CSIR-NGRI Seismological Observatory (HYB) Started in a wintery morning on December 11, 1967 after Koyna M6.3
earthquake, CSIR-NGRI Seismological
Observatory (HYB) has made significant contribution to the study of
Seismology in India by producing very
high-quality seismological data followed by accurate analysis over the years.
The observatory has been
equipped with World Wide Standard Seismograph Network (WWSSN) equipment
comprising three component Benioff
Short Period Seismometer and Press Ewing Long Period Seismometer with
photographic paper recording initially
in the 1967. In addition to it, a Very Broadband seismometer with a digital recorder has been installed in 1989. The
seismological data has been shared with United States Geological Survey,
International Seismological Centre,
Berkshire, United Kingdom, National Centre for Seismology, New Delhi and
other national agencies.
July 10, 2024, 07:14:54.3hours IST, 19.417N, 77.410E, 4.5ML, 28km NNE of
Nanded (Maharashtra)
The observatory has made significant contributions in understanding the Intra
Plate Earthquakes in
Peninsular Shield and Himalayan Region including Koyna Earthquake M6.3
(1967), Bhadrachalam Earthquake
M5.7 (1969), Broach Earthquake M5.4 (1970), Mudhol Earthquake Swarm (1984),
Killari Earthquake M6.3
(1993), Jabalpur Earthquake M5.8 (1997), Chamoli Earthquake M6.8 (1999), Bhuj
Earthquake M7.7 (2001),
Nanded Earthquake Swarm (2007), Chakalikoda (Nellore district) Earthquake
Swarm (2016-2017), Vijayapura
Earthquake swarm (2021)
The micro earthquake activity in and around Hyderabad has also been
studied with Medchal Earthquake
M4.5 (1983) being the largest followed by Gundipet Earthquake
Swarm (1982), Saroornagar
Earthquake Swarm (1984), Jubilee Hills Earthquake Swarm sequences in 1994,
1995, 1998, 2000 and 2017,
Vanasthalipuram Earthquake swarm (2010) and Borabanda Earthquake swarm (2017
and 2020).
Strong Ground Motion Seismology
Comparison of the observed and predicted PGA values with GMPEs.
India is one of the most seismically active regions in the world and the
Himalayan arc in
particular pose a high seismic risk in northern India as well as the
adjoining nations. According to the
current seismic zone map of India around 59% of the country is prone to
earthquakes. The Himalayas has
already experienced 3 catastrophic earthquakes with M > 8.0 in past 1897
Shillong (M8.2); 1934
Bihar-Nepal (M8.4); and 1950 Assam-Tibet (M8.7) (Bilham 2011) which resulted
in loss of many lives and
infrastructures. But if any earthquake with similar size happens in the
Himalayan region in the near
future, it will adversely affect several millions of lives and monetary loss
would be of multi-billion
US dollars. Therefore, it is necessary to monitor seismicity continuously in
the Himalayan region and
delineate the potential zone of future great earthquake and evaluate seismic
hazard levels unfailingly.
CSIR – NGRI has established a seismic network in Himalayan region and is
continuously expanding the
network which includes both Broadband seismographs and Strong motion
accelerographs. The Seismic Hazard
studies in Himalayan region focuses on understanding characteristics of
strong ground motions through
modeling of strong ground motions, evaluation and development of empirical
relations, evaluation of
source, medium and site properties. As an example, results from Sharma et.
al. 2021 are shown where
researchers evaluated ground motion parameters for seismic hazard assessment
from two moderate sized
earthquakes occurred during 2017 in Uttarakhand region. The observed ground
motion parameters (Peak
ground accelerations) are compared with results from simulation and
attenuation relationships (now known
as GMPEs) developed for shallow crustal earthquakes.
