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Seismic Microzonation

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CHAPTER 1.
INTRODUCTION
1.1 GENERAL
Seismic hazard is defined as any physical phenomenon, such as ground shaking or
ground failure, which is associated with an earthquake and that, may produce adverse
effects on human activities.
Many earthquakes in the past have given many lessons that still have to be learnt
which are very essential to plan infrastructure and even to mitigate such calamities in
future. Very preliminary process of reducing the effects of earthquake is by assessing the
hazard itself. Till date Seismic hazard of the region has been represented in the form of
zonation map. Seismic zonation is usually carried out in two parts, one at macro level and
another at micro level. For a larger area like zonation of country or continent macro level is
adopted.
Macrozonation is carried out considering the seismicity, geology in larger scales
without considering geotechnical aspects. But microzonation is carried out in smaller scale
by considering regional seismicity, geology and local site conditions. Micro level zonations
are becoming important for the cities and urban centers due to increasing population
agglomeration in the cities, which result in rapid and unplanned constructions. The cities
are more hazardous and high risk areas even for the moderate earthquakes. Seismic
Microzonation is the first step to minimize seismic related loss of lives and damages.
Microzonation has generally been recognized as the most accepted tool in seismic hazard
assessment and risk evaluation and it is defined as the zonation with respect to ground
motion characteristics taking into account the source and site conditions.
Making improvements on the conventional macrozonation maps and regional
hazard maps, microzonation of a region generate detailed maps that predict the hazard at
much smaller scales. Seismic microzonation is the generic name for subdividing a region
into individual areas having different potentials, hazardous earthquake effects, defining
their specific seismic behavior for engineering design, land use and urban planning.
The basic steps of seismic microzonation are to model the rupture mechanism at the source
of an earthquake, evaluate the propagation of waves through the earth to the top of the
bedrock, determine the effects of local soil profile and thus develop a surface hazard map
indicating the vulnerability of the area to potential seismic hazards. Essentially
microzonation is required to compile three essential components of seismology,
geotechnical and structural engineering. Each component has to be dealt separately in
detail and represent variation of the essential parameters and then compile in fashion to
give final map for land use, city planning, disaster management and planning and post
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earthquake relief work. Seismic Microzonation falls into the category of “applied
research”. That is why it has to be upgraded and revised based on the latest information.
Seismology component involves understating seismicity of region and compiling
available geology data, deep geophysical data and earthquake data. Seismotectonic map
has to be prepared to show seismic sources and with past earthquakes to depict seismology
component. This is the base for seismic hazard analysis, where rock level hazard
parameters in the form of spectral or peak ground acceleration are mapped. Second
component consists of understanding geotechnical character of study area, estimating the
modification of seismic waves and its induced effects. Basically this involves assessment
of different effects due to seismic hazard identified in the seismology component.
These two components will be dealt in detail and discussed with respect to the
seismic zonation mapping. Third component involves assessment of damage potential of
buildings in the region and cost assessment which are called as seismic vulnerability and
risk assessment.
SEISMIC ZONATION MAP OF INDIA
Before 2002
(BIS, 1893-1970)
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BIS, 2002
1.2 FACTORS AFFECTING SEISMIC HAZARD AT A LOCATION
1. Earthquake magnitude
2. The source-to-site distance
3. Earthquake rate of occurrence (return period)
4. Duration of ground shaking
Earthquake Magnitude – The magnitude is a number that characterizes the
relative size of an earthquake. Quantitative measure of its strength in terms of energy
released at focus. It is a measure of the size of the earthquake source and is the same
number no matter where we are or what the shaking feels like. Magnitudes can be based on
any of the following:
Ml - local magnitude is defined as the logarithm of the maximum trace amplitude recorded
on a Wood-Anderson seismometer located 100km from the epicenter of the earthquake.
The local magnitude is the best known magnitude scale, but it is not always the most
appropriate scale for description of earthquake size.
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2. Mb – Body wave magnitude is based on the longitudinal wave amplitude and their
period. This magnitude scale becomes insensitive to the actual size of an earthquake for
magnitudes of 6.4 or greater.
