LAUSR

A rising level of groundwater is a critical trigger for deep-seated landslides. Accordingly, an effective measure to improve the stability of a landslide is to reduce the groundwater level of a slope by using a drainage system. This study investigates the effectiveness of drainage tunnels in increasing the rainfall threshold of a deep-seated landslide. Monitoring results show that the movement of the landslide is highly sensitive to the prevailing groundwater level (GL), and the value of GL has a direct connection with the movement of a slope. Based on continuous monitoring of data of groundwater level (GL) and precipitation, the Particle Swarm Optimization Support Vector Machine (PSO-SVM) model was developed to predict GL based on antecedent rainfall. The calculated results show that the performance of the PSO-SVM model is acceptable. Using intensity-duration-frequency (IDF) analysis and the PSO-SVM model, the rainfall threshold of the landslide in this study was estimated to range from 63 to 78 mm before the drainage tunnel was completed. This contrasted with a rainfall threshold ranging from 144 to 162 mm after the drainage tunnel was completed. This shows that the construction of a drainage tunnel increased the rainfall threshold of the landslide significantly, nearly doubling it.