Flood sensitivity assessment of super cities

Area of Science:

• Environmental Science
• Urban Planning
• Geographic Information Science

Background:

• Urbanization increases impervious surfaces, limiting rainwater infiltration and exacerbating waterlogging and flash floods in super cities.
• Flood sensitivity assessment is crucial for predicting and mitigating disasters in rapidly developing urban areas.
• Previous studies often analyzed flash floods and waterlogging separately, and focused on smaller areas, necessitating a comprehensive approach for super cities.

Purpose of the Study:

• To identify flood-vulnerable areas in Beijing, a major super city, by creating a flood sensitivity map.
• To evaluate the combined sensitivity of flash floods and waterlogging using integrated data.
• To provide a reference for flood risk analysis in other super cities globally.

Main Methods:

• Utilized Geographic Information System (GIS) and Remote Sensing (RS) for spatial analysis.
• Applied a Logistic Regression (LR) model incorporating 12 predictor variables including elevation, slope, rainfall, and Land Use/Land Cover (LULC).
• Integrated historical flood points (flash floods and waterlogging) for model training (70%) and testing (30%), validated using Area Under Curve (AUC).

Main Results:

• Elevation, slope, rainfall, LULC, soil, and Topographic Wetness Index (TWI) were identified as the most influential factors in flood sensitivity.
• The LR model achieved a high prediction accuracy, with an AUC of 81.0% on the test dataset.
• Approximately 27.44% of the study area was classified as high or extremely high risk, encompassing 69.26% of recorded flood events.

Conclusions:

• The developed flood sensitivity map accurately identifies high-risk zones in Beijing, crucial for urban flood risk management.
• Integrating flash flood and waterlogging assessments provides a more comprehensive understanding of urban flood hazards.
• The findings offer valuable insights for policymakers to develop targeted strategies for mitigating flood damage in super cities and similar urban environments.