Parameters of infiltration models affected by the infiltration measurement technique and land-use

Detalhes bibliográficos
Autor(a) principal: Karahan,Gülay
Data de Publicação: 2022
Outros Autores: Pachepsky,Yakov
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Ciência do Solo (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100411
Resumo: ABSTRACT The measurement method (MM) and the land-use (LU) are two soil structure-related attributes that are available in infiltration experiments. This study aims to hypothesize that measurement technique and land-use might be good predictors of the performance of infiltration parameter values and models. The Soil Water Infiltration Global (SWIG), which includes about 5000 experiments worldwide and assembled in the Institute of Agrosphere in Jülich, Germany, was used. Except for the known properties such as texture, measurement method, and land-use, changes were observed in organic carbon content, saturated hydraulic conductivity, bulk density, pH, initial water content, and the electrical conductivity of saturated paste. Horton and Mezencev models outperformed from Green and Amp and Two-term Philip models, hence it has been seen that Horton and Mezencev models could be preferred according to the measurement method. To determine the most influential predictors of these two models’ parameters, the machine learning method “regression trees” was applied. In 80 % of cases for both models, the textural class, the MM (40 % of cases), and the LU were found as the most influential predictors. The accuracy of parameter estimates increased when a subset of measurements was used with the same method to estimate infiltration parameters. Textural class, LU, bulk density, and K sat were determined as the most influential predictors for the parameters of the Horton. However, textural class, LU, and organic carbon content became most important in the case of the Mezencev model. Overall, estimates of the infiltration equation parameters can be more accurate if they have been developed for the same MM as in the task at hand. The MM and the LU provide useful surrogate information about the effect of soil structure on infiltration.
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spelling Parameters of infiltration models affected by the infiltration measurement technique and land-usewater infiltrationsoil structuremodelingregression treesmeasurement methodABSTRACT The measurement method (MM) and the land-use (LU) are two soil structure-related attributes that are available in infiltration experiments. This study aims to hypothesize that measurement technique and land-use might be good predictors of the performance of infiltration parameter values and models. The Soil Water Infiltration Global (SWIG), which includes about 5000 experiments worldwide and assembled in the Institute of Agrosphere in Jülich, Germany, was used. Except for the known properties such as texture, measurement method, and land-use, changes were observed in organic carbon content, saturated hydraulic conductivity, bulk density, pH, initial water content, and the electrical conductivity of saturated paste. Horton and Mezencev models outperformed from Green and Amp and Two-term Philip models, hence it has been seen that Horton and Mezencev models could be preferred according to the measurement method. To determine the most influential predictors of these two models’ parameters, the machine learning method “regression trees” was applied. In 80 % of cases for both models, the textural class, the MM (40 % of cases), and the LU were found as the most influential predictors. The accuracy of parameter estimates increased when a subset of measurements was used with the same method to estimate infiltration parameters. Textural class, LU, bulk density, and K sat were determined as the most influential predictors for the parameters of the Horton. However, textural class, LU, and organic carbon content became most important in the case of the Mezencev model. Overall, estimates of the infiltration equation parameters can be more accurate if they have been developed for the same MM as in the task at hand. The MM and the LU provide useful surrogate information about the effect of soil structure on infiltration.Sociedade Brasileira de Ciência do Solo2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100411Revista Brasileira de Ciência do Solo v.46 2022reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.36783/18069657rbcs20210147info:eu-repo/semantics/openAccessKarahan,GülayPachepsky,Yakoveng2022-06-07T00:00:00Zoai:scielo:S0100-06832022000100411Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0100-0683&lng=es&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||sbcs@ufv.br1806-96570100-0683opendoar:2022-06-07T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false
dc.title.none.fl_str_mv Parameters of infiltration models affected by the infiltration measurement technique and land-use
title Parameters of infiltration models affected by the infiltration measurement technique and land-use
spellingShingle Parameters of infiltration models affected by the infiltration measurement technique and land-use
Karahan,Gülay
water infiltration
soil structure
modeling
regression trees
measurement method
title_short Parameters of infiltration models affected by the infiltration measurement technique and land-use
title_full Parameters of infiltration models affected by the infiltration measurement technique and land-use
title_fullStr Parameters of infiltration models affected by the infiltration measurement technique and land-use
title_full_unstemmed Parameters of infiltration models affected by the infiltration measurement technique and land-use
title_sort Parameters of infiltration models affected by the infiltration measurement technique and land-use
author Karahan,Gülay
author_facet Karahan,Gülay
Pachepsky,Yakov
author_role author
author2 Pachepsky,Yakov
author2_role author
dc.contributor.author.fl_str_mv Karahan,Gülay
Pachepsky,Yakov
dc.subject.por.fl_str_mv water infiltration
soil structure
modeling
regression trees
measurement method
topic water infiltration
soil structure
modeling
regression trees
measurement method
description ABSTRACT The measurement method (MM) and the land-use (LU) are two soil structure-related attributes that are available in infiltration experiments. This study aims to hypothesize that measurement technique and land-use might be good predictors of the performance of infiltration parameter values and models. The Soil Water Infiltration Global (SWIG), which includes about 5000 experiments worldwide and assembled in the Institute of Agrosphere in Jülich, Germany, was used. Except for the known properties such as texture, measurement method, and land-use, changes were observed in organic carbon content, saturated hydraulic conductivity, bulk density, pH, initial water content, and the electrical conductivity of saturated paste. Horton and Mezencev models outperformed from Green and Amp and Two-term Philip models, hence it has been seen that Horton and Mezencev models could be preferred according to the measurement method. To determine the most influential predictors of these two models’ parameters, the machine learning method “regression trees” was applied. In 80 % of cases for both models, the textural class, the MM (40 % of cases), and the LU were found as the most influential predictors. The accuracy of parameter estimates increased when a subset of measurements was used with the same method to estimate infiltration parameters. Textural class, LU, bulk density, and K sat were determined as the most influential predictors for the parameters of the Horton. However, textural class, LU, and organic carbon content became most important in the case of the Mezencev model. Overall, estimates of the infiltration equation parameters can be more accurate if they have been developed for the same MM as in the task at hand. The MM and the LU provide useful surrogate information about the effect of soil structure on infiltration.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100411
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832022000100411
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.36783/18069657rbcs20210147
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
dc.source.none.fl_str_mv Revista Brasileira de Ciência do Solo v.46 2022
reponame:Revista Brasileira de Ciência do Solo (Online)
instname:Sociedade Brasileira de Ciência do Solo (SBCS)
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instname_str Sociedade Brasileira de Ciência do Solo (SBCS)
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institution SBCS
reponame_str Revista Brasileira de Ciência do Solo (Online)
collection Revista Brasileira de Ciência do Solo (Online)
repository.name.fl_str_mv Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)
repository.mail.fl_str_mv ||sbcs@ufv.br
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