Coseismic slip distribution of 2009 L’Aquila earthquake derived from InSAR and GPS data

Abstract

To better understand the mechanism of the Mw6.3 L’Aquila (Central Italy) earthquake occurred in 2009, global positioning system (GPS) and interferometric synthetic aperture radar (InSAR) data were used to derive the coseismic slip distribution of the earthquake fault. Firstly, based on the homogeneous elastic half-space model, the fault geometric parameters were solved by the genetic algorithm. The best fitting model shows that the fault is a 13.7 km×14.1 km rectangular fault, in 139.3° strike direction and 50.2° southwest-dipping. Secondly, fixing the optimal fault geometric parameters, the fault plane was extended and discretized into 16×16 patches, each with a size of 1 km×1 km, and the non-uniform slip distribution of the fault was inverted by the steepest descent method with an appropriate smoothing ratio based on the layered crustal structure model. The preferred solution shows that the fault is mainly a normal fault with slight right-lateral strike slip, the maximum slip of 1.01 m is located in the depth of 8.28 km, the average rake is −100.9°, and the total geodetic moment is about 3.34×1018 N·m (Mw 6.28). The results are much closer than previous studies in comparison with the seismological estimation. These demonstrate that the coseismic fault slip distribution of the L’Aquila earthquake inverted by the crustal model considering layered characters is reliable.

Keywords

L’Aquila earthquake / interferometric synthetic aperture radar / global positioning system (GPS) / slip distribution

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Foundation item: Projects(40974006, 40774003) supported by the National Natural Science Foundation of China; Project(NCET-08-0570) supported by the Program for New Century Excellent Talents in Chinese Universities; Projects(2011JQ001, 2009QZZD004) supported by the Fundamental Research Funds for the Central Universities in China; Projects(09K005, 09K006) supported by the Key Laboratory for Precise Engineering Surveying & Hazard Monitoring of Hunan Province, China; Project(1343-74334000023) supported by the Graduate Degree Thesis Innovation Foundation of Central South University, China