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JDR Vol.8 No.2 pp. 266-273
(2013)
doi: 10.20965/jdr.2013.p0266

Paper:

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Seismic Source of 1746 Callao Earthquake from Tsunami Numerical Modeling

Cesar Jimenez*1,*2, Nabilt Moggiano*2, Erick Mas*3,
Bruno Adriano*3, Shunichi Koshimura*3, Yushiro Fujii*4,
and Hideaki Yanagisawa*5

*1Fenlab, Universidad Nacional Mayor de San Marcos (UNMSM), Av Venezuela s/n, Lima, Peru

*2Direccion de Hidrografia y Navegacion (DHN), Calle Roca N 116, Chucuito-Callao, Peru

*3Laboratory of Remote Sensing and Geoinformatics for Disaster Management, International Research Institute of Disaster Science, Tohoku University, Aoba 6-6-03, Sendai 980-8579, Japan

*4International Institute of Seismology and Earthquake Engineering, Building Research Institute, Tatehara, Tsukuba, Ibaraki 305-0802, Japan

*5Department of Regional Management, Faculty of Liberal Arts, Tohoku Gakuin University, 2-1-1 Tenjinzawa, Izumi-ku, Sendai, Miyagi 981-3193, Japan

Received:
November 2, 2012
Accepted:
February 8, 2013
Published:
March 1, 2013
Creative Commons License
Keywords:
seismic source, tsunami, simulation
Abstract
In this paper a model of slip distribution is proposed for the 1746 Callao earthquake and tsunami based on macroseismic observations written in historical documents. This is done using computational tools such as tsunami numerical simulation through a forward process by trial and error. The idea is to match historical observations with numerical simulation results to obtain a plausible seismic source model. Results show a high asperity from Cañete to Huacho, which would explain the great destruction in this area. The rupture directivity of the seismic source, from north to south, would explain the value of the arrival time of the first tsunami wave at Callao. A kinematic seismic source model was used as a first approximation of the event. The estimated magnitude was Mw9.0.
Cite this article as:
C. Jimenez, N. Moggiano, E. Mas, B. Adriano, S. Koshimura, Y. Fujii, and H. Yanagisawa, “Seismic Source of 1746 Callao Earthquake from Tsunami Numerical Modeling,” J. Disaster Res., Vol.8 No.2, pp. 266-273, 2013.
Data files:
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