High-performance computing in urban flood modeling: A study on spatial partitioning techniques and parallel performance☆

China has been frequently affected by urban flooding incidents in recent years. Using hydrodynamic models to simulating urban flooding process is an effective measure in flood control. Considerable literatures of hydrodynamic models confine its scope to relatively small areas or low-resolution limited by computing resources and model performance. Relatively less research of HPC in urban flood modeling is conducted. This paper introduces a parallel model based on hydrodynamic principles and MPI, designed for simulating urban flooding runoff processes on the powerful computing resources of a national supercomputing center in China. Detailed simulations of the runoff process and the distribution of flood-prone areas within the campus of Tsinghua University under varying storm conditions are studied. Six distinct 2D parallel partitioning arrangement schemes are tested and timed for performance assessment. A comprehensive analysis is conducted on each partitioning scheme's parallel performance. The findings indicate that the model demonstrates near-linear speed-up with remarkable efficiency. This model holds the potential for practical application in large-scale parallel computing, offering significant advancements in flood prediction.