Quantitative flood disaster loss-resilience with the multilevel hybrid evaluation model

Journal of environmental management(2023)

引用 0|浏览17
暂无评分
摘要
The severity of global flood disasters is growing, causing loss of human life and property. Building a high-resilience social system, an important means of sustainable flood control, can address these flood-related issues. Numerous studies have carried out disaster resilience evaluations and explored the correlation between flood disaster loss and intensity, but neglected to analyze the role of resilience construction in disaster loss reduction. This study proposed a research route for linking flood loss and disaster loss to quantify the relationship between the two. Take Guangdong Province, China as a study case, the mixed-effects (ME) model and multilevel hybrid evaluation model (MHEM) were established to assess disaster loss and resilience of cities, respectively. Subsequently, disaster resilience curves were built to quantitatively evaluate disaster resilience and corresponding disaster loss. The results show that (1) the ME model can concurrently build the disaster intensity-loss curves of multiple cities with high fitting accuracy. The MHEM combines multiple methods to determine the evaluation result with the highest consistency, showing high reliability. (2) The central and southern regions of Guangdong Province have low disaster loss and high resilience, while the northern regions have high disaster loss and low resilience. (3) With the improvement of disaster resistance, the reduction in disaster loss gradually decreases. Disaster loss in low-resilience cities exhibits greater randomness than that in high-resilience cities, and increasing their resilience can more significantly reduce their level of loss. This study provides a quantitative basis and available methods for comprehensive responses to natural disasters and adaptation to global climate change.
更多
查看译文
关键词
Disaster resilience,Flood loss,Mixed-effects model,Multilevel hybrid evaluation model,Multicriteria decision making
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要