Development of a Decision Support System for Optimizing Urban Green Infrastructure Placement to Maximize Stormwater Infiltration and Reduce Flood Risk under Climate Change Scenarios

Urban flooding is increasingly concerning due to climate change and rapid urbanization. Factors such as intensified rainfall, urban sprawl, and reduced permeable surfaces heighten flood risks, making efficient stormwater management crucial. This study focuses on developing a Decision Support System (DSS) to optimize green infrastructure (GI) placement in urban areas, aiming to enhance stormwater infiltration and reduce flood risks under climate change scenarios. The research reviews current strategies for GI planning and DSS in urban flood management. By integrating GIS tools, hydrological models, and climate data, the DSS identifies ideal locations for GI measures like rain gardens, bioswales, and permeable pavements, promoting effective stormwater management while addressing climate change. Hydrological models simulate stormwater behavior under varying rainfall conditions, and GIS maps potential GI sites within urban areas. Simulations of future extreme rainfall events assess GI performance under changing climate conditions. Results show significant reductions in stormwater runoff and flood risks, particularly in areas with high impervious surfaces. Challenges such as space constraints in dense urban areas, scalability of GI solutions, and long-term maintenance are discussed. The study concludes that integrating GI with traditional stormwater systems offers a comprehensive approach to urban flood mitigation, with the DSS serving as a key tool for urban planners and policymakers.