Landslide susceptibility mapping using frequency ratio method and GIS in south eastern part of Nilgiri District, Tamilnadu, India

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1 susceptibility mapping using frequency ratio method and GIS in south eastern part of Nilgiri District, Tamilnadu, India Ram Mohan.V 1, Jeyaseelan.A 1, Naveen Raj.T 1, Narmatha.T 1, Jayaprakash.M 2 1 Department of Geology, University of Madras, Guindy campus, Chennai 2 Department of Applied Geology, University of Madras,Guindy campus,chennai emjaypee@gmail.com ABSTRACT The study area is located in the Nilgiri district of TamilNadu, India. Most of the landslides during November, 2009 occurred between Burliyar and Katteri along the road, Nagapattinam Gudalur National Highway (NH 67). More than 80 major landslides were reported within three days from 8 to 10 November, 2009, which took 48 human lives, and also imparted severe damage to houses, roads and railway lines. Detailed investigation was carried out on the landslide that occurred during the month of November, 2009 in Nilgiri District. The investigation involved systematic collection of data pertaining to the geological, structural and geomorphic variables. The Susceptibility Index map was prepared using GIS and it divides the study area into five zones of landslide susceptibility viz., very low, low, moderate, high and very high. Key words: s, Susceptibility Index Map, GIS, Nilgiri, Tamilnadu. 1.Introduction s are one of the most common natural disasters in hilly regions. The landslides were more in the Burliyar Coonoor Ketti sector as the region received heavy rainfall of 378mm in Burliyar, 899 mm in Coonoor and 1171 mm in Ketti in three days from 8 th to 10 th November, 2009 while the annual average rainfall is 1210 mm in Coonoor and 1856 mm in the district. Around 80 landslides were investigated within the Nilgiri district. Among these landslides, 41 occurred within the study area. These landslides are a result of excavation of the slope or its toe, drawdown of reservoirs, deforestation, improper discharging of sewage water from settlements, establishment of settlements in unstable slopes, creation of dumps of very loose waste or artificial vibrations that may be caused due to road traffic or heavy machinery. The developments that have taken place in the region has disturbed the mountainous ecosystem particularly steep slopes were created when the ground is levelled for housing and road construction. The change in landuse by clearing the forests for establishing plantation and vegetable crops also have an adverse impact as areas which were stable due to the presence of forests which have deep rooting trees, which can bind the soil, are transformed into unstable areas if shallow rooting plants are raised. The main types of landslides occurring in the study area are: Falling, Subsiding, Sliding, and Flowing. In the study area, it has been observed that natural slopes are disturbed due to cutting of roads for construction 951

2 purposes, prevention of natural drainage and the changing land use pattern are the factors contributing to landslides and landslips. Most of the times it is triggered by high intense down pour. 2. Materials and Methods For the study area, maps relevant to landslide occurrence were constructed in vector type spatial datasets using the Arc/Info GIS 9.1 software package. Contour lines that included an elevation value on the topographic map were digitized. These included topographic maps at a scale of 1:25,000. A digital elevation model (DEM) was constructed using the software. The slope, aspect, and hillshade view were prepared using the DEM. A land use/land cover map was extracted from LANDSAT MSS satellite image and the data was classified according to Google Earth images. A zonation map was prepared using geological, landslide distribution, slope, land use, aspect, drainage s, and distance to road maps. The data was processed, analyzed and synthesized to get to the root of the problem of landslides along the road in the Nilgiri district. In order to get the landslide prone areas, the triggering criteria should be assigned to each map layer. Depending on the threat posed by each category the Susceptibility Index, i.e., weightages were assigned. The data layers have been integrated in GIS environment by overlay analysis. 2.1 About the Study Area The study area is a part of the Western Ghats (TN uplands) and lies between the latitudes 11 o N and 11 o N, and longitudes 76 o E and 76 o E. The maximum and minimum altitudes are 2040m and 550m above mean sea level. It lies in the Survey of India toposheet no.58a/15/sw. The temperature is 25 0 C 10 0 C during summer and 21 0 C 5 0 C during winter. Most of the landslides occurred between Burliyar and Katteri along the road (~11 kms), Nagapattinam Gudalur National Highway (NH 67). The southern part of the area investigated is defined by Coonoor River which flows in ENE direction. The eastern boundary of the area is defined by Burliar Odai which is a tributary of the Coonoor River which joins Coonoor River in the south eastern tip of the area. The northern boundary coincides with the rainwater divide between the Burliar Odai microwatershed and the streams joining the Coonoor River between Katteri and Burliar is shown the (Figure. 1). The selection of the boundary is taking into consideration the entire slope contributing to the landslides for the Katteri Burliar segment of the NH 67 is investigated for its landslide susceptibility. The Marappalam area wherein landslides have been frequent is located in the eastern part of the area. 2.2 Geology and Geomorphology The bedrock geology of the study area consists mainly of Charnockite. This Hypersthenebearing bluish grey rock forms the basement in high grade metamorphic terrain. It is 952

