Zhuang Yao, Bao Ruijuan, Zhang Rongyan, et al. Refined risk assessment of tropical cyclone disasters in Fujian. J Appl Meteor Sci, 2022, 33(3): 319-328. DOI:  10.11898/1001-7313.20220306.
Citation: Zhuang Yao, Bao Ruijuan, Zhang Rongyan, et al. Refined risk assessment of tropical cyclone disasters in Fujian. J Appl Meteor Sci, 2022, 33(3): 319-328. DOI:  10.11898/1001-7313.20220306.

Refined Risk Assessment of Tropical Cyclone Disasters in Fujian

DOI: 10.11898/1001-7313.20220306
  • Received Date: 2021-12-23
  • Rev Recd Date: 2022-02-25
  • Publish Date: 2022-05-31
  • Tropical cyclones have brought huge economic losses to Fujian Province. In order to achieve dynamic monitoring and early warning of wind and rain disaster risks caused by tropical cyclones, the disaster-causing mechanism of tropical cyclones is analyzed. A refined risk assessment method is developed to meet the needs of real-time decision-making on disaster prevention, mitigation, and reducing the economic losses caused by tropical cyclones.Through multiple rounds of rationality tests, 7 rain-induced disaster factors and 4 wind-induced disaster factors are picked out based on the tropical cyclone wind and rain data of 66 national meteorological stations from 1981 to 2021. And then, the risk assessment model of tropical cyclone disaster factors is established using the range standardization and correlation coefficient objective weighting method, and the risk level is divided by the natural breakpoint method and the disaster impacts.The results show that the risk assessment index system of disaster factors is reasonable, and the spatial distribution of disaster risk is investigated. The high rain risk areas are located along the coast, and the rain risk of Nanping and Sanming areas is low; the high wind risk area is significantly narrower than the high rain risk area, and the risk level decreases fast inland. Among them, the coastal areas from Luoyuan Bay to Chongwu are protected by the terrain barrier of Taiwan, and the risk is one level lower than that of the north and south parts of the coast. In addition, after the tropical cyclone lands on the east coast of Guangdong and moves northward, it often stays in the low-pressure cloud over the west of Fujian, resulting in a high risk area in the northwest of Fujian. Based on the spatial distribution of a single tropical cyclone, the disaster situation and the encrypted wind and rain data of regional stations, using the function of GIS and combining several typical tropical cyclone cases, a reasonable threshold for hazard classification is designed. It is targeted, especially urban waterlogging and mountain torrent disasters, which are basically consistent with the disaster situation, and provide more valuable reference information for meteorological disaster decision-making services.
  • Fig. 1  Tropical cyclone warning zone for Fujian

    Fig. 2  Risk distribution of rain induced, wind induced, wind and rain induced

    Fig. 3  Risk distribution of disaster factors by tropical cyclone Maria

    Fig. 4  Risk distribution of disaster factors by tropical cyclones with rain disasters

    Fig. 5  Risk distribution of disaster factors by tropical cyclone Saomai with wind disaster

    Fig. 6  Risk distribution of disaster factors for tropical cyclones with both wind and rain

    Table  1  Risk assessment index system of tropical cyclone disaster-causing factors

    等级 降水因子 大风因子
    第1级 雨危险性 风危险性
    第2级(气象要素) 降水 风速
    第3级(因子) 过程日最大降水量(单站), 过程累积最大降水量(单站), 过程1 h最大降水量, 过程3 h最大降水量, 过程暴雨站日数, 过程大暴雨站日数, 过程特大暴雨站日数 过程日最大风速(单站), 过程日极大风速(单站), 过程最大风速不低于8级站日数, 过程极大风速不低于12级站日数
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    Table  2  Risk assessment classification of disaster-causing factors for tropical cyclone disaster at county level

    等级 含义 降水因子 大风因子 风雨综合因子
    1 低危险 0~0.2060 0~0.0995 0~0.1255
    2 较低危险 0.2061~0.2967 0.0996~0.1954 0.1256~0.2158
    3 中等危险 0.2968~0.4017 0.1955~0.2853 0.2159~0.3209
    4 较高危险 0.4018~0.5230 0.2854~0.4495 0.3210~0.4490
    5 高危险 0.5231~1 0.4496~1 0.4491~1
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    Table  3  Risk assessment classification of disaster-causing factors for tropial cyclone disaster at township level

