Research on monitoring and early warning methods for industrial pollution in soft soil areas: application of time-lapse high-density
electrical resistivity tomography
FENG Shi-jin, CHEN Jia-zhuo, GAO Meng-wen, et al. Research on monitoring and early warning methods for industrial pollution in soft soil areas: application of time-lapse high-density
electrical resistivity tomography[J]. 2025, 46(4): 1323-1334.
FENG Shi-jin, CHEN Jia-zhuo, GAO Meng-wen, et al. Research on monitoring and early warning methods for industrial pollution in soft soil areas: application of time-lapse high-density
electrical resistivity tomography[J]. 2025, 46(4): 1323-1334.DOI: 10.16285/j.rsm.2024.0754.
Electrical resistivity tomography (ERT) has been gradually applied in the environmental geotechnical field
but its applicability for identifying organic pollution in soft soil areas lacks systematic validation and application examples. Through high-density electrical resistivity testing conducted at a chemical industry site in Shanghai
coupled with verification through borehole sampling and analysis of pollution characteristics
the pollution features of the site were effectively identified. Results indicate that contaminated areas exhibit localized high resistivity (above 70 Ω·m) and significant zones of encapsulation. Validation through borehole excavation confirmed the efficacy of high-density electrical resistivity tomography in discerning non-aqueous phase organic pollutants in soft soil areas. Analysis of longitudinal data revealed that point resistivity in polluted areas exhibits a trend of initial decrease
followed by an increase and subsequent decrease with depth. Based on pollution delineation results
a long-term monitoring system was established
proposing a quantitative evaluation method for continuous ERT monitoring information based on image grayscale correlation theory. By calculating image correlation coefficients throughout infiltration tests
rapid early warning of non-aqueous phase organic pollutants can be achieved
providing theoretical and technical references for rapid determination
monitoring
and early warning of pollution leaks in enterprises.