Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP

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Study region The Chancay-Huaral (CH) coastal river basin in the Lima Region, Peru, between the Pacific Ocean and the Andean Cordillera. Study focus Climate change impacts on annual and monthly discharges in the CH Basin are assessed for the future period 2051–2080. Hydrological modeling is sensitive...

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Detalles Bibliográficos
Autores: Olsson, T., Kämäräinen, M., Santos, Darwin, Seitola, T., Tuomenvirta, H., Haavisto, R., Lavado-Casimiro, W.
Formato: artículo
Fecha de Publicación:2017
Institución:Servicio Nacional de Meteorología e Hidrología del Perú
Repositorio:SENAMHI-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.senamhi.gob.pe:20.500.12542/46
Enlace del recurso:http://repositorio.senamhi.gob.pe/handle/20.500.12542/46
https://doi.org/ 10.1016/j.ejrh.2017.05.011
https://hdl.handle.net/20.500.12542/46
Nivel de acceso:acceso abierto
Materia:Cambio Climático
Cuencas
Hydrological Modeling
Peru
Quantile mapping
https://purl.org/pe-repo/ocde/ford#1.05.11
gestion de recursos hidricos de cuenca - Agua
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dc.title.en_US.fl_str_mv Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
title Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
spellingShingle Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
Olsson, T.
Cambio Climático
Cuencas
Hydrological Modeling
Peru
Quantile mapping
https://purl.org/pe-repo/ocde/ford#1.05.11
gestion de recursos hidricos de cuenca - Agua
title_short Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
title_full Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
title_fullStr Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
title_full_unstemmed Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
title_sort Downscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAP
author Olsson, T.
author_facet Olsson, T.
Kämäräinen, M.
Santos, Darwin
Seitola, T.
Tuomenvirta, H.
Haavisto, R.
Lavado-Casimiro, W.
author_role author
author2 Kämäräinen, M.
Santos, Darwin
Seitola, T.
Tuomenvirta, H.
Haavisto, R.
Lavado-Casimiro, W.
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Olsson, T.
Kämäräinen, M.
Santos, Darwin
Seitola, T.
Tuomenvirta, H.
Haavisto, R.
Lavado-Casimiro, W.
dc.subject.es_PE.fl_str_mv Cambio Climático
Cuencas
topic Cambio Climático
Cuencas
Hydrological Modeling
Peru
Quantile mapping
https://purl.org/pe-repo/ocde/ford#1.05.11
gestion de recursos hidricos de cuenca - Agua
dc.subject.en_US.fl_str_mv Hydrological Modeling
Peru
Quantile mapping
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#1.05.11
dc.subject.sinia.es_PE.fl_str_mv gestion de recursos hidricos de cuenca - Agua
description Study region The Chancay-Huaral (CH) coastal river basin in the Lima Region, Peru, between the Pacific Ocean and the Andean Cordillera. Study focus Climate change impacts on annual and monthly discharges in the CH Basin are assessed for the future period 2051–2080. Hydrological modeling is sensitive to biases in input variables. Therefore, bias-corrected time series of temperature and precipitation from 31 General Circulation Models (GCMs) with the emission scenarios RCP4.5 and RCP8.5 (Representative Concentration Pathways) were used as inputs for the Water Evaluation and Planning System model (WEAP). Bias correction and downscaling of the GCMs were implemented using a quantile mapping method. New hydrological insights for the region On average, GCMs indicate increased annual mean temperatures by 3.1 °C (RCP4.5) and by 4.3 °C (RCP8.5) and precipitation sum by 20% (RCP4.5) and by 28% (RCP8.5). With increasing total precipitation, river discharges are also found to increase, but the variability among the GCMs is considerable. The largest increases in monthly discharge are projected to occur in the wet season (November − April) − with up to 31% increase of December multi-model mean. Despite the larger annual discharge for the mean multi-model result, discharges in the dry season may decrease according to some GCMs, showing the need for an adapted future water management.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2019-07-20T01:09:01Z
dc.date.available.none.fl_str_mv 2019-07-20T01:09:01Z
dc.date.issued.fl_str_mv 2017-10
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
dc.type.sinia.es_PE.fl_str_mv text/publicacion cientifica
dc.type.version.none.fl_str_mv info:eu-repo/semantics/acceptedVersion
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status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv http://repositorio.senamhi.gob.pe/handle/20.500.12542/46
dc.identifier.isni.none.fl_str_mv 0000 0001 0746 0446
dc.identifier.doi.none.fl_str_mv https://doi.org/ 10.1016/j.ejrh.2017.05.011
dc.identifier.url.none.fl_str_mv https://hdl.handle.net/20.500.12542/46
http://repositorio.senamhi.gob.pe/handle/20.500.12542/46
url http://repositorio.senamhi.gob.pe/handle/20.500.12542/46
https://doi.org/ 10.1016/j.ejrh.2017.05.011
https://hdl.handle.net/20.500.12542/46
identifier_str_mv 0000 0001 0746 0446
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv urn:issn:2214-5818
dc.rights.es_PE.fl_str_mv info:eu-repo/semantics/openAccess
Reconocimiento - No comercial - Compartir igual (CC BY-NC-SA)
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eu_rights_str_mv openAccess
rights_invalid_str_mv Reconocimiento - No comercial - Compartir igual (CC BY-NC-SA)
https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.es_PE.fl_str_mv application/pdf
dc.publisher.es_PE.fl_str_mv Elsevier B.V.