3 interbanded with or carries enclaves of sputa crustal rocks of divergent composition including metasedimentary sequences. Figure 1: shows the base map of the study area The Charnockite has granulitic texture and carries Quartz, Feldspar, Hypersthene, Garnet, and Hornblende. Biotite, Apatite and Zircon are present as accessory minerals. Variants of Charnockite, especially the basic or ultra basic types are found in a few places. A small portion in the western side is covered by Western Ghats with Lateritic soils. Vegetation types have been described as evergreen and secondary forest, grasslands, shrubs, land without Scrub and cultivated crops. Dense forest with coffee plantation dominates the vegetation in the area in the eastern part and tea plantations with lesser forest are observed in the western part. The vegetation is controlled by the climatic conditions and altitude with indigenous species dominating the eastern part and in the western part plantation of trees characteristic of high altitude namely silver oak, pine and casurina varieties change the vegetative cover. The drainage of the study area is superimposed with shaded relief which describes the angles and shadows are shown in the (Figure. 2). 953

4 Figure 2: shows the shaded relief with drainage A greater part of Nilgiri district is deeply weathered. As a result, development of thick soil over rock is a common feature. The thickness of the soil reaches 40 m at some places. The exposed soil sections reveal a humus zone of 0.5 to 1 m. (A zone), followed downward by red or brown or yellow silt and clay. The silt and clay form the B zone which is quite thick. The weathered zone (C zone) between the clay and the fresh rock is normally about a meter thick. 3. Relationship between slope and landslides Slope is classified into five categories viz., 0 5, 5 15, 15 25, 25 35, >35. It is found that majority of the area falls in the category of followed by 15 25, >35, 5 15, and 0 5. Slope Table 1: Frequency ratio of slope to landslide occurrences No. of occurrence occurrence % % Ratio Class > Total

5 From the calculation of frequency ratio, class intervals of and are maximum with 13 landslides each out of 41 slides which is 63.40%. The landslide percentage of is divided by the percentage of the class which is to calculate the frequency ratio which is Similarly the frequency ratios for the other classes are calculated. The frequency ratios for the different classes of slope used in the study are given in (Table. 1). 3.1 Relationship between distance to drainage and s Majority of landslides (92.69%) in the area have been occurred close to the stream with in a distance of 150 m and only 3 landslides (7.32%) have occurred with in 200 m distance, no landslide has taken place beyond 200 m and up to 350 m. Hence, distance to drainage taken as basis for landslide hazard zonation.this is due to the fact that the land slides are due to the creation of steep slope due to erosion. From the frequency ratio (Table. 2) it is evident that 92.69% of the landslides have occurred within a distance of 150 m from the drainage and hence the factor can be effectively used. Table 2: Frequency ratio of distance from drainage to landslide occurrences Drainage Buffer Class No. of occurrence occurrence % % Ratio 0 50m m m m m >250m Total Relationship between Landuse / Land Cover and s The landuse/landcover exerts a control over landslides and is considered next to slope in importance, as human activities and consequent deforestation has altered the stability of slopes. The urban activities result in the modification of slope due to widening of road and leveling of the terrain forming steep cut. As a result high frequency was arrived for the dense forest where most of the road network occurs. The landuse factor has been classified as Tea plantation, Dense forest, Settlement Land without scrub, and Scrub forest. Land with Dense forest forms the dominant landuse followed by Tea plantation, Scrub forest, Settlement and Land without scrub.the frequency ratio for landslides calculated for landuse factor is given in (Table. 3) The highest ratio is noticed in dense forest as the field is prepared for road network with heavy traffic vibration. There are some blockages of culverts along the road. This enables percolation of water during rains and the pore pressure of clay bearing soil increases. The susceptibility for landslides increases manifold where tea plantations are cultivated. Tea 955

