LANDSLIDE HAZARD ZONATION
USING THE RELATIVE EFFECT
METHOD IN SOUTH EASTERN PART
OF NILGIRIS, TAMILNADU, INDIA.
Naveen Raj, T*
Research scholar, Department of Geology, University of Madras, Maraimalai campus, Chennai - 600 025 TAMILNADU INDIA.
Ram Mohan.V
Department of Geology, University of Madras, Maraimalai campus, Chennai - 600 025, INDIA
Backiaraj. S
Department of Geology, University of Madras, Maraimalai campus, Chennai - 600 025, INDIA
Muthusamy.S
Department of Applied Geology, University of Madras, Maraimalai campus, Chennai - 600 025, INDIA
ABSTRACT
Landslides occur frequently due to climatologic and geologic conditions with high tectonic activities. In this paper, the landslide hazard and the effect of landslide-related factors at South Eastern part of Nilgiri District, Tamilnadu using the Relative Effect Method (REM) model, Geographic Information System (GIS) and remote sensing data have been evaluated. There are different methods of landslide hazard zonation with some advantages and disadvantages. The authors suggest the Relative Effect Method (REM), which is statistical method using GIS software for landslide hazard zonation. This method determines the relative effect (RE) of each unit, such as surface geology, slope morphometry, climatic conditions, land use and land cover by calculating the ratio of the unit portion in coverage and landslide. The function that is used in this method is logarithmic. The advantages of the logarithmic function are in domain determination for output data and equality for plus and minus domains of calculated RE's. All the thematic layers are Display manipulate and analysis has been carried out to evaluate layers such as geology, geomorphology, slope, soil, land use and drainages. The computed index for each grid for each factor was summed and grouped into five classes. The landslide susceptibility map can be used to reduce damage associated with landslides and to land cover planning.
Keywords: Landslides, Relative Effective Method, GIS, Nilgiris, Hazard Zonation.
1. Introduction
Landslides are frequent and annually recurring phenomena in the Nilgiri plateau. Outward and downward movement of mass, consisting of rocks and soils, due to natural or man-made process is termed as a landslide. When the landslides endanger humans and their installations, they are known as hazards and when they cause property damage and loss of life, they are known as disasters. The unprecedented rains caused more than a hundred landslides within an area of 250 sq.kms in 1978 and in 1979 the incidence of landslides was on a much larger scale and nearly two hundred landslides were recorded in the Nilgiris district. Such severity of disastrous landslides has not been felt in any part of the country so far.
Heavy rains in November, 1979 brought in large scale landslides in the Coonoor sector, eventually overtaking the landslide investigation which was in progress. The devastation due to landslides was even more severe in 1979 than in 1978. This new development entailed partial reorientation of work and modification of priorities. As the landslides of 1979 were more massive and of larger magnitude, detailed profiles of landslides, detailed mapping on larger scale and in a few instances, survey with terrestrial photogrammetric work, were
taken up.
2. Research Area
Fig 1: Base Map of the study area
The area for which landslide susceptibility map (LSM) is prepared, lies between the latitudes 11o12’30”N and 11o35’00”N,and longitudes 76o35’30”E and 76o54’30”E, and covers an area of 526 km2 approximately is given in the (Fig.1). The area falls under survey of India Toposheet no 58 A/11 and 58 A/15.The minimum and maximum altitudes are550m and 2070m respectively above mean sea level.
2.1 Regional Geology
The Nilgiri ranges comprise Archaean metamorphic rocks which include Charnockite. Charnockite rocks have been referred in earlier literature as Dharwar schists. They are at present included under the “Sargur schists”. A brief description of the individual rock formations is given below.
2.1.1 Charnockite
2.2 Geomorphology
Fig 2: Geomorphology of the study area
The Nilgiris hills, rising aloft from the uplands of Coimbatore is a plateau sloping steeply into the Mysore plateau towards north and merging gradually with the Western ghats in the north-west, west and south-west. The long axis of the plateau is in the direction of east-north-east. Over the years, phsiographers have been made a moot point that the Eastern Ghat abut into the Western Ghat in the Nilgiri ranges.The plateau has a length of 55km and a width of 32 km approximately, occupying an area of 1800 sq.km. It is bound by the Bhavani river on the southern side and by the Moyar river in the north. The water divide in this part of the Peninsula passes through the western edge of the plateau as shown in the (Fig 2)
.
3. METHODOLOGY
In this study, the relative effect of a parameter as a determining factor of slope instability is quantitatively determined by introducing a ‘Relative Effect’ function (RE). Given an area of study that contains a certain number of landslides, various thematic maps (geology, slope, soil thickness, soil texture, soil permeability, plant and forest) are prepared. Each map is covered individually by the landslide map. For every unit, the ratio of the unit area, a, to the total area of the study, A, and the ratio of the landslide area in the unit,
sld, to the area of total landslide, SLD, are calculated; AR= a/A
SR= sld/SLD
The relative effect function is then defined as:
RE =Log (SR +ε),
AR
Where epsilon is a very positive value near zero.
