The use of uncertainty analysis is gaining considerable attention in catchment hydrological modeling. In particular, the choice of appropriate model structure, identifiability of parameter values, and the reduction of model predictive uncertainty are deemed as essential elements of hydrological modeling. The chosen model structure must be parsimonious, and the parameters used must either be derivable from field-measured data or inferred unambiguously from analysis of catchment response data. In this paper, a long-term water balance model for the Susannah Brook catchment in Western Australia has been pursued using the “downward approach,” which is a systematic approach to determine the model with the minimum level of complexity, with parameter values that, in theory, are derivable from existing physiographic data relating to the catchment. Through analysis of rainfall-runoff response at three different timescales and exploring the climate, soil, and vegetation controls on the water balance response at these timescales, an initial model structure was formulated, and a priori model parameter values were estimated. Further investigation with the use of auxiliary data such as deuterium concentration in the streamflow exposed inadequacies in the chosen model structure. Two more model structures were then proposed and investigated through formulating alternative hypotheses regarding the underlying causes of observed variability, including those suggested by observed deuterium composition in the streamflows and observed groundwater level dynamics. Along the way, the resulting models were systematically evaluated in three dimensions: ability to reproduce observations, predictive uncertainty, and physical realism. The final model, which included an efficient but detailed representation of unsaturated zone time delay, was found to be superior on all three counts, i.e., improved performance, reduced predictive uncertainty, and improved physical realism. These improvements can be directly attributed to the use of the auxiliary data (deuterium composition and groundwater level dynamics), which identified weaknesses in previous model structures, and the multiple wetting front model of water movement in the unsaturated zone, which captured more effectively the time delay in the unsaturated zone.