A Comparative Study on Lagrangian Stochastic Models for Sediment Transport

Probabilistic analysis of sediment movement has been initiated in the field of sediment transport to provide more information on key variables of sediment transport associated with stochastic properties. The key variables in the stochastic modeling approach can be considered stochastic variables. One can target one or multiple stochastic variable(s) in stochastic modeling. Selection of targeted stochastic variables may alter the way to simulate the natural phenomena. Which stochastic variables we select as a target variable can affect the simulating way to explain natural phenomena based on physical processes. In this study, we introduce a Lagrangian stochastic model for sediment transport that can be defined as the "first-order" stochastic particle tracking model. Whereas the "zeroth-order" Lagrangian stochastic models have one state variable of "particle position", the "first-order" Lagrangian stochastic models typically have two state variables such as "particle velocity" and "particle position". As a result, we obtain the ensemble statistics of particle velocity modeled by the proposed stochastic particle tracking model. Thus, we present how effectively stochastic models describe natural sediment transport processes with proper selections of stochastic variables. We also verify the proposed models with experimental data.