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Assessing the effectiveness of green infrastructures on urban flooding reduction: A community scale study

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  • Liu, Wen
  • Chen, Weiping
  • Peng, Chi

Abstract

The risk of urban flooding is increasing as a result of rapid urbanization. Green infrastructure (GI) is an emerging planning and design concept to mitigate urban flooding. A community scale simulation model was developed to quantify the effectiveness of GI on reducing the volume and peak flow of urban flooding. Five scenarios, namely expanding green space, converting to concave green space, constructing a runoff retention structure, converting to porous brick pavement, and combining previous four measures were considered for an urban community in Beijing. The outcomes showed that the model performed responsively to simulate the storm runoffs at varying recurrence intervals under these scenarios. Simulation results showed that, the impervious surfaces have the most contribution to the storm runoffs of the community. The reduction capacity for single GI facility was limited, especially in bigger storm events. The integrated GI configuration has effective reduction percentage, such as the total runoff reduction was ranged from 100% to 85.0% and the peak flow reduced 100–92.8%. This work can guide local planners and decision makers in their actions on green infrastructures in community scale.

Suggested Citation

  • Liu, Wen & Chen, Weiping & Peng, Chi, 2014. "Assessing the effectiveness of green infrastructures on urban flooding reduction: A community scale study," Ecological Modelling, Elsevier, vol. 291(C), pages 6-14.
    • Handle: RePEc:eee:ecomod:v:291:y:2014:i:c:p:6-14
    DOI: 10.1016/j.ecolmodel.2014.07.012
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    References listed on IDEAS

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    1. Luis Bettencourt & Geoffrey West, 2010. "A unified theory of urban living," Nature, Nature, vol. 467(7318), pages 912-913, October.
    2. Chen, Shaoqing & Chen, Bin & Fath, Brian D., 2013. "Ecological risk assessment on the system scale: A review of state-of-the-art models and future perspectives," Ecological Modelling, Elsevier, vol. 250(C), pages 25-33.
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