震害损失评估中房屋抗致死性水平区划关键技术研究——以山东为例

Key Technologies for zoning of building anti-lethality levels in seismic damage loss assessment: a case study of Shandong province

摘要

破坏性地震导致的人员伤亡主要源于震后房屋建筑的倒塌与损毁,因此获取房屋抗致死性水平区划是震后灾害损失评估的核心参数。以山东省为研究区域,针对房屋抗致死性水平模型构建及矩阵本地化的关键技术展开深入探究。采用层次分析法(AHP)确定本地化抗致死性模型(矩阵)所需的各结构类型因子与区域调整因子的权重,生成全省建筑抗致死性水平等级区划图;通过精细化人口格网数据实现致死性矩阵的本地化,获得地震烈度Ⅵ至Ⅸ度下的人员死亡分布;开展70次模拟地震实验,对比评估结果与易损性结果,并以2023年8月6日山东平原5.5级地震为例进行精度验证。研究结果表明:本地化矩阵的σ值显著低于未本地化矩阵,其与易损性评估结果的一致性更高,表明矩阵本地化工作的必要性,评估可靠性更强;真实震例计算得到,本文模型评估死亡人数为0~1人,而传统易损性矩阵评估结果为3~5人,验证了矩阵数值反演的准确性;随着震级增大,评估差值及σ值同步增加,这与实地调查中农村空心化导致老旧房屋使用率降低的现象相吻合。

Abstract

The casualties caused by major earthquakes primarily stem from the collapse and damage of buildings after the earthquake. Therefore, obtaining the zoning of building anti-lethality levels is a critical parameter for rapid post-earthquake emergency assessment. Taking Shandong Province as the study area, this research investigates in depth the key technologies for constructing the building anti-lethality level model and realizing matrix localization. The study uses the Analytic Hierarchy Process (AHP) to determine the weights of multi-structural lethality models and regional adjustment factors, generating a province-wide zoning map of building anti-lethality levels. Through fine-grained population grid data, the localization of the lethality matrix is achieved to obtain the distribution of casualties under seismic intensities from Ⅵ to Ⅸ. Seventy simulated earthquake experiments are conducted to compare the assessment results with vulnerability model results, and the accuracy is validated using the M5.5 Pingyuan earthquake in Shandong on August 6, 2023 as a case study. The results show that the σ-value of the localized matrix is significantly lower than that of the non-localized matrix, indicating higher consistency with vulnerability assessment results and stronger assessment reliability; In the real earthquake case, the localized lethality matrix estimates 0~1 fatalities, while the traditional vulnerability matrix predicts 3~5 fatalities, verifying the accuracy of matrix numerical inversion; As the earthquake magnitude increases, both the assessment discrepancy and σ-value increase synchronously, which is consistent with the field observation that rural hollowing-out leads to reduced occupancy rates of old buildings.

关键词

致死性 / 区域背景 / 数值反演 / 震害评估 / 矩阵本地化

Key words

lethality / regional background / numerical inversion / seismic damage assessment / matrix localization

参考文献

[1] 于贵华, 徐锡伟, 陈桂华, 等 . 汶川8.0级地震地表变形局部化样式与建筑物破坏特征关系初步研究[J]. 地球物理学报, 2009, 52(12): 3027-3041.

[2] Yu Guihua, Xu Xiwei, Chen Guihua, et al. Relationship between the localization of earthquake surface ruptures and building damages associated with the Wenchuan 8.0 earthquake[J]. Chinese Journal of Geophysics, 2009, 52(12): 3027-3041. (in Chinese)

[3] 时振梁, 鄢家全, 汪素云. 建筑物的破坏和断层附近的地面运动[J]. 地球物理学报, 1978,(3): 234-241.

[4] Shi Zhenliang, Yan Jiaquan, Wang Suyun. Damage to structures and ground displacement near the faults[J]. Chinese Journal of Geophysics, 1978, 21(3): 234-241. (in Chinese)

[5] 聂高众, 夏朝旭, 范熙伟. 基于历史地震人员死亡数据的抗致死性水平分级[J]. 地质科学, 2020, 55(4): 1298-1314.

