ORIGINAL RESEARCH
Bio-Swale Column Experiments and Simulation
of Hydrologic Impacts on Urban Road
Stormwater Runoff
Jiake Li1, Ya Li1, Jiayang Zhang1, Huaien Li1, Yajiao Li3
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1State Key Laboratory Base of Eco-Hydraulic Engineering in Arid area,
Xi’an University of Technology, Xi'an, Shaanxi 710048, China
2School of Architecture and Civil Engineering, Xi’an University of Science and Technology,
Xi'an, Shaanxi 710054, China
Submission date: 2015-09-04
Final revision date: 2015-10-19
Acceptance date: 2015-10-19
Publication date: 2016-01-25
Pol. J. Environ. Stud. 2016;25(1):173-184
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ABSTRACT
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.