Integrating Grey–Green Infrastructure in Urban Stormwater Management: A Multi–Objective Optimization Framework for Enhanced Resilience and Cost Efficiency
Year: 2025
Type: article
Abstract: Urban stormwater management systems are increasingly strained by rapid urbanization and climate change, yet existing planning approaches often lack holistic optimization frameworks that account for both green and grey infrastructure (GREI) under uncertain future conditions. This study introduces a multi–objective optimization framework for Grey–Green Infrastructure (GGI), which integrates green infrastructure (GI) with GREI to enhance urban flood resilience, cost efficiency, and adaptability. The framework addresses life cycle cost (LCC), technological resilience (Tech-R), and operational resilience (Oper-R), offering a comprehensive approach to navigating the complexities of urban stormwater management. Key findings reveal that: (1) GGI systems optimized for resilience achieve a 33% improvement in Oper-R, with only a marginal increase in LCC of less than 9%, highlighting their robustness under GREI failure scenarios; (2) the integration of bioretention cells (BCs) and porous pavements (PPs) into GGI increases Tech-R by 7.1%, enhancing soil water retention and permeability, particularly in densely urbanized contexts; and (3) decentralized GGI systems exhibit superior adaptability to extreme weather events, with Design D reducing LCC to USD 53.9 M while maintaining no overflow under a 5–year rainfall event. The framework was validated in Zhujiang New Town, Guangzhou, where optimized GGI designs reduced average pipe diameters and manhole depths by 0.2–0.3 m compared to GREI–only systems, demonstrating both cost and resilience advantages. These findings provide decision–makers with a robust tool for evaluating trade–offs in stormwater infrastructure planning, advancing sustainable urban water management.
Source: Applied Sciences
DOI: 10.3390/app15073852
Authors: Lie Wang, Jiayu Zhao, Ziheng Xiong, Ji’an Zhuang, Mo Wang
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G6530796832
OpenAlex ID: W4409048479