[6] Nie Gaozhong, Xia Chaoxu, Fan Xiwei. Grading of anti-lethal level based on historical earthquake mortality data[J]. Chinese Journal of Geology (Scientia Geologica Sinica), 2020, 55(4): 1298-1314. (in Chinese)

[7] 孙钦瑶, 钟秀梅, 马金莲, 等 . 基于GF-2遥感影像的甘东南农村建筑物结构分类方法[J]. 遥感技术与应用, 2025, 40(1): 192-201.

[8] Sun Qinyao, Zhong Xiumei, Ma Jinlian, et al. Classification method for rural building structures in southeast Gansu Province based on remote sensing images[J]. Remote Sensing Technology and Application, 2025, 40(1): 192-201. (in Chinese)

[9] 李延唯, 余世舟. 东部地区地震人员伤亡评估方法研究[J]. 世界地震工程, 2021, 37(3): 207-213.

[10] Li Yanwei, Yu Shizhou. Study on the assessment method of earthquake casualties in the eastern region[J]. World Earthquake Engineering, 2021, 37(3): 207-213. (in Chinese)

[11] 代友林, 刘洋, 梁远玲, 等 . 芦山6.1级地震与泸县6.0级地震人员伤亡对比分析[J]. 震灾防御技术, 2022, 17(4): 674-681.

[12] Dai Youlin, Liu Yang, Liang Yuanling, et al. Comparative analysis of casualties between Lushan M6.1 earthquake and Luxian M6.0 earthquake[J]. Technology for Earthquake Disaster Prevention, 2022, 17(4): 674-681. (in Chinese)

[13] 许瑞杰, 贾召亮, 郑川, 等 . 滇西地区基于单体建筑的震后人员死亡评估方法研究[J]. 地震研究, 2023, 46(3): 394-402.

[14] Xu Ruijie, Jia Zhaoliang, Zheng Chuan, et al. Study on the assessment method of post-earthquake fatality in western Yunnan based on the single building[J]. Journal of Seismological Research, 2023, 46(3): 394-402. (in Chinese)

[15] 袁小祥, 林旭川, 窦爱霞, 等 . 基于震前高分影像和震害仿真的建筑物震害快速评估: 以四川泸定6.8级地震为例[J]. 地球物理学报, 2023, 66(4): 1438-1447.

[16] Yuan Xiaoxiang, Lin Xuchuan, Dou Aixia, et al. Rapid assessment of building seismic damage based on pre-earthquake high-resolution images and seismic simulation, taking the Luding M6.8 earthquake in Sichuan as an example[J]. Chinese Journal of Geophysics, 2023, 66(4): 1438-1447. (in Chinese)

[17] 尹之潜. 地震灾害损失预测研究[J]. 地震工程与工程振动, 1991, 11(4): 87-96.

[18] Yin Zhiqian. A study for predicting earthquake disaster loss Earthquake Disaster[J]. Earthquake Engineering and Engineering Dynamics, 1991, 11(4): 87-96. (in Chinese)

[19] 王晓青, 窦爱霞, 王龙, 等 . 2013年四川芦山7.0级地震烈度遥感评估[J]. 地球物理学报, 2015, 58(1): 163-171.

[20] Wang Xiaoqing, Dou Aixia, Wang Long, et al. RS-based assessment of seismic intensity of the 2013 Lushan, Sichuan, China M_S7.0 earthquake [J]. Chinese Journal of Geophysics, 2015, 58(1): 163-171. (in Chinese)

[21] 袁海红, 高晓路, 戚伟. 城市地震风险精细化评估: 以北京海淀区为例[J]. 地震地质, 2016, 38(1): 197-210.