There are three cases for estimating a relative effect of each unit depending on it’s RE.
1) REis less than zero when the share of a unit in landsliding is less than its share in area Coverage. This means that it has an effect of decreasing landslide risk (negative effect).
2) RE is greater than zero when the share of a unit in landsliding is greater than its share in area coverage. This means that it has an effect of increasing landslide risk (positive effect).
3) RE is zero when the share of a unit in landsliding is equal to its share in area coverage. This means that it has no effect of decreasing or increasing landslide risk.
The advantage of using logarithmic function is that the positive effect and negative effect are quantitively equal. Then using a GIS, all maps are integrated and an evaluation of landslide risk is determined by algebraic summation of REs, multiplied by alpha,
Where Alpha is zero if there is no risk of landslide (e.g., slopes less than 5 degrees), otherwise the value of alpha is 1.The higher positive values of slide risk indicate a higher risk of landslide and the higher minus values of slide risk indicate a lower risk of landslide.
We can also judge the effectiveness of a unit by simple summation of absolute values of REs. Units with higher values of summation of absolute REs, will be more effective and more important in landslide management and hazard mitigation than those with lower values.
4. LANDSLIDE HAZARD MAPPING
Interpretation of future landslide occurrence needs an understanding of conditions and processes controlling landslides in the study area. Three physical factors such as past history, slope steepness, and bedrock are the minimum components necessary to assess landslide hazard zonation. It is also useful to add a hydrologic factor to reflect the important role which ground water often plays in the occurrence of landslides.
An indication of this factor is usually obtained indirectly by looking at vegetation, slope orientation, or precipitation zones. All of these factors are capable of being mapped. Specific combinations of these factors are associated with differing degrees of landslide hazards. The identification of the extension of these combinations over the area being assessed results in a landslide hazard map.
The scope of this study was to generate landslide hazard zonation maps that can be utilized to identify the potential landslide hazard in the mountainous area. A landslide zonation map was prepared based on REs of the geological units, soil type, landuse and landcover, geomorphology, drainage density, distance to drainage, lineament density, slope (Tables 1 to 8).
Table 1. Percentage of geological units coverage and related slide.
Type % of coverage % of slide R.E.
Charnockite 98.90912548 100 0.005
Hornblende Biotite Gneiss
1.137262357 0 0
Table 2. Percentage of landuse and landcover units coverage and related slide.
Type % of coverage % of slide R.E.
Built-up land 3.65256806 4.229607251 0.064
Crop Land 13.82908034 6.64652568 -0.318
Decidious Forest 0.105765225 0 0
Evergreen/Semi-Evergreen Forest
4.047615423 1.510574018 -0.428
Forest Blanks 0.745266358 0 0
Forest Plantations 17.60607458 10.57401813 -0.221
Tea Plantations 49.37337057 75.52870091 0.185
Land with Scrub 4.289717083 1.510574018 -0.453
Land without Scrub 0.259538887 0 0
Reservoirs 0.227708383 0 0
Scrub Forest 5.697075501 0 0
Barren Rocky 0.037816761 0 0
Tanks 0.061863516 0 0
River 0.008637644 0 0
Canal 0.111807122 0 0
Table 3. Percentage of geomorphological units coverage and related slide.
Type % of coverage % of slide R.E.
Barren Valley 2.919067263 1.510574018 -0..286
Barren Plateau 12.74673359 16.3141994 0.107
Dissected Plateau 22.88946449 25.98187311 0.055
Dissected Upland 50.56932372 41.3897281 -0.087
Fracture Valley Fill 1.811756845 0.906344411 -0.301
Reservoir 0.252361252 0 0
Intermontane Valley 0.148134362 0 0
Table 4. Percentage of slope units coverage and related slide.
Type % of coverage % of slide R.E.
0 - 5° 10.11102281 5.135951662 -0.294
5 - 15° 51.02474525 57.70392749 0.053
15 - 25° 27.59715133 29.00302115 0.022
25 - 35° 8.380940304 6.64652568 -0.101
>35° 2.458822624 1.510574018 -0.212
Table 5. Percentage of lineament density units coverage and related slide.
Type % of coverage % of slide R.E.
0-000000-0.000368 13.52973218 11.48036254 -0.071
0.000368-0.000736 33.80534701 41.3897281 0.088
0.000736-0.001104 34.30399845 31.41993958 -0.038
0.001104-0.001472 14.94437018 15.70996979 0.022
0.001472-0.001839 3.321421427 0 0
Table 6. Percentage of drainage density units coverage and related slide.
