Complex hydrological descriptions at the hillslope scale have been difficult to incorporate within a catchment modeling framework because of the disparity between the scale of measurements and the scale of model subunits. As a result, parameters represented in many conceptual models are often not related to physical properties and therefore cannot be established prior to a model calibration. While tolerable for predictions involving water quantity, water quality simulations require additional attention to transport processes, flow path sources, and water age. This paper examines how isotopic estimates of residence time may be used to subsume flow path process complexity and to provide a simple, scalable evaluative data source for water quantity- and quality-based conceptual models. We test a set of simple distributed hydrologic models (from simple to more complex) against measured discharge and residence time and employ a simple Monte Carlo framework to evaluate the identifiability of parameters and how the inclusion of residence time contributes to the evaluative process. Results indicate that of the models evaluated, only the most complex, including an explicit unsaturated zone volume and an effective porosity, successfully reproduced both discharge dynamics and residence time. In addition, the inclusion of residence time in the evaluation of the accepted models results in a reduction of the a posteriori parameter uncertainty. Results from this study support the conclusion that the incorporation of soft data, in this case, isotopically estimated residence times, in model evaluation is a useful mechanism to bring experimental evidence into the process of model evaluation and selection, thereby providing one mechanism to further reconcile hillslope-scale complexity with catchment-scale simplicity.