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The purpose of this thesis is to conduct a detailed examination of the forward-directivity characteristics of near-fault ground motions produced in the 2010-11 Canterbury earthquakes, including evaluating the efficacy of several existing empirical models which form the basis of frameworks for considering directivity in seismic hazard assessment. A wavelet-based pulse classification algorithm developed by Baker (2007) is firstly used to identify and characterise ground motions which demonstrate evidence of forward-directivity effects from significant events in the Canterbury earthquake sequence. The algorithm fails to classify a large number of ground motions which clearly exhibit an early-arriving directivity pulse due to: (i) incorrect pulse extraction resulting from the presence of pulse-like features caused by other physical phenomena; and (ii) inadequacy of the pulse indicator score used to carry out binary pulse-like/non-pulse-like classification. An alternative ‘manual’ approach is proposed to ensure 'correct' pulse extraction and the classification process is also guided by examination of the horizontal velocity trajectory plots and source-to-site geometry. Based on the above analysis, 59 pulse-like ground motions are identified from the Canterbury earthquakes , which in the author's opinion, are caused by forward-directivity effects. The pulses are also characterised in terms of their period and amplitude. A revised version of the B07 algorithm developed by Shahi (2013) is also subsequently utilised but without observing any notable improvement in the pulse classification results. A series of three chapters are dedicated to assess the predictive capabilities of empirical models to predict the: (i) probability of pulse occurrence; (ii) response spectrum amplification caused by the directivity pulse; (iii) period and amplitude (peak ground velocity, PGV) of the directivity pulse using observations from four significant events in the Canterbury earthquakes. Based on the results of logistic regression analysis, it is found that the pulse probability model of Shahi (2013) provides the most improved predictions in comparison to its predecessors. Pulse probability contour maps are developed to scrutinise observations of pulses/non-pulses with predicted probabilities. A direct comparison of the observed and predicted directivity amplification of acceleration response spectra reveals the inadequacy of broadband directivity models, which form the basis of the near-fault factor in the New Zealand loadings standard, NZS1170.5:2004. In contrast, a recently developed narrowband model by Shahi & Baker (2011) provides significantly improved predictions by amplifying the response spectra within a small range of periods. The significant positive bias demonstrated by the residuals associated with all models at longer vibration periods (in the Mw7.1 Darfield and Mw6.2 Christchurch earthquakes) is likely due to the influence of basin-induced surface waves and non-linear soil response. Empirical models for the pulse period notably under-predict observations from the Darfield and Christchurch earthquakes, inferred as being a result of both the effect of nonlinear site response and influence of the Canterbury basin. In contrast, observed pulse periods from the smaller magnitude June (Mw6.0) and December (Mw5.9) 2011 earthquakes are in good agreement with predictions. Models for the pulse amplitude generally provide accurate estimates of the observations at source-to-site distances between 1 km and 10 km. At longer distances, observed PGVs are significantly under-predicted due to their slower apparent attenuation. Mixed-effects regression is employed to develop revised models for both parameters using the latest NGA-West2 pulse-like ground motion database. A pulse period relationship which accounts for the effect of faulting mechanism using rake angle as a continuous predictor variable is developed. The use of a larger database in model development, however does not result in improved predictions of pulse period for the Darfield and Christchurch earthquakes. In contrast, the revised model for PGV provides a more appropriate attenuation of the pulse amplitude with distance, and does not exhibit the bias associated with previous models. Finally, the effects of near-fault directivity are explicitly included in NZ-specific probabilistic seismic hazard analysis (PSHA) using the narrowband directivity model of Shahi & Baker (2011). Seismic hazard analyses are conducted with and without considering directivity for typical sites in Christchurch and Otira. The inadequacy of the near-fault factor in the NZS1170.5: 2004 is apparent based on a comparison with the directivity amplification obtained from PSHA.

The results of seismic hazard analysis (SHA) play a crucial role in assessing seismic risks and mitigating seismic hazards. SHA calculations generally involve magnitude and distance distribution models, and ground motion prediction models as components. Many alternatives have been proposed for these component models. SHA calculations may be demanding in terms of processing power depending on the models and analysis parameters involved, and especially the size of the site for which the analysis is to be performed. In this thesis, we develop a grid-based SHA application which provides the necessary computational power and enables the investigation of the effects of applying different models. Our application not only includes various already implemented component models but also allows integration of newly developed ones.

