以空间光滑的地震活动性模型为空间分布函数的地震危险性分析方法

根据华北地区的地震目录,建立了4个空间光滑的地震活动性模型,并以这些模型为空间分布函数,将华北地震区每个地震带的地震年发生率分配到空间格点中,计算这一地区的地震危险性．结果表明,采用仪器记录地震计算得到的地震活动性模型和地震危险性结果能够反映华北地区现今的地震活动水平和地震危险性水平,符合人们对现今华北地区地震危险性的认识;采用历史破坏性地震（Mge;4.7）计算的地震活动性模型和地震危险性结果,较好地反映了华北地区中强地震活动区的地震危险性水平;以地震应变计算地震活动率,并根据点椭圆模型和线椭圆模型计算得到的地震活动性模型,能够较好地反映大地震的活动水平和空间构造特征．将根据4个模型计算得到的50年超越概率10%峰值加速度（PGA）分布加权平均,得到综合的华北地区PGA分布,并将该PGA分布与根据《中国地震动参数区划图》中综合潜源方案计算得到的50年超越概率10%的PGA分布做了比较,发现二者无本质差别,均能反映华北地震区的地震危险性水平．当然,二者也具有一定的差异:前者计算得到的符合PGAge;100 cm/s2条件的区域面积明显要比后者的大,而符合PGAge;250 cm/s2条件的区域面积则比后者的要小. 这主要是由于潜在震源区类型和空间分布函数不同造成的．      

湖南地区分布式地震活动性模型在PSHA中的应用研究

本文采用了空间光滑地震活动性模型,该模型无需潜在震源区划分,同时发展了概率地震危险性分析新方法。根据三种地震目录资料建立了三种地震活动性模型,利用高斯光滑函数获得了湖南区域内的比值分布特征,使用了两种典型的衰减模型,计算了50年内超越概率10％的地震动峰值加速度（PGA）分布。其分析结果显示PGA分布特征与中国地震动参数区划图大体一致,部分区域PGA提高,PGA达0．05g的区域显著扩大,其中包括邵阳、湘潭、吉首、怀化等重要城市,而这种PGA分布特征与该地区地震活动性特征是一致的。概率危险性曲线的结果表明常德等地区的潜在地震危险性比湖南区域内其他城市高。表明此模型用于地震危险性计算中是简便易行的,且具有较高的精度。尤其对于地质和地震构造信息缺乏的弱震区和中强震区,该方法作为替代方法并有着广泛的应用价值。     

与特征断层结合的地震活动空间光滑模型在衡水市活断层地震危险性评价中的应用

在衡水市活断层地震危险性评价中,应用研究区域的地震活动性数据建立恰当的分布式地震活动性空间光滑模型,并结合断层对周边地震危险性的影响,计算前磨头断裂和衡水断裂在不同超越概率下上限震级分别为6.5、6.0级的区域基岩峰值加速度。研究发现,研究区域内50年超越概率为63%的基岩峰值加速度略有增加;50年超越概率为10%、5%的基岩峰值加速度在断层附近有所增加。研究表明在较低超越概率的情况下,断层周围如深州市、冀州市和衡水市辖区的地震危险性大于其他地区;利用仪器记录资料得到的地震活动性模型并结合断层资料计算出的地震危险性结果能够反映衡水地区现今的地震活动水平和危险性水平。     

基于华北区域地震活动性分布的地震危险性评价模型

采用了分布式地震活动性模型. 该模型无需潜在震源区划分,同时简化了地震危险性概率分析方法. 根据破坏性地震目录建立了3个地震活动性模型,利用高斯光滑函数获得了华北区域内的a值分布特征,使用3种典型的衰减模型,分别计算了50年内超越概率10%, 5%和2%的地震动峰值加速度分布. 其分析结果显示了峰值加速度分布特征与我国第四代区划图大体一致,特定地震活动区（太原、 石家庄等地区）的峰值加速度略高于第四代区划图的结果,而这种峰值加速度分布特征与该地区较高的地震活动性特征是一致的. 概率危险性曲线结果表明,唐山、太原和北京等地区的潜在地震危险性比华北区域内其它城市高.      

