Bio-Swale Column Experiments and Simulation of Hydrologic Impacts on Urban Road Stormwater Runoff

被引:6
|
作者
Li, Jiake [1 ]
Li, Ya [1 ]
Zhang, Jiayang [1 ]
Li, Huaien [1 ]
Li, Yajiao
机构
[1] Xian Univ Technol, State Key Lab Base Ecohydraul Engn Arid Area, Xian 710048, Shaanxi, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
bio-swale urban road runoff; water reduction; SPSS; multiple stepwise regression model; BIORETENTION AMENDMENT; FILTER MEDIA; REMOVAL; PERFORMANCE; BIOFILTERS; MITIGATION; PHOSPHORUS; CELL;
D O I
10.15244/pjoes/60280
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The acceleration of urbanization has resulted in the increase of urban surface runoff. Bio-swale is a promising stormwater control measure that has been proven to be hydrologically effective on urban surface runoff. Column studies were conducted to determine the optimal bio-swale composition. Results demonstrated that water reduction was proportional to inflow decrease. Columns that planted border privet and Ophiopogon japonicus showed a larger water quantity reduction compared with that of planted boxwood and ryegrass, glossy privet and Chlorophytum comosum 'Variegatum' in vegetation tests, which was the same as the order of measured transpiration capacity of the plants. Water reduction rate increases dramatically with decreasing planting soil thickness. By contrast, no significant change occurs once the thickness of the artificial filler layer is altered. The bio-swale column with a high-infiltration rate artificial filler produced a good hydrological control effect. Sand was found to be the optimal media among the selected media compositions. Although the inclusion of an additional ponding depth affected total water reduction, it produced a stable outflow. SPSS software was used to assess the relationship between water reduction rate and its influence. On the one hand, water reduction rate increased linearly with increasing water inflow, soil thickness, and ponding depth. On the other, water reduction rate grew linearly with increasing plant factor and artificial filler infiltration rate. The multiple linear regression model revealing the relationship between the water reduction effect, and its influencing factors were obtained via the stepwise regression method in the SPSS software.
引用
收藏
页码:173 / 184
页数:12
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