Uncertainty Assessment of Future High and Low Flow Projections According to Climate Downscaling and Hydrological Models

The quantitative assessment of change in water availability and appropriate water resources management are needed for corresponding adaptation. However, there are large uncertainties in climate change impact assessment on water resources. In this sense, the aims of this study are to suggest the uncertainty assessment method for climate change impact assessment and to investigate the uncertainty characteristics for high and low flow between downscaling methods and hydrological models. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods (SPP), and 2 hydrological models (HYM) were applied on the Chungju dam basin, Korea. The results of uncertainty analysis showed that RCM has the largest sources of uncertainty in 1-day maximum dam inflow (about 40.7%), while HYM has the largest sources of uncertainty in 30-days minimum dam inflow (about 41.5%). In other words, high flow was mainly effected by RCM and low flow by HYM. The proposed methodology in this study can be used to quantify the uncertainties caused by RCM, SPP, and HYM.