Klai M. auteur aut IRD Monga Olivier auteur aut IRD Jouini M. S. auteur aut IRD Pot V. auteur aut IRD text journalArticle eng text/pdf reformatted digital access This paper deals with the computational modeling of biological dynamics in soil using an exact micro-scale pore space description from 3D Computed Tomography (CT) images. Within this context, computational costs and storage requirements constitute critical factors for running simulations on large datasets over extended periods. In this research, we represent the pore space by a graph of voxels (Voxel Graph-Based Approach, VGA) and model transport in fully saturated conditions (two-phase system) using Fick's law and coupled diffusion with biodegradation processes to simulate microbial decomposition in soil. To significantly decrease the computational time of our approach, the diffusion model is solved by means of Euler discretization schemes, along with parallelization strategies. We also tested several numerical strategies, including implicit, explicit, synchronous, and asynchronous schemes. To validate our VGA, we compare it with LBioS, a 3D model that integrates diffusion (via the Lattice Boltzmann method) with biodegradation, and Mosaic, a Pore Network Geometrical Modelling (PNGM) which represents the pore space using geometrical primitives. Our method yields result similar to those of LBioS in a quarter of the computing time. While slower than Mosaic, it is more accurate and requires no calibration. Additionally, we show that our approach can improve PNGM-based simulations by using a machine-learning approach to approximate diffusional conductance coefficients. specialized 068 074 020 20 3 e0313853 [25 ] 2025 1932-6203 https://www.documentation.ird.fr/hor/fdi:010092893 10.1371/journal.pone.0313853 1932-6203 [F B010092893] https://www.documentation.ird.fr/hor/fdi:010092893 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2025-04/010092893.pdf IRD - Base Horizon / Pleins textes 2025-04-02 2025-11-04 fdi:010092893 fre