Parallelization of a two-dimensional flood inundation model based on domain decomposition

Flood modelling often involves prediction of the inundated extent over large spatial and temporal scales. As the dimensionality of the system and the complexity of the problems increase, the need to obtain quick solutions becomes a priority. However, for large-scale problems or situations where fine resolution data is required, it is often not possible or practical to run the model on a single computer in a reasonable timeframe. This paper presents the development and testing of a parallelized 2D diffusion-based flood inundation model (FloodMap-Parallel) which enables largescale simulations to be run on distributed multi-processors. The model has been applied to three locations in the UK with different flow and topographical boundary conditions. The accuracy of the parallelized model and its computational efficiency have been tested. The predictions obtained from the parallelized model match those obtained from the serialized simulations. The computational performance of the model has been investigated in relation to the granularity of the domain decomposition, the total number of cells and the domain decomposition configuration pattern. Results show that the parallelized model is more effective with simulations of low granularity and a large number of cells. The large communication overhead associated with the potential loadimbalance between sub-domains is a major bottleneck in utilizing this approach with higher domain granularity.