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1.
A. B. Baba E. E. Papadimitriou B. C. Papazachos C. A. Papaioannou B. G. Karakostas 《Pure and Applied Geophysics》2000,157(5):765-783
2.
"Parametric-historic" Procedure for Probabilistic Seismic Hazard Analysis Part II: Assessment of Seismic Hazard at Specified Site 总被引:3,自引:0,他引:3
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4.
Xavier Casamitjana Jordi Colomer Harindra J. S. Fernando 《Aquatic Sciences - Research Across Boundaries》2000,62(1):79-90
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6.
S. P. Satyabala 《Pure and Applied Geophysics》2003,160(9):1611-1650
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Ram Bichar Singh Yadav Jayant Nath Tripathi Bal Krishna Rastogi Mridul Chandra Das Sumer Chopra 《Pure and Applied Geophysics》2010,167(11):1331-1342
Northeast India and adjoining regions (20°–32° N and 87°–100° E) are highly vulnerable to earthquake hazard in the Indian
sub-continent, which fall under seismic zones V, IV and III in the seismic zoning map of India with magnitudes M exceeding 8, 7 and 6, respectively. It has experienced two devastating earthquakes, namely, the Shillong Plateau earthquake
of June 12, 1897 (M
w
8.1) and the Assam earthquake of August 15, 1950 (M
w
8.5) that caused huge loss of lives and property in the Indian sub-continent. In the present study, the probabilities of
the occurrences of earthquakes with magnitude M ≥ 7.0 during a specified interval of time has been estimated on the basis of three probabilistic models, namely, Weibull,
Gamma and Lognormal, with the help of the earthquake catalogue spanning the period 1846 to 1995. The method of maximum likelihood
has been used to estimate the earthquake hazard parameters. The logarithmic probability of likelihood function (ln L) is estimated
and used to compare the suitability of models and it was found that the Gamma model fits best with the actual data. The sample
mean interval of occurrence of such earthquakes is estimated as 7.82 years in the northeast India region and the expected
mean values for Weibull, Gamma and Lognormal distributions are estimated as 7.837, 7.820 and 8.269 years, respectively. The
estimated cumulative probability for an earthquake M ≥ 7.0 reaches 0.8 after about 15–16 (2010–2011) years and 0.9 after about 18–20 (2013–2015) years from the occurrence of
the last earthquake (1995) in the region. The estimated conditional probability also reaches 0.8 to 0.9 after about 13–17
(2008–2012) years in the considered region for an earthquake M ≥ 7.0 when the elapsed time is zero years. However, the conditional probability reaches 0.8 to 0.9 after about 9–13 (2018–2022)
years for earthquake M ≥ 7.0 when the elapsed time is 14 years (i.e. 2009). 相似文献
8.
G. Petiau 《Pure and Applied Geophysics》2000,157(3):357-382
9.
Temporal distribution of earthquakes with M w > 6 in the Dasht-e-Bayaz region, eastern Iran has been investigated using time-dependent models. Based on these types of models, it is assumed that the times between consecutive large earthquakes follow a certain statistical distribution. For this purpose, four time-dependent inter-event distributions including the Weibull, Gamma, Lognormal, and the Brownian Passage Time (BPT) are used in this study and the associated parameters are estimated using the method of maximum likelihood estimation. The suitable distribution is selected based on logarithm likelihood function and Bayesian Information Criterion. The probability of the occurrence of the next large earthquake during a specified interval of time was calculated for each model. Then, the concept of conditional probability has been applied to forecast the next major (M w > 6) earthquake in the site of our interest. The emphasis is on statistical methods which attempt to quantify the probability of an earthquake occurring within a specified time, space, and magnitude windows. According to obtained results, the probability of occurrence of an earthquake with M w > 6 in the near future is significantly high. 相似文献
10.
