Many researchers have pointed out that the accumulation of strain energy in the Penninsular Indian Shield region may lead to earthquakes of significant magnitude(Srinivasan and Sreenivas, 1977; Valdiya, 1998; Purnachandra Rao, 1999; Seeber et al., 1999; Ramalingeswara Rao, 2000; Gangrade and Arora, 2000). However very few studies have been carried out to quantify the seismic hazard of the entire Pennisular Indian region. In the present study the seismic hazard evaluation of South Indian region (8.0° N - 20° N; 72° E - 88° E) was done using the deterministic and probabilistic seismic hazard approaches. Effects of two of the important geotechnical aspects of seismic hazard, site response and liquefaction, have also been evaluated and the results are presented in this work. The peak ground acceleration (PGA) at ground surface level was evaluated by considering the local site effects. The liquefaction potential index (LPI) and factor of safety against liquefaction wee evaluated based on performance based liquefaction potential evaluation method. The first step in the seismic hazard analysis is to compile the earthquake catalogue. Since a comprehensive catalogue was not available for the region, it was complied by collecting data from different national (Guaribidanur Array, Indian Meterorological Department (IMD), National Geophysical Research Institute (NGRI) Hyderabad and Indira Gandhi Centre for Atomic Research (IGCAR) Kalpakkam etc.) and international agencies (Incorporated Research Institutions for Seismology (IRIS), International Seismological Centre (ISC), United States Geological Survey (USGS) etc.). The collected data was in different magnitude scales and hence they were converted to a single magnitude scale. The magnitude scale which is chosen in this study is the moment magnitude scale, since it the most widely used and the most advanced scientific magnitude scale. The declustering of earthquake catalogue was due to remove the related events and the completeness of the catalogue was analysed using the method suggested by Stepp (1972). Based on the complete part of the catalogue the seismicity parameters were evaluated for the study area. Another important step in the seismic hazard analysis is the identification of vulnerable seismic sources. The different types of seismic sources considered are (i) linear sources (ii) point sources (ii) areal sources. The linear seismic sources were identified based on the seismotectonic atlas published by geological survey of India (SEISAT, 2000). The required pages of SEISAT (2000) were scanned and georeferenced. The declustered earthquake data was superimposed on this and the sources which were associated with earthquake magnitude of 4 and above were selected for further analysis. The point sources were selected using a method similar to the one adopted by Costa et.al. (1993) and Panza et al. (1999) and the areal sources were identified based on the method proposed by Frankel et al. (1995). In order to map the attenuation properties of the region more precisely, three attenuation relations, viz. Toto et al. (1997), Atkinson and Boore (2006) and Raghu Kanth and Iyengar (2007) were used in this study. The two types of uncertainties encountered in seismic hazard analysis are aleatory and epistemic. The uncertainty of the data is the cause of aleatory variability and it accounts for the randomness associated with the results given by a particular model. The incomplete knowledge in the predictive models causes the epistemic uncertainty (modeling uncertainty). The aleatory variability of the attenuation relations are taken into account in the probabilistic seismic hazard analysis by considering the standard deviation of the model error. The epistemic uncertainty is considered by multiple models for the evaluation of seismic hazard and combining them using a logic tree. Two different methodologies were used in the evaluation of seismic hazard, based on deterministic and probabilistic analysis. For the evaluation of peak horizontal acceleration (PHA) and spectral acceleration (Sa) values, a new set of programs were developed in MATLAB and the entire analysis was done using these programs. In the deterministic seismic hazard analysis (DSHA) two types of seismic sources, viz. linear and point sources, were considered and three attenuation relations were used. The study area was divided into small grids of size 0.1° x 0.1° (about 12000 grid points) and the PHA and Sa values were evaluated for the mean and 84th percentile values at the centre of each of the grid points. A logic tree approach, using two types of sources and three attenuation relations, was adopted for the evaluation of PHA and Sa values. Logic tree permits the use of alternative models in the hazard evaluation and appropriate weightages can be assigned to each model. By evaluating the 84th percentile values, the uncertainty in spectral acceleration values can also be considered (Krinitzky, 2002). The spatial variations of PHA and Sa values for entire South India are presented in this work. The DSHA method will not consider the