Complexity–entropy analysis of daily stream flow time series in the continental United States

Autores
Serinaldi, Francesco; Zunino, Luciano José; Rosso, Osvaldo Aníbal
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy HS versus Jensen–Shannon complexity CJS 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 HS and CJS 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.
Centro de Investigaciones Ópticas
Materia
Física
Ingeniería
Stream flow
Complexity–entropy causality plane
Permutation entropy
Permutation statistical complexity
Bandt and Pompe method
Hurst parameter
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/146362

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network_name_str SEDICI (UNLP)
spelling Complexity–entropy analysis of daily stream flow time series in the continental United StatesSerinaldi, FrancescoZunino, Luciano JoséRosso, Osvaldo AníbalFísicaIngenieríaStream flowComplexity–entropy causality planePermutation entropyPermutation statistical complexityBandt and Pompe methodHurst parameterComplexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy H<sub>S</sub> versus Jensen–Shannon complexity C<sub>JS</sub> 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 H<sub>S</sub> and C<sub>JS</sub> 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.Centro de Investigaciones Ópticas2014-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf1685-1708http://sedici.unlp.edu.ar/handle/10915/146362enginfo:eu-repo/semantics/altIdentifier/issn/1436-3240info:eu-repo/semantics/altIdentifier/issn/1436-3259info:eu-repo/semantics/altIdentifier/doi/10.1007/s00477-013-0825-8info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:14:56Zoai:sedici.unlp.edu.ar:10915/146362Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:14:56.582SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Complexity–entropy analysis of daily stream flow time series in the continental United States
title Complexity–entropy analysis of daily stream flow time series in the continental United States
spellingShingle Complexity–entropy analysis of daily stream flow time series in the continental United States
Serinaldi, Francesco
Física
Ingeniería
Stream flow
Complexity–entropy causality plane
Permutation entropy
Permutation statistical complexity
Bandt and Pompe method
Hurst parameter
title_short Complexity–entropy analysis of daily stream flow time series in the continental United States
title_full Complexity–entropy analysis of daily stream flow time series in the continental United States
title_fullStr Complexity–entropy analysis of daily stream flow time series in the continental United States
title_full_unstemmed Complexity–entropy analysis of daily stream flow time series in the continental United States
title_sort Complexity–entropy analysis of daily stream flow time series in the continental United States
dc.creator.none.fl_str_mv Serinaldi, Francesco
Zunino, Luciano José
Rosso, Osvaldo Aníbal
author Serinaldi, Francesco
author_facet Serinaldi, Francesco
Zunino, Luciano José
Rosso, Osvaldo Aníbal
author_role author
author2 Zunino, Luciano José
Rosso, Osvaldo Aníbal
author2_role author
author
dc.subject.none.fl_str_mv Física
Ingeniería
Stream flow
Complexity–entropy causality plane
Permutation entropy
Permutation statistical complexity
Bandt and Pompe method
Hurst parameter
topic Física
Ingeniería
Stream flow
Complexity–entropy causality plane
Permutation entropy
Permutation statistical complexity
Bandt and Pompe method
Hurst parameter
dc.description.none.fl_txt_mv Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy H<sub>S</sub> versus Jensen–Shannon complexity C<sub>JS</sub> 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 H<sub>S</sub> and C<sub>JS</sub> 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.
Centro de Investigaciones Ópticas
description Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized Shannon entropy H<sub>S</sub> versus Jensen–Shannon complexity C<sub>JS</sub> 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 H<sub>S</sub> and C<sub>JS</sub> 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.
publishDate 2014
dc.date.none.fl_str_mv 2014-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/146362
url http://sedici.unlp.edu.ar/handle/10915/146362
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1436-3259
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00477-013-0825-8
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
1685-1708
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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