An initial model of seismic microzonation of Sikkim …earthqhaz.net/imp_pubs/2005_J of Asian Earth...

An initial model of seismic microzonation of Sikkim Himalaya

through thematic mapping and GIS integration

of geological and strong motion featuresq

Sankar Kumar Nath*

Department of Geology and Geophysics, Indian Institute of Technology, Kharagpur-721302, India

Accepted 10 March 2004

Abstract

Seismic microzonation and hazard mapping was undertaken in the Sikkim Himalaya with local site conditions and strong ground motion

attributes incorporated into a geographic information system. A strong motion network in Sikkim consisting of 9 digital accelerographs

recorded more than 100 events during 1998–2002, of which 72 events are selected with signal-to-noise ratios $3 for the estimation of site

response (SR), peak ground acceleration (PGA) and resonance frequency (RF) at all stations. With these data and inputs from IRS-1C LISS

III digital data, topo-sheets, geographical boundary of the State of Sikkim, surface geological maps, soil taxonomy map at 1:50,000 scale and

seismic refraction profiles, the seismological and geological thematic maps, namely, SR, PGA, RF, lithology, soil class, slope, drainage, and

landslide layers were generated. The geological and seismological layers are assigned normalized weights and feature ranks following a pair-

wise comparison hierarchical approach and later integrated through GIS to create the microzonation map of the region. The overall SR, PGA

and resonance frequency show an increasing trend in a NW–SE direction, peaking at Singtam in the lesser Himalaya. Six major hazard zones

are demarcated with different percentages of probability index values in the geological, seismological hazard and microzonation maps.

The maximum risk is attached to a probability greater than 78% in the Singtam and adjoining area. These maps offer generally better spatial

representation of seismic hazards including site-specific analysis as a first level microzonation attempt.

q 2004 Elsevier Ltd. All rights reserved.

Keywords: Seismic hazard; Site response; Peak ground acceleration; Resonance frequency; GIS integration; Microzonation

1. Introduction

Five major earthquakes occurred in India over the past

decade. The devastating Bhuj earthquake of 26th January

2001 is still fresh in our memory. The Himalayan region

is a 2500 km long belt from Kashmir in the west to

Arunachal Pradesh in the east. It can be divided into

several seismotectonic blocks, including the Darjeeling–

Sikkim, where a good number of moderate magnitude

earthquakes ðM $ 5:0Þ had been recorded in the past.

Global Positioning System (GPS) measurements show

that India and southern Tibet converge at a rate of

20 ^ 3 mm/year (Bilham et al., 2001). Bilham et al.

(2001) divided the Himalaya into 10 imaginary sections,

each around 220 km in length. At the observed conver-

gence rate of 20 mm/year (Bilham et al., 2001), at least 6

of these 10 regions have an accumulated slip potential of

4 m. This is equivalent to the slip believed to be

associated with the 1934 Bihar earthquake that killed

10,700 people. By 2002, the Bureau of Indian Standard

mapped four seismic zones in India, namely (i) Zone-V:

PGA of 0.4 g and above with 10% probability of

exceedence in 50 years and MMI of IX and above,

occupying about 12% of the country (ii) Zone IV: PGA

0.25 g and MMI VIII, occupying 18% of the country (iii)

Zone III: PGA 0.2 g and MMI VII, occupying 26% of the

country (iv) Zone II: PGA 0.1 g and MMI VI. However,

these zones cannot predict with certainty what ground

acceleration will be experienced by structures situated in

them. It is the level of ground acceleration, coupled with

site-specific effects, which actually buffet buildings due to

the impact of an earthquake. The Sikkim Himalaya

(Fig. 1a) is located in an earthquake-prone part of the

eastern Himalaya along the Darjeeling–Sikkim tract.

1367-9120/$ - see front matter q 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.jseaes.2004.03.002

Journal of Asian Earth Sciences 25 (2005) 329–343

www.elsevier.com/locate/jaes

q Originally submitted for the 17 Himalaya Tibet Workshop.* Tel.: þ91-3222-283-374; fax: þ91-3222-282-268.

