A multi-objective decision-making framework for implementing green-grey infrastructures to enhance urban drainage system resilience

Abstract

Green-grey infrastructures implementation for addressing urban flood damages and urban drainage system’ (UDS) resilience (respectively) needs comprehensive evaluation under various planning and design influencing factors. In this paper, a multi-objective decision-making framework is developed for the optimization of green-grey infrastructures to understand the trade-off between benefits and retrofit costs under various design configurations, rainfall intensities, and system performance indicators. In the developed framework, the grey infrastructure locations are optimally determined by using Analytic Hierarchy Process (AHP) method with three defined indicators (e.g., flood volume and flood duration of flooding nodes, sensitivity of flooding nodes) and maximum percentage of each type of green infrastructure (GI) in each sub-catchment based on land-use analysis as a preliminary step of the multi-objective optimization process, followed by decision-making procedure. The application results reveal that optimal designs of grey infrastructure are more cost-effective and may have a significant influence on the reduction of flood damages and outlet peak flow compared to GI from their individual evaluations, while GI improves UDS’ functionality performance indicators (e.g., resilience, reliability, and sustainability) better than grey infrastructure. However, a combined implementation of both infrastructures boosts their advantages because of the synchronization effect compared to individual scenarios, providing the most cost-effective optimal UDS designs. Moreover, the cost-effectiveness of coupled green-grey infrastructures designs could be enhanced from lower to higher design storms because of higher rate of utilization of stormwater infiltration and storage capacities of both infrastructures. The framework presented in this study can be conveniently generalized to other case-studies for optimal implementation of green-grey infrastructures as long as including their local economic parameters, climatic patterns, urban development plans and green-grey infrastructures design guidelines.