Green infrastructure practice and a sustainability key performance indicators framework for neighbourhood-level construction of sponge city programme

In recent years, the Sponge City program (SCP) of China, as a sustainable stormwater management approach, has been strengthened as a national strategic level program. The Green Infrastructure (GI), due to its multi-objective and multi-benefits, has been adopted as an important measure of this new nationwide initiative. However, there is a lack of a comprehensive quantitative evaluation system for neighbourhood scale SCP. Hence, in the process of GI plan optimization, selection of implementation methods to balance its multi-benefits has become one of the key obstacles in the practice of SCP. To support robust decision making on multi-objective GI planning and comprehensive assessment, the analytic hierarchy process (AHP) has been used as a structural and systematic technique. In addition, a set of sustainability key performance indicators (KPIs) including requisite dimensions is the foundation for neighbourhood scale sustainability. Hence, AHP-based evaluation system including selection, weighting and ranking of the KPIs, is defined as a key performance indicator framework (KPIF), which is still in need for further development. Taking the GI planning for the Liangnong, Siming Lake sponge node restoration as an example, this paper develops KPIF with a comprehensive evaluation system for high-quality “Sponge Node” transitional construction. This KPIF consists of three basic criteria: “Environmental Performance”, “Economic and Adaptability Performance”, and “Social-cultural Performance and Wellbeing Performance”. In addition, 15 weighted KPIs are concluded and amongst them, the followings were relatively high: weight of the ATRCR, the promotion of biodiversity, the construction cost saving, the maintenance cost saving, and the level of recreational and wellbeing improvements for all people. In addition, the developed KPIF provides a reference for similar program’s decision-making, not only for the Jiangnan area of China, but also for quantitatively comprehensive evaluations of SCP in other regions.