Application of geophysical monitoring techniques as aids to probabilistic risk-based management of landfill sites

摘要

Increasingly stringent regulatory regimes, in conjunction with landfill development in environmentally sensitive locations and the large number of abandoned landfill sites, are significantly increasing the responsibilities of local authorities and environmental agencies. These responsibilities include the identification and/or monitoring of: locations of contaminated land; boundaries of waste sites; nature of the landfill content; location, extent, content and depth of closed landfill sites; leachate plumes escaping from both operational and closed sites and the performance of landfill liners. Probabilistic risk based modelling is a standard methodology for monitoring and managing the environmental impact of landfill sites. A critical problem in the implementation of probabilistic risk based modelling is the large uncertainty in the shallow geology, internal structure and leachate distribution of landfills caused by the severe lack of both surface and subsurface information from within and outside the landfill site. The utility of two non-invasive ground based geophysical monitoring techniques, ground penetrating radar and reflectance spectroscopy, as aids to characterising the three-dimensional structure and distribution of leachate within a landfill has been investigated. Strong correlations between red edge inflection position and chlorophyll and metal concentration have been demonstrated from grassland species affected by leachate contamination of the soil adjacent to the landfill study site. The results of this study have demonstrated how recent advances in equipment, techniques and software mean that field-based reflectance spectroscopy and Ground Penetrating Radar can now provide environmental scientists with cost-effective, rapid techniques to characterise landfill sites in three dimensions, aid landfill managers in positioning additional boreholes and field sampling surveys, and provide data as inputs to leachate migration modelling. [PUBLICATION ABSTRACT]