Assessment of the vulnerability of buildings destroyed during postfire debris flow events in Kule village, Yajiang County, China

Abstract

Debris flows are frequently triggered by rainstorms after wildfires and pose severe threats to downstream residents and buildings in mountainous regions. However, there has been limited focus on developing a comprehensive framework to assess the physical vulnerability of buildings to postfire debris flows. This study presents a quantitative approach for establishing a physical vulnerability model based on observed building damage and simulated debris flow intensities. Detailed field surveys established a building damage database in Kule village, Yajiang County. Numerical simulations using the FLO-2D model were performed to reproduce the debris flow process and quantify the debris flow intensity, including the flow depth, flow velocity, impact pressure, momentum flux, overturning moment, and relative burial height. Physical vulnerability curves were developed for brick-concrete buildings and compared with those obtained in previous studies, and the differences in vulnerability curves, intensity indicators, and functional models were examined. The results revealed that the lognormal cumulative distribution function (LNCDF) model achieved the best performance, with relative error less than 10 % and prediction accuracy exceeding 85 %. Critical thresholds for complete building damage were identified as a flow depth of 2.5 m and impact pressure of 25 kPa. The momentum flux demonstrated greater sensitivity in distinguishing different damage categories, whereas the impact pressure provided more precise vulnerability index predictions. The proposed physical vulnerability model can evaluate the building structural resistance to debris flows in wildfire-affected areas, providing a systematic foundation for risk management and mitigation strategies.