AbstractAccurate and rapid simulation and monitoring of urban inundation play important roles in urban flood prediction and warning. This paper presents a case study of campus-scale rainfall-flood inundation, including simulation and monitoring work, conducted at Xi’an University of Technology. A surface hydrodynamic numerical model based on graphics processing unit (GPU) acceleration technology is proposed. It is termed as GPU-accelerated surface water flow and associated transport (GAST), and is employed to simulate and analyze the rainfall runoff process and the drainage pipe network process of the study area. A uniform grid of 624×550 units with a high resolution of 1 m was used. Moreover, a monitoring system was established in the study area to dynamically monitor and acquire data in real time, including the water level in the drainage pipe network, rainfall, and inundation. Eventually, the monitoring system provides observed data for validating the model. The findings from this study indicate that inundation and the drainage process can be effectively computed by the model. The GPU accelerates the simulation time approximately 2.9 times faster than real time. This study proposed a novel approach for disaster prevention and the mitigation of urban flooding. In addition, the system can produce a data set to help validate numerical models for small-scale urban flood processes.