Flood Simulation using rainfall-runoff-inundation (RRI) model, over Tripoli City, Lebanon

Abstract. Flood inundation modeling aims to minimize flood risks by providing a complete understanding of flood dynamics. This research evaluates the effectiveness of the Rainfall-Runoff-Inundation (RRI) model in simulating flood inundation along the Abou Ali River in Tripoli, Lebanon during the flood events on 18 February 2018. The RRI model is a two-dimensional distributed hydrologic model that simulates rainfall, runoff and flood inundation processes simultaneously. The key inputs utilized in this study are: Topographical data acquired from HydroSHEDS, rainfall data obtained from the Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), soil data provided by the Food and Agriculture Organization (FAO) and land use/cover derived from the Sentinel-2 mission, a global dataset with a 10-meter resolution, which was generated by Impact Observatory, Microsoft, and Esri. The model performance is validated by comparing the findings to observed data, which reveals consistency in terms of discharge rates, flood extent and water depth. Moreover, the simulated hydrograph achieved a satisfactory calibration, reflected by a coefficient of determination (R²) of 0.845 and a peak discharge rate of 39 m³/s nearly matching the real data. This research shows the effectiveness of the RRI model in simulating flood events in the Abou Ali River and highlights the significance of flood modeling in flood risk assessment and mitigation. This approach offers valuable insights for building efficient flood mitigation strategies in Lebanon.