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| Effectiveness of Vegetated Waterway in Controlling Non-Point Source Pollution Based on SWAT Model |
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| KeyWord:non-point source pollution; SWAT model; best management practices; vegetated waterway |
| Author Name | Affiliation | | ZHANG Pei-pei | State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China | | LI Qiong | Yichang Hydrologic Bureau, Yichang 443000, China | | KAN Hong-tao | Yichang Hydrologic Bureau, Yichang 443000, China | | WANG Jia-wei | State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China | | YU Wen-wen | State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China | | LIU Rui-min | State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China |
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| Abstract: |
| Non-point source（NPS） pollution is considered to be a major contributor to local water degradation in the Three Gorges Reservoir Area of China. Xiangxi River, which is a large watershed near the Three Gorges Reservoir, was selected to investigate the effectiveness of vegetated waterway in alleviating agricultural NPS pollution using SWAT（Soil and Water Assessment Tool） model. DEM, soil data, land use data in 2011 and the meteorological data from 1970 to 2011 were input to the SWAT model to simulate total N（TN） and total P（TP） pollution loads before and after applying vegetated waterway management in 2011. The pollution loads were divided into five classes with Jenk optimal methods. The SWAT model generated satisfying results. Total N and TP pollution loads were 1388 t and 239 t, respectively, which were both concentrated in Nanyang River and the downstream of Gufu and Gaolan River. Applying vegetated waterway reduced TN and TP pollution loads to 1120 t and 157 t, respectively. The reduction rates of TN and TP were 16.7% and 34%, respectively. These results could help local managers design effective management practices to improve water quality in similar watersheds. |
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