Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/8295
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dc.contributor.authorDikbaş, Fatih-
dc.contributor.authorFirat, M.-
dc.contributor.authorKoç, Abdullah Cem-
dc.contributor.authorGüngör, Mahmud-
dc.date.accessioned2019-08-16T12:38:12Z
dc.date.available2019-08-16T12:38:12Z
dc.date.issued2013-
dc.identifier.issn2193-567X-
dc.identifier.urihttps://hdl.handle.net/11499/8295-
dc.identifier.urihttps://doi.org/10.1007/s13369-013-0542-0-
dc.description.abstractThe major problem in ungauged basins for planning and management of water resources projects is to estimate the flood magnitudes and frequencies. The identification of hydrologically homogeneous regions is one of the most important steps of regional frequency analysis. In this study, K-Means clustering method is applied to classify the maximum annual flows and identify the hydrologically homogeneous groups. For this aim, the annual maximum river flows, coefficient of variation and skewness of annual maximum river flows, latitude and longitude at 117 stations operated by the General Directorate of Electrical Power Resources Survey and Development Administration throughout Turkey are used. The optimal number of groups was determined as seven. Regional homogeneity test based on L-moments method is applied to check homogeneity of these seven regions identified by clustering analysis. The results show that regions defined by K-Means method can be used for regional flood frequency analysis. According to the results, K-Means method is recommended to identify the hydrologically homogeneous regions for regional frequency analysis. © 2013 King Fahd University of Petroleum and Minerals.en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofArabian Journal for Science and Engineeringen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAnnual maximum flowen_US
dc.subjectCluster analysisen_US
dc.subjectHomogeneous regionen_US
dc.subjectK-Meansen_US
dc.titleDefining Homogeneous Regions for Streamflow Processes in Turkey Using a K-Means Clustering Methoden_US
dc.typeArticleen_US
dc.identifier.volume38en_US
dc.identifier.issue6en_US
dc.identifier.startpage1313
dc.identifier.startpage1313en_US
dc.identifier.endpage1319en_US
dc.authorid0000-0001-5779-2801-
dc.authorid0000-0001-7553-1373-
dc.authorid0000-0001-8019-1430-
dc.identifier.doi10.1007/s13369-013-0542-0-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-84878045493en_US
dc.identifier.wosWOS:000319075100003en_US
dc.identifier.scopusqualityQ3-
dc.ownerPamukkale University-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.dept10.02. Civil Engineering-
crisitem.author.dept10.02. Civil Engineering-
crisitem.author.dept10.02. Civil Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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