Numerical Modeling of Biofilm–Flow Dynamics in Gravel-Bed Rivers: A Framework for Sustainable Restoration

This study investigates biofilm–flow interactions in gravel-bed rivers using a novel numerical model. Traditional hydrodynamic models often overlook biofilm-induced roughness coupling, prompting the development of a mesoscopic Lattice Boltzmann Method (LBM) framework that dynamically links biofilm thickness to equivalent roughness. Key insights include a dual-phase mechanism: moderate biofilm growth reduces hydraulic resistance by smoothing gravel pores, while excessive growth increases resistance via flow obstruction. Validated against 65-day flume experiments, the model accurately predicted biomass (ash-free dry mass) and velocity profiles. Current limitations involve reliance on empirical biofilm formulas, lack of natural river validation (non-uniform substrates, dynamic flows), and computational barriers in 3D large-scale simulations. Future directions include integrating biogeochemical factors (temperature, nutrients), multiscale microbial-morphology frameworks, and GPU-accelerated high-resolution modeling.