PUBLIC SAFETY

Research on community resilience stress testing method under rainstorm waterlogging disaster

  • DAI Xin ,
  • HUANG Hong ,
  • YU Fucai ,
  • WU Aizhi ,
  • SHI Deyi ,
  • ZHANG Peng
Expand
  • 1. Institute of Public Safety Research, School of Safety Science, Tsinghua University, Beijing 100084, China;
    2. Beijing Academy of Emergency Management Science and Technology, Beijing 101101, China

Received date: 2024-02-19

  Online published: 2024-08-21

Abstract

[Objective] Recently, extreme precipitation has increased globally. Waterlogging disasters caused by rainfall have endangered people's lives and caused property losses. As the cell of the city, the community is the fundamental unit to resiliently withstand disasters. However, stress testing in the community resilience field is still in its infancy, and little research exists on relevant theoretical and technical frameworks. Therefore, this paper uses a rainstorm waterlogging disaster as an example to study the community resilience stress test method and provides application cases. [Methods] The community resilience stress test stimulates and assesses community resilience in response to various emergency events. Herein, the resilience curve method is used to calculate community resilience. This paper presents a specific community resilience stress test method for rainstorm waterlogging disasters. First, using the historical rainstorm disaster data and rainstorm intensity formula, 12 extreme rainfall scenarios were designed according to the 2 dimensions of hourly rain intensity and rainfall duration, covering 30-200 mm hourly rain intensity. Second, based on InfoWorks Integrated Catchment Modeling, this paper constructs a community rainstorm waterlogging hydrodynamic model. This study conducted the community rainstorm waterlogging measurement experiment in the rainy season. The monitoring data obtained are used for parameter calibration and validation of the hydrodynamic model. Then, this paper presented a resilience evaluation method focusing on engineering resilience. The system performance of community rainstorm waterlogging is defined by the proportion of inundated areas. The system performance of a drainage network is defined by the fullness of the drainage network. Community waterlogging resilience was calculated using these two types of system performance. Resilience is expressed using the area of the concave portion of the system performance curve of community rainstorm waterlogging. The termination time of the integral is calculated as the time when the system performance of the drainage network returns to 1. [Results] Using the community J in Beijing as an example, this paper conducted a stress test on the community's waterlogging resilience under 12 different extreme rainfall scenarios, based on the results of hydrodynamic simulation. The results show that community resilience is less affected by rainfall duration and positively correlated with hourly rainfall intensity under rainstorm waterlogging disasters. Under the extreme rainfall scenario of 200 mm/h, about 44% of the community was flooded, and the maximum water depth was nearly 1 m. About 95% of drainage pipes are overloaded. It takes 5.7 hours to fully restore the drainage capacity of the network. Waterlogging spots of varying severity in this community are observed. This paper provides targeted suggestions on how to improve community resilience under rainstorm waterlogging disasters for five main waterlogging-prone spots. [Conclusions] This paper proposes a stress test method for community resilience to waterlogging and analyzes the evolution process of resilience and risk tolerance of community J from two perspectives: drainage capacity of pipe network and inundated area of the community. This method provides a quantitative assessment of community resilience. The test results can be used for monitoring and investigating rainstorm waterlogging risk in community institutions and government departments. These results are conducive to preventing and resolving disaster risks in advance.

Cite this article

DAI Xin , HUANG Hong , YU Fucai , WU Aizhi , SHI Deyi , ZHANG Peng . Research on community resilience stress testing method under rainstorm waterlogging disaster[J]. Journal of Tsinghua University(Science and Technology), 2024 , 64(9) : 1587 -1596 . DOI: 10.16511/j.cnki.qhdxxb.2024.27.017