uncertainties involved in the earthquake recurrence process, hypocentral distance and the attenuation properties. Hence the seismic hazard analysis was done based on the probabilistic seismic hazard analysis (PSHA), and the evaluation of PHA and Sa values were done by considering the uncertainties involved in the earthquake occurrence process. The uncertainties in earthquake recurrence rate, hypocentral location and attenuation characteristic were considered in this study. For evaluating the seismicity parameters and the maximum expected earthquake magnitude (mmax) the study area was divided into different source zones. The division of study area was done based on the spatial variation of the seismicity parameters ‘a’ and ‘b’ and the mmax values were evaluated for each of these zones and these values were used in the analysis. Logic tree approach was adopted in the analysis and this permits the use of multiple models. Twelve different models (2 sources x 2 zones x 3 attenuation) were used in the analysis and based on the weightage for each of them; the final PHA and Sa values at bed rock level were evaluated. These values were evaluated for a grid size of 0.1° x 0.1° and the spatial variation of these values for return periods of 475 and 2500 years (10% and 2% probability of exceedance in 50 years) are presented in this work. Both the deterministic and probabilistic analyses highlighted that the seismic hazard is high at Koyna region. The PHA values obtained for Koyna, Bangalore and Ongole regions are higher than the values given by BIS-1893(2002). The values obtained for south western part of the study area, especially for parts of kerala are showing the PHA values less than what is provided in BIS-1893(2002). The 84th percentile values given DSHA can be taken as the upper bound PHA and Sa values for South India. The main geotechnical aspects of earthquake hazard are site response and seismic soil liquefaction. When the seismic waves travel from the bed rock through the overlying soil to the ground surface the PHA and Sa values will get changed. This amplification or de-amplification of the seismic waves depends on the type of the overlying soil. The assessment of site class can be done based on different site classification schemes. In the present work, the surface level peak ground acceleration (PGA) values were evaluated based on four different site classes suggested by NEHRP (BSSC, 2003) and the PGA values were developed for all the four site classes based on non-linear site amplification technique. Based on the geotechnical site investigation data, the site class can be determined and then the appropriate PGA and Sa values can be taken from the respective PGA maps. Response spectra were developed for the entire study area and the results obtained for three major cities are discussed here. Different methods are suggested by various codes to Smooth the response spectra. The smoothed design response spectra were developed for these cities based on the smoothing techniques given by NEHRP (BSSC, 2003), IS code (BIS-1893,2002) and Eurocode-8 (2003). A Comparison of the results obtained from these studies is also presented in this work. If the site class at any location in the study area is known, then the peak ground acceleration (PGA) values can be obtained from the respective map. This provides a simplified methodology for evaluating the PGA values for a vast area like South India. Since the surface level PGA values were evaluated for different site classes, the effects of surface topography and basin effects were not taken into account. The analysis of response spectra clearly indicates the variation of peak spectral acceleration values for different site classes and the variation of period of oscillation corresponding to maximum Sa values. The comparison of the smoothed design response spectra obtained using different codal provisions suggest the use of NEHRP(BSSC, 2003) provisions. The conventional liquefaction analysis method takes into account only one earthquake magnitude and ground acceleration values. In order to overcome this shortfall, a performance based probabilistic approach (Kramer and Mayfield, 2007) was adopted for the liquefaction potential evaluation in the present work. Based on this method, the factor of safety against liquefaction and the SPT values required to prevent liquefaction for return periods of 475 and 2500 years were evaluated for Bangalore city. This analysis was done based on the SPT data obtained from 450 boreholes across Bangalore. A new method to evaluate the liquefaction return period based on CPT values is proposed in this work. To validate the new method, an analysis was done for Bangalore by converting the SPT values to CPT values and then the results obtained were compared with the results obtained using SPT values. The factor of safety against liquefaction at different depths were integrated using liquefaction potential index (LPI) method for Bangalore. This was done by calculating the factor of safety values at different depths based on a performance based method and then the LPI