文章摘要
叶丁嘉1,王国复2,尹宜舟2,宋月旻1,孙劭2.基于灰色关联法的县域台风灾情评估方法初探[J].海洋气象学报,2019,39(1):68-75
基于灰色关联法的县域台风灾情评估方法初探
Study on typhoon disaster assessment at county level based on grey relational analysis
  
DOI:10.19513/j.cnki.issn2096-3599.2019.01.007
中文关键词: 台风灾害  历史灾害损失  灰色关联法  灾情评估
英文关键词: typhoon disaster  historical disaster loss  grey relational analysis  disaster assessment
基金项目:公益性行业(气象)专项(GYHY201406017); 国家自然科学基金项目(41505060)
作者单位
叶丁嘉1,王国复2,尹宜舟2,宋月旻1,孙劭2 (1. 中国海洋大学山东 青岛2661002. 国家气候中心北京 100081) 
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中文摘要:
   利用2000—2016年的县域台风灾害历史灾情数据,选取受灾人数、死亡人数、倒损房屋数、农作物受灾面积和直接经济损失为评估指标,在对各项指标进行分级的基础上,通过灰色关联分析法建立了以县域为单位的台风灾害综合灾损指标,对所选取市县的台风灾害损失情况进行了分级评估分析。结果表明,所选取的指标能够快速实现不同台风灾害、不同市县间的台风灾害严重程度的对比分析,具有实际应用价值。灾害等级分布结果显示,东南沿海市县为台风灾害多发区,浙江省、广东省和福建省的各市县为严重灾害(特大型、大型灾害)的易发区;8月、9月为严重灾害的多发时间。以不同登陆地点、不同影响范围的1210号“达维”台风和1513号“苏迪罗”台风为例,对灾情评估的合理性进行了验证。
英文摘要:
   According to the historical data of typhoon disasters in county regions from 2000 to 2016, a number of assessment indicators have been selected, including disaster affected population, death toll, the number of toppled and damaged houses, disaster affected crop areas, and direct economic loss. On the basis of grading these factors, an assessment index of typhoon-induced disasters in China at county level is established using grey relational analysis method, and the typhoon disasters in the selected cities and counties are graded and assessed. The results show that the indicators selected can provide comparative analysis of the extent of varied typhoon disasters and typhoon disasters in different cities and counties, making the index valuable for practical application. According to the grade distribution statistics, cities and counties in the southeast coast of China are prone to typhoon disasters, and cities and counties in Zhejiang Province, Guangdong Province, and Fujian Province are prone to serious (severe and extremely severe) disasters. Serious disasters are more likely to happen in August and September. Taking Typhoon DAMREY (2012) and SOUDELOR (2015), which are of different landing sites and ranges of influence, as examples, the reasonableness of disaster assessment is verified.
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