Dispersion modeling is crucial for marine environmental modeling and management. However, operational applications require a practical balance between model accuracy and computational efficiency. To address this challenge, we develop and validate a generalized cell-based model (CBM) framework for contaminant dispersion. The framework enhances physical realism through a novel three-dimensional (3D) transport model and a formulation for chemical reactions. Additionally, a new discretization-based approach is proposed to robustly relate the CBM’s diffusion coefficient to its partial differential equation counterpart, improving performance in scenarios with sharp gradients of the concentration level. The proposed framework’s favorable trade-off between accuracy and efficiency is demonstrated in a comparative simulation study, where the 3D CBM reduces computation time from 14.72 s to 0.06 s compared to finite-element methods (FEM), with a relative Root Mean Square Error (RMSE) of 7.67%. To demonstrate its practical applicability, the proposed framework is validated using ocean current and nitrate concentration data from the Copernicus Marine Environment Monitoring Service. After identifying a key model parameter from the data, the model’s forward predictions accurately reproduce the observed nitrate concentration patterns, confirming its suitability for operational scenarios.

In practice, achieving a balance between accuracy, stability, and computational efficiency in modeling contaminant dispersion in marine environments remains challenging due to complex physical dynamics and numerical constraints. To address these challenges, an enhanced cell-based model (CBM) is developed and applied to simulate pollutant transport in the ocean. The CBM discretizes the spatial domain into uniform cells, resulting in a naturally parallelizable structure, and characterizes the transport process by incorporating both water flow-driven convection and diffusion effects. Moreover, two approaches are proposed for estimating the diffusion coefficient, and their performance is compared to a first-order upwind scheme finite-difference method (FDM) solution. Finally, the CBM is comprehensively compared with both the FDM and the finite-element method (FEM) solvers under varying spatial and temporal resolutions. Simulation results show that the CBM is less affected by the Courant-Friedrichs-Lewy (CFL) conditions and demonstrates stable convergence where the FDM fails or requires stricter settings. In addition, the CBM offers a favorable trade-off between accuracy and computational efficiency under coarse configurations. These results indicate that the CBM provides a reliable foundation for dynamic modeling and integration with learning-based frameworks in marine environment simulations.