3. Ms - surface wave magnitude is based on the amplitude of maximum ground
displacement caused by Rayleigh waves with a period of about 20 seconds and the
epicentral distance of the seismometer measured in degrees.
4. Mw – Moment magnitude is bases on the seismic moment M0, which is a direct
measure of the factors that produce rupture along the fault. This magnitude does not have
an upper limit. Where Lf and Wf are the length and width of a fault area, Sf is the average
slip on the fault during an earthquake in meters, μ is the shear modulus of the Earth crust.
The source-to-site distance - Much of the energy released by rupture along a fault
takes the form of stress waves. As stress waves travel away from the source of an
earthquake, they spread out and are partially absorbed by the materials they travel through.
As a result, the specific energy decreases with increasing distance from the source. The
distance between the source of an earthquake and particular site can be interpreted in
different ways.
Earthquake rate of occurrence (return period) - A return period is an estimate
of the interval of time between earthquakes. It is a statistical measurement denoting the
average recurrence interval over an extended period of time, and is usually required for
risk analysis.
Duration of ground motion – The duration of ground motion is related to the time required
for release of accumulated strain energy by rupture along the fault. As the length, or area, of
fault rupture increases, the time required for rupture increases. As a result, the duration of
ground motion increases with increasing earthquake magnitude.
1.3 REPRESENTATION OF SEISMIC HAZARD
The seismic hazard can be expressed in different ways: from simple observed
macroseismic fields, to seismostatistical calculations to analyse earthquake occurrences in
time and space and assessing their dynamic effects in a certain site or region, to
sophisticated seismogeological approaches to evaluating the maximum expected
earthquake effects on the Earth surface.
Representation of seismic hazard and ground motion includes
1) The selection and utilization of national ground motion maps;
2) The representation of site response effects; and
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3) The possible incorporation of other parameters and effects, including energy or
duration of ground motions, vertical ground motions, near source horizontal ground
motions, and spatial variations of ground motions.
Seismic hazard can be represented in different ways but most frequently in terms of values
or probability distributions of accelerations, velocities, or Displacements of either bedrock
or the ground surface.
1.4 SEISMIC HAZARD APPROACHES
Two different seismic hazard maps have been generated, one using deterministic
seismic microzonation map based on PGA from DSHA and another is the probabilistic
seismic microzonation map based on PGA from PSHA.
The major parameters used are PGA at rock level from deterministic and
probabilistic approaches, site response parameters of amplification and predominant
frequency, elevation levels to account topographical variation and factor of safety against
liquefaction. In both the maps, only rock level PGA is changed and other parameters are
kept similar.
Deterministic Seismic Hazard Analysis:Deterministic Seismic Hazard Analysis (DSHA) is done for a particular earthquake, either
assumed or realistic. The DSHA approach uses the known seismic sources sufficiently near
the site and available historical seismic and geological data to generate discrete, singlevalued events or models of ground motion at the site. Typically one or more earthquakes
are specified by magnitude and location with respect to the site. Usually the earthquakes
are assumed to occur on the portion of the site closest to the site. The site ground motions
are estimated deterministically, given the magnitude, source-to-site distance, and site
condition.
Probabilistic Seismic Hazard Analysis:Probabilistic seismic hazard analysis (PSHA) is the most widely used approach for
the determination of seismic design loads for engineering structures. The use of
probabilistic concept has allowed uncertainties in the size, location, and rate of recurrence
of earthquakes and in the variation of ground motion characteristics with earthquake size
and location to be explicitly considered for the evaluation of seismic hazard. In addition,
PSHA provides a frame work in which these uncertainties can be identified, quantified and
combined in a rational manner to provide a more complete picture of the seismic hazard.
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1.5 METHOLOGY
A general methodology in doing the seismic microzonation of a region can be divided into
the following four major heads:
1. Estimation of the ground motion parameters using the historical seismicity and
recorded earthquake motion data which includes the location of potential sources,
magnitude, mechanism, epicentral distances.
2. Site characterization using geological, geomorphological, geophysical and
geotechnical data.
