The use of field water retention and ambient temperature for developing the soil-water characteristic curve

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.