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In this article, the spatial variation of ground motion in Imphal City has been estimated by the finite-fault seismological model coupled with site response analysis. The important seismic sources around Imphal City have been identified from the fault map and past seismicity data. The rock level acceleration time histories at Imphal City for the 1869 Cachar (Mw 7.5) earthquake and a hypothetical Mw 8.1 event in the Indo-Burma subduction zone have been estimated by a stochastic finite-fault model. Soil investigation data of 122 boreholes have been collected from several construction projects in Imphal City. Site response analysis has been carried out and the surface level ground motion has been determined for Imphal City for these two earthquake events. The results are presented in the form of peak ground acceleration (PGA) contour map. From the present study it has been ascertained that the maximum amplification for PGA over Imphal City is as high as 2.5. The obtained contour maps can serve as guidelines for identifying vulnerable areas and disaster mitigation in Imphal City. [ABSTRACT FROM AUTHOR]

Peninsular India (PI), which lies south of 24°N 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. [ABSTRACT FROM AUTHOR]

This article presents an engineering approach to estimate the existing seismic hazard for Mumbai city. After assembling a catalogue of past earthquakes and analysing the database statistically, the recurrence relation for the control region is found out. This is used to compute the probability of ground motion that can be induced by each of the twenty-three known faults that exist around the city. Final results are presented in the form of peak ground acceleration and response spectra, for two different return periods. These results can be directly used by engineers as basic inputs in earthquake-resistant design of structures in and around Mumbai. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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, whereas 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 interannual 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. [ABSTRACT FROM AUTHOR]