蒙古国地区背景地震危险性分析

根据蒙古国及其周边地区的背景地震目录（M≤6.0）,采用空间光滑地震活动性的方法研究了蒙古国地区背景地震危险性水平,给出了蒙古国50年超越概率10 %的峰值加速度分布图。结果表明蒙古国大部分地区背景地震危险性水平为0.05 g,部分地区高达0.1~0.15 g,意味着蒙古国地区背景地震危险性高,在进行地震危险性分析和地震区划时应充分考虑背景地震活动,采用不同起始震级的地震活动性模型计算得到的地震危险性水平具有较大的空间差异,因此在采用空间光滑地震活动性模型进行地震危险性分析时应采用多个模型加权平均的方法,平衡地震频度和地震震级的影响。     

无震级上限累计b值及其回归确定方法

本文指出,目前地震危险性分析中广泛使用的用线性回归求取累计b值,然后用震级累计分布函数或概率密度函数确定地震重现关系的传统做法,理论上是错误的,实际上总是系统地高估b值,低估高震级部分的地震频次.研究区域本身的实际b值越小,回归时使用资料的震级范围越小,震级分档间隔越小,则上述系统编差越大.故对于震级上限较低的地区,若仅用历史地震线性回归求b值,由于能控制的震级下限较高,资料震级范围较小,回归所得的b值可明显偏高,从而导致地震危险性分析的系统编差.本文提出用无震级上限累计b值取代传统的有震级上限累计b值,并给出了回归求取无震级上限累计b值的实际方法.      

东北地震区小震资料完整性分析及其对地震活动性参数的影响研究

以东北地震区为例,基于G-R关系的震级-频度分布原理,研究了东北地震区最小完整性震级MC的时间分布特征和各时段的空间分布特征,统计了研究区内的地震活动性参数,探讨了小震资料完整性分析对地震活动性参数和地震危险性计算结果的影响。研究表明：对区域小震资料进行完整性分析,可以在低地震活动地区获得较准确的地震活动性参数,更好地反映了该区未来的地震活动趋势。本文的研究方法和结论可供地震资料完整性分析和地震活动性分析时参考。     

东北地震区小震资料完整性分析及其对地震活动性参数的影响研究

以东北地震区为例,基于G-R关系的震级·频度分布原理,研究了东北地震区最小完整性震级MC的时间分布特征和各时段的空间分布特征,统计了研究区内的地震活动性参数,探讨了小震资料完整性分析对地震活动性参数和地震危险性计算结果的影响.研究表明,对区域小震资料进行完整性分析,可以在低水平地震活动地区获得较准确的地震活动性参数,更好地反映了该区未来的地震活动趋势.本文的研究方法和结论可供地震资料完整性分析和地震活动性分析时参考.     

地震活动性参数的数理基础、相关性及筛选

从各种地震活动性参数的解析表达式入手,分析了诸参数对地震活动强度和频度的依赖性和相关性．一类为区域地震活动性统计参数,文中共分析了17个;另一类为地震活动分布类参数,即时间、空间、震级分布类参数．分布类参数的存在基础及合理性在于其分布模型的适用性．文中对地震时间、空间、震级的自然概率分布、泊松分布、威布尔（Weibull）分布和分形的解析式进行了形式类比和分析,并以实例说明．对余震序列衰减系数P值、H值、震群序列U值、F值和熵值K也作了初步评价,并给出了评价地震活动性参数之间相关性的另一途径,即分析计算输出时序曲线之间的关联度．文中推荐相似性关联度RY1Y2和相对变化斜率关联度GY1Y2作判定量．最后就众多地震活动性参量的筛选与应用提出了初步看法．      

空间光滑活动模型在东部海域地震危险性评价中的应用

以中国东部近海海域(25～41°N,117～126°E)为研究区域,基于区域地震构造背景和地震活跃水平等资料划分地震构造单元,依次采用基于地震目录的圆形高斯光滑模型和断层导向性的椭圆光滑模型的地震活动参数评价方法,计算各网格点的地震发生率.并利用网格源的地震危险性概率评价方法,由不同输入地震目录得到该区域50年超越概率10％的加速度峰值区划结果.     

