Remediation of metal and radionuclide contaminants in soil and groundwater systems is challenging because of their strong chemical interactions with mineral surfaces and low concentration limits for human health requirements. By stimulating the activity of natural microorganisms it is possible to manipulate the redox state of contaminants and greatly decrease their solubility, rendering them immobile and therefore reducing the risk of human exposure. Accurate numerical models of bioremediation are needed to support design and evaluation of field implementations. Although there is extensive evidence suggesting the important role that mobile (planktonic) bacteria play in bioremediation of metals, both from field experiments and numerical studies, few models used for this purpose directly simulate planktonic bacteria movement or include active motility or chemotaxis effects. We propose to perform microscale experiments using advanced microfluidics and imaging techniques to develop models of microbial movements in porous media. These models will be incorporated into pore-scale simulations that will be used to generalize the experimental observations to a broader range of pore geometries and flow conditions. The overarching objective of this research is to improve the predictive capabilities of numerical simulators by incorporating understanding of microbial motility and implications of storing electrons during motion processes, which will provide better tools to guide remedial design and decisions aimed at protecting the public from exposure to subsurface contaminants.