Research on risk identification and information resilience of emergency information for extraordinary urban rainstorm disaster

doi:10.16265/j.cnki.issn1003-3033.2026.01.1761

Abstract

Abstract:

To address the problems of information distortion, transmission interruption, and response failure in emergency information systems during urban extreme rainstorm disasters, the study first identified five categories of risk—information source, information acquisition, information storage, information processing, and information transmission—from the perspective of the information processing lifecycle. Taking "7·20" Zhengzhou rainstorm event as a case, the risk factors of emergency information were systematically revealed. Subsequently, the connotation of emergency information resilience was defined, and a resilience structure was constructed. Finally, a "risk-resilience" coupling theoretical framework of emergency information resilience for urban extreme rainstorm disasters was established. The Results show that emergency information resilience is formed by the coupled effect of institutional resilience, social resilience, organizational resilience, and physical resilience. The theoretical framework of emergency information resilience consists of four stages. Including scientific construction of information resilience, integration of information risk early warning and response, cutting off the path of information risk diffusion, and enhancing the adaptability of information systems. The theoretical framework of the role of urban mega-rainstorm disaster emergency information resilience constructed in the text significantly improves the absorption capacity, recovery capacity and adaptability of information systems in response to complex disaster impacts.

Key words: emergency management, urban extreme rainstorm disaster, emergency information risk, risk identification, information resilience

CLC Number:

X915.5

JIANG Runzhou, FENG Wei. Research on risk identification and information resilience of emergency information for extraordinary urban rainstorm disaster[J]. China Safety Science Journal, 2026, 36(1): 208-215.

