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Hans Estrup Andersen

Quantification of macropore flow in Danish soils using near-saturated hydraulic properties

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Quantification of macropore flow in Danish soils using near-saturated hydraulic properties. / Kotlar, Ali Mehmandoost; de Jong van Lier, Quirijn; Andersen, Hans Estrup; Nørgaard, Trine; Iversen, Bo V.

In: Geoderma, Vol. 375, 114479, 10.2020.

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@article{e506b5010df947d1bc2307d28dc6e527,
title = "Quantification of macropore flow in Danish soils using near-saturated hydraulic properties",
abstract = "Larger pores allowing macropore flow can rapidly transport contaminants as well as nutrients from the soil surface to the subsoil and groundwater. Modeling of the involved macropore flow is complex due to large number of required parameters. One way to deal with this difficulty is the precise evaluation of the soil hydraulic conductivity function using robust pedotransfer functions for the near-saturated part. Aiming to develop pedotransfer functions to estimate saturated and unsaturated hydraulic conductivities [Ks and K(h)] as well as water contents at specific pressure heads, we used Gaussian Process Regression (GPR), a non-parametric machine learning model, to obtain van Genuchten (1980) retention and conductivity parameters for Danish soils based on soil texture and organic matter. We defined K10 as K(h) at − 10 cm pressure head. The difference between the logarithm of Ks and K10 [log(Ks) − log(K10)] was denominated log(Kjump) and was assumed to convey the potential degree of macropore flow considering only soil hydraulic properties. Macropore flow in Denmark was evaluated through the developed PTFs for log(Ks) and log(K10) with an average RMSE of 0.635 and 0.594 (for K in cm d−1) under a confidence interval obtained by bootstrapping. Dynamics of pressure head in an initially saturated soil column with a zero-flux top boundary condition and a 2 m deep groundwater level were simulated using the Hydrus-1D model. The result of this modeling showed that soils in the eastern part of Denmark had a higher likelihood to experience macropore flow. Finally, using the spatial distribution of meteorological data, a macropore flow map of Denmark was produced. Precipitation was a dominating factor on macropore flow in sandy clay loam and sandy loam soils when compared to sandy and loamy sand soils. Finally, maps of relative risk classes of macropore flow qualitatively differentiated land areas in Denmark for vulnerability of nutrient loss and groundwater contamination.",
keywords = "Drip infiltrometer, Hydrus-1D, Macroporosity, Pedotransfer functions, Unsaturated hydraulic conductivity",
author = "Kotlar, {Ali Mehmandoost} and {de Jong van Lier}, Quirijn and Andersen, {Hans Estrup} and Trine N{\o}rgaard and Iversen, {Bo V.}",
year = "2020",
month = oct,
doi = "10.1016/j.geoderma.2020.114479",
language = "English",
volume = "375",
journal = "Geoderma",
issn = "0016-7061",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Quantification of macropore flow in Danish soils using near-saturated hydraulic properties

AU - Kotlar, Ali Mehmandoost

AU - de Jong van Lier, Quirijn

AU - Andersen, Hans Estrup

AU - Nørgaard, Trine

AU - Iversen, Bo V.

PY - 2020/10

Y1 - 2020/10

N2 - Larger pores allowing macropore flow can rapidly transport contaminants as well as nutrients from the soil surface to the subsoil and groundwater. Modeling of the involved macropore flow is complex due to large number of required parameters. One way to deal with this difficulty is the precise evaluation of the soil hydraulic conductivity function using robust pedotransfer functions for the near-saturated part. Aiming to develop pedotransfer functions to estimate saturated and unsaturated hydraulic conductivities [Ks and K(h)] as well as water contents at specific pressure heads, we used Gaussian Process Regression (GPR), a non-parametric machine learning model, to obtain van Genuchten (1980) retention and conductivity parameters for Danish soils based on soil texture and organic matter. We defined K10 as K(h) at − 10 cm pressure head. The difference between the logarithm of Ks and K10 [log(Ks) − log(K10)] was denominated log(Kjump) and was assumed to convey the potential degree of macropore flow considering only soil hydraulic properties. Macropore flow in Denmark was evaluated through the developed PTFs for log(Ks) and log(K10) with an average RMSE of 0.635 and 0.594 (for K in cm d−1) under a confidence interval obtained by bootstrapping. Dynamics of pressure head in an initially saturated soil column with a zero-flux top boundary condition and a 2 m deep groundwater level were simulated using the Hydrus-1D model. The result of this modeling showed that soils in the eastern part of Denmark had a higher likelihood to experience macropore flow. Finally, using the spatial distribution of meteorological data, a macropore flow map of Denmark was produced. Precipitation was a dominating factor on macropore flow in sandy clay loam and sandy loam soils when compared to sandy and loamy sand soils. Finally, maps of relative risk classes of macropore flow qualitatively differentiated land areas in Denmark for vulnerability of nutrient loss and groundwater contamination.

AB - Larger pores allowing macropore flow can rapidly transport contaminants as well as nutrients from the soil surface to the subsoil and groundwater. Modeling of the involved macropore flow is complex due to large number of required parameters. One way to deal with this difficulty is the precise evaluation of the soil hydraulic conductivity function using robust pedotransfer functions for the near-saturated part. Aiming to develop pedotransfer functions to estimate saturated and unsaturated hydraulic conductivities [Ks and K(h)] as well as water contents at specific pressure heads, we used Gaussian Process Regression (GPR), a non-parametric machine learning model, to obtain van Genuchten (1980) retention and conductivity parameters for Danish soils based on soil texture and organic matter. We defined K10 as K(h) at − 10 cm pressure head. The difference between the logarithm of Ks and K10 [log(Ks) − log(K10)] was denominated log(Kjump) and was assumed to convey the potential degree of macropore flow considering only soil hydraulic properties. Macropore flow in Denmark was evaluated through the developed PTFs for log(Ks) and log(K10) with an average RMSE of 0.635 and 0.594 (for K in cm d−1) under a confidence interval obtained by bootstrapping. Dynamics of pressure head in an initially saturated soil column with a zero-flux top boundary condition and a 2 m deep groundwater level were simulated using the Hydrus-1D model. The result of this modeling showed that soils in the eastern part of Denmark had a higher likelihood to experience macropore flow. Finally, using the spatial distribution of meteorological data, a macropore flow map of Denmark was produced. Precipitation was a dominating factor on macropore flow in sandy clay loam and sandy loam soils when compared to sandy and loamy sand soils. Finally, maps of relative risk classes of macropore flow qualitatively differentiated land areas in Denmark for vulnerability of nutrient loss and groundwater contamination.

KW - Drip infiltrometer

KW - Hydrus-1D

KW - Macroporosity

KW - Pedotransfer functions

KW - Unsaturated hydraulic conductivity

UR - http://www.scopus.com/inward/record.url?scp=85085739911&partnerID=8YFLogxK

U2 - 10.1016/j.geoderma.2020.114479

DO - 10.1016/j.geoderma.2020.114479

M3 - Journal article

AN - SCOPUS:85085739911

VL - 375

JO - Geoderma

JF - Geoderma

SN - 0016-7061

M1 - 114479

ER -