摘要
以湖南省长沙县的金井流域为例,于2013—2014年春夏秋冬四季随机采集流域内120口饮用水井水体样品,研究景观格局对地下水硝态氮(NO_3^--N)浓度的影响。研究结果表明:金井流域地下水存在NO_3^--N污染,NO_3^--N浓度超过世界卫生组织饮用水标准(>10 mg N·L^(-1))样品数占总样品数的4.9%~17.5%,且夏季和冬季NO_3^--N浓度超过世界卫生组织饮用水标准的频率高于春季和秋季;地下水文系统对NO_3^--N的输移使得流域地下水NO_3^--N浓度呈现明显的空间自相关性,采用Moran′s I全局指数评价方法的分析结果表明,夏季和秋季的空间自相关性较强(0.254~0.277),而冬季和春季的空间自相关性较弱(0.152~0.170);采样空间滞后模型对地下水NO_3^--N浓度与土地利用景观格局指数的拟合结果表明,地下水NO_3^--N浓度与农田、林地、居民地的面积比例显著相关(P<0.05),且模型模拟的决定系数随季节和距离水井半径不同而变化。
Groundwater samples were randomly collected from 120 wells in the selected Jinjing River catchment, Changsha County, Hunan Province, in the spring, summer, autumn, and winter of 2013—2014, to determine landscape pattern effects on groundwater nitrate concentrations(NO3^--N)using the Moran′s I index and spatial lag regression analysis. The results suggested that:groundwater NO3^--N pollution occurred in the catchment, with 4.9%^17.5% samples exceeding the WHO drinking water standards(10 mg N·L^(-1)), and particularly higher pollution frequencies in summer and winter than those in spring and autumn seasons; groundwater NO3^--N concentrations showed obvious spatial auto-correlation mainly due to the NO3^--N transport through groundwater flow, and the Moran′s global indices were greater in summer and autumn(0.254^0.277)than in spring and winter(0.152^0.170)at the catchment scale; groundwater NO3^--N concentrations significantly related to the areal proportion of agriculture, forest, and residential area when fitted by the spatial lag regression model(P0.05),and their determine coefficients of fitting strongly varied with seasons and the radius from the wells. Therefore, the results could provide technical basis for reasonable landscape planning to protect the groundwater environment and drinking water safety in subtropical hilly agri-cultural catchments.
出处
《农业环境科学学报》
CAS
CSCD
北大核心
2017年第4期753-760,共8页
Journal of Agro-Environment Science
基金
国家科技支撑计划项目(2014BAD14B01,2014BAD14B05)
湖南省科协决策咨询研究计划课题~~
关键词
氮素
土地利用方式
面源污染
流域环境
生态水文过程
nitrogen
land use type
non-point source pollution
catchment environment
eco-hydrological process