Green roofs are effective tools for stormwater control in highly urbanized areas since they allow the reduction of peak runoffs and volumes discharged in sewer systems. Their design is quite standardized, except for the thickness of the growing medium layer, which is strictly related to vegetation type and rainfall regime. The paper proposes an analytical probabilistic approach that relates the climatic variables, the growing medium thickness, and the water content in the condition of fulfilled field capacity to the probability that runoff from green roofs exceeds a fixed threshold. The developed equations also consider the possibility of a reduced retention capacity due to previous rainfall events, that strongly influence the performance of these green infrastructures, especially when short dry periods and/or low evapotranspiration rates occur. This feature, neglected by the traditional design storm approach, and only partially considered by previous analytical probabilistic models, represent a great potentiality of the proposed equations that are also more user-friendly and less time-consuming than continuous simulation analysis. The focus of the paper is on the influence of climatic parameters on runoff probability. To this aim to perform the monthly analysis is fundamental, especially when there is a strong variability of the climatic parameters throughout the year. The model was tested in a case study in Milano, Italy. The application presented a good agreement between the results obtained from the proposed equations and those obtained from the continuous simulation of recorded data. The results also highlighted the importance of performing analysis on a monthly scale.
Keywords: Climatic parameters; Flood risk mitigation; Green roofs; Probabilistic models; Stormwater management.
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