(The solid line indicates the mean values and +/− 1 standard deviation is
represented by the dashed
lines. Stars represent the predicted values and the observed PGA values are
represented by circles)
Seismic Anisotropy
Map showing Individual shear wave splitting measurements plotted at a depth
of 200 km beneath
the Kumaon-Garhwal Himalaya
Prolonged deformation due to tectonic activity results in the development of
anisotropy in the
crust and upper mantle. Different factors generate anisotropy at various
depth ranges, such as
fluid-filled cracks, stratigraphy or fault-zone fabrics in the upper crust
and lattice-preferred
orientation (LPO) of minerals in the lower crust and upper mantle. In the
upper mantle, the LPO of
minerals (mainly olivine) is generally caused by dislocation creep. Shear
wave splitting, an elastic
analogue of optical birefringence, offers an effective means to measure
seismic anisotropy. When a shear
wave passes through an anisotropic medium, it splits into fast and slow
waves, with the former polarized
parallel to the anisotropic fast axis and the latter polarized orthogonal to
it.
Using core-refracted phases like SKS is popular for estimating azimuthal
anisotropy. The
parameterization of azimuthal anisotropy using the core refracted phases is
done in terms of the
polarization of the fast wave and the difference in the travel time between
the fast and slow wave, that
is delay time (e.g., as shown in Figure). These are used as proxies to
decipher the past and present-day
deformation patterns. The crustal and mantle deformation in the stable and
actively deformed regions of
India are extensively studied using the shear wave splitting technique. One
such kind of work is carried
out in Kumaon-Garhwal Himalaya (KGH) using core-refracted phases (XK(K)S)
phases recorded at 53
broadband seismic stations. For this region, the northern part of the lesser
Himalaya shows a slightly
smaller delay time compared to its southern part, which is attributed to the
weakening of azimuthal
anisotropy caused by the dipping of the Indian lithosphere. Based on the
orientation of fast
polarisation azimuths (FPAs), the KGH region can be divided into four
subregions. The strong ENE-WSW
orientation in the central part could result from a slightly variable
anisotropy in the crust to the
upper part of the lithosphere or basal topography causing deflection of
mantle flow. Also, the NW
orientation in the southeastern part of KGH is associated with a shallow
source within the lithosphere.
Application of the spatial coherency technique to single-layered anisotropic
parameters results in a
depth of 220-240 km, implying that the dominant source of anisotropy could
lie in the upper mantle.
Applications of AI/ML in seismology
Artificial intelligence (AI), Machine learning (ML) and Deep learning (DL)
have gained increasing attention
in the field of seismology in recent years. With the growth of digital seismic
data and advances in
computational power, AI/ML algorithms have been applied to various
seismological problems, such as
earthquake detection, early warning and seismic hazard assessment. Earthquake
seismology uses a sequence of
processing steps to monitor seismic activity. These steps were initially
performed manually by skilled
analysts and later were performed automatically with algorithms designed to
detect impulsive phase arrivals.
By applying AI/ML/DL algorithms one can automatically detect, locate and
calculate magnitudes of earthquakes
from seismograms. Motivated by the successful application of Deep-Learning
models in seismic monitoring and
growing amount of data set, applying the DL techniques to the ongoing Palghar
(Maharashtra) earthquake swarm
which started in November 2019. The technique could detect more than thousands
of events with less
magnitudes and compared the results those obtained from traditional
techniques. DL algorithms are efficient
and accurate tools for data reprocessing in order to better understand the
space-time evolution of
earthquake sequences. This study demonstrates that machine-learning-based
earthquake catalogue development
is now feasible and will yield new insights into earthquake behaviour.
Seismic Monitoring of Dams
Srisailam Dam
CSIR-NGRI carries out Seismic monitoring of 24 Dams including Nagarjuna Sagar
Dam, Srisailam Dam and Sriram Sagar Dam in Andhra Pradesh and Telangana
states, Dhamni (Surya) Dam and Bhatsa dam in Maharashtra state and Mullai
Periyar Dam, Mettur Dam, Sholayar Dam, Upper Kodayar Dam, Lower Kodayar Dam,
Servalar Dam, Tamiraparani Dam, Manalar Dam, Ervangalar Dam, Periyar Forebay
Dam, Upper Aliyar Dam, Kadamparai Dam, Pillur Dam, Upper Bhavani Dam, Emerald
Dam, Avalanche Dam, Porthimund Dam, Pykara Dam, Mukurthy Dam in Tamilnadu
state under seven different projects sponsored by respective state government
departments.