Seismic hazard analysis is concerned with estimating risk to human populations due to earthquakes and the other natural disasters that they cause. In many parts of the world, earthquake-generated tsunamis are especially dangerous. Assessing the risk for seismic disasters relies on historical data that indicate which fault zones are capable of supporting significant earthquakes. Due to the nature of geologic time scales, the era of seismological data collection with modern instruments has captured only a part of the Earth's seismic hot zones. However, non-instrumental records, such as anecdotal accounts in newspapers, personal journals, or oral tradition, provide limited information on earthquakes that occurred before the modern era. Here, we introduce a method for reconstructing the source earthquakes of historical tsunamis based on anecdotal accounts. We frame the reconstruction task as a Bayesian inference problem by making a probabilistic interpretation of the anecdotal records. Utilizing robust models for simulating earthquakes and tsunamis provided by the software package GeoClaw, we implement a Metropolis-Hastings sampler for the posterior distribution on source earthquake parameters. In this work, we present our analysis of the 1852 Banda Arc earthquake and tsunami as a case study for the method. Our method is implemented as a Python package, which we call tsunamibayes. It is available, open-source, on GitHub: https://github.com/jwp37/tsunamibayes.

Seismic hazard analysis is concerned with estimating risk to human populations due to earthquakes and the other natural disasters that they cause. In many parts of the world, earthquake-generated tsunamis are especially dangerous. Assessing the risk for seismic disasters relies on historical data that indicate which fault zones are capable of supporting significant earthquakes. Due to the nature of geologic time scales, the era of seismological data collection with modern instruments has captured only a part of the Earth's seismic hot zones. However, non-instrumental records, such as anecdotal accounts in newspapers, personal journals, or oral tradition, provide limited information on earthquakes that occurred before the modern era. Here, we introduce a method for reconstructing the source earthquakes of historical tsunamis based on anecdotal accounts. We frame the reconstruction task as a Bayesian inference problem by making a probabilistic interpretation of the anecdotal records. Utilizing robust models for simulating earthquakes and tsunamis provided by the software package GeoClaw, we implement a Metropolis-Hastings sampler for the posterior distribution on source earthquake parameters. In this work, we present our analysis of the 1852 Banda Arc earthquake and tsunami as a case study for the method. Our method is implemented as a Python package, which we call tsunamibayes. It is available, open-source, on GitHub: https://github.com/jwp37/tsunamibayes.

Properly accounting for the uncertainties in predicting ground motion parameters is critical for Probabilistic Seismic Hazard Analyses (PSHA). This is particularly important for critical facilities that are designed for long return period motions. Non-ergodic PSHA is a framework that allows for this proper accounting of uncertainties. This, in turn, allows for more informed decisions by designers, owners and regulating agencies. The ergodic assumption implies that the standard deviation applicable to a specific source-path-site combination is equal to the standard deviation estimated using a database with multiple source-path-site combinations. The removal of the ergodic assumption requires dense instrumental networks operating in seismically active zones so that a sufficient number of recordings are made. Only recently, with the advent of networks such as the Japanese KiK-net network has this become possible. This study contributes to the state of the art in earthquake engineering and engineering seismology in general and in non-ergodic seismic hazard analysis in particular. The study is divided in for parts. First, an automated protocol was developed and implemented to process a large database of strong ground motions for GMPE development. A comparison was conducted between the common records in the database processed within this study and other studies. The comparison showed the viability of using the automated algorithm to process strong ground motions. On the other hand, the automated algorithm resulted in narrower usable frequency bandwidths because of the strict criteria adopted for processing the data. Second, an approach to include path-specific attenuation rates in GMPEs was proposed. This approach was applied to a subset of the KiK-net database. The attenuation rates across regions that contains volcanoes was found to be higher than other regions which is in line with the observations of other researchers. Moreover, accounting for the path-specific attenuation rates reduced the aleatoric variability associated with predicting pseudo-spectral accelerations. Third, two GMPEs were developed for active crustal earthquakes in Japan. The two GMPEs followed the ergodic and site-specific formulations, respectively. Finally, a comprehensive residual analysis was conducted to find potential biases in the residuals and propose models to predict some components of variability as a function of some input parameters. / Ph. D.

