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Chinese Journal of Applied Ecology ›› 2018, Vol. 29 ›› Issue (12): 4089-4096.doi: 10.13287/j.1001-9332.201812.020

• Research paper • Previous Articles     Next Articles

Simulation of sponge city landscape pattern optimization based on the storm water management model (SWMM)

CHU Ya-qi1*, ZENG Jian1, SHI Yu2, XIU Dai-xi2   

  1. 1Tianjing University School of Architecture, Tianjin 300072, China;
    2Shenyang Jianzhu University, Shenyang 110168, China
  • Received:2018-07-18 Revised:2018-10-11 Online:2018-12-20 Published:2018-12-20
  • Supported by:
    This work was supported by the National Natural Science Foundation Key Project of China (51438009), the Ministry of Education Philosophy and Social Science Major Project (15JZD025), and the Liaoning Province Key Research and Development Foundation Project (2017229003).2018-07-18 Received, 2018-10-11 Accepted.*

Abstract: With the rapid urbanization and increasing urban impervious areas in China, urban water-logging has become increasingly serious. The concept of sponge city was proposed based on the low impact development (LID) idea. We analyzed the impacts of landscape pattern optimization scenario on urban surface runoff and rainwater control ability in central urban area of Shen-Fu New Town in Liaoning Province. The storm intensity formula was used to construct rainfall process in different return periods. The landscape patterns of the study area were optimized based on sponge city concept. The storm water management model (SWMM) was used to simulate the differences of surface runoff and rainwater regulation ability under the pre-planning scenario and the landscape pattern optimization scenario. The results showed that total runoff and runoff coefficient of the study area were increased with increasing rainfall return period. In the same rainfall return period, the runoff coefficient was significantly reduced. The reduction of total runoff gradually increased, being 2.94, 3.58, 3.72, and 4.19 mm during the 1-year, 3-year, 5-year and 50-year return period under landscape pattern optimization scenario. The corresponding reduction rate was gradually reduced, being 23.9%, 16.4%, 14.3%, and 9.3%, respectively. Landscape pattern optimization scenario could meet the requirements that the rainfall was controlled at 20.8 mm when the rainfall return period p=1 year, the rainwater pipe network would not overload when p=3 years, and the river channel would not overflow when p=50 years.