    等级 含义 降水因子 大风因子 风雨综合因子
    1 低危险 0~0.2252 0~0.2124 0~0.1051
    2 较低危险 0.2253~0.3206 0.2125~0.2767 0.1052~0.2041
    3 中等危险 0.3207~0.4312 0.2768~0.3300 0.2042~0.2917
    4 较高危险 0.4313~0.5413 0.3301~0.4039 0.2918~0.4078
    5 高危险 0.5414~1 0.4040~1 0.4079~1
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  • [1]
    Chen X. Vulnerability diagnosis and assessment of typhoon disaster system at coastal regions, a case study of Fujian Province. J Catastrophology, 2007, 22(3): 6-10. doi:  10.3969/j.issn.1000-811X.2007.03.002
    [2]
    Li X, Zhang L. Formation mechanism and microphysics characteristics of heavy rainfall caused by northward-moving typhoon. J Appl Meteor Sci, 2022, 33(1): 29-42. doi:  10.11898/1001-7313.20220103
    [3]
    Yang S N, Duan Y H. Extremity analysis on the precipitation and environmental field of Typhoon Rumbia in 2018. J Appl Meteor Sci, 2020, 31(3): 290-302. doi:  10.11898/1001-7313.20200304
    [4]
    Cheng Z Q, Lin L X, Yang G J, et al. Rapid intensification and associated large-scaled circulation of super Typhoon Rammasun in 2014. J Appl Meteor Sci, 2017, 28(3): 318-326. doi:  10.11898/1001-7313.20170306
    [5]
    Dilley M, Chen R S, Deichmann U, et al. Natural Disaster Hot- spots: A Risk Analysis Synthesis Report. Washington DC: Hazard Management Unit, World Bank, 2005: 1-132.
    [6]
    Wei Z J, Sui G J, Tang D L. An Overview of assessment and approaches on typhoon disaster. J Catastrophology, 2012, 27(4): 107-113. doi:  10.3969/j.issn.1000-811X.2012.04.023
    [7]
    Yin J, Dai E F, Wu S H. Integrated risk assessment and zoning of typhoon disaster in China. Sci Geogr Sinica, 2013, 33(11): 1370-1376. https://www.cnki.com.cn/Article/CJFDTOTAL-DLKX201311012.htm
    [8]
    Han J, Dai E F. System-dynamics-based disaster reduction decision for typhoon disaster. J Catastrophology, 2021, 36(2): 220-227;234. doi:  10.3969/j.issn.1000-811X.2021.02.038
    [9]
    Ye D J, Wang G F, Yin Y Z, et al. Study on typhoon disaster assessment at county level based on grey relational analysis. J Marine Meteor, 2019, 39(1): 68-75. https://www.cnki.com.cn/Article/CJFDTOTAL-SDQX201901007.htm
    [10]
    He L F, Chen S, Guo Y Q. Observation characteristics and synoptic mechanisms of Typhoon Lekima extreme rainfall in 2019. J Appl Meteor Sci, 2020, 31(5): 513-526. doi:  10.11898/1001-7313.20200501
    [11]
    Chen Y L, Zhu X C, Hu B, et al. Investigate on the pre-assessment of typhoon disaster in Ningbo based on BP neural network. Trans Atmos Sci, 2018, 41(5): 668-675. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201805010.htm
    [12]
    Tan R P, Zhang W D. Multiple attribute decision making method based on DEMATEL and fuzzy distance of trapezoidal fuzzy neutrosophic numbers and its application in typhoon disaster evaluation. J Intell Fuzzy Syst, 2020, 39(3): 3413-3439. doi:  10.3233/JIFS-191758
    [13]
    Zhang R Y, Xu Z H, You L J, et al. Wind and rainfall features and risk assessment of tropical cyclone in Fujian. J Appl Meteor Sci, 2012, 23(6): 672-682. doi:  10.3969/j.issn.1001-7313.2012.06.004
    [14]
    Chen K J, Chen Y Y, Chen J. Risk assessment and analysis of typhoon disaster in east Guangdong in the period 1989-2017. Res Soil Water Conserv, 2019, 26(3): 362-366;372. https://www.cnki.com.cn/Article/CJFDTOTAL-STBY201903056.htm
    [15]
    Kong L S, Zhang X Z. Sensitive experiments on reconstruction model of historical typhoon wind field in the Northwest Pacific Ocean. J Appl Meteor Sci, 2022, 33(1): 56-68. doi:  10.11898/1001-7313.20220105
    [16]
    Zhu J, Lu Y, Li G P, et al. Risk assessment of typhoon disaster in Fujian Provice of each country. J Catastrophology, 2017, 32(3): 204-209. doi:  10.3969/j.issn.1000-811X.2017.03.034
    [17]
    Lin R X, Ye J Y. Visualization analysis of the typhoon researches in China. Journal of Institute of Disaster Prevention, 2020, 22(1): 38-45. doi:  10.3969/j.issn.1673-8047.2020.01.006
    [18]
    Zhang Y, Li S S, Chen H, et al. Evaluation of typhoon disaster risk in Guangdong Province. J Trop Meteor, 2017, 33(2): 281-288. https://www.cnki.com.cn/Article/CJFDTOTAL-RDQX201702015.htm
    [19]
