Saini Yang, Guofan Yin, Xianwu Shi, Hao Liu, Ying Zou. Modeling the Adverse Impact of Rainstorms on a Regional Transport Network[J]. International Journal of Disaster Risk Science, 2016, 7(1): 77-87. doi: 10.1007/s13753-016-0082-9
Citation: Saini Yang, Guofan Yin, Xianwu Shi, Hao Liu, Ying Zou. Modeling the Adverse Impact of Rainstorms on a Regional Transport Network[J]. International Journal of Disaster Risk Science, 2016, 7(1): 77-87. doi: 10.1007/s13753-016-0082-9

Modeling the Adverse Impact of Rainstorms on a Regional Transport Network

doi: 10.1007/s13753-016-0082-9
Funds:

This study was sponsored by the National Science Foundation of China Youth Project (#41401599), the National Basic Research Program of China (2012CB955402), the Beijing Municipal Science and Technology Commission (Z151100002115040), the International Cooperation Project (2012DFG20710), and the International Center of Collaborative Research on Disaster Risk Reduction.

  • Available Online: 2021-04-26
  • Cities are centers of socioeconomic activities, and transport networks carry cargoes and passengers from one city to another. However, transport networks are influenced by meteorological hazards, such as rainstorms, hurricanes, and fog. Adverse weather impacts can easily spread over a network. Existing models evaluating such impacts usually neglect the transdisciplinary nature of approaches for dealing with this problem. In this article, a mesoscopic mathematical model is proposed to quantitatively assess the adverse impact of rainstorms on a regional transport network in northern China by measuring the reduction in traffic volume. The model considers four factors: direct and secondary impacts of rainstorms, interdependency between network components, and recovery abilities of cities. We selected the Beijing-Tianjin-Hebei region as the case study area to verify our model. Socioeconomic, precipitation, and traffic volume data in this area were used for model calibration and validation. The case study highlights the potential of the proposed model for rapid disaster loss assessment and risk reduction planning.
  • loading
  • Amin, M. 2000. Toward self-healing infrastructure systems. Computer 33(8): 44–53.
    Attoh-Okine, N.O., A.T. Cooper, and S. Mensah. 2009. Formulation of resilience index of urban infrastructure using belief functions. Systems Journal 3(2): 147–153.
    Baidu Map. n.d. http://map.baidu.com. Accessed 6 Mar 2015.
    Bloomfield, R., L. Buzna, P. Popov, K. Salako, and D. Wright. 2009. Stochastic modelling of the effects of interdependencies between critical infrastructures. Proceedings of the 4th international workshop, critical information infrastructures security, 30 September–2 October 2009, Bonn, 201–212.
    Buzna, L., K. Peters, and D. Helbing. 2006. Modelling the dynamics of disaster spreading in networks. Physica A: Statistical Mechanics and its Applications 363(1):132–140.
    Camacho, F.J., A. García, and E. Belda. 2010. Analysis of impact of adverse weather on freeway free-flow speed in Spain. Transportation Research Record: Journal of the Transportation Research Board 2169(1): 150–159.
    Chang, S.E., T.L. McDaniels, J. Mikawoz, and K. Peterson. 2007. Infrastructure failure interdependencies in extreme events: Power outage consequences in the 1998 ice storm. Natural Hazards 41(2): 337–358.
    Chang, S.E., T. McDaniels, J. Fox, R. Dhariwal, and H. Longstaff. 2014. Toward disaster-resilient cities: Characterizing resilience of infrastructure systems with expert judgments. Risk Analysis 34(3): 416–434.
    China News. n.d. News communication: 21 July storm caused economic losses of 11.64 billion yuan in Beijing. http://www.chinanews.com/gn/2012/07-25/4058908.shtml. Accessed 6 Mar 2015 (in Chinese).
    Chung, Y. 2012. Assessment of non-recurrent congestion caused by precipitation using archived weather and traffic flow data. Transport Policy 19(1): 167–173.
