水文地质工程地质2025，Vol.52Issue(5)：1-9,9.DOI:10.16030/j.cnki.issn.1000-3665.202411040
多环芳烃运移模拟中数据驱动方法的应用
Coupled data-driven and physical mechanism modeling of polycyclic aromatic hydrocarbon transport
摘要
Abstract
Polycyclic aromatic hydrocarbons(PAHs)are among the primary organic contaminants in groundwater,and numerical modeling of PAHs transport is a crucial tool for efficient groundwater pollution remediation.Under actual groundwater contamination conditions,the co-transport mechanism of contaminants and colloids is often neglected due to the difficulty in accurately characterizing the types and distribution of colloids within the aquifer matrix.This omission introduces structural errors into the model,resulting in significant biases in predictive outcomes.This study focuses on fluoranthene and phenanthrene,addressing the neglected co-transport mechanisms of PAHs and colloids by employing Gaussian process regression(GPR)to correct structural model errors.A PAHs transport model coupling data-driven and physical mechanisms was developed.Through saturated sand column experiments on PAHs transport,the predictive performance of models using uncoupled and coupled data-driven approaches was compared and analyzed.The results indicate that groundwater PAHs transport models neglecting the co-transport mechanisms of PAHs and colloids exhibit significant structural errors.Direct parameter calibration fails to compensate for the omitted co-transport mechanisms,leading to substantial prediction biases.The application of the GPR model effectively compensates for the PAHs-colloid co-transport mechanisms and corrects structural errors in the groundwater model.During the validation period,the 95％confidence interval coverage of observed concentrations improved by 56.84％for fluoranthene and 19.04％for phenanthrene.NSE increased by 40.09％and 21.73％,while RMSE dropped by 33.10％and 55.38％,MAE by 32.00％and 46.34％,respectively.The predictive performance of the groundwater PAHs transport model improved significantly.The coupled data-driven and physics-based approach proposed in this study provides a viable framework for accurate simulation of PAHs transport in site groundwater,contributing to precise and efficient groundwater contamination remediation.关键词
数据驱动/高斯过程回归/马尔科夫链蒙特卡洛方法/数值模拟/多环芳烃运移Key words
data-driven method/Gaussian process regression/MCMC/numerical simulation/polycyclic aromatic hydrocarbon transport分类
天文与地球科学引用本文复制引用
曾献奎,田靖龙,王瑾彤,吴吉春..多环芳烃运移模拟中数据驱动方法的应用[J].水文地质工程地质,2025,52(5):1-9,9.基金项目
江苏省省级地质勘查项目(苏财资环[2021]46号) （苏财资环[2021]46号）
国家重点研发计划项目(2022YFC3703200) （2022YFC3703200）
