Flood Risk Assessment in Urban Environments: Dynamic Modeling and Multi-Scenario Analysis

Abstract

Urban flooding has become one of the most significant challenges for rapidly urbanizing cities, where intensive land development, increasing impervious surfaces, and complex topography substantially amplify surface runoff and flash flood hazards. The aim of this study is to develop an integrated methodological framework for assessing urban flood risk through dynamic hydrological modelling and multi-scenario spatial analysis using Geographic Information Systems. The study was conducted within a highly urbanized micro-catchment located in the Yasamal district of Baku, Azerbaijan, characterized by steep relief, predominantly impermeable clay soils, and dense urban development. The methodology combines Digital Elevation Model analysis, land use and land cover assessment, hydrological soil classification, the Rational and Soil Conservation Service Curve Number methods, runoff concentration modelling based on the National Resources Conservation Service Kinematic Wave approach, and Geographic Information Systems-based spatial analysis. Rainfall scenarios ranging from 1 to 100 mm were simulated to evaluate runoff generation, peak discharge, flood propagation, and the spatial distribution of flood hazards at the individual building level. The results demonstrate that the interaction between relief morphology, intensive urbanization, and low soil infiltration capacity creates favourable conditions for rapid stormwater accumulation and flash flood formation. Approximately 79% of the total runoff is concentrated within three critical topographic depressions, while floodwaters reach the most vulnerable buildings within only 3.0–4.3 minutes under high-intensity rainfall scenarios. Comparative analysis revealed that the Rational method provides more reliable estimates of peak discharge and runoff concentration time, whereas the Soil Conservation Service Curve Number method more accurately predicts runoff volume. Their combined application significantly improves the reliability of urban flood assessment. The proposed Geographic Information Systems-based multi-scenario framework enables the identification of flood corridors, localized hazard hotspots, and vulnerable infrastructure with high spatial accuracy, providing an effective decision-support tool for sustainable urban planning, stormwater management, climate adaptation, and the development of resilient urban infrastructure.