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Original Articles

Assessing stormwater runoff reduction capacity of existing green infrastructure in the city of Ghent

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Pages 749-761 | Received 31 Jan 2020, Accepted 03 Mar 2020, Published online: 17 Mar 2020
 

ABSTRACT

Stormwater runoff is the major source of surface flooding in urban communities. Urban surface water flooding is one of the most worrisome issues, due to their negative impacts on public health. Green infrastructure has developed as an alternative approach to cope with urban surface water flooding. The runoff reduction capacity of green infrastructure needs to be elucidated to better support green infrastructure planning. There are some models to assess the runoff reduction capacity of the landscape. However, these models do not consider landscape patterns and usually need large time, data, making it less accessible to urban planners and decision-makers. A group of studies have indicated that landscape structures are significantly affecting the surface runoff. Therefore, an empirical model was adapted in this study, including two parameters of runoff coefficient and landscape metrics, to map the runoff reduction capacity of green infrastructure in the city of Ghent. The results show that grasslands contribute most to stormwater runoff reduction of 118.3 million m3 and forests controlled the lowest runoff of 44.8 million m3. Agriculture lands with the highest reduction amount per square kilometer of 3.51 million m3/km2, and Forests with the lowest of 1.92 million m3/km2. The spatial distribution of runoff reduction capacity of green infrastructure indicates the high capacity green infrastructure is mainly concentrated in the southwest and northeast suburban areas. The core areas scattered with less green infrastructure and low runoff reduction capacity. The results provide a better understanding of spatial characteristics and stormwater runoff reduction capacity of existing green infrastructure in Ghent.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the China Scholarship Council.

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