6.1.4 Earth Observation for Crustal Tectonics and Earthquake Hazards
Elliott et al. (2020) illustrated the current methods for the exploitation of data from Earth Observing satellites to measure and understand earthquakes and shallow crustal tectonics. The aim of applying such methods to Earth Observation data is to improve our knowledge of the active fault sources that generate earthquake shaking hazards. Examples of the use of Earth Observation, including the measurement and modelling of earthquake deformation processes and the earthquake cycle using both radar and optical imagery are provided. They also highlighted the importance of combining these orbiting satellite datasets with airborne, in situ and ground-based geophysical measurements to fully characterize the spatial and timescale of temporal scales of the triggering of earthquakes from an example of surface water loading. Finally, they concluded with an outlook on the anticipated shift from the more established method of observing earthquakes to the systematic measurement of the longer-term accumulation of crustal strain.
6.1.5 Contributions of Space Missions to Better Tsunami Science: Observations, Models and Warnings
Global Navigation Satellite System (GNSS) data have a key role in better describing the ground deformation following a tsunamigenic earthquake close to the coast. The GNSS observations complement seismological data to constrain the rupture model rapidly and robustly. Interferometric Synthetic Aperture Radar (SAR) also contributes to this field, as well as optical imagery, relevant to monitoring elevation changes following subaerial landslides. The observation of the sea-level variations, in the near field and during the propagation across the ocean, can also increasingly benefit from GNSS data (from GNSS buoys) and from robust satellite communication: pressure gauges anchored on the seafloor in the deep ocean contribute to warning systems only by data continuously transmitted through satellites. The sounding of ionospheric Total Electron Content (TEC) variations through GNSS, altimetry, or a ground-based airglow camera, is a promising way to record tsunami initiation and propagation indirectly. Finally, GNSS, optical and SAR imagery are essential to map and quantify the damage following tsunami flooding. Satellite data are expected to contribute more to operational systems in the future provided they are reliably available and analyzed in real time (Hebert et al., 2020).
6.1.6 Aftershock Duration of Strong to Major Himalayan Earthquakes
Earthquakes of M\(\ge\) 5 tend to be locally damaging, specifically when these are the aftershocks of larger earthquakes, as the main shock would have weakened the structures. For the rescue operations and general well-being of the residents, it is helpful if an estimate is available as to how long M \(\ge\) 5 aftershocks would continue to occur. Earthquakes M \(\ge\) 6.5 tend to be followed by aftershocks of M \(\ge\) 5. In this study by Gupta and Rekhapalli (2022), aftershock sequences of seven earthquakes of magnitude M \(\ge\) 6.5 were analyzed. Six among these are in the Himalayan region and the remaining one is in the near vicinity in China. The analysis suggests that the number of M \(\ge\) 5 aftershocks and the duration of their occurrence decrease with the decrease of the mainshock magnitude. For the 2008 Sichuan earthquake of M 7.9 there were 136 M \(\ge\) 5 aftershocks, while for 1975 Kinnaur earthquake of M 6.8 there were only 9. The aftershock duration of the Himalayan region earthquakes obeys the exponential law, where the A and c are constants associated with regional fault settings. This relation is helpful in providing an estimate of the time for which M \(\ge\) 5 aftershock activity would continue after the occurrence of M \(\ge\) 6.5 earthquakes.
6.2 Microzonation Studies
CSIR-NGRI prepared a first-cut
Earthquake Disaster Risk Index (EDRI) map to capture the relative risk across Lucknow and Dehradun cities. These maps were handed over to the State Disaster Management Authority of respective States.
CSIR-4PI carried out microzonation of Srinagar region of the Kashmir Valley (Gupta S.V., et al., 2020, 2022). They conducted an extensive high-resolution microtremor ambient noise survey at 429 locations. The acquired dataset was processed using the
Horizontal to Vertical Spectral Ratio (HVSR) technique to map the resonance frequency, the thickness of sedimentary cover and to identify areas prone to seismic amplification. The HVSR curves show the peaks in the range of 0.22 Hz to 9.96 Hz indicating heterogeneous and complex sedimentary cover in the region. Inversion of the HVSR curves gives the shear waves velocity distribution which highlights two distinct reflective surfaces in most of the areas. They also used the estimated fundamental frequency of various types of houses/buildings located in Srinagar city to assess the possibility of resonance in case of occurrence of any earthquake.
ISR has undertaken site-specific seismic hazard assessment and microzonation studies for areas of rapid growth, e.g. Special Investment Regions, Special Economic Zones, large and tall structures, and industrial hubs. These include Liquified Natural Gas / Liquid Petroleum Gas storage tanks at Mundra, Dhamra (Odisha), Dadra and Nagar Haveli, cable stayed bridge at Zuari River, Goa, and Indian Oil Corporation Ltd. Bongaigaon Refinery. The Institute has completed seismic microzonation of Bhuj city under a Ministry of Earth Sciences (MoES) sponsored project. In addition, it has undertaken seismic microzonation study of Amritsar, Meerut, Agra, Lucknow, Kanpur, Varanasi, Patna and Dhanbad towns under a project sponsored by MoES.
The concept of seismic vulnerability is a yard-stick of damage estimation from a probable earthquake, considering physical cum social dimension and enables a basis for decision-makers to develop preparedness and mitigation strategies. Baruah et al. (2020) used several parameters, e.g. shear wave velocity characteristics, geomorphology, slope angle, building typology, and the number of occupants, to estimate the dimension of vulnerability for the Shillong city. Based on this study, they inferred that more than 60% of Shillong city falls under moderate to high vulnerability and the rest is less vulnerable.