The authors employ the high-density resistivity method to image the subsurface structure of a mountain in Erdaojiang District, Tonghua City, Jilin Province, China, to evaluate the potential risk of slope failure on surrounding residential areas and infrastructure, and identify a shallow fault that extends across the center of the mountain and is perpendicular to the mountain slope and accurately locate the spatial position and depth of another fault on the southern side of the mountain. The results provide an important basis for evaluating mountain slope stability. This study also demonstrates that the high-density resistivity method is effective for detecting mountain faults.
Key words
Erdaojiang District /
Tonghua City /
Jilin Province /
high-density resistivity method /
electrical resistivity structure /
mountain faults
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
Jiang Y L, Zhang C X, Zhou Q Q. 2008. Application of the high density resistivity method to landslide prediction. Journal of Chengdu University of Technology (Science & Technology Edition), 35(5):542-546. (in Chinese with English abstract)
Liu G X. 2005. The principle and method of electrical exploration. Beijing:Geological Publishing House, 63-69
Wang Z H. 2019. Application of Multi-electrode resistivity method in estimation of stability of mountain. Journal of Disaster Prevention and Reduction, 35(4):56-61. (in Chinese with English abstract)
Yan Y J, Meng G X, Lyu Q T, et al. 2012. The progress and prospect of the electrical resistivity imaging survey. Geophysical and Geochemical Exploration, 36(4):576-584. (in Chinese with English abstract)
Zhang W. 2010. Study on the influence of different positions of power supply electrodes on the observation data of common devices of induced polarization method:master's degree thesis. Changsha:Central South University. (in Chinese with English abstract)
Zhao G H. 2006. High density electronic prospecting and its application. Mineral Resources and Geology, 20(2):166-168. (in Chinese with English abstract)
Funding
Supported by National Key R&D Program of China and Fundamental Research Funds for the Central Universities (2017YFC0601305).
PDF(2623 KB)