Type % of coverage % of slide R.E.
0.000000-0.001190 4.986526049 0.604229607 -0.917
0.001190-0.002398 28.89292672 19.93957704 -0.161
0.002398-0.003570 48.01124058 53.17220544 0.044
0.003570-0.004760 16.69578266 25.3776435 0.182
0.004760-0.005936 1.462979624 0.906344411 -0.208
Table 7. Percentage of distance to drainage units coverage and related slide.
Type % of coverage % of slide R.E.
0-50 27.77350293 28.39879154 0.010
50-100 24.51131899 27.79456193 0.055
100-150 18.76573193 19.93957704 0.026
150-200 12.48304149 12.68882175 0.007
200-600 16.0489671 11.17824773 -0.157
600-1300 0.471344319 0 0
Table 8. Percentage of soil units coverage and related slide.
Type % of coverage % of slide R.E.
Clayey Soils 82.63188118 90.33232628 0.039
Loamy Soils 17.41385266 9.667673716 -0.256
Table 9. Percentage area of risk classes
Class Area (m2) Area percentage from Basin
Very Low 36169 21.65225
Low 912107 54.60026
Moderate 12617 7.553055
High 14655 8.773085
Very High 12397 7.421354
Sum 167045 100
Fig 3 Landslide Hazard Zonation Map
5. Conclusions
In lulc units, built-up land and tea plantations shows the positive values indicates that high possibility for landslides and also shows the rapid development of urban in the study area whereas in geomorphology units, barren plateau, dissected plateau and valley shows the positive values.Through this study, it is evinced again that the geomatics technology is a proven tool for landslide studies in order to properly understand, identify and suggest remedial measures.
References
[1] Aleotti, P. and Chowdury, R.: 1999, Landslide hazard assessment: summary review and new perspectives, Bull. Eng. Geol. Envir., 58(1), 21–44.
[2] Brabb, E. E.: 1984, Innovative approaches to landslide hazard mapping, In: Landslides-Glissements de Terrain, IV International Symposium on Landslides, Vol. 1, Toronto, Canada, pp. 307–323.
[3] Carrara, A., Cardinali, M., Detti, R., Guzzetti, F., Psqui, V., and Reichenbach, P.: 1991, GIS techniques and statistical models in evaluating landslide hazard, Earth SurfaceProcesses and Landforms16, 427–445.
[4] Carrara, A., Cardinali, M., Guzzetti, F., and Reichenbach, P.: 1995, GIS technology in mapping landslide hazard, In: A. Carrara and F. Guzzetti (eds.), Geographical Information Systems inAssessing Natural Hazards, Kluwer Academic Publisher, The Netherlands, pp. 135–175.
[5] Chung, C. F. and Fabbri, A. G.: 1999, Probabilistic prediction models for landslide hazard mapping, Photogram metric Engineering & Remote Sensing 65(12), 1389–1399.
[6] Cruden, DM (1991) A simple definition of a landslide. Bull Int Assoc Eng Geol V. 43, pp. 27-29.
[7] Cruden DM, Varnes DJ: 1996, Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides—investigation and mitigation. Special Report 247. Transportation Re-search Board, Washington, pp 36–75 273, scale 1:24,000, 8 pp.
[8] Ganapathi, G.P., Mahendran, K. and Sekar. S.K. (2010)Need and Urgency of Landslide Risk Planning for Nilgiri District, Tamil Nadu State, India, Int. Jour. of Geomatics and Geosciences. V. 1, No 1, pp. 29-40.
[9] Jaiswal. P et al.: 2010 Quantitative assessment of landslide risk in India, Natural Hazards Earth System Sciences., 10, 1253–1267. [10] Jaiswal, P. and van Westen, C. J.:2009, Estimating temporal probability for landslide initiation along transportation routes based on
[11] Seshagiri, D. N., Upendran, R. and Lakshmikantham, C.B. (1980) Nilgiris Landslides: Report on the First Phase of geological Investigation – A collaborative Study. Unpublished Report of State Geology Branch, Industries Department. 48 p.
[12] Van Westen, C. J.: 1993, Application of Geographic Information Systems to Landslide Hazard Zonation, ITC Publication 15, 245 pp. [13] Van Westen C.J.: GIS in landslide hazard zonation: A review with examples from the Colombian Andes. In: Price M.F.& Heywood
D.I. (eds.), Taylor and Francis, London, 1994, 135-165.
[14] Varnes, D. J.: 1978, Slope movement: types and processes, In: R. L. Schuster and R. J. Krizek (eds), Landslides: Analysis and trol, Transportation Research Board, National Academy of Sciences, Washington D.C. Special Report 176, Chapter 2: 11–33.
