复杂网络下雨洪灾害链风险分析及断链减灾研究

doi:10.16265/j.cnki.issn1003-3033.2023.12.2006

摘要/Abstract

摘要：

为提高雨洪灾害突发事件的应急处置和灾害救援能力,在复杂网络视角下分析雨洪灾害链风险,通过案例分析,统计雨洪灾害的次生衍生灾害事件和相互关系,构建雨洪灾害链网络拓扑结构;建立雨洪灾害风险评价模型,计算得出灾害网络的节点重要度、边的脆弱度和灾害链的风险度。结果表明:“暴雨-滑坡-基础设施损坏”和“暴雨-滑坡-道路桥梁摧毁-交通瘫痪”这2条链是雨洪灾害防治的重点。在雨洪灾害发生前管控重要节点,并在雨洪灾害发生后对风险度较高的边及时截断,可有效防止雨洪灾害次生衍生事件的发生和蔓延。

关键词: 复杂网络, 雨洪灾害, 灾害链, 风险度, 节点重要度

Abstract:

In order to improve the emergency response and disaster rescue capability of rain and flood disasters, the risk analysis on the rain and flood disaster chain under complex networks was conducted in this study. The secondary derivative disaster events and interrelationships of rain and flood disaster were counted and the network topology structure of the rain and flood disaster chain was constructed. The rain and flood disaster risk assessment model was established, and the node importance degree, the edge vulnerability degree and the risk degree of disaster chain were calculated. The results show that the two chains of "rainstorm-landslide-infrastructure damage" and "rainstorm-landslide-road-bridge destruction-traffic paralysis" are the key points in the prevention and control of rain and flood damage. Controlling important nodes before the occurrence of rain and flood disasters, and cutting off the edge with high risk in time after the occurrence of rain and flood disasters can effectively prevent the occurrence and spread of secondary derivative events of rain and flood disasters.

Key words: rainstorm flood disaster, complex network, disaster chain, risk degree, node importance

李磊, 马梦格, 折亚亚, 王雨秋, 房子豪, 王帆. 复杂网络下雨洪灾害链风险分析及断链减灾研究[J]. 中国安全科学学报, 2023, 33(12): 192-197.

LI Lei, MA Mengge, SHE Yaya, WANG Yuqiu, FANG Zihao, WANG Fan. Risk analysis of rainstorm flood disaster chain and research on disaster mitigation of broken chain under complex network[J]. China Safety Science Journal, 2023, 33(12): 192-197.

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参考文献 13

[1]	哈斯, 张继权, 佟斯琴, 等. 灾害链研究进展与展望[J]. 灾害学, 2016, 31( 2):131-138.
	HA Si, ZHANG Jiquan, TONG Siqin, et al. Progress and prospect of the research on disaster chain[J]. Journal of Catastrophology, 2016, 31(2):131-138.
[2]	WATTS D J, STROGATZ S H. Collective dynamics of "small-world" networks[J]. Nature, 1998, 393(6684): 440-442. doi: 10.1038/30918
[3]	LI Jian, CHEN Changkun. Modeling the dynamics of disaster evolution along causality networks with cycle chains[J]. Physica A Statistical Mechanics & Its Applications, 2014, 401:251-264.
[4]	BUZNA L, PETERS K, HELBING D. Modelling the dynamics of disaster spreading in networks,in physica a-statistical mechanics and its applications[C]. Tyrol: Conference on In formation and Material Flows in Compex Network, 2006:132-140.
[5]	吴书强, 邵必林, 边根庆, 等. 基于复杂网络的高校火灾灾害链分析及应急管理决策研究[J]. 灾害学, 2022, 37(2):156-161,166.
	WU Shuqiang, SHAO Bilin, BIAN Genqing, et al. Research on fire disaster chain analysis and emergency management decision-making in colleges and universities based on complex networkt[J]. Journal of Catastrophology, 2022, 37(2):156-161,166.
[6]	李浩然, 王子恒, 杨起帆, 等. 复杂网络下地铁灾害链演化模型与风险分析[J]. 中国安全科学学报, 2021, 31(11):141-147. doi: 10.16265/j.cnki.issn 1003-3033.2021.11.020
	LI Haoran, WANG Ziheng, YANG Qifan, et al. Evolutionary model and risk analysis of metro disaster chain under complex network[J]. China Safety Science Journal, 2021, 31(11):141-147. doi: 10.16265/j.cnki.issn 1003-3033.2021.11.020
[7]	黄昕, 靳健, 林作忠, 等. 基于复杂网络的城市深部空间火灾灾害链分析及智慧减灾方法研究[J]. 应用基础与工程科学学报, 2021, 29(5):1280-1291.
	HUANG Xin, JIN Jian, LIN Zuozhong, et al. Complex network-based analysis on fire disaster chain of urban deep underground space and intelligent disaster mitigation measures[J]. Journal of Basic Science and Engineering, 2021, 29(5):1280-1291.
[8]	刘海云, 韩晓松, 翟振岗, 等. 基于复杂网络的燃气管线破裂灾害链风险分析[J]. 中国安全生产科学技术, 2020, 16(9):37-42.
	LIU Haiyun, HAN Xiaosong, ZHAI Zhengang, et al. Risk analysis on rupture disaster chain of gas pipeline based on complex network[J]. Journal of Safety Science and Technology, 2020, 16(9):37-42.
[9]	孟令晗, 张靖岩, 杨玲. 商业综合体灾害链风险评估研究[J]. 中国安全生产科学技术, 2020, 16(7):43-47.
	MENG Linghan, ZHANG Jingyan, YANG Ling. Research on risk assessment of disaster chains in commercial complex[J]. Journal of Safety Science and Technology, 2020, 16(7):43-47.
[10]	罗军华, 林孝松, 牟凤云, 等. 山区暴雨-农业灾害链复杂网络静态风险分析[J]. 中国安全科学学报, 2020, 30(3):163-170. doi: 10.16265/j.cnki.issn1003-3033.2020.03.025
	LUO Junhua, LIN Xiaosong, MU Fengyun, et al. Static risk analysis on rainstorm-agricultural disaster chain in mountainous areas based on complex network[J]. China Safety Science Journal, 2020, 30(3):163-170. doi: 10.16265/j.cnki.issn1003-3033.2020.03.025
[11]	宋英华, 张小莹, 吕伟. 城镇-森林交界域火灾灾害链网络模型构建及风险分析[J]. 中国安全生产科学技术, 2020, 16(5):122-128.
	SONG Yinghua, ZHANG Xiaoying, LYU Wei. Construction of disaster chain network model and risk analysis on wildland-urban interface fire[J]. Journal of Safety Science and Technology, 2020, 16(5):122-128.
[12]	BONACICH P F. Factoring and weighting approaches to status scores and clique identification[J]. Journal of Mathematical Sociology, 1972, 2(1):113-120. doi: 10.1080/0022250X.1972.9989806
[13]	张子超, 郝蔚琳, 张伊凡. 一种复杂网络中节点安全重要性排序的度量方法[J]. 信息安全学报, 2019, 4(1):79-88.
	ZHANG Zichao, HAO Weilin, ZHANG Yifan. A measure approach for ranking the security importance of node security importance in complex network[J]. Journal of Cyber Security, 2019, 4(1):79-88. doi: 10.32604/jcs.2022.029020

