In view of the frequent occurrence of floods due to climate change, and the fact that a large calculation domain, with complex land types, is required for solving the problem of the flood simulations, this paper proposes an optimized non-uniform grid model combined with a high-resolution model based on the graphics processing unit (GPU) acceleration to simulate the surface water flow process. For the grid division, the topographic gradient change is taken as the control variable and different optimization criteria are designed according to different land types. In the numerical model, the Godunov-type method is adopted for the spatial discretization, the TVD-MUSUL and Runge-Kutta methods are used to improve the model’s spatial and temporal calculation accuracies, and the simulation time is reduced by leveraging the GPU acceleration. The model is applied to ideal and actual case studies. The results show that the numerical model based on a non-uniform grid enjoys a good stability. In the simulation of the urban inundation, approximately 40%–50% of the urban average topographic gradient change to be covered is taken as the threshold for the non-uniform grid division, and the calculation efficiency and accuracy can be optimized. In this case, the calculation efficiency of the non-uniform grid based on the optimized parameters is 2–3 times of that of the uniform grid, and the approach can be adopted for the actual flood simulation in large-scale areas.

针对气候变化导致洪水频繁发生，以及解决洪水模拟问题需要大的计算域、复杂的土地类型，本文提出了一种优化的非均匀网格模型。基于图形处理单元（GPU）加速的高分辨率模型，用于模拟地表水流动过程。网格划分以地形坡度变化为控制变量，根据不同的土地类型设计不同的优化准则。在数值模型中，采用Godunov型方法进行空间离散化，采用TVD-MUSUL和Runge-Kutta方法提高模型的时空计算精度，并利用GPU加速减少仿真时间。该模型适用于理想和实际案例研究。结果表明，基于非均匀网格的数值模型具有良好的稳定性。在城市淹没模拟中，以待覆盖的城市平均地形坡度变化的约40%～50%作为非均匀网格划分的阈值，可以优化计算效率和精度。在这种情况下，基于优化参数的非均匀网格计算效率是均匀网格的2-3倍，该方法可用于大范围地区的实际洪水模拟。以要覆盖的城市平均地形坡度变化的约40%~50%作为非均匀网格划分的阈值，可以优化计算效率和精度。在这种情况下，基于优化参数的非均匀网格计算效率是均匀网格的2-3倍，该方法可用于大范围地区的实际洪水模拟。以要覆盖的城市平均地形坡度变化的约40%~50%作为非均匀网格划分的阈值，可以优化计算效率和精度。在这种情况下，基于优化参数的非均匀网格计算效率是均匀网格的2-3倍，该方法可用于大范围地区的实际洪水模拟。