Accurate representation of soil organic matter (SOM) dynamics in Earth System Models is critical for future climate prediction, yet large uncertainties exist regarding how, and to what extent, the suite of proposed relevant mechanisms should be included. To investigate how various mechanisms interact to influence SOM storage and dynamics, we developed a SOM reaction network integrated in a one-dimensional, multi-phase and multi-component reactive transport solver. The model includes representations of bacterial and fungal activity, multiple archetypal polymeric and monomeric carbon substrate groups, aqueous chemistry, aqueous advection and diffusion, gaseous diffusion, and adsorption (and protection) and desorption from the soil mineral phase. The model predictions reasonably matched observed depth-resolved SOM and dissolved organic carbon (DOC) stocks in grassland ecosystems as well as lignin content and fungi to aerobic bacteria ratios. We performed a suite of sensitivity analyses under equilibrium and dynamic conditions to examine the role of dynamic sorption, microbial assimilation rates, and carbon inputs. To our knowledge, observations do not exist to fully test such a complicated model structure or to test the hypotheses used to explain observations of substantial storage of very old SOM below the rooting depth. Nevertheless, we demonstrated that a reasonable combination of sorption parameters, microbial biomass and necromass dynamics, and advective transport can match observations without resorting to an arbitrary depth-dependent decline in SOM turnover rates, as is often done. We conclude that, contrary to assertions derived from existing turnover time based model formulations, observed carbon content and 14C vertical profiles are consistent with a representation of SOM consisting of carbon compounds without designated intrinsic turnover times, vertical aqueous transport, and dynamic protection on mineral surfaces.