Inverse estimation of the soil water retention curve parameters using double-ring infiltration data

Document Type : Original Article

Abstract

Quantitative knowledge of soil water characteristic curve is crucial for modeling water flow and transport processes in agriculture and hydrology. In this study, HYDRUS2D/3D software was used to estimate the hydraulic parameters of van Genuchten-Mualem model via inverse modeling using double-ring infiltrometers. Double-ring infiltration experiment was conducted in three sites with different soil textures (i.e., silty clay, loam and sandy loam) with three replications. Disturbed and undisturbed soil samples were also collected from three depths (0−10, 10−30 and 30−60 cm) per each soil and some soil physical properties such as bulk density, texture, initial water content and saturated water content were measured. Soil water retention curve was determined for the matric suctions lower than 100 cm H2O by sand box, and for the matric suction range 100−15000 cm H2O using pressure plate. The van Genuchten model with Mualem’s restriction was fitted to the soil water retention data by RETC software. The accuracy and reliability of the HYDRUS predictions were evaluated. The results showed that inverse estimation of soil hydraulic parameters provided a reliable alternative method for determining the soil water retention curve at horizon/field scale. The soil water retention curves obtained from the RETC fitting had very good correspondence with those derived from inverse modeling; the efficacy parameters of inverse estimation (i.e., Pearson’s correlation coefficient (r), root of mean squared differences (RMSD, m3 m-3), absolute value of mean differences (AMD, m3 m-3) and the mean difference (MD, m3 m3)) were 0.988, 0.036, 0.012 and 0.008, respectively. Also there was a good agreement between the water content values measured in the soil profile and those predicted by HYDRUS (R2= 0.936).

Keywords

References

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Applied Soil Research
Volume 4, Issue 2
February 2017
Pages 26-37

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History

  • Receive Date: 05 April 2016
  • Revise Date: 10 December 2016
  • Accept Date: 07 February 2017

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