Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale

Autores
Domenech, Marisa Beatriz; Castro Franco, Mauricio; Costa, Jose Luis; Amiotti, Nilda Mabel
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soil depth has played a key role in the development of soil survey, implementation of soil-specific management and validation of hydrological models. Generally, soil depth at field scale is difficult to map due to complex interactions of factors of soil formation at field scale. As a result, the conventional sampling schemes to map soil depth are generally laborious, time consuming and expensive. In this study, we presented, tested and evaluated a method to optimize the sampling scheme to map soil depth to petrocalcic horizon at field scale. The method was tested with real data at four agricultural fields localized in the southeast Pampas plain of Argentina. The purpose of the method was to minimize the sample dataset size to map soil depth to petrocalcic horizon based on ordinary cokriging, five calibration sample sizes (returned by Conditioned Latin hypercube –cLHS-), and apparent electrical conductivity (ECa) or elevation as variables of auxiliary information. The results suggest that (i) only 30% of samples collected on a 30-m grid are required to provide high prediction accuracy (R2 > 0.95) to map soil depth to petrocalcic horizon; (ii) an independent validation dataset based on 50% of the samples on a 30-m grid is adequate to validate the most realistic accuracy estimate; and (iii) ECa and elevation, as variables of auxiliary information, are sufficient to map soil depth to petrocalcic horizon. The method proposed provides a significant improvement over conventional to map soil depth and allows reducing cost, time and field labour. Extrapolation of the results to other areas needs to be tested.
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Barrow; Argentina
Fil: Castro Franco, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Amiotti, Nilda Mabel. Universidad Nacional del Sur. Departamento de Agronomía; Argentina
Materia
Argentina
Conditioned Latin Hypercube
Digital Soil Mapping
Ordinary Cokriging
Precision Agriculture
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/72845
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Sampling scheme optimization to map soil depth to petrocalcic horizon at field scaleDomenech, Marisa BeatrizCastro Franco, MauricioCosta, Jose LuisAmiotti, Nilda MabelArgentinaConditioned Latin HypercubeDigital Soil MappingOrdinary CokrigingPrecision Agriculturehttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Soil depth has played a key role in the development of soil survey, implementation of soil-specific management and validation of hydrological models. Generally, soil depth at field scale is difficult to map due to complex interactions of factors of soil formation at field scale. As a result, the conventional sampling schemes to map soil depth are generally laborious, time consuming and expensive. In this study, we presented, tested and evaluated a method to optimize the sampling scheme to map soil depth to petrocalcic horizon at field scale. The method was tested with real data at four agricultural fields localized in the southeast Pampas plain of Argentina. The purpose of the method was to minimize the sample dataset size to map soil depth to petrocalcic horizon based on ordinary cokriging, five calibration sample sizes (returned by Conditioned Latin hypercube –cLHS-), and apparent electrical conductivity (ECa) or elevation as variables of auxiliary information. The results suggest that (i) only 30% of samples collected on a 30-m grid are required to provide high prediction accuracy (R2 > 0.95) to map soil depth to petrocalcic horizon; (ii) an independent validation dataset based on 50% of the samples on a 30-m grid is adequate to validate the most realistic accuracy estimate; and (iii) ECa and elevation, as variables of auxiliary information, are sufficient to map soil depth to petrocalcic horizon. The method proposed provides a significant improvement over conventional to map soil depth and allows reducing cost, time and field labour. Extrapolation of the results to other areas needs to be tested.Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Barrow; ArgentinaFil: Castro Franco, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Amiotti, Nilda Mabel. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaElsevier Science2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/72845Domenech, Marisa Beatriz; Castro Franco, Mauricio; Costa, Jose Luis; Amiotti, Nilda Mabel; Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale; Elsevier Science; Geoderma; 290; 3-2017; 75-820016-7061CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.geoderma.2016.12.012info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0016706116310096info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:42:04Zoai:ri.conicet.gov.ar:11336/72845instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:42:04.372CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
title Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
spellingShingle Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
Domenech, Marisa Beatriz
Argentina
Conditioned Latin Hypercube
Digital Soil Mapping
Ordinary Cokriging
