Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata
journal contributionposted on 06.03.2015, 11:39 by L. Liu, Y. Liu, X. Wang, Dapeng Yu, K. Liu, H. Huang, G. Hu
Flash floods have occurred frequently in the urban areas of southern China. An effective process-oriented urban flood inundation model is urgently needed for urban storm-water and emergency management. This study develops an efficient 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 dynamics can be simulated with little preprocessing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented to govern the water flow in a rectangular template of three cells by three cells 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 closed-circuit television (CCTV) videos 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) show that the model is capable of effectively simulating flow dynamics. The high computational efficiency of the CA model can meet the needs of city emergency management.
This work was supported by the National High Technology Research and Development Program of China (863 Program) (no. 2012AA121402, 2012AA121403), the National Basic Research Program of China (973 Program) (no. 2012CB955903) Foundations, the National Natural Science Foundation of China (no. 41301419), and Fundamental Research Funds for the Central Universities (no. 14gpy09)
- Social Sciences
- Geography and Environment