Abstract
Rainfall is a major triggering factor of shallow landslides in mountainous and steep terrain all over the world. The main mechanism of shallow landslides is that the water infiltration may generate pore-water pressure resulting in a decrease of the shear strength of the soil in the potential sliding zone. Therefore, a better knowledge regarding the soil moisture responding to the water infiltration is the key to effectively predict the occurrence of the rainfall-induced shallow landslides. In this work, a 1-D slope soil column model is developed to investigate the soil moisture response to the water infiltration into a slope, for the purpose to predict shallow landslides. During the artificial rainfall, the moisture content at different soil depths and pore water pressure at the bottom of the soil column are monitored. The downward process of the wetting front and the rising of the groundwater level are recorded. It is found that the increase of the degree of saturation Sr can be separated to two steps: 1) Sr increases from the initial state to a critical value due to the water infiltration, and then keeps constant for a long period; 2) Sr increases again until the fully saturated state is reached due to the rising of the groundwater level. Using the monitoring data, the downward infiltration rate of the water and the upward rising rate of the groundwater level are calculated. The results show that both rates are proportional to the artificial rainfall intensity. Based on the monitoring data, an empirical model is proposed to predict the distribution and temporal evolution of soil moisture content in the soil. The model parameters are calibrated and the performance of the empirical model is evaluated. The results show that the proposed model can predict the distribution and evolution of soil moisture at different rainfall intensities, and show the possibility to predict shallow landslides by means of the soil moisture monitoring in field.
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