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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 9 | Copyright
Hydrol. Earth Syst. Sci., 22, 4621-4632, 2018
https://doi.org/10.5194/hess-22-4621-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 Sep 2018

Research article | 04 Sep 2018

Predicting the soil water retention curve from the particle size distribution based on a pore space geometry containing slit-shaped spaces

Chen-Chao Chang1,2 and Dong-Hui Cheng1,2 Chen-Chao Chang and Dong-Hui Cheng
  • 1School of Environmental Sciences and Engineering, Chang'an University, Xi'an, 710054, China
  • 2Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Chang'an University, Ministry of Education, Xi'an, China

Abstract. Traditional models employed to predict the soil water retention curve (SWRC) from the particle size distribution (PSD) always underestimate the water content in the dry range of the SWRC. Using the measured physical parameters of 48 soil samples from the UNSODA unsaturated soil hydraulic property database, these errors were proven to originate from an inaccurate estimation of the pore size distribution. A method was therefore proposed to improve the estimation of the water content at high suction heads using a pore model comprising a circle-shaped central pore connected to slit-shaped spaces. In this model, the pore volume fraction of the minimum pore diameter range and the corresponding water content were accordingly increased. The predicted SWRCs using the improved method reasonably approximated the measured SWRCs, which were more accurate than those obtained using the traditional method and the scaling approach in the dry range of the SWRC.

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The soil water retention curve (SWRC) is fundamental to researching water flow and chemical transport in unsaturated media. However, the traditional prediction models underestimate the water content in the dry range of the SWRC. A method was therefore proposed to improve the estimation of the SWRC using a pore model containing slit-shaped spaces. The results show that the predicted SWRCs using the improved method reasonably approximated the measured SWRCs.
The soil water retention curve (SWRC) is fundamental to researching water flow and chemical...
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