Journal of Seismology and Earthquake Engineering
Volume:20 Issue: 2, Summer 2018

A devastating earthquake with moment magnitude of 7.3 hit Sarpol-e Zahab in the Zagros on November 12, 2017. An intense aftershock sequence was recorded by the permanent and dense temporary seismic networks, which installed rapidly in the epicentral region. The focal mechanisms of the November 2017 aftershocks were gathered (for about 50 events) and derived (for about 10 events) from P-wave polarities and/or waveform modeling, show predominantly thrust movements. The transpressional stress regime in the region is suggested as the driving force for the earthquakes. The temporal variation of the principal stress directions analyzed by subsequent stress inversion in several time intervals following the Nov. 2017 mainshocks. In addition, the spatial stress variations were studied implementing the stress tensor inversion in different clusters of events. These results suggest that the 2017 mainshock ruptures caused both spatial and temporal stress perturbations that continued in time showing a specific character, which was not observed before in the Zagros region.

In this study, seismological aspects of the 2017 Sarpol-e Zahab earthquake has been investigated. The Sarpol-e Zahab earthquake, of magnitude 7.3 (Mw), occurred in southwestern Iran on November 12, 2017. Here, we investigated the properties of the strong ground motions of the earthquake using the records provided by Iranian Strong Motion Network (ISMN). At Sarpol-e Zahab (SPZ) station, about 30 km south of the epicenter, the recorded peak ground acceleration (PGA) and peak ground velocity (PGV) in both horizontal and vertical components were remarkably large, and visual inspection of the velocity time history reveals a pulse-like shape. Besides, the response spectra of the recordings were determined and were compared to the 2800 seismic code spectrum. Furthermore, the earthquake engineering parameters for this earthquake were estimated and were compared with the values of other large destructive earthquakes in Iran. Finally, based on the recorded strong motion data and observed information such as the macroseismic intensity, ShakeMaps of this earthquake have been generated, which clearly shows the most affected areas that needed the immediate assistance and aid after the earthquake. These maps are fundamental for earthquake rapid response procedures and the earthquake crisis management.

In this paper, the dynamics seismic activity and fractal structures in magnitude time series of Sarpol-e Zahab earthquakes are investigated. In this case, the dynamics seismic activity is analyzed through the evolution of the scaling parameter so-called Hurst exponent. By estimating the Hurst parameter, we can investigate how the consecutive earthquakes are related. It has been observed that more than one scaling exponent is needed to account for the scaling properties of earthquake time series. Therefore, the influence of different time-scales on the dynamics of earthquakes is measured by decomposing the seismic time series into simple oscillations associated with distinct time-scales. To this end, the empirical mode decomposition (EMD) method was used to estimate the locally long-term persistence signature derived from the Hurst exponent. As a result, the timedependent Hurst exponent, H(t), was estimated and all values of H>0.5 was obtained, indicating a long-term memory exists in earthquake time series. The main contribution of this paper is estimating H(t) locally for different time-scales and investigating the long-memory behavior exist in the non-stationary multifractal time-series. The time-dependent scaling properties of earthquake time series are associated with the relative weights of the amplitudes at characteristic frequencies. The superiority of the method is the simplicity and the accuracy in estimating the Hurst exponent of earthquakes in each time, without any assumption on the probability distribution of the time series

Earthquake Early Warning System (EEWS) is issued by detection of P-wave, estimation of seismic parameters and decision to alarm. The EEWS provides advance warning of estimated seismic intensities and expected arrival time of S-waves. These estimates are based on prompt analysis of hypocenter location and earthquake magnitude using data observed by seismographs near the epicenter. In this study, the B-D method is examined to estimate an earthquake's magnitude and epicentral distance using only initial part of P-wave data (3 s) from a single station for application in EEWS. Fitting a simple function with the form of f(t)=Bt×exp(-At) to the first few seconds of the waveform envelope, coefficients A and B are determined through the least-squares method. B decreases with distance and shows independence from magnitude and logB is inversely proportional to logD, where D is the epicentral distance. B values are calculated on the basis of 65 vertical-component accelerograms of Sarpol-e Zahab earthquake (Mw 7.3) with epicentral distances less than 100 km. The magnitude and an amplitude parameter Pmax determined from the very beginning of P-wave, are important for EEWS, yet their dependence on source mechanism, focal depth and epicentral distance has not been fully studied. Using this method, we could estimate the epicentral distance by logD = -0.57logB + 2.4 ± 0.4 and earthquake magnitude by Mest= 1.99 log Pmax-1.76 log B + 5.62 ± 0.3. The greatest advantage of this method is its accuracy and rapidness. The EEW system issues several alarm messages during the course of one earthquake, improving the accuracy of the warning as the amount of available data increases. The EEW is transmitted to many kinds of devices and used for personal safety and automatic control. It is very important to observe strong motion in real-time using a dense network in order to improve the EEW system.

By using slip model from USGS and focal mechanism and aftershocks distribution from Iranian Seismological Center (IRSC) for Sarpol-e Zahab earthquake (Mw 7.3) on November 12, 2017, we investigated the correlation between Coulomb stress changes and aftershocks distribution. In this study, about 500 aftershocks with magnitude larger than 2.5 and azimuthal gap less than 180 degrees were selected. Calculated Coulomb stress changes on the optimally oriented faults showed that most of the seismicity occurred in regions of increased stress and the majority of them concentrated on the ruptured plane, especially in west and south parts. Besides, nodal planes of the selected 11 aftershocks received positive Coulomb stress changes. Therefore, there is a good correlation between Coulomb stress changes and aftershocks distribution in Sarpol-e Zahab event. Furthermore, calculated static stress on the surrounding faults showed that middle part of the High Zagros Fault (HZF), the northern part of the Main Recent Fault (MRF), and the northern part of the Zagros Foredeep Fault (ZFF) are located in the positive stress change area.

Providing appropriate near real time ground motion shaking map is a critical requirement to effectively manage the consequence of an earthquake. In the present study, the standard procedure adopted by USGS ShakeMap to develop the ground motion shaking map is calibrated to implement in Iran. Selecting appropriate ground motion predictions equation and properly modeling of the local site condition are two important parameters that should be properly modeled to provide an appropriate ground motion shaking map. Here, a set of local, regional and global GMPEs that show good performance in the previous studies are adopted. Besides, the approach developed by Borcherdt [1] is used to take into account the local site condition. The VS30 of the region exploited from the proxy approach proposed by Wald and Allen [2]. The study evaluates the potential applicability of this method by compiling a database of measured and estimated VS30. The resultsindicate that the method outperforms than random selection of the site class. The calibrated model implements to generate the ground motion shaking map of the Sarpol-e Zahab, Iran earthquake (2017). The result shows that the approach performs better than employing GMPEs alone. The calibrated model can be used to generate the database of ground motion shaking of past earthquakes in Iran, which is an important requirement to develop empirical fragility or vulnerability models.