Employing K-means clustering to reconstruct missing water surface elevations in LiDAR digital elevation models for hydrodynamic simulation

Key Points

• Improved accuracy of water surface elevations enhances hydrodynamic simulations significantly.
• Inclusion of k-means clustering led to a 30% reduction in elevation errors over traditional methods.
• Analysis of missing elevations used digital elevation models derived from LiDAR data.
• The approach highlights potential for increased reliability in hydrodynamic modeling efforts.