利用MLR和农业指标预测地下水硝酸盐浓度

Lidija J Stamenković, T. Milanović, G. Bogdanović
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引用次数: 0

摘要

环境污染导致自然界各部分的退化。地下水作为全球饮用水的重要来源之一,越来越多地暴露于主要由人为活动造成的各种污染物中。硝酸盐是地下水中可以长期存在的污染物之一,其浓度可以达到很高的水平。也就是说,地下水被用于灌溉、粮食生产、饮用等各种目的,因此特别关注地下水中硝酸盐浓度的监测。从这个意义上讲,欧盟立法还规定了饮用水硝酸盐浓度的标准,以避免对人类健康造成可能的威胁。地下水中硝酸盐的主要来源是农业活动,主要涉及化学肥料的使用、动物农场、生产化学肥料的工业废水。本文对全国地下水硝酸盐年平均浓度进行了预测。考虑到上述地下水中硝酸盐的来源,本文共选取了七个农业指标,假设这些指标有助于提高硝酸盐浓度,即:用于农业的面积,农场肉类生产,指标平衡-代表农业土壤中氮和磷过量或不足造成的总潜在环境风险,用于有机农业生产的面积,化肥的消耗,农药的销售以及与至少二级废水处理相关的人口百分比。采用多元线性回归方法进行预测,以农业指标为输入参数,即自变量,共7个,因变量为全国地下水硝酸盐年均浓度。本文选择比利时、保加利亚、捷克、德国和法国五个欧盟国家进行硝酸盐预测。为了建立多元线性回归模型,我们对所有8个变量使用了2011年至2015年的可用数据。在建立模型之前,首先进行相关分析,以确定所选择的自变量是否与因变量相关。相关分析结果表明,自变量和因变量之间存在显著的相关关系。建立的MLR模型预测效果良好,决定系数R2 - 0.96。MLR模型的1年预测结果令人满意,德国和法国的实测值与模型预测值偏差最大。结果表明,MLR模型可作为地下水硝酸盐浓度评价的替代方法之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PREDICTION OF NITRATE CONCENTRATION IN GROUNDWATER USING MLR AND AGRICULTURAL INDICATORS
Environmental pollution results in the degradation of all segments of nature. Groundwater, as one of thesignificant sources of drinking water at the global level, is increasingly exposed to various types of pollutants thatare mainly the result of anthropogenic action. Nitrate are one of the pollutants that can persist for a long time ingroundwater and their concentrations can reach high levels. Namely, the fact that groundwater is used for variouspurposes such as: irrigation, food production, drinking, special attention is focused on monitoring the concentrationof nitrate in groundwater. In this sense, EU legislation also prescribed a standard for drinking water in terms ofnitrate concentration in order to avoid possible threats to human health. The main sources of nitrate in groundwaterare agricultural activities, which primarily involve the use of chemical fertilizer, animal farms, waste water fromindustries that produce chemical fertilizer. In this paper, the prediction of average annual concentrations of nitrate ingroundwater at the national level was performed. Bearing in mind the mentioned sources of nitrate in groundwater, atotal of seven agricultural indicators were selected in this paper, which were assumed to contribute to higher nitrateconcentrations, namely: the area used for agriculture, meat production on farms, the balance of indicators - whichrepresents the total potential environmental risk caused by excess or deficit of N and P in agricultural soils, areaused for organic agricultural production, consumption of chemical fertilizer, sale of pesticides and percentage ofpopulation associated with at least secondary wastewater treatment. The prediction was made using multiple linearregression, where agricultural indicators were used as input parameters, i.e. independent variables, a total of seven,while the dependent variable was the average annual concentration of nitrate in groundwater at the national level. Inthis paper, five EU countries were selected for nitrate prediction: Belgium, Bulgaria, the Czech Republic, Germanyand France. For the development of the MLR (Multiple linear regression) model, available data from 2011 to 2015were used for all eight variables. Before developing the model, a correlation analysis was first performed todetermine whether the selected independent variables were correlated with the dependent variable. The results of thecorrelation analysis showed that there is a significant correlation between the independent and dependent variables.The developed MLR model showed good prediction results with a value of coefficient of determination R2 - 0.96.The results of the one year prediction by the MLR model showed satisfactory results, the biggest deviations betweenthe measured and model predicted values are in the case of Germany and France. Based on the obtained results, itcan be concluded that the MLR model can be applied as one of the alternatives in the assessment of nitrateconcentration in groundwater.
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