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Along a subduction zone, great megathrust earthquakes recur either after long seismic gaps lasting several decades to centuries or over much shorter periods lasting hours to a few years when cascading successions of earthquakes rupture nearby segments of the fault. We analyze a decade of continuous Global Positioning System observations along the South American continent to estimate changes in deformation rates between the 2010 Maule (M8.8) and 2015 Illapel (M8.3) Chilean earthquakes. We find that surface velocities increased after the 2010 earthquake, in response to continental-scale viscoelastic mantle relaxation and to regional-scale increased degree of interplate locking. We propose that increased locking occurs transiently during a super-interseismic phase in segments adjacent to a megathrust rupture, responding to bending of both plates caused by coseismic slip and subsequent afterslip. Enhanced strain rates during a super-interseismic phase may therefore bring a megathrust segment closer to failure and possibly triggered the 2015 event.
The seismicity of the Dead Sea fault zone (DSFZ) during the last two millennia is characterized by a number of damaging and partly devastating earthquakes. These events pose a considerable seismic hazard and seismic risk to Syria, Lebanon, Palestine, Jordan, and Israel. The occurrence rates for large earthquakes along the DSFZ show indications to temporal changes in the long-term view. The aim of this thesis is to find out, if the occurrence rates of large earthquakes (Mw ≥ 6) in different parts of the DSFZ are time-dependent and how. The results are applied to probabilistic seismic hazard assessments (PSHA) in the DSFZ and neighboring areas. Therefore, four time-dependent statistical models (distributions), including Weibull, Gamma, Lognormal and Brownian Passage Time (BPT), are applied beside the exponential distribution (Poisson process) as the classical time-independent model. In order to make sure, if the earthquake occurrence rate follows a unimodal or a multimodal form, a nonparametric bootstrap test of multimodality has been done. A modified method of weighted Maximum Likelihood Estimation (MLE) is applied to estimate the parameters of the models. For the multimodal cases, an Expectation Maximization (EM) method is used in addition to the MLE method. The selection of the best model is done by two methods; the Bayesian Information Criterion (BIC) as well as a modified Kolmogorov-Smirnov goodness-of-fit test. Finally, the confidence intervals of the estimated parameters corresponding to the candidate models are calculated, using the bootstrap confidence sets. In this thesis, earthquakes with Mw ≥ 6 along the DSFZ, with a width of about 20 km and inside 29.5° ≤ latitude ≤ 37° are considered as the dataset. The completeness of this dataset is calculated since 300 A.D. The DSFZ has been divided into three sub zones; the southern, the central and the northern sub zone respectively. The central and the northern sub zones have been investigated but not the southern sub zone, because of the lack of sufficient data. The results of the thesis for the central part of the DSFZ show that the earthquake occurrence rate does not significantly pursue a multimodal form. There is also no considerable difference between the time-dependent and time-independent models. Since the time-independent model is easier to interpret, the earthquake occurrence rate in this sub zone has been estimated under the exponential distribution assumption (Poisson process) and will be considered as time-independent with the amount of 9.72 * 10-3 events/year. The northern part of the DSFZ is a special case, where the last earthquake has occurred in 1872 (about 137 years ago). However, the mean recurrence time of Mw ≥ 6 events in this area is about 51 years. Moreover, about 96 percent of the observed earthquake inter-event times (the time between two successive earthquakes) in the dataset regarding to this sub zone are smaller than 137 years. Therefore, it is a zone with an overdue earthquake. The results for this sub zone verify that the earthquake occurrence rate is strongly time-dependent, especially shortly after an earthquake occurrence. A bimodal Weibull-Weibull model has been selected as the best fit for this sub zone. The earthquake occurrence rate, corresponding to the selected model, is a smooth function of time and reveals two clusters within the time after an earthquake occurrence. The first cluster begins right after an earthquake occurrence, lasts about 80 years, and is explicitly time-dependent. The occurrence rate, regarding to this cluster, is considerably lower right after an earthquake occurrence, increases strongly during the following ten years and reaches its maximum about 0.024 events/year, then decreases over the next 70 years to its minimum about 0.0145 events/year. The second cluster begins 80 years after an earthquake occurrence and lasts until the next earthquake occurs. The earthquake occurrence rate, corresponding to this cluster, increases extremely slowly, such as it can be considered as an almost constant rate about 0.015 events/year. The results are applied to calculate the time-dependent PSHA in the northern part of the DSFZ and neighbouring areas.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.