Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin

Autores
Antico, Andres; Schlotthauer, Gaston; Torres, Maria Eugenia
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The current understanding of hydroclimatic processes is largely based on time series analysis of observations such as river discharge. Although records of these variables are often nonlinear and nonstationary, they have been commonly analyzed by classical methods designed for linear and/or stationary data. This study investigates the possibility of analyzing hydroclimatic time series using a novel data-driven method named Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), which is suitable for nonlinear and nonstationary signals. CEEMDAN is here applied to a monthly mean discharge record (1904–2010) of the Paraná River (South America). The results obtained in this way are interpreted by comparing them with CEEMDAN decompositions of other records such as climate index time series. It is found that Paraná flow modes consist of (i) annual and intraannual oscillations reflecting the rainfall seasonality of different Paraná Basin sectors, and (ii) interannual to interdecadal changes linked to climate cycles like El Niño/Southern Oscillation, the North Atlantic Oscillation, and the Interdecadal Pacific Oscillation. A nonlinear trend of Paraná discharge is found and reveals a monotonic increase that could be attributed to global warming and anthropogenic land-cover changes. The spectral separation of modes obtained using CEEMDAN is cleaner than that achieved by the Ensemble Empirical Mode Decomposition technique. This makes it easier to interpret CEEMDAN results. Hence, CEEMDAN is proposed as a powerful method for extracting physically meaningful information from hydroclimatic data.
Fil: Antico, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
Fil: Torres, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
Materia
Empirical Mode Decomposition
Complete EEMD with Adaptive Noise
Nonlinear Trends
Paraná River
Hydroclimatic Variability
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/85993
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/85993
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River BasinAntico, AndresSchlotthauer, GastonTorres, Maria EugeniaEmpirical Mode DecompositionComplete EEMD with Adaptive NoiseNonlinear TrendsParaná RiverHydroclimatic Variabilityhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1The current understanding of hydroclimatic processes is largely based on time series analysis of observations such as river discharge. Although records of these variables are often nonlinear and nonstationary, they have been commonly analyzed by classical methods designed for linear and/or stationary data. This study investigates the possibility of analyzing hydroclimatic time series using a novel data-driven method named Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), which is suitable for nonlinear and nonstationary signals. CEEMDAN is here applied to a monthly mean discharge record (1904–2010) of the Paraná River (South America). The results obtained in this way are interpreted by comparing them with CEEMDAN decompositions of other records such as climate index time series. It is found that Paraná flow modes consist of (i) annual and intraannual oscillations reflecting the rainfall seasonality of different Paraná Basin sectors, and (ii) interannual to interdecadal changes linked to climate cycles like El Niño/Southern Oscillation, the North Atlantic Oscillation, and the Interdecadal Pacific Oscillation. A nonlinear trend of Paraná discharge is found and reveals a monotonic increase that could be attributed to global warming and anthropogenic land-cover changes. The spectral separation of modes obtained using CEEMDAN is cleaner than that achieved by the Ensemble Empirical Mode Decomposition technique. This makes it easier to interpret CEEMDAN results. Hence, CEEMDAN is proposed as a powerful method for extracting physically meaningful information from hydroclimatic data.Fil: Antico, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; ArgentinaFil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaFil: Torres, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; ArgentinaAmerican Geophysical Union2014-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/85993Antico, Andres; Schlotthauer, Gaston; Torres, Maria Eugenia; Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin; American Geophysical Union; Journal of Geophysical Research; 119; 3; 2-2014; 1218-12332169-8996CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1002/2013JD020420info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013JD020420info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:56Zoai:ri.conicet.gov.ar:11336/85993instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:53:56.694CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
title Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
spellingShingle Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
Antico, Andres
Empirical Mode Decomposition
Complete EEMD with Adaptive Noise
Nonlinear Trends
Paraná River
Hydroclimatic Variability
title_short Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
title_full Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
