Low flow projections in response to global warming and the uncertainty decomposition into different components are performed with the focus on the Chungju basin, South Korea. Four downscaled climate simulations, two bias correction methods, and two hydrological models with two different potential evapotranspiration computation methods are applied to constitute the 32 ensemble members (4 × 2 × 4) of low flows projections. An analysis of the variance is used to decompose the total variance in the low flow projections into the contribution from three different sources. The result shows that hydrological models, particularly their structures, are the key factor that affects the low flow projections. They contribute more than 85% of the total uncertainty, and the projected change of low flow using different hydrological models can be of opposite signs, even under the same climate input data. On the other hand, the uncertainties related to climate simulation and bias correction are much smaller, comprising around 10 and 2%, respectively. The possible mechanisms behind the large uncertainty of projected low flow are investigated by comparing the relevant hydrological variables obtained from different hydrological simulations. The different representations in the hydrological models for the freezing of the soil layer during winter, which will undergo large changes as temperature increases, are likely to affect the projected change in low flow greatly. The difference in potential evapotranspiration methods also affects the low flow projections, but its contribution is relatively weaker than the effects of the hydrological model structure.
