New methods for predicting and measuring dispersion in rivers

By: , and 

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Abstract

To develop a better predictive tool for dispersion in rivers over a range of temporal and spatial scales, our group has developed a simple Lagrangian model that is applicable for a wide range of coordinate systems and flow modeling methodologies. The approach allows dispersion computations for a large suite of discretizations, model dimensions (1-, 2-, or 3-dimensional), spatial and temporal discretization, and turbulence closures. As the model is based on a discrete non-interacting particle approach, parallelization is straightforward, such that simulations with large numbers of particles are tractable. Results from the approach are compared to dispersion measurements made with conventional Rhodamine WT dye experiment in which typical at-a-point sensors are employed to determine concentration. The model performs well, but spatial resolution for experiments over large and or complex river flows was inadequate for model testing. To address this issue, we explored the idea of measuring spatial concentrations in river flows using hyperspectral remote sensing. Experiments both for idealized channels and real rivers show that this technique is viable and can provide high levels of spatial detail in concentration measurements with quantitatively accurate concentrations.

Additional publication details

Publication type Conference Paper
Title New methods for predicting and measuring dispersion in rivers
DOI 10.1051/e3sconf/20184005052
Volume 40
Year Published 2018
Language English
Publisher E3S Sciences
Contributing office(s) National Research Program - Central Branch
Description 8 p.
Larger Work Type Book
Larger Work Subtype Conference publication
Larger Work Title E3S Web of Conferences
Conference Title River Flow 2018 - Ninth International Conference on Fluvial Hydraulics
Conference Location Lyon-Villeurbanne, France
Conference Date September 5-8, 2018