基于物元分析的矿区地下水水质评价  

Mining area groundwater quality evaluation based on matter-element analysis

作　　者：刘红艳[1] 

机构地区：[1]中国矿业大学(北京)地球科学与测绘工程学院,北京100083

出　　处：《煤炭与化工》2016年第7期43-45,48,共4页Coal and Chemical Industry

基　　金：国家自然科学基金(41272276)

摘　　要：矿区开采造成水体污染,为了解矿区水体污染情况,试将物元分析法应用于阜新海州露天矿矿区地下水水质评价中,并根据矿区地下水水质状况选出总硬度、SO_4^(2-)、CL^-、溶解性总固体、硝酸盐具有代表性的污染因子进行评价。为对矿区水质的了解,选取了3个远离矿区的对比点,7个矿区内的监测点位。结果表明,3个对照点位的水质为Ⅰ-Ⅱ类,水质较好;阜新海州露天矿矿区地下水水质为Ⅳ-Ⅴ类,水体污染严重;物元分析法是对不同评价因子所占权重比例进行综合评判,评价结果全面、系统、准确,与RBF神经网络对该矿区地下水的评价结果基本一直,说明物元分析法在矿区地下水水质评价中适用。Mining causes water pollution, to understand the mining area water pollution situation, applying the matter-element analysis to Fuxin Haizhou open-pit mining area groundwater quality evaluation, according to the mining area groundwater quality status, total hardness, SO_4^（2-）, CL^-, total soluble solids, nitrate pollution factors of representative evaluation are elected. As an understanding of the mining area water quality, the comparison of three away from mine point,seven monitoring points within the mining area. The results showed that the water quality of three control point for Ⅰ-Ⅱclass, water quality is better; Fuxin haizhou open-pit coal mine mining area groundwater quality for Ⅳ-Ⅴ class, water pollution is serious; Matter-element analysis method of the ratio of different evaluation factors were weighted comprehensive evaluation, the evaluation results with systematic, accurate, comprehensive advantages are consistent with RBF neural network evaluation results of the groundwater, illustrating the matter-element analysis method applied well in the assessment of groundwater quality in mining area.

关 键 词：水质评价 物元分析 矿区地下水 海州露天矿 

分 类 号：TD167[矿业工程—矿山地质测量]