References

[1] 孔锋. 2012年北京"7·21"特大暴雨洪涝灾害应对及启示[J].中国减灾, 2022(9):42-45.KONG F. Response to the" July 21"heavy rain and flood disaster in Beijing in 2012 and its implications[J]. Disaster Reduction in China, 2022(9):42-45.(in Chinese)
[2] 国务院灾害调查组.河南郑州" 7·20"特大暴雨灾害调查报告[R].北京:国务院灾害调查组, 2022.Disaster Investigation Team of the State Council. Investigation report of "July 20" heavy rain disaster in Zhengzhou, Henan Province[R]. Beijing:Disaster Investigation Team of the State Council, 2022.(in Chinese)
[3] 景鹏旭,徐一凡,门丽君,等."7·31"特大暴雨引发的门头沟区地质灾害调研及紧急应对策略研究[J].中国应急救援, 2024(1):72-77.JING P X, XU Y F, MEN L J, et al. Research on geological hazards and emergency response strategies under" July 31"torrential rainstorm in Mentougou district[J]. China Emergency Rescue, 2024(1):72-77.(in Chinese)
[4] 李瑞奇,黄弘,周睿.基于韧性曲线的城市安全韧性建模[J].清华大学学报(自然科学版), 2020, 60(1):1-8.LI R Q, HUANG H, ZHOU R. Resilience curve modelling of urban safety resilience[J]. Journal of Tsinghua University (Science and Technology), 2020, 60(1):1-8.(in Chinese)
[5] FOX-LENT C, BATES M E, LINKOV I. A matrix approach to community resilience assessment:An illustrative case at Rockaway Peninsula[J]. Environment Systems and Decisions, 2015, 35(2):209-218.
[6] GILLESPIE-MARTHALER L, NELSON K, BAROUD H, et al. Selecting indicators for assessing community sustainable resilience[J]. Risk Analysis, 2019, 39(11):2479-2498.
[7] 王淑良,陈辰,张建华,等.基于复杂网络的关联公共交通系统韧性分析[J].复杂系统与复杂性科学, 2022, 19(4):47-54.WANG S L, CHEN C, ZHANG J H, et al. Resilience analysis of public interdependent transport system based on complex network[J]. Complex Systems and Complexity Science, 2022, 19(4):47-54.(in Chinese)
[8] SEN M K, DUTTA S, KABIR G. Flood resilience of housing infrastructure modeling and quantification using a Bayesian belief network[J]. Sustainability, 2021, 13(3):1026.
[9] VARVIN M, BEIKI P, HEJAZI S J, et al. Assessment of infrastructure resilience in multi-hazard regions:A case study of Khuzestan Province[J]. International Journal of Disaster Risk Reduction, 2023, 88:103601.
[10] FU X R, WANG D, LUAN Q H, et al. Community scale assessment of the effectiveness of designed discharge routes from building roofs for stormwater reduction[J]. Remote Sensing, 2022, 14(13):2970.
[11] PACKHAM N, WOEBBEKING F. Correlation scenarios and correlation stress testing[J]. Journal of Economic Behavior&Organization, 2023, 205:55-67.
[12] BARBIERI P N, LUSIGNANI G, PROSPERI L, et al. Model-based approach for scenario design:Stress test severity and banks'resiliency[J]. Quantitative Finance, 2022, 22(10):1927-1954.
[13] MA Z H, NIE S L, LIAO H T. A load spectra design method for multi-stress accelerated testing[J]. Proceedings of the Institution of Mechanical Engineers, Part O:Journal of Risk and Reliability, 2022, 236(6):994-1006.
[14] AYDIN N Y, DUZGUN H S, WENZEL F, et al. Integration of stress testing with graph theory to assess the resilience of urban road networks under seismic hazards[J]. Natural Hazards, 2018, 91(1):37-68.
[15] 巴曙松,朱元倩.压力测试在银行风险管理中的应用[J].经济学家, 2010(2):70-79.BA S S, ZHU Y Q. The application of stress test in bank risk management[J]. Economist, 2010(2):70-79.(in Chinese)