E-mail address: [email protected] (S.K. Nath).

http://www.elsevier.com/locate/jaes

Fig. 1. (a) Generalized geological map of the Himalayas, showing the different geotectonic domains and lithounits. Inset shows the location of the Sikkim

Himalaya. MBT, Main Boundary Thrust; NP, Nanga Parvat; ND, Nanda Devi. (b) Schematic geological map of the Sikkim Himalaya (after Neogi et al., 1998).

S.K. Nath / Journal of Asian Earth Sciences 25 (2005) 329–343330

The recent damaging earthquake of 1988 (M 6.7) was

distinctly felt in the Darjeeling–Sikkim Himalaya, and the

isoseismal VII contour passed through the towns of

Darjeeling and Gangtok.

It is therefore necessary to develop a microzonation map

of earthquake prone areas like Sikkim Himalaya in order to

display seismic hazards on an urban block-by block scale,

based on local conditions such as soil types that affect

ground motion levels and vulnerability to soil liquefaction.

Seismic microzonation consists of several subtasks, namely,

a study of the seismotectonic setting of a region, ground

failure susceptibility analysis, geotechnical parameteriza-

tion, spatial variation of ground motion using both weak and

strong motion recordings, estimation of site amplification

factors, study of attenuation relations, seismological

simulation of source and propagation effects (broadband

and strong motion seismometry) and thematic mapping.

To produce a microzonation map, it is important to include

site effects, a digital map of the lithological conditions, soil,

a digital map showing the topographic effect (% slope), peak

ground acceleration (PGA) and the resonance/predominant

frequency (RF) of ground motion at different sites.

The Sikkim Himalaya is considered in the present study in

order to develop a quasi-probabilistic microzonational

model at a 1:50,000 scale.

2. The Sikkim Himalaya

2.1. Regional geologic setting

In the Sikkim region, the different lithounits (Acharyya,

1998) are dispersed in an arcuate regional fold pattern

(Fig. 1b, Neogi et al., 1998). The ’core’ of the region is

occupied by Lesser Himalayan low-grade metapelites and

interbedded metapsammite belonging to the Daling Group

(Proterozoic to Mesozoic). The distal parts of the region are

characterized by medium-to high-grade crystalline rocks of

the Higher Himalayan Belt (Higher Himalayan Crystalline

Complex, HHC). A prominent ductile shear zone, the Main

Central Thrust (MCT) separates the two belts. In this region,

the MCT is the southernmost occurrence of a number of

northward-dipping ductile shear zones within the Higher

Himalayan Crystalline Complex. Gondwana (Carbonifer-

ous-Permian) and molasse-type Siwalik (Miocene–Plio-

cene) sedimentary rocks of the Sub-Himalayan Zone

(not shown in the map) occur in the southern part of the

region. In the extreme north, a thick pile of Cambrian to

Eocene fossiliferous sediments of the Tethyan Zone

(Tehtyan Sedimentary sequence, Fig. 1b) overlie the HHC

on the hanging wall side of a series of north-dipping normal

faults constituting the South Tibetan Detachment System

(STDS) (Gansser, 1964).

2.2. Microseismicity

Geological Survey of India in the eastern Himalaya

carried out two microearthquake surveys, one during

1992–1993 in the Darjeeling Himalaya, and the other

during 1994–1995 in the Sikkim Himalaya (De, 2000).

About 400 earthquakes were recorded and about 100

earthquakes ðMd¼ 1:0–5:0Þ are precisely located within

50 km of the networks. The epicentre map and N–S cross

section (Kayal, 2001) of the earthquakes are shown in

Fig. 2a and b. It is observed that the earthquakes are

mostly clustered to the north of MBT, at a depth range of

10–40 km, with the majority of the earthquakes occurring

below the plane of detachment (Fig. 2b). A well-

constrained composite fault plane solution for a group

of earthquakes (depth 10–40 km) shows thrust faulting

with a strike-slip component. The depth section and the

fault-plane solution suggest that the MBT is seismogenic

up to the mantle in this part of the Himalaya. The

recorded strong motion events (72 earthquakes with

magnitude between 2.2 and 5.6) also show clustering in

the same source region (Fig. 2c and d) as that of the

microearthquake survey and thus support the tectonic

model of the region.

