A comprehensive earthquake catalogue for the Iranian Plateau (400 B.C. to December 31, 2018)

Mousavi-Bafrouei, Seyed Hasan; Mahani, Alireza Babaie

doi:10.1007/s10950-020-09923-6

Cited by 23 publications

(3 citation statements)

References 77 publications

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“…For Ecuador, we retrieved the earthquake catalogue from "Instituto Geofísico de la Escuela Politécnica Nacional" (download from https://www.igepn.edu.ec/ (accessed on 30 April 2022). For the Iran earthquake catalogue, we used the one provided by Mousavi-Bafrouei and Mahani [35], which includes the period investigated in this paper. Finally, we retrieved the Japan Meteorological Agency (JMA) Unified Hypocenter Catalog for the Japan earthquake.…”

Section: Earthquake Cataloguesmentioning

confidence: 99%

Developing a Fuzzy Inference System Based on Multi-Sensor Data to Predict Powerful Earthquake Parameters

Akhoondzadeh

Marchetti

2022

Remote Sensing

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Predicting the parameters of upcoming earthquakes has always been one of the most challenging topics in studies related to earthquake precursors. Increasing the number of sensors and satellites and consequently incrementing the number of observable possible earthquake precursors in different layers of the lithosphere, atmosphere, and ionosphere of the Earth has opened the possibility of using data fusion methods to estimate and predict earthquake parameters with low uncertainty. In this study, a Mamdani fuzzy inference system (FIS) was proposed and implemented in five case studies. In particular, the magnitude of Ecuador (16 April 2016), Iran (12 November 2017), Papua New Guinea (14 May 2019), Japan (13 February 2021), and Haiti (14 August 2021) earthquakes were estimated by FIS. The results showed that in most cases, the highest number of anomalies was usually observed in the period of about one month before the earthquake and the predicted magnitude of the earthquake in these periods was slightly different from the actual magnitude value. Therefore, based on the results of this study, it could be concluded that if a significant number of anomalies are observed in the time series of different precursors, it is likely that an earthquake of the magnitude predicted by the proposed FIS system within the Dobrovolsky area of the studied location will happen during the next month.

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Section: Earthquake Cataloguesmentioning

confidence: 99%

Developing a Fuzzy Inference System Based on Multi-Sensor Data to Predict Powerful Earthquake Parameters

Akhoondzadeh

Marchetti

2022

Remote Sensing

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“…In the databank, moment magnitude is provided from international and national bulletins for only 12% of events (387 of 3180 events), for the remaining events we used the magnitude conversion relationships of Mousavi-Bafrouei and Mahani (2020) to obtain the more homogenous magnitude information and increase the number of earthquakes associated with moment magnitude values. In Fig.…”

Section: Structure Of the Databankmentioning

confidence: 99%

The recently compiled strong motion databank of Iran

Shokouhirad,

Ansari,

Ghafory-Ashtiany

2023

Preprint

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This paper presents a comprehensive and integrated databank of the Iranian strong ground motions that occurred from 1973 to 2018. The databank consists of 7196 three-component acceleration records from 3180 earthquakes and 1157 stations in Iran. In this paper, the characteristics of the Iranian strong ground motion data are presented in terms of event, station, and recording distributions. The events are characterized by magnitude in the range 2.4–7.7. Shear wave velocity has been measured and reported at 603 strong motion stations of the databank. In this study, three different empirical techniques are applied to classify the stations. A new method is proposed for site classification based on the correlation coefficient between the horizontal-to-vertical (H/V) response spectral ratios of the ground motion records recorded by each station. It is noticeable that the raw accelerograms have been uniformly processed in the entire databank using the filtering and wavelet de-noising methods to remove high- and low-frequency noise. Moreover, by comparison between the Fourier Amplitude Spectrum (FAS) of the noises detected in all acceleration and velocity time series by the filtering and the wavelet de-noising methods, it was determined that the mean and mode of FAS of the noises detected by the wavelet de-noising method in most of the frequencies is higher than mean and mode of FAS of the noises detected by the filtering method.

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“…In this study, possibly for the first time, both the probabilistic and the deterministic approaches to 𝑚 estimation was applied to Iran. The input information for the probabilistic procedures is the recent magnitude-type homogeneous earthquake catalog provided by Mousavi-Bafrouei and Mahani (2020). The product of computation is the 𝑚 map for the territory of Iran.…”

Section: Introductionmentioning

confidence: 99%

Estimating the maximum earthquake magnitude in the Iranian Plateau

et al. 2021

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The Iranian Plateau has been subjected to destructive earthquakes throughout its history. Reliable assessment of the seismic hazard in this earthquake-prone region is therefore essential. Our study focuses on estimating the maximum earthquake magnitude as one of the main parameters of seismic hazard analysis. We implemented two quantitative approaches, namely probabilistic and deterministic. The probabilistic method allows combining the historical (i.e., incomplete) and the instrumental parts of a catalog with different levels of completeness and considers the uncertainties in earthquake magnitude determination. In this study, we used a unified, declustered, and complete catalog of earthquakes in Iran, covering the period from the 4th century B.C. to 2019. We calculated the maximum possible magnitudes for hundreds of grid points by using the seismicity data in a 200-km radial region around each grid point. The maximum possible earthquake was observed to vary between 6.0 and 8.2 and the highest values were found in the Alborz-Azarbayejan seismotectonic province, Kopeh-Dagh, central east Iran, Makran, and the southeast Zagros. The lowest 𝑚 values were found in the Persian Gulf, Arabian Platform, Esfahan-Sirjan region, and the Dasht-e-Kavir Desert in central Iran. As a second part to this study, we calculated the maximum credible earthquakes for 1 103 identified major faults by using five empirical magnitude-scaling relationships. Our results were consistent with both the observed earthquakes and the seismic potential of the various seismogenic zones of Iran. The study results can be used in future seismic hazard analyses, and have fundamental implications for mitigating seismic risk in Iran.

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A comprehensive earthquake catalogue for the Iranian Plateau (400 B.C. to December 31, 2018)

Cited by 23 publications

References 77 publications

Developing a Fuzzy Inference System Based on Multi-Sensor Data to Predict Powerful Earthquake Parameters

Developing a Fuzzy Inference System Based on Multi-Sensor Data to Predict Powerful Earthquake Parameters

The recently compiled strong motion databank of Iran

Estimating the maximum earthquake magnitude in the Iranian Plateau

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