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通过收集、整理和分析青藏高原东北部22条断裂带上古地震定量数据,拟定了该区的地震复发概率密度函数.根据此函数对区内东昆仑断裂带东段不同段落上未来100年内强震原地复发的条件概率进行了初步研究.结果表明,该断裂带上自西向东的3个破裂段中,玛沁段和塔藏段未来20、50、100年的复发概率值介于0.76%~7.36%之间,玛曲段未来20、50年的复发概率值介于2.0%~5.26%,属于低概率事件;玛曲段未来100年的复发概率值为10.82%,属于中概率事件;整个段未来100年内至少发生一次7级以上强震的联合概率可达21.87%,属于中概率事件.考虑到概率模型的不确定性,进一步对各段进行了危险性的定性分类,综合评价认为玛沁段在未来百年内发生大震的危险性较低,玛曲段和塔藏段未来百年发生大震的危险性较高.最后将本文拟合的概率密度函数与传统通用函数计算的条件概率值进行比较,发现通用的复发概率函数随着自变量t/R的增大,因变量P的反映不如本文拟合函数的敏感. 相似文献
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本文针对具有明确分段的特征断层源,从震级的不确定性出发,在弹性回跳理论的基础上提出一种随机特征滑动模型(stochastic characteristic-slip model,SCS)。在随机特征滑动模型中,不仅在参数确定过程中考虑了震级与复发间隔之间的相关性,还可以在计算未来一段时间内地震发生概率的过程中,同时得到特征地震的震级分布。本论文主要包括两个研究方向:1随机特征滑动模型及其参数的确定方法,其中,强震复发的统计规律是确定模型参数的基本依据;2随机特征滑动模型在强震发生概率计算和地震危险性分析中的应用方法研究。随机特征滑动模型及其参数的确定方法包括以下3个主要内容:(1)针对强震复发概率的计算,本文在弹性回跳理论和特征地震模型的基础上提出一种随机特征滑动模型。它是一种计算强震复发概率的模型,其目的是为地震危险性分析提供依据。在地震危险性分析过程中,要考虑强震复发的时间相关性,不仅需要给出复发周期的分布,还需要给出震级的分布。从地震矩累积的角度来考虑,两者是相关联的,不可以独立考虑。因此,在随机特征滑动模型的建立及其参数确定的过程中,均需考虑震级与复发间隔的相关性。虽然断裂上的地震矩累积率并不是恒定不变的,因此累积时间和震级的关系也存在一定的不确定性和随机性,但对于大地震特别是7.5级以上的特大地震而言,研究表明这种随机扰动并不大。此外,在当前的认识水平上,在强震发生概率的计算中,若还同时可以得到一个合理的具有平均意义的震级分布,对地震危险性分析工作具有一定的实用价值。针对断层破裂尺度数据和历史地震数据,本文分别提出了两种SCS模型参数的确定方法。若利用断层破裂尺度来确定随机特征滑动模型的参数,需要首先得到震级-破裂尺度的经验关系式;若利用历史地震或古地震数据来确定模型的参数,则需要首先确定强震复发周期的自然变异性或不确定性。(2)震级-破裂尺度的统计规律研究。本文系统搜集和整理了48个中国板内强震的发震断层的震源破裂参数和震级资料(包括面波震级与矩震级),并在此基础上利用最小二乘拟合方法得到各种震级与破裂尺度之间的经验关系式,并与前人给出的关系式进行了比较研究。同时还得到了我国面波震级与矩震级之间的经验关系式。(3)强震复发周期的统计规律研究。对于归一化无量纲地震复发间隔数据(T/Tave),本论文利用蒙特卡罗方法研究表明:不同样本量的T/Tave数据是不符合独立同分布的,而不符合独立同分布的数据不可以放在一起进行统计。针对这个问题,本研究对利用归一化无量纲地震复发间隔(T/Tave)数据进行拟合的方法做了改进,提出对非同分布的数据先进行标准化处理,然后再放在一起统计,与前人的计算方法相比,这种新的计算方法在数学上更为合理。本研究分别利用前人和自己收集的不同区域范围(环太平洋地震带、郯庐断裂带、青藏高原东北部等区域)的T/Tave数据集进行统计分析,结果表明:利用不同区域范围的数据集所得到的στ存在一定的差异,变化范围在0.30~0.42之间。但由于每个数据集中的T/Tave的数据量有限,我们也很难确定στ是否存在区域性差异,更难对这种差异性进行定量化。断层源上复发周期的自然变异性一般也会采用复发间隔变异系数α来描述。对于变异系数α的确定,除了可以由T/Tave统计得到,本研究还提出了一种通过对大量断层源上的复发间隔变异系数估值α′的统计来确定α的方法。