Refining Assignment of Runoff Control Targets with a Landscape Statistical Model: A Case Study in the Beijing Urban Sub-Center, China

Abstract

Rapid urbanization has triggered large changes to both the urban landscape and the yield and degree of confluence of runoff. The annual runoff volume control rate (ARVCR) is the key target identified in sponge city overall planning and is based on local natural and social conditions. However, the large impact that landscape patterns have on the runoff process causes the capacity to implement the targets to differ between those patterns. Refinement of ARVCR targets based on landscape pattern indices is therefore needed. This study identified statistical relationships between landscape indices and runoff control targets in the delta pilot region of the Beijing urban sub-center and extended the statistical model to the Beijing urban sub-center, an area almost 20 times larger than the pilot region. Landscape factors were quantified based on their area, shape, and distribution. In the delta pilot region, the runoff control volume for each block was obtained from a simulation using the SWMM model, and the correlation between landscape indices and runoff control volume capacity in different functional land-use blocks was identified by multiple linear stepwise regression. Because the distributions of landscape indices were similar in the pilot delta area and the Beijing urban sub-center, the model could be extended to the much larger study area. The statistical model provided a runoff control scheme that produced a refined assignment of the total annual runoff control target and provided guidance that could be implemented in land-use planning.