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.