A Broadband seismograph has been installed in the vicinity of the dam to
monitor the micro earthquakes that occur around the dam. Strong Motion
Accelerographs have been installed in the dam structure including dam crest
and galleries as well as free field to assess the dynamic behaviour of the
dam for near field earthquakes.
Seismological studies at Koyna: In India, the first observation of Reservoir Triggered Seismicity (RTS) was noticed in the vicinity of
Koyna dam just after its impoundment in 1962. This phenomenon successfully explains the observation of intra
plate seismicity which corresponds to the impoundment of the reservoir. Another reservoir, Warna was created
in 1985 and it also contributed to the RTS in the region. The seismicity occurs within a small region of 30
km X 20 km. In order to monitor the seismic activity, initially CSIR-NGRI took initiative to deploy digital
seismic stations, however at present 15 surface broadband and 8 borehole short-period seismic stations are
in operation. Previously, several observations have been made regarding the source processes and nature of
seismicity in the region, such as the correlation between the water level and occurrence of seismicity,
difference between the normal earthquake and RTS (Gupta et al., 1972a,b; Gupta and Rastogi, 1974; Gupta,
1992; Rastogi et al., 1997; Talwani, 1997). Recent analysis on variation in stress pattern and the
segregation of focal mechanisms enabled to derive a tectonic model with alternating cycles of strike-slip
and normal type (Rao and Shashidhar, 2016). Using the waveform inversion, a precise determination of focal
depths has been attempted using local seismic waveforms (Shashidhar et al., 2011) identified the Donachiwada
fault is the causative source for the 1967 Koyna earthquake (Mw6.3). A number of seismological studies have
been carried out in this region to understand the source mechanism and structure, however, the triggering
phenomenon of seismicity is poorly resolved. In this direction, to understand the role of fluid, pore
pressure, loading and unloading of the reservoirs and source mechanism a major initiative were taken by the
MoES to drill deep boreholes in and around the region. The main advantage of borehole observation is the
increased sensitivity due to the rapid decrease in noise wave intensity with depth, since the interference
consists mainly of surface waves. Scientific deep drilling in the region has revealed that the Deccan trap
has 932.5m thick and underlain by the basement rock (Roy et al., 2013). The major science objectives and
feasibility were discussed with the international community through ICDP workshops (Gupta and Nayak, 2011;
Shashidhar et al., 2016). The deployment of borehole seismic sensors is first of its kind in India. The high
signal to noise ratio waveforms has the potential not only to detect the sub M1.0 seismic events but also
can provide structural information with unprecedented resolution. The results show that the absolute errors
in locations of earthquake based on the borehole data ranges from 800 to 300m (Shashidhar et al., 2016;
2020). We aim for a detailed study of earthquake mechanism; to map the distribution of the faults based on
the micro-seismicity and also to achieve the accurate velocity structure associated with the fault zones in
this region.
A network map of the borehole and broadband seismic stations in the
Koyna-Warna region. In the inset,
India map
indicates the study region.
Earthquakes of M≥4.0 in the Koyna-Warna region since 1967. The star (in
red) denotes the largest
earthquake
of M 6.3 of 10 December 1967. The open circles in white are the locations of
events without focal
mechanism
solutions, while the yellow ones are the recent ones with mechanisms. The
lines are the faults /
lineaments
inferred from LANDSAT images (Langston 1981). Also seen are the Koyna and
Warna reservoirs situated
about 25 km
apart, just east of the Western Ghat escarpment. (Rao and Shashidhar 2016)
The comprehensive set of 50 earthquake focal mechanism solutions in the
Koyna-Warna region compiled from
previous studies (grey) and from moment tenor inversion of waveform data by
the authors in their
previous work
and the present work (black). (Rao and Shashidhar 2016).
