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

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 con...

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Main Authors: Domenech, Marisa Beatriz, Castro Franco, Mauricio, Costa, Jose Luis, Amiotti, Nilda Mabel
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: 2018
Subjects:
Online Access: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
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author Domenech, Marisa Beatriz
Castro Franco, Mauricio
Costa, Jose Luis
Amiotti, Nilda Mabel
author_browse Amiotti, Nilda Mabel
Castro Franco, Mauricio
Costa, Jose Luis
Domenech, Marisa Beatriz
author_facet Domenech, Marisa Beatriz
Castro Franco, Mauricio
Costa, Jose Luis
Amiotti, Nilda Mabel
author_sort Domenech, Marisa Beatriz
collection INTA Digital
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.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
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spelling INTA23082019-01-22T17:37:41Z Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale Domenech, Marisa Beatriz Castro Franco, Mauricio Costa, Jose Luis Amiotti, Nilda Mabel Suelo Horizontes del Suelo Hidrología Soil Soil Horizons Hydrology Profundidad del Suelo Horizonte Petrocálcico 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 2018-05-02T15:53:22Z 2018-05-02T15:53:22Z 2017-03-15 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 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 eng info:eu-repo/semantics/restrictedAccess application/pdf Geoderma 290 : 75-82. (March 2017)
spellingShingle Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
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
title 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_short 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
topic Suelo
Horizontes del Suelo
Hidrología
Soil
Soil Horizons
Hydrology
Profundidad del Suelo
Horizonte Petrocálcico
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
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AT costajoseluis samplingschemeoptimizationtomapsoildepthtopetrocalcichorizonatfieldscale
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