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Multi-hazard joint probability distribution model for wind speed, wind direction and rain intensity

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Abstract

Multiple disasters such as strong wind and torrential rain pose great threats to civil infrastructures. However, most existing studies ignored the dependence structure between them, as well as the effect of wind direction. From the dimension of the engineering sector, this paper introduces the vine copula to model the joint probability distribution (JPD) of wind speed, wind direction and rain intensity based on the field data in Yangjiang, China during 1971–2020. First, the profiles of wind and rain in the studied area are statistically analyzed, and the original rainfall amounts are converted into short-term rain intensity. Then, the marginal distributions of individual variables and their pairwise dependence structures are built, followed by the development of the trivariate joint distribution model. The results show that the constructed vine copula-based model can well characterize the dependence structure between wind speed, wind direction and rain intensity. Meanwhile, the JPD characteristics of wind speed and rain intensity show significant variations depending on wind direction, thus the effect of wind direction cannot be neglected. The proposed JPD model will be conducive for reasonable and precise performance assessment of structures subjected to multiple hazards of wind and rain actions.

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Authors and Affiliations

  1. School of Civil Engineering, Shandong University, Jinan, 250061, China

    WenZhe Bi, Li Tian & SiYao Zhang

  2. Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, 116024, China

    Chao Li

Authors
  1. WenZhe Bi
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  2. Li Tian
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  3. Chao Li
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  4. SiYao Zhang
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Corresponding authors

Correspondence to Li Tian or Chao Li.

Additional information

The authors acknowledge the China Meteorological Administration for providing the recorded wind and rain data. This work was supported by the National Natural Science Foundation of China (Grant Nos. 52178489 and 52078106) and the Young Scholars Program of Shandong University (Grant No. 2017WLJH33.

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The supporting information is available online at https://tech.scichina.com and https://link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Bi, W., Tian, L., Li, C. et al. Multi-hazard joint probability distribution model for wind speed, wind direction and rain intensity. Sci. China Technol. Sci. 66, 336–345 (2023). https://doi.org/10.1007/s11431-022-2210-3

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  • DOI: https://doi.org/10.1007/s11431-022-2210-3

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