Integrated statistical forecasting, HECRAS modeling, and GIS for urban flood hazard assessment under data-scarce conditions

Urban flood hazard assessment in data-scarce regions remains a major challenge for sustainable water and urban management. This study presents an integrated statistical–hydrodynamic–geographic information system framework to quantify compound flood hazards in the Vushtrri urban area, located in the Sitnica River basin in northern Kosovo. The methodology combines autoregressive moving average with exogenous variables discharge forecasting, Gumbel–Copula dependence analysis between rainfall and river flow, and two-dimensional hydraulic modelling to simulate flood depth, inundation extent, and flood volume. A total of 47 scenarios were analysed, integrating observed and forecast-based river discharges with multiple rainfall intensities and temporal structures. The results show that pluvial flooding generated by intense rainfall represents a substantially higher hazard to the urban area than fluvial flooding caused by Sitnica River overflows. Maximum flood depths reach approximately 6 m, with inundation covering about 20% of the study area, primarily affecting built-up zones. Forecast-based scenarios indicate an increasing tendency in extreme river flows over 5–15-year horizons, while rainfall–discharge dependence remains weak. Despite the projected increase in river flows, fluvial flood risk within the city remains limited due to the protective role of existing embankments. These findings demonstrate that rainfall-driven flooding is the dominant driver of urban flood risk in Vushtrri and highlight the importance of integrating statistical forecasting, hydraulic modelling, and spatial analysis for robust flood hazard assessment and mitigation planning in data-scarce regions.