Applications of multiscale change point detections to monthly stream flow and rainfall in Xijiang River in southern China, part I: correlation and variance
Publication in refereed journal


Times Cited
Altmetrics Information
.

Other information
AbstractThis article, as part I, introduces three algorithms and applies them to both series of the monthly stream flow and rainfall in Xijiang River, southern China. The three algorithms include (1) normalization of probability distribution, (2) scanning U test for change points in correlation between two time series, and (3) scanning F-test for change points in variances. The normalization algorithm adopts the quantile method to normalize data from a non-normal into the normal probability distribution. The scanning U test and F-test have three common features: grafting the classical statistics onto the wavelet algorithm, adding corrections for independence into each statistic criteria at given confidence respectively, and being almost objective and automatic detection on multiscale time scales. In addition, the coherency analyses between two series are also carried out for changes in variance. The application results show that the changes of the monthly discharge are still controlled by natural precipitation variations in Xijiang’s fluvial system. Human activities disturbed the ecological balance perhaps in certain content and in shorter spells but did not violate the natural relationships of correlation and variance changes so far.
All Author(s) ListZhu Y, Jiang J, Huang C, Chen YD, Zhang Q
Journal nameTheoretical and Applied Climatology
Year2019
Month4
Volume Number136
Issue Number1-2
PublisherSpringer
Pages237 - 248
ISSN0177-798X
eISSN1434-4483
LanguagesEnglish-United States

Last updated on 2020-23-10 at 02:29