3. Assessment of the local site effects which includes site amplification, predominant
frequency, liquefaction hazard, landslides, tsunami etc.
4. Preparation of the seismic microzonation maps.
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CHAPTER 2.
LITERATURE REVIEW
2.1 SEISMIC RISK ANALYSIS
Cornell (1968) introduces a method for the evaluation of the seismic risk of an
engineering project. The method is based on the influence of all potential sources of
earthquakes and the average activity rates. Arbitrary geographical relationships between
the site and potential point, line, or areal sources can be modelled with computational ease.
The results of this analysis presented in terms of ground motion parameter (such as peak
acceleration) versus average return period.
Gupta (2006) introduce Seismic hazard map for Northeast India based on the
uniform hazard response spectra for absolute acceleration. This approach is free from
regionalizing the seismotectonic sources to perform the hazard analysis. Also a developed
a new attenuation model for pseudo-spectral velocity by using recorded accelerogram in
Northeast India. The model is able to capture the frequency dependent variations in
pseudo-spectral velocity (PSV), and properly accounts for the effects of earthquake
magnitude, epicentral distance, and focal depth on the pseudo-spectral velocity (PSV)
spectral shapes, for both horizontal and vertical motions. This analysis maps provide much
more detailed and direct information about the seismic hazard.
Malik (2006) carried out works to obtain seismic hazard and spectral strong ground
motion on bed rock for the northeast Indian region using the complete and the extreme part
of the earthquake catalogue. The region has been divided into four major seismogenic
sources namely, the regional features in the Himalayas i.e., main boundary thrust and main
central thrust, eastern syntaxis, shillong massif and the north south trending arakan yoma
seismic belt. The seismic hazard is estimated for ten seismogenic zones which are further
subdivisions of these four seismogenic sources based on the seismotectonics modeling of
the area. The results of the probabilistic seismic hazard analysis may be used for the
seismic microzonation and for earthquake engineering use.
Kolathayar (2013) discussed seismic hazard analysis for the state of Tripura and
Mizoram in North East India to evaluate the ground motion at bedrock level. It was done
considering the available earthquake catalogs collected from different sources since 1731–
2010 within a distance of 500 km from the political boundaries of the states. Earthquake
data were declustered to remove the foreshocks and aftershocks in time and space window
and then statistical analysis is carried out for data completeness using the predictive ground
motion equations given by Atkinson and Boore (Bull Seismol Soc Am 93:1703–1729,
2003) and Gupta (Soil Dyn Earthq Eng 30:368–377, 2010) for subduction belt. The results
of this analysis were presented in the form of hazard curve, peak ground acceleration
(PGA) and uniform hazard spectra.
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2.2 MICROZONATION USING GIS APPROACH
Nath (2004) introduced seismic ground motion hazard map in the Sikkim Himalaya
with local and regional site conditions incorporated through geographic information
system. The geological themes are united to form the basic condition coverage of the
region. The seismological themes were assigned normalized weights and feature ranks
following a pair-wise comparison hierarchical approach and later integrated to evolve the
seismic hazard map. When geological and seismological layers are integrated together
through GIS, microzonation map is prepared.
The advantage of using GIS for seismic hazard mapping lies in its capability to
calculate areas and lengths of geometric features. The hazard maps presented here may be
useful for land use planning or for making hazard mitigation decisions. These maps are
generally better representation of seismic hazard including site-specific analysis, and may
be used for recognizing hazardous areas at a regional scale. The geologic site condition
map is an initial model to describe areas that may exhibit different seismic shaking
characteristics during future earthquakes.
Pal (2007) prepared first order seismic microzonation map of Delhi using five
thematic layers viz., Peak Ground Acceleration (PGA) contour, different soil types up to 6
m depth, geology, groundwater fluctuation and bedrock depth, integrated on GIS platform.
The integration is performed following a pair-wise comparison of Analytical Hierarchy
Process (AHP).
