Rainfall Induced Flood Hazard Zonation of Abbottabad City and its Vicinity using HEC-RAS 2D and Rain-On-Grid Simulation

Abstract

Flood hazard assessment is crucial for effective disaster management and vulnerability zonation, particularly in areas prone to excessive rainfall events. This study integrates the HEC-RAS 2D with the Rain-On-Grid (ROG) technique to simulate rainfall-induced flooding in Abbottabad city and its vicinity. The ROG approach enables direct application of rainfall onto the computational grid, allowing for a more accurate representation of overland flow and flood propagation in complex terrains. The model incorporates hydrological data in the form of historical rainfall and geospatial data, including high-resolution Digital Elevation Model (DEM), land use, and soil type, to establish the Curve Number (CN), which is used to estimate runoff potential. Simulations provide insights into flood velocity and inundation depth extent, highlighting high-risk zones within the study area. Results demonstrate that the HEC-RAS-2D and ROG framework enhances flood prediction accuracy. The findings of this study contribute to flood risk assessment by providing reliable flood hazard zonation mapping of Abbottabad city and its vicinity. Flood hazard classification based on the product of Depth and Velocity (D×V) indicates the distribution of different hazard levels (H) for a 100-year return period, where H-1 covers 7. 993%, H-2 covers 6.224%, H-3 covers 3.544%, H-4 covers 3.184%, H-5 covers 27.806%, and H-6 covers 51.266% of the total inundated area. A significant portion of the inundated area is classified as high hazard (H-5), and very high hazard (H-6) requires specialised flood management strategies and disaster resilience landuse planning for existing and future population settlements. The study also underscores the potential of integrating ROG with HEC-RAS-2D to enhance flood forecasting in regions with limited hydrological data.