Monitoring of slow moving landslide at 46th km of Simpang Pulai Gua Musang highway, Malaysia

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1 Landslides and Engineered Slopes: Protecting Society through Improved Understanding Eberhardt et al. (eds) 2012 Taylor & Francis Group, London, ISBN Monitoring of slow moving landslide at 46th km of Simpang Pulai Gua Musang highway, Malaysia S. Jamaludin, C.H. Abdullah & K.B. Jaafar Slope Engineering Branch, Public Works Department, Malaysia M. Anuri Geotechnical Department, KISB, Malaysia ABSTRACT: A series of localized landslides have occurred since the beginning of construction of a cut slope at 46th kilometer of the Simpang Pulai Kuala Berang highway project, a mountainous area in the State of Perak, Malaysia. In August 2007, crack or head scrap of the landslide was observed 70 m above the Right-Of-Way (ROW) of the construction with about 3 m displacement. To manage landslide risk faced by road users, surface movement was manually monitored using total station on daily basis since the middle of December Starting from January 2010, an early warning system using automatic or robotic total station with 30 minutes frequency survey was established, replacing manually method used before. Warning criteria was developed based on movement pattern as mentioned by Varnes in 1978, Saito linearity and modified velocity scale or classes according to Cruden and Varnes in INTRODUCTION The highway connecting Simpang Pulai in State of Perak to Kuala Berang in the State of Trengganu is the second East-West Coast Highway (Fig. 1). Construction of the highway was divided into 8 packages, traversing through mountainous terrain of Mid-Range. The construction of Package 2 was started in 1997 and was originally scheduled to be completed in However due to a series of major landslide occurrences, the completion and opening of the highway to the public was extensively delayed until This is due to a significant and large landslide that occurred in September 2003 in a newly-cut slope in a mountainous area located at the 44th kilometer as reported by Jamaludin et al. (2008). Beside the 44th kilometer landslide as discussed by Jamaludin et al. (2008), another location i,e, at the stretch between 46th and 47th kilometres of the highway, a series of localise landslides was occurred since the beginning of the earthworks for construction of a cut slopes in To manage landslide risk faced by road users, monitoring of surface movement of the landslide was established as an early warning. Manual survey using total station was started on 14 December 2007, on daily frequency basis. Starting from January 2010, the manual total station was then replaced by automatic or robotic total station with 30 minutes frequency survey. Figure 1. Location of the site. Warning criteria were developed based on two criteria: (i) movement pattern as mentioned by Varnes in 1978 where he divided the movement into three phases: i.e. primary creep, secondary creep and tertiary creep and (ii) velocity scale or classes according to Cruden and Varnes in 1996 where landslide velocity was grouped into 7 scales from 1387

2 Extremely Slow (Velocity Class I) to Extremely Rapid (Velocity Class 7). 2 ABOUT THE LANDSLIDE Generally, the geology of the landslide area is consist of a sequence of metasedimentary rocks, which are confined within a 4 km-wide, and they have been highly deformed and faulted, and have undergone low to medium-grade dynamic metamorphism. The original sedimentary rocks are thought to have been deposited during the Ordovician and deformed and metamorphosed during the late Palaeozoic (Jones 1970). The metasedimentary rocks have been intruded by granite plutons that are predominantly Permian to Jurassic in age. The cut areas were cut into various heights from 24 to 60 m based on road alignment and topographic of the area. Ground water was observed coming from the lower part of the cut slope and horizontal drains were installed to lower down the ground water level. Soil nailing and gunite were installed to stabilise and to protect the cut slope from surface erosion and infiltration. During wet season of late 2006, more ground water and cracks were observed and gunite was starting to detached from the slope face. Work on installing more horizontal drains, longer soil nails and gunite were started in April The works were then stopped due to safety reasons when more prominent displacement was observed. In late August 2007, survey team was deployed to map the crack or head scrap of the landslide which was observed beyond the Right-Of-Way (ROW) of the road construction. The location of the head scarp of the landslide is about 70 m from the ROW (82 m from the as-built top of cut slope and 167 m from centre-line of the road) with 2 m to 3 m displacement. Figures 2 and 3 show the condition of the slope surface at the early stage of failure observed whereas Figure 4 shows the condition of the slope surface in Figure 5 shows the location of the tension crack located 70 m above the ROW of the road. Figure 3. Remedial works was carried out by introducing of horizontal drain, soil nailing and guniting at Ch Figure 4. Photo of the site taken the early 2010 shows all gunite facing was strip-off from slope face. Figure 5. Tension crack observed 70 m beyond construction works. 3 LANDSLIDE MONITORING Figure 2. Early stage of defect observed on slope at Ch Evidence from the past works at the site shows that the landslide problem is too extensive to be taken care by structural reinforcement, and it is not economically justifiable. Further remedial works may not be warranted without a better understanding 1388