This study aimed at identifying tiny zones that would be vulnerable during
earthquakes. Seismic microzonation is aimed for this reason.The seismic microzonation
map thus generated will be of immense help for the Urban Development Authorities for
planning of future construc-tion projects. It will also be of use for assessment of seismic
risk to the existing construction, defense installation, heavy industry, and important
structures like dams, nuclear power stations and other public utility services.
Ganapathy (2011) produced first level seismic microzonation map of Chennai city
in a GIS platform using the themes, Peak Ground Acceleration (PGA), Shear wave
velocity at 3 m, Geology, Ground water fluctuation and bed rock depth.
The near potential seismic sources were identified from the remote-sensing study
and seismo-tectonic details from published literatures. The peak ground acceleration for
these seismic sources were estimated based on the attenuation relationship. The analysis
involved grid datasets (the discrete datasets from different themes were converted to grids)
to compute the final seismic hazard grid through integration and weightage analysis of the
source themes. The resultant map is useful information in construction planning of
forthcoming buildings. Also it is helpful as a base material to identify seismic risk.
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Manahiloh (2018) introduced Shear wave velocity and soil type microzonation
using neural networks and geographic information system. A microzonation algorithm that
combines neural networks (NNs) and geographic information system (GIS) is developed.In
the field, standard penetration and downhole tests are conducted. Atterberg limit test and
sieve analysis are performed on soil specimens retrieved during field-testing. The field and
laboratory data are used as inputs, in the integrated NNs-GIS algorithm, for developing the
microzonation of shear wave velocity and soil type of a selected site. The algorithm is
equipped with the ability to automatically update the microzonation maps upon addition of
new data.The approach could be adopted for microzonation of liquefaction potential,
landslide risks, settlements, etc.The detailed soil condition maps generated with the
proposed algorithm could be used in construction site selection, risk analysis, and
geotechnical engineering designs.
2.3 MICROZONATION ASSESSMENT
Ram (1997) discussed probabilistic assessment of Earthquake Hazards in the
North-East Indian Peninsula and Hindukush Region. The probability of the occurrence of
great earthquakes with magnitude greater than 7.0 during a specified interval of time was
estimated on the basis of four probabilistic models, namely, Weibull, Gamma, Lognormal
and Exponential for the NE Indian peninsula and Hindukush regions. The model
parameters had been estimated by the method of Maximum Likelihood Estimates (MLE)
and the Method of Moments (MOM). It should be mentioned that the result is related to the
assumption that the process of earthquake occurrence is temporally stable.
Sitharam (2014) described deterministic as well as probabilistic methods attempted
for seismic hazard assessment of Tripura and Mizoram states at bedrock level condition.
An updated earthquake catalogue is collected from various national and international
seismological agencies. The homogenization, declustering and data completeness analysis
of events have been carried out before hazard evaluation. Seismicity parameters have been
estimated using G–R relationship for each source zone. Ground motion equations
(Atkinson and Boore 2003; Gupta 2010) were validated with the observed PGA (peak
ground acceleration) values before use in the hazard evaluation.
Results are presented in the form of PGA using both DSHA (deterministic seismic
hazard analysis) and PSHA (probabilistic seismic hazard analysis) with 2 and 10%
probability of exceedance in 50 years, and spectral acceleration (T = 0. 2 s, 1.0 s) for both
the states (2% probability of exceedance in 50 years).
The hazard map developed using both the methods (DSHA and PSHA) provide a
clear idea about the measure of variability or degree of uncertainty/errors involved in the
estimated hazard values for a location in a quantitative manner/form. These maps can be
used as a direct input in site response study to know the surface level hazard. These maps
also provide useful information for other purposes, such as estimation of earthquake
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insurance premium, identifying most vulnerable locations and selection of an appropriate
location for important infrastructure and the most possible severe locations for detailed site
specific evaluation of seismic hazards. The seismic hazard analysis presented here is an
important step towards an accurate evaluation of seismic hazard potential in the area.
