| 1,560 | 5 | 422 |
| 下载次数 | 被引频次 | 阅读次数 |
【目的】科学评估灾害风险对提升区域灾害防御能力、针对性地制定防灾抗灾减灾措施具有重要意义。【方法】以福州市为例，基于地面气象观测资料、历史台风灾害数据，以及1 km网格的人口、经济、建筑物等承灾体调查数据，运用Copula函数和风险矩阵模型，综合评估不同重现期情景下台风大风和台风暴雨复合致灾风险。【结果】结果表明：(1)千年一遇情景下，闽清县风雨设计值最小，复合重现期对应设计值为26.03 m/s与463.72 mm;罗源县和长乐区复合重现期对应设计值最大，分别为57.78 m/s、1 173.87 mm与65.42 m/s、1 094.27 mm。(2)随着重现期水平提高，致灾因子危险性自东部沿海向西部山区增大。承灾体中高、高脆弱性地区主要分布于福州市主城区以及东南临海乡镇，与人口、经济和建筑物的集中度密切相关。(3)福州市台风灾害风险大致呈“东高西低”格局，随着重现期水平提高，灾害风险由东北、东南部沿海向内陆地区提高，福州市主城区、长乐区、罗源县、福清市风险高于其余地区。(4)极端灾害条件下(如千年一遇),中高、高风险区主要位于福州市东北、东南部与主城区，占全市总面积的34.5%。【结论】福州市台风灾害风险大致呈“东高西低”格局，随着重现期水平提高，灾害风险由东北、东南部沿海向内陆地区提高，极端灾害条件下(如千年一遇),中高、高风险区主要位于福州市东北、东南部与主城区。
Abstract：[Objective] Scientific evaluation of disaster risks is crucial for improving regional disaster prevention capabilities and formulating targeted measures for disaster prevention, response, and mitigation. [Methods] Taking Fuzhou City as an example, the ground meteorological observations, historical typhoon disaster data, and 1 km-grid survey data of population, economy, buildings, and other disaster-bearing bodies were utilized. Then, the Copula function and risk matrix model were used to assess the compound disaster risks from typhoon-induced gales and storms under different return periods. [Results] The results indicated that:(1) under the scenario of 1 000-year compound return period, the design values of typhoon extreme wind speed and cumulative rainfall in Minqing County were the smallest, with the values being 26.03 m/s and 463.72 mm, respectively. Luoyuan County and Changle District showed the maximum design values under this compound return period, reaching 57.78 m/s and 1 173.87 mm, and 65.42 m/s and 1 094.27 mm, respectively.(2) As the level of return period increased, the hazard levels of disaster-inducing factors exhibited an increasing trend from the eastern coastal areas to the western mountainous areas. Moderately high and high vulnerability zones of disaster-bearing bodies were primarily distributed in the main urban area of Fuzhou City and the southeastern coastal towns, demonstrating strong spatial correlation with the concentration of population, economy, and buildings.(3) The risk of typhoon disasters in Fuzhou City generally exhibited a pattern of “high in the east and low in the west”. As the level of return period increased, disaster risks escalated from the northeastern and southeastern coastal areas to inland areas. The risks in the main urban area of Fuzhou City, Changle District, Luoyuan County, and Fuqing City were higher than other regions.(4) Under the conditions of extreme disasters(such as 1 000-year return period), medium-high and high-risk zones were mainly concentrated in the northeast, southeast, and main urban area of Fuzhou City, accounting for 34.5% of the total area of the city. [Conclusion] The risk of typhoon disasters in Fuzhou City generally exhibits a pattern of “high in the east and low in the west”. As the level of return period increases, the disaster risk gradually intensifies from the northeastern and southeastern coastal areas to inland areas. Under the conditions of extreme disasters(such as 1 000-year return period), medium-high and high-risk zones are mainly distributed in the northeast, southeast, and main urban area of Fuzhou City.
[1] BALAGURU K,FOLTZ G R,LEUNG L R,et al.Global warming-induced upper-ocean freshening and the intensification of super typhoons [J].Nature Communications,2016,7:13670.
[2] 梁必骐，梁经萍，温之平.中国台风灾害及其影响的研究[J].自然灾害学报，1995,4(1):84-91.LIANG Biqi,LIANG Jingping,WEN Zhiping.Research on typhoon disasters and their effects in China [J].Journal of Natural Disasters,1995,4 (1):84-91.
[3] 殷洁，戴尔阜，吴绍洪.中国台风灾害综合风险评估与区划[J].地理科学，2013,33(11):1370-1376.YIN Jie,DAI Erfu,WU Shaohong.Comprehensive risk assessment and zoning of typhoon disasters in China [J].Geographic Sciences,2013,33 (11):1370-1376.
