Moisture content is the most important factor affecting the stability of slopes against heavy rainfall events. In most of risk management methods for slope disasters, the rainfall intensity is used as the dominant index to evaluate the probability of failure events in an area. However, each slope should have individual hydraulic characteristics, and its probability of failure should be different from other slopes even under the same rainfall conditions. Some slope may contain a lot of water quickly after starting of rainfall, while some slope may show quick drainage after it stopped to rain. Such individual properties of each slope can be evaluated by observing the time histories of moisture contents in the slope ground together with rainfall records. In this paper, an attempt to establish a mathematical model on drainage process in a slope ground is reported. There is a simple relationship between the current moisture contents and the drainage rate of moisture, although this relation is affected by the adjacent rainfall intensity. The drainage properties of a slope can be evaluated by watching the behaviors of moisture contents at rainfall events with relatively low intensity. And the model parameters obtained by such weak rainfall events can be used to estimate the drainage rate after heavy rainfall events with some correction of the parameters, by using real time monitoring system.

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Monitoring and early warning is one of the most effective methods toward reduction of accident induced by landslide and slope failure during rainfall. The traditional methods such as extensometers and bore-hole inclinometers are common monitoring ways, but the traditional equipment is expensive and not easy to install in field site. The authors have developed wireless sensor units with Micro Electro Mechanical Systems (MEMS) tilt sensor and volumetric water content sensor and proposed an early warning system as one of more feasible countermeasures to avoid slope failure accident. The warning system including developed tilt sensor unit, has been deployed in several actual slopes for validation and verification of field performance in Japan.

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Slope failures are major natural disasters in Hiroshima prefecture, Japan under intense rainfall conditions. Both people and property were affected severely due to these disastrous events during past few decades. 32,000 planar slopes and valleys were susceptible to failure in Hiroshima prefecture, Japan have been identified by Hiroshima prefectural government and was developed a hazard assessment system thoroughly based on rainfall and past records of the data. However, the developed system can only be accommodated in a large area 5 km x 5km grid, and not be possible to predict the individual slope failure in the region. Geotechnical investigation of natural slopes is challengeable especially when natural slopes having higher gradients and access is difficult and also to estimate shear strength parameters spatially. Recently, authors have conducted a series of in-situ investigations based on the newly developed lightweight dynamic cone penetrometer to examine its applicability in analyzing the slopes covered with weathering remnants of granitic rocks. Six patterns were identified based on the penetration resistance varying with the depth. Semi-variogram analysis showed that the correlated distance of cone resistance varies with 11 to 30 m depending on the depth. A series of laboratory calibration tests based on the lightweight dynamic cone penetration tests, and direct shear tests were conducted at different void ratios and degrees of saturation. Based on the laboratory calibration test results, a method of determining void ratio, e from the data of q_d was presented. Based on this, two formulas to evaluate shear strength parameters, cohesion and friction angle, were established with the cone resistance and the degree of saturation. As a whole proposed method can be successfully applied to individual slopes to determine the profile thickness, and to evaluate the shear strength parameters spatially. Based on this, hazard assessment of individual slopes can be made.

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As global warming brings forth extreme precipitation in the typhoon-prone region in Asia, e.g. Hong Kong, Taiwan and Japan, the need for a scalable and yet accurate landslide sensing system becomes increasingly urgent. Natural slopes are the focus since their failures are often large-scale and disastrous; however, it is extremely expensive to monitor every single hazardous natural slope in existence with the current monitoring system. The MEMS (Micro-Electro-Mechanical Systems) technology which makes miniature yet accurate sensors available (e.g. accelerometer, gyroscope and magnetometer), will be pivotal towards the realization of a scalable landslide warning system. In this paper, we present the Smart Soil Particle (SSP) sensing system we build to detect the precursory tilts of a large-scale potential landslide site in LuShan, Taiwan. The SSP consists of the sensing module (i.e., low-noise MEMS accelerometer and a motion sensor) and the processing module (Raspberry Pi, a single-board computer). Both cost less than HKD$850; the price makes it possible to deploy a huge amount of SSPs on the slope surface without the fear of losing any. The processing module is capable of handling a large programmable data transfer rate (up to 800 samples/second/channel) through a 3G modem. In the back-end is a decentralized structured data storage system constructed to handle the massive data inflow from multiple SSPs. The whole system is built to send and receive data at a near real-time speed. With a proper noise control and shielding of the wires, we show that the low-noise SSPs are able to capture a small earthquake and also tiny vibrations due to cars passing by.

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A non-welded part of pyroclastic flow, Shirasu in Japanese, is widely distributed on the ground surface in Kagoshima Prefecture. The slopes composed of Shirasu and other volcanic products often fail due to heavy rain in the rainy season. In order to prevent natural disasters due to shallow landslides, six test field points, where past occurrence of landslides due to heavy rainfall was identified, have been determined in the Takakuma experimental forest of Kagoshima University. In this study, site investigation and in situ tests on shallow landslide scars of Shirasu natural slopes are conducted to investigate the stability of the slopes and the effect of revegetation and soil development of forest topsoils from the viewpoint of forest ecology and geotechnical engineering. In the site investigation, the growth condition of forest trees, the measurement of dry density of topsoil and investigation using soil augers are carried out. Furthermore, simple dynamic cone penetration test and the investigation of slope topsoil using a soil strength probe are performed in situ.

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Probable Maximum Precipitation (PMP), which is an extreme rainfall level widely used for dam and reservoir engineering, has been taken as a practical reference for expressing extreme rainfall events for formulating landslide scenarios in Hong Kong’s landslide emergency preparedness. Landslide hazards had been assessed based on scenarios corresponding to 90% of the 24-hour PMP, which was estimated by Hong Kong Observatory in 1999. The results indicated that more than 3,000 landslides affecting buildings or roads would occur if Hong Kong Island is struck by a storm of this level of rainfall. An updating of the 24-hour PMP has recently been carried out using the method of storm transposition. In this method, the major storm associated with Typhoon Morakot, which lashed Taiwan seriously in 2009, was targeted to be transposed to Hong Kong. Based on the Step Duration Orographic Intensification Factor (SDOIF) Method, storm separation technique was applied to separate the convergence component from the orographic component of the major storm and the convergence component was transposed and then combined with the local orographic factors in Hong Kong for PMP estimate. This paper will present the method adopted in the transposition and discuss the results for the updating of the PMP estimate. The assessment of the landslide scenarios corresponding to the updated PMP will also be discussed.

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This paper presents a case study of Taipingshan landslide triggered by Typhoon Saola. The Taipingshan villa is one of the most famous scenic spots at Taipingshan National Forest Recreation Area in northern Taiwan. Since early 1990s, the unstable appearances of slopes had occurred frequently in the study area, such as tension cracks, ground settlements, man-made structures cracking…etc. Therefore, a series of geological investigations and in-site/laboratory tests were carried out to estimate the slope stability and predict the rainfall threshold of landslides in 2010. The results show that the critical rainfall threshold of the case study is around 1,765 mm. In 2012, however, Typhoon Saola brought tremendous rainfall to hit eastern Taiwan. The main scarp of sliding mass B located at the History Exhibition Hall in the study area. According to in-situ extensometer data, the broken moment of extensometer shows that the real accumulated rainfall which triggered this landslide is 1,694 mm. The results of coupled analysis have been demonstrated in good agreement from the field monitoring data during the typhoon event. Our preliminary results appear to be useful for assessing the rainfall threshold of landslides. The findings can also be a good reference to establish an early warning system of landslides.

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