High-resolution Hydrodynamic Mapping at Stream Confluences using LSPIV

Authors: Quinn Lewis*, University of Illinois, Bruce L Rhoads, University of Illinois at Urbana Champaign
Topics: Geomorphology, Water Resources and Hydrology
Keywords: LSPIV, UAS, stream confluences, turbulence, flow structure
Session Type: Paper
Day: 4/12/2018
Start / End Time: 3:20 PM / 5:00 PM
Room: Balcony K, Marriott, River Tower Elevators, 4th Floor
Presentation File: No File Uploaded

Although past field work on flow dynamics at stream confluences has provided information on mean velocities and turbulence at specific cross sections, this past work has not produced detailed characterizations of spatial and temporal variation in the hydrodynamics of confluences. This study uses large-scale particle image velocimetry (LSPIV) obtained from unmanned aerial systems (UAS) to map surficial characteristics of the mean flow and turbulence at two small stream confluences in unprecedented detail. LSPIV-measurements of surface velocities are integrated with cross-sectional velocity measurements and insight gained from previous field and computational modeling studies to significantly improve the understanding of flow at these confluences. LSPIV reveals similarities and differences in hydrodynamic conditions both within each confluence and between the confluences. In particular, the method provides a dense array of information on velocities that can be used to map distinct hydrodynamic zones within the confluences. Moreover, changes in the patterns of velocity vectors over time allow characterization of evolving turbulent structures in the mixing interface between confluent flows. Both the spatial pattern of hydrodynamic zones and the development of turbulent structures within the mixing interface vary according to changes in incoming flow conditions and morphological differences between the confluences. Analyses using LSPIV not only enrich the interpretation of traditional in-stream velocity data acquired in the field, but make comparison between field data and numerical models more meaningful.

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