Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru

Descripción del Articulo

The present study investigates the application of the index flood L-moments-based regional frequency analysis procedure (RFA-LM) to the annual maximum 24-h rainfall (AM) of 33 rainfall gauge stations (RGs) to estimate rainfall quantiles at the Titicaca Lake drainage (TL). The study region was chosen...

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Detalles Bibliográficos
Autores: Fernández Palomino, Carlos, 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:20.500.12542/47
Enlace del recurso:https://hdl.handle.net/20.500.12542/47
https://doi.org/10.1007/s00704-016-1845-3
Nivel de acceso:acceso cerrado
Materia:Drainage
Flood
Interpolation
Kriging
Precipitation assessment
Precipitation intensity
Raingauge
Lake Titicaca
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oai_identifier_str oai:repositorio.senamhi.gob.pe:20.500.12542/47
network_acronym_str SEAM
network_name_str SENAMHI-Institucional
repository_id_str 4818
dc.title.en_US.fl_str_mv Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
title Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
spellingShingle Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
Fernández Palomino, Carlos
Drainage
Flood
Interpolation
Kriging
Precipitation assessment
Precipitation intensity
Raingauge
Lake Titicaca
title_short Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
title_full Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
title_fullStr Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
title_full_unstemmed Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
title_sort Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru
author Fernández Palomino, Carlos
author_facet Fernández Palomino, Carlos
Lavado-Casimiro, W.
author_role author
author2 Lavado-Casimiro, W.
author2_role author
dc.contributor.author.fl_str_mv Fernández Palomino, Carlos
Lavado-Casimiro, W.
dc.subject.en_US.fl_str_mv Drainage
Flood
Interpolation
Kriging
Precipitation assessment
Precipitation intensity
Raingauge
Lake Titicaca
topic Drainage
Flood
Interpolation
Kriging
Precipitation assessment
Precipitation intensity
Raingauge
Lake Titicaca
description The present study investigates the application of the index flood L-moments-based regional frequency analysis procedure (RFA-LM) to the annual maximum 24-h rainfall (AM) of 33 rainfall gauge stations (RGs) to estimate rainfall quantiles at the Titicaca Lake drainage (TL). The study region was chosen because it is characterised by common floods that affect agricultural production and infrastructure. First, detailed quality analyses and verification of the RFA-LM assumptions were conducted. For this purpose, different tests for outlier verification, homogeneity, stationarity, and serial independence were employed. Then, the application of RFA-LM procedure allowed us to consider the TL as a single, hydrologically homogeneous region, in terms of its maximum rainfall frequency. That is, this region can be modelled by a generalised normal (GNO) distribution, chosen according to the Z test for goodness-of-fit, L-moments (LM) ratio diagram, and an additional evaluation of the precision of the regional growth curve. Due to the low density of RG in the TL, it was important to produce maps of the AM design quantiles estimated using RFA-LM. Therefore, the ordinary Kriging interpolation (OK) technique was used. These maps will be a useful tool for determining the different AM quantiles at any point of interest for hydrologists in the region.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2019-07-20T01:25:50Z
dc.date.available.none.fl_str_mv 2019-07-20T01:25:50Z
dc.date.issued.fl_str_mv 2017-08
dc.type.en_US.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12542/47
dc.identifier.isni.none.fl_str_mv 0000 0001 0746 0446
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/s00704-016-1845-3
url https://hdl.handle.net/20.500.12542/47
https://doi.org/10.1007/s00704-016-1845-3
identifier_str_mv 0000 0001 0746 0446
dc.language.iso.en_US.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv urn:issn:0177-798X
dc.rights.none.fl_str_mv info:eu-repo/semantics/closedAccess
Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/3.0/us/
eu_rights_str_mv closedAccess
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
http://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.format.none.fl_str_mv application/pdf
dc.publisher.en_US.fl_str_mv Springer-Verlag Wien
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
instacron:SENAMHI
instname_str Servicio Nacional de Meteorología e Hidrología del Perú
instacron_str SENAMHI
institution SENAMHI
reponame_str SENAMHI-Institucional
collection SENAMHI-Institucional
dc.source.issue.es_PE.fl_str_mv 129
dc.source.initialpage.es_PE.fl_str_mv 1295
dc.source.endpage.es_PE.fl_str_mv 1307
dc.source.journal.es_PE.fl_str_mv Theoretical and Applied Climatology
bitstream.url.fl_str_mv http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/47/2/license.txt
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spelling Fernández Palomino, CarlosLavado-Casimiro, W.2019-07-20T01:25:50Z2019-07-20T01:25:50Z2017-08https://hdl.handle.net/20.500.12542/470000 0001 0746 0446https://doi.org/10.1007/s00704-016-1845-3The present study investigates the application of the index flood L-moments-based regional frequency analysis procedure (RFA-LM) to the annual maximum 24-h rainfall (AM) of 33 rainfall gauge stations (RGs) to estimate rainfall quantiles at the Titicaca Lake drainage (TL). The study region was chosen because it is characterised by common floods that affect agricultural production and infrastructure. First, detailed quality analyses and verification of the RFA-LM assumptions were conducted. For this purpose, different tests for outlier verification, homogeneity, stationarity, and serial independence were employed. Then, the application of RFA-LM procedure allowed us to consider the TL as a single, hydrologically homogeneous region, in terms of its maximum rainfall frequency. That is, this region can be modelled by a generalised normal (GNO) distribution, chosen according to the Z test for goodness-of-fit, L-moments (LM) ratio diagram, and an additional evaluation of the precision of the regional growth curve. Due to the low density of RG in the TL, it was important to produce maps of the AM design quantiles estimated using RFA-LM. Therefore, the ordinary Kriging interpolation (OK) technique was used. These maps will be a useful tool for determining the different AM quantiles at any point of interest for hydrologists in the region.Por paresapplication/pdfengSpringer-Verlag Wienurn:issn:0177-798Xinfo:eu-repo/semantics/closedAccessAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de Américahttp://creativecommons.org/licenses/by-nc-nd/3.0/us/Servicio Nacional de Meteorología e Hidrología del PerúRepositorio Institucional - SENAMHI12912951307Theoretical and Applied Climatologyreponame:SENAMHI-Institucionalinstname:Servicio Nacional de Meteorología e Hidrología del Perúinstacron:SENAMHIDrainageFloodInterpolationKrigingPrecipitation assessmentPrecipitation intensityRaingaugeLake TiticacaRegional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peruinfo:eu-repo/semantics/articleLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/47/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5220.500.12542/47oai:repositorio.senamhi.gob.pe:20.500.12542/472022-01-11 19:13:01.286Repositorio Institucional SENAMHIrepositorio@senamhi.gob.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