The objective of this study is to examine the usefulness of climate model simulations (GCM) in Korea water resource management. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. AMIP-II(Atmospheric Model Intercomparison Project-II) type GCM simulation done by ECMWF(European Centre for Medium-Range Weather Forecasts) was used for indicator variable and observed mean average precipitation(MAP) values on 7 major river basins were used as target variable. Monte Carlo simulation is used to establish the significance of the estimator values. The results show that GCM simulations done by ECMWF are skillful in discriminating the high from the low of the observed MAP for wet season in all seven basins of Korea, but not enough for dry season.