节点序号	灾害事件	节点序号	灾害事件
V₁	暴雨	V₁₀	房屋倒塌
V₂	滑坡(崩塌)	V₁₁	人员伤亡
V₃	泥石流	V₁₂	道路桥梁冲毁
V₄	水位上涨	V₁₃	交通瘫痪
V₅	地面积水	V₁₄	人居环境受损
V₆	河流决堤	V₁₅	生活不便
V₇	道路被淹	V₁₆	网络舆情
V₈	基础设施损坏	V₁₇	经济损失
V₉	农作物受损	—	—

序号	节点	点度中心性	中介中心性	紧密度中心性	重要度
1	V₁₆	0.500	0.152	0.640	1.516
2	V₂	0.438	0.110	0.640	1.346
3	V₃	0.438	0.110	0.640	1.346
4	V₈	0.438	0.108	0.640	1.341
5	V₁₂	0.438	0.064	0.615	1.208
6	V₉	0.375	0.061	0.571	1.093
7	V₁₃	0.375	0.052	0.571	1.070
8	V₁	0.250	0.100	0.516	1.005
9	V₇	0.313	0.030	0.552	0.932
10	V₁₀	0.313	0.027	0.552	0.925
11	V₁₅	0.313	0.022	0.533	0.894
12	V₁₇	0.313	0.022	0.533	0.894
13	V₆	0.188	0.055	0.516	0.829
14	V₅	0.188	0.027	0.471	0.716
15	V₁₁	0.188	0.006	0.485	0.677
16	V₁₄	0.188	0.001	0.471	0.652
17	V₄	0.125	0.011	0.410	0.552

序号	灾害边	平均路径长度	脆弱度	致灾率	风险度	序号	灾害边	平均路径长度	脆弱度	致灾率	风险度
1	V₁-V₂	1.88	17.93	0.61	76.20	11	V₃-V₈	1.87	7.47	0.54	26.01
2	V₁-V₃	1.88	1.99	0.54	58.62	12	V₃-V₉	1.85	1.85	0.64	24.11
3	V₁-V₄	1.91	6.50	0.86	58.62	13	V₃-V₁₀	1.86	1.86	0.46	17.27
4	V₁-V₅	1.92	6.52	0.82	49.01	14	V₃-V₁₁	1.86	1.86	0.43	16.76
5	V₂-V₈	1.87	13.07	0.54	42.86	15	V₃-V₁₂	1.87	3.74	0.39	16.07
6	V₂-V₉	1.85	3.71	0.68	33.66	16	V₃-V₁₄	1.85	1.85	0.61	16.07
7	V₂-V₁₀	1.86	3.72	0.50	30.00	17	V₄-V₆	1.91	14.22	0.39	15.40
8	V₂-V₁₁	1.86	3.72	0.50	28.59	18	V₅-V₇	1.87	9.92	0.68	15.28
9	V₂-V₁₂	1.87	5.60	0.39	28.01	19	V₅-V₁₃	1.88	7.50	0.54	15.11
10	V₂-V₁₄	1.85	3.71	0.64	27.90	20	V₆-V₈	1.90	11.43	0.54	12.35

节点编号	出度	入度	度	节点编号	出度	入度	度
V₁	4	0	4	V₁₀	3	2	5
V₂	6	1	7	V₁₁	1	2	3
V₃	6	1	7	V₁₂	4	3	7
V₄	1	1	2	V₁₃	3	3	6
V₅	2	1	3	V₁₄	0	3	3
V₆	2	1	3	V₁₅	0	5	5
V₇	4	1	5	V₁₆	0	8	8
V₈	3	4	7	V₁₇	0	5	5
V₉	4	2	6

灾害链	风险度
1-2-8-15	183.83
1-2-8-17	183.83
1-2-8-16	153.80
1-2-12-13-15	138.87
1-2-12-13-17	136.88
1-2-12-13-16	132.29
1-2-12-17	106.88
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