Figures/Tables 3

References 22

[1]	李华, 郭皓杰, 谢辉, 等. 基于信息熵的森林火灾应急指挥信息传递分析[J]. 中国安全科学学报, 2023, 33 (1): 80-87. doi: 10.16265/j.cnki.issn1003-3033.2023.01.2359
	LI Hua, GUO Haojie, XIE Hui, et al. Information transmission analysis of forest fire emergency command based on information entropy[J]. China Safety Science Journal, 2023, 33 (1): 80-87. doi: 10.16265/j.cnki.issn1003-3033.2023.01.2359
[2]	ZHANG Guirong, FENG Wei, LEI Yu, et al. Generation and evolution mechanism of systemic risk (SR)induced by extreme precipitation in Chinese urban system: a case study of Zhengzhou "7·20" incident[J]. International Journal of Disaster Risk Reduction, 2022, 83: DOI:10.1016/j.ijdrr.2022.103401.
[3]	IGOR L, BENJAMIN T. The science and practice of resilience[M]. Cham: Springer, 2019: 1-20.
[4]	朱正威, 刘莹莹. 韧性治理:风险与应急管理的新路径[J]. 行政论坛, 2020, 27(5): 81-87.
	ZHU Zhengwei, LIU Yingying. Resilient governance: a new approach for risk and emergency management[J]. Administrative Tribune, 2020, 27(5):81-87.
[5]	李琼, 肖立志. 数智赋能社区应急治理:何以可能,何以可为?基于上海市L街道“社区大脑”建设的案例分析[J]. 广州大学学报:社会科学版, 2024, 23 (2): 108-122.
	LI Qiong, XIAO Lizhi. Digital intelligence empowers community emergency governance:why is it possible and what can be done:a case study based on the construction of "community brain" in l street of Shanghai[J]. Journal of Guangzhou University: Social Sciences Edition, 2024, 23 (2): 108-122.
[6]	周利敏, 罗运泽. 数智赋能:智慧城市时代的应急管理[J]. 理论探讨, 2023(2): 69-78.
	ZHOU Limin, LUO Yunze. Digital intelligence empowerment: emergency management in the smart city era[J]. Theoretical Investigation, 2023(2): 69-78.
[7]	张桂蓉, 王雨晴. 数智赋能推进敏捷化应急情报体系研究[J]. 现代情报, 2024, 44 (4): 3-10,31.
	ZHANG Guirong, WANG Yuqing. Empowering digital intelligence to promote the agility of emergency intelligence system[J]. Journal of Modern Information, 2024, 44 (4): 3-10,31.
[8]	COMFORT L, ZAFORECKI A. Coordination in rapidly evolving disaster response systems the role of information[J]. American Behavioral Scientist, 2004, 48 (3): 295-313. doi: 10.1177/0002764204268987
[9]	ZHANG Lin, WANG Jinyu, WANG Xin, et al. Research on cross-city emergency management collaboration mechanism in major emergencies: insights from a knowledge management perspective[J]. Journal of Knowledge Management, 2025, 29 (3): 735-751. doi: 10.1108/JKM-05-2023-0442
[10]	CHEN Rui, SHARMAN R, RAO H. Coordination in the emergency response management[J]. Communications of the ACM, 2008, 51:66-73.
[11]	张桂蓉, 雷雨, 冯伟, 等. 大数据驱动下应急信息协同机制研究[J]. 情报杂志, 2022, 41 (4): 181-185,201.
	ZHANG Guirong, LEI Yu, FENG Wei, et al. Research on emergency information collaboration mechanism driven by big data[J]. Journal of Intelligence, 2022, 41 (4): 181-185,201.
[12]	WANG Yanqing, CHEN Hong. Blockchain: a potential technology to improve the performance of collaborative emergency management with multi-agent participation[J]. International Journal of Disaster Risk Reduction, 2022,72: DOI: 10.1016/j.ijdrr.2022.102867.
[13]	STAIR R, REYNOLDS G. Principles of information systems:11^th edition[M]. Boston, MA: Cengage Learning, 2013:10-20.
[14]	吴超. 安全信息认知通用模型构建及其启示[J]. 中国安全生产科学技术, 2017, 13 (3): 5-11.
	WU Chao. Construction of universal model on safety information cognition and its enlightenment[J]. Journal of Safety Science and Technology, 2017, 13 (3): 5-11.
[15]	张桂蓉, 冯伟. 社会-技术系统下安全信息处理多级不对称模式及其优化[J]. 情报杂志, 2021, 40(10):122-127,178.
	ZHANG Guirong, FENG Wei. The multi-level asymmetric model and its optimization of safety information processing from the perspective of the social-technical system[J]. Journal of Intelligence, 2021, 40(10):122-127,178.
[16]	UNDRR. Making cities resilient: my city is getting ready[EB/OL]. [2025-05-11] https://www.unisdr. org/campaign/resilientcities/.
[17]	邓胜利, 袁梦. 面向韧性社会的信息韧性理论内涵与实践路径[J]. 图书情报知识, 2025, 42(5):44-53,65.
	DENG Shengli, YUAN Meng. Theoretical connotation and practical path of information resilience for resilient society[J]. Documentation, Information & Knowledge, 2025, 42(5): 44-53,65.
[18]	张海波. 新时代国家应急管理体制机制的创新发展[J]. 人民论坛·学术前沿, 2019(5):6-15.
	ZHANG Haibo. Innovation and development of national emergency management institution and mechanism in the new era[J]. Frontiers, 2019(5): 6-15.
[19]	JABAREEN Y. The risk city resilience trajectory[M]. Dordrecht: Springer, 2015:55-60.
[20]	王秉, 曹春秀, 王渊洁. 数字政府安全韧性的内涵与模型[J]. 情报科学, 2024, 42 (7): 45-50.
	WANG Bing, CAO Chunxiu, WANG Yuanjie. The connotation and model of digital government security and safety resilience[J]. Information Science, 2024, 42 (7): 45-50.
[21]	陈长坤, 陈以琴, 施波, 等. 雨洪灾害情境下城市韧性评估模型[J]. 中国安全科学学报, 2018, 28(4):1-6. doi: 10.16265/j.cnki.issn1003-3033.2018.04.001
	CHEN Changkun, CHEN Yiqin, SHI Bo, et al. An model for evaluating urban resilience to rainstorm flood disasters[J]. China Safety Science Journal, 2018, 28(4):1-6. doi: 10.16265/j.cnki.issn1003-3033.2018.04.001
[22]	HOLLING C S. Resilient and stability of ecological systems[J]. Annual Review of Ecology and Systematics, 1973, 4(1):1-23. doi: 10.1146/ecolsys.1973.4.issue-1