地学前缘 ›› 2025, Vol. 32 ›› Issue (4): 376-387.DOI: 10.13745/j.esf.sf.2025.4.13

• “健康地质调查”专栏 • 上一篇    下一篇

基于关联性监测指标的辽东湾地下水硝酸盐源解析

徐东辉(), 黎涛*(), 林艳竹, 陈添斐   

  1. 中国地质环境监测院, 北京 100081
  • 收稿日期:2025-01-15 修回日期:2025-03-27 出版日期:2025-07-25 发布日期:2025-08-04
  • 通信作者: *黎 涛(1984—),男,高级工程师,主要从事地下水监测和水文地质水资源信息化研究。 E-mail: jcylitao@mail.cgs.gov.cn
  • 作者简介:徐东辉(1997—),男,工程师,主要从事地下水大数据挖掘与水质监测工作。E-mail: donghuixu123@126.com
  • 基金资助:
    国家自然科学基金项目(U2444219);中国地质调查局地质调查项目(DD20211256);江西省“科技+”联合计划(2023KDG01008)

Source apportionment of nitrate in groundwater based on correlation monitoring indicators in Liaodong Bay

XU Donghui(), LI Tao*(), LIN Yanzhu, CHEN Tianfei   

  1. China Institute of Geo-Environment Monitoring, Beijing 100081, China
  • Received:2025-01-15 Revised:2025-03-27 Online:2025-07-25 Published:2025-08-04

摘要:

针对辽东湾地区地下水中硝酸盐来源,本研究通过多方法融合构建污染源解析体系。采集51组浅层地下水样品,综合运用Extended Durov图示法、Pearson相关分析与随机森林算法,筛选出TDS、 SO 4 2 -、Ca2+等9项硝酸盐关联性监测指标。采用正定矩阵因子分解法(PMF)定量解析辽东湾典型山丘区硝酸盐污染源贡献特征。结果表明: 研究区地下水化学类型以HCO3·Cl-Na·Ca型为主,硝酸盐超标率达20%且空间异质性显著。源解析显示,辽东沿渤海诸河山丘区水质主要受控于海水入侵(39.4%)、农业化肥(27.3%)、地质背景(19.1%)和生活污水(14.2%)4类来源。其中硝酸盐污染57.27%源自农业化肥施用,42.52%与海水入侵密切关联,且TDS、 SO 4 2 -、Ca2+等关键指标呈现同源性特征。本研究建立的“多方法融合-关联指标筛选-定量源解析”技术体系,为滨海地区地下水污染监测网络优化与防控策略制定提供了科学依据。

关键词: 辽东湾, 地下水, 硝酸盐, PMF, 随机森林

Abstract:

In this study, we developed an integrated pollution source apportionment framework to investigate nitrate origins in groundwater within the Liaodong Bay region. By analyzing 51 shallow groundwater samples, we employed the Expanded Durov diagram, Pearson correlation analysis, and random forest algorithm to identify nine monitoring indicators significantly correlated with nitrate concentrations, including TDS, SO 4 2 -, and Ca2+. The Positive Matrix Factorization (PMF) method was applied to quantify nitrate pollution sources in typical mountainous areas. Results revealed that the predominant hydrochemical type is HCO3·Cl-Na·Ca, with a nitrate exceedance rate of 20% (relative to GB/T 14848-2017) and pronounced spatial heterogeneity. Source apportionment of nitrate contamination identified two dominant sources: agricultural fertilizer application (57.27%) and processes associated with seawater intrusion (42.52%). Key indicators such as TDS, SO 4 2 -, and Ca2+ exhibit strong co-variation patterns, indicating shared pollution pathways. The integrated framework of “multi-method integration, screening of correlated indicators, and quantitative source apportionment” established in this study provides a scientific foundation for optimizing groundwater pollution monitoring networks and formulating targeted mitigation strategies for nitrate in coastal regions.

Key words: Liaodong Bay, groundwater, nitrate, PMF, random forest

中图分类号: