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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/146362
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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 |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/issn/1436-3240 info:eu-repo/semantics/altIdentifier/issn/1436-3259 info:eu-repo/semantics/altIdentifier/doi/10.1007/s00477-013-0825-8 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International (CC BY 4.0) |
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application/pdf 1685-1708 |
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