Document Type : Research Paper

Abstract

Soil hydraulic properties are key soil physical characteristics that are required to conduct soil and water related studies such as irrigation and drainage. In this study, three indirect methods: inverse modeling, pedo-transfer function, and the semi-physical method of Arya et al., were compared in a sandy loam soil to estimate soil moisture retention and unsaturated hydraulic conductivity curves. Subsequently, they were applied to simulate soil moisture in irrigated furrows. In the indirect methods, soil hydraulic properties were estimated from easily measured soil data. Using the neural network-based pedo-transfer function of ROSETTA code, soil hydraulic parameters were obtained from soil textural fractions (percentage of sand, silt and clay), bulk density, and two water retention points as input. In the inverse method, the most sensitive soil hydraulic properties were estimated using the Levenberg-Marquardt optimization algorithm in combination with the HYDRUS-2D numerical code. In the semi-physical method, both soil retention and unsaturated hydraulic conductivity curves were predicted from a particle size distribution curve. The predicted soil hydraulic properties were applied to simulate soil moisture below the irrigated furrows during two subsequent irrigations. The results showed that the inverse modeling and Arya et al. methods predicated the soil water content well in the experimental furrows while the pedo-transfer function of ROSETTA overestimated soil water content.

Keywords

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