May 21, 2021, Yangbi, Yunnan MS 6.4 Analysis of the Results of Rapid Assessment of Earthquake Disaster Losses
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摘要: 本文针对2021年5月21日云南漾濞6.4级地震,选取不同的地震烈度衰减关系模型,对各模型地震影响场评估结果与发布的地震烈度图进行对比分析,并对地震影响范围不确定性进行研究。选取多种死亡人数评估模型,分别计算各模型在不同地震影响场下的死亡人数、人口分布数量,探讨各地震影响场模型下的人口分布特征及影响人员死亡的主要因素。通过对比分析可知,导致此次地震灾害损失评估结果与真实地震现场结果不同的主要原因是地震影响场分布、人口分布、房屋建筑抗震能力偏差、地形地貌、次生灾害等多种因素不同。研究结果表明,有效提高地震灾害损失快速评估精确性的途径为提高地震影响场评估精度,提高人口分布、房屋建筑等数据空间分布评估精度,后期专家检验等。Abstract: This paper selects different seismic intensity attenuation relationship models for the May 21, 2021 Yangbi M6.4 earthquake in Yunnan, and compares and analyzes the seismic impact field evaluation results of each model with the released seismic intensity map, and conducts a comparison of various intensity attenuation models. Uncertainty analysis of the earthquake impact range; select multiple casualty assessment models to calculate and analyze the number of deaths and population distribution of each death model under different earthquake impact fields, and explore the population distribution characteristics of each earthquake impact field model And the main factors affecting the casualties of the earthquake. Through comparative analysis, it can be seen that the main reasons for the difference between the loss assessment results of the Yunnan Yangbi M6.4 earthquake and the real earthquake site results are: the distribution of the earthquake affected field, the population distribution, the deviation of the estimation of the building (seismic capacity), the topography, and the frequency of the earthquake. It is caused by various factors such as natural disasters. The results show that the ways to effectively improve the accuracy of the rapid assessment of earthquake disaster losses are: improving the accuracy of the earthquake impact field assessment, improving the accuracy of the spatial distribution of data such as population distribution, housing and construction, and major factors such as later expert intervention.
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Key words:
- Earthquake disaster loss /
- Intensity /
- Casualties /
- Population distribution /
- Assessment
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表 1 地震现场影响场评估结果与5种地震影响场评估模型
Table 1. On-site evaluation results and five types of earthquake-influenced field evaluation models
表 2 地震现场影响场评估结果与5种影响场模型评估结果对比
Table 2. Comparison of the assessment results of the earthquake impact field between the earthquake site and the five assessment models
模型 最高
烈度Ⅵ度区/km Ⅶ度区/km Ⅷ度区/km Ⅵ度区
面积/km²Ⅶ度区
面积/km²Ⅷ度区
面积/km²长轴长度 短轴长度 长轴长度 短轴长度 长轴长度 短轴长度 a Ⅷ度 106 76 50 28 19 10 5 500 930 170 b Ⅷ度 118 82 51 29 11 5 6493 1 112 36 c Ⅷ度 119 76 51 29 11 6 5 914 1 104 43 d Ⅷ度 156 88 58 29 4 3 9 467 1 309 13 e Ⅶ度 93 54 31 16 — — 3 522 376 — f Ⅷ度 119 75 56 35 18 12 5 481 1 386 166 表 3 西南地区人口密度分组
Table 3. Population density groups in southwest China
人口密度$ \rho $/(人·km−2) b0 b1 b2 b3 相关系数R2 $ \rho < 60 $ −23.390 3.230 −0.000 030 −0.980 0.965 $ 60 \leqslant \rho < 150 $ 4.926 −0.762 0.000 300 1.559 0.980 $ \rho > 150 $ −10.485 1.763 0.000 006 −0.276 0.980 表 4 人员死亡评估模型计算结果对比
Table 4. Comparison of earthquake death assessment results of different impact field assessment models
影响场
模型最高
烈度实际死亡
人数/人刘金龙
模型/人Page P. A.模型/人 肖光先
模型/人李雯
模型/人陈棋福模型/人 a Ⅷ度 3 15 10 2 2 25 b Ⅷ度 3 15 10 1 3 25 c Ⅷ度 3 15 10 2 3 25 d Ⅷ度 3 15 10 2 8 25 e Ⅶ度 3 12 5 1 4 2 f Ⅷ度 3 15 10 2 5 25 表 5 各模型下的人口数量估算结果
Table 5. Population estimation results under each model
模型 最高
烈度Ⅵ度区
面积/km²Ⅶ度区
面积/km²Ⅷ度区
面积/km²Ⅵ度区
人口数量/万人Ⅶ度区
人口数量/万人Ⅷ度区
人口数量/万人a Ⅷ度 5 500 930 170 85.793 8 4.265 1 3.432 2 b Ⅷ度 6 493 1 112 36 99.000 0 8.500 0 0.170 0 c Ⅷ度 5 914 1 104 43 89.000 0 8.500 0 0.200 0 d Ⅷ度 9 467 1 309 13 130.000 0 9.600 0 0.040 0 e Ⅶ度 3 522 376 — 24.000 0 1.500 0 — f Ⅷ度 5 481 1 386 166 86.000 0 10.000 0 0.750 0 表 6 云南漾濞6.4级地震临震前震(M>3.0)目录
Table 6. Catalogue of imminent foreshocks (M>3.0) of the M6.4 Yangbi earthquake
序号 时间 纬度 经度 震级/级 震源深度/km 震中位置 1 2021-05-18 18:49 26.65°N 99.93°E 3.2 8 云南漾濞 2 2021-05-18 20:56 26.65°N 99.93°E 3.0 8 云南漾濞 3 2021-05-18 21:39 25.65°N 99.93°E 4.0 8 云南漾濞 4 2021-05-19 3:27 25.65°N 99.92°E 3.1 8 云南漾濞 5 2021-05-19 20:05 25.66°N 99.92°E 4.4 8 云南漾濞 6 2021-05-19 21:13 25.68°N 99.89°E 3.2 8 云南漾濞 7 2021-05-20 21:13 25.67°N 99.90°E 3.2 11 云南漾濞 8 2021-05-21 20:56 25.63°N 99.93°E 4.2 8 云南漾濞 9 2021-05-21 21:21 25.63°N 99.92°E 5.6 10 云南漾濞 10 2021-05-21 21:23 25.66°N 99.97°E 4.5 8 云南漾濞 -
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