Exposure Assessment of Compound Disaster System in Guangdong-Hong Kong-Macao Greater Bay Area

NAVIGATE

Table of Contents

STATISTICS

Viewed187

Downloads181

Exposure Assessment of Compound Disaster System in Guangdong-Hong Kong-Macao Greater Bay Area

[HTML] PDF下载 (181)

[1]HUANG Li,WANG Yunqing,WANG Wei,et al.Exposure Assessment of Compound Disaster System in Guangdong-Hong Kong-Macao Greater Bay Area[J].Journal of Zhengzhou University (Engineering Science),2024,45(04):95-101.[doi:10.13705/ j.issn.1671-6833.2024.01.013]

Copy

Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 45 Number of periods: 2024 04 Page number: 95-101 Column: Public date: 2024-06-16

Title:: Exposure Assessment of Compound Disaster System in Guangdong-Hong Kong-Macao Greater Bay Area

Author(s):: HUANG Li¹; 2; WANG Yunqing³; WANG Wei²; 3; SONG Yue²; 3; SHI Yuxin³; 1.School of Public Administration, Hohai University, Nanjing 211100, China; 2.Key Laboratory of Ministry of Education for Coastal Disaster and Protection, Hohai University, Nanjing 210098, China; 3.College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

Keywords:: compound disasters; Guangdong-Hong Kong-Macao Greater Bay Area; exposure evaluation; order rela tionship analysis; TOPSIS method

CLC:: X43X915.5

DOI:: 10.13705/ j.issn.1671-6833.2024.01.013

Abstract:: In order to prevent and reduce the disaster losses caused by compound disasters to cities, it was of great theoretical and practical significance to study the exposure degree of chain compound disaster system. Through the research and analysis of the exposure degree of chain compound disaster system, considering the existing research and defining the connotation of the exposure degree of the compound disaster system, the evaluation model and cal culation method of the exposure degree of the chain compound disaster system were deduced and established. Tak ing the rainstorm-landslide disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area as an example for em pirical analysis, the evaluation index system of regional disaster chain exposure was screened and constructed from the aspects of population, economy and society. The order relationship analysis and TOPSIS method were used to calculate the single disaster exposure index of rainstorm and landslide in 52 districts and counties in the bay area. Then, the theoretical model of exposure degree of chain compound disaster system and ArcGIS image processing technology were used to obtain the zoning map of rainstorm-landslide disaster chain exposure in the Guangdong Hong Kong-Macao Greater Bay Area, and the corresponding disaster prevention and mitigation measures were put forward according to the exposure degree attribute of each regional disaster chain. The results showed that the expo sure index corresponding to the economically developed areas was significantly higher than that of other regions, and the low exposure were mainly in the relatively backward areas. Among the indicators, population density and GDP per land area account for the main position, which had the highest impact on regional exposure. By the exposure of regional compound disaster systems, reasonable scientific basis and decision-making support could serve for the government and relevant departments, helping the government, urban planners, and the public better understand and respond to disaster risks, thereby reduce the losses and impacts of disasters.

References:: [1] NG K S, LECKEBUSCH G C. A new view on the risk of typhoon occurrence in the western North Pacific[J]. Nat ural Hazards and Earth System Sciences, 2021, 21(2): 663-682.
[2] 于文颖, 纪瑞鹏, 王鹏, 等. 辽宁玉米典型复合农业气象灾害影响损失评估[J]. 灾害学, 2022, 37(3): 84-92.

YU W Y, JI R P, WANG P, et al. Maize loss assess ment of typical multiple agrometeorological disasters in Li aoning province, China[J]. Journal of Catastrophology, 2022, 37(3): 84-92.

[3] 刘曙光, 郑伟强, 周正正, 等. 极端暴雨下城市地下空间洪涝风险及灾害防控[J]. 郑州大学学报(工学版), 2023, 44(2): 22-29, 81.

LIU S G, ZHENG W Q, ZHOU Z Z, et al. Flood risk and control in urban underground spaces with extreme rainfall[J]. Journal of Zhengzhou University (Engineer ing Science), 2023, 44(2): 22-29, 81.

[4] 张金萍, 张朝阳, 左其亭. 极端暴雨下城市内涝模拟与应急响应能力评估[J]. 郑州大学学报(工学版), 2023, 44(2): 30-37.

ZHANG J P, ZHANG Z Y, ZUO Q T. Urban waterlogging simulation and emergency response capacity evaluation with extreme rainstorms[J]. Journal of Zhengzhou Univer sity (Engineering Science), 2023, 44(2): 30-37.

[5] 朱雪虹. 顾及居民出行的城市洪涝灾害暴露性计算方法研究[D]. 南京: 南京师范大学, 2018.

