Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador

Descripción del Articulo

Satellites are an alternative source of rainfall data used as input to hydrological models in poorly gauged or ungauged regions. They are also useful in regions with highly heterogeneous precipitation, such as the tropical Andes. This paper evaluates three satellite precipitation datasets (TMPA, CMO...

Descripción completa

Detalles Bibliográficos
Autores: Zubieta, R., Getirana, A., Espinoza, J.C., Lavado-Casimiro, W.
Formato: artículo
Fecha de Publicación:2015
Institución:Servicio Nacional de Meteorología e Hidrología del Perú
Repositorio:SENAMHI-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.senamhi.gob.pe:20.500.12542/54
Enlace del recurso:https://hdl.handle.net/20.500.12542/54
https://doi.org/10.1016/j.jhydrol.2015.06.064
Nivel de acceso:acceso cerrado
Materia:Hydrological modeling
Precipitation dataset
Satellite
Amazon Basin
id SEAM_ea19e7e42b9073a1185424e27786826b
oai_identifier_str oai:repositorio.senamhi.gob.pe:20.500.12542/54
network_acronym_str SEAM
network_name_str SENAMHI-Institucional
repository_id_str 4818
dc.title.en_US.fl_str_mv Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
title Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
spellingShingle Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
Zubieta, R.
Hydrological modeling
Precipitation dataset
Satellite
Amazon Basin
title_short Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
title_full Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
title_fullStr Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
title_full_unstemmed Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
title_sort Impacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuador
author Zubieta, R.
author_facet Zubieta, R.
Getirana, A.
Espinoza, J.C.
Lavado-Casimiro, W.
author_role author
author2 Getirana, A.
Espinoza, J.C.
Lavado-Casimiro, W.
author2_role author
author
author
dc.contributor.author.fl_str_mv Zubieta, R.
Getirana, A.
Espinoza, J.C.
Lavado-Casimiro, W.
dc.subject.en_US.fl_str_mv Hydrological modeling
Precipitation dataset
Satellite
Amazon Basin
topic Hydrological modeling
Precipitation dataset
Satellite
Amazon Basin
description Satellites are an alternative source of rainfall data used as input to hydrological models in poorly gauged or ungauged regions. They are also useful in regions with highly heterogeneous precipitation, such as the tropical Andes. This paper evaluates three satellite precipitation datasets (TMPA, CMORPH, PERSIANN), as well as a dataset based only on rain gauge data (HYBAM), and their impacts on the water balance of the Western Amazon basin, a region where hydrological modeling and hydrological forecasting are poorly developed. These datasets were used as inputs in the MGB-IPH hydrological model to simulate streamflows for the 2003-2009 period. The impacts of precipitation on model parameterization and outputs were evaluated in two calibration experiments. In Experiment 1, parameter sets were separately defined for each catchment; in Experiment 2, a single parameter set was defined for the entire basin. TMPA shows overestimated precipitation over the northern region, while CMORPH and PERSIANN significantly underestimate rainfall in the same that region and along the Andes. TMPA and CMORPH lead to similar estimates of mean evapotranspiration (~2. mm/day) for different regions along the entire basin, while PERSIANN is the least accurate (~0.5. mm/day). Overall, better scores for streamflow simulations are obtained with Experiment 1 forced by HYBAM and TMPA. Nevertheless, results using the three satellite datasets indicate inter-basin differences, low performance in the northern and high in the southern regions. Low model performances are mainly related to scale issues and forcing errors in small basins over regions that present very low rainfall seasonality.
publishDate 2015
dc.date.accessioned.none.fl_str_mv 2019-07-21T18:17:25Z
dc.date.available.none.fl_str_mv 2019-07-21T18:17:25Z
dc.date.issued.fl_str_mv 2015-09
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/20.500.12542/54
dc.identifier.isni.none.fl_str_mv 0000 0001 0746 0446
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.jhydrol.2015.06.064
url https://hdl.handle.net/20.500.12542/54
https://doi.org/10.1016/j.jhydrol.2015.06.064
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:0022-1694
dc.rights.none.fl_str_mv info:eu-repo/semantics/closedAccess
dc.rights.*.fl_str_mv Atribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América
dc.rights.uri.*.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 Elsevier
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.volume.es_PE.fl_str_mv 528
dc.source.initialpage.es_PE.fl_str_mv 599
dc.source.endpage.es_PE.fl_str_mv 612
dc.source.journal.es_PE.fl_str_mv Journal of Hydrology
bitstream.url.fl_str_mv http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/54/2/license.txt
bitstream.checksum.fl_str_mv 8a4605be74aa9ea9d79846c1fba20a33
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio Institucional SENAMHI
repository.mail.fl_str_mv repositorio@senamhi.gob.pe
_version_ 1770866393953075200
spelling Zubieta, R.Getirana, A.Espinoza, J.C.Lavado-Casimiro, W.2019-07-21T18:17:25Z2019-07-21T18:17:25Z2015-09https://hdl.handle.net/20.500.12542/540000 0001 0746 0446https://doi.org/10.1016/j.jhydrol.2015.06.064Satellites are an alternative source of rainfall data used as input to hydrological models in poorly gauged or ungauged regions. They are also useful in regions with highly heterogeneous precipitation, such as the tropical Andes. This paper evaluates three satellite precipitation datasets (TMPA, CMORPH, PERSIANN), as well as a dataset based only on rain gauge data (HYBAM), and their impacts on the water balance of the Western Amazon basin, a region where hydrological modeling and hydrological forecasting are poorly developed. These datasets were used as inputs in the MGB-IPH hydrological model to simulate streamflows for the 2003-2009 period. The impacts of precipitation on model parameterization and outputs were evaluated in two calibration experiments. In Experiment 1, parameter sets were separately defined for each catchment; in Experiment 2, a single parameter set was defined for the entire basin. TMPA shows overestimated precipitation over the northern region, while CMORPH and PERSIANN significantly underestimate rainfall in the same that region and along the Andes. TMPA and CMORPH lead to similar estimates of mean evapotranspiration (~2. mm/day) for different regions along the entire basin, while PERSIANN is the least accurate (~0.5. mm/day). Overall, better scores for streamflow simulations are obtained with Experiment 1 forced by HYBAM and TMPA. Nevertheless, results using the three satellite datasets indicate inter-basin differences, low performance in the northern and high in the southern regions. Low model performances are mainly related to scale issues and forcing errors in small basins over regions that present very low rainfall seasonality.Por paresapplication/pdfengElsevierurn:issn:0022-1694info: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 - SENAMHI528599612Journal of Hydrologyreponame:SENAMHI-Institucionalinstname:Servicio Nacional de Meteorología e Hidrología del Perúinstacron:SENAMHIHydrological modelingPrecipitation datasetSatelliteAmazon BasinImpacts of satellite-based precipitation datasets on rainfall-runoff modeling of the Western Amazon basin of Peru and Ecuadorinfo:eu-repo/semantics/articleLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://repositorio.senamhi.gob.pe/bitstream/20.500.12542/54/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5220.500.12542/54oai:repositorio.senamhi.gob.pe:20.500.12542/542022-03-18 10:18:26.612Repositorio Institucional SENAMHIrepositorio@senamhi.gob.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
score 13.959468
Nota importante:
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).