Abstract: Extreme rainstorm and flood events can significantly affect urban operational efficiency by disrupting residents, travel behavior. In order to accurately describe the characteristics of urban travel damage under the influence of heavy rainfall, take the "23·7" extremely heavy rainstorm event in Beijing as an example, and integrates high-resolution quantitative precipitation estimation products with origin-destination data derived from mobile phone signaling. Grid-scale indicators of travel-volume loss rate and disruption duration were developed to quantitatively analyze the differences in population travel response under different functional zones, rainfall levels, and intraday time periods. The results show that the rainstorm event significantly reduced total travel volumes across all functional zones,while the basic diurnal rhythm of "morning peak-daytime declineevening peak" remained unchanged. Residential areas exhibited the largest absolute loss, followed by business office areas and parks/greenspaces, indicating that both commuting activities and leisure-recreation trips were markedly suppressed. Further analysis of mobility loss characteristics shows that commercial areas had the highest loss rate and the longest disruption duration,while residential, educational,and medical areas also experienced relatively high levels of mobility disruption. The impacts of different rainstorm levels on mobility displayed nonlinear characteristics. Residential and business office areas were particularly sensitive to rainfall disturbance,and concentrated travel during morning and evening peaks amplified the suppressive effect of rainfall on human mobility. These findings provide scientific support for spatially and temporally differentiated traffic management,public service guarantee,and urban resilience enhancement under extreme rainstorm scenarios.