Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale

Saturated hydraulic conductivity () is one of the crucial hydraulic properties for assessing water and solute transport in soils. However, direct measurement of is time consuming and arduous. Alternatively, pedotransfer functions (PTFs) have been developed to estimate indirectly through more easil...

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Main Authors: Xi Zhang, Junfeng Zhu, Ole Wendroth, Christopher Matocha, Dwayne Edwards
Format: Article
Language:English
Published: Wiley 2019-05-01
Series:Vadose Zone Journal
Online Access:https://dl.sciencesocieties.org/publications/vzj/articles/18/1/180151
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spelling doaj-68ca66c44f044312a829ca82a51e3dda2020-11-25T03:18:48ZengWileyVadose Zone Journal1539-16632019-05-0118110.2136/vzj2018.08.0151Effect of Macroporosity on Pedotransfer Function Estimates at the Field ScaleXi ZhangJunfeng ZhuOle WendrothChristopher MatochaDwayne EdwardsSaturated hydraulic conductivity () is one of the crucial hydraulic properties for assessing water and solute transport in soils. However, direct measurement of is time consuming and arduous. Alternatively, pedotransfer functions (PTFs) have been developed to estimate indirectly through more easily measurable soil properties that are part of regional, national, or international databases. These PTFs are usually based on datasets collected from large regions. However, their validity for a specific site remains unclear. The objectives of this study were to evaluate the performance of established PTFs in estimating in a specific field and improve PTFs to arrive at a locally adapted estimation result for . Forty-one soil samples were collected from 10 locations at five depths at a farmland in western Kentucky for hydraulic conductivity and physical property measurements. The performance of seven PTFs in estimating was evaluated using the root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (). At this scale, all the selected PTFs exhibited unsatisfactory prediction of (high RMSE, low NSE and ). In the field studied, approximately 60% of variance in could be explained by soil texture and macropore components based on factor analysis. Clay content and macroporosity were identified as the most representative variables for each component. The performance of a PTF in estimating for the field site investigated was significantly improved by including macroporosity (pores with diameter >75 μm) as a predictor. The results confirmed that soil structure was crucial in characterizing soil hydraulic conductivity.https://dl.sciencesocieties.org/publications/vzj/articles/18/1/180151
collection DOAJ
language English
format Article
sources DOAJ
author Xi Zhang
Junfeng Zhu
Ole Wendroth
Christopher Matocha
Dwayne Edwards
spellingShingle Xi Zhang
Junfeng Zhu
Ole Wendroth
Christopher Matocha
Dwayne Edwards
Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
Vadose Zone Journal
author_facet Xi Zhang
Junfeng Zhu
Ole Wendroth
Christopher Matocha
Dwayne Edwards
author_sort Xi Zhang
title Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
title_short Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
title_full Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
title_fullStr Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
title_full_unstemmed Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
title_sort effect of macroporosity on pedotransfer function estimates at the field scale
publisher Wiley
series Vadose Zone Journal
issn 1539-1663
publishDate 2019-05-01
description Saturated hydraulic conductivity () is one of the crucial hydraulic properties for assessing water and solute transport in soils. However, direct measurement of is time consuming and arduous. Alternatively, pedotransfer functions (PTFs) have been developed to estimate indirectly through more easily measurable soil properties that are part of regional, national, or international databases. These PTFs are usually based on datasets collected from large regions. However, their validity for a specific site remains unclear. The objectives of this study were to evaluate the performance of established PTFs in estimating in a specific field and improve PTFs to arrive at a locally adapted estimation result for . Forty-one soil samples were collected from 10 locations at five depths at a farmland in western Kentucky for hydraulic conductivity and physical property measurements. The performance of seven PTFs in estimating was evaluated using the root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (). At this scale, all the selected PTFs exhibited unsatisfactory prediction of (high RMSE, low NSE and ). In the field studied, approximately 60% of variance in could be explained by soil texture and macropore components based on factor analysis. Clay content and macroporosity were identified as the most representative variables for each component. The performance of a PTF in estimating for the field site investigated was significantly improved by including macroporosity (pores with diameter >75 μm) as a predictor. The results confirmed that soil structure was crucial in characterizing soil hydraulic conductivity.
url https://dl.sciencesocieties.org/publications/vzj/articles/18/1/180151
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