Seismic risk assessment for developing countries : Pakistan as a case study

Modern Earthquake Risk Assessment (ERA) methods usually require seismo-tectonic information for Probabilistic Seismic Hazard Assessment (PSHA) that may not be readily available in developing countries. To bypass this drawback, this paper presents a practical event-based PSHA method that uses instrumental seismicity, available historical seismicity, as well as limited information on geology and tectonic setting. Historical seismicity is integrated with instrumental seismicity to determine the long-term hazard. The tectonic setting is included by assigning seismic source zones associated with known major faults. Monte Carlo simulations are used to generate earthquake catalogues with randomized key hazard parameters. A case study region in Pakistan is selected to demonstrate the effectiveness of the method. The results indicate that the proposed method produces seismic hazard maps consistent with previous studies, thus being suitable for generating such maps in regions where limited data are available. The PSHA procedure is developed as an integral part of an ERA framework named EQRAM. The framework is also used to determine seismic risk in terms of annual losses for the study region

Strong ground motion at Bhuj city during the Kutch earthquake

In the absence of near field strong motion records, the level of ground motion during the devastating 26 January 2001 earthquake has to be found by indirect means. For the city of Bhuj, three broad band velocity time histories have been recorded by India Meteorological Department. In this paper these data are processed to obtain an estimate of strong ground motion at Bhuj. It is estimated that the peak ground acceleration at Bhuj was of the order of 0.38 g. Ground motion in the surrounding region is indirectly found using available spectral response recorder (SRR) data. These instrument-based results are compared with analytical results obtained from a half-space regional model

Intrinsic mode functions and a strategy for forecasting Indian monsoon rainfall

Indian monsoon rainfall data is shown to be decomposable into six empirical time series, called intrinsic mode functions. This helps one to identify the first empirical mode as a nonlinear part and the remaining as the linear part of the data. The nonlinear part is handled by artificial neural network (ANN) techniques, where as the linear part is amenable for modeling through simple regression concepts. It is found that the proposed model explains between 75 to 80% of the inter annual variability (IAV) of eight regional rainfall series considered here. The model is efficient in statistical forecasting of rainfall as verified on an independent subset of the data series. It is demonstrated that the model is capable of foreshadowing the drought of 2002, with the help of only antecedent data. The statistical forecast of All India rainfall for the year of 2004 is 80.34 cms with a standard deviation of 3.3 cms. This expected value is 94.25% of the longterm climatic average

Forecasting of seasonal monsoon rainfall at subdivision level

It is shown that time series data of monsoon seasonal rainfall at subdivision level is decomposable into six uncorrelated components. These narrowband processes called intrinsic mode functions, in decreasing order of importance, reflect the influence of ENSO, sunspot activity and tidal cycle on inter annual rainfall variability. The decomposition helps in proposing a statistical method to forecast monsoon rainfall in the three subdivisions of Karnataka

Strong motion compatible source geometry

Strong motion array records are analyzed in this paper to identify and map the source zone of four past earthquakes. The source is represented as a sequence of double couples evolving as ramp functions, triggering at different instants, distributed in a region yet to be mapped. The known surface level ground motion time histories are treated as responses to the unknown double couples on the fault surface. The location, orientation, magnitude, and risetime of the double couples are found by minimizing the mean square error between analytical solution and instrumental data. Numerical results are presented for Chi-Chi, Imperial Valley, San Fernando, and Uttarakashi earthquakes. Results obtained are in good agreement with field investigations and those obtained from conventional finite fault source inversions

Estimation of seismic spectral acceleration in Peninsular India

Peninsular India (PI), which lies south of $24^oN$ latitude, has experienced several devastating earthquakes in the past. However, very few strong motion records are available for developing attenuation relations for ground acceleration, required by engineers to arrive at rational design response spectra for construction sites and cities in PI. Based on a well-known seismological model, the present paper statistically simulates ground motion in PI to arrive at an empirical relation for estimating 5% damped response spectra, as a function of magnitude and source to site distance, covering bedrock and soil conditions. The standard error in the proposed relationship is reported as a function of the frequency, for further use of the results in probabilistic seismic hazard analysis

Strong Ground Motion Estimation During the Kutch, India Earthquake

In the absence of strong motion records, ground motion during the 26th stop January, 2001 Kutch, India earthquake, has been estimated by analytical methods. A contour map of peak ground acceleration (PGA) values in the near source region is provided. These results are validated by comparing them with spectral response recorder data and field observations. It is found that very near the epicenter, PGA would have exceeded 0.6 g. A set of three aftershock records have been used as empirical Green's functions to simulate ground acceleration time history and 5% damped response spectrum at Bhuj City. It is found that at Bhuj, PGA would have been 0.31 g-0.37 g. It is demonstrated that source mechanism models can be effectively used to understand spatial variability of large-scale ground movements near urban areas due to the rupture of active faults