Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/22005 |
Resumo: | Many agro-environmental studies focusing on the efficient management of soils and water resources make use of soil water simulation models. Reliable soil hydraulic properties are critical for ensuring the accuracy of model simulations. However, soil hydraulic parameters in northern China are generally derived using external pedotransfer functions (PTFs) that do not take into account the specificities of local edaphoclimatic conditions due to the lack of a better alternative. Therefore, the main objective of this paper was to develop PTFs for estimating the soil water retention curve (SWRC) in northern China agricultural soils (named PTF-ANC). A total of 440 soil horizons were collected from the existing literature. A flexible soil-textural conversion program was first developed to harmonize soil particle-size data into the United States Department of Agriculture (USDA) classification system. The SWRC parameters of the van Genuchten model were also generated by curve fitting. Then, the PTF-ANC were developed using artificial neural networks, with soil texture and bulk density being used as input data and with a basic three-layer back-propagation neural network. The PTF-ANC showed an acceptable accuracy when predicting the SWRC, indicating a strong application potential for northern China soils. Comparison of estimates with two widely used external PTFs also showed that these were not suitable for characterizing the SWRC of northern China agricultural soils. This is due to the fact that the main soil textures (silt and silty loam textures) found in northern China soils were misrepresented in those external soil databases. Overall, this paper presented the absolute necessity of developing specific PTFs for northern China agricultural soils |
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Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needsFonctions de pédotransfert pour estimer les propriétés de rétention d'eau du sol des sols agricoles du nord de la Chine: développement et besoinsneural networknon-linear fittingpedotransfer functionssoil hydraulic parameterssoil water modeltextural data conversionMany agro-environmental studies focusing on the efficient management of soils and water resources make use of soil water simulation models. Reliable soil hydraulic properties are critical for ensuring the accuracy of model simulations. However, soil hydraulic parameters in northern China are generally derived using external pedotransfer functions (PTFs) that do not take into account the specificities of local edaphoclimatic conditions due to the lack of a better alternative. Therefore, the main objective of this paper was to develop PTFs for estimating the soil water retention curve (SWRC) in northern China agricultural soils (named PTF-ANC). A total of 440 soil horizons were collected from the existing literature. A flexible soil-textural conversion program was first developed to harmonize soil particle-size data into the United States Department of Agriculture (USDA) classification system. The SWRC parameters of the van Genuchten model were also generated by curve fitting. Then, the PTF-ANC were developed using artificial neural networks, with soil texture and bulk density being used as input data and with a basic three-layer back-propagation neural network. The PTF-ANC showed an acceptable accuracy when predicting the SWRC, indicating a strong application potential for northern China soils. Comparison of estimates with two widely used external PTFs also showed that these were not suitable for characterizing the SWRC of northern China agricultural soils. This is due to the fact that the main soil textures (silt and silty loam textures) found in northern China soils were misrepresented in those external soil databases. Overall, this paper presented the absolute necessity of developing specific PTFs for northern China agricultural soilsWileyRepositório da Universidade de LisboaXu, XuLi, HuaweiSun, ChenRamos, Tiago B.Darouich, HanaaXiong, YunwuQu, ZhongyiHuang, Guanhua2021-09-24T15:19:08Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/22005engIrrig. and Drain. 2021;1–1610.1002/ird.2584info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:51:33Zoai:www.repository.utl.pt:10400.5/22005Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:06:31.314987Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs Fonctions de pédotransfert pour estimer les propriétés de rétention d'eau du sol des sols agricoles du nord de la Chine: développement et besoins |
title |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
spellingShingle |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs Xu, Xu neural network non-linear fitting pedotransfer functions soil hydraulic parameters soil water model textural data conversion |
title_short |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
title_full |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
title_fullStr |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
title_full_unstemmed |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
title_sort |
Pedotransfer functions for estimating soil water retention properties of northern China agricultural soils: Development and needs |
author |
Xu, Xu |
author_facet |
Xu, Xu Li, Huawei Sun, Chen Ramos, Tiago B. Darouich, Hanaa Xiong, Yunwu Qu, Zhongyi Huang, Guanhua |
author_role |
author |
author2 |
Li, Huawei Sun, Chen Ramos, Tiago B. Darouich, Hanaa Xiong, Yunwu Qu, Zhongyi Huang, Guanhua |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Xu, Xu Li, Huawei Sun, Chen Ramos, Tiago B. Darouich, Hanaa Xiong, Yunwu Qu, Zhongyi Huang, Guanhua |
dc.subject.por.fl_str_mv |
neural network non-linear fitting pedotransfer functions soil hydraulic parameters soil water model textural data conversion |
topic |
neural network non-linear fitting pedotransfer functions soil hydraulic parameters soil water model textural data conversion |
description |
Many agro-environmental studies focusing on the efficient management of soils and water resources make use of soil water simulation models. Reliable soil hydraulic properties are critical for ensuring the accuracy of model simulations. However, soil hydraulic parameters in northern China are generally derived using external pedotransfer functions (PTFs) that do not take into account the specificities of local edaphoclimatic conditions due to the lack of a better alternative. Therefore, the main objective of this paper was to develop PTFs for estimating the soil water retention curve (SWRC) in northern China agricultural soils (named PTF-ANC). A total of 440 soil horizons were collected from the existing literature. A flexible soil-textural conversion program was first developed to harmonize soil particle-size data into the United States Department of Agriculture (USDA) classification system. The SWRC parameters of the van Genuchten model were also generated by curve fitting. Then, the PTF-ANC were developed using artificial neural networks, with soil texture and bulk density being used as input data and with a basic three-layer back-propagation neural network. The PTF-ANC showed an acceptable accuracy when predicting the SWRC, indicating a strong application potential for northern China soils. Comparison of estimates with two widely used external PTFs also showed that these were not suitable for characterizing the SWRC of northern China agricultural soils. This is due to the fact that the main soil textures (silt and silty loam textures) found in northern China soils were misrepresented in those external soil databases. Overall, this paper presented the absolute necessity of developing specific PTFs for northern China agricultural soils |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-24T15:19:08Z 2021 2021-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/22005 |
url |
http://hdl.handle.net/10400.5/22005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Irrig. and Drain. 2021;1–16 10.1002/ird.2584 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131157753757696 |