Assessment of soil salinity indexes using electrical conductivity sensors

The salinity tolerance of plants can be improved by efficient irrigation management and salt flushing, which require a continuous and precise knowledge of the salinity in the soil or substrate. Soil sensors that measure electrical conductivity play an essential role in monitoring soil salinity. Howe...

Descripción completa

Detalles Bibliográficos
Autores: Bañón, Sebastián, Álvarez Martín, Sara, Bañón, Daniel, Ortuño Gallud, M. Fernanda, Sánchez-Blanco, María Jesús
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/258493
Acceso en línea:http://hdl.handle.net/10261/258493
Access Level:acceso abierto
Palabra clave:Soil moisture
Soil probe
Electrical conductivity
Substrate
Lysimeter
id ES_e284cef80ef8bdb76af18f38b7e0ee96
oai_identifier_str oai:digital.csic.es:10261/258493
network_acronym_str ES
network_name_str España
repository_id_str
spelling Assessment of soil salinity indexes using electrical conductivity sensorsBañón, SebastiánÁlvarez Martín, SaraBañón, DanielOrtuño Gallud, M. FernandaSánchez-Blanco, María JesúsSoil moistureSoil probeElectrical conductivitySubstrateLysimeterThe salinity tolerance of plants can be improved by efficient irrigation management and salt flushing, which require a continuous and precise knowledge of the salinity in the soil or substrate. Soil sensors that measure electrical conductivity play an essential role in monitoring soil salinity. However, the correct interpretation of salinity measurements using soil sensors depends on developing appropriate salinity indexes. This work studied the potential of several salinity indexes based on the bulk EC (ECb) directly measured by soil sensors, and on pore water EC (ECw) estimated by the Hilhorst model (ECwHI). The methodology used in the experiments is based on the simultaneous use of scales and sensors, which allowed the automatic monitoring of the real salinity levels of the substrate, and the conductivity measurements made with the soil sensor. Regression studies were carried out to know how well the proposed salinity indexes explain real salinity. In general, all the indexes were suitable for estimating the relative changes in substrate salinity, as long as they met certain requirements. For example, ECwHI was seen to be a reliable salinity index when substrate moisture was high and constant. However, there was no such requirement when the ECwHI was corrected according to the current substrate water content, or when the salinity index was calculated as the average of the ECwHI values between two successive irrigation events. ECb was an efficient salinity indicator as long as the moisture content was constant, although its accuracy increased at a high moisture level. The findings led us to propose a new salinity index calculated with the slopes of the linear section of the quadratic moisture adjustment, which avoids the need for the substrate moisture content to be constant.This research was funded by the Ministry of Science, Innovation, and Universities of Spain, and the European Regional Development Fund, grant number RTI2018-093997-B-I00, and by the Spanish AEI (grant number PCI 2019-103608) under the PRIMA programme in the frame of the PRECIMED project. PRIMA is an Art.185 initiative supported and co-funded under Horizon 2020, the European Union’s Programme for Research and InnovationElsevier BVMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)European CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2022202220212022info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/258493reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093997-B-I00info:eu-repo/grantAgreement/MICIU/ICTI2017-2020/PCI 2019-103608http://dx.doi.org/10.1016/j.scienta.2021.110171Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2584932026-05-22T06:33:51Z
dc.title.none.fl_str_mv Assessment of soil salinity indexes using electrical conductivity sensors
title Assessment of soil salinity indexes using electrical conductivity sensors
spellingShingle Assessment of soil salinity indexes using electrical conductivity sensors
Bañón, Sebastián
Soil moisture
Soil probe
Electrical conductivity
Substrate
Lysimeter
title_short Assessment of soil salinity indexes using electrical conductivity sensors
title_full Assessment of soil salinity indexes using electrical conductivity sensors
title_fullStr Assessment of soil salinity indexes using electrical conductivity sensors
title_full_unstemmed Assessment of soil salinity indexes using electrical conductivity sensors
title_sort Assessment of soil salinity indexes using electrical conductivity sensors
dc.creator.none.fl_str_mv Bañón, Sebastián
Álvarez Martín, Sara
Bañón, Daniel
Ortuño Gallud, M. Fernanda
Sánchez-Blanco, María Jesús
author Bañón, Sebastián
author_facet Bañón, Sebastián
Álvarez Martín, Sara
Bañón, Daniel
Ortuño Gallud, M. Fernanda
Sánchez-Blanco, María Jesús
author_role author
author2 Álvarez Martín, Sara
Bañón, Daniel
Ortuño Gallud, M. Fernanda
Sánchez-Blanco, María Jesús
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Soil moisture
Soil probe
Electrical conductivity
Substrate
Lysimeter
topic Soil moisture
Soil probe
Electrical conductivity
Substrate
Lysimeter
description The salinity tolerance of plants can be improved by efficient irrigation management and salt flushing, which require a continuous and precise knowledge of the salinity in the soil or substrate. Soil sensors that measure electrical conductivity play an essential role in monitoring soil salinity. However, the correct interpretation of salinity measurements using soil sensors depends on developing appropriate salinity indexes. This work studied the potential of several salinity indexes based on the bulk EC (ECb) directly measured by soil sensors, and on pore water EC (ECw) estimated by the Hilhorst model (ECwHI). The methodology used in the experiments is based on the simultaneous use of scales and sensors, which allowed the automatic monitoring of the real salinity levels of the substrate, and the conductivity measurements made with the soil sensor. Regression studies were carried out to know how well the proposed salinity indexes explain real salinity. In general, all the indexes were suitable for estimating the relative changes in substrate salinity, as long as they met certain requirements. For example, ECwHI was seen to be a reliable salinity index when substrate moisture was high and constant. However, there was no such requirement when the ECwHI was corrected according to the current substrate water content, or when the salinity index was calculated as the average of the ECwHI values between two successive irrigation events. ECb was an efficient salinity indicator as long as the moisture content was constant, although its accuracy increased at a high moisture level. The findings led us to propose a new salinity index calculated with the slopes of the linear section of the quadratic moisture adjustment, which avoids the need for the substrate moisture content to be constant.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/258493
url http://hdl.handle.net/10261/258493
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093997-B-I00
info:eu-repo/grantAgreement/MICIU/ICTI2017-2020/PCI 2019-103608
http://dx.doi.org/10.1016/j.scienta.2021.110171
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier BV
publisher.none.fl_str_mv Elsevier BV
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869422392812503040
score 15,811543

Similares en LA Referencia