<p>Hydrological models are useful tools to explore the hydrological impact of climate change. Many of these models require calibration. A frequently employed strategy is to calibrate the five parameters that were found to be most relevant as identified in a sensitivity analysis. However, parameter sensitivity varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity within a plausible climate change rate, and investigate if changes in sensitivity propagate into the calibration strategy. We employed three frequently used hydrological models (SAC, VIC, and HBV), and explored parameter sensitivity changes across 605 catchments in the United States by comparing a GCM-forced historical and future period. Consistent among all models is that the sensitivity of snow parameters decreases in the future. Which parameters increase in sensitivity is less consistent among the models. In 43 % to 49 % of the catchments, dependent on the model, at least one parameter changes in the future in the top-5 most sensitive parameters. The maximum number of changes in the parameter top-5 is two, in 2–4 % of the investigated catchments. The value of the parameters that enter the top-5 cannot easily be identified based on historical data, because the model is not yet sensitive to these parameters. This requires an adapted calibration strategy for long-term projections, for which we provide several suggestions. The disagreement among the models on processes becoming relevant in future projections also calls for a strict evaluation of the adequacy of the model structure and the model parameters implemented therein.</p>