A hydro-environmental model chain in the Doam dam basin, Korea, was developed for an impact assessment under the Intergovernmental Panel on Climate Change's A1B scenario. The feasible downscaling scheme composed of an artificial neural network (ANN) and non-stationary quantile mapping was applied to the GCM (Global Climate Model) output. The impacts under climate and land use change scenarios were examined and projected using the Soil and Water Assessment Tool (SWAT) model. The daily SWAT model was calibrated and validated for 2003–2004 and 2006–2008, respectively. Meanwhile the monthly SS (suspended solids) was calibrated and validated for 1999–2001 and 2007–2009, respectively. The simulation results illustrated that under the assumption of 1–5% urbanization of the forest area, the hydrologic impact is relatively negligible and the climate change impacts are dominant over the urbanization impacts. Additionally the partial impacts of land use changes were analyzed under five different scenarios: partial change of forest to urban (PCFUr), to bare field, to grassland, to upland crop (PCFUp), and to agriculture (PCFA). The analysis of the runoff change shows the highest rate of increase, 73.57% in April, for the PCFUp scenario. The second and third highest rate increases, 37.83% and 31.45% in May, occurred under the PCFA and PCFUr scenarios, respectively.