Groundwater flow and solute transport are often driven by heterogeneities that elude easy identification. It is also difficult to select and describe the physico-chemical processes controlling solute behavior. As a result, definition of a conceptual model involves numerous assumptions both on the selection of processes and on the representation of their spatial variability. Even if a unique conceptual model could be identified, estimation of its parameters may be highly uncertain. Using a calibrated model for making groundwater predictions involves three types of uncertainties: those associated with the correctness of the conceptual model, which may arise during model construction or during prediction; those related to the accuracy of model parameters; and those corresponding to uncertainties in future stresses. In this context, validating a numerical model by comparing its predictions with actual measurements may not be sufficient for evaluting whether or not it provides a good representation of ‘reality’. Predictions will be close to measurements, regardless of model validity, if these are taken from experiments that stress well-calibrated model modes. On the other hand, predictions will be far from measurements when model parameters are very uncertain, even if the model is indeed a very good representation of the real system. Hence, we contend that ‘classical’ validation of hydrogeological models is not possible. Rather, models should be viewed as theories about the real system. This can be proven wrong, but they cannot be proven right. In this sense, we propose to follow a rigorous modeling approach in which different sources of uncertainty are explicitly recognized. The application of one such approach is illustrated by modeling a laboratory uranium tracer test performed on fresh granite, which was used as Test Case 1b in INTRAVAL.