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江汉平原地下水中硝酸盐的分布及影响因素
引用本文:杨静,肖天昀,李海波,王全荣. 江汉平原地下水中硝酸盐的分布及影响因素[J]. 中国环境科学, 2018, 38(2): 710-718
作者姓名:杨静  肖天昀  李海波  王全荣
作者单位:中国地质大学(武汉)环境学院, 湖北 武汉 430074
基金项目:国家自然科学基金资助项目(41502229,41772252);中国地质调查局资助项目(1212011120084)
摘    要:基于2011~2014年825个地下水采样点测试结果,采用半方差函数模型和普通克里格插值方法,研究了江汉平原地下水中NO3-N的空间变异和分布特征.运用证据权重法,选取降雨入渗补给量、地下水位埋深、渗透系数、包气带岩性、土地利用类型、土壤类型和土壤全氮含量7个因子建立预测模型,分析其对硝酸盐分布的影响规律.结果表明,江汉平原地下水NO3-N含量经Box-Cox变换后服从正态分布,其半方差函数最佳拟合模型为球状模型,空间相关性为87.93%,相关距离为68.02km.研究区地下水NO3-N含量具有南部高、北部及西部山前平原低的特点.地下水中NO3-N含量超过10mg/L分布面积所占比例达8.61%.成功率曲线表明模型预测精度为0.91,预测结果较好.江汉平原地下水NO3-N含量与该区降雨入渗补给量、渗透系数和土壤全氮含量具有良好的正响应关系,与地下水位埋深呈负响应关系.当包气带岩性为砂砾石、土地利用类型为建设用地及土壤类型为冲积土覆盖条件时,地下水极易受硝酸盐污染.

关 键 词:地质统计学  半方差函数  空间变异  证据权重法  
收稿时间:2017-07-03

Spatial distribution and influencing factors of the NO3-N concentration in groundwater in Jianghan Plain
YANG Jing,XIAO Tian-yun,LI Hai-bo,WANG Quan-rong. Spatial distribution and influencing factors of the NO3-N concentration in groundwater in Jianghan Plain[J]. China Environmental Science, 2018, 38(2): 710-718
Authors:YANG Jing  XIAO Tian-yun  LI Hai-bo  WANG Quan-rong
Affiliation:School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
Abstract:Semi-variogram model and ordinary Kriging interpolation method were used to analyse the spatial distribution and variation of the NO3-N concentration based on 825groundwater samples collected from 2011 to 2014 in Jianghan Plain. Seven hydrological factors, including net recharge, depth to groundwater, hydraulic conductivity, vadose zone material, land use type, soil type, and soil total nitrogen, were used to predict the posteriori probability distribution of the NO3-N concentration, where the contributions of these factors were calculated using Weights of Evidence (W of E) method. Results indicated that the NO3-N concentration in Jianghan Plain followed the normal distribution after Box-Cox transformation. A spherical model was appropriate to evaluate the spatial distribution of NO3-N concentration. The spatial correlation of the NO3-N concentration existed within a range of 68.02km with the nugget/sill being 87.93%. The NO3-N concentration showed that the higher values located in south region while the lower values located in north and west region. The area with the NO3-N concentration exceeding 10mg/L accounted for 8.61% of the total area. In addition, the success rate curve indicated a good performance of the WofE model at a precision value of 0.91. The groundwater recharge indicated a positive relationship with the vulnerability to nitrate contamination as well as hydraulic conductivity and soil total nitrogen, while the groundwater depth indicated a negative relationship. When the lithology of vadose zone was sand and gravel, the type of land use was for the urban or construction, and soil type was alluvial, the aquifer was very easy to be polluted by nitrate.
Keywords:geostatistics  semi-variogram  spatial variation  Weights of Evidence  
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