该方法首先利用最大似然估计法计算出不同地震序列的变异系数估计值,然后再对这些变异系数的估计值进行统计分析。本文在广泛搜集的39个地震序列的基础上,利用本文给出的计算方法得到了一个通用的变异系数值α=0.34。随机特征滑动模型在强震发生概率计算和地震危险性分析中的应用方法研究包括以下4个主要内容:(1)在随机特征滑动模型的基础上,本文又提出了基于随机特征滑动模型的地震危险性分析方法。该方法中独立考虑研究区域内地震地质资料较丰富的一级破裂源,时间分布上采用随机特征滑动模型,空间分布上采用特征地震的原地复发模式,同时考虑断层几何形态的不确定性。利用本文方法得到的地震危险性计算结果具有很强的时间相关性,可以为地震灾害预防和地震备灾等工作提供数据支持。(2)利用随机特征滑动模型或其他更新模型来计算未来几十年内发生强震的条件概率时,需要给出上一次大震的离逝时间T,而很多活动断裂缺少历史大震的记载,若采用泊松模型可能会低估强震发生的概率。针对这种缺少大震离逝时间的活动断裂,本研究提出了一种以记载完整的强震平静期长度Ts为参数的条件概率计算方法。本文以东昆仑断裂带塔藏段为例,利用本文给出的条件概率计算方法得到:塔藏段未来50年发生强震的可能性为0.075 8。该计算方法不仅适用于随机特征滑动模型,还适用于其他更新模型。跟世界上大多数国家相比,我国有着相对悠久的地震史料记载,因此,该方法对于强震发生概率的估计具有重要意义。(3)由于断层破裂活动的复杂性,一个大的破裂往往不是单一的破裂,而是包含有较小量级的破裂。这些较小量级的破裂,可能分布于破裂段上的特定段落,构成次级破裂单元。对于一些较大断裂,次级破裂源上也可以发生震级较大的强震。采用泊松模型可能会低估这种中强地震的发生率,因此,在次级破裂源上强震发生概率的计算中考虑到地震复发的时间相关性也很重要。若要建立次级破裂源上的随机特征滑动模型,首先需要明确不同破裂源上的年平均地震矩累积率M0,这就要求将断层上的地震矩累积率合理地分配到不同级别的破裂源上。本文分成两种情况分别讨论次级破裂源上的地震矩累积率M0的确定方法。第一种情况是次级破裂源上历史地震(或古地震)序列比较稀少,只有地质学家给出的不同破裂源发生地震的相对发生率,针对这种情况,本研究基于地震矩平衡的原则,提出一种地震矩累积率分配方法;第二种是次级破裂源上有相对丰富的历史地震(或古地震)序列的情况,并以古地震资料较为丰富的海原断裂为例,计算了次级破裂源上的地震矩累积率和强震发生概率。(4)随机特征滑动模型的基本假定是特征断层源上的地震矩累积率在较长时期上是恒定的,这是一个理想化模型,实际上,特征断层源上的地震矩累积率不是恒定的,而是存在一定的随机扰动和不确定性,这种扰动可能由中小地震的地震矩释放以及断层间库仑应力转移等原因造成的。为了在随机特征滑动模型中考虑这种不确定性,本研究提出了一种考虑断层间相互影响的改进随机特征滑动模型。在该模型中,假定断层源上的地震矩自然累积率是恒定的,同时还要考虑中小地震释放和附近大地震库仑应力转移对该断层源上地震矩积累量的改变量。本研究选取鲜水河北西段为研究对象,反复模拟未来50年的地震序列,得到了鲜水河北西段的炉霍、倡促、道孚和乾宁各段上包括单段破裂和联合破裂在内的各种大地震事件的发生概率。 相似文献
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如何使用古地震序列数据评估数值模拟得到的长期人工地震目录的准确度是地震数值预报研究所面临的重要问题.为探讨上述问题,本文开发了计算人工地震目录与古地震序列匹配度的平均绝对误差法和余弦相似度法,并将其应用于青藏高原东北缘地区,获得了与该地区古地震序列数据匹配较好的人工地震目录.基于匹配较好的目录,本文还计算了海原断裂及香山天景山断裂发生大地震后,大地震在区域四条主要断裂的迁移概率.研究结果表明:(1)以上两种方法均可用于评估人工地震目录与古地震序列的匹配度;(2)与未进行匹配的人工地震目录的迁移概率计算结果比较,通过古地震数据匹配的人工地震目录的计算结果更优,即更接近于基于古地震数据计算的地震迁移概率;(3)当大地震在海原断裂上发生后,海原断裂再次发生大地震的概率最大,约为47%,其次是香山天景山断裂,约为23%~27%.本文对评估基于动力学数值模型产生的长期人工合成地震目录的准确度做出了调查与探索,为区域地震数值预报研究提供了参考. 相似文献
