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Automatic imaging of earthquake rupture processes by iterative deconvolution and stacking of high‐rate GPS and strong motion seismograms
Author(s) -
Zhang Yong,
Wang Rongjiang,
Zschau Jochen,
Chen Yuntai,
Parolai Stefano,
Dahm Torsten
Publication year - 2014
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1002/2013jb010469
Subject(s) - deconvolution , seismology , seismogram , geology , smoothing , inversion (geology) , computer science , global positioning system , waveform , robustness (evolution) , algorithm , nonlinear system , synthetic data , geodesy , computer vision , telecommunications , radar , biochemistry , chemistry , physics , quantum mechanics , gene , tectonics
By combining the complementary advantages of conventional network inversion and backprojection methods, we have developed an iterative deconvolution and stacking (IDS) approach for imaging earthquake rupture processes with near‐field complete waveform data. This new approach does not need any manual adjustment of the physical (empirical) constraints, such as restricting the rupture time and duration, and smoothing the spatiotemporal slip distribution. Therefore, it has the ability to image complex multiple ruptures automatically. The advantages of the IDS method over traditional linear or nonlinear optimization algorithms are demonstrated by the case studies of the 2008 Wenchuan and 2011 Tohoku earthquakes. For such large earthquakes, the IDS method is considerably more stable and efficient than previous inversion methods. Additionally, the robustness of this method is demonstrated by comprehensive synthetic tests, indicating its potential contribution to tsunami and earthquake early warning and rapid response systems. It is also shown that the IDS method can be used for teleseismic waveform inversions. For the two major earthquakes discussed here, the IDS method can provide, without tuning any physical or empirical constraints, teleseismic rupture models consistent with those derived from the near‐field GPS and strong motion data.