A Conceptual Flood Model Based on Cellular Automata for Probabilistic Risk Applications.

This paper describes a simplified flood model based on cellular automata in order to be implemented in applications, which require the simulation of a great number of flood scenarios at regional scale. The model is based on a top-down evaluation of the flow process through the cells of the DEM. According to the conditions in a Moore Neighbourhood, the cells are classified in a dynamic process in four possible states with its own rules. To verify the quality of the results, an evaluation is carried out using the benchmarking tests and results shown in Neelz and Pender (2013). Besides, the 2D models HEC-RAS and Iber were used to evaluate quantitatively the efficiency of the model in terms of water depth and flood extent. From this, it is observed that the model produces very acceptable results especially where dynamic effects are less significant.