Loading…

In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths

The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory throug...

Full description

Saved in:
Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2021-01, Vol.21 (2), p.447
Main Authors: Zeitoun, Reem, Vandergeest, Mark, Vasava, Hiteshkumar Bhogilal, Machado, Pedro Vitor Ferrari, Jordan, Sean, Parkin, Gary, Wagner-Riddle, Claudia, Biswas, Asim
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743
cites cdi_FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743
container_end_page
container_issue 2
container_start_page 447
container_title Sensors (Basel, Switzerland)
container_volume 21
creator Zeitoun, Reem
Vandergeest, Mark
Vasava, Hiteshkumar Bhogilal
Machado, Pedro Vitor Ferrari
Jordan, Sean
Parkin, Gary
Wagner-Riddle, Claudia
Biswas, Asim
description The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 m m between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.
doi_str_mv 10.3390/s21020447
format article
fullrecord <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_18e2fa529be24ffe861162ca51eaa7e9</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_18e2fa529be24ffe861162ca51eaa7e9</doaj_id><sourcerecordid>2477872795</sourcerecordid><originalsourceid>FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743</originalsourceid><addsrcrecordid>eNpdkk1vEzEQhleIin7AgT-ALHGBw1J_23tBQmkLkSJVIiCOlnd33Dps1qntrdR_j5OUqO1lPBq_88yMPVX1nuAvjDX4PFGCKeZcvapOCKe81pTi10_84-o0pRXGlDGm31THjHEmKCYn1d_5WC99ntBlyn5tsw8jCg4tgx_QH5shop-QYdzFZ1O8B-RHtPRDRotg18iO_c55QMutu01LyGZ04Z2DWPL2pAvY5Nv0tjpydkjw7vE8q35fXf6a_agX19_ns2-LuuOyyTWwzoHE0jENimuMCe-kpX1PpZakYa2A3opiRUvAdcJh2RYDlrVME8XZWTXfc_tgV2YTy1zxwQTrzS4Q4o2xMftuAEM0UGcFbVqgvLRcChBJOysIWKugKayve9ZmatfQd2WkaIdn0Oc3o781N-HeKE2lUKQAPj0CYribIGWz9qmDYbAjhCkZypUSWGmuivTjC-kqTHEsT7VTaUVVI4rq817VxZBSBHdohmCzXQdzWIei_fC0-4Py__-zf9lorzA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2477872795</pqid></control><display><type>article</type><title>In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths</title><source>Open Access: PubMed Central</source><source>Publicly Available Content Database</source><creator>Zeitoun, Reem ; Vandergeest, Mark ; Vasava, Hiteshkumar Bhogilal ; Machado, Pedro Vitor Ferrari ; Jordan, Sean ; Parkin, Gary ; Wagner-Riddle, Claudia ; Biswas, Asim</creator><creatorcontrib>Zeitoun, Reem ; Vandergeest, Mark ; Vasava, Hiteshkumar Bhogilal ; Machado, Pedro Vitor Ferrari ; Jordan, Sean ; Parkin, Gary ; Wagner-Riddle, Claudia ; Biswas, Asim</creatorcontrib><description>The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 m m between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.</description><identifier>ISSN: 1424-8220</identifier><identifier>EISSN: 1424-8220</identifier><identifier>DOI: 10.3390/s21020447</identifier><identifier>PMID: 33435201</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Efficiency ; Entrapment ; field capacity ; Groundwater recharge ; Hydraulics ; Hydrology ; Irrigation ; Laboratories ; Loam soils ; matric potential ; Methods ; parametric models ; Parametric statistics ; permanent wilting ; Scheduling ; Sensors ; Silt loam ; Soil sciences ; soil water content ; Soil water storage ; Water measurement ; Water shortages</subject><ispartof>Sensors (Basel, Switzerland), 2021-01, Vol.21 (2), p.447</ispartof><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743</citedby><cites>FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743</cites><orcidid>0000-0003-0801-3546 ; 0000-0003-4176-4421</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2477872795/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2477872795?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25752,27923,27924,37011,37012,44589,53790,53792,74897</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33435201$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zeitoun, Reem</creatorcontrib><creatorcontrib>Vandergeest, Mark</creatorcontrib><creatorcontrib>Vasava, Hiteshkumar Bhogilal</creatorcontrib><creatorcontrib>Machado, Pedro Vitor Ferrari</creatorcontrib><creatorcontrib>Jordan, Sean</creatorcontrib><creatorcontrib>Parkin, Gary</creatorcontrib><creatorcontrib>Wagner-Riddle, Claudia</creatorcontrib><creatorcontrib>Biswas, Asim</creatorcontrib><title>In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths</title><title>Sensors (Basel, Switzerland)</title><addtitle>Sensors (Basel)</addtitle><description>The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 m m between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.