values were evaluated. The entire liquefaction potential analysis and the evaluation of LPI values were done using a set of newly developed programs in MATLAB. Based on the above approaches it is possible to evaluate the SPT and CPT values required to prevent liquefaction for any given return period. An analysis was done to evaluate the SPT and CPT values required to prevent liquefaction for entire South India for return periods of 475 and 2500 years. The spatial variations of these values are presented in this work. The liquefaction potential analysis of Bangalore clearly indicates that majority of the area is safe against liquefaction. The liquefaction potential map developed for South India, based on both SPT and CPT values, will help hazard mitigation authorities to identify the liquefaction vulnerable area. This in turn will help in reducing the liquefaction hazard.

Past earthquakes have demonstrated that Indian sub-continent is highly vulnerable to earthquake hazards. It has been estimated that about 59 percent of the land area of the Indian subcontinent has potential risk from moderate to severe earthquakes (NDMA, 2010). Major earthquakes in the last 20 years such as Khillari (30th September 1993), Jabalpur (22nd May 1997), Chamoli (29th March 1999) and Bhuj (26th January 2001) earthquakes have resulted in more than 23,000 deaths and extensive damage to infrastructure (NDMA, 2010). Although it is well known that the major earthquake hazard prone areas in India are the Himalayan region (inter-plate zone) and the north-east region, (subduction zone) the seismicity of Peninsular India cannot be underestimated. Many studies (Seeber et al., 1999; Rao, 2000; Gangrade & Arora, 2000) have proved that the seismicity of Peninsular India is significantly high and may lead to earthquakes of sizeable magnitude. This necessitates a seismic zonation for the country, as well as various regions in it. Seismic zonation is the first step towards an effective earthquake risk mitigation study. Seismic zonation is a process in which a large region is demarcated into small zones based on the levels of earthquake hazard. Seismic zonation is generally carried out at three different levels based on the aerial extent of the region, importance of site and the population. They are micro-level, meso-level and macro-level. The macro-level zonation is generally carried out for large landmass such as a state or a country. The earthquake hazard parameters used for macro-level zoning are generally evaluated with less reliability. The typical example of a macro-level zonation is the seismic zonation map of India prepared by BIS-1893 (2002), where the entire India is demarcated into four seismic zones based on past seismicity and tectonic conditions. Generally the macro-level seismic zonation is carried out based on peak horizontal acceleration (PHA) estimated at bedrock level without giving emphasis on the local soil conditions. Seismic zonation at the meso-level is carried out for cities and urban centers with a population greater than 5,00,000. The earthquake hazard parameters, for the meso-level zonation are evaluated with greater degree of reliability, compared to the macro-level zoning. The micro-level zonation is carried out for sites which host critical installations such as nuclear power plants (NPPs). As the NPPs are considered as very sensitive structures, the earthquake parameters, for the micro-level zonation of the NPP sites are estimated with a highest degree of reliability. The local soil conditions and site effects are properly counted for carrying out the micro as well as the meso-level zonation. Several researchers have carried out meso-level zonation considering effects of all major earthquake hazards such as PHA, site amplification, liquefaction (Mohanty et al., 2007; Nath et al., 2008; Sitharam & Anbazhagan, 2008 etc.) Even though the above definitions and descriptions are available for various levels of zonation, the key issue lies in the adoption of the suitable one for a given region. There are only a few guidelines available regarding the use of a particular level of zonation for a given study area. Based on the recommendation of the disaster management authority, the government of India has initiated the seismic zonation of all major cities in India. As it is evident that large resources are required in order to carry out seismic site characterization and site effect estimation, both the micro and meso-level zonations cannot be carried out for all these cities. Hence there is a need to propose appropriate guidelines to define the suitability of each level zonation for various re-gions in the country. Moreover there are many methodologies available for site characterization and estimation of site effects such as site amplification and liquefaction. The appropriateness of these methodologies for various levels of seismic zonations also needs to be assessed in order to optimize use of resources for seismic zonation. Hence in the present study, appropriate techniques for site characterization and earthquake hazard estimation for