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eISSN: 2083-5906
ISSN: 1230-1485
ISSN: 1230-1485
ORIGINAL RESEARCH
Analysis of Groundwater Chemistry and Water
Source Characteristics in the Banji Mining
Area Based on a Dual Model Combining
APCS-MLR and PMF
1
National Engineering Laboratory for Protection of Coal Mine Eco-environment,
Huainan Mining (Group) Co., Ltd, Huainan 232000, China
2
Ping An Coal Mining Engineering Technology Research Institute Co. Ltd., Huainan, Anhui 232001, China
3
School of Earth and Environment, Anhui University of Science and Technology, Huainan, Anhui 232001, China
Submission date: 2026-07-07
Final revision date: 2026-07-30
Acceptance date: 2026-08-20
Online publication date: 2026-09-29
Corresponding author
Qiding Ju
School of Earth and Environment, Anhui University of Science and Technology, 168 Taifeng Avenue, Tianjia'an District, 232001, Huainan, China
School of Earth and Environment, Anhui University of Science and Technology, 168 Taifeng Avenue, Tianjia'an District, 232001, Huainan, China
KEYWORDS
groundwater hydrochemistrysource apportionmentAbsolute Principal Component Scores-Multiple Linear Regression (APCS-MLR)Positive Matrix Factorization (PMF)mine water inrush hazard
TOPICS
ABSTRACT
Quantitative hydrochemical source apportionment underpins precise mine water inrush prevention
and inter-aquifer pollution control. Ninety-two groundwater samples from four aquifers in the
Anhui Banji Mining Area were tested for six major ions (Ca2+, Mg2+, Na++K+, Cl−, SO42−, HCO3−).
Piper diagrams and Pearson correlation analysis identified dominant HCO3-Ca·Mg hydrochemical
facies, with some Quaternary pore water evolving into the Cl·SO4-Na type due to evaporite leaching.
Parallel Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) and Positive
Matrix Factorization (PMF) models were used for multi-source contribution quantification and crossverification.
APCS-MLR extracted three factors (83.99% cumulative variance) representing evaporite
leaching, carbonate dissolution and silicate weathering, but produced unassigned residuals and
negative contributions due to its unconstrained linear algorithm. Validated by the Root Mean Square
Error (RMSE) elbow rule and Bootstrap test, PMF selected three optimal factors with stronger endmember
indication, all non-negative contributions summing to 100% per ion. Both models agreed on
key water-rock reactions, while PMF performed better in end-member recognition and robustness. This
dual-model mutual verification improves the reliability of single-method results, reveals hydrochemical
evolution driven by structures and mining disturbances, and offers technical support for water inrush
source identification in Huainan coal mines.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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