According to recent researches on climate change, the global warming is obvious to increase rainfall
intensity. Damage caused by extreme hydrologic events due to global change is steadily getting bigger and bigger.
Recently, frequently occurring heavy rainfalls surely affect the trend of rainfall observations. Probability precipitation
estimation method used in designing and planning hydrological resources assumes that rainfall data is stationary. The
stationary probability precipitation estimation method could be very weak to abnormal rainfalls occurred by climate
change, because stationary probability precipitation estimation method cannot reflect increasing trend of rainfall
intensity. This study analyzed temporal variation of trend in rainfall time series at 51 stations which are not
significant for statistical trend tests. After modeling rainfall time series with maintaining observed statistical
characteristics, this study also estimated whether rainfall data is significant for the statistical trend test in near
future. It was found that 13 stations among sample stations will have trend within 10 years. The results indicate
that non-stationary probability precipitation estimation method must be applied to sufficiently consider increase trend
of rainfall.
Keywords : Temporal variation, Climate Change, Trend, Rainfall time series