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Two-Dimensional Modeling of Flow and Contaminant Transport in Meandering Channels

8 pagesPublished: September 20, 2018

Abstract

In this study, a depth-averaged two-dimensional hydrodynamic model and scalar transport model were used to analyze the characteristics of both velocity field and concentration field of the complex flow in meandering channels. The two-dimensional shallow water model used in this study adopted the dispersion stress method in order to induce the effect of secondary flow which is normally omitted in the depth averaging process of the shallow water equation. A new vertical profile equation for the secondary flow was applied to the momentum equations by adopting the dispersion stress method. Comparisons with the experimental results of the large meandering channels of the River Experiment Center of KICT show that the computed values of the water surface profile and velocity magnitude were in good agreement with the observed data. The results of the 2D advection-dispersion model show that the longitudinal dispersion is much larger than theoretical results by Elder (1959) in meandering channels.

Keyphrases: advection-dispersion model, dispersion coefficient, dispersion stress, meandering channel, primary flow distribution, shallow water model

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1911--1918

Links:
BibTeX entry
@inproceedings{HIC2018:Two_Dimensional_Modeling_of_Flow,
  author    = {Il Won Seo and Jaehyun Shin},
  title     = {Two-Dimensional Modeling of Flow and Contaminant Transport in Meandering Channels},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  pages     = {1911--1918},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {https://easychair.org/publications/paper/31F6},
  doi       = {10.29007/d361}}
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