基于BP神经网络的北京昌平山前平原地下水水质评价
发布时间：2019-02-09 19:03
【摘要】：该文采用单因子评价方法对昌平区浅层地下水的超标因子进行筛选,结合水文地球化学理论探讨各因子超标原因,分析浅层地下水水质的空间分布特征,并采用BP神经网络法对水质进行综合评级。从综合评级结果来看,12眼监测井中1眼为Ⅴ类水质,5眼为Ⅳ类水质,6眼为Ⅲ类水质。单因子筛选结果表明,总硬度、总溶解性固体、氮素、氟化物等为该区最主要的超标因子。经分析可知,山前平原地带浅层地下水中氟化物为原生污染,氮素污染物主要来源于地表污染物下渗,总硬度和总溶解性固体的升高主要受地表污染物下渗、氮素的迁移转化等因素的影响。研究可为研究区地下水管理工作提供可靠数据。
[Abstract]:In this paper, the single factor evaluation method is used to screen the surpassing factors of shallow groundwater in Changping area, and the reasons for the surpassing of these factors are discussed in combination with hydrogeochemical theory, and the spatial distribution characteristics of shallow groundwater quality are analyzed. BP neural network was used to evaluate the water quality. According to the comprehensive rating results, one of 12 monitoring wells was of class V water quality, five of them were water quality of class 鈪，
本文编号：2419295
[Abstract]:In this paper, the single factor evaluation method is used to screen the surpassing factors of shallow groundwater in Changping area, and the reasons for the surpassing of these factors are discussed in combination with hydrogeochemical theory, and the spatial distribution characteristics of shallow groundwater quality are analyzed. BP neural network was used to evaluate the water quality. According to the comprehensive rating results, one of 12 monitoring wells was of class V water quality, five of them were water quality of class 鈪，
本文编号：2419295
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