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Recurrence statistics of large earthquakes has a long-term economic and societal importance. This study investigates the temporal distribution of large (M ≥ 6) earthquakes in the Nepal Himalaya. We compile earthquake data of more than 200 years (1800–2022) and calculate interevent times of successive main shocks. We then derive recurrence-time statistics of large earthquakes using a set of twelve reference statistical distributions. These distributions include the time-independent exponential and time-dependent gamma, lognormal, Weibull, Levy, Maxwell, Pareto, Rayleigh, inverse Gaussian, inverse Weibull, exponentiated exponential and exponentiated Rayleigh. Based on a sample of 38 interoccurrence times, we estimate model parameters via the maximum likelihood estimation and provide their respective confidence bounds through Fisher information and Cramer–Rao bound. Using three model selection approaches, namely the Akaike information criterion (AIC), Kolmogorov–Smirnov goodness-of-fit test and the Chi-square test, we rank the performance of the applied distributions. Our analysis reveals that (i) the best fit comes from the exponentiated Rayleigh (rank 1), exponentiated exponential (rank 2), Weibull (rank 3), exponential (rank 4) and the gamma distribution (rank 5), (ii) an intermediate fit comes from the lognormal (rank 6) and the inverse Weibull distribution (rank 7), whereas (iii) the distributions, namely Maxwell (rank 8), Rayleigh (rank 9), Pareto (rank 10), Levy (rank 11) and inverse Gaussian (rank 12), show poor fit to the observed interevent times. Using the best performed exponentiated Rayleigh model, we observe that the estimated cumulative and conditional occurrence of a M ≥ 6 event in the Nepal Himalaya reach 0.90–0.95 by 2028–2031 and 2034–2037, respectively. We finally present a number of conditional probability curves (hazard function curves) to examine future earthquake hazard in the study region. Overall, the findings provide an important basis for a variety of practical applications, including infrastructure planning, disaster insurance and probabilistic seismic hazard analysis in the Nepal Himalaya. [ABSTRACT FROM AUTHOR]

Utilizing an updated dataset of 145 GNSS surface velocities, this study examines the fault slip rate and fault geometry along the Main Himalayan Thrust (MHT) in the central Himalaya. Employing a Bayesian inversion model, the present analysis reveals that the upper portion of the MHT ramp exhibits full locking, while the lower flat displays creeping motion. The estimated locking depth and fault depth of MFT range from 4.3 ± 2.6 km to 9.7 ± 2.2 km and 13.5 ± 3.1 km to 15.8 ± 1.9 km, respectively, along the central Himalaya. Further, the slip rate along the transition zone lies in the range of 1.4 ± 0.8 mm/yr to 2.7 ± 0.5 mm/yr. Considering the amount of uncertainties as ~1–2 mm/yr in GNSS velocities, the study suggests that the transition zone along the middle flat of the MHT also exhibits locking behavior. Thus, the estimated locking depth extends to ~15.0 km down-dip and covers a horizontal distance of ~90 km (locking line) on the surface, reaching the foothills of the Higher Himalaya. Furthermore, along the deeper flat of the MHT, the slip rate ranges from 19.4 ± 2.5 mm/yr in the west to 12.8 ± 1.6 mm/yr in the east along Nepal Himalaya. The analysis also calculates the slip deficit rate along the MHT fault plane, revealing values of ~15.1 mm/yr in western Nepal, ~12.7 mm/yr in central Nepal, and ~10.6 mm/yr in eastern Nepal. These slip deficit rates across different segments of central Nepal indicate the potential for large earthquakes in the region. The results are further supported by a resolution test using a checkerboard synthetic model, demonstrating the capability of the GNSS network to capture the slip rate along the MHT. These findings inevitably contribute to a comprehensive assessment of the seismic hazard potential in the central Himalayan region. [ABSTRACT FROM AUTHOR]