3 of the geomorphological, geological and hydrogeological aspects of the site. To manage landslide risk faced by road users, real-time automatic monitoring is a good alternative as an early warning. This monitoring will ensure that the loss of life and damage to property can be minimized. The area is extremely remote in term of data communication and is located in a blind-spot of GSM (Global System for Mobile Communications) mode of communication coverage. Due to that, surface movement was monitored manually, first on 14 December 2007 using a Sokkia SET5E; a surveying instrument which is a combined theodolite and electronic distance measurement device. Six markers (optical prisms) have been surveyed, but unfortunately one of them was damaged from the beginning month of monitoring. Locations of the five remaining prisms are as shown in Figure 6 (P2, P3, P4, P5 and P6). A proper setup of robotic total station or total station with Cyclic Operating System (CYCLOPS); Leica TCA2003 was installed at the site and a first data was automatically captured on 1st January The monitoring system was installed by locally appointed contractor: Konsortium MyStar Communications and SolData (Asia) Ltd from Hong Kong. It was installed in a proper concrete structure building for safety from vandalisms and protection from severe weather at the sites. Due to the nature of the site: thick primary tropical forest beyond constructed area or ROW of the highway and limited line-of-sight, only ten monitoring prisms were installed. Five of them were installed at the same point of the manually monitoring prisms. Figure 6 shows the locations of the 10 optical prisms installed (Fung et al. 2010). Surveys are being carried out at half-hour intervals, automatically controlled by a control station. The control station is a small industrial computer running the Windows operating system fitted with a wireless communication system with satellite communications. The control station is used to programme the automatic total station for the monitoring. The collected survey data are stored on the non-volatile memory in the base station. To overcome communication and power system problem, specially designed satellite communications and power systems were deployed. Satellite Communications, SATCOM was used and its antenna is installed outside and close to the housing. The satellite communication system includes a 1.80 m diameter antenna and a modem. The modem is linked to a network switch and then to an industrial computer, which, in turn directly controls the automatic total station. Figure 7 shows the housing for total station and antenna for satellite communications. Considering of remoteness of the site and unstable weather conditions such as foggy weather and heavy rainfall, properly designed solar power was chosen as the key power supply to the system. Solar panels were installed on the roof of the housing. The survey data collected on site are sent to the Geoscope Web Database located in the Slope Engineering Branch, at the headquarters of the Public Works Department in Kuala Lumpur with the satellite communications. Generally, the Geoscope Web Database consists of 6 modules, namely, Database, Data Acquisition, Alarm, Visualisation, Reporting, and Web Sever. After processing, the interpreted data is then available for display as a web service. It can be viewed with any internet browser equipped with the Geoscope Web Client. The user can open the designated URL in an internet browser to go through the login process as shown in Figure 8. Figure 9 shows graphical presentation of slope movement in form of Cumulative Displacement (Y-axis) versus Date (X-axis). Figure 6. Location of the monitoring prisms (Fung et al. 2010). Figure 7. Housing for total station and antenna for satellite communications. 1389

4 Figure 8. Login page of the monitoring software. Figure 10. The three phase creep model of Varnes (1978). Figure 11. Saito linearity for non-brittle landslide (Petley & Allison 2006). Figure 9. Graphical presentation of slope movement showing a plot of Date (X-axis) versus Cumulative Displacement (Y-axis). 