regions at different scale levels were determined. Using the appropriate techniques, the seismic zonation was carried out both at the micro and macro-level, incorporating all major earthquake hazards. The state of Karnataka and the Kalpakkam NPP site were chosen for the macro and micro−level seismic zonation in this study. Kalpakkam NPP site is situated in Tamil Nadu, India, 70 kilometres south of Chennai city. The NPP site covers an area of 3000 acres. The site is situated along the Eastern coastal belt of India known as Coromandel coast with Bay of Bengal on the east side. The NPP site host major facilities such as Indira Gandhi Centre for Atomic Research (IGCAR), Madras Atomic Power Station (MAPS), Fast Reactor Fuel Reprocessing (FRFC) Plant, Fast Breeder Test Reactor (FBTR), Prototype Fast Breeder Reactor (PFBR) etc. The state Karnataka lies in the southern part of India, covering an area of 1,91,791 km2, thus approximately constituting 5.83% of the total geographical area of India. Both the study areas lie in the Indian Peninsular which is identified as one of the most prominent and largest Precambrian shield region of the world. The first and foremost step towards the seismic zonation is to prepare a homogenised earthquake catalogue. All the earthquake events within 300 km radius from the boundary of two study areas were collected from various national and international agencies. The earthquake events thus obtained were found to be in different magnitude scales and hence all these events were converted to the moment magnitude scale. A declustering procedure was applied to the earthquake catalogue of the two study area in order to remove aftershocks, foreshocks and dependent events. The completeness analysis was carried out and the seismicity parameters for the two study areas were evaluated based on the complete part of earthquake catalogues. The next major step toward the estimation of earthquake hazard and seismic zonation is the identification and mapping of the earthquake sources. Three source models, mainly; 1) linear source model, 2) point source model and 3) areal source model were used in the present study for characterizing earthquake sources in the two study areas. All the linear sources (faults and lineaments) within 300 km radius from the boundary of two study areas were identified and mapped from SEISAT (2000). In addition to SEISAT (2000), some lineaments were also mapped from the works of Ganesha Raj & Nijagunappa (2004). These lineaments and faults were mapped and georeferenced in a GIS platform on which earthquake events were then super-imposed to give seismotectonic atlas. Seismotectonic atlas was prepared for both the study areas. The point source model (Costa et al. 1993; Panza et al. 1999) and areal source model (Frankel, 1995) were also adopted in this work. Deterministic and probabilistic seismic hazard analysis was found to be appropriated for micro, meso and macro-level zonations. Hence in the present study, the seismic hazard at bedrock level, both at the micro and macro-level were evaluated using the deterministic as well as the probabilistic methodologies. In order to address the epistemic uncertainties in source models and attenuation relations, a logic tree methodology was incorporated with the deterministic and probabilistic approaches. As the deterministic seismic hazard analysis (DSHA) considers only the critical scenario, knowing the maximum magnitude that can occur at a source and the shortest distance between that source and the site and the peak horizontal acceleration (PHA) at that site is estimated using the frequency dependent attenuation relation. Both for the micro as well as the macro-level, the DSHA was carried out, considering grid sizes of 0.001◦ × 0.001◦ and 0.05◦ × 0.05◦respectively. A MATLAB program was developed to evaluate PHA at the center of each of these grid points. The epistemic uncertainties in source models and attenuation relations have been addressed using a logic tree approach (Bommer et al., 2005). A typical logic tree consists of a series of nodes to which several models with different weightages are assigned. Allotment of these weightages to different branch depends upon the degree of uncertainties in the model, and its accuracy. However the sum of all weightages of different branches at a particular node must be unity. Two types of seismic sources are employed in DSHA and they are linear and smoothed point sources. Since both the types of sources were of equal importance, equal weightages were assigned to each of them. The focal depth in the present study was taken as 15 km. The attenuation properties of the region were modelled using three attenuation relations, Viz. Campbell & Bozorgnia (2003), Atkinson & Boore (2006) and Raghu Kanth & Iyengar (2007). The attenuation relation proposed by Raghu Kanth & Iyengar (2007) was given higher weightage of 0.4 since it was devel-oped for the Indian peninsular region. The attenuation relations by Atkinson & Boore (2006) and Campbell & Bozorgnia (2003) which were developed for Eastern North American shield region, shared