Tectonics of the Koyna region as inferred jointly from the 1967 (M 6.3) and
the 2012 (Mw 4.8)
earthquakes are
plotted with the topography of the study region as indicated in figure1.
Focal mechanism solution for
the 1967
earthquake is by Chandra (1976)-b while the solution for the 2012 earthquake
is from the present study.
Circles
represent the aftershocks including the largest aftershock of Mw 3.7 located
very close to the Mw 4.8
earthquake. KRFZ is the Koyna River Fault Zone and D is the Donachiwada
fault. (Shashidhar et al. 2013)
Focal mechanism solutions in the Koyna–Warna region plotted as a function
of time from 1967 to 2017
show a
periodic variation of predominantly strike-slip (SS), normal type(N)
mechanisms over the years. The
dotted line
indicates the lower latitude limit of the M ≥ 4 earthquakes so far except for
the earthquake of Mw 4.0
of
2017. (Shashidhar et al. 2019).
Comparison of event locations obtained by combining surface and borehole
networks using the
‘HYPOCENTRE’ location algorithm (squares), event locations retrieved using
borehole network data and
a grid search algorithm (triangles) and event locations attained employing
borehole network data and a
cross-correlation relative location algorithm (circles). Western Ghats
escarpment as well as water
reservoirs
close to Kandavan and Paraleninai marked by arrows. Dashed line:
deep-reaching lineament taken from
Arora et al.
(2018). UDG: Udgiri surface station. (Shashidhar et al. 2020).
Individual splitting measurements (lines) made using the local S phases
plotted at the stations
(circles). Rose
diagram of the fast polarization azimuths (grey shaded) is shown for the
surface stations within the
rectangles
and at the respective stations (circle). At the respective stations, the
stereographic projection of the
fast
polarization azimuths and delay times (lines) are plotted as a function of
backazimuth and incidence
angle. In
each stereograph, the circles represent the incidence angle from 10° to 50°
with a 10° increment.
The orientation and length of the lines correspond to the fast polarization
azimuth and delay time,
respectively. The blue and magenta lines correspond to the surface and
borehole stations. The grey arrow
represents the absolute plate motion direction in a no-net rotation frame.
(Roy and Shashidhar 2023).
Started in a wintery morning on December 11, 1967 after Koyna M6.3
earthquake, CSIR-NGRI Seismological
Observatory (HYB) has made significant contribution to the study of
Seismology in India by producing very
high-quality seismological data followed by accurate analysis over the years.
The observatory has been
equipped with World Wide Standard Seismograph Network (WWSSN) equipment
comprising three component Benioff
Short Period Seismometer and Press Ewing Long Period Seismometer with
photographic paper recording initially
in the 1967. In addition to it, a Very Broadband seismometer with a digital recorder has been installed in 1989. The
seismological data has been shared with United States Geological Survey,
International Seismological Centre,
Berkshire, United Kingdom, National Centre for Seismology, New Delhi and
other national agencies.
