台风灾害多元致灾因子联合分布研究

doi:10.13249/j.cnki.sgs.2018.12.021

摘要/Abstract

摘要：

以沿海城市海口为例,运用三维Copula函数构建台风灾害多元致灾因子联合分布模型,开展多元致灾因子相互作用下的台风灾害事件联合重现期和失效概率的分析,提出全面评估台风灾害影响的研究思路。结果表明：三维Gumbel Copula函数能够合理描述台风灾害多元致灾因子之间的联合分布,以单变量作为设计依据会低估具有一定严重程度的台风灾害发生频次,相对于单变量重现期和二维联合重现期,三变量联合重现期的计算结果更加贴近实际情况。防台措施设计标准的制定应全面考虑台风灾害多元致灾因子,且应充分考虑各致灾因子间的相互作用以及设计期内的失效概率。研究成果可为中国沿海省市的可持续发展以及减灾、防灾政策的制定等提供重要的科学依据。

关键词: 台风灾害, 致灾因子, 联合分布, Copula函数

Abstract:

Coastal cities are highly vulnerable to typhoons due to the special geographical location. A typhoon is often accompanied by strong winds, heavy rains and high tide events. Strong winds, heavy rains and high tides are three disaster-causing factors of typhoon. Current studies of typhoon most focus on univariate and bivariate frequency analysis of disaster-causing factors. If only the joint characteristics of univariate or bivariate functions are analyzed, the factual hazard mechanism of typhoon in coastal zones cannot be explored. However, until now, there is some lack of knowledge about multivariate joint probability distribution of winds, rainfall and storm tides. The joint probability distribution can reveal the occurrence probability of multiple variables. Therefore, it is meaningful to investigate the trivariate joint probability distribution of winds, rainfall and storm tides for typhoon disaster management in coastal zones. Taking the Haikou city as an example, this paper uses the three-dimensional Copula function to construct the joint distribution model of multiple hazard factors of typhoon disasters and analyzes the joint return period of typhoon disasters and failure probability under the interaction of multiple hazard factors. The results show that the three-dimensional Gumbel Copula function can reasonably describe the joint distribution of multiple hazard factors of typhoon disasters. Multivariate return period analysis can provide more adequate and comprehensive information about risks than univariate return period analysis. Univariate design analysis will underestimate the occurrence frequency of typhoon disasters with a certain degree of severity, and the design standard of prevention measures should consider the multiple hazard factors of typhoon disasters comprehensively, and give full consideration to the failure probability during the design period. The research results can provide important scientific evidences for the sustainable development of China's coastal provinces and cities and the formulation of disaster prevention and disaster prevention policies.

Key words: typhoon, hazard factors, joint distribution, Copula function

中图分类号:

P458.1+24

许红师, 练继建, 宾零陵, 徐奎. 台风灾害多元致灾因子联合分布研究[J]. 地理科学, 2018, 38(12): 2118-2124.

Hongshi Xu, Jijian Lian, Lingling Bin, Kui Xu. Joint Distribution of Multiple Typhoon Hazard Factors[J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(12): 2118-2124.

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分布	Gaussian Copula	Student’s t-Copula	Gumbel Copula
K-S	0.149	0.149	0.118
OLS	0.048	0.046	0.046
AIC	-135.353	-138.304	-142.219

单变量重现期（a）	风速 T（m/s）	降雨 H(mm)	潮位 Z(m)	联合重现期（a）
单变量重现期（a）	风速 T（m/s）	降雨 H(mm)	潮位 Z(m)	T-H	T-Z	H-Z	T-H-Z
5	40.56	95.73	2.94	1.33	1.34	1.51	1.06
10	43.92	132.14	3.16	2.51	2.55	2.74	1.90
20	47.08	167.93	3.37	4.88	4.97	5.14	3.58
50	51.07	214.64	3.65	12.02	12.26	12.30	8.53
100	53.98	249.68	3.85	23.91	24.39	24.19	16.70