title_fullStr Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
title_full_unstemmed Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
title_sort Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin
dc.creator.none.fl_str_mv Antico, Andres
Schlotthauer, Gaston
Torres, Maria Eugenia
author Antico, Andres
author_facet Antico, Andres
Schlotthauer, Gaston
Torres, Maria Eugenia
author_role author
author2 Schlotthauer, Gaston
Torres, Maria Eugenia
author2_role author
author
dc.subject.none.fl_str_mv Empirical Mode Decomposition
Complete EEMD with Adaptive Noise
Nonlinear Trends
Paraná River
Hydroclimatic Variability
topic Empirical Mode Decomposition
Complete EEMD with Adaptive Noise
Nonlinear Trends
Paraná River
Hydroclimatic Variability
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The current understanding of hydroclimatic processes is largely based on time series analysis of observations such as river discharge. Although records of these variables are often nonlinear and nonstationary, they have been commonly analyzed by classical methods designed for linear and/or stationary data. This study investigates the possibility of analyzing hydroclimatic time series using a novel data-driven method named Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), which is suitable for nonlinear and nonstationary signals. CEEMDAN is here applied to a monthly mean discharge record (1904–2010) of the Paraná River (South America). The results obtained in this way are interpreted by comparing them with CEEMDAN decompositions of other records such as climate index time series. It is found that Paraná flow modes consist of (i) annual and intraannual oscillations reflecting the rainfall seasonality of different Paraná Basin sectors, and (ii) interannual to interdecadal changes linked to climate cycles like El Niño/Southern Oscillation, the North Atlantic Oscillation, and the Interdecadal Pacific Oscillation. A nonlinear trend of Paraná discharge is found and reveals a monotonic increase that could be attributed to global warming and anthropogenic land-cover changes. The spectral separation of modes obtained using CEEMDAN is cleaner than that achieved by the Ensemble Empirical Mode Decomposition technique. This makes it easier to interpret CEEMDAN results. Hence, CEEMDAN is proposed as a powerful method for extracting physically meaningful information from hydroclimatic data.
Fil: Antico, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
Fil: Schlotthauer, Gaston. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; Argentina
Fil: Torres, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas; Argentina
description The current understanding of hydroclimatic processes is largely based on time series analysis of observations such as river discharge. Although records of these variables are often nonlinear and nonstationary, they have been commonly analyzed by classical methods designed for linear and/or stationary data. This study investigates the possibility of analyzing hydroclimatic time series using a novel data-driven method named Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), which is suitable for nonlinear and nonstationary signals. CEEMDAN is here applied to a monthly mean discharge record (1904–2010) of the Paraná River (South America). The results obtained in this way are interpreted by comparing them with CEEMDAN decompositions of other records such as climate index time series. It is found that Paraná flow modes consist of (i) annual and intraannual oscillations reflecting the rainfall seasonality of different Paraná Basin sectors, and (ii) interannual to interdecadal changes linked to climate cycles like El Niño/Southern Oscillation, the North Atlantic Oscillation, and the Interdecadal Pacific Oscillation. A nonlinear trend of Paraná discharge is found and reveals a monotonic increase that could be attributed to global warming and anthropogenic land-cover changes. The spectral separation of modes obtained using CEEMDAN is cleaner than that achieved by the Ensemble Empirical Mode Decomposition technique. This makes it easier to interpret CEEMDAN results. Hence, CEEMDAN is proposed as a powerful method for extracting physically meaningful information from hydroclimatic data.
publishDate 2014
dc.date.none.fl_str_mv 2014-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/85993
Antico, Andres; Schlotthauer, Gaston; Torres, Maria Eugenia; Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin; American Geophysical Union; Journal of Geophysical Research; 119; 3; 2-2014; 1218-1233
2169-8996
CONICET Digital
CONICET
url http://hdl.handle.net/11336/85993
identifier_str_mv Antico, Andres; Schlotthauer, Gaston; Torres, Maria Eugenia; Analysis of hydroclimatic variability and trends using a novel empirical mode decomposition: Application to the Paraná River Basin; American Geophysical Union; Journal of Geophysical Research; 119; 3; 2-2014; 1218-1233
2169-8996
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1002/2013JD020420
info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2013JD020420
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Geophysical Union
publisher.none.fl_str_mv American Geophysical Union
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842269257781477376
score 13.13397

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