Susceptibility of Shallow Landslide in Fraser Hill Catchment, Pahang Malaysia. Wan Nor Azmin Sulaiman and Mohd.Hafiz Rosli

Transcription

1 EnvironmentAia The international journal publihed by the Thai Society of Higher Education Intitute on Environment Available online at EnvironmentAia 3(pecial iue) (2010) Suceptibility of Shallow Landlide in Fraer Hill Catchment, Pahang Malayia Wan Nor Azmin Sulaiman and Mohd.Hafiz Roli Department of Environmental Science, Faculty of Environmental Studie, UPM Serdang, Selangor, Malayia Abtract In tropical area epecially during monoon eaon intene precipitation i the main caued that trigger the natural hallow landlide phenomena. Thi phenomenon can be diatrou and widepread in occurrence even in unditurbed foreted catchment. In thi paper, an attempt ha been made to evaluate the uceptibility of natural hill lope to failure for a popular hill reort area, the Fraer Hill Catchment under different rainfall regime and oil thickne. A Digital Elevation Model (DEM) wa prepared for the 8.2 km 2 catchment. A GIS baed determinitic model wa then applied to predict the patial landlide occurrence within catchment. Model input parameter include bulk denity, friction angle, coheion and hydraulic conductivity were gathered through in itu and lab analyi a well a from previou oil analyi record. Landlide location were recorded uing GPS a well a previou air photo and atellite imagery to etablih landlide ource area inventory. The landlide uceptibility map wa produced under different precipitation eventû imulation to ee the effect of precipitation to tability of the hill lope of the catchment. The reult were categorized into naturally untable (Defended, Upper Threhold, Lower Threhold), marginal intability (Quai Stable) and table area (Moderately Stable and Stable). Reult of the imulation indicated notable change in precipitation effect on Defended area i between 10mm to 40mm range in a ingle torm event. However, when torm event i exceeded 120mm, the reult on Defended area produced by the model tend to be contant further on. For area categorized a naturally untable (Factor of Safety, SF<1), with 110mm of precipitation in a ingle torm event and oil depth at 2 meter and 4 meter could affect 69.51% and 69.88% repectively of the catchment area fall under that cla. In addition, the model wa able to detect 4% more of the landlide inventory under hallower oil depth of 2 meter. Keyword: determinitic model; landlide; GIS; lope tability; precipitation threhold. 1. Introduction Landlide i one of natural hazard that often occur all over the world. In tropical climate uch a Malayia, the phenomenon i common epecially in hilly area during monoon eaon. Seriou natural landlide in thi country normally occur in monoon eaon where intene precipitation i the main triggering factor (Jamaludin et al., 2006). Early indication of the lope tability prone area uch a the landlide hazard map may help planner and developer to chooe favorable location for locating development cheme. Careful engineering and geologic tudy could then follow before uch pecific project could be implemented. There are many approache to aeing lope tability and landlide hazard (Sidle et al., 1985; Montgomery and Dietrich, 1989; Carrera et al., 1991; Dietrich et al., 1992; Sidle, 1992; Dietrich et al., 1993; Montgomery and Dietrich, 1994; Pack, 1995). Apparently, GIS have become an eential tool for landlide hazard aement becaue of it ability to incorporate patial data input (Huabin et al., 2005; Van Weten, 2000; Gull et al., 2008). In area which i faced with high intenity rainfall, it i a well known fact that the hydrological factor may influence to certain degree on lope tability in addition to it geology propertie. In thi tudy, a determinitic baed model which combined infinite lope method and teady tate hydrology wa ued to delineate potential hallow landlide area within Fraer Hill catchment. There wa no previou tudy on the apect of landlide prediction for the catchment with the exception of few iolated piecemeal project (IKRAM, 2007) 1.1. Study Area The tudy area i located in Fraer Hill. Fraer Hill i a popular highland reort in Malayia. Landlide occaion that often occur, may dim it potential a a popular hill reort. The Fraer Hill geomorphology i characterized by hilly terrain and mot of the natural lope are teep with 50 gradient (IKRAM, 2007). The range of elevation in Fraer Hill i from 400 to 1300 meter above ea level. According to (Gaim et al., 2001), the mean annual rainfall for the catchment i about 2624 mm with average of 208 rain- day in a year. Baed on exiting geological map, the catchment and it urrounding i mainly compoed by Main Range Granite. The tudy catchment ha an area of 8.2 km 2.