equal weightages of 0.3. Maps showing spatial variation of PHA value at bedrock level, for both micro and macro-level are presented. Response spectra at the rock level for important location in the two study areas were evaluated for 8 different periods of oscillations, and the results are presented in this thesis. Probabilistic seismic hazard analysis (PSHA) incorporating logic tree approach was per-formed for both micro as well as macro-level considering similar grid sizes as in DSHA. Two types of seismic sources considered in the PSHA are linear sources and smoothed gridded areal sources (Frankel, 1995) with equal weightage distribution in the logic tree structure. Smoothed gridded areal sources can also account the scattered earthquake events. The hypocentral distance was calculated by considering a focal depth of 15 km, as in the case of DSHA method. A MAT-LAB program was developed for PSHA. The same attenuation relations employed in DSHA were used in PSHA as well with the same weightage allotment in logic tree structure. Considering all major uncertainties, a uniform hazard response spectrum (UHRS), showing the variation of PHA values with the mean annual rate of exceedance (MARE), was evaluated for each grid point. From the uniform hazard response spectrum, the PHA corresponding to any return period can be evaluated. Maps showing the spatial variation of PHA value at bedrock level, corresponding to 475 year and 2500 year return periods for both micro and macro-level are presented. Response spectra at the rock level for important location in two study areas were evaluated for eight different periods of oscillations, and the results are presented in this thesis. In order to assess various earthquake hazards like ground motion amplification and soil liquefaction, a thorough understanding of geotechnical properties of the top overburden soil mass is essential. As these earthquake hazards strongly depend on the geotechnical properties of the soil, site characterization based on these properties will provide a better picture of these hazards. In the present study, seismic site characterization was carried both at the micro and macro-level using average shear wave velocity for top 30 m overburden (Vs30). At the micro-level, the shear wave velocity profile at major locations was evaluated using multichannel analysis of surface waves (MASW) tests. MASW is an indirect geophysical method used in geotechnical investigations and near surface soil characterization based on the dispersion characteristics of surface waves (Park et al., 1999). The MASW test setup consists of 24-channel geophones of 4.5 Hz capacity. A 40 kg propelled energy generator (PEG) was used for generating surface wave. Based on the recordings of geophones, the dispersion characteristics of surface waves were evaluated in terms of a dispersion curve. The shear wave velocity (Vs) profile at a particular location was determined by performing inversion analysis (Xia et al., 1999). After the evaluation of V s profile at all major locations, the site characterization at the micro-level was carried out as per NEHRP (BSSC, 2003) and IBC (2009) recommendations. Maps showing the spatial distribution of various site classes at the micro-level are presented in this thesis. Standard penetration tests were also carried out in the site as part of subsurface investigation and in this study a new correlation between V s and corrected SPT-N values was also developed. Apart from carrying out site characterization, low strain soil stiffness profile was evaluated based on SPT and MASW data. In this work, seismic site characterization at the macro-level was also carried out. As it is not physically and economically viable to carry out geotechnical and geophysical testing for such a large area, like the Karnataka state, the seismic site characterization was carried out based on topographic slope maps. Wald & Allen (2007) has reported that the topographic slope is a perfect indicator of site conditions. Based on the correlation studies carried out for different regions, Wald & Allen (2007) has proposed slope ranges corresponding to each site class. In this study, the topographic map for the entire state of Karnataka was derived from ASTER Global Digital Elevation Model GDEM. This thesis also presents a comparison study between the Vs30map generated from topographic slope data and Vs30map developed using geophysical field tests, for Bangalore and Chennai. Based on this study, it is concluded that topographic slopes can be used for developing Vs30maps for meso and macro-level with reasonable accuracy. The topographic map for macro-level was generated at a grid size of 0.05◦ × 0.05◦. Based on the value of slope at a particular grid point, the Vs30for that grid point was assigned as per Wald & Allen (2007). A similar procedure was repeated for all the grid points. Spatial variation of various seismic site classes for the macro-level has been presented in this work. The site amplification hazard was estimated for both micro and the macro-level. The assessment of site amplification is very important for shallow founded structures and other geotechnical structures like retaining walls and dams, floating piles and underground structures as the possible earthquake damages are mostly due to extensive shaking. The site amplification hazard at the micro-level was estimated using 1D equivalent linear ground response analyses. The earthquake motion required for carrying out ground response analysis was simulated from a target response spectrum. 