Planet earth is restless and one cannot control its inside activities and vibrations those leading to natural hazards. Earthquake is one of such natural hazards that have affected the mankind most. Most of the causalities due to earthquakes happened not because of earthquakes as such, but because of poorly designed structures which could not withstand the earthquake forces. The improper building construction techniques adopted and the high population density are the major causes of the heavy damage due to earthquakes. The damage due to earthquakes can be reduced by following proper construction techniques, taking into consideration of appropriate forces on the structure that can be caused due to future earthquakes. The steps towards seismic hazard evaluation are very essential to estimate an optimal and reliable value of possible earthquake ground motion during a specific time period. These predicted values can be an input to assess the seismic vulnerability of an area based on which new construction and the restoration works of existing structures can be carried out. A large number of devastating earthquakes have occurred in India in the past. The northern region of India, which is along the plate boundary of the Indian plate with the Eurasian plate, is seismically very active. The north eastern movement of Indian plate has caused deformation in the Himalayan region, Tibet and the North Eastern India. Along the Himalayan belt, the Indian and Eurasian plates converge at the rate of about 50 mm/year (Bilham 2004; Jade 2004). The North East Indian (NEI) region is known as one of the most seismically active regions in the world. However the peninsular India, which is far away from the plate boundary, is a stable continental region, which is considered to be of moderate seismic activity. Even though, the activity is considered to be moderate in the Peninsular India, world’s deadliest earthquake occurred in this region (Bhuj earthquake 2001). The rapid drifting of Indian plate towards Himalayas in the north east direction with a high velocity along with its low plate thickness might be the cause of high seismicity of the Indian region. Bureau of Indian Standard has published a seismic zonation map in 1962 and revised it in 1966, 1970, 1984 and 2002. The latest version of the seismic zoning map of India assigns four levels of seismicity for the entire Country in terms of different zone factors. The main drawback of the seismic zonation code of India (BIS-1893, 2002) is that, it is based on the past seismic activity and not based on a scientific seismic hazard analysis. Several seismic hazard studies, which were taken up in the recent years, have shown that the hazard values given by BIS-1893 (2002) need to be revised (Raghu Kanth and Iyengar 2006; Vipin et al. 2009; Mahajan et al. 2009 etc.). These facts necessitate a comprehensive study for evaluating the seismic hazard of India and development of a seismic zonation map of India based on the Peak Ground Acceleration (PGA) values. The objective of this thesis is to estimate the seismic hazard of entire India using updated seismicity data based on the latest and different methodologies. The major outcomes of the thesis can be summarized as follows. An updated earthquake catalog that is uniform in moment magnitude, has been prepared for India and adjoining areas for the period till 2010. Region specific magnitude scaling relations have been established for the study region, which facilitated the generation of a homogenous earthquake catalog. By carefully converting the original magnitudes to unified MW magnitudes, we have removed a major obstacle for consistent assessment of seismic hazards in India. The earthquake catalog was declustered to remove the aftershocks and foreshocks. Out of 203448 events in the raw catalog, 75.3% were found to be dependent events and remaining 50317 events were identified as main shocks of which 27146 events were of MW ≥ 4. The completeness analysis of the catalog was carried out to estimate completeness periods of different magnitude ranges. The earthquake catalog containing the details of the earthquake events until 2010 is uploaded in the website the catalog was carried out to estimate completeness periods of different magnitude ranges. The earthquake catalog containing the details of the earthquake events until 2010 is uploaded in the website the catalog was carried out to estimate completeness periods of different magnitude ranges. The earthquake catalog containing the details of the earthquake events until 2010 is uploaded in the website A quantitative study of the spatial distribution of the seismicity rate across India and its vicinity has been performed. The lower b values obtained in shield regions imply that the energy released in these regions is mostly from large magnitude events. The b value of northeast India and Andaman Nicobar region is around unity which implies that the energy released is compatible for both smaller and larger events. The effect of aftershocks in the seismicity parameters was also studied. Maximum likelihood estimations of the b value from the raw and declustered earthquake catalogs show significant changes leading to a larger proportion of low magnitude events as foreshocks and aftershocks. The inclusions of dependent events in the catalog affect the relative abundance of low and high magnitude earthquakes. Thus, greater inclusion of dependent events leads to higher b values and higher activity rate. Hence, the seismicity parameters obtained from the declustered catalog is valid as they tend to follow a Poisson distribution. Mmax does not significantly change, since it depends on the largest observed magnitude rather than the inclusion of dependent events (foreshocks and aftershocks). The spatial variation of the seismicity parameters can be used as a base to identify regions of similar characteristics and to delineate regional seismic source zones. Further, Regions of similar seismicity characteristics were identified based on fault alignment, earthquake event distribution and spatial variation of seismicity parameters. 104 regional seismic source zones were delineated which are inevitable input to seismic hazard analysis. Separate subsets of the catalog were created for each of these zones and seismicity analysis was done for each zone after estimating the cutoff magnitude. The frequency magnitude distribution plots of all the source zones can be found at http://civil.iisc.ernet.in/~sitharam . There is considerable variation in seismicity parameters and magnitude of completeness across the study area. The b values for various regions vary from a lower value of 0.5 to a higher value of 1.5. The a value for different zones vary from a lower value of 2 to a higher value of 10. The analysis of seismicity parameters shows that there is considerable difference in the earthquake recurrence rate and Mmax in India. The coordinates of these source zones and the seismicity parameters a, b & Mmax estimated can be directly input into the Probabilistic seismic hazard analysis. The seismic hazard evaluation of the Indian landmass based on a state-of-the art Probabilistic Seismic Hazard Analysis (PSHA) study has been performed using the classical Cornell–McGuire approach with different source models and attenuation relations. The most recent knowledge of seismic activity in the region has been used to evaluate the hazard incorporating uncertainty associated with different modeling parameters as well as spatial and temporal uncertainties. The PSHA has been performed with currently available data and their best possible scientific interpretation using an appropriate instrument such as the logic tree to explicitly account for epistemic uncertainty by considering alternative models (source models, maximum magnitude in hazard computations, and ground-motion attenuation relationships). The hazard maps have been produced for horizontal ground motion at bedrock level (Shear wave velocity ≥ 3.6 km/s) and compared with the earlier studies like Bhatia et al., 1999 (India and adjoining areas); Seeber et al, 1999 (Maharashtra state); Jaiswal and Sinha, 2007 (Peninsular India); Sitharam and Vipin, 2011 (South India); Menon et al., 2010 (Tamilnadu). It was observed that the seismic hazard is moderate in Peninsular shield (except the Kutch region of Gujarat), but the hazard in the North and Northeast India and Andaman-Nicobar region is very high. The ground motion predicted from the present study will not only give hazard values for design of structures, but also will help in deciding the locations of important structures such as nuclear power plants. The evaluation of surface level PGA values is of very high importance in the engineering design. The surface level PGA values were evaluated for the entire study area for four NEHRP site classes using appropriate amplification factors. If the site class at any location in the study area is known, then the ground level PGA values can be obtained from the respective map. In the absence of VS30 values, the site classes can be identified based on local geological conditions. Thus this method provides a simplified methodology for evaluating the surface level PGA values. The evaluation of PGA values for different site classes were evaluated based on the PGA values obtained from the DSHA and PSHA. This thesis also presents VS30 characterization of entire country based on the topographic gradient using existing correlations. Further, surface level PGA contour map was developed based on the same. Liquefaction is the conversion of formally stable cohesionless soils to a fluid mass, due to increase in pore pressure and is prominent in areas that have groundwater near the surface and sandy soil. Soil liquefaction has been observed during the earthquakes because of the sudden dynamic earthquake load, which in turn increases the pore pressure. The evaluation of liquefaction potential involves evaluation of earthquake loading and evaluation of soil resistance to liquefaction. In the present work, the spatial variation of the SPT value required to prevent liquefaction has been estimated using a probabilistic methodology, for entire India. To summarize, the major contribution of this thesis are the development of region specific magnitude correlations suitable for Indian subcontinent and an updated homogeneous earthquake catalog for India that is uniform in moment magnitude scale. The delineation and characterization of regional seismic source zones for a vast country like India is a unique contribution, which requires reasonable observation and engineering judgement. Considering complex seismotectonic set up of the country, the present work employed numerous methodologies (DSHA and PSHA) in analyzing the seismic hazard using appropriate instrument such as the logic tree to explicitly account for epistemic uncertainties considering alternative models (For Source model, Mmax estimation and Ground motion prediction equations) to estimate the PGA value at bedrock level. Further, VS30 characterization of India was done based on the topographic gradient, as a first level approach, which facilitated the development of surface level PGA map for entire country using appropriate amplification factors. Above factors make the present work very unique and comprehensive touching various aspects of seismic hazard. It is hoped that the methodology and outcomes presented in this thesis will be beneficial to practicing engineers and researchers working in the area of seismology and geotechnical engineering in particular and to the society as a whole.

