大洪水
洪水风险评估
洪水(心理学)
脆弱性(计算)
城市群
风险评估
风险分析(工程)
环境规划
环境资源管理
气候变化
地理
环境科学
水资源管理
业务
计算机科学
经济地理学
生态学
计算机安全
考古
心理学
心理治疗师
生物
作者
Yongheng Wang,Qingtao Zhang,Kairong Lin,Zhiyong Liu,Y. F. Liang,Yue Liu,Chunlin Li
标识
DOI:10.1016/j.watres.2024.121591
摘要
Risk assessment and adaptation have become key focuses in the examination of urban flooding risk. In recent decades, global climate change has resulted in a high incidence of extreme weather events, notably flooding. This study introduces a spatial multi-indicator model developed for assessing flood risk at the urban agglomeration scale. A crucial addition to the model is the incorporation of an adaptive capacity within the IPCC risk framework. The model systematically considers various flood risk indicators related to the economic, social, and geographic environments of the central and southern Liaoning urban agglomeration (CSLN). It generates a spatial distribution map of integrated flood risk for multiple scenario combinations. Furthermore, the intricate relationship between different risk indicators and flood risk was analyzed using correlation analysis and the Light Gradient Boosting Machine model (Light GBM). The findings reveal notable variations in flood risk under different scenarios. The inclusion of vulnerability indicators increased flood risk by 33%, while the subsequent inclusion of adaptive indicators decreased flood risk by 45%. Dense populations and assets contribute to high flood risk, while adaptive capacity significantly mitigates urban flood risk. The framework adopted in this paper can be applied to other areas where urban agglomeration-scale flood risk assessment is needed, and can contribute to advancing scientific research on flood forecasting and mitigation.
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