Remote sensing of visible dye concentrations during a tracer experiment on a large, turbid river
Understanding dispersion in rivers is critical for numerous applications, such as characterizing larval drift for endangered fish species and responding to spills of hazardous materials. Injecting a visible dye into the river can yield insight on dispersion processes, but conventional field instrumentation yields limited data on variations in dye concentration over time at a few, fixed points. Remote sensing can provide more detailed, spatially distributed information on the dye's motion, but this approach has only been tested in clear-flowing streams. The purpose of this study was to assess the potential of remote sensing to facilitate tracer studies in more turbid rivers. To pursue this objective, we injected Rhodamine WT dye into the Missouri River and collected field spectra from a boat, videos from a small unoccupied aircraft system (sUAS), and orthophotos from an airplane. Applying an optimal band ratio analysis (OBRA) algorithm to the field spectra revealed strong correlations (R2 = 0.936) between a spectrally based quantity and in situ concentration measurements. OBRA also performed well for broadband RGB (red, green, blue) images extracted from the sUAS-based videos; the resulting concentration maps were used to produce animations that captured movement of the dye pulse. Spectral mixture analysis of repeat orthophoto coverage yielded relative concentration estimates that provided a synoptic perspective on dispersion of the dye throughout the entire 13.8 km reach over the full 2.5-hr duration of the experiment. The results of this study demonstrate the potential to remotely sense tracer dye concentrations in large, highly turbid rivers.
Citation Information
Publication Year | 2022 |
---|---|
Title | Remote sensing of visible dye concentrations during a tracer experiment on a large, turbid river |
DOI | 10.1029/2021WR031396 |
Authors | Carl J. Legleiter, Brandon James Sansom, R. B. Jacobson |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Water Resources Research |
Index ID | 70230199 |
Record Source | USGS Publications Warehouse |
USGS Organization | WMA - Integrated Modeling and Prediction Division |