Flood risk assessment and mapping is required for management and mitigation of flood in mountain cities. However, the specific characteristics of population, society, economy, environment, transportation and other disaster-bearing bodies in various regions of mountain cities are significantly different, which increases the uncertainty of risk assessment index weight and risk assessment accuracy. To overcome these problems, the triangular fuzzy number-based analytical hierarchy process (TFN-AHP) was employed to determine the weights of eleven indexes influencing flooding. Further, the geographic information system (GIS) spatial statistics technique was introduced to investigate global regional risk pattern, as well as to identify local risk hot spots. Experiments were conducted using open data of Chongqing, China. From the results, it was observed that the TFN-AHP has a higher efficiency in flood risk assessment on mountain cities than the AHP method. The dynamically changing risk pattern and risk hot spots were explored, and the results are generally consistent with seasonal characteristics of precipitation. Lastly, sensitivity analysis of assessment factors’ weights was conducted. The comparative consequences indicate that TFN-AHP can better assess the flooding risk and can be successfully applied to urban development policy.