After an earthquake, the rapid assessment of economic losses enables government agencies to accurately evaluate the severity of the disaster, thereby initiating the appropriate level of emergency response in a timely manner. By analysing the scope of the affected area and the scale of property losses, rescue resources can be rationally allocated to the most severely impacted regions, thereby effectively mitigating the losses caused by the disaster, while securing valuable time for emergency rescue and disaster relief efforts. To address the challenges in predicting earthquake economic losses, including numerous influencing factors, high computational demands, and complex model training, this study develops a Support Vector Machine (SVM) model optimized by Principal Component Analysis (PCA) and Genetic Algorithm (GA). PCA reduces the dimensionality of economic loss-related factors by eliminating redundancy, selecting principal components with high contribution rates as SVM inputs, with economic loss as the output. GA optimizes SVM performance parameters to establish the PCA-GA-SVM model. Testing on sample data shows it outperforms GA-SVM, GA-BP (Genetic Algorithm-optimized Back-Propagation neural network), and PCA-GA-BP models, achieving an average prediction accuracy of 95.94%, with a mean absolute percentage error (MADE) of 4.0522%, normalized root mean square error (NRMSE) of 2.361%, and coefficient of determination (R2) of 0.9994. These results underscore the model's accuracy and generalization ability, making it an effective tool for rapid, reliable earthquake loss prediction.

Since the occurrence of the Tangshan MS7.8 earthquake, Guye—Luanxian area has been a frequently occurrence of aftershocks. The fault and geological structure are very complex in Guye—Luanxian area. What are the differences in the fragmentation degree of these faults? The problems are concerned by seismologists. To answer these questions, by using the waveform records of the mobile seismic network densely deployed in the Guye—Luanxian area from August 2020 to July 2021, we study the anisotropy of the upper crust in Guye—Luanxian area according to the principle of shear wave splitting. The following conclusions are obtained: (1) The average polarization direction of fast shear wave in Guye—Luanxian area is NE86.2°±27.8°, the average time delay of slow shear wave in this area is 2.37±1.25 ms·km-1. The first dominant polarization direction of fast shear wave is ENE, which is consistent with the direction of principal compressive stress of regional background, the second dominant direction is NE direction, which reveals the tectonic significance that the faults in this area are mainly developed in NE direction. (2) The polarization direction of fast shear wave near the Tangshan fault zone shows the second dominant direction in NE direction, which is consistent with the fault strike. The time delay of slow shear wave of stations near the fault is higher, and the difference of time delay in stations is smaller, which indicates that the regional anisotropy is stronger, and the fragmentation degree along the NE direction is stronger and homogeneity. (3) The polarization direction of fast shear wave near Luanxian—Leting fault and Lulong fault shows complexity, indicating that the intersection of two active faults produces a complex crustal fracture structure in the crust. The time delay of slow shear wave in stations near the fault is higher, and the time delay difference of each station is larger, which indicates that the regional anisotropy and fragmentation degree are stronger, and the fragmentation is heterogeneity. (4) The polarization direction of fast shear wave at stations near the Fengtai—Yejituo fault and Zhenzizhen fault is consistent with the direction of regional principal compressive stress. The slow shear wave time delay of stations near the fault is the smallest, indicating that the Fengtai—Yejituo fault and Zhenzizhen fault have no influence on the polarization direction of fast shear wave at nearby stations, regional anisotropy and fragmentation degree are weaker, and may be indicating closure of fracture internal cracks in the faults. Moreover, we also discussed whether the tip effect on the Tangshan fault after the 1976 Tangshan MS7.8 earthquake has an impact on the stress field in the northern segment of the Tangshan fault zone. The results of this study not only reflect the relationship between the complexity of fault distribution and crustal anisotropy, but also reveal the difference of crustal anisotropy on faults with different degrees of fragmentation.