3. Geological inputs

The geological inputs include IRS-1C LISS III digital

data of March 2000, topo-sheets from the Survey of India,

geographical boundary of the State of Sikkim, surface

geological maps (Neogi et al., 1998), soil taxonomy map

at 1:50,000 scale from National Bureau of Soil Survey

(1994) and seismic refraction profiles. All the maps and

topo-sheets were scanned at 200 DPI with a resolution of

6 m for a scale of 1:50,000 and rectified with a common

base using a Everest polyconic projection system. A

second-degree polynomial surface, fitted during the

rectification process, removed any distortion in the

scanned image. The respective features on each rectified

raster image were digitized for conversion to a vector

layer/coverage using ARC INFO GIS software. The

IRS-1C LISS III data were converted to a False Color

Composite (FCC) for the generation of multi-spectral

images, which were also rectified to the same base. The

themes thus generated are geographical boundaries of

Sikkim and its districts along with geological attributes

that include lithounits, soil taxonomy, drainage, lakes and

glaciers, height contours and landslides. In the lithounit

layer of the geological themes, the significant attribute

consists of the Higher Himalayan Crystalline rocks and

Lesser Himalaya. The physiographic zones of soil of

Sikkim from the National Bureau of Soil Survey were

vectorized and stored as the soil taxonomy GIS

coverage. The soil classification is based on composition,

grain size and lithology. Site classification is done as sites

S.K. Nath / Journal of Asian Earth Sciences 25 (2005) 329–343 331

IB (b . 1500 m/s), IC (b ¼ 700–1500 m/s), II

(b ¼ 350–700 m/s) and III (b ¼ 180–350 m/s) by com-

bining polygons of the same broader taxonomy as

depicted in Fig. 3a.

The FCC of IRS-1C, LISS III image is used to spot

the landslide and to build a polygon theme. Height

contour and drainage themes are arc layers, which are

used to generate the triangulated irregular network (TIN)

Fig. 2. (a) Microseismicity map of the Sikkim and Darjeeling area, eastern Himalaya (after Kayal, 2001). (b) N–S depth-section of the earthquakes. Mantle

depth is from gravity data (after Kayal, 2001). (c) Earthquake events located in the Sikkim and Darjeeling area during 1998–2003 by the IIT Kharagpur Sikkim

Strong Motion Network. (d) N–S depth-section from the strong motion events.


Fig. 3. (a) Soil site classification and drainage coverage of Sikkim. (b) Slope map of Sikkim.


of Sikkim and later to create a ‘%slope’ layer shown in

Fig. 3b.

4. Strong motion data processing and seismological

attribute generation

A 9-station strong motion network (Fig. 4) in Sikkim

established by IIT, Kharagpur, has been operative since

1998. One Kinemetrics Altus K2 and 8 Kinemetrics Altus

ETNA high dynamic range strong motion accelerographs

were installed to continuously monitor the signals that

satisfy the event detection criteria. A trigger level of 0.02%

of the full-scale (2 g) was set for data recording.

The dynamic range of the systems is 108 dB at 200

samples/sec with an 18-bit resolution. The data for more

than 100 local earthquakes ð2:2 # M # 5:6Þ was recorded

during 1998–2002. The present analysis is based on 72

events, which were recorded with a good signal-to-noise

ratio (signal-to-background ratio $ 3). These events are

plotted in Fig. 4 on the IRS image and show a clustering in

the lesser Himalayan zone to the north of MBT. The event

recording history is presented in Table 1.

