济南市城区泉水离子成分变化特征与回归分析

Ionic composition variation characteristics and regression analysis of spring water in Jinan City

    摘要
  • 摘要: 以济南市城区泉水SO4 2−、NO3 −、Cl−为研究对象，从降水、补源、人类活动3个维度选取影响因子，研究影响因子与3种离子浓度的相关性；以通径分析判定影响因子的直接作用和间接作用，通过计算决策系数判定影响因子对离子浓度变化的作用大小和方向；通过建立的回归方程预测泉水NO3 −浓度和环境可承载的废水排放总量。结果表明：2008—2019年，城区泉水SO4 2−、Cl−、NO3 −浓度均呈上升趋势，SO4 2−和Cl−浓度为显著上升（P<0.01）。废水排放总量与SO4 2−、Cl−浓度呈显著正相关（P<0.01，P<0.05），相关系数分别为0.811和0.577；补源水库H+浓度与NO3 −浓度呈显著正相关（P<0.05），相关系数为0.692。各影响因子中，对泉水SO4 2−、NO3 −、Cl−浓度直接作用最大的均为废水排放总量。废水排放总量在SO4 2−、Cl−浓度变化过程中起增进作用；水库H+浓度、降水量、废水排放总量在泉水NO3 −浓度变化过程中起增进作用，水库H+浓度为主要决策变量。通过方程预测2020年泉水NO3 −浓度为8.42 mg/L，满足GB/T 14818—2017《地下水质量标准》Ⅲ类标准。如将泉水NO3 −浓度保持在10 mg/L以下，废水排放总量应控制在6.324×109 m3以内。

     

    Abstract: Taking SO4 2−, NO3 −, Cl− in spring water in Jinan City as the research objects, the influence factors from three aspects of precipitation, source supplement and human activities were selected, and the correlation between the influence factors and the concentrations of the three ions was studied. The path analysis was used to determine the direct and indirect effects of the influencing factors. The action size and direction of the influencing factors on the change of ion concentrations were determined by calculating the decision coefficient. The regression equation was established and used to predict the concentration of NO3 − in spring water and the total amount of wastewater that could be carried by environment. The results showed that the concentration of SO4 2−, Cl− and NO3 − in spring water showed an upward trend, and SO4 2− and Cl− increased significantly (P < 0.01) from 2008 to 2019. There was a significant positive correlation between the amount of wastewater and the concentration of SO 4 2− and Cl− (P < 0.01, P < 0.05), and the correlation coefficients were 0.811 and 0.577, respectively. There was a significant positive correlation between the concentration of H + and NO3 − in source supplement reservoir (P < 0.05), and the correlation coefficient was 0.692. Among the influencing factors, the amount of wastewater had the greatest direct effect on the concentration of SO 4 2−, Cl− and NO3 − in spring water. The amount of wastewater played an increasing role in the change of SO4 2− and Cl− concentrations. Precipitation, H+ concentration and the amount of wastewater in reservoir played an increasing role in NO3 − concentration change of spring water , and H+ in reservoir was the main decision variable. The equation predicted that NO3 − concentration of spring water would be 8.42 mg/L in 2020, meeting Class Ⅲ standard of Quality Standard for Ground Water (GB/T 14818-2017). If NO3 − concentration of spring water kept below 10 mg/L, the total amount of wastewater could be controlled within 6324 million cubic meters.

     

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