Urban Flood Risk Assessment Using High-Resolution 3D Building Models and Multi-Temporal Meteorological Data

Urban areas are increasingly exposed to flood hazards due to climate change, densification and growing urbanization. Remote sensing datasets can be used to monitor the floods and warn the population. Much more, simulations of hazards, using high resolution geospatial datasets combined with meteorological data can be derived. In this case, solutions prior to the events can be implemented, so increasing the resilience of cities to natural hazards.

This study presents a high-resolution 3D urban model of Brașov, Romania, developed from an airborne photogrammetric datasets acquired in 2025, and its application in urban flood risk assessment. The 3D building models were obtained using footprints from the national topographic database and the height derived from the computed normalized Digital Surface Model (nDSM). For the flood modelling the hydrological network and land cover data were used.

To assess flood risk, time series precipitation dataset was analyzed and used in the modelling framework. The combined analysis under different scenarios, enabled the identification of flood areas and the estimation of the number of exposed buildings. The results highlight the importance of high-resolution 3D urban data for understanding flood dynamics in complex urban settings and support decision-making processes related to urban planning, risk mitigation, and climate resilience. The output also represents a starting point for a Digital Twin for Brașov.