4.1. Site response estimation

The greatest challenge in estimating site response (SR)

from earthquake data is removing the source and path

effects The non-reference-site-dependent technique used

here involves deconvolution of the vertical-component

signal from the horizontal-components, so that the

obscuring effects of source function and instrument

response are removed, leaving a signal composed of

primarily S-wave conversions below the station. The

deconvolved horizontal component called the receiver

function trace is the best representation of the SR since

the local site conditions are relatively transparent to the

motion that appears on the vertical component.

Suppose a network has recorded J events by I stations

(each event may not be recorded by all I stations). Then the

amplitude spectrum of the jth event recorded at the ith

station for the kth frequency, OijðfkÞ can be written in the

frequency domain as a product of a source term EjðfkÞ; a path

Fig. 4. Strong motion network and earthquake events located on the IRS image of Sikkim.


Table 1

Event recording history by the Strong Motion Network in Sikkim

Sl. no. Event (YYMMDD-HMMSS) Lat (8N) Long (8E) Mag (Mb) Depth (km) Singtam Gezing Mangan Gangtok Lachen Chungthang Jorethang Aritar Melli

1. 990307-061439.48 27-15.10 88-23.57 4.6 23.5 * * *

2. 990614-090336.11 27-26.19 88-27.05 4.9 23.1 * * *

3. 990618-093618.21 27-22.04 88-41.72 3.2 10.0 * * *

4. 990619-075749.20 27-21.21 88-21.92 3.7 14.7 * * *

5. 990702-060130.16 27-15.10 88-29.10 4.2 17.8 * * *

6. 990710-091107.85 27-21.68 88-21.48 4.0 14.6 * * *

7. 990714-060130.83 27-15.10 88-29.10 3.7 17.4 * * *

8. 000101-001129.46 27-17.87 88-35.10 4.1 10.0 * * *

9. 000407-102647.49 27-23.09 88-31.10 3.1 5.0 * * *

10. 000418-132502.59 27-31.31 88-38.10 4.1 10.0 * * *

11. 000523-035201.88 27-14.18 88-06.67 2.2 10.0 * * *

12. 000531-045313.28 27-16.12 88-34.51 3.1 7.5 * * *

13. 000531-062118.81 27-33.21 88-23.94 3.5 7.4 * * *

14. 000603-055559.17 27-12.91 88-26.35 3.0 5.6 * * *

15. 000608-083235.65 27-12.18 88-22.24 3.2 5.5 * * *

16. 000602-085141.48 27-14.06 88-25.27 5.1 22.3 * * *

17. 000607-091014.88 27-16.54 88-17.73 4.9 18.9 * * *

18. 000603-162811.84 27-17.52 87-58.57 3.2 10.0 * * *

19. 000610-120748.83 27-11.18 88-18.52 5.1 23.4 * * *

20. 000613-070908.15 27-30.10 88-21.91 3.4 10.0 * * *

21. 000616-061211.61 27-40.70 88-17.73 3.3 10.0 * * *

22. 000618-164557.29 27-23.63 88-22.84 3.6 14.9 * * *

23. 000629-042625.83 27-24.00 88-50.09 3.1 10.0 * * *

24. 000630-092717.62 27-19.67 88-26.07 3.6 6.1 * * *

25. 000704-102644.40 27-10.47 88-26.90 4.4 22.5 * * *

26. 000716-075704.02 27-12.01 88-29.10 3.3 10.0 * * *

27. 000727-032015.18 27-17.10 88-15.10 3.8 5.3 * * *

28. 000807-032152.39 27-19.32 88-25.10 3.4 10.0 * * *

29. 000807-135938.95 27-17.10 88-20.02 4.3 10.0 * * *

30. 000820-172625.34 27-21.77 88-17.20 3.0 7.8 * * *

31. 000823-070009.30 27-15.70 88-19.05 2.9 6.7 * * *