4 WARNING CRITERIA Works by Wang et al. (2005), Petley & Allison (2006) and Chang et al. (2006) are informative papers in the development of prediction model for this landslide. In Wang et al. (2005), they have developed a new prediction model based on generalized model on deep creep theory. Each landslide failure starts from deep creep deformation, towards accelerated creep through a constant strain effect transition. Thus, most predictions of landslides can adopt the creep theory as a physical theoretical basis. As such, the creep is caused by shear stress localization, pore water stress variation, all levels of deviatoric stress, etc. (Fell et al. 2000). Saito developed an innovative approach for predicting the failure time (Saito 1969), which has been extended by other researchers, for example by Fukuzono (1990). Movement pattern as defined by Varnes (1978) was used as a basis for first criteria of monitoring. Varnes (1978) divided stages of movement into 3 stages; i.e. primary creep, secondary creep and tertiary creep (Figure 10). Primary creep represents the initiation of movement and it was characterized by an initially high, but consistently declining, displacement rate. In secondary creep stage the rate of movement is low, but note that it is now accepted that it is not constant. In an ideal system such movement might be described by a power law relationship between displacement rate and time. In tertiary creep the displacement rate increases rapidly as the landslide accelerates to final failure. Monitoring will be continued until there is sign of tertiary creep characteristics developed, and at this stage, as advised by Fell et al. (2000), it is useful to have some guidance on the likely future behavior of the slope, in particular, how long it will take to reach the collapse conditions and at what velocity is collapse imminent. Near-failure prediction is probably the most important aspect of landslide mitigation (Wang et al. 2005). Accordingly, prediction for an active landslide has to be dynamically-based or update-based daily work and a fitting to the monitoring data from the tertiary stage is critical (Wang et al. 2005). Based on that, Saito linearity (Saito 1969) where inverse strain rate versus time plot was used as prediction of time of final failure as suggested by Petley & Allison (2006). Figure 11 shows example of Saito linearity for non-brittle landslide (Petley & Allison 2006). For this monitoring system, similar method; i.e. inverse velocity versus time plot was 1390

5 Table 1. Proposed warning level for the site. Alarm level Typical velocity limit Proposed response Level 1: (Normal situation) Less than 2 mm/hr (slow) Daily data monitoring Level 2: Yellow (advisory) 2 mm/hr to 9 mm/hr (slow) Continuous monitoring, data analysis & review, field observation Level 3: Orange (watch) 9 mm/hr to 18 mm/hr (slow) Increase preparedness, continuous data analysis, inform police/preparedness team Level 4: Red (danger) >18 mm/hr (moderate) Continuous monitoring, decision to be made (to evacuate/close the road) used as the second criteria of monitoring, where at this time movement was monitored very closely: hourly basis. Monitoring data was received automatically by the server, but plotting of Saito linearity graph was performed manually. In cases where there was no time to plot Saito linearity, velocity scale or classes suggested by Cruden & Varnes (1996) was used as a guided for the third criteria of monitoring. Cruden & Varnes (1996) divided landslide velocity into 7 scales from Extremely Slow (Velocity Class I) to Extremely Rapid (Velocity Class 7). To make this velocity scale more practical, it was modified to suite according to the accuracy of the total station, i.e. 1 mm. Table 1 shows the proposed warning level for the site. This proposed warning will be continuously reviewed based on frequency of each warning level and its actual displacement at site. Figure 12. Total displacement of 5 prisms located at the ROW boundary (upper most) taken from 15 Dec until 22 July MONITORING RESULTS AND DISCUSSION As stated earlier, there are 10 monitoring prisms installed at the site, but only 5 prisms were monitored closely i.e. the 5 uppermost prisms located at the boundary of ROW (TP11, TP21, TP31, TP41 and TP51). Cumulative displacement of every prism was plotted against date as shown in Figure 12. Daily rainfall was included in the plotting but unfortunately due to frequent breakdown of the rain-gauge during some critical times, rainfall data cannot be dependable for analysis and warning purposes. At certain duration as shown in Figure 12, wet season will cause change in velocity of the landslide movement. The figure also shows the movement pattern at the early stage was similar to Primary Creep phase as suggested by Varnes (1978), but from the end of 2008 it was difficult to predict. From December 2008, it shows decreasing in velocity but speedup again somewhere in August 2009 until October After resting for several months, it start moving faster again in June The movement gradually increased from June 2010 until May 2011 where it starts to slow again. Figure 13. Inverse velocity versus time plot. Every time that there is change in the rate of movement, similar to approaching tertiary creep, detail monitoring was carried out based on Saito linearity plot. Figure 13 shows inverse velocity versus time plot for critical duration from 23rd June 2010 to 8th July From the plot, the pattern shows it was quite similar to the Saito linearity for non-brittle landslide as discussed by Petley & Allison (2006). This was in agreement to the nature of landslide because the landslide mass was informed of soil slope. Results of monitoring based on velocity for the date from 23rd June 2010 to 8th July 2010 is as shown in Table 2. It shows that at most of the time all prisms fall on alarm Level 1. Only prism PT21 and prism PT41 experienced higher level alarm i.e. three times and one time respectively falls into alarm Level

