AbstractThe dispersal rates of self‐propelled microorganisms affect their spatial interactions and the ecological functioning of microbial communities. Microbial dispersal rates affect risk of contamination of water resources by soil‐borne pathogens, the inoculation of plant roots, or the rates of spoilage of food products. In contrast with the wealth of information on microbial dispersal in water replete systems, very little is known about their dispersal rates in unsaturated porous media. The fragmented aqueous phase occupying complex soil pore spaces suppress motility and limits dispersal ranges in unsaturated soil. The primary objective of this study was to systematically evaluate key factors that shape microbial dispersal in model unsaturated porous media to quantify effects of saturation, pore space geometry, and chemotaxis on characteristics of principles that govern motile microbial dispersion in unsaturated soil. We constructed a novel 3‐D angular pore network model (PNM) to mimic aqueous pathways in soil for different hydration conditions; within the PNM, we employed an individual‐based model that considers physiological and biophysical properties of motile and chemotactic bacteria. The effects of hydration conditions on first passage times in different pore networks were studied showing that fragmentation of aquatic habitats under dry conditions sharply suppresses nutrient transport and microbial dispersal rates in good agreement with limited experimental data. Chemotactically biased mean travel speed of microbial cells across 9 mm saturated PNM was ∼3 mm/h decreasing exponentially to 0.45 mm/h for the PNM at matric potential of (for , dispersal practically ceases and the mean travel time to traverse the 9 mm PNM exceeds 1 year). Results indicate that chemotaxis enhances dispersal rates by orders of magnitude relative to random (diffusive) motions. Model predictions considering microbial cell sizes relative to available liquid pathways sizes were in good agreement with experimental results for unsaturated soils. The new modeling platform enables quantitative consideration of key biophysical factors (e.g., pore space heterogeneities and hydration conditions) governing microbial interactions in 3‐D soil pore spaces.