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A software (EQK_SRC_PARA) has been developed to estimate spectral parameters of earthquake source spectrum, namely: low frequency displacement spectral level (Ω 0 ), corner frequency above which spectrum decays with a rate of 2 (f c ), the cut-off frequency above which the spectrum again decays (f max ) and the rate of decay above f max (N). A Brune's source model [1,2] that yield a fall-off of 2 beyond corner frequency is considered with high cut-off frequency factor presented by Boore [3] that fits well for frequencies greater than f max . The software EQK_SRC_PARA is written in MATLAB and uses input data in Sesame ASCII Format (SAF) format. The obtained spectral parameters have been used to estimate source parameters (e.g., seismic moment, source dimension and stress drop etc.) and to develop scaling laws for the study region. The cut-off frequency "f max " can also be studied and interpreted to confirm about its origin.

Earthquake Early Warning (EEW) system is a real-time earthquake damage mitigation system. It detects, analyzes and transmits information of the impending event at the potential user sites. In the present study, an attempt has been made to develop a multi-parameter-based EEW algorithm for accurate and reliable issuance of EEW. In the present study, not only the individual parameters such as maximum predominant period (t max p ), average period (t c ) , peak displacement (P d ), cumulative absolute velocity and root sum of squares cumulative velocity have been used to develop an algorithm but also various combinations have been attempted to issue alarm. The criterion for issuing warning is based on the alarm status of combinations of parameters at nearest four stations within selected epicentral distance of the event. It has been concluded that three parameter preference-based approach provides most efficient results at a time window of 4 s. The data-set for estimating various parameters required for multi-parameter algorithm has been taken from K-NET seismic array (Japan). The algorithm has been validated on the data taken from different regions. Based on the validation carried out using Indian and PEER-NGA database, the results revealed better performance of multi-parametric EEW algorithm.

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