Author(s): Mengnan He; Cheng Chen; Donghao Wu

Linked Author(s):

Keywords: Flow pattern; Cellular automata; Converge flow; Diverge flow; Water distribution weight

Abstract: Accurately characterizing urban surface runoff process is essential for reducing the uncertainty of urban hydrological model. Based on the quantification of flow pattern urban surface runoff flow characteristics, this study proposed an optimal urban flow direction algorithm based on cellular automata (UCA), and the UCA algorithm was verified by the the numerical simulation and physical experiments under different rainfall events. Results showed that the optimal water distribution weights of UCA algorithm for converge flow and diverge flow are 2.0 and 1.1 respectively. The relative error and root mean square error between the UCA’s simulation and theoretical values of specific catchment area are the smallest on ellipsoid, inversed ellipsoid, saddle and plane slopes. The Nash Efficiency (NSE) coefficient of UCA algorithm is significantly higher than that of the classical 4+4N algorithm (with an increase of NSE by 0.12~0.69). In particular, the misjudgment of the initial runoff flow pattern by the 4+4N algorithm can be effectively corrected under the light rain event, which can provide a better solution for urban waterlogging and non-point source pollution modeling in the future.

DOI: https://doi.org/10.3850/iahr-hic2483430201-138

Year: 2024