Modelling effective soil depth at field scale from soil sensors and geomorphometric indices

Autores
Castro Franco, Mauricio; Domenech, Marisa Beatriz; Costa, Jose Luis; Aparicio, Virginia Carolina
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.
EEA Barrow
EEA Balcarce
Fil: Castro Franco, Mauricio. Universidad de los Llanos; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; Argentina
Fil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Aparicio, Virginia Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fuente
Acta Agronómica 66 (2) : 228-234. (2017)
Materia
Suelo
Hidrología
Geomorfología
Soil
Hydrology
Geomorphology
Profundidad del Suelo
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/2294
Acceder
id INTADig_4b8a6366a12fff6660796c849329706e
oai_identifier_str oai:localhost:20.500.12123/2294
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Modelling effective soil depth at field scale from soil sensors and geomorphometric indicesCastro Franco, MauricioDomenech, Marisa BeatrizCosta, Jose LuisAparicio, Virginia CarolinaSueloHidrologíaGeomorfologíaSoilHydrologyGeomorphologyProfundidad del SueloThe effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.EEA BarrowEEA BalcarceFil: Castro Franco, Mauricio. Universidad de los Llanos; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; ArgentinaFil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; ArgentinaFil: Aparicio, Virginia Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina2018-04-27T14:30:42Z2018-04-27T14:30:42Z2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810http://hdl.handle.net/20.500.12123/22940120-28122323-0118https://doi.org/10.15446/acag.v66n2.53282Acta Agronómica 66 (2) : 228-234. (2017)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-29T13:44:17Zoai:localhost:20.500.12123/2294instacron: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 13:44:18.268INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
spellingShingle Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
Castro Franco, Mauricio
Suelo
Hidrología
Geomorfología
Soil
Hydrology
Geomorphology
Profundidad del Suelo
title_short Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_full Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_fullStr Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_full_unstemmed Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_sort Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
dc.creator.none.fl_str_mv Castro Franco, Mauricio
Domenech, Marisa Beatriz
Costa, Jose Luis
Aparicio, Virginia Carolina
author Castro Franco, Mauricio
author_facet Castro Franco, Mauricio
Domenech, Marisa Beatriz
Costa, Jose Luis
Aparicio, Virginia Carolina
author_role author
author2 Domenech, Marisa Beatriz
Costa, Jose Luis
Aparicio, Virginia Carolina
author2_role author
author
author
dc.subject.none.fl_str_mv Suelo
Hidrología
Geomorfología
Soil
Hydrology
Geomorphology
Profundidad del Suelo
topic Suelo
Hidrología
Geomorfología
Soil
Hydrology
Geomorphology
Profundidad del Suelo
dc.description.none.fl_txt_mv The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.
EEA Barrow
EEA Balcarce
Fil: Castro Franco, Mauricio. Universidad de los Llanos; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Domenech, Marisa Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Barrow; Argentina
Fil: Costa, Jose Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
Fil: Aparicio, Virginia Carolina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina
description The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.
publishDate 2017
dc.date.none.fl_str_mv 2017
2018-04-27T14:30:42Z
2018-04-27T14:30:42Z
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://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810
http://hdl.handle.net/20.500.12123/2294
0120-2812
2323-0118
https://doi.org/10.15446/acag.v66n2.53282
url https://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282/57810
http://hdl.handle.net/20.500.12123/2294
https://doi.org/10.15446/acag.v66n2.53282
identifier_str_mv 0120-2812
2323-0118
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Acta Agronómica 66 (2) : 228-234. (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
_version_ 1844619121613864960
score 12.559606

Publicaciones similares