基于特大地震发生率的川滇地区地震危险性预测新模型

川滇地区是我国地震危险性较高的地区之一.本文基于对特大强震的风险性考虑,使用全球地震模型OpenQuake软件,建立了川滇地区地震危险性预测新模型.首先根据构造特征划分多个震源分区,并整理出这些震源分区内断层活动特征与滑动速率;基于震源分区和断层模型,使用GPS应变率转换成的锥形古登堡-里克特关系作为整个区域的地震积累率,并允许超过历史最大震级的特大地震的出现,结合活动断层滑动速率所积累的地震发生率,给出震源分区内断层地震源和背景地震源的地震发生率的比率分配关系;在活动断层分段上,保留了大型断裂或其主要部分,没有根据小的阶区来对断层进行详细分段,以便分配特大地震发生率;并使用地震率平滑方法分配背景地震发生率.最后在OpenQuake中加入地震动预测方程,计算出了川滇地区的PGA分布图,为区域地震危险性提供科学依据.     

中强地震活动区地震年平均发生率确定方法的比较

Two kinds of methods for determining seismic parameters are presented,that is,the potential seismic source zoning method and grid-spatially smoothing method. The Gaussian smoothing method and the modified Gaussian smoothing method are described in detail, and a comprehensive analysis of the advantages and disadvantages of these methods is made. Then,we take central China as the study region,and use the Gaussian smoothing method and potential seismic source zoning method to build seismic models to calculate the mean annual seismic rate. Seismic hazard is calculated using the probabilistic seismic hazard analysis method to construct the ground motion acceleration zoning maps. The differences between the maps and these models are discussed and the causes are investigated. The results show that the spatial smoothing method is suitable for estimating the seismic hazard over the moderate and low seismicity regions or the hazard caused by background seismicity; while the potential seismic source zoning method is suitable for estimating the seismic hazard in well-defined seismotectonics. Combining the spatial smoothing method and the potential seismic source zoning method with an integrated account of the seismicity and known seismotectonics is a feasible approach to estimate the seismic hazard in moderate and low seismicity regions.     

Seismic hazard estimation based on the distributed seismicity in northern China

In this paper, we have proposed an alternative seismic hazard modeling by using distributed seismicites. The distributed seismicity model does not need delineation of seismic source zones, and simplify the methodology of probabilistic seismic hazard analysis. Based on the devastating earthquake catalogue, we established three seismi- city model, derived the distribution of a-value in northern China by using Gaussian smoothing function, and cal-culated peak ground acceleration distributions for this area with 2%, 5% and 10% probability of exceedance in a 50-year period by using three attenuation models, respectively. In general, the peak ground motion distribution patterns are consistent with current seismic hazard map of China, but in some specific seismic zones which in-clude Shanxi Province and Shijiazhuang areas, our results indicated a little bit higher peak ground motions and zonation characters which are in agreement with seismicity distribution patterns in these areas. The hazard curves have been developed for Beijing, Tianjin, Taiyuan, Tangshan, and Ji’nan, the metropolitan cities in the northern China. The results showed that Tangshan, Taiyuan, Beijing has a higher seismic hazard than that of other cities mentioned above.     

用空间光滑方法评估弱地震活动区的地震活动性参数

本文以长江中游地震带为研究区域,该区地震活动比较弱,发震构造不清晰,但人口、经济分布集中,中小地震往往会造成强烈的社会影响。自有记载以来,共记录到122次Ms≥4．7级的地震,最大的地震为1631年常德63/4级地震,在这样的区域进行地震危险性分析,依据构造特征和地震活动进行潜源划分的方法会带来较大的不确定性,为了更合理地评价其危险性,本文试图先在研究区内划分活动水平相当的等b值区域,然后利用空间光滑法计算各区的地震年平均发生率分布。结果显示,各分区内年平均发生率存在较大差异,年发生率分布图与现代和历史地震震中分布格局基本一致,为潜源区划分提供了一种量化的空间参考数据。     

A Probabilistic Assessment of Earthquake Hazard Parameters in NW Himalaya and the Adjoining Regions

