Uncertainty analysis of sediment size estimations in gravel-bed reaches in Southern Brazil

Zambrano, F. C. ; Kobiyama, Masato ; Narvaez Campo, Gabriel Fernando

Année de publication
2025

Understanding sediment size distribution is essential for comprehending the hydrogeomorphological dynamics of mountain river systems. Manual and automated techniques for sampling surface sediments in gravel-bed rivers can generate uncertainties naturally. This study aims to comprehend field-walking techniques (manual) and photogrammetric analysis (automation) by estimating uncertainties in sediment size distribution. Measurements were conducted at five sites along the Forromeco River in southern Brazil, including field pebble counting and UAV-based photogrammetry. To calculate the nominal diameter, field measurements provide three axes of the sediment, while photogrammetry only two. A binomial probability distribution model was applied to estimate the percentile confidence interval of sediment size, thus enabling an assessment of the uncertainty between the adopted techniques. Results indicate that 3-axis measurements generally yield smaller sediment sizes compared to 2-axis methods, reflecting the influence of the sediment shape on the shortest axis magnitude. Statistical analysis by site showed no differences between the nominal diameter computed with 3-axis or 2-axis. However, a four sites ensemble revealed discrepancies. Drone-derived measurements, while efficient, tended to overlook finer sediments and overestimate larger sizes, particularly in areas with vegetation obstacles. The present study highlights the importance of considering the sediment shape, sediment configuration and regional lithology when interpreting drone data. Overall, the 3-axis field pebble counting method provides more accurate sediment size characterization in mountain rivers like the Forromeco. This research contributes to the understanding of sediment dynamics in mountainous regions, aiding in the management of water and sediment resources, and mitigating flood-related disasters.</p>

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