Abstract
The movement of contaminants and biota within river channels is influenced by the flow field via various processes of dispersion. Understanding and modeling of these processes thus can facilitate applications ranging from the prediction of travel times for spills of toxic materials to the simulation of larval drift for endangered species of fish. A common means of examining dispersion in rivers involves conducting tracer experiments with a visible tracer dye. Whereas conventional in situ instruments can only measure variations in dye concentration over time at specific, fixed locations, remote sensing could provide more detailed, spatially-distributed information for characterizing dispersion patterns and validating two-dimensional numerical models. Although previous studies have demonstrated the potential to infer dye concentrations from remotely sensed data in clear-flowing streams, whether this approach can be applied to more turbid rivers remains an open question. To evaluate the feasibility of mapping spatial patterns of dispersion in streams with greater turbidity, we conducted an experiment that involved manipulating dye concentration and turbidity within a pair of tanks while acquiring field spectra and hyperspectral and RGB (red, green, blue) images from a small Unoccupied Aircraft System (sUAS). Applying an optimal band ratio analysis (OBRA) algorithm to these data sets indicated strong relationships between spatially averaged reflectance (i.e., water color) and Rhodamine WT dye concentration across four different turbidity levels from 40–60 NTU. Moreover, we obtained high correlations between spectrally based quantities (i.e., band ratios) and dye concentration for the original, essentially continuous field spectra; field spectra resampled to the bands of a five-band imaging system and an RGB camera; and both hyperspectral and RGB images acquired from an sUAS during the experiment. The results of this study thus confirmed the potential to map dispersion patterns of tracer dye via remote sensing and suggested that this empirical approach can be extended to more turbid rivers than those examined previously.
Highlights
Flow patterns in rivers affect the movement of constituents suspended or dissolved within the water column or drifting at the water surface, including pollutants, nutrients, and organisms.The mechanisms by which these materials are redistributed by the flow are collectively referred to as dispersion processes
As a precursor to tracer studies planned for the Missouri River, which is a much more turbid fluvial environment than those we have examined to date, we conducted an experiment to assess the potential to remotely sense dye concentrations in water bodies with greater turbidity
As an initial test of the feasibility of retrieving tracer concentrations based on the reflectance characteristics of turbid river water, we performed optimal band ratio analysis (OBRA) of field spectra collected during an experiment in which both dye concentration and turbidity were manipulated as described above
Summary
The mechanisms by which these materials are redistributed by the flow are collectively referred to as dispersion processes. An understanding of these processes can inform a broad range of applications. Dispersion modeling can help guide emergency management by predicting how spills of oil and other toxic materials move through river systems, estimating residence times, and identifying areas where contaminants might accumulate. This type of information can help agencies issue timely warnings and direct remediation efforts appropriately [1,2]. Erwin et al [4] used a dispersion model to characterize the drift of endangered pallid sturgeon larvae on the Missouri River
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