抄録
A non-stationary time series is composed of the trend and some jumps by the change of a mean value and a variance. There is no study example which hasdealt with the power of test fora jump of variance in a hydrological time series.
In this paper, the Monte Carlo simulations are applied to compare the power of the statistical tests: Student's t test, F test, Mann-Whitney test and bootstrap test to assess the significance of jumps to affect the mean value and the variance of a time series with Normal, Logarithm Normal and General Extreme Value distributions. And also, the outliers in the annual maximum daily rainfall (MDR) and annual maximum non-rainfall days (NRD) data of each 22 meteorological observatories in Hokkaido are detected at Tomakomai and Hiroo for MDR data, and at Esashi for NRD data, respectively. Then the normalized conditionsto change these three outliers into normal values are introduced by using a numerical simulation.
