Abstract
In hydrological statistics, the traditional assessment of goodness of fit test is interested in the testing precision to the sample generated from supposed PDF. However, the ability to reject the hypotheses when the supposed PDF is different from real PDF should be also emphasized. In addition, the sensitivity of test method to series length is important in hydrological analysis. Three methods of goodness of fit test that include Chi-Square (C-S), Kolmogorov-Smirnov (K-S), and Anderson-Darling (A-D) tests are applied in this study. The results of power test indicate that the most powerful tests for normal, uniform, P3, and Weibull distribution are K-S, C-S, and A-D tests, respectively. The test method with the best comprehensive power is C-S test, followed by K-S and A-D test.
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