Assessment of the coupled effects of vegetation leaf and root characteristics on soil suction: an integrated numerical modeling and probabilistic approach

Root depth and leaf area ratio are two important features of a plant and exhibit a coupled relation. Assessing their coupled effects on induced soil suction is essential for analyzing the performance of a green infrastructure, such as water storage/drainage in green roofs and stability of a vegetated slope. Previously soil moisture induced by vegetation was often presented deterministically without considering the overall effects of leaf and root characteristics in a probabilistic manner. The main objective of this study is to investigate the influence of coupled variations in root and leaf characteristics on vegetation-induced soil suction. In addition, the coupled effects were analyzed using statistical approach. Different combinations of the leaf area index and root depth of the same plant were assessed. Probabilistic analysis was then conducted by computing suction profiles in form of quantiles. It was found that the biggest variability in suction profiles occurs at around 0.6 times the root depth and the minimum occurred at near surface and at maximum root depth. This depth at 0.6 times root depth corresponds to the maximum root density. It implies that the probabilistic analysis becomes more and more important while assessing suction profiles near the maximum root density.