Adaptation as an indicator of measuring low-impact-development effectiveness in urban flooding risk mitigation

Frequent and intensive urban flooding requires an extensive adoption of low-impact development (LID) to supplement traditional drainage infrastructures. Our study conceptualizes the resilient infrastructure framework with a particular reference to adaptation, an adjustment capacity in the social-ecological system to withstand various natural hazards and absorb negative impacts. We argue that adaption is an indicator for measuring LID effectiveness. A methodological framework is adopted using a time-dependent technique with a hydrodynamic inundation model to evaluate LID effectiveness. Results of a case study in Gongming, Shenzhen, China, show that LID projects can effectively reinforce adaptation capacity. However, spatial inequality and accumulation of different levels of adaptation are evident. This outcome is due to a relatively low absorption capacity because most areas will have a relatively high recovery capacity but retain a low absorption capacity with the construction of LID projects. A relatively mild increase in absorption capacity is due to the quality of man-made infrastructural development is conflicting across different areas of Gongming, for example some infrastructures are constructed by the government, whereas others by developers and villagers. In addition, the topographical factor makes some areas in Gongming lower-lying than others and is therefore increasingly vulnerable to urban flooding during rainstorms given the difficulty of discharging the surface runoff, thereby limiting the effectiveness of LID projects. Furthermore, the spatial inequality of adaptation improvement where LID projects cannot be evenly distributed within the research area leads to the unequal distribution of adaptation. These findings can confirm that the government can practically use adaptation as an indicator in evaluating LID effectiveness and identifying the problematic stages of drainage resilience in urban flooding risk mitigation. (C) 2019 Published by Elsevier B.V.