Using Meta-Heuristic Optimization Algorithms to Determine Baseflow and Comparing Their Temporal Performance

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Accurate and simple determination of baseflow is an extremely important issue. In this study, the baseflow levels of Göksu station number 1805 in the Seyhan basin were determined by calibrating the Lyne and Hollick, Chapman, Chapman and Maxwell methods available in the literature using meta-heuristic optimization methods. The meta-heuristic algorithms used for calibration in the study were run thirty times each. Thus the reliability, the reliability of the algorithms was tested with the standard deviations obtained. The study also measured the temporal performance of the algorithms. In addition, the baseflows of Göksu station were determined and their percentage rates were found separately according to all three methods and intuitive methods, and the results obtained were compared. By examining the results obtained in this section, the average baseflow rate of the basin was also determined. Furthermore, each phase of the study was repeated over a five-year period, with the objective of measuring its sustainability. Consequently, it has been demonstrated that the method can be employed over extended periods.

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https://rdlopen.rawdatalibrary.net/r/munzur/924Resmi atıflarda kullanılan kalıcı adres
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https://doi.org/10.1007/s40996-024-01558-8Yayıncı resmi DOI adresi
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dc.contributor.authorAcar, Ramazan
dc.contributor.authorSapliogu, Kemal
dc.date.accessioned2026-10-28T14:53:45.369075179Z
dc.date.available2026-10-28T14:53:45.369075179Z
dc.date.issued2025
dc.description.abstractAccurate and simple determination of baseflow is an extremely important issue. In this study, the baseflow levels of Göksu station number 1805 in the Seyhan basin were determined by calibrating the Lyne and Hollick, Chapman, Chapman and Maxwell methods available in the literature using meta-heuristic optimization methods. The meta-heuristic algorithms used for calibration in the study were run thirty times each. Thus the reliability, the reliability of the algorithms was tested with the standard deviations obtained. The study also measured the temporal performance of the algorithms. In addition, the baseflows of Göksu station were determined and their percentage rates were found separately according to all three methods and intuitive methods, and the results obtained were compared. By examining the results obtained in this section, the average baseflow rate of the basin was also determined. Furthermore, each phase of the study was repeated over a five-year period, with the objective of measuring its sustainability. Consequently, it has been demonstrated that the method can be employed over extended periods.
dc.identifier.doi10.1007/s40996-024-01558-8
dc.identifier.endpage1869
dc.identifier.issn2228-6160
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105001479999
dc.identifier.startpage1851
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/924
dc.identifier.volume49
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofIranian Journal of Science and Technology - Transactions of Civil Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBaseflow
dc.subjectGenetic algorithm
dc.subjectGrey wolf optimizer
dc.subjectOptimization
dc.subjectParticle swarm optimization
dc.subjectSymbiotic organisms search algorithm
dc.titleUsing Meta-Heuristic Optimization Algorithms to Determine Baseflow and Comparing Their Temporal Performance
dc.typeArticle
rdl.citation.openalex1
rdl.citation.scopus0
rdl.oa.statusclosed
rdl.scopus.quartileQ2
rdl.sdgSDG06
rdl.source.indexSCOPUS