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.
Highlights
Sediment that is trapped behind dams reduces reservoir capacity
This study examines the probable source regions of deposited sediments using a Backward–Forward Stochastic Diffusion Particle Tracking Model (Backward–Forward stochastic diffusion particle tracking model (SD-PTM)), a method of Lagrangian dynamics [18]
Based on SD-PTM and the assumption that the timescale is small enough to enable the limit of the difference quotient of the governing equation to be properly estimated, the backward SD-PTM is developed by converting the operators of the numerical Lagrangian equations
Summary
Sediment that is trapped behind dams reduces reservoir capacity. Adequate knowledge of the sediment transport process in rivers is needed [6]. The Shihmen reservoir, located in Taoyuan, is one of the main reservoirs in northern Taiwan It provides domestic as well as agricultural water supply and hydroelectricity for more than three million people in northern Taiwan. The Shihmen reservoir plays the role as a detention basin for the Taipei Basin. It has an effective storage capacity of nearly 309 million cubic meters, of which the sediment has occupied 31.6% since 2009 [7]. To manage reservoirs in a more sustainable way, identifying the source of the sediment particles is one step toward dealing with the problem [4]
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