The present study aims at understanding the seismotectonic province of the Shillong Plateau (SP) by identifying the potential seismic source zones within a radius of 500 km from the centre of the SP. From existing literature and earthquake (EQ) data, the seismotectonic region is found to vary in terms of seismicity, tectonic features, geology, thickness of overburden, rupture characteristics and rate of movement. Thus, entire 500-km-radius seismotectonic region is divided into four seismic source zones: namely (1) the Shillong Plateau–Assam Valley Zone (SP-AVZ), (2) the Indo-Burma Ranges Zone (IBRZ), (3) the Bengal Basin Zone (BBZ) and (4) the Eastern Himalaya Zone (EHZ). EQ catalogues for each source zone is analysed for completeness of magnitude and time. Seismic parameter b estimated using a maximum likelihood method is found to be 0.91 ± 0.03, 0.94 ± 0.02, 0.80 ± 0.03 and 0.89 ± 0.03 for the SP-AVZ, IBRZ, BBZ and EHZ, respectively. In addition, the maximum likelihood method is used to estimate the mean annual activity rate, maximum possible magnitude (m max), return period and probability of exceedance for the four zones. The b values estimated suggest that the BBZ is seismically more active; however, the rate of occurrence of EQs is highest in the IBRZ. Findings from this study are an indication of the relative contribution from each of the four seismic source zones towards a seismic hazard of the SP. 相似文献
11.
Since March 2014, an unusually large amount of earthquakes occur southeast of the city of Darmstadt in the northern Upper Rhine Graben. During the period, until April 2015, we have recorded 356 earthquakes with magnitudes ranging from ML?=??0.6 to 4.2. We identified two source clusters separated laterally by about 5 km. The hypocentres within these clusters are aligned vertically extending over a depth range from 1 to 8 km with a lateral extent of about 1 to 2 km. Focal mechanisms show left-lateral strike-slip movements; b values are changing with time between b?=?0.6 and b?=?0.9. This is the first time in almost 150 years that such high earthquake rates have been observed in the region. Historical accounts dating back to the nineteenth century report of over 2000 felt earthquakes over a time span from 1869 to 1871. From these, maximum intensities of VII have been estimated. Other seismic activities in the region were reported in the 1970s. The observations of the 2014–2015 earthquake series do not completely match a typical main shock–aftershock sequence or a typical earthquake swarm. Especially the activity at the beginning of the earthquake series may be considered as a mixture of a main shock–aftershock sequence and a short-lasting swarm event. Whether or not the time gap between the current seismic activity, which actually takes place at the same locations as parts of the seismic swarm in 1869–1871, and the seismic activity in the nineteenth century or the seismic activity in the 1970s can be interpreted as a seismic cycle remains unclear. 相似文献
12.
S. T. G. Raghukanth 《Bulletin of Earthquake Engineering》2011,9(5):1361-1386
India’s urban population has increased in the recent times. An earthquake near an urban agglomeration has the potential to
cause severe damage. In this article, seismicity parameters for region surrounding important urban agglomerations in India
are estimated. A comprehensive earthquake catalogue for the region (6°E–42°E latitude and 60°N–100°N longitude) including
historic and pre-historic events has been compiled from various sources. To estimate the parameters, past earthquake data
in a control region of radius 300 km has been assembled to quantify the seismicity around each urban agglomeration. The collected
earthquake data is first evaluated for its completeness. From combined (historical and instrumental) data, the seismicity
parameters b-value, seismic activity rate, λ and maximum expected magnitude (m
max
) have been obtained from the methodology proposed by Kijko and Graham (1998). The obtained activity rates indicate that region surrounding Guwahati urban agglomeration is the most seismically active
region followed by Srinagar, Patna, Amritsar and Chandigarh. 相似文献
13.
