基于农户视角的洪灾社会脆弱度及影响因素——以安康市4个滨河村庄为例

降低洪灾社会脆弱度是缓解洪灾社会影响,建立洪水韧性的重要途径。本文从敏感性、适应性和暴露度3个方面构建微观尺度下的洪灾社会脆弱度评价指标体系,以安康市4个滨河村庄为例,运用基于熵权的综合指数法评价农户的洪灾社会脆弱度,并通过BP神经网络分析厘清评价指标与社会脆弱度之间的重要性关系,识别出洪灾社会脆弱度的主要影响因素。据此提出相应的对策建议作为降低农户洪灾社会脆弱度的实践依据。研究表明：①案例村调研样本中近一半的农户处于高社会脆弱度等级,由此推算,研究区有715个农户具有较高的洪灾社会脆弱度;②受访者健康状况、防汛信息渠道、避灾疏散方式、建筑质量、是否有病残人口、家庭收入多样性、5岁以下幼儿比重和60岁以上老年人比重是农户社会脆弱度的主要影响因素;③基于农户视角的洪灾社会脆弱度评价能准确地识别出脆弱度较高的农户,其结果在降低洪灾社会脆弱度方面更具有现实意义。

Social vulnerable degree of floods and its influencing factors based on the perspective of rural households: A case study of four riverside villages in Ankang City

Reducing social vulnerability to floods is an important way to alleviate the social impact of flood disasters and to improve flood resilience. This article constructs an evaluation index system for social vulnerability to floods with regard to sensitivity, adaptability, and exposure based on a micro-scale analysis. Taking four riverside villages in Ankang City as an example, we adopted the integrated index weighted by entropy method to evaluate rural households' social vulnerability to floods. Then we clarify the importance of the relationship between evaluation index and social vulnerability by BP neural network method, and identify the major influencing factors of flood vulnerability. Accordingly, countermeasures and suggestions are put forward as a practical basis for reducing the rural households' social vulnerability to floods. The main results of this research are as follows. (1) Half of the households (715) in the case study villages showed a high level of social vulnerability. (2) The difference in social vulnerability is mainly a result of eight factors, including health status of the respondents, information channel on flood prevention, evacuation method, building quality, sick or disabled person in a household, household income diversification, proportion of children under the age of 5, and proportion of older people over 60 years of age. (3) Social vulnerability evaluation based on the perspective of rural households can accurately identify vulnerable farmers and analyze the influencing factors, which have more realistic significance for reducing the social vulnerability to floods of rural households.