6 plantations and settlements rank next in the susceptibility followed by dense forest plantations. When the tea planters converted large tracts of forests into tea estates, they have left only the steep slopes as forests which have difficulty for accessibility. Thus forests exist only in the steep slopes. Table 3: Frequency ratio of Landuse and landcover to landslide occurrences Landuse & Landcover No. of. occurrence occurrence % % Ratio Settlements Scrub forest Tea plantation Dense forest Land without scrub Total Relationship between Drainage Density and s The next factor considered is drainage density. The drainage density ranges from 0 to 2100 m/m 2 and is classified into five classes viz., m/m 2, m/m 2, m/m 2, m/m 2 and m/m 2.based on Natural Breaks (Jenk s) method. The percentage of landslides in general decrease with increasing drainage density (Table. 4). The frequency ratio shows that highest ratio is found in areas with a drainage density of m/m 2, followed by m/m 2, m/m m/m 2 and m/m 2. The drainage density is an important factor as rain water percolates in areas with low drainage density. However, in the study area highest ratio is found in drainage density class 526 to 864 m/m 2 which, suggests that the erosional action by streams also play a role in increasing the slope instability. Further, high drainage density is encountered in steeper slopes. The relationship between drainage density and landslides. Table 4: Frequency ratio of Drainage Density to landslide occurrences Drainage Density Class No.of. occurrence occurrence % % Ratio Total

7 4. Reclassification using Frequency Ratios The thematic maps of the five causative factors selected for the landslide hazard map generation were assigned the frequency ratio for the respective classes using ArcGIS spatial analyst extension tool for the preparation of the final map. The reclassified raster map/data for the themes are given in (Figure.3). 4.1 Susceptibility Mapping The frequency ratios were calculated for the five factors used in hazard mapping using the probabilistic model. The five factors were converted in the form of 12 x 12 m 2 grid cells to calculate a landslide susceptibility index (LSI). The total number of cells was and the number of landslide occurrence is 41. Using GIS software, the grids were overlaid with the geographic coverage for the study area. During the overlay, the LSI was calculated by summation of each factor s frequency ratio value (Tables 7.1 to 7.5) according to the following formula; LSI = ΣFr (where Fr = the frequency ratio of each factor s type or range). Figure 3: contributing factors reclassified contributing factors on FR Using the LSI assigned to each cell, the landslide Hazard map is created. First the weighted sum of slope and drainage density was prepared as these natural factors are considered to have a greater influence on landslide susceptibility.subsequently, landuse, 957