1D equivalent linear analyses were performed using SHAKE 2000 software. Spatial variations of surface level PHA values, site amplification, predominant frequency throughout the study area are presented in this work. As it is not physically viable to assess site amplification hazard at the macro-level using the 1D ground response analysis, the surface level PHA value for the entire state of Karnataka was estimated using a non-linear site amplification technique pro-posed by Raghu Kanth & Iyengar (2007). Based on the site class in which particular grid belongs and bedrock level PHA value, the amplification for that grid point was evaluated using regression equations developed by Raghu Kanth & Iyengar (2007). The liquefaction hazard both at the micro and macro-level was evaluated and included in this thesis. The micro-level liquefaction hazard was estimated in terms of liquefaction potential index (LPI) based on SPTN values (Iwasaki et al., 1982). As the LPI was evaluated by integrating the factor of safety against liquefaction (FSL) at all depths, it can effectively represent the liquefaction susceptibility of the soil column. LPI at the micro-level was evaluated by both deterministic as well as the probabilistic approaches. In the deterministic approach, the FSLat a particular depth was evaluated as the ratio of the cyclic resistance of the soil layer to the cyclic stress induced by earth-quake motion. The cyclic stress was estimated as per Seed & Idriss (1971), while the cyclic soil resistance was characterised from the corrected SPT-N values as proposed by Idriss & Boulanger (2006). However in the probabilistic method, the mean annual rate of exceedance (MARE) of factor of safety against liquefaction at different depth was estimated using SPT field test data by considering all uncertainties. From the MARE curve, the FS L for 475 year and 2500 year return period were evaluated. Once FS L at different depth were evaluated, the LPI for the borehole is calculated by integrating FS L for all depths. The liquefaction hazard at the macro-level was estimated in terms of SPT and CPT values required to prevent liquefaction at 3 m depth, using a probabilistic approach. The probabilistic approach accounts the contribution of several magnitudes acceleration scenarios on the liquefaction potential at a given site. Based on the methodology proposed by Kramer & Mayfield (2007), SPT and CPT values required to resist liquefaction corresponding to return periods of 475 years and 2500 years were evaluated at the macro-level. It has been observed that the spatial distribution of intensity of each these hazard in a region is distinct from the other due to the predominant influence of local geological conditions rather than the source characteristics of the earthquake. Hence it’ll be difficult to assess risk and vulnerability of a region when these hazards are treated separately. Thus, all major earthquake hazards are to be integrated to an index number, which effectively represents the combined effect of all hazards. In the present study, all major earthquake hazards were integrated to a hazard index value, both at the micro as well as macro-level using the Analytical Hierarchy Process (AHP) proposed by Saaty (1980). Both micro and macro-level seismic zonation was performed based on the spatial distribution of hazard index value. This thesis also presents the assessment of earthquake induced landslides at the macro-level in the appendix. Landslide hazards are a major natural disaster that affects most of the hilly regions around the world. This is a first attempt of it kind to evaluate seismically induced landslide hazard at the macro-level in a quantitative manner. Landslide hazard was assessed based on Newmark’s method (Newmark, 1965). The Newmark’s model considers the slope at the verge of failure and is modelled as a rigid block sliding along an incline plane under the influence of a threshold acceleration. The value of threshold acceleration depends upon the static factor of safety and slope angle. At the macro-level, the slope map for the entire state of Karnataka was derived from ASTER GDEM, considering a grid size of 50 m × 50 m. The earthquake motion which induces driving force on the slope to destabilize it was evaluated for each grid point with slope value 10 degree and above using DSHA. Knowing the slope value and peak horizontal acceleration (PHA) at a grid point, the seismic landslide hazard in terms of static factor of safety required to resist landslide was evaluated using Newmark’s method. This procedure is repeated for all grid points, having slope value 10 degree and above.