dc.source.es_PE.fl_str_mv Servicio Nacional de Meteorología e Hidrología del Perú
Repositorio Institucional - SENAMHI
dc.source.none.fl_str_mv reponame:SENAMHI-Institucional
instname:Servicio Nacional de Meteorología e Hidrología del Perú
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instname_str Servicio Nacional de Meteorología e Hidrología del Perú
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dc.source.volume.es_PE.fl_str_mv 13
dc.source.initialpage.es_PE.fl_str_mv 26
dc.source.endpage.es_PE.fl_str_mv 42
dc.source.journal.es_PE.fl_str_mv Journal of Hydrology: Regional Studies
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spelling Olsson, T.Kämäräinen, M.Santos, DarwinSeitola, T.Tuomenvirta, H.Haavisto, R.Lavado-Casimiro, W.2019-07-20T01:09:01Z2019-07-20T01:09:01Z2017-10http://repositorio.senamhi.gob.pe/handle/20.500.12542/460000 0001 0746 0446https://doi.org/ 10.1016/j.ejrh.2017.05.011https://hdl.handle.net/20.500.12542/46http://repositorio.senamhi.gob.pe/handle/20.500.12542/46Study region The Chancay-Huaral (CH) coastal river basin in the Lima Region, Peru, between the Pacific Ocean and the Andean Cordillera. Study focus Climate change impacts on annual and monthly discharges in the CH Basin are assessed for the future period 2051–2080. Hydrological modeling is sensitive to biases in input variables. Therefore, bias-corrected time series of temperature and precipitation from 31 General Circulation Models (GCMs) with the emission scenarios RCP4.5 and RCP8.5 (Representative Concentration Pathways) were used as inputs for the Water Evaluation and Planning System model (WEAP). Bias correction and downscaling of the GCMs were implemented using a quantile mapping method. New hydrological insights for the region On average, GCMs indicate increased annual mean temperatures by 3.1 °C (RCP4.5) and by 4.3 °C (RCP8.5) and precipitation sum by 20% (RCP4.5) and by 28% (RCP8.5). With increasing total precipitation, river discharges are also found to increase, but the variability among the GCMs is considerable. The largest increases in monthly discharge are projected to occur in the wet season (November − April) − with up to 31% increase of December multi-model mean. Despite the larger annual discharge for the mean multi-model result, discharges in the dry season may decrease according to some GCMs, showing the need for an adapted future water management.Por paresThis work was supported by the Finnish Academy through funding of the AquaFutura project (grant decision 250529 ) and by the Fortum Foundation (grant number 201500127 ). We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. The U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provided coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank the editor, Professor Patrick Willems, and four anonymous reviewers for providing valuable comments to improve considerably the manuscript.application/pdfengElsevier B.V.urn:issn:2214-5818info:eu-repo/semantics/openAccessReconocimiento - No comercial - Compartir igual (CC BY-NC-SA)https://creativecommons.org/licenses/by-nc-sa/4.0/Servicio Nacional de Meteorología e Hidrología del PerúRepositorio Institucional - SENAMHI132642Journal of Hydrology: Regional Studiesreponame:SENAMHI-Institucionalinstname:Servicio Nacional de Meteorología e Hidrología del Perúinstacron:SENAMHICambio ClimáticoCuencasHydrological ModelingPeruQuantile mappinghttps://purl.org/pe-repo/ocde/ford#1.05.11gestion de recursos hidricos de cuenca - AguaDownscaling climate projections for the Peruvian coastal Chancay-Huaral Basin to support river discharge modeling with WEAPinfo:eu-repo/semantics/articletext/publicacion cientificainfo:eu-repo/semantics/acceptedVersionORIGINALOlsson-2017-Downscaling.pdfOlsson-2017-Downscaling.pdfapplication/pdf1648358http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/46/1/Olsson-2017-Downscaling.pdf625a1684ae93d293bcc7c856a718236dMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81037http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/46/2/license_rdf80294ba9ff4c5b4f07812ee200fbc42fMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/46/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53TEXTOlsson-2017-Downscaling.pdf.txtOlsson-2017-Downscaling.pdf.txtExtracted texttext/plain81210http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/46/4/Olsson-2017-Downscaling.pdf.txtbd4ab474a4a8f86976af49dc9cfa9556MD54THUMBNAILOlsson-2017-Downscaling.pdf.jpgOlsson-2017-Downscaling.pdf.jpgGenerated Thumbnailimage/jpeg7339http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/46/5/Olsson-2017-Downscaling.pdf.jpg41edd800b75e582ff9a85d479c531969MD5520.500.12542/46oai:repositorio.senamhi.gob.pe:20.500.12542/462025-10-23 17:05:04.387Repositorio Institucional SENAMHIrepositorio@senamhi.gob.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