Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.4901
DC FieldValueLanguage
dc.contributor.authorKhoshnazar, Ali-
dc.contributor.authorCorzo Perez, Gerald A.-
dc.contributor.authorDiaz, Vitali-
dc.contributor.authorAminzadeh, Milad-
dc.contributor.authorCerón Pineda, Roberto Adolfo-
dc.date.accessioned2023-01-30T10:04:15Z-
dc.date.available2023-01-30T10:04:15Z-
dc.date.issued2022-10-27-
dc.identifier.citationHydrology Research 53 (11): 1393-1413 (2022-11-01)de_DE
dc.identifier.issn0029-1277de_DE
dc.identifier.urihttp://hdl.handle.net/11420/14691-
dc.description.abstractDrought assessment and monitoring are essential for its proper management. Drought indices play a fundamental role in this. This research introduces the Wet-environment Evapotranspiration and Precipitation Standardized Index (WEPSI) for drought assessment and monitoring. WEPSI incorporates water supply and demand into the drought index calculation. WEPSI considers precipitation (P) for water supply and wet-environment evapotranspiration (ETw) for water demand. We use an asymmetric complementary relationship to calculate ETw with actual (ETa) and potential evapotranspiration (ETp). WEPSI is tested in the transboundary Lempa River basin in the Central American dry corridor. ETw is estimated based on evapotranspiration data calculated using the Water Evaluation And Planning (WEAP) system hydrological model. To investigate the performance of WEPSI, we compare it with two well-known meteorological indices (Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index), together with a hydrological index (Standardized Runoff Index), in terms of statistical metrics and mutual information (MI). We compare WEPSI-derived droughts and historical information, including crop production, cereal yield, and the Oceanic Nino Index (ONI). Results show WEPSI has the highest correlation and MI, and the lowest deviation. It is consistent with the records of the crop production index, cereal yield, and the ONI. Findings show that WEPSI can be used for agricultural drought assessments.en
dc.language.isoende_DE
dc.publisherIWA Publ.de_DE
dc.relation.ispartofHydrology researchde_DE
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/de_DE
dc.subjectdrought indexde_DE
dc.subjectLempa River basinde_DE
dc.subjectmutual informationde_DE
dc.subjectWEAPde_DE
dc.subjectWEPSIde_DE
dc.subjectwet-environment evapotranspirationde_DE
dc.subject.ddc004: Informatikde_DE
dc.subject.ddc550: Geowissenschaftende_DE
dc.titleWet-environment Evapotranspiration and Precipitation Standardized Index (WEPSI) for drought assessment and monitoringde_DE
dc.typeArticlede_DE
dc.identifier.doi10.15480/882.4901-
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.0210085-
tuhh.oai.showtruede_DE
tuhh.abstract.englishDrought assessment and monitoring are essential for its proper management. Drought indices play a fundamental role in this. This research introduces the Wet-environment Evapotranspiration and Precipitation Standardized Index (WEPSI) for drought assessment and monitoring. WEPSI incorporates water supply and demand into the drought index calculation. WEPSI considers precipitation (P) for water supply and wet-environment evapotranspiration (ETw) for water demand. We use an asymmetric complementary relationship to calculate ETw with actual (ETa) and potential evapotranspiration (ETp). WEPSI is tested in the transboundary Lempa River basin in the Central American dry corridor. ETw is estimated based on evapotranspiration data calculated using the Water Evaluation And Planning (WEAP) system hydrological model. To investigate the performance of WEPSI, we compare it with two well-known meteorological indices (Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index), together with a hydrological index (Standardized Runoff Index), in terms of statistical metrics and mutual information (MI). We compare WEPSI-derived droughts and historical information, including crop production, cereal yield, and the Oceanic Nino Index (ONI). Results show WEPSI has the highest correlation and MI, and the lowest deviation. It is consistent with the records of the crop production index, cereal yield, and the ONI. Findings show that WEPSI can be used for agricultural drought assessments.de_DE
tuhh.publisher.doi10.2166/nh.2022.062-
tuhh.publication.instituteGeohydroinformatik B-9de_DE
tuhh.identifier.doi10.15480/882.4901-
tuhh.type.opus(wissenschaftlicher) Artikel-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.issue11de_DE
tuhh.container.volume53de_DE
tuhh.container.startpage1393de_DE
tuhh.container.endpage1413de_DE
dc.rights.nationallicensefalsede_DE
dc.identifier.scopus2-s2.0-85146366149de_DE
local.status.inpressfalsede_DE
local.type.versionpublishedVersionde_DE
datacite.resourceTypeArticle-
datacite.resourceTypeGeneralJournalArticle-
item.grantfulltextopen-
item.creatorGNDKhoshnazar, Ali-
item.creatorGNDCorzo Perez, Gerald A.-
item.creatorGNDDiaz, Vitali-
item.creatorGNDAminzadeh, Milad-
item.creatorGNDCerón Pineda, Roberto Adolfo-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairetypeArticle-
item.mappedtypeArticle-
item.creatorOrcidKhoshnazar, Ali-
item.creatorOrcidCorzo Perez, Gerald A.-
item.creatorOrcidDiaz, Vitali-
item.creatorOrcidAminzadeh, Milad-
item.creatorOrcidCerón Pineda, Roberto Adolfo-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
crisitem.author.deptGeohydroinformatik B-9-
crisitem.author.orcid0000-0002-7122-6432-
crisitem.author.orcid0000-0002-2773-7817-
crisitem.author.orcid0000-0002-5502-4099-
crisitem.author.orcid0000-0002-0074-3600-
crisitem.author.parentorgStudiendekanat Bauwesen (B)-
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