Bedload sediment transport in rivers can cause impacts, such as bed erosion/deposition, sandbank formation and changes in flow capacity. Bedload sampling techniques have limitations related to spatial and temporal resolution. These constraints are more relevant in rivers with dunes and high sediment transport. This paper presents a comparison between bedload transport rates estimated with direct and indirect methods in a river with sand dunes. The case study area is a stretch of the Taquari River, in Brazil. Surveys were carried out on three consecutive days, during a flood season. A SonTek M9-ADCP with HydroSurveyor capabilities activated was used to simultaneously measure bathymetry and water velocities throughout a river reach, and also to perform moving-bed tests at six verticals along a predefined cross-section. A mechanical trap (Helley–Smith) was used to collect bedload samples at the same time and positions where the moving-bed tests were performed. Sediment transport was calculated and compared following different approaches: (1) ADCP-BT (Bottom Tracking); (2) modified ISSDOTv2 method (dune tracking); (3) HelleySmith mechanical trap; (4) and five empirical equations. The results showed good agreement between the methodologies, indicating the potential of using ADCPs for hydro sedimentological studies due to the advantages of integrating bathymetry, flow velocity and bedload data.

The low density of precipitation gauges, the areas of difficult access and the high number of missing values hinder a rapid and effective hydrological monitoring. Thus, the present study aims to statistically validate the precipitation estimates by the data Tropical Rainfall Measuring Mission (TRMM) in relation to the data observed in the Conventional Meteorological Stations (CMSs) in the geographic regions of Brazil. The statistical indicators used were: Correlation Coefficient (r), Mean Absolute Error (MAE), Percentage of Bias (Pbias), T-Test and Mann-Witiney Test. It is concluded that the precipitation data estimated via TRMM are effective and reliable alternatives for hydrological studies in areas that do not have in-situ gauges and/or need to fill missing values in the five regions of the country, especially in the driest months and in larger time scales.