The maximum likelihood estimation method is applied to study the geographical distribution of earthquake hazard parameters and seismicity in 28 seismogenic source zones of NW Himalaya and the adjoining regions. For this purpose, we have prepared a reliable, homogeneous and complete earthquake catalogue during the period 1500–2010. The technique used here allows the data to contain either historical or instrumental era or even a combination of the both. In this study, the earthquake hazard parameters, which include maximum regional magnitude (M _max), mean seismic activity rate (λ), the parameter b (or β?=?b/log e) of Gutenberg–Richter (G–R) frequency-magnitude relationship, the return periods of earthquakes with a certain threshold magnitude along with their probabilities of occurrences have been calculated using only instrumental earthquake data during the period 1900–2010. The uncertainties in magnitude have been also taken into consideration during the calculation of hazard parameters. The earthquake hazard in the whole NW Himalaya region has been calculated in 28 seismogenic source zones delineated on the basis of seismicity level, tectonics and focal mechanism. The annual probability of exceedance of earthquake (activity rate) of certain magnitude is also calculated for all seismogenic source zones. The obtained earthquake hazard parameters were geographically distributed in all 28 seismogenic source zones to analyze the spatial variation of localized seismicity parameters. It is observed that seismic hazard level is high in Quetta-Kirthar-Sulaiman region in Pakistan, Hindukush-Pamir Himalaya region and Uttarkashi-Chamoli region in Himalayan Frontal Thrust belt. The source zones that are expected to have maximum regional magnitude (M _max) of more than 8.0 are Quetta, southern Pamir, Caucasus and Kashmir-Himanchal Pradesh which have experienced such magnitude of earthquakes in the past. It is observed that seismic hazard level varies spatially from one zone to another which suggests that the examined regions have high crustal heterogeneity and seismotectonic complexity.     

Time-dependent seismic hazard analysis for the Greater Tehran and surrounding areas

This study presents a time-dependent approach for seismic hazard in Tehran and surrounding areas. Hazard is evaluated by combining background seismic activity, and larger earthquakes may emanate from fault segments. Using available historical and paleoseismological data or empirical relation, the recurrence time and maximum magnitude of characteristic earthquakes for the major faults have been explored. The Brownian passage time (BPT) distribution has been used to calculate equivalent fictitious seismicity rate for major faults in the region. To include ground motion uncertainty, a logic tree and five ground motion prediction equations have been selected based on their applicability in the region. Finally, hazard maps have been presented.     

K-means cluster analysis and seismicity partitioning for Pakistan

Pakistan and the western Himalaya is a region of high seismic activity located at the triple junction between the Arabian, Eurasian and Indian plates. Four devastating earthquakes have resulted in significant numbers of fatalities in Pakistan and the surrounding region in the past century (Quetta, 1935; Makran, 1945; Pattan, 1974 and the recent 2005 Kashmir earthquake). It is therefore necessary to develop an understanding of the spatial distribution of seismicity and the potential seismogenic sources across the region. This forms an important basis for the calculation of seismic hazard; a crucial input in seismic design codes needed to begin to effectively mitigate the high earthquake risk in Pakistan. The development of seismogenic source zones for seismic hazard analysis is driven by both geological and seismotectonic inputs. Despite the many developments in seismic hazard in recent decades, the manner in which seismotectonic information feeds the definition of the seismic source can, in many parts of the world including Pakistan and the surrounding regions, remain a subjective process driven primarily by expert judgment. Whilst much research is ongoing to map and characterise active faults in Pakistan, knowledge of the seismogenic properties of the active faults is still incomplete in much of the region. Consequently, seismicity, both historical and instrumental, remains a primary guide to the seismogenic sources of Pakistan. This study utilises a cluster analysis approach for the purposes of identifying spatial differences in seismicity, which can be utilised to form a basis for delineating seismogenic source regions. An effort is made to examine seismicity partitioning for Pakistan with respect to earthquake database, seismic cluster analysis and seismic partitions in a seismic hazard context. A magnitude homogenous earthquake catalogue has been compiled using various available earthquake data. The earthquake catalogue covers a time span from 1930 to 2007 and an area from 23.00° to 39.00°N and 59.00° to 80.00°E. A threshold magnitude of 5.2 is considered for K-means cluster analysis. The current study uses the traditional metrics of cluster quality, in addition to a seismic hazard contextual metric to attempt to constrain the preferred number of clusters found in the data. The spatial distribution of earthquakes from the catalogue was used to define the seismic clusters for Pakistan, which can be used further in the process of defining seismogenic sources and corresponding earthquake recurrence models for estimates of seismic hazard and risk in Pakistan. Consideration of the different approaches to cluster validation in a seismic hazard context suggests that Pakistan may be divided into K?=?19 seismic clusters, including some portions of the neighbouring countries of Afghanistan, Tajikistan and India.