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The July 4, 2019 Mw6.4 and subsequent July 6, 2019 Mw7.1 Ridgecrest Sequence earthquakes in California, USA, ruptured orthogonal fault planes in the Little Lake Fault Zone, a low slip rate (1 mm/year) dextral fault zone in the region linking the Eastern California Shear Zone (ECSZ) and Walker Lane. This region is tectonically interesting because it accommodates approximately one fourth of plate boundary motion and has been proposed to be an incipient transform fault system that could eventually become the main tectonic boundary, replacing the San Andreas Fault. Additionally, large ruptures of such low slip rate faults are important to understand from the context of seismic hazard. We investigate the interaction within this fault system and demonstrate a novel kinematic slip method that inverts for both earthquakes simultaneously, allowing us to use Interferometric Synthetic Aperture Radar (InSAR) data that spans both earthquakes, along with seismic (strong-motion accelerometer) and geodetic (high-rate Global Navigation Satellite Systems (GNSS) and GNSS static offset) datasets that recorded each earthquake separately. We also present results of Coulomb stress change modeling to evaluate how the Mw6.4 earthquake may have affected the subsequent Mw7.1 event. Our findings suggest a complex rupture process and interactions between several fault structures, including dynamic and static triggering between splays involved in the July 4th Mw6.4 and July 6th Mw7.1 events. The integration of seismic and geodetic datasets provides constraints on rupture continuation through stepovers, as well as important context for regional models of seismic source characterization and hazard.

How to cite: Goldberg, D., Melgar, D., Sahakian, V., Thomas, A., Xu, X., Crowell, B., and Geng, J.: Using Seismic and Geodetic Observations in a Simultaneous Kinematic Model of the 2019 Ridgecrest, California Earthquakes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11146, https://doi.org/10.5194/egusphere-egu2020-11146, 2020.

Earthquakes have been observed to initiate and terminate near geometrical irregularities (bends, step-overs, branching of secondary faults). Rupture segmentationinfluences the seismic radiation and therefore, the related seismic hazard. Good imaging of rupture segmentation helps to characterize fault geometries at depth for follow-up tectonic, stress-field or other analyses. From reported earthquake source models it appears that large earthquakes with magnitudes above 7 are most often segmented, while earthquakes with magnitudes below 6.5 most often are not. If this observationreflects nature or if it is rather an artifact of our abilities to well observe and infer earthquake sources can not be answered without an objective strategy to constrain rupture complexity. However, data-driven analyses of rupture segmentation are not often conducted in source modeling as it is mostly pre-defined through a given and fixed number of sources. 

We, here, propose a segmentation-sensitive source analysis by combining a model-independent teleseismic back-projection and image segmentation methods with a kinematic fault inversion. Our approach is twofold. We first develop a time-domain multi-array back-projection of teleseismic data with robust estimations of uncertainties based on bootstrapping of the travel-time models and array weights (Palantiri software, https://braunfuss.github.io/Palantiri/). Backprojection has proven to be a powerful tool to infer rupture propagation from teleseismic data and identify irregularities of the rupture process over time.

We then model the earthquake sources with the results obtained from the backprojection and additional information obtained from the application of image segmentation methods to the InSAR displacement maps. For this second step, we use a combination of different observations (teleseismic waveforms and surface displacement maps based on InSAR) to increase the resolution on the spatio-temporal evolution of fault slip. We develop a novel Informational criterion based transdimensional optimization scheme to model an adequate representation of the source complexity. We present our method on two cases study: the 2016 Muji Mw 6.7 earthquake (Pamir) and the 2008-2009 Qaidam (Tibet) sequence of earthquakes. We find that the 2008 Qaidam earthquake ruptures one segment, the 2016 Muji earthquake on two segments and the Qaidam 2009 earthquake on two or three segments.

This work is based on the open-source, python-based Pyrocko toolbox and is conducted within the project “Bridging Geodesy and Seismology” (www.bridges.uni-kiel.de<http://www.bridges.uni-kiel.de>) funded by the DFG through an Emmy-Noether grant.

How to cite: Steinberg, A., Sudhaus, H., Krüger, F., Vasyura-Bathke, H., Daout, S., and Isken, M. P.: Joint seismic and geodetic transdimensional earthquake source optimization guided by multi-array teleseismic backprojection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13379, https://doi.org/10.5194/egusphere-egu2020-13379, 2020.