2 Fraer Hill Figure 1. Location of Fraer Hill Catchment (not in cale) 2. Methodology 2.1. Digital Elevation Model (DEM) Topography of an area i the main factor that controlled the landlide procee. Nowaday, patial topography can be repreented in digital form. Digital elevation model i the digital form that repreent the topography of a catchment and it play an important role in repreenting the hape of the land urface for landlide tudy (Carrara & Pike, 2008). DEM can be derived from everal technique. The accuracy of the output of landlide uceptibility map relied heavily on the accuracy of the DEM ource itelf. In thi tudy, DEM wa generated from digital contour digitized from a topographic map in cale of 1: When exported into the model, the pixel of the DEM wa et to 10m x 10m. Fig. 2 how the DEM for the catchment Model Application and Analyi A determinitic baed lope tability model ued to ae the intability condition and to etablih a landlide uceptible map wa SINMAP, developed by Pack et al. (1998). SINMAP wa deigned a an extenion to ArcView GIS, a product of Environmental Sytem Reearch Intitute, Inc. SINMAP i applied to hallow tranitional land liding phenomena controlled by hallow groundwater convergence (Pack et al., 2001). The mathematical model developed by Pack et al. (1998) available for tudying hallow landlide, take into account the infinite plane lope tability model coupled with a teady tate topographic hydrologic model. The infinite lope tability model factor of afety (SF) (ratio of tabilizing to detabilizing force) i given by (implified for wet and dry denity the ame, from Hammond et al., 1992) C r FS C D D g g co 2 g w D g in co w D w tan (1) Where C r i root coheion [N/m 2 ], C i oil coheion [N/m 2 ], θ i lope angle, ρ i wet oil denity [kg/m 3 ], ρ w i the denity of water [kg/m 3 ], g i gravitational acceleration (9.81 m/ 2 ), D the vertical oil depth [m], D w the vertical height of the water table within the oil layer [m], and φ the internal friction angle of the oil [-]. The lope angle θ i the arc tangent of the lope, S, expreed a a decimal drop per unit horizontal ditance. Fig. 3 illutrate the geometry aumed in equation (1). Figure 2. DEM for Fraer Hill Catchment Figure 3. Infinite Slope Stability Model Schematic (Pack et al., 1998) 67

3 SINMAP approach with the hydrologic model i to interpret the oil thickne a pecified perpendicular to the lope, rather than oil depth meaured vertically. Soil thickne, h [m], and depth are related a follow: With thi change, FS reduce to: (2) Where, w Dw D hw h = relative wetne, C C r C h g = combined coheion made dimenionle relative to the perpendicular oil thickne, r w = water to oil denity ratio. The relative wetne index a below: Ra w Min, 1 (3) T in To define the tability index, wetne index from Eq.(3) i incorporated into the dimenionle factor of afety, Eq. (2) which become: (4) The variable a and θ are derived from Digital Elevation Model (DEM) wherea the value of C, tan φ, r and R/T are uer input. DEM, oil and hydrologic propertie and landlide ource area inventory of the catchment are neceary to generate the tability index grid which can be ued a landlide uceptibility zoning. In the analyi, the geotechnical input for the model; oil denity, friction angle and coheion were held contant throughout the proce. Hydraulic conductivity for the catchment alo wa held contant but the rainfall event were manipulated uing the three precipitation event a hown Table 1. Table 2 how the geotechnical input applied for thi tudy. In thi model, uncertainty factor i applied where the calibration region are area within which ingle lower bound and upper bound of calibration parameter value can repreent tranmiivity/recharge ratio (T/R), dimenionle coheion (C), and friction angle (f). In thi tudy, the minimum value of each of thee parameter wa