Campus Units

Agronomy

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

3-14-2019

Journal or Book Title

Journal of Hydrology

DOI

10.1016/j.jhydrol.2019.03.027

Abstract

The Mualem-van Genuchten model has been widely used for estimating unsaturated soil hydraulic conductivity (Ku) from measured saturated hydraulic conductivity (Ks) and fitted water retention curve (WRC) parameters. Soil bulk density (ρb) variations affect the accuracy of Ku estimates. In this study, we extend the Mualem-van Genuchten model to account for the ρb effect with ρb-related WRC and Ks models. We apply two functions (A and B) that relate the van Genuchten WRC model to ρb and two models (1 and 2) that estimate Ks with various ρb. By combining the ρb-related WRC functions and Ks models, we develop four integrated approaches (i.e., A1, A2, B1, and B2) for estimating Ku at various ρb. Kumeasurements made on five soils with various textures and ρb are used to evaluate the accuracy of the four approaches. The results show that all approaches produce reasonable Ku estimates, with average root mean square errors (RMSEs) less than 0.35 (expressed in dimensionless unit because logarithmic Ku values are used). Approach A2, with an average RMSE of 0.25, agrees better with Ku measurements than does Approach A1 that has an average RMSE of 0.28. This is because Model 2 accounts for the WRC shape effect near saturation. Approaches A1 and A2 give more accurate Ku estimates than do Approaches B1 and B2 which both have average RMSEs of 0.35, because Function A performs better in estimating WRCs than does Function B. The proposed approaches could be incorporated into simulation models for improved prediction of water, solute, and gas transport in soils.

Comments

This is a manuscript of an article published as Tian, Z., Kool, D., Ren, T., Horton, R., Heitman, J.L., Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model, Journal of Hydrology (2019), doi: 10.1016/j.jhydrol.2019.03.027.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier B.V.

Language

en

File Format

application/pdf

Available for download on Saturday, March 14, 2020

Published Version

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