Civil Insight: A Technical Magazine Volume 3 | Page 52
Shrestha P. et al.
Civil Insight (2019) 51-56
collected from the National Seismological Center (NSC) and the United States Geological Survey (USGS).
The obtained data consisted of local magnitude , surface wave magnitude , body wave magnitude
, moment magnitude , and intensity scale Ǥ
Fig. 1. Location of the dam site of Upper Seti Hydropower Project
For uniformity and consistency, the magnitudes and intensity levels were converted into a single moment
magnitude using the following equations:
Conversion from to (Gutenberg & Richter, 1956)
ൌ ͲǤ ͳǤͲ
ሺͳሻ
ሺʹሻ
Conversion from to (Wang et al., 2010)
ൌ ͲǤͻͺ ͲǤͲ͵
Conversion from to (Liu et al., 2007)
ൌ ͳǤͲ Ȃ ͲǤ͵
ሺ͵ሻ
Conversion from to seismic moment ( ) (Ambraseys & Douglas, 2004)
ൌ ͳǤͲ͵ͳǤͷ ሺ ͷǤͻͶሻሺͶሻ
ൌ ͳͻǤ͵ͺͲǤͻ͵ ሺ ൏ͷǤͻͶሻሺͷሻ
Conversion from to moment magnitude ( ) (Hanks & Kanamori, 2004)
ൌ ͲǤ ȗ Ȃ ͳͲǤ͵ሺሻ
2.2) Earthquake Declustering
The data obtained from the section 2.1 above consist of various main shocks and aftershocks. For further
processing, only major or main earthquake events were required since aftershocks are non-Poissionian in
nature. Therefore, the aftershocks were removed using MATLAB (MATLAB, 2015) for further processing.
This process of removal of aftershocks is known as declustering. Gardner and Knopoff (1974) have
provided a dynamic window algorithm for aftershocks removal, also called declustering algorithm. After
occurrence of earthquake of magnitude , if another earthquake occurs within days and epicenter is
within km from that particular magnitude, as specified in Table 1, then the earthquake is identified as
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