Investigating anthropically induced effects in streamflow dynamics by using permutation entropy and statistical complexity analysis: A case study

作     者：Stosic, Tatijana Telesca, Luciano de Souza Ferreira, Diego Vicente Stosic, Borko 

作者机构：Univ Fed Rural Pernambuco Dept Estat & Informat Rua Dom Manoel Medeiros S-N BR-52171900 Recife PE Brazil CNR Inst Methodol Environm Anal I-85050 Tito Italy 

出 版 物：《JOURNAL OF HYDROLOGY》 (水文学杂志)

年 卷 期：2016年第540卷第0期

页      面：1136-1145页

核心收录：

学科分类：08[工学] 0708[理学-地球物理学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 0814[工学-土木工程] 

基　　金：CAPES CNPq [306719/2012-6] 

主　　题：Streamflow Dam Permutation entropy Statistical complexity 

摘      要：In this paper we investigated the influence of the construction of Sobradinho dam on daily streamflow of Sao Francisco river, Brazil, using permutation entropy method. We analyzed a long daily streamflow time series recorded during the period 1929-2010 encompassing the construction of Sobradinho dam between 1973 and 1979. We found that the original and deseasonalized streamflow time series are characterized by clear different complexity and entropy patterns before the construction of the dam;while, after it, their degree of randomness and complexity are nearly identical. Furthermore, investigating the oscillatory behavior of the entropy and complexity time variation, the periodicity of 3.67 years was identified, identical to one of the main periodicities revealed in the Multivariate ENSO Index (MEI). Such finding confirms the close relationship between streamflow dynamics and ENSO phenomenon. After the construction of the dam, the time variation of entropy and complexity changes almost abruptly toward stochastic regime characterized by higher entropy and lower complexity. Although the dam operations could be considered responsible for such abrupt dynamical change in the streamflow, we cannot exclude the presence of a co-induced ENSO effect;in fact, the analysis of MEI shows a strikingly similar and concomitant change in the long-term trend, identified by using the singular spectrum analysis. (C) 2016 Elsevier B.V. All rights reserved.