ued a the calibration for lower bound and the maximum value a an upper bound Geotechnical Data h D co C co 1 wr FS in The model required everal geotechnical input. The input were oil denity, internal friction angle and coheion and oil depth. Soil denity wa determined tan R a C co 1 min,1r tan in T FS in Table 1. Geotechnical input ued in thi tudy Parameter Value Soil Denity, ρ, Kg / m Friction angle, φ, Coheion, c in the laboratory by weighing and meauring the volume of unditurbed ample. Internal friction angle value wa gathered from an unpublihed report of landlide that occurred in Fraer Hill by (IKRAM, 2007). Although there were alo other reference that produced the reult of internal friction angle in Malayia (Komoo, 1985; Ting et al., 1972), the one from IKRAM wa ued in thi tudy. Soil depth varied all over the catchment and from the interpretation of geologic and oil map and obervation on the actual lope failure location during the in itu, we are able to etimate the depth of the oil. Coheion i another geotechnical input required by thi model. The uggeted value by the author of the model (Pack et al., 1998) for coheion wa applied to thi model ince there i no available data regarding the parameter for thi catchment Hydrological Data Hydrological input in thi model wa in term of wetne index (T/R), ratio of tranmiivity (T) (m2 / hr) of the oil and rainfall recharge into the oil (R). T i the tranmiivity or the vertical integral of the hydraulic conductivity of oil and can be determined by: T ( k ) h Where k i the hydraulic conductivity of the oil determined in the lab uing permeameter while h i the thickne of the oil above the failure urface. k wa determined uing contant head method a uggeted by Zaitchick et al., (2003). Thee hydraulic conductivity value were then multiplied by the oil depth (h). The h value wa aumed to be contant 2 Table 2. Rik of Landlide according to certain cumulative torm event Rik of Landlide Cumulative Rainfall (mm) No <30 Low 30 to 60 Medium 61 to 100 High >100 (Adapted from DID webite: gov.my/explain.htm) 68

4 Table 3. Precipitation event according to rik of landlide clae Rik of Landlide Rainfall event in a ingle torm (mm) No Low Medium High (Adapted from DID webite: my/explain.htm) and 4 meter depth for all over the catchment area (baed on average oil depth). Baed on lab analyi, the minimum of hydraulic conductivity in Fraer Hill catchment wa m/hr and the maximum value wa found out at the lower part of the catchment which wa m/hr. R i the teady tate recharge that can be defined a: = Rainfall - (Infiltration + Evaporation) In thi tudy, we adopt the torm event that would trigger landlide a propoed by Drainage and Irrigation Malayia (DID, 2009). Table 2 howed the claification from DID bae on a ingle torm event. The DID, claification i baed on a ingle torm event typically range from two to four hour of rain. In thi analyi, we ued all 13 precipitation event within the claification to repreent each cla of landlide hazard (no, low, medium and high hazard). We attempted to ae which precipitation event triggered mot of the catchment area to landlide categorized a Defended (the mot hazard area indicate by thi model). Table 3 how the precipitation event ued in recharge (R) etimation in thi tudy. Finally, the tranmiivity wa divided by the recharge rate to define the upper and lower T / R (m) value. The final T / R value ued hown in Table Landlide inventory SPOT 5 atellite image were ued to identify the poible landlide location through viual Table 4. Table of the T/R (m) value ued for each precipitation threhold in the SINMAP analyi Rainfall Event (mm) T/R (m) Lower Bound Upper Bound interpretation a well a ground truthing had been done to confirm the pecific location. During in itu viit, the coordinate of the landlide location had been taken uing GPS. Throughout the in itu tudy, not the entire landlide location can be acceed due to dene foret and very teep lope. Thi inventoried data wa then ued to validate the model prediction. 