Probabilistic Seismic Hazard Assessment of Southern Offshore East Java Using Poisson and Gutenberg–Richter Models
Keywords:
Earthquake probability, Gutenberg–Richter law, Poisson distribution, seismic hazard
Abstract
The southern region of East Java is part of the Sunda Subduction Zone, which has high seismic activity due to the convergence of the Indo-Australian and Eurasian Plates. This study aims to analyze the probability of earthquake occurrences in the southern offshore of East Java using the Poisson distribution and the Gutenberg–Richter law. Earthquake catalog data from the International Seismological Centre (ISC) for the period 1996–2025 were used. After declustering using the Gardner and Knopoff method, 1,348 mainshock events were obtained. The initial Magnitude of Completeness ( ) was determined to be 4.0 using the Maximum Curvature (MAXC) method, then corrected to 4.2, resulting in 888 events with a mean magnitude of . The seismic parameters obtained were and . The Kolmogorov–Smirnov test showed that the annual earthquake data follow a Poisson distribution (Dcalculated (0.204086)≤ DTable (0.297595)), confirming the validity of the Poisson model. Extrapolation using the Gutenberg–Richter law yielded earthquake probabilities for of 92.78% within 50 years, of 15.42%, and of 1.06%. This study is expected to serve as a reference for seismic hazard assessment and disaster risk mitigation in the southern coastal area of East Java.
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References
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[2] W. Wella, R. I. Desanti, and S. Suryasari, “A Comparative Study of Machine Learning Approaches to Megathrust Earthquake Prediction in Subduction Zones,” J. Appl. Data Sci., vol. 6, no. 4, pp. 2421–2435, 2025, doi: https://doi.org/10.47738/jads.v6i4.904.
[3] Y. Asnawi et al., “Soil classification in a seismically active environment based on join analysis of seismic parameters,” Glob. J. Environ. Sci. Manag., vol. 8, no. 3, pp. 297–314, 2022, doi: https://doi.org/10.22034/gjesm.2022.03.01.
[4] A. Arimuko, P.-F. Chen, Y. Serhalawan, and E. Sujarwanto, “Improved Aftershock of the 2006 Yogyakarta MW 6.4 Earthquake Sequence Using Deep Learning and Its Correlates with Tectonic Setting,” Ann. Geophys., vol. 69, p. 9409, 2026.
[5] B. Anggarajati, Y. Yatini, and W. Raharjo, “Application of K-means clustering and B-value algorithms for analysis of earthquake dangerous zones in Java Island,” Int. J. Adv. Appl. Sci., vol. 13, no. 4, pp. 907–915, 2024, doi: http://doi.org/10.11591/ijaas.v13.i4.pp907-915.
[6] F. S. Rahmatullah et al., “Development of Peak Ground Motion Acceleration Map of Surabaya City based on Probabilistic Seismic Hazard Analysis,” in IOP Conference Series: Earth and Environmental Science, IOP Publishing, 2025, p. 12032. doi: https://doi.org/10.1088/1755-1315/1458/1/012032.
[7] R. Annisa, M. Jannah, A. H. Saputro, and T. Lestari, “Enhancing Seismic Data Accuracy: An Advanced Health Diagnosis Method for Seismometers Performance Evaluation,” in Journal of Physics: Conference Series, IOP Publishing, 2024, p. 12049. doi: https://doi.org/10.1088/1742-6596/2866/1/012049.
[8] M. Wannewitz and M. Garschagen, “The role of social identities for collective adaptation capacities–general considerations and lessons from Jakarta, Indonesia,” Int. J. Disaster Risk Reduct., vol. 100, p. 104194, 2024, doi: https://doi.org/10.1016/j.ijdrr.2023.104194.
[9] P. Zhou and S. Xia, “Effects of the heterogeneous subducting plate on seismicity: constraints from b-values in the Andaman–Sumatra–Java subduction zone,” Phys. Earth Planet. Inter., vol. 304, p. 106499, 2020, doi: https://doi.org/10.1016/j.pepi.2020.106499.
[10] M. D. Petersen et al., “The 2018 update of the US National Seismic Hazard Model: Overview of model and implications,” Earthq. Spectra, vol. 36, no. 1, pp. 5–41, 2020, doi: https://doi.org/10.1177/8755293019878199.
[11] International Seismological Centre, “International Seismological Centre On-line Bulletin,” ISC. Accessed: May 10, 2026. [Online]. Available: https://www.isc.ac.uk/iscbulletin/search/catalogue/
[12] D. Poudyal, N. Nordin, and S. N. A. Roslan, “Comparative declustering approaches for seismic data: insights from gardner-knopoff, gruenthal, reasenberg, and uhrhammer in the Kathmandu Valley,” Ann. Geophys., vol. 68, 2025, doi: https://doi.org/10.4401/ag-9178.
[13] X. Wang, J. Li, A. Feng, and D. Sornette, “Estimating magnitude completeness in earthquake catalogs: A comparative study of catalog‐based methods,” J. Geophys. Res. Solid Earth, vol. 130, no. 9, p. e2025JB031441, 2025, doi: https://doi.org/10.1029/2025JB031441.
[14] V. A. Pavlenko and A. D. Zavyalov, “Comparative analysis of the methods for estimating the magnitude of completeness of earthquake catalogs,” Izv. Phys. Solid Earth, vol. 58, no. 1, pp. 89–105, 2022, doi: https://doi.org/10.1134/S1069351322010062.
[15] J. Woessner and S. Wiemer, “Assessing the quality of earthquake catalogues: Estimating the magnitude of completeness and its uncertainty,” Bull. Seismol. Soc. Am., vol. 95, no. 2, pp. 684–698, 2005, doi: https://doi.org/10.1785/0120040007.
[16] P. Li, C. Chen, Y. Sun, and W. Wang, “Poisson multi-bernoulli mixture filter for multiple extended object tracking using kolmogorov–smirnov test,” IEEE Sens. J., vol. 25, no. 4, pp. 6541–6555, 2025, doi: https://doi.org/10.1109/JSEN.2024.3521436.
[17] K. P. D. Drajati and F. Roshafara, “Penerapan Proses Poisson Nonhomogen untuk Memprediksi Kejadian Gempa Bumi Jawa Barat,” in Bandung Conference Series: Statistics, 2025, pp. 713–720. doi: https://doi.org/10.29313/bcss.v5i2.20757.
[18] Y. Yang, N. Dousti Mousavi, Z. Yu, and J. Yang, “From Poisson observations to fitted negative binomial distribution: Y. Yang et al.,” Stat. Pap., vol. 67, no. 3, p. 62, 2026, doi: https://doi.org/10.1007/s00362-026-01842-x.
[19] K. Aki, “Maximum likelihood estimate of b in the formula log N= a− bM and its confidence limits,” Bull. Earthq. Res. Inst. Univ. Tokyo, vol. 43, pp. 237–239, 1965.
[20] A. M. Lombardi, “A statistical framework for detection of b-value anomalies in Italy,” Geophys. J. Int., vol. 237, no. 2, pp. 729–740, 2024, doi: https://doi.org/10.1093/gji/ggae068.
[21] B. Gutenberg and C. F. Richter, “Frequency of earthquakes in California,” 1944.
[22] P. Adetokunbo et al., “Geostatistical Analysis for Magnitude Scale Conversion and Gutenberg-Richter Parameter Estimation: Insights from Regional Seismicity of Nubian-Eurasian Plate Boundary Region,” J. Geosci. Environ. Prot., vol. 13, no. 7, pp. 230–248, 2025, doi: https://doi.org/10.4236/gep.2025.137014.
[23] C. A. Cornell, “Engineering seismic risk analysis,” Bull. Seismol. Soc. Am., vol. 58, no. 5, pp. 1583–1606, 1968.
[24] E. H. Field, K. R. Milner, and K. A. Porter, “Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast,” Earthq. Spectra, vol. 41, no. 3, pp. 1977–1997, 2025, doi: https://doi.org/10.1177/87552930251340677.
Published
2026-10-02
Section
Articles
Copyright (c) 2026 Ajril Abyad Al Haq, Eriska Fitri Kurniawati
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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