ENSO MODULATIONS ON STREAMFLOW CHARACTERISTICS

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dc.contributor.authorMarti, Ali Ihsan
dc.contributor.authorYerdelen, Cahit
dc.contributor.authorKahya, Ercan
dc.date.accessioned2020-03-26T17:48:28Z
dc.date.available2020-03-26T17:48:28Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractEl Nino Southern Oscillation (ENSO) has been linked to climate and hydrologic anomalies throughout the world. This paper presents how ENSO modulates the basic statistical characteristics of streamflow time series that is assumed to be affected by ENSO. For this we first considered hypothetical series that can be obtained from the original series at each station by assuming non-occurrence of El Nino events in the past. Instead those data belonging to El Nino years were simulated by the Radial Based Artificial Neural Network (RBANN) method. Then we compared these data to the original series to see a significant difference with respect to their basic statistical characteristics (i.e., variance, mean and autocorrelation parameters). Various statistical hypothesis testing methods were used for four different scenarios. Consequently if there exist a significant difference, then it can be inferred that the ENSO events modulate the major statistical characteristics of streamflow series concerned. The results of this research were in good agreement with those of the previous studies.en_US
dc.description.sponsorshipTUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [YDABAG 102Y146]en_US
dc.description.sponsorshipWe appreciate Dr. Karabork who helped us conduct the hypothesis testing and reviewed the manuscript. This work was supported by the TUBITAK under research project no: YDABAG 102Y146.en_US
dc.identifier.endpage43en_US
dc.identifier.issn1794-6190en_US
dc.identifier.issn2339-3459en_US
dc.identifier.issue1en_US
dc.identifier.startpage31en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24888
dc.identifier.volume14en_US
dc.identifier.wosWOS:000280304400003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherUNIV NACIONAL DE COLOMBIAen_US
dc.relation.ispartofEARTH SCIENCES RESEARCH JOURNALen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectStreamflowen_US
dc.subjectENSO Modulationen_US
dc.subjectRadial Based Artificial Neural Network Modelen_US
dc.subjectTurkeyen_US
dc.titleENSO MODULATIONS ON STREAMFLOW CHARACTERISTICSen_US
dc.typeArticleen_US

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