吉林市平原区地下水水质评价及成因分析

为进行吉林市平原区水质评价和水质成因分析,从该市平原区34个水质监测井的监测数据中选取铁、锰、氨氮等8项指标,运用BP神经网络法进行评价,并将评价结果与《地下水质量标准GBT14848-93》中的加附注评分法进行对比分析。评价结果基本一致,表明BP神经网络方法的评价结果可信,能够对地下水水质进行综合评价。该评价方法不需要确定权值,避免了赋予权值时主观误差的产生。所绘制的吉林市平原区地下水水质分区图表明,平原区地下水Ⅳ、Ⅴ级别水质区占较大面积,而Ⅱ、Ⅲ级别水质区分布较少。公因子空间分布图表明,平原区地下水水质的主要人为影响因素是化工企业的工业废水、烟尘等的不当排放,排污管道的渗漏,工业废弃物和生活垃圾的堆放以及农业中化肥农药的过量使用等。

Quality assessment and cause analysis of groundwater in plain area of Jilin City

To assess the quality of groundwater in Jilin City and analyze its causes, we select 8 indexes from the data of 34 water quality monitoring wells, including indexes of iron, manganese, ammonia nitrogen, etc., and use BP neural network to assess the water quality and compare the results with that of the grading method of attaching notes in Groundwater Quality Standard GBT14848-93. The assessment results of BP neural network are basically consistent with that of the standard, which proves that the results are credible and that BP neural network can be used to comprehensively assess groundwater quality. In BP neural network, the determination of weight parameters is not required, so it can avoid the subjective error. According to the zoning map of groundwater quality for plain area of Jilin city, IV and V class waters in the region account for a large portion whileⅡ and Ⅲ class waters are few. According to the spatial distribution maps of common factors, it is concluded that the main human causes for groundwater pollution are improper discharge of industrial waste water, smoky dust etc., leakage of sewage pipes, industrial waste and garbage and the excessive use of fertilizer and pesticide in farmland.