</description><subject>Efficiency</subject><subject>Entrapment</subject><subject>field capacity</subject><subject>Groundwater recharge</subject><subject>Hydraulics</subject><subject>Hydrology</subject><subject>Irrigation</subject><subject>Laboratories</subject><subject>Loam soils</subject><subject>matric potential</subject><subject>Methods</subject><subject>parametric models</subject><subject>Parametric statistics</subject><subject>permanent wilting</subject><subject>Scheduling</subject><subject>Sensors</subject><subject>Silt loam</subject><subject>Soil sciences</subject><subject>soil water content</subject><subject>Soil water storage</subject><subject>Water measurement</subject><subject>Water shortages</subject><issn>1424-8220</issn><issn>1424-8220</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpdkk1vEzEQhleIin7AgT-ALHGBw1J_23tBQmkLkSJVIiCOlnd33Dps1qntrdR_j5OUqO1lPBq_88yMPVX1nuAvjDX4PFGCKeZcvapOCKe81pTi10_84-o0pRXGlDGm31THjHEmKCYn1d_5WC99ntBlyn5tsw8jCg4tgx_QH5shop-QYdzFZ1O8B-RHtPRDRotg18iO_c55QMutu01LyGZ04Z2DWPL2pAvY5Nv0tjpydkjw7vE8q35fXf6a_agX19_ns2-LuuOyyTWwzoHE0jENimuMCe-kpX1PpZakYa2A3opiRUvAdcJh2RYDlrVME8XZWTXfc_tgV2YTy1zxwQTrzS4Q4o2xMftuAEM0UGcFbVqgvLRcChBJOysIWKugKayve9ZmatfQd2WkaIdn0Oc3o781N-HeKE2lUKQAPj0CYribIGWz9qmDYbAjhCkZypUSWGmuivTjC-kqTHEsT7VTaUVVI4rq817VxZBSBHdohmCzXQdzWIei_fC0-4Py__-zf9lorzA</recordid><startdate>20210110</startdate><enddate>20210110</enddate><creator>Zeitoun, Reem</creator><creator>Vandergeest, Mark</creator><creator>Vasava, Hiteshkumar Bhogilal</creator><creator>Machado, Pedro Vitor Ferrari</creator><creator>Jordan, Sean</creator><creator>Parkin, Gary</creator><creator>Wagner-Riddle, Claudia</creator><creator>Biswas, Asim</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0801-3546</orcidid><orcidid>https://orcid.org/0000-0003-4176-4421</orcidid></search><sort><creationdate>20210110</creationdate><title>In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths</title><author>Zeitoun, Reem ; Vandergeest, Mark ; Vasava, Hiteshkumar Bhogilal ; Machado, Pedro Vitor Ferrari ; Jordan, Sean ; Parkin, Gary ; Wagner-Riddle, Claudia ; Biswas, Asim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Efficiency</topic><topic>Entrapment</topic><topic>field capacity</topic><topic>Groundwater recharge</topic><topic>Hydraulics</topic><topic>Hydrology</topic><topic>Irrigation</topic><topic>Laboratories</topic><topic>Loam soils</topic><topic>matric potential</topic><topic>Methods</topic><topic>parametric models</topic><topic>Parametric statistics</topic><topic>permanent wilting</topic><topic>Scheduling</topic><topic>Sensors</topic><topic>Silt loam</topic><topic>Soil sciences</topic><topic>soil water content</topic><topic>Soil water storage</topic><topic>Water measurement</topic><topic>Water shortages</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zeitoun, Reem</creatorcontrib><creatorcontrib>Vandergeest, Mark</creatorcontrib><creatorcontrib>Vasava, Hiteshkumar Bhogilal</creatorcontrib><creatorcontrib>Machado, Pedro Vitor Ferrari</creatorcontrib><creatorcontrib>Jordan, Sean</creatorcontrib><creatorcontrib>Parkin, Gary</creatorcontrib><creatorcontrib>Wagner-Riddle, Claudia</creatorcontrib><creatorcontrib>Biswas, Asim</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health &amp; Medical Complete (ProQuest Database)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Sensors (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zeitoun, Reem</au><au>Vandergeest, Mark</au><au>Vasava, Hiteshkumar Bhogilal</au><au>Machado, Pedro Vitor Ferrari</au><au>Jordan, Sean</au><au>Parkin, Gary</au><au>Wagner-Riddle, Claudia</au><au>Biswas, Asim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths</atitle><jtitle>Sensors (Basel, Switzerland)</jtitle><addtitle>Sensors (Basel)</addtitle><date>2021-01-10</date><risdate>2021</risdate><volume>21</volume><issue>2</issue><spage>447</spage><pages>447-</pages><issn>1424-8220</issn><eissn>1424-8220</eissn><abstract>The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 m m between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>33435201</pmid><doi>10.3390/s21020447</doi><orcidid>https://orcid.org/0000-0003-0801-3546</orcidid><orcidid>https://orcid.org/0000-0003-4176-4421</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1424-8220
ispartof Sensors (Basel, Switzerland), 2021-01, Vol.21 (2), p.447
issn 1424-8220
1424-8220
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_18e2fa529be24ffe861162ca51eaa7e9
source Open Access: PubMed Central; Publicly Available Content Database
subjects Efficiency
Entrapment
field capacity
Groundwater recharge
Hydraulics
Hydrology
Irrigation
Laboratories
Loam soils
matric potential
Methods
parametric models
Parametric statistics
permanent wilting
Scheduling
Sensors
Silt loam
Soil sciences
soil water content
Soil water storage
Water measurement
Water shortages
title In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T11%3A52%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=In-Situ%20Estimation%20of%20Soil%20Water%20Retention%20Curve%20in%20Silt%20Loam%20and%20Loamy%20Sand%20Soils%20at%20Different%20Soil%20Depths&rft.jtitle=Sensors%20(Basel,%20Switzerland)&rft.au=Zeitoun,%20Reem&rft.date=2021-01-10&rft.volume=21&rft.issue=2&rft.spage=447&rft.pages=447-&rft.issn=1424-8220&rft.eissn=1424-8220&rft_id=info:doi/10.3390/s21020447&rft_dat=%3Cproquest_doaj_%3E2477872795%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c469t-e3cfe606f38e7480014c6a2dd2686193b5eda5b5e5b1efc5f06b5f0ea3b381743%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2477872795&rft_id=info:pmid/33435201&rfr_iscdi=true