3. Reult and Dicuion Uing the DEM and landlide inventory data, the SINMAP model wa ued to derive a tability index (SI) map. Thi SI give the prediction of landlide hazard prone area in term of Factor of Safety (FS). The SI i defined a the probability that a location i table auming uniform ditribution of the model input over their uncertainty range. The range of the SI value i between 0 (mot untable) and 1 (leat untable). Table 5 how the ix tability index claification in term of SI value a defined in the model output. The Lower Threhold, Upper Threhold Table 5. Stability Cla Definition (SINMAP Uer Manual, 1998) Condition Cla Predicted State SI >1.5 1 Stable lope zone 1.5>SI> Moderately table zone 1.25>SI>1.0 3 Quai-table lope zone 1.0>SI>0.5 4 Lower threhold lope zone 0.5>SI>0.0 5 Upper threhold lope zone 0.0 >SI 6 Defended lope zone 69

5 Figure 4. Percentage of Defended area according to different precipitation event for 2 meter of oil depth and Defended clae have SI value le than 1 and can be grouped a naturally untable while Quai-Stable i defined for marginal intability cla where the SI value between 1.0 and Moderately Stable and Stable cla can be conidered a table a they have SI value higher than The reult of the imulation for the hazard area according to Defended cla wa hown in Fig. 4, A expected, with higher precipitation threhold ued, the model tend to generate more Defended area. The mot notable change of precipitation effect on the hazard area affected i between 10mm, to 40 mm of precipitation. When the precipitation threhold wa increaed from 40 mm to 120mm, the change i rather mall range from 0.04% to 0.62%. However, when the threhold wa et at 130mm, it gave the imilar reult a impoing 120mm of precipitation. It can be aumed that the total area predicted a Defended area will remain contant when the amount of precipitation i more than 110mm. Fig. 5 howed the Stability Index (SI) grid for Fraer Hill catchment when the oil depth and rainfall are conidered at 2 meter and 110 mm repectively. Baed on tatitical output of the model in Table 6, by holding the oil depth to be contant throughout the analyi at 2 meter and rainfall i 110mm, the model able to predict 65% of the total landlide inventory. At the ame time total of untable area (FS<1) i 69.51% or 5.7 km of the catchment area to be conidered. Likewie in Table 7, for oil depth of 4 meter, the model predicted 5.8 km of total area to be conidered a naturally untable. 61% of the landlide inventory wa able to recognize by the model. A B C D Figure 5. Stability index grid map baed on four precipitation event. A, B, C and D repreent SI map uing 10mm, 30mm, 70mm and 110mm of precipitation repectively. The oil depth i 2 meter. 70

6 Figure 6. SI map for oil depth equal to 4 meter and rainfall i 110mm 4. Concluion Suceptibility of hallow landlide in Fraer Hill Catchment wa tudied under different rainfall amount and oil depth uing SINMAP model. In thi analyi it wa found that the model i more enitive to precipitation event under 120 mm. beyond that the model predicted almot contant reult for each type of hazard cla. Thee trend appeared to be the ame either uing oil depth of 2 and 4 meter. With oil depth of 4 meter, more hazard area wa detected a compared to 2 meter oil depth (with difference of 0.37 km 2 ). However, by uing 2 meter of oil depth, the model wa able to detect 4% more of landlide inventory compared to analyi uing 4 meter of oil depth. The analyi alo indicated that with greater oil depth, it will reult in more hazard area but did not reflect that it will alo able to detect more of recorded/ inventoried landlide. The reult of the