When nature meets technology: AI-informed discovery of soil-water-root physical interaction

Abstract

Nature-based solution using vegetation has been considered as a sustainable and environmentally friendly approach to improve slope performance through root reinforcement and variations of soil matric suction upon transpiration. During plant growth, roots explore soil pore space. How fundamentally the pore structure might evolve with time following root growth dynamics and how this dynamic soil-root interaction may modify the hydraulic properties of unsaturated soils remain unclear. This paper reports the use of advanced technologies including artificial intelligence (AI) to aid the discovery of soil-root-water physical interaction and the characterisation of the hydraulic properties of rooted soils. A newly developed miniature unsaturated triaxial apparatus that enables rooted soil samples to subject to simultaneous in-situ loading and X-ray imaging is introduced. An AI-informed image processing technique is illustrated, aiming to enhance the reliability of phase segmentation of X-ray computer tomography (CT) images of four-phase unsaturated rooted soils for quantifying 3-D pore structure and root phenotype. New discoveries of how roots interact with the pore space, including the dynamic changes in the distribution, orientation and connectivity of soil pore sizes, and how this pore-level information can be used to explain the hydraulic properties are discussed.