4.7 Article

Construction of a cellular automata-based model for rainfall-runoff and NPS pollution simulation in an urban catchment

Journal

JOURNAL OF HYDROLOGY
Volume 568, Issue -, Pages 929-942

Publisher

ELSEVIER
DOI: 10.1016/j.jhydrol.2018.11.029

Keywords

Cellular automata; Nonpoint source pollution; Hydrology; Overland routing process; Landscape configuration; Urban

Funding

  1. State Key Program of National Natural Science Foundation of China [41530635]
  2. Open Foundation of the State Key Laboratory of Urban and Regional Ecology of China, China [SKLURE2017-2-2]
  3. Interdiscipline Research Funds of Beijing Normal University, China

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Overland routing processes are critical for understanding the water environment impact of the urbanization-induced land-cover change and guiding the optimized landscape planning. However, current models generally tend to simplify the overland flow process by a semi-distributed routing approach. In this study, the cellular automata-based hydrology and NPS pollution model (CA-HNPSM) is established by integrating the CA-based overland runoff routing algorithm and the NPS pollution module. Three-layer spaces were also constructed by considering the hydrological connection among urban roofs, land surfaces and artificial drainage networks. Simplified sewer routing modules were introduced to improve the applicability of the CA algorithm in urban NPS pollution studies with insufficient drainage data. Then, the CA-HNPSM is tested in a real case study on an urban catchment in Beijing, China. Based on the results, the CA-HNPSM shows good performance in both the hydrological and NPS simulations in terms of the Nash-Sutcliffe efficiency coefficient and coefficient of determination. Detailed overland routing processes and hydrological and pollution results are provided. In addition, landscape configurations along the overland flow routs could also be identified. These overland results can be used as powerful reference for optimized landscape planning and the allocation of management measures.

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