[4] 周紫蕊，廖卫红，雷晓辉，等.基于 InfoWorks ICM 的城市河网调控与分析：以福州市仓山区龙津阳岐片区为例[J].南水北调与水利科技(中英文),2023,21(4):770-779.ZHOU Z R,LIAO W H,LEI X H,et al.InfoWorks ICM-based urban river network regulation and analysis:A case study of Longjin Yangqi area in Cangshan District,Fuzhou City[J].South-to-North Water Transfers and Water Science & Technology,2023,21(4):770-779.
[5] 石先武，方伟华.1949—2010年西北太平洋热带气旋时空分布特征分析[J].北京师范大学学报(自然科学版),2015(3):287-292.SHI Xianwu,FANG Weihua.Spatial and temporal distribution characteristics analysis of tropical cyclones in the northwest Pacific from 1949 to 2010 [J].Journal of Beijing Normal University(Natural Science),2015 (3):287-292.
[6] 刘倩，高路，赵鹏，等.2000—2016年中国热带气旋灾害时空特征研究[J].中国防汛抗旱，2020,30(5):50-57.LIU Qian,GAO Lu,ZHAO Peng,et al.Study on the spatiotemporal characteristics of tropical cyclone disasters in China from 2000 to 2016 [J].China Flood and Drought Management,2020,30 (5):50-57.
[7] 向纯怡，高拴柱，刘达.2021年西北太平洋和南海台风活动概述[J].海洋气象学报，2022,42(1):39-49.XIANG Chunyi,GAO Shuanzhu,LIU Da.Overview of typhoon activities in the northwest Pacific and South China Sea in 2021 [J].Journal of Marine Meteorology 2022,42 (1):39-49.
[8] 杨慧娟，李宁，雷飏.我国沿海地区近54a台风灾害风险特征分析[J].气象科学，2007,27(4):413-418.YANG Huijuan,LI Ning,LEI Yang.Risk analysis of typhoon disasters in coastal areas of China in the past 54 years [J].Journal of Meteorological Science,2007,27(4):413-418.
[9] 王然，连芳，余瀚，等.基于孕灾环境的全球台风灾害链分类与区域特征分析[J].地理研究，2016,35(5):836-850.WANG Ran,LIAN Fang,YU Han,et al.Classification and regional characteristics analysis of global typhoon disaster chain based on pregnancy disaster environment [J].Journal of Geographical Research 2016,35(5):836-850.
[10] 张鹏，张云霞，汪洋，等.1978—2020年中国台风灾害灾情时空分布格局及影响因素分析[J].热带地理，2024,44(6):1047-1063.ZHANG Peng,ZHANG Yunxia,WANG Yang,et al.Analysis of the spatiotemporal distribution pattern and influencing factors of typhoon disasters in China from 1978 to 2020 [J].Tropical Geography,2024,44 (6):1047-1063.
[11] CHEN T,CHEN S,ZHOU M,et al.Northward shift in landfall locations of tropical cyclones over the western North Pacific during the last four decades[J].Advances in Atmospheric Sciences,2022,39(2):304-319.
[12] CHA Y,CHOI J W,AHN J B.Interdecadal changes in the genesis activity of the first tropical cyclones over the western North Pacific from 1979 to 2016[J].Climate Dynamics,2022,60(5/6):1885-1906.
[13] 李铮，邱兰兰，王伟，等.北上台风时空变化特征及其与ENSO的关系[J].热带地理，2024,44(6):973-986.LI Zheng,QIU Lanlan,WANG Wei,et al.Spatiotemporal variation characteristics of northbound typhoons and their relationship with ENSO [J].Tropical Geography,2024,44 (6):973-986.
[14] QIN L J,ZHU L Y,LIAO X L,et al.Recent northward shift of tropical cyclone economic risk in China[J].Natural Hazards,2024,1(1).https://www.nature.com/articles/s44304-024-00008-9.
[15] 杨晓亮，杨敏，隆璘雪，等.影响环渤海地区的北上台风特征及其各类典型大暴雨过程分析[J].海洋预报，2021,38(4):99-106.YANG Xiaoliang,YANG Min,LONG Linxue,et al.Characteristics of northward typhoons affecting the Bohai Rim area and analysis of various typical heavy rainstorm processes [J].Marine Forecasts,2021,38 (4):99-106.
[16] 李颖，金茹，许娈，等.基于路径与环境场最优赋权的致灾相似台风检索方法研究[J].水利水电技术(中英文),2023,54 (7):14-26.LI Ying,JIN Ru,XU Luan,et al.Study on the optimal weighting impact of typhoon track and environmental field in similar typhoon retrieval model for similar disasters[J].Water Resources and Hydropower Engineering,2023,54(7):14-26.