Gandhi (2018) had given a methodoly to estimate the effect of soil on ground motion
and to estimate the strong ground motion parameters at surface, soil modeling and the
ground response analysis have been conducted along uniformly distributed boreholes
drilled up to a depth of 50 m. The methodology is divided into three parts (i) Estimation of
depth of Engineering Bed layer (EBL) (a layer with a shear wave velocity 400 m/
s≤Vs≤750 m/s, N value>80 and minimum soil variation below it) through soil modeling,
(ii) Estimation of Ground Motion at EBL due to scenario earthquake at nearby active fault
and (iii) Estimation of surface strong ground motion using 1D ground response analysis
through SHAKE 2000 program.
2.4 MICROZONATION USING GEO-TECHNICAL METHODS
Nakamura (1989) describe a new processing method that employ microtremor
observation yet producing accurate estimation of characteristic of ground motion,
investigation with boring. The method used vertical component and horizontal component.
The method is based on the assumption that the ratio of horizontal and vertical spectra of
surface treamor as an appropriate transfer function. The method can supplement the boring
investigation results for proper and minute estimation of the characteristic of surface layer
and it is expected to demonstrate validity in collection of fundamental data for estimation
of detailed earthquake damage.
Tokimatsu (2005) introduced a methodology for estimating the S-wave velocity
profile of subsurface soils using both microtremor dispersion curve and H/V spectrum. In
the inversion, both microtremor dispersion and H/V data are assumed to be the Rayleighwave dispersion curve and the surface (both Rayleigh and Love) wave H/V spectrum that
have been theoretically derived by taking into account the effects of their fundamental and
higher modes. Sensitivity analyses indicate that the surface-wave H/V ratio is sensitive to
the bedrock VS structure more than the Rayleigh-wave phase velocity, confirming that the
proposed joint inversion including H/V spectrum is promising.
Boulanger (2006) discussed Semi-empirical procedures for evaluating the
liquefaction potential of saturated cohesion less soils during earthquakes.The stress
reduction factor (rd), earthquake magnitude scaling factor for cyclic stress ratios
(MSF), overburden correction factor for cyclic stress ratios (Ks), and the overburden
normalization factor for penetration resistances (CN) are discussed and modified
relations are presented. These modified relations are used in re-evaluations of the
SPT and CPT case history databases. Based on these re-evaluations, revised SPT- and
CPT-based liquefaction correlations are recommended for use in practice. The
reliability of any liquefaction evaluation depends directly on the quality of the site
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characterization, including the quality (and not necessarily the quantity) of the in situ and
laboratory test data. The importance of quality field and laboratory work cannot be
overstated.
Anbazhagan (2010) carried out the liquefaction potential analysis to estimate the
liquefaction return period. The entire range of peak ground acceleration (PGA) and
earthquake magnitudes was used in the evaluation of liquefaction return period. The
seismic hazard analysis was done using probabilistic approach to evaluate the peak
horizontal acceleration at bed rock level. The soil resistance for the area was characterized
using the standard penetration test (SPT) values obtained from boreholes. These SPT data
along with the PGA values obtained from the probabilistic seismic hazard analysis were
used to evaluate the liquefaction return period for the area. The entire process of
liquefaction potential evaluation, starting from collection of earthquake data, identifying
the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return
period were carried out, and the entire analysis was done based on the probabilistic
approach.
Das (2018) carried out the liquefaction potential of Agartala City in Northeast
India. The evaluation liquefaction potential are obtained using borehole SPT data were
collected from geotechnical consultancy. Dynamic properties of soil are determined using
SPT data. The cyclic shear stress of the soil layers are estimated considering the peak
surface ground acceleration 0.36g. Idriss and Boulanger (2010)and Boulanger and Idriss
(2015 and 2014) methodology are adopted to identify the liquefaction potential in terms of
factor of safety and probability. The results are presented in maps on Geographical
Information System (GIS) platform using the QGIS software. The liquefaction potential
maps are much useful for the professional engineers, government agencies and disaster
management authorities for future development and planning of the city against
liquefaction failure.
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CHAPTER 3.
OBJECTIVES AND SCOPE
SCOPE •
Providing useful information for land use planning.
•
Providing basic seismic hazard information for regional damage potential estimate.
•
Providing information on site effects to be accounted for, in design of new structure.