In recent years, China has experienced frequent catastrophic earthquakes, causing huge casualties. If the death toll can be quickly predicted after a disaster, then relief supplies can be delivered in a timely and reasonable manner, and the death toll and property losses can be minimized. Therefore, rapid and effective prediction of earthquake deaths plays a key role in guiding post-earthquake emergency rescue. However, there are many factors affecting the number of deaths in an earthquake. Aimed at this issue, a prediction model for earthquake deaths based on extreme learning machine (ELM) optimized by principal component analysis (PCA) and beetle antennae search (BAS) algorithm has been proposed in this study. Firstly, this study selected sample data of destructive earthquakes in mainland China in the past 50 years, then PCA was used to reduce the dimensionality of the factors affecting earthquake deaths, the principal components with lower contribution rates were removed, and the principal components with higher contribution rates were used as the input variables of ELM. Meanwhile, the earthquake deaths were used as the output variable, and the connection weights and thresholds of ELM was optimized using BAS. Finally, the prediction model for earthquake deaths based on PCA-BAS-ELM was established. The established model was used to predict the test samples. The results showed that the prediction results of PCA-BAS-ELM model had a higher fit with the actual values, and its mean square error, mean absolute percentage error and root mean square error were 2.433, 2.756% and 5.443, respectively, which suggested higher prediction accuracy.

Based on comprehensively analyse on the seismic risk of Yanqing-Huailai basin, the potential seismogenic fault is Qujiayao-Fangjiachong segment of the northern margin fault of Yanqing-Fanshan basin is determined, with a probable magnitude of 7.0.Based on the 3D structural model of Yanqing-Huailai basin with thick surface sediments, two rupture modes are set to simulate the ground motion of the scenario earthquake for studying the amplification effect of the basin structure.It is found that the shallow sedimentary structure of the basin has a more significant impact on the ground motion in the shorter period.The larger amplification factor usually corresponds to the larger quaternary thickness, and the maximum amplification factor is located in Yanqing Basin.

利用西藏地震台网记录到的2017年11月18日西藏米林6.9级地震及其余震序列资料,研究此次地震的发震机制断层.双差定位结果显示,余震沿着主震的NW和SE方向往两侧扩展分布,震源深度主要集中在2～12 km,同时从短轴剖面上地震分布推断,此次米林地震的发震断层倾角约为45°.对ML3.5以上的余震采用CAP方法进行波形拟合震源机制反演,其结果显示,此次米林地震序列震源错动类型以逆冲和走滑为主,比较符合该区域的构造动力环境.应力场反演结果显示,米林地震序列主压应力轴(S1轴)方向为NNE-NS向,主张应力轴(S3轴)方向为SEE-SE向;反映的断层错动方式为逆冲兼走滑类型.地震余震序列展布以及震源机制分布显示断层走向和断层特性与帕隆—旁辛断裂的特征较为吻合,推测米林地震的发震断裂为帕隆—旁辛断裂.

基于云南大理亚失稳台网的震相到时,采用双差层析成像方法对2021年云南漾濞6.4级地震震源区进行P波速度结构反演,进而分析漾濞地震的发震构造.射线分布和棋盘测试都显示亚失稳台网对漾濞地震震源区覆盖得很好,在2～12 km的深度范围内,随着深度增加,P波的速度模型分辨效果越来越好,震源区内分辨率可以达到0.1°×0.1°.反演获得的震源区速度结构具有明显的横向不均匀性,漾濞6.4级地震发生在高低速交界附近的高速体内,地震序列主要沿NW-SE向展布,走向基本平行于维西-乔后断裂.

扫描2022年芦山MS 6.1地震和马尔康MS 6.0地震震前不同震级档调制比图像,同时给出震前b值分布图像,结果表明:2次6级地震前震中附近不同震级档调制比均出现高值异常.最小扫描震级越高,调制比扫描结果越稳定清晰,调制比高值异常出现时间越晚,同时最小扫描震级越高,异常范围、幅度也越大,异常与震中位置和发震时间关联性越强.调制比异常的幅度和范围与应力水平有关,2次地震震前震中附近均出现低b值区域,且马尔康MS 6.0地震震中附近调制比异常和低b值异常都比芦山MS 6.1地震更突出,推断马尔康MS 6.0地震孕震区应力水平可能高于芦山MS 6.1地震孕震区应力水平.

