Probabilistic forecast of next earthquake event in Makran subduction zone using Weibull distribution

Keywords: probability distribution, earthquake prediction, Weibull distribution, statistical analysis, seismicity, Makran subduction zone

Abstract

Earthquake is the most lethal type of natural disaster. Researchers have been working to develop precise earthquake prediction methods to save lives. A statistical investigation is an effective earthquake prediction method because they offer more details about the seismic risk or hazard issue. This study utilizes seismic data from the Makran subduction zone from 1934 to 2017. Probability distributions may be employed to assess the risk of seismic events and earthquake occurrence probability. This work estimates the probability of the next major event in the Makran subduction zone through Weibull distribution by considering strong earthquakes with a magnitude (Mw ≥ 6) in the intervals (in years) between two consecutive earthquakes. The probabilities of the forthcoming seismic event have been estimated based on the previous earthquake record, pictorially. The calculated parameters of the Weibull distribution for the Makran subduction zone may help to forecast the probabilities of a strong earthquake and describe the pattern of earthquake average return time. The calculated probability for the Weibull distribution reaches 0.92 after ten years since the last strong earthquake in 2021, indicating that the Weibull distribution within and around the present research area in 2031 will be 92%.

Author Biographies

Adil REHMAN, University of Chinese Academy of Sciences, Beijing 100049, China

Key Laboratory of Computational Geodynamics

Huai ZHANG, University of Chinese Academy of Sciences, Beijing 100049, China

Key Laboratory of Computational Geodynamics

Published
2024-04-01
How to Cite
REHMAN, A., & ZHANG, H. (2024). Probabilistic forecast of next earthquake event in Makran subduction zone using Weibull distribution. Contributions to Geophysics and Geodesy, 54(1), 85-93. https://doi.org/10.31577/congeo.2024.54.1.5
Section
original research papers