    Chung, E., O. Ohtani, H. Warita, M. Kuwahara, and H. Morita. 2006. Does weather affect highway capacity. In Proceedings of the symposium on highway capacity, Yokohama. http://its.iis.u-tokyo.ac.jp/pdf/5th%20ISHC%20Yokohama%202006%20Chung.pdf. Accessed 6 Mar 2015.
    Dehman, A. 2012. Effect of inclement weather on two capacity flows at recurring freeway bottlenecks. Transportation Research Record: Journal of the Transportation Research Board 2286(1): 84–93.
    Godschalk, D.R. 2003. Urban hazard mitigation: Creating resilient cities. Natural Hazards Review 4(3): 136–143.
    Guo, C., H. Xiao, H. Yang, and Q. Tang. 2015. Observation and modeling analyses of the macro-and microphysical characteristics of a heavy rain storm in Beijing. Atmospheric Research 156: 125–141.
    Henry, D., and J.E. Ramirez-Marquez. 2012. Generic metrics and quantitative approaches for system resilience as a function of time. Reliability Engineering & System Safety 99: 114–122.
    Hoel, L.A., N.J. Garber, and A.W. Sadek. 2007. Transportation infrastructure engineering: A multimodal integration. Chicago: Thomson Nelson.
    Jiang, X., H. Yuan, M. Xue, X. Chen, and X. Tan. 2014. Analysis of a heavy rainfall event over Beijing during 21–22 July 2012 based on high resolution model analyses and forecasts. Journal of Meteorological Research 28: 199–212.
    Johansson, J., and H. Hassel. 2010. An approach for modelling interdependent infrastructures in the context of vulnerability analysis. Reliability Engineering & System Safety 95(12): 1335–1344.
    Munson, B.R., D. Young, and T.H. Okiishi. 2006. Fundamentals of fluid mechanics, 5th edn. New York: Wiley.
    National Bureau of Statistics of China. n.d. National data. http://data.stats.gov.cn/. Accessed 6 Mar 2015 (in Chinese).
    Rahmstorf, S., and D. Coumou. 2011. Increase of extreme events in a warming world. Proceedings of the National Academy of Sciences of the United States of America 108(44): 17905–17909.
    Rinaldi, S.M., J.P. Peerenboom, and T.K. Kelly. 2001. Identifying, understanding, and analyzing critical infrastructure interdependencies. Control Systems 21(6): 11–25.
    Saberi, M., and R.L. Bertini. 2010. Empirical analysis of the effects of rain on measured freeway traffic parameters. 89th Annual Meeting of the Transportation Research Board, Washington, DC. http://trid.trb.org/view.aspx?id=910448. Accessed 6 Mar 2015.
    Santos, J.R., L.C. Herrera, K.D.S. Yu, S.A.T. Pagsuyoin, and R.R. Tan. 2014. State of the art in risk analysis of workforce criticality influencing disaster preparedness for interdependent systems. Risk Analysis 34(6): 1056–1068.
    Smith, B.L., K.G. Byrne, R.B. Copperman, S.M. Hennessy, and N.J. Goodall. 2004. An investigation into the impact of rainfall on freeway traffic flow. 83rd Annual Meeting of the Transportation Research Board, Washington, DC. http://people.virginia.edu/~njg2q/TRB_2004.pdf. Accessed 6 Mar 2015.
    Su, B., H. Huang, and Y. Li. 2016. Integrated simulation method for waterlogging and traffic congestion under urban rainstorms. Natural Hazards 81(1): 23–40.
    Weng, J., L. Liu, and J. Rong. 2013. Impacts of snowy weather conditions on expressway traffic flow characteristics. Discrete dynamics in nature and society 2013. Article 791743.
    World Meteorological Organization (WMO). 2011. WMO statement on the status of the global climate in 2010. WMO-No. 1074. http://www.wmo.int/pages/prog/wcp/wcdmp/statement/documents/1074_en.pdf. Accessed 6 Mar 2015.
    Yang, S.N., J.Y. Ye, X.C. Zhang, and H. Liu. 2012. Study of the impact of rainfall on freeway traffic flow in Southeast China. International Journal of Critical Infrastructures 8(2/3): 230–241.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (46) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return