Growing urbanization has expanded the use of impervious surfaces, or hard surfaces that allow little or no stormwater infiltration into the ground. Asphalt, concrete and stone which do not allow for water to seep back into the ground results in urban runoff and in some cases flooding. Damage and loss of life from urban flooding has made identifying mitigation measures a priority.
Knowing the difficulty with monitoring on a citywide scale, researchers Ganggang Bai; Jingming Hou; Yangwei Zhang; Hao Han; Dong Yang; Baoshan Shi; Yue Ma; and Guoqiang Ji, at Xi’an University of Technology developed a small-scale campus model. Their research, “High-Resolution Simulation and Monitoring of Urban Flood Processes at the Campus Scale,” published in the Journal of Hydrologic Engineering, offers a method for monitoring and simulation on campuses and other small-scale areas, which can provide important technical support for the early warning of urban flooding.
Learn more about their study and how it can provide strong technical support for urban flood control research. Read the abstract below, then the full paper in the ASCE Library: https://ascelibrary.org/doi/10.1061/(ASCE)HE.1943-5584.0002113
Abstract
Accurate 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.
Read the full paper in the ASCE Library: https://ascelibrary.org/doi/10.1061/(ASCE)HE.1943-5584.0002113
