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Evaluating the effectiveness of environmental sustainability indicators in optimizing green-grey infrastructure for
Yu Zhang1, Haiwei Yin2, Ming Liu3
1School of Architecture and Urban Planning, Nanjing University, No 22, Hankou Road, Nanjing 210093, PR China; Key Laboratory of Urban AI and Green Built Environment of Provincial Higher Education Institutes, Nanjing University, No 22, Hankou Road, Nanjing 210093, PR China.
Abstract:
Green-grey infrastructure is recommended as an innovative stormwater management strategy in response to urban flooding and climate change. Currently, the indicators used to optimize sustainable green-grey infrastructure and evaluate its stormwater management performance have been limited and based on self-defined criteria. In this study, we developed a comprehensive environmental sustainability indicator that integrates reliability, resilience, vulnerability, and hydrological sustainability as one of the objectives for optimizing green-grey infrastructure layout. The new indicator fully considered both system-level and component-level failures. Graph-theoretic algorithm coupled with NSGA-Ⅱ was applied to support the layout design and optimization. Additionally, the hydro-hydraulic performance of representative optimized layouts under extreme storms and climate change scenarios was re-evaluated to compare the effectiveness of various self-defined environmental sustainability indicators. The results demonstrated that under the same budget conditions, layouts optimized using the environmental sustainability indicator proposed in this study demonstrated superior performance, primarily reflected in less flood severity, flood duration, and conduit surcharge. Furthermore, it was effective and necessary to comprehensively consider the system-level overload consequences, the component-level failure-recovery process, and the extent of restoration to the natural hydrological state in the green-grey optimization process. This framework aims to address the stormwater management challenges posed by short-term extreme storms and long-term climate changes, while balancing sustainable economic and natural hydrological states.
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