Reply on RC2

Abstract. Debris flows are frequently triggered by rainstorms after wildfires and pose severe threats to the lives of 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 on the basis of the observed building damage features and simulated debris flow intensity values. Detailed field surveys were conducted in Kule village, Yajiang County, to analyse the characteristics of postfire debris flows and establish a building damage database. 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 provides the highest statistical significance in terms of the relative error and prediction accuracy. 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 be used to evaluate the structural resistance of buildings to debris flows in wildfire-affected areas, thus providing a systematic foundation for formulating risk management and mitigation strategies.