    Yu X B, Yu X R, Ji Z H, et al. Risk assessment and analysis of typhoon disaster in China's south-east coastal areas-based on information diffusion theory. J Catastrophology, 2019, 34(1): 73-77. doi:  10.3969/j.issn.1000-811X.2019.01.015
    [20]
    Liu H X, Lu Y J, Wang M, et al. Risk assessment of extreme typhoon disasters based on information diffusion technology. J Trop Ocean, 2020, 39(3): 31-41. https://www.cnki.com.cn/Article/CJFDTOTAL-RDHY202003004.htm
    [21]
    Zhou Y F, Cheng X N, Cai J, et al. Study on comprehensive risk assessment of typhoon disasters. China Public Security(Academy Editon), 2013(1): 31-37. doi:  10.3969/j.issn.1672-2396.2013.01.008
    [22]
    Li Z Y, Xu Y W, Wang J Y, et al. Evaluation model of meteorological disaster loss with normalized indices based on projection pursuit regression. J Appl Meteor Sci, 2016, 27(4): 480-487. doi:  10.11898/1001-7313.20160411
    [23]
    Yang T, Duan Y H, Xu J, et al. Simulation of the urbanization impact on precipitation of landfalling tropical cyclone Nida(2016). J Appl Meteor Sci, 2018, 29(4): 410-422. doi:  10.11898/1001-7313.20180403
    [24]
    Zhang Y H, Fan G Z, Ma Q Y, et al. The evaluation model of typhoon disaster influence on Zhejiang Province. J Appl Meteor Sci, 2009, 20(6): 772-776. doi:  10.3969/j.issn.1001-7313.2009.06.017
    [25]
    Wei Z J, Ma H L, Tang D L. Trend assessment of typhoon disasters based on the improved entropy method. J Catastrophology, 2017, 32(3): 7-11. doi:  10.3969/j.issn.1000-811X.2017.03.002
    [26]
    Lu Y J, Liu H X, Wang M. Typhoon disaster risk assessment based on combined weights and fuzzy stochastic methods. Fuzzy Systems and Mathematicis, 2020, 34(2): 151-163. https://www.cnki.com.cn/Article/CJFDTOTAL-MUTE202002017.htm
    [27]
    Xu H S, Lian J J, Bin L L, et al. Joint distributionof multiple typhoon hazard factors. Sci Geogr Sinica, 2018, 38(12): 2118-2124. https://www.cnki.com.cn/Article/CJFDTOTAL-DLKX201812021.htm
    [28]
    Niu H Y, Liu M, Lu M, et al. Risk assessment of typhoon hazard factors in China coastal areas during last 20 years. Journal of East China Normal University(Nat Sci Ed), 2011, 31(6): 20-25;35. doi:  10.3969/j.issn.1000-5641.2011.06.003
    [29]
    Liu F T, Xu E Q. Spatio-temporal correlation analysis of typhoon characteristics and disaster assessment in Hainan Province. J Catastrophology, 2020, 35(2): 217-223. doi:  10.3969/j.issn.1000-811X.2020.02.039
    [30]
    Zhang Z W, Zhang J H, Zhao Z Z, et al. Analysis of risks in Hainan Island typhoon hazard factor based on GIS. J Anhui Agri Sci, 2011, 39(11): 6587-6590. doi:  10.3969/j.issn.0517-6611.2011.11.112
    [31]
    Gong Z W, Hu L. Influence factor analysis of typhoon disaster assessment. J Nat Disa, 2015, 24(1): 203-213. https://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH201501026.htm
    [32]
    Zhang L J, Liu M, Lu M, et al. The hazard assessment of typhoon in southeast coastal areas of China. Yangtze River, 2010, 41(6): 81-83;91. doi:  10.3969/j.issn.1001-4179.2010.06.021
    [33]
    Blaikie P, Cannon T, Davis I, et al. At Risk: Natural Hazard, People's Vulnerability and Disasters. London: Routledgei, 1994: 1-210.
    [34]
    Li B N. Fuzzy Mathematics and Application. Hefei: Hefei University of Technology Press, 2007.
    [35]
    Cai Y L, Cao S S, Du M Y, et al. Estimation and analysis of driving factors of total AHF in prefecture-level of China. J Geo-info Sci, 2021, 23(3): 405-418. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXX202103006.htm
    [36]
    Lin R X, Wang X. Preliminary study about Guangdong flood disaster risk based on ArcGIS. Guangdong Water Resources and Hydropower, 2016(5): 41-45. https://www.cnki.com.cn/Article/CJFDTOTAL-GDSD201605011.htm
    [37]
    Zheng X J, Lu N M, Luo J N, et al. Analysis of the characteristics of water vapor image of rainstorm in Fujian Province on 8 August 1996. Marine Forecasts, 1997, 14(4): 51-58. https://www.cnki.com.cn/Article/CJFDTOTAL-HYYB704.006.htm
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    • Received : 2021-12-23
    • Accepted : 2022-02-25
    • Published : 2022-05-31

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