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地震危险性分析中的不确定性处理和表征,一直是核电厂厂址地震安全性评价中倍受关注的重要问题,尤其是日本福岛核事故后,无论是确定核电厂厂址的设计基准地震动,还是进行核电厂地震风险评价,都更加重视地震危险性分析中的不确定性.本文通过理论分析重点说明了衰减关系的不确定性,包括标准差和截断水平对核电厂地震安全性评价的影响,并在此基础上,通过算例和讨论说明了概率性方法截断水平的选取问题,探讨了现行确定性方法和概率性方法在截断水平选取上的差异.分析计算结果表明,在地震活动较弱的区域,概率性方法截断水平为3,确定性方法截断水平为0的现行做法是恰当的.但是,对于发震构造大震复发间隔较小的区域,为了使二者在超越概率方面协调,恰当提高确定性方法的截断水平更为合理. 相似文献
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汶川Ms8.0地震发生在青藏高原东缘NE向龙门山断裂带上,造成以映秀、北川为中心的长达300km的同震地表破裂带.初步研究认为,龙门山断裂带大震复发属于特征地震模式.本文在考虑地形差异影响下,用有限元数值模拟方法对汶川地震的大震复发周期进行研究.初步结果表明:龙门山断裂带大震复发周期为3908～4482a,该结果与古地震、断层滑动法、地震矩率、GPS数据确定等给出的结果具有较好的一致性,为龙门山断裂带的地震活动性及地震危险性研究提供重要的定量依据. 相似文献
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Uncertainties in probability of occurrence of strong earthquakes for fault sources in the Central Apennines,Italy 总被引：1，自引：1，他引：0
Aybige Akinci David Perkins Anna Maria Lombardi Roberto Basili 《Journal of Seismology》2010,14(1):95-117
Using the characteristic earthquake model, we calculate the probability of occurrence of earthquakes M
w > 5.5 for individual fault sources in the Central Apennines for the 30-year period (2007–2037). We show the effect of time-dependent
and time-independent occurrence (Brownian passage time (BPT) and Poisson) models together with uncertain slip rates and uncertain
maximum magnitudes and, hence, uncertain recurrence times. In order to reduce the large prior geological slip rate uncertainty
distribution for most faults, we obtain a posterior slip rate uncertainty distribution using a likelihood function obtained
from regional historical seismicity. We assess the uncertainty of maximum magnitude by assuming that the uncertainty in fault
width and length are described by a normal distribution with standard deviation equal to ±20% of the mean values. We then
estimate the uncertainties of the 30-year probability of occurrence of a characteristic event using a Monte Carlo procedure.
