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...
| Autores: | , , , |
|---|---|
| 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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| 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 |
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Consejo Nacional de Ciencia Tecnología e Innovación |
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CONCYTEC |
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CONCYTEC |
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CONCYTEC-Institucional |
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CONCYTEC-Institucional |
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Repositorio Institucional CONCYTEC |
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repositorio@concytec.gob.pe |
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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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13.413352 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).