Climate-impact projections are subject to uncertainty arising from climate models, greenhouse gases emission scenarios,
bias correction and downscaling methods (BCDS), and the impact models. We studied the effects of hydrological model
parameterization and regionalization (HM-P and HM-R) on the cascade of uncertainty. We developed a new, widely-applicable approach that improves our understanding of how HM-P and HM-R along with other uncertainty drivers contribute to the overall uncertainty in climate-impact projections.
