沿海地区风暴潮灾害的脆弱性组合评价及原因探析

袁顺; 赵昕; 李琳琳

doi:10.3969/j.issn.0253-4193.2016.02.002

沿海地区风暴潮灾害的脆弱性组合评价及原因探析

doi: 10.3969/j.issn.0253-4193.2016.02.002

1.
中国海洋大学海洋与大气学院, 山东青岛 266100
2.
中国海洋大学经济学院, 山东青岛 266100

基金项目: 国家自然科学基金项目(71373247);海洋公益性行业科研专项(201305020);国家社科基金重大项目(15ZDB171);中国海洋发展研究会青年项目(CAMAQN201413);山东省优秀中青年科学家奖励基金项目(BS2015HZ006);中国博士后基金项目(2015M572077)。

计量
- 文章访问数: 950
- HTML全文浏览量: 6
- PDF下载量: 990
- 被引次数: 0
出版历程
- 收稿日期: 2015-03-14
- 修回日期: 2015-06-09

Combination evaluation and case analysis of vulnerability of storm surge in coastal provinces of China

1.
College of Oceanic and Atmospheric Science, Ocean University of China, Qingdao 266100, China
2.
College of Economics, Ocean University of China, Qingdao 266100, China

摘要

摘要: 以典型海洋灾害风暴潮为研究对象,以国家海洋局统计公报数据、国家统计局和各省市统计数据为数据源,将粗糙集理论(RST)与组合赋权策略(CWM)结合建立了基于RST-CWM的风暴潮灾害脆弱性组合评价模型。利用粗糙集的知识简约属性、投影寻踪组合赋权思想进行沿海各省市地区海洋风暴潮灾害脆弱性的综合评价。测算结果表明:沿海地区基于RST-CWM模型的风暴潮灾害脆弱性呈现出一定的空间差异性,但研究区各省市海洋风暴潮灾害脆弱性与地理位置分布没有必然的联系,说明在沿海地区开展海洋防灾减灾工作,若只注重地理区划并不一定能改善当地风暴潮脆弱程度。研究区各省市海洋灾害脆弱程度大小排序为:山东、天津、福建、广东、广西、辽宁、江苏、浙江、海南、河北、上海,同时,各省市的脆弱性要素即暴露性、敏感性及适应性构成有所差异,说明完备海洋风暴潮防灾减灾机制的驱动力是多样的,风暴潮防治应综合考虑灾害本身和人为因素。
- 风暴潮灾害 /
- 脆弱性 /
- 组合评价 /
- 粗糙集理论
Abstract: This paper researched the storm surge disasters in coastal provinces of China. Based on the data sources including the State Oceanic Administration, statistical yearbooks of State Statistical Bureau and coastal provinces, the Rough Set Theory and the Combination Weighting Method were combined to build the RST-CWM model for the purpose of assessing the vulnerability of storm surge disasters. And the evaluation results show that the vulnerability of storm surge disasters in coastal provinces varied spatially. However, this variation did not show a significant connection with geographical location. In this case, only focusing on geographical location in policy-making was likely to be inefficient. The most vulnerable area was Shandong while the least was Shanghai. Furthermore, the vulnerability of storm surge disasters was discomposed into exposure, sensitivity and adaptability, which varied from provinces. It indicated that diverse driving forces should be employed to optimize marine disaster prevention and reduction policies, during which natural and human factors should be taken into account.
- storm surge disasters /
- vulnerability /
- combination evaluation model /
- rough set theory

HTML全文

参考文献(16)

Pelling M. Visions of risk: a review of international indicators of disaster risk and its management[M]. ISDR/UNDP: Kingps College,University of London,2004.

Zapata R,Caballeros R. Un tema del desarrollo: vulnerabilidad frente a los desastres[J]. CEPAL,Naciones Unidas,Mexico,DF,2000: 45.

Kasperson J X,Kasperson R E. Global environmental risk[M]. Tokyo: United Nations University Press,2013.

Füssel H M. A generally applicable conceptual framework for climate change research,Global Environmental Change[J]. Global Environmental Change,2007,17(2): 155-167.

Turner II B L,Kasperson R E,Matson P A,et al. A framework for vulnerability analysis in sustainability science[J]. Proceedings of the National Academy of Sciences,2003,100(14): 8074-8079.

李映红,陶占盛,秦喜文,等. 基于组合赋权法的地质灾害可拓学评价模型研究[J]. 哈尔滨工业大学学报,2011,11: 141-144. Li Yinghong,Tao Zhansheng,Qin Wenxi,et al. Compination Weight Method for determing the index weight in geological disaster risk extenics evaluation[J]. Journal of Harbin Institute of Technology,2011,11: 141-144.

Pawlak Z. Rough sets[J]. International Journal of Computer & Information Sciences,1982,11(5): 341-356.

Pelling M. Visions of risk: A review of international indicators of disaster risk and its management[R]. ISDR/UNDP: Kingps College,University of London,2004: 1-56.

吕跃进,张旭娜,韦碧鹏. 基于优势关系粗糙集的模糊综合评价的权重确定[J]. 统计与决策,2012,20:44-46. Lv Yuejin,Zhang Xuna,Wei Bipeng. Weighting methods of the Fuzzy comprehensive evaluation based rough set theory with dominance[J]. Statistics & Decision,2012,20:44-46.

郭亚军. 综合评价理论、方法与拓展[M]. 北京:科学出版社,2012:62-101. Guo Yajun. Comprehensive Evaluation Theory,Methods and Extensions[M]. Beijing: Science Press,2012:62-101.

赵庆良,许世远,王军,等. 上海城市系统洪灾脆弱度评价[J]. 中国人口·资源与环境,2009(5): 143-147. Zhao Qingliang,Xu Shiyuan,Wang Jun,et al. Assessment of urban system vulnerability degree to flood disaster in Shanghai[J]. China Population Resources and Environment,2009(5): 143-147.

马辉. 综合评价系统中的客观赋权方法[J]. 合作经济与科技,2009,17:50-51. Ma Hui. Objecting weighting methods in comprehensive evaluation system[J]. Cooperative Economy & Science,2009,17: 50-51.

陈磊,徐伟,周忻,等. 自然灾害社会脆弱性评估研究——以上海市为例[J]. 灾害学,2012(1): 98-100,110. Chen Lei,Xu Wei,Zhou Xin,et al. Assessment of social vulnerability to natural disasters:a case study of Shanghai[J]. Journal of Catastrophology,2012(1): 98-100,110.

曾宪报. 关于组合评价法的事前事后检验[J]. 统计研究,1997(6): 56-58. Zeng Xianbao. Test before and after the combinatorial assess[J]. Statistical Research,1997(6): 56-58.

彭猛业,楼超华,高尔生. 加权平均组合评价法及其应用[J]. 中国卫生统计,2004(3):17-20. Peng Mengye,Lou Chaohua,Gao Ersheng. Combinatorial evaluation method of weighting average and its application[J]. Chinese Journal of Health Statistics,2004(3): 17-20.

李珠瑞,马溪骏,彭张林. 基于离差最大化的组合评价方法研究[J]. 中国管理科学,2013(1):174-179. Li Zhurui,Ma Xijun,Peng Zhanglin. Research on combination evaluation method bases on maximizing deviations[J].Chinese Journal of Management Science,2013(1): 174-179.

施引文献

资源附件(0)

访问统计