Simulating stochastic transport: An efficient random displacement model for multi-domain applications in ecology, hydraulics, and environmental systems

The random displacement model (RDM) can efficiently simulate particle transport processes, which are difficult to observe, incorporating stochastic and hydraulic parameters. In recent decades, it has been used in many domains, including environments, hydraulics, and ecology. However, the results exhibit significant uncertainties arising from the model resolution, hydrodynamic accuracy, intrinsic characteristics of particles, and boundary conditions. The objective of the present study is to comprehensively interpret the RDM from theory to application, and emphasize essential considerations for users in different domains. The study also provides several application strategies for the model, based on several practical RDM cases. Determining the turbulent diffusivity and velocity profiles in complex flow field is a critical step to precisely simulate particle movement. Furthermore, the physical and biological properties of passive and active particles require fundamental investigation to extend the applicability of the model. Existing studies suggest that flexibly coupling the RDM with other numerical models customized to the characteristics of distinct problems will substantially expand the utility of the RDM and could yield innovative approaches for addressing previously intractable issues.