Abstract
Along the 4 major rivers in korea, there are automatic water quality monitoring (AWQM) stations to immediately respond to any pollution incident. Real-time data (temperature, DO, pH, EC and TOC) collected at each station were statistically treated to exclude outliers and keep valid data using Dixon's test and Discordance test. These applied methods were compared in terms of the number of the outliers sorted out. There was no significant difference between these methods. On the other hand, more outliers were sorted out from EC and TOC data, comparing with other water quality items. EC data did not show partly any variation for a long time at H station. If measured signal does not exceed ${\pm}0.001mS/cm$ from the sectional mean, the signal should be treated as normal data. Therefore, another routine was added to the data screening system, some data which were removed as outlier were restored.