Estimation of van Genuchten Equation Parameters in Laboratory and through Inverse Modeling with Hydrus-1D

Abstract

Soil water retention curve (SWRC) becomes important because it guides when and how much to irrigate, optimizing the use of water; can be obtained in the field or laboratory, being commonly determined in the laboratory with porous plate apparatus, and the determination is compromised by issues such as time and labor. In this context, inverse modeling emerges, which allows to obtain a variable going from the effect to the cause, using Hydrus-1D. Hence, this study aims to obtain van Genuchten equation parameters through inverse modeling with Hydrus-1D and make the respective comparisons and inferences. Matric potential data were obtained over time in an instantaneous profile-type experiment. Six sets of three tensiometers each were installed surrounding the center of the experimental plot, at depths of 0.20, 0.35 and 0.50 m. Target depth was 0.35 m, where the roots of most crops are concentrated, and the other tensiometers were used to obtain the potential gradient. Matric potential data were used to feed Hydrus-1D and obtain the van Genuchten equation parameters. Laboratory curves were obtained using porous plate apparatus, with four replicates. It was concluded that, in general, the Hydrus-1D model estimates van Genuchten equation parameters and, consequently, the SWCC of an Argissolo more consistently with field conditions than those obtained in the laboratory; and, provided it is fed with field data, the Hydrus-1D simulates well the behavior of matric potential and moisture over time, reducing the time and labor in the procedures to obtain van Genuchten equation parameters in the laboratory.

Assessing the influence of cover crop on soil water dynamics using soil moisture measurements and hydrus‐1D simulations

“…Furthermore, it is interesting to observe if Hydrus-1D could be used to simulate water flow for a CC system. Hydrus-1D is widely used in the estimation of soil hydraulic parameters using laboratorymeasured soil water retention data (Nascimento et al, 2018) and tension disc infiltrometer data in the field (Abd Rashid et al, 2015). Ket et al (2018) recently used in-situ dynamic soil moisture and soil water potential data to obtain soil water retention curve by inverse modeling approach of Hydrus-1D.…”

“…Furthermore, it is interesting to observe if Hydrus‐1D could be used to simulate water flow for a CC system. Hydrus‐1D is widely used in the estimation of soil hydraulic parameters using laboratory‐measured soil water retention data (Nascimento et al., 2018) and tension disc infiltrometer data in the field (Abd Rashid et al., 2015). Ket et al.…”

Parameter Estimation for Soil Water Retention Curve Using the Salp Swarm Algorithm

“…Chen et al [21] used the Monte-Carlo method to analyze the sensitivity of the parameters and uncertainty of the van Genuchten model to obtain the key parameters and a posteriori parameter distribution to guide the parameter identification, and a new type of intelligent algorithm-difference search algorithm was then employed to identify these parameters. Nascimento et al [22] estimated the parameters of the van Genuchten model using the inverse modeling function of Hydrus-1D, and the results revealed that the Hydrus-1D can simulate well the behavior of matric potential and moisture over time if the field data is fed.…”

Evaluating the effect of initial soil moisture content on the infiltration characteristics using Empirical and Hydrus 1D Models

“…The calibration of soil hydraulic parameters (ϴr, α, ϴs, Ks, and n) for the two layers was optimized initially through pedotransfer function using field data such as percentage of particle size, bulk density, field capacity, permanent wilting point, and initial soil moisture content values. To determine soil hydraulic parameters θr, θs, α, n, and Ks were further calibrated using inverse optimization techniques [14]. By using observed soil water.…”