Physically based probabilistic analysis of sediment deposition in open channel flow

Jungsun Oh, Jung Il Choi, Sung Uk Choi, Christina W. Tsai

Research output: Contribution to journalArticle

Abstract

This paper proposes a physically based probabilistic model for predicting the longitudinal distance of sediment deposition in an open channel flow. Numerical simulations were performed using a stochastic particle-tracking model to obtain the probability density functions (PDFs) of the longitudinal deposition spots. A skewness-kurtosis analysis and probability-probability plot confirmed that the PDF of the deposition locations had a lognormal type distribution. The distribution parameters, which include the mean and variance, were examined to analyze the effect of two particle-related factors, namely, the particle size and initial release point, on the PDF of the deposition locations. Smaller particles and a higher release point were found to produce, on average, longer travel distances to the deposition location and a more-dispersive distribution of the locations. The physical relationships between the distribution parameters of the PDF and the particle-related factors were considered for better prediction of the distribution parameters. The findings of the present study confirm the robustness and accuracy of a probabilistic model parameterized by physically based regression for predicting the spatial patterns of sediment deposition locations.

Original languageEnglish
Article number04016106
JournalJournal of Hydraulic Engineering
Volume143
Issue number5
DOIs
Publication statusPublished - 2017 May 1

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Water Science and Technology
  • Mechanical Engineering

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