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| 山洪视角下社区韧性影响因素及其定量分析 | |
| 引用本文： | 钟鸣,肖璐,张倩,温家洪.山洪视角下社区韧性影响因素及其定量分析[J].地理科学进展,2022,41(3):423-436. |
| 作者姓名： | 钟鸣 肖璐 张倩 温家洪 |
| 作者单位： | 1. 中山大学地理科学与规划学院,广州 510275 2. 南方海洋科学与工程广东省实验室(珠海),广东 珠海 519080 3. 广东省水利水电科学研究院,广州 510275 4. 上海师范大学环境与地理科学学院,上海 200234; |
| 基金项目： | 国家重点研发计划;南方海洋科学与工程广东省实验室(珠海)创新团队建设项目;国家自然科学基金 |
| 摘 要： | 山洪灾害具有广泛性、突发性、破坏性等特征,开展山洪易发区的社区韧性评估,从而提高灾害应对能力是当前防灾减灾的前沿热点和难点。论文提出了一套多学科的综合方法：① 利用中介效应明晰了山洪视角下社区韧性评价体系各指标间的定量化传递关系;② 构建了基于决策实验室分析和解释结构模型的耦合数学模型,确定社区韧性影响因素的多级递阶解释结构模型,分析社区韧性的差异化影响因素;③ 采用信息扩散方法,定量分析山洪灾害社区韧性的变化趋势并排序。以粤北山洪易发区为例,从城镇、村落、城乡结合部3种类型社区进行灾害韧性分析。结果表明：山洪视角下的社区韧性指标体系是一个多维度多层次的复杂网络系统,包括环境、社会、心理、制度和信息沟通5个方面;不同类型社区灾害韧性的直接影响因素呈差异化特征,而供排水设施建设和洪灾应急演练为社区韧性的根本影响因素,对增强山洪视角下社区韧性发挥本质性作用;由于调研村落多位于山洪频发区,居民防范灾害、减轻灾害影响的意识较强,村落较城镇和城乡结合社区呈现出更高的韧性。研究可为提升粤北山洪易发区社区韧性及社区防灾减灾能力提供科学参考,该综合分析方法亦可为其他类型灾害的精细化防灾减灾提供支持。 |
| 关 键 词： | 山洪灾害 社区韧性 解释结构模型法 中介效应 信息扩散 |
| 收稿时间： | 2021-06-08 |
| 修稿时间： | 2021-08-22 |
Influencing factors and quantitative analysis of community resilience to flash floods |
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| ZHONG Ming,XIAO Lu,ZHANG Qian,WEN Jiahong.Influencing factors and quantitative analysis of community resilience to flash floods[J].Progress in Geography,2022,41(3):423-436. | |
| Authors: | ZHONG Ming XIAO Lu ZHANG Qian WEN Jiahong |
| Institution: | 1. School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China 2. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, Guangdong, China 3. Guangdong Research Institute of Water Resources and Hydropower, Guangzhou 510275, China 4. School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China; |
| Abstract: | Based on the characteristics of flash floods such as extensiveness, abruptness, and destructiveness, the current focus of disaster prevention and mitigation is to assess the resilience of communities in regions with frequent flash flood disasters, so as to enhance the disaster response level. This study proposed a set of multidisciplinary integrated methods: 1) The quantitative transmission relationship among the indicators of the community resilience evaluation system under the impact of flash floods was clarified by examining the mediating effect. 2) The coupling decision mathematical model of the decision laboratory model and the interpretive structure model was established, the multilevel interpretive structure model of the influencing factors of community resilience was constructed, and then the differential influencing factors of community resilience were analyzed. 3) Information diffusion method was used to quantitatively analyze and rank the community resilience of flash flood disasters. Taking the flood-prone areas in northern Guangdong Province as the research area, this study analyzed three types of communities—that is, towns, villages, and peri-urban areas, and the results show that the community resilience indicator system from the perspective of flash flood impact is a multi-dimensional and multi-layered complex network system, including five aspects: environmental, social, psychological, institutional, and communication. The direct influencing factors of community resilience to different types of disasters are different. The construction of water supply and drainage facilities and flood emergency drills, as the fundamental influencing factors of community resilience, play an essential role in enhancing community resilience to flash floods. Since most of the surveyed villages are located in areas with frequent flash floods, residents have a high awareness of disaster prevention and mitigation and the villages show higher community resilience than the sample towns and peri-urban areas. The study can provide an important reference for improving the resilience of communities in the flood-prone areas in northern Guangdong and their disaster prevention and mitigation capabilities. This comprehensive analysis method can also provide strategic support to the refinement of disaster prevention and mitigation of other types of disasters. |
| Keywords: | flash floods community resilience interpretative structural model mediating effect information diffusion method |
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