This study presents a novel enhancement for Lagrangian particle transport modeling by integrating Coherent Structures theory. Lagrangian transport modeling is frequently utilized to forecast the trajectories of floating particles in the ocean despite the unstable nature of geophysical velocity fields that inevitably result in large trajectory errors. Current particle tracking methodologies often rely on deploying numerous particles and incorporating diffusion mechanisms into models to estimate particle probabilities across different locations. However, this approach can result in significant disparities in the final particle locations, thereby posing challenges in scenarios such as search and rescue operations and oil spill containment. To address these limitations, this study leverages dynamical systems and Eulerian Coherent Structures to improve particle tracking accuracy and diminish uncertainty.