Session C3 - Green roof performance

Four experimental green roofs with different configurations of underlaying storage and outflow control have been installed on the GROOF platform at INSA Lyon, France. Collecting data with a 1 min time step (rainfall and other meteorological quantities, water storage, outflow and actual evapotranspiration) started in June 2002. Four years of data (June 2022-May 2026) allow to evaluate comparatively the hydrological performance of the green roofs under various meteorological conditions, which will contribute to improve their design and to refine modelling tools. Data analysis shows that a very significant part of annual rainfall is evapotranspirated, with differences depending on substrate depths, water storage and outflow control. A first inventory of vegetation, after 3 years, reveals significant differences between the vegetated roofs, with more new species appearing when the substrate depth is higher.

This study investigates the hydrological performance of a green roof in contrasting climates: tropical Belo Horizonte and temperate Île-de-France. An EPA SWMM model, calibrated with experimental data from Brazil, simulated the green roof's behavior over two-year periods for both regions. Results show that green roofs significantly reduced runoff coefficients and peak discharges in both contexts (approx. 30% peak reduction). In high-rainfall Belo Horizonte, runoff decreased by 26%, while in lower-rainfall Île-de-France, a stronger proportional effect yielded a 47% reduction. Markedly higher green roof evapotranspiration in both cities highlights their enhanced water retention capacity. This research confirms green roofs provide robust, consistent hydrological benefits across distinct climates, performing better proportionally in lower-rainfall conditions, performance that is likely to decrease in the context of climate change.

Green roofs can reduce stormwater runoff in urban areas by capturing rainfall. The extent of this capture is partially influenced by vegetation type and cover, which can be manipulated to optimise run-off reduction. However, in the absence of routine maintenance, planted green roof vegetation is often replaced by ‘weedy’ spontaneous species with unknown rainfall retention qualities. To better understand the role of spontaneous vegetation in green roof stormwater mitigation, we undertook a 100-day rainfall simulation, including a ‘dry’ and ‘wet’ phase, involving 14 plant species that occur spontaneously on green roofs in Mediterranean-type climates. During the dry phase, modules with spontaneous vegetation cover retained 88 % of applied rainfall regardless of substrate depth and had 6 % greater retention than bare substrate. During the wet phase, deep substrate modules with spontaneous vegetation cover had 30 % greater retention than other treatment combinations. These findings demonstrate that spontaneous vegetation can increase stormwater retention on green roofs relative to bare substrate and have similar retention performance to commonly utilised species. However, the extent to which stormwater mitigation on green roofs is enhanced by spontaneous vegetation is dependent on factors that are more important for rainfall retention, such as substrate depth and rainfall patterns.

The integration of sustainable stormwater management systems, such as green roofs, makes it possible to achieve a “zero-discharge” approach by promoting on-site infiltration and fully regulating excess runoff, thereby helping maintain hydrological balance and improving flood resilience. With an increase in the likelihood of extreme precipitation events in future, it is essential to evaluate the effectiveness of green roofs for future climate scenarios. This work aims to provide the foundations for a sizing tool capable of proposing “zero-discharge” rooftop solutions adapted to the local regulatory constraints of a municipality. Its application to Paris is presented here. A non-linear reservoir model embedded with a multifractal-based pore size distribution (PSD) model was used for hydrological modelling and simulation of the water flow through the green roof. The performance of the green roof was evaluated using climate data (past and future) downscaled to fine temporal resolution through a double cascade simulation model in the universal multifractal (UM) framework. The results from the study indicate that the effectiveness of green roofs reduces due to the increase in the intensities of precipitation events in the future. Hence, to combat future precipitation extremes, the configuration and operational conditions of green roofs must be designed and implemented appropriately.