Seismic hazard and risk assessment based on pattern recognition: Himalayas and adjacent territories
IR@C-MMACS: CSIR-Centre for Mathematical Modelling and Computer Simulation, Bangalore
View Archive Info| Field | Value | |
| Title |
Seismic hazard and risk assessment based on pattern recognition: Himalayas and adjacent territories
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| Creator |
Parvez, I A
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| Subject |
Computational Seismology
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| Description |
Due to devastating consequences the historical records on earthquakes
are known from 2100 B.C., however, most of those before the middle of
the 18th century are generally lacking a quantitative calibrated
description, so that a scientifically sound analysis of seismic activity
(including the issues of hazard and risk) usually refer to a few decades
at best and in many cases to a rather limited region. The abruptness
along with apparent irregularity and infrequency of earthquake
occurrences facilitate a common perception that earthquakes are
random unpredictable phenomena. Such a perception has made most
of the contemporary methodologies for seismic hazard and risk
assessment relying on evidently pre-conceptual hypotheses and
eventually misleads to repetition of tragic “surprises” like the 26
December 2004 Sumatra-Andaman mega-earthquake and associated
tsunami, the 26 January 2001 Gujarat and the 15 May 2008 Wenchuan
great earthquakes, the major 8 October 2005 Muzaffarabad (Kashmir)
and other disastrous seismic events in the future.
Over the last decades pattern recognition has proved its
effectiveness in identifying earthquake-prone areas as well as in
intermediate-term diagnosis of the incipient earthquake. The observed
seismic dynamics prior to and after mega, great, major, strong, and
even moderate earthquakes demonstrate common patterns of
predictability that could be used for phenomenological seismic hazard
assessment. The approach is based on the confirmed fractal nature of
earthquakes and their distribution in space and time and the existence
of typical scenarios in the course of durable phase transitions in a
complex hierarchical non-linear system of blocks-and-faults of the Earth
lithosphere. This approach has been tested and eventually confirmed by
subsequent occurrence of target earthquakes in many seismic regions
of the world studied previously for a number of magnitude ranges.
We propose to reach the objectives of the proposal by using
the reproducible quantitative methodologies and algorithms that have
passed extensive testing (including the most rigid one in real time and
history) and allow integrating a unified scaling law for earthquakes with
many scales of pattern recognition aimed at earthquake prediction –
from term-less identification of the areas of medium or batter range in
space down to intermediate-term or better accuracy in time. Specifically,
we plan (i) to identify geomorphologic nodes prone to hazardous
earthquakes and to define their characteristic features by analyzing the
available topographic, geomorphic and geological data; (ii) to compile a
calibrated earthquake catalog for the Himalayas and adjacent areas by
problem oriented methodology and software designed at IIEPT&MG
RAS and CSIR- C-MMACS; (iii) to map coefficients of the unified scaling
law for earthquakes in the region along with the recurrence rates of
great, major, strong, and moderate earthquakes; (iv) to evaluate
different estimates of seismic risk for the principal cities of India and
adjacent countries; (v) to establish and set up, where possible,
monitoring of seismic activity and biannual regular updates for diagnosis
of the times of increased probability of earthquakes of different size
using the latest advances of the M8-type algorithms and their
modifications. The results of such a data driven phenomenological
analysis could be supplemented independently with realistic earthquake
scenarios and/or convolved with data on different objects of risk.
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| Publisher |
CSIR Centre for Mathematical Modelling and Computer Simulation
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| Date |
2009
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| Type |
Monograph
NonPeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://cir.cmmacs.ernet.in/171/1/parvez%2DCM0902.pdf
Parvez, I A (2009) Seismic hazard and risk assessment based on pattern recognition: Himalayas and adjacent territories. Other. CSIR Centre for Mathematical Modelling and Computer Simulation, C-MMACS,Bangalore 560037,India. (Unpublished) |
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| Relation |
http://cir.cmmacs.ernet.in/171/
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