Uncertainty on each parameter is represented by the 16th and the 84th percentiles of simulated values. These percentiles bound
the range that has a 68% probability of including the real value of the parameter. We do these both for the Poisson case and
for the BPT case by varying the aperiodicity parameter (α value) using the values 0.3, 0.5, and 0.7. The Bayesian posterior slip rate uncertainties typically differ by a factor of
about 2 from the 16th to the 84th percentile. Occurrence probabilities for the next 30 years at the 84th percentile typically
range from 1% to 2% for faults where the Poisson model dominates and from 2% to 21% where one of the BPT models dominates.
The uncertainty in occurrence probability under the time-dependent hypothesis is very large, when measured by the ratio of
the 84th to the 16th percentile, frequently being as much as two orders of magnitude. On the other hand, when measured by
standard deviation, these standard deviations range from 2% to 6% for those faults whose elapsed time since previous event
is large, but always 2% or less for faults with relatively recent previous occurrence, because the probability of occurrence
is always small. 相似文献
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Ｄｉｓｃｕｓｓｉｏｎｏｎｕｎｃｅｒｔａｉｎｔｉｅｓ，ａｔｔｅｎｕａｔｉｏｎｏｆｇｒｏｕｎｄ ｍｏｔｉｏｎａｎｄａｓｅｉｓｍｉｃｄｅｓｉｇｎｃｒｉｔｅｒｉｏｎＴｉａｎ－ＺｈｏｎｇＺＨＡＮＧ（张天中）；Ｙｕｎ－ＳｈｅｎｇＭＡ（马云生）ａｎｄＸｉＳＨＵ（舒... 相似文献
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Christos Kourouklas Eleftheria Papadimitriou George Tsaklidis Vassilios Karakostas 《Journal of Seismology》2018,22(5):1225-1246
The determination of strong earthquakes’ recurrence time above a predefined magnitude, associated with specific fault segments, is an important component of seismic hazard assessment. The occurrence of these earthquakes is neither periodic nor completely random but often clustered in time. This fact in connection with their limited number, due to shortage of the available catalogs, inhibits a deterministic approach for recurrence time calculation, and for this reason, application of stochastic processes is required. In this study, recurrence time determination in the area of North Aegean Trough (NAT) is developed by the application of time-dependent stochastic models, introducing an elastic rebound motivated concept for individual fault segments located in the study area. For this purpose, all the available information on strong earthquakes (historical and instrumental) with Mw ≥ 6.5 is compiled and examined for magnitude completeness. Two possible starting dates of the catalog are assumed with the same magnitude threshold, Mw ≥ 6.5 and divided into five data sets, according to a new segmentation model for the study area. Three Brownian Passage Time (BPT) models with different levels of aperiodicity are applied and evaluated with the Anderson–Darling test for each segment in both catalog data where possible. The preferable models are then used in order to estimate the occurrence probabilities of Mw ≥ 6.5 shocks on each segment of NAT for the next 10, 20, and 30 years since 01/01/2016. Uncertainties in probability calculations are also estimated using a Monte Carlo procedure. It must be mentioned that the provided results should be treated carefully because of their dependence to the initial assumptions. Such assumptions exhibit large variability and alternative means of these may return different final results. 相似文献
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A. Lourens F. C. van Geer 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(1):237-249
In many fields of study, and certainly in hydrogeology, uncertainty propagation is a recurring subject. Usually, parametrized probability density functions (PDFs) are used to represent data uncertainty, which limits their use to particular distributions. Often, this problem is solved by Monte Carlo simulation, with the disadvantage that one needs a large number of calculations to achieve reliable results. In this paper, a method is proposed based on a piecewise linear approximation of PDFs. The uncertainty propagation with these discretized PDFs is distribution independent. The method is applied to the upscaling of transmissivity data, and carried out in two steps: the vertical upscaling of conductivity values from borehole data to aquifer scale, and the spatial interpolation of the transmissivities. The results of this first step are complete PDFs of the transmissivities at borehole locations reflecting the uncertainties of the conductivities and the layer thicknesses. The second step results in a spatially distributed transmissivity field with a complete PDF at every grid cell. We argue that the proposed method is applicable to a wide range of uncertainty propagation problems. 相似文献
