A Novel Lidar-Integrated Flood Simulation Model for Enhanced Flood Hazard-Exposure Mapping

Flooding is a major natural hazard that causes significant risks to communities worldwide, particularly within the Kelani River basin in Sri Lanka, one of the country’s most flood-prone regions. Effective flood risk management requires accurate flood simulation modeling supported by advanced technologies such as Light Detection and Ranging (LiDAR), which provides high-resolution elevation data. However, disconnected depressions and the unrealistic spreading of water across unconnected terrain continue to limit the accuracy of conventional flood simulation approaches. The study introduces a LiDAR-integrated flood simulation approach that incorporates a connectivity-constrained inundation algorithm to overcome identified limitations. A high-resolution LiDAR-derived Digital Elevation Model (DEM) and gauge records were integrated within a Python-based simulation framework. The model employed a connected component analysis to ensure realistic flood propagation by linking inundated areas to the river system. Results demonstrated that the model effectively excluded non-vulnerable areas and disconnected depressions, increasing its accuracy. The findings confirm the potential of LiDAR data and advanced image processing techniques for reliable flood risk modeling.