TITLE:
Geophysical Investigation of a Solid Waste Disposal Site Using Integrated Electrical Resistivity Tomography and Multichannel Analyses of Surface Waves Methods
AUTHORS:
Ruobai Zhao, Neil Anderson, Jing Sun
KEYWORDS:
Electrical Resistivity Tomography, Electrical Resistivity Imaging, Multichannel Analyses of Surface Waves, CCR, Solid Waste Landfill, CCR Landfill, ERT, ERI, MASW
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.8 No.3,
March
24,
2020
ABSTRACT: Electrical resistivity tomography survey was deployed at a solid waste landfill in southwest Missouri USA with the intent to map variations in moisture content through the solid waste and underlying subsurface, and to map the top of bedrock. Multichannel analyses of surface waves survey was also deployed to map variations in engineering properties of the solid waste and underlying subsurface, and to constrain the interpretations of top of bedrock. The 2-D resistivity images through the waste suggest rainwater seeps through the cap cover system of the solid waste landfill, and moisture content within the solid waste increases with solid waste burial depth. The resistivity anomalies displayed by the soil and bedrock directly underneath the solid waste suggests a lateral component to moisture infiltrating at the toe of the landfill, which is flowing inward to the base of solid waste structural low. The 1-D shear wave velocity profiles obtained from the multichannel analyses of surface waves survey helped interpret the top of bedrock underneath the solid waste, where top of bedrock is difficult to map using electrical resistivity tomography, as shallow fractured bedrock is moist and displays comparable resistivity values to that of overlying soil. Not surprisingly, the top of bedrock is readily identified on the electrical resistivity tomography profiles in places where subsurface is relatively dry. The deployment of the combined non- invasive, cost and time effective geophysical surveys, along with engineering judgement on available site history data, has reasonably identified potential landfill seepage pathways. The methodology presented could be used in similar site investigation settings.