Stochastic processes, in the form of stochastic differential equations (SDEs), integrate stochastic elements to account for the inherent randomness in sediment particle trajectories in an open-channel turbulent flow. Accordingly, a stochastic diffusion particle tracking model has been proposed in the literature to analyze suspended sediment dynamics. In this work, we develop a reflected stochastic diffusion particle tracking model (RSDPTM) for suspended sediment motion in a two-dimensional open-channel flow based on reflected SDE (RSDE), which is a mathematically consistent theory for stochastic processes in a bounded region. The Eulerian model given in terms of the Fokker–Planck equation is also proposed by formulating boundary conditions for the confined domain. The existence and uniqueness of the solution to the proposed RSDE are proven, and the strong order of convergence of the projected Euler–Maruyama method is discussed. In order to correctly incorporate the physical mechanism of sediment-laden open-channel flow, an improved algorithm considering the threshold criteria of sediment suspension is proposed. The ensemble means, variances, and mean-squared displacements in both streamwise and vertical directions are discussed. It is observed that the particle motion in both directions follows anomalous diffusion, which is the deviation from normal or Fickian diffusion theory. Finally, the proposed model is validated through the suspended sediment concentration (SSC) distribution by comparing it with relevant experiential data, and the comparison shows an excellent agreement between the estimated and measured values of SSC. In summary, the proposed RSDPTM and improved algorithm may enhance our idea about the inherent randomness of suspended sediment motion in an open-channel turbulent flow.
Kumbhakar et al. (Tue,) studied this question.