Abstract. Flash floods have occurred frequently and severely in the urban areas of South China. An effective process-oriented urban flood inundation model becomes an urgent demand for urban storm water and emergency management. This study develops an effective and flexible cellular automaton (CA) model to simulate storm water runoff and the flood inundation process during extreme storm events. The process of infiltration, inlets discharge and flow dynamic can be simulated only with little pre-processing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented in a cellular automation (CA) model to govern the water flow in a 3 x 3 cell template of a raster layer. The model is calibrated by one storm event and validated by another in a small urban catchment in Guangzhou of Southern China. The depth of accumulated water at the catchment outlet is interpreted from street monitoring sensors and verified by on-site survey. A good level of agreement between the simulated process and the reality is reached for both storm events. The model reproduces the changing extent and depth of flooded areas at the catchment outlet with an accuracy of 4 cm in water depth. Comparisons with a physically-based 2-D model (FloodMap) results show that the model have the capability of simulating flow dynamics. The high computational efficiency of CA model can satisfy the demand of city emergency management. The encouraging results of the simulations demonstrate that the CA-based approach is capable of effectively representing the key processes associated with a storm event and reproducing the process of water accumulation at the catchment outlet for making process-considered city emergency management decisions.
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