8 distance to drainage and distance to road were also overlayed and the different maps prepared. Since distances to road have high values which may overshadow other factors, it is not considered for the preparation of the final map shown in Final map with all the four factors is presented in (Figure.4). 4.2 Validation The map generated should be validated and unless it is validated the numerical method is useless and cannot be used. The validation is done to whether its predictions matched the expected results. The landslide inventory map which took into consideration the slope, drainage density, landuse and distance to drainage of the area, is overlaid on the Hazard Map and the number of landslides falling in each susceptibility zone is calculated is shown in the (Table.5). In the Hazard map prepared for the study area and classified based on Equal Interval method. The Susceptibility Zonation (LSZ) map is graded into five classes vary low, low, moderate, high and very high using natural break method of Jenks available in ArcGIS. ArcMap identifies break points by picking the class breaks that best group similar values and maximize the differences between classes. The features are divided into classes whose boundaries are set where there are relatively big jumps in the data values. Figure 4: Susceptibility Map of the Study area 958

9 Table 5: The variation in the number of landslides falling in different hazard classes Name of LH Class s falling in LSS Zones defined by Equal Interval method s falling in LSS Zones defined by Natural Break method Number Percentage Number Percentage Very Low Low Moderate High Very High Total in High & Very High % % 5. Conclusions 1. Slope and Landuse are the important landslide causing factors and high resolution data if available will help to prepare a detailed landslide hazard map which can be used with confidence. 2. The vibrations due to heavy traffic are also a main factor for landslides along the road. The heavy vehicles should be controlled during rainy seasons. 3. The landslides identified in the field are circular failures and they occurred in the areas close to road and the erosion of the banks and removal of support is one of the main processes responsible for landslides. 4. s are more frequent in areas with Vegetable crops particularly in tea estate. 5. Drainage density exerts a great influence on landslide susceptibility as erosional action of the streams is the main cause for slope instability and areas with high drainage density are found to be unfavourable. 6. Majority of the landslides have occurred close to I and II order streams and hence, the incipient erosion taking place in the hills is one of the reasons for slope failure. 7. s are not encountered in steep slopes as the charnockites which occur in such areas are massive and less jointed. Rock falls are very rare in the area. 959

10 The landslide Susceptibility map prepared is verified and the fact more than 85% of the slides have taken place in High and Very High susceptibility classes shows that the methodology is sound and can be used for Nilgiri District. 6. References 1. Aleotti, P. and Chowdury, R. (1999), hazard assessment: summary review and new perspectives, Bulletin of Engineering Geology and the Environment, 58(1), pp Brabb, E. E. (1984), Innovative approaches to landslide hazard mapping, In: s Glissements de Terrain, IV International Symposium on s,. Toronto, Canada, 1, pp Carrara, A., (1983), Multivariate models for landslide hazard evaluation, Mathematical Geology 15, pp Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Psqui, V., and Reichenbach, P.: (1991), GIS techniques and statistical models in evaluating landslide hazard, Earth Surface Processes and Landforms 16, pp Chung, C. J., Fabbri, A., and Van Westen, C. J.(1995), Multivariate regression analysis for landslide hazard zonation, In: A. Carrara and F. Guzetti (eds), Geographical Information Systems in Assessing Natural Hazards, Kluwer Academic Publishers, the Netherlands, pp Cruden DM, Varnes DJ: 1996, types and processes. In: Turner AK, Schuster RL (eds) s investigation and mitigation. Special Report 247. Transportation Re search Board, Washington, pp , scale 1:24,000, 8 pp 7. Jaiswal. P et al,.(2010), Quantitative assessment of landslide risk in India, Natural Hazards Earth System Sciences., 10, pp Jaiswal, P. and van Westen, C. J.(2009), Estimating temporal probability for landslide initiation along transportation routes based on rainfall thresholds, Geomorphology, 112, pp Seshagiri, D. N. and Badrinarayanan, B.(1982), The Nilgiri landslides, GSI Misc Pub No Van Westen, C. J., (1993), Application of Geographic Information Systems to Hazard Zonation, ITC Publication 15, pp Varnes, D.J. (1984), hazard zonation: a review of principles and practice, Natural Hazards 3, UNESCO: 63p 960

11 12. Venugopal, D, (2004),Development Conservation Dilemma in the Nilgiri Mountains of South India, Journal of Mountain science., 1(1), pp