The hydro-mechanical properties of the vadose zone are strongly influenced by seasonal cycles. The hydraulic behavior of this zone is determined by the coupling of biotic and abiotic factors. The biotic factors are controlled by the physiology and anatomy of the vegetation growing in the area, while the abiotic factors depend on the local soil characteristics, such as water content, void ratio, and matrix structure. In this laboratory-scale investigation, we assess the influence of active biomass, water content, and suction on the particle and pore structure rearrangement. We use x-ray computed tomography and 3D digital image correlation to quantify plant roots at different stages of growth, soil deformation, and water content fluctuations. Our results show that the bulk porosity of vegetated soil is strongly affected by the induced water cycles. The global micro-structure rearrangement due to the double effects of plant water uptake and induced drying-wetting cycles translates into a final bulk porosity increase.

The integrity and performance of geo-infrastructures have been receiving growing attention in the last two decades. Differential settlements are critical forms of distresses that lead to loss of functionality and even failures. Differential settlement is typically initiated by uncontrolled waste dumping and uncompacted fills coupled-exacerbated seasonal volumetric soil changes triggered by wetting and drying cycles. Therefore, it is paramount to continuously monitor load-deformation patterns without interrupting usage. It is also vital to consider the effect of vegetation and meteorological factors on soil properties. More data is needed to build robust correlations between basic soil properties/characteristics, vegetation, weather, and hydraulic properties of soils. Despite recognizing the significance of the long-term effects of vegetation and climate on soil's behavior, very modest effort has been invested in developing intelligent systems and models that allow for the prediction of soil parameters in relation to water retention and stress-deformation characteristics using the input of vegetation and atmospheric parameters. This study uses field and laboratory testing to develop a predictive model encompassing quantified environmental and vegetation factors. The program employed field monitoring sensors measuring soil water potential and soil moisture with varying proximity to the vegetation. Real-time data collected by the field sensors and thermal imaging assisted in postulating a quantified relation between a radial fluctuation of the soil suction from the tree roots and the vegetation parameters. Upon laboratory verification, these relationships were processed to develop a graphical model to represent the quantification of the varying soil suction with climatic and vegetative parameters. The model's outcome supports the design of geotechnical infrastructure, especially through evaluating soil water retention without disrupting the natural habitat.