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1

Spatial distribution of seismic cycle progression in northeast India and Bangladesh regions inferred from natural time analysis

Pasari Sumanta, Verma Himanshu, Sharma Yogendra, Choudhary Neha

Acta Geophysica

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2023

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Vol. 71, no. 1

89--100

EN

The ability to determine the current state of seismic cycle of large sized earthquakes is of profound importance in societal policymaking and disaster preparation. In this article, we present a probabilistic formulation of event-based natural time counts to develop earthquake potential score (EPS) at 36 cities from northeast India, Bangladesh, and adjoining areas. The time-dependent natural time analysis provides an attractive regional seismic hazard evaluation method, because it (1) exhibits spatiotemporal and clustering invariability, ensuring model consistency, (2) considers "seismic cycles" for a network of faults in a defined area, and (3) enables some physical interpretations aligned with earthquake generation process characterized by stress accumulation and moment release. The modeling results for M≥6 events reveal that EPS values lie between 41 and 94%, with the scores of Agartala (91%), Aizawl (84%), Dimapur (80%), Guwahati (41%), Imphal (90%), Malda (70%), Shillong (52%), Siliguri (73%), Barisal (59%), Chittagong (94%), Comilla (88%), Dhaka (78%), Mymensingh (81%), Narayanganj (77%), Rangpur (55%), and Sylhet (60%). These values essentially serve as a yardstick to statistically assess the current state of regional seismic cycle progression in the study region, bringing out some key information to the decision-makers, engineers, scientists, and citizens to improve earthquake preparedness and mitigation strategies.

2

Frequency magnitude distribution and spatial correlation dimension of earthquakes in north-east Himalaya and adjacent regions

Tiwari Ram Krishna, Paudyal Harihar

Geologos

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2022

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Vol. 28, No. 2

115--128

EN

The north-east sector of the Himalaya is one of the most active tectonic belts, with complex geological and tectonic features. The b-value and spatial correlation dimension (Dc) of earthquake distribution in the north-east Himalaya and its adjacent regions (20–32°N and 88–98°E) are estimated in the present study. Based on seismicity and faulting pattern, the region is divided into five active regions, namely the (i) South-Tibet, (ii) Eastern-Syntaxis, (iii) Himalayan-Frontal Arc, (iv) Arakan-Yoma belt and (v) Shillong-Plateau. A homogeneous catalogue of 1,416 earthquakes (mb ≥ 4.5) has been prepared from a revised catalogue of the ISC (International Seismological Centre). The b-value has been appraised by the maximum likelihood estimation method, while Dc values have been calculated by the correlation integral meth-od; b-values of 1.08 ± 0.09, 1.13 ± 0.05, 0.92 ± 0.05, 1.00 ± 0.03 and 0.98 ± 0.08 have been computed for the South-Tibet, Eastern-Syntaxis, Himalayan-Frontal Arc, Arakan-Yoma belt and Shillong-Plateau region, respectively. The Dc values computed for the respective regions are 1.36 ± 0.02, 1.74 ± 0.04, 1.57 ± 0.01, 1.8 ± 0.01, and 1.83 ± 0.02. These values are > 1.5, except for the South-Tibet (1.36 ± 0.02). The b-values around the global average value (1.0) reflect the stress level and seismic activity of the regions, while high Dc values refer to the heterogeneity of the seismogenic sources.

3

Neural network based hybrid ground motion prediction equations for Western Himalayas and North Eastern India

Dhanya J., Raghukanth S. T. G.

Acta Geophysica

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2020

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Vol. 68, no. 2

303--324

EN

This work aims at developing a hybrid ground motion prediction equation (GMPE) for spectral acceleration in Western Himalayas and North-Eastern India. The GMPE is derived using an efcient nonparametric modelling based on neural network algorithm. In this study, owing to sparsity in the recorded ground motions (498 recordings) for the region, the available information is combined with 13,294 records from the well-tested NGA-West 2 database. For the methodology adopted in the study, regional fags are assigned to the records. Thus, given a magnitude, distance, shear wave velocity, fault type and region, the model is able to predict the possible spectral acceleration. The developed GMPE is observed to be unbiased with respect to region. Further, the inter- and intra-event standard deviations are also in acceptable ranges. It is observed that developed GMPE for Western Himalayas and North-Eastern India is able to capture all the known ground motion characteristics. Additionally, the GMPE is compared with the existing GMPE for rock-type soil condition available for the Western Himalayas and North-Eastern India. Furthermore, applicability of the developed GMPE model in estimating hazard is analysed by obtaining the uniform hazard response spectra for Delhi and Guwahati.