A systematic approach is described for determining the minimum level of model complexity required to predict runoff in New Zealand catchments, with minimal calibration, at decreasing timescales. Starting with a lumped conceptual model representing the most basic hydrological processes needed to capture water balance, model complexity is systematically increased in response to demonstrated deficiencies in model predictions until acceptable accuracy is achieved. Sensitivity and error analyses are performed to determine the dominant physical controls on streamflow variability. It is found that dry catchments are sensitive to a threshold storage parameter, producing inaccurate results with little confidence, while wet catchments are relatively insensitive, producing more accurate results with more confidence. Sensitivity to the threshold parameter is well correlated with climate and timescale, and in combination with the results of two previous studies, this allowed the postulation of a qualitative relationship between model complexity, timescale, and the climatic dryness index (DI). This relationship can provide an a priori understanding of the model complexity required to accurately predict streamflow with confidence in small catchments under given climate and timescales and a conceptual framework for model selection. The objective of the paper is therefore not to present a perfect model for any of the catchments studied but rather to present a systematic approach to modeling based on making inferences from data that can be applied with respect to different model designs, catchments and timescales.