[22] Yuan Haihong, Gao Xiaolu, Qi Wei. Assessing the seismic risk of cities at fine-scale: a case study of Haidian district in Beijing, China[J]. Seismology and Geology, 2016, 38(1): 197-210. (in Chinese)

[23] 张维佳, 杨天青, 白仙富, 等 . 基于地区差异性修正因素的川滇地区地震人员伤亡动态评估方法研究[J]. 中国地震, 2021, 37(1): 197-205.

[24] Zhang Weijia, Yang Tianqing, Bai Xianfu, et al. Dynamic assessment method of earthquake casualties in consideration of regional difference between Sichuan and Yunnan Provinces[J]. Earthquake Research in China, 2021, 37(1): 197-205. (in Chinese)

[25] Alel M, Ramly N, Chafar M, et al. Estimation of life casualties for seismic vulnerability assessment in Bukit Tinggi, Pahang, Malaysia[C]// Proceedings of the ACSME Conference, 2013.

[26] 齐文华. 从遥感到社感: 基于多元感知的地震灾害风险评估系列方法研究[D]. 北京: 中国地震局地质研究所, 2022.

[27] Qi Wenhua. From remote to social sensing: multi-sensing based approaches to the assessment of seismic disaster risk[D]. Beijing: Institute of Geology, China Earthquake Administration, 2022. (in Chinese)

[28] 聂高众, 夏朝旭, 范熙伟, 等 . 基于历史地震数据的建筑物致死性水平研究[J]. 地质科学, 2021, 56(4): 1250-1266.

[29] Nie Gaozhong, Xia Chaoxu, Fan Xiwei, et al. Research on the lethal level of buildings based on historical seismic data[J]. Chinese Journal of Geology (Scientia Geologica Sinica), 2021, 56(4): 1250-1266. (in Chinese)

[30] 夏朝旭. 基于实地调查的地震人员死亡致死性评估技术研究[D]. 北京: 中国地震局地质研究所, 2020.

[31] Xia Chaoxu. Research on lethal assessment technique of earthquake death based on field investigation[D]. Beijing: Institute of Geology, China Earthquake Administrator, 2020. (in Chinese)

[32] 侯建盛, 李洋, 宋立军, 等 . 2014年云南景谷6.6级地震与云南鲁甸6.5级地震致灾因素分析[J]. 灾害学, 2015, 30(2): 100-101,143.

[33] Hou Jiansheng, Li Yang, Song Lijun, et al. Cause analysis of M6.6 Jinggu earthquake and M6.5 Ludian earthquake in Yunnan in 2014[J]. Journal of Catastrophology, 2015, 30(2): 100-101,143. (in Chinese)

[34] 洪海春, 尤捷, 陶小三, 等 . 2014年云南鲁甸地震和景谷地震的震害对比研究[J]. 地震工程学报, 2015, 37(4): 1013-1022.

[35] Hong Haichun, You Jie, Tao Xiaosan, et al. Comparative study of seismic damage induced by 2014 Ludian M_S6.5 and Jinggu M_S6.6 earthquakes in Yunnan Province [J]. China Earthquake Engineering Journal, 2015, 37(4): 1013-1022. (in Chinese)

[36] 赵煜, 韩旭昊, 孙艳萍, 等 . 基于PSO-ELM的地震死亡人员评估方法研究[J]. 地震工程学报, 2024, 46(3): 742-750.

[37] Zhao Yu, Han Xuhao, Sun Yanping, et al. Method for estimating earthquake casualties based on PSO-ELM[J]. China Earthquake Engineering Journal, 2024, 46(3): 742-750. (in Chinese)

[38] Ferreira M A, Oliveira C S, de Sá F M. Estimating human losses in earthquake models: a discussion[M]// Human casualties in earthquakes: progress in modelling and mitigation. Dordrecht: Springer, 2011: 255-266.

[39] Ceferino L, Kiremidjian A, Deierlein G. Regional multi severity casualty estimation due to building damage following a M_W8.8 earthquake scenario in Lima, Peru [J]. Earthquake Spectra, 2018, 34(4): 1739-1761.

基金资助

中国地震局应急青年重点任务(CEAEDEM20250206)

山东省地震局科技创新团队(TD202403)