Development of a Backward–Forward Stochastic Particle Tracking Model for Identification of Probable Sedimentation Sources in Open Channel Flow

Chelsie Chia-Hsin Liu, Christina W. Tsai and Yu-Ying Huang
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Chelsie Chia-Hsin Liu: Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan
Christina W. Tsai: Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan
Yu-Ying Huang: Department of Civil Engineering, National Taiwan University, Taipei 10617, Taiwan

Mathematics, 2021, vol. 9, issue 11, 1-35

Abstract: As reservoirs subject to sedimentation, the dam gradually loses its ability to store water. The identification of the sources of deposited sediments is an effective and efficient means of tackling sedimentation problems. A state-of-the-art Lagrangian stochastic particle tracking model with backward–forward tracking methods is applied to identify the probable source regions of deposited sediments. An influence function is introduced into the models to represent the influence of a particular upstream area on the sediment deposition area. One can then verify if a specific area might be a probable source by cross-checking the values of influence functions calculated backward and forward, respectively. In these models, the probable sources of the deposited sediments are considered to be in a grid instead of at a point for derivation of the values of influence functions. The sediment concentrations in upstream regions must be known a priori to determine the influence functions. In addition, the accuracy of the different types of diffusivity at the water surface is discussed in the study. According to the results of the case study of source identification, the regions with higher sediment concentrations computed by only backward simulations do not necessarily imply a higher likelihood of sources. It is also shown that from the ensemble results when the ensemble mean of the concentration is higher, the ensemble standard deviation of the concentration is also increased.

Keywords: sediment particle movement; stochastic model; particle tracking model; probable source; diffusivity; concentration distribution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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