TY  - JOUR
A1  - Steinberg, Andreas
A1  - Sudhaus, Henriette
A1  - Heimann, Sebastian
A1  - Krüger, Frank
T1  - Sensitivity of InSAR and teleseismic observations to earthquake rupture segmentation
T2  - Geophysical journal international
N2  - Earthquakes often rupture across more than one fault segment. If such rupture segmentation occurs on a significant scale, a simple point-source or one-fault model may not represent the rupture process well. As a consequence earthquake characteristics inferred, based on one-source assumptions, may become systematically wrong. This might have effects on follow-up analyses, for example regional stress field inversions and seismic hazard assessments. While rupture segmentation is evident for most M-w > 7 earthquakes, also smaller ones with 5.5 < M-w < 7 can be segmented. We investigate the sensitivity of globally available data sets to rupture segmentation and their resolution to reliably estimate the mechanisms in presence of segmentation. We focus on the sensitivity of InSAR (Interferometric Synthetic Aperture Radar) data in the static near-field and seismic waveforms in the far-field of the rupture and carry out non-linear and Bayesian optimizations of single-source and two-sources kinematic models (double-couple point sources and finite, rectangular sources) using InSAR and teleseismic waveforms separately. Our case studies comprises of four M-w 6-7 earthquakes: the 2009 L'Aquila and 2016 Amatrice (Italy) and the 2005 and 2008 Zhongba (Tibet) earthquakes. We contrast the data misfits of different source complexity by using the Akaike informational criterion (AIC). We find that the AIC method is well suited for data-driven inferences on significant rupture segmentation for the given data sets. This is based on our observation that an AIC-stated significant improvement of data fit for two-segment models over one-segment models correlates with significantly different mechanisms of the two source segments and their average compared to the single-segment mechanism. We attribute these modelled differences to a sufficient sensitivity of the data to resolve rupture segmentation. Our results show that near-field data are generally more sensitive to rupture segmentation of shallow earthquakes than far-field data but that also teleseismic data can resolve rupture segmentation in the studied magnitude range. We further conclude that a significant difference in the modelled source mechanisms for different segmentations shows that an appropriate choice of model segmentation matters for a robust estimation of source mechanisms. It reduces systematic biases and trade-off and thereby improves the knowledge on the rupture. Our study presents a strategy and method to detect significant rupture segmentation such that an appropriate model complexity can be used in the source mechanism inference. A similar, systematic investigation of earthquakes in the range of M-w 5.5-7 could provide important hazard-relevant statistics on rupture segmentation. In these cases single-source models introduce a systematic bias. Consideration of rupture segmentation therefore matters for a robust estimation of source mechanisms of the studied earthquakes.
KW  - radar interferometry
KW  - waveform inversion
KW  - earthquake source observations
Y1  - 2020
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/57631
SN  - 0956-540X
SN  - 1365-246X
VL  - 223
IS  - 2
SP  - 875
EP  - 907
PB  - Oxford Univ. Press
CY  - Oxford
ER  -