Accuracy and Computational Efficiency of 2D Urban Surface Flood Modelling Based on Cellular Automata

Abstract

There is an emerging abundance of freely available high resolution (one meter or less) LIDAR data due to the advent of remote sensing, which enables wider applications of detailed flood risk modelling and analysis. Digital terrain surface data often comes in raster form, i.e., a square regular grid, and often requires conversion into a specific computational mesh for two-dimensional (2D) flood modelling that adopts triangular irregular meshes. 2D modelling of flood water movement through urban areas requires resolution of complex flow paths around buildings, which requires both high accuracy and computational efficiency. Water distribution and wastewater systems in the UK contain over 700,000km of water distribution and sewer pipes, which represents a large risk exposure from flooding caused by sewer surcharging or distribution pipe breaks. This makes it important for utilities to understand and predict where clean or dirty water flows will be directed when they leave the system. In order to establish risk assessment many thousands of simulations may be required, calling for the most computational efficient models possible.Cellular Automata (CA) represents a method of running simulations based on a regular square grid, thus saving set-up time of configuring the terrain data into an irregular triangular mesh. It also offers a more uniform memory pattern for very fast modern, highly parallel hardware, such as general purpose graphical processing units (GPGPU). In this paper the performance of the CADDIES [1], a CA platform and associate flood modelling software caFloodPro, using a square regular grid and Von Neumann neighbourhood, is compared to industry standard software using triangular irregular meshes for similar resolutions. A minimum time step is used to control the computational complexity of the algorithm, which then creates a trade-off between the processing speeds of simulations and the accuracy resulting from the limitations used within the local rule to cope with relatively large time steps. This study shows that using CA based methods on regular square grids offers process speed increases in terms of 5-20 times over that of the industry standard software using irregular triangular meshes, while maintaining 98-99% flooding extent accuracy.