32. 000828-081613.22 27- 9.10 88-18.10 3.8 16.8 * * *

33. 000902-071511.39 27-22.05 88-16.62 4.1 10.0 * * *

34. 000904-124810.75 27-17.10 88-21.36 3.7 10.0 * * *

35. 000906-190748.59 27-30.10 88-31.10 4.5 20.6 * * *

36. 000908-021531.27 27-26.16 88-26.37 4.3 17.5 * * *

37. 000921-075141.18 27-22.96 88-31.10 5.1 17.8 * * *

38. 000925-044616.89 27-23.50 88-22.32 3.3 10.0 * * *

39. 001003-050216.82 27-13.64 88-29.10 5.1 25.3 * * *

40. 001018-142214.62 27-21.28 88-29.10 4.5 24.5 * * *

41. 001117-213502.15 27-14.51 88-32.82 3.8 10.0 * * *

42. 001123-065050.82 27-15.01 88-18.10 4.3 23.5 * * *

43. 001201-035523.01 27-12.38 88-18.81 4.3 13.0 * * *

44. 010209-095929.88 27-17.95 88-16.98 3.2 5.4 * * *

(continued on next page)

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Table 1 (continued)

Sl. no. Event (YYMMDD-HMMSS) Lat (8N) Long (8E) Mag (Mb) Depth (km) Singtam Gezing Mangan Gangtok Lachen Chungthang Jorethang Aritar Melli

45. 010104-023638.89 27-13.35 88-21.46 4.1 21.3 * * *

46. 010105-180834.26 27-13.98 88-22.73 3.0 10.0 * * *

47. 011116-042438.85 27-21.48 88-10.03 4.0 19.0 * * *

48. 011115-143251.00 27-09.10 88-18.10 4.1 21.2 * * *

49. 011123-103104.04 27-22.20 88-26.18 4.8 10.0 * * *

50. 011202-224108.27 27-15.10 88-27.92 5.6 26.2 * * *

51. 011203-010022.79 27-21.56 88-14.20 3.4 3.5 * * *

52. 020316-112647.00 27-21.10 88-35.10 5.1 20.0 * * *

53. 020408-115025.80 27-28.26 88-20.47 3.0 10.0 * * *

54. 020422-093640.01 27-43.81 88-57.85 5.1 19.4 * * *

55. 020424-141804.71 27- 5.39 88-52.01 3.5 5.3 * * *

56. 020425-045812.86 27-17.08 88-37.72 5.1 22.9 * * *

57. 020425-011644.82 27- 8.86 88-49.83 4.5 10.0 * * *

58. 020425-082136.09 27-14.54 88-47.00 5.2 25.4 * * *

59. 020425-113005.57 27-19.11 88-18.10 5.1 26.4 * * *

60. 020426-030442.79 27-28.78 88-24.24 4.4 10.0 * * *

61. 020426-095755.09 27-21.10 88-35.10 4.3 10.0 * * *

62. 020426-155142.54 27-18.10 88-38.47 4.1 10.0 * * *

63. 020427-120349.41 27-34.49 88-39.58 2.5 12.1 * * *

64. 020428-054806.41 27-11.24 88-43.03 5.0 24.1 * * *

65. 020429-013853.14 27-24.67 88-23.33 3.7 6.0 * * *

66. 020429-062843.47 27-14.18 88-35.10 4.2 10.0 * * *

67. 020429-124356.14 27-12.00 88-42.25 5.0 27.8 * * *

68. 020430-064601.89 26-54.67 88-32.71 3.9 10.0 * * *

69. 020430-134913.09 27-21.07 88-48.09 3.0 9.9 * * *

70. 020501-024400.51 27-21.10 88-35.10 4.7 17.1 * * *

71. 020501-114553.25 27-34.45 88-32.43 4.4 10.0 * * *

72. 020502-102838.32 26-58.13 88-52.06 4.0 10.0 * * *

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Fig. 5. Site response contours overlain on an elevation (TIN) map of Sikkim at (a) 3 Hz, and (b) 9 Hz.


term, PijðfkÞ; and a site effect term, SiðfkÞ:

OijðfkÞ ¼ EjðfkÞPijðfkÞSiðfkÞ ð1Þ

Taking the natural logarithm, Eq. (1) becomes:

ln OijðfkÞ ¼ ln EjðfkÞ þ ln PijðfkÞ þ ln SiðfkÞ ð2Þ

This linear expression often forms the basis of separating

the source, path, and site effects (Nath et al., 2000, 2002).

