Influence of model parameters on synthesized high-frequency strong-motion waveforms

Waveform modeling is an important and helpful instrument of modern seismology that may provide valuable information. However, synthesizing seismograms requires to define many parameters, which differently affect the final result. Such parameters may be: the design of the grid, the structure model, the source time functions, the source mechanism, the rupture velocity. Variations in parameters may produce significantly different seismograms. We synthesize seismograms from a hypothetical earthquake and numerically estimate the influence of some of the used parameters. Firstly, we present the results for high-frequency near-fault waveforms obtained from defined model by changing tested parameters. Secondly, we present the results of a quantitative comparison of contributions from certain parameters on synthetic waveforms by using misfit criteria. For the synthesis of waveforms we used 2D/3D elastic finite-difference wave propagation code E3D [1] based on the elastodynamic formulation of the wave equation on a staggered grid. This code gave us the opportunity to perform all needed manipulations using a computer cluster. To assess the obtained results, we use misfit criteria [2] where seismograms are compared in time-frequency and phase by applying a continuous wavelet transform to the seismic signal. [1] - Larsen, S. and C.A. Schultz (1995). ELAS3D: 2D/3D elastic finite-difference wave propagation code, Technical Report No. UCRL-MA-121792, 19 pp. [2] - Kristekova, M., Kristek, J., Moczo, P., Day, S.M., 2006. Misfit criteria for quantitative comparison of seismograms. Bul. of Seis. Soc. of Am. 96(5), 1836–1850

Slip distribution, coseismic deformation and Coulomb stress change for the 12 May 2008Wenchuan (China, Mw7.9) earthquake

The May 12, 2008 Wenchuan earthquake (Mw7.9) took place at the transition between the mountainous chain of Shan and the basin of Sichuan along the Longmen Shan Fault zone (31.1oN, 103.3oE; USGS). With a magnitude of 7.9 and a depth of ∼19 km the earthquake produced a 300-km-long fault rupture. It was the largest earthquake recorded in the region during the last centuries. It claimed more than 69,000 lives, induced widespread destruction over the region and raised concern about seismic hazard and source characterization for the Sichuan province. In the frame of our study, we selected 40 broadband waveforms (IRIS Consortium, USA) with good quality and satisfactory azimuthal coverage. Body waveforms were prepared for inversion using Kikuchi and Kanamori’s method [1] to obtain the spatiotem- poral slip distribution of a finite rupture model (length=300 km, strike=229o, dip=33o, width=60 km). The slip distribution model obtained was used to determine the coseismic deformation and the stress change distribution using the Coulomb 3.0 software [2]. Our coseismic deformation results was compared with data from GPS stations located near the fault rupture. Results show that directions of coseismic deformations are consistent with GPS observations close to the fault. Finally, we compare aftershock hypocenters that occurred during one month after the main shock with the Coulomb stress changes caused by this shock in the region. We observed that most aftershocks are located along the main fault plane without any noticeable clustering in the areas of increased stress. Our results suggest the rupture of the 2008 Wenchuan earthquake was essentially unilateral, from SW to NE (N49E), covering a 260km length and with duration about 105 sec. The strongest moment release occurred about 85km from the hypocenter, ∼30sec after the start of the rupture. Motions are dominated by thrust mechanism, but the superficial section of the second half of the rupture also shows a significant strike-slip component. [1]- Kikuchi, M., and Kanamori, H., 1982, Inversion of complex body waves: Bull. Seismol. Soc. Am., v. 72, p. 491-506. [2] -King, G. C. P., Stein, R. S. y Lin, J, 1994, Static stress changes and the triggering of earthquakes. Bull. Seismol. Soc. Am. 84,935-953

STRON GGROUND MOTION SIMULATIONS AND ASSESMENT OF INFLUENCE OF MODEL PARAMETERS ON WAVEFORMS

Modeling near-field ground motion is an important and useful tool of modern seismology. It helps in studies of seismic events and mitigation of seismic hazards. Several approaches are widely used to obtain synthetic ground motion for a finite earthquake source. In our work we use a finite difference algorithm, developed for 3D structures and kinematic source model, to compute near-field ground motions from a real moderate event with pre-existing slip distribution model. Lately, synthetic seismograms are quantitatively compared with observed waveforms from near-field seismic stations in order to justify created model. Furthermore, we independently changed several source parameters (rupture velocity, source dimension and geometry), and structure (velocity model) in order to evaluate their influence on the waveforms. We applied quantitative misfit criteria, based on wavelet transform, for the comparison of seismogram

Strong Ground Motion Simulations and Assessment of Influence of Model Parameters on the Waveforms

Modeling near-field ground motion is an important and useful tool of modern seismology. In our work we use a finite difference algorithm to compute near-field ground motions from a real moderate event with pre-existing slip distribution model. Lately, synthetic seismograms are quantitatively compared with observed waveforms from near-field seismic stations in order to justify created model. Furthermore, we independently changed several source parameters (rupture velocity, source dimension and geometry), and structure (velocity model) in order to evaluate their influence on the waveforms. For the comparison of seismograms we applied quantitative misfit criteria based on wavelet transform

A decision support system based on GIS, multi-criteria decision making methods and structural properties analysis for transport network vulnerability and resilience assessment

International audienc

Road network management in the context of natural hazards: a decision-aiding process based on multi-criteria decision making methods and network structural properties analysis

International audienceIn mountain areas, transport infrastructures (roads, railways) are exposed to natural hazards such as avalanches, torrent floods and rockfalls. Road networks are known to be essential for economic, safety, social, environmental and safety reasons: they can therefore be considered as critical networks. Effects of natural phenomena on exposed roads can affect either users, road infrastructures or the linking function itself with indirect remote consequences. This paper describes a methodology based on structural properties analysis to assess the indirect vulnerability of road networks. Attractiveness factors (population flows, economic activities, access to rescue, health facilities . . . ) are used to identify the importance of road sections. Physical features (slope, width . . . ) and snow avalanches exposure, considering variable quality information, are used as constraints. The software GeoGraphLab (GGL) provides structural indicators which inform decision-maker about their networks criticality and resilience is used in the context of natural hazards.En montagne, les infrastructures de transport (routes, voies ferrées) sont exposées aux phénomènes naturels tels que les avalanches, les crues torrentielles et les chutes de blocs. Les réseaux routiers sont reconnus comme essentiels pour des raisons économiques, sociales, sécuritaires et environnementales: ils font, à ce titre, ainsi partie des réseaux dits critiques. Les effets des phénomènes naturels sur les routes exposées affectent soit directement les utilisateurs, les infrastructures ou la fonction de liaison de la route avec des conséquences indirectes distantes. Cet article décrit une méthodologie basée sur l’analyse des propriétés structurelles des réseaux pour évaluer la vulnérabilité indirecte des réseaux routiers. Des facteurs d’attractivité (flux de population, activités économiques, accès aux services de secours, santé . . . ) sont utilisés pour identifier l’importance des sections de route. Les caractéristiques physiques (pente, largeur . . . ) et l’exposition aux avalanches, prenant en compte la qualité variable des informations, sont utilisées comme contraintes. Le logiciel GeoGraphLab (GGL) est mis en oeuvre dans le contexte des risques naturels en montagne: il fournit des indicateurs structurels qui renseigne les décideurs sur la criticité et la résilience de leurs réseaux