Strategic implementation of green roofs for urban pluvial flood risk reduction: A case study of Milan, Italy

The rise in intensity and frequency of extreme precipitation events is increasing the concern regarding pluvial floods in European cities. Urbanisation exacerbates the impacts of pluvial floods by affecting the infiltration process. Nature-based solutions, particularly Green Roofs (GRs), are promoted to mitigate these risks, as GRs can be implemented on existing buildings without requiring additional ground space. This study presents a risk-based framework to evaluate the potential of GRs in reducing pluvial flood risk in Milan by examining three implementation strategies, namely Water Depth (WD), Area (Ar), and Random Iteration (ITE). The framework integrates a hybrid hazard model, combining the empirical Curve Number method with a Cellular Automata approach using a hydrograph. The proposed hybrid approach enables us to link land-use-driven changes in flood volume to flood propagation. Extreme rainfall events with durations of 1, 6, and 24 hours were derived from ERA5. Residential building exposure data were extracted from OpenStreetMap and municipal datasets. Vulnerability was integrated within the framework using the INSYDE model, complemented by four additional vulnerability functions for sensitivity analysis. Results indicate that GRs can effectively reduce pluvial flood-induced losses, with reductions of 16-69% across different rainfall durations. However, their effectiveness declines with longer rainfall periods and higher return periods. Among the allocation strategies, WD provided higher benefits for events with durations of 1 and 6 hours. Overall, GRs can substantially reduce flood risk. The study provides an integrated framework to support evidence-based decision-making for the strategic implementation of GRs for pluvial flood risk reduction.