房屋建筑区是组成居民地的重要设施,是人类生产生活居住的重要空间,同时也是破坏性地震发生后造成人员伤亡和财产损失的直接载体,震后对建筑物的快速评估,对指导抗震救灾、预估地震损失具有重要的意义,因此房屋建筑成为了遥感影像识别提取的焦点.本文通过(1)下载包含房屋建筑区的天地图2D平面地图;(2)采集房屋建筑区RGB色彩值,对天地图数据进行重分类;(3)按照房屋建筑区分类值,提取相关数据,以上三个步骤得到了2D平面地图的房屋建筑区数据.以遥感影像数据为基础对张家口地区房屋建筑区的提取结果进行验证,证实了提取方法的有效性和精确性.在数据应用方面,房屋建筑区数据可与三维场景建模相结合,为应急指挥者快速了解震中区域的地形地貌、居民地分布情况、交通、断裂分布情况及潜在地质灾害隐患点提供直观的数据支撑.

2020年2月18日山东济南长清发生M4.1(Ms 4.1)地震,基于中国地震台网中心的观测报告,使用双差定位法对济南长清地震序列进行重定位,利用重定位后的地震参数拟合了断层面的走向及倾角.利用P波初动方法求取了 5个震源机制解,并反演了震源区的局部应力场,根据局部应力场和断层面参数计算了滑动角.得到以下初步结论:长清地震序列从SE向NW延伸、倾向NE;断层面拟合得到断层面走向NW(320.5°),倾角接近垂直(84.8°),滑动角为15.7°,本文推断发震断层为走向NW、倾角近垂直且具有左旋走滑性质的隐伏次级断裂.主震震源机制解是正走滑型地震,其节面Ⅰ走向111°、倾角65°、滑动角-45°,5个震源机制解按时间顺序呈正断走滑型与走滑型地震相互交替出现.震源区局部应力场呈正断兼少量走滑的应力机制,与山东背景应力场不同.本文认为在太平洋板块自东向西推挤作用背景下,鲁中隆起与其西北凹陷区垂向运动差异,是济南长清发生地震的根本原因.

The tectonic stress field is essential for understanding the regional dynamic tectonics and deformation mechanism. To obtain the accurate tectonic stress field in Yunnan and its nearby regions, and to analyze where there are discrepancies in stress fields in previous studies, we collect the existing focal mechanism solutions and invert the focal mechanism solutions of earthquakes that occurred in recent years, using the gCAP method. In total, 1302 focal mechanism solutions were obtained within the study area. Then, we propose a method for quantitatively setting the grid size for the regional stress field inversion, and remove the grids with different stress field results between damped and undamped inversions. Based on a large number of focal mechanism solution data, the accurate stress field in study area is obtained, summarized as follows. First, the types of focal mechanism solutions in Yunnan and its adjacent areas are mainly strike-slip, which is distributed throughout the study area. Thrust with strike-slip and thrust earthquakes are mainly distributed in the border area between Yunnan and Sichuan Basin, while normal fault and normal with strike-slip earthquakes are less, and mainly distributed in western and northwestern Yunnan. To some extent, the diversity of focal mechanism solutions in the study area reflects the spatial differences of tectonic activities and stress fields. Second, the overall stress field in Yunnan shows that the azimuth trajectory of the principal compressive stress axis is distributed in a fan shape with the northwest corner as the center, and the azimuth trajectory of the principal extensional stress axis is distributed in an arc shape with the northwest corner as the center, which reflects that the migration of materials from the Tibeten Plateau to the southeast has a controlling effect on the stress field in the study area. Third, the stress field in the study area is mainly strike-slip faulting, with thrust and normal stress regime existing in a few areas, and the results are generally consistent with the previous research results. Finally, the crustal stress field in Tengchong volcanic area is strike-slip faulting, which is consistent with the strike-slip-dominated faults in Tengchong area. To some extent, it implies that the current volcanic activity has little influence on shallow crustal stress field.

通过计算1976年唐山7.8级地震、滦县7.1级地震、宁河6.9级地震产生的库仑破裂应力,得到这3次地震在唐山地区的库仑破裂应力演变过程;将研究区域(39.0°～40.5°N,117.0°～119.0°E)1979年以来的1.0级及以上地震双差重定位结果同库仑破裂应力分布对比分析,认为历史大震对现今地震的调制作用变弱;通过分析2002—2020年部分中强地震受库仑破裂应力作用情况,认为历史大震可能对蓟运河断裂附近区域触发作用较明显,而对唐山断裂附近区域的触发作用不明显,2020年7月12日古冶5.1级地震、2021年4月16日滦州4.3级地震受到了历史大震的抑制作用.

