Green roof stormwater retention performance is fundamentally related to design configurations and climates. Efficient tools for assessing stormwater retention performance of green roofs with various configurations in different climates are highly desirable for practical applications. In this study, a hydrological model which can be used to simulate dynamic changes in moisture content and evapotranspiration of green roofs is developed and tested (with average Nash-Sutcliffe Efficiency of 0.8197 for calibration and 0.8252 for verification) using monitoring data (2018-2019) of four green roofs with various configurations. The model is applied to simulate long-term (1970-2018) moisture content, actual evapotranspiration, and retention performance of green roofs in eight cities across different climates of China. Green roofs built with engineered soil and Portulaca grandiflora show the largest evapotranspiration and thus provide the largest stormwater retention rates (R), while green roofs with light growing medium and Sedum lineare show the lowest evapotranspiration and R. R of green roofs increases as climate changes from humid to arid. Green roofs at Guangzhou (humid climate) provide the lowest R (28% ± 3%) caused by plenty of rainfall (1827 mm), while green roofs at Urumqi (desert climate) show the lowest mean annual actual evapotranspiration (167-269 mm) but provide the largest R (84% ± 5%) as a result of the lowest annual rainfall (282 mm). The results highlight that stormwater retention performance of green roofs could be enhanced through configuration optimization. However, a limiting factor in improving green roofs water retention rates may be the peculiarity of local climatic conditions.

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http://dx.doi.org/10.1016/j.jenvman.2022.115447DOI Listing

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