although this procedure was not shown in this paper, some preliminary results indicate good agreement with the total bedload rates presented here [57]. The calculation of moving-bed particle velocity from the difference in bottom-tracking and RTK-GNSS-derived velocities, for the case when the boat is in motion, is a routine not yet available, neither on RiverSurveyor software nor on HydroSurveyor software. The development of a tool integrated into HydroSurveyor that encompasses this issue would be a great contribution to mapping bedload velocities and their spatial variability throughout a river reach. It was suggested to the ADCP manufacturer. Another promising approach to estimate bedload rates in rivers with bedforms is the acoustic mapping velocimetry (AMV) method [58]. The technique combines components and processing protocols from two contemporary nonintrusive approaches: acoustic and image-based. The bedform mapping is conducted with acoustic surveys (preferably multibeam-echo soundings), while the estimation of the velocity of the bedforms is obtained with processing techniques pertaining to image-based velocimetry. The bedload rates are \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Advantages** & & & **Disadvantages** \\ \hline Empirical & & & & \(\bullet\) & Field measurements are necessary for the determination of hydraulic and sedimentometric parameters. \\  & \(\bullet\) & Easy to implement. & & \(\bullet\) & Parameters are space-time averaged for the river cross-section, not accounting for local effects. \\  & \(\bullet\) & Wide use and discussion in the & & \(\bullet\) & Each equation is developed for specific site conditions. \\  & & & & \(\bullet\) & The formulations predict the maximum bedload transport rate that a flow in equilibrium can produce. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._then computed by applying Equation (10) [38], where dune heights can be calculated manually and individually for each dune or by using an automated technique [59]. Conceptualization, P.R., T.B.B., R.B.P.