扬州城区古运河局部河段水质时间变化特性——以扬农化工厂河段为例
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摘要
为揭示扬州城区古运河局部河段水质的时间变化特性,选取古运河扬农化工厂河段为研究区,采用相关系数法、变异系数法、单因子标识指数法以及多元线性回归法对该河段2015年10月至2017年9月(2年)水温WT、pH、溶解氧DO、电导率EC、溶解性总固体TDS等水质参数的观测结果进行分析,对各参数的变化特性进行评价。结果显示:上下游断面同一水质参数均呈高度正相关,但不同季度的相关系数有所变化;各水质参数的变异性从大到小依次为DO>WT>TDS>EC>pH;以DO为指标的水质标识指数结果表明:水温低于14℃且pH高于7.3时水质类别多为Ⅰ、Ⅱ或Ⅲ类水,水温高于14℃且pH低于7.3时多为Ⅳ、Ⅴ类水;多元线性回归模型的分析结果表明:DO与WT呈负相关,与pH为正相关,pH变化对DO的影响大于WT,上游断面DO与WT、pH的相关性均高于下游断面。
The objective of the current research is to reveal the main temporal variation characteristics of water quality for a local reach of the Yangnong Chemical Plant of the Ancient Canal in Yangzhou City. Observation of the water quality parameters, such as the water temperature(WT), pH, dissolved oxygen(DO), electrical conductivity(EC) and dissolved total solids(TDS), had been conducted in the period from October 2015 to September 2017(2 years). The analysis of the water quality parameters has been carried out by using the methods of correlation coefficient method, coefficient of variation method, single factor identification index method and multiple linear regression method. The results indicates that each corresponding parameter of the upstream and downstream sections is highly positively correlated, while the correlation coefficients of each parameter showed seasonal change; the order of the variability of water quality parameters is DO>WT>TDS>EC>pH during the research period; the single factor identification index of DO exhibits that when the WT is lower than 14 ℃ and pH is higher than 7.3, the water quality category is mostly Ⅰ, Ⅱ or Ⅲ, and when WT is higher than 14 ℃ and pH is lower than 7.3, the waters quality category is most of Ⅳ or Ⅴ; according to results of the multiple linear regression model, DO is negatively correlated with WT and positively correlated with pH; the effect of pH change on DO is greater than that of WT; the correlations between DO and WT, and DO and pH of the upstream-section are both higher than that of the downstream-section.
The objective of the current research is to reveal the main temporal variation characteristics of water quality for a local reach of the Yangnong Chemical Plant of the Ancient Canal in Yangzhou City. Observation of the water quality parameters, such as the water temperature(WT), pH, dissolved oxygen(DO), electrical conductivity(EC) and dissolved total solids(TDS), had been conducted in the period from October 2015 to September 2017(2 years). The analysis of the water quality parameters has been carried out by using the methods of correlation coefficient method, coefficient of variation method, single factor identification index method and multiple linear regression method. The results indicates that each corresponding parameter of the upstream and downstream sections is highly positively correlated, while the correlation coefficients of each parameter showed seasonal change; the order of the variability of water quality parameters is DO>WT>TDS>EC>pH during the research period; the single factor identification index of DO exhibits that when the WT is lower than 14 ℃ and pH is higher than 7.3, the water quality category is mostly Ⅰ, Ⅱ or Ⅲ, and when WT is higher than 14 ℃ and pH is lower than 7.3, the waters quality category is most of Ⅳ or Ⅴ; according to results of the multiple linear regression model, DO is negatively correlated with WT and positively correlated with pH; the effect of pH change on DO is greater than that of WT; the correlations between DO and WT, and DO and pH of the upstream-section are both higher than that of the downstream-section.
引文
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[2] 靳梦,窦明.城市化对水系连通功能影响评价研究——以郑州市为例[J].中国农村水利水电,2013,(12):41-45.
[3] 陈振涛,滑磊,金倩楠.引水改善城市河网水质效果评估研究[J].长江科学院院报,2015,32(7):45-51.
[4] B Odemis, F Evrendilek.Monitoring Water Quality and Quantity of National Watersheds in Turkey[J].Environ Monit Assess, 2007,(133):215-229.
[5] B J Amiri, K Nakane.Modeling the Linkage Between River Water Quality and Landscape Metrics in the Chugoku District of Japan[J].Water Resour Manage, 2009,(23):931-956.
[6] I S Eneji, A P Onuche, R Sha'Ato.Spatial and Temporal Variation in Water Quality of River Benue, Nigeria[J].Journal of Environmental Protection, 2012,(3):915-921.
[7] F Othman, Alaa Eldin M E, I Mohamed.Trend analysis of a tropical urban river water quality in Malaysia[J].Journal of Environmental Monitoring, 2012,(14):3 164-3 173.
[8] 崔雪梅,赵盼盼,章爱群.4种河流水质评价方法的比较研究——以槐荫河为例[J].节水灌溉,2015(5):46-49.
[9] 程琳琳,杨开宇,杜鹃,等.河北省河流水质时空变化特征及受人类活动的影响分析[J].水资源与水工程学报,2015,26(1):1-7.
[10] 嵇晓燕,聂学军,李文攀,等.近十年淮河流域化学需氧量和氨氮浓度变化特征[J].节水灌溉,2016(12):85-89.
[11] 王杰,毛建忠,谢永红,等.2008-2014年滇池水质时空变化特征分析[J].人民长江,2018,49(5):11-15.
[12] 李晓储,孙传余,董志良,等.扬州古运河生态环境林建设研究[J].江苏林业科技,2002,29(2):1-4.
[13] 徐坤,牟春友. 运用方差分析法分析白城市月亮湖水库水质[J].中国环境监测,2009,25(2):67-68.
[14] 赵微,林健,王树芳,等.变异系数法评价人类活动对地下水环境的影响[J].环境科学,2013,34(4):1 277-1 283.
[15] 徐祖信.我国河流单因子水质标识指数评价方法研究[J].同济大学学报(自然科学版),2005,33(3):321-325.
[16] 张宇红,胡成.单因子标识指数法在浑河抚顺段水质评价中的应用[J].环境科学与技术,2011,34(6G):276-280.
[17] 曾春芬,黄文钰,王伟霞,等.天目湖溶解氧分布特征及环境影响因子[J].长江流域资源与环境,2010,19(4):445-451.
[18] 郑国萍,赵立强,俞百印,等.多元线性回归模型参数估计的递推算法及误差分析[J].大学数学,2007,23(3):78-82.
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