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INTRODUCTION
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Green roofs are a sustainable, low-impact development (LID) technique. They are an alternative to roofs constructed from other materials (concrete, clay or slate tiles, sheet metal, thatch, etc.), so they do not require additional space on a lot. They can reduce peak stormwater runoff and runoff volume and improve the quality of runoff, which can lower the risk of frequent urban floods and improve the quality of receiving waters (Versini et al. 2015).
Green roofs are typically divided into two main engineering categories, namely intensive and extensive. Intensive green roofs have deep soil layers, while extensive vegetated roofs have thin soil layers (Saadatian et al. 2013). Each green roof includes the following common elements: vegetation layer, growing media, filter fabric, drainage layer, protection layer, waterproof barrier and roof structure.
To explore the benefits of green roofs in urban runoff management, the quantitative impacts of the hydrological characteristics of green roofs have already been studied in several works based on experimental observation or modeling. Typically, quite small surfaces of experimental green roofs were instrumented to set continuous runoff and precipitation data in short periods of time (not exceeding 3 years). These data are then analyzed to study and explain the fluctuation of green roof response in terms of peak discharge and runoff volumes (Getter et al. 2007).
Conversely, some studies have attempted to simulate the hydrological response of green roofs by using adapted models. They were usually devoted to reproducing observed runoff at the experimented roof scale or to extrapolate green roof impact at the urban catchment scale (Locatelli et al. 2014; Versini et al. 2015; Castiglia Feitosa & Wilkinson 2016).
Villarreal & Bengtsson (2005) found that water retention within a green roof was dependent to a great extent on rainfall intensity; the lower the intensity the greater the retention. For a rain intensity of 0.4 mm/min and slopes with gradients of 1 in 2 and 1 in 14, the retention was 62% and 39% of the simulated precipitation, respectively, whereas for a rain intensity of 1.3 mm/min and slopes with gradients of 1 in 2 and 1 in 14, the retention was 21% and 10% of the applied precipitation, respectively. In addition, more research has focused on the observation and simulation of the...