Comparative Assessment of Entropy Weighting and Ordered Weighted Averaging in Flood Hazard Mapping: A Case Study of Kampala City.

Abstract

This study compares Entropy Weighting and Ordered Weighted Averaging (OWA) for flood hazard mapping in an urban area prone to heavy rainfall, topographic variability, and urbanization. Six flooding factors—rainfall, slope, flow accumulation, elevation, flow direction, and land use/land cover (LULC)—were processed using GIS tools. Rainfall was mapped via Inverse Distance Weighting, slope and flow accumulation from a Digital Elevation Model, and LULC from Landsat 8 imagery, with factors classified into susceptibility classes (Very Low to Very High). Entropy Weighting assigned objective weights based on spatial variability, prioritizing rainfall (0.201) and flow accumulation (0.166). OWA used flexible, expert-driven weights to emphasize urban flood risks from LULC and flow accumulation. GIS-based weighted overlay produced flood hazard maps with five risk zones, validated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) against 150 historical flood points. Entropy Weighting outperformed OWA (AUC 0.8142 vs. 0.7196), better identifying flood-prone areas. Rainfall was the primary flood driver, with high-susceptibility zones linked to urban flooding. Low-gradient slopes (<5 degrees) and low-elevation areas were prone to waterlogging, worsened by impermeable urban surfaces. Entropy Weighting excelled in capturing risks in rainfall-heavy urban areas, while OWA highlighted urban risks but underestimated some low-slope zones. Entropy Weighting is recommended for standardized flood hazard mapping to guide urban planning, such as enhancing drainage systems. OWA’s flexibility suits scenario-based planning, but its performance could improve by incorporating factors like soil permeability and refining weights. This study offers a robust framework for flood risk management in urban settings.