Author(s): Elisa Caccamo; Carlo Vincenzo Camporeale

Linked Author(s): Carlo Camporeale

Keywords: Bathymetry reconstruction; DTM bathymetric correction; Morphodynamics; Hydrodynamics; Orco river

Abstract: River bathymetry is fundamental for understanding fluvial hydraulics, sediment dynamics, and ecomorphological processes. Yet estimating riverbed topography remains a major challenge in fluvial and ecohydraulic research. Traditional in-situ methods -- such as single- or multi-beam echo sounding -- provide accurate depth measurements but require substantial logistical effort and are often limited by site accessibility, safety constraints, and survey costs. Remote sensing offers a promising alternative (Jawak et al., 2015), however most techniques cannot directly penetrate the water column in turbid or fast-flowing rivers, and their applicability is still constrained by sensor availability and cost-effectiveness. Hybrid reconstruction approaches that combine surveyed cross-sections with topographic data have therefore been proposed (Song et al., 2020). Although valuable, these methods typically require a relatively dense network of field surveys and may struggle in morphologically complex reaches. As a result, a key research gap remains: how to automatically generate physically consistent, reach-scale bathymetry across complex river networks using minimal field data. This study addresses this gap by introducing a methodological framework for automatic bathymetric reconstruction based on remotely sensed topography and easily accessible hydraulic information, integrating hydraulic constraints and morphodynamic principles (Ragno et al., 2023). The resulting DTM is a consistent approximation of the submerged topography, ready for use in morphodynamic or ecohydraulic analyses.

DOI: https://doi.org/10.64697/iahr.proc.ise2026.abs.277

Year: 2026