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Global sensitivity analysis for a numerical model of radionuclide migration from the RRC “Kurchatov Institute” radwaste disposal site 总被引：1，自引：1，他引：0
E. Volkova B. Iooss F. Van Dorpe 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):17-31
Today, in different countries, there exist sites with contaminated groundwater formed as a result of inappropriate handling
or disposal of hazardous materials or wastes. Numerical modeling of such sites is an important tool for a correct prediction
of contamination plume spreading and an assessment of environmental risks associated with the site. Many uncertainties are
associated with a part of the parameters and the initial conditions of such environmental numerical models. Statistical techniques
are useful to deal with these uncertainties. This paper describes the methods of uncertainty propagation and global sensitivity
analysis that are applied to a numerical model of radionuclide migration in a sandy aquifer in the area of the RRC “Kurchatov
Institute” radwaste disposal site in Moscow, Russia. We consider 20 uncertain input parameters of the model and 20 output
variables (contaminant concentration in the observation wells predicted by the model for the end of 2010). Monte Carlo simulations
allow calculating uncertainty in the output values and analyzing the linearity and the monotony of the relations between input
and output variables. For the non monotonic relations, sensitivity analyses are classically done with the Sobol sensitivity
indices. The originality of this study is the use of modern surrogate models (called response surfaces), the boosting regression
trees, constructed for each output variable, to calculate the Sobol indices by the Monte Carlo method. It is thus shown that
the most influential parameters of the model are distribution coefficients and infiltration rate in the zone of strong pipe
leaks on the site. Improvement of these parameters would considerably reduce the model prediction uncertainty. 相似文献
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The estimation of site intensity occurrence probabilities in low seismic activity regions has been studied from different points of view. However, no method has been definitively established because several problems arise when macroseismic historical data are incomplete and the active zones are not well determined. The purpose of this paper is to present a method that estimates site occurrence probabilities and at the same time measures the uncertainties inherent in these probabilities in low activity regions. The region to be studied is divided into very broad seismic zones. An exponential intensity probability law is adjusted for each zone and the degree of uncertainty in the assumed incompleteness of the catalogue is evaluated for each intensity. These probabilities are used to establish what may be termed ‘prior site occurrence models’. A Bayesian method is used to improve ‘prior models’ and to obtain the ‘posterior site occurrence models’. Epicentre locations are used to recover spatial information lost in the prior broad zoning. This Bayesian correction permits the use of specific attenuation for different events and may take into account, by means of conservative criteria, epicentre location errors. Following Bayesian methods, probabilities are assumed to be random variables and their distribution may be used to estimate the degree of uncertainty arising from (a) the statistical variance of estimators, (b) catalogue incompleteness and (c) mismatch of data to prior assumptions such as Poisson distribution for events and exponential distribution for intensities. The results are maps of probability and uncertainty for each intensity. These maps exhibit better spatial definition than those obtained by means of simple, broad zones. Some results for Catalonia (NE of Iberian Peninsula) are shown. 相似文献