Ram Bichar Singh Yadav Jayant Nath Tripathi Bal Krishna Rastogi Sumer Chopra 《Pure and Applied Geophysics》2008,165(9-10):1813-1833
The Gujarat and adjoining region falls under all four seismic zones V, IV, III and II of the seismic zoning map of India, and is one of the most seismically prone intracontinental regions of the world. It has experienced two large earthquakes of magnitude M w 7.8 and 7.7 in 1819 and 2001, respectively and several moderate earthquakes during the past two centuries. In the present study, the probability of occurrence of earthquakes of M ≥ 5.0 has been estimated during a specified time interval for different elapsed times on the basis of observed time intervals between earthquakes using three stochastic models namely, Weibull, Gamma and Lognormal. A complete earthquake catalogue has been used covering the time interval of 1819 to 2006. The whole region has been divided into three major seismic regions (Saurashtra, Mainland Gujarat and Kachchh) on the basis of seismotectonics and geomorphology of the region. The earthquake hazard parameters have been estimated using the method of maximum likelihood. The logarithmic of likelihood function (ln L) is estimated and used to test the suitability of models in three different regions. It was found that the Weibull model fits well with the actual data in Saurashtra and Kachchh regions, whereas Lognormal model fits well in Mainland Gujarat. The mean intervals of occurrence of earthquakes are estimated as 40.455, 20.249 and 13.338 years in the Saurashtra, Mainland Gujarat and Kachchh region, respectively. The estimated cumulative probability (probability that the next earthquake will occur at a time later than some specific time from the last earthquake) for the earthquakes of M ≥ 5.0 reaches 0.9 after about 64 years from the last earthquake (1993) in Saurashtra, about 49 years from the last earthquake (1969) in Mainland Gujarat and about 29 years from the last earthquake (2006) in the Kachchh region. The conditional probability (probability that the next earthquake will occur during some specific time interval after a certain elapsed time from last earthquake) is also estimated and it reaches about 0.8 to 0.9 during the time interval of about 57 to 66 years from the last earthquake (1993) in Saurashtra region, 31 to 51 years from the last earthquake (1969) in Mainland Gujarat and about 21 to 28 years from the last earthquake (2006) in Kachchh region. 相似文献
14.
Probabilistic Assessment of Earthquake Hazards in the North-East Indian Peninsula and Hindukush Regions 总被引:2,自引:0,他引:2
—The Himalayan region is one of the most seismic prone areas of the world. The North-East (NE) Indian peninsula and the Hindukush regions mark the zone of collision of the Indian and Eurasian plates. The probability of the occurrence of great earthquakes with magnitude greater than 7.0 during a specified interval of time has been estimated on the basis of four probabilistic models, namely, Weibull, Gamma, Lognormal and Exponential for the NE Indian peninsula and Hindukush regions. The model parameters have been estimated by the method of Maximum Likelihood Estimates (MLE) and the Method of Moments (MOM). The cumulative probability is estimated for a period of 40 years from 1964 and is ranging between 0.881 to 0.995 by the year 1995, using all four models for the NE Indian peninsula. The conditional probability is also estimated and it is concluded that the NE Indian peninsula would expect a great earthquake at any time in the remaining years of the present century. For the Hindukush region, the cumulative probability has already crossed its highest value, but no earthquake of magnitude greater than 7.0 has occurred after 1974 in this area. It may attribute to the occurrence of frequent shocks of moderate size, as seventeen earthquakes of magnitude greater than 6.0, including four greater than 6.4, have been reported until 1994 from this region. 相似文献
15.
Charles-Philippe Lienemann Marc Monnerat Janusz Dominik Didier Perret 《Aquatic Sciences - Research Across Boundaries》1999,61(2):133-149
16.
Steady convective exchange flows down slopes 总被引:2,自引:0,他引:2
Jeff J. Sturman Carolyn E. Oldham Greg N. Ivey 《Aquatic Sciences - Research Across Boundaries》1999,61(3):260-278
17.
