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Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
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Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
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Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling

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Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling
Journal Article

Suitability of UAV-Based RGB and Multispectral Photogrammetry for Riverbed Topography in Hydrodynamic Modelling

2026
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Overview
This study assesses the suitability of UAV aerial imagery-based photogrammetry for reconstructing underwater riverbed topography and its application in two-dimensional (2D) hydrodynamic modelling, with a particular focus on comparing RGB, multispectral, and fused RGB–multispectral imagery. Four Lithuanian rivers—Verknė, Šušvė, Jūra, and Mūša—were selected to represent a wide range of hydromorphological and hydraulic conditions, including variations in bed texture, vegetation cover, and channel complexity. High-resolution digital elevation models (DEMs) were generated from field-based surveys and UAV imagery processed using Structure-from-Motion photogrammetry. Two-dimensional hydrodynamic models were created and calibrated in HEC-RAS 6.5 using measurement-based DEMs and subsequently applied using photogrammetry-derived DEMs to isolate the influence of terrain input on model performance. The results showed that UAV-derived DEMs systematically overestimate riverbed elevation, particularly in deeper or vegetated sections, resulting in underestimated water depths. RGB imagery provided greater spatial detail but was more susceptible to local anomalies, whereas multispectral imagery produced smoother surfaces with a stronger positive elevation bias. The fusion of RGB and multispectral imagery consistently reduced spatial noise and improved hydrodynamic simulation performance across all river types. Despite moderate vertical deviations of 0.10–0.25 m, relative flow patterns and velocity distributions were reproduced with acceptable accuracy. The findings demonstrate that combined spectral UAV aerial imagery in photogrammetry is a robust and cost-effective alternative for hydrodynamic modelling in shallow lowland rivers, particularly where relative hydraulic characteristics are of primary interest.