Relationship of soil moisture characteristic curve and mechanical properties in Entisols and Inceptisols of Iran

Eisa Ebrahimi; Hossein  Bayat; Mahboobeh Fallah

doi:10.1016/j.geodrs.2021.e00434

Relationship of soil moisture characteristic curve and mechanical properties in Entisols and Inceptisols of Iran

Eisa Ebrahimi, Hossein Bayat, Mahboobeh Fallah

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Abstract

The objective of this research was to investigate the relationship between soil moisture characteristic curve (SMCC) and confined compression curve (CCC), and the ability to estimate the SMCC from the CCC. Five provinces of Iran have been chosen as sampling sites and soil samples (150) were collected from these areas, and some properties of the soil samples were determined. The Gardner model has been fitted to the measured SMCC and CCC. The Gardner model's stress-void ratio coefficients, as well as the CCC properties, were used to estimate the soil moisture at five levels (five classes of variables) through the Gardner model using artificial neural networks (ANNs). A more accurate estimation of the water content was obtained by combining the basic soil properties, and three key properties of soil compression. In addition, the integral root mean square error (IRMSE) in the training and testing steps was reduced from 0.107 and 0.111 to 0.095 and 0.096, respectively. In conclusion, the use of CCC data to estimate the SMCC at all levels of the input variables indicated very favorable results with an increase in the accuracy of the water content estimation between 4% and 16% in both training and testing steps.

Original language	English
Article number	e00434
Number of pages	13
Journal	Geoderma Regional
Volume	27
Early online date	19 Aug 2021
DOIs	https://doi.org/10.1016/j.geodrs.2021.e00434
Publication status	Published - Dec 2021

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Geoderma Regional. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Geoderma Regional, 27, (2021)
DOI: 10.1016/j.geodrs.2021.e00434

© 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
.

Funder

Funding Information:
This work was funded by Bu-Ali Sina University, Hamedan, Iran.

Keywords

Entisols
Inceptisols
Pedotransfer function
Soil hydraulic properties
Soil water management
Soil water retention

ASJC Scopus subject areas

Soil Science

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10.1016/j.geodrs.2021.e00434

Post-PrintAccepted author manuscript, 1.24 MBLicence: CC BY-NC-ND

Cite this

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title = "Relationship of soil moisture characteristic curve and mechanical properties in Entisols and Inceptisols of Iran",

abstract = "The objective of this research was to investigate the relationship between soil moisture characteristic curve (SMCC) and confined compression curve (CCC), and the ability to estimate the SMCC from the CCC. Five provinces of Iran have been chosen as sampling sites and soil samples (150) were collected from these areas, and some properties of the soil samples were determined. The Gardner model has been fitted to the measured SMCC and CCC. The Gardner model's stress-void ratio coefficients, as well as the CCC properties, were used to estimate the soil moisture at five levels (five classes of variables) through the Gardner model using artificial neural networks (ANNs). A more accurate estimation of the water content was obtained by combining the basic soil properties, and three key properties of soil compression. In addition, the integral root mean square error (IRMSE) in the training and testing steps was reduced from 0.107 and 0.111 to 0.095 and 0.096, respectively. In conclusion, the use of CCC data to estimate the SMCC at all levels of the input variables indicated very favorable results with an increase in the accuracy of the water content estimation between 4% and 16% in both training and testing steps.",

keywords = "Entisols, Inceptisols, Pedotransfer function, Soil hydraulic properties, Soil water management, Soil water retention",

author = "Eisa Ebrahimi and Hossein Bayat and Mahboobeh Fallah",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Geoderma Regional. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Geoderma Regional, 27, (2021) DOI: 10.1016/j.geodrs.2021.e00434 {\textcopyright} 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ .",

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AU - Ebrahimi, Eisa

AU - Bayat, Hossein

AU - Fallah, Mahboobeh

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Geoderma Regional. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Geoderma Regional, 27, (2021) DOI: 10.1016/j.geodrs.2021.e00434 © 2021, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ .

PY - 2021/12

Y1 - 2021/12

N2 - The objective of this research was to investigate the relationship between soil moisture characteristic curve (SMCC) and confined compression curve (CCC), and the ability to estimate the SMCC from the CCC. Five provinces of Iran have been chosen as sampling sites and soil samples (150) were collected from these areas, and some properties of the soil samples were determined. The Gardner model has been fitted to the measured SMCC and CCC. The Gardner model's stress-void ratio coefficients, as well as the CCC properties, were used to estimate the soil moisture at five levels (five classes of variables) through the Gardner model using artificial neural networks (ANNs). A more accurate estimation of the water content was obtained by combining the basic soil properties, and three key properties of soil compression. In addition, the integral root mean square error (IRMSE) in the training and testing steps was reduced from 0.107 and 0.111 to 0.095 and 0.096, respectively. In conclusion, the use of CCC data to estimate the SMCC at all levels of the input variables indicated very favorable results with an increase in the accuracy of the water content estimation between 4% and 16% in both training and testing steps.

AB - The objective of this research was to investigate the relationship between soil moisture characteristic curve (SMCC) and confined compression curve (CCC), and the ability to estimate the SMCC from the CCC. Five provinces of Iran have been chosen as sampling sites and soil samples (150) were collected from these areas, and some properties of the soil samples were determined. The Gardner model has been fitted to the measured SMCC and CCC. The Gardner model's stress-void ratio coefficients, as well as the CCC properties, were used to estimate the soil moisture at five levels (five classes of variables) through the Gardner model using artificial neural networks (ANNs). A more accurate estimation of the water content was obtained by combining the basic soil properties, and three key properties of soil compression. In addition, the integral root mean square error (IRMSE) in the training and testing steps was reduced from 0.107 and 0.111 to 0.095 and 0.096, respectively. In conclusion, the use of CCC data to estimate the SMCC at all levels of the input variables indicated very favorable results with an increase in the accuracy of the water content estimation between 4% and 16% in both training and testing steps.

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KW - Inceptisols

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Relationship of soil moisture characteristic curve and mechanical properties in Entisols and Inceptisols of Iran

Abstract

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