Nolan B T
U.S. Geological Survey, 413 National Center, Reston, VA 20192, USA.
Ground Water. 2001 Mar-Apr;39(2):290-9. doi: 10.1111/j.1745-6584.2001.tb02311.x.
Characteristics of nitrogen loading and aquifer susceptibility to contamination were evaluated to determine their influence on contamination of shallow ground water by nitrate. A set of 13 explanatory variables was derived from these characteristics, and variables that have a significant influence were identified using logistic regression (LR). Multivariate LR models based on more than 900 sampled wells predicted the probability of exceeding 4 mg/L of nitrate in ground water. The final LR model consists of the following variables: (1) nitrogen fertilizer loading (p-value = 0.012); (2) percent cropland-pasture (p < 0.001); (3) natural log of population density (p < 0.001); (4) percent well-drained soils (p = 0.002); (5) depth to the seasonally high water table (p = 0.001); and (6) presence or absence of a fracture zone within an aquifer (p = 0.002). Variables 1-3 were compiled within circular, 500 m radius areas surrounding sampled wells, and variables 4-6 were compiled within larger areas representing targeted land use and aquifers of interest. Fitting criteria indicate that the full logistic-regression model is highly significant (p < 0.001), compared with an intercept-only model that contains none of the explanatory variables. A goodness-of-fit test indicates that the model fits the data well, and observed and predicted probabilities of exceeding 4 mg/L nitrate in ground water are strongly correlated (r2 = 0.971). Based on the multivariate LR model, vulnerability of ground water to contamination by nitrate depends not on any single factor but on the combined, simultaneous influence of factors representing nitrogen loading sources and aquifer susceptibility characteristics.
评估了氮负荷特征和含水层对污染的敏感性,以确定它们对浅层地下水硝酸盐污染的影响。从这些特征中得出了一组13个解释变量,并使用逻辑回归(LR)确定了具有显著影响的变量。基于900多个采样井的多变量LR模型预测了地下水中硝酸盐超过4mg/L的概率。最终的LR模型由以下变量组成:(1)氮肥负荷(p值=0.012);(2)农田-牧场百分比(p<0.001);(3)人口密度的自然对数(p<0.001);(4)排水良好土壤的百分比(p=0.002);(5)季节性高水位深度(p=0.001);以及(6)含水层内是否存在断裂带(p=0.002)。变量1-3是在围绕采样井的半径为500m的圆形区域内编制的,变量4-6是在代表目标土地利用和感兴趣含水层的较大区域内编制的。拟合标准表明,与不包含任何解释变量的仅含截距模型相比,完整的逻辑回归模型具有高度显著性(p<0.001)。拟合优度检验表明该模型与数据拟合良好,且地下水中硝酸盐超过4mg/L的观测概率和预测概率高度相关(r2=0.971)。基于多变量LR模型,地下水对硝酸盐污染的脆弱性不取决于任何单一因素,而是取决于代表氮负荷源和含水层敏感性特征的因素的综合、同时影响。