Large earthquakes in the vicinity of Antarctica have the potential to cause post-seismic deformation on the continent, affecting measurements of displacement and gravity field change from GRACE or those attempting to constrain models of glacial isostatic adjustment.

In November 2013 a magnitude 7.7 strike-slip earthquake occurred in the Scotia Sea around 650 km from the northern tip of the Antarctic Peninsula. GPS coordinate time series from the Peninsula region show a change in rate after this event indicating a far-field post-seismic deformation signal is present. At these far-field locations, the effects of fault after-slip are likely negligible and hence we consider the deformation to be due to post-seismic viscoelastic deformation. Here we use a global spherical finite element model to investigate the extent of post-seismic viscoelastic deformation in the northern Antarctic Peninsula. We investigate possible 1D earth models that can fit the GPS data and consider the effect of including a simple 3D earth structure in the region. These results, combined with previous results showing East Antarctica is still deforming following 1998 M_w 8.2 intraplate earthquake, suggest that much of Antarctica is deforming due to recent post-seismic deformation.

How to cite: Nield, G., King, M., Koulali, A., Samrat, N., and Steffen, R.: Post-Seismic Deformation in the Northern Antarctic Peninsula Following the 2013 Magnitude 7.7 Scotia Sea Earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3704, https://doi.org/10.5194/egusphere-egu2020-3704, 2020.

The Reykjanes Peninsula (RP) is a transtensional plate boundary in southwest Iceland that marks the transition of the Mid-Atlantic Ridge (MAR) from the offshore divergent Reykjanes Ridge (RR) in the west to the South Iceland Seismic Zone (SISZ) in the east. The seismicity here trends ~N80°E in central RP and bends to ~N45°E at its western tip as it joins RR. Seismic surveys, geodetic studies, and recent GPS-based kinematic models indicate that the seismic zone is a collection of strike-slip and normal faults (e.g., Keiding et al., 2008). Meanwhile, the tectonic processes in the region also manifest as NE-SW trending volcanic fissures and normal faults, and N-S oriented dextral faults (e.g., Clifton and Kattenhorn, 2006). The largest of these fissure and normal-fault systems in RP is the Krísuvík-Trölladyngja volcanic system, which is a high-energy geothermal zone. The seismicity here predominantly manifests RP’s transtentional tectonics; however, also hosts triggered events such as those following the 17 June 2000 Mw6.5 earthquake in the SISZ (Árnadottir et al., 2004) ~80 km east of Krísuvík. Stress inversions of microearthquakes from 1997-2006 in the RP indicate that the current stress state is mostly strike-slip with increased normal component to the west, indicating that the seismicity is driven by plate diverging motion (Keiding et al., 2009). However, the geothermal system in Krísuvík is a potential secondary source for triggered seismicity and deformation. This study uses seismic and geodetic data to evaluate the activity in the Krísuvík-Trölladyngja volcanic system. The seismic data is used to identify specific areas of focused activity and evaluate variations in the stress field associated with plate motion and/or geothermal activity over space and time. The data used, within the time period 2007-2016, was collected by the the South Icelandic Lowland (SIL) seismic network operated and managed by the Iceland Meterological Office (IMO). Furthermore, variations in seismicity are compared to crustal deformation observed with TerraSAR-X images from 2009-2019. Crustal changes in the Krísuvík area are quantified to develop a model for corresponding deformation sources. These changes are then correlated with the stress-field variations determined with seismic analysis.

How to cite: M. Parameswaran, R., Th. Bjarnason, I., and Sigmundsson, F.: Seismic and geodetic response to crustal deformation in Krísuvík volcanic system, southwest Iceland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10569, https://doi.org/10.5194/egusphere-egu2020-10569, 2020.

