E3S Web Conf.
Volume 40, 2018River Flow 2018 - Ninth International Conference on Fluvial Hydraulics
|Number of page(s)||8|
|Section||Fluid mechanics and sediment processes|
|Published online||05 September 2018|
New methods for predicting and measuring dispersion in rivers
United States Geological Survey, Geomorphology and Sediment Transport Laboratory, Golden, Colorado, 80403, USA
2 Kyoto University, Department of Civil Engineering, Kyoto, Japan
3 Seoul National University, Department of Civil and Environmental Engineering, Seoul, South Korea
4 Korean Institute for Civil Engineering and Construction Technology, Andong, South Korea
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.