华中农业大学资源与环境学院,武汉 430070
黄愿(1998—),女,硕士研究生,主要从事农业面源污染防控研究。E-mail: 1957@webmail.hzau.edu.cn
赵劲松(1978—),男,博士,副教授,主要从事农业面源污染防控研究。E-mail: jszhao@mail.hzau.edu.cn
收稿:2025-08-07,
修回:2025-09-12,
录用:2025-09-25,
网络首发:2025-12-19,
纸质出版:2026-04-01
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黄愿,郭梦娜,罗子瑶,等.湖南龙堰流域农业面源污染关键源区解析与治理策略[J].水土保持学报,2026,40(2):365-374.
HUANG Yuan, GUO Mengna, LUO Ziyao, et al. analysis of critical source areas and management strategies for agricultural non-point source pollution in Longyan watershed, Hunan Province[J].Journal of Soil and Water Conservation,2026,40(2):365-374.
黄愿,郭梦娜,罗子瑶,等.湖南龙堰流域农业面源污染关键源区解析与治理策略[J].水土保持学报,2026,40(2):365-374. DOI: 10.13870/j.cnki.stbcxb.2026.02.007. CSTR: 32310.14.stbcxb.2026.02.007.
HUANG Yuan, GUO Mengna, LUO Ziyao, et al. analysis of critical source areas and management strategies for agricultural non-point source pollution in Longyan watershed, Hunan Province[J].Journal of Soil and Water Conservation,2026,40(2):365-374. DOI: 10.13870/j.cnki.stbcxb.2026.02.007. CSTR: 32310.14.stbcxb.2026.02.007.
目的
2
旨在识别流域面源污染关键源区并进行针对性治理,为农业小流域氮、磷流失防治提供理论依据和实践指导。
方法
2
以湖南省典型亚热带低山丘陵小流域龙堰流域为研究对象,基于野外监测和实地调查数据,结合SWAT模型及K-means聚类识别流域面源污染关键源区,并根据关键源区特征设计不同管理措施,评估其应用效果。
结果
2
1)识别了总氮、总磷2类关键源区:总氮关键源区贡献流域48.9%氮流失量,主要受施肥强度驱动;总磷关键源区贡献49.6%磷流失量,受水文泥沙过程影响较大。2)化肥减量30%结合少耕措施对氮削减效果最佳,最高削减率达19.5%;工程性措施对磷削减效果最优,最高削减率为35.5%。3)基于关键源区的精准治理显著提升措施效益(
p
<
0.05),在关键源区尺度下氮、磷的单位面积削减率分别达流域尺度的5.35、6.90倍。
结论
2
龙堰流域氮、磷面源污染关键源区的成因与空间分布各异,差异化治理是实现农业小流域面源污染精准防控的有效路径。
Objective
2
This study aims to identify critical source areas (CSAs) of non-point source pollution in watersheds and implement targeted management strategies, thereby providing a theoretical basis and practical guidance for the prevention and control of nitrogen and phosphorus loss in small agricultural watersheds.
Methods
2
The Longyan watershed, a typical subtropical low-mountain and hilly small watershed in Hunan Province, was selected as the study area. Based on field monitoring and on-site survey data, the SWAT model combined with K-means clustering was used to identify CSAs of non-point source pollution in the watershed. Additionally, according to the characteristics of the CSAs, different management practices were designed, and their application effectiveness was evaluated.
Results
2
1) Two types of CSAs were identified: total nitrogen CSAs (TN-CSAs) and total phosphorus CSAs (TP-CSAs). TN-CSAs contributed 48.9% of nitrogen loss in the watershed, primarily driven by fertilizer application intensity. TP-CSAs accounted for 49.6% of phosphorus loss, largely influenced by hydrological and sediment processes. 2) A 30% reduction in chemical fertilizer combined with reduced tillage achieved the best effect on reducing nitrogen loss, with the highest reduction rate reaching 19.5%. Engineering practices had the best effect on reducing phosphorus l
oss, with the highest reduction rate of 35.5%. 3) Precision management based on CSAs significantly enhanced the benefits of the practices (
p
<
0.05). At the scale of CSAs, the reduction rates per unit area for nitrogen and phosphorus reached 5.35 and 6.90 times those at the watershed scale, respectively.
Conclusion
2
The causes and spatial distribution of CSAs for nitrogen and phosphorus non-point source pollution in the Longyan watershed exhibit distinct characteristics. Differentiated management is an effective pathway for achieving precise prevention and control of non-point source pollution in small agricultural watersheds.
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