PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)

Descripción del Articulo

Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration d...

Descripción completa

Detalles Bibliográficos
Autores: Llauca H., Lavado-Casimiro W., Montesinos C., Santini W., Rau P.
Formato: artículo
Fecha de Publicación:2021
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/2343
Enlace del recurso:https://hdl.handle.net/20.500.12390/2343
https://doi.org/10.3390/w13081048
Nivel de acceso:acceso abierto
Materia:Water balance model
Fourier Amplitude Test
GR2M
Peru
PISCO product
http://purl.org/pe-repo/ocde/ford#1.05.11
id CONC_7c26ac84ff863e28144dc9a8e8327ef3
oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/2343
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
title PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
spellingShingle PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
Llauca H.
Water balance model
Fourier Amplitude Test
GR2M
Peru
PISCO product
http://purl.org/pe-repo/ocde/ford#1.05.11
title_short PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
title_full PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
title_fullStr PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
title_full_unstemmed PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
title_sort PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)
author Llauca H.
author_facet Llauca H.
Lavado-Casimiro W.
Montesinos C.
Santini W.
Rau P.
author_role author
author2 Lavado-Casimiro W.
Montesinos C.
Santini W.
Rau P.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Llauca H.
Lavado-Casimiro W.
Montesinos C.
Santini W.
Rau P.
dc.subject.none.fl_str_mv Water balance model
topic Water balance model
Fourier Amplitude Test
GR2M
Peru
PISCO product
http://purl.org/pe-repo/ocde/ford#1.05.11
dc.subject.es_PE.fl_str_mv Fourier Amplitude Test
GR2M
Peru
PISCO product
dc.subject.ocde.none.fl_str_mv http://purl.org/pe-repo/ocde/ford#1.05.11
description Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regional-ization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe efficiency (NSEsqrt ), and water balance error (WBE) metrics. The results show a very well representation of monthly discharges for a large portion of Peruvian sub-basins (KGE ? 0.75, NSEsqrt ? 0.65, and ?0.29 < WBE < 0.23). Finally, this study introduces a product of continuous monthly discharge rates in Peru, named PISCO_HyM_GR2M, to understand surface water balance in data-scarce sub-basins. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
publishDate 2021
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 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.citation.none.fl_str_mv Llauca, H., Lavado-Casimiro, W., Montesinos, C., Santini, W., & Rau, P. (2021). PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020). Water, 13(8), 1048. https://doi.org/10.3390/w13081048
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/2343
dc.identifier.doi.none.fl_str_mv https://doi.org/10.3390/w13081048
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85104678514
identifier_str_mv Llauca, H., Lavado-Casimiro, W., Montesinos, C., Santini, W., & Rau, P. (2021). PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020). Water, 13(8), 1048. https://doi.org/10.3390/w13081048
2-s2.0-85104678514
url https://hdl.handle.net/20.500.12390/2343
https://doi.org/10.3390/w13081048
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Water (Switzerland)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0/
dc.publisher.none.fl_str_mv MDPI AG
publisher.none.fl_str_mv MDPI AG
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
bitstream.url.fl_str_mv https://repositorio.concytec.gob.pe/bitstreams/4373a1c5-cfc3-46fa-be9b-eadd22e3f73b/download
https://repositorio.concytec.gob.pe/bitstreams/5b7fd9dc-7798-4955-b82d-492a22613e0c/download
https://repositorio.concytec.gob.pe/bitstreams/03cacf88-fe74-4060-9a56-bf99cacc1903/download
bitstream.checksum.fl_str_mv e27301528b155a3cc85e047713d42d8e
35d15d2add54760486404a7df77b3db2
1338bd85222330d6e48e9c2571365b85
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
_version_ 1844883043712499712
spelling Publicationrp05612600rp05614600rp05613600rp05615600rp05616600Llauca H.Lavado-Casimiro W.Montesinos C.Santini W.Rau P.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2021Llauca, H., Lavado-Casimiro, W., Montesinos, C., Santini, W., & Rau, P. (2021). PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020). Water, 13(8), 1048. https://doi.org/10.3390/w13081048https://hdl.handle.net/20.500.12390/2343https://doi.org/10.3390/w130810482-s2.0-85104678514Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regional-ization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe efficiency (NSEsqrt ), and water balance error (WBE) metrics. The results show a very well representation of monthly discharges for a large portion of Peruvian sub-basins (KGE ? 0.75, NSEsqrt ? 0.65, and ?0.29 &lt; WBE &lt; 0.23). Finally, this study introduces a product of continuous monthly discharge rates in Peru, named PISCO_HyM_GR2M, to understand surface water balance in data-scarce sub-basins. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengMDPI AGWater (Switzerland)info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/Water balance modelFourier Amplitude Test-1GR2M-1Peru-1PISCO product-1http://purl.org/pe-repo/ocde/ford#1.05.11-1PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)info:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTECORIGINALPISCO_HyM_GR2M - water-13-01048.pdfPISCO_HyM_GR2M - water-13-01048.pdfapplication/pdf6990156https://repositorio.concytec.gob.pe/bitstreams/4373a1c5-cfc3-46fa-be9b-eadd22e3f73b/downloade27301528b155a3cc85e047713d42d8eMD51TEXTPISCO_HyM_GR2M - water-13-01048.pdf.txtPISCO_HyM_GR2M - water-13-01048.pdf.txtExtracted texttext/plain61146https://repositorio.concytec.gob.pe/bitstreams/5b7fd9dc-7798-4955-b82d-492a22613e0c/download35d15d2add54760486404a7df77b3db2MD52THUMBNAILPISCO_HyM_GR2M - water-13-01048.pdf.jpgPISCO_HyM_GR2M - water-13-01048.pdf.jpgGenerated Thumbnailimage/jpeg5742https://repositorio.concytec.gob.pe/bitstreams/03cacf88-fe74-4060-9a56-bf99cacc1903/download1338bd85222330d6e48e9c2571365b85MD5320.500.12390/2343oai:repositorio.concytec.gob.pe:20.500.12390/23432025-01-19 22:01:06.859https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessopen 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##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="e7bab3af-d978-4cb8-95b9-64b6a67b4b4f"> <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>PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020)</Title> <PublishedIn> <Publication> <Title>Water (Switzerland)</Title> </Publication> </PublishedIn> <PublicationDate>2021</PublicationDate> <DOI>https://doi.org/10.3390/w13081048</DOI> <SCP-Number>2-s2.0-85104678514</SCP-Number> <Authors> <Author> <DisplayName>Llauca H.</DisplayName> <Person id="rp05612" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Lavado-Casimiro W.</DisplayName> <Person id="rp05614" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Montesinos C.</DisplayName> <Person id="rp05613" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Santini W.</DisplayName> <Person id="rp05615" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Rau P.</DisplayName> <Person id="rp05616" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>MDPI AG</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by/4.0/</License> <Keyword>Water balance model</Keyword> <Keyword>Fourier Amplitude Test</Keyword> <Keyword>GR2M</Keyword> <Keyword>Peru</Keyword> <Keyword>PISCO product</Keyword> <Abstract>Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regional-ization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe efficiency (NSEsqrt ), and water balance error (WBE) metrics. The results show a very well representation of monthly discharges for a large portion of Peruvian sub-basins (KGE ? 0.75, NSEsqrt ? 0.65, and ?0.29 &amp;lt; WBE &amp;lt; 0.23). Finally, this study introduces a product of continuous monthly discharge rates in Peru, named PISCO_HyM_GR2M, to understand surface water balance in data-scarce sub-basins. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.078757
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).