Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin

Autores
Meis, Melanie; Llano, Maria Paula; Rodriguez, Daniela Andrea
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discharge and the seasonal climatic index NIÑO 3.4. We start by estimating the phase shift between the index and mean seasonal (trimester) discharge values. Based on this result, we align the series and use the copula method to fit a joint distribution. We end up with a model that is particularly useful for quantifying the probability of occurrence of extreme events and monitoring their return periods. As a final step, we generate predictions and validate the model by splitting the series into training and test datasets. We develop a simple effective model for monitoring discharges using the El Niño Southern Oscillation (ENSO) index.
Fil: Meis, Melanie. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Llano, Maria Paula. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Materia
ENSO
EXTREME EVENTS
JOINT PROBABILITY
LA PLATA BASIN
MONITORING
RETURN PERIOD
VALIDATION
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:11336/144406
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata BasinMeis, MelanieLlano, Maria PaulaRodriguez, Daniela AndreaENSOEXTREME EVENTSJOINT PROBABILITYLA PLATA BASINMONITORINGRETURN PERIODVALIDATIONhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discharge and the seasonal climatic index NIÑO 3.4. We start by estimating the phase shift between the index and mean seasonal (trimester) discharge values. Based on this result, we align the series and use the copula method to fit a joint distribution. We end up with a model that is particularly useful for quantifying the probability of occurrence of extreme events and monitoring their return periods. As a final step, we generate predictions and validate the model by splitting the series into training and test datasets. We develop a simple effective model for monitoring discharges using the El Niño Southern Oscillation (ENSO) index.Fil: Meis, Melanie. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Llano, Maria Paula. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaTaylor & Francis2020-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/144406Meis, Melanie; Llano, Maria Paula; Rodriguez, Daniela Andrea; Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin; Taylor & Francis; Hydrological Sciences Journal-Journal Des Sciences Hydrologiques; 11-2020; 1-600262-6667CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/02626667.2020.1843655info:eu-repo/semantics/altIdentifier/doi/10.1080/02626667.2020.1843655info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:51:14Zoai:ri.conicet.gov.ar:11336/144406instacron: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 09:51:15.217CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
title Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
spellingShingle Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
Meis, Melanie
ENSO
EXTREME EVENTS
JOINT PROBABILITY
LA PLATA BASIN
MONITORING
RETURN PERIOD
VALIDATION
title_short Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
title_full Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
title_fullStr Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
title_full_unstemmed Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
title_sort Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
dc.creator.none.fl_str_mv Meis, Melanie
Llano, Maria Paula
Rodriguez, Daniela Andrea
author Meis, Melanie
author_facet Meis, Melanie
Llano, Maria Paula
Rodriguez, Daniela Andrea
author_role author
author2 Llano, Maria Paula
Rodriguez, Daniela Andrea
author2_role author
author
dc.subject.none.fl_str_mv ENSO
EXTREME EVENTS
JOINT PROBABILITY
LA PLATA BASIN
MONITORING
RETURN PERIOD
VALIDATION
topic ENSO
EXTREME EVENTS
JOINT PROBABILITY
LA PLATA BASIN
MONITORING
RETURN PERIOD
VALIDATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discharge and the seasonal climatic index NIÑO 3.4. We start by estimating the phase shift between the index and mean seasonal (trimester) discharge values. Based on this result, we align the series and use the copula method to fit a joint distribution. We end up with a model that is particularly useful for quantifying the probability of occurrence of extreme events and monitoring their return periods. As a final step, we generate predictions and validate the model by splitting the series into training and test datasets. We develop a simple effective model for monitoring discharges using the El Niño Southern Oscillation (ENSO) index.
Fil: Meis, Melanie. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Llano, Maria Paula. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rodriguez, Daniela Andrea. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
description Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discharge and the seasonal climatic index NIÑO 3.4. We start by estimating the phase shift between the index and mean seasonal (trimester) discharge values. Based on this result, we align the series and use the copula method to fit a joint distribution. We end up with a model that is particularly useful for quantifying the probability of occurrence of extreme events and monitoring their return periods. As a final step, we generate predictions and validate the model by splitting the series into training and test datasets. We develop a simple effective model for monitoring discharges using the El Niño Southern Oscillation (ENSO) index.
publishDate 2020
dc.date.none.fl_str_mv 2020-11
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/11336/144406
Meis, Melanie; Llano, Maria Paula; Rodriguez, Daniela Andrea; Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin; Taylor & Francis; Hydrological Sciences Journal-Journal Des Sciences Hydrologiques; 11-2020; 1-60
0262-6667
CONICET Digital
CONICET
url http://hdl.handle.net/11336/144406
identifier_str_mv Meis, Melanie; Llano, Maria Paula; Rodriguez, Daniela Andrea; Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin; Taylor & Francis; Hydrological Sciences Journal-Journal Des Sciences Hydrologiques; 11-2020; 1-60
0262-6667
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/full/10.1080/02626667.2020.1843655
info:eu-repo/semantics/altIdentifier/doi/10.1080/02626667.2020.1843655
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
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
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
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score 13.13397

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