School of Soil and Water Conservation, Beijing Forestry University, Beijing, 100083, China.
School of Soil and Water Conservation, Beijing Forestry University, Beijing, 100083, China; National Station for Forest Ecosystem Research in Ji County, Ji County, 042200, Shanxi Province, China; Beijing Engineering Research Center of Soil and Water Conservation, Beijing, 100083, China.
J Environ Manage. 2022 Oct 1;319:115447. doi: 10.1016/j.jenvman.2022.115447. Epub 2022 Jun 18.
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.
绿色屋顶的雨水滞留性能从根本上与设计配置和气候有关。对于不同气候条件下不同配置的绿色屋顶雨水滞留性能评估，高效的工具是实际应用中非常需要的。本研究利用四种不同配置的绿色屋顶的监测数据（2018-2019 年），开发并测试了一种可用于模拟绿色屋顶水分含量和蒸散量动态变化的水文模型（校准的平均纳什-苏特克里夫效率为 0.8197，验证的平均纳什-苏特克里夫效率为 0.8252）。该模型被应用于模拟中国八个不同气候城市的绿色屋顶的长期（1970-2018 年）水分含量、实际蒸散量和滞留性能。使用工程土壤和马齿苋建造的绿色屋顶具有最大的蒸散量，因此具有最大的雨水滞留率（R），而使用轻质生长介质和景天建造的绿色屋顶具有最低的蒸散量和 R。随着气候从湿润变为干旱，绿色屋顶的 R 会增加。广州（湿润气候）的绿色屋顶由于降雨量充足（1827 毫米），提供的 R 最低（28%±3%），而乌鲁木齐（干旱气候）的绿色屋顶年平均实际蒸散量最低（167-269 毫米），但由于年降雨量最低（282 毫米），提供的 R 最大（84%±5%）。结果表明，通过配置优化可以提高绿色屋顶的雨水滞留性能。然而，提高绿色屋顶保水率的一个限制因素可能是当地气候条件的特殊性。
