The PUB initiative aims to integrate knowledge of hydrological processes to provide the best hydrological characterization of ungauged basins. This requires the integration of models and methods to achieve those objectives. In this paper, recent modelling activities are reviewed, with the aim of demonstrating potential application to ungauged basins. First, the development and testing of process-oriented hydrological models is presented. Examples are shown of the utility of remote sensing in conditioning hydrological model parameters at the catchment scale. Subsequently, a Bayesian error-sensitive model calibration scheme (BATEA) is presented. This scheme acknowledges that rainfall errors propagate and persist in hydrological models, corrupting the parameter estimates. It is shown that BATEA offers parameter estimates unbiased by error in rainfall data. BATEA will be applied to multiple models across a range of basins using MOPEX and Australian data. As regionalization relationships will be derived through unbiased model parameter estimates, it is hoped that stronger relationships between catchment characteristics and model parameter values may be identified, permitting improved model performance in ungauged basins. Finally, multi-decadal climate variability across New South Wales is demonstrated and an ENSO-based mechanism is elucidated. Such understanding of climate/hydrology interfaces offers a greater insight into hydrological risk assessment at different temporal scales and may easily be coupled to regionalized models for ungauged basins at continental scales.