Lagrangian Stochastic Sediment Dynamics in Turbulent Flows

Sediment transport plays a crucial role in shaping our natural and engineered landscapes, affecting everything from riverbanks to coastal regions and ecological habitats. It is key to effective disaster management, helping predict and mitigate the effects of floods, landslides, and coastal erosion. However, modeling how sediment moves through water and landscapes remains a complex challenge. This complexity is due to the unpredictable nature of turbulent flows and sediment movement, compounded by issues such as natural variability, lack of sufficient data for accurate model testing, and high computational demand.

This research introduces an innovative approach by integrating Lagrangian turbulent velocity theory into sediment transport models. By developing a new model that utilizes differentiable stochastic processes, this study aims to enhance our ability to predict and understand how particles behave in turbulent flows. This advanced modeling technique addresses key challenges like the unpredictability, intermittent behavior, and memory effects associated with particle movement in turbulent conditions. Ultimately, this research seeks to refine our understanding of sediment dynamics, pushing the boundaries of existing models and providing more reliable tools for environmental management.