Reliability test for detecting change-point of hydrological time series
A Bayesian model for analyzing change-points of time series is established to study the abrupt change of the mean value of strong autocorrelated and abnormal distributed hydrological time series. The maximum annual runoff time series from 1942 to 2008 of one hydrometric station is analyzed; the results of the Bayesian model show that 1989 is the most probable change-point location with the largest posterior probability. But whether there exists abrupt change on earth cannot be detected from the Bayesian model result; further reliability test should be done to testify the change around 1989 belongs to chance fluctuation or there exists abrupt change indeed. Resampling method is used to determine the reliability of the estimated change-point. The result shows that there exists abrupt change indeed; the change around 1989 is far more than stochastic fluctuation. Taking the randomness of observed time series into account, reliability test should be done when using Bayesian model to detect the change-point location in future work and bootstrap resampling method is recommended.
NETL
NSTL
万方数据
维普
