Green Infrastructure as a Climate Shield: Nonlinear Flood Response and Extremes Saturation in a Tropical Andean Urban Watershed

ABSTRACT Assessing flood risk under climate change in data‐scarce tropical mountain watersheds requires transparent, reproducible frameworks that explicitly address methodological uncertainties. This study introduces an integrated methodology to evaluate green infrastructure's hydrological role across land‐cover and climate scenarios. It combines Coupled Model Intercomparison Project Phase 6 (CMIP6) projections with Quantile Mapping bias correction, Generalized Extreme Value (GEV) analysis, physically informed intensity–duration–frequency (IDF) curve development, and spatially explicit Hydrologic Engineering Center–Hydrologic Modeling System (HEC‐HMS). Designed for regions with limited gauging infrastructure, the framework leverages satellite‐derived precipitation from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), open‐access climate data. Applied to the Güanguiltagua Metropolitan Park in Quito, Ecuador, the approach reveals context‐specific responses: under projections from the Max Planck Institute Earth System Model version 1.2 Low Resolution (MPI‐ESM1‐2‐LR), extreme events (return periods T ≥ 50 years) exhibit a saturation signal converging towards ~95 mm/day—a pattern consistent with documented shifts in Andean convective regimes yet contingent on model resolution and requiring validation with convection‐permitting simulations. Critically, conservation of natural cover (Curve Number, CN = 45) consistently reduces peak flows by 73%–85% across all scenarios and return periods, demonstrating green infrastructure's dependable buffering capacity. Urbanized sub‐basins (CN = 85) show minimal climate sensitivity, underscoring persistent vulnerability. Findings are explicitly contextualized within methodological constraints (single general circulation model [GCM], coarse resolution, Soil Conservation Service Curve Number [SCS‐CN] assumptions), avoiding overgeneralization. The framework's modular design enables adaptation across Global South contexts, offering a transparent template for region‐specific flood risk assessment where climate projections and green infrastructure intersect.