analyi baed on different oil depth to map SI map reflect thi cenario. It i important to note that a lope tability map produced in thi tudy indicate the probability of hill lope failure rather than the actual landlide hazard. It i important to note that the landlide uceptibility map produced in thi tudy indicate the probability of hill lope failure rather than the actual landlide hazard. Figure 7. Slope (degree) - Area (m 2 ) Plot of Fraer Hill Catchmen Baed on the SA plot, 73.5% of the landlide occurred on lope of more than 10 degree. However there were alo landlide occurred in flat area epecially thoe located in the Fraer Hill town which caued by modification of road. Detailed interpretation of the SA Plot were provided a the tatitical ummary in Table 6 and Table 7 for 2 and 4 meter oil depth repectively. Table 6. Statitical ummary of analyi uing 2 meter of oil depth Stable Moderately Quai Lower Upper Defended Stable Stable Threhold Threhold Catchment (km 2 ) 8.2 Area, km % of Region No. Of Landlide (LS), # % of LS LS Denity (#/km 2 )

7 Table 7. Statitical ummary of analyi uing 4 meter of oil depth Stable Moderately Quai Lower Upper Defended Stable Stable Threhold Threhold Region Area, km % of Region No. Of Landlide (LS), # % of LS LS Denity (#/km 2 ) Acknowledgement The author thank the Minitry of Higher Education, Malayia for upporting thi reearch, under fundamental reearch grant: project no We alo would like to thank officer of The Raub Foretry Department and IKRAM for their help and conultation while thi tudy wa carried out. The view expreed by the authour do not neccearily reflect thoe of the agency. Reference Carrara A, Pike RJ. GIS technology and model for aeing landlide hazard and rik. Geomorphology 2008; 94 (3-4): Gaim BM, Rahim AS, Rahman AZ, Yaakub J. Hydrologic variable of Fraerû Hill. (Ed: Latiff, Zakaria Z, Ia MZ, Salleh MK, Hahim MN, Din BL) Bukit Fraer: Perekitaran Fizikal, Biologi dan Soio-ekonomi. Univeriti Kebangaan Malayia, Bangi Gulla G, Antronico L, Iaquinta P, Terranova O. Suceptibility and triggering cenario at a regional cale for hallow landlide. Geomorphology 2008; 99(1-4): IKRAM. Geotechnical Invetigation Report For Slope and Overall Study at Puncak Inn and Bunglow Cini Fraer, Hill for Fraer, Hill Development Corporation (Pahang State Tourim) Pahang Darul Makmur. An unpublihed technical report Drainage and Irrigation Department, Malayia. 2008; URL: explain. htm Jamaludin S, Huat BKB, Omar H. Evaluation of lope aement ytem for predicting landlide of cut lope in granitic and meta-ediment formation. American Journal of Environmental Science 2006; 2(4): Montgomery D, Dietrich W. Source Area, Drainage Denity and Channel Initiation. Water Reource Reearch 1989; 25 (8): Pack RT. Statitically-baed terrain tability mapping methodology for the Kamloop Foret Region, Britih Columbia, Proceeding of the 48th Canadian Geotechnical Conference, Canadian Geotechnical Society, Vancouver, B.C Pack RT, Tarboton DG, Goodwin CN. Terrain tability mapping with SINMAP technical decription and uer, guide for verion 1.00, Rep , Terratech Conult. Ltd, Salmon Arm, B.C., Canada Sidle RC, Pearce AJ, O'Loughlin CL. Hilllope Stability and Land Ue, Water Reource Monograph 11 Edition, American Geophyical Union. 1985; 140. Sidle R. A Theoretical Model of the Effect of Timber harveting on Slope Stability, Water Reource Reearch 1992; 28(7): Zaitchik BF, van E HM, Sullivan PJ. Modeling Slope Stability in Hondura: Parameter Senitivity and Scale of Aggregation. Soil Science Society of America Journal 2003; 67(1): Received 19 September 2009 Accepted 29 October 2009 Correpondence to Dr. Wan Nor Azmin Bin Sulaiman Department of Environmental Science, Faculty of Environmental Studie, Univeriti Putra Malayia, UPM Serdang, Selangor, Malayia Tel: (603) Fax: (603) wannor@env.upm.edu.my 72