Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8487227 | Agriculture, Ecosystems & Environment | 2018 | 10 Pages |
Abstract
Pesticide loss triggered by runoff is one of the most important sources of non-point pollution. The effects of grass hedges (Melilotus albus and Pennisetum alopecuroides) on atrazine runoff under different rain intensities and slope gradients were evaluated. The plot-scale experiments were carried out on a maize (Zea mays) field on slopes with 15% and 20% gradients using simulated rainfall (rain intensity of 30 and 45 mm hâ1). Atrazine residues were investigated in runoff water and soil taken from three depths (0-5, 5-10, and 10-15 cm) in the middle and base of the slope after runoff events. Total atrazine loss in runoff water ranged from 2.3% to 4.9% of that applied from plots without grass hedges. Grass hedges decreased atrazine loss by 37%-76% and surface runoff by 27%-72%, and Pennisetum showed better efficacy than Melilotus, especially under higher rain intensity. Atrazine loss showed a significant positive linear correlation with surface runoff volume. Grass hedges had a more significant effect on atrazine loss than rain intensity and slope gradient. But they functioned less effectively if used under intense rain or/and steep slope conditions. Atrazine residues remained in the surface 15 cm soil were higher for the plots with grass hedges than the control plots. These results suggest that grass hedges not only significantly reduced atrazine loss by reducing the surface runoff, but also reduced the amount of atrazine leaching to deeper soil layer. P. alopecuroides was a suitable grass-hedge species for controlling atrazine losses in northern China and similar regions. Other management practices or control measures should be integrated with grass hedges in strongly sloping cropland in high-rainfall areas to maintain pesticide losses at an acceptable level.
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Agricultural and Biological Sciences
Agronomy and Crop Science
Authors
Qinghai Wang, Cui Li, Zhuo Pang, Haifeng Wen, Ruilun Zheng, Jie Chen, Xueju Ma, Xiaoe Que,