The processing starts with Butterworth bandpass filtering

of each accelerogram within a 0.5–16 Hz frequency range

for each event. Let the S-wave amplitude and the

background noise amplitude be AijðfkÞ and BijðfkÞ; respect-

ively. Then the signal amplitude spectrum at the frequency

fk is expressed as,

OijðfkÞ ¼ AijðfkÞ2 BijðfkÞ ð3Þ

A five-point smoothing window is chosen for all the

spectral amplitudes at the central frequencies 1, 3, 5, 7, 9

and 11 Hz to reduce randomness in the data. Thus the

receiver function SRijðfkÞ can be computed at each i site for

the jth event at the central frequency fk as,

SRijðfkÞ ¼

1ffiffi2

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiabsHijðfkÞl

2NS þ absHijðfkÞl

2EW

q

absVijðfkÞð4Þ

where, HijðfkÞlNS;HijðfkÞlEW and VijðfkÞ are the Fourier

spectra of the NS, EW and vertical components

respectively. The event average SR contours at 3 and 9 Hz

are overlain on the elevation map of Sikkim and displayed

in Fig. 5a and b respectively.

4.2. Peak ground acceleration and resonance frequency

The peak horizontal acceleration (PGA) is the most

commonly used measure of the intensity of shaking at a site

and is taken to be the largest absolute value of the horizontal

acceleration recorded at a site. It is also possible to extract

the maximum of the vector sum of two orthogonal

components of the horizontal ground acceleration recorded

at a site. As the peak accelerations (a) and peak velocities

(v) are usually associated with motions of different

frequencies, the ratio v=a can be related to the frequency

content of the motion. For earthquake motions that include

several frequencies, the parameter 2pv=a can be interpreted

as the period of vibration of an equivalent harmonic wave,

thereby providing an indication of the predominant period

of the ground motion. Power spectrum also plays a

significant role in deciding the predominant frequency of

ground motion at each site.

4.3. Seismological thematic mapping

GIS application to seismological thematic mapping

generated strong ground motion attributes, namely, contours

of SR at the central frequencies 1, 3, 5, 7, 9, and 11 Hz;

Fig. 6. (a) Union of soil site class, lithology and site response at 5 Hz.

Drainage and PGA contours are overlain on the combined coverage.

(b) Union of soil class, lithology and site response at 5 Hz. Drainage and

resonance frequency contours are overlain on the combined coverage.


PGA, and resonance frequency (RF) with built up polygon

topology having attributes classified within the range of

assigned values. The composite site-condition vector

coverage helped in the polygon interpolation of

seismological attributes using least square error energy

minimization criterion. Even the strong motion network and

epicenters of the events form two vector layers for future

overlay on the hazard map. The PGA and RF contours

overlain on the composite site condition map of Sikkim in

Fig. 6a and b show the spatial variation of strong motion

impact in the region.

5. GIS integration and microzonational model

For microzonation and hazard delineation, all of the

above themes are reclassified into two broad groups,

Geological and Seismological. A representative flow chart

for microzonation is depicted in Fig. 7. The Geological

themes include slope (S), soil (SO), lithology (G) and

landslides (L). Each theme has a weight in the 4–1 scale

depending on their contribution towards a seismic

hazard, the higher weight in this case being attached to

slope due to the rugged topography. For determining

the weight of a theme, we used Saaty’s Analytical Hierarchy

Process (Shahid et al., 2003). In this method, a matrix of

pairwise comparisons (ratios) between the factors is

constructed and used to derive the individual normalized

weights of each factor. The pairwise comparison is

performed by calculating the principal eigen vector of the

matrix and the elements of the matrix are in the range of 0 to

1 summing to ‘1’ in each column. The weights for each

theme can be calculated by averaging the values in each row

of the matrix. These weights will also sum to ‘1’ and can be

used in deriving the weighted sum of rating or scores of each

region of cells or polygon of the mapped layers. Since the

values within each thematic map/layer vary significantly,

they are classified into various ranges or types known as the

features of a layer. These features are then assigned ratings

or scores within each layer, normalized between 0–1.

