地下水主要组分水化学异常识别方法对比:以柳江盆地为例

发布时间：2019-03-12 17:55

【摘要】：地下水化学组分的异常识别是构建水化学背景值及开展人类活动影响程度识别量化的重要基础.以往提出的基于5种水化学图的主要组分异常识别方法取得了良好效果,但是该方法考虑的水化学图种类过多,计算复杂.为简化水化学图法,本文以柳江盆地为例,尝试采用Durov图替代5种水化学图,对地下水主要组分进行异常识别.为此,分别对比分析了水化学图与数理统计法组合出的7种异常识别方法的剔除效果,并进行方法可靠性检验.结果表明,数理统计法与水化学图法结合识别地下水异常相对于两者单独使用可以取得更好的识别效果;其中3σ准则+5种水化学图法和3σ准则+Durov图法对地下水主要组分异常识别效果最好;并证实采用Durov图可以有效替代5种水化学图进行地下水主要组分的异常识别,既保留了水化学识别异常的科学性,又大大简化了异常识别计算的过程.
[Abstract]:Anomaly recognition of groundwater chemical components is an important basis for constructing hydrochemical background value and quantifying the influence degree of human activities. The main component anomaly recognition method based on 5 kinds of hydrochemical diagrams has achieved good results, but the method considers too many types of hydrochemical diagrams and the calculation is complicated. In order to simplify the hydrochemical mapping method, taking Liujiang basin as an example, this paper attempts to use Durov diagram instead of 5 hydrochemical maps to identify the main components of groundwater. For this reason, the elimination effects of 7 kinds of anomaly recognition methods combined with hydrochemical diagram and mathematical statistics are compared and analyzed, and the reliability of the method is tested. The results show that the combination of mathematical statistics method and hydrochemical map method can achieve better recognition results than using the two methods alone. Among them, the 3 蟽 criterion, 5 kinds of water chemistry map method and 3 蟽 criterion Durov diagram method have the best effect on the anomaly recognition of the main components of groundwater. It is proved that the Durov diagram can effectively replace the five hydrochemical maps for the anomaly recognition of the main components of groundwater, which not only preserves the scientific nature of the hydrochemical recognition anomaly, but also greatly simplifies the process of anomaly recognition and calculation.
【作者单位】：中国地质大学(北京)水资源与环境学院水资源与环境工程北京市重点实验室;
【基金】：国土资源大调查项目(1212011121170)
【分类号】：P641.3;X523

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