Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures

40 Pags.- 6 Figs.- 6 Tabls. The definitive version is available at: https://www.sciencedirect.com/science/journal/00167061

Detalles Bibliográficos
Autores: Gaspar Ferrer, Leticia, Blake, William H., Smith, Hugh G., Lizaga Villuendas, Iván, Navas Izquierdo, Ana
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/172741
Acceso en línea:http://hdl.handle.net/10261/172741
Access Level:acceso abierto
Palabra clave:Sediment tracing
Laboratory mixtures
Pro unmixing model
Geochemistry
Particle size
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spelling Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixturesGaspar Ferrer, LeticiaBlake, William H.Smith, Hugh G.Lizaga Villuendas, IvánNavas Izquierdo, AnaSediment tracingLaboratory mixturesPro unmixing modelGeochemistryParticle size40 Pags.- 6 Figs.- 6 Tabls. The definitive version is available at: https://www.sciencedirect.com/science/journal/00167061Sediment source fingerprinting is increasingly used to provide insight into the dynamics of catchment sediment transfer processes, yet relatively few studies seek to validate source apportionments obtained from unmixing models. Our work focuses on simulating natural processes to test the accuracy of source apportionments obtained using a multivariate unmixing model called FingerPro. A relevant laboratory experiment is proposed to test the sensitivity of the model, using as experimental sediments 14 artificial mixtures composed of different proportions and numbers of sources selected from five soils as experimental sources. Twelve artificial mixtures were created by mixing a known proportion of source soils sieved to <63 μm in different proportions obtaining experimental sediments with three or four sources (experiment 1), while two additional artificial mixtures were prepared by combining mixing and sieving to obtain experimental sediments sieved to <40 and < 15 μm (experiment 2). This research aims to test the sensitivity of the model by comparing the estimated source contributions for three sets of selected tracers (experiment 1) and for variations in particle size of the sources and mixtures (experiment 2). Experiment 1 show that source apportionments estimated by the FingerPro model for the same mixture reached maximum differences of 10% by using different tracers, with significantly different GOF and RMSE values between tracer sets (GOF means: 90% set A, 94% set B and 96% set C; RMSE means: 1.9% set A, 3% set B and 2.7% set C). Experiment 2 showed the inconsistency of model outputs when sources and mixtures had different particle size fractions. The accuracy of the model declined as the sediment become finer, and the mean RMSE increased from 2% to 4% up to 12% for mixtures at <63, <20 and < 15 μm, respectively. The source apportionments estimated using a particle size correction factor improved slightly but not in all cases, with a maximum improvement of around one-third of the RMSE (mixture 10-B). Our results highlight the usefulness of employing artificial mixtures to test the accuracy of model simulations based on different tracer selections, source combinations and particle size fractions.Financial support from project (CGL2014-52986-R) is gratefully acknowledged.Peer reviewedElsevierMinisterio de Economía y Competitividad (España)Gaspar Ferrer, Leticia [0000-0002-3473-7110]Navas Izquierdo, Ana [0000-0002-4724-7532]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]201820182019info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/172741reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttps://doi.org/10.1016/j.geoderma.2018.10.005Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1727412026-05-22T06:33:51Z
dc.title.none.fl_str_mv Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
title Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
spellingShingle Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
Gaspar Ferrer, Leticia
Sediment tracing
Laboratory mixtures
Pro unmixing model
Geochemistry
Particle size
title_short Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
title_full Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
title_fullStr Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
title_full_unstemmed Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
title_sort Testing the sensitivity of a multivariate mixing model using geochemical fingerprints with artificial mixtures
dc.creator.none.fl_str_mv Gaspar Ferrer, Leticia
Blake, William H.
Smith, Hugh G.
Lizaga Villuendas, Iván
Navas Izquierdo, Ana
author Gaspar Ferrer, Leticia
author_facet Gaspar Ferrer, Leticia
Blake, William H.
Smith, Hugh G.
Lizaga Villuendas, Iván
Navas Izquierdo, Ana
author_role author
author2 Blake, William H.
Smith, Hugh G.
Lizaga Villuendas, Iván
Navas Izquierdo, Ana
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
Gaspar Ferrer, Leticia [0000-0002-3473-7110]
Navas Izquierdo, Ana [0000-0002-4724-7532]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Sediment tracing
Laboratory mixtures
Pro unmixing model
Geochemistry
Particle size
topic Sediment tracing
Laboratory mixtures
Pro unmixing model
Geochemistry
Particle size
description 40 Pags.- 6 Figs.- 6 Tabls. The definitive version is available at: https://www.sciencedirect.com/science/journal/00167061
publishDate 2018
dc.date.none.fl_str_mv 2018
2018
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/172741
url http://hdl.handle.net/10261/172741
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1016/j.geoderma.2018.10.005
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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