Classification of precipitation series using fuzzy cluster method

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dc.authoridFIRAT, MAHMUT/0000-0002-8010-9289
dc.authoridGÜNGÖR, Mahmud/0000-0001-8019-1430
dc.authoridDIKBAS, Fatih/0000-0001-5779-2801
dc.authoridKoc, Abdullah Cem/0000-0001-7553-1373
dc.authorwosidGüngör, Mahmud/AAA-8524-2021
dc.authorwosidFIRAT, MAHMUT/ABG-7962-2020
dc.authorwosidDİKBAŞ, Fatih/HJP-4307-2023
dc.authorwosidKoç, Abdullah Cem/D-1451-2016
dc.authorwosidGÜNGÖR, Mahmud/AAB-3534-2020
dc.contributor.authorDikbas, Fatih
dc.contributor.authorFirat, Mahmut
dc.contributor.authorKoc, A. Cem
dc.contributor.authorGungor, Mahmud
dc.date.accessioned2024-08-04T20:36:01Z
dc.date.available2024-08-04T20:36:01Z
dc.date.issued2012
dc.departmentİnönü Üniversitesien_US
dc.description.abstractThe identification of hydrologically homogeneous regions is one of the most important steps of regional frequency analysis. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close regions or stations. In this study, fuzzy cluster method (Fuzzy C-Means: FCM) is applied to classify the precipitation series and identify the hydrologically homogeneous groups. The choice of appropriate cluster method and the variables that will be used according to the data of the basin is also very important. In the context of this study, total precipitation data of stations operated by National Meteorology Works (DMI) in Turkish basins for cluster analysis are used. The optimal number of groups is determined as six, based on different performance evaluation indexes. Regional homogeneity tests based on L-moments method are applied to check homogeneity of these six regions identified by cluster analysis. Regional homogeneity test results show that regions defined by FCM method are sufficiently homogeneous for regional frequency analysis. According to the results, FCM method is recommended for classifying the precipitation series and for identifying the hydrologically homogenous regions. Copyright (c) 2011 Royal Meteorological Societyen_US
dc.description.sponsorshipTUBITAK (Turkish National Science Foundation) [107Y318]en_US
dc.description.sponsorshipThis research was supported by TUBITAK (Turkish National Science Foundation) under the Project Number 107Y318. The authors are grateful to the Editor and Anonymous Reviewers for their helpful and constructive comments on an earlier draft of this paper.en_US
dc.identifier.doi10.1002/joc.2350
dc.identifier.endpage1603en_US
dc.identifier.issn0899-8418
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-84864145708en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1596en_US
dc.identifier.urihttps://doi.org/10.1002/joc.2350
dc.identifier.urihttps://hdl.handle.net/11616/95730
dc.identifier.volume32en_US
dc.identifier.wosWOS:000306656700013en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWiley-Blackwellen_US
dc.relation.ispartofInternational Journal of Climatologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectcluster analysisen_US
dc.subjectclassificationen_US
dc.subjectfuzzy clusteren_US
dc.subjectannual total precipitationen_US
dc.subjecthydrologically homogeneous regionen_US
dc.titleClassification of precipitation series using fuzzy cluster methoden_US
dc.typeArticleen_US

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