Technical note: Advances in flash flood monitoring using unmanned aerial vehicles (UAVs)

Abstract

Unmanned aerial vehicles (UAVs) have the potential to capture information about the earth's surface in dangerous and previously inaccessible locations. Through image acquisition of flash flood events and subsequent object-based analysis, highly dynamic and oft-immeasurable hydraulic phenomena may be quantified at previously unattainable spatial and temporal resolutions. The potential for this approach to provide valuable information about the hydraulic conditions present during dynamic, high-energy flash floods has until now not been explored. In this paper we adopt a novel approach, utilizing the Kande-Lucas-Tomasi (KLT) algorithm to track features present on the water surface which are related to the free-surface velocity. Following the successful tracking of features, a method analogous to the vector correction method has enabled accurate geometric rectification of velocity vectors. Uncertainties associated with the rectification process induced by unsteady camera movements are subsequently explored. Geo-registration errors are relatively stable and occur as a result of persistent residual distortion effects following image correction. The apparent ground movement of immobile control points between measurement intervals ranges from 0.05 to 0.13 m. The application of this approach to assess the hydraulic conditions present in the Alyth Burn, Scotland, during a 1 : 200 year flash flood resulted in the generation of an average 4.2 at a rate of 508 measurements s-1. Analysis of these vectors provides a rare insight into the complexity of channel-overbank interactions during flash floods. The uncertainty attached to the calculated velocities is relatively low, with a spatial average across the area of ±0.15 m s-1. Little difference is observed in the uncertainty attached to out-of-bank velocities (±0.15 m s-1), and within-channel velocities (±0.16 m s-1), illustrating the consistency of the approach.