Hydrologic modeling and streamflow prediction of ungauged basins is an unsolved scientific problem as well as a policy-relevant science theme emerging as a major challenge to the hydrologic community. One way to address this problem is to improve hydrologic modeling capability through the use of spatial data and spatially distributed physically based models. This dissertation is composed of three papers focused on 1) the use of spatially distributed hydrologic models with spatially distributed precipitation inputs, 2) advanced multi-objective calibration techniques that estimate parameter uncertainty and use stream gauge and temperature data from multiple locations, and 3) an examination of the relationship between high-resolution soils data and streamflow recession for use in a priori parameter estimation in ungauged catchments. This research contributes to the broad quest to reduce uncertainty in predictions at ungauged basins by integrating developments of innovative modeling techniques with analyses that advance our understanding of natural systems.