Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics

Abstract

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters.

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Notes

  1. 1.

    First of all, the Yangtze River region experiences frequent heavy rainstorms. As the capital of six dynasties in ancient China, the capital of Jiangsu province and one of the cities with the largest population in the Yangtze River region, Nanjing city has been suffering from heavy rainstorms for a long time. For instance, the heavy rainstorm from June, 2016 to July, 2016 imposed great influence on Nanjing. The rainfall in 10 h on June 10th broke the record of daily rainfall within a century. The heavy rainstorm did not stop until June 27th, causing many regions submerged and subway outrage of multiple lines. Second, since the data of microlog and road traffic of the present paper are all from Nanjing, the paper chooses Nanjing as the case for research.

  2. 2.

    The disaster index came from Cheng et al. (2011) and the weights were determined by 3 rainstorm disaster experts of Jiangsu meteorological bureau.

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Acknowledgements

This research was supported by: The Natural Science Foundation of China (91546117, 71373131); Key Project of National Social and Scientific Fund Program (16ZDA047); The Ministry of Education Scientific Research Foundation for the returned overseas students (No. 2013-693, Ji Guo). This research was also supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Flagship Major Development of Jiangsu Higher Education Institutions.

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Correspondence to Xianhua Wu.

Appendix

Appendix

See Tables 9, 10 and 11.

Table 9 Urban rainstorm waterlogging reflecting table
Table 10 Waterlogging rating coding table
Table 11 Subjective emotion rating coding table

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Wu, X., Cao, Y., Xiao, Y. et al. Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics. Ann Oper Res 290, 865–896 (2020). https://doi.org/10.1007/s10479-018-2904-1

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Keywords

  • Microblogging data
  • Urban rainstorm and waterlogging disasters
  • Location-routing problem
  • NSGA-III algorithm