6 Table 2. Frequency of alarm level reached by each prism for the period from 23rd June 2010 to 8th July Prism Alarm level Level 2 Level 3 Level 4 PT PT PT PT PT Tertiary Creep phase. Inverse velocity plot based on Saito linearity was performed when it enter Tertiary Creep phase and based on plot for critical duration from 23rd June 2010 to 8th July 2010, its shows similar pattern or behavior of the Saito linearity for non-brittle landslide as discussed by Petley & Allison (2006). Monitoring based on velocity during this critical time shows that at most of the time all prisms fall on alarm Level 1. Only prism PT21 and prism PT41 experienced higher level alarm i.e. three times and one time respectively falls into alarm Level 2. None of the prisms reach alarm Level 3 and Level 4. 6 SUMMARY AND CONCLUSION A series of localized landslides occurred since the beginning of the earthworks in 1999 for construction of cut slopes between 46th to 47th kilometres of the Simpang Pulai Kuala Berang road project, in a mountainous area of the State of Perak, Malaysia. From geological aspect, the landslide occurred in residual soil of metasediment formation consisting of mica-schist, graphite schist, quartzite and phyllite which outcrops in a narrow belt contained within the granites which form the mountain range. The cut areas were cut into various heights from 24 to 60 m based on road alignment and topographic of the area. Various measures such as soil nailing, guniting and horizontal drain works were carried out to strengthen the slope and to stop the landslide movement but they didn t work. In late August 2007, survey team was deployed to map the crack or head scrap of the landslide which was observed beyond the Right-Of-Way (ROW) of the road construction. The location of the head scarp of the landslide is about 70 m from the ROW (82 m from the as-built top of cut slope and 167 m from centre-line of the road) with 2 m to 3 m displacement. To manage landslide risk faced by road users, monitoring of surface movement of the landslide was established as an early warning. Manual survey using total station was started on 14 December 2007, on daily frequency basis. Starting from January 2010, the manual total station was then replaced by automatic or robotic total station with 30 minutes frequency survey. Warning criteria was developed based on three criteria: (i) movement patterns divided into three phases: i.e. primary creep, secondary creep and tertiary creep (Varnes 1978), (ii) inverse velocity plot based on Saito linearity (Saito 1969) and (iii) simplified velocity scale or classes according to Cruden & Varnes (1996). Results from monitoring show that in terms of movement pattern it was passing through Secondary Creep phase and at many times it was entering REFERENCES Chang K.T, Mothersille D, Barley T, Ho A & Wang Predicting slope failure using real-time monitoring technology and the TRS sensor. In Proc. of International Conference on Slopes, Malaysia, pp Cruden, D.M. & Varnes, D.J Landslide types and processes. In Turner, K.T, and Schuster, R.L. (eds); Landslides: Investigation and Mitigation. Transportation Research Board National Research Council, Special Report no: 247, Washington D.C Fell, R., Hungr, O., Leroueil, S. & Riemer, W Keynote lecture- Geotechnical engineering of the stability of natural slopes, and cuts and fills in soil. In Geo Eng 2000, pp Fukuzono, T Recent studies on time prediction of slope failure. Landslide News: 4: 9 12 Fung W.H.T, Le Goff D & Krishnan S Instrumentation data monitoring system for slope safety monitoring in Malaysia. In Proc. of the International Conference on Slope Chiang Mai, Thailand, pp Jamaludin, S., Jaafar, K.B., Abdullah, C.H. & Mohamad, A Landslide warning system for Mount Pass, Malaysia based on surface monitoring technique. In Proc. of the International Conference on Management of Landslide Hazard in the Asia-Pacific Region. Sendai, Miyagi Prefecture, Japan, pp Jones, C.R Geology and mineral resources of the Grik Area, Upper Perak. Geological Survey West Malaysia, District Memoir 11. Ministry of Lands and Mines Malaysia. 144p. Petley, D.N. & Allison, R.J On the movement of landslides. In Proc. of International Conference on Slopes, Malaysia, pp Saito, M Forecasting time of slope failure by tertiary creep. In Proc. of the 7th International Conference on Soil Mechanics and Foundation Engineering, Mexico City, Vol.2, pp Varnes, D.J Slope Movement types and processes. In Schuster, R.L., Krizek, R.J. (eds), Landslides Analysis and Control. National Academy of Sciences Transportation Research Board Special Report, 176, pp Wang J.F., Wu F.Q., Su A.J. & Chen Z.Y A generalized model for landslide prediction. In Hungr, Fell, Couture & Eberhardt (eds.), Proc. of The International Conference on Landslide Risk Management, Landslide Risk Management. Balkema, CD W040_Wang. 1392