Precision Agriculture
title_short Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
title_full Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
title_fullStr Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
title_full_unstemmed Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
title_sort Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale
dc.creator.none.fl_str_mv Domenech, Marisa Beatriz
Castro Franco, Mauricio
Costa, Jose Luis
Amiotti, Nilda Mabel
author Domenech, Marisa Beatriz
author_facet Domenech, Marisa Beatriz
Castro Franco, Mauricio
Costa, Jose Luis
Amiotti, Nilda Mabel
author_role author
author2 Castro Franco, Mauricio
Costa, Jose Luis
Amiotti, Nilda Mabel
author2_role author
author
author
dc.subject.none.fl_str_mv Argentina
Conditioned Latin Hypercube
Digital Soil Mapping
Ordinary Cokriging
Precision Agriculture
topic Argentina
Conditioned Latin Hypercube
Digital Soil Mapping
Ordinary Cokriging
Precision Agriculture
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Soil depth has played a key role in the development of soil survey, implementation of soil-specific management and validation of hydrological models. Generally, soil depth at field scale is difficult to map due to complex interactions of factors of soil formation at field scale. As a result, the conventional sampling schemes to map soil depth are generally laborious, time consuming and expensive. In this study, we presented, tested and evaluated a method to optimize the sampling scheme to map soil depth to petrocalcic horizon at field scale. The method was tested with real data at four agricultural fields localized in the southeast Pampas plain of Argentina. The purpose of the method was to minimize the sample dataset size to map soil depth to petrocalcic horizon based on ordinary cokriging, five calibration sample sizes (returned by Conditioned Latin hypercube –cLHS-), and apparent electrical conductivity (ECa) or elevation as variables of auxiliary information. The results suggest that (i) only 30% of samples collected on a 30-m grid are required to provide high prediction accuracy (R2 > 0.95) to map soil depth to petrocalcic horizon; (ii) an independent validation dataset based on 50% of the samples on a 30-m grid is adequate to validate the most realistic accuracy estimate; and (iii) ECa and elevation, as variables of auxiliary information, are sufficient to map soil depth to petrocalcic horizon. The method proposed provides a significant improvement over conventional to map soil depth and allows reducing cost, time and field labour. Extrapolation of the results to other areas needs to be tested.
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Barrow; Argentina
Fil: Castro Franco, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Amiotti, Nilda Mabel. Universidad Nacional del Sur. Departamento de Agronomía; Argentina
description Soil depth has played a key role in the development of soil survey, implementation of soil-specific management and validation of hydrological models. Generally, soil depth at field scale is difficult to map due to complex interactions of factors of soil formation at field scale. As a result, the conventional sampling schemes to map soil depth are generally laborious, time consuming and expensive. In this study, we presented, tested and evaluated a method to optimize the sampling scheme to map soil depth to petrocalcic horizon at field scale. The method was tested with real data at four agricultural fields localized in the southeast Pampas plain of Argentina. The purpose of the method was to minimize the sample dataset size to map soil depth to petrocalcic horizon based on ordinary cokriging, five calibration sample sizes (returned by Conditioned Latin hypercube –cLHS-), and apparent electrical conductivity (ECa) or elevation as variables of auxiliary information. The results suggest that (i) only 30% of samples collected on a 30-m grid are required to provide high prediction accuracy (R2 > 0.95) to map soil depth to petrocalcic horizon; (ii) an independent validation dataset based on 50% of the samples on a 30-m grid is adequate to validate the most realistic accuracy estimate; and (iii) ECa and elevation, as variables of auxiliary information, are sufficient to map soil depth to petrocalcic horizon. The method proposed provides a significant improvement over conventional to map soil depth and allows reducing cost, time and field labour. Extrapolation of the results to other areas needs to be tested.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/72845
Domenech, Marisa Beatriz; Castro Franco, Mauricio; Costa, Jose Luis; Amiotti, Nilda Mabel; Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale; Elsevier Science; Geoderma; 290; 3-2017; 75-82
0016-7061
CONICET Digital
CONICET
url http://hdl.handle.net/11336/72845
identifier_str_mv Domenech, Marisa Beatriz; Castro Franco, Mauricio; Costa, Jose Luis; Amiotti, Nilda Mabel; Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale; Elsevier Science; Geoderma; 290; 3-2017; 75-82
0016-7061
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.geoderma.2016.12.012
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0016706116310096
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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