A novel framework for urban flood risk assessment: Multiple perspectives and causal analysis

Area of Science:

• Environmental Science
• Urban Planning
• Climate Change Adaptation

Background:

• Global climate change drives increased extreme weather events and urban flooding.
• Urban flood risk assessment and adaptation are critical research areas.
• Existing frameworks often lack integrated adaptive capacity at the urban agglomeration scale.

Purpose of the Study:

• To develop and apply a spatial multi-indicator model for assessing urban flood risk at the urban agglomeration scale.
• To incorporate adaptive capacity into the Intergovernmental Panel on Climate Change (IPCC) risk framework.
• To analyze the influence of vulnerability and adaptive capacity on flood risk in the central and southern Liaoning urban agglomeration (CSLN).

Main Methods:

• Development of a spatial multi-indicator model integrating economic, social, and geographic factors.
• Application of the model to the central and southern Liaoning urban agglomeration (CSLN).
• Utilized correlation analysis and the Light Gradient Boosting Machine (Light GBM) model to analyze indicator relationships.

Main Results:

• Flood risk varied significantly across different scenarios.
• Inclusion of vulnerability indicators increased flood risk by 33%.
• Inclusion of adaptive capacity indicators decreased flood risk by 45%, demonstrating its mitigating effect.

Conclusions:

• Dense populations and assets exacerbate urban flood risk.
• Adaptive capacity is a key factor in mitigating urban flood risk.
• The developed framework is applicable to other urban agglomerations for flood risk assessment and mitigation strategies.