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基于知信行模型的我国居民洪灾风险感知评价

周倩,刘德林   

  • 出版日期:2019-08-28 发布日期:2019-08-28

Evaluation of flood risk perception of Chinese residents based on KAP model

ZHOU Qian,LIU Delin   

  • Online:2019-08-28 Published:2019-08-28

摘要: 居民的灾害风险感知水平对防灾减灾政策的实施具有重要影响。以KAP模型(知识-态度-行为,Knowledge-Attitude-Practice)为理论框架,从知识、态度和行为3个方面构建了我国居民洪灾风险感知的评价指标体系。通过网络问卷调查获取数据,利用序关系分析法计算指标权重,构建了洪灾风险感知指数,用于对居民的风险感知水平进行评价。评价结果表明:① 我国居民的洪灾态度表现最为积极,平均得分为7.84分;其次为洪灾行为,平均得分为6.45分;洪灾知识最为匮乏,平均得分仅为6.28分。② 居民洪灾风险感知水平整体不高,平均得分7.83分;多数调查样本处于中低水平,分别占样本总量的36.50%和46.01%。建议政府合理开展洪灾宣传教育和应急演练;社区应做好防灾减灾准备,制定科学的应急预案;居民应积极关注洪灾信息、学习防洪减灾知识。

关键词: 洪灾风险, 风险感知, KAP模型, 防灾减灾, 序关系分析法

Abstract: Residents′ risk perception of disasters is important in the implementation of disaster prevention and mitigation. Based on the KAP (Knowledge, Attitude, Practice) model, we constructed an evaluation index system for flood risk perception of Chinese residents from aspects of knowledge, attitude and behavior. The data were obtained from online questionnaires. Index weights were calculated by using order relation analysis method. The flood risk perception index was constructed to evaluate the residents' risk perception level. The results showed that:① Chinese residents are most positive in attitude towards floods, with an average score of 7.84; they score 6.45 in taking risk-averse measures in response to the threat of flooding; and they knowledge of floods tend to be scarce, with an average score of 6.28. ② Residents’ perception level of flood risk is unsatisfactory, with a score of 7.83; most of the survey samples are in the low to medium levels, accounting for 36.50% and 46.01% of total samples. It is suggested that the government should reinforce publicity, education and emergency drills; the community should prepare for disaster prevention and mitigation, and make contingency plans; residents should pay attention to flood information and learn knowledge on flood control and disaster reduction.

Key words: flood risk analysis, risk perception, KAP model, disaster prevention and mitigation, order relation analysis