Prediction of wetting pattern dimensions under moistube irrigation with a multivariate nonlinear model

Abstract

Moistube irrigation is a new micro-irrigation technology. Accurately estimating its wetting pattern dimensions presents a challenge. Therefore, it is necessary to develop models for efficient assessment of the wetting transport pattern in order to design a cost-effective moistube irrigation system. To achieve this goal, this study developed a multivariate nonlinear regression model and compared it with a dimensional model. HYDRUS-2D was used to perform numerical simulations of 56 irrigation scenarios with different factors. The experiments showed that the shape of the wetting soil body approximated a cylinder and was mainly affected by soil texture, pressure head, and matric potential. A multivariate nonlinear model using a power function relationship between wetting size and irrigation time was developed, with a determination coefficient greater than 0.99. The model was validated for cases with six soil texture types, with mean average absolute errors of 0.43–0.90 cm, root mean square errors of 0.51–0.95 cm, and mean deviation percentage values of 3.23%–6.27%. The multivariate nonlinear regression model outperformed the dimensional model. It can therefore provide a scientific foundation for the development of moistube irrigation systems.