Study of Rain-Induced Landslides Prediction in Malaysia

Thursday, 18 December 2014
Swee Peng Koay, Universiti Sains Malaysia, Seberang Perai, Malaysia, Habibah Lateh, Universiti Sains Malaysia, Penang, Malaysia, Hiroshi Fukuoka, Niigata University, Niigata, Japan, Naoki Sakai, Earth Science and Disaster Pre, Tsukuba, Japan, Satoshi Murakami, Ibaraki University, Mito, Japan, Tomofumi Koyama, Kansai University, Osaka, Japan and Suhaimi bin Jamaludin, Public Works Department Malaysia, Kuala Lumpur, Malaysia
In Malaysia, rain-induced landslides are occurring more often recently. Millions of Malaysian Ringgit are allocated for risky slope monitoring and slope failure measurement in the government budget every year.

However, there are thousands of slopes which are classified as dangerous slopes, and implementing site monitoring system in all slopes, with physical devices, to monitor the movement of the soil in the slopes are too costly and almost impossible.

In our study, we propose 2 methods to predict the slope failure, which are (1)Accumulated Rainfall vs. Rainfall Intensity and (2)Working Rainfall vs. Rainfall Intensity, with water table drawdown period consideration. The curve of jointed data will be reset to 0 if the rain stop period is longer than the period of water table drawdown to pre-rain level.

The critical line, in these 2 methods, which determines if the slope is in a risk state, should be generated by collecting historical landslides data. However, unlike the other developed countries, a complete historical landslides data in Malaysia is difficult to be obtained. We propose that the critical line is drawn by referring to the simulation result of the factor of slope stability F, with the slope parameters and rainfall data, to cover the uncompleted historical landslides data. If the curves cross over the critical line, the probability of slope failure is considered high.

In this study, the proposed methods managed to show that 2 occurrences of landslides, in Malaysia, could be predicted if it was applied earlier. In future, further study on fine tuning of these two methods and selecting the more accuracy method from these two methods may assist the government authorities to judge the movement of the slopes before disseminating data and information for early warning system.