Enhancement of two‐dimensional hydrodynamic modelling based on UAV‐ flow velocity data

• Published in: Earth Surface Processes and Landforms
• Main Authors: Wolff, Franziska, Lotsari, Eliisa, Spieler, Diana, Elias, Melanie, Eltner, Anette
• Other Authors: Research Council of Finland, Deutscher Akademischer Austauschdienst, Itä-Suomen Yliopisto, Aalto-Yliopisto
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2024
• Subjects: Northern Finland
• Online Access: http://dx.doi.org/10.1002/esp.5853; https://onlinelibrary.wiley.com/doi/pdf/10.1002/esp.5853

Abstract 2D hydrodynamic models deepen the understanding of hydromorphological processes in fluvial systems. UAV (Unoccupied Aerial Vehicles) can record complementary calibration and validation data for these models of large areas. In this study, we created a 2D hydrodynamic model of the Pulmanki River in Northern Finland under shallow, open‐channel conditions based on three calibration sets. We examined the potential of UAV‐flow velocities for model validation. Here, we applied a cross‐validation approach comprising the conversion from surface to depth‐averaged velocity and vice versa using fixed velocity coefficients (α). We further assessed the conversion performance including hydraulic variables to evaluate this coupled numerical‐experimental concept. Our model showed good performance in the three calibration runs for water level and depth‐averaged velocity. The calculation of surface to depth‐averaged velocity identified the coefficient α = 0.8 as the best choice with R 2 = 0.62 for the straight river reach, indicating a good agreement between converted velocity and the reference data. A poor agreement, however, is evident for the meander section with R 2 = 0.406. While there were no statistically significant relationships between the conversion performance and hydraulic variables, there were observable trends in the residuals indicating over‐ and underestimation of converted velocities, particularly in relation to bathymetry and distance to the channel centre, with variations based on the river structure. Our study demonstrates that UAV reference data has the potential to enhance 2D hydrodynamic models but particularly improves our understanding of spatial flow distribution.