Geostatistics applied to predictive modeling of seismic damage in Sarmiento (San Juan, Argentina)

Authors

  • Luciana Narvaez Departamento de Geografía, Facultad de Filosofía, Humanidades y Artes. Universidad Nacional de San Juan. Instituto de Geografía Aplicada https://orcid.org/0000-0002-1208-3929

Keywords:

mapas, cuantificacion, amenaza

Abstract

The Sarmiento Department, like the entire province of San Juan, has a seismic history marked by powerful and destructive earthquakes, such as those recorded in 1894, 1941, 1944, 1952, 1977, and 2021. These events have left a profound impact, causing severe damage and even the collapse of homes, public buildings, and historic structures, along with substantial economic losses affecting large sectors of the population. Unfortunately, they have also resulted in a significant number of injuries and fatalities.

In response to this context, the objective of this study is to advance the understanding of population-level damage in the Sarmiento Department by quantifying it and applying advanced spatial analysis methodologies. To achieve this, geostatistical methods are employed to develop predictive models of seismic damage, as the variables involved exhibit spatial continuity and are therefore well suited to this type of analysis. The results offer clear and concise predictive models that can support decision-making and management actions in the event of a seismic event.

Downloads

Download data is not yet available.

References

CFCyC (2016). Atlas socioeconómico de la provincia de San Juan. Centro de Fotogrametría, Cartografía y Catastro. Facultad de Ingeniería. Universidad Nacional de San Juan. Instituto Geográfico Nacional (IGN).

Armstrong, M., & Roth, C. (1997). Notas del curso Geoestadística. Centro de Geoestadística de la Escuela Nacional Superior de Minas de París, Fontainebleau, Francia.

Braga, F., Dolce, M., & Liberatore, D. (1982). A statistical study on damaged buildings and an ensuing review of the MSK-76 scale, 7th. European Conference on Earthquake Engineering. Atenas, Grecia.

Cardona, O. (2001). Estimación holística del riesgo sísmico utilizando sistemas dinámicos complejos. Tesis doctoral. Universidad Politécnica de Cataluña.

DGyCSJ, Dirección de Geodesia y Catastro de la Provincia de San Juan. (2019). Base de datos de edificaciones del Departamento Sarmiento [Archivo shapefile no publicado]. Gobierno de San Juan.

FEMA/NIBS (1999), Federal Emergency Management Agency. HAZUS technical manual. Washington D. C.

INDEC (2022) Instituto Nacional de Estadísticas y Censo. Servicios estadísticos: Datos de población. Recuperado de https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-165

Mouroux, P., Bertrand, E., Bour, M., Le Brun, B., Depinois, S., Masure, P. & The Risk-UE Team (2004). The european Risk-Ue Project: an advanced approach to earthquake risk scenarios. 13th World Conference on Earthquake Engineering.Vancouver, B.C., Canada, August 1-6, 2004, Paper No. 3329.

Masure, P. & Lutoff, C. (2006), Urban system exposure to natural disasters: an integrated approach, in Oliveira C.S, Roca A., Goula X, “Assessing and managing earthquake risk. Geoscientific and Engineering Knowledge for Earthquake Risk Mitigation: developments, tools, techniques", Ed Springer, pp. 239-259.

Márquez, E. (2018). Recopilado y compilado de la geoestadística. Facultad de Ingeniería. Universidad Nacional de San Juan. Argentina.

Matheron, G. (1970). La Théorie des Variables Régionalisées et ses Applications. Les Cahiers du Centre de Morphologie Mathématique de Fontainebleau (Fascicule 5). École des Mines de Paris.

Medvedev, S. V. (1978). Seismic intensity scale MSK-76. Schweizerische Geophysikalische Kommission.

Rashed, T., & Weeks, J. (2003) Metodología SIG para el análisis de la vulnerabilidad sísmica: Ciudad de Los Ángeles. International Journal of Geographical Information Science 17(6), 574-576.

Published

2025-11-27

Issue

Section

Human geography

ARK

How to Cite

Geostatistics applied to predictive modeling of seismic damage in Sarmiento (San Juan, Argentina). (2025). Boletín Geográfico, 47(PC). https://revele.uncoma.edu.ar/index.php/geografia/article/view/6321

Similar Articles

1-10 of 36

You may also start an advanced similarity search for this article.