Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]

Descripción del Articulo

The extraordinary El Niño Costero of 2017 has affected the Peruvian coast, mainly in the Piura region, with the flooding of the Piura river, impacting rural and urban areas in the middle and lower basin. This paper analyses the situation from the perspective of hydrology. Since 2002, the basin has h...

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Detalles Bibliográficos
Autores: de Reyes M.F., Olivares A., Neyra D., Gonzalez I.
Formato: artículo
Fecha de Publicación:2020
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2593
Enlace del recurso:https://hdl.handle.net/20.500.12390/2593
https://doi.org/10.18687/LACCEI2020.1.1.276
Nivel de acceso:acceso abierto
Materia:Piura River
El Niño Costero 2017
Forecast
Maximum outflow
Multiple linear regression
http://purl.org/pe-repo/ocde/ford#1.05.06
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network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
title Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
spellingShingle Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
de Reyes M.F.
Piura River
El Niño Costero 2017
Forecast
Maximum outflow
Multiple linear regression
http://purl.org/pe-repo/ocde/ford#1.05.06
title_short Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
title_full Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
title_fullStr Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
title_full_unstemmed Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
title_sort Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]
author de Reyes M.F.
author_facet de Reyes M.F.
Olivares A.
Neyra D.
Gonzalez I.
author_role author
author2 Olivares A.
Neyra D.
Gonzalez I.
author2_role author
author
author
dc.contributor.author.fl_str_mv de Reyes M.F.
Olivares A.
Neyra D.
Gonzalez I.
dc.subject.none.fl_str_mv Piura River
topic Piura River
El Niño Costero 2017
Forecast
Maximum outflow
Multiple linear regression
http://purl.org/pe-repo/ocde/ford#1.05.06
dc.subject.es_PE.fl_str_mv El Niño Costero 2017
Forecast
Maximum outflow
Multiple linear regression
dc.subject.ocde.none.fl_str_mv http://purl.org/pe-repo/ocde/ford#1.05.06
description The extraordinary El Niño Costero of 2017 has affected the Peruvian coast, mainly in the Piura region, with the flooding of the Piura river, impacting rural and urban areas in the middle and lower basin. This paper analyses the situation from the perspective of hydrology. Since 2002, the basin has had an early warning system (EWS) made up of a hydrometeorological network and a forecast model, NAXOS. The EWS predicted flows at the Los Ejidos hydrometric station, located immediately upstream of Piura City. The hydrometeorological network has been gradually losing its operation and NAXOS has been left uncalibrated. Its inaccurate forecasts contributed to poor decision-making in disaster prevention in 2017. With the hydro-meteorological information of that year, three models of deterministic forecast of the flow in Los Ejidos have been adjusted by means of multiple linear regression, with 12 hours of anticipation for maximum events, starting from daily precipitation and upstream flows, coming from conventional and automatic stations. In moderate flows, it is even possible to have 18 hours of anticipation. The model provides an adequate approximation of the hydrographs of summer 2017. For the maximum flow, 3468 m3/s, forecast values were obtained with an error of less than 5%. The model has also been validated with data from the year 2019, obtaining satisfactory values. This model can be used by the authorities, in view of the possible occurrence of future events, for the timely adoption of preventive measures. © 2020 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/2593
dc.identifier.doi.none.fl_str_mv https://doi.org/10.18687/LACCEI2020.1.1.276
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85096749828
url https://hdl.handle.net/20.500.12390/2593
https://doi.org/10.18687/LACCEI2020.1.1.276
identifier_str_mv 2-s2.0-85096749828
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.none.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.publisher.none.fl_str_mv Latin American and Caribbean Consortium of Engineering Institutions
publisher.none.fl_str_mv Latin American and Caribbean Consortium of Engineering Institutions
