This paper presents a joint inversion approach for combining crosshole seismic travel time and borehole flowmeter test data to estimate hydrogeological zonation. The approach is applied to a complex, fractured Department of Energy field site located at the Oak Ridge National Laboratory in Tennessee, United States. We consider seismic slowness (the inverse of seismic velocity) and hydrogeological zonation indicators as unknown variables and use a physically based model with unknown parameters to relate the seismic slowness to the zonation indicators. We jointly estimate all the unknown parameters in the model by conditioning them to the crosshole seismic travel times as well as the borehole flowmeter data using a Bayesian model and a Markov chain Monte Carlo sampling method. The fracture zonation estimates are qualitatively compared to bromide tracer breakthrough data and to uranium biostimulation experiment results. The comparison suggests that the joint inversion approach adequately estimated the fractured zonation and that the fracture zonation influenced biostimulation efficacy. Our study suggests that the new joint hydrogeophysical inversion approach is flexible and effective for integrating various types of data sets within complex subsurface environments and that seismic travel time data have the potential to provide valuable information about fracture zonation.