基于SWAT模型的龙溪河泸县境内面源污染特征分析
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摘要
应用分布式水文模型SWAT,首次以龙溪河泸县境内的面源污染为研究对象,通过对该流域的面源污染进行调查、监测和模拟,定量计算和分析该流域面源污染的时空分布规律以及识别关键污染源和污染关键区。结果表明:①SWAT模型在该研究区具有较好适用性,径流、氮磷负荷的纳什效率系数E_(ns)在0.6～0.75,决定系数R~2在0.75～0.85,相对误差Re在10%～30%;②年产水量、TN产量、TP产量丰水期显著多于平水期,丰水期比重大约为70%～80%,平水期多于枯水期,枯水期产量比重在5%以内;③面源污染是各个子流域最主要的污染类型,农业化肥污染与农村生活污染在面源污染中所占比重最大;④农村生活污染对TN产量影响最大,农业化肥污染对TP产量影响最大;⑤11、13号子流域是非点源污染的关键区,选定云锦镇为重点防治区。
The distributed hydrological model SWAT is firstly applied in Longxi River Basin in Luxian County as a typical area in this paper.Through the investigation,monitoring and simulation of the non-point source pollution in this basin,it has calculated quantitatively and analyzed the spatial and temporal distribution law of non-point source pollution,as well as the identification of the key pollution sources and the key pollution areas. The results show that: ① The SWAT model is highly applicable in the research area. The Nash efficiency coefficient of runoff and nitrogen and phosphorus load is between 0.6 and 0.75,and the determination coefficient is between 0.75 and 0.85,and the relative error is between 10% and 30%. ② The annual output of water,TN and TP are significantly higher in the wet period than in the level period,as well as in the level period than in the dry period. The yield in the wet period accounts for about 70%-80%,and the yield ratio in the dry period is less than 5%. ③ The non-point source pollution is the most important type of pollution in each sub-basin,among which the agricultural fertilizer pollution and the rural living pollution account for the largest proportion. ④ The rural living pollution has the largest impact on TN yield,and The agricultural fertilizer pollution has the largest impact on TP yield. ⑤ Yunjin Town is selected for prevention and control emphatically,as the sub-basin 11 and sub-basin 13 are the key areas of non-point source pollution.
The distributed hydrological model SWAT is firstly applied in Longxi River Basin in Luxian County as a typical area in this paper.Through the investigation,monitoring and simulation of the non-point source pollution in this basin,it has calculated quantitatively and analyzed the spatial and temporal distribution law of non-point source pollution,as well as the identification of the key pollution sources and the key pollution areas. The results show that: ① The SWAT model is highly applicable in the research area. The Nash efficiency coefficient of runoff and nitrogen and phosphorus load is between 0.6 and 0.75,and the determination coefficient is between 0.75 and 0.85,and the relative error is between 10% and 30%. ② The annual output of water,TN and TP are significantly higher in the wet period than in the level period,as well as in the level period than in the dry period. The yield in the wet period accounts for about 70%-80%,and the yield ratio in the dry period is less than 5%. ③ The non-point source pollution is the most important type of pollution in each sub-basin,among which the agricultural fertilizer pollution and the rural living pollution account for the largest proportion. ④ The rural living pollution has the largest impact on TN yield,and The agricultural fertilizer pollution has the largest impact on TP yield. ⑤ Yunjin Town is selected for prevention and control emphatically,as the sub-basin 11 and sub-basin 13 are the key areas of non-point source pollution.
引文
[1]向霄,钟玲盈,王鲁梅.非点源污染模型研究进展[J].上海交通大学学报(农业科学版),2013,31(2):53-60.
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[6]SHARPLEY A N.The enrichment of soil phosphorus in runoff sediments[J].J.Environ.Qual.,1980,9(3):521-526.
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[8]穆婧,史明昌,郭宏忠,等.基于SWAT模型的小流域面源污染负荷时空分异研究-以重庆市万州区陈家沟小流域为例[J].中国水土保持,2013(9):49-52.
[9]罗运祥,苏保林,杨武志,等.基于SWAT的柴河水库流域非点源污染识别与评价[J].北京师范大学学报(自然科学版),2012,48(5):510-514.
[10]陈媛,郭秀锐,程水源,等.SWAT模型在三峡库区流域非点源污染模拟的适用性研究[J].安全与环境学报,2012,12(2):146-152.
[11]汤国安,杨昕.地理信息系统操作Arc GIS地理信息系统空间分析实验教程[M].2版.北京:科学出版社,2012.
[12]GB/T 17296-2009,中国土壤分类与代码[S].
[13]翟玥,尚晓,沈剑,等.SWAT模型在洱海流域面源污染评价中的应用[J].环境科学研究,2012,25(6):666-671.
[14]杨凯杰,吕昌河.SWAT模型应用与不确定性综述[J].水土保持学报,2018,32(1):17-24,31.
[2]李瑞雪,余长明,倪九派,等.三峡库区农业非点源污染的思考[J].中国农学通报,2005,21(9):372-375.
[3]环境保护部,国家统计局,农业部.第一次全国污染源普查公报[N].人民日报,2010-02-10(16).
[4]程红光,岳勇,杨胜天,等.黄河流域非点源污染负荷估算与分析[J].环境科学学报,2005,26(26):384-391.
[5]周利.农村非点源污染迁移转化机理及规律研究[D].南京:河海大学,2006.
[6]SHARPLEY A N.The enrichment of soil phosphorus in runoff sediments[J].J.Environ.Qual.,1980,9(3):521-526.
[7]胡文慧,李光永,孟国霞,等.基于SWAT模型的汾河灌区非点源污染负荷评估[J].水利学报,2013,44(11):1 309-1 316.
[8]穆婧,史明昌,郭宏忠,等.基于SWAT模型的小流域面源污染负荷时空分异研究-以重庆市万州区陈家沟小流域为例[J].中国水土保持,2013(9):49-52.
[9]罗运祥,苏保林,杨武志,等.基于SWAT的柴河水库流域非点源污染识别与评价[J].北京师范大学学报(自然科学版),2012,48(5):510-514.
[10]陈媛,郭秀锐,程水源,等.SWAT模型在三峡库区流域非点源污染模拟的适用性研究[J].安全与环境学报,2012,12(2):146-152.
[11]汤国安,杨昕.地理信息系统操作Arc GIS地理信息系统空间分析实验教程[M].2版.北京:科学出版社,2012.
[12]GB/T 17296-2009,中国土壤分类与代码[S].
[13]翟玥,尚晓,沈剑,等.SWAT模型在洱海流域面源污染评价中的应用[J].环境科学研究,2012,25(6):666-671.
[14]杨凯杰,吕昌河.SWAT模型应用与不确定性综述[J].水土保持学报,2018,32(1):17-24,31.
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