Urban   neighbourhoods face pluvial flood and heatwave risks which can be tackled   using blue green infrastructure (BGI), yet existing BGI design tools cannot   parametrically evaluate multi-hazard performance at the design stage. This   thesis develops an integrated parametric workflow combining FastFlood and   ENVI-met within Grasshopper, enabling systematic variation of BGI parameters   across trees, shrubs, surfaces, and water bodies, with simultaneous   assessment of flood depth, flow velocity, and daytime/evening thermal   comfort. Performance is structured through the IPCC risk framework (flood   sensitivity, heat sensitivity, and adaptive capacity) to identify which   parameters most influence outcomes and under what conditions.

Results show   surface roughness dominates flood performance while trees dominate daytime   heat mitigation, with clear trade-offs between hazard domains, confirming BGI   design cannot be reduced to single-hazard optimization. A TOPSIS-based   multicriteria framework translates this evidence into comparative design   guidance, demonstrating that strategy preferences are sensitive to criterion   weights, particularly when adaptive capacity indicators are included.

The thesis   concludes that a parametric BGI workflow is both feasible and necessary,   offering a replicable methodology for evidence-informed, climate-adaptive   urban design.