地震的发生与地壳应力场有密切的联系,地震是应力积累到一定程度使得断层破裂的结果,而大地震之前的应力场变化与大地震的孕育和发生有着最直接的联系.为理解地震活动较低的2008年汶川地震之前的构造应力场与该地震发生的关系,文中采用能综合利用小地震P波初动信息的综合震源机制方法求解汶川地震之前的应力场.首先采用2001年1月—2008年5月12日汶川8.0级地震前的P波初动符号求解了四川地区大量中小地震的综合震源机制,发现综合震源机制的压轴和张轴方向以龙门山断裂带、鲜水河断裂带和华蓥山断裂带为界.龙门山断裂带以西至龙日坝断裂的川北地块压轴近SEE-NWW向,张轴近垂直,致使该地块在龙门山断裂带上表现为以逆冲为主兼右旋走滑的运动方式,有益于汶川地震孕育过程中的应力积累.鲜水河断裂南段及附近地区的震源力学机制呈现为走滑模式,完美地解释了鲜水河断裂上一系列走滑大地震的滑动行为.华蓥山断裂南东段则呈现为逆冲模式,与前人提出的该地区的古应力模式一致.为研究汶川地震之前地壳应力场随时间的变化,文中还分时段计算了汶川地震前综合震源机制旋转到汶川地震震源机制的旋转角变化,发现采用不同作者和机构得到的汶川地震震源机制均可得到旋转角在震前1年达到最小值的结论,且低于旋转角的标准差.以上结果表明,汶川地震之前出现了应力方向趋于促使主震破裂方向的现象.

基于第五代地震动区划图,利用PyQt5设计了一款开源可视化的地震动参数计算软件.软件主要包含2个功能:①根据Ⅱ类场地基本地震动峰值加速度和加速度谱特征周期值计算其他各类场地、各级地震动峰值加速度值和加速度谱特征周期值;②根据多场点峰值加速度和场地类型进行场地调整,并对调整后的结果进行分区.该软件在地震安全性评价工作和全国地震风险普查工作的应用中有效提高了工作效率,以期为同类工作提供使用、借鉴和参考.

2020年2月3日,四川省成都市青白江区发生MS5.1地震,震中位于川西盆地的龙泉山断裂带北段.龙泉山断裂带北段存在东、西2支断层,2条断层与震中的距离相近.目前,此次地震的发震断层、地震成因与动力来源尚不清楚.文中尝试采用多元约束方法,将地球物理学、地震学、大地测量学理论和构造地质学与断层相关褶皱理论相结合,对青白江MS5.1地震进行了综合研究.地震反射剖面揭示了龙泉山背斜北段的基本构造特征,为发育在4～6km深度的中下三叠统膏盐滑脱层之上的逆冲断层和反冲断层的组合,且具有突破式断层传播褶皱特征;研究中采用CAP波形反演法得到了此次地震的震源矩心深度和震源机制解,其中震源矩心深度为5km,表明地震与浅层断层活动有关;震源机制解的节面Ⅰ为18°/32°/100°,节面Ⅱ为186°/59°/84°;通过Hyposat定位法和双差定位法对青白江地震序列进行重定位,得到主震的震中位置为(30.73°N,104.48°E),定位的61次余震主要集中分布于龙泉山断裂带北段东支附近,且具有较好的关联性,东支断层的产状与震源机制解节面Ⅰ一致,为倾向NW的低角度逆断层.研究提取了震中附近的InSAR同震形变场,同震形变量最大可达4cm;地震造成的形变在震中西北部为隆起,东南部为凹陷,且最大凹陷部位位于震中与龙泉山东支断裂之间,符合东支断裂逆冲的活动特征.文中通过多学科交叉的多元约束,对2020年青白江MS5.1地震的发震构造进行了详细分析,厘定了发震断层并探讨了可能的地震动力学背景,可为龙泉山地区的断层活动性分析和地震风险评估提供一定的科学依据.

