湖北农业科学 ›› 2020, Vol. 59 ›› Issue (5): 49-53.doi: 10.14088/j.cnki.issn0439-8114.2020.05.009

• 资源·环境 • 上一篇    下一篇

基于SPSS的广西水库地下水化学特征及其形成原因分析

刘国子, 杨凤根, 许斌   

  1. 河海大学地球科学与工程学院,南京 211100
  • 修回日期:2019-07-15 出版日期:2020-03-10 发布日期:2020-06-05
  • 通讯作者: 杨凤根(1963-),副教授,主要从事水文地球化学及环境地球化学研究,(电子信箱)yangfg@hhu.edu.cn。
  • 作者简介:刘国子(1994-),男,安徽滁州人,在读硕士研究生,研究方向为水文地质学,(电话)18260062738(电子信箱)1078124769@
  • 基金资助:
    水利部公益性行业科研专项(201301044)

Analysis of groundwater chemical characteristics and formation causes of reservoirs in Guangxi based on SPSS

LIU Guo-zi, YANG Feng-gen, XU Bing   

  1. School of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China
  • Revised:2019-07-15 Online:2020-03-10 Published:2020-06-05

摘要: 利用多元统计分析软件(SPSS)对广西水库地下水化学特征及其形成原因进行了分析。通过相关分析、因子分析、聚类分析发现,地下水各个组分相关性较大,依存度较高。因子1、因子2、因子3中水化学类型分别为重碳酸-氯化物-钙型水、硫酸-镁钾型水、硫酸-钾钠型水,这与舒卡列夫分类法基本一致。研究区内岩溶作用(白云岩、石灰岩、岩盐溶解)、阳离子交换吸附及石膏的溶滤作用对地下水化学特征有一定的影响,地下水化学特征呈现明显的时空差异性,不同地点地下水中优势组分有所不同。

关键词: 地下水化学特征, 多元统计分析软件(SPSS), 相关性分析, 因子分析, 聚类分析, 广西

Abstract: : The multi-statistical analysis software was used to analyze the chemical characteristics and formation causes of the groundwater in the reservoir area of Guangxi. Through correlation analysis, factor analysis and cluster analysis, it was found that the groundwater components were highly correlated and the dependence was high. The chemical types of water in factor 1, factor 2, and factor 3 were bicarbonate-chloride-calcium type water, sulfuric acid-magnesium potassium type water, and sulfuric acid-potassium sodium type water, which were basically consistent with the Shukalev classification. The karstification (dolomite, limestone, rock salt dissolution), cation exchange adsorption and gypsum leaching of the study area had certain influence on the chemical characteristics of groundwater. The chemical characteristics of groundwater showed obvious spatial and temporal differences, and the dominant group of groundwater in different locations were different.

Key words: groundwater chemical characteristics, SPSS, correlation analysis, factor analysis, cluster analysis, Guangxi

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