[17] 应急管理部.2023 年全国自然灾害基本情况.(2024-01-20)[2024-03-25].https://www.mem.gov.cn/xw/yjglbgzdt/202401/ t20240120_475697.shtml.Emergency Management Department of the People′s Republic of China.Basic situation of natural disasters in China in 2023.(2024-01-20) [2024-03-25].https:// www.mem.gov.cn/xw/yjglbgzdt/202401/t20240120_475697.shtml.
[18] YIN J,YIN Z,XU S.composite risk assessment of typhoon-induced disaster for China′s coastal area[J].Natural Hazards,2013,69(3):1423-1434.
[19] LU Y,REN F,ZHU W.Risk zoning of typhoon disasters in Zhejiang Province,China[J].Natural Hazards and Earth System Sciences,2018,11:2921-2932.
[20] WANG K,YANG Y,RENIERS G,et al.A study into the spatiotemporal distribution of typhoon storm surge disasters in China[J].Natural Hazards,2021,108(1):1237-1256.
[21] 王章立，邱奕翔，杨光，等.台风“格美”暴雨洪水防御实践与思考[J].水利发展研究，2025,25(1):43-47,55.WANG Zhangli,QIU Yixiang,YANG Guang,et al.Practice and experience of typhoon “Gemei”rainstorm flood prevention[J].Water Resources Development Research,2025,25(1):43-47,55.
[22] TAO S,HUA Y,DONG S.Hazard risk assessment of tropical cyclones based on joint probability theory[J].海洋学报：英文版，2023,42(6):89-99.
[23] 金玲，张欣馨，陈佩燕，等.台风影响下的学校风灾风险评估模型研究：以浦东新区部分沿海学校为例[J].灾害学，2022,37(2):54-59.JIN Ling,ZHANG Xinxin,CHEN Peiyan,et al.Study on the wind disaster risk assessment model of schools under typhoon impact:A case study of some coastal schools in Pudong New Area [J].Journal of Catastrophology,2022,37 (2):54-59.
[24] 陈勇全.华南沿海海上风电的台风大风风险评估研究[D].昆明：云南财经大学，2023.CHEN Yongquan.Research on Typhoon and Gale Risk Assessment of Offshore Wind Power along the South China Coast [D].Kunming:Yunnan University of Finance and Economics,2023.
[25] 李颖，杨程，方伟华，等.台风灾害输电线路杆塔脆弱性与风险评估：以浙江省为例[J].热带地理，2024,44(6):1113-1126.LI Ying,YANG Cheng,FANG Weihua,et al.Vulnerability and risk assessment of transmission line towers in typhoon disasters:A case study of Zhejiang Province [J].Tropical Geography,2024,44 (6):1113-1126.
[26] 罗玲，娄小芬，傅良，等.ECMWF极端降水预报指数在华东台风暴雨中的应用研究[J].气象，2019,45(10):1382-1391.LUO Ling,LOU Xiaofen,FU Liang,et al.The application of ECMWF extreme precipitation forecast index in storm rainfall over East China observatory [J].Meteorological Monthly,2019,45 (10):1382-1391.
[27] WANG Xu,ZHANG Lifeng,WANG Yuan,et al.Influence of typhoons in the western pacific on summer precipitation in the eastern Northwest China [J].Chinese Journal of Atmospheric Sciences,2024,48(2):507-520.
[28] QIN Xiaochen,WU Yilong,LIN Tianshu,et al.Urban flood dynamic risk assessment based on typhoon rainfall process:A case study of typhoon“Lupit”(2109) in Fuzhou,China[J].Remote Sensing,2023,15:3116.
[29] 张炜月，林昕，郑凌琳.福州地区近20年台风降水特征分析[J].海峡科学，2020(5):3-8.ZHANG Weiyue,LIN Xin,ZHENG Linglin.Analysis of typhoon precipitation characteristics in Fuzhou area in the past 20 Years [J].Strait Science,2020 (5):3-8.
[30] 林芳.浅议福建福州市2013—2016年台风洪涝灾害[J].中国防汛抗旱，2018,28(3):41-44.LIN Fang.A brief discussion on typhoon and flood disasters in Fuzhou City,Fujian Province from 2013 to 2016 [J].China Flood and Drought Management 2018,28 (3):41-44.
[31] 张晓宇，韦波，杨昊宇，等.基于GIS的广东省台风灾害风险性评价[J].热带气象学报，2018,34(6):783-790.ZHANG Xiaoyu,WEI Bo,YANG Haoyu,et al.Risk assessment of typhoon disasters in Guangdong Province based on GIS [J].Journal of Tropical Meteorology,2018,34 (6):783-790.
