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dc.rights.licenseopenen_US
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorJALON ROJAS, Isabel
ORCID: 0000-0003-4254-4084
IDREF: 160580730
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSCHMIDT, Sabine
IDREF: 131836129
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSOTTOLICHIO, Aldo
IDREF: 158099699
dc.date.accessioned2024-06-04T13:44:44Z
dc.date.available2024-06-04T13:44:44Z
dc.date.issued2016-03-01
dc.identifier.issn1541-5856en_US
dc.identifier.urioai:crossref.org:10.1002/lom3.10097
dc.identifier.uriorcid:0000-0002-5985-9747:10.1002/lom3.10097
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/200253
dc.description.abstractEnHigh-frequency monitoring is currently a major component in the management and research of the coastal system responses to ongoing global changes. This monitoring is essential in tidal systems to address the multiscale variability of physico-chemical parameters. The analysis of the resulting multiscale, nonlinear, non-stationary and noisy time series requires adequate techniques; however, to date, there are no standardized methods. Spectral methods might be useful tools to reveal the main variability time scales, and thus their associated forcings. The most widely used methods in coastal systems are Lomb-Scargle Periodogram (LSP), Singular Spectral Analysis (SSA), Continuous Wavelet Transform (CWT), and Empirical Mode Decomposition (EMD), but their relevance for high-frequency, long-term records is still largely unexplored. In this article, these spectral methods are tested and compared using a high-frequency 10-yr turbidity dataset in the Gironde estuary. Advantages and limitations of each method are evaluated on the basis of five criteria: (1) efficiency for incomplete time series, (2) appropriateness for time-varying analysis, (3) ability to recognize processes without complementary environmental variables, (4) capacity to calculate the relative importance of forcings, and (5) capacity to identify long-term trends. SSA is the only analysis method to satisfy all the criteria, even with 70% missing data. Combining methods is also a promising strategy; i.e., SSA1LSP for better recognition of processes; CWT1SSA and EMD1CWT for short-term (seasonal) and long-term (>1 yr) analysis, respectively. The purpose of this methodological framework is to serve as a reference for future postprocessing of data from monitoring programs in coastal waters.
dc.language.isoENen_US
dc.sourcecrossref
dc.sourceorcid
dc.title.enEvaluation of spectral methods for high-frequency multiannual time series in coastal transitional waters: advantages of combined analyses: Tests of spectral analysis on coastal time series
dc.typeArticle de revueen_US
dc.identifier.doi10.1002/lom3.10097en_US
dc.subject.halSciences de l'environnementen_US
bordeaux.journalLimnology and Oceanography: Methodsen_US
bordeaux.page381-396en_US
bordeaux.volume14en_US
bordeaux.hal.laboratoriesEPOC : Environnements et Paléoenvironnements Océaniques et Continentaux - UMR 5805en_US
bordeaux.issue6en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.teamMETHYSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcedissemin
hal.identifierhal-04600833
hal.version1
hal.date.transferred2024-06-04T13:44:46Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcedissemin
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Limnology%20and%20Oceanography:%20Methods&rft.date=2016-03-01&rft.volume=14&rft.issue=6&rft.spage=381-396&rft.epage=381-396&rft.eissn=1541-5856&rft.issn=1541-5856&rft.au=JALON%20ROJAS,%20Isabel&SCHMIDT,%20Sabine&SOTTOLICHIO,%20Aldo&rft.genre=article


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