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.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22259号 / 理博第4573号 / 新制||理||1657(附属図書館) / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 James Mori, 教授 久家 慶子, 教授 岩田 知孝 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

In many areas of the world, seismic hazards pose a great risk to both human and natural populations. In particular, earthquake-induced tsunamis are especially dangerous to many areas in the Pacific. The study and quantification of these seismic events can both help scientists better understand how these natural hazards occur and help at-risk populations make better preparations for these events. However, many events of interest occurred too long ago to be recorded by modern instruments, so data on these earthquakes are sparse and unreliable. To remedy this, a Bayesian method for reconstructing the source earthquakes for these historical tsunamis based on anecdotal data, called TsunamiBayes, has been developed and used to study historical events that occurred in 1852 and 1820. One drawback of this method is the computational cost to reconstruct posterior distributions on tsunami source parameters. In this work, we improve on the TsunamiBayes method by introducing higher-order MCMC methods, specifically the Hamiltonian Monte Carlo (HMC) method to increase sample acceptance rate and therefore reduce computation time. Unfortunately the exact gradient for this problem is not available, and so we make use of a surrogate gradient via a neural network fitted to the forward model. We examine the effects of this surrogate gradient HMC sampling method on the posterior distribution for an 1852 event in the Banda Sea, compare results to previous results collected usisng random walk, and note the benefits of the surrogate gradient in this context.