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The accuracy of river velocity measurements plays an important role in the effective management of water resources. Various methods have been developed to measure river velocity. Currently, image-based techniques provide a promising approach to avoid physical contact with targeted water bodies by researchers. In this study, measured surface velocities collected under low flow and high flow conditions in the Houlong River, Taiwan, using large-scale particle image velocimetry (LSPIV) captured by an unmanned aerial vehicle (UAV) and a terrestrial fixed station were analyzed and compared. Under low flow conditions, the mean absolute errors of the measured surface velocities using LSPIV from a UAV with shooting heights of 9, 12, and 15 m fell within 0.055 ± 0.015 m/s, which was lower than that obtained using LSPIV on video recorded from a terrestrial fixed station (i.e., 0.34 m/s). The mean absolute errors obtained using LSPIV derived from UAV aerial photography at a flight height of 12 m without seeding particles and with different seeding particle densities were slightly different, and fell within the range of 0.095 ± 0.025 m/s. Under high flow conditions, the mean absolute errors associated with using LSPIV derived from terrestrial fixed photography and LSPIV derived from a UAV with flight heights of 32, 62, and 112 m were 0.46 m/s and 0.49 m/s, 0.27 m, and 0.97 m/s, respectively. A UAV flight height of 62 m yielded the best measured surface velocity result. Moreover, we also demonstrated that the optimal appropriate interrogation area and image acquisition time interval using LSPIV with a UAV were 16 × 16 pixels and 1/8 s, respectively. These two parameters should be carefully adopted to accurately measure the surface velocity of rivers.

Large-Scale Particle Image Velocimetry to Measure Streamflow from Videos Recorded from Unmanned Aerial Vehicle and Fixed Imaging System