Similarly, Seismological themes are also assigned

weights on the 3–1 scale. A Seismo-geological pairwise

comparison table is also generated for combined integration

of both groups taken together. The layer-wise

normalized weight and feature scores for all themes are

given in Table 2.

All of the thematic maps are registered with one another

through ground control points and integrated step-by-step

Fig. 7. Flow chart depicting quasi-probabilistic microzonation model.


using the aggregation method in GIS. The geologic

hazard potential index GHZI for the geological class is

calculated as,

GHZI ¼ ½SwSr þ SOwSOr þ GwGr þ LwLr�=Sw ð5Þ

where w represents the normalized weight of a theme

and r the normalized rank of a feature in the theme.

GHZI is a dimensionless quantity that helps in indexing

the probability of seismic hazard and hence microzona-

tion of a region. In Fig. 8a the integrated GHZI layer is

displayed with six distinct zones, namely, ,16, 16–33,

33–50, 50–66, 66–83, .83%. It is evident that the

lesser Himalaya poses a comparatively high earthquake

hazard.

Similarly, the seismological themes are integrated to

form the seismic hazard potential index layer SHZI as,

SHZI ¼ ½SRwSRr þ PGAwPGAr þ RFwRFr�=Sw ð6Þ

w being the normalized weight of a theme and r the

normalized rank of a feature in the theme. The evolved

Table 2

Normalized weight and feature rating of the thematic maps

Theme Weight Feature Rating Normalized rating

Site response 0.25 ,2.20 1 0

2.20–2.25 2 0.0556

2.25–2.30 3 0.1111

2.30–2.35 4 0.1667

· · · · · · · · ·

· · · · · · · · ·

2.90–2.95 16 0.8333

2.95–3.00 17 0.8889

3.00–3.05 18 0.9444

.3.05 19 1

Peak ground acceleration 0.2143 ,0.00115 1 0

0.00115–0.00130 2 0.0256

0.00130–0.00145 3 0.0513

0.00145–0.00160 4 0.0769

· · · · · · · · ·

· · · · · · · · ·

0.00640–0.00655 37 0.9231

0.00655–0.00670 38 0.9487

0.00670–0.00685 39 0.9744

.0.00685 40 1

Resonance frequency 0.1786 ,6.10 1 0

6.10–6.20 2 0.0333

6.20–6.30 3 0.0667

6.30–6.40 4 0.1

· · · · · · · · ·

· · · · · · · · ·

8.70–8.80 28 0.9

8.80–8.90 29 0.9333

8.90–9.00 30 0.9667

.9.00 31 1

Slope (%) 0.1429 ,15 1 0

15–30 2 0.2

31–45 3 0.4

46–60 4 0.6

61–75 5 0.8

.75 6 1

Soil (b) 0.1071 IB 1 0

IC 2 0.3333

II 3 0.6667

III 4 1

Lithology 0.0714 Higher Himalayan crystalline 1 0

Lesser Himalayan 2 1

Landslides 0.0357 No landslides 1 0

Landslides 2 1


layers are displayed for SR at a central frequency of 3 Hz in

Fig. 8b. Six zones indicated as %SHZI are ,22, 22–37,

37–52, 52–67, 67–82, .82%, the highest being at the

Singtam strong motion site.