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp06674600rp06673600rp06675600rp00748600de Reyes M.F.Olivares A.Neyra D.Gonzalez I.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2020https://hdl.handle.net/20.500.12390/2593https://doi.org/10.18687/LACCEI2020.1.1.2762-s2.0-85096749828The extraordinary El Niño Costero of 2017 has affected the Peruvian coast, mainly in the Piura region, with the flooding of the Piura river, impacting rural and urban areas in the middle and lower basin. This paper analyses the situation from the perspective of hydrology. Since 2002, the basin has had an early warning system (EWS) made up of a hydrometeorological network and a forecast model, NAXOS. The EWS predicted flows at the Los Ejidos hydrometric station, located immediately upstream of Piura City. The hydrometeorological network has been gradually losing its operation and NAXOS has been left uncalibrated. Its inaccurate forecasts contributed to poor decision-making in disaster prevention in 2017. With the hydro-meteorological information of that year, three models of deterministic forecast of the flow in Los Ejidos have been adjusted by means of multiple linear regression, with 12 hours of anticipation for maximum events, starting from daily precipitation and upstream flows, coming from conventional and automatic stations. In moderate flows, it is even possible to have 18 hours of anticipation. The model provides an adequate approximation of the hydrographs of summer 2017. For the maximum flow, 3468 m3/s, forecast values were obtained with an error of less than 5%. The model has also been validated with data from the year 2019, obtaining satisfactory values. This model can be used by the authorities, in view of the possible occurrence of future events, for the timely adoption of preventive measures. © 2020 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengLatin American and Caribbean Consortium of Engineering InstitutionsProceedings of the LACCEI international Multi-conference for Engineering, Education and Technologyinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/Piura RiverEl Niño Costero 2017-1Forecast-1Maximum outflow-1Multiple linear regression-1http://purl.org/pe-repo/ocde/ford#1.05.06-1Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]info:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2593oai:repositorio.concytec.gob.pe:20.500.12390/25932024-05-30 16:09:38.016https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="61957029-21dc-4d6a-b3b6-72b011bce5b3"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Forecast model of piura river flows calibrated with El Niño Costero 2017 [Pronóstico de caudales del río Piura calibrado con El Niño Costero 2017]</Title> <PublishedIn> <Publication> <Title>Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology</Title> </Publication> </PublishedIn> <PublicationDate>2020</PublicationDate> <DOI>https://doi.org/10.18687/LACCEI2020.1.1.276</DOI> <SCP-Number>2-s2.0-85096749828</SCP-Number> <Authors> <Author> <DisplayName>de Reyes M.F.</DisplayName> <Person id="rp06674" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Olivares A.</DisplayName> <Person id="rp06673" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Neyra D.</DisplayName> <Person id="rp06675" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Gonzalez I.</DisplayName> <Person id="rp00748" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Latin American and Caribbean Consortium of Engineering Institutions</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by-nc-nd/4.0/</License> <Keyword>Piura River</Keyword> <Keyword>El Niño Costero 2017</Keyword> <Keyword>Forecast</Keyword> <Keyword>Maximum outflow</Keyword> <Keyword>Multiple linear regression</Keyword> <Abstract>The extraordinary El Niño Costero of 2017 has affected the Peruvian coast, mainly in the Piura region, with the flooding of the Piura river, impacting rural and urban areas in the middle and lower basin. This paper analyses the situation from the perspective of hydrology. Since 2002, the basin has had an early warning system (EWS) made up of a hydrometeorological network and a forecast model, NAXOS. The EWS predicted flows at the Los Ejidos hydrometric station, located immediately upstream of Piura City. The hydrometeorological network has been gradually losing its operation and NAXOS has been left uncalibrated. Its inaccurate forecasts contributed to poor decision-making in disaster prevention in 2017. With the hydro-meteorological information of that year, three models of deterministic forecast of the flow in Los Ejidos have been adjusted by means of multiple linear regression, with 12 hours of anticipation for maximum events, starting from daily precipitation and upstream flows, coming from conventional and automatic stations. In moderate flows, it is even possible to have 18 hours of anticipation. The model provides an adequate approximation of the hydrographs of summer 2017. For the maximum flow, 3468 m3/s, forecast values were obtained with an error of less than 5%. The model has also been validated with data from the year 2019, obtaining satisfactory values. This model can be used by the authorities, in view of the possible occurrence of future events, for the timely adoption of preventive measures. © 2020 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
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