Clustering of rainfall stations in RH-24 Mexico region using the hurst exponent in semivariograms

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dc.creatorVíctor Gustavo Tercero Gómez
dc.date2015
dc.date.accessioned2018-10-18T20:12:50Z
dc.date.available2018-10-18T20:12:50Z
dc.descriptionAn important topic in the study of the time series behavior and, in particular, meteorological time series is the long-range dependence. This paper explores the behavior of rainfall variations in different periods, using long-range correlations analysis. Semivariograms and Hurst exponent were applied to historical data in different pluviometric stations of the Río Bravo-San Juan watershed, at the hydrographic RH-24 Mexico region. The database was provided by the Water National Commission (CONAGUA). Using the semivariograms, the Hurst exponent was obtained and used as an input to perform a cluster analysis of rainfall stations. Groups of homogeneous samples that might be useful in a regional frequency analysis were obtained through the process. © 2015 Francisco Gerardo Benavides-Bravo et al.
dc.identifier.doi10.1155/2015/629254
dc.identifier.issn1024123X
dc.identifier.urihttp://hdl.handle.net/11285/630307
dc.identifier.volume2015
dc.languageeng
dc.publisherHindawi Publishing Corporation
dc.relationhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84953775695&doi=10.1155%2f2015%2f629254&partnerID=40&md5=440c40fe3cc5ec9c14b23dbc916663df
dc.relationInvestigadores
dc.relationEstudiantes
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceMathematical Problems in Engineering
dc.subjectCluster analysis
dc.subjectTime series
dc.subjectHistorical data
dc.subjectHomogeneous samples
dc.subjectHurst exponents
dc.subjectLong range correlations
dc.subjectLong range dependence
dc.subjectPluviometric stations
dc.subjectRainfall variation
dc.subjectRegional frequency analysis
dc.subjectRain
dc.subject.classification7 INGENIERÍA Y TECNOLOGÍA
dc.titleClustering of rainfall stations in RH-24 Mexico region using the hurst exponent in semivariograms
dc.typeArtículo
refterms.dateFOA2018-10-18T20:12:50Z

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