ZHU X H. Research on calculation method of urban ex posure to flood hazard considering residents′ trip[D]. Nanjing: Nanjing Normal University, 2018.
[6] POLSKY C, NEFF R, YARNAL B. Building comparable global change vulnerability assessments: the vulnerability scoping diagram[J]. Global Environmental Change, 2007, 17(3/4): 472-485.

[7] TELLMAN B, SULLIVAN J A, KUHN C, et al. Satellite imaging reveals increased proportion of population ex posed to floods[J]. Nature, 2021, 596(7870): 80-86.

[8] SUN H M, WANG Y J, CHEN J, et al. Exposure of population to droughts in the Haihe River Basin under global warming of 1.5 and 2.0℃ scenarios[J]. Quater nary International, 2017, 453: 74-84.

[9] 王艳君, 高超, 王安乾, 等. 中国暴雨洪涝灾害的暴露度与脆弱性时空变化特征[J]. 气候变化研究进展, 2014, 10(6): 391-398.

WANG Y J, GAO C, WANG A Q, et al. Temporal and spatial variation of exposure and vulnerability of flood dis aster in China[J]. Climate Change Research, 2014, 10 (6): 391-398.

[10]谢伏瞻,刘雅鸣. 应对气候变化报告(2019): 防范气候风险[M]. 北京: 社会科学文献出版社, 2019.

XIE F Z, LIU Y M. Annual report on actions to address climate change(2019): climate risk prevention[M]. Beijing: Social Science Academic Press, 2019.

[11]张柳红, 伍红雨, 向昆仑, 等. 1961—2021年粤港澳大湾区暴雨气候变化特征[J]. 中山大学学报(自然科学版)(中英文), 2023, 62(4): 32-44.

ZHANG L H, WU H Y, XIANG K L, et al. Climate change characteristics of rainstorm in Guangdong-Hong Kong-Macao Greater Bay Area from 1961 to 2021[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2023, 62(4): 32-44.

[12]薛斯文, 解雪峰, 吴涛, 等. 杭州城市边缘区暴露度评价[J]. 农学学报, 2022, 12(5): 85-90.

XUE S W, XIE X F, WU T, et al. Exposure degree e valuation of urban fringe in Hangzhou[J]. Journal of Ag riculture, 2022, 12(5): 85-90.

[13]闫康子. 暴露度研究综述[J]. 农业灾害研究, 2023, 13(2): 169-172.

YAN K Z. Review of exposure research[J]. Journal of Agricultural Catastrophology, 2023, 13(2): 169-172.

[14] CLARK G E, MOSER S C, RATICK S J, et al. Assessing the vulnerability of coastal communities to extreme storms: the case of Revere, MA., USA[J]. Mitigation and Adap tation Strategies for Global Change, 1998, 3(1): 59-82.

[15]广东省统计局. 广东统计年鉴[M]. 北京: 中国统计出版社, 2020.

Statistics Bureau of Guangdong Province. Guangdong statis tical yearbook[M].Beijing: China Statistics Press, 2020.

[16]郭亚军. 综合评价理论与方法[M]. 北京: 科学出版社, 2002.

GUO Y J. Theory and method of comprehensive evalua tion[M]. Beijing: Science Press, 2002.

[17]董文旭, 王方明, 王芳, 等. 三种赋权法在应急准备能力评估领域的适用性对比分析研究[J]. 计算机与应用化学, 2018, 35(9): 725-731.

DONG W X, WANG F M, WANG F, et al. A compara tive study on applicability of three weight assignment methods in the capability assessment for emergency readi ness[J]. Computers and Applied Chemistry, 2018, 35 (9): 725-731.

[18]徐新良.中国多年度区县行政区划边界数据[EB/ OL]. [2023-08-10]. https:∥www. resdc. cn/DOI/ DOI.aspx?DOIID=120.

XU X L. Multi-year administrative division boundary data of districts and counties in China[EB/OL]. [2023-08-10]. https:∥www.resdc.cn/DOI/DOI.aspx?DOIID=120.

[19]潘元贵, 伍中庚, 孙东, 等. 四川渠县 “8·8”特大暴雨引发的地质灾害分布特征与成因分析[J]. 中国地质灾害与防治学报, 2022, 33(4): 125-133.

PAN Y G, WU Z G, SUN D, et al. Analysis on the dis tributive characteristics and causes of the geological disas ters induced by the “8·8” heavy rainstorm in Qu County, Sichuan Province[J]. The Chinese Journal of Geological Hazard and Control, 2022, 33(4): 125-133.

Similar References:

Memo

Last Update: 2024-06-14