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.
EEA Barrow
EEA Balcarce
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). 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 (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Amiotti, Nilda Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fuente
Geoderma 290 : 75-82. (March 2017)
Materia
Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/2308
Acceder
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oai_identifier_str oai:localhost:20.500.12123/2308
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Sampling scheme optimization to map soil depth to petrocalcic horizon at field scaleDomenech, Marisa BeatrizCastro Franco, MauricioCosta, Jose LuisAmiotti, Nilda MabelSueloHorizontes del SueloHidrologíaSoilSoil HorizonsHydrologyProfundidad del SueloHorizonte PetrocálcicoSoil 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.EEA BarrowEEA BalcarceFil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; ArgentinaFil: Castro Franco, Mauricio. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Amiotti, Nilda Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina2018-05-02T15:53:22Z2018-05-02T15:53:22Z2017-03-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://www.sciencedirect.com/science/article/pii/S0016706116310096#!http://hdl.handle.net/20.500.12123/23080016-7061https://doi.org/10.1016/j.geoderma.2016.12.012Geoderma 290 : 75-82. (March 2017)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-29T13:44:17Zoai:localhost:20.500.12123/2308instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:18.31INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
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
Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
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 Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
topic Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
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.
EEA Barrow
EEA Balcarce
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). 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 (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Amiotti, Nilda Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; 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 2017-03-15
2018-05-02T15:53:22Z
2018-05-02T15:53:22Z
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 https://www.sciencedirect.com/science/article/pii/S0016706116310096#!
http://hdl.handle.net/20.500.12123/2308
0016-7061
https://doi.org/10.1016/j.geoderma.2016.12.012
url https://www.sciencedirect.com/science/article/pii/S0016706116310096#!
http://hdl.handle.net/20.500.12123/2308
https://doi.org/10.1016/j.geoderma.2016.12.012
identifier_str_mv 0016-7061
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Geoderma 290 : 75-82. (March 2017)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.559606

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