Statistical analysis of seismic b-value using non-parametric Kolmogorov–Smirnov test and probabilistic seismic hazard parametrization for Nepal and its surrounding regions

This study aims to characterize the frequency magnitude distribution factor (b-value) for Nepal and its surrounding area-thereby focusing on conducting spatiotemporal and depth-wise analysis of b-value fluctuations before the November 9, 2022 earthquake of magnitude MW 6.3. Using the non-parametric Kolmogorov–Smirnov (K–S) test, earthquake events with a magnitude MW ≥ 3.5 reported between 1900 and 2022 from the earthquake catalog compiled by the International Seismological Centre (ISC) and the United States Geological Survey (USGS) were analysed. We determined the minimum magnitude of completeness (MC) using the Maximum Curvature Method (MAXC). Furthermore, we divided the study region into equal-sized square grids and computed b-values using the maximum likelihood technique for each grid. We analysed the relationship between the b-value and seismic parameters such as focal depth, seismic moment release, and radon gas anomalies, along with their spatial correlations and patterns. Results indicate minimal seismicity in the lower crust compared to the upper crust and lead to establish an inverse relationship between the b-value and seismic moment release. We established plausible correlations between temporal variations of the b-value and variations in radon gas concentration as an earthquake precursor in different medium. Additionally, we utilized the Gumbel extreme value theory to estimate the mean return period, the most likely maximum yearly earthquake, and probabilities of recurrence of different magnitudes across different periods for credible seismic hazard analysis. We found the most likely maximum yearly earthquake for the region to be 5.53, with a mean return period of 5 years for the November 9, 2022 earthquake. The mean return period of earthquakes with magnitudes ranging from 5.0 to 6.5 (MW) was estimated to be 5–10 years. These findings contribute to a better understanding of the intricate seismotectonic configuration of the region and serve as earthquake precursors for potential future destructive earthquakes.