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Complexity–entropy analysis of daily stream flow time series in the continental United States
Publikationstyp
Journal Article
Date Issued
2014-10-01
Sprache
English
Author(s)
Serinaldi, Francesco
Zunino, Luciano
Rosso, Osvaldo A.
Volume
28
Issue
7
Start Page
1685
End Page
1708
Citation
Stochastic Environmental Research and Risk Assessment 28 (7): 1685-1708 (2014)
Publisher DOI
Scopus ID
Publisher
Springer
Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy (Formula presented.) that has been introduced in nonlinear dynamics analysis to classify signals according to their degrees of randomness and complexity. In this study, we explore the applicability of CECP in hydrological studies by analyzing 80 daily stream flow time series recorded in the continental United States during a period of 75 years, surrogate sequences simulated by autoregressive models (with independent or long-range memory innovations), Theiler amplitude adjusted Fourier transform and Theiler phase randomization, and a set of signals drawn from nonlinear dynamic systems. The effect of seasonality, and the relationships between the CECP quantifiers and several physical and statistical properties of the observed time series are also studied. The results point out that: (1) the CECP can discriminate chaotic and stochastic signals in presence of moderate observational noise; (2) the signal classification depends on the sampling frequency and aggregation time scales; (3) both chaotic and stochastic systems can be compatible with the daily stream flow dynamics, when the focus is on the information content, thus setting these results in the context of the debate on observational equivalence; (4) the empirical relationships between (Formula presented.) and Hurst parameter H, base flow index, basin drainage area and stream flow quantiles highlight that the CECP quantifiers can be considered as proxies of the long-term low-frequency groundwater processes rather than proxies of the short-term high-frequency surface processes; (6) the joint application of linear and nonlinear diagnostics allows for a more comprehensive characterization of the stream flow time series.
Subjects
Bandt and Pompe method
Complexity–entropy causality plane
Hurst parameter
Permutation entropy
Permutation statistical complexity
Stream flow
DDC Class
620: Engineering