Finally, Geological and Seismological attributes are

integrated together to generate full-scale microzonation

map using CHZI as,

CHZI ¼ ½SRwSRr þ PGAwPGAr þ RFwRFr þ SwSr

þ SOwSOr þ GwGr þ LwLr�=Sw ð7Þ

The notations have their usual meanings. The combined

microzonation map is presented in Fig. 9 at a central

frequency of 3 Hz. In this layer, six major zones are again

mapped, namely ,15, 15–31, 31–47, 47–63, 63–78,

.78%. This diagram represents the first order microzona-

tion map of Sikkim.

6. Discussion and conclusions

The Darjeeling–Sikkim Himalayas are well known to

be seismically active. The microearthquake survey in the

Darjeeling and Sikkim tract (Fig. 2a and b) showed that

MBT is seismogenic down to the mantle in this region

with an estimated b-value of 0.61 (Kayal, 2001). All 72

events recorded by the strong motion network also

clustered in the same source zone (Fig. 2c and d). Fixing

of the seismicity to delineate the hazard and to determine

the resulting risk cannot be fruitfully undertaken for

macro-regions. This calls for a multi-disciplinary effort on

the part of scientists and engineers to create a seismic

hazard map through microzonation by incorporating a

variety of factors including geology, topography, sub-soil

condition, building morphology, earthquake ground

motion amplification, etc.

The process of overlaying, combining and finally

integration of various geologic and seismologic maps

are complicated spatial operations that are optimally

performed in a GIS environment. The integration of

lithounit, soil site class and slope coverages provide the

site-condition of the Sikkim region on which the

seismological attributes are overlain. The South Sikkim

exhibits higher SR values (Fig. 5) compared to the North,

which is mostly covered by competent bedrock. The

South Sikkim, being mostly covered by coarse textured

skeletal soils susceptible to water erosion and landslide

hazards, represents weak geological formations and hence

has higher site amplification values. This is also the case

with PGA and RF (Fig. 6). The overall PGA and

resonance frequencies in the lesser Himalaya are much

higher than those in the higher Himalayan crystalline

rocks, the northern Sikkim being seismically more stable.

As MBT is approached, the attribute values increase

further. Referring to Fig. 8b, six SHI zones with ,22,

22–37, 37–52, 52–67, 67–82, .82% at 3 Hz could be

Fig. 8. (a) Hazard zonation map of Sikkim by GIS integration of

geological attributes (low frequency site effects centered at 3 Hz).

(b) Seismic hazard zonation map of Sikkim by GIS integration of strong

motion data generated seismological attributes (low frequency site effects

centered at 3 Hz).


identified, the maximum seismic hazard probability being

at the strong motion site of Singtam. These zones can be

qualitatively classified as no-hazard to having a maximum

probability of experiencing earthquake hazard, with low,

fair, moderate and high hazard potentials in between. In

the microzonation vector layer of integrated seismological

and geological themes (Fig. 9), again six major zones are

mapped, namely ,15, 15–31, 31–47, 47–63, 63–78,

.78% at the low frequency end, with similar

probabilistic risk classifications. The maximum risk is

attached to a probability greater than 78% in the Singtam

and adjoining area.

The advantage of using GIS for seismic hazard mapping

lies in its capability to calculate areas and lengths of

geometric features.

The microzonation map presented here may be useful

for land use planning or for making hazard mitigation

decisions. The geologic site condition map is an

initial model to describe areas that may exhibit

different seismic shaking characteristics during future

earthquakes.

Acknowledgements

The author is grateful for the support provided by the

Department of Science and Technology, Government

of India under the earmarked research grants

DST/23(97)/ESS/95 and DST/23(218)/ESS/98. Department

of Science and Technology, Government of Sikkim helped

in monitoring the strong motion network in the interior of

Sikkim. The critical review and constructive suggestions of

the anonymous referees and the editorial board have

significantly enhanced the paper’s contents with better

scientific exposition.

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Fig. 9. Seismic microzonation map of Sikkim by GIS integration of major geological and strong motion data generated seismological attributes.


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