四川盆地南部的长宁页岩气开发区附近地震频发,近年来已发生近10次ML>4.0的中型地震和万余次ML1.0~3.0的小微地震,灾害风险持续增高。由于国家地震台网的固定台站较为分散,难以捕捉到1级以下微震事件的精确信息,通过近场微震监测数据来分析页岩气开发区的地震风险演化趋势,已经成为势在必行的科学问题。本文基于专门布设的13个近场流动台站和国家地震台网固定台站2017年2月至2018年6月监测拾取到的1万余个地震事件,采用最大似然估计法计算了双差定位后地震目录的b值,详细探讨了长宁页岩气开发区的b值演化特征。基于更低的最小完整震级,估计出区域总体b值为0.98±0.02,略高于前人研究结果。拟合直线的双线性特征和错位分布指示出b值演化可能存在明显的时空差异特征。通过分析验证了这一结果,并且发现5个地震事件数量快速增加的时间段恰好伴随着b值的强振荡特征和相关空间距离SCL值的稳定低值分布,认为可能与附近的页岩气压裂开采存在关联。分析认为4个较大震级事件发生之前出现的b值下降应归因于震前的应力累积过程,类似于一般的大型天然地震事件。 相似文献
18.
This paper investigates the suitability of a three-parameter (scale, shape, and location) Weibull distribution in probabilistic assessment of earthquake hazards. The performance is also compared with two other popular models from same Weibull family, namely the two-parameter Weibull model and the inverse Weibull model. A complete and homogeneous earthquake catalog (Yadav et al. in Pure Appl Geophys 167:1331–1342, 2010) of 20 events (M ≥ 7.0), spanning the period 1846 to 1995 from north–east India and its surrounding region (20°–32°N and 87°–100°E), is used to perform this study. The model parameters are initially estimated from graphical plots and later confirmed from statistical estimations such as maximum likelihood estimation (MLE) and method of moments (MoM). The asymptotic variance–covariance matrix for the MLE estimated parameters is further calculated on the basis of the Fisher information matrix (FIM). The model suitability is appraised using different statistical goodness-of-fit tests. For the study area, the estimated conditional probability for an earthquake within a decade comes out to be very high (≥0.90) for an elapsed time of 18 years (i.e., 2013). The study also reveals that the use of location parameter provides more flexibility to the three-parameter Weibull model in comparison to the two-parameter Weibull model. Therefore, it is suggested that three-parameter Weibull model has high importance in empirical modeling of earthquake recurrence and seismic hazard assessment. 相似文献
19.
The Reviewed Event Bulletin (REB) of the International Data Center (IDC) has been used in order to investigate the seismicity of the Northwest Himalaya and its neighboring region for the time period June 1999 to March 2015 within the geographical coordinates 25–40° N latitude and 65–85° E longitude. We have used a very precisely located earthquake dataset recorded by the International Monitoring System (IMS) Network containing 7,583 events with body wave magnitudes from 2.5 to 6.3. The study area has been subdivided into six regions based on the Flinn-Engdahl (F-E) seismic and geographical regionalization scheme, which was used as the region classifications of the International Data Center catalog. The examined region includes NW India, Pakistan, Nepal, Xizang, Kashmir, and Hindukush. For each region, Magnitudes of completeness (Mc) and Gutenberg-Richter (GR) recurrence parameters (a and b values) have been estimated. The Gutenberg-Richter analysis is preceded by an overview of the seismotectonics of the study area. The obtained Mc values vary from 3.5 to 3.9. The lower value of Mc was found mainly in Xizang region whereas the higher Mc threshold is evident in Pakistan region. However, the b values vary from 1.19 to 1.48. The lowest b value is recorded in Xizang region, which is mostly related to the Main Karakoram Thrust (MKT) fault, whereas the highest b values are recorded in NW India and Kashmir regions, which are mostly related to the Main Frontal Thrust (MFT) fault. The REB for the selected period has been compared to the most renowned bulletin of global seismicity, namely that issued by the National Earthquake Information Center (NEIC) of the United States Geological Survey (USGS). A study of 4,821 events recorded by USGS in the study region indicates that about 36 % of seismic events were missed and the catalog is considered as complete for events with magnitudes ≥4.0. However, both a and b values are obviously higher than those of IMS catalog. The a and b parameters in the Gutenberg-Richter magnitude–frequency relationship have been utilized to forecast the probability of future earthquakes of different magnitudes and returned periods (recurrence intervals). 相似文献
20.
K. Koch 《Pure and Applied Geophysics》2002,159(4):759-778