School of Water Resources and Environment, Beijing Key Laboratory of Water Resources and Environmental Engineering, MOE Key Laboratory of Groundwater Circulation and Environmental Evolution, China University of Geosciences (Beijing), Beijing, 100083, PR China.
School of Water Resources and Environment, Beijing Key Laboratory of Water Resources and Environmental Engineering, MOE Key Laboratory of Groundwater Circulation and Environmental Evolution, China University of Geosciences (Beijing), Beijing, 100083, PR China.
Water Res. 2019 Oct 15;163:114880. doi: 10.1016/j.watres.2019.114880. Epub 2019 Jul 17.
Nitrate pollution in groundwater has become a widespread problem worldwide, but understanding of the factors influencing groundwater nitrate pollution remains limited. Numerous studies have attributed nitrate pollution mostly to surface conditions and have neglected the role of hydrogeology. Therefore, this study used the Shaying River Basin as the study area and developed a least squares surface fitting (LSSF) model to systematically analyze the effect of hydrogeological conditions and surface pollution loads on groundwater nitrate pollution. Intrinsic vulnerability and total soil nitrogen (TSN) were used to represent hydrogeological conditions and surface pollution loads, respectively. The results showed that the concentrations of NO-N in shallow groundwater ranged from 0.002 to 256.29 mg/L (with an average of 14.38 mg/L). The concentration had an overall decreasing trend along the flow path. The water chemistry tended to change from HCO-Ca to HCO·Cl-Ca as the NO-N concentration increased. Groundwater nitrate pollution was simultaneously controlled by intrinsic vulnerability and TSN, and the LSSF model explained 83.5% of the result within a 95% confidence interval. These findings explained the phenomenon by which some areas had high surface loads but no serious groundwater nitrate pollution and some areas had nitrate pollution but no high surface loads. Nitrate accumulated in high levels in areas with a high intrinsic vulnerability due to hydrogeological conditions. TSN, which was the main source of NO-N in groundwater, came mainly from agricultural nitrogen fertilizer inputs and livestock manure. These findings provide helpful information for those tasked with managing and controlling groundwater quality.
地下水硝酸盐污染已成为全球范围内普遍存在的问题,但人们对影响地下水硝酸盐污染的因素的了解仍然有限。许多研究将硝酸盐污染主要归因于地表状况,而忽视了水文地质的作用。因此,本研究以沙颍河流域为研究区,建立了最小二乘曲面拟合(LSSF)模型,系统分析了水文地质条件和地表污染负荷对地下水硝酸盐污染的影响。内在脆弱性和总土壤氮(TSN)分别用来代表水文地质条件和地表污染负荷。结果表明,浅层地下水中的 NO-N 浓度范围为 0.002-256.29mg/L(平均值为 14.38mg/L)。浓度沿水流方向总体呈下降趋势。随着 NO-N 浓度的增加,水化学性质趋于从 HCO-Ca 转变为 HCO·Cl-Ca。地下水硝酸盐污染同时受到内在脆弱性和 TSN 的控制,LSSF 模型在 95%置信区间内解释了 83.5%的结果。这些发现解释了一些地区尽管地表负荷高,但地下水硝酸盐污染并不严重,而另一些地区硝酸盐污染严重,但地表负荷不高的现象。由于水文地质条件,内在脆弱性高的地区硝酸盐积累水平较高。TSN 是地下水中 NO-N 的主要来源,主要来自农业氮肥投入和牲畜粪便。这些发现为管理和控制地下水质量提供了有价值的信息。