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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...

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Autores principales: Zeitoun, Reem, Vandergeest, Mark, Vasava, Hiteshkumar Bhogilal, Machado, Pedro Vitor Ferrari, Jordan, Sean, Parkin, Gary, Wagner-Riddle, Claudia, Biswas, Asim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826571/
https://www.ncbi.nlm.nih.gov/pubmed/33435201
http://dx.doi.org/10.3390/s21020447
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author Zeitoun, Reem
Vandergeest, Mark
Vasava, Hiteshkumar Bhogilal
Machado, Pedro Vitor Ferrari
Jordan, Sean
Parkin, Gary
Wagner-Riddle, Claudia
Biswas, Asim
author_facet Zeitoun, Reem
Vandergeest, Mark
Vasava, Hiteshkumar Bhogilal
Machado, Pedro Vitor Ferrari
Jordan, Sean
Parkin, Gary
Wagner-Riddle, Claudia
Biswas, Asim
author_sort Zeitoun, Reem
collection PubMed
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(3)m(−3) 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.
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spelling pubmed-78265712021-01-25 In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths Zeitoun, Reem Vandergeest, Mark Vasava, Hiteshkumar Bhogilal Machado, Pedro Vitor Ferrari Jordan, Sean Parkin, Gary Wagner-Riddle, Claudia Biswas, Asim Sensors (Basel) Article 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(3)m(−3) 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. MDPI 2021-01-10 /pmc/articles/PMC7826571/ /pubmed/33435201 http://dx.doi.org/10.3390/s21020447 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zeitoun, Reem
Vandergeest, Mark
Vasava, Hiteshkumar Bhogilal
Machado, Pedro Vitor Ferrari
Jordan, Sean
Parkin, Gary
Wagner-Riddle, Claudia
Biswas, Asim
In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title_full In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title_fullStr In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title_full_unstemmed In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title_short In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths
title_sort in-situ estimation of soil water retention curve in silt loam and loamy sand soils at different soil depths
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7826571/
https://www.ncbi.nlm.nih.gov/pubmed/33435201
http://dx.doi.org/10.3390/s21020447
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