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.
Water covers most of the Earth’s surface and is nowhere near a good ecological or recreational state in many areas of the world. Moreover, only a small fraction of the water is potable. As climate change-induced extreme weather events become ever more prevalent, more and more issues arise, such as worsening water quality problems. Therefore, protecting invaluable and useable drinking water is critical. Environmental agencies must continuously check water sources to determine whether they are in a good or healthy state regarding pollutant levels and ecological status. The currently available tools are better suited for stationary laboratory use, and domain specialists lack suitable tools for on-site visualisation and interactive exploration of environmental data. Meanwhile, data collection for laboratory analysis requires substantial time and significant effort. We, therefore, developed an augmented reality system with a Microsoft HoloLens 2 device to explore the visualisation of water quality and status in situ. The developed prototype visualises geo-referenced sensor measurements incorporated into the perspective of the surroundings. Any users interested in water bodies’ conditions can quickly examine and retrieve an overview of water body status using augmented reality and then take necessary steps to address the current situation.