[16] HU D N, YAN J Q, ZHAO J L, et al. Ontology-based scenario modeling and analysis for bank stress testing[J]. Decision Support Systems, 2014, 63:81-94.
[17] 陆婷婷,崔晓鹏.北京两次特大暴雨过程观测对比[J].大气科学, 2022, 46(1):111-132.LU T T, CUI X P. Observational comparison of two torrential rainfall events in Beijing[J]. Chinese Journal of Atmospheric Sciences, 2022, 46(1):111-132.(in Chinese)
[18] 中华人民共和国住房和城乡建设部,国家市场监督管理总局.室外排水设计标准:GB 50014-2021[S].北京:中国计划出版社, 2021.Ministry of Housing and Urban-Rural Development of the People's Republic of China, State Administration of Market Supervision and Administration of the People's Republic of China. Standard for design of outdoor wastewater engineering:GB 50014-2021[S]. Beijing:China Planning Press, 2021.(in Chinese)
[19] 俞露,荆燕燕,许拯民.辅助排水防涝规划编制的设计降雨雨型研究[J].中国给水排水, 2015, 31(19):141-145.YU L, JING Y Y, XU Z M. Study on design rainfall pattern supporting urban drainage and waterlogging prevention planning[J]. China Water&Wastewater, 2015, 31(19):141-145.(in Chinese)
[20] 黄华兵,王先伟,柳林.城市暴雨内涝综述:特征、机理、数据与方法[J].地理科学进展, 2021, 40(6):1048-1059. HUANG H B, WANG X W, LIU L. A review on urban pluvial floods:Characteristics, mechanisms, data, and research methods[J]. Progress in Geography, 2021, 40(6):1048-1059.(in Chinese)
[21] 北京市规划和国土资源管理委员会,北京市质量技术监督局.城镇雨水系统规划设计暴雨径流计算标准:DB11/T 969-2016[S].北京:北京市质量技术监督局, 2017. Beijing Municipal Commission of Planning, Land and Resources Management, Beijing Municipal Bureau of Quality and Technical Supervision. Standard of rainstorm runoff calculation for urban storm drainage system planning and design:DB11/T 969-2016[S]. Beijing:Beijing Bureau of Quality and Technical Supervision, 2017.(in Chinese)
[22] 李海川,范丹丹,燕乃一.水利部新闻发布会聚焦海河" 23·7"流域性特大洪水防御情况.中国水利报, 2023-08-22(002).LI H C, FAN D D, YAN N Y. Ministry of Water Resources press conference focused on Haihe River" 23·7"regional flood prevention. China Water Resources News, 2023-08-22(002).(in Chinese)
[23] 谌舟颖,孔锋.河南郑州" 7·20"特大暴雨洪涝灾害应急管理碎片化及综合治理研究[J].水利水电技术(中英文), 2022, 53(8):1-14.CHEN Z Y, KONG F. Study on fragmentation of emergency management during"7·20"extreme rainstorm flood disaster in Zhengzhou of Henan Province and relevant comprehensive treatment[J]. Water Resources and Hydropower Engineering, 2022, 53(8):1-14.(in Chinese)
[24] 徐宗学,叶陈雷.城市暴雨洪涝模拟:原理、模型与展望[J].水利学报, 2021, 52(4):381-392.XU Z X, YE C L. Simulation of urban flooding/waterlogging processes:Principle, models and prospects[J]. Journal of Hydraulic Engineering, 2021, 52(4):381-392.(in Chinese)
[25] 黄国如,王欣,黄维.基于InfoWorks ICM模型的城市暴雨内涝模拟[J].水电能源科学, 2017, 35(2):66-70, 60.HUANG G R, WANG X, HUANG W. Simulation of rainstorm water logging in urban area based on InfoWorks ICM model[J]. Water Resources and Power, 2017, 35(2):66-70, 60.(in Chinese)
[26] 北京市水科学技术研究院.北京发布首份城市积水内涝风险地图--北京市水科学技术研究院[J].北京水务, 2022(5):12.Beijing Institute of Water Science and Technology. Beijing releases the first urban waterlogging risk map-Beijing Water Science&Technology Institute[J]. Beijing Water, 2022(5):12.(in Chinese)
Outlines

/