In this paper, two emerging strategies for the reduction of the computational time of 2D large-scale flood simulations are compared, with the aim of evaluating their strengths and limitations and of suggesting guidelines for their effective application. The analysis is based on two state-of-the-art raster flood models with different governing equations and parallelization strategies: PARFLOOD, a GPU-accelerated code that solves the fully dynamic shallow water equations, and LISFLOOD-FP, which combines a parallel implementation for CPU with simplified equations (local-inertial approximation). The results of two case studies (a river flood propagation, and a lowland inundation) suggest that, at coarse grid resolutions, the parallelized simplified model LISFLOOD-FP can represent a good alternative to fully dynamic models in terms of accuracy and runtime, while the GPU-parallel code PARFLOOD is more efficient in case of high-resolution simulations with millions of cells, despite the greater complexity of the numerical scheme.

在本文中，对减少二维大规模洪水模拟计算时间的两种新兴策略进行了比较，目的是评估它们的优势和局限性，并为它们的有效应用提出指导方针。该分析基于具有不同控制方程和并行化策略的两种最先进的栅格洪水模型：PARFLOOD，一种用于求解全动态浅水方程的 GPU 加速代码，以及 LISFLOOD-FP，它结合了并行实现对于具有简化方程（局部惯性近似）的 CPU。两个案例研究（河流洪水传播和低地淹没）的结果表明，在粗网格分辨率下，