Assessing Urban Flood Resilience through the Lens of a Dynamic Flood Resilience Index: Systematic Review
Abstract
Urban flooding is becoming more frequent and damaging due to the combined effects of climate change and rapid urbanization, exposing the limitations of conventional risk-based flood-management approaches. Consequently, resilience-based strategies have gained attention for managing uncertainty, system complexity, and recovery capacity in urban flood contexts. Flood-resilience index (FRI) frameworks are widely used to operationalize resilience by integrating social, economic, infrastructural, institutional, and environmental dimensions into composite indicators. However, many existing FRI frameworks rely on static or snapshot-based assessments that inadequately represent feedback mechanisms, temporal evolution, and nonstationary flood regimes. This study presents a systematic literature review examining how geographic information systems (GIS), multicriteria decision-making (MCDM), and system dynamics modeling (SDM) have been applied individually and in combination to support urban flood-resilience assessment. Seventy-six peer-reviewed studies published between 2010 and 2024 were analyzed using qualitative content analysis and frequency-based quantitative synthesis. The review synthesizes dominant methodological practices and identifies recurring limitations related to indicator aggregation, weighting, spatial representation, uncertainty treatment, and temporal dynamics. The findings show that GIS–MCDM approaches enable spatially explicit and structured resilience assessment but are commonly constrained by static assumptions and criterion independence. SDM applications offer strong potential for capturing feedback-driven system behavior and for the long-term evolution of resilience, yet are rarely integrated with GIS-based MCDM FRIs. The paper proposes a formalized synthesis-based framework that integrates GIS, MCDM, and SDM to support spatially explicit and dynamically informed urban flood-resilience assessment. It highlights key research gaps for future development.