In India, the first observation of Reservoir Triggered Seismicity (RTS) was noticed in the vicinity of
Koyna dam just after its impoundment in 1962. This phenomenon successfully explains the observation of intra
plate seismicity which corresponds to the impoundment of the reservoir. Another reservoir, Warna was created
in 1985 and it also contributed to the RTS in the region. The seismicity occurs within a small region of 30
km X 20 km. In order to monitor the seismic activity, initially CSIR-NGRI took initiative to deploy digital
seismic stations, however at present 15 surface broadband and 8 borehole short-period seismic stations are
in operation. Previously, several observations have been made regarding the source processes and nature of
seismicity in the region, such as the correlation between the water level and occurrence of seismicity,
difference between the normal earthquake and RTS (Gupta et al., 1972a,b; Gupta and Rastogi, 1974; Gupta,
1992; Rastogi et al., 1997; Talwani, 1997). Recent analysis on variation in stress pattern and the
segregation of focal mechanisms enabled to derive a tectonic model with alternating cycles of strike-slip
and normal type (Rao and Shashidhar, 2016). Using the waveform inversion, a precise determination of focal
depths has been attempted using local seismic waveforms (Shashidhar et al., 2011) identified the Donachiwada
fault is the causative source for the 1967 Koyna earthquake (Mw6.3). A number of seismological studies have
been carried out in this region to understand the source mechanism and structure, however, the triggering
phenomenon of seismicity is poorly resolved. In this direction, to understand the role of fluid, pore
pressure, loading and unloading of the reservoirs and source mechanism a major initiative were taken by the
MoES to drill deep boreholes in and around the region. The main advantage of borehole observation is the
increased sensitivity due to the rapid decrease in noise wave intensity with depth, since the interference
consists mainly of surface waves. Scientific deep drilling in the region has revealed that the Deccan trap
has 932.5m thick and underlain by the basement rock (Roy et al., 2013). The major science objectives and
feasibility were discussed with the international community through ICDP workshops (Gupta and Nayak, 2011;
Shashidhar et al., 2016). The deployment of borehole seismic sensors is first of its kind in India. The high
signal to noise ratio waveforms has the potential not only to detect the sub M1.0 seismic events but also
can provide structural information with unprecedented resolution. The results show that the absolute errors
in locations of earthquake based on the borehole data ranges from 800 to 300m (Shashidhar et al., 2016;
2020). We aim for a detailed study of earthquake mechanism; to map the distribution of the faults based on
the micro-seismicity and also to achieve the accurate velocity structure associated with the fault zones in
this region.
Earthquakes of M≥4.0 in the Koyna-Warna region since 1967. The star (in
red) denotes the largest
earthquake
of M 6.3 of 10 December 1967. The open circles in white are the locations of
events without focal
mechanism
solutions, while the yellow ones are the recent ones with mechanisms. The
lines are the faults /
lineaments
inferred from LANDSAT images (Langston 1981). Also seen are the Koyna and
Warna reservoirs situated
about 25 km
apart, just east of the Western Ghat escarpment. (Rao and Shashidhar 2016)
Focal mechanism solutions in the Koyna–Warna region plotted as a function
of time from 1967 to 2017
show a
periodic variation of predominantly strike-slip (SS), normal type(N)
mechanisms over the years. The
dotted line
indicates the lower latitude limit of the M ≥ 4 earthquakes so far except for
the earthquake of Mw 4.0
of
2017. (Shashidhar et al. 2019).
Comparison of event locations obtained by combining surface and borehole
networks using the
‘HYPOCENTRE’ location algorithm (squares), event locations retrieved using
borehole network data and
a grid search algorithm (triangles) and event locations attained employing
borehole network data and a
cross-correlation relative location algorithm (circles). Western Ghats
escarpment as well as water
reservoirs
close to Kandavan and Paraleninai marked by arrows. Dashed line:
deep-reaching lineament taken from
Arora et al.
(2018). UDG: Udgiri surface station. (Shashidhar et al. 2020).
Individual splitting measurements (lines) made using the local S phases
plotted at the stations
(circles). Rose
diagram of the fast polarization azimuths (grey shaded) is shown for the
surface stations within the
rectangles
and at the respective stations (circle). At the respective stations, the
stereographic projection of the
fast
polarization azimuths and delay times (lines) are plotted as a function of
backazimuth and incidence
angle. In
each stereograph, the circles represent the incidence angle from 10° to 50°
with a 10° increment.
The orientation and length of the lines correspond to the fast polarization
azimuth and delay time,
respectively. The blue and magenta lines correspond to the surface and
borehole stations. The grey arrow
represents the absolute plate motion direction in a no-net rotation frame.
(Roy and Shashidhar 2023).
