The Influence of Hydrologic Parameters on the Hydraulic Efficiency of an Extensive Green Roof in Mediterranean Area

In an urban environment, green roofs represent a sustainable solution for mitigating stormwater volumes and hydrograph peaks. So far, many literature studies have investigated the hydraulic efficiency and the subsurface runoffcoefficient of green roofs, showing their strong variability according to several factors, including the characteristics of storm events. Furthermore, only few studies have focused on the hydraulic efficiency of green roofs under Mediterranean climate conditions and defined the influencing hydrological parameters on the subsurface runoffcoefficient. Nevertheless, for designing purposes, it is crucial to properly assess the subsurface runoffcoefficient of a given green roof under specific climate conditions and its influencing factors. This study intends to, firstly, evaluate the subsurface runoffcoefficient at daily and event-time scales for a given green roof, through a conceptual model implemented in SWMM. The model was loaded with both daily and 1-min rainfall data from two Mediterranean climate sites, one in Thessaloniki, Greece and one in Cosenza, Italy, respectively. Then, the most influencing hydrological parameters were examined through a statistical regression analysis. The findings show that the daily subsurface runoffcoefficient is 0.70 for both sites, while the event-based one is 0.79 with a standard deviation of 0.23 for the site in Cosenza, Italy. The multiple linear regression analysis revealed that the influencing parameters are the rainfall intensity and antecedent dry weather period with a confidence level of 95%. This study demonstrated that, due to the high variability of the subsurface runoffcoefficient, the use of a unique value for design purposes is inappropriate and that a preliminary estimation could be obtained as a function of the total rainfall depth and the antecedent dry weather period by using the validated multi-regression relationship which is site specific. © 2016 by the authors.