LSPIV Measurements of Two‐Dimensional Flow Structure in Streams Using Small Unmanned Aerial Systems: 1. Accuracy Assessment Based on Comparison With Stationary Camera Platforms and In‐Stream Velocity Measurements

Abstract

Measuring two‐dimensional (2‐D) patterns of flow in rivers at high resolution over large areas is challenging using traditional velocity‐measurement methods, which provide data at specific locations or cross sections. Large‐scale particle image velocimetry (LSPIV) based on imagery obtained from fixed camera platforms can measure flow velocity on the surface of rivers and is generally accurate compared to near‐surface velocity measurements obtained by traditional methods. The proliferation of inexpensive small unmanned aerial systems (sUAS) equipped with high‐resolution cameras and onboard GPS has the potential to facilitate measurements of flow patterns in rivers using LSPIV, but few studies have assessed the accuracy of sUAS‐derived LSPIV compared to fixed‐platform LSPIV and in‐stream velocity measurements. This study assesses the accuracy of sUAS‐based LSPIV for measuring 2‐D mean surface velocities as well as quasi‐instantaneous 2‐D velocities obtained from successive image frames. For persistent 2‐D flow, mean velocities derived from sUAS‐based LSPIV match those obtained by stationary camera platforms, and velocities measured by both LSPIV methods agree with near‐surface velocities measured by an acoustic Doppler velocimeter. Quasi‐instantaneous velocities are degraded by camera movement and low pixel resolution, but capturing the evolution of 2‐D flow structures is possible in certain circumstances. The results confirm that sUAS‐derived LSPIV provides accurate, high‐resolution measurements of mean surface velocities over large spatial areas of persistent 2‐D flow and can characterize evolving 2‐D flow structures under favorable conditions. sUAS‐based LSPIV is a valuable new method for mapping of 2‐D patterns of surface flow in rivers—an issue explored in a companion paper.

LSPIV Measurements of Two‐Dimensional Flow Structure in Streams Using Small Unmanned Aerial Systems: 2. Hydrodynamic Mapping at River Confluences

“…Extensive field testing indicates that LSPIV‐derived surface velocities obtained from the UAS are within 1–2 cm/s of near‐surface values of streamwise velocity ( U ) and within 2–3 cm/s of near‐surface values of cross‐stream velocity ( V ) obtained from simultaneous ADV measurements (Lewis & Rhoads, ). An exception is the portion of the flow at KRCS within about 1 m of the channel banks where complex patterns of flow restricted the density of seeding material.…”

“…Although indirect evidence from field measurements of turbulence within the mixing interface at confluences is suggestive of the existence of these modes of vortex development (Rhoads & Sukhodolov, ; Sukhodolov & Rhoads, ), direct evidence is lacking and requires visualization of turbulent structures at confluences. Recent work suggests that LSPIV has the potential to provide direct evidence of different modes of vortex development within the confluence mixing interface (Lewis & Rhoads, , ).…”

“…Correspondence to: Q. W. Lewis, qwlewis@iu.edu Citation: Lewis, Q. W., & Rhoads, B. L. (2018). LSPIV measurements of two-dimensional flow structure in streams using small unmanned aerial systems: 2.…”

Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

“…As mentioned above, we used PIVlab [45] to perform data evaluation. PIVlab is a popular MATLAB-based software that has proven its quality in many previous studies [20,22,26,36,[56][57][58][59][60][61]. It is Open Source and can be used for free, and it is actively developed and well supported.…”

“…A widely applied approach to data acquisition in natural flow conditions is aerial video recording with the help of unmanned aerial systems (UAS), often called drones [22][23][24][25][26][27]. The advantage of using UAS as a camera-carrying platform is their applicability in previously inaccessible locations and the possibility to record nadir videos of large regions of interest (ROI).…”