[32] 潘金兰，徐庆娟，刘合香.基于AHP-TOPSIS最优组合赋权的台风灾害风险评估[J].南宁师范大学学报：自然科学版，2021,38(1):60-67.PAN Jinlan,XU Qingjuan,LIU Hexiang.Typhoon disaster risk assessment based on AHP-TOPSIS optimal combination weighting [J].Journal of Nanning Normal University:Natural Science,2021,38 (1):60-67.
[33] WANG Zhenkang,XIA Nan,ZHAO Xin,et al.Comprehensive risk assessment of typhoon disasters in China′s coastal areas based on multi-source geographic big data.Science of The Total Environment,2024,926:171815.
[34] 杨奕杰.基于近20年历史数据的中国沿海城市台风灾害风险评估[D].上海：上海海洋大学，2022.YANG Yijie.Risk Assessment of Typhoon Disasters in Coastal Cities of China based on Historical Data from the Past 20 Years [D].Shanghai:Shanghai Ocean University,2022.
[35] 福州市人民政府.2022 年福州市行政区划情况[EB/OL].(2023-09-20)[2024-07-10].https://www.fuzhou.gov.cn/zgfzzt/zjrc/qhyg/202309/t20230920_4681575.htm.Fuzhou Municipal People′s Government.Administrative divisions of Fuzhou City in 2023 and 2022[EB/OL] (2023-09-20)[2024-07-10].https://www.fuzhou.gov.cn/zgfzzt/zjrc/qhyg/202309/t2023 0920_4681575.htm.
[36] 福州市人民政府.2023.2022 年福州市自然资源情况[EB/OL].(2023-09-11) [2024-07-10].https://www.fuzhou.gov.cn/zgfzzt/zjrc/zrdl/202309/t20230911_4671377.htm.Fuzhou Municipal People′s Government.Natural Resources Situation of Fuzhou City in 2023 and 2022[EB/OL] (2023-09-11) [2024-07-10].https://www.fuzhou.gov.cn/zgfzzt/zjrc/zrdl/202309/t2023 0911_4671377.htm.
[37] 戴志忠.福州地区水文特性分析[J].水利科技，2004(3):9-11.DAI Zhizhong.Analysis of hydrological characteristics in Fuzhou area [J].Hydraulic Science and Technology,2004 (3):9-11.
[38] 人民网.2023.降雨突破历史极值!福建福州受灾5万多人，直接经济损失超5亿元[EB/OL].(2023-09-09) [2024-07-10].https://slt.fujian.gov.cn/wzsy/mtjj/202309/t20230918_626004 7.htm.People′s Daily Online 2023.Rainfall breaks historical record! More than 50000 people in Fuzhou,Fujian were affected by the disaster,resulting in direct economic losses exceeding 500 million yuan[EB/OL] (2023-09-09) [2024-07-10].https://slt.fujian.gov.cn/wzsy/mtjj/202309/t20230918_6260047.htm.
[39] 许红师.沿海城市多维致灾洪涝风险分析与灾防决策模型研究[D].天津：天津大学，2024.XU Hongshi.Research on Multidimensional Flood Risk Analysis and Disaster Prevention Decision Model in Coastal Cities [D].Tianjin:Tianjin University,2024.
[40] 高小童，秦志龙，高新宇.含海上风电-光伏-储能的多能源发输电系统可靠性评估[J].发电技术，2022,43(4):626-635.GAO X T,QIN Z L,GAO X Y.Reliability evaluation of multi-energy generation and transmission system with offshore wind power-photovoltaic-energy storage[J].Power Generation Technology,2022,43(4):626-635.
[41] NELSEN R B.An Introduction to Copulas[M].New York:Springer Verlag,2006.
[42] 吴佳瑶，张煜洲，陈柯，等.基于AHP-熵权法的城市内涝风险评估：以杭州市滨江区为例[J].浙江水利水电学院学报，2024,36(1):38-45.WU Jiayao,ZHANG Yuzhou,CHEN Ke,et al.Urban waterlogging risk assessment based on AHP entropy weight method:A case study of Binjiang District,Hangzhou City[J].Journal of Zhejiang University of Water Resources and Electric Power,2024,36(1):38-45.
基本信息:
DOI：10.13928/j.cnki.wrahe.2025.05.001
中图分类号:P429
引用信息:
[1]高鹏举,周翔,郑玉烽,等.台风大风暴雨复合致灾的灾害风险评估研究：以福州市为例[J].水利水电技术(中英文),2025,56(05):1-14.DOI:10.13928/j.cnki.wrahe.2025.05.001.
基金信息:
国家自然科学基金项目“东南沿海山地丘陵区暖季暴雨时空异质性及其致洪效应”(42271030); 福建省科技厅杰青项目“全球升温1.5℃~3℃情景下福建复合极端气候事件的致灾风险预估”(2022J06018); 福建省“雏鹰计划”青年拔尖人才计划
2024-10-21
2024-10-21
2024-10-21