以山前隐伏断裂——滦县西断裂探测为例,提出以浅层地震反射波法为主,结合高密度电阻率法加以佐证的综合地球物理勘探方法组合模式,结果揭示滦县西断裂在剖面上显示高倾角正断层,结合跨断层钻孔联合地质剖面探测验证结果,通过对滦县西断裂的探测证明该套地球物理方法应用于山前隐伏断裂的探测效果良好,为城市国土空间规划、重大工程建设、抗震设防等提供了必要的地球物理依据和地质保障.

1 研究背景 2010年8月金钟水库蓄水活动开始之后,福建仙游地区地震活动性增强,小震频发.截至2014年12月31日,共记录地震3471次,其中4级以上地震5次,3级以上地震20次,2级以上地震101次,最大地震为2013年9月4日4.8级地震.

1976年宁河MS6.9地震,是天津地区有历史记载以来的最大地震,也是唐山地震的第二大余震,对当地造成了较大的人员伤亡和经济损失.虽已过去40多年,但是宁河地震发震构造的研究基础还比较薄弱,尚未形成清晰统一的认识.华北地区人口稠密,经济发达,对宁河地震的发震构造展开研究,对该地区的中长期地震预测、重要工程的抗震设防及唐山地震的破裂机理研究等具有重要的实用价值和科学意义.通过地质地貌调查、小地震精定位及钻孔联合探测等并结合前人的烈度调查结果,获得以下主要认识:1)1976年宁河6.9级地震的发震构造不大可能是NW向的蓟运河断裂,而更可能是NE向的构造,即付庄-高庄断裂.宁河地震NE向的发震构造与华北的区域地震构造环境相统一,即绝大多数强震发生在NE-NNE向断裂上;2)付庄-高庄断裂与唐山断裂组成了一个右旋左阶式的"挤压型阶区",可以很好地解释唐山主震时断裂西南部逆冲子事件的出现;3)付庄-高庄断裂是天津地区已知的唯一出露于地表的全新世活动断裂,其作为一个潜在的、具有7级左右发震能力的危险源,对滨海新区的经济建设具有十分重要的意义,建议对该断裂开展进一步的研究.

滦县西断裂是1976年7月28日滦县MS7.1级地震的发震构造,对该断层的第四纪活动性研究有助于了解断层的演化和历史地震活动性.但有关该断裂的第四纪活动性研究至今尚无定论.本文通过浅层地震勘探和钻孔联合剖面相结合的方法,针对滦县西断裂开展系统的第四纪活动性研究,结果显示滦县西断裂为全新世活动断裂.

采用地震相对定位方法——Sbox方法,利用云南洱源亚失稳台阵、云南固定台网和临时台网的震相到时数据,对滇西北地区2018年3月18日—2020年5月21日发生的地震进行重新定位.在此基础上分析了云南漾濞MS6.4地震序列的空间分布特征.结果显示,Sbox方法可显著锐化地震分布图像,增加地震丛集性,从而提高地震分布对深部构造的分辨率;漾濞MS6.4地震序列与背景地震在空间分布上呈现明显的补位现象,漾濞地震属于单侧破裂,破裂方向为自北西向南东方向.在漾濞地震前几年或更长一段时期内,破裂面北西端及深部小地震发育,形成预破裂,震前在漾濞地震断层面区域形成相对地震空区,直至漾濞地震序列的发生填补了该空区.

使用HASH方法反演了云南亚失稳台网记录的滇西北地区2018年3月—2020年8月期间1338个中小地震震源机制解,震源机制解各参数统计分析和系统聚类结果显示,该区震源破裂以正断层为主,占比57.8％,各类解平均的P轴方位以NNW-SSE和NNE-SSW为主,整体呈近NS向,与云南地区整体的震源机制类型不一致,表现出局部构造影响下的应力场非均匀性.震源机制解一致性参数空间扫描显示,2021年5月21日漾濞6.4级地震发生在一致性参数由低值区向高值区过渡地带,结合速度结构和矩张量反演结果进一步对漾濞地震的发震机理进行了讨论.