OBJECTIVE •
•
To define seismic actions for designing or improving the resistance of structure
such as building, bridges and plants,
To plan land use so as to reduce the level of hazard.
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CHAPTER 4.
CONCLUSION
This report is prepared aiming towards the analysis of seismic microzonation. The seismic
hazard analysis may be used for the seismic microzonation and for earthquake engineering
use. It will also be of use for assessment of seismic risk to the existing construction,
defence installation, heavy industry, and important structures like dams, nuclear power
stations and other public utility services.
Based on the literature study a summary has been framed. Subsequently, effort has
been made to find out the scope of work area and finally, an objective of the present work is
reported.
15
REFERENCE
•
Allin, C., Cornell (1968), “Engineering Seismic Risk Analysis”, Bulletin of the
Seismological Society of America. Vol. 58, No. 5, pp. 1583-1606.
•
Arai, H. and Tokimatsu, K. (2005), “S-Wave Velocity Profiling by Joint Inversion
of Microtremor Dispersion Curve and Horizontal-to-Vertical (H/V) Spectrum”,
Bulletin of the Seismological Society of America, Vol. 95, No. 5, pp. 1766-1778.
•
Das, S., Gupta, I.D., Gupta, V.K. (2006), “A Probabilistic Seismic Hazard Analysis
of Northeast India”, Earthquake Spectra, Volume 22, No. 1, pages 1–27.
•
Ganapathy, G. P. (2011), “First level seismic microzonation map of Chennai city – a
GIS approach”, Nat. Hazards Earth Syst. Sci., 11, 549– 559, doi:10.5194/nhess11-549-2011.
•
Idriss, I. M. and Boulanger, R. W. (2006) “Semi-empirical procedures for
evaluating liquefaction potential during earthquakes”, Soil. Dyn. Earthq. Eng., 26,
115-130.
•
Mohanty, W. K., Walling, M. Y., Nath, S. K., and Pal, I. (2007), “First order
seismic microzonation of Delhi”, India using Geographic Information system
(GIS), Nat.
Hazard, 40, 245-260.
•
Mohammad, M. N., Mohammad, S. M., Manahiloha, K.N., (2018) “Shear
wave velocity and soil type microzonation using neural networks and
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http://dx.doi.org/10.1016/j.soildyn.2017.10.001.
•
Mohan, K., Rastogi, B. K., Pancholi, V., Gandhi, D. (2018) “Seismic hazard
assessment at micro level in Gandhinagar (the capital of Gujarat, India) considering
soil effects”, https://doi.org/10.1016/j.soildyn.2018.03.007.
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Nakamura, Y. (1989) “A method for dynamic characteristic estimation of
subsurface using microtreamor on the ground surface”, Q. Rert. RTRI Jpn. 30, 2533.
•
Nath, S. K.,(2004) “ Seismic hazard mapping and microzonation in the
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motion attributes”, Nat. Hazard, 31, 319-342.
16
•
•
Parvez, I. A. And Ram, A. (1997) “Probabilistic assessment of earthquake hazards
in the Northeast Indian peninsula and Hindukush regions”, Pure appl. Geophys.
149, 731-746.
Sharma, M. L., Malik, S. (2006) “Probabilistic seismic hazard analysis and
estimation of spectral strong ground motion on bed rock in north east India”, 4th
international conference on earthquake engineering, Taipei, Taiwan, pp 12-13.
•
Sil, A., Sitharam, T. G. And kolathayar, V. (2013) “Probabilistic seismic hazard
analysis of Tripura and Mizoram states”, Nat. Hazards 68, no.2, 1089-1108.
•
Sitharam, T. G. and Sil, A. (2014) “Comprehensive seismic hazard assessment of
Tripura and Mizoram states”, J. Earth Syst. Sci. 123, No. 4, June 2014, pp. 837–
857.
•
Vipin, K. S., Sitharam, T. G., Anbazhagan, P. (2010), “Probabilistic Evaluation of
Seismic Soil Liquefaction Potential Based on SPT Data”, Nat Hazards, 53:547–
560.
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