Variation in seismic amplitudes provides different information from the subsurface such as evidence of hydrocarbon accumulation or changes in the lithologies. Furthermore, amplitude anomalies may also be created by thin layers. However, amplitude anomalies are affected by various factors that may not be caused by changes in the lithology or the existence of hydrocarbons such as those caused by acquisition or processing of the seismic data. Hence, these effects need to be understood, eliminated or reduced to background noise levels. Reprocessing of 2D (1992, Caulerpa) and 3D (1995, Laminaria) pre-stack seismic data were applied to examine the veracity of amplitude anomalies at the seabed  in the Laminaria High NW  Shelf of Australia. This study showed that by applying simple but similar processing steps to that applied to the 3D seismic volume that were used in previous studies; it is possible to produce similar amplitude anomalies at the seabed. However, it was noted that amplitude anomalies at the seabed are sensitive to the velocity model; in particular, when applying radon demultiple to suppress the multiple energy in the seismic data. The result of reprocessing these data suggested that the different results of mapping the seabed reflector in this study and previous studies could result from the different processing parameters applied to each data set. Furthermore, reprocessing of the 2D (1992, Caulerpa) that covered the Laminaria High showed similar but not identical amplitude anomalies compared with the original 3D seismic volume (1995), and it is proposed that these difference could be related to the processing applied on each data set. It is concluded in this study, that amplitude anomalies at the seabed are frequency dependent so any manipulation in the frequency filters could affect these amplitude anomalies.

How to cite: Abdulkareem, L.: Quantitative analysis for amplitude anomalies at the seabed in the Laminaria High North West Shelf of Austuralia from 2D (1992 Caulerpa) and 3D (1995, Laminaria) pre-stack seismic data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2059, https://doi.org/10.5194/egusphere-egu2020-2059, 2020.

Total Electron Content (TEC) measured by the Global Positioning System (GPS) is useful to register the pre-earthquake ionospheric anomalies appearing before a large earthquake. In this paper, the TEC value was predicted using the deep neural network. Also, the anomaly is detected utilizing this predicted value and the definition of the threshold value, leading to the use of the anomaly as a precursor. In neural networks, Convolutional Neural Network (ConvNets or CNNs) is one of the main categories to do images recognition, image classifications, object detections, facial recognition, etc. In this study, the CNNs has been applied to the ionospheric TEC of the Global Ionosphere Maps (GIM) data on a powerful earthquake in Chile on the 1st of April in 2014. In this method, a two-hour TEC observation is converted into a time series for this region for several consecutive days before and after the occurrence of an earthquake. The prediction of the non-linear time series is formulated as a method for specific pattern recognition in the input data using ConvNets. Results indicate that under suitable conditions the TEC values can be estimated properly in the aforementioned days and hours by ConvNets. In order to show the efficiency of this method in predicting the time series, the results obtained from this research were compared with those from other researches.

How to cite: Bagheri, H., Farzaneh, H., and Amin, H.: The detection of seismo-ionospheric anomalies using the deep neural network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-548, https://doi.org/10.5194/egusphere-egu2020-548, 2020.

Assessing the temporal evolution of stresses along seismogenic faults is typically done by combining geodetic observations collected near the locations of previous large earthquakes with modeling of the interseismic, coseismic, and postseismic deformation. Here we explore whether it is feasible to link the charge phase of large earthquakes to rigid microplate motions, which can be inferred from geodetic observations that are instead collected further away from crustal faults. We use numerical simulations of the dynamics and associated kinematics of an idealized, rigid microplate subject to stress buildups and drop-offs from a series of earthquakes. Simulations span the charging cycle of a single 6.5 < M_W < 8 earthquake. Several M_W < 6.5 earthquakes distributed according to the Gutenberg-Richter law occur meanwhile. We use large ensembles of simulations featuring randomly-generated earthquake hypocenters and make statistical assessments of the fraction of model time needed for the microplate motions to depart from the initial one to a degree that is larger than typical geodetic uncertainties, and for at least 90% of the remaining time before the large earthquake occurs. We find such a fraction (i) to be only one tenth in simulations that do feature a large earthquake, (ii) to be longer in simulations that do not, and (iii) to remain small for realistic microplate geometries and asthenosphere viscosity/thickness values. Our inferences hold also when we simulate geodetic time series shorter than the large-earthquake cycle, and even when we assume that only half of the stress buildup affects the microplate rigid motion.

How to cite: Iaffaldano, G. and Martin de Blas, J.: Using rigid microplate motions to detect the stress buildup preceding large earthquakes: a feasibility test based on synthetic models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12670, https://doi.org/10.5194/egusphere-egu2020-12670, 2020.

We processed data from ~600 GPS stations, covering the period 1999-2018, to provide new insights into the crustal motion and deformation of Sichuan and Yunnan, China. We used the derived velocity field to evaluate two-dimensional strain rate tensors, and mapped the main, maximum shear, dilatation, east-west and north-south strain rates.The spatial distribution of the main strain rate in the Sichuan-Yunnan region generally shows an orderly deflection. The minimum principal strain rate is northeastward in the west of the Sichuan-Yunnan block boundary, gradually deflects eastward and southeastward toward the east and south, and returns to the northeast direction until the southwestern edge of Sichuan-Yunnan. This reflects the complex tectonic dynamics background of the study area. The high value of the maximum shear strain rate is mainly distributed along the eastern boundary of the Sichuan-Yunnan block, especially near the Xianshuihe-Xiaojiang fault, where the maximum shear strain rate exceeds 4.0 × 10^-8 / a. The area strain rate in the study region shows that the areas of compression and expansion are comparable, with weak tensions prevailing in the interior and compression in the marginal areas. The strain rate result also shows that the east-west strain rate component in the southern Sichuan-Yunnan is dominated by positive value, and the north is dominated by negative value. It indicates that the east-west deformation in the south of the Sichuan-Yunnan is dominated by expansion, and in the north is dominated by contraction. The north-south component strain rate shows that there is a significant positive high-value zone in and around the Xianshuihe fault zone, while southern Sichuan-Yunnan is a more significant negative-value zone, and the distribution of negative high-value zones is controlled by the south boundary of the Sichuan-Yunnan block. Based on the fault activity and focal mechanism data, the study area was divided into several seismic source zones. We translated the geodetic strain rates into rates of seismic moment release in each zone and compared them with earthquake catalog-based moment rates, to evaluate the potential of seismic activity of the region. The analysis shows the geodetic strain is completely released seismically for most of the study area. However, for the southern Yunnan，the geodesy-based moment rates are more than 2 times higher than the earthquake-based rates. This result indicates that at least a large earthquake may occur in southern Yunnan in the future.

How to cite: Zhao, J., Wu, Y., Liang, H., and Du, K.: Strain patterns of Sichuan and Yunnan, China from GPS data and comparison between seismic and geodetic moment release, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13090, https://doi.org/10.5194/egusphere-egu2020-13090, 2020.

How to cite: D'Acquisto, M., Herman, M., and Govers, R.: On the cause of enhanced landward motion of the overriding plate after a major subduction earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18250, https://doi.org/10.5194/egusphere-egu2020-18250, 2020.

The Nankai trough has hosted ~M8 interplate earthquakes with the interval of 100-200 years. The crustal activity in southwest (SW) Japan in the overriding plate was relatively quiet after the last coupled megathrust ruptures occurred in 1944 and 1946. In the recent 20 years, however, SW Japan has experienced ~M7 earthquakes such as the 2016 Kumamoto earthquake. Similar activation of crustal earthquakes in the later stage of the megathrust earthquake cycles can be found in the historical earthquake occurrence based on paleographical studies. Such a change cannot be resolved by the probabilistic approaches, which usually rely on paleo-seismological data on longer timescales. Here, we show a deterministic way to quantify the current stressing state on the source faults due to megathrust coupling at the Nankai trough, making use of the data captured by the dense, modern geodetic network in Japan.

We constructed a 3-D finite element model (FEM) around the Japanese islands including the viscoelastic feature in the asthenosphere. The geometry of plate boundary on the Philippine Sea slab is based on earthquake distributions determined by the previous studies. In particular, the bended geometry at the junction of the Nankai trough and the Ryukyu trench is crucial for calculating stress. The plate boundary is divided into 8 x 27 patches to generate Green’s functions. The model region is divided into about 1000,000 tetrahedral elements with dimension of 5-100 km. We revised the source fault model by the Headquarters for Earthquake Research Promotion based on recent geophysical and geological data and added new faults in the Sea of Japan.

Our inter-seismic inversion suggests ~8 cm/year slip-rate deficit, which is consistent with the previous studies. Using the slip distribution, we calculate stressing rates on the source faults over SW Japan. In particular, positive Coulomb stressing rate on the source faults of the 2016 Kumamoto earthquake and the other M7 earthquakes is consistent with their occurrence. The crustal earthquakes before the 1944 and 1946 megathrust events also occurred in the region with source faults with positive Coulomb stressing rate.

How to cite: Hashima, A., Sato, H., Ishiyama, T., Freed, A., and Becker, T.: Fault stressing in the overriding plate due to megathrust coupling along the Nankai trough, Japan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18393, https://doi.org/10.5194/egusphere-egu2020-18393, 2020.