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

doi:10.13745/j.esf.sf.2025.4.13

Abstract

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

CLC Number:

X523

XU Donghui, LI Tao, LIN Yanzhu, CHEN Tianfei. Source apportionment of nitrate in groundwater based on correlation monitoring indicators in Liaodong Bay[J]. Earth Science Frontiers, 2025, 32(4): 376-387.

Figures/Tables 10

Fig.1 Simplified hydrogeological map of the Liaodong Bay

Fig.2 Distribution of sampling points in the study area

Table 1 Test methods and detection limits for groundwater samples

水产指标	检测方法	检出限	水产指标	检测方法	检出限
$N O 3 -$	紫外分光光度法	0.04 mg/L	Cl^-	离子色谱法	0.15 mg/L
K⁺	原子吸收光谱法	0.1 mg/L	Fe	原子吸收光谱法	0.1 mg/L
Na⁺	原子吸收光谱法	0.1 mg/L	Mn	原子吸收光谱法	0.1 mg/L
$HCO 3 -$	酸标准溶液滴定法	1 mg/L	Ca²⁺	原子吸收光谱法	0.1 mg/L
$CO 3 2 -$	酸标准溶液滴定法	1 mg/L	Mg²⁺	原子吸收光谱法	0.1 mg/L
pH	玻璃电极法	0.01	COD_Mn	酸性高锰酸钾法	0.5 mg/L
TDS	180 ℃干燥重量法	0.1 mg/L	NH₄-N	分光光度法	0.025 mg/L
$SO 4 2 -$	离子色谱法	0.75 mg/L	$NO 2 -$	分光光度法	0.02 mg/L

Table 1 Test methods and detection limits for groundwater samples

水产指标	检测方法	检出限	水产指标	检测方法	检出限
$N O 3 -$	紫外分光光度法	0.04 mg/L	Cl^-	离子色谱法	0.15 mg/L
K⁺	原子吸收光谱法	0.1 mg/L	Fe	原子吸收光谱法	0.1 mg/L
Na⁺	原子吸收光谱法	0.1 mg/L	Mn	原子吸收光谱法	0.1 mg/L
$HCO 3 -$	酸标准溶液滴定法	1 mg/L	Ca²⁺	原子吸收光谱法	0.1 mg/L
$CO 3 2 -$	酸标准溶液滴定法	1 mg/L	Mg²⁺	原子吸收光谱法	0.1 mg/L
pH	玻璃电极法	0.01	COD_Mn	酸性高锰酸钾法	0.5 mg/L
TDS	180 ℃干燥重量法	0.1 mg/L	NH₄-N	分光光度法	0.025 mg/L
$SO 4 2 -$	离子色谱法	0.75 mg/L	$NO 2 -$	分光光度法	0.02 mg/L

Fig.3 Statistical analysis of monitoring indicators

Fig.4 Extended Durov diagram for groundwater in Liaodong Bay

Fig.5 Correlation analysis

Fig.6 Ranking of relative importance for groundwater chemical indicators

Fig.7 PMF source profiles

Fig.8 Proportion of major factors in source apportionment

Fig.9 Contribution rate of major factors to water quality indicators

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