Semi-Markov models for the evaluation of time, location, magnitude and depth of earthquakes in southern Peru 2023
DOI:
https://doi.org/10.21754/iecos.v25i2.2196Keywords:
Seismic, semi-Markov, Cluster AnalysisAbstract
Peru is located in the South Pacific seismic region and frequently experiences significant earthquakes. Among the most relevant events are the 8.4 magnitude earthquake in Arequipa in 2001, the 7.9 magnitude earthquake in Ica in August 2007 and again a 6.3 magnitude earthquake in Arequipa in July 2017. These events underscore the need for seismic risk studies in the region.
This study is of a descriptive and correlational type, with a cross-sectional design, whose objective is to identify the areas in southern Peru with the highest risk of experiencing high magnitude earthquakes. The data come from the Geophysical Institute of Peru and cover the period from 1960 to 2023, analyzing earthquakes with a magnitude equal to or greater than 5.5 MW. The methodology of (Sadeghian, 2012), based on the semi-Markov model, was applied to predict time and location of seismic events, extending this model also to depth states. The Pisco-Ica and Chala-Atico areas are highlighted as the most at risk for the occurrence of large magnitude earthquakes.
Downloads
References
Altinok, Y., & Kolcak, D. (1999). An application of the semi-Markov model for earthquake occurrences in North Anatolia, Turkey. Journal of the Balkan Geophysical Society, 2(4), 90-99. https://www.balkangeophysoc.gr/online-journal/1999_V2/nov1999/pdf/v2-4-1.pdf
Alvarez, E. E. (2005). Alvarez, Estimation in stationary Markov renewal processes, with application to earthquake forecasting in Turkey. Environmental Science, Engineering, Mathematics Methodology and Computing in Applied Probability, 7, 119-130. https://doi.org/10.1007/s11009-005-6658-2
Garavaglia, E., & Pavani, R. (2011). About earthquake forecasting by Markov renewal processes. Methodology and Computing in Applied Probability, 13, 155-169. https://doi.org/10.1007/s11009-009-9137-3
IGP, I. G. (2023). Descargar Datos. Instituto Geofísico del Perú. Obtenido de https://ultimosismo.igp.gob.pe/descargar-datos-sismicos
Janssen, J., & Manca, R. (2006). Applied semi-Markov processes. Springer Science & Business Media. https://doi.org/10.1007/0-387-29548-8
Leonard Kaufman, Peter J. Rouseeuw (2005) Finding Groups in Data. An Introduction to Cluster Analysis. Wiley-Interscience
Masala, G. (2012). Earthquakes occurrences estimation through a parametric semi-Markov approach. Journal of Applied Statistics, 39(1), 81-96. https://doi.org/10.1080/02664763.2011.578617
Sadeghian, R. (2012). Forecasting time and place of earthquakes using a Semi-Markov model (with case study in Tehran province). Journal of Industrial Engineering International, 8, 1-7. https://doi.org/10.1186/2251-712X-8-20
Tavera, H. (2001). Peligro sísmico en Lima y el país. Revista del Centro de Estudios y Prevención de desastres, 8(14), 30-35. http://hdl.handle.net/20.500.12816/832
Tavera, H., Salas, H., Jimenez, C., Antayhua Vera, Y. T., Vilcapoma, L., Millones, J., ... & Rodríguez, S. (2001). El terremoto de la región del sur del Perú del 23 de junio de 2001. Instituto Geofísico del Perú. http://hdl.handle.net/20.500.12816/1121
Tavera, H., Bernal, I., & Salas, H. (2007). El sismo de Pisco del 15 de agosto, 2007 (7.9 Mw) departamento de Ica - Perú (informe preliminar). Instituto Geofísico del Perú. http://hdl.handle.net/20.500.12816/1115
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Carlos Risco Franco, Marlene Angela Payano Mendez, Joel Salomon Rios Nima
This work is licensed under a Creative Commons Attribution 4.0 International License.
CC BY 4.0 DEED Attribution 4.0 International
