Abstract

Info

Title:: Mutation Test on Rainfall and Runoff Time Series Based on Sample Entropy

Author(s):: XUE Lian-qing; LIU Yuan-hong; ZHANG Meng-ze; WANG Si-qi; LI Jun; 1. School of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China; 2. School of Water and Architectural Engineering, Shihezi University, Shihezi 832003, Xinjiang, China; 3. School of Wentian, Hohai University, Ma’anshan 243031, Anhui, China; 4. Tai’an Bureau of Hydrology, Tai’an 271000, Shandong, China

Keywords:: engineering hydrology; time series; mutation test; Mann-Kendall method; sample entropy; complexity; Xiangjiang river basin

Abstract:: The traditional mutation test method including Mann-Kendall method, which is mainly based on the theories of linear, probability and statistic, is insufficient for testing the highly complex and nonlinear hydrological time series. Combined with moving and moving cut data technologies, sample entropy based on nonlinear dynamic parameter was applied for the mutation test on rainfall and runoff time series in Xiangjiang river basin. The test data included daily rainfall in several meteorological stations and daily runoff in Xiangtan control station of Xiangjiang river basin from 1961 to 2009. The results show that the sample entropy of daily rainfall and runoff time series is smallest, the complexity is lowest, and the predictability is highest; the mutations of runoff occur in 1966, 1983, 1992 and 2002, the mutations of rainfall occur in 1966, 1987 and 2002; the combination of moving sample entropy and moving cut data sample entropy can not only recognize the mutation effectively, but also discover the characteristics of dynamic variation before and after the mutation of time series.