A framework for urban pluvial flood resilient spatial planning through blue-green infrastructure

Blue-Green Infrastructure (BGI) is gaining global recognition as an innovative pathway to urban resilience. Current research on urban flood resilience focus on outcome-based variables like runoff, flood depth, duration, etc. with very limited studies on the inherent capacity of the system to adapt and transform in a disaster. Outcome-based assessments can result in overestimating risk and underestimation of resources in a socio-ecological system. Another lacuna is the theoretical ambiguity on 'resilience', as many studies considered resilience as a normative condition ignoring the notion of socio-ecological resilience as a capacity. The lack of a multi-dimensional approach is also a major research gap. The impact created by BGI in flood resilience depends on socio-political and bio-physical dimensions. To address these gaps, this study identifies and prioritizes the critical BGI dimensions, criteria, and variables and proposes a framework to optimize flood-resilient spatial planning. This research uses a systematic literature review with multi-criteria decision-making (MCDM) to identify and prioritize parameters. Three primary criteria: (a) capacity, (b) connectivity, and (c) diversity with 42 variables are identified to assess urban flood resilience. The results are validated and weighted using MCDM techniques of Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). The study outcome is presented as a framework of dimensions, criteria, and variables that can evaluate the adaptive and transformative capacity of BGI. This research can be improved by including dimensions of physical infrastructure and by performing a case study-based validation. This study provides an effective methodological framework to assess and